Data integration to identify biological markers of neurodevelopmental disorders

Abstract

Neurodevelopmental disorders are polygenic and multifactorial. Besides the genetic component, evidences from animal and human studies indicate that environmental adversities and / or psychosocial stresses experienced early in life can trigger epigenetic changes that may influence brain plasticity, neural circuit connectivity and functioning. These changes may affect the adequate development of cognitive functions, emotional reactivity and sociability, increasing the risk for presenting neurodevelopmental disorders. The crucial role of the epigenetic machinery in the biological incorporation of exposure to stress in early life has been demonstrated in several animal models. These were exposed to different prenatal and / or postnatal stresses such as nutrition, drugs, inadequate maternal care, separation of the mother-child binomial and social enrichment / isolation, suggesting epigenetic molecular markers of risk. However, most of these studies are performed with exposure to specific environmental factors, such as nicotine use during pregnancy. That is, these studies disregard that an individual is normally exposed to several environmental stressors and that each individual responds individually to them. Another important point is that the sexes respond differently to stress exposure, thus adding an additional level of variability to the possible neurodevelopmental trajectories. Polygenic risk scores (PRSs) have contributed to a better understanding of these disorders, but these only consider the effect of genetic variations. It is necessary to search for methods to integrate PRSs with epigenetic risk markers, sex of the concept and the temporal effect of exposure to different types of stress to identify susceptibility markers associated with risk phenotypes for neurodevelopmental disorders. This project proposes a multidisciplinary approach using Systemic Biology tools and machine learning to integrate complex data, that is, of different natures. Specifically, we aim to achieve the following objectives: 1) to integrate environmental exposure data, and show that a multivariate stress construct approach is associated with individual biomarkers of stress reactivity by improving the prediction of phenotypes associated with neurodevelopmental trajectories; 2) to integrate data of gene expression, epigenetics, sex of the concept and environmental exposure to develop a biological model to explain differences in susceptibility between sexes for neurodevelopmental disorders; 3) to integrate polygenic risk scores data with environmental exposure and epigenetic molecular markers of risk to characterize genomic areas, that could be evaluated improving the prediction of phenotypes associated with neurodevelopmental trajectories. The completion of these objectives will provide new methodologies for complex data integration, molecular targeting and identification of potential preventive measures related to the development of neurodevelopmental disorders. (AU)