Frequency of Insulin Resistance in People with Thyroid Dysfunction

Background: Thyroid dysfunction is an endocrine disorder with a recognized association with type 2 diabetes mellitus. Thyroid hormones have a remarkable effect on glucose metabolism and can cause insulin resistance (IR). This study was aimed at assessing the relationship between IR and thyroid dysfunction. Methods: This case–control study was conducted at the endocrinology outpatient clinics of Ibrahim Malik Hospital and Omdurman Military Hospital in Khartoum State, Sudan between May 2018 and January 2019. Fasting blood glucose (FBG), fasting insulin level, and thyroid function test (TFT) were measured for each candidate and IR was estimated using the HOMA-IR equation. Results: Thirty-one patients with thyroid dysfunction and fifty-seven control participants were enrolled. The highest mean FBG was found among cases (105.3 ± 15.7 mg/dl) compared to the controls (97 ± 12.1 mg/dl), but the difference was not statistically significant (P-value = 0.598). The mean fasting insulin level was 9.22 ± 4 IU/ml in the cases and 9.4 ± 4.2 IU/ml in controls, without a significant difference (P-value = 0.681). The highest HOMA-IR score was found among cases (2.4 ± 1.2). It was 2.4 ± 1.3 in hyperthyroidism, 2.3 ± 1.1 in hypothyroidism, and 2.4 ± 1.2 in controls, and the difference was insignificant (P-value = 0.859). IR was higher in the cases (58.1%) compared to the controls (52.6%) but again not statistically significant (P-value = 0.396). Among cases, IR was encountered in 61.9% and 50% of hyperthyroid and hypothyroid patients, respectively. Conclusion: Patients with thyroid dysfunction have some level of IR that was not statistically significant when compared with controls.

Effect of dietary fat intake and genetic risk on glucose and insulin-related traits in Brazilian young adults

Purpose The development of metabolic diseases such as type 2 diabetes (T2D) is closely linked to a complex interplay between genetic and dietary factors. The prevalence of abdominal obesity, hyperinsulinemia, dyslipidaemia, and high blood pressure among Brazilian adolescents is increasing and hence, early lifestyle interventions targeting these factors might be an effective strategy to prevent or slow the progression of T2D. Methods We aimed to assess the interaction between dietary and genetic factors on metabolic disease-related traits in 200 healthy Brazilian young adults. Dietary intake was assessed using 3-day food records. Ten metabolic disease-related single nucleotide polymorphisms (SNPs) were used to construct a metabolic-genetic risk score (metabolic-GRS). Results We found significant interactions between the metabolic-GRS and total fat intake on fasting insulin level (Pinteraction = 0.017), insulin-glucose ratio (Pinteraction = 0.010) and HOMA-B (Pinteraction = 0.002), respectively, in addition to a borderline GRS-fat intake interaction on HOMA-IR (Pinteraction = 0.051). Within the high-fat intake category [37.98 ± 3.39% of total energy intake (TEI)], individuals with ≥ 5 risk alleles had increased fasting insulin level (P = 0.021), insulin-glucose ratio (P = 0.010), HOMA-B (P = 0.001) and HOMA-IR (P = 0.053) than those with < 5 risk alleles. Conclusion Our study has demonstrated a novel GRS-fat intake interaction in young Brazilian adults, where individuals with higher genetic risk and fat intake had increased glucose and insulin-related traits than those with lower genetic risk. Large intervention and follow-up studies with an objective assessment of dietary factors are needed to confirm our findings.

Fasting Insulin and Risk of Cancer Related Mortality in Non-diabetic Adults: A Dose-response Meta-analysis of Cohort Studies

Background: Insulin is known to have direct and indirect effects on cell cycle progression, proliferation and metastatic activities. We performed a dose-response meta-analysis to investigate the association between hyperinsulinemia and all-cause cancer related mortality. Methods: A systematic literature search was conducted on MEDLINE and SCOPUS databases to include all published articles up to January 2019. Combined hazard ratios (HRs) with 95% Confidence Intervals (CIs) were estimated using DerSimonian and Laird random-effects models. A dose-response analysis was also conducted to further explore insulin’s relationship with cancer-related mortality. Results: We identified seven studies, with a total of 23,990 participants, who reported the association between hyperinsulinemia and cancer-related mortality. Results from the eligible studies indicated that higher fasting insulin levels were not associated with an increased risk of cancer mortality (pooled HR: 1.14, 95% CI: 0.99-1.32), however, significant heterogeneity was present (I2 = 60.3%, P heterogeneity = 0.001). A subgroup analysis based on gender demonstrated a significant association between fasting insulin level and cancer mortality in men (pooled HR: 1.92, 95% CI: 1.23-3.01, P heterogeneity = 0.281). Conclusion: This dose-response meta-analysis showed a direct significant association between fasting insulin level and cancer mortality in men.

Fasting Insulin Level Changes after Large Volume Liposuction

Background Obesity is a disabling disease which has gained greater attention worldwide. It significantly increases the risk for other diseases such as insulin independent diabetes mellitus also known as diabetes type 2. The most common surgical procedure for obesity is liposuction. It is traditionally performed either as small-volume liposuction or large-volume liposuction. Aim of the Work to spot the light on the effect of large volume liposuction on fasting insulin level changes after 3 months postoperative and to find if LVL may obtain any improvement in metabolic variables. This study will provide the clinician with a more valid basis on which to advise patients undergoing body-contouring procedures, particularly to ensure realistic expectations regarding the effects of body-reshaping procedures on general health. Patients and Mehtods This is prospective study was conducted on a total of 15 overweight and obese (BMI 26–35 kg/m2) premenopausal women (age 21–40years). All subjects were at their maximum body weight and weight stable for at least 3 months. The study took place at Ain Shams University Hospitals and other authorized hospitals under supervision of thesis supervisors studying fasting insulin changes after 3 months following large volume liposuction. Results The present study demonstrates that large-volume abdominal liposuction should, by itself, be considered a clinical therapy for obesity and its metabolic sequelae. Aspiration of large amounts of subcutaneous abdominal fat in women with abdominal obesity, besides having cosmetic benefits, does significantly improve fasting insulin levels. Therefore, the procedure is safe and could successfully help obese subjects to reduce their potential metabolic risks. Conclusion The analysis of the study suggests that plastic surgery could play a role in metabolism. The surgical removal of fat is not detrimental with regard to variation of metabolic indices.

The Association between Habitual Sleep Duration and Sleep Quality with Glycemic Traits: Assessment by Cross-Sectional and Mendelian Randomization Analyses

Evidence on whether habitual sleep duration and sleep quality are associated with increased insulin resistance is inconsistent. Here, we investigated the associations between different measures of habitual sleep with glycemic traits through cross-sectional and Mendelian randomization (MR) analyses. We assessed the associations of sleep duration and sleep quality with glycemic traits using multivariable linear regression models adjusted for potential confounders in 4672 middle-aged (45–65 years; 48% men) nondiabetic participants of the Netherlands Epidemiology of Obesity (NEO) study. Genetic variants for total, short, and long sleep duration were used as instrumental variables in MR analyses using summary-level data of glycemic traits in nondiabetic individuals (MAGIC; n = 58,074). In cross-sectional analyses, shortest sleepers (median 5.0 h of sleep per night) had 14.5% (95% confidence interval (CI): 2.0; 28.6%) higher fasting insulin level and 16.3% (95% CI: 2.7; 31.7%) higher HOMA-β. Bad sleep quality was associated with higher insulin resistance (e.g., 14.3% (95% CI: 4.7; 24.9%) higher HOMA-IR). All these associations disappeared after adjustment for BMI and the risk of sleep apnea. MR analyses did not indicate a causal association between total, short or long sleep duration and glycemic traits. Therefore, our used measures of habitual sleep duration and sleep quality are unlikely to directly associate with insulin resistance.

Prediabetes and serum insulin levels

Prediabetes remains a diagnostic dilemma. It refers to impaired glycaemic values without reaching the threshold for diagnosing diabetes mellitus. Prediabetes is an important risk factor for the development of diabetes mellitus, and it constitutes the stage during which microvascular and macrovascular complications are initiated. Early and accurate identification of this stage is the gold standard for prevention of diabetes and its consequences. Despite the multiplicity of diagnostic tests proposed for identification of this condition, a reliable test remains elusive. This article aims at reviewing the different available tests for diagnosis of prediabetes states with a focus on serum insulin levels. Insulin plays a major role in the pathophysiology and development of prediabetes. Different mechanisms of insulin resistance and insulin secretion are established in different subtypes of prediabetes. Therefore, fasting insulin level seems to be a reliable and promising tool for diagnosis and management of prediabetes.