Plasma C-peptide and glycated albumin and subsequent risk of cancer: From a large prospective case-cohort study in Japan

A novel antisense lncRNA, ARBAG harboring an RNA destabilizing GWAS variant for C-peptide dictates the transcript isoforms of GABRA6 in cerebellum

Human disease-associated genetic variations often map to long non-coding RNA (lncRNA) genes; however, elucidation of their functional impact is challenging. We previously identified a new genetic variant rs4454083 (A/G) residing in exon of an uncharacterized lncRNA ARBAG that strongly associates with plasma levels of C-peptide, a hormone that regulates insulin bioavailability. On the opposite strand, rs4454083 also corresponds to an intron of a cerebellum-specific GABA receptor subunit gene GABRA6 that mediates strengthening of inhibitory synapses by insulin. Here, we show that alleles of rs4454083 modulate transcript levels of the antisense gene, ARBAG, which then controls the expression of the sense gene, GABRA6. Predisposing to low C-peptide, GG (a minor allele genotype across ethnicities) stabilizes ARBAG lncRNA causing higher transcript levels in cerebellum. ARBAG lncRNA abundance leads to cleavage of GABRA6 mRNA at the complementary region, resulting in a dysfunctional GABRA6 protein that would not be recruited for synapse strengthening. Together, our findings in human cerebellar cell-line and induced Pluripotent Stem Cells (iPSCs) demonstrate biological role of a novel lncRNA in determining the ratio of mRNA isoforms of a protein-coding gene and the ability of an embedded variant in modulating lncRNA stability leading to inter-individual differences in protein expression.

Koyanagi Y, Matsuo K, Mikami H, Kusakabe M, Takeuchi K, Wakai K. Associations of metabolic syndrome and metabolically unhealthy obesity with cancer mortality: The Japan Multi-Institutional Collaborative Cohort (J-MICC) study

Purpose

The association between metabolic syndrome (MetS) and the risk of death from cancer is still a controversial issue. The purpose of this study was to examine the associations of MetS and metabolically unhealthy obesity (MUHO) with cancer mortality in a Japanese population.

Methods

We used data from the Japan Multi-Institutional Collaborative Cohort Study. The study population consisted of 28,554 eligible subjects (14,103 men and 14,451 women) aged 35–69 years. MetS was diagnosed based on the criteria of the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) and the Japan Society for the Study of Obesity (JASSO), using the body mass index instead of waist circumference. The Cox proportional hazards analysis was used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for total cancer mortality in relation to MetS and its components. Additionally, the associations of obesity and the metabolic health status with cancer mortality were examined.

Results

During an average 6.9-year follow-up, there were 192 deaths from cancer. The presence of MetS was significantly correlated with increased total cancer mortality when the JASSO criteria were used (HR = 1.51, 95% CI 1.04–2.21), but not when the NCEP-ATP III criteria were used (HR = 1.09, 95% CI 0.78–1.53). Metabolic risk factors, elevated fasting blood glucose, and MUHO were positively associated with cancer mortality (P <0.05).

Conclusion

MetS diagnosed using the JASSO criteria and MUHO were associated with an increased risk of total cancer mortality in the Japanese population.

Prospective associations of hemoglobin A1c and c-peptide with risk of diabetes-related cancers in the Cancer Prevention Study-II Nutrition Cohort

Self-reported type 2 diabetes mellitus (T2DM) is a risk factor for many cancers, suggesting its pathology relates to carcinogenesis. We conducted a case-cohort study to examine associations of hemoglobin A1c (HbA1c) and c-peptide with cancers associated with self-reported T2DM. This study was drawn from a prospective cohort of 32,383 women and men who provided blood specimens at baseline: c-peptide and HbA1c were assessed in 3,000 randomly selected participants who were cancer-free-at-baseline and an additional 2,281 participants who were cancer-free-at-baseline and subsequently diagnosed with incident colorectal, liver, pancreatic, female breast, endometrial, ovarian, bladder, or kidney cancers. Weighted-Cox regression models estimated hazards ratios (HRs) and 95% confidence intervals (CI), adjusted for covariates. C-peptide was associated with higher risk of liver cancer (per standard deviation (SD) HR: 1.80; 95%CI: 1.32-2.46). HbA1c was associated with higher risk of pancreatic cancer (per SD HR: 1.21 95%CI 1.05-1.40) and with some suggestion of higher risks for all-cancers-of-interest (per SD HR: 1.05; 95%CI: 0.99-1.11) and colorectal (per SD HR: 1.09; 95%CI: 0.98-1.20), ovarian (per SD HR: 1.18; 95%CI 0.96-1.45) and bladder (per SD HR: 1.08; 95%CI 0.96-1.21) cancers. Compared to no self-reported T2DM and HbA1c <6.5% (reference group), self-reported T2DM and HbA1c <6.5% (i.e., T2DM in good glycemic control) was not associated with risk of colorectal cancer, whereas it was associated with higher risks of all-cancers-of-interest combined (HR: 1.28; 95%CI: 1.01-1.62), especially for breast and endometrial cancers. Additional large, prospective studies are needed to further explore the roles of hyperglycemia, hyperinsulinemia, and related metabolic traits with T2DM-associated cancers to better understand the mechanisms underlying the self-reported T2DM-cancer association and to identify persons at higher cancer risk.

Glycated albumin as biomarker: Evidence and its outcomes

Glycemic control markers are important for the diagnosis and treatment of diabetes. Hemoglobin A1c (A1C) is an important marker that is mandatory in routine medical examinations; however, it is well known that it has some limitations. In this review, we focus on the limitation of A1C and introduce a relatively new marker, glycated albumin (GA), which can be used to complement A1C. First, for a better understanding of the characteristics of each marker, we sort the similarities and differences of glycemic control markers as well as the characteristics of each marker. Second, we point out the limitation of A1C, introduce GA as an alternative indicator, and discuss the limitations of GA. Finally, we summarize important evidence regarding the utility of GA. We hope that this review provides useful information that permits more effective usage of GA as well as other glycemic control markers.