Microglial metabolism is a pivotal factor in sexual dimorphism in Alzheimer’s disease

Guillot-Sestier, Marie-Victoire; Araiz, Ana Rubio; Mela, Virginia; Gaban, Aline Sayd; O’Neill, Eoin; Joshi, Lisha; Chouchani, Edward T.; Mills, Evanna L.; Lynch, Marina A.

doi:10.1038/s42003-021-02259-y

Cited by 84 publications

(97 citation statements)

References 37 publications

(68 reference statements)

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“…These observations highlight important cell-type-specific contributions to Alzheimer’s disease progression in different sexes, which has drawn considerable research efforts in recent years. 47 , 48 Lastly, sex has also been considered as a covariate in the linear regression of SI against all the neuropathological and clinical biomarkers in all three cohorts. They are all not significant except in the IFG region from the MSBB cohort ( Fig.…”

Section: Discussionmentioning

confidence: 99%

Deep learning-based brain transcriptomic signatures associated with the neuropathological and clinical severity of Alzheimer’s disease

Wang

Chen²,

Su³

et al. 2021

Brain Communications

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Brain tissue gene expression from donors with and without Alzheimer’s disease (AD) have been used to help inform the molecular changes associated with the development and potential treatment of this disorder. Here, we use a deep learning method to analyze RNA-seq data from 1,114 brain donors from the Accelerating Medicines Project for Alzheimer’s Disease (AMP-AD) consortium to characterize post-mortem brain transcriptome signatures associated with amyloid-β plaque, tau neurofibrillary tangles, and clinical severity in multiple Alzheimer’s disease dementia populations. Starting from the cross-sectional data in the Religious Orders Memory and Aging Project (ROSMAP) cohort (n = 634), a deep learning framework was built to obtain a trajectory that mirrors Alzheimer’s disease progression. A severity index (SI) was defined to quantitatively measure the progression based on the trajectory. Network analysis was then carried out to identify key gene (index gene) modules present in the model underlying the progression. Within this dataset, severity indexes were found to be very closely correlated with all Alzheimer’s disease neuropathology biomarkers (R ∼ 0.5, p < 1e-11) and global cognitive function (R = -0.68, p < 2.2e-16). We then applied the model to additional transcriptomic datasets from different brain regions (MAYO, n = 266; Mount Sinai Brain Bank, n = 214), and observed that the model remained significantly predictive (p < 1e-3) of neuropathology and clinical severity. The index genes that significantly contributed to the model were integrated with Alzheimer’s disease co-expression regulatory networks, resolving four discrete gene modules that are implicated in vascular and metabolic dysfunction in different cell types respectively. Our work demonstrates the generalizability of this signature to frontal and temporal cortex measurements and additional brain donors with Alzheimer’s disease, other age-related neurological disorders and controls; and revealed the transcriptomic network modules contribute to neuropathological and clinical disease severity. This study illustrates the promise of using deep learning methods to analyze heterogeneous omics data and discover potentially targetable molecular networks that can inform the development, treatment and prevention of neurodegenerative diseases like Alzheimer’s disease.

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Section: Discussionmentioning

confidence: 99%

Deep learning-based brain transcriptomic signatures associated with the neuropathological and clinical severity of Alzheimer’s disease

Wang

Chen²,

Su³

et al. 2021

Brain Communications

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“…PFKFB3 is a master regulator of glycolysis [ 26 , 27 ], the expression of which correlates with microglial activation in aged mice and APP/PS1 mice [ 1 , 8 , 10 , 11 ]. We assessed cytosolic PFKFB3 as a proxy marker of enzyme activation and, although no statistically significant changes were observed between treatment groups, DMF decreased cytosolic PFKFB3 in microglia from female mice by 40% which approached significance ( p = 0.081), while no difference in total PFKFB3 was observed ( Figure 3 F).…”

Section: Resultsmentioning

confidence: 99%

“…In the past few years, research has begun to focus on evaluating sex-related differences in microglia with clear differences identified during development and early life [ 32 ]. There is growing evidence of changes that persist into adulthood and age, including increased antigen presentation in the cortex of males compared with females [ 4 ], upregulation in microglia-specific genes that are indicative of inflammatory processes in aged females compared with males [ 33 ], particularly aged female APP/PS1 mice [ 11 ], increased responsiveness to LPS in aged female mice compared with males [ 34 ], sex-related responses to engrafted microglia in EAE [ 35 ] and middle cerebral artery occlusion [ 2 ], and sex-related differences in response to trauma [ 36 ]. The factors that contribute to these changes remain to be clarified but probably include hormonal differences [ 5 ] and epigenetic changes [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, as in the case of macrophages [ 7 , 40 ], activated microglia in the aged brain and brain of APP/PS1 mice switch their metabolism towards glycolysis [ 1 , 8 , 9 , 10 ]. Furthermore, in microglia from APP/PS1 mice, microglial activation was more marked, and the switch to glycolysis was observed only in cells from female mice [ 11 ]. Here, the DMF-induced changes in microglia were accompanied by metabolic changes; the data show that DMF decreases glycolysis in microglia isolated from female mice while the opposite effect of DMF was observed in cells from male mice where glycolysis was increased.…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, microglia prepared from aged mice [ 1 ] and APP/PS1 mice [ 10 ], which adopt an inflammatory phenotype, display increased glycolysis and increased PFKFB3 and these changes are associated with reduced phagocytosis and chemotaxis. Interestingly, we have recently found that activation of microglia with the associated switch in metabolism and function that occur in microglia from APP/PS1 mice are sex-dependent, with more profound changes in cells from female, compared with male mice [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

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The Modulatory Effects of DMF on Microglia in Aged Mice Are Sex-Specific

Mela

Gaban

O’Neill

et al. 2022

Cells

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There is a striking sex-related difference in the prevalence of many neurodegenerative diseases, highlighting the need to consider whether treatments may exert sex-specific effects. A change in microglial activation state is a common feature of several neurodegenerative diseases and is considered to be a key factor in driving the inflammation that characterizes these conditions. Among the changes that have been described is a switch in microglial metabolism towards glycolysis which is associated with production of inflammatory mediators and reduced function. Marked sex-related differences in microglial number, phenotype and function have been described in late embryonic and early postnatal life in rodents and some reports suggest that sexual dimorphism extends into adulthood and age and, in models of Alzheimer’s disease, the changes are more profound in microglia from female, compared with male, mice. Dimethyl fumarate (DMF) is a fumaric acid ester used in the treatment of psoriasis and relapsing remitting multiple sclerosis and, while its mechanism of action is unclear, it possesses anti-inflammatory and anti-oxidant properties and also impacts on cell metabolism. Here we treated 16–18-month-old female and male mice with DMF for 1 month and assessed its effect on microglia. The evidence indicates that it exerted sex-specific effects on microglial morphology and metabolism, reducing glycolysis only in microglia from female mice. The data suggest that this may result from its ability to inactivate glyceraldehyde-3-phosphate dehydrogenase (GAPDH).

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The Role of Immunity in Alzheimer's Disease

McManus

2022

Advanced Biology

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Based on this, it has been suggested that reducing co-morbidities in the elderly and extending the period of healthy aging will have a significant impact on decreasing the number of individuals with such impairments in 2050, with a knock-on effect of reducing the cost of dementia care.It is widely acknowledged that neuroinflammation is a critical step on the road to dementia. It is produced as a reaction to the ongoing protein deposition and cell loss observed in individuals with cognitive impairment and it has been argued that such inflammatory factors can in turn exacerbate ongoing cellular changes and hasten the progression to severe cognitive decline. This review will detail the role of the innate and adaptive immune system in the progression of AD. Specifically we will cover microglia mediated-neuroinflammation and the contribution of peripheral cells, namely T cells, on the progression to cognitive decline and the potential therapies that are under development to tackle these pathways will be discussed. Alzheimer's DiseaseThe most common cause of cognitive impairment or dementia is AD. This accounts for 60-80% of dementia cases [5] and is characterized by the build-up of two different proteins, amyloid-β (Aβ) and tau, along with cognitive changes. Aβ is cleaved from amyloid precursor protein (APP) and these monomers aggregate into oligomers and fibrils, ultimately forming Aβ-containing plaques that are 200-650 μm 2 in size. [6] Aβ can also undergo posttranslational modifications such as phosphorylation and nitration, which accelerate this process. [7,8] Tau is a protein found in neurons that is involved in microtubule stabilization, however in AD (and other Frontotemporal dementias -FTDs) tau becomes hyperphosphorylated and accumulates forming neurofibrillary tangles (NFTs). These deposits vary considerably in size from 10 to 500 μm 2 . [9] The severity of pathological changes (particularly the NFTs) correlate with neuronal loss and the increasing cognitive decline in those with AD. [10][11][12] The observed cognitive impairment in AD differs significantly across disease stages, and ranges from mild cognitive impairment (MCI), which can progress to moderate and then severe dementia. Indeed 68-80% of those who receive an initial diagnosis of MCI go on to develop AD within 6 years. [13][14][15] MCI is the first stage of cognitive decline and features initial With the increase in the aging population, age-related conditions such as dementia and Alzheimer's disease will become ever more prevalent in society. As there is no cure for dementia and extremely limited therapeutic options, researchers are examining the mechanisms that contribute to the progression of cognitive decline in hopes of developing better therapies and even an effective, long-lasting treatment for this devastating condition. This review will provide an updated perspective on the role of immunity in triggering the changes that lead to the development of dementia. It will detail the latest findings on Aβ-and tau-induced microglial activation, i...

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Microglial metabolism is a pivotal factor in sexual dimorphism in Alzheimer’s disease

Cited by 84 publications

References 37 publications

Deep learning-based brain transcriptomic signatures associated with the neuropathological and clinical severity of Alzheimer’s disease

Deep learning-based brain transcriptomic signatures associated with the neuropathological and clinical severity of Alzheimer’s disease

The Modulatory Effects of DMF on Microglia in Aged Mice Are Sex-Specific

The Role of Immunity in Alzheimer's Disease

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