Racialized Health Inequities: Quantifying Socioeconomic and Stress Pathways Using Moderated Mediation

Racism drives population health inequities by shaping the unequal distribution of key social determinants of health, such as socioeconomic resources and exposure to stressors. Research on interrelationships among race, socioeconomic resources, stressors, and health has proceeded along two lines that have largely remained separate: one examining differential effects of socioeconomic resources and stressors on health across racialized groups (moderation processes), and the other examining the role of socioeconomic resources and stressors in contributing to racial inequities in health (mediation processes). We conceptually and analytically integrate these areas using race theory and a novel moderated mediation approach to path analysis to formally quantify the extent to which an array of socioeconomic resources and stressors-collectively and individually-mediate racialized health inequities among a sample of older adults from the Health and Retirement Study. Our results yield theoretical contributions by showing how the socioeconomic status-health gradient and stress processes are racialized (24% of associations examined varied by race), substantive contributions by quantifying the extent of moderated mediation of racial inequities (approximately 70%) and the relative importance of various social factors, and methodological contributions by showing how commonly used simple mediation approaches that ignore racialized moderation processes overestimate-by between 5% and 30%-the collective roles of socioeconomic status and stressors in accounting for racial inequities in health.

Genome-wide Association Meta-analysis of Childhood and Adolescent Internalizing Symptoms

OBJECTIVE

To investigate the genetic architecture of internalizing symptoms in childhood and adolescence.

METHOD

In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument.

RESULTS

The meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa.

CONCLUSION

Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

Genetic association study of childhood aggression across raters, instruments, and age

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E-06), PCDH7 (P = 2.0E-06), and IPO13 (P = 2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg = 0.46 between self- and teacher-assessment to rg = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range [Formula: see text]: 0.19-1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg = ~-0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range [Formula: see text]: 0.46-0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.

Illness, Social Disadvantage, and Sexual Risk Behavior in Adolescence and the Transition to Adulthood

This study investigated the influence of illness on sexual risk behavior in adolescence and the transition to adulthood, both directly and through moderation of the impact of social disadvantage. We hypothesized positive effects for social disadvantages and illness on sexual risk behavior, consistent with the development of faster life history strategies among young people facing greater life adversity. Using the first two waves of the National Longitudinal Study of Adolescent to Adult Health, we developed a mixed-effects multinomial logistic regression model predicting sexual risk behavior in three comparisons: risky nonmonogamous sex versus safer nonmonogamous sex, versus monogamous sex, and versus being sexually inactive, by social characteristics, illness, interactions thereof, and control covariates. Multiple imputation was used to address a modest amount of missing data. Subjects reporting higher levels of illness had lower odds of having safer nonmonogamous sex (OR = 0.84, p < .001), monogamous sex (OR = 0.82, p < .001), and being sexually inactive (OR = 0.74, p < .001) versus risky nonmonogamous sex, relative to subjects in better health. Illness significantly moderated the sex (OR = 0.88, p < .01), race/ethnicity (e.g., OR = 1.21, p < .001), and childhood SES (OR = 0.94; p < .01) effects for the sexually inactive versus risky nonmonogamous sex comparison. Substantive findings were generally robust across waves and in sensitivity analyses. These findings offer general support for the predictions of life history theory. Illness and various social disadvantages are associated with increased sexual risk behavior in adolescence and the transition to adulthood. Further, analyses indicate that the buffering effects of several protective social statuses against sexual risk-taking are substantially eroded by illness.

A large-scale genome-wide association study meta-analysis of cannabis use disorder

BACKGROUND

Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.

METHODS

To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations.

FINDINGS

We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia.

INTERPRETATION

These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.

FUNDING

National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

Genome-Wide Association Study of Suicide Death and Polygenic Prediction of Clinical Antecedents

OBJECTIVE

Death by suicide 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 sizable suicide death cohorts available for analysis. To address this limitation, the authors conducted the first comprehensive genomic analysis of suicide death using previously unpublished genotype data from a large population-ascertained cohort.

METHODS

The analysis sample comprised 3,413 population-ascertained case subjects of European ancestry and 14,810 ancestrally matched control subjects. Analytical methods included principal component 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, and polygenic score analyses, as well as single-nucleotide polymorphism (SNP) heritability and genetic correlation estimation using linkage disequilibrium score regression.

RESULTS

Genome-wide association analysis identified two genome-wide significant loci (involving six SNPs: rs34399104, rs35518298, rs34053895, rs66828456, rs35502061, and rs35256367). Gene-based analyses implicated 22 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide death heritability was estimated at an h2SNP value of 0.25 (SE=0.04) and a value of 0.16 (SE=0.02) when converted to a liability scale. Notably, suicide polygenic scores were significantly predictive across training and test sets. Polygenic scores for several other psychiatric disorders and psychological traits were also predictive, particularly scores for behavioral disinhibition and major depressive disorder.

CONCLUSIONS

Multiple genome-wide significant loci and genes were identified and polygenic score prediction of suicide death case-control status was demonstrated, adjusting for ancestry, in independent training and test sets. Additionally, the suicide death sample was found to have increased genetic risk for behavioral disinhibition, major depressive disorder, depressive symptoms, autism spectrum disorder, psychosis, and alcohol use disorder compared with the control sample.

Molecular Genetic Risk for Psychosis Is Associated With Psychosis Risk Symptoms in a Population-Based UK Cohort: Findings From Generation Scotland

OBJECTIVE

Subthreshold psychosis risk symptoms in the general population may be associated with molecular genetic risk for psychosis. This study sought to optimize the association of risk symptoms with genetic risk for psychosis in a large population-based cohort in the UK (N = 9104 individuals 18-65 years of age) by properly accounting for population stratification, factor structure, and sex.

METHODS

The newly expanded Generation Scotland: Scottish Family Health Study includes 5391 females and 3713 males with age M [SD] = 45.2 [13] with both risk symptom data and genetic data. Subthreshold psychosis symptoms were measured using the Schizotypal Personality Questionnaire-Brief (SPQ-B) and calculation of polygenic risk for schizophrenia was based on 11 425 349 imputed common genetic variants passing quality control. Follow-up examination of other genetic risks included attention-deficit hyperactivity disorder (ADHD), autism, bipolar disorder, major depression, and neuroticism.

RESULTS

Empirically derived symptom factor scores reflected interpersonal/negative symptoms and were positively associated with polygenic risk for schizophrenia. This signal was largely sex specific and limited to males. Across both sexes, scores were positively associated with neuroticism and major depressive disorder.

CONCLUSIONS

A data-driven phenotypic analysis enabled detection of association with genetic risk for schizophrenia in a population-based sample. Multiple polygenic risk signals and important sex differences suggest that genetic data may be useful in improving future phenotypic risk assessment.

Early external-environmental and internal-health predictors of risky sexual and aggressive behavior in adolescence: An integrative approach

External predictive adaptive response (PAR) models assume that developmental exposures to stress carry predictive information about the future state of the environment, and that development of a faster life history (LH) strategy in this context functions to match the individual to this expected harsh state. More recently internal PAR models have proposed that early somatic condition (i.e., physical health) critically regulates development of LH strategies to match expected future somatic condition. Here we test the integrative hypothesis that poor physical health mediates the relation between early adversity and faster LH strategies. Data were drawn from a longitudinal study (birth to age 16; N = 1,388) of mostly African American participants with prenatal substance exposure. Results demonstrated that both external environmental conditions early in life (prenatal substance exposure, socioeconomic adversity, caregiver distress/depression, and adverse family functioning) and internal somatic condition during preadolescence (birthweight/gestational age, physical illness) uniquely predicted the development of faster LH strategies in adolescence (as indicated by more risky sexual and aggressive behavior). Consistent with the integrative hypothesis, the effect of caregiver distress/depression on LH strategy was mostly mediated by worse physical health. Discussion highlights the implications of these findings for theory and research on stress, development, and health.

Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium

To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR z = -5.39, p = 7.2 × 10-8). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N > 360,000) found association of this variant with propensity to use dietary supplements (p = 1.68 × 10-8). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (EUR + AFR z = 4.69, p = 10-6), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (AFR z = 5.55, p = 2.9 × 10-8) and a significant association with musculoskeletal disorders in the UK Biobank (p = 4.88 × 10-7). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (n = 466,571) was positively associated with OD (OD vs. unexposed controls, p = 8.1 × 10-5; OD cases vs. exposed controls, p = 0.054) and OE (exposed vs. unexposed controls, p = 3.6 × 10-5). A PRS based on a GWAS of neuroticism (n = 390,278) was positively associated with OD (OD vs. unexposed controls, p = 3.2 × 10-5; OD vs. exposed controls, p = 0.002) but not with OE (p = 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction.

Transition preparation activities among families of youth on the autism spectrum: Preliminary study using repeated assessments across a school year

Much is still unknown about the transition to adulthood for youth with autism spectrum disorder (ASD), including what preparation activities best support positive adult outcomes. Parents play a crucial role in the transition planning and preparation process, yet the existing literature lacks detailed information about parent perceptions about transition preparation activities. To examine family transition preparation activities, we conducted a ten-month study of the transition preparation process of 15 families of youth with ASD across an academic year. Youth were ages 14-17 and 93% male. We collected data on transition preparation activity time spent and parent satisfaction over twenty data collection points. We used multi-level modeling to determine longitudinal trajectories of parent-reported preparation for the transition to adulthood based on endorsed transition preparation activities. Findings from this preliminary study revealed that discussions about the future were the most commonly endorsed activities, while social activities were most associated with increased parental perception of transition preparation over time. This study expands understanding of various transition preparation activities engaged in by families of youth with ASD during high school, though research with a larger and more diverse sample is needed to extend findings.

Pathway-based polygene risk for severe depression implicates drug metabolism in CONVERGE

BACKGROUND

The Psychiatric Genomics Consortium (PGC) has made major advances in the molecular etiology of MDD, confirming that MDD is highly polygenic. Pathway enrichment results from PGC meta-analyses can also be used to help inform molecular drug targets. Prior to any knowledge of molecular biomarkers for MDD, drugs targeting molecular pathways (MPs) proved successful in treating MDD. It is possible that examining polygenicity within specific MPs implicated in MDD can further refine molecular drug targets.

METHODS

Using a large case-control GWAS based on low-coverage whole genome sequencing (N = 10 640) in Han Chinese women, we derived polygenic risk scores (PRS) for MDD and for MDD specific to each of over 300 MPs previously shown to be relevant to psychiatric diagnoses. We then identified sets of PRSs, accounting for critical covariates, significantly predictive of case status.

RESULTS

Over and above global MDD polygenic risk, polygenic risk within the GO: 0017144 drug metabolism pathway significantly predicted recurrent depression after multiple testing correction. Secondary transcriptomic analysis suggests that among genes in this pathway, CYP2C19 (family of Cytochrome P450) and CBR1 (Carbonyl Reductase 1) might be most relevant to MDD. Within the cases, pathway-based risk was additionally associated with age at onset of MDD.

CONCLUSIONS

Results indicate that pathway-based risk might inform etiology of recurrent major depression. Future research should examine whether polygenicity of the drug metabolism gene pathway has any association with clinical presentation or treatment response. We discuss limitations to the generalizability of these preliminary findings, and urge replication in future research.

Hazardous air pollutants are associated with worse performance in reading, math, and science among US primary schoolchildren

Emerging evidence demonstrates that chronic exposure to air pollution may negatively impact children's cognitive processing and memory. Little is currently known about how air pollution impacts individual children's academic performance through time. Academic performance is practically important, given its linkage to children's future life course trajectories. Individual-level, longitudinal data from 16,000 US primary school students are combined with a tract-level hazardous air pollutant (HAP) measure to assess how kindergarten exposures are associated with competencies in reading, math and science through third grade. We employed linear mixed models with repeated measures within children (e.g., five math tests across four years), clustering within census tracts, and random effects specified at the child- and census tract-levels. Controlling for a comprehensive list of time variant and time invariant covariates, we found statistically significant associations between higher levels of HAPs and lower reading (b = -0.02; p < 0.05), math (b = -0.02; p < 0.001), and science (b = -0.05; p < 0.001) scores. These negative effects of pollution on academic competency in the early primary school years add to the weight of evidence that air pollution harms children's academic potential.

Sexual Orientation Disparities in Pregnancy and Infant Outcomes

Objectives Little is known about maternal and infant health among sexual minority women (SMW), despite the large body of research documenting their multiple preconception risk factors. This study used data from the 2006-2015 National Survey of Family Growth (NSFG) to investigate sexual orientation inequities in pregnancy and birth outcomes, including miscarriage, stillbirth, preterm birth, and birth weight. Methods Women reported 19,955 study eligible pregnancies and 15,996 singleton live births. Sexual orientation was measured using self-reported identity and histories of same-sex sexual experiences (heterosexual-WSM [women who only report sex with men]; heterosexual-WSW [women who report sex with women]; bisexual, and lesbian). Logistic regression models were used that adjusted for several maternal characteristics. Results Compared to heterosexual-WSM, heterosexual-WSW (OR 1.25, 95% CI 1.00-1.58) and bisexual and lesbian women (OR 1.77, 95% CI 1.34-2.35) were more likely to report miscarriage, and bisexual and lesbian women were more likely to report a pregnancy ending in stillbirth (OR 2.85, 95% CI 1.40-5.83). Lesbian women were more likely to report low birth weight infants (OR 2.64, 95% CI 1.38-5.07) and bisexual and lesbian women were more likely to report very preterm births (OR 1.84, 95% CI 1.11-3.04) compared to heterosexual-WSM. Conclusions for Practice This study documents significant sexual orientation inequities in pregnancy and birth outcomes. More research is needed to understand the mechanisms that underlie disparate outcomes and to develop interventions to improve sexual minority women's maternal and infant health.

Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

Bleeding, cramping, and satisfaction among new copper IUD users: A prospective study

OBJECTIVE

We assess change in bleeding, cramping, and IUD 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 six-level ordinal scale. We used multiple imputation to address nonrandom attrition. Structural equation models for count and ordered outcomes were used to model bleeding, cramping, and IUD satisfaction growth curves over the six monthly repeated assessments.

RESULTS

Bleeding significantly decreased (approximately 23%) 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 notably 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 across the study (t = -2.31, p<0.05) and at 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.

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.

The Impact of Sexual Satisfaction, Functioning, and Perceived Contraceptive Effects on Sex Life on IUD and Implant Continuation at 1 Year

INTRODUCTION

Contraceptives improve women's lives and public health, but many women discontinue their contraceptive method owing to dissatisfaction. An underexamined aspect of contraceptive discontinuation is sexual acceptability, or how contraception affects sexual experiences. Investigators' aims were two-fold: 1) to document changes in multiple domains of women's sexual experiences with their intrauterine device (IUD) or contraceptive implant over time and 2) to examine whether these sexuality factors were associated with method continuation at 12 months.

METHODS

We enrolled 200 eligible family planning clients and collected data at baseline and at 1, 3, 6, and 12 months. Sexual acceptability measures included the Female Sexual Function Index-6, the New Sexual Satisfaction Scale, and participants' perceptions of whether their contraceptive method had had a neutral, positive, or negative effect on their sex life. Survival analysis and Cox regression with time-varying covariates related sexuality measures to method continuation over time while controlling for other relevant factors.

RESULTS

Among 193 women who received an IUD or implant, 20% selected the copper IUD, 46% the levonorgestrel IUD, and 34% the etonogestrel implant. Ten percent discontinued their method during the year. Although changes in Female Sexual Function Index-6 and New Sexual Satisfaction Scale scores were not associated with discontinuation, individuals who perceived that their method detracted from their sexual experience had significantly higher removal rates than those who reported no sexual changes or positive sexual changes (adjusted hazard ratio, 8.04; 95% CI, 1.53-42.24), even when controlling for method type, bleeding changes, and a variety of covariates and controls.

CONCLUSIONS

Although limited by the small sample of discontinuers, we found that women's perceptions of how their method affects their sex life were associated with contraceptive continuation over time. Sexual acceptability should receive more attention in both contraceptive research and counseling.

Incorporating epigenetic mechanisms to advance fetal programming theories

Decades of fetal programming research indicates that we may be able to map the origins of many physical, psychological, and medical variations and morbidities before the birth of the child. While great strides have been made in identifying associations between prenatal insults, such as undernutrition or psychosocial stress, and negative developmental outcomes, far less is known about how adaptive responses to adversity regulate the developing phenotype to match stressful conditions. As the application of epigenetic methods to human behavior has exploded in the last decade, research has begun to shed light on the role of epigenetic mechanisms in explaining how prenatal conditions shape later susceptibilities to mental and physical health problems. In this review, we describe and attempt to integrate two dominant fetal programming models: the cumulative stress model (a disease-focused approach) and the match-mismatch model (an evolutionary-developmental approach). In conjunction with biological sensitivity to context theory, we employ these two models to generate new hypotheses regarding epigenetic mechanisms through which prenatal and postnatal experiences program child stress reactivity and, in turn, promote development of adaptive versus maladaptive phenotypic outcomes. We conclude by outlining priority questions and future directions for the fetal programming field.

Polygenic prediction of the phenome, across ancestry, in emerging adulthood

BACKGROUND

Identifying genetic relationships between complex traits in emerging adulthood can provide useful etiological insights into risk for psychopathology. College-age individuals are under-represented in genomic analyses thus far, and the majority of work has focused on the clinical disorder or cognitive abilities rather than normal-range behavioral outcomes.

METHODS

This study examined a sample of emerging adults 18-22 years of age (N = 5947) to construct an atlas of polygenic risk for 33 traits predicting relevant phenotypic outcomes. Twenty-eight hypotheses were tested based on the previous literature on samples of European ancestry, and the availability of rich assessment data allowed for polygenic predictions across 55 psychological and medical phenotypes.

RESULTS

Polygenic risk for schizophrenia (SZ) in emerging adults predicted anxiety, depression, nicotine use, trauma, and family history of psychological disorders. Polygenic risk for neuroticism predicted anxiety, depression, phobia, panic, neuroticism, and was correlated with polygenic risk for cardiovascular disease.

CONCLUSIONS

These results demonstrate the extensive impact of genetic risk for SZ, neuroticism, and major depression on a range of health outcomes in early adulthood. Minimal cross-ancestry replication of these phenomic patterns of polygenic influence underscores the need for more genome-wide association studies of non-European populations.

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

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.

Opportunities for an enhanced integration of neuroscience and genomics

Neuroimaging and genetics are two rapidly expanding fields of research. Thoughtful integration of these areas is critical for ongoing large-scale research into the genetic mechanisms underlying brain structure, function, and development. Neuroimaging genetics has been slow to evolve relative to psychiatric genetics research, and some may be unaware that new statistical methods allow for the genomic analysis of more modestly-sized imaging samples. We present a broad overview of the extant imaging genetics literature, provide an interpretation of the major problems surrounding the integration of neuroimaging and genetics, discuss the influence and impact of genetics consortia, and suggest statistical genetic analyses that expand the repertoire of imaging researchers amassing rich behavioral data in modestly-sized samples. Specific attention is paid to the creative use of polygenic risk scoring in imaging genetic analyses, with primers on the most current risk scoring applications.

Age of onset and family history as indicators of polygenic risk for major depression

BACKGROUND

The extent to which earlier age of onset (AO) is a reflection of increased genetic risk for major depression (MD) is still unknown. Previous biometrical research has provided mixed empirical evidence for the genetic overlap of AO with MD. If AO is demonstrated to be relevant to molecular polygenic risk for MD, incorporation of AO as a phenotype could enhance future genetic studies.

METHODS

This research estimated the SNP-based heritability of AO in the China, Oxford and VCU Experimental Research on Genetic Epidemiology (CONVERGE) case-control sample (N = 9,854; MD case, n = 4,927). Common single nucleotide polymorphism heritability of MD was also examined across both high and low median-split AO groups, and best linear unbiased predictor (BLUP) scores of polygenic risk, in split-halves, were used to predict AO. Distributions of genetic risk across early and late AO were compared, and presence of self-reported family history (FH) of MD was also examined as a predictor of AO.

RESULTS

AO was not significantly heritable and polygenic risk derived from the aggregated effects of common genetic variants did not significantly predict AO in any analysis. AO was modestly but significantly lower in cases with a first-degree genetic FH of MD.

CONCLUSIONS

Findings indicate that AO is associated with greater self-reported genetic risk for MD in cases, yet not associated with common variant polygenic risk for MD. Future studies of early MD may benefit more from the examination of important moderating variables such as early life events.

Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence

BACKGROUND

Previous 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.

METHODS

We 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.

RESULTS

No 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 (p = 1.47 × 10^-5 ; q = 0.019), an alcohol dehydrogenase, and ADORA1 (p = 5.29 × 10^-5 ; q = 0.035), an adenosine receptor that belongs to a G-protein-coupled receptor gene family.

CONCLUSIONS

To 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.

The Rate of Change in Alcohol Misuse Across Adolescence is Heritable

BACKGROUND

Alcohol 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.

METHODS

Participants 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 (N = 4,545, 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 (N = 3,380), followed by secondary genetic analyses.

RESULTS

No individual marker met genomewide significance criteria. Top markers mapped to biologically plausible candidate genes. The slope term was moderately heritable (h²_SNP = 0.26, p = 0.009), and replication attempts using a meta-analysis of independent samples provided support for implicated variants at the aggregate level. Nominally significant (p < 0.00001) markers mapped to putatively active genomic regions in brain tissue more frequently than expected by chance.

CONCLUSIONS

These 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.

Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion.

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

AIMS

This 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.

METHOD

DSM 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).

RESULTS

Among 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.

CONCLUSIONS

Results 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.

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

INTRODUCTION

Genome-wide association study meta-analyses have robustly implicated three loci that affect susceptibility for smoking: CHRNA5\CHRNA3\CHRNB4, CHRNB3\CHRNA6 and EGLN2\CYP2A6. 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.

METHODS

We employed targeted capture of the CHRNA5\CHRNA3\CHRNB4, CHRNB3\CHRNA6, and EGLN2\CYP2A6 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.

RESULTS

In 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 CHRNB3\CHRNA6 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.

CONCLUSIONS

We found that multiple variants implicating multiple processes explain the signal. Some variants can be prioritized for functional follow-up.

Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder

IMPORTANCE

Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63,000 participants (including MDD cases).

OBJECTIVES

To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD.

DESIGN, SETTING, AND PARTICIPANTS

Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63,661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014.

MAIN OUTCOMES AND MEASURES

Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts.

RESULTS

A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10-9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10-8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10-12 < P < .05) and MDD (4.02 × 10-9 < P < .05) in the 2 other cohorts.

CONCLUSIONS AND RELEVANCE

This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.

Refinement of schizophrenia GWAS loci using methylome-wide association data

Recent genome-wide association studies (GWAS) have made substantial progress in identifying disease loci. The next logical step is to design functional experiments to identify disease mechanisms. This step, however, is often hampered by the large size of loci identified in GWAS that is caused by linkage disequilibrium between SNPs. In this study, we demonstrate how integrating methylome-wide association study (MWAS) results with GWAS findings can narrow down the location for a subset of the putative casual sites. We use the disease schizophrenia as an example. To handle "data analytic" variation, we first combined our MWAS results with two GWAS meta-analyses (N = 32,143 and 21,953), that had largely overlapping samples but different data analysis pipelines, separately. Permutation tests showed significant overlapping association signals between GWAS and MWAS findings. This significant overlap justified prioritizing loci based on the concordance principle. To further ensure that the methylation signal was not driven by chance, we successfully replicated the top three methylation findings near genes SDCCAG8, CREB1 and ATXN7 in an independent sample using targeted pyrosequencing. In contrast to the SNPs in the selected region, the methylation sites were largely uncorrelated explaining why the methylation signals implicated much smaller regions (median size 78 bp). The refined loci showed considerable enrichment of genomic elements of possible functional importance and suggested specific hypotheses about schizophrenia etiology. Several hypotheses involved possible variation in transcription factor-binding efficiencies.

Genetics of adverse reactions to haloperidol in a mouse diallel: a drug-placebo experiment and Bayesian causal analysis

Haloperidol is an efficacious antipsychotic drug that has serious, unpredictable motor side effects that limit its utility and cause noncompliance in many patients. Using a drug-placebo diallel of the eight founder strains of the Collaborative Cross and their F1 hybrids, we characterized aggregate effects of genetics, sex, parent of origin, and their combinations on haloperidol response. Treating matched pairs of both sexes with drug or placebo, we measured changes in the following: open field activity, inclined screen rigidity, orofacial movements, prepulse inhibition of the acoustic startle response, plasma and brain drug level measurements, and body weight. To understand the genetic architecture of haloperidol response we introduce new statistical methodology linking heritable variation with causal effect of drug treatment. Our new estimators, "difference of models" and "multiple-impute matched pairs", are motivated by the Neyman-Rubin potential outcomes framework and extend our existing Bayesian hierarchical model for the diallel (Lenarcic et al. 2012). Drug-induced rigidity after chronic treatment was affected by mainly additive genetics and parent-of-origin effects (accounting for 28% and 14.8% of the variance), with NZO/HILtJ and 129S1/SvlmJ contributions tending to increase this side effect. Locomotor activity after acute treatment, by contrast, was more affected by strain-specific inbreeding (12.8%). In addition to drug response phenotypes, we examined diallel effects on behavior before treatment and found not only effects of additive genetics (10.2-53.2%) but also strong effects of epistasis (10.64-25.2%). In particular: prepulse inhibition showed additivity and epistasis in about equal proportions (26.1% and 23.7%); there was evidence of nonreciprocal epistasis in pretreatment activity and rigidity; and we estimated a range of effects on body weight that replicate those found in our previous work. Our results provide the first quantitative description of the genetic architecture of haloperidol response in mice and indicate that additive, dominance-like inbreeding and parent-of-origin effects contribute strongly to treatment effect heterogeneity for this drug.

Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization

Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In this study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine (MA)-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate, FDR <0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent MA levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization.

Large-scale neurochemical metabolomics analysis identifies multiple compounds associated with methamphetamine exposure

Methamphetamine (MA) is an illegal stimulant drug of abuse with serious negative health consequences. The neurochemical effects of MA have been partially characterized, with a traditional focus on classical neurotransmitter systems. However, these directions have not yet led to novel drug treatments for MA abuse or toxicity. As an alternative approach, we describe here the first application of metabolomics to investigate the neurochemical consequences of MA exposure in the rodent brain. We examined single exposures at 3 mg/kg and repeated exposures at 3 mg/kg over 5 days in eight common inbred mouse strains. Brain tissue samples were assayed using high-throughput gas and liquid chromatography mass spectrometry, yielding quantitative data on >300 unique metabolites. Association testing and false discovery rate control yielded several metabolome-wide significant associations with acute MA exposure, including compounds such as lactate (p = 4.4 × 10^-5, q = 0.013), tryptophan (p = 7.0 × 10^-4, q = 0.035) and 2-hydroxyglutarate (p = 1.1 × 10^-4, q = 0.022). Secondary analyses of MA-induced increase in locomotor activity showed associations with energy metabolites such as succinate (p = 3.8 × 10^-7). Associations specific to repeated (5 day) MA exposure included phosphocholine (p = 4.0 × 10^-4, q = 0.087) and ergothioneine (p = 3.0 × 10^-4, q = 0.087). Our data appear to confirm and extend existing models of MA action in the brain, whereby an initial increase in energy metabolism, coupled with an increase in behavioral locomotion, gives way to disruption of mitochondria and phospholipid pathways and increased endogenous antioxidant response. Our study demonstrates the power of comprehensive MS-based metabolomics to identify drug-induced changes to brain metabolism and to develop neurochemical models of drug effects.

Genotype-based ancestral background consistently predicts efficacy and side effects across treatments in CATIE and STAR*D

Only a subset of patients will typically respond to any given prescribed drug. The time it takes clinicians to declare a treatment ineffective leaves the patient in an impaired state and at unnecessary risk for adverse drug effects. Thus, diagnostic tests robustly predicting the most effective and safe medication for each patient prior to starting pharmacotherapy would have tremendous clinical value. In this article, we evaluated the use of genetic markers to estimate ancestry as a predictive component of such diagnostic tests. We first estimated each patient’s unique mosaic of ancestral backgrounds using genome-wide SNP data collected in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) (n = 765) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) (n = 1892). Next, we performed multiple regression analyses to estimate the predictive power of these ancestral dimensions. For 136/89 treatment-outcome combinations tested in CATIE/STAR*D, results indicated 1.67/1.84 times higher median test statistics than expected under the null hypothesis assuming no predictive power (p<0.01, both samples). Thus, ancestry showed robust and pervasive correlations with drug efficacy and side effects in both CATIE and STAR*D. Comparison of the marginal predictive power of MDS ancestral dimensions and self-reported race indicated significant improvements to model fit with the inclusion of MDS dimensions, but mixed evidence for self-reported race. Knowledge of each patient’s unique mosaic of ancestral backgrounds provides a potent immediate starting point for developing algorithms identifying the most effective and safe medication for a wide variety of drug-treatment response combinations. As relatively few new psychiatric drugs are currently under development, such personalized medicine offers a promising approach toward optimizing pharmacotherapy for psychiatric conditions.

Race-ethnicity and health trajectories: tests of three hypotheses across multiple groups and health outcomes

Racial-ethnic disparities in static levels of health are well documented. Less is known about racial-ethnic differences in age trajectories of health. The few studies on this topic have examined only single health outcomes and focused on black-white disparities. This study extends prior research by using a life course perspective, panel data from the Health and Retirement Study, and multilevel growth curve models to investigate racial-ethnic differences in the trajectories of serious conditions and functional limitations among blacks, Mexican Americans, and whites. We test three hypotheses on the nature of racial-ethnic disparities in health across the life course (aging-as-leveler, persistent inequality, and cumulative disadvantage). Results controlling for mortality selection reveal that support for the hypotheses varies by health outcome, racial-ethnic group, and life stage. Controlling for childhood socioeconomic status, adult social and economic resources, and health behaviors reduces but does not eliminate racial-ethnic disparities in health trajectories.

Pharmacogenomic study of side-effects for antidepressant treatment options in STAR*D

BACKGROUND

Understanding individual differences in susceptibility to antidepressant therapy side-effects is essential to optimize the treatment of depression.

METHOD

We performed genome-wide association studies (GWAS) to search for genetic variation affecting the susceptibility to side-effects. The analysis sample consisted of 1439 depression patients, successfully genotyped for 421K single nucleotide polymorphisms (SNPs), from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Outcomes included four indicators of side-effects: general side-effect burden, sexual side-effects, dizziness and vision/hearing-related side-effects. Our criterion for genome-wide significance was a prespecified threshold ensuring that, on average, only 10% of the significant findings are false discoveries.

RESULTS

Thirty-four SNPs satisfied this criterion. The top finding indicated that 10 SNPs in SACM1L mediated the effects of bupropion on sexual side-effects (p = 4.98 × 10(-7), q = 0.023). Suggestive findings were also found for SNPs in MAGI2, DTWD1, WDFY4 and CHL1.

CONCLUSIONS

Although our findings require replication and functional validation, this study demonstrates the potential of GWAS to discover genes and pathways that could mediate adverse effects of antidepressant medication.

The glial cell modulators, ibudilast and its amino analog, AV1013, attenuate methamphetamine locomotor activity and its sensitization in mice

Over 800,000 Americans abuse the psychomotor stimulant, methamphetamine, yet its abuse is without an approved medication. Methamphetamine induces hypermotor activity, and sensitization to this effect is suggested to represent aspects of the addiction process. Methamphetamine's regulation of 3'-5'-cyclic adenosine monophosphate (cAMP) levels may be partially responsible for its behavioral effects, and compounds that inhibit phosphodiesterase (PDE), the enzyme that degrades cAMP, can alter methamphetamine-induced behaviors. Methamphetamine also activates glial cells and causes a subsequent increase in pro-inflammatory cytokine levels. Modulation of glial cell activation is associated with changes in behavioral responses, and substances that oppose inflammatory activity can attenuate drug-induced behaviors. Ibudilast (aka AV411; 3-isobutyryl-2-isopropylpyrazolo-[1,5-a]pyridine), inhibits both PDE and glial pro-inflammatory activity. Ibudilast's amino analog, AV1013, modulates similar glial targets but negligibly inhibits PDE. The present study determined whether ibudilast and AV1013 would attenuate methamphetamine-induced locomotor activity and its sensitization in C57BL/6J mice. Mice were treated b.i.d. with ibudilast (1.8-13 mg/kg), AV1013 (10-56 mg/kg) or their vehicles intraperitoneally for 7 days, beginning 48 h before 5 days of daily 1-h locomotor activity tests. Each test was initiated by either a methamphetamine (3 mg/kg) or a saline injection. Ibudilast significantly (P<0.05) reduced the acute, chronic, and sensitization effects of methamphetamine's locomotor activity without significantly affecting activity by itself. AV1013 had similar anti-methamphetamine effects, suggesting that glial cell activity, by itself, can modulate methamphetamine's effects and perhaps serve as a medication target for its abuse.

Racial differences in depression trajectories among older women: socioeconomic, family, and health influences

Despite recent increases in life course research on mental illness, important questions remain about the social patterning of, and explanations for, depression trajectories among women in later life. The authors investigate competing theoretical frameworks for the age patterning of depressive symptoms and the physical health, socioeconomic, and family mechanisms differentiating black and white women. Using data from the National Longitudinal Survey of Mature Women, the authors use linear mixed (growth curve) models to estimate trajectories of distress for women aged 52 to 81 years (N = 3,182). The results demonstrate that: (1) there are persistently higher levels of depressive symptoms among black women relative to white women throughout later life; (2) physical health and socioeconomic status account for much of the racial gap in depressive symptoms; and (3) marital status moderates race differences in distress. The findings highlight the importance of physical health, family, and socioeconomic status in racial disparities in mental health.

Analysis of efficacy and side effects in CATIE demonstrates drug response subgroups and potential for personalized medicine

OBJECTIVE

This study aims to improve understanding of antipsychotic non/response and assess the potential for personalized schizophrenia treatment.

METHODS

We used data from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE). Efficacy measures included the Positive and Negative Syndrome Scale (PANSS) and neurocognitive functioning. Side effect measures included weight, lipids, glucose, heart rate and QT prolongation. Latent class analysis was conducted for each of the five drugs on the individual treatment effects to study whether there were subgroups of drug responders. The posterior probabilities of belonging to a particular response group were correlated across drugs to examine if patients not responding to one drug are likely to respond to a different drug and whether response to one drug may help to predict response to another drug.

RESULTS

We identified four qualitatively distinct response groups: Optimal Responders, Average Responders, Global Responders and Non-Responders. Different patterns of correlations with demographics and clinical variables across classes provided further support for the validity of these groups. The low correlations between posterior probabilities of the same response groups across drugs implied that patients generally belonged to different response groups for different drugs.

CONCLUSIONS

Our results demonstrate the existence of subgroups of patients characterized by distinct patterns of drug response. Further, findings suggest that patients who experience a poor response to one drug may be an optimal responder to another antipsychotic. Taken together these findings demonstrate the potential to personalize schizophrenia treatment and highlight the importance of identifying better predictors of drug response.

Genomewide pharmacogenomic study of metabolic side effects to antipsychotic drugs

Understanding individual differences in the susceptibility to metabolic side effects as a response to antipsychotic therapy is essential to optimize the treatment of schizophrenia. Here, we perform genomewide association studies (GWAS) to search for genetic variation affecting the susceptibility to metabolic side effects. The analysis sample consisted of 738 schizophrenia patients, successfully genotyped for 492K single nucleotide polymorphisms (SNPs), from the genomic subsample of the Clinical Antipsychotic Trial of Intervention Effectiveness study. Outcomes included 12 indicators of metabolic side effects, quantifying antipsychotic-induced change in weight, blood lipids, glucose and hemoglobin A1c, blood pressure and heart rate. Our criterion for genomewide significance was a pre-specified threshold that ensures, on average, only 10% of the significant findings are false discoveries. A total of 21 SNPs satisfied this criterion. The top finding indicated that a SNP in Meis homeobox 2 (MEIS2) mediated the effects of risperidone on hip circumference (q=0.004). The same SNP was also found to mediate risperidone's effect on waist circumference (q=0.055). Genomewide significant finding were also found for SNPs in PRKAR2B, GPR98, FHOD3, RNF144A, ASTN2, SOX5 and ATF7IP2, as well as in several intergenic markers. PRKAR2B and MEIS2 both have previous research indicating metabolic involvement, and PRKAR2B has previously been shown to mediate antipsychotic response. Although our findings require replication and functional validation, this study shows the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antipsychotic medication.

Genome-wide pharmacogenomic study of neurocognition as an indicator of antipsychotic treatment response in schizophrenia

Neurocognitive deficits are a core feature of schizophrenia and, therefore, represent potentially critical outcome variables for assessing antipsychotic treatment response. We performed genome-wide association studies (GWAS) with 492K single nucleotide polymorphisms (SNPs) in a sample of 738 patients with schizophrenia from the Clinical Antipsychotic Trials of Intervention Effectiveness study. Outcome variables consisted of a neurocognitive battery administered at multiple time points over an 18-month period, measuring processing speed, verbal memory, vigilance, reasoning, and working memory domains. Genetic mediation of improvements in each of these five domains plus a composite neurocognitive measure was assessed for each of five antipsychotics (olanzapine, perphenazine, quetiapine, risperidone, and ziprasidone). Six SNPs achieved genome-wide significance using a pre-specified threshold that ensures, on average, only 1 in 10 findings is a false discovery. These six SNPs were located within, or in close proximity to, genes EHF, SLC26A9, DRD2, GPR137B, CHST8, and IL1A. The more robust findings, that is those significant across multiple neurocognitive domains and having adjacent SNPs showing evidence for association, were rs286913 at the EHF gene (p-value 6.99 × 10(-8), q-value 0.034, mediating the effects of ziprasidone on vigilance), rs11240594 at SLC26A9 (p-value 1.4 × 10(-7), q-value 0.068, mediating the effects of olanzapine on processing speed), and rs11677416 at IL1A (p-value 6.67 × 10(-7), q-value 0.081, mediating the effects of olanzapine on working memory). This study has generated several novel candidate genes for antipsychotic response. However, our findings will require replication and functional validation. To facilitate replication efforts, we provide all GWAS p-values for download.

Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics

Schizophrenia is an often devastating neuropsychiatric illness. Understanding the genetic variation affecting response to antipsychotics is important to develop novel diagnostic tests to match individual schizophrenia patients to the most effective and safe medication. In this study, we use a genome-wide approach to detect genetic variation underlying individual differences in response to treatment with the antipsychotics olanzapine, quetiapine, risperidone, ziprasidone and perphenazine. Our sample consisted of 738 subjects with DSM-IV schizophrenia who took part in the Clinical Antipsychotic Trials of Intervention Effectiveness. Subjects were genotyped using the Affymetrix 500 K genotyping platform plus a custom 164 K chip to improve genome-wide coverage. Treatment outcome was measured using the Positive and Negative Syndrome Scale. Our criterion for genome-wide significance was a prespecified threshold that ensures that, on an average, only 10% of the significant findings are false discoveries. The top statistical result reached significance at our prespecified threshold and involved a single-nucleotide polymorphism (SNP) in an intergenic region on chromosome 4p15. In addition, SNPs in Ankyrin Repeat and Sterile Alpha Motif Domain-Containing Protein 1B (ANKS1B) and in the Contactin-Associated Protein-Like 5 gene (CNTNAP5), which mediated the effects of olanzapine and risperidone on Negative symptoms, were very close to our threshold for declaring significance. The most significant SNP in CNTNAP5 is nonsynonymous, giving rise to an amino-acid substitution. In addition to highlighting our top results, we provide all P-values for download as a resource for investigators with the requisite samples to carry out replication. This study demonstrates the potential of genome-wide association studies to discover novel genes that mediate the effects of antipsychotics, which could eventually help to tailor drug treatment to schizophrenic patients.

Antipsychotic-induced vacuous chewing movements and extrapyramidal side effects are highly heritable in mice

Pharmacogenomics is yet to fulfill its promise of manifestly altering clinical medicine. As one example, a predictive test for tardive dyskinesia (TD) (an adverse drug reaction consequent to antipsychotic exposure) could greatly improve the clinical treatment of schizophrenia but human studies are equivocal. A complementary approach is the mouse-then-human design in which a valid mouse model is used to identify susceptibility loci, which are subsequently tested in human samples. We used inbred mouse strains from the Mouse Phenome Project to estimate the heritability of haloperidol-induced activity and orofacial phenotypes. In all, 159 mice from 27 inbred strains were chronically treated with haloperidol (3 mg kg(-1) per day via subdermal slow-release pellets) and monitored for the development of vacuous chewing movements (VCMs; the mouse analog of TD) and other movement phenotypes derived from open-field activity and the inclined screen test. The test battery was assessed at 0, 30, 60, 90 and 120 days in relation to haloperidol exposure. As expected, haloperidol caused marked changes in VCMs, activity in the open field and extrapyramidal symptoms (EPS). Unexpectedly, factor analysis demonstrated that these measures were imprecise assessments of a latent construct rather than discrete constructs. The heritability of a composite phenotype was ∼0.9 after incorporation of the longitudinal nature of the design. Murine VCMs are a face valid animal model of antipsychotic-induced TD, and heritability estimates from this study support the feasibility of mapping of susceptibility loci for VCMs.

Genome-wide association study of antipsychotic-induced QTc interval prolongation

QT prolongation is associated with increased risk of cardiac arrhythmias. Identifying the genetic variants that mediate antipsychotic-induced prolongation may help to minimize this risk, which might prevent the removal of efficacious drugs from the market. We performed candidate gene analysis and five drug-specific genome-wide association studies (GWASs) with 492K single-nucleotide polymorphisms to search for genetic variation mediating antipsychotic-induced QT prolongation in 738 schizophrenia patients from the Clinical Antipsychotic Trial of Intervention Effectiveness study. Our candidate gene study suggests the involvement of NOS1AP and NUBPL (P-values=1.45 × 10(-05) and 2.66 × 10(-13), respectively). Furthermore, our top GWAS hit achieving genome-wide significance, defined as a Q-value <0.10 (P-value=1.54 × 10(-7), Q-value=0.07), located in SLC22A23, mediated the effects of quetiapine on prolongation. SLC22A23 belongs to a family of organic ion transporters that shuttle a variety of compounds, including drugs, environmental toxins and endogenous metabolites, across the cell membrane. This gene is expressed in the heart and is integral in mouse heart development. The genes mediating antipsychotic-induced QT prolongation partially overlap with the genes affecting normal QT interval variation. However, some genes may also be unique for drug-induced prolongation. This study demonstrates the potential of GWAS to discover genes and pathways that mediate antipsychotic-induced QT prolongation.

Pathways to the All-Volunteer Military

OBJECTIVES: The present study investigates the role of a disadvantaged background, the lack of social connectedness, and behavioral problems in channeling young men to the opportunities of the all-volunteer military instead of to college and the labor market. METHODS: Data from three waves of the National Longitudinal Study of Adolescent Health in the United States. The analytic sample consists of 6,938 white, black, and other males. RESULTS: The greatest likelihood of military service versus college and the labor force occurs when young men of at least modest ability come from disadvantaged circumstances, experience minimal connectedness to others, and report a history of adolescent fighting. DISCUSSION: Findings suggest the importance of access to post-high school education and worklife opportunities as a military service incentive for less advantaged young men in the all volunteer era.

A statistical method for excluding non-variable CpG sites in high-throughput DNA methylation profiling

BACKGROUND

High-throughput DNA methylation arrays are likely to accelerate the pace of methylation biomarker discovery for a wide variety of diseases. A potential problem with a standard set of probes measuring the methylation status of CpG sites across the whole genome is that many sites may not show inter-individual methylation variation among the biosamples for the disease outcome being studied. Inclusion of these so-called "non-variable sites" will increase the risk of false discoveries and reduce statistical power to detect biologically relevant methylation markers.

RESULTS

We propose a method to estimate the proportion of non-variable CpG sites and eliminate those sites from further analyses. Our method is illustrated using data obtained by hybridizing DNA extracted from the peripheral blood mononuclear cells of 311 samples to an array assaying 1505 CpG sites. Results showed that a large proportion of the CpG sites did not show inter-individual variation in methylation.

CONCLUSIONS

Our method resulted in a substantial improvement in association signals between methylation sites and outcome variables while controlling the false discovery rate at the same level.