Male brain ages faster: the age and gender dependence of subcortical volumes

Associations between cardiometabolic multimorbidity and cerebrospinal fluid biomarkers of Alzheimer's disease pathology in cognitively intact adults: the CABLE study

BACKGROUND

Cardiometabolic multimorbidity is associated with an increased risk of dementia, but the pathogenic mechanisms linking them remain largely undefined. We aimed to assess the associations of cardiometabolic multimorbidity with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathology to enhance our understanding of the underlying mechanisms linking cardiometabolic multimorbidity and AD.

METHODS

This study included 1464 cognitively intact participants from the Chinese Alzheimer's Biomarker and LifestylE (CABLE) database. Cardiometabolic diseases (CMD) are a group of interrelated disorders such as hypertension, diabetes, heart diseases (HD), and stroke. Based on the CMD status, participants were categorized as CMD-free, single CMD, or CMD multimorbidity. CMD multimorbidity is defined as the coexistence of two or more CMDs. The associations of cardiometabolic multimorbidity and CSF biomarkers were examined using multivariable linear regression models with demographic characteristics, the APOE ε4 allele, and lifestyle factors as covariates. Subgroup analyses stratified by age, sex, and APOE ε4 status were also performed.

RESULTS

A total of 1464 individuals (mean age, 61.80 years; age range, 40-89 years) were included. The markers of phosphorylated tau-related processes (CSF P-tau181: β = 0.165, P = 0.037) and neuronal injury (CSF T-tau: β = 0.065, P = 0.033) were significantly increased in subjects with CMD multimorbidity (versus CMD-free), but not in those with single CMD. The association between CMD multimorbidity with CSF T-tau levels remained significant after controlling for Aβ42 levels. Additionally, significantly elevated tau-related biomarkers were observed in patients with specific CMD combinations (i.e., hypertension and diabetes, hypertension and HD), especially in long disease courses.

CONCLUSIONS

The presence of cardiometabolic multimorbidity was associated with tau phosphorylation and neuronal injury in cognitively normal populations. CMD multimorbidity might be a potential independent target to alleviate tau-related pathologies that can cause cognitive impairment.

Exome-wide tandem repeats confer large effects on subcortical volumes in UK Biobank participants

The human subcortex is involved in memory and cognition. Structural and functional changes in subcortical regions is implicated in psychiatric conditions. We performed an association study of subcortical volumes using 15,941 tandem repeats (TRs) derived from whole exome sequencing (WES) data in 16,527 unrelated European ancestry participants. We identified 17 loci, most of which were associated with accumbens volume, and nine of which had fine-mapping probability supporting their causal effect on subcortical volume independent of surrounding variation. The most significant association involved NTN1 -[GCGG] N and increased accumbens volume (β=5.93, P=8.16x10 -9 ). Three exonic TRs had large effects on thalamus volume ( LAT2 -[CATC] N β=-949, P=3.84x10 -6 and SLC39A4 -[CAG] N β=-1599, P=2.42x10 -8 ) and pallidum volume ( MCM2 -[AGG] N β=-404.9, P=147x10 -7 ). These genetic effects were consistent measurements of per-repeat expansion/contraction effects on organism fitness. With 3-dimensional modeling, we reinforced these effects to show that the expanded and contracted LAT2 -[CATC] N repeat causes a frameshift mutation that prevents appropriate protein folding. These TRs also exhibited independent effects on several psychiatric symptoms, including LAT2 -[CATC] N and the tiredness/low energy symptom of depression (β=0.340, P=0.003). These findings link genetic variation to tractable biology in the brain and relevant psychiatric symptoms. We also chart one pathway for TR prioritization in future complex trait genetic studies.

Feasibility of brain age predictions from clinical T1-weighted MRIs

An individual's brain predicted age minus chronological age (brain-PAD) obtained from MRIs could become a biomarker of disease in research studies. However, brain age reports from clinical MRIs are scant despite the rich clinical information hospitals provide. Since clinical MRI protocols are meant for specific clinical purposes, performance of brain age predictions on clinical data need to be tested. We explored the feasibility of using DeepBrainNet, a deep network previously trained on research-oriented MRIs, to predict the brain ages of 840 patients who visited 15 facilities of a health system in Florida. Anticipating a strong prediction bias in our clinical sample, we characterized it to propose a covariate model in group-level regressions of brain-PAD (recommended to avoid Type I, II errors), and tested its generalizability, a requirement for meaningful brain age predictions in new single clinical cases. The best bias-related covariate model was scanner-independent and linear in age, while the best method to estimate bias-free brain ages was the inverse of a scanner-independent and quadratic in brain age function. We demonstrated the feasibility to detect sex-related differences in brain-PAD using group-level regression accounting for the selected covariate model. These differences were preserved after bias correction. The Mean-Average Error (MAE) of the predictions in independent data was ∼8 years, 2-3 years greater than reports for research-oriented MRIs using DeepBrainNet, whereas an R2 (assuming no bias) was 0.33 and 0.76 for the uncorrected and corrected brain ages, respectively. DeepBrainNet on clinical populations seems feasible, but more accurate algorithms or transfer-learning retraining is needed.

Volumetric Differences in Cerebellum and Brainstem in Patients with Migraine: A UK Biobank Study

Background: The cerebellum and the brainstem are two brain structures involved in pain processing and modulation that have also been associated with migraine pathophysiology. The aim of this study was to investigate possible associations between the morphology of the cerebellum and brainstem and migraine, focusing on gray matter differences in these brain areas. Methods: The analyses were based on data from 712 individuals with migraine and 45,681 healthy controls from the UK Biobank study. Generalized linear models were used to estimate the mean gray matter volumetric differences in the brainstem and the cerebellum. The models were adjusted for important biological covariates such as BMI, age, sex, total brain volume, diastolic blood pressure, alcohol intake frequency, current tobacco smoking, assessment center, material deprivation, ethnic background, and a wide variety of health conditions. Secondary analyses investigated volumetric correlation between cerebellar sub-regions. Results: We found larger gray matter volumes in the cerebellar sub-regions V (mean difference: 72 mm3, 95% CI [13, 132]), crus I (mean difference: 259 mm3, 95% CI [9, 510]), VIIIa (mean difference: 120 mm3, 95% CI [0.9, 238]), and X (mean difference: 14 mm3, 95% CI [1, 27]). Conclusions: Individuals with migraine show larger gray matter volumes in several cerebellar sub-regions than controls. These findings support the hypothesis that the cerebellum plays a role in the pathophysiology of migraine.

Gender-Specific Interactions in a Visual Object Recognition Task in Persons with Opioid Use Disorder

Opioid use disorder (OUD)-associated overdose deaths have reached epidemic proportions worldwide over the past two decades, with death rates for men reported at twice the rate for women. Using a controlled, cross-sectional, age-matched (18-56 y) design to better understand the cognitive neuroscience of OUD, we evaluated the electroencephalographic (EEG) responses of male and female participants with OUD vs. age- and gender-matched non-OUD controls during a simple visual object recognition Go/No-Go task. Overall, women had significantly slower reaction times (RTs) than men. In addition, EEG N200 and P300 event-related potential (ERP) amplitudes for non-OUD controls were significantly larger for men, while their latencies were significantly shorter than for women. However, while N200 and P300 amplitudes were not significantly affected by OUD for either men or women in this task, latencies were also affected differentially in men vs. women with OUD. Accordingly, for both N200 and P300, male OUD participants exhibited longer latencies while female OUD participants exhibited shorter ones than in non-OUD controls. Additionally, robust oscillations were found in all participants during a feedback message associated with performance in the task. Although alpha and beta power during the feedback message were significantly greater for men than women overall, both alpha and beta oscillations exhibited significantly lower power in all participants with OUD. Taken together, these findings suggest important gender by OUD differences in cognitive processing and reflection of performance in this simple visual task.

Sex Difference in Cigarette-Smoking Status and Its Association with Brain Volumes Using Large-Scale Community-Representative Data

BACKGROUND

Cigarette smoking is believed to accelerate age-related neurodegeneration. Despite significant sex differences in both smoking behaviors and brain structures, the active literature is equivocal in parsing out a sex difference in smoking-associated brain structural changes.

OBJECTIVE

The current study examined subcortical and lateral ventricle gray matter (GM) volume differences among smokers, active, past, and never-smokers, stratified by sex.

METHODS

The current study data included 1959 Dallas Heart Study (DHS) participants with valid brain imaging data. Stratified by gender, multiple-group comparisons of three cigarette-smoking groups were conducted to test whether there is any cigarette-smoking group differences in GM volumes of the selected regions of interest (ROIs).

RESULTS

The largest subcortical GM volumetric loss and enlargement of the lateral ventricle were observed among past smokers for both females and males. However, these observed group differences in GM volumetric changes were statistically significant only among males after adjusting for age and intracranial volumes.

CONCLUSIONS

The study findings suggest a sex difference in lifetime-smoking-associated GM volumetric changes, even after controlling for aging and intracranial volumes.

Assessing volumetric brain differences in migraine and depression patients: a UK Biobank study

BACKGROUND

Migraine and depression are two of the most common and debilitating conditions. From a clinical perspective, they are mostly prevalent in women and manifest a partial overlapping symptomatology. Despite the high level of comorbidity, previous studies hardly investigated possible common patterns in brain volumetric differences compared to healthy subjects. Therefore, the current study investigates and compares the volumetric difference patterns in sub-cortical regions between participants with migraine or depression in comparison to healthy controls.

METHODS

The study included data from 43 930 participants of the large UK Biobank cohort. Using official ICD10 diagnosis, we selected 712 participants with migraine, 1 853 with depression and 23 942 healthy controls. We estimated mean volumetric difference between the groups for the different sub-cortical brain regions using generalized linear regression models, conditioning the model within the levels of BMI, age, sex, ethnical background, diastolic blood pressure, current tobacco smoking, alcohol intake frequency, Assessment Centre, Indices of Multiple Deprivation, comorbidities and total brain volume.

RESULTS

We detected larger overall volume of the caudate (mean difference: 66, 95% CI [-3, 135]) and of the thalamus (mean difference: 103 mm³, 95% CI [-2, 208]) in migraineurs than healthy controls. We also observed that individuals with depression appear to have also larger overall (mean difference: 47 mm³, 95% CI [-7, 100]) and gray matter (mean difference: 49 mm³, 95% CI [2, 95]) putamen volumes than healthy controls, as well as larger amygdala volume (mean difference: 17 mm³, 95% CI [-7, 40]).

CONCLUSION

Migraineurs manifested larger overall volumes at the level of the nucleus caudate and of the thalamus, which might imply abnormal pain modulation and increased migraine susceptibility. Larger amygdala and putamen volumes in participants with depression than controls might be due to increased neuronal activity in these regions.

Molecular differences in brain regional vulnerability to aging between males and females

Background

Aging-related cognitive decline is associated with brain structural changes and synaptic loss. However, the molecular mechanisms of cognitive decline during normal aging remain elusive.

Results

Using the GTEx transcriptomic data from 13 brain regions, we identified aging-associated molecular alterations and cell-type compositions in males and females. We further constructed gene co-expression networks and identified aging-associated modules and key regulators shared by both sexes or specific to males or females. A few brain regions such as the hippocampus and the hypothalamus show specific vulnerability in males, while the cerebellar hemisphere and the anterior cingulate cortex regions manifest greater vulnerability in females than in males. Immune response genes are positively correlated with age, whereas those involved in neurogenesis are negatively correlated with age. Aging-associated genes identified in the hippocampus and the frontal cortex are significantly enriched for gene signatures implicated in Alzheimer's disease (AD) pathogenesis. In the hippocampus, a male-specific co-expression module is driven by key synaptic signaling regulators including VSNL1, INA, CHN1 and KCNH1; while in the cortex, a female-specific module is associated with neuron projection morphogenesis, which is driven by key regulators including SRPK2, REPS2 and FXYD1. In the cerebellar hemisphere, a myelination-associated module shared by males and females is driven by key regulators such as MOG, ENPP2, MYRF, ANLN, MAG and PLP1, which have been implicated in the development of AD and other neurodegenerative diseases.

Conclusions

This integrative network biology study systematically identifies molecular signatures and networks underlying brain regional vulnerability to aging in males and females. The findings pave the way for understanding the molecular mechanisms of gender differences in developing neurodegenerative diseases such as AD.

Evaluation of transorbital sonography measures of optic nerve diameter in the context of global and regional brain volume in multiple sclerosis

Transorbital sonography (TOS) could be a swift and convenient method to detect the atrophy of the optic nerve, possibly providing a marker that might reflect other quantitative structural markers of multiple sclerosis (MS). Here we evaluate the utility of TOS as a complementary tool for assessing optic nerve atrophy, and investigate how TOS-derived measures correspond to volumetric brain markers in MS. We recruited 25 healthy controls (HC) and 45 patients with relapsing-remitting MS and performed B-mode ultrasonographic examination of the optic nerve. Patients additionally underwent MRI scans to obtain T1-weighted, FLAIR and STIR images. Optic nerve diameters (OND) were compared between HC, MS patients with and without history of optic neuritis (non-ON) using a mixed-effects ANOVA model. The relationship between within-subject-average OND and global and regional brain volumetric measures was investigated using FSL SIENAX, voxel-based morphometry and FSL FIRST. OND was significantly different between HC-MS (HC = 3.2 ± 0.4 mm, MS = 3 ± 0.4 mm; p < 0.019) and we found significant correlation between average OND and normalised whole brain (β = 0.42, p < 0.005), grey matter (β = 0.33, p < 0.035), white matter (β = 0.38, p < 0.012) and ventricular cerebrospinal fluid volume (β = - 0.36, p < 0.021) in the MS group. History of ON had no impact on the association between OND and volumetric data. In conclusion, OND is a promising surrogate marker in MS, that can be simply and reliably measured using TOS, and its derived measures correspond to brain volumetric measures. It should be further explored in larger and longitudinal studies.

Multimodal imaging of the aging brain: Baseline findings of the LoCARPoN study

We quantified and investigated multimodal brain MRI measures in the LoCARPoN Study due to lack of normative data among Indians. A total of 401 participants (aged 50-88 years) without stroke or dementia completed MRI investigation. We assessed 31 brain measures in total using four brain MRI modalities, including macrostructural (global & lobar volumes, white matter hyperintensities [WMHs]), microstructural (global and tract-specific white matter fractional anisotropy [WM-FA] and mean diffusivity [MD]) and perfusion measures (global and lobar cerebral blood flow [CBF]). The absolute brain volumes of males were significantly larger than those of females, but such differences were relatively small (<1.2% of intracranial volume). With increasing age, lower macrostructural brain volumes, lower WM-FA, greater WMHs, higher WM-MD were found (P = 0.00018, Bonferroni threshold). Perfusion measures did not show significant differences with increasing age. Hippocampal volume showed the greatest association with age, with a reduction of approximately 0.48%/year. This preliminary study augments and provides insight into multimodal brain measures during the nascent stages of aging among the Indian population (South Asian ethnicity). Our findings establish the groundwork for future hypothetical testing studies.

Confounds in neuroimaging: A clear case of sex as a confound in brain-based prediction

Muscle weakness is common in many neurological, neuromuscular, and musculoskeletal conditions. Muscle size only partially explains muscle strength as adaptions within the nervous system also contribute to strength. Brain-based biomarkers of neuromuscular function could provide diagnostic, prognostic, and predictive value in treating these disorders. Therefore, we sought to characterize and quantify the brain's contribution to strength by developing multimodal MRI pipelines to predict grip strength. However, the prediction of strength was not straightforward, and we present a case of sex being a clear confound in brain decoding analyses. While each MRI modality-structural MRI (i.e., gray matter morphometry), diffusion MRI (i.e., white matter fractional anisotropy), resting state functional MRI (i.e., functional connectivity), and task-evoked functional MRI (i.e., left or right hand motor task activation)-and a multimodal prediction pipeline demonstrated significant predictive power for strength (R ² = 0.108-0.536, p ≤ 0.001), after correcting for sex, the predictive power was substantially reduced (R ² = -0.038-0.075). Next, we flipped the analysis and demonstrated that each MRI modality and a multimodal prediction pipeline could significantly predict sex (accuracy = 68.0%-93.3%, AUC = 0.780-0.982, p < 0.001). However, correcting the brain features for strength reduced the accuracy for predicting sex (accuracy = 57.3%-69.3%, AUC = 0.615-0.780). Here we demonstrate the effects of sex-correlated confounds in brain-based predictive models across multiple brain MRI modalities for both regression and classification models. We discuss implications of confounds in predictive modeling and the development of brain-based MRI biomarkers, as well as possible strategies to overcome these barriers.

Thalamic nuclei atrophy at high and heterogenous rates during cognitively unimpaired human aging

The thalamus is a central integration structure in the brain, receiving and distributing information among the cerebral cortex, subcortical structures, and the peripheral nervous system. Prior studies clearly show that the thalamus atrophies in cognitively unimpaired aging. However, the thalamus is comprised of multiple nuclei involved in a wide range of functions, and the age-related atrophy of individual thalamic nuclei remains unknown. Using a recently developed automated method of identifying thalamic nuclei (3T or 7T MRI with white-matter-nulled MPRAGE contrast and THOMAS segmentation) and a cross-sectional design, we evaluated the age-related atrophy rate for 10 thalamic nuclei (AV, CM, VA, VLA, VLP, VPL, pulvinar, LGN, MGN, MD) and an epithalamic nucleus (habenula). We also used T1-weighted images with the FreeSurfer SAMSEG segmentation method to identify and measure age-related atrophy for 11 extra-thalamic structures (cerebral cortex, cerebral white matter, cerebellar cortex, cerebellar white matter, amygdala, hippocampus, caudate, putamen, nucleus accumbens, pallidum, and lateral ventricle). In 198 cognitively unimpaired participants with ages spanning 20-88 years, we found that the whole thalamus atrophied at a rate of 0.45% per year, and that thalamic nuclei had widely varying age-related atrophy rates, ranging from 0.06% to 1.18% per year. A functional grouping analysis revealed that the thalamic nuclei involved in cognitive (AV, MD; 0.53% atrophy per year), visual (LGN, pulvinar; 0.62% atrophy per year), and auditory/vestibular (MGN; 0.64% atrophy per year) functions atrophied at significantly higher rates than those involved in motor (VA, VLA, VLP, and CM; 0.37% atrophy per year) and somatosensory (VPL; 0.32% atrophy per year) functions. A proximity-to-CSF analysis showed that the group of thalamic nuclei situated immediately adjacent to CSF atrophied at a significantly greater atrophy rate (0.59% atrophy per year) than that of the group of nuclei located farther from CSF (0.36% atrophy per year), supporting a growing hypothesis that CSF-mediated factors contribute to neurodegeneration. We did not find any significant hemispheric differences in these rates of change for thalamic nuclei. Only the CM thalamic nucleus showed a sex-specific difference in atrophy rates, atrophying at a greater rate in male versus female participants. Roughly half of the thalamic nuclei showed greater atrophy than all extra-thalamic structures examined (0% to 0.54% per year). These results show the value of white-matter-nulled MPRAGE imaging and THOMAS segmentation for measuring distinct thalamic nuclei and for characterizing the high and heterogeneous atrophy rates of the thalamus and its nuclei across the adult lifespan. Collectively, these methods and results advance our understanding of the role of thalamic substructures in neurocognitive and disease-related changes that occur with aging.

A Causal Analysis of the Effect of Age and Sex Differences on Brain Atrophy in the Elderly Brain

We studied how brain volume loss in old age is affected by age, the APOE gene, sex, and the level of education completed. The quantitative characterization of brain volume loss at an old age relative to a young age requires-at least in principle-two MRI scans, one performed at a young age and one at an old age. There is, however, a way to address this problem when having only one MRI scan obtained at an old age. We computed the total brain losses of elderly subjects as a ratio between the estimated brain volume and the estimated total intracranial volume. Magnetic resonance imaging (MRI) scans of 890 healthy subjects aged 70 to 85 years were assessed. A causal analysis of factors affecting brain atrophy was performed using probabilistic Bayesian modelling and the mathematics of causal inference. We found that both age and sex were causally related to brain atrophy, with women reaching an elderly age with a 1% larger brain volume relative to their intracranial volume than men. How the brain ages and the rationale for sex differences in brain volume losses during the adult lifespan are questions that need to be addressed with causal inference and empirical data. The graphical causal modelling presented here can be instrumental in understanding a puzzling scientific area of study-the biological aging of the brain.

Chromosomal and environmental contributions to sex differences in the vulnerability to neurological and neuropsychiatric disorders: Implications for therapeutic interventions

Neurological and neuropsychiatric disorders affect men and women differently. Multiple sclerosis, Alzheimer's disease, anxiety disorders, depression, meningiomas and late-onset schizophrenia affect women more frequently than men. By contrast, Parkinson's disease, autism spectrum condition, attention-deficit hyperactivity disorder, Tourette's syndrome, amyotrophic lateral sclerosis and early-onset schizophrenia are more prevalent in men. Women have been historically under-recruited or excluded from clinical trials, and most basic research uses male rodent cells or animals as disease models, rarely studying both sexes and factoring sex as a potential source of variation, resulting in a poor understanding of the underlying biological reasons for sex and gender differences in the development of such diseases. Putative pathophysiological contributors include hormones and epigenetics regulators but additional biological and non-biological influences may be at play. We review here the evidence for the underpinning role of the sex chromosome complement, X chromosome inactivation, and environmental and epigenetic regulators in sex differences in the vulnerability to brain disease. We conclude that there is a pressing need for a better understanding of the genetic, epigenetic and environmental mechanisms sustaining sex differences in such diseases, which is critical for developing a precision medicine approach based on sex-tailored prevention and treatment.

Automated brain volumetric program measuring regional brain atrophy in diagnosis of mild cognitive impairment and Alzheimer's disease dementia

A quantitative analysis of brain volume can assist in the diagnosis of Alzheimer's disease (AD) which is ususally accompanied by brain atrophy. With an automated analysis program Quick Brain Volumetry (QBraVo) developed for volumetric measurements, we measured regional volumes and ratios to evaluate their performance in discriminating AD dementia (ADD) and mild cognitive impairment (MCI) patients from normal controls (NC). Validation of QBraVo was based on intra-rater and inter-rater reliability with a manual measurement. The regional volumes and ratios to total intracranial volume (TIV) and to total brain volume (TBV) or total cerebrospinal fluid volume (TCV) were compared among subjects. The regional volume to total cerebellar volume ratio named Standardized Atrophy Volume Ratio (SAVR) was calculated to compare brain atrophy. Diagnostic performances to distinguish among NC, MCI, and ADD were compared between MMSE, SAVR, and the predictive model. In total, 56 NCs, 44 MCI, and 45 ADD patients were enrolled. The average run time of QBraVo was 5 min 36 seconds. Intra-rater reliability was 0.999. Inter-rater reliability was high for TBV, TCV, and TIV (R = 0.97, 0.89 and 0.93, respectively). The medial temporal SAVR showed the highest performance for discriminating ADD from NC (AUC = 0.808, diagnostic accuracy = 80.2%). The predictive model using both MMSE and medial temporal SAVR improved the diagnostic performance for MCI in NC (AUC = 0.844, diagnostic accuracy = 79%). Our results demonstrated QBraVo is a fast and accurate method to measure brain volume. The regional volume calculated as SAVR could help to diagnose ADD and MCI and increase diagnostic accuracy for MCI.

Kidney function, brain morphology and cognition in the elderly: sex differences in the Austrian Stroke Prevention Study

Impaired kidney function is associated with structural brain changes and cognitive dysfunction. In the aging kidney, hemodynamic and structural alterations reduce the glomerular filtration rate (eGFR). Little is known about differences between men and women regarding decline of kidney function and brain damage.

In this community-based study, we assessed associations between the eGFR, focal and diffuse brain abnormalities and cognitive functions. Sex-specific effects were analyzed by interaction terms eGFR x sex on brain structure and cognition. Interactive effects were assessed using mixed-models –stratified by sex.

Overall, 196 women and 129 men (median age 68 years and mean eGFR 73.8±14.9 ml/min/1.73m²) were included. Significant associations existed between eGFR and cortical volume (β: 1.53E-04; SE: 6.72E-05; p=0.023 for neocortex). Sex exerted a significant interactive effect. Only in men, eGFR related to cortical volumes of all lobes and of deep gray matter structures (p= 0.001 for total gray matter, p=0.0004 for neocortex). In the whole group eGFR was not associated with cognition, but men with lower eGFR performed worse on tests for executive function, which, after FDR correction, was not significant.

We conclude, that in community-dwelling middle-aged and elderly individuals, reduced eGFR relates to brain volume loss in men but not in women.

Resting State Alpha Electroencephalographic Rhythms Are Affected by Sex in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment: A Retrospective and Exploratory Study

In the present retrospective and exploratory study, we tested the hypothesis that sex may affect cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms recorded in normal elderly (Nold) seniors and patients with Alzheimer's disease and mild cognitive impairment (ADMCI). Datasets in 69 ADMCI and 57 Nold individuals were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands and fixed beta (14-30 Hz) and gamma (30-40 Hz) bands. Each group was stratified into matched females and males. The sex factor affected the magnitude of rsEEG source activities in the Nold seniors. Compared with the males, the females were characterized by greater alpha source activities in all cortical regions. Similarly, the parietal, temporal, and occipital alpha source activities were greater in the ADMCI-females than the males. Notably, the present sex effects did not depend on core genetic (APOE4), neuropathological (Aβ42/phospho-tau ratio in the cerebrospinal fluid), structural neurodegenerative and cerebrovascular (MRI) variables characterizing sporadic AD-related processes in ADMCI seniors. These results suggest the sex factor may significantly affect neurophysiological brain neural oscillatory synchronization mechanisms underpinning the generation of dominant rsEEG alpha rhythms to regulate cortical arousal during quiet vigilance.

Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder. Neuroanatomic heterogeneity limits our understanding of ADHD's etiology. This study aimed to parse heterogeneity of ADHD and to determine whether patient subgroups could be discerned based on subcortical brain volumes.

METHODS

Using the large ENIGMA-ADHD Working Group dataset, four subsamples of 993 boys with and without ADHD and to subsamples of 653 adult men, 400 girls, and 447 women were included in analyses. We applied exploratory factor analysis (EFA) to seven subcortical volumes in order to constrain the complexity of the input variables and ensure more stable clustering results. Factor scores derived from the EFA were used to build networks. A community detection (CD) algorithm clustered participants into subgroups based on the networks.

RESULTS

Exploratory factor analysis revealed three factors (basal ganglia, limbic system, and thalamus) in boys and men with and without ADHD. Factor structures for girls and women differed from those in males. Given sample size considerations, we concentrated subsequent analyses on males. Male participants could be separated into four communities, of which one was absent in healthy men. Significant case-control differences of subcortical volumes were observed within communities in boys, often with stronger effect sizes compared to the entire sample. As in the entire sample, none were observed in men. Affected men in two of the communities presented comorbidities more frequently than those in other communities. There were no significant differences in ADHD symptom severity, IQ, and medication use between communities in either boys or men.

CONCLUSIONS

Our results indicate that neuroanatomic heterogeneity in subcortical volumes exists, irrespective of ADHD diagnosis. Effect sizes of case-control differences appear more pronounced at least in some of the subgroups.

Structural brain volumes of individuals at clinical high risk for psychosis: a meta-analysis

Background

Structural magnetic resonance imaging studies in individuals at clinical high risk (CHR) for psychosis have yielded conflicting results.

Methods

The aims of this study were to compare intracranial and structural brain volumes and variability of CHR individuals with those of healthy control (HC) subjects and to investigate brain volume differences and variability in CHR subjects with and without transition to psychosis. The PubMed and Embase databases were searched for relevant studies published before June 1, 2020.

Results

A total of 34 studies were deemed eligible, which included baseline data of 2111 CHR and 1472 HC participants. In addition, data were included for 401 CHR subjects who subsequently transitioned to psychosis and 1023 nontransitioned CHR participants. Whole-brain and left, right, and bilateral hippocampal volume were significantly smaller in CHR subjects than in HC subjects. Cerebrospinal fluid and lateral ventricle volumes were significantly larger in CHR subjects than in HC subjects. Variability was not significantly different in CHR subjects compared with HC subjects. CHR individuals with and without subsequent transition to psychosis did not show significant differences in any of the volumetric assessments or in variability.

Conclusions

This meta-analysis demonstrates reduced whole-brain and hippocampal volumes and increased cerebrospinal fluid and lateral ventricle volumes in CHR individuals. However, no significant differences were observed in any of the volumetric assessments between CHR individuals with and without subsequent transition to psychosis. These findings suggest that although structural brain alterations are present before the onset of the disorder, they may not significantly contribute to the identification of CHR individuals at the highest risk for the development of psychosis.

Sex differences in brain atrophy and cognitive impairment in Parkinson's disease patients with and without probable rapid eye movement sleep behavior disorder

Background

The presence of rapid eye movement sleep behavior disorder (RBD) contributes to increase cognitive impairment and brain atrophy in Parkinson’s disease (PD), but the impact of sex is unclear. We aimed to investigate sex differences in cognition and brain atrophy in PD patients with and without probable RBD (pRBD).

Methods

Magnetic resonance imaging and cognition data were obtained for 274 participants from the Parkinson's Progression Marker Initiative database: 79 PD with pRBD (PD-pRBD; male/female, 54/25), 126 PD without pRBD (PD-non pRBD; male/female, 73/53), and 69 healthy controls (male/female, 40/29). FreeSurfer was used to obtain volumetric and cortical thickness data.

Results

Males showed greater global cortical and subcortical gray matter atrophy than females in the PD-pRBD group. Significant group-by-sex interactions were found in the pallidum. Structures showing a within-group sex effect in the deep gray matter differed, with significant volume reductions for males in one structure in in PD-non pRBD (brainstem), and three in PD-pRBD (caudate, pallidum and brainstem). Significant group-by-sex interactions were found in Montreal Cognitive Assessment (MoCA) and Symbol Digits Modalities Test (SDMT). Males performed worse than females in MoCA, phonemic fluency and SDMT in the PD-pRBD group.

Conclusion

Male sex is related to increased cognitive impairment and subcortical atrophy in de novo PD-pRBD. Accordingly, we suggest that sex differences are relevant and should be considered in future clinical and translational research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10728-x.

Intra- and interhemispheric symmetry of subcortical brain structures: a volumetric analysis in the aging human brain

Here, we address the hemispheric interdependency of subcortical structures in the aging human brain. In particular, we investigated whether subcortical volume variations can be explained by the adjacency of structures in the same hemisphere or are due to the interhemispheric development of mirror subcortical structures in the brain. Seven subcortical structures in each hemisphere were automatically segmented in a large sample of 3312 magnetic resonance imaging (MRI) studies of elderly individuals in their 70s and 80s. We performed Eigenvalue analysis, and found that anatomic volumes in the limbic system and basal ganglia show similar statistical dependency whether considered in the same hemisphere (intrahemispherically) or different hemispheres (interhemispherically). Our results indicate that anatomic bilaterality of subcortical volumes is preserved in the aging human brain, supporting the hypothesis that coupling between non-adjacent subcortical structures might act as a mechanism to compensate for the deleterious effects of aging.

Structural volume and cortical thickness differences between males and females in cognitively normal, cognitively impaired and Alzheimer's dementia population

We investigated differences due to sex in brain structural volume and cortical thickness in older cognitively normal (N=742), cognitively impaired (MCI; N=540) and Alzheimer's Dementia (AD; N=402) individuals from the ADNI and AIBL datasets (861 Males and 823 Females). General linear models were used to control the effect of relevant covariates including age, intracranial volume, magnetic resonance imaging (MRI) scanner field strength and scanner types. Significant volumetric differences due to sex were observed within different cortical and subcortical regions of the cognitively normal group. The number of significantly different regions was reduced in the MCI group, and no region remained different in the AD group. Cortical thickness was overall thinner in males than females in the cognitively normal group, and likewise, the differences due to sex were reduced in the MCI and AD groups. These findings were sustained after including cerebrospinal fluid (CSF) Tau and phosphorylated tau (pTau) as additional covariates.

Smaller total brain volume but not subcortical structure volume related to common genetic risk for ADHD

BACKGROUND

Mechanistic endophenotypes can inform process models of psychopathology and aid interpretation of genetic risk factors. Smaller total brain and subcortical volumes are associated with attention-deficit hyperactivity disorder (ADHD) and provide clues to its development. This study evaluates whether common genetic risk for ADHD is associated with total brain volume (TBV) and hypothesized subcortical structures in children.

METHODS

Children 7-15 years old were recruited for a case-control study (N = 312, N = 199 ADHD). Children were assessed with a multi-informant, best-estimate diagnostic procedure and motion-corrected MRI measured brain volumes. Polygenic scores were computed based on discovery data from the Psychiatric Genomics Consortium (N = 19 099 ADHD, N = 34 194 controls) and the ENIGMA + CHARGE consortium (N = 26 577).

RESULTS

ADHD was associated with smaller TBV, and altered volumes of caudate, cerebellum, putamen, and thalamus after adjustment for TBV; however, effects were larger and statistically reliable only in boys. TBV was associated with an ADHD polygenic score [β = -0.147 (-0.27 to -0.03)], and mediated a small proportion of the effect of polygenic risk on ADHD diagnosis (average ACME = 0.0087, p = 0.012). This finding was stronger in boys (average ACME = 0.019, p = 0.008). In addition, we confirm genetic variation associated with whole brain volume, via an intracranial volume polygenic score.

CONCLUSION

Common genetic risk for ADHD is not expressed primarily as developmental alterations in subcortical brain volumes, but appears to alter brain development in other ways, as evidenced by TBV differences. This is among the first demonstrations of this effect using molecular genetic data. Potential sex differences in these effects warrant further examination.

Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder which spans several years from preclinical manifestations to dementia. In recent years, interest in the application of machine learning (ML) algorithms to personalized medicine has grown considerably, and a major challenge that such models face is the transferability from the research settings to clinical practice. The objective of this work was to demonstrate the transferability of the Subtype and Stage Inference (SuStaIn) model from well-characterized research data set, employed as training set, to independent less-structured and heterogeneous test sets representative of the clinical setting. The training set was composed of MRI data of 1043 subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI), and the test set was composed of data from 767 subjects from OASIS, Pharma-Cog, and ViTA clinical datasets. Both sets included subjects covering the entire spectrum of AD, and for both sets volumes of relevant brain regions were derived from T1-3D MRI scans processed with Freesurfer v5.3 cross-sectional stream. In order to assess the predictive value of the model, subpopulations of subjects with stable mild cognitive impairment (MCI) and MCIs that progressed to AD dementia (pMCI) were identified in both sets. SuStaIn identified three disease subtypes, of which the most prevalent corresponded to the typical atrophy pattern of AD. The other SuStaIn subtypes exhibited similarities with the previously defined hippocampal sparing and limbic predominant atrophy patterns of AD. Subject subtyping proved to be consistent in time for all cohorts and the staging provided by the model was correlated with cognitive performance. Classification of subjects on the basis of a combination of SuStaIn subtype and stage, mini mental state examination and amyloid-β_1-42 cerebrospinal fluid concentration was proven to predict conversion from MCI to AD dementia on par with other novel statistical algorithms, with ROC curves that were not statistically different for the training and test sets and with area under curve respectively equal to 0.77 and 0.76. This study proves the transferability of a SuStaIn model for AD from research data to less-structured clinical cohorts, and indicates transferability to the clinical setting.

Genetic scores for adult subcortical volumes associate with subcortical volumes during infancy and childhood

Individual differences in subcortical brain volumes are highly heritable. Previous studies have identified genetic variants that underlie variation in subcortical volumes in adults. We tested whether those previously identified variants also affect subcortical regions during infancy and early childhood. The study was performed within the Generation R study, a prospective birth cohort. We calculated polygenic scores based on reported GWAS for volumes of the accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus. Participants underwent cranial ultrasound around 7 weeks of age (range: 3-20), and we obtained metrics for the gangliothalamic ovoid, a predecessor of the basal ganglia. Furthermore, the children participated in a magnetic resonance imaging (MRI) study around the age of 10 years (range: 9-12). A total of 340 children had complete data at both examinations. Polygenic scores primarily associated with their corresponding volumes at 10 years of age. The scores also moderately related to the diameter of the gangliothalamic ovoid on cranial ultrasound. Mediation analysis showed that the genetic influence on subcortical volumes at 10 years was only mediated for 16.5-17.6% of the total effect through the gangliothalamic ovoid diameter at 7 weeks of age. Combined, these findings suggest that previously identified genetic variants in adults are relevant for subcortical volumes during early life, and that they affect both prenatal and postnatal development of the subcortical regions.

Dump the "dimorphism": Comprehensive synthesis of human brain studies reveals few male-female differences beyond size

With the explosion of neuroimaging, differences between male and female brains have been exhaustively analyzed. Here we synthesize three decades of human MRI and postmortem data, emphasizing meta-analyses and other large studies, which collectively reveal few reliable sex/gender differences and a history of unreplicated claims. Males' brains are larger than females' from birth, stabilizing around 11 % in adults. This size difference accounts for other reproducible findings: higher white/gray matter ratio, intra- versus interhemispheric connectivity, and regional cortical and subcortical volumes in males. But when structural and lateralization differences are present independent of size, sex/gender explains only about 1% of total variance. Connectome differences and multivariate sex/gender prediction are largely based on brain size, and perform poorly across diverse populations. Task-based fMRI has especially failed to find reproducible activation differences between men and women in verbal, spatial or emotion processing due to high rates of false discovery. Overall, male/female brain differences appear trivial and population-specific. The human brain is not "sexually dimorphic."

Sex effects on brain structure in de novo Parkinson's disease: a multimodal neuroimaging study

Parkinson's disease varies in severity and age of onset. One source of this variability is sex. Males are twice as likely as females to develop Parkinson's disease, and tend to have more severe symptoms and greater speed of progression. However, to date, there is little information in large cohorts on sex differences in the patterns of neurodegeneration. Here we used MRI and clinical information from the Parkinson Progression Markers Initiative to measure structural brain differences between sexes in Parkinson's disease after regressing out the expected effect of age and sex. We derived atrophy maps from deformation-based morphometry of T1-weighted MRI and connectivity from diffusion-weighted MRI in de novo Parkinson's disease patients (149 males: 83 females) with comparable clinical severity, and healthy control participants (78 males: 39 females). Overall, even though the two patient groups were matched for disease duration and severity, males demonstrated generally greater brain atrophy and disrupted connectivity. Males with Parkinson's disease had significantly greater tissue loss than females in 11 cortical regions including bilateral frontal and left insular lobe, right postcentral gyrus, left inferior temporal and cingulate gyrus and left thalamus, while females had greater atrophy in six cortical regions, including regions in the left frontal lobe, right parietal lobe, left insular gyrus and right occipital cortex. Local efficiency of white matter connectivity showed greater disruption in males in multiple regions such as basal ganglia, hippocampus, amygdala and thalamus. These findings support the idea that development of Parkinson's disease may involve different pathological mechanisms and yield distinct prognosis in males and females, which may have implications for research into neuroprotection, and stratification for clinical trials.

Whole Brain and Cranial Size Adjustments in Volumetric Brain Analyses of Sex- and Age-Related Trends

Our goal was to determine the influence of sex, age and the head/brain size on the compartmental brain volumes in the radiologically verified healthy population (96 subjects; 54 women and 42 men) from the Upper Silesia region in Poland. The MRI examinations were done using 3T Philips Achieva with the same T1-weighted and T2-weighted protocols. The image segmentation procedures were performed with SPM (Statistical Parameter Mapping) and FSL-FIRST software. The volumes of 14 subcortical structures for the left and right hemispheres and 4 overall volumes were calculated. The General Linear Models (GLM) analysis was used with and without the Total Brain Volume (TBV) and Intracranial Volume (ICV) parameters as the covariates to study the regional vs. global brain atrophy. After the ICV/TBV adjustments, the majority of sex differences in the specific volumes of interest (VOIs) revealed to be linked to the difference in the head/brain size parameters. The analysis also confirmed the significant effect of the aging process on the brain loss. After the TBV adjustment, the age- and sex-related volumetric trends for the gray and white matter volumes were observed: the negative age dependence of the gray matter volume is more pronounced in the males, while in case of the white matter the positive age-related trend in the female group is weaker. The local losses of the left caudate nucleus and the right thalamus are more advanced than the global brain atrophy. Different head-size correction strategies are not interchangeable and may yield various volumetric results, but when used together, facilitate studies on the regional dependencies inherent to a healthy, but aging, brain.

MAGNIMS consensus recommendations on the use of brain and spinal cord atrophy measures in clinical practice

Early evaluation of treatment response and prediction of disease evolution are key issues in the management of people with multiple sclerosis (MS). In the past 20 years, MRI has become the most useful paraclinical tool in both situations and is used clinically to assess the inflammatory component of the disease, particularly the presence and evolution of focal lesions - the pathological hallmark of MS. However, diffuse neurodegenerative processes that are at least partly independent of inflammatory mechanisms can develop early in people with MS and are closely related to disability. The effects of these neurodegenerative processes at a macroscopic level can be quantified by estimation of brain and spinal cord atrophy with MRI. MRI measurements of atrophy in MS have also been proposed as a complementary approach to lesion assessment to facilitate the prediction of clinical outcomes and to assess treatment responses. In this Consensus statement, the Magnetic Resonance Imaging in MS (MAGNIMS) study group critically review the application of brain and spinal cord atrophy in clinical practice in the management of MS, considering the role of atrophy measures in prognosis and treatment monitoring and the barriers to clinical use of these measures. On the basis of this review, the group makes consensus statements and recommendations for future research.

Differences in Total Brain Volume between Sexes in a Cognitively Unimpaired Elderly Population

OBJECTIVES

Although a large number of studies have shown brain volumetric differences between men and women, only a few investigations have analyzed brain tissue volumes in representative samples of the general elderly population. We investigated differences in gray matter (GM) volumes, white matter (WM) volumes, and intracranial volumes (ICVs) between the sexes in individuals older than 66 years using structural magnetic resonance imaging (MRI).

METHODS

Using FreeSurfer version 5.3, we obtained the ICVs and GM and WM volumes from the MRI datasets of 84 men and 92 women. To correct for interindividual variations in ICV, GM and WM volumes were adjusted with a method using the residuals of a least-square-derived linear regression between raw volumes and ICVs. We then performed an analysis of covariance comparing men and women, including age and years of schooling as confounding factors.

RESULTS

Women had a lower socioeconomic status overall and fewer years of schooling than men. The comparison of unadjusted brain volumes showed larger GM and WM volumes in men. After the ICV correction, the adjusted volumes of GM and WM were larger in women.

CONCLUSION

After the ICV correction and taking into account differences in socioeconomic status and years of schooling, our results confirm previous findings of proportionally larger GM in women, as well as larger WM volumes. These results in an elderly population indicate that brain volumetric differences between sexes persist throughout the aging process. Additional studies combining MRI and other biomarkers to identify the hormonal and molecular bases influencing such differences are warranted.

Sex-Based Differences in Cortical and Subcortical Development in 436 Individuals Aged 4-54 Years

Sex-based differences in brain development have long been established in ex vivo studies. Recent in vivo studies using magnetic resonance imaging (MRI) have offered considerable insight into sex-based variations in brain maturation. However, reports of sex-based differences in cortical volumes and thickness are inconsistent. We examined brain maturation in a cross-sectional, single-site cohort of 436 individuals (201 [46%] males) aged 4-54 years (median = 16 years). Cortical thickness, cortical surface area, subcortical surface area, volumes of the cerebral cortex, white matter (WM), cortical and subcortical gray matter (GM), including the thalamic subnuclei, basal ganglia, and hippocampi were calculated using automatic segmentation pipelines. Subcortical structures demonstrated distinct curvilinear trajectories from the cortex, in both volumetric maturation and surface-area expansion in relation to age. Surface-area analysis indicated that dorsal regions of the thalamus, globus pallidus and striatum, regions demonstrating structural connectivity with frontoparietal cortices, exhibited extensive expansion with age, and were inversely related to changes seen in cortical maturation, which contracted with age. Furthermore, surface-area expansion was more robust in males in comparison to females. Age- and sex-related maturational changes may reflect alterations in dendritic and synaptic architecture known to occur during development from early childhood through to mid-adulthood.

Distinct Functional Connectivity Patterns Are Associated With Social and Cognitive Lifestyle Factors: Pathways to Cognitive Reserve

The importance of diverse lifestyle factors in sustaining cognition during aging and delaying the onset of decline in Alzheimer's disease and related dementias cannot be overstated. We explored the influence of cognitive, social, and physical lifestyle factors on resting-state lagged linear connectivity (LLC) in high-density electroencephalography (EEG) in adults, ages 35-75 years. Diverse lifestyle factors build cognitive reserve (CR), protecting cognition in the presence of physical brain decline. Differences in LLC were examined between high- and low-CR groups formed using cognitive, social, and exercise lifestyle factors. LLC is a measure of lagged coherence that excludes zero phase contributions and limits the effects of volume conduction on connectivity estimates. Significant differences in LLC were identified for cognitive and social factors, but not exercise. Participants high in social CR possessed greater local and long-range connectivity in theta and low alpha for eyes-open and eyes-closed recording conditions. In contrast, participants high in cognitive CR exhibited greater eyes-closed long-range connectivity between the occipital lobe and other cortical regions in low alpha. Greater eyes-closed local LLC in delta was also present in men high in cognitive CR. Cognitive factor scores correlated with sustained attention, whereas social factors scores correlated with spatial working memory. Gender was a significant covariate in our analyses, with women displaying higher local and long-range LLC in low beta. Our findings support distinct relationships between CR and LLC, as well as CR and cognitive function for cognitive and social subcomponents. These patterns reflect the importance of diverse lifestyle factors in building CR.

Glucocerebrosidase regulators SCARB2 and TFEB are up-regulated in Lewy body disease brain

Mutations in the glucocerebrosidase (GCase) gene (GBA) and GCase deficiency are major risk factors for Lewy body diseases. Decreased GCase activity enhances alpha-synuclein aggregation and disease development. Lysosomal integral membrane protein type 2, encoded by SCARB2, binds GCase targeting it to lysosomes and transcription factor EB (Tfeb) regulates lysosomal proteostasis. Our aim was to find out if GCase deficiency in Lewy body diseases is accompanied by SCARB2 and TFEB deregulation at the transcriptional level involving alternative splicing as well. Relative mRNA expression of two SCARB2 and two TFEB transcripts was studied by real-time PCR in post-mortem brain samples of cases with pure Lewy body pathology (LBP), cases with concomitant LBP and Alzheimer disease-like pathology, and controls. TFEB expression was increased in the temporal cortex and caudate nucleus of LBP cases, and SCARB2 was differentially expressed. Female-gender associated overexpression of all transcripts was found in the caudate nucleus, and disease duration associated TFEB expression changes in the temporal cortex. SCARB2 and TFEB expression correlated negatively with GBA mRNA expression in the temporal cortex. Our findings show disease-specific deregulation of TFEB and SCARB2 expression affecting alternative promoter usage and alternative splicing in Lewy body diseases.

Multi-study validation of data-driven disease progression models to characterize evolution of biomarkers in Alzheimer's disease

Understanding the sequence of biological and clinical events along the course of Alzheimer's disease provides insights into dementia pathophysiology and can help participant selection in clinical trials. Our objective is to train two data-driven computational models for sequencing these events, the Event Based Model (EBM) and discriminative-EBM (DEBM), on the basis of well-characterized research data, then validate the trained models on subjects from clinical cohorts characterized by less-structured data-acquisition protocols.

Seven independent data cohorts were considered totalling 2389 cognitively normal (CN), 1424 mild cognitive impairment (MCI) and 743 Alzheimer's disease (AD) patients. The Alzheimer's Disease Neuroimaging Initiative (ADNI) data set was used as training set for the constriction of disease models while a collection of multi-centric data cohorts was used as test set for validation. Cross-sectional information related to clinical, cognitive, imaging and cerebrospinal fluid (CSF) biomarkers was used.

Event sequences obtained with EBM and DEBM showed differences in the ordering of single biomarkers but according to both the first biomarkers to become abnormal were those related to CSF, followed by cognitive scores, while structural imaging showed significant volumetric decreases at later stages of the disease progression. Staging of test set subjects based on sequences obtained with both models showed good linear correlation with the Mini Mental State Examination score (R²_EBM = 0.866; R²_DEBM = 0.906). In discriminant analyses, significant differences (p-value ≤ 0.05) between the staging of subjects from training and test sets were observed in both models. No significant difference between the staging of subjects from the training and test was observed (p-value > 0.05) when considering a subset composed by 562 subjects for which all biomarker families (cognitive, imaging and CSF) are available.

Event sequence obtained with DEBM recapitulates the heuristic models in a data-driven fashion and is clinically plausible. We demonstrated inter-cohort transferability of two disease progression models and their robustness in detecting AD phases. This is an important step towards the adoption of data-driven statistical models into clinical domain.

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Data-driven event sequences describe evolution of relevant biomarkers in AD.

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Agreement between event sequences and heuristic AD progression models

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Accuracy in classifying subjects from clinical cohorts up to 91%

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Staging of subjects and MMSE scores of individuals show linear relation.

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Transferability of AD progression models based on research data to clinical cohorts

Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies

The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.

Brain volume is related to neurological impairment and to copper overload in Wilson's disease

Introduction

To determine whether brain volume was associated with functional and neurological impairments and with copper overload markers in patients with Wilson’s disease.

Methods

In 48 treatment-naïve patients, we assessed functional and neurological impairments with the Unified Wilson’s Disease Rating Scale, measured normalized brain volumes based on magnetic resonance images, and assessed concentration of non-ceruloplasmin-bound copper. We correlated brain volume measures with functional and neurological impairment scores and copper overload indices.

Results

Functional and neurological impairments correlated with all brain volume measures, including the total brain volume and the volumes of white matter and gray matter (both peripheral gray matter and deep brain nuclei). Higher non-ceruloplasmin-bound copper concentrations were associated with greater functional and neurological impairments and lower brain volumes.

Conclusions

Our findings provided the first in vivo evidence that the severity of brain atrophy is a correlate of functional and neurological impairments in patients with Wilson’s disease and that brain volume could serve as a marker of neurodegeneration induced by copper.

Electronic supplementary material

The online version of this article (10.1007/s10072-019-03942-z) contains supplementary material, which is available to authorized users.

Designing in vitro Blood-Brain Barrier Models Reproducing Alterations in Brain Aging

Blood-brain barrier (BBB) modeling in vitro is a huge area of research covering study of intercellular communications and development of BBB, establishment of specific properties that provide controlled permeability of the barrier. Current approaches in designing new BBB models include development of new (bio) scaffolds supporting barriergenesis/angiogenesis and BBB integrity; use of methods enabling modulation of BBB permeability; application of modern analytical techniques for screening the transfer of metabolites, bio-macromolecules, selected drug candidates and drug delivery systems; establishment of 3D models; application of microfluidic technologies; reconstruction of microphysiological systems with the barrier constituents. Acceptance of idea that BBB in vitro models should resemble real functional activity of the barrier in different periods of ontogenesis and in different (patho) physiological conditions leads to proposal that establishment of BBB in vitro model with alterations specific for aging brain is one of current challenges in neurosciences and bioengineering. Vascular dysfunction in the aging brain often associates with leaky BBB, alterations in perivascular microenvironment, neuroinflammation, perturbed neuronal and astroglial activity within the neurovascular unit, impairments in neurogenic niches where microvascular scaffold plays a key regulatory role. The review article is focused on aging-related alterations in BBB and current approaches to development of “aging” BBB models in vitro.

Age-related changes in cortical and subcortical structures of healthy adult brains: A surface-based morphometry study

BACKGROUND

Cerebral structures in both cortical and subcortical regions change with aging. More specific and comprehensive studies are needed to better elucidate these changes.

PURPOSE

To investigate the relationships between age and cerebral structures regarding cortical and subcortical changes.

STUDY TYPE

Cross-cohort research.

POPULATION

54 healthy adults (28 females) aged 21-71 years.

FIELD STRENGTH/SEQUENCE

T₁ -weighted imaging was performed at 1.5T.

ASSESSMENT

The cortical thickness, local gyrification index (LGI), and the volumes of total gray matter (GM), white matter (WM), white matter hyperintensity (WMH), deep gray matter nuclei (putamen, pallidum, thalamus, caudate, amygdala, accumbens area, and hippocampus), ventricles, and hippocampal subfields were obtained using FreeSurfer software.

STATISTICAL TESTS

Regression analysis was performed to determine the relationships between age and cortical thickness, LGI, and volumes of subcortical structures. Uncorrected P values ≤ 0.001 and R²  > 0.16 were considered significant.

RESULTS

The cortical thickness and LGI decreased with age throughout almost all brain regions (R²  > 0.16; P ≤ 0.001). Except for the volumes of the WM and 4th ventricle (R²  < 0.16; P > 0.001), the volumes of the GM, WMH, lateral ventricle, inferior lateral ventricle, and 3rd ventricle showed a nonlinear correlation with aging (R²  > 0.16; P ≤ 0.001). For deep gray matter nuclei, the thalamus volume was significantly decreased with aging (R²  = 0.256; P = 0.001). Additionally, the hippocampus volume was initially increased and then decreased at age of 50, mainly in the granule cell layer of the dentate gyrus (GC-DG), cornus ammonis 2/3 (CA2/3), CA4, and fissure (R²  > 0.16; P ≤ 0.001). The volumes of the putamen, pallidum, accumbens area, amygdala and caudate showed no significance with aging (R²  < 0.16; P > 0.001).

DATA CONCLUSION

The results comprehensively show the relationships between age and cerebral structures in multiple brain regions, and these findings may help identify normal aging and other age-related neuroradiological disorders.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:152-163.

Gender-Specific Degeneration of Dementia-Related Subcortical Structures Throughout the Lifespan

Age-related changes in brain structure are a question of interest to a broad field of research. Structural decline has been consistently, but not unambiguously, linked to functional consequences, including cognitive impairment and dementia. One of the areas considered of crucial importance throughout this process is the medial temporal lobe, and primarily the hippocampal region. Gender also has a considerable effect on volume deterioration of subcortical grey matter (GM) structures, such as the hippocampus. The influence of age×gender interaction on disproportionate GM volume changes might be mediated by hormonal effects on the brain. Hippocampal volume loss appears to become accelerated in the postmenopausal period. This decline might have significant influences on neuroplasticity in the CA1 region of the hippocampus highly vulnerable to pathological influences. Additionally, menopause has been associated with critical pathobiochemical changes involved in neurodegeneration. The micro- and macrostructural alterations and consequent functional deterioration of critical hippocampal regions might result in clinical cognitive impairment-especially if there already is a decline in the cognitive reserve capacity. Several lines of potential vulnerability factors appear to interact in the menopausal period eventually leading to cognitive decline, mild cognitive impairment, or Alzheimer's disease. This focused review aims to delineate the influence of unmodifiable risk factors of neurodegenerative processes, i.e., age and gender, on critical subcortical GM structures in the light of brain derived estrogen effects. The menopausal period appears to be of key importance for the risk of cognitive decline representing a time of special vulnerability for molecular, structural, and functional influences and offering only a narrow window for potential protective effects.

Finding of increased caudate nucleus in patients with Alzheimer's disease

OBJECTIVES

A recently published study using an automated MRI volumetry method (NeuroQuant®) unexpectedly demonstrated larger caudate nucleus volume in patients with Alzheimer's disease dementia (AD) compared to patients with subjective and mild cognitive impairment (SCI and MCI). The aim of this study was to explore this finding.

MATERIALS & METHODS

The caudate nucleus and the hippocampus volumes were measured (both expressed as ratios of intracranial volume) in a total of 257 patients with SCI and MCI according to the Winblad criteria and AD according to ICD-10 criteria. Demographic data, cognitive measures, and APOE-ɛ4 status were collected.

RESULTS

Compared with non-dementia patients (SCI and MCI), AD patients were older, more of them were female, and they had a larger caudate nucleus volume and smaller hippocampus volume (P<.001). In multiple linear regression analysis, age and female sex were associated with larger caudate nucleus volume, but neither diagnosis nor memory function was. Age, gender, and memory function were associated with hippocampus volume, and age and memory function were associated with caudate nucleus/hippocampus ratio.

CONCLUSIONS

A larger caudate nucleus volume in AD patients was partly explained by older age and being female. These results are further discussed in the context of (1) the caudate nucleus possibly serving as a mechanism for temporary compensation; (2) methodological properties of automated volumetry of this brain region; and (3) neuropathological alterations. Further studies are needed to fully understand the role of the caudate nucleus in AD.

Early Prediction of Alzheimer's Disease Using Null Longitudinal Model-Based Classifiers

Incipient Alzheimer’s Disease (AD) is characterized by a slow onset of clinical symptoms, with pathological brain changes starting several years earlier. Consequently, it is necessary to first understand and differentiate age-related changes in brain regions in the absence of disease, and then to support early and accurate AD diagnosis. However, there is poor understanding of the initial stage of AD; seemingly healthy elderly brains lose matter in regions related to AD, but similar changes can also be found in non-demented subjects having mild cognitive impairment (MCI). By using a Linear Mixed Effects approach, we modelled the change of 166 Magnetic Resonance Imaging (MRI)-based biomarkers available at a 5-year follow up on healthy elderly control (HC, n = 46) subjects. We hypothesized that, by identifying their significant variant (vr) and quasi-variant (qvr) brain regions over time, it would be possible to obtain an age-based null model, which would characterize their normal atrophy and growth patterns as well as the correlation between these two regions. By using the null model on those subjects who had been clinically diagnosed as HC (n = 161), MCI (n = 209) and AD (n = 331), normal age-related changes were estimated and deviation scores (residuals) from the observed MRI-based biomarkers were computed. Subject classification, as well as the early prediction of conversion to MCI and AD, were addressed through residual-based Support Vector Machines (SVM) modelling. We found reductions in most cortical volumes and thicknesses (with evident gender differences) as well as in sub-cortical regions, including greater atrophy in the hippocampus. The average accuracies (ACC) recorded for men and women were: AD-HC: 94.11%, MCI-HC: 83.77% and MCI converted to AD (cAD)-MCI non-converter (sMCI): 76.72%. Likewise, as compared to standard clinical diagnosis methods, SVM classifiers predicted the conversion of cAD to be 1.9 years earlier for females (ACC:72.5%) and 1.4 years earlier for males (ACC:69.0%).