Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Motazedi E

PROVIDER: S-EPMC10022308 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

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

Motazedi Ehsan E Cheng Weiqiu W Thomassen Jesper Q JQ Frei Oleksandr O Rongve Arvid A Athanasiu Lavinia L Bahrami Shahram S Shadrin Alexey A Ulstein Ingun I Stordal Eystein E Brækhus Anne A Saltvedt Ingvild I Sando Sigrid B SB O'Connell Kevin S KS Hindley Guy G van der Meer Dennis D Bergh Sverre S Nordestgaard Børge G BG Tybjærg-Hansen Anne A Bråthen Geir G Pihlstrøm Lasse L Djurovic Srdjan S Frikke-Schmidt Ruth R Fladby Tormod T Aarsland Dag D Selbæk Geir G Seibert Tyler M TM Dale Anders M AM Fan Chun C CC Andreassen Ole A OA

Journal of Alzheimer's disease : JAD 20220101 4

<h4>Background</h4>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.<h4>Objective</h4>The aim of this study was to estimate age-dependent risk of late-onset AD using polygenic predictors in Nordic populations.<h4>Meth ...[more]

PMID: 35848024

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Project description:ObjectiveGenome-wide association studies (GWAS) have identified over 30 susceptibility loci associated with Alzheimer's disease (AD). Using AD GWAS data from the International Genomics of Alzheimer's Project (IGAP), Polygenic Risk Score (PRS) was successfully applied to predict life time risk of AD development. A recently introduced Polygenic Hazard Score (PHS) is able to quantify individuals with age-specific genetic risk for AD. The aim of this study was to quantify the age-specific genetic risk for AD with PRS and compare the results generated by PRS with those from PHS.MethodsQuantification of individual differences in age-specific genetic risk for AD identified by the PRS, was performed with Cox Regression on 9903 (2626 cases and 7277 controls) individuals from the Genetic and Environmental Risk in Alzheimer's Disease consortium (GERAD). Polygenic Hazard Scores were generated for the same individuals. The age-specific genetic risk for AD identified by the PRS was compared with that generated by the PHS. This was repeated using varying SNPs P-value thresholds for disease association.ResultsPolygenic Risk Score significantly predicted the risk associated with age at AD onset when SNPs were preselected for association to AD at P ≤ 0.001. The strongest effect (B = 0.28, SE = 0.04, P = 2.5 × 10-12) was observed for PRS based upon genome-wide significant SNPs (P ≤ 5 × 10-8). The strength of association was weaker with less stringent SNP selection thresholds.InterpretationBoth PRS and PHS can be used to predict an age-specific risk for developing AD. The PHS approach uses SNP effect sizes derived with the Cox Proportional Hazard Regression model. When SNPs were selected based upon AD GWAS case/control P ≤ 10-3, we found no advantage of using SNP effects sizes calculated with the Cox Proportional Hazard Regression model in our study. When SNPs are selected for association with AD risk at P > 10-3, the age-specific risk prediction results are not significant for either PRS or PHS. However PHS could be more advantageous than PRS of age specific AD risk predictions when SNPs are prioritized for association with AD age at onset (i.e., powerful Cox Regression GWAS study).

Project description:Mounting evidence indicates that the polygenic basis of late-onset Alzheimer's disease can be harnessed to identify individuals at greatest risk for cognitive decline. We have previously developed and validated a polygenic hazard score comprising of 31 single nucleotide polymorphisms for predicting Alzheimer's disease dementia age of onset. In this study, we examined whether polygenic hazard scores are associated with: (i) regional tracer uptake using amyloid PET; (ii) regional volume loss using longitudinal MRI; (iii) post-mortem regional amyloid-β protein and tau associated neurofibrillary tangles; and (iv) four common non-Alzheimer's pathologies. Even after accounting for APOE, we found a strong association between polygenic hazard scores and amyloid PET standard uptake volume ratio with the largest effects within frontal cortical regions in 980 older individuals across the disease spectrum, and longitudinal MRI volume loss within the entorhinal cortex in 607 older individuals across the disease spectrum. We also found that higher polygenic hazard scores were associated with greater rates of cognitive and clinical decline in 632 non-demented older individuals, even after controlling for APOE status, frontal amyloid PET and entorhinal cortex volume. In addition, the combined model that included polygenic hazard scores, frontal amyloid PET and entorhinal cortex volume resulted in a better fit compared to a model with only imaging markers. Neuropathologically, we found that polygenic hazard scores were associated with regional post-mortem amyloid load and neuronal neurofibrillary tangles, even after accounting for APOE, validating our imaging findings. Lastly, polygenic hazard scores were associated with Lewy body and cerebrovascular pathology. Beyond APOE, we show that in living subjects, polygenic hazard scores were associated with amyloid deposition and neurodegeneration in susceptible brain regions. Polygenic hazard scores may also be useful for the identification of individuals at the highest risk for developing multi-aetiological dementia.

Dataset Information

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

Background

Objective

Methods

Results

Conclusion

Publications

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

Similar Datasets

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