Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults

Utility of multimodal longitudinal imaging data for dynamic prediction of cardiovascular and renal disease: the CARDIA study

Background

Medical examinations contain repeatedly measured data from multiple visits, including imaging variables collected from different modalities. However, the utility of such data for the prediction of time-to-event is unknown, and only a fraction of the data is typically used for risk prediction. We hypothesized that multimodal longitudinal imaging data could improve dynamic disease prognosis of cardiovascular and renal disease (CVRD).

Methods

In a multi-centered cohort of 5,114 CARDIA participants, we included 166 longitudinal imaging variables from five imaging modalities: Echocardiography (Echo), Cardiac and Abdominal Computed Tomography (CT), Dual-Energy x-ray Absorptiometry (DEXA), Brain Magnetic Resonance Imaging (MRI) collected from young adulthood to mid-life over 30 years (1985-2016) to perform dynamic survival analysis of CVRD events using machine learning dynamic survival analysis (Dynamic-DeepHit, LTRCforest, and Extended Cox for Time-varying Covariates). Risk probabilities were continuously updated as new data were collected. Model performance was assessed using integrated AUC and C-index and compared to traditional risk factors.

Results

Longitudinal imaging data, even when being irregularly collected with high missing rates, improved CVRD dynamic prediction (0.03 in integrated AUC, up to 0.05 in C-index compared to traditional risk factors; best model's C-index = 0.80-0.83 up to 20 years from baseline) from young adulthood followed up to midlife. Among imaging variables, Echo and CT variables contributed significantly to improved risk estimation. Echo measured in early adulthood predicted midlife CVRD risks almost as well as Echo measured 10-15 years later (0.01 C-index difference). The most recent CT exam provided the most accurate prediction for short-term risk estimation. Brain MRI markers provided additional information from cardiac Echo and CT variables that led to a slightly improved prediction.

Conclusions

Longitudinal multimodal imaging data readily collected from follow-up exams can improve CVRD dynamic prediction. Echocardiography measured early can provide a good long-term risk estimation, while CT/calcium scoring variables carry atherosclerotic signatures that benefit more immediate risk assessment starting in middle-age.

Exploring sex differences: insights into gene expression, neuroanatomy, neurochemistry, cognition, and pathology

Increased knowledge about sex differences is important for development of individualized treatments against many diseases as well as understanding behavioral and pathological differences. This review summarizes sex chromosome effects on gene expression, epigenetics, and hormones in relation to the brain. We explore neuroanatomy, neurochemistry, cognition, and brain pathology aiming to explain the current state of the art. While some domains exhibit strong differences, others reveal subtle differences whose overall significance warrants clarification. We hope that the current review increases awareness and serves as a basis for the planning of future studies that consider both sexes equally regarding similarities and differences.

Differential alterations in brain structural network organization during addiction between adolescents and adults

BACKGROUND

The adolescent brain may be susceptible to the influences of illicit drug use. While compensatory network reorganization is a unique developmental characteristic that may restore several brain disorders, its association with methamphetamine (MA) use-induced damage during adolescence is unclear.

METHODS

Using independent component (IC) analysis on structural magnetic resonance imaging data, spatially ICs described as morphometric networks were extracted to examine the effects of MA use on gray matter (GM) volumes and network module connectivity in adolescents (51 MA users v. 60 controls) and adults (54 MA users v. 60 controls).

RESULTS

MA use was related to significant GM volume reductions in the default mode, cognitive control, salience, limbic, sensory and visual network modules in adolescents. GM volumes were also reduced in the limbic and visual network modules of the adult MA group as compared to the adult control group. Differential patterns of structural connectivity between the basal ganglia (BG) and network modules were found between the adolescent and adult MA groups. Specifically, adult MA users exhibited significantly reduced connectivity of the BG with the default network modules compared to control adults, while adolescent MA users, despite the greater extent of network GM volume reductions, did not show alterations in network connectivity relative to control adolescents.

CONCLUSIONS

Our findings suggest the potential of compensatory network reorganization in adolescent brains in response to MA use. The developmental characteristic to compensate for MA-induced brain damage can be considered as an age-specific therapeutic target for adolescent MA users.

Adherence to a healthy lifestyle and brain structural imaging markers

Previous research has linked specific modifiable lifestyle factors to age-related cognitive decline in adults. Little is known about the potential role of an overall healthy lifestyle in brain structure. We examined the association of adherence to a healthy lifestyle with a panel of brain structural markers among 2,413 participants in PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study in China and 19,822 participants in UK Biobank (UKB). A healthy lifestyle score (0-5) was constructed based on five modifiable lifestyle factors: diet, physical activity, smoking, alcohol consumption, and body mass index. Validated multimodal neuroimaging markers were derived from brain magnetic resonance imaging. In the cross-sectional analysis of PRECISE, participants who adopted four or five low-risk lifestyle factors had larger total brain volume (TBV; β = 0.12, 95% CI: - 0.02, 0.26; p-trend = 0.05) and gray matter volume (GMV; β = 0.16, 95% CI: 0.01, 0.30; p-trend = 0.05), smaller white matter hyperintensity volume (WMHV; β = - 0.35, 95% CI: - 0.50, - 0.20; p-trend < 0.001) and lower odds of lacune (Odds Ratio [OR] = 0.48, 95% CI: 0.22, 1.08; p-trend = 0.03), compared to those with zero or one low-risk factors. Meanwhile, in the prospective analysis in UKB (with a median of 7.7 years' follow-up), similar associations were observed between the number of low-risk lifestyle factors (4-5 vs. 0-1) and TBV (β = 0.22, 95% CI: 0.16, 0.28; p-trend < 0.001), GMV (β = 0.26, 95% CI: 0.21, 0.32; p-trend < 0.001), white matter volume (WMV; β = 0.08, 95% CI: 0.01, 0.15; p-trend = 0.001), hippocampus volume (β = 0.15, 95% CI: 0.08, 0.22; p-trend < 0.001), and WMHV burden (β = - 0.23, 95% CI: - 0.29, - 0.17; p-trend < 0.001). Those with four or five low-risk lifestyle factors showed approximately 2.0-5.8 years of delay in aging of brain structure. Adherence to a healthier lifestyle was associated with a lower degree of neurodegeneration-related brain structural markers in middle-aged and older adults.

Topography of associations between cardiovascular risk factors and myelin loss in the ageing human brain

Our knowledge of the mechanisms underlying the vulnerability of the brain's white matter microstructure to cardiovascular risk factors (CVRFs) is still limited. We used a quantitative magnetic resonance imaging (MRI) protocol in a single centre setting to investigate the cross-sectional association between CVRFs and brain tissue properties of white matter tracts in a large community-dwelling cohort (n = 1104, age range 46-87 years). Arterial hypertension was associated with lower myelin and axonal density MRI indices, paralleled by higher extracellular water content. Obesity showed similar associations, though with myelin difference only in male participants. Associations between CVRFs and white matter microstructure were observed predominantly in limbic and prefrontal tracts. Additional genetic, lifestyle and psychiatric factors did not modulate these results, but moderate-to-vigorous physical activity was linked to higher myelin content independently of CVRFs. Our findings complement previously described CVRF-related changes in brain water diffusion properties pointing towards myelin loss and neuroinflammation rather than neurodegeneration.

Age and Sex-Related Effects on Single-Subject Gray Matter Networks in Healthy Participants

Recent developments in image analysis have enabled an individual’s brain network to be evaluated and brain age to be predicted from gray matter images. Our study aimed to investigate the effects of age and sex on single-subject gray matter networks using a large sample of healthy participants. We recruited 812 healthy individuals (59.3 ± 14.0 years, 407 females, and 405 males) who underwent three-dimensional T1-weighted magnetic resonance imaging. Similarity-based gray matter networks were constructed, and the following network properties were calculated: normalized clustering, normalized path length, and small-world coefficients. The predicted brain age was computed using a support-vector regression model. We evaluated the network alterations related to age and sex. Additionally, we examined the correlations between the network properties and predicted brain age and compared them with the correlations between the network properties and chronological age. The brain network retained efficient small-world properties regardless of age; however, reduced small-world properties were observed with advancing age. Although women exhibited higher network properties than men and similar age-related network declines as men in the subjects aged < 70 years, faster age-related network declines were observed in women, leading to no differences in sex among the participants aged ≥ 70 years. Brain age correlated well with network properties compared to chronological age in participants aged ≥ 70 years. Although the brain network retained small-world properties, it moved towards randomized networks with aging. Faster age-related network disruptions in women were observed than in men among the elderly. Our findings provide new insights into network alterations underlying aging.

Amplitudes of resting-state functional networks - investigation into their correlates and biophysical properties

Resting-state fMRI studies have shown that multiple functional networks, which consist of distributed brain regions that share synchronised spontaneous activity, co-exist in the brain. As these resting-state networks (RSNs) have been thought to reflect the brain's intrinsic functional organization, intersubject variability in the networks' spontaneous fluctuations may be associated with individuals' clinical, physiological, cognitive, and genetic traits. Here, we investigated resting-state fMRI data along with extensive clinical, lifestyle, and genetic data collected from 37,842 UK Biobank participants, with the object of elucidating intersubject variability in the fluctuation amplitudes of RSNs. Functional properties of the RSN amplitudes were first examined by analyzing correlations with the well-established between-network functional connectivity. It was found that a network amplitude is highly correlated with the mean strength of the functional connectivity that the network has with the other networks. Intersubject clustering analysis showed the amplitudes are most strongly correlated with age, cardiovascular factors, body composition, blood cell counts, lung function, and sex, with some differences in the correlation strengths between sensory and cognitive RSNs. Genome-wide association studies (GWASs) of RSN amplitudes identified several significant genetic variants reported in previous GWASs for their implications in sleep duration. We provide insight into key factors determining RSN amplitudes and demonstrate that intersubject variability of the amplitudes primarily originates from differences in temporal synchrony between functionally linked brain regions, rather than differences in the magnitude of raw voxelwise BOLD signal changes. This finding additionally revealed intriguing differences between sensory and cognitive RSNs with respect to sex effects on temporal synchrony and provided evidence suggesting that synchronous coactivations of functionally linked brain regions, and magnitudes of BOLD signal changes, may be related to different genetic mechanisms. These results underscore that intersubject variability of the amplitudes in health and disease need to be interpreted largely as a measure of the sum of within-network temporal synchrony and amplitudes of BOLD signals, with a dominant contribution from the former.

Overnutrition Induced Cognitive Impairment: Insulin Resistance, Gut-Brain Axis, and Neuroinflammation

Overnutrition-related obesity has become a worldwide epidemic, and its prevalence is expected to steadily rise in the future. It is widely recognized that obesity exerts negative impacts on metabolic disorders such as type 2 diabetes mellitus (T2DM) and cardiovascular diseases. However, relatively fewer reports exist on the impairment of brain structure and function, in the form of memory and executive dysfunction, as well as neurogenerative diseases. Emerging evidence indicates that besides obesity, overnutrition diets independently induce cognitive impairments via multiple mechanisms. In this study, we reviewed the clinical and preclinical literature about the detrimental effects of obesity or high-nutrition diets on cognitive performance and cerebral structure. We mainly focused on the role of brain insulin resistance (IR), microbiota-gut-brain axis, and neuroinflammation. We concluded that before the onset of obesity, short-term exposure to high-nutrition diets already blunted central responses to insulin, altered gut microbiome composition, and activated inflammatory mediators. Overnutrition is linked with the changes in protein expression in brain insulin signaling, leading to pathological features in the brain. Microbiome alteration, bacterial endotoxin release, and gut barrier hyperpermeability also occur to trigger mental and neuronal diseases. In addition, obesity or high-nutrition diets cause chronic and low-grade systematic inflammation, which eventually spreads from the peripheral tissue to the central nervous system (CNS). Altogether, a large number of unknown but potential routes interact and contribute to obesity or diet-induced cognitive impairment. The challenge for future research is to identify effective interventions involving dietary shifts and personalized therapy targeting the underlying mechanisms to prevent and improve cognition deficits.

Association of blood pressure with brain structure in youth with and without bipolar disorder

BACKGROUND

We previously found that blood pressure (BP) is elevated, and associated with poorer neurocognition, in youth with bipolar disorder (BD). While higher BP is associated with smaller brain structure in adults, studies have not examined this topic in BD or youth.

METHODS

Participants were 154 youth, ages 13-20 (n = 81 BD, n = 73 HC). Structural magnetic resonance imaging and diastolic (DBP), and systolic (SBP) pressure were obtained. Region of interest (ROI; anterior cingulate cortex [ACC], insular cortex, hippocampus) and vertex-wise analyses controlling for age, sex, body-mass-index, and intracranial volume investigated BP-neurostructural associations; a group-by-BP interaction was also assessed.

RESULTS

In ROI analyses, higher DBP in the overall sample was associated with smaller insular cortex area (β=-0.18 p = 0.007) and was associated with smaller ACC area to a significantly greater extent in HC vs. BD (β=-0.14 p = 0.015). In vertex-wise analyses, higher DBP and SBP were associated with smaller area and volume in the insular cortex, frontal, parietal, and temporal regions in the overall sample. Additionally, higher SBP was associated with greater thickness in temporal and parietal regions. Finally, higher SBP was associated with smaller area and volume in frontal, parietal, and temporal regions to a significantly greater extent in BD vs. HC.

LIMITATIONS

Cross-sectional design, single assessment of BP.

CONCLUSION

BP is associated with brain structure in youth, with variability related to structural phenotype (volume vs. thickness) and psychiatric diagnosis (BD vs. HC). Future studies evaluating temporality of these findings, and the association of BP changes on brain structure in youth, are warranted.

Associations of dietary markers with brain volume and connectivity: A systematic review of MRI studies

The high prevalence of unhealthy dietary patterns and related brain disorders, such as dementia, emphasizes the importance of research that examines the effect of dietary factors on brain health. Identifying markers of brain health, such as volume and connectivity, that relate to diet is an important first step towards understanding the lifestyle determinants of healthy brain ageing. We conducted a systematic review of 52 studies (total n = 21,221 healthy participants aged 26-80 years, 55 % female) that assessed with a range of MRI measurements, which brain areas, connections, and cerebrovascular factors were associated with dietary markers. We report associations between regional brain measures and dietary health. Collectively, lower diet quality was related to reduced brain volume and connectivity, especially in white and grey matter of the frontal, temporal and parietal lobe, cingulate, entorhinal cortex and the hippocampus. Associations were also observed in connecting fibre pathways and in particular the default-mode, sensorimotor and attention networks. However, there were also some inconsistencies in research methods and findings. We recommend that future research use more comprehensive and consistent dietary measures, more representative samples, and examine the role of key subcortical regions previously highlighted in relevant animal work.

Effects of physical activity on brain function and structure in older adults: A systematic review

Despite increasing evidence that physical activity (PA) contributes to brain health in older individuals, both at the level of brain structure and function, this relationship is not yet well established. To explore this potential association, a systematic literature search was performed using PubMed, Scopus, and Web of Science, adhering to PRISMA guidelines. A total of 32 studies met the eligibility criteria: 24 cross-sectional and 8 longitudinal. Results from structural Magnetic Resonance Imaging (MRI) showed that PA associated with larger brain volumes (less brain atrophy) specifically in brain regions vulnerable to dementia, comprising the hippocampus, temporal, and frontal regions. Furthermore, functional MRI (fMRI) showed greater task-relevant activity in brain areas recruited in executive function and memory tasks. However, the dose-response relationship is unclear due to the high variability in PA measures. Further research using objective measures is needed to better understand which PA type, intensity, frequency, and duration, has the greatest protective effect on brain health. Findings highlight the importance of PA in both cognitive decline and dementia prevention.

Associations Between Cardiovascular Risk, Structural Brain Changes, and Cognitive Decline

BACKGROUND

The impact of cardiovascular risk burden on cognitive trajectories and brain structure changes remains unclear.

OBJECTIVES

This study aimed to examine whether cardiovascular risk burden assessed by the Framingham General Cardiovascular Risk Score (FGCRS) is associated with cognitive decline and structural brain differences.

METHODS

Within the Rush Memory and Aging Project, 1,588 dementia-free participants (mean age: 79.5 years) were followed for up to 21 years. FGCRS was assessed at baseline and categorized into tertiles (lowest, middle, and highest). Episodic memory, semantic memory, working memory, visuospatial ability, and perceptual speed were assessed annually with a battery of 19 tests, from which composite scores were derived. A subsample (n = 378) of participants underwent magnetic resonance imaging. Structural total and regional brain volumes were estimated. Data were analyzed using linear mixed-effects models and linear regression models.

RESULTS

In all participants, FGCRS ranged from 4 to 28 (mean score: 15.6 ± 3.7). Compared with the lowest tertile of FGCRS, the highest tertile was associated with faster decline in global cognition (β = -0.019; 95% confidence interval [CI]: -0.035 to -0.003), episodic memory (β = -0.023; 95% CI: -0.041 to -0.004), working memory (β = -0.021; 95% CI: -0.035 to -0.007), and perceptual speed (β = -0.027; 95% CI: -0.042 to -0.011) over the follow-up. In magnetic resonance imaging data analyses, higher FGCRS was related to smaller volumes of the hippocampus (β = -0.021; 95% CI: -0.042 to -0.000), gray matter (β = -1.569; 95% CI: -2.757 to -0.382), and total brain (β = -1.588; 95% CI: -2.832 to -0.344), and greater volume of white matter hyperintensities (β = 0.035; 95% CI: 0.001 to 0.069).

CONCLUSIONS

Higher cardiovascular risk burden may predict decline in episodic memory, working memory, and perceptual speed and is associated with neurodegeneration and vascular lesions in the brain.

Machine-learning based exploration of determinants of gray matter volume in the KORA-MRI study

To identify the most important factors that impact brain volume, while accounting for potential collinearity, we used a data-driven machine-learning approach. Gray Matter Volume (GMV) was derived from magnetic resonance imaging (3T, FLAIR) and adjusted for intracranial volume (ICV). 93 potential determinants of GMV from the categories sociodemographics, anthropometric measurements, cardio-metabolic variables, lifestyle factors, medication, sleep, and nutrition were obtained from 293 participants from a population-based cohort from Southern Germany. Elastic net regression was used to identify the most important determinants of ICV-adjusted GMV. The four variables age (selected in each of the 1000 splits), glomerular filtration rate (794 splits), diabetes (323 splits) and diabetes duration (122 splits) were identified to be most relevant predictors of GMV adjusted for intracranial volume. The elastic net model showed better performance compared to a constant linear regression (mean squared error = 1.10 vs. 1.59, p < 0.001). These findings are relevant for preventive and therapeutic considerations and for neuroimaging studies, as they suggest to take information on metabolic status and renal function into account as potential confounders.

Aberrant patterns of default-mode network functional connectivity associated with metabolic syndrome: A resting-state study

INTRODUCTION

Metabolic syndrome (MetS) is a clustering of three or more cardiovascular risk factors (RF), including hypertension, obesity, high cholesterol, or hyperglycemia. MetS and its component RFs are more prevalent in older age, and can be accompanied by alterations in brain structure. Studies have shown altered functional connectivity (FC) in samples with individual RFs as well as in clinical populations that are at higher risk to develop MetS. These studies have indicated that the default mode network (DMN) may be particularly vulnerable, yet little is known about the overall impact of MetS on FC in this network.

METHODS

In this study, we evaluated the integrity of FC to the DMN in participants with MetS relative to non-MetS individuals. Using a seed-based connectivity analysis approach, resting-state functional MRI (fMRI) data were analyzed, and the FC measures among the DMN seed (isthmus of the cingulate) and rest of the brain voxels were estimated.

RESULTS

Participants with MetS demonstrated reduced positive connectivity between the DMN seed and left superior frontal regions, and reduced negative connectivity between the DMN seed and left superior parietal, left postcentral, right precentral, right superior temporal and right superior parietal regions, after accounting for age- and sex-effects.

CONCLUSIONS

Our results suggest that MetS is associated with alterations in FC between the DMN and other regions of the brain. Furthermore, these results indicate that the overall burden of vascular RFs associated with MetS may, in part, contribute to the pathophysiology underlying aberrant FC in the DMN.

A Metabolic Obesity Profile Is Associated With Decreased Gray Matter Volume in Cognitively Healthy Older Adults

Obesity is a risk factor for cognitive decline and gray matter volume loss in aging. Studies have shown that different metabolic factors, e.g., dysregulated glucose metabolism and systemic inflammation, might mediate this association. Yet, even though these risk factors tend to co-occur, they have mostly been investigated separately, making it difficult to establish their joint contribution to gray matter volume structure in aging. Here, we therefore aimed to determine a metabolic profile of obesity that takes into account different anthropometric and metabolic measures to explain differences in gray matter volume in aging. We included 748 elderly, cognitively healthy participants (age range: 60 - 79 years, BMI range: 17 - 42 kg/m2) of the LIFE-Adult Study. All participants had complete information on body mass index, waist-to-hip ratio, glycated hemoglobin, total blood cholesterol, high-density lipoprotein, interleukin-6, C-reactive protein, adiponectin and leptin. Voxelwise gray matter volume was extracted from T1-weighted images acquired on a 3T Siemens MRI scanner. We used partial least squares correlation to extract latent variables with maximal covariance between anthropometric, metabolic and gray matter volume and applied permutation/bootstrapping and cross-validation to test significance and reliability of the result. We further explored the association of the latent variables with cognitive performance. Permutation tests and cross-validation indicated that the first pair of latent variables was significant and reliable. The metabolic profile was driven by negative contributions from body mass index, waist-to-hip ratio, glycated hemoglobin, C-reactive protein and leptin and a positive contribution from adiponectin. It positively covaried with gray matter volume in temporal, frontal and occipital lobe as well as subcortical regions and cerebellum. This result shows that a metabolic profile characterized by high body fat, visceral adiposity and systemic inflammation is associated with reduced gray matter volume and potentially reduced executive function in older adults. We observed the highest contributions for body weight and fat mass, which indicates that factors underlying sustained energy imbalance, like sedentary lifestyle or intake of energy-dense food, might be important determinants of gray matter structure in aging.

Inflammatory DEpression Advances in Schizophrenia (IDEAS): A precision medicine approach of the national FACE-SZ cohort

BACKGROUND

Major Depressive Disorder (MDD) is a therapeutic challenge in schizophrenia (SZ). Untangling different forms of MDD appears as the best current strategy to improve remission to treatment in the so-called precision medicine approach.

AIMS

The objectives of the present study were to determine (i) the prevalence of Inflammatory Depression (ID) in stabilized SZ outpatients (ii) if ID was associated with clinical or cognitive profiles that may help clinicians detecting ID (iii) if antidepressants were effective in ID and (iv) the biological correlates of ID that may orientate personalized treatments.

METHOD

Participants were consecutively included and received a thorough 2 days- clinical assessment.

RESULTS

785 subjects were recruited in the FACE-SZ cohort. 289 (36.8%) were diagnosed with MDD (remitted or unremitted), of them 57 with ID (19.7%). No clinical or cognitive features were associated with ID (all p > 0.05). ID has been associated with increased abdominal perimeter (aOR = 4.48, p = 0.002) and latent Toxoplasma infection (aOR = 2.19, p = 0.04). While antidepressants were associated with decreased depressive symptoms level in ID, 44% of the subjects remained unremitted under antidepressant, with no association with CRP blood levels.

CONCLUSIONS

ID may not differ from other forms of depression by its clinical symptoms but by its aetiologies. ID is associated with increased perivisceral fat and latent Toxoplasma infection that are both potentially related to gut/microbiota disturbances. Specific anti-inflammatory drugs and microbiota-targeted therapeutics appear as promising strategies in the treatment of inflammatory depression in schizophrenia.

BrainMap VBM: An environment for structural meta-analysis

The BrainMap database is a community resource that curates peer-reviewed, coordinate-based human neuroimaging literature. By pairing the results of neuroimaging studies with their relevant meta-data, BrainMap facilitates coordinate-based meta-analysis (CBMA) of the neuroimaging literature en masse or at the level of experimental paradigm, clinical disease, or anatomic location. Initially dedicated to the functional, task-activation literature, BrainMap is now expanding to include voxel-based morphometry (VBM) studies in a separate sector, titled: BrainMap VBM. VBM is a whole-brain, voxel-wise method that measures significant structural differences between or within groups which are reported as standardized, peak x-y-z coordinates. Here we describe BrainMap VBM, including the meta-data structure, current data volume, and automated reverse inference functions (region-to-disease profile) of this new community resource. CBMA offers a robust methodology for retaining true-positive and excluding false-positive findings across studies in the VBM literature. As with BrainMap's functional database, BrainMap VBM may be synthesized en masse or at the level of clinical disease or anatomic location. As a use-case scenario for BrainMap VBM, we illustrate a trans-diagnostic data-mining procedure wherein we explore the underlying network structure of 2,002 experiments representing over 53,000 subjects through independent components analysis (ICA). To reduce data-redundancy effects inherent to any database, we demonstrate two data-filtering approaches that proved helpful to ICA. Finally, we apply hierarchical clustering analysis (HCA) to measure network- and disease-specificity. This procedure distinguished psychiatric from neurological diseases. We invite the neuroscientific community to further exploit BrainMap VBM with other modeling approaches.

Sex/gender differences in cognition, neurophysiology, and neuroanatomy

In this mini-review, I summarize and interpret the current status of sex/gender differences in terms of brain anatomy, brain function, behavior, and cognition. Based on this review and the reported findings, I conclude that most of these sex/gender differences are not large enough to support the assumption of sexual dimorphism in terms of brain anatomy, brain function, cognition, and behavior. Instead, I suggest that many brain and cognitive features are modulated by environment, culture, and practice (and several other influences). These influences interact with the menstrual cycle, the general hormone level, and current gender stereotypes in a way that has not yet been fully understood.

Metabolic syndrome and its components with neuron-specific enolase: a cross-sectional study in large health check-up population in China

OBJECTIVE

This study was aimed at investigating the relationship between neuron-specific enolase (NSE) and components of metabolic syndrome (MS).

DESIGN

Cross-sectional study.

SETTING

Chinese health check-up population.

PARTICIPANTS

40 684 health check-up people were enrolled in this study from year 2014 to 2016.

MAIN OUTCOME MEASURES

OR and coefficient for MS.

RESULTS

The percentage of abnormal NSE and MS was 26.85% and 8.85%, respectively. There were significant differences in sex, body mass index, drinking habit, triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), blood pressure and MS between low-NSE and high-NSE groups. In logistic regression analysis, elevated NSE was present in MS, higher body mass index, hypertriglyceridaemia, hypertension and low-HDL groups. Stepwise linear analysis showed a negative correlation between NSE and fasting blood glucose (FBG) (<6.0 mmol/L), and a positive correlation between NSE and TGs (<20 mmol/L), systolic blood pressure (75-200 mm Hg), HDL-C (0.75-2.50 mmol/L), diastolic blood pressure (<70 mm Hg) and FBG (6.00-20.00 mmol/L). Furthermore, MS was positively correlated with NSE within the range of 2.00-7.50 ng/mL, but had a negative correlation with NSE within the range of 7.50-23.00 ng/mL.

CONCLUSION

There are associations between NSE with MS and its components. The result suggests that NSE may be a potential predictor of MS. Further research could be conducted in discussing the potential mechanism involved.