- Browse by Author
Browsing by Author "Goh, Sheng-Yang M."
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease(Wiley, 2021-07-05) Keret, Ophir; Staffaroni, Adam M.; Ringman, John M.; Cobigo, Yann; Goh, Sheng-Yang M.; Wolf, Amy; Allen, Isabel Elaine; Salloway, Stephen; Chhatwal, Jasmeer; Brickman, Adam M.; Reyes-Dumeyer, Dolly; Bateman, Randal J.; Benzinger, Tammie L.S.; Morris, John C.; Ances, Beau M.; Joseph-Mathurin, Nelly; Perrin, Richard J.; Gordon, Brian A.; Levin, Johannes; Vöglein, Jonathan; Jucker, Mathias; la Fougère, Christian; Martins, Ralph N.; Sohrabi, Hamid R.; Taddei, Kevin; Villemagne, Victor L.; Schofield, Peter R.; Brooks, William S.; Fulham, Michael; Masters, Colin L.; Ghetti, Bernardino; Saykin, Andrew J.; Jack, Clifford R.; Graff-Radford, Neill R.; Weiner, Michael; Cash, David M.; Allegri, Ricardo F.; Chrem, Patricio; Yi, Su; Miller, Bruce L.; Rabinovici, Gil D.; Rosen, Howard J.; Pathology and Laboratory Medicine, School of MedicineIntroduction: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. Methods: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. Results: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials.Item Plasma Neurofilament Light for Prediction of Disease Progression in Familial Frontotemporal Lobar Degeneration(American Academy of Neurology, 2021-05-04) Rojas, Julio C.; Wang, Ping; Staffaroni, Adam M.; Heller, Carolin; Cobigo, Yann; Wolf, Amy; Goh, Sheng-Yang M.; Ljubenkov, Peter A.; Heuer, Hilary W.; Fong, Jamie C.; Taylor, Joanne B.; Veras, Eliseo; Song, Linan; Jeromin, Andreas; Hanlon, David; Yu, Lili; Khinikar, Arvind; Sivasankaran, Rajeev; Kieloch, Agnieszka; Valentin, Marie-Anne; Karydas, Anna M.; Mitic, Laura L.; Pearlman, Rodney; Kornak, John; Kramer, Joel H.; Miller, Bruce L.; Kantarci, Kejal; Knopman, David S.; Graff-Radford, Neill; Petrucelli, Leonard; Rademakers, Rosa; Irwin, David J.; Grossman, Murray; Ramos, Eliana Marisa; Coppola, Giovanni; Mendez, Mario F.; Bordelon, Yvette; Dickerson, Bradford C.; Ghoshal, Nupur; Huey, Edward D.; Mackenzie, Ian R.; Appleby, Brian S.; Domoto-Reilly, Kimiko; Hsiung, Ging-Yuek R.; Toga, Arthur W.; Weintraub, Sandra; Kaufer, Daniel I.; Kerwin, Diana; Litvan, Irene; Onyike, Chiadikaobi U.; Pantelyat, Alexander; Roberson, Erik D.; Tartaglia, Maria C.; Foroud, Tatiana; Chen, Weiping; Czerkowicz, Julie; Graham, Danielle L.; van Swieten, John C.; Borroni, Barbara; Sanchez-Valle, Raquel; Moreno, Fermin; Laforce, Robert; Graff, Caroline; Synofzik, Matthis; Galimberti, Daniela; Rowe, James B.; James B., Mario; Finger, Elizabeth; Vandenberghe, Rik; de Mendonça, Alexandre; Tagliavini, Fabrizio; Santana, Isabel; Ducharme, Simon; Butler, Chris R.; Gerhard, Alexander; Levin, Johannes; Danek, Adrian; Otto, Markus; Sorbi, Sandro; Cash, David M.; Convery, Rhian S.; Bocchetta, Martina; Foiani, Martha; Greaves, Caroline V.; Peakman, Georgia; Russell, Lucy; Swift, Imogen; Todd, Emily; Rohrer, Jonathan D.; Boeve, Bradley F.; Rosen, Howard J.; Boxer, Adam L.; Neurology, School of MedicineObjective: We tested the hypothesis that plasma neurofilament light chain (NfL) identifies asymptomatic carriers of familial frontotemporal lobar degeneration (FTLD)-causing mutations at risk of disease progression. Methods: Baseline plasma NfL concentrations were measured with single-molecule array in original (n = 277) and validation (n = 297) cohorts. C9orf72, GRN, and MAPT mutation carriers and noncarriers from the same families were classified by disease severity (asymptomatic, prodromal, and full phenotype) using the CDR Dementia Staging Instrument plus behavior and language domains from the National Alzheimer's Disease Coordinating Center FTLD module (CDR+NACC-FTLD). Linear mixed-effect models related NfL to clinical variables. Results: In both cohorts, baseline NfL was higher in asymptomatic mutation carriers who showed phenoconversion or disease progression compared to nonprogressors (original: 11.4 ± 7 pg/mL vs 6.7 ± 5 pg/mL, p = 0.002; validation: 14.1 ± 12 pg/mL vs 8.7 ± 6 pg/mL, p = 0.035). Plasma NfL discriminated symptomatic from asymptomatic mutation carriers or those with prodromal disease (original cutoff: 13.6 pg/mL, 87.5% sensitivity, 82.7% specificity; validation cutoff: 19.8 pg/mL, 87.4% sensitivity, 84.3% specificity). Higher baseline NfL correlated with worse longitudinal CDR+NACC-FTLD sum of boxes scores, neuropsychological function, and atrophy, regardless of genotype or disease severity, including asymptomatic mutation carriers. Conclusions: Plasma NfL identifies asymptomatic carriers of FTLD-causing mutations at short-term risk of disease progression and is a potential tool to select participants for prevention clinical trials. Trial registration information: ClinicalTrials.gov Identifier: NCT02372773 and NCT02365922. Classification of evidence: This study provides Class I evidence that in carriers of FTLD-causing mutations, elevation of plasma NfL predicts short-term risk of clinical progression.