Polygenic score

A polygenic score is a concept in genetics. It is a number which adds up different aspects of a person as shown by their genetics. Bear in mind that is is now possible to have a very complete sequence of a person's genetic material (roughly, genes).[1][2][3]

Polygenic scores are usually created from large scientific studies that look at the DNA of many people. These are called genome-wide association studies (GWASs). They can find out how important certain variants are. "Effect" is the name for the importance of a variant. Polygenic scores are made by adding up the effects of a large number of genetic variants. These genetic variants are known as alleles or SNPs.[4][5][6]

It is used to estimate how likely a person is to have a trait or disease. It suggests how likely a person is to, for example, suffer a disease or disability as a result of their genetics.[7][8][9][10][11] A polygenic score is the effect of many genetic variants on a trait. Polygenic scores can also tell how much of a trait or disease someone will have.[12][13][14][15][16]

Polygenic scores can be used in adult humans. Polygenic scores are also sometimes used to decide if embryos are likely to have a disease.

  1. Dudbridge F (March 2013). "Power and predictive accuracy of polygenic risk scores". PLOS Genetics. 9 (3): e1003348. doi:10.1371/journal.pgen.1003348. PMC 3605113. PMID 23555274.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  2. Torkamani A, Wineinger NE, Topol EJ (September 2018). "The personal and clinical utility of polygenic risk scores". Nature Reviews. Genetics. 19 (9): 581–590. doi:10.1038/s41576-018-0018-x. PMID 29789686. S2CID 46893131.
  3. Lambert SA, Abraham G, Inouye M (November 2019). "Towards clinical utility of polygenic risk scores". Human Molecular Genetics. 28 (R2): R133–R142. doi:10.1093/hmg/ddz187. PMID 31363735.
  4. Dudbridge F (March 2013). "Power and predictive accuracy of polygenic risk scores". PLOS Genetics. 9 (3): e1003348. doi:10.1371/journal.pgen.1003348. PMC 3605113. PMID 23555274.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  5. Torkamani A, Wineinger NE, Topol EJ (September 2018). "The personal and clinical utility of polygenic risk scores". Nature Reviews. Genetics. 19 (9): 581–590. doi:10.1038/s41576-018-0018-x. PMID 29789686. S2CID 46893131.
  6. Lambert SA, Abraham G, Inouye M (November 2019). "Towards clinical utility of polygenic risk scores". Human Molecular Genetics. 28 (R2): R133–R142. doi:10.1093/hmg/ddz187. PMID 31363735.
  7. de Vlaming R, Groenen PJ (2015). "The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics". BioMed Research International. 2015: 143712. doi:10.1155/2015/143712. PMC 4529984. PMID 26273586.
  8. Lewis CM, Vassos E (November 2017). "Prospects for using risk scores in polygenic medicine". Genome Medicine. 9 (1): 96. doi:10.1186/s13073-017-0489-y. PMC 5683372. PMID 29132412.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  9. Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C, Choi SH, et al. (September 2018). "Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations". Nature Genetics. 50 (9): 1219–1224. doi:10.1038/s41588-018-0183-z. PMC 6128408. PMID 30104762.
  10. Yanes T, Meiser B, Kaur R, Scheepers-Joynt M, McInerny S, Taylor S, et al. (March 2020). "Uptake of polygenic risk information among women at increased risk of breast cancer". Clinical Genetics. 97 (3): 492–501. doi:10.1111/cge.13687. hdl:11343/286783. PMID 31833054. S2CID 209342044.
  11. Vilhjálmsson BJ, Yang J, Finucane HK, Gusev A, Lindström S, Ripke S, et al. (October 2015). "Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores". American Journal of Human Genetics. 97 (4): 576–592. doi:10.1016/j.ajhg.2015.09.001. PMC 4596916. PMID 26430803.
  12. de Vlaming R, Groenen PJ (2015). "The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics". BioMed Research International. 2015: 143712. doi:10.1155/2015/143712. PMC 4529984. PMID 26273586.
  13. Lewis CM, Vassos E (November 2017). "Prospects for using risk scores in polygenic medicine". Genome Medicine. 9 (1): 96. doi:10.1186/s13073-017-0489-y. PMC 5683372. PMID 29132412.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  14. Khera AV, Chaffin M, Aragam KG, Haas ME, Roselli C, Choi SH, et al. (September 2018). "Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations". Nature Genetics. 50 (9): 1219–1224. doi:10.1038/s41588-018-0183-z. PMC 6128408. PMID 30104762.
  15. Yanes T, Meiser B, Kaur R, Scheepers-Joynt M, McInerny S, Taylor S, et al. (March 2020). "Uptake of polygenic risk information among women at increased risk of breast cancer". Clinical Genetics. 97 (3): 492–501. doi:10.1111/cge.13687. hdl:11343/286783. PMID 31833054. S2CID 209342044.
  16. Vilhjálmsson BJ, Yang J, Finucane HK, Gusev A, Lindström S, Ripke S, et al. (October 2015). "Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores". American Journal of Human Genetics. 97 (4): 576–592. doi:10.1016/j.ajhg.2015.09.001. PMC 4596916. PMID 26430803.

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