The association between cognitive function and white matter lesion location in older adults: a systematic review

BackgroundMaintaining cognitive function is essential for healthy aging and to function autonomously within society. White matter lesions (WMLs) are associated with reduced cognitive function in older adults. However, whether their anatomical location moderates these associations is not well-established. This review systematically evaluates peer-reviewed evidence on the role of anatomical location in the association between WMLs and cognitive function.MethodsIn accordance with the preferred reporting items for systematic reviews and meta-analysis (PRISMA) statement, databases of EMBASE, PUBMED, MEDLINE, and CINAHL, and reference lists of selected papers were searched. We limited our search results to adults aged 60 years and older, and studies published in the English language from 2000 to 2011. Studies that investigated the association between cognitive function and WML location were included. Two independent reviewers extracted: 1) study characteristics including sample size, sample characteristic, and study design; 2) WML outcomes including WML location, WML quantification method (scoring or volume measurement), strength of the MRI magnet in Tesla, and MRI sequence used for WML detection; and 3) cognitive function outcomes including cognitive tests for two cognitive domains of memory and executive function/processing speed.ResultsOf the 14 studies included, seven compared the association of subcortical versus periventricular WMLs with cognitive function. Seven other studies investigated the association between WMLs in specific brain regions (e.g., frontal, parietal lobes) and cognitive function. Overall, the results show that a greater number of studies have found an association between periventricular WMLs and executive function/processing speed, than subcortical WMLs. However, whether WMLs in different brain regions have a differential effect on cognitive function remains unclear.ConclusionsEvidence suggests that periventricular WMLs may have a significant negative impact on cognitive abilities of older adults. This finding may be influenced by study heterogeneity in: 1) MRI sequences, WML quantification methods, and neuropsychological batteries; 2) modifying effect of cardiovascular risk factors; and 3) quality of studies and lack of sample size calculation.

[1]  J. Ioannidis,et al.  The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration , 2009, Annals of Internal Medicine [serial online].

[2]  Domenico Inzitari,et al.  Cognitive Decline and Dementia Related to Cerebrovascular Diseases: Some Evidence and Concepts , 2009, Cerebrovascular Diseases.

[3]  I. Deary,et al.  Cognitive Correlates of Cerebral White Matter Lesions and Water Diffusion Tensor Parameters in Community-Dwelling Older People , 2005, Cerebrovascular Diseases.

[4]  D. Marcus,et al.  White matter lesions are prevalent but differentially related with cognition in aging and early Alzheimer disease. , 2005, Archives of neurology.

[5]  A. Hofman,et al.  Cerebral white matter lesions and cognitive function: The Rotterdam scan study , 2000, Annals of neurology.

[6]  Roger Tam,et al.  The association between cognitive function and white matter lesion location in older adults: A systematic review , 2012, Alzheimer's & Dementia.

[7]  G. Pearlson,et al.  White Matter Hyperintensities Predict Functional Decline in Voiding, Mobility, and Cognition in Older Adults , 2010, Journal of the American Geriatrics Society.

[8]  D. Arnold,et al.  Magnetic resonance techniques for the in vivo assessment of multiple sclerosis pathology: Consensus report of the white matter study group , 2005, Journal of magnetic resonance imaging : JMRI.

[9]  D. Na,et al.  Voxel‐Based Analysis of Diffusion Tensor Imaging in Patients with Subcortical Vascular Cognitive Impairment: Correlates with Cognitive and Motor Deficits , 2011, Journal of neuroimaging : official journal of the American Society of Neuroimaging.

[10]  F. Fregni,et al.  Sample size calculation in physical medicine and rehabilitation: a systematic review of reporting, characteristics, and results in randomized controlled trials. , 2011, Archives of physical medicine and rehabilitation.

[11]  J. Garcìa,et al.  Pathogenesis of leukoaraiosis: a review. , 1997, Stroke.

[12]  Nicola Moscufo,et al.  Demographic and biological influences on cognitive reserve , 2009, Journal of clinical and experimental neuropsychology.

[13]  R. Kronmal,et al.  Neurologic correlates of infarction-like lesion location on magnetic resonance imaging in the cardiovascular health study , 2000 .

[14]  B. Winblad,et al.  Post-mortem distribution of dopamine and homo-vanillic acid in human brain, variations related to age, and a review of the literature , 2005, Journal of Neural Transmission.

[15]  Andreas Roesler,et al.  Single and combined effects of cerebral white matter lesions and lacunar infarctions on cognitive function in an elderly population. , 2009, The journals of gerontology. Series A, Biological sciences and medical sciences.

[16]  H. Haug,et al.  Morphometry of the human cortex cerebri and corpus striatum during aging , 1991, Neurobiology of Aging.

[17]  R. He,et al.  Unified Approach for Multiple Sclerosis Lesion Segmentation on Brain MRI , 2006, Annals of Biomedical Engineering.

[18]  Charles DeCarli,et al.  White Matter Hyperintensities and Subclinical Infarction: Associations With Psychomotor Speed and Cognitive Flexibility , 2008, Stroke.

[19]  B Fischl,et al.  Correlations between MRI white matter lesion location and executive function and episodic memory , 2011, Neurology.

[20]  Denise C. Park,et al.  The adaptive brain: aging and neurocognitive scaffolding. , 2009, Annual review of psychology.

[21]  P. Scheltens,et al.  MRI-Defined Subcortical Ischemic Vascular Disease: Baseline Clinical and Neuropsychological Findings , 2009, Cerebrovascular Diseases.

[22]  Roger C. Tam,et al.  Optimizing the Use of Radiologist Seed Points for Improved Multiple Sclerosis Lesion Segmentation , 2010, IEEE Transactions on Biomedical Engineering.

[23]  A. Algra,et al.  Automated and Visual Scoring Methods of Cerebral White Matter Hyperintensities: Relation with Age and Cognitive Function , 2007, Cerebrovascular Diseases.

[24]  K. Hwang,et al.  Regional white matter hyperintensities in normal aging, single domain amnestic mild cognitive impairment, and mild Alzheimer’s disease , 2011, Journal of Clinical Neuroscience.

[25]  H. Markus,et al.  The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis , 2010, BMJ : British Medical Journal.

[26]  G J Blauw,et al.  Increase in periventricular white matter hyperintensities parallels decline in mental processing speed in a non-demented elderly population , 2006, Journal of Neurology, Neurosurgery & Psychiatry.

[27]  M. Audiffren,et al.  Processing speed and executive functions in cognitive aging: How to disentangle their mutual relationship? , 2012, Brain and Cognition.

[28]  H. C. Chui,et al.  White matter lesions impair frontal lobe function regardless of their location , 2004, Neurology.

[29]  F. Gunning-Dixon,et al.  The cognitive correlates of white matter abnormalities in normal aging: a quantitative review. , 2000, Neuropsychology.

[30]  W. M. van der Flier,et al.  Reliability and Sensitivity of Visual Scales versus Volumetry for Evaluating White Matter Hyperintensity Progression , 2008, Cerebrovascular Diseases.

[31]  Giovanni B. Frisoni,et al.  White matter lesions in the elderly: Pathophysiological hypothesis on the effect on brain plasticity and reserve , 2008, Journal of the Neurological Sciences.

[32]  J. Alvarez,et al.  Executive Function and the Frontal Lobes: A Meta-Analytic Review , 2006, Neuropsychology Review.

[33]  K. Meguro,et al.  Prevalence and cognitive performances of vascular cognitive impairment no dementia in Japan: the Osaki–Tajiri Project , 2007, European journal of neurology.

[34]  G. Vauquelin,et al.  The effect of aging on the D1 dopamine receptors in human frontal cortex , 1990, Brain Research.

[35]  Leonardo Pantoni,et al.  Pathophysiology of Age-Related Cerebral White Matter Changes , 2002, Cerebrovascular Diseases.

[36]  A. Hofman,et al.  Cerebral white matter lesions, vascular risk factors, and cognitive function in a population‐based study , 1994, Neurology.

[37]  David W. McNeal,et al.  Volumetric effects of motor cortex injury on recovery of dexterous movements , 2009, Experimental Neurology.

[38]  J. Kaye,et al.  Impact of white matter hyperintensity volume progression on rate of cognitive and motor decline , 2008, Neurology.

[39]  Bertil Olsson,et al.  Cerebral Lesions on Magnetic Resonance Imaging, Heart Disease, and Vascular Risk Factors in Subjects Without Stroke: A Population‐Based Study , 1994, Stroke.

[40]  K. Kinsella.  Demographic Dimensions of Global Aging , 2000 .

[41]  L. Lipsitz,et al.  Cerebral white matter changes and geriatric syndromes: is there a link? , 2004, The journals of gerontology. Series A, Biological sciences and medical sciences.

[42]  J. O'Brien,et al.  Cognitive Associations of Subcortical White Matter Lesions in Older People , 2002, Annals of the New York Academy of Sciences.

[43]  L. Pantoni,et al.  The relation between white-matter lesions and cognition , 2007, Current opinion in neurology.

[44]  D. W. Desmond.  Cognition and White Matter Lesions , 2002, Cerebrovascular Diseases.

[45]  Massimo Filippi,et al.  The effect of white matter lesions on cognition in the elderly—small but detectable , 2007, Nature Clinical Practice Neurology.

[46]  Erik D. Reichle,et al.  From the Selectedworks of Marcel Adam Just Working Memory and Executive Function: Evidence from Neuroimaging Classic Issues Neuroimaging Results Working Memory and Executive Function: Evidence from Neuroimaging Reconstruals Suggested by the Neuroimaging Data Collaboration and Redundancy , 2022 .