The Genetic Spectrum of Maturity-Onset Diabetes of the Young (MODY) in Qatar, a Population-Based Study
Abstract
:1. Introduction
2. Results
2.1. Study Overview
2.2. Identification of Previously Known MODY Causative Variants
2.3. Identifying Potentially Novel MODY-Causing Mutations
2.4. Estimating the Prevalence of MODY in Qatar
3. Discussion
4. Materials and Methods
4.1. Study Participants
4.2. Phenotypic Data and Patient Classification
4.3. Whole-Genome Sequencing
4.4. Bioinformatics Analysis to Identify MODY-Causing Mutations
4.5. Statistical Analysis
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Skoczek, D.; Dulak, J.; Kachamakova-Trojanowska, N. Maturity Onset Diabetes of the Young-New Approaches for Disease Modelling. Int. J. Mol. Sci. 2021, 22, 7553. [Google Scholar] [CrossRef] [PubMed]
- Hu, M.; Cherkaoui, I.; Misra, S.; Rutter, G.A. Functional Genomics in Pancreatic beta Cells: Recent Advances in Gene Deletion and Genome Editing Technologies for Diabetes Research. Front. Endocrinol. 2020, 11, 576632. [Google Scholar] [CrossRef] [PubMed]
- Shields, B.M.; Hicks, S.; Shepherd, M.H.; Colclough, K.; Hattersley, A.T.; Ellard, S. Maturity-onset diabetes of the young (MODY): How many cases are we missing? Diabetologia 2010, 53, 2504–2508. [Google Scholar] [CrossRef] [PubMed]
- Mohan, V.; Radha, V.; Nguyen, T.T.; Stawiski, E.W.; Pahuja, K.B.; Goldstein, L.D.; Tom, J.; Anjana, R.M.; Kong-Beltran, M.; Bhangale, T.; et al. Comprehensive genomic analysis identifies pathogenic variants in maturity-onset diabetes of the young (MODY) patients in South India. BMC Med. Genet. 2018, 19, 22. [Google Scholar] [CrossRef] [Green Version]
- Patel, K.A.; Kettunen, J.; Laakso, M.; Stančáková, A.; Laver, T.W.; Colclough, K.; Johnson, M.B.; Abramowicz, M.; Groop, L.; Miettinen, P.J.; et al. Heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance. Nat. Commun. 2017, 8, 888. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Peixoto-Barbosa, R.; Reis, A.F.; Giuffrida, F.M.A. Update on clinical screening of maturity-onset diabetes of the young (MODY). Diabetol. Metab. Syndr. 2020, 12, 50. [Google Scholar] [CrossRef] [PubMed]
- Bonnefond, A.; Boissel, M.; Bolze, A.; Durand, E.; Toussaint, B.; Vaillant, E.; Gaget, S.; Graeve, F.D.; Dechaume, A.; Allegaert, F.; et al. Pathogenic variants in actionable MODY genes are associated with type 2 diabetes. Nat. Metab. 2020, 2, 1126–1134. [Google Scholar] [CrossRef]
- Mahajan, A.; Taliun, D.; Thurner, M.; Robertson, N.R.; Torres, J.M.; Rayner, N.W.; Payne, A.J.; Steinthorsdottir, V.; Scott, R.A.; Grarup, N.; et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat. Genet. 2018, 50, 1505–1513. [Google Scholar] [CrossRef] [Green Version]
- Stoy, J.; Edghill, E.L.; Flanagan, S.E.; Ye, H.; Paz, V.P.; Pluzhnikov, A.; Below, J.E.; Hayes, M.G.; Cox, N.J.; Lipkind, G.M.; et al. Insulin gene mutations as a cause of permanent neonatal diabetes. Proc. Natl. Acad. Sci. USA 2007, 104, 15040–15044. [Google Scholar] [CrossRef] [Green Version]
- Vedovato, N.; Cliff, E.; Proks, P.; Poovazhagi, V.; Flanagan, S.E.; Ellard, S.; Hattersley, A.T.; Ashcroft, F.M. Neonatal diabetes caused by a homozygous KCNJ11 mutation demonstrates that tiny changes in ATP sensitivity markedly affect diabetes risk. Diabetologia 2016, 59, 1430–1436. [Google Scholar] [CrossRef]
- Flanagan, S.E.; Dung, V.C.; Houghton, J.A.L.; De Franco, E.; Ngoc, C.T.B.; Damhuis, A.; Ashcroft, F.M.; Harries, L.W.; Ellard, S. An ABCC8 Nonsense Mutation Causing Neonatal Diabetes through Altered Transcript Expression. J. Clin. Res. Pediatr. Endocrinol. 2017, 9, 260–264. [Google Scholar] [CrossRef] [PubMed]
- Mughal, S.A.; Park, R.; Nowak, N.; Gloyn, A.L.; Karpe, F.; Matile, H.; Malecki, M.T.; McCarthy, M.I.; Stoffel, M.; Owen, K.R. Apolipoprotein M can discriminate HNF1A-MODY from Type 1 diabetes. Diabet. Med. 2013, 30, 246–250. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ræder, H.; Haldorsen, I.S.; Ersland, L.; Grüner, R.; Taxt, T.; Søvik, O.; Molven, A.; Njølstad, P.R. Pancreatic Lipomatosis Is a Structural Marker in Nondiabetic Children with Mutations in Carboxyl-Ester Lipase. Diabetes 2007, 56, 444–449. [Google Scholar] [CrossRef] [Green Version]
- Ricci, P.; Magalhães, P.; Krochmal, M.; Pejchinovski, M.; Daina, E.; Caruso, M.R.; Goea, L.; Belczacka, I.; Remuzzi, G.; Umbhauer, M.; et al. Urinary proteome signature of Renal Cysts and Diabetes syndrome in children. Sci. Rep. 2019, 9, 2225. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kim, S.H. Maturity-Onset Diabetes of the Young: What Do Clinicians Need to Know? Diabetes Metab. J. 2015, 39, 468–477. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Relan, S.; Hessel, F.C.; Timmons, K.D.; Sonabend, R.; Redondo, M.J. Maturity-Onset Diabetes of the Young (MODY) in a Racially Diverse Pediatric Population. Diabetes 2018, 67, 1529-P. [Google Scholar] [CrossRef]
- Yorifuji, T.; Fujimaru, R.; Hosokawa, Y.; Tamagawa, N.; Shiozaki, M.; Aizu, K.; Jinno, K.; Maruo, Y.; Nagasaka, H.; Tajima, T.; et al. Comprehensive molecular analysis of Japanese patients with pediatric-onset MODY-type diabetes mellitus. Pediatr. Diabetes 2012, 13, 26–32. [Google Scholar] [CrossRef]
- Yorifuji, T.; Higuchi, S.; Kawakita, R.; Hosokawa, Y.; Aoyama, T.; Murakami, A.; Kawae, Y.; Hatake, K.; Nagasaka, H.; Tamagawa, N. Genetic basis of early-onset, maturity-onset diabetes of the young-like diabetes in Japan and features of patients without mutations in the major MODY genes: Dominance of maternal inheritance. Pediatr. Diabetes 2018, 19, 1164–1172. [Google Scholar] [CrossRef]
- Carmody, D.; Naylor, R.N.; Bell, C.D.; Berry, S.; Montgomery, J.T.; Tadie, E.C.; Hwang, J.L.; Greeley, S.A.W.; Philipson, L.H. GCK-MODY in the US National Monogenic Diabetes Registry: Frequently misdiagnosed and unnecessarily treated. Acta Diabetol. 2016, 53, 703–708. [Google Scholar] [CrossRef] [Green Version]
- Doğan, M.; Eröz, R.; Bolu, S.; Yüce, H.; Gezdirici, A.; Arslanoğlu, İ.; Teralı, K. Study of ten causal genes in Turkish patients with clinically suspected maturity-onset diabetes of the young (MODY) using a targeted next-generation sequencing panel. Mol. Biol. Rep. 2022, 49, 7483–7495. [Google Scholar] [CrossRef]
- Hwang, J.S.; Shin, C.H.; Yang, S.W.; Jung, S.Y.; Huh, N. Genetic and clinical characteristics of Korean maturity-onset diabetes of the young (MODY) patients. Diabetes Res. Clin. Pract. 2006, 74, 75–81. [Google Scholar] [CrossRef] [PubMed]
- Matsha, T.E.; Raghubeer, S.; Tshivhase, A.M.; Davids, S.F.G.; Hon, G.M.; Bjorkhaug, L.; Erasmus, R.T. Incidence of HNF1A and GCK MODY Variants in a South African Population. Appl. Clin. Genet. 2020, 13, 209–219. [Google Scholar] [CrossRef] [PubMed]
- Saraswathi, S.; Al-Khawaga, S.; Elkum, N.; Hussain, K. A Systematic Review of Childhood Diabetes Research in the Middle East Region. Front. Endocrinol. 2019, 10, 805. [Google Scholar] [CrossRef] [PubMed]
- Johnson, S.R.; Ellis, J.J.; Leo, P.J.; Anderson, L.K.; Ganti, U.; Harris, J.E.; Curran, J.A.; McInerney-Leo, A.M.; Paramalingam, N.; Song, X.; et al. Comprehensive genetic screening: The prevalence of maturity-onset diabetes of the young gene variants in a population-based childhood diabetes cohort. Pediatr. Diabetes 2019, 20, 57–64. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Haris, B.; Saraswathi, S.; Al-Khawaga, S.; Hasnah, R.; Saeed, A.; Mundekkadan, S.; Hamed, N.; Afyouni, H.; Abdel-Karim, T.; Mohammed, S.; et al. Epidemiology, genetic landscape and classification of childhood diabetes mellitus in the State of Qatar. J. Diabetes Investig. 2021, 12, 2141–2148. [Google Scholar] [CrossRef]
- Al Thani, A.; Fthenou, E.; Paparrodopoulos, S.; Al Marri, A.; Shi, Z.; Qafoud, F.; Afifi, N. Qatar Biobank Cohort Study: Study Design and First Results. Am. J. Epidemiol. 2019, 188, 1420–1433. [Google Scholar] [CrossRef]
- Weir, C.B.; Jan, A. BMI Classification Percentile and Cut Off Points; StatPearls: Treasure Island, FL, USA, 2022. [Google Scholar]
- Nkonge, K.M.; Nkonge, D.K.; Nkonge, T.N. The epidemiology, molecular pathogenesis, diagnosis, and treatment of maturity-onset diabetes of the young (MODY). Clin. Diabetes Endocrinol. 2020, 6, 20. [Google Scholar] [CrossRef]
- Sun, H.; Saeedi, P.; Karuranga, S.; Pinkepank, M.; Ogurtsova, K.; Duncan, B.B.; Stein, C.; Basit, A.; Chan, J.C.N.; Mbanya, J.C.; et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res. Clin. Pract. 2022, 183, 109119. [Google Scholar] [CrossRef]
- Al-Thani, M.H.; Al-Mutawa, K.A.; Alyafei, S.A.; Ijaz, M.A.; Khalifa, S.A.H.; Kokku, S.B.; Mishra, A.C.M.; Poovelil, B.V.; Soussi, M.B.; Toumi, A.A.; et al. Characterizing epidemiology of prediabetes, diabetes, and hypertension in Qataris: A cross-sectional study. PLoS ONE 2021, 16, e0259152. [Google Scholar] [CrossRef]
- International Diabetes Federation. IDF Diabetes Atlas, 10th ed.; International Diabetes Federation: Brussels, Belgium, 2021. [Google Scholar]
- International Diabetes Federation. IDF Middle East and North Africa Region; International Diabetes Federation: Brussels, Belgium, 2022. [Google Scholar]
- Pihoker, C.; Gilliam, L.K.; Ellard, S.; Dabelea, D.; Davis, C.; Dolan, L.M.; Greenbaum, C.J.; Imperatore, G.; Lawrence, J.M.; Marcovina, S.M.; et al. Prevalence, characteristics and clinical diagnosis of maturity onset diabetes of the young due to mutations in HNF1A, HNF4A, and glucokinase: Results from the SEARCH for Diabetes in Youth. J. Clin. Endocrinol. Metab. 2013, 98, 4055–4062. [Google Scholar] [CrossRef]
- Shields, B.M.; McDonald, T.J.; Ellard, S.; Campbell, M.J.; Hyde, C.; Hattersley, A.T. The development and validation of a clinical prediction model to determine the probability of MODY in patients with young-onset diabetes. Diabetologia 2012, 55, 1265–1272. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yang, Y.S.; Kwak, S.H.; Park, K.S. Update on Monogenic Diabetes in Korea. Diabetes Metab. J. 2020, 44, 627–639. [Google Scholar] [CrossRef] [PubMed]
- Sirugo, G.; Williams, S.M.; Tishkoff, S.A. The Missing Diversity in Human Genetic Studies. Cell 2019, 177, 26–31. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Borowiec, M.; Liew, C.W.; Thompson, R.; Boonyasrisawat, W.; Hu, J.; Mlynarski, W.M.; El Khattabi, I.; Kim, S.H.; Marselli, L.; Rich, S.S.; et al. Mutations at the BLK locus linked to maturity onset diabetes of the young and beta-cell dysfunction. Proc. Natl. Acad. Sci. USA 2009, 106, 14460–14465. [Google Scholar] [CrossRef] [Green Version]
- Bonnefond, A.; Yengo, L.; Philippe, J.; Dechaume, A.; Ezzidi, I.; Vaillant, E.; Gjesing, A.P.; Andersson, E.A.; Czernichow, S.; Hercberg, S.; et al. Reassessment of the putative role of BLK-p.A71T loss-of-function mutation in MODY and type 2 diabetes. Diabetologia 2013, 56, 492–496. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lu, J.; Cheng, C.; Cheng, Z.C.; Wu, Q.; Shen, H.; Yuan, M.X.; Zhang, B.; Yang, J.K. The dual role of RFX6 in directing beta cell development and insulin production. J. Mol. Endocrinol. 2021, 66, 129–140. [Google Scholar] [CrossRef] [PubMed]
- Imaki, S.; Iizuka, K.; Horikawa, Y.; Yasuda, M.; Kubota, S.; Kato, T.; Liu, Y.; Takao, K.; Mizuno, M.; Hirota, T.; et al. A novel RFX6 heterozygous mutation (p.R652X) in maturity-onset diabetes mellitus: A case report. J. Diabetes Investig. 2021, 12, 1914–1918. [Google Scholar] [CrossRef]
- Sinnott-Armstrong, N.; Tanigawa, Y.; Amar, D.; Mars, N.; Benner, C.; Aguirre, M.; Venkataraman, G.R.; Wainberg, M.; Ollila, H.M.; Kiiskinen, T.; et al. Genetics of 35 blood and urine biomarkers in the UK Biobank. Nat. Genet. 2021, 53, 185–194. [Google Scholar] [CrossRef]
- Ray, D.; Chatterjee, N. A powerful method for pleiotropic analysis under composite null hypothesis identifies novel shared loci between Type 2 Diabetes and Prostate Cancer. PLoS Genet. 2020, 16, e1009218. [Google Scholar] [CrossRef]
- Aigha, I.I.; Abdelalim, E.M. NKX6.1 transcription factor: A crucial regulator of pancreatic beta cell development, identity, and proliferation. Stem Cell Res. Ther. 2020, 11, 459. [Google Scholar] [CrossRef]
- Vujkovic, M.; Keaton, J.M.; Lynch, J.A.; Miller, D.R.; Zhou, J.; Tcheandjieu, C.; Huffman, J.E.; Assimes, T.L.; Lorenz, K.; Zhu, X.; et al. Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis. Nat. Genet. 2020, 52, 680–691. [Google Scholar] [CrossRef] [PubMed]
- Tatsi, E.B.; Kanaka-Gantenbein, C.; Scorilas, A.; Chrousos, G.P.; Sertedaki, A. Next generation sequencing targeted gene panel in Greek MODY patients increases diagnostic accuracy. Pediatr. Diabetes 2020, 21, 28–39. [Google Scholar] [CrossRef] [PubMed]
- Mbarek, H.; Devadoss Gandhi, G.; Selvaraj, S.; Al-Muftah, W.; Badji, R.; Al-Sarraj, Y.; Saad, C.; Darwish, D.; Alvi, M.; Fadl, T.; et al. Qatar genome: Insights on genomics from the Middle East. Hum. Mutat. 2022, 43, 499–510. [Google Scholar] [CrossRef] [PubMed]
- Thareja, G.; Al-Sarraj, Y.; Belkadi, A.; Almotawa, M.; Ismail, S.; Al-Muftah, W.; Badji, R.; Mbarek, H.; Darwish, D.; Fadl, T.; et al. Whole genome sequencing in the Middle Eastern Qatari population identifies genetic associations with 45 clinically relevant traits. Nat. Commun. 2021, 12, 1250. [Google Scholar] [CrossRef] [PubMed]
- Kent, W.J.; Sugnet, C.W.; Furey, T.S.; Roskin, K.M.; Pringle, T.H.; Zahler, A.M.; Haussler, D. The human genome browser at UCSC. Genome Res. 2002, 12, 996–1006. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Stenson, P.D.; Mort, M.; Ball, E.V.; Chapman, M.; Evans, K.; Azevedo, L.; Hayden, M.; Heywood, S.; Millar, D.S.; Phillips, A.D.; et al. The Human Gene Mutation Database (HGMD®): Optimizing its use in a clinical diagnostic or research setting. Hum. Genet. 2020, 139, 1197–1207. [Google Scholar] [CrossRef] [PubMed]
- Landrum, M.J.; Lee, J.M.; Benson, M.; Brown, G.R.; Chao, C.; Chitipiralla, S.; Gu, B.; Hart, J.; Hoffman, D.; Jang, W.; et al. ClinVar: Improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 2018, 46, D1062–D1067. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kircher, M.; Witten, D.M.; Jain, P.; O’Roak, B.J.; Cooper, G.M.; Shendure, J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 2014, 46, 310–315. [Google Scholar] [CrossRef] [Green Version]
- Ng, P.C.; Henikoff, S. SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003, 31, 3812–3814. [Google Scholar] [CrossRef] [Green Version]
- Adzhubei, I.A.; Schmidt, S.; Peshkin, L.; Ramensky, V.E.; Gerasimova, A.; Bork, P.; Kondrashov, A.S.; Sunyaev, S.R. A method and server for predicting damaging missense mutations. Nat. Method. 2010, 7, 248–249. [Google Scholar] [CrossRef]
Type 1 Diabetes | Type 2 Diabetes | Non-Diabetes | |
---|---|---|---|
Number of subjects ♦ | 72 (0.5%) | 2915 (20.3%) | 11,377 (79.2%) |
Age (mean ± SD) | 38.43 ± 14.7 * | 51.76 ± 11.8 * | 35.05 ± 11.7 |
Male | 34 (47.2%) | 1216 (41.7%) | 5104 (44.9%) |
Female | 38 (52.8%) | 1699 (58.3%) | 6273 (55.1%) |
BMI (kg/m²) ** | 28.6 ± 5.1 | 32.3 ± 6.0 * | 28.9 ± 6.0 |
Underweight | - | 3 (0.1%) | 262 (2.3%) |
Normal weight | 18 (25.0%) | 236 (8.1%) * | 2672 (23.5%) |
Overweight | 28 (38.9%) | 889 (30.5%) * | 4047 (35.6%) |
Obese | 25 (34.7%) | 1777 (61.0%) * | 4385 (38.5%) |
N/A | 1 (1.4%) | 10 (0.3%) | 11 (0.1%) |
HbA1c (%) | 8.8 ± 1.5 * | 7.4 ± 1.8 * | 5.3 ± 0.4 |
C-peptide (ng/mL) | 0.32 ± 0.14 * | 2.83 ± 1.67 * | 2.02 ± 1.4 |
Family History of Diabetes | |||
Father | 33 (45.8%) * | 1357 (46.5%) * | 4790 (42.1%) |
Mother | 33 (45.8%) * | 1810 (62.1%) * | 5113 (44.9%) |
Both | 18 (25.0%) * | 966 (33.1) * | 2504 (22.0%) |
Treatment | |||
Insulin | 72 (100.0%) | 645 (22.1%) | - |
Tablets | - | 2011 (69.0%) | - |
Gene * | MODY | ID | Ref/Alt | Protein Change | N | MAF | Penetrance (%) | Diagnosis (n) | CADD | HGMD | QCI | ClinVar | SIFT | PolyPhen-2 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
HNF4A | 1 | rs1555817727 | C/T | p.Arg312cys | 1 | 0.000035 | 100 | T2DM | 30 | DM | P | LP | D | P.D |
GCK | 2 | rs1375656631 | C/T | p.Ala259Thr | 3 | 0.000104 | 66.6 | N.D (1) T2DM (2) | 24.4 | DM | P | P | D | Benign |
GCK | 2 | rs104894005 | C/G | p.Glu279Gln | 1 | 0.000035 | 0 | N.D | 22.2 | DM | LP | P | T | Benign |
HNF1A | 3 | rs137853238 | G/A | p.Arg272his | 1 | 0.000035 | 100 | T2DM | 31 | DM | P | P | D | P.D |
HNF1A | 3 | rs587778397 | C/T | p.Arg177Trp | 5 | 0.000174 | 20 | N.D (4) T2DM (1) | 25.7 | DM | LP | VUS | T | P.D |
HNF1A | 3 | rs371717826 | C/G | p.Pro379arg | 3 | 0.000104 | 0 | N.D (3) | 26.7 | DM | P | N/A | D | P.D |
HNF1A | 3 | rs754729248 | C/G | p.Pro379Ala | 1 | 0.000035 | 0 | N.D (1) | 25 | DM | VUS | P | D | P.D |
KLF11 | 7 | rs121912645 | G/T | p.Ala347Ser | 1 | 0.000035 | 0 | N.D (1) | < 10 | DM | P | P | T | Benign |
BLK | 11 | rs766934515 | T/G | p.Val113Gly | 5 | 0.000174 | 0 | N.D (5) | 29.9 | DM? | LP | N/A | D | P.D |
ABCC8 | 12 | rs761862121 | T/G | p.Lys889Thr | 3 | 0.000104 | 0 | N.D (3) | 27.5 | DM | P | VUS | D | P.D |
Gene | MODY | ID | Ref/Alt | Protein Change | N | MAF | Penetrance (%) * | Diagnosis (n) | CADD | HGMD | QCI | ClinVar | SIFT | PolyPhen-2 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
HNF4A | 1 | rs769007443 | G/A | p.Gly64Arg | 1 | 0.000035 | 0 | N.D | 25.9 | DM | VUS | N/A | D | P.D |
HNF4A | 1 | rs371124358 | G/A | p.Arg310Gln | 1 | 0.000035 | 100 | T2DM | 23.5 | DM | VUS | VUS | T | Benign |
HNF4A | 1 | rs377151067 | G/A | p.V404I | 1 | 0.000035 | 100 | T2DM | 22.8 | DM | VUS | N/A | T | Benign |
GCK | 2 | rs193922285 | C/A | p.Met462Ile | 5 | 0.000174 | 40 | N.D (3) T2DM (2) | 22.9 | DM | VUS | VUS | T | Benign |
HNF1A | 3 | rs201095611 | G/A | p.Ala161Thr | 6 | 0.000209 | 16.67 | N.D (5) T1DM (1) | 27.3 | DM | VUS | VUS | D | P.D |
HNF1A | 3 | rs867576513 | T/C | p.Met283Thr | 6 | 0.000209 | 33.3 | N.D (4) T2DM (2) | 25.6 | DM | VUS | N/A | D | P.D |
HNF1A | 3 | rs368683806 | G/A | p.Gly415Arg | 1 | 0.000035 | 0 | N.D | 31 | DM | VUS | VUS | D | P.D |
HNF1A | 3 | rs577078110 | C/A | p.His505Asn | 2 | 0.000070 | 0 | N.D (2) | 26.3 | DM | VUS | N/A | D | P.D |
HNF1A | 3 | rs202039659 | A/G | p.His514Arg | 11 | 0.000383 | 27.2 | N.D (8) T2DM (3) | 24.8 | DM | VUS | VUS | D | P.D |
PDX1 | 4 | rs753249965 | G/A | p.Gly55Asp | 3 | 0.000104 | 0 | N.D (3) | 23.7 | DM | VUS | N/A | D | Benign |
HNF1B | 5 | rs113042313 | C/T | p.Gly370Ser | 1 | 0.000035 | 0 | N.D | 21 | DM | VUS | N/A | T | Benign |
BLK | 11 | rs368427116 | C/T | p.Thr270Met | 5 | 0.000174 | 0 | N.D (5) | 25.4 | DM | VUS | N/A | T | P.D |
Gene | MODY | Chr:Pos | ID | Ref/ Alt | Protein Change | N * | MAF | CADD | gnomAD MAF | SIFT | PolyPhen-2 |
---|---|---|---|---|---|---|---|---|---|---|---|
HNF4A | 1 | 20:44418486 | - | T/C | p.Met237Thr | 1 | 0.000035 | 26.2 | - | D | P.D |
HNF4A | 1 | 20:44424203 | rs776656815 | C/G | p.Leu360Val | 1 | 0.000035 | 22.8 | 0.0000239 | D | Benign |
GCK | 2 | 7:44145572 | - | A/T | p.Met393Lys | 1 | 0.000035 | 26.2 | - | D | Benign |
HNF1A | 3 | 12:120993541 | - | G/A | p.Gly183Glu | 1 | 0.000035 | 26.1 | - | D | P.D |
HNF1A | 3 | 12:120979082 | - | A/T | p.Glu105Val | 2 | 0.000070 | 25.2 | - | D | Benign |
HNF1A | 3 | 12:120999538 | - | C/T | p.Ser591Phe | 1 | 0.000035 | 24.1 | - | D | P.D |
PDX1 | 4 | 13:27924690 | rs1357043267 | G/C | p.Glu281Gln | 3 | 0.000104 | 23.1 | 0.000119 | D | Benign |
HNF1B | 5 | 17:37744622 | - | G/A | p.Thr88Ile | 1 | 0.000035 | 25.4 | - | D | Benign |
HNF1B | 5 | 17:37731607 | rs755951130 | T/C | p.Asn345Asp | 1 | 0.000035 | 22.6 | 0.0000081 | T | Benign |
NEUROD1 | 6 | 2:181678436 | - | G/A | p.Thr142Ile | 1 | 0.000035 | 28.2 | - | D | P.D |
KLF11 | 7 | 2:10046337 | - | A/G | p.Asp77Gly | 1 | 0.000035 | 27.9 | - | D | P.D |
KLF11 | 7 | 2:10048367 | - | C/T | p.Pro344Ser | 1 | 0.000035 | 23.2 | - | D | P.D |
KLF11 | 7 | 2:10046240 | - | A/T | p.Met45Leu | 1 | 0.000035 | 20.1 | - | T | Benign |
CEL | 8 | 9:133070564 | rs766487195 | G/A | p.Gly467Arg | 1 | 0.000035 | 26.1 | 0.0000080 | D | P.D |
CEL | 8 | 9:133064413 | rs748643667 | G/A | p.Val29Met | 1 | 0.000035 | 25.3 | 0.0000040 | D | P.D |
CEL | 8 | 9:133066888 | rs773198000 | C/G | p.Ser243Arg | 1 | 0.000035 | 22.9 | 0.0000242 | D | P.D |
CEL | 8 | 9:133069087 | - | A/G | p.Thr375Ala | 1 | 0.000035 | 22.3 | - | D | Benign |
BLK | 11 | 8:11554800 | rs775313404 | A/G | p.Tyr177Cys | 1 | 0.000035 | 29.4 | 0.0000119 | D | P.D |
ABCC8 | 12 | 11:17404576 | rs769818698 | C/T | p.Val1165Met | 2 | 0.000070 | 23.1 | 0.0000955 | D | Benign |
ABCC8 | 12 | 11:17427908 | - | C/T | p.Gly692Glu | 1 | 0.000035 | 22.7 | - | T | Benign |
KCNJ11 | 13 | 11:17387440 | - | G/T | p.Gln131Lys | 1 | 0.000035 | 24.2 | - | T | P.D |
KCNJ11 | 13 | 11:17387761 | rs867211548 | C/T | p.Val24Ile | 1 | 0.000035 | 20.7 | - | T | Benign |
APPL1 | 14 | 3:57269587 | - | A/T | p.Asn677Ile | 1 | 0.000035 | 21.4 | - | T | Benign |
RFX6 | - | 6:116922098 | rs1485759457 | G/A | p.Val462Met | 1 | 0.000035 | 26.1 | - | D | P.D |
RFX6 | - | 6:116927531 | rs762356403 | C/T | p.Ser797Leu | 1 | 0.000035 | 22.9 | 0.0000081 | D | Benign |
RFX6 | - | 6:116924786 | - | A/C | p.Asn558Thr | 1 | 0.000035 | 22.4 | - | T | Benign |
NKX6-1 | - | 4:84498074 | - | G/A | p.Ser52Phe | 2 | 0.000070 | 24.2 | - | D | Benign |
NKX6-1 | - | 4:84498145 | rs369821275 | C/G | p.Met28Ile | 2 | 0.000070 | 23.5 | 0.0000525 | D | Benign |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Elashi, A.A.; Toor, S.M.; Diboun, I.; Al-Sarraj, Y.; Taheri, S.; Suhre, K.; Abou-Samra, A.B.; Albagha, O.M.E. The Genetic Spectrum of Maturity-Onset Diabetes of the Young (MODY) in Qatar, a Population-Based Study. Int. J. Mol. Sci. 2023, 24, 130. https://doi.org/10.3390/ijms24010130
Elashi AA, Toor SM, Diboun I, Al-Sarraj Y, Taheri S, Suhre K, Abou-Samra AB, Albagha OME. The Genetic Spectrum of Maturity-Onset Diabetes of the Young (MODY) in Qatar, a Population-Based Study. International Journal of Molecular Sciences. 2023; 24(1):130. https://doi.org/10.3390/ijms24010130
Chicago/Turabian StyleElashi, Asma A., Salman M. Toor, Ilhame Diboun, Yasser Al-Sarraj, Shahrad Taheri, Karsten Suhre, Abdul Badi Abou-Samra, and Omar M. E. Albagha. 2023. "The Genetic Spectrum of Maturity-Onset Diabetes of the Young (MODY) in Qatar, a Population-Based Study" International Journal of Molecular Sciences 24, no. 1: 130. https://doi.org/10.3390/ijms24010130
APA StyleElashi, A. A., Toor, S. M., Diboun, I., Al-Sarraj, Y., Taheri, S., Suhre, K., Abou-Samra, A. B., & Albagha, O. M. E. (2023). The Genetic Spectrum of Maturity-Onset Diabetes of the Young (MODY) in Qatar, a Population-Based Study. International Journal of Molecular Sciences, 24(1), 130. https://doi.org/10.3390/ijms24010130