title: Gender differences of brain glucose metabolic networks revealed by FDG-PET: evidence from a large cohort of 400 young adults.
abstract: BACKGROUND
  Gender differences of the human brain are an important issue in neuroscience research. In recent years, an increasing amount of evidence has been gathered from noninvasive neuroimaging studies supporting a sexual dimorphism of the human brain. However, there is a lack of imaging studies on gender differences of brain metabolic networks based on a large population sample.
  
  
  METHODS
  FDG PET data of 400 right-handed, healthy subjects, including 200 females (age: 25:45 years, mean age ± SD: 40.9 ± 3.9 years) and 200 age-matched males were obtained and analyzed in the present study. We first investigated the regional differences of brain glucose metabolism between genders using a voxel-based two-sample t-test analysis. Subsequently, we investigated the gender differences of the metabolic networks. Sixteen metabolic covariance networks using seed-based correlation were analyzed. Seven regions showing significant regional metabolic differences between genders, and nine regions conventionally used in the resting-state network studies were selected as regions-of-interest. Permutation tests were used for comparing within- and between-network connectivity between genders.
  
  
  RESULTS
  Compared with the males, females showed higher metabolism in the posterior part and lower metabolism in the anterior part of the brain. Moreover, there were widely distributed patterns of the metabolic networks in the human brain. In addition, significant gender differences within and between brain glucose metabolic networks were revealed in the present study.
  
  
  CONCLUSIONS
  This study provides solid data that reveal gender differences in regional brain glucose metabolism and brain glucose metabolic networks. These observations might contribute to the better understanding of the gender differences in human brain functions, and suggest that gender should be included as a covariate when designing experiments and explaining results of brain glucose metabolic networks in the control and experimental individuals or patients.
authors.affiliation: Department of Nuclear Medicine, Jinling Hospital, Clinical school of Medical College, Nanjing University, Nanjing, China.
authors.forename: Yuxiao
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Department of Medical Imaging, Jinling Hospital, Clinical school of Medical College, Nanjing University, Nanjing, China.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Xu
authors.affiliation: Department of Pharmacology, Soochow University, Suzhou, China.
authors.forename: Kai
authors.initials: K
authors.lastname: Li
authors.affiliation: Department of Nuclear Medicine, Jinling Hospital, Clinical school of Medical College, Nanjing University, Nanjing, China.
authors.forename: Hong
authors.initials: H
authors.lastname: Zhu
authors.affiliation: Department of Medical Imaging, Jinling Hospital, Clinical school of Medical College, Nanjing University, Nanjing, China.
authors.forename: Rongfeng
authors.initials: R
authors.lastname: Qi
authors.affiliation: Department of Medical Imaging, Jinling Hospital, Clinical school of Medical College, Nanjing University, Nanjing, China.
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: Department of Medical Imaging, Jinling Hospital, Clinical school of Medical College, Nanjing University, Nanjing, China.
authors.forename: Guangming
authors.initials: G
authors.lastname: Lu
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging* / Q000378:metabolism*; D015331:Cohort Studies; D005260:Female; D019788:Fluorodeoxyglucose F18; D005947:Glucose / Q000378:metabolism*; D006801:Humans; D008297:Male; D053858:Metabolic Networks and Pathways; D008875:Middle Aged; D049268:Positron-Emission Tomography; D012737:Sex Factors
chemical_list: D019788:Fluorodeoxyglucose F18; D005947:Glucose