A Developmentally-Informative Genome-wide Association Study of Alcohol Use Frequency.

Contemporary genome-wide association study (GWAS) methods typically do not account for variability in genetic effects throughout development. We applied genomic structural equation modeling to combine developmentally-informative phenotype data and GWAS to create polygenic scores (PGS) for alcohol use frequency that are specific to developmental stage. Longitudinal cohort studies targeted for gene-identification analyses include the Collaborative Study on the Genetics of Alcoholism (adolescence n = 1,118, early adulthood n = 2,762, adulthood n = 5,255), the National Longitudinal Study of Adolescent to Adult Health (adolescence n = 3,089, early adulthood n = 3,993, adulthood n = 5,149), and the Avon Longitudinal Study of Parents and Children (ALSPAC; adolescence n = 5,382, early adulthood n = 3,613). PGS validation analyses were conducted in the COGA sample using an alternate version of the discovery analysis with COGA removed. Results suggest that genetic liability for alcohol use frequency in adolescence may be distinct from genetic liability for alcohol use frequency later in developmental periods. The age-specific PGS predicts an increase of 4 drinking days per year per PGS standard deviation when modeled separately from the common factor PGS in adulthood. The current work was underpowered at all steps of the analysis plan. Though small sample sizes and low statistical power limit the substantive conclusions that can be drawn regarding these research questions, this work provides a foundation for future genetic studies of developmental variability in the genetic underpinnings of alcohol use behaviors and genetically-informed, age-matched phenotype prediction.

Examining the association of familial and social stress, trauma, and support on mood, anxiety, and behavioral symptoms and diagnoses in youth at risk for bipolar disorder and controls.

INTRODUCTION: Youth with a family history of bipolar disorder (At-Risk) have a higher risk of developing psychiatric disorders and experiencing environmental stressors than youth without such family history (Control). We studied the differential associations of familial and environmental factors on developing psychiatric diagnoses and symptoms, in At-Risk and Control youth. METHODS: At-Risk and Control youth (N = 466, ages 9-22) were systematically assessed for severity of symptoms, psychiatric diagnoses, and self-reported measures of stress and social support. We tested the association of family history and measures of stress or support with symptom severity and diagnoses. RESULTS: At-Risk youth had higher symptom severity scores and were more frequently diagnosed with psychiatric disorders (all p values < 0.001). When predicting mood symptom severity, family history had an interaction effect with stressful life events (p < 0.001) and number of distinct traumatic events (p = 0.001). In multivariate models, At-Risk status predicted anxiety disorders (OR = 2.7, CI 1.3-5.4, p = 0.005) and anxiety severity (Coefficient = 0.4, CI 0.2-0.7, p < 0.001) but not mood or behavioral disorder diagnoses or severity. LIMITATIONS: Measures of stress and social support were based on self-report. Not all participants had passed through the period of risk for developing the outcomes under study and the follow up period was variable. We could not fully study the differential impact of physical or sexual abuse due to low frequency of occurrence in controls. CONCLUSION: At-Risk youth exhibit more severe mood symptoms compared to Controls when exposed to similar levels of stress or trauma. At-Risk youth are also more prone to develop anxiety which may be a precursor for bipolar disorder.

Defining Suicidal Thought and Behavior Phenotypes for Genetic Studies.

Background: Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation. Methods: A subgroup of clinician researchers and experts from the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) reviewed existing PGC definitions for SI, SA, SD, and control groups and generated preliminary consensus guidelines for instrument-derived and international classification of disease (ICD) data. ICD lists were validated in two independent datasets (N = 9,151 and 12,394). Results: Recommendations are provided for evaluated instruments for SA and SI, emphasizing selection of lifetime measures phenotype-specific wording. Recommendations are also provided for defining SI and SD from ICD data. As the SA ICD definition is complex, SA code list recommendations were validated against instrument results with sensitivity (range = 15.4% to 80.6%), specificity (range = 67.6% to 97.4%), and positive predictive values (range = 0.59-0.93) reported. Conclusions: Best-practice guidelines are presented for the use of existing information to define SI/SA/SD in consortia research. These proposed definitions are expected to facilitate more homogeneous data aggregation for genetic and multisite studies. Future research should involve refinement, improved generalizability, and validation in diverse populations.