Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Evaluation of intraoperative neuromonitoring (IONM) data with the Mainz IONM Quality Assurance and Analysis tool.

BACKGROUND: Intraoperative neuromonitoring is widely used in thyroid and parathyroid surgery to prevent unilateral and especially bilateral recurrent nerve paresis. Reference values for amplitude and latency for the recurrent laryngeal nerve and vagus nerve have been published. However, data quality measures that exclude errors of the underlying intraoperative neuromonitoring (IONM) data (immanent software errors, false data labelling) before statistical analysis have not yet been implemented. METHODS: The authors developed an easy-to-use application (the Mainz IONM Quality Assurance and Analysis tool) using the programming language R. This tool allows visualization, automated and manual correction, and statistical analysis of complete raw data sets (electromyogram signals of all stimulations) from intermittent and continuous neuromonitoring in thyroid and parathyroid surgery. The Mainz IONM Quality Assurance and Analysis tool was used to evaluate IONM data generated and exported from 'C2' and 'C2 Xplore' neuromonitoring devices (inomed Medizintechnik GmbH) after surgery. For the first time, reference values for latency and amplitude were calculated based on 'cleaned' IONM data. RESULTS: Intraoperative neuromonitoring data files of 1935 patients consecutively operated on from June 2014 to May 2020 were included. Of 1921 readable files, 34 were excluded for missing data labelling. Automated plausibility checks revealed: less than 3 per cent device errors for electromyogram signal detection; 1138 files (approximately 60 per cent) contained potential labelling errors or inconsistencies necessitating manual review; and 915 files (48.5 per cent) were indeed erroneous. Mean(s.d.) reference onset latencies for the left vagus nerve, right vagus nerve, recurrent laryngeal nerve, and external branch of the superior laryngeal nerve were 6.8(1.1), 4.2(0.8), 2.5(1.1), and 2.1(0.5) ms, respectively. CONCLUSION: Due to high error frequencies, IONM data should undergo in-depth review and multi-step cleaning processes before analysis to standardize scientific reporting. Device software calculates latencies differently; therefore reference values are device-specific (latency) and/or set-up-specific (amplitude). Novel C2-specific reference values for latency and amplitude deviate considerably from published values.

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.

Venglustat combined with imiglucerase for neurological disease in adults with Gaucher disease type 3: the LEAP trial.

Gaucher disease type 3 is a chronic neuronopathic disorder with wide-ranging effects, including hepatosplenomegaly, anaemia, thrombocytopenia, skeletal disease and diverse neurological manifestations. Biallelic mutations in GBA1 reduce lysosomal acid ß-glucosidase activity, and its substrates, glucosylceramide and glucosylsphingosine, accumulate. Enzyme replacement therapy and substrate reduction therapy ameliorate systemic features of Gaucher disease, but no therapies are approved for neurological manifestations. Venglustat is an investigational, brain-penetrant, glucosylceramide synthase inhibitor with potential to improve the disease by rebalancing influx of glucosylceramide with impaired lysosomal recycling. The Phase 2, open-label LEAP trial (NCT02843035) evaluated orally administered venglustat 15 mg once-daily in combination with maintenance dose of imiglucerase enzyme replacement therapy during 1 year of treatment in 11 adults with Gaucher disease type 3. Primary endpoints were venglustat safety and tolerability and change in concentration of glucosylceramide and glucosylsphingosine in CSF from baseline to Weeks 26 and 52. Secondary endpoints included change in plasma concentrations of glucosylceramide and glucosylsphingosine, venglustat pharmacokinetics in plasma and CSF, neurologic function, infiltrative lung disease and systemic disease parameters. Exploratory endpoints included changes in brain volume assessed with volumetric MRI using tensor-based morphometry, and resting functional MRI analysis of regional brain activity and connectivity between resting state networks. Mean (SD) plasma venglustat AUC0-24 on Day 1 was 851 (282) ng•h/ml; Cmax of 58.1 (26.4) ng/ml was achieved at a median tmax 2.00 h. After once-daily venglustat, plasma concentrations (4 h post-dose) were higher compared with Day 1, indicating ∼2-fold accumulation. One participant (Patient 9) had low-to-undetectable venglustat exposure at Weeks 26 and 52. Based on mean plasma and CSF venglustat concentrations (excluding Patient 9), steady state appeared to be reached on or before Week 4. Mean (SD) venglustat concentration at Week 52 was 114 (65.8) ng/ml in plasma and 6.14 (3.44) ng/ml in CSF. After 1 year of treatment, median (inter-quartile range) glucosylceramide decreased 78% (72, 84) in plasma and 81% (77, 83) in CSF; median (inter-quartile range) glucosylsphingosine decreased 56% (41, 60) in plasma and 70% (46, 76) in CSF. Ataxia improved slightly in nine patients: mean (SD, range) total modified Scale for Assessment and Rating of Ataxia score decreased from 2.68 [1.54 (0.0 to 5.5)] at baseline to 1.55 [1.88 (0.0 to 5.0)] at Week 52 [mean change: -1.14 (95% CI: -2.06 to -0.21)]. Whole brain volume increased slightly in patients with venglustat exposure and biomarker reduction in CSF (306.7 ± 4253.3 mm3) and declined markedly in Patient 9 (-13894.8 mm3). Functional MRI indicated stronger connectivity at Weeks 26 and 52 relative to baseline between a broadly distributed set of brain regions in patients with venglustat exposure and biomarker reduction but not Patient 9, although neurocognition, assessed by Vineland II, deteriorated in all domains over time, which illustrates disease progression despite the intervention. There were no deaths, serious adverse events or discontinuations. In adults with Gaucher disease type 3 receiving imiglucerase, addition of once-daily venglustat showed acceptable safety and tolerability and preliminary evidence of clinical stability with intriguing but intrinsically inconsistent signals in selected biomarkers, which need to be validated and confirmed in future research.

Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study.

The presentation and underlying pathophysiology of type 2 diabetes (T2D) is complex and heterogeneous. Recent studies attempted to stratify T2D into distinct subgroups using data-driven approaches, but their clinical utility may be limited if categorical representations of complex phenotypes are suboptimal. We apply a soft-clustering (archetype) method to characterize newly diagnosed T2D based on 32 clinical variables. We assign quantitative clustering scores for individuals and investigate the associations with glycemic deterioration, genetic risk scores, circulating omics biomarkers, and phenotypic stability over 36 months. Four archetype profiles represent dysfunction patterns across combinations of T2D etiological processes and correlate with multiple circulating biomarkers. One archetype associated with obesity, insulin resistance, dyslipidemia, and impaired ß cell glucose sensitivity corresponds with the fastest disease progression and highest demand for anti-diabetic treatment. We demonstrate that clinical heterogeneity in T2D can be mapped to heterogeneity in individual etiological processes, providing a potential route to personalized treatments.

Processes Underlying Glycemic Deterioration in Type 2 Diabetes: An IMI DIRECT Study.

OBJECTIVE: We investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: A total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), ß-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA1c deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression. RESULTS: Faster HbA1c progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R 2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07-0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role. CONCLUSIONS: Deteriorating insulin sensitivity and ß-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, ß-cell function, and insulin clearance may be relevant to prevent progression.

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.

BACKGROUND: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. METHODS: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. RESULTS: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. CONCLUSIONS: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Gut Mucosal Gene Expression and Metabolic Changes After Roux-en-Y Gastric Bypass Surgery.

OBJECTIVE: Changes in the secretion of gut-derived peptide hormones have been associated with the metabolic benefits of Roux-en-Y gastric bypass (RYGB) surgery. In this study, the effects of RYGB on anthropometrics, postprandial plasma hormone responses, and mRNA expression in small intestinal mucosa biopsy specimens before and after RYGB were evaluated. METHODS: In a cross-sectional study, 20 individuals with obesity undergoing RYGB underwent mixed meal tests and upper enteroscopy with retrieval of small intestinal mucosa biopsy specimens 3 months before and after surgery. Concentrations of circulating gut and pancreatic hormones during mixed meal tests as well as full mRNA sequencing of biopsy specimens were evaluated. RESULTS: RYGB-induced improvements of body weight and composition, insulin resistance, and circulating cholesterols were accompanied by significant changes in postprandial plasma responses of pancreatic and gut hormones. Global gene expression analysis of biopsy specimens identified 2,437 differentially expressed genes after RYGB, including changes in genes that encode prohormones and G protein-coupled receptors. CONCLUSIONS: RYGB affects the transcription of a wide range of genes, indicating that the observed beneficial metabolic effects of RYGB may rely on a changed expression of several genes in the gut. RYGB-induced changes in the expression of genes encoding signaling peptides and G protein-coupled receptors may disclose new gut-derived treatment targets against obesity and diabetes.

Short-term variability of the human serum metabolome depending on nutritional and metabolic health status.

The intra-individual variability of the human serum metabolome over a period of 4 weeks and its dependence on metabolic health and nutritional status was investigated in a single-center study under tightly controlled conditions in healthy controls, pre-diabetic individuals and patients with type-2 diabetes mellitus (T2DM, n = 10 each). Untargeted metabolomics in serum samples taken at three different days after overnight fasts and following intake of a standardized mixed meal showed that the human serum metabolome is remarkably stable: The median intra-class correlation coefficient (ICC) across all metabolites and all study participants was determined as 0.65. ICCs were similar for the three different health groups, before and after meal intake, and for different metabolic pathways. Only 147 out of 1438 metabolites (10%) had an ICC below 0.4 indicating poor stability over time. In addition, we confirmed previously identified metabolic signatures differentiating healthy, pre-diabetic and diabetic individuals. To our knowledge, this is the most comprehensive study investigating the temporal variability of the human serum metabolome under such tightly controlled conditions.

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. METHODS AND FINDINGS: We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one. CONCLUSIONS: In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community. TRIAL REGISTRATION: ClinicalTrials.gov NCT03814915.

The surgical dilemma of primary surgery for follicular thyroid neoplasms.

Follicular thyroid carcinoma is the second most prevalent form of differentiated thyroid carcinoma, following papillary thyroid carcinoma. Preoperative diagnosis is hampered by the fact that fine-needle aspiration cytology as well as supplemental molecular analysis cannot unambiguously distinguish between follicular thyroid carcinoma and benign follicular thyroid adenoma. The 2017 WHO classification defines three histological subtypes of follicular thyroid carcinoma: minimally invasive (excellent prognosis), encapsulated angioinvasive, and widely invasive type (higher risk of recurrence and metastatic spread). The fact that definite characterization of follicular neoplasms is predominantly a postoperative histological diagnosis (core criteria: capsular, vascular and adjacent tissue invasion) translates into the challenge for the thyroid surgeon to plan preoperatively for presence of malignancy and, if required, to adapt the surgical strategy according to intraoperative (frozen section) or postoperative histological findings. Until improved tools for pre-/intraoperative diagnosis are available, the malignant potential of a follicular thyroid lesion can be assessed by stratifying the patient according to clinical risk factors (presence of metastases, advanced patient age, tumor size). A stepwise, escalating surgical approach with restricted primary resection (hemithyroidectomy) and completion surgery based on the definite histopathology is another option to solve this dilemma. The currently recommended surgical treatment strategies for FTCs as published by ATA, BTA, CAEK and ESES are discussed. There is consensus that prophylactic lymphadenectomy is not required for FTCs and that hemithyroidectomy is sufficient in low-risk FTCs (capsular invasion only) whereas thyroidectomy with postoperative radioiodine therapy is indicated in high-risk FTCs (angioinvasion; widely invasive FTC).

Investigating Intestinal Glucagon After Roux-en-Y Gastric Bypass Surgery.

CONTEXT: After Roux-en-Y gastric bypass (RYGB) surgery, postprandial plasma glucagon concentrations have been reported to increase. This occurs despite concomitant improved glucose tolerance and increased circulating plasma concentrations of insulin and the glucagon-inhibiting hormone glucagon-like peptide 1 (GLP-1). OBJECTIVE: To investigate whether RYGB-induced hyperglucagonemia may be derived from the gut. DESIGN AND SETTING: Substudy of a prospective cross-sectional study at a university hospital in Copenhagen, Denmark. PARTICIPANTS: Morbidly obese individuals undergoing RYGB (n = 8) with or without type 2 diabetes. INTERVENTIONS: Three months before and after RYGB, participants underwent upper enteroscopy with retrieval of gastrointestinal mucosal biopsy specimens. Mixed-meal tests were performed 1 week and 3 months before and after RYGB. MAIN OUTCOME MEASURES: The 29-amino acid glucagon concentrations in plasma and in mucosal gastrointestinal biopsy specimens were assessed using mass spectrometry-validated immunoassays, and a new monoclonal antibody reacting with immunoreactive glucagon was used for immunohistochemistry. RESULTS: Postprandial plasma concentrations of glucagon after RYGB were increased. Expression of the glucagon gene in the small intestine increased after surgery. Glucagon was identified in the small-intestine biopsy specimens obtained after, but not before, RYGB. Immunohistochemically, mucosal biopsy specimens from the small intestine harbored cells costained for GLP-1 and immunoreactive glucagon. CONCLUSION: Increased concentrations of glucagon were observed in small-intestine biopsy specimens and postprandially in plasma after RYGB. The small intestine harbored cells immunohistochemically costaining for GLP-1 and glucagon-like immunoreactivity after RYGB. Glucagon derived from small-intestine enteroendocrine l cells may contribute to postprandial plasma concentrations of glucagon after RYGB.

Successful Performance of Laboratory Investigations with Blood Glucose Meters Employing a Dynamic Electrochemistry-Based Correction Algorithm Is Dependent on Careful Sample Handling.

BACKGROUND: Devices employing electrochemistry-based correction algorithms (EBCAs) are optimized for patient use and require special handling procedures when tested in the laboratory. This study investigated the impact of sample handling on the results of an accuracy and hematocrit interference test performed with BG*Star, iBG*Star; OneTouch Verio Pro and Accu-Chek Aviva versus YSI Stat 2300. METHODS: Venous heparinized whole blood was manipulated to contain three different blood glucose concentrations (64-74, 147-163, and 313-335 mg/dL) and three different hematocrit levels (30%, 45%, and 60%). Sample preparation was done by either a very EBCA-experienced laboratory testing team (A), a group experienced with other meters but not EBCAs (B), or a team inexperienced with meter testing (C). Team A ensured physiological pO2 and specific sample handling requirements, whereas teams B and C did not consider pO2. Each sample was tested four times with each device. In a separate experiment, a different group similar to group B performed the experiment before (D1) and after (D2) appropriate sample handling training. RESULTS: Mean absolute deviation from YSI was calculated as a metrix for all groups and devices. Mean absolute relative difference was 4.3% with team A (B: 9.2%, C: 5.2%). Team B had much higher readings and team C produced 100% of "sample composition" errors with high hematocrit levels. In a separate experiment, group D showed a result similar to group B before the training and improved significantly when considering the sample handling requirements (D1: 9.4%, D2: 4.5%, P < 0.05). CONCLUSIONS: Laboratory performance testing of EBCA devices should only be performed by trained staff considering specific sample handling requirements. The results suggest that healthcare centers should evaluate EBCA-based devices with capillary blood from patients in accordance with the instructions for use to achieve reliable results.

Continuous Intraoperative Neuromonitoring in Thyroid Surgery.

Intermittent intraoperative neuromonitoring (I-IONM) has been introduced to thyroid surgery during the past two decades. The neuromonitoring devices (hardware and software) were significantly improved with the development of the second and third device generations. Needle electrodes, which were widely used 10 years ago, are almost completely substituted by less invasive, optimized endotracheal tube electrodes that ensure signal stability. In addition, recommendations of surgical societies for the standardized application of IONM have been established and incorporated into guidelines. However, due to the already very low frequency of (permanent) recurrent laryngeal nerve (RLN) paralysis following primary thyroid resections, a significant benefit of IONM compared to the "gold standard" of visual identification of the RLN alone has not been demonstrated so far. Moreover, the idea to enable surgeons to recognize impending nerve damage during (not after) dissection cannot be implemented with I-IONM techniques. The main benefit of I-IONM, therefore, remains the possible change of resection strategy in case of a "loss of signal (LOS)" after resection of one thyroid lobe in patients with planned bilateral resection. The recent introduction of continuous neuromonitoring (C-IONM) represents a significant step forward, potentially enabling the surgeon to react before irreversible damage to the RLN occurs. Preliminary data are supporting this methodological advantage.

Evaluation of the effects of insufficient blood volume samples on the performance of blood glucose self-test meters.

BACKGROUND: Accuracy of blood glucose readings is (among other things) dependent on the test strip being completely filled with sufficient sample volume. The devices are supposed to display an error message in case of incomplete filling. This laboratory study was performed to test the performance of 31 commercially available devices in case of incomplete strip filling. METHODS: Samples with two different glucose levels (60-90 and 300-350 mg/dl) were used to generate three different sample volumes: 0.20 µl (too low volume for any device), 0.32 µl (borderline volume), and 1.20 µl (low but supposedly sufficient volume for all devices). After a point-of-care capillary reference measurement (StatStrip, NovaBiomedical), the meter strip was filled (6x) with the respective volume, and the response of the meters (two devices) was documented (72 determinations/meter type). Correct response was defined as either an error message indicating incomplete filling or a correct reading (±20% compared with reference reading). RESULTS: Only five meters showed 100% correct responses [BGStar and iBGStar (both Sanofi), ACCU-CHEK Compact+ and ACCU-CHEK Mobile (both Roche Diagnostics), OneTouch Verio (LifeScan)]. The majority of the meters (17) had up to 10% incorrect reactions [predominantly incorrect readings with sufficient volume; Precision Xceed and Xtra, FreeStyle Lite, and Freedom Lite (all Abbott); GlucoCard+ and GlucoMen GM (both Menarini); Contour, Contour USB, and Breeze2 (all Bayer); OneTouch Ultra Easy, Ultra 2, and Ultra Smart (all LifeScan); Wellion Dialog and Premium (both MedTrust); FineTouch (Terumo); ACCU-CHEK Aviva (Roche); and GlucoTalk (Axis-Shield)]. Ten percent to 20% incorrect reactions were seen with OneTouch Vita (LifeScan), ACCU-CHEK Aviva Nano (Roche), OmniTest+ (BBraun), and AlphaChek+ (Berger Med). More than 20% incorrect reactions were obtained with Pura (Ypsomed), GlucoCard Meter and GlucoMen LX (both Menarini), Elite (Bayer), and MediTouch (Medisana). CONCLUSIONS: In summary, partial and incomplete blood filling of glucose meter strips is often associated with inaccurate reading. These findings underline the importance of appropriate patient education on this aspect of blood glucose self-monitoring.

Blood glucose meters employing dynamic electrochemistry are stable against hematocrit interference in a laboratory setting.

BACKGROUND: Hematocrit (HCT) is known to be a confounding factor that interferes with many blood glucose (BG) measurement technologies, resulting in wrong readings. Dynamic electrochemistry has been identified as one possible way to correct for these potential deviations. The purpose of this laboratory investigation was to assess the HCT stability of four BG meters known to employ dynamic electrochemistry (BGStar and iBGStar, Sanofi; Wavesense Jazz, AgaMatrix; Wellion Linus, MedTrust) in comparison with three other devices (GlucoDock, Medisana; OneTouch Verio Pro, LifeScan; FreeStyle Freedom InsuLinx, Abbott-Medisense). METHODS: Venous heparinized blood was immediately aliquoted after draw and manipulated to contain three different BG concentrations (60-90, 130-160, and 280-320 mg/dl) and five different HCT levels (25%, 35%, 45%, 55%, and 60%). After careful oxygenation to normal blood oxygen pressure, each of the resulting 15 different samples was measured six times with three devices and three strip lots of each meter. The YSI Stat 2300 served as laboratory reference method. Stability to HCT influence was assumed when less than 10% difference occurred between the highest and lowest mean glucose deviations in relation to HCT concentrations [hematocrit interference factor (HIF)]. RESULTS: Five of the investigated self-test meters showed a stable performance with the different HCT levels tested in this investigation: BGStar (HIF 4.6%), iBGStar (6.6%), Wavesense Jazz (4.1%), Wellion Linus (8.5%), and OneTouch Verio Pro (6.2%). The two other meters were influenced by HCT (FreeStyle InsuLinx 17.8%; GlucoDock 46.5%). CONCLUSIONS: In this study, meters employing dynamic electrochemistry, as used in the BGStar and iBGStar devices, were shown to correct for potential HCT influence on the meter results. Dynamic electrochemistry appears to be an effective way to handle this interfering condition.

The precision study: examining the inter- and intra-assay variability of replicate measurements of BGStar, iBGStar and 12 other blood glucose monitors.

OBJECTIVE: Self-monitoring of blood glucose is a key element in diabetes management. Accurate and precise performance of blood glucose monitors (BGMs) ensures that valid values are obtained to guide treatment decisions by patients and physicians. BGStar and iBGStar are hand-held BGMs that use dynamic electrochemistry to correct for potential interferences and thereby minimize system errors. RESEARCH DESIGN AND METHODS: A single-center, in vitro diagnostic device performance evaluation with heparinized oxygenated venous blood samples (intra-assay precision) and control solutions (interassay precision) was performed in a laboratory setting, comparing BGStar and iBGStar with 12 competitors. MAIN OUTCOME MEASURES: The primary outcome was the coefficient of variation percent (CV%) of the BGMs investigated. RESULTS: In inter-assay precision analyses, all but GlucoMen LX had a CV <5%, and in intra-assay precision analyses, 10 of the 14 devices tested had CV <5%. BGStar and iBGStar had a CV <5% in both the inter- and intra-assay precision analyses. The smallest variation was found in the near-normoglycemic glucose range (5.3 - 8.0 mmol/l) for both BGStar and iBGStar in the inter-assay precision analysis. CONCLUSIONS: BGStar and iBGStar were proven to have very good inter-assay and high intra-assay precision, demonstrating low scattering of replicate measurements with both clinical samples and control solutions.

Hematocrit interference of blood glucose meters for patient self-measurement.

BACKGROUND: Abnormal hematocrit levels may interfere with glucose readings of patient self-assessment blood glucose (BG) meters. The aim of this laboratory investigation was to assess the potential influence of hematocrit variations on a variety of BG meters applying different measurement technologies. METHODS: Venous heparinized blood was manipulated to contain three different BG concentrations (50-90, 120-180, and 280-350 mg/dl) and five different hematocrit levels (25%, 35%, 45%, 55%, and 65%). After careful oxygenation to normal blood oxygen pressure (65-100 mmHg), each sample was measured (eight times) with the following devices: Accu-Chek® Aviva Nano and Active, Breeze®2 and Contour®, FreeStyle Freedom Lite®, GlucoDr. auto™, Glucofix® mio Plus, GlucoLab™, GlucoMen® LX Plus, Nova Max® Link, Nova Max® Plus, OneTouch® Ultra®2 and Verio®, On Call® Plus and Platinum, Optium Xceed®, Precision Xceed®, and TaiDoc Fora TD-4227. A YSI 2300 STAT Plus™ glucose analyzer served as reference method. Stability to hematocrit influence was assumed, with <10% mean glucose result bias between the highest and lowest hematocrit levels. RESULTS: Six of the investigated meters showed a stable performance in this investigation: Accu-Chek Active (7%), Glucofix mio Plus (5%), GlucoMen LX Plus (4%), Nova Max Plus (4%), Nova Max Link (7%), and OneTouch Verio (3%). All other meters failed this hematocrit interference test, with FreeStyle Freedom Lite (11%), and On Call Platinum (12%) being the better devices and On Call Plus (68%), GlucoLab (51%), TaiDoc Fora TD-4227 (39%), and Breeze 2 (38%) showing the worst performance. CONCLUSIONS: Hematocrit may affect BG meter performance in daily routine. In case of interference, low hematocrit values (<35%) result in too high readings. Our results encourage use of meters that are not affected by hematocrit interference.

Determination of hematocrit interference in blood samples derived from patients with different blood glucose concentrations.

BACKGROUND: We performed a blood glucose meter hematocrit (HCT) interference test with lower sample manipulation requirements by using blood samples from patients with different blood glucose (BG) levels. METHODS: Blood from five patients with different BG levels (2.8, 5.6, 8.3, 13.9, 19.4 mmol/liter) was manipulated to contain five different HCT concentrations (35/40/45/50/55%). Each sample was measured three times in parallel with 14 BG testing devices (reference method: YSI 2300 STAT Plus™ Glucose Analyzer). The largest mean deviations in both directions from the reference method (normalized to 100% at 45% HCT) were added as a measure for hematocrit interference factor (HIF). A HIF >10% was considered to represent clinically relevant HCT interference. RESULTS: Few devices showed no clinically relevant HCT interference at high/low BG levels: BGStar® (7.2%, 7.3%), iBGStar® (9.0%, 8.6%), Contour® (10.0%, 4.6%), OneTouch® Verio™ 2 (10.0%, 5.2%), and GlucoMen® LX (7.2%, 5.1%). Other devices showed interference at one or both glucose ranges: ACCU-CHEK® Aviva (12.6%, 10.7%), Aviva Nano (7.2%, 10.5%), Breeze2 (3.6%, 30.2%), GlucoCard G+ (12.6%, 7.0%), OneTouch® Ultra®2 (12.6%, 25.6%), FreeStyle Freedom Lite® (9.0%, 11.0%), Precision Xceed (16.2%, 15.3%), and MediTouch® (19.8%, 28.0%). The deviations in all devices were less pronounced in the HCT range of 35-50%. CONCLUSIONS: The results of this trial with less sample manipulation (HCT only) confirmed previous examinations with HCT and glucose manipulation. The same devices showed HCT stability as previously observed. Artificial sample manipulation may be less crucial than expected when evaluating HCT interference.