Autophagy is a cellular bulk degradation process used as an alternative source of energy and metabolites and implicated in various diseases. Inefficient autophagy in nutrient-deprived cancer cells ...would be beneficial for cancer therapy making its modulation valuable as a therapeutic strategy for cancer treatment, especially in combination with chemotherapy. Dipyridamole (DIP) is a vasodilator and antithrombotic drug. Its major effects involve the block of nucleoside uptake and phosphodiestesase inhibition, leading to increased levels of intracellular cAMP. Here we report that DIP increases autophagic markers due to autophagic flux blockage, resembling autophagosome maturation and/or closure impairment. Treatment with DIP results in an increased number of autophagosomes and autolysosomes and impairs degradation of SQSTM1/p62. As blockage of autophagic flux decreases the recycling of cellular components, DIP reduced the intracellular ATP levels in cancer cells. Autophagic flux blockage was neither through inhibition of lysosome function nor blockage of nucleoside uptake, but could be prevented by treatment with a PKA inhibitor, suggesting that autophagic flux failure mediated by DIP results from increased intracellular levels of cAMP. Treatment with DIP presented antiproliferative effects in vitro alone and in combination with chemotherapy drugs. Collectively, these data demonstrate that DIP can impair autophagic degradation, by preventing the normal autophagosome maturation, and might be useful in combination anticancer therapy.
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•Dipyridamole (DIP) blocks autophagic flux.•DIP leads to the accumulation of double-membrane structures, resembling failure in autophagosome maturation process.•DIP treatment has antiproliferative effects in vitro and sensitizes cancer cells to antineoplastic treatments.
Ischemic stroke is a major cause of death and disability, intensely demanding innovative and accessible therapeutic strategies. Approaches presenting a prolonged period for therapeutic intervention ...and new treatment administration routes are promising tools for stroke treatment. Here, we evaluated the potential neuroprotective properties of nasally administered human adipose tissue mesenchymal stem cell (hAT-MSC)-derived extracellular vesicles (EVs) obtained from healthy individuals who underwent liposuction. After a single intranasal EV (200 µg/kg) administered 24 h after a focal permanent ischemic stroke in rats, a higher number of EVs, improvement of the blood-brain barrier, and re-stabilization of vascularization were observed in the recoverable peri-infarct zone, as well as a significant decrease in infarct volume. In addition, EV treatment recovered long-term motor (front paws symmetry) and behavioral impairment (short- and long-term memory and anxiety-like behavior) induced by ischemic stroke. In line with these findings, our work highlights hAT-MSC-derived EVs as a promising therapeutic strategy for stroke.
Background
The SIRT1 enzyme is involved in adipose tissue (AT) lipolysis. FOXO1 is a protein that plays a significant role in regulating metabolism. Adiponectin is an adipokine, secreted by the AT, ...which has been considered to have an antiobesity function. PPARγ is one of the key actors in adipocytes differentiation. This study was undertaken to investigate whether resveratrol can regulate SIRT1, FOXO1, adiponectin, PPARγ1–3, and PPARβ/δ in human AT.
Methods
The effects of resveratrol were analyzed in freshly isolated adipocytes prepared from visceral fat tissue samples obtained during bariatric surgery. Genes messenger ribonucleic acid (mRNA) levels were determined by qRT-PCR.
Results
Ours results show that resveratrol modulates the studied genes, increasing SIRT1 (
p
= 0.021), FOXO1 (
p
= 0.001), and adiponectin (
p
= 0.025) mRNA expression and decreasing PPARγ1–3 (
p
= 0.003) mRNA in human visceral adipocytes.
Conclusions
Resveratrol,
in vitro
and at low concentration, modulates genes that are related to lipid metabolism, possibly preventing metabolic disease in human visceral adipose tissue (VAT).
Tissue accumulation and high urinary excretion of ethylmalonic acid (EMA) are found in ethylmalonic encephalopathy (EE), an inherited disorder associated with cerebral and cerebellar atrophy whose ...pathogenesis is poorly established. The in vitro and in vivo effects of EMA on bioenergetics and redox homeostasis were investigated in rat cerebellum. For the in vitro studies, cerebellum preparations were exposed to EMA, whereas intracerebellar injection of EMA was used for the in vivo evaluation. EMA reduced state 3 and uncoupled respiration in vitro in succinate‐, glutamate‐, and malate‐supported mitochondria, whereas decreased state 4 respiration was observed using glutamate and malate. Furthermore, mitochondria permeabilization and succinate supplementation diminished the decrease in state 3 with succinate. EMA also inhibited the activity of KGDH, an enzyme necessary for glutamate oxidation, in a mixed manner and augmented mitochondrial efflux of α‐ketoglutarate. ATP levels were markedly reduced by EMA, reflecting a severe bioenergetic disruption. Docking simulations also indicated interactions between EMA and KGDH and a competition with glutamate and succinate for their mitochondrial transporters. In vitro findings also showed that EMA decreased mitochondrial membrane potential and Ca2+ retention capacity, and induced swelling in the presence of Ca2+, which were prevented by cyclosporine A and ADP and ruthenium red, indicating mitochondrial permeability transition (MPT). Moreover, EMA, at high concentrations, mildly increased ROS levels and altered antioxidant defenses in vitro and in vivo. Our data indicate that EMA‐induced impairment of glutamate and succinate oxidation and MPT may contribute to the pathogenesis of the cerebellum abnormalities in EE.
We show that ethylmalonic acid (EMA), one of the main metabolites accumulating in ethylmalonic encephalopathy, disturbs oxidation of succinate and glutamate leading to decreased adenosine triphosphate (ATP) levels in rat cerebellum by inhibiting mitochondrial dicarboxylate (mDC) and glutamate (GC) carriers, reducing α‐ketoglutarate dehydrogenase (KGDH) activity and increasing α‐ketoglutarate (α‐KG) efflux by α‐KG/malate carrier (α‐KGC). These disturbances in bioenergetics possibly cause mitochondrial permeability transition (MPT) pore opening. EMA also increases superoxide levels that inhibit aconitase (Aco) activity and provoke oxidative stress. It is postulated that these pathomechanisms underlie the cerebellum abnormalities observed in ethylmalonic encephalopathy.
Background
The ATN classification system assumes a sequential model of disease progression. However, there are groups of individuals in the same ATN category that exhibit a predominance of ...abnormality (higher burden) of one of the biomarkers, creating heterogeneous ATN groups regarding pathological predominance. Thus, we tested the hypothesis that individuals clustered by ATN biomarker abnormality predominance may offer an alternative to groups defined using biomarkers cut‐offs.
Method
We assessed 103 cognitively impaired individuals(CDR> = 0.5) from the TRIAD cohort with available measures of plasma phosphorylated tau‐181, brain MRI, amyloid PET, and tau PET. We used the K‐means algorithm to stratify participants into three clusters. We compared the clusters on composite measures of memory, executive functioning, language, and visuospatial processing. To examine the utility of the discovered clusters, we compared them to traditional ATN categories in the prediction of neuropsychological measures. We did so by creating three categories: patients positive on all three ATN biomarkers, patients positive on two of the three biomarkers, and patients positive on either one or none. Additionally, we created an inflammation, amyloid and tau deposition probabilistic map anchored on young controls(n = 51, mean age = 23.74).
Result
We uncovered 3 clusters: an amyloid predominant (AP) cluster, a tau/phosphor‐tau predominant cluster (TP), and a cluster showing no predominance with low levels on all biomarkers (CN)(figure 1). Notably, levels of neurodegeneration and inflammation were similar between the AP and TP clusters. The AP cluster significantly differed from the CN cluster in memory only. Participants in the TP cluster had significantly lower scores in memory, executive functioning, language, and visuospatial processing than the other two clusters. In comparison, using threshold‐based ATN groups showed milder differences in memory and executive functioning, and no differences in language and visuospatial processing(figure 2). Furthermore, cluster membership moderated the relationship between various biomarkers, to the point of reversing the direction of correlation(figure 3).
Conclusion
Our results highlight the biological heterogeneity present within the Alzheimer’s disease continuum and that the pathological predominance of amyloid and tau is associated with different disease phenotypes. Approaching dementia patients with an eye on the predominance of pathology rather than cutoffs for abnormality may provide a better understanding of AD pathological subtypes.
Background
Deep learning models, particularly convolutional neural networks (CNNs), have shown promise in Alzheimer’s disease (AD) classification using tau PET data. However, limited sample sizes and ...unharmonized tau tracers present challenges to developing an agnostic tau tracer tool to predict AD using machine learning. Transfer learning, which leverages pre‐trained models for related tasks, may address these issues. Here we evaluate the effectiveness of transfer learning in optimizing 3D CNNs for AD classification with distinct cohorts and tau tracers.
Method
We used tau PET images from ADNI (18FFlortaucipir, n = 437) and TRIAD (18FMK‐6240, n = 423) cohorts, categorizing patients into CU (cognitively unimpaired) and CI (cognitively impaired). Standardized uptake value ratios (SUVR) were used for tau PET data. Separate 3D CNNs were trained for each tracer, with SUVR volumes as input and diagnosis as output. For transfer learning, we trained a model on 18FFlortaucipir data with a reduced learning rate, using a pre‐trained model from 18FMK‐6240. Models underwent 5‐fold cross‐validation, and metrics were computed as the average of validation metrics across folds. To avoid data leakage, images from the same subject were assigned to the same fold.
Result
The model trained on 18FMK‐6240 tracer demonstrated higher classification performance than 18FFlortaucipir (AUC = 0.84 vs 0.67; Figure 1. F1‐score = 79.77% vs 64.66%; Table 1). To enhance the classification performance of 18FFlortaucipir model, we employed a transfer learning approach by leveraging the model pre‐trained with 18FMK‐6240. With this approach, we observed a slight improvement in all classification metrics compared to the model trained solely on 18FFlortaucipir data (AUC = 0.71 vs 0.67; Figure 1. Accuracy = 71.39% vs 67.72, F1‐score = 67.97% vs 64.66%; Table 1).
Conclusion
This finding highlights the value of transfer learning in optimizing deep learning models for Alzheimer’s disease classification, particularly when handling tau tracers with varying performance levels. Our results are consistent with previous on transfer learning’s effectiveness in this context. These preliminary findings indicate that applying this technique to larger datasets of tau tracers may further enhance model performance, potentially leading to the development of a tau tracer‐agnostic tool that overcomes the need of tracer harmonization for predicting dementia.
Background
Cerebrospinal fluid (CSF) and Positron emission tomography (PET) amyloid‐β biomarkers are commonly used interchangeably to measure amyloid‐β deposition, an early event in the development ...of Alzheimer’s disease (AD). However, it is not uncommon to find individuals with discordant measurements of amyloid‐β CSF and PET. It has been hypothesized that this discordance may be an intermediate step between the CSF and brain amyloid deposition, and that discordant individuals might be in different disease stages or have different disease phenotypes. Here, we applied blood transcriptomic analysis to evaluate differences in amyloid‐β CSF and PET discordant and concordant individuals.
Method
We analyzed the blood transcriptome of 200 individuals from the ADNI cohort who had measurements of both CSF amyloid‐β42 and 18FFlorbetapir PET at baseline and at 2‐year follow‐up. The demographic characteristics of the sample are presented in table 1. Our analysis yielded four groups: CSF+/PET‐ (n = 18), CSF‐/PET+ (n = 19), CSF+/PET+ (n = 76), and CSF‐/PET‐ (n = 87). The latter was the control group for all analyses. Differentially expressed genes (DEGs, uncorrected p‐value < 0.01) were used for gene set enrichment analysis (GSEA) to identify group‐specific altered biological pathways.
Result
CSF+/PET‐, CSF‐/PET+ and CSF+/PET+ individuals showed a great proportion of unshared DEGs (Figure 1). The CSF+/PET‐ group, which is thought to represent a very early stage in the disease, presented the highest number of unshared DEGs (273) with upregulated GO terms involved mainly in metabolic processes. The CSF‐/PET+ group possessed 113 unique DEGs, while the CSF+/PET+ possessed 47. Interestingly, these groups presented similar alterations in biological processes, representing mainly alterations in immune response and inflammation.
Conclusion
Our results highlight the differences in the blood transcriptomic phenotype between CSF and PET amyloid‐β concordant and discordant individuals. Importantly, individuals very early in the AD continuum (CSF+/PET‐) presented the most distinct phenotype. Our results suggest that blood transcriptomics are able to capture subtle changes in brain amyloid‐β and might help identify individuals in different stages of AD.
Background
The ATN classification system assumes a sequential model of disease progression. However, there are groups of individuals in the same ATN category that exhibit a predominance of ...abnormality (higher burden) of one of the biomarkers, creating heterogeneous ATN groups regarding pathological predominance. Thus, we tested the hypothesis that individuals clustered by ATN biomarker abnormality predominance may offer an alternative to groups defined using biomarkers cut‐offs.
Method
We assessed 103 cognitively impaired individuals(CDR> = 0.5) from the TRIAD cohort with available measures of plasma phosphorylated tau‐181, brain MRI, amyloid PET, and tau PET. We used the K‐means algorithm to stratify participants into three clusters. We compared the clusters on composite measures of memory, executive functioning, language, and visuospatial processing. To examine the utility of the discovered clusters, we compared them to traditional ATN categories in the prediction of neuropsychological measures. We did so by creating three categories: patients positive on all three ATN biomarkers, patients positive on two of the three biomarkers, and patients positive on either one or none. Additionally, we created an inflammation, amyloid and tau deposition probabilistic map anchored on young controls(n = 51, mean age = 23.74).
Results
We uncovered 3 clusters: an amyloid predominant (AP) cluster, a tau/phosphor‐tau predominant cluster (TP), and a cluster showing no predominance with low levels on all biomarkers (CN)(figure 1). Notably, levels of neurodegeneration and inflammation were similar between the AP and TP clusters. The AP cluster significantly differed from the CN cluster in memory only. Participants in the TP cluster had significantly lower scores in memory, executive functioning, language, and visuospatial processing than the other two clusters. In comparison, using threshold‐based ATN groups showed milder differences in memory and executive functioning, and no differences in language and visuospatial processing(figure 2). Furthermore, cluster membership moderated the relationship between various biomarkers, to the point of reversing the direction of correlation(figure 3).
Conclusion
Our results highlight the biological heterogeneity present within the Alzheimer’s disease continuum and that the pathological predominance of amyloid and tau is associated with different disease phenotypes. Approaching dementia patients with an eye on the predominance of pathology rather than cutoffs for abnormality may provide a better understanding of AD pathological subtypes.
Background
Recent epidemiological studies showed that patients with attention‐deficit/hyperactivity disorder (ADHD) are more likely to be diagnosed with Alzheimer’s Disease (AD). Additionally, ...increased genetic risk for ADHD, measured with ADHD polygenic risk scores (ADHD‐PRS), was associated with amyloid‐dependent cognitive decline in older adults. However, it is unclear whether higher genetic risk for ADHD is associated with worse cognitive function in patients with AD dementia.
Method
We used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to investigate the association between cognitive function (Preclinical Alzheimer Cognitive Composite PACC, executive function, and memory) and ADHD‐PRS in subjects with AD dementia. Additionally, we tested whether ADHD‐PRS potentiated brain hypometabolism measured with 18FFDG‐PET. Analyses were controlled by age, sex, years of study, and number of APOE ε4 alleles.
Result
We evaluated baseline data from 264 AD patients (114 women 43.2%, mean SD age of 75 7.6 years). ADHD‐PRS was associated with decreased cognitive function (p‐value = .04, η2 = .01, Figure 1a), more specifically in executive function (p‐value = .04, η2 = .01, Figure 1c). Higher ADHD‐PRS was associated with brain hypometabolism in frontal, parietal, and temporal regions (Figure 2a,b). Brain hypometabolism correlated with worse cognitive function in the following regions: postcentral gyrus (p‐value = .01, η2 = .03), superior parietal gyrus (p‐value = .001, η2 = .07), precentral gyrus (p‐value = .004, η2 = .05), and fusiform gyrus (p‐value<.0001, η2 = .08, Figure 2c,d,e,f). Finally, decreased metabolism in these four regions mediated the effect of ADHD‐PRS on cognitive function (Figure 3).
Conclusion
Findings indicate that a higher genetic risk for ADHD is correlated with impaired cognitive function with small effect sizes. Moreover, the effects of the genetic risk of ADHD on cognitive function were mediated by hypometabolism in frontal, parietal, and temporal brain regions, which could point to a decrease resilience to AD pathology in individuals with ADHD. Clinically, our findings suggest that patients with comorbid ADHD and AD dementia have a more severe disease phenotype, with potential implications for prognosis and treatment.
Amyloid-β oligomers (AβOs) toxicity causes mitochondrial dysfunction, leading to synaptic failure in Alzheimer’s disease (AD). Considering presynaptic high energy demand and tight Ca
2+
regulation, ...impairment of mitochondrial function can lead to deteriorated neural activity and cell death. In this study, an AD mouse model induced by ICV (intracerebroventricular) injection of AβOs was used to investigate the toxicity of AβOs on presynaptic function. As a therapeutic approach, GUO (guanosine) was given by oral route to evaluate the neuroprotective effects on this AD model. Following 24 h and 48 h from the model induction, behavioral tasks and biochemical analyses were performed, respectively. AβOs impaired object recognition (OR) short-term memory and reduced glutamate uptake and oxidation in the hippocampus. Moreover, AβOs decreased spare respiratory capacity, reduced ATP levels, impaired Ca
2+
handling, and caused mitochondrial swelling in hippocampal synaptosomes. Guanosine crossed the BBB, recovered OR short-term memory, reestablished glutamate uptake, recovered mitochondrial Ca
2+
homeostasis, and partially prevented mitochondrial swelling. Therefore, this endogenous purine presented a neuroprotective effect on presynaptic mitochondria and should be considered for further studies in AD models.
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