Together, these findings support advocacy for policies that support patient access to MC. This study has several limitations. First, MC use remains controversial, and this may limit our patients’ willingness to report MC use and provide honest opinions on MC. We attempted to minimize this bias through collecting data anonymously, but this bias may still be present. The controversy behind MC may have impacted which patients responded to our survey, and thus, despite our favorable response rate of 72.5%, we cannot rule out nonresponse bias affecting our findings. Additionally, this study is conducted with patients presenting to outpatient hand and upperextremity clinics in 2 states in which MC has been legalized for at least 4 years, therefore limiting the generalizability of study findings for patients in states where MC has been recently legalized or where it remains illegal. We defined MC as any legal MC product in our study survey , but investigating patient responses to specific MC products could be explored further in future studies. Further, our patient population consists of predominantly patients with health insurance, which limits the generalizability of study findings. Lastly, our study is limited in that we do not collect information on the patients’ current pain levels, chronicity of symptoms, or RC use status, which could affect patient willingness to use MC. These variables may act as confounders of patient perception of MC, and these relationships should be explored further in future studies. This study found that most hand and upper-extremity orthopedic patients presenting to outpatient offices would consider using MC, and most perceive it as a safe treatment option for common orthopedic conditions. Moreover, 10% of survey participants were already using MC. One of the major barriers to MC use is the financial cost. Most patients support insurance coverage of MC, suggesting that in the future insurance coverage could potentially offset the cost barrier to MC use.
Further studies are necessary to evaluate the effectiveness of MC for the treatment of common hand conditions, as well as to better define the long-term safety and side effects of MC in this patient population.Under suppressive antiretroviral therapies , infection with Human Immuno deficiency Virus remains a challenge, both due to the maintenance of cellular reservoirs and to chronic inflammation driven by low viral replication and dysregulated immune mechanisms . In end organs such as the brain, indoor grow tent where the majority of the HIV-1 targets and reservoirs are of myeloid origin , the remaining inflammatory environment contributes to co-morbidities , including neurological and cognitive problems , particularly if ART is not introduced sufficiently early . Substance use disorders are frequent among the HIV-infected population, further contributing to cognitive impairment . Nonetheless, the mechanisms by which addictive substances and HIV interact are multfactorial and poorly understood. Drugs of abuse impact the brain reward system, by modifying levels and balance of neurotransmitters . The HIV target cells, macrophages and microglia, as well as CD4 T cells, express receptors to neurotransmitters, so SUDs are likely to impact mechanisms of immune and inflammatory, and anti-viral responses . Biomarkers that detect the effect of SUDs, and distinguish HIV in that context, may clarify how drugs affect HIV and inflammation. Cannabis is one of the most prevalent substances among HIVþ subjects, compared to the non-infected population , either prescribed for ameliorating symptoms associated with the virus or with ART , or used recreationally, as well as a component of polysubstance use , which in itself is a risk factor for HIV infection. The effects of cannabis may drastically differ from the effects of stimulant drugs such as Methamphetamine , particularly in the context of HIV infection . Yet, similar to other drugs of abuse, cannabis may be a confounder shifting the expression of biomarkers of inflammation and cognition, masking our ability to clearly measure the impact of virus, ART or other treatments in the immune status and brain pathogenesis, or may be altogether beneficial. In terms of cognition, cannabis exposure has been linked to lower odds of impairment in people living with HIV. On the other hand, impaired verbal learning and memory, may be negatively impacted by cannabis use .
Other studies report no differences, or detrimental effects in HIV-negative populations, suggesting that the observed effects of cannabis, including its benefits, may be largely domain and context-dependent. It has been reported that cannabis use improves biomarkers of inflammation in the CSF and plasma of HIVþ subjects and decreases the number of circulating inflammatory cells . We have tested the value of a large panel of transcripts associated with inflammation and neurological disorders, digitally multiplexed and detectable in peripheral blood cells from HIV-positive and HIV-negative subjects, users of cannabis or not . The differences between groups were analyzed using a systems biology approach that identified associated gene networks based on pathways and molecular interfaces, for identifying and visualizing orchestrated transcriptional patterns consistent with HIV infection, CAN exposure, and their interactions. Trends in the behaviors of gene clusters and their predicted regulators revealed that effects of cannabis differ between HIVand HIVþ groups. Moreover, mixed statistical models have pinpointed genes that are further influenced by cannabis in the context of polysubstance use. These context-dependent effects of cannabis indicate the complexity of its molecular actions and properties, and the challenges of biomarker discovery in the context of SUDs. At the same time, the results suggest that cannabis in the context of HIV infection may drive benefits by promoting a decrease of pro-inflammatory and neurotoxic transcriptional patterns, changes and changes in gene clusters associated with leukocyte transmigration and neurological disorders.Molecular markers of neuroinflammation, activation and leukocyte transmigration were measured in the peripheral blood cells under the hypothesis that cannabis use has an effect by itself and on modulating the effects of HIV. A panel of 784 markers relevant to neurological disorders and inflammation were tested by Nanostring. Of these 381 did not produce any signal in any of the specimens and were excluded from the analysis. The expression of genes with significant signal over noise in more than arbitrarily 10% of the samples was normalized by an average of 8 housekeeping genes.
Hierarchical clustering performed using average normalization method applied to digital gene expression data has revealed similarities between HIV-/CANþ, HIVþ/CAN- and HIVþ/ CANþ, but all these groups were distinct from HIV-/CAN-. Clustering also allowed to identify individual specimens that showed patterns distinct from the majority within groups . Systems biology strategies were used to identify defining expression patterns in transcriptional data, and gene clusters exhibiting orchestrated behaviors perturbed by HIV infection, by the use of cannabis, or by their interaction. We have identified significant trends in a number of gene clusters functionally annotated to biological processes and pathways of relevance to the neuropathogenesis of HIV. Overall, the analysis indicates context-dependent effects of cannabis. The majority of the digitally multiplexed genes exhibited detectable and overlapping interactions based on pathway, as indicated in Fig. 4. The visual inspection of the cluster in Fig. 4 shows that both HIV and cannabis alone increase the expression of a number of genes indicated by nodes with orange color . In cells from HIVþ/CANþ individuals, a number of genes showed decreased expression compared to HIV-/CAN- . HIV infection in the context of cannabis, revealed by the comparison of HIVþ/CANþ and HIV-/CANþ , was characterized by stronger upregulation of genes, but also several genes with decreased expression. The effects of cannabis in the context of HIV measured by the ratio between HIVþ/CANþ and HIVþ/CAN-, were characterized by a higher number of down regulated genes, and a more modest upregulation, as suggested by overall lighter orange shades. A complete list of the genes in this network and T ratio in indicated comparisons can be found in Supplementary Materials 1. Pathway-based interactions were subdivided for identification of embedded functional annotations impacted by HIV and/or cannabis, identified by DAVID Bioinformatics Resources with a gene list input. Individual functional annotations were then assembled in GeneMania for visualization of effects. A complete list of significant pathways and functional annotations can be found in Supplementary Materials 1. The pathways selected for visualization were curated based on the expression of inflammatory genes, significance to neurological disorders in the context of HIV, viral infection, pathogenesis and networks with interventional value.
For instance, a gene network functionally annotated to viral host interactions was identified , where the ratio between HIVþ/CAN- and HIV-/CAN- indicated that HIV increased a number of genes annotated to that function. The ratio between HIV-/ CANþ and HIV-/CAN- , as well as between HIVþ/CANþ subjects were compared to HIV-/CANþ , indicated that both cannabis alone and HIV in the context of cannabis use increased a large number of genes in this cluster, but several genes were also decreased in both conditions, including the Ras homolog gene family GTPase RhoA, the Proteasome 20S Subunit Beta 8 , indoor hydroponics grow tent the intracellular cholesterol transporter , the E1A Binding Protein P300 and the histone deacetylase Sirtuin 1 . The ratio between HIVþ/CANþ and HIVþ/CAN- indicated that cannabis in the context of HIV was associated with a mild increase of genes in viral host interaction function , and a decrease in the general transcription factor IIB and the ubiquitin protein ligase 3A were characteristic of this comparison. Apoptosis was also identified as a relevant functional annotation , showing differential effects of HIV and/or cannabis. HIV alone decreased Caspase 7 CASP7, but increased CASP9 and the apoptosis regulator BCL2 . The effect of cannabis, on the other hand , indicated decrease in BCL2 . Likewise, HIV in the context of cannabis had a decrease in BCL2 . On the other hand, the ratio between HIVþ/CANþ and HIVþ/CAN- indicated that cannabis decreased or had mild effects on the expression of genes associated with apoptotic functions detectable in peripheral leukocytes . Neurodegeneration and inflammation were functional annotations identified in BIOCARTA. Given the large degree of overlap between these networks , we applied a merge network function in Cytoscape, which is shown in Fig. 7. The visualization of this gene network indicates that both HIV and cannabis increase genes with functions in neurodegeneration and inflammation , but cannabis decreased key contributors to the inflammatory process such as IL1b, TLR2, MyD88 and PARK7, as well as RASGRP1 . HIV infection in the context of cannabis indicated patterns that were similar to cannabis alone, with decreased expression in the same genes. Moreover, cannabis in the context of HIV elevated TLR2, TLR4 and MyD88, but had no or mild effects, or decreased a number of genes in this network .
Functional annotations associated with leukocyte-vascular adhesion and transmigration capacity were also sorted from pathway interactions. These functions were affected by HIV and cannabis.Yet cannabis lowered the expression of a large number of genes with cytoskeleton and signaling properties, including RHOA, AKT3, RAC1, BRAF and BCL2 . HIV in the context of cannabis had also lower MAPK1 and CTNNB1 compared to uninfected cannabis users . HIVþ cannabis users had a high number of genes that were lower or mildly changed compared to HIV non-cannabis users . Inflammation is highly regulated by a kinases. HIV and cannabis affected the expression of a number of kinases and genes involved in kinase regulation. The effects were differential and context-dependent. All the conditions showed decrease in CAMK4, in comparison to respective controls . HIV alone decreased mTOR, CSF1R, EPHA4, PDPK1 and DGKE . Cannabis alone, as well as HIV in the context of cannabis , decreased ATK3 and MAPKPK2. Cannabis alone decreased CALM1 . HIV in the context of cannabis decreased the expression of PGK1 and RAF1 . Cannabis in the context of HIV decreased several genes in this network that were either not modified or increased by the other conditions . These included MAP2K1, MAPK9, MAPK3, PRKCA and PDPK1 .Networks analyzed above have shown distinct effects of cannabis, which differed between cannabis alone and in the context of HIV. We used iRegulon to make predictions on transcription factors usage associated with these context-dependent patterns, in order to identify regulatory and co-regulatory elements. Fig. 11 shows the same gene network assembled based on pathway interactions in Fig. 3, but now reorganized based on the expression of transcription factor motifs in these genes’ promoters. The table legend in Fig. 11 shows the transcription factors mostly associated with the genes in the network.