Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

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New methods, persistent issues, and one solution: Gene-environment interaction studies of childhood cognitive development

Children’s differences in cognitive development stem from the complex interplay of genetic and environmental factors. Identifying gene-environment interactions in cognitive development is key for effectively targeting interventions that improve children’s life chances. The advent of polygenic scores, which aggregate DNA variants to index a person’s genetic propensities for phenotypic development, has created unprecedented opportunities for pinpointing gene-environment interactions. Yet, the issue of statistical power -- the probability of detecting a true effect – prevails, and no replicable gene-environment interactions in child cognitive development have been reported. The solution is simple and daunting at the same time: Gathering larger samples will be the key to ushering a new era of replicable gene-environment interaction findings

Data and data dictionary for "Links between Personality, Affective Cognition, Emotion Regulation and Affective Disorders"

Vulnerability to anxiety and depressive disorders is affected by risk and resilience factors, such as personality, use of emotion regulation strategies, and affective cognition. Previous research has identified personality constructs best explaining variance in anxiety and depression (Lyon et al, 2020; 2021), however the mediating mechanisms are unknown. This study aimed to investigate the mediating roles of emotion regulation strategies and affective cognition in the relationship between personality constructs and affective disorders. Data were collected from a sample of 276 students and staff at the University of Manchester. Measures included both broad and narrow Big Five personality constructs; COPE Inventory strategies; a dot-probe task to measure attentional biases to emotional information; both a questionnaire and a computerised cognitive to measure interpretation of emotional images; and measures of anxiety and depression

Code for "Links between Personality, Affective Cognition, Emotion Regulation and Affective Disorders"

Vulnerability to anxiety and depressive disorders is affected by risk and resilience factors, such as personality, use of emotion regulation strategies, and affective cognition. Previous research has identified personality constructs best explaining variance in anxiety and depression (Lyon et al, 2020; 2021), however the mediating mechanisms are unknown. This study aimed to investigate the mediating roles of emotion regulation strategies and affective cognition in the relationship between personality constructs and affective disorders. Data were collected from a sample of 276 students and staff at the University of Manchester. Measures included both broad and narrow Big Five personality constructs; COPE Inventory strategies; a dot-probe task to measure attentional biases to emotional information; both a questionnaire and a computerised cognitive to measure interpretation of emotional images; and measures of anxiety and depression

Data for "Emotion Regulation Strategies Mediate the Relationship between Personality and Mental Health during COVID-19"

Anxiety and depression are the most prevalent classes of mental illnesses; rates of anxiety and depression have been exacerbated due to the COVID-19 pandemic. Vulnerability to anxiety and depression are affected by risk and resilience factors, such as personality constructs. Recent research (e.g., Lyon et al, 2020; 2021) suggests that, out of all 30 NEO-PI-R personality constructs, variance in anxiety and depression are explained by a small number of personality constructs. However it is unclear which mechanisms mediate the relationship between these personality constructs and anxiety and depression. The purpose of this study was to investigate the mediating effect of emotion regulation strategies on the relationship between personality constructs and COVID-related anxiety and depression. Data were collected from a sample of 210 students at the University of Manchester. Measures included a select number of narrow Big Five personality facets which explain variance in anxiety and depression (facets depression, assertiveness, gregariousness, positive emotion and competence), select COPE Inventory strategies associated with coping with pandemics, and COVID-related anxiety and depression. Measures of COPE strategies and mental health were adapted to refer to coping and mental health in response to COVID pandemic