The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank

Background: Fluid intelligence declines with advancing age, starting in early adulthood. Within-subject declines in fluid intelligence are highly correlated with contemporaneous declines in the ability to live and function independently. To support healthy aging, the mechanisms underlying these declines need to be better understood. Methods: In this pre-registered analysis, we applied latent growth curve modelling to investigate the neural determinants of longitudinal changes in fluid intelligence across three time points in 185,317 individuals (N=9,719 two waves, N=870 three waves) from the UK Biobank (age range: 39-73 years). Results: We found a weak but significant effect of cross-sectional age on the mean fluid intelligence score, such that older individuals scored slightly lower. However, the mean longitudinal slope was positive, rather than negative, suggesting improvement across testing occasions. Despite the considerable sample size, the slope variance was non-significant, suggesting no reliable individual differences in change over time. This null-result is likely due to the nature of the cognitive test used. In a subset of individuals, we found that white matter microstructure (N=8839, as indexed by fractional anisotropy) and grey-matter volume (N=9931) in pre-defined regions-of-interest accounted for complementary and unique variance in mean fluid intelligence scores. The strongest effects were such that higher grey matter volume in the frontal pole and greater white matter microstructure in the posterior thalamic radiations were associated with higher fluid intelligence scores. Conclusions: In a large preregistered analysis, we demonstrate a weak but significant negative association between age and fluid intelligence. However, we did not observe plausible longitudinal patterns, instead observing a weak increase across testing occasions, and no significant individual differences in rates of change, likely due to the suboptimal task design. Finally, we find support for our preregistered expectation that white- and grey matter make separate contributions to individual differences in fluid intelligence beyond age.

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The neural determinants of age-related changes in fluid intelligence: a pre-registered, longitudinal analysis in UK Biobank

Wellcome Open Research ◽

10.12688/wellcomeopenres.14241.2 ◽

2018 ◽

Vol 3 ◽

pp. 38 ◽

Cited By ~ 9

Author(s):

Rogier A. Kievit ◽

Delia Fuhrmann ◽

Gesa Sophia Borgeest ◽

Ivan L. Simpson-Kent ◽

Richard N. A. Henson

Keyword(s):

Individual Differences ◽

White Matter ◽

Grey Matter ◽

Fluid Intelligence ◽

Grey Matter Volume ◽

Uk Biobank ◽

Matter Volume ◽

White Matter Microstructure ◽

The Mean ◽

Intelligence Scores

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Subcortical volume and white matter integrity abnormalities in major depressive disorder: findings from UK Biobank imaging data

10.1101/070912 ◽

2016 ◽

Author(s):

Xueyi Shen ◽

Lianne M. Reus ◽

Simon R. Cox ◽

Mark J. Adams ◽

David C. Liewald ◽

...

Keyword(s):

Major Depressive Disorder ◽

White Matter ◽

Depressive Disorder ◽

Grey Matter ◽

White Matter Integrity ◽

Grey Matter Volume ◽

Uk Biobank ◽

Imaging Data ◽

Major Depressive ◽

Matter Volume

AbstractPrevious reports of altered grey and white matter structure in Major Depressive Disorder (MDD) have been inconsistent. Recent meta-analyses have, however, reported reduced hippocampal grey matter volume in MDD and reduced white matter integrity in several brain regions. The use of different diagnostic criteria, scanners and imaging sequences may, however, obscure further anatomical differences. In this study, we tested for differences in subcortical grey matter volume (n=1157) and white matter integrity (n=1089) between depressed individuals and controls in the subset of 8590 UK Biobank Imaging study participants who had undergone depression assessments. Whilst we found no significant differences in subcortical volumes, significant reductions were found in depressed individuals versus controls in global white matter integrity, as measured by fractional anisotropy (FA) (β=-0.182, p=0.005). We also found reductions in FA in association/commissural fibres (β=-0.184, pcorrected=0.010) and thalamic radiations (β=-0.159, pcorrected=0.020). Tract-specific FA reductions were also found in the left superior longitudinal fasciculus (β=-0.194, pcorrected=0.025), superior thalamic radiation (β=-0.224, pcorrected=0.009) and forceps major (β=-0.193, pcorrected=0.025) in depression (all betas standardised). Our findings provide further evidence for disrupted white matter integrity in MDD.

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21. Alterations to white matter microstructure and grey matter volume in adult Niemann-Pick Type C

Journal of Clinical Neuroscience ◽

10.1016/j.jocn.2010.07.022 ◽

2010 ◽

Vol 17 (12) ◽

pp. 1616

Author(s):

Mark Walterfang ◽

Michael C. Fahey ◽

Patricia Desmond ◽

Amanda G. Wood ◽

Marc Seal ◽

...

Keyword(s):

White Matter ◽

Grey Matter ◽

Grey Matter Volume ◽

Matter Volume ◽

White Matter Microstructure ◽

Type C ◽

Niemann Pick

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Modelling the cascade of biomarker changes in GRN-related frontotemporal dementia

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp-2020-323541 ◽

2021 ◽

pp. jnnp-2020-323541

Author(s):

Jessica L Panman ◽

Vikram Venkatraghavan ◽

Emma L van der Ende ◽

Rebecca M E Steketee ◽

Lize C Jiskoot ◽

...

Keyword(s):

White Matter ◽

Frontotemporal Dementia ◽

Disease Severity ◽

Grey Matter ◽

Clinical Stage ◽

Data Driven ◽

Grey Matter Volume ◽

Matter Volume ◽

Mutation Carriers ◽

Individual Disease

ObjectiveProgranulin-related frontotemporal dementia (FTD-GRN) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-GRN, in a data-driven way.MethodsWe included 56 presymptomatic and 35 symptomatic GRN mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD-GRN and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes.ResultsLanguage functioning and NfL were the earliest abnormal biomarkers in FTD-GRN. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA.ConclusionDegeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-GRN, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic GRN mutation carriers at risk of conversion to the clinical stage.

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Morphological changes after cranial fractionated photon radiotherapy: localized loss of white matter and grey matter volume with increasing dose

Clinical and Translational Radiation Oncology ◽

10.1016/j.ctro.2021.08.010 ◽

2021 ◽

Author(s):

S.H.J. Nagtegaal ◽

S David ◽

E.E. van Grinsven ◽

M.J.E. van Zandvoort ◽

E. Seravalli ◽

...

Keyword(s):

White Matter ◽

Grey Matter ◽

Morphological Changes ◽

Grey Matter Volume ◽

Matter Volume ◽

Photon Radiotherapy

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Age differentiation within grey matter, white matter and between memory and white matter in an adult lifespan cohort

10.1101/148452 ◽

2017 ◽

Cited By ~ 2

Author(s):

Susanne M. M. de Mooij ◽

Richard N. A. Henson ◽

Lourens J. Waldorp ◽

Cam-CAN ◽

Rogier A. Kievit

Keyword(s):

White Matter ◽

Cognitive Functions ◽

Structural Equation ◽

Grey Matter ◽

Fluid Intelligence ◽

Cognitive Factors ◽

Equation Modeling ◽

Grey Matter Volume ◽

Adult Lifespan ◽

Age Related

AbstractIt is well-established that brain structures and cognitive functions change across the lifespan. A longstanding hypothesis called age differentiation additionally posits that the relations between cognitive functions also change with age. To date however, evidence for age-related differentiation is mixed, and no study has examined differentiation of the relationship between brain and cognition. Here we use multi-group Structural Equation Modeling and SEM Trees to study differences within and between brain and cognition across the adult lifespan (18-88 years) in a large (N>646, closely matched across sexes), population-derived sample of healthy human adults from the Cambridge Centre for Ageing and Neuroscience (www.cam-can.org). After factor analyses of grey-matter volume (from T1- and T2-weighted MRI) and white-matter organisation (fractional anisotropy from Diffusion-weighted MRI), we found evidence for differentiation of grey and white matter, such that the covariance between brain factors decreased with age. However, we found no evidence for age differentiation between fluid intelligence, language and memory, suggesting a relatively stable covariance pattern between cognitive factors. Finally, we observed a specific pattern of age differentiation between brain and cognitive factors, such that a white matter factor, which loaded most strongly on the hippocampal cingulum, became less correlated with memory performance in later life. These patterns are compatible with reorganization of cognitive functions in the face of neural decline, and/or with the emergence of specific subpopulations in old age.Significance statementThe theory of age differentiation posits age-related changes in the relationships between cognitive domains, either weakening (differentiation) or strengthening (de-differentiation), but evidence for this hypothesis is mixed. Using age-varying covariance models in a large cross-sectional adult lifespan sample, we found age-related reductions in the covariance among both brain measures (neural differentiation), but no covariance change between cognitive factors of fluid intelligence, language and memory. We also observed evidence of uncoupling (differentiation) between a white matter factor and cognitive factors in older age, most strongly for memory. Together, our findings support age-related differentiation as a complex, multifaceted pattern that differs for brain and cognition, and discuss several mechanisms that might explain the changing relationship between brain and cognition.

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Individual differences in during decision making under uncertainty: Loss aversion covaries with insular grey matter volume

Personality and Individual Differences ◽

10.1016/j.paid.2013.07.183 ◽

2014 ◽

Vol 60 ◽

pp. S10 ◽

Cited By ~ 1

Author(s):

S. Markett ◽

G. Voigt ◽

C. Montag ◽

B. Weber ◽

M. Reuter

Keyword(s):

Decision Making ◽

Individual Differences ◽

Loss Aversion ◽

Grey Matter ◽

Decision Making Under Uncertainty ◽

Grey Matter Volume ◽

Matter Volume

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Causal effect of atrial fibrillation on brain white or grey matter volume: A Mendelian randomization study

10.1101/2020.12.17.20248314 ◽

2020 ◽

Author(s):

Sehoon Park ◽

Soojin Lee ◽

Yaerim Kim ◽

Semin Cho ◽

Kwangsoo Kim ◽

...

Keyword(s):

Atrial Fibrillation ◽

White Matter ◽

Grey Matter ◽

Mendelian Randomization ◽

Brain Volume ◽

Causal Effect ◽

Grey Matter Volume ◽

Volume Loss ◽

White Matter Volume ◽

Matter Volume

AbstractBackgroundAtrial fibrillation (AF) and brain volume loss are prevalent in older individuals. Further study investigating the causal effect of AF on brain volume is warranted.MethodsThis study was a Mendelian randomization (MR) analysis. The genetic instrument for AF was constructed from a previous genome-wide association study (GWAS) meta-analysis and included 537,409 individuals of European ancestry. The outcome summary statistics for quantile-normalized white or grey matter volume measured by magnetic resonance imaging were provided by the previous GWAS of 8426 white British UK Biobank participants. The main MR method was the inverse variance weighted method, supported by sensitivity MR analysis including MR-Egger regression and the weighted median method. The causal estimates from AF to white or grey matter volume were further adjusted for effects of any stroke or ischemic stroke by multivariable MR analysis.ResultsA higher genetic predisposition for AF (one standard deviation increase) was significantly associated with lower white matter volume [beta −0.128 (−0.208, −0.048)] but not grey matter volume [beta −0.041 (−0.101, 0.018)], supported by all utilized sensitivity MR analyses. The multivariable MR analysis indicated that AF is causally linked to lower white matter volume independent of the stroke effect.ConclusionsAF is a causative factor for white matter volume loss. The effect of AF on grey matter volume was inapparent in this study. A future trial is necessary to confirm whether appropriate AF management can be helpful in preventing cerebral white matter volume loss or related brain disorders in AF patients.

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Age-specific adult rat brain MRI templates and tissue probability maps

10.31219/osf.io/htgqn ◽

2021 ◽

Cited By ~ 1

Author(s):

Eilidh MacNicol ◽

Paul Wright ◽

Eugene Kim ◽

Irene Brusini ◽

Oscar Esteban ◽

...

Keyword(s):

White Matter ◽

Rat Brain ◽

Grey Matter ◽

Brain Volume ◽

Grey Matter Volume ◽

Total Brain Volume ◽

Adult Rat ◽

Matter Volume ◽

Probability Maps ◽

Total Brain

Age-specific resources mitigate biases in human MRI processing arising from structural changes across the lifespan. There are fewer age-specific resources for preclinical imaging, and they only represent developmental periods rather than adulthood. Since rats recapitulate many facets of human aging, it was hypothesized that brain volume and each tissue’s relative contribution to total brain volume would change with age in the adult rat. However, the currently available tissue probability maps, which provide a priori information for tissue volume estimation, provide inaccurate grey matter probabilities in subcortical structures, particularly the thalamus. Consequently, age-specific templates and tissue probability maps were generated from a longitudinal study that scanned a cohort of rats at 3, 5, 11, and 17 months old. Mixed-effects models assessed the effect of age on brain, grey matter, white matter, and CSF volumes, and the relative tissue proportions. Grey and white matter volume increased with age, and the tissue proportions relative to total brain volume varied throughout adulthood. Furthermore, we present evidence of a systematic underestimation of thalamic grey matter volume with existing resources, which is mitigated with the use of age-specific tissue probability maps since the derived estimates better matched histological evidence. To reduce age-related biases in image pre-processing, a set of rat brain resources from across the adult lifespan is consequently released to expand the preclinical MRI community’s fundamental resources.

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