Summary
Our ability to read is a must to navigate our current society, and despite the large variability in skill within the general population, it is often taken for granted. This project aims to help elucidate the mechanisms from genes to reading behaviour, by identifying anatomical brain imaging markers correlated to reading ability using an automated pipeline that can be used in the context of large imaging genetic datasets. We need to systematically characterise how reading expertise is reflected in the brain in order to be able to ask questions about its genetics underpinnings in large datasets without behavioural reading measures. We need to identify small genetic effects that additively contribute to the ready-to-read brain because it will pinpoint to relevant biological pathways that are the substrate of reading ability. We need to understand the extend to which the same genetic markers influence reading and its brain correlates, and whether genetic influences on reading performance are mediated through brain morphology, to help discern between different risk profiles for reading difficulties.
BIG READING integrates behavioural, brain imaging and genome-wide data in automated scalable pipelines to gain a deeper understanding of the link between genes and reading behaviour. I will analyse structural imaging markers correlated to reading-related traits in deeply phenotyped datasets of the general population to systematically characterise how reading expertise is reflected in the brain. I will perform heritability and genome-wide association scans in datasets with tens of thousands of participants to identify small genetic effects that additively contribute to the ready-to-read brain. I will perform genetic overlap analyses to define the extend of shared influence of genes on reading and its brain correlates and use genes as instruments to make causal inferences between brain markers and reading ability. This project will provide a foundation for future studies on how
BIG READING integrates behavioural, brain imaging and genome-wide data in automated scalable pipelines to gain a deeper understanding of the link between genes and reading behaviour. I will analyse structural imaging markers correlated to reading-related traits in deeply phenotyped datasets of the general population to systematically characterise how reading expertise is reflected in the brain. I will perform heritability and genome-wide association scans in datasets with tens of thousands of participants to identify small genetic effects that additively contribute to the ready-to-read brain. I will perform genetic overlap analyses to define the extend of shared influence of genes on reading and its brain correlates and use genes as instruments to make causal inferences between brain markers and reading ability. This project will provide a foundation for future studies on how
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| Web resources: | https://cordis.europa.eu/project/id/101027016 |
| Start date: | 01-09-2022 |
| End date: | 31-08-2024 |
| Total budget - Public funding: | 172 932,48 Euro - 172 932,00 Euro |
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Original description
Our ability to read is a must to navigate our current society, and despite the large variability in skill within the general population, it is often taken for granted. This project aims to help elucidate the mechanisms from genes to reading behaviour, by identifying anatomical brain imaging markers correlated to reading ability using an automated pipeline that can be used in the context of large imaging genetic datasets. We need to systematically characterise how reading expertise is reflected in the brain in order to be able to ask questions about its genetics underpinnings in large datasets without behavioural reading measures. We need to identify small genetic effects that additively contribute to the ready-to-read brain because it will pinpoint to relevant biological pathways that are the substrate of reading ability. We need to understand the extend to which the same genetic markers influence reading and its brain correlates, and whether genetic influences on reading performance are mediated through brain morphology, to help discern between different risk profiles for reading difficulties.BIG READING integrates behavioural, brain imaging and genome-wide data in automated scalable pipelines to gain a deeper understanding of the link between genes and reading behaviour. I will analyse structural imaging markers correlated to reading-related traits in deeply phenotyped datasets of the general population to systematically characterise how reading expertise is reflected in the brain. I will perform heritability and genome-wide association scans in datasets with tens of thousands of participants to identify small genetic effects that additively contribute to the ready-to-read brain. I will perform genetic overlap analyses to define the extend of shared influence of genes on reading and its brain correlates and use genes as instruments to make causal inferences between brain markers and reading ability. This project will provide a foundation for future studies on how
Status
SIGNEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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