Use Of Diagnostic Markers Research Articles

Proteomic and lipidomic biomarkers in the diagnosis and progression of inflammatory bowel disease - a review.

There is an increasing prevalence of inflammatory bowel disease (IBD) and to date, no effective treatment has been developed and the exact etiology of this disease remains unknown. Nevertheless, a growing number of proteomic and lipidomic studies have identified certain proteins and lipids which can be used successfully in patients to improve diagnoses and monitoring of treatment. We have focused on the applications of proteins and lipids for IBD diagnostics, including differentiation of Crohn's disease (CD) and ulcerative colitis (UC), treatment monitoring, monitoring of clinical state, likelihood of relapse, and their potential for novel targeted treatments. Analysis of protein and lipid profiles can: improve the availability and use of diagnostic markers; improve understanding of the pathomechanisms of IBD, for example, several studies have implicated platelet dysfunction (PF4), autoimmune responses (granzyme B, perforin), and abnormal metabolism (arachidonic acid pathways); aid in monitoring patient health; and improve therapeutics (experimental phosphatidylcholine therapy has been shown to result in an improvement in intestinal condition). Despite the enormous progress of proteomics and lipidomics in recent years and the development of new technologies, further research is needed to select some of the most sensitive and specific markers applicable in diagnosing and treating IBD.

Training population selection and use of fixed effects to optimize genomic predictions in a historical USA winter wheat panel

Key messageThe optimization of training populations and the use of diagnostic markers as fixed effects increase the predictive ability of genomic prediction models in a cooperative wheat breeding panel.Plant breeding programs often have access to a large amount of historical data that is highly unbalanced, particularly across years. This study examined approaches to utilize these data sets as training populations to integrate genomic selection into existing pipelines. We used cross-validation to evaluate predictive ability in an unbalanced data set of 467 winter wheat (Triticum aestivum L.) genotypes evaluated in the Gulf Atlantic Wheat Nursery from 2008 to 2016. We evaluated the impact of different training population sizes and training population selection methods (Random, Clustering, PEVmean and PEVmean1) on predictive ability. We also evaluated inclusion of markers associated with major genes as fixed effects in prediction models for heading date, plant height, and resistance to powdery mildew (caused by Blumeria graminis f. sp. tritici). Increases in predictive ability as the size of the training population increased were more evident for Random and Clustering training population selection methods than for PEVmean and PEVmean1. The selection methods based on minimization of the prediction error variance (PEV) outperformed the Random and Clustering methods across all the population sizes. Major genes added as fixed effects always improved model predictive ability, with the greatest gains coming from combinations of multiple genes. Maximum predictabilities among all prediction methods were 0.64 for grain yield, 0.56 for test weight, 0.71 for heading date, 0.73 for plant height, and 0.60 for powdery mildew resistance. Our results demonstrate the utility of combining unbalanced phenotypic records with genome-wide SNP marker data for predicting the performance of untested genotypes.

High-Throughput Analysis of Global DNA Methylation Using Methyl-Sensitive Digestion.

DNA methylation is a major regulatory process of gene transcription, and aberrant DNA methylation is associated with various diseases including cancer. Many compounds have been reported to modify DNA methylation states. Despite increasing interest in the clinical application of drugs with epigenetic effects, and the use of diagnostic markers for genome-wide hypomethylation in cancer, large-scale screening systems to measure the effects of drugs on DNA methylation are limited. In this study, we improved the previously established fluorescence polarization-based global DNA methylation assay so that it is more suitable for application to human genomic DNA. Our methyl-sensitive fluorescence polarization (MSFP) assay was highly repeatable (inter-assay coefficient of variation = 1.5%) and accurate (r2 = 0.99). According to signal linearity, only 50–80 ng human genomic DNA per reaction was necessary for the 384-well format. MSFP is a simple, rapid approach as all biochemical reactions and final detection can be performed in one well in a 384-well plate without purification steps in less than 3.5 hours. Furthermore, we demonstrated a significant correlation between MSFP and the LINE-1 pyrosequencing assay, a widely used global DNA methylation assay. MSFP can be applied for the pre-screening of compounds that influence global DNA methylation states and also for the diagnosis of certain types of cancer.

The use of biomarkers for the etiologic diagnosis of MCI in Europe: An EADC survey

We investigated the use of Alzheimer's disease (AD) biomarkers in European Alzheimer's Disease Consortium centers and assessed their perceived usefulness for the etiologic diagnosis of mild cognitive impairment (MCI). We surveyed availability, frequency of use, and confidence in diagnostic usefulness of markers of brain amyloidosis (amyloid positron emission tomography [PET], cerebrospinal fluid [CSF] Aβ42) and neurodegeneration (medial temporal atrophy [MTA] on MR, fluorodeoxyglucose positron emission tomography [FDG-PET], CSF tau). The most frequently used biomarker is visually rated MTA (75% of the 37 responders reported using it “always/frequently”) followed by CSF markers (22%), FDG-PET (16%), and amyloid-PET (3%). Only 45% of responders perceive MTA as contributing to diagnostic confidence, where the contribution was rated as “moderate”. Seventy-nine percent of responders felt “very/extremely” comfortable delivering a diagnosis of MCI due to AD when both amyloid and neuronal injury biomarkers were abnormal (P < .02 versus any individual biomarker). Responders largely agreed that a combination of amyloidosis and neuronal injury biomarkers was a strongly indicative AD signature.

Abattoir survey of abomasal lesions associated with ostertagiosis in adult cattle

Infections with Ostertagia ostertagi in adult cattle have been studied through longitudinal abattoir surveys of cull cows (Agneessens and others 2000, Borgsteede and others 2000, Murphy and others 2006), and...

Optimising repeat prostate biopsy decisions and procedures

What's known on the subject? and What does the study add? Due to the fear of missing clinically significant cancer, it is often uncertain whether a repeat biopsy should be performed in men with ≥ 1 prior negative prostate biopsies but persistent suspicion of prostate cancer. However, the repeat biopsy may again be negative and a biopsy may be associated with anxiety, discomfort and complications (resulting in hospitalisation in 4.1% of men). This review discusses strategies to optimise repeat biopsy procedures in order to better predict the biopsy outcome. Optimising repeat biopsy procedures include adjusting the location and number of cores and the use of MRI to detect suspicious areas. The use of diagnostic markers, e.g. (Prostate CAncer) gene 3, which is predictive of biopsy outcome, can aid in guiding repeat biopsy decisions and reduce the number of unnecessary and uncomfortable biopsies. To review strategies to optimise repeat biopsy procedures and to better predict the biopsy outcome. As it is often uncertain whether a repeat biopsy should be performed in men with ≥ 1 previous negative prostate biopsies but persistent suspicion of prostate cancer. The repeat biopsy may also be negative and a biopsy may be associated with anxiety, discomfort and occasionally (severe) complications. A search in PubMed was performed to find English language original and review articles related to repeat prostate biopsies. Strategies to optimise repeat biopsy procedures include applying the appropriate indications and adjusting the location and number of biopsy cores. The PROGENSA™ Prostate CAncer gene 3 (PCA3) Assay is a highly prostate cancer-specific test. A higher PCA3 Score corresponds with an increased probability of a positive repeat biopsy and including the PCA3 Score in multivariate models significantly increased their predictive accuracy for predicting repeat biopsy outcome. The PCA3 Score seems also to be predictive of future biopsy outcome. In clinical practice it is often uncertain whether a prostate biopsy should be repeated or not. Optimising repeat biopsy procedures and the use of diagnostic markers, such as PCA3, can increase the probability of a positive repeat biopsy and reduce the number of unnecessary and uncomfortable biopsies.

Use of diagnostic markers to monitor fasciolosis and gastrointestinal nematodes on an organic dairy farm

A 12-month study was conducted to assess and monitor gastrointestinal tract nematodes and liver fluke in cohorts of cattle on a Scottish organic dairy farm. Various diagnostic markers for helminth...

Considerations on the use of diagnostic markers in management of patients with bladder cancer

Although the incidence of bladder cancer lags behind that of other malignancies, it has the highest rate of recurrence among all US malignancies. The propensity to recur and the possibility of disease progression require aggressive surveillance, which has led to bladder cancer being the most expensive malignancy to treat in the United States. Current non-tailored surveillance strategies applied uniformly to all patients with non-muscle invasive bladder cancer may impose excessive diagnostic burden on patients with low-grade disease for the sake of adequately monitoring those with potentially aggressive disease. The recent identification of several bladder cancer tumor markers has led to attempts to determine if these markers can enhance existing surveillance strategies by possibly tailoring surveillance strategies to individual patients. These markers may result in cost savings by properly identifying which patients can safely delay cystoscopy and which patients require more periodic assessment. Furthermore, we may be able to identify those patients with "occult disease" that require more invasive assessments and earlier aggressive treatment. We will review diagnostic considerations in the use of these markers for the detection of recurrent bladder cancer and summarize the benefits and costs of the more promising bladder cancer markers.

New Insights Into the Diagnostic Accuracy of Complexed and Total Prostate Specific Antigen Using Discordance Analysis Characteristics

Comparison of diagnostic performances of total and complexed prostate specific antigen (tPSA, cPSA) using ROC curve analysis resulted in controversial interpretations. To overcome the biases due to analysis of subgroups selected by concentration ranges of only 1 marker the novel approach named discordance analysis characteristics is presented. DAC method includes only patients who are discordantly categorized by the tests under investigation using cutoffs with identical sensitivity. Within those patients parameters describing diagnostic accuracy are calculated. The systematic nature of the results is confirmed by varying the cutoffs. DAC method is demonstrated considering the example of cPSA and tPSA data from 2 prostate cancer studies with a total of 1,624 patients (study A and B, of 283 and 565 with as well as 417 and 359 men without prostate cancer, respectively). PSA concentrations were measured using the Bayer assays. The DAC method proved that cPSA outperformed tPSA regarding the criteria diagnostic specificity and positive predictive value. Among discordantly tested patients cPSA detected patients with an about 2-fold higher risk to have prostate cancer and with a 3.6 to 5.5-fold better specificity than tPSA. Using cPSA instead of tPSA more than 10% of unnecessary biopsies could be avoided in the tPSA range of 3 to 5 ng/ml. The superior diagnostic performance of cPSA in comparison with tPSA warrants the recommendation to use cPSA as initial test in prostate cancer diagnostics. The DAC method is generally recommended to replace comparative ROC analyses of subgroups to evaluate the diagnostic usefulness of markers.

Generalized Covariance-Adjusted Discriminants: Perspective and Application

When discriminant analysis is used in practice for assessing the usefulness of diagnostic markers, the lack of control over covariates motivates the need for their adjustment in the analysis. This necessity for adjustment arises especially when the researcher's aim is classification based on a set of diagnostic markers and is not based on a set of covariates for which there exists known heterogeneity among the subjects with respect to the groups under consideration. The traditional covariance-adjusted approach is restrictive for such applications in that they assume linear covariates and a normal distribution for the the feature vector. Further, there is no available method for variable selection in using such covariance-adjusted models. In this paper, we generalize the traditional covariance-adjusted model to a general normal and logistic model, where these generalized models not only relax the distributional assumptions on the feature vector but also allow for nonlinear covariates. Exact and asymptotic tests are also derived for the problem of variable selection for these new models. The methodology is illustrated with both simulated data and an actual data set from a psychiatric study on using the Social Rhythm Metric for patients with anxiety disorders.

Confidence Intervals for the Generalized ROC Criterion

Receiver operating characteristic (ROC) curves are frequently used to assess the usefulness of diagnostic markers. When several diagnostic markers are available, they can be combined by a best linear combination: that is, when the area under the ROC curve of this combination is maximized among all possible linear combinations. This maximal area is the generalized ROC criterion, which provides a measure of how effective the combination of the markers is. This criterion needs to be estimated from the data, and is usually evaluated against single markers. In the present paper, we provide confidence intervals for the generalized ROC criterion under the assumption of homogeneous covariance matrices, derive an approximation for the heterogeneous covariance matrices case, and evaluate the approximation via a simulation study. Finally, we present an illustrative example.

1 A clinical and neurochemical approach to the use of diagnostic markers for Alzheimer's disease

1 A clinical and neurochemical approach to the use of diagnostic markers for Alzheimer's disease

Linear Combinations of Multiple Diagnostic Markers

Abstract The receiver operating characteristic (ROC) curve is a simple and meaningful measure to assess the usefulness of diagnostic markers. To use the information carried by multiple markers, we note that Fisher's linear discriminant function provides a linear combination of markers to maximize the sensitivity over the entire specificity range uniformly under the multivariate normal distribution model with proportional covariance matrices. With no restriction on covariance matrices, we also provide a solution of the best linear combination of markers in the sense that the area under the ROC curve of this combination is maximized among all possible linear combinations. We illustrate both situations discussed in the article with a cancer clinical trial data.