Skip Navigation
Skip to contents

Diabetes Metab J : Diabetes & Metabolism Journal



Page Path
HOME > Search
2 "Next generation sequencing"
Article category
Publication year
Funded articles
Brief Report
Identification of Two Cases of Ciliopathy-Associated Diabetes and Their Mutation Analysis Using Whole Exome Sequencing
Min Kyeong Kim, Soo Heon Kwak, Shinae Kang, Hye Seung Jung, Young Min Cho, Seong Yeon Kim, Kyong Soo Park
Diabetes Metab J. 2015;39(5):439-443.   Published online October 22, 2015
  • 4,793 View
  • 49 Download
  • 5 Web of Science
  • 6 Crossref
AbstractAbstract PDFPubReader   

Alström syndrome and Bardet-Biedl syndrome are autosomal recessively inherited ciliopathies with common characteristics of obesity, diabetes, and blindness. Alström syndrome is caused by a mutation in the ALMS1 gene, and Bardet-Biedl syndrome is caused by mutations in BBS1-16 genes. Herein we report genetically confirmed cases of Alström syndrome and Bardet-Biedl syndrome in Korea using whole exome sequencing.


Exome capture was done using SureSelect Human All Exon Kit V4+UTRs (Agilent Technologies). HiSeq2000 system (Illumina) was used for massive parallel sequencing. Sanger sequencing was used for genotype confirmation and familial cosegregation analysis.


A 21-year old Korean woman was clinically diagnosed with Alström syndrome. She had diabetes, blindness, obesity, severe insulin resistance, and hearing loss. Whole exome sequencing revealed a nonsense mutation in exon 10 of ALMS1 (c.8776C>T, p.R2926X) and a seven base-pair deletion resulting in frameshift mutation in exon 8 (c.6410_6416del, p.2137_2139del). A 24-year-old Korean man had Bardet-Biedl syndrome with diabetes, blindness, obesity, and a history of polydactyly. Whole exome sequencing revealed a nonsynonymous mutation in exon 11 of the BBS1 gene (c.1061A>G, p.E354G) and mutation at the normal splicing recognition site of exon 7 of the BBS1 gene (c.519-1G>T).


We found novel compound heterozygous mutations of Alström syndrome and Bardet-Biedl syndrome using whole exome sequencing. The whole exome sequencing successfully identified novel genetic variants of ciliopathy-associated diabetes.


Citations to this article as recorded by  
  • Genotype–phenotype associations in Alström syndrome: a systematic review and meta-analysis
    Brais Bea-Mascato, Diana Valverde
    Journal of Medical Genetics.2024; 61(1): 18.     CrossRef
  • Differentiating monogenic and syndromic obesities from polygenic obesity: Assessment, diagnosis, and management
    Angela K. Fitch, Sonali Malhotra, Rushika Conroy
    Obesity Pillars.2024; 11: 100110.     CrossRef
  • Whole exome sequencing identifies rare biallelic ALMS1 missense and stop gain mutations in familial Alström syndrome patients
    Naglaa M. Kamal, Ahmed N. Sahly, Babajan Banaganapalli, Omran M. Rashidi, Preetha J. Shetty, Jumana Y. Al-Aama, Noor A. Shaik, Ramu Elango, Omar I. Saadah
    Saudi Journal of Biological Sciences.2020; 27(1): 271.     CrossRef
  • Established and emerging strategies to crack the genetic code of obesity
    V. Tam, M. Turcotte, D. Meyre
    Obesity Reviews.2019; 20(2): 212.     CrossRef
  • Identifying Pathogenic Variants of Monogenic Diabetes Using Targeted Panel Sequencing in an East Asian Population
    Seung Shin Park, Se Song Jang, Chang Ho Ahn, Jung Hee Kim, Hye Seung Jung, Young Min Cho, Young Ah Lee, Choong Ho Shin, Jong Hee Chae, Jae Hyun Kim, Sung Hee Choi, Hak C Jang, Jee Cheol Bae, Jong Cheol Won, Sung-Hoon Kim, Jong-Il Kim, Soo Heon Kwak, Kyong
    The Journal of Clinical Endocrinology & Metabolism.2019; 104(9): 4188.     CrossRef
  • Whole exome sequencing as a diagnostic tool for patients with ciliopathy-like phenotypes
    Sheila Castro-Sánchez, María Álvarez-Satta, Mohamed A. Tohamy, Sergi Beltran, Sophia Derdak, Diana Valverde, Anand Swaroop
    PLOS ONE.2017; 12(8): e0183081.     CrossRef
Sulwon Lecture 2009
The Search for Genetic Risk Factors of Type 2 Diabetes Mellitus
Kyong Soo Park
Diabetes Metab J. 2011;35(1):12-22.   Published online February 28, 2011
  • 4,998 View
  • 58 Download
  • 23 Crossref
AbstractAbstract PDFPubReader   

Type 2 diabetes mellitus (T2DM) is caused by complex interplay between multiple genetic and environmental factors. The three major approaches used to identify the genetic susceptibility include candidate gene approach, familial linkage analysis and genome- wide association analysis. Recent advance in genome-wide association studies have greatly improved our understanding of the pathophysiology of T2DM. As of the end of 2010, there are more than 40 confirmed T2DM-associated genetic loci. Most of the T2DM susceptibility genes were implicated in decreased β-cell function. However, these genetic variations have a modest effect and their combination only explains less than 10% of the T2DM heritability. With the advent of the next-generation sequencing technology, we will soon identify rare variants of larger effect as well as causal variants. These advances in understanding the genetics of T2DM will lead to the development of new therapeutic and preventive strategies and individualized medicine.


Citations to this article as recorded by  
  • Diabetes: Risk factor and translational therapeutic implications for Alzheimer's disease
    Jeffrey Cummings, Andrew Ortiz, Janelle Castellino, Jefferson Kinney
    European Journal of Neuroscience.2022; 56(9): 5727.     CrossRef
  • Association of gene polymorphisms with body weight changes in prediabetic patients
    Farida V. Valeeva, Mariya S. Medvedeva, Kamilya B. Khasanova, Elena V. Valeeva, Tatyana A. Kiseleva, Emiliya S. Egorova, Craig Pickering, Ildus I. Ahmetov
    Molecular Biology Reports.2022; 49(6): 4217.     CrossRef
  • Analysis of the association of FTO, PPARG and PPARGC1A gene polymorphisms with carbohydrate metabolism disorders
    Farida V. Valeeva, Kamilya B. Khasanova, Elizaveta A. Sozinova, Tatyana A. Kiseleva, Elena V. Valeeva, Emiliya S. Egorova, Ildus I. Ahmetov
    Kazan medical journal.2022; 103(4): 592.     CrossRef
  • Associations between new and old anthropometric indices with type 2 diabetes mellitus and risk of metabolic complications: a cross-sectional analytical study
    Parichehr Amiri, Ahmad Zare Javid, Leila Moradi, Neda Haghighat, Rahim Moradi, Hossein Bavi Behbahani, Milad Zarrin, Hadi Bazyar
    Jornal Vascular Brasileiro.2021;[Epub]     CrossRef
  • When will individuals meet their personalized probabilities? A philosophical note on risk prediction
    Olaf M. Dekkers, Jesse M. Mulder
    European Journal of Epidemiology.2020; 35(12): 1115.     CrossRef
  • From Pre-Diabetes to Diabetes: Diagnosis, Treatments and Translational Research
    Radia Khan, Zoey Chua, Jia Tan, Yingying Yang, Zehuan Liao, Yan Zhao
    Medicina.2019; 55(9): 546.     CrossRef
  • Systematic analysis of genes and diseases using PheWAS-Associated networks
    Ali Khosravi, Morteza Kouhsar, Bahram Goliaei, B. Jayaram, Ali Masoudi-Nejad
    Computers in Biology and Medicine.2019; 109: 311.     CrossRef
  • Protective effects of asiatic acid in a spontaneous type 2 diabetic mouse model
    Wen Sun, Guangyuan Xu, Xuan Guo, Guangbin Luo, Lili Wu, Yi Hou, Xiangyu Guo, Jingxin Zhou, Tunhai Xu, Lingling Qin, Yixin Fan, Li Han, Motlalepula Matsabisa, Xuesheng Ma, Tonghua Liu
    Molecular Medicine Reports.2017; 16(2): 1333.     CrossRef
  • Are We in the Same Risk of Diabetes Mellitus? Gender- and Age-Specific Epidemiology of Diabetes in 2001 to 2014 in the Korean Population
    Bo Kyung Koo, Min Kyong Moon
    Diabetes & Metabolism Journal.2016; 40(3): 175.     CrossRef
  • Efficient Strategy to Identify Gene-Gene Interactions and Its Application to Type 2 Diabetes
    Donghe Li, Sungho Won
    Genomics & Informatics.2016; 14(4): 160.     CrossRef
  • Genetic polymorphisms associated with overweight and obesity in uncontrolled Type 2 diabetes mellitus
    Nor Bahirah Kasim, Hasniza Zaman Huri, Shireene Ratna Vethakkan, Luqman Ibrahim, Bashar Mudhaffar Abdullah
    Biomarkers in Medicine.2016; 10(4): 403.     CrossRef
  • A multicenter clinical study to determine the efficacy of a novel fenugreek seed (Trigonella foenum-graecum) extract (Fenfuro™) in patients with type 2 diabetes
    Narsingh Verma, Kauser Usman, Naresh Patel, Arvind Jain, Sudhir Dhakre, Anand Swaroop, Manashi Bagchi, Pawan Kumar, Harry G. Preuss, Debasis Bagchi
    Food & Nutrition Research.2016; 60(1): 32382.     CrossRef
  • Association between -308G/A TNFA Polymorphism and Susceptibility to Type 2 Diabetes Mellitus: A Systematic Review
    Geisa Izetti Luna, Izabel Cristina Rodrigues da Silva, Mauro Niskier Sanchez
    Journal of Diabetes Research.2016; 2016: 1.     CrossRef
  • Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes
    Mohamad Hafizi Abu Bakar, Mohamad Roji Sarmidi, Kian-Kai Cheng, Abid Ali Khan, Chua Lee Suan, Hasniza Zaman Huri, Harisun Yaakob
    Molecular BioSystems.2015; 11(7): 1742.     CrossRef
  • Predictive modeling for incident and prevalent diabetes risk evaluation
    Katya L Masconi, Justin Basile Echouffo-Tcheugui, Tandi E Matsha, Rajiv T Erasmus, Andre Pascal Kengne
    Expert Review of Endocrinology & Metabolism.2015; 10(3): 277.     CrossRef
  • Polymorphism of gene UBE2E2 and the risk of developing diabetes type 2
    Elena Vladimirovna Kazakova, Yanhui Wu, Meijun Chen, Tongtong Wang, Lulu Sun, Hong Qiao
    Diabetes mellitus.2015; 18(3): 46.     CrossRef
  • The Architecture of Risk for Type 2 Diabetes: Understanding Asia in the Context of Global Findings
    Noraidatulakma Abdullah, John Attia, Christopher Oldmeadow, Rodney J. Scott, Elizabeth G. Holliday
    International Journal of Endocrinology.2014; 2014: 1.     CrossRef
  • Translational medicine as a new clinical tool and application which improves metabolic diseases: perspectives from 2012 Sino‐American symposium on clinical and translational medicine
    Lin Shi, Elena López Villar, Chengshui Chen
    Clinical and Translational Medicine.2014;[Epub]     CrossRef
  • Frequency of Fat Mass and Obesity-Associated Gene rs9939609 and Peroxisome Proliferator-Activated Receptor Gamma 2 Gene rs1801282 Polymorphisms among Trinidadian Neonates of Different Ethnicities and Their Relationship to Anthropometry at Birth
    Candace E. Cuthbert, D. Dan Ramdath, Jerome E. Foster
    Lifestyle Genomics.2014; 7(1): 39.     CrossRef
  • Genetics of type 2 diabetes and potential clinical implications
    Soo Heon Kwak, Kyong Soo Park
    Archives of Pharmacal Research.2013; 36(2): 167.     CrossRef
  • Genetics in Diabetes Mellitus - Contribution to the Classification and Management
    Jeesuk Yu
    Annals of Pediatric Endocrinology & Metabolism.2012; 17(4): 211.     CrossRef
  • Genome-wide association studies with metabolomics
    Jerzy Adamski
    Genome Medicine.2012; 4(4): 34.     CrossRef
  • Typ-2-Diabetes-assoziierte Gene
    J. Kriebel, H. Grallert, T. Illig
    Der Diabetologe.2012; 8(1): 26.     CrossRef

Diabetes Metab J : Diabetes & Metabolism Journal
Close layer