Genomewide Study of Epigenetic Biomarkers of Opioid Dependence in European- American Women

Profiling neuronal methylome and hydroxymethylome of opioid use disorder in the human orbitofrontal cortex

Opioid use disorder (OUD) is influenced by genetic and environmental factors. While recent research suggests epigenetic disturbances in OUD, this is mostly limited to DNA methylation (5mC). DNA hydroxymethylation (5hmC) has been widely understudied. We conducted a multi-omics profiling of OUD in a male cohort, integrating neuronal-specific 5mC and 5hmC as well as gene expression profiles from human postmortem orbitofrontal cortex (OUD = 12; non-OUD = 26). Single locus methylomic analysis and co-methylation analysis showed a higher number of OUD-associated genes and gene networks for 5hmC compared to 5mC; these were enriched for GPCR, Wnt, neurogenesis, and opioid signaling. 5hmC marks also showed a higher correlation with gene expression patterns and enriched for GWAS of psychiatric traits. Drug interaction analysis revealed interactions with opioid-related drugs, some used as OUD treatments. Our multi-omics findings suggest an important role of 5hmC and reveal loci epigenetically dysregulated in OFC neurons of individuals with OUD.

Association between methylation in the promoter region of the GAD2 gene and opioid use disorder

DNA methylation is one of the epigenetic mechanisms involved in opioid use disorder. GAD2 is a key catalyticase in gamma amino butyric acid (GABA) synthesis from glutamate, that is implicated in opioid-induced rewarding effect. To reveal the relationship and the underlying mechanism between GAD2 gene methylation and opioid use disorder, we first examined and compared the methylation levels in the promoter region of the GAD2 gene in peripheral blood between 120 patients with opioid use disorder and 110 healthy controls by using a targeted approach. A diagnostic model with methylation biomarkers was established to distinguish opioid use disorder and healthy control groups. Correlations between methylation levels in the promoter region of the GAD2 gene and the duration and dosage of opioid use were then determined. Finally, the transcription factors that potentially bind to the target sequences including the detected CpG sites were predicted with the JASPAR database. Our results demonstrated that hypermethylation in the promoter region of the GAD2 gene was associated with opioid use disorder. A diagnostic model based on 10 methylation biomarkers could distinguish the opioid use disorder and healthy control groups. Several correlations between methylation levels in the GAD2 gene promoter and the duration and dosage of opioid use were observed. Transcription factors TFAP2A, Arnt and Runx1 were predicted to bind to the target sequences including several CpG sites detected in the present study in the GAD2 gene promoter. Our findings highlight and extend the role of DNA methylation in the GAD2 gene in opioid use disorder.

Genetic and epigenetic studies of opioid abuse disorder - the potential for future diagnostics

INTRODUCTION

Opioid use disorder (OUD) is a global problem that often begins with prescribed medications. The available treatment and maintenance plans offer solutions for the consumption rate by individuals leaving the outstanding problem of relapse, which is a major factor hindering the long-term efficacy of treatments.

AREAS COVERED

Understanding the neurobiology of addiction and relapse would help identifying the core causes of relapse and distinguish vulnerable from resilient individuals, which would lead to more targeted and effective treatment and provide diagnostics to screen individuals who have a propensity to OUD. In this review, we cover the neurobiology of the reward system highlighting the role of multiple brain regions and opioid receptors in the development of the disorder. We also review the current knowledge of the epigenetics of addiction and the available screening tools for aberrant use of opioids.

EXPERT OPINION

Relapse remains an anticipated limitation in the way of recovery even after long period of abstinence. This highlights the need for diagnostic tools that identify vulnerable patients and prevent the cycle of addiction. Finally, we discuss the limitations of the available screening tools and propose possible solutions for the discovery of addiction diagnostics.

Decoding the role of transcriptomic clocks in the human prefrontal cortex

Aging is a complex process with interindividual variability, which can be measured by aging biological clocks. Aging clocks are machine-learning algorithms guided by biological information and associated with mortality risk and a wide range of health outcomes. One of these aging clocks are transcriptomic clocks, which uses gene expression data to predict biological age; however, their functional role is unknown. Here, we profiled two transcriptomic clocks (RNAAgeCalc and knowledge-based deep neural network clock) in a large dataset of human postmortem prefrontal cortex (PFC) samples. We identified that deep-learning transcriptomic clock outperforms RNAAgeCalc to predict transcriptomic age in the human PFC. We identified associations of transcriptomic clocks with psychiatric-related traits. Further, we applied system biology algorithms to identify common gene networks among both clocks and performed pathways enrichment analyses to assess its functionality and prioritize genes involved in the aging processes. Identified gene networks showed enrichment for diseases of signal transduction by growth factor receptors and second messenger pathways. We also observed enrichment of genome-wide signals of mental and physical health outcomes and identified genes previously associated with human brain aging. Our findings suggest a link between transcriptomic aging and health disorders, including psychiatric traits. Further, it reveals functional genes within the human PFC that may play an important role in aging and health risk.

Native doublet microtubules from Tetrahymena thermophila reveal the importance of outer junction proteins

Cilia are ubiquitous eukaryotic organelles responsible for cellular motility and sensory functions. The ciliary axoneme is a microtubule-based cytoskeleton consisting of two central singlets and nine outer doublet microtubules. Cryo-electron microscopy-based studies have revealed a complex network inside the lumen of both tubules composed of microtubule-inner proteins (MIPs). However, the functions of most MIPs remain unknown. Here, we present single-particle cryo-EM-based analyses of the Tetrahymena thermophila native doublet microtubule and identify 42 MIPs. These data shed light on the evolutionarily conserved and diversified roles of MIPs. In addition, we identified MIPs potentially responsible for the assembly and stability of the doublet outer junction. Knockout of the evolutionarily conserved outer junction component CFAP77 moderately diminishes Tetrahymena swimming speed and beat frequency, indicating the important role of CFAP77 and outer junction stability in cilia beating generation and/or regulation.

Within subject cross-tissue analyzes of epigenetic clocks in substance use disorder postmortem brain and blood

There is a possible accelerated biological aging in patients with substance use disorders (SUD). The evaluation of epigenetic clocks, which are accurate estimators of biological aging based on DNA methylation changes, has been limited to blood tissue in patients with SUD. Consequently, the impact of biological aging in the brain of individuals with SUD remains unknown. In this study, we evaluated multiple epigenetic clocks (DNAmAge, DNAmAgeHannum, DNAmAgeSkinBlood, DNAmPhenoAge, DNAmGrimAge, and DNAmTL) in individuals with SUD (n = 42), including alcohol (n = 10), opioid (n = 19), and stimulant use disorder (n = 13), and controls (n = 10) in postmortem brain (prefrontal cortex) and blood tissue obtained from the same individuals. We found a higher DNAmPhenoAge (β = 0.191, p-value = 0.0104) and a nominally lower DNAmTL (β = -0.149, p-value = 0.0603) in blood from individuals with SUD compared to controls. SUD subgroup analysis showed a nominally lower brain DNAmTL in subjects with alcohol use disorder, compared to stimulant use disorder and controls (β = 0.0150, p-value = 0.087). Cross-tissue analyzes indicated a lower blood DNAmTL and a higher blood DNAmAge compared to their respective brain values in the SUD group. This study highlights the relevance of tissue specificity in biological aging studies and suggests that peripheral measures of epigenetic clocks in SUD may depend on the specific type of drug used.

Opioid medication use and blood DNA methylation: epigenome-wide association meta-analysis

Aim: To identify differential methylation related to prescribed opioid use. Methods: This study examined whether blood DNA methylation, measured using Illumina arrays, differs by recent opioid medication use in four population-based cohorts. We meta-analyzed results (282 users; 10,560 nonusers) using inverse-variance weighting. Results: Differential methylation (false discovery rate <0.05) was observed at six CpGs annotated to the following genes: KIAA0226, CPLX2, TDRP, RNF38, TTC23 and GPR179. Integrative epigenomic analyses linked implicated loci to regulatory elements in blood and/or brain. Additionally, 74 CpGs were differentially methylated in males or females. Methylation at significant CpGs correlated with gene expression in blood and/or brain. Conclusion: This study identified DNA methylation related to opioid medication use in general populations. The results could inform the development of blood methylation biomarkers of opioid use.

Effect of Prenatal Opioid Exposure on the Human Placental Methylome

Prenatal exposure to addictive drugs can lead to placental epigenetic modifications, but a methylome-wide evaluation of placental DNA methylation changes after prenatal opioid exposure has not yet been performed. Placental tissue samples were collected at delivery from 19 opioid-exposed and 20 unexposed control full-term pregnancies. Placental DNA methylomes were profiled using the Illumina Infinium HumanMethylationEPIC BeadChip. Differentially methylated CpG sites associated with opioid exposure were identified with a linear model using the ‘limma’ R package. To identify differentially methylated regions (DMRs) spanning multiple CpG sites, the ‘DMRcate’ R package was used. The functions of genes mapped by differentially methylated CpG sites and DMRs were further annotated using Enrichr. Differentially methylated CpGs (n = 684, unadjusted p < 0.005 and |∆β| ≥ 0.05) were mapped to 258 genes (including PLD1, MGAM, and ALCS2). Differentially methylated regions (n = 199) were located in 174 genes (including KCNMA1). Enrichment analysis of the top differentially methylated CpG sites and regions indicated disrupted epigenetic regulation of genes involved in synaptic structure, chemical synaptic transmission, and nervous system development. Our findings imply that placental epigenetic changes due to prenatal opioid exposure could result in placental dysfunction, leading to abnormal fetal brain development and the symptoms of opioid withdrawal in neonates.

CpH methylome analysis in human cortical neurons identifies novel gene pathways and drug targets for opioid use disorder

INTRODUCTION

DNA methylation (DNAm), an epigenetic mechanism, has been associated with opioid use disorder (OUD) in preclinical and human studies. However, most of the studies have focused on DNAm at CpG sites. DNAm at non-CpG sites (mCpHs, where H indicates A, T, or C) has been recently shown to have a role in gene regulation and to be highly abundant in neurons. However, its role in OUD is unknown. This work aims to evaluate mCpHs in the human postmortem orbital frontal cortex (OFC) in the context of OUD.

METHODS

A total of 38 Postmortem OFC samples were obtained from the VA Brain Bank (OUD = 12; Control = 26). mCpHs were assessed using reduced representation oxidative bisulfite sequencing in neuronal nuclei. Differential analysis was performed using the "methylkit" R package. Age, ancestry, postmortem interval, PTSD, and smoking status were included as covariates. Significant mCpHs were set at q-value < 0.05. Gene Ontology (GO) and KEGG enrichment analyses were performed for the annotated genes of all differential mCpH loci using String, ShinyGO, and amiGO software. Further, all annotated genes were analyzed using the Drug gene interaction database (DGIdb).

RESULTS

A total of 2,352 differentially methylated genome-wide significant mCpHs were identified in OUD, mapping to 2,081 genes. GO analysis of genes with differential mCpH loci showed enrichment for nervous system development (p-value = 2.32E-19). KEGG enrichment analysis identified axon guidance and glutamatergic synapse (FDR 9E-4-2.1E-2). Drug interaction analysis found 3,420 interactions between the annotated genes and drugs, identifying interactions with 15 opioid-related drugs, including lofexidine and tizanidine, both previously used for the treatment of OUD-related symptoms.

CONCLUSION

Our findings suggest a role of mCpHs for OUD in cortical neurons and reveal important biological pathways and drug targets associated with the disorder.

Genetics of substance use disorders in the era of big data

Substance use disorders (SUDs) are conditions in which the use of legal or illegal substances, such as nicotine, alcohol or opioids, results in clinical and functional impairment. SUDs and, more generally, substance use are genetically complex traits that are enormously costly on an individual and societal basis. The past few years have seen remarkable progress in our understanding of the genetics, and therefore the biology, of substance use and abuse. Various studies - including of well-defined phenotypes in deeply phenotyped samples, as well as broadly defined phenotypes in meta-analysis and biobank samples - have revealed multiple risk loci for these common traits. A key emerging insight from this work establishes a biological and genetic distinction between quantity and/or frequency measures of substance use (which may involve low levels of use without dependence), versus symptoms related to physical dependence.

Epigenome-wide study of brain DNA methylation following acute opioid intoxication

BACKGROUND

Opioid abuse poses significant risk to individuals in the United States and epigenetic changes are a leading potential biomarker of opioid abuse. Current evidence, however, is mostly limited to candidate gene analysis in whole blood. To clarify the association between opioid abuse and DNA methylation, we conducted an epigenome-wide analysis of DNA methylation in brain samples of individuals who died from acute opioid intoxication and group-matched controls.

METHODS

Tissue samples were extracted from the dorsolateral prefrontal cortex of 153 deceased individuals (Mage = 35.42; 62 % male; 77 % European ancestry). The study included 72 opioid samples, 53 psychiatric controls, and 28 normal controls. The epigenome-wide analysis was implemented using the Illumina MethylationEPIC BeadChip; analyses adjusted for sociodemographic characteristics, negative control principal components, ancestry principal components, cellular composition, and surrogate variables. Horvath's epigenetic age and Levine's PhenoAge were calculated, and gene set enrichment analyses were performed.

RESULTS

Although no CpG sites survived false-discovery rate correction for multiple testing, 13 sites surpassed a relaxed significance threshold (p < 1.0 × 10-5). One of these sites was located within Netrin-1, a gene implicated in kappa opioid receptor activity. There was an association between opioid use and accelerated PhenoAge (b = 2.24, se = 1.11, p = .045). Gene set enrichment analyses revealed enrichment of differential methylation in GO and KEGG pathways broadly related to substance use.

CONCLUSIONS

Netrin-1 may be associated with opioid overdose, and future research with larger samples across stages of opioid use will elucidate the complex genomics of opioid abuse.

Global DNA methylation levels in white blood cells of patients with chronic heroin use disorder. A prospective study

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Opioid abstinence for 21 days does not affect global DNA methylation levels in white blood cells.

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All participants in the study completed a 21-day “dry” detoxification program.

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Findings do not rule out the possibility of site-specific methylation changes.

Background

Increasing scientific evidence shows the significant role of epigenetic mechanisms in drug use disorder, abstinence and relapse. Studies on human subjects are limited compared to those on animals, for various reasons such as poly-substance abuse, high drop-out rate and technical difficulties.

Objectives

Our goal was to evaluate whether a monitored abstinence period of 21 days could induce changes in global DNA methylation in chronic heroin users.

Method

In the current study, we present data on global DNA methylation on a set of 18 male patients with chronic heroin use disorder, carefully selected based on inclusion and exclusion criteria, who were hospitalized and closely monitored during a 21-day detoxification program, one of the few where no opioid agonist is administered. The participants were sampled twice, once upon enrolment to the program and once upon completion.

Results

According to our results, no difference in global DNA methylation was detected between samples collected upon enrolment and samples collected upon completion of the program.

Conclusion

The findings of this study do not rule out the possibility that the 21-day abstinence period was not long enough to observe changes in global DNA methylation, or that abstinence induced site-specific methylation changes (but not global changes), that certainly merit further evaluation.

Identifying factors associated with opioid cessation in a biracial sample using machine learning

Aim

Racial disparities in opioid use disorder (OUD) management exist, however, and there is limited research on factors that influence opioid cessation in different population groups.

Methods

We employed multiple machine learning prediction algorithms least absolute shrinkage and selection operator, random forest, deep neural network, and support vector machine to assess factors associated with ceasing opioid use in a sample of 1,192 African Americans (AAs) and 2,557 individuals of European ancestry (EAs) who met Diagnostic and Statistical Manual of Mental Disorders, 5th Edition criteria for OUD. Values for nearly 4,000 variables reflecting demographics, alcohol and other drug use, general health, non-drug use behaviors, and diagnoses for other psychiatric disorders, were obtained for each participant from the Semi-Structured Assessment for Drug Dependence and Alcoholism, a detailed semi-structured interview.

Results

Support vector machine models performed marginally better on average than other machine learning methods with maximum prediction accuracies of 75.4% in AAs and 79.4% in EAs. Subsequent stepwise regression considered the 83 most highly ranked variables across all methods and models and identified less recent cocaine use (AAs: odds ratio (OR) = 1.82, P = 9.19 × 10^-5; EAs: OR = 1.91, P = 3.30 × 10^-15), shorter duration of opioid use (AAs: OR = 0.55, P = 5.78 × 10^-6; EAs: OR = 0.69, P = 3.01 × 10^-7), and older age (AAs: OR = 2.44, P = 1.41 × 10^-12; EAs: OR = 2.00, P = 5.74 × 10^-9) as the strongest independent predictors of opioid cessation in both AAs and EAs. Attending self-help groups for OUD was also an independent predictor (P < 0.05) in both population groups, while less gambling severity (OR = 0.80, P = 3.32 × 10^-2) was specific to AAs and post-traumatic stress disorder recovery (OR = 1.93, P = 7.88 × 10^-5), recent antisocial behaviors (OR = 0.64, P = 2.69 × 10^-3), and atheism (OR = 1.45, P = 1.34 × 10^-2) were specific to EAs. Factors related to drug use comprised about half of the significant independent predictors in both AAs and EAs, with other predictors related to non-drug use behaviors, psychiatric disorders, overall health, and demographics.

Conclusions

These proof-of-concept findings provide avenues for hypothesis-driven analysis, and will lead to further research on strategies to improve OUD management in EAs and AAs.

Biomarkers to predict staging and treatment response in opioid dependence: A narrative review

Opioid use disorder is a devastating disorder with a high burden in terms of overdose mortality, with an urgent need for more personalized prevention or therapeutic interventions. For this purpose, the description and validation of biological measures of staging or treatment response is a highly active research field. We conducted a narrative review on the pathophysiology of opioid use disorder to propose staging of the disease and search for research studies proposing or demonstrating the predictive value of biomarkers. We propose a IV stage description of opioid use disorder, from (I) vulnerability stage to (II) disease progression, (III) constituted opioid dependence and were several type of treatments can be applied, to the reach a (IV) modified health state. We classified biomarkers studies according to the stage of the disorder they were intended to predict, and to the three categories of methods they used: anatomical and functional aspects of the brain, genetic/transcriptomic/epigenetic studies, and lastly biomarkers of systemic modifications associated with opioid use disorder, especially regarding the immune system. Most studies predicting Stage III that we reviewed collected data from small samples sizes and were cross-sectional association studies comparing opioid dependent patients and control groups. Pharmacogenetic biomarkers are proposed to predict treatment response. Future research should now emphasize prospective studies, replication in independent samples, and predictive value calculation of each biomarker. The most promising results are multimodal evaluations to be able to measure the state of the brain reward system in living individuals.

The Genomics of Opioid Addiction Longitudinal Study (GOALS): study design for a prospective evaluation of genetic and non-genetic factors for development of and recovery from opioid use disorder

BACKGROUND

The opioid use disorder and overdose crisis in the United States affects public health as well as social and economic welfare. While several genetic and non-genetic risk factors for opioid use disorder have been identified, many of the genetic associations have not been independently replicated, and it is not well understood how these factors interact. This study is designed to evaluate relationships among these factors prospectively to develop future interventions to help prevent or treat opioid use disorder.

METHODS

The Genomics of Opioid Addiction Longitudinal Study (GOALS) is a prospective observational study assessing the interplay of genetic and non-genetic by collecting comprehensive genetic and non-genetic information on 400 participants receiving medication for opioid use disorder. Participants will be assessed at four time points over 1 year. A saliva sample will be collected for large-scale genetic data analyses. Non-genetic assessments include validated surveys measuring addiction severity, depression, anxiety, and adverse childhood experiences, as well as treatment outcomes such as urine toxicology results, visit frequency, and number of pre and post-treatment overdoses extracted from electronic medical records.

DISCUSSION

We will use these complex data to investigate the relative contributions of genetic and non-genetic risk factors to opioid use disorder and related treatment outcomes.

Modeling SARS-CoV-2 infection in individuals with opioid use disorder with brain organoids

The COVID-19 pandemic has aggravated a preexisting epidemic: the opioid crisis. Much literature has shown that the circumstances imposed by COVID-19, such as social distancing regulations, medical and financial instability, and increased mental health issues, have been detrimental to those with opioid use disorder (OUD). In addition, unexpected neurological sequelae in COVID-19 patients suggest that COVID-19 compromises neuroimmunity, induces hypoxia, and causes respiratory depression, provoking similar effects as those caused by opioid exposure. Combined conditions of COVID-19 and OUD could lead to exacerbated complications. With limited human in vivo options to study these complications, we suggest that iPSC-derived brain organoid models may serve as a useful platform to investigate the physiological connection between COVID-19 and OUD. This mini-review highlights the advances of brain organoids in other neuropsychiatric and infectious diseases and suggests their potential utility for investigating OUD and COVID-19, respectively.

Exposure to drugs of abuse induce effects that persist across generations

Substance use disorders are highly prevalent and continue to be one of the leading causes of disability in the world. Notably, not all people who use addictive drugs develop a substance use disorder. Although substance use disorders are highly heritable, patterns of inheritance cannot be explained purely by Mendelian genetic mechanisms. Vulnerability to developing drug addiction depends on the interplay between genetics and environment. Additionally, evidence from the past decade has pointed to the role of epigenetic inheritance in drug addiction. This emerging field focuses on how environmental perturbations, including exposure to addictive drugs, induce epigenetic modifications that are transmitted to the embryo at fertilization and modify developmental gene expression programs to ultimately impact subsequent generations. This chapter highlights intergenerational and transgenerational phenotypes in offspring following a history of parental drug exposure. Special attention is paid to parental preconception exposure studies of five drugs of abuse (alcohol, cocaine, nicotine, cannabinoids, and opiates) and associated behavioral and physiological outcomes in offspring. The highlighted studies demonstrate that parental exposure to drugs of abuse has enduring effects that persist into subsequent generations. Understanding the contribution of epigenetic inheritance in drug addiction may provide clues for better treatments and therapies for substance use disorders.

Genetic variation regulates opioid-induced respiratory depression in mice

In the U.S., opioid prescription for treatment of pain nearly quadrupled from 1999 to 2014. The diversion and misuse of prescription opioids along with increased use of drugs like heroin and fentanyl, has led to an epidemic in addiction and overdose deaths. The most common cause of opioid overdose and death is opioid-induced respiratory depression (OIRD), a life-threatening depression in respiratory rate thought to be caused by stimulation of opioid receptors in the inspiratory-generating regions of the brain. Studies in mice have revealed that variation in opiate lethality is associated with strain differences, suggesting that sensitivity to OIRD is genetically determined. We first tested the hypothesis that genetic variation in inbred strains of mice influences the innate variability in opioid-induced responses in respiratory depression, recovery time and survival time. Using the founders of the advanced, high-diversity mouse population, the Diversity Outbred (DO), we found substantial sex and genetic effects on respiratory sensitivity and opiate lethality. We used DO mice treated with morphine to map quantitative trait loci for respiratory depression, recovery time and survival time. Trait mapping and integrative functional genomic analysis in GeneWeaver has allowed us to implicate Galnt11, an N-acetylgalactosaminyltransferase, as a gene that regulates OIRD.

Effect of short-term prescription opioids on DNA methylation of the OPRM1 promoter

Background

A long-term opioid use has been associated with hypermethylation of the opioid receptor mu 1 (OPRM1) promoter. Very little is currently known about the early epigenetic response to therapeutic opioids. Here, we examine whether we can detect DNA methylation changes associated with a few days’ use of prescribed opioids. Genome-wide DNA methylation was assayed in a cohort of 33 opioid-naïve participants who underwent standard dental surgery followed by opioid self-administration. Saliva samples were collected before surgery (visit 1), and at two postsurgery visits at 2.7 ± 1.5 days (visit 2), and 39 ± 10 days (visit 3) after the discontinuation of opioid analgesics.

Results

The perioperative methylome underwent significant changes over the three visits that were primarily due to postoperative inflammatory response and cell heterogeneity. To specifically examine the effect of opioids, we started with a candidate gene approach and evaluated 10 CpGs located in the OPRM1 promoter. There was a significant cross-sectional variability in opioid use, and for participants who self-administered the prescribed drugs, the total dosage ranged from 5–210 morphine milligram equivalent (MME). Participants were categorized by cumulative dosage into three groups: < 25 MME, 25–90 MME, and ≥ 90 MME. Using mixed-effects modeling, 4 CpGs had significant positive associations with opioid dose at two-tailed p value < 0.05, and overall, 9 of the 10 OPRM1 promoter CpGs showed the predicted higher methylation in the higher dose groups relative to the lowest dose group. After adjustment for age, cellular heterogeneity, and past tobacco use, the promoter mean methylation also had positive associations with cumulative MME (regression coefficient = 0.0002, one-tailed p value = 0.02) and duration of opioid use (regression coefficient = 0.003, one-tailed p value = 0.001), but this effect was significant only for visit 3. A preliminary epigenome-wide association study identified a significant CpG in the promoter of the RAS-related signaling gene, RASL10A, that may be predictive of opioid dosage.

Conclusion

The present study provides evidence that the hypermethylation of the OPRM1 promoter is in response to opioid use and that epigenetic differences in OPRM1 and other sites are associated with a short-term use of therapeutic opioids.

Evaluating the Correlations Between Osteoporosis and Lifestyle-Related Factors Using Transcriptome-Wide Association Study

Osteoporosis (OP) is a multi-factorial bone disease influenced by genetic factors, age, and lifestyles. The aim of this study is to evaluate the genetic correlations between OP and multiple lifestyle-related factors, and explore the genes underlying the detected genetic correlations. Linkage disequilibrium score regression (LDSC) analysis was applied to evaluate the genetic correlations of total body bone mineral density (TB-BMD) of different ages (including 15-30 years, 30-45 years, 45-60 years, and over 60 years) with four common lifestyle/environment-related factors (including serum 25-hydroxyvitamin D, cigarette smoking, alcohol dependence, and caffeine metabolites). Transcriptome-wide association studies (TWAS) of TB-BMD (30-45 years) and smoking were conducted in peripheral blood (PB), whole blood (WB), and adipose tissues. The identified candidate genes were also subjected to gene set enrichment analysis (GSEA). Genetic correlation was only observed between TB-BMD (30-45 years) and cigarette smoking status (P = 0.01, LD score = 0.11 ± 0.04). No significant genetic correlation was detected for other lifestyle/environmental factors, including serum 25-hydroxyvitamin D, alcohol dependence, and caffeine metabolites for TB-BMD within all of the four age groups. TWAS identified 85 genes in PB and 163 genes in WB for TB-BMD, as well as 123 genes in PB and 257 genes in WB for smoking. Multiple common candidate genes shared by both TB-BMD and smoking were detected, such as MAP1LC3B (P_TB-BMD-PB = 1.00 × 10^-3, P_smoking-PB = 9.62 × 10^-3, P_TB-BMD-WB = 2.99 × 10^-2) and SLC23A3 (P_TB-BMD-WB = 1.48 × 10^-2, P_smoking-WB = 8.76 × 10^-3). GSEA detected one GO terms for TB-BMD (cytosol) in WB, one GO term for smoking (mitochondrion) in PB, and one pathway (oocyte meiosis) for smoking in WB.