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Sex Differences in the Physiological Network of Healthy Young Subjects

  • Barajas-Martínez, Antonio1, 2, 3
  • Ibarra-Coronado, Elizabeth2, 4
  • Fossion, Ruben2, 4
  • Toledo-Roy, Juan Claudio2, 4
  • Martínez-Garcés, Vania5
  • López-Rivera, Juan Antonio2, 6
  • Tello-Santoyo, Geraldine3
  • Lavin, Rusland D.2
  • Gómez, José Luis6
  • Stephens, Christopher R.2, 4
  • Aguilar-Salinas, Carlos A.7
  • Estañol, Bruno2, 7
  • Torres, Nimbe7
  • Tovar, Armando R.7
  • Resendis-Antonio, Osbaldo2, 8
  • Hiriart, Marcia2, 9
  • Frank, Alejandro2, 4, 10
  • Rivera, Ana Leonor2, 4
  • 1 Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México, Mexico City , (Mexico)
  • 2 Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City , (Mexico)
  • 3 Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City , (Mexico)
  • 4 Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México, Mexico City , (Mexico)
  • 5 Plan de Estudios Combinados en Medicina (PECEM-MD/PhD), Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City , (Mexico)
  • 6 Facultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City , (Mexico)
  • 7 Instituto Nacional de Ciencias Médicas y Nutrición “Salvador Zubirán”, Mexico City , (Mexico)
  • 8 Instituto Nacional de Medicina Genómica, Coordinación de la Investigación Científica-Red de Apoyo a la Investigación, UNAM, Mexico City , (Mexico)
  • 9 Instituto de Fisiología Celular, Mexico City , (Mexico)
  • 10 El Colegio Nacional, Mexico City , (Mexico)
Published Article
Frontiers in Physiology
Frontiers Media SA
Publication Date
May 11, 2021
DOI: 10.3389/fphys.2021.678507
  • Physiology
  • Original Research


Within human physiology, systemic interactions couple physiological variables to maintain homeostasis. These interactions change according to health status and are modified by factors such as age and sex. For several physiological processes, sex-based distinctions in normal physiology are present and defined in isolation. However, new methodologies are indispensable to analyze system-wide properties and interactions with the objective of exploring differences between sexes. Here we propose a new method to construct complex inferential networks from a normalization using the clinical criteria for health of physiological variables, and the correlations between anthropometric and blood tests biomarkers of 198 healthy young participants (117 women, 81 men, from 18 to 27 years old). Physiological networks of men have less correlations, displayed higher modularity, higher small-world index, but were more vulnerable to directed attacks, whereas networks of women were more resilient. The networks of both men and women displayed sex-specific connections that are consistent with the literature. Additionally, we carried out a time-series study on heart rate variability (HRV) using Physionet’s Fantasia database. Autocorrelation of HRV, variance, and Poincare’s plots, as a measure of variability, are statistically significant higher in young men and statistically significant different from young women. These differences are attenuated in older men and women, that have similar HRV distributions. The network approach revealed differences in the association of variables related to glucose homeostasis, nitrogen balance, kidney function, and fat depots. The clusters of physiological variables and their roles within the network remained similar regardless of sex. Both methodologies show a higher number of associations between variables in the physiological system of women, implying redundant mechanisms of control and simultaneously showing that these systems display less variability in time than those of men, constituting a more resilient system.

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