Tissue-Specific Alteration of Metabolic Pathways Influences Glycemic Regulation

Abstract

SummaryMetabolic dysregulation in multiple tissues alters glucose homeostasis and influences risk for type 2 diabetes (T2D). To identify pathways and tissues influencing T2D-relevant glycemic traits (fasting glucose [FG], fasting insulin [FI], two-hour glucose [2hGlu] and glycated hemoglobin [HbA1c]), we investigated associations of exome-array variants in up to 144,060 individuals without diabetes of multiple ancestries. Single-variant analyses identified novel associations at 21 coding variants in 18 novel loci, whilst gene-based tests revealed signals at two genes, TF (HbA1c) and G6PC (FG, FI). Pathway and tissue enrichment analyses of trait-associated transcripts confirmed the importance of liver and kidney for FI and pancreatic islets for FG regulation, implicated adipose tissue in FI and the gut in 2hGlu, and suggested a role for the non-endocrine pancreas in glucose homeostasis. Functional studies demonstrated that a novel FG/FI association at the liver-enriched G6PC transcript was driven by multiple rare loss-of-function variants. The FG/HbA1c-associated, islet-specific G6PC2 transcript also contained multiple rare functional variants, including two alleles within the same codon with divergent effects on glucose levels. Our findings highlight the value of integrating genomic and functional data to maximize biological inference.Highlights23 novel coding variant associations (single-point and gene-based) for glycemic traits51 effector transcripts highlighted different pathway/tissue signatures for each traitThe exocrine pancreas and gut influence fasting and 2h glucose, respectivelyMultiple variants in liver-enriched G6PC and islet-specific G6PC2 influence glycemia

The Trans-Ancestral Genomic Architecture of Glycaemic Traits

“…Of these, four are shared ( P <5×10 -8 ) with South Asian ancestry, two with East Asian ancestry, and two with Hispanic ancestry ( Supplementary Figure 9 ). The complexity of association signals at this locus is consistent with previous work that also reported common variant (MAF>5%) association signals and multiple rare variant (MAF≤1%) associations at this locus that influenced protein function by multiple mechanisms 27 .…”

“…For example, among the 87 variants, 10 are coding variants including several missense such as the HBB Glu7Val mentioned above, GCKR Leu446Pro, RREB1 Asp1771Asn, G6PC2 Pro324Ser, GLP1R Ala316Thr, and TMPRSS6 Val736Ala, each of which have been proposed or shown to affect gene function 12,40–44 . We also additionally identify AMPD3 Val311Leu (PPA=0.989) and TMC6 Trp125Arg (PPA>0.999) variants associated with HbA1c which were previously detected in an exome array analysis but had not been fine-mapped with certainty due to the absence of backbone GWAS data 27 . Our current fine-mapping data now suggest these variants are likely to be causal and identify the cognate genes as the effector transcripts driving these associations.…”

Molecular and functional profiling of human islets: from heterogeneity to human phenotypes

“…Other initiatives focus primarily on the molecular phenotyping of human islets, such as the Integrated Network for Systematic analysis of Pancreatic Islet RNA Expression (InsPIRE) group [35]. These reveal important insights into islet gene regulation (as previously reviewed [7]) and make important contributions to understanding the impact of islet-localised genetic signals on in vivo glycaemic traits [9], but no programme has yet released data on the combined molecular and functional profiling of a large number of human islet preparations. 'Islet Gene View', developed by the Excellence of Diabetes (EXODIAB) research group in Sweden and described in a recent preprint [6], may fill this gap once it is made publicly available, by connecting genetic variation, transcript expression and insulin responses in samples from 188 donors.…”

“…Moving towards in vivo human phenotypes Data from HPAP may eventually be used to link detailed islet phenotypes to in vivo human metabolic function by integration with GWAS and phenome-wide association studies (PheWAS), as has been done with islet transcript-expression data [9]. More direct connections between islet molecular and physiological profiles can, however, be facilitated by the study of tissues taken directly from metabolically phenotyped individuals.…”

“…Phenotyping whole intact islets at scale has proved somewhat easier. Key insights that have been reiterated as a result of newer phenotyping efforts include the substantial variation in insulin secretion amongst islet preparations [8], and important strides have been made in the elucidation of links between metabolic phenotypes and islet genomics [9]. Nonetheless, important challenges remain in understanding the association between the impact of molecular variation on islet function and in vivo glucose homeostasis.…”