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Why Weight Loss Medications Work Differently for Different People

Writer: Rucha Natekar
Rucha Natekar
29 minutes ago
3 min read

In the STEP 1 trial, 1,961 adults with obesity and no diabetes took semaglutide (either a 2.4 mg or placebo) for 68 weeks, alongside lifestyle support. Average weight change was a 14.9% loss on semaglutide and a 2.4% loss on placebo.


In the SURMOUNT-1 trial, adults on the highest dose of tirzepatide (15 mg) lost an average of 20.9% of body weight over 72 weeks, compared with 3.1% on placebo.


Behind these averags is a wide range of individual results. In SURMOUNT-1, 56.7% of people on the 15 mg dose lost 20% or more of their body weight, and about 9% did not reach even a 5% loss. They had the same medication, same dose but had different outcomes. Why?


Weight loss on any medication reflects a mix of influences: dose and adherence, nutrition, sleep, stress, activity, hormones, other medications, sex, age, which medication is used, and biology. Genetics is one major layer among these.


What do we know about genes with respect to body weight

A systematic review of BMI heritability pooled 88 estimates from twin studies (140,525 twins in total) and 27 estimates from family studies. Twin-study estimates ranged from 0.47 to 0.90, with a median of 0.75. Family-study estimates ranged from 0.24 to 0.81, with a median of 0.46. Estimates were generally higher in children than in adults.


Heritability describes how much of the variation in a trait across a population is linked to genetic differences.


What the newest research says about GLP-1 medications

In April 2026, Nature published a genome-wide association study from 23andMe researchers: "Genetic predictors of GLP1 receptor agonist weight loss and side effects." It analyzed self-reported data from 27,885 people taking GLP-1 medications. Key findings:

  • A missense variant in the GLP1R gene (rs10305420) was associated with greater weight loss, about 0.76 kg more per copy of the effect allele. This corresponds to roughly a 0.641% greater decrease in BMI.

  • Variation in GLP1R and in GIPR was associated with nausea or vomiting. The GIPR association (rs1800437) appeared only in people taking tirzepatide.

  • The researchers combined genetic findings with factors such as sex, age, and which medication a person takes. Among 23andMe research participants, estimated weight loss ranged from 6% to 20% of starting weight, and the likelihood of nausea or vomiting ranged from 5% to 78%, depending on genetics and other factors.


An independent expert comment on the paper offered context. The effect of a single variant is small in clinical terms, and the data are self-reported. In the paper, self-reported weight loss was larger than weight loss recorded in linked health records (about 11.8% versus 5.8%). Sex, age, and the specific medication remain important predictors of how much weight a person loses.


What a genetic report can offer

Used responsibly, genetic information can help you:

  • Learn about variants linked to appetite, metabolism, body weight regulation, and medication response

  • See which findings come from direct research on GLP-1 medications and which come from broader pathway-level research

  • Bring more specific questions to your prescriber or care team

  • Keep a record of your genomic data that can be reinterpreted as the science develops

It works best as one input alongside your medical history, lab work, and your clinician's guidance. Genetic testing for GLP-1 response is not yet part of routine clinical practice for choosing or dosing these medications.


Two ways to explore your genetics

If you already have raw DNA data from a service such as 23andMe or AncestryDNA, PredictivCare's WeightTwin reinterprets an existing raw data file into a report focused on weight and wellness, so you do not need to submit a new sample.


If you want a deeper look. GenomeTwin or WeightTwin uses whole genome/exome sequencing combined with a deeper analysis for a fuller view of your genomic and expression data.


Sources and further reading

Clinical trials

Genetics of body weight

Genetics of GLP-1 medication response

 
 
 

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