Ersoezlue Ersin, Perneczky Robert, Tato Maia, Utecht Julia, Kurz Carolin, Häckert Jan, Guersel Selim, Burow Lena, Koller Gabriele, Stoecklein Sophia, Keeser Daniel, Papazov Boris, Totzke Marie, Ballarini Tommaso, Brosseron Frederic, Buerger Katharina, Dechent Peter, Dobisch Laura, Ewers Michael, Fliessbach Klaus, Glanz Wenzel, Haynes John Dylan, Heneka Michael T, Janowitz Daniel, Kilimann Ingo, Kleineidam Luca, Laske Christoph, Maier Franziska, Munk Matthias H, Peters Oliver, Priller Josef, Ramirez Alfredo, Roeske Sandra, Roy Nina, Scheffler Klaus, Schneider Anja, Schott Björn H, Spottke Annika, Spruth Eike J, Teipel Stefan, Unterfeld Chantal, Wagner Michael, Wang Xiao, Wiltfang Jens, Wolfsgruber Steffen, Yakupov Renat, Duezel Emrah, Jessen Frank, Rauchmann Boris-Stephan
Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany.
Department of Gerontopsychiatry and Developmental Disorders, kbo-Isar-Amper-Klinikum Haar, University Teaching Hospital of LMU Munich, Germany.
J Alzheimers Dis. 2023;92(3):925-940. doi: 10.3233/JAD-220464.
Cognitive reserve (CR) explains inter-individual differences in the impact of the neurodegenerative burden on cognitive functioning. A residual model was proposed to estimate CR more accurately than previous measures. However, associations between residual CR markers (CRM) and functional connectivity (FC) remain unexplored.
To explore the associations between the CRM and intrinsic network connectivity (INC) in resting-state networks along the neuropathological-continuum of Alzheimer's disease (ADN).
Three hundred eighteen participants from the DELCODE cohort were stratified using cerebrospinal fluid biomarkers according to the A(myloid-β)/T(au)/N(eurodegeneration) classification. CRM was calculated utilizing residuals obtained from a multilinear regression model predicting cognition from markers of disease burden. Using an independent component analysis in resting-state fMRI data, we measured INC of resting-state networks, i.e., default mode network (DMN), frontoparietal network (FPN), salience network (SAL), and dorsal attention network. The associations of INC with a composite memory score and CRM and the associations of CRM with the seed-to-voxel functional connectivity of memory-related were tested in general linear models.
CRM was positively associated with INC in the DMN in the entire cohort. The A+T+N+ group revealed an anti-correlation between the SAL and the DMN. Furthermore, CRM was positively associated with anti-correlation between memory-related regions in FPN and DMN in ADN and A+T/N+.
Our results provide evidence that INC is associated with CRM in ADN defined as participants with amyloid pathology with or without cognitive symptoms, suggesting that the neural correlates of CR are mirrored in network FC in resting-state.
认知储备（CR）解释了神经退行性负担对认知功能影响的个体差异。有人提出一种残差模型来比以前的测量方法更准确地估计CR。然而，残余CR标志物（CRM）与功能连接性（FC）之间的关联仍未得到探索。
探讨CRM与阿尔茨海默病神经病理连续体（ADN）静息态网络中固有网络连接性（INC）之间的关联。
根据脑脊液生物标志物，将来自DELCODE队列的318名参与者按照A（淀粉样蛋白-β）/T（tau蛋白）/N（神经退行性变）分类进行分层。利用从预测疾病负担标志物的多线性回归模型获得的残差计算CRM。通过对静息态功能磁共振成像数据进行独立成分分析，我们测量了静息态网络的INC，即默认模式网络（DMN）、额顶叶网络（FPN）、突显网络（SAL）和背侧注意网络。在一般线性模型中测试了INC与复合记忆评分和CRM之间的关联以及CRM与记忆相关的种子点到体素功能连接性之间的关联。
在整个队列中，CRM与DMN中的INC呈正相关。A+T+N+组显示SAL与DMN之间存在反相关。此外，在ADN和A+T/N+中，CRM与FPN和DMN中记忆相关区域之间的反相关呈正相关。
我们的结果提供了证据，表明INC与定义为有或无认知症状的淀粉样蛋白病理参与者的ADN中的CRM相关，这表明CR的神经关联在静息态网络FC中得到反映。
