PAX4 loss of function increases diabetes risk by altering human pancreatic endocrine cell development.

The coding variant (p.Arg192His) in the transcription factor PAX4 is associated with an altered risk for type 2 diabetes (T2D) in East Asian populations. In mice, Pax4 is essential for beta cell formation but its role on human beta cell development and/or function is unknown. Participants carrying the PAX4 p.His192 allele exhibited decreased pancreatic beta cell function compared to homozygotes for the p.192Arg allele in a cross-sectional study in which we carried out an intravenous glucose tolerance test and an oral glucose tolerance test. In a pedigree of a patient with young onset diabetes, several members carry a newly identified p.Tyr186X allele. In the human beta cell model, EndoC-ßH1, PAX4 knockdown led to impaired insulin secretion, reduced total insulin content, and altered hormone gene expression. Deletion of PAX4 in human induced pluripotent stem cell (hiPSC)-derived islet-like cells resulted in derepression of alpha cell gene expression. In vitro differentiation of hiPSCs carrying PAX4 p.His192 and p.X186 risk alleles exhibited increased polyhormonal endocrine cell formation and reduced insulin content that can be reversed with gene correction. Together, we demonstrate the role of PAX4 in human endocrine cell development, beta cell function, and its contribution to T2D-risk.

Trans-interaction of risk loci 6p24.1 and 10q11.21 is associated with endothelial damage in coronary artery disease.

BACKGROUND AND AIMS: Single nucleotide polymorphism rs6903956 has been identified as one of the genetic risk factors for coronary artery disease (CAD). However, rs6903956 lies in a non-coding locus on chromosome 6p24.1. We aim to interrogate the molecular basis of 6p24.1 containing rs6903956 risk alleles in endothelial disease biology. METHODS AND RESULTS: We generated induced pluripotent stem cells (iPSCs) from CAD patients (AA risk genotype at rs6903956) and non-CAD subjects (GG non-risk genotype at rs6903956). CRISPR-Cas9-based deletions (Δ63-89bp) on 6p24.1, including both rs6903956 and a short tandem repeat variant rs140361069 in linkage disequilibrium, were performed to generate isogenic iPSC-derived endothelial cells. Edited CAD endothelial cells, with removal of 'A' risk alleles, exhibited a global transcriptional downregulation of pathways relating to abnormal vascular physiology and activated endothelial processes. A CXC chemokine ligand on chromosome 10q11.21, CXCL12, was uncovered as a potential effector gene in CAD endothelial cells. Underlying this effect was the preferential inter-chromosomal interaction of 6p24.1 risk locus to a weak promoter of CXCL12, confirmed by chromatin conformation capture assays on our iPSC-derived endothelial cells. Functionally, risk genotypes AA/AG at rs6903956 were associated significantly with elevated levels of circulating damaged endothelial cells in CAD patients. Circulating endothelial cells isolated from patients with risk genotypes AA/AG were also found to have 10 folds higher CXCL12 transcript copies/cell than those with non-risk genotype GG. CONCLUSIONS: Our study reveals the trans-acting impact of 6p24.1 with another CAD locus on 10q11.21 and is associated with intensified endothelial injury.

An open source tool to compute measures of inpatient glycemic control: translating from healthcare analytics research to clinical quality improvement.

OBJECTIVES: The objective of this study is to facilitate monitoring of the quality of inpatient glycemic control by providing an open-source tool to compute glucometrics. To allay regulatory and privacy concerns, the tool is usable locally; no data are uploaded to the internet. MATERIALS AND METHODS: We extended code, initially developed for healthcare analytics research, to serve the clinical need for quality monitoring of diabetes. We built an application, with a graphical interface, which can be run locally without any internet connection. RESULTS: We verified that our code produced results identical to prior work in glucometrics. We extended the prior work by including additional metrics and by providing user customizability. The software has been used at an academic healthcare institution. CONCLUSION: We successfully translated code used for research methods into an open source, user-friendly tool which hospitals may use to expedite quality measure computation for the management of inpatients with diabetes.

Evaluating the effectiveness of a multi-faceted inpatient diabetes management program among hospitalised patients with diabetes mellitus.

BACKGROUND: Diabetes mellitus (DM) is one of the most common chronic diseases. Individuals with DM are more likely to be hospitalised and stay longer than those without DM. Inpatient hypoglycemia and hyperglycemia, which are associated with adverse outcomes, are common, but can be prevented through hospital quality improvement programs. METHODS: We designed a multi-faceted intervention program with the aim of reducing inpatient hypoglycemia and hyperglycemia. This was implemented over seven phases between September 2013 to January 2016, and covered all the non-critical care wards in a tertiary hospital. The program represented a pragmatic approach that leveraged on existing resources and infrastructure within the hospital. We calculated glucometric outcomes in June to August 2016 and compared them with those in June to August 2013 to assess the overall effectiveness of the program. We used regression models with generalised estimating equations to adjust for potential confounders and account for correlations of repeated outcomes within patients and admissions. RESULTS: We observed significant reductions in patient-days affected by hypoglycemia (any glucose reading < 4 mmol/L: OR = 0.71, 95% CI: 0.61 to 0.83, p <  0.001), and hyperglycemia (any glucose reading > 14 mmol/L: OR = 0.84, 95% CI: 0.71 to 0.99, p = 0.041). Similar findings were observed for admission-level hypoglycemia and hyperglycemia. Further analyses suggested that these reductions started to occur four to 6 months post-implementation. CONCLUSIONS: Our program was associated with sustained improvements in clinically relevant outcomes. Our described intervention could be feasibly implemented by other secondary and tertiary care hospitals by leveraging on existing infrastructure and work force.

Effects of external counter-pulsation on endothelial function assessed by peripheral artery tonometry, levels of glycaemia and metabolic markers in individuals with type 2 diabetes mellitus.

BACKGROUND AND AIMS: External counter-pulsation (ECP) generates sheer stress thereby improving endothelial function and anginal symptoms in coronary artery disease. Endothelial dysfunction is also involved in the pathogenesis of T2DM. The aim of this pilot study was to investigate the use of ECP at different doses in improving endothelial function and glycaemic markers in T2DM. METHODS: This prospective study involved 46 subjects with T2DM randomly assigned to receive 35 sessions of ECP at different regimens (0.5 h versus 1 h) and duration (7 versus 12 weeks). Endothelial function was evaluated by reactive hyperaemia index (RHI) via peripheral arterial tonometry at the start, midpoint and end of study. Other secondary outcomes included fasting glucose, HOMA-IR, HbA1c, blood pressure, lipid profile, weight and vibration sense. RESULTS: There was no change in RHI across all 3 regimens of ECP individually or collectively at the end of the study (ΔRHI +0.01%, p = 0.458). Glycaemic markers also remained unchanged at endpoint. Subgroup analysis showed an improvement in RHI (ΔRHI +20.6%, p = 0.0178) in subjects with more severe endothelial dysfunction at baseline. CONCLUSION: ECP did not show a beneficial effect on endothelial function or glycemic control in this South-East Asian population with T2DM at any of the three regimens. This may partly be explained by less severe endothelial dysfunction and less insulin resistance in our population at baseline.

Genome-Wide Association for HbA1c in Malay Identified Deletion on SLC4A1 that Influences HbA1c Independent of Glycemia.

CONTEXT: Glycated hemoglobin A1c (HbA1c) level is used to screen and diagnose diabetes. Genetic determinants of HbA1c can vary across populations and many of the genetic variants influencing HbA1c level were specific to populations. OBJECTIVE: To discover genetic variants associated with HbA1c level in nondiabetic Malay individuals. DESIGN AND PARTICIPANTS: We conducted a genome-wide association study (GWAS) analysis for HbA1c using 2 Malay studies, the Singapore Malay Eye Study (SiMES, N = 1721 on GWAS array) and the Living Biobank study (N = 983 on GWAS array and whole-exome sequenced). We built a Malay-specific reference panel to impute ethnic-specific variants and validate the associations with HbA1c at ethnic-specific variants. RESULTS: Meta-analysis of the 1000 Genomes imputed array data identified 4 loci at genome-wide significance (P < 5 × 10-8). Of the 4 loci, 3 (ADAM15, LINC02226, JUP) were novel for HbA1c associations. At the previously reported HbA1c locus ATXN7L3-G6PC3, association analysis using the exome data fine-mapped the HbA1c associations to a 27-bp deletion (rs769664228) at SLC4A1 that reduced HbA1c by 0.38 ±â€…0.06% (P = 3.5 × 10-10). Further imputation of this variant in SiMES confirmed the association with HbA1c at SLC4A1. We also showed that these genetic variants influence HbA1c level independent of glucose level. CONCLUSION: We identified a deletion at SLC4A1 associated with HbA1c in Malay. The nonglycemic lowering of HbA1c at rs769664228 might cause individuals carrying this variant to be underdiagnosed for diabetes or prediabetes when HbA1c is used as the only diagnostic test for diabetes.

Robust estimation of the effect of an exposure on the change in a continuous outcome.

BACKGROUND: The change in two measurements of a continuous outcome can be modelled directly with a linear regression model, or indirectly with a random effects model (REM) of the individual measurements. These methods are susceptible to model misspecifications, which are commonly addressed by applying monotonic transformations (e.g., Box-Cox transformation) to the outcomes. However, transforming the outcomes complicates the data analysis, especially when variable selection is involved. We propose a robust alternative through a novel application of the conditional probit (cprobit) model. METHODS: The cprobit model analyzes the ordered outcomes within each subject, making the estimate invariant to monotonic transformation on the outcome. By scaling the estimate from the cprobit model, we obtain the exposure effect on the change in the observed or Box-Cox transformed outcome, pending the adequacy of the normality assumption on the raw or transformed scale. RESULTS: Using simulated data, we demonstrated a similar good performance of the cprobit model and REM with and without transformation, except for some bias from both methods when the Box-Cox transformation was applied to scenarios with small sample size and strong effects. Only the cprobit model was robust to skewed subject-specific intercept terms when a Box-Cox transformation was used. Using two real datasets from the breast cancer and inpatient glycemic variability studies which utilize electronic medical records, we illustrated the application of our proposed robust approach as a seamless three-step workflow that facilitates the use of Box-Cox transformation to address non-normality with a common underlying model. CONCLUSIONS: The cprobit model provides a seamless and robust inference on the change in continuous outcomes, and its three-step workflow is implemented in an R package for easy accessibility.

Handling ties in continuous outcomes for confounder adjustment with rank-ordered logit and its application to ordinal outcomes.

The rank-ordered logit (rologit) model was recently introduced as a robust approach for analysing continuous outcomes, with the linear exposure effect estimated by scaling the rank-based log-odds estimate. Here we extend the application of the rologit model to continuous outcomes with ties and ordinal outcomes treated as imperfectly-observed continuous outcomes. By identifying the functional relationship between survival times and continuous outcomes, we explicitly establish the equivalence between the rologit and Cox models to justify the use of the Breslow, Efron and perturbation methods in the analysis of continuous outcomes with ties. Using simulation, we found all three methods perform well with few ties. Although an increasing extent of ties increased the bias of the log-odds and linear effect estimates and resulted in reduced power, which was somewhat worse when the model was mis-specified, the perturbation method maintained a type I error around 5%, while the Efron method became conservative with heavy ties but outperformed Breslow. In general, the perturbation method had the highest power, followed by the Efron and then the Breslow method. We applied our approach to three real-life datasets, demonstrating a seamless analytical workflow that uses stratification for confounder adjustment in studies of continuous and ordinal outcomes.

Using marginal standardisation to estimate relative risk without dichotomising continuous outcomes.

BACKGROUND: Although criticisms regarding the dichotomisation of continuous variables are well known, applying logit model to dichotomised outcomes is the convention because the odds ratios are easily obtained and they approximate the relative risks (RRs) for rare events. METHODS: To avoid dichotomisation when estimating RR, the marginal standardisation method that transforms estimates from logit or probit model to RR estimate is extended to include estimates from linear model in the transformation. We conducted a simulation study to compare the statistical properties of the estimates from: (i) marginal standardisation method between models for continuous (i.e., linear model) and dichotomised outcomes (i.e., logit or probit model), and (ii) marginal standardisation method and distributional approach (i.e., marginal mean method) applied to linear model. We also compared the diagnostic test for probit, logit and linear models. For the real dataset analysis, we applied these analytical approaches to assess the management of inpatient hyperglycaemia in a pilot intervention study. RESULTS: Although the RR estimates from the marginal standardisation method were generally unbiased for all models in the simulation study, the marginal standardisation method for linear model provided estimates with higher precision and power than logit or probit model, especially when the baseline risks were at the extremes. When comparing approaches that avoid dichotomisation, RR estimates from these approaches had comparable performance. Assessing the assumption of error distribution was less powerful for logit or probit model via link test when compared with diagnostic test for linear model. After accounting for multiple thresholds representing varying levels of severity in hyperglycaemia, marginal standardisation method for linear model provided stronger evidence of reduced hyperglycaemia risk after intervention in the real dataset analysis although the RR estimates were similar across various approaches. CONCLUSIONS: When compared with approaches that do not avoid dichotomisation, the RR estimated from linear model is more precise and powerful, and the diagnostic test from linear model is more powerful in detecting mis-specified error distributional assumption than the diagnostic test from logit or probit model. Our work describes and assesses the methods available to analyse data involving studies of continuous outcomes with binary representations.

A stratification approach using logit-based models for confounder adjustment in the study of continuous outcomes.

The control of confounding is an area of extensive epidemiological research, especially in the field of causal inference for observational studies. Matched cohort and case-control study designs are commonly implemented to control for confounding effects without specifying the functional form of the relationship between the outcome and confounders. This paper extends the commonly used regression models in matched designs for binary and survival outcomes (i.e. conditional logistic and stratified Cox proportional hazards) to studies of continuous outcomes through a novel interpretation and application of logit-based regression models from the econometrics and marketing research literature. We compare the performance of the maximum likelihood estimators using simulated data and propose a heuristic argument for obtaining the residuals for model diagnostics. We illustrate our proposed approach with two real data applications. Our simulation studies demonstrate that our stratification approach is robust to model misspecification and that the distribution of the estimated residuals provides a useful diagnostic when the strata are of moderate size. In our applications to real data, we demonstrate that parity and menopausal status are associated with percent mammographic density, and that the mean level and variability of inpatient blood glucose readings vary between medical and surgical wards within a national tertiary hospital. Our work highlights how the same class of regression models, available in most statistical software, can be used to adjust for confounding in the study of binary, time-to-event and continuous outcomes.

Feasibility of representing adherence to blood glucose monitoring through visualizations: A pilot survey study among healthcare workers.

BACKGROUND: Measuring adherence to processes is one of the established ways to quantify the quality of healthcare. Providing timely feedback to healthcare workers on the level of adherence can improve process measures. However, it is challenging to present data on adherence to repetitive time-sensitive tasks in a clear manner. OBJECTIVES: We used inpatient glucose monitoring as a test case to explore the feasibility of using visualizations to communicate adherence to repetitive scheduled tasks to healthcare workers. METHODS: We selected four candidate plots that represented distribution across time: histogram, probability density function plot (pdf plot), violin plot and cumulative density function plot (cdf plot). Doctors and nurses involved in inpatient diabetes care in a tertiary hospital were invited to complete a self-administered questionnaire that measured self-reported baseline knowledge, performance, and perception towards the visualizations. Performance was assessed by determining if a participant was able to correctly identify visualizations representing protocol adherence. We also assessed the perception of usability of these visualizations for monitoring protocol adherence. Binomial regression models were used to identify factors associated with overall performance and perception. Logistic regression models with generalized estimating equation were used to compare performance and perception between visualizations, and identify effect modifiers. RESULTS: A total of 57 doctors and nurses completed the questionnaire. Participants were most familiar with histogram (87.7%), followed by cdf plot (61.4%), pdf plot (40.4%), and violin plot (7%). However, the percentages of participants who identified non-adherence using these plots were generally lower, ranging from 29.8% to 40.4%. Participants' perception of usability ranged from 14% to 17.5% across these visualizations. More favorable perceptions were found among participants with baseline knowledge for two or more visualizations (adjusted odds ratio: 3.21; 95%CI: 1.29, 7.96; p-value: 0.012) and having identified two or more non-adherent visualizations (adjusted odds ratio: 4.23; 95%CI: 1.95, 9.16; p-value: < 0.001). CONCLUSIONS: Adherence to repetitive time-sensitive tasks can be presented in the form of visualizations. However, nurses' and doctors' knowledge and understanding of these visualizations are generally poor. This may influence their perception of usability of these plots. Therefore, these visualizations need to be implemented in tandem with training on their interpretation, to enhance the usefulness of these plots in motivating quality improvement.

Utilizing distributional analytics and electronic records to assess timeliness of inpatient blood glucose monitoring in non-critical care wards.

BACKGROUND: Regular and timely monitoring of blood glucose (BG) levels in hospitalized patients with diabetes mellitus is crucial to optimizing inpatient glycaemic control. However, methods to quantify timeliness as a measurement of quality of care are lacking. We propose an analytical approach that utilizes BG measurements from electronic records to assess adherence to an inpatient BG monitoring protocol in hospital wards. METHODS: We applied our proposed analytical approach to electronic records obtained from 24 non-critical care wards in November and December 2013 from a tertiary care hospital in Singapore. We applied distributional analytics to evaluate daily adherence to BG monitoring timings. A one-sample Kolmogorov-Smirnov (1S-KS) test was performed to test daily BG timings against non-adherence represented by the uniform distribution. This test was performed among wards with high power, determined through simulation. The 1S-KS test was coupled with visualization via the cumulative distribution function (cdf) plot and a two-sample Kolmogorov-Smirnov (2S-KS) test, enabling comparison of the BG timing distributions between two consecutive days. We also applied mixture modelling to identify the key features in daily BG timings. RESULTS: We found that 11 out of the 24 wards had high power. Among these wards, 1S-KS test with cdf plots indicated adherence to BG monitoring protocols. Integrating both 1S-KS and 2S-KS information within a moving window consisting of two consecutive days did not suggest frequent potential change from or towards non-adherence to protocol. From mixture modelling among wards with high power, we consistently identified four components with high concentration of BG measurements taken before mealtimes and around bedtime. This agnostic analysis provided additional evidence that the wards were adherent to BG monitoring protocols. CONCLUSIONS: We demonstrated the utility of our proposed analytical approach as a monitoring tool. It provided information to healthcare providers regarding the timeliness of daily BG measurements. From the real data application, there were empirical evidences suggesting adherence of BG timings to protocol among wards with adequate power for assessing timeliness. Our approach is extendable to other areas of healthcare where timeliness of patient care processes is important.

Relationship between measured average glucose by continuous glucose monitor and HbA1c measured by three different routine laboratory methods.

OBJECTIVES: The relationship between glycated hemoglobin A1c (HbA1c) and average glucose has been described by the empirically derived estimated average glucose (eAG) equation in the A1c-Derived Average Glucose (ADAG) study, with extensive calibration efforts in four secondary reference HbA1c methods. It is not known if this relationship is preserved when HbA1c is measured by routine laboratory methods under routine conditions. DESIGN AND METHODS: We measured average glucose (mAG) by six days of continuous glucose monitoring in 45 adults with stable HbA1c (<1% HbA1c change in the preceding two months). Subjects with medical conditions that may confound HbA1c measurement, including anemia and hemoglobinopathy, were excluded. HbA1c was measured using Bio-Rad Variant II (cation-exchange HPLC), Bio-Rad in2it (boronate affinity HPLC) and Roche Tina-quant (immunoassay) methods. RESULTS: The average differences between eAG derived from the routine HbA1c methods and mAG were 10.4% (Variant II), 6.0% (Tina-quant) and 1.0% (in2it). The regression coefficients between the mAG and HbA1c are different between in2it (mAG, mmol/L=0.58 × %HbA1c + 2.3), Tina-quant and Variant II (both mAG, mmol/L=0.66 × %HbA1c + 1.9). However, the 95% confidence intervals of the slope and bias of these methods overlap. The correlation between mAG and HbA1c was greatest when measured using the Variant II (r(2)=0.84), followed by Tina-quant (r(2)=0.82) and in2it (r(2)=0.71). CONCLUSIONS: The relationship between HbA1c and measured average glucose is method-dependent despite improved HbA1c standardization. The differences in relationship may reflect as discrepant eAG and home glucose monitoring results.

Macro-thyrotropin: a case report and review of literature.

CONTEXT: Isolated elevation of TSH in the absence of thyroid symptoms can be very rarely caused by a macromolecule formed between TSH and Ig (macro-TSH), confounding the interpretation of thyroid function test results. OBJECTIVE: We described the use of several commonly available laboratory-based approaches to investigate an isolated TSH elevation [232 mIU/liter; free T(4), 10 pmol/liter (reference interval, 10.0-23.0 pmol/liter), Vitros platform] in a clinically euthyroid elderly gentleman, which led to the diagnosis of macro-TSH. METHODS AND RESULTS: TSH concentration of the patient was significantly lower (122 mIU/liter) when measured on the Advia Centaur platform. Serial dilution of the patient's sample showed a nonlinear increase in TSH recovery at increasing dilution (nonlinearity). Polyethylene glycol precipitation and mixing the patient's sample with a hypothyroid patient sample showed reduced TSH recovery, suggesting the presence of a high molecular weight interfering substance and excess TSH binding capacity, respectively. Heterophile blocking tube studies and rheumatoid factors were negative. Gel filtration chromatography demonstrated a TSH peak fraction that approximated the molecular size of IgG; together with the excess TSH binding capacity, this indicated the presence of TSH-IgG macro-TSH. A review of 12 macro-TSH case reports showed that samples with macro-TSH produce over-recovery with dilution, return negative results on anti-animal and anti-heterophile blocking studies, and commonly have recovery of less than 20% when subjected to polyethylene glycol precipitation. CONCLUSION: Macro-TSH is an underrecognized laboratory interference. Routine laboratory techniques described above can help diagnose this rare entity. A close dialogue between the physician and the laboratory is important in approaching such cases.

Severe hypoglycemia associated with an illegal sexual enhancement product adulterated with glibenclamide: MR imaging findings.

PURPOSE: To describe the magnetic resonance (MR) imaging findings associated with severe hypoglycemia after consumption of an illegal sexual enhancement product (Power 1 Walnut) adulterated with glibenclamide, an oral hypoglycemic agent used to treat diabetes mellitus. MATERIALS AND METHODS: Institutional review board approval was obtained for this retrospective study. Records in eight male patients with severe hypoglycemia of unknown cause, without prior treatment for diabetes, and with positive blood toxicology results for glibenclamide were reviewed. MR imaging included diffusion-weighted imaging and, in some patients, MR angiography, dynamic contrast material-enhanced perfusion MR imaging, and MR spectroscopy. RESULTS: In seven patients, there were hyperintense abnormalities on diffusion-weighted and T2-weighted images in the hippocampus and cerebral cortex, sparing the subcortical white matter and cerebellum. Three patients had abnormalities of the splenium of the corpus callosum, and one had widespread involvement, including the caudate nucleus, basal ganglia, and internal capsule bilaterally. In three patients, unilateral cortical involvement, which did not conform to the typical cerebral arterial territories, was noted. In one patient, perfusion MR imaging showed slightly increased relative cerebral blood volume, and MR spectroscopy revealed no evidence of abnormal lactate in the affected cerebral cortex. CONCLUSION: Diffusion-weighted MR imaging findings in patients with severe hypoglycemia showed typical lesions in the hippocampus and cerebral cortex, but the caudate nucleus and basal ganglia were involved in only the most severely affected patient. The splenium of the corpus callosum and internal capsule were also abnormal in three patients, and unilateral cortical lesions could be distinguished from acute ischemic stroke by the pattern of involvement and MR angiographic, perfusion, and spectroscopic findings.