Dataset Information

Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior.

ABSTRACT: Human variation in brain morphology and behavior are related and highly heritable. Yet, it is largely unknown to what extent specific features of brain morphology and behavior are genetically related. Here, we introduce a computationally efficient approach for multivariate genomic-relatedness-based restricted maximum likelihood (MGREML) to estimate the genetic correlation between a large number of phenotypes simultaneously. Using individual-level data (N = 20,190) from the UK Biobank, we provide estimates of the heritability of gray-matter volume in 74 regions of interest (ROIs) in the brain and we map genetic correlations between these ROIs and health-relevant behavioral outcomes, including intelligence. We find four genetically distinct clusters in the brain that are aligned with standard anatomical subdivision in neuroscience. Behavioral traits have distinct genetic correlations with brain morphology which suggests trait-specific relevance of ROIs. These empirical results illustrate how MGREML can be used to estimate internally consistent and high-dimensional genetic correlation matrices in large datasets.

SUBMITTER: de Vlaming R

PROVIDER: S-EPMC8511103 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior.

de Vlaming Ronald R Slob Eric A W EAW Jansen Philip R PR Dagher Alain A Koellinger Philipp D PD Groenen Patrick J F PJF Rietveld Cornelius A CA

Communications biology 20211012 1

Human variation in brain morphology and behavior are related and highly heritable. Yet, it is largely unknown to what extent specific features of brain morphology and behavior are genetically related. Here, we introduce a computationally efficient approach for multivariate genomic-relatedness-based restricted maximum likelihood (MGREML) to estimate the genetic correlation between a large number of phenotypes simultaneously. Using individual-level data (N = 20,190) from the UK Biobank, we provide ...[more]

PMID: 34642422

Similar Datasets

Project description:BackgroundIrritable bowel syndrome (IBS) often co-occurs with psychiatric and gastrointestinal disorders. A recent genome-wide association study (GWAS) identified several genetic risk variants for IBS. However, most of the heritability remains unidentified, and the genetic overlap with psychiatric and somatic disorders is not quantified beyond genome-wide genetic correlations. Here, we characterize the genetic architecture of IBS, further, investigate its genetic overlap with psychiatric and gastrointestinal phenotypes, and identify novel genomic risk loci.MethodsUsing GWAS summary statistics of IBS (53,400 cases and 433,201 controls), and psychiatric and gastrointestinal phenotypes, we performed bivariate casual mixture model analysis to characterize the genetic architecture and genetic overlap between these phenotypes. We leveraged identified genetic overlap to boost the discovery of genomic loci associated with IBS, and to identify specific shared loci associated with both IBS and psychiatric and gastrointestinal phenotypes, using the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework. We used functional mapping and gene annotation (FUMA) for functional analyses.ResultsIBS was highly polygenic with 12k trait-influencing variants. We found extensive polygenic overlap between IBS and psychiatric disorders and to a lesser extent with gastrointestinal diseases. We identified 132 independent IBS-associated loci (condFDR < 0.05) by conditioning on psychiatric disorders (n = 127) and gastrointestinal diseases (n = 24). Using conjFDR, 70 unique loci were shared between IBS and psychiatric disorders. Functional analyses of shared loci revealed enrichment for biological pathways of the nervous and immune systems. Genetic correlations and shared loci between psychiatric disorders and IBS subtypes were different.ConclusionsWe found extensive polygenic overlap of IBS and psychiatric and gastrointestinal phenotypes beyond what was revealed with genetic correlations. Leveraging the overlap, we discovered genetic loci associated with IBS which implicate a wide range of biological pathways beyond the gut-brain axis. Genetic differences may underlie the clinical subtype of IBS. These results increase our understanding of the pathophysiology of IBS which may form the basis for the development of individualized interventions.

Project description:Shared developmental, physiological, and molecular mechanisms can generate strong genetic covariances across suites of traits, constraining genetic variability, and evolvability to certain axes in multivariate trait space ("variational modules" or "syndromes"). Such trait suites will not only respond jointly to selection; they will also covary across populations that diverged from one another by genetic drift. We report evidence for such a genetically correlated trait suite that links traits related to energy metabolism along a "power-endurance" axis in Drosophila melanogaster. The "power" pole of the axis is characterized by high potential for energy generation and expenditure-high expression of glycolysis and TCA cycle genes, high abundance of mitochondria, and high spontaneous locomotor activity. The opposite "endurance" pole is characterized by high triglyceride (fat) reserves, locomotor endurance, and starvation resistance (and low values of traits associated with the "power" pole). This trait suite also aligns with the first principal component of metabolome; the "power" direction is characterized by low levels of trehalose (blood sugar) and high levels of some amino acids and their derivatives, including creatine, a compound known to facilitate energy production in muscles. Our evidence comes from six replicate "Selected" populations adapted to a nutrient-poor larval diet regime during 250 generations of experimental evolution and six "Control" populations evolved in parallel on a standard diet regime. We found that, within each of these experimental evolutionary regimes, the above traits strongly covaried along this "power-endurance" axis across replicate populations which diversified by drift, indicating a shared genetic architecture. The two evolutionary regimes also drove divergence along this axis, with Selected populations on average displaced towards the "power" direction compared to Controls. Aspects of this "power-endurance" axis resemble the "pace of life" syndrome and the "thrifty phenotype"; it may have evolved as part of a coordinated organismal response to nutritional conditions.

Dataset Information

Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior.

Publications

Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets