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Study on Environmental and GenomeWide predictors of early structural brain Alterations in Young students

Periodic Reporting for period 3 - SEGWAY (Study on Environmental and GenomeWide predictors of early structural brain Alterations in Young students)

Reporting period: 2018-12-01 to 2020-05-31

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 aims 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. Replication of our findings will be sought in the multigenerational Framingham Heart Study and other independent studies. Identifying common biological mechanisms underlying both early and late-life structural brain changes would 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.
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 imputed to the latest reference panels allowing inference of genotypes at >26M sites, and whole genome sequencing in a large subset proving information on >38M single nucleotide variants and allowing to derive different types of structural variation. Additional funding has been secured to enrich the biobank with epigenetic and metabolomic markers. Several publications have already been generated describing the heritability of and novel genetic risk variants for MRI-markers of brain aging, their impact of brain structure in young adults, as well as the (causal) relation and shared genetic variation of the corresponding MRI-markers 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.

-Duperron MG, et al. Burden of Dilated Perivascular Spaces, an Emerging Marker of Cerebral Small Vessel Disease, Is Highly Heritable. Stroke 2018 PMID: 29311265
-Malik R, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet 2018 PMID: 29531354
-Chauhan G, et al. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting. Neurology 2019 PMID: 30651383
-Debette S, et al. Clinical Significance of Magnetic Resonance Imaging Markers of Vascular Brain Injury: A Systematic Review and Meta-analysis. JAMA Neurol 2019 PMID: 30422209
-Jian X, et al. Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38 for White Matter Hyperintensities on Brain Magnetic Resonance Imaging.Stroke 2018 PMID: 30002152
-Mishra A, et al. Association of variants in HTRA1 and NOTCH3 with MRI-defined extremes of cerebral small vessel disease in older subjec. Brain 2019 PMID: 30859180
-Duperron MG et al. High dilated perivascular space burden: a new MRI marker for risk of intracerebral hemorrhage.Neurobiol Aging 2019 PMDI: 31629114
-Satizabal C et al. Genetic architecture of subcortical brain structures in 38,851 individuals. Nat Genet 2019 PMID: 31636452
-Beaudet G et al. Age-Related Changes of Peak Width Skeletonized Mean Diffusivity (PSMD) Across the Adult Lifespan: A Multi-Cohort Study. Front Psychiatry 2020 PMID: 32425831
-Sargurupremraj M et al. Cerebral small vessel disease genomics: implications across the lifespan. Nat Comm 2020, accepted in principle
We are creating 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 are taking 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 could provide 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. Cognitive decline and dementia represent a major public health concern, and exploring their risk factors and mechanisms is of the utmost importance at the community level.
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.
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