Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer’s disease

Franzmeier, Nicolai; Düzel, Emrah; Jessen, Frank; Büerger, Katharina; Xiong, Chengjie; Duering, Marco; Dichgans, Martin; Haass, Christian; Suárez‐Calvet, Marc; Fagan, Anne M.; Paumier, Katrina L.; Benzinger, Tammie L.S.; Masters, Colin L.; Morris, John C.; Perneczky, Robert; Janowitz, Daniel; Catak, Cihan; Wolfsgruber, Steffen; Wagner, Michael; Teipel, Stefan J.; Kilimann, Ingo; Ramı́rez, Alfredo; Rossor, Martin N.; Jucker, Mathias; Chhatwal, Jasmeer P.; Spottke, Annika; Boecker, Henning; Brosseron, Frederic; Falkai, Peter; Fließbach, Klaus; Heneka, Michael T.; Laske, Christoph; Nestor, Peter J.; Peters, Oliver; Fuentes, Manuel; Menne, Felix; Priller, Josef; Spruth, Eike Jakob; Franke, Christiana; Schneider, Anja; Kofler, Barbara; Westerteicher, Christine; Speck, Oliver; Wiltfang, Jens; Bartels, Claudia; Caballero, Miguel Ángel Araque; Metzger, Coraline D.; Bittner, Daniel; Weiner, Michael W.; Lee, Jae‐Hong; Salloway, Stephen; Danek, Adrian; Goate, Alison; Schofield, Peter R.; Bateman, Randall J.; Ewers, Michael

doi:10.1093/brain/awy008

Cited by 91 publications

(85 citation statements)

References 76 publications

(110 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Prior work has highlighted a link between increased resting state functional connectivity and markers of cognitive reserve (e.g., greater years of education) in diverse cohorts, including healthy ageing, and those with mild cognitive impairment and Alzheimer’s disease (Arenaza-Urquijo et al ., 2013; Franzmeier et al ., 2017; 2018). However, increased functional connectivity does not necessarily lend itself to a specific mechanistic interpretation per se .…”

Section: Discussionmentioning

confidence: 99%

Dopamine Depletion Alters Macroscopic Network Dynamics in Parkinson’s Disease

Shine

Bell

Matar

et al. 2018

Preprint

View full text Add to dashboard Cite

Parkinson’s disease is primarily characterised by diminished dopaminergic function, however the impact of these impairments on large-scale brain dynamics remains unclear. It has been difficult to disentangle the direct effects of Parkinson’s disease from compensatory changes that reconfigure the functional signature of the whole brain network. To examine the causal role of dopamine depletion in network-level topology, we investigated time-varying network structure in 37 individuals with idiopathic Parkinson’s disease, both ‘On’ and ‘Off’ dopamine replacement therapy, along with 50 age-matched, healthy control subjects using resting-state functional MRI. By tracking dynamic network-level topology, we found that the Parkinson’s disease ‘Off’ state was associated with greater network-level integration than in the ‘On’ state. The extent of integration in the ‘Off’ state inversely correlated with motor symptom severity, suggesting that a shift toward a more integrated network topology may be a compensatory mechanism associated with preserved motor function in the dopamine depleted ‘Off’ state. Furthermore, we were able to demonstrate that measures of both cognitive and brain reserve (i.e., premorbid intelligence and whole brain grey matter volume) had a positive relationship with the relative increase in network integration observed in the dopaminergic ‘Off’ state. This suggests that each of these factors plays an important role in promoting network integration in the dopaminergic ‘Off’ state. Our findings provide a mechanistic basis for understanding the PD ‘Off’ state and provide a further conceptual link with network-level reconfiguration. Together, our results highlight the mechanisms responsible for pathological and compensatory change in Parkinson’s disease.

show abstract

Section: Discussionmentioning

confidence: 99%

Dopamine Depletion Alters Macroscopic Network Dynamics in Parkinson’s Disease

Shine

Bell

Matar

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Identifying brain signatures or markers of resilience across studies will be an important step . For example, several studies have provided converging evidence of the involvement of lateral frontal and medial prefrontal regions supporting resilience at older ages (see for example [14,15]).…”

Section: Tackling the Issue Of Matching Concepts To Mechanisms Mappinmentioning

confidence: 99%

Improving the resistance and resilience framework for aging and dementia studies

Arenaza‐Urquijo

Vemuri

2020

Alz Res Therapy

View full text Add to dashboard Cite

Background: The "resistance vs resilience" to Alzheimer's disease (AD) framework (coping vs avoiding) has gained interest in the field in the last year. In this viewpoint, our effort is (i) to provide clarity to the usage of the framework in the context of the ATN (amyloid/tau/neurodegeneration) system as well as in lifespan and cognitive aging studies and (ii) to discuss the challenges of matching these concepts to specific biological mechanisms. Main body: In the context of the ATN system, the main goal of the resistance vs resilience framework is to make a fundamental distinction between risk factors that may help halt the development of AD pathologies (AT) ("resistance") vs delay processes downstream to AT, i.e., neurodegeneration (N) and the clinical expression of the disease ("resilience"). The process of resilience in dementia and aging research should be envisioned as a process that is developed over the lifespan. Greater neurobiological capital to start with (initial brain reserve), maintaining brain structure and function (brain maintenance), or greater adaptability of cognitive strategies to perform a task (cognitive reserve) could all contribute to higher resilience to pathologies later in life. Simply put, resilience is not only a response to pathological processes (i.e. increased brain function to compensate for increasing AD pathology) but also reflects individual differences in brain structure and function that can be built over the lifespan (e.g., through education, lifetime cognitive, and physical activities). Further, the resistance vs resilience terminology can be extended to study other pathological processes such as cerebrovascular lesions, Lewy body disease, or TDP-43. However, some challenges do exist: (i) when studying multiple neuropathologies, the study design and framework will drive the usage of terminology; (ii) it is unavoidable that the measurements of resilience (brain structure and function) will reflect both the effect of pathologies and the impact of several risk and protective factors throughout the lifespan. Therefore, identifying resilience brain markers across lifespan, aging, and dementia studies, notably with longitudinal study designs, will be an important step towards understanding mechanisms of action.Conclusions: While the field advances towards consensus definitions of existing concepts, the resistance vs resilience terminology may provide clarity in the communication of results in aging and dementia studies as well as provide a framework for the development of both hypotheses and study designs.

show abstract

“…Thus, the effect of aging appears to influence GE of the superior and inferior parts of the brain differently. The frontal regions may not have elicited connectivity degeneration because of cognitive reserve (CR; Reuter-Lorenz et al, 2008; Franzmeier et al, 2018; Martínez et al, 2017; Colangeli et al, 2016). According to Benson et al (2018), “higher functional connectivity in fronto-parietal and salience networks may protect against detrimental effects of white matter lesions on executive functions.” The nodal regions associated with higher cognitive functions may be protected against cerebrovascular pathology by the intrinsic networks encompassing the frontal and parietal lobes.…”

Section: Discussionmentioning

confidence: 99%

Area-specific Biased Global Efficiency in Functional Connectivity Provides Features Negatively Correlated with Age

Akama

Ota

2020

Preprint

View full text Add to dashboard Cite

12It has been acknowledged that graph-theoretical coefficients computed from the 13 adjacency matrix of cerebral resting-state functional connectivity (RSFC) represent 14aging of the brain and its plasticity facilitating cognitive reserve. In particular, global 15 efficiency (GE) has been recognized as a crucial graph index for age-dependent RSFC. 16Using the dataset of the Nathan Kline Institute-Rockland Sample [NKI-RS], we found 17 that the regions of the brain in which GE values decay with age were located in the 18 subcortical zone and the cerebellum, whereas an opposite relationship was found in 19 many frontal and parietal regions. Based on this systematic tendency, a new coefficient 20 was proposed that corrects GE, referred to as biased GE (BGE); BGE is calculated by 21 changing the sign of the weight between the superior and the inferior parts of the brain 22 before separately averaging the respective sign groups of area-specific corrected GE 23 values, to influence the raw global network GE. The BGE showed a significant negative 24 correlation with age, irrespective of the scan condition, and strong consistency as an 25 information source of a subject's identity. We propose that this new index could play an 26 important role in the clinical context of preventive medicine and the maintenance of 27 healthy brains. 28

show abstract

Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer’s disease

Cited by 91 publications

References 76 publications

Dopamine Depletion Alters Macroscopic Network Dynamics in Parkinson’s Disease

Dopamine Depletion Alters Macroscopic Network Dynamics in Parkinson’s Disease

Improving the resistance and resilience framework for aging and dementia studies

Area-specific Biased Global Efficiency in Functional Connectivity Provides Features Negatively Correlated with Age

Contact Info

Product

Resources

About