The genetic landscape of substance use disorders.

Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.

Genome-wide association study meta-analysis of dizygotic twinning illuminates genetic regulation of female fecundity.

STUDY QUESTION: Which genetic factors regulate female propensity for giving birth to spontaneous dizygotic (DZ) twins? SUMMARY ANSWER: We identified four new loci, GNRH1, FSHR, ZFPM1, and IPO8, in addition to previously identified loci, FSHB and SMAD3. WHAT IS KNOWN ALREADY: The propensity to give birth to DZ twins runs in families. Earlier, we reported that FSHB and SMAD3 as associated with DZ twinning and female fertility measures. STUDY DESIGN, SIZE, DURATION: We conducted a genome-wide association meta-analysis (GWAMA) of mothers of spontaneous dizygotic (DZ) twins (8265 cases, 264 567 controls) and of independent DZ twin offspring (26 252 cases, 417 433 controls). PARTICIPANTS/MATERIALS, SETTING, METHODS: Over 700 000 mothers of DZ twins, twin individuals and singletons from large cohorts in Australia/New Zealand, Europe, and the USA were carefully screened to exclude twins born after use of ARTs. Genetic association analyses by cohort were followed by meta-analysis, phenome wide association studies (PheWAS), in silico and in vivo annotations, and Zebrafish functional validation. MAIN RESULTS AND THE ROLE OF CHANCE: This study enlarges the sample size considerably from previous efforts, finding four genome-wide significant loci, including two novel signals and a further two novel genes that are implicated by gene level enrichment analyses. The novel loci, GNRH1 and FSHR, have well-established roles in female reproduction whereas ZFPM1 and IPO8 have not previously been implicated in female fertility. We found significant genetic correlations with multiple aspects of female reproduction and body size as well as evidence for significant selection against DZ twinning during human evolution. The 26 top single nucleotide polymorphisms (SNPs) from our GWAMA in European-origin participants weakly predicted the crude twinning rates in 47 non-European populations (r = 0.23 between risk score and population prevalence, s.e. 0.11, 1-tail P = 0.058) indicating that genome-wide association studies (GWAS) are needed in African and Asian populations to explore the causes of their respectively high and low DZ twinning rates. In vivo functional tests in zebrafish for IPO8 validated its essential role in female, but not male, fertility. In most regions, risk SNPs linked to known expression quantitative trait loci (eQTLs). Top SNPs were associated with in vivo reproductive hormone levels with the top pathways including hormone ligand binding receptors and the ovulation cycle. LARGE SCALE DATA: The full DZT GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/). LIMITATIONS, REASONS FOR CAUTION: Our study only included European ancestry cohorts. Inclusion of data from Africa (with the highest twining rate) and Asia (with the lowest rate) would illuminate further the biology of twinning and female fertility. WIDER IMPLICATIONS OF THE FINDINGS: About one in 40 babies born in the world is a twin and there is much speculation on why twinning runs in families. We hope our results will inform investigations of ovarian response in new and existing ARTs and the causes of female infertility. STUDY FUNDING/COMPETING INTEREST(S): Support for the Netherlands Twin Register came from the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organization for Health Research and Development (ZonMW) grants, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, 911-09-032, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI.NL, 184.021.007), Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB, European Research Council (ERC-230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1) and the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health and Grand Opportunity grants 1RC2 MH089951. The QIMR Berghofer Medical Research Institute (QIMR) study was supported by grants from the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485, 552498, 1050208, 1075175). L.Y. is funded by Australian Research Council (Grant number DE200100425). The Minnesota Center for Twin and Family Research (MCTFR) was supported in part by USPHS Grants from the National Institute on Alcohol Abuse and Alcoholism (AA09367 and AA11886) and the National Institute on Drug Abuse (DA05147, DA13240, and DA024417). The Women's Genome Health Study (WGHS) was funded by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with support for genotyping provided by Amgen. Data collection in the Finnish Twin Registry has been supported by the Wellcome Trust Sanger Institute, the Broad Institute, ENGAGE-European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement number 201413, National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, AA-09203, AA15416, and K02AA018755) and the Academy of Finland (grants 100499, 205585, 118555, 141054, 264146, 308248, 312073 and 336823 to J. Kaprio). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. For NESDA, funding was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10000-1002), the Center for Medical Systems Biology (CSMB, NVVO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University's Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, ROI D0042157-01A, MH081802, Grand Opportunity grants 1 RC2 Ml-1089951 and IRC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. Work in the Del Bene lab was supported by the Programme Investissements d'Avenir IHU FOReSIGHT (ANR-18-IAHU-01). C.R. was supported by an EU Horizon 2020 Marie Sklodowska-Curie Action fellowship (H2020-MSCA-IF-2014 #661527). H.S. and K.S. are employees of deCODE Genetics/Amgen. The other authors declare no competing financial interests. TRIAL REGISTRATION NUMBER: N/A.

Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning.

Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.

E-MAGMA: an eQTL-informed method to identify risk genes using genome-wide association study summary statistics.

MOTIVATION: Genome-wide association studies have successfully identified multiple independent genetic loci that harbour variants associated with human traits and diseases, but the exact causal genes are largely unknown. Common genetic risk variants are enriched in non-protein-coding regions of the genome and often affect gene expression (expression quantitative trait loci, eQTL) in a tissue-specific manner. To address this challenge, we developed a methodological framework, E-MAGMA, which converts genome-wide association summary statistics into gene-level statistics by assigning risk variants to their putative genes based on tissue-specific eQTL information. RESULTS: We compared E-MAGMA to three eQTL informed gene-based approaches using simulated phenotype data. Phenotypes were simulated based on eQTL reference data using GCTA for all genes with at least one eQTL at chromosome 1. We performed 10 simulations per gene. The eQTL-h2 (i.e. the proportion of variation explained by the eQTLs) was set at 1%, 2% and 5%. We found E-MAGMA outperforms other gene-based approaches across a range of simulated parameters (e.g. the number of identified causal genes). When applied to genome-wide association summary statistics for five neuropsychiatric disorders, E-MAGMA identified more putative candidate causal genes compared to other eQTL-based approaches. By integrating tissue-specific eQTL information, these results show E-MAGMA will help to identify novel candidate causal genes from genome-wide association summary statistics and thereby improve the understanding of the biological basis of complex disorders. AVAILABILITY AND IMPLEMENTATION: A tutorial and input files are made available in a github repository: https://github.com/eskederks/eMAGMA-tutorial. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A gene co-expression network-based analysis of multiple brain tissues reveals novel genes and molecular pathways underlying major depression.

Major depression is a common and severe psychiatric disorder with a highly polygenic genetic architecture. Genome-wide association studies have successfully identified multiple independent genetic loci that harbour variants associated with major depression, but the exact causal genes and biological mechanisms are largely unknown. Tissue-specific network approaches may identify molecular mechanisms underlying major depression and provide a biological substrate for integrative analyses. We provide a framework for the identification of individual risk genes and gene co-expression networks using genome-wide association summary statistics and gene expression information across multiple human brain tissues and whole blood. We developed a novel gene-based method called eMAGMA that leverages tissue-specific eQTL information to identify 99 biologically plausible risk genes associated with major depression, of which 58 are novel. Among these novel associations is Complement Factor 4A (C4A), recently implicated in schizophrenia through its role in synaptic pruning during postnatal development. Major depression risk genes were enriched in gene co-expression modules in multiple brain tissues and the implicated gene modules contained genes involved in synaptic signalling, neuronal development, and cell transport pathways. Modules enriched with major depression signals were strongly preserved across brain tissues, but were weakly preserved in whole blood, highlighting the importance of using disease-relevant tissues in genetic studies of psychiatric traits. We identified tissue-specific genes and gene co-expression networks associated with major depression. Our novel analytical framework can be used to gain fundamental insights into the functioning of the nervous system in major depression and other brain-related traits.

Evaluating the role of alcohol consumption in breast and ovarian cancer susceptibility using population-based cohort studies and two-sample Mendelian randomization analyses.

Alcohol consumption is correlated positively with risk for breast cancer in observational studies, but observational studies are subject to reverse causation and confounding. The association with epithelial ovarian cancer (EOC) is unclear. We performed both observational Cox regression and two-sample Mendelian randomization (MR) analyses using data from various European cohort studies (observational) and publicly available cancer consortia (MR). These estimates were compared to World Cancer Research Fund (WCRF) findings. In our observational analyses, the multivariable-adjusted hazard ratios (HR) for a one standard drink/day increase was 1.06 (95% confidence interval [CI]; 1.04, 1.08) for breast cancer and 1.00 (0.92, 1.08) for EOC, both of which were consistent with previous WCRF findings. MR ORs per genetically predicted one standard drink/day increase estimated via 34 SNPs using MR-PRESSO were 1.00 (0.93, 1.08) for breast cancer and 0.95 (0.85, 1.06) for EOC. Stratification by EOC subtype or estrogen receptor status in breast cancers made no meaningful difference to the results. For breast cancer, the CIs for the genetically derived estimates include the point-estimate from observational studies so are not inconsistent with a small increase in risk. Our data provide additional evidence that alcohol intake is unlikely to have anything other than a very small effect on risk of EOC.

Associations between the CADM2 gene, substance use, risky sexual behavior, and self-control: A phenome-wide association study.

Risky behaviors, such as substance use and unprotected sex, are associated with various physical and mental health problems. Recent genome-wide association studies indicated that variation in the cell adhesion molecule 2 (CADM2) gene plays a role in risky behaviors and self-control. In this phenome-wide scan for risky behavior, it was tested if underlying common vulnerability could be (partly) explained by pleiotropic effects of this gene and how large the effects were. Single nucleotide polymorphism (SNP)-level and gene-level association tests within four samples (25 and Up, Spit for Science, Netherlands Twin Register, and UK Biobank and meta-analyses over all samples (combined sample of 362,018 participants) were conducted to test associations between CADM2, substance- and sex-related risk behaviors, and various measures related to self-control. We found significant associations between the CADM2 gene, various risky behaviors, and different measures of self-control. The largest effect sizes were found for cannabis use, sensation seeking, and disinhibition. Effect sizes ranged from 0.01% to 0.26% for single top SNPs and from 0.07% to 3.02% for independent top SNPs together, with sufficient power observed only in the larger samples and meta-analyses. In the largest cohort, we found indications that risk-taking proneness mediated the association between CADM2 and latent factors for lifetime smoking and regular alcohol use. This study extends earlier findings that CADM2 plays a role in risky behaviors and self-control. It also provides insight into gene-level effect sizes and demonstrates the feasibility of testing mediation. These findings present a good starting point for investigating biological etiological pathways underlying risky behaviors.

An integrative systems-based analysis of substance use: eQTL-informed gene-based tests, gene networks, and biological mechanisms.

Genome-wide association studies have identified multiple genetic risk factors underlying susceptibility to substance use, however, the functional genes and biological mechanisms remain poorly understood. The discovery and characterization of risk genes can be facilitated by the integration of genome-wide association data and gene expression data across biologically relevant tissues and/or cell types to identify genes whose expression is altered by DNA sequence variation (expression quantitative trait loci; eQTLs). The integration of gene expression data can be extended to the study of genetic co-expression, under the biologically valid assumption that genes form co-expression networks to influence the manifestation of a disease or trait. Here, we integrate genome-wide association data with gene expression data from 13 brain tissues to identify candidate risk genes for 8 substance use phenotypes. We then test for the enrichment of candidate risk genes within tissue-specific gene co-expression networks to identify modules (or groups) of functionally related genes whose dysregulation is associated with variation in substance use. We identified eight gene modules in brain that were enriched with gene-based association signals for substance use phenotypes. For example, a single module of 40 co-expressed genes was enriched with gene-based associations for drinks per week and biological pathways involved in GABA synthesis, release, reuptake and degradation. Our study demonstrates the utility of eQTL and gene co-expression analysis to uncover novel biological mechanisms for substance use traits.

Genetic heterogeneity in self-reported depressive symptoms identified through genetic analyses of the PHQ-9.

BACKGROUND: Depression is a clinically heterogeneous disorder. Previous large-scale genetic studies of depression have explored genetic risk factors of depression case-control status or aggregated sums of depressive symptoms, ignoring possible clinical or genetic heterogeneity. METHODS: We analyse data from 148 752 subjects of white British ancestry in the UK Biobank who completed nine items of a self-rated measure of current depressive symptoms: the Patient Health Questionnaire (PHQ-9). Genome-Wide Association analyses were conducted for nine symptoms and two composite measures. LD Score Regression was used to calculate SNP-based heritability (h2SNP) and genetic correlations (rg) across symptoms and to investigate genetic correlations with 25 external phenotypes. Genomic structural equation modelling was used to test the genetic factor structure across the nine symptoms. RESULTS: We identified nine genome-wide significant genomic loci (8 novel), with no overlap in loci across symptoms. h2SNP ranged from 6% (concentration problems) to 9% (appetite changes). Genetic correlations ranged from 0.54 to 0.96 (all p < 1.39 × 10-3) with 30 of 36 correlations being significantly smaller than one. A two-factor model provided the best fit to the genetic covariance matrix, with factors representing 'psychological' and 'somatic' symptoms. The genetic correlations with external phenotypes showed large variation across the nine symptoms. CONCLUSIONS: Patterns of SNP associations and genetic correlations differ across the nine symptoms, suggesting that current depressive symptoms are genetically heterogeneous. Our study highlights the value of symptom-level analyses in understanding the genetic architecture of a psychiatric trait. Future studies should investigate whether genetic heterogeneity is recapitulated in clinical symptoms of major depression.

Potential influence of socioeconomic status on genetic correlations between alcohol consumption measures and mental health.

BACKGROUND: Frequency and quantity of alcohol consumption are metrics commonly used to measure alcohol consumption behaviors. Epidemiological studies indicate that these alcohol consumption measures are differentially associated with (mental) health outcomes and socioeconomic status (SES). The current study aims to elucidate to what extent genetic risk factors are shared between frequency and quantity of alcohol consumption, and how these alcohol consumption measures are genetically associated with four broad phenotypic categories: (i) SES; (ii) substance use disorders; (iii) other psychiatric disorders; and (iv) psychological/personality traits. METHODS: Genome-Wide Association analyses were conducted to test genetic associations with alcohol consumption frequency (N = 438 308) and alcohol consumption quantity (N = 307 098 regular alcohol drinkers) within UK Biobank. For the other phenotypes, we used genome-wide association studies summary statistics. Genetic correlations (rg) between the alcohol measures and other phenotypes were estimated using LD score regression. RESULTS: We found a substantial genetic correlation between the frequency and quantity of alcohol consumption (rg = 0.52). Nevertheless, both measures consistently showed opposite genetic correlations with SES traits, and many substance use, psychiatric, and psychological/personality traits. High alcohol consumption frequency was genetically associated with high SES and low risk of substance use disorders and other psychiatric disorders, whereas the opposite applies for high alcohol consumption quantity. CONCLUSIONS: Although the frequency and quantity of alcohol consumption show substantial genetic overlap, they consistently show opposite patterns of genetic associations with SES-related phenotypes. Future studies should carefully consider the potential influence of SES on the shared genetic etiology between alcohol and adverse (mental) health outcomes.

Exploring Phenotypic and Genetic Overlap Between Cannabis Use and Schizotypy.

There is a well-established relationship between cannabis use and psychosis, although the exact nature of this relationship is not fully understood. Recent studies have observed significant genetic overlap between a diagnosis of schizophrenia and lifetime cannabis use. Expanding on this work, the current study aimed to examine whether genetic overlap also occurs for subclinical psychosis (schizotypy) and cannabis use, as well as examining the phenotypic association between the traits. Phenotypic correlations were calculated for a variety of schizotypy and cannabis phenotypes in the UK Biobank (UKB), and single nucleotide polymorphism (SNP)-based heritability estimates and genetic correlations were calculated for these UKB phenotypes as well as for several other variables taken from recent genomewide association studies. Positive phenotypic correlations were observed between 11 out of 12 pairs of the cannabis use and schizotypy phenotypes (correlation range .05-.18), indicating a robust association between increased symptoms of schizotypy and cannabis use. SNP-based heritability estimates for two schizotypy phenotypes remained significant after multiple testing correction: social anhedonia (h2SNP = .08, SE = .02, N = 4025) and ever seen an unreal vision (h2SNP = .35, SE = .10, N = 150,717). Finally, one significant genetic correlation was observed between schizotypy and cannabis use, a negative correlation between social anhedonia and number of times used cannabis (rg = -.30, p = .012). The current study suggests the relationship between cannabis use and psychosis is also seen in subclinical symptoms of psychosis, but further research with larger samples is needed to determine the biological mechanisms underlying this association.

A Comparison of Excessive Drinking, Binge Drinking and Alcohol Dependence in Ethnic Minority Groups in the Netherlands: The HELIUS Study.

BACKGROUND: The Dutch multi-ethnic Healthy Life in an Urban Setting study recently showed that alcohol consumption was lower in ethnic minority groups than those of Dutch origin, but that binge drinking in drinkers of Turkish and Moroccan origin was relatively high. The aim of the current study is to examine factors that may contribute to the differences in drinking patterns and how they relate to the relationship between drinking patterns and alcohol dependence (AD) across ethnic groups. METHODS: The rate of last year alcohol use, alcohol use patterns and AD was assessed in 4,635 Dutch, 4,317 Moroccan, 4,036 Turkish, 2,459 Ghanaian, 4,426 African Surinamese and 3,357 South-Asian Surinamese participants (both men and women) born in Amsterdam, the Netherlands. RESULTS: Compared to the Dutch, the prevalence of (regular) drinking is substantially lower in all ethnic minority groups and regular drinkers among most ethnic minority groups have a lower adjusted risk to develop binge drinking and AD than the Dutch. For the prevalence of regular drinking, the ethnic differences are bigger than for the prevalence of current drinking. However, regular drinkers of Moroccan origin have a risk similar to the Dutch to develop binge drinking and AD; a finding that could not be explained by group differences in age, sex, religiosity, perceived discrimination, depression or guilt feelings about drinking. DISCUSSION: The prevalence data show that current drinking is lower and that regular drinking is much lower in ethnic minorities and - with the exception of those of Moroccan origin - ethnic minority regular drinkers also have a significant lower risk to develop binge drinking or AD than regular drinkers of Dutch origin. This implies that the magnitude of problematic alcohol use is substantially smaller in ethnic minorities than in the ethnic Dutch population of Amsterdam. Unfortunately, no explanation was found for the special risk situation of regular drinkers of Moroccan origin.

Contribution of Alcohol and Nicotine Dependence to the Prevalence of Depressed Mood in Different Ethnic Groups in The Netherlands: The HELIUS Study.

Objective: Ethnic minorities report different levels of drinking and smoking and higher rates of depression compared to native populations. In this study we aimed to investigate in six ethnic groups whether tobacco and alcohol use were associated with depressive symptoms, which are more prevalent in ethnic minorities.Methods: Cross-sectional data from the multi-ethnic Healthy Life in an Urban Setting (HELIUS) study sample (N = 22,471) was used, comprising 4,580 native Dutch participants which were compared with participants from five ethnic minority groups (3,259 South Asian Surinamese, 4,292 African Surinamese, 2,262 Ghanaian, 3,891 Turkish, and 4,187 Moroccan).Results: Alcohol misuse was positively associated with depressed mood in all ethnic groups except for the Dutch and the Ghanaians. Nicotine dependence was positively associated with depressed mood in all ethnic groups except for the Ghanaian group.Conclusions: Alcohol misuse and nicotine dependence were significantly associated with depressed mood in most but not all ethnic groups and especially in men. However, across all groups the contribution of alcohol misuse and nicotine dependence to depressed mood was small. Prospective multi-ethnic studies should confirm whether the relations are causal and elucidate their direction.

Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium.

BACKGROUND: Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. METHODS: Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). RESULTS: Positive genetic correlation was observed between MD and AD (rgMD-AD = + 0.47, P = 6.6 × 10-10). AC-quantity showed positive genetic correlation with both AD (rgAD-AC quantity = + 0.75, P = 1.8 × 10-14) and MD (rgMD-AC quantity = + 0.14, P = 2.9 × 10-7), while there was negative correlation of AC-frequency with MD (rgMD-AC frequency = -0.17, P = 1.5 × 10-10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10-6). There was no evidence for reverse causation. CONCLUSION: This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.

Sex differences in the genetic architecture of obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) is a highly heritable complex phenotype that demonstrates sex differences in age of onset and clinical presentation, suggesting a possible sex difference in underlying genetic architecture. We present the first genome-wide characterization of the sex-specific genetic architecture of OCD, utilizing the largest set of OCD cases and controls available from the Psychiatric Genomics Consortium. We assessed evidence for several mechanisms that may contribute to sex differences including a sex-dependent liability threshold, the presence of individual sex-specific risk variants on the autosomes and the X chromosome, and sex-specific pleiotropic effects. Furthermore, we tested the hypothesis that genetic heterogeneity between the sexes may obscure associations in a sex-combined genome-wide association study. We observed a strong genetic correlation between male and female OCD and no evidence for a sex-dependent liability threshold model, suggesting that sex-combined analysis does not suffer from widespread loss of power because of genetic heterogeneity between the sexes. While we did not detect any significant sex-specific genome-wide single nucleotide polymorphisms (SNP) associations, we did identify two significant gene-based associations in females: GRID2 and GRP135, which showed no association in males. We observed that the SNPs with sexually differentiated effects showed an enrichment of regulatory variants influencing expression of genes in brain and immune tissues. These findings suggest that future studies with larger sample sizes hold great promise for the identification of sex-specific genetic risk factors for OCD.

The Biological Contributions to Gender Identity and Gender Diversity: Bringing Data to the Table.

The American Psychological Association defines gender identity as, "A person's deeply-felt, inherent sense of being a boy, a man, or a male; a girl, a woman, or a female; or an alternative gender (e.g., genderqueer, gender nonconforming, gender neutral) that may or may not correspond to a person's sex assigned at birth or to a person's primary or secondary sex characteristics" (American Psychological Association, Am Psychol 70(9):832-864, 2015). Here we review the evidence that gender identity and related socially defined gender constructs are influenced in part by innate factors including genes. Based on the data reviewed, we hypothesize that gender identity is a multifactorial complex trait with a heritable polygenic component. We argue that increasing the awareness of the biological diversity underlying gender identity development is relevant to all domains of social, medical, and neuroscience research and foundational for reducing health disparities and promoting human-rights protections for gender minorities.

Parental Smoking and Adult Offspring's Smoking Behaviors in Ethnic Minority Groups: An Intergenerational Analysis in the HELIUS Study.

Introduction: To understand smoking behaviors among ethnic minority groups, studies have largely focused on societal factors, with little attention to family influences. Yet studies among majority groups have identified parental smoking as an important risk factor. It is unknown whether this applies to ethnic minority groups. We investigated the association between parental smoking and adult offspring's smoking behaviors among ethnic minority groups with an immigrant background. Methods: We used data from the Healthy Life in an Urban Setting study from Amsterdam (the Netherlands) from January 2011 to December 2015. The sample consisted of 2184 parent-offspring pairs from South-Asian Surinamese, African Surinamese, Turkish, Moroccan, and Ghanaian origin. We collected self-reported smoking data: current status, duration of exposure to parental smoking, number of daily cigarettes, heavy smoking ( > 10 cigarettes/day), and nicotine dependency (using the Fagerström Test). Analyses were stratified by offspring's age, cohabitation with parent, education (parent/offspring), offspring's cultural orientation, and gender concordance within pairs. Logistic regression was used. Results: Overall, parental smoking was associated with offspring's smoking behaviors (eg, current smoking: odds ratio 2.33; 95% confidence interval 1.79-3.03), with little ethnic variation. We found dose-response associations between exposure to parental smoking and offspring's smoking. The associations were similar across different strata but stronger in gender-concordant pairs (3.16; 2.12-4.51 vs. 1.73; 1.15-2.59 in gender-discordant pairs; p-value for interaction .017). Conclusions: Parental smoking is associated with offspring's smoking behaviors in ethnic minority groups across different strata but particularly in gender-concordant pairs. Similar to majority groups, family influences matter to smoking behaviors in ethnic minority groups. Implications: Our findings have deepened our understanding of smoking behaviors among ethnic minority groups. Future studies should simultaneously consider societal factors and parental influences, to comprehensively understand their impact on smoking among ethnic minority groups. Also, smoking patterns among family members should be addressed in individual counselling, irrespective of ethnicity.

The relation between obesity and depressed mood in a multi-ethnic population. The HELIUS study.

PURPOSE: To examine the association between obesity and depressed mood in a large multi-ethnic population and check for consistency in this association across six ethnic groups. METHODS: Data of 21,030 persons (18-70 years) were sourced from the HELIUS study. Cross-sectional relationships between obesity measures [body mass index (kg/m2) and waist circumference (cm)] and depressed mood (PHQ-9 score ≥ 10) were analysed. Consistency of associations was investigated across ethnic groups by interaction terms (ethnicity*obesity measures) in basic (age, sex, education) and fully (health behaviours and somatic health) adjusted models. RESULTS: Obesity was prevalent in all ethnic groups, but varied substantially. After sociodemographic adjustment, obesity measures were associated with increased odds of depressed mood but this was inconsistent across ethnic groups. Obesity (BMI ≥ 30 or highest waist circumference quartile) was strongly and significantly associated with depressed mood in the Dutch [Odds Ratio (OR) = 1.72; 95% Confidence intervals (CI) 1.24-2.40, and OR = 1.86; 95% CI 1.38-2.50], respectively, and African Surinamese (OR = 1.60; 95% CI 1.29-1.98 and OR = 1.59; 95% CI 1.27-2.00, respectively) but had a weaker, non-significant association in other ethnic groups (South-Asian Surinamese, Ghanaian, Moroccan, Turkish groups). Adjustment for health behaviours and somatic health had limited effect on this pattern. CONCLUSION: Obesity was associated with a higher risk of depressed mood. However, ethnic differences were found: the obesity-depressed mood association was strong in the Dutch and African Surinamese populations, but not in other ethnic groups. Future studies should explore whether differential normative values or pathophysiology across ethnic groups explain why the obesity-depression association is inconsistent across ethnic groups.

Measurement invariance testing of the PHQ-9 in a multi-ethnic population in Europe: the HELIUS study.

BACKGROUND: In Western European countries, the prevalence of depressive symptoms is higher among ethnic minority groups, compared to the host population. We explored whether these inequalities reflect variance in the way depressive symptoms are measured, by investigating whether items of the PHQ-9 measure the same underlying construct in six ethnic groups in the Netherlands. METHODS: A total of 23,182 men and women aged 18-70 of Dutch, South-Asian Surinamese, African Surinamese, Ghanaian, Turkish or Moroccan origin were included in the HELIUS study and had answered to at least one of the PHQ-9 items. We conducted multiple group confirmatory factor analyses (MGCFA), with increasingly stringent model constraints (i.e. assessing Configural, Metric, Strong and Strict measurement invariance (MI)), and regression analysis, to confirm comparability of PHQ-9 items across ethnic groups. RESULTS: A one-factor model, where all nine items reflect a single underlying construct, showed acceptable model fit and was used for MI testing. In each subsequent step, change in goodness-of-fit measures did not exceed 0.015 (RMSEA) or 0.01 (CFI). Moreover, strict invariance models showed good or acceptable model fit (Men: RMSEA = 0.050; CFI = 0.985; Women: RMSEA = 0.058; CFI = 0.979), indicating between-group equality of item clusters, factor loadings, item thresholds and residual variances. Finally, regression analysis did not indicate potential ethnicity-related differential item functioning (DIF) of the PHQ-9. CONCLUSIONS: This study provides evidence of measurement invariance of the PHQ-9 regarding ethnicity, implying that the observed inequalities in depressive symptoms cannot be attributed to DIF.

What Cure Models Can Teach us About Genome-Wide Survival Analysis.

The aim of logistic regression is to estimate genetic effects on disease risk, while survival analysis aims to determine effects on age of onset. In practice, genetic variants may affect both types of outcomes. A cure survival model analyzes logistic and survival effects simultaneously. The aim of this simulation study is to assess the performance of logistic regression and traditional survival analysis under a cure model and to investigate the benefits of cure survival analysis. We simulated data under a cure model and varied the percentage of subjects at risk for disease (cure fraction), the logistic and survival effect sizes, and the contribution of genetic background risk factors. We then computed the error rates and estimation bias of logistic, Cox proportional hazards (PH), and cure PH analysis, respectively. The power of logistic and Cox PH analysis is sensitive to the cure fraction and background heritability. Our results show that traditional Cox PH analysis may erroneously detect age of onset effects if no such effects are present in the data. In the presence of genetic background risk even the cure model results in biased estimates of both the odds ratio and the hazard ratio. Cure survival analysis takes cure fractions into account and can be used to simultaneously estimate the effect of genetic variants on disease risk and age of onset. Since genome-wide cure survival analysis is not computationally feasible, we recommend this analysis for genetic variants that are significant in a traditional survival analysis.