Exome Sequencing Analysis in Severe, Early-Onset Chronic Obstructive Pulmonary Disease

Effect of nitric oxide synthase gene polymorphism on inflammatory response in patients with chronic obstructive pulmonary disease

This study aimed to investigate the association between nitric oxide synthase gene polymorphisms and the inflammatory responses in patients with 'fast-' and 'slow-' developing chronic obstructive pulmonary disease (COPD). In the main process, 190 patients with slow-developing COPD, 94 patients with fast-developing COPD and 105 healthy volunteers were selected for inclusion. Endothelial nitric oxide synthase (eNOS) was detected using western-blot eNOS sites, and inducible nitric oxide synthase (iNOS) was detected through SNPshot. T helper 17 cells (Th17) and regulator T (Treg) cells were detected via flow cytometry, and interferon-gamma, tumour necrosis factor-alpha, interleukin (IL)-17, IL-10, IL-6, IL-4 and IL-2 were detected using a cytometric bead array. The final results and conclusions drawn from the tests suggest that Th17/Treg-mediated immune inflammation plays an important role in the pathogenesis of COPD, but whether it affects the development of COPD needs further investigation. Overall, COPD patients with a young age of onset, young age of smoking initiation and small body mass index, as well as COPD patients with CC at rs3729508 in the iNOS gene and non-GG at rs7830 in the eNOS gene, may be more likely to contract fast-developing COPD.

Evaluation of Pulmonary Fibrosis Outcomes by Race and Ethnicity in US Adults

Importance

Pulmonary fibrosis (PF) is characterized by progressive scarring of lung tissue and poor survival. Racial and ethnic minority populations face the greatest risk of morbidity and mortality from disparities impacting respiratory health, but the pattern of age at clinically relevant outcomes across diverse racial and ethnic populations with PF is unknown.

Objective

To compare the age at PF-related outcomes and the heterogeneity in survival patterns among Hispanic, non-Hispanic Black, and non-Hispanic White participants.

Design, Setting, and Participants

This cohort study included adult patients with a PF diagnosis and used data from prospective clinical registries: the Pulmonary Fibrosis Foundation Registry (PFFR) for the primary cohort and registries from 4 geographically distinct tertiary hospitals in the US for the external multicenter validation (EMV) cohort. Patients were followed between January 2003 and April 2021.

Exposures

Race and ethnicity comparisons between Black, Hispanic, and White participants with PF.

Main Outcomes and Measures

Age and sex distribution of participants were measured at the time of study enrollment. All-cause mortality and age at PF diagnosis, hospitalization, lung transplant, and death were assessed in participants over 14 389 person-years. Differences between racial and ethnic groups were compared using Wilcoxon rank sum tests, Bartlett 1-way analysis of variance, and χ2 tests, and crude mortality rates and rate ratios were assessed across racial and ethnic categories using Cox proportional hazards regression models.

Results

In total, 4792 participants with PF were assessed (mean [SD] age, 66.1 [11.2] years; 2779 [58.0%] male; 488 [10.2%] Black, 319 [6.7%] Hispanic, and 3985 [83.2%] White); 1904 were in the PFFR and 2888 in the EMV cohort. Black patients with PF were consistently younger than White patients (mean [SD] age at baseline, 57.9 [12.0] vs 68.6 [9.6] years; P < .001). Hispanic and White patients were predominantly male (Hispanic: PFFR, 73 of 124 [58.9%] and EMV, 109 of 195 [55.9%]; and White: PFFR, 1090 of 1675 [65.1%] and EMV, 1373 of 2310 [59.4%]), while Black patients were less likely to be male (PFFR, 32 of 105 [30.5%] and EMV, 102 of 383 [26.6%]). Compared with White patients, Black patients had a lower crude mortality rate ratio (0.57 [95% CI, 0.31-0.97), but for Hispanic patients, the mortality rate ratio was similar to that of White patients (0.89; 95% CI, 0.57-1.35). Mean (SD) hospitalization events per person were highest among Black patients compared with Hispanic and White patients (Black: 3.6 [5.0]; Hispanic, 1.8 [1.4]; and White, 1.7 [1.3]; P < .001). Black patients were consistently younger than Hispanic and White patients at first hospitalization (mean [SD] age: Black, 59.4 [11.7] years; Hispanic, 67.5 [9.8] years; and White, 70.0 [9.3] years; P < .001), lung transplant (Black, 58.6 [8.6] years; Hispanic, 60.5 [6.1] years; and White, 66.9 [6.7] years; P < .001), and death (Black, 68.7 [8.4] years; Hispanic, 72.9 [7.6] years; and White, 73.5 [8.7] years; P < .001). These findings remained consistent in the replication cohort and in sensitivity analyses within prespecified deciles of age groups.

Conclusions and Relevance

In this cohort study of participants with PF, racial and ethnic disparities, especially among Black patients, were found in PF-related outcomes, including earlier onset of death. Further research is essential to identify and mitigate the underlying responsible factors.

Assessing the contribution of rare genetic variants to phenotypes of chronic obstructive pulmonary disease using whole-genome sequence data

RATIONALE

Genetic variation has a substantial contribution to chronic obstructive pulmonary disease (COPD) and lung function measurements. Heritability estimates using genome-wide genotyping data can be biased if analyses do not appropriately account for the nonuniform distribution of genetic effects across the allele frequency and linkage disequilibrium (LD) spectrum. In addition, the contribution of rare variants has been unclear.

OBJECTIVES

We sought to assess the heritability of COPD and lung function using whole-genome sequence data from the Trans-Omics for Precision Medicine program.

METHODS

Using the genome-based restricted maximum likelihood method, we partitioned the genome into bins based on minor allele frequency and LD scores and estimated heritability of COPD, FEV1% predicted and FEV1/FVC ratio in 11 051 European ancestry and 5853 African-American participants.

MEASUREMENTS AND MAIN RESULTS

In European ancestry participants, the estimated heritability of COPD, FEV1% predicted and FEV1/FVC ratio were 35.5%, 55.6% and 32.5%, of which 18.8%, 19.7%, 17.8% were from common variants, and 16.6%, 35.8%, and 14.6% were from rare variants. These estimates had wide confidence intervals, with common variants and some sets of rare variants showing a statistically significant contribution (P-value < 0.05). In African-Americans, common variant heritability was similar to European ancestry participants, but lower sample size precluded calculation of rare variant heritability.

CONCLUSIONS

Our study provides updated and unbiased estimates of heritability for COPD and lung function, and suggests an important contribution of rare variants. Larger studies of more diverse ancestry will improve accuracy of these estimates.

Exome and Sputum Microbiota as Predictive Markers of Frequent Exacerbations in Chronic Obstructive Pulmonary Disease

Frequent acute exacerbations are the leading cause of high rates of hospitalization and mortality in chronic obstructive pulmonary disease (COPD). Despite the enormous worldwide medical burden, reliable molecular markers for effective early diagnosis and prognosis of acute exacerbations are still lacking. Both the host genetics and airway microbiome are known to play potential roles in the pathogenesis of frequent exacerbations. Here, we performed whole exome sequencing (WES) and 16S rRNA gene sequencing to explore the interaction between these two factors and their implications in the pathogenesis of frequent exacerbations. We collected peripheral blood (n = 82), sputum samples (n = 59) and clinical data from 50 frequent-exacerbation phenotype (FE) COPD patients and 32 infrequent-exacerbation phenotype (IE) as controls. Based on filtering the deleterious sites, candidate mutated genes shared only in FE patients and did not occur in the IE group were identified. Microbiota analysis revealed significant differences in bacterial diversity and composition between FE and IE groups. We report the underlying pathogenic gene including, AATF, HTT, CEP350, ADAMTS9, TLL2 genes, etc., and explore their possible genotypic-phenotypic correlations with microbiota dysbiosis. Importantly, we observed that AATF gene mutations were significantly negatively correlated with microbial richness and diversity. Our study indicated several deleterious mutations in candidate genes that might be associated with microbial dysbiosis and the increased risk of frequent acute exacerbations in COPD patients. These results provide novel evidence that exomes and related microbiomes may potentially serve as biomarkers for predicting frequent acute exacerbations in COPD patients.

Whole-Exome Sequencing of Bronchial Epithelial Cells Reveals a Genetic Print of Airway Remodelling in COPD

The remodelling of the airways is a hallmark of chronic obstructive pulmonary disease, but it is highly heterogeneous and erratically distributed in the airways. To assess the genetic print of remodelling in chronic obstructive pulmonary disease (COPD), we performed a comparative whole-exome sequencing analysis on microdissected bronchial epithelia. Lung resections from four non-COPD and three COPD subjects (ex-smokers and current smokers) were formalin-fixed paraffin-embedded (FFPE). Non-remodelled and remodelled bronchial epithelia were isolated by laser microdissection. Genomic DNA was captured and sequenced. The comparative quantitative analysis identified a list of 109 genes as having variants in remodelled epithelia and 160 genes as having copy number alterations in remodelled epithelia, mainly in COPD patients. The functional analysis highlighted cilia-associated processes. Therefore, bronchial-remodelled epithelia appeared genetically more altered than non-remodelled epithelia. Characterizing the unique molecular print of airway remodelling in respiratory diseases may help uncover additional factors contributing to epithelial dysfunctions, ultimately providing additional targetable proteins to correct epithelial remodelling and improve lung function.

Genetics of chronic obstructive pulmonary disease: understanding the pathobiology and heterogeneity of a complex disorder

Chronic obstructive pulmonary disease (COPD) is a deadly and highly morbid disease. Susceptibility to and heterogeneity of COPD are incompletely explained by environmental factors such as cigarette smoking. Family-based and population-based studies have shown that a substantial proportion of COPD risk is related to genetic variation. Genetic association studies have identified hundreds of genetic variants that affect risk for COPD, decreased lung function, and other COPD-related traits. These genetic variants are associated with other pulmonary and non-pulmonary traits, demonstrate a genetic basis for at least part of COPD heterogeneity, have a substantial effect on COPD risk in aggregate, implicate early-life events in COPD pathogenesis, and often involve genes not previously suspected to have a role in COPD. Additional progress will require larger genetic studies with more ancestral diversity, improved profiling of rare variants, and better statistical methods. Through integration of genetic data with other omics data and comprehensive COPD phenotypes, as well as functional description of causal mechanisms for genetic risk variants, COPD genetics will continue to inform novel approaches to understanding the pathobiology of COPD and developing new strategies for management and treatment.

Whole-Exome Sequencing Implicates the USP34 rs777591A > G Intron Variant in Chronic Obstructive Pulmonary Disease in a Kashi Cohort

Genetic factors are important factors in chronic obstructive pulmonary disease (COPD) onset. Plenty of risk and new causative genes for COPD have been identified in patients of the Chinese Han population. In contrast, we know considerably little concerning the genetics in the Kashi COPD population (Uyghur). This study aims at clarifying the genetic maps regarding COPD susceptibility in Kashi (China). Whole-exome sequencing (WES) was used to analyze three Uyghur families with COPD in Kashi (eight patients and one healthy control). Sanger sequencing was also used to verify the WES results in 541 unrelated Uyghur COPD patients and 534 Uyghur healthy controls. WES showed 72 single nucleotide variants (SNVs), two deletions, and small insertions (InDels), 26 copy number variants (CNVs), and 34 structural variants (SVs), including g.71230620T > A (rs12449210T > A, NC_000,016.10) in the HYDIN axonemal central pair apparatus protein (HYDIN) gene and g.61190482A > G (rs777591A > G, NC_000002.12) in the ubiquitin-specific protease 34 (USP34) gene. After Sanger sequencing, we found that rs777591“AA” under different genetic models except for the dominant model (adjusted OR = 0.8559, 95%CI 0.6568–1.115, p > .05), could significantly reduce COPD risk, but rs12449210T > A was not related to COPD. In stratified analysis of smoking status, rs777591“AA” reduced COPD risk significantly among the nonsmoker group. Protein and mRNA expression of USP34 in cigarette smoke extract-treated BEAS-2b cells increased significantly compared with those in the control group. Our findings associate the USP34 rs777591“AA” genotype as a protector factor in COPD.

Identification of novel key genes associated with the metastasis of prostate cancer based on bioinformatics prediction and validation

Background

Metastatic prostate cancer (PCa) is a lethal tumor. However, the molecular mechanisms underlying PCa progression have not been fully elucidated.

Methods

Transcriptome expression profiling and clinical information on primary and metastatic PCa samples were obtained from TCGA. R software was used to screen the DEGs, and LASSO logistical regression method was utilized to identify the pivotal PCa metastasis-related DEGs. The transcriptional expression levels of the key genes were analyzed using the UALCAN database, and the corresponding protein expression were validated by Immunohistochemistry (IHC). Survival analysis of the key genes was performed using the GEPIA database. Wound healing assay and Transwell assay were conducted to determine whether knockdown of the key genes influence the migration and invasion abilities of PCa cells (22Rv1 and PC3). GSEA was performed to predict key genes-mediated signaling pathways for the development of PCa. Western blotting was used to evaluate the expression changes of E-cadherin, Twist1, and Vimentin in PCa cells with the key genes silencing. An in vivo mouse metastatic model for PCa was also generated to verify the important role of ISG15 and CST2 in PCa metastasis.

Results

A comparison between primary and metastatic PCa tissues was conducted, and 19 DEGs were screened. Among these, three key genes were identified that might be closely associated with PCa progression according to the LASSO logistical analysis, namely ISG15, DNAH8, and CST2. Further functional experiments revealed that knockdown of ISG15 and CST2 suppressed wound healing, migration, and invasion of PCa cells. To explore the molecular mechanism of ISG15 and CST2 in the development of PCa, GSEA was performed, and it was found that both genes play crucial roles in cell adhesion molecules, extracellular matrix-receptor interaction, and focal adhesion. Western blotting results exhibited that inhibiting ISG15 and CST2 led to increase the expression of E-cadherin and decrease the expression of Twist1 and Vimentin. Additionally, the metastatic in vivo study demonstrated that both PC3 and 22Rv1 cells expressing with luciferase-shISG15 and luciferase-shCST2 had significantly lower detectable bioluminescence than that in the control PCa cells.

Conclusion

ISG15 and CST2 may participate in PCa metastasis by regulating the epithelial-mesenchymal transition (EMT) signaling pathway. These findings may help to better understand the pathogenetic mechanisms governing PCa and provide promising therapeutic targets for metastatic PCa therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02258-3.

Genetic profiling for disease stratification in chronic obstructive pulmonary disease and asthma

PURPOSE OF REVIEW

In asthma and chronic obstructive pulmonary disease (COPD), the movement towards genetic profiling with a push towards 'personalized medicine' has been hindered by complex environment--gene interactions and lack of tools to identify clear causal genetic traits. In this review, we will discuss the need for genetic profiling in asthma and COPD, what methods are currently used in the clinics and the recent finding using new sequencing methods.

RECENT FINDINGS

Over the past 10-15 years, genome-wide association studies analysis of common variants has provide little in the way of new genetic profiling markers for asthma and COPD. Whole exome/genome sequencing has provided a new method to identify lowly abundant alleles, which might have a much higher impact. Although, low population numbers due to high costs has hindered early studies, recent studies have reached genome wide significance.

SUMMARY

The use of genetic profiling of COPD in the clinic is current limited to the identification of Alpha-1 antitrypsin deficiency, while being absent in asthma. Advances in sequencing technology provide new avenues to identify disease causes or therapy response altering variants that in the short-term will allow for the development of screening procedures for disease to identify patients at risk of developing asthma or COPD.

Genetic Advances in Chronic Obstructive Pulmonary Disease. Insights from COPDGene

Chronic obstructive pulmonary disease (COPD) is a common and progressive disease that is influenced by both genetic and environmental factors. For many years, knowledge of the genetic basis of COPD was limited to Mendelian syndromes, such as alpha-1 antitrypsin deficiency and cutis laxa, caused by rare genetic variants. Over the past decade, the proliferation of genome-wide association studies, the accessibility of whole-genome sequencing, and the development of novel methods for analyzing genetic variation data have led to a substantial increase in the understanding of genetic variants that play a role in COPD susceptibility and COPD-related phenotypes. COPDGene (Genetic Epidemiology of COPD), a multicenter, longitudinal study of over 10,000 current and former cigarette smokers, has been pivotal to these breakthroughs in understanding the genetic basis of COPD. To date, over 20 genetic loci have been convincingly associated with COPD affection status, with additional loci demonstrating association with COPD-related phenotypes such as emphysema, chronic bronchitis, and hypoxemia. In this review, we discuss the contributions of the COPDGene study to the discovery of these genetic associations as well as the ongoing genetic investigations of COPD subtypes, protein biomarkers, and post-genome-wide association study analysis.

Initiating drug therapy in early stage chronic obstructive pulmonary disease: does it impact the course and outcome?

PURPOSE OF REVIEW

Early chronic obstructive pulmonary disease (COPD) is emerging in importance for the clinical and research settings. This review will highlight a proposed definition of early COPD, examine early and midlife factors that lead to development of early COPD and review the literature pertaining to the treatment of mild COPD to gain insight into potential therapeutic approaches for early disease.

RECENT FINDINGS

Early COPD can be defined as disease occurring in patients younger than 50 years in age with a 10-pack-year or more smoking history and abnormal spirometry, imaging or lung function decline. Childhood exposures (maternal smoking and recurrent respiratory infections), childhood and adult asthma, and smoking affect middle-age lung function. Multiple studies of long-acting muscarinic antagonists (LAMAs) in mild COPD have shown improvements in lung function and symptoms scores. Smoking cessation also has a beneficial effect on longitudinal lung function.

SUMMARY

Early COPD is an important manifestation of COPD, with a newly proposed definition and associated risk factors identified. Inferring from studies on mild COPD cohorts, LAMAs and smoking cessation may have a positive effect on longitudinal lung function and symptomatic improvement.

Applying Functional Genomics to Chronic Obstructive Pulmonary Disease

Genome-wide association studies (GWAS) have identified more than 20 genomic regions associated with chronic obstructive pulmonary disease (COPD) susceptibility. However, the functional genetic variants within these COPD GWAS loci remain largely unidentified, thus limiting translation of these GWAS discoveries to new disease insights. Whole-exome and whole-genome sequencing studies have the potential to identify rare genetic determinants of COPD. Efforts to understand the biological effects of novel COPD genetic loci include gene-targeted murine models, integration of additional omics data (including transcriptomics and epigenetics), and functional variant identification. COPD genetic determinants likely act through biological networks, and a variety of network-based approaches have been used to gain insights into COPD susceptibility and heterogeneity.

Genetics of COPD

Although chronic obstructive pulmonary disease (COPD) risk is strongly influenced by cigarette smoking, genetic factors are also important determinants of COPD. In addition to Mendelian syndromes such as alpha-1 antitrypsin deficiency, many genomic regions that influence COPD susceptibility have been identified in genome-wide association studies. Similarly, multiple genomic regions associated with COPD-related phenotypes, such as quantitative emphysema measures, have been found. Identifying the functional variants and key genes within these association regions remains a major challenge. However, newly identified COPD susceptibility genes are already providing novel insights into COPD pathogenesis. Network-based approaches that leverage these genetic discoveries have the potential to assist in decoding the complex genetic architecture of COPD.

Whole-Genome Sequencing in Severe Chronic Obstructive Pulmonary Disease

Genome-wide association studies have identified common variants associated with chronic obstructive pulmonary disease (COPD). Whole-genome sequencing (WGS) offers comprehensive coverage of the entire genome, as compared with genotyping arrays or exome sequencing. We hypothesized that WGS in subjects with severe COPD and smoking control subjects with normal pulmonary function would allow us to identify novel genetic determinants of COPD. We sequenced 821 patients with severe COPD and 973 control subjects from the COPDGene and Boston Early-Onset COPD studies, including both non-Hispanic white and African American individuals. We performed single-variant and grouped-variant analyses, and in addition, we assessed the overlap of variants between sequencing- and array-based imputation. Our most significantly associated variant was in a known region near HHIP (combined P = 1.6 × 10^-9); additional variants approaching genome-wide significance included previously described regions in CHRNA5, TNS1, and SERPINA6/SERPINA1 (the latter in African American individuals). None of our associations were clearly driven by rare variants, and we found minimal evidence of replication of genes identified by previously reported smaller sequencing studies. With WGS, we identified more than 20 million new variants, not seen with imputation, including more than 10,000 of potential importance in previously identified COPD genome-wide association study regions. WGS in severe COPD identifies a large number of potentially important functional variants, with the strongest associations being in known COPD risk loci, including HHIP and SERPINA1. Larger sample sizes will be needed to identify associated variants in novel regions of the genome.

metaFARVAT: An Efficient Tool for Meta-Analysis of Family-Based, Case-Control, and Population-Based Rare Variant Association Studies

Family-based designs have been shown to be powerful in detecting the significant rare variants associated with human diseases. However, very few significant results have been found owing to relatively small sample sizes and the fact that statistical analyses often suffer from high false-negative error rates. These limitations can be avoided by combining results from multiple studies via meta-analysis. However, statistical methods for meta-analysis with rare variants are limited for family-based samples. In this report, we propose a tool for the meta-analysis of family-based rare variant associations, metaFARVAT. metaFARVAT is based on a quasi-likelihood score for each variant. These scores are combined to generate burden test, variable-threshold test, sequence kernel association test (SKAT), and optimal SKAT statistics. The proposed method tests homogeneous and heterogeneous effects of variants among different studies and can be applied to both quantitative and dichotomous phenotypes. Simulation results demonstrated the robustness and efficiency of the proposed method in different scenarios. By applying metaFARVAT to data from a family-based study and a case-control study, we identified a few promising candidate genes, including DLEC1, which is associated with chronic obstructive pulmonary disease.

High-Throughput Sequencing in Respiratory, Critical Care, and Sleep Medicine Research. An Official American Thoracic Society Workshop Report

High-throughput, "next-generation" sequencing methods are now being broadly applied across all fields of biomedical research, including respiratory disease, critical care, and sleep medicine. Although there are numerous review articles and best practice guidelines related to sequencing methods and data analysis, there are fewer resources summarizing issues related to study design and interpretation, especially as applied to common, complex, nonmalignant diseases. To address these gaps, a single-day workshop was held at the American Thoracic Society meeting in May 2017, led by the American Thoracic Society Section on Genetics and Genomics. The aim of this workshop was to review the design, analysis, interpretation, and functional follow-up of high-throughput sequencing studies in respiratory, critical care, and sleep medicine research. This workshop brought together experts in multiple fields, including genetic epidemiology, biobanking, bioinformatics, and research ethics, along with physician-scientists with expertise in a range of relevant diseases. The workshop focused on application of DNA and RNA sequencing research in common chronic diseases and did not cover sequencing studies in lung cancer, monogenic diseases (e.g., cystic fibrosis), or microbiome sequencing. Participants reviewed and discussed study design, data analysis and presentation, interpretation, functional follow-up, and reporting of results. This report summarizes the main conclusions of the workshop, specifically addressing the application of these methods in respiratory, critical care, and sleep medicine research. This workshop report may serve as a resource for our research community as well as for journal editors and reviewers of sequencing-based manuscript submissions in our research field.

Whole exome sequencing analysis in severe chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD), one of the leading causes of death worldwide, is substantially influenced by genetic factors. Alpha-1 antitrypsin deficiency demonstrates that rare coding variants of large effect can influence COPD susceptibility. To identify additional rare coding variants in patients with severe COPD, we conducted whole exome sequencing analysis in 2543 subjects from two family-based studies (Boston Early-Onset COPD Study and International COPD Genetics Network) and one case-control study (COPDGene). Applying a gene-based segregation test in the family-based data, we identified significant segregation of rare loss of function variants in TBC1D10A and RFPL1 (P-value < 2x10-6), but were unable to find similar variants in the case-control study. In single-variant, gene-based and pathway association analyses, we were unable to find significant findings that replicated or were significant in meta-analysis. However, we found that the top results in the two datasets were in proximity to each other in the protein-protein interaction network (P-value = 0.014), suggesting enrichment of these results for similar biological processes. A network of these association results and their neighbors was significantly enriched in the transforming growth factor beta-receptor binding and cilia-related pathways. Finally, in a more detailed examination of candidate genes, we identified individuals with putative high-risk variants, including patients harboring homozygous mutations in genes associated with cutis laxa and Niemann-Pick Disease Type C. Our results likely reflect heterogeneity of genetic risk for COPD along with limitations of statistical power and functional annotation, and highlight the potential of network analysis to gain insight into genetic association studies.

Cystic Fibrosis Disease Modifiers: Complex Genetics Defines the Phenotypic Diversity in a Monogenic Disease

In many respects, genetic studies in cystic fibrosis (CF) serve as a paradigm for a human Mendelian genetic success story. From recognition of the condition as a heritable pathological entity to implementation of personalized treatments based on genetic findings, this multistep pathway of progress has focused on the genetic underpinnings of CF clinical disease. Along this path was the recognition that not all CFTR gene mutations produce the same disease and the recognition of the complex, multifactorial nature of CF genotype–phenotype relationships. The non- CFTR genetic components (gene modifiers) that contribute to variation in phenotype are the focus of this review. A multifaceted approach involving candidate gene studies, genome-wide association studies, and gene expression studies has revealed significant gene modifiers for multiple CF phenotypes. The bold challenges for the future are to integrate the findings into our understanding of CF pathogenesis and to use the knowledge to develop novel therapies.

Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes

Meta-analysis of genetic association studies increases sample size and the power for mapping complex traits. Existing methods are mostly developed for datasets without missing values, i.e. the summary association statistics are measured for all variants in contributing studies. In practice, genotype imputation is not always effective. This may be the case when targeted genotyping/sequencing assays are used or when the un-typed genetic variant is rare. Therefore, contributed summary statistics often contain missing values. Existing methods for imputing missing summary association statistics and using imputed values in meta-analysis, approximate conditional analysis, or simple strategies such as complete case analysis all have theoretical limitations. Applying these approaches can bias genetic effect estimates and lead to seriously inflated type-I or type-II errors in conditional analysis, which is a critical tool for identifying independently associated variants. To address this challenge and complement imputation methods, we developed a method to combine summary statistics across participating studies and consistently estimate joint effects, even when the contributed summary statistics contain large amounts of missing values. Based on this estimator, we proposed a score statistic called PCBS (partial correlation based score statistic) for conditional analysis of single-variant and gene-level associations. Through extensive analysis of simulated and real data, we showed that the new method produces well-calibrated type-I errors and is substantially more powerful than existing approaches. We applied the proposed approach to one of the largest meta-analyses to date for the cigarettes-per-day phenotype. Using the new method, we identified multiple novel independently associated variants at known loci for tobacco use, which were otherwise missed by alternative methods. Together, the phenotypic variance explained by these variants was 1.1%, improving that of previously reported associations by 71%. These findings illustrate the extent of locus allelic heterogeneity and can help pinpoint causal variants.

It is of great interest to estimate the joint effects of multiple variants from large scale meta-analyses, in order to fine-map causal variants and understand the genetic architecture for complex traits. The summary association statistics from participating studies in a meta-analysis often contain missing values at some variant sites, as the imputation methods may not work well and the variants with low imputation quality will be filtered out. Missingness is especially likely when the underlying genetic variant is rare or the participating studies use targeted genotyping array that is not suitable for imputation. Existing methods for conditional meta-analysis do not properly handle missing data, and can incorrectly estimate correlations between score statistics. As a result, they can produce highly inflated type-I errors for conditional analysis, which will result in overestimated phenotypic variance explained and incorrect identification of causal variants. We systematically evaluated this bias and proposed a novel partial correlation based score statistic. The new statistic has valid type-I errors for conditional analysis and much higher power than the existing methods, even when the contributed summary statistics contain a large fraction of missing values. We expect this method to be highly useful in the sequencing age for complex trait genetics.

A Genome-Wide Linkage Study for Chronic Obstructive Pulmonary Disease in a Dutch Genetic Isolate Identifies Novel Rare Candidate Variants

Chronic obstructive pulmonary disease (COPD) is a complex and heritable disease, associated with multiple genetic variants. Specific familial types of COPD may be explained by rare variants, which have not been widely studied. We aimed to discover rare genetic variants underlying COPD through a genome-wide linkage scan. Affected-only analysis was performed using the 6K Illumina Linkage IV Panel in 142 cases clustered in 27 families from a genetic isolate, the Erasmus Rucphen Family (ERF) study. Potential causal variants were identified by searching for shared rare variants in the exome-sequence data of the affected members of the families contributing most to the linkage peak. The identified rare variants were then tested for association with COPD in a large meta-analysis of several cohorts. Significant evidence for linkage was observed on chromosomes 15q14-15q25 [logarithm of the odds (LOD) score = 5.52], 11p15.4-11q14.1 (LOD = 3.71) and 5q14.3-5q33.2 (LOD = 3.49). In the chromosome 15 peak, that harbors the known COPD locus for nicotinic receptors, and in the chromosome 5 peak we could not identify shared variants. In the chromosome 11 locus, we identified four rare (minor allele frequency (MAF) <0.02), predicted pathogenic, missense variants. These were shared among the affected family members. The identified variants localize to genes including neuroblast differentiation-associated protein (AHNAK), previously associated with blood biomarkers in COPD, phospholipase C Beta 3 (PLCB3), shown to increase airway hyper-responsiveness, solute carrier family 22-A11 (SLC22A11), involved in amino acid metabolism and ion transport, and metallothionein-like protein 5 (MTL5), involved in nicotinate and nicotinamide metabolism. Association of SLC22A11 and MTL5 variants were confirmed in the meta-analysis of 9,888 cases and 27,060 controls. In conclusion, we have identified novel rare variants in plausible genes related to COPD. Further studies utilizing large sample whole-genome sequencing should further confirm the associations at chromosome 11 and investigate the chromosome 15 and 5 linked regions.

RNAseq analysis of bronchial epithelial cells to identify COPD-associated genes and SNPs

Background

There is a need for more powerful methods to identify low-effect SNPs that contribute to hereditary COPD pathogenesis. We hypothesized that SNPs contributing to COPD risk through cis-regulatory effects are enriched in genes comprised by bronchial epithelial cell (BEC) expression patterns associated with COPD.

Methods

To test this hypothesis, normal BEC specimens were obtained by bronchoscopy from 60 subjects: 30 subjects with COPD defined by spirometry (FEV1/FVC < 0.7, FEV1% < 80%), and 30 non-COPD controls. Targeted next generation sequencing was used to measure total and allele-specific expression of 35 genes in genome maintenance (GM) genes pathways linked to COPD pathogenesis, including seven TP53 and CEBP transcription factor family members. Shrinkage linear discriminant analysis (SLDA) was used to identify COPD-classification models. COPD GWAS were queried for putative cis-regulatory SNPs in the targeted genes.

Results

On a network basis, TP53 and CEBP transcription factor pathway gene pair network connections, including key DNA repair gene ERCC5, were significantly different in COPD subjects (e.g., Wilcoxon rank sum test for closeness, p-value = 5.0E-11). ERCC5 SNP rs4150275 association with chronic bronchitis was identified in a set of Lung Health Study (LHS) COPD GWAS SNPs restricted to those in putative regulatory regions within the targeted genes, and this association was validated in the COPDgene non-hispanic white (NHW) GWAS. ERCC5 SNP rs4150275 is linked (D’ = 1) to ERCC5 SNP rs17655 which displayed differential allelic expression (DAE) in BEC and is an expression quantitative trait locus (eQTL) in lung tissue (p = 3.2E-7). SNPs in linkage (D’ = 1) with rs17655 were predicted to alter miRNA binding (rs873601). A classifier model that comprised gene features CAT, CEBPG, GPX1, KEAP1, TP73, and XPA had pooled 10-fold cross-validation receiver operator characteristic area under the curve of 75.4% (95% CI: 66.3%–89.3%). The prevalence of DAE was higher than expected (p = 0.0023) in the classifier genes.

Conclusions

GM genes comprised by COPD-associated BEC expression patterns were enriched for SNPs with cis-regulatory function, including a putative cis-rSNP in ERCC5 that was associated with COPD risk. These findings support additional total and allele-specific expression analysis of gene pathways with high prior likelihood for involvement in COPD pathogenesis.

Electronic supplementary material

The online version of this article (10.1186/s12890-018-0603-y) contains supplementary material, which is available to authorized users.

Whole-Transcriptome Sequencing: a Powerful Tool for Vascular Tissue Engineering and Endothelial Mechanobiology

Among applicable high-throughput techniques in cardiovascular biology, whole-transcriptome sequencing is of particular use. By utilizing RNA that is isolated from virtually all cells and tissues, the entire transcriptome can be evaluated. In comparison with other high-throughput approaches, RNA sequencing is characterized by a relatively low-cost and large data output, which permits a comprehensive analysis of spatiotemporal variation in the gene expression profile. Both shear stress and cyclic strain exert hemodynamic force upon the arterial endothelium and are considered to be crucial determinants of endothelial physiology. Laminar blood flow results in a high shear stress that promotes atheroresistant endothelial phenotype, while a turbulent, oscillatory flow yields a pathologically low shear stress that disturbs endothelial homeostasis, making respective arterial segments prone to atherosclerosis. Severe atherosclerosis significantly impairs blood supply to the organs and frequently requires bypass surgery or an arterial replacement surgery that requires tissue-engineered vascular grafts. To provide insight into patterns of gene expression in endothelial cells in native or bioartificial arteries under different biomechanical conditions, this article discusses applications of whole-transcriptome sequencing in endothelial mechanobiology and vascular tissue engineering.

COPD: time to improve its taxonomy?

Due to well-conducted epidemiological studies and advances in genetics, molecular biology, translational research, the advent of computed tomography of the lungs and bioinformatics, the diagnosis of chronic obstructive pulmonary disease (COPD) as a single entity caused by susceptibility to cigarette smoke is no longer tenable. Furthermore, the once-accepted concept that COPD results from a rapid and progressive loss of lung function over time is not true for a sizeable proportion of adults with the disease. Now we know that some genetic predisposition and/or different environmental interactions (nutritional, infectious, pollution and immunological) may negatively modulate post-natal lung development and lead to poorly reversible airflow limitation later in life, consistent with COPD. We believe it is time to rethink the taxonomy of this disease based on the evidence at hand. To do so, we have followed the principles outlined in the 1980s by J.D. Scadding who proposed that diseases can be defined by four key characteristics: 1) clinical description (syndrome), 2) disorder of structure (morbid anatomy), 3) disorder of function (pathophysiology) and 4) causation (aetiology). Here, we propose a pragmatic approach to the taxonomy of COPD based on different processes that result in a similar syndromic presentation. It can accommodate changes over time, as the pathobiology that may lead to COPD expands. We hope that stakeholders in the field may find it useful to better define the patients now boxed into one single entity, so that specific studies can be designed and conducted for each type of COPDs.

Natural history of COPD: gaps and opportunities

Understanding the natural history of a disease is as important as knowing its cause(s) for effective disease prevention and treatment. Yet, our current understanding of the natural history of chronic obstructive pulmonary disease (COPD) is incomplete and often controversial. This article discusses the current gaps, and hence opportunities for research, in this field. In particular, it discusses the following six specific questions. 1) Is COPD a “single” disease? 2) Is COPD “only” a lung disease? 3) When does COPD begin or what is “early” COPD? 4) How does COPD “progress”? 5) How do we assess disease “severity”? 6) Can COPD be prevented (beyond smoking cessation) or its course be modified once detected?

A new review series starts in ERJ Open Research: “Gaps in our understanding of COPD”http://ow.ly/CFSD30gpXs8

What do polymorphisms tell us about the mechanisms of COPD?

COPD (chronic obstructive pulmonary disease) is characterized by irreversible lung airflow obstruction. Cigarette smoke is the major risk factor for COPD development. However, only a minority number of smokers develop COPD, and there are substantial variations in lung function among smokers, suggesting that genetic determinants in COPD susceptibility. During the past decade, genome-wide association studies and exome sequencing have been instrumental to identify the genetic determinants of complex traits, including COPD. Focused studies have revealed mechanisms by which genetic variants contribute to COPD and have led to novel insights in COPD pathogenesis. Through functional investigations of causal variants in COPD, from the proteinase-antiproteinase theory to emerging roles of developmental pathways (such as Hedgehog and Wnt pathways) in COPD, we have greatly expanded our understanding on this complex pulmonary disease. In this review, we critically review functional investigations on roles of genetic polymorphisms in COPD, and discuss future challenges and opportunities in discovering novel mechanisms of functional variants.

Using omics approaches to understand pulmonary diseases

Omics approaches are high-throughput unbiased technologies that provide snapshots of various aspects of biological systems and include: 1) genomics, the measure of DNA variation; 2) transcriptomics, the measure of RNA expression; 3) epigenomics, the measure of DNA alterations not involving sequence variation that influence RNA expression; 4) proteomics, the measure of protein expression or its chemical modifications; and 5) metabolomics, the measure of metabolite levels. Our understanding of pulmonary diseases has increased as a result of applying these omics approaches to characterize patients, uncover mechanisms underlying drug responsiveness, and identify effects of environmental exposures and interventions. As more tissue- and cell-specific omics data is analyzed and integrated for diverse patients under various conditions, there will be increased identification of key mechanisms that underlie pulmonary biological processes, disease endotypes, and novel therapeutics that are efficacious in select individuals. We provide a synopsis of how omics approaches have advanced our understanding of asthma, chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), idiopathic pulmonary fibrosis (IPF), and pulmonary arterial hypertension (PAH), and we highlight ongoing work that will facilitate pulmonary disease precision medicine.

Extreme Trait Whole-Genome Sequencing Identifies PTPRO as a Novel Candidate Gene in Emphysema with Severe Airflow Obstruction

RATIONALE

Genetic association studies in chronic obstructive pulmonary disease have primarily tested for association with common variants, the results of which explain only a portion of disease heritability. Because rare variation is also likely to contribute to susceptibility, we used whole-genome sequencing of subjects with clinically extreme phenotypes to identify genomic regions enriched for rare variation contributing to chronic obstructive pulmonary disease susceptibility.

OBJECTIVES

To identify regions of rare genetic variation contributing to emphysema with severe airflow obstruction.

METHODS

We identified heavy smokers that were resistant (n = 65) or susceptible (n = 64) to emphysema with severe airflow obstruction in the Pittsburgh Specialized Center of Clinically Oriented Research cohort. We filtered whole-genome sequencing results to include only rare variants and conducted single variant tests, region-based tests across the genome, gene-based tests, and exome-wide tests.

MEASUREMENTS AND MAIN RESULTS

We identified several suggestive associations with emphysema with severe airflow obstruction, including a suggestive association of all rare variation in a region within the gene ZNF816 (19q13.41; P = 4.5 × 10^-6), and a suggestive association of nonsynonymous coding rare variation in the gene PTPRO (P = 4.0 × 10^-5). Association of rs61754411, a rare nonsynonymous variant in PTPRO, with emphysema and obstruction was demonstrated in all non-Hispanic white individuals in the Pittsburgh Specialized Center of Clinically Oriented Research cohort. We found that cells containing this variant have decreased signaling in cellular pathways necessary for survival and proliferation.

CONCLUSIONS

PTPRO is a novel candidate gene in emphysema with severe airflow obstruction, and rs61754411 is a previously unreported rare variant contributing to emphysema susceptibility. Other suggestive candidate genes, such as ZNF816, are of interest for future studies.

Genome-wide association study of subclinical interstitial lung disease in MESA

Background

We conducted a genome-wide association study (GWAS) of subclinical interstitial lung disease (ILD), defined as high attenuation areas (HAA) on CT, in the population-based Multi-Ethnic Study of Atherosclerosis Study.

Methods

We measured the percentage of high attenuation areas (HAA) in the lung fields on cardiac CT scan defined as voxels with CT attenuation values between -600 and -250 HU. Genetic analyses were performed in MESA combined across race/ethnic groups: non-Hispanic White (n = 2,434), African American (n = 2,470), Hispanic (n = 2,065) and Chinese (n = 702), as well as stratified by race/ethnicity.

Results

Among 7,671 participants, regions at genome-wide significance were identified for basilar peel-core ratio of HAA in FLJ35282 downstream of ANRIL (rs7852363, P = 2.1x10⁻⁹) and within introns of SNAI3-AS1 (rs140142658, P = 9.6x10⁻⁹) and D21S2088E (rs3079677, P = 2.3x10⁻⁸). Within race/ethnic groups, 18 additional loci were identified at genome-wide significance, including genes related to development (FOXP4), cell adhesion (ALCAM) and glycosylation (GNPDA2, GYPC, GFPT1 and FUT10). Among these loci, SNP rs6844387 near GNPDA2 demonstrated nominal evidence of replication in analysis of n = 1,959 participants from the Framingham Heart Study (P = 0.029). FOXP4 region SNP rs2894439 demonstrated evidence of validation in analysis of n = 228 White ILD cases from the Columbia ILD Study compared to race/ethnicity-matched controls from MESA (one-sided P = 0.007). In lung tissue from 15 adults with idiopathic pulmonary fibrosis compared to 15 adults without lung disease. ANRIL (P = 0.001), ALCAM (P = 0.03) and FOXP4 (P = 0.046) were differentially expressed.

Conclusions

Our results suggest novel roles for protein glycosylation and cell cycle disinhibition by long non-coding RNA in the pathogenesis of ILD.

Electronic supplementary material

The online version of this article (doi:10.1186/s12931-017-0581-2) contains supplementary material, which is available to authorized users.

Gene-based segregation method for identifying rare variants in family-based sequencing studies

Whole-exome sequencing using family data has identified rare coding variants in Mendelian diseases or complex diseases with Mendelian subtypes, using filters based on variant novelty, functionality, and segregation with the phenotype within families. However, formal statistical approaches are limited. We propose a gene-based segregation test (GESE) that quantifies the uncertainty of the filtering approach. It is constructed using the probability of segregation events under the null hypothesis of Mendelian transmission. This test takes into account different degrees of relatedness in families, the number of functional rare variants in the gene, and their minor allele frequencies in the corresponding population. In addition, a weighted version of this test allows incorporating additional subject phenotypes to improve statistical power. We show via simulations that the GESE and weighted GESE tests maintain appropriate type I error rate, and have greater power than several commonly used region-based methods. We apply our method to whole-exome sequencing data from 49 extended pedigrees with severe, early-onset chronic obstructive pulmonary disease (COPD) in the Boston Early-Onset COPD study (BEOCOPD) and identify several promising candidate genes. Our proposed methods show great potential for identifying rare coding variants of large effect and high penetrance for family-based sequencing data. The proposed tests are implemented in an R package that is available on CRAN (https://cran.r-project.org/web/packages/GESE/).

Boosting Gene Mapping Power and Efficiency with Efficient Exact Variance Component Tests of Single Nucleotide Polymorphism Sets

Single nucleotide polymorphism (SNP) set tests have been a powerful method in analyzing next-generation sequencing (NGS) data. The popular sequence kernel association test (SKAT) method tests a set of variants as random effects in the linear mixed model setting. Its P-value is calculated based on asymptotic theory that requires a large sample size. Therefore, it is known that SKAT is conservative and can lose power at small or moderate sample sizes. Given the current cost of sequencing technology, scales of NGS are still limited. In this report, we derive and implement computationally efficient, exact (nonasymptotic) score (eScore), likelihood ratio (eLRT), and restricted likelihood ratio (eRLRT) tests, ExactVCTest, that can achieve high power even when sample sizes are small. We perform simulation studies under various genetic scenarios. Our ExactVCTest (i.e., eScore, eLRT, eRLRT) exhibits well-controlled type I error. Under the alternative model, eScore P-values are universally smaller than those from SKAT. eLRT and eRLRT demonstrate significantly higher power than eScore, SKAT, and SKAT optimal (SKAT-o) across all scenarios and various samples sizes. We applied these tests to an exome sequencing study. Our findings replicate previous results and shed light on rare variant effects within genes. The software package is implemented in the open source, high-performance technical computing language Julia, and is freely available at https://github.com/Tao-Hu/VarianceComponentTest.jl Analysis of each trait in the exome sequencing data set with 399 individuals and 16,619 genes takes around 1 min on a desktop computer.

Increasing Generality and Power of Rare-Variant Tests by Utilizing Extended Pedigrees

Recently, multiple studies have performed whole-exome or whole-genome sequencing to identify groups of rare variants associated with complex traits and diseases. They have primarily utilized case-control study designs that often require thousands of individuals to reach acceptable statistical power. Family-based studies can be more powerful because a rare variant can be enriched in an extended pedigree and segregate with the phenotype. Although many methods have been proposed for using family data to discover rare variants involved in a disease, a majority of them focus on a specific pedigree structure and are designed to analyze either binary or continuously measured outcomes. In this article, we propose RareIBD, a general and powerful approach to identifying rare variants involved in disease susceptibility. Our method can be applied to large extended families of arbitrary structure, including pedigrees with only affected individuals. The method accommodates both binary and quantitative traits. A series of simulation experiments suggest that RareIBD is a powerful test that outperforms existing approaches. In addition, our method accounts for individuals in top generations, which are not usually genotyped in extended families. In contrast to available statistical tests, RareIBD generates accurate p values even when genetic data from these individuals are missing. We applied RareIBD, as well as other methods, to two extended family datasets generated by different genotyping technologies and representing different ethnicities. The analysis of real data confirmed that RareIBD is the only method that properly controls type I error.