Ageing and brain white matter structure in 3,513 UK Biobank participants

Prevalence and Risk Factors of Cerebral Microbleeds: Analysis From the UK Biobank

BACKGROUND AND OBJECTIVES

To determine the prevalence of and risk factors for cerebral microbleeds (CMBs) at different locations in a large healthy community population.

METHODS

A total of 8,159 participants from the UK Biobank with MRI scans suitable for CMB analysis were included. Brain susceptibility-weighted imaging data were acquired on 2 identical 3.0T scanners. The Microbleed Anatomical Rating Scale was used to identify definite CMBs. Generalized linear models were used to determine independent associations with all CMBs and lobar, deep, and infratentorial CMBs.

RESULTS

The mean age at scan was 62.1 ± 7.4 years. One or more definite CMBs were detected in 572 (7.0%) participants. Of those with CMBs, 439 (76.7%) had lobar CMBs, 103 (18.0%) had deep CMBs, and 83 (14.5%) had infratentorial CMBs. Age was an independent risk factor for CMBs in all locations. APOE4 and male sex were positively associated and higher body mass index was negatively associated with lobar CMBs. Hypertension, smoking, and alcohol consumption were associated with deep CMBs, but not with lobar CMBs. Only age was associated with infratentorial CMBs. The associations were unchanged after controlling for white matter hyperintensity lesion volume as a marker of small vessel disease severity.

DISCUSSION

In this large population-based study, CMB prevalence detected using a low sensitivity and high specificity system was 7%. There were distinct risk factor profiles for CMBs in lobar and deep locations consistent with different underlying pathophysiologic processes.

TRIAL REGISTRATION INFORMATION

Clinical Trial registration number: UK Biobank application number 19463.

Reliability of the freehand region-of-interest method in quantitative cerebral diffusion tensor imaging

Background

Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique used for evaluating changes in the white matter in brain parenchyma. The reliability of quantitative DTI analysis is influenced by several factors, such as the imaging protocol, pre-processing and post-processing methods, and selected diffusion parameters. The region-of-interest (ROI) method is most widely used of the post-processing methods because it is found in commercial software. The focus of our research was to study the reliability of the freehand ROI method using various intra- and inter-observer analyses.

Methods

This study included 40 neurologically healthy participants who underwent diffusion MRI of the brain with a 3 T scanner. The measurements were performed at nine different anatomical locations using a freehand ROI method. The data extracted from the ROIs included the regional mean values, intra- and inter-observer variability and reliability. The used DTI parameters were fractional anisotropy (FA), the apparent diffusion coefficient (ADC), and axial (AD) and radial (RD) diffusivity.

Results

The average intra-class correlation coefficient (ICC) of the intra-observer was found to be 0.9 (excellent). The single ICC results were excellent (> 0.8) or adequate (> 0.69) in eight out of the nine regions in terms of FA and ADC. The most reliable results were found in the frontobasal regions. Significant differences between age groups were also found in the frontobasal regions. Specifically, the FA and AD values were significantly higher and the RD values lower in the youngest age group (18–30 years) compared to the other age groups.

Conclusions

The quantitative freehand ROI method can be considered highly reliable for the average ICC and mostly adequate for the single ICC. The freehand method is suitable for research work with a well-experienced observer. Measurements should be performed at least twice in the same region to ensure that the results are sufficiently reliable. In our study, reliability was slightly undermined by artifacts in some regions such as the cerebral peduncle and centrum semiovale. From a clinical point of view, the results are most reliable in adults under the age of 30, when age-related changes in brain white matter have not yet occurred.

Differential Associations of White Matter Brain Age With Language-Related Mechanisms in Word-Finding Ability Across the Adult Lifespan

Research on cognitive aging has established that word-finding ability declines progressively in late adulthood, whereas semantic mechanism in the language system is relatively stable. The aim of the present study was to investigate the associations of word-finding ability and language-related components with brain aging status, which was quantified by using the brain age paradigm. A total of 616 healthy participants aged 18–88 years from the Cambridge Centre for Ageing and Neuroscience databank were recruited. The picture-naming task was used to test the participants’ language-related word retrieval ability through word-finding and word-generation processes. The naming response time (RT) and accuracy were measured under a baseline condition and two priming conditions, namely phonological and semantic priming. To estimate brain age, we established a brain age prediction model based on white matter (WM) features and estimated the modality-specific predicted age difference (PAD). Mass partial correlation analyses were performed to test the associations of WM-PAD with the cognitive performance measures under the baseline and two priming conditions. We observed that the domain-specific language WM-PAD and domain-general WM-PAD were significantly correlated with general word-finding ability. The phonological mechanism, not the semantic mechanism, in word-finding ability was significantly correlated with the domain-specific WM-PAD. In contrast, all behavioral measures of the conditions in the picture priming task were significantly associated with chronological age. The results suggest that chronological aging and WM aging have differential effects on language-related word retrieval functions, and support that cognitive alterations in word-finding functions involve not only the domain-specific processing within the frontotemporal language network but also the domain-general processing of executive functions in the fronto-parieto-occipital (or multi-demand) network. The findings further indicate that the phonological aspect of word retrieval ability declines as cerebral WM ages, whereas the semantic aspect is relatively resilient or unrelated to WM aging.

Accelerated Brain Aging in Mild Traumatic Brain Injury: Longitudinal Pattern Recognition with White Matter Integrity

Mild traumatic brain injury (mTBI) initiating long-term effects on white matter integrity resembles brain-aging changes, implying an aging process accelerated by mTBI. This longitudinal study aims to investigate the mTBI-induced acceleration of the brain-aging process by developing a neuroimaging model to predict brain age. The brain-age prediction model was defined using relevance vector regression based on fractional anisotropy from diffusion tensor imaging of 523 healthy individuals. The model was used to estimate the brain-predicted age difference (brain-PAD) between the chronological and estimated brain age in 116 acute mTBI patients and 63 healthy controls. Fifty patients were followed for 6 ∼ 12 months to evaluate the longitudinal changes in brain-PAD. We investigated whether brain-PAD was greater in patients of older age, post-concussion complaints, and apolipoprotein E (APOE) ɛ4 genotype, and whether it had the potential to predict neuropsychological outcomes. The brain-age prediction model predicted brain age accurately (r = 0.96). The brains of mTBI patients in the acute phase were estimated to be "older," with greater brain-PAD (2.59 ± 5.97 years) than the healthy controls (0.12 ± 3.19 years) (p < 0.05), and remained stable 6-12 month post-injury (2.50 ± 4.54 years). Patients who were older or who had post-concussion complaints, rather than APOE ɛ4 genotype, had greater brain-PADs (p < 0.001, p = 0.024). Additionally, brain-PAD in the acute phase predicted information processing speed at the 6 ∼ 12 month follow-up (r = -0.36, p = 0.01). In conclusion, mTBI accelerates the brain-aging process, and brain-PAD may be capable of evaluating aging-associated issues post-injury, such as increased risks of neurodegeneration.

Alterations in Diffusion Measures of White Matter Integrity Associated with Healthy Aging

This study aimed to characterize age-related white matter changes by evaluating patterns of overlap between the linear association of age with fractional anisotropy (FA) with mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). Specifically, we assessed patterns of overlap between diffusion measures of normal appearing white matter by covarying for white matter hyperintensity (WMH) load, as WMHs are thought to increase with age and impact diffusion measures. Seventy-nine healthy adults aged between 18 and 75 years took part in the study. Diffusion tensor imaging (DTI) data were based on 61 directions acquired with a b-value of 2,000. We found five main patterns of overlap: FA alone (15.95%); FA and RD (31.90%); FA and AD (12.99%); FA, RD, and AD (27.93%); and FA, RD, and MD (8.79%). We showed that cognitively healthy aging adults had low WMH load, which subsequently had minimal effect on diffusion measures. We discuss how patterns of overlap may reflect underlying biological changes observed with aging such as loss of myelination, axonal damage, as well as mild microstructural and chronic white matter impairments. This study contributes to understanding the underlying causes of degeneration in specific regions of the brain and highlights the importance of considering the impact of WMHs in aging studies of white matter.

A history of previous childbirths is linked to women's white matter brain age in midlife and older age

Maternal brain adaptations occur in response to pregnancy, but little is known about how parity impacts white matter and white matter ageing trajectories later in life. Utilising global and regional brain age prediction based on multi-shell diffusion-weighted imaging data, we investigated the association between previous childbirths and white matter brain age in 8,895 women in the UK Biobank cohort (age range = 54-81 years). The results showed that number of previous childbirths was negatively associated with white matter brain age, potentially indicating a protective effect of parity on white matter later in life. Both global white matter and grey matter brain age estimates showed unique contributions to the association with previous childbirths, suggesting partly independent processes. Corpus callosum contributed uniquely to the global white matter association with previous childbirths, and showed a stronger relationship relative to several other tracts. While our findings demonstrate a link between reproductive history and brain white matter characteristics later in life, longitudinal studies are required to establish causality and determine how parity may influence women's white matter trajectories across the lifespan.

Oligodendrocytes in the aging brain

More than half of the human brain volume is made up of white matter: regions where axons are coated in myelin, which primarily functions to increase the conduction speed of axon potentials. White matter volume significantly decreases with age, correlating with cognitive decline. Much research in the field of non-pathological brain aging mechanisms has taken a neuron-centric approach, with relatively little attention paid to other neural cells. This review discusses white matter changes, with focus on oligodendrocyte lineage cells and their ability to produce and maintain myelin to support normal brain homoeostasis. Improved understanding of intrinsic cellular changes, general senescence mechanisms, intercellular interactions and alterations in extracellular environment which occur with aging and impact oligodendrocyte cells is paramount. This may lead to strategies to support oligodendrocytes in aging, for example by supporting myelin synthesis, protecting against oxidative stress and promoting the rejuvenation of the intrinsic regenerative potential of progenitor cells. Ultimately, this will enable the protection of white matter integrity thus protecting cognitive function into the later years of life.

Alterations in Brain Network Organization in Adults With Obesity as Compared With Healthy-Weight Individuals and Seniors

OBJECTIVE

Life expectancy and obesity rates have drastically increased in recent years. An unhealthy weight is related to long-lasting medical disorders that might compromise the normal course of aging. The aim of the current study of brain connectivity patterns was to examine whether adults with obesity would show signs of premature aging, such as lower segregation, in large-scale networks.

METHODS

Participants with obesity (n = 30, mean age = 32.8 ± 5.68 years) were compared with healthy-weight controls (n = 33, mean age = 30.9 ± 6.24 years) and senior participants who were stroke-free and without dementia (n = 30, mean age = 67.1 ± 6.65 years) using resting-state magnetic resonance imaging and graph theory metrics (i.e., small-world index, clustering coefficient, characteristic path length, and degree).

RESULTS

Contrary to our hypothesis, participants with obesity exhibited a higher clustering coefficient compared with senior participants (t = 5.06, p < .001, d = 1.23, 95% CIbca = 0.64 to 1.88). Participants with obesity also showed lower global degree relative to seniors (t = -2.98, p = .014, d = -0.77, 95% CIbca = -1.26 to -0.26) and healthy-weight controls (t = -2.92, p = .019, d = -0.72, 95% CIbca = -1.19 to -0.25). Regional degree alterations in this group were present in several functional networks.

CONCLUSIONS

Participants with obesity displayed greater network clustering than did seniors and also had lower degree compared with seniors and individuals with normal weight, which is not consistent with the notion that obesity is associated with premature aging of the brain. Although the cross-sectional nature of the study precludes causal inference, the overly clustered network patterns in obese participants could be relevant to age-related changes in brain function because regular networks might be less resilient and metabolically inefficient.

The Relations Between Physical Activity Level, Executive Function, and White Matter Microstructure in Older Adults

The population of older adults is increasing, indicating a need to examine factors that may prevent or mitigate age-related cognitive decline. The current study examined whether microstructural white matter characteristics mediated the relation between physical activity and executive function in older adults without any self-reported psychiatric and neurological disorders or cognitive impairment (N = 43, mean age = 73 y). Physical activity was measured by average intensity and number of steps via accelerometry. Diffusion tensor imaging was used to examine microstructural white matter characteristics, and neuropsychological testing was used to examine executive functioning. Parallel mediation models were analyzed using microstructural white matter regions of interest as mediators of the association between physical activity and executive function. Results indicated that average steps was significantly related to executive function (β = 0.0003, t = 2.829, P = .007), while moderate to vigorous physical activity was not (β = 0.0007, t = 1.772, P = .08). White matter metrics did not mediate any associations. This suggests that microstructural white matter characteristics alone may not be the mechanism by which physical activity impacts executive function in aging.

Age-Related Variations in Regional White Matter Volumetry and Microstructure During the Post-adolescence Period: A Cross-Sectional Study of a Cohort of 1,713 University Students

Human brain white matter undergoes a protracted maturation that continues well into adulthood. Recent advances in diffusion-weighted imaging (DWI) methods allow detailed characterizations of the microstructural architecture of white matter, and they are increasingly utilized to study white matter changes during development and aging. However, relatively little is known about the late maturational changes in the microstructural architecture of white matter during post-adolescence. Here we report on regional changes in white matter volume and microstructure in young adults undergoing university-level education. As part of the MRi-Share multi-modal brain MRI database, multi-shell, high angular resolution DWI data were acquired in a unique sample of 1,713 university students aged 18-26. We assessed the age and sex dependence of diffusion metrics derived from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) in the white matter regions as defined in the John Hopkins University (JHU) white matter labels atlas. We demonstrate that while regional white matter volume is relatively stable over the age range of our sample, the white matter microstructural properties show clear age-related variations. Globally, it is characterized by a robust increase in neurite density index (NDI), and to a lesser extent, orientation dispersion index (ODI). These changes are accompanied by a decrease in diffusivity. In contrast, there is minimal age-related variation in fractional anisotropy. There are regional variations in these microstructural changes: some tracts, most notably cingulum bundles, show a strong age-related increase in NDI coupled with decreases in radial and mean diffusivity, while others, mainly cortico-spinal projection tracts, primarily show an ODI increase and axial diffusivity decrease. These age-related variations are not different between males and females, but males show higher NDI and ODI and lower diffusivity than females across many tracts. These findings emphasize the complexity of changes in white matter structure occurring in this critical period of late maturation in early adulthood.

A single mode of population covariation associates brain networks structure and behavior and predicts individual subjects' age

Multiple human behaviors improve early in life, peaking in young adulthood, and declining thereafter. Several properties of brain structure and function progress similarly across the lifespan. Cognitive and neuroscience research has approached aging primarily using associations between a few behaviors, brain functions, and structures. Because of this, the multivariate, global factors relating brain and behavior across the lifespan are not well understood. We investigated the global patterns of associations between 334 behavioral and clinical measures and 376 brain structural connections in 594 individuals across the lifespan. A single-axis associated changes in multiple behavioral domains and brain structural connections (r = 0.5808). Individual variability within the single association axis well predicted the age of the subject (r = 0.6275). Representational similarity analysis evidenced global patterns of interactions across multiple brain network systems and behavioral domains. Results show that global processes of human aging can be well captured by a multivariate data fusion approach.

Structural impairments in hippocampal and occipitotemporal networks specifically contribute to decline in place and face category processing but not to other visual object categories in healthy aging

BACKGROUND

Functional neuroimaging studies have identified a set of nodes in the occipital-temporal cortex that preferentially respond to faces in comparison with other visual objects. By contrast, the processing of places seems to rely on parahippocampal cortex and structures heavily implicated in memory (e.g., the hippocampus). It has been suggested that human aging leads to decreased neural specialization of core face and place processing areas and impairments in face and place perception.

METHODS

Using mediation analysis, we tested the potential contribution of micro- and macrostructure within the hippocampal and occipitotemporal systems to age-associated effects in face and place category processing (as measured by 1-back working memory tasks) in 55 healthy adults (age range 23-79 years). To test for specific contributions of the studied structures to face/place processing, we also studied a distinct tract (i.e., the anterior thalamic radiation [ATR]) and cognitive performance for other visual object categories (objects, bodies, and verbal material). Constrained spherical deconvolution-based tractography was used to reconstruct the fornix, the inferior longitudinal fasciculus (ILF), and the ATR. Hippocampal volumetric measures were segmented from FSL-FIRST toolbox.

RESULTS

It was found that age associates with (a) decreases in fractional anisotropy (FA) in the fornix, in right ILF (but not left ILF), and in the ATR (b) reduced volume in the right and left hippocampus and (c) decline in visual object category processing. Importantly, mediation analysis showed that micro- and macrostructural impairments in the fornix and right hippocampus, respectively, associated with age-dependent decline in place processing. Alternatively, microstructural impairments in right hemispheric ILF associated with age-dependent decline in face processing. There were no other mediator effects of micro- and macrostructural variables on age-cognition relationships.

CONCLUSION

Together, the findings support specific contributions of the fornix and right hippocampus in visuospatial scene processing and of the long-range right hemispheric occipitotemporal network in face category processing.

Brain-age in midlife is associated with accelerated biological aging and cognitive decline in a longitudinal birth cohort

An individual's brainAGE is the difference between chronological age and age predicted from machine-learning models of brain-imaging data. BrainAGE has been proposed as a biomarker of age-related deterioration of the brain. Having an older brainAGE has been linked to Alzheimer's, dementia, and mortality. However, these findings are largely based on cross-sectional associations which can confuse age differences with cohort differences. To illuminate the validity of brainAGE as a biomarker of accelerated brain aging, a study is needed of a large cohort all born in the same year who nevertheless vary on brainAGE. In the Dunedin Study, a population-representative 1972-73 birth cohort, we measured brainAGE at age 45 years, as well as the pace of biological aging and cognitive decline in longitudinal data from childhood to midlife (N = 869). In this cohort, all chronological age 45 years, brainAGE was measured reliably (ICC = 0.81) and ranged from 24 to 72 years. Those with older midlife brainAGEs tended to have poorer cognitive function in both adulthood and childhood, as well as impaired brain health at age 3. Furthermore, those with older brainAGEs had an accelerated pace of biological aging, older facial appearance, and early signs of cognitive decline from childhood to midlife. These findings help to validate brainAGE as a potential surrogate biomarker for midlife intervention studies that seek to measure dementia-prevention efforts in midlife. However, the findings also caution against the assumption that brainAGE scores represent only age-related deterioration of the brain as they may also index central nervous system variation present since childhood.

Large-scale GWAS reveals genetic architecture of brain white matter microstructure and genetic overlap with cognitive and mental health traits (n = 17,706)

Individual variations of white matter (WM) tracts are known to be associated with various cognitive and neuropsychiatric traits. Diffusion tensor imaging (DTI) and genome-wide single-nucleotide polymorphism (SNP) data from 17,706 UK Biobank participants offer the opportunity to identify novel genetic variants of WM tracts and explore the genetic overlap with other brain-related complex traits. We analyzed the genetic architecture of 110 tract-based DTI parameters, carried out genome-wide association studies (GWAS), and performed post-GWAS analyses, including association lookups, gene-based association analysis, functional gene mapping, and genetic correlation estimation. We found that DTI parameters are substantially heritable for all WM tracts (mean heritability 48.7%). We observed a highly polygenic architecture of genetic influence across the genome (p value = 1.67 × 10^-05) as well as the enrichment of genetic effects for active SNPs annotated by central nervous system cells (p value = 8.95 × 10^-12). GWAS identified 213 independent significant SNPs associated with 90 DTI parameters (696 SNP-level and 205 locus-level associations; p value < 4.5 × 10^-10, adjusted for testing multiple phenotypes). Gene-based association study prioritized 112 significant genes, most of which are novel. More importantly, association lookups found that many of the novel SNPs and genes of DTI parameters have previously been implicated with cognitive and mental health traits. In conclusion, the present study identifies many new genetic variants at SNP, locus and gene levels for integrity of brain WM tracts and provides the overview of pleiotropy with cognitive and mental health traits.

The effect of vascular health factors on white matter microstructure mediates age-related differences in executive function performance

Even within healthy aging, vascular risk factors can detrimentally influence cognition, with executive functions (EF) particularly vulnerable. Fronto-parietal white matter (WM) connectivity in part, supports EF and may be particularly sensitive to vascular risk. Here, we utilized structural equation modeling in 184 healthy adults (aged 20-94 years of age) to test the hypotheses that: 1) fronto-parietal WM microstructure mediates age effects on EF; 2) higher blood pressure (BP) and white matter hyperintensity (WMH) burden influences this association. All participants underwent comprehensive cognitive and neuropsychological testing including tests of processing speed, executive function (with a focus on tasks that require switching and inhibition) and completed an MRI scanning session that included FLAIR imaging for semi-automated quantification of white matter hyperintensity burden and diffusion-weighted imaging for tractography. Structural equation models were specified with age (as a continuous variable) and blood pressure predicting within-tract WMH burden and fractional anisotropy predicting executive function and processing speed. Results indicated that fronto-parietal white matter of the genu of the corpus collosum, superior longitudinal fasciculus, and the inferior frontal occipital fasciculus (but not cortico-spinal tract) mediated the association between age and EF. Additionally, increased systolic blood pressure and white matter hyperintensity burden within these white matter tracts contribute to worsening white matter health and are important factors underlying age-brain-behavior associations. These findings suggest that aging brings about increases in both BP and WMH burden, which may be involved in the degradation of white matter connectivity and in turn, negatively impact executive functions as we age.

Neurite Imaging Reveals Widespread Alterations in Gray and White Matter Neurite Morphology in Healthy Aging and Amnestic Mild Cognitive Impairment

Aging is the major risk factor for neurodegenerative diseases and affects neurite distributions throughout the brain, yet underlying neurobiological mechanisms remain unclear. Multi-shell diffusion-weighted imaging and neurite orientation dispersion and density imaging (NODDI) now provide in vivo biophysical measurements that explain these biological processes in the cortex and white matter. In this study, neurite distributions were evaluated in the cortex and white matter in healthy older adults and patients with amnestic mild cognitive impairment (aMCI) that provides fundamental contributions regarding healthy aging and neurodegeneration. Older age was associated with reduced neurite density and neurite orientation dispersion (ODI) in widespread cortical regions. In contrast, increased ODI was only observed in the right thalamus and hippocampus with age. For the first time, we also reported a widespread age-associated decrease in neurite density along major white matter tracts correlated with decreased cortical neurite density in the tract endpoints in healthy older adults. We further examined alterations in cortical and white matter neurite microstructures in aMCI patients and found significant neurite morphology deficits in memory networks correlated with memory performance. Our findings indicate that neurite parameters provide valuable information regarding cortical and white matter microstructure and complement myeloarchitectural information in healthy aging and aMCI.

The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students

We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1870 young healthy adults, aged 18-35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility-weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early ageing.

Distant histories of mild traumatic brain injury exacerbate age-related differences in white matter properties

We examined associations of distant histories of mild traumatic brain injury (mTBI) with non-linear and linear trajectories of white matter (WM) properties across a wide age range (23-77). Diffusion tensor imaging (DTI) data obtained from 171 Veterans with histories of clinically diagnosed mTBIs and 115 controls were subjected to tractography, isolating 20 major WM tracts. Non-linear and linear effects of age on each tract's diffusion properties were examined in terms of their interactions with group (mTBI and control). The non-linear model revealed 7 tracts in which the mTBI group's DTI metrics rapidly deviated from control trajectories in middle and late adulthoods, despite the injuries having occurred in the late 20s, on average. In contrast, no interactions between prior injuries and age were detected when examining linear trajectories. Distant mTBIs may thus accelerate normal age-related trajectories of WM degeneration much later in life. As such, life-long histories of head trauma should be assessed in all patients in their mid-to-late adulthoods, whether neurologically healthy or presenting with seemingly unrelated neuropathology.

Supplementary and Premotor Aspects of the Corticospinal Tract Show Links with Restricted and Repetitive Behaviors in Middle-Aged Adults with Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) show motor impairment into adulthood and risk decline during aging, but little is known about brain changes in aging adults with ASD. Few studies of ASD have directly examined the corticospinal tract (CST)-the major descending pathway in the brain responsible for voluntary motor behavior-outside its primary motor (M1) connections. In 26 middle-aged adults with ASD and 26 age-matched typical comparison participants, we used diffusion imaging to examine the microstructure and volume of CST projections from M1, dorsal premotor (PMd), supplementary motor area (SMA), and primary somatosensory (S1) cortices with respect to age. We also examined relationships between each CST sub-tract (-cst), motor skills, and autism symptoms. We detected no significant group or age-related differences in tracts extending from M1 or other areas. However, sub-tracts of the CST extending from secondary (but not primary) motor areas were associated with core autism traits. Increased microstructural integrity of left PMd-cst and SMA-cst were associated with less-severe restricted and repetitive behaviors (RRB) in the ASD group. These findings suggest that secondary motor cortical areas, known to be involved in selecting motor programs, may be implicated in cognitive motor processes underlying RRB in ASD.

Age affects white matter microstructure and episodic memory across the older adult lifespan

Diffusion imaging studies have observed age-related degradation of white matter that contributes to cognitive deficits separately in younger-old (ages 65-89) and oldest-old (ages 90+) adults. But it remains unclear whether these age effects are magnified in advanced age groups, which may reflect disease-related pathology. Here, we tested whether age-related differences in white matter microstructure followed linear or nonlinear patterns across the entire older adult lifespan (65-98 years), these patterns were influenced by oldest-old adults at increased risk of dementia (cognitive impairment no dementia, CIND), and they explained age effects on episodic memory. Results revealed nonlinear microstructure declines across fiber classes (medial temporal, callosal, association, projection and/or thalamic) that were largest for medial temporal fibers. These patterns remained after excluding oldest-old participants with CIND, indicating that aging of white matter microstructure cannot solely be explained by pathology associated with early cognitive impairment. Moreover, finding that the effect of age on episodic memory was mediated by medial temporal fiber microstructure suggests it is essential for facilitating memory-related neural signals across the older adult lifespan.

Effect of Aerobic Exercise on White Matter Tract Microstructure in Young and Middle-Aged Healthy Adults

Recent evidence suggests that being physically active can mitigate age-related white matter (WM) changes. In a randomized clinical trial, the effect of 6-month aerobic exercise (AE) or stretching/toning interventions on measures of WM microstructure (WMM) was assessed in a sample of 74 adults aged 20-67 years. Major WM pathways were reconstructed. No significant group-level change in WM tract microstructure following an AE training was observed. Without adjustment for multiple comparisons, an increase in fractional anisotropy (FA) and a decrease in mean diffusivity (MD) of the uncinate fasciculus were observed post-intervention in the AE group in comparison with the stretching group. In the AE group, a significant increase in cardiorespiratory fitness was measured but did not correlate with FA and MD change. The present results of this study are in accordance with similar studies in healthy adults that did not show significant benefit on WMM after participating in an AE program. Clinical Trial Registration: Clinicaltrials.gov identifier, NCT01179958.

Associations of perceived adverse lifetime experiences with brain structure in UK Biobank participants

BACKGROUND

Adversity experiences (AEs) are major risk factors for psychiatric illness, and ample evidence suggests that adversity-related changes in brain structure enhance this vulnerability. To achieve greater understanding of the underlying biological pathways, increased convergence among findings is needed. Suggested future directions may benefit from the use of large population samples which may contribute to achieving this goal. We addressed mechanistic pathways by investigating the associations between multiple brain phenotypes and retrospectively reported AEs in early life (child adversity) and adulthood (partner abuse) in a large population sample, using a cross-sectional approach.

METHODS

The UK Biobank resource was used to access imaging-derived phenotypes (IDPs) from 6,751 participants (aged: M = 62.1, SD = 7.2, range = 45-80), together with selected reports of childhood AEs and adult partner abuse. Principal component analysis was used to reduce the dimensionality of the data prior to multivariate tests.

RESULTS

The data showed that participants who reported experiences of childhood emotional abuse ('felt hated by family member as a child') had smaller cerebellar and ventral striatum volumes. This result was also depicted in a random subset of participants; however, we note small effect sizes ( ηp2  < .01), suggestive of modest biological changes.

CONCLUSIONS

Using a large population cohort, this study demonstrates the value of big datasets in the study of adversity and using automatically preprocessed neuroimaging phenotypes. While retrospective and cross-sectional characteristics limit interpretation, this study demonstrates that self-perceived adversity reports, however nonspecific, may still expose neural consequences, identifiable with increased statistical power.

Differential Age Trajectories of White Matter Changes Between Sexes Correlate with Cognitive Performances

Background: Aging is accompanied by a gradual deterioration in multiple cognitive abilities and brain structures. Both cognitive function and white matter (WM) structure are found to be associated with neurodegeneration diseases and correlated with sex during aging. However, it is still unclear whether the brain structural change could be attributable to sex, and how sex would affect cognitive performances during aging. Materials and Methods: Diffusion magnetic resonance imaging (MRI) scans were performed on 1127 healthy participants (age range: 21-89) at a single site. The age trajectories of the WM tract microstructure were delineated to estimate the turning age and changing rate between sexes. The canonical correlation analysis and moderated mediation analysis were used to examine the relationship between sex-linked WM tracts and cognitive performances. Results: The axon intactness and demyelination of sex-linked tracts during aging were multifaceted. Sex-linked tracts in females peak around 5 years later than those in males but change significantly faster after the turning age. Projection and association tracts (e.g., corticospinal tracts and parahippocampal cingulum) contributed to a significant decrease in visuospatial functions (VS) and executive functions (E). We discovered that there is a stronger indirect effect of sex-linked tracts on cognitive functions in females than in males. Conclusion: Our findings suggest that the vulnerable projection and association tracts in females may induce negative impacts on integrating multiple functions, which results in a faster decrease in VS and E.

Selective Effects of Healthy Cognitive Aging and Catechol-O-Methyl Transferase Polymorphism on Limbic White Matter Tracts

Introduction: The cingulum bundle and uncinate fasciculus are major limbic white matter tracts involved in emotion, memory, and cognition. The main goal of the present study was to investigate the relationship between age and structural properties of the uncinate fasciculus and the cingulum bundle using diffusion tensor imaging (DTI) tractography in a large cohort of healthy individuals. The second goal was to determine the effects of the catechol-O-methyl transferase (COMT) gene polymorphism on the DTI measurements of these white matter tracts. Methods: We recruited 140 healthy participants (18-85 years old). DTI data sets were acquired on a 1.5T magnetic resonance imaging system. The rostral, dorsal, and parahippocampal cingulum, as well as uncinate fasciculus, were delineated using deterministic tractography. Fractional anisotropy (FA), mean (MD), radial (RD), and axial (AD) diffusivities, tract volume, linear (C_l), planar (C_p), and spherical (C_s) tensor shapes were calculated. The COMT polymorphism (methionine homozygous vs. valine carriers) was determined using single nucleotide polymorphism. Results: We found that age was negatively associated with FA, but positively associated with MD and RD for the rostral cingulum, dorsal cingulum, and the uncinate fasciculus but not for the parahippocampal cingulum. Furthermore, individuals with the COMT methionine homozygous had higher FA and lower MD, RD, AD, and C_s values in the right rostral cingulum compared with the valine carriers across the entire adult life span. Discussion: This study indicates that limbic tracts might be nonuniformly affected by healthy aging, and the methionine homozygous genotype might be associated with micro/macro white matter properties of the right rostral cingulum.

[A review on the application of UK Biobank in neuroimaging]

UK Biobank (UKB) is a forward-looking epidemiological project with over 500, 000 people aged 40 to 69, whose image extension project plans to re-invite 100, 000 participants from UKB to perform multimodal brain magnetic resonance imaging. Large-scale multimodal neuroimaging combined with large amounts of phenotypic and genetic data provides great resources to conduct brain health-related research. This article provides an in-depth overview of UKB in the field of neuroimaging. Firstly, neuroimage collection and imaging-derived phenotypes are summarized. Secondly, typical studies of UKB in neuroimaging areas are introduced, which include cardiovascular risk factors, regulatory factors, brain age prediction, normality, successful and morbid brain aging, environmental and genetic factors, cognitive ability and gender. Lastly, the open challenges and future directions of UKB are discussed. This article has the potential to open up a new research field for the prevention and treatment of neurological diseases.

Fractional Anisotropy in Selected, Motor-Related White Matter Tracts and Its Cross-Sectional and Longitudinal Associations With Motor Function in Healthy Older Adults

Background

While it is well-known that deficits in motor performance and brain structural connectivity occur in the course of healthy aging, it is still unclear if and how these changes are related to each other. While some cross-sectional studies suggest that white matter (WM) microstructure is positively associated with motor function in healthy older adults, more evidence is needed. Moreover, longitudinal data is required to estimate whether similar associations can be found between trajectories of change in WM microstructure and motor function. The current study addresses this gap by investigating age-associations and longitudinal changes in WM microstructure and motor function, and the cross-sectional (level-level) and longitudinal (level-change, change-change) association between these two domains.

Method

We used multiple-occasion data (covering 4 years) from a large sample (N = 231) of healthy older adults from the Longitudinal Healthy Aging Brain (LHAB) database. To measure WM microstructure, we used diffusion-weighted imaging data to compute mean FA in three selected WM tracts [forceps minor (FMIN); superior longitudinal fasciculus (SLF); corticospinal tract (CST)]. Motor function was measured via two motor speed tests (grooved pegboard, finger tapping) and one motor strength test (grip force test), separately for the left and the right hand. The statistical analysis was conducted with longitudinal growth curve models in the structural equation modeling framework.

Results

The results revealed longitudinal decline and negative cross-sectional age-associations for mean WM FA in the FMIN and SLF, and for motor function in all tests, with a higher vulnerability for left than right hand motor performance. Regarding cross-domain associations, we found a significant positive level-level correlation among mean WM FA in the FMIN with motor speed. Mean FA in SLF and CST was not correlated with motor performance measures, and none of the level-change or change-change associations were significant. Overall, our results (a) provide important insights into aging-related changes of fine motor abilities and FA in selected white matter tracts associated with motor control, (b) support previous cross-sectional work showing that neural control of movement in older adults also involves brain structures outside the core motor system and (c) align with the idea that, in healthy aging, compensatory mechanisms may be in place and longer time delays may be needed to reveal level-change or change-change associations.

Age-Related Alterations in DTI Metrics in the Human Brain-Consequences for Age Correction

Background: Over the life span, the diffusion metrics in brain MRI show different, partly nonlinear changes. These age-dependent changes also seem to exhibit regional differences with respect to the brain anatomy. The age correction of a study cohort's diffusion metrics might thus require consideration of age-related factors. Methods: Diffusion tensor imaging data sets were acquired from 219 healthy participants at ages between 19 and 81 years. Fractional anisotropy (FA), mean diffusivity (MD), and axial and radial diffusivity (AD and RD, respectively) maps were analyzed by a tract of interest-based fiber tracking approach. To describe diffusion metrics as a function of the participant age, linear splines were used to perform curve fitting in 21 specific tract systems covering different functional areas and diffusion directions. Results: In the majority of tracts, an interpolation with a change of alteration rate during adult life described the diffusion properties more accurately than a linear model. Consequently, the diffusion properties remained relatively stable until a decrease (of FA) or increase (of MD, AD, and RD) started at a region-specific time point, whereas a uniform change of diffusion properties was observed only in a few tracts. Single tracts, e.g., located in the cerebellum, remained nearly unaltered throughout the ages between 19 and 81 years. Conclusions: Age corrections of diffusion properties should not be applied to all white matter regions and all age spans in the same way. Therefore, we propose three different approaches for age correction based on fiber tracking techniques, i.e., no correction for areas that do not experience age-related changes and two variants of an age correction depending on the age range of the cohort and the tracts considered.

Age- and gender-related differences in brain tissue microstructure revealed by multi-component T2 relaxometry

In spite of extensive work, inconsistent findings and lack of specificity in most neuroimaging techniques used to examine age- and gender-related patterns in brain tissue microstructure indicate the need for additional research. Here, we performed the largest Multi-component T₂ relaxometry cross-sectional study to date in healthy adults (N = 145, 18-60 years). Five quantitative microstructure parameters derived from various segments of the estimated T₂ spectra were evaluated, allowing a more specific interpretation of results in terms of tissue microstructure. We found similar age-related myelin water fraction (MWF) patterns in men and women but we also observed differential male related results including increased MWF content in a few white matter tracts, a faster decline with age of the intra- and extra-cellular water fraction and its T₂ relaxation time (i.e. steeper age related negative slopes) and a faster increase in the free and quasi-free water fraction, spanning the whole grey matter. Such results point to a sexual dimorphism in brain tissue microstructure and suggest a lesser vulnerability to age-related changes in women.

Beyond fingerprinting: Choosing predictive connectomes over reliable connectomes

Recent years have seen a surge of research on variability in functional brain connectivity within and between individuals, with encouraging progress toward understanding the consequences of this variability for cognition and behavior. At the same time, well-founded concerns over rigor and reproducibility in psychology and neuroscience have led many to question whether functional connectivity is sufficiently reliable, and call for methods to improve its reliability. The thesis of this opinion piece is that when studying variability in functional connectivity-both across individuals and within individuals over time-we should use behavior prediction as our benchmark rather than optimize reliability for its own sake. We discuss theoretical and empirical evidence to compel this perspective, both when the goal is to study stable, trait-level differences between people, as well as when the goal is to study state-related changes within individuals. We hope that this piece will be useful to the neuroimaging community as we continue efforts to characterize inter- and intra-subject variability in brain function and build predictive models with an eye toward eventual real-world applications.

The Role of Thyroid Hormone in Neuronal Protection

Thyroid hormone is essential for brain development and brain function in the adult. During development, thyroid hormone acts in a spatial and temporal-specific manner to regulate the expression of genes essential for normal neural cell differentiation, migration, and myelination. In the adult brain, thyroid hormone is important for maintaining normal brain function. Thyroid hormone excess, hyperthyroidism, and thyroid hormone deficiency, hypothyroidism, are associated with disordered brain function, including depression, memory loss, impaired cognitive function, irritability, and anxiety. Adequate thyroid hormone levels are required for normal brain function. Thyroid hormone acts through a cascade of signaling components: activation and inactivation by deiodinase enzymes, thyroid hormone membrane transporters, and nuclear thyroid hormone receptors. Additionally, the hypothalamic-pituitary-thyroid axis, with negative feedback of thyroid hormone on thyrotropin-releasing hormone (TRH) and thyroid-stimulating hormone (TSH) secretion, regulates serum thyroid hormone levels in a narrow range. Animal and human studies have shown both systemic and local reduction in thyroid hormone availability in neurologic disease and after brain trauma. Treatment with thyroid hormone and selective thyroid hormone analogs has resulted in a reduction in injury and improved recovery. This article will describe the thyroid hormone signal transduction pathway in the brain and the role of thyroid hormone in the aging brain, neurologic diseases, and the protective role when administered after traumatic brain injury. © 2021 American Physiological Society. Compr Physiol 11:1-21, 2021.

Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition

White matter microstructure undergoes progressive changes during the lifespan, but the neurobiological underpinnings related to ageing and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging, to investigate the microstructural alterations due to demographics, common age-related pathological processes (amyloid, tau and white matter hyperintensities) and cognition. We also compared Neurite Orientation Dispersion and Density Imaging findings to the older Diffusion Tensor Imaging model-based findings. Three hundred and twenty-eight participants (264 cognitively unimpaired, 57 mild cognitive impairment and 7 dementia with a mean age of 68.3 ± 13.1 years) from the Mayo Clinic Study of Aging with multi-shell diffusion imaging, fluid attenuated inversion recovery MRI as well as amyloid and tau PET scans were included in this study. White matter tract level diffusion measures were calculated from Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, white matter hyperintensities, amyloid and tau as predictors. Analyses were also performed with each diffusion MRI measure as a predictor of cognitive outcomes. Age and white matter hyperintensities were the strongest predictors of all white matter diffusion measures with low associations with amyloid and tau. However, neurite density decrease from Neurite Orientation Dispersion and Density Imaging was observed with amyloidosis specifically in the temporal lobes. White matter integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures. All diffusion measures provided information about white matter ageing and white matter changes due to age-related pathological processes and were associated with cognition. Neurite orientation dispersion and density imaging and diffusion tensor imaging are two different diffusion models that provide distinct information about variation in white matter microstructural integrity. Neurite Orientation Dispersion and Density Imaging provides additional information about synaptic density, organization and free water content which may aid in providing mechanistic insights into disease progression.

Quantitative measurement of macromolecular tissue properties in white and gray matter in healthy aging and amnestic MCI

Healthy and pathological aging influence brain microstructure via complex processes. Discerning these processes requires measurements that are sensitive to specific biological properties of brain tissue. We integrated a novel quantitative R1 measure with multi-shell diffusion weighted imaging to map age-associated changes in macromolecular tissue volume (MTV) along major white matter tracts in healthy older adults and patients with amnestic Mild Cognitive Impairment (aMCI). Reduced MTV in association tracts was associated with older age in healthy aging, was correlated with memory performance, and distinguished aMCI from controls. We also mapped changes in gray matter tissue properties using quantitative R1 measurements. We documented a widespread decrease in R1 with advancing age across the cortex and decreased R1 in aMCI compared with controls in regions implicated in episodic memory. Our data are the first to characterize MTV loss along major white matter tracts in aMCI and suggest that qMRI is a sensitive measure for detecting subtle degeneration of white and gray matter tissue that cannot be detected by conventional MRI and diffusion measures.

Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fiber architecture

Diffusion tensor imaging (DTI) consistently detects increased mean diffusivity and decreased fractional anisotropy with advancing age in regions of primarily single white matter (WM) fiber populations, but findings have been inconsistent in regions of more complex fiber architecture. Given that DTI remains more common for characterizing aging WM than advanced diffusion MRI models due to DTI's simplicity, robustness, and efficiency, it is critical to strive to maximize the information extracted from DTI across the entire WM. The present study uses an orthogonal diffusion tensor decomposition based on the 3 eigenvalue moments (mean diffusivity, norm of anisotropy, and mode of anisotropy), yielding clear voxelwise degeneration patterns across the WM, including regions of complex fiber architecture. This indicates that the previous challenges of DTI in these regions were due to the choice of tensor decomposition rather than the DTI model itself. This study therefore presents a revised view of DTI of aging WM and indicates how age-related degeneration in complex fiber architecture can manifest in forms other than decreased fractional anisotropy.

Reorganization of brain structural networks in aging: A longitudinal study

Normal aging is characterized by structural and functional changes in the brain contributing to cognitive decline. Structural connectivity (SC) describes the anatomical backbone linking distinct functional subunits of the brain and disruption of this communication is thought to be one of the potential contributors for the age-related deterioration observed in cognition. Several studies already explored brain network's reorganization during aging, but most focused on average connectivity of the whole-brain or in specific networks, such as the resting-state networks. Here, we aimed to characterize longitudinal changes of white matter (WM) structural brain networks, through the identification of sub-networks with significantly altered connectivity along time. Then, we tested associations between longitudinal changes in network connectivity and cognition. We also assessed longitudinal changes in topological properties of the networks. For this, older adults were evaluated at two timepoints, with a mean interval time of 52.8 months (SD = 7.24). WM structural networks were derived from diffusion magnetic resonance imaging, and cognitive status from neurocognitive testing. Our results show age-related changes in brain SC, characterized by both decreases and increases in connectivity weight. Interestingly, decreases occur in intra-hemispheric connections formed mainly by association fibers, while increases occur mostly in inter-hemispheric connections and involve association, commissural, and projection fibers, supporting the last-in-first-out hypothesis. Regarding topology, two hubs were lost, alongside with a decrease in connector-hub inter-modular connectivity, reflecting reduced integration. Simultaneously, there was an increase in the number of provincial hubs, suggesting increased segregation. Overall, these results confirm that aging triggers a reorganization of the brain structural network.

Association between APOE e4 and white matter hyperintensity volume, but not total brain volume or white matter integrity

Apolipoprotein (APOE) e4 genotype is an accepted risk factor for accelerated cognitive aging and dementia, though its neurostructural substrates are unclear. The deleterious effects of this genotype on brain structure may increase in magnitude into older age. This study aimed to investigate in UK Biobank the association between APOE e4 allele presence vs. absence and brain imaging variables that have been associated with worse cognitive abilities; and whether this association varies by cross-sectional age. We used brain magnetic resonance imaging (MRI) and genetic data from a general-population cohort: the UK Biobank (N = 8395 after exclusions). We adjusted for the covariates of age in years, sex, Townsend social deprivation scores, smoking history and cardiometabolic diseases. There was a statistically significant association between APOE e4 genotype and increased (i.e. worse) white matter (WM) hyperintensity volumes (standardised beta = 0.088, 95% confidence intervals = 0.036 to 0.139, P = 0.001), a marker of poorer cerebrovascular health. There were no associations with left or right hippocampal, total grey matter (GM) or WM volumes, or WM tract integrity indexed by fractional anisotropy (FA) and mean diffusivity (MD). There were no statistically significant interactions with age. Future research in UK Biobank utilising intermediate phenotypes and longitudinal imaging hold significant promise for this area, particularly pertaining to APOE e4’s potential link with cerebrovascular contributions to cognitive aging.

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.

Neurovascular-glymphatic dysfunction and white matter lesions

Cerebral white matter lesions (WML) represent a spectrum of age-related structural changes that are identified as areas of white matter high signal intensity on brain magnetic resonance imaging (MRI). Preservation of white matter requires proper functioning of both the cerebrovascular and glymphatic systems. The cerebrovascular safeguards adequate cerebral blood flow to supply oxygen, energy, and nutrients through a dynamic process of cerebral autoregulation and neurovascular coupling to keep up with global and regional demands of the brain. The glymphatic system maintains white matter integrity by preserving flow of interstitial fluid, exchanging metabolic waste and eventually its clearance into the venous circulation. Here, we argue that these two systems should not be considered separate entities but as one single physiologically integrated unit to preserve brain health. Due to the process of aging, damage to the neurovascular-glymphatic system accumulates over the life course. It is an insidious process that ultimately leads to the disruption of cerebral autoregulation, to the neurovascular uncoupling, and to the accumulation of metabolic waste products. As cerebral white matter is particularly vulnerable to hypoxic, inflammatory, and metabolic insults, WML are the first recognized pathologies of neurovascular-glymphatic dysfunction. A better understanding of the underlying pathophysiology will provide starting points for developing effective strategies to prevent a wide range of clinical disorders among which there are gait disturbances, functional dependence, cognitive impairment, and dementia.

Working Memory Training Effects on White Matter Integrity in Young and Older Adults

OBJECTIVES

Working memory is essential for daily life skills like reading comprehension, reasoning, and problem-solving. Healthy aging of the brain goes along with working memory decline that can affect older people's independence in everyday life. Interventions in the form of cognitive training are a promising tool for delaying age-related working memory decline, yet the underlying structural plasticity of white matter is hardly studied.

METHODS

We conducted a longitudinal diffusion tensor imaging study to investigate the effects of an intensive four-week adaptive working memory training on white matter integrity quantified by global and tract-wise mean diffusivity. We compared diffusivity measures of fiber tracts that are associated with working memory of 32 young and 20 older participants that were randomly assigned to a working memory training group or an active control group.

RESULTS

The behavioral analysis showed an increase in working memory performance after the four-week adaptive working memory training. The neuroanatomical analysis revealed a decrease in mean diffusivity in the working memory training group after the training intervention in the right inferior longitudinal fasciculus for the older adults. There was also a decrease in mean diffusivity in the working memory training group in the right superior longitudinal fasciculus for the older and young participants after the intervention.

CONCLUSION

This study shows that older people can benefit from working memory training by improving their working memory performance that is also reflected in terms of improved white matter integrity in the superior longitudinal fasciculus and the inferior longitudinal fasciculus, where the first is an essential component of the frontoparietal network known to be essential in working memory.

Warped Bayesian Linear Regression for Normative Modelling of Big Data.. [PMID: 34798518 PMCID: PMC7613680 DOI: 10.1101/2021.04.05.438429]

Normative modelling is becoming more popular in neuroimaging due to its ability to make predictions of deviation from a normal trajectory at the level of individual participants. It allows the user to model the distribution of several neuroimaging modalities, giving an estimation for the mean and centiles of variation. With the increase in the availability of big data in neuroimaging, there is a need to scale normative modelling to big data sets. However, the scaling of normative models has come with several challenges.

So far, most normative modelling approaches used Gaussian process regression, and although suitable for smaller datasets (up to a few thousand participants) it does not scale well to the large cohorts currently available and being acquired. Furthermore, most neuroimaging modelling methods that are available assume the predictive distribution to be Gaussian in shape. However, deviations from Gaussianity can be frequently found, which may lead to incorrect inferences, particularly in the outer centiles of the distribution. In normative modelling, we use the centiles to give an estimation of the deviation of a particular participant from the ‘normal’ trend. Therefore, especially in normative modelling, the correct estimation of the outer centiles is of utmost importance, which is also where data are sparsest.

Here, we present a novel framework based on Bayesian Linear Regression with likelihood warping that allows us to address these problems, that is, to scale normative modelling elegantly to big data cohorts and to correctly model non-Gaussian predictive distributions. In addition, this method provides also likelihood-based statistics, which are useful for model selection.

To evaluate this framework, we use a range of neuroimaging-derived measures from the UK Biobank study, including image-derived phenotypes (IDPs) and whole-brain voxel-wise measures derived from diffusion tensor imaging. We show good computational scaling and improved accuracy of the warped BLR for certain IDPs and voxels if there was a deviation from normality of these parameters in their residuals.

The present results indicate the advantage of a warped BLR in terms of; computational scalability and the flexibility to incorporate non-linearity and non-Gaussianity of the data, giving a wider range of neuroimaging datasets that can be correctly modelled.

Multivariate white matter alterations are associated with epilepsy duration

Previous studies investigating associations between white matter alterations and duration of temporal lobe epilepsy (TLE) have shown differing results, and were typically limited to univariate analyses of tracts in isolation. In this study, we apply a multivariate measure (the Mahalanobis distance), which captures the distinct ways white matter may differ in individual patients, and relate this to epilepsy duration. Diffusion MRI, from a cohort of 94 subjects (28 healthy controls, 33 left-TLE and 33 right-TLE), was used to assess the association between tract fractional anisotropy (FA) and epilepsy duration. Using ten white matter tracts, we analysed associations using the traditional univariate analysis (z-scores) and a complementary multivariate approach (Mahalanobis distance), incorporating multiple white matter tracts into a single unified analysis. For patients with right-TLE, FA was not significantly associated with epilepsy duration for any tract studied in isolation. For patients with left-TLE, the FA of two limbic tracts (ipsilateral fornix, contralateral cingulum gyrus) were significantly negatively associated with epilepsy duration (Bonferonni corrected p < .05). Using a multivariate approach we found significant ipsilateral positive associations with duration in both left, and right-TLE cohorts (left-TLE: Spearman's ρ = 0.487, right-TLE: Spearman's ρ = 0.422). Extrapolating our multivariate results to duration equals zero (i.e., at onset) we found no significant difference between patients and controls. Associations using the multivariate approach were more robust than univariate methods. The multivariate Mahalanobis distance measure provides non-overlapping and more robust results than traditional univariate analyses. Future studies should consider adopting both frameworks into their analysis in order to ascertain a more complete understanding of epilepsy progression, regardless of laterality.

Accelerating Structural Degeneration in Temporal Regions and Their Effects on Cognition in Aging of MCI Patients

Age is the major risk factor for Alzheimer's disease (AD) and for mild cognitive impairment (MCI). However, there is limited evidence about MCI-specific aging-related simultaneous changes of the brain structure and their impact on cognition. We analyzed the brain imaging data from 269 subjects (97 MCI patients and 172 cognitively normal [CN] elderly) using voxel-based morphometry and tract-based spatial statistics procedures to explore the special structural pattern during aging. We found that the patients with MCI showed accelerated age-related reductions in gray matter volume in the left planum temporale, thalamus, and posterior cingulate gyrus. The similar age×group interaction effect was found in the fractional anisotropy of the bilateral parahippocampal cingulum white matter tract, which connects the temporal regions. Importantly, the age-related temporal gray matter and white matter alterations were more significantly related to performance in memory and attention tasks in MCI patients. The accelerated degeneration patterns in the brain structure provide evidence for different neural mechanisms underlying aging in MCI patients. Temporal structural degeneration may serve as a potential imaging marker for distinguishing the progression of the preclinical AD stage from normal aging.

Molecular and Diffusion Tensor Imaging Biomarkers of Traumatic Brain Injury: Principles for Investigation and Integration

The last 20 years have seen the advent of new technologies that enhance the diagnosis and prognosis of traumatic brain injury (TBI). There is recognition that TBI affects the brain beyond initial injury, in some cases inciting a progressive neuropathology that leads to chronic impairments. Medical researchers are now searching for biomarkers to detect and monitor this condition. Perhaps the most promising developments are in the biomolecular and neuroimaging domains. Molecular assays can identify proteins indicative of neuronal injury and/or degeneration. Diffusion imaging now allows sensitive evaluations of the brain's cellular microstructure. As the pace of discovery accelerates, it is important to survey the research landscape and identify promising avenues of investigation. In this review, we discuss the potential of molecular and diffusion tensor imaging (DTI) biomarkers in TBI research. Integration of these technologies could advance models of disease prognosis, ultimately improving care. To date, however, few studies have explored relationships between molecular and DTI variables in patients with TBI. Here, we provide a short primer on each technology, review the latest research, and discuss how these biomarkers may be incorporated in future studies.

Tract Specificity of Age Effects on Diffusion Tensor Imaging Measures of White Matter Health

Well-established literature indicates that older adults have poorer cerebral white matter integrity, as measured through diffusion tensor imaging (DTI). Age differences in DTI have been observed widely across white matter, although some tracts appear more sensitive to the effects of aging than others. Factors like APOE ε4 status and sex may contribute to individual differences in white matter integrity that also selectively impact certain tracts, and could influence DTI changes in aging. The present study explored the degree to which age, APOE ε4, and sex exerted global vs. tract specific effects on DTI metrics in cognitively healthy late middle-aged to older adults. Data from 49 older adults (ages 54–92) at two time-points separated by approximately 2.7 years were collected. DTI metrics, including fractional anisotropy (FA) and mean diffusivity (MD), were extracted from nine white matter tracts and global white matter. Results showed that across timepoints, FA and MD increased globally, with no tract-specific changes observed. Baseline age had a global influence on both measures, with increasing age associated with lower FA and higher MD. After controlling for global white matter FA, age additionally predicted FA for the genu, callosum body, inferior fronto-occipital fasciculus (IFOF), and both anterior and posterior cingulum. Females exhibited lower global FA on average compared to males. In contrast, MD was selectively elevated in the anterior cingulum and superior longitudinal fasciculus (SLF), for females compared to males. APOE ε4 status was not predictive of either measure. In summary, these results indicate that age and sex are associated with both global and tract-specific alterations to DTI metrics among a healthy older adult cohort. Older women have poorer white matter integrity compared to older men, perhaps related to menopause-induced metabolic changes. While age-related alterations to white matter integrity are global, there is substantial variation in the degree to which tracts are impacted, possibly as a consequence of tract anatomical variability. The present study highlights the importance of accounting for global sources of variation in DTI metrics when attempting to investigate individual differences (due to age, sex, or other factors) in specific white matter tracts.

Brain Magnetic Resonance Imaging Phenome-Wide Association Study With Metal Transporter Gene SLC39A8

The SLC39A8 gene encodes a divalent metal transporter, ZIP8. SLC39A8 is associated with pleiotropic effects across multiple tissues, including the brain. We determine the different brain magnetic resonance imaging (MRI) phenotypes associated with SLC39A8. We used a phenome-wide association study approach followed by joint and conditional association analysis. Using the summary statistics datasets from a brain MRI genome-wide association study on adult United Kingdom (UK) Biobank participants, we systematically selected all brain MRI phenotypes associated with single-nucleotide polymorphisms (SNPs) within 500 kb of the SLC39A8 genetic locus. For all significant brain MRI phenotypes, we used GCTA-COJO to determine the number of independent association signals and identify index SNPs for each brain MRI phenotype. Linkage equilibrium for brain phenotypes with multiple independent signals was confirmed by LDpair. We identified 24 brain MRI phenotypes that vary due to MRI type and brain region and contain a SNP associated with the SLC39A8 locus. Missense ZIP8 polymorphism rs13107325 was associated with 22 brain MRI phenotypes. Rare ZIP8 variants present in a published UK Biobank dataset are associated with 6 brain MRI phenotypes also linked to rs13107325. Among the 24 datasets, an additional 4 association signals were identified by GCTA-COJO and confirmed to be in linkage equilibrium with rs13107325 using LDpair. These additional association signals represent new probable causative SNPs in addition to rs13107325. This study provides leads into how genetic variation in SLC39A8, a trace mineral transport gene, is linked to brain structure differences and may affect brain development and nervous system function.

Large-Scale Morphological Network Efficiency of Human Brain: Cognitive Intelligence and Emotional Intelligence

Network efficiency characterizes how information flows within a network, and it has been used to study the neural basis of cognitive intelligence in adolescence, young adults, and elderly adults, in terms of the white matter in the human brain and functional connectivity networks. However, there were few studies investigating whether the human brain at different ages exhibited different underpins of cognitive and emotional intelligence (EI) from young adults to the middle-aged group, especially in terms of the morphological similarity networks in the human brain. In this study, we used 65 datasets (aging 18–64), including sMRI and behavioral measurements, to study the associations of network efficiency with cognitive intelligence and EI in young adults and the middle-aged group. We proposed a new method of defining the human brain morphological networks using the morphological distribution similarity (including cortical volume, surface area, and thickness). Our results showed inverted age × network efficiency interactions in the relationship of surface-area network efficiency with cognitive intelligence and EI: a negative age × global efficiency (nodal efficiency) interaction in cognitive intelligence, while a positive age × global efficiency (nodal efficiency) interaction in EI. In summary, this study not only proposed a new method of morphological similarity network but also emphasized the developmental effects on the brain mechanisms of intelligence from young adult to middle-aged groups and may promote mental health study on the middle-aged group in the future.

Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques

Brain age prediction studies aim at reliably estimating the difference between the chronological age of an individual and their predicted age based on neuroimaging data, which has been proposed as an informative measure of disease and cognitive decline. As most previous studies relied exclusively on magnetic resonance imaging (MRI) data, we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves age prediction using a large cohort of healthy subjects (N = 613, age 18-88 years) from the Cam-CAN repository. To this end, we examined the performance of dimensionality reduction and multivariate associative techniques, namely Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA), to tackle the high dimensionality of neuroimaging data. Using MEG features (mean absolute error (MAE) of 9.60 years) yielded worse performance when compared to using MRI features (MAE of 5.33 years), but a stacking model combining both feature sets improved age prediction performance (MAE of 4.88 years). Furthermore, we found that PCA resulted in inferior performance, whereas CCA in conjunction with Gaussian process regression models yielded the best prediction performance. Notably, CCA allowed us to visualize the features that significantly contributed to brain age prediction. We found that MRI features from subcortical structures were more reliable age predictors than cortical features, and that spectral MEG measures were more reliable than connectivity metrics. Our results provide an insight into the underlying processes that are reflective of brain aging, yielding promise for the identification of reliable biomarkers of neurodegenerative diseases that emerge later during the lifespan.

Exploratory factor analysis with structured residuals for brain network data

Dimension reduction is widely used and often necessary to make network analyses and their interpretation tractable by reducing high-dimensional data to a small number of underlying variables. Techniques such as exploratory factor analysis (EFA) are used by neuroscientists to reduce measurements from a large number of brain regions to a tractable number of factors. However, dimension reduction often ignores relevant a priori knowledge about the structure of the data. For example, it is well established that the brain is highly symmetric. In this paper, we (a) show the adverse consequences of ignoring a priori structure in factor analysis, (b) propose a technique to accommodate structure in EFA by using structured residuals (EFAST), and (c) apply this technique to three large and varied brain-imaging network datasets, demonstrating the superior fit and interpretability of our approach. We provide an R software package to enable researchers to apply EFAST to other suitable datasets.

Cell of all trades: oligodendrocyte precursor cells in synaptic, vascular, and immune function

Oligodendrocyte precursor cells (OPCs) are not merely a transitory progenitor cell type, but rather a distinct and heterogeneous population of glia with various functions in the developing and adult central nervous system. In this review, we discuss the fate and function of OPCs in the brain beyond their contribution to myelination. OPCs are electrically sensitive, form synapses with neurons, support blood-brain barrier integrity, and mediate neuroinflammation. We explore how sex and age may influence OPC activity, and we review how OPC dysfunction may play a primary role in numerous neurological and neuropsychiatric diseases. Finally, we highlight areas of future research.

In vivo coupling of dendritic complexity with presynaptic density in primary tauopathies

Understanding the cellular underpinnings of neurodegeneration remains a challenge; loss of synapses and dendritic arborization are characteristic and can be quantified in vivo, with [¹¹C]UCB-J PET and MRI-based Orientation Dispersion Imaging (ODI), respectively. We aimed to assess how both measures are correlated, in 4R-tauopathies of progressive supranuclear palsy - Richardson's Syndrome (PSP-RS; n = 22) and amyloid-negative (determined by [¹¹C]PiB PET) Corticobasal Syndrome (Cortiobasal degeneration, CBD; n =14), as neurodegenerative disease models, in this proof-of-concept study. Compared to controls (n = 27), PSP-RS and CBD patients had widespread reductions in cortical ODI, and [¹¹C]UCB-J non-displaceable binding potential (BP_ND) in excess of atrophy. In PSP-RS and CBD separately, regional cortical ODI was significantly associated with [¹¹C]UCB-J BP_ND in disease-associated regions (p < 0.05, FDR corrected). Our findings indicate that reductions in synaptic density and dendritic complexity in PSP-RS and CBD are more severe and extensive than atrophy. Furthermore, both measures are tightly coupled in vivo, furthering our understanding of the pathophysiology of neurodegeneration, and applicable to studies of early neurodegeneration with a safe and widely available MRI platform.

Brain microstructure mediates sex-specific patterns of cognitive aging

Normal brain aging is characterized by declining neuronal integrity, yet it remains unclear how microstructural injury influences cognitive aging and whether such mechanisms differ between sexes. Using restriction spectrum imaging (RSI), we examined sex differences in associations between brain microstructure and cognitive function in 147 community-dwelling older men and women (56-99 years). Gray and white matter microstructure correlated with global cognition, executive function, visuospatial memory, episodic memory, and logical memory, with the strongest associations for restricted, hindered and free isotropic diffusion. Associations were stronger for women than for men, a difference likely due to greater age-related variability in cognitive scores and microstructure in women. Isotropic diffusion mediated effects of age on cognition for both sexes, though distinct mediation patterns were present for women and men. For women, hippocampal and corpus callosum microstructure mediated age effects on verbal and visuospatial memory, respectively, whereas for men fiber microstructure (mainly fornix and corpus callosum) mediated age effects on executive function and visuospatial memory. These findings implicate sex-specific pathways by which changing brain cytoarchitecture contributes to cognitive aging, and suggest that RSI may be useful for evaluating risk for cognitive decline or monitoring efficacy of interventions to preserve brain health in later life.