Compared with heterosexual persons, non-heterosexual persons have worse mental health. Sexual Minority Stress Theory (SMST) explains the disparity as resulting from stigma and discrimination. To the extent that heterosexual genetic relatives reared with non-heterosexual persons also have worse mental health, SMST is falsified. We conducted a systematic meta-analysis of studies containing family-genetic comparison data to interrogate the empirical support for SMST.

We systematically identified 17 empirical studies in which twins or non-twin siblings reported on both their sexual orientation and their mental health. Subsequently, we conducted a multilevel meta-analysis, focusing on the degree to which any sexual orientation disparity in mental health diminished with genetic relatedness.

Most of the mental health disparities between non-heterosexual and heterosexual persons were eliminated after controlling for family-genetic factors.

The mental health disparity between non-heterosexual and heterosexual persons is reduced by up to two-thirds once familial background factors are accounted for by comparing monozygotic twins discordant for sexual orientation. This suggests that shared familial causes, and not minority stress, are the most important causes of mental health disparities in non-heterosexual persons.

Depression exhibits significant heterogeneity in its genetic underpinnings. The role of genetic components in the development of depression and its comorbidities remains insufficiently explored.

First, depression risk loci from a large-scale genome-wide meta-analysis were annotated to Gene Ontology (GO) terms by functional enrichment. GO-based polygenic risk scores (GO-PRS) were then calculated for individuals in the UK Biobank. Principal component analysis (PCA) was applied for dimensionality reduction, followed by cluster analysis to identify genetic subtypes of depression. Multistate models were applied to assess the impact of genetic patterns on the trajectory from healthy status to incident depression, and depression to 26 subsequent diseases, as well as the associations between environmental factors and disease trajectories across genetic subtypes.

Participants were categorized into three genetic subtypes: immune-dominant, neuro-dominant, and comprehensive-risk. Significant differences in risk of depression and subsequent diseases, and susceptibility to environmental factors were observed across subtypes. Comprehensive-risk subtype showed higher risks of depression compared to immune-dominant (HR: 1.10, 95% CI: 1.05–1.15) and neuro-dominant subtype (HR: 1.12, 95% CI: 1.08–1.16). Comprehensive-risk subtype exhibited higher risks of transition from depression to subsequent diseases, such as anemia compared to immune-dominant subtype, and diseases of the digestive system compared to neuro-dominant subtype. Environmental factors were more strongly associated with the transition from depression to subsequent diseases in immune-dominant and comprehensive-risk subtypes, including cardiovascular, respiratory, and metabolic diseases.

Our findings highlight the genetic heterogeneity of depression and comorbidities, and shed light on how genetic components modulate responses to environmental factors.

Anxiety disorders show striking sex differences in prevalence, symptoms, and clinical characteristics, shaping how they manifest and are experienced.

Here, we report the first sex-specific meta-analysis of genome-wide association studies (GWAS) of anxiety, leveraging two of the largest biobank datasets, UK Biobank and All of Us, comprising 85,042 female cases with 196,789 controls and 36,732 male cases with 136,924 controls. Functional annotation, sex-specific polygenic scores (PGS), and genetic correlations were performed to assess genetic differences and functional implications.

In females, 21 lead SNPs were significantly associated with anxiety, compared to five in males. Although the genetic correlation between sexes was high, it was significantly different from one, indicating partially distinct genetic architectures. In addition, both the SNP-based observed and liability-scale heritabilities (assuming a 2:1 female-to-male prevalence ratio) were significantly higher in females. Gene-based tests and functional prioritization identified different genes associated with anxiety in females and males. Moreover, genetic correlation analyses revealed stronger associations of female anxiety with attention-deficit/hyperactivity disorder (ADHD) and body mass index (BMI), whereas male anxiety showed stronger correlations with waist-hip-ratio-adjusted BMI.

While the overall genetic architecture of anxiety is largely shared, our findings reveal distinct sex-specific genetic associations and correlations, highlighting the value of analyzing the sexes separately to uncover genetic signals that may be masked in sex-combined samples.

Cognitive reserve (CR) is a protective factor in first-episode psychosis (FEP), influencing cognitive, clinical, and functional outcomes. CR is shaped by a combination of genetic, clinical, and environmental factors, yet the extent of their respective contributions remains unclear. This study investigates the influence of polygenic risk scores (PRS), clinical and environmental variables on CR in FEP.

A cohort of 174 individuals with non-affective FEP, aged 25.5 (SD=5.3), was analyzed. CR was assessed using a socio-behavioral proxy. PRS for educational attainment (PRSEA), intelligence (PRSIQ), cognitive performance (PRSCP), occupational attainment (PRSOA), physical activity (PRSPA), and schizophrenia (PRSSZ) were calculated. Age at onset, socioeconomic status, birth weight, and family history of psychosis were considered. Multiple regression models were employed to evaluate the impact of the different predictors on CR.

PRSEA (p=0.002), age at onset (p=5.32x10-5), and family history of psychosis (p=0.001) emerged as the strongest contributors to CR. Higher PRSEA was associated with higher levels of CR, while earlier age at onset and positive family history were associated with lower CR. The model incorporating environmental, clinical, and genetic variables explained 17.7% of the variance in CR, and the one without PRS explained 13.5%. The inclusion of PRSEA in the model improved the explanatory power (Δadj.R2=0.042) and predictive accuracy (ΔRMSE=−0.288).

These findings highlight the role of precision psychiatry in better understanding CR. Early identification of individuals with earlier onset, family history of psychosis, and lower genetic predisposition to educational attainment may help characterize those with lower CR.

Childhood-onset cardiomyopathies are rare and not well characterised. This study aimed to describe the clinical features of a paediatric cohort with primary cardiomyopathies, with a particular focus on aetiology and both short- and long-term outcomes.

A retrospective descriptive study was conducted, including patients diagnosed with primary cardiomyopathies before the age of 18. Clinical presentation, aetiology, and outcomes were analysed for each morphological subtype of cardiomyopathy.

A total of 76 patients met the inclusion criteria. Dilated cardiomyopathy was the most common subtype (48.6%), followed by hypertrophic (31.5%), left ventricular non-compaction (10.5%), restrictive (5.2%), and arrhythmogenic cardiomyopathy (3.9%). The mean age at diagnosis was 6.3 ± 5.6 years, with a slight female predominance (56.6%). The rate of genetic diagnosis was 25.6%; the most commonly identified pathogenic or likely pathogenic variants were in MYH7, FLNC, TTN, and MYBPC3, across different morphological subtypes. A total of 94.7% of patients received at least one cardiovascular medication, and 9.2% received intracardiac devices. The overall mortality rate was 22.3%, and the heart transplant rate was 15.7%.

These findings highlight the heterogeneous aetiology of paediatric cardiomyopathies and the variability in outcomes according to morphological, genetic, and clinical subtypes. The results underscore the importance of individualised evaluation and management for affected patients.

Large biobanks offer unprecedented data for psychiatric genomic research, but concerns exist about representativeness and generalizability. This study examined depression prevalence and polygenic risk score (PRS) associations in the All of Us data to assess potential impacts of nonrepresentative sampling.

Depression prevalence and correlates were analyzed in two subsamples: those with self-reported personal medical history (PMH) data (N = 185,232 overall; N = 114,739 with genetic data) and those with electronic health record (EHR) data (N = 287,015 overall; N = 206,175 with genetic data). PRS weights were estimated across ancestry groups. Associations of PRS with depression were examined by state and ancestry.

Depression prevalence varied across states in both PMH (16.7–35.9%) and EHR (0.2–45.8%) data. Concordance between PMH and EHR diagnoses was low (kappa: 0.29, 95% CI: 0.30–0.30). Overall, one standard deviation increase in depression PRS was associated with lifetime depression based on PMH (odds ratio [OR] = 1.05, 95% confidence interval [CI]: 1.04–1.07) and EHR (OR = 1.05, 95% CI: 1.04–1.07). Results were generally consistent by ancestry, with the strongest signal for European ancestry (PMH: OR = 1.10, 95% CI: 1.08–1.12; EHR: OR = 1.07, 95% CI: 1.05–1.10). Associations between PRS and lifetime depression were largely consistent and significant associations varied minimally (ORs = 1.06–1.45) by state of residence in both subsamples.

Recorded depression prevalence by state in All of Us demonstrates a wide range, likely reflecting recruitment differences, EHR data completeness, and true geographic variation; yet PRS associations remained relatively stable. As studies like All of Us expand, accounting for sample composition and measurement approaches will be crucial for generating actionable findings.

Social connections might be protective against depressive and anxious symptoms and dementia in later life. The extent to which social connections are heritable versus modifiable in older age remains unknown.

We aimed to investigate the heritability of social connections and their influence on mental and cognitive health over time among older adults in a longitudinal cohort.

We analysed data from the Older Australian Twins Study (333 monozygotic, 266 dizygotic twins; 65+ years) at three time-points over 6 years. We examined the factor structure and heritability of baseline social connections and their associations with mental and cognitive health longitudinally.

We found three weakly heritable social connections factors: (a) interacting with friends/neighbours/community (h2 = 0.09, 95% CI: 0.00, 0.44); (b) family interactions/childcare (h2 = 0.13, 95% CI: 0.00, 0.43); (c) involvement in religious groups/caregiving (h2 = 0.00, 95% CI: 0.00, 0.19). Strong genetic correlations were observed between depressive symptoms and factors a (r = −0.96) and b (r = −0.60). More frequent baseline interactions with friends/neighbours/community were associated with fewer depressive symptoms cross-sectionally (B = −0.14, p = .004) and longitudinally (B = −0.09, p = 0.006), but the associations between social connections and cognitive health were not significant.

Social connections were weakly heritable, suggesting large environmental determination. Connections with friends/neighbours/community were associated with better mental health cross-sectionally and over time.