Kayleen Williams

Evidence suggests that lung injury, inflammation and extracellular matrix remodelling precede lung fibrosis in interstitial lung disease (ILD). We examined whether a quantitative measure of increased lung attenuation on computed tomography (CT) detects lung injury, inflammation and extracellular matrix remodelling in community-dwelling adults sampled without regard to respiratory symptoms or smoking.We measured high attenuation areas (HAA; percentage of lung voxels between -600 and -250 Hounsfield Units) on cardiac CT scans of adults enrolled in the Multi-Ethnic Study of Atherosclerosis.HAA was associated with higher serum matrix metalloproteinase-7 (mean adjusted difference 6.3% per HAA doubling, 95% CI 1.3-11.5), higher interleukin-6 (mean adjusted difference 8.8%, 95% CI 4.8-13.0), lower forced vital capacity (FVC) (mean adjusted difference -82 mL, 95% CI -119--44), lower 6-min walk distance (mean adjusted difference -40 m, 95% CI -1--80), higher odds of interstitial lung abnormalities at 9.5 years (adjusted OR 1.95, 95% CI 1.43-2.65), and higher all cause-mortality rate over 12.2 years (HR 1.58, 95% CI 1.39-1.79).High attenuation areas are associated with biomarkers of inflammation and extracellular matrix remodelling, reduced lung function, interstitial lung abnormalities, and a higher risk of death among community-dwelling adults.

Genome-wide association studies (GWAS) have emerged as powerful means for identifying genetic loci related to complex diseases. However, the role of environment and its potential to interact with key loci has not been adequately addressed in most GWAS. Networks of collaborative studies involving different study populations and multiple phenotypes provide a powerful approach for addressing the challenges in analysis and interpretation shared across studies. The Gene, Environment Association Studies (GENEVA) consortium was initiated to: identify genetic variants related to complex diseases; identify variations in gene-trait associations related to environmental exposures; and ensure rapid sharing of data through the database of Genotypes and Phenotypes. GENEVA consists of several academic institutions, including a coordinating center, two genotyping centers and 14 independently designed studies of various phenotypes, as well as several Institutes and Centers of the National Institutes of Health led by the National Human Genome Research Institute. Minimum detectable effect sizes include relative risks ranging from 1.24 to 1.57 and proportions of variance explained ranging from 0.0097 to 0.02. Given the large number of research participants (N>80,000), an important feature of GENEVA is harmonization of common variables, which allow analyses of additional traits. Environmental exposure information available from most studies also enables testing of gene-environment interactions. Facilitated by its sizeable infrastructure for promoting collaboration, GENEVA has established a unified framework for genotyping, data quality control, analysis and interpretation. By maximizing knowledge obtained through collaborative GWAS incorporating environmental exposure information, GENEVA aims to enhance our understanding of disease etiology, potentially identifying opportunities for intervention.

We studied whether ambient air pollution is associated with interstitial lung abnormalities (ILAs) and high attenuation areas (HAAs), which are qualitative and quantitative measurements of subclinical interstitial lung disease (ILD) on computed tomography (CT). We performed analyses of community-based dwellers enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) study. We used cohort-specific spatio-temporal models to estimate ambient pollution (fine particulate matter (PM 2.5 ), nitrogen oxides (NO x ), nitrogen dioxide (NO 2 ) and ozone (O 3 )) at each home. A total of 5495 participants underwent serial assessment of HAAs by cardiac CT; 2671 participants were assessed for ILAs using full lung CT at the 10-year follow-up. We used multivariable logistic regression and linear mixed models adjusted for age, sex, ethnicity, education, tobacco use, scanner technology and study site. The odds of ILAs increased 1.77-fold per 40 ppb increment in NO x (95% CI 1.06 to 2.95, p = 0.03). There was an overall trend towards an association between higher exposure to NO x and greater progression of HAAs (0.45% annual increase in HAAs per 40 ppb increment in NO x ; 95% CI −0.02 to 0.92, p = 0.06). Associations of ambient fine particulate matter (PM 2.5 ), NO x and NO 2 concentrations with progression of HAAs varied by race/ethnicity (p = 0.002, 0.007, 0.04, respectively, for interaction) and were strongest among non-Hispanic white people. We conclude that ambient air pollution exposures were associated with subclinical ILD.

Using ~60,000 SNPs selected for minimal linkage disequilibrium, we perform population structure analysis of 1,374 unrelated Hispanic individuals from the Multi-Ethnic Study of Atherosclerosis (MESA), with self-identification corresponding to Central America (n = 93), Cuba (n = 50), the Dominican Republic (n = 203), Mexico (n = 708), Puerto Rico (n = 192), and South America (n = 111). By projection of principal components (PCs) of ancestry to samples from the HapMap phase III and the Human Genome Diversity Panel (HGDP), we show the first two PCs quantify the Caucasian, African, and Native American origins, while the third and fourth PCs bring out an axis that aligns with known South-to-North geographic location of HGDP Native American samples and further separates MESA Mexican versus Central/South American samples along the same axis. Using k-means clustering computed from the first four PCs, we define four subgroups of the MESA Hispanic cohort that show close agreement with self-identification, labeling the clusters as primarily Dominican/Cuban, Mexican, Central/South American, and Puerto Rican. To demonstrate our recommendations for genetic analysis in the MESA Hispanic cohort, we present pooled and stratified association analysis of triglycerides for selected SNPs in the LPL and TRIB1 gene regions, previously reported in GWAS of triglycerides in Caucasians but as yet unconfirmed in Hispanic populations. We report statistically significant evidence for genetic association in both genes, and we further demonstrate the importance of considering population substructure and genetic heterogeneity in genetic association studies performed in the United States Hispanic population.