New Delhi: Why do blockbuster weight-loss drugs deliver dramatic results for some patients and barely move the needle for others? A new study points to genetics as a key — though partial —explanation, opening the door to more personalised obesity treatment.
The study, published in Nature on 8 April, focuses on medications known as GLP-1 receptor agonists, which are widely used to treat obesity and Type 2 Diabetes. These include drugs such as semaglutide and tirzepatide, which have gained global attention for their effectiveness in reducing body weight. Researchers analysed data from nearly 28,000 patients for a duration of 8.3 months.
“Genetic variation is known to have an important role in treatment response, both for intended and adverse events,” the report reads.
The study further added that GLP‑1 receptor aganist drugs promote weight loss by acting on specific receptors in the body that regulate hunger and digestion. These receptors are influenced by a person’s genes, which can vary from one individual to another. As a result, the effectiveness of the medication and the likelihood of side effects are different in one person to another, which is why some people experience significant weight loss while others see only modest effects.
Genetic differences also make certain individuals more sensitive to how these drugs affect the stomach and brain, leading to side effects, such as nausea and diarrhoea.
The study also found that women tended to experience slightly greater reductions in body weight than men (−12.2 per cent versus −10.0 per cent), and that higher baseline BMI and longer treatment were also associated with significant weight loss.
Researchers, however, also noted that genes are only one side of this story because, other factors, such as diet, lifestyle, age, dosage, and overall health, also play a role in determining weight loss.
Also Read: Weight-loss drugs are changing. Here’s what to know about GLP-1s
How individuals respond to treatment
The study also highlighted the substantial variability in weight-loss outcomes among individuals receiving GLP-1–based therapies. It shows that while some individuals achieved clinically significant weight reduction (in some cases exceeding 25 per cent of body weight), some only lost around five per cent.
Genetic factors were found to have a statistically significant but modest effect size, meaning they influence outcomes but do not account for the full range of responses seen across individuals.
The findings further noted the potential for personalised medicine in weight-loss treatment. By analysing genetic data alongside clinical and demographic information, researchers were able to create models that could predict which patients are more likely to respond favourably to GLP-1 therapies.
These predictive models were tested in an independent electronic health record dataset, showing that patients could be stratified by expected weight-loss outcomes. The researchers said that genetic testing is not yet ready for routine clinical use, and more research is needed before these predictions can be implemented.
The study also underscores that genetics is only one factor influencing drug response. The researchers examined non-genetic predictors such as sex, age, ancestry, baseline body mass index (BMI), and treatment duration.
The study further compared self-reported survey data with electronic health records (EHRs) to understand how people responded to GLP-1 drugs. The study collated EHRs of 909 participants, out of which 195 people also completed a survey. The self-reported weight loss was higher than what EHRs showed.
The median weight loss reported in surveys was about −11.8 per cent of BMI, while EHRs recorded −5.79 per cent. Even for participants who had both survey and EHR data, the difference remained: −14.14 per cent vs −8.43 per cent BMI. Despite these differences, the trends between survey and EHR data were similar, showing a reasonable correlation (Pearson r = 0.57).
It shows that self-reported surveys are a useful way to track treatment, even though EHR data sometimes shows smaller weight-loss numbers.
(Edited by Insha Jalil Waziri)