Ovarian Hormone-Dependent Effects of Dietary Lipids on APP/PS1 Mouse Brain

Diets with Higher ω-6/ω-3 Ratios Show Differences in Ceramides and Fatty Acid Levels Accompanied by Increased Amyloid-Beta in the Brains of Male APP/PS1 Transgenic Mice

Senile plaque formation as a consequence of amyloid-β peptide (Aβ) aggregation constitutes one of the main hallmarks of Alzheimer's disease (AD). This pathology is characterized by synaptic alterations and cognitive impairment. In order to either prevent or revert it, different therapeutic approaches have been proposed, and some of them are focused on diet modification. Modification of the ω-6/ω-3 fatty acids (FA) ratio in diets has been proven to affect Aβ production and senile plaque formation in the hippocampus and cortex of female transgenic (TG) mice. In these diets, linoleic acid is the main contribution of ω-6 FA, whereas alpha-linoleic acid (ALA), eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and docosapentaenoic acid (DPA) are the contributors of ω-3 FA. In the present work, we have explored the effect of ω-6/ω-3 ratio modifications in the diets of male double-transgenic APPswe/PS1ΔE9 (AD model) and wild-type mice (WT). Amyloid burden in the hippocampus increased in parallel with the increase in dietary ω-6/ω-3 ratio in TG male mice. In addition, there was a modification in the brain lipid profile proportional to the ω-6/ω-3 ratio of the diet. In particular, the higher the ω-6/ω-3 ratio, the lower the ceramides and higher the FAs, particularly docosatetraenoic acid. Modifications to the cortex lipid profile was mostly similar between TG and WT mice, except for gangliosides (higher levels in TG mice) and some ceramide species (lower levels in TG mice).

Brain lipidomics as a rising field in neurodegenerative contexts: Perspectives with Machine Learning approaches

Lipids are essential for cellular functioning considering their role in membrane composition, signaling, and energy metabolism. The brain is the second most abundant organ in terms of lipid concentration and diversity only after adipose tissue. However, in the central system (CNS) lipid dysregulation has been linked to the etiology, progression, and severity of neurodegenerative diseases such as Alzheimeŕs, Parkinson, and Multiple Sclerosis. Advances in the human genome and subsequent sequencing technologies allowed us the study of lipidomics as a promising approach to diagnosis and treatment of neurodegeneration. Lipidomics advances rapidly increased the amount and quality of data allowing the integration with other omic types as well as implementing novel bioinformatic and quantitative tools such as machine learning (ML). Integration of lipidomics data with ML, as a powerful quantitative predictive approach, led to improvements in diagnostic biomarker prediction, clinical data integration, network, and systems approaches for neural behavior, novel etiology markers for inflammation, and neurodegeneration progression and even Mass Spectrometry image analysis. In this sense, by exploiting lipidomics data with ML is possible to improve the identification of new biomarkers or unveil new molecular mechanisms associated with lipid impairment across neurodegeneration. In this review, we present the lipidomic neurobiology state-of-the-art highlighting its potential applications to study neurodegenerative conditions. Also, we present theoretical background, applications, and advances in the integration of lipidomics with ML. This review opens the door to new approaches in this rising field.

Alterations of GABA B receptors in the APP/PS1 mouse model of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the progressive decline of memory and cognitive function. The disease is characterized by the presence of amyloid plaques, tau tangles, altered inflammatory signaling, and alterations in numerous neurotransmitter signaling systems, including γ-aminobutyric acid (GABA). Given the extensive role of GABA in regulating neuronal activity, a careful investigation of GABA-related changes is needed. Further, given persistent inflammation has been demonstrated to drive AD pathology, the presence of GABA B receptor expressed on glia that serve a role regulation of the immune response adds to potential implications of altered GABA in AD. There has not previously been a systematic evaluation of GABA-related changes in an amyloid model of AD that specifically focuses on examining changes in GABA B receptors. In the present study, we examined alterations in several GABA-specific targets in the APP/PS1 mouse model at different ages. In the 4-month-old cohort, no significant deficits in spatial learning and memory or alterations in any of the GABAergic targets were observed compared with wild-type controls. However, we identified significant alterations in several GABA-related targets in the 6-month-old cohort that exhibited spatial learning deficits that include changes in glutamic acid decarboxylase 65, GABA transporter type 3, and GABA B receptors protein and mRNA levels. This was the same cohort at which learning and memory deficits and significant amyloid pathology was observed. Overall, our study provides evidence of altered GABAergic signaling in an amyloid model of AD at a time point consistent with AD-related deficits.