TY - JOUR
T1 - Discerning asthma endotypes through comorbidity mapping
AU - Jia, Gengjie
AU - Zhong, Xue
AU - Im, Hae Kyung
AU - Schoettler, Nathan
AU - Pividori, Milton
AU - Hogarth, D. Kyle
AU - Sperling, Anne I.
AU - White, Steven R.
AU - Naureckas, Edward T.
AU - Lyttle, Christopher S.
AU - Terao, Chikashi
AU - Kamatani, Yoichiro
AU - Akiyama, Masato
AU - Matsuda, Koichi
AU - Kubo, Michiaki
AU - Cox, Nancy J.
AU - Ober, Carole
AU - Rzhetsky, Andrey
AU - Solway, Julian
N1 - Funding Information:
J.S. reports grants from NIH, during the conduct of the study; grants from NIH, personal fees from PulmOne Advanced Medical Devices, Ltd, Israel, personal fees and non-financial support from Regeneron/Sanofi-Genzyme, grants from Chicago Biomedical Consortium Accelerator Network, outside the submitted work; in addition, J.S. has US Patents #6,090,618, #6,114,311, #6,284,743, #6,291,211, #6,297,221, #6,331,527, #7,169,764 issued, and two patent applications (WO2020206109 and WO2020206118) pending. The other authors declare no competing interests. S.W. reports grants from NIH during the conduct of the study; grants from NIH and personal fees from Regeneron/Sanofi-Genzyme and Astra-Zeneca, outside the submitted work.
Funding Information:
We are grateful to the many volunteers whose data were used in this study, and Andy Dahl for comments on earlier versions of this manuscript. This research has been conducted using the UK Biobank Resource under Application Number 44300. The datasets used for part of the replication analysis were obtained from Vanderbilt University Medical Center’s BioVU, which is supported by numerous sources: institutional funding, private agencies, and federal grants. These include the NIH-funded Shared Instrumentation Grant S10OD017985 and S10RR025141; and CTSA grants UL1TR002243, UL1TR000445, and UL1RR024975. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. Genomic data are also supported by investigator-led projects that include U01HG004798, R01NS032830, RC2GM092618, P50GM115305, U01HG006378, U19HL065962, R01HD074711; and additional funding sources listed at https://victr.vumc.org/biovu-funding/ . The BBJ project was supported by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) and the Japan Agency for Medical Research and Development (AMED) under grant number JP17km0305002 (M.K.). This work was funded by National Institutes of Health grants R01 HL122712 (J.S.), UL1 TR002389 (J.S.), R01 HL104608 (C.O.), R01 HL129735 (C.O.), U19 AI095230 (S.W.), U01 HL108634 (A.R.), U19 AI62310 (C.O.), UG3/UH1 OD023282 (C.O.), R01 MH107666 (H.K.I.), P30 DK20595 (H.K.I.), K08 HL153955 (N.S.), U01 HG009086 (N.J.C.), and R01 MH113362 (N.J.C.), by Rafael Rivera III Memorial Foundation for Asthma Research (J.S.), by the DARPA Big Mechanism program under ARO contract W911NF1410333 (A.R.), and by a gift from Liz and Kent Dauten (A.R.).
Funding Information:
We are grateful to the many volunteers whose data were used in this study, and Andy Dahl for comments on earlier versions of this manuscript. This research has been conducted using the UK Biobank Resource under Application Number 44300. The datasets used for part of the replication analysis were obtained from Vanderbilt University Medical Center’s BioVU, which is supported by numerous sources: institutional funding, private agencies, and federal grants. These include the NIH-funded Shared Instrumentation Grant S10OD017985 and S10RR025141; and CTSA grants UL1TR002243, UL1TR000445, and UL1RR024975. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. Genomic data are also supported by investigator-led projects that include U01HG004798, R01NS032830, RC2GM092618, P50GM115305, U01HG006378, U19HL065962, R01HD074711; and additional funding sources listed at https://victr.vumc.org/biovu-funding/. The BBJ project was supported by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) and the Japan Agency for Medical Research and Development (AMED) under grant number JP17km0305002 (M.K.). This work was funded by National Institutes of Health grants R01 HL122712 (J.S.), UL1 TR002389 (J.S.), R01 HL104608 (C.O.), R01 HL129735 (C.O.), U19 AI095230 (S.W.), U01 HL108634 (A.R.), U19 AI62310 (C.O.), UG3/UH1 OD023282 (C.O.), R01 MH107666 (H.K.I.), P30 DK20595 (H.K.I.), K08 HL153955 (N.S.), U01 HG009086 (N.J.C.), and R01 MH113362 (N.J.C.), by Rafael Rivera III Memorial Foundation for Asthma Research (J.S.), by the DARPA Big Mechanism program under ARO contract W911NF1410333 (A.R.), and by a gift from Liz and Kent Dauten (A.R.).
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Asthma is a heterogeneous, complex syndrome, and identifying asthma endotypes has been challenging. We hypothesize that distinct endotypes of asthma arise in disparate genetic variation and life-time environmental exposure backgrounds, and that disease comorbidity patterns serve as a surrogate for such genetic and exposure variations. Here, we computationally discover 22 distinct comorbid disease patterns among individuals with asthma (asthma comorbidity subgroups) using diagnosis records for >151 M US residents, and re-identify 11 of the 22 subgroups in the much smaller UK Biobank. GWASs to discern asthma risk loci for individuals within each subgroup and in all subgroups combined reveal 109 independent risk loci, of which 52 are replicated in multi-ancestry meta-analysis across different ethnicity subsamples in UK Biobank, US BioVU, and BioBank Japan. Fourteen loci confer asthma risk in multiple subgroups and in all subgroups combined. Importantly, another six loci confer asthma risk in only one subgroup. The strength of association between asthma and each of 44 health-related phenotypes also varies dramatically across subgroups. This work reveals subpopulations of asthma patients distinguished by comorbidity patterns, asthma risk loci, gene expression, and health-related phenotypes, and so reveals different asthma endotypes.
AB - Asthma is a heterogeneous, complex syndrome, and identifying asthma endotypes has been challenging. We hypothesize that distinct endotypes of asthma arise in disparate genetic variation and life-time environmental exposure backgrounds, and that disease comorbidity patterns serve as a surrogate for such genetic and exposure variations. Here, we computationally discover 22 distinct comorbid disease patterns among individuals with asthma (asthma comorbidity subgroups) using diagnosis records for >151 M US residents, and re-identify 11 of the 22 subgroups in the much smaller UK Biobank. GWASs to discern asthma risk loci for individuals within each subgroup and in all subgroups combined reveal 109 independent risk loci, of which 52 are replicated in multi-ancestry meta-analysis across different ethnicity subsamples in UK Biobank, US BioVU, and BioBank Japan. Fourteen loci confer asthma risk in multiple subgroups and in all subgroups combined. Importantly, another six loci confer asthma risk in only one subgroup. The strength of association between asthma and each of 44 health-related phenotypes also varies dramatically across subgroups. This work reveals subpopulations of asthma patients distinguished by comorbidity patterns, asthma risk loci, gene expression, and health-related phenotypes, and so reveals different asthma endotypes.
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U2 - 10.1038/s41467-022-33628-8
DO - 10.1038/s41467-022-33628-8
M3 - Article
C2 - 36344522
AN - SCOPUS:85141473016
SN - 2041-1723
VL - 13
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 6712
ER -