Diabetes & Metabolism Journal

Original Article

Genetics
Exome Chip Analysis of 14,026 Koreans Reveals Known and Newly Discovered Genetic Loci Associated with Type 2 Diabetes Mellitus: Seong Beom Cho, Jin Hwa Jang, Myung Guen Chung, Sang Cheol Kim; Diabetes Metab J. 2021;45(2):231-240. Published online July 28, 2020; DOI: https://doi.org/10.4093/dmj.2019.0163

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Background

Most loci associated with type 2 diabetes mellitus (T2DM) discovered to date are within noncoding regions of unknown functional significance. By contrast, exonic regions have advantages for biological interpretation.

Methods

We analyzed the association of exome array data from 14,026 Koreans to identify susceptible exonic loci for T2DM. We used genotype information of 50,543 variants using the Illumina exome array platform.

Results

In total, 7 loci were significant with a Bonferroni adjusted P=1.03×10⁻⁶. rs2233580 in paired box gene 4 (PAX4) showed the highest odds ratio of 1.48 (P=1.60×10⁻¹⁰). rs11960799 in membrane associated ring-CH-type finger 3 (MARCH3) and rs75680863 in transcobalamin 2 (TCN2) were newly identified loci. When we built a model to predict the incidence of diabetes with the 7 loci and clinical variables, area under the curve (AUC) of the model improved significantly (AUC=0.72, P<0.05), but marginally in its magnitude, compared with the model using clinical variables (AUC=0.71, P<0.05). When we divided the entire population into three groups—normal body mass index (BMI; <25 kg/m²), overweight (25≤ BMI <30 kg/m²), and obese (BMI ≥30 kg/m²) individuals—the predictive performance of the 7 loci was greatest in the group of obese individuals, where the net reclassification improvement was highly significant (0.51; P=8.00×10⁻⁵).

Conclusion

We found exonic loci having a susceptibility for T2DM. We found that such genetic information is advantageous for predicting T2DM in a subgroup of obese individuals.

Citations

Citations to this article as recorded by

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Nutrients.2023; 15(9): 2144. CrossRef
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Brief Report

Genetics
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; DOI: https://doi.org/10.4093/dmj.2015.39.5.439

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Abstract PDF PubReader

Background

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.

Methods

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.

Results

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).

Conclusion

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

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
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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
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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
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