| Title: | MUTATE: a human genetic atlas of multiorgan artificial intelligence endophenotypes using genome-wide association summary statistics |
| Journal: | Briefings in Bioinformatics |
| Published: | 4 Mar 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40135505/ |
| DOI: | https://doi.org/10.1093/bib/bbaf125 |
| URL: | http://dx.doi.org/10.1093/bib/bbaf125 |
Publication 15654
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Abstract
Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide intermediate phenotypes (i.e. endophenotypes) that bridge the genetics and clinical manifestations of human disease. However, the genetic architecture of these AI endophenotypes remains largely unexplored in the context of human multiorgan system diseases. Using publicly available genome-wide association study summary statistics from the UK Biobank (UKBB), FinnGen, and the Psychiatric Genomics Consortium, we comprehensively depicted the genetic architecture of 2024 multiorgan AI endophenotypes (MAEs). We comparatively assessed the single-nucleotide polymorphism-based heritability, polygenicity, and natural selection signatures of 2024 MAEs using methods commonly used in the field. Genetic correlation and Mendelian randomization analyses reveal both within-organ relationships and cross-organ interconnections. Bi-directional causal relationships were established between chronic human diseases and MAEs across multiple organ systems, including Alzheimer's disease for the brain, diabetes for the metabolic system, asthma for the pulmonary system, and hypertension for the cardiovascular system. Finally, we derived polygenic risk scores for the 2024 MAEs for individuals not used to calculate MAEs and returned these to the UKBB. Our findings underscore the promise of the MAEs as new instruments to ameliorate overall human health. All results are encapsulated into the MUlTiorgan AI endophenoTypE genetic atlas and are publicly available at https://labs-laboratory.com/mutate.</p>
9 Keywords
- Artificial Intelligence
- Endophenotypes
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Humans
- Mendelian Randomization Analysis
- Multifactorial Inheritance
- Phenotype
- Polymorphism, Single Nucleotide
9 Authors
- Aleix Boquet-Pujadas
- Jian Zeng
- Ye Ella Tian
- Zhijian Yang
- Li Shen
- Andrew Zalesky
- Christos Davatzikos
- the MULTI Consortium
- Junhao Wen
Enabling scientific discoveries that improve human health