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A. C. Heat

Bio: A. C. Heat is an academic researcher from Washington University in St. Louis. The author has contributed to research in topics: Odds ratio & Major depressive disorder. The author has an hindex of 2, co-authored 2 publications receiving 74 citations.

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Journal ArticleDOI
TL;DR: How polygenic risk score may be informative at different points in the disease trajectory is considered giving examples of progress in the field and discussing obstacles that need to be addressed before clinical implementation.
Abstract: Genome-wide association studies have shown unequivocally that common complex disorders have a polygenic genetic architecture and have enabled researchers to identify genetic variants associated with diseases. These variants can be combined into a polygenic risk score that captures part of an individual’s susceptibility to diseases. Polygenic risk scores have been widely applied in research studies, confirming the association between the scores and disease status, but their clinical utility has yet to be established. Polygenic risk scores may be used to estimate an individual’s lifetime genetic risk of disease, but the current discriminative ability is low in the general population. Clinical implementation of polygenic risk score (PRS) may be useful in cohorts where there is a higher prior probability of disease, for example, in early stages of diseases to assist in diagnosis or to inform treatment choices. Important considerations are the weaker evidence base in application to non-European ancestry and the challenges in translating an individual’s PRS from a percentile of a normal distribution to a lifetime disease risk. In this review, we consider how PRS may be informative at different points in the disease trajectory giving examples of progress in the field and discussing obstacles that need to be addressed before clinical implementation.

542 citations

Journal ArticleDOI
TL;DR: The persistent alterations associated with childhood maltreatment are summarized, including alterations in the hypothalamic-pituitary-adrenal axis and inflammatory cytokines, which may contribute to disease vulnerability and a more pernicious disease course.
Abstract: A large body of evidence has demonstrated that exposure to childhood maltreatment at any stage of development can have long-lasting consequences. It is associated with a marked increase in risk for psychiatric and medical disorders. This review summarizes the literature investigating the effects of childhood maltreatment on disease vulnerability for mood disorders, specifically summarizing cross-sectional and more recent longitudinal studies demonstrating that childhood maltreatment is more prevalent and is associated with increased risk for first mood episode, episode recurrence, greater comorbidities, and increased risk for suicidal ideation and attempts in individuals with mood disorders. It summarizes the persistent alterations associated with childhood maltreatment, including alterations in the hypothalamic-pituitary-adrenal axis and inflammatory cytokines, which may contribute to disease vulnerability and a more pernicious disease course. The authors discuss several candidate genes and environmental factors (for example, substance use) that may alter disease vulnerability and illness course and neurobiological associations that may mediate these relationships following childhood maltreatment. Studies provide insight into modifiable mechanisms and provide direction to improve both treatment and prevention strategies.

218 citations

Journal ArticleDOI
TL;DR: The results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.
Abstract: Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094–92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10−7 versus rg = −0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10−4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.

101 citations

Journal ArticleDOI
TL;DR: Given the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods, and highlight large differences in genetic and environmental influences between psychiatric disorders.
Abstract: Background Most studies underline the contribution of heritable factors for psychiatric disorders. However, heritability estimates depend on the population under study, diagnostic instruments, and study designs that each has its inherent assumptions, strengths, and biases. We aim to test the homogeneity in heritability estimates between two powerful, and state of the art study designs for eight psychiatric disorders. Methods We assessed heritability based on data of Swedish siblings (N = 4 408 646 full and maternal half-siblings), and based on summary data of eight samples with measured genotypes (N = 125 533 cases and 208 215 controls). All data were based on standard diagnostic criteria. Eight psychiatric disorders were studied: (1) alcohol dependence (AD), (2) anorexia nervosa, (3) attention deficit/hyperactivity disorder (ADHD), (4) autism spectrum disorder, (5) bipolar disorder, (6) major depressive disorder, (7) obsessive-compulsive disorder (OCD), and (8) schizophrenia. Results Heritability estimates from sibling data varied from 0.30 for Major Depression to 0.80 for ADHD. The estimates based on the measured genotypes were lower, ranging from 0.10 for AD to 0.28 for OCD, but were significant, and correlated positively (0.19) with national sibling-based estimates. When removing OCD from the data the correlation increased to 0.50. Conclusions Given the unique character of each study design, the convergent findings for these eight psychiatric conditions suggest that heritability estimates are robust across different methods. The findings also highlight large differences in genetic and environmental influences between psychiatric disorders, providing future directions for etiological psychiatric research.

100 citations

Journal ArticleDOI
TL;DR: Recent efforts to identify depression subtypes using clinical and data-driven approaches are reviewed, differences in genetic architecture of depression across contexts are examined, and it is argued that heterogeneity in operationalizations of depression is likely a considerable source of inconsistency.
Abstract: With progress in genome-wide association studies of depression, from identifying zero hits in ~16 000 individuals in 2013 to 223 hits in more than a million individuals in 2020, understanding the genetic architecture of this debilitating condition no longer appears to be an impossible task The pressing question now is whether recently discovered variants describe the etiology of a single disease entity There are a myriad of ways to measure and operationalize depression severity, and major depressive disorder as defined in the Diagnostic and Statistical Manual of Mental Disorders-5 can manifest in more than 10 000 ways based on symptom profiles alone Variations in developmental timing, comorbidity and environmental contexts across individuals and samples further add to the heterogeneity With big data increasingly enabling genomic discovery in psychiatry, it is more timely than ever to explicitly disentangle genetic contributions to what is likely 'depressions' rather than depression Here, we introduce three sources of heterogeneity: operationalization, manifestation and etiology We review recent efforts to identify depression subtypes using clinical and data-driven approaches, examine differences in genetic architecture of depression across contexts, and argue that heterogeneity in operationalizations of depression is likely a considerable source of inconsistency Finally, we offer recommendations and considerations for the field going forward

78 citations