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Association of a Low-Frequency Variant in HNF1A With Type 2 Diabetes in a Latino Population
Open accessAbstract
IMPORTANCE: Latino populations have one of the highest prevalences of type 2 diabetes worldwide. OBJECTIVES: To investigate the association between rare protein-coding genetic variants and prevalence of type 2 diabetes in a large Latino population and to explore potential molecular and physiological mechanisms for the observed relationships. DESIGN, SETTING, AND PARTICIPANTS: Whole-exome sequencing was performed on DNA samples from 3756 Mexican and US Latino individuals (1794 with type 2 diabetes and 1962 without diabetes) recruited from 1993 to 2013. One variant was further tested for allele frequency and association with type 2 diabetes in large multiethnic data sets of 14,276 participants and characterized in experimental assays. MAIN OUTCOME AND MEASURES: Prevalence of type 2 diabetes. Secondary outcomes included age of onset, body mass index, and effect on protein function. RESULTS: A single rare missense variant (c.1522G>A [p.E508K]) was associated with type 2 diabetes prevalence (odds ratio [OR], 5.48; 95% CI, 2.83-10.61; P = 4.4 × 10(-7)) in hepatocyte nuclear factor 1-α (HNF1A), the gene responsible for maturity onset diabetes of the young type 3 (MODY3). This variant was observed in 0.36% of participants without type 2 diabetes and 2.1% of participants with it. In multiethnic replication data sets, the p.E508K variant was seen only in Latino patients (n = 1443 with type 2 diabetes and 1673 without it) and was associated with type 2 diabetes (OR, 4.16; 95% CI, 1.75-9.92; P = .0013). In experimental assays, HNF-1A protein encoding the p.E508K mutant demonstrated reduced transactivation activity of its target promoter compared with a wild-type protein. In our data, carriers and noncarriers of the p.E508K mutation with type 2 diabetes had no significant differences in compared clinical characteristics, including age at onset. The mean (SD) age for carriers was 45.3 years (11.2) vs 47.5 years (11.5) for noncarriers (P = .49) and the mean (SD) BMI for carriers was 28.2 (5.5) vs 29.3 (5.3) for noncarriers (P = .19). CONCLUSIONS AND RELEVANCE: Using whole-exome sequencing, we identified a single low-frequency variant in the MODY3-causing gene HNF1A that is associated with type 2 diabetes in Latino populations and may affect protein function. This finding may have implications for screening and therapeutic modification in this population, but additional studies are required.
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“Another example is the p.E508K missense mutation in HNF1A, with carrier frequency of 0.1% of the general population and 0.7% of Latinos,8 which confers up to 5-fold increased risk for type 2 diabetes.9”
From Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations (2018) · cites this paper as [9]
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Cites
A framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R. E., Garimella, K. V., Maguire, J., Hartl, C., Philippakis, A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,457
Self-citationAn integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711
Self-citationVariance component model to account for sample structure in genome-wide association studies
Kang, H. M., Sul, J. H., Service, S. K., Zaitlen, N. A., Kong, S.-Y., Freimer, N. B., Sabatti, C., & Eskin, E. (2010) · Nature Genetics · doi:10.1038/ng.548 · Cited by 2,817
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V., Steinthorsdottir, V., Strawbridge, R. J., Khan, H., Grallert, H., et al. (2012) · Nature Genetics · doi:10.1038/ng.2383 · Cited by 1,912
Self-citationTwelve type 2 diabetes susceptibility loci identified through large-scale association analysis
The MAGIC investigators, Voight, B. F., The GIANT Consortium, Scott, L. J., Steinthorsdottir, V., Morris, A. P., Dina, C., Welch, R. P., Zeggini, E., Huth, C., et al. (2010) · Nature Genetics · doi:10.1038/ng.609 · Cited by 1,761
Self-citationEvolution and functional impact of rare coding variation from deep sequencing of human exomes
Tennessen, J. A., Bigham, A. W., O’Connor, T. D., Fu, W., Kenny, E. E., Gravel, S., McGee, S., Do, R., Liu, X., Jun, G., et al. (2012) · Science · doi:10.1126/science.1219240 · Cited by 1,613
Self-citationLi, B., & Leal, S. M. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.06.024 · Cited by 1,527
Genetic Mapping in Human Disease
Altshuler, D., Daly, M. J., & Lander, E. S. (2008) · Science · doi:10.1126/science.1156409 · Cited by 1,452
Self-citationPrevalence of diabetes and impaired fasting glucose in adults in the U.S. population
Cowie, C. C., Rust, K. F., Byrd-Holt, D. D., Eberhardt, M. S., Flegal, K. M., Engelgau, M. M., Saydah, S. H., Williams, D. E., Geiss, L. S., & Gregg, E. W. (2006) · Diabetes Care · doi:10.2337/dc06-0062 · Cited by 1,210
DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Mahajan, A., Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) Consortium, Go, M. J., Zhang, W., Below, J. E., Gaulton, K. J., et al. (2014) · Nature Genetics · doi:10.1038/ng.2897 · Cited by 1,034
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Cole, J. B., & Florez, J. C. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-020-0278-5 · Cited by 1,797
Self-citationDiabetes mellitus: The epidemic of the century
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Fuchsberger, C., Flannick, J., Teslovich, T. M., Mahajan, A., Agarwala, V., Gaulton, K. J., Ma, C., Fontanillas, P., Moutsianas, L., McCarthy, D. J., et al. (2016) · Nature · doi:10.1038/nature18642 · Cited by 1,051
Self-citationGenetic analyses of diverse populations improves discovery for complex traits
Wojcik, G. L., Graff, M., Nishimura, K. K., Tao, R., Haessler, J., Gignoux, C. R., Highland, H. M., Patel, Y. M., Sorokin, E. P., Avery, C. L., et al. (2019) · Nature · doi:10.1038/s41586-019-1310-4 · Cited by 1,033
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Ishigaki, K., Akiyama, M., Kanai, M., Takahashi, A., Kawakami, E., Sugishita, H., Sakaue, S., Matoba, N., Low, S.-K., Okada, Y., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0640-3 · Cited by 508
Genetics of Type 2 Diabetes—Pitfalls and Possibilities
Prasad, R., & Groop, L. (2015) · Genes · doi:10.3390/genes6010087 · Cited by 458
Mahajan, A., Wessel, J., Willems, S. M., Zhao, W., Robertson, N. R., Chu, A. Y., Gan, W., Kitajima, H., Taliun, D., Rayner, N. W., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0084-1 · Cited by 442
Self-citationCharacterization of Greater Middle Eastern genetic variation for enhanced disease gene discovery
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Self-citationIshigaki, K., Sakaue, S., Terao, C., Luo, Y., Sonehara, K., Yamaguchi, K., Amariuta, T., Too, C. L., Laufer, V. A., Scott, I. C., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01213-w · Cited by 347
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Ramamoorthy, A., Pacanowski, M., Bull, J. C., & Zhang, L. (2015) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.61 · Cited by 341
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Wang, D. D., & Hu, F. B. (2018) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(18)30037-8 · Cited by 281
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Li, Y. R., & Keating, B. J. (2014) · Genome Medicine · doi:10.1186/s13073-014-0091-5 · Cited by 214
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Karczewski, K. J., Gupta, R., Kanai, M., Lu, W., Tsuo, K., Wang, Y., Walters, R. K., Turley, P., Callier, S., Shah, N. N., et al. (2024) · medRxiv · doi:10.1101/2024.03.13.24303864 · Cited by 166
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Bonnefond, A., & Froguel, P. (2015) · Cell Metabolism · doi:10.1016/j.cmet.2014.12.020 · Cited by 174
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Self-citationGenomic insights into the causes of type 2 diabetes
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Self-citationCommon and rare forms of diabetes mellitus: towards a continuum of diabetes subtypes
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Self-citationMonogenic Diabetes: What It Teaches Us on the Common Forms of Type 1 and Type 2 Diabetes
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Self-citationBonàs‐Guarch, S., Guindo-Martínez, M., Miguel-Escalada, I., Grarup, N., Sebastián, D., Rodríguez-Fos, E., Sánchez, F., Planas-Fèlix, M., Cortés-Sánchez, P., González, S., et al. (2018) · Nature Communications · doi:10.1038/s41467-017-02380-9 · Cited by 123
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Mohlke, K. L., & Boehnke, M. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv264 · Cited by 124
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Karczewski, K. J., Gupta, R., Kanai, M., Lu, W., Tsuo, K., Wang, Y., Walters, R. K., Turley, P., Callier, S., Shah, N. N., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02335-7 · Cited by 274
Genetics of Venous Thrombosis: update in 2015
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Precision medicine in diabetes: an opportunity for clinical translation
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HNF1A：From Monogenic Diabetes to Type 2 Diabetes and Gestational Diabetes Mellitus
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Basile, K. J., Guy, V. C., Schwartz, S. S., & Grant, S. F. A. (2014) · Current Diabetes Reports · doi:10.1007/s11892-014-0550-9 · Cited by 44
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Murphy, R., Colclough, K., Pollin, T. I., Iklé, J. M., Svalastoga, P., Maloney, K. A., Saint‐Martin, C., Molnes, J., PMDI, A., Tobias, D. K., et al. (2023) · Communications Medicine · doi:10.1038/s43856-023-00369-8 · Cited by 55
Althari, S., Najmi, L. A., Bennett, A. J., Aukrust, I., Rundle, J. K., Colclough, K., Molnes, J., Kaci, A., Nawaz, S., van der Lugt, T., et al. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.08.016 · Cited by 40
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Self-citationWojcik, G. L., Fuchsberger, C., Taliun, D., Welch, R., Martin, A. R., Shringarpure, S., Carlson, C. S., Abecasis, G. R., Kang, H. M., Boehnke, M., et al. (2018) · G3 Genes Genomes Genetics · doi:10.1534/g3.118.200502 · Cited by 42
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Rajabli, F., Benchek, P. H., Tosto, G., Kushch, N. A., Sha, J., Bazemore, K., Zhu, C., Lee, W., Haut, J., Hamilton‐Nelson, K. L., et al. (2025) · Genome biology · doi:10.1186/s13059-025-03564-z · Cited by 44
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Berumen-Campos, J., Orozco, L., Gallardo‐Rincón, H., Rivas, F., Barrera, E., Benuto, R. E., Garcia‐Ortíz, H., Marin-Madina, M., Juárez-Torres, E., Alvarado-Silva, A., et al. (2023) · Biology of Sex Differences · doi:10.1186/s13293-023-00521-y · Cited by 28
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Fernández-López, J. C., Romero-Cordoba, S. L., Rebollar‐Vega, R., Alfaro-Ruíz, L. A., Jiménez‐Morales, S., Beltrán‐Anaya, F. O., Arellano-Llamas, R., Cedro‐Tanda, A., Ríos-Romero, M., Ramirez-Florencio, M., et al. (2019) · Human Genomics · doi:10.1186/s40246-018-0188-9 · Cited by 25
Metadata
- Authors
- Estrada, K., Aukrust, I., Bjørkhaug, L., Burtt, N. P., Mercader, J. M., García-Ortiz, H., Huerta-Chagoya, A., Moreno-Macías, H., Walford, G., Flannick, J., Williams, A. L., Gómez-Vázquez, M. J., Fernandez-Lopez, J. C., Martínez-Hernández, A., Centeno-Cruz, F., Mendoza-Caamal, E., Revilla-Monsalve, C., Islas-Andrade, S., Córdova, E. J., Soberón, X., González-Villalpando, M. E., Henderson, E., Wilkens, L. R., Le Marchand, L., Arellano-Campos, O., Ordóñez-Sánchez, M. L., Rodríguez-Torres, M., Rodríguez-Guillén, R., Riba, L., Najmi, L. A., Jacobs, S. B. R., Fennell, T., Gabriel, S., Fontanillas, P., Hanis, C. L., Lehman, D. M., Jenkinson, C. P., Abboud, H. E., Bell, G. I., Cortes, M. L., Boehnke, M., González-Villalpando, C., Orozco, L., Haiman, C. A., Tusié-Luna, T., Aguilar-Salinas, C. A., Altshuler, D., Njølstad, P. R., Florez, J. C., & MacArthur, D. G.
- Affiliations
- Broad Institute (US)
- University of Bergen (NO)
- Haukeland University Hospital (NO)
- Instituto Nacional de Medicina Genómica, Tlalpan, Mexico City, Mexico
- Instituto de Investigaciones Biomédicas, UNAM Unidad de Biología Molecular y Medicina Genómica, UNAM/INCMNSZ, Coyoacán, Mexico City, Mexico
- Universidad Autónoma Metropolitana (MX)
- Harvard University (US)
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (MX)
- National Institute of Genomic Medicine (MX)
- Unidad de Investigación Médica en Enfermedades Metabólicas, CMN SXXI, Instituto Mexicano del Seguro Social, Mexico City
- Instituto Nacional de Salud Pública (MX)
- University of Southern California (US)
- University of Hawaii Cancer Center (US)
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
- Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Sección XVI, Tlalpan, Mexico City, Mexico
- The University of Texas Health Science Center at Houston (US)
- The University of Texas at San Antonio Health Science Center (US)
- University of Chicago (US)
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts
- University of Michigan (US)
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Publica, Mexico City, Mexico
- Instituto de Investigaciones Biomédicas, UNAM Unidad de Biología Molecular y Medicina Genómica, UNAM/INCMNSZ, Coyoacán, Mexico City, Mexico17Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Sección XVI, Tlalpan, Mexico City, Mexico
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts3Department of Medicine, Harvard Medical School, Boston, Massachusetts7Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit),
- ORCID
- Estrada, Karol
- Aukrust, Ingvild
- Bjørkhaug, Lise
- Burtt, Noël P.
- Mercader, Josep M.
- Moreno-Macías, Hortensia
- Flannick, Jason
- Williams, Amy L.
- Martínez-Hernández, Angélica
- Centeno-Cruz, Federico
- Córdova, Emilio J.
- Soberón, Xavier
- Henderson, E.
- Wilkens, Lynne R.
- Jacobs, Suzanne B.R.
- Gabriel, Stacey
- Fontanillas, Pierre
- Hanis, Craig L.
- Lehman, Donna M.
- Jenkinson, Christopher P.
- Boehnke, Michael
- Orozco, Lorena
- Haiman, Christopher A.
- Aguilar-Salinas, Carlos A.
- Altshuler, David
- Njølstad, Pål R.
- MacArthur, Daniel G.
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2014-06-11
- Volume
- 311
- Issue
- 22
- Pages
- 2305
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC4425850
- OpenAlex
- W2055830789
- Cited by
- 259
- References
- 57
- Citations by year
- 2026: 7 · 2025: 12 · 2024: 22 · 2023: 24 · 2022: 24 · 2021: 21 · 2020: 15 · 2019: 22 · 2018: 30 · 2017: 22 · 2016: 31 · 2015: 23 · 2014: 6
- FWCI
- 17.95
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Funders
- Consejo Nacional de Ciencia y Tecnología
- Helse Vest
- National Institutes of Health
- National Heart, Lung, and Blood Institute (R01HL024799, P01HL045522, R01HL24799)
- National Cancer Institute (R35CA053890, CA164973, R01CA144034, R01CA080205, U01CA063464, R37CA054281, R35-CA53890, R01CA054281, R01 CA 80205, R01CA063464, UM1CA164973, CA054281, CA063464, R01CA055069, U01CA164973)
- National Institute of Diabetes and Digestive and Kidney Diseases (U01DK085526, R01 DK057295, U01DK057295, U01DK085501, U01DK062370, R01DK042273, R01DK047482, R01DK053889, R01DK098032, R01DK033665, P30DK020572)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- type 2 diabetes, HNF1A, rare missense variants, Latino population, Mexican Americans, MODY3, genetic susceptibility, transactivation activity, age of onset, body mass index, exome sequencing, genetic association, diabetes prevalence, protein-coding variants, age at onset of diabetes
- MeSH terms
- Adult, Aged, Diabetes Mellitus, Type 2, Female, Genotype, Hispanic or Latino, Humans, Male, Mexico, Middle Aged, United States, Sequence Analysis, DNA, Age of Onset, Mutation, Missense, Hepatocyte Nuclear Factor 1-alpha
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