HAI Book 2025 - Flipbook - Page 370
Katsumi, Yuta
83
EOAD-signature atrophy predicts progression to dementia in patients
with early-onset MCI due to Alzheimer9s disease
Thiago Paranhos1, Yuta Katsumi1, Michael Brickhouse1, Ryan Eckbo1, Alexander Zaitsev1, Anna
Du1, Ani Eloyan2, Kelly N. Nudelman3, Tatiana Foroud3, Jeffrey L. Dage3,4, Maria C. Carrillo5, Gil
D. Rabinovici6, Liana Apostolova3,4,7, Bradford C. Dickerson1, Alexandra Touroutoglou1, LEADS
Consortium3
Frontotemporal Disorders Unit and Massachusetts Alzheimer’s Disease Research Center, Department of Neurology,
Massachusetts General Hospital and Harvard Medical School, Boston, MA, US
2
Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, RI, US
3
Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, US
4
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, US
5
Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, IL, US
6
Department of Neurology, University of California – San Francisco, San Francisco, CA, US
7
Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine
Indianapolis, Indianapolis, IN, US
1
Prognostic risk stratification for patients at the mild cognitive impairment (MCI) stage of early-onset Alzheimer9s
disease (EOAD) would allow professionals and loved ones to make better-informed medical and life planning
decisions. While research including our own (Bakkour, Morris, Dickerson, 2009) has demonstrated the prognostic
value of MRI-based measures of brain structure in late-onset amnestic AD, its utility for predicting progression to
dementia in EOAD remains unclear. Here, we measured the magnitude of cortical atrophy within our recently
described EOAD signature regions (Touroutoglou et al. 2023) in patients with EOAD at the MCI stage (N=84)
recruited in LEADS. The main goal of the study was to evaluate the utility of this measure as a predictor of time to
subsequent progression to dementia. Our second goal was to examine the independent or synergistic
contributions of EOAD signature of atrophy and standard clinical severity measures used in clinical trials. For each
patient, we measured the time between baseline visit and subsequent visit at which progression to mild dementia
was documented or last observation. Baseline cortical atrophy was measured as W-scores (i.e., Z-scores adjusted
for age and sex relative to a sample of healthy controls) in the EOAD signature. Baseline clinical severity was
quantified with the Clinical Dementia Rating Sum-of-Boxes scores (CDR-SB). Simple and multivariable Cox
regression models examined the relationship between atrophy in EOAD signature, CDR-SB, and the likelihood of
progression to dementia. Greater baseline atrophy in the EOAD signature predicted higher risk of progression to
dementia (hazard ratio = 1.2, 95% CI 1.1-1.3) and provided additive value to the CDR-SB (hazard ratio: 2.1, 95%
CI:1.7-2.8) in predicting progression. These findings point to the role of EOAD MRI signature as an imaging
biomarker to guide prognostication for patients with EOAD and their families and to inform the design of clinical
trials.
Keywords: Magnetic Resonance Imaging; Clinical Dementia Rating Scale Sum of Boxes; prognostication; diseasemodifying therapies; risk stratification
HAI2025 - 370
