Affiliations: [a] Neuroimaging Laboratory, Santa Lucia Foundation, IRCCS, Rome, Italy
| [b] Institute of Neurology, Catholic University, Rome, Italy
| [c] Department of Clinical and Behavioural Neurology, Santa Lucia Foundation, IRCCS, Rome, Italy
| [d] Department of Systems Medicine, University of Rome ‘Tor Vergata’, Rome, Italy
| [e] Brighton & Sussex Medical School, CISC, University of Sussex, Brighton, Falmer, East Sussex, UK
Correspondence:
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Correspondence to: Dr. Laura Serra, Neuroimaging Laboratory, Santa Lucia Foundation, IRCCS, Via Ardeatina 306, 00179 Rome, Italy. Tel.: +39 06 5150 1547; Fax: +39 06 5150 1213; E-mail: [email protected].
Abstract: Changes in the residual memory variance are considered as a dynamic aspect of cognitive reserve (d-CR). We aimed to investigate for the first time the neural substrate associated with changes in the residual memory variance overtime in patients with amnestic mild cognitive impairment (aMCI). Thirty-four aMCI patients followed-up for 36 months and 48 healthy elderly individuals (HE) were recruited. All participants underwent 3T MRI, collecting T1-weighted images for voxel-based morphometry (VBM). They underwent an extensive neuropsychological battery, including six episodic memory tests. In patients and controls, factor analyses were used on the episodic memory scores to obtain a composite memory score (C-MS). Partial Least Square analyses were used to decompose the variance of C-MS in latent variables (LT scores), accounting for demographic variables and for the general cognitive efficiency level; linear regressions were applied on LT scores, striping off any contribution of general cognitive abilities, to obtain the residual value of memory variance, considered as an index of d-CR. LT scores and d-CR were used in discriminant analysis, in patients only. Finally, LT scores and d-CR were used as variable of interest in VBM analysis. The d-CR score was not able to correctly classify patients. In both aMCI patients and HE, LT1st and d-CR scores showed correlations with grey matter volumes in common and in specific brain areas. Using CR measures limited to assess memory function is likely less sensitive to detect the cognitive decline and predict the evolution of Alzheimer’s disease. In conclusion, d-CR needs a measure of general cognition to identify conversion to Alzheimer’s disease efficiently.
