We have developped a custom-made mouthguard model which seems to be a potential protective device to avoid or limit the cumulative brain effects of head accelerations during repeated sport-related impacts, as found previously in a first experimental study. We want to continue the development of this mouthguard in order to integrate measurement sensors (accelerations and pressure) of exposure to sport-related head impacts, in order to be able to study the link between these impacts and brain modifications, suspected of lead to neurodegenerative diseases. The objectives and methodology are divided into 3 workpackages (WP). WP1 will consist of the experimental development of a connected mouthguard: the objective is to develop the measurement system, from the selection of the sensors (inertial unit and pressure sensor) to the integration into our 3D-printed mouthguard model after checking the reliability of the recorded data and adaptating the 3D printing procedure, and with a rechargeable battery and wireless transmission of energy and data. The objective of WP2 will be the validation of this numerical tool for monitoring head impacts and accelerations suffered during sports practice in real conditions: the prototype will be tested with rugby and soccer players, to check the ability of the system to measure head accelerations correctly, by calibrating the data first through non-contact runs and gradually integrating voluntary contacts at different intensities, and then impacts in real conditions. The WP3 aims to assess brain and cognitive hyper-acute and long-term changes in high-level athletes, depending on their exposition to head impacts monitoring by the numerical mouthguard. Neurocognitive and functional near-infrared spectroscopy data will be compared pre and post heading, between 2 groups equipped with either our mouthguard or another connected mouthguard or without mouthguard. Possible correlations with peak linear and angular head acceleration or with muscles activity recordings will be studied. Besides, a prospective cohort of 100 athletes exposed to high risk of head impacts will be followed over 3 consecutive years with an accurate monitoring of all head impacts through our connected mouthguard. The primary endpoint will be the season-to-season evolution of brain activation changes correlated to number of head impacts and mean peak of head acceleration during these impacts. Ultimately, the goal will be to transfer this technology to industry to make it accessible to all and allow users to both monitor their exposure and protect their health.

Faced with health crises, the elderly are among the most at risk, as the 2003 heat wave in French has shown, excess mortality related to age being particularly marked in people living alone or in nursing homes. Even though the COVID-19 epidemic is far from over, it is more than likely that the elderly population will again be one of the most affected. Beyond the medical characteristics, specificities which relate to attitudes, psychological and social functioning contribute to this phenomenon. Apart from a crisis situation, the consequences of an illness are very different from one elderly subject to another depending on psychological resources, lifestyle, social support, adaptation of the home, accessibility of services and shops... Some studies have looked at the consequences of confinement, but none in the elderly population even though we have reasons to believe that this population is particularly vulnerable at least on 3 levels: 1) to the response to infectious agent due to its physiological characteristics; 2) because of the psychosocial characteristics which make a party even more at risk of severe repercussions of the infection (dependent persons, cognitive disorders, isolated persons, living in institutions); 3) to confinement situation due to reduced psychological adjustment capacity in the elderly. This project consists of rapidly setting up a phone survey of 1000 elderly people in order to address the following questions: 1) What are the attitudes, the psychological and social experience of the elderly facing the COVID-19 crisis and confinement: the level of stress, anxiety, social support during confinement, access to information, to the guidelines and measures implemented by government authorities, the level of understanding and adherence to these guidelines, representations of the epidemic, access to services restricted in this context or to digital communication tools? 2) To what extent these characteristics, representations and attitudes have an impact on health, mortality (related and not related to COVID-19) and capacities for resilience in the face of this crisis? The phone survey will take place during and post-confinement. While setting up a vast general population survey in just a few days is hardly possible, and even more so when research staff are also subject to confinement, our team has the means to do so: immediate access to population cohort studies coordinated by the team; a corpus of information already available on these subjects (health and functional indicators, medication, lifestyle, social environment, cognitive deficits, depression, etc.) which will limit the data collection to the crisis situation; prospective follow-up (availability of information before the crisis thanks to the cohorts; during and post-confinement thanks to the survey, in the longer term with prospective follow-up of the cohorts); human resources (11 psychologists will carry out telework interviews). This epidemic being likely to repeat itself, the knowledge that we will draw from this study should help us to communicate better towards the elderly population and establish specific instructions for seniors; but also, to better target among this already at risk category of population, the most at risk ones, in order to be able to set up medico-social action plans even before Day 1 of the epidemic. Today in France, municipality services have very little means of contacting these people, most municipalities referring to "heat wave" files made up of people who have voluntarily taken the step to appear in it. Although welcome, this initiative will unfortunately be insufficient.

University students, already at risk of suicide, are considerably affected by the COVID-19 epidemic because of their isolation and concerns about their studies and financial resources. The objective of the ECLIPSE project is to assess the impact of the COVID-19 epidemic on suicide risk among students. Specifically, we will: (1) describe the consequences of the epidemic and lockdown on students’ mental health and particularly on suicidal thoughts and their evolution; (2) identify suicidal risk profiles in this context; (3) analyze the psychological impact of the epidemic on healthcare students using mixed-methods; 4) describe fluctuations in suicidal thoughts and their association with short-term risk factors, particularly emotional variability. Our multidisciplinary project will deploy complementary methods: longitudinal analysis of existing questionnaires, semi-structured interviews, experience sampling method. Our final goal is to identify the profiles of students at risk, which will allow us to intervene before the suicidal crisis and promote an effective suicide prevention policy program.

With their large amount of multivariate information collected repeatedly over visits, epidemiological cohorts allows for the in-depth study of the dynamic and multidimensional aspects of health phenomena. Yet, valid statistical methods that jointly analyze multiple dynamic processes are lacking. DyMES aims to develop innovative statistical models and apply them to large cohort data to understand and predict multivariate health processes. We will focus on two neurodegenerative diseases, Alzheimer’s Disease (AD) and Multiple System Atrophy (MSA), which share major methodological challenges such as the coexistence of multiple inter-related progressive impairments. We will tackle four issues: Task 1: Prediction. We will develop joint models to analyze multiple longitudinal dimensions and clinical events. From them, we will be able to compute individual dynamic predictions of clinical events that make use of all the information previously collected on an individual. For instance, repeated measures of cognitive functions, dependency to daily activities and neuro-imaging markers will be exploited to predict the risk of dementia. Task 2: Causality. We will develop an innovative approach to quantify temporal influences between dynamic processes. By using mechanistic models in discrete time, the method can unravel complex causal relationships between processes, and as such help understand underlying physio-pathological mechanisms. In MSA we will for instance identify the relations between autonomic system and functional progression; in AD we will disentangle the dynamic relationships between brain structures and clinical manifestations. Task 3: Long-term and time-varying exposures. Modifying lifestyle factors is a promising perspective for prevention in AD but little is known on exposure trajectories in relationship with late-life outcomes (e.g., most critical exposures and/or time windows). We will develop statistical methods that will enable the simultaneous analysis of several time-varying exposures (e.g., cardio-metabolic exposures in midlife) linked with health outcomes (e.g., cognitive decline after 70 years old). For exposures and disease markers concomitantly observed in late-life, we will also exploit task 2 developments and separate causal associations between exposures and markers from changes in exposures due to the underlying disease. Task 4: Dissemination. We will largely improve the diffusion of up-to-date statistical models with validated user-friendly R packages. By implementing a parallelized estimation algorithm, we will speed up all the estimation programs developed by the team in the past and within this project. DyMES will leverage data from four complementary cohorts in AD: the population-based cohorts Paquid and 3C study, the MEMENTO study, and the large American Nurses’ Health Study with lifestyle exposures collected from midlife. In MSA, we will analyze one of the largest cohorts worldwide from the French national reference center. Thanks to the access to high quality data and the multidisciplinary project team comprising statisticians, epidemiologists and neurologists working in close vicinity, the project has the ambition to: - provide innovative statistical models with efficient associated programs to the statistical and epidemiological communities that are essential for the analysis of multivariate longitudinal data; - answer burning questions such as unravel the influences between processes involved in a disease, predict its progression or identify lifestyle behaviors and time windows to optimize prevention. Although motivated by MSA and AD, the project will apply far beyond. It will enhance the statistical analysis of longitudinal epidemiological studies by providing valid reproducible methods, and the understanding of chronic diseases with repercussions for public health in the long-term.

A quantum leap in development of therapeutics of dementia can be achieved through improved understanding of the natural resilience mechanisms of brain cells to various noxious influences like vascular insults. However our understanding of such resilience pathways is limited, as majority of studies in past focused primarily on exploring the causes of neurodegeneration with little attention given towards understanding why some people besides at higher risk of cerebrovascular injury show minimal signs of neurodegeneration on MRI. I hypothesize that rare exonic variants with loss- or gain-of-function effects on genes involved in brain’s resilience pathways might protect brain cells from degeneration in individuals at an elevated common variant polygenic risk of cerebrovascular insults. I propose the Brain Resilience Initiative: genes shielding the brain from Cerebrovascular insultS (BRICS) project, which aims to identify rare and low frequency variants in genes involved in resilience mechanisms of the brain to cerebrovascular insults: ischemia and hemorrhage, using genetic instruments. This project will be performed on two well-characterized French population-based cohorts of older adults: 3C and MEMENTO, and large multi-cohort/biobank data from UKBB and the JPND-BRIDGET network, leveraging the cutting edge genetic and brain imaging data, to identify genetic variants associated with brain resilience to cerebrovascular insults. Identified genes would not only improve our understanding of the mechanism underlying brain resilience, but also serve as a potential drug targets for dementia prevention and treatment.