Neuropsychological Test Performance and MRI Markers of Dementia Risk

Supplemental Digital Content is available in the text. Background: To use neuropsychological assessments for studying the underlying disease processes contributing to dementia, it is crucial that they correspond to magnetic resonance imaging (MRI)-based measures of dementia, regardless of educational level. Methods: French 3-City Dijon MRI study cohort members (n=1782) with assessments of white matter lesion volume (WMLV), hippocampal volume (HCV), and cerebrospinal fluid volume (CSFV), and 6 waves of neuropsychological assessments over 11 years, including Mini-Mental State Examination (MMSE), plus 5 other tests combined using a Z-score or item-response theory (IRT-cognition) comprised the study cohort. We evaluated, testing interactions, whether education modified associations of MRI markers with intercept or rate of change of MMSE, Z-score composite, or IRT-cognition. Results: In linear models, education modified the associations of WMLV and CSFV with MMSE and CSFV and Z-score composite. In mixed models, education modified the associations of WMLV and CSFV with level of MMSE and the association of HCV with slope of MMSE. Education also modified the association with CSFV and slope of Z-score composite decline. There was no evidence that education modified associations between MRI measures and level or slope of IRT-cognition. Conclusions: Longitudinal analysis of correctly scaled neuropsychological assessments may provide unbiased proxies for MRI-based measures of dementia risk.

[1]  Carole Dufouil,et al.  Antihypertensive Treatment and Change in Blood Pressure Are Associated With the Progression of White Matter Lesion Volumes: The Three-City (3C)–Dijon Magnetic Resonance Imaging Study , 2011, Circulation.

[2]  Akihito Kamata,et al.  A Note on the Relation Between Factor Analytic and Item Response Theory Models , 2008 .

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

[4]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[5]  T. Manolio,et al.  Education and the cognitive decline associated with MRI-defined brain infarct , 2006, Neurology.

[6]  C. Jack,et al.  NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease , 2018, Alzheimer's & Dementia.

[7]  A. Brickman,et al.  Will biomarker-based diagnosis of Alzheimer’s disease maximize scientific progress? Evaluating proposed diagnostic criteria , 2018, European Journal of Epidemiology.

[8]  K. Lunetta,et al.  Education attenuates the effect of medial temporal lobe atrophy on cognitive function in Alzheimer's disease: the MIRAGE study. , 2009, Journal of Alzheimer's disease : JAD.

[9]  R. Holman,et al.  Vascular Factors and Risk of Dementia: Design of the Three-City Study and Baseline Characteristics of the Study Population , 2003, Neuroepidemiology.

[10]  Phil Wood Confirmatory Factor Analysis for Applied Research , 2008 .

[11]  B. Mazoyer,et al.  Association of plasma β-amyloid with MRI markers of structural brain aging the 3-City Dijon study , 2015, Neurobiology of Aging.

[12]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[13]  R. Reitan Validity of the Trail Making Test as an Indicator of Organic Brain Damage , 1958 .

[14]  B. Reed,et al.  Application of item response theory for development of a global functioning measure of dementia with linear measurement properties. , 2000, Statistics in medicine.

[15]  J. Schneider,et al.  Education modifies the relation of AD pathology to level of cognitive function in older persons , 2003, Neurology.

[16]  Yves Rosseel,et al.  lavaan: An R Package for Structural Equation Modeling , 2012 .

[17]  Charles DeCarli,et al.  Structural Imaging Measures of Brain Aging , 2014, Neuropsychology Review.

[18]  Ron Brookmeyer,et al.  Forecasting the prevalence of preclinical and clinical Alzheimer's disease in the United States , 2018, Alzheimer's & Dementia.

[19]  R. Green,et al.  Calibrating Longitudinal Cognition in Alzheimer's Disease Across Diverse Test Batteries and Datasets , 2014, Neuroepidemiology.

[20]  Tamara B Harris,et al.  Association of plasma beta-amyloid level and cognitive reserve with subsequent cognitive decline. , 2011, JAMA.

[21]  B Isaacs,et al.  The Set Test as an Aid to the Detection of Dementia in Old People , 1973, British Journal of Psychiatry.

[22]  A. Gross,et al.  Application of Latent Variable Methods to the Study of Cognitive Decline When Tests Change over Time , 2015, Epidemiology.