Daniel E. Adkins

Meta-analysis of genome-wide association studies of anxiety disorders

Anxiety disorders (ADs), namely generalized AD, panic disorder and phobias, are common, etiologically complex conditions with a partially genetic basis. Despite differing on diagnostic definitions based on clinical presentation, ADs likely represent various expressions of an underlying common diathesis of abnormal regulation of basic threat–response systems. We conducted genome-wide association analyses in nine samples of European ancestry from seven large, independent studies. To identify genetic variants contributing to genetic susceptibility shared across interview-generated DSM-based ADs, we applied two phenotypic approaches: (1) comparisons between categorical AD cases and supernormal controls, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. We used logistic and linear regression, respectively, to analyze the association between these phenotypes and genome-wide single nucleotide polymorphisms. Meta-analysis for each phenotype combined results across the nine samples for over 18u2009000 unrelated individuals. Each meta-analysis identified a different genome-wide significant region, with the following markers showing the strongest association: for case–control contrasts, rs1709393 located in an uncharacterized non-coding RNA locus on chromosomal band 3q12.3 (P=1.65 × 10−8); for FS, rs1067327 within CAMKMT encoding the calmodulin-lysine N-methyltransferase on chromosomal band 2p21 (P=2.86 × 10−9). Independent replication and further exploration of these findings are needed to more fully understand the role of these variants in risk and expression of ADs.

SNP-based heritability estimates of the personality dimensions and polygenic prediction of both neuroticism and major depression: findings from CONVERGE.

Biometrical genetic studies suggest that the personality dimensions, including neuroticism, are moderately heritable (~0.4 to 0.6). Quantitative analyses that aggregate the effects of many common variants have recently further informed genetic research on European samples. However, there has been limited research to date on non-European populations. This study examined the personality dimensions in a large sample of Han Chinese descent (N=10u2009064) from the China, Oxford, and VCU Experimental Research on Genetic Epidemiology study, aimed at identifying genetic risk factors for recurrent major depression among a rigorously ascertained cohort. Heritability of neuroticism as measured by the Eysenck Personality Questionnaire (EPQ) was estimated to be low but statistically significant at 10% (s.e.=0.03, P=0.0001). In addition to EPQ, neuroticism based on a three-factor model, data for the Big Five (BF) personality dimensions (neuroticism, openness, conscientiousness, extraversion and agreeableness) measured by the Big Five Inventory were available for controls (n=5596). Heritability estimates of the BF were not statistically significant despite high power (>0.85) to detect heritabilities of 0.10. Polygenic risk scores constructed by best linear unbiased prediction weights applied to split-half samples failed to significantly predict any of the personality traits, but polygenic risk for neuroticism, calculated with LDpred and based on predictive variants previously identified from European populations (N=171u2009911), significantly predicted major depressive disorder case–control status (P=0.0004) after false discovery rate correction. The scores also significantly predicted EPQ neuroticism (P=6.3 × 10−6). Factor analytic results of the measures indicated that any differences in heritabilities across samples may be due to genetic variation or variation in haplotype structure between samples, rather than measurement non-invariance. Findings demonstrate that neuroticism can be significantly predicted across ancestry, and highlight the importance of studying polygenic contributions to personality in non-European populations.

Deep Sequencing of Three Loci Implicated in Large-Scale Genome-Wide Association Study Smoking Meta-Analyses.

INTRODUCTIONnGenome-wide association study meta-analyses have robustly implicated three loci that affect susceptibility for smoking: CHRNA5CHRNA3CHRNB4, CHRNB3CHRNA6 and EGLN2CYP2A6. Functional follow-up studies of these loci are needed to provide insight into biological mechanisms. However, these efforts have been hampered by a lack of knowledge about the specific causal variant(s) involved. In this study, we prioritized variants in terms of the likelihood they account for the reported associations.nnnMETHODSnWe employed targeted capture of the CHRNA5CHRNA3CHRNB4, CHRNB3CHRNA6, and EGLN2CYP2A6 loci and flanking regions followed by next-generation deep sequencing (mean coverage 78×) to capture genomic variation in 363 individuals. We performed single locus tests to determine if any single variant accounts for the association, and examined if sets of (rare) variants that overlapped with biologically meaningful annotations account for the associations.nnnRESULTSnIn total, we investigated 963 variants, of which 71.1% were rare (minor allele frequency < 0.01), 6.02% were insertion/deletions, and 51.7% were catalogued in dbSNP141. The single variant results showed that no variant fully accounts for the association in any region. In the variant set results, CHRNB4 accounts for most of the signal with significant sets consisting of directly damaging variants. CHRNA6 explains most of the signal in the CHRNB3CHRNA6 locus with significant sets indicating a regulatory role for CHRNA6. Significant sets in CYP2A6 involved directly damaging variants while the significant variant sets suggested a regulatory role for EGLN2.nnnCONCLUSIONSnWe found that multiple variants implicating multiple processes explain the signal. Some variants can be prioritized for functional follow-up.

Enrichment methods provide a feasible approach to comprehensive and adequately powered investigations of the brain methylome

Abstract Methylome-wide association studies are typically performed using microarray technologies that only assay a very small fraction of the CG methylome and entirely miss two forms of methylation that are common in brain and likely of particular relevance for neuroscience and psychiatric disorders. The alternative is to use whole genome bisulfite (WGB) sequencing but this approach is not yet practically feasible with sample sizes required for adequate statistical power. We argue for revisiting methylation enrichment methods that, provided optimal protocols are used, enable comprehensive, adequately powered and cost-effective genome-wide investigations of the brain methylome. To support our claim we use data showing that enrichment methods approximate the sensitivity obtained with WGB methods and with slightly better specificity. However, this performance is achieved at <5% of the reagent costs. Furthermore, because many more samples can be sequenced simultaneously, projects can be completed about 15 times faster. Currently the only viable option available for comprehensive brain methylome studies, enrichment methods may be critical for moving the field forward.

Deep sequencing of 71 candidate genes to characterize variation associated with alcohol dependence

BACKGROUNDnPrevious genomewide association studies (GWASs) have identified a number of putative risk loci for alcohol dependence (AD). However, only a few loci have replicated and these replicated variants only explain a small proportion of AD risk. Using an innovative approach, the goal of this study was to generate hypotheses about potentially causal variants for AD that can be explored further through functional studies.nnnMETHODSnWe employed targeted capture of 71 candidate loci and flanking regions followed by next-generation deep sequencing (mean coverage 78X) in 806 European Americans. Regions included in our targeted capture library were genes identified through published GWAS of alcohol, all human alcohol and aldehyde dehydrogenases, reward system genes including dopaminergic and opioid receptors, prioritized candidate genes based on previous associations, and genes involved in the absorption, distribution, metabolism, and excretion of drugs. We performed single-locus tests to determine if any single variant was associated with AD symptom count. Sets of variants that overlapped with biologically meaningful annotations were tested for association in aggregate.nnnRESULTSnNo single, common variant was significantly associated with AD in our study. We did, however, find evidence for association with several variant sets. Two variant sets were significant at the q-value <0.10 level: a genic enhancer for ADHFE1 (pxa0=xa01.47xa0×xa010-5 ; qxa0=xa00.019), an alcohol dehydrogenase, and ADORA1 (pxa0=xa05.29xa0×xa010-5 ; qxa0=xa00.035), an adenosine receptor that belongs to a G-protein-coupled receptor gene family.nnnCONCLUSIONSnTo our knowledge, this is the first sequencing study of AD to examine variants in entire genes, including flanking and regulatory regions. We found that in addition to protein coding variant sets, regulatory variant sets may play a role in AD. From these findings, we have generated initial functional hypotheses about how these sets may influence AD.

Psychometric modeling of abuse and dependence symptoms across six illicit substances indicates novel dimensions of misuse

AIMSnThis study explored the factor structure of DSM III-R/IV symptoms for substance abuse and dependence across six illicit substance categories in a population-based sample of males.nnnMETHODnDSM III-R/IV drug abuse and dependence symptoms for cannabis, sedatives, stimulants, cocaine, opioids and hallucinogens from 4179 males born 1940-1970 from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders were analyzed. Confirmatory factor analyses tested specific hypotheses regarding the latent structure of substance misuse for a comprehensive battery of 13 misuse symptoms measured across six illicit substance categories (78 items).nnnRESULTSnAmong the models fit, the latent structure of substance misuse was best represented by a combination of substance-specific factors and misuse symptom-specific factors. We found no support for a general liability factor to illicit substance misuse.nnnCONCLUSIONSnResults indicate that liability to misuse illicit substances is drug class specific, with little evidence for a general liability factor. Additionally, unique dimensions capturing propensity toward specific misuse symptoms (e.g., tolerance, withdrawal) across substances were identified. While this finding requires independent replication, the possibility of symptom-specific misuse factors, present in multiple substances, raises the prospect of genetic, neurobiological and behavioral predispositions toward distinct, narrowly defined features of drug abuse and dependence.

The Rate of Change in Alcohol Misuse Across Adolescence is Heritable

BACKGROUNDnAlcohol use typically begins during adolescence and escalates into young adulthood. This represents an important period for the establishment of alcohol use and misuse patterns, which can have psychosocial and medical consequences. Although changes in alcohol use during this time have been phenotypically characterized, their genetic nature is poorly understood.nnnMETHODSnParticipants of the Avon Longitudinal Study of Parents and Children completed the Alcohol Use Disorders Identification Test (AUDIT) 4 times from age 16 to 20. We used Mplus to construct a growth model characterizing changes in AUDIT scores across time (Nxa0=xa04,545, where data were available for at least 2 time points). The slope of the model was used as the phenotype in a genomewide association study (Nxa0=xa03,380), followed by secondary genetic analyses.nnnRESULTSnNo individual marker met genomewide significance criteria. Top markers mapped to biologically plausible candidate genes. The slope term was moderately heritable (h2SNP = 0.26, pxa0=xa00.009), and replication attempts using a meta-analysis of independent samples provided support for implicated variants at the aggregate level. Nominally significant (pxa0<xa00.00001) markers mapped to putatively active genomic regions in brain tissue more frequently than expected by chance.nnnCONCLUSIONSnThese results build on prior studies by demonstrating that common genetic variation impacts alcohol misuse trajectories. Influential loci map to genes that merit additional research, as well as to intergenic regions with regulatory functions in the central nervous system. These findings underscore the complex biological nature of alcohol misuse across development.

Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative

The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.

Genome-wide association study of suicide death: Results from the first wave of Utah completed suicide data

Objective Suicide death is a highly preventable, yet growing, worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizeable suicide death cohorts available for study. To address this limitation, we conducted the first comprehensive genomic analysis of suicide death, using a previously unpublished suicide cohort. Methods The analysis sample consisted of 3,413 population-ascertained cases of European ancestry and 14,810 ancestrally matched controls. Analytical methods included principle components analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic relatedness matrix), gene and gene set enrichment testing, polygenic score analyses, as well as SNP heritability and genetic correlation estimation using LD score regression. Results GWAS identified two genome-wide significant loci (6 SNPs, p<5×10−8). Gene-based analyses implicated 19 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide heritability was estimated h2 =0.2463, SE = 0.0356 using summary statistics from a multivariate logistic GWAS adjusting for ancestry. Notably, suicide polygenic scores were robustly predictive of out of sample suicide death, as were polygenic scores for several other psychiatric disorders and psychological traits, particularly behavioral disinhibition and major depressive disorder. Conclusions In this report, we identify multiple genome-wide significant loci/genes, and demonstrate robust polygenic score prediction of suicide death case-control status, adjusting for ancestry, in independent training and test sets. Additionally, we report that suicide death cases have increased genetic risk for behavioral disinhibition, major depression, autism spectrum disorder, psychosis, and alcohol use disorder relative to controls. Results demonstrate the ability of polygenic scores to robustly, and multidimensionally, predict suicide death case-control status.Background: Heritability of suicide risk is estimated at 43%, thus genetic risk likely plays an important role in completion of suicide. Previous genetic research has focused primarily on suicidal behavior ornideation rather than actual completed suicide. And previous genome-wide association studies of completion of suicide have been very small due to the difficulty in obtaining suicide sample data, and have been unable to identify genome-wide significant variants, likely due to power limitations. This study presents results from the first wave of a large Utah sample of completed suicides, and represent the most statistically powerful sample of completed suicide to date.nMethods: Tissue samples from 1321 decedents were collected via partnership with the Utah Office of the Medical Examiner and genotyped using the Illumina Infinium PsychArray platform. Bioconductor package RaMWAS (A.S.) was used on post-QC hard call data (271,894 common variants) to conduct GWAS. Because the sample is from Utah, the authors were able to conduct a relatively direct comparison with 1000 Genomes controls also from Utah (CEU), as well as European controls (EUR). The first GWAS with Utah CEU controls (n of only 99) was followed by a second GWAS with EUR controls (n = 503) with and without CEU included in the control sample.nResults: Analyses identified 8 SNPs in 6 genes associated with the completion of suicide. Six SNPs met genome-widesignificanceat5x10- 8 .Two of these variant hits were replicated using EUR controls not including the CEU sample, though the case sample was the same in both analyses. Subsequent QC steps (linkage disequilibrium analysis and EUR GWAS replication) further substantiated significant results implicating cytochrome P450 genes.nConclusions: This GWAS and partial replication of findings across control samples, using hard call genotype data, represents a significant step toward understanding the genetic architecture of suicide. These are late breaking results, and in January this group will follow up with analyses using the full 2 waves (N = 4800 cases), a far larger control group, and imputed data to ~11 million variants. Analyses to date implicate cytochrome P450 sites involved in metabolism of arachidonic acid and related inflammatory mediators. Results implicate inflammation in suicide risk, and also add to the growing body of evidence that lung function may be tied to suicide.

Bleeding, Cramping, and Satisfaction Among New Copper IUD Users: A Prospective Study

Objective We assess change in bleeding, cramping, and satisfaction among new copper (Cu) IUD users during the first six months of use, and evaluate the impact of bleeding and cramping on method satisfaction. Methods We recruited 77 women ages 18–45 for this prospective longitudinal observational cohort study. Eligible women reported regular menses, had no exposure to hormonal contraception in the last three months, and desired a Cu IUD for contraception. We collected data prospectively for 180 days following IUD insertion. Monthly, Participants reported bleeding scores using the validated pictorial blood loss assessment chart (PBAC), IUD satisfaction using a five-point Likert scale, and cramping using a seven-level ordinal scale. We used multiple imputation to address nonrandom attrition. Structural equation models for count and ordered outcomes modeled bleeding, cramping, and satisfaction growth curves over the six monthly repeated assessments. Results Bleeding significantly decreased (approximately 25%) over the course of the study from an estimated PBAC=195 at one month post-insertion to PBAC=151 at six months (t=−2.38, p<0.05). Additionally, IUD satisfaction improved over time (t=2.65, p<0.01), increasing from between “Neutral” and “Satisfied” to “Satisfied”, over the six month study. Cramping decreased sharply over the six-month study from between biweekly and weekly, to once or twice a month (t=−4.38, p<0.001). Finally, bleeding, but not cramping, was associated with IUD satisfaction (study mean: t=−2.31, p<0.05; study end: t=−2.81, p<0.01). Conclusions New Cu IUD users reported decreasing bleeding and cramping, and increasing IUD satisfaction, over the first six months. Method satisfaction was negatively associated with bleeding.