Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex.

Background: Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms underlying the development and progression of AUD remain limited. Here, we interrogate AUD-associated DNA methylation (DNAm) changes within and across addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC). Methods: Illumina HumanMethylation EPIC array data from 119 decedents of European ancestry (61 cases, 58 controls) were analyzed using robust linear regression, with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public gene regulatory data and published genetic and epigenetic studies. We additionally tested for brain region-shared and -specific associations using mixed effects modeling and assessed implications of these results using public gene expression data. Results: At a false discovery rate ≤ 0.05, we identified 53 CpGs significantly associated with AUD status for NAc and 31 CpGs for DLPFC. In a meta-analysis across the regions, we identified an additional 21 CpGs associated with AUD, for a total of 105 unique AUD-associated CpGs (120 genes). AUD-associated CpGs were enriched in histone marks that tag active promoters and our strongest signals were specific to a single brain region. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors; all others represent novel associations. Conclusions: Our findings identify AUD-associated methylation signals, the majority of which are specific within NAc or DLPFC. Some signals may constitute predisposing genetic and epigenetic variation, though more work is needed to further disentangle the neurobiological gene regulatory differences associated with AUD.

Investigating the Relationship Between Smoking Behavior and Global Brain Volume.

Background: Previous studies have shown that brain volume is negatively associated with cigarette smoking, but there is an ongoing debate about whether smoking causes lowered brain volume or a lower brain volume is a risk factor for smoking. We address this debate through multiple methods that evaluate directionality: Bradford Hill's criteria, which are commonly used to understand a causal relationship in epidemiological studies, and mediation analysis. Methods: In 32,094 participants of European descent from the UK Biobank dataset, we examined the relationship between a history of daily smoking and brain volumes, as well as an association of genetic risk score to ever smoking with brain volume. Results: A history of daily smoking was strongly associated with decreased brain volume, and a history of heavier smoking was associated with a greater decrease in brain volume. The strongest association was between total gray matter volume and a history of daily smoking (effect size = -2964 mm3, p = 2.04 × 10-16), and there was a dose-response relationship with more pack years smoked associated with a greater decrease in brain volume. A polygenic risk score for smoking initiation was strongly associated with a history of daily smoking (effect size = 0.05, p = 4.20 × 10-84), but only modestly associated with total gray matter volume (effect size = -424 mm3, p = .01). Mediation analysis indicated that a history of daily smoking mediated the relationship between the smoking initiation polygenic risk score and total gray matter volume. Conclusions: A history of daily smoking is strongly associated with a decreased total brain volume.

Evaluating 17 methods incorporating biological function with GWAS summary statistics to accelerate discovery demonstrates a tradeoff between high sensitivity and high positive predictive value.

Where sufficiently large genome-wide association study (GWAS) samples are not currently available or feasible, methods that leverage increasing knowledge of the biological function of variants may illuminate discoveries without increasing sample size. We comprehensively evaluated 17 functional weighting methods for identifying novel associations. We assessed the performance of these methods using published results from multiple GWAS waves across each of five complex traits. Although no method achieved both high sensitivity and positive predictive value (PPV) for any trait, a subset of methods utilizing pleiotropy and expression quantitative trait loci nominated variants with high PPV (>75%) for multiple traits. Application of functionally weighting methods to enhance GWAS power for locus discovery is unlikely to circumvent the need for larger sample sizes in truly underpowered GWAS, but these results suggest that applying functional weighting to GWAS can accurately nominate additional novel loci from available samples for follow-up studies.

Trans-ancestry epigenome-wide association meta-analysis of DNA methylation with lifetime cannabis use.

Cannabis is widely used worldwide, yet its links to health outcomes are not fully understood. DNA methylation can serve as a mediator to link environmental exposures to health outcomes. We conducted an epigenome-wide association study (EWAS) of peripheral blood-based DNA methylation and lifetime cannabis use (ever vs. never) in a meta-analysis including 9436 participants (7795 European and 1641 African ancestry) from seven cohorts. Accounting for effects of cigarette smoking, our trans-ancestry EWAS meta-analysis revealed four CpG sites significantly associated with lifetime cannabis use at a false discovery rate of 0.05 [Formula: see text]: cg22572071 near gene ADGRF1, cg15280358 in ADAM12, cg00813162 in ACTN1, and cg01101459 near LINC01132. Additionally, our EWAS analysis in participants who never smoked cigarettes identified another epigenome-wide significant CpG site, cg14237301 annotated to APOBR. We used a leave-one-out approach to evaluate methylation scores constructed as a weighted sum of the significant CpGs. The best model can explain 3.79% of the variance in lifetime cannabis use. These findings unravel the DNA methylation changes associated with lifetime cannabis use that are independent of cigarette smoking and may serve as a starting point for further research on the mechanisms through which cannabis exposure impacts health outcomes.

COVID-19 pandemic stressors are associated with reported increases in frequency of drunkenness among individuals with a history of alcohol use disorder.

Some sources report increases in alcohol use have been observed since the start of the COVID-19 pandemic, particularly among women. Cross-sectional studies suggest that specific COVID-19-related stressful experiences (e.g., social disconnection) may be driving such increases in the general population. Few studies have explored these topics among individuals with a history of Alcohol Use Disorders (AUD), an especially vulnerable population. Drawing on recent data collected by the Collaborative Study on the Genetics of Alcoholism (COGA; COVID-19 study N = 1651, 62% women, age range: 30-91) in conjunction with AUD history data collected on the sample since 1990, we investigated associations of COVID-19 related stressors and coping activities with changes in drunkenness frequency since the start of the pandemic. Analyses were conducted for those without a history of AUD (N: 645) and three groups of participants with a history of AUD prior to the start of the pandemic: (1) those experiencing AUD symptoms (N: 606), (2) those in remission who were drinking (N: 231), and (3) those in remission who were abstinent (had not consumed alcohol for 5+ years; N: 169). Gender-stratified models were also examined. Exploratory analyses examined the moderating effects of 'problematic alcohol use' polygenic risk scores (PRS) and neural connectivity (i.e., posterior interhemispheric alpha EEG coherence) on associations between COVID-19 stressors and coping activities with changes in the frequency of drunkenness. Increases in drunkenness frequency since the start of the pandemic were higher among those with a lifetime AUD diagnosis experiencing symptoms prior to the start of the pandemic (14% reported increased drunkenness) when compared to those without a history of AUD (5% reported increased drunkenness). 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, although only women experiencing pre-pandemic AUD symptoms reported significantly greater rates of increased drunkenness since the start of the pandemic compared to men in this group (17% of women vs. 5% of men). 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 (including those with AUD symptoms and those remitted from 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 decreased social interactions 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 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. Our results demonstrated that only individuals with pre-pandemic AUD symptoms reported greater increases in drunkenness frequency since the start of the COVID-19 pandemic compared to those without a lifetime history of AUD. This increase was more pronounced among women than men in this group. However, COVID-19-related stressors and coping activities were associated with changes in the frequency of drunkenness among all groups of participants with a prior history of AUD, including those experiencing AUD symptoms, as well as abstinent and non-abstinent participants in remission. Perceived stress, essential worker status, media consumption, social connections (especially for women), and relationship quality (especially for men) are specific areas of focus for designing intervention and prevention strategies aimed at reducing pandemic-related alcohol misuse among this particularly vulnerable group. Interestingly, these associations were not observed for individuals without a prior history of AUD, supporting prior literature that demonstrates that widespread stressors (e.g., pandemics, terrorist attacks) disproportionately impact the mental health and alcohol use of those with a prior history of problems.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci.

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWAS) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N=52) and nonsmokers (N=171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and using a two-stage multiple testing approach with eigenMT and Bonferroni corrections. We found >2 million significant meQTL variants (padj<0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects; five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTLs for 958 unique eGenes (padj<0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTIN1 and ITIH4 colocalized across all data types (GWAS + meQTL + eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Demographic differences in the cascade of care for unhealthy alcohol use: A cross-sectional analysis of data from the 2015-2019 National Survey on Drug Use and Health.

BACKGROUND: The screening, brief intervention, and referral to treatment (SBIRT) model is recommended by the U.S. Preventive Services Task Force to improve recognition of and intervention for unhealthy alcohol use. How SBIRT implementation differs by demographic characteristics is poorly understood. METHODS: We analyzed data from the 2015-2019 National Survey on Drug Use and Health from respondents ≥18 years old who used an outpatient clinic and had at least one alcoholic drink within the past year. Respondents were grouped into one of three mutually exclusive groups: "no binge drinking or alcohol use disorder (AUD)," "binge drinking without AUD," or "AUD." Outcome variables were likelihood of screening, brief intervention (BI), referral to treatment (RT), and AUD treatment. The demographic predictors on which outcomes were regressed included gender, age, race and ethnicity, sexual orientation, insurance status, and history of military involvement. Consistent with SBIRT guidelines, the entire sample was included in the screening model; screened persons with either binge drinking without AUD or with AUD were included in the BI model; screened persons with AUD were included in the RT model, and persons referred to treatment with AUD were included in the AUD treatment model. RESULTS: Analyses included 120,804 respondents. Women were more likely than men to be screened, but less likely to receive BI or RT. When referred to treatment, women were more likely than men to receive it. Persons aged ≥50 were least likely to be screened about alcohol, but most likely to receive BI, while persons aged 18-25 were least likely to receive BI or AUD treatment. Racial and ethnic minorities were less likely than White persons to be screened; Asians were less likely to receive RT, and Black persons were less likely to receive treatment than White persons. Persons identifying as gay, lesbian, or bisexual were equally as likely or more likely to receive SBIRT or AUD treatment as those identifying as heterosexual. Persons without insurance were less likely to be screened than those with insurance. Persons with a history of military involvement were more likely to be screened and receive BI and RT than persons who had not served in the military. CONCLUSIONS: Demographic disparities in SBIRT implementation exist. Addressing the sources of these disparities and minimizing attrition from care could improve outcomes for persons with unhealthy alcohol use.

Discovery of 95 PTSD loci provides insight into genetic architecture and neurobiology of trauma and stress-related disorders.

Posttraumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 novel). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (e.g., GRIA1, GRM8, CACNA1E ), developmental, axon guidance, and transcription factors (e.g., FOXP2, EFNA5, DCC ), synaptic structure and function genes (e.g., PCLO, NCAM1, PDE4B ), and endocrine or immune regulators (e.g., ESR1, TRAF3, TANK ). Additional top genes influence stress, immune, fear, and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

Leveraging Implementation Science in the Treatment of Tobacco Use Disorder.

The tobacco use disorder field has an armamentarium of approaches to help people quit smoking: medication-based treatment for tobacco use, digital therapeutics for just-intime behavioral interventions, genetic and metabolic biomarkers to guide tobacco treatment, to name a few. Whether the treatment approach is old or new, an underlying truth remains: the benefit is only as great as the extent to which these treatment approaches reach individuals who need them most and prove effective and feasible to implement in real-world settings. Further, certain treatments tend to be used more robustly in practice, namely, those that address a great need yet are low in cost, burden, and risk of clinical harms. This is where implementation science comes in, providing guidance on how best to get effective treatments adopted and used in clinical and community settings. Implementation science holds the keys to the uptake and routine use of evidence-based treatments and should be more fully leveraged in the tobacco use disorder field. At the same time, disruptive technologies in treatment are breaking new ground, pushing the field of implementation science to build a bigger "toolbox" of ways to improve access and quality of treatment in an ever-evolving landscape. In this paper, we underscore this synergy between tobacco treatment and implementation science. We spotlight emerging trends in tobacco use, effective and emerging treatment approaches for tobacco use, and ways that implementation science intersects with the current and evolving landscape of tobacco use and substance use disorder more broadly.

Genomic medicine to reduce tobacco and related disorders: Translation to precision prevention and treatment.

Genomic medicine can enhance prevention and treatment. First, we propose that advances in genomics have the potential to enhance assessment of disease risk, improve prognostic predictions, and guide treatment development and application. Clinical implementation of polygenic risk scores (PRSs) has emerged as an area of active research. The pathway from genomic discovery to implementation is an iterative process. Second, we provide examples on how genomic medicine has the potential to solve problems in prevention and treatment using two examples: Lung cancer screening and evidence-based tobacco treatment are both under-utilized and great opportunities for genomic interventions. Third, we discuss the translational process for developing genomic interventions from evidence to implementation by presenting a model to evaluate genomic evidence for clinical implementation, mechanisms of genomic interventions, and patient desire for genomic interventions. Fourth, we present potential challenges in genomic interventions including a great need for evidence in all diverse populations, little evidence on treatment algorithms, challenges in accommodating a dynamic evidence base, and implementation challenges in real world clinical settings. Finally, we conclude that research to identify genomic markers that are associated with smoking cessation success and the efficacy of smoking cessation treatments is needed to empower people of all diverse ancestry. Importantly, genomic data can be used to help identify patients with elevated risk for nicotine addiction, difficulty quitting smoking, favorable response to specific pharmacotherapy, and tobacco-related health problems.

The collaborative study on the genetics of alcoholism: Sample and clinical data.

The collaborative study on the genetics of alcoholism (COGA) is a multi-site, multidisciplinary project with the goal of identifying how genes are involved in alcohol use disorder and related outcomes, and characterizing how genetic risk unfolds across development and in conjunction with the environment and brain function. COGA is a multi-generational family-based study in which probands were recruited through alcohol treatment centers, along with a set of community comparison families. Nearly 18,000 individuals from >2200 families have been assessed over a period of over 30 years with a rich phenotypic battery that includes semi-structured psychiatric interviews and questionnaire measures, along with DNA collection and electrophysiological data on a large subset. Participants range in age from 7 to 97, with many having longitudinal assessments, providing a valuable opportunity to study alcohol use and problems across the lifespan. Here we provide an overview of data collection methods for the COGA sample, and details about sample characteristics and comorbidity. We also review key research findings that have emerged from analyses of the COGA data. COGA data are available broadly to researchers, and we hope this overview will encourage further collaboration and use of these data to advance the field.

Racial and Ethnic Inequities in Buprenorphine and Methadone Utilization Among Reproductive-Age Women with Opioid Use Disorder: an Analysis of Multi-state Medicaid Claims in the USA.

BACKGROUND: Associations between race/ethnicity and medications to treat OUD (MOUD), buprenorphine and methadone, in reproductive-age women have not been thoroughly studied in multi-state samples. OBJECTIVE: To evaluate racial/ethnic variation in buprenorphine and methadone receipt and retention in a multi-state U.S. sample of Medicaid-enrolled, reproductive-age women with opioid use disorder (OUD) at the beginning of OUD treatment. DESIGN: Retrospective cohort study. SUBJECTS: Reproductive-age (18-45 years) women with OUD, in the Merative™ MarketScan® Multi-State Medicaid Database (2011-2016). MAIN MEASURES: Differences by race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, "other" race/ethnicity) in the likelihood of receiving buprenorphine and methadone during the start of OUD treatment (yes/no) were estimated using multivariable logistic regression. Differences in time to medication discontinuation (days) by race/ethnicity were evaluated using multivariable Cox regression. RESULTS: Of 66,550 reproductive-age Medicaid enrollees with OUD (84.1% non-Hispanic White, 5.9% non-Hispanic Black, 1.0% Hispanic, 5.3% "other"), 15,313 (23.0%) received buprenorphine and 6290 (9.5%) methadone. Non-Hispanic Black enrollees were less likely to receive buprenorphine (adjusted odds ratio, aOR = 0.76 [0.68-0.84]) and more likely to be referred to methadone clinics (aOR = 1.78 [1.60-2.00]) compared to non-Hispanic White participants. Across both buprenorphine and methadone in unadjusted analyses, the median discontinuation time for non-Hispanic Black enrollees was 123 days compared to 132 days and 141 days for non-Hispanic White and Hispanic enrollees respectively (χ2 = 10.6; P = .01). In adjusted analyses, non-Hispanic Black enrollees experienced greater discontinuation for buprenorphine and methadone (adjusted hazard ratio, aHR = 1.16 [1.08-1.24] and aHR = 1.16 [1.07-1.30] respectively) compared to non-Hispanic White peers. We did not observe differences in buprenorphine or methadone receipt or retention for Hispanic enrollees compared to the non-Hispanic White enrollees. CONCLUSIONS: Our data illustrate inequities between non-Hispanic Black and non-Hispanic White Medicaid enrollees with regard to buprenorphine and methadone utilization in the USA, consistent with literature on the racialized origins of methadone and buprenorphine treatment.

Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features.

Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (the memory group) were compared with a matched control group who did not have memory problems. The random forests model identified specific features from each domain that contributed to the classification of the memory group vs. the control group (AUC = 88.29%). Specifically, individuals from the memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except for some connections involving the anterior cingulate cortex, which were predominantly hypoconnected. Other significant contributing features were: (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past five years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past twelve months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive "uplift" life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity data collected ~18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict the alcohol-related memory problems that arise in later life.

Benzodiazepine, Z-drug, and sleep medication prescriptions in male and female people with opioid use disorder on buprenorphine and comorbid insomnia: an analysis of multistate insurance claims.

STUDY OBJECTIVES: In adult populations, women are more likely than men to be prescribed benzodiazepines. However, such disparities have not been investigated in people with opioid use disorder (OUD) and insomnia receiving buprenorphine, a population with particularly high sedative/hypnotic receipt. This retrospective cohort study used administrative claims data from Merative MarketScan Commercial and MultiState Medicaid Databases (2006-2016) to investigate sex differences in the receipt of insomnia medication prescriptions among patients in OUD treatment with buprenorphine. METHODS: We included people aged 12-64 years with diagnoses of insomnia and OUD-initiating buprenorphine during the study timeframe. The predictor variable was sex (female versus male). The primary outcome was receipt of insomnia medication prescription within 60 days of buprenorphine start, encompassing benzodiazepines, Z-drugs, or non-sedative/hypnotic insomnia medications (e.g. hydroxyzine, trazodone, and mirtazapine). Associations between sex and benzodiazepine, Z-drug, and other insomnia medication prescription receipt were estimated using Poisson regression models. RESULTS: Our sample included 9510 individuals (female n = 4637; male n = 4873) initiating buprenorphine for OUD who also had insomnia, of whom 6569 (69.1%) received benzodiazepines, 3891 (40.9%) Z-drugs, and 8441 (88.8%) non-sedative/hypnotic medications. Poisson regression models, adjusting for sex differences in psychiatric comorbidities, found female sex to be associated with a slightly increased likelihood of prescription receipt: benzodiazepines (risk ratio [RR], RR = 1.17 [1.11-1.23]), Z-drugs (RR = 1.26 [1.18-1.34]), and non-sedative/hypnotic insomnia medication (RR = 1.07, [1.02-1.12]). CONCLUSIONS: Sleep medications are commonly being prescribed to individuals with insomnia in OUD treatment with buprenorphine, with sex-based disparities indicating a higher prescribing impact among female than male OUD treatment patients.

Initiation and Treatment Discontinuation of Medications for Opioid Use Disorder in Pregnant People Compared With Nonpregnant People.

OBJECTIVE: To examine the association between pregnancy and medications for opioid use disorder (MOUD) initiation and discontinuation among reproductive-aged people receiving treatment for opioid use disorder (OUD) in the United States. METHODS: We conducted a retrospective cohort study of people with gender recorded as female, aged 18-45 years, in the Merative TM MarketScan ® Commercial and Multi-State Medicaid Databases (2006-2016). Opioid use disorder and pregnancy status were identified based on inpatient or outpatient claims for established International Classification of Diseases, Ninth and Tenth Revision diagnosis and procedure codes. The main outcomes were buprenorphine and methadone initiation and discontinuation, determined by using pharmacy and outpatient procedure claims. Analyses were conducted at the treatment episode level. Adjusting for insurance status, age, and co-occurring psychiatric and substance use disorders, we used logistic regression to estimate MOUD initiation and used Cox regression to estimate MOUD discontinuation. RESULTS: Our sample included 101,772 reproductive-aged people with OUD, encompassing 155,771 treatment episodes (mean age 30.8 years, 64.4% Medicaid insurance, 84.1% White), of whom 2,687 (3.2%, encompassing 3,325 episodes) were pregnant. In the pregnant group, 51.2% of treatment episodes (1,703/3,325) involved psychosocial treatment without MOUD, in comparison with 61.1% (93,156/152,446) in the nonpregnant comparator group. In adjusted analyses assessing likelihood of initiation for individual MOUD, pregnancy status was associated with an increase in buprenorphine (adjusted odds ratio [aOR] 1.57, 95% CI 1.44-1.70) and methadone initiation (aOR 2.04, 95% CI 1.82-2.27). Discontinuation rates of MOUD at 270 days were high for both buprenorphine (72.4% for nonpregnant episodes vs 59.9% for pregnant episodes) and methadone (65.7% for nonpregnant episodes vs 54.1% for pregnant episodes). Pregnancy was associated with a decreased likelihood of discontinuation at 270 days for both buprenorphine (adjusted hazard ratio [aHR] 0.71, 95% CI 0.67-0.76) and methadone (aHR 0.68, 95% CI 0.61-0.75), in comparison with nonpregnant status. CONCLUSION: Although a minority of reproductive-aged people with OUD in the United States are initiated on MOUD, pregnancy is associated with a significant increase in treatment initiation and a reduced risk of medication discontinuation.

Principal component regression analysis of familial psychiatric histories and suicide risk factors among adults with opioid use disorder.

This study explores familial psychiatric risk factors that are closely linked to suicide risk among patients with opioid use disorder (OUD) as measured by the Family History Assessment Module (FHAM). Data was derived from adults diagnosed with OUD (N = 389). To analyze the covariance between the 11 items of the FHAM, principal component analysis was applied to infer principal components (PC) scores. Log-binominal regression was conducted to quantify the associations between PC scores and mental health symptoms (e.g., lifetime suicidal attempt, P30D suicidal ideation, depression, and anxiety). Analyses revealed that the first 3 three PCs could account for 56% of the total variance of the FHAM items within the data. Family history of substance misuse (PC1) was positively associated with lifetime suicide attempts and severe anxiety. Family history of serious mental illness (PC2) and of suicidal behavior (PC3) were not significantly associated with any outcomes. Our findings suggest current suicide risk is associated with an array of familial psychiatric issues among people with OUD. However, family history of suicide attempts and death by suicide has less bearing on current suicide risk in OUD patients whereas family history of substance use confers significant risk. Findings underscore suicide-related preventive interventions as necessary components of treatment plans among people with OUD, who commonly report family histories of substance misuse.

A flexible modeling approach for biomarker-based computation of absolute risk of Alzheimer's disease dementia.

INTRODUCTION: As Alzheimer's disease (AD) biomarkers rapidly develop, tools are needed that accurately and effectively communicate risk of AD dementia. METHODS: We analyzed longitudinal data from >10,000 cognitively unimpaired older adults. Five-year risk of AD dementia was modeled using survival analysis. RESULTS: A demographic model was developed and validated on independent data with area under the receiver operating characteristic curve (AUC) for 5-year prediction of AD dementia of 0.79. Clinical and cognitive variables (AUC = 0.79), and apolipoprotein E genotype (AUC = 0.76) were added to the demographic model. We then incorporated the risk computed from the demographic model with hazard ratios computed from independent data for amyloid positron emission tomography status and magnetic resonance imaging hippocampal volume (AUC = 0.84), and for plasma amyloid beta (Aß)42/Aß40 (AUC = 0.82). DISCUSSION: An adaptive tool was developed and validated to compute absolute risks of AD dementia. This approach allows for improved accuracy and communication of AD risk among cognitively unimpaired older adults.