Elham Assary

Anxiety is heritable and exists on a continuum, with symptoms ranging from adaptive threat response to clinical disorder. Here we performed a genome-wide association meta-analysis of generalized anxiety symptom severity in 693,869 individuals of European ancestry from 14 cohorts. We identified 80 independent genome-wide significant variants within 74 loci, 39 of which were newly associated with anxiety. SNP-based heritability was 5.9% (posterior s.d. = 0.15%). Polygenic scores were significantly associated with anxiety symptom severity and disorder in European, African and South Asian ancestry samples ( R ² = 1.2–2.9%). Significant genetic correlations ( r _g ) were estimated with mental and physical health traits, including case–control anxiety, neuroticism and depression ( r _g = 0.71–0.85), irritable bowel syndrome ( r _g = 0.57), coronary artery disease, endometriosis and migraine ( r _g = 0.20–0.27). Gene-based and pathway analyses implicated synaptic and axonal processes, with enriched expression in the brain. These findings highlight the discovery power gained from analysing a quantitative trait rather than a case–control phenotype in anxiety genetics.

Background: Smoking and depression often co-occur in young adults, potentially due to reciprocal causal effects and/or shared underlying etiological factors. Here, we tested causal hypotheses between smoking quantity (cigarettes per day; CigDay ) and depressive symptoms ( DepSx ) using novel Biometrical Cross-Lagged Panel Models (CLPMs), which integrate twin developmental and direction-of-causation analyses for more robust causal inference in longitudinal twin studies. Methods: Study sample included 10,034 participants (61.6% females; 4,112 twin pairs) from the Twins Early Development Study, with up to six repeated assessments spanning ages 21–29. The Biometrical CLPM provided three key innovations over standard twin CLPM: distinct autoregressive processes of latent genetic and environmental factors; cross-lagged genetic and environmental liabilities, contrasting confounding and causation; and cross-sectional causal effects, distinguishing between proximal (short-term) and distal (lagged) causation. Results: In the two largest waves assessed approximately four years apart, genetic liabilities for both variables remained highly stable, while environmental influences showed considerable temporal variation. In the standard CLPM, CigDay predicted DepSx four years later. However, in the Biometrical CLPM, the cross-lagged phenotypic associations were attenuated and non-significant when accounting for the differential genetic and environmental developmental processes. Adding the cross-sectional causal paths revealed significant bidirectional proximal effects, with a stronger CigDay→DepSx effect. Across all six waves with intervals up to two years, analyses consistently showed significant bidirectional cross-lagged associations. Conclusions: The findings support a reinforcing feedback loop between CigDay and DepSx during young adulthood, involving bidirectional effects that persist for up to two years but dissipate over longer intervals.

Introductory paragraph: Panic attacks, sudden episodes of intense fear accompanied by physical and psychological symptoms, affect approximately 23% of the population ^1,2 . Panic disorder, diagnosed in 2– 4% ³ , involves recurrent attacks followed by persistent worry about further attacks, leading to functional impairment and avoidance behaviours ^1,2 . We conducted genome-wide association meta-analyses of panic attacks and panic disorder (61,746 and 29,775 cases, respectively, and 105,814 controls), identifying the first genome-wide significant variants for both traits (16 for panic attacks; 7 for panic disorder). Geneset analysis using single-cell RNA sequencing data implicated afferent neurons from the eye, heart, and lung in panic attacks, suggesting a critical role for sensory processing and interoceptive awareness. Further analyses suggested that these associations generalize to other psychiatric disorders. These findings offer novel insights into the biological mechanisms underlying panic, the role of afferent neurons, and may inform the development of more targeted and effective interventions.

Individual sensitivity to environmental exposures may be genetically influenced. This genotype-by-environment interplay implies differences in phenotypic variance across genotypes, but these variants have proven challenging to detect. Genome-wide association studies of monozygotic twin differences are conducted through family-based variance analyses, which are more robust to the systemic biases that impact population-based methods. We combined data from 21,792 monozygotic twins (10,896 pairs) from 11 studies to conduct one of the largest genome-wide association study meta-analyses of monozygotic phenotypic differences, in children, adolescents and adults separately, for seven psychiatric and neurodevelopmental phenotypes: attention deficit hyperactivity disorder symptoms, autistic traits, anxiety and depression symptoms, psychotic-like experiences, neuroticism and wellbeing. The proportions of phenotypic variance explained by single-nucleotide polymorphisms in these phenotypes were estimated (h ² = 0–18%), but were imprecise. We identified 13 genome-wide significant associations (single-nucleotide polymorphisms, genes and gene sets), including genes related to stress reactivity for depression, growth factor-related genes for autistic traits and catecholamine uptake-related genes for psychotic-like experiences. This is the largest genetic study of monozygotic twins to date by an order of magnitude, evidencing an alternative method to study the genetic architecture of environmental sensitivity. The statistical power was limited for some analyses, calling for better-powered future studies.

Individual sensitivity to environmental exposures may be genetically influenced. This genotype-by-environment interplay implies differences in phenotypic variance across genotypes. However, environmental sensitivity genetic variants have proven challenging to detect. GWAS of monozygotic twin differences is a family-based variance analysis method, which is more robust to systemic biases that impact population-based methods. We combined data from up to 21,792 monozygotic twins (10,896 pairs) from 11 studies to conduct the largest GWAS meta-analysis of monozygotic phenotypic differences in children and adolescents/adults for seven psychiatric and neurodevelopmental phenotypes: attention deficit hyperactivity disorder (ADHD) symptoms, autistic traits, anxiety and depression symptoms, psychotic-like experiences, neuroticism, and wellbeing. The SNP-heritability of variance in these phenotypes were estimated (h2: 0% to 18%), but were imprecise. We identified a total of 13 genome-wide significant associations (SNP, gene, and gene-set), including genes related to stress-reactivity for depression, growth factor-related genes for autistic traits and catecholamine uptake-related genes for psychotic-like experiences. Monozygotic twins are an important new source of evidence about the genetics of environmental sensitivity.

Greater environmental sensitivity has been associated with increased risk of mental health problems, especially in response to stressors, and lower levels of subjective wellbeing. Conversely, sensitivity also correlates with lower risk of emotional problems in the absence of adversity, and in response to positive environmental influences. Additionally, sensitivity has been found to correlate positively with autistic traits. Individual differences in environmental sensitivity are partly heritable, but it is unknown to what extent the aetiological factors underlying sensitivity overlap with those on emotional problems (anxiety and depressive symptoms), autistic traits and wellbeing. The current study used multivariate twin models and data on sensitivity, emotional problems, autistic traits, and several indices of psychological and subjective wellbeing, from over 2800 adolescent twins in England and Wales. We found that greater overall sensitivity correlated with greater emotional problems, autistic traits, and lower subjective wellbeing. A similar pattern of correlations was found for the Excitation and Sensory factors of sensitivity, but, in contrast, the Aesthetic factor was positively correlated with psychological wellbeing, though not with emotional problems nor autistic traits. The observed correlations were largely due to overlapping genetic influences. Importantly, genetic influences underlying sensitivity explained between 2 and 12% of the variations in emotional problems, autistic traits, and subjective wellbeing, independent of trait-specific or overlapping genetic influences. These findings encourage incorporating the genetics of environmental sensitivity in future genomic studies aiming to delineate the heterogeneity in emotional problems, autistic traits, and wellbeing.

Background: Emotional symptoms, such as anxiety and depressive symptoms, are common during adolescence, often persist over time, and can precede the emergence of severe anxiety and depressive disorders. Studies suggest that a vicious cycle of reciprocal influences between emotional symptoms and interpersonal difficulties may explain why some adolescents suffer from persisting emotional symptoms. However, the role of different types of interpersonal difficulties, such as social isolation and peer victimisation, in these reciprocal associations is still unclear. In addition, the lack of longitudinal twin studies conducted on emotional symptoms during adolescence means that the genetic and environmental contributions to these relationships during adolescence remain unknown. Methods: Participants ( N = 15,869) from the Twins Early Development Study completed self‐reports of emotional symptoms, social isolation and peer victimisation at 12, 16 and 21 years old. A phenotypic cross‐lagged model examined reciprocal associations between variables over time, and a genetic extension of this model examined the aetiology of the relationships between variables at each timepoint. Results: First, emotional symptoms were reciprocally and independently associated with both social isolation and peer victimisation over time, indicating that different forms of interpersonal difficulties uniquely contributed to emotional symptoms during adolescence and vice versa. Second, early peer victimisation predicted later emotional symptoms via social isolation in mid‐adolescence, indicating that social isolation may constitute an intermediate pathway through which peer victimisation predicts longer‐term emotional symptoms. Finally, individual differences in emotional symptoms were mostly accounted for by non‐shared environmental factors at each timepoint, and both gene–environment and individual‐specific environmental mechanisms were involved in the relationships between emotional symptoms and interpersonal difficulties. Conclusions: Our study highlights the necessity to intervene early in adolescence to prevent the escalation of emotional symptoms over time and to consider social isolation and peer victimisation as important risk factors for the long‐term persistence of emotional symptoms.

Diathesis‐stress models conceptualise individual differences in propensity for psychopathology as an interaction between environmental risk factors and intra‐individual vulnerabilities. In contrast, the differential susceptibility theory and related frameworks view intra‐individual differences as variations in sensitivity to the environments rather than merely vulnerability to them. Specifically, they suggest that more sensitive individuals are more affected by the quality of their context, whether positive or negative, than others who are less sensitive. Empirical research over the last two decades has found support for this notion in that greater sensitivity is associated with a greater risk of psychopathology in adverse contexts, but also with lower risk in positive environments. However, despite growing academic and public interest in this field, it is currently unclear to what extent the differential susceptibility model is relevant, or applicable, to clinical practice. The purpose of this review is to focus on the differential susceptibility theory as an alternative explanation of individual differences in mental health and examine its relevance in the treatment of mental health problems in young people. We provide an overview of differential susceptibility and related theories, and current relevant research in the field. We identify potential implications of differential susceptibility models for understanding and treating mental health problems in young people, whilst also highlighting important gaps in research that limit their application at present. Finally, we suggest directions for future research that will assist in the translation of differential susceptibility theories into clinical practice.

Background: Despite being considered a measure of environmental risk, reported life events are partly heritable. One mechanism that may contribute to this heritability is genetic influences on sensitivity, relating to how individuals process and interpret internal and external signals. The aim of this study was to explore the genetic and environmental overlap between self‐reported life events and measures of sensitivity. Methods: At age 17, 2,939 individuals from the Twins Early Development Study (TEDS) completed measures of anxiety sensitivity (Children's Anxiety Sensitivity Index), environmental sensitivity (Highly Sensitive Child Scale) and reported their experience of 20 recent life events. Using multivariate Cholesky decomposition models, we investigated the shared genetic and environmental influences on the associations between these measures of sensitivity and the number of reported life events, as well as both negative and positive ratings of life events. Results: The majority of the associations between anxiety sensitivity, environmental sensitivity and reported life events were explained by shared genetic influences (60%–75%), with the remainder explained by nonshared environmental influences (25%–40%). Environmental sensitivity showed comparable genetic correlations with both negative and positive ratings of life events ( r _A = .21 and .15), anxiety sensitivity only showed a significant genetic correlation with negative ratings of life events ( r _A = .33). Approximately 10% of the genetic influences on reported life events were accounted for by influences shared with anxiety sensitivity and environmental sensitivity. Conclusion: Differences in how individuals process the contextual aspects of the environment or interpret their own physical and emotional response to environmental stimuli may be one mechanism through which genetic liability influences the subjective experience of life events.