{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Ritchie SJ"],"funding":["Medical Research Council","Wellcome Trust","Biotechnology and Biological Sciences Research Council"],"pagination":["146-158"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC5759896"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["62"],"pubmed_abstract":["Fully characterizing age differences in the brain is a key task for combating aging-related cognitive decline. Using propensity score matching on 2 independent, narrow-age cohorts, we used data on childhood cognitive ability, socioeconomic background, and intracranial volume to match participants at mean age of 92 years (n = 42) to very similar participants at mean age of 73 years (n = 126). Examining a variety of global and regional structural neuroimaging variables, there were large differences in gray and white matter volumes, cortical surface area, cortical thickness, and white matter hyperintensity volume and spatial extent. In a mediation analysis, the total volume of white matter hyperintensities and total cortical surface area jointly mediated 24.9% of the relation between age and "],"journal":["Neurobiology of aging"],"pubmed_title":["Brain structural differences between 73- and 92-year olds matched for childhood intelligence, social background, and intracranial volume."],"pmcid":["PMC5759896"],"funding_grant_id":["G0701120","G1001245","MR/R024065/1","MR/N003403/1","15/SAG09977","MR/K026992/1","MR/M013111/1"],"pubmed_authors":["Gow AJ","Corley J","Dickie DA","Karama S","Maniega SM","Wardlaw JM","Ritchie SJ","Valdes Hernandez MDC","Pattie A","Anblagan D","Sibbett R","Royle NA","Deary IJ","Cox SR","Starr JM","Redmond P","Bastin ME","Taylor AM","Booth T"],"additional_accession":[]},"is_claimable":false,"name":"Brain structural differences between 73- and 92-year olds matched for childhood intelligence, social background, and intracranial volume.","description":"Fully characterizing age differences in the brain is a key task for combating aging-related cognitive decline. Using propensity score matching on 2 independent, narrow-age cohorts, we used data on childhood cognitive ability, socioeconomic background, and intracranial volume to match participants at mean age of 92 years (n = 42) to very similar participants at mean age of 73 years (n = 126). Examining a variety of global and regional structural neuroimaging variables, there were large differences in gray and white matter volumes, cortical surface area, cortical thickness, and white matter hyperintensity volume and spatial extent. In a mediation analysis, the total volume of white matter hyperintensities and total cortical surface area jointly mediated 24.9% of the relation between age and ","dates":{"release":"2018-01-01T00:00:00Z","publication":"2018 Feb","modification":"2025-04-19T02:00:34.327Z","creation":"2019-03-26T22:59:28Z"},"accession":"S-EPMC5759896","cross_references":{"pubmed":["29149632"],"doi":["10.1016/j.neurobiolaging.2017.10.005"]}}