Plasma insulin, C‐peptide and blood glucose and the risk of gastric cancer: The Japan Public Health Center‐based prospective study

Abstract

To date, the association between diabetes mellitus (DM) and gastric cancer has been controversial, including the underlying mechanism. We investigated the association between plasma diabetic biomarkers (insulin, C-peptide, and blood glucose) and gastric cancer risk. In addition, homeostasis model assessment of insulin resistance (HOMA-IR) and homeostasis model assessment of b-cell function (HOMA-b) were calculated. A total of 36,745 subjects aged 40-69 years in the Japan Public Health Center-based prospective study (JPHC) who returned the baseline questionnaire and provided blood samples were followed from 1990 to 2004. In the present analysis, 477 cases and 477 matched controls were used. The odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) for developing gastric cancer were calculated using conditional logistic regression models. Plasma insulin was positively associated with increased risk of gastric cancer; compared to tertile 1, ORs were 1.69 (95% CI 5 1.11-2.59) and 2.01 (1.19-3.38) for tertiles 2 and 3, respectively (p for trend 5 0.009). In men, Cpeptide was also positively associated with a significant risk; corresponding ORs were 1.42 (0.85-2.38) and 1.91 (1.03-3.54), respectively (p for trend 5 0.04). These findings were confirmed for blood samples from the fasting group (8 hr after a meal). Higher HOMA-IR was also associated with increased risk, whereas no association was observed for blood glucose. Our findings suggest that Japanese population with higher insulin and C-peptide levels derived from insulin resistance have an elevated risk of gastric cancer.Gastric cancer is the second leading cause of death and the fourth most common cancer in the world. 1 Although Helicobacter pylori (H. pylori) infection is well known as a major risk factor for gastric cancer, only some of the people infected with H. pylori will develop gastric cancer. Therefore, other risk factors might affect the association between H. pylori and gastric cancer occurrence.Diabetes mellitus (DM) is associated with many types of cancer, including colorectal, liver, breast, and pancreatic cancer.2 However, the association between DM and gastric cancer remains to be clarified. Some prospective studies reported that DM determined by questionnaire or medical records is positively associated with gastric cancer, 3-6 but others found a null association.7-12 However, DM can be easily misclassified when based on self-report of disease in questionnaire survey or medical records. To overcome this problem, several studies were directly based on diabetic biomarkers, such as hemoglobin A1c (HbA1c) and blood glucose, but the associations were also inconsistent in these prospective studies. [13][14][15][16]

Diabetic biomarkers and the risk of proximal or distal gastric cancer

“…Hyperinsulinemia and/or hyperglycemia because of insulin resistance (IR) are important components to the biological mechanisms underlying the association between diabetes and cancer . However, the results of prospective studies conducted in Korea and Japan remained heterogeneous despite the measurement of diabetic biomarkers such as serum insulin, glucose, C‐peptide, and hemoglobin A1c (HbA1c) …”

Inhibition of N-methyl-N-nitrosourea-induced gastric tumorigenesis by Liuwei Dihuang Pill in db/db mice

“…Hyperinsulinemia is the most prominent feature of type 2 diabetes, as a result of insulin resistance. The high level of insulin is a risk of gastric cancer for promotion of cell proliferation[3]. This possibility is supported by a study in mice, in which hyperinsulinemia promoted gastric tumor growth in diet-induced obesity[25].…”

“…However, hyperinsulinemia and insulin-like growth factor (IGF) may play a central role in the promotion of tumorigenesis. A large Japanese case-control study has demonstrated that hyperinsulinemia and serum C peptide are positively correlated with increased risk of gastric cancer[3]. A high level of insulin increases the bioavailability of serum IGF-1.…”

Privacy-Preserving Outsourced Calculation on Floating Point Numbers

“…In the e-heathcare cloud example, some decision making model can be used to automatically check a patients' health status. The parameters of the decision making model frequently contain real numbers (e.g., the probability used in the naïve Bayes model [8]), so do the outsourced personal health data (e. g., blood glucose, insulin, and C-peptide levels are often constructed as non-integer, see the recent study involving 36,745 subjects aged 4069 years in the Japan Public Health Center-based prospective study [9]). However, cryptosystems are generally designed to protect only integer values and computations on integers affect the accuracy of data and decision making results, and even may lead to wrong diagnosis of a patient's illness.…”

“…Step-3 can be parallel executed which only takes one round communication 9. Note that x · y = x × y (defined in Section V-A).…”