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Risk of chronic obstructive pulmonary disease (COPD) is determined by both cigarette smoking and genetic susceptibility, but little is known about gene-by-smoking interactions. We performed a genome-wide association analysis of 179,689 controls and 21,077 COPD cases from UK Biobank subjects of European ancestry recruited from 2006 to 2010, considering genetic main effects and gene-by-smoking interaction effects simultaneously (2-degrees-of-freedom (df) test) as well as interaction effects alone (1-df interaction test). We sought to replicate significant results in COPDGene (United States, 2008–2010) and SpiroMeta Consortium (multiple countries, 1947–2015) data. We considered 2 smoking variables: 1) ever/never and 2) current/noncurrent. In the 1-df test, we identified 1 genome-wide significant locus on 15q25.1 (cholinergic receptor nicotinic β4 subunit, or CHRNB4) for ever- and current smoking and identified PI*Z allele (rs28929474) of serpin family A member 1 (SERPINA1) for ever-smoking and 3q26.2 (MDS1 and EVI1 complex locus, or MECOM) for current smoking in an analysis of previously reported COPD loci. In the 2-df test, most of the significant signals were also significant for genetic marginal effects, aside from 16q22.1 (sphingomyelin phosphodiesterase 3, or SMPD3) and 19q13.2 (Egl-9 family hypoxia inducible factor 2, or EGLN2). The significant effects at 15q25.1 and 19q13.2 loci, both previously described in prior genome-wide association studies of COPD or smoking, were replicated in COPDGene and SpiroMeta. We identified interaction effects at previously reported COPD loci; however, we failed to identify novel susceptibility loci.

SUMMARY To quantify polygenic effects, i.e. undetected genetic effects, in large-scale association studies, we propose a generalized estimating equation (GEE) based estimation framework. We develop a marginal model for single-variant association test statistics of complex diseases that generalizes existing approaches such as LD Score regression and that is applicable to population-based designs, to family-based designs or to arbitrary combinations of both. We extend the standard GEE approach so that the parameters of the proposed marginal model can be estimated based on working-correlation/linkage-disequilibrium (LD) matrices from external reference panels. Our method achieves substantial efficiency gains over standard approaches, while it is robust against misspecification of the LD structure, i.e. the LD structure of the reference panel can differ substantially from the true LD structure in the study population. In simulation studies and in applications to population-based and family-based studies, we illustrate the features of the proposed GEE framework. Our results suggest that our approach can be up to 100% more efficient than existing methodology.

Motivation: For the analysis of rare variants in sequence data, numerous approaches have been suggested. Fixed and flexible threshold approaches collapse the rare variant information of a genomic region into a test statistic with reduced dimensionality. Alternatively, the rare variant information can be combined in statistical frameworks that are based on suitable regression models, machine learning, etc. Although the existing approaches provide powerful tests that can incorporate information on allele frequencies and prior biological knowledge, differences in the spatial clustering of rare variants between cases and controls cannot be incorporated. Based on the assumption that deleterious variants and protective variants cluster or occur in different parts of the genomic region of interest, we propose a testing strategy for rare variants that builds on spatial cluster methodology and that guides the identification of the biological relevant segments of the region. Our approach does not require any assumption about the directions of the genetic effects. Results: In simulation studies, we assess the power of the clustering approach and compare it with existing methodology. Our simulation results suggest that the clustering approach for rare variants is well powered, even in situations that are ideal for standard methods. The efficiency of our spatial clustering approach is not affected by the presence of rare variants that have opposite effect size directions. An application to a sequencing study for non-syndromic cleft lip with or without cleft palate (NSCL/P) demonstrates its practical relevance. The proposed testing strategy is applied to a genomic region on chromosome 15q13.3 that was implicated in NSCL/P etiology in a previous genome-wide association study, and its results are compared with standard approaches. Availability: Source code and documentation for the implementation in R will be provided online. Currently, the R-implementation only supports genotype data. We currently are working on an extension for VCF files. Contact: moc.liamelgoog@reif.edieh

A generic hexadeoxyribonucleotide microchip has been applied to test the DNA-binding properties of HU histone-like bacterial protein, which is known to have a low sequence specificity. All 4096 hexamers flanked within 8mers by degenerate bases at both the 3′- and 5′-ends were immobilized within the 100 × 100 × 20 mm polyacrylamide gel pads of the microchip. Single-stranded immobilized oligonucleotides were converted in some experiments to the double-stranded form by hybridization with a specified mixture of 8mers. The DNA interaction with HU was characterized by three type of measurements: (i) binding of FITC-labeled HU to microchip oligonucleotides; (ii) melting curves of complexes of labeled HU with single-stranded microchip oligonucleotides; (iii) the effect of HU binding on melting curves of microchip double-stranded DNA labeled with another fluorescent dye, Texas Red. Large numbers of measurements of these parameters were carried out in parallel for all or many generic microchip elements in real time with a multi-wavelength fluorescence microscope. Statistical analysis of these data suggests some preference for HU binding to G/C-rich single-stranded oligonucleotides. HU complexes with double-stranded microchip 8mers can be divided into two groups in which HU binding either increased the melting temperature (Tm) of duplexes or decreased it. The stabilized duplexes showed some preference for presence of the sequence motifs AAG, AGA and AAGA. In the second type of complex, enriched with A/T base pairs, the destabilization effect was higher for longer stretches of A/T duplexes. Binding of HU to labeled duplexes in the second type of complex caused some decrease in fluorescence. This decrease also correlates with the higher A/T content and lower Tm. The results demonstrate that generic microchips could be an efficient approach in analysis of sequence specificity of proteins.