Brain white matter damage in aging and cognitive ability in youth and older age

Cerebral white matter hyperintensities (WMH) reflect accumulating white matter damage with aging and impair cognition. The role of childhood intelligence is rarely considered in associations between cognitive impairment and WMH. We studied community-dwelling older people all born in 1936, in whom IQ had been assessed at age 11 years. We assessed medical histories, current cognitive ability and quantified WMH on MR imaging. Among 634 participants, mean age 72.7 (SD 0.7), age 11 IQ was the strongest predictor of late life cognitive ability. After accounting for age 11 IQ, greater WMH load was significantly associated with lower late life general cognitive ability (β = −0.14, p < 0.01) and processing speed (β = −0.19, p < 0.001). WMH were also associated independently with lower age 11 IQ (β = −0.08, p < 0.05) and hypertension. In conclusion, having more WMH is significantly associated with lower cognitive ability, after accounting for prior ability, age 11IQ. Early-life IQ also influenced WMH in later life. Determining how lower IQ in youth leads to increasing brain damage with aging is important for future successful cognitive aging.

[1]  Christian Enzinger,et al.  Section Editor: Progression of Leukoaraiosis and Cognition , 2022 .

[2]  Norman J Beauchamp,et al.  Incidence, Manifestations, and Predictors of Worsening White Matter on Serial Cranial Magnetic Resonance Imaging in the Elderly: The Cardiovascular Health Study , 2005, Stroke.

[3]  Yaakov Stern,et al.  Cognitive Reserve: Implications for Assessment and Intervention , 2013, Folia Phoniatrica et Logopaedica.

[4]  F. Barkhof,et al.  CT and MRI Rating of White Matter Lesions , 2002, Cerebrovascular Diseases.

[5]  Ian J. Deary,et al.  Brain lesions, hypertension and cognitive ageing in the 1921 and 1936 Aberdeen birth cohorts , 2011, AGE.

[6]  Patrick Rabbitt,et al.  White matter lesions account for all age-related declines in speed but not in intelligence. , 2007, Neuropsychology.

[7]  Bengt Muthén,et al.  Moments of the censored and truncated bivariate normal distribution , 1990 .

[8]  Ian J. Deary,et al.  Edinburgh Research Explorer Intelligence and personality as predictors of illness and death: How researchers in differential psychology and chronic disease epidemiology are collaborating to understand and address health inequalities , 2013 .

[9]  J. Kaye,et al.  Cognitive impairment risk , 2009, Neurology.

[10]  Nazahah Mustafa,et al.  The balance between cognitive reserve and brain imaging biomarkers of cerebrovascular and Alzheimer's diseases. , 2011, Brain : a journal of neurology.

[11]  D. Tate,et al.  Subjective cognitive complaints relate to white matter hyperintensities and future cognitive decline in patients with cardiovascular disease. , 2009, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[12]  N. Benowitz Cigarette smoking and cardiovascular disease: pathophysiology and implications for treatment. , 2003, Progress in cardiovascular diseases.

[13]  O Almkvist,et al.  White-matter hyperintensity and neuropsychological functions in dementia and healthy aging. , 1992, Archives of neurology.

[14]  Joanna M. Wardlaw,et al.  How Much Do Focal Infarcts Distort White Matter Lesions and Global Cerebral Atrophy Measures? , 2012, Cerebrovascular Diseases.

[15]  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.

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

[17]  L Penke,et al.  Brain white matter tract integrity as a neural foundation for general intelligence , 2012, Molecular Psychiatry.

[18]  P. Visscher,et al.  The Lothian Birth Cohort 1936: a study to examine influences on cognitive ageing from age 11 to age 70 and beyond , 2007, BMC geriatrics.

[19]  T. Erkinjuntti,et al.  Educational History Is an Independent Predictor of Cognitive Deficits and Long-Term Survival in Postacute Patients With Mild to Moderate Ischemic Stroke , 2012, Stroke.

[20]  R. Marioni,et al.  Age-associated cognitive decline. , 2009, British medical bulletin.

[21]  Sfc Brain,et al.  New multispectral MRI data fusion technique for white matter lesion segmentation:method and comparison with thresholding in FLAIR images , 2010 .

[22]  Ian J Deary,et al.  The impact of childhood intelligence on later life: following up the Scottish mental surveys of 1932 and 1947. , 2004, Journal of personality and social psychology.

[23]  T. Salthouse When does age-related cognitive decline begin? , 2009, Neurobiology of Aging.

[24]  K. Widaman Common Factor Analysis Versus Principal Component Analysis: Differential Bias in Representing Model Parameters? , 1993, Multivariate behavioral research.

[25]  I. Deary,et al.  Brain Aging, Cognition in Youth and Old Age and Vascular Disease in the Lothian Birth Cohort 1936: Rationale, Design and Methodology of the Imaging Protocol* , 2011, International journal of stroke : official journal of the International Stroke Society.

[26]  S. Reise,et al.  Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. , 1997 .

[27]  S. Pendlebury,et al.  Prevalence, incidence, and factors associated with pre-stroke and post-stroke dementia: a systematic review and meta-analysis , 2009, The Lancet Neurology.

[28]  C. Dufouil,et al.  Influence of education on the relationship between white matter lesions and cognition , 2003, Neurology.

[29]  K. Schermelleh-Engel,et al.  Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures. , 2003 .

[30]  Benjamin S Aribisala,et al.  Close Correlation between Quantitative and Qualitative Assessments of White Matter Lesions , 2012, Neuroepidemiology.

[31]  N. Sattar,et al.  Differences in atherosclerosis according to area level socioeconomic deprivation: cross sectional, population based study , 2009, BMJ : British Medical Journal.

[32]  Ian J. Deary,et al.  Some guidelines for structural equation modelling in cognitive neuroscience: The case of Charlton et al.’s study on white matter integrity and cognitive ageing , 2010, Neurobiology of Aging.

[33]  Roger T Staff,et al.  Cerebral white matter abnormalities and lifetime cognitive change: a 67-year follow-up of the Scottish Mental Survey of 1932. , 2003, Psychology and aging.

[34]  A Hofman,et al.  Hypertension and cerebral white matter lesions in a prospective cohort study. , 2002, Brain : a journal of neurology.

[35]  Maria del C. Valdés Hernández,et al.  Automatic segmentation of brain white matter and white matter lesions in normal aging: comparison of five multispectral techniques. , 2012, Magnetic resonance imaging.

[36]  I. Deary,et al.  The neuroscience of human intelligence differences , 2010, Nature Reviews Neuroscience.

[37]  W. Holmes Finch,et al.  Confirmatory Factor Analytic Procedures for the Determination of Measurement Invariance , 2006 .