Gene-level analysis of rare variants in 363,977 whole exome sequences identifies an association of GIGYF1 loss of function with type 2 diabetes

Abstract

Sequencing of large cohorts offers an unprecedented opportunity to identify rare genetic variants and to find novel contributors to human disease. We used gene-based collapsing tests to identify genes associated with glucose, HbA1c and T2D diagnosis in 363,977 exome-sequenced participants in the UK Biobank. We identified known associations with diabetes including variants in GCK, HNF1A and PDX1, genes involved in Mendelian forms of diabetes. Novel associations were identified for GIGYF1 predicted loss of function (pLOF), TNRC6B pLOF and PFAS predicted damaging missense variants. Multiple rare variants contributed to these associations, including singleton variants. The most significant novel associations were seen for GIGYF1 pLOF which associated with increased levels of glucose (0.77 mmol/L increase, p = 4.42 × 10−12) and HbA1c (4.33 mmol/mol, p = 1.28 × 10−14) as well as T2D diagnosis (OR = 4.15, p= 6.14 x10−11). GIGYF1 pLOF also associated with decreased cholesterol levels as well as an increased risk of hypothyroidism. An independent common variant association for glucose and T2D was identified at GIGYF1 which replicated in additional datasets. Our results highlight the role of GIGYF1 in regulating insulin signaling and protecting from diabetes.

Assessing the contribution of rare-to-common protein-coding variants to circulating metabolic biomarker levels via 412,394 UK Biobank exome sequences

“…Most (68%, 880/1,303) genebiomarker relationships detected via the collapsing analysis were captured through models that exclusively focused on PTV classes ("ptv" and "ptv5pcnt"), while the remaining 32% were attributable to models that incorporated missense variants. We detected more significant associations using our "ptv" and "ptv5pcnt" models than a prior study 21 that also performed gene-level collapsing analysis using the UKB exome sequence data, albeit with a different analytical framework. For instance, associations between PTVs in 12 genes and HbA1c that we detected were not reported in the other study: this includes the glucose metabolism genes HK1 and G6PC2 (Figure S1).…”

“…The signal between GIGYF1 PTVs and LDL-cholesterol (adjusted for the effect of statins) remained significant upon adjusting for hypothyroidism (beta=-0.55 [-0.71,-0.38]; p=6.2x10 -11 ), suggesting that the GIGYF1 locus likely influences cholesterol levels independent of solely thyroid hormone-mediated pathways. Thus, by leveraging information from over 400,000 UKB exomes, our study provides a more comprehensive picture regarding GIGYF1's biomarker fingerprint and associated clinical traits, expanding on previously reported common 7 and rare variant associations 21,22 at this locus.…”

Systematic single-variant and gene-based association testing of thousands of phenotypes in 426,370 UK Biobank exomes

“…The UK Biobank is a collection of over 500,000 participants with standardized, detailed phenotypic data on which GWAS have been run extensively. Recent studies have leveraged previous releases of the exome sequence data to explore various aspects of rare variant associations in this dataset (7)(8)(9). Here, we present and publicly release results from a systematic, large-scale rare variant association analysis of 3,700 phenotypes in more than 300,000 exome sequenced individuals.…”

Identifying interpretable gene-biomarker associations with functionally informed kernel-based tests in 190,000 exomes

“…We recovered 136 (83%) of the 163 significant associations reported by [14] for the same phenotypes in their gene-based variant collapsing analysis on the UK Biobank 200k WES release (Supplementary [32], or a larger tranche of UK Biobank exome sequencing data yet unreleased to 153 the public [33], have confirmed the association of GIGYF1 with Type II diabetes (T2D). The association with…”