Impaired pancreatic beta-cell function after a single dose of oral iron: A before-and-after (pre-post) study.

BACKGROUND: Although in vitro and animal studies have shown that iron loading in pancreatic beta cells impairs insulin secretion, no human studies have documented the acute effects of oral iron on beta-cell insulin secretory capacity. In the present study, we determined beta-cell insulin secretory capacity at baseline and after a single oral dose of iron (ferrous sulphate, 120 mg elemental iron) in healthy male individuals. METHODS: Fifteen healthy male volunteers underwent an oral glucose tolerance test (OGTT) to document baseline glucose tolerance and insulin secretion kinetics (baseline OGTT). One week later, the same subjects underwent a second OGTT, 2 h after an oral dose of ferrous sulphate (120 mg of elemental iron) (post-iron OGTT). Changes in disposition index, insulin secretion kinetics, glucose tolerance, insulin resistance, insulin clearance and iron-related parameters in serum were determined. RESULTS: Compared to baseline OGTT, the areas under the curve (AUC) for serum iron and transferrin saturation increased by 125% and 118%, respectively, in the post-iron OGTT. The disposition index decreased by 20% (p = 0.009) and the AUC for glucose concentrations increased by 5.7% (p < 0.001) during the post-iron OGTT. The insulin secretion rate was marginally lower during the first hour (-3.5%, p = 0.63), but became significantly higher during the second hour (22%, p = 0.005) of the post-iron OGTT. Insulin resistance and insulin clearance rate were not affected by iron intake. CONCLUSIONS: The decrease in disposition index and glucose tolerance observed after the oral dose of iron points to an acute iron-induced impairment in pancreatic beta-cell insulin secretory capacity.

Association of dietary patterns and health outcomes by spatial regression analysis of nationally representative survey data from India.

Background: Our aim was to study the regional differences in dietary patterns in India and their association with population-level nutrition-related health indicators such as the prevalence of anemia, overweight, undernutrition, and hyperglycemia. Objectives: To identify and characterize the dietary patterns from publicly available nationally representative survey data on food consumption conducted by the National Sample Survey Office (NSSO) to study the regional differences in dietary patterns. Methods: Dietary patterns were identified by factor analysis of per capita food consumption data from the household consumer expenditure survey (2011). Mean factor scores of dietary patterns were calculated for each district separately for urban and rural regions. Ecological association of factor scores with the district-level percentage prevalence of health indicators from the National Family Health Survey-4 (2015-2016) data was done by the Spatial Durbin Model of spatial regression analysis. Results: Factor analyses revealed four dietary patterns which were similar in terms of the food items that characterized the factors for both rural and urban regions. Direct effects of dietary patterns by spatial regression analyses were observed with several health outcomes after adjusting for differences in socioeconomic development. Prevalence of anemia was positively associated with "Milk and wheat-rich diet" among men in the rural regions but negatively associated with other dietary patterns. Prevalence of overweight and high blood glucose was positively associated with "Rice and meat-rich diet" and "Coconut and seafood rich diet" in the rural regions. "Refined oil and tur dal-rich diet" was positively associated with the prevalence of overweight and hypertension in urban regions and negatively associated with underweight and anemia in men in rural and urban regions. Conclusions: Spatial regression analyses revealed several important associations between dietary patterns and health outcomes, mostly in rural regions and some in urban regions. These results suggest the role of the major food items consumed in different regions and their impact on health outcomes in India and may have implications in tailoring dietary modifications accordingly.

Maturity onset diabetes of the young in India - a distinctive mutation pattern identified through targeted next-generation sequencing.

OBJECTIVE: To establish and utilize a Next-Generation Sequencing (NGS)-based strategy to screen for maturity onset diabetes of the young (MODY) gene mutations in subjects with early-onset diabetes. PATIENTS AND METHODS: Maturity onset diabetes of the young (MODY) genetic testing was carried out in 80 subjects of Asian Indian origin with young onset diabetes to identify mutations in a comprehensive panel of ten MODY genes. A novel multiplex polymerase chain reaction (PCR)-based target enrichment was established, followed by NGS on the Ion Torrent Personal Genome Machine (PGM). All the mutations and rare variants were confirmed by Sanger sequencing. RESULTS: We identified mutations in 11 (19%) of the 56 clinically diagnosed MODY subjects and seven of these mutations were novel. The identified mutations include p.H241Q, p.E59Q, c.-162G>A 5' UTR in NEUROD1, p.V169I cosegregating with c.493-4G>A and c.493-20C>T, p.E271K in HNF4A, p.A501S in HNF1A, p.E440X in GCK, p.V177M in PDX1, p.L92F in HNF1B and p.R31L in PAX4 genes. Interestingly, two patients with NEUROD1 mutation were also positive for the p.E224K mutation in PDX1 gene. These patients with coexisting NEUROD1-PDX1 mutations showed a marked reduction in glucose-induced insulin secretion. All 24 subjects who had not met the clinical criteria of MODY were negative for the mutations. To the best of our knowledge, this is the first report of PDX1, HNF1B, NEUROD1 and PAX4 mutations from India. CONCLUSIONS: Multiplex PCR coupled with NGS provides a rapid, cost-effective and accurate method for comprehensive parallelized genetic testing of MODY. When compared to earlier reports, we have identified a higher frequency and a novel digenic mutation pattern involving NEUROD1 and PDX1 genes.

Genetic predisposition and high exposure to colistin in the early treatment period as independent risk factors for colistin-induced nephrotoxicity.

Colistin is known to cause nephrotoxicity due to its extensive reabsorption and accumulation in renal tubules. In vitro studies have identified the functional role of colistin transporters such as OCTN2, PEPT2, megalin, and P-glycoprotein. However, the role of these transporter gene variants in colistin-induced nephrotoxicity has not been studied. Utilizing targeted next-generation sequencing, we screened for genetic polymorphisms covering the colistin transporters (SLC15A1, SLC15A2, SLC22A5, LRP2, and ABCB1) in 42 critically ill patients who received colistimethate sodium. The genetic variants rs2257212 ((NM_021082.4):c.1048C>G) and rs13397109 ((NM_004525.3):C.7626C > T) were identified as being associated with an increased incidence of acute kidney injury (AKI) on Day 7. Colistin area under the curve (AUC) was predicted using a previously published pharmacokinetic model of colistin. Using logistic regression analysis, the predicted 24-h AUC of colistin was identified as an important contributor for increased odds of AKI on Day 7. Among 42 patients, 4 (9.5%) were identified as having high predisposition to colistin-induced AKI based on the presence of predisposing genetic variants. Determination of the presence of the abovementioned genetic variants and early therapeutic drug monitoring may reduce or prevent colistin-induced nephrotoxicity and facilitate dose optimization of colistimethate sodium.

Transmission Dynamics of COVID-19 and Utility of Contact Tracing in Risk Assessment of Health-Care Worker Exposure during COVID-19 Pandemic.

Background: In the COVID-19 pandemic, the frontline health-care workers (HCWs) are at increased risk of acquiring infection either through household or workplace exposure. Objectives: To assess the risk of acquiring infection after COVID-19 exposure, we evaluated the effectiveness of a contact tracing assessment to identify the high-risk contacts. Materials and Methods: All HCW who tested COVID-19 positive in July 2020 were interviewed to do risk assessment based on their exposure, advised quarantine, and then followed up on day 14 for development of symptoms of COVID-19. Results: Contact tracing identified 2569 HCW contacts for 422 index positive cases, among which 1642 (63.9%) were contactable for follow-up. Among 1642 contacts, 12.97% developed COVID-19 symptoms within 14 days of the exposure. Household contacts comprising (142 out of 956, 14.9%) had a higher risk of becoming symptomatic than workplace contacts (71 out of 686, 10.3%) ([odds ratio 0.66 (confidence interval 0.49-0.89)]. Of these, 76.6% of the household exposure and 55.4% of significant workplace exposure were tested positive for COVID-19. Conclusions: Based on the risk assessment, we found that a HCW is likely to acquire infection at home rather than at the workplace, and hence, an appropriate quarantine policy can help decrease the transmission and mitigate staff shortage.

Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS).

OBJECTIVES: Geographical Information Surveillance (GIS) is an advanced digital technology tool that maps location-based data and helps in epidemiological modeling. We applied GIS to analyze patterns of spread and hotspots of COVID-19 cases in the Vellore district in South India. METHODS: Laboratory-confirmed COVID-19 cases from the Vellore district and neighboring taluks from March 2020 to June 2021 were geocoded and spatial maps were generated. Time trends exploring urban-rural burden with an age-sex distribution of cases and other variables were correlated with outcomes. RESULTS: A total of 45,401 cases of COVID-19 were detected, with 20,730 cases during the first wave and 24,671 cases during the second wave. The overall incidence rates of COVID-19 were 462.8 and 588.6 per 100,000 population during the first and second waves, respectively. The spread pattern revealed epicenters in densely populated urban areas with radial spread sparing rural areas in the first wave. The case fatality rate was 1.89% and 1.6% during the first and second waves, which increased with advancing age. CONCLUSIONS: Modern surveillance systems like GIS can accurately predict the trends and spread patterns during future pandemics. In addition, real-time mapping can help design risk mitigation strategies, thereby preventing the spread to rural areas.

An Atypical Form of Diabetes Among Individuals With Low BMI.

OBJECTIVE: Diabetes among individuals with low BMI (<19 kg/m2) has been recognized for >60 years as a prevalent entity in low- and middle-income countries (LMICs) and was formally classified as "malnutrition-related diabetes mellitus" by the World Health Organization (WHO) in 1985. Since the WHO withdrew this category in 1999, our objective was to define the metabolic characteristics of these individuals to establish that this is a distinct form of diabetes. RESEARCH DESIGN AND METHODS: State-of-the-art metabolic studies were used to characterize Indian individuals with "low BMI diabetes" (LD) in whom all known forms of diabetes were excluded by immunogenetic analysis. They were compared with demographically matched groups: a group with type 1 diabetes (T1D), a group with type 2 diabetes (T2D), and a group without diabetes. Insulin secretion was assessed by C-peptide deconvolution. Hepatic and peripheral insulin sensitivity were analyzed with stepped hyperinsulinemic-euglycemic pancreatic clamp studies. Hepatic and myocellular lipid contents were assessed with 1H-nuclear magnetic resonance spectroscopy. RESULTS: The total insulin secretory response was lower in the LD group in comparison with the lean group without diabetes and the T2D group. Endogenous glucose production was significantly lower in the LD group than the T2D group (mean ± SEM 0.50 ± 0.1 vs. 0.84 ± 0.1 mg/kg · min, respectively; P < 0.05). Glucose uptake was significantly higher in the LD group in comparison with the T2D group (10.1 ± 0.7 vs. 4.2 ± 0.5 mg/kg · min; P < 0.001). Visceral adipose tissue and hepatocellular lipids were significantly lower in LD than in T2D. CONCLUSIONS: These studies are the first to demonstrate that LD individuals in LMICs have a unique metabolic profile, suggesting that this is a distinct entity that warrants further investigation.

Evidence of dysregulated iron homeostasis in newly diagnosed diabetics, but not in pre-diabetics.

AIM: Diabetes mellitus has been reported to be associated with increased serum levels of ferritin. The basis of this association is unclear. It is also not precisely known whether other iron-related parameters, including hepcidin (the central regulator of systemic iron homeostasis), are affected under these circumstances. This study attempted to determine this. METHODS: Adult men (normoglycemic or newly diagnosed with diabetes or pre-diabetes) were recruited. Anthropometric, metabolic, and hematological and iron-related parameters in blood were measured. Indices of insulin resistance (HOMA-IR) and pancreatic beta cell function (HOMA-ß) were calculated. RESULTS: Subjects in the 3 groups were similar in age, and anthropometric and hematological parameters. Serum ferritin and hepcidin levels were higher in diabetics, than in pre-diabetics and in control subjects. These elevations seen were not linked to the presence of inflammation. HOMA-IR was higher in diabetics, and HOMA-ß lower in diabetics and pre-diabetics, than in control subjects. HOMA-IR and serum ferritin were positively correlated with one another. CONCLUSION: Elevated levels of serum ferritin and hepcidin in newly diagnosed diabetics (but not pre-diabetics) indicate dysregulated iron homeostasis, with the former positively associated with insulin resistance in these patients.

Differential performance of surrogate indices of fasting insulin resistance in low-birthweight and normal-birth weight cohorts: Observations from Hyperinsulinaemic-Euglycaemic clamp studies in young, Asian Indian males.

AIM: To evaluate the predictive accuracy of surrogate measures of fasting insulin resistance/sensitivity like the Homeostasis model assessment for insulin resistance (HOMA -IR), Fasting glucose/insulin ratio (FG-IR), Quantitative insulin sensitivity check index (QUICKI), and the 20/fasting C peptide x fasting plasma glucose [20/(FCP × FPG)] index in comparison to M value derived from hyperinsulinaemic-euglycaemic clamp (HEC) studies in two birth weight based cohorts of Asian Indian males. METHODS: HEC studies were performed in non-diabetic Asian Indian males (n = 117), born of normal birth weight (n = 59, birth weight > 2.5 kgs) and low birth weight (n = 58, birth weight < 2.5 kgs). Anthropometry and biochemical analysis were done. Surrogate indices of fasting insulin resistance were calculated and data were analysed by Pearson's correlation and Random calibration model analysis. RESULTS: Amongst surrogate indices of fasting insulin resistance/sensitivity, the mean values for HOMA-IR, QUICKI, FG-IR, 20/(FCP × FPG) index and M value were similar between the two groups. Significant positive correlation was observed for FG-IR and QUICKI with M value (the gold standard measure of insulin sensitivity derived from HEC procedure) in the low birth weight cohort in contrast to the normal birth weight cohort, wherein no significant correlation was observed for any of the indices. Random calibration model analysis showed highest predictive accuracy for QUICKI in both the study groups. CONCLUSION: The QUICKI index showed highest predictive accuracy in the normal birth weight and the low birth weight cohorts of Asian Indian males.

Indirect Calorimetry: From Bench to Bedside.

Accurate determination of energy expenditure (EE) is vitally important yet often neglected in clinical practice. Indirect calorimetry (IC) provides one of the most sensitive, accurate, and noninvasive measurements of EE in an individual. Over the last couple of decades, this technique has been applied to clinical circumstances such as acute illness and parenteral nutrition. Beyond assessing the nutritional needs, it has also shed light on various aspects of nutrient assimilation, thermogenesis, the energetics of physical exercise, and the pathogenesis of obesity and diabetes. However, because of little or no experience with IC provided during medical education, the benefits of IC are poorly appreciated. Newer technology, cost-effectiveness, and a better understanding of how to interpret measurements should lead to more frequent use of IC. This review focuses on the physicochemical background of IC, the various indications for use, techniques and instruments, potential pitfalls in measurement, and the recent advances in technology that has adapted the technique to long-term studies in humans.

Surrogate measures of insulin sensitivity when compared to euglycemic hyperinsulinemic clamp studies in Asian Indian men without diabetes.

AIM: Fasting surrogate measures of insulin sensitivity are increasingly used in research and clinical practice. To assess the reliability of these measures, we aimed to evaluate multiple fasting surrogate measures simultaneously in non-diabetic subjects in comparison with the euglycemic hyperinsulinemic clamp study. METHODS: Sixteen normoglycemic male South Indian subjects were studied. After an overnight fast, blood samples were collected for glucose, insulin and lipid profile measurements, and stepped euglycemic hyperinsulinemic clamp studies were performed on all subjects. Steady state glucose infusion rates (M value) during low and high insulin phases of the clamp were calculated. Correlation of M value with surrogate markers of insulin sensitivity was performed. Predictive accuracy of surrogate indices was measured in terms of Root Mean Squared Error (RMSE) and leave-one-out cross-validation-type RMSE of prediction using a calibration model. RESULTS: M values showed a strong and significant correlation (p<0.01) with the following surrogate markers: Fasting insulin (r=-0.714), Fasting glucose to insulin ratio (FGIR, r=0.747) and Raynaud index (r=0.714). FGIR had a significantly lower RMSE when compared with HOMA-IR and QUICKI. CONCLUSIONS: Among the surrogate measures, FGIR had the strongest correlation with M values. FGIR was also the most accurate surrogate measure, as assessed by the calibration model.

Parental determinants of metabolic syndrome among adolescent Asian Indians: A cross-sectional analysis of parent-offspring trios.

BACKGROUND: The aim of the present study was to investigate the relationship between parental metabolic syndrome (MS) and the risk of MS and associated abnormalities in adolescent offspring. METHODS: This cross-sectional study was performed on 304 adolescents (12-16 years; 236 children with at least one parent and 124 father-mother-child trios) recruited from four schools representing different socioeconomic strata from Vellore, India. Anthropometric data was collected and blood pressure, blood glucose, and lipids were measured. RESULTS: The prevalence of MS in adolescent offspring, fathers, and mothers was 3.3%, 52.5%, and 48.7% respectively. The most commonly observed metabolic abnormality among adolescents was lower high-density lipoprotein. Maternal waist circumference (WC) was strongly correlated with adolescent body mass index (P = 0.007), WC (P < 0.001), serum triglycerides (P = 0.02), and systolic (P = 0.005) and diastolic (P = 0.01) blood pressure. Maternal MS status was significantly associated with a greater risk of central obesity (WC odds ratio [OR] 2.02; 95% confidence interval [CI] 1.21-3.17) in offspring. Both parents having MS conferred a significant effect on the child's WC (OR 1.21; 95% CI 1.72-2.07) and increased risk of MS (OR 6.19; 95% CI 1.64-23.26). CONCLUSIONS: This study highlights the possible heritable parental components that may contribute to the MS phenotype in offspring: MS in adolescent offspring is related to parental MS status, and maternal traits reflect offspring adiposity and metabolic traits more strongly than paternal factors. Therefore, adolescent children of parents with MS should be targets for primordial prevention of cardiometabolic disease.