Phenome-wide genetic-correlation analysis and genetically informed causal inference of amyotrophic lateral sclerosis

Abstract

Leveraging genome-wide association statistics generated from a large study of amyotrophic lateral sclerosis (ALS; 29,612 cases and 122,656 controls) and UK Biobank (UKB; 4,024 phenotypes, up to 361,194 participants), we conducted a phenome-wide analysis of ALS genetic liability and identified 46 genetically correlated traits, such as fluid intelligence score (rg = − 0.21, p = 1.74 × 10–6), "spending time in pub or social club” (rg = 0.24, p = 2.77 × 10–6), non-work related walking (rg = − 0.25, p = 1.95 × 10–6), college education (rg = − 0.15, p = 7.08 × 10–5), “ever diagnosed with panic attacks (rg = 0.39, p = 4.24 × 10–5), and “self-reported other gastritis including duodenitis” (rg = 0.28, p = 1.4 × 10–3). To assess the putative directionality of these genetic correlations, we conducted a latent causal variable analysis, identifying significant genetic causality proportions (gĉp) linking ALS genetic liability to seven traits. While the genetic component of “self-reported other gastritis including duodenitis" showed a causal effect on ALS (gĉp = 0.50, p = 1.26 × 10–29), the genetic liability to ALS is potentially causal for multiple traits, also including an effect on "ever being diagnosed with panic attacks” (gĉp = 0.79, p = 5.011 × 10–15) and inverse effects on “other leisure/social group activities” (gĉp = 0.66, p = 1 × 10–4) and prospective memory result (gĉp = 0.35, p = 0.005). Our subsequent Mendelian randomization analysis indicated that some of these associations may be due to bidirectional effects. In conclusion, this phenome-wide investigation of ALS polygenic architecture highlights the widespread pleiotropy linking this disorder with several health domains.

Phenome-wide causal associations between osteoarthritis and other complex traits through the latent causal variable analysis

“…In the present study, to explore the relationships with OA, we leveraged the GWAS summary statistics from European ancestry for 1355 phenotypes available in the CTG-VL platform to conduct the latent causal variable (LCV) analysis. This analytical approach was facilitated by the Phenome-wide LCV pipeline ( https://github.com/lukejoconnor/LCV ), an integral component of the CTG-VL platform [ 18 , 19 ]. A comprehensive elucidation of the Phenome-wide LCV pipeline’s methodology was available in the previous publication [ 20 ].…”