Analytical Variation Between Two Different TSH Reagents from the Same Manufacturer.

Thyroid stimulating hormone (TSH) immunoassays are known for giving varying results based on the platform of testing and the generation of kit used. It is generally expected that the results should not vary to affect clinical diagnosis and management. We aimed to perform method comparison study between two TSH assays by the same manufacturer Siemens Healthineers. Results show that there is a large proportional error between the assays with a bias of -3.71mIu/L indicating that TSH assay gives higher values for TSH for the same patient as measured against the TSH3-Ultra kit. This can affect interpretation of results leading to false increase in patients categorized under hypothyroidism and subclinical hypothyroidism. We strongly suggest, to prevent errors in clinical evaluation of a patient with thyroid dysfunction, validation of the performance of the assay and method comparison should be performed in-house.

Detection and accurate false discovery rate control of differentially methylated regions from whole genome bisulfite sequencing.

With recent advances in sequencing technology, it is now feasible to measure DNA methylation at tens of millions of sites across the entire genome. In most applications, biologists are interested in detecting differentially methylated regions, composed of multiple sites with differing methylation levels among populations. However, current computational approaches for detecting such regions do not provide accurate statistical inference. A major challenge in reporting uncertainty is that a genome-wide scan is involved in detecting these regions, which needs to be accounted for. A further challenge is that sample sizes are limited due to the costs associated with the technology. We have developed a new approach that overcomes these challenges and assesses uncertainty for differentially methylated regions in a rigorous manner. Region-level statistics are obtained by fitting a generalized least squares regression model with a nested autoregressive correlated error structure for the effect of interest on transformed methylation proportions. We develop an inferential approach, based on a pooled null distribution, that can be implemented even when as few as two samples per population are available. Here, we demonstrate the advantages of our method using both experimental data and Monte Carlo simulation. We find that the new method improves the specificity and sensitivity of lists of regions and accurately controls the false discovery rate.

Use of Partial Least Squares improves the efficacy of removing unwanted variability in differential expression analyses based on RNA-Seq data.

RNA-Seq technology has revolutionized the face of gene expression profiling by generating read count data measuring the transcript abundances for each queried gene on multiple experimental subjects. But on the downside, the underlying technical artefacts and hidden biological profiles of the samples generate a wide variety of latent effects that may potentially distort the actual transcript/gene expression signals. Standard normalization techniques fail to correct for these hidden variables and lead to flawed downstream analyses. In this work I demonstrate the use of Partial Least Squares (built as an R package 'SVAPLSseq') to correct for the traces of extraneous variability in RNA-Seq data. A novel and thorough comparative analysis of the PLS based method is presented along with some of the other popularly used approaches for latent variable correction in RNA-Seq. Overall, the method is found to achieve a substantially improved estimation of the hidden effect signatures in the RNA-Seq transcriptome expression landscape compared to other available techniques.

Spurious hyperphosphatemia in a case of multiple myeloma.

A 50 year old male was admitted in our hospital with anemia and impaired renal function. He was subsequently found to have extremely elevated serum phosphate level (24 mg/dL, reference interval: 2.5-4.5 mg/dL) with normal serum calcium when assayed on a Beckman Coulter AU 480(®) analyser. Clinico-biochemical discrepancy led to the suspicion of spurious hyperphosphatemia. Serum total protein was grossly elevated with gross reversal of albumin to globulin ratio. Serum electrophoresis revealed a large M band and was confirmed as Ig G-Kappa type on immunofixation. Subsequently a bone marrow aspiration biopsy confirmed the diagnosis of multiple myeloma. The patient serum was then reassayed for phosphate on a Vitros(®) 250 Dry Chemistry platform and the result was within normal reference interval. Paraproteinemias are a common cause of analytical interference in clinical biochemistry laboratories and as multilayered film technology platforms like Vitros(®) assay most routine analytes on a protein free filtrate they are unaffected by paraprotein interference. Clinically discordant patient results should always be interpreted keeping such interferences in mind.

svapls: an R package to correct for hidden factors of variability in gene expression studies.

BACKGROUND: Hidden variability is a fundamentally important issue in the context of gene expression studies. Collected tissue samples may have a wide variety of hidden effects that may alter their transcriptional landscape significantly. As a result their actual differential expression pattern can be potentially distorted, leading to inaccurate results from a genome-wide testing for the important transcripts. RESULTS: We present an R package svapls that can be used to identify several types of unknown sample-specific sources of heterogeneity in a gene expression study and adjust for them in order to provide a more accurate inference on the original expression pattern of the genes over different varieties of samples. The proposed method implements Partial Least Squares regression to extract the hidden signals of sample-specific heterogeneity in the data and uses them to find the genes that are actually correlated with the phenotype of interest. We also compare our package with three other popular softwares for testing differential gene expression along with a detailed illustration on the widely popular Golub dataset. Results from the sensitivity analyes on simulated data with widely different hidden variation patterns reveal the improved detection power of our R package compared to the other softwares along with reasonably smaller error rates. Application on the real-life dataset exhibits the efficacy of the R package in detecting potential batch effects from the dataset. CONCLUSIONS: Overall, Our R package provides the user with a simplified framework for analyzing gene expression data with a wide range of hidden variation patterns and delivering a differential gene expression analysis with substantially improved power and accuracy.The R package svapls is freely available at http://cran.r-project.org/web/packages/svapls/index.html.

Surrogate variable analysis using partial least squares (SVA-PLS) in gene expression studies.

MOTIVATION: In a typical gene expression profiling study, our prime objective is to identify the genes that are differentially expressed between the samples from two different tissue types. Commonly, standard analysis of variance (ANOVA)/regression is implemented to identify the relative effects of these genes over the two types of samples from their respective arrays of expression levels. But, this technique becomes fundamentally flawed when there are unaccounted sources of variability in these arrays (latent variables attributable to different biological, environmental or other factors relevant in the context). These factors distort the true picture of differential gene expression between the two tissue types and introduce spurious signals of expression heterogeneity. As a result, many genes which are actually differentially expressed are not detected, whereas many others are falsely identified as positives. Moreover, these distortions can be different for different genes. Thus, it is also not possible to get rid of these variations by simple array normalizations. This both-way error can lead to a serious loss in sensitivity and specificity, thereby causing a severe inefficiency in the underlying multiple testing problem. In this work, we attempt to identify the hidden effects of the underlying latent factors in a gene expression profiling study by partial least squares (PLS) and apply ANCOVA technique with the PLS-identified signatures of these hidden effects as covariates, in order to identify the genes that are truly differentially expressed between the two concerned tissue types. RESULTS: We compare the performance of our method SVA-PLS with standard ANOVA and a relatively recent technique of surrogate variable analysis (SVA), on a wide variety of simulation settings (incorporating different effects of the hidden variable, under situations with varying signal intensities and gene groupings). In all settings, our method yields the highest sensitivity while maintaining relatively reasonable values for the specificity, false discovery rate and false non-discovery rate. Application of our method to gene expression profiling for acute megakaryoblastic leukemia shows that our method detects an additional six genes, that are missed by both the standard ANOVA method as well as SVA, but may be relevant to this disease, as can be seen from mining the existing literature.

Effects of biaxial oscillatory shear stress on endothelial cell proliferation and morphology.

Wall shear stress (WSS) on anchored cells affects their responses, including cell proliferation and morphology. In this study, the effects of the directionality of pulsatile WSS on endothelial cell proliferation and morphology were investigated for cells grown in a Petri dish orbiting on a shaker platform. Time and location dependent WSS was determined by computational fluid dynamics (CFD). At low orbital speed (50 rpm), WSS was shown to be uniform (0-1 dyne/cm(2)) across the bottom of the dish, while at higher orbital speed (100 and 150 rpm), WSS remained fairly uniform near the center and fluctuated significantly (0-9 dyne/cm(2)) near the side walls of the dish. Since WSS on the bottom of the dish is two-dimensional, a new directional oscillatory shear index (DOSI) was developed to quantify the directionality of oscillating shear. DOSI approached zero for biaxial oscillatory shear of equal magnitudes near the center and approached one for uniaxial pulsatile shear near the wall, where large tangential WSS dominated a much smaller radial component. Near the center (low DOSI), more, smaller and less elongated cells grew, whereas larger cells with greater elongation were observed in the more uniaxial oscillatory shear (high DOSI) near the periphery of the dish. Further, cells aligned with the direction of the largest component of shear but were randomly oriented in low magnitude biaxial shear. Statistical analyses of the individual and interacting effects of multiple factors (DOSI, shear magnitudes and orbital speeds) showed that DOSI significantly affected all the responses, indicating that directionality is an important determinant of cellular responses.

Correlation between lipid peroxidation-induced TBARS level and disease severity in obsessive-compulsive disorder.

Oxidative stress is thought to play an important role in several neuropsychiatric diseases including obsessive-compulsive disorder (OCD). Thiobarbituric acid reacting substances (TBARS) are products formed as a result of free radical induced lipid peroxidation in the human body. Our study investigated the correlation between TBARS and the clinical severity of OCD as indicated by the Yale Brown Obsessive Compulsive Scale (YBOCS). Serum TBARS was estimated in thirty nine newly diagnosed drug free OCD patients and thirty three disease free control subjects. Mean values for serum TBARS were found to be significantly higher (P < 0.001) in cases than in controls (5.85 nmol/ml and 3.90 nmol/ml with an SD of 0.56 and 0.81 respectively). A strong positive correlation (rs = 0.757, p < 0.01) between the lipid peroxidation marker TBARS and the disease severity indicator YBOCS was found among cases. Significant positive correlation was also found between TBARS and the obsessive and compulsive subscales of YBOCS. These findings were in tune with previous studies, which suggested oxidative stress induced increased free radical generation in the OCD patients. Our findings may help in understanding the development and progress of OCD and the treatment of patients of OCD in future.

Study of oxidative stress in obsessive compulsive disorder in response to treatment with Fluoxetine.

Oxidative stress has been found to play important role in several neuropsychiatric diseases including Obsessive Compulsive Disorder. A longitudinal case control study was conducted to evaluate the oxidative stress in 30 newly diagnosed obsessive compulsive disorder patients and same number of control patients. Serum thiobarbituric acid reacting substances, plasma ascorbate were assessed to evaluate oxidative stress and Yale Brown obsessive compulsive scale for disease severity before and after treatment with Fluoxetine at the average dosage of 40 mg/day. Improvement in Yale Brown obsessive compulsive scale score by about 43% after 12 weeks treatment was associated with significantly decreased thiobarbituric acid reacting substances and increased plasma ascorbate values (p < 0.05). The newly diagnosed obsessive compulsive disorder patients had higher serum thiobarbituric acid reacting substances as well as a lower plasma ascorbate levels than the control population. Thus, the present study suggested a significant role of oxidative stress in obsessive compulsive disorder and showed that a successful treatment with Fluoxetine not only improves the clinical scenario but also reduces the oxidative stress that may further improve the prognosis of the disease.

Impact of Bi-Axial Shear on Atherogenic Gene Expression by Endothelial Cells.

This study demonstrated the effects of the directionality of oscillatory wall shear stress (WSS) on proliferation and proatherogenic gene expression (I-CAM, E-Selectin, and IL-6) in the presence of inflammatory mediators leukotriene B4 (LTB4) and bacterial lipopolysaccharide (LPS) from endothelial cells grown in an orbiting culture dish. Computational fluid dynamics (CFD) was applied to quantify the flow in the dish, while an analytical solution representing an extension of Stokes second problem was used for validation. Results indicated that WSS magnitude was relatively constant near the center of the dish and oscillated significantly (0-0.9 Pa) near the side walls. Experiments showed that LTB4 dominated the shear effects on cell proliferation and area. Addition of LPS didn't change proliferation, but significantly affected cell area. The expression of I-CAM1, E-Selectin and IL-6 were altered by directional oscillatory shear index (DOSI, a measure of the biaxiality of oscillatory shear), but not shear magnitude. The significance of DOSI was further reinforced by the strength of its interactions with other atherogenic factors. Hence, directionality of shear appears to be an important factor in regulating gene expression and provides a potential explanation of the propensity for increased vascular lesions in regions in the arteries with oscillating biaxial flow.

Measurement of serum-phosphate concentration in immunoglobulin G monoclonal gammopathy after PEG-precipitation.

INTRODUCTION: Spurious hyperphosphatemia is a relatively common phenomenon in patients with monoclonal gammopathy which can compromise patient safety. A cost-effective routine method is desirable for laboratories to reduce or eliminate the protein interference. METHODS: A protein free sample was obtained after precipitation with PEG-6000 (polyethylene glycol). S-phosphate concentration was measured with routine wet chemistry method in normal and monoclonal gammopathy samples before and after precipitation. Monoclonal samples were also measured by dry chemistry that includes an ultrafiltration step. The protein pattern before and after precipitation was checked by electrophoresis. RESULTS: No effect of PEG precipitation on S-phosphate concentration was demonstrated in normal serum. After PEG precipitation of proteins in monoclonal gammopathies serum wet chemistry gave the same results as dry chemistry i.e. after ultrafiltration. CONCLUSION: PEG precipitation of proteins offers a cost-effective method to eliminate protein interferences in monoclonal gammopathies.

Interference of the Hope Hemoglobin With Hemoglobin A1c Results.

Hemoglobin A1c (HbA1c) is now considered to be the marker of choice in diagnosis and management of diabetes mellitus, based on the results of certain landmark clinical trials. Herein, we report the case of a 52-year-old ethnic Southeast Asian Indian man with impaired glucose tolerance whose glycated hemoglobin (ie, HbA1c) levels, as measured via Bio-Rad D10 high-performance liquid chromatography (HPLC) and Roche Tina-quant immunoassay were 47.8% and 44.0%, respectively. No variant hemoglobin (Hb) peak was observed via the D10 chromatogram. We assayed the patient specimen on the Sebia MINICAP capillary electrophoresis platform; the HbA1c level was 6.8%, with a large variant Hb peak of 42.0%. This finding suggested the possible presence of the heterozygous Hb Hope, which can result in spuriously elevated HbA1c results on HPLC and turbidimetric immunoassays. Although the capillary electrophoresis system was able to identify the variant, the A1c results should not be considered accurate due to overlapping of the variant and adult Hb peaks on the electrophoretogram reading. Hb Hope is usually clinically silent but can present such analytical challenges. Through this case study, we critically discuss the limitations of various HbA1c assay methods, highlighting the fact that laboratory professionals need to be aware of occurrences of Hb Hope, to help ensure patient safety.