Life-Course Dyslipidemia and Midlife White Matter Hyperintensities: The Bogalusa Heart Study
Christian P. Corsten1,2, Franklin M. Epps1,2, Ileana De Anda-Duran4, Benjamin Almond2, Jacob Albers3, Alexandra Keenan4, David J. Libon5, Lydia A. Bazzano6, Owen Carmichael1
1Pennington Biomedical Research Center, Baton Rouge, LA, USA, 2LSU College of Science, Baton Rouge, LA, USA, 3Emergency Medicine, LSUHSC, Baton Rouge, LA, USA, 4Tulane University, New Orleans, LA, USA, 5Rowan University, New Jersey Institute for Successful Aging and the Department of Psychology, Stratford, NJ and Glassboro, NJ, USA, 6Internal Medicine, UTSW, Dallas, TX, USA
Whether life-course lipid burden shapes midlife brain health, and whether that differs by sex, is unclear.
•Sustained dyslipidemia promotes endothelial dysfunction, harming cerebral perfusion and small-vessel integrity [1,2]
•Dyslipidemia's atherosclerotic effects reach the cerebral microvasculature, contributing to white matter hyperintensities (WMH) [3,4]
•Prior lipid-brain findings are inconsistent [5] and may be sex-specific [6], potentially reflecting the menopause transition [7]
•This study tests whether a novel cumulative dyslipidemia metric (cAUC) predicts midlife WMH, and whether this differs by sex
Lipid burden was tracked from childhood through midlife brain imaging.
•Community-based cohort followed from childhood into midlife since 1972
•Included: ≥2 lipid exams (1985–2010) + brain MRI (2017–2025)
Key terms:
•WMH – T2/FLAIR MRI marker of cerebral small-vessel disease (aging, vascular risk, cognitive decline)
•cAUC – area-under-the-curve summary of cumulative HDL, LDL, and triglyceride deviation from optimal levels
cAUC captures cumulative lipid burden across adulthood, not just a single snapshot.
•% deviation from optimal HDL, LDL, triglycerides calculated at each exam (1985–2010) using AHA/ACC thresholds
•Cumulative exposure = area under the deviation-age curve ÷ years observed (AUC rate)
•Composite Dyslipidemia Burden (cAUC) = sum of the 3 AUC rates, z-scored within sex
WMH and gray matter volume came from validated structural MRI.
•3T scanner (GE Discovery, 32-ch head coil), T1-weighted BRAVO + axial FLAIR; WMH and GMV/TIV quantified via established methods
Sex-stratified regression tested whether the cAUC–WMH link depends on sex.
•WMH_INT (rank-based inverse normal transformed); GMV/TIV analyzed untransformed
•Sex-stratified OLS with HC3 standard errors; adjusted for age at MRI and race
•Sensitivity analyses added statin duration and hypertension; pooled model tested sex × cAUC interaction
The sample (N = 215) was mostly female and White American.
•N = 215; 65% female; 81% White American; mean age 56.8 ± 5.3y at MRI
•Men carried significantly greater cAUC than women (0.61 vs. 0.44, p = 0.006) (Table 1)
The cAUC–WMH association was sex-specific.
•Women (n=139): each 1-SD increase in cAUC linked to 0.13-SD higher WMH_INT (β = 0.129, 95% CI [0.014, 0.245], p = 0.029)
•Men (n=76): association not significant, opposite direction (β = −0.155, 95% CI [−0.371, 0.061], p = 0.161), despite men carrying greater cAUC (Figure 3)
•Formal sex × cAUC interaction confirmed, adjusting for statin exposure (β = 0.239, 95% CI [0.006, 0.472], p = 0.045)
•cAUC was not linked to gray matter volume in either sex; no single lipid fraction independently predicted WMH – supporting cAUC as a cumulative measure
Life-course lipid burden is linked to brain injury in women – supporting early, sex-aware lipid monitoring.
•Greater life-course dyslipidemia burden was linked to higher midlife WMH volume in women, but not men
•Confirmed by formal sex × cAUC interaction testing
•Supports a life-course neurovascular framework linking lipid dysregulation to later cerebrovascular injury
•Reinforces the 2026 ACC/AHA Guideline's call for vigilant lipid monitoring from early adulthood, particularly in women
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8.Blumenthal RS, Morris PB, Gaudino M, et al. 2026 ACC/AHA Guideline on the Management of Dyslipidemia. J Am Coll Cardiol. Published online March 13, 2026.
Funded by the Pennington Biomedical Research Foundation and NIH grants R01AG077497, R01AG077000, RF1AG075769, RF1AG041200, and R01AG062309.
Christian.Corsten@pbrc.edu | ccorst@lsuhsc.edu | 225-716-1682
