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Overestimated prediction using polygenic prediction derived from summary statistics
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, David Keetae | - |
dc.contributor.author | Chen, Mingshen | - |
dc.contributor.author | Kim, Seungsoo | - |
dc.contributor.author | Joo, Yoonjung Yoonie | - |
dc.contributor.author | Loving, Rebekah K. | - |
dc.contributor.author | Kim, Hyoung Seop | - |
dc.contributor.author | Cha, Jiook | - |
dc.contributor.author | Yoo, Shinjae | - |
dc.contributor.author | Kim, Jong Hun | - |
dc.date.accessioned | 2023-09-18T05:38:54Z | - |
dc.date.available | 2023-09-18T14:41:11Z | - |
dc.date.issued | 2023-09-14 | - |
dc.identifier.citation | BMC Genomic Data, Vol.24(1):52 | ko_KR |
dc.identifier.issn | 2730-6844 | - |
dc.identifier.uri | https://hdl.handle.net/10371/195570 | - |
dc.description.abstract | Background
When polygenic risk score (PRS) is derived from summary statistics, independence between discovery and test sets cannot be monitored. We compared two types of PRS studies derived from raw genetic data (denoted as rPRS) and the summary statistics for IGAP (sPRS). Results Two variables with the high heritability in UK Biobank, hypertension, and height, are used to derive an exemplary scale effect of PRS. sPRS without APOE is derived from International Genomics of Alzheimers Project (IGAP), which records ΔAUC and ΔR2 of 0.051 ± 0.013 and 0.063 ± 0.015 for Alzheimers Disease Sequencing Project (ADSP) and 0.060 and 0.086 for Accelerating Medicine Partnership - Alzheimers Disease (AMP-AD). On UK Biobank, rPRS performances for hypertension assuming a similar size of discovery and test sets are 0.0036 ± 0.0027 (ΔAUC) and 0.0032 ± 0.0028 (ΔR2). For height, ΔR2 is 0.029 ± 0.0037. Conclusion Considering the high heritability of hypertension and height of UK Biobank and sample size of UK Biobank, sPRS results from AD databases are inflated. Independence between discovery and test sets is a well-known basic requirement for PRS studies. However, a lot of PRS studies cannot follow such requirements because of impossible direct comparisons when using summary statistics. Thus, for sPRS, potential duplications should be carefully considered within the same ethnic group. | ko_KR |
dc.description.sponsorship | This work was supported by the U.S. Department of Energy (DOE), Office of Science (SC), Advanced Scientific Computing Research program under award DE-SC-0012704 and used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC award ASCR-ERCAP0023081. Additionally, the computational resources for this study were supported by the internal funding of Ilsan Hospital | ko_KR |
dc.language.iso | en | ko_KR |
dc.publisher | BMC | ko_KR |
dc.subject | Polygenic risk score | - |
dc.subject | Complex genetic disease | - |
dc.subject | Alzheimer’s disease | - |
dc.subject | Overestimation bias | - |
dc.title | Overestimated prediction using polygenic prediction derived from summary statistics | ko_KR |
dc.type | Article | ko_KR |
dc.identifier.doi | 10.1186/s12863-023-01151-4 | ko_KR |
dc.citation.journaltitle | BMC Genomic Data | ko_KR |
dc.language.rfc3066 | en | - |
dc.rights.holder | BioMed Central Ltd., part of Springer Nature | - |
dc.date.updated | 2023-09-17T03:09:44Z | - |
dc.citation.volume | 24 | ko_KR |
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