Systems biology analysis of human genomes points to key pathways conferring spina bifida risk
(2021) In Proceedings of the National Academy of Sciences of the United States of America 118(51).- Abstract
Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to... (More)
Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders.
(Less)
- author
- organization
- publishing date
- 2021-12-21
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Case-Control Studies, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Spinal Dysraphism/genetics, Systems Biology, Transcription Factors/genetics
- in
- Proceedings of the National Academy of Sciences of the United States of America
- volume
- 118
- issue
- 51
- article number
- e2106844118
- pages
- 10 pages
- publisher
- National Academy of Sciences
- external identifiers
-
- scopus:85122629178
- pmid:34916285
- ISSN
- 1091-6490
- DOI
- 10.1073/pnas.2106844118
- language
- English
- LU publication?
- yes
- id
- 2b393661-e4d6-4cd6-887b-fe0e3ef3b787
- date added to LUP
- 2022-02-21 15:36:27
- date last changed
- 2024-03-21 05:48:48
@article{2b393661-e4d6-4cd6-887b-fe0e3ef3b787, abstract = {{<p>Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders.</p>}}, author = {{Aguiar-Pulido, Vanessa and Wolujewicz, Paul and Martinez-Fundichely, Alexander and Elhaik, Eran and Thareja, Gaurav and Abdel Aleem, Alice and Chalhoub, Nader and Cuykendall, Tawny and Al-Zamer, Jamel and Lei, Yunping and El-Bashir, Haitham and Musser, James M and Al-Kaabi, Abdulla and Shaw, Gary M and Khurana, Ekta and Suhre, Karsten and Mason, Christopher E and Elemento, Olivier and Finnell, Richard H and Ross, M Elizabeth}}, issn = {{1091-6490}}, keywords = {{Case-Control Studies; Genetic Predisposition to Disease; Genome, Human; Genome-Wide Association Study; Humans; Spinal Dysraphism/genetics; Systems Biology; Transcription Factors/genetics}}, language = {{eng}}, month = {{12}}, number = {{51}}, publisher = {{National Academy of Sciences}}, series = {{Proceedings of the National Academy of Sciences of the United States of America}}, title = {{Systems biology analysis of human genomes points to key pathways conferring spina bifida risk}}, url = {{http://dx.doi.org/10.1073/pnas.2106844118}}, doi = {{10.1073/pnas.2106844118}}, volume = {{118}}, year = {{2021}}, }