Effects of Vascular Risk Factors on the Association of Blood-Based Biomarkers with Alzheimer's Disease.

Background: Comorbidities may influence the levels of blood-based biomarkers for Alzheimer's disease (AD). We investigated whether differences in risk factors or comorbid conditions might explain the discordance between clinical diagnosis and biomarker classifications in a multi-ethnic cohort of elderly individuals. Aims: To evaluate the relationship of medical conditions and other characteristics, including body mass index (BMI), vascular risk factors, and head injury, with cognitive impairment and blood-based biomarkers of AD, phosphorylated tau (P-tau 181, P-tau 217), in a multi-ethnic cohort. Methods: Three-hundred individuals, aged 65 and older, were selected from a prospective community-based cohort for equal representation among three racial/ethnic groups: non-Hispanic White, Hispanic/Latino and African American/Black. Participants were classified into four groups based on absence (Asym) or presence (Sym) of cognitive impairment and low (NEG) or high (POS) P-tau 217 or P-tau 181 levels, determined previously in the same cohort: (Asym/NEG, Asym/POS, Sym/NEG, Sym/POS). We examined differences in individual characteristics across the four groups. We performed post-hoc analysis examining the differences across biomarker and cognitive status. Results: P-tau 217 or P-tau 181 positive individuals had lower BMI than P-tau negative participants, regardless of symptom status. Symptomatic and asymptomatic participants did not differ in terms of BMI. BMI was not a mediator of the effect of P-tau 217 or P-tau 181 on dementia. Frequencies of other risk factors did not differ between the four groups of individuals. Conclusions: Participants with higher levels of P-tau 217 or P-tau 181 consistent with AD had lower BMI regardless of whether the individual was symptomatic. These findings suggest that weight loss may change with AD biomarker levels before onset of cognitive decline. They do not support BMI as a confounding variable. Further longitudinal studies could explore the relationship of risk factors with clinical diagnoses and biomarkers.