> Details
Altmann, Andre;
Aksman, Leon M;
Oxtoby, Neil P;
Young, Alexandra L;
Weiner, Michael;
Aisen, Paul;
Petersen, Ronald;
Weiner, Michael;
Aisen, Paul;
Petersen, Ronald;
Jack, Clifford R;
Jagust, William;
Landau, Susan;
Rivera-Mindt, Monica;
Okonkwo, Ozioma;
Shaw, Leslie M;
Lee, Edward B;
Toga, Arthur W;
Beckett, Laurel;
Harvey, Danielle;
Green, Robert C;
Saykin, Andrew J;
Nho, Kwangsik;
Perrin, Richard J;
[...]
Towards cascading genetic risk in Alzheimer’s disease
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- Media type: E-Article
- Title: Towards cascading genetic risk in Alzheimer’s disease
- Contributor: Altmann, Andre; Aksman, Leon M; Oxtoby, Neil P; Young, Alexandra L; Weiner, Michael; Aisen, Paul; Petersen, Ronald; Weiner, Michael; Aisen, Paul; Petersen, Ronald; Jack, Clifford R; Jagust, William; Landau, Susan; Rivera-Mindt, Monica; Okonkwo, Ozioma; Shaw, Leslie M; Lee, Edward B; Toga, Arthur W; Beckett, Laurel; Harvey, Danielle; Green, Robert C; Saykin, Andrew J; Nho, Kwangsik; Perrin, Richard J; [...]
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Published:
Oxford University Press (OUP), 2024
- Published in: Brain, 147 (2024) 8, Seite 2680-2690
- Language: English
- DOI: 10.1093/brain/awae176
- ISSN: 0006-8950; 1460-2156
- Origination:
- Footnote:
- Description: Abstract Alzheimer’s disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (−). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer’s disease. Here, we investigate whether genetic risk for Alzheimer’s disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer’s Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A−T− status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T− status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T− status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A−T− to A+T−, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70–4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84–1.42; P = 0.53). Conversely, for the transition from A+T− to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05–2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27–2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05–6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87–3.49; P = 0.12). The genetic risk for late-onset Alzheimer’s disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer’s disease, in addition to opening therapeutic windows for targeted interventions.