INTRODUCTION: Blood-based biomarkers of amyloid pathology and neurodegeneration are entering clinical use. It is critical to understand what factors affect the levels of these markers. METHODS: Plasma markers (Aβ42, Aβ40, NfL, T-tau, Aβ42/40 ratio) were measured on the Quanterix Simoa HD-1 analyzer for 996 Mayo Clinic Study of Aging (MCSA) participants, aged 51 to 95 years. All other data were collected during in-person MCSA visits or abstracted from the medical record. RESULTS: Among cognitively unimpaired (CU) participants, all plasma markers correlated with age. Linear regression models revealed multiple relationships. For example, higher Charlson Comorbidity Index and chronic kidney disease were associated with higher levels of all biomarkers. Some relationships differed between mild cognitive impairment and dementia participants. DISCUSSION: Multiple variables affect plasma biomarkers of amyloid pathology and neurodegeneration among CU in the general population. Incorporating this information is critical for accurate interpretation of the biomarker levels and for the development of reference ranges.
INTRODUCTION: Blood-based biomarkers of amyloid pathology and neurodegeneration are entering clinical use. It is critical to understand what factors affect the levels of these markers. METHODS: Plasma markers (Aβ42, Aβ40, NfL, T-tau, Aβ42/40 ratio) were measured on the Quanterix Simoa HD-1 analyzer for 996 Mayo Clinic Study of Aging (MCSA) participants, aged 51 to 95 years. All other data were collected during in-person MCSA visits or abstracted from the medical record. RESULTS: Among cognitively unimpaired (CU) participants, all plasma markers correlated with age. Linear regression models revealed multiple relationships. For example, higher Charlson Comorbidity Index and chronic kidney disease were associated with higher levels of all biomarkers. Some relationships differed between mild cognitive impairment and dementia participants. DISCUSSION: Multiple variables affect plasma biomarkers of amyloid pathology and neurodegeneration among CU in the general population. Incorporating this information is critical for accurate interpretation of the biomarker levels and for the development of reference ranges.
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