JPND BRain Imaging, cognition, Dementia and next generation GEnomics
Lead Research Organisation:
University of Edinburgh
Department Name: Centre Cogn Ageing and Cogn Epidemiology
Abstract
Establishing efficient prevention strategies for dementia and Alzheimer disease (AD) is a major health priority for the coming years. An important hurdle is that pathological processes leading to AD begin many years before clinical diagnosis, hence efficient prevention should be initiated very early. This requires identifying individuals in the general population who are at high risk of developing dementia and exploring the molecular pathways underlying the structural brain alterations that precede the occurrence of dementia, an essential step for identifying novel relevant drug targets. To tackle these important questions we propose to explore the genetic and epigenetic determinants of quantitative MRI-markers of brain aging that are powerful predictors of dementia/AD risk, and to examine the clinical significance of the markers in a population-based setting. Leveraging the extensive information collected within the largest European population-based cohort studies with neuroimaging data, we will first search for genetic variants associated with established and novel MRI-markers of brain aging, focusing particularly on rare variants, using both an agnostic and candidate locus approach (loci identified through genome-wide association studies [GWAS] as associated AD or with MRI-markers of brain aging). In contrast with GWAS signals, rare variants may lead to the discovery of causal variants, and have hardly been explored in association with structural MRI-markers. Second, we will take an original lifetime perspective, through examination of samples in various age categories spanning from young adulthood to older age, many of which with repeated MRI and blood sampling. Indeed, there is increasing evidence that early-life factors play an important role in the occurrence of late-onset neurodegenerative diseases. We propose an innovative exploration of lifetime changes in methylation associated with structural brain alterations using a novel bisulfite sequencing technology, to help identify functional and disease relevant variants. We will also study the modifying effect of vascular risk factors and socio-economic status on genetic/epigenetic determinants of brain aging. Third, we will explore the clinical significance of genetic and epigenetic markers we identify by examining their association with cognitive performance, cognitive decline and risk of dementia/AD, capitalizing on the elaborate cognitive testing and prospective dementia surveillance available in all studies.
Technical Summary
we propose to explore the genetic and epigenetic determinants of quantitative MRI-markers of brain aging that are powerful predictors of dementia/AD risk, and to examine the clinical significance of the markers in a population-based setting. Leveraging the extensive information collected within the largest European population-based cohort studies with neuroimaging data, we will first search for genetic variants associated with established and novel MRI-markers of brain aging, focusing particularly on rare variants, using both an agnostic and candidate locus approach (loci identified through genome-wide association studies [GWAS] as associated AD or with MRI-markers of brain aging). In contrast with GWAS signals, rare variants may lead to the discovery of causal variants, and have hardly been explored in association with structural MRI-markers. Second, we will take an original lifetime perspective, through examination of samples in various age categories spanning from young adulthood to older age, many of which with repeated MRI and blood sampling. Indeed, there is increasing evidence that early-life factors play an important role in the occurrence of late-onset neurodegenerative diseases. We propose an innovative exploration of lifetime changes in methylation associated with structural brain alterations using a novel bisulfite sequencing technology, to help identify functional and disease relevant variants. We will also study the modifying effect of vascular risk factors and socio-economic status on genetic/epigenetic determinants of brain aging. Third, we will explore the clinical significance of genetic and epigenetic markers we identify by examining their association with cognitive performance, cognitive decline and risk of dementia/AD, capitalizing on the elaborate cognitive testing and prospective dementia surveillance available in all studies.
Planned Impact
B. Innovation
Leveraging existing brain imaging and genomic resources in multiple large population-based cohorts we plan to take an original multimodal approach to explore the genetic and epigenetic determinants of structural brain aging and their clinical significance as early predictors of cognitive decline and dementia. The diverse background and age distribution of participating cohorts will enable us to account for early life factors and lifetime changes in brain structure and epigenomic architecture.
This network gathers most large European population-based samples with high resolution brain imaging combined with extensive cognitive testing,incident dementia surveillance, and extensive and repeated assessment of clinical comorbidities and socio-economic factors. Cutting edge image processing techniques will be implemented to capture subtle changes in brain structure. We also plan to utilize innovative next generation sequencing (NGS) technology for analysis of rare variants, including a novel custom methylC-seq. capture assay to examine so far unexplored epigenomic determinants of brain aging. Innovative methods to analyze and interrogate ultra-high-dimensional data based on omics-technologies, developed by the JPND HD-READY (High-Dimensional REsearch in Alzheimer's Disease) working group, will be implemented.
C. Significance
Genetic association studies on structural brain aging have so far almost exclusively explored common single nucleotide
variants. Expanding the search to rare or low frequency variants and to epigenetic modifications, as proposed in this application, would substantially enrich our understanding of the biological mechanisms underlying early structural brain alterations that portend an increased dementia risk, and thus contribute to facilitating the discovery of novel therapeutic targets. Findings from this project may also: (i) contribute to identifying populations at higher risk of accelerated brain aging, more likely to benefit from interventions aiming at preventing dementia; (ii) help define quantitative intermediate endpoints for future clinical trials; (iii) provide useful information on the optimal timing for preventative interventions. Taken together, this project has an important potential of facilitating the development of novel preventive strategies for dementia and AD.
Leveraging existing brain imaging and genomic resources in multiple large population-based cohorts we plan to take an original multimodal approach to explore the genetic and epigenetic determinants of structural brain aging and their clinical significance as early predictors of cognitive decline and dementia. The diverse background and age distribution of participating cohorts will enable us to account for early life factors and lifetime changes in brain structure and epigenomic architecture.
This network gathers most large European population-based samples with high resolution brain imaging combined with extensive cognitive testing,incident dementia surveillance, and extensive and repeated assessment of clinical comorbidities and socio-economic factors. Cutting edge image processing techniques will be implemented to capture subtle changes in brain structure. We also plan to utilize innovative next generation sequencing (NGS) technology for analysis of rare variants, including a novel custom methylC-seq. capture assay to examine so far unexplored epigenomic determinants of brain aging. Innovative methods to analyze and interrogate ultra-high-dimensional data based on omics-technologies, developed by the JPND HD-READY (High-Dimensional REsearch in Alzheimer's Disease) working group, will be implemented.
C. Significance
Genetic association studies on structural brain aging have so far almost exclusively explored common single nucleotide
variants. Expanding the search to rare or low frequency variants and to epigenetic modifications, as proposed in this application, would substantially enrich our understanding of the biological mechanisms underlying early structural brain alterations that portend an increased dementia risk, and thus contribute to facilitating the discovery of novel therapeutic targets. Findings from this project may also: (i) contribute to identifying populations at higher risk of accelerated brain aging, more likely to benefit from interventions aiming at preventing dementia; (ii) help define quantitative intermediate endpoints for future clinical trials; (iii) provide useful information on the optimal timing for preventative interventions. Taken together, this project has an important potential of facilitating the development of novel preventive strategies for dementia and AD.
Organisations
Publications
Jia T
(2020)
Neurobehavioural characterisation and stratification of reinforcement-related behaviour.
in Nature human behaviour
Patel Y
(2019)
Maturation of the Human Cerebral Cortex During Adolescence: Myelin or Dendritic Arbor?
in Cerebral cortex (New York, N.Y. : 1991)
Prendergast JGD
(2019)
Linked Mutations at Adjacent Nucleotides Have Shaped Human Population Differentiation and Protein Evolution.
in Genome biology and evolution
Shin J
(2020)
Global and Regional Development of the Human Cerebral Cortex: Molecular Architecture and Occupational Aptitudes.
in Cerebral cortex (New York, N.Y. : 1991)
Brouwer RM
(2022)
Genetic variants associated with longitudinal changes in brain structure across the lifespan.
in Nature neuroscience
Velthorst E
(2018)
Genetic risk for schizophrenia and autism, social impairment and developmental pathways to psychosis
in Translational Psychiatry
Hofer E
(2020)
Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.
in Nature communications
Satizabal CL
(2019)
Genetic architecture of subcortical brain structures in 38,851 individuals.
in Nature genetics
Chauhan G
(2019)
Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting.
in Neurology
Description | Project grant - JPND (Deary) |
Amount | £592,325 (GBP) |
Funding ID | MR/N027558/1 |
Organisation | Medical Research Council (MRC) |
Department | MRC Human Nutrition Research Group |
Sector | Academic/University |
Country | United Kingdom |
Start | 04/2016 |
End | 04/2019 |
Title | Data from: Decreased brain connectivity in smoking contrasts with increased connectivity in drinking |
Description | In a group of 831 participants from the general population in the Human Connectome Project, smokers exhibited low overall functional connectivity, and more specifically of the lateral orbitofrontal cortex which is associated with non-reward mechanisms, the adjacent inferior frontal gyrus, and the precuneus. Participants who drank a high amount had overall increases in resting state functional connectivity, and specific increases in reward-related systems including the medial orbitofrontal cortex and the cingulate cortex. Increased impulsivity was found in smokers, associated with decreased functional connectivity of the non-reward-related lateral orbitofrontal cortex; and increased impulsivity was found in high amount drinkers, associated with increased functional connectivity of the reward-related medial orbitofrontal cortex. The main findings were cross-validated in an independent longitudinal dataset with 1176 participants, IMAGEN. Further, the functional connectivities in 14-year-old non-smokers (and also in female low-drinkers) were related to who would smoke or drink at age 19. An implication is that these differences in brain functional connectivities play a role in smoking and drinking, together with other factors. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
URL | https://datadryad.org/stash/dataset/doi:10.5061/dryad.736t01r |