scholarly journals Association of SBP and BMI with cognitive and structural brain phenotypes in UK Biobank

2020 ◽  
Vol 38 (12) ◽  
pp. 2482-2489
Author(s):  
Amy C. Ferguson ◽  
Rachana Tank ◽  
Laura M. Lyall ◽  
Joey Ward ◽  
Paul Welsh ◽  
...  
Keyword(s):  
Uk Biobank ◽  
Structural Brain

scholarly journals Structural brain imaging correlates of general intelligence in UK Biobank

Intelligence ◽  
2019 ◽  
Vol 76 ◽  
pp. 101376 ◽  
Author(s):  
S.R. Cox ◽  
S.J. Ritchie ◽  
C. Fawns-Ritchie ◽  
E.M. Tucker-Drob ◽  
I.J. Deary
Keyword(s):  
Brain Imaging ◽  
General Intelligence ◽  
Uk Biobank ◽  
Structural Brain ◽  
Structural Brain Imaging

scholarly journals Association between polygenic risk for Alzheimer’s disease, brain structure and cognitive abilities in UK Biobank.

2021 ◽  
Author(s):  
Rachana Tank ◽  
Joey Ward ◽  
Kristin E. Flegal ◽  
Daniel Smith ◽  
Mark E.S. Bailey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Fluid Intelligence ◽  
Late Onset ◽  
Brain Mri ◽  
Brain Magnetic Resonance Imaging ◽  
Healthy Adults ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Structural Brain

Background and purpose: Previous studies testing associations between polygenic risk for late-onset Alzheimer’s disease (LOAD-PGR) and brain magnetic resonance imaging (MRI) measures have been limited by small samples and inconsistent consideration of potential confounders. This study investigates whether higher LOAD-PGR is associated with differences in structural brain imaging and cognitive values in a relatively large sample of non-demented, generally healthy adults (UK Biobank). Method: Summary statistics were used to create PGR scores for n=32,790 participants using LDpred. Outcomes included 12 structural MRI volumes and 6 concurrent cognitive measures. Models were adjusted for age, sex, body mass index, genotyping chip, 8 principal components, lifetime smoking, apolipoprotein (APOE) e4 genotype and socioeconomic deprivation. We tested for statistical interactions between APOE e4 allele dose and LOAD-PGR vs. all outcomes. Results: In fully adjusted models, LOAD-PGR was associated with worse fluid intelligence (standardised beta [β] = -0.080 per LOAD-PGR standard deviation, p = 0.002), matrix completion (β = -0.102, p = 0.003), smaller left hippocampal total (β = -0.118, p = 0.002) and body (β = -0.069, p = 0.002) volumes, but not other hippocampal subdivisions. There were no significant APOE x LOAD-PGR score interactions for any outcomes in fully adjusted models. Discussion: This is the largest study to date investigating LOAD-PGR and non-demented structural brain MRI and cognition phenotypes. LOAD-PGR was associated with smaller hippocampal volumes and aspects of cognitive ability in healthy adults, and could supplement APOE status in risk stratification of cognitive impairment/LOAD.

scholarly journals Lack of evidence for interactions between APOE and Klotho genotypes on cognitive, dementia and brain imaging metrics in UK Biobank

2021 ◽  
Author(s):  
Rachana Tank ◽  
Joey Ward ◽  
Daniel J. Smith ◽  
Kristin E. Flegal ◽  
Donald M. Lyall
Keyword(s):  
Cognitive Impairment ◽  
Brain Imaging ◽  
Brain Structure ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Cognitive Test ◽  
Uk Biobank ◽  
Type 1 Error ◽  
Structural Brain

AbstractImportanceRecent research has suggested that genetic variation in the Klotho (KL) locus may modify the association between apolipoprotein e (APOE) e4 genotype and cognitive impairment.ObjectiveLarge-scale testing for associations and interactions between KL and APOE genotypes vs. risk of dementia (n=1,570 cases), cognitive abilities (n=174,513) and brain structure (n = 13,158) in older (60+ years) participants.Design, setting and participantsCross-sectional and prospective data (UK Biobank).Main outcomes and measuresKL status was indexed with heterozygosity of the rs9536314 polymorphism (vs. not), in unrelated people with vs. without APOE e4 genotype, using regression and interaction tests. We assessed non-demented cognitive scores (processing speed; reasoning; memory; executive function), multiple structural brain imaging, and clinical dementia outcomes. All tests were corrected for age, sex, assessment centre, eight principal components for population stratification, genotypic array, smoking history, deprivation, and self-reported medication history.ResultsAPOE e4 presence (vs. not) was associated with increased risk of dementia, worse cognitive abilities and brain structure differences. KL heterozygosity was associated with less frontal lobe grey matter. There were no significant APOE/KL interactions for cognitive, dementia or brain imaging measures (all P>0.05).Conclusions and relevanceWe found no evidence of APOE/KL interactions on cognitive, dementia or brain imaging outcomes. This could be due to some degree of cognitive test imprecision, generally preserved participant health potentially due to relatively young age, type-1 error in prior studies, or indicative of a significant age-dependent KL effect only in the context of marked AD pathology.Key pointsQuestion: Klotho genotype has been previously shown to ‘offset’ a substantial amount of the APOE e4/cognitive impairment association. Is this modification effect apparent in large-scale independent data, in terms of non-demented cognitive abilities, brain structure and dementia prevalence?Findings: In aged 60 years and above participants from UK Biobank, we found significant associations of APOE and Klotho genotypes on cognitive, structural brain and dementia outcomes, but no significant interactions.Meaning: This could reflect somewhat healthy participants, prior type 1 error or cognitive/dementia ascertainment imprecision, and/or that Klotho genotypic effects are age and neuropathology dependent.

scholarly journals Loneliness is linked to specific subregional alterations in hippocampus-default network co-variation

2021 ◽  
Author(s):  
Chris Zajner ◽  
R. Nathan Spreng ◽  
Danilo Bzdok
Keyword(s):  
Social Deprivation ◽  
Molecular Layer ◽  
Population Level ◽  
Social Neuroscience ◽  
Association Cortex ◽  
Default Network ◽  
White Matter Tract ◽  
Uk Biobank ◽  
Brain Scans ◽  
Structural Brain

Social interaction complexity makes humans unique. But in times of social deprivation this strength risks to expose important vulnerabilities. Human social neuroscience studies have placed a premium on the default network (DN). In contrast, hippocampus (HC) subfields have been intensely studied in rodents and monkeys. To bridge these two literatures, we here quantified how DN subregions systematically co-vary with specific HC subfields in the context of subjective social isolation (i.e., loneliness). By co-decomposition using structural brain scans of ~40,000 UK Biobank participants, loneliness was specially linked to midline subregions in the uncovered DN patterns. These association cortex signatures coincided with concomitant HC patterns implicating especially CA1 and molecular layer. These patterns also showed a strong affiliation with the fornix white-matter tract and the nucleus accumbens. In addition, separable signatures of structural HC-DN co-variation had distinct associations with the genetic predisposition for loneliness at the population level.

scholarly journals The effect of network thresholding and weighting on structural brain networks in the UK Biobank

NeuroImage ◽  
2020 ◽  
Vol 211 ◽  
pp. 116443 ◽  
Author(s):  
Colin R. Buchanan ◽  
Mark E. Bastin ◽  
Stuart J. Ritchie ◽  
David C. Liewald ◽  
James W. Madole ◽  
...  
Keyword(s):  
Brain Networks ◽  
Uk Biobank ◽  
The Uk ◽  
Structural Brain

scholarly journals Subjective social isolation is linked to subregional alterations in hippocampus-default network co-variation

2021 ◽  
Author(s):  
Chris Zajner ◽  
Robert Nathan Spreng ◽  
Danilo Bzdok
Keyword(s):  
Social Isolation ◽  
Social Deprivation ◽  
Molecular Layer ◽  
Population Level ◽  
Social Neuroscience ◽  
Association Cortex ◽  
Default Network ◽  
Uk Biobank ◽  
Brain Scans ◽  
Structural Brain

Social interaction complexity makes humans unique. But in times of social deprivation this strength risks to expose important vulnerabilities. Human social neuroscience studies have placed a premium on the default network (DN). In contrast, hippocampus (HC) subfields have been intensely studied in rodents and monkeys. To bridge these two literatures, we here quantified how DN subregions systematically co-vary with specific HC subfields in the context of subjective social isolation (i.e., loneliness). By co-decomposition using structural brain scans of ~40,000 UK Biobank participants, loneliness was specially linked to midline subregions in the uncovered DN patterns. These association cortex signatures coincided with concomitant HC patterns implicating especially CA1 and molecular layer. These patterns also showed a strong affiliation with the fornix white-matter tract and the nucleus accumbens. In addition, separable signatures of structural HC-DN co-variation had distinct associations with the genetic predisposition for loneliness at the population level.

scholarly journals Association between polygenic risk for Alzheimer’s disease, brain structure and cognitive abilities in UK Biobank

2021 ◽  
Author(s):  
Rachana Tank ◽  
Joey Ward ◽  
Kristin E. Flegal ◽  
Daniel J. Smith ◽  
Mark E. S. Bailey ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Fluid Intelligence ◽  
Late Onset ◽  
Brain Mri ◽  
Brain Magnetic Resonance Imaging ◽  
Healthy Adults ◽  
Uk Biobank ◽  
Polygenic Risk ◽  
Structural Brain

AbstractPrevious studies testing associations between polygenic risk for late-onset Alzheimer’s disease (LOAD-PGR) and brain magnetic resonance imaging (MRI) measures have been limited by small samples and inconsistent consideration of potential confounders. This study investigates whether higher LOAD-PGR is associated with differences in structural brain imaging and cognitive values in a relatively large sample of non-demented, generally healthy adults (UK Biobank). Summary statistics were used to create PGR scores for n = 32,790 participants using LDpred. Outcomes included 12 structural MRI volumes and 6 concurrent cognitive measures. Models were adjusted for age, sex, body mass index, genotyping chip, 8 genetic principal components, lifetime smoking, apolipoprotein (APOE) e4 genotype and socioeconomic deprivation. We tested for statistical interactions between APOE e4 allele dose and LOAD-PGR vs. all outcomes. In fully adjusted models, LOAD-PGR was associated with worse fluid intelligence (standardised beta [β] = −0.080 per LOAD-PGR standard deviation, p = 0.002), matrix completion (β = −0.102, p = 0.003), smaller left hippocampal total (β = −0.118, p = 0.002) and body (β = −0.069, p = 0.002) volumes, but not other hippocampal subdivisions. There were no significant APOE x LOAD-PGR score interactions for any outcomes in fully adjusted models. This is the largest study to date investigating LOAD-PGR and non-demented structural brain MRI and cognition phenotypes. LOAD-PGR was associated with smaller hippocampal volumes and aspects of cognitive ability in healthy adults and could supplement APOE status in risk stratification of cognitive impairment/LOAD.

The Relationship Between Glycaemia, Cognitive Function, Structural Brain Outcomes and Dementia: A Mendelian Randomisation Study in the UK Biobank

Diabetes ◽  
2021 ◽  
pp. db200895
Author(s):  
Victoria Garfield ◽  
Aliki-Eleni Farmaki ◽  
Ghazaleh Fatemifar ◽  
Sophie V. Eastwood ◽  
Rohini Mathur ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
The Uk ◽  
The Relationship ◽  
Structural Brain

scholarly journals The effect of network thresholding and weighting on structural brain networks in the UK Biobank

2019 ◽  
Author(s):  
Colin R. Buchanan ◽  
Mark E. Bastin ◽  
Stuart J. Ritchie ◽  
David C. Liewald ◽  
James Madole ◽  
...  
Keyword(s):  
White Matter ◽  
Mean Diffusivity ◽  
Clustering Coefficient ◽  
Uk Biobank ◽  
Whole Brain ◽  
Threshold Levels ◽  
Network Measures ◽  
Structural Networks ◽  
The Uk ◽  
Structural Brain

AbstractWhole-brain structural networks can be constructed using diffusion MRI and probabilistic tractography. However, measurement noise and the probabilistic nature of the tracking procedure result in an unknown proportion of spurious white matter connections. Faithful disentanglement of spurious and genuine connections is hindered by a lack of comprehensive anatomical information at the network-level. Therefore, network thresholding methods are widely used to remove ostensibly false connections, but it is not yet clear how different thresholding strategies affect basic network properties and their associations with meaningful demographic variables, such as age. In a sample of 3,153 generally healthy volunteers from the UK Biobank Imaging Study (aged 44—77 years), we constructed 85 × 85 node whole-brain structural networks and applied two principled network thresholding approaches (consistency and proportional thresholding). These were applied over a broad range of threshold levels across six alternative network weightings (streamline count, fractional anisotropy, mean diffusivity and three novel weightings from neurite orientation dispersion and density imaging) and for four common network measures (mean edge weight, characteristic path length, network efficiency and network clustering coefficient). We compared network measures against age associations and found that the most commonly-used level of proportional-thresholding from the literature (retaining 68.7% of all possible connections) yielded significantly weaker age-associations (0.070 ≤ |β| ≤ 0.406) than the consistency-based approach which retained only 30% of connections (0.140 ≤ |β| ≤ 0.409). However, we determined that the stringency of the threshold was a stronger determinant of the network-age association than the choice of threshold method and the two thresholding approaches identified a highly overlapping set of connections (ICC = 0.84) when matched at a plausible level of network sparsity (70%). Generally, more stringent thresholding resulted in more age-sensitive network measures in five of the six network weightings, except at the highest levels of sparsity (>90%), where crucial connections were then removed. At two commonly-used threshold levels, the age-associations of the connections that were discarded (mean β ≤ |0.068|) were significantly smaller in magnitude than the corresponding age-associations of the connections that were retained (mean β ≤ |0.219|, p < 0.001, uncorrected). Given histological evidence of widespread degeneration of structural brain connectivity with increasing age, these results indicate that stringent thresholding methods may be most accurate in identifying true white matter connections.

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