Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/32770
Title: The effect of Alzheimer’s biomarker positivity on neuropsychological networks
Authors: Wright, LM
De Marco, M
Ferguson, CE
Keywords: amyloid;tauopathy;graph theory;cognitive network;fluency
Issue Date: 21-Jan-2026
Publisher: Oxford University Press (OUP) on behalf of the Guarantors of Brain
Citation: Wright, M.L., De Marco, M. and Ferguson, C.E. (2026) 'The effect of Alzheimer’s biomarker positivity on neuropsychological networks', Brain Communications, 0 (ahead of print), fcag015, pp. 1 - 48. doi: 10.1093/braincomms/fcag015.
Abstract: Although network neuropsychology is a promising approach to the study of clinical profiles, the link between Alzheimer’s disease biomarkers and neuropsychological networks is still undetermined. We hypothesised that network differences would exist between biomarker-positive and biomarker-negative participants, and that these would be driven by network nodes corresponding to performance on tests of episodic memory, as this is the cognitive domain most distinctively affected by Alzheimer’s disease since the earliest clinical stages. In this case-control study, we investigated sub-cohorts of individuals who had been 1) enrolled in the National Alzheimer’s Coordinating Center initiative, and 2) tested with Version 3 of the Uniform Data Set neuropsychological battery (i.e., consisting of 11 tests). These included 1,263 “β-amyloid positive” (A+), 1,594 “β-amyloid negative” (A-), 442 “β-amyloid and hyperphosphorylated tau positive” (A+T+), and 734 “β -amyloid and hyperphosphorylated tau negative” (A-T-) participants. We first calculated neuropsychological residuals by regressing out age, years of education, sex, Clinical Dementia Rating scores, and timepoint distance between neuropsychological and biomarker assessment. Secondly, we used rank-based correlations to define conditional associations across all pairs of test scores (i.e., the nodes of the network). Thirdly, we imposed a penalty (i.e., via the Least Absolute Shrinkage and Selection Operator method) to control for network sparsity. We then tested for differences in global network metrics and node centrality between A+ and A-, and between A+T+ and A-T- participants using permutation-based inferential models. Differences were found between biomarker-positive and biomarker-negative sub-cohorts in global network metrics but, contrarily to our hypothesis, no differences were found in relation to episodic memory nodes. A significant node difference, however, was instead found in relation to Category Fluency (i.e., a test of semantic memory), with increased centrality observed among A+ participants. A similar, yet nonsignificant trend was also observed between A+T+ and A-T- participants. Network neuropsychology can complement and expand the study of cognitive performance carried out via “traditional” univariate approaches. While univariate analyses reveal episodic memory decline in people with Alzheimer’s disease, this is not accompanied by any abnormalities at a neuropsychological network level. Our findings, however, highlight the importance of semantic memory alterations in A+ individuals. The wide set of neural and cognitive resources that sustain semantic memory may play a supportive role in the presence of neuropathology.
Description: Accepted manuscripts are PDF versions of the author’s final manuscript, as accepted for publication by the journal but prior to copyediting or typesetting. They can be cited using the author(s), article title, journal title, year of online publication, and DOI. They will be replaced by the final typeset articles, which may therefore contain changes. The DOI will remain the same throughout.
Supplementary data are available online at: https://academic.oup.com/braincomms/advance-article/doi/10.1093/braincomms/fcag015/8436063#supplementary-data .
URI: http://bura.brunel.ac.uk/handle/2438/32770
DOI: https://doi.org/10.1093/braincomms/fcag015
Other Identifiers: ORCiD: Laura M. Wright https://orcid.org/0000-0002-0558-7811
ORCiD: Matteo De Marco https://orcid.org/0000-0002-9240-8067
Article number: fcag015
Appears in Collections:Dept of Life Sciences Research Papers

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