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Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors

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 glycate...

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Autores principales: Johnson, Matthew P., Keyho, Ryan, Blackburn, Nicholas B., Laston, Sandra, Kumar, Satish, Peralta, Juan, Thapa, Suman S., Towne, Bradford, Subedi, Janardan, Blangero, John, Williams-Blangero, Sarah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6476113/
https://www.ncbi.nlm.nih.gov/pubmed/31089471
http://dx.doi.org/10.1155/2019/2310235
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author Johnson, Matthew P.
Keyho, Ryan
Blackburn, Nicholas B.
Laston, Sandra
Kumar, Satish
Peralta, Juan
Thapa, Suman S.
Towne, Bradford
Subedi, Janardan
Blangero, John
Williams-Blangero, Sarah
author_facet Johnson, Matthew P.
Keyho, Ryan
Blackburn, Nicholas B.
Laston, Sandra
Kumar, Satish
Peralta, Juan
Thapa, Suman S.
Towne, Bradford
Subedi, Janardan
Blangero, John
Williams-Blangero, Sarah
author_sort Johnson, Matthew P.
collection PubMed
description 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 = 1,800). 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 values: 1.15 × 10(−5) and 3.39 × 10(−5), respectively). We localized a significant (LOD score = 3.18) and novel GSP QTL on chromosome 11q, which has been previously linked to type 2 diabetes. Two common (MAF > 0.4) SNPs within the chromosome 11 QTL were associated with GSP (adjusted pvalue < 5.87 × 10(−5)): an intronic variant (rs10790184) in the DSCAML1 gene and a 3′UTR variant (rs8258) in the CEP164 gene. Significant positive correlations were observed between GSP or %GA and blood pressure, and lipid traits (p values: 0.0062 to 1.78 × 10(−9)). A significant negative correlation was observed between %GA and HDL cholesterol (p = 1.12 × 10(−5)). 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.
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spelling pubmed-64761132019-05-14 Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors Johnson, Matthew P. Keyho, Ryan Blackburn, Nicholas B. Laston, Sandra Kumar, Satish Peralta, Juan Thapa, Suman S. Towne, Bradford Subedi, Janardan Blangero, John Williams-Blangero, Sarah J Diabetes Res Research Article 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 = 1,800). 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 values: 1.15 × 10(−5) and 3.39 × 10(−5), respectively). We localized a significant (LOD score = 3.18) and novel GSP QTL on chromosome 11q, which has been previously linked to type 2 diabetes. Two common (MAF > 0.4) SNPs within the chromosome 11 QTL were associated with GSP (adjusted pvalue < 5.87 × 10(−5)): an intronic variant (rs10790184) in the DSCAML1 gene and a 3′UTR variant (rs8258) in the CEP164 gene. Significant positive correlations were observed between GSP or %GA and blood pressure, and lipid traits (p values: 0.0062 to 1.78 × 10(−9)). A significant negative correlation was observed between %GA and HDL cholesterol (p = 1.12 × 10(−5)). 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. Hindawi 2019-04-04 /pmc/articles/PMC6476113/ /pubmed/31089471 http://dx.doi.org/10.1155/2019/2310235 Text en Copyright © 2019 Matthew P. Johnson et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Johnson, Matthew P.
Keyho, Ryan
Blackburn, Nicholas B.
Laston, Sandra
Kumar, Satish
Peralta, Juan
Thapa, Suman S.
Towne, Bradford
Subedi, Janardan
Blangero, John
Williams-Blangero, Sarah
Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors
title Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors
title_full Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors
title_fullStr Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors
title_full_unstemmed Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors
title_short Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors
title_sort glycated serum protein genetics and pleiotropy with cardiometabolic risk factors
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6476113/
https://www.ncbi.nlm.nih.gov/pubmed/31089471
http://dx.doi.org/10.1155/2019/2310235
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