Penn researchers use AI to find menstrual and temperature side effects of weight-loss drugs in Reddit posts

UPenn researchers analyzed 400,000+ Reddit posts and found GLP-1 drugs may cause unreported reproductive and temperature-related side effects. Nearly 4% of users reporting side effects described menstrual changes.

Published on: Apr 11, 2026
Penn researchers use AI to find menstrual and temperature side effects of weight-loss drugs in Reddit posts

Researchers use AI to identify unreported GLP-1 side effects from Reddit discussions

University of Pennsylvania researchers analyzed more than 400,000 Reddit posts to identify side effects of GLP-1 drugs that may not appear in clinical trials or drug labels. The study, published in Nature Health, found two classes of symptoms warranting further investigation: reproductive issues like irregular menstrual cycles and temperature-related complaints such as chills and hot flashes.

The research covered posts from nearly 70,000 Reddit users over more than six years. About 44% of users described at least one side effect, most commonly gastrointestinal distress-a known effect that validates the method.

What the data revealed

Nearly 4% of users who reported side effects described reproductive symptoms, including menstrual changes such as intermenstrual bleeding, heavy bleeding, and irregular cycles. This percentage would be higher in a female-only sample, the researchers noted.

Fatigue ranked as the second most common complaint among Reddit users, despite appearing in relatively few clinical trial reports. Temperature-related symptoms also emerged as a notable pattern.

"These drugs are thought to work by engaging the hypothalamus, which helps regulate a wide variety of hormones," said Jena Shaw Tronieri, a senior researcher at Penn's Center for Weight and Eating Disorders. "That doesn't mean the medications are necessarily causing these symptoms, but it could suggest that reports of menstrual changes and body temperature fluctuations are worth studying more systematically."

Why social media data matters for drug safety

Clinical trials identify the most dangerous side effects but often miss what patients worry about most. Large language models now enable researchers to analyze social media posts at scale, mapping varied symptom descriptions to medical terminology in ways that were previously impractical.

"Clinical trials are the gold standard, but by design, they are slow," said Sharath Chandra Guntuku, the study's senior author. "This is not a replacement for trials, but it can move much faster, and that speed matters when a drug goes from niche to mainstream almost overnight."

Reddit users are younger, more likely to be male, and disproportionately based in the United States-limitations the researchers acknowledge. Still, the patterns they identified align with how GLP-1 drugs like semaglutide and tirzepatide function in the body.

Next steps

The team plans to expand the analysis beyond Reddit and English-language communities to see whether the same patterns appear across different platforms and populations. The researchers also hope clinicians will investigate the side effects patients are discussing online.

For drugs that trend rapidly online-particularly those in loosely regulated markets like injectable peptides-patient discussions on platforms like Reddit and TikTok may offer early warning signs about actual user experiences.


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