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Despite the success of antiretroviral therapy, approximately 20–50% of HIV-infected individuals have HIVassociated neurocognitive disorder. HIV infection and stimulation of monocytes and lymphocytes promotes trafficking into the central nervous system, triggering a neuroinflammatory response. Within the CNS, inflammation leads to activation of microglia, the resident immune cells in the brain, which induces chemokines and cytokines that drive a chemotactic gradient along the blood -brain barrier and allows further infiltration of infected and uninfected peripheral immune cells. Chemokines and cytokines function as immunomodulatory proteins that influence HIV neuropathogenesis with both positive and negative effects that may contribute to the ongoing prevalence of HAND. The chemokine C-C motif ligand 2 , alternatively known as monocyte chemoattractant protein-1 , is a b-chemokine that is expressed during inflammation and that, upon activation of its receptor , can induce chemotaxis of monocytes to inflammatory sites generated by injury and infectious events. CCL2 is expressed by monocytes, macrophages, dendritic cells, neurons, astrocytes, microglia and endothelial cells, while CCR2 is expressed by monocytes, microglia, astrocytes, epithelial cells, activated T cells and dendritic cells. CCL2 has been identified as the most potent activator of macrophages in comparison to other monocyte chemoattractants, including RANTES, macrophage inflammatory protein-1a , MIP- 1 b, MCP-2 b and MCP-3. CCL2 levels in the brain and cerebrospinal fluid are elevated in HIV patients with encephalitis, AIDS patients with cytomegalovirus, AIDS dementia and HIV-positive patients with cerebral inflammation. Recently,pruning cannabis peripheral blood monocyte expression of CCR2 has been shown to predict HAND in combination ART – era HIV cohorts. Elevated levels of CCL2 expression have also been observed in non HIV-positive samples.

In patients with mild cognitive impairment and Alzheimer’s disease, higher levels of CSF CCL2 correlated with lower cognitive scores. The presence of elevated CCL2 in HIV-positive patients with neuroinflammation, predictive power of monocyte CCR2 for HAND and elevations of CCL2 in non HIVpositive patients with neurocognitive deficits suggests that CCL2 may have a critical role in the neuropathogenesis of HAND and other noninfectious dementing disorders. A number of studies have examined genetic variation in the CCL2 gene and identified single nucleotide polymorphisms to be associated with HIV-disease progression and neurocognitive functioning over time. Individuals with an A to G polymorphism in the CCL2 enhancer region, annotated as rs1024611 , have higher CCL2 levels in serum, plasma and CSF than individuals without the A to G polymorphism. Increased CCL2 expression from the – 2578G allele has also been investigated in pathologic conditions and was found to be associated with higher incidences of tuberculosis, breast cancer and atherosclerosis, suggesting that the SNP is involved in chronic inflammatory conditions. Among HIV-infected individuals, homozygosity for the -2578G allele was associated with accelerated disease progression, enhanced leukocyte recruitment to tissues and a 4.5-fold risk for HIV-associated dementia. In a study examining the -2578G allele in a cognitively impaired population, elderly patients with senile dementia due to Alzheimer’s disease, CCL2 serum levels were significantly higher in patients who carried at least one G allele, whereas the highest levels of CCL2 were present in patients carrying two G alleles. The -2578G allele has also been reported to be associated with diminished performance in working memory over time in HIV infected individuals. The HIV-positive group who did not carry the -2578G allele improved at a faster rate in working memory than the HIV-positive group who carried the -2578G allele, but not faster than the HIVnegative groups. However, direct associations between the CCL2 rs1024611 SNP and HIV-disease progression have not been consistent across studies , suggesting that there may be intermediate mechanisms that mediate the association between CCL2 genotype, host immune responses and neurocognitive outcomes.

Although CCL2 expression in both plasma and serum has been linked to neurocognitive impairment, the purpose of the current study was to elucidate interrelationships between CCL2 genotype at the rs1024611 SNP, CCL2 levels in CSF, expression of other neuroinflammatory markers in the CSF. In addition, we considered plasma viral load, CD4þ cell count and neurocognitive performance in our analysis of HIV-infected individuals. We hypothesized that HIV-positive carriers of the CCL2 -2578G allele would exhibit high levels of CCL2 expression in CSF, and that elevated levels of CCL2 would be associated with higher concentrations of other proinflammatory markers in CSF, higherneurocognitive deficit scores, higher HIV viral load and a lower CD4þ T-cell count in blood plasma. We also hypothesized that accounting for CSF levels of CCL2 would explicate the relationship between CCL2 genotype and cognition.The cohort that was examined consisted of 145 HIVinfected individuals enrolled in the National NeuroAIDS Tissue Consortium cohort for whom CCL2 genotyping and CSF samples were available. The NNTC is a multicentre consortium engaged in a longitudinal study of adults with HIV/AIDS. The four participating clinical centres in the United States were The National Neurological AIDS Bank located in Los Angeles, California, USA; the Texas NeuroAIDS Research Center located in Galveston, Texas, USA; the Manhattan HIV Brain Bank located in New York, New York, USA; and the California NeuroAIDS Tissue Network located in San Diego, California, USA. Participants are administered a comprehensive battery of psychometric measurements that include tests of neuropsychological function and self-report instruments that estimate past and current substance and psychiatric illness. Neurological examinations, lumbar puncture for CSF collection and laboratory tests were conducted for plasma HIV viral load and plasma CD4þ lymphocyte count. The following were the inclusion criteria in the current study: at least 18 years of age, fluent in the English language, at least sixth grade education, able to provide informed consent.

Exclusion criteria were as follows: no history of CNS opportunistic infections , no history of traumatic brain injury, no history of learning disability or other developmental disorders and no other major neurologic syndromes .In line with previous reports, the results of this study showed that carriers of the -2578G allele had significantly higher levels of CCL2 in CSF. In addition, higher CCL2 expression was correlated with neurocognitive deficit score, higher levels of other proinflammatory markers in CSF, higher plasma viral load and lower CD4þ lymphocyte counts. We did not observe a significant interaction between CCL2 genotype at rs1024611 and neurocognitive deficit score, suggesting that carrying the -2578G allele alone does not appear to effect cognition. Instead, the findings suggest that increased expression of CCL2, modulated by CCL2 genotype, influences neurocognitive test performance. As expected, there was a strong correlation between CCL2 genotype and CCL2 expression, which led to the investigation of whether CSF CCL2 expression was acting as a moderating variable to the effects of CCL2 genotype on cognition. This suggests that the -2578G genotype results in a more reactive immune response, and increased viral load results in higher concentrations of CCL2 than normal, resulting in neurocognitive dysfunction. After controlling for CCL2 expression, the association between genotype and cognition emerged, indicating that CCL2 genotype has an effect on cognition, which may be moderated by CCL2 expression. Using plasma viral load to further probe the relationship between CCL2 genotype on cognition in the context of HIV infection,drying room we found that in the presence of high viral load, the CCL2 -2578G allele was associated with greater CCL2 expression and neurocognitive deficit. Although plasma viral load was used as a surrogate for CSF viral load , these results suggest that as HIV infection persists, carrying the – 2578G allele will lead to worse cognitive outcomes . The results also suggest that carrying the CCL2 -2578G allele and thereby expressing higher levels of CCL2 may contribute to or support a pro-inflammatory state in the CNS. We found that CSF CCL2 was associated with increased sCD14, sIL-6Ra, IL-2, IL-6, BAFF and sTNFR2. However, we are unable to determine whether increased CCL2 expression is a consequence of an already established pro-inflammatory state or if induction of CCL2 drives the pro-inflammatory immune response. Interestingly, in addition to CCL2, we found that BAFF and sTNFR2 correlated with cognitive performance; however, CCL2 was the only marker that was associated with CCL2 genotype. These results suggest that BAFF and sTNFR2 may also play an important role in neuroinflammation and cognitive impairment among HIV-infected individuals. B-cell activating factor , a cytokine that is a member of the TNF superfamily, plays a critical role in mediating B-cell differentiation, activation and survival to generate efficient B-cell responses.

Within the CNS, BAFF is expressed by microglia and astrocytes, with recombinant BAFF inducing secretion ofinflammatory markers, IL-6 and TNF-a, and IL-10, highlighting BAFF’s contribution to the inflammatory response. Consistent with our results, elevated levels of BAFF in CSF from patients with inflammatory neurological diseases, including HIV, have been reported to be significantly higher than in patients with nonin- flammatory neurological diseases. These findings highlight the importance of controlled BAFF expression for an efficient B-cell response, which is a contributing factor in HIV disease progression. Increased CSF BAFF may be indicative of neuroinflammation and may be important in the persistence of HIV within the CNS. TNFR2 is a receptor for TNF-a, a key regulatory cytokine in the inflammatory response, and upon binding, induces a signalling cascade to promote cell survival. TNFR2 is expressed by lymphocytes , microglia, oligodendrocytes, astrocytes, endothelial cells, myocytes, thymocytes and mesenchymal stem cells. Soluble TNFR2 can be generated via shedding from the cell surface and may act as a scavenger in a protective capacity by sequestering TNF-a to reduce TNF mediated inflammation. TNFR2 signalling in neurologic disorders and cognitive impairment has been examined and increased levels of sTNFR2 have been reported in CSF and plasma from patients diagnosed with bipolar disorder, mild cognitive impairment and AD compared with healthy controls. Increased staining for TNFRs has also been demonstrated in brains of individuals with HIV encephalitis and other opportunistic infections, and one report has described an association of plasma sTNFR2 with HIV-associated cognitive abnormalities. These results suggest that increased sTNFR2 expression in CSF may serve as a marker of the neuroinflammatory response to HIV and may play an important role in HIV neuropathogenesis and neurocognitive impairment. Our results indicate that individuals carrying the CCL2 – 2578G allele expressed higher levels of CCL2 in CSF and correlational analyses demonstrated that increased CCL2 was associated with increased pro-inflammatory markers, including sCD14, sIL-6Ra, IL-2, IL-6, BAFF and sTNFR2, in addition to greater cognitive deficit. These results are in line with previous studies reporting that increased levels of CCL2 are associated with a faster rate of cognitive decline. Furthermore, the CCL2- CCR2 axis was recently reported to be a critical signalling pathway in HAND, with CCR2 on CD14þCD16þ monocytes serving as a peripheral biomarker for HAND . Overproduction of cytokines in the CNS may allow for HIV-infected cells to persist in the brain despite antiretroviral therapy treatment. As stated previously, CCL2 expression was also correlated with plasma viral load. This is of particular clinical importance because the failure to adequately suppress viral replication may result in repeated BBB insults that further contribute to peripheral immune cell migration into the CNS. This is an area that requires further investigation and has the potential to inform therapeutic interventions. Owing to the cross-sectional nature of the current study, we cannot determine whether the expression of CCL2 is a precursor, consequence or simply correlative to cognitive status. It is possible that elevations in CCL2 expression in CSF may signal other inflammatory processes or genetic influences that were not evaluated in the current study. For instance, HIV-1 Tat protein is produced in infected astrocytes and may be secreted and taken up by neighbouring cells, and has been identified as a potential factor in the pathophysiology of HAND. Expression of the CCL2 gene has been shown to be directly transactivated by HIV-1 Tat protein in human astrocytes. Although we cannot determine from this study whether the CCL2 gene is solely driving the CCL2 gradient or whether the presence of infected cells or HIV- 1 Tat are also contributing to CCL2 expression, the results suggest a link between CCL2 genotype and cognition that warrants further study. Overall, these results underscore the importance of examining intermediate phenotypes as modulating factors that may link host genotype to cognitive outcomes in HIV.Treatment-seeking individuals with an alcohol use disorder exhibit a range of neurocognitive and inhibitory control deficits.

Participants provided written informed consent for participation.We assessed the prevalence, severity, and duration of pain using questions from the Brief Pain Inventory .We asked participants whether they had experienced pain or taken medicine for pain in the past week. Next, we asked participants to rate their average pain over the past week on a 0–10 numeric rating scale, where 0 was ‘no pain’ and 10 was ‘pain as bad as you can imagine’. We categorized average pain ratings as no to mild , moderate , and severe pain.If individuals indicated in response to the first question that they had not experienced pain in the past week, we classified their pain as ‘zero’. We asked participants with pain how long they had experienced their pain. We categorized these answers as ‘less than 3 months’, ‘3 months to 5 years’, and ‘more than 5 years’. We categorized participants with moderate to severe pain lasting over 3 months as experiencing chronic pain.We asked participants to rate how their pain interfered with their enjoyment of life and general activity on a scale of 0 to 10 .3 We categorized these responses as mild , moderate , and severe interference . We inquired about health conditions that are prevalent in this population and likely associated with pain, including arthritis, human immunodeficiency virus , diabetes, and traumatic brain injury .To assess for HIV infection, we asked participants whether they had ever been tested and if so, for the result of the test. We asked participants whether a clinician had ever told them that they had diabetes or arthritis. To evaluate for a history of likely TBI,cannabis drying racks we asked participants whether they had ever been hit in the head, and if so, whether any of the three most severe head injuries resulted in loss of consciousness.To assess the association of chronic pain with living environment, we used participants’ self report of the places where they had stayed for the prior 6 months.

We performed a cluster analysis to create a classification of living environments.We used Ward’s linkage to minimize the sum-of-square differences within groups. We performed visual analysis of a dendrogram representing the structure of the data to select the optimum number of clusters. Using bivariate matrices, we confirmed that we could identify natural groupings. We used kmedians cluster methodology to verify cluster classifications.We performed chi-square tests of significance for differences in the independent variables representing the domains we hypothesized to be associated with chronic moderate to severe pain. These results informed a multivariate logistic regression analysis in which we included all hypothesized variables that were associated at a p<0.2 level in the bivariate analyses. Then, we used backward selection to define our final, reduced model. We performed a sensitivity analysis to evaluate missing data in our final model by assuming that missing dichotomous variables were either positive or negative and measuring their effects on the observed odds ratios and confidence intervals. We performed all analyses with SAS 9.4 . A total of 350 participants completed the enrollment interview .Two people did not provide information on pain, leaving a sample of 348. The cohort was 77.3% male, 79.6% African American, and 74.4% high school-educated . The median age was 58 years, with a range from 50–80 years. Almost half of participants first experienced homelessness after turning. Almost half of participants reported being diagnosed with arthritis. Three-quarters endorsed a personal history of abuse. Nearly a third reported symptoms consistent with PTSD and over a third reported recent anxiety. Symptoms of depression and substance use problems were common .In the overall cohort, 17.2% reported moderate pain and 39.4% reported severe pain over the past week. Approximately half of participants reported experiencing chronic moderate to severe pain. The majority of participants experiencing pain reported chronic pain . The median duration of both moderate and severe pain was 5 years .

Most individuals with pain reported that it interfered with both general activity and life enjoyment. Participants with severe pain reported the most interference . We derived four categories of participants based on their current living environments: unsheltered , cohabiters , multiple institution users , and recently homeless . Participants in the unsheltered group spent a large portion of the prior 6 months in unsheltered locations; cohabiters spent a large portion of their time staying with friends and family; multiple institution users stayed in multiple locations including shelters, transitional housing, motels, and jails ; and renters, who had recently become homeless, spent a large portion of their time in rental housing.In the bivariate analyses, compared with the no to mild pain group, participants with chronic moderate to severe pain described significantly more depressive symptoms, PTSD, recent anxiety, arthritis, histories of traumatic brain injury, and histories of abuse . We did not find an association with living environment, gender, race, or substance use. We included significant variables as well as those that met the pre-specified criterion of p<0.2 in our full multivariate model. In our reduced multivariate model, we found significant associations between PTSD , arthritis , and a history of abuse with chronic pain . Depressive symptoms were not significant in the reduced multivariate model.In a sample of adults 50 and older experiencing homelessness, almost half of the participants reported chronic moderate to severe pain. While definitions for chronic pain vary within the literature, the prevalence of chronic pain in the general population ranges from 2.0% to 40.0%.Studies of pain in community living older adults found the prevalence of any pain to range from 28%–59%.Studies of pain in nursing home residents found the prevalence of pain to range between 32%–57%, with more than half of that reported to be moderate-severe pain.Despite the younger age of our sample, we found a higher prevalence of chronic moderate-severe pain. Participants reported their pain to be longstanding: three-quarters of those with moderate or severe pain reported that their pain had lasted for 5 years or more.

Participants reported a high prevalence of pain interference, which suggests that, despite other barriers faced by homeless adults, pain plays a role in reducing self-efficacy and quality of life.Consistent with other research, we found an association between a personal history of victimization,arthritis, and PTSD symptoms with chronic pain.In contrast to other populations,we did not find an association between either substance use, number of chronic medical conditions, nor depression and chronic pain. Our study population experiences a higher burden of chronic disease, injuries, substance use, and mental health problems, than the general population. Despite a median age of 58, our participants had a higher prevalence of functional and cognitive impairments than the general population of older adults in their 70s and 80s.The high prevalence of these factors, as well as unique factors associated with homelessness may explain the high prevalence of chronic pain in our sample.Homeless adults experience harsh environmental conditions: approximately half spent almost all of their nights outdoors, without shelter. A significant minority spent many nights in group shelter situations, where individuals may sleep on floor mats or low quality mattresses. These conditions may contribute to the high prevalence of chronic pain. The lack of an association between substance use and chronic pain may be due to its overall high prevalence in our sample. We found that PTSD was more prevalent than in the general population and that it was associated with chronic pain. More than 40% of those who experienced chronic moderate to severe pain and more than 20% of those who did not, had likely PTSD, compared to approximately 8% of the general population.These prevalence ratios are similar to those found in other studies of homeless populations. PTSD is common in homeless populations, possibly due to a high prevalence of traumatic childhood experiences,pots for cannabis plants high prevalence of experiencing interpersonal violence, exposure to violence while homeless, coexisting psychiatric disorders, and poor social support.Unstable housing status may itself contribute to the development of PTSD.Existing research conceptualizes the relationships between chronic pain and PTSD to be one of mutual maintenance.Mutual maintenance asserts that mental health and substance use disorders maintain or worsen existing pain, while pain worsens these underlying conditions. The effective management of both pain and mental health problems should incorporate treatment of pain and behavioral health conditions simultaneously and longitudinally.We found a high prevalence of arthritis and a strong association between arthritis and chronic pain. In studies of primary care in the general population, older individuals are more likely than younger ones to attribute pain to arthritis. Approximately one-quarter of chronic pain in adults ≥55 years is attributed to arthritis.In a previous study of chronic pain in homeless adults of all ages, between 9% and 24% attributed their pain to arthritis.

Homeless older adults may have fewer evidence-based treatment options for arthritis pain than the general population, due to difficulties accessing regular medical care, low-impact exercise, and healthy food choices.Finally, our study found that victimization throughout the life course was associated with chronic pain. Similar associations were found in other populations.The increased recognition of the role of trauma in chronic pain and other clinical conditions has led to the development of “trauma informed care” as an approach to address patients’ experiences of trauma. Trauma informed care refers to the reorientation of systems of care to incorporate a fundamental understanding of the role that traumatic experiences play in the lives and symptoms of people seeking care. Although limited data exists as to its effectiveness, especially for the relief of somatic symptoms such as physical pain, data that do exist suggest that trauma informed care reduces PTSD and depressive symptoms.While the efficacy of opioid analgesics for the treatment of chronic non-cancer pain is questioned, their use for this condition remains widespread.While older adults may, counterintuitively, experience a lower risk of overdose than younger adults,10 the cooccurrence of substance use disorders and the chaotic conditions of homelessness limit the use of opioids in this population. While multiple consensus statements describe multidisciplinary care as the best approach for the management of chronic pain, limited data are available to support its efficacy.Most studies showed only a modest effect for a minority of participants with no or minimal benefits lasting after six months.Even if this care were efficacious, homeless individuals face numerous barriers to engaging in longitudinal care, including their need to prioritize food and housing, lack of insurance or financial resources, inadequate transportation, and inability to communicate with clinicians between visits.The health care of patients experiencing homelessness and the challenges of managing chronic pain are both foci of increasing research interest,yet chronic pain remains largely understudied among homeless adults. Homeless individuals face many barriers to research participation, and in particular, few studies focused on the emerging population of older homeless individuals. Most existing studies of homeless populations recruit either from health care facilities or homeless shelters, which may not be representative. By using population-based sampling and focusing on older homeless adults, our study provides the first estimates of chronic pain in a high-risk, but poorly understood, group of individuals. Our data demonstrate that chronic pain is not only common, but that it has detrimental effects on life enjoyment and general activity in older homeless adults. By decreasing functioning, chronic pain presents yet another hurdle for marginalized and under-resourced individuals to receive much needed health care and social services. In addition to causing physical and emotional distress, chronic pain can hamper individuals’ abilities to obtain and retain employment and stable housing, let alone to manage other health problems. This study has several limitations. The analysis is cross-sectional, so we cannot identify causality. Only 12% of the study participants are aged 65 or over, reflecting, in part, premature mortality among homeless adults. While homeless populations are considered “older” by age 50,13, 14 the study population is younger than most studies of older adults. Study participants’ poor access to health care may lead to under reporting of chronic health conditions, limiting our ability to find associations. Due to the stigma associated with victimization, participants may have under reported experiences of verbal, physical, or sexual abuse. This misclassification would limit our ability to find an association between abuse and chronic pain, so our results could be interpreted as conservative. We did not assess pain related diagnoses, such as back pain, sprains, strains, or fractures, or obtain participants’ understanding of the causes of their pain. We did not attain data on how they managed their pain or whether they had received treatment, including medication, for their pain.

Craving likely represents a more proximal determinant of alcohol use than stimulation and sedation, which are shown to indirectly influence alcohol self-administration through craving . An additional exploratory aim was to test whether a characteristic of AUD severity, withdrawal-related dysphoria, moderated ibudilast’s effects on daily alcohol-induced changes in mood and craving. Notably, we found that individuals without a reported history of withdrawal-related dysphoria who were treated with ibudilast showed attenuation of alcohol-induced changes in craving, urge, and positive mood when compared to placebo. This tempering of alcohol’s effects may reflect ibudilast’s enhancement of antiinflammatory and neurotrophic factors suspected to impact dopaminergic signaling in rewards regions, such as the nucleus accumbens, where PDE4 and PDE10 are highly expressed . However, individuals who endorsed this withdrawal-dysphoric profile did not appear to benefit from treatment via this mechanism, such that ibudilast did not significantly blunt acute rewarding and reinforcing effects of alcohol. Although intriguing, these moderation findings should be interpreted with caution given the limited sample size, particularly the subgroup of individuals reporting experiences with withdrawal-related dysphoria . Despite these findings, preliminary analyses from this two-week RCT show that withdrawal dysphoria did not moderate clinical response to ibudilast regarding rates of heavy drinking or drinks per drinking day. Notably, these subjective response results are somewhat in contrast to what might be expected for individuals with a history of withdrawal and experiencing the “dark side of addiction”,cannabis indoor grow system such that these individuals may potentially show greater dysfunction of the immune system and thus may be predicted to have better response to an anti-inflammatory treatment, such as ibudilast.

However, it is suspected that other mechanisms may be central to the maintenance of AUD among individuals with withdrawal dysphoria, beyond the enhancing effects of alcohol. Namely, these individuals may primarily drink to feel ‘normal’ and alleviate physiological or psychological distress, particularly during early abstinence , which was not the focus on the current study. The present findings also differ somewhat from our laboratory’s initial efficacy trial of ibudilast, in which individuals with higher levels of depression showed attenuation of alcohol-induced increases in positive mood and ‘wanting’ during intravenous alcohol administration . A relevant difference between these studies is that participants enrolled in the efficacy trial were likely in a state of early abstinence, as they were asked to refrain from drinking for safety reasons; yet those enrolled in the present trial were not asked to change their drinking behaviors and consumed alcohol on roughly 60% of trial days and around 6 DPDD on average. In preclinical models, withdrawal increases the expression of innate immune markers in brain regions regulating autonomic and emotional states and while speculative, may thus represent a unique condition with the potential to impact ibudilast’s therapeutic effects. For instance, ibudilast reduced opioid withdrawal symptoms among individuals with heroin dependence and another PDE4 inhibitor, rolipram, diminished withdrawal-induced behaviors indicative of negative affect in rodents . Future research evaluating the impact of withdrawal states on immune signaling in larger clinical samples is needed to advance understanding of these complex processes and immune intervention. These findings should be considered in the context of the study’s strengths and limitations. One limitation is that DDAs were reported retrospectively once daily, which is less temporally accurate than EMA designs.

As such, items on subjective response and drinking were reported by participants concurrently the morning following a drinking episode and did not capture one’s subjective response level at a specific BrAC or blood alcohol curve limb. As such, this weakens our ability to draw a causal link between the effect of subjective response on alcohol intake and may introduce recall bias. Next, participants with more non-drinking days and incomplete DDAs during the trial are suspected to have greater error variance in their data given the lower number of observations with subjective response data. The lack of daily pre-drinking data on stimulation and sedation prevented us from examiningdaily changes in these variables, such that we could not account for pre-drinking levels. The sample was comprised of non-treatment seeking individuals with moderate AUD on average and the majority did not fall in the withdrawal-related dysphoria category. Future work with ibudilast in more diverse and treatment-seeking samples with more significant experiences of withdrawal-related dysphoria is needed. This study’s strengths include a clinical AUD sample enrolled in a rigorous double-blind RCT testing a promising novel pharmacotherapy. This trial displayed strong medication adherence rates and tolerability. Further, DDAs had high completion rates and the data comprise a substantial number of drinking episodes . Morning reports are also less likely to be affected by the intoxicating effects of alcohol that may lend to reporting errors, as could be seen with EMA or nightly reports. Finally, to our knowledge, this is the first study on the effect of immune modulation on subjective alcohol response in the natural environment. In closing, this daily diary study complements findings from our previous reports of ibudilast treatment for AUD by examining medication effects on subjective response during real-world drinking episodes.

The nuanced nature of the findings, including the distinction among those with and without withdrawal-related dysphoria and within vs. between person subjective response effects, speak to the heterogeneity of AUD and dynamic mechanisms maintaining alcohol use. Ibudilast’s effects on subjective alcohol responses, such as positive mood and craving, appear to be nuanced and perhaps most salient for individuals drinking for positive reinforcement as opposed to normalizing. Treatment with ibudilast potentiated the within-person relations between stimulation/ sedation and alcohol intake in this trial, such that an individual’s quantity of consumption on a given day appears to be more tightly connected to subjective response. The ecologically valid nature of these DDA, through retrospective reports of past day drinking and subjective responses to alcohol, provide a clinically useful window into how individuals experience and recall alcohol’s effects while taking ibudilast, compared to placebo. Novel medications and novel biological targets call for careful assessment of mechanisms beyond the “usual suspects”, such as changes in mean levels of subjective response and alcohol craving. Ultimately, the combination of multiple scientific approaches, including human laboratory, DDAs, neuroimaging, and biomarker assessment, offer complementary and clinically useful findings that can inform the development of ibudilast, and immune treatments for AUD more broadly.In 2021, an estimated 66,570 women in the United States will be diagnosed with uterine cancer and 21,410 will be diagnosed with ovarian cancer.Within each of these diseases, the worst outcomes are among patients with the rarest forms: uterine carcinosarcoma and ovarian carcinosarcoma . Although only 5% of uterine cancers are UCS,this aggressive disease causes 15% of all uterine cancer deaths.Similarly, between 1% and 4% of ovarian cancers are OCS, and patients with OCS have a shorter 5-year survival than those with other ovarian cancers .In part, these poor outcomes are because these patients often present at a late stage. For example,cannabis equipment more than half of patients with UCS present with regional or distant metastases,and 5-year disease-free survival is shortest in those with the latest stage disease . Outcomes are often poor even in those diagnosed with early-stage UCS; more than 50% of such patients experience disease recurrence, leading to death.Standard treatment for patients with UCS and OCS is surgery , peritoneal washings, and retroperitoneal lymph node assessment.Developing and testing treatments for these diseases has been hampered, as historically, UCS was treated with other sarcomas. However, recent evidence indicates that the carcinomatous components dictate tumor behavior,and molecular studies demonstrated that the sarcomatous components are derived from the carcinomatous components through metaplastic transformation.Thus, in 2009, the International Federation of Gynecology and Obstetrics mandated that UCS should be staged as an endometrial carcinoma.A 2013 Cochrane review of both published and unpublished data from the large phase III trials in UCS evaluated the efficacy of adjuvant radiotherapy, paclitaxel and ifosfamide , cisplatin, ifosfamide, and mesna, or ifosfamide alone. The review concluded that patients in the PI and cisplatin, ifosfamide, and mesna arms had longer overall survival and progression-free survival than those in the radiotherapy or ifosfamide-alone arms, but those in the cisplatin, ifosfamide, and mesna arm experienced greater toxicity than those in the PI or ifosfamide-alone arms. Thus, PI was established as the evidence-driven standard for treating UCS.

However, this regimen has three important limitations. First, it is difficult to administer, requiring 3 days of infusion. Second, it requires the use of growth factor support. Third, it is associated with a greater risk for central neurologic toxicity than other chemotherapy regimens, especially for older patients. Paclitaxel and carboplatin has been a standard regimen for epithelial ovarian carcinoma since the late 1990s and became the standard for endometrial carcinomas with the results of GOG-209.This regimen has been evaluated in small studies of patients with both OCS and UCS. For example, among 28 patients with OCS treated with PC, 16 had a complete response and six had a partial response, and the median OS for all patients was 27 months. Thus, PC was recommended for all stages of OCS.GOG-0232 evaluated 55 patients with UCS treated with PC and found that 13% of patients had confirmed complete response and 41% had partial response. The total overall response rate was 54% , which compared favorably with earlier ifosfamide-based regimens for similar patients.Given the limitations of PI noted above, the efficacy of PC in ovarian carcinomas, and the findings of small studies evaluating PC in patients with OCS and UCS, PC could be a good alternative to PI. Here, we tested the null hypothesis that PC was inferior to PI for patients with all stages of UCS and OCS.The study accrued 637 women between August 17, 2009, and March 24, 2014, at 176 sites across the United States and Korea. As of February 18, 2019, the median follow-up time was 61 months. Ninety-eight patients deemed ineligible on central review were distributed equally across treatment arms as shown in the CONSORT diagram . Of all eligible patients enrolled, 24 were never treated and 20 withdrew consent to continuous follow-up. Of the 449 eligible patients enrolled with uterine primary disease , 21 were never treated with protocol-assigned treatment . Select patient and tumor characteristics of the patients with UCS are shown in Table 1, and additional details are given in Appendix Table A1 . For characteristics of the patients with OCS, see Appendix Table A2 . Most participants were between the age 50 and 79 years and non-Hispanic or White and had a stage I or III uterine primary disease. More than 60% of patients completed all planned treatment, and the median time on treatment was 16 weeks from random assignment. Thirteen percent of participants discontinued treatment because of progression, 9% refused some or all treatment, and 13% discontinued treatment early because of AEs or death. Similar numbers of cycles of therapy were given to eligible patients in both regimens; 69% received four-six cycles of PC, and 70% received four-six cycles of PI. Major protocol violations occurred more commonly in the PI arm than in the PC arm and were often due to the complex dosing adjustments required in response to nadir blood counts.This open-label, randomized, phase III therapeutic non-inferiority clinical trial shows that PC is not inferior to PI in terms of OS and PFS and significantly increases PFS duration for patients with UCS. Findings were similar but not statistically significant in the smaller OCS cohort. Overall, the toxicity and patient-reported quality-of-life profiles were similar for the two drug regimens. These results establish that PC should be used as a standard regimen for patients with UCS and should be considered for treating patients with OCS. These findings are important because PC is easier to administer than is PI. Moreover, patients with UCS could be considered for inclusion in clinical trials for patients with the more common epithelial sub-types of uterine cancer treated with PC. Similarly, it may be reasonable to combine OCS patients with other epithelial subtypes in ovarian cancer trials. Both UCS and OCS have significant racial and age disparities in risk and outcome. For example, UCS occurs up to three times more frequently in Black women than in White women, and this disparity appears to be increasing. In addition, carcinosarcomas are most common in older women; the mean age at diagnosis is 68 years.In part, this is because tamoxifen and previous radiation therapy are likely risk factors.

More importantly, greater reductions in discounting predict a greater likelihood of protracted abstinence among cocaine users and smokers . Thus, if a causative link between D2 /D3 receptor availability and temporal discounting is established, it may lead to the development of novel D2 /D3 -targeted interventions which could be used to more effectively treat a variety of disorders. In conclusion, the results of this study indicate that low D2 / D3 receptor availability is associated with steep temporal discounting. This link may explain why some individuals choose to continue using drugs despite knowledge of their future negative consequences, and could help to guide strategies for treating substance abuse and other psychiatric disorders.Dissociation, which involves detachment from one’s physical and emotional experiences and is associated with symptoms such as depersonalization , de-realization , and other amnesic/ fugue states, is generally understood to be a psychological defense in the face of current and past trauma . There is some evidence that dissociation is linked to genetic factors within the context of early trauma exposure . Furthermore, childhood physical and sexual abuse are associated with elevated dissociative symptoms in homeless veteran populations and younger populations including homeless teens . In fact, child abuse appears to be one of the more robust predictors of dissociation in adulthood . Adult survivors of childhood abuse are more likely to experience dissociative symptoms than individuals who are not survivors of childhood abuse in both clinical and non-clinical populations . Several studies across a variety of cultures and populations have demonstrated that survivors of childhood sexual abuse are more likely to develop dissociative symptoms than those who have experienced other types of childhood abuse . Furthermore,4×8 grow table with wheels numerous studies have noted that individuals who are victims of childhood abuse are more likely to become victims of violence in adulthood .

Given that survivors of childhood abuse are at increased risk of exposure to other traumas across the lifespan , Chu has suggested that dissociation experienced after childhood sexual abuse may mediate the influence of childhood sexual abuse on future increased risk for adult violent victimization . Although the mechanisms behind violent victimization remain varied and unclear, it is suggested that elevated dissociative symptoms may be linked to a suppressed anticipatory anxiety response, which increases the likelihood that individuals with a history of childhood abuse may put themselves in potentially dangerous situations . One study that investigated the relationship between post traumatic stress disorder and dissociative symptoms in a sample of college women found no evidence that dissociative symptoms mediated violent victimization . However, other studies have found evidence that dissociation may be associated with an increased likelihood of violent physical and sexual victimization in both clinical and non-clinical adult samples . Whether differences in results are due to different populations, different research questions, or other factors is unclear. Few investigations have directly assessed the relationship between violence and dissociation among homeless and unstably housed women and none have attempted to establish a causal or directional relationship between child abuse, dissociation, and recent adult violent victimization. The dearth of relevant research leaves a notable gap in our understanding of how childhood abuse and dissociation may lead to violent victimization, especially for particularly vulnerable populations such as homeless and unstably housed women. Our prior work among homeless and unstably housed women found extremely high levels of childhood abuse , as well as recent violent victimization . Within the same sample of homeless and unstably housed women, we have also shown that recent sexual violence is strongly associated with other subsequent negative outcomes such as the increased likelihood of stimulant use initiation .

The disproportionately common occurrence of violence against unstably housed women, and the strong influence of violence on a variety of other mental health conditions, makes these critical issues to address in this population . The current study aimed to increase our understanding of the relationships between childhood abuse, dissociation, and violent victimization in the same population of homeless and unstably housed adult women. Using the Chu model, which hypothesizes that dissociation resulting from childhood sexual abuse increases risk for future sexual violence, as a frame we asked women to report any violent victimization six months prior to an initial assessment and in the intervening six months prior to a followup assessment. Our hypothesis was that after accounting for psychiatric comorbidity and other sociocultural factors unique to homeless persons, childhood physical abuse, childhood sexual abuse and dissociation would still predict both physical and sexual violence between the initial assessment and the six-month follow-up interview. We also hypothesized that dissociation would mediate the influence of childhood physical abuse and sexual abuse on physical and sexual violence. This prospective analysis was conducted within the Shelter, Health, and Drug Outcomes among Women Study, a community-based observational cohort study designed to understand risks for poor health and victimization among homeless and unstably housed women. As we have described elsewhere , a mobile outreach team used systematic probability sampling to recruit a cohort reflective of the larger San Francisco homeless and unstably housed female population. Details regarding recruitment have been previously published . In brief, study participants were recruited from homeless shelters, free meal programs and low-income single room occupancy hotels. Eligibility was limited to biological females who were ≥ 18 years old and who had a history of housing instability .

Three-hundred homelessness or unstably housed women were enrolled in the cohort between 2008 and 2010, and followed every six months for a total of 7 time points ranging for a follow-up period of up to 3 years from recruitment date. In accordance with the aims of the parent study, HIV-positive women were over sampled so that they comprised 50% of the total cohort. The two-hundred-eighty-one participants who completed enrollment and 6- month follow-up interviews were included in the current study. Participants engaged in check-in visits with study staff between semi-annual study visits to update contact information and to ensure they remained engaged in study activities. All participants provided written informed consent. Upon enrollment, structured interviews were conducted in a private space at a community-based field site. Study questionnaires were interviewer administered. Socially sensitive questions, including those regarding violent victimization and drug use, were administered via an audio computer-assisted self-interviewing approach in which participants listened to questions through headphones and entered responses into a computer. All questionnaires and study procedures were pilot tested to ensure appropriateness for the target population. Reimbursement of $15 was given for each study interview. Study procedures were approved by the Institutional Review Board at the University of California, San Francisco.Measurement of violent victimization—Violent victimization was assessed using questions based on the Severity of Violence Against Women Scales ,grow tray stand which were tested previously in this cohort . Physical violence was defined as being hit, slapped, kicked, bitten, choked, shot, stabbed, or struck with an object. Sexual violence was defined as being forced to have sex of any kind. Physical and sexual violence occurring before age 18 were classified as childhood abuse. Adult violent victimization occurring in the preceding six months was assessed at the baseline and at the six-month follow-up. Dissociative Experiences Scale—Dissociation was assessed at the initial assessment using the Dissociative Experiences Scale , a 28 item scale where items related to dissociative experiences are rated on a 10-point scale. Items assess feelings of depersonalization they actually see themselves as if they were looking at another person. What percentage of the time do you have the experience?”, de-realization , and other dissociative experiences . The DES demonstrates excellent convergent and predictive validity in clinical and non-clinical populations . Higher scores on the DES indicate more self-reported dissociative experiences. The DES total score was computed as the sum of the 28 items. The DES does not provide a diagnosis of a dissociative disorder; however, for the purposes of this study it was defined as a score > 45 . Individual characteristics—Demographic, social, structural, and behavioral characteristics previously associated with health and violence among low-income women were used to describe the cohort.

Socioeconomic status was measured in terms of dichotomous indicators of low income , any unmet subsistence needs Gelberg, Gallagher, Andersen, & Koegel, , and homelessness . Substance use was measured by dichotomous indicators of any current cocaine use, any current methamphetamine use, any current opiate use, and current at-risk alcohol use . Mental health diagnoses were assessed at the initial assessment by the computerized Diagnostic Interview Schedule for the DSM-IV . Thirty-nine psychiatric diagnoses were assessed, including anxiety disorders , mood disorders , psychotic disorders , substance use disorders associated with alcohol, amphetamines, cocaine, opiates, and sedatives; abuse and dependence associated with hallucinogens, inhalants, marijuana, and phencyclidine; and dependence on other drugs, as well as somatization disorder, pain disorder, and dementia. All diagnoses assessed the presence versus absence of disorders. STATA Statistical Software: Release 13.1 was used to conduct all statistical analyses . Descriptive statistics were first generated for the variables described above. We then employed two separate hierarchical logistic regression models to understand the effects of four main characteristics on physical violence and sexual violence at the six-month follow up. The four main effects were childhood physical abuse, childhood sexual abuse, violent victimization during the six months prior to the initial assessment, and dissociation reported at the initial assessment. Specifically, physical violence in the six months prior to initial assessment was used to predict physical violence in the six months after initial assessment. Similarly, sexual violence in the six months prior to initial assessment was used to predict sexual violence in the six months after initial assessment. Main effects were estimated controlling for age, race, and, in accordance with our prior work regarding significant correlates of violence in this cohort , whether participants had recently experienced unmet subsistence needs. Ten theoretically and diagnostically relevant psychiatric diagnosis variables were created from the thirty-nine diagnoses assessed by the DIS. Related diagnoses were grouped into categories reflecting depressive, anxiety, bipolar, psychotic, alcohol, cannabis, amphetamine, cocaine, and opiate disorders, while uncommon diagnoses, such as dementia, were not included. We then used the Variance Inflation Factor to evaluate multicollinearity. Out of the ten psychiatric diagnoses, two highly dependent variables, any anxiety disorder; VIF = 13.02 and any bipolar disorder; VIF = 12.56 were dropped from the final list of variables that were included in the final analyses due to multicollinearity . Hierarchical modeling included four steps. The initial model included age in years, race, and dichotomous indicators of unmet subsistence needs, and violent victimization in the six months prior to initial assessment. The second step of the model included childhood physical abuse and childhood sexual abuse. The third step included mental health and substance use diagnoses. The final step included dissociation as measured by the DES total score. Interactions between dissociation and relevant covariates such as the presence of a substance use disorder were also tested because substance use is associated with symptoms similar to dissociation. Omnibus χ2 tests were used to assess model fit in predicting either physical violence or sexual violence at each step of analysis. McFadden’s R2 was used to assess proportion of model variance explained. Wald χ2 tests used to assess whether each subsequent model was incrementally more predictive of violent victimization from the previous one. Mediation analyses were based on significant relationships between childhood physical and sexual abuse, dissociation, and physical and sexual violence identified in the logistic regression analyses. Bootstrapping was used to assess whether dissociation mediated childhood abuse and violent victimization. Bootstrap estimates on 10,000 replications were obtained using a user written binary mediation ado program in conjunction with STATA’s native bootstrap code. Bootstrapping is generally recommended over other methods of testing indirect effects because it does not assume normality and has greater power while maintaining control over Type I error rates . Compared to the entire cohort , a lower proportion of study participants included in follow-up analyses were homeless at baseline ; no statistically significant differences existed between excluded and included participants according to drug use or mental health variables. Among those enrolled, 93% completed a six-month followup and were included in the current analysis . Approximately 70% of study participants included in the current analysis were women of color. The mean age was 47 years .

E-cigarettes have been marketed as a form of harm reduction from traditional cigarette smoking, but neither the safety nor the efficacy of these devices has been established, and little is known about the short and long term pulmonary and systemic health effects. This review focuses on the known and unknown toxins contained in e-cigarette aerosols, lung diseases induced by vaping, and the predicted long-term consequences of e-cigarette use. Particular attention is given to the e-cigarette or vaping product use-associated lung injury epidemic that began in 2019 and is ongoing. E-cigarettes are devices composed of a power source, heating element, and liquid reservoir that heat and aerosolize e-liquids to make vapor that is inhaled into the lungs in a process known as vaping. E-liquids are most often composed of 1) Addictive substances such as nicotine and/or tetrahydrocannabinol , 2) Flavorings, and 3) Solvents . There are many types of vaping devices, but the most frequently used include pod vapes, box mods, and vape pens . The pod devices were widely popularized by the company Juul, which developed its sleek device to look like a flash-drive that quickly became the most profitable e-cigarette by the end of 2017. The e-liquids in Juul pods contain high concentrations of the more rapidly absorbed nicotinic salts complexed with benzoic acid, compared to free based nicotine, thus increasing the addictive potential and toxicity. Given that nicotine exposure influences long-term molecular, biochemical, and functional changes in the adolescent brain, it is not surprising that teens who vape are at increased risk of subsequent use of traditional cigarettes, marijuana, opioids, and other illicit drugs with addictive potential.

THC also induces alterations in reward networks in the adolescent brain, which increases risk for future drug use,plant bench indoor and regular cannabis users of any age have poorer neurocognitive functioning and functional brain alterations relative to nonusers. Although vaping devices are not an approved nicotine replacement therapy, the Federal Drug Administration has allowed e-cigarette manufacturers to design e-liquids using components that have been ”generally recognized as safe” . Compounds that have GRAS status are only assessed as safe to ingest via the gastrointestinal tract, or put on the skin. Thus, the vast majority of compounds with this designation have not been tested for safety via the inhalation route. There are thousands of different flavoring ingredients used, and thermal decomposition of propylene glycol, glycerol, and flavoring agents result in the production of toxic aldehydes at levels that exceed occupational safety standards. Chemical flavorings such as diacetyl and 2,3-pentanedione, present in many e-liquids, have been found to induce transcriptomic changes that disrupt cilia function in human airway epithelium, impairing mucociliary clearance. Cumulative exposure to diacetyl is well known to be associated with the development of the irreversible airway fibrosing disorder bronchiolitis obliterans , with the term “popcorn lung” used when referring to BO described in microwave popcorn factory workers. Other toxins found in e-cigarette vapor with inhalant and systemic toxicities including terpenes, acrylonitrile, formaldehyde, crotonaldehyde, propylene oxide, acrylamide, and heavy metals. None of these products are currently regulated, but there is even greater cause for concern regarding the inhalant toxicity for the components in “black market” or counterfeit e-liquids and devices as well modified devices. Finally, microbial toxins may contaminate vaping devices even prior to use.

One study tested the leading U.S. pod vape and found that 81% of devices contained B-D-glucan, a fungal cell wall marker, and 23% contained endotoxin, found in the outer wall of gram-negative bacteria. Both of these microbial contaminants are associated with asthma and hypersensitivity pneumonitis.E-cigarettes have been marketed as a form of harm reduction from traditional cigarette smoking, but neither the safety nor the efficacy of these devices has been established, and little is known about the short and long term pulmonary and systemic health effects. There have been increasing reports in the literature of negative pulmonary effects with the recent epidemic of e-cigarette or vaping product use-associated lung injury  being the most immediately concerning. Reports of the development of chronic respiratory symptoms, increased asthma morbidity, and the development of diffuse lung disease in both adolescents and adults highlight significant pulmonary toxicity and compel further research. E-cigarette users are more likely to report chronic respiratory symptoms and conditions in both adolescents and adults. In a large study from Hong Kong of 45,000 adolescents who vaped in the previous month reported chronic cough or phlegm production with increased odds. In a smaller study of 2,000 high school students in Southern California, past and current vaping was associated with a nearly two-fold increase in the risk of chronic bronchitis symptoms. In a longitudinal analysis of adults in the Population Assessment of Tobacco and Health Waves 1, 2, and 3 with data collected from 2013-2016, a significant association between former and current use at Wave 1 and incident respiratory disease at Waves 2 or 3 was demonstrated, controlling for combustible tobacco smoking and other demographic, and clinical variables. In this study, dual use of cigarettes and ecigarettes had increased odds of developing respiratory disease of 3.30 compared with a never smoker/vaper. Among asthmatic patients, primary e-cigarette use and secondhand exposure confers increased morbidity.

Interestingly, vaping is more popular among asthmatic teenagers as compared to their non-asthmatic peers. The reason for this observation is unclear, but may be related to the commonly held belief that vaping is safer than smoking cigarettes. Among adult never cigarette smokers, current e-cigarette use was associated with 39% higher odds of self-reported asthma compared to never e-cigarette users. In South Korea, vaping in high school students was associated with increased odds of being diagnosed with asthma and more missed days of school secondary to asthma. The Florida Youth Tobacco Survey showed that past-30-day e-cigarette use was associated with having an asthma attack in the past 12 months among high school participants with asthma. This survey later revealed that 33% of 11- to 17-year-olds with asthma had secondhand ecigarette exposure, and this exposure was associated with increased risk of asthma exacerbation. There are also case reports of two adolescent asthmatic e-cigarette users who presented with life-threatening status asthmaticus requiring VV-ECMO[36]. This may indicate increased risk for more severe exacerbations among asthmatic teens who are vaping. In addition, EVALI cases from both the Illinois and Wisconsin cohort and Rochester cohort reported higher- than expected rate of EVALI in asthmatics. Vaping has been linked to various rare pulmonary conditions and pathologic abnormalities. There have been multiple case reports of different types of severe and life-threatening diffuse lung disease in patients using vaping products including hypersensitivity pneumonitis, eosinophilic pneumonitis, diffuse alveolar hemorrhage, lipoid pneumonia and bronchiolitis. These case reports demonstrate that there is undeniable harm associated with vaping even before decades of use. Among patients with EVALI, pathology results included findings consistent with acute lung injury including acute fibrinous pneumonitis,greenhouse rolling racks diffuse alveolar damage, and organizing pneumonia. Taken together these pathological findings indicate that severe lung injury in multiple different patterns can occur in the setting of vaping. Although the mechanism of injury in these patients is currently unknown, it is presumed that there are both product and host related factors contributing to lung injury. Given that multiple components of vaping products can cause pulmonary toxicity, it is unlikely that there is only one chemical component leading to these diverse patterns of toxic lung injury. Beyond the scope of this review are systemic toxicities as well as trauma due to explosions, thermal injuries and acute intoxications including ingestion of e-liquids.The national outbreak of e-cigarette, or vaping, product use-associated lung injury has been the first vaping related disease to affect thousands of people . At its core, it is a chemical inhalation injury, most likely caused by heating, aerosolization and inhalation of Vitamin E within THC liquids and vape pens. Examination of airways and lungs of those affected has yielded a pattern of epithelial and alveolar damage. Neutrophils and foamy macrophages are often documented, with lipid laden phagosomes when directly tested through appropriate lipid stains; however, lipid laden macrophages are most likely evidence of vaping in general, not specific to EVALI.

Although it has been clear for years that users of e-cigarettes and vaping devices were inhaling known toxins such as diacetyl and formaldehyde, this disease entity was the first to demonstrate that inhalation of clouds of chemicals that have never been tested for safety via inhalation methods can lead to significant impacts on public health. EVALI was first recognized in August 2019, with the number of recognized cases rising precipitously until December 2019. The connection with THC was made within several weeks – approximately 82% of those affected had vaped THC – while the identification of Vitamin E acetate as a prime suspect took months, and has not been confirmed as the etiologic agent at this time. Fourteen percent of those affected vaped nicotine containing e-liquids only, but upon review these subjects were older, female and had less leukocytosis, suggesting that they may have been suffering from a different vaping induced lung disease. Overall, EVALI is a disease of the young, with a median age of 24 years. It also predominantly affects males , which may be directly related to epidemiologic patterns of THC vaping. The majority of patients present with respiratory , gastrointestinal and systemic symptoms, and are found to have elevations in erythrocyte sedimentation rate , Creactive protein , white blood cell counts, and liver function tests. Beyond these factors, bilateral lung infiltrates are the key diagnostic finding on radiographic imaging. The mortality rate is quite low, at 2.4% , with the highest mortality rate in older e-cigarette users with comorbidities. The median age of deceased EVALI patients was 49.5 years, with a range from 15 up to 75 years. Of the cases identified up to December, approximately 47% required ICU admission and 22% required intubation. Because only moderate to severe cases were tracked, the reported numbers are likely to severely underestimate those affected. Since Vitamin E acetate within THC e-liquids has been identified as a likely causal agent, and with the intense media coverage of this disease entity, there is hope that the incidence of this particular vaping disease will decrease. However, as vaping increases across society, with millions of users inhaling hundreds of thousands of chemicals including lipophilic agents similar to VEA, it is clear that vaping associated lung diseases are here to stay. Conventional tobacco has been smoked for over 5000 years and is very well known to cause a myriad of long-term health problems, not the least of which is lung disease. Because modern vaping devices have been on the market for less than 16 years, and only widely used for 5, very little is known about how chronic use will affect human health. Murine data suggest that some vapers will develop emphysema, heart disease, renal failure, and even liver fibrosis, but these diseases will be couched in genetic predisposition, type of e-device used and the chemicals within the inhaled aerosol. Because vaping aerosols contain chemicals that cytotoxic and cause DNA damage, it is unsurprising that murine models have demonstrated increased occurrence of lung toxicities. Thus, it is hypothesized that long-term vaping will lead to increased incidence of cancer. Because acute and subacute vaping can increase airway resistance and airway reactivity, it is believed that chronic use of e-cigarettes will lead to more severe disease in asthmatics. Vaping alters the function of myeloid cells, including granulocytes, such that it is likely that vaping will alter the function of eosinophils as well, leading to vaping induced changes in allergic diseases. Asthma has many phenotypes, including eosinophilic and neutrophilic subtypes, and with the knowledge that vaping has broad effects on immune cells, e-cigarette use may impact multiple asthma phenotypes. Studies in humans thus far are limited to acute and short-term effects, but consistently demonstrate that vaping impacts both pulmonary and cardiovascular function. Gene expression from airway samples evidence changes that parallel those in cigarette smoking, which is worrisome in that it predicts that vapers will develop the same lung diseases that smokers do – namely emphysema, chronic obstructive pulmonary disease , and respiratory bronchiolitis interstitial lung disease. In addition, altered human neutrophil function suggests that vapers will be at higher risk for bacterial infections as well as autoimmune disease. While longitudinal studies on the health effects of chronic e-cigarette use are needed, the data thus far suggest that vaping will have substantial adverse impacts across organ systems, leading to significant morbidity and mortality over time.

For home prepared diets, a list of ingredients and the source of the recipe was requested. Participants also identified where they obtained information on choosing the diet. For the supplement section, participants answered questions on which products were added or stopped in response to the cancer diagnosis, in addition to which supplements participants maintained both before and after the diagnosis. Participants were then asked where they obtained information on supplements and where they purchased these products for their dogs. The treat section asked for the names of commonly given treats, how often the treat was given, and if the treat was used as a food topper or given with medications. The diet and supplement sections collected both past and present information, whereas the treat section only collected present information. To accommodate requests from initial survey testers and increase the overall survey experience, some questions did not force a response . This was to allow dog owners to complete the survey, even if they did not remember specifics for a particular question, and to reduce the total number of survey pages. Owners who altered their dog’s diets because of a cancer diagnosis were given questions on the previous diet, but responses were not forced for brand , form of diet , ingredients , or recipe source . For the supplement section, responses were only forced for general supplement categories . Questions involving specific supplement types , informational resources used, and where supplements were bought did not force a response. The questions in the treat section did not force responses.Data were collected from the medical record including date of birth, date of first visit to the oncology services, body weight at first visit , sex, spay/neuter status, diagnosis, time from diagnosis to survey completion, breed, body condition score , appetite level at first visit ,cannabis growing system whether or not any signs of gastrointestinal disease were present at latest visit, and address. Address information was used to determine 2021 estimated census tract median family income.

Survey data were exported into RStudio version 2022.12.0 for statistical analysis using R version 4.2.2 . Descriptive statistics were used to describe dog demographics. For diets and supplement use, reasons for changes and informational resources were reported as n values and percentages. Data were checked for normality using a Shapiro-Wilk’s test. A logistic regression model was fitted to predict diet swapping based on information in the medical record or survey. We used the Akaike information criterion to select from the possible variables of using veterinarians as a diet information resource, weight , diagnosis group, estimated family income , BCS, sex, and appetite at first visit . A P value of <.05 was considered statistically significant.The survey was distributed to 438 owners . Ten owners completed the survey but did not meet inclusion criteria, and these responses were omitted from analysis. One hundred twenty-eight responses included data for at least 1 nutrition related question and were retained for analysis. One hundred twenty of the responses were complete; any survey that reached the end was considered complete, regardless of optional questions answered. The median time from diagnosis to survey response was 61 days, with a range of 2 to 472 days . Most questions forced responses and the reported sample sizes will align with the number of respondents reaching a particular part of the survey . However, the sections that did not force a response had fluctuating sample sizes resulting from respondents proceeding through the survey without answering a particular question.Out of the 128 dogs for which we had available survey data, 55.5% were male and 44.5% were female . Omitting 2 dogs without date of birth in their medical records, the ages of 126 dogs were normally distributed with a mean of 9.9 years and a SD of 3.1 years. Omitting 1 dog without weight recorded at time of visit, 127 dogs had a median weight of 26.0 kg, with a range of 3.2 to 64.0 kg. All dogs had their breed recorded in the medical record, with 25.0% listed as mixed breed.

Among purebred dogs , the most common breeds were golden retrievers , Labrador retrievers , and German shepherds . Only 102 of the 128 dogs had a BCS recorded in their medical record; the median BCS was a 5, with a minimum of 3 and a maximum of 9. Diagnoses for all 128 dogs were divided into 5 categories: epithelial origin tumors , mesenchymal origin tumors , round cell tumors , benign tumors with clinical effect diagnosed as pituitary tumors or thymomas, and undefined masses . For the 108 dogs with appetite described in the medical record at the time of visit, 13 had decreased appetite , 91 had normal appetite , and 4 had increased appetite . 22.7% of all respondents reported any GI clinical signs in the time between initial presentation and survey completion. Out of 128 respondents who answered diet information questions, 47.7% altered their dog’s diet in response to a cancer diagnosis. Out of 124 respondents providing supplement information, 28.2% altered supplements in response to a cancer diagnosis, 20.9% altered both diets and supplements, and 54.8% altered diets and/or supplements.The informational resource most widely used for both diets and supplements was veterinarians . Among owners who changed their dog’s diet , the most common reason was loss of appetite , followed by veterinarian recommendation , and felt old diet was unhealthy . Only 8% of respondents who changed their dog’s diet did so for both reasons of loss of appetite and a veterinarian recommendation. Many owners selected the “other” option . In this textbox, owners listed out reasons including previous dogs with cancer doing well on another diet, adding more meat, or reducing carbohydrates. Owners could select multiple options, with 28% of owners reporting multiple reasons. Before diagnosis , 72.7% of dogs were fed commercial diets exclusively, 3.1% of dogs were fed home prepared diets exclusively, and 24.2% were fed a combination of commercial and home-prepared diets.

After diagnosis, 59.4% of dogs were fed commercial diets exclusively, 7.0% of dogs were fed home-prepared diets exclusively, and 33.6% were fed a combination of commercial and home-prepared diets. There was a significant increase in proportion of dogs fed at least some home-prepared foods as part of their diet after the cancer diagnosis . However, there was no significant difference in the proportion of dogs fed any portion of their intake from a commercial diet after the cancer diagnosis . However, many dogs fed commercial diets both before and after diagnosis changed commercial formulas; out of 49 respondents that provided this information for both time points, 23 switched diets . The most common recipe source for those making home-prepared diets, both before and after a cancer diagnosis, was self formulation . Of the 31 owners using home-prepared diets before diagnosis, 45% reported using self-formulation as the only recipe source. Of the 51 owners using home-prepared diets after diagnosis, 39% only used self-formulation. Veterinarians were the second most used resource both before and after a cancer diagnosis . The most common special diet category fed before diagnosis was grain-free diets, and the most common after diagnosis was diets for a medical condition . The term “natural” was included in the brand or product name of 6.9% of commercial diets before diagnosis and 6.0% of diets after, which was not significantly different .An overview of supplements given,flood table including proportions given both before and after diagnosis, is presented in Table 4. Out of 124 respondents providing full or partial supplement information, 85 owners reported supplement use at any time, including 70 owners who reported supplement usage before diagnosis and 76 who reported supplement usage after diagnosis. There was no significant difference in number of dogs receiving supplements before or after a diagnosis . The most common supplements were joint support products . The most commonly added supplements after diagnosis were herbal products . Out of the 14 owners who added herbal supplements, 12 owners provided specific types; among these owners, 7 reported adding mushroom supplements, and 4 reported adding cannabidiol or tetrahydrocannabinol . Among 83 respondents who specified where supplements were purchased, they were most likely to buy some or all of them online , followed by veterinary offices and pet stores . Other responses included warehouse stores , pharmacies , dispensaries , or other locations .This study examined owner decisions regarding diet and supplement alterations after a cancer diagnosis. The average age of dogs in this sample, around 10 years old, is similar to what has been reported in other studies for the age of development of cancer.Given that older dogs have a higher incidence of degenerative joint disease, this might be related to the finding that joint support products were the most commonly used supplements, both before and after a cancer diagnosis; this is consistent with supplement use in dogs with cancer.For total number of dogs receiving supplements, our data showed no significant change after a cancer diagnosis. Dogs with cancer are more likely to receive supplements than healthy dogs in the general population,which was not evaluated in this study.

Our findings might also reflect the owner’s focus on supporting their dog during chemotherapy and other treatments during the period of time close to diagnosis. Some owners added supplement products after diagnosis. Mushroom-based and CBD/THC supplements were added at the highest rates after a cancer diagnosis; this is consistent with these supplements being more commonly given to dogs with cancer when compared to healthy dogs.This helps to confirm that some of these differences are attributable to a cancer diagnosis, rather than solely because of other factors such as age. Although mushrooms have anticancer potential in mice, this has not been shown in dogs.Similarly, although CBD use is common and has some efficacy in inducing apoptosis and perturbing mitochondrial function in canine glioma cell lines,there are currently no studies on its anti-cancer effect in vivo. Furthermore, the addition of CBD to treats, foods, and supplements intended for animals is not allowed by the United States Food and Drug Administration and remains an illegal practice, which might have led to under reporting in this survey.Another potential instance of under reporting was loss of appetite; more owners reported loss of appetite in the survey than during their initial visit to the oncology service. However, this could also be the result of appetite normalizing before the visit, or appetite loss occurring between the visit and survey completion. We predicted this increase before conducting the survey, and this increase was in-line with the results of a previous study.An increase in feeding of home-prepared foods is similarly reported when comparing the general dog population to those with cancer.The increased use of these foods could potentially lead to inadequate nutrient intake, given that home prepared diets are commonly unbalanced.This concern is compounded by self-formulation of recipes, which was the most common source for home-prepared diets in the present study. However, this could be skewed by owners who added just a couple self-selected ingredients to supplement a commercial diet, rather than fully developed recipes, since many owners gave home-prepared meals in conjunction with commercial diets. One strategy to address this potential problem would be referral to a board-certified veterinary nutritionist to ensure any home-prepared diet is complete and balanced. An alternative strategy could be to discuss with the owner their concerns with commercial pet foods. Collecting a comprehensive nutritional history is not only important for ensuring dietary needs are met, but the conversation could lead to discussion regarding perceived problems of commercial pet foods. The current study did not find the accompanying decrease in commercial diets that has been shown elsewhere with the vast majority of owners using a commercial diet for part or all of their dog’s foods. As our sample comprised dogs with a recent diagnosis of cancer, this might suggest that inclusion of home-prepared elements precedes the complete exclusion of commercial diets, and our survey was conducted too close to the time of diagnosis to find exclusion of commercial diets. However, for owners feeding a commercial diet both before and after diagnosis, nearly half stopped feeding the pre-cancer diagnosis diet. It is possible that our sample would ultimately have stayed on their second commercial diet, rather than eliminating commercial elements entirely.

Among methodologic considerations and limitations, the main outcome measure in this study, initiation of any tobacco use, is a critical milestone, particularly among youth for whom daily smoking may develop over several years.However, long-term established tobacco use deserves attention in future research. Speculatively, youth might report tobacco use differently with in-home questionnaire administration versus in-school questionnaire administration, with unclear impact on the present results. In our 2- and 3-year models, we did not account for the timing of tobacco initiation or time-varying exposures or covariables. However, in an 11-year longitudinal study in Italy, the authors reported that living with smoking family members in adolescence and absence of a household smoking ban in young adulthood were both associated with established smoking among young adults.In the current study, findings were similar in a 1-year repeated measures analysis that allowed for intraperson variation.The COVID-19 pandemic has led to disruptions in daily social activities, schooling, and employment for millions of people globally. For some, the pandemic has also led to financial insecurity, exposure to potentially hazardous working conditions, illness, and the illness and/or loss of a loved one. Research has linked traumatic stress from previous viral outbreaks and other mass-traumatic events to increases in alcohol use, particularly in vulnerable groups such as those with a history of alcohol use disorders . Much less is known, however, about the risk and protective factors for alcohol use during and after prolonged stressors, such as the COVID-19 pandemic. While there is mixed evidence across different study populations,weed trimming tray several initial reports have suggested that rates of alcohol use have increased since the start of the COVID-19 pandemic for some vulnerable groups.

Researchers have posited a variety of COVID-19-related hardships, such as social disconnection, lack of access to healthcare services, and economic difficulties, as potential explanations for these increases. However, it remains unknown which specific types of stressful COVID-19-related experiences are associated with increases in alcohol misuse and what healthy coping strategies might mitigate risk. Prior research has demonstrated that some groups are more vulnerable to stress-related increases in alcohol misuse. For example, stressful events are associated with the recurrence of AUD, which underscores concern about the COVID-19 pandemic’s effect on alcohol use among individuals with a history of AUD. One recent study found that approximately half of adults in recovery from a substance use disorder reported cravings during a pandemic isolation period and that their craving was prompted by loneliness, lack of support, and financial stress, among other factors. In addition, during the COVID-19 pandemic, access to mutual-help groups and specialized AUD treatments may have diminished. This has played out in some early data on individuals with a lifetime history of AUD, which showed that ~20% of participants reported increases in their alcohol use since the pandemic began, with a significant portion of individuals reporting decreased access to substance use disorder treatment. However, other data have shown that 88.9% of women and 88.8% of men in a national survey of adults with ‘resolved’ AUD reported that the COVID-19 pandemic had not affected their recovery at all, and that ‘return to drinking’ events were infrequent. These mixed findings indicate that research is needed to understand the association between potential stressors related to the COVID-19 pandemic and increases in drinking among individuals with a past AUD, and differences between those in remission from AUD and those who are experiencing symptoms of AUD. Women may be particularly vulnerable to increases in drinking during the COVID-19 pandemic.

Two independent studies found that women were more likely than men to have a recurrence of AUD when experiencing interpersonal conflict, whereas men were more likely than women to have a recurrence of AUD in response to social isolation. Higher trauma exposure was associated with a higher risk of relapse only in women. Being married has been identified as a relapse risk factor for women but a protective factor for men. Because gender differences are often not examined in studies of individuals with AUD, robust, nuanced, and consistent findings regarding the role of gender in the associations of stress with drinking outcomes are unavailable. Since the start of the COVID-19 pandemic, some studies have found greater increases in adverse drinking outcomes among women than men. Given the unique stressors experienced by women during the COVID-19 pandemic, primarily related to balancing work and caregiving duties, further research is needed regarding gender differences in the relationships between COVID-19 pandemic stressors and increases in drinking among individuals with past AUD. In addition, individuals at heightened risk for AUD are more vulnerable to stress-related alcohol use. For example, genetic and/ or neural risk factors for AUD have been shown to increase the association between traumatic stress and alcohol use problems. There is also a growing literature suggesting that individuals exposed to traumatic stress differ in terms of temporally sensitive EEG-based measures of neural functional connectivity, which are also associated with heightened risk for alcohol use disorder. EEG coherence, the degree of synchrony in brain oscillatory activity between neural networks in two brain regions, is a heritable measure of neural functional connectivity that has been studied extensively and is correlated with various aspects of cognitive functioning and psychopathology.

While decades of research have focused on genetic and neurocognitive differences observed among those with alcohol use problems, few studies have examined interactions between measures of brain functioning and social environmental factors with respect to risk for alcohol use/misuse. Research teasing apart specific types of stressful COVID-19- related experiences associated with problematic alcohol use , and detailing how they interact with individualized risk factors , will allow us to better understand strategies that may buffer against the re-emergence, exacerbation, or new development of AUD that may occur as the COVID-19 pandemic continues to unfold. This study analyzed new data collected during the first months of the COVID-19 pandemic from longtime participants in the Collaborative Study on the Genetics of Alcoholism study, in conjunction with their data on AUD and drinking collected in prior assessments. The primary aim of this study was to examine the associations between COVID-19-related stressors and coping activities with changes in drunkenness frequency since the start of the pandemic among men and women with and without a history of AUD. Using information from earlier data collections, we further categorized individuals as having had no prior history of AUD pre-pandemic, having been symptomatic of AUD prepandemic, having been in remission from AUD but drinking prepandemic, or having been in remission from AUD and abstinent pre-pandemic. Gender differences in the associations of COVID- 19-related stressors and coping activities with changes in drunkenness frequency were also examined. An exploratory aim was to examine the roles that polygenic risk for problematic alcohol use and neural connectivity played as moderators of these associations.Details on the Collaborative Study on the Genetics of Alcoholism data collection and procedures have been published previously. Briefly,cannabis grow setup since 1990 over 17,000 individuals from families densely affected with AUD and from community comparison families have participated in the COGA study. Participants were administered a comprehensive evaluation that included clinical assessments of substance use and psychiatric disorders using the Semi-Structured Assessment for the Genetics of Alcoholism research interview. In a subset of families, DNA was collected, and a brain functioning protocol was administered that included measures of EEG during resting state, such as measures of neural connectivity. The current COGA protocol began in 2019 when the project turned to a onetime follow-up assessment of previous COGA participants currently in two life stages: participants aged 50 or older , the majority of whom have a lifetime history of AUD, and participants aged 30–40 from a longitudinal study of youth and young adult offspring from COGA families, approximately half of whom have a lifetime history of AUD. In these samples, over 95% had DNA and GWAS data available, and over 75% completed at least one EEG assessment. Further details on these earlier studies have been published.Descriptive characteristics of the analytic sample are displayed in Table 1. Briefly, the average age of participants was 51; 62% were women, 16% self-identified as Black, and 8% self-identified as Hispanic . Differences in characteristics of each analytic group as a function of past AUD history are depicted in Table 1. Individuals without a history of AUD were more likely to be women and Black and had less severe alcohol-related history and other substance use, compared to individuals with a history of AUD and were younger compared only to abstinent individuals in remission from AUD. Increases in drunkenness frequency since the start of the pandemic as a function of pre-pandemic AUD status are displayed in Fig. 1.

Increases in drunkenness frequency since the start of the pandemic were significantly greater among those experiencing AUD symptoms prior to the start of the pandemic when compared to those without a history of AUD . Among individuals in remission from AUD prior to the start of the pandemic, rates of increased drunkenness were 10% for those who were drinking pre-pandemic and 4% for those who had previously been abstinent. Across all groups, women reported nominally greater increases in drunkenness frequency when compared with men; however, only women experiencing pre-pandemic AUD symptoms reported significantly greater rates of increased drunkenness since the start of the pandemic compared to women without a history of AUD . To capture the shared variance represented by the 33 COVID- 19-related stress and coping activities items shown in Supplementary Table 1 and to reduce the multiple test burden, each item was entered into an exploratory factor analysis. While models ranging from 7 to 11 factors all provided a good fit to the data , a 9-factor solution provided the best balance of model fit and interpretability. To obtain factor scores, we subsequently conducted a confirmatory factor analysis including 9 latent factors indexing COVID-19 related illness and severity, family member illness and death, media consumption, perceived stress, economic hardship, healthy coping activities, relationship quality, social disconnection, and essential worker status. Several of the COVID-19-related factors were correlated ; among the most highly correlated factors were perceived stress with social disconnection , media consumption , and economic hardships . Essential worker status was also highly correlated with COVID illness . The main effects of COVID-19-related stress and healthy coping latent factors on change in drunkenness frequency are displayed in Table 2 and Fig. 2. Note, Fig. 2 depicts group-level change in terms of participants who reported that their frequency of drunkenness has increased or decreased since the start of the pandemic. Among those without a prior history of AUD, associations between COVID-19 risk and protective factors with increases in drunkenness frequency were not observed. Among all groups with a history of AUD , perceived stress was associated with increases in drunkenness. Among the remitted-abstinent group, essential worker status was associated with increases in drunkenness. Gender differences in these associations were observed . Among women in the remitted-abstinent group, essential worker status, perceived stress, media consumption, and social disconnection were associated with increases in drunkenness. Among men in the remitted-drinking group, perceived stress was associated with increases in drunkenness, and increased relationship quality was associated with decreases in drunkenness. Exploratory analyses examining whether polygenic risk for ‘problematic alcohol use’ and/or low alpha EEG interhemispheric coherence moderate the associations of the COVID-19 factors and changes in drunkenness are presented in Supplementary Table 3. Exploratory analyses indicated that associations between family illness or death with increases in drunkenness and increased relationship quality with decreases in drunkenness were more pronounced among the remitted-drinking participants with higher PRS. Associations between family illness or death, media consumption, and economic hardships with increases in drunkenness and healthy coping with decreases in drunkenness were more pronounced among the remitted-abstinent group with lower interhemispheric alpha EEG connectivity. In this study, we examined the association of COVID-19-related stress and healthy coping activities with changes in drunkenness frequency since the start of the COVID-19 pandemic among participants with and without a history of AUD, including those experiencing symptoms and those in remission from AUD prior to the pandemic. Our results demonstrated that compared to those without a lifetime history of AUD, non-remitted individuals with a history of AUD reported greater increases in drunkenness frequency since the start of the COVID-19 pandemic; however, this difference was not observed among those who had been in remission from their AUD, regardless of their drinking status.

The oral microbiome is one of the most diverse microbial niches in the human body, including over 600 different microorganisms . It is in continual contact with the environment, and has been shown to be susceptible to many environmental effects. These environmental factors include tobacco use, romantic partners, and cohabitation. The microbes reside in sub-niches along the oral cavity including on the tongue, cheek, and teeth. The salivary microbiome has been shown to be representative of many the oral microbiome niches, which is thought to be due to the fact that microorganisms from the oral cavity surfaces shed into the saliva. Previous salivary microbiome studies have identified specific microbiota that are present in almost all individuals, referred to as the core microbiome. Saliva is also accessible, making it ideal for surveys of populations for microbiome studies. In this paper, we describe an unbiased approach to studying the effects of human genes on the oral microbiome with a two-step strategy. The first step utilizes twin information to establish heritable phenotypes related to the microbiome; and the second identifies DNA sequence variation associated with the identified highly heritable traits. From 16S rRNA sequence information, a large number of potential phenotypes can be explored with the twin studies to allow identification of the most heritable and therefore the phenotypes most likely to be mapped in the association study. A key strength of this approach lies in the independence of the data underlying the two steps reducing multiple testing and type 1 effects on the power to carry out the test for association. The ability to refine a phenotype prior to carrying out an association study can lead to greater likelihood of detecting specific SNPs that influence it. We show,plant benches with the largest oral microbiome twin study to date, that multiple phenotypes of the salivary microbiome are heritable.

Using these phenotypes, we identify promising host gene candidates in a genome wide association study of an separate sample that may play a role in establishing the oral microbiome.Samples from 1504 twins of whom 111 within-twin longitudinal samples with at least 3500 reads and DNA samples from 1481 unrelated individuals with at least 3000 reads produced 2664 and 2679 OTUs respectively. All samples were rarefied to 2500 sequences to retain as many samples as possible to improve power with little effect to results. To avoid analyses of OTUs that were the result of sequencing or PCR error, OTUs that were not present in at least 2 subjects and observed at least 10 times were removed, resulting in 895 OTUs in the twins and 931 OTUs in the unrelated individuals. One of the unrelated individuals was later removed during analysis due to cryptic relatedness leaving 1480 people in the unrelated sample.β-diversity was analyzed via Bray Curtis and UniFrac using QIIME and R. Analyses included 366 MZ pairs, 386 DZ pairs, and 37,832 unrelated pairs obtained by using age and DNA collection year matched non-cotwin pairs from the twin sets. P values were calculated similarly to as previously described. In short, the pair labels were permuted 10,000 times and the W test statistic collected from each permutation. The P value was then calculated by dividing the number of W test statistics greater than the observed W test statistic plus 1 by the number of permutations plus 1. Biplot analyses were used as implemented in QIIME . In experiments where cohabitation was required, only cotwins 18 and under and those over 18 who identified themselves as cohabitating were included, which removed 328 subjects from the total twin sample who were living separate from their cotwin. This population of 588 twins pairs is referred to as the “cohabitation sample.” Cohen’s D effect size for β-diversity measurements was calculated using the R package ‘effectsize’ .

Microbial traits included taxonomic groups, OTUs, α -diversity measurements, and principal coordinates from β-diversity measurements , collapsing all perfectly correlated traits. Microbial traits were then processed within each population separately: twin pairs, European unrelated , and Admixture American unrelated . Traits were transformed to z-scores and then categorized as either continuous or categorical . Shapiro Wilk test was performed use the R packaged ‘stats’. Categorical traits were then binned based upon z-score transformation on all non-zero values : zero counts, less than or equal to −1, greater than −1 and equal or less than 0, greater than 0 and less than or equal to 1, greater than 1. Some traits failed to categorize due to lack of variation, resulting in the final trait counts: twins , EUR unrelated , ADM unrelated . Only the continuous traits were used in the EUR and ADM populations so data is provided only for those traits. Descriptions of all traits can be found in Additional file 1: Tables S11–14.The MZ and DZ ICC values were calculated using the R package ‘irr’ and were compared using the Wilcoxon Signed Rank Sum test function in the R package ‘stats’. The ICC values were calculated for all taxonomic groups that were categorized to be treated as continuous traits . P value was calculated as similarly to as previously described in which the zygosity labels of the twin pairs were randomized 10,000 times and the ICC values then calculated. This analysis compared the overall distribution of the ICC values for the MZ twin pairs compared to the DZ twin pairs. Because the entire distribution was compared and not each taxa individually multiple testing correction was not needed. In addition the ICC values for the remaining 17 continuous traits were determined .Genome Complex Trait Analysis was performed on all traits categorized as continuous in both the twin and unrelated populations using the GCTA software. The GCTA analysis was performed on the cleaned imputed genotypes described above in the European sample . The following covariates were included in the model: age; sex; sequencing run ; year DNA was collected; saliva collection method for 16S sequencing; DNA collection method for host genotyping; and the first 10 PCs to control for population stratification.

GCTA estimates for the Admixture American sample were not reported due to the small sample size after the threshold of IBS estimates less than 0.025 were applied.Genome wide association study analyses were performed using the software EPACTS. The Q.EMMAX function was used, analyzing the dosage information for each variant. The GWAS analyses were performed in the ADM and EUR ancestry groups separately. For both analyses a kinship matrix and first 10 principal components were included to control for population stratification within each ancestry sample . In addition to controlling for population stratification the following covariates were included in the model: age; sex; sequencing run ; year DNA was collected; saliva collection method for 16S sequencing; DNA collection method for host genotyping; and tobacco use . The kinship matrix was created based upon all 22 autosomes using the kinship function in EPACTS. To rule out the possibility that stratification or computational method influenced results, three additional methods utilizing different programs and methods for controlling for population stratification were carried out. These were: EPACTS with only the kinship matrix made from all SNPs ; PLINK with the first 10 PCs ; and GCTA with the leave-one-out kinship matrix . For all methods the following covariates were included in the model: age; sex; sequencing run ; year DNA was collected; saliva collection method for 16S sequencing; and DNA collection method for host genotyping.We performed an analysis of 752 twin pairs from the Colorado Twin Registry to estimate host genetic and environmental contributions to salivary microbiome composition. The sample included 366 monozygoticpairs , 263 same sex,rolling bench and 123 opposite sex dizygotic pairs that ranged from 11 to 24 years of age. Taxonomic analyses using sequencing of variable region IV of the 16S rRNA amplicon prepared from the saliva of each twin was carried out using QIIME on high-quality Illumina MiSeq paired end reads as previously reported. We determined phyla abundances to be Firmicutes , Proteobacteria , Bacteriodites , Actinobacteria , and Fusobacteria from the 2664 operational taxonomic units found, which is consistent with the “core” salivary microbiome we and others have previously reported. All of our analyses included only OTUs that were present in at least 2 subjects and observed at least 10 times in total after rarefying at 2500 reads. This filtering yielded 895 OTUs that were considered for all subsequent experiments. Measurements comparing mean β-diversity among MZ, DZ and unrelated individuals allows for assessment of microbial population differences between groups. With either Bray-Curtis or Weighted UniFrac measures of β-diversity among MZ twin pairs were significantly more similar to each other than DZ twin pairs, and for all 3 β-diversity measurements MZ and DZ twin pairs were significantly more similar to each other than to unrelated individuals . This analysis was also carried out with abundant OTUs and all OTUs with very similar results .

Rarefaction at 2500 reads produced consistent results across all rarefactions , so for subsequent analyses, one rarefaction to 2500 reads is shown. We could detect no significant effect on any β-diversity measure due to sex when comparing same sex vs opposite sex dizygotic twin pairs perhaps because the sample size did provide enough power to differentiate sex effects from interindividual variation . In subsequent DZ analyses therefore, opposite sex pairs were included. The Colorado Twin Registry includes highly detailed phenotypic information that is invaluable inidentifying and controlling for environmental confounders that may play an important role. Living together is a covariate influencing microbial populations in humans. It is well-known that MZs tend to cohabitate longer than DZs and indeed our previous work has shown that shared environment influences the oral microbiome. Therefore, it was possible that the tendency of MZ cotwins to live together longer could be driving the observed heritability. To examine this potential confounder, we reanalyzed the data in Fig. 1a based on questionnaire data from the sample in which we restricted the analysis to only cohabitating pairs . While ideally we would have also analyzed only twin pairs living apart, our sample size did not permit it. As seen in Fig. 1b, MZs remained significantly more similar to each other than DZ twin pairs for the Bray-Curtis and Weighted UniFrac measurement, and was also observed in the abundant and unfiltered/ unrarefied OTU tables described above . We conclude that cohabitation does not play a significant role in the observed microbiome heritability. To quantify the differences between groups the Cohen’s D effect size was calculated for all β-diversity measurements for both the full sample and the sample limited to twin pairs who were cohabitating . Comparisons between the unrelated and twin pairs yielded medium to large effect sizes. All other comparisons were either small or negligible, the largest of which being between MZ and DZ pairs for Bray Curtis. To quantify the effect cohabitation had on β-diversity measurements the effect size between all twin pairs and just pairs living together were compared for all measurements yielding only negligible effect sizes consistent with a conclusion that cohabitation was not driving observed heritability. The stability of the oral microbiome over time in adults is reported to be remarkably high relative to that of other body sites. To confirm and extend this observation, we assessed the stability of the oral microbiome in longitudinal samples from our cohort for 111 individuals, 2–7 years apart . The mean β-diversity measurements between longitudinal samples were compared to the mean of unrelated individuals of different ages. For all three β-diversity measurements examined subjects were significantly more similar to themselves than were unrelated individuals . Intraclass correlation coefficients are useful for estimating heritability of individual observations within a group of related observations ; the higher the ICC values for MZ pairs compared to DZ pairs, the greater the heritability. As shown in Fig. 2, ICC values for essentially all abundant taxa are significantly greater in MZ than DZ pairs. No significant difference was observed between the same sex and opposite sex DZ pairs across the taxa analyzed. The set of taxa analyzed were those that were categorized as continuous . Significance was established with Wilcoxon Signed Rank tests strongly supporting the heritability of taxon abundance in this twin set. We also tested 4 different alpha diversity measures , the first 3 principal coordinates for three different β-diversity measurements and saw that most traits were consistent with the conclusion that MZ cotwins are more similar than DZ cotwins.

We will also examine intervention efficacy on other opioid outcomes , other substance misuse and consequences, and impaired driving. Further, we will also measure intervention costs and identify moderators/mediators of efficacy. In this paper, we describe the RCT protocol with a focus on evaluation of primary and secondary outcomes.We are testing the efficacy of behavioral interventions as secondary prevention for opioid misuse and opioid use disorder among AYAs in a 2 x 2 factorial RCT design with two intake and two post-intake conditions. Conditions delivered at intake are: 1) a single video delivered health coach session, and 2) an EUC control condition of a community resource brochure. Post-intake conditions are: 1) portal messaging that lasts for 30 days, or 2) EUC control brochure delivered at 30 days. This combination effectively results in 4 groups as shown in Figure 1 . The health coach session occurs during intake and the portal begins at intake and occurs over the following 30 days. Depending on randomization, the EUC resource brochure is either delivered at intake or 30 days later . EUC essentially functions as a control condition, with the provision of minimal resources that exceed the current standard of care in the ED pertaining to opioid screening and prevention as done in a number of prior ED-based studies.In total, we seek to enroll 1170 ED patients ages 16 to 30 . Recruitment occurs either in-person or remotely, a secondary recruitment approach that was added because of restrictions on in-person research activities during the COVID-19 pandemic. All procedures are IRB approved.As part of our funding mechanism and with IRB approval, we piloted the interventions and EUC described in detail below in the Spring of 2020, with N = 40 AYAs enrolled with informed consent/assent and the same trial eligibility criteria described below.

Each participant received the EUC at enrollment,cut flower transport bucket the health coach session, 30 days of portal messaging, and a 1-month follow-up invitation e-mail . After enrolling the first 10 participants using ED-based recruitment methods, we paused recruitment to refine interventions based on participants’ feedback. During this pause, in-person recruitment efforts were suspended due to the COVID-19 pandemic, and the remaining 30 participants were recruited remotely after their ED visit and all interventions were delivered remotely in private from staff homes to participants’ homes. Among the participants who participated in pilot testing the health coach session, 38 provided acceptability ratings. Their intervention satisfaction was M = 9.3 on a 10-point scale with 10 being the highest possible rating. Similarly, on a 10-point scale, ratings for recommending the intervention were M = 9.0 . Fidelity coding of selected sessions was based on the Motivational Interviewing Treatment Integrity Code33 with fidelity exceeding “fair” thresholds, and nearly all markers exceeding “good” thresholds. These included the following means: M = 4.3 relational scale, M = 3.9 technical score, M = 71.5% complex reflections, and M = 1.7:1 reflection/question ratio. Next with regard to the portal, among our first 10 participants, portal engagement was lower than expected with only 60% replying at all. Thus, we used participant feedback to make several functional and design changes prior to recruiting the next 30 participants. These changes included adding a “remember me” function to avoid needing to remember a password, updating the look and feel of the portal, adding use of an emoji avatar chosen by participants, branded token items valuing ~$1 mailed weekly . We also evaluated use of an incentive structure for portal messaging with the final 30 participants.

Thus, we enrolled 10 participants each into cohorts: a) no incentive for message replies, b) $1 incentive for each reply with ability to earn up to $20, and c) $5 incentive for each reply with ability to earn up to $20. Engagement, as measured by number of replies from participants, was higher in these latter cohorts. The no incentive cohort had a M = 11.8 messages received with 100% replying, the $1 incentive group had M = 10.0 messages received with 80% replying, and the $5 incentive group had M = 15.6 messages received with 100% replying. Given that functional and design changes in the portal appeared to result in increased engagement without the use of additional incentives, we elected to not incentivize participation in the planned RCT, especially since there would be additional challenges associated with later implementation of incentives within healthcare systems. Finally, among 37 pilot participants who provided feedback ratings for the portal, ratings of satisfaction were M = 8.5 and recommendation were M =8.9 , on a 10-point scale with 10 being the highest rating. Modified MITI fidelity coding for complex reflections and reflection-to-question ratio exceeded benchmarks such that were on average 59.5% complex reflections and the average reflection-to-question ratio was 2.9:1. Overall, the feasibility of our pilot testing supported the inclusion of the intervention conditions in the planned RCT. The acceptability data provided by participants at follow-up was promising, particularly given refinements to the portal condition, and staff demonstrated acceptable fidelity to the intervention model. Participants are recruited from the Michigan Medicine pediatric and adult EDs in Ann Arbor, Michigan. Combined, these EDs have about 100,000 visits per year and are located in adjacent, but separate hospitals and maintain independently functioning systems of triage, medical staffing, and physical space allocation.

Recruiting from both EDs enhances generalizability to pediatric and adult ED settings. Historically, the average ED length of stay as been 3-4 hours which facilitates completion of in-person research protocols during the visit, although the COVID-19 pandemic has altered ED patient flow. Currently, there are no opioid-focused prevention programs in the study setting and opioid-related clinical care focuses primarily on treatment referrals and prescription monitoring. We attempt to recruit English-speaking patients ages 16-30 presenting to the ED for any reason in-person or remotely to complete an eligibility screening. Staff approach participants in the ED, and remote recruitment is used when staff are unable to recruit in the ED or to supplement in-person recruitment because of physical distancing limitations on approaching patients with suspected COVID and the number of staff who can be present at any one time due to COVID-related restrictions. When approaching potential participants, they must be medically and cognitively able to provide consent/assent; thus patients presenting with acute substance intoxication are excluded until able to consent. Individuals presenting to the ED with a chief complaint of acute sexual assault or acute suicidality will be excluded from screening. Those presenting with a current cancer diagnosis or currently receiving cancer treatment and pregnant women will also be excluded . AYAs who participated in our pilot study described below or who may be taking part in other current behavioral intervention trials at this study site are also excluded . Screened participants are eligible for the trial based on past 12-month prescription opioid use plus at least 1 other risk factor , or 12-month opioid misuse as described in the measures below . Screened individuals reporting injecting drugs or screening as high risk for current opioid use disorder based on a NIDA-Modified ASSIST V229–32 score of 27+ are excluded due to the study focus on prevention of development of opioid use disorder. These individuals are instead referred for treatment; staff direct them to options listed in study resource brochure if recruited remotely and if in recruited in-person staff offer referral to ED social worker. All procedures herein have been piloted in the study setting and among AYAs,procona flower transport containers including consenting and enrolling minors. Research assistants identify patients ages 16-30 via the electronic health record and tracking system, with a waiver of HIPAA authorization. Patients who meet screening exclusion criteria are not approached. Staff approach screening eligible patients based on triage time/status or discharge date/time using a standard script. Two-stage consent for ages 18+ and parental consent/child assent rare obtained for screening and, subsequently, the RCT. Staff review limits to confidentiality and study procedures during consenting/assenting. Specifically, parents are consented concurrently for screen and baseline . Subsequently, youth assent is obtained for screen and baseline. Study data is not shared with parents or guardians and confidentiality would only be broken in the case of acute risk, such as acute suicidality, homicidality, or child abuse, to preserve adolescents’ or others’ safety. For in-person recruitment, research staff approach ED patients ages 16-30 for consent/assent to self-administer a brief web-based screening survey on iPads. Surveys are paused during medical procedures and consultations such as x-rays, assessments, and blood draws.

For remote recruitment, research assistants contact ED patients ages 16-30 after discharge for consent/assent to complete the screening survey on their personal device or by phone. Participants screened in person receive a gift valuing $1.00 for survey completion. AYAs meeting eligibility criteria above are invited to participate in the RCT. After consenting/assenting, RCT participants complete a baseline survey and are randomized to conditions. Randomization is stratified by sex, age , and opioid risk severity : none or higher and occurs in blocks of 8 within strata to equalize over time. Randomization is computer generated in Qualtrics and is not be known by recruitment staff until after completion of the baseline survey when staff run the randomization program to reveal condition. Staff then orient participants to their assigned condition. Because this is a behavioral intervention where participants are receiving counseling interventions, participants and coaches are not blind to their condition. Participants then receive their assigned intake condition at intake and are then oriented to their post-intake condition . If needed, those unable to complete all intake activities in the ED may complete them in person, by telephone, or video call; these activities are scheduled prior to leaving the ED. Participants who join the study remotely, or who do not complete enrollment during the ED visit, may have up to 30 days to complete intake activities. Enrolled participants receive a token gift in-person or by mail. Participants are asked to complete follow-up assessments lasting approximately 25-30 minutes that mirror baseline measures at 3-, 6-, and 12-months. Participants are remunerated in cash or gift card . Follow-ups are primarily online, without staff interaction, however, in the event a participant elects in-person follow-up staff administering assessments are blinded to condition assignment.Consistent with a telemedicine hub model, research assistants connect participants to the remote health coach using a telehealth platform such as Facetime or Zoom. Health coaches are bachelor’s-level or higher staff hired who have relevant backgrounds and experience in fields such as social work, psychology, counseling. Health coaches are further trained in MI and CBT strategies by the study team and supervised weekly by experienced master’s-level coordinators and doctoral-level investigators. The ~45 minute session blends elements of efficacious brief motivational interventions from our prior work, including an opioid-focused brief intervention and developmentally appropriate content for ages 16-30 based on our prior alcohol-focused brief interventions.The intervention guide is housed in an internal website that is only accessible to study staff and includes decision-support screens to guide intervention delivery and enhance fidelity , allowing health coaches to collect within session para-data , consistent with prior work that found para-data are associated with important MI mechanisms and clinical outcomes.Our session, outlined in Table 1 is rooted in the Why Change and How Change model of MI.The remote health coach session uses MI strategies to engage and explore individuals’ situations, allowing for in-the-moment tailoring to address needs relevant for AYAs using MI concepts . During Why Change, health coaches review and affirm participants’ goals and strengths, and invite discussion of opioid misuse as well as other substance use. MI skills , seeking permission, Elicit-Provide-Elicit, elaboration, rulers, and autonomy support are used. Elicit-Provide-Elicit is a tool for collaborative psychoeducation used to explore risk perceptions of opioid medications and/or overdose in a highly tailored manner .Personallyspecific benefits of change are elicited and reinforced; as many young people may be pre-contemplative about change, health coaches learn to elicit hypothetical benefits of future change or scenarios for choosing to avoid use . After summarizing change talk, health coaches explore How Change, eliciting personally tailored tools to address misuse of substances and risk factors. Tools include brainstorming alternatives to address motives and risks . If applicable, participants are encouraged to consult their primary care or other medical providers with questions.

CBSST appears to be an effective intervention to address these concerns that requires minimal resources and a relatively brief treatment interval, making it ideally suited to adaptation to a variety of clinical settings. Future studies will compare CBSST to standard outpatient care with a focus on additional outcomes, including quality of life and healthcare utilization.Bipolar disorder is a severe, chronic, and disabling mental illness characterized by recurrent episodes of hypomania or mania and depression. The evidence from twin, family, and adoption studies provide compelling evidence for a strong genetic predisposition to BPD with heritability estimated to be as high as ≥80% . Given BPD is a heterogeneous disease with substantial phenotypic and genetic complexities, the identification for BPD risk loci has proven to be difficult. Some researchers have proposed that dissecting BPD into clinical subgroups with distinct sub-phenotypes may result in genetically homogeneous cohorts to facilitate the mapping of BPD susceptibility genes . Among the subphenotypes, early-onset BPD is of particular interest as several independent cohort studies have demonstrated their existence. Comparing to the non-early-onset BPD, the early-onset subtype is associated with a more severe form of clinical manifestations characterized by frequent psychotic features, more mixed episodes, greater psychiatric comorbidity such as drug and alcohol abuse and anxiety disorders, higher risk of suicide attempt, worse cognitive performance, and poorer response to prophylactic lithium treatment. In addition, the pattern of disease inheritance seems to differ between early‐ and late‐onset BPD families, with the former involving greater heritability. These observations indicate that early-onset BPD may be a genetically homogenoussubset and thus could be used for genetic study to identify its susceptibility genes.

A number of BPD genes identified by genome-wide association study have been widely replicated and intensively studied,cannabis grow equipment but these studies did not include early-onset BPD. Over the past two decades, a host of studies have investigated genetic loci responsible for early-onset BPD through linkage-analyses, candidate–gene association, analyses of copy number variants , and GWAS, but findings are inconclusive. Candidate–gene association studies have identified a number of genes potentially associated with early-onset BPD, including glycogen synthase kinase 3-β gene, circadian clock gene Per 3, serotonin transporter gene, brain-derived neurotrophic factor gene, and gene coding synaptosomal-associated protein SNAP25. However, very few positive findings of these studies have been replicated independently. Findings from linkage studies suggested chromosomal regions harboring the susceptibility genes at 3p14 and 21q22, plus the loci at 18p11, 6q25, 9q34 and 20q11 with nominal significance. Studies of CNVs in early-onset BPD were based on relatively small effect sizes and were irreproducible, suggesting that CNVs are unlikely the major source of liability. Finally, GWAS failed to find any risk variant with genome-wide statistical significance in Caucasian populations, despite some variants showed suggestive significance. In previous genetic studies, the definition of early-onset in BPD typically ranged from 15 to 25 years of age. These association studies were largely conducted with small sample size and were under powered . Most of them compared early-onset BPD vs. healthy control. Such a case–control design is more likely to identify susceptibility gene for BPD per se, but not for the early-onset sub-type. The optimal strategy to identify gene for the early-onset BPD is to include the non-early-onset BPD group for comparison. In this paper, we reported findings from a GWAS with high-density SNP chips on early-onset, defined as ≤20 years of age, BPI patients of Han Taiwanese descent.

The clinical phenotype assessment of manic and depressive episodes was performed by well-trained psychiatric nurses and psychiatrists using a cross culturally validated and reliable Chinese version of the Schedules for Clinical Assessment in Neuropsychiatry, supplemented by available medical records. All of them were diagnosed according to the DSM-IV criteria for BPI disorder with recurrent episodes of mania with or without depressive episode. The assessment of onset age was based on a life chart prepared with graphic depiction of lifetime clinical course for each of the BPI patient recruited. This life chart included largely all the mood episodes with date of onset , duration, and severity . The construction of this life chart was based on integrated information gathered from direct interview with patients and their family members, interviews with in-charge psychiatrists, and a thorough medical chart review. Different definitions for early onset of BPI have been proposed in previous work. Our selection of 20 as the age threshold was based on a systematic review for pediatric BPD. The age at onset was defined by the first mood episode . Of all patients, 1306 with genotyping data available were included in the discovery group for GWAS and the rest 473 without genotyping data were included in the replication group.In this paper, we have reported one of the largest GWASs to investigate genetic susceptibility to early-onset BPI with the first mood episode occurring ≤20 years of age. We employed standardized psychiatric interview and constructed a life chart with detailed clinical history to ensure the accuracy and homogeneity of phenotype for genotyping. Our GWAS with high-density SNP chips identified the SNP rs11127876 in CADM2 gene to be associated with early-onset BPI in both discovery and replication groups, and meta-analysis for the association was close to genome-wide significance .

The gene CADM2 on chromosome 3 encodes a synaptic cell adhesion molecule that is prominently expressed in neurons, and plays key roles in the development, differentiation, and maintaining synaptic circuitry of the central nervous system. In previous GWASs, CADM2 has been found to be associated with a number of mental health related traits, including alcohol consumption, cannabis use, reduced anxiety, neuroticism and conscientiousness, and increased risk-taking behavior. CADM2 was also reported to be associated with executive functioning and processing speed, general cognitive function, and educational attainment. Though there have been no investigations examining the risk-taking phenotype in early-onset relative to non early-onset BPD, Homes et al. showed that BPD patients with a past history of alcohol abuse or dependence had a higher risk-taking propensity, suggesting a relationship between early-onset BPD and risk-taking propensity. Of note, Morris et al. suggested that CADM2 variants may not only link with psychological traits, but also influence metabolic-related traits, such as body mass index, blood pressure, and C-reactive protein. In addition, they found that CADM2 variants had genotype specific effects on CADM2 expression levels in adult brain and adipose tissues. The finding highlights the potential pleiotropy of CADM2 gene, i.e., the genetic variants may influence multiple traits, and shared biological mechanisms across brain and adipose tissues through the regulation of CADM2 expression. Given that the metabolic comorbidities are prevalent in patients with early-onset BPD, it is conceivable that CADM2 variants may influence both psychological and physical traits, further contributing to a more severe clinical subtype of BPD with accompanying risk of metabolic adversities. In addition, an association between risk-taking and obesity has also been implicated in previous research, which suggests that risk takers tend to overlook health-related outcomes and are prone to aberrant reward circuitry predisposing them to poor dietary choices and excessive intake. Collectively,vertical grow rack in line with the characteristics found to be associated with CADM2 variants, it is likely that CADM2 may exert an effect on the constellation of clinical features related to early-onset BPD with greater symptom severity . Therefore, our findings suggest that CADM2 genetic variants may have significant effects on a subtype of BPD with early-onset. Two previous GWASs comparing early-onset BPD patients with healthy controls did not find any genetic variants reaching genome-wide significance. Our study included a larger sample of early-onset BPI patients to conduct GWAS using high-density genotyping . The statistical power was calculated using Post-hoc Power Calculator , combining the allelic frequencies of both discovery and replication groups. In this study of two independent samples of BPI with dichotomous endpoint, the power reached 99.4% and 18.2% under type I error = 0.05 and = 5 × 10−8 , respectively. Results of our study are also likely to be under powered under the stringency setting of type I error. However, the frequency of risk allele T was higher in patients with onset ≤20 than in patients with onset >20 in both discovery and replication groups. We believe all these have provided strong evidence to confirm the association of this SNP with earlyonset BPD. In Table 2, the minor allele frequencies differ quite a bit between the discovery and replication cohorts. In the NCBI SNP database, minor allele frequency of rs11127876 is 0.08 in Han Chinese in Beijing, close to our results and suggest that the different allele frequencies observed in Table 2 may mainly result from our sampling. The over-representative minor allele frequency in replication group may have come from random sampling or effects of hidden characters of our patients recruited. Genetic variant of CADM2 has been reported to be associated with behavioral and metabolic traits, which were not assessed in this study.

Though the minor allele frequencies of rs11127876 were different in discovery and replication groups, the same direction of ORs of rs11127876 minor allele supports the reliability of our findings. The SNP rs75928006 located in the upstream of MIR522 reached genome-wide significance in discovery group but failed to show statistical significance in replication group. MIR522 promotes glioblastoma cell proliferation, but there was no evidence to suggest its association with any psychiatric disorders. One major limitation of this study is the possibility of recall bias about the exact onset age of the first mood episode of BPI, particular when there was a long history of the illness. Previous studies have however suggested that age at onset can be assessed reliably. The preparation of life chart containing detailed clinical course and treatment based on a semi-structured clinical interview plus a thorough medical chart review for individual patients should have overcome this potential limitation satisfactorily. In summary, we have identified a genetic locus rs11127876 in CADM2 gene to be associated with earlyonset BPI. The finding has reflected the co-sharing genetic features of psychiatric disorders and behavioral traits. Further investigations of the CADM2 biological function in BPI are warranted.The misuse of opiates is a serious problem worldwide, is increasing in young adults, and has substantial individual and societal consequences. In 2014 in the United States alone, approximately 1.9 million people had an opiate use disorder, including 586,000 heroin users. Neuroimaging in opiate dependence indicates both altered brain structure, particularly in the anterior cingulate cortex , and brain function involving dorsolateral prefrontal cortex and ACC. Magnetic resonance spectroscopy allows the non-invasive quantitation of brain metabolites that provide information on the neurophysiologic integrity of brain tissue. The few 1H MRS studies in opiate dependence to date revealed lower concentration of N-acetylaspartate , a marker of neuronal integrity, in the medial frontal cortex, including the ACC, as well as lower glutamate , a primary excitatory neurotransmitter, or glutamate+glutamine concentration in some but not all studies. The discrepant MRS findings may relate to differences among study participants regarding the prevalence and severity of comorbid substance use , the type, dose and duration of replacement therapy for heroin users , and/or participant age. The ACC, DLPFC and orbitofrontal cortex are important components of the brain reward/executive oversight system, a neural network critically involved in the development and maintenance of addictive disorders. Structural brain imaging in opiate dependence revealed generally lower gray matter volume or density in frontal regions, including the DLPFC, with thinner frontal cortices related to longer duration of opiate misuse. Functional MR imaging showed that the DLPFC, OFC and ACC are involved in decision making, and in opiate dependent individuals, lower task-based fMRI activity in the ACC related to compromised behavioural control of cognitive interference. Furthermore, smaller frontal gray matter volume in opiate dependence related to higher impulsivity on the Barratt Impulsivity Scale . Correspondingly, opiate dependence is associated with cognitive deficits, primarily in executive functioning and self-regulation . Thus, the neuroimaging literature in opiate dependence suggests altered frontal brain structure as well as compromised neuronal integrity and glutamatergic metabolism. Few if any studies however investigated their relationships to opioid and other substance use behaviour or cognition. Further research into specific regional brain effects and their potential cognitive and behavioural correlates may inform better targeted treatment of individuals with opioid use disorders.