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Common genetic risk variants have been implicated in the etiology of clinical attention-deficit/hyperactivity disorder (ADHD) diagnoses and symptoms in the general population. However, given the extensive comorbidity across ADHD and other psychiatric conditions, the extent to which genetic variants associated with ADHD also influence broader psychopathology dimensions remains unclear. The aim of this study was to evaluate the associations between ADHD polygenic risk scores (PRS) and a broad range of childhood psychiatric symptoms, and to quantify the extent to which such associations can be attributed to a general factor of childhood psychopathology. We derived ADHD PRS for 13,457 children aged 9 or 12 from the Child and Adolescent Twin Study in Sweden, using results from an independent meta-analysis of genome-wide association studies of ADHD diagnosis and symptoms. We estimated associations between ADHD PRS, a general psychopathology factor, and several dimensions of neurodevelopmental, externalizing, and internalizing symptoms, using structural equation modeling. Higher ADHD PRS were statistically significantly associated with elevated neurodevelopmental, externalizing, and depressive symptoms (R2 = 0.26–1.69%), but not with anxiety. After accounting for a general psychopathology factor, on which all symptoms loaded positively (mean loading = 0.50, range = 0.09–0.91), an association with specific hyperactivity/impulsivity remained significant. ADHD PRS explained ~ 1% (p value < 0.0001) of the variance in the general psychopathology factor and ~ 0.50% (p value < 0.0001) in specific hyperactivity/impulsivity. Our results suggest that common genetic risk variants associated with ADHD, and captured by PRS, also influence a general genetic liability towards broad childhood psychopathology in the general population, in addition to a specific association with hyperactivity/impulsivity symptoms.

Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.

Clare Turnbull and colleagues report discovery of 19 new susceptibility loci for testicular germ cell tumor (TGCT) and provide evidence for a network of physical interactions between TGCT risk variants and candidate causal genes. Their findings implicate widespread disruption of developmental transcriptional regulators in TGCT susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in oncogenesis. Genome-wide association studies (GWAS) have transformed understanding of susceptibility to testicular germ cell tumors (TGCTs), but much of the heritability remains unexplained. Here we report a new GWAS, a meta-analysis with previous GWAS and a replication series, totaling 7,319 TGCT cases and 23,082 controls. We identify 19 new TGCT risk loci, roughly doubling the number of known TGCT risk loci to 44. By performing in situ Hi-C in TGCT cells, we provide evidence for a network of physical interactions among all 44 TGCT risk SNPs and candidate causal genes. Our findings implicate widespread disruption of developmental transcriptional regulators as a basis of TGCT susceptibility, consistent with failed primordial germ cell differentiation as an initiating step in oncogenesis 1 . Defective microtubule assembly and dysregulation of KIT–MAPK signaling also feature as recurrently disrupted pathways. Our findings support a polygenic model of risk and provide insight into the biological basis of TGCT.

Despite considerable progress in schizophrenia genetics, most findings have been for large rare structural variants and common variants in well-imputed regions with few genes implicated from exome sequencing. Whole genome sequencing (WGS) can potentially provide a more complete enumeration of etiological genetic variation apart from the exome and regions of high linkage disequilibrium. We analyze high-coverage WGS data from 1162 Swedish schizophrenia cases and 936 ancestry-matched population controls. Our main objective is to evaluate the contribution to schizophrenia etiology from a variety of genetic variants accessible to WGS but not by previous technologies. Our results suggest that ultra-rare structural variants that affect the boundaries of topologically associated domains (TADs) increase risk for schizophrenia. Alterations in TAD boundaries may lead to dysregulation of gene expression. Future mechanistic studies will be needed to determine the precise functional effects of these variants on biology. Common variants identified by large-scale genomewide association studies cannot account fully account for the heritability of schizophrenia (SCZ). Here, the authors report high-coverage whole-genome sequencing of 1162 SCZ cases and 936 controls and explore the contribution of different types of variants to SCZ.

Thomas Whitington and colleagues present a detailed characterization of gene regulatory mechanisms underlying prostate cancer susceptibility. Their analysis highlights key mechanisms altered by disease-associated SNPs, including widespread disruption of ternary complexes involving AR, FOXA1 and HOXB13. Molecular characterization of genome-wide association study (GWAS) loci can uncover key genes and biological mechanisms underpinning complex traits and diseases. Here we present deep, high-throughput characterization of gene regulatory mechanisms underlying prostate cancer risk loci. Our methodology integrates data from 295 prostate cancer chromatin immunoprecipitation and sequencing experiments with genotype and gene expression data from 602 prostate tumor samples. The analysis identifies new gene regulatory mechanisms affected by risk locus SNPs, including widespread disruption of ternary androgen receptor (AR)-FOXA1 and AR-HOXB13 complexes and competitive binding mechanisms. We identify 57 expression quantitative trait loci at 35 risk loci, which we validate through analysis of allele-specific expression. We further validate predicted regulatory SNPs and target genes in prostate cancer cell line models. Finally, our integrated analysis can be accessed through an interactive visualization tool. This analysis elucidates how genome sequence variation affects disease predisposition via gene regulatory mechanisms and identifies relevant genes for downstream biomarker and drug development.

Understanding the pathophysiological substrates of schizophrenia is a major challenge for current neuropsychiatric research. As part of a set of multi-omics experiments, we performed an extensive case-control proteomics study on 192 post-mortem tissue sections from prefrontal cortex from 96 individuals, including 47 cases with schizophrenia and 49 healthy controls. Using two independently measured cortical datasets, we identified 387 proteins differentially expressed between schizophrenia cases and controls at a 5% FDR threshold. This significantly regulated set of proteins contains genes located in GWAS-identified schizophrenia loci and proteins identified by pQTL analysis. Gene ontology analysis using GOAT provided evidence for regulation of several major protein categories, emphasizing downregulation of mitochondrial oxidative respiration, ribosomes and the proteasome, upregulation of kinases and (small) GTPases. SynGO analysis supports the notion of synaptic dysfunction in schizophrenia, with major regulators of pre- and postsynaptic function compromised. Our findings highlight the complex molecular dysregulation in schizophrenia, with mitochondrial function downregulated versus signaling and trafficking upregulated, and synapse function disrupted; in combination with prior avenues of research, these finding support a role for energy deficits compromising highly ATP dependent neuronal function as a target for therapeutic interventions. Schizophrenia is a complex brain disorder with its underlying protein changes generally not well understood. Here, authors show widespread alterations in the prefrontal cortex, marked by reduced energy production and disrupted synaptic function.

While music engagement is often regarded as beneficial for mental health, some studies report higher risk for depression and anxiety among musicians. This study investigates whether shared underlying genetic influences (genetic pleiotropy) or gene-environment interaction could be at play in the music-mental health association using measured genotypes. In 5,648 Swedish twins with information on music and sport engagement, creative achievements, self-reported mental health and psychiatric diagnoses based on nationwide patient registries, we derived polygenic scores for major depression, bipolar disorder, schizophrenia, neuroticism, sensitivity to environmental stress, depressive symptoms and general musicality. In line with phenotypic associations, individuals with higher polygenic scores for major depression and bipolar disorder were more likely to play music, practice more music and reach higher levels of general artistic achievements, while a higher genetic propensity for general musicality was marginally associated with a higher risk for a depression diagnosis. Importantly, polygenic scores for major depression and bipolar remained associated with music engagement when excluding individuals who experienced psychiatric symptoms, just as a genetic propensity for general musicality predicted a depression diagnosis regardless of whether and how much individuals played music. In addition, we found no evidence for gene-environment interaction: the phenotypic association between music engagement and mental health outcomes did not differ for individuals with different genetic vulnerability for mental health problems. Altogether, our findings suggest that mental health problems observed in musically active individuals are partly explained by a pre-existing genetic risk for depression and bipolar disorder and likely reflect horizontal pleiotropy (when one gene influences multiple traits), rather than causal influences of mental health on music engagement, or vice versa (referred to as vertical pleiotropy).

Treatment response and resistance in major depressive disorder (MDD) are suggested to be heritable. Due to significant challenges in defining treatment-related phenotypes, our understanding of their genetic bases is limited. This study aimed to derive a stringent definition of treatment resistance and to investigate the genetic overlap between treatment response and resistance in MDD. Using electronic medical records on the use of antidepressants and electroconvulsive therapy (ECT) from Swedish registers, we derived the phenotype of treatment-resistant depression (TRD) and non-TRD within ~4500 individuals with MDD in three Swedish cohorts. Considering antidepressants and lithium are first-line treatment and augmentation used for MDD, respectively, we generated polygenic risk scores (PRS) of antidepressants and lithium response for individuals with MDD and evaluated their associations with treatment resistance by comparing TRD with non-TRD. Among 1778 ECT-treated MDD cases, nearly all (94%) used antidepressants before their first ECT and the vast majority had at least one (84%) or two (61%) antidepressants of adequate duration, suggesting these MDD cases receiving ECT were resistant to antidepressants. We did not observe a significant difference in the mean PRS of antidepressant response between TRD and non-TRD; however, we found that TRD cases had a significantly higher PRS of lithium response compared to non-TRD cases (OR = 1.10–1.12 under various definitions). The results support the evidence of heritable components in treatment-related phenotypes and highlight the overall genetic profile of lithium-sensitivity in TRD. This finding further provides a genetic explanation for lithium efficacy in treating TRD.

Children who experience adversities have an elevated risk of mental health problems. However, the extent to which adverse childhood experiences (ACEs) cause mental health problems remains unclear, as previous associations may partly reflect genetic confounding. In this Registered Report, we used DNA from 11,407 children from the United Kingdom and the United States to investigate gene–environment correlations and genetic confounding of the associations between ACEs and mental health. Regarding gene–environment correlations, children with higher polygenic scores for mental health problems had a small increase in odds of ACEs. Regarding genetic confounding, elevated risk of mental health problems in children exposed to ACEs was at least partially due to pre-existing genetic risk. However, some ACEs (such as childhood maltreatment and parental mental illness) remained associated with mental health problems independent of genetic confounding. These findings suggest that interventions addressing heritable psychiatric vulnerabilities in children exposed to ACEs may help reduce their risk of mental health problems. In 11,407 children, Baldwin et al. report gene–environment correlations between polygenic scores for psychiatric disorders and adverse childhood experiences, as well as partial genetic confounding of associations between adverse childhood experiences and mental health.

Background Mammographic density (MD) is a strong and heritable intermediate phenotype of breast cancer, but much of its genetic variation remains unexplained. Methods We conducted a genetic association study of volumetric MD in a Swedish mammography screening cohort ( n = 9498) to identify novel MD loci. Associations with volumetric MD phenotypes (percent dense volume, absolute dense volume, and absolute nondense volume) were estimated using linear regression adjusting for age, body mass index, menopausal status, and six principal components. We also estimated the proportion of MD variance explained by additive contributions from single-nucleotide polymorphisms (SNP-based heritability [ h 2 SNP ]) in 4948 participants of the cohort. Results In total, three novel MD loci were identified (at P < 5 × 10 − 8 ): one for percent dense volume ( HABP2 ) and two for the absolute dense volume (INHBB, LINC01483) . INHBB is an established locus for ER-negative breast cancer, and HABP2 and LINC01483 represent putative new breast cancer susceptibility loci, because both loci were associated with breast cancer in available meta-analysis data including 122,977 breast cancer cases and 105,974 control subjects ( P < 0.05). h 2 SNP (SE) estimates for percent dense, absolute dense, and nondense volume were 0.29 (0.07), 0.31 (0.07), and 0.25 (0.07), respectively. Corresponding ratios of h 2 SNP to previously observed narrow-sense h 2 estimates in the same cohort were 0.46, 0.72, and 0.41, respectively. Conclusions These findings provide new insights into the genetic basis of MD and biological mechanisms linking MD to breast cancer risk. Apart from identifying three novel loci, we demonstrate that at least 25% of the MD variance is explained by common genetic variation with h 2 SNP / h 2 ratios varying between dense and nondense MD components.