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Sex and bacterial infectious diseases
J-L Mege1, F Bretelle1,2, M Leone1,3
1Aix-Marseille Université, IRD, APHM, MEPHI, IHU-Méditerranée Infection, Marseille, France.
New Microbes and New Infections
|November 8, 2018
Summary
Infectious disease outcomes differ significantly between sexes, with males often experiencing more severe infections. Biological factors, including sex hormones and X-linked genes, contribute to this observed sex dimorphism.
Area of Science:
- Infectious disease epidemiology
- Immunology
- Sex differences in health
Background:
- Infectious diseases exhibit unequal distribution between males and females.
- Epidemiological studies show more male patients with sepsis, contrary to expectations based on age demographics.
- Factors like lifestyle and healthcare access contribute, but biological differences warrant consideration.
Purpose of the Study:
- To explore the reasons behind sex dimorphism in infectious disease susceptibility and severity.
- To investigate the role of biological factors, such as X-linked variability and sex hormones, in sex-based differences in infection response.
- To reconcile findings from animal models with clinical observations in human patients.
Main Methods:
- Review of epidemiological data on sex distribution in infectious diseases.
- Analysis of biological mechanisms, including X-linked gene expression and hormonal influences.
- Comparison of findings from animal models of infection with human clinical data.
Main Results:
- Animal models demonstrate more severe infection responses in males compared to females.
- Female sex hormones appear to attenuate the inflammatory response to infection.
- Observed sex dimorphism in infectious diseases is influenced by lifestyle, exposure, and healthcare access, alongside biological factors.
Conclusions:
- Biological sex is a significant factor influencing infectious disease outcomes.
- Sex hormones play a role in modulating the immune response to pathogens.
- Translating findings from experimental models to clinical practice requires accounting for confounding variables such as age and hormonal fluctuations.
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