Biology subjects

Fingerlin, T. E.

Publications and source records attributed to Fingerlin, T. E..

3 recordsLinked to original sources

bioRxiv2020

Identification of Influential Variants in Significant Aggregate Rare Variant Tests

IntroductionStudies that examine the role of rare variants in both simple and complex disease are increasingly common. Though the usual approach of testing rare variants in aggregate sets is more powerful than testing individual variants, it is of interest to identify the variants that are plausible drivers of the association. We present a novel method for prioritization of rare variants after a significant aggregate test by quantifying the influence of the variant on the aggregate test of association. MethodsIn addition to providing a measure used to rank variants, we use outlier detection methods to present the computationally efficient Rare Variant Influential Filtering Tool (RIFT) to identify a subset of variants that influence the disease association. We evaluated several outlier detection methods that vary based on the underlying variance measure: interquartile range (Tukey fences), median absolute deviation and standard deviation. We performed 1000 simulations for 50 regions of size 3kb and compared the true and false positive rates. We compared RIFT using the Inner Tukey to two existing methods: adaptive combination of p-values (ADA) and a Bayesian hierarchical model (BeviMed). Finally, we applied this method to data from our targeted resequencing study in idiopathic pulmonary fibrosis (IPF). ResultsAll outlier detection methods observed higher sensitivity to detect uncommon variants (0.001 < MAF > 0.03) compared to very rare variants (MAF < 0.001). For uncommon variants, RIFT had a lower median false positive rate compared to the ADA. ADA and RIFT had significantly higher true positive rates than that observed for BeviMed. When applied to two regions found previously associated with IPF including 100 rare variants, we identified six polymorphisms with the greatest evidence for influencing the association with IPF. DiscussionIn summary, RIFT has a high true positive rate while maintaining a low false positive rate for identifying polymorphisms influencing rare variant association tests. This work provides an approach to obtain greater resolution of the rare variant signals within significant aggregate sets; this information can provide an objective measure to prioritize variants for follow-up experimental studies and insight into the biological pathways involved.

genetics↗

bioRxiv2019

Genome-wide association study of susceptibility to idiopathic pulmonary fibrosis

RationaleIdiopathic pulmonary fibrosis (IPF) is a complex lung disease characterised by scarring of the lung that is believed to result from an atypical response to injury of the epithelium. The mechanisms by which this arises are poorly understood and it is likely that multiple pathways are involved. The strongest genetic association with IPF is a variant in the promoter of MUC5B where each copy of the risk allele confers a five-fold risk of disease. However, genome-wide association studies have reported additional signals of association implicating multiple pathways including host defence, telomere maintenance, signalling and cell-cell adhesion.\n\nObjectivesTo improve our understanding of mechanisms that increase IPF susceptibility by identifying previously unreported genetic associations.\n\nMethods and measurementsWe performed the largest genome-wide association study undertaken for IPF susceptibility with a discovery stage comprising up to 2,668 IPF cases and 8,591 controls with replication in an additional 1,467 IPF cases and 11,874 controls. Polygenic risk scores were used to assess the collective effect of variants not reported as associated with IPF.\n\nMain resultsWe identified and replicated three new genome-wide significant (P<5x10-8) signals of association with IPF susceptibility (near KIF15, MAD1L1 and DEPTOR) and confirm associations at 11 previously reported loci. Polygenic risk score analyses showed that the combined effect of many thousands of as-yet unreported IPF risk variants contribute to IPF susceptibility.\n\nConclusionsNovel association signals support the importance of mTOR signalling in lung fibrosis and suggest a possible role of mitotic spindle-assembly genes in IPF susceptibility.

genomics↗

bioRxiv2018

Expanded genetic landscape of chronic obstructive pulmonary disease reveals heterogeneous cell type and phenotype associations

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide novel insights into disease pathogenesis. To broaden COPD genetic risk loci discovery and identify cell type and phenotype associations we performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci with P value < 5x10-8; 47 were previously described in association with either COPD or population-based lung function. Of the remaining 35 novel loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified enrichment for loci in lung tissue, smooth muscle and alveolar type II cells. We found 9 shared genomic regions between COPD and asthma and 5 between COPD and pulmonary fibrosis. COPD genetic risk loci clustered into groups of quantitative imaging features and comorbidity associations. Our analyses provide further support to the genetic susceptibility and heterogeneity of COPD.

genetics↗