{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T10:54:52Z","timestamp":1761562492957,"version":"3.37.3"},"reference-count":53,"publisher":"Wiley","license":[{"start":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T00:00:00Z","timestamp":1554336000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1C06RR020547","1R01EY024384"],"award-info":[{"award-number":["1C06RR020547","1R01EY024384"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000053","name":"National Eye Institute","doi-asserted-by":"publisher","award":["1C06RR020547","1R01EY024384"],"award-info":[{"award-number":["1C06RR020547","1R01EY024384"]}],"id":[{"id":"10.13039\/100000053","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008635","name":"University of Texas Health Science Center at San Antonio","doi-asserted-by":"publisher","award":["1C06RR020547","1R01EY024384"],"award-info":[{"award-number":["1C06RR020547","1R01EY024384"]}],"id":[{"id":"10.13039\/100008635","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Diabetes Research"],"published-print":{"date-parts":[[2019,4,4]]},"abstract":"Measurements of fasting glucose (FG) or glycated hemoglobin A1c (HbA1c) are two clinically approved approaches commonly used to determine glycemia, both of which are influenced by genetic factors. Obtaining accurate measurements of FG or HbA1c is not without its challenges, though. Measuring glycated serum protein (GSP) offers an alternative approach for assessing glycemia. The aim of this study was to estimate the heritability of GSP and GSP expressed as a percentage of total serum albumin (%GA) using a variance component approach and localize genomic regions (QTLs) that harbor genes likely to influence GSP and %GA trait variation in a large extended multigenerational pedigree from Jiri, Nepal (n<\/mml:mi>=<\/mml:mo>1,800<\/mml:mn><\/mml:math>). We also performed quantitative bivariate analyses to assess the relationship between GSP or %GA and several cardiometabolic traits. Additive genetic effects significantly influence variation in GSP and %GA levels (p<\/mml:mi><\/mml:math> values: 1.15<\/mml:mn>\u00d7<\/mml:mo>10<\/mml:mn><\/mml:mrow>\u2212<\/mml:mo>5<\/mml:mn><\/mml:mrow><\/mml:msup><\/mml:math> and 3.39<\/mml:mn>\u00d7<\/mml:mo>10<\/mml:mn><\/mml:mrow>\u2212<\/mml:mo>5<\/mml:mn><\/mml:mrow><\/mml:msup><\/mml:math>, respectively). We localized a significant (LOD score<\/mml:mtext>=<\/mml:mo>3.18<\/mml:mn><\/mml:math>) and novel GSP QTL on chromosome 11q, which has been previously linked to type 2 diabetes. Two common (MAF<\/mml:mtext>><\/mml:mo>0.4<\/mml:mn><\/mml:math>) SNPs within the chromosome 11 QTL were associated with GSP (adjusted p<\/mml:mi><\/mml:math>value<\/mml:mtext><<\/mml:mo>5.87<\/mml:mn>\u00d7<\/mml:mo>10<\/mml:mn><\/mml:mrow>\u2212<\/mml:mo>5<\/mml:mn><\/mml:mrow><\/mml:msup><\/mml:math>): an intronic variant (rs10790184) in the DSCAML1<\/jats:italic> gene and a 3\u2032<\/mml:mo><\/mml:mrow><\/mml:msup><\/mml:math>UTR variant (rs8258) in the CEP164<\/jats:italic> gene. Significant positive correlations were observed between GSP or %GA and blood pressure, and lipid traits (p<\/mml:mi><\/mml:math> values: 0.0062 to 1.78<\/mml:mn>\u00d7<\/mml:mo>10<\/mml:mn><\/mml:mrow>\u2212<\/mml:mo>9<\/mml:mn><\/mml:mrow><\/mml:msup><\/mml:math>). A significant negative correlation was observed between %GA and HDL cholesterol (p<\/mml:mi>=<\/mml:mo>1.12<\/mml:mn>\u00d7<\/mml:mo>10<\/mml:mn><\/mml:mrow>\u2212<\/mml:mo>5<\/mml:mn><\/mml:mrow><\/mml:msup><\/mml:math>). GSP is influenced by genetic factors and can be used to assess glycemia and diabetes risk. Thus, GSP measurements can facilitate glycemic studies when accurate FG and\/or HbA1c measurements are difficult to obtain. GSP can also be measured from frozen blood (serum) samples, which allows the prospect of retrospective glycemic studies using archived samples.<\/jats:p>","DOI":"10.1155\/2019\/2310235","type":"journal-article","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T19:42:15Z","timestamp":1554406935000},"page":"1-9","source":"Crossref","is-referenced-by-count":8,"title":["Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors"],"prefix":"10.1155","volume":"2019","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3278-1844","authenticated-orcid":true,"given":"Matthew P.","family":"Johnson","sequence":"first","affiliation":[{"name":"South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"},{"name":"Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9956-6909","authenticated-orcid":true,"given":"Ryan","family":"Keyho","sequence":"additional","affiliation":[{"name":"The University of Texas at Austin, Austin, Texas 78705, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9774-1539","authenticated-orcid":true,"given":"Nicholas B.","family":"Blackburn","sequence":"additional","affiliation":[{"name":"South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"},{"name":"Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandra","family":"Laston","sequence":"additional","affiliation":[{"name":"South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"},{"name":"Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1969-4431","authenticated-orcid":true,"given":"Satish","family":"Kumar","sequence":"additional","affiliation":[{"name":"South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"},{"name":"Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Peralta","sequence":"additional","affiliation":[{"name":"South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"},{"name":"Department of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA"},{"name":"Menzies Institute for Medical Research, University of Tasmania, Hobart 7000, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suman S.","family":"Thapa","sequence":"additional","affiliation":[{"name":"Tilganga Institute of Ophthalmology, Gaushala, Bagmati Bridge, P.O. 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