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

Han, Shan; Li, Panlong; Liu, Hua; Nie, Binbin; Yin, Xianzhen; Zhang, Tianhao; Sun, Xuming; Zhang, Wei; Feng, Ting; Wang, Luying; Hu, Yichao; Dong, Guanglong; Gao, Hongkai; Du, Jin; Ma, Lin; Li, Demin; Shan, Baoci

doi:10.1007/s00234-019-02202-3

Cited by 20 publications

(16 citation statements)

References 38 publications

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“…The diffuse and uniform nature of the BMI‐related brain alterations may be more congruent with cortical thinning as a consequence of obesity. The negative effects of BMI on brain structure are supported by a Mendelian randomization study, 40 several longitudinal studies, demonstrating that obesity or obesity‐related metabolic alterations precede and accelerate brain changes over time 18,41 and by improvement of brain indices following a successful treatment of obesity 42–44 …”

Section: Discussionmentioning

confidence: 98%

“…Obesity may represent a risk factor for neuroprogression in BD which can be modified or managed. Obesity‐related cortical alterations might be preventable or even reversible through weight management by dietary, lifestyle, surgical, or pharmacological interventions 42–44 . Furthermore, the current psychiatric medications have a very limited range of pharmacodynamic properties and the number of mechanistically different medications is proportional to efficacy in managing severe, multifactorial disorders.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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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 imagingderived 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

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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“…If obesity leads to brain alterations, this represents a manageable/modifiable risk factor for neuroprogressive BD [ 75 ]. Obesity-related structural brain abnormalities might be preventable or even reversible with dietary/lifestyle/surgical interventions focused on weight management [ 76 – 78 ]. Also, medications targeting obesity, such as liraglutide, may have neuroprotective effects, as also documented in participants with BD [ 79 ].…”

Section: Discussionmentioning

confidence: 99%

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

McWhinney¹,

Abé²,

Alda³

et al. 2021

Mol Psychiatry

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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.

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“…This finding is consistent with our previous meta-analysis providing strong evidence that obesity is associated with lower grey matter density in brain regions involved in cognition and emotional regulation [ 28 ]. If the mechanisms underlying the link between obesity and reductions in grey matter volume measured by MRI remain largely unknown, recent evidence indicates that visceral obesity-related metabolic alterations, including insulin resistance, dyslipidemia, and low-grade chronic inflammation, might mediate the link between obesity and brain abnormalities [ 64 , 65 ]. Moreover, brain alterations observed in individuals with obesity may also involve chronic inflammation, increased oxidative stress or cellular autophagy associated with obesity [ 66 ].…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2021

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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.

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

Cited by 20 publications

References 38 publications

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

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

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

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

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