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1.
Chest ; 2019 Sep 23.
Artigo em Inglês | MEDLINE | ID: mdl-31557467

RESUMO

BACKGROUND: Asthma is a common respiratory disorder with a highly heterogeneous nature that remains poorly understood. The objective was to use whole genome sequencing (WGS) data to identify regions of common genetic variation contributing to lung function in individuals with a diagnosis of asthma. METHODS: WGS data were generated for 1,053 individuals from trios and extended pedigrees participating in the family-based Genetic Epidemiology of Asthma in Costa Rica study. The degree to which participants were affected by asthma was defined through a physician's diagnosis of asthma, and most participants with asthma also had airway hyperresponsiveness (AHR) to methacholine. Family-based association tests for single variants were performed to assess the associations with lung function phenotypes. RESULTS: A plausible association was identified between baseline FEV1/FVC ratio and a single-nucleotide polymorphism in the top hit cysteine-rich secretory protein LCCL domain-containing 2 (CRISPLD2) (rs12051168; P = 3.6 × 10-8 in the unadjusted model) that retained suggestive significance in the covariate-adjusted model (P = 5.6 × 10-6). Rs12051168 was also nominally associated with other related phenotypes: baseline FEV1 (P = 3.3 × 10-3), postbronchodilator (PB) FEV1 (7.3 × 10-3), and PB FEV1/FVC ratio (P = 2.7 × 10-3). The identified baseline FEV1/FVC ratio and rs12051168 association was meta-analyzed and replicated in three independent cohorts in which most participants with asthma also had confirmed AHR (combined weighted z-score P = .015) but not in cohorts without information about AHR. CONCLUSIONS: These findings suggest that using specific asthma characteristics, such as AHR, can help identify more genetically homogeneous asthma subgroups with genotype-phenotype associations that may not be observed in all children with asthma. CRISPLD2 also may be important for baseline lung function in individuals with asthma who also may have AHR.

2.
Nat Genet ; 51(3): 494-505, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30804561

RESUMO

Chronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide new 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 associated with P < 5 × 10-8; 47 of these were previously described in association with either COPD or population-based measures of lung function. Of the remaining 35 new loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified functional enrichment of COPD risk 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 based on associations with quantitative imaging features and comorbidities. Our analyses provide further support for the genetic susceptibility and heterogeneity of COPD.


Assuntos
Predisposição Genética para Doença/genética , Doença Pulmonar Obstrutiva Crônica/genética , Adulto , Idoso , Asma/genética , Estudos de Casos e Controles , Feminino , Expressão Gênica/genética , Loci Gênicos/genética , Estudo de Associação Genômica Ampla/métodos , Humanos , Pulmão/fisiopatologia , Masculino , Pessoa de Meia-Idade , Fenótipo , Polimorfismo de Nucleotídeo Único/genética , Fibrose Pulmonar/genética , Fumar/genética
3.
Artigo em Inglês | MEDLINE | ID: mdl-30079747

RESUMO

RATIONALE: The identification of causal variants responsible for disease associations from genome-wide association studies (GWAS) facilitates functional understanding of the biological mechanisms by which those genetic variants influence disease susceptibility. OBJECTIVE: We aim to identify causal variants in or near the FAM13A GWAS locus associated with COPD. METHODS: We used an integrated approach featuring conditional genetic analysis, massively parallel reporter assays (MPRA), traditional reporter assays, chromatin conformation capture assays, and CRISPR-based gene editing to characterize COPD-associated regulatory variants in the FAM13A region in human bronchial epithelial cell lines. MEASUREMENTS AND MAIN RESULTS: Conditional genetic association suggests the presence of two independent COPD association signals in FAM13A. MPRA identified 45 regulatory variants within FAM13A, among which six variants were prioritized for further investigation. Three COPD-associated variants demonstrated significant allele-specific activity in reporter assays. One of three variants, rs2013701, was tested in the endogenous genomic context by CRISPR-based genome editing that confirmed its allele-specific effects on FAM13A expression and on cell proliferation, providing functional characterization for this COPD-associated variant. CONCLUSIONS: The human GWAS association near FAM13A may contain independent association signals. MPRA identified multiple functional variants in this region, including rs2013701, a putative COPD-causing variant with allele-specific regulatory activity.

4.
Hum Mol Genet ; 27(21): 3801-3812, 2018 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-30060175

RESUMO

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.

5.
J Thorac Oncol ; 13(10): 1483-1495, 2018 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-29981437

RESUMO

BACKGROUND: Genome-wide association studies are widely used to map genomic regions contributing to lung cancer (LC) susceptibility, but they typically do not identify the precise disease-causing genes/variants. To unveil the inherited genetic variants that cause LC, we performed focused exome-sequencing analyses on genes located in 121 genome-wide association study-identified loci previously implicated in the risk of LC, chronic obstructive pulmonary disease, pulmonary function level, and smoking behavior. METHODS: Germline DNA from 260 case patients with LC and 318 controls were sequenced by utilizing VCRome 2.1 exome capture. Filtering was based on enrichment of rare and potential deleterious variants in cases (risk alleles) or controls (protective alleles). Allelic association analyses of single-variant and gene-based burden tests of multiple variants were performed. Promising candidates were tested in two independent validation studies with a total of 1773 case patients and 1123 controls. RESULTS: We identified 48 rare variants with deleterious effects in the discovery analysis and validated 12 of the 43 candidates that were covered in the validation platforms. The top validated candidates included one well-established truncating variant, namely, BRCA2, DNA repair associated gene (BRCA2) K3326X (OR = 2.36, 95% confidence interval [CI]: 1.38-3.99), and three newly identified variations, namely, lymphotoxin beta gene (LTB) p.Leu87Phe (OR = 7.52, 95% CI: 1.01-16.56), prolyl 3-hydroxylase 2 gene (P3H2) p.Gln185His (OR = 5.39, 95% CI: 0.75-15.43), and dishevelled associated activator of morphogenesis 2 gene (DAAM2) p.Asp762Gly (OR = 0.25, 95% CI: 0.10-0.79). Burden tests revealed strong associations between zinc finger protein 93 gene (ZNF93), DAAM2, bromodomain containing 9 gene (BRD9), and the gene LTB and LC susceptibility. CONCLUSION: Our results extend the catalogue of regions associated with LC and highlight the importance of germline rare coding variants in LC susceptibility.

6.
Sci Rep ; 8(1): 9319, 2018 Jun 18.
Artigo em Inglês | MEDLINE | ID: mdl-29915320

RESUMO

Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on lung function using Korea Associated Resource (KARE) data with the spirometric variables-forced expiratory volume in 1 s (FEV1). We found that variations in FEV1 were different among smoking status. Thus, we considered a linear mixed model for association analysis under heteroscedasticity according to smoking status. We found a previously identified locus near SOX9 on chromosome 17 to be the most significant based on a joint test of the main and interaction effects of smoking. Smoking interactions were replicated with Gene-Environment of Interaction and phenotype (GENIE), Multi-Ethnic Study of Atherosclerosis-Lung (MESA-Lung), and COPDGene studies. We found that individuals with minor alleles, rs17765644, rs17178251, rs11870732, and rs4793541, tended to have lower FEV1 values, and lung function decreased much faster with age for smokers. There have been very few reports to replicate a common variant gene-smoking interaction, and our results revealed that statistical models for gene-smoking interaction analyses should be carefully selected.

7.
Am J Respir Cell Mol Biol ; 59(5): 614-622, 2018 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-29949718

RESUMO

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.

8.
Front Genet ; 9: 133, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29725345

RESUMO

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.

9.
BMC Med Genomics ; 11(Suppl 2): 39, 2018 Apr 20.
Artigo em Inglês | MEDLINE | ID: mdl-29697360

RESUMO

BACKGROUND: A Mendelian transmission produces phenotypic and genetic relatedness between family members, giving family-based analytical methods an important role in genetic epidemiological studies-from heritability estimations to genetic association analyses. With the advance in genotyping technologies, whole-genome sequence data can be utilized for genetic epidemiological studies, and family-based samples may become more useful for detecting de novo mutations. However, genetic analyses employing family-based samples usually suffer from the complexity of the computational/statistical algorithms, and certain types of family designs, such as incorporating data from extended families, have rarely been used. RESULTS: We present a Workbench for Integrated Superfast Association studies for Related Data (WISARD) programmed in C/C++. WISARD enables the fast and a comprehensive analysis of SNP-chip and next-generation sequencing data on extended families, with applications from designing genetic studies to summarizing analysis results. In addition, WISARD can automatically be run in a fully multithreaded manner, and the integration of R software for visualization makes it more accessible to non-experts. CONCLUSIONS: Comparison with existing toolsets showed that WISARD is computationally suitable for integrated analysis of related subjects, and demonstrated that WISARD outperforms existing toolsets. WISARD has also been successfully utilized to analyze the large-scale massive sequencing dataset of chronic obstructive pulmonary disease data (COPD), and we identified multiple genes associated with COPD, which demonstrates its practical value.

10.
Stat Med ; 36(13): 2081-2099, 2017 06 15.
Artigo em Inglês | MEDLINE | ID: mdl-28222494

RESUMO

Recent improvements in sequencing technology have enabled the investigation of so-called missing heritability, and a large number of affected subjects have been sequenced in order to detect significant associations between human diseases and rare variants. However, the cost of genome sequencing is still high, and a statistically powerful strategy for selecting informative subjects would be useful. Therefore, in this report, we propose a new statistical method for selecting cases and controls for sequencing studies based on family history. We assume that disease status is determined by unobserved liability scores. Our method consists of two steps: first, the conditional means of liability are estimated with the liability threshold model given the individual's disease status and those of their relatives. Second, the informative subjects are selected with the estimated conditional means. Our simulation studies showed that statistical power is substantially affected by the subject selection strategy chosen, and power is maximized when affected (unaffected) subjects with high (low) risks are selected as cases (controls). The proposed method was successfully applied to genome-wide association studies for type 2 diabetes, and our analysis results reveal the practical value of the proposed methods. Copyright © 2017 John Wiley & Sons, Ltd.


Assuntos
Estudos de Casos e Controles , Predisposição Genética para Doença/genética , Anamnese , Seleção de Pacientes , Análise de Sequência de DNA , Adulto , Diabetes Mellitus Tipo 2/genética , Feminino , Frequência do Gene/genética , Estudo de Associação Genômica Ampla/métodos , Estudo de Associação Genômica Ampla/estatística & dados numéricos , Humanos , Masculino , Anamnese/métodos , Modelos Estatísticos , Linhagem , República da Coreia , Fatores de Risco , Análise de Sequência de DNA/métodos
11.
Genet Epidemiol ; 41(4): 309-319, 2017 05.
Artigo em Inglês | MEDLINE | ID: mdl-28191685

RESUMO

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/).


Assuntos
Variação Genética , Doença Pulmonar Obstrutiva Crônica/genética , Análise de Sequência de DNA/métodos , Idade de Início , Boston , Simulação por Computador , Bases de Dados Genéticas , Família , Genoma Humano , Humanos , Modelos Genéticos , Penetrância , Padrões de Referência
12.
Genetics ; 204(3): 921-931, 2016 11.
Artigo em Inglês | MEDLINE | ID: mdl-27646141

RESUMO

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.


Assuntos
Mapeamento de Sequências Contíguas/métodos , Polimorfismo de Nucleotídeo Único , Software , Exoma , Humanos
13.
Am J Hum Genet ; 99(4): 846-859, 2016 Oct 06.
Artigo em Inglês | MEDLINE | ID: mdl-27666371

RESUMO

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.


Assuntos
Família , Predisposição Genética para Doença/genética , Variação Genética/genética , Linhagem , Conjuntos de Dados como Assunto , Grupos Étnicos/genética , Feminino , Genótipo , Humanos , Masculino , Modelos Genéticos , Fenótipo , Projetos de Pesquisa
14.
Genet Epidemiol ; 40(6): 502-11, 2016 09.
Artigo em Inglês | MEDLINE | ID: mdl-27312886

RESUMO

Family-based designs have been repeatedly shown to be powerful in detecting the significant rare variants associated with human diseases. Furthermore, human diseases are often defined by the outcomes of multiple phenotypes, and thus we expect multivariate family-based analyses may be very efficient in detecting associations with rare variants. However, few statistical methods implementing this strategy have been developed for family-based designs. In this report, we describe one such implementation: the multivariate family-based rare variant association tool (mFARVAT). mFARVAT is a quasi-likelihood-based score test for rare variant association analysis with multiple phenotypes, and tests both homogeneous and heterogeneous effects of each variant on multiple phenotypes. Simulation results show that the proposed method is generally robust and efficient for various disease models, and we identify some promising candidate genes associated with chronic obstructive pulmonary disease. The software of mFARVAT is freely available at http://healthstat.snu.ac.kr/software/mfarvat/, implemented in C++ and supported on Linux and MS Windows.


Assuntos
Variação Genética , Modelos Genéticos , Simulação por Computador , Estudos de Associação Genética , Humanos , Funções Verossimilhança , Fenótipo
15.
Genet Epidemiol ; 40(6): 475-85, 2016 09.
Artigo em Inglês | MEDLINE | ID: mdl-27325607

RESUMO

Although the X chromosome has many genes that are functionally related to human diseases, the complicated biological properties of the X chromosome have prevented efficient genetic association analyses, and only a few significantly associated X-linked variants have been reported for complex traits. For instance, dosage compensation of X-linked genes is often achieved via the inactivation of one allele in each X-linked variant in females; however, some X-linked variants can escape this X chromosome inactivation. Efficient genetic analyses cannot be conducted without prior knowledge about the gene expression process of X-linked variants, and misspecified information can lead to power loss. In this report, we propose new statistical methods for rare X-linked variant genetic association analysis of dichotomous phenotypes with family-based samples. The proposed methods are computationally efficient and can complete X-linked analyses within a few hours. Simulation studies demonstrate the statistical efficiency of the proposed methods, which were then applied to rare-variant association analysis of the X chromosome in chronic obstructive pulmonary disease. Some promising significant X-linked genes were identified, illustrating the practical importance of the proposed methods.


Assuntos
Genes Ligados ao Cromossomo X , Modelos Genéticos , Alelos , Cromossomos Humanos X , Feminino , Variação Genética , Humanos , Linhagem , Fenótipo , Inativação do Cromossomo X
16.
Am J Respir Crit Care Med ; 194(1): 48-57, 2016 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-26771213

RESUMO

RATIONALE: Chronic obstructive pulmonary disease (COPD) susceptibility is in part related to genetic variants. Most genetic studies have been focused on genome-wide common variants without a specific focus on coding variants, but common and rare coding variants may also affect COPD susceptibility. OBJECTIVES: To identify coding variants associated with COPD. METHODS: We tested nonsynonymous, splice, and stop variants derived from the Illumina HumanExome array for association with COPD in five study populations enriched for COPD. We evaluated single variants with a minor allele frequency greater than 0.5% using logistic regression. Results were combined using a fixed effects meta-analysis. We replicated novel single-variant associations in three additional COPD cohorts. MEASUREMENTS AND MAIN RESULTS: We included 6,004 control subjects and 6,161 COPD cases across five cohorts for analysis. Our top result was rs16969968 (P = 1.7 × 10(-14)) in CHRNA5, a locus previously associated with COPD susceptibility and nicotine dependence. Additional top results were found in AGER, MMP3, and SERPINA1. A nonsynonymous variant, rs181206, in IL27 (P = 4.7 × 10(-6)) was just below the level of exome-wide significance but attained exome-wide significance (P = 5.7 × 10(-8)) when combined with results from other cohorts. Gene expression datasets revealed an association of rs181206 and the surrounding locus with expression of multiple genes; several were differentially expressed in COPD lung tissue, including TUFM. CONCLUSIONS: In an exome array analysis of COPD, we identified nonsynonymous variants at previously described loci and a novel exome-wide significant variant in IL27. This variant is at a locus previously described in genome-wide associations with diabetes, inflammatory bowel disease, and obesity and appears to affect genes potentially related to COPD pathogenesis.


Assuntos
Exoma/genética , Predisposição Genética para Doença/genética , Interleucina-27/genética , Doença Pulmonar Obstrutiva Crônica/genética , Adulto , Idoso , Feminino , Frequência do Gene/genética , Humanos , Masculino , Pessoa de Meia-Idade
17.
Am J Respir Crit Care Med ; 193(12): 1353-63, 2016 06 15.
Artigo em Inglês | MEDLINE | ID: mdl-26736064

RESUMO

RATIONALE: Genomic regions identified by genome-wide association studies explain only a small fraction of heritability for chronic obstructive pulmonary disease (COPD). Alpha-1 antitrypsin deficiency shows that rare coding variants of large effect also influence COPD susceptibility. We hypothesized that exome sequencing in families identified through a proband with severe, early-onset COPD would identify additional rare genetic determinants of large effect. OBJECTIVES: To identify rare genetic determinants of severe COPD. METHODS: We applied filtering approaches to identify potential causal variants for COPD in whole exomes from 347 subjects in 49 extended pedigrees from the Boston Early-Onset COPD Study. We assessed the power of this approach under different levels of genetic heterogeneity using simulations. We tested genes identified in these families using gene-based association tests in exomes of 204 cases with severe COPD and 195 resistant smokers from the COPDGene study. In addition, we examined previously described loci associated with COPD using these datasets. MEASUREMENTS AND MAIN RESULTS: We identified 69 genes with predicted deleterious nonsynonymous, stop, or splice variants that segregated with severe COPD in at least two pedigrees. Four genes (DNAH8, ALCAM, RARS, and GBF1) also demonstrated an increase in rare nonsynonymous, stop, and/or splice mutations in cases compared with resistant smokers from the COPDGene study; however, these results were not statistically significant. We demonstrate the limitations of the power of this approach under genetic heterogeneity through simulation. CONCLUSIONS: Rare deleterious coding variants may increase risk for COPD, but multiple genes likely contribute to COPD susceptibility.


Assuntos
Exoma/genética , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla/métodos , Doença Pulmonar Obstrutiva Crônica/genética , Deficiência de alfa 1-Antitripsina/genética , Adulto , Boston , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Índice de Gravidade de Doença
19.
Am J Hum Genet ; 95(5): 553-64, 2014 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-25439724

RESUMO

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).


Assuntos
Genética Populacional/métodos , Linhagem , Doença Pulmonar Obstrutiva Crônica/genética , Software , Sequência de Bases , Simulação por Computador , Exoma/genética , Frequência do Gene , Humanos , Dados de Sequência Molecular , Análise de Sequência de DNA , Texas
20.
BMC Proc ; 8(Suppl 1 Genetic Analysis Workshop 18Vanessa Olmo): S33, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-25519381

RESUMO

The revolution in next-generation sequencing has made obtaining both common and rare high-quality sequence variants across the entire genome feasible. Because researchers are now faced with the analytical challenges of handling a massive amount of genetic variant information from sequencing studies, numerous methods have been developed to assess the impact of both common and rare variants on disease traits. In this report, whole genome sequencing data from Genetic Analysis Workshop 18 was used to compare the power of several methods, considering both family-based and population-based designs, to detect association with variants in the MAP4 gene region and on chromosome 3 with blood pressure. To prioritize variants across the genome for testing, variants were first functionally assessed using prediction algorithms and expression quantitative trait loci (eQTLs) data. Four set-based tests in the family-based association tests (FBAT) framework--FBAT-v, FBAT-lmm, FBAT-m, and FBAT-l--were used to analyze 20 pedigrees, and 2 variance component tests, sequence kernel association test (SKAT) and genome-wide complex trait analysis (GCTA), were used with 142 unrelated individuals in the sample. Both set-based and variance-component-based tests had high power and an adequate type I error rate. Of the various FBATs, FBAT-l demonstrated superior performance, indicating the potential for it to be used in rare-variant analysis. The updated FBAT package is available at: http://www.hsph.harvard.edu/fbat/.

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