Background: Type 2 diabetes (T2D) is one of the leading causes of mortality and is a public health challenge worldwide. Metformin is the first-choice treatment for T2D; its pharmacokinetics (PK) is facilitated by members of the solute carrier (SLC) superfamily of transporters, it is not metabolized, and it is excreted by the kidney. Although interindividual variability in metformin pharmacokinetics is documented in the Mexican population, its pharmacogenomics is still underexplored. We aimed to identify variants in metformin SLC transporter genes associated with metformin PK and response in Mexican patients. Methods: Using exome data from 2217 Mexican adults, we identified 86 biallelic SNVs in the eight known genes encoding SLC transporters, with a minor allele frequency ≥ 1%, which were analyzed in an inadequate glycemic control (IGC) association study in T2D metformin treated patients. Metformin PK was evaluated in a pediatric cohort and the effect of associated SNVs was correlated. Results: Functional annotation classified two SNVs as pathogenic. The association study revealed two blocks associated with IGC. These haplotypes comprise rs622591, rs4646272, rs4646273, and rs4646276 in SLC22A1; and rs1810126 and rs668871 in SLC22A3. PK profiles revealed that homozygotes of the SLC22A1 haplotype reached lower plasma metformin concentrations 2 h post administration than the other groups. Conclusions: Our findings highlight the potential of pharmacogenomics studies to enhance precision medicine, which may involve dosage adjustments or the exploration of alternative therapeutic options. These hold significant implications for public health, particularly in populations with a high susceptibility to develop metabolic diseases, such as Latin Americans.

Endoplasmic reticulum stress (ERS) is activated in all cells by stressors such as hyperglycemia. However, it remains unclear which specific serum biomarkers of ERS are consistently altered in type 2 diabetes (T2D). We aimed to identify serum ERS biomarkers that are consistently altered in T2D and its complications, and their correlation with metabolic and anthropometric variables. We performed a systematic review and meta-analysis following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-Analyses and Systematic Reviews of Observational Studies (MOOSE). The risk of bias was assessed using the Newcastle–Ottawa scale. Random-effects models weighted by the inverse variance were employed to estimate the standardized mean difference and correlations as effect size measures. Indicators of heterogeneity and meta-regressions were evaluated. Of the 1206 identified studies, 22 were finally included, representing 11,953 subjects (2224 with T2D and 9992 non-diabetic controls). Most studies were of high quality. Compared with controls, subjects with T2D had higher circulating levels of heat shock protein 70 (HSP70; SMD: 2.30, 95% CI 1.13–3.46; p < 0.001) and secretagogin (SMD: 0.60, 95%CI 0.19–1.01; p < 0.001). They also had higher serum levels of peroxiredoxin-1, -2, -4, and -6. Secretagogin inversely correlated with HOMA-IR, yet positively correlated with HOMA-B, HbA1c, and FPG. PRX4 negatively correlated with HbA1c and FPG, while HSP70 positively correlated with HbA1c. In conclusion, six ERS biomarkers are consistently elevated in human T2D and correlate with glycemic control, insulin resistance, and β-cell function. Emerging evidence links serum ERS biomarkers to diabetes complications, but further research should evaluate their prognostic implications.

Myopathy, Lactic Acidosis, and Sideroblastic Anemia type 2 (MLASA2) is a rare mitochondrial disorder caused by pathogenic variants (PVs) in the YARS2 gene (which encodes the Mt-TyrRS protein. We performed a comprehensive clinical–molecular synthesis by integrating a systematic review and meta-analysis of all published MLASA2 cases with survival modeling and three-dimensional structural mapping. Across the aggregated cohort, anemia (88.6%), sideroblastic phenotype (85.7%), and lactic acidosis (82.9%) were the most prevalent phenotypes. Fifteen PVs were identified, dominated by p.(Phe52Leu) (29.4%). Survival estimates were 94.1% at 10 years, 70.7% at 30 years, and 42.4% at 50 years; cardiomyopathy and diagnosis before age 10 were associated with decreased survival. We generated the first 3D structural map of all reported Mt-TyrRS PVs, identifying nine spatial hotspots across catalytic, anticodon-binding, and tRNA-binding domains. An integrated framework combining structural density, clinical severity, in silico predictions, and ΔΔG destabilization classified three clusters as High-risk, three as Medium-risk, and three as Low-risk. Among them, cluster 3, a large catalytic hotspot encompassing 44 residues and including nearly half of all MLASA2 cases, showed the strongest pathogenic convergence. This clinical–structural integration provides new insights for a better comprehension of MLASA2, enhancing variant interpretation and improving diagnostic and prognostic precision.

Mitochondrial DNA (mtDNA) variation has traditionally been investigated in the context of human evolution and rare mitochondrial diseases; however, growing evidence suggests that it may also contribute to susceptibility to common metabolic disorders. This review integrates current knowledge of mitochondrial biology, mtDNA genetics, heteroplasmy, and the global distribution of mitochondrial haplogroups to examine their roles in health and disease. In this narrative review, we synthesized English-language studies identified through PubMed, Scopus, and Web of Science from January 1988 to May 2026, prioritizing evidence according to relevance, scientific contribution, recency, and historical significance. We summarize evidence showing how pathogenic variants (PVs) in mtDNA genes impair oxidative phosphorylation (OXPHOS), increase reactive oxygen species (ROS) production, and disrupt cellular bioenergetics, thereby contributing to the multisystem manifestations of mitochondrial diseases. We further discuss population-specific mitochondrial haplogroups and their reported population-specific associations with metabolic phenotypes, including obesity, type 2 diabetes (T2D), and cardiovascular disease (CVD). Finally, we review recent advances in next-generation sequencing technologies and their contributions to the molecular diagnosis of mitochondrial diseases and the characterization of genotype–phenotype relationships. Collectively, current evidence supports a well-established pathogenic role for specific mtDNA variants in primary mitochondrial disorders, whereas the contributions of common polymorphisms and haplogroups to complex metabolic disease remain largely associative and require further replication and functional validation.