New computer-aided diagnosis of dementia using positron emission tomography: brain regional sensitivity-mapping method

Purpose

We devised a new computer-aided diagnosis method to segregate dementia using one estimated index (Total Z score) derived from the Brodmann area (BA) sensitivity map on the stereotaxic brain atlas. The purpose of this study is to investigate its accuracy to differentiate patients with Alzheimer''s disease (AD) or mild cognitive impairment (MCI) from normal adults (NL).

Methods

We studied 101 adults (NL: 40, AD: 37, MCI: 24) who underwent ¹⁸FDG positron emission tomography (PET) measurement. We divided NL and AD groups into two categories: a training group with (Category A) and a test group without (Category B) clinical information. In Category A, we estimated sensitivity by comparing the standard uptake value per BA (SUVR) between NL and AD groups. Then, we calculated a summated index (Total Z score) by utilizing the sensitivity-distribution maps and each BA z-score to segregate AD patterns. To confirm the validity of this method, we examined the accuracy in Category B. Finally, we applied this method to MCI patients.

Results

In Category A, we found that the sensitivity and specificity of differentiation between NL and AD were all 100%. In Category B, those were 100% and 95%, respectively. Furthermore, we found this method attained 88% to differentiate AD-converters from non-converters in MCI group.

Conclusions

The present automated computer-aided evaluation method based on a single estimated index provided good accuracy for differential diagnosis of AD and MCI. This good differentiation power suggests its usefulness not only for dementia diagnosis but also in a longitudinal study.     

Multivariate protein signatures of pre-clinical Alzheimer's disease in the Alzheimer's disease neuroimaging initiative (ADNI) plasma proteome dataset

Background

Recent Alzheimer''s disease (AD) research has focused on finding biomarkers to identify disease at the pre-clinical stage of mild cognitive impairment (MCI), allowing treatment to be initiated before irreversible damage occurs. Many studies have examined brain imaging or cerebrospinal fluid but there is also growing interest in blood biomarkers. The Alzheimer''s Disease Neuroimaging Initiative (ADNI) has generated data on 190 plasma analytes in 566 individuals with MCI, AD or normal cognition. We conducted independent analyses of this dataset to identify plasma protein signatures predicting pre-clinical AD.

Methods and Findings

We focused on identifying signatures that discriminate cognitively normal controls (n = 54) from individuals with MCI who subsequently progress to AD (n = 163). Based on p value, apolipoprotein E (APOE) showed the strongest difference between these groups (p = 2.3×10⁻¹³). We applied a multivariate approach based on combinatorial optimization ((α,β)-k Feature Set Selection), which retains information about individual participants and maintains the context of interrelationships between different analytes, to identify the optimal set of analytes (signature) to discriminate these two groups. We identified 11-analyte signatures achieving values of sensitivity and specificity between 65% and 86% for both MCI and AD groups, depending on whether APOE was included and other factors. Classification accuracy was improved by considering “meta-features,” representing the difference in relative abundance of two analytes, with an 8-meta-feature signature consistently achieving sensitivity and specificity both over 85%. Generating signatures based on longitudinal rather than cross-sectional data further improved classification accuracy, returning sensitivities and specificities of approximately 90%.

Conclusions

Applying these novel analysis approaches to the powerful and well-characterized ADNI dataset has identified sets of plasma biomarkers for pre-clinical AD. While studies of independent test sets are required to validate the signatures, these analyses provide a starting point for developing a cost-effective and minimally invasive test capable of diagnosing AD in its pre-clinical stages.     

CSF concentrations of cAMP and cGMP are lower in patients with Creutzfeldt-Jakob disease but not Parkinson's disease and amyotrophic lateral sclerosis

Background

The cyclic nucleotides cyclic adenosine-3′,5′-monophosphate (cAMP) and cyclic guanosine-3′,5′-monophosphate (cGMP) are important second messengers and are potential biomarkers for Parkinson''s disease (PD), amyotrophic lateral sclerosis (ALS) and Creutzfeldt-Jakob disease (CJD).

Methodology/Principal Findings

Here, we investigated by liquid chromatography/tandem mass spectrometry (LC-MS/MS) the cerebrospinal fluid (CSF) concentrations of cAMP and cGMP of 82 patients and evaluated their diagnostic potency as biomarkers. For comparison with a well-accepted biomarker, we measured tau concentrations in CSF of CJD and control patients. CJD patients (n = 15) had lower cAMP (−70%) and cGMP (−55%) concentrations in CSF compared with controls (n = 11). There was no difference in PD, PD dementia (PDD) and ALS cases. Receiver operating characteristic (ROC) curve analyses confirmed cAMP and cGMP as valuable diagnostic markers for CJD indicated by the area under the curve (AUC) of 0.86 (cAMP) and 0.85 (cGMP). We calculated a sensitivity of 100% and specificity of 64% for cAMP and a sensitivity of 67% and specificity of 100% for cGMP. The combination of both nucleotides increased the sensitivity to 80% and specificity to 91% for the term cAMPxcGMP (AUC 0.92) and to 93% and 100% for the ratio tau/cAMP (AUC 0.99).

Conclusions/Significance

We conclude that the CSF determination of cAMP and cGMP may easily be included in the diagnosis of CJD and could be helpful in monitoring disease progression as well as in therapy control.     

Multicentric validation of proteomic biomarkers in urine specific for diabetic nephropathy

Background

Urine proteome analysis is rapidly emerging as a tool for diagnosis and prognosis in disease states. For diagnosis of diabetic nephropathy (DN), urinary proteome analysis was successfully applied in a pilot study. The validity of the previously established proteomic biomarkers with respect to the diagnostic and prognostic potential was assessed on a separate set of patients recruited at three different European centers. In this case-control study of 148 Caucasian patients with diabetes mellitus type 2 and duration ≥5 years, cases of DN were defined as albuminuria >300 mg/d and diabetic retinopathy (n = 66). Controls were matched for gender and diabetes duration (n = 82).

Methodology/Principal Findings

Proteome analysis was performed blinded using high-resolution capillary electrophoresis coupled with mass spectrometry (CE-MS). Data were evaluated employing the previously developed model for DN. Upon unblinding, the model for DN showed 93.8% sensitivity and 91.4% specificity, with an AUC of 0.948 (95% CI 0.898-0.978). Of 65 previously identified peptides, 60 were significantly different between cases and controls of this study. In <10% of cases and controls classification by proteome analysis not entirely resulted in the expected clinical outcome. Analysis of patient''s subsequent clinical course revealed later progression to DN in some of the false positive classified DN control patients.

Conclusions

These data provide the first independent confirmation that profiling of the urinary proteome by CE-MS can adequately identify subjects with DN, supporting the generalizability of this approach. The data further establish urinary collagen fragments as biomarkers for diabetes-induced renal damage that may serve as earlier and more specific biomarkers than the currently used urinary albumin.     

Predicting AD Conversion: Comparison between Prodromal AD Guidelines and Computer Assisted PredictAD Tool

Purpose

To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI and CSF biomarkers.

Methods

Altogether 391 MCI cases (158 AD converters) were selected from the ADNI cohort. All the cases had baseline cognitive tests, MRI and/or CSF levels of Aβ1–42 and Tau. Using baseline data, the status of MCI patients (AD or MCI) three years later was predicted using current diagnostic research guidelines and the PredictAD software tool designed for supporting clinical diagnostics. The data used were 1) clinical criteria for episodic memory loss of the hippocampal type, 2) visual MTA, 3) positive CSF markers, 4) their combinations, and 5) when the PredictAD tool was applied, automatically computed MRI measures were used instead of the visual MTA results. The accuracies of diagnosis were evaluated with the diagnosis made 3 years later.

Results

The PredictAD tool achieved the overall accuracy of 72% (sensitivity 73%, specificity 71%) in predicting the AD diagnosis. The corresponding number for a clinician’s prediction with the assistance of the PredictAD tool was 71% (sensitivity 75%, specificity 68%). Diagnosis with the PredictAD tool was significantly better than diagnosis by biomarkers alone or the combinations of clinical diagnosis of hippocampal pattern for the memory loss and biomarkers (p≤0.037).

Conclusion

With the assistance of PredictAD tool, the clinician can predict AD conversion more accurately than the current diagnostic criteria.     

Identification of miRNA-103 in the cellular fraction of human peripheral blood as a potential biomarker for malignant mesothelioma--a pilot study

Background

To date, no biomarkers with reasonable sensitivity and specificity for the early detection of malignant mesothelioma have been described. The use of microRNAs (miRNAs) as minimally-invasive biomarkers has opened new opportunities for the diagnosis of cancer, primarily because they exhibit tumor-specific expression profiles and have been commonly observed in blood of both cancer patients and healthy controls. The aim of this pilot study was to identify miRNAs in the cellular fraction of human peripheral blood as potential novel biomarkers for the detection of malignant mesothelioma.

Methodology/Principal Findings

Using oligonucleotide microarrays for biomarker identification the miRNA levels in the cellular fraction of human peripheral blood of mesothelioma patients and asbestos-exposed controls were analyzed. Using a threefold expression change in combination with a significance level of p<0.05, miR-103 was identified as a potential biomarker for malignant mesothelioma. Quantitative real-time PCR (qRT-PCR) was used for validation of miR-103 in 23 malignant mesothelioma patients, 17 asbestos-exposed controls, and 25 controls from the general population. For discrimination of mesothelioma patients from asbestos-exposed controls a sensitivity of 83% and a specificity of 71% were calculated, and for discrimination of mesothelioma patients from the general population a sensitivity of 78% and a specificity of 76%.

Conclusions/Significance

The results of this pilot study show that miR-103 is characterized by a promising sensitivity and specificity and might be a potential minimally-invasive biomarker for the diagnosis of mesothelioma. In addition, our results support the concept of using the cellular fraction of human blood for biomarker discovery. However, for early detection of malignant mesothelioma the feasibility of miR-103 alone or in combination with other biomarkers needs to be analyzed in a prospective study.     

Cost-effectiveness of magnetic resonance imaging with a new contrast agent for the early diagnosis of Alzheimer's disease

Background

Used as contrast agents for brain magnetic resonance imaging (MRI), markers for beta-amyloid deposits might allow early diagnosis of Alzheimer''s disease (AD). We evaluated the cost-effectiveness of such a diagnostic test, MRI+CLP (contrastophore-linker-pharmacophore), should it become clinically available.

Methodology/Principal Findings

We compared the cost-effectiveness of MRI+CLP to that of standard diagnosis using currently available cognition tests and of standard MRI, and investigated the impact of a hypothetical treatment efficient in early AD. The primary analysis was based on the current French context for 70-year-old patients with Mild Cognitive Impairment (MCI). In alternative “screen and treat” scenarios, we analyzed the consequences of systematic screenings of over-60 individuals (either population-wide or restricted to the ApoE4 genotype population). We used a Markov model of AD progression; model parameters, as well as incurred costs and quality-of-life weights in France were taken from the literature. We performed univariate and probabilistic multivariate sensitivity analyses.The base-case preferred strategy was the standard MRI diagnosis strategy. In the primary analysis however, MRI+CLP could become the preferred strategy under a wide array of scenarios involving lower cost and/or higher sensitivity or specificity. By contrast, in the “screen and treat” analyses, the probability of MRI+CLP becoming the preferred strategy remained lower than 5%.

Conclusions/Significance

It is thought that anti-beta-amyloid compounds might halt the development of dementia in early stage patients. This study suggests that, even should such treatments become available, systematically screening the over-60 population for AD would only become cost-effective with highly specific tests able to diagnose early stages of the disease. However, offering a new diagnostic test based on beta-amyloid markers to elderly patients with MCI might prove cost-effective.     

Comparison of a clinical prediction rule and a LAM antigen-detection assay for the rapid diagnosis of TBM in a high HIV prevalence setting

Background/Objective

The diagnosis of tuberculous meningitis (TBM) in resource poor TB endemic environments is challenging. The accuracy of current tools for the rapid diagnosis of TBM is suboptimal. We sought to develop a clinical-prediction rule for the diagnosis of TBM in a high HIV prevalence setting, and to compare performance outcomes to conventional diagnostic modalities and a novel lipoarabinomannan (LAM) antigen detection test (Clearview-TB®) using cerebrospinal fluid (CSF).

Methods

Patients with suspected TBM were classified as definite-TBM (CSF culture or PCR positive), probable-TBM and non-TBM.

Results

Of the 150 patients, 84% were HIV-infected (median [IQR] CD4 count = 132 [54; 241] cells/µl). There were 39, 55 and 54 patients in the definite, probable and non-TBM groups, respectively. The LAM sensitivity and specificity (95%CI) was 31% (17;48) and 94% (85;99), respectively (cut-point ≥0.18). By contrast, smear-microscopy was 100% specific but detected none of the definite-TBM cases. LAM positivity was associated with HIV co-infection and low CD4 T cell count (CD4<200 vs. >200 cells/µl; p = 0.03). The sensitivity and specificity in those with a CD4<100 cells/µl was 50% (27;73) and 95% (74;99), respectively. A clinical-prediction rule ≥6 derived from multivariate analysis had a sensitivity and specificity (95%CI) of 47% (31;64) and 98% (90;100), respectively. When LAM was combined with the clinical-prediction-rule, the sensitivity increased significantly (p<0.001) to 63% (47;68) and specificity remained high at 93% (82;98).

Conclusions

Despite its modest sensitivity the LAM ELISA is an accurate rapid rule-in test for TBM that has incremental value over smear-microscopy. The rule-in value of LAM can be further increased by combination with a clinical-prediction rule, thus enhancing the rapid diagnosis of TBM in HIV-infected persons with advanced immunosuppression.     

Distinct transthyretin oxidation isoform profile in spinal fluid from patients with Alzheimer’s disease and mild cognitive impairment

Background

Transthyretin (TTR), an abundant protein in cerebrospinal fluid (CSF), contains a free, oxidation-prone cysteine residue that gives rise to TTR isoforms. These isoforms may reflect conditions in vivo. Since increased oxidative stress has been linked to neurodegenerative disorders such as Alzheimer’s disease (AD) it is of interest to characterize CSF-TTR isoform distribution in AD patients and controls. Here, TTR isoforms are profiled directly from CSF by an optimized immunoaffinity-mass spectrometry method in 76 samples from patients with AD (n = 37), mild cognitive impairment (MCI, n = 17)), and normal pressure hydrocephalus (NPH, n = 15), as well as healthy controls (HC, n = 7). Fractions of three specific oxidative modifications (S-cysteinylation, S-cysteinylglycinylation, and S-glutathionylation) were quantitated relative to the total TTR protein. Results were correlated with diagnostic information and with levels of CSF AD biomarkers tau, phosphorylated tau, and amyloid β_1-42 peptide.

Results

Preliminary data highlighted the high risk of artifactual TTR modification due to ex vivo oxidation and thus the samples for this study were all collected using strict and uniform guidelines. The results show that TTR is significantly more modified on Cys(10) in the AD and MCI groups than in controls (NPH and HC) (p ≤ 0.0012). Furthermore, the NPH group, while having normal TTR isoform distribution, had significantly decreased amyloid β peptide but normal tau values. No obvious correlations between levels of routine CSF biomarkers for AD and the degree of TTR modification were found.

Conclusions

AD and MCI patients display a significantly higher fraction of oxidatively modified TTR in CSF than the control groups of NPH patients and HC. Quantitation of CSF-TTR isoforms thus may provide diagnostic information in patients with dementia symptoms but this should be explored in larger studies including prospective studies of MCI patients. The development of methods for simple, robust, and reproducible inhibition of in vitro oxidation during CSF sampling and sample handling is highly warranted. In addition to the diagnostic information the possibility of using TTR as a CSF oxymeter is of potential value in studies monitoring disease activity and developing new drugs for neurodegenerative diseases.     

Apolipoprotein E4 frequencies in a Japanese population with Alzheimer's disease and dementia with Lewy bodies

Background

The apolipoprotein E (APOE) ε4 allele has been reported to be a risk factor for Alzheimer''s disease (AD) and dementia with Lewy bodies (DLB). Previous neuropathological studies have demonstrated similar frequencies of the APOE ε4 allele in AD and DLB. However, the few ante-mortem studies on APOE allele frequencies in DLB have shown lower frequencies than post-mortem studies. One reason for this may be inaccuracy of diagnosis. We examined APOE genotypes in subjects with AD, DLB, and a control group using the latest diagnostic criteria and MRI, SPECT, and MIBG myocardial scintigraphy.

Methods

The subjects of this study consisted of 145 patients with probable AD, 50 subjects with probable DLB, and a control group. AD subjects were divided into two groups based on age of onset: early onset AD (EOAD) and late onset AD (LOAD). All subjects had characteristic features on MRI, SPECT, and/or myocardial scintigraphy.

Results

The rate of APOE4 carrier status was 18.3% and the frequency of the ε4 allele was 9.7% in controls. The rate of APOE4 carrier status and the frequency of the ε4 allele were 47% and 27% for LOAD, 50% and 31% for EOAD, and 42% and 31% for DLB, respectively.

Conclusion

The APOE4 genotypes in this study are consistent with previous neuropathological studies suggesting accurate diagnosis of AD and DLB. APOE4 genotypes were similar in AD and DLB, giving further evidence that the ε4 allele is a risk factor for both disorders.     

Diagnostic accuracy of PCR in gambiense sleeping sickness diagnosis, staging and post-treatment follow-up: a 2-year longitudinal study

Background

The polymerase chain reaction (PCR) has been proposed for diagnosis, staging and post-treatment follow-up of sleeping sickness but no large-scale clinical evaluations of its diagnostic accuracy have taken place yet.

Methodology/Principal Findings

An 18S ribosomal RNA gene targeting PCR was performed on blood and cerebrospinal fluid (CSF) of 360 T. brucei gambiense sleeping sickness patients and on blood of 129 endemic controls from the Democratic Republic of Congo. Sensitivity and specificity (with 95% confidence intervals) of PCR for diagnosis, disease staging and treatment failure over 2 years follow-up post-treatment were determined. Reference standard tests were trypanosome detection for diagnosis and trypanosome detection and/or increased white blood cell concentration in CSF for staging and detection of treatment failure. PCR on blood showed a sensitivity of 88.4% (84.4–92.5%) and a specificity of 99.2% (97.7–100%) for diagnosis, while for disease staging the sensitivity and specificity of PCR on cerebrospinal fluid were 88.4% (84.8–91.9%) and 82.9% (71.2–94.6%), respectively. During follow-up after treatment, PCR on blood had low sensitivity to detect treatment failure. In cerebrospinal fluid, PCR positivity vanished slowly and was observed until the end of the 2 year follow-up in around 20% of successfully treated patients.

Conclusions/Significance

For T.b. gambiense sleeping sickness diagnosis and staging, PCR performed better than, or similar to, the current parasite detection techniques but it cannot be used for post-treatment follow-up. Continued PCR positivity in one out of five cured patients points to persistence of living or dead parasites or their DNA after successful treatment and may necessitate the revision of some paradigms about the pathophysiology of sleeping sickness.     

A blood-based screening tool for Alzheimer's disease that spans serum and plasma: findings from TARC and ADNI

Context

There is no rapid and cost effective tool that can be implemented as a front-line screening tool for Alzheimer''s disease (AD) at the population level.

Objective

To generate and cross-validate a blood-based screener for AD that yields acceptable accuracy across both serum and plasma.

Design, Setting, Participants

Analysis of serum biomarker proteins were conducted on 197 Alzheimer''s disease (AD) participants and 199 control participants from the Texas Alzheimer''s Research Consortium (TARC) with further analysis conducted on plasma proteins from 112 AD and 52 control participants from the Alzheimer''s Disease Neuroimaging Initiative (ADNI). The full algorithm was derived from a biomarker risk score, clinical lab (glucose, triglycerides, total cholesterol, homocysteine), and demographic (age, gender, education, APOE*E4 status) data.

Major Outcome Measures

Alzheimer''s disease.

Results

11 proteins met our criteria and were utilized for the biomarker risk score. The random forest (RF) biomarker risk score from the TARC serum samples (training set) yielded adequate accuracy in the ADNI plasma sample (training set) (AUC = 0.70, sensitivity (SN) = 0.54 and specificity (SP) = 0.78), which was below that obtained from ADNI cerebral spinal fluid (CSF) analyses (t-tau/Aβ ratio AUC = 0.92). However, the full algorithm yielded excellent accuracy (AUC = 0.88, SN = 0.75, and SP = 0.91). The likelihood ratio of having AD based on a positive test finding (LR+) = 7.03 (SE = 1.17; 95% CI = 4.49–14.47), the likelihood ratio of not having AD based on the algorithm (LR−) = 3.55 (SE = 1.15; 2.22–5.71), and the odds ratio of AD were calculated in the ADNI cohort (OR) = 28.70 (1.55; 95% CI = 11.86–69.47).

Conclusions

It is possible to create a blood-based screening algorithm that works across both serum and plasma that provides a comparable screening accuracy to that obtained from CSF analyses.     

A Nationwide Population-Based Cohort Study: Will Anxiety Disorders Increase Subsequent Cancer Risk?

Background

The aim of this study was to evaluate a possible association between malignancy and anxiety disorders (AD) in Taiwan.

Methods

We employed data from the National Health Insurance system of Taiwan. The AD cohort contained 24,066 patients with each patient randomly frequency matched according to age and sex with 4 individuals from the general population without AD. Cox''s proportional hazard regression analysis was conducted to estimate the influence of AD on the risk of cancer.

Results

Among patients with AD, the overall risk of developing cancer was only 1% higher than among subjects without AD, and the difference was not significant (hazard ratio [HR] = 1.01, 95% confidence interval [95% CI] = 0.95–1.07). With regard to individual types of cancer, the risk of developing prostate cancer among male patients with AD was significantly higher (HR = 1.32, 95% CI = 1.02–1.71). On the other hand, the risk of cervical cancer among female patients with AD was marginally significantly lower than among female subjects without AD (HR = 0.72, 95% CI = 0.51–1.03).

Limitations

One major limitation is the lack of information regarding the life style or behavior of patients in the NHI database, such as smoking and alcohol consumption.

Conclusions

Despite the failure to identify a relationship between AD and the overall risk of cancer, we found that Taiwanese patients with AD had a higher risk of developing prostate cancer and a lower risk of developing cervical cancer.     

Longitudinal Study of CSF Biomarkers in Patients with Alzheimer's Disease

Background

The CSF biomarkers tau and Aβ42 can identify patients with AD, even during the preclinical stages. However, previous studies on longitudinal changes of tau and Aβ42 in individual patients with AD and elderly controls report somewhat inconsistent results.

Methodology/Principal Findings

We investigated the levels of tau and Aβ42 at baseline and after 1 year in 100 patients with AD. In a second cohort of 45 AD patients we measured the CSF biomarkers at baseline and after 2 years. Moreover, in 34 healthy elderly controls the CSF biomarkers were followed for 4 years. The baseline levels of tau were increased with >60% in AD patients compared to controls (p<0.001), while baseline Aβ42 levels were decreased with >50% (p<0.001). In the AD group followed for 2 years, tau increased with 16% compared to the baseline levels (p<0.05). However, the levels of tau were stable over 4 years in the controls. The levels of Aβ42 did not change significantly over time in any of the groups. In the patients with AD, tau was moderately associated with worse cognitive performance already at baseline (p<0.05).

Conclusions/Significance

Tau and Aβ42 in CSF seem to reflect the underlying disease state in both early and late stages of AD. The slight increase in tau over time observed in the patients with AD is modest when compared to the relatively large difference in absolute tau levels between AD patients and controls. Therefore, these markers maintain their usefulness as state markers over time and might serve as surrogate markers for treatment efficacy in clinical trials.     

Molecular prognostic prediction for locally advanced nasopharyngeal carcinoma by support vector machine integrated approach

Background

Accurate prognostication of locally advanced nasopharyngeal carcinoma (NPC) will benefit patients for tailored therapy. Here, we addressed this issue by developing a mathematical algorithm based on support vector machine (SVM) through integrating the expression levels of multi-biomarkers.

Methodology/Principal Findings

Ninety-seven locally advanced NPC patients in a randomized controlled trial (RCT), consisting of 48 cases serving as training set and 49 cases as testing set of SVM models, with 5-year follow-up were studied. We designed SVM models by selecting the variables from 38 tissue molecular biomarkers, which represent 6 tumorigenesis signaling pathways, and 3 EBV-related serological biomarkers. We designed 3 SVM models to refine prognosis of NPC with 5-year follow-up. The SVM1 displayed highly predictive sensitivity (sensitivity, specificity were 88.0% and 81.9%, respectively) by integrating the expression of 7 molecular biomarkers. The SVM2 model showed highly predictive specificity (sensitivity, specificity were 84.0% and 94.5%, respectively) by grouping the expression level of 12 molecular biomarkers and 3 EBV-related serological biomarkers. The SVM3 model, constructed by combination SVM1 with SVM2, displayed a high predictive capacity (sensitivity, specificity were 88.0% and 90.3%, respectively). We found that 3 SVM models had strong power in classification of prognosis. Moreover, Cox multivariate regression analysis confirmed these 3 SVM models were all the significant independent prognostic model for overall survival in testing set and overall patients.

Conclusions/Significance

Our SVM prognostic models designed in the RCT displayed strong power in refining patient prognosis for locally advanced NPC, potentially directing future target therapy against the related signaling pathways.     

Shorter telomeres may mark early risk of dementia: preliminary analysis of 62 participants from the nurses' health study

Background

Dementia takes decades to develop, and effective prevention will likely require early intervention. Thus, it is critical to identify biomarkers of preclinical disease, allowing targeting of high-risk subjects for preventive efforts. Since telomeres shorten with age and oxidative stress, both of which are important contributors to the onset of dementia, telomere length might be a valuable biomarker.

Methodology/Principal Findings

Among 62 participants of the Nurses'' Health Study, we conducted neurologic evaluations, including patient and caregiver interviews, physical exam, neurologic exam, and neuropsychologic testing. We also conducted magnetic resonance imaging (MRI) in a sample of 29 of these women. In these preliminary data, after adjustment for numerous health and lifestyle factors, we found that truncated telomeres in peripheral blood leukocytes segregate with preclinical dementia states, including mild cognitive impairment (MCI); the odds of MCI were 12-fold higher (odds ratio = 12.00, 95% confidence interval 1.24–116.5) for those with shorter telomere length compared to longer telomere length. In addition, decreasing telomere length was strongly related to decreasing hippocampal volume (p = 0.038).

Conclusions

These preliminary data suggest that telomere length may be a possible early marker of dementia risk, and merits further study in large, prospective investigations.     

Utility of quantitative sensory testing and screening tools in identifying HIV-associated peripheral neuropathy in Western Kenya: pilot testing

Background/Aim

Neuropathy is the most common neurologic complication of HIV but is widely under-diagnosed in resource-constrained settings. We aimed to identify tools that accurately distinguish individuals with moderate/severe peripheral neuropathy and can be administered by non-physician healthcare workers (HCW) in resource-constrained settings.

Methods

We enrolled a convenience sample of 30 HIV-infected outpatients from a Kenyan HIV-care clinic. A HCW administered the Neuropathy Severity Score (NSS), Single Question Neuropathy Screen (Single-QNS), Subjective Peripheral Neuropathy Screen (Subjective-PNS), and Brief Peripheral Neuropathy Screen (Brief-PNS). Monofilament, graduated tuning fork, and two-point discrimination examinations were performed. Tools were validated against a neurologist''s clinical assessment of moderate/severe neuropathy.

Results

The sample was 57% male, mean age 38.6 years, and mean CD4 count 324 cells/µL. Neurologist''s assessment identified 20% (6/30) with moderate/severe neuropathy. Diagnostic utilities for moderate/severe neuropathy were: Single-QNS - 83% sensitivity, 71% specificity; Subjective-PNS-total - 83% sensitivity, 83% specificity; Subjective-PNS-max and NSS - 67% sensitivity, 92% specificity; Brief-PNS - 0% sensitivity, 92% specificity; monofilament - 100% sensitivity, 88% specificity; graduated tuning fork - 83% sensitivity, 88% specificity; two-point discrimination - 75% sensitivity, 58% specificity.

Conclusions

Pilot testing suggests Single-QNS, Subjective-PNS, and monofilament examination accurately identify HIV-infected patients with moderate/severe neuropathy and may be useful diagnostic tools in resource-constrained settings.     

Interferon-gamma release assays for the diagnosis of active tuberculosis in HIV-infected patients: a systematic review and meta-analysis

Background

Interferon-gamma release assays (IGRAs) have provided a new method for the diagnosis of Mycobacterium tuberculosis infection. However, the role of IGRAs for the diagnosis of active tuberculosis (TB), especially in HIV-infected patients remains unclear.

Methods

We searched PubMed, EMBASE and Cochrane databases to identify studies published in January 2001–July 2011 that evaluated the evidence of using QuantiFERON-TB Gold in-tube (QFT-GIT) and T-SPOT.TB (T-SPOT) on blood for the diagnosis of active TB in HIV-infected patients.

Results

The search identified 16 eligible studies that included 2801 HIV-infected individuals (637 culture confirmed TB cases). The pooled sensitivity for the diagnosis of active TB was 76.7% (95%CI, 71.6–80.5%) and 77.4% (95%CI, 71.4–82.6%) for QFT-GIT and T-SPOT, respectively, while the specificity was 76.1% (95%CI, 74.0–78.0%) and 63.1% (95%CI, 57.6–68.3%) after excluding the indeterminate results. Studies conducted in low/middle income countries showed slightly lower sensitivity and specificity when compared to that in high-income countries. The proportion of indeterminate results was as high as 10% (95%CI, 8.8–11.3%) and 13.2% (95%CI, 10.6–16.0%) for QFT-GIT and T-SPOT, respectively.

Conclusion

IGRAs in their current formulations have limited accuracy in diagnosing active TB in HIV-infected patients, and should not be used alone to rule out or rule in active TB cases in HIV-infected patients. Further modification is needed to improve their accuracy.     

Bladder cancer diagnosis and identification of clinically significant disease by combined urinary detection of Mcm5 and nuclear matrix protein 22

Background

Urinary biomarkers for bladder cancer detection are constrained by inadequate sensitivity or specificity. Here we evaluate the diagnostic accuracy of Mcm5, a novel cell cycle biomarker of aberrant growth, alone and in combination with NMP22.

Methods

1677 consecutive patients under investigation for urinary tract malignancy were recruited to a prospective blinded observational study. All patients underwent ultrasound, intravenous urography, cystoscopy, urine culture and cytologic analysis. An immunofluorometric assay was used to measure Mcm5 levels in urine cell sediments. NMP22 urinary levels were determined with the FDA-approved NMP22® Test Kit.

Results

Genito-urinary tract cancers were identified in 210/1564 (13%) patients with an Mcm5 result and in 195/1396 (14%) patients with an NMP22 result. At the assay cut-point where sensitivity and specificity were equal, the Mcm5 test detected primary and recurrent bladder cancers with 69% sensitivity (95% confidence interval = 62–75%) and 93% negative predictive value (95% CI = 92–95%). The area under the receiver operating characteristic curve for Mcm5 was 0.75 (95% CI = 0.71–0.79) and 0.72 (95% CI = 0.67–0.77) for NMP22. Importantly, Mcm5 combined with NMP22 identified 95% (79/83; 95% CI = 88–99%) of potentially life threatening diagnoses (i.e. grade 3 or carcinoma in situ or stage ≥pT1) with high specificity (72%, 95% CI = 69–74%).

Conclusions

The Mcm5 immunoassay is a non-invasive test for identifying patients with urothelial cancers with similar accuracy to the FDA-approved NMP22 ELISA Test Kit. The combination of Mcm5 plus NMP22 improves the detection of UCC and identifies 95% of clinically significant disease. Trials of a commercially developed Mcm5 assay suitable for an end-user laboratory alongside NMP22 are required to assess their potential clinical utility in improving diagnostic and surveillance care pathways.     

Aberrant hippocampal subregion networks associated with the classifications of aMCI subjects: a longitudinal resting-state study

Background

Altered hippocampal structure and function is a valuable indicator of possible conversion from amnestic type mild cognitive impairment (aMCI) to Alzheimer''s disease (AD). However, little is known about the disrupted functional connectivity of hippocampus subregional networks in aMCI subjects.

Methodology/Principal Findings

aMCI group-1 (n = 26) and controls group-1 (n = 18) underwent baseline and after approximately 20 months follow up resting-state fMRI scans. Integrity of distributed functional connectivity networks incorporating six hippocampal subregions (i.e. cornu ammonis, dentate gyrus and subicular complex, bilaterally) was then explored over time and comparisons made between groups. The ability of these extent longitudinal changes to separate unrelated groups of 30 subjects (aMCI-converters, n = 6; aMCI group-2, n = 12; controls group-2, n = 12) were further assessed. Six longitudinal hippocampus subregional functional connectivity networks showed similar changes in aMCI subjects over time, which were mainly associated with medial frontal gyrus, lateral temporal cortex, insula, posterior cingulate cortex (PCC) and cerebellum. However, the disconnection of hippocampal subregions and PCC may be a key factor of impaired episodic memory in aMCI, and the functional index of these longitudinal changes allowed well classifying independent samples of aMCI converters from non-converters (sensitivity was 83.3%, specificity was 83.3%) and controls (sensitivity was 83.3%, specificity was 91.7%).

Conclusions/Significance

It demonstrated that the functional changes in resting-state hippocampus subregional networks could be an important and early indicator for dysfunction that may be particularly relevant to early stage changes and progression of aMCI subjects.