Gray matter reduction related to decreased serum creatinine and increased triglyceride, Hemoglobin A1C, and low-density lipoprotein in subjects with obesity

Association of glycosylated hemoglobin concentrations with structural and functional brain changes in the normoglycemic population: A systematic review

Optimal glucose control is crucial for maintaining brain health and preventing metabolic and cognitive disorders in the general population. Glycosylated hemoglobin (HbA1c) serves as a key marker for assessing glucose intolerance and its impact on brain structure and function in healthy individuals. However, existing literature presents conflicting findings, necessitating a systematic review to consolidate current knowledge in this domain. This systematic review examines 26 English-language studies involving participants aged 15 years and above, investigating the relationship between HbA1c levels and brain health. Studies focusing on normal/general populations and utilizing magnetic resonance imaging (MRI) as the imaging modality were included. Exclusion criteria encompassed review articles, abstracts, letters, animal studies, and research involving neuropsychiatric or metabolic diseases. Data were gathered from PubMed, Scopus, and Web of Science databases up to November 2023. Analysis reveals significant associations between HbA1c levels and various brain metrics, including volume, cortical thickness, fractional anisotropy, mean diffusivity, activity, and connectivity. However, findings exhibit inconsistency, likely attributed to disparities in sample characteristics and study sizes. Notably, hippocampal volume, white matter hyperintensity, and ventral attention network connectivity emerge as frequently affected structures and functions, mirroring trends observed in diabetic populations. Despite inconclusive evidence, glucose intolerance appears to exert considerable influence on select brain structures and functions in individuals without diagnosed metabolic disorders. Understanding these associations is critical for mitigating the risk of cognitive decline and dementia in healthy populations. Future investigations should aim to elucidate the intricate relationship between HbA1c concentrations and brain health parameters in normoglycemic individuals.

Large-scale functional network connectivity mediates the associations between lipids metabolism and cognition in type 2 diabetes

Type 2 diabetes (T2D) is associated with dyslipidemia and mild cognitive impairment. This study investigated the relationships between serum lipids metabolism, cognition, and functional connectivity (FC) within and between brain networks in T2D patients. The study included 102 T2D patients and 45 healthy controls who underwent functional magnetic resonance imaging, lipid profile tests, and cognitive assessments. Thirteen functional networks were identified using independent component analysis. The statistical analyses included multivariate analysis of covariance, partial correlation, canonical correlation, and mediation analyses. We found widely reduced between-network FCs in T2D, especially between the ventral sensorimotor network (SMN) and dorsal attention network (DAN) (p = 0.001) and between the ventral SMN and lateral visual network (VN) (p < 0.001). Moreover, lower between-network FCs were correlated with worse serum lipids metabolism and poorer cognitive performance (all p < 0.05). Importantly, between-network FCs mediated the relationship between lipid metabolism and cognition (β = -0.3136, 95% CI: -0.7660, -0.0186). Within-network analyses revealed altered FCs within the anterior default mode network, DAN, and lateral VN, each positively correlated with global cognition (all p < 0.01). Our results suggest the potential of improving cognitive function by regulating serum lipids in individuals with T2D.

Machine-learning-based analysis of the sensitivity and specificity on lipid-lowering effect of one-month-administered statins

Few predictive studies have been reported on the efficacy of atorvastatin in reducing lipoprotein cholesterol to be qualified after 1-month course of treatment in different individuals. A total of 14,180 community-based residents aged ≥ 65 received health checkup, 1013 of whom had low-density lipoprotein (LDL) higher than 2.6mmol/L so that they were put on 1-month course of treatment with atorvastatin. At its completion, lipoprotein cholesterol was measured again. With < 2.6 mmol/L considered as the treatment standard, 411 individuals were judged as the qualified group, and 602, and as the unqualified group. The basic sociodemographic features covered 57 items. The data were randomly divided into train sets and test ones. The recursive random-forest algorithm was applied to predicting the patients response to atorvastatin, the recursive feature elimination method, to screening all the physical indicators. The overall accuracy, sensitivity and specificity were calculated, respectively, and so were the receiver operator characteristic curve and the area under the curve of the test set. In the prediction model on the efficacy of 1-month treatment of statins for LDL, the sensitivity, 86.86%; and the specificity, 94.83%. In the prediction model on the efficacy of the same treatment for triglyceride, the sensitivity, 71.21%; and the specificity, 73.46%. As to the prediction of total cholesterol, the sensitivity, 94.38%; and the specificity, 96.55%. And in the case of high-density lipoprotein (HDL), the sensitivity, 84.86%; and the specificity, 100%. recursive feature elimination analysis showed that total cholesterol was the most important feature of atorvastatin efficacy of reducing LDL; that HDL was the most important one of its efficacies of reducing triglycerides; that LDL was the most important one of its efficacies of reducing total cholesterol; and that triglyceride was the most important one of its efficacies of reducing HDL. Random-forest can help predict whether atorvastatin efficacy of reducing lipoprotein cholesterol to be qualified after 1-month course of treatment in different individuals.

Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants

BACKGROUND

Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

METHODS

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

RESULTS

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

CONCLUSIONS

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Mechanisms linking obesity and its metabolic comorbidities with cerebral grey and white matter changes

Obesity is a preventable risk factor for cerebrovascular disorders and it is associated with cerebral grey and white matter changes. Specifically, individuals with obesity show diminished grey matter volume and thickness, which seems to be more prominent among fronto-temporal regions in the brain. At the same time, obesity is associated with lower microstructural white matter integrity, and it has been found to precede increases in white matter hyperintensity load. To date, however, it is unclear whether these findings can be attributed solely to obesity or whether they are a consequence of cardiometabolic complications that often co-exist with obesity, such as low-grade systemic inflammation, hypertension, insulin resistance, or dyslipidemia. In this narrative review we aim to provide a comprehensive overview of the potential impact of obesity and a number of its cardiometabolic consequences on brain integrity, both separately and in synergy with each other. We also identify current gaps in knowledge and outline recommendations for future research.

Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals

AIMS

Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry.

METHODS

We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles.

RESULTS

We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex.

CONCLUSIONS

We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.

Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles  and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.

Association between Visceral Adiposity Index, Binge Eating Behavior, and Grey Matter Density in Caudal Anterior Cingulate Cortex in Severe Obesity

Visceral adipose tissue accumulation is an important determinant of metabolic risk and can be estimated by the visceral adiposity index (VAI). Visceral adiposity may impact brain regions involved in eating behavior. We aimed to examine the association between adiposity measurements, binge eating behavior, and grey matter density. In 20 men and 59 women with severe obesity, Grey matter density was measured by voxel-based morphometry for six regions of interest associated with reward, emotion, or self-regulation: insula, orbitofrontal cortex, caudal and rostral anterior cingulate cortex (ACC), ventromedial prefrontal cortex (vmPFC), and dorsolateral prefrontal cortex (DLPFC). Binge eating behavior, depression and impulsivity was assessed by the Binge Eating Scale, Beck Depression Inventory and UPPS Impulsive Behavior Scale, respectively. Men and women were distinctively divided into two subgroups (low-VAI and high-VAI) based on the mean VAI score. Women with high-VAI were characterized by metabolic alterations, higher binge eating score and lower grey matter density in the caudal ACC compared to women with low-VAI. Men with high-VAI were characterized by a higher score for the sensation-seeking subscale of the UPPS–Impulsive Behavior Scale compared to men with low-VAI. Using a moderation–mediation analysis, we found that grey matter density in the caudal ACC mediates the association between VAI and binge eating score. In conclusion, visceral adiposity is associated with higher binge eating severity in women. Decreased grey matter density in the caudal ACC, a region involved in cognition and emotion regulation, may influence this relationship.

Obesity as a Risk Factor for Accelerated Brain Ageing in First-Episode Psychosis-A Longitudinal Study

BACKGROUND

Obesity is highly prevalent in schizophrenia, with implications for psychiatric prognosis, possibly through links between obesity and brain structure. In this longitudinal study in first episode of psychosis (FEP), we used machine learning and structural magnetic resonance imaging (MRI) to study the impact of psychotic illness and obesity on brain ageing/neuroprogression shortly after illness onset.

METHODS

We acquired 2 prospective MRI scans on average 1.61 years apart in 183 FEP and 155 control individuals. We used a machine learning model trained on an independent sample of 504 controls to estimate the individual brain ages of study participants and calculated BrainAGE by subtracting chronological from the estimated brain age.

RESULTS

Individuals with FEP had a higher initial BrainAGE than controls (3.39 ± 6.36 vs 1.72 ± 5.56 years; β = 1.68, t(336) = 2.59, P = .01), but similar annual rates of brain ageing over time (1.28 ± 2.40 vs 1.07±1.74 estimated years/actual year; t(333) = 0.93, P = .18). Across both cohorts, greater baseline body mass index (BMI) predicted faster brain ageing (β = 0.08, t(333) = 2.59, P = .01). For each additional BMI point, the brain aged by an additional month per year. Worsening of functioning over time (Global Assessment of Functioning; β = -0.04, t(164) = -2.48, P = .01) and increases especially in negative symptoms on the Positive and Negative Syndrome Scale (β = 0.11, t(175) = 3.11, P = .002) were associated with faster brain ageing in FEP.

CONCLUSIONS

Brain alterations in psychosis are manifest already during the first episode and over time get worse in those with worsening clinical outcomes or higher baseline BMI. As baseline BMI predicted faster brain ageing, obesity may represent a modifiable risk factor in FEP that is linked with psychiatric outcomes via effects on brain structure.

Structural Brain Changes Associated with Overweight and Obesity

Obesity is a global health problem with a broad set of comorbidities, such as malnutrition, metabolic syndrome, diabetes, systemic hypertension, heart failure, and kidney failure. This review describes recent findings of neuroimaging and two studies of cell density regarding the roles of overnutrition-induced hypothalamic inflammation in neurodegeneration. These studies provided consistent evidence of smaller cortical thickness or reduction in the gray matter volume in people with overweight and obesity; however, the investigated brain regions varied across the studies. In general, bilateral frontal and temporal areas, basal nuclei, and cerebellum are more commonly involved. Mechanisms of volume reduction are unknown, and neuroinflammation caused by obesity is likely to induce neuronal loss. Adipocytes, macrophages of the adipose tissue, and gut dysbiosis in overweight and obese individuals result in the secretion of the cytokines and chemokines that cross the blood-brain barrier and may stimulate microglia, which in turn also release proinflammatory cytokines. This leads to chronic low-grade neuroinflammation and may be an important factor for apoptotic signaling and neuronal death. Additionally, significant microangiopathy observed in rat models may be another important mechanism of induction of apoptosis. Neuroinflammation in neurodegenerative diseases (such as Alzheimer's and Parkinson's diseases) may be similar to that in metabolic diseases induced by malnutrition. Poor cognitive performance, mainly in executive functions, in individuals with obesity is also discussed. This review highlights the neuroinflammatory and neurodegenerative mechanisms linked to obesity and emphasizes the importance of developing effective prevention and treatment intervention strategies for overweight and obese individuals.

Association of mid-life serum lipid levels with late-life brain volumes: The atherosclerosis risk in communities neurocognitive study (ARICNCS)

BACKGROUND

Limited information exists regarding the association between midlife lipid levels and late-life total and regional brain volumes.

METHODS

We studied 1872 participants in the longitudinal community-based Atherosclerosis Risk in Communities Neurocognitive Study. Serum lipid levels were measured in 1987-1989 (mean age, 53 ± 5 years). Participants underwent 3T brain MRI scans in 2011-2013. Brain volumes were measured using FreeSurfer image analysis software. Linear regression models were used to assess the associations between serum lipids and brain volumes modeled in standard deviation (SD) units, adjusting for potential confounders.

RESULTS

In adjusted analyses, one SD higher low-density lipoprotein cholesterol (LDL) levels were associated with larger total brain volumes (β 0.033, 95% CI 0.006-0.060) as well as larger volumes of the temporal (β 0.038, 95% CI 0.003-0.074) and parietal lobes (β 0.044, 95% CI 0.009-0.07) and Alzheimer disease-related region (β 0.048, 95% CI 0.048-0.085). Higher triglyceride levels were associated with smaller total brain volumes (β -0.033, 95% CI -0.060, -0.007). The associations between LDL levels and brain volumes were modified by age (P for interaction <0.001), with higher LDL levels associated with larger total and regional brain volumes only among adults >53 years at baseline, and were attenuated after application of weights to account for informative attrition, although associations with the parietal and Alzheimer's disease-related region remained significant. High-density lipoprotein cholesterol was not associated with brain volumes.

CONCLUSION

Higher LDL levels in late midlife were associated with larger brain volumes later in life, while higher triglyceride levels were associated with smaller brain volumes. These associations were driven by adults >53 years at baseline.

Short-term effects of a Paleolithic lifestyle intervention in breast cancer patients undergoing radiotherapy: a pilot and feasibility study

Evolutionary principles are rarely considered in clinical oncology. We here aimed to test the feasibility and effects of a dietary and physical activity intervention based on evolutionary considerations in an oncological setting. A total of 13 breast cancer patients referred to our clinic for curative radiotherapy were recruited for this pilot study. The women were supposed to undertake a "Paleolithic lifestyle" (PL) intervention consisting of a Paleolithic diet and daily outdoor activity of at least 30 min duration while undergoing radiotherapy. Body composition was measured weekly by bioimpedance analysis. Blood parameters were assessed before, during, and at the end of radiotherapy. A control group on an unspecified standard diet (SD) was assigned by propensity score matching. A total of eleven patients completed the study. The majority of patients (64%) reported feeling good or very good during the intervention. The intervention group experienced an average decrease of 0.4 kg body weight (p < 0.001) and 0.34 kg (p < 0.001) fat mass per week, but fat-free and skeletal muscle mass were not significantly affected. Vitamin D levels increased slightly from 23.8 (11-37.3) ng/ml to 25.1 (22.6-41.6) ng/ml (p = 0.053). β-hydroxybutyrate levels were significantly increased and triglycerides and free T3 hormone levels significantly reduced by the PL intervention. This pilot study shows that adoption of a PL intervention during curative radiotherapy of breast cancer patients is feasible and able to reduce fat mass. Daily outdoor activity could eliminate vitamin D deficiency (vitamin D < 20 ng/ml). Future studies are needed to confirm these findings.

Large-Scale Internetwork Functional Connectivity Mediates the Relationship between Serum Triglyceride and Working Memory in Young Adulthood

Previous research has demonstrated that serum lipid profile is associated with cognitive function as well as brain structure and function in middle-aged, elderly, and clinical populations. However, the nature and extent of lipids-brain-cognition relationships in young adulthood are largely unknown. In this study, 157 healthy young adults underwent resting-state functional MRI scans. Functional connectivity between and within 14 functional networks were calculated using independent component analysis. Peripheral venous blood samples were collected to measure serum lipids. Working memory was assessed using a 3-back task. Linear regression, correlation, and mediation analyses were conducted to test for potential associations between serum lipids, inter- and intranetwork functional connectivity, and working memory performance. We found that higher serum triglyceride (TG) level was correlated with stronger connectivity between left frontoparietal and ventral attention networks, between right frontoparietal and dorsal attention networks, between right frontoparietal and dorsal sensorimotor networks, between right frontoparietal and lateral visual networks, and between salience (SN) and ventral sensorimotor (vSMN) networks, as well as lower connectivity between posterior default mode and left frontoparietal networks, between left frontoparietal and medial visual networks, and between ventral attention and dorsal sensorimotor networks. In addition, higher SN-vSMN connectivity was related to lower 3-back accuracy. More importantly, the relationship between serum TG and 3-back accuracy was mediated by SN-vSMN connectivity. Our findings not only may expand existing knowledge regarding serum lipids-brain-cognition relations from the perspective of large-scale functional network organization but also may inform a translational conceptualization of how to improve cognitive function through regulating serum lipids.

Higher Body-Mass Index and Lower Gray Matter Volumes in First Episode of Psychosis

BACKGROUND

Neurostructural alterations are often reported in first episode of psychosis (FEP), but there is heterogeneity in the direction and location of findings between individual studies. The reasons for this heterogeneity remain unknown. Obesity is disproportionately frequent already early in the course of psychosis and is associated with smaller brain volumes. Thus, we hypothesized that obesity may contribute to brain changes in FEP.

METHOD

We analyzed MRI scans from 120 participants with FEP and 114 healthy participants. In primary analyses, we performed voxel-based morphometry (VBM) with small volume corrections to regions associated with FEP or obesity in previous meta-analyses. In secondary analyses, we performed whole-brain VBM analyses.

RESULTS

In primary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in a) left fronto-temporal region (pTFCE = 0.008) and b) left postcentral gyrus (pTFCE = 0.043). When controlling for FEP, BMI was associated with lower GM volume in left cerebellum (pTFCE < 0.001). In secondary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in the a) cerebellum (pTFCE = 0.004), b) left frontal (pTFCE = 0.024), and c) right temporal cortex (pTFCE = 0.031). When controlling for FEP, BMI was associated with lower GM volume in cerebellum (pTFCE = 0.004). Levels of C-reactive protein, HDL and LDL-cholesterol correlated with obesity related neurostructural alterations.

CONCLUSIONS

This study suggests that higher BMI, which is frequent in FEP, may contribute to cerebellar alterations in schizophrenia. As previous studies showed that obesity-related brain alterations may be reversible, our findings raise the possibility that improving the screening for and treatment of obesity and associated metabolic changes could preserve brain structure in FEP.

Brain structural changes in CADASIL patients: A morphometric magnetic resonance imaging study

BACKGROUND

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a subcortical, inherited, cerebral small vessel disease. Several studies have revealed the involvement of specific cortical regions. However, the structural brain alterations and their clinical correlations remain largely undetermined.

METHODS

We evaluated 22 CADASIL patients and 22 age- and sex-matched healthy controls. We used surface- and voxel-based morphometric data derived from 3.0-T magnetic resonance imaging (MRI) to explore structural changes in gray and white matter. We calculated Pearson correlations between such data and clinical and MRI metrics.

RESULTS

Compared with controls, CADASIL patients exhibited significantly decreased cortical thickness in the left supramarginal gyrus, superior temporal gyrus, transverse temporal gyrus, insula, lateral orbitofrontal gyrus, isthmus cingulate gyrus and precentral gyrus. An extensive decrease in the white (but not gray) matter volume was also evident, predominantly in the frontal, parietal, temporal, and occipital lobes. The number of previous strokes or transient ischemic attacks was negatively associated with the cortical thickness of the left pars opercularis and right posterior cingulate gyrus.

CONCLUSION

Reductions in cortical thickness and white matter volume were evident in CADASIL patients compared with controls, and higher numbers of strokes and transient ischemic attacks were associated with regional cortical thinning.