Updates In Common Genetic Variants May Help Guide Drug Selection For Treating Uncontrolled Diabetes

1. Introduction

Metabolic mechanisms are a complex network of biochemical reactions that ensure proper nutrition consumption, energy production, and energy balance within a range that optimizes the structural integrity and function of cells, tissues, and the organism [1,2]. The hepatopancreatic unit plays a fundamental role in adjusting metabolism and the flow of energy across various tissues, activating complex regulatory genes, cells, and mediators to achieve this balance (Figure 1). A similar level of dynamic complexity is observed across vertebrates in order to coordinate the diverse cell types and functions. Consequently, metabolic networks are highly interconnected to sustain homeostasis [3].

An individual's metabolism, which consists of life-sustaining biochemical reactions, is influenced by genetic factors to maintain an evolutionarily stable strategy. Accumulating evidence demonstrates that factors such as age, nutrition, physical activity, and environmental influences impact an individual's metabolic processes [4,5,6,7]. Thus, the set point for metabolism is molded not only by genetic factors but also by extrinsic variables [8,9].

Glucose, the body's primary source of energy, is tightly regulated. While normal fasting blood glucose levels typically range between 70 and 80 mg/dL in most individuals, there is considerable variability in glucose levels even among healthy people. This biological variation is largely genetically determined. In general, when glucose disturbances are mild, the glucose homeostatic system helps resolve these perturbations, maintaining glucose levels within a narrow range to meet the body's needs [10]. However, when the disturbance in glucose homeostasis is significant and sustained, the homeostatic response may develop into a pathological process, resulting in abnormal glucose accumulation. Over time, this can lead to insulin resistance, insulin deficiency, and ultimately T2DM.

We conducted an electronic search in October 2024 using PubMed, Medline, U.S. Food and Drug Administration (FDA, fda.gov), ClinicalTrials.gov, and Scopus databases, with keywords and MeSH (medical subject headings) terms such as genetic polymorphisms in DNA coding regions and the prevalence of specific polymorphisms across different ethnic groups.

This review aims to summarize current knowledge on the gene and the most common epigenetic variants and their relationship to diabetes risk and prevention, particularly among patients with uncontrolled diabetes. Additionally, it outlines newly approved therapies, and those under investigation (Phase 2 and Phase 3) as novel options for treating T2DM. Although high proportion of individuals with T2DM is on treamtent for their condition, only a small fraction of T2DM patients achieve glycemic control with existing treatments, making uncontrolled T2DM a major clinical isuue. Therefore, new treatment strategies are urgently needed to prevent serious complications and reduce the need for hospitalization.

2. Definition of Uncontrolled T2DM

Plasma glycosylated hemoglobin A1C (HbA1C) levels serve as a key indicator of long-term blood glucose control [11], playing a central role in both diagnosis [12] and monitoring of individuals with diabetes. According to the American Diabetes Association (ADA) [13], the American College of Physicians (ACP) [14], the Association of Clinical Endocrinologists [15], the American College of Endocrinology [16], and the World Health Organization (WHO), uncontrolled diabetes is defined as chronic hyperglycemia, with HbA1C levels exceeding 7.9%.

3. Heterogeneity of Uncontrolled T2DM

T2DM is a polygenic disorder [17,18], with multiple genetic risk alleles contributing to an individual’s susceptibility [19]. While hundreds of genomic sites are associated with an increased risk of T2DM, only a small fraction are located in protein-coding regions of DNA. Interestingly, many polymorphisms identified through genome-wide association studies (GWAS) are found in noncoding regions, which often play a significant role in human diseases [20]. In contrast, rare familial forms of diabetes, caused by mutations in a single gene (monogenic diabetes), can lead to hyperglycemia and a diabetic phenotype due to alterations in protein sequences [21].

T2DM arises from a complex interaction between genetic and environmental factors [22]. Risk factors such as poor diet, lack of physical activity, and surprisingly noise and air pollution [23,24,25] contribute significantly to its onset. Genetic factors account for approximately 20% to 80% of the population's risk for T2DM [26].

Monogenic forms of diabetes, which are caused by mutations in a single gene [27,28], include conditions such as neonatal diabetes [29], maternally inherited diabetes with deafness [30,31], and syndromic forms like Bardet-Biedl syndrome and Wolfram syndrome [32,33]. Below, we summariz the key findings on T2DM-associated monogenic genes that influence insulin secretion, inflammation, and insulin sensitivity, which are emerging as key targets for developing novel antidiabetic therapies.

Among the T2DM-associated monogenic genes, we explore the preproinsulin gene, mutations of which can lead to hyperinsulinemia, hyperproinsulinemia, and neonatal diabetes mellitus. This review focuses on specific gene variants such as PPARγ, TCF7L2, KCNJ11, HNF4α, p.Arg114Trp, GLIS3, and LEP, as these variants represent strong candidates because of their roles in insulin regulation and insulin signaling. They are well-supported by replication studies and play significant roles in pancreatic beta-cell function and energy metabolism in the context of T2DM pathogenesis (Table 1). Moreover, these genes endode proteins that are the recent emerging targets that already in the focus for developing new therapies in the treatment of uncontrolled diabetes.

3.1. Peroxisome Proliferator-Activated Receptor Gamma (PPARγ)

PPARs (PPARα, PPARγ, PPARβ) belong to the nuclear hormone receptor superfamily of ligand-activated transcription factors [48]. PPARα is predominantly expressed in adipose tissue [49] and plays a crucial role in regulating adipocyte differentiation [50], free fatty acid uptake, and storage. PPARγ is highly expressed in monocytes and macrophages, where it inhibits inflammatory responses by modulating the nuclear factor-κB (NF-κB) signaling pathway [50,51,52]. In addition to its anti-inflammatory functions, PPARγ activation is essential for macrophage differentiation, polarization, and lipid metabolism [50].

PPARγ regulates glucose homeostasis [50]. PPARγ agonists have been shown to reduce fibrosis in organs like the pancreas and liver [53], which play a crucial role in regulating the rate of glucose metabolism and controlling glucose homeostasis. Deficiencies in PPARγ and leptin are associated with metabolic syndrome, characterized by dyslipidemia, renal hypertrophy, and elevated levels of the profibrotic cytokine transforming growth factor beta (TGFβ) in the kidneys [54]. Notably, studies have demonstrated that deletion of the PPARγ gene in the epiblast of mice leads to the development of T2DM and renal fibrosis [55]. Similarly, macrophage-specific deletion of PPARγ results in lupus-like autoimmune glomerulonephritis [56], emphasizing the critical role of PPARγ in inflammation. Inflammation, reactive oxygen species, and diabetes have a bi-directional relationship [57].

Several studies have extensively examined the role of PPARγ [55,58,59,60]. Disease-associated mutations in PPARγ can result in either complete or partial loss of function [61], depending on their impact on the residual activity of the encoded mutant PPARγ. Variants in the PPARγ gene have been linked to severe obesity [60], insulin resistance [61], a decreased risk of T2DM in certain ancestries [62] or increased risk of T2DM [45], hypercholesterolemia [63], and systemic sclerosis characterized by diffuse fibrosis and vascular abnormalities [64]. Taken together, these studies provide irrefutable evidence of the pathogenicity of several common PPARγ variants when inherited and their influences on glycemic physiology.

3.2. Maturity-Onset Diabetes of the Young (MODY)

Maturity-Onset Diabetes of the Young (MODY) is a heterogeneous genetic disorder caused by mutations in genes involved in beta-cell dysfunction, leading to insulin deficiency [65,66]. MODY can be classified into at least 14 various types based on clinical presentation, two of which will be discussed here. MODY 1 and MODY 13 are associated with increased risk of T2DM in several studies and large-scale meta-analyses [67,68,69].

MODY is characterized by inherited beta-cell dysfunction, leading to reduced insulin secretion and elevated blood glucose levels. The severity of hyperglycemia and beta-cell dysfunction varies depending on the type of MODY. The global prevalence of MODY is estimated to range from 1-5% of diabetic patients [70], with a mutation carrier rate of approximately 1-5 in 10,000 individuals in the general population.

3.2.1. HNF4α and Its Role in Diabetes

Obesity and hyperinsulinemia are observed in MODY 1 [71]. The most common causes of MODY are mutations in hepatocyte nuclear factor 4-α (HNF4α, p.Arg114Trp) [72,73] with reduced penetrance [39,40], which exhibits autosomal dominant inheritance. HNF4α regulates hepatic genes [38]. HNF4α (p.Arg114Trp) is characterized by pancreatic β-cell dysfunction. Evidence suggests that HNF4α regulates glucose transport and metabolism [74]. Mutations in HNF4α are generally associated with a progressive decline in pancreatic beta cell function and a vascular risk profile similar to that of T2DM [75]. However, the individuals with MODY do not have either ketoacidosis or pancreatic autoantibodies. They are nonobese individuals who have diabetes at young age, but it can occur at any age. Mutations in HNF4α are the most common cause of MODY in the European countries [76]. Notably, HNF4α variants do not appear to contribute significantly in the European American population [40]. HNF4α (p.Arg114Trp) variant is associated with an approximate eight-fold increased T2DM risk in T2DM genome-wide association studies [77]. These patients with this disease should receive a stronger β cell-preserving therapy.

3.2.2. KCNJ11 and Its Role in Diabetes

KCNJ11 is a member of the potassium channel genes [41]. The protein encoded by KCNJ11 is an inward-rectifying channel (Kir6.2), which is characterized by allowing the efflux of potassium into the cell [78]. The elevation of cytosolic potassium levels depolarizes the cell membrane and subsequently activates calcium ion channel, leading to the elevation of calcium levels. Increased intracellular free calcium levels are essential for insulin secretion from pancreatic β-cells [79]. These calcium channels trigger the voltage-dependent potassium channels to repolarize the cell membrane. Kir 6.2 protein (consists of 4 subunits) is controlled by G-protein and is associated with the sulfonylurea receptor (made of 4 subunits) encoded by the ABCC8 gene [35]. Kir6.2 is implicated in the regulation of cellular metabolism and contribute to the mechanisms by which hypoglycemia stimulates glucagon release from pancreatic α-cells. Several reviews can provide the readers with a more detailed understanding of the structure, function, and regulation of potassium inward-rectifying channel superfamily [41,78,80].

Mutations in KCNJ11 typically occur de novo during gametogenesis or embryogenesis [81]. While genome-wide association studies on KCNJ11 gene have identified over 180 single nucleotide polymorphisms (SNPs) [82,83], three of which are located in the coding regions and are associated with increased risk of diabetes [41]. These three SNPs include rs5215, rs5218, and rs5219 [42], which will be discussed here.

KCNJ11 rs5218 variant is associated with the pathogenesis of T2DM, whereas rs5215 and rs5219 are found in individuals with T1DM, T2DM. The KCNJ11 gene variant (rs5219) is strongly related to the levels of the circulating HbA1c in this disease [84] and can cause transient neonatal diabetes or permanent neonatal diabetes. Both rs5215 and rs5219 polymorphism were associated with blood pressure levels among patients with T2DM [85,86,87]. The correlation between rs5219 in patients with T2DM and the medication response is controversial. KCNJ11 rs5219 gene polymorphism also is found to be implicated in gestational diabetes mellitus in people in China [88] but not in individuals from Sweden [89,90]. These studies suggest that background polygenic risk in the population in China differ greatly with respect to disease prevalence and incidence. A meta-analysis showed that the KCNJ11 rs5219 polymorphism is a risk factor for developing T2DM in Caucasians and in populations from East Asia [91], and an independent predictor of T2DM in the Iraqi population in the Middle East [92]. Another study provides no evidence supporting a relationship between rs5219 and the risk of diabetes in Iranian [93]. The lack of association could potentially be due to the absence of other environmental elements such as obesity [94] and hypertension [85]. Rs5219 is found to be associated with several diseases including hyperinsulinemic hypoglycemia [95], familial 2 [82], and MODY 13.

The role of rs5219 in medication response remains contentious. While the KCNJ11 gene polymorphism (rs5219) is associated with hepatitis insulin sensitivity [96], it is not associated with diabetic peripheral neuropathy [97]. Several studies provide evidence that the diabetic patients with KCNJ11 rs5219 variant are susceptible to metformin therapy [98], metformin and sulfonylurea combination therapy [99], metformin and gliclazide therapy [100] in different ethnic groups [98]. Patients with KCNJ11 gene polymorphism (rs5219) are more responsive to glimepiride and glibenclamide than those being treated with gliclazide [84]. However, another study indicates that patients with rs5219 variant exhibit the impairment of glibenclamide-induced insulin release, highlighting an example of pharmacogenetics in T2DM [101].

These findings highlight the importance of genetic variability in drug response, underscoring the potential for personalized treatment strategies to reduce healthcare disparities and enhance precision medicine.

3.2.3. GLIS3 and Its Role in Diabetes

Gli-similar 3 (GIS3), a key transcription factor in insulin production, is a compensatory β-cell proliferation in adults [102,103,104]. GLIS family of proteins (GLIS 1, GLIS 2, GLIS 3) carry significant role in the regulation of a number of physiological processes [105,106]. Mutations in GLIS proteins have been implicated in several pathologies such as neonatal diabetes mellitus, congenital hypothyroidism, congenital glaucoma, and cystic kidneys [107,108].

Defective GLIS3 results in impaired insulin function, which may arise abnormal pancreatic development [109], dysfunctional β-cells, or β-cell destruction [105,108,110]. In vitro deficiency of GLIS3 in β-cells triggers the activation of the intrinsic pathway of apoptosis [111], thereby susceptibility to diabetes. Individuals with P/LP GLIS3 variants are associated with increased T2DM risk [37]. Rare missense mutations in GLIS3 are linked to elevated HbA1c levels and an increased risk of T2DM [112]. GLIS3 rs10758593 variant is associated with T2DM in an Egyptian population [36]. Polymorphism of the GLIS3 gene is found to be associated with the development of MODY in a Russian population sample [113].

Given its role in insulin production and β-cell function, GLIS3 is emerging as a potential therapeutic target. Inhibiting the apoptotic effects of GLIS3 could help reduce complications from neonatal diabetes and improve β-cell function, making it a promising avenue for future T2DM treatments.

3.3. LEP Variant and Its Role in T2DM and Obesity

While the genetic causes of T2DM remain complex, certain rare genetic variants have been identified that increase the risk of developing the disease. A recent study identified a rare enhancer variant near the LEP gene (rs147287548), particularly prevalent in African and African American populations, which increases the risk of diabetes by four-fold [43]. The LEP gene encodes leptin, a hormone primarily produced by adipose tissue that regulates body weight. Leptin levels are positively correlated with body mass index (BMI) and fat mass [114].

Diet in high fat, carbohydrate, fructose, and low in protein reduce leptin secretion, known as leptin resistance [115]. A high-protein diet triggers sustained reduction in appetite and reduced plasma leptin [116]. Congenital leptin deficiency is associated with excessive hunger and weight gain, while increased leptin levels are linked to T2DM [117]. Interestingly, recombinant leptin treatment in children with leptin deficiency has shown a sustained reduction in body weight, particularly through fat loss [118]. These findings underscore the role of leptin in body weight regulation and highlight its potential as a therapeutic target for obesity and T2DM.

3.4. OPG Gene

Recent genetic evidence indicates that monogenic rare variants and SNPs are responsible for susceptibility to high blood pressure via alterations in the components of renin-angiotensin system, including natriuretic peptides, the sympathetic neuronal system, endothelial dysfunction, and inflammation [119,120]. Notably, 50% of people with insulin resistance are susceptible to develop hypertension, in the early phase of the disease [121,122]. This suggests that insulin resistance leads to genetic and epigenetic perturbations that results in hypertension. Both diabetes and hypertension are recognized as the major risk factors for CV disease [123], and have substantial overlap in the CV disease complications, including atherosclerosis, dyslipidemia, and obesity (Figure 2). Needless to say, prevalence of diabetes associated complications varies among different ethnic population [124], leading to the notion that disparities in the variant allele frequencies among different ethnic regions may play a role in disease susceptibility [125].

Vascular calcification, an age related phenomenon, is common to both diabetes [126] and hypertension [127]. The intimal calcification not only contributes to a reduction in vascular compliance [127] but also is linked to vessel stiffness. Arterial stiffening, a hallmark of atherosclerosis, is a known pathophysiological mechanism of hypertension [128]. Although the underlying mechanisms of diabetes-induced atherosclerosis remain a dilemma, higher levels of arterial calcification are observed in patients with diabetes at the clinical and pathological level [129]. Osteoprotegerin (OPG), a biomarker of vascular calcification, is a decoy receptor for receptor-activator for NF-κB ligand (RANKL), which has been implicated in pathophysiology of vascular calcification [126]. OPG is also found to be associated with myocardial stiffness [130], hypertension, and diabetes [47,131,132]. Recent genetic evidence indicates that CV risks are higher in T2DM patients with hypertensions expressing OPG rs2073618 gene polymorphism [47] (Table 1).

In conclusion, T2DM is influenced by a complex interplay between genetic predisposition and epigenetic factors.

4. Diabetes Inheritance and Personalized Treatment Approaches

4.1. Current Treatment Guidelines for Diabetes

The ADA recommends a stepwise approach for managing diabetes, with metformin as the first-line treatment, followed by other agents like sulfonylureas, glucagon-like peptide-1 (GLP-1) receptor agonists, or sodium-glucose co-transporter-2 (SGLT2) inhibitors (Figure 2). These guidelines emphasize individual patient factors such as CV, kidney, and liver health, along with comorbidities, preferences, and risk of hypoglycemia [133].

However, emerging data suggest that this "one-size-fits-all" approach may not be effective for all patients. Diabetes is a multifactorial disease, with endothelial dysfunction, inflammation, oxidative stress, insulin resistance, and chronic hyperglycemia-induced coagulation [134] and fibrinolysis impairment [135] all contributing to thrombotic diseases in T2DM patients [57,136,137] . Genetic variability, particularly in different ethnic groups, can significantly influence drug efficacy, often leading to suboptimal outcomes.

4.2. Genetic Variability and Ethnic Differences in Drug Response

Genetic differences influence responses to common antidiabetic medications [138]. For example, the PPARγ gene, a susceptibility locus for T2DM [139], is also the molecular target of thiazolidinediones [140]. Similarly, KCNJ11, which encodes a potassium channel involved in insulin secretion, is a target for sulfonylureas, with genetic variation influencing medication responses, as seen in changes to fasting glucose and HbA1c levels [140]. Furthermore, TCF7L2 polymorphisms have been associated with insulin secretion and response to GLP-1 receptor agonists and sulfonylureas [140,141].

Additionally, SLC2A2 gene, encodes the facilitated glucose transporter GLUT2, variations affect hepatic metformin uptake, influencing its therapeutic effectiveness [142]. It is suggested that SLC2A2 rs8192675 can serve as a potential biomarker for stratified medicine [142]. Research also shows that African Americans exhibit a stronger glycemic response to metformin compared to European Americans [143].

The implications of these findings are significant. Integrating pharmacogenomic testing into diabetes care could pave the way for personalized treatment strategies that maximize efficacy and minimize adverse effects. Developing genotype-guided treatment protocols, supported by evidence from diverse, large-scale studies, could transform diabetes care into a precision medicine framework. Such an approach not only has the potential to improve individual outcomes but also to address disparities in treatment effectiveness across different population groups, promoting equity in healthcare delivery.

5. Obesity and Its Association with Insulin Resistance

Obesity is a medical condition characterized by the excessive accumulation of body fat, which poses significant health risks, including reduced life expectancy and an increased incidence of various diseases [144]. The most common measure of obesity is BMI, which classifies individuals based on their weight relative to height. According to the WHO, a BMI of 25 or higher is classified as overweight, and a BMI of 30 or higher is considered obese. The prevalence of overweight and obesity has been steadily increasing in both children and adults from 1990 to 2022 [145].

Several factors contribute to obesity, including the consumption of energy-dense, nutrient-poor foods, poor eating habits, lack of physical activity, hormonal imbalances, genetic predisposition, and certain illnesses and medications [146,147]. As a highly complex condition, obesity involves multiple genetic loci and pathways that regulate energy balance, appetite, and metabolism. Among the most prominent complications of obesity are metabolic syndrome, stroke, osteoarthritis, and certain types of cancer (such as endometrial, colon, and gall bladder cancer) [148,149].

Unfortunately, most current treatments for obesity, including pharmacological agents, are associated with serious side effects and variable clinical outcomes [150].

Obesity is closely associated with insulin resistance [151], making it a significant risk factor for the development of T2DM. Genetic studies have identified several genes linked to both obesity and insulin resistance, such as Pro12Ala PPAR-γ, fat mass and obesity-associated (FTO), and retinol binding protein. Research has uncovered hundreds of genetic loci associated with obesity, revealing its heterogeneous nature across different populations. Variants in genes like FTO and melanortin-4 receptor (MC4R) have been consistently linked to BMI and fat distribution, highlighting the genetic underpinnings of obesity [152,153]. However, the interaction between genetic susceptibility and environmental factors like diet and physical activity is still not fully understood, leading to significant variability in obesity-related outcomes.

Importantly, many of the genetic loci implicated in obesity also overlap with pathways involved in glucose metabolism, suggesting a shared genetic foundation between obesity and metabolic disorders like T2DM. For example, FTO gene variants not only influence BMI but also affect insulin sensitivity and glucose regulation [152]. Similarly, MC4R polymorphisms, which are key regulators of appetite and energy expenditure, have been linked to impaired glycemic control alongside obesity [154]. These findings underscore the interrelated nature of genetic pathways governing both conditions, which can manifest differently depending on an individual's genetic profile and environmental influences.

5.1. Gene-Environment Interactions in Obesity

The heterogeneity observed in obesity can be further amplified by gene-environment interactions. For instance, the PPARγ gene, which plays a critical role in lipid metabolism and adipogenesis, exhibits variable effects on obesity risk depending on factors such as dietary fat intake [155]. Furthermore, epigenetic modifications, including DNA methylation and histone acetylation, regulate gene expression in response to environmental influences, contributing to obesity [156]. These epigenetic mechanisms also play a role in metabolic outcomes, highlighting the dynamic interplay between genetic predisposition and environmental factors in shaping the health risks associated with obesity.

These findings suggest that the heterogeneity of obesity is not determined by genetics alone but is also influenced by external factors, including diet and lifestyle. For example, transient hyperglycemia has been shown to induce p65 gene, a regulator of inflammation [157], expression in endothelial cells, which can persist for several days [158]. Additionally, obesity risk alleles, such as those in the FTO gene [159] and LEPR gene [160], are influenced by diet composition and physical activity levels [159].

5.2. Implications for Personalized Medicine and Obesity Management

Understanding the genetic heterogeneity of obesity has profound implications for both clinical practice and public health. Environmental factors can interact with genetically determined glucose homeostasis in genetically susceptible individuals, contributing to the development of obesity and diabetes. For instance, evidence suggests that hyperglycemia can activate genes that perpetuate endothelial dysfunction, a key feature of metabolic disorders [158]. By leveraging insights from genomic studies, clinicians can develop more targeted strategies for managing obesity and its associated complications, such as T2DM.

Genetic profiling could help identify individuals at higher risk for obesity-related metabolic disorders, allowing for earlier and more personalized interventions. Moreover, integrating genomic and epigenetic data into obesity research could offer new therapeutic targets and inform precision medicine approaches. This personalized approach could provide more effective treatments tailored to an individual’s genetic makeup and environmental exposure, ultimately improving health outcomes.

By addressing the genetic diversity of obesity, we can better understand the complex factors that contribute to its development and its association with metabolic diseases, such as T2DM. This understanding is critical for reducing the global burden of obesity-related diseases and improving overall health.

6. Need for New Treatments

Despite the availability of a variety of pharmacotherapies for glycemic control in T2DM, including biguanides, thiazolidinediones, and sulfonylureas, their major limitation is that they often tend to lose effectiveness after a few years. This suggests that T2DM management remains difficult and challenging, in part due to the genetic variability among patients. These genetic variants are key factors that influence disease susceptibility, response to therapy, and clinical outcomes. Other significant barriers to effective diabetes management include the side effects of current treatments, such as weight gain, hypoglycemia, fluid retention, and gastrointestinal discomfort.

The rising incidence of diabetes, coupled with the limitations of existing medications and their adverse effects, has driven the FDA to approve new antidiabetic drugs almost every year in recent years. This reflects a growing need for more effective, sustainable, and safer treatment options for T2DM (Table 2).

6.1. Novel Pharmacological Therapies in T2DM

Several novel pharmacological treatments have recently been developed and approved to improve the management of T2DM:

6.1.1. Brenzavvy (Bexagliflozin)

Brenzavvy is an FDA-approved oral SGLT2 inhibitor [161] designed for use in adult patients with T2DM to help improve blood sugar control alongside diet and exercise (Table 2). The kidneys play a crucial role in glucose homeostasis by reabsorbing glucose through the SGLT2 protein in the renal proximal convoluted tubules. Bexagliflozin reduces glucose reabsorption, lowers the renal threshold for glucose, and promotes urinary glucose excretion, significantly lowering blood sugar levels. It is particularly beneficial for T2DM patients with chronic kidney disease (CKD) [162] (eGFR between 30-60 mL/min/1.73 m²). In addition to improving glycemic control [162], brenzavvy also helps reduce CV and renal complications in these patients. However, common side effects include yeast infections, diabetic ketoacidosis, kidney or bladder infections, and increased urination (Table 2).

6.1.2. Tirzepatide

Tirzepatide is considered a novel medication recently approved for treating T2DM in the USA (Table 2). Tirzepatide is a synthetic polypeptide and acts as dual agonists for the GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) receptors, key mediators of insulin secretion that are also expressed in certain brain regions that regulate food intake [163]. Tirzepatide is shown to significantly improve glycemic control and promote weight loss similar to GLP-1 medications such as semaglutide [164]. It is reported that tirzepatide outperforms dulaglutide, semaglutide (Ozempic, Figure 3), degludec, and glargine in terms of glycemic control [165], which may help reduce microvascular complications. It is feasible to assume that if tirzepatide is implemented shortly after the diagnosis of T2DM, it might potentially cause a long-term reduction in microvascular disease. Tirzepatide is currently used as a second-line diabetes medication to maintain glycemic levels in the recommended range in order to delay or prevent diabetes-related complications [166].

6.1.3. Kerendia (finerenone)

Kerendia is an FDA-approved mineralocorticoid receptor antagonist [167]. Compared to other antagonists, finerenone is more potent and selective for the mineralocorticoid receptor [168]. It has been shown to reduce CV and renal complications, particularly in patients with diabetes and kidney disease [167] (Table 2). Finerenone is an adjunctive medication, that provides a promising option for managing T2DM in individuals with comorbid conditions affecting both the heart and kidneys. It is not an essential part of treatment but may help offer a dual benefit in reducing adverse CV and renal outcomes [169].

These novel therapies represent significant advances in the treatment of T2DM, addressing not only glycemic control but also reducing comorbidities such as CV and renal complications, thus improving patient outcomes and quality of life.

6.2. Clinical Trial of Antidiabetic Therapy in Patients T2DM

Our search yielded 33 eligible clinical trials. Among these studies, we identified 15 new compounds. In the clinical studies, compared with placebo, dipeptidyl peptidase 4 (DPP-4) inhibitors, new SGLT2 inhibitors, insulin secretion inducer (Exenatide)/ SGLT2 inhibitor combination, oral small-molecule glucagon-like peptide-1 receptor agonist (GLP1 RA), and GLP1 RA are found to be more effective in improving glycemic control and appear to have no or minimal side effects for most participants. The summary of these potential new treatments is shown in (Table 3).

7. Future Perspectives

The impact of human genetic variation on metabolic homeostasis is becoming increasingly evident, particularly in T2DM. Rare genetic variants play a significant role in altering the metabolic phenotype of individuals with T2DM. Understanding these genetic variations and their role in energy homeostasis, as well as the regulation of food intake, could pave the way for developing more targeted and effective treatments for T2DM.

The etiology of T2DM is influenced by several complex factors, including the central nervous system (CNS), which regulates glucose metabolism, and a combination of genetic and environmental factors. Key hormones involved in metabolic regulation, such as insulin, glucagon, GLP-1, and GIP, also play pivotal roles in disease development. Lifestyle factors, including glucolipotoxicity diets and sedentary behavior, as well as altered islet architecture, vascular endothelial dysfunction, immune system changes, and pancreatic islet behavior, all contribute to the pathogenesis of T2DM.

Due to the intricate and interconnected systems that govern metabolism, the pathogenesis of T2DM remains mechanistically complex and not yet fully understood. Future therapeutic research will need to consider how these diverse networks of systems and processes interact synergistically to produce the altered metabolic phenotype in T2DM. Additionally, research must explore how new treatments, such as bexagliflozin, tirzepatide, and finerenone, can influence the hormones involved in metabolic homeostasis, ultimately striving to produce a metabolic profile that closely resembles that of a healthy individual.

Both bexagliflozin and tirzepatide have shown considerable promise as novel agents that provide more effective therapies for T2DM, while also offering beneficial effects on multiple organs involved in disease pathology. However, the genetic profile of each patient can significantly influence their response to these drugs. Gene variants may lead to variations in drug efficacy and potential side effects, signifying the need for a personalized approach to treatment. Enormous progress has been made in identifying and cataloging the genetic basis of T2DM based on GWAS. However, we should continue to improve our understanding of the genetic basis of T2DM and elucidate how these variants influence cellular pathways, leading to the observed disease trait. Our newly gained knowledge would immensely help improve patient management by helping clinicians predict which treatments will be most effective for individual patients.

8. Conclusions

Uncontrolled T2DM often progresses into a multisystemic illness that encompasses micro- and macrovascular dysfunction, clotting abnormalities, renal injury, inflammation, retinopathy, and peripheral neuronal damage. These complications have already caused significant morbidity and debilitation in a large fraction of patients with T2DM worldwide. Despite our growing understanding of the genetic drivers of disease heterogeneity and advancements in treatment strategies, uncontrolled T2DM remains a significant global health challenge.

Recent advancements in T2DM treatment, such as new DPP-4 inhibitors, oral small-molecule GLP1-RAs, new SGLT2 inhibitors, and oral insulin, show considerable promise in managing hyperglycemia, particularly in patients with uncontrolled T2DM or hypertensive patients with T2DM. However, diagnostic and treatment options for this subset of patients are currently insufficient. While positive results have been reported in a limited number of clinical trials, there is still a need for rigorous further research to assess the efficacy and potential side effects of these treatments.

Moreover, new clinical trials are required to evaluate treatments that address the underlying physiological mechanisms of uncontrolled T2DM, including persistent hyperglycemia, as well as the etiological heterogeneity that drives the disease's development and progression. Only through a more comprehensive understanding of both the genetic and environmental factors at play, together with advancements in precision medicine, will we be able to address the challenges posed by T2DM in order to improve patient outcomes worldwide.