Brain aging, cognition in youth and old age and vascular disease in the Lothian Birth Cohort 1936: rationale, design and methodology of the imaging protocol

The Advanced BRain Imaging on ageing and Memory (ABRIM) data collection: Study design, data processing, and rationale

To understand the neurocognitive mechanisms that underlie heterogeneity in cognitive ageing, recent scientific efforts have led to a growing public availability of imaging cohort data. The Advanced BRain Imaging on ageing and Memory (ABRIM) project aims to add to these existing datasets by taking an adult lifespan approach to provide a cross-sectional, normative database with a particular focus on connectivity, myelinization and iron content of the brain in concurrence with cognitive functioning, mechanisms of reserve, and sleep-wake rhythms. ABRIM freely shares MRI and behavioural data from 295 participants between 18-80 years, stratified by age decade and sex (median age 52, IQR 36-66, 53.20% females). The ABRIM MRI collection consists of both the raw and pre-processed structural and functional MRI data to facilitate data usage among both expert and non-expert users. The ABRIM behavioural collection includes measures of cognitive functioning (i.e., global cognition, processing speed, executive functions, and memory), proxy measures of cognitive reserve (e.g., educational attainment, verbal intelligence, and occupational complexity), and various self-reported questionnaires (e.g., on depressive symptoms, pain, and the use of memory strategies in daily life and during a memory task). In a sub-sample (n = 120), we recorded sleep-wake rhythms using an actigraphy device (Actiwatch 2, Philips Respironics) for a period of 7 consecutive days. Here, we provide an in-depth description of our study protocol, pre-processing pipelines, and data availability. ABRIM provides a cross-sectional database on healthy participants throughout the adult lifespan, including numerous parameters relevant to improve our understanding of cognitive ageing. Therefore, ABRIM enables researchers to model the advanced imaging parameters and cognitive topologies as a function of age, identify the normal range of values of such parameters, and to further investigate the diverse mechanisms of reserve and resilience.

Differential risk factor profile and neuroimaging markers of small vessel disease between lacunar ischemic stroke and deep intracerebral hemorrhage

Background

Lacunar ischemic stroke (LIS) and deep intracerebral hemorrhage (dICH) are two stroke phenotypes of deep perforator arteriopathy. It is unclear what factors predispose individuals with deep perforator arteriopathy to either ischemic or hemorrhagic events.

Objectives

We aimed to investigate risk factors and neuroimaging features of small vessel disease (SVD) associated with LIS versus dICH in a cross-sectional study.

Methods

We included patients with clinically presenting, magnetic resonance imaging-confirmed LIS or dICH from two tertiary hospitals between 2010 and 2021. We recorded vascular risk factors and SVD markers, including lacunes, white matter hyperintensities (WMH), perivascular spaces (PVS), and cerebral microbleeds (CMB). Logistic regression modeling was used to determine the association between vascular risk factors, SVD markers, and stroke phenotype. We further created WMH probability maps to compare WMH distribution between LIS and dICH.

Results

A total of 834 patients with LIS (mean age 61.7 ± 12.1 years) and 405 with dICH (57.7 ± 13.2 years) were included. Hypertension was equally frequent between LIS and dICH (72.3% versus 74.8%, p = 0.349). Diabetes mellitus, hyperlipidemia, smoking, and prior ischemic stroke were more associated with LIS [odds ratio (OR) (95% confidence interval (CI)), 0.35 (0.25-0.48), 0.32 (0.22-0.44), 0.31 (0.22-0.44), and 0.38 (0.18-0.75)]. Alcohol intake and prior ICH were more associated with dICH [OR (95% CI), 2.34 (1.68-3.28), 2.53 (1.31-4.92)]. Lacunes were more prevalent in LIS [OR (95% CI) 0.23 (0.11-0.43)], while moderate-to-severe basal-ganglia PVS and CMB were more prevalent in dICH [OR (95% CI) 2.63 (1.35-5.27), 4.95 (2.71-9.42)]. WMH burden and spatial distribution did not differ between groups.

Conclusion

The microangiopathy underlying LIS and dICH reflects distinct risk profiles and SVD features, hence possibly SVD subtype susceptibility. Prospective studies with careful phenotyping and genetics are needed to clarify the mechanisms underlying this difference.

Life-course neighbourhood deprivation and brain structure in older adults: the Lothian Birth Cohort 1936

Neighbourhood disadvantage may be associated with brain health but the importance of exposure at different stages of the life course is poorly understood. Utilising the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and local neuroimaging measures at age 73. A total of 689 participants had at least one valid brain measures (53% male); to maximise the sample size structural equation models with full information maximum likelihood were conducted. Residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (β = -0.06; SE = 0.02; sample size[N] = 658; number of pairwise complete observations[n]=390), grey matter (β = -0.11; SE = 0.03; N = 658; n = 390), and normal-appearing white matter volumes (β = -0.07; SE = 0.03; N = 658; n = 390), thinner cortex (β = -0.14; SE = 0.06; N = 636; n = 379), and lower general white matter fractional anisotropy (β = -0.19; SE = 0.06; N = 665; n = 388). We also found some evidence on the accumulating impact of neighbourhood deprivation from birth to late adulthood on age 73 total brain (β = -0.06; SE = 0.02; N = 658; n = 276) and grey matter volumes (β = -0.10; SE = 0.04; N = 658; n = 276). Local analysis identified affected focal cortical areas and specific white matter tracts. Among individuals belonging to lower social classes, the brain-neighbourhood associations were particularly strong, with the impact of neighbourhood deprivation on total brain and grey matter volumes, and general white matter fractional anisotropy accumulating across the life course. Our findings suggest that living in deprived neighbourhoods across the life course, but especially in mid- to late adulthood, is associated with adverse brain morphologies, with lower social class amplifying the vulnerability.

Epigenetic scores of blood-based proteins as biomarkers of general cognitive function and brain health

BACKGROUND

Epigenetic Scores (EpiScores) for blood protein levels have been associated with disease outcomes and measures of brain health, highlighting their potential usefulness as clinical biomarkers. They are typically derived via penalised regression, whereby a linear weighted sum of DNA methylation (DNAm) levels at CpG sites are predictive of protein levels. Here, we examine 84 previously published protein EpiScores as possible biomarkers of cross-sectional and longitudinal measures of general cognitive function and brain health, and incident dementia across three independent cohorts.

RESULTS

Using 84 protein EpiScores as candidate biomarkers, associations with general cognitive function (both cross-sectionally and longitudinally) were tested in three independent cohorts: Generation Scotland (GS), and the Lothian Birth Cohorts of 1921 and 1936 (LBC1921 and LBC1936, respectively). A meta-analysis of general cognitive functioning results in all three cohorts identified 18 EpiScore associations (absolute meta-analytic standardised estimates ranged from 0.03 to 0.14, median of 0.04, PFDR < 0.05). Several associations were also observed between EpiScores and global brain volumetric measures in the LBC1936. An EpiScore for the S100A9 protein (a known Alzheimer disease biomarker) was associated with general cognitive functioning (meta-analytic standardised beta: - 0.06, P = 1.3 × 10-9), and with time-to-dementia in GS (Hazard ratio 1.24, 95% confidence interval 1.08-1.44, P = 0.003), but not in LBC1936 (Hazard ratio 1.11, P = 0.32).

CONCLUSIONS

EpiScores might make a contribution to the risk profile of poor general cognitive function and global brain health, and risk of dementia, however these scores require replication in further studies.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

Blood pressure variability, central autonomic network dysfunction and cerebral small vessel disease in APOE4 carriers

Background

Increased blood pressure variability (BPV) is a risk factor for cerebral small vessel disease (CSVD) and neurodegeneration, independent of age and average blood pressure, particularly in apolipoprotein E4 (APOE4) carriers. However, it remains uncertain whether BPV elevation is a cause or a consequence of vascular brain injury, or to what degree injury to the central autonomic network (CAN) may contribute to BPV-associated risk in APOE4 carriers.

Methods

Independently living older adults (n=70) with no history of stroke or dementia were recruited from the community and underwent 5 minutes of resting beat-to-beat blood pressure monitoring, genetic testing, and brain MRI. Resting BPV, APOE genotype, CSVD burden on brain MRI, and resting state CAN connectivity by fMRI were analyzed. Causal mediation and moderation analysis evaluated BPV and CAN effects on CSVD in APOE4 carriers (n=37) and non-carriers (n=33).

Results

Higher BPV was associated with the presence and extent of CSVD in APOE4 carriers, but not non-carriers, independent of CAN connectivity (B= 18.92, P= .02), and CAN connectivity did not mediate the relationship between BPV and CSVD. In APOE4 carriers, CAN connectivity moderated the relationship between BPV and CSVD, whereby BPV effects on CSVD were greater in those with lower CAN connectivity (B= 36.43, P= .02).

Conclusions

Older APOE4 carriers with higher beat-to-beat BPV exhibit more extensive CSVD, independent of average blood pressure, and the strength of CAN connectivity does not mediate these effects. Findings suggest increased BPV is more likely a cause, not a consequence, of CSVD. BPV is more strongly associated with CSVD in APOE4 carriers with lower rsCAN connectivity, suggesting CAN dysfunction and BPV elevation may have synergistic effects on CSVD. Further studies are warranted to understand the interplay between BPV and CAN function in APOE4 carriers.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

Sleep quality, perivascular spaces and brain health markers in ageing - A longitudinal study in the Lothian Birth Cohort 1936

BACKGROUND

Sleep is thought to play a major role in brain health and general wellbeing. However, few longitudinal studies have explored the relationship between sleep habits and imaging markers of brain health, particularly markers of brain waste clearance such as perivascular spaces (PVS), of neurodegeneration such as brain atrophy, and of vascular disease, such as white matter hyperintensities (WMH). We explore these associations using data collected over 6 years from a birth cohort of older community-dwelling adults in their 70s.

METHOD

We analysed brain MRI data from ages 73, 76 and 79 years, and self-reported sleep duration, sleep quality and vascular risk factors from community-dwelling participants in the Lothian Birth Cohort 1936 (LBC1936) study. We calculated sleep efficiency (at age 76), quantified PVS burden (at age 73), and WMH and brain volumes (age 73 to 79), calculated the white matter damage metric, and used structural equation modelling (SEM) to explore associations and potential causative pathways between indicators related to brain waste cleaning (i.e., sleep and PVS burden), brain and WMH volume changes during the 8th decade of life.

RESULTS

Lower sleep efficiency was associated with a reduction in normal-appearing white matter (NAWM) volume (β = 0.204, P = 0.009) from ages 73 to 79, but not concurrent volume (i.e. age 76). Increased daytime sleep correlated with less night-time sleep (r = -0.20, P < 0.001), and with increasing white matter damage metric (β = -0.122, P = 0.018) and faster WMH growth (β = 0.116, P = 0.026). Shorter night-time sleep duration was associated with steeper 6-year reduction of NAWM volumes (β = 0.160, P = 0.011). High burden of PVS at age 73 (volume, count, and visual scores), was associated with faster deterioration in white matter: reduction of NAWM volume (β = -0.16, P = 0.012) and increasing white matter damage metric (β = 0.37, P < 0.001) between ages 73 and 79. On SEM, centrum semiovale PVS burden mediated 5% of the associations between sleep parameters and brain changes.

CONCLUSION

Sleep impairments, and higher PVS burden, a marker of impaired waste clearance, were associated with faster loss of healthy white matter and increasing WMH in the 8th decade of life. A small percentage of the effect of sleep in white matter health was mediated by the burden of PVS consistent with the proposed role for sleep in brain waste clearance.

Life-course neighbourhood deprivation and brain structure in older adults: The Lothian Birth Cohort 1936

Neighbourhood disadvantage may be associated with brain health but the importance at different stages of the life course is poorly understood. Utilizing the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and regional neuroimaging measures at age 73. We found that residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (β=-0.06; SE=0.02; n=390) and grey matter volume (β=-0.11; SE=0.03; n=390), thinner cortex (β=-0.15; SE=0.06; n=379), and lower general white matter fractional anisotropy (β=-0.19; SE=0.06; n=388). Regional analysis identified affected focal cortical areas and specific white matter tracts. Among individuals belonging to lower occupational social classes, the brain-neighbourhood associations were stronger, with the impact of neighbourhood deprivation accumulating across the life course. Our findings suggest that living in deprived neighbourhoods is associated with adverse brain morphologies, with occupational social class adding to the vulnerability.

Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.

Assessment of perivascular space filtering methods using a three-dimensional computational model

Growing interest surrounds the assessment of perivascular spaces (PVS) on magnetic resonance imaging (MRI) and their validation as a clinical biomarker of adverse brain health. Nonetheless, the limits of validity of current state-of-the-art segmentation methods are still unclear. Here, we propose an open-source three-dimensional computational framework comprising 3D digital reference objects and evaluate the performance of three PVS filtering methods under various spatiotemporal imaging considerations (including sampling, motion artefacts, and Rician noise). Specifically, we study the performance of the Frangi, Jerman and RORPO filters in enhancing PVS-like structures to facilitate segmentation. Our findings were three-fold. First, as long as voxels are isotropic, RORPO outperforms the other two filters, regardless of imaging quality. Unlike the Frangi and Jerman filters, RORPO's performance does not deteriorate as PVS volume increases. Second, the performance of all "vesselness" filters is heavily influenced by imaging quality, with sampling and motion artefacts being the most damaging for these types of analyses. Third, none of the filters can distinguish PVS from other hyperintense structures (e.g. white matter hyperintensities, stroke lesions, or lacunes) effectively, the area under precision-recall curve dropped substantially (Frangi: from 94.21 [IQR 91.60, 96.16] to 43.76 [IQR 25.19, 63.38]; Jerman: from 94.51 [IQR 91.90, 95.37] to 58.00 [IQR 35.68, 64.87]; RORPO: from 98.72 [IQR 95.37, 98.96] to 71.87 [IQR 57.21, 76.63] without and with other hyperintense structures, respectively). The use of our computational model enables comparing segmentation methods and identifying their advantages and disadvantages, thereby providing means for testing and optimising pipelines for ongoing and future studies.

Deep attention super-resolution of brain magnetic resonance images acquired under clinical protocols

Vast quantities of Magnetic Resonance Images (MRI) are routinely acquired in clinical practice but, to speed up acquisition, these scans are typically of a quality that is sufficient for clinical diagnosis but sub-optimal for large-scale precision medicine, computational diagnostics, and large-scale neuroimaging collaborative research. Here, we present a critic-guided framework to upsample low-resolution (often 2D) MRI full scans to help overcome these limitations. We incorporate feature-importance and self-attention methods into our model to improve the interpretability of this study. We evaluate our framework on paired low- and high-resolution brain MRI structural full scans (i.e., T1-, T2-weighted, and FLAIR sequences are simultaneously input) obtained in clinical and research settings from scanners manufactured by Siemens, Phillips, and GE. We show that the upsampled MRIs are qualitatively faithful to the ground-truth high-quality scans (PSNR = 35.39; MAE = 3.78E−3; NMSE = 4.32E−10; SSIM = 0.9852; mean normal-appearing gray/white matter ratio intensity differences ranging from 0.0363 to 0.0784 for FLAIR, from 0.0010 to 0.0138 for T1-weighted and from 0.0156 to 0.074 for T2-weighted sequences). The automatic raw segmentation of tissues and lesions using the super-resolved images has fewer false positives and higher accuracy than those obtained from interpolated images in protocols represented with more than three sets in the training sample, making our approach a strong candidate for practical application in clinical and collaborative research.

Topological relationships between perivascular spaces and progression of white matter hyperintensities: A pilot study in a sample of the Lothian Birth Cohort 1936

Enlarged perivascular spaces (PVS) and white matter hyperintensities (WMH) are features of cerebral small vessel disease which can be seen in brain magnetic resonance imaging (MRI). Given the associations and proposed mechanistic link between PVS and WMH, they are hypothesized to also have topological proximity. However, this and the influence of their spatial proximity on WMH progression are unknown. We analyzed longitudinal MRI data from 29 out of 32 participants (mean age at baseline = 71.9 years) in a longitudinal study of cognitive aging, from three waves of data collection at 3-year intervals, alongside semi-automatic segmentation masks for PVS and WMH, to assess relationships. The majority of deep WMH clusters were found adjacent to or enclosing PVS (waves-1: 77%; 2: 76%; 3: 69%), especially in frontal, parietal, and temporal regions. Of the WMH clusters in the deep white matter that increased between waves, most increased around PVS (waves-1-2: 73%; 2-3: 72%). Formal statistical comparisons of severity of each of these two SVD markers yielded no associations between deep WMH progression and PVS proximity. These findings may suggest some deep WMH clusters may form and grow around PVS, possibly reflecting the consequences of impaired interstitial fluid drainage via PVS. The utility of these relationships as predictors of WMH progression remains unclear.

Circulating Metabolome and White Matter Hyperintensities in Women and Men

BACKGROUND

White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites.

METHODS

We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted P values (PFDR)<0.05 were considered significant.

RESULTS

In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH (PFDR<0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men (PFDR.full.adj=1.40×10-7) and in both the pooled sample (PFDR.full.adj=1.66×10-4) and statin-untreated (PFDR.full.adj=1.65×10-6) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate (PFDR=0.047).

CONCLUSIONS

Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain a sizable proportion of WMH variance.

Cohort profile for the STratifying Resilience and Depression Longitudinally (STRADL) study: A depression-focused investigation of Generation Scotland, using detailed clinical, cognitive, and neuroimaging assessments

STratifying Resilience and Depression Longitudinally (STRADL) is a population-based study built on the Generation Scotland: Scottish Family Health Study (GS:SFHS) resource. The aim of STRADL is to subtype major depressive disorder (MDD) on the basis of its aetiology, using detailed clinical, cognitive, and brain imaging assessments. The GS:SFHS provides an important opportunity to study complex gene-environment interactions, incorporating linkage to existing datasets and inclusion of early-life variables for two longitudinal birth cohorts. Specifically, data collection in STRADL included: socio-economic and lifestyle variables; physical measures; questionnaire data that assesses resilience, early-life adversity, personality, psychological health, and lifetime history of mood disorder; laboratory samples; cognitive tests; and brain magnetic resonance imaging. Some of the questionnaire and cognitive data were first assessed at the GS:SFHS baseline assessment between 2006-2011, thus providing longitudinal measures relevant to the study of depression, psychological resilience, and cognition. In addition, routinely collected historic NHS data and early-life variables are linked to STRADL data, further providing opportunities for longitudinal analysis. Recruitment has been completed and we consented and tested 1,188 participants.

Blood-based epigenome-wide analyses of cognitive abilities

BACKGROUND

Blood-based markers of cognitive functioning might provide an accessible way to track neurodegeneration years prior to clinical manifestation of cognitive impairment and dementia.

RESULTS

Using blood-based epigenome-wide analyses of general cognitive function, we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in general cognitive function (g). A DNAm predictor explains ~4% of the variance, independently of a polygenic score, in two external cohorts. It also associates with circulating levels of neurology- and inflammation-related proteins, global brain imaging metrics, and regional cortical volumes.

CONCLUSIONS

As sample sizes increase, the ability to assess cognitive function from DNAm data may be informative in settings where cognitive testing is unreliable or unavailable.

Contribution of white matter hyperintensities to ventricular enlargement in older adults

Lateral ventricles might increase due to generalized tissue loss related to brain atrophy. Alternatively, they may expand into areas of tissue loss related to white matter hyperintensities (WMH). We assessed longitudinal associations between lateral ventricle and WMH volumes, accounting for total brain volume, blood pressure, history of stroke, cardiovascular disease, diabetes and smoking at ages 73, 76 and 79, in participants from the Lothian Birth Cohort 1936, including MRI data from all available time points. Lateral ventricle volume increased steadily with age, WMH volume change was more variable. WMH volume decreased in 20% and increased in remaining subjects. Over 6 years, lateral ventricle volume increased by 3% per year of age, 0.1% per mm Hg increase in blood pressure, 3.2% per 1% decrease of total brain volume, and 4.5% per 1% increase of WMH volume. Over time, lateral ventricle volumes were 19% smaller in women than men. Ventricular and WMH volume changes are modestly associated and independent of general brain atrophy, suggesting that their underlying processes do not fully overlap.

Mediterranean-Type Diet and Brain Structural Change from 73 to 79 Years in the Lothian Birth Cohort 1936

OBJECTIVES

To test whether Mediterranean-type Diet (MeDi) at age 70 years is associated with longitudinal trajectories of total brain MRI volume over a six-year period from age 73 to 79.

DESIGN

Cohort study which uses a correlational design.

SETTING

Participants residing in the Lothian region of Scotland and living independently in the community.

PARTICIPANTS

A relatively healthy Scottish sample drawn from the Lothian Birth Cohort 1936.

MEASUREMENTS

Total brain volume measurements were available at ages 73, 76 and 79 (N ranged 332 to 563). Adherence to the MeDi was based on food frequency questionnaire data collected three years before the baseline imaging scans, and was used in growth curve models to predict the trajectory of total brain volume change.

RESULTS

No association was found (p>.05) between adherence to the MeDi at age 70 and total brain volume change from 73 to 79 years in minimally-adjusted (sex) or fully adjusted models controlling for additional health confounders.

CONCLUSIONS

Variation in adherence to the MeDi was not predictive of total brain atrophy over a six-year period. This suggests that previous findings of dietary associations with brain volume are not long lasting or become less important as ageing-related conditions account for greater variation in brain volume change. More frequent collection of dietary intake data is needed to clarify these findings.

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

DNA Methylation and Protein Markers of Chronic Inflammation and Their Associations With Brain and Cognitive Aging

BACKGROUND AND OBJECTIVES

To investigate chronic inflammation in relation to cognitive aging by comparison of an epigenetic and serum biomarker of C-reactive protein and their associations with neuroimaging and cognitive outcomes.

METHODS

At baseline, participants (n = 521) were cognitively normal, around 73 years of age (mean 72.4, SD 0.716), and had inflammation, vascular risk (cardiovascular disease history, hypertension, diabetes, smoking, alcohol consumption, body mass index), and neuroimaging (structural and diffusion MRI) data available. Baseline inflammatory status was quantified by a traditional measure of peripheral inflammation-serum C-reactive protein (CRP)-and an epigenetic measure (DNA methylation [DNAm] signature of CRP). Linear models were used to examine the inflammation-brain health associations; mediation analyses were performed to interrogate the relationship between chronic inflammation, brain structure, and cognitive functioning.

RESULTS

We demonstrate that DNAm CRP shows significantly (on average 6.4-fold) stronger associations with brain health outcomes than serum CRP. DNAm CRP is associated with total brain volume (β = -0.197, 95% confidence interval [CI] -0.28 to -0.12, p _FDR = 8.42 × 10^-6), gray matter volume (β = -0.200, 95% CI -0.28 to -0.12, p _FDR = 1.66 × 10^-5), and white matter volume (β = -0.150, 95% CI -0.23 to -0.07, p _FDR = 0.001) and regional brain atrophy. We also find that DNAm CRP has an inverse association with global and domain-specific (speed, visuospatial, and memory) cognitive functioning and that brain structure partially mediates this CRP-cognitive association (up to 29.7%), dependent on lifestyle and health factors.

DISCUSSION

These results support the hypothesis that chronic inflammation may contribute to neurodegenerative brain changes that underlie differences in cognitive ability in later life and highlight the potential of DNAm proxies for indexing chronic inflammatory status.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that a DNAm signature of CRP levels is more strongly associated with brain health outcomes than serum CRP levels.

Associations between total MRI-visible small vessel disease burden and domain-specific cognitive abilities in a community-dwelling older-age cohort

Cerebral small vessel disease (SVD) is a leading cause of vascular cognitive impairment, however the precise nature of SVD-related cognitive deficits, and their associations with structural brain changes, remain unclear. We combined computational volumes and visually-rated MRI markers of SVD to quantify total SVD burden, using data from the Lothian Birth Cohort 1936 (n = 540; age: 72.6 ± 0.7 years). We found negative associations between total SVD burden and general cognitive ability (standardized β: -0.363; 95%CI: [-0.49, -0.23]; p(FDR) < 0.001), processing speed (-0.371 [-0.50, -0.24]; p(FDR) < 0.001), verbal memory (-0.265; [-0.42, -0.11]; p(FDR) = 0.002), and visuospatial ability (-0.170; [-0.32, -0.02]; p(FDR) = 0.029). Only the association between SVD burden and processing speed remained after accounting for covariance with general cognitive ability (-0.325; [-0.61, -0.04]; p(FDR) = 0.029). This suggests that SVD's association with poorer processing speed is not driven by, but is independent of its association with poorer general cognitive ability. Tests of processing speed may be particularly sensitive to the cognitive impact of SVD, but all major cognitive domains should be tested to determine the full range of SVD-related cognitive characteristics.

Birth weight is associated with brain tissue volumes seven decades later but not with MRI markers of brain ageing

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Larger birth weight is associated with larger brain tissue volumes at age 73.

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Birth weight is not associated with age-associated brain features.

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Effect of birth weight on brain volumes is independent of overall body size.

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Early life growth is likely to confer brain tissue reserve in later life.

Birth weight, an indicator of fetal growth, is associated with cognitive outcomes in early life (which are predictive of cognitive ability in later life) and risk of metabolic and cardiovascular disease across the life course. Brain health in older age, indexed by MRI features, is associated with cognitive performance, but little is known about how variation in normal birth weight impacts on brain structure in later life. In a community dwelling cohort of participants in their early seventies we tested the hypothesis that birth weight is associated with the following MRI features: total brain (TB), grey matter (GM) and normal appearing white matter (NAWM) volumes; whiter matter hyperintensity (WMH) volume; a general factor of fractional anisotropy (gFA) and peak width skeletonised mean diffusivity (PSMD) across the white matter skeleton. We also investigated the associations of birth weight with cortical surface area, volume and thickness. Birth weight was positively associated with TB, GM and NAWM volumes in later life (β ≥ 0.194), and with regional cortical surface area but not gFA, PSMD, WMH volume, or cortical volume or thickness. These positive relationships appear to be explained by larger intracranial volume, rather than by age-related tissue atrophy, and are independent of body height and weight in adulthood. This suggests that larger birth weight is linked to more brain tissue reserve in older life, rather than age-related brain structural features, such as tissue atrophy or WMH volume.

An epigenetic predictor of death captures multi-modal measures of brain health

Individuals of the same chronological age exhibit disparate rates of biological ageing. Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm). A novel epigenetic clock, termed 'DNAm GrimAge' has outperformed its predecessors in predicting the risk of mortality as well as many age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 (n = 709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over the eighth decade (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 × 10-16). Higher DNAm GrimAge was associated with lower age 11 IQ (β = -0.11), lower age 73 general cognitive ability (β = -0.18), decreased brain volume (β = -0.25) and increased brain white matter hyperintensities (β = 0.17). There was tentative evidence for a longitudinal association between DNAm GrimAge and cognitive decline from age 70 to 79. Sixty-nine of 137 health- and brain-related phenotypes tested were significantly associated with GrimAge. Adjusting all models for childhood intelligence attenuated to non-significance a small number of associations (12/69 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge associates with lower cognitive ability and brain vascular lesions in older age, independently of early-life cognitive ability. This epigenetic predictor of mortality associates with different measures of brain health and may aid in the prediction of age-related cognitive decline.

Cohort profile for the STratifying Resilience and Depression Longitudinally (STRADL) study: A depression-focused investigation of Generation Scotland, using detailed clinical, cognitive, and neuroimaging assessments

STratifying Resilience and Depression Longitudinally (STRADL) is a population-based study built on the Generation Scotland: Scottish Family Health Study (GS:SFHS) resource. The aim of STRADL is to subtype major depressive disorder (MDD) on the basis of its aetiology, using detailed clinical, cognitive, and brain imaging assessments. The GS:SFHS provides an important opportunity to study complex gene-environment interactions, incorporating linkage to existing datasets and inclusion of early-life variables for two longitudinal birth cohorts. Specifically, data collection in STRADL included: socio-economic and lifestyle variables; physical measures; questionnaire data that assesses resilience, early-life adversity, personality, psychological health, and lifetime history of mood disorder; laboratory samples; cognitive tests; and brain magnetic resonance imaging. Some of the questionnaire and cognitive data were first assessed at the GS:SFHS baseline assessment between 2006-2011, thus providing longitudinal measures relevant to the study of depression, psychological resilience, and cognition. In addition, routinely collected historic NHS data and early-life variables are linked to STRADL data, further providing opportunities for longitudinal analysis. Recruitment has been completed and we consented and tested 1,188 participants.

Cerebral small vessel disease burden and longitudinal cognitive decline from age 73 to 82: the Lothian Birth Cohort 1936

Slowed processing speed is considered a hallmark feature of cognitive decline in cerebral small vessel disease (SVD); however, it is unclear whether SVD's association with slowed processing might be due to its association with overall declining general cognitive ability. We quantified the total MRI-visible SVD burden of 540 members of the Lothian Birth Cohort 1936 (age: 72.6 ± 0.7 years; 47% female). Using latent growth curve modelling, we tested associations between total SVD burden at mean age 73 and changes in general cognitive ability, processing speed, verbal memory and visuospatial ability, measured at age 73, 76, 79 and 82. Covariates included age, sex, vascular risk and childhood cognitive ability. In the fully adjusted models, greater SVD burden was associated with greater declines in general cognitive ability (standardised β: -0.201; 95% CI: [-0.36, -0.04]; p_FDR = 0.022) and processing speed (-0.222; [-0.40, -0.04]; p_FDR = 0.022). SVD burden accounted for between 4 and 5% of variance in declines of general cognitive ability and processing speed. After accounting for the covariance between tests of processing speed and general cognitive ability, only SVD's association with greater decline in general cognitive ability remained significant, prior to FDR correction (-0.222; [-0.39, -0.06]; p = 0.008; p_FDR = 0.085). Our findings do not support the notion that SVD has a specific association with declining processing speed, independent of decline in general cognitive ability (which captures the variance shared across domains of cognitive ability). The association between SVD burden and declining general cognitive ability supports the notion of SVD as a diffuse, whole-brain disease and suggests that trials monitoring SVD-related cognitive changes should consider domain-specific changes in the context of overall, general cognitive decline.

Relationship between inferior frontal sulcal hyperintensities on brain MRI, ageing and cerebral small vessel disease

Raised signal in cerebrospinal fluid (CSF) on fluid-attenuated inversion recovery (FLAIR) may indicate raised CSF protein or debris and is seen in inferior frontal sulci on routine MRI. To explore its clinical relevance, we assessed the association of inferior frontal sulcal hyperintensities (IFSH) on FLAIR with demographics, risk factors, and small vessel disease markers in three cohorts (healthy volunteers, n=44; mild stroke patients, n=105; older community-dwelling participants from Lothian birth cohort 1936, n=101). We collected detailed clinical data, scanned all subjects on the same 3T MRI scanner and 3-dimensional FLAIR sequence and developed a scale to rate IFSH. In adjusted analyses, the IFSH score increased with age (per 10-year increase; OR 1.69; 95% CI, 1.42-2.02), and perivascular spaces score in centrum semiovale in stroke patients (OR 1.73; 95% CI, 1.13-2.69). Since glymphatic CSF clearance declines with age and drains partially via the cribriform plate to the nasal lymphatics, IFSH on 3T MRI may be a non-invasive biomarker of altered CSF clearance and justifies further research in larger, more diverse samples.

Comparison of structural MRI brain measures between 1.5 and 3 T: Data from the Lothian Birth Cohort 1936

Multi‐scanner MRI studies are reliant on understanding the apparent differences in imaging measures between different scanners. We provide a comprehensive analysis of T₁‐weighted and diffusion MRI (dMRI) structural brain measures between a 1.5 T GE Signa Horizon HDx and a 3 T Siemens Magnetom Prisma using 91 community‐dwelling older participants (aged 82 years). Although we found considerable differences in absolute measurements (global tissue volumes were measured as ~6–11% higher and fractional anisotropy [FA] was 33% higher at 3 T than at 1.5 T), between‐scanner consistency was good to excellent for global volumetric and dMRI measures (intraclass correlation coefficient [ICC] range: .612–.993) and fair to good for 68 cortical regions (FreeSurfer) and cortical surface measures (mean ICC: .504–.763). Between‐scanner consistency was fair for dMRI measures of 12 major white matter tracts (mean ICC: .475–.564), and the general factors of these tracts provided excellent consistency (ICC ≥ .769). Whole‐brain structural networks provided good to excellent consistency for global metrics (ICC ≥ .612). Although consistency was poor for individual network connections (mean ICCs: .275−.280), this was driven by a large difference in network sparsity (.599 vs. .334), and consistency was improved when comparing only the connections present in every participant (mean ICCs: .533–.647). Regression‐based k‐fold cross‐validation showed that, particularly for global volumes, between‐scanner differences could be largely eliminated (R² range .615–.991). We conclude that low granularity measures of brain structure can be reliably matched between the scanners tested, but caution is warranted when combining high granularity information from different scanners.

Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines

BACKGROUND

Aging-related cognitive decline is a primary risk factor for Alzheimer's disease and related dementias. More precise identification of the neurobiological bases of cognitive decline in aging populations may provide critical insights into the precursors of late-life dementias.

METHODS

Using structural and diffusion brain magnetic resonance imaging data from the UK Biobank (n = 8185; age range, 45-78 years), we examined aging of regional gray matter volumes (nodes) and white matter structural connectivity (edges) within 9 well-characterized networks of interest in the human brain connectome. In the independent Lothian Birth Cohort 1936 (n = 534; all 73 years of age), we tested whether aging-sensitive connectome elements are enriched for key domains of cognitive function before and after controlling for early-life cognitive ability.

RESULTS

In the UK Biobank, age differences in individual connectome elements corresponded closely with principal component loadings reflecting connectome-wide integrity (|rnodes| = .420; |redges| = .583), suggesting that connectome aging occurs on broad dimensions of variation in brain architecture. In the Lothian Birth Cohort 1936, composite indices of node integrity were predictive of all domains of cognitive function, whereas composite indices of edge integrity were associated specifically with processing speed. Elements within the central executive network were disproportionately predictive of late-life cognitive function relative to the network's small size. Associations with processing speed and visuospatial ability remained after controlling for childhood cognitive ability.

CONCLUSIONS

These results implicate global dimensions of variation in the human structural connectome in aging-related cognitive decline. The central executive network may demarcate a constellation of elements that are centrally important to age-related cognitive impairments.

Three major dimensions of human brain cortical ageing in relation to cognitive decline across the eighth decade of life

Different brain regions can be grouped together, based on cross-sectional correlations among their cortical characteristics; this patterning has been used to make inferences about ageing processes. However, cross-sectional brain data conflate information on ageing with patterns that are present throughout life. We characterised brain cortical ageing across the eighth decade of life in a longitudinal ageing cohort, at ages ~73, ~76, and ~79 years, with a total of 1376 MRI scans. Volumetric changes among cortical regions of interest (ROIs) were more strongly correlated (average r = 0.805, SD = 0.252) than were cross-sectional volumes of the same ROIs (average r = 0.350, SD = 0.178). We identified a broad, cortex-wide, dimension of atrophy that explained 66% of the variance in longitudinal changes across the cortex. Our modelling also discovered more specific fronto-temporal and occipito-parietal dimensions that were orthogonal to the general factor and together explained an additional 20% of the variance. The general factor was associated with declines in general cognitive ability (r = 0.431, p < 0.001) and in the domains of visuospatial ability (r = 0.415, p = 0.002), processing speed (r = 0.383, p < 0.001) and memory (r = 0.372, p < 0.001). Individual differences in brain cortical atrophy with ageing are manifest across three broad dimensions of the cerebral cortex, the most general of which is linked with cognitive declines across domains. Longitudinal approaches are invaluable for distinguishing lifelong patterns of brain-behaviour associations from patterns that are specific to aging.

Association of common genetic variants with brain microbleeds: A genome-wide association study

OBJECTIVE

To identify common genetic variants associated with the presence of brain microbleeds (BMBs).

METHODS

We performed genome-wide association studies in 11 population-based cohort studies and 3 case-control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of APOE ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.

RESULTS

BMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR]any BMB [95% confidence interval (CI)] 1.33 [1.21-1.45]; p = 2.5 × 10-10). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19-1.50]; p = 1.0 × 10-6) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86-1.25]; p = 0.68). APOE ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.

CONCLUSIONS

Genetic variants in the APOE region are associated with the presence of BMB, most likely due to the APOE ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.

Age- and memory- related differences in hippocampal gray matter integrity are better captured by NODDI compared to single-tensor diffusion imaging

Single-tensor diffusion imaging (DTI) has traditionally been used to assess integrity of white matter. For example, we previously showed that integrity of limbic white matter tracts declines in healthy aging and relates to episodic memory performance. However, multi-compartment diffusion models may be more informative about microstructural properties of gray matter. The current study examined hippocampal gray matter integrity using both single-tensor and multi-compartment (neurite orientation dispersion and density imaging, NODDI) diffusion imaging. Younger (20-38 years) and older (59-84 years) adults also completed the Mnemonic Similarity Task to measure mnemonic discrimination performance. Results revealed age-related declines in both single-tensor (lower fractional anisotropy, higher mean diffusivity) and multi-compartment (higher restricted, hindered and free diffusion) measures of hippocampal gray matter integrity. As expected, NODDI measures (hindered and free diffusion) captured more age-related variance than DTI measures. Moreover, mnemonic discrimination of highly similar lure items in memory was related to hippocampal gray matter integrity in younger but not older adults. These findings support the notion that age-related differences in gray matter integrity are better captured by multi-compartment versus single-tensor diffusion models and show that the relationship between mnemonic discrimination and hippocampal gray matter integrity is moderated by age.

Generation of twenty four induced pluripotent stem cell lines from twenty four members of the Lothian Birth Cohort 1936

Cognitive decline is among the most feared aspects of ageing. We have generated induced pluripotent stem cells (iPSCs) from 24 people from the Lothian Birth Cohort 1936, whose cognitive ability was tested in childhood and in older age. Peripheral blood mononuclear cells (PBMCs) were reprogrammed using non-integrating oriP/EBNA1 backbone plasmids expressing six iPSC reprogramming factors (OCT3/4 (POU5F1), SOX2, KLF4, L-Myc, shp53, Lin28, SV40LT). All lines demonstrated STR matched karyotype and pluripotency was validated by multiple methods. These iPSC lines are a valuable resource to study molecular mechanisms underlying individual differences in cognitive ageing and resilience to age-related neurodegenerative diseases.

Neurology-related protein biomarkers are associated with cognitive ability and brain volume in older age

Identifying biological correlates of late life cognitive function is important if we are to ascertain biomarkers for, and develop treatments to help reduce, age-related cognitive decline. Here, we investigated the associations between plasma levels of 90 neurology-related proteins (Olink® Proteomics) and general fluid cognitive ability in the Lothian Birth Cohort 1936 (LBC1936, N = 798), Lothian Birth Cohort 1921 (LBC1921, N = 165), and the INTERVAL BioResource (N = 4451). In the LBC1936, 22 of the proteins were significantly associated with general fluid cognitive ability (β between -0.11 and -0.17). MRI-assessed total brain volume partially mediated the association between 10 of these proteins and general fluid cognitive ability. In an age-matched subsample of INTERVAL, effect sizes for the 22 proteins, although smaller, were all in the same direction as in LBC1936. Plasma levels of a number of neurology-related proteins are associated with general fluid cognitive ability in later life, mediated by brain volume in some cases.

Attitudes to ageing, biomarkers of ageing and mortality: the Lothian Birth Cohort 1936

Objective

To investigate whether people with more positive attitudes to ageing are biologically younger as defined by leucocyte telomere length, accelerated DNA methylation GrimAge (AgeAccelGrim) and brain-predicted age difference, and whether these biomarkers explain relationships between attitudes to ageing and mortality.

Methods

We used linear regression to examine cross-sectionally attitudes to ageing (measured using the Attitudes to Ageing Questionnaire) and the three biomarkers in 758 adults, mean age 72.5 years, from the Lothian Birth Cohort 1936. We used Cox proportional hazards models to examine longitudinally attitudes to ageing and mortality and the role of the biomarkers.

Results

More positive attitude to physical change was associated with younger biological age, as measured by AgeAccelGrim and brain-predicted age difference in age-adjusted and sex-adjusted models: for an SD higher score, AgeAccelGrim was lower by -0.73 (95% CI -1.03 to -0.42) of a year, and brain-predicted age difference was lower by -0.87 (1.51 to 0.23) of a year. Both associations were attenuated by adjustment for covariates and not significant after simultaneous adjustment for all covariates and correction for multiple testing. More positive attitudes to physical change were associated with lower mortality: for an SD higher score the age-adjusted and sex-adjusted HR (95% CI) was 0.66 (0.56 to 0.78). Adjustment for AgeAccelGrim or brain-predicted age difference attenuated this association slightly. It remained significant after adjustment for all covariates.

Conclusion

We found partial evidence that attitudes to ageing are linked with ageing biomarkers but they accounted for only a little of the association between attitudes and mortality.

Quantitative measurements of enlarged perivascular spaces in the brain are associated with retinal microvascular parameters in older community-dwelling subjects

BACKGROUND

Perivascular Spaces (PVS) become increasingly visible with advancing age on brain MRI, yet their relationship to morphological changes in the underlying microvessels remains poorly understood. Retinal and cerebral microvessels share morphological and physiological properties. We compared computationally-derived PVS morphologies with retinal vessel morphologies in older people.

METHODS

We analysed data from community-dwelling individuals who underwent multimodal brain MRI and retinal fundus camera imaging at mean age 72.55 years (SD=0.71). We assessed centrum semiovale PVS computationally to determine PVS total volume and count, and mean per-subject individual PVS length, width and size. We analysed retinal images using the VAMPIRE software suite, obtaining the Central Retinal Artery and Vein Equivalents (CRVE and CRAE), Arteriole-to-Venule ratio (AVR), and fractal dimension (FD) of both eyes. We investigated associations using general linear models, adjusted for age, gender, and major vascular risk factors.

RESULTS

In 381 subjects with all measures, increasing total PVS volume and count were associated with decreased CRAE in the left eye (volume β=-0.170, count β=-0.184, p<0.001). No associations of PVS with CRVE were found. The PVS total volume, individual width and size increased with decreasing FD of the arterioles (a) and venules (v) of the left eye (total volume: FDa β=-0.137, FDv β=-0.139, p<0.01; width: FDa β=-0.144, FDv β=-0.158, p<0.01; size: FDa β=-0.157, FDv β=-0.162, p<0.01).

CONCLUSIONS

Increase in PVS number and size visible on MRI reflect arteriolar narrowing and lower retinal arteriole and venule branching complexity, both markers of impaired microvascular health. Computationally-derived PVS metrics may be an early indicator of failing vascular health and should be tested in longitudinal studies.

Fluctuating asymmetry in brain structure and general intelligence in 73-year-olds

Fluctuating body asymmetry is theorized to indicate developmental instability, and to have small positive associations with low socioeconomic status (SES). Previous studies have reported small negative associations between fluctuating body asymmetry and cognitive functioning, but relationships between fluctuating brain asymmetry and cognitive functioning remain unclear. The present study investigated the association between general intelligence (a latent factor derived from a factor analysis on 13 cognitive tests) and the fluctuating asymmetry of four structural measures of brain hemispheric asymmetry: cortical surface area, cortical volume, cortical thickness, and white matter fractional anisotropy. The sample comprised members of the Lothian Birth Cohort 1936 (LBC1936, N = 636, mean age = 72.9 years). Two methods were used to calculate structural hemispheric asymmetry: in the first method, regions contributed equally to the overall asymmetry score; in the second method, regions contributed proportionally to their size. When regions contributed equally, cortical thickness asymmetry was negatively associated with general intelligence (β = −0.18,p < .001). There was no association between cortical thickness asymmetry and childhood SES, suggesting that other mechanisms are involved in the thickness asymmetry-intelligence association. Across all cortical metrics, asymmetry of regions identified by the parieto-frontal integration theory (P-FIT) was not more strongly associated with general intelligence than non-P-FIT asymmetry. When regions contributed proportionally, there were no associations between general intelligence and any of the asymmetry measures. The implications of these findings, and of different methods of calculating structural hemispheric asymmetry, are discussed.

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Previous work has shown links between cortical asymmetry and intelligence.

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In the current study, two methods of calculating global cortical hemispheric asymmetry were compared.

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Equal region contribution: the association between cortical thickness asymmetry and general intelligence was β = −0.18.

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Proportional region contribution: no associations between three measures of cortical asymmetry and general intelligence.

The striatum, the hippocampus, and short-term memory binding: Volumetric analysis of the subcortical grey matter's role in mild cognitive impairment

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Hippocampal atrophy plays no role in short-term memory binding.

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The globus pallidus could be part of the brain network supporting binding.

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Total brain atrophy does not correlate with striatal grey matter atrophy in MCI.

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Striatal grey matter atrophy reflects in total brain atrophy in controls.

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Hippocampal and parahippocampal volumes correlate in MCI and controls.

Background

Deficits in short-term memory (STM) binding are a distinguishing feature of preclinical stages leading to Alzheimer's disease (AD). However, the neuroanatomical correlates of conjunctive STM binding are largely unexplored. Here we examine the possible association between the volumes of hippocampi, parahippocampal gyri, and grey matter within the subcortical structures – all found to have foci that seemingly correlate with basic daily living activities in AD patients - with cognitive tests related to conjunctive STM binding.

Materials and methods

Hippocampal, thalamic, parahippocampal and corpus striatum volumes were semi-automatically quantified in brain magnetic resonance images from 25 cognitively normal people and 21 patients with Mild Cognitive Impairment (MCI) at high risk of AD progression, who undertook a battery of cognitive tests and the short-term memory binding test. Associations were assessed using linear regression models and group differences were assessed using the Mann-Whitney U test.

Results

Hippocampal and parahippocampal gyrus volumes differed between MCI and control groups. Although the grey matter volume in the globus pallidus (r = -0.71, p < 0.001) and parahippocampal gyry (r = -0.63, p < 0.05) correlated with a STM binding task in the MCI group, only the former remained associated with STM binding deficits in MCI patients, after correcting for age, gender and years of education (β = -0.56,P = 0.042) although with borderline significance.

Conclusions

Loss of hippocampal volume plays no role in the processing of STM binding. Structures within the basal ganglia, namely the globus pallidus, could be part of the extrahippocampal network supporting binding. Replication of this study in large samples is now needed.

Computational quantification of brain perivascular space morphologies: Associations with vascular risk factors and white matter hyperintensities. A study in the Lothian Birth Cohort 1936

BACKGROUND AND PURPOSE

Perivascular Spaces (PVS), also known as Virchow-Robin spaces, seen on structural brain MRI, are important fluid drainage conduits and are associated with small vessel disease (SVD). Computational quantification of visible PVS may enable efficient analyses in large datasets and increase sensitivity to detect associations with brain disorders. We assessed the associations of computationally-derived PVS parameters with vascular factors and white matter hyperintensities (WMH), a marker of SVD.

PARTICIPANTS

Community dwelling individuals (n = 700) from the Lothian Birth Cohort 1936 who had multimodal brain MRI at age 72.6 years (SD = 0.7).

METHODS

We assessed PVS computationally in the centrum semiovale and deep corona radiata on T2-weighted images. The computationally calculated measures were the total PVS volume and count per subject, and the mean individual PVS length, width and size, per subject. We assessed WMH by volume and visual Fazekas scores. We compared PVS visual rating to PVS computational metrics, and tested associations between each PVS measure and vascular risk factors (hypertension, diabetes, cholesterol), vascular history (cardiovascular disease and stroke), and WMH burden, using generalized linear models, which we compared using coefficients, confidence intervals and model fit.

RESULTS

In 533 subjects, the computational PVS measures correlated positively with visual PVS ratings (PVS count r = 0.59; PVS volume r = 0.61; PVS mean length r = 0.55; PVS mean width r = 0.52; PVS mean size r = 0.47). PVS size and width were associated with hypertension (OR 1.22, 95% CI [1.03 to 1.46] and 1.20, 95% CI [1.01 to 1.43], respectively), and stroke (OR 1.34, 95% CI [1.08 to 1.65] and 1.36, 95% CI [1.08 to 1.71], respectively). We found no association between other PVS measures and diabetes, hypercholesterolemia or cardiovascular disease history. Computational PVS volume, length, width and size were more strongly associated with WMH (PVS mean size versus WMH Fazekas score β = 0.66, 95% CI [0.59 to 0.74] and versus WMH volume β = 0.43, 95% CI [0.38 to 0.48]) than computational PVS count (WMH Fazekas score β = 0.21, 95% CI [0.11 to 0.3]; WMH volume β = 0.14, 95% CI [0.09 to 0.19]) or visual score. Individual PVS size showed the strongest association with WMH.

CONCLUSIONS

Computational measures reflecting individual PVS size, length and width were more strongly associated with WMH, stroke and hypertension than computational count or visual PVS score. Multidimensional computational PVS metrics may increase sensitivity to detect associations of PVS with risk exposures, brain lesions and neurological disease, provide greater anatomic detail and accelerate understanding of disorders of brain fluid and waste clearance.

Epigenetic signatures of smoking associate with cognitive function, brain structure, and mental and physical health outcomes in the Lothian Birth Cohort 1936

Recent advances in genome-wide DNA methylation (DNAm) profiling for smoking behaviour have given rise to a new, molecular biomarker of smoking exposure. It is unclear whether a smoking-associated DNAm (epigenetic) score has predictive value for ageing-related health outcomes which is independent of contributions from self-reported (phenotypic) smoking measures. Blood DNA methylation levels were measured in 895 adults aged 70 years in the Lothian Birth Cohort 1936 (LBC1936) study using the Illumina 450K assay. A DNA methylation score based on 230 CpGs was used as a proxy for smoking exposure. Associations between smoking variables and health outcomes at age 70 were modelled using general linear modelling (ANCOVA) and logistic regression. Additional analyses of smoking with brain MRI measures at age 73 (n = 532) were performed. Smoking-DNAm scores were positively associated with self-reported smoking status (P < 0.001, eta-squared ɳ2 = 0.63) and smoking pack years (r = 0.69, P < 0.001). Higher smoking DNAm scores were associated with variables related to poorer cognitive function, structural brain integrity, physical health, and psychosocial health. Compared with phenotypic smoking, the methylation marker provided stronger associations with all of the cognitive function scores, especially visuospatial ability (P < 0.001, partial eta-squared ɳp2 = 0.022) and processing speed (P < 0.001, ɳp2 = 0.030); inflammatory markers (all P < 0.001, ranges from ɳp2 = 0.021 to 0.030); dietary patterns (healthy diet (P < 0.001, ɳp2 = 0.052) and traditional diet (P < 0.001, ɳp2 = 0.032); stroke (P = 0.006, OR 1.48, 95% CI 1.12, 1.96); mortality (P < 0.001, OR 1.59, 95% CI 1.42, 1.79), and at age 73; with MRI volumetric measures (all P < 0.001, ranges from ɳp2 = 0.030 to 0.052). Additionally, education was the most important life-course predictor of lifetime smoking tested. Our results suggest that a smoking-associated methylation biomarker typically explains a greater proportion of the variance in some smoking-related morbidities in older adults, than phenotypic measures of smoking exposure, with some of the accounted-for variance being independent of phenotypic smoking status.

Predictors of gait speed and its change over three years in community-dwelling older people

We aimed to assess whether and how changes in brain volume and increases in white matter hyperintensity (WMH) volume over three years predict gait speed and its change independently of demographics, vascular risk factors and physical status. We analyzed 443 individuals from the Lothian Birth Cohort 1936, at mean age 73 and 76 years. Gait speed at age 76 was predicted by age, grip strength and body mass index at mean age 73, three-year brain volume decrease and WMH volume increase, explaining 26.1% of variance. Decline in gait speed to age 76 was predicted by the same five variables explaining 40.9% of variance. In both analyses, grip strength and body mass index explained the most variance. A clinically significant decline in gait speed (≥ 0.1 m/s per year) occurred in 24.4%. These individuals had more structural brain changes. Brain volume and WMH changes were independent predictors of gait dysfunction and its three-year change, but the impact of malleable physical factors such as grip strength or body mass index was greater.

Spatial Gradient of Microstructural Changes in Normal-Appearing White Matter in Tracts Affected by White Matter Hyperintensities in Older Age

Background and Purpose: White matter hyperintensities (WMH) are commonly seen on structural MRI of older adults and are a manifestation of underlying and adjacent tissue damage. WMH may contribute to cortical disconnection and cognitive dysfunction, but it is unclear how WMH affect intersecting or nearby white matter tract integrity. This study investigated the effects of WMH on tract microstructure by determining the spatial distribution of water diffusion characteristics in white matter tract areas adjacent to both intersecting and nearby WMH. Methods: We used diffusion and structural MRI data from 52 representative participants from the Lothian Birth Cohort 1936 (72.2 ± 0.7 years) including a range of WMH burden. We segmented WMH, reconstructed 18 main white mater tracts using automated quantitative tractography and identified intersections between tracts and WMH. We measured mean diffusivity (MD) and fractional anisotropy (FA) in tract tissue at 2 mm incremental distances from tract-intersecting and non-intersecting (nearby) WMH. Results: We observed a spatial gradient of FA and MD abnormalities for most white matter tracts which diminished with a similar distance pattern for tract-intersecting and nearby WMH. Overall, FA was higher, while MD was lower around nearby WMH compared with tract-intersecting WMH. However, for some tracts, FA was lower in areas immediately surrounding nearby WMH, although with faster normalization than in FA values surrounding tract-intersecting WMH. Conclusion: WMH have similar effects on tract infrastructure, whether they be intersecting or nearby. However, the observed differences in tract water diffusion properties around WMH suggest that degenerative processes in small vessel disease may propagate further along the tract for intersecting WMH, while in some areas of the brain there is a larger and more localized accumulation of axonal damage in tract tissue nearby a non-connected WMH. Longitudinal studies should address differential effects of intersecting vs. nearby WMH progression and how they contribute to cognitive aging.

Sleep and brain morphological changes in the eighth decade of life

OBJECTIVE

Sleep is important for brain health. We analysed associations between usual sleep habits and magnetic resonance imaging (MRI) markers of neurodegeneration (brain atrophy), vascular damage (white matter hyperintensities, WMH) and waste clearance (perivascular spaces, PVS) in older community-dwelling adults.

METHOD

We collected self-reported usual sleep duration, quality and medical histories from the Lothian Birth Cohort 1936 (LBC1936) age 76 years and performed brain MRI. We calculated sleep efficiency, measured WMH and brain volumes, quantified PVS, and assessed associations between sleep measures and brain markers in multivariate models adjusted for demographic and medical history variables.

RESULTS

In 457 subjects (53% males, mean age 76 ± 0.65 years), we found: brain and white matter loss with increased weekend daytime sleep (β = -0.114, P = 0.03; β = -0.122, P = 0.007 respectively), white matter loss with less efficient sleep (β = 0.132, P = 0.011) and PVS increased with interrupted sleep (OR 1.84 95% CI, P = 0.025).

CONCLUSION

Cross-sectional associations of sleep parameters with brain atrophy and more PVS suggest adverse relationships between usual sleep habits and brain health in older people that should be evaluated longitudinally.

Reaction time variability and brain white matter integrity

Objective: Mean speed of responding is the most commonly used measure in the assessment of reaction time (RT). An alternative measure is intraindividual variability (IIV): the inconsistency of responding across multiple trials of a test. IIV has been suggested as an important indicator of central nervous system functioning, and as such, there has been increasing interest in the associations between IIV and brain imaging metrics. Results however, have been inconsistent. The present seeks to provide a comprehensive evaluation of the associations between a variety of measures of brain white matter integrity and individual differences in choice RT (CRT) IIV. Method: MRI brain scans of members of the Lothian Birth Cohort 1936 were assessed to obtain measures of the volume and severity of white matter hyperintensities, and the integrity of brain white matter tracts. CRT was assessed with a 4 CRT task on a separate occasion. Data were analyzed using multiple regression (N range = 358–670). Results: Greater volume of hyperintensities and more severe hyperintensities in frontal regions were associated with higher CRT IIV. White matter tract integrity, as assessed by both fractional anisotropy and mean diffusivity, showed the smallest effect sizes in associations with CRT IIV. Associations with hyperintensities were attenuated and no longer significant after controlling for M CRT. Conclusions: Taken together, the results of the present study suggested that IIV was not incrementally predictive of white matter integrity over mean speed. This is in contrast to previous reports, and highlights the need for further study.

Variability in speeded cognitive test performance has been argued to be a potential early marker of cognitive decline and progression into mild cognitive impairment in aging. Evidence as to the robustness of the relationship, and the potential neurological underpinnings is varied. Our results suggest that average speeded performance, not variability, may be more reliably related to various measures of the brain. These findings are in contrast to much of the extant literature, highlighting the need for further research.

Imaging the aged brain: pertinence and methods

The global population is ageing at an accelerating speed. The ability to perform working memory tasks together with rapid processing becomes increasingly difficult with increases in age. With increasing national average life spans and a rise in the prevalence of age-related disease, it is pertinent to discuss the unique perspectives that can be gained from imaging the aged brain. Differences in structure, function, blood flow, and neurovascular coupling are present in both healthy aged brains and in diseased brains and have not yet been explored to their full depth in contemporary imaging studies. Imaging methods ranging from optical imaging to magnetic resonance imaging (MRI) to newer technologies such as photoacoustic tomography each offer unique advantages and challenges in imaging the aged brain. This paper will summarize first the importance and challenges of imaging the aged brain and then offer analysis of potential imaging modalities and their representative applications. The potential breakthroughs in brain imaging are also envisioned.

Retinal microvasculature and cerebral small vessel disease in the Lothian Birth Cohort 1936 and Mild Stroke Study

Research has suggested that the retinal vasculature may act as a surrogate marker for diseased cerebral vessels. Retinal vascular parameters were measured using Vessel Assessment and Measurement Platform for Images of the Retina (VAMPIRE) software in two cohorts: (i) community-dwelling older subjects of the Lothian Birth Cohort 1936 (n = 603); and (ii) patients with recent minor ischaemic stroke of the Mild Stroke Study (n = 155). Imaging markers of small vessel disease (SVD) (white matter hyperintensities [WMH] on structural MRI, visual scores and volume; perivascular spaces; lacunes and microbleeds), and vascular risk measures were assessed in both cohorts. We assessed associations between retinal and brain measurements using structural equation modelling and regression analysis. In the Lothian Birth Cohort 1936 arteriolar fractal dimension accounted for 4% of the variance in WMH load. In the Mild Stroke Study lower arteriolar fractal dimension was associated with deep WMH scores (odds ratio [OR] 0.53; 95% CI, 0.32–0.87). No other retinal measure was associated with SVD. Reduced fractal dimension, a measure of vascular complexity, is related to SVD imaging features in older people. The results provide some support for the use of the retinal vasculature in the study of brain microvascular disease.

Longitudinal multi-centre brain imaging studies: guidelines and practical tips for accurate and reproducible imaging endpoints and data sharing

Background

Research involving brain imaging is important for understanding common brain diseases. Study endpoints can include features and measures derived from imaging modalities, providing a benchmark against which other phenotypical data can be assessed. In trials, imaging data provide objective evidence of beneficial and adverse outcomes. Multi-centre studies increase generalisability and statistical power. However, there is a lack of practical guidelines for the set-up and conduct of large neuroimaging studies.

Methods

We address this deficit by describing aspects of study design and other essential practical considerations that will help researchers avoid common pitfalls and data loss.

Results

The recommendations are grouped into seven categories: (1) planning, (2) defining the imaging endpoints, developing an imaging manual and managing the workflow, (3) performing a dummy run and testing the analysis methods, (4) acquiring the scans, (5) anonymising and transferring the data, (6) monitoring quality, and (7) using structured data and sharing data.

Conclusions

Implementing these steps will lead to valuable and usable data and help to avoid imaging data wastage.

Brain Peak Width of Skeletonized Mean Diffusivity (PSMD) and Cognitive Function in Later Life

It is suggested that the brain's peak width of skeletonized water mean diffusivity (PSMD) is a neuro-biomarker of processing speed, an important aspect of cognitive aging. We tested whether PSMD is more strongly correlated with processing speed than with other cognitive domains, and more strongly than other structural brain MRI indices. Participants were 731 Lothian Birth Cohort 1936 members, mean age = 73 years (SD = 0.7); analytical sample was 656-680. Cognitive domains tested were as follows: processing speed (5 tests), visuospatial (3), memory (3), and verbal (3). Brain-imaging variables included PSMD, white matter diffusion parameters, hyperintensity volumes, gray and white matter volumes, and perivascular spaces. PSMD was significantly associated with processing speed (-0.27), visuospatial ability (-0.23), memory ability (-0.17), and general cognitive ability (-0.25); comparable correlations were found with other brain-imaging measures. In a multivariable model with the other imaging variables, PSMD provided independent prediction of visuospatial ability and general cognitive ability. This incremental prediction, coupled with its ease to compute and possibly better tractability, might make PSMD a useful brain biomarker in studies of cognitive aging.

Meta-analysis of epigenome-wide association studies of cognitive abilities

Cognitive functions are important correlates of health outcomes across the life-course. Individual differences in cognitive functions are partly heritable. Epigenetic modifications, such as DNA methylation, are susceptible to both genetic and environmental factors and may provide insights into individual differences in cognitive functions. Epigenome-wide meta-analyses for blood-based DNA methylation levels at ~420,000 CpG sites were performed for seven measures of cognitive functioning using data from 11 cohorts. CpGs that passed a Bonferroni correction, adjusting for the number of CpGs and cognitive tests, were assessed for: longitudinal change; being under genetic control (methylation QTLs); and associations with brain health (structural MRI), brain methylation and Alzheimer's disease pathology. Across the seven measures of cognitive functioning (meta-analysis n range: 2557-6809), there were epigenome-wide significant (P < 1.7 × 10-8) associations for global cognitive function (cg21450381, P = 1.6 × 10-8), and phonemic verbal fluency (cg12507869, P = 2.5 × 10-9). The CpGs are located in an intergenic region on chromosome 12 and the INPP5A gene on chromosome 10, respectively. Both probes have moderate correlations (~0.4) with brain methylation in Brodmann area 20 (ventral temporal cortex). Neither probe showed evidence of longitudinal change in late-life or associations with white matter brain MRI measures in one cohort with these data. A methylation QTL analysis suggested that rs113565688 was a cis methylation QTL for cg12507869 (P = 5 × 10-5 and 4 × 10-13 in two lookup cohorts). We demonstrate a link between blood-based DNA methylation and measures of phonemic verbal fluency and global cognitive ability. Further research is warranted to understand the mechanisms linking genomic regulatory changes with cognitive function to health and disease.