Hippocampus-driving progressive structural alterations in medication-naïve major depressive disorder

Li, Yuting; Wang, Chun; Teng, Changjun; Jiao, Kaili; Song, Xiu Zhen; Tan, Yarong; Xiao, Chaoyong; Zhang, Ning; Zhong, Yuan

doi:10.1016/j.jad.2019.05.053

Cited by 19 publications

(6 citation statements)

References 32 publications

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“…The protective effect of this model may be partly attributable to its regular consumption of vegetables. Reasonable mechanisms for this connection from the vegetable perspective are as follows: First, oxidative stress may be related to the abnormalities of the amygdala and hippocampus in patients with severe depression ( 38 ). Vegetables contain a lot of antioxidant compounds, which are beneficial for depression by reducing oxidative stress.…”

Section: Discussionmentioning

confidence: 99%

The Joint Association Between Multiple Dietary Patterns and Depressive Symptoms in Adults Aged 55 and Over in Northern China

Zhan

et al. 2022

Front. Nutr.

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BackgroundDepression is a common psychiatric disorder in older adults that affects their health-related quality of life. Two percent of adults over the age of 55 suffer from major depression, and the prevalence of depression increases with age. Even in the absence of major depressive disorder, 10–15% of older adults have clinically significant depressive symptoms.ObjectivesEpidemiological studies on the association between different gender eating patterns and depression show inconsistent associations. Our study examined whether different gender eating patterns are related to depression. We consider eating patterns individually and as a joint exposure to predefined eating patterns.MethodsPrincipal component analysis (PCA) was performed on the data of the 24-h diet recall dietary intake, and the dietary pattern was determined. Linear regression models are used to explore the relationship between different diets and depression of men and women; weighted quantile sum (WQS) regression, quantile g calculation (qgcomp) and Bayesian kernel machine regression (BKMR) are performed as Secondary analysis.ResultsIn the dietary patterns model, we found that the vegetable and fruit-based diet has a significant inhibitory effect in women, and the egg-milk-based diet has a significant inhibitory effect in men. We found that when all dietary factors are above the 55th percentile, there is a significant positive correlation between multiple dietary patterns and depression risk. We also determined a positive correlation between meat and obesity risk and a negative correlation between egg and milk and vegetables and fruits.ConclusionsIn the study population, after controlling for other baseline indicators and predictors of dietary pattern exposure, a fruit and vegetable-based diet was associated with a slightly healthier and lower risk of depression, while a meat-based dietary pattern associated with a higher risk of depression, and this association effect varies between genders.

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Section: Discussionmentioning

confidence: 99%

The Joint Association Between Multiple Dietary Patterns and Depressive Symptoms in Adults Aged 55 and Over in Northern China

Zhan

et al. 2022

Front. Nutr.

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“…Although the brain regions found in the Hays et al study are not consistent with previous studies, the authors suggest that the reason for this change is suggestive of neurodegeneration leading to CBF dysregulation and the existence of a neural compensatory mechanism for cognitive decline in some brain regions. T1-mapping has been used to study many central nervous system disorders such as epilepsy (Massire et al, 2021), multiple sclerosis (Massire et al, 2021;Thaler et al, 2021) and depression (Li et al, 2019). However, the findings of AD research are 10.3389/fnins.2022.974651 controversial (Tang et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

A diagnostic index based on pseudo-continuous arterial spin labeling and T1-mapping improves efficacy in discriminating Alzheimer’s disease from normal cognition

Wang

et al. 2022

Front. Neurosci.

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BackgroundPseudo-continuous arterial spin labeling (pCASL) is widely used to quantify cerebral blood flow (CBF) abnormalities in patients with Alzheimer’s disease (AD). T1-mapping techniques assess microstructural characteristics in various pathologic changes, but their application in AD remains in the exploratory stage. We hypothesized that combining quantitative CBF and T1 values would generate diagnostic results with higher accuracy than using either method alone in discriminating AD patients from cognitively normal control (NC) subjects.Materials and methodsA total of 45 patients diagnosed with AD and 33 NC subjects were enrolled, and cognitive assessment was performed for each participant according to the Chinese version of the Mini-Mental State Examination (MMSE). T1-weighted magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) and pCASL sequence were scanned on a 3T MR scanner. A brain morphometric analysis was integrated into prototype sequence, providing tissue classification and morphometric segmentation results. Quantitative CBF and T1 values of each brain region were automatically generated inline after data acquisition. Independent samples t-test was used to compare regional CBF and T1 values controlled by false discovery rate correction (corrected p < 0.01). The model with combined CBF and T1 values was compared with the individual index by performing receiver operating characteristic curves analysis. The associations between the MMSE score and CBF and T1 values of the brain were investigated using partial correlations.ResultsCerebral blood flow of the right caudate nucleus (RCc) and left hippocampus (LHc) was significantly lower in the AD group compared with the NC group, while the T1 values of the right caudate nucleus (RCt) and left hippocampus (LHt) increased in the AD group. Prediction accuracies of 73.1, 77.2, 75.9, and 81.3% were achieved for each of the above parameters, respectively. In distinguishing patients from controls using the corresponding optimized cut-off values, most combinations of parameters were elevated (area under curve = 0.775–0.894). The highest area under curve value was 0.944, by combining RCc, LHc, RCt, and LHt.ConclusionIn this preliminary study, the combined model based on pCASL and T1-mapping improved the diagnostic performance of discriminating AD and NC groups. T1-mapping may become a competitive technique for quantitatively measuring pathologic changes in the brain.

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“…Meanwhile, causal network of structural covariance (CaSCN) analysis sequences the structure images in a pseudo-time series according to the disease progression and can map the causal relationships among regions using signed-path coefficient Granger causality (GC) analysis (6). Both methods have been successfully used to investigate the structural network as well as the causal relationship among SCN components in patients with major depressive disorder (7), generalized anxiety disorder (8,9), and schizophrenia (10,11). However, to date, no study has used SCN and CaSCN analysis on cirrhotic patients; thus, the SCN and the potential causal relationships among the aberrant SCN components in cirrhotic patients with NMHE and MHE are still unclear.…”

Section: Introductionmentioning

confidence: 99%

Progressive Brain Structural Impairment Assessed via Network and Causal Analysis in Patients With Hepatitis B Virus-Related Cirrhosis

et al. 2022

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ObjectivesThis research amid to elucidate the disease stage-specific spatial patterns and the probable sequences of gray matter (GM) deterioration as well as the causal relationship among structural network components in hepatitis B virus-related cirrhosis (HBV-RC) patients.MethodsTotally 30 HBV-RC patients and 38 healthy controls (HC) were recruited for this study. High-resolution T1-weighted magnetic resonance imaging and psychometric hepatic encephalopathy score (PHES) were evaluated in all participants. Voxel-based morphometry (VBM), structural covariance network (SCN), and causal SCN (CaSCN) were applied to identify the disease stage-specific GM abnormalities in morphology and network, as well as their causal relationship.ResultsCompared to HC (0.443 ± 0.073 cm3), the thalamus swelled significantly in the no minimal hepatic encephalopathy (NMHE) stage (0.607 ± 0.154 cm3, p <0.05, corrected) and further progressed and expanded to the bilateral basal ganglia, the cortices, and the cerebellum in the MHE stage (p < 0.05, corrected). Furthermore, the thalamus swelling had a causal effect on other parts of cortex-basal ganglia-thalamus circuits (p < 0.05, corrected), which was negatively correlated with cognitive performance (r = −0.422, p < 0.05). Moreover, the thalamus-related SCN also displayed progressive deterioration as the disease advanced in HBV-RC patients (p < 0.05, corrected).ConclusionProgressive deterioration of GM morphology and SCN exists in HBV-RC patients during advanced disease, displaying thalamus-related causal effects. These findings indicate that bilateral thalamus morphology as well as the thalamus-related network may serve as an in vivo biomarker for monitoring the progression of the disease in HBV-RC patients.

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Hippocampus-driving progressive structural alterations in medication-naïve major depressive disorder

Cited by 19 publications

References 32 publications

The Joint Association Between Multiple Dietary Patterns and Depressive Symptoms in Adults Aged 55 and Over in Northern China

The Joint Association Between Multiple Dietary Patterns and Depressive Symptoms in Adults Aged 55 and Over in Northern China

A diagnostic index based on pseudo-continuous arterial spin labeling and T1-mapping improves efficacy in discriminating Alzheimer’s disease from normal cognition

Progressive Brain Structural Impairment Assessed via Network and Causal Analysis in Patients With Hepatitis B Virus-Related Cirrhosis

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