Glycated Serum Protein Genetics and Pleiotropy with Cardiometabolic Risk Factors

Autor: Juan M. Peralta, Sandra Laston, Janardan Subedi, John Blangero, Suman S Thapa, Satish Kumar, Matthew P. Johnson, Nicholas B. Blackburn, Bradford Towne, Sarah Williams-Blangero, Ryan Keyho
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Blood Glucose
Male
Glycosylation
Endocrinology
Diabetes and Metabolism
Blood Pressure
lcsh:Diseases of the endocrine glands. Clinical endocrinology
Body Mass Index
Diabetes mellitus genetics
0302 clinical medicine
Endocrinology
Polymorphism (computer science)
Risk Factors
Additive genetic effects
Aged
80 and over
0303 health sciences
Blood Proteins
Middle Aged
Lipids
3. Good health
Pedigree
Phenotype
Cardiovascular Diseases
Female
Research Article
Adult
medicine.medical_specialty
Diabetes risk
Article Subject
Adolescent
Genotype
Quantitative Trait Loci
030209 endocrinology & metabolism
Single-nucleotide polymorphism
Quantitative trait locus
Biology
Polymorphism
Single Nucleotide
03 medical and health sciences
Young Adult
stomatognathic system
Nepal
Internal medicine
medicine
Diabetes Mellitus
Humans
Genetic Predisposition to Disease
Serum Albumin
030304 developmental biology
Glycemic
Aged
Retrospective Studies
Family Health
Glycated Hemoglobin
lcsh:RC648-665
Cholesterol
HDL
Heritability
Hypoglycemia
Hyperglycemia
Lod Score
Biomarkers
Zdroj: Journal of Diabetes Research
Journal of Diabetes Research, Vol 2019 (2019)
ISSN: 2314-6753
2314-6745
Popis: 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.
Databáze: OpenAIRE
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