Differential Effect of Left vs. Right White Matter Hyperintensity Burden on Functional Decline: The Northern Manhattan Study

Prevalence and clinical characteristics of white matter hyperintensities in Migraine: A meta-analysis

BACKGROUND

Current evidences show an increased risk of white matter hyperintensities (WMHs) in migraineurs compared to age-matched controls. However, WMHs prevalence and the associations between WMHs and clinical characteristics in migraineurs have not been systematically evaluated using a meta-analytical approach. This study explored the pooled prevalence of WMHs and the associations of WMHs with the clinical characteristics in patients with migraine.

METHODS

A systematic review and meta-analysis of observational studies reporting the occurrence and clinical characteristics of patients with WMHs attributed to migraine was performed. We searched the PubMed, Web of Science, and Embase databases. Random-effects models were used to calculate the pooled prevalence rate, odds ratio (OR), or mean difference (MD) with corresponding 95% confidence intervals (CIs).

RESULTS

Thirty eligible studies were identified including 3,502 migraineurs aged 37.2 (mean) years. The pooled WMHs prevalence was 44 %, 45 %, and 38 % in migraine, migraine with aura, and migraine without aura groups, respectively. In migraineurs with WMHs, the frontal lobe and subcortical white matter were the most susceptible area. Compared with non-migraine controls, patients with migraine had increased odds for WMHs (OR 4.32, 95 % CI = 2.56-7.28, I² = 67 %). According to reported univariable results from included studies, pooled analysis showed that clinical characteristics including age, presence of aura, disease duration, hypertension, diabetes mellitus and right-to-left shunt were associated with the presence of WMHs. Migraine pain and aura characteristics were not related to WMHs.

CONCLUSIONS

These data suggest that WMHs are common in migraine, especially in those who are older or have aura, hypertension, diabetes mellitus, or right-to-left shunt. A better understanding of the WMHs attributed to migraine is needed in future studies.

White matter hyperintensity distribution differences in aging and neurodegenerative disease cohorts

INTRODUCTION

White matter hyperintensities (WMHs) are common magnetic resonance imaging (MRI) findings in the aging population in general, as well as in patients with neurodegenerative diseases. They are known to exacerbate the cognitive deficits and worsen the clinical outcomes in the patients. However, it is not well-understood whether there are disease-specific differences in prevalence and distribution of WMHs in different neurodegenerative disorders.

METHODS

Data included 976 participants with cross-sectional T1-weighted and fluid attenuated inversion recovery (FLAIR) MRIs from the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) cohort of the Canadian Consortium on Neurodegeneration in Aging (CCNA) with eleven distinct diagnostic groups: cognitively intact elderly (CIE), subjective cognitive impairment (SCI), mild cognitive impairment (MCI), vascular MCI (V-MCI), Alzheimer's dementia (AD), vascular AD (V-AD), frontotemporal dementia (FTD), Lewy body dementia (LBD), cognitively intact elderly with Parkinson's disease (PD-CIE), cognitively impaired Parkinson's disease (PD-CI), and mixed dementias. WMHs were segmented using a previously validated automated technique. WMH volumes in each lobe and hemisphere were compared against matched CIE individuals, as well as each other, and between men and women.

RESULTS

All cognitively impaired diagnostic groups had significantly greater overall WMH volumes than the CIE group. Vascular groups (i.e. V-MCI, V-AD, and mixed dementia) had significantly greater WMH volumes than all other groups, except for FTD, which also had significantly greater WMH volumes than all non-vascular groups. Women tended to have lower WMH burden than men in most groups and regions, controlling for age. The left frontal lobe tended to have a lower WMH burden than the right in all groups. In contrast, the right occipital lobe tended to have greater WMH volumes than the left.

CONCLUSIONS

There were distinct differences in WMH prevalence and distribution across diagnostic groups, sexes, and in terms of asymmetry. WMH burden was significantly greater in all neurodegenerative dementia groups, likely encompassing areas exclusively impacted by neurodegeneration as well as areas related to cerebrovascular disease pathology.

Associations of deformation-based brain morphometry with cognitive level and decline within older Blacks without dementia

Blacks are at higher risk of developing cognitive impairment with age than non-Hispanic Whites, yet most brain morphometry and cognition research is performed with White samples or with mixed samples that control for race or compare across racial groups. A deeper understanding of the within-group variability in associations between brain structure and cognitive decline in Blacks is critically important for designing appropriate outcomes for clinical trials, predicting adverse outcomes, and developing interventions to preserve cognitive function, but no studies have examined these associations longitudinally within Blacks. We performed deformation-based morphometry in 376 older Black participants without dementia and examined associations of deformation-based morphometry with cognitive level and decline for global cognition and five cognitive domains. After correcting for widespread age-associated effects, there remained regions with less tissue and more cerebrospinal fluid associated with level and rate of decline in global cognition, memory, and perceptual speed. Further study is needed to examine the moderators of these associations, identify adverse outcomes predicted by brain morphometry, and deepen knowledge of underlying biological mechanisms.

Vascular Cognitive Impairment (VCI)

Vascular cognitive impairment (VCI) is predominately caused by vascular risk factors and cerebrovascular disease. VCI includes a broad spectrum of cognitive disorders, from mild cognitive impairment to vascular dementia caused by ischemic or hemorrhagic stroke, and vascular factors alone or in a combination with neurodegeneration including Alzheimer's disease (AD) and AD-related dementia. VCI accounts for at least 20-40% of all dementia diagnosis. Growing evidence indicates that cerebrovascular pathology is the most important contributor to dementia, with additive or synergistic interactions with neurodegenerative pathology. The most common underlying mechanism of VCI is chronic age-related dysregulation of CBF, although other factors such as inflammation and cardiovascular dysfunction play a role. Vascular risk factors are prevalent in VCI and if measured in midlife they predict cognitive impairment and dementia in later life. Particularly, hypertension, high cholesterol, diabetes, and smoking at midlife are each associated with a 20 to 40% increased risk of dementia. Control of these risk factors including multimodality strategies with an inclusion of lifestyle modification is the most promising strategy for treatment and prevention of VCI. In this review, we present recent developments in age-related VCI, its mechanisms, diagnostic criteria, neuroimaging correlates, vascular risk determinants, and current intervention strategies for prevention and treatment of VCI. We have also summarized the most recent and relevant literature in the field of VCI.

Prediction of functional outcome using the novel asymmetric middle cerebral artery index in cryptogenic stroke patients

BACKGROUND

Etiology is unknown in approximately one-quarter of stroke patients after evaluation, which is termed cryptogenic stroke (CS). The prognosis of CS patients is largely undetermined. We created a novel index from transcranial Doppler parameters including mean flow velocity (MV) and pulsatility index (PI) and investigated whether the calculation of asymmetry in the novel parameter can predict functional outcomes in CS patients.

METHODS

We made the middle cerebral artery (MCA) index (%) as a novel parameter, which was calculated as 100 X (MCA MV + MCA PI X 10) / (MCA MV-MCA PI X 10). The MCA asymmetry index (%) was also calculated as 100 X (|Rt MCA index-Lt MCA index|) / (Rt MCA index + Lt MCA index) / 2. Poor functional outcomes were defined as modified Rankin Scale score (mRS) ≥3 at 3 months after stroke onset.

RESULTS

A total of 377 CS patients were included. Among them, 52 (13.8%) patients had a poor outcome. The overall MCA asymmetry index was two-fold higher in CS patients with a poor outcome (10.26%) compared to those with a good outcome (5.41%, p = 0.002). In multivariable analysis, the overall MCA asymmetry index (OR, 1.054, 95% CI, 1.013-1.096, p = 0.009) and the cutoff value of the overall MCA asymmetry index >9 were associated with poor outcomes at 3 months (OR, 3.737, 95% CI, 1.530-9.128, p = 0.004).

CONCLUSION

We demonstrated that the novel asymmetric MCA index can predict short-term functional outcomes in CS patients.

Cerebral white matter disease and functional decline in older adults from the Northern Manhattan Study: A longitudinal cohort study

BACKGROUND

Cerebral white matter hyperintensities (WMHs) on MRI are common and associated with vascular and functional outcomes. However, the relationship between WMHs and longitudinal trajectories of functional status is not well characterized. We hypothesized that whole brain WMHs are associated with functional decline independently of intervening clinical vascular events and other vascular risk factors.

METHODS AND FINDINGS

In the Northern Manhattan Study (NOMAS), a population-based racially/ethnically diverse prospective cohort study, 1,290 stroke-free individuals underwent brain MRI and were followed afterwards for a mean 7.3 years with annual functional assessments using the Barthel index (BI) (range 0-100) and vascular event surveillance. Whole brain white matter hyperintensity volume (WMHV) (as percentage of total cranial volume [TCV]) was standardized and treated continuously. Generalized estimating equation (GEE) models tested associations between whole brain WMHV and baseline BI and change in BI, adjusting for sociodemographic, vascular, and cognitive risk factors, as well as stroke and myocardial infarction (MI) occurring during follow-up. Mean age was 70.6 (standard deviation [SD] 9.0) years, 40% of participants were male, 66% Hispanic; mean whole brain WMHV was 0.68% (SD 0.84). In fully adjusted models, annual functional change was -1.04 BI points (-1.20, -0.88), with -0.74 additional points annually per SD whole brain WMHV increase from the mean (-0.99, -0.49). Whole brain WMHV was not associated with baseline BI, and results were similar for mobility and non-mobility BI domains and among those with baseline BI 95-100. A limitation of the study is the possibility of a healthy survivor bias, which would likely have underestimated the associations we found.

CONCLUSIONS

In this large population-based study, greater whole brain WMHV was associated with steeper annual decline in functional status over the long term, independently of risk factors, vascular events, and baseline functional status. Subclinical brain ischemic changes may be an independent marker of long-term functional decline.

Functional Trajectories, Cognition, and Subclinical Cerebrovascular Disease

BACKGROUND AND PURPOSE

Cognition and education influence functional trajectories, but whether associations differ with subclinical brain infarcts (SBI) or white matter hyperintensity volume (WMHV) is unknown. We hypothesized that SBI and WMHV moderated relationships between cognitive performance and education and functional trajectories.

METHODS

A total of 1290 stroke-free individuals underwent brain magnetic resonance imaging and were followed for 7.3 years (mean) with annual functional assessments with the Barthel index (range, 0-100). Magnetic resonance imaging measurements included pathology-informed SBI (PI-SBI) and WMHV (% total cranial volume). Generalized estimating equation models tested associations between magnetic resonance imaging variables and baseline Barthel index and change in Barthel index, adjusting for demographic, vascular, cognitive, and social risk factors, and stroke and myocardial infarction during follow-up. We tested interactions among education level, baseline cognitive performance (Mini-Mental State score), and functional trajectories and ran models stratified by levels of magnetic resonance imaging variables.

RESULTS

Mean age was 70.6 (SD, 9.0) years; 19% had PI-SBI, and mean WMHV was 0.68%. Education did not modify associations between cognition and functional trajectories. PI-SBI modified associations between cognition and functional trajectories (P=0.04) with a significant protective effect of better cognition on functional decline seen only in those without PI-SBI. There was no significant interaction for WMHV (P=0.8). PI-SBI, and greater WMHV, were associated with 2- to 3-fold steeper functional decline, holding cognition constant.

CONCLUSIONS

PI-SBI moderated the association between cognition and functional trajectories, with 3-fold greater decline among those with PI-SBI (compared with no PI-SBI) and normal baseline cognition. This highlights the strong and independent association between subclinical markers and patient-centered trajectories over time.