While Alzheimer’s disease (AD) classical diagnostic criteria rely on clinical data from a stablished symptomatic disease, newer criteria aim to identify the disease in its earlier stages. For that, they incorporated the use of AD’s specific biomarkers to reach a diagnosis, including the identification of Aβ and tau depositions, glucose hypometabolism, and cerebral atrophy. These biomarkers created a new concept of the disease, in which AD’s main pathological processes have already taken place decades before we can clinically diagnose the first symptoms. Therefore, AD is now considered a dynamic disease with a gradual progression, and dementia is its final stage. With that in mind, new models were proposed, considering the orderly increment of biomarkers and the disease as a continuum, or the variable time needed for the disease’s progression. In 2011, the National Institute on Aging and the Alzheimer’s Association (NIA-AA) created separate diagnostic recommendations for each stage of the disease continuum—preclinical, mild cognitive impairment, and dementia. However, new scientific advances have led them to create a unifying research framework in 2018 that, although not intended for clinical use as of yet, is a step toward shifting the focus from the clinical symptoms to the biological alterations and toward changing the future diagnostic and treatment possibilities. This review aims to discuss the role of biomarkers in the onset of AD.

In recent years, the idea that sleep is critical for cognitive processing has gained strength. Alzheimer's disease (AD) is the most common form of dementia worldwide and presents a high prevalence of sleep disturbances. However, it is difficult to establish causal relations, since a vicious circle emerges between different aspects of the disease. Nowadays, we know that sleep is crucial to consolidate memory and to remove the excess of beta-amyloid and hyperphosphorilated tau accumulated in AD patients' brains. In this review, we discuss how sleep disturbances often precede in years some pathological traits, as well as cognitive decline, in AD. We describe the relevance of sleep to memory consolidation, focusing on changes in sleep patterns in AD in contrast to normal aging. We also analyze whether sleep alterations could be useful biomarkers to predict the risk of developing AD and we compile some sleep-related proposed biomarkers. The relevance of the analysis of the sleep microstructure is highlighted to detect specific oscillatory patterns that could be useful as AD biomarkers.the risk of developing AD [9]. Similarly, Bubu and colleagues estimated in a meta-analysis that the risk of dementia in patients with sleep disorders was 1.68 times greater [10]. Moreover, in a recent multi-center study, both midlife and late-life terminal insomnia were associated with a higher risk of dementia [11].It is interesting to note that affected brain structures in people with disturbed sleep coincide with vulnerable areas in AD. Lower gray matter volume in hippocampus, precuneus, amygdala, and cingulate gyrus [12][13][14][15][16][17][18][19], and a higher degree of cortical atrophy have been described in cognitively-unimpaired insomnia patients [14,20]. A recent study performed in cognitively unimpaired adults aged between 45 and 75, found that insomnia patients presented decreases in grey matter volume in AD-related areas, that concur with other studies. Furthermore, they found greater volume in the left caudate in these subjects, which can also be seen in presymptomatic carriers of an AD genetic mutation [21]. Finally, a very recent study in middle-aged, cognitively unimpaired adults found lower grey matter volumes in the left angular gyrus, the bilateral superior frontal gyri, the thalami, and the right hippocampus in insomniac APOE-ε4 carriers (AD's main risk factor) when compared to non-carriers with or without insomnia [21].This temporal and anatomical relationship could suggest that sleep disturbances may influence or exacerbate AD pathology and that improving sleep may help slow down its progression [22,23]. Additionally, sleep alterations could be used to predict the risk of developing dementia and could also serve as early indicators of the disease. If sleep disorders constitute a risk factor to initiate or to accelerate the clinical course of AD, they could be used to develop disease biomarkers. Furthermore, a sleep biomarker with high sensitivity and specificity would be extremely useful, as electrophysiological re...

Obesity is known to induce leptin and insulin resistance. Leptin is a peptide hormone synthesized in adipose tissue that mainly regulates food intake. It has been shown that insulin stimulates the production of leptin when adipocytes are exposed to glucose to encourage satiety; while leptin, via a negative feedback, decreases the insulin release and enhances tissue sensitivity to it, leading to glucose uptake for energy utilization or storage. Therefore, resistance to insulin is closely related to leptin resistance. Obesity in middle age has also been related to Alzheimer’s disease (AD). In recent years, the relation between impaired leptin signaling pathway and the onset of AD has been studied. In all this context the role of the blood brain barrier (BBB) is crucial. Slow excitotoxicity happens in AD due to an excess of the neurotransmitter glutamate. Since leptin has been shown to regulate N -methyl- D -aspartate (NMDA) receptors, we want to review the link between these pathological pathways, and how they are affected by other AD triggering factors and its role in the onset of AD.

Biomarkers for disease diagnosis and prognosis are crucial in clinical practice. They should be objective and quantifiable and respond to specific therapeutic interventions. Optimal biomarkers should reflect the underlying process (pathological or not), be reproducible, widely available, and allow measurements repeatedly over time. Ideally, biomarkers should also be non-invasive and cost-effective. This review aims to focus on the usefulness and limitations of electroencephalography (EEG) in the search for Alzheimer’s disease (AD) biomarkers. The main aim of this article is to review the evolution of the most used biomarkers in AD and the need for new peripheral and, ideally, non-invasive biomarkers. The characteristics of the EEG as a possible source for biomarkers will be revised, highlighting its advantages compared to the molecular markers available so far.

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