Overlap of Genetic Risk between Interstitial Lung Abnormalities and Idiopathic Pulmonary Fibrosis

Rationale: Interstitial lung abnormalities (ILAs) are associated with the highest genetic risk locus for idiopathic pulmonary fibrosis (IPF); however, the extent to which there are unique associations among individuals with ILAs or additional overlap with IPF is not known.Objectives: To perform a genome-wide association study (GWAS) of ILAs.Methods: ILAs and a subpleural-predominant subtype were assessed on chest computed tomography (CT) scans in the AGES (Age Gene/Environment Susceptibility), COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]), Framingham Heart, ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points), MESA (Multi-Ethnic Study of Atherosclerosis), and SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) studies. We performed a GWAS of ILAs in each cohort and combined the results using a meta-analysis. We assessed for overlapping associations in independent GWASs of IPF.Measurements and Main Results: Genome-wide genotyping data were available for 1,699 individuals with ILAs and 10,274 control subjects. The MUC5B (mucin 5B) promoter variant rs35705950 was significantly associated with both ILAs (P = 2.6 × 10-27) and subpleural ILAs (P = 1.6 × 10-29). We discovered novel genome-wide associations near IPO11 (rs6886640, P = 3.8 × 10-8) and FCF1P3 (rs73199442, P = 4.8 × 10-8) with ILAs, and near HTRE1 (rs7744971, P = 4.2 × 10-8) with subpleural-predominant ILAs. These novel associations were not associated with IPF. Among 12 previously reported IPF GWAS loci, five (DPP9, DSP, FAM13A, IVD, and MUC5B) were significantly associated (P < 0.05/12) with ILAs.Conclusions: In a GWAS of ILAs in six studies, we confirmed the association with a MUC5B promoter variant and found strong evidence for an effect of previously described IPF loci; however, novel ILA associations were not associated with IPF. These findings highlight common genetically driven biologic pathways between ILAs and IPF, and also suggest distinct ones

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

Molecular signatures of idiopathic pulmonary fibrosis.

Molecular patterns and pathways in idiopathic pulmonary fibrosis (IPF) have been extensively investigated but few studies have assimilated multi-omic platforms to provide an integrative understanding of molecular patterns that are relevant in IPF. Herein, we combine coding and non-coding transcriptome, DNA methylome, and proteome from IPF and healthy lung tissue to identify molecules and pathways associated with this disease. RNA sequencing, Illumina MethylationEPIC array, and liquid chromatography-mass spectrometry (LC-MS) proteomic data were collected on lung tissue from 24 IPF cases and 14 control subjects. Significant differential features were identified using linear models adjusting for age and sex, inflation and bias where appropriate. Data Integration Analysis for Biomarker discovery using a Latent component method for Omics studies (DIABLO) was used for integrative multi-omic analysis. We identified 4,643 differentially expressed transcripts aligning to 3,439 genes, 998 differentially abundant proteins, 2,500 differentially methylated regions (DMRs), and 1,269 differentially expressed lncRNAs that were significant after correcting for multiple tests (false discovery rate [FDR]&lt;0.05). Unsupervised hierarchical clustering using 20 coding mRNA, protein, methylation, and lncRNA features with highest loadings on the top latent variable from the four datasets demonstrates perfect separation of IPF and control lungs. Our analysis confirmed previously validated molecules and pathways known to be dysregulated in disease, and implicated novel molecular features as potential drivers and modifiers of disease. For example, four proteins, 18 DMRs, and 10 lncRNAs were found to have strong correlations (r&gt;0.8) with MMP7. Therefore, using a systems biology approach, we have identified novel molecular relationships in IPF

Investigation of the vitamin D receptor gene (VDR) and its interaction with protein tyrosine phosphatase, non-receptor type 2 gene (PTPN2) on risk of islet autoimmunity and type 1 diabetes:The Diabetes Autoimmunity Study in the Young (DAISY)

<p>The present study investigated the association between variants in the vitamin D receptor gene (VDR) and protein tyrosine phosphatase, non-receptor type 2 gene (PTPN2), as well as an interaction between VDR and PTPN2 and the risk of islet autoimmunity (IA) and progression to type 1 diabetes (T1D). The Diabetes Autoimmunity Study in the Young (DAISY) has followed children at increased risk of T1D since 1993. Of the 1692 DAISY children genotyped for VDR rs1544410, VDR rs2228570, VDR rs11568820, PTPN2 rs1893217, and PTPN2 rs478582, 111 developed IA, defined as positivity for GAD, insulin or IA-2 autoantibodies on 2 or more consecutive visits, and 38 IA positive children progressed to T1D. Proportional hazards regression analyses were conducted.</p><p>There was no association between IA development and any of the gene variants, nor was there evidence of a VDR*PTPN2 interaction. Progression to T1D in IA positive children was associated with the VDR rs2228570 GG genotype (HR: 0.49, 95% Cl: 0.26-0.92) and there was an interaction between VDR rs1544410 and PTPN2 rs1893217 (p(interaction) = 0.02). In children with the PTPN2 rs1893217 AA genotype, the VDR rs1544410 AA/AG genotype was associated with a decreased risk of T1D (HR: 0.24, 95% CI: 0.11-0.53, p = 0.0004), while in children with the PTPN2 rs1893217 GG/GA genotype, the VDR rs1544410 AA/AG genotype was not associated with T1D (HR: 1.32,95% CI: 0.43-4.06, p = 0.62). These findings should be replicated in larger cohorts for confirmation. The interaction between VDR and PTPN2 polymorphisms in the risk of progression to T1D offers insight concerning the role of vitamin D in the etiology of T1D. (C) 2012 Elsevier Ltd. All rights reserved.</p>

An Update on the Global Idiopathic Pulmonary Fibrosis (IPF) Collaborative Network: A Platform for IPF Genetics

American Thoracic Society International Conference Abstracts > C72. PULMONARY FIBROSIS: MECHANISMS AND MODEL

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

10.1186/s12864-015-2192-yBMC Genomics161110