Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations.
Age at onset
Alzheimer’s disease
Nordic ancestry
polygenic hazard score
Journal
Journal of Alzheimer's disease : JAD
ISSN: 1875-8908
Titre abrégé: J Alzheimers Dis
Pays: Netherlands
ID NLM: 9814863
Informations de publication
Date de publication:
2022
2022
Historique:
pubmed:
19
7
2022
medline:
24
8
2022
entrez:
18
7
2022
Statut:
ppublish
Résumé
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. The aim of this study was to estimate age-dependent risk of late-onset AD using polygenic predictors in Nordic populations. 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). 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. 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.
Sections du résumé
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.
Identifiants
pubmed: 35848024
pii: JAD220174
doi: 10.3233/JAD-220174
pmc: PMC10022308
mid: NIHMS1867056
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1533-1544Subventions
Organisme : NIBIB NIH HHS
ID : K08 EB026503
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG017560
Pays : United States
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