Association of state Medicaid expansion status with rates of suicide among US adults

Importance: In the US, suicide is the 10th leading cause of death and a serious mental health emergency. National programs that address suicide list access to mental health care as key in prevention, and more large-scale policies are needed to improve access to mental health care and address this crisis. The Patient Protection and Affordable Care Act (ACA) Medicaid Expansion Program was implemented in several states with the goal of increasing access to the health care system. Objective: To compare changes in suicide rates in states that expanded Medicaid under the ACA vs states that did not. Design, Setting, and Participants: In this cross-sectional study, state-level mortality rates were obtained from the National Center for Health Statistics for US individuals aged 20 to 64 years from January 1, 2000, to December 31, 2018. Data analysis was performed from April 18, 2021, to April 15, 2022. Exposures: Changes in suicide mortality rates among nonelderly adults before and after Medicaid expansion in expansion and nonexpansion states were compared using adjusted difference-in-differences analyses via hierarchical bayesian linear regression. Main Outcomes and Measures: Suicide rates using death by suicide as the primary measure. Results: Of the total population at risk for suicide, 50.4% were female, 13.3% were Black, 79.5% were White, and 7.2% were of other races. The analytic data set contained suicide mortality data for 2907 state-age-year units covering the general US population. A total of 553 912 deaths by suicide occurred during the study period, with most occurring in White (496 219 [89.6%]) and male (429 580 [77.6%]) individuals. There were smaller increases in the suicide rate after 2014 in Medicaid expansion (2.56 per 100 000 increase) compared with nonexpansion states (3.10 per 100 000 increase). In adjusted difference-in-differences analysis, a significant decrease of -0.40 (95% credible interval, -0.66 to -0.14) suicides per 100 000 individuals was found, translating to 1818 suicides that were averted in 2015 to 2018. Conclusions and Relevance: In this cross-sectional study, although suicide rates increased in both groups, blunting of these rates occurred among nonelderly adults in the Medicaid expansion states compared with nonexpansion states. Because this difference may be linked to increased access to mental health care, policy makers should consider suicide prevention as a benefit of expanding access to health care

The efficacy of short tandem repeat polymorphisms versus single-nucleotide polymorphisms for resolving population structure

Accurately resolving population structure in a sample is important for both linkage and association studies. In this study we investigated the power of single-nucleotide polymorphisms (SNPs) in detecting population structure in a sample of 286 unrelated individuals. We varied the number of SNPs to determine how many are required to approach the degree of resolution obtained with the Collaborative Study on the Genetics of Alcoholism (COGA) short tandem repeat polymorphisms (STRPs). In addition, we selected SNPs with varying minor allele frequencies (MAFs) to determine whether low or high frequency SNPs are more efficient in resolving population structure. We conclude that a set of at least 100 evenly spaced SNPs with MAFs of 40–50% is required to resolve population structure in this dataset. If SNPs with lower MAFs are used, then more than 250 SNPs may be required to obtain reliable results

Risky sexual behaviors and sexually transmitted diseases: a comparison study of cocaine-dependent individuals in treatment versus a community-matched sample

Cocaine users routinely engage in high-risk sexual behaviors that place them at an elevated risk of contracting HIV and other blood-borne infections. The purpose of the present study was to compare trading sex for drugs and/or money, having 10 or more sexual partners in 1 year, and sexually transmitted diseases (STDs) of cocaine-dependent individuals in treatment for their dependence across race and gender and against participants who live in their community. Cocaine-dependent individuals (n = 459) were identified through nine publicly and privately funded inpatient and outpatient chemical dependency treatment centers in the St. Louis area during 2001–2006. Community-based participants (n = 459) were matched to cocaine-dependent participants on age, ethnicity, gender, and zip code of residence. Mean age of the sample was 36 years old, 50% were Caucasians, 50% were African American, and 47% were male. Nearly half of cocaine-dependent participants in treatment had traded sex for drugs and/or money and over one-third had more than 10 sexual partners in 1 year with a risk concentrated among African Americans even after controlling for income and educational attainment. Participants recruited from the community with some exposure to cocaine reported similar rates of high risk sexual behaviors as the cocaine dependent subjects from treatment settings. It is important for clinicians to recognize that once released from treatment, cocaine-dependent individuals may be returning to high-risk environments where sexual risk behaviors are occurring in the context of cocaine use

Defining alcohol-related phenotypes in humans. The Collaborative Study on the Genetics of Alcoholism.

Alcoholism is a disease that runs in families and results at least in part from genetic risk factors. The Collaborative Study on the Genetics of Alcoholism (COGA) is a Federally funded effort to identify and characterize those genetic factors. The study involves more than 1,000 alcoholic subjects and their families, with researchers conducting comprehensive psychological, physiological, electrophysiological, and genetic analyses of the participants. These analyses have identified several traits, or phenotypes, that appear to be genetically determined, such as the presence of alcohol dependence, the level of response to alcohol, the presence of coexisting depression, or the maximum number of drinks a person consumes per occasion. Genetic analyses have identified regions on several chromosomes that are associated with these phenotypes and need to be studied further

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations

Harmonization of Neuroticism and Extraversion phenotypes across inventories and cohorts in the Genetics of Personality Consortium : an application of Item Response Theory

Peer reviewe

Potential causal association between gut microbiome and posttraumatic stress disorder

Background: The causal effects of gut microbiome and the development of posttraumatic stress disorder (PTSD) are still unknown. This study aimed to clarify their potential causal association using mendelian randomization (MR). Methods: The summary-level statistics for gut microbiome were retrieved from a genome-wide association study (GWAS) of the MiBioGen consortium. As to PTSD, the Freeze 2 datasets were originated from the Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group (PGC-PTSD), and the replicated datasets were obtained from FinnGen consortium. Single nucleotide polymorphisms meeting MR assumptions were selected as instrumental variables. The inverse variance weighting (IVW) method was employed as the main approach, supplemented by sensitivity analyses to evaluate potential pleiotropy and heterogeneity and ensure the robustness of the MR results. We also performed reverse MR analyses to explore PTSD’s causal effects on the relative abundances of specific features of the gut microbiome. Results: In Freeze 2 datasets from PGC-PTSD, eight bacterial traits revealed a potential causal association between gut microbiome and PTSD (IVW, all P < 0.05). In addition, Genus.Dorea and genus.Sellimonas were replicated in FinnGen datasets, in which eight bacterial traits revealed a potential causal association between gut microbiome and the occurrence of PTSD. The heterogeneity and pleiotropy analyses further supported the robustness of the IVW findings, providing additional evidence for their reliability. Conclusion: Our study provides the potential causal impact of gut microbiomes on the development of PTSD, shedding new light on the understanding of the dysfunctional gut-brain axis in this disorder. Our findings present novel evidence and call for investigations to confirm the association between their links, as well as to illuminate the underlying mechanisms

Potential causal association between gut microbiome and posttraumatic stress disorder

Funding Information: We thank the participants and working staff including the Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group, the FinnGen consortium, and the MiBioGen consortium. Publisher Copyright: © 2024, The Author(s).Background: The causal effects of gut microbiome and the development of posttraumatic stress disorder (PTSD) are still unknown. This study aimed to clarify their potential causal association using mendelian randomization (MR). Methods: The summary-level statistics for gut microbiome were retrieved from a genome-wide association study (GWAS) of the MiBioGen consortium. As to PTSD, the Freeze 2 datasets were originated from the Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group (PGC-PTSD), and the replicated datasets were obtained from FinnGen consortium. Single nucleotide polymorphisms meeting MR assumptions were selected as instrumental variables. The inverse variance weighting (IVW) method was employed as the main approach, supplemented by sensitivity analyses to evaluate potential pleiotropy and heterogeneity and ensure the robustness of the MR results. We also performed reverse MR analyses to explore PTSD’s causal effects on the relative abundances of specific features of the gut microbiome. Results: In Freeze 2 datasets from PGC-PTSD, eight bacterial traits revealed a potential causal association between gut microbiome and PTSD (IVW, all P < 0.05). In addition, Genus.Dorea and genus.Sellimonas were replicated in FinnGen datasets, in which eight bacterial traits revealed a potential causal association between gut microbiome and the occurrence of PTSD. The heterogeneity and pleiotropy analyses further supported the robustness of the IVW findings, providing additional evidence for their reliability. Conclusion: Our study provides the potential causal impact of gut microbiomes on the development of PTSD, shedding new light on the understanding of the dysfunctional gut-brain axis in this disorder. Our findings present novel evidence and call for investigations to confirm the association between their links, as well as to illuminate the underlying mechanisms.publishersversionpublishe

Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information

Funding Information: This work was supported by the National Institute of Mental Health / U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium ), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience . Statistical analyses were carried out on the LISA/Genetic Cluster Computer ( https://userinfo.surfsara.nl/systems/lisa ) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. Funding Information: MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc., RallyPoint Networks, Inc., Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled “Genotype-guided dosing of opioid agonists,” filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Funding Information: This work was supported by the National Institute of Mental Health/ U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience. Statistical analyses were carried out on the LISA/Genetic Cluster Computer (https://userinfo.surfsara.nl/systems/lisa) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. This material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting true views of the U.S. Department of the Army or the Department of Defense. We thank the investigators who comprise the PGC-PTSD working group and especially the more than 206,000 research participants worldwide who shared their life experiences and biological samples with PGC-PTSD investigators. We thank Mark Zervas for his critical input. Full acknowledgments are in Supplement 1. MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc. RallyPoint Networks, Inc. Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled ?Genotype-guided dosing of opioid agonists,? filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: © 2021 Society of Biological PsychiatryBackground: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.publishersversionpublishe

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms