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AI Flags Potential GLP-1 Symptoms in 400,000 Reddit Posts: Pennsylvania Study

Researchers examined more than five years of Reddit posts involving nearly 70,000 users discussing semaglutide and tirzepatide and found reports of menstrual changes and temperature-related symptoms among the main classes of symptoms identified.
A person uses an injection pen to administer medication into their abdomen.
September 14, 2026 05:30 PM IST | Written by Supriya Singh | Edited by Pratima O Pareek

Artificial intelligence (AI) analysis of more than 400,000 Reddit posts has identified several symptoms reported by users of GLP-1 drugs, including the weight-loss and diabetes drugs semaglutide and tirzepatide, that may not be fully reflected in clinical trials or official regulatory information, according to a study by researchers at the University of Pennsylvania.

The study analysed more than five years of posts from nearly 70,000 Reddit users discussing semaglutide, the active ingredient in Ozempic, Wegovy and Rybelsus, and tirzepatide, the active ingredient in Mounjaro and Zepbound.

Researchers identified two groups of symptoms that they said warrant further investigation. These are reproductive symptoms, including changes in menstrual cycles, and temperature-related complaints, such as chills and hot flashes.

The researchers said the user reports could provide signals for further clinical research.

“Some of the side effects we found, like nausea, are well known, and that shows that the method is picking up a real signal,” says Sharath Chandra Guntuku, research associate professor in Computer and Information Science (CIS) at Penn Engineering and the study’s senior author. He said the less well-documented symptoms could serve as leads from patients themselves that clinicians may want to investigate further.

The researchers stressed that Reddit users are not representative of all people taking GLP-1 medications. The users tend to be younger, are more likely to be male and are disproportionately based in the United States.

About 44% of users reported at least one side effect, most commonly gastrointestinal problems.

However, researchers also identified symptoms that were less prominently represented in existing clinical evidence. Nearly 4% of users who reported side effects described reproductive symptoms, including bleeding between periods, heavy bleeding and irregular menstrual cycles.

Users also described temperature-related complaints, including chills, feeling cold, hot flashes and symptoms resembling a fever.

Fatigue was another notable finding and ranked as the second most common complaint among Reddit users, despite reaching reporting thresholds in relatively few clinical trials.

The researchers said the findings may warrant further investigation because the hypothalamus, a region of the brain involved in regulating hormones, reproduction and body temperature, is thought to play a role in how GLP-1 drugs work.

“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,” said Jena Shaw Tronieri, senior research investigator at Penn’s Center for Weight and Eating Disorders and a co-author of the study.

The study used what Guntuku describes as “computational social listening” to analyse large volumes of online discussions. A key challenge was that Reddit users often describe symptoms in different ways. Researchers used large language models (LLMs) to help map these social media posts to standardised medical terminology in the Medical Dictionary for Regulatory Activities (MedDRA), which is widely used to classify medical conditions, symptoms and adverse events.

The researchers noted that clinical trials may not capture all the symptoms that concern patients, while large collections of social media posts can offer additional insights despite not being representative.

“Large language models have made it possible to do this kind of analysis much faster with a level of standardization that could be difficult to achieve before,” said Neil Sehgal, the study’s first author and a doctoral student in CIS advised by Guntuku and Ungar.

Sehgal said the menstrual irregularities represented a signal that warranted further investigation.

The researchers plan to broaden the analysis beyond Reddit and English-language communities to see whether similar patterns emerge across other platforms and populations.

Guntuku said the approach is not a replacement for clinical trials but can provide signals much faster.

Also Read: NeurIPS 2026 Workshop Lineup Points to AI’s Shift Beyond LLMs and Data Centres

Authors

  • AI FrontPage Reporter Supriya Singh

    Supriya Singh is a Reporter at AI FrontPage covering the AI & Education and AI & Jobs beats. She brings six years of print and digital experience, including three years at The Asian Age, where she reported on higher education, Delhi government, and crime. She is based in Delhi-NCR.

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  • Pratima Pareek, Editor and Co-founder of AI FrontPage

    Pratima O Pareek is an Editor and Co-Founder of AI FrontPage. A gold medalist in Mass Communication and Journalism, she's worked across national and international newsrooms, bringing sharp editorial instincts and a commitment to clarity. She believes in cutting through the noise to deliver stories that actually matter.
    Off the clock, she watches offbeat cinema, follows tennis, and explores new places like a traveler, not a tourist.

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