Identifying a causal link between prolactin signaling pathways and COVID-19 vaccine-induced menstrual changes

Identifying a causal link between prolactin signaling pathways and COVID-19 vaccine-induced menstrual changes

COVID-19 vaccines have been instrumental tools in the fight against SARS-CoV-2 helping to reduce disease severity and mortality. At the same time, just like any other therapeutic, COVID-19 vaccines were associated with adverse events. Women have reported menstrual cycle irregularity after receiving...

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Bibliographic Details
Published in:npj vaccines Vol. 8; no. 1; p. 129
Main Authors: Hajjo, Rima, Momani, Ensaf, Sabbah, Dima A., Baker, Nancy, Tropsha, Alexander
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 01-09-2023
Nature Publishing Group
Nature Portfolio
Subjects:
631/250/590/2293
692/1807/2782
Biological effects
Biomedical and Life Sciences
Biomedicine
COVID-19
COVID-19 vaccines
Fertility
Immunization
Infectious Diseases
Infertility
Medical Microbiology
Menstruation
Public Health
Side effects
Vaccine
Vaccines
Virology
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Summary:COVID-19 vaccines have been instrumental tools in the fight against SARS-CoV-2 helping to reduce disease severity and mortality. At the same time, just like any other therapeutic, COVID-19 vaccines were associated with adverse events. Women have reported menstrual cycle irregularity after receiving COVID-19 vaccines, and this led to renewed fears concerning COVID-19 vaccines and their effects on fertility. Herein we devised an informatics workflow to explore the causal drivers of menstrual cycle irregularity in response to vaccination with mRNA COVID-19 vaccine BNT162b2. Our methods relied on gene expression analysis in response to vaccination, followed by network biology analysis to derive testable hypotheses regarding the causal links between BNT162b2 and menstrual cycle irregularity. Five high-confidence transcription factors were identified as causal drivers of BNT162b2-induced menstrual irregularity, namely: IRF1, STAT1, RelA (p65 NF-kB subunit), STAT2 and IRF3. Furthermore, some biomarkers of menstrual irregularity, including TNF, IL6R, IL6ST, LIF, BIRC3, FGF2, ARHGDIB, RPS3, RHOU, MIF, were identified as topological genes and predicted as causal drivers of menstrual irregularity. Our network-based mechanism reconstruction results indicated that BNT162b2 exerted biological effects similar to those resulting from prolactin signaling. However, these effects were short-lived and didn’t raise concerns about long-term infertility issues. This approach can be applied to interrogate the functional links between drugs/vaccines and other side effects.
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ISSN:2059-0105
2059-0105
DOI:10.1038/s41541-023-00719-6