Life expectancy has gradually grown over the last century. This has deeply affected healthcare costs, since the growth of an aging population is correlated to the increasing burden of chronic diseases. This represents the interesting challenge of how to manage patients with chronic diseases in order to improve health care budgets. Effective primary prevention could represent a promising route. To this end, precision, together with personalized medicine, are useful instruments in order to investigate pathological processes before the appearance of clinical symptoms and to guide physicians to choose a targeted therapy to manage the patient. Cardiovascular and neurodegenerative diseases represent suitable models for taking full advantage of precision medicine technologies applied to all stages of disease development. The availability of high technology incorporating artificial intelligence and advancement progress made in the field of biomedical research have been substantial to understand how genes, epigenetic modifications, aging, nutrition, drugs, microbiome and other environmental factors can impact health and chronic disorders. The aim of the present review is to address how precision and personalized medicine can bring greater clarity to the clinical and biological complexity of these types of disorders associated with high mortality, involving tremendous health care costs, by describing in detail the methods that can be applied. This might offer precious tools for preventive strategies and possible clues on the evolution of the disease and could help in predicting morbidity, mortality and detecting chronic disease indicators much earlier in the disease course. This, of course, will have a major effect on both improving the quality of care and quality of life of the patients and reducing time efforts and healthcare costs.

Though the acute effects of SARS-CoV-2 infection have been extensively reported, the long-term effects are less well described. Specifically, while clinicians endure to battle COVID-19, we also need to develop broad strategies to manage post-COVID-19 symptoms and encourage those affected to seek suitable care. This review addresses the possible involvement of the lung, heart and brain in post-viral syndromes and describes suggested management of post-COVID-19 syndrome. Post-COVID-19 respiratory manifestations comprise coughing and shortness of breath. Furthermore, arrhythmias, palpitations, hypotension, increased heart rate, venous thromboembolic diseases, myocarditis and acute heart failure are usual cardiovascular events. Among neurological manifestations, headache, peripheral neuropathy symptoms, memory issues, lack of concentration and sleep disorders are most commonly observed with varying frequencies. Finally, mental health issues affecting mental abilities and mood fluctuations, namely anxiety and depression, are frequently seen. Finally, long COVID is a complex syndrome with protracted heterogeneous symptoms, and patients who experience post-COVID-19 sequelae require personalized treatment as well as ongoing support.

Arterial hypertension (AH) is a progressive issue that grows in importance with the increased average age of the world population. The potential role of artificial intelligence (AI) in its prevention and treatment is firmly recognized. Indeed, AI application allows personalized medicine and tailored treatment for each patient. Specifically, this article reviews the benefits of AI in AH management, pointing out diagnostic and therapeutic improvements without ignoring the limitations of this innovative scientific approach. Consequently, we conducted a detailed search on AI applications in AH: the articles (quantitative and qualitative) reviewed in this paper were obtained by searching journal databases such as PubMed and subject-specific professional websites, including Google Scholar. The search terms included artificial intelligence, artificial neural network, deep learning, machine learning, big data, arterial hypertension, blood pressure, blood pressure measurement, cardiovascular disease, and personalized medicine. Specifically, AI-based systems could help continuously monitor BP using wearable technologies; in particular, BP can be estimated from a photoplethysmograph (PPG) signal obtained from a smartphone or a smartwatch using DL. Furthermore, thanks to ML algorithms, it is possible to identify new hypertension genes for the early diagnosis of AH and the prevention of complications. Moreover, integrating AI with omics-based technologies will lead to the definition of the trajectory of the hypertensive patient and the use of the most appropriate drug. However, AI is not free from technical issues and biases, such as over/underfitting, the “black-box” nature of many ML algorithms, and patient data privacy. In conclusion, AI-based systems will change clinical practice for AH by identifying patient trajectories for new, personalized care plans and predicting patients’ risks and necessary therapy adjustments due to changes in disease progression and/or therapy response.

Inflammation is a physiological process by which the body responds to external insults and stress conditions, and it is characterized by the production of pro-inflammatory mediators such as cytokines. The acute inflammatory response is solved by removing the threat. Conversely, a chronic inflammatory state is established due to a prolonged inflammatory response and may lead to tissue damage. Based on the evidence of a reciprocal regulation between inflammation process and calcium unbalance, here we described the involvement of a calcium sensor in cardiac diseases with inflammatory drift. Indeed, the Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) is activated in several diseases with an inflammatory component, such as myocardial infarction, ischemia/reperfusion injury, pressure overload/hypertrophy, and arrhythmic syndromes, in which it actively regulates pro-inflammatory signaling, among which includes nuclear factor kappa-B (NF-κB), thus contributing to pathological cardiac remodeling. Thus, CaMKII may represent a key target to modulate the severity of the inflammatory-driven degeneration.

Long-living individuals (LLIs) are used to study exceptional longevity. A number of genetic variants have been found associated in LLIs to date, but further identification of variants would improve knowledge on the mechanisms regulating the rate of aging. Therefore, we performed a genome-wide association study on 410 LLIs and 553 young control individuals with a 317K single-nucleotide polymorphism (SNP) chip to identify novel traits associated with aging. Among the top ( p < 1 × 10 ⁻⁴ ) SNPs initially identified, we found rs10491334 ( CAMKIV ) (odds ratio [OR] = 0.55; 95% confidence interval [CI] 0.42–0.73; p = 2.88 × 10 ⁻⁵ ), a variant previously reported associated with diastolic blood pressure, associated also in a replication set of 116 LLIs and 160 controls (OR = 0.54; 95% CI 0.32–0.90; p = 9 × 10 ⁻³ ). Furthermore, in vitro analysis established that calcium/calmodulin-dependent protein kinase IV (CAMKIV) activates the survival proteins AKT, SIRT1, and FOXO3A, and we found that homozygous carriers of rs10491334 have a significant reduction in CAMKIV expression. This, together with the observed reduction in minor-allele carriers among centenarians, points to a detrimental role for the SNP. In conclusion, prolongevity genes are activated by CAMKIV, the levels of which are influenced by rs10491334, a SNP associated with human longevity.