Hypothalamic gray matter volume loss in hypnic headache

2010 ◽  
Vol 69 (3) ◽  
pp. 533-539 ◽  
Author(s):  
Dagny Holle ◽  
Steffen Naegel ◽  
Sarah Krebs ◽  
Charly Gaul ◽  
Elke Gizewski ◽  
...  
Keyword(s):  
Gray Matter ◽  
Gray Matter Volume ◽  
Volume Loss ◽  
Hypnic Headache ◽  
Matter Volume

scholarly journals Moderating Effect of Insulin Resistance on the Relationship between Gray Matter Volumes and Cognitive Function

2018 ◽  
Vol 7 (11) ◽  
pp. 413 ◽  
Author(s):  
Jiyeon Lee ◽  
Jihyeon Kim ◽  
Seong Shin ◽  
Soowon Park ◽  
Dong Yoon ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Insulin Resistance ◽  
Alzheimer's Disease ◽  
Cognitive Function ◽  
Cognitive Decline ◽  
Gray Matter ◽  
Structural Changes ◽  
Gray Matter Volume ◽  
Volume Loss ◽  
Matter Volume

Background: It is controversial whether exposure to insulin resistance accelerates cognitive deterioration. The present study aimed to investigate the association between insulin resistance and gray matter volume loss to predict the cognitive decline. Methods: We recruited 160 participants (78 with Alzheimer’s disease and 82 without Alzheimer’s disease). Insulin resistance, regional gray matter volume, and cognitive function were assessed. A hierarchical moderated multiple regression (MMR) model was used to determine any associations among insulin resistance, structural changes in the brain, and cognitive decline. Results: The volumes of 7 regions in the gray matter were negatively related to insulin resistance in Alzheimer’s disease (p =0.032). Hierarchical MMR analysis indicated that insulin resistance did not directly affect the cognitive decline but moderated the cognitive decline through the decrease in gray matter volume in the key brain regions, i.e., inferior orbitofrontal gyrus (left), middle cingulate gyrus (right), hippocampus (right), and precuneus (right) (p < 0.05 in each case). Conclusion: Insulin resistance appears to exacerbate the cognitive decline associated with several gray matter volume loss.

Association of regional gray matter volume loss and progression of white matter lesions in multiple sclerosis — A longitudinal voxel-based morphometry study

NeuroImage ◽  
2009 ◽  
Vol 45 (1) ◽  
pp. 60-67 ◽  
Author(s):  
Kerstin Bendfeldt ◽  
Pascal Kuster ◽  
Stefan Traud ◽  
Hanspeter Egger ◽  
Sebastian Winklhofer ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
White Matter ◽  
Gray Matter ◽  
Gray Matter Volume ◽  
White Matter Lesions ◽  
Volume Loss ◽  
Voxel Based Morphometry ◽  
Matter Volume

scholarly journals Association of Ideomotor Apraxia With Frontal Gray Matter Volume Loss in Corticobasal Syndrome

2009 ◽  
Vol 66 (10) ◽  
Author(s):  
Edward D. Huey ◽  
Matteo Pardini ◽  
Alyson Cavanagh ◽  
Eric M. Wassermann ◽  
Dimitrios Kapogiannis ◽  
...  
Keyword(s):  
Gray Matter ◽  
Gray Matter Volume ◽  
Corticobasal Syndrome ◽  
Volume Loss ◽  
Matter Volume ◽  
Ideomotor Apraxia

Predominant gray matter volume loss in patients with end-stage renal disease: a voxel-based morphometry study

2013 ◽  
Vol 28 (4) ◽  
pp. 647-654 ◽  
Author(s):  
Long Jiang Zhang ◽  
Jiqiu Wen ◽  
Ling Ni ◽  
Jianhui Zhong ◽  
Xue Liang ◽  
...  
Keyword(s):  
Renal Disease ◽  
Gray Matter ◽  
End Stage Renal Disease ◽  
Gray Matter Volume ◽  
Volume Loss ◽  
Voxel Based Morphometry ◽  
Matter Volume ◽  
Stage Renal Disease ◽  
End Stage

Regional Gray Matter Volume Loss Is Associated with Gait Impairments in Young Brain-Injured Individuals

2017 ◽  
Vol 34 (5) ◽  
pp. 1022-1034 ◽  
Author(s):  
David Drijkoningen ◽  
Sima Chalavi ◽  
Stefan Sunaert ◽  
Jacques Duysens ◽  
Stephan P. Swinnen ◽  
...  
Keyword(s):  
Gray Matter ◽  
Gray Matter Volume ◽  
Volume Loss ◽  
Matter Volume ◽  
Brain Injured ◽  
Gait Impairments

scholarly journals 3069 Characterizing the Neural Signature of Metabolic Syndrome

2019 ◽  
Vol 3 (s1) ◽  
pp. 4-4
Author(s):  
Eithan Kotkowski ◽  
Larry R. Price ◽  
Crystal G. Franklin ◽  
Maximino Salazar ◽  
Ralph A. DeFronzo ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Waist Circumference ◽  
Gray Matter ◽  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Gray Matter Volume ◽  
Volume Loss ◽  
Matter Volume ◽  
Fasting Plasma ◽  
Neural Signature

OBJECTIVES/SPECIFIC AIMS: Our objective is to understand the influence of the features comprising metabolic syndrome (central obesity, raised fasting plasma glucose, triglycerides, blood pressure, and decreased HDL cholesterol) on brain structure in men and women. With the understanding that MetS is a strong predictor of gray matter volume loss in specific brain regions, in this study we sought to quantify the influence of each of the metabolic syndrome biometric variables on the structures involved in the neural signature of metabolic syndrome. METHODS/STUDY POPULATION: We conducted multiple linear regression analyses on a cross-sectional sample of 800 individuals from the Genetics of Brian Structure (GOBS) image archive (352 men and 448 women). GOBS is an offshoot of the San Antonio Heart Study involving an extended pedigree of Mexican Americans from the greater San Antonio area. Its goal is to localize, identify, and characterize genes/quantitative trait loci associated with variations in brain structure and function (Winkler, 2010). The archive has continuously added participants from approximately 40 families since 2006. Neuroanatomic (T1-weighted MRI scans obtained on a Siemens 3T scanner and processed using FSL), neurocognitive, and biometric phenotypes have been obtained for each subject (including blood lipids). Linear regressions were run using SPSS and incorporated biometric and gray matter volume values obtained from 800 GOBS participants. RESULTS/ANTICIPATED RESULTS: Linear regressions incorporating metabolic syndrome variables as dependent variables and gray matter volume from regions involved in the neural signature of metabolic syndrome as predictors show significant predictive patterns that are largely similar between men and women, with some differences. Another linear regression conducted with gray matter volume from the neural signature of metabolic syndrome as the dependent variable and metabolic syndrome variables as predictors show that waist circumference and triglycerides are the greatest predictors of gray matter volume loss in men, and fasting plasma glucose and waist circumference are the greatest predictors of gray matter volume loss in women. DISCUSSION/SIGNIFICANCE OF IMPACT: Significant sex differences in the relationships between metabolic syndrome variables and gray matter volume changes between brain regions comprising the neural signature of metabolic syndrome were identified. waist circumference, fasting plasma glucose, and triglycerides are the most reliable predictors of gray matter volume loss. The variance in gray matter volume of the neural signature of metabolic syndrome in men is more significantly explained by waist circumference and triglycerides (when accounting for age) and in women is more significantly explained by waist circumference and fasting plasma glucose (when accounting for age). A model of metabolic syndrome that emphasizes a risk of neurodegeneration should focus on waist circumference for both men and women and weigh the remaining variables accordingly by sex (triglycerides in men and fasting plasma glucose in women).

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