Kathleen C. Barnes

Future Research Directions in Asthma. An NHLBI Working Group Report

Asthma is a common chronic disease without cure. Our understanding of asthma onset, pathobiology, classification, and management has evolved substantially over the past decade; however, significant asthma-related morbidity and excess healthcare use and costs persist. To address this important clinical condition, the NHLBI convened a group of extramural investigators for an Asthma Research Strategic Planning workshop on September 18-19, 2014, to accelerate discoveries and their translation to patients. The workshop focused on (1) in utero and early-life origins of asthma, (2) the use of phenotypes and endotypes to classify disease, (3) defining disease modification, (4) disease management, and (5) implementation research. This report summarizes the workshop and produces recommendations to guide future research in asthma.

Analysis of CD4+ T-cell gene expression in allergic subjects using two different microarray platforms

Background:u2002 Allergic diseases are thought to involve dysregulated activation of T cells including CD4+ lymphocytes. T‐cell activation results in changes in gene expression, but the optimal method to study gene expression profiles in T cells, and how this changes over time, are not known.

Short communication: Analysis of CD4+ T‐cell gene expression in allergic subjects using two different microarray platforms

Background:u2002 Allergic diseases are thought to involve dysregulated activation of T cells including CD4+ lymphocytes. T‐cell activation results in changes in gene expression, but the optimal method to study gene expression profiles in T cells, and how this changes over time, are not known.

Challenges and disparities in the application of personalized genomic medicine to populations with African ancestry.

To characterize the extent and impact of ancestry-related biases in precision genomic medicine, we use 642 whole-genome sequences from the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) project to evaluate typical filters and databases. We find significant correlations between estimated African ancestry proportions and the number of variants per individual in all variant classification sets but one. The source of these correlations is highlighted in more detail by looking at the interaction between filtering criteria and the ClinVar and Human Gene Mutation databases. ClinVars correlation, representing African ancestry-related bias, has changed over time amidst monthly updates, with the most extreme switch happening between March and April of 2014 (r=0.733 to r=−0.683). We identify 68 SNPs as the major drivers of this change in correlation. As long as ancestry-related bias when using these clinical databases is minimally recognized, the genetics community will face challenges with implementation, interpretation and cost-effectiveness when treating minority populations.

Do COPD subtypes really exist? COPD heterogeneity and clustering in 10 independent cohorts

Background COPD is a heterogeneous disease, but there is little consensus on specific definitions for COPD subtypes. Unsupervised clustering offers the promise of ‘unbiased’ data-driven assessment of COPD heterogeneity. Multiple groups have identified COPD subtypes using cluster analysis, but there has been no systematic assessment of the reproducibility of these subtypes. Objective We performed clustering analyses across 10 cohorts in North America and Europe in order to assess the reproducibility of (1) correlation patterns of key COPD-related clinical characteristics and (2) clustering results. Methods We studied 17u2009146 individuals with COPD using identical methods and common COPD-related characteristics across cohorts (FEV1, FEV1/FVC, FVC, body mass index, Modified Medical Research Council score, asthma and cardiovascular comorbid disease). Correlation patterns between these clinical characteristics were assessed by principal components analysis (PCA). Cluster analysis was performed using k-medoids and hierarchical clustering, and concordance of clustering solutions was quantified with normalised mutual information (NMI), a metric that ranges from 0 to 1 with higher values indicating greater concordance. Results The reproducibility of COPD clustering subtypes across studies was modest (median NMI range 0.17–0.43). For methods that excluded individuals that did not clearly belong to any cluster, agreement was better but still suboptimal (median NMI range 0.32–0.60). Continuous representations of COPD clinical characteristics derived from PCA were much more consistent across studies. Conclusions Identical clustering analyses across multiple COPD cohorts showed modest reproducibility. COPD heterogeneity is better characterised by continuous disease traits coexisting in varying degrees within the same individual, rather than by mutually exclusive COPD subtypes.

Genetic variants affecting cross-sectional lung function in adults show little or no effect on longitudinal lung function decline

Background Genome-wide association studies have identified numerous genetic regions that influence cross-sectional lung function. Longitudinal decline in lung function also includes a heritable component but the genetic determinants have yet to be defined. Objectives We aimed to determine whether regions associated with cross-sectional lung function were also associated with longitudinal decline and to seek novel variants which influence decline. Methods We analysed genome-wide data from 4167 individuals from the Busselton Health Study cohort, who had undergone spirometry (12u2005695 observations across eight time points). A mixed model was fitted and weighted risk scores were calculated for the joint effect of 26 known regions on baseline and longitudinal changes in FEV1 and FEV1/FVC. Potential additional regions of interest were identified and followed up in two independent cohorts. Results The 26 regions previously associated with cross-sectional lung function jointly showed a strong effect on baseline lung function (p=4.44×10−16 for FEV1/FVC) but no effect on longitudinal decline (p=0.160 for FEV1/FVC). This was replicated in an independent cohort. 39 additional regions of interest (48 variants) were identified; these associations were not replicated in two further cohorts. Conclusions Previously identified genetic variants jointly have a strong effect on cross-sectional lung function in adults but little or no effect on the rate of decline of lung function. It is possible that they influence COPD risk through lung development. Although no genetic variants have yet been associated with lung function decline at stringent genome-wide significance, longitudinal change in lung function is heritable suggesting that there is scope for future discoveries.

Surfactant protein D is a causal risk factor for COPD: results of Mendelian randomisation

Surfactant protein D (SP-D) is produced primarily in the lung and is involved in regulating pulmonary surfactants, lipid homeostasis and innate immunity. Circulating SP-D levels in blood are associated with chronic obstructive pulmonary disease (COPD), although causality remains elusive. In 4061 subjects with COPD, we identified genetic variants associated with serum SP-D levels. We then determined whether these variants affected lung tissue gene expression in 1037 individuals. A Mendelian randomisation framework was then applied, whereby serum SP-D-associated variants were tested for association with COPD risk in 11u200a157 cases and 36u200a699 controls and with 11u2005years decline of lung function in the 4061 individuals. Three regions on chromosomes 6 (human leukocyte antigen region), 10 (SFTPD gene) and 16 (ATP2C2 gene) were associated with serum SP-D levels at genome-wide significance. In Mendelian randomisation analyses, variants associated with increased serum SP-D levels decreased the risk of COPD (estimate −0.19, p=6.46×10−03) and slowed the lung function decline (estimate=0.0038, p=7.68×10−3). Leveraging genetic variation effect on protein, lung gene expression and disease phenotypes provided novel insights into SP-D biology and established a causal link between increased SP-D levels and protection against COPD risk and progression. SP-D represents a very promising biomarker and therapeutic target for COPD. Surfactant protein D is a causal risk factor for COPD http://ow.ly/n1OG30eUQlf

The genetics of smoking in individuals with chronic obstructive pulmonary disease

BackgroundSmoking is the principal modifiable environmental risk factor for chronic obstructive pulmonary disease (COPD) which affects 300 million people and is the 3rd leading cause of death worldwide. Most of the genetic studies of smoking have relied on self-reported smoking status which is vulnerable to reporting and recall bias. Using data from the Lung Health Study (LHS), we sought to identify genetic variants associated with quantitative smoking and cessation in individuals with mild to moderate COPD.MethodsThe LHS is a longitudinal multicenter study of mild-to-moderate COPD subjects who were all smokers at recruitment. We performed genome-wide association studies (GWASs) for salivary cotinine (nu2009=u20094024), exhaled carbon monoxide (eCO) (nu2009=u20092854), cigarettes per day (CPD) (nu2009=u20092706) and smoking cessation at year 5 follow-up (nu2009=u2009717 quitters and 2175 smokers). The GWAS analyses were adjusted for age, gender, and genetic principal components.ResultsFor cotinine levels, SNPs near UGT2B10 gene achieved genome-wide significance (i.e. Pu2009<u20095u2009×u200910−u20098) with top SNP rs10023464, Pu2009=u20091.27u2009×u200910−u200911. For eCO levels, one significant SNP was identified which mapped to the CHRNA3 gene (rs12914385, Pu2009=u20092.38u2009×u200910−u20098). A borderline region mapping to KCNMA1 gene was associated with smoking cessation (rs207675, Pu2009=u20095.95u2009×u200910−u20098). Of the identified loci, only the CHRNA3/5 locus showed significant associations with lung function but only in heavy smokers. No regions met genome-wide significance for CPD.ConclusionThe study demonstrates that using objective measures of smoking such as eCO and/or salivary cotinine can more precisely capture the genetic contribution to multiple aspects of smoking behaviour. The KCNMA1 gene association with smoking cessation may represent a potential therapeutic target and warrants further studies.Trial registrationThe Lung Health Study ClinicalTrials.gov Identifier: NCT00000568. Date of registration: October 28, 1999.

Gene Coexpression Networks in Whole Blood Implicate Multiple Interrelated Molecular Pathways in Obesity in People with Asthma: Blood Gene Coexpression Networks of Asthma with Obesity

Asthmatic children who develop obesity through adolescence have poorer disease outcomes compared with those who do not. This study aimed to characterize the biology of childhood asthma complicated by adult obesity.

Optimized distributed systems achieve significant performance improvement on sorted merging of massive VCF files

Abstract Background Sorted merging of genomic data is a common data operation necessary in many sequencing-based studies. It involves sorting and merging genomic data from different subjects by their genomic locations. In particular, merging a large number of variant call format (VCF) files is frequently required in large-scale whole-genome sequencing or whole-exome sequencing projects. Traditional single-machine based methods become increasingly inefficient when processing large numbers of files due to the excessive computation time and Input/Output bottleneck. Distributed systems and more recent cloud-based systems offer an attractive solution. However, carefully designed and optimized workflow patterns and execution plans (schemas) are required to take full advantage of the increased computing power while overcoming bottlenecks to achieve high performance. Findings In this study, we custom-design optimized schemas for three Apache big data platforms, Hadoop (MapReduce), HBase, and Spark, to perform sorted merging of a large number of VCF files. These schemas all adopt the divide-and-conquer strategy to split the merging job into sequential phases/stages consisting of subtasks that are conquered in an ordered, parallel, and bottleneck-free way. In two illustrating examples, we test the performance of our schemas on merging multiple VCF files into either a single TPED or a single VCF file, which are benchmarked with the traditional single/parallel multiway-merge methods, message passing interface (MPI)–based high-performance computing (HPC) implementation, and the popular VCFTools. Conclusions Our experiments suggest all three schemas either deliver a significant improvement in efficiency or render much better strong and weak scalabilities over traditional methods. Our findings provide generalized scalable schemas for performing sorted merging on genetics and genomics data using these Apache distributed systems.