The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5–20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson’s disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations.

; for the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium IMPORTANCE Increasing evidence shows that physical activity is associated with reduced risk for depression, pointing to a potential modifiable target for prevention. However, the causality and direction of this association are not clear; physical activity may protect against depression, and/or depression may result in decreased physical activity. OBJECTIVE To examine bidirectional relationships between physical activity and depression using a genetically informed method for assessing potential causal inference. DESIGN, SETTING, AND PARTICIPANTS This 2-sample mendelian randomization (MR) used independent top genetic variants associated with 2 physical activity phenotypesself-reported (n = 377 234) and objective accelerometer-based (n = 91 084)-and with major depressive disorder (MDD) (n = 143 265) as genetic instruments from the largest available, nonoverlapping genome-wide association studies (GWAS). GWAS were previously conducted in diverse observational cohorts, including the UK Biobank (for physical activity) and participating studies in the Psychiatric Genomics Consortium (for MDD) among adults of European ancestry. Mendelian randomization estimates from each genetic instrument were combined using inverse variance weighted meta-analysis, with alternate methods (eg, weighted median, MR Egger, MR-Pleiotropy Residual Sum and Outlier [PRESSO]) and multiple sensitivity analyses to assess horizontal pleiotropy and remove outliers. Data were analyzed from May 10 through July 31, 2018. MAIN OUTCOMES AND MEASURES MDD and physical activity. RESULTS GWAS summary data were available for a combined sample size of 611 583 adult participants. Mendelian randomization evidence suggested a protective relationship between accelerometer-based activity and MDD (odds ratio [OR], 0.74 for MDD per 1-SD increase in mean acceleration; 95% CI, 0.59-0.92; P = .006). In contrast, there was no statistically significant relationship between MDD and accelerometer-based activity (β = −0.08 in mean acceleration per MDD vs control status; 95% CI, −0.47 to 0.32; P = .70). Furthermore, there was no significant relationship between self-reported activity and MDD (OR, 1.28 for MDD per 1-SD increase in metabolic-equivalent minutes of reported moderate-to-vigorous activity; 95% CI, 0.57-3.37; P = .48), or between MDD and self-reported activity (β = 0.02 per MDD in standardized metabolic-equivalent minutes of reported moderate-to-vigorous activity per MDD vs control status; 95% CI, −0.008 to 0.05; P = .15). CONCLUSIONS AND RELEVANCE Using genetic instruments identified from large-scale GWAS, robust evidence supports a protective relationship between objectively assessed-but not self-reported-physical activity and the risk for MDD. Findings point to the importance of objective measurement of physical activity in epidemiologic studies of mental health and support the hypothesis that enhancing physical activity may be an effective prevention strategy for depression.

For many years, psychiatrists have tried to understand factors involved in response to medications or psychotherapies, in order to personalize their treatment choices. There is now a broad and growing interest in the idea that we can develop models to personalize treatment decisions using new statistical approaches from the field of machine learning and applying them to larger volumes of data. In this pursuit, there has been a paradigm shift away from experimental studies to confirm or refute specific hypotheses towards a focus on the overall explanatory power of a predictive model when tested on new, unseen datasets. In this paper, we review key studies using machine learning to predict treatment outcomes in psychiatry, ranging from medications and psychotherapies to digital interventions and neurobiological treatments. Next, we focus on some new sources of data that are being used for the development of predictive models based on machine learning, such as electronic health records, smartphone and social media data, and on the potential utility of data from genetics, electrophysiology, neuroimaging and cognitive testing. Finally, we discuss how far the field has come towards implementing prediction tools in real‐world clinical practice. Relatively few retrospective studies to‐date include appropriate external validation procedures, and there are even fewer prospective studies testing the clinical feasibility and effectiveness of predictive models. Applications of machine learning in psychiatry face some of the same ethical challenges posed by these techniques in other areas of medicine or computer science, which we discuss here. In short, machine learning is a nascent but important approach to improve the effectiveness of mental health care, and several prospective clinical studies suggest that it may be working already.

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The Western Cape of South Africa has one of the highest rates of fetal alcohol spectrum disorders (FASD) globally. Reducing alcohol use during pregnancy is a pressing public health priority for this region, but insight into the experiences of women who drink during pregnancy is lacking. Convenience sampling in alcohol-serving venues was used to identify women who were currently pregnant (n=12) or recently post-partum (n=12) and reported drinking during the pregnancy period. In-depth qualitative interviews were conducted between April and August 2013. Interviews explored drinking narratives, with textual data analyzed for themes related to factors that contributed to drinking during pregnancy. All but one woman reported her pregnancy as unplanned. The majority sustained or increased drinking after pregnancy recognition, with patterns typically including multiple days of binge drinking per week. Analysis of the textual data revealed five primary factors that contributed to drinking during pregnancy: 1) women used alcohol as a strategy to cope with stressors and negative emotions, including those associated with pregnancy; 2) women drank as a way to retain social connection, often during a difficult period of life transition; 3) social norms in women's peer groups supported drinking during pregnancy; 4) women lacked attachment to the pregnancy or were resistant to motherhood; and 5) women were driven physiologically by alcohol addiction. Our data suggest that alcohol-serving settings are important sites to identify and target women at risk of drinking during pregnancy. Intervention approaches to reduce alcohol use during pregnancy should include counseling and contraception to prevent unwanted pregnancies, mental health and coping interventions targeting pregnant women, peer-based interventions to change norms around perinatal drinking, and treatment for alcohol dependence during pregnancy. Our findings suggest that innovative interventions that go beyond the boundaries of the health care system are urgently needed to address FASD in this region.

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Pregnant and postpartum women face unique challenges during the COVID-19 pandemic that may put them at elevated risk of mental health problems. However, few large-scale and no cross-national studies have been conducted to date that investigate modifiable pandemic-related behavioral or cognitive factors that may influence mental health in this vulnerable group. This international study sought to identify and measure the associations between pandemic-related information seeking, worries, and prevention behaviors on perinatal mental health during the COVID-19 pandemic. An anonymous, online, cross-sectional survey of pregnant and postpartum women was conducted in 64 countries between May 26, 2020 and June 13, 2020. The survey, available in twelve languages, was hosted on the Pregistry platform for COVID-19 studies (https://corona.pregistry.com) and advertised in social media channels and online parenting forums. Participants completed measures on demographics, COVID-19 exposure and worries, information seeking, COVID-19 prevention behaviors, and mental health symptoms including posttraumatic stress via the IES-6, anxiety/depression via the PHQ-4, and loneliness via the UCLA-3. Of the 6,894 participants, substantial proportions of women scored at or above the cut-offs for elevated posttraumatic stress (2,979 [43%]), anxiety/depression (2,138 [31%], and loneliness (3,691 [53%]). Information seeking from any source (e.g., social media, news, talking to others) five or more times per day was associated with more than twice the odds of elevated posttraumatic stress and anxiety/depression, in adjusted models. A majority of women (86%) reported being somewhat or very worried about COVID-19. The most commonly reported worries were related to pregnancy and delivery, including family being unable to visit after delivery (59%), the baby contracting COVID-19 (59%), lack of a support person during delivery (55%), and COVID-19 causing changes to the delivery plan (41%). Greater worries related to children (i.e., inadequate childcare, their infection risk) and missing medical appointments were associated with significantly higher odds of posttraumatic stress, anxiety/depression and loneliness. Engaging in hygiene-related COVID-19 prevention behaviors (face mask-wearing, washing hands, disinfecting surfaces) were not related to mental health symptoms or loneliness. Elevated posttraumatic stress, anxiety/depression, and loneliness are highly prevalent in pregnant and postpartum women across 64 countries during the COVID-19 pandemic. Excessive information seeking and worries related to children and medical care are associated with elevated symptoms, whereas engaging in hygiene-related preventive measures were not. In addition to screening and monitoring mental health symptoms, addressing excessive information seeking and women’s worries about access to medical care and their children’s well-being, and developing strategies to target loneliness (e.g., online support groups) should be part of intervention efforts for perinatal women. Public health campaigns and medical care systems need to explicitly address the impact of COVID-19 related stressors on mental health in perinatal women, as prevention of viral exposure itself does not mitigate the pandemic’s mental health impact.

ClinicalTrials.gov NCT02223390.