Shared genetic and experimental links between obesity-related traits and asthma subtypes in UK Biobank

Zhu, Zhaozhong; Guo, Yanjun; Shi, Huwenbo; Liu, Cong-Lin; Panganiban, Ronald Allan M; Chung, Wonil; O’Connor, Luke; Himes, Blanca E.; Gazal, Steven; Hasegawa, Kohei; Camargo, Carlos A.; Qi, Lü; Moffatt, Miriam F.; Hu, Frank B.; Lu, Quan; Cookson, William; Liang, Liming

doi:10.1016/j.jaci.2019.09.035

Cited by 278 publications

(271 citation statements)

References 80 publications

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“…In this review, we have summarized the current status of cross-trait genetics studies for the shared and distinct genetic effects between asthma subtypes and their shared genetics with coexistent diseases or traits. 12,[19][20][21][22][26][27][28][29]31 We have surveyed a broad range of major analytic methods at each phase of the genome-wide cross-trait analysis, namely, genetic correlation, cross-trait meta-analysis, Mendelian randomization, polygenic risk score, and functional analysis. We have also discussed scientific goals for each phase, as well as the advantages and limitations for these methods.…”

Section: Discussion and Future Directionsmentioning

confidence: 99%

“…19,20 These fundamental studies largely depend on single-trait analysis, and they can be further extended by our recently implemented study design called genome-wide cross-trait analysis, which is broadly applicable to asthma and many other diseases and/or traits. The design has been successfully applied to the UK Biobank and GWAS consortia data sets and has determined the shared genetic architectures between asthma and allergic diseases, 22 obesity, 12 and mental health disorders, 21 which were reproducible in other studies. [26][27][28][29] A genome-wide cross-trait analysis features several analyses: genetic correlation, cross-trait meta-analysis, Mendelian randomization, polygenic risk score, and GWAS functional analysis.…”

Section: Genome-wide Cross-trait Analysis Study Designmentioning

confidence: 99%

“…Finally, in the cross-trait analysis of obesity and asthma, CPASSOC has been used to determine potential shared loci and variations in MYL6 and ACOXL and replicated them in a mouse model. 12 Many cross-trait effects are not surprising. For example, variants in the C11orf30, IL1R1, and FLG genes, as well as in the HLA region, are associated with allergic diseases and asthma, 22 as was found in previous studies with individual traits.…”

Section: Cross-trait Meta-analysismentioning

confidence: 99%

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Investigating asthma heterogeneity through shared and distinct genetics: Insights from genome-wide cross-trait analysis

Zhu

Hasegawa

Camargo

et al. 2021

Journal of Allergy and Clinical Immunology

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Asthma is a heterogeneous respiratory disease reflecting distinct pathobiologic mechanisms. These mechanisms are based, at least partly, on different genetic factors shared by many other conditions, such as allergic diseases and obesity. Investigating the shared genetic effects enables better understanding of the mechanisms of phenotypic correlations and is less subject to confounding by environmental factors. The increasing availability of large-scale genome-wide association study (GWAS) for asthma has enabled researchers to examine the genetic contributions to the epidemiologic associations between asthma subtypes and those between coexisting diseases and/or traits and asthma. Studies have found not only shared but also distinct genetic components between asthma subtypes, indicating that the heterogeneity is related to distinct genetics. This review summarizes a recently compiled analytic approach-genome-wide cross-trait analysis-to determine shared and distinct genetic architecture. The genome-wide cross-trait analysis features in several analytic aspects: genetic correlation, cross-trait meta-analysis, Mendelian randomization, polygenic risk score, and functional analysis. In this article, we discuss in detail the scientific goals that can be achieved by these analyses, their advantages, and their limitations. We also make recommendations for future directions: (1) ethnicity-specific asthma GWASs and (2) application of cross-trait methods to multiomics data to dissect the heritability found in GWASs. Finally, these analytic approaches are also applicable to complex and heterogeneous traits beyond asthma. (J Allergy Clin Immunol 2020;nnn:nnnnnn.)

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Section: Discussion and Future Directionsmentioning

confidence: 99%

Section: Genome-wide Cross-trait Analysis Study Designmentioning

confidence: 99%

Section: Cross-trait Meta-analysismentioning

confidence: 99%

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Investigating asthma heterogeneity through shared and distinct genetics: Insights from genome-wide cross-trait analysis

Zhu

Hasegawa

Camargo

et al. 2021

Journal of Allergy and Clinical Immunology

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“…After this study was performed, new GWASs and functional annotation analysis have been published with new interesting asthma loci such as TNF receptor superfamily member 8 ( TNFRSF8 ) [ 143 ], and Collagen Type XVI Alpha 1 Chain ( COL16A1 ) [ 147 ], and more studies are to come. This is indeed very important since further functional activity experiments of candidate genes are still needed to understand the dynamic molecular events behind the pathogenesis of airway diseases.…”

Section: Therapeutic Implications and Future Prospectsmentioning

confidence: 99%

Genomics of asthma, allergy and chronic rhinosinusitis: novel concepts and relevance in airway mucosa

Laulajainen‐Hongisto

Lyly

Hanif

et al. 2020

Clin Transl Allergy

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Genome wide association studies (GWASs) have revealed several airway disease-associated risk loci. Their role in the onset of asthma, allergic rhinitis (AR) or chronic rhinosinusitis (CRS), however, is not yet fully understood. The aim of this review is to evaluate the airway relevance of loci and genes identified in GWAS studies. GWASs were searched from databases, and a list of loci associating significantly (p < 10–8) with asthma, AR and CRS was created. This yielded a total of 267 significantly asthma/AR–associated loci from 31 GWASs. No significant CRS -associated loci were found in this search. A total of 170 protein coding genes were connected to these loci. Of these, 76/170 (44%) showed bronchial epithelial protein expression in stained microscopic figures of Human Protein Atlas (HPA), and 61/170 (36%) had a literature report of having airway epithelial function. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation analyses were performed, and 19 functional protein categories were found as significantly (p < 0.05) enriched among these genes. These were related to cytokine production, cell activation and adaptive immune response, and all were strongly connected in network analysis. We also identified 15 protein pathways that were significantly (p < 0.05) enriched in these genes, related to T-helper cell differentiation, virus infection, JAK-STAT signaling pathway, and asthma. A third of GWAS-level risk loci genes of asthma or AR seemed to have airway epithelial functions according to our database and literature searches. In addition, many of the risk loci genes were immunity related. Some risk loci genes also related to metabolism, neuro-musculoskeletal or other functions. Functions overlapped and formed a strong network in our pathway analyses and are worth future studies of biomarker and therapeutics.

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“…9 Interestingly, this individual was also noted to be obese (a common feature of ciliopathy syndromes); the CLUAP1 locus has been published as associated with BMI and type 2 diabetes in previous GWAS studies. [37][38][39][40]…”

Section: Cluap1mentioning

confidence: 99%

Mendelian pathway analysis of laboratory traits reveals distinct roles for ciliary subcompartments in common disease pathogenesis

Drivas

Lucas

Zhang

et al. 2020

Preprint

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SummaryRare monogenic disorders of the primary cilium, termed ciliopathies, are characterized by extreme presentations of otherwise-common diseases, such as diabetes, hepatic fibrosis, and kidney failure. However, despite a revolution in our understanding of the cilium’s role in rare disease pathogenesis, the organelle’s contribution to common disease remains largely unknown. We hypothesized that common genetic variants affecting Mendelian ciliopathy genes might also contribute to common complex diseases pathogenesis more generally. To address this question, we performed association studies of 16,875 common genetic variants across 122 well-characterized ciliary genes with 12 quantitative laboratory traits characteristic of ciliopathy syndromes in 378,213 European-ancestry individuals in the UK BioBank. We incorporated tissue-specific gene expression analysis, expression quantitative trait loci (eQTL) and Mendelian disease information into our analysis, and replicated findings in meta-analysis to increase our confidence in observed associations between ciliary genes and human phenotypes. 73 statistically-significant gene-trait associations were identified across 34 of the 122 ciliary genes that we examined (including 8 novel, replicating associations). With few exceptions, these ciliary genes were found to be widely expressed in human tissues relevant to the phenotypes being studied, and our eQTL analysis revealed strong evidence for correlation between ciliary gene expression levels and patient phenotypes. Perhaps most interestingly our analysis identified different ciliary subcompartments as being specifically associated with distinct sets of patient phenotypes, offering a number of testable hypotheses regarding the cilium’s role in common complex disease. Taken together, our data demonstrate the utility of a Mendelian pathway-based approach to genomic association studies, and challenge the widely-held belief that the cilium is an organelle important mainly in development and in rare syndromic disease pathogenesis. The continued application of techniques similar to those described here to other phenotypes/Mendelian diseases is likely to yield many additional fascinating associations that will begin to integrate the fields of common and rare disease genetics, and provide insight into the pathophysiology of human diseases of immense public health burden.Contacttheodore.drivas@gmail.com

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Shared genetic and experimental links between obesity-related traits and asthma subtypes in UK Biobank

Cited by 278 publications

References 80 publications

Investigating asthma heterogeneity through shared and distinct genetics: Insights from genome-wide cross-trait analysis

Investigating asthma heterogeneity through shared and distinct genetics: Insights from genome-wide cross-trait analysis

Genomics of asthma, allergy and chronic rhinosinusitis: novel concepts and relevance in airway mucosa

Mendelian pathway analysis of laboratory traits reveals distinct roles for ciliary subcompartments in common disease pathogenesis

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