FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385633218> ?p ?o ?g. }

• W4385633218 abstract "Abstract Background Polygenic risk scores (PRSs) are proposed for use in clinical and research settings for risk stratification. PRS predictions often show bias toward the population of available genome-wide association studies, which is typically of European ancestry. This study aims to assess the performance differences of ancestry-specific PRS and test the implementation of multi-ancestry PRS to enhance the generalizability of low-density lipoprotein (LDL) cholesterol predictions in the East Asian population Methods We computed ancestry-specific and multi-ancestry PRS for LDL using data from the global lipid consortium while accounting for population-specific linkage disequilibrium patterns using PRS-CSx method. We first conducted an ancestry-wide analysis using the UK Biobank dataset (n=423,596) and then applied the same models to the Taiwan Biobank dataset (TWB, n=68,978). PRS performances were based on linear regression with adjustment for age, sex, and principal components. PRS strata were considered to assess the extent to which a PRS categorization can stratify individuals for LDL cholesterol levels in East Asian samples. Results Population-specific PRS better predicted LDL levels within the target population but multi-ancestry PRS were more generalizable. In the TWB dataset, covariate-adjusted R 2 values were 9.3% for ancestry-specific PRS, 6.7% for multi-ancestry PRS, and 4.5% for European-specific PRS. Similar trends (8.6%, 7.8%, 6.2%) were observed in the smaller East Asian population of the UK Biobank (n=1,480). Consistent with the R 2 values, PRS stratification in East Asians (TWB) effectively captured a heterogenous variability in LDL blood cholesterol levels across PRS strata. The mean difference in LDL levels between the lowest and highest East Asian-specific PRS (EAS_PRS) deciles was 0.82, compared to 0.59 for European-specific PRS (EUR_PRS) and 0.76 for multi-ancestry PRS. Notably, the mean LDL values in the top decile of multi-ancestry PRS were comparable to those of EAS_PRS (3.543 vs. 3.541, P =0.86). Conclusions Our analysis of the PRS prediction model for LDL cholesterol further supports the issue of PRS generalizability across populations. Our targeted analysis of the East Asian (EAS) population revealed that integrating non-European genotyping data, accounting for population-specific linkage disequilibrium, and considering meta-analyses of non-European-based GWAS alongside powerful European-based GWAS can enhance the generalizability of LDL PRS." @default.
• W4385633218 created "2023-08-08" @default.
• W4385633218 creator A5003352072 @default.
• W4385633218 creator A5013713722 @default.
• W4385633218 creator A5032669663 @default.
• W4385633218 creator A5034766389 @default.
• W4385633218 creator A5051454986 @default.
• W4385633218 creator A5053379839 @default.
• W4385633218 creator A5054453758 @default.
• W4385633218 creator A5057437092 @default.
• W4385633218 creator A5061914842 @default.
• W4385633218 creator A5066913932 @default.
• W4385633218 date "2023-08-06" @default.
• W4385633218 modified "2023-09-29" @default.
• W4385633218 title "Trans-ancestry polygenic models for the prediction of LDL blood levels: An analysis of the UK Biobank and Taiwan Biobank" @default.
• W4385633218 cites W1985941759 @default.
• W4385633218 cites W2072152755 @default.
• W4385633218 cites W2895486342 @default.
• W4385633218 cites W2963160524 @default.
• W4385633218 cites W2970480306 @default.
• W4385633218 cites W3046594723 @default.
• W4385633218 cites W3052902836 @default.
• W4385633218 cites W3111115779 @default.
• W4385633218 cites W3127157887 @default.
• W4385633218 cites W3129840172 @default.
• W4385633218 cites W3166155592 @default.
• W4385633218 cites W3205644245 @default.
• W4385633218 cites W3216286867 @default.
• W4385633218 cites W4206175800 @default.
• W4385633218 cites W4211005061 @default.
• W4385633218 cites W4220778359 @default.
• W4385633218 cites W4229035861 @default.
• W4385633218 cites W4281666919 @default.
• W4385633218 cites W4283712790 @default.
• W4385633218 cites W4291019306 @default.
• W4385633218 cites W4304698823 @default.
• W4385633218 cites W4307232193 @default.
• W4385633218 cites W4319791885 @default.
• W4385633218 cites W4320480795 @default.
• W4385633218 cites W4321444446 @default.
• W4385633218 cites W4323275420 @default.
• W4385633218 cites W4376959645 @default.
• W4385633218 doi "https://doi.org/10.1101/2023.08.03.23293320" @default.
• W4385633218 hasPublicationYear "2023" @default.
• W4385633218 type Work @default.
• W4385633218 citedByCount "0" @default.
• W4385633218 crossrefType "posted-content" @default.
• W4385633218 hasAuthorship W4385633218A5003352072 @default.
• W4385633218 hasAuthorship W4385633218A5013713722 @default.
• W4385633218 hasAuthorship W4385633218A5032669663 @default.
• W4385633218 hasAuthorship W4385633218A5034766389 @default.
• W4385633218 hasAuthorship W4385633218A5051454986 @default.
• W4385633218 hasAuthorship W4385633218A5053379839 @default.
• W4385633218 hasAuthorship W4385633218A5054453758 @default.
• W4385633218 hasAuthorship W4385633218A5057437092 @default.
• W4385633218 hasAuthorship W4385633218A5061914842 @default.
• W4385633218 hasAuthorship W4385633218A5066913932 @default.
• W4385633218 hasBestOaLocation W43856332181 @default.
• W4385633218 hasConcept C104317684 @default.
• W4385633218 hasConcept C116567970 @default.
• W4385633218 hasConcept C135763542 @default.
• W4385633218 hasConcept C137132547 @default.
• W4385633218 hasConcept C144024400 @default.
• W4385633218 hasConcept C149923435 @default.
• W4385633218 hasConcept C153209595 @default.
• W4385633218 hasConcept C166976648 @default.
• W4385633218 hasConcept C2908647359 @default.
• W4385633218 hasConcept C35605836 @default.
• W4385633218 hasConcept C37463918 @default.
• W4385633218 hasConcept C54355233 @default.
• W4385633218 hasConcept C71924100 @default.
• W4385633218 hasConcept C75069973 @default.
• W4385633218 hasConcept C86803240 @default.
• W4385633218 hasConceptScore W4385633218C104317684 @default.
• W4385633218 hasConceptScore W4385633218C116567970 @default.
• W4385633218 hasConceptScore W4385633218C135763542 @default.
• W4385633218 hasConceptScore W4385633218C137132547 @default.
• W4385633218 hasConceptScore W4385633218C144024400 @default.
• W4385633218 hasConceptScore W4385633218C149923435 @default.
• W4385633218 hasConceptScore W4385633218C153209595 @default.
• W4385633218 hasConceptScore W4385633218C166976648 @default.
• W4385633218 hasConceptScore W4385633218C2908647359 @default.
• W4385633218 hasConceptScore W4385633218C35605836 @default.
• W4385633218 hasConceptScore W4385633218C37463918 @default.
• W4385633218 hasConceptScore W4385633218C54355233 @default.
• W4385633218 hasConceptScore W4385633218C71924100 @default.
• W4385633218 hasConceptScore W4385633218C75069973 @default.
• W4385633218 hasConceptScore W4385633218C86803240 @default.
• W4385633218 hasLocation W43856332181 @default.
• W4385633218 hasOpenAccess W4385633218 @default.
• W4385633218 hasPrimaryLocation W43856332181 @default.
• W4385633218 hasRelatedWork W2045440288 @default.
• W4385633218 hasRelatedWork W2052183100 @default.
• W4385633218 hasRelatedWork W2069960324 @default.
• W4385633218 hasRelatedWork W2141828160 @default.
• W4385633218 hasRelatedWork W2774178947 @default.
• W4385633218 hasRelatedWork W2776986292 @default.
• W4385633218 hasRelatedWork W3125966262 @default.
• W4385633218 hasRelatedWork W4383534178 @default.
• W4385633218 hasRelatedWork W4385633218 @default.

• next