Characterization of hair cortisol concentration pre-conception and during pregnancy.

BACKGROUND: The hypothalamic pituitary adrenal (HPA) axis is a system involved in stress and pregnancy regulation, and hair cortisol concentration (HCC) is a promising biomarker of its activity. Assessing factors that influence HCC in the prenatal period is critical to understand whether and how HPA axis (dys-)regulation influences maternal health and child development, particularly in high-risk populations from low- and middle-income countries (LMICs). AIMS: This study aimed at characterizing preconception and pregnancy HCC with respect to multiple sociodemographic, pregnancy-related, and hair-related factors. METHODS: In a sample of N = 2581 pregnant women in Perú, participants from two cohort studies provided a 6 cm scalp hair sample at three prenatal timepoints. Each hair sample was cut into two segments of 3 cm that represent cortisol secretion at four times: preconception, first-, second- and third trimester of pregnancy. Hair cortisol was extracted using liquid chromatography tandem mass spectrometry (LC-MS/MS). Spearman correlations, paired t-tests, and ANOVA were used to assess differences in log-transformed values of HCC (logHCC) across maternal sociodemographic, pregnancy-related, and hair-related factors. Multivariable linear regressions were used to examine independent associations of HCCs with selected correlates. RESULTS: Mean logHCC values showed an increase across the four prenatal periods. Preconception BMI was consistently associated with HCC in all three trimesters, while difficulty accessing basic foods, education, hair dyeing, and infant sex showed time-specific associations with HCCs. In sensitivity analyses, we detected no substantial segment effects in the associations of HCCs with maternal characteristics. CONCLUSION: This study is the largest to characterize HCC in pregnant women from a LMIC. Our findings provide a foundation for the use of HCC as a biomarker of prenatal HPA axis activity for future studies. This foundation may contribute to finding valid biomarkers of stress-response systems to promote maternal and child health.

Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

Genetic influences on testosterone and PTSD.

Females are twice as likely to experience PTSD as compared to males. Although sex differences in prevalence are well-established, little is known about why such sex differences occur. Biological factors that vary with sex, including sex hormone production, may contribute to these differences. Considerable evidence links sex hormones, such as testosterone, to PTSD risk though less is known about the shared genetic underpinnings. The objective of the present study was to test for genetic relationships between testosterone and PTSD. To do so, we used summary statistics from large, publicly available genetic consortia to conduct linkage disequilibrium score regression to estimate the genetic correlations between PTSD and testosterone in males and females, and two-sample, bi-directional Mendelian randomization to examine potential causal relationships of testosterone on PTSD and the reverse. Heritability estimates of testosterone were significantly higher in males (0.17, SE = 0.02) than females (0.11, SE = 0.01; z = 2.46, p = 00.01). The correlation between testosterone and PTSD was negative in males (rg = -0.11, SE = 0.02, p = 6.7 x 10-6), but not significant in females (rg = 0.002, SE = 0.03, p = 0.95). MR analyses found no evidence of a causal effect of testosterone on PTSD or the reverse. Findings are consistent with phenotypic literature suggesting a relationship between testosterone and PTSD that may be sex-specific. This work provides early evidence of a relationship between testosterone and PTSD genotypically and suggests an avenue for future research that will enable a better understanding of disparities in PTSD.

Are novel treatments for brain disorders hiding in plain sight?

Psychiatric diseases are strongly influenced by genetics, but genetically guided treatments have been slow to develop, and precise molecular mechanisms remain mysterious. Although individual locations in the genome tend to not contribute powerfully to psychiatric disease incidence, genome-wide association studies (GWAS) have now successfully linked hundreds of specific genetic loci to psychiatric disorders [1-3]. Here, building upon results from well-powered GWAS of four phenotypes relevant to psychiatry, we motivate an exploratory workflow leading from GWAS screening, through causal testing in animal models using methods such as optogenetics, to new therapies in human beings. We focus on schizophrenia and the dopamine D2 receptor (DRD2), hot flashes and the neurokinin B receptor (TACR3), cigarette smoking and receptors bound by nicotine (CHRNA5, CHRNA3, CHRNB4), and alcohol use and enzymes that help to break down alcohol (ADH1B, ADH1C, ADH7). A single genomic locus may not powerfully determine disease at the level of the population, but the same locus may nevertheless represent a potent treatment target suitable for population-wide therapeutic approaches.

Correlates of preconception and pregnancy hair cortisol concentrations.

Assessing factors that influence chronic stress biomarkers like hair cortisol concentrations (HCCs) in pregnancy is critical to prevent adverse pregnancy outcomes. Thus, we aimed to identify correlates of HCC preconception and during pregnancy. 2,581 pregnant women participated in the study. HCC was available at four time periods: pre-pregnancy (0-3 months preconception, n = 1,023), and in the first (1-12 weeks, n = 1,734), second (13-24 weeks, n = 1,534), and third (25-36 weeks, n = 835) trimesters. HCC was assessed using liquid chromatography tandem mass spectrometry (LC-MS/MS). Sociodemographic, pregnancy- and hair-related characteristics, and measures of psychosocial stress, were interrogated as potential correlates of HCC. Spearman correlations, paired t-tests, and ANOVA were used to assess differences in log-transformed values of HCC (logHCC) across maternal characteristics. Multivariable linear regressions were used to identify the correlates of HCCs after adjusting for confounders. Mean logHCC values increased across the four prenatal periods (P < 0.001). In multivariable analyses, pre-pregnancy BMI was consistently associated with all HCCs, while gestational age, economic hardship, hair dyeing, and depression, showed time-specific associations with HCC. In conclusion, this study showed evidence of factors influencing HCC levels before and during pregnancy. The most consistent association was seen with pre-pregnancy BMI. Depression was also associated with HCC concentrations.

Integrative analyses highlight functional regulatory variants associated with neuropsychiatric diseases.

Noncoding variants of presumed regulatory function contribute to the heritability of neuropsychiatric disease. A total of 2,221 noncoding variants connected to risk for ten neuropsychiatric disorders, including autism spectrum disorder, attention deficit hyperactivity disorder, bipolar disorder, borderline personality disorder, major depression, generalized anxiety disorder, panic disorder, post-traumatic stress disorder, obsessive-compulsive disorder and schizophrenia, were studied in developing human neural cells. Integrating epigenomic and transcriptomic data with massively parallel reporter assays identified differentially-active single-nucleotide variants (daSNVs) in specific neural cell types. Expression-gene mapping, network analyses and chromatin looping nominated candidate disease-relevant target genes modulated by these daSNVs. Follow-up integration of daSNV gene editing with clinical cohort analyses suggested that magnesium transport dysfunction may increase neuropsychiatric disease risk and indicated that common genetic pathomechanisms may mediate specific symptoms that are shared across multiple neuropsychiatric diseases.

Lifelong restructuring of 3D genome architecture in cerebellar granule cells.

The cerebellum contains most of the neurons in the human brain and exhibits distinctive modes of development and aging. In this work, by developing our single-cell three-dimensional (3D) genome assay-diploid chromosome conformation capture, or Dip-C-into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we resolved the first 3D genome structures of single cerebellar cells, created life-spanning 3D genome atlases for both humans and mice, and jointly measured transcriptome and chromatin accessibility during development. We found that although the transcriptome and chromatin accessibility of cerebellar granule neurons mature in early postnatal life, 3D genome architecture gradually remodels throughout life, establishing ultra-long-range intrachromosomal contacts and specific interchromosomal contacts that are rarely seen in neurons. These results reveal unexpected evolutionarily conserved molecular processes that underlie distinctive features of neural development and aging across the mammalian life span.

Discovery of 95 PTSD loci provides insight into genetic architecture and neurobiology of trauma and stress-related disorders.

Posttraumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 novel). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (e.g., GRIA1, GRM8, CACNA1E ), developmental, axon guidance, and transcription factors (e.g., FOXP2, EFNA5, DCC ), synaptic structure and function genes (e.g., PCLO, NCAM1, PDE4B ), and endocrine or immune regulators (e.g., ESR1, TRAF3, TANK ). Additional top genes influence stress, immune, fear, and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

Cerebellar Granule Cells Develop Non-neuronal 3D Genome Architecture over the Lifespan.

The cerebellum contains most of the neurons in the human brain, and exhibits unique modes of development, malformation, and aging. For example, granule cells-the most abundant neuron type-develop unusually late and exhibit unique nuclear morphology. Here, by developing our high-resolution single-cell 3D genome assay Dip-C into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we were able to resolve the first 3D genome structures of single cerebellar cells, create life-spanning 3D genome atlases for both human and mouse, and jointly measure transcriptome and chromatin accessibility during development. We found that while the transcriptome and chromatin accessibility of human granule cells exhibit a characteristic maturation pattern within the first year of postnatal life, 3D genome architecture gradually remodels throughout life into a non-neuronal state with ultra-long-range intra-chromosomal contacts and specific inter-chromosomal contacts. This 3D genome remodeling is conserved in mice, and robust to heterozygous deletion of chromatin remodeling disease-associated genes (Chd8 or Arid1b). Together these results reveal unexpected and evolutionarily-conserved molecular processes underlying the unique development and aging of the mammalian cerebellum.

Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort.

A new era of human postmortem tissue research has emerged thanks to the development of 'omics technologies that measure genes, proteins, and spatial parameters in unprecedented detail. Also newly possible is the ability to construct polygenic scores, individual-level metrics of genetic risk (also known as polygenic risk scores/PRS), based on genome-wide association studies, GWAS. Here, we report on clinical, educational, and brain gene expression correlates of polygenic scores in ancestrally diverse samples from the Human Brain Collection Core (HBCC). Genotypes from 1418 donors were subjected to quality control filters, imputed, and used to construct polygenic scores. Polygenic scores for schizophrenia predicted schizophrenia status in donors of European ancestry (p = 4.7 × 10-8, 17.2%) and in donors with African ancestry (p = 1.6 × 10-5, 10.4% of phenotypic variance explained). This pattern of higher variance explained among European ancestry samples was also observed for other psychiatric disorders (depression, bipolar disorder, substance use disorders, anxiety disorders) and for height, body mass index, and years of education. For a subset of 223 samples, gene expression from dorsolateral prefrontal cortex (DLPFC) was available through the CommonMind Consortium. In this subgroup, schizophrenia polygenic scores also predicted an aggregate gene expression score for schizophrenia (European ancestry: p = 0.0032, African ancestry: p = 0.15). Overall, polygenic scores performed as expected in ancestrally diverse samples, given historical biases toward use of European ancestry samples and variable predictive power of polygenic scores across phenotypes. The transcriptomic results reported here suggest that inherited schizophrenia genetic risk influences gene expression, even in adulthood. For future research, these and additional polygenic scores are being made available for analyses, and for selecting samples, using postmortem tissue from the Human Brain Collection Core.

Shared genetic influences on depression and menopause symptoms.

BACKGROUND: Women experience major depression and post-traumatic stress disorder (PTSD) approximately twice as often as men. Estrogen is thought to contribute to sex differences in these disorders, and reduced estrogen is also known to be a key driver of menopause symptoms such as hot flashes. Moreover, estrogen is used to treat menopause symptoms. In order to test for potential shared genetic influences between menopause symptoms and psychiatric disorders, we conducted a genome-wide association study (GWAS) of estrogen medication use (as a proxy for menopause symptoms) in the UK Biobank. METHODS: The analysis included 232 993 women aged 39-71 in the UK Biobank. The outcome variable for genetic analyses was estrogen medication use, excluding women using hormonal contraceptives. Trans-ancestry GWAS meta-analyses were conducted along with genetic correlation analyses on the European ancestry GWAS results. Hormone usage was also tested for association with depression and PTSD. RESULTS: GWAS of estrogen medication use (compared to non-use) identified a locus in the TACR3 gene, which was previously linked to hot flashes in menopause [top rs77322567, odds ratio (OR) = 0.78, p = 7.7 × 10-15]. Genetic correlation analyses revealed shared genetic influences on menopause symptoms and depression (rg = 0.231, s.e.= 0.055, p = 2.8 × 10-5). Non-genetic analyses revealed higher psychiatric symptoms scores among women using estrogen medications. CONCLUSIONS: These results suggest that menopause symptoms have a complex genetic etiology which is partially shared with genetic influences on depression. Moreover, the TACR3 gene identified here has direct clinical relevance; antagonists for the neurokinin 3 receptor (coded for by TACR3) are effective treatments for hot flashes.

Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information.

BACKGROUND: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). METHODS: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. RESULTS: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. CONCLUSIONS: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.

Examining Sex-Differentiated Genetic Effects Across Neuropsychiatric and Behavioral Traits.

BACKGROUND: The origin of sex differences in prevalence and presentation of neuropsychiatric and behavioral traits is largely unknown. Given established genetic contributions and correlations, we tested for a sex-differentiated genetic architecture within and between traits. METHODS: Using European ancestry genome-wide association summary statistics for 20 neuropsychiatric and behavioral traits, we tested for sex differences in single nucleotide polymorphism (SNP)-based heritability and genetic correlation (rg < 1). For each trait, we computed per-SNP z scores from sex-stratified regression coefficients and identified genes with sex-differentiated effects using a gene-based approach. We calculated correlation coefficients between z scores to test for shared sex-differentiated effects. Finally, we tested for sex differences in across-trait genetic correlations. RESULTS: We observed no consistent sex differences in SNP-based heritability. Between-sex, within-trait genetic correlations were high, although <1 for educational attainment and risk-taking behavior. We identified 4 genes with significant sex-differentiated effects across 3 traits. Several trait pairs shared sex-differentiated effects. The top genes with sex-differentiated effects were enriched for multiple gene sets, including neuron- and synapse-related sets. Most between-trait genetic correlation estimates were not significantly different between sexes, with exceptions (educational attainment and risk-taking behavior). CONCLUSIONS: Sex differences in the common autosomal genetic architecture of neuropsychiatric and behavioral phenotypes are small and polygenic and unlikely to fully account for observed sex-differentiated attributes. Larger sample sizes are needed to identify sex-differentiated effects for most traits. For well-powered studies, we identified genes with sex-differentiated effects that were enriched for neuron-related and other biological functions. This work motivates further investigation of genetic and environmental influences on sex differences.

Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia.

Retrotransposons can cause somatic genome variation in the human nervous system, which is hypothesized to have relevance to brain development and neuropsychiatric disease. However, the detection of individual somatic mobile element insertions presents a difficult signal-to-noise problem. Using a machine-learning method (RetroSom) and deep whole-genome sequencing, we analyzed L1 and Alu retrotransposition in sorted neurons and glia from human brains. We characterized two brain-specific L1 insertions in neurons and glia from a donor with schizophrenia. There was anatomical distribution of the L1 insertions in neurons and glia across both hemispheres, indicating retrotransposition occurred during early embryogenesis. Both insertions were within the introns of genes (CNNM2 and FRMD4A) inside genomic loci associated with neuropsychiatric disorders. Proof-of-principle experiments revealed these L1 insertions significantly reduced gene expression. These results demonstrate that RetroSom has broad applications for studies of brain development and may provide insight into the possible pathological effects of somatic retrotransposition.

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.

Short-Term Mental Health Sequelae of Bereavement Predict Long-Term Physical Health Decline in Older Adults: U.S. Health and Retirement Study Analysis.

OBJECTIVES: Spousal death is a common late-life event with health-related sequelae. Evidence linking poor mental health to disease suggests the hypothesis that poor mental health following death of a spouse could be a harbinger of physical health decline. Thus, identification of bereavement-related mental health symptoms could provide an opportunity for prevention. METHODS: We analyzed data from N = 39,162 individuals followed from 1994 to 2016 in the U.S. Health and Retirement Study; N = 5,061 were widowed during follow-up. We tested change in mental and physical health from prebereavement through the 5 years following spousal death. RESULTS: Bereaved spouses experienced an increase in depressive symptoms following their spouses' deaths but the depressive shock attenuated within 1 year. Bereaved spouses experienced increases in disability, chronic-disease morbidity, and hospitalization, which grew in magnitude over time, especially among older respondents. Bereaved spouses were at increased risk of death compared to nonbereaved respondents. The magnitude of depressive symptoms in the immediate aftermath of spousal death predicted physical-health decline and mortality risk over 5 years of follow-up. DISCUSSION: Bereavement-related depressive symptoms indicate a risk for physical health decline and death in older adults. Screening for depressive symptoms in bereaved older adults may represent an opportunity for intervention to preserve healthy life span.

Analysis of Genetically Regulated Gene Expression Identifies a Prefrontal PTSD Gene, SNRNP35, Specific to Military Cohorts.

To reveal post-traumatic stress disorder (PTSD) genetic risk influences on tissue-specific gene expression, we use brain and non-brain transcriptomic imputation. We impute genetically regulated gene expression (GReX) in 29,539 PTSD cases and 166,145 controls from 70 ancestry-specific cohorts and identify 18 significant GReX-PTSD associations corresponding to specific tissue-gene pairs. The results suggest substantial genetic heterogeneity based on ancestry, cohort type (military versus civilian), and sex. Two study-wide significant PTSD associations are identified in European and military European cohorts; ZNF140 is predicted to be upregulated in whole blood, and SNRNP35 is predicted to be downregulated in dorsolateral prefrontal cortex, respectively. In peripheral leukocytes from 175 marines, the observed PTSD differential gene expression correlates with the predicted differences for these individuals, and deployment stress produces glucocorticoid-regulated expression changes that include downregulation of both ZNF140 and SNRNP35. SNRNP35 knockdown in cells validates its functional role in U12-intron splicing. Finally, exogenous glucocorticoids in mice downregulate prefrontal Snrnp35 expression.

Shared molecular genetic risk of alcohol dependence and posttraumatic stress disorder (PTSD).

Alcohol use disorder (AUD) and posttraumatic stress disorder (PTSD) frequently co-occur, highlighting the importance of understanding the etiology of these comorbid conditions. Although AUD and PTSD are moderately heritable with modest overlap in genetic risk as estimated from family studies, there has been a paucity of work using molecular genetic data to estimate shared genetic effects on these conditions. This study used large-scale genomewide molecular data to examine shared genetic risk for AUD, specifically alcohol dependence (AD), and PTSD through cross-trait linkage disequilibrium (LD) score regression (LDSC; also known as LDSR). Summary statistics came from the Psychiatric Genomics Consortium (PGC) PTSD Workgroup Freeze 2 European ancestry (EA) participants (N = 174,659) and AD summary statistics in EA participants (N = 38,686) came from the PGC Substance Use Disorders (SUD) Workgroup. We performed LDSC to estimate genetic correlation between AD and PTSD using HapMap3 variants and LD scores from the 1000 Genomes project. A moderate, significant correlation was observed between AD and PTSD (rg = .35, p = .02), with sex differences identified through stratified analyses. Our results are the first to demonstrate evidence of a shared molecular genetic etiology for AD and PTSD. Further research is needed to better understand possible sex differences in shared heritability and extend these results to additional populations. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Genomic influences on self-reported childhood maltreatment.

Childhood maltreatment is highly prevalent and serves as a risk factor for mental and physical disorders. Self-reported childhood maltreatment appears heritable, but the specific genetic influences on this phenotype are largely unknown. The aims of this study were to (1) identify genetic variation associated with self-reported childhood maltreatment, (2) estimate SNP-based heritability (h2snp), (3) assess predictive value of polygenic risk scores (PRS) for childhood maltreatment, and (4) quantify genetic overlap of childhood maltreatment with mental and physical health-related phenotypes, and condition the top hits from our analyses when such overlap is present. Genome-wide association analysis for childhood maltreatment was undertaken, using a discovery sample from the UK Biobank (UKBB) (n = 124,000) and a replication sample from the Psychiatric Genomics Consortium-posttraumatic stress disorder group (PGC-PTSD) (n = 26,290). h2snp for childhood maltreatment and genetic correlations with mental/physical health traits were calculated using linkage disequilibrium score regression. PRS was calculated using PRSice and mtCOJO was used to perform conditional analysis. Two genome-wide significant loci associated with childhood maltreatment (rs142346759, p = 4.35 × 10-8, FOXP1; rs10262462, p = 3.24 × 10-8, FOXP2) were identified in the discovery dataset but were not replicated in PGC-PTSD. h2snp for childhood maltreatment was ~6% and the PRS derived from the UKBB was significantly predictive of childhood maltreatment in PGC-PTSD (r2 = 0.0025; p = 1.8 × 10-15). The most significant genetic correlation of childhood maltreatment was with depressive symptoms (rg = 0.70, p = 4.65 × 10-40), although we show evidence that our top hits may be specific to childhood maltreatment. This is the first large-scale genetic study to identify specific variants associated with self-reported childhood maltreatment. Speculatively, FOXP genes might influence externalizing traits and so be relevant to childhood maltreatment. Alternatively, these variants may be associated with a greater likelihood of reporting maltreatment. A clearer understanding of the genetic relationships of childhood maltreatment, including particular abuse subtypes, with a range of phenotypes, may ultimately be useful in in developing targeted treatment and prevention strategies.