Colocalization analysis of 3' UTR alternative polyadenylation quantitative trait loci reveals novel mechanisms underlying associations with lung function.

While many disease-associated single nucleotide polymorphisms (SNPs) are expression quantitative trait loci (eQTLs), a large proportion of genome-wide association study (GWAS) variants are of unknown function. Alternative polyadenylation (APA) plays an important role in posttranscriptional regulation by allowing genes to shorten or extend 3' untranslated regions (UTRs). We hypothesized that genetic variants that affect APA in lung tissue may lend insight into the function of respiratory associated GWAS loci. We generated alternative polyadenylation (apa) QTLs using RNA sequencing and whole genome sequencing on 1241 subjects from the Lung Tissue Research Consortium (LTRC) as part of the NHLBI TOPMed project. We identified 56 179 APA sites corresponding to 13 582 unique genes after filtering out APA sites with low usage. We found that a total of 8831 APA sites were associated with at least one SNP with q-value < 0.05. The genomic distribution of lead APA SNPs indicated that the majority are intronic variants (33%), followed by downstream gene variants (26%), 3' UTR variants (17%), and upstream gene variants (within 1 kb region upstream of transcriptional start site, 10%). APA sites in 193 genes colocalized with GWAS data for at least one phenotype. Genes containing the top APA sites associated with GWAS variants include membrane associated ring-CH-type finger 2 (MARCHF2), nectin cell adhesion molecule 2 (NECTIN2), and butyrophilin subfamily 3 member A2 (BTN3A2). Overall, these findings suggest that APA may be an important mechanism for genetic variants in lung function and chronic obstructive pulmonary disease (COPD).

A novel piwi-interacting RNA associates with type 2-high asthma phenotypes.

BACKGROUND: Piwi-interacting RNAs (piRNAs), comprising the largest noncoding RNA group, regulate transcriptional processes. Whether piRNAs are associated with type 2 (T2)-high asthma is unknown. OBJECTIVE: We sought to investigate the association between piRNAs and T2-high asthma in childhood asthma. METHODS: We sequenced plasma samples from 462 subjects in the Childhood Asthma Management Program (CAMP) as the discovery cohort and 1165 subjects in the Genetics of Asthma in Costa Rica Study (GACRS) as a replication cohort. Sequencing reads were filtered first, and piRNA reads were annotated and normalized. Linear regression was used for the association analysis of piRNAs and peripheral blood eosinophil count, total serum IgE level, and long-term asthma exacerbation in children with asthma. Mediation analysis was performed to investigate the effect direction. We then ascertained if the circulating piRNAs were present in asthmatic airway epithelial cells in a Gene Expression Omnibus (GEO; www.ncbi.nlm.nih.gov/geo) public data set. RESULTS: Fifteen piRNAs were significantly associated with eosinophil count in CAMP (P ≤ .05), and 3 were successfully replicated in GACRS. Eleven piRNAs were associated with total IgE in CAMP, and one of these was replicated in GACRS. All 22 significant piRNAs were identified in epithelial cells in vitro, and 6 of these were differentially expressed between subjects with asthma and healthy controls. Fourteen piRNAs were associated with long-term asthma exacerbation, and effect of piRNAs on long-term asthma exacerbation are mediated through eosinophil count and serum IgE level. CONCLUSION: piRNAs are associated with peripheral blood eosinophils and total serum IgE in childhood asthma and may play important roles in T2-high asthma.

Lung function, airway and peripheral basophils and eosinophils are associated with molecular pharmacogenomic endotypes of steroid response in severe asthma.

INTRODUCTION: Asthma is a complex disease with heterogeneous expression/severity. There is growing interest in defining asthma endotypes consistently associated with different responses to therapy, focusing on type 2 inflammation (Th2) as a key pathological mechanism. Current asthma endotypes are defined primarily by clinical/laboratory criteria. Each endotype is likely characterised by distinct molecular mechanisms that identify optimal therapies. METHODS: We applied unsupervised (without a priori clinical criteria) principal component analysis on sputum airway cells RNA-sequencing transcriptomic data from 19 asthmatics from the Severe Asthma Research Program at baseline and 6-8 weeks follow-up after a 40 mg dose of intramuscular corticosteroids. We investigated principal components PC1, PC3 for association with 55 clinical variables. RESULTS: PC3 was associated with baseline Th2 clinical features including blood (rank-sum p=0.0082) and airway (rank-sum p=0.0024) eosinophilia, FEV1 change (Kendall tau-b R=-0.333 (-0.592 to -0.012)) and follow-up FEV1 albuterol response (Kendall tau-b R=0.392 (0.079 to 0.634)). PC1 with blood basophlia (rank-sum p=0.0191). The top 5% genes contributing to PC1, PC3 were enriched for distinct immune system/inflammation ontologies suggesting distinct subject-specific clusters of transcriptomic response to corticosteroids. PC3 association with FEV1 change was reproduced in silico in a comparable independent 14-subject (baseline, 8 weeks after daily inhaled corticosteroids (ICS)) airway epithelial cells microRNAome dataset. CONCLUSIONS: Transcriptomic PCs from this unsupervised methodology define molecular pharmacogenomic endotypes that may yield novel biology underlying different subject-specific responses to corticosteroid therapy in asthma, and optimal personalised asthma care. Top contributing genes to these PCs may suggest new therapeutic targets.

Lung tissue shows divergent gene expression between chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are characterized by shared exposures and clinical features, but distinct genetic and pathologic features exist. These features have not been well-studied using large-scale gene expression datasets. We hypothesized that there are divergent gene, pathway, and cellular signatures between COPD and IPF. METHODS: We performed RNA-sequencing on lung tissues from individuals with IPF (n = 231) and COPD (n = 377) compared to control (n = 267), defined as individuals with normal spirometry. We grouped the overlapping differential expression gene sets based on direction of expression and examined the resultant sets for genes of interest, pathway enrichment, and cell composition. Using gene set variation analysis, we validated the overlap group gene sets in independent COPD and IPF data sets. RESULTS: We found 5010 genes differentially expressed between COPD and control, and 11,454 genes differentially expressed between IPF and control (1% false discovery rate). 3846 genes overlapped between IPF and COPD. Several pathways were enriched for genes upregulated in COPD and downregulated in IPF; however, no pathways were enriched for genes downregulated in COPD and upregulated in IPF. There were many myeloid cell genes with increased expression in COPD but decreased in IPF. We found that the genes upregulated in COPD but downregulated in IPF were associated with lower lung function in the independent validation cohorts. CONCLUSIONS: We identified a divergent gene expression signature between COPD and IPF, with increased expression in COPD and decreased in IPF. This signature is associated with worse lung function in both COPD and IPF.

Analysis of genetically driven alternative splicing identifies FBXO38 as a novel COPD susceptibility gene.

While many disease-associated single nucleotide polymorphisms (SNPs) are associated with gene expression (expression quantitative trait loci, eQTLs), a large proportion of complex disease genome-wide association study (GWAS) variants are of unknown function. Some of these SNPs may contribute to disease by regulating gene splicing. Here, we investigate whether SNPs that are associated with alternative splicing (splice QTL or sQTL) can identify novel functions for existing GWAS variants or suggest new associated variants in chronic obstructive pulmonary disease (COPD). RNA sequencing was performed on whole blood from 376 subjects from the COPDGene Study. Using linear models, we identified 561,060 unique sQTL SNPs associated with 30,333 splice sites corresponding to 6,419 unique genes. Similarly, 708,928 unique eQTL SNPs involving 15,913 genes were detected at 10% FDR. While there is overlap between sQTLs and eQTLs, 55.3% of sQTLs are not eQTLs. Co-localization analysis revealed that 7 out of 21 loci associated with COPD (p<1x10-6) in a published GWAS have at least one shared causal variant between the GWAS and sQTL studies. Among the genes identified to have splice sites associated with top GWAS SNPs was FBXO38, in which a novel exon was discovered to be protective against COPD. Importantly, the sQTL in this locus was validated by qPCR in both blood and lung tissue, demonstrating that splice variants relevant to lung tissue can be identified in blood. Other identified genes included CDK11A and SULT1A2. Overall, these data indicate that analysis of alternative splicing can provide novel insights into disease mechanisms. In particular, we demonstrated that SNPs in a known COPD GWAS locus on chromosome 5q32 influence alternative splicing in the gene FBXO38.

Circulating MicroRNAs and Treatment Response in Childhood Asthma.

Rationale: Inhaled corticosteroids (ICS) are key treatments for controlling asthma and preventing asthma attacks. However, the responsiveness to ICS varies among individuals. MicroRNAs (miRNAs) have been lauded for their prognostic utility.Objectives: We hypothesized that circulating miRNAs obtained at baseline/prerandomization in the Childhood Asthma Management Program (CAMP) could serve as biomarkers and biologic mediators of ICS clinical response over the 4-year clinical trial period.Methods: We selected baseline serum samples from 462 CAMP subjects subsequently randomized to either ICS (budesonide) or placebo. Samples underwent small RNA sequencing, and read counts were normalized and filtered by depth and coverage. Linear regression was used to associate miRNAs with change in FEV1% (prebronchodilator FEV1 as a percent predicted) over the 4-year treatment period in both main effects and interaction models. We validated the function of the top associated miRNAs by luciferase reporter assays of glucocorticoid-mediated transrepression and predicted response to ICS through logistic regression models.Measurements and Main Results: We identified 7 miRNAs significantly associated with FEV1% change (P ≤ 0.05) and 15 miRNAs with significant interaction (P ≤ 0.05) to ICS versus placebo treatments. We selected three miRNAs for functional validation, of which hsa-miR-155-5p and hsa-miR-532-5p were significantly associated with changes in dexamethasone-induced transrepression of NF-κB. Combined, these two miRNAs were predictive of ICS response over the course of the clinical trial, with an area under the receiver operating characteristic curve of 0.86.Conclusions: We identified two functional circulating miRNAs predictive of asthma ICS treatment response over time.

RNA-sequencing across three matched tissues reveals shared and tissue-specific gene expression and pathway signatures of COPD.

BACKGROUND: Multiple gene expression studies have been performed separately in peripheral blood, lung, and airway tissues to study COPD. We performed RNA-sequencing gene expression profiling of large-airway epithelium, alveolar macrophage and peripheral blood samples from the same subset of COPD cases and controls from the COPDGene study who underwent bronchoscopy at a single center. Using statistical and gene set enrichment approaches, we sought to improve the understanding of COPD by studying gene sets and pathways across these tissues, beyond the individual genomic determinants. METHODS: We performed differential expression analysis using RNA-seq data obtained from 63 samples from 21 COPD cases and controls (includes four non-smokers) via the R package DESeq2. We tested associations between gene expression and variables related to lung function, smoking history, and CT scan measures of emphysema and airway disease. We examined the correlation of differential gene expression across the tissues and phenotypes, hypothesizing that this would reveal preserved and private gene expression signatures. We performed gene set enrichment analyses using curated databases and findings from prior COPD studies to provide biological and disease relevance. RESULTS: The known smoking-related genes CYP1B1 and AHRR were among the top differential expression results for smoking status in the large-airway epithelium data. We observed a significant overlap of genes primarily across large-airway and macrophage results for smoking and airway disease phenotypes. We did not observe specific genes differentially expressed in all three tissues for any of the phenotypes. However, we did observe hemostasis and immune signaling pathways in the overlaps across all three tissues for emphysema, and amyloid and telomere-related pathways for smoking. In peripheral blood, the emphysema results were enriched for B cell related genes previously identified in lung tissue studies. CONCLUSIONS: Our integrative analyses across COPD-relevant tissues and prior studies revealed shared and tissue-specific disease biology. These replicated and novel findings in the airway and peripheral blood have highlighted candidate genes and pathways for COPD pathogenesis.

CTNNA3 and SEMA3D: Promising loci for asthma exacerbation identified through multiple genome-wide association studies.

BACKGROUND: Asthma exacerbations are a major cause of morbidity and medical cost. OBJECTIVE: The objective of this study was to identify genetic predictors of exacerbations in asthmatic subjects. METHODS: We performed a genome-wide association study meta-analysis of acute asthma exacerbation in 2 pediatric clinical trials: the Childhood Asthma Management Program (n = 581) and the Childhood Asthma Research and Education (n = 205) network. Acute asthma exacerbations were defined as treatment with a 5-day course of oral steroids. We obtained a replication cohort from Biobank of Vanderbilt University Medical Center (BioVU; n = 786), the Vanderbilt University electronic medical record-linked DNA biobank. We used CD4(+) lymphocyte genome-wide mRNA expression profiling to identify associations of top single nucleotide polymorphisms with mRNA abundance of nearby genes. RESULTS: A locus in catenin (cadherin-associated protein), alpha 3 (CTNNA3), reached genome-wide significance (rs7915695, P = 2.19 × 10(-8); mean exacerbations, 6.05 for minor alleles vs 3.71 for homozygous major alleles). Among the 4 top single nucleotide polymorphisms replicated in BioVU, rs993312 in Sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3D (SEMA3D) was significant (P = .0083) and displayed stronger association among African Americans (P = .0004 in BioVU [mean exacerbations, 3.91 vs 1.53]; P = .0089 in the Childhood Asthma Management Program [mean exacerbations, 6.0 vs 3.25]). CTNNA3 variants did not replicate in BioVU. A regulatory variant in the CTNNA3 locus was associated with CTNNA3 mRNA expression in CD4(+) cells from asthmatic patients (P = .00079). CTNNA3 appears to be active in the immune response, and SEMA3D has a plausible role in airway remodeling. We also provide a replication of a previous association of purinergic receptor P2X, ligand-gated ion channel, 7 (P2RX7), with asthma exacerbation. CONCLUSIONS: We identified 2 loci associated with exacerbations through a genome-wide association study. CTNNA3 met genome-wide significance thresholds, and SEMA3D replicated in a clinical biobank database.

Overlap between COPD genetic association results and transcriptional quantitative trait loci.

Rationale: Genome-wide association studies (GWAS) have identified multiple genetic loci associated with chronic obstructive pulmonary disease (COPD). When integrated with GWAS results, expression quantitative trait locus (eQTL) studies can provide insight into biological mechanisms involved in disease by identifying single nucleotide polymorphisms (SNPs) that contribute to whole gene expression. However, there are multiple genetically driven regulatory and isoform-specific effects which cannot be detected in traditional eQTL analyses. Here, we identify SNPs that are associated with alternative splicing (sQTL) in addition to eQTLs to identify novel functions for COPD associated genetic variants. Methods: We performed RNA sequencing on whole blood from 3743 subjects in the COPDGene Study. RNA sequencing data from lung tissue of 1241 subjects from the Lung Tissue Research Consortium (LTRC), and whole genome sequencing data on all subjects. Associations between all SNPs within 1000 kb of a gene (cis-) and splice and gene expression quantifications were tested using tensorQTL. In COPDGene a total of 11,869,333 SNPs were tested for association with 58,318 splice clusters, and 8,792,206 SNPs were tested for association with 70,094 splice clusters in LTRC. We assessed colocalization with COPD-associated SNPs from a published GWAS[1]. Results: After adjustment for multiple statistical testing, we identified 28,110 splice-sites corresponding to 3,889 unique genes that were significantly associated with genotype in COPDGene whole blood, and 58,258 splice-sites corresponding to 10,307 unique genes associated with genotype in LTRC lung tissue. We found 7,576 sQTL splice-sites corresponding to 2,110 sQTL genes were shared between whole blood and lung, while 20,534 sQTL splice-sites in 3,518 genes were unique to blood and 50,682 splice-sites in 9,677 genes were unique to lung. To determine what proportion of COPD-associated SNPs were associated with transcriptional splicing, we performed colocalization analysis between COPD GWAS and sQTL data, and found that 38 genomic windows, corresponding to 38 COPD GWAS loci had evidence of colocalization between QTLs and COPD. The top five colocalizations between COPD and lung sQTLs include NPNT , FBXO38 , HHIP , NTN4 and BTC . Conclusions: A total of 38 COPD GWAS loci contain evidence of sQTLs, suggesting that analysis of sQTLs in whole blood and lung tissue can provide novel insights into disease mechanisms.

Joint clinical and molecular subtyping of COPD with variational autoencoders.

Chronic Obstructive Pulmonary Disease (COPD) is a complex, heterogeneous disease. Traditional subtyping methods generally focus on either the clinical manifestations or the molecular endotypes of the disease, resulting in classifications that do not fully capture the disease's complexity. Here, we bridge this gap by introducing a subtyping pipeline that integrates clinical and gene expression data with variational autoencoders. We apply this methodology to the COPDGene study, a large study of current and former smoking individuals with and without COPD. Our approach generates a set of vector embeddings, called Personalized Integrated Profiles (PIPs), that recapitulate the joint clinical and molecular state of the subjects in the study. Prediction experiments show that the PIPs have a predictive accuracy comparable to or better than other embedding approaches. Using trajectory learning approaches, we analyze the main trajectories of variation in the PIP space and identify five well-separated subtypes with distinct clinical phenotypes, expression signatures, and disease outcomes. Notably, these subtypes are more robust to data resampling compared to those identified using traditional clustering approaches. Overall, our findings provide new avenues to establish fine-grained associations between the clinical characteristics, molecular processes, and disease outcomes of COPD.

Hepatitis C and HIV detection by blood RNA-sequencing in cohort of smokers.

Detection of viruses by RNA and DNA sequencing has improved the understanding of the human virome. We sought to identify blood viral signatures through secondary use of RNA-sequencing (RNA-seq) data in a large study cohort. The ability to reveal undiagnosed infections with public health implications among study subjects with available sequencing data could enable epidemiologic surveys and may lead to diagnosis and therapeutic interventions, leveraging existing research data in a clinical context. We detected viral RNA in peripheral blood RNA-seq data from a COPD-enriched population of current and former smokers. Correlation between viral detection and both reported infections and relevant disease outcomes was evaluated. We identified Hepatitis C virus RNA in 228 subjects and HIV RNA in 30 subjects. Overall, we observed 31 viral species, including Epstein-Barr virus and Cytomegalovirus. We observed an enrichment of Hepatitis C and HIV infections among subjects reporting liver disease and HIV infections, respectively. Higher interferon expression scores were observed in the subjects with Hepatitis C and HIV infections. Through secondary use of RNA-seq from a cohort of current and former smokers, we detected peripheral blood viral signatures. We identified HIV and Hepatitis C virus (HCV), highlighting potential public health implications for the approach described this study. We observed correlations with reported infections, chronic infection outcomes and the host transcriptomic response, providing evidence to support the validity of the approach.

Early Changes in Immune Cell Count, Metabolism, and Function Following Sleeve Gastrectomy: A Prospective Human Study.

OBJECTIVE: To characterize longitudinal changes in blood biomarkers, leukocyte composition, and gene expression following laparoscopic sleeve gastrectomy (LSG). BACKGROUND: LSG is an effective treatment for obesity, leading to sustainable weight loss and improvements in obesity-related comorbidities and inflammatory profiles. However, the effects of LSG on immune function and metabolism remain uncertain. METHODS: Prospective data were collected from 23 enrolled human subjects from a single institution. Parameters of weight, comorbidities, and trends in blood biomarkers and leukocyte subsets were observed from preoperative baseline to 1 year postsurgery in 3-month follow-up intervals. RNA sequencing was performed on pairs of whole blood samples from the first 6 subjects of the study (baseline and 3 months postsurgery) to identify genome-wide gene expression changes associated with undergoing LSG. RESULTS: LSG led to a significant decrease in mean total body weight loss (18.1%) at 3 months and among diabetic subjects a reduction in hemoglobin A1c. Improvements in clinical inflammatory and hormonal biomarkers were demonstrated as early as 3 months after LSG. A reduction in neutrophil-lymphocyte ratio was observed, driven by a reduction in absolute neutrophil counts. Gene set enrichment analyses of differential whole blood gene expression demonstrated that after 3 months LSG induced transcriptomic changes not only in inflammatory cytokine pathways but also in several key metabolic pathways related to energy metabolism. CONCLUSIONS: LSG induces significant changes in the composition and metabolism of immune cells as early as 3 months postoperatively. Further evaluation is required of bariatric surgery's effects on immunometabolism and the consequences for host defense and metabolic disease.

Peripheral blood microbial signatures in current and former smokers.

The human microbiome has a role in the development of multiple diseases. Individual microbiome profiles are highly personalized, though many species are shared. Understanding the relationship between the human microbiome and disease may inform future individualized treatments. We hypothesize the blood microbiome signature may be a surrogate for some lung microbial characteristics. We sought associations between the blood microbiome signature and lung-relevant host factors. Based on reads not mapped to the human genome, we detected microbial nucleic acids through secondary use of peripheral blood RNA-sequencing from 2,590 current and former smokers with and without chronic obstructive pulmonary disease (COPD) from the COPDGene study. We used the Genome Analysis Toolkit (GATK) microbial pipeline PathSeq to infer microbial profiles. We tested associations between the inferred profiles and lung disease relevant phenotypes and examined links to host gene expression pathways. We replicated our analyses using a second independent set of blood RNA-seq data from 1,065 COPDGene study subjects and performed a meta-analysis across the two studies. The four phyla with highest abundance across all subjects were Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. In our meta-analysis, we observed associations (q-value < 0.05) between Acinetobacter, Serratia, Streptococcus and Bacillus inferred abundances and Modified Medical Research Council (mMRC) dyspnea score. Current smoking status was associated (q < 0.05) with Acinetobacter, Serratia and Cutibacterium abundance. All 12 taxa investigated were associated with at least one white blood cell distribution variable. Abundance for nine of the 12 taxa was associated with sex, and seven of the 12 taxa were associated with race. Host-microbiome interaction analysis revealed clustering of genera associated with mMRC dyspnea score and smoking status, through shared links to several host pathways. This study is the first to identify a bacterial microbiome signature in the peripheral blood of current and former smokers. Understanding the relationships between systemic microbial signatures and lung-related phenotypes may inform novel interventions and aid understanding of the systemic effects of smoking.

COMPSRA: a COMprehensive Platform for Small RNA-Seq data Analysis.

Small RNA-Seq is a common means to interrogate the small RNA'ome or the full spectrum of small RNAs (<200 nucleotide length) of a biological system. A pivotal problem in NGS based small RNA analysis is identifying and quantifying the small RNA'ome constituent components. For example, small RNAs in the circulatory system (circulating RNAs) are potential disease biomarkers and their function is being actively investigated. Most existing NGS data analysis tools focus on the microRNA component and a few other small RNA types like piRNA, snRNA and snoRNA. A comprehensive platform is needed to interrogate the full small RNA'ome, a prerequisite for down-stream data analysis. We present COMPSRA, a comprehensive modular stand-alone platform for identifying and quantifying small RNAs from small RNA sequencing data. COMPSRA contains prebuilt customizable standard RNA databases and sequence processing tools to enable turnkey basic small RNA analysis. We evaluated COMPSRA against comparable existing tools on small RNA sequencing data set from serum samples of 12 healthy human controls, and COMPSRA identified a greater diversity and abundance of small RNA molecules. COMPSRA is modular, stand-alone and integrates multiple customizable RNA databases and sequence processing tool and is distributed under the GNU General Public License free to non-commercial registered users at https://github.com/cougarlj/COMPSRA.

Early changes in immune cell metabolism and function are a hallmark of sleeve gastrectomy: a prospective human study.

OBJECTIVE: To characterize longitudinal changes in blood biomarkers, leukocyte composition, and gene expression following laparoscopic sleeve gastrectomy (LSG). BACKGROUND: LSG is an effective treatment for obesity, leading to sustainable weight loss and improvements in obesity-related co-morbidities and inflammatory profiles. However, the effects of LSG on immune function and metabolism remain uncertain. METHODS: Prospective data was collected from 23 enrolled human subjects from a single institution. Parameters of weight, co-morbidities, and trends in blood biomarkers and leukocyte subsets were observed from pre-operative baseline to one year in three-month follow-up intervals. RNA-sequencing was performed on pairs of whole blood samples from the first six subjects of the study (baseline and three months post-surgery) to identify genome-wide gene expression changes associated with undergoing LSG. RESULTS: LSG led to a significant decrease in mean total body weight loss (18.1%) at three months and among diabetic subjects a reduction in HbA1c. Improvements in clinical inflammatory and hormonal biomarkers were demonstrated as early as three months after LSG. A reduction in neutrophil-lymphocyte ratio was observed, driven by a reduction in absolute neutrophil counts. Gene set enrichment analyses of differential whole blood gene expression demonstrated that after three months, LSG induced transcriptomic changes not only in inflammatory cytokine pathways but also in several key metabolic pathways related to energy metabolism. CONCLUSIONS: LSG induces significant changes in the composition and metabolism of immune cells as early as three months post-operatively. Further evaluation is required of bariatric surgery's effects on immunometabolism and consequences for host defense and metabolic disease.

Correction to: RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking.

Following publication of the original article [1], the authors provided an updated accession number in the "Availability of data and materials" section of the declarations.

RNA sequencing identifies novel non-coding RNA and exon-specific effects associated with cigarette smoking.

BACKGROUND: Cigarette smoking is the leading modifiable risk factor for disease and death worldwide. Previous studies quantifying gene-level expression have documented the effect of smoking on mRNA levels. Using RNA sequencing, it is possible to analyze the impact of smoking on complex regulatory phenomena (e.g. alternative splicing, differential isoform usage) leading to a more detailed understanding of the biology underlying smoking-related disease. METHODS: We used whole-blood RNA sequencing to describe gene and exon-level expression differences between 229 current and 286 former smokers in the COPDGene study. We performed differential gene expression and differential exon usage analyses using the voom/limma and DEXseq R packages. Samples from current and former smokers were compared while controlling for age, gender, race, lifetime smoke exposure, cell counts, and technical covariates. RESULTS: At an adjusted p-value <0.05, 171 genes were differentially expressed between current and former smokers. Differentially expressed genes included 7 long non-coding RNAs that have not been previously associated with smoking: LINC00599, LINC01362, LINC00824, LINC01624, RP11-563D10.1, RP11-98G13.1, AC004791.2. Secondary analysis of acute smoking (having smoked within 2-h) revealed 5 of the 171 smoking genes demonstrated an acute response above the baseline effect of chronic smoking. Exon-level analyses identified 9 exons from 8 genes with significant differential usage by smoking status, suggesting smoking-induced changes in isoform expression. CONCLUSIONS: Transcriptomic changes at the gene and exon levels from whole blood can refine our understanding of the molecular mechanisms underlying the response to smoking.

Genetic loci associated with chronic obstructive pulmonary disease overlap with loci for lung function and pulmonary fibrosis.

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 × 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, while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis (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. 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.