Causal Inference of Genetic Variants and Genes in Amyotrophic Lateral Sclerosis

Authors

Siyu Pan
Xinxuan Liu
Tianzi Liu
Zhongming Zhao
Yulin Dai
Yin-Ying Wang
Peilin Jia
Fan Liu

Publication Date

1-1-2022

Journal

Frontiers in Genetics

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal progressive multisystem disorder with limited therapeutic options. Although genome-wide association studies (GWASs) have revealed multiple ALS susceptibility loci, the exact identities of causal variants, genes, cell types, tissues, and their functional roles in the development of ALS remain largely unknown. Here, we reported a comprehensive post-GWAS analysis of the recent large ALS GWAS (n = 80,610), including functional mapping and annotation (FUMA), transcriptome-wide association study (TWAS), colocalization (COLOC), and summary data-based Mendelian randomization analyses (SMR) in extensive multi-omics datasets. Gene property analysis highlighted inhibitory neuron 6, oligodendrocytes, and GABAergic neurons (Gad1/Gad2) as functional cell types of ALS and confirmed cerebellum and cerebellar hemisphere as functional tissues of ALS. Functional annotation detected the presence of multiple deleterious variants at three loci (9p21.2, 12q13.3, and 12q14.2) and highlighted a list of SNPs that are potentially functional. TWAS, COLOC, and SMR identified 43 genes at 24 loci, including 23 novel genes and 10 novel loci, showing significant evidence of causality. Integrating multiple lines of evidence, we further proposed that rs2453555 at 9p21.2 and rs229243 at 14q12 functionally contribute to the development of ALS by regulating the expression of C9orf72 in pituitary and SCFD1 in skeletal muscle, respectively. Together, these results advance our understanding of the biological etiology of ALS, feed into new therapies, and provide a guide for subsequent functional experiments.

Keywords

amyotrophic lateral sclerosis, causal variants, causal genes, cell type, transcriptome-wide association analysis, colocalization analysis, summary data-based Mendelian randomization analysis

DOI

10.3389/fgene.2022.917142

PMID

35812739

PMCID

PMC9257137

PubMedCentral® Posted Date

6-22-2022

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes