Polygenic Resilience Scores are Associated with Lower Penetrance of Schizophrenia Risk Genes, Protection Against Psychiatric and Medical Disorders, and Enhanced Mental Well-Being and Cognition.

In the past decade, significant advances have been made in finding genomic risk loci for schizophrenia (SCZ). This, in turn, has enabled the search for SCZ resilience loci that mitigate the impact of SCZ risk genes. Recently, we discovered the first genomic resilience profile for SCZ, completely independent from the established risk loci for SCZ. We posited that these resilience loci protect against SCZ for those having a heighted genomic risk for SCZ. Nevertheless, our understanding of genetic resilience remains limited. It remains unclear whether resilience loci foster protection against adverse states associated with SCZ risk related to clinical, cognitive, and brain-structural phenotypes. To address this knowledge gap, we analyzed data from 487,409 participants from the UK Biobank, and found that resilience loci for SCZ afforded protection against lifetime psychiatric (schizophrenia, bipolar disorder, anxiety, and depression) and non-psychiatric medical disorders (such as asthma, cardiovascular disease, digestive disorders, metabolic disorders, and external causes of morbidity and mortality). Resilience loci also protected against self-harm behaviors, improved fluid intelligence, and larger whole-brain and brain-regional sizes. Overall, this study sheds light on the range of phenotypes that are significantly associated with resilience loci within the general population, revealing distinct patterns separate from those associated with SCZ risk loci. Our findings indicate that resilience loci may offer protection against serious psychiatric and medical outcomes, co-morbidities, and cognitive impairment. Therefore, it is conceivable that resilience loci facilitate adaptive processes linked to improved health and life expectancy.

Inconsistent Methods Used to Set Airway Pressure Release Ventilation in Acute Respiratory Distress Syndrome: A Systematic Review and Meta-Regression Analysis.

Airway pressure release ventilation (APRV) is a protective mechanical ventilation mode for patients with acute respiratory distress syndrome (ARDS) that theoretically may reduce ventilator-induced lung injury (VILI) and ARDS-related mortality. However, there is no standard method to set and adjust the APRV mode shown to be optimal. Therefore, we performed a meta-regression analysis to evaluate how the four individual APRV settings impacted the outcome in these patients. Methods: Studies investigating the use of the APRV mode for ARDS patients were searched from electronic databases. We tested individual settings, including (1) high airway pressure (PHigh); (2) low airway pressure (PLow); (3) time at high airway pressure (THigh); and (4) time at low pressure (TLow) for association with PaO2/FiO2 ratio and ICU length of stay. Results: There was no significant difference in PaO2/FiO2 ratio between the groups in any of the four settings (PHigh difference -12.0 [95% CI -100.4, 86.4]; PLow difference 54.3 [95% CI -52.6, 161.1]; TLow difference -27.19 [95% CI -127.0, 72.6]; THigh difference -51.4 [95% CI -170.3, 67.5]). There was high heterogeneity across all parameters (PhHgh I2 = 99.46%, PLow I2 = 99.16%, TLow I2 = 99.31%, THigh I2 = 99.29%). Conclusions: None of the four individual APRV settings independently were associated with differences in outcome. A holistic approach, analyzing all settings in combination, may improve APRV efficacy since it is known that small differences in ventilator settings can significantly alter mortality. Future clinical trials should set and adjust APRV based on the best current scientific evidence available.

A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.

A polygenic resilience score moderates the genetic risk for schizophrenia: Replication in 18,090 cases and 28,114 controls from the Psychiatric Genomics Consortium.

Identifying heritable factors that moderate the genetic risk for schizophrenia (SCZ) could help clarify why some individuals remain unaffected despite having relatively high genetic liability. Previously, we developed a framework to mine genome-wide association (GWAS) data for common genetic variants that protect high-risk unaffected individuals from SCZ, leading to derivation of the first-ever "polygenic resilience score" for SCZ (resilient controls n = 3786; polygenic risk score-matched SCZ cases n = 18,619). Here, we performed a replication study to verify the moderating effect of our polygenic resilience score on SCZ risk (OR = 1.09, p = 4.03 × 10-5 ) using newly released GWAS data from 23 independent case-control studies collated by the Psychiatric Genomics Consortium (PGC) (resilient controls n = 2821; polygenic risk score-matched SCZ cases n = 5150). Additionally, we sought to optimize our polygenic resilience-scoring formula to improve subsequent modeling of resilience to SCZ and other complex disorders. We found significant replication of the polygenic resilience score, and found that strict pruning of SNPs based on linkage disequilibrium to known risk SNPs and their linked loci optimizes the performance of the polygenic resilience score.

Novel genome-wide associations for effort valuation and psychopathology in children and adults.

The Research Domain Criteria (RDoC) initiative was established by the US National Institute of Mental Health as a multilevel, disorder-agnostic framework for analysis of human psychopathology through designated domains and constructs, including the "Positive Valence Systems" domain focused on reward-related behavior. This study investigates the reward valuation subconstruct of "effort" and its association with genetic markers, functional neurobiological pathways, and polygenic risk scores for psychopathology in 1215 children aged 6-12 and their parents (n = 1044). All participants completed the effort expenditure for rewards task (EEfRT), which assesses "effort" according to two quantitative measures: hard-task choice and reward sensitivity. Genetic association analyses were undertaken in MAGMA, utilizing EEfRT outcome variables as genome-wide association studies phenotypes to compute SNP and gene-level associations. Genome-wide association analyses found two distinct genetic loci that were significantly associated with measures of reward sensitivity and a separate genetic locus associated with hard task choice. Gene-set enrichment analysis yielded significant associations between "effort" and multiple gene sets involved in reward processing-related pathways, including dopamine receptor signaling, limbic system and forebrain development, and biological response to cocaine. These results serve to establish "effort" as a relevant construct for understanding reward-related behavior at the genetic level and support the RDoC framework for assessing disorder-agnostic psychopathology.

miRNA cargo in circulating vesicles from neurons is altered in individuals with schizophrenia and associated with severe disease.

While RNA expression appears to be altered in several brain disorders, the constraints of postmortem analysis make it impractical for well-powered population studies and biomarker development. Given that the unique molecular composition of neurons are reflected in their extracellular vesicles (EVs), we hypothesized that the fractionation of neuron derived EVs provides an opportunity to specifically profile their encapsulated contents noninvasively from blood. To investigate this hypothesis, we determined miRNA expression in microtubule associated protein 1B (MAP1B)-enriched serum EVs derived from neurons from a large cohort of individuals with schizophrenia and nonpsychiatric comparison participants. We observed dysregulation of miRNA in schizophrenia subjects, in particular those with treatment-resistance and severe cognitive deficits. These data support the hypothesis that schizophrenia is associated with alterations in posttranscriptional regulation of synaptic gene expression and provides an example of the potential utility of tissue-specific EV analysis in brain disorders.

Clinical Features of Genetic Resilience in Chronic Obstructive Pulmonary Disease.

Introduction: In the personalized risk quantification of chronic obstructive pulmonary disease (COPD), genome-wide association studies and polygenic risk scores (PRS) complement traditional risk factors, such as age and cigarette smoking. However, despite being at considerable levels of risk, some individuals do not develop COPD. Research on COPD resilience remains largely unexplored. Methods: We applied the previously published COPD PRS to whole genome sequencing data from non-Hispanic white and African American individuals in the COPDGene study. We defined genetic resilience as individuals unaffected by COPD with a polygenic risk score above the 90 th percentile. We defined risk-matched case individuals as those with COPD (i.e., FEV 1 /FVC < 0.70) and a PRS above the 90 th percentile. We defined low risk individuals without COPD (i.e., FEV 1 /FVC > 0.70) as a polygenic risk score below the 10 th percentile. We compared genetically resilient individuals to risk-matched individuals with COPD and low risk individuals by demographics, lung function, respiratory symptoms, co-morbidities, and chest CT scan measurements. We also performed survival analyses, differential expression analysis, and matching for sensitivity analyses. Results: We identified 211 resilient individuals without COPD, 605 genetic risk-matched individuals with COPD, and 527 low-risk individuals without COPD. Resilient individuals had higher FEV 1 % predicted and lower percent emphysema. In contrast, resilient individuals had higher airway wall thickness compared to low-risk unaffected individuals. While there was no difference in survival between low-risk and resilient individuals, resilient individuals had higher survival compared to risk matched cases. We also identified two genes that were differentially expressed between low-risk unaffected individuals and resilient individuals. Conclusion: Genetically resilient individuals had a reduced burden of COPD disease-related measures compared to risk-matched cases but had subtly increased measures compared to low-risk unaffected individuals. Further genetic studies will be needed to illuminate the underlying pathobiology of our observations.

BrainGENIE: The Brain Gene Expression and Network Imputation Engine.

In vivo experimental analysis of human brain tissue poses substantial challenges and ethical concerns. To address this problem, we developed a computational method called the Brain Gene Expression and Network-Imputation Engine (BrainGENIE) that leverages peripheral-blood transcriptomes to predict brain tissue-specific gene-expression levels. Paired blood-brain transcriptomic data collected by the Genotype-Tissue Expression (GTEx) Project was used to train BrainGENIE models to predict gene-expression levels in ten distinct brain regions using whole-blood gene-expression profiles. The performance of BrainGENIE was compared to PrediXcan, a popular method for imputing gene expression levels from genotypes. BrainGENIE significantly predicted brain tissue-specific expression levels for 2947-11,816 genes (false-discovery rate-adjusted p < 0.05), including many transcripts that cannot be predicted significantly by a transcriptome-imputation method such as PrediXcan. BrainGENIE recapitulated measured diagnosis-related gene-expression changes in the brain for autism, bipolar disorder, and schizophrenia better than direct correlations from blood and predictions from PrediXcan. We developed a convenient software toolset for deploying BrainGENIE, and provide recommendations for how best to implement models. BrainGENIE complements and, in some ways, outperforms existing transcriptome-imputation tools, providing biologically meaningful predictions and opening new research avenues.

Polygenic risk for alcohol consumption and multisite chronic pain: Associations with ad lib drinking behavior.

Interrelations between alcohol use disorder and chronic pain have received increasing empirical attention, and several lines of evidence support the possibility of shared genetic liability. However, research on the genetic contributions to the component processes of these complex and potentially overlapping phenotypes remains scarce. The goal of the present study was to test polygenic risk scores (PRSs) for alcohol consumption and multisite chronic pain as predictors of ad lib drinking behavior during an experimental taste test. PRSs were calculated for 209 pain-free, moderate-to-heavy drinkers (57.9% male; 63.6% White). Among White participants, the alcohol and chronic pain PRSs showed nominally significant (ps < .05) positive associations with the volume of alcohol consumed and peak blood alcohol concentration (BAC), respectively. However, associations did not survive correction for multiple comparisons. When stratifying results by experimental condition (between-subjects design: no-pain vs. pain), the alcohol PRS was significantly and negatively associated with the volume of alcohol poured, consumed, and peak BAC among Black participants randomized to the no-pain condition (all false discovery rate [FDR]p < .05). Conversely, the chronic pain PRS was significantly and positively associated with study outcomes among White participants in both the no-pain (alcohol consumed; FDRp = .037) and pain conditions (peak BAC; FDRp = .017). These findings lend partial support to the assertion that alcohol consumption in the laboratory is reflective of drinking behavior in naturalistic settings. This was also the first study to use a pain-related PRS to predict alcohol outcomes, which may be indicative of shared etiology between base and target traits. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Pain as a causal motivator of alcohol consumption: Associations with gender and race.

Despite accumulating evidence indicating reciprocal interrelations between pain and alcohol consumption, no prior work has examined pain as a proximal antecedent of drinking. The goal of the current study was to test the effects of experimental pain induction on ad-lib alcohol consumption among moderate-to-heavy drinkers without chronic pain (N = 237; 42% female; 37% Black; M = 3.26daily drinks). Participants were randomized to either pain-induction (capsaicin + thermal heat paradigm) or no-pain-control conditions. Experimental pain induction lasted for 15 minutes, during which ad-lib alcohol consumption was assessed using an established taste test paradigm. As hypothesized, results indicated that participants randomized to the pain-induction condition poured and consumed more alcohol and reached a higher peak blood alcohol concentration than those randomized to the no-pain condition (ps < 0.05; ηp² range = 0.018-0.021). Exploratory analyses revealed the effects of pain on alcohol consumption to be most pronounced among participants who self-identified as male or Black (relative to female or White, respectively). These findings indicate that the experience of pain serves as a causal, situational motivator for alcohol consumption, and suggest that current drinkers may be susceptible to escalating their consumption of alcohol in the context of pain. Future research is needed to explicate observed differences in the effects of pain on drinking as a function of gender and race, and to extend this work to individuals with chronic pain and varying levels of alcohol use. Collectively, these findings may help inform the development of integrated treatments to address co-occurring pain and alcohol use. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Polygenic resilience scores capture protective genetic effects for Alzheimer's disease.

Polygenic risk scores (PRSs) can boost risk prediction in late-onset Alzheimer's disease (LOAD) beyond apolipoprotein E (APOE) but have not been leveraged to identify genetic resilience factors. Here, we sought to identify resilience-conferring common genetic variants in (1) unaffected individuals having high PRSs for LOAD, and (2) unaffected APOE-ε4 carriers also having high PRSs for LOAD. We used genome-wide association study (GWAS) to contrast "resilient" unaffected individuals at the highest genetic risk for LOAD with LOAD cases at comparable risk. From GWAS results, we constructed polygenic resilience scores to aggregate the addictive contributions of risk-orthogonal common variants that promote resilience to LOAD. Replication of resilience scores was undertaken in eight independent studies. We successfully replicated two polygenic resilience scores that reduce genetic risk penetrance for LOAD. We also showed that polygenic resilience scores positively correlate with polygenic risk scores in unaffected individuals, perhaps aiding in staving off disease. Our findings align with the hypothesis that a combination of risk-independent common variants mediates resilience to LOAD by moderating genetic disease risk.

Family History of Alcohol Use Disorder as a Predictor of Endogenous Pain Modulation Among Moderate to Heavy Drinkers.

Family history of alcohol use disorder (AUD) is frequently endorsed by persons with chronic pain. Although individuals with a family history of AUD have demonstrated enhanced sensitivity to painful stimulation, previous research has not examined endogenous pain modulation in this population. The goal of this study was to test family history of AUD as a predictor of conditioned pain modulation, offset analgesia, and temporal summation among a sample of moderate and heavy drinkers. Adults with no current pain (N = 235; 58.3% male; Mage = 34.3; 91.9% non-Hispanic; 60% white) were evaluated for family history of AUD at baseline and pain modulatory outcomes were assessed via quantitative sensory testing. Participants with a family history of AUD (relative to those without) evinced a pro-nociceptive pain modulation profile in response to experimental pain. Specifically, family history of AUD was associated with deficits in pain-inhibitory processes. Approximately 4% of the variance in endogenous pain modulation was accounted for by family history, and exploratory analyses suggested these effects may be driven by paternal AUD. PERSPECTIVE: The current findings suggest individuals with a family history of AUD demonstrate pain modulatory function that may predispose them to the development of chronic pain. Clinically, these data may inform pain management approaches for individuals with a family history of AUD.

Bipolar Disorder, Religion, and Spirituality: A Scoping Review.

Mental health clinicians frequently study the religion and spirituality (R/S) of their patients. There is, however, a paucity of empirical research concerning R/S of patients with bipolar disorder. This lack is exacerbated by the absence of an evaluation of how these studies relate to each other. Reviews to date concern almost exclusively quantitative studies; a review that synthesizes quantitative and qualitative research is needed. The aim of this paper is to provide a synthesis of empirical studies that is useful in clinical practice. Systematic searches for relevant journal articles in SCOPUS, PubMed, and PsycInfo found 14 quantitative and four qualitative studies. The research reveals that intrinsic religiosity and positive religious coping are the dimensions of R/S that have the most positive correlations with improvement of bipolar disorder symptoms as revealed by measures of clinical outcomes. Patients struggle with their religious experiences, and they wish that R/S would be taken into account by mental health professionals. The quantitative studies are not in conflict with the patient/person-centered focus of qualitative studies. This integration of quantitative data with a patient/person-centered focus shows how belief and illness affect each other. The tensions inherent in such an integration provide new insights for research and treatment. Unfortunately, the qualitative literature has not caught up with quantitative approaches in terms of diagnostic rigor.

Brief Report: Expectancies for alcohol analgesia are associated with greater alcohol use among moderate-to-heavy drinkers without chronic pain.

BACKGROUND AND OBJECTIVES: Expectancies for alcohol analgesia (i.e., expectations that drinking alcohol will reduce pain) have been associated with greater alcohol consumption among individuals with chronic pain, and there is reason to believe that such expectancies may also contribute to drinking behavior among alcohol users without a current chronic pain condition. Therefore, the objective of these analyses was to test associations between a measure of expectancies for alcohol analgesia (EAA) and alcohol use among drinkers without current pain. METHOD: These are secondary analyses of baseline data collected from 200 moderate-to-heavy adult drinkers (39% women). RESULTS: EAA scores were positively associated with quantity/frequency of drinking, urge to drink, and other alcohol outcome expectancies (ps < .01). DISCUSSION AND CONCLUSIONS: Expectancies that alcohol will reduce pain are associated with heavier drinking among drinkers without pain. Over time, such expectancies may contribute to the development of alcohol use disorder and chronically painful conditions. SCIENTIFIC SIGNIFICANCE: This study provides the first evidence that even moderate-to-heavy drinkers without chronic pain may still hold expectancies for alcohol analgesia, and that this may be related to greater quantity/frequency of drinking.

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors.

BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

Schizophrenia, autism spectrum disorders and developmental disorders share specific disruptive coding mutations.

People with schizophrenia are enriched for rare coding variants in genes associated with neurodevelopmental disorders, particularly autism spectrum disorders and intellectual disability. However, it is unclear if the same changes to gene function that increase risk to neurodevelopmental disorders also do so for schizophrenia. Using data from 3444 schizophrenia trios and 37,488 neurodevelopmental disorder trios, we show that within shared risk genes, de novo variants in schizophrenia and neurodevelopmental disorders are generally of the same functional category, and that specific de novo variants observed in neurodevelopmental disorders are enriched in schizophrenia (P = 5.0 × 10-6). The latter includes variants known to be pathogenic for syndromic disorders, suggesting that schizophrenia be included as a characteristic of those syndromes. Our findings imply that, in part, neurodevelopmental disorders and schizophrenia have shared molecular aetiology, and therefore likely overlapping pathophysiology, and support the hypothesis that at least some forms of schizophrenia lie on a continuum of neurodevelopmental disorders.

Editors' Note and Special Communication: Research Priorities in Child and Adolescent Mental Health Emerging From the COVID-19 Pandemic.

Over the last year, the coronavirus disease 2019 (COVID-19) pandemic has resulted in profound disruptions across the globe, with school closures, social isolation, job loss, illness, and death affecting the lives of children and families in myriad ways. In an Editors' Note in our June 2020 issue,1 our senior editorial team described this Journal's role in advancing knowledge in child and adolescent mental health during the pandemic and outlined areas we identified as important for science and practice in our field. Since then, the Journal has published articles on the impacts of the pandemic on child and adolescent mental health and service systems,2-5 which are available in a special collection accessible through the Journal's website.6 Alongside many opinion papers, the pace of publication of empirical research in this area is rapidly expanding, covering important issues such as increased frequency of mental health symptoms among children and adolescents3,5,7-10 and changes in patterns of clinical service use such as emergency department visits.11-14 As the Senior Editors prepared that Editors' Note, they were acutely aware that the priorities that they identified were broad and generated by only a small group of scientists and clinicians. Although this had the advantage of enabling us to get this information out to readers quickly, we decided that a more systematic approach to developing recommendations for research priorities would be of greater long-term value. We were particularly influenced by the efforts of the partnership between the UK Academy of Medical Scientists and a UK mental health research charity (MQ: Transforming Mental Health) to detail COVID-19-related research priorities for "Mental Health Science" that was published online by Holmes et al. in The Lancet Psychiatry in April 2020.15 Consistent with its focus on mental health research across the lifespan, several recommendations highlighted child development and children's mental health. However, a more detailed assessment of research priorities related to child and adolescent mental health was beyond the scope of that paper. Furthermore, the publication of that position paper preceded the death of George Floyd at the hands of Minneapolis police on May 25, 2020, which re-energized efforts to acknowledge and to address racism and healthcare disparities in the United States and many other countries. To build upon the JAACAP Editors' Note1 and the work of Holmes et al.,15 we conducted an international survey of professionals-practitioners and researchers-working on child and adolescent development and pediatric mental health to identify concerns about the impact of the pandemic on children, adolescents, and their families, as well as what is helping families navigate these impacts, and the specific research topics that are of greatest importance.

Autophagy, apoptosis, and neurodevelopmental genes might underlie selective brain region vulnerability in attention-deficit/hyperactivity disorder.

Large-scale brain imaging studies by the ENIGMA Consortium identified structural changes associated with attention-deficit/hyperactivity disorder (ADHD). It is not clear why some brain regions are impaired and others spared by the etiological risks for ADHD. We hypothesized that spatial variation in brain cell organization and/or pathway expression levels contribute to selective brain region vulnerability (SBRV) in ADHD. In this study, we used the largest available collection of magnetic resonance imaging (MRI) results from the ADHD ENIGMA Consortium (subcortical MRI n = 3242; cortical MRI n = 4180) along with high-resolution postmortem brain microarray data from Allen Brain Atlas (donors n = 6) from 22 brain regions to investigate our SBRV hypothesis. We performed deconvolution of the bulk transcriptomic data to determine abundances of neuronal and nonneuronal cells in the brain. We assessed the relationships between gene-set expression levels, cell abundance, and standardized effect sizes representing regional changes in brain sizes in cases of ADHD. Our analysis yielded significant correlations between apoptosis, autophagy, and neurodevelopment genes with smaller brain sizes in ADHD, along with associations to regional abundances of astrocytes and oligodendrocytes. The lack of enrichment of common genetic risk variants for ADHD within implicated gene sets suggests an environmental etiology to these differences. This work provides novel mechanistic clues about SBRV in ADHD.

A polygenic resilience score moderates the genetic risk for schizophrenia.

Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531-538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected individuals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known "polygenic resilience score" that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent samples. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder.

Effects of Polygenic Risk and Perceived Friends' Drinking and Disruptive Behavior on Development of Alcohol Use Across Adolescence.

OBJECTIVE: Developmental theory posits interacting individual and contextual factors that contribute to alcohol use across adolescence. Despite the well-documented salience of peer environmental influences on adolescent drinking, it is not known whether peer environments moderate polygenic risks for trajectories of alcohol use. The current theoretically based investigation aimed to test developmental gene-environment interaction (G×E) effects across adolescence. METHOD: Latent growth curve models tested interactive associations of polygenic risk scores and adolescents' perceived friend drinking and disruptive behavior with adolescents' initial level of alcohol use frequency at age 16 years old and change in alcohol frequency from ages 16 to 20. The sample comprised 8,941 White adolescents (49% female) from Great Britain within the Avon Longitudinal Study of Parents and Children (ALSPAC). RESULTS: Greater polygenic risk was associated with more frequent initial drinking as well as escalations in drinking frequency over the subsequent 5 years in latent growth curve models. Contrary to study hypotheses, no significant G×E effects were identified after controlling for confounding main and interaction effects. CONCLUSIONS: Adolescents at heightened genetic risk may accelerate their alcohol use across adolescence, although not significantly more so in the presence of these alcohol-promoting peer environments. Future well-powered, theoretically driven replication efforts are needed to examine generalizability of these findings across diverse samples.