Genome-phenome explorer (GePhEx): a tool for the visualization and interpretation of phenotypic relationships supported by genetic evidence

Locus-level antagonistic selection shaped the polygenic architecture of human complex diseases

BACKGROUND

We aimed to evaluate the potential role of antagonistic selection in polygenic diseases: if one variant increases the risk of one disease and decreases the risk of another disease, the signals of genetic risk elimination by natural selection will be distorted, which leads to a higher frequency of risk alleles.

METHODS

We applied local genetic correlations and transcriptome-wide association studies to identify genomic loci and genes adversely associated with at least two diseases. Then, we used different population genetic metrics to measure the signals of natural selection for these loci and genes.

RESULTS

First, we identified 2120 cases of antagonistic pleiotropy (negative local genetic correlation) among 87 diseases in 716 genomic loci (antagonistic loci). Next, by comparing with non-antagonistic loci, we observed that antagonistic loci explained an excess proportion of disease heritability (median 6%), showed enhanced signals of balancing selection, and reduced signals of directional polygenic adaptation. Then, at the gene expression level, we identified 31,991 cases of antagonistic pleiotropy among 98 diseases at 4368 genes. However, evidence of altered signals of selection pressure and heritability distribution at the gene expression level is limited.

CONCLUSION

We conclude that antagonistic pleiotropy is widespread among human polygenic diseases, and it has distorted the evolutionary signal and genetic architecture of diseases at the locus level.

mGWAS-Explorer: Linking SNPs, Genes, Metabolites, and Diseases for Functional Insights

Tens of thousands of single-nucleotide polymorphisms (SNPs) have been identified to be significantly associated with metabolite abundance in over 65 genome-wide association studies with metabolomics (mGWAS) to date. Obtaining mechanistic or functional insights from these associations for translational applications has become a key research area in the mGWAS community. Here, we introduce mGWAS-Explorer, a user-friendly web-based platform to help connect SNPs, metabolites, genes, and their known disease associations via powerful network visual analytics. The application of the mGWAS-Explorer was demonstrated using a COVID-19 and a type 2 diabetes case studies.

The shared genetic architecture of schizophrenia, bipolar disorder and lifespan

Psychiatric disorders such as Schizophrenia (SCZ) and Bipolar Disorder (BD) represent an evolutionary paradox, as they exhibit strong negative effects on fitness, such as decreased fecundity and early mortality, yet they persist at a worldwide prevalence of approximately 1%. Molecular mechanisms affecting lifespan, which may be widely common among complex diseases with fitness effects, can be studied by the integrated analysis of data from genome-wide association studies (GWAS) of human longevity together with any disease of interest. Here, we report the first of such studies, focusing on the genetic overlap-pleiotropy-between two psychiatric disorders with shortened lifespan, SCZ and BD, and human parental lifespan (PLS) as a surrogate of life expectancy. Our results are twofold: first, we demonstrate extensive polygenic overlap between SCZ and PLS and to a lesser extent between BD and PLS. Second, we identified novel loci shared between PLS and SCZ (n = 39), and BD (n = 8). Whereas most of the identified SCZ (66%) and BD (62%) pleiotropic risk alleles were associated with reduced lifespan, we also detected some antagonistic protective alleles associated to shorter lifespans. In fact, top-associated SNPs with SCZ seems to explain longevity variance explained (LVE) better than many other life-threatening diseases, including Type 2 diabetes and most cancers, probably due to a high overlap with smoking-related pathways. Overall, our study provides evidence of a genetic burden driven through premature mortality among people with SCZ, which can have profound implications for understanding, and potentially treating, the mortality gap associated with this psychiatric disorder.