Analysis of 149 FDA adverse event reports identified a potential link between CGRP antagonist migraine drugs and Raynaud's phenomenon, with the PI3K/AKT pathway as the likely mechanism for small molecule drugs.
149 RP adverse event reportsAcross 7 CGRP antagonists in the FDA database, with fremanezumab showing the strongest statistical signal and PI3K/AKT identified as the underlying mechanism
What the researchers found
From the FAERS database (Q2 2018 to Q1 2025), 149 adverse event reports linked CGRP antagonists to Raynaud's phenomenon across 7 drugs:
- Erenumab had the most reports
- Fremanezumab showed the strongest adverse event signal across all four statistical methods
- Drug-gene network analysis identified key molecular nodes: AKT1, EGFR, ERBB2 for rimegepant
- KEGG pathway analysis revealed PI3K signaling as the most likely mechanism for small molecule CGRP antagonists (rimegepant, atogepant, ubrogepant) inducing Raynaud's
- The PI3K/AKT pathway connects CGRP blockade to vascular dysfunction
The authors recommend regular monitoring for Raynaud's in patients receiving CGRP antagonists, particularly those with underlying vascular dysfunction.
Why it matters
CGRP is a potent vasodilator — blocking it to treat migraines could theoretically cause blood vessel constriction elsewhere. This study provides the first systematic evidence that CGRP antagonists may trigger Raynaud's phenomenon, an important safety consideration for the millions of patients now taking these drugs for migraine prevention and treatment.
How the study worked
Disproportionality analysis of the FAERS database using four established signal detection methods. Gene targets of CGRP antagonists and Raynaud's were predicted using multiple databases. Protein-protein interaction (PPI) networks were built using STRING. KEGG pathway enrichment analysis identified potential mechanisms. Analysis covered Q2 2018 through Q1 2025.
What this study cannot tell us
FAERS data is based on voluntary reporting and cannot establish causation — only a statistical signal. Reporting biases may affect which drugs appear more frequently. The 149 reports represent a small fraction of total CGRP antagonist users. The drug-gene network analysis is computational and requires experimental validation. Pre-existing vascular conditions in reported patients were not always documented.
How to read the evidence
This is a pharmacovigilance study using real-world adverse event data with computational network analysis. FAERS-based studies can identify potential safety signals but cannot establish causation — they generate hypotheses requiring clinical validation.
When this study was published
Published in 2025 with data through early 2025, this study provides the most current safety signal analysis for CGRP antagonists and vascular adverse events.
The bigger picture
CGRP plays essential roles beyond migraine — including maintaining blood vessel dilation and protecting against hypertension. As CGRP-targeting therapies become blockbuster drugs prescribed to millions, understanding their vascular side effects becomes critical. This study highlights the need to monitor the long-term cardiovascular safety of chronic CGRP blockade.
Questions still open
- Should patients with Raynaud's or other vascular conditions avoid CGRP antagonists?
- Do antibody-based CGRP blockers (erenumab, fremanezumab) carry different Raynaud's risk than small molecule gepants?
- Does the duration of CGRP antagonist use correlate with Raynaud's risk?
Common questions
What is Raynaud's phenomenon and why might CGRP drugs cause it?
Should I stop my CGRP migraine medication if I get cold fingers?
Read the original research
Calcitonin gene-related peptide antagonists in Raynaud's phenomenon: a disproportionality study based on real data and drug-gene network analysis.
Naunyn-Schmiedeberg's archives of pharmacology
Citation
Zhu, Haibin; Ma, Minghua; Tian, Weiwei; Wu, Tingting; Wang, Yan; Huo, Yan; Liao, Xiaolan. (2025). Calcitonin gene-related peptide antagonists in Raynaud's phenomenon: a disproportionality study based on real data and drug-gene network analysis.. Naunyn-Schmiedeberg's archives of pharmacology. https://doi.org/10.1007/s00210-025-04877-3