Associations between SLC16A11 variants and diabetes in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Epistasis Between HLA-DRB1*16:02:01 and SLC16A11 T-C-G-T-T Reduces Odds for Type 2 Diabetes in Southwest American Indians

We sought to identify genetic/immunologic contributors of type 2 diabetes (T2D) in an indigenous American community by genotyping all study participants for both high-resolution HLA-DRB1 alleles and SLC16A11 to test their risk and/or protection for T2D. These genes were selected based on independent reports that HLA-DRB1*16:02:01 is protective for T2D and that SLC16A11 associates with T2D in individuals with BMI <35 kg/m2. Here, we test the interaction of the two loci with a more complete data set and perform a BMI sensitivity test. We defined the risk protection haplotype of SLC16A11, T-C-G-T-T, as allele 2 of a diallelic genetic model with three genotypes, SLC16A11*11, *12, and *22, where allele 1 is the wild type. Both earlier findings were confirmed. Together in the same logistic model with BMI ≥35 kg/m2, DRB1*16:02:01 remains protective (odds ratio [OR] 0.73), while SLC16A11 switches from risk to protection (OR 0.57 [*22] and 0.78 [*12]); an added interaction term was statistically significant (OR 0.49 [*12]). Bootstrapped (b = 10,000) statistical power of interaction, 0.4801, yielded a mean OR of 0.43. Sensitivity analysis demonstrated that the interaction is significant in the BMI range of 30-41 kg/m2. To investigate the epistasis, we used the primary function of the HLA-DRB1 molecule, peptide binding and presentation, to search the entire array of 15-mer peptides for both the wild-type and ancient human SLC16A11 molecules for a pattern of strong binding that was associated with risk and protection for T2D. Applying computer binding algorithms suggested that the core peptide at SLC16A11 D127G, FSAFASGLL, might be key for moderating risk for T2D with potential implications for type 1 diabetes.

ARTICLE HIGHLIGHTS

Molecular characteristic analysis of single-nucleotide polymorphisms in SLC16A9/hMCT9

AIMS

Human monocarboxylate transporter 9 (hMCT9), encoded by SLC16A9, is a transporter that mediates creatine transport across the transmembrane. Previously, we reported that hMCT9 is an extracellular pH- and Na+-sensitive creatine transporter with two kinetic components. Recently, some variants of hMCT9 have been found to be associated with serum uric acid levels, hyperuricemia, and gout. Among these, two single-nucleotide polymorphisms (SNPs) have also been reported: rs550527563 (L93M) and rs2242206 (T258K). However, the effect of these SNPs on hMCT9 transport activity remains unclear. This study aimed to determine the influence of hMCT9 L93M and T258K on transport characteristics.

MAIN METHODS

hMCT9 L93M and T258K were constructed by site-directed mutagenesis and expressed in Xenopus laevis oocyte. Transport activity of uric acid and creatine via hMCT9 were measured by using a Xenopus laevis oocyte heterologous expression system.

KEY FINDINGS

We assessed the transport activity of uric acid and creatine, and observed that hMCT9-expressing oocytes transported uric acid approximately 3- to 4-fold more than water-injected oocytes. hMCT9 L93M slightly reduced the transport activity of creatine, whereas hMCT9 T258K did not affect the transport activity. Interestingly, hMCT9 T258K abolished Na+ sensitivity and altered the substrate affinity from two components to one.

SIGNIFICANCE

In conclusion, hMCT9 SNPs affect transport activity and characteristics. hMCT9 L93M and T258K may induce dysfunction and contribute to pathologies such as hyperuricemia and gout. This is a first study to evaluate molecular characteristics of hMCT9 SNPs.

Interactions between genetic and lifestyle factors on cardiometabolic disease-related outcomes in Latin American and Caribbean populations: A systematic review

Introduction

The prevalence of cardiometabolic diseases has increased in Latin American and the Caribbean populations (LACP). To identify gene-lifestyle interactions that modify the risk of cardiometabolic diseases in LACP, a systematic search using 11 search engines was conducted up to May 2022.

Methods

Eligible studies were observational and interventional studies in either English, Spanish, or Portuguese. A total of 26,171 publications were screened for title and abstract; of these, 101 potential studies were evaluated for eligibility, and 74 articles were included in this study following full-text screening and risk of bias assessment. The Appraisal tool for Cross-Sectional Studies (AXIS) and the Risk Of Bias In Non-Randomized Studies-of Interventions (ROBINS-I) assessment tool were used to assess the methodological quality and risk of bias of the included studies.

Results

We identified 122 significant interactions between genetic and lifestyle factors on cardiometabolic traits and the vast majority of studies come from Brazil (29), Mexico (15) and Costa Rica (12) with FTO, APOE, and TCF7L2 being the most studied genes. The results of the gene-lifestyle interactions suggest effects which are population-, gender-, and ethnic-specific. Most of the gene-lifestyle interactions were conducted once, necessitating replication to reinforce these results.

Discussion

The findings of this review indicate that 27 out of 33 LACP have not conducted gene-lifestyle interaction studies and only five studies have been undertaken in low-socioeconomic settings. Most of the studies were cross-sectional, indicating a need for longitudinal/prospective studies. Future gene-lifestyle interaction studies will need to replicate primary research of already studied genetic variants to enable comparison, and to explore the interactions between genetic and other lifestyle factors such as those conditioned by socioeconomic factors and the built environment. The protocol has been registered on PROSPERO, number CRD42022308488.

Systematic review registration

https://clinicaltrials.gov, identifier CRD420223 08488.

Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations

Polygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a trait, yet they fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). We address this via a machine learning approach, validated in nine complex phenotypes in a multi-ancestry population. We use an ensemble method of SNP selection followed by gradient boosted trees (XGBoost) to allow for non-linearities and interaction effects. We compare our results to the standard, linear PRS model developed using PRSice, LDpred2, and lassosum2. Combining a PRS as a feature in an XGBoost model results in a relative increase in the percentage variance explained compared to the standard linear PRS model by 22% for height, 27% for HDL cholesterol, 43% for body mass index, 50% for sleep duration, 58% for systolic blood pressure, 64% for total cholesterol, 66% for triglycerides, 77% for LDL cholesterol, and 100% for diastolic blood pressure. Multi-ancestry trained models perform similarly to specific racial/ethnic group trained models and are consistently superior to the standard linear PRS models. This work demonstrates an effective method to account for non-linearities and interaction effects in genetics-based prediction models.

Downregulation of SLC16A11 is Present in Offspring of Mothers with Gestational Diabetes

BACKGROUND

Studies have identified that diseases in pregnancy affect fetal growth and development of the newborn. In Mexican population, the gene SLC16A11 has been identified as a factor that increases the risk of developing type 2 diabetes mellitus. To date, information is scarce about its expression in gestational diabetes mellitus (GDM); epigenetic modifications due to maternal hyperglycemic state could be identified early in fetal development.

PURPOSE

This study aimed to determine the SLC16A11 expression and methylation status in umbilical cord blood of newborns offspring of mothers with or without GDM.

METHODS

Cross-sectional, analytic study. Pregnant patients undergoing caesarean delivery with and without GDM in the Unidad Medica de Alta Especialidad Hospital de Gineco-obstetricia #4 Luis Castelazo Ayala, Instituto Mexicano del Seguro Social, were invited to participate. DNA was extracted from the mothers' blood cells, or umbilical cord blood cells of their newborns, and subjected to methylation status. Total RNA was used to evaluate the SLC16A11 expression by endpoint RT-PCR. Variables were analyzed with Student t. Values of p <0.05 were considered statistically significant.

RESULTS

A SLC16A11 downregulation was observed for newborns, while methylation status was found in only 1 of 68 mother-child pairs. Somatometry of newborns showed no differences between groups. Differences were found in total cholesterol, triglycerides, ALT, glucose, and HbA1c.

CONCLUSIONS

For the first time, a differential expression for SLC16A11 was observed in offspring. Downregulation in this gene expression could characterize the offspring from GDM. No difference was found in somatometry of newborns of mothers with and without GDM.

Deletion of the diabetes candidate gene Slc16a13 in mice attenuates diet-induced ectopic lipid accumulation and insulin resistance

Genome-wide association studies have identified SLC16A13 as a novel susceptibility gene for type 2 diabetes. The SLC16A13 gene encodes SLC16A13/MCT13, a member of the solute carrier 16 family of monocarboxylate transporters. Despite its potential importance to diabetes development, the physiological function of SLC16A13 is unknown. Here, we validate Slc16a13 as a lactate transporter expressed at the plasma membrane and report on the effect of Slc16a13 deletion in a mouse model. We show that Slc16a13 increases mitochondrial respiration in the liver, leading to reduced hepatic lipid accumulation and increased hepatic insulin sensitivity in high-fat diet fed Slc16a13 knockout mice. We propose a mechanism for improved hepatic insulin sensitivity in the context of Slc16a13 deficiency in which reduced intrahepatocellular lactate availability drives increased AMPK activation and increased mitochondrial respiration, while reducing hepatic lipid content. Slc16a13 deficiency thereby attenuates hepatic diacylglycerol-PKCε mediated insulin resistance in obese mice. Together, these data suggest that SLC16A13 is a potential target for the treatment of type 2 diabetes and non-alcoholic fatty liver disease.

Genetic variants in the SLC16A11 gene are associated with increased BMI and insulin levels in nondiabetic Chilean population

Objective

To study the association of SLC16A11 gene variants with obesity and metabolic markers in nondiabetic Chilean adults.

Methods

This cross-sectional study included 263 non-diabetic adults. The genotype of the rs75493593 polymorphism of SLC16A11 gene was performed by real-time PCR. It's association with adiposity markers (body weight, BMI, waist circumference and fat mass percentage), metabolic markers (glucose, insulin, HOMA_IR, leptin, total cholesterol, LDLc, HDLc, triglycerides, ALT, GGT and hsCRP) and blood pressure was analyzed by linear regression.

Results

The minor allele (T) of the SLC16A11 gene (rs75493593) has a frequency of 29.7% among Chileans. Risk genotypes (GT and TT) were associated with a significant 1.49 mU/l increase in plasmatic insulin for each copy of the minor allele (95% CI: 0.12, 2.87, p < 0.05). This association remained significant after adjusting for socio-demographic variables, physical activity and smoking (1.36 mU/l, 95% CI: 0.16, 2.58 p < 0.05), but was lost when BMI was included as a confounding factor. Higher BMI was also significantly associated with polymorphic genotypes in SLC16A11, independent of socio-demographic variables.

Conclusion

The minor allele of the SLC16A11 gene (T) is highly prevalent among Chileans and is associated with increased insulin and BMI in nondiabetic individuals. These findings suggest that the genetic variant in SLC16A11 is not only associated with type 2 diabetes as previously shown in Mexicans, but is also related to early metabolic alterations in healthy subjects that may lead to type 2 diabetes.

Solute Carrier Transporters as Potential Targets for the Treatment of Metabolic Disease

The solute carrier (SLC) superfamily comprises more than 400 transport proteins mediating the influx and efflux of substances such as ions, nucleotides, and sugars across biological membranes. Over 80 SLC transporters have been linked to human diseases, including obesity and type 2 diabetes (T2D). This observation highlights the importance of SLCs for human (patho)physiology. Yet, only a small number of SLC proteins are validated drug targets. The most recent drug class approved for the treatment of T2D targets sodium-glucose cotransporter 2, product of the SLC5A2 gene. There is great interest in identifying other SLC transporters as potential targets for the treatment of metabolic diseases. Finding better treatments will prove essential in future years, given the enormous personal and socioeconomic burden posed by more than 500 million patients with T2D by 2040 worldwide. In this review, we summarize the evidence for SLC transporters as target structures in metabolic disease. To this end, we identified SLC13A5/sodium-coupled citrate transporter, and recent proof-of-concept studies confirm its therapeutic potential in T2D and nonalcoholic fatty liver disease. Further SLC transporters were linked in multiple genome-wide association studies to T2D or related metabolic disorders. In addition to presenting better-characterized potential therapeutic targets, we discuss the likely unnoticed link between other SLC transporters and metabolic disease. Recognition of their potential may promote research on these proteins for future medical management of human metabolic diseases such as obesity, fatty liver disease, and T2D. SIGNIFICANCE STATEMENT: Given the fact that the prevalence of human metabolic diseases such as obesity and type 2 diabetes has dramatically risen, pharmacological intervention will be a key future approach to managing their burden and reducing mortality. In this review, we present the evidence for solute carrier (SLC) genes associated with human metabolic diseases and discuss the potential of SLC transporters as therapeutic target structures.