Glucose-Induced Changes in Gene Expression in Human Pancreatic Islets: Causes Or Consequences of Chronic Hyperglycemia

Diabetes Volume 66, December 2017 3013

Glucose-Induced Changes in Gene Expression in Human Pancreatic Islets: Causes or Consequences of Chronic Hyperglycemia

Emilia Ottosson-Laakso,1 Ulrika Krus,1 Petter Storm,1 Rashmi B. Prasad,1 Nikolay Oskolkov,1 Emma Ahlqvist,1 João Fadista,2 Ola Hansson,1 Leif Groop,1,3 and Petter Vikman1

Diabetes 2017;66:3013–3028 | https://doi.org/10.2337/db17-0311

Dysregulation of gene expression in islets from patients In patients with type 2 diabetes (T2D), islet function de- with type 2 diabetes (T2D) might be causally involved clines progressively. Although the initial pathogenic trigger in the development of hyperglycemia, or it could develop of impaired b-cell function is still unknown, elevated glu- as a consequence of hyperglycemia (i.e., glucotoxicity). cose levels are known to further aggravate b-cell function, a To separate the genes that could be causally involved condition referred to as glucotoxicity, which can stimulate in pathogenesis from those likely to be secondary to hy- apoptosis and lead to reduced b-cell mass (1–5). Prolonged perglycemia, we exposed islets from human donors to exposure to hyperglycemia also can induce endoplasmic re- STUDIES ISLET normal or high glucose concentrations for 24 h and ana- ticulum (ER) stress and production of reactive oxygen spe- ﬁ lyzed gene expression. We compared these ndings with cies (6), which can further impair islet function and thereby gene expression in islets from donors with normal glucose the ability of islets to secrete the insulin needed to meet the tolerance and hyperglycemia (including T2D). The genes increased demands imposed by insulin resistance and obe- whose expression changed in the same direction after sity (7). Although these changes are likely to contribute to short-term glucose exposure, as in T2D, were considered most likely to be a consequence of hyperglycemia. Genes deterioration of islet function in patients with manifest whose expression changed in hyperglycemia but not disease, they are less likely to explain the development of after short-term glucose exposure, particularly those T2D in individuals with normoglycemia. In previous studies, we analyzed the gene expression that also correlated with insulin secretion, were consid- ﬁ ered the strongest candidates for causal involvement pro le in individuals with chronically elevated glucose as in T2D. For example, ERO1LB, DOCK10, IGSF11,and measured by elevated HbA1c levels (8,9). However, these PRR14L were downregulated in donors with hyperglyce- studies could not demonstrate whether the changes in gene mia and correlated positively with insulin secretion, expression are the cause or the consequence of hyperglyce- suggesting a protective role, whereas TMEM132C was mia.Onewaytoaddressthisquestionistocomparegene upregulated in hyperglycemia and correlated negatively expression in islets chronically exposed to hyperglycemia with insulin secretion, suggesting a potential pathogenic (prediabetes or diabetes) with gene expression changes after role. This study provides a catalog of gene expression short-term exposure to hyperglycemia, with the assump- changes in human pancreatic islets after exposure to tion that gene expression changes seen in islets from pa- glucose. tients with T2D but not after short-term hyperglycemia are the cause rather than the consequence of hyperglycemia (i.e., contributing to the pathogenesis of T2D). Thus, we The function of pancreatic islets is critical for maintaining performed RNA sequencing of human islets incubated at glucose homeostasis, and dynamic changes of gene expres- physiological (5.5 mmol/L) and high (18.9 mmol/L) glucose sion is part of the islets’ response to blood glucose changes. concentrations and compared the glucose-regulated genes

1Lund University Diabetes Centre, Department of Clinical Sciences, Lund Univer- This article contains Supplementary Data online at http://diabetes sity, Malmö, Sweden .diabetesjournals.org/lookup/suppl/doi:10.2337/db17-0311/-/DC1. 2 Department of Epidemiology Research, Statens Serum Institut, Copenhagen, © 2017 by the American Diabetes Association. Readers may use this article as Denmark long as the work is properly cited, the use is educational and not for profit, and the 3 Finnish Institute of Molecular Medicine, University of Helsinki, Helsinki, Finland work is not altered. More information is available at http://www.diabetesjournals Corresponding author: Emilia Ottosson-Laakso, [email protected]. .org/content/license. Received 12 March 2017 and accepted 30 August 2017. 3014 Glucose-Induced Changes in Gene Expression Diabetes Volume 66, December 2017 with the gene expression profile seen in islets from hyper- annotation to guide the alignment, and featureCounts (15) glycemic donors (8). was used to count the number of reads aligned to the genes. Samples with ,10 million counts and genes with ,2counts RESEARCH DESIGN AND METHODS per million (CPM) in $10 samples were excluded from Donors and Islet Culture further analysis. The raw counts were transformed to log2 Human islets of Langerhans were obtained from the CPM, and the mean-variance trend was identified by using Human Tissue Laboratory (Lund University), which is funded mean-variance modeling at the observational level (voom) (16) by the Excellence Of Diabetes Research in Sweden (EXODIAB) to allow for linear modeling after batch correction with network (www.exodiab.se/home) in collaboration with The ComBat (17). Differential expression was analyzed by using Nordic Network for Clinical Islet Transplantation Program the paired data for 31 pairs of normoglycemic donor islets # (www.nordicislets.org). All islet donors had given consent (HbA1c 6% [42 mmol/mol]) and 14 pairs of hyperglycemic for donation of organs for medical research, and the proce- donor islets (HbA1c .6% [42 mmol/mol]) separately by dures were approved by the ethics committee at Lund Univer- fitting a linear model with linear models for microarray sity (Malmö, Sweden; permit number 2011263). The islets and RNA sequencing data (limma) (18). To exclude that were prepared from cadaver donors by using enzymatic diges- the number of genes responding to glucose was not due to tion and density gradient separation. Islet preparation purity differences in group size, we permuted 14 normoglycemic and count were determined as described previously (10). Be- samples 1,000 times and calculated the mean number of tween 3,000 and 5,000 islets each from 45 donors were di- changed genes by using the R function sample (19). vided into two pools that were incubated for 24 h in CMRL Linear modeling also was used to analyze differential gene ex- 1066 medium (ICN Biomedicals) containing 5.5 mmol/L or pression (adjusted for age, sex, and days in culture) in untreated 18.9 mmol/L glucose at 37°C. The study design is described islets from 81 donors with normoglycemia (HbA1c ,6% [42 A in Fig. 1 , and the clinical characteristics of the donors can mmol/mol]), 19 donors with hyperglycemia (HbA1c ,6.5% be found in Supplementary Table 1. RNA from the islets [48 mmol/mol]), and 16 donors with T2D (HbA1c $6.5% was extracted by using the miRNeasy Mini Kit (QIAGEN). [48 mmol/mol]), including the samples in the glucose-treated RNA quantity and integrity was assessed with an ND-1000 data set and overlapping a previous study by us (8). The HbA1c spectrophotometer (NanoDrop) and on a 2100 Bioanalyzer cutoffs for the groups were chosen to reflect the increased – or a 2200 TapeStation instrument (Agilent Technologies). risk seen in individuals with HbA1c 6.0 6.5% and to follow the recommendations by the International Expert Commit- Sample Preparation and Sequencing tee Report on the Role of the A1C Assay in the Diagnosis With RNA sequencing, we performed a truly global analysis of Diabetes (20). without a priori assumptions (11). A total of 1-mg high-quality RNA (RNA integrity number $8)wasusedasinputforthe The Effect of Coding Variants on In Vivo Insulin Secretion TruSeq RNA Library Preparation Kit (Illumina). The resulting To test the effect of gene expression on insulin secretion libraries were quality controlled on a 2200 TapeStation in vivo in humans, we used exome genotype array data to instrument before sequencing on a HiSeq 2000 system (Illu- find potential loss-of-function and gain-of-function variants mina) for an average depth of 32.4 mol/L paired-end reads in filtered genes. Genotypes with a frequency .5% from (2 3 100 base pairs). the human Infinium Exome-24 v1.1 array (Illumina) Insulin Secretion were obtained from the Prevalence, Prediction and Preven- Insulin secretion capacity of the islet preparations was tion-Botnia study (21), and association with corrected insulin evaluated by stimulatory index (SI). Twenty handpicked response (CIR) was performed, adjusted for age, sex, and P , islets were perifused with low glucose (1.67 mmol/L) for BMI, in 3,720 samples; unadjusted 0.05 was considered fi 42 min, high glucose (20 mmol/L) for 48 min, and then low nominally signi cant. The single nucleotide polymorphisms glucose again. Fractions were collected at 6-min intervals, and (SNPs) in coding parts of the gene were considered as po- the secreted insulin was measured by ELISA. SI was defined tential loss-of-function/gain-of-function variants. as the ratio between the areas under the curve calculated for Expression Quantitative Trait Loci Analysis in the Human the low and high glucose concentrations (12). SI was used for Islets all estimates of insulin secretion in the in vitro experiments. Islet expression quantitative trait loci (eQTLs) were used to fi Apoptosis and Cell Viability Assay investigate genetic ndings from the RNA sequencing experiments. More details can be found in the Supplemen- To test the effect of high glucose incubation for 24 h on islet tary Data and Supplementary Table 2. viability and apoptosis, we incubated islets from three donors in normal and high glucose for 24 h as described above. More RESULTS details can be found in the Supplementary Data. Expression Changes in Response to Chronic Analysis of RNA Sequencing Data Hyperglycemia in Human Islets The data were aligned to hg19 with STAR (Spliced Transcripts The aim of the project was to identify genes whose ex- Alignment to Reference) (13) by using the GENCODE (En- pression was altered in islets from donors with hypergly- cyclopedia of Genes and Gene Variants) (14) v20 gene cemia but not changed by exposure to acute hyperglycemia diabetes.diabetesjournals.org Ottosson-Laakso and Associates 3015

Figure 1—General study design. A: Islets from human cadaver donors (81 with normoglycemia [NG] and 35 with hyperglycemia [HG]) were isolated for transcriptome sequencing. Islets from 45 of these donors also were divided into two pools that were incubated in normal or high glucose for 24 h before differential expression analysis. B: The number of genes whose expression differed between islets from donors with NGT (n = 81) and AGT (19 with HG and 16 with T2D) and the number of genes whose expression changed after exposure to high glucose for 24 h in 31 islets from donors with NG and 14 with HG.

or whose expression was altered in the opposite direction, identified as expressed (defined as .2CPMin.10 sam- assuming that such genes are more likely to be a cause than ples), corresponding to 27% of the genes in the GENCODE a consequence of hyperglycemia and thus involved in the v20 gene annotation and 70% of the protein coding genes pathogenesis of impaired insulin secretion leading to T2D. (n = 13,999). Incubation of islets from the 31 donors with Altogether, expression of 717 genes (Fig. 1B and Supplemen- normoglycemia (HbA1c #6%) in high glucose resulted in tary Table 3) differed among donors with normoglycemia up- or downregulation (FDR-corrected P value [q] , 0.05) (HbA1c ,6%), hyperglycemia (HbA1c $6% or ,6.5%), and of 4,658 genes (Supplementary Table 6 and Fig. 1B). Infor- T2D (HbA1c $6.5%) islets at a false discovery rate (FDR) of mation on the top 10 genes whose expression increased or 5%. Of them, 392 were not affected by acute glucose expo- decreased after short-term hyperglycemia is provided in Fig. sure (see below and Supplementary Tables 4 and 5). 2. In islets from donors with hyperglycemia (HbA1c .6%), expression of 107 genes changed in response to exposure Expression Changes in Response to Short-term to glucose (Fig. 1B and Supplementary Table 7), which is Hyperglycemia in Human Islets far less than the 4,658 genes whose expression changed Islets from 45 human cadaver donors (31 normoglycemic and in normoglycemic islets. Part of this finding could be 14 hyperglycemic) were incubated at normal (5.5 mmol/L) explained by differences in the number of donors (n =31 or high glucose (18.9 mmol/L) concentrations for 24 h vs. 14). However, after permuting 14 normoglycemic is- (Fig. 1A). RNA sequencing yielded an average 32.4 million lets 1,000 times by using the sample package in R (19), paired-end reads per sample. A total of 15,958 genes were the median number of differentially expressed genes was 3016 Glucose-Induced Changes in Gene Expression Diabetes Volume 66, December 2017

Figure 2—Genes regulated by acute glucose exposure in human islets. The top 10 genes that are upregulated (A) or downregulated (B)inislets treated with high glucose (18.9 mmol/L) vs. normal glucose (5.5 mmol/L) for 24 h. Data are mean values, with bars showing minimum–maximum values. ***q < 0.001.

501 (interquartile range 499) and significantly higher than expression correlates with insulin secretion, we used that that of donors with hyperglycemia (501 vs. 107; P = 0.04), variant as a proxy for insulin secretion. For the eQTLs demonstrating the unresponsiveness to glucose of islets analysis, we used genome-wide association study (GWAS) from donors with hyperglycemia (Supplementary Fig. 1). genotype data in combination with RNA sequencing data Of these 107 genes, only 18 were affected by acute glucose from 191 donors. We identified one or more eQTLs in in islets from donors with hyperglycemia (Supplementary 16 of the 392 genes that differed between donors with Table 8). normoglycemia and donors with hyperglycemia and was To ensure that the gene expression changes we observed not affected by acute glucose exposure in the same direction, in the islets after glucose incubation is not due to differ- including the SID1 transmembrane family member 1 ences in cell viability and/or cell numbers, we tested the effect (SIDT1) and forkhead box E1 (FOXE1) genes; these variants of high glucose incubation on islet function by measuring also were nominally associated with SI in the islets. The apoptosis and cell viability. Islets from four normoglycemic same eQTLs in the SIDT1 gene were nominally associated islets were incubated for 24 h at a high (18.9 mmol/L) or (P , 0.05) with T2D in the DIAGRAM (Diabetes Genetics normal (5.5 mmol/L) glucose concentration. Neither apo- Replication and Meta-analysis) study (22) (Supplementary ptosis (n =3;P = 0.20) (Supplementary Fig. 2B)northe Table 9). An eQTL SNP in the rhomboid 5 homolog 1 gene number of viable cells (n =3;P = 0.46) (Supplementary Fig. (RHBDF1) was nominally associated with CIR. 2C)wassignificantly affected by high glucose incubation for To increase the likelihood that a gene would be involved 24 h. The glucose-stimulated insulin secretion is affected in the pathogenesis of or protection from T2D, we searched already after 24 h of preincubation in high glucose, with forpotentialloss-orgain-of-functionvariantsinthe92 increased basal insulin secretion (n =4;P = 0.01) (Supple- genes whose expression correlated with SI and explored mentary Fig. 2A). whether such variants would influence in vivo insulin secretion (CIR). Five genes (transmembrane protein Genes Whose Expression Was Unaffected by Acute 132C [TMEM132C], ERO1LB, dedicator of cytokinesis pro- Hyperglycemia but Correlated With Insulin Secretion tein 10 [DOCK10], proline-rich 14-like protein [PRR14L], To identify genes possibly involved in T2D pathogenesis, we and IGSF11)(Fig.3D and Supplementary Table 10) har- screened for genes whose expression was unaffected by bored variants, which were associated with CIR corrected acute hyperglycemia, correlated negatively with insulin forage,sex,andBMI.ExpressionofERO1LB, DOCK10, secretion, and showed increased expression in donors PRR14L,andIGSF11 was positively correlated with insulin with hyperglycemia compared with donors with normogly- secretion and downregulated in donors with hyperglycemia cemia (or vice versa if protective). Expression of 392 genes and, thus, were potentially protective against T2D. For ex- differed between the donor groups (FDR ,0.05) (Supple- ample, the expression of ERO1LB was lower in donors with mentary Tables 4 and 5) and was not affected by acute hyperglycemia (b = 20.37, q = 0.02) and correlated posi- glucose exposure in the same direction. Of them, 92 genes tively with insulin secretion (Pearson r = 0.29; P = 0.002). A correlated with insulin secretion (Table 1 and Fig. 3). coding variant (with a possible effect on expression) in Noncoding genetic variants influencing gene expression this gene was nominally associated with decreased CIR are referred to as eQTLs and can be used to explore the (rs2477599, allele T, b = 20.03; P = 0.03), suggesting that effects of gene expression on a phenotype. If the variant expression of ERO1LB is required for normal insulin secre- was associated with the expression of a gene whose tion. In contrast, expression of TMEM132C was higher in ibtsdaeejunl.r tosnLas n Associates and Ottosson-Laakso diabetes.diabetesjournals.org

Table 1—Genes possibly involved in T2D pathogenesis Acute glucose T2D, HG vs. NGT Insulin secretion Gene ID HGNC symbol AveExpr (log2CPM) log2FC q value AveExpr (log2CPM) Regression coefﬁcient b qvalue rPvalue ENSG00000186832 KRT16 ———20.16 0.83 3.41E-02 20.19 4.68E-02 ENSG00000124212 PTGIS ———20.06 0.73 2.28E-02 20.20 3.02E-02 ENSG00000101213 PTK6 ———0.00 0.55 1.91E-02 20.21 2.99E-02 ENSG00000154764 WNT7A ———1.17 0.48 3.57E-02 20.24 9.56E-03 ENSG00000101134 DOK5 ———1.32 0.45 2.03E-02 20.20 3.17E-02 ENSG00000160183 TMPRSS3 ———2.57 0.44 4.43E-02 20.29 2.24E-03 ENSG00000140285 FGF7 ———3.00 0.43 4.29E-02 20.23 1.69E-02 ENSG00000141497 ZMYND15 ———20.14 0.43 3.15E-02 20.26 4.77E-03 ENSG00000181234 TMEM132C ———2.23 0.40 1.65E-02 20.23 1.41E-02 ENSG00000101276 SLC52A3 ———0.46 0.40 3.63E-02 20.21 2.82E-02 ENSG00000131981 LGALS3 ———5.91 0.37 3.24E-02 20.22 1.99E-02 ENSG00000007384 RHBDF1 ———3.28 0.35 3.87E-02 20.20 3.31E-02 ENSG00000124225 PMEPA1 ———7.82 0.31 3.38E-02 20.23 1.37E-02 ENSG00000051128 HOMER3 ———1.98 0.31 4.21E-02 20.21 2.31E-02 ENSG00000115641 FHL2 ———4.47 0.30 2.75E-02 20.19 4.72E-02 ENSG00000136732 GYPC ———3.33 0.30 4.54E-02 20.19 4.82E-02 ENSG00000135318 NT5E ———4.70 0.29 3.88E-02 20.21 2.89E-02 ENSG00000198053 SIRPA ———5.04 0.29 2.94E-02 20.19 4.73E-02 ENSG00000250742 ————1.32 0.28 3.34E-02 20.22 2.10E-02 ENSG00000168994 PXDC1 ———3.89 0.25 4.97E-02 20.19 4.64E-02 ENSG00000139832 RAB20 ———4.16 0.24 3.59E-02 20.26 6.32E-03 ENSG00000145901 TNIP1 ———7.08 0.23 4.74E-02 20.22 1.86E-02 ENSG00000146278 PNRC1 ———6.49 0.20 2.91E-02 20.23 1.45E-02 ENSG00000198818 SFT2D1 ———4.83 0.20 2.56E-02 20.25 8.36E-03 ENSG00000241852 C8orf58 ———2.25 0.17 4.14E-02 20.19 4.80E-02 ENSG00000177879 AP3S1 ———5.27 0.14 3.84E-02 20.21 2.52E-02 ENSG00000265808 SEC22B 6.96 0.11 4.76E-02 6.85 20.1 0.04 0.35 4.34E-02 ENSG00000172943 PHF8 ———5.76 20.10 2.58E-02 0.26 4.85E-03 ENSG00000162852 CNST ———5.47 20.11 3.12E-02 0.20 3.80E-02 ENSG00000184708 EIF4ENIF1 ———4.81 20.12 1.47E-02 0.19 4.70E-02 ENSG00000197296 FITM2 5.61 0.14 9.11E-03 5.48 20.12 0.03 0.40 2.02E-02 Continued on p. 3018 3017 3018

Table 1—Continued Acute glucose T2D, HG vs. NGT Insulin secretion lcs-nue hne nGn Expression Gene in Changes Glucose-Induced Gene ID HGNC symbol AveExpr (log2CPM) log2FC q value AveExpr (log2CPM) Regression coefﬁcient b qvalue rPvalue ENSG00000171503 ETFDH ———5.62 20.14 1.99E-02 0.19 4.49E-02 ENSG00000183530 PRR14L ———6.39 20.14 2.46E-02 0.24 1.26E-02 ENSG00000064393 HIPK2 ———7.87 20.15 4.58E-02 0.25 8.31E-03 ENSG00000170145 SIK2 ———7.42 20.16 2.17E-02 0.26 6.08E-03 ENSG00000109654 TRIM2 ———6.79 20.16 3.59E-02 0.19 4.12E-02 ENSG00000135469 COQ10A ———3.81 20.16 4.02E-02 0.19 4.77E-02 ENSG00000159082 SYNJ1 ———4.96 20.17 2.90E-02 0.19 4.18E-02 ENSG00000102053 ZC3H12B ———1.90 20.17 3.96E-02 0.19 4.91E-02 ENSG00000117707 PROX1 ———5.70 20.18 3.08E-02 0.19 4.53E-02 ENSG00000139116 KIF21A ———6.67 20.18 2.23E-02 0.26 6.51E-03 ENSG00000272325 NUDT3 ———5.11 20.19 1.50E-02 0.20 3.17E-02 ENSG00000134982 APC ———6.76 20.19 1.63E-02 0.25 8.74E-03 ENSG00000102781 KATNAL1 ———5.16 20.19 4.38E-02 0.19 4.93E-02 ENSG00000198712 MT-CO2 ———11.86 20.19 4.14E-02 0.24 1.18E-02 ENSG00000165572 KBTBD6 ———4.92 20.20 3.66E-02 0.24 1.17E-02 ENSG00000154822 PLCL2 ———5.64 20.20 4.34E-02 0.20 3.29E-02 ENSG00000185920 PTCH1 ———4.55 20.20 1.99E-02 0.28 2.45E-03 ENSG00000132846 ZBED3 ———4.50 20.20 1.50E-02 0.20 3.21E-02 ENSG00000120696 KBTBD7 ———4.58 20.22 3.94E-02 0.24 1.01E-02 ENSG00000198300 PEG3 ———6.16 20.23 4.75E-02 0.21 2.45E-02 ENSG00000166206 GABRB3 ———7.10 20.24 4.40E-02 0.21 2.71E-02 ENSG00000119737 GPR75 ———2.23 20.24 2.29E-02 0.24 1.22E-02 ENSG00000177707 PVRL3 ———6.22 20.24 2.54E-02 0.19 4.17E-02 Diabetes ENSG00000072858 SIDT1 ———2.70 20.25 2.91E-02 0.21 2.96E-02 ENSG00000091972 CD200 ———5.78 20.25 4.93E-02 0.20 3.64E-02 oue6,Dcme 2017 December 66, Volume ENSG00000150526 MIA2 ———0.83 20.25 3.40E-02 0.29 1.62E-03 ENSG00000165548 TMEM63C ———6.09 20.26 2.93E-02 0.26 5.21E-03 ENSG00000198780 FAM169A ———4.28 20.26 4.32E-02 0.19 4.27E-02 ENSG00000144847 IGSF11 3.58 0.43 1.88E-05 3.28 20.26 0.04 0.44 9.56E-03 ENSG00000196440 ARMCX4 ———5.62 20.28 2.54E-02 0.23 1.37E-02 ENSG00000144290 SLC4A10 ———5.59 20.28 4.94E-02 0.26 6.29E-03 Continued on p. 3019 ibtsdaeejunl.r tosnLas n Associates and Ottosson-Laakso diabetes.diabetesjournals.org

Table 1—Continued Acute glucose T2D, HG vs. NGT Insulin secretion Gene ID HGNC symbol AveExpr (log2CPM) log2FC q value AveExpr (log2CPM) Regression coefﬁcient b qvalue rPvalue ENSG00000065320 NTN1 ———3.78 20.29 3.26E-02 0.25 6.87E-03 ENSG00000147488 ST18 ———6.05 20.30 1.99E-02 0.23 1.47E-02 ENSG00000171004 HS6ST2 ———3.35 20.31 1.65E-02 0.20 3.17E-02 ENSG00000185065 ————0.42 20.31 1.87E-02 0.19 4.13E-02 ENSG00000224093 ————2.31 20.32 1.50E-02 0.26 5.36E-03 ENSG00000151789 ZNF385D ———2.61 20.32 3.57E-02 0.19 4.43E-02 ENSG00000132938 MTUS2 ———4.80 20.32 1.86E-02 0.25 7.65E-03 ENSG00000135905 DOCK10 ———4.69 20.33 1.20E-02 0.21 2.80E-02 ENSG00000117069 ST6GALNAC5 ———3.41 20.33 3.48E-02 0.19 4.22E-02 ENSG00000250056 LINC01018 ———2.73 20.34 3.61E-02 0.20 3.52E-02 ENSG00000168032 ENTPD3 ———5.84 20.35 2.90E-02 0.22 2.28E-02 ENSG00000050438 SLC4A8 ———5.72 20.35 1.56E-02 0.23 1.65E-02 ENSG00000077279 DCX ———2.29 20.35 2.18E-02 0.23 1.32E-02 ENSG00000126733 DACH2 ———2.89 20.35 1.53E-02 0.20 3.30E-02 ENSG00000168824 ————3.43 20.36 2.58E-02 0.25 6.88E-03 ENSG00000123612 ACVR1C ———4.58 20.36 3.15E-02 0.21 2.89E-02 ENSG00000086619 ERO1LB ———9.16 20.37 1.81E-02 0.29 1.72E-03 ENSG00000182836 PLCXD3 ———7.70 20.37 8.88E-03 0.24 1.00E-02 ENSG00000186197 EDARADD ———4.28 20.37 9.52E-03 0.27 3.57E-03 ENSG00000257951 ————1.02 20.37 1.58E-02 0.19 4.16E-02 ENSG00000145569 FAM105A ———6.22 20.38 1.60E-02 0.21 2.32E-02 ENSG00000050030 KIAA2022 ———4.57 20.41 3.66E-03 0.22 2.04E-02 ENSG00000138622 HCN4 ———2.97 20.42 1.85E-03 0.24 9.27E-03 ENSG00000175175 PPM1E ———5.29 20.44 5.29E-03 0.19 4.29E-02 ENSG00000112164 GLP1R ———5.32 20.48 7.98E-03 0.23 1.30E-02 ENSG00000204091 TDRG1 ———20.49 20.49 1.49E-02 0.19 4.14E-02 ENSG00000247381 PDX1-AS1 ———2.11 20.62 2.20E-02 0.19 4.72E-02 ENSG00000116329 OPRD1 ———20.01 20.65 4.71E-03 0.30 1.13E-03 ENSG00000178919 FOXE1 ———20.20 20.68 5.29E-03 0.31 9.15E-04 ENSG00000151834 GABRA2 ———0.16 21.22 2.72E-05 0.28 3.19E-03 Expression of 92 genes that differed between islets from cadaver donors with NGT, HG, and T2D but did not change after exposure to short-term HG in human islets. The genes also show a correlation with insulin secretion (SI) in human islets. AveExpr, average expression; HG, hyperglycemia; HGNC, Human Genome Organisation Gene Nomenclature Committee. 3019 3020 Glucose-Induced Changes in Gene Expression Diabetes Volume 66, December 2017

Figure 3—Genes possibly involved in T2D pathogenesis. Ninety-two genes were uniquely differentially expressed in untreated islets from 81 donors with NGT (HbA1c <6%), 18 donors with hyperglycemia (HG) (HbA1c <6.5%), and 16 donors with T2D (HbA1c $6.5%) and correlated with insulin secretion (SI). A: Twenty-six potentially pathogenic genes were upregulated in AGT islets and negatively correlated with insulin secretion. B: Sixty-six genes were downregulated in islets from donors with HG and positively correlated with insulin secretion. The graphs show the correlation of the average expression of the respective genes in 115 islets vs. HbA1c and insulin secretion. C:Expressionofthefive genes that also had potential loss-of-function variants associated with in vivo insulin secretion in NGT, HG, and T2D. D: Correlation of the gene expression with in vitro insulin secretion (SI). Four genes (ERO1LB, DOCK10, PRR14L,andIGSF11) were downregulated in T2D, and TMEM132C was upregulated. Data are mean with minimum–maximum values. diabetes.diabetesjournals.org Ottosson-Laakso and Associates 3021 donors with hyperglycemia (b = 0.40, q = 0.02) and cor- by chance (22% correlate with SI vs. 9% of genes in related negatively with insulin secretion (Pearson r = 20.23; general; Fisher exact test P , 0.0001) (Fig. 4 and Table 3). P = 0.01). A coding variant in TMEM132C was associated The genes A-kinase anchoring protein 6 (AKAP6), GALNT2, with impaired CIR (rs11059681, allele G, b = 20.03; P = and FERMT1 also harbored coding variants associated with 0.03), making it a potential candidate to contribute to the CIR (Supplementary Table 13). Finally, expression of the pathogenesis of T2D. SIPA1L2, HRK, TMED132D, MBP,andCPEB1 genes was also affected by acute glucose exposure in islets from donors Are Genes in Established T2D Loci Affected by Acute with hyperglycemia; gene expression of TMEM132D and Hyperglycemia? MBP correlated with SI (Supplementary Table 14). Of note, To obtain some insight into the potential role of genes/loci MBP had an eQTL SNP (rs1667903, effect allele C, previously reported to be associated with T2D or glycemic b = 20.50, q , 0.05) that was associated with both SI and traits, we analyzed whether expression of 134 genes CIR (b = 21.52 [P , 0.05] and b =0.14[P , 0.05]). associated with T2D or glycemic traits was influenced by SI CIR hyperglycemia and whether they harbored variants influ- DISCUSSION encing expression (eQTLs) (22–29). Expression of 21 genes Differences in gene expression between human pancreatic harboring such variants (Supplementary Table 11) changed islets from donors with hyperglycemia and normoglycemia in response to short-term hyperglycemia, whereas expres- may be a physiological consequence or the cause of elevated sion of 7 genes differed between individuals with normal glucose.Theseeffectshavebeendifficult to separate in cross- glucose tolerance (NGT) and abnormal glucose tolerance sectional studies, which have not explored changes in gene (AGT) (i.e., hyperglycemia [SLC2A2 (b = 20.66, q , 0.01), expression in response to short-term (acute) hyperglycemia. We RASGRP1 (b = 20.38, q , 0.01), PDX1 (b = 20.33, q , providesuchamapinisletsfrombothdonorswithnormogly- 0.05), PCSK1 (b = 20.32, q , 0.05), ZBED3 (b = 20.20, cemia and donors with hyperglycemia exposed to high glucose q , 0.05), PROX1 (b = 20.18, q , 0.05), FTO (b = 20.12, for 24 h. Not surprisingly, because glucose is a transcriptional q , 0.05)]). Expression of PROX1 and ZBED3 also correlated modulator (31), ;30% of the genes expressed in the human positively with SI (r =0.19[P , 0.05] and 0.20 [P , 0.05], BCAR1 islets are acutely regulated by glucose (Supplementary Table respectively). The T2D-associated SNP rs7202877 6). Only 20% of genes changed in response to short-term wasalsoaneQTLintheislets.TheSNPwasassociatedwith hyperglycemia in islets from donors with hyperglycemia SI (effect allele G, b = 1.87; P , 0.05) but was not an eQTL (Supplementary Table 7), suggesting that they already are for the BCAR1 but for the pseudogene RP11-331F4.4. An- turned on or off by chronic hyperglycemia. Of note, these other 13 T2D GWAS SNPs influenced expression of nearby islets were subjected to a washout period where they were genes (cis-eQTLs) whereof 3 influenced more than one gene cultured at 5.5 mmol/L glucose for several days after iso- (rs3132524, rs1167800, and rs3829109). Seven of these 13 lation, so the lack of acute effect of glucose might also be eQTLs were not eQTLs for the gene suggested in the GWAS, – the consequence of a metabolic memory. such as rs1046896, which tags fructosamine 3 kinase related To identify genes that might be causally involved in the protein (FN3KRP) (Table 2). The expression of FN3KRP pathogenesis of T2D, we postulated that they would not was negatively correlated with SI (r = 20.19; P , 0.05). only show differences in expression between islets from None of these eQTL genes were differentially expressed donors with hyperglycemia or normoglycemia but also show in islets from donors with hyperglycemia compared with that expression would not change in the same direction islets from donors with normoglycemia, although expression after short-term hyperglycemia. Furthermore, we expected of STARD10 was upregulated by acute glucose exposure that these changes in gene expression would correlate with (log2 fold change [log2FC] = 0.20, q , 0.05). The SNP insulin secretion. One of these genes was ERO1LB that rs10830963, which is one of the strongest eQTLs for the encodes an oxidoreductase involved in the folding of pro- melatonin receptor 1B gene (MTNR1B) in human islets (30) insulinintheER.KnockdownofERO1LB in the insulin was nominally associated with CIR (G allele, b = 20.11; P , misfolding–prone Akita mouse resulted in islet destruction 0.05). The same was seen for rs11257655 in the calcium/ and development of diabetes (32). In support of this, ex- calmodulin-dependent protein kinase ID (CAMK1D)gene pression of Ero1b was reduced in islets from two dia- (T allele, b = 20.14; P , 0.01). betic mouse models. However, overexpression of Ero1b also Changes in Gene Expression Attributed to Glucotoxicity seemstoinduceERstressinb-cells, leading to impaired We assumed that similar changes in gene expression seen glucose-stimulated insulin release and suggesting a possible after acute and long-term (prediabetes and diabetes) glucose U-shaped effect of ERO1LB expression on ER stress (33). exposure could possibly be attributed to glucotoxicity. A Four other putatively causative genes (TMEM132C, DOCK10, total of 325 genes (46% of the genes changed in donors PRR14L,andIGSF11) harbored potential loss-of-function with hyperglycemia and T2D) had similar gene expression variants associated with in vivo insulin secretion. TMEM132C changes both after 24-h glucose exposure and in islets from is an interesting candidate, but little is known about its role donors with hyperglycemia (Supplementary Table 12). Of in islet function. Expression of DOCK10 and PRR14L were them, the expression of 73 genes correlated with SI (48 pos- both possibly protective in the islets. Dock10 is a potential itively and 25 negatively), which is more than expected guaninenucleotideexchangefactorrequiredfortheactivation 3022 lcs-nue hne nGn Expression Gene in Changes Glucose-Induced

Table 2—Genome-wide–signiﬁcant GWAS T2D/glycemic trait SNPs as eQTLs in human pancreatic islets GWAS loci eQTLs Locus SNP Trait GWAS effect allele eQTL gene q value Allele change Direction Gene annotation ERAP2 rs1019503 2-h glucose A ERAP2 1.75e-34 G.A + protein_coding

FN3K rs1046896 HbA1c T FN3KRP 2.27e-07 C.T 2 protein_coding

MTNR1B rs10830963 T2D, FBG, HbA1c,HOMA-B,CIR G MTNR1B 4.73e-11 C.G + protein_coding CDC123/ CAMK1D rs11257655 T2D T CAMK1D 8.97e-09 C.T + protein_coding ARAP1 rs11603334 T2D, FBG, FPG G STARD10 1.58e-06 G.A + protein_coding HIP1 rs1167800 FI A STAG3L1, PMS2P3 0.001, 0.05 G.A 2, 2 transcribed_unprocessed_ pseudogene ADCY5 rs11708067 T2D, FBG, 2-h glucose A RP11-797D24.4 2.02e-05 A.G+antisense UBE2E2 rs1496653 T2D A UBE2E2 0.05 A.G 2 protein_coding POU5F1/ TCF19 rs3132524 T2D G CDSN, HCG27 1.05e-05, 0.02 T.C 2, + protein_coding GPSM1/ DNLZ rs3829109 T2D, FBG G DNLZ, GPSM1, CARD9 0.0005, 0.03, 0.003 G.A 2, 2, 2 protein_coding FOXA2 rs6113722 FBG G LINC00261 0.009 G.A 2 lincRNA BCAR1 rs7202877 T2D T RP11-331F4.4 0.01 T.G 2 transcribed_unprocessed_ pseudogene SNX7 rs9727115 FPG G SNX7 0.003 G.A 2 protein_coding Diabetes Thirteen of the 131 established T2D/glycemic trait loci (Supplementary Table 11) are eQTLs in the human islets. The eight genes marked in bold text are not the closest genes to the SNP. FBG, fasting blood glucose; FI, fasting serum insulin; FPG, fasting plasma glucose; HOMA-B, HOMA b-cell function; lincRNA, long intergenic noncoding RNA. oue6,Dcme 2017 December 66, Volume diabetes.diabetesjournals.org Ottosson-Laakso and Associates 3023

Figure 4—Potentially glucotoxic-sensitive genes. In total, 73 genes were differentially expressed in the AGT islets (hyperglycemia [HG]: HbA1c $6% or <6.5%; T2D: HbA1c $6.5%) compared with NGT (HbA1c <6%) and were changed by acute high glucose exposure (18.9 mmol/L for 24 h) as well as correlated with in vitro insulin secretion (SI). A: The correlation of the average expression in 31 islets of the 25 upregulated genes. B: The correlation of the 48 downregulated genes vs. insulin secretion. C:Expressionoftheﬁve genes (SIPA1L2, HRK, TMEM132D, MBP,andCPEB1) that also were changed by acute high glucose exposure in islets from donors with HG (n = 14) that might represent genes that are the most sensitive to the toxic effects of glucose. D: Correlation of the gene expression with in vitro insulin secretion (SI) of the ﬁve genes. Data are mean with minimum–maximum values. 3024

Table 3—Glucose-sensitive genes AGT vs. NGT Acute glucose Insulin secretion lcs-nue hne nGn Expression Gene in Changes Glucose-Induced Gene ID Gene symbol AveExpr (log2CPM) Regression coefﬁcient b q value log2FC q value Pearson rPvalue ENSG00000145888 GLRA1 2.84 20.69 5.29E-03 20.83 1.15E-06 0.34 2.08E-04 ENSG00000167037 SGSM1 4.86 20.27 1.86E-02 20.29 2.63E-03 0.29 1.62E-03 ENSG00000226852 — 1.40 21.02 4.48E-10 20.62 1.18E-03 0.29 1.72E-03 ENSG00000034510 TMSB10 8.16 0.32 8.63E-03 0.36 8.06E-03 20.29 2.20E-03 ENSG00000157388 CACNA1D 6.24 20.25 3.84E-02 20.23 1.51E-02 0.28 3.34E-03 ENSG00000173926 MARCH3 3.02 0.22 3.40E-02 0.22 1.68E-02 20.27 3.34E-03 ENSG00000128872 TMOD2 6.12 20.21 3.51E-02 20.33 7.44E-05 0.27 4.53E-03 ENSG00000197747 S100A10 6.53 0.47 9.98E-03 0.48 3.73E-03 20.26 4.82E-03 ENSG00000087095 NLK 5.14 20.14 6.84E-03 20.13 5.26E-03 0.26 5.63E-03 ENSG00000104381 GDAP1 5.25 20.21 3.13E-02 20.22 3.41E-02 0.26 5.91E-03 ENSG00000134121 CHL1 3.72 20.68 6.32E-04 20.37 5.16E-03 0.26 5.91E-03 ENSG00000010278 CD9 6.95 0.17 4.40E-02 0.19 1.13E-03 20.25 7.72E-03 ENSG00000163191 S100A11 7.32 0.30 3.80E-02 0.36 1.30E-03 20.25 7.92E-03 ENSG00000170500 LONRF2 6.59 20.23 2.10E-02 20.30 6.64E-03 0.25 8.01E-03 ENSG00000183255 PTTG1IP 8.17 0.18 1.36E-02 0.23 1.22E-02 20.25 8.26E-03 ENSG00000088538 DOCK3 4.05 20.29 2.18E-02 20.40 1.75E-03 0.25 8.66E-03 ENSG00000115112 TFCP2L1 4.44 20.28 1.50E-02 20.29 1.35E-03 0.25 8.71E-03 ENSG00000100558 PLEK2 2.64 0.37 3.66E-02 0.41 4.37E-03 20.25 9.10E-03 ENSG00000101311 FERMT1 2.97 0.40 4.94E-02 0.35 3.03E-02 20.24 9.43E-03 ENSG00000151952 TMEM132D 4.92 20.30 1.98E-02 20.65 4.99E-06 0.24 9.70E-03 ENSG00000011422 PLAUR 4.90 0.42 1.09E-02 0.23 3.05E-02 20.24 1.06E-02 ENSG00000132640 BTBD3 7.05 20.28 9.58E-04 20.31 5.14E-04 0.24 1.10E-02

ENSG00000231290 APCDD1L-AS1 3.90 20.50 2.73E-03 20.36 2.20E-03 0.24 1.12E-02 Diabetes ENSG00000091157 WDR7 5.82 20.15 4.33E-02 20.13 1.88E-02 0.24 1.12E-02 ENSG00000145087 STXBP5L 4.31 20.35 1.50E-02 20.37 2.63E-02 0.24 1.18E-02 oue6,Dcme 2017 December 66, Volume ENSG00000134138 MEIS2 6.78 20.22 1.86E-02 20.33 4.70E-05 0.24 1.19E-02 ENSG00000228794 LINC01128 5.37 20.19 4.02E-02 20.22 8.49E-03 0.23 1.35E-02 ENSG00000151320 AKAP6 3.68 20.22 4.05E-02 20.47 5.76E-04 0.23 1.44E-02 ENSG00000198768 APCDD1L 3.77 20.43 1.53E-02 20.28 4.52E-02 0.23 1.57E-02 ENSG00000196878 LAMB3 6.41 0.47 2.54E-02 0.38 1.49E-02 20.23 1.59E-02 ENSG00000258057 BCDIN3D-AS1 0.70 20.31 5.29E-03 20.26 2.65E-02 0.23 1.63E-02 Continued on p. 3025 ibtsdaeejunl.r tosnLas n Associates and Ottosson-Laakso diabetes.diabetesjournals.org

Table 3—Continued AGT vs. NGT Acute glucose Insulin secretion Gene ID Gene symbol AveExpr (log2CPM) Regression coefﬁcient b q value log2FC q value Pearson rPvalue ENSG00000240694 PNMA2 7.33 20.26 4.05E-02 20.40 3.76E-03 0.22 1.75E-02 ENSG00000125814 NAPB 5.55 20.24 1.50E-02 20.31 7.00E-03 0.22 1.79E-02 ENSG00000137673 MMP7 8.01 0.46 2.71E-02 0.30 1.91E-02 20.22 1.79E-02 ENSG00000178177 LCORL 4.90 20.25 1.08E-02 20.15 4.41E-02 0.22 1.81E-02 ENSG00000162374 ELAVL4 5.26 20.29 2.31E-02 20.44 2.26E-03 0.22 1.88E-02 ENSG00000126773 PCNXL4 6.02 20.12 3.41E-02 20.18 5.99E-04 0.22 2.17E-02 ENSG00000128881 TTBK2 5.18 20.18 2.75E-02 20.30 4.31E-04 0.22 2.18E-02 ENSG00000057704 TMCC3 5.29 20.29 1.08E-02 20.21 4.87E-02 0.22 2.25E-02 ENSG00000131037 EPS8L1 1.98 0.51 2.34E-02 0.39 3.27E-02 20.21 2.35E-02 ENSG00000186188 FFAR4 3.59 20.52 1.85E-03 20.41 5.10E-03 0.21 2.35E-02 ENSG00000124570 SERPINB6 6.73 0.13 3.57E-02 0.23 2.41E-05 20.21 2.36E-02 ENSG00000198908 BHLHB9 4.20 20.21 1.67E-02 20.29 3.85E-03 0.21 2.48E-02 ENSG00000074416 MGLL 4.62 0.40 2.91E-02 0.27 2.70E-02 20.21 2.60E-02 ENSG00000197971 MBP 6.88 20.17 2.68E-02 20.62 1.69E-06 0.21 2.68E-02 ENSG00000116141 MARK1 4.93 20.27 1.07E-02 20.38 8.30E-04 0.21 2.78E-02 ENSG00000143641 GALNT2 6.82 0.27 3.59E-02 0.28 1.22E-02 20.21 2.80E-02 ENSG00000116128 BCL9 5.95 20.17 2.42E-02 20.28 1.57E-03 0.21 2.80E-02 ENSG00000156650 KAT6B 5.89 20.15 3.84E-02 20.28 4.53E-05 0.21 2.88E-02 ENSG00000006432 MAP3K9 5.64 20.17 1.68E-02 20.17 2.29E-03 0.21 2.90E-02 ENSG00000174306 ZHX3 5.98 20.16 3.26E-02 20.27 1.13E-03 0.21 2.94E-02 ENSG00000175505 CLCF1 2.62 0.40 2.91E-02 0.31 9.02E-03 20.21 2.95E-02 ENSG00000213977 TAX1BP3 1.97 0.36 1.24E-02 0.38 1.74E-02 20.20 3.11E-02 ENSG00000062598 ELMO2 6.01 20.19 6.64E-04 20.12 3.56E-03 0.20 3.19E-02 ENSG00000107864 CPEB3 4.11 20.19 5.29E-03 20.23 1.95E-03 0.20 3.19E-02 ENSG00000253958 CLDN23 2.56 0.31 1.94E-02 0.28 3.06E-02 20.20 3.25E-02 ENSG00000132470 ITGB4 4.27 0.56 2.31E-02 0.70 2.29E-03 20.20 3.27E-02 ENSG00000127328 RAB3IP 6.32 20.15 1.09E-02 20.16 3.31E-03 0.20 3.36E-02 ENSG00000143469 SYT14 5.29 20.35 1.10E-02 20.63 8.25E-05 0.20 3.39E-02 ENSG00000146232 NFKBIE 3.59 0.28 3.77E-02 0.38 4.51E-03 20.20 3.43E-02 ENSG00000179331 RAB39A 2.53 20.36 1.22E-02 20.36 8.45E-03 0.20 3.47E-02 ENSG00000197991 PCDH20 2.71 20.35 2.10E-02 20.44 9.32E-04 0.20 3.58E-02 3025 Continued on p. 3026 3026 Glucose-Induced Changes in Gene Expression Diabetes Volume 66, December 2017

of the rho family of GTPases, and Dock10 interacts with Cdc42 to promote the formation of the guanosine triphosphate– bound activated form (34). Cdc42 activated by glucose (35) has previously been associated with insulin secretion in ro- value dent and human islets (36). Small interfering RNA–mediated silencing of Cdc42 in isolated islets results in impaired second phase insulin secretion (37). DOCK10 deﬁciency could,

rP therefore, potentially impair insulin secretion through its effect on GTPases, such as Cdc42. 0.20 3.68E-02 0.200.19 3.90E-02 4.12E-02 0.19 4.43E-02 0.19 4.86E-02 2 2 2 2 2 In addition, two genes, SIDT1 and RHBDF1,thatshowed different expression in islets from donors with hyperglycemia and normoglycemia harbored eQTLs that were associated with insulin secretion. The A allele of eQTL SNP retion (SI). AveExpr, average expression. rs11929640 was associated with increased expression of SIDT1 in the islets and with increased in vitro insulin secretion. Expression of SIDT1 was decreased in islets from the donors with hyperglycemia and correlated positively with SI, suggesting a link between decreased expression 0.430.20 4.19E-03 3.51E-02 0.20 0.20 3.87E-02 3.88E-02 0.150.23 3.06E-02 1.65E-02 0.19 0.19 4.94E-02 4.97E-02 0.13 4.13E-02 0.19 4.14E-02 0.31 4.02E-02 0.19and impaired 4.90E-02 insulin secretion. SIDT1 encodes an RNA 2 2 2 2 2 2 transporter that can transfer small RNA molecules, such as micro RNA, inside the cell (38). The RHBDF1 gene showed increased expression in islets from donors with hyperglycemia and correlated negatively with insulin secretion. In

q value log2FC q value Pearson contrast, the T allele of the eQTL SNP rs9930775 was associated with decreased expression and in vivo insulin secretion, suggesting that the ﬁrst ﬁnding was a consequence

b of hyperglycemia, whereas the eQTL could reflect a causal genetic mechanism. These findings will require validation by cient fi genetic engineering, predominantly in human islets. Thirteen of the 134 established T2D/glycemic trait loci 0.270.19 3.08E-02 1.65E-02 0.130.16 2.54E-02 3.62E-02 0.17 2.58E-02 0.27 2.10E-02 2 2 2 2 2 2 had eQTLs in human islets, with most of them showing cis effects (only 7 trans). Expression FN3KRP correlated negatively with insulin secretion in islets. Of note, the T allele of AGT vs. NGT Acute glucose Insulin secretion hyperglycemia (AGT) that correlated negatively with in vitro insulin sec the eQTL SNP rs1046896 in FN3KRP has been previously associated with increased HbA1c levels (23). Because expression of FN3KRP was decreased in T allele carriers, the data suggest that normal expression of FN3KRP is required for maintaining normal insulin secretion. Of note, the GWAS 9 FN3KRP 0.77 0.40 1.50E-02 0.42 1.49E-02 4.37 3.335.21 0.43 0.28 3.12E-02 2.28E-02 0.40 0.48 7.68E-03 3.35E-04 1.87 7.09 4.96 3.78 0.40 2.61E-02 0.47 1.81E-03 5.87 1.36 3.38 0.49SNP is located 1.68E-02 in the 3 0.49untranslated 2.86E-03 region of ,but the gene suggested in the literature to be affected by the SNP is the paralog FN3K. Both genes encode enzymes involved in deglycation of proteins, but they have different substrates. FN3K, but not FN3KRP, can phosphorylate fructosamine, which is glycated by glucose (39). In line with other published results from our group (40),

BIK the rs10830963 T2D risk allele was a strong eQTL for in- HN1 KIF3A TYMP CAPG TRAK1 ACRBP SH2D3A SFMBT1 GNRHR2 SLC30A4 creased expression of MTNR1B and was associated with decreased in vivo insulin secretion. Paradoxically, rare loss-of-function variants in MTNR1B have also been associated with elevated glucose levels (41). Although the common rs10830963 is the strongest eQTL observed in human islets, rare loss-of-function variants would most likely exert their effects in most organs where MTNR1B is expressed Continued and, thereby, possibly increase the risk of diabetes by other — mechanisms than the common variant. The T2D risk locus rs11257655 located between CDC123 Table 3 ENSG00000100290 Gene ID Gene symbol AveExpr (log2CPM) Regression coef ENSG00000104154 ENSG00000125731 ENSG00000111644 ENSG00000182606 Genes whose expression changed in the same direction by acute and long-term ENSG00000042493 ENSG00000189159 ENSG00000131437 ENSG00000163935 ENSG00000025708 ENSG00000211451 and CAMK1D was an eQTL for the CAMK1D gene. The risk diabetes.diabetesjournals.org Ottosson-Laakso and Associates 3027 allele was associated with increased expression of CAMK1D Funding. Support for this research was provided by the European Research and associated with in vivo insulin secretion. This risk allele Council (ERC) under the European Union’s Seventh Framework Programme (FP7/ has been shown to increase transcriptional activity possibly 2007–2013)/ERC grant agreement no. 269045 awarded to L.G. The work was also through FOXA1 and FOXA2 (42). The current results agree supported by project grants from the Vetenskapsrådet (Swedish Research Council) to L.G. (Dnr 2010-3490) and Pfizer. that as with eQTLs observed in other tissues, the locus fl CAMK1D CDC123 Duality of Interest. No potential con icts of interest relevant to this article regulates the expression of ,not .Al- were reported. though the role of CAMK1D in the pathogenesis of T2D Author Contributions. E.O.-L. and U.K. performed experiments. E.O.-L., remains speculative, it may involve regulation of gene tran- U.K., P.S., R.B.P., N.O., E.A., J.F., and P.V. performed analysis of the data. E.O.-L., scription through phosphorylation and activation of CREBP U.K., P.S., R.B.P., N.O., E.A., J.F., O.H., L.G., and P.V. critically revised and (43). CREBP is important for many aspects of b-cell func- contributed to the manuscript. E.O.-L., L.G., and P.V. wrote the draft of the tion, including insulin exocytosis (44). manuscript. O.H., L.G., and P.V. designed the study. P.V. is the guarantor of this work This study also provides information on genes sensitive and, as such, had full access to all the data in the study and takes responsibility for to glucotoxicity, assuming that genes changed similarly by theintegrityofthedataandtheaccuracyofthedataanalysis. both acute and chronic hyperglycemia are susceptible to References glucotoxicity (Fig. 4 and Table 3). Three of these genes har- 1. U.K. Prospective Diabetes Study Group. U.K. Prospective Diabetes Study 16. bored coding variants associated with in vivo insulin secre- Overview of 6 years’ therapy of type II diabetes: A progressive disease. Diabetes AKAP6 GALNT2 FERMT1 AKAP6 tion: , ,and . could possibly 1995;44:1249–1258 influence insulin secretion through modulation of protein 2. Butler AE, Janson J, Bonner-Weir S, Ritzel R, Rizza RA, Butler PC. Beta-cell kinase A because mice with disruption of another A-kinase deficit and increased beta-cell apoptosis in humans with type 2 diabetes. Diabetes anchoring protein (AKAP150) show impaired insulin secre- 2003;52:102–110 tion (45). Expression of AKAP6 was positively correlated 3. Kaiser N, Leibowitz G, Nesher R. Glucotoxicity and beta-cell failure in type 2 with insulin secretion, suggesting that glucose-induced diabetes mellitus. J Pediatr Endocrinol Metab 2003;16:5–22 downregulation of AKAP6 could result in impaired insulin 4. Ferrannini E, Gastaldelli A, Miyazaki Y, Matsuda M, Mari A, DeFronzo RA. b-Cell secretion. In support of this, a coding variant in the gene function in subjects spanning the range from normal glucose tolerance to overt – was negatively associated with insulin secretion in vivo. diabetes: a new analysis. J Clin Endocrinol Metab 2005;90:493 500 Moreover, expression of TMEM132D and MBP was de- 5. Marchetti P, Bugliani M, Boggi U, Masini M, Marselli L. The pancreatic beta cells in human type 2 diabetes. Adv Exp Med Biol 2012;771:288–309 creased after both acute and chronic hyperglycemia and 6. 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Identification of novel genes for glucose Studies of human islets are subject to a number of metabolism based upon expression pattern in human islets and effect on insulin – difficulties. A considerable number of factors will affect the secretion and glycemia. Hum Mol Genet 2015;24:945 955 fi islets’ phenotype connected to the nature of death of the 10. Friberg AS, Brandhorst H, Buchwald P, et al. Quanti cation of the islet product: presentation of a standardized current good manufacturing practices compliant donor, harvest of the organs, preparations of the islets, and system with minimal variability. Transplantation 2011;91:677–683 so forth. In this study, we attempted to address these issues 11. Vikman P, Fadista J, Oskolkov N. RNA sequencing: current and prospective by using paired data where the changes we see by treating uses in metabolic research. J Mol Endocrinol 2014;53:R93–R101 the islets with glucose are observed within the islet prepa- 12. 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