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Background: Multimorbidity (defined as ≥2 chronic conditions) has been associated with increased risk of mild cognitive impairment and cross-sectionally with imaging biomarkers of neurodegeneration in cognitively unimpaired persons aged ≥70 years. Its association with preclinical Alzheimer's disease stages has not been studied in detail yet. The objective of the study was to assess the cross-sectional association of multimorbidity with preclinical Alzheimer's disease stages and suspected non-amyloid pathophysiology in cognitively unimpaired participants of the Mayo Clinic Study of Aging (≥50 years of age).Methods: The study included 1,535 cognitively unimpaired participants with multimorbidity, 11C-PiB positron emission topography and magnetic resonance imaging data available. Abnormal (elevated) 11C-PiB-positron emission topography retention ratio (A+; standardized uptake value ratio >1.42) and abnormal (reduced) Alzheimer's disease signature cortical thickness (N+; <2.67 mm) were used to define biomarker combinations (A-N-, A+N-, A-N+, A+N+). Chronic medical conditions were ascertained by using the Rochester Epidemiology Project medical records linkage system and International Classification of Diseases criteria. Cross-sectional associations were examined using multinomial logistic regression models adjusting for age, sex, education, and apolipoprotein E ɛ4 allele status.Results: Frequency of A+, N+, A+N+, and A-N+ biomarker groups increased significantly with increasing number of chronic conditions. Multimorbidity was significantly associated with A+N+ (vs A-N-; odds ratio, 1.76, 95% confidence interval 1.02, 2.90) and A-N+ (vs A-N-; odds ratio, 2.16, 95% confidence interval 1.47, 3.18). There was a dose-response relationship between increasing number of chronic conditions (eg, 0-1, 2-3, and 4+) and the odds of A+N+ and A-N+ (vs A-N-).Conclusions: Multimorbidity was associated with biomarker combinations that included neurodegeneration with or without elevated amyloid deposition (ie, A-N+, A+N+). The associations should be validated in longitudinal studies. [ABSTRACT FROM AUTHOR]