Effects and Thresholds of Young to Midlife Vascular Risks on Brain Health

Author:

Maas Matthew B.12ORCID,Mahinrad Simin1ORCID,Sedaghat Sanaz13ORCID,Yaffe Kristine4,Launer Lenore J.5ORCID,Bryan R. Nick6ORCID,Sidney Stephen7,Gorelick Philip B.1ORCID,Lloyd-Jones Donald M.28ORCID,Sorond Farzaneh A.1ORCID

Affiliation:

1. Department of Neurology (M.B.M., S.M., S. Sedaghat, P.B.G., F.A.S.), Northwestern University, Chicago, IL.

2. Institute for Public Health and Medicine (M.B.M., D.M.L.-J.), Northwestern University, Chicago, IL.

3. Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (S. Sedaghat).

4. Departments of Neurology, Psychiatry, and Epidemiology, University of California, San Francisco (K.Y.).

5. Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD (L.J.L.).

6. Department of Radiology, University of Pennsylvania, Philadelphia (R.N.B.).

7. Division of Research, Kaiser Permanente Northern California, Oakland (S. Sidney).

8. Department of Preventative Medicine (D.M.L.-J.), Northwestern University, Chicago, IL..

Abstract

BACKGROUND: Vascular risk factors, particularly hypertension, are important contributors to accelerated brain aging. We sought to quantify vascular risk factor risks over adulthood and assess the empirical evidence for risk thresholds. METHODS: We used SBP (systolic blood pressure) and diastolic blood pressure, total cholesterol, fasting blood glucose, and body mass index measurements collected from participants in the CARDIA study (Coronary Artery Risk Development in Young Adults) at 2- to 5-year intervals through year 30. The Montreal Cognitive Assessment and domain-specific cognitive tests were performed at year 30. White matter hyperintensity volume was measured by magnetic resonance imaging. We used a 2-step method to fit longitudinal vascular risk factor exposures to optimized spline functions with mixed-effects models, then used the participant-specific random effects that characterized individual exposures over time in cross-sectional models adjusted for sex, race, age, and education to study effects on midlife brain health. RESULTS: Change in SBP up to 33 years of age was negatively associated with Montreal Cognitive Assessment scores (−0.29 Montreal Cognitive Assessment Z score per mm Hg/y change [95% CI, −0.49 to −0.09]; P =0.005), with similar effects for SBP changes from 33 to 49 years of age (−0.08 [95% CI, −0.16 to 0.01]; P =0.08). We observed comparable, significant associations between SBP exposure during those ages, midlife performance on specific cognitive domains, and volume of white matter hyperintensity (all P <0.05). SBP ≤111 mm Hg was the estimated threshold below which no harmful association with midlife cognitive performance was identified. CONCLUSIONS: SBP in early adulthood is the vascular risk factor most strongly associated with midlife cognitive performance and white matter hyperintensity burden, with SBP 111 mm Hg suggested as a harm threshold.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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