Unlocking the genetic code for blood sugar reveals new risks for diabetes and lung problems

A recent study published in the journal Natural genetics performed a genome-wide association study (GWAS) meta-analysis of random glucose (RG).

Genetic factors are determinants of glucose homeostasis and susceptibility to type 2 diabetes (T2D). GWAS of glycemic traits in non-diabetic individuals have shown predictors of insulin, glucose, and other responses after glucose challenge tests or during fasting. However, glucose control involves responses to a variety of stimuli that have been omitted from these studies.

In research and clinical practice, blood glucose is often measured at different times throughout the day. Although intrinsically more variable than standard measures, the study team reasoned that the RG would broadly represent the complex processes of glucose regulation in organ systems across the board.

Study: A randomized GWAS of glucose in 476,326 individuals provides insight into the pathophysiology of diabetes, complications and treatment stratification. Tatiana Shepeleva / Shutterstock

Review and results

In the present study, researchers performed a GWAS meta-analysis of RG in 476,326 non-diabetic subjects of European and other ancestries. Analyzes were adjusted for sex, age, and time since last meal. Individuals with diabetes or hyperglycemia were excluded. Covariates were selected after phenotype modeling.

The team identified 150 different traits through a conditional analysis of genome-wide significance within 120 loci. Of these, 53 indicators were first described in glycemic indicators. The various symbols identified in European ancestry had common meanings for people of other ancestries. The team observed an overlap of two-thirds of the RG traits with loci associated with T2D.

Notably, sex dimorphism was found at 13 RG loci. Lead variants in the three FG loci previously described (associated thyroid adenoma [THADA]Ras response element binding 1 [RREB1]and Tet methylcytosine dioxygenase 2 [TET2]) and two new RG loci (N-myristolytransferase 1 [NMT1] and control factor X1 [RFX1]) were common coding variants (the minor allele frequently [MAF] ≥ 5%).

Besides, RG-related single nucleotide polymorphisms (SNPs) in other three loci (endoplasmic reticulum degradation enhances α-mannosidase like protein 3 [EDEM3]neuronal differentiation 1 [NEUROD1]and glucagon-like peptide 1 receptor [GLP1R]) were a variety of low codes (MAF – 1% to <5%). In addition, 30 RG loci were identified in the rare frequency range (MAF - 0.001% to < 1%).

After that, the team put forward GLP1R, a therapeutic target for T2D, a functional analysis. RG data were used to validate the experimental framework for predicting responses to GLP-1R agonists. Functional impact of a lead missense variant at rs10305492 (A316T) in GLP1R which had a powerful effect of reducing RG and 16 one GLP1R coding variants were assessed by measuring the recruitment of GLP-1-induced small G proteins in cells expressing wild-type or variant GLP-1R.

The researchers noted that the mini-G_s A functional link was the prediction of the RG effect of the variant, combining the experimentally determined function of GLP-1R in blood homeostasis. In addition, a corresponding functional analysis was performed to identify other types of tissues and cells with an etiological role in glucose metabolism.

The colon, ileum, cartilage, adrenal glands, pancreas, and adrenal cortex were highlighted by data analysis performed by advanced integration of complex symptoms (DEPICT) analysis. Similarly, the cell type expression-specific integration for complex traits (CELLECT) analysis highlighted pancreatic cell types and intestinal tissue. Chapters RG are especially associated with an enriched expression in the cells of the pancreatic polypeptide, which surpasses the β cells of insulin that are normally involved.

The researchers tested the overlap between the traits identified in the current analysis and those from a large GWAS on the gut microbiome. They identify two levels (Collinsella and Lachnospiraceae–FCS020) sharing signals with RG at the same location (ABO-FUT2), its effects on the RG can be mixed with the abundance of these genes, producing glucose from galactose and lactose. This multi-omics analysis has shown extensive evidence of a relationship between RG variants and gut health.

Finally, the researchers evaluated the correlation of the RG gene with other phenotypes to estimate the shared genetic contribution using a linkage-disequilibrium (LD) regression analysis. There was a positive correlation of the RG gene with squamous cell lung cancer and lung cancer and a negative correlation with lung function-related characteristics, such as forced expiratory volume in one second (FEV1) and forced vital capacity (FVC).

Bidirectional Mendelian randomization (MR) showed a causal effect of T2D and RG on lung function but not vice versa. A sedentary lifestyle and smoking reduce lung function, independent of the effects of T2D and RG. Multivariable MR showed that the effects of T2D and RG on FVC were independent of screen time and smoking per day. These data confirmed the causal effect of glycemic dysregulation on lung function as a new complication of diabetes.

Conclusions

In total, the study showed 44 additional loci associated with glycemic symptoms. The active nature of GLP1R coding variation confirmed its role in blood sugar regulation. The analysis found mediators below glycemic control, emphasizing the role of the intestine. The causal effect of RG and T2D on lung function was demonstrated by MR. The results highlight the use of current methods to confirm findings from observational studies and promote chronic lung dysfunction as a new complication of diabetes.