Biology subjects

Merikangas, A. K.

Publications and source records attributed to Merikangas, A. K..

3 recordsLinked to original sources

bioRxiv2023

The overlapping genetic architecture of psychiatric disorders and cortical brain structure

Both psychiatric vulnerability and cortical structure are shaped by the cumulative effect of common genetic variants across the genome. However, the shared genetic underpinnings between psychiatric disorders and brain structural phenotypes, such as thickness and surface area of the cerebral cortex, remains elusive. In this study, we employed pleiotropy-informed conjunctional false discovery rate analysis to investigate shared loci across genome-wide association scans of regional cortical thickness, surface area, and seven psychiatric disorders in approximately 700,000 individuals of European ancestry. Aggregating regional measures, we identified 50 genetic loci shared between psychiatric disorders and surface area, as well as 26 genetic loci shared with cortical thickness. Risk alleles exhibited bidirectional effects on both cortical thickness and surface area, such that some risk alleles for each disorder increased regional brain size while other risk alleles decreased regional brain size. Due to bidirectional effects, in many cases we observed extensive pleiotropy between an imaging phenotype and a psychiatric disorder even in the absence of a significant genetic correlation between them. The impact of genetic risk for psychiatric disorders on regional brain structure did exhibit a consistent pattern across highly comorbid psychiatric disorders, with 80% of the genetic loci shared across multiple disorders displaying consistent directions of effect. Cortical patterning of genetic overlap revealed a hierarchical genetic architecture, with the association cortex and sensorimotor cortex representing two extremes of shared genetic influence on psychiatric disorders and brain structural variation. Integrating multi-scale functional annotations and transcriptomic profiles, we observed that shared genetic loci were enriched in active genomic regions, converged on neurobiological and metabolic pathways, and showed differential expression in postmortem brain tissue from individuals with psychiatric disorders. Cumulatively, these findings provide a significant advance in our understanding of the overlapping polygenic architecture between psychopathology and cortical brain structure.

genetics↗

bioRxiv2021

Stability of Polygenic Scores Across Discovery Genome-Wide Association Studies

Polygenic scores (PGS) are commonly evaluated in terms of their predictive accuracy at the population level by the proportion of phenotypic variance they explain. To be useful for precision medicine applications, they also need to be evaluated at the individual patient level when phenotypes are not necessarily already known. Hence, we investigated the stability of PGS in European-American (EUR)- and African-American (AFR)-ancestry individuals from the Philadelphia Neurodevelopmental Cohort (PNC) and the Adolescent Brain Cognitive Development (ABCD) cohort using different discovery GWAS for post-traumatic stress disorder (PTSD), type-2 diabetes (T2D), and height. We found that pairs of EUR-ancestry GWAS for the same trait had genetic correlations > 0.92. However, PGS calculated from pairs of sameancestry and different-ancestry GWAS had correlations that ranged from <0.01 to 0.74. PGS stability was higher for GWAS that explained more of the trait variance, with height PGS being more stable than PTSD or T2D PGS. Focusing on the upper end of the PGS distribution, different discovery GWAS do not consistently identify the same individuals in the upper quantiles, with the best case being 60% of individuals above the 80th percentile of PGS overlapping from one height GWAS to another. The degree of overlap decreases sharply as higher quantiles, less heritable traits, and different-ancestry GWAS are considered. PGS computed from different discovery GWAS have only modest correlation at the level of the individual patient, underscoring the need to proceed cautiously with integrating PGS into precision medicine applications.

genetics↗

bioRxiv2019

Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data

ObjectivePrediction of disease risk is a key component of precision medicine. Common, complex traits such as psychiatric disorders have a complex polygenic architecture making the identification of a single risk predictor difficult. Polygenic risk scores (PRS) denoting the sum of an individuals genetic liability for a disorder are a promising biomarker for psychiatric disorders, but require evaluation in a clinical setting. MethodsWe develop PRS for six psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, anorexia nervosa) and 17 non-psychiatric traits in over 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We perform phenome-wide association analyses to test their association across disease categories. ResultsFour of the six psychiatric PRS were associated with their primary phenotypes (odds ratios between 1.2-1.6). Individuals in the highest quintile of risk had between 1.4-2.9 times higher odds of the disorder than the remaining 80% of individuals. Cross-trait associations were identified both within the psychiatric domain and across trait domains. PRS for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder. ConclusionsWe demonstrate that the genetic architecture of common psychiatric disorders identified in a clinical setting confirms that which has been derived from large consortia. Even though the risk associated is low in this context, these results suggest that as identification of genetic markers proceeds, PRS is a promising approach for prediction of psychiatric disorders and associated conditions in clinical registries.

genetics↗