Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent patient populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never-smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD.

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide(1). We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 x 10(-6)) in 9,498 cases and 9,748 controls. In the combined meta-analysis, we identified 22 loci associated at genome-wide significance, including 13 new associations with COPD. Nine of these 13 loci have been associated with lung function in general population samples(2-7), while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis(8,9) (FAM13A and DSP) but that had opposite risk alleles for COPD. None of our loci overlapped with genome-wide associations for asthma, although one locus has been implicated in joint susceptibility to asthma and obesity(10). We also identified genetic correlation between COPD and asthma. Our findings highlight new loci associated with COPD, demonstrate the importance of specific loci associated with lung function to COPD, and identify potential regions of genetic overlap between COPD and other respiratory diseases

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide novel insights into disease pathogenesis. 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 < 5 × 10 −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 several lung cell types. We found 14 COPD loci shared with either asthma or 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.

Understanding and correctly utilizing relatedness among samples is essential for genetic analysis; however, managing sample records and pedigrees can often be error prone and incomplete. Data sets ascertained by random sampling often harbor cryptic relatedness that can be leveraged in genetic analyses for maximizing power. We have developed a method that uses genome-wide estimates of pairwise identity by descent to identify families and quickly reconstruct and score all possible pedigrees that fit the genetic data by using up to third-degree relatives, and we have included it in the software package PRIMUS (Pedigree Reconstruction and Identification of the Maximally Unrelated Set). Here, we validate its performance on simulated, clinical, and HapMap pedigrees. Among these samples, we demonstrate that PRIMUS can verify reported pedigree structures and identify cryptic relationships. Finally, we show that PRIMUS reconstructed pedigrees, all of which were previously unknown, for 203 families from a cohort collected in Starr County, TX (1,890 samples).

Electron concentration profiles have been obtained for Al x Ga 1Ϫx N/GaN heterostructure field-effect transistor structures. Analysis of the measured electron distributions demonstrates the influence of piezoelectric effects in coherently strained layers on III-V nitride heterostructure device characteristics. Characterization of a nominally undoped Al 0.15 Ga 0.85 N/GaN transistor structure reveals the presence of a high sheet carrier density in the GaN channel which may be explained as a consequence of piezoelectrically induced charges present at the Al 0.15 Ga 0.85 N/GaN interface. Measurements performed on an Al 0.15 Ga 0.85 N/GaN transistor structure with a buried Al 0.15 Ga 0.85 N isolation layer indicate a reduction in electron sheet concentration in the transistor channel and accumulation of carriers below the Al 0.15 Ga 0.85 N isolation layer, both of which are attributable to piezoelectric effects.

Primary spontaneous pneumothorax (PSP) is a common manifestation of Birt-Hogg-Dubé syndrome caused by folliculin gene (FLCN) mutation, which is also found in isolated familial PSP cases. A complete genetic analysis of FLCN was performed in 102 unrelated Chinese patients with isolated PSP and 21 of their family members. Three novel mutations (c.924_926del, c.1611_1631del and c.1740C>T) and a previously reported mutation (c.1733insC) were identified in five familial and five sporadic PSP patients. Of the 21 family members of patients with PSP including 3 previous considered as sporadic, 4 (19%) had history of at least one episode of PSP and 9 (43%) were FLCN mutant carriers without PSP. Seven of the nine (78%) mutant carriers had pulmonary cysts detected by high-resolution computed tomography (HRCT). Although c.924_926del and c.1611_1631del were found in eight patients from the same geographic district, haplotype analysis demonstrated that they did not share the same affected haplotype, thus excluding common ancestry. This study first demonstrates that FLCN mutation contributes to not only familial but also 'apparently sporadic' patients with isolated PSP. It suggests that mutation analysis and HRCT scan may be recommended for first-degree family members of PSP patients with FLCN mutations, irrespective of their family history status of PSP.

Background Prognostic tools are required to guide clinical decision-making in COVID-19. Methods We studied the relationship between the ratio of interleukin (IL)-6 to IL-10 and clinical outcome in 80 patients hospitalized for COVID-19, and created a simple 5-point linear score predictor of clinical outcome, the Dublin-Boston score. Clinical outcome was analysed as a three-level ordinal variable (“Improved”, “Unchanged”, or “Declined”). For both IL-6:IL-10 ratio and IL-6 alone, we associated clinical outcome with a) baseline biomarker levels, b) change in biomarker level from day 0 to day 2, c) change in biomarker from day 0 to day 4, and d) slope of biomarker change throughout the study. The associations between ordinal clinical outcome and each of the different predictors were performed with proportional odds logistic regression. Associations were run both “unadjusted” and adjusted for age and sex. Nested cross-validation was used to identify the model for incorporation into the Dublin-Boston score. Findings The 4-day change in IL-6:IL-10 ratio was chosen to derive the Dublin-Boston score. Each 1 point increase in the score was associated with a 5.6 times increased odds for a more severe outcome (OR 5.62, 95% CI -3.22–9.81, P = 1.2 × 10 −9 ). Both the Dublin-Boston score and the 4-day change in IL-6:IL-10 significantly outperformed IL-6 alone in predicting clinical outcome at day 7. Interpretation The Dublin-Boston score is easily calculated and can be applied to a spectrum of hospitalized COVID-19 patients. More informed prognosis could help determine when to escalate care, institute or remove mechanical ventilation, or drive considerations for therapies. Funding Funding was received from the Elaine Galwey Research Fellowship, American Thoracic Society, National Institutes of Health and the Parker B Francis Research Opportunity Award.

The CREATE-ECLA Randomized Controlled TrialThe CREATE-ECLA Trial Group Investigators* See also pp 427 and 489.