Epigenetics of nutrition in aging

There is a need to identify factors that are able to influence health in old age and to develop interventions that could slow down the process of aging and its associated pathologies. Lifestyle modifications, and especially nutrition, appear to be promising strategies to promote healthy aging. Their impact on aging biomarkers has been poorly investigated. In the first part of this work, we evaluated the impact of a one-year Mediterranean-like diet, delivered within the framework of the NU-AGE project in 120 elderly subjects, on epigenetic age acceleration measures assessed with Horvath’s clock. We observed a rejuvenation of participants after nutritional intervention. The effect was more marked in the group of Polish females and in subjects who were epigenetically older at baseline. In the second part of this work, we developed a new model of epigenetic biomarker, based on a gene-targeted approach with the EpiTYPER® system. We selected six regions of interest (associated with ELOVL2, NHLRC1, SIRT7/MAFG, AIM2, EDARADD and TFAP2E genes) and constructed our model through a ridge regression analysis. In controls, estimation of chronological age was accurate, with a correlation coefficient between predicted and chronological age of 0.92 and a mean absolute deviation of 4.70 years. Our model was able to capture phenomena of accelerated or decelerated aging, in Down syndrome subjects and centenarians and offspring respectively. Applying our model to samples of the NU-AGE project, we observed similar results to the ones obtained with the canonical epigenetic clock, with a rejuvenation of the individuals after one-year of nutritional intervention. Together, our findings indicate that nutrition can promote epigenetic rejuvenation and that epigenetic age acceleration measures could be suitable biomarkers to evaluate their impact. We demonstrated that the effect of the dietary intervention is country-, sex- and individual-specific, thus suggesting the need for a personalized approach to nutritional interventions.

Bayesian Analysis of Linear Inverse Problems with Applications in Economics and Finance

In my PhD thesis I propose a Bayesian nonparametric estimation method for structural econometric models where the functional parameter of interest describes the economic agent's behavior. The structural parameter is characterized as the solution of a functional equation, or by using more technical words, as the solution of an inverse problem that can be either ill-posed or well-posed. From a Bayesian point of view, the parameter of interest is a random function and the solution to the inference problem is the posterior distribution of this parameter. A regular version of the posterior distribution in functional spaces is characterized. However, the infinite dimension of the considered spaces causes a problem of non continuity of the solution and then a problem of inconsistency, from a frequentist point of view, of the posterior distribution (i.e. problem of ill-posedness). The contribution of this essay is to propose new methods to deal with this problem of ill-posedness. The first one consists in adopting a Tikhonov regularization scheme in the construction of the posterior distribution so that I end up with a new object that I call regularized posterior distribution and that I guess it is solution of the inverse problem. The second approach consists in specifying a prior distribution on the parameter of interest of the g-prior type. Then, I detect a class of models for which the prior distribution is able to correct for the ill-posedness also in infinite dimensional problems. I study asymptotic properties of these proposed solutions and I prove that, under some regularity condition satisfied by the true value of the parameter of interest, they are consistent in a "frequentist" sense. Once I have set the general theory, I apply my bayesian nonparametric methodology to different estimation problems. First, I apply this estimator to deconvolution and to hazard rate, density and regression estimation. Then, I consider the estimation of an Instrumental Regression that is useful in micro-econometrics when we have to deal with problems of endogeneity. Finally, I develop an application in finance: I get the bayesian estimator for the equilibrium asset pricing functional by using the Euler equation defined in the Lucas'(1978) tree-type models.