An expanded analysis framework for multivariate GWAS connects inflammatory biomarkers to functional variants and disease

Abstract

Multivariate methods are known to increase the statistical power of association detection, but they have lacked essential follow-up analysis tools necessary for understanding the biology underlying these associations. We developed a novel computational workflow for multivariate GWAS followup analyses, including fine-mapping and identification of the subset of traits driving associations (driver traits). Many follow-up tools require univariate regression coefficients which are lacking from multivariate results. Our method overcomes this problem by using Canonical Correlation Analysis to turn each multivariate association into its optimal univariate Linear Combination Phenotype (LCP).This enables an LCP-GWAS, which in turn generates the statistics required for follow-up analyses.We implemented our method on 12 highly correlated inflammatory biomarkers in a Finnish population-based study. Altogether, we identified 11 associations, four of which (F5, ABO, C1orf140 and PDGFRB) were not detected by biomarker-specific analyses. Fine-mapping identified 19 signals within the 11 loci and driver trait analysis determined the traits contributing to the associations. A phenome-wide association study on the 19 putative causal variants from the signals in 176,899 individuals from the FinnGen study revealed 53 disease associations (p < 1×10 -4 ). Several reported pQTLs in the 11 loci provided orthogonal evidence for the biologically relevant functions of the putative causal variants. Our novel multivariate analysis workflow provides a powerful addition to standard univariate GWAS analyses by enabling multivariate GWAS follow-up and thus promoting the advancement of powerful multivariate methods in genomics. INTRODUCTIONGenome-wide association studies (GWAS) of biomarkers have been highly successful in identifying novel biological pathways and their impact on health and disease. Biomarkers increase statistical power in GWAS, compared to disease diagnoses, due to their quantitative nature and lack of errors

Multi-Trait Genome-Wide Association Study of Atherosclerosis Detects Novel Pleiotropic Loci

“…To further differentiate whether our signal was novel, we performed an additional conditional analysis on the coding variant rs34631529 in PAD data without any notable changes in the PCSK6 locus signal (Supplementary Figure S36). We further note that previous GWAS have found that variants at this locus are associated with inflammatory markers (Iyengar et al, 2015;Hackinger et al, 2018;Nath et al, 2019;Folkersen et al, 2020;Richardson et al, 2020;Ruotsalainen et al, 2021).…”

Inflammatory and infectious upper respiratory diseases associate with 41 genomic loci and type 2 inflammation

“…The fine-mapped set of CDTA-linked variants near ABO includes rs923383567-C [a.k.a. rs657152-C, linked with COVID-19 severity 86 ] and rs879055593-C, the latter of which was linked with interleukin-4 driven pathogenesis in a recent multitrait analysis 88 . The NFKBIZ locus has two SNPs with near-equal posterior inclusion probability in fine-mapping: rs1456200-A and rs1456202-G (Supplementary Figure 6 ).…”

The Transition Period Updated: A Review of the New Insights into the Adaptation of Dairy Cows to the New Lactation

“…The availability of sensors automatically monitoring these behavioral measures allows the detection of alterations that might reflect illness or disease risk in an animal [81,136,137]. Chewing and rumination times are affected by several factors [138], and their trends around calving reflect the likelihood of dairy cows developing severe inflammatory conditions or diseases in early lactation [139][140][141]. Cows with reduced rumination time before calving are known to maintain this even after calving, and these animals are more likely to develop health disorders during the peripartum phase (i.e., metabolic and digestive disorders and severe cases of mastitis and metritis) compared to cows with a greater rumination time ante-partum [140,142].…”

“…Recently, Abuelo et al [1] extended such a relationship way beyond the TP, demonstrating that cows with the greatest reduction of rumination time at dry-off were more likely to develop ketosis or lameness in early lactation. Moreover, peripartum trends of plasma analytes from cows with a reduced rumination time during the first few days of lactation typically reflect a more marked inflammatory condition compared with those from cows having high rumination time at the onset of lactation [140,141]. This suggests that the occurrence of severe inflammation around parturition is associated with a slower increase of rumination time after calving.…”