Genetic identification of a common collagen disease in Puerto Ricans via identity-by-descent mapping in a health system Article Swipe
Gillian M. Belbin
,
Jacqueline A. Odgis
,
Elena P. Sorokin
,
Muh-Ching Yee
,
Sumita Kohli
,
Benjamin S. Glicksberg
,
Christopher R. Gignoux
,
Genevieve L. Wojcik
,
Tielman Van Vleck
,
Janina M. Jeff
,
Michael D. Linderman
,
Claudia Schurmann
,
Douglas M. Ruderfer
,
Xiaoqiang Cai
,
Amanda Merkelson
,
Anne E. Justice
,
Kristin L. Young
,
Misa Graff
,
Kari E. North
,
Ulrike Peters
,
Regina James
,
Lucia A. Hindorff
,
Ruth Kornreich
,
Lisa Edelmann
,
Omri Gottesman
,
Eli Stahl
,
Judy H. Cho
,
Ruth J. F. Loos
,
Erwin P. Böttinger
,
Girish N. Nadkarni
,
Noura S. Abul‐Husn
,
Eimear E. Kenny
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.7554/elife.25060
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.7554/elife.25060
Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic Bio Me biobank in New York City. By linking to medical records, we discover a locus associated with both elevated genetic relatedness and extreme short stature. We link the gene, COL27A1 , with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease.
Related Topics
Concepts
Mendelian inheritance
Pedigree chart
Disease
Genetics
Locus (genetics)
Biobank
Genomics
Biology
Genetic linkage
Population
Identity by descent
Evolutionary biology
Allele
Medicine
Haplotype
Gene
Genome
Pathology
Environmental health
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.7554/elife.25060
- OA Status
- gold
- Cited By
- 85
- References
- 115
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2951886963
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2951886963Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.7554/elife.25060Digital Object Identifier
- Title
-
Genetic identification of a common collagen disease in Puerto Ricans via identity-by-descent mapping in a health systemWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-09-11Full publication date if available
- Authors
-
Gillian M. Belbin, Jacqueline A. Odgis, Elena P. Sorokin, Muh-Ching Yee, Sumita Kohli, Benjamin S. Glicksberg, Christopher R. Gignoux, Genevieve L. Wojcik, Tielman Van Vleck, Janina M. Jeff, Michael D. Linderman, Claudia Schurmann, Douglas M. Ruderfer, Xiaoqiang Cai, Amanda Merkelson, Anne E. Justice, Kristin L. Young, Misa Graff, Kari E. North, Ulrike Peters, Regina James, Lucia A. Hindorff, Ruth Kornreich, Lisa Edelmann, Omri Gottesman, Eli Stahl, Judy H. Cho, Ruth J. F. Loos, Erwin P. Böttinger, Girish N. Nadkarni, Noura S. Abul‐Husn, Eimear E. KennyList of authors in order
- Landing page
-
https://doi.org/10.7554/elife.25060Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.7554/elife.25060Direct OA link when available
- Concepts
-
Mendelian inheritance, Pedigree chart, Disease, Genetics, Locus (genetics), Biobank, Genomics, Biology, Genetic linkage, Population, Identity by descent, Evolutionary biology, Allele, Medicine, Haplotype, Gene, Genome, Pathology, Environmental healthTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
85Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 11, 2024: 3, 2023: 11, 2022: 6, 2021: 16Per-year citation counts (last 5 years)
- References (count)
-
115Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| citation_normalized_percentile.value | 0.97543562 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |