Hippocampal volume across age: Nomograms derived from over 19,700 people in UK Biobank

Effects of reducing sedentary behaviour by increasing physical activity, on cognitive function, brain function and structure across the lifespan: a systematic review and meta-analysis

OBJECTIVE

To examine the acute and chronic effects of reducing prolonged sedentary time (ST) with physical activity (PA) on cognitive and brain health.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Scopus, CINAHL, PsycINFO, SPORTDiscus, Web of Science, and ProQuest Dissertation and Theses.

ELIGIBILITY CRITERIA

Randomised controlled trials (RCTs) published from inception to 17 June 2024, with healthy participants without cognitive impairment or neurological conditions that affect cognitive functioning, aged ≥4 years, testing acute and chronic effects of reducing ST and/or prolonged ST by reallocating ST to PA on cognitive function, brain function, and structure.

RESULTS

We included 25 RCTs (n=1289) investigating acute (21 studies) and chronic (4 studies) effects on cognitive function (acute: n=20, chronic: n=4) and brain function (acute: n=7, chronic: n=1); there were no studies on brain structure. Acutely interrupting continuous ST with either multiple or a single PA bout improved cognitive function measured from 3 hours to three consecutive days based on 91 effect sizes (g=0.17, 95% CI: 0.05 to 0.29, p=0.005, I 2=45.5%). When comparing single versus multiple PA bouts, only multiple PA bouts yielded a positive effect on cognitive function based on 72 effect sizes (g=0.20, 95% CI: 0.06 to 0.35, p=0.006; I 2=48.8%). Chronic studies reported null findings on cognitive function (n=4), with some evidence of improved neural efficiency of the hippocampus (n=1).

CONCLUSION

Interrupting ST with PA acutely improves cognitive function. The evidence from chronic studies remains inconclusive.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020200998.

Age-related decline in blood-brain barrier function is more pronounced in males than females in parietal and temporal regions

The blood-brain barrier (BBB) plays a pivotal role in protecting the central nervous system (CNS), and shielding it from potential harmful entities. A natural decline of BBB function with aging has been reported in both animal and human studies, which may contribute to cognitive decline and neurodegenerative disorders. Limited data also suggest that being female may be associated with protective effects on BBB function. Here, we investigated age and sex-dependent trajectories of perfusion and BBB water exchange rate (kw) across the lifespan in 186 cognitively normal participants spanning the ages of 8-92 years old, using a non-invasive diffusion-prepared pseudo-continuous arterial spin labeling (DP-pCASL) MRI technique. We found that the pattern of BBB kw decline with aging varies across brain regions. Moreover, results from our DP-pCASL technique revealed a remarkable decline in BBB kw beginning in the early 60 s, which was more pronounced in males. In addition, we observed sex differences in parietal and temporal regions. Our findings provide in vivo results demonstrating sex differences in the decline of BBB function with aging, which may serve as a foundation for future investigations into perfusion and BBB function in neurodegenerative and other brain disorders.

Morphological characterization of the hippocampus: a first database in Ecuador

Introduction

The hippocampal volume is a well-known biomarker to detect and diagnose neurological, psychiatric, and psychological diseases. However, other morphological descriptors are not analyzed. Furthermore, not available databases, or studies, were found with information related to the hippocampal morphology from Latin-American patients living in the Andean highlands.

Methods

The hippocampus is manually segmented by two medical imaging specialists on normal brain magnetic resonance images. Then, its morphological qualitative and quantitative descriptors (volume, sphericity, roundness, diameter, volume-surface ratio, and aspect ratio) are computed via 3D digital level-set-based mathematical representation. Furthermore, other morphological descriptors and their possible correlation with the hippocampal volume is analyzed.

Results

We introduce a first database with the hippocampus' morphological characterization of 63 patients from Quito, Ecuador, male and female, aged between 18 and 95 years old.

Discussion

This study provides new research opportunities to neurologists, psychologists, and psychiatrists, to further understand the hippocampal morphology of Andean and Latin American patients.

Normative Neuroimaging Library: Designing a Comprehensive and Demographically Diverse Dataset of Healthy Controls to Support Traumatic Brain Injury Diagnostic and Therapeutic Development

The past decade has seen impressive advances in neuroimaging, moving from qualitative to quantitative outputs. Available techniques now allow for the inference of microscopic changes occurring in white and gray matter, along with alterations in physiology and function. These existing and emerging techniques hold the potential of providing unprecedented capabilities in achieving a diagnosis and predicting outcomes for traumatic brain injury (TBI) and a variety of other neurological diseases. To see this promise move from the research lab into clinical care, an understanding is needed of what normal data look like for all age ranges, sex, and other demographic and socioeconomic categories. Clinicians can only use the results of imaging scans to support their decision-making if they know how the results for their patient compare with a normative standard. This potential for utilizing magnetic resonance imaging (MRI) in TBI diagnosis motivated the American College of Radiology and Cohen Veterans Bioscience to create a reference database of healthy individuals with neuroimaging, demographic data, and characterization of psychological functioning and neurocognitive data that will serve as a normative resource for clinicians and researchers for development of diagnostics and therapeutics for TBI and other brain disorders. The goal of this article is to introduce the large, well-curated Normative Neuroimaging Library (NNL) to the research community. NNL consists of data collected from ∼1900 healthy participants. The highlights of NNL are (1) data are collected across a diverse population, including civilians, veterans, and active-duty service members with an age range (18-64 years) not well represented in existing datasets; (2) comprehensive structural and functional neuroimaging acquisition with state-of-the-art sequences (including structural, diffusion, and functional MRI; raw scanner data are preserved, allowing higher quality data to be derived in the future; standardized imaging acquisition protocols across sites reflect sequences and parameters often recommended for use with various neurological and psychiatric conditions, including TBI, post-traumatic stress disorder, stroke, neurodegenerative disorders, and neoplastic disease); and (3) the collection of comprehensive demographic details, medical history, and a broad structured clinical assessment, including cognition and psychological scales, relevant to multiple neurological conditions with functional sequelae. Thus, NNL provides a demographically diverse population of healthy individuals who can serve as a comparison group for brain injury study and clinical samples, providing a strong foundation for precision medicine. Use cases include the creation of imaging-derived phenotypes (IDPs), derivation of reference ranges of imaging measures, and use of IDPs as training samples for artificial intelligence-based biomarker development and for normative modeling to help identify injury-induced changes as outliers for precision diagnosis and targeted therapeutic development. On its release, NNL is poised to support the use of advanced imaging in clinician decision support tools, the validation of imaging biomarkers, and the investigation of brain-behavior anomalies, moving the field toward precision medicine.

Brain Charts for the Rhesus Macaque Lifespan

Recent efforts to chart human brain growth across the lifespan using large-scale MRI data have provided reference standards for human brain development. However, similar models for nonhuman primate (NHP) growth are lacking. The rhesus macaque, a widely used NHP in translational neuroscience due to its similarities in brain anatomy, phylogenetics, cognitive, and social behaviors to humans, serves as an ideal NHP model. This study aimed to create normative growth charts for brain structure across the macaque lifespan, enhancing our understanding of neurodevelopment and aging, and facilitating cross-species translational research. Leveraging data from the PRIMatE Data Exchange (PRIME-DE) and other sources, we aggregated 1,522 MRI scans from 1,024 rhesus macaques. We mapped non-linear developmental trajectories for global and regional brain structural changes in volume, cortical thickness, and surface area over the lifespan. Our findings provided normative charts with centile scores for macaque brain structures and revealed key developmental milestones from prenatal stages to aging, highlighting both species-specific and comparable brain maturation patterns between macaques and humans. The charts offer a valuable resource for future NHP studies, particularly those with small sample sizes. Furthermore, the interactive open resource (https://interspeciesmap.childmind.org) supports cross-species comparisons to advance translational neuroscience research.

The relationship between hippocampal changes in healthy aging and Alzheimer's disease: a systematic literature review

Introduction

Neurobiological changes in the hippocampus are a common consequence of aging. However, there are differences in the rate of decline and overall volume loss in people with no cognitive impairment compared to those with mild cognitive impairment (MCI) and Alzheimer's disease (AD). This systematic literature review was conducted to determine the relationship between hippocampal atrophy and changes in hippocampal volume in the non-cognitively impaired brain and those with MCI or AD.

Methods

This systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The PubMed database was searched up to September 15, 2022, for longitudinal magnetic resonance imaging studies reporting hippocampal atrophy or volume change in cognitively normal aging individuals and patients with MCI and/or AD. Study selection was divided into two steps: (1) identification and retrieval of relevant studies; (2) screening the studies by (a) title/abstract and (b) full text. Two teams, each consisting of two independent reviewers, determined whether the publications met the inclusion criteria for the systematic review. An evidence table was populated with data extracted from eligible publications and inclusion in the final systematic review was confirmed.

Results

The systematic search identified 357 publications that were initially screened by title/abstract, of which, 115 publications were retrieved and reviewed by full text for eligibility. Seventeen publications met the eligibility criteria; however, during data extraction, two studies were determined to not meet the inclusion criteria and were excluded. The remaining 15 studies were included in the systematic review. Overall, the results of these studies demonstrated that the hippocampus and hippocampal subfields change over time, with both decreased hippocampal volume and increased rate of hippocampal atrophy observed. Hippocampal changes in AD were observed to be greater than hippocampal changes in MCI, and changes in MCI were observed to be greater than those in normal aging populations.

Conclusion

Published literature suggests that the rate of hippocampal decline and extent of loss is on a continuum that begins in people without cognitive impairment and continues to MCI and AD, and that differences between no cognitive impairment, MCI, and AD are quantitative rather than qualitative.

Circadian timing, melatonin and hippocampal volume in later-life adults

Hippocampal atrophy is a prominent neurodegenerative feature of Alzheimer's disease and related dementias. Alterations in circadian rhythms can exacerbate cognitive aging and neurodegeneration. This study aimed to examine how dim light melatonin onset and melatonin levels are associated with hippocampal volume in cognitively healthy individuals. We studied data from 52 later-life adults (mean age ± SD = 70.0 ± 6.3 years). T1-weighted anatomical images from 3.0 T magnetic resonance imaging data were collected and processed using the BRAINSTools toolbox. Dim light melatonin onset was used to assess circadian timing. The area under the curve was calculated to quantify melatonin concentration levels 6 hr before bedtime, and 14-day wrist actigraphy data were used to assess habitual bedtime. Multiple linear regression modelling with hippocampal volume as the dependent variable was used to analyse the data adjusting for age and sex. The average dim light melatonin onset was 19:45 hours (SD = 84 min), and area under the curve of melatonin levels 6 hr before habitual bedtime was 38.4 pg ml-1 × hr (SD = 29.3). We found that later dim light melatonin onset time (b = 0.16, p = 0.005) and greater area under the curve of melatonin levels 6 hr before habitual bedtime (b = 0.05, p = 0.046) were associated with greater adjusted hippocampal volume. The time between dim light melatonin onset and the midpoint of sleep timing was not associated with hippocampal volume. The findings suggest that earlier circadian timing (dim light melatonin onset) and reduced melatonin may be associated with reduced hippocampal volume in older adults. Future research will help researchers utilize circadian rhythm information to delay brain aging.

Sex and gender differences in cognitive resilience to aging and Alzheimer's disease

Sex and gender-biological and social constructs-significantly impact the prevalence of protective and risk factors, influencing the burden of Alzheimer's disease (AD; amyloid beta and tau) and other pathologies (e.g., cerebrovascular disease) which ultimately shape cognitive trajectories. Understanding the interplay of these factors is central to understanding resilience and resistance mechanisms explaining maintained cognitive function and reduced pathology accumulation in aging and AD. In this narrative review, the ADDRESS! Special Interest Group (Alzheimer's Association) adopted a multidisciplinary approach to provide the foundations and recommendations for future research into sex- and gender-specific drivers of resilience, including a sex/gender-oriented review of risk factors, genetics, AD and non-AD pathologies, brain structure and function, and animal research. We urge the field to adopt a sex/gender-aware approach to resilience to advance our understanding of the intricate interplay of biological and social determinants and consider sex/gender-specific resilience throughout disease stages. HIGHLIGHTS: Sex differences in resilience to cognitive decline vary by age and cognitive status. Initial evidence supports sex-specific distinctions in brain pathology. Findings suggest sex differences in the impact of pathology on cognition. There is a sex-specific change in resilience in the transition to clinical stages. Gender and sex factors warrant study: modifiable, immune, inflammatory, and vascular.

Traffic-related air pollution and APOE4 can synergistically affect hippocampal volume in older women: new findings from UK Biobank

A growing research body supports the connection between neurodegenerative disorders, including Alzheimer's disease (AD), and traffic-related air pollution (TRAP). However, the underlying mechanisms are not well understood. A deeper investigation of TRAP effects on hippocampal volume (HV), a major biomarker of neurodegeneration, may help clarify these mechanisms. Here, we explored TRAP associations with the HV in older participants of the UK Biobank (UKB), taking into account the presence of APOE e4 allele (APOE4), the strongest genetic risk factor for AD. Exposure to TRAP was approximated by the distance of the participant's main residence to the nearest major road (DNMR). The left/right HV was measured by magnetic resonance imaging (MRI) in cubic millimeters (mm3). Analysis of variance (ANOVA), Welch test, and regression were used to examine statistical significance. We found significant interactions between DNMR and APOE4 that influenced HV. Specifically, DNMR <50m (equivalent of a chronically high exposure to TRAP), and carrying APOE4 were synergistically associated with a significant (P = 0.01) reduction in the right HV by about 2.5% in women aged 60-75 years (results for men didn't reach a statistical significance). Results of our study suggest that TRAP and APOE4 jointly promote neurodegeneration in women. Living farther from major roads may help reduce the risks of neurodegenerative disorders, including AD, in female APOE4 carriers.

Aging Brain from a Lifespan Perspective

Research during the last two decades has shown that the brain undergoes continuous changes throughout life, with substantial heterogeneity in age trajectories between regions. Especially, temporal and prefrontal cortices show large changes, and these correlate modestly with changes in the corresponding cognitive abilities such as episodic memory and executive function. Changes seen in normal aging overlap with changes seen in neurodegenerative conditions such as Alzheimer's disease; differences between what reflects normal aging vs. a disease-related change are often blurry. This calls for a dimensional view on cognitive decline in aging, where clear-cut distinctions between normality and pathology cannot be always drawn. Although much progress has been made in describing typical patterns of age-related changes in the brain, identifying risk and protective factors, and mapping cognitive correlates, there are still limits to our knowledge that should be addressed by future research. We need more longitudinal studies following the same participants over longer time intervals with cognitive testing and brain imaging, and an increased focus on the representativeness vs. selection bias in neuroimaging research of aging.

In vivo mapping of hippocampal venous vasculature and oxygenation using susceptibility imaging at 7T

Mapping the small venous vasculature of the hippocampus in vivo is crucial for understanding how functional changes of hippocampus evolve with age. Oxygen utilization in the hippocampus could serve as a sensitive biomarker for early degenerative changes, surpassing hippocampal tissue atrophy as the main source of information regarding tissue degeneration. Using an ultrahigh field (7T) susceptibility-weighted imaging (SWI) sequence, it is possible to capture oxygen-level dependent contrast of submillimeter-sized vessels. Moreover, the quantitative susceptibility mapping (QSM) results derived from SWI data allow for the simultaneous estimation of venous oxygenation levels, thereby enhancing the understanding of hippocampal function. In this study, we proposed two potential imaging markers in a cohort of 19 healthy volunteers aged between 20 and 74 years. These markers were: 1) hippocampal venous density on SWI images and 2) venous susceptibility (Δχvein) in the hippocampus-associated draining veins (the inferior ventricular veins (IVV) and the basal veins of Rosenthal (BVR) using QSM images). They were chosen specifically to help characterize the oxygen utilization of the human hippocampus and medial temporal lobe (MTL). As part of the analysis, we demonstrated the feasibility of measuring hippocampal venous density and Δχvein in the IVV and BVR at 7T with high spatial resolution (0.25 × 0.25 × 1 mm3). Our results demonstrated the in vivo reconstruction of the hippocampal venous system, providing initial evidence regarding the presence of the venous arch structure within the hippocampus. Furthermore, we evaluated the age effect of the two quantitative estimates and observed a significant increase in Δχvein for the IVV with age (p=0.006, r2 = 0.369). This may suggest the potential application of Δχvein in IVV as a marker for assessing changes in atrophy-related hippocampal oxygen utilization in normal aging and neurodegenerative diseases such as AD and dementia.

ANTsX neuroimaging-derived structural phenotypes of UK Biobank

UK Biobank is a large-scale epidemiological resource for investigating prospective correlations between various lifestyle, environmental, and genetic factors with health and disease progression. In addition to individual subject information obtained through surveys and physical examinations, a comprehensive neuroimaging battery consisting of multiple modalities provides imaging-derived phenotypes (IDPs) that can serve as biomarkers in neuroscience research. In this study, we augment the existing set of UK Biobank neuroimaging structural IDPs, obtained from well-established software libraries such as FSL and FreeSurfer, with related measurements acquired through the Advanced Normalization Tools Ecosystem. This includes previously established cortical and subcortical measurements defined, in part, based on the Desikan-Killiany-Tourville atlas. Also included are morphological measurements from two recent developments: medial temporal lobe parcellation of hippocampal and extra-hippocampal regions in addition to cerebellum parcellation and thickness based on the Schmahmann anatomical labeling. Through predictive modeling, we assess the clinical utility of these IDP measurements, individually and in combination, using commonly studied phenotypic correlates including age, fluid intelligence, numeric memory, and several other sociodemographic variables. The predictive accuracy of these IDP-based models, in terms of root-mean-squared-error or area-under-the-curve for continuous and categorical variables, respectively, provides comparative insights between software libraries as well as potential clinical interpretability. Results demonstrate varied performance between package-based IDP sets and their combination, emphasizing the need for careful consideration in their selection and utilization.

Fetal influence on the human brain through the lifespan

Human fetal development has been associated with brain health at later stages. It is unknown whether growth in utero, as indexed by birth weight (BW), relates consistently to lifespan brain characteristics and changes, and to what extent these influences are of a genetic or environmental nature. Here we show remarkably stable and lifelong positive associations between BW and cortical surface area and volume across and within developmental, aging and lifespan longitudinal samples (N = 5794, 4-82 y of age, w/386 monozygotic twins, followed for up to 8.3 y w/12,088 brain MRIs). In contrast, no consistent effect of BW on brain changes was observed. Partly environmental effects were indicated by analysis of twin BW discordance. In conclusion, the influence of prenatal growth on cortical topography is stable and reliable through the lifespan. This early-life factor appears to influence the brain by association of brain reserve, rather than brain maintenance. Thus, fetal influences appear omnipresent in the spacetime of the human brain throughout the human lifespan. Optimizing fetal growth may increase brain reserve for life, also in aging.

Aerobic exercise training effects on hippocampal volume in healthy older individuals: a meta-analysis of randomized controlled trials

We conducted a meta-analysis of randomized controlled trials investigating the effects of aerobic exercise training (AET) lasting ≥ 4 weeks on hippocampal volume and cardiorespiratory fitness (CRF) in cognitively unimpaired, healthy older individuals. Random-effects robust variance estimation models were used to test differences between AET and controls, while meta-regressions tested associations between CRF and hippocampal volume changes. We included eight studies (N = 554) delivering fully supervised AET for 3 to 12 months (M = 7.8, SD = 4.5) with an average AET volume of 129.85 min/week (SD = 45.5) at moderate-to-vigorous intensity. There were no significant effects of AET on hippocampal volume (SMD = 0.10, 95% CI - 0.01 to 0.21, p = 0.073), but AET moderately improved CRF (SMD = 0.30, 95% CI 0.12 to 0.48, p = 0.005). Improvement in CRF was not associated with changes in hippocampal volume (bSE = 0.05, SE = 0.51, p = 0.923). From the limited number of studies, AET does not seem to impact hippocampal volume in cognitively unimpaired, healthy older individuals. Notable methodological limitations across investigations might mask the lack of effects.

A framework to select tuning parameters for nonparametric derivative estimation

In this paper, we propose a general framework to select tuning parameters for the nonparametric derivative estimation. The new framework broadens the scope of the previously proposed generalizedC p $C_p$ criterion by replacing the empirical derivative with any other linear nonparametric smoother. We provide the theoretical support of the proposed derivative estimation in a random design and justify it through simulation studies. The practical application of the proposed framework is demonstrated in the study of the age effect on hippocampal gray matter volume in healthy adults from the IXI dataset and the study of the effect of age and body mass index on blood pressure from the Pima Indians dataset.

Volumetric analysis of hippocampal subregions and subfields in left and right semantic dementia

Two variants of semantic dementia are recognized based on the laterality of temporal lobe involvement: a left-predominant variant associated with verbal knowledge impairment and a right-predominant variant associated with behavioural changes and non-verbal knowledge loss. This cross-sectional clinicoradiologic study aimed to assess whole hippocampal, subregion, and/or subfield volume loss in semantic dementia versus controls and across its variants. Thirty-five semantic dementia participants and 15 controls from the Neurodegenerative Research Group at Mayo Clinic who had completed 3.0-T volumetric magnetic resonance imaging and 18F-fluorodeoxyglucose-positron emission tomography were included. Classification as left-predominant (n = 25) or right-predominant (n = 10) variant was based on temporal lobe hypometabolism. Volumes of hippocampal subregions (head, body, and tail) and subfields (parasubiculum, presubiculum, subiculum, cornu ammonis 1, cornu ammonis 3, cornu ammonis 4, dentate gyrus, molecular layer, hippocampal-amygdaloid transition area, and fimbria) were obtained using FreeSurfer 7. Subfield volumes were measured separately from head and body subregions. We fit linear mixed-effects models using log-transformed whole hippocampal/subregion/subfield volumes as dependent variables; age, sex, total intracranial volume, hemisphere and a group-by-hemisphere interaction as fixed effects; and subregion/subfield nested within hemisphere as a random effect. Significant results (P < 0.05) are hereby reported. At the whole hippocampal level, the dominant (predominantly involved) hemisphere of both variants showed 23-27% smaller volumes than controls. The non-dominant (less involved) hemisphere of the right-predominant variant also showed volume loss versus controls and the left-predominant variant. At the subregional level, both variants showed 17-28% smaller dominant hemisphere head, body, and tail than controls, with the right-predominant variant also showing 8-12% smaller non-dominant hemisphere head than controls and left-predominant variant. At the subfield level, the left-predominant variant showed 12-36% smaller volumes across all dominant hemisphere subfields and 14-15% smaller non-dominant hemisphere parasubiculum, presubiculum (head and body), subiculum (head) and hippocampal-amygdaloid transition area than controls. The right-predominant variant showed 16-49% smaller volumes across all dominant hemisphere subfields and 14-22% smaller parasubiculum, presubiculum, subiculum, cornu ammonis 3, hippocampal-amygdaloid transition area (all from the head) and fimbria of non-dominant hemisphere versus controls. Comparison of dominant hemispheres showed 16-29% smaller volumes of the parasubiculum, presubiculum (head) and fimbria in the right-predominant than left-predominant variant; comparison of non-dominant hemispheres showed 12-15% smaller cornu ammonis 3, cornu ammonis 4, dentate gyrus, hippocampal-amygdaloid transition area (all from the head) and cornu ammonis 1, cornu ammonis 3 and cornu ammonis 4 (all from the body) in the right-predominant variant. All hippocampal subregion/subfield volumes are affected in semantic dementia, although some are more affected in both dominant and non-dominant hemispheres of the right-predominant than the left-predominant variant by the time of presentation. Involvement of hippocampal structures is apparently more subregion dependent than subfield dependent, indicating possible superiority of subregion volumes as disease biomarkers.

Comprehensive assessment of sleep duration, insomnia, and brain structure within the UK Biobank cohort

STUDY OBJECTIVES

To assess for associations between sleeping more than or less than recommended by the National Sleep Foundation (NSF), and self-reported insomnia, with brain structure.

METHODS

Data from the UK Biobank cohort were analyzed (N between 9K and 32K, dependent on availability, aged 44 to 82 years). Sleep measures included self-reported adherence to NSF guidelines on sleep duration (sleeping between 7 and 9 hours per night), and self-reported difficulty falling or staying asleep (insomnia). Brain structural measures included global and regional cortical or subcortical morphometry (thickness, surface area, volume), global and tract-related white matter microstructure, brain age gap (difference between chronological age and age estimated from brain scan), and total volume of white matter lesions.

RESULTS

Longer-than-recommended sleep duration was associated with lower overall grey and white matter volumes, lower global and regional cortical thickness and volume measures, higher brain age gap, higher volume of white matter lesions, higher mean diffusivity globally and in thalamic and association fibers, and lower volume of the hippocampus. Shorter-than-recommended sleep duration was related to higher global and cerebellar white matter volumes, lower global and regional cortical surface areas, and lower fractional anisotropy in projection fibers. Self-reported insomnia was associated with higher global gray and white matter volumes, and with higher volumes of the amygdala, hippocampus, and putamen.

CONCLUSIONS

Sleeping longer than recommended by the NSF is associated with a wide range of differences in brain structure, potentially indicative of poorer brain health. Sleeping less than recommended is distinctly associated with lower cortical surface areas. Future studies should assess the potential mechanisms of these differences and investigate long sleep duration as a putative marker of brain health.

Investigating the synergistic effects of hormone replacement therapy, apolipoprotein E and age on brain health in the UK Biobank

Global prevalence of Alzheimer's Disease has a strong sex bias, with women representing approximately two-thirds of the patients. Yet, the role of sex-specific risk factors during midlife, including hormone replacement therapy (HRT) and their interaction with other major risk factors for Alzheimer's Disease, such as apolipoprotein E (APOE)-e4 genotype and age, on brain health remains unclear. We investigated the relationship between HRT (i.e., use, age of initiation and duration of use) and brain health (i.e., cognition and regional brain volumes). We then consider the multiplicative effects of HRT and APOE status (i.e., e2/e2, e2/e3, e3/e3, e3/e4 and e4/e4) via a two-way interaction and subsequently age of participants via a three-way interaction. Women from the UK Biobank with no self-reported neurological conditions were included (N = 207,595 women, mean age = 56.25 years, standard deviation = 8.01 years). Generalised linear regression models were computed to quantify the cross-sectional association between HRT and brain health, while controlling for APOE status, age, time since attending centre for completing brain health measure, surgical menopause status, smoking history, body mass index, education, physical activity, alcohol use, ethnicity, socioeconomic status, vascular/heart problems and diabetes diagnosed by doctor. Analyses of structural brain regions further controlled for scanner site. All brain volumes were normalised for head size. Two-way interactions between HRT and APOE status were modelled, in addition to three-way interactions including age. Results showed that women with the e4/e4 genotype who have used HRT had 1.82% lower hippocampal, 2.4% lower parahippocampal and 1.24% lower thalamus volumes than those with the e3/e3 genotype who had never used HRT. However, this interaction was not detected for measures of cognition. No clinically meaningful three-way interaction between APOE, HRT and age was detected when interpreted relative to the scales of the cognitive measures used and normative models of ageing for brain volumes in this sample. Differences in hippocampal volume between women with the e4/e4 genotype who have used HRT and those with the e3/e3 genotype who had never used HRT are equivalent to approximately 1-2 years of hippocampal atrophy observed in typical health ageing trajectories in midlife (i.e., 0.98%-1.41% per year). Effect sizes were consistent within APOE e4/e4 group post hoc sensitivity analyses, suggesting observed effects were not solely driven by APOE status and may, in part, be attributed to HRT use. Although, the design of this study means we cannot exclude the possibility that women who have used HRT may have a predisposition for poorer brain health.

Is vestibular function related to human hippocampal volume?

BACKGROUND

Recent studies implicate the effect of vestibular loss on cognitive decline, including hippocampal volume loss. As hippocampal atrophy is an important biomarker of Alzheimer's disease, exploring vestibular dysfunction as a risk factor for dementia and its role in hippocampal atrophy is of interest.

OBJECTIVE

To replicate previous literature on whole-brain and hippocampal volume in semicircular canal dysfunction (bilateral vestibulopathy; BV) and explore the association between otolith function and hippocampal volume.

METHODS

Hippocampal and whole-brain MRI volumes were compared in adults aged between 55 and 83 years. Participants with BV (n = 16) were compared to controls individually matched on age, sex, and hearing status (n = 16). Otolith influence on hippocampal volume in preserved semicircular canal function was evaluated (n = 34).

RESULTS

Whole-brain and targeted hippocampal approaches using volumetric and surface-based measures yielded no significant differences when comparing BV to controls. Binary support vector machines were unable to classify inner ear health status above chance level. Otolith parameters were not associated with hippocampal volume in preserved semicircular canal function.

CONCLUSIONS

No significant differences in whole-brain or hippocampal volume were found when comparing BV participants with healthy controls. Saccular parameters in subjects with preserved semicircular canal function were not associated with hippocampal volume changes.

Convergence of Accelerated Brain Volume Decline in Normal Aging and Alzheimer's Disease Pathology

Background

Age represents the largest risk factor for Alzheimer's disease (AD) but is typically treated as a covariate. Still, there are similarities between brain regions affected in AD and those showing accelerated decline in normal aging, suggesting that the distinction between the two might fall on a spectrum.

Objective

Our goal was to identify regions showing accelerated atrophy across the brain and investigate whether these overlapped with regions involved in AD or where related to amyloid.

Methods

We used a longitudinal sample of 137 healthy older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI), who underwent magnetic resonance imaging (MRI). In addition, a total of 79 participants also had longitudinal positron emission tomography (PET) data. We computed linear-mixed effects models for brain regions declining faster than the average to investigate variability in the rate of change.

Results

23 regions displayed a 0.5 standard deviation (SD) above average decline over 2 years. Of these, 52% overlapped with regions showing similar decline in a matched AD sample. Beyond this, the left precuneus, right superior frontal, transverse temporal, and superior temporal sulcus showed accelerated decline. Lastly, atrophy in the precuneus was associated with increased amyloid load.

Conclusions

Accelerated decline in normal aging might contribute to the detection of early signs of AD among healthy individuals.

Higher fresh fruit intake relates to larger grey matter volumes in areas involved in dementia and depression: A UK Biobank study

The benefits of consuming fruits and vegetables are widely accepted. While previous studies suggest a protective role of fruits and vegetables against a variety of diseases such as dementia and depression, the biological mechanisms/effects remain unclear. Here we investigated the effect of fruit and vegetable consumption on brain structure. Particularly on grey matter (GM) and white matter (WM) volumes, regional GM volumes and subcortical volumes. Cross-sectional imaging data from UK Biobank cohort was used. A total of 9925 participants (Mean age 62.4 ± 7.5 years, 51.1 % men) were included in the present analysis. Measures included fruit and vegetable intake, other dietary patterns and a number of selected lifestyle factors and clinical data. Brain volumes were derived from structural brain magnetic resonance imaging. General linear model was used to study the associations between brain volumes and fruit/vegetable intakes. After adjusting for selected confounding factors, salad/raw vegetable intake showed a positive association with total white matter volume, fresh fruit intake showed a negative association with total grey matter (GM) volume. Regional GM analyses showed that higher fresh fruit intake was associated with larger GM volume in the left hippocampus, right temporal occipital fusiform cortex, left postcentral gyrus, right precentral gyrus, and right juxtapositional lobule cortex. We conclude that fruit and vegetable consumption seems to specifically modulate brain volumes. In particular, fresh fruit intake may have a protective role in specific cortical areas such as the hippocampus, areas robustly involved in the pathophysiology of dementia and depression.

Hippocampal microstructure, but not macrostructure, mediates age differences in episodic memory

Introduction

Separate unimodal magnetic resonance imaging (MRI) literatures have shown that hippocampal gray matter macrostructure (volume) and microstructure (diffusion) decline with age and relate to episodic memory performance, with multimodal MRI studies reporting that episodic memory may be better explained by a combination of these metrics. However, these effects are often assessed independent of age or only within older adults and therefore do not address whether these distinct modalities explain variance in (i.e, mediate) the effect of age on episodic memory.

Methods

Here, we simultaneously examined the unique and joint contribution of hippocampal volume and diffusion to age-related differences in episodic memory in 83 younger and 61 older adults who underwent a T1- and diffusion-weighted MRI and completed the Rey Auditory Verbal Learning Test.

Results

As expected, older age was significantly related to smaller volume and higher diffusion (intracellular, dispersion, and free) in bilateral hippocampus and to worse episodic memory performance (immediate and delayed free recall, recognition). Structural equation modelling revealed that the age-memory relationship was significantly mediated by hippocampal diffusion, but not volume. A non-significant influential indirect effect further revealed that the structural metrics did not jointly mediate the age-memory relationship.

Discussion

Together, these findings indicate that hippocampal microstructure uniquely contributes to age-related differences in episodic memory and suggest that volume and diffusion capture distinct neurobiological properties of hippocampal gray matter.

Mapping mesoscale connectivity within the human hippocampus

The connectivity of the hippocampus is essential to its functions. To gain a whole system view of intrahippocampal connectivity, ex vivo mesoscale (100 μm isotropic resolution) multi-shell diffusion MRI (11.7T) and tractography were performed on entire post-mortem human right hippocampi. Volumetric measurements indicated that the head region was largest followed by the body and tail regions. A unique anatomical organization in the head region reflected a complex organization of the granule cell layer (GCL) of the dentate gyrus. Tractography revealed the volumetric distribution of the perforant path, including both the tri-synaptic and temporoammonic pathways, as well as other well-established canonical connections, such as Schaffer collaterals. Visualization of the perforant path provided a means to verify the borders between the pro-subiculum and CA1, as well as between CA1/CA2. A specific angularity of different layers of fibers in the alveus was evident across the whole sample and allowed a separation of afferent and efferent connections based on their origin (i.e. entorhinal cortex) or destination (i.e. fimbria) using a cluster analysis of streamlines. Non-canonical translamellar connections running along the anterior-posterior axis were also discerned in the hilus. In line with "dentations" of the GCL, mossy fibers were bunching together in the sagittal plane revealing a unique lamellar organization and connections between these. In the head region, mossy fibers projected to the origin of the fimbria, which was distinct from the body and tail region. Mesoscale tractography provides an unprecedented systems view of intrahippocampal connections that underpin cognitive and emotional processing.

ANTsX neuroimaging-derived structural phenotypes of UK Biobank

UK Biobank is a large-scale epidemiological resource for investigating prospective correlations between various lifestyle, environmental, and genetic factors with health and disease progression. In addition to individual subject information obtained through surveys and physical examinations, a comprehensive neuroimaging battery consisting of multiple modalities provides imaging-derived phenotypes (IDPs) that can serve as biomarkers in neuroscience research. In this study, we augment the existing set of UK Biobank neuroimaging structural IDPs, obtained from well-established software libraries such as FSL and FreeSurfer, with related measurements acquired through the Advanced Normalization Tools Ecosystem. This includes previously established cortical and subcortical measurements defined, in part, based on the Desikan-Killiany-Tourville atlas. Also included are morphological measurements from two recent developments: medial temporal lobe parcellation of hippocampal and extra-hippocampal regions in addition to cerebellum parcellation and thickness based on the Schmahmann anatomical labeling. Through predictive modeling, we assess the clinical utility of these IDP measurements, individually and in combination, using commonly studied phenotypic correlates including age, fluid intelligence, numeric memory, and several other sociodemographic variables. The predictive accuracy of these IDP-based models, in terms of root-mean-squared-error or area-under-the-curve for continuous and categorical variables, respectively, provides comparative insights between software libraries as well as potential clinical interpretability. Results demonstrate varied performance between package-based IDP sets and their combination, emphasizing the need for careful consideration in their selection and utilization.

Timing of lifespan influences on brain and cognition

Modifiable risk and protective factors for boosting brain and cognitive development and preventing neurodegeneration and cognitive decline are embraced in neuroimaging studies. We call for sobriety regarding the timing and quantity of such influences on brain and cognition. Individual differences in the level of brain and cognition, many of which present already at birth and early in development, appear stable, larger, and more pervasive than differences in change across the lifespan. Incorporating early-life factors, including genetics, and investigating both level and change will reduce the risk of ascribing undue importance and causality to proximate factors in adulthood and older age. This has implications for both mechanistic understanding and prevention.

The major TMEM106B dementia risk allele affects TMEM106B protein levels, fibril formation, and myelin lipid homeostasis in the ageing human hippocampus

BACKGROUND

The risk for dementia increases exponentially from the seventh decade of life. Identifying and understanding the biochemical changes that sensitize the ageing brain to neurodegeneration will provide new opportunities for dementia prevention and treatment. This study aimed to determine how ageing and major genetic risk factors for dementia affect the hippocampal proteome and lipidome of neurologically-normal humans over the age of 65. The hippocampus was chosen as it is highly susceptible to atrophy with ageing and in several neurodegenerative diseases.

METHODS

Mass spectrometry-based proteomic and lipidomic analysis of CA1 hippocampus samples from 74 neurologically normal human donors, aged 66-104, was used in combination with multiple regression models and gene set enrichment analysis to identify age-dependent changes in the proteome and lipidome. ANOVA was used to test the effect of major dementia risk alleles in the TMEM106B and APOE genes on the hippocampal proteome and lipidome, adjusting for age, gender, and post-mortem interval. Fibrillar C-terminal TMEM106B fragments were isolated using sarkosyl fractionation and quantified by immunoblotting.

RESULTS

Forty proteins were associated with age at false discovery rate-corrected P < 0.05, including proteins that regulate cell adhesion, the cytoskeleton, amino acid and lipid metabolism, and ribosomal subunits. TMEM106B, a regulator of lysosomal and oligodendrocyte function, was regulated with greatest effect size. The increase in TMEM106B levels with ageing was specific to carriers of the rs1990622-A allele in the TMEM106B gene that increases risk for frontotemporal dementia, Alzheimer's disease, Parkinson's disease, and hippocampal sclerosis with ageing. Rs1990622-A was also associated with higher TMEM106B fibril content. Hippocampal lipids were not significantly affected by APOE genotype, however levels of myelin-enriched sulfatides and hexosylceramides were significantly lower, and polyunsaturated phospholipids were higher, in rs1990622-A carriers after controlling for APOE genotype.

CONCLUSIONS

Our study demonstrates that TMEM106B protein abundance is increased with brain ageing in humans, establishes that dementia risk allele rs1990622-A predisposes to TMEM106B fibril formation in the hippocampus, and provides the first evidence that rs1990622-A affects brain lipid homeostasis, particularly myelin lipids. Our data suggests that TMEM106B is one of a growing list of major dementia risk genes that affect glial lipid metabolism.

More than just risk for Alzheimer's disease: APOE ε4's impact on the aging brain

The apolipoprotein ε4 (APOE ε4) allele is most commonly associated with increased risk for late-onset Alzheimer's disease (AD). However, recent longitudinal studies suggest that these risks are overestimated; most ε4 carriers will not develop dementia in their lifetime. In this article, we review new evidence regarding the impact of APOE ε4 on cognition among healthy older adults. We discuss emerging work from animal models suggesting that ε4 impacts brain structure and function in multiple ways that may lead to age-related cognitive impairment, independent from AD pathology. We discuss the importance of taking an individualized approach in future studies by incorporating biomarkers and neuroimaging methods that may better disentangle the phenotypic influences of APOE ε4 on the aging brain from prodromal AD pathology.

Plasma ceramides relate to mild cognitive impairment in middle-aged men: The Maastricht Study

Introduction

There is an urgent need for biomarkers identifying individuals at risk of early-stage cognitive impairment. Using cross-sectional data from The Maastricht Study, this study included 197 individuals with mild cognitive impairment (MCI) and 200 cognitively unimpaired individuals aged 40 to 75, matched by age, sex, and educational level.

Methods

We assessed the association of plasma sphingolipid and ceramide transfer protein (CERT) levels with MCI and adjusted for potentially confounding risk factors. Furthermore, the relationship of plasma sphingolipids and CERTs with magnetic resonance imaging brain volumes was assessed and age- and sex-stratified analyses were performed.

Results

Associations of plasma ceramide species C18:0 and C24:1 and combined plasma ceramide chain lengths (ceramide risk score) with MCI were moderated by sex, but not by age, and higher levels were associated with MCI in men. No associations were found among women. In addition, higher levels of ceramide C20:0, C22:0, and C24:1, but not the ceramide risk score, were associated with larger volume of the hippocampus after controlling for covariates, independent of MCI. Although higher plasma ceramide C18:0 was related to higher plasma CERT levels, no association of CERT levels was found with MCI or brain volumes.

Discussion

Our results warrant further analysis of plasma ceramides as potential markers for MCI in middle-aged men. In contrast to previous studies, no associations of plasma sphingolipids with MCI or brain volumes were found in women, independent of age. These results highlight the importance of accounting for sex- and age-related factors when examining sphingolipid and CERT metabolism related to cognitive function.

PRO: Do We Still Need Whole-Brain Irradiation for Brain Metastases?

(1) Background: In recent decades, the use of whole-brain radiation therapy (WBRT) in the treatment of brain metastases has significantly decreased, with clinicians fearing adverse neurocognitive events and data showing limited efficacy regarding local tumor control and overall survival. The present study thus aimed to reassess the role that WBRT holds in the treatment of brain metastases. (2) Methods: This review summarizes the available evidence from 1990 until today supporting the use of WBRT, as well as new developments in WBRT and their clinical implications. (3) Results: While one to four brain metastases should be exclusively treated with radiosurgery, WBRT does remain an option for patients with multiple metastases. In particular, hippocampus-avoidance WBRT, WBRT with dose escalation to the metastases, and their combination have shown promising results and offer valid alternatives to local stereotactic radiotherapy. Ongoing and published prospective trials on the efficacy and toxicity of these new methods are presented. (4) Conclusions: Unlike conventional WBRT, which has limited indications, modern WBRT techniques continue to have a significant role to play in the treatment of multiple brain metastases. In which situations radiosurgery or WBRT should be the first option should be investigated in further studies. Until then, the therapeutic decision must be made individually depending on the oncological context.

Detection of subclinical epileptiform discharges in Alzheimer's disease using long-term outpatient EEG monitoring

BACKGROUND

In patients with Alzheimer's disease (AD) without clinical seizures, up to half have epileptiform discharges on long-term in-patient electroencephalography (EEG) recordings. Long-term in-patient monitoring is obtrusive, and expensive as compared to outpatient monitoring. No studies have so far investigated if long-term outpatient EEG monitoring is able to identify epileptiform discharges in AD. Our aim is to investigate if epileptiform discharges as measured with ear-EEG are more common in patients with AD compared to healthy elderly controls (HC).

METHODS

In this longitudinal observational study, 24 patients with mild to moderate AD and 15 age-matched HC were included in the analysis. Patients with AD underwent up to three ear-EEG recordings, each lasting up to two days, within 6 months.

RESULTS

The first recording was defined as the baseline recording. At baseline, epileptiform discharges were detected in 75.0% of patients with AD and in 46.7% of HC (p-value = 0.073). The spike frequency (spikes or sharp waves/24 h) was significantly higher in patients with AD as compared to HC with a risk ratio of 2.90 (CI: 1.77-5.01, p < 0.001). Most patients with AD (91.7%) showed epileptiform discharges when combining all ear-EEG recordings.

CONCLUSIONS

Long-term ear-EEG monitoring detects epileptiform discharges in most patients with AD with a three-fold increased spike frequency compared to HC, which most likely originates from the temporal lobes. Since most patients showed epileptiform discharges with multiple recordings, elevated spike frequency should be considered a marker of hyperexcitability in AD.

Deriving a robust deep-learning model for subcortical brain segmentation by using a large-scale database: Preprocessing, reproducibility, and accuracy of volume estimation

Increasing the accuracy and reproducibility of subcortical brain segmentation is advantageous in various related clinical applications. In this study, we derived a segmentation method based on a convolutional neural network (i.e., U-Net) and a large-scale database consisting of 7039 brain T1-weighted MRI data samples. We evaluated the method by using experiments focused on three distinct topics, namely, the necessity of preprocessing steps, cross-institutional and longitudinal reproducibility, and volumetric accuracy. The optimized model, MX_RW-where "MX" is a mix of RW and nonuniform intensity normalization data and "RW" is raw data with basic preprocessing-did not require time-consuming preprocessing steps, such as nonuniform intensity normalization or image registration, for brain MRI before segmentation. Cross-institutional testing revealed that MX_RW (Dice similarity coefficient: 0.809, coefficient of variation: 4.6%, and Pearson's correlation coefficient: 0.979) exhibited a performance comparable with that of FreeSurfer (Dice similarity coefficient: 0.798, coefficient of variation: 5.6%, and Pearson's correlation coefficient: 0.973). The computation time per dataset of MX_RW was generally less than 5 s (even when tested without graphics processing units), which was notably faster than FreeSurfer. Thus, for time-restricted applications, MX_RW represents a competitive alternative to FreeSurfer.

Association of Dementia Risk With Focal Epilepsy and Modifiable Cardiovascular Risk Factors

Importance

Epilepsy has been associated with cognitive impairment and potentially dementia in older individuals. However, the extent to which epilepsy may increase dementia risk, how this compares with other neurological conditions, and how modifiable cardiovascular risk factors may affect this risk remain unclear.

Objective

To compare the differential risks of subsequent dementia for focal epilepsy compared with stroke and migraine as well as healthy controls, stratified by cardiovascular risk.

Design, Setting, and Participants

This cross-sectional study is based on data from the UK Biobank, a population-based cohort of more than 500 000 participants aged 38 to 72 years who underwent physiological measurements and cognitive testing and provided biological samples at 1 of 22 centers across the United Kingdom. Participants were eligible for this study if they were without dementia at baseline and had clinical data pertaining to a history of focal epilepsy, stroke, or migraine. The baseline assessment was performed from 2006 to 2010, and participants were followed up until 2021.

Exposures

Mutually exclusive groups of participants with epilepsy, stroke, and migraine at baseline assessment and controls (who had none of these conditions). Individuals were divided into low, moderate, or high cardiovascular risk groups based on factors that included waist to hip ratio, history of hypertension, hypercholesterolemia, diabetes, and smoking pack-years.

Main Outcomes and Measures

Incident all-cause dementia; measures of executive function; and brain total hippocampal, gray matter, and white matter hyperintensity volumes.

Results

Of 495 149 participants (225 481 [45.5%] men; mean [SD] age, 57.5 [8.1] years), 3864 had a diagnosis of focal epilepsy only, 6397 had a history of stroke only, and 14 518 had migraine only. Executive function was comparable between participants with epilepsy and stroke and worse than the control and migraine group. Focal epilepsy was associated with a higher risk of developing dementia (hazard ratio [HR], 4.02; 95% CI, 3.45 to 4.68; P < .001), compared with stroke (HR, 2.56; 95% CI, 2.28 to 2.87; P < .001), or migraine (HR, 1.02; 95% CI, 0.85 to 1.21; P = .94). Participants with focal epilepsy and high cardiovascular risk were more than 13 times more likely to develop dementia (HR, 13.66; 95% CI, 10.61 to 17.60; P < .001) compared with controls with low cardiovascular risk. The imaging subsample included 42 353 participants. Focal epilepsy was associated with lower hippocampal volume (mean difference, -0.17; 95% CI, -0.02 to -0.32; t = -2.18; P = .03) and lower total gray matter volume (mean difference, -0.33; 95% CI, -0.18 to -0.48; t = -4.29; P < .001) compared with controls. There was no significant difference in white matter hyperintensity volume (mean difference, 0.10; 95% CI, -0.07 to 0.26; t = 1.14; P = .26).

Conclusions and Relevance

In this study, focal epilepsy was associated with a significant risk of developing dementia, to a greater extent than stroke, which was magnified substantially in individuals with high cardiovascular risk. Further findings suggest that targeting modifiable cardiovascular risk factors may be an effective intervention to reduce dementia risk in individuals with epilepsy.

Socioeconomic Deprivation, Genetic Risk, and Incident Dementia

INTRODUCTION

Socioeconomic factors and genetic predisposition are established risk factors for dementia. It remains unclear whether associations of socioeconomic deprivation with dementia incidence are modified by genetic risk.

METHODS

Participants in the UK Biobank aged ≥60 years and of European ancestry without dementia at baseline (2006-2010) were eligible for the analysis, with the main exposures area-level deprivation based on the Townsend Deprivation Index and individual-level socioeconomic deprivation based on car and home ownership, housing type and income, and polygenic risk of dementia. Dementia was ascertained in hospital and death records. Analysis was conducted in 2021.

RESULTS

In this cohort study, 196,368 participants (mean [SD] age=64.1 [2.9] years, 52.7% female) were followed up for 1,545,316 person-years (median [IQR] follow-up=8.0 [7.4-8.6] years). In high genetic risk and high area-level deprivation, 1.71% (95% CI=1.44, 2.01) developed dementia compared with 0.56% (95% CI=0.48, 0.65) in low genetic risk and low-to-moderate area-level deprivation (hazard ratio=2.31; 95% CI=1.84, 2.91). In high genetic risk and high individual-level deprivation, 1.78% (95% CI=1.50, 2.09) developed dementia compared with 0.31% (95% CI=0.20, 0.45) in low genetic risk and low individual-level deprivation (hazard ratio=4.06; 95% CI=2.63, 6.26). There was no significant interaction between genetic risk and area-level (p=0.77) or individual-level (p=0.07) deprivation. An imaging substudy including 11,083 participants found a greater burden of white matter hyperintensities associated with higher socioeconomic deprivation.

CONCLUSIONS

Individual-level and area-level socioeconomic deprivation were associated with increased dementia risk. Dementia prevention interventions may be particularly effective if targeted to households and areas with fewer socioeconomic resources, regardless of genetic vulnerability.

Quantifying numerical and spatial reliability of hippocampal and amygdala subdivisions in FreeSurfer

On-going, large-scale neuroimaging initiatives can aid in uncovering neurobiological causes and correlates of poor mental health, disease pathology, and many other important conditions. As projects grow in scale with hundreds, even thousands, of individual participants and scans collected, quantification of brain structures by automated algorithms is becoming the only truly tractable approach. Here, we assessed the spatial and numerical reliability for newly deployed automated segmentation of hippocampal subfields and amygdala nuclei in FreeSurfer 7. In a sample of participants with repeated structural imaging scans (N = 928), we found numerical reliability (as assessed by intraclass correlations, ICCs) was reasonable. Approximately 95% of hippocampal subfields had "excellent" numerical reliability (ICCs ≥ 0.90), while only 67% of amygdala subnuclei met this same threshold. In terms of spatial reliability, 58% of hippocampal subfields and 44% of amygdala subnuclei had Dice coefficients ≥ 0.70. Notably, multiple regions had poor numerical and/or spatial reliability. We also examined correlations between spatial reliability and person-level factors (e.g., participant age; T1 image quality). Both sex and image scan quality were related to variations in spatial reliability metrics. Examined collectively, our work suggests caution should be exercised for a few hippocampal subfields and amygdala nuclei with more variable reliability.

Normative models for neuroimaging markers: Impact of model selection, sample size and evaluation criteria

Modelling population reference curves or normative modelling is increasingly used with the advent of large neuroimaging studies. In this paper we assess the performance of fitting methods from the perspective of clinical applications and investigate the influence of the sample size. Further, we evaluate linear and non-linear models for percentile curve estimation and highlight how the bias-variance trade-off manifests in typical neuroimaging data. We created plausible ground truth distributions of hippocampal volumes in the age range of 45 to 80 years, as an example application. Based on these distributions we repeatedly simulated samples for sizes between 50 and 50,000 data points, and for each simulated sample we fitted a range of normative models. We compared the fitted models and their variability across repetitions to the ground truth, with specific focus on the outer percentiles (1st, 5th, 10th) as these are the most clinically relevant. Our results quantify the expected decreasing trend in variance of the volume estimates with increasing sample size. However, bias in the volume estimates only decreases a modest amount, without much improvement at large sample sizes. The uncertainty of model performance is substantial for what would often be considered large samples in a neuroimaging context and rises dramatically at the ends of the age range, where fewer data points exist. Flexible models perform better across sample sizes, especially for non-linear ground truth. Surprisingly large samples of several thousand data points are needed to accurately capture outlying percentiles across the age range for applications in research and clinical settings. Performance evaluation methods should assess both bias and variance. Furthermore, caution is needed when attempting to go near the ends of the age range captured by the source data set and, as is a well known general principle, extrapolation beyond the age range should always be avoided. To help with such evaluations of normative models we have made our code available to guide researchers developing or utilising normative models.

Revisiting the stress recovery hypothesis: Differential associations of cortisol stress reactivity and recovery after acute psychosocial stress with markers of long-term stress and health

Exposure to excessive and long-term stress may result in dysregulation of the stress system, including the acute stress response. In particular, failure to downregulate stress-related reactivity may lead to prolonged stress responses and the accumulation of allostatic load. However, the contribution of altered acute cortisol recovery to chronic stress and associated health impairments has often been neglected. Addressing this lack of research, we explored whether recovery from - more so than reactivity to - acute stress captures the basal stress load of an individual. Using Piecewise Growth Curve Models with Landmark Registration, we analyzed cortisol reactivity and recovery slopes of 130 healthy participants exposed to a standardized psychosocial laboratory stressor. Reactivity and recovery were predicted by measures indicative of long-term stress and its downstream effects, including self-report questionnaires, diurnal cortisol indices [cortisol awakening response (CAR); diurnal cortisol slope], markers of pro-inflammatory activity (interleukin-6; high-sensitive C-reactive protein), and hippocampal volume (HCV). Among these measures, only an increased CAR was specifically and consistently associated with relatively impaired recovery. Since the CAR represents the physiological enhancement needed to meet the anticipated demands of the forthcoming day, this finding may highlight the contribution of cognitive processes in determining both CAR and acute stress recovery. Furthermore, greater cortisol reactivity covaried with smaller HCV, showing that increased acute reactivity translates to health-relevant downstream effects. The lack of further associations between long-term and acute stress measures may arise from biases in self-reported chronic stress and the rigorously health-screened study sample. Overall, our findings suggest that while cortisol stress recovery might not supersede reactivity as an indicator of the long-term stress load or associated health effects, recovery and reactivity have differential utility in describing individuals' allostatic states.

The major TMEM106B dementia risk allele affects TMEM106B protein levels and myelin lipid homeostasis in the ageing human hippocampus

Background The risk for dementia increases exponentially from the seventh decade of life. Identifying and understanding the biochemical changes that sensitize the ageing brain to neurodegeneration will provide new opportunities for dementia prevention and treatment. This study aimed to determine how ageing and major genetic risk factors for dementia affect the hippocampal proteome and lipidome of neurologically-normal humans over the age of 65. The hippocampus was chosen as it is highly susceptible to atrophy with ageing and in several neurodegenerative diseases. Methods Mass spectrometry-based proteomic and lipidomic analysis of CA1 hippocampus samples from 74 neurologically normal human donors, aged 66-104, was used in combination with multiple regression models and gene set enrichment analysis to identify age-dependent changes in the proteome and lipidome. ANOVA was used to test the effect of major dementia risk alleles in the TMEM106B and APOE genes on the hippocampal proteome and lipidome, adjusting for age, gender, and post-mortem interval. Results Forty proteins were associated with age at false discovery rate-corrected P < 0.05, including proteins that regulate cell adhesion, the cytoskeleton, amino acid and lipid metabolism, and ribosomal subunits. Transmembrane protein 106B (TMEM106B), a regulator of lysosomal and oligodendrocyte function, was regulated with greatest effect size. The increase in TMEM106B levels with age was specific to carriers of the rs1990622-A allele in the TMEM106B gene that is associated with increased risk for frontotemporal dementia, Alzheimer's disease, Parkinson's disease, and hippocampal sclerosis with ageing. Hippocampal lipids were not significantly affected by APOE genotype, however levels of myelin-enriched sulfatides and hexosylceramides were significantly lower, and polyunsaturated phospholipids were higher, in rs1990622-A carriers after controlling for APOE genotype. Conclusions Our study provides the first evidence that TMEM106B protein abundance is increased with brain ageing in humans, and the first evidence that the major TMEM106B dementia risk allele affects brain lipid homeostasis, with a clear effect on myelin lipid content. Our data implies that TMEM106B is one of a growing list of major dementia risk genes that affect glial lipid metabolism.

Deciphering the Effect of Different Genetic Variants on Hippocampal Subfield Volumes in the General Population

The aim of this study was to disentangle the effects of various genetic factors on hippocampal subfield volumes using three different approaches: a biologically driven candidate gene approach, a hypothesis-free GWAS approach, and a polygenic approach, where AD risk alleles are combined with a polygenic risk score (PRS). The impact of these genetic factors was investigated in a large dementia-free general population cohort from the Study of Health in Pomerania (SHIP, n = 1806). Analyses were performed using linear regression models adjusted for biological and environmental risk factors. Hippocampus subfield volume alterations were found for APOE ε4, BDNF Val, and 5-HTTLPR L allele carriers. In addition, we were able to replicate GWAS findings, especially for rs17178139 (MSRB3), rs1861979 (DPP4), rs7873551 (ASTN2), and rs572246240 (MAST4). Interaction analyses between the significant SNPs as well as the PRS for AD revealed no significant results. Our results confirm that hippocampal volume reductions are influenced by genetic variation, and that different variants reveal different association patterns that can be linked to biological processes in neurodegeneration. Thus, this study underlines the importance of specific genetic analyses in the quest for acquiring deeper insights into the biology of hippocampal volume loss, memory impairment, depression, and neurodegenerative diseases.

Changes in hippocampal volume during a preceding 10-year period do not correlate with cognitive performance and hippocampal blood‒brain barrier permeability in cognitively normal late-middle-aged men

Hippocampal blood-brain barrier (BBB) permeability may increase in normal healthy ageing and contribute to neurodegenerative disease. To examine this hypothesis, we investigated the correlation between blood-brain barrier (BBB) permeability, regional brain volume, memory functions and health and lifestyle factors in The Metropolit 1953 Danish Male Birth Cohort. We used dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with a gadolinium-based contrast agent to assess BBB permeability in 77 participants in the cohort. BBB permeability was measured as K_i values in the hippocampus, thalamus and white matter. Over a 10-year period, we observed progressive atrophy of both the left and right hippocampus (p = 0.001). There was no significant correlation between current BBB permeability and hippocampal volume, prior atrophy or cognition. The hippocampus volume ratio was associated with better visual and verbal memory scores (p < 0.01). Regional BBB differences revealed higher K_i values in the hippocampus and white matter than in the thalamus (p < 0.001). Participants diagnosed with type II diabetes had significantly higher BBB permeability in the white matter (p = 0.015) and thalamus (p = 0.016), which was associated with a higher Fazekas score (p = 0.024). We do not find evidence that BBB integrity is correlated with age-related hippocampal atrophy or cognitive functions. The association between diabetes, white matter hyperintensities and increased BBB permeability is consistent with the idea that cerebrovascular disease compromises BBB integrity. Our findings suggest that the hippocampus is particularly prone to age-related atrophy, which may explain some of the cognitive changes that accompany older age, but this prior atrophy is not correlated with current BBB permeability.

Age, Education Years, and Biochemical Factors Are Associated with Selective Neuronal Changes in the Elderly Hippocampus

Brain aging involves regional alterations of specific cellular subpopulations in the human hippocampus: a network hub for memory consolidation. The present study investigates whether age, sex, education years, and the concentration of neuropathological and inflammatory proteins influence neuronal-type marker expression in the elderly hippocampus. We analyzed the digital images (1 µm/pixel) of postmortem hippocampal sections from 19 non-demented individuals (from 78 to 99 years). This material was obtained from the "Aging Dementia and TBI Study" open database. Brain samples were processed through in situ hybridization (ISH) for the immunodetection of VGLUT1 (glutamatergic transporter) and GAT1 (GABAergic transporter) and mRNAs and Luminex protein quantifications. After image acquisition, we delineated the dentate gyrus, CA 3/2, and CA1 hippocampal subdivisions. Then, we estimated the area fraction in which the ISH markers were expressed. Increased VGLUT1 was observed in multiple hippocampal subfields at late ages. This glutamatergic marker is positively correlated with beta-amyloid and tau proteins and negatively correlated with interleukin-7 levels. Additionally, education years are positively correlated with GAT1 in the hippocampus of elderly women. This GABAergic marker expression is associated with interferon-gamma and brain-derived neurotrophic factor levels. These associations can help to explain how hippocampal sub-regions and neurotransmitter systems undergo distinct physiological changes during normal aging.

Challenges for machine learning in clinical translation of big data imaging studies

Combining deep learning image analysis methods and large-scale imaging datasets offers many opportunities to neuroscience imaging and epidemiology. However, despite these opportunities and the success of deep learning when applied to a range of neuroimaging tasks and domains, significant barriers continue to limit the impact of large-scale datasets and analysis tools. Here, we examine the main challenges and the approaches that have been explored to overcome them. We focus on issues relating to data availability, interpretability, evaluation, and logistical challenges and discuss the problems that still need to be tackled to enable the success of "big data" deep learning approaches beyond research.

Adapting UK Biobank imaging for use in a routine memory clinic setting: The Oxford Brain Health Clinic

The Oxford Brain Health Clinic (BHC) is a joint clinical-research service that provides memory clinic patients and clinicians access to high-quality assessments not routinely available, including brain MRI aligned with the UK Biobank imaging study (UKB). In this work we present how we 1) adapted the UKB MRI acquisition protocol to be suitable for memory clinic patients, 2) modified the imaging analysis pipeline to extract measures that are in line with radiology reports and 3) explored the alignment of measures from BHC patients to the largest brain MRI study in the world (ultimately 100,000 participants). Adaptations of the UKB acquisition protocol for BHC patients include dividing the scan into core and optional sequences (i.e., additional imaging modalities) to improve patients' tolerance for the MRI assessment. We adapted the UKB structural MRI analysis pipeline to take into account the characteristics of a memory clinic population (e.g., high amount of white matter hyperintensities and hippocampal atrophy). We then compared the imaging derived phenotypes (IDPs) extracted from the structural scans to visual ratings from radiology reports, non-imaging factors (age, cognition) and to reference distributions derived from UKB data. Of the first 108 BHC attendees (August 2020-November 2021), 92.5 % completed the clinical scans, 88.0 % consented to use of data for research, and 43.5 % completed the additional research sequences, demonstrating that the protocol is well tolerated. The high rates of consent to research makes this a valuable real-world quality research dataset routinely captured in a clinical service. Modified tissue-type segmentation with lesion masking greatly improved grey matter volume estimation. CSF-masking marginally improved hippocampal segmentation. The IDPs were in line with radiology reports and showed significant associations with age and cognitive performance, in line with the literature. Due to the age difference between memory clinic patients of the BHC (age range 65-101 years, average 78.3 years) and UKB participants (44-82 years, average 64 years), additional scans on elderly healthy controls are needed to improve reference distributions. Current and future work aims to integrate automated quantitative measures in the radiology reports and evaluate their clinical utility.

Pilates and Cognitive Stimulation in Dual Task an Intervention Protocol to Improve Functional Abilities and Minimize the Rate of Age-Related Cognitive Decline in Postmenopausal Women

It is already known the effectiveness of Pilates training on cognitive and functional abilities. It is also known that dual-task exercise and cognitive stimuli improve cognition and functional capacity. However, no previous report combined cognitive stimuli and Pilates in dual task and measured its effects on the cognitive and physical performances of postmenopausal women.

OBJECTIVE

To apply an interventional dual-task (PILATES-COG) protocol and to evaluate its influence on memory, language, and functional physical performances on healthy, community-dwelling postmenopausal older women.

METHODS

47 women with amenorrhea for at least 12 months participated in this study. Those allocated on the PILATES-COG group underwent a 12-week, twice a week regimen of 50 min sessions of simultaneous mat Pilates exercise program and cognitive tasks. Cognitive and physical functional performance were assessed. Two-way mixed ANOVA was used for data analysis, and Bonferroni post hoc tests were used for within- and between-group comparisons.

RESULTS

The PILATES-COG group showed significant improvement after the intervention in semantic verbal fluency (p < 0.001; ηρ² = 0.268), phonological verbal fluency (p < 0.019; ηρ² = 0.143), immediate memory (p < 0.001; ηρ² = 0.258), evocation memory (p < 0.001 ηρ² = 0.282), lower-limb muscle strength (p < 0.001; ηρ² = 0.447), balance (p < 0.001; ηρ² = 0.398), and dual-ask cost (p < 0.05; ηρ² = 0.111) assessments on healthy, community-dwelling postmenopausal older women.

CONCLUSION

This is the first report of a feasible and effective approach using Pilates and cognitive stimulation in dual task for the reduction of age-related cognitive decline and the improvement of physical functional performance in healthy postmenopausal women.

Brain aging differs with cognitive ability regardless of education

Higher general cognitive ability (GCA) is associated with lower risk of neurodegenerative disorders, but neural mechanisms are unknown. GCA could be associated with more cortical tissue, from young age, i.e. brain reserve, or less cortical atrophy in adulthood, i.e. brain maintenance. Controlling for education, we investigated the relative association of GCA with reserve and maintenance of cortical volume, -area and -thickness through the adult lifespan, using multiple longitudinal cognitively healthy brain imaging cohorts (n = 3327, 7002 MRI scans, baseline age 20-88 years, followed-up for up to 11 years). There were widespread positive relationships between GCA and cortical characteristics (level-level associations). In select regions, higher baseline GCA was associated with less atrophy over time (level-change associations). Relationships remained when controlling for polygenic scores for both GCA and education. Our findings suggest that higher GCA is associated with cortical volumes by both brain reserve and -maintenance mechanisms through the adult lifespan.

Nomograms of human hippocampal volume shifted by polygenic scores

Nomograms are important clinical tools applied widely in both developing and aging populations. They are generally constructed as normative models identifying cases as outliers to a distribution of healthy controls. Currently used normative models do not account for genetic heterogeneity. Hippocampal volume (HV) is a key endophenotype for many brain disorders. Here, we examine the impact of genetic adjustment on HV nomograms and the translational ability to detect dementia patients. Using imaging data from 35,686 healthy subjects aged 44-82 from the UK Biobank (UKB), we built HV nomograms using Gaussian process regression (GPR), which - compared to a previous method - extended the application age by 20 years, including dementia critical age ranges. Using HV polygenic scores (HV-PGS), we built genetically adjusted nomograms from participants stratified into the top and bottom 30% of HV-PGS. This shifted the nomograms in the expected directions by ~100 mm3 (2.3% of the average HV), which equates to 3 years of normal aging for a person aged ~65. Clinical impact of genetically adjusted nomograms was investigated by comparing 818 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database diagnosed as either cognitively normal (CN), having mild cognitive impairment (MCI) or Alzheimer's disease (AD) patients. While no significant change in the survival analysis was found for MCI-to-AD conversion, an average of 68% relative decrease was found in intra-diagnostic-group variance, highlighting the importance of genetic adjustment in untangling phenotypic heterogeneity.

Neuropathology and cholinesterase expression in the brains of octogenarians and older

A subset of octogenarians and older maintain normal cognitive function (CNOO) despite high prevalence and incidence of cognitive decline attributed to neurodegeneration or aging in the population. The rostral prefrontal cortex (rPFC) and hippocampal formation are brain regions integral to cognition, namely attention and memory, facilitated in part by cholinergic innervation. We hypothesized that preserved cholinergic neurotransmission in these regions contributes to intact cognition in the CNOO. To test this, we evaluated the burden of neuropathological and cholinesterase-associated protein aggregates in the rPFC and hippocampal formation. Tissues from age- and sex-matched CNOO and Alzheimer's disease (AD) rPFC and hippocampal formation were stained for β-amyloid (Aβ), tau, α-synuclein, phosphorylated TAR DNA-binding protein 43 (pTDP-43), acetylcholinesterase (AChE), and butyrylcholinesterase (BChE). The relative abundance of neuropathological aggregates was semi-quantitatively scored. Deposition of Aβ plaques, tau neurofibrillary tangles (NFT) and pTDP-43 inclusions were comparable between CNOO and AD cases. Intraneuronal Aβ and tau-positive thorny astrocytes consistent with aging-related tau astrogliopathy, were also noted in the rPFC. Abundance of BChE-positive plaque pathology was significantly higher in AD than in CNOO cases in most regions of interest, followed closely by abundance of AChE-positive plaque pathology. BChE- and AChE-activities were also associated with varied NFT morphologies. CNOO cases maintained cognition despite a high neuropathological burden in the rPFC and hippocampal formation. BChE-positive and, to a lesser extent, AChE-positive pathologies were significantly lower in most regions in the CNOO compared to AD. This suggests a specificity of cholinesterase-associated neuropathology with AD. We conclude that while CNOO have cholinesterase-associated neuropathology in the rPFC and hippocampal formation, abundance in this population is significantly lower compared to AD which may contribute to their intact cognition.

Higher-order multi-shell diffusion measures complement tensor metrics and volume in gray matter when predicting age and cognition

Recent advances in diffusion-weighted imaging have enabled us to probe the microstructure of even gray matter non-invasively. However, these advanced multi-shell protocols are often not included in large-scale studies as they significantly increase scan time. In this study, we investigated whether one set of multi-shell diffusion metrics commonly used in gray matter (as derived from Neurite Orientation Dispersion and Density Imaging, NODDI) provide enough additional information over typical tensor and volume metrics to justify the increased acquisition time, using the cognitive aging framework in the human hippocampus as a testbed. We first demonstrated that NODDI metrics are robust and reliable by replicating previous findings from our lab in a larger population of 79 younger (20.41 ± 1.89 years, 46 females) and 75 older (73.56 ± 6.26 years, 45 females) adults, showing that these metrics in the hippocampal subfields are sensitive to age and memory performance. We then asked how these subfield specific hippocampal NODDI metrics compared with standard tensor metrics and volume in predicting age and memory ability. We discovered that both NODDI and tensor measures separately predicted age and cognition in comparable capacities. However, integrating these modalities together considerably increased the predictive power of our logistic models, indicating that NODDI and tensor measures may be capturing independent microstructural information. We use these findings to encourage neuroimaging data collection consortiums to include a multi-shell diffusion sequence in their protocols since existing NODDI measures (and potential future multi-shell measures) may be able to capture microstructural variance that is missed by traditional approaches, even in studies exclusively examining gray matter.

Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging

A key aim in epidemiological neuroscience is identification of markers to assess brain health and monitor therapeutic interventions. Quantitative susceptibility mapping (QSM) is an emerging magnetic resonance imaging technique that measures tissue magnetic susceptibility and has been shown to detect pathological changes in tissue iron, myelin and calcification. We present an open resource of QSM-based imaging measures of multiple brain structures in 35,273 individuals from the UK Biobank prospective epidemiological study. We identify statistically significant associations of 251 phenotypes with magnetic susceptibility that include body iron, disease, diet and alcohol consumption. Genome-wide associations relate magnetic susceptibility to 76 replicating clusters of genetic variants with biological functions involving iron, calcium, myelin and extracellular matrix. These patterns of associations include relationships that are unique to QSM, in particular being complementary to T2* signal decay time measures. These new imaging phenotypes are being integrated into the core UK Biobank measures provided to researchers worldwide, creating the potential to discover new, non-invasive markers of brain health.

RapidPlan hippocampal sparing whole brain model version 2-how far can we reduce the dose?

Whole-brain radiotherapy has been the standard palliative treatment for patients with brain metastases due to its effectiveness, availability, and ease of administration. Recent clinical trials have shown that limiting radiation dose to the hippocampus is associated with decreased cognitive toxicity. In this study, we updated an existing Knowledge Based Planning model to further reduce dose to the hippocampus and improve other dosimetric plan quality characteristics. Forty-two clinical cases were contoured according to guidelines. A new dosimetric scorecard was created as an objective measure for plan quality. The new Hippocampal Sparing Whole Brain Version 2 (HSWBv2) model adopted a complex recursive training process and was validated with five additional cases. HSWBv2 treatment plans were generated on the Varian Halcyon^TM and TrueBeam^TM systems and compared against plans generated from the existing (HSWBv1) model released in 2016. On the Halcyon^TM platform, 42 cases were re-planned. Hippocampal D_100% from HSWBv2 and HSWBv1 models had an average dose of 5.75 Gy and 6.46 Gy, respectively (p < 0.001). HSWBv2 model also achieved a hippocampal D_mean of 7.49 Gy, vs 8.10 Gy in HSWBv1 model (p < 0.001). Hippocampal D_0.03CC from HSWBv2 model was 9.86 Gy, in contrast to 10.57 Gy in HSWBv1 (p < 0.001). For PTV_3000, D_98% and D_2% from HSWBv2 model were 28.27 Gy and 31.81 Gy, respectively, compared to 28.08 Gy (p = 0.020) and 32.66 Gy from HSWBv1 (p < 0.001). Among several other dosimetric quality improvements, there was a significant reduction in PTV_3000 V_105% from 35.35% (HSWBv1) to 6.44% (HSWBv2) (p < 0.001). On 5 additional validation cases, dosimetric improvements were also observed on TrueBeam^TM. In comparison to published data, the HSWBv2 model achieved higher quality hippocampal avoidance whole brain radiation therapy treatment plans through further reductions in hippocampal dose while improving target coverage and dose conformity/homogeneity. HSWBv2 model is shared publicly.

Prediction of Chronological Age in Healthy Elderly Subjects with Machine Learning from MRI Brain Segmentation and Cortical Parcellation

Normal aging is associated with changes in volumetric indices of brain atrophy. A quantitative understanding of age-related brain changes can shed light on successful aging. To investigate the effect of age on global and regional brain volumes and cortical thickness, 3514 magnetic resonance imaging scans were analyzed using automated brain segmentation and parcellation methods in elderly healthy individuals (69–88 years of age). The machine learning algorithm extreme gradient boosting (XGBoost) achieved a mean absolute error of 2 years in predicting the age of new subjects. Feature importance analysis showed that the brain-to-intracranial-volume ratio is the most important feature in predicting age, followed by the hippocampi volumes. The cortical thickness in temporal and parietal lobes showed a superior predictive value than frontal and occipital lobes. Insights from this approach that integrate model prediction and interpretation may help to shorten the current explanatory gap between chronological age and biological brain age.