Frontotemporal Dementia (FTD) is the form of neurodegenerative dementia with the highest prevalence after Alzheimer’s disease, equally distributed in men and women. It includes several variants, generally characterized by behavioural instability and language impairments. Although few mendelian genes (MAPT, GRN, and C9orf72) have been associated to the FTD phenotype, in most cases there is only evidence of multiple risk loci with relatively small effect size. To date, there are no comprehensive studies describing FTD at molecular level, highlighting possible genetic interactions and signalling pathways at the origin FTD-associated neurodegeneration. In this study, we designed a broad FTD genetic interaction map of the Italian population, through a novel network-based approach modelled on the concepts of disease-relevance and interaction perturbation, combining Steiner tree search and Structural Equation Model (SEM) analysis. Our results show a strong connection between Calcium/cAMP metabolism, oxidative stress-induced Serine/Threonine kinases activation, and postsynaptic membrane potentiation, suggesting a possible combination of neuronal damage and loss of neuroprotection, leading to cell death. In our model, Calcium/cAMP homeostasis and energetic metabolism impairments are primary causes of loss of neuroprotection and neural cell damage, respectively. Secondly, the altered postsynaptic membrane potentiation, due to the activation of stress-induced Serine/Threonine kinases, leads to neurodegeneration. Our study investigates the molecular underpinnings of these processes, evidencing key genes and gene interactions that may account for a significant fraction of unexplained FTD aetiology. We emphasized the key molecular actors in these processes, proposing them as novel FTD biomarkers that could be crucial for further epidemiological and molecular studies.

Background and objectives: Prospective investigations on cardiovascular risk factors in populations provide a unique opportunity to dissect time-dependent quantitative complex traits, such as arterial blood pressure (BP), into their polygenic and environmental components. BP heritability analyses were carried out on 2620 patients belonging to 711 nuclear pedigrees that could be followed up throughout 25 years in the Gubbio Population Study. Methods: Each patient's BP serial measurements were summarized into individual intercepts (expected values at baseline) and slopes (time-related changes), which were predicted through latent curve models. These models considered either age in years or waves (times from the first survey) as time axis and were linked at a family level in the heritability analyses using additive polygenic–common environment–unique error models adjusted for sex, age and clinical variables. Results: The additive genetic effect explained 32–49% of the variance of SBP values at baseline, the wave-dependent analysis with nuclear pedigrees and the sibs-household matrix accounting for higher heritability values. Heritability of DBP baseline value was lower than that of SBP in analyses by age (5–15%), but fell in the same heritability range as SBP on the analysis by waves (36–37%). The BP variation over time (slope) explained by an additive genetic effect ranged from 33 to 43% and from 24 to 25% for SBP and DBP, respectively, in the analysis by age. Shared environment also exerted a significant influence, but explained a smaller portion of the variances (4–17%) for both traits. Conclusion: Longitudinal data from the Gubbio population show strong to moderate genetic influences on SBP and DBP baseline values and changes over time with a smaller, though significant, effect of environment.