Title |
Measuring shared variants in cohorts of discordant siblings with applications to autism
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Published in |
Proceedings of the National Academy of Sciences of the United States of America, June 2017
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DOI | 10.1073/pnas.1700439114 |
Pubmed ID | |
Authors |
Kenny Ye, Ivan Iossifov, Dan Levy, Boris Yamrom, Andreas Buja, Abba M. Krieger, Michael Wigler |
Abstract |
We develop a method of analysis [affected to discordant sibling pairs (A2DS)] that tests if shared variants contribute to a disorder. Using a standard measure of genetic relation, test individuals are compared with a cohort of discordant sibling pairs (CDS) to derive a comparative similarity score. We ask if a test individual is more similar to an unrelated affected than to the unrelated unaffected sibling from the CDS and then, sum over such individuals and pairs. Statistical significance is judged by randomly permuting the affected status in the CDS. In the analysis of published genotype data from the Simons Simplex Collection (SSC) and the Autism Genetic Resource Exchange (AGRE) cohorts of children with autism spectrum disorder (ASD), we find strong statistical significance that the affected are more similar to the affected than to the unaffected of the CDS (P value ∼ 0.00001). Fathers in multiplex families have marginally greater similarity (P value = 0.02) to unrelated affected individuals. These results do not depend on ethnic matching or gender. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 4 | 36% |
France | 1 | 9% |
Canada | 1 | 9% |
Unknown | 5 | 45% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 11 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 43 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 8 | 19% |
Researcher | 6 | 14% |
Student > Master | 5 | 12% |
Student > Bachelor | 4 | 9% |
Student > Doctoral Student | 4 | 9% |
Other | 4 | 9% |
Unknown | 12 | 28% |
Readers by discipline | Count | As % |
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Psychology | 8 | 19% |
Biochemistry, Genetics and Molecular Biology | 5 | 12% |
Agricultural and Biological Sciences | 5 | 12% |
Computer Science | 2 | 5% |
Medicine and Dentistry | 2 | 5% |
Other | 5 | 12% |
Unknown | 16 | 37% |