Maria Vassilaki1, Jeremiah A Aakre2, Michelle M Mielke2, Yonas E Geda2, Walter K Kremers2, Rabe E Alhurani2, Mary M Machulda2, David S Knopman2, Ronald C Petersen2, Val J Lowe2, Clifford R Jack2, Rosebud O Roberts1. 1. From the Departments of Health Sciences Research (M.V., J.A.A., M.M. Mielke, Y.E.G., W.K.K., R.C.P., R.O.R.) and Neurology (M.M. Mielke, Y.E.G., R.E.A., D.S.K., R.C.P., R.O.R.), Mayo Clinic, Rochester, MN; Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ; Mayo Clinic Graduate School of Medicine (R.E.A.), Rochester, MN; and Departments of Psychiatry and Psychology (M.M. Machulda) and Radiology (V.J.L., C.R.J.), Mayo Clinic, Rochester, MN. roberts.rosebud@mayo.edu Vassilaki.Maria@mayo.edu. 2. From the Departments of Health Sciences Research (M.V., J.A.A., M.M. Mielke, Y.E.G., W.K.K., R.C.P., R.O.R.) and Neurology (M.M. Mielke, Y.E.G., R.E.A., D.S.K., R.C.P., R.O.R.), Mayo Clinic, Rochester, MN; Departments of Psychiatry and Psychology and Neurology (Y.E.G.), Mayo Clinic, Scottsdale, AZ; Mayo Clinic Graduate School of Medicine (R.E.A.), Rochester, MN; and Departments of Psychiatry and Psychology (M.M. Machulda) and Radiology (V.J.L., C.R.J.), Mayo Clinic, Rochester, MN.
Abstract
OBJECTIVE: To assess the cross-sectional association between multimorbidity and imaging biomarkers of brain pathology in the population-based Mayo Clinic Study of Aging (MCSA). METHODS: The study consisted of 1,449 MCSA participants who were cognitively normal at the time of MRI. A subset of the participants also had (11)C-Pittsburgh compound B (n = 689) and (18)fluorodeoxyglucose (n = 688) PET scans available. Information on multimorbidity (defined as ≥2 chronic conditions) in the 5 years prior to the first imaging study was captured from the medical record using ICD-9 codes for chronic conditions and the Rochester Epidemiology Project medical records linkage system. The cross-sectional association of multimorbidity and imaging biomarkers was examined using logistic and linear regression models. RESULTS: Among 1,449 cognitively normal participants (mean age 79 years; 50.9% men), 85.4% had multimorbidity (≥2 chronic conditions). Multimorbidity and severe multimorbidity (≥4 chronic conditions) were associated with abnormal Alzheimer disease (AD) signature meta-region of interest (meta-ROI) (18)F-FDG hypometabolism (odds ratio [OR] 2.03; 95% confidence interval [CI] 1.10-3.77 and OR 2.22; 95% CI 1.18-4.16, respectively), and with abnormal AD signature MRI cortical thickness (OR 1.53; 95% CI 1.09-2.16 and OR 1.76; 95% CI 1.24-2.51, respectively), but was not associated with amyloid accumulation. CONCLUSIONS: Multimorbidity was associated with brain pathology through mechanisms independent of amyloid deposition and such neuronal injury and pathology was present before any symptomatic evidence of cognitive impairment. Longitudinal follow-up will provide insights into potential causal associations of multimorbidity with changes in brain pathology.
OBJECTIVE: To assess the cross-sectional association between multimorbidity and imaging biomarkers of brain pathology in the population-based Mayo Clinic Study of Aging (MCSA). METHODS: The study consisted of 1,449 MCSA participants who were cognitively normal at the time of MRI. A subset of the participants also had (11)C-Pittsburgh compound B (n = 689) and (18)fluorodeoxyglucose (n = 688) PET scans available. Information on multimorbidity (defined as ≥2 chronic conditions) in the 5 years prior to the first imaging study was captured from the medical record using ICD-9 codes for chronic conditions and the Rochester Epidemiology Project medical records linkage system. The cross-sectional association of multimorbidity and imaging biomarkers was examined using logistic and linear regression models. RESULTS: Among 1,449 cognitively normal participants (mean age 79 years; 50.9% men), 85.4% had multimorbidity (≥2 chronic conditions). Multimorbidity and severe multimorbidity (≥4 chronic conditions) were associated with abnormal Alzheimer disease (AD) signature meta-region of interest (meta-ROI) (18)F-FDG hypometabolism (odds ratio [OR] 2.03; 95% confidence interval [CI] 1.10-3.77 and OR 2.22; 95% CI 1.18-4.16, respectively), and with abnormal AD signature MRI cortical thickness (OR 1.53; 95% CI 1.09-2.16 and OR 1.76; 95% CI 1.24-2.51, respectively), but was not associated with amyloid accumulation. CONCLUSIONS: Multimorbidity was associated with brain pathology through mechanisms independent of amyloid deposition and such neuronal injury and pathology was present before any symptomatic evidence of cognitive impairment. Longitudinal follow-up will provide insights into potential causal associations of multimorbidity with changes in brain pathology.
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