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Menopausal Vasomotor Symptoms and White Matter Hyperintensities in Midlife Women
Rebecca C Thurston1, Minjie Wu2, Yue-Fang Chang2
1From the Department of Psychiatry (R.C.T., M.W., H.J.A.), Epidemiology (R.C.T., E.A.B.-M.), Psychology (R.C.T.), and Neurosurgery (Y.-F.C.), University of Pittsburgh, PA; Department of Neurology and Epidemiology and Population Health (C.A.D.), Albert Einstein College of Medicine, Bronx, NY; and Department of Psychiatry (P.M.), University of Illinois at Chicago, IL. thurstonrc@upmc.edu.
Background And Objectives:
The menopause transition is increasingly recognized as a time of importance for women's brain health. A growing body of work indicates that the classic menopausal symptom, vasomotor symptom (VMS), may be associated with poorer cardiovascular health. Other work links VMS to poorer cognition. We investigate whether VMS, when rigorously assessed using physiologic measures, are associated with greater white matter hyperintensity volume (WMHV) among midlife women. We consider a range of potential explanatory factors in these associations and explore whether VMS are associated with the spatial distribution of WMHV.
Methods:
Women aged 45-67 years and free of hormone therapy underwent 24 hours of physiologic VMS monitoring (sternal skin conductance), actigraphy assessment of sleep, physical measures, phlebotomy, and 3 Tesla neuroimaging. Associations between VMS (24-hour, wake, and sleep VMS, with wake and sleep intervals defined by actigraphy) and whole brain WMHV were considered in linear regression models adjusted for age, race, education, smoking, body mass index, blood pressure, insulin resistance, and lipids. Secondary models considered WMHV in specific brain regions (deep, periventricular, frontal, temporal, parietal, and occipital) and additional covariates including sleep.
Results:
The study sample included 226 women. Physiologically assessed VMS were associated with greater whole brain WMHV in multivariable models, with the strongest associations observed for sleep VMS (24-hour VMS, B[SE] = 0.095 [0.045], p = 0.032; Wake VMS, B[SE] = 0.078 [0.046], p = 0.089, Sleep VMS, B[SE] = 0.173 [0.060], p = 0.004). Associations were not accounted for by additional covariates including actigraphy-assessed sleep (wake after sleep onset). When considering the spatial distribution of WMHV, sleep VMS were associated with both deep WMHV, periventricular WMHV, and frontal lobe WMHV.
Discussion:
VMS, particularly VMS occurring during sleep, were associated with greater WMHV. Identification of female-specific midlife markers of poor brain health later in life is critical to identify women who warrant early intervention and prevention. VMS have the potential to serve as female-specific midlife markers of brain health in women.
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