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      Identification of Novel Single Nucleotide Polymorphisms Associated with Acute Respiratory Distress Syndrome by Exome-Seq

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          Abstract

          Acute respiratory distress syndrome (ARDS) is a lung condition characterized by impaired gas exchange with systemic release of inflammatory mediators, causing pulmonary inflammation, vascular leak and hypoxemia. Existing biomarkers have limited effectiveness as diagnostic and therapeutic targets. To identify disease-associating variants in ARDS patients, whole-exome sequencing was performed on 96 ARDS patients, detecting 1,382,399 SNPs. By comparing these exome data to those of the 1000 Genomes Project, we identified a number of single nucleotide polymorphisms (SNP) which are potentially associated with ARDS. 50,190SNPs were found in all case subgroups and controls, of which89 SNPs were associated with susceptibility. We validated three SNPs (rs78142040, rs9605146 and rs3848719) in additional ARDS patients to substantiate their associations with susceptibility, severity and outcome of ARDS. rs78142040 (C>T) occurs within a histone mark (intron 6) of the Arylsulfatase D gene. rs9605146 (G>A) causes a deleterious coding change (proline to leucine) in the XK, Kell blood group complex subunit-related family, member 3 gene. rs3848719 (G>A) is a synonymous SNP in the Zinc-Finger/Leucine-Zipper Co-Transducer NIF1 gene. rs78142040, rs9605146, and rs3848719 are associated significantly with susceptibility to ARDS. rs3848719 is associated with APACHE II score quartile. rs78142040 is associated with 60-day mortality in the overall ARDS patient population. Exome-seq is a powerful tool to identify potential new biomarkers for ARDS. We selectively validated three SNPs which have not been previously associated with ARDS and represent potential new genetic biomarkers for ARDS. Additional validation in larger patient populations and further exploration of underlying molecular mechanisms are warranted.

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          Genetic control of obesity and gut microbiota composition in response to high-fat, high-sucrose diet in mice.

          Obesity is a highly heritable disease driven by complex interactions between genetic and environmental factors. Human genome-wide association studies (GWAS) have identified a number of loci contributing to obesity; however, a major limitation of these studies is the inability to assess environmental interactions common to obesity. Using a systems genetics approach, we measured obesity traits, global gene expression, and gut microbiota composition in response to a high-fat/high-sucrose (HF/HS) diet of more than 100 inbred strains of mice. Here we show that HF/HS feeding promotes robust, strain-specific changes in obesity that are not accounted for by food intake and provide evidence for a genetically determined set point for obesity. GWAS analysis identified 11 genome-wide significant loci associated with obesity traits, several of which overlap with loci identified in human studies. We also show strong relationships between genotype and gut microbiota plasticity during HF/HS feeding and identify gut microbial phylotypes associated with obesity. Copyright © 2013 Elsevier Inc. All rights reserved.
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            Quality control and quality assurance in genotypic data for genome-wide association studies.

            Genome-wide scans of nucleotide variation in human subjects are providing an increasing number of replicated associations with complex disease traits. Most of the variants detected have small effects and, collectively, they account for a small fraction of the total genetic variance. Very large sample sizes are required to identify and validate findings. In this situation, even small sources of systematic or random error can cause spurious results or obscure real effects. The need for careful attention to data quality has been appreciated for some time in this field, and a number of strategies for quality control and quality assurance (QC/QA) have been developed. Here we extend these methods and describe a system of QC/QA for genotypic data in genome-wide association studies (GWAS). This system includes some new approaches that (1) combine analysis of allelic probe intensities and called genotypes to distinguish gender misidentification from sex chromosome aberrations, (2) detect autosomal chromosome aberrations that may affect genotype calling accuracy, (3) infer DNA sample quality from relatedness and allelic intensities, (4) use duplicate concordance to infer SNP quality, (5) detect genotyping artifacts from dependence of Hardy-Weinberg equilibrium test P-values on allelic frequency, and (6) demonstrate sensitivity of principal components analysis to SNP selection. The methods are illustrated with examples from the "Gene Environment Association Studies" (GENEVA) program. The results suggest several recommendations for QC/QA in the design and execution of GWAS. (c) 2010 Wiley-Liss, Inc.
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              Pre-B-cell colony-enhancing factor as a potential novel biomarker in acute lung injury.

              Although the pathogenic and genetic basis of acute lung injury (ALI) remains incompletely understood, the identification of novel ALI biomarkers holds promise for unique insights. Expression profiling in animal models of ALI (canine and murine) and human ALI detected significant expression of pre-B-cell colony-enhancing factor (PBEF), a gene not previously associated with lung pathophysiology. These results were validated by real-time polymerase chain reaction and immunohistochemistry studies, with PBEF protein levels significantly increased in both bronchoalveolar lavage fluid and serum of ALI models and in cytokine- or cyclic stretch-activated lung microvascular endothelium. We genotyped two PBEF single-nucleotide polymorphisms (SNPs) in a well characterized sample of white patients with sepsis-associated ALI, patients with severe sepsis, and healthy subjects and observed that carriers of the haplotype GC from SNPs T-1001G and C-1543T had a 7.7-fold higher risk of ALI (95% confidence interval 3.01-19.75, p < 0.001). The T variant from the SNP C-1543T resulted in a significant decrease in the transcription rate (1.8-fold; p < 0.01) by the reporter gene assay. Together, these results strongly indicate that PBEF is a potential novel biomarker in ALI and demonstrate the successful application of robust genomic technologies in the identification of candidate genes in complex lung disease.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                5 November 2014
                : 9
                : 11
                : e111953
                Affiliations
                [1 ]Department of Pediatrics, Division of Experimental and Translational Genetics, Children's Mercy Hospital, University of Missouri - Kansas City School of Medicine, Kansas City, Missouri, United States of America
                [2 ]Department of Biomedical and Health Informatics, University of Missouri - Kansas City School of Medicine, Kansas City, Missouri, United States of America
                University of Illinois College of Medicine, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: SQY LZ. Performed the experiments: KS SC. Analyzed the data: KS DG DPH. Contributed reagents/materials/analysis tools: SQY KS. Contributed to the writing of the manuscript: SQY LZ LV DPH DG KS.

                Article
                PONE-D-14-30342
                10.1371/journal.pone.0111953
                4221189
                25372662
                6a0d1ae0-0fc8-42c8-8271-e98d53993eaa
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 July 2014
                : 29 September 2014
                Page count
                Pages: 11
                Funding
                Funding was in part provided by NHLBI/NIH Grant (HL080042 & HL080042-S1, Ye, SQ), start-up fund and endowments of Children's Mercy Hospitals and Clinics, UMKC (Ye, SQ), and a Sarah Morrison Student Research Award of UMKC (Shortt, K). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Evolutionary Biology
                Population Genetics
                Genetics
                Medicine and Health Sciences
                Clinical Genetics
                Personalized Medicine
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. Sequencing data have been submitted to the NCBI BioProject database (Accession ID: 262819, http://www.ncbi.nlm.nih.gov/bioproject/262819).

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