Genome-wide Pleiotropy Analyses between Chronic Physical Conditions and Brain Disorders
Poster No:
870
Submission Type:
Abstract Submission
Authors:
Yujie Zhao1, Wei Cheng1
Institutions:
1Fudan University, Shanghai, - Select -
First Author:
Co-Author:
Introduction:
Comorbidity between chronic physical conditions and brain disorders is highly prevalent, driven prominently by the shared genetic architecture. Yet, the extent to which shared genetics contribute to these complex comorbidities remains unclear. To elucidate the shared genetic etiologies between chronic and brain diseases, and to reveal the effect of polygenic risk architecture on the risk of comorbidity.
Methods:
Leveraging the published large-scale genome-wide association studies (GWAS), we first performed cross-trait genetic correlation analyses between 9 chronic physical conditions and 15 brain disorders. Genome-wide pleiotropic association analyses sequentially detected pleiotropic single nucleotide polymorphisms (SNPs), loci, and genes, and enrichment analyses elucidated the potential shared neurobiological pathways. Bidirectional Mendelian Randomization (MR) analyses were utilized to identify the causality across these pairwise diseases. Survival analyses using diagnostic outcomes from UK Biobank (UKB) and polygenic risk scores (PRSs) evaluated whether PRS for one disease predicts the risk of comorbidity with another disorder.
Results:
Incorporating the GWAS data involving 9 chronic physical conditions and 15 brain disorders, we uncovered substantial genetic correlations among 35 out of 135 pairwise diseases. Pleiotropic analyses revealed 3,448 significant pleiotropic SNPs across these 35 pairwise diseases, mapped to 250 pleiotropic loci, with 63 loci showing evidence of colocalization. Gene-based association analyses pinpointed 167 unique pleiotropic genes, notably enriched in brain structural tissues, including the hippocampus, amygdala, and anterior cingulate cortex, as well as neuronal development phenotypes and protein synthesis pathways. In disease-level analyses, cross-trait MR analyses illustrated bidirectional causality in 4 disease pairs and 25 associations with unidirectional causality. Survival analyses identified extensive results on PRS-based risk prediction for developing comorbidity, across 2 chronic physical conditions (CHD and T2D) and 8 brain disorders (ALD, ANX, AD, BP, MDD, MS, PTSD, and SCZ), and demonstrated increased polygenic level of one disease would escalate the risk of comorbidity with another disease in pairs by up to six-fold.
Conclusions:
These findings uncovered a comprehensive landscape of shared genomic variants, loci, genes, and neurobiological pathways between these two categories of diseases, providing a foundation for developing precision medicine approaches from a polygenic perspective.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s)
Neurodevelopmental/ Early Life (eg. ADHD, autism)
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Genetics:
Genetic Association Studies 2
Genetics Other 1
Keywords:
Cortex
Data analysis
Degenerative Disease
Phenotype-Genotype
Psychiatric Disorders
Sub-Cortical
1|2Indicates the priority used for review
·Manhattan plots of pleiotropic analysis and genome-wide gene-based association analysis
·Gene-level and disease-level analyses