Carotid Intima–Media Thickness Is Associated With White Matter Hyperintensity Burden in Adulthood: The Bogalusa Heart Study
Christian P. Corsten1,2,3, Franklin M. Epps1,2, Jade Jenkins9, Yizhuo Liu10, Bilen Mekonnen4, Grecia Garcia Flores4, David J. Libon7, Lydia A. Bazzano8, Owen T. Carmichael1, Ileana De Anda-Duran4
1Pennington Biomedical Research Center, Baton Rouge, LA, USA, 2LSU Health Sciences Center, New Orleans, LA, USA, 3LSU College of Science, Baton Rouge, LA, USA, 4Tulane University, New Orleans, LA, USA, 7Rowan University, New Jersey Institute for Successful Aging and the Department of Stratford, NJ, and the Department of Psychology, Glassboro, NJ, USA, 8Internal Medicine, UTSW, Dallas, TX, USA, 9[Affiliation TBD], 10[Affiliation TBD]
Subclinical atherosclerosis may injure the brain well before midlife dementia symptoms appear.
•Vascular risk factors (hypertension, dyslipidemia, diabetes, atherosclerosis) are consistently linked to cognitive decline and dementia [1,2]
•Atherosclerosis can injure the brain via altered blood flow, chronic hypoperfusion, and endothelial dysfunction, contributing to cerebral small vessel disease [3,4]
•White matter hyperintensities (WMH) reflect this small-vessel injury and predict cognitive decline; carotid intima-media thickness (cIMT) is a noninvasive marker of subclinical atherosclerosis [5,6]
•This study tests whether cIMT predicts midlife WMH burden in the Bogalusa Heart Study [7]
A 50-year community cohort links life-course vascular health to midlife brain imaging.
•Community cohort followed from childhood into midlife since 1972
•Analytic sample: participants with carotid ultrasound (2013–2016) and brain MRI (2017–2025)
•Key terms:
–WMH – T2/FLAIR MRI marker of cerebral small-vessel disease (aging, vascular risk, cognitive decline)
–cIMT – noninvasive ultrasound marker of subclinical atherosclerosis and vascular burden
cIMT measured via standardized ultrasound protocol.
•Far-wall thickness averaged across 6 segments (carotid bulb, common, internal; right/left) by one trained sonographer
•Composite cIMT = average of segmental maxima, standardized to a z-score
WMH burden was quantified from validated structural MRI sequences.
•3T scanner (GE Discovery, 32-channel head coil); T1-weighted BRAVO + axial FLAIR
•WMH volume quantified with established methods; rank-based inverse normal transformed (WMH_INT) for skew
Six nested OLS models tested whether the cIMT–WMH link holds after adjustment.
•OLS regression with HC3 robust standard errors; outcome = WMH_INT, exposure = cIMT_z
•Models sequentially added: demographics/exam timing → cognitive/education → cardiometabolic medications → health behaviors (Table 1)
•All analyses run in Python (pandas, scipy, statsmodels)
The analytic sample (N = 251) was predominantly female and White American, in midlife.
•N = 251; 62.9% female; 77.7% White American
•Mean age: 55.7 ± 5.4y at MRI; 48.5 ± 4.9y at carotid ultrasound (Table 2)
Higher cIMT signals a heavier white matter hyperintensity burden.
•Unadjusted: each 1-SD increase in cIMT predicted higher WMH_INT (β = 0.164, 95% CI [0.058, 0.270], p = 0.002; N = 251)
•After adjusting for sex, race, age, and ultrasound–MRI interval: association persisted (β = 0.120, 95% CI [0.003, 0.237], p = 0.045)
•Stayed directionally consistent through cognitive/education, medication, and behavior adjustments – reaching significance again in the medication- and behavior-adjusted models (Table 3)
•Fully adjusted: β = 0.119, 95% CI [−0.004, 0.242], p = 0.059 (N = 250) – just short of significance, but consistent in direction
cIMT is an early vascular marker of brain injury in midlife.
•Greater subclinical atherosclerotic burden (cIMT) was linked to higher WMH burden in midlife
•Association was robust unadjusted and only partially attenuated after full adjustment
•Supports cIMT as an early marker of brain injury and a key window for cardiovascular prevention
1.Livingston G, Huntley J, Sommerlad A, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396(10248):413–446.
2.Iadecola C. The pathobiology of vascular dementia. Neuron. 2013;80(4):844–866.
3.Gorelick PB, Scuteri A, Black SE, et al. Vascular contributions to cognitive impairment and dementia. Stroke. 2011;42(9):2672–2713.
4.Wardlaw JM, Smith C, Dichgans M. Mechanisms of sporadic cerebral small vessel disease. Lancet Neurol. 2013;12(5):483–497.
5.Debette S, Markus HS. Clinical importance of white matter hyperintensities on brain MRI. Lancet Neurol. 2010;9(9):910–922.
6.Stein JH, Korcarz CE, Hurst RT, et al. Use of carotid ultrasound to identify subclinical vascular disease. Circulation. 2008;118(8):e218–e237.
7.De Anda-Duran I, Fernandez Alonso C, Libon DJ, et al. Carotid intima-media thickness and midlife cognitive function. Neurology. 2022;98(18):e1828–e1836.
●
Grant numbers: RF1AG075769, R01 AG077497, R01 AG041200, and R01 AG062309
Christian.Corsten@pbrc.edu | ccorst@lsuhsc.edu | 225-716-1682
