Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations
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Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations. / Motazedi, Ehsan; Cheng, Weiqiu; Thomassen, Jesper Q.; Frei, Oleksandr; Rongve, Arvid; Athanasiu, Lavinia; Bahrami, Shahram; Shadrin, Alexey; Ulstein, Ingun; Stordal, Eystein; Brækhus, Anne; Saltvedt, Ingvild; Sando, Sigrid B.; O'Connell, Kevin S.; Hindley, Guy; Van Der Meer, Dennis; Bergh, Sverre; Nordestgaard, Brge G.; Tybjærg-Hansen, Anne; Brthen, Geir; Pihlstrm, Lasse; Djurovic, Srdjan; Frikke-Schmidt, Ruth; Fladby, Tormod; Aarsland, Dag; Selbæk, Geir; Seibert, Tyler M.; Dale, Anders M.; Fan, Chun C.; Andreassen, Ole A.
In: Journal of Alzheimer's Disease, Vol. 88, No. 4, 2022, p. 1533-1544.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations
AU - Motazedi, Ehsan
AU - Cheng, Weiqiu
AU - Thomassen, Jesper Q.
AU - Frei, Oleksandr
AU - Rongve, Arvid
AU - Athanasiu, Lavinia
AU - Bahrami, Shahram
AU - Shadrin, Alexey
AU - Ulstein, Ingun
AU - Stordal, Eystein
AU - Brækhus, Anne
AU - Saltvedt, Ingvild
AU - Sando, Sigrid B.
AU - O'Connell, Kevin S.
AU - Hindley, Guy
AU - Van Der Meer, Dennis
AU - Bergh, Sverre
AU - Nordestgaard, Brge G.
AU - Tybjærg-Hansen, Anne
AU - Brthen, Geir
AU - Pihlstrm, Lasse
AU - Djurovic, Srdjan
AU - Frikke-Schmidt, Ruth
AU - Fladby, Tormod
AU - Aarsland, Dag
AU - Selbæk, Geir
AU - Seibert, Tyler M.
AU - Dale, Anders M.
AU - Fan, Chun C.
AU - Andreassen, Ole A.
N1 - Publisher Copyright: © 2022 - IOS Press. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Background: Polygenic hazard scores (PHS) estimate age-dependent genetic risk of late-onset Alzheimer's disease (AD), but there is limited information about the performance of PHS on real-world data where the population of interest differs from the model development population and part of the model genotypes are missing or need to be imputed. Objective: The aim of this study was to estimate age-dependent risk of late-onset AD using polygenic predictors in Nordic populations. Methods: We used Desikan PHS model, based on Cox proportional hazards assumption, to obtain age-dependent hazard scores for AD from individual genotypes in the Norwegian DemGene cohort (n = 2,772). We assessed the risk discrimination and calibration of Desikan model and extended it by adding new genotype markers (the Desikan Nordic model). Finally, we evaluated both Desikan and Desikan Nordic models in two independent Danish cohorts: The Copenhagen City Heart Study (CCHS) cohort (n = 7,643) and The Copenhagen General Population Study (CGPS) cohort (n = 10,886). Results: We showed a robust prediction efficiency of Desikan model in stratifying AD risk groups in Nordic populations, even when some of the model SNPs were missing or imputed. We attempted to improve Desikan PHS model by adding new SNPs to it, but we still achieved similar risk discrimination and calibration with the extended model. Conclusion: PHS modeling has the potential to guide the timing of treatment initiation based on individual risk profiles and can help enrich clinical trials with people at high risk to AD in Nordic populations.
AB - Background: Polygenic hazard scores (PHS) estimate age-dependent genetic risk of late-onset Alzheimer's disease (AD), but there is limited information about the performance of PHS on real-world data where the population of interest differs from the model development population and part of the model genotypes are missing or need to be imputed. Objective: The aim of this study was to estimate age-dependent risk of late-onset AD using polygenic predictors in Nordic populations. Methods: We used Desikan PHS model, based on Cox proportional hazards assumption, to obtain age-dependent hazard scores for AD from individual genotypes in the Norwegian DemGene cohort (n = 2,772). We assessed the risk discrimination and calibration of Desikan model and extended it by adding new genotype markers (the Desikan Nordic model). Finally, we evaluated both Desikan and Desikan Nordic models in two independent Danish cohorts: The Copenhagen City Heart Study (CCHS) cohort (n = 7,643) and The Copenhagen General Population Study (CGPS) cohort (n = 10,886). Results: We showed a robust prediction efficiency of Desikan model in stratifying AD risk groups in Nordic populations, even when some of the model SNPs were missing or imputed. We attempted to improve Desikan PHS model by adding new SNPs to it, but we still achieved similar risk discrimination and calibration with the extended model. Conclusion: PHS modeling has the potential to guide the timing of treatment initiation based on individual risk profiles and can help enrich clinical trials with people at high risk to AD in Nordic populations.
KW - Age at onset
KW - Alzheimer's disease
KW - Nordic ancestry
KW - polygenic hazard score
U2 - 10.3233/JAD-220174
DO - 10.3233/JAD-220174
M3 - Journal article
C2 - 35848024
AN - SCOPUS:85137007982
VL - 88
SP - 1533
EP - 1544
JO - Journal of Alzheimer's Disease
JF - Journal of Alzheimer's Disease
SN - 1387-2877
IS - 4
ER -
ID: 328238001