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. 2022 May 23;14(1):72.
doi: 10.1186/s13195-022-01006-7.

Dynamic functional connectivity patterns associated with dementia risk

Sophie Dautricourt  1   2 , Julie Gonneaud #  1 , Brigitte Landeau #  1 , Vince D Calhoun  3 , Robin de Flores  1 , Géraldine Poisnel  1 , Salma Bougacha  1 , Valentin Ourry  1   4 , Edelweiss Touron  1 , Elizabeth Kuhn  1 , Harriet Demintz-King  5 , Natalie L Marchant  5 , Denis Vivien  1 , Vincent de la Sayette  2   4 , Antoine Lutz  6 , Gaël Chételat  7 ; Medit-Ageing Research Group
Collaborators, Affiliations

Dynamic functional connectivity patterns associated with dementia risk

Sophie Dautricourt et al. Alzheimers Res Ther. .

Abstract

Background: This study assesses the relationships between dynamic functional network connectivity (DFNC) and dementia risk.

Methods: DFNC of the default mode (DMN), salience (SN), and executive control networks was assessed in 127 cognitively unimpaired older adults. Stepwise regressions were performed with dementia risk and protective factors and biomarkers as predictors of DFNC.

Results: Associations were found between times spent in (i) a "weakly connected" state and lower self-reported engagement in early- and mid-life cognitive activity and higher LDL cholesterol; (ii) a "SN-negatively connected" state and higher blood pressure, higher depression score, and lower body mass index (BMI); (iii) a "strongly connected" state and higher self-reported engagement in early-life cognitive activity, Preclinical Alzheimer's cognitive composite-5 score, and BMI; and (iv) a "DMN-negatively connected" state and higher self-reported engagement in early- and mid-life stimulating activities and lower LDL cholesterol and blood pressure. The lower number of state transitions was associated with lower brain perfusion.

Conclusion: DFNC states are differentially associated with dementia risk and could underlie reserve.

Keywords: Cardiovascular risk factors; Cognition; Cognitive reserve; Dementia risk; Dynamic functional network connectivity; Lifestyle; Sliding window analysis.

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Conflict of interest statement

GC has received research support from the EU’s Horizon 2020 research and innovation programme (grant agreement number 667696), Inserm, Fondation d’entreprise MMA des Entrepreneurs du Futur, Fondation Alzheimer, Programme Hospitalier de Recherche Clinique, Région Normandie, Association France Alzheimer et maladies apparentées and Fondation Vaincre Alzheimer (all to Inserm), and personal fees from Fondation d’entreprise MMA des Entrepreneurs du Futur. All other authors have no relevant financial or non-financial interests to disclose.

Figures

Fig. 1
Fig. 1
Flow chart
Fig. 2
Fig. 2
Intrinsic connectivity networks. Representation of the seven independent component spatial maps obtained from the fully automated spatially constrained ICA and categorized according to their anatomical and functional properties in three distinct functional networks: the default mode network (in red), salience network (in blue), and executive control network (in yellow)
Fig. 3
Fig. 3
Dynamic connectivity states. The four states identified from the DFNC analysis are represented. The color scale indicates positive (red), neutral (green), and negative (blue) connectivity between the ICA components of the DMN, SN, and ECN. Numbers 1 to 7 refer to the ICA components represented in Fig. 2. DFNC dynamic functional network connectivity, DMN default mode network, SN salience network, ECN executive control network
Fig. 4
Fig. 4
Scatterplots represent linear regression between dementia risk factors and mean/total time spent in each state. CAQ=Cognitive Activity Questionnaire; LEQ=Lifetime of Experiences Questionnaire
Fig. 5
Fig. 5
Scatterplots represent linear regressions between the PACC5 and the mean and total time spent in state 3 (model 2). PACC5 = Preclinical Alzheimer's Cognitive Composite score-5
See this image and copyright information in PMC

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