Several studies have identified nearly 40 different type 2 diabetes susceptibility loci, mainly in European populations, but few of them have been evaluated in the Mexican population. The aim of this study was to examine the extent to which 24 common genetic variants previously associated with type 2 diabetes are associated in Mexican Mestizos. Twenty-four single nucleotide polymorphisms (SNPs) in or near genes (KCNJ11, PPARG, TCF7L2, SLC30A8, HHEX, CDKN2A/2B, CDKAL1, IGF2BP2, ARHGEF11, JAZF1, CDC123/CAMK1D, FTO, TSPAN8/LGR5, KCNQ1, THADA, ADAMTS9, NOTCH2, NXPH1, RORA, UBQLNL, and RALGPS2) were genotyped in Mexican Mestizos. A case-control association study comprising 1,027 type 2 diabetic individuals and 990 control individuals was conducted. To account for population stratification, a panel of 104 ancestry-informative markers was analyzed. Association to type 2 diabetes was found for rs13266634 (SLC30A8), rs7923837 (HHEX), rs10811661 (CDKN2A/2B), rs4402960 (IGF2BP2), rs12779790 (CDC123/CAMK1D), and rs2237892 (KCNQ1). In addition, rs7754840 (CDKAL1) was associated in the nonobese type 2 diabetic subgroup, and for rs7903146 (TCF7L2), association was observed for early-onset type 2 diabetes. Lack of association for the rest of the variants may have resulted from insufficient power to detect smaller allele effects.

Epidemiological and physiological similarities among Gestational Diabetes Mellitus (GDM) and Type 2 Diabetes (T2D) suggest that both diseases, share a common genetic background. T2D risk variants have been associated to GDM susceptibility. However, the genetic architecture of GDM is not yet completely understood. We analyzed 176 SNPs for 115 loci previously associated to T2D, GDM and body mass index (BMI), as well as a set of 118 Ancestry Informative Markers (AIMs), in 750 pregnant Mexican women. Association with GDM was found for two of the most frequently replicated T2D loci: a TCF7L2 haplotype (CTTC: rs7901695, rs4506565, rs7903146, rs12243326; P=2.16x10^-06; OR=2.95) and a KCNQ1 haplotype (TTT: rs2237892, rs163184, rs2237897; P=1.98x10^-05; OR=0.55). In addition, we found two loci associated to glycemic traits: CENTD2 (60’ OGTT glycemia: rs1552224, P=0.03727) and MTNR1B (HOMA B: rs1387153, P=0.05358). Remarkably, a major susceptibility SLC16A11 locus for T2D in Mexicans was not shown to play a role in GDM risk. The fact that two of the main T2D associated loci also contribute to the risk of developing GDM in Mexicans, confirm that both diseases share a common genetic background. However, lack of association with a Native American contribution T2D risk haplotype, SLC16A11, suggests that other genetic mechanisms may be in play for GDM.

Type 2 diabetes mellitus (T2D) is a leading cause of morbidity and mortality in Mexico. Here, we aimed to report incidence rates (IR) of type 2 diabetes in middle-aged apparently-healthy Mexican adults, identify risk factors associated to ID and develop a predictive model for ID in a high-risk population. Prospective 3-year observational cohort, comprised of apparently-healthy adults from urban settings of central Mexico in whom demographic, anthropometric and biochemical data was collected. We evaluated risk factors for ID using Cox proportional hazard regression and developed predictive models for ID. We included 7636 participants of whom 6144 completed follow-up. We observed 331 ID cases (IR: 21.9 per 1000 person-years, 95%CI 21.37–22.47). Risk factors for ID included family history of diabetes, age, abdominal obesity, waist-height ratio, impaired fasting glucose (IFG), HOMA2-IR and metabolic syndrome. Early-onset ID was also high (IR 14.77 per 1000 person-years, 95%CI 14.21–15.35), and risk factors included HOMA-IR and IFG. Our ID predictive model included age, hypertriglyceridemia, IFG, hypertension and abdominal obesity as predictors (Dxy = 0.487, c-statistic = 0.741) and had higher predictive accuracy compared to FINDRISC and Cambridge risk scores. ID in apparently healthy middle-aged Mexican adults is currently at an alarming rate. The constructed models can be implemented to predict diabetes risk and represent the largest prospective effort for the study metabolic diseases in Latin-American population.

High serum triglyceride (TG) levels is an established risk factor for coronary heart disease (CHD). Fat is stored in the form of TGs in human adipose tissue. We hypothesized that gene co-expression networks in human adipose tissue may be correlated with serum TG levels and help reveal novel genes involved in TG regulation. Gene co-expression networks were constructed from two Finnish and one Mexican study sample using the blockwiseModules R function in Weighted Gene Co-expression Network Analysis (WGCNA). Overlap between TG-associated networks from each of the three study samples were calculated using a Fisher’s Exact test. Gene ontology was used to determine known pathways enriched in each TG-associated network. We measured gene expression in adipose samples from two Finnish and one Mexican study sample. In each study sample, we observed a gene co-expression network that was significantly associated with serum TG levels. The TG modules observed in Finns and Mexicans significantly overlapped and shared 34 genes. Seven of the 34 genes (ARHGAP30, CCR1, CXCL16, FERMT3, HCST, RNASET2, SELPG) were identified as the key hub genes of all three TG modules. Furthermore, two of the 34 genes (ARHGAP9, LST1) reside in previous TG GWAS regions, suggesting them as the regional candidates underlying the GWAS signals. This study presents a novel adipose gene co-expression network with 34 genes significantly correlated with serum TG across populations.

Summary: Infections can lead to persistent or long-term symptoms and diseases such as shingles after varicella zoster, cancers after human papillomavirus, or rheumatic fever after streptococcal infections ^{1, 2} . Similarly, infection by SARS-CoV-2 can result in Long COVID, a condition characterized by symptoms of fatigue and pulmonary and cognitive dysfunction ^3–5 . The biological mechanisms that contribute to the development of Long COVID remain to be clarified. We leveraged the COVID-19 Host Genetics Initiative ^{6, 7} to perform a genome-wide association study for Long COVID including up to 6,450 Long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We identified the first genome-wide significant association for Long COVID at the FOXP4 locus. FOXP4 has been previously associated with COVID-19 severity ⁶ , lung function ⁸ , and cancers ⁹ , suggesting a broader role for lung function in the pathophysiology of Long COVID. While we identify COVID-19 severity as a causal risk factor for Long COVID, the impact of the genetic risk factor located in the FOXP4 locus could not be solely explained by its association to severe COVID-19. Our findings further support the role of pulmonary dysfunction and COVID-19 severity in the development of Long COVID.