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.

Brain age predicts mortality.

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.

Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study.

Higher polygenic risk score for schizophrenia (szPGRS) has been associated with lower cognitive function and might be a predictor of decline in brain structure in apparently healthy populations. Age-related declines in structural brain connectivity-measured using white matter diffusion MRI -are evident from cross-sectional data. Yet, it remains unclear how graph theoretical metrics of the structural connectome change over time, and whether szPGRS is associated with differences in ageing-related changes in human brain connectivity. Here, we studied a large, relatively healthy, same-year-of-birth, older age cohort over a period of 3 years (age ∼ 73 years, N = 731; age ∼76 years, N = 488). From their brain scans we derived tract-averaged fractional anisotropy (FA) and mean diffusivity (MD), and network topology properties. We investigated the cross-sectional and longitudinal associations between these structural brain variables and szPGRS. Higher szPGRS showed significant associations with longitudinal increases in MD in the splenium (ß = 0.132, pFDR = 0.040), arcuate (ß = 0.291, pFDR = 0.040), anterior thalamic radiations (ß = 0.215, pFDR = 0.040) and cingulum (ß = 0.165, pFDR = 0.040). Significant declines over time were observed in graph theory metrics for FA-weighted networks, such as mean edge weight (ß = -0.039, pFDR = 0.048) and strength (ß = -0.027, pFDR = 0.048). No significant associations were found between szPGRS and graph theory metrics. These results are consistent with the hypothesis that szPGRS confers risk for ageing-related degradation of some aspects of structural connectivity.

Cognitive function, disease burden and the structural connectome in systemic lupus erythematosus.

Objective To investigate brain structural connectivity in relation to cognitive abilities and systemic damage in systemic lupus erythematosus (SLE). Methods Structural and diffusion MRI data were acquired from 47 patients with SLE. Brains were segmented into 85 cortical and subcortical regions and combined with whole brain tractography to generate structural connectomes using graph theory. Global cognitive abilities were assessed using a composite variable g, derived from the first principal component of three common clinical screening tests of neurological function. SLE damage ( LD) was measured using a composite of a validated SLE damage score and disease duration. Relationships between network connectivity metrics, cognitive ability and systemic damage were investigated. Hub nodes were identified. Multiple linear regression, adjusting for covariates, was employed to model the outcomes g and LD as a function of network metrics. Results The network measures of density (standardised ß = 0.266, p = 0.025) and strength (standardised ß = 0.317, p = 0.022) were independently related to cognitive abilities. Strength (standardised ß = -0.330, p = 0.048), mean shortest path length (standardised ß = 0.401, p = 0.020), global efficiency (standardised ß = -0.355, p = 0.041) and clustering coefficient (standardised ß = -0.378, p = 0.030) were independently related to systemic damage. Network metrics were not related to current disease activity. Conclusion Better cognitive abilities and more SLE damage are related to brain topological network properties in this sample of SLE patients, even those without neuropsychiatric involvement and after correcting for important covariates. These data show that connectomics might be useful for understanding and monitoring cognitive function and white matter damage in SLE.

Fatigue and cognitive function in systemic lupus erythematosus: associations with white matter microstructural damage. A diffusion tensor MRI study and meta-analysis.

Objective The objective of this study was to investigate fatigue and cognitive impairments in systemic lupus erythematous (SLE) in relation to diffuse white matter microstructural brain damage. Methods Diffusion tensor MRI, used to generate biomarkers of brain white matter microstructural integrity, was obtained in patients with SLE and age-matched controls. Fatigue and cognitive function were assessed and related to SLE activity, clinical data and plasma biomarkers of inflammation and endothelial dysfunction. Results Fifty-one patients with SLE (mean age 48.8 ± 14.3 years) were included. Mean diffusivity (MD) was significantly higher in all white matter fibre tracts in SLE patients versus age-matched healthy controls ( p < 0.0001). Fatigue in SLE was higher than a normal reference range ( p < 0.0001) and associated with lower MD ( ß = -0.61, p = 0.02), depression ( ß = 0.17, p = 0.001), anxiety ( ß = 0.13, p = 0.006) and higher body mass index ( ß = 0.10, p = 0.004) in adjusted analyses. Poorer cognitive function was associated with longer SLE disease duration ( p = 0.003) and higher MD ( p = 0.03) and, in adjusted analysis, higher levels of IL-6 ( ß = -0.15, p = 0.02) but not with MD. Meta-analysis (10 studies, n = 261, including the present study) confirmed that patients with SLE have higher MD than controls. Conclusion Patients with SLE have more microstructural brain white matter damage for age than the general population, but this does not explain increased fatigue or lower cognition in SLE. The association between raised IL-6 and worse current cognitive function in SLE should be explored in larger datasets.

Cigarette smoking and thinning of the brain's cortex.

Cigarette smoking is associated with cognitive decline and dementia, but the extent of the association between smoking and structural brain changes remains unclear. Importantly, it is unknown whether smoking-related brain changes are reversible after smoking cessation. We analyzed data on 504 subjects with recall of lifetime smoking data and a structural brain magnetic resonance imaging at age 73 years from which measures of cortical thickness were extracted. Multiple regression analyses were performed controlling for gender and exact age at scanning. To determine dose-response relationships, the association between smoking pack-years and cortical thickness was tested and then repeated, while controlling for a comprehensive list of covariates including, among others, cognitive ability before starting smoking. Further, we tested associations between cortical thickness and number of years since last cigarette, while controlling for lifetime smoking. There was a diffuse dose-dependent negative association between smoking and cortical thickness. Some negative dose-dependent cortical associations persisted after controlling for all covariates. Accounting for total amount of lifetime smoking, the cortex of subjects who stopped smoking seems to have partially recovered for each year without smoking. However, it took ~25 years for complete cortical recovery in affected areas for those at the mean pack-years value in this sample. As the cortex thins with normal aging, our data suggest that smoking is associated with diffuse accelerated cortical thinning, a biomarker of cognitive decline in adults. Although partial recovery appears possible, it can be a long process.

Childhood cognitive ability accounts for associations between cognitive ability and brain cortical thickness in old age.

Associations between brain cortical tissue volume and cognitive function in old age are frequently interpreted as suggesting that preservation of cortical tissue is the foundation of successful cognitive aging. However, this association could also, in part, reflect a lifelong association between cognitive ability and cortical tissue. We analyzed data on 588 subjects from the Lothian Birth Cohort 1936 who had intelligence quotient (IQ) scores from the same cognitive test available at both 11 and 70 years of age as well as high-resolution brain magnetic resonance imaging data obtained at approximately 73 years of age. Cortical thickness was estimated at 81 924 sampling points across the cortex for each subject using an automated pipeline. Multiple regression was used to assess associations between cortical thickness and the IQ measures at 11 and 70 years. Childhood IQ accounted for more than two-third of the association between IQ at 70 years and cortical thickness measured at age 73 years. This warns against ascribing a causal interpretation to the association between cognitive ability and cortical tissue in old age based on assumptions about, and exclusive reference to, the aging process and any associated disease. Without early-life measures of cognitive ability, it would have been tempting to conclude that preservation of cortical thickness in old age is a foundation for successful cognitive aging when, instead, it is a lifelong association. This being said, results should not be construed as meaning that all studies on aging require direct measures of childhood IQ, but as suggesting that proxy measures of prior cognitive function can be useful to take into consideration.

Effects of acute glucocorticoid blockade on metabolic dysfunction in patients with Type 2 diabetes with and without fatty liver.

To investigate the potential of therapies which reduce glucocorticoid action in patients with Type 2 diabetes we performed a randomized, double-blinded, placebo-controlled crossover study of acute glucocorticoid blockade, using the glucocorticoid receptor antagonist RU38486 (mifepristone) and cortisol biosynthesis inhibitor (metyrapone), in 14 men with Type 2 diabetes. Stable isotope dilution methodologies were used to measure the rates of appearance of glucose, glycerol, and free fatty acids (FFAs), including during a low-dose (10 mU·m⁻² ·min⁻¹) hyperinsulinemic clamp, and subgroup analysis was conducted in patients with high or low liver fat content measured by magnetic resonance spectroscopy (n = 7/group). Glucocorticoid blockade lowered fasting glucose and insulin levels and improved insulin sensitivity of FFA and glycerol turnover and hepatic glucose production. Among this population with Type 2 diabetes high liver fat was associated with hyperinsulinemia, higher fasting glucose levels, peripheral and hepatic insulin resistance, and impaired suppression of FFA oxidation and FFA and glycerol turnover during hyperinsulinemia. Glucocorticoid blockade had similar effects in those with and without high liver fat. Longer term treatments targeting glucocorticoid action may be useful in Type 2 diabetes with and without fatty liver.

Neuroticism, depressive symptoms and white-matter integrity in the Lothian Birth Cohort 1936.

BACKGROUND: Clinical depression is associated with reductions in white-matter integrity in several long tracts of the brain. The extent to which these findings are localized or related to depressive symptoms or personality traits linked to disease risk remains unclear. Method Members of the Lothian Birth Cohort 1936 (LBC936) were assessed in two waves at mean ages of 70 and 73 years. At wave 1, they underwent assessments of depressive symptoms and the personality traits of neuroticism and extraversion. Brain diffusion magnetic resonance imaging (MRI) data were obtained at the second wave and mood assessments were repeated. We tested whether depressive symptoms were related to reduced white-matter tract fractional anisotropy (FA), a measure of integrity, and then examined whether high neuroticism or low extraversion mediated this relationship. RESULTS: Six hundred and sixty-eight participants provided useable data. Bilateral uncinate fasciculus FA was significantly negatively associated with depressive symptoms at both waves (standardized ß=0.12-0.16). Higher neuroticism and lower extraversion were also significantly associated with lower uncinate FA bilaterally (standardized ß=0.09-0.15) and significantly mediated the relationship between FA and depressive symptoms. CONCLUSIONS: Trait liability to depression and depressive symptoms are associated with reduced structural connectivity in tracts connecting the prefrontal cortex with the amygdala and anterior temporal cortex. These effects suggest that frontotemporal disconnection is linked to the etiology of depression, in part through personality trait differences.

Brain white matter tract integrity as a neural foundation for general intelligence.

General intelligence is a robust predictor of important life outcomes, including educational and occupational attainment, successfully managing everyday life situations, good health and longevity. Some neuronal correlates of intelligence have been discovered, mainly indicating that larger cortices in widespread parieto-frontal brain networks and efficient neuronal information processing support higher intelligence. However, there is a lack of established associations between general intelligence and any basic structural brain parameters that have a clear functional meaning. Here, we provide evidence that lower brain-wide white matter tract integrity exerts a substantial negative effect on general intelligence through reduced information-processing speed. Structural brain magnetic resonance imaging scans were acquired from 420 older adults in their early 70s. Using quantitative tractography, we measured fractional anisotropy and two white matter integrity biomarkers that are novel to the study of intelligence: longitudinal relaxation time (T1) and magnetisation transfer ratio. Substantial correlations among 12 major white matter tracts studied allowed the extraction of three general factors of biomarker-specific brain-wide white matter tract integrity. Each was independently associated with general intelligence, together explaining 10% of the variance, and their effect was completely mediated by information-processing speed. Unlike most previously established neurostructural correlates of intelligence, these findings suggest a functionally plausible model of intelligence, where structurally intact axonal fibres across the brain provide the neuroanatomical infrastructure for fast information processing within widespread brain networks, supporting general intelligence.

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.

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 ß: -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.

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 ß: -0.201; 95% CI: [-0.36, -0.04]; pFDR = 0.022) and processing speed (-0.222; [-0.40, -0.04]; pFDR = 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; pFDR = 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.

Psychotic-like experiences, polygenic risk scores for schizophrenia, and structural properties of the salience, default mode, and central-executive networks in healthy participants from UK Biobank.

Schizophrenia is a highly heritable disorder with considerable phenotypic heterogeneity. Hallmark psychotic symptoms can be considered as existing on a continuum from non-clinical to clinical populations. Assessing genetic risk and psychotic-like experiences (PLEs) in non-clinical populations and their associated neurobiological underpinnings can offer valuable insights into symptom-associated brain mechanisms without the potential confounds of the effects of schizophrenia and its treatment. We leveraged a large population-based cohort (UKBiobank, N = 3875) including information on PLEs (obtained from the Mental Health Questionnaire (MHQ); UKBiobank Category: 144; N auditory hallucinations = 55, N visual hallucinations = 79, N persecutory delusions = 16, N delusions of reference = 13), polygenic risk scores for schizophrenia (PRSSZ) and multi-modal brain imaging in combination with network neuroscience. Morphometric (cortical thickness, volume) and water diffusion (fractional anisotropy) properties of the regions and pathways belonging to the salience, default-mode, and central-executive networks were computed. We hypothesized that these anatomical concomitants of functional dysconnectivity would be negatively associated with PRSSZ and PLEs. PRSSZ was significantly associated with a latent measure of cortical thickness across the salience network (r = -0.069, p = 0.010) and PLEs showed a number of significant associations, both negative and positive, with properties of the salience and default mode networks (involving the insular cortex, supramarginal gyrus, and pars orbitalis, pFDR < 0.050); with the cortical thickness of the insula largely mediating the relationship between PRSSZ and auditory hallucinations. Generally, these results are consistent with the hypothesis that higher genetic liability for schizophrenia is related to subtle disruptions in brain structure and may predispose to PLEs even among healthy participants. In addition, our study suggests that networks engaged during auditory hallucinations show structural associations with PLEs in the general population.

The effects of a neuregulin 1 variant on white matter density and integrity.

Theories of abnormal anatomical and functional connectivity in schizophrenia and bipolar disorder are supported by evidence from functional magnetic resonance imaging (MRI), structural MRI and diffusion tensor imaging (DTI). The presence of similar abnormalities in unaffected relatives suggests such disconnectivity is genetically mediated, albeit through unspecified loci. Neuregulin 1 (NRG1) is a psychosis susceptibility gene with effects on neuronal migration, axon guidance and myelination that could potentially explain these findings. In the current study, unaffected subjects were genotyped at the NRG1 single nucleotide polymorphism (SNP) rs6994992 (SNP8NRG243177) locus, previously associated with increased risk for psychosis, and the effect of genetic variation at this locus on white matter density (T(1)-weighted MRI) and integrity (DTI) was ascertained. Subjects with the risk-associated TT genotype had reduced white matter density in the anterior limb of the internal capsule and evidence of reduced structural connectivity in the same region using DTI. We therefore provide the first imaging evidence that genetic variation in NRG1 is associated with reduced white matter density and integrity in human subjects. This finding is discussed in the context of NRG1 effects on neuronal migration, axon guidance and myelination.

A diffusion tensor MRI study of white matter integrity in subjects at high genetic risk of schizophrenia.

Diffusion tensor imaging (DTI) has previously shown compromised white matter integrity in frontotemporal white matter fibers in patients with schizophrenia, as indicated by reduced fractional anisotropy (FA). In the present study we investigated whether reduced white matter FA is also present in relatives of individuals with schizophrenia who are at high risk (HR) for genetic reasons. Twenty-two HR subjects, 31 patients with schizophrenia and 51 control subjects underwent DTI. We compared FA between the three groups in the cingulum cingulate gyri, the uncinate and the arcuate fasciculi and the anterior limb of the internal capsules (ALIC). A voxel-based analysis showed lower FA in patients with schizophrenia compared to controls in left and right uncinate (p<0.03), the left arcuate (p<0.03) and left and right ALIC (p<0.01). Using an automatic region-of-interest analysis, less sensitive to potential misregistration errors, produced essentially the same results, as well as reduced FA of the ALIC in the HR group compared to controls (p<0.05). This study replicates previous findings showing lower FA in frontotemporal white matter fibers of schizophrenia patients. We also found reduced FA in the ALIC of both patients and subjects at high risk of schizophrenia when compared to controls. This may be a possible indicator of the higher vulnerability of relatives to develop the disorder.

Anatomical flow phantoms of the nonplanar carotid bifurcation, part I: computer-aided design and fabrication.

Doppler ultrasound is widely used in the diagnosis and monitoring of arterial disease. Current clinical measurement systems make use of continuous and pulsed ultrasound to measure blood flow velocity; however, the uncertainty associated with these measurements is great, which has serious implications for the screening of patients for treatment. Because local blood flow dynamics depend to a great extent on the geometry of the affected vessels, there is a need to develop anatomically accurate arterial flow phantoms with which to assess the accuracy of Doppler blood flow measurements made in diseased vessels. In this paper, we describe the computer-aided design and manufacturing (CAD-CAM) techniques that we used to fabricate anatomical flow phantoms based on images acquired by time-of-flight magnetic resonance imaging (TOF-MRI). Three-dimensional CAD models of the carotid bifurcation were generated from data acquired from sequential MRI slice scans, from which solid master patterns were made by means of stereolithography. Thereafter, an investment casting procedure was used to fabricate identical flow phantoms for use in parallel experiments involving both laser and Doppler ultrasound measurement techniques.

Association of polygenic risk for major psychiatric illness with subcortical volumes and white matter integrity in UK Biobank.

Major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BP) are common, disabling and heritable psychiatric diseases with a complex overlapping polygenic architecture. Individuals with these disorders, as well as their unaffected relatives, show widespread structural differences in corticostriatal and limbic networks. Structural variation in many of these brain regions is also heritable and polygenic but whether their genetic architecture overlaps with that of major psychiatric disorders is unknown. We sought to address this issue by examining the impact of polygenic risk of MDD, SCZ, and BP on subcortical brain volumes and white matter (WM) microstructure in a large single sample of neuroimaging data; the UK Biobank Imaging study. The first release of UK Biobank imaging data comprised participants with overlapping genetic data and subcortical volumes (N = 978) and WM measures (N = 816). The calculation of polygenic risk scores was based on genome-wide association study results generated by the Psychiatric Genomics Consortium. Our findings indicated no statistically significant associations between either subcortical volumes or WM microstructure, and polygenic risk for MDD, SCZ or BP. These findings suggest that subcortical brain volumes and WM microstructure may not be closely linked to the genetic mechanisms of major psychiatric disorders.