Obesity has reached epidemic levels globally, with serious health and economic consequences.
While lifestyle factors play a key role, genetics also influence a person’s susceptibility to weight gain or difficulty losing weight.
An emerging field called pharmacogenomics is uncovering how genetics impacts response to medications that cause weight gain as a side effect, as well as medications used to promote weight loss.
Key facts:
- Obesity rates have tripled since 1975. It is now estimated to affect 650 million adults worldwide.
- Weight gain is a common side effect of many widely prescribed medications including antipsychotics, antidepressants, antiepileptics, oral contraceptives, diabetes drugs, beta blockers, and steroids.
- There is significant individual variability in weight loss response to anti-obesity medications like phentermine, liraglutide, orlistat and more.
- Specific gene variants affect drug metabolism and response. Identifying an individual’s pharmacogenomic profile could optimize medication selection and dosing.
Source: Obesity 2021
The Science Behind Pharmacogenomics
Pharmacogenomics examines how variations in genes affect response to medications.
It combines the fields of pharmacology (the science of drugs) and genomics (the science of genes).
The goal is to develop optimized, personalized therapies tailored to a person’s genetic makeup.
A genotype refers to the particular gene variants a person possesses.
The phenotype is the observable physical characteristics and clinical effects.
Single nucleotide polymorphisms (SNPs) are small variations in the DNA sequence that can impact how a gene functions.
Pharmacogenomics looks at how SNPs and other genetic differences influence drug absorption, metabolism, distribution and actions at the target site.
This can significantly alter therapeutic efficacy and risk of adverse reactions.
Weight Gain as a Medication Side Effect & Genetics
Gaining weight is an annoying and potentially harmful side effect of many common medications.
The most problematic drug classes include antipsychotics, antidepressants, antiepileptics, oral contraceptives, diabetes medications, beta blockers and corticosteroids.
Research shows antipsychotics like olanzapine and clozapine frequently cause substantial weight gain, likely by interacting with serotonin, dopamine, histamine and adrenergic receptors in the brain.
Studies reveal certain mutations in the HTR2C gene protect against this effect.
Antidepressants, especially older tricyclics and mirtazapine, also often increase weight.
Variants in COMT and TPH1 genes are linked to more weight gain in patients taking SSRIs and SNRIs.
Among antiepileptics, valproic acid is most associated with weight gain.
Polymorphisms in the LEPR, ANKK1 and PRKAA2 genes correlate with greater BMI increase in patients taking valproate.
Oral contraceptives and systemic glucocorticoids like prednisone also commonly lead to added pounds.
Research is still needed on specific gene variants influencing this adverse effect.
Finally, diabetes medications including sulfonylureas, thiazolidinediones and insulin can cause weight gain by improving glucose control and appetite.
Variants in PLIN and other genes may impact weight changes with these therapies.
Gene Profiles Predict Efficacy of Weight Loss Drugs
In contrast to the weight gain effects above, pharmacogenomics is also being used to predict response to medications for losing weight.
Anti-obesity drugs work through various mechanisms including suppressing appetite, increasing satiety, blocking fat absorption or altering metabolism.
Phentermine is the most widely prescribed short-term obesity medication.
It acts on trace amine receptors to suppress appetite. Its combination with topiramate was recently approved for long-term treatment.
Specific variations in the INSR gene are associated with enhanced weight loss with topiramate.
Liraglutide, a GLP-1 receptor agonist, induces weight loss by increasing satiety and delaying gastric emptying.
Studies show the rs6923761 variant in GLP-1R results in greater BMI and fat reduction with liraglutide.
Orlistat works by blocking absorption of dietary fats.
Research found females with the rs5443 polymorphism in GNB3 lose less fat mass on orlistat compared to non-carriers.
The combination drug bupropion-naltrexone impacts weight by modulating dopamine and opioid pathways involved in eating behaviors.
Minimal data is available so far on genetic predictors of response.
Finally, the withdrawn drugs sibutramine and lorcaserin have some pharmacogenomic data.
Variants in GNB3, ADIPOQ and other genes associate with enhanced weight loss results from sibutramine.
From Research to Clinical Practice: Pharmacogenomics
While pharmacogenomic testing for weight management is not yet mainstream, significant evidence supports the influence of genetics on obesity, weight gain and response to medications targeting weight.
Identifying an individual’s genomic profile can potentially optimize treatment approaches.
Genetic screening may guide choice of anti-obesity therapy based on likelihood of response.
Testing may also indicate higher risk of weight gain with specific drugs, allowing selection of alternatives less influenced by a patient’s genotype.
However, clinical implementation faces barriers including limited provider awareness of pharmacogenomic testing, lack of evidence-based dosing guidelines, and inadequate insurance coverage.
More research and education are still needed to facilitate translation into routine medical care.
In conclusion, pharmacogenomics is paving the way toward personalized weight management tailored to the individual based on genetic makeup.
Harnessing this knowledge has potential to improve health on both individual and population levels.
While there is more work to be done, the future is bright for genetics-guided, precision treatment of obesity.
References
- Study: Pharmacogenomics of medication-induced weight gain and anti-obesity medications
- Authors: Sneha Singh et al. (2021)
