Patterns of Regional Cerebral Blood Flow as a Function of Age Throughout the Lifespan

Biological age and brain age in midlife: relationship to multimorbidity and mental health

Biological age and brain age estimated using biological and neuroimaging measures have recently emerged as surrogate aging biomarkers shown to be predictive of diverse health outcomes. As aging underlies the development of many chronic conditions, surrogate aging biomarkers capture health at the whole person level, having the potential to improve our understanding of multimorbidity. Our study investigates whether elevated biological age and brain age are associated with an increased risk of multimorbidity using a large dataset from the Midlife in the United States Refresher study. Ensemble learning is utilized to combine multiple machine learning models to estimate biological age using a comprehensive set of biological markers. Brain age is obtained using Gaussian processes regression and neuroimaging data. Our study is the first to examine the relationship between accelerated brain age and multimorbidity. Furthermore, it is the first attempt to explore how biological age and brain age are related to multimorbidity in mental health. Our findings hold the potential to advance the understanding of disease accumulation and their relationship with aging.

The Legacy of the TTASAAN Report - Premature Conclusions and Forgotten Promises About SPECT Neuroimaging: A Review of Policy and Practice Part II

Brain perfusion single photon emission computed tomography (SPECT) scans were initially developed in 1970s. A key radiopharmaceutical, hexamethylpropyleneamine oxime (HMPAO), was not stabilized until 1993 and most early SPECT scans were performed on single-head gamma cameras. These early scans were of inferior quality. In 1996, the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology (TTASAAN) issued a report regarding the use of SPECT in the evaluation of neurological disorders. This two-part series explores the policies and procedures related to perfusion SPECT functional neuroimaging. In Part I, the comparison between the quality of the SPECT scans and the depth of the data for key neurological and psychiatric indications at the time of the TTASAAN report vs. the intervening 25 years were presented. In Part II, the technical aspects of perfusion SPECT neuroimaging and image processing will be explored. The role of color scales will be reviewed and the process of interpreting a SPECT scan will be presented. Interpretation of a functional brain scans requires not only anatomical knowledge, but also technical understanding on correctly performing a scan, regardless of the scanning modality. Awareness of technical limitations allows the clinician to properly interpret a functional brain scan. With this foundation, four scenarios in which perfusion SPECT neuroimaging, together with other imaging modalities and testing, lead to a narrowing of the differential diagnoses and better treatment. Lastly, recommendations for the revision of current policies and practices are made.

Factors Influencing Change in Brain-Predicted Age Difference in a Cohort of Healthy Older Individuals

Background

There is considerable variability in the rate at which we age biologically, and the brain is particularly susceptible to the effects of aging.

Objective

We examined the test-retest reliability of brain age at one- and three-year intervals and identified characteristics that predict the longitudinal change in brain-predicted age difference (brain-PAD, defined by deviations of brain age from chronological age).

Methods

T1-weighted magnetic resonance images were acquired at three timepoints from 497 community-dwelling adults (73.8±3.5 years at baseline, 48% were female). Brain age was estimated from whole brain volume, using a publicly available algorithm trained on an independent dataset. Linear mixed models were used, adjusting for sex, age, and age2.

Results

Excellent retest reliability of brain age was observed over one and three years. We identified a significant sex difference in brain-PAD, where a faster rate of brain aging (worsening in brain age relative to chronological age) was observed in men, and this finding replicated in secondary analyses. The effect size, however, was relatively weak, equivalent to 0.16 years difference per year. A higher score in physical health related quality of life and verbal fluency were associated with a faster rate of brain aging, while depression was linked to a slower rate of brain aging, but these findings were not robust.

Conclusion

Our study provides consistent evidence that older men have slightly faster brain atrophy than women. Given the sparsity of longitudinal research on brain age in older populations, future prospective studies are needed to confirm our findings.

Associations of alcohol use, HIV infection, and age with brain white matter microstructure

Heavy drinking and HIV infection are independently associated with damage to the brain's white matter. The purpose of the current study was to investigate whether current alcohol consumption, HIV infection, and associated characteristics were associated with indices of white matter microstructural integrity in people living with HIV (PLWH) and seronegative individuals. PLWH and controls were categorized as non-drinkers, moderate drinkers, or heavy drinkers. White matter fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) were assessed using diffusion tensor imaging (DTI). Voxelwise analyses using tract-based spatial statistics were followed by confirmatory region-of-interest (ROI) analyses. Data from 108 participants (62 PLWH, 46 controls) were suitable for analysis. Average age (± standard deviation) was 45.2 ± 11.1 years, and the sample was 42% female. The majority of PLWH were on antiretroviral therapy (94%) and were virally suppressed (69%). PLWH and controls did not differ on substance use. Heavier alcohol intake was significantly associated with lower FA and higher RD in widespread areas. Heavy drinking was significantly associated with higher AD in a small region. The main effect of HIV was not significant, but a significant HIV-age interaction was observed. Follow-up ROI analyses confirmed the main effect of drinking group and HIV-age interaction. In conclusion, results are consistent with a dose-dependent association of alcohol use with lower white matter microstructural coherence. Concordance between FA and RD findings suggests dysmyelination as a mechanism. Findings underscore the need to address unhealthy alcohol use in HIV-positive and seronegative individuals, the consequences of which may be exacerbated by aging.

Patterns of Regional Cerebral Blood Flow as a Function of Obesity in Adults

Background:

While obesity has been shown to be a risk factor for Alzheimer’s disease, the potential mechanisms underlying this risk may be clarified with better understanding of underlying physiology in obese persons.

Objective:

To identify patterns of cerebral perfusion abnormality in adults as a function of body mass index (BMI) defined weight categories, including overweight or obese status.

Methods:

A large psychiatric cohort of 35,442 brain scans across 17,721 adults (mean age 40.8±16.2 years, range 18–94 years) were imaged with SPECT during baseline and concentration scans, the latter done after each participant completed the Connors Continuous Performance Test II. ANOVA was done to identify patterns of perfusion abnormality in this cohort across BMI designations of underweight (BMI < 18.5), normal weight (BMI = 18.5 to 24.9), overweight (BMI 24.9 to 29.9), obesity (BMI≥30), and morbid obesity (BMI≥40). This analysis was done for 128 brain regions quantifying SPECT perfusion using the automated anatomical labeling (AAL) atlas.

Results:

Across adulthood, higher BMI correlated with decreased perfusion on both resting and concentration brain SPECT scans. These are seen in virtually all brain regions, including those influenced by AD pathology such as the hippocampus.

Conclusion:

Greater BMI is associated with cerebral perfusion decreases in both resting and concentration SPECT scans across adulthood.

Factors associated with brain ageing - a systematic review

Background

Brain age is a biomarker that predicts chronological age using neuroimaging features. Deviations of this predicted age from chronological age is considered a sign of age-related brain changes, or commonly referred to as brain ageing. The aim of this systematic review is to identify and synthesize the evidence for an association between lifestyle, health factors and diseases in adult populations, with brain ageing.

Methods

This systematic review was undertaken in accordance with the PRISMA guidelines. A systematic search of Embase and Medline was conducted to identify relevant articles using search terms relating to the prediction of age from neuroimaging data or brain ageing. The tables of two recent review papers on brain ageing were also examined to identify additional articles. Studies were limited to adult humans (aged 18 years and above), from clinical or general populations. Exposures and study design of all types were also considered eligible.

Results

A systematic search identified 52 studies, which examined brain ageing in clinical and community dwelling adults (mean age between 21 to 78 years, ~ 37% were female). Most research came from studies of individuals diagnosed with schizophrenia or Alzheimer’s disease, or healthy populations that were assessed cognitively. From these studies, psychiatric and neurologic diseases were most commonly associated with accelerated brain ageing, though not all studies drew the same conclusions. Evidence for all other exposures is nascent, and relatively inconsistent. Heterogenous methodologies, or methods of outcome ascertainment, were partly accountable.

Conclusion

This systematic review summarised the current evidence for an association between genetic, lifestyle, health, or diseases and brain ageing. Overall there is good evidence to suggest schizophrenia and Alzheimer’s disease are associated with accelerated brain ageing. Evidence for all other exposures was mixed or limited. This was mostly due to a lack of independent replication, and inconsistency across studies that were primarily cross sectional in nature. Future research efforts should focus on replicating current findings, using prospective datasets.

Trial registration

A copy of the review protocol can be accessed through PROSPERO, registration number CRD42020142817.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02331-4.

Normalization of Cerebral Blood Flow, Neurochemicals, and White Matter Integrity after Kidney Transplantation

BACKGROUND

CKD is associated with abnormalities in cerebral blood flow, cerebral neurochemical concentrations, and white matter integrity. Each of these is associated with adverse clinical consequences in the non-CKD population, which may explain the high prevalence of dementia and stroke in ESKD. Because cognition improves after kidney transplantation, comparing these brain abnormalities before and after kidney transplantation may identify potential reversibility in ESKD-associated brain abnormalities.

METHODS

In this study of patients with ESKD and age-matched healthy controls, we used arterial spin labeling to assess the effects of kidney transplantation on cerebral blood flow and magnetic resonance spectroscopic imaging to measure cerebral neurochemical concentrations (N-acetylaspartate, choline, glutamate, glutamine, myo-inositol, and total creatine). We also assessed white matter integrity measured by fractional anisotropy (FA) and mean diffusivity (MD) with diffusion tensor imaging. We used a linear mixed model analysis to compare longitudinal, repeated brain magnetic resonance imaging measurements before, 3 months after, and 12 months after transplantation and compared these findings with those of healthy controls.

RESULTS

Study participants included 29 patients with ESKD and 19 controls; 22 patients completed post-transplant magnetic resonance imaging. Cerebral blood flow, which was higher in patients pretransplant compared with controls (P=0.003), decreased post-transplant (P<0.001) to values in controls. Concentrations of neurochemicals choline and myo-inositol that were higher pretransplant compared with controls (P=0.001 and P<0.001, respectively) also normalized post-transplant (P<0.001 and P<0.001, respectively). FA increased (P=0.001) and MD decreased (P<0.001) post-transplant.

CONCLUSIONS

Certain brain abnormalities in CKD are reversible and normalize with kidney transplantation. Further studies are needed to understand the mechanisms underlying these brain abnormalities and to explore interventions to mitigate them even in patients who cannot be transplanted.

CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER

Cognitive Impairment and Imaging Correlates in End Stage Renal Disease, NCT01883349.

Consistent Cerebral Blood Flow Covariance Networks across Healthy Individuals and Their Similarity with Resting State Networks and Vascular Territories

Cerebral blood flow (CBF) represents the local blood supply to the brain, and it can be considered a proxy for neuronal activation. Independent component analysis (ICA) can be applied to CBF maps to derive patterns of spatial covariance across subjects. In the present study, we aimed to assess the consistency of the independent components derived from CBF maps (CBF-ICs) across a cohort of 92 healthy individuals. Moreover, we evaluated the spatial similarity of CBF-ICs with respect to resting state networks (RSNs) and vascular territories (VTs). The data were acquired on a 1.5 T scanner using arterial spin labeling (ASL) and resting state functional magnetic resonance imaging. Similarity was assessed considering the entire ASL dataset. Consistency was evaluated by splitting the dataset into subsamples according to three different criteria: (1) random split of age and sex-matched subjects, (2) elderly vs. young, and (3) males vs. females. After standard preprocessing, ICA was performed. Both consistency and similarity were assessed by visually comparing the CBF-ICs. Then, the degree of spatial overlap was quantified with Dice Similarity Coefficient (DSC). Frontal, left, and right occipital, cerebellar, and thalamic CBF-ICs were consistently identified among the subsamples, independently of age and sex, with fair to moderate overlap (0.2 < DSC ≤ 0.6). These regions are functional hubs, and their involvement in many neurodegenerative pathologies has been observed. As slight to moderate overlap (0.2< DSC < 0.5) was observed between CBF-ICs and some RSNs and VTs, CBF-ICs may mirror a combination of both functional and vascular brain properties.