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Structural brain magnetic resonance imaging (MRI) traits share part of their genetic variance with cognitive traits. Here, we use genetic association results from large meta-analytic studies of genome-wide association (GWA) for brain infarcts (BI), white matter hyperintensities, intracranial, hippocampal, and total brain volumes to estimate polygenic scores for these traits in three Scottish samples: Generation Scotland: Scottish Family Health Study (GS:SFHS), and the Lothian Birth Cohorts of 1936 (LBC1936) and 1921 (LBC1921). These five brain MRI trait polygenic scores were then used to: (1) predict corresponding MRI traits in the LBC1936 (numbers ranged 573 to 630 across traits), and (2) predict cognitive traits in all three cohorts (in 8,115–8,250 persons). In the LBC1936, all MRI phenotypic traits were correlated with at least one cognitive measure, and polygenic prediction of MRI traits was observed for intracranial volume. Meta-analysis of the correlations between MRI polygenic scores and cognitive traits revealed a significant negative correlation (maximal r = 0.08) between the HV polygenic score and measures of global cognitive ability collected in childhood and in old age in the Lothian Birth Cohorts. The lack of association to a related general cognitive measure when including the GS:SFHS points to either type 1 error or the importance of using prediction samples that closely match the demographics of the GWA samples from which prediction is based. Ideally, these analyses should be repeated in larger samples with data on both MRI and cognition, and using MRI GWA results from even larger meta-analysis studies.
Variation in human cognitive ability is of consequence to a large number of health and social outcomes and is substantially heritable. Genetic linkage, genome-wide association, and copy number variant studies have investigated the contribution of genetic variation to individual differences in normal cognitive ability, but little research has considered the role of rare genetic variants. Exome sequencing studies have already met with success in discovering novel trait-gene associations for other complex traits. Here, we use exome sequencing to investigate the effects of rare variants on general cognitive ability. Unrelated Scottish individuals were selected for high scores on a general component of intelligence (g). The frequency of rare genetic variants (in n = 146) was compared with those from Scottish controls (total n = 486) who scored in the lower to middle range of the g distribution or on a proxy measure of g. Biological pathway analysis highlighted enrichment of the mitochondrial inner membrane component and apical part of cell gene ontology terms. Global burden analysis showed a greater total number of rare variants carried by high g cases versus controls, which is inconsistent with a mutation load hypothesis whereby mutations negatively affect g. The general finding of greater non-synonymous (vs. synonymous) variant effects is in line with evolutionary hypotheses for g. Given that this first sequencing study of high g was small, promising results were found, suggesting that the study of rare variants in larger samples would be worthwhile.
Background: Cognitive assessment of older persons, particularly those with impairment, is hampered by measurement error and the ethical issues of testing people with dementia. A potential source of valuable information about end-of-life cognitive status can be gained from those who knew the respondent well – mostly relatives or friends. This study tested the association between last cognitive assessment before death and a retrospective informant assessment of cognition.
Methods: Data were analyzed from 248 participants from the Medical Research Council Cognitive Function and Ageing Study who were aged 71 to 102 years at death. Late-life cognition was assessed 0 to 8 years before death using the Mini-mental State Examination (MMSE) and the informant measure was taken 0 to 7 years after death using a Retrospective Informant Interview (RInI).
Results: Zero-inflated Poisson regression showed a strong association between MMSE scores and RInI scores – those scoring 29–30 on the MMSE had a RInI score four times lower than those who scored <18 (p < 0.001). The time between MMSE and death was also a significant predictor with each additional year increasing RInI scores by 12.4% (p < 0.001). The time between death and RInI was only a significant predictor when including measures that were taken four years or more after death.
Conclusions: Cognitive scores from retrospective informant interviews are strongly associated with late-life MMSE scores taken close to death. This suggests that the RInI can be used as a proxy measure of cognition in the period leading up to death.
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