Laser capture microdissection of human pancreatic islets reveals novel eQTLs associated with type 2 diabetes

TY - JOUR

T1 - Laser capture microdissection of human pancreatic islets reveals novel eQTLs associated with type 2 diabetes

AU - Khamis, Amna

AU - Canouil, Mickaël

AU - Siddiq, Afshan

AU - Crouch, Hutokshi

AU - Falchi, Mario

AU - Bulow, Manon von

AU - Ehehalt, Florian

AU - Marselli, Lorella

AU - Distler, Marius

AU - Richter, Daniela

AU - Weitz, Jürgen

AU - Bokvist, Krister

AU - Xenarios, Ioannis

AU - Thorens, Bernard

AU - Schulte, Anke M

AU - Ibberson, Mark

AU - Bonnefond, Amelie

AU - Marchetti, Piero

AU - Solimena, Michele

AU - Froguel, Philippe

N1 - Copyright © 2019 The Authors. Published by Elsevier GmbH.. All rights reserved.

PY - 2019/6

Y1 - 2019/6

N2 - OBJECTIVE: Genome wide association studies (GWAS) for type 2 diabetes (T2D) have identified genetic loci that often localise in non-coding regions of the genome, suggesting gene regulation effects. We combined genetic and transcriptomic analysis from human islets obtained from brain-dead organ donors or surgical patients to detect expression quantitative trait loci (eQTLs) and shed light into the regulatory mechanisms of these genes.METHODS: Pancreatic islets were isolated either by laser capture microdissection (LCM) from surgical specimens of 103 metabolically phenotyped pancreatectomized patients (PPP) or by collagenase digestion of pancreas from 100 brain-dead organ donors (OD). Genotyping (> 8.7 million single nucleotide polymorphisms) and expression (> 47,000 transcripts and splice variants) analyses were combined to generate cis-eQTLs.RESULTS: After applying genome-wide false discovery rate significance thresholds, we identified 1,173 and 1,021 eQTLs in samples of OD and PPP, respectively. Among the strongest eQTLs shared between OD and PPP were CHURC1 (OD p-value=1.71 × 10-24; PPP p-value = 3.64 × 10-24) and PSPH (OD p-value = 3.92 × 10-26; PPP p-value = 3.64 × 10-24). We identified eQTLs in linkage-disequilibrium with GWAS loci T2D and associated traits, including TTLL6, MLX and KIF9 loci, which do not implicate the nearest gene. We found in the PPP datasets 11 eQTL genes, which were differentially expressed in T2D and two genes (CYP4V2 and TSEN2) associated with HbA1c but none in the OD samples.CONCLUSIONS: eQTL analysis of LCM islets from PPP led us to identify novel genes which had not been previously linked to islet biology and T2D. The understanding gained from eQTL approaches, especially using surgical samples of living patients, provides a more accurate 3-dimensional representation than those from genetic studies alone.

AB - OBJECTIVE: Genome wide association studies (GWAS) for type 2 diabetes (T2D) have identified genetic loci that often localise in non-coding regions of the genome, suggesting gene regulation effects. We combined genetic and transcriptomic analysis from human islets obtained from brain-dead organ donors or surgical patients to detect expression quantitative trait loci (eQTLs) and shed light into the regulatory mechanisms of these genes.METHODS: Pancreatic islets were isolated either by laser capture microdissection (LCM) from surgical specimens of 103 metabolically phenotyped pancreatectomized patients (PPP) or by collagenase digestion of pancreas from 100 brain-dead organ donors (OD). Genotyping (> 8.7 million single nucleotide polymorphisms) and expression (> 47,000 transcripts and splice variants) analyses were combined to generate cis-eQTLs.RESULTS: After applying genome-wide false discovery rate significance thresholds, we identified 1,173 and 1,021 eQTLs in samples of OD and PPP, respectively. Among the strongest eQTLs shared between OD and PPP were CHURC1 (OD p-value=1.71 × 10-24; PPP p-value = 3.64 × 10-24) and PSPH (OD p-value = 3.92 × 10-26; PPP p-value = 3.64 × 10-24). We identified eQTLs in linkage-disequilibrium with GWAS loci T2D and associated traits, including TTLL6, MLX and KIF9 loci, which do not implicate the nearest gene. We found in the PPP datasets 11 eQTL genes, which were differentially expressed in T2D and two genes (CYP4V2 and TSEN2) associated with HbA1c but none in the OD samples.CONCLUSIONS: eQTL analysis of LCM islets from PPP led us to identify novel genes which had not been previously linked to islet biology and T2D. The understanding gained from eQTL approaches, especially using surgical samples of living patients, provides a more accurate 3-dimensional representation than those from genetic studies alone.

KW - Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/genetics

KW - Cytochrome P450 Family 4/genetics

KW - Diabetes Mellitus, Type 2/genetics

KW - Humans

KW - Islets of Langerhans/metabolism

KW - Kinesin/genetics

KW - Laser Capture Microdissection

KW - Membrane Proteins/genetics

KW - Peptide Synthases/genetics

KW - Polymorphism, Single Nucleotide

KW - Quantitative Trait Loci

U2 - 10.1016/j.molmet.2019.03.004

DO - 10.1016/j.molmet.2019.03.004

M3 - Article

C2 - 30956117

SN - 2212-8778

VL - 24

SP - 98

EP - 107

JO - Molecular Metabolism

JF - Molecular Metabolism

ER -