Literature DB >> 23937595

A genome-wide search for type 2 diabetes susceptibility genes in an extended Arab family.

Habiba S Al Safar1, Heather J Cordell, Osman Jafer, Denise Anderson, Sarra E Jamieson, Michaela Fakiola, Kamal Khazanehdari, Guan K Tay, Jenefer M Blackwell.   

Abstract

Twenty percent of people aged 20 to 79 have type 2 diabetes (T2D) in the United Arab Emirates (UAE). Genome-wide association studies (GWAS) to identify genes for T2D have not been reported for Arab countries. We performed a discovery GWAS in an extended UAE family (N=178; 66 diabetic; 112 healthy) genotyped on the Illumina Human 660 Quad Beadchip, with independent replication of top hits in 116 cases and 199 controls. Power to achieve genome-wide significance (commonly P=5×10(-8)) was therefore limited. Nevertheless, transmission disequilibrium testing in FBAT identified top hits at Chromosome 4p12-p13 (KCTD8: rs4407541, P=9.70×10(-6); GABRB1: rs10517178/rs1372491, P=4.19×10(-6)) and 14q13 (PRKD1: rs10144903, 3.92×10(-6)), supported by analysis using a linear mixed model approximation in GenABEL (4p12-p13 GABRG1/GABRA2: rs7662743, Padj-agesex=2.06×10(-5); KCTD8: rs4407541, Padj-agesex=1.42×10(-4); GABRB1: rs10517178/rs1372491, Padj-agesex=0.027; 14q13 PRKD1: rs10144903, Padj-agesex=6.95×10(-5)). SNPs across GABRG1/GABRA2 did not replicate, whereas more proximal SNPs rs7679715 (Padj-agesex=0.030) and rs2055942 (Padj-agesex=0.022) at COX7B2/GABRA4 did, in addition to a trend distally at KCTD8 (rs4695718: Padj-agesex=0.096). Modelling of discovery and replication data support independent signals at GABRA4 (rs2055942: Padj-agesex-combined=3×10(-4)) and at KCTD8 (rs4695718: Padj-agesex-combined=2×10(-4)). Replication was observed for PRKD1 rs1953722 (proxy for rs10144903; Padj-agesex=0.031; Padj-agesex-combined=2×10(-4)). These genes may provide important functional leads in understanding disease pathogenesis in this population.
© 2013 John Wiley & Sons Ltd/University College London.

Entities:  

Keywords:  Type 2 diabetes; UAE; association analysis; family‐based GWAS

Mesh:

Year:  2013        PMID: 23937595     DOI: 10.1111/ahg.12036

Source DB:  PubMed          Journal:  Ann Hum Genet        ISSN: 0003-4800            Impact factor:   1.670


  18 in total

1.  Genome-wide meta-analysis associates GPSM1 with type 2 diabetes, a plausible gene involved in skeletal muscle function.

Authors:  Qiuju Ding; Amelia Li Min Tan; E J Parra; Miguel Cruz; Xueling Sim; Yik-Ying Teo; Jirong Long; Habiba Alsafar; Enrico Petretto; E-Shyong Tai; Huimei Chen
Journal:  J Hum Genet       Date:  2020-01-21       Impact factor: 3.172

Review 2.  Identifying Common Genetic Risk Factors of Diabetic Neuropathies.

Authors:  Ini-Isabée Witzel; Herbert F Jelinek; Kinda Khalaf; Sungmun Lee; Ahsan H Khandoker; Habiba Alsafar
Journal:  Front Endocrinol (Lausanne)       Date:  2015-05-28       Impact factor: 5.555

3.  Identifying diabetes-related important protein targets with few interacting partners with the PageRank algorithm.

Authors:  Vince I Grolmusz
Journal:  R Soc Open Sci       Date:  2015-04-29       Impact factor: 2.963

4.  Prospecting major genes in dairy buffaloes.

Authors:  G M F de Camargo; R R Aspilcueta-Borquis; M R S Fortes; R Porto-Neto; D F Cardoso; D J A Santos; S A Lehnert; A Reverter; S S Moore; H Tonhati
Journal:  BMC Genomics       Date:  2015-10-28       Impact factor: 3.969

5.  Genetic risk variants for metabolic traits in Arab populations.

Authors:  Prashantha Hebbar; Naser Elkum; Fadi Alkayal; Sumi Elsa John; Thangavel Alphonse Thanaraj; Osama Alsmadi
Journal:  Sci Rep       Date:  2017-01-20       Impact factor: 4.379

6.  Utilization of genetic data can improve the prediction of type 2 diabetes incidence in a Swedish cohort.

Authors:  Hadi Zarkoob; Sarah Lewinsky; Peter Almgren; Olle Melander; Hossein Fakhrai-Rad
Journal:  PLoS One       Date:  2017-07-12       Impact factor: 3.240

7.  Genetic variants in KCNJ11, TCF7L2 and HNF4A are associated with type 2 diabetes, BMI and dyslipidemia in families of Northeastern Mexico: A pilot study.

Authors:  Hugo Leonid Gallardo-Blanco; Jesus Zacarías Villarreal-Perez; Ricardo Martin Cerda-Flores; Andres Figueroa; Celia Nohemi Sanchez-Dominguez; Juana Mercedes Gutierrez-Valverde; Iris Carmen Torres-Muñoz; Fernando Javier Lavalle-Gonzalez; Esther Carlota Gallegos-Cabriales; Laura Elia Martinez-Garza
Journal:  Exp Ther Med       Date:  2016-12-22       Impact factor: 2.447

8.  Harnessing Qatar Biobank to understand type 2 diabetes and obesity in adult Qataris from the First Qatar Biobank Project.

Authors:  Ehsan Ullah; Raghvendra Mall; Reda Rawi; Naima Moustaid-Moussa; Adeel A Butt; Halima Bensmail
Journal:  J Transl Med       Date:  2018-04-12       Impact factor: 5.531

9.  First genome-wide association study in an Australian aboriginal population provides insights into genetic risk factors for body mass index and type 2 diabetes.

Authors:  Denise Anderson; Heather J Cordell; Michaela Fakiola; Richard W Francis; Genevieve Syn; Elizabeth S H Scaman; Elizabeth Davis; Simon J Miles; Toby McLeay; Sarra E Jamieson; Jenefer M Blackwell
Journal:  PLoS One       Date:  2015-03-11       Impact factor: 3.240

10.  Candidate gene analysis supports a role for polymorphisms at TCF7L2 as risk factors for type 2 diabetes in Sudan.

Authors:  Amir T Ibrahim; Ayman Hussain; Mohamed A M Salih; Omima Abdeen Ibrahim; Sarra E Jamieson; Muntaser E Ibrahim; Jenefer M Blackwell; Hiba S Mohamed
Journal:  J Diabetes Metab Disord       Date:  2016-03-01
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.