Phosphatidylethanol (PEth) in blood samples from "driving under the influence" cases as indicator for prolonged excessive alcohol consumption.

Phosphatidylethanol (PEth) is considered as specific biomarker of alcohol consumption. Due to accumulation after repeated drinking, PEth is suitable to monitor long-term drinking behavior. To examine the applicability of PEth in "driving under the influence of alcohol" cases, 142 blood samples with blood alcohol concentrations (BAC) ranging from 0.0-3.12 ‰ were analyzed for the presence of PEth homologues 16:0/18:1 (889 ± 878 ng/mL; range and 16:0/18:2 (355 ± 315 ng/mL; range and excessive alcohol consumption with acceptable sensitivity and specificity in accordance with the 1.6 ‰ BAC limit. With a threshold of 700 ng/mL for PEth 16:0/18:1, prolonged excessive alcohol consumption was detected in 65.9 % of drunk drivers with a BAC ≥ 1.6 ‰ and in 31.6 % of the samples with a BAC < 1.6 ‰. Similar results were obtained for PEth 16:0/18:2 with a threshold of 300 ng/mL. Both criteria, PEth 16:0/18:1 and PEth 16:0/18:2, were conform in the evaluation of drinking habits in 88.7 % of blood samples. These results show the possibility to detect prolonged excessive alcohol consumption, even if the BAC is below the legal threshold of 1.6 ‰ for driving aptitude assessment. As a consequence, concentrations of PEth 16:0/18:1 ≥ 700 ng/mL and of PEth 16:0/18:2 ≥ 300 ng/mL may be considered as indicators for the necessity of driving aptitude assessment in addition to BAC.

A Neuromonitoring Approach to Facial Nerve Preservation During Image-guided Robotic Cochlear Implantation.

HYPOTHESIS A multielectrode probe in combination with an optimized stimulation protocol could provide sufficient sensitivity and specificity to act as an effective safety mechanism for preservation of the facial nerve in case of an unsafe drill distance during image-guided cochlear implantation. BACKGROUND A minimally invasive cochlear implantation is enabled by image-guided and robotic-assisted drilling of an access tunnel to the middle ear cavity. The approach requires the drill to pass at distances below 1 mm from the facial nerve and thus safety mechanisms for protecting this critical structure are required. Neuromonitoring is currently used to determine facial nerve proximity in mastoidectomy but lacks sensitivity and specificity necessaries to effectively distinguish the close distance ranges experienced in the minimally invasive approach, possibly because of current shunting of uninsulated stimulating drilling tools in the drill tunnel and because of nonoptimized stimulation parameters. To this end, we propose an advanced neuromonitoring approach using varying levels of stimulation parameters together with an integrated bipolar and monopolar stimulating probe. MATERIALS AND METHODS An in vivo study (sheep model) was conducted in which measurements at specifically planned and navigated lateral distances from the facial nerve were performed to determine if specific sets of stimulation parameters in combination with the proposed neuromonitoring system could reliably detect an imminent collision with the facial nerve. For the accurate positioning of the neuromonitoring probe, a dedicated robotic system for image-guided cochlear implantation was used and drilling accuracy was corrected on postoperative microcomputed tomographic images. RESULTS From 29 trajectories analyzed in five different subjects, a correlation between stimulus threshold and drill-to-facial nerve distance was found in trajectories colliding with the facial nerve (distance <0.1 mm). The shortest pulse duration that provided the highest linear correlation between stimulation intensity and drill-to-facial nerve distance was 250 μs. Only at low stimulus intensity values (≤0.3 mA) and with the bipolar configurations of the probe did the neuromonitoring system enable sufficient lateral specificity (>95%) at distances to the facial nerve below 0.5 mm. However, reduction in stimulus threshold to 0.3 mA or lower resulted in a decrease of facial nerve distance detection range below 0.1 mm (>95% sensitivity). Subsequent histopathology follow-up of three representative cases where the neuromonitoring system could reliably detect a collision with the facial nerve (distance <0.1 mm) revealed either mild or inexistent damage to the nerve fascicles. CONCLUSION Our findings suggest that although no general correlation between facial nerve distance and stimulation threshold existed, possibly because of variances in patient-specific anatomy, correlations at very close distances to the facial nerve and high levels of specificity would enable a binary response warning system to be developed using the proposed probe at low stimulation currents.

Predicting the onset of psychosis in patients at clinical high risk: practical guide to probabilistic prognostic reasoning

Prediction of psychosis in patients at clinical high risk (CHR) has become a mainstream focus of clinical and research interest worldwide. When using CHR instruments for clinical purposes, the predicted outcome is but only a probability; and, consequently, any therapeutic action following the assessment is based on probabilistic prognostic reasoning. Yet, probabilistic reasoning makes considerable demands on the clinicians. We provide here a scholarly practical guide summarising the key concepts to support clinicians with probabilistic prognostic reasoning in the CHR state. We review risk or cumulative incidence of psychosis in, person-time rate of psychosis, Kaplan-Meier estimates of psychosis risk, measures of prognostic accuracy, sensitivity and specificity in receiver operator characteristic curves, positive and negative predictive values, Bayes’ theorem, likelihood ratios, potentials and limits of real-life applications of prognostic probabilistic reasoning in the CHR state. Understanding basic measures used for prognostic probabilistic reasoning is a prerequisite for successfully implementing the early detection and prevention of psychosis in clinical practice. Future refinement of these measures for CHR patients may actually influence risk management, especially as regards initiating or withholding treatment.

First international external quality assessment of molecular diagnostics for Mers-CoV

BACKGROUND: Since the discovery of Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012, diagnostic protocols were quickly published and deployed globally. OBJECTIVES: We set out to assess the quality of MERS-CoV molecular diagnostics worldwide. STUDY DESIGN: Both sensitivity and specificity were assessed using 12 samples containing different viral loads of MERS-CoV or common coronaviruses (OC43, 229E, NL63, HKU1). RESULTS: The panel was sent to more than 106 participants, of which 99 laboratories from 6 continents returned 189 panel results.Scores ranged from 100% (84 laboratories) to 33% (1 laboratory). 15% of respondents reported quantitative results, 61% semi-quantitative (Ct-values or time to positivity) and 24% reported qualitative results. The major specific technique used was real-time RT-PCR using the WHO recommended targets upE, ORF1a and ORF1b. The evaluation confirmed that RT-PCRs targeting the ORF1b are less sensitive, and therefore not advised for primary diagnostics. CONCLUSIONS: The first external quality assessment MERS-CoV panel gives a good insight in molecular diagnostic techniques and their performances for sensitive and specific detection of MERS-CoV RNA globally. Overall, all laboratories were capable of detecting MERS-CoV with some differences in sensitivity. The observation that 8% of laboratories reported false MERS-CoV positive single assay results shows room for improvement, and the importance of using confirmatory targets.

Magnetic resonance tomography of the knee joint

OBJECTIVES To compare the diagnostic performance of magnetic resonance imaging (MRI) in terms of sensitivity and specificity using a field strength of <1.0 T (T) versus ≥1.5 T for diagnosing or ruling out knee injuries or knee pathologies. METHODS The systematic literature research revealed more than 10,000 references, of which 1598 abstracts were reviewed and 87 full-text articles were retrieved. The further selection process resulted in the inclusion of four systematic reviews and six primary studies. RESULTS No differences could be identified in the diagnostic performance of low- versus high-field MRI for the detection or exclusion of meniscal or cruciate ligament tears. Regarding the detection or grading of cartilage defects and osteoarthritis of the knee, the existing evidence suggests that high-field MRI is tolerably specific but not very sensitive, while there is literally no evidence for low-field MRI because only a few studies with small sample sizes and equivocal findings have been performed. CONCLUSIONS We can recommend the use of low-field strength MRI systems in suspected meniscal or cruciate ligament injuries. This does, however, not apply to the diagnosis and grading of knee cartilage defects and osteoarthritis because of insufficient evidence.

Diagnostic Accuracy of Copeptin in the Differential Diagnosis of the Polyuria-polydipsia Syndrome: A Prospective Multicenter Study

CONTEXT The polyuria-polydipsia syndrome comprises primary polydipsia (PP) and central and nephrogenic diabetes insipidus (DI). Correctly discriminating these entities is mandatory, given that inadequate treatment causes serious complications. The diagnostic "gold standard" is the water deprivation test with assessment of arginine vasopressin (AVP) activity. However, test interpretation and AVP measurement are challenging. OBJECTIVE The objective was to evaluate the accuracy of copeptin, a stable peptide stoichiometrically cosecreted with AVP, in the differential diagnosis of polyuria-polydipsia syndrome. DESIGN, SETTING, AND PATIENTS This was a prospective multicenter observational cohort study from four Swiss or German tertiary referral centers of adults >18 years old with the history of polyuria and polydipsia. MEASUREMENTS A standardized combined water deprivation/3% saline infusion test was performed and terminated when serum sodium exceeded 147 mmol/L. Circulating copeptin and AVP levels were measured regularly throughout the test. Final diagnosis was based on the water deprivation/saline infusion test results, clinical information, and the treatment response. RESULTS Fifty-five patients were enrolled (11 with complete central DI, 16 with partial central DI, 18 with PP, and 10 with nephrogenic DI). Without prior thirsting, a single baseline copeptin level >21.4 pmol/L differentiated nephrogenic DI from other etiologies with a 100% sensitivity and specificity, rendering a water deprivation testing unnecessary in such cases. A stimulated copeptin >4.9 pmol/L (at sodium levels >147 mmol/L) differentiated between patients with PP and patients with partial central DI with a 94.0% specificity and a 94.4% sensitivity. A stimulated AVP >1.8 pg/mL differentiated between the same categories with a 93.0% specificity and a 83.0% sensitivity. LIMITATION This study was limited by incorporation bias from including AVP levels as a diagnostic criterion. CONCLUSION Copeptin is a promising new tool in the differential diagnosis of the polyuria-polydipsia syndrome, and a valid surrogate marker for AVP. Primary Funding Sources: Swiss National Science Foundation, University of Basel.

Evaluation of a Commercial ELISA for the Detection of Antibodies to Sarcoptes scabiei in Wild Boar (Sus scrofa).

Sarcoptic mange occurs in free-ranging wild boar (Sus scrofa) but has been poorly described in this species. We evaluated the performance of a commercial indirect enzyme-linked immunosorbent assay (ELISA) for serodiagnosis of sarcoptic mange in domestic swine when applied to wild boar sera. We tested 96 sera from wild boar in populations without mange history ("truly noninfected") collected in Switzerland between December 2012 and February 2014, and 141 sera from free-ranging wild boar presenting mange-like lesions, including 50 live animals captured and sampled multiple times in France between May and August 2006 and three cases submitted to necropsy in Switzerland between April 2010 and February 2014. Mite infestation was confirmed by skin scraping in 20 of them ("truly infected"). We defined sensitivity of the test as the proportion of truly infected that were found ELISA-positive, and specificity as the proportion of truly noninfected that were found negative. Sensitivity and specificity were 75% and 80%, respectively. Success of antibody detection increased with the chronicity of lesions, and seroconversion was documented in 19 of 27 wild boar sampled multiple times that were initially negative or doubtful. In conclusion, the evaluated ELISA has been successfully applied to wild boar sera. It appears to be unreliable for early detection in individual animals but may represent a useful tool for population surveys.

Towards an Earlier Diagnosis of Primary Ciliary Dyskinesia: Which Patients Should Undergo Detailed Diagnostic Testing?

Primary ciliary dyskinesia is a rare heterogeneous recessive genetic disorder of motile cilia, leading to chronic upper and lower respiratory symptoms. Prevalence is estimated at around 1:10,000, but many patients remain undiagnosed, while others receive the label incorrectly. Proper diagnosis is complicated by the fact that the key symptoms such as wet cough, chronic rhinitis and recurrent upper and lower respiratory infection, are common and nonspecific. There is no single gold standard test to diagnose PCD. Presently, the diagnosis is made by augmenting the medical history and physical examination with in patients with a compatible medical history following a demanding combination of tests including nasal nitric oxide, high- speed video microscopy, transmission electron microscopy, genetics, and ciliary culture. These tests are costly and need sophisticated equipment and experienced staff, restricting use to highly specialised centers. Therefore, it would be desirable to have a screening test for identifying those patients who should undergo detailed diagnostic testing. Three recent studies focused on potential screening tools: one paper assessed the validity of nasal nitric oxide for screening, and two studies developed new symptom-based screening tools. These simple tools are welcome, and hopefully remind physicians whom to refer for definitive testing. However, they have been developed in tertiary care settings, where 10 to 50% of tested patients have PCD. Sensitivity and specificity of the tools are reasonable, but positive and negative predictive values may be poor in primary or secondary care settings. While these studies take an important step forward towards an earlier diagnosis of PCD, more remains to be done before we have tools tailored to different health care settings.

Accuracy of diagnostic testing in primary ciliary dyskinesia.

Diagnosis of primary ciliary dyskinesia (PCD) lacks a "gold standard" test and is therefore based on combinations of tests including nasal nitric oxide (nNO), high-speed video microscopy analysis (HSVMA), genotyping and transmission electron microscopy (TEM). There are few published data on the accuracy of this approach.Using prospectively collected data from 654 consecutive patients referred for PCD diagnostics we calculated sensitivity and specificity for individual and combination testing strategies. Not all patients underwent all tests.HSVMA had excellent sensitivity and specificity (100% and 93%, respectively). TEM was 100% specific, but 21% of PCD patients had normal ultrastructure. nNO (30 nL·min(-1) cut-off) had good sensitivity and specificity (91% and 96%, respectively). Simultaneous testing using HSVMA and TEM was 100% sensitive and 92% specific.In conclusion, combination testing was found to be a highly accurate approach for diagnosing PCD. HSVMA alone has excellent accuracy, but requires significant expertise, and repeated sampling or cell culture is often needed. TEM alone is specific but misses 21% of cases. nNO (≤30 nL·min(-1)) contributes well to the diagnostic process. In isolation nNO screening at this cut-off would miss ∼10% of cases, but in combination with HSVMA could reduce unnecessary further testing. Standardisation of testing between centres is a future priority.

PICADAR: a diagnostic predictive tool for primary ciliary dyskinesia.

Symptoms of primary ciliary dyskinesia (PCD) are nonspecific and guidance on whom to refer for testing is limited. Diagnostic tests for PCD are highly specialised, requiring expensive equipment and experienced PCD scientists. This study aims to develop a practical clinical diagnostic tool to identify patients requiring testing.Patients consecutively referred for testing were studied. Information readily obtained from patient history was correlated with diagnostic outcome. Using logistic regression, the predictive performance of the best model was tested by receiver operating characteristic curve analyses. The model was simplified into a practical tool (PICADAR) and externally validated in a second diagnostic centre.Of 641 referrals with a definitive diagnostic outcome, 75 (12%) were positive. PICADAR applies to patients with persistent wet cough and has seven predictive parameters: full-term gestation, neonatal chest symptoms, neonatal intensive care admittance, chronic rhinitis, ear symptoms, situs inversus and congenital cardiac defect. Sensitivity and specificity of the tool were 0.90 and 0.75 for a cut-off score of 5 points. Area under the curve for the internally and externally validated tool was 0.91 and 0.87, respectively.PICADAR represents a simple diagnostic clinical prediction rule with good accuracy and validity, ready for testing in respiratory centres referring to PCD centres.

Biological Signatures of Vaccine Responses

The set of host- and pathogen-specific molecular features of a disease comprise its “signature”. We hypothesize that biological signatures enables distinctions between vaccinated vs. infected individuals. In our research, using porcine samples, protocols were developed that could also be used to identify biological signatures of human disease. Different classes of molecular features will be tested during this project, including indicators of basic immune capacity, which are being studied at this instance. These indicators of basic immune response such as porcine cytokines and antibodies were validated using Enzyme-linked immunosorbent assay (ELISA). This is an established method that detects antigens by their interaction with a specific antibody coupled to a polystyrene substrate. Serum from naïve and vaccinated pigs was tested for the presence of cytokines. We were able to differentiate the presence of porcine IL-6 in normal porcine serum with or without added porcine IL-6 by ELISA. In addition, four different cytokines were spotted on a grating-coupled surface plasmon resonance imaging system (GCSPRI) chip and antibody specific for IL-8 was run over the chip. Only the presence of IL-8 was detected; therefore, there was no cross-reactivity in this combination of antigens and antibodies. This system uses a multiplexed sensor chip to identify components of a sample run over it. The detection is accomplished by the change in refractive index caused by the interaction between the antibody spotted on the sensor chip and the antigen present in the sample. As the multiplexed GCSPRI is developed, we will need to optimize both sensitivity and specificity, minimizing the potential for cross-reactivity between individual analytes. The next step in this project is to increase the sensitivity of detection of the analytes. Currently, we are using two different antibodies (that recognize a different part of the antigen) to amplify the signal emitted by the interaction of antibody with its cognate antigen. The development of this sensor chip would not only allow to detect FMD virus, but also to differentiate between infected and vaccinated individuals, on location. Furthermore, the diagnosis of other diseases could be done with increased accuracy, and in less time due to the microarray approach.

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

A PCR based assay for the detection of enteric pathogens from Hemoccult(RTM) cards

Background. Large field studies in travelers' diarrhea (TD) in multiple destinations are limited by the need to perform stool cultures on site in a timely manner. A method for the collection, transport and storage of fecal specimens that does not require immediate processing, refrigeration and is stable for months would be advantageous. ^ Objectives. Determine if enteric pathogen bacterial DNA can be identified in cards routinely used for evaluation of fecal occult blood. ^ Methods. U.S. students traveling to Mexico in 2005-07 were followed for occurrence of diarrheal illness. When ill, students provided a stool specimen for culture and occult blood by the standard method. Cards were then stored at room temperature prior to DNA extraction. A multiplex fecal PCR was performed to identify enterotoxigenic Escherichia coli and enteroaggregative E. coli (EAEC) in DNA extracted from stools and occult blood cards. ^ Results. Significantly more EAEC cases were identified by PCR done in DNA extracted from cards (49%) or from frozen feces (40%) than by culture followed by HEp-2 adherence assays (13%). Similarly more ETEC cases were detected in card DNA (38%) than fecal DNA (30%) or culture followed by hybridization (10%). Sensitivity and specificity of the card test was 75% and 62%, respectively, and 50% and 63%, respectively, when compared to EAEC and ETEC culture, respectively, and 53% and 51%, respectively compared to EAEC multiplex fecal PCR and 56% and 70%, respectively, compared to ETEC multiplex fecal PCR. ^ Conclusions. DNA extracted from fecal cards used for detection of occult blood is of use in detecting enteric pathogens. ^

Analysis of Mycobacterium tuberculosis in the state of Texas for rifampin resistance using molecular beacons

Mycobacterium tuberculosis, a bacillus known to cause disease in humans since ancient times, is the etiological agent of tuberculosis (TB). The infection is primarily pulmonary, although other organs may also be affected. The prevalence of pulmonary TB disease in the US is highest along the US-Mexico border, and of the four US states bordering Mexico, Texas had the second highest percentage of cases of TB disease among Mexico-born individuals in 1999 (CDC, 2001). Between the years of 1993 and 1998, the prevalence of drug-resistant (DR) TB was 9.1% among Mexican-born individuals and 4.4% among US-born individuals (CDC, 2001). In the same time period, the prevalence of multi-drug resistant (MDR) TB was 1.4% among Mexican-born individuals and 0.6% among US-born individuals (CDC, 2001). There is a renewed urgency in the quest for faster and more effective screening, diagnosis, and treatment methods for TB due to the resurgence of tuberculosis in the US during the mid-1980s and early 1990s (CDC, 2007a), and the emergence of drug-resistant, multidrug-resistant, and extremely drug-resistant tuberculosis worldwide. Failure to identify DR and MDR-TB quickly leads to poorer treatment outcomes (CDC, 2007b). The recent rise in TB/HIV comorbidity further complicates TB control efforts. The gold standard for identification of DR-TB requires mycobacterial growth in culture, a technique taking up to three weeks, during which time DR/MDR-TB individuals harboring resistant organisms may be receiving inappropriate treatment. The goal of this study was to determine the sensitivity and specificity of real-time quantitative polymerase chain reaction (qPCR) using molecular beacons in the Texas population. qPCR using molecular beacons is a novel approach to detect mycobacterial mutations conferring drug resistance. This technique is time-efficient and has been shown to have high sensitivity and specificity in several populations worldwide. Rifampin (RIF) susceptibility was chosen as the test parameter because strains of M. tuberculosis which are resistant to RIF are likely to also be MDR. Due to its status as a point of entry for many immigrants into the US, control efforts against TB and drug-resistant TB in Texas is a vital component of prevention efforts in the US as a whole. We show that qPCR using molecular beacons has high sensitivity and specificity when compared with culture (94% and 87%, respectively) and DNA sequencing (90% and 96%, respectively). We also used receiver operator curve analysis to calculate cutoff values for the objective determination of results obtained by qPCR using molecular beacons. ^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^