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AuthorRodriguez-Flores, Juan L.
AuthorMessai-Badji, Radja
AuthorRobay, Amal
AuthorTemanni, Ramzi
AuthorSyed, Najeeb
AuthorMarkovic, Monika
AuthorAl-khayat, Eiman
AuthorQafoud, Fatima
AuthorNawaz, Zafar
AuthorBadii, Ramin
AuthorAl-Sarraj, Yasser
AuthorMbarek, Hamdi
AuthorAl-Muftah, Wadha
AuthorAlvi, Muhammad
AuthorRostami, Mahboubeh R.
AuthorCruzado, Juan Carlos Martinez
AuthorMezey, Jason G.
AuthorShakaki, Alya Al
AuthorMalek, Joel A.
AuthorGreenblatt, Matthew B.
AuthorFakhro, Khalid A.
AuthorMachaca, Khaled
AuthorAl-Nabet, Ajayeb
AuthorAfifi, Nahla
AuthorBrooks, Andrew
AuthorIsmail, Said I.
AuthorAlthani, Asmaa
AuthorCrystal, Ronald G.
Available date2023-08-28T09:09:49Z
Publication Date2022
Publication Namenpj Genomic Medicine
ResourceScopus
ISSN20567944
URIhttp://dx.doi.org/10.1038/s41525-021-00270-0
URIhttp://hdl.handle.net/10576/46832
AbstractRisk genes for Mendelian (single-gene) disorders (SGDs) are consistent across populations, but pathogenic risk variants that cause SGDs are typically population-private. The goal was to develop "QChip1," an inexpensive genotyping microarray to comprehensively screen newborns, couples, and patients for SGD risk variants in Qatar, a small nation on the Arabian Peninsula with a high degree of consanguinity. Over 108 variants in 8445 Qatari were identified for inclusion in a genotyping array containing 165,695 probes for 83,542 known and potentially pathogenic variants in 3438 SGDs. QChip1 had a concordance with whole-genome sequencing of 99.1%. Testing of QChip1 with 2707 Qatari genomes identified 32,674 risk variants, an average of 134 pathogenic alleles per Qatari genome. The most common pathogenic variants were those causing homocystinuria (1.12% risk allele frequency), and Stargardt disease (2.07%). The majority (85%) of Qatari SGD pathogenic variants were not present in Western populations such as European American, South Asian American, and African American in New York City and European and Afro-Caribbean in Puerto Rico; and only 50% were observed in a broad collection of data across the Greater Middle East including Kuwait, Iran, and United Arab Emirates. This study demonstrates the feasibility of developing accurate screening tools to identify SGD risk variants in understudied populations, and the need for ancestry-specific SGD screening tools. 2022, The Author(s).
SponsorThis is a collaborative work between Qatar Genome, Qatar Biobank, Weill Cornell (New York and Qatar), Hamad Medical Corporation and Sidra Medicine. We are thankful for everyone who contributed to this endeavor from all participating institutes. We would like to especially thank all participants in this study for their continuous support. We thank Dr. Fatemeh Abbaszadeh, for quality control and implementing QChip in the diagnostic services; N. Mohamed for editorial support, E. Betancourt for administrative support, E. Guzman for IT support, and J. Pillardy for high-performance computing support. J.R.F. also thanks Alan R. Shuldiner and Regeneron Genetics Center for supporting, J.R.F. to help complete this project. Special thanks to Alphonse Tharangeval at the Dasman Diabetes Institute in Kuwait for providing allele frequency lookups, and to the Center for Arab Genetic Studies in UAE, the GME Variome at University of California at San Diego and the Iranomefor providing public access to their databases. The authors are saddened by the passing of Andrew Brooks after the manuscript was submitted to the journal for review. This publication was made possible by The Qatar Foundation, the Weill Cornell Medical College in Qatar; NPRP 09-741-3 193, NPRP 5-436-3-116, NPRP 7-1425-3-370, NPRP 7-1301-3-336, and NPRP P8-1913-3-396 from the Qatar National Research Fund (a member of the Qatar Foundation). The findings achieved herein are solely the responsibility of the authors.
Languageen
PublisherNature Research
SubjectMedical research
Risk factors
TitleThe QChip1 knowledgebase and microarray for precision medicine in Qatar
TypeArticle
Issue Number1
Volume Number7
dc.accessType Open Access


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