Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease

Zhao, Wei; Rasheed, Awais; Tikkanen, Emmi; Lee, Jung‐Jin; Butterworth, Adam S.; Howson, Joanna M.M.; Assimes, Themistocles L.; Chowdhury, Rajiv; Orho‐Melander, Marju; Damrauer, Scott M.; Small, Aeron; Asma, Senay; Imamura, Minako; Yamauch, T; Chambers, John C.; Chen, Peng; Sapkota, Bishwa Raj; Shah, Nabi; Jabeen, Sehrish; Surendran, Praveen; Lu, Yingchang; Zhang, Weihua; Imran, Atif; Abbas, Shahid; Majeed, Faisal; Trindade, Kevin; Qamar, Nadeem; Mallick, Nadeem Hayyat; Yaqoob, Zia; Saghir, Tahir; Rizvi, Syed Nadeem Hasan; Memon, Anis; Rasheed, Syed Zahed; Memon, Fazal-ur-Rehman; Mehmood, Khalid; Ahmed, Naveeduddin; Qureshi, Irshad Hussain; Tanveer-us-Salam,; Iqbal, Wasim; Malik, Uzma; Mehra, N. K.; Kuo, Jane Z.; Sheu, Wayne H‐H; Guo, Xiuqing; Hsiung, Chao A.; Juang, Jyh-Ming Jimmy; Taylor, Kent D.; Hung, Yi‐Jen; Lee, Wen‐Jane; Quertermous, Thomas; Lee, I-Te; Hsu, Chih‐Cheng; Böttinger, Erwin P.; Ralhan, Sarju; Teo, Yik Ying; Wang, Tzung‐Dau; Alam, Dewan S.; Angelantonio, Emanuele Di; Epstein, Steve; Nielsen, Sune F.; Nordestgaard, Børge G.; Tybjærg‐Hansen, Anne; Young, Robin; Benn, Marianne; Frikke‐Schmidt, Ruth; Kamstrup, Pia R.; Biobank, Michigan; Jukema, J. Wouter; Sattar, Naveed; Smit, Roelof A.J.; Chung, Ren‐Hua; Liang, Kae‐Woei; Anand, Sonia S.; Sanghera, Dharambir K.; Ripatti, Samuli; Loos, Ruth J.F.; Kooner, Jaspal S.; Tai, E. Shyong; Rotter, Jerome I.; Chen, Yii‐Der Ida; Frossard, Philippe; Maeda, Shiro; Kadowaki, Takashi; Reilly, Muredach P.; Paré, Guillaume; Melander, Olle; Salomaa, Veikko; Rader, Daniel J.; Danesh, John; Voight, Benjamin F.; Saleheen, Danish

doi:10.1038/ng.3943

Cited by 248 publications

(204 citation statements)

References 54 publications

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“…Six of these 80 signals mapped within known T2D loci, five reconfirming earlier observations. At the sixth ( TMEM18 ), fine-mapping highlighted the lead regional SNP as rs62107261 (MAF=4.6%) rather than the previously-reported common lead variant rs2867125 (MAF=17%)2; at this locus, the common and low-frequency variants constitute distinct signals, with the former relegated to secondary status in this analysis following emergence of the stronger association at rs62107261.…”

Section: Resultsmentioning

confidence: 70%

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

et al. 2018

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We aggregated genome-wide genotyping data from 32 European-descent GWAS (74,124 T2D cases, 824,006 controls) imputed to high-density reference panels of >30,000 sequenced haplotypes. Analysis of ˜27M variants (˜21M with minor allele frequency [MAF]<5%), identified 243 genome-wide significant loci (p<5x10-8; MAF 0.02%-50%; odds ratio [OR] 1.04-8.05), 135 not previously-implicated in T2D-predisposition. Conditional analyses revealed 160 additional distinct association signals (p<10-5) within the identified loci. The combined set of 403 T2D-risk signals includes 56 low-frequency (0.5%≤MAF<5%) and 24 rare (MAF<0.5%) index SNPs at 60 loci, including 14 with estimated allelic OR>2. Forty-one of the signals displayed effect-size heterogeneity between BMI-unadjusted and adjusted analyses. Increased sample size and improved imputation led to substantially more precise localisation of causal variants than previously attained: at 51 signals, the lead variant after fine-mapping accounted for >80% posterior probability of association (PPA) and at 18 of these, PPA exceeded 99%. Integration with islet regulatory annotations enriched for T2D association further reduced median credible set size (from 42 variants to 32) and extended the number of index variants with PPA>80% to 73. Although most signals mapped to regulatory sequence, we identified 18 genes as human validated therapeutic targets through coding variants that are causal for disease. Genome wide chip heritability accounted for 18% of T2D-risk, and individuals in the 2.5% extremes of a polygenic risk score generated from the GWAS data differed >9-fold in risk. Our observations highlight how increases in sample size and variant diversity deliver enhanced discovery and single-variant resolution of causal T2D-risk alleles, and the consequent impact on mechanistic insights and clinical translation.

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Section: Resultsmentioning

confidence: 70%

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

et al. 2018

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“…Of relevance to T2D is our finding two known-T2D associated genes associated with cis-eQTLs (MCM6, DARS) and four with trans-eQTLs (DGKB, GTF3AP5-AGMO, IL23R/IL12RB2, SLC44A4). The DGKB/GTF3AP5-AGMO region has the most annotation to GWAS hits with variants in the genes showing genome-wide significant associations with T2D 28,29 , fasting plasma glucose traits [30][31][32] and glycated hemoglobin 33 . IL23R/IL12RB2 is a known GWAS locus for age of onset of T2D 34 while variants in SLC44A4 have been implicated in the interaction between T2D and iron status biomarkers.…”

Section: Discussionmentioning

confidence: 99%

A Novel Type 2 Diabetes Locus in sub-Saharan Africans, ZRANB3, is Implicated in Beta Cell Proliferation

Adeyemo

Chen

Doumatey

et al. 2019

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Genome analysis of diverse human populations has contributed to the identification of novel genomic loci for diseases of major clinical and public health impact. Here, we report the largest genome-wide analysis of type 2 diabetes (T2D) in sub-Saharan Africans, an understudied ancestral group. We analyzed ~18 million autosomal SNPs in 5,231 individuals from Nigeria, Ghana and Kenya. TCF7L2 rs7903156 was the most significant locus (p=7.288 X 10 -13 ). We identified a novel genome wide significant locus: ZRANB3 (Zinc Finger RANBP2-Type Containing 3, lead SNP chr2:136064024, T allele frequency=0.034, p=2.831x10 -9 ). Knockdown of the zebrafish ortholog resulted in reduction in pancreatic beta cell number in the developing organism, suggesting a potential mechanism for its effect on glucose hemostasis. We also showed transferability in our study of 32 established T2D loci. Our findings provide evidence of a novel candidate T2D locus and advance understanding of the genetics of T2D in non-European ancestry populations.

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“…This region includes the HMGA2 gene, which belongs to the High Mobility Group A (HMGA) chromatin architectural factors that are highly expressed during development of the embryo (Sgarra et al 2018). HMGA2 carries GWAS-identified SNPs associated with phenotypes from different stages of life such as birth weight (Horikoshi et al 2016; Horikoshi et al 2013), birth and infant length (van der Valk et al 2015), childhood height (Weedon et al 2007), and type 2 diabetes (Mahajan et al 2014; Morris et al 2012; Ng et al 2014; Voight et al 2010; Zhao et al 2017) and anthropometric traits (Carty et al 2012; He et al 2015; Justice et al 2017; N’Diaye et al 2011; Shungin et al 2015; Soranzo et al 2009; Weedon et al 2007) in adulthood. It is noteworthy that SNPs associated with risk of type 2 diabetes (Ng et al 2014) and adult height (N’Diaye et al 2011) in African Americans were also associated with birth weight in our population.…”

Section: Discussionmentioning

confidence: 99%

Admixture mapping and fine-mapping of birth weight loci in the Black Women’s Health Study

et al. 2018

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Several genome-wide association studies (GWAS) have identified genetic variants associated with birth weight. To date, however, most GWAS of birth weight have focused primarily on European ancestry samples even though prevalence of low birth weight is higher among African-Americans. We conducted admixture mapping using 2918 ancestral informative markers in 2596 participants of the Black Women's Health Study, with the goal of identifying novel genomic regions where local African ancestry is associated with birth weight. In addition, we performed a replication analysis of 11 previously identified index single nucleotide polymorphisms (SNPs), and fine-mapped those genetic loci to identify better or new genetic variants associated with birth weight in African-Americans. We found that high African ancestry at 12q14 was associated with low birth weight, and we identified multiple independent birth weight-lowering variants in this genomic region. We replicated the association of a previous GWAS SNP in ADRB1 and our fine-mapping efforts suggested the presence of new birth weight-associated variants in ADRB1, HMGA2, and SLC2A4. Further studies are needed to determine whether birth weight-associated loci can in part explain race-associated birth weight disparities.

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Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease

Cited by 248 publications

References 54 publications

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

A Novel Type 2 Diabetes Locus in sub-Saharan Africans, ZRANB3, is Implicated in Beta Cell Proliferation

Admixture mapping and fine-mapping of birth weight loci in the Black Women’s Health Study

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