Abstract: Alzheimer’s disease (AD) is a primary cause of dementia. AD is a neurodegenerative disorder, characterized by synapses loss, extracellular amyloid plaques composed of the amyloid-β peptide (Aβ) and intracellular aggregates of hyperphosphorylated tau protein. AD is a complex disease linked to multiple interacting factors, both environmental and genetic, which can contribute to the onset and severity of the disease. Longitudinal studies have highlighted several cardiovascular risk factors that can increase the risk of AD. The genetic landscape of AD has changed dramatically in recent decades. Early studies identified mutations in the amyloid precursor protein gene (APP) as well as proteins that are involved in the enzymatic cleavage of APP to toxic β-amyloid (Aβ), namely presenilin-1 and presnilin-2. However, these mutations were found in familial cases of early-onset AD, while the causes of sporadic late-onset AD are still unknown. The latest advances in Genome-wide Association Studies (GWAS), sequencing, and bioinformatics have begun to unravel the complex genetic architecture of the sporadic form of AD. GWAS were able to uncover common variants with high frequency in the population that individually carried low risk (Robinson et al., 2017). The advent of next-generation and third-generation sequencing platforms shows great promise in further unravelling the genetics of AD. Exome sequencing has been gradually optimized to identify mutations in protein-coding regions, and genome sequencing detects potential disease-causing mutations in non-coding sections of DNA. It has been suggested that underlying the base of neurodegenerative diseases, there is, also, an involvement of epigenetic mechanisms able to influence the expression of genes without altering the DNA sequence, including methylation, non-coding RNAs such as microRNA, and chromatin remodeling (Fenoglio et al., 2018). All these findings radically changed the understanding of AD pathology. In fact, the understanding of the genetic and epigenetic mechanisms and the biological pathways underlying AD has and will continue to have significant benefits also for the search for new therapeutic targets. Clinical symptoms of AD are assessed by instrumental and cognitive examinations, associated with the patient’s medical history, to establish a “probable AD” diagnosis (McKhann et al., 1984). To complete these assessments, five biomarkers of AD, divided into two categories, were validated in clinical practice. The first category of biomarkers concerns the dosage of the Aβ protein, i.e. the decrease in the concentrations of the Aβ42 protein in the cerebrospinal fluid (CSF). A second biomarker uses positron emission tomography (PET), a neuroimaging technique to measure Aβ deposition by calculating the absorption and retention of a tracer. These techniques are well correlated, and have been validated by post mortem examination. The second category of biomarkers concerns neurodegeneration: a first kind of biomarker is the total tau protein and phosphorylated tau assay in the patient’s CSF, which increases during the course of the disease; a second kind of biomarker is the use of structural magnetic resonance imaging to measure increased atrophy during AD. A third category of biomarkers is hypometabolism in disease as measured by [18F] fluorodeoxyglucose PET imaging. Again these correlate well with post mortem outcomes (Lashley et al., 2018). In summary, definitive diagnosis of AD is only possible with a post mortem examination of brain tissue showing senile plaques and neurofibrillary tangles. Diagnosis, even at an early stage, is now performed by tests on CSF and with PET, but these tests are expensive or invasive. To date, there are no peripheral AD biomarkers used in clinical practice, so, considering the invasive nature of lumbar puncture for CSF sampling and the cost of neuroimaging, there is an absolute need to have specific biomarkers for early diagnosis of AD. In this regard, recent works have shown that high-precision tests for plasma Aβ42/Aβ40 detection are predictive for the accumulation of Aβ in the brain. Therefore, the development of blood-based Aβ biomarkers is of great interest (Schindler et al., 2019). So overall, identification of cost-effective biomarkers and use of more accessible biofluids, such as blood, could represent valid peripheral biomarkers for the AD diagnosis.