Browsing by Author "Dore, Vincent"

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    Polygenic scores for Alzheimer’s disease risk and resilience predict age at onset of amyloid‐β
    (Wiley, 2025-01-03) O’Brien, Eleanor K.; Porter, Tenielle; Fernandez, Shane; Cox, Timothy; Dore, Vincent; Bourgeat, Pierrick; Goudey, Benjamin; Doecke, James D.; Masters, Colin L.; Rowe, Christopher C.; Villemagne, Victor L.; Cruchaga, Carlos; Saykin, Andrew J.; Laws, Simon M.; ADOPIC Consortium (AIBL, ADNI, OASIS); Radiology and Imaging Sciences, School of Medicine
    Background: Genome‐wide association studies (GWAS) have identified numerous genetic variants associated with Alzheimer’s disease (AD) risk, but genetic variation in the onset and progression of AD pathology is less understood. Accumulation of amyloid‐β (Aβ) in the brain is a key pathological hallmark of AD beginning 10 – 20 years prior to cognitive symptoms. We investigated the genetic basis of variation in age at onset (AAO) of brain Aβ by comparing the performance of polygenic scores (PGSs) based on AD risk and resilience with a Aβ‐AAO trait‐specific PGS. Method: 1122 participants from the Alzheimer’s Dementia Onset and Progression in International Cohorts (ADOPIC) study underwent genome‐wide SNP genotyping and assessment of brain Aβ using positron emission tomography (PET) imaging at two or more timepoints. AAO was the age at which participants were estimated to have crossed the 20 centiloid (CL) threshold for high Aβ. We utilised AD risk and resilience GWAS summary statistics and conducted a GWAS for AAO using a cross‐validation approach (10 test‐validation folds). We used PRSice to identify optimal PGSs for Aβ‐AAO for risk (PGSRisk), resilience (PGSResilience) and Aβ‐AAO (PGSAAO). Result: PGSRisk and PGSResilience were both significantly associated with Aβ‐AAO, such that higher PGSRisk and lower PGSResilience were associated with an earlier Aβ‐AAO. PGSRisk showed the strongest association and explained more variance in Aβ‐AAO than did PGSAAO. When stratified by APOE ε4 carriage, the strongest genetic risk factor for AD, the association of PGSRisk with Aβ‐AAO was stronger among ε4 non‐carriers, whilst PGSResilience, was more strongly associated with Aβ‐AAO in ε4 carriers. Conclusion: PGS based on genetic risk and resilience for AD are both significant predictors of the age at which people are estimated to cross the threshold for high brain Aβ burden. Predicting the age at which a person will pass this threshold would enable treatment at an earlier stage, when it may more effectively delay or prevent symptom onset.
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    The prevalence of tau‐PET positivity in aging and dementia
    (Wiley, 2025-01-09) Coomans, Emma M.; Groot, Colin; Rowe, Christopher C.; Dore, Vincent; Villemagne, Victor L.; van de Giessen, Elsmarieke; van der Flier, Wiesje M.; Pijnenburg, Yolande A. L.; Visser, Pieter Jelle; den Braber, Anouk; Pontecorvo, Michael; Shcherbinin, Sergey; Kennedy, Ian A.; Jagust, William J.; Baker, Suzanne L.; Harrison, Theresa M.; Gispert, Juan Domingo; Shekari, Mahnaz; Minguillon, Carolina; Smith, Ruben; Mattsson-Carlgren, Niklas; Palmqvist, Sebastian; Strandberg, Olof; Stomrud, Erik; Malpetti, Maura; O'Brien, John T.; Rowe, James B.; Jäger, Elena; Bischof, Gérard N.; Drzezga, Alexander; Garibotto, Valentina; Frisoni, Giovanni; Peretti, Débora Elisa; Schöll, Michael; Skoog, Ingmar; Kern, Silke; Sperling, Reisa A.; Johnson, Keith A.; Risacher, Shannon L.; Saykin, Andrew J.; Carrillo, Maria C.; Dickerson, Brad C.; Apostolova, Liana G.; Barthel, Henryk; Rullmann, Michael; Messerschmidt, Konstantin; Vandenberghe, Rik; Van Laere, Koen; Spruyt, Laure; Franzmeier, Nicolai; Brendel, Matthias; Gnörich, Johannes; Benzinger, Tammie L. S.; Lagarde, Julien; Sarazin, Marie; Bottlaender, Michel; Villeneuve, Sylvia; Poirier, Judes; Seo, Sang Won; Gu, Yuna; Kim, Jun Pyo; Mormino, Elizabeth; Young, Christina B.; Vossler, Hillary; Rosa-Neto, Pedro; Therriault, Joseph; Rahmouni, Nesrine; Coath, William; Cash, David M.; Schott, Jonathan M.; Rabinovici, Gil D.; La Joie, Renaud; Rosen, Howard J.; Johnson, Sterling C.; Christian, Bradley T.; Betthauser, Tobey J.; Hansson, Oskar; Ossenkoppele, Rik; Radiology and Imaging Sciences, School of Medicine
    Background Tau‐PET imaging allows in‐vivo detection of neurofibrillary tangles. One tau‐PET tracer (i.e., [18F]flortaucipir) has received FDA‐approval for clinical use, and multiple other tau‐PET tracers have been implemented into clinical trials for participant selection and/or as a primary or secondary outcome measure. To optimize future use of tau‐PET, it is essential to understand how demographic, clinical and genetic factors affect tau‐PET‐positivity rates. Method This large‐scale multi‐center study includes 9713 participants from 35 cohorts worldwide who underwent tau‐PET with [18F]flortaucipir (n = 6420), [18F]RO948 (n = 1999), [18F]MK6240 (n = 878) or [18F]PI2620 (n = 416) (Table‐1). We analyzed individual‐level tau‐PET SUVR data using a cerebellar reference region that were processed either centrally (n = 3855) or by each cohort (n = 5858). We computed cohort‐specific SUVR thresholds based on the mean + 2 standard deviations in a temporal meta‐region of amyloid‐negative cognitively normal (CN) individuals aged >50. Logistic generalized estimating equations were used to estimate tau‐PET‐positivity probabilities, using an exchangeable correlation structure to account for within‐cohort correlations. Analyses were performed with (interactions between) age, amyloid‐status, and APOE‐e4 carriership as independent variables, stratified for syndrome diagnosis. Result The study included 5962 CN participants (7.5% tau‐PET‐positive), 1683 participants with mild cognitive impairment (MCI, 33.8% tau‐PET‐positive) and 2068 participants with a clinical diagnosis of dementia (62.1% tau‐PET‐positive) (Figure‐1). From age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 1.2% [95% CI: 0.9%‐1.5%] to 3.7% [2.3%‐5.1%] among CN amyloid‐negative participants; and from 16.4% [10.8%‐22.1%] to 20.5% [18.8%‐22.2%] among CN amyloid‐positive participants. Among amyloid‐negative participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity increased from 3.5% [1.6%‐5.3%] to 11.8% [7.1%‐16.5%] and from 12.6% [4.5%‐20.7%] to 15.9% [6.7%‐25.1%] respectively. In contrast, among amyloid‐positive participants with MCI and dementia, from age 60 to 80 years, the estimated prevalence of tau‐PET‐positivity decreased from 66.5% [57.0%‐76.0%] to 48.3% [42.9%‐53.8%] and from 92.3% [88.7%‐95.9%] to 73.4% [67.5%‐79.3%] respectively. APOE‐e4 status primarily modulated the association of age with tau‐PET‐positivity estimates among CN and MCI amyloid‐positive participants (Figure‐2). Conclusion This large‐scale multi‐cohort study provides robust prevalence estimates of tau‐PET‐positivity, which can aid the interpretation of tau‐PET in the clinic and inform clinical trial designs.