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Xiu-Li Lim,1,* Boon-Wee Teo,2,* Bee-Choo Tai,1 Tien Y Wong,3 Daniel P-K Ng1 1Department of Epidemiology and Public Health, 2Department of Medicine, Yong Loo Lin School of Medicine, National University Health System, 3Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore*Joint first authorsBackground: The main objective of this study was to investigate whether plasma pentosidine levels were associated with cataract and low estimated glomerular filtration rate (eGFR) in nonproteinuric type 2 diabetic patients.Methods: We characterized 888 nonproteinuric type 2 diabetic patients residing in Singapore according to their eGFR values. Proteinuria was excluded on the basis of multiple urinalyses. Patients with low renal function (cases, n = 125) and controls (n = 763) were defined as having eGFR < and ≥60 mL/min/1.73 m2, respectively. Pentosidine levels were measured by enzyme-linked immunosorbent assay. Multinomial logistic regression was used to test the association between plasma pentosidine levels and the joint phenotype of cataract and low eGFR.Results: Cases had higher triacylglycerol values, higher systolic blood pressure, and were more likely to be treated with two or more antihypertensive medications. In univariate analysis, cases were potentially more than twice as likely to have had a history of cataract compared with controls. This association persisted in multivariate analyses after adjusting for the significant covariates, hypertension and triacylglycerol, but was attenuated when age was included in the model. Plasma pentosidine levels were significantly higher in cases with low eGFR who also had a history of cataract. This association persisted in multivariate analyses that included the covariates, glycosylated hemoglobin, hypertension, and diabetic retinopathy, as well as age.Conclusion: Carbonyl stress, as reflected by pentosidine levels, is present in a subset of nonproteinuric diabetic patients. Clinically, this stress was associated with the joint presence of cataract and low eGFR.Keywords: advanced glycation endproducts, Chinese, normoalbuminuria, renal function

Objective: The potassium voltage-gated channel, KQT-like subfamily, member 1 (KCNQ1) has been found through a genome-wide association study to be a strong candidate for conferring susceptibility to type 2 diabetes in East Asian and European populations. Our objective was to describe the association between polymorphisms at the KCNQ1 locus with insulin resistance, beta-cell function, and other type 2 diabetes-related traits in a sample of Chinese, Malays, and Asian Indians living in Singapore.Research Design and Methods: We examined the associations between four previously reported KCNQ1 single-nucleotide polymorphisms (SNPs) with type 2 diabetes-related traits in 3,734 participants from the population-based 1998 Singapore National Health Survey cohort (2,520 Chinese, 693 Malay, and 521 Asian Indians). Insulin resistance was calculated from fasting insulin and glucose using the homeostasis model assessment method, whereas pancreatic beta-cell function was assessed using the corrected insulin response at 120 min (CIR(120)).Results: SNPs rs2237897, rs2237892, and rs2283228 were significantly associated with type 2 diabetes (odds ratio [OR] 1.48, P = 3 x 10(-4); OR 1.38, P = 0.002; OR 1.31, P = 0.012, respectively). Within the Chinese population, the risk alleles for rs2237897, rs2237892, and rs2283228 were significantly associated with higher fasting glucose levels (P = 0.014, 0.011, and 0.034, respectively) and reduced CIR(120)(P = 0.007, 0.013, and 0.014, respectively). A similar trend was observed among the Malay and Asian Indian minority groups, although this did not reach statistical significance because of limited sample sizes.Conclusions: The increased risk for type 2 diabetes associated with KCNQ1 is likely to be caused by a reduction in insulin secretion. Further studies will be useful to replicate these findings and to fully delineate the role of KCNQ1 and its related pathways in disease pathogenesis. [ABSTRACT FROM AUTHOR]

Objective: A key consideration when setting up genetic studies is the case definition. For diabetic nephropathy, the case definition is typically based on the presence of albuminuria. However, it has been long debated whether diabetic nephropathy cases defined in this way may have a high prevalence of nondiabetic kidney disease, especially if diabetic retinopathy is absent.Research Design and Methods: We performed a meta-analysis of 53 studies comprising 17,791 subjects investigating the angiotensin-I converting enzyme insertion/deletion polymorphism, taking into account the requirement for diabetic retinopathy in the case definition and assuming a random-effects model.Results: No publication bias was observed. The overall pooled odds ratio (OR) for all 53 studies was 0.78 (95% CI 0.70-0.87; P < 0.001), which indicated a significant protection against diabetic nephropathy for genotype II compared with carriage of the D-allele. The pooled OR for the 11 studies (n = 3,413) requiring diabetic retinopathy in the case definition was 0.68 (0.53-0.86; P = 0.002), and this was not significantly different from the pooled OR of 0.81 (0.71-0.92; P = 0.001) obtained from the 42 remaining studies (n = 14,378) (P = 0.198). This lack of any significant effect of diabetic retinopathy was reiterated in subgroup analyses based on the type of diabetes present.Conclusions: Stipulating the presence of diabetic retinopathy in the case definition of diabetic nephropathy did not appear to confer tangible benefits when detecting genetic associations. Besides reducing sample sizes, this stipulation makes the interpretation of genetic associations more difficult due to the potential confounding presence of diabetic retinopathy. [ABSTRACT FROM AUTHOR]

Previous investigations of the ACE gene as a susceptibility factor for diabetic nephropathy have primarily focused on its insertion/deletion (Ins/Del) polymorphism. In a departure from these earlier studies, we used three tagging markers (A-5466C, T-3892C, and Ins/Del) at the ACE locus to test for disease haplotype associations. A case-control study design was used where case subjects were type 2 diabetic patients with advanced diabetic nephropathy, as indicated by the presence of proteinuria or chronic renal failure/end-stage renal disease, while control subjects were normoalbuminuric, despite >6 years of diabetes. None of the individual markers showed significant disease association when considered on their own. However, haplotype analyses revealed a near doubling in the prevalence of the A.T.D risk haplotype in case subjects (0.136) compared with control subjects (0.075) (P = 0.009), thus providing first evidence for a disease haplotype for advanced diabetic nephropathy at the ACE locus. [ABSTRACT FROM AUTHOR]

Machine-learning (ML) models in flow cytometry have the potential to reduce error rates, increase reproducibility, and boost the efficiency of clinical labs. While numerous ML models for flow cytometry data have been proposed, few studies have described the clinical deployment of such models. Realizing the potential gains of ML models in clinical labs requires not only an accurate model but also infrastructure for automated inference, error detection, analytics and monitoring, and structured data extraction. Here, we describe an ML model for the detection of Acute Myeloid Leukemia (AML), along with the infrastructure supporting clinical implementation. Our infrastructure leverages the resilience and scalability of the cloud for model inference, a Kubernetes-based workflow system that provides model reproducibility and resource management, and a system for extracting structured diagnoses from full-text reports. We also describe our model monitoring and visualization platform, an essential element for ensuring continued model accuracy. Finally, we present a post-deployment analysis of impacts on turn-around time and compare production accuracy to the original validation statistics., (© 2025 The Author(s). Cytometry Part B: Clinical Cytometry published by Wiley Periodicals LLC on behalf of International Clinical Cytometry Society.)

This review will explore the integration of machine learning (ML) techniques to enhance the analysis of increasingly complex and voluminous flow cytometry data, as traditional manual methods are insufficient for handling this data. We attempt to provide a comprehensive introduction to ML in flow cytometry, detailing the transition from manual gating to computational methods and emphasizing the importance of data quality. Key ML techniques are discussed, including supervised learning methods like logistic regression, support vector machines, and neural networks, which rely on labeled data to classify disease states. Unsupervised methods, such as k-means clustering, FlowSOM, UMAP, and t-SNE, are highlighted for their ability to identify novel cell populations without predefined labels. We also delve into newer semi-supervised and weakly supervised methods, which leverage partial labeling to improve model performance. Practical aspects of implementing ML in clinical settings are addressed, including regulatory considerations, data preprocessing, model training, validation, and the importance of generalizability, and we underscore the collaborative effort required among pathologists, data scientists, and laboratory professionals to ensure robust model development and deployment. Finally, we show the transformative potential of ML in flow cytometry in uncovering new biological insights through advanced computational techniques.

Clinical flow cytometry laboratories require quality control materials for assay development, validation, and performance monitoring, including new reagent lot qualification. However, finding suitable controls for populations with uncommonly expressed antigens or for rare populations, such as mast cells, can be difficult. To that end, we evaluated synthetic abnormal mast cell particles (SAMCP), developed together with, and manufactured by, Slingshot Biosciences. The SAMCP's were designed to phenotypically mimic abnormal neoplastic mast cells: they were customized to have the same light scatter and autofluorescence properties of mast cells, along with surface antigen levels of CD45, CD33, CD117, CD2, CD25, and CD30 consistent with that seen in mast cell disease. We evaluated several performance characteristics of these particles using ARUP's high sensitivity clinical mast cell assay, including limit of detection, off-target activity and FMO controls, precision, scatter properties of the particles utilizing several different cytometer platforms, and particle antigen stability. The phenotype of the SAMCP mimicked abnormal mast cells, and they could be distinguished from normal native mast cells. FMO controls demonstrated specificity of each of the markers, and no off-target binding was detected. The limit of detection of the particles spiked into normal bone marrow was found to be ≤0.003% in a limiting dilution assay. The mast cell particles were found to perform similarly on Becton Dickinson Lyric, Cytek Aurora, and Beckman Coulter Navios and CytoFLEX platforms. Within run and between run precision were less than 10% CV. SAMCP were stable up to 13 days with minimal loss of antigen fluorescence intensity. The SAMCP's were able to successfully mimic neoplastic mast cells based on the results of our high sensitivity mast cell flow cytometry panel. These synthetic cell particles represent an exciting and innovative technology, which can fulfill vital needs in clinical flow cytometry such as serving as standardized control materials for assay development and performance monitoring., (© 2024 The Author(s). Cytometry Part B: Clinical Cytometry published by Wiley Periodicals LLC on behalf of International Clinical Cytometry Society.)

Clinical flow cytometry plays a vital role in the diagnosis and monitoring of various red blood cell disorders. The high throughput, precision, and automation potential of this technique allows for cost-effective and timely analysis compared to older and more manual test methods. Flow cytometric analysis serves as the gold standard diagnostic method for multiple hematological disorders, especially in clinical scenarios where an assay needs to have high sensitivity, high specificity, and a short turnaround time. In this review, we discuss the role of flow cytometric analysis in paroxysmal nocturnal hemoglobinuria, fetal-maternal hemorrhage, and hereditary spherocytosis., Competing Interests: Disclosure Authors have nothing to disclose., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Multiparameter flow cytometry data is visually inspected by expert personnel as part of standard clinical disease diagnosis practice. This is a demanding and costly process, and recent research has demonstrated that it is possible to utilize artificial intelligence (AI) algorithms to assist in the interpretive process. Here we report our examination of three previously published machine learning methods for classification of flow cytometry data and apply these to a B-cell neoplasm dataset to obtain predicted disease subtypes. Each of the examined methods classifies samples according to specific disease categories using ungated flow cytometry data. We compare and contrast the three algorithms with respect to their architectures, and we report the multiclass classification accuracies and relative required computation times. Despite different architectures, two of the methods, flowCat and EnsembleCNN, had similarly good accuracies with relatively fast computational times. We note a speed advantage for EnsembleCNN, particularly in the case of addition of training data and retraining of the classifier., (© 2024 International Clinical Cytometry Society.)

Flow cytometry is a key clinical tool in the diagnosis of many hematologic malignancies and traditionally requires close inspection of digital data by hematopathologists with expert domain knowledge. Advances in artificial intelligence (AI) are transferable to flow cytometry and have the potential to improve efficiency and prioritization of cases, reduce errors, and highlight fundamental, previously unrecognized associations with underlying biological processes. As a multidisciplinary group of stakeholders, we review a range of critical considerations for appropriately applying AI to clinical flow cytometry, including use case identification, low and high risk use cases, validation, revalidation, computational considerations, and the present regulatory frameworks surrounding AI in clinical medicine. In particular, we provide practical guidance for the development, implementation, and suggestions for potential regulation of AI-based methods in the clinical flow cytometry laboratory. We expect these recommendations to be a helpful initial framework of reference, which will also require additional updates as the field matures., (© 2024 International Clinical Cytometry Society.)

Objective: This study is aimed at ascertaining the feasibility of conducting the 1-minute sit-to-stand (1MSTS) and 30-second sit-to-stand (30SSTS) tests for healthy participants via video consultation. A secondary aim was to compare the relationship between the 1MSTS and 30SSTS., Methods: A total of 63 participants were recruited via the Singapore Institute of Technology emails and social media in 2020 during the peak of COVID-19. Prior to the sit-to-stand testing, all participants completed the consent form and physical activity questionnaires. Anthropometric data such as height and weight were also collected prior to testing. An instructional video detailing the sit-to-stand (STS) movement and the requirements for the environment set-up were sent to the participants via email. All STS tests were conducted virtually via the Zoom application. Healthy participants aged 21 to 55 years old performed a 1MSTS and 30SSTS each in random order., Results: All recruited participants completed the STS tests with no reported adverse events. Majority of participants were from the 21- to 25-year-old age groups, and the average number of repetitions performed by this group was 21.9 ± 5.6 for the 30SSTS and 44.7 ± 12.6 for the 1MSTS., Conclusion: Conducting the STS tests via video consultation was demonstrated to be safe and feasible. The number of repetitions performed in the 1MSTS is correlated to that of the 30SSTS, but 1MSTS has the ability to elicit a greater HR response among younger adults., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2023 Deng Peng Ng et al.)

T cells expressing chimeric antigen receptors (CARs) have shown remarkable therapeutic activity against different types of cancer. However, the wider use of CAR T cells has been hindered by the potential for life-threatening toxicities due to on-target off-tumor killing of cells expressing low amounts of the target antigen. CD229, a signaling lymphocyte-activation molecule (SLAM) family member, has previously been identified as a target for CAR T cell-mediated treatment of multiple myeloma (MM) due to its high expression on the surfaces of MM cells. CD229 CAR T cells have shown effective clearance of MM cells in vitro and in vivo. However, healthy lymphocytes also express CD229, albeit at lower amounts than MM cells, causing their unintended targeting by CD229 CAR T cells. To increase the selectivity of CD229 CAR T cells for MM cells, we used a single amino acid substitution approach of the CAR binding domain to reduce CAR affinity. To identify CARs with increased selectivity, we screened variant binding domains using solid-phase binding assays and biolayer interferometry and determined the cytotoxic activity of variant CAR T cells against MM cells and healthy lymphocytes. We identified a CD229 CAR binding domain with micromolar affinity that, when combined with overexpression of c-Jun, confers antitumor activity comparable to parental CD229 CAR T cells but lacks the parental cells' cytotoxic activity toward healthy lymphocytes in vitro and in vivo. The results represent a promising strategy to improve the efficacy and safety of CAR T cell therapy that requires clinical validation.

Background: The purpose of this study was to explore the effects biomarkers have on the duration and speed of clinical trials in oncology., Materials and Methods: Clinical trial data was pooled from www.clinicaltrials.gov within the 4 cancer indications of non-small cell lung cancer, breast cancer, melanoma, and colorectal cancer. Heatmaps of clinical timelines were used to display differences in the frequency and timing of clinical trials across trials that used or did not use biomarkers, for all 4 indications., Results: Screening of 8630 clinical trials across the 4 indications yielded 671 unique drugs corresponding to 1224 eligible trials used in our analysis. The constructed heatmaps visually represented that biomarkers did not have an effect on the time gap between trial phases for non-small cell lung cancer and melanoma but did for colorectal and breast cancer trials, reducing the speed of trial timelines. It was also observed that biomarker trials were more often concurrent over shorter periods of time and began later in the timeline for non-small cell lung and colorectal cancers., Conclusion: The novel visualization method revealed longer gaps between trial phases, later clinical trial start times, and shorter periods of concurrently run trials for drugs that used biomarkers. The study highlights that biomarker-driven trials might impact drug approval timelines and need to be considered carefully in clinical development plan., (© The Author(s) 2022. Published by Oxford University Press.)

Context.—: Delta checks are a powerful technique for monitoring clinical assays in many disciplines but have not been routinely used in molecular testing., Objective.—: To determine if the biologically determined kinetics of BCR-ABL1's rise and fall could allow the development of a delta check in BCR-ABL1 testing., Design.—: Nine years of BCR-ABL1 p210 results were evaluated, and patients with 3 or more results were selected for inclusion. The kinetics of these percentages of international standard values were plotted against time along with the median and the 90th and 95th percentile lines. A Monte Carlo simulation of a batch mix-up was performed for 6 months of data to determine the efficacy of the proposed cutoff., Results.—: The median kinetics showed a 1-log drop of the percentage of international standard in 90 days, with less than 5% of cases showing faster than a 2-log drop in 90 days, and less than 2.5% showing a faster than 3-log drop in 90 days (extrapolated to 1 log in 30 days). The Monte Carlo simulation of a batch mix-up showed that an average batch mix-up of 23 samples could routinely be flagged by this cutoff, albeit with wide variance., Conclusions.—: These results suggest that using a drop in the percentage of international standard of greater than 1 log in 30 days can be a useful trigger in implementing a delta-check system for this molecular test.

Therapies in myeloma are rapidly advancing with a host of new targeted therapies coming to market. While these drugs offer significant survival benefits and better side-effect profiles compared with conventional chemotherapeutics, they raise significant difficulties in monitoring post-therapy disease status by flow cytometry due to assay interference and/or selection of phenotypically different sub-clones. The principal culprit, anti-CD38 monoclonal antibodies, limits the ability to detect plasma cells based on classical CD38/CD45 gating. Other markers, such as CD138, are known to be suboptimal by flow cytometry. Various techniques have been proposed to overcome this problem. The most promising of these techniques has been the marker VS38c, a monoclonal antibody targeting an endoplasmic reticulum protein which has shown high sensitivity for plasma cells. Alternative techniques for gating plasma cells, while variably effective in the near term are already the subject of several targeted therapies rendering their usefulness limited in the longer term. Likewise, future targets of these therapies may render present aberrancy markers ineffective in MRD testing. These therapies pose challenges that must be overcome with new markers and novel panels in order for flow cytometric MRD testing to remain relevant., (© 2021 John Wiley & Sons Ltd.)

Objectives: Clinical flow cytometry is laborious, time-consuming, and expensive given the need for data review by highly trained personnel such as technologists and pathologists as well as the significant number of normal cases. Given these issues, automation in analysis and diagnosis holds the key to major efficiency gains. The objective was to design an automated pipeline for the diagnosis of B-cell malignancies in flow cytometry and evaluate its performance against our standard clinical diagnostic flow cytometry process., Methods: Using 3,417 cases of peripheral blood data over 6 months from our 10-color B-cell screening tube, we used a newly described method for feature extraction and dimensionality reduction called UMAP on the raw flow cytometry data followed by random forest classification to classify cases without gating on specific population., Results: Our automated classifier was able to achieve greater than 95% accuracy in diagnosing all B-cell malignancies, and even better performance for specific malignancies for which the panel was designed, such as chronic lymphocytic leukemia. By adjusting classifier cutoffs, 100% sensitivity could be achieved with an albeit low 14% specificity. Hypothetically, this would allow 11% of the cases to be autoverified without human intervention., Conclusions: These results suggest that a clinical implementation of this pipeline can greatly assist in quality control, improve turnaround time, and decrease staff workloads., (© American Society for Clinical Pathology, 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Enzyme kinetics is the study of enzymatic catalytic rates in biochemical reactions. This topic is commonly taught to life science students in introductory biochemistry courses during their undergraduate education. Unlike most other biochemistry topics, which focus on visual structures of biomolecules and their processes, enzyme kinetics is explained primarily through abstract mathematical and two-dimensional graphical plots. However, these abstract/symbolic representations often make it difficult for students to relate the kinetic parameters to the underlying molecular system that is being described. In this article, we present the design and development of a web-based multimedia interactive learning tool, biomolecular interactive tutorials (BIOMINT) to help students better bridge the relationships between these abstract mathematical models and the molecular behaviors, interactions, and dynamics that produce kinetic phenomena. This learning tool can be accessed at https://bit.ly/biomint. © 2019 International Union of Biochemistry and Molecular Biology, 48(1):74-79, 2020., (© 2019 International Union of Biochemistry and Molecular Biology.)

The mathematical models that describe enzyme kinetics are invaluable predictive tools in numerous scientific fields. However, the daunting mathematical language used to describe kinetic behavior can be confusing for life science students; they often struggle to conceptualize and relate the mathematical representations to the molecular phenomena occurring at both macroscopic and microscopic levels. Students with less developed abstract and mathematical thinking skills may benefit from a visual learning approach. The paucity of visual resources for enzyme kinetics makes this a fertile field for developing novel learning media. We discuss developing a three-dimensional animation aimed at introducing key concepts of Michaelis-Menten enzyme kinetics to undergraduate life science students. This animation uses both realistic and metaphoric depictions of the underlying molecular players, environments, and interactions in enzyme kinetics to contextualize and explain the relationship between the mathematical models and underlying molecular systems. The animation can be viewed at bit.ly/michaelis-menten. © 2018 International Union of Biochemistry and Molecular Biology, 46(5):561-565, 2018., (© 2018 International Union of Biochemistry and Molecular Biology.)

Changes in pH can alter the structure and activity of proteins and may be used by the cell to control molecular function. This coupling can also be used in non-native applications through the design of pH-sensitive biomolecules. For example, the pH (low) insertion peptide (pHLIP) can spontaneously insert into a lipid bilayer when the pH decreases. We have previously shown that the α-helicity and helix-helix interactions of the TM2 α-helix of the proteolipid protein (PLP) are sensitive to the local hydrophobicity at its C-terminus. Given that there is an ionizable residue (Glu-88) at the C-terminus of this transmembrane (TM) segment, we hypothesized that changing the ionization state of this residue through pH may alter the local hydrophobicity of the peptide enough to affect both its secondary structure and helix-helix interactions. To examine this phenomenon, we synthesized peptide analogues of the PLP TM2 α-helix (wild-type sequence (66)AFQYVIYGTASFFFLYGALLLAEGF(90)). Using circular dichroism and Förster resonance energy transfer in the membrane-mimetic detergent sodium dodecyl sulfate, we found that a decrease in pH increases both peptide α-helicity and the extent of self-association. This pH-dependent effect is due specifically to the presence of Glu-88 at the C-terminus. Additional experiments in which Phe-90 was mutated to residues of varying hydrophobicities indicated that the strength of this effect is dependent on the local hydrophobicity near Glu-88. Our results have implications for the design of TM peptide switches and improve our understanding of how membrane protein structure and activity can be regulated through local molecular environmental changes.

Objectives: Diagnosing classical Hodgkin lymphoma (cHL) by flow cytometry (FC) relies on an observer gating rare populations of Hodgkin/Reed Sternberg (HRS) cells. Here, we apply machine-learning methods to aid in the detection of rare tumor cell populations using data derived from clinical FC analysis of cHL as a model disease., Methods: FC data from 144 clinical cases using a nine-color FC reagent panel were analyzed using Python 2.7 and the "scikit-learn" module., Results: Seventy-eight 50 × 50 two-dimensional histograms were generated from routine FC data and a reciprocal power function applied to favor rare events. Data were classified by support vector machine (SVM), gradient boosting, and random forest classifiers. All three classifiers showed no statistical difference in performance, with 89%-92% accuracy on cross-validation. Nearly all classifiers misclassified the same set of cases, with more false-positive than false-negative cases. Dimensionality reduction by ensemble methods selected for data points in a CD5+/ CD40+/CD64- region., Conclusions: All classifiers provide probabilistic confidences for each result, and diagnostic cutoffs can be chosen to minimize false negatives and serve as a screening tool. Computational exclusion of manually gated HRS cells had little impact on the overall performance of selected support vectors in SVM or dimensionality reduction, suggesting that features of the immune response in cHL may dictate the method accuracy. We hypothesize there are distinct inflammatory cells that suggest cHL., (Copyright© by the American Society for Clinical Pathology.)

In this issue of Structure, Zhang and colleagues compare the helix-helix interaction spaces of an extensive database of soluble and membrane proteins. Intriguingly, the resultant clusters show similar helix interaction geometries between the protein classes, differing in detail only by patterns of local interactions and inter-helical distances., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Central to the formation of tertiary structure in membrane protein folding is the presence of amino acid sequence motifs (such as "small-XXX-small" segments) in the TM segments that promote interaction-compatible surfaces through which the TM α-helices interact. Here, we sought to elucidate additional factors that may work in tandem to dictate the ultimate interaction fate of TM-embedded segments. In this context, we used proteolipid protein (PLP), the major protein from central nervous system myelin for which mutant-dependent non-native oligomerization has been implicated in neurological disorders, to explore the specific effects of TM boundary residues (the membrane entry and exit points), keying on the secondary structure and self-association of peptides corresponding to the PLP TM2 α-helix (wild-type sequence ⁶⁶AFQYVIYGTASFFFLYGALLLAEGF⁹⁰). Using gel electrophoresis, circular dichroism, and Förster resonance energy transfer in the membrane-mimetic detergent sodium dodecyl sulfate (SDS), we found that mutation of F90 to residues such as A, I, L, or V maintains the onset of TM2-TM2 dimerization, whereas mutation to E, G, Q, N, S, or T abrogates dimer formation. We attribute this sensitivity to changes in local hydrophobicity, viz., a decrease in hydrophobicity reduces local lipid-peptide interactions, which in turn disrupts peptide α-helicity and hence the effectiveness of an incipient interaction-compatible surface. Our results show that the secondary structure and oligomeric state of PLP TM2 Lys-tagged peptides are significantly modulated by the specific nature of their C-terminal boundary residue, thus providing insight as to how point mutations, particularly where they produce disease states, can compromise the folding process.

In Asia, young-onset type 2 diabetes (YOD) is characterized by obesity and increased risk for cardiovascular disease (CVD). In a genome-wide association study (GWAS) of 99 Chinese obese subjects with familial YOD diagnosed before 40-year-old and 101 controls, the T allele of rs1408888 in intron 1 of DACH1(Dachshund homolog 1) was associated with an odds ratio (OR) of 2.49(95% confidence intervals:1.57-3.96, P = 8.4 × 10(-5)). Amongst these subjects, we found reduced expression of DACH1 in peripheral blood mononuclear cells (PBMC) from 63 cases compared to 65 controls (P = 0.02). In a random cohort of 1468 cases and 1485 controls, amongst top 19 SNPs from GWAS, rs1408888 was associated with type 2 diabetes with a global P value of 0.0176 and confirmation in a multiethnic Asian case-control cohort (7370/7802) with an OR of 1.07(1.02-1.12, P(meta)  = 0.012). In 599 Chinese non-diabetic subjects, rs1408888 was linearly associated with systolic blood pressure and insulin resistance. In a case-control cohort (n = 953/953), rs1408888 was associated with an OR of 1.54(1.07-2.22, P = 0.019) for CVD in type 2 diabetes. In an autopsy series of 173 non-diabetic cases, TT genotype of rs1408888 was associated with an OR of 3.31(1.19-9.19, P = 0.0214) and 3.27(1.25-11.07, P = 0.0184) for coronary heart disease (CHD) and coronary arteriosclerosis. Bioinformatics analysis revealed that rs1408888 lies within regulatory elements of DACH1 implicated in islet development and insulin secretion. The T allele of rs1408888 of DACH1 was associated with YOD, prediabetes and CVD in Chinese.

Background: DNA methylation plays crucial roles in epigenetic gene regulation in normal development and disease pathogenesis. Efficient and accurate quantification of DNA methylation at single base resolution can greatly advance the knowledge of disease mechanisms and be used to identify potential biomarkers. We developed an improved pipeline based on reduced representation bisulfite sequencing (RRBS) for cost-effective genome-wide quantification of DNA methylation at single base resolution. A selection of two restriction enzymes (TaqαI and MspI) enables a more unbiased coverage of genomic regions of different CpG densities. We further developed a highly automated software package to analyze bisulfite sequencing results from the Solexa GAIIx system., Results: With two sequencing lanes, we were able to quantify ~1.8 million individual CpG sites at a minimum sequencing depth of 10. Overall, about 76.7% of CpG islands, 54.9% of CpG island shores and 52.2% of core promoters in the human genome were covered with at least 3 CpG sites per region., Conclusions: With this new pipeline, it is now possible to perform whole-genome DNA methylation analysis at single base resolution for a large number of samples for understanding how DNA methylation and its changes are involved in development, differentiation, and disease pathogenesis.

Background: Steatosis and steatohepatitis have been associated with increased morbidity and mortality after liver resection. Our objective was to determine the effect of a preoperative calorie-restricted diet on steatosis and steatohepatitis in patients undergoing liver resection., Methods: We studied 111 consecutive patients who had major elective hepatic resections. More than 90% of the patients had cancer resections. The mean body mass index was 27.2; 32% had a body mass index ≥30. A week-long calorie- and fat-restricted diet was instituted in the most recent patient group (n = 51). We retrospectively evaluated steatosis and steatohepatitis in the diet and no-diet control groups. Clinical outcomes of the 2 groups, including complications and blood loss, were compared., Results: The preoperative diet patients had less steatosis (15.7% vs 25.5% of hepatocytes containing fat, P = .05) than the nondiet controls. A lower percentage of patients in the diet group had steatohepatitis than in the nondiet group (15% vs 27%, P =.02). Preoperative diet patients had less mean intraoperative blood loss than nondiet patients (600 mL vs 906 mL, P = .002). There was no difference in overall or infectious complications between the groups., Conclusion: We have shown for the first time that short-term calorie restriction before liver resection significantly reduces both hepatic steatosis and steatohepatitis. Dietary modification also was associated with decreased intraoperative blood loss. This intervention is easily instituted; therefore, it is clinically feasible., (Copyright © 2013 Mosby, Inc. All rights reserved.)

Type 2 diabetes (T2D) is a complex disease characterized by beta cell dysfunctions. Islet amyloid polypeptide (IAPP) is highly conserved and co-secreted with insulin with over 40% of autopsy cases of T2D showing islet amyloid formation due to IAPP aggregation. Dysregulation in IAPP processing, stabilization and degradation can cause excessive oligomerization with beta cell toxicity. Previous studies examining genetic associations of pathways implicated in IAPP metabolism have yielded conflicting results due to small sample size, insufficient interrogation of gene structure and gene-gene interactions. In this multi-staged study, we screened 89 tag single nucleotide polymorphisms (SNPs) in 6 candidate genes implicated in IAPP metabolism and tested for independent and joint associations with T2D and beta cell dysfunctions. Positive signals in the stage-1 were confirmed by de novo and in silico analysis in a multi-centre unrelated case-control cohort. We examined the association of significant SNPs with quantitative traits in a subset of controls and performed bioinformatics and relevant functional analyses. Amongst the tag SNPs, rs1583645 in carboxypeptidase E (CPE) and rs6583813 in insulin degrading enzyme (IDE) were associated with 1.09 to 1.28 fold increased risk of T2D (P Meta = 9.4×10(-3) and 0.02 respectively) in a meta-analysis of East Asians. Using genetic risk scores (GRS) with each risk variant scoring 1, subjects with GRS≥3 (8.2% of the cohort) had 56% higher risk of T2D than those with GRS = 0 (P = 0.01). In a subcohort of control subjects, plasma IAPP increased and beta cell function index declined with GRS (P = 0.008 and 0.03 respectively). Bioinformatics and functional analyses of CPE rs1583645 predicted regulatory elements for chromatin modification and transcription factors, suggesting differential DNA-protein interactions and gene expression. Taken together, these results support the importance of dysregulation of IAPP metabolism in T2D in East Asians.

Down syndrome (DS), commonly caused by an extra copy of chromosome 21 (chr21), occurs in approximately one out of 700 live births. Precisely how an extra chr21 causes over 80 clinically defined phenotypes is not yet clear. Reduced representation bisulfite sequencing (RRBS) analysis at single base resolution revealed DNA hypermethylation in all autosomes in DS samples. We hypothesize that such global hypermethylation may be mediated by down-regulation of TET family genes involved in DNA demethylation, and down-regulation of REST/NRSF involved in transcriptional and epigenetic regulation. Genes located on chr21 were up-regulated by an average of 53% in DS compared to normal villi, while genes with promoter hypermethylation were modestly down-regulated. DNA methylation perturbation was conserved in DS placenta villi and in adult DS peripheral blood leukocytes, and enriched for genes known to be causally associated with DS phenotypes. Our data suggest that global epigenetic changes may occur early in development and contribute to DS phenotypes., Competing Interests: The authors have declared that no competing interests exist.

We performed a genome-wide association study (GWAS) and a multistage meta-analysis of type 2 diabetes (T2D) in Punjabi Sikhs from India. Our discovery GWAS in 1,616 individuals (842 case subjects) was followed by in silico replication of the top 513 independent single nucleotide polymorphisms (SNPs) (P < 10⁻³) in Punjabi Sikhs (n = 2,819; 801 case subjects). We further replicated 66 SNPs (P < 10⁻⁴) through genotyping in a Punjabi Sikh sample (n = 2,894; 1,711 case subjects). On combined meta-analysis in Sikh populations (n = 7,329; 3,354 case subjects), we identified a novel locus in association with T2D at 13q12 represented by a directly genotyped intronic SNP (rs9552911, P = 1.82 × 10⁻⁸) in the SGCG gene. Next, we undertook in silico replication (stage 2b) of the top 513 signals (P < 10⁻³) in 29,157 non-Sikh South Asians (10,971 case subjects) and de novo genotyping of up to 31 top signals (P < 10⁻⁴) in 10,817 South Asians (5,157 case subjects) (stage 3b). In combined South Asian meta-analysis, we observed six suggestive associations (P < 10⁻⁵ to < 10⁻⁷), including SNPs at HMG1L1/CTCFL, PLXNA4, SCAP, and chr5p11. Further evaluation of 31 top SNPs in 33,707 East Asians (16,746 case subjects) (stage 3c) and 47,117 Europeans (8,130 case subjects) (stage 3d), and joint meta-analysis of 128,127 individuals (44,358 case subjects) from 27 multiethnic studies, did not reveal any additional loci nor was there any evidence of replication for the new variant. Our findings provide new evidence on the presence of a population-specific signal in relation to T2D, which may provide additional insights into T2D pathogenesis.

Background: Anorexia nervosa is an eating disorder that is often preceded by excessive physical activity. As such, exercise is not often prescribed in the clinical management of individuals with anorexia nervosa., Objective: To examine the effects of supervised exercise training in patients with anorexia nervosa., Data Sources: Five databases were searched from their inception to Week 14 of 2011 using the subject headings 'anorexia' and 'exercise' to identify relevant studies., Eligibility Criteria: PRISMA guidelines were followed. Studies that investigated the effects of inclusion of supervised exercise training in clinical management with usual management in patients diagnosed with anorexia nervosa were included in this review. Case reports were excluded., Data Extraction and Synthesis: Two reviewers independently extracted data using a standardised assessment form. Quality assessment was rated for the controlled trials and single-group studies using the PEDro scale and Downs and Black scale, respectively. Fixed or random effect approaches were used to determine effect size, depending on the heterogeneity of the studies., Results: Pooled randomised controlled trials and quasi-randomised studies showed no significant effect of supervised exercise training on selected anthropometric measurements, while the single-group studies showed significant improvement in weight and body fat. Although Short Form-36 revealed no training effect, distorted feelings about food and exercise were reduced. Cardiovascular fitness also improved with no decrease in weight., Limitations: Heterogeneity of exercise training programmes, small sample size (n≤20) for 67% of the trials, and inability to exclude publication bias., Conclusions: Inclusion of supervised exercise training in the comprehensive management of patients with anorexia nervosa appears to be safe, as no detrimental effect was observed in anthropometry. Strength and cardiovascular fitness were also shown to improve., (Copyright © 2012 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.)

Aims/hypothesis: A Japanese study had earlier reported that KCNQ1 single-nucleotide polymorphisms (SNPs) may be associated with diabetic nephropathy. To further investigate this finding, we analysed three SNPs, rs2237895, rs2237897 and rs2283228, within the KCNQ1 locus for association with albuminuria among Chinese type 2 diabetic patients residing in Singapore. Albuminuria was analysed as both categorical (micro- and macroalbuminuria) and continuous traits (log(e) albumin/creatinine ratio [ACR])., Methods: A total of 752 Chinese patients with type 2 diabetes were included in the study. Albuminuria was determined by ACR using spot urine samples, and renal function was approximated using estimated GFR. Genotyping was performed using invader and Taqman assays as appropriate. Multivariate regression analyses were used to analyse the associations between SNPs and renal traits., Results: Significant associations were detected between rs2283228 and macroalbuminuria (p < 0.001, corrected p < 0.01), as well as log(e) ACR (p = 0.004, corrected p = 0.036) after multiple hypothesis testing and adjustment for potential confounding. A trend of increasing OR was observed with increasing severity of diabetic nephropathy (low and high microalbuminuria, macroalbuminuria). rs2237897, previously implicated in the earlier Japanese study, was also associated with macroalbuminuria, but this finding did not remain significant after correction for multiple testing. Meta-analyses of the Chinese and Japanese studies revealed both SNPs to be significantly associated with macroalbuminuria., Conclusions/interpretation: Together with the previous Japanese study, our findings support the hypothesis that, in addition to KCNQ1 being an established type 2 diabetes gene, genetic variation in this gene may contribute to susceptibility to diabetic nephropathy in East Asians.

Background: We tested for associations between estimated glomerular filtration rate (eGFR) and retinol-binding protein 4 (RBP4) haplotypes found on human chromosome 10q23. This locus had been linked to eGFR in a previous linkage scan in patients with Type 2 diabetes mellitus., Methods: We analysed 469 patients with Type 2 diabetes and 174 normoalbuminuric controls for associations between RBP4 haplotypes and eGFR. For comparison with controls, 295 cases with proteinuria/end-stage renal disease were tested for associations with advanced diabetic nephropathy. Genotyping was performed using high-resolution DNA melting assays. Data analysis was performed using the haplo.stats package., Results: Genetic variations in RBP4 were not associated with advanced diabetic nephropathy. Compared with the common A/G/G/C haplotype, C/A/A/C carriers among the normoalbuminuric controls had higher eGFR values among younger patients but lower eGFRs among the older patients (effect size=2.2, P=3.3×10(-7)). Furthermore, while eGFR values were fairly consistent over the range of systolic blood pressure (SBP) values for the common haplotype, eGFR in C/A/A/C carriers increased with SBP (effect size=3.6, P=1.5×10(-2)). There was a significant interaction between the C/A/A/C haplotype and HbA1c as they affect eGFR compared to the common haplotype (effect size=2.1, P=2.1×10(-3)). Power calculations demonstrated that our study had >90% power to detect the observed interactions even while performing multiple hypotheses testing. The interaction between SBP and the C/A/A/C haplotype remained significant (P=2.8×10(-2)) even when these three haplotype-environment interactions were simultaneously estimated., Conclusion: RBP4 haplotypes may be important in genetically modulating renal function in response to environmental challenges among patients with Type 2 diabetes.

Helix-helix interactions play a central role in the folding and assembly of integral α-helical membrane proteins and are fundamentally dictated by the amino acid sequence of the TM domain. It is not surprising then that missense mutations that target these residues are often linked to disease. In this review, we focus on the molecular mechanisms through which missense mutations lead to aberrant folding and/or assembly of these proteins, and then discuss pharmacological approaches that may potentially mitigate or reverse the negative effects of these mutations. Improving our understanding of how missense mutations affect the interactions between TM α-helices will increase our capability to develop effective therapeutic approaches to counter the misassembly of these proteins and, ultimately, disease. This article is part of a Special Issue entitled: Protein Folding in Membranes., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Genome-wide association studies (GWAS) have become the preferred experimental design in exploring the genetic etiology of complex human traits and diseases. Standard SNP-based meta-analytic approaches have been utilized to integrate the results from multiple experiments. This fundamentally assumes that the patterns of linkage disequilibrium (LD) between the underlying causal variants and the directly genotyped SNPs are similar across the populations for the same SNPs to emerge with surrogate evidence of disease association. We introduce a novel strategy for assessing regional evidence of phenotypic association that explicitly incorporates the extent of LD in the region. This provides a natural framework for combining evidence from multi-ethnic studies of both dichotomous and quantitative traits that (i) accommodates different patterns of LD, (ii) integrates different genotyping platforms and (iii) allows for the presence of allelic heterogeneity between the populations. Our method can also be generalized to perform gene-based or pathway-based analyses. Applying this method on real GWAS data in type 2 diabetes (T2D) boosted the association evidence in regions well-established for T2D etiology in three diverse South-East Asian populations, as well as identified two novel gene regions and a biologically convincing pathway that are subsequently validated with data from the Wellcome Trust Case Control Consortium.

Multiple genetic loci associated with obesity or body mass index (BMI) have been identified through genome-wide association studies conducted predominantly in populations of European ancestry. We performed a meta-analysis of associations between BMI and approximately 2.4 million SNPs in 27,715 east Asians, which was followed by in silico and de novo replication studies in 37,691 and 17,642 additional east Asians, respectively. We identified ten BMI-associated loci at genome-wide significance (P < 5.0 × 10(-8)), including seven previously identified loci (FTO, SEC16B, MC4R, GIPR-QPCTL, ADCY3-DNAJC27, BDNF and MAP2K5) and three novel loci in or near the CDKAL1, PCSK1 and GP2 genes. Three additional loci nearly reached the genome-wide significance threshold, including two previously identified loci in the GNPDA2 and TFAP2B genes and a newly identified signal near PAX6, all of which were associated with BMI with P < 5.0 × 10(-7). Findings from this study may shed light on new pathways involved in obesity and demonstrate the value of conducting genetic studies in non-European populations.

Aims/hypothesis: We carried out a urinary metabolomic study to gain insight into low estimated GFR (eGFR) in patients with non-proteinuric type 2 diabetes., Methods: Patients were identified as being non-proteinuric using multiple urinalyses. Cases (n = 44) with low eGFR and controls (n = 46) had eGFR values <60 and ≥60 ml min(-1) 1.73 m(-2), respectively, as calculated using the Modification of Diet in Renal Disease formula. Urine samples were analysed by liquid chromatography/mass spectrometry (LC/MS) and GC/MS. False discovery rates were used to adjust for multiple hypotheses testing, and selection of metabolites that best predicted low eGFR status was achieved using least absolute shrinkage and selection operator logistic regression., Results: Eleven GC/MS metabolites were strongly associated with low eGFR after correction for multiple hypotheses testing (smallest adjusted p value = 2.62 × 10(-14), largest adjusted p value = 3.84 × 10(-2)). In regression analysis, octanol, oxalic acid, phosphoric acid, benzamide, creatinine, 3,5-dimethoxymandelic amide and N-acetylglutamine were selected as the best subset for prediction and allowed excellent classification of low eGFR (AUC = 0.996). In LC/MS, 19 metabolites remained significant after multiple hypotheses testing had been taken into account (smallest adjusted p value = 2.04 × 10(-4), largest adjusted p value = 4.48 × 10(-2)), and several metabolites showed stronger evidence of association relative to the uraemic toxin, indoxyl sulphate (adjusted p value = 3.03 × 10(-2)). The potential effect of confounding on the association between metabolites was excluded., Conclusions/interpretation: Our study has yielded substantial new insight into low eGFR and provided a collection of potential urinary biomarkers for its detection.

Objective: Recent genome-wide association studies (GWAS) have identified 38 obesity-associated loci among European populations. However, their contribution to obesity in other ethnicities is largely unknown., Methods: We utilised five GWAS (N=10 482) from Chinese (three cohorts, including one with type 2 diabetes and another one of children), Malay and Indian ethnic groups from Singapore. Data sets were analysed individually and subsequently in combined meta-analysis for Z-score body-mass index (BMI) associations., Results: Variants at the FTO locus showed the strongest associations with BMI Z-score after meta-analysis (P-values 1.16 × 10(-7)-7.95 × 10(-7)). We further detected associations with nine other index obesity variants close to the MC4R, GNPDA2, TMEM18, QPCTL/GIPR, BDNF, ETV5, MAP2K5/SKOR1, SEC16B and TNKS/MSRA loci (meta-analysis P-values ranging from 3.58 × 10(-4)-1.44 × 10(-2)). Three other single-nucleotide polymorphisms (SNPs) from CADM2, PTBP2 and FAIM2 were associated with BMI (P-value ≤ 0.0418) in at least one dataset. The neurotrophin/TRK pathway (P-value=0.029) was highlighted by pathway-based analysis of loci that had statistically significant associations among Singaporean populations., Conclusion: Our data confirm the role of FTO in obesity predisposition among Chinese, Malays and Indians, the three major Asian ethnic groups. We additionally detected associations for 12 obesity-associated SNPs among Singaporeans. Thus, it is likely that Europeans and Asians share some of the genetic predisposition to obesity. Furthermore, the neurotrophin/TRK signalling may have a central role for common obesity among Asians.

Background: The involvement of nephrin in controlling renal function is unclear with the literature only emphasizing its role in albuminuria. We therefore investigated the potential association between nephrinuria as evidenced by the appearance of urinary immunopositive nephrin fragments, with multiple renal traits., Methods: Western blot analysis of the urine samples from a cross-sectional study of 381 Chinese type 2 diabetic patients revealed four distinct protein fragments, indicative of nephrinuria. Albuminuria was measured in random spot urine samples using the albumin/creatinine ratio (ACR), while estimated glomerular filtration rate (eGFR) was calculated using the creatinine-based Modification of Diet in Renal Disease formula., Results: Each nephrin fragment was associated with a decline in eGFR (smallest P = 0.001). Even with the inclusion of logarithmic form of ACR (ln ACR) in the multivariate model, nephrinuria still remained significantly associated with lower eGFR (smallest P < 0.05). Nephrinuria was also strongly associated with lnACR and this finding was independent of eGFR (smallest P < 0.001). Thus, nephrinuria was independently associated with both renal traits in the form of lnACR and eGFR. Furthermore, nephrinuria was significantly associated with lower eGFR even among normoalbuminuric patients (ACR ≤ 30 mg/g) (smallest P = 0.002), potentially implicating nephrinuria in the development of normoalbuminuric renal insufficiency. Apart from the renal traits under investigation, the presence of nephrinuria did not associate with other patient clinical characteristics., Conclusions: Nephrinuria was associated with multiple renal traits in type 2 diabetes even in normoalbuminuric patients who are traditionally perceived as having a low risk of chronic kidney disease.