Periodic Reporting for period 4 - SEGWAY (Study on Environmental and GenomeWide predictors of early structural brain Alterations in Young students)
Reporting period: 2020-06-01 to 2022-05-31
Mounting evidence suggests that early life factors have an important impact on the occurrence of late-life neurological diseases. From a public health perspective this is of particular relevance for dementia. With increasing longevity the number of persons affected by dementia is increasing drastically, with no available preventive treatment, resulting in a major burden at the individual and socio-economic level. Converging evidence indicates that pathological processes likely begin many years before clinical diagnosis. Interestingly, measures of brain structure on magnetic resonance imaging (MRI) that were shown to be powerful determinants of dementia in older persons can already show subtle alterations in young and middle-aged adults. The SEGWAY project aimed to: (i) explore the contribution of variations in the genetic make-up of individuals to structural brain measures in young adults in their early twenties participating in the i-Share study, the largest ongoing study on student’s health; (ii) take a lifetime perspective by examining the shared genetic contribution to alterations in brain structure in young adulthood (i-Share study) and late-life, among participants of a large French population-based study, aged 65 years and older (3C-Dijon study); (iii) explore whether the impact of genetic factors on brain changes is modulated by the exposure to vascular risk factors (hypertension, hypercholesterolemia, obesity, smoking…) with an established impact on brain aging; (iv) examine the clinical significance of genes associated with changes in brain structure by testing their association with cognitive performance in both age groups, and with dementia risk in older adults. Identifying common biological mechanisms underlying both early and late-life structural brain changes may provide important information on the mechanisms and time-course of brain aging throughout a lifetime and could be of major importance for identifying novel drug targets and characterizing high risk populations most likely to benefit from early preventative interventions. Over the course of the project we have contributed to the discovery of >50 novel genetic risk variants associated with MRI-markers of brain aging in older adults, in collaboration with additional population-based studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. We found that several of these genetic variants already showed strong associations with structural brain variations in young adults in their twenties. We found this to be particularly prominent for genetic risk variants for MRI-markers of vascular brain aging, i.e. for white matter hyperintensity volume (WMH), strongly associated with changes in diffusion tensor imaging in young adults, and for perivascular space burden (PVS), strongly associated with PVS burden in the brain white matter of young adults. Genetically determined WMH was associated with an increased risk of ischemic stroke, hemorrhagic stroke and Alzheimer type dementia. We found that, in aggregate, genetic risk variants for WMH showed significant interaction with hypertension in relation with WMH burden.
We have created a unique database to explore genetic determinants of brain structure in young adults, with high resolution brain MRI, genome-wide genotype data, and whole genome sequencing in a large subset. Several publications have been generated describing the heritability of and novel genetic risk variants for MRI-markers of brain aging, their impact on brain structure in young adults, as well as the (causal) relation and shared genetic variation with cognitive performance and decline, dementia and stroke. Using novel cutting-edge statistical approaches and bioinformatics tools we, for instance, recently demonstrated that genetic variants associated with MRI-markers of vascular brain aging already show significant association with MRI-markers of brain microstructure in young adults. Our results also suggest a causal association of these MRI-markers with risk of stroke and Alzheimer type dementia. We also conducted the first genomic study on perivascular space burden, an emerging MRI-marker of cerebral small vessel disease (the main vascular contribution to dementia), identifying >20 independent genetic risk loci, a large proportion of which are already associated with PVS in the white matter at age 20. In another set of studies we contributed to identifying over 50 novel risk variants for both cortical measures (surface, volume, thickness) and subcortical brain structures. We found that heritability of subcortical brain structures tended to decrease with increasing age and observed that some genetic risk variants for subcortical volumes in older age already showed association with the same structure at age 20. The SEGWAY project also enabled important progress in characterizing subtle structural brain variations in young adults and their change across the lifespan, with a particular focus on diffusion-based imaging, these have been described in various publications. SEGWAY also provided a forum to discuss ethical aspects related to genomic and imaging studies in young adults, leading to one of the first publications describing the protocol of incidental finding management in young healthy adults on brain MRI
We have created a pioneering molecular and brain imaging database of young adults, which, combined with the extensive clinical, imaging, and socio-demographic data collected in the i-Share study, represents an exceptional resource. Cutting-edge image processing techniques are being implemented and MRI-markers have been generated. The combination of genome-wide genotyping and whole genome sequencing in a large subset provides a comprehensive assessment of all coding and noncoding genetic variants, both common and rare. Moreover, leveraging extensive brain imaging and genomic resources in older community persons, we have taken an original “lifespan” perspective, by exploring shared genetic determinants of brain structure between young and older adults. There is a crucial need to improve our understanding of the genetic basis and temporal sequence that lead from structural brain changes in early adulthood to accelerated brain aging in late life, portending an increased risk of common late-life neurological diseases, such as dementia. Indeed, no efficient strategies are currently available for the prevention of dementia, and identifying the molecular underpinnings of lifetime changes in brain structure provides invaluable information to identify novel therapeutic targets and to detect populations at highest risk of accelerated brain aging and dementia who would be most likely to benefit from early, intensive interventions. Bringing genetic association findings into clinical use, e.g. for identification of drugable molecular targets, requires multiple additional steps, including identification of the causal variant(s) and gene(s). We have set up innovative in silico bioinformatics pipelines to functionally explore identified association signals and facilitate the subsequent design of functional experiments, that we have also started conducting through complementary funding.