Assessing the diagnostic accuracy of a sequence of tests

We consider the assessment of the overall diagnostic accuracy of a sequence of tests (e.g. repeated screening tests). The complexity of diagnostic choices when two or more continuous tests are used in sequence is illustrated, and different approaches to reducing the dimensionality are presented and evaluated. For instance, in practice, when a single test is used repeatedly in routine screening, the same screening threshold is typically used at each screening visit. One possible alternative is to adjust the threshold at successive visits according to individual-specific characteristics. Such possibilities represent a particular slice of a receiver operating characteristic surface, corresponding to all possible combinations of test thresholds. We focus in the development and examples on the setting where an overall test is defined to be positive if any of the individual tests are positive ('believe the positive'). The ideas developed are illustrated by an example of application to screening for prostate cancer using prostate-specific antigen.     

A Bayesian hierarchical non-linear regression model in receiver operating characteristic analysis of clustered continuous diagnostic data

Receiver operating characteristic (ROC) analysis is a useful evaluative method of diagnostic accuracy. A Bayesian hierarchical nonlinear regression model for ROC analysis was developed. A validation analysis of diagnostic accuracy was conducted using prospective multi-center clinical trial prostate cancer biopsy data collected from three participating centers. The gold standard was based on radical prostatectomy to determine local and advanced disease. To evaluate the diagnostic performance of PSA level at fixed levels of Gleason score, a normality transformation was applied to the outcome data. A hierarchical regression analysis incorporating the effects of cluster (clinical center) and cancer risk (low, intermediate, and high) was performed, and the area under the ROC curve (AUC) was estimated.     

Power and sample size calculation of comparative diagnostic accuracy studies with multiple correlated test results

We consider the power and sample size calculation of diagnostic studies with normally distributed multiple correlated test results. We derive test statistics and obtain power and sample size formulas. The methods are illustrated using an example of comparison of CT and PET scanner for detecting extra-hepatic disease for colorectal cancer.     

A Model for Adjusting for Nonignorable Verification Bias in Estimation of the ROC Curve and Its Area with Likelihood‐Based Approach

Summary In estimation of the ROC curve, when the true disease status is subject to nonignorable missingness, the observed likelihood involves the missing mechanism given by a selection model. In this article, we proposed a likelihood‐based approach to estimate the ROC curve and the area under the ROC curve when the verification bias is nonignorable. We specified a parametric disease model in order to make the nonignorable selection model identifiable. With the estimated verification and disease probabilities, we constructed four types of empirical estimates of the ROC curve and its area based on imputation and reweighting methods. In practice, a reasonably large sample size is required to estimate the nonignorable selection model in our settings. Simulation studies showed that all four estimators of ROC area performed well, and imputation estimators were generally more efficient than the other estimators proposed. We applied the proposed method to a data set from research in Alzheimer's disease.     

Maximum likelihood ratio tests for comparing the discriminatory ability of biomarkers subject to limit of detection

Summary .   In this article, we consider comparing the areas under correlated receiver operating characteristic (ROC) curves of diagnostic biomarkers whose measurements are subject to a limit of detection (LOD), a source of measurement error from instruments' sensitivity in epidemiological studies. We propose and examine the likelihood ratio tests with operating characteristics that are easily obtained by classical maximum likelihood methodology.     

A comparison of likelihood ratio tests and Rao's score test for three separable covariance matrix structures

The problem of testing the separability of a covariance matrix against an unstructured variance‐covariance matrix is studied in the context of multivariate repeated measures data using Rao's score test (RST). The RST statistic is developed with the first component of the separable structure as a first‐order autoregressive (AR(1)) correlation matrix or an unstructured (UN) covariance matrix under the assumption of multivariate normality. It is shown that the distribution of the RST statistic under the null hypothesis of any separability does not depend on the true values of the mean or the unstructured components of the separable structure. A significant advantage of the RST is that it can be performed for small samples, even smaller than the dimension of the data, where the likelihood ratio test (LRT) cannot be used, and it outperforms the standard LRT in a number of contexts. Monte Carlo simulations are then used to study the comparative behavior of the null distribution of the RST statistic, as well as that of the LRT statistic, in terms of sample size considerations, and for the estimation of the empirical percentiles. Our findings are compared with existing results where the first component of the separable structure is a compound symmetry (CS) correlation matrix. It is also shown by simulations that the empirical null distribution of the RST statistic converges faster than the empirical null distribution of the LRT statistic to the limiting χ² distribution. The tests are implemented on a real dataset from medical studies.     

A new method for post Genome-Wide Association Study (GWAS) analysis of colorectal cancer in Taiwan

Recently, single nucleotide polymorphisms (SNPs) located in specific loci or genes have been identified associated with susceptibility to colorectal cancer (CRC) in Genome-Wide Association Studies (GWAS). However, in different ethnicities and regions, the genetic variations and the environmental factors can widely vary. Therefore, here we propose a post-GWAS analysis method to investigate the CRC susceptibility SNPs in Taiwan by conducting a replication analysis and bioinformatics analysis. One hundred and forty-four significant SNPs from published GWAS results were collected by a literature survey, and two hundred and eighteen CRC samples and 385 normal samples were collected for post-GWAS analysis. Finally, twenty-six significant SNPs were identified and reported as associated with susceptibility to colorectal cancer, other cancers, obesity, and celiac disease in a previous GWAS study. Functional analysis results of 26 SNPs indicate that most biological processes identified are involved in regulating immune responses and apoptosis. In addition, an efficient prediction model was constructed by applying Jackknife feature selection and ANOVA testing. As compared to another risk prediction model of CRC for European Caucasians population, which performs 0.616 of AUC by using 54 SNPs, the proposed model shows good performance in predicting CRC risk within the Taiwanese population, i.e., 0.724 AUC by using 16 SNPs. We believe that the proposed risk prediction model is highly promising for predicting CRC risk within the Taiwanese population. In addition, the functional analysis results could be helpful to explore the potential associated regulatory mechanisms that may be involved in CRC development.     

Causal associations of sarcopenia-related traits with cardiometabolic disease and Alzheimer's disease and the mediating role of insulin resistance: A Mendelian randomization study

The causal influence of sarcopenia on cardiometabolic disease and Alzheimer's disease and whether and to what extent insulin resistance plays a mediating role therein were unclear. We performed two-step, two-sample Mendelian randomization applying genetic instruments of sarcopenia-related traits based on GWASs from the UK Biobank (up to 461,026 European participants) to examine their causal associations with six cardiometabolic diseases and Alzheimer's disease extracted from large-scale European descent GWASs with adjustment for body fat percentage and physical activity, and to assess proportions of the causal effects mediated by insulin resistance. Genetic instruments of insulin resistance were derived from the GWASs by Meta-Analyses of Glucose and Insulin-related traits Consortium and Global Lipids Genetics Consortium. Each 1-SD lower grip strength, appendicular lean mass (ALM) and whole-body lean mass (WBLM), as well as lower walking pace, were causally associated with higher risks of diabetes (odds ratio [OR] range: 1.20 [95% confidence interval: 1.10–1.32] for ALM to 2.30 [1.14–4.68] for walking pace), nonalcoholic fatty liver disease ([NAFLD], 1.33 [1.08–1.64] for ALM to 2.30 [1.02–5.18] for grip strength), hypertension (1.12 [1.05–1.20] for ALM to 4.43 [2.68–7.33] for walking pace), coronary heart disease ([CHD], 1.20 [1.13–1.27] for ALM to 2.73 [1.84–4.05] for walking pace), myocardial infarction ([MI], 1.18 [1.11–1.25] for ALM to 2.47 [1.63–3.73] for walking pace), small vessel stroke (1.25 [1.15–1.37] for ALM to 1.29 [1.10–1.52] for WBLM), and Alzheimer's disease (1.10 [1.05–1.15] for ALM to 1.28 [1.19–1.38] for WBLM). These causal associations were largely independent of body fat percentage and physical activity. Insulin resistance mediated 16%–34% of the effect of grip strength and 7%–28% of the effect of ALM on diabetes, NAFLD, hypertension, CHD, and MI. The direct effect of WBLM on diabetes diminished toward null with adjustment for insulin resistance. We found no evidence that insulin resistance was on the causal pathways from walking pace to the studied disease outcomes. Causal findings from the inverse-variance weighted method were validated by sensitivity analyses. These findings support improving sarcopenia-related traits as precautions against major cardiometabolic diseases and Alzheimer's disease, with particular emphasis on insulin resistance as a target in the intervention of sarcopenia-related cardiometabolic risk.     

Spin-Labelling Studies of the Interaction of 9-Amino-1,2,3,4-Tetrahydroacridine (Tha), A Proposed Drug for the Treatment of Alzheimer's Disease,with Erythrocyte Membranes

ESR spin labels specific for skeletal proteins or cell-surface sialic acid have been used to monitor the interaction of 9-amino-1,2,3,4-tetrahydroacridine (THA) and its structural analogs with human eryth-rocyte membranes. The results suggest that THA significantly increases skeletal protein-protein interactions and may secondarily alter the physical state of the opposite side of the membrane. The fully aromatic analog of THA, 9-aminoacridine, showed even more pronounced effects on skeletal proteins than did THA. These results are discussed in relation to possible interaction sites of THA in erythrocyte ghosts and to potential mechanisms by which THA reportedly increases mental function of victims of Alzheimer's disease.     

A roadmap for investigating the role of the prion protein in depression associated with neurodegenerative disease

The physiological properties of the native, endogenous prion protein (PrP^C) is a matter of concern, due to its pleiotropic functions and links to neurodegenerative disorders and cancer. In line with our hypothesis that the basic function of PrP^C is to serve as a cell surface scaffold for the assembly of signaling modules, multiple interactions have been identified of PrP^C with signaling molecules, including neurotransmitter receptors. We recently reported evidence that PrP^C may modulate monoaminergic neurotransmission, as well as depressive-like behavior in mice. Here, we discuss how those results, together with a number of other studies, including our previous demonstration that both inflammatory and behavioral stress modulate PrP^C content in neutrophils, suggest a distributed role of PrP^C in clinical depression and inflammation associated with neurodegenerative diseases. An overarching understanding of the multiple interventions of PrP^C upon physiological events may both shed light on the pathogenesis of, as well as help the identification of novel therapeutic targets for clinical depression, Prion and Alzheimer's Diseases.     

The molecular behavior of a single β‐amyloid inside a dipalmitoylphosphatidylcholine bilayer at three different temperatures: An atomistic simulation study: Aβ interaction with DPPC: Atomistic simulation

The behavior of a single Aβ40 molecule within a dipalmitoylphosphatidylcholine (DPPC) bilayer was studied by all‐atom molecular dynamics simulations. The effect of membrane structure was investigated on Aβ40 behavior, secondary structure, and insertion depth. Simulations were performed at three temperatures (323, 310, and 300 K) to probe three different bilayer fluidities. Results show that at all above temperatures, the peptide contains two short helices, coil, bend, and turn structures. At 300 K, the peptide contains a region with β structure in C‐terminal region. Our results also show that Aβ decreases the bilayer thickness and the order of lipids in its vicinity which leads to water insertion into the bilayer and concomitant increase in the local fluidity. The peptide remains embedded in the bilayer at all temperatures, and become inserted into the bilayer up to several residues at 323 and 310 K. At 310 and 300 K, the dominant interaction energy between Aβ and bilayer changes from electrostatic to van der Waals. It can be proposed that at higher temperatures (e.g., 323 K), Lys28 and the C‐terminal region of the peptide play the role of two anchors that keep Aβ inside the top leaflet. This study demonstrates that Aβ molecule can perturb the integrity of cellular membranes. Proteins 2017; 85:1298–1310. © 2017 Wiley Periodicals, Inc.     

In vitro affinity maturation of an anti-PSA antibody for prostate cancer diagnostic assay

Prostate-specific antigen (PSA) is a serum marker that is widely used for the diagnosis of prostatic diseases. Various subforms of free PSA, which are associated with prostate cancer differently, have been identified in sera. Thus, specific detection of certain subforms could permit discrimination between benign and malignant cases. Although the monoclonal antibody 5D3D11 displays the desired selectivity, its relative weak binding affinity prevents its development into an effective diagnostic tool. The directed-evolution strategy presented here succeeds in enhancing affinity and immunoassay sensitivity while maintaining selectivity.Starting without structural data, we constructed four independent phage-display single-chain variable fragment (scFv) libraries targeting hot spots from CDR-L1, H1, H2, and H3. Mutations derived from each library were combined, yielding further affinity gains. This constitutes the first demonstration of additivity for independently selected complementarity-determining region (CDR) hot-spot mutations. The X-ray structure of the Fab′ 5D3D11-PSA complex (after it became available) inspired the design of two new libraries targeting CDR-L3 that resulted in other higher-affinity variants. Attempts at combining the new variants with previous ones did not result in further gains, suggesting that mutations from the two strategies provide alternative but noncomplementary solutions for affinity enhancement of 5D3D11. The results can be interpreted to provide a plausible explanation for the observed lack of additivity.Finally, with respect to the wild-type scFv, the best binders show an enhancement of sensitivity in sandwich immunoassay. Its ability to discriminate between prostate cancer sera and benign prostatic hyperplasia sera has now been confirmed through the dosage of 63 patients.     

Profiling of differentially expressed proteins in stage IV colorectal cancers with good and poor outcomes

Screening patients at high risk of recurrence of cancer would allow for more accurate and personalized treatment. In this study, we tried to identify the prognosis-related protein profile by applying two different quantitative proteomic techniques, difference in-gel electrophoresis and cleavable isotope-coded affinity tag method. Six tumor tissues were obtained from stage IV colorectal cancer (CRC) patients, of which three have survived more than five years (good prognostic group, GPG) and the other three died within 25 months (poor prognostic group, PPG) after palliative surgery and subsequent chemotherapy treatment. From the two independent quantitative analyses, we identified 175 proteins with abundance ratios greater than 2-fold. Gene ontology analysis revealed that proteins related to cellular assembly/organization and movement were generally increased in the PPG. Twenty-two proteins, including caveolin-1, were chosen for confirmatory studies by Western blot and immunohistochemistry. The Western blot data for each individual protein were analyzed with Mann-Whitney tests, and a multi-marker panel was generated by logistic regression analysis. Five proteins, fatty acid binding protein 1, intelectin 1, transitional endoplasmic reticulum ATPase, transgelin and tropomyosin 2, were significantly different between the two prognostic groups within 95% confidence. No single protein could completely distinguish the two groups from each other. However, a combination of the five proteins effectively distinguished PPG from GPG patients (AUC=1). Our study suggests a multi-marker panel composed of proteome signatures that provide accurate predictive information and potentially assist personalized therapy. This article is part of a Special Issue entitled: Proteomics: The clinical link.     

Targeted biochemical profiling of brain from Huntington's disease patients reveals novel metabolic pathways of interest

Huntington's disease (HD) is a devastating, progressive neurodegenerative disease with a distinct phenotype characterized by chorea and dystonia, incoordination, cognitive decline and behavioral difficulties. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Herein DI/LC-MS/MS was used to accurately identify and quantify 185 metabolites in post mortem frontal lobe and striatum from HD patients and healthy control cases. The findings link changes in energy metabolism and phospholipid metabolism to HD pathology and also demonstrate significant reductions in neurotransmitters. Further investigation into the oxidation of fatty acids and phospholipid metabolism in pre-clinical models of HD are clearly warranted for the identification of potential therapies. Additionally, panels of 5 metabolite biomarkers were identified in both the frontal lobe (AUC?=?0.962 (95% CI: 0.85–1.00) and striatum (AUC?=?0.988 (95% CI: 0.899–1.00). This could have clinical utility in more accessible biomatrices such as blood serum for the early detection of those entering the prodromal phase of the disease, when treatment is believed to be most effective. Further evaluation of these biomarker panels in human cohorts is justified to determine their clinical efficacy.