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.

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.

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.

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.

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.

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.

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.

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.

An epigenetic pathway approach to investigating associations between prenatal exposure to maternal mood disorder and newborn neurobehavior.

Following recent advances in behavioral and psychiatric epigenetics, researchers are increasingly using epigenetic methods to study prenatal exposure to maternal mood disorder and its effects on fetal and newborn neurobehavior. Despite notable progress, various methodological limitations continue to obscure our understanding of the epigenetic mechanisms underpinning prenatal exposure to maternal mood disorder on newborn neurobehavioral development. Here we detail this problem, discussing limitations of the currently dominant analytical approaches (i.e., candidate epigenetic and epigenome-wide association studies), then present a solution that retains many benefits of existing methods while minimizing their shortcomings: epigenetic pathway analysis. We argue that the application of pathway-based epigenetic approaches that target DNA methylation at transcription factor binding sites could substantially deepen our mechanistic understanding of how prenatal exposures influence newborn neurobehavior.

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.

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 (h2SNP = 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.

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.

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.

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.

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.

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.

Genome-Wide Meta-Analysis of Longitudinal Alcohol Consumption Across Youth and Early Adulthood.

The public health burden of alcohol is unevenly distributed across the life course, with levels of use, abuse, and dependence increasing across adolescence and peaking in early adulthood. Here, we leverage this temporal patterning to search for common genetic variants predicting developmental trajectories of alcohol consumption. Comparable psychiatric evaluations measuring alcohol consumption were collected in three longitudinal community samples (N=2,126, obs=12,166). Consumption-repeated measurements spanning adolescence and early adulthood were analyzed using linear mixed models, estimating individual consumption trajectories, which were then tested for association with Illumina 660W-Quad genotype data (866,099 SNPs after imputation and QC). Association results were combined across samples using standard meta-analysis methods. Four meta-analysis associations satisfied our pre-determined genome-wide significance criterion (FDR<0.1) and six others met our 'suggestive' criterion (FDR<0.2). Genome-wide significant associations were highly biological plausible, including associations within GABA transporter 1, SLC6A1 (solute carrier family 6, member 1), and exonic hits in LOC100129340 (mitofusin-1-like). Pathway analyses elaborated single marker results, indicating significant enriched associations to intuitive biological mechanisms, including neurotransmission, xenobiotic pharmacodynamics, and nuclear hormone receptors (NHR). These findings underscore the value of combining longitudinal behavioral data and genome-wide genotype information in order to study developmental patterns and improve statistical power in genomic studies.

Genome-wide association study of patient-rated and clinician-rated global impression of severity during antipsychotic treatment.

OBJECTIVE: To examine the unique and congruent findings between multiple raters in a genome-wide association study (GWAS) in the context of understanding individual differences in treatment response during antipsychotic therapy for schizophrenia. MATERIALS AND METHODS: We performed GWAS to search for genetic variation affecting treatment response. The analysis sample included 738 patients with schizophrenia, successfully genotyped for ∼492k single nucleotide polymorphisms (SNPs) from the Clinical Antipsychotic Trial of Intervention Effectiveness. Outcomes included both clinician and patient report of illness severity on global impression scales, the clinical global impression severity scale and patient global impression, respectively. Our criterion for genome-wide significance was a prespecified threshold ensuring that, on average, only 10% of the significant findings are false discoveries. RESULTS: Thirteen SNPs reached genome-wide significance. The top findings indicated three SNPs in PDE4D, 5q12.1 (P=4.2×10, 1.6×10, 1.8×10), mediating the effects of quetiapine on patient-reported severity and an additional three SNPs in TJP1, 15q13.1 (P=2.25×10, 4.86×10, 4.91×10), mediating the effects of risperidone on patient-reported severity. For clinician-reported severity, two SNPs in PPA2, 4q24 (P=3.68×10, 5.05×10), were found to reach genome-wide significance. CONCLUSION: We found evidence of both a novel and a consistent association when examining the results from the patient and clinician ratings, suggesting that different raters may capture unique facets of schizophrenia. Although our findings require replication and functional validation, this study shows the potential of GWAS to discover genes that potentially mediate treatment response of antipsychotic medication.

Genes, environments, and developmental research: methods for a multi-site study of early substance abuse.

The importance of including developmental and environmental measures in genetic studies of human pathology is widely acknowledged, but few empirical studies have been published. Barriers include the need for longitudinal studies that cover relevant developmental stages and for samples large enough to deal with the challenge of testing gene-environment-development interaction. A solution to some of these problems is to bring together existing data sets that have the necessary characteristics. As part of the National Institute on Drug Abuse-funded Gene-Environment-Development Initiative, our goal is to identify exactly which genes, which environments, and which developmental transitions together predict the development of drug use and misuse. Four data sets were used of which common characteristics include (1) general population samples, including males and females; (2) repeated measures across adolescence and young adulthood; (3) assessment of nicotine, alcohol, and cannabis use and addiction; (4) measures of family and environmental risk; and (5) consent for genotyping DNA from blood or saliva. After quality controls, 2,962 individuals provided over 15,000 total observations. In the first gene-environment analyses, of alcohol misuse and stressful life events, some significant gene-environment and gene-development effects were identified. We conclude that in some circumstances, already collected data sets can be combined for gene-environment and gene-development analyses. This greatly reduces the cost and time needed for this type of research. However, care must be taken to ensure careful matching across studies and variables.