Review ArticleCerebral White Matter Hyperintensity in African Americans and European Americans with Type 2 Diabetes
Section snippets
Study Populations
For analyses in DHS-Mind (including AA-DHS-Mind participants), a subsample was selected comprising all 46 unrelated AA participants recruited to date and 156 age- and sex-matched unrelated EAs with similar demographic and clinical characteristics as the AA participants. Recruitment and ascertainment of DHS participants has been described previously. In brief, the DHS recruited siblings concordant for T2D without evidence of advanced renal insufficiency through internal medicine clinics and
Results
The distribution of WMH was compared in the 46 AAs and 156 matched EAs in the DHS-Mind series. As in the full AA-DHS sample,21 the AAs had a similar mean duration of T2D as the EAs despite being on average 6 years younger than the EAs (Table 1). Baseline data revealed that AAs in the DHS-Mind had higher mean diastolic blood pressure (73.0 vs 68.6 mm Hg) and slightly lower mean body mass index (33.7 vs 36.0 kg/m2). There were no statistically significant differences between the AAs and EAs in
Discussion
Our analysis of independent datasets including patients with T2D residing in North Carolina revealed equal or slightly lower levels of WMH in AAs compared with EAs. These findings stand in stark contrast to those of 2 previous reports. The Chicago Health and Aging Project (CHAP) and Washington Heights–Inwood Columbia Aging Project (WHICAP) reported equal or greater WMH scores in AAs relative to EAs, as well as significantly higher burdens of conventional CBVD risk factors in AAs. CHAP assessed
Acknowledgments
We thank all of the participants in this study, as well as Cassandra Bethea, RN, principal recruiter for the DHS-Mind study, and Sally Mauney, Carol Thomas, and Joni Hanna, study coordinators for the DHS-Mind study.
Author Contributions: JD, KMS, JAM, and BIF conceptualized and designed the study. JD conducted the statistical analyses, with input from CH, KMS, JAM, and BIF. YG wrote the application for searching the hospital database to identify the sample of patients with clinically indicated
References (30)
- et al.
A systematic review and meta-analysis of ethnic differences in use of dementia treatment, care, and research
Am J Geriatr Psychiatry
(2010) - et al.
Age-associated alterations in cortical gray and white matter signal intensity and gray to white matter contrast
Neuroimage
(2009) - et al.
Racial and ethnic differences in incident myocardial infarction in end-stage renal disease patients: The USRDS
Kidney Int
(2006) - et al.
Apoptosis in leukoaraiosis
AJNR Am J Neuroradiol
(2000) - et al.
Ischemic basis for deep white matter hyperintensities in major depression: A neuropathological study
Arch Gen Psychiatry
(2002) - et al.
Pathogenesis of leukoaraiosis: A review
Stroke
(1997) - et al.
Brain white matter hyperintensities: Relative importance of vascular risk factors in nondemented elderly people
Radiology
(2005) - et al.
The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: Systematic review and meta-analysis
BMJ
(2010) - et al.
Cerebral white matter lesions and the risk of dementia
Arch Neurol
(2004) - et al.
White matter hyperintensity on cranial magnetic resonance imaging: A predictor of stroke
Stroke
(2004)
Association of MRI markers of vascular brain injury with incident stroke, mild cognitive impairment, dementia, and mortality: The Framingham Offspring Study
Stroke
The association of magnetic resonance imaging measures with cognitive function in a biracial population sample
Arch Neurol
Brain morphology in older African Americans, Caribbean Hispanics, and whites from northern Manhattan
Arch Neurol
White matter hyperintensity and cognitive functioning in the racial and ethnic minority cohort of the Framingham Heart Study
Neuroepidemiology
Hypertension, cardiac disease, and compliance in minority patients
Am J Med
Cited by (17)
White matter hyperintensities in diverse populations: A systematic review of literature in the United States
2024, Cerebral Circulation - Cognition and BehaviorRacial differences in white matter hyperintensity burden in older adults
2023, Neurobiology of AgingCitation Excerpt :When examining WMHs in a racially diverse cohort, results have been conflicting as to whether racial differences in WMH burden exist. For example, some studies report that there are no significant differences in WMH burden because of racial group (when comparing African American/Black individuals [hereafter referred to as Black{s}] to European American/Caucasian/White individuals [hereafter referred to as White{s}]) (Amariglio et al., 2020; Divers et al., 2013). Conversely, other studies have reported increased WMH burden in Blacks compared to Whites (Brickman et al., 2008; Zahodne et al., 2015).
Construction and validation of a cerebral white matter hyperintensity probability map of older Koreans
2021, NeuroImage: ClinicalCitation Excerpt :First, the differences between age groups may not necessarily indicate the age-associated changes because this study employed a cross-sectional design. Second, our WMP may not be directly applicable to the population of different ethnicities like Caucasians and/or living in different geographic regions because brain shape is different between ethnic groups (Lee et al., 2016) and the risk of WMH is also different between ethnic groups and/or geographic regions with different lifestyles and environments (Divers et al., 2013; Gow et al., 2012). Third, although we tried to compensate for differences in resolution of the images by normalizing them to a common template, pooling MR images from two different scanners and protocols might influence the accuracy for the measurement (Schnack et al., 2004).
Relationships between cerebral structure and cognitive function in African Americans with type 2 diabetes
2018, Journal of Diabetes and its ComplicationsCitation Excerpt :In multi-ethnic cohorts, type 2 diabetes is associated with brain atrophy and WML burden, which are in turn associated with poorer cognitive performance.21, 22 We previously reported in the DHS MIND study that the extent of white matter disease is similar between African Americans and European Americans with type 2 diabetes.43 WML burden was associated with poorer cognitive performance in European American participants (DSC, RAVLT and semantic fluency) and with DSC and Stroop interference in African Americans.21, 22
Racial Difference in Cerebral Microbleed Burden Among a Patient Population in the Mid-South United States
2018, Journal of Stroke and Cerebrovascular DiseasesCitation Excerpt :In our study, although African-Americans had a higher rate of large confluent white matter lesions, we did not observe a significant racial difference in the severity of white matter disease. This observation is consistent with our previous observation among African-Americans and White stroke patients20 as well as results from Wake Forest datasets containing black and white patients with type 2 diabetes.21 However, Nyquist et al found that African-American race is an independent risk factor for severe white matter lesions in a population enriched for vascular risk factors.22
Racial Difference in Cerebral Microbleed Burden among Ischemic Stroke Patients
2017, Journal of Stroke and Cerebrovascular DiseasesCitation Excerpt :Although African American stroke patients had a higher rate of large confluent white matter lesions in our study, we did not observe a significant racial difference in the severity of DWML. Analyses of independent Wake Forest datasets containing patients with type 2 diabetes also did not show a higher rate of white matter hyperintensity among African Americans.45 However, Nyquist et al found that African American race is an independent risk factor for extreme DWML volume in a population enriched for vascular risk factors.46
Supported in part by the General Clinical Research Center of the Wake Forest University School of Medicine grant MO1 RR07122, National Institute of Diabetes and Digestive and Kidney Diseases grant RO1 DK071891 (to BIF), National Heart, Lung, and Blood Institute grant RO1 HL67348 (to DWB), National Institute of Diabetes and Digestive and Kidney Diseases grant F32 DK083214(to CH), and National Institute of Neurological Disorders and Stroke grant RO1 NS075107 (to JD, JAM, and BIF).