Genes May Decide How Well Your Diabetes Drugs Work, Review Finds

Two of the most widely prescribed drugs in modern medicine, metformin and the sodium-glucose cotransporter-2 (SGLT2) inhibitors, work remarkably well for most people with type 2 diabetes, yet they fail or cause side effects in a substantial minority of patients. A new integrative review published in Health Science Reports argues that a large part of this unexplained variability may be written in the genome, and that the era of gene-guided diabetes therapy is approaching, even if it has not yet arrived.

The review, led by researchers synthesizing evidence from PubMed, Scopus and EBSCO up to July 2026, screened the literature according to PRISMA 2020 guidelines and ultimately included 31 original human studies: 18 on metformin and 13 on SGLT2 inhibitors. The authors deliberately chose an integrative framework, allowing them to combine pharmacogenetic association studies, pharmacokinetic investigations and clinical response data into a single narrative synthesis. Because the included studies varied so widely in design, populations and outcome measures, the team did not perform a formal meta-analysis or a uniform risk-of-bias assessment, instead weighing evidence by consistency, biological plausibility and sample size.

The scale of the clinical problem is enormous. According to the latest International Diabetes Federation Atlas figures cited in the review, roughly 589 million adults worldwide are living with type 2 diabetes, about one in nine adults, and that number is projected to reach 853 million by 2050. More than 90 percent of all adults with diabetes have the type 2 form, and approximately 252 million people, some 43 percent of the diabetic population, remain undiagnosed. With lifestyle change alone insufficient for most patients, pharmacotherapy is the backbone of treatment, which makes predictable drug response a global public health priority.

Metformin, the biguanide that has anchored first-line diabetes therapy for more than six decades, lowers glucose primarily by suppressing hepatic gluconeogenesis. It downregulates key gluconeogenic enzymes such as phosphoenolpyruvate carboxykinase and glucose-6-phosphatase, dampens glucagon-driven cAMP and protein kinase A signalling, and blocks mitochondrial glycerophosphate dehydrogenase, limiting the conversion of lactate and glycerol into glucose. It also activates AMP-activated protein kinase by inhibiting mitochondrial complex I, which reduces ATP and raises AMP, thereby curbing glucose production and lipogenesis while improving insulin sensitivity and promoting GLUT4-mediated glucose uptake in muscle and fat. Beyond glycemia, the drug has attracted interest for potential roles in cancer, polycystic ovary syndrome, non-alcoholic fatty liver disease and aging, and recent work suggests it may modulate the gut microbiome and stimulate the appetite-related metabolite N-lactoyl-phenylalanine.

Because metformin is not meaningfully metabolized, its fate in the body depends almost entirely on membrane transporters. Organic cation transporters encoded by SLC22A1 (OCT1), SLC22A2 (OCT2) and SLC22A3 (OCT3) mediate hepatic uptake, renal uptake and tissue distribution, while the multidrug and toxin extrusion proteins MATE1 and MATE2, encoded by SLC47A1 and SLC47A2, handle efflux into bile and urine. Polymorphisms in these genes can alter intracellular drug concentrations, systemic exposure and clearance, and thereby shift both glycemic efficacy and tolerability. The review identifies SLC22A1 as the most consistent genetic marker of metformin response: reduced-function OCT1 alleles have been linked across Han Chinese, Danish, Jordanian, Mexican-Mestizo and South Indian cohorts to attenuated HbA1c reductions, lower plasma metformin concentrations and higher rates of gastrointestinal intolerance. Notably, Danish data showed that carriers of the rs72552763 deletion experienced roughly 1.1 percent less HbA1c lowering at six months than non-carriers.

The evidence for the other transporter genes is more modest and less reproducible. SLC22A2 variants, particularly rs316019, appear to influence renal clearance of metformin more than glucose-lowering effect, with some studies showing reduced clearance in carriers and others finding no significant interaction at all. SLC22A3 and SLC47A1 show moderate, population-dependent associations with glycemic response, while SLC47A2 findings are inconsistent across South Indian and Iraqi cohorts. Intriguingly, the ATM gene, which encodes a kinase functionally linked to AMPK signalling rather than drug transport, has been associated with variability in metformin efficacy in both Chinese and large European cohorts, demonstrating that pharmacodynamic pathways, not just pharmacokinetic ones, shape who responds. The review’s authors stress that none of these individual associations yet supports routine genotype-guided metformin prescribing.

SGLT2 inhibitors, by contrast, represent a younger and genetically less charted pharmacogenomic landscape. This drug class, including canagliflozin, dapagliflozin, empagliflozin, ertugliflozin and bexagliflozin, descends conceptually from phlorizin, a compound isolated from apple tree bark whose glucose-blocking properties in the kidney were recognized as early as the 1930s. Modern gliflozins selectively inhibit SGLT2, the transporter responsible for reabsorbing roughly 90 to 97 percent of filtered glucose in the proximal tubule, forcing the excess glucose out in urine through an entirely insulin-independent mechanism. In persistent hyperglycemia, renal SGLT2 expression is upregulated, so blocking it counteracts a maladaptive amplification loop. Although their glucose-lowering effect is modest, large trials have established robust cardiovascular and renoprotective benefits, making them a cornerstone of contemporary care.

Pharmacogenetically, SGLT2 inhibitors are metabolized mainly by glucuronidation through UGT1A9 and UGT2B4. Reduced-function variants such as UGT1A9*3 (p.Met33Thr) increase systemic exposure to canagliflozin and ertugliflozin by about 1.26 to 1.45-fold in pharmacokinetic studies, but these changes have not translated into clinically meaningful differences in efficacy or dose requirements, and pooled analyses of more than 1,600 participants concluded that no dose adjustment is warranted. Variants in the drug target gene SLC5A2, which encodes SGLT2 itself, show associations with glucose homeostasis, HbA1c and diabetes risk in some populations, and one Slovenian study linked the rs9934336 A allele to higher fasting glucose and increased risk of diabetic retinopathy. Emerging but preliminary data suggest SLC5A2 variants may even modulate cardiorenal outcomes, possibly reflecting a form of natural SGLT2 inhibition that limits additional drug benefit. Meanwhile, the PNPLA3 I148M variant, a major determinant of fatty liver disease, appears to modify how much liver fat patients lose on dapagliflozin, with risk-allele carriers responding less to monotherapy but more when the drug is combined with omega-3 carboxylic acids.

The review’s comparative analysis highlights how mechanistically distinct these two drug classes are, and why their pharmacogenetic profiles differ so sharply. Metformin acts on the liver and depends on a well-characterized transporter network, giving it the most mature pharmacogenetic evidence base of any oral glucose-lowering agent. SGLT2 inhibitors act on the kidney, are cleared by hepatic glucuronidation, and carry strong cardiorenal benefits with very low hypoglycemia risk, but their genetic determinants remain emerging and modest in effect. The authors grade SLC22A1 as the most promising biomarker for clinical use, while most other metformin genes and all SGLT2-related markers remain investigational or exploratory. A recurring theme is that drug response is inherently polygenic: no single variant explains enough variance to guide treatment alone, and genetic effects operate within a web of clinical and environmental modifiers including renal function, diet, concomitant medications and the gut microbiome, which is estimated to contribute alongside genetics to roughly a third of the individual variation in metformin response.

Looking forward, the review outlines several priorities for translating pharmacogenomics into practice. Polygenic risk scores tailored to metformin and SGLT2 inhibitors must be developed, but current discovery cohorts are heavily Eurocentric, limiting generalizability to South Asian, Latino and African populations where genetic architecture and drug response may differ. Multi-omics integration, combining genomics with proteomics, metabolomics, metagenomics and epigenomics, is proposed as the path to more accurate prediction, potentially accelerated by artificial intelligence. Implementation science matters too: clinicians have expressed frustration with commercial pharmacogenetic panels that lack actionable diabetes-specific information and are not embedded in electronic medical records. Ultimately, the authors conclude that large prospective, multicenter, ethnically diverse interventional studies, ideally piggybacking on ongoing cardiovascular and renal trials of SGLT2 inhibitors, are essential before gene-guided glycemic therapy can move from promising biology to routine clinical decision-making.

Subject of Research: Pharmacogenetics of metformin and SGLT2 inhibitor response in type 2 diabetes

Article Title: Gene‐Guided Therapy in Type 2 Diabetes Mellitus: An Integrative Review of the Pharmacogenetics of Metformin and Sodium‐Glucose Cotransporter‐2 Inhibitors

Article References: Hossain, I., Haidar, M., Ratul, M. A., Sumona, J. F., Shabnaz, S., Nokib, A. F., & Fatema‐Tuz‐Zohora (2026). Gene‐Guided Therapy in Type 2 Diabetes Mellitus: An Integrative Review of the Pharmacogenetics of Metformin and Sodium‐Glucose Cotransporter‐2 Inhibitors. Endocrinology, Diabetes & Metabolism, 9(6), Article e70343. https://doi.org/10.1002/edm2.70343

Image Credits: AI Generated

DOI: 10.1002/edm2.70343

Keywords: type 2 diabetes, metformin, SGLT2 inhibitors, pharmacogenetics, OCT1, MATE1, UGT1A9, SLC5A2, precision medicine, polygenic risk scores, drug transporters, Health Science Reports