Polygenic risk scores: a biased prediction?
Abstract A new study highlights the biases and inaccuracies of polygenic risk scores (PRS) when predicting disease risk in individuals from populations other than those used in their derivation. The design bias of workhorse tools used for research, particularly genotyping arrays, contributes to thes...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2018-12-01
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| Series: | Genome Medicine |
| Online Access: | http://link.springer.com/article/10.1186/s13073-018-0610-x |
| _version_ | 1818307848893890560 |
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| author | Francisco M. De La Vega Carlos D. Bustamante |
| author_facet | Francisco M. De La Vega Carlos D. Bustamante |
| author_sort | Francisco M. De La Vega |
| collection | DOAJ |
| description | Abstract A new study highlights the biases and inaccuracies of polygenic risk scores (PRS) when predicting disease risk in individuals from populations other than those used in their derivation. The design bias of workhorse tools used for research, particularly genotyping arrays, contributes to these distortions. To avoid further inequities in health outcomes, the inclusion of diverse populations in research, unbiased genotyping, and methods of bias reduction in PRS are critical. |
| first_indexed | 2024-12-13T07:04:54Z |
| format | Article |
| id | doaj.art-ccbb03c7f5454b07928e14f988e9fba5 |
| institution | Directory Open Access Journal |
| issn | 1756-994X |
| language | English |
| last_indexed | 2024-12-13T07:04:54Z |
| publishDate | 2018-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Medicine |
| spelling | doaj.art-ccbb03c7f5454b07928e14f988e9fba52022-12-21T23:55:51ZengBMCGenome Medicine1756-994X2018-12-011011310.1186/s13073-018-0610-xPolygenic risk scores: a biased prediction?Francisco M. De La Vega0Carlos D. Bustamante1Department of Biomedical Data Science, Stanford University School of MedicineDepartment of Biomedical Data Science, Stanford University School of MedicineAbstract A new study highlights the biases and inaccuracies of polygenic risk scores (PRS) when predicting disease risk in individuals from populations other than those used in their derivation. The design bias of workhorse tools used for research, particularly genotyping arrays, contributes to these distortions. To avoid further inequities in health outcomes, the inclusion of diverse populations in research, unbiased genotyping, and methods of bias reduction in PRS are critical.http://link.springer.com/article/10.1186/s13073-018-0610-x |
| spellingShingle | Francisco M. De La Vega Carlos D. Bustamante Polygenic risk scores: a biased prediction? Genome Medicine |
| title | Polygenic risk scores: a biased prediction? |
| title_full | Polygenic risk scores: a biased prediction? |
| title_fullStr | Polygenic risk scores: a biased prediction? |
| title_full_unstemmed | Polygenic risk scores: a biased prediction? |
| title_short | Polygenic risk scores: a biased prediction? |
| title_sort | polygenic risk scores a biased prediction |
| url | http://link.springer.com/article/10.1186/s13073-018-0610-x |
| work_keys_str_mv | AT franciscomdelavega polygenicriskscoresabiasedprediction AT carlosdbustamante polygenicriskscoresabiasedprediction |