Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD
Autor: | Sun, Wei, Kechris, Katerina, Jacobson, Sean, Drummond, M Bradley, Hawkins, Gregory A, Yang, Jenny, Chen, Ting-Huei, Quibrera, Pedro Miguel, Anderson, Wayne, Barr, R Graham, Basta, Patricia V, Bleecker, Eugene R, Beaty, Terri, Casaburi, Richard, Castaldi, Peter, Cho, Michael H, Comellas, Alejandro, Crapo, James D, Criner, Gerard, Demeo, Dawn, Christenson, Stephanie A, Couper, David J, Curtis, Jeffrey L, Doerschuk, Claire M, Freeman, Christine M, Gouskova, Natalia A, Han, MeiLan K, Hanania, Nicola A, Hansel, Nadia N, Hersh, Craig P, Hoffman, Eric A, Kaner, Robert J, Kanner, Richard E, Kleerup, Eric C, Lutz, Sharon, Martinez, Fernando J, Meyers, Deborah A, Peters, Stephen P, Regan, Elizabeth A, Rennard, Stephen I, Scholand, Mary Beth, Silverman, Edwin K, Woodruff, Prescott G, O'Neal, Wanda K, Bowler, Russell P, SPIROMICS Research Group, COPDGene Investigators |
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Přispěvatelé: | Gibson, Greg |
Rok vydání: | 2016 |
Předmět: |
0301 basic medicine
Cancer Research Chronic bronchitis Pulmonology Physiology Gene Expression Genome-wide association study QH426-470 Bioinformatics Biochemistry Pulmonary Disease Chronic Obstructive Mathematical and Statistical Techniques 0302 clinical medicine Medicine and Health Sciences 2.1 Biological and endogenous factors Aetiology Lung Genetics (clinical) Genetics Genomics Hematology Blood Proteins Single Nucleotide Obstructive lung disease Body Fluids 3. Good health Phenotypes Blood Physical Sciences Respiratory Biomarker (medicine) Anatomy Statistics (Mathematics) Research Article Chronic Obstructive Genotype Chronic Obstructive Pulmonary Disease Quantitative Trait Loci Single-nucleotide polymorphism Biology Quantitative trait locus Research and Analysis Methods Polymorphism Single Nucleotide ABO Blood-Group System Pulmonary Disease 03 medical and health sciences ABO blood group system Genome-Wide Association Studies medicine Humans Genetic Predisposition to Disease Statistical Methods Polymorphism Molecular Biology Ecology Evolution Behavior and Systematics Genetic association Emphysema COPDGene Investigators Prevention Human Genome Biology and Life Sciences Computational Biology Human Genetics SPIROMICS Research Group Genome Analysis medicine.disease Good Health and Well Being 030104 developmental biology 030228 respiratory system Mathematics Biomarkers Meta-Analysis Genome-Wide Association Study Developmental Biology |
Zdroj: | PLoS genetics, vol 12, iss 8 PLoS Genetics PLoS Genetics, Vol 12, Iss 8, p e1006011 (2016) |
ISSN: | 1553-7404 |
Popis: | Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10−10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group. Author Summary Precision medicine is an emerging approach that takes into account variability in genes, gene and protein expression, environment and lifestyle. Recent advances in high-throughput genome-wide genotyping, genomics, and proteomics coupled with the creation of large, highly-phenotyped clinical cohorts now allows for integration of these molecular data sets at the individual level. Here we use genome-wide genotyping and blood measurements of 88 biomarkers in 1,340 subjects from two large NIH-supported clinical cohorts of smokers (SPIROMICS and COPDGene) to identify more than 300 novel DNA variants that influence measurement of blood protein levels (pQTLs). We find that many DNA variants explain a large portion of the variability of measured protein expression in blood. Furthermore, we show that integration of DNA variants with blood biomarker levels can improve the ability of predictive models to reflect the relationship between biomarker and disease features (e.g., emphysema) within chronic obstructive pulmonary disease (COPD). |
Databáze: | OpenAIRE |
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