The relationship between telomere length and neuropsychological test performance in a diverse sample of Wisconsin Alzheimer's Disease Research Center participants.

Background: Age is the most significant predictor of Alzheimer's disease and related dementias (ADRD). Biological age, in contrast to chronological age, is modifiable – shaped by environmental and social factors which contribute to the functional declines observed in aging. Accelerated biological aging has been observed in historically underrepresented populations in ADRD research who are at highest risk for developing ADRD. Telomere length (TL) is a marker of biological age and empirically associated with cognitive aging. However, this association has not been investigated in historically underrepresented populations such as American Indians / Alaska Natives (AI/AN). This study reports on the utility of TL to predict cognitive performance in a sample of middle‐aged and older adults from Wisconsin communities historically underrepresented in ADRD research. Method: The Wisconsin Alzheimer's Disease Research Center's (WADRC) Inclusion of Underrepresented Groups Core engages AI/AN, Blacks / African Americans (B/AA), and participants of multi‐race and ethnicity identities through community based participatory research practices. A sample (n = 188) identifying their race as AI/AN or B/AA were included if they provided whole blood and completed the Rey Auditory Verbal Learning Test (RAVLT, Trials 1‐5) and the Trails Making Test (TMT, A and B times) for verbal learning and executive functioning, respectively. DNA was extracted from whole blood and analyzed with monochrome multiplex quantitative polymerase chain reaction for TL. Multivariable linear regression analyses tested relationships between TL and cognitive test performance. Result: The participants (mean age = 60.88 ±9.06) were majority female, with 79.26% B/AA and 12.77% AI/AN (Table 1). In bivariate analyses, TL significantly correlated with all outcomes: longer telomeres correlated with better verbal learning and executive functioning performance (Figure 1A‐C). In multivariable regression models, TL significantly predicted cognitive performance for all outcomes independent of participant sex, race, age, and cognitive status (Table 2). Conclusion: These findings suggest that TL is a strong predictor of cognitive performance for historically underrepresented populations, offering potential opportunities for screening of accelerated biological aging and interventions. The community‐led research at the WADRC makes this analysis the first of its kind to include AI/AN participants. Future ADRD research should consider behavioral and socioeconomic interventions shown to modify biological aging. [ABSTRACT FROM AUTHOR]