{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:40:11Z","timestamp":1760060411289,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:00:00Z","timestamp":1755820800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000057","name":"NIGMS","doi-asserted-by":"publisher","award":["P20GM103442","R01-MD012765","R01HD104756","U01DK123795"],"award-info":[{"award-number":["P20GM103442","R01-MD012765","R01HD104756","U01DK123795"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NIMHD","award":["P20GM103442","R01-MD012765","R01HD104756","U01DK123795"],"award-info":[{"award-number":["P20GM103442","R01-MD012765","R01HD104756","U01DK123795"]}]},{"name":"NICHD","award":["P20GM103442","R01-MD012765","R01HD104756","U01DK123795"],"award-info":[{"award-number":["P20GM103442","R01-MD012765","R01HD104756","U01DK123795"]}]},{"name":"NIDDK","award":["P20GM103442","R01-MD012765","R01HD104756","U01DK123795"],"award-info":[{"award-number":["P20GM103442","R01-MD012765","R01HD104756","U01DK123795"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JPM"],"abstract":"<jats:p>Background\/Objectives: Gestational diabetes mellitus (GDM) is a state of hyperglycemia during pregnancy, increasing the risk of birth complications, and subsequent type 2 diabetes mellitus in the mother and offspring. Risk factors such as diet, obesity, and family history have demonstrated strong association with GDM, but no clear pathophysiology has been ascertained. Methods: An analysis was conducted on 38 women with and 296 without GDM, within a case\/control study of pre-eclampsia. The genetic variants examined were selected from among a published polygenic risk score of 10 variants (PRS-10). Genetic models were evaluated for each variant by multivariate logistic regression methods adjusted for age, body mass index, and pre-eclampsia. Since the genotypes for three of the PRS-10 were not available, a risk score comprising the total risk alleles among seven of the variants (PRS-7) was evaluated among those with all genotypes available. Results: Multivariate logistic regression showed significant, independent, positive associations between body mass index (BMI) and age. The posited PRS-7 showed a trend (OR 1.56, 95% CI 0.92\u20132.56, p = 0.070), and sensitivity analysis comprising three variants (PRS-3) was significantly associated with GDM (OR 2.43, 95% CI 1.17\u20135.06, p = 0.017). In univariate analysis, rs1421085 was associated with GDM (OR 0.50, 95% CI 0.26\u20130.95, p = 0.034), but not after adjustment for covariates, and paradoxically not for the expected risk allele. None of the other six variants showed an individual association with GDM. The previously published meta-analysis of PRS-10 showed a degree of heterogeneity (pQ= 0.03) among the three cohorts analyzed, suggesting that variant effects may differ according to the genetic background, which points to the importance of examining the generalizability of any posited polygenic risk scores. Conclusions: In conclusion, we provide additional support for and further refine the results of a previously published polygenic risk score for GDM in an ethically unrelated population.<\/jats:p>","DOI":"10.3390\/jpm15090395","type":"journal-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T11:50:31Z","timestamp":1755863431000},"page":"395","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Polygenic Risk Score Associated with Gestational Diabetes Mellitus in an AmericanIndian Population"],"prefix":"10.3390","volume":"15","author":[{"given":"Karrah","family":"Peterson","sequence":"first","affiliation":[{"name":"Pathology Department, University of North Dakota, Grand Forks, ND 58202, USA"},{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7060-7778","authenticated-orcid":false,"given":"Camille E.","family":"Powe","sequence":"additional","affiliation":[{"name":"Diabetes Unit, Endocrine Division, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"Broad Institute, Cambridge, MA 02142, USA"},{"name":"Harvard Medical School, Harvard University, Boston, MA 02115, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8324-2803","authenticated-orcid":false,"given":"Quan","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA"},{"name":"Center for Computational and Genomic Medicine, Children\u2019s Hospital of Philadelphia, Philadelphia, PA 19104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Crystal","family":"Azure","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tia","family":"Azure","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hailey","family":"Davis","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kennedy","family":"Gourneau","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shyanna","family":"LaRocque","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Craig","family":"Poitra","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sabra","family":"Poitra","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shayden","family":"Standish","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4865-6631","authenticated-orcid":false,"given":"Tyler J.","family":"Parisien","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2960-9203","authenticated-orcid":false,"given":"Kelsey J.","family":"Morin","sequence":"additional","affiliation":[{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7813-0724","authenticated-orcid":false,"given":"Lyle G.","family":"Best","sequence":"additional","affiliation":[{"name":"Pathology Department, University of North Dakota, Grand Forks, ND 58202, USA"},{"name":"Natural Sciences, Turtle Mountain Community College, Belcourt, ND 58316, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1111\/j.1600-0897.2011.01076.x","article-title":"Genetic variants, immune function, and risk of pre-eclampsia among American Indians","volume":"67","author":"Best","year":"2012","journal-title":"Am. J. Reprod. Immunol."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Best, L.G., Saxena, R., Anderson, C.M., Barnes, M.R., Hakonarson, H., Falcon, G., Martin, C., Castillo, B.A., Karumanchi, A., and Keplin, K. (2013). Two variants of the C-reactive protein gene are associated with risk of pre-eclampsia in an American Indian population. PLoS ONE, 8, Erratum in PLoS ONE\u00a02013, 8.","DOI":"10.1371\/journal.pone.0071231"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e49","DOI":"10.1097\/AOG.0000000000002501","article-title":"ACOG Practice Bulletin No. 190: Gestational Diabetes Mellitus","volume":"131","author":"Caughey","year":"2018","journal-title":"Obstet. Gynecol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Modzelewski, R., Stefanowicz-Rutkowska, M.M., Matuszewski, W., and Bandurska-Stankiewicz, E.M. (2022). Gestational Diabetes Mellitus-Recent Literature Review. J. Clin. Med., 11.","DOI":"10.3390\/jcm11195736"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"487","DOI":"10.2337\/diacare.25.3.487","article-title":"A comparison of rates, risk factors, and outcomes of gestational diabetes between aboriginal and non-aboriginal women in the Saskatoon health district","volume":"25","author":"Dyck","year":"2002","journal-title":"Diabetes Care"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Plows, J.F., Stanley, J.L., Baker, P.N., Reynolds, C.M., and Vickers, M.H. (2018). The Pathophysiology of Gestational Diabetes Mellitus. Int. J. Mol. Sci., 19.","DOI":"10.3390\/ijms19113342"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"e003324","DOI":"10.1136\/bmjdrc-2023-003324","article-title":"Effect of the interaction between advanced maternal age and pre-pregnancy BMI on pre-eclampsia and GDM in Central China","volume":"11","author":"Sun","year":"2023","journal-title":"BMJ Open Diabetes Res. Care"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Giannakou, K., Evangelou, E., Yiallouros, P., Christophi, C.A., Middleton, N., Papatheodorou, E., and Papatheodorou, S.I. (2019). Risk factors for gestational diabetes: An umbrella review of meta-analyses of observational studies. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0215372"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"6692695","DOI":"10.1155\/2021\/6692695","article-title":"Factors Associated with Gestational Diabetes Mellitus: A Meta-Analysis","volume":"2021","author":"Zhang","year":"2021","journal-title":"J. Diabetes Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1055\/s-0039-1700797","article-title":"Gestational Diabetes in the Population Served by Brazilian Public Health Care. Prevalence and Risk Factors","volume":"42","author":"Madi","year":"2020","journal-title":"Rev. Bras. Ginecol. Obstet."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/0091-2182(94)90015-9","article-title":"Current perspectives on preeclampsia","volume":"39","author":"Roberts","year":"1994","journal-title":"J. Nurse Midwifery"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"268","DOI":"10.2337\/db20-0772","article-title":"Genetic Loci and Physiologic Pathways Involved in Gestational Diabetes Mellitus Implicated Through Clustering","volume":"70","author":"Powe","year":"2021","journal-title":"Diabetes"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e0175071","DOI":"10.1371\/journal.pone.0175071","article-title":"Assessing gene-environment interaction effects of FTO, MC4R and lifestyle factors on obesity using an extreme phenotype sampling design: Results from the HUNT study","volume":"12","author":"Langaas","year":"2017","journal-title":"PLoS ONE"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Namjou, B., Stanaway, I.B., Lingren, T., Mentch, F.D., Benoit, B., Dikilitas, O., Niu, X., Shang, N., Shoemaker, A.H., and Carey, D.J. (2020). Evaluation of the MC4R gene across eMERGE network identifies many unreported obesity-associated variants. Int. J. Obes. (Lond.).","DOI":"10.1038\/s41366-020-00675-4"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1093\/hmg\/ddy327","article-title":"Meta-analysis of genome-wide association studies for body fat distribution in 694\u00a0649 individuals of European ancestry","volume":"28","author":"Pulit","year":"2019","journal-title":"Hum. Mol. Genet."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2726","DOI":"10.1007\/s00125-024-06256-8","article-title":"Genetics of glucose homeostasis in pregnancy and postpartum","volume":"67","author":"Lowe","year":"2024","journal-title":"Diabetologia"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Tsay, A., and Wang, J.C. (2023). The Role of PIK3R1 in Metabolic Function and Insulin Sensitivity. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms241612665"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1505","DOI":"10.1038\/s41588-018-0241-6","article-title":"Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps","volume":"50","author":"Mahajan","year":"2018","journal-title":"Nat. Genet."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1036088","DOI":"10.3389\/fendo.2022.1036088","article-title":"Genetic variants for prediction of gestational diabetes mellitus and modulation of susceptibility by a nutritional intervention based on a Mediterranean diet","volume":"13","author":"Barabash","year":"2022","journal-title":"Front. Endocrinol. (Lausanne)"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Keating, B.J., Tischfield, S., Murray, S.S., Bhangale, T., Price, T.S., Glessner, J.T., Galver, L., Barrett, J.C., Grant, S.F.A., and Farlow, D.N. (2008). Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies. PLoS ONE, 3.","DOI":"10.1371\/journal.pone.0003583"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1086\/519795","article-title":"PLINK: A tool set for whole-genome association and population-based linkage analyses","volume":"81","author":"Purcell","year":"2007","journal-title":"Am. J. Hum. Genet."},{"key":"ref_22","unstructured":"Available online: https:\/\/www.ncbi.nlm.nih.gov\/snp."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"144302","DOI":"10.1016\/j.gene.2019.144302","article-title":"The roles of ADIPOQ rs266729 and MTNR1B rs10830963 polymorphisms in patients with gestational diabetes mellitus: A meta-analysis","volume":"730","author":"Bai","year":"2020","journal-title":"Gene"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2754","DOI":"10.1210\/clinem\/dgae275","article-title":"Genetic Underpinnings of Fasting and Oral Glucose-stimulated Based Insulin Sensitivity Indices","volume":"109","author":"Suleman","year":"2024","journal-title":"J. Clin. Endocrinol. Metab."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Vejrazkova, D., Vankova, M., Vcelak, J., Krejci, H., Anderlova, K., Tura, A., Pacini, G., Sumova, A., Sladek, M., and Bendlova, B. (2022). The rs10830963 Polymorphism of the MTNR1B Gene: Association With Abnormal Glucose, Insulin and C-peptide Kinetics. Front. Endocrinol., 13.","DOI":"10.3389\/fendo.2022.868364"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1038\/s41574-025-01114-y","article-title":"Insulin resistance in type 2 diabetes mellitus","volume":"21","author":"Accili","year":"2025","journal-title":"Nat. Rev. Endocrinol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4125","DOI":"10.1111\/jcmm.17441","article-title":"MC4R biased signalling and the conformational basis of biological function selections","volume":"26","author":"Liu","year":"2022","journal-title":"J. Cell. Mol. Med."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1056\/NEJMoa1502214","article-title":"FTO Obesity Variant Circuitry and Adipocyte Browning in Humans","volume":"373","author":"Claussnitzer","year":"2015","journal-title":"N. Engl. J. Med."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1186\/s13098-017-0234-0","article-title":"Gene variants in the FTO gene are associated with adiponectin and TNF-alpha levels in gestational diabetes mellitus","volume":"9","author":"Saucedo","year":"2017","journal-title":"Diabetol. Metab. Syndr."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"128","DOI":"10.4093\/dmj.2024.0139","article-title":"Identification and Potential Clinical Utility of Common Genetic Variants in Gestational Diabetes among Chinese Pregnant Women","volume":"49","author":"Tam","year":"2025","journal-title":"Diabetes Metab. J."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1111\/cen.13356","article-title":"A genetic risk score that includes common type 2 diabetes risk variants is associated with gestational diabetes","volume":"87","author":"Kawai","year":"2017","journal-title":"Clin. Endocrinol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1159","DOI":"10.1507\/endocrj.EJ23-0245","article-title":"Associations between a polygenic risk score and the risk of gestational diabetes mellitus in a Chinese population: A case-control study","volume":"70","author":"Li","year":"2023","journal-title":"Endocr. J."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1186\/s13098-022-00788-y","article-title":"An early prediction model for gestational diabetes mellitus based on genetic variants and clinical characteristics in China","volume":"14","author":"Wu","year":"2022","journal-title":"Diabetol. Metab. Syndr."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Cheng, J., Meng, C., Li, J., Kong, Z., and Zhou, A. (2024). Integrating polygenic risk scores in the prediction of gestational diabetes risk in China. Front. Endocrinol., 15.","DOI":"10.3389\/fendo.2024.1391296"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1758","DOI":"10.1007\/s00125-018-4637-8","article-title":"Genetic variants of gestational diabetes mellitus: A study of 112 SNPs among 8722 women in two independent populations","volume":"61","author":"Ding","year":"2018","journal-title":"Diabetologia"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Peri\u0161i\u0107, M.M., Vladimir, K., Karpov, S., \u0160torga, M., Mostashari, A., and Khanin, R. (2022). Polygenic Risk Score and Risk Factors for Gestational Diabetes. J. Pers. Med., 12.","DOI":"10.20944\/preprints202207.0305.v1"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"e81498","DOI":"10.7554\/eLife.81498","article-title":"Born in Bradford and START investigators. The genetic risk of gestational diabetes in South Asian women","volume":"11","author":"Lamri","year":"2022","journal-title":"Elife"}],"container-title":["Journal of Personalized Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-4426\/15\/9\/395\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:33:45Z","timestamp":1760034825000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-4426\/15\/9\/395"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,22]]},"references-count":37,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2025,9]]}},"alternative-id":["jpm15090395"],"URL":"https:\/\/doi.org\/10.3390\/jpm15090395","relation":{},"ISSN":["2075-4426"],"issn-type":[{"type":"electronic","value":"2075-4426"}],"subject":[],"published":{"date-parts":[[2025,8,22]]}}}