Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

  • Ehsan Motazedi
  • Weiqiu Cheng
  • Jesper Q. Thomassen
  • Oleksandr Frei
  • Arvid Rongve
  • Lavinia Athanasiu
  • Shahram Bahrami
  • Alexey Shadrin
  • Ingun Ulstein
  • Eystein Stordal
  • Anne Brækhus
  • Ingvild Saltvedt
  • Sigrid B. Sando
  • Kevin S. O'Connell
  • Guy Hindley
  • Dennis Van Der Meer
  • Sverre Bergh
  • Brge G. Nordestgaard
  • Geir Brthen
  • Lasse Pihlstrm
  • Srdjan Djurovic
  • Tormod Fladby
  • Dag Aarsland
  • Geir Selbæk
  • Tyler M. Seibert
  • Anders M. Dale
  • Chun C. Fan
  • Ole A. Andreassen

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.

TidsskriftJournal of Alzheimer's Disease
Udgave nummer4
Sider (fra-til)1533-1544
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
The authors would like to thank the participants of the Norwegian Dementia Genetics Network (DemGene) and the clinical units involved in data collection, as well as the participants and staff of the Copenhagen City Heart Study (CCHS) and the Copenhagen General Population Study (CGPS) for their important contributions. EM and WC received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 801133. The other authors were funded by the Research Council of Norway (OAA: 213837, 223273, 229129, 248778, 248980, 262656, 273291, 283798, 311993), the South-Eastern Norway Regional Health Authority (OAA: 2013–123, 2017–112, 2019–108, 2020–034), National Institute on Aging (R01 AG08724, R01 AG17561, R01 AG028555, R01 AG060470), EU JPND: PMI-AD RCN 311993 and the European Union’s Horizon 2020 research and innovation program (grant #847776 CoMorMent). We gratefully acknowledge support from the American National Institute of Health (NS057198, EB00790), KG Jebsen Stiftelsen, and the Norwegian Health Association (22731). The CCHS and CGPS studies were funded by the Danish Heart Association, the Danish Lung Association, the Velux Foundation, and the Lundbeck Foundation.

Publisher Copyright:
© 2022 - IOS Press. All rights reserved.

ID: 328238001