Use Of Clinical Tests Research Articles

Free-listing and Semantic Knowledge: A Tool for Detecting Alzheimer Disease?

Impairment in semantic knowledge contributes to Alzheimer disease (AD)-related decline. However, the particulars of the impact AD has on specific domains of knowledge remain debatable. To investigate the impact of AD on specific semantic categories that are integral to daily functions-living things and man-made objects. We administered a free-listing task (written version) to 19 individuals with AD and 15 cognitively normal older adults and assessed the task's relationship with other cognitive and functional tests in clinical use. We compared the contents of the lists of salient concepts generated by the AD and control groups. Group membership (AD or control), after controlling for age, sex, formal education, and an estimate of premorbid intellectual ability, predicted the groups' performance on the free-listing task across two categories. Functional status was inversely related to performance on the free-listing task, holding demographic variables constant. Based on a comparison of the contents of the free lists that were generated by the two groups, it was possible to conclude that, in individuals with AD, conceptual knowledge central to the respective categories was well preserved, whereas the peripheral conceptual material showed evidence of degradation. The free-listing task, which is an easy-to-administer and cost-effective tool, could aid in the preliminary detection of semantic knowledge dysfunction, revealing concepts that are better preserved and, possibly, the characterization of AD. Cognitive assessment tools that can be applied across cultures are needed, and the free-listing task has the potential to address this gap.

Acceptable performance of blood biomarker tests of amyloid pathology - recommendations from the Global CEO Initiative on Alzheimer's Disease.

Anti-amyloid treatments for early symptomatic Alzheimer disease have recently become clinically available in some countries, which has greatly increased the need for biomarker confirmation of amyloid pathology. Blood biomarker (BBM) tests for amyloid pathology are more acceptable, accessible and scalable than amyloid PET or cerebrospinal fluid (CSF) tests, but have highly variable levels of performance. The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to consider the minimum acceptable performance of BBM tests for clinical use. Amyloid PET status was identified as the reference standard. For use as a triaging test before subsequent confirmatory tests such as amyloid PET or CSF tests, the BBM Workgroup recommends that a BBM test has a sensitivity of ≥90% with a specificity of ≥85% in primary care and ≥75-85% in secondary care depending on the availability of follow-up testing. For use as a confirmatory test without follow-up tests, a BBM test should have performance equivalent to that of CSF tests - a sensitivity and specificity of ~90%. Importantly, the predictive values of all biomarker tests vary according to the pre-test probability of amyloid pathology and must be interpreted in the complete clinical context. Use of BBM tests that meet these performance standards could enable more people to receive an accurate and timely Alzheimer disease diagnosis and potentially benefit from new treatments.

Analysis of potential microRNA biomarkers for multiple sclerosis

Multiple sclerosis (MS) is a chronic demyelinating autoimmune neurodegenerative disorder for which no specific blood biomarker is available. MicroRNAs (miRNAs) have been investigated for their diagnostic potential in MS. However, MS-associated miRNAs are rarely replicated in different MS populations, thus impeding their use in clinical testing. Here, we evaluated the fold expression of seven reported MS miRNAs associated with MS incidence and clinical characteristics in 76 MS patients and 75 healthy control plasma samples. We found miR-23a-3p to be upregulated in relapsing-remitting MS (RRMS), while miR-326 was downregulated. MiR-150-5p and -320a-3p were significantly downregulated in secondary progressive MS (SPMS) patients compared to RRMS. High disability was associated with low miR-320a-3p, whereas low BDNF levels were associated with upregulation of miR-150-5p and downregulation of miR-326 expression in the total cohort. MiR-23a-3p and miR-326 showed significant diagnostic sensitivity, specificity, and accuracy for RRMS diagnosis. In addition, miR-150-5p and miR-320a-3p had comparable significant diagnostic test performance metrics distinguishing SPMS from RRMS. Therefore, there is potential for including miR-23a-3p and miR-326 in an RRMS diagnostic miRNA panel. Moreover, we have shown that miR-150-5p and miR-320a-3p could be novel RRMS conversion to SPMS biomarkers. The use of these miRNAs in MS diagnosis and prognosis warrants further investigation.

Evaluating User Experience and DNA Yield from Self-Collection Devices.

The COVID-19 pandemic emphasized an urgent need for devices used in the self-collection of biospecimens in an evolving patient care system. The mailing of biospecimen self-collection kits to patients, with samples returned via mail, provides a more convenient testing regimen, but could also impart patient sampling variabilities. User compliance with device directions is central to downstream testing of collected biospecimens and clear instructions are central to this goal. Here, we performed an evaluation of 10 oral DNA collection devices involving either swab or saliva self-collection and analyzed ease of use and comfort level with a device, as well as DNA recovery quantity/quality and sample stability. We show that while these DNA quality/quantity metrics are comparable between devices, users prefer direct saliva collection over swab-based devices. This information is useful in guiding future experiments including their use in human RNA, microbial, or viral sample collection/recovery and their use in clinical testing.

Advances in the clinical measurement of glucagon: from diagnosis to therapy.

Glucagon has many functions: it promotes glucose production, fatty acid oxidation, thermogenesis, energy consumption, lipolysis, and myocardial contraction, and suppresses lipogenesis, appetite, and gastrointestinal motility. Which of these functions are physiological and which are pharmacological is not fully understood. Although the Mercodia sandwich ELISA provides significantly higher specificity of glucagon measurement than does conventional competitive RIA, it cannot provide accurate plasma glucagon values in the presence of elevated cross-reacting plasma glicentin. This occurs in patients post-pancreatectomy or bariatric surgery and in around 30% of outpatients suspected for glucose intolerance who have not had surgery. Thus, our newly developed sandwich ELISA with higher specificity and higher sensitivity than the Mercodia sandwich ELISA is needed for accurate measurements of plasma glucagon in diabetic patients. It is expected that the new sandwich ELISA will contribute to personalized medicine for diabetes by its use in clinical tests to accurately diagnose the conditions of diabetic patients in order to design better individual treatment strategies. Meanwhile, clinical trials are being conducted worldwide to apply glucagon/GLP-1 receptor dual agonists and glucagon/GLP-1/GIP receptor triagonists to the treatment of obesity, fatty liver, and diabetes. Most clinical trials have shown that both types of drugs have stronger effects on weight reduction, improving fatty liver, and glucose tolerance than do the single GLP-1 receptor agonists. Glucagon is expected to be used as a new diagnostic marker and in a new therapeutic strategy based on a true understanding of its physiological and pharmacological functions.

Abstract 6416: Early stage endometrioid endometrial cancer recurrence risk stratification using a machine learning RNA-seq gene expression signature

Abstract Endometrioid endometrial cancer (EEC) adjuvant therapy decisions rely on risk stratification using histology, grade, stage, and lymphovascular space invasion (LVSI). Recently, molecular classification systems originating from TCGA, evaluated in GOG-210 and PORTEC-3 defined four prognostic subtypes based on POLE, MSI-H/MMR-D, and p53 alterations. Although valuable, this molecular approach still has significant limitations such as applicability to the majority of EEC patients categorized as no-specific molecular profile (NSMP) and the potential need to resolve pathogenic and prognostic heterogeneity within MMR-D, and TP53 subtypes. These unmet needs were key motivators for Tempus to develop a molecular classifier predicting distant recurrence risk in early-stage EEC with a focus on high intermediate-risk (HIR) patients. The RNA-seq-based gene expression profiler (GEP) was trained using a machine-learning pipeline with TCGA data which resulted in a 24 gene signature that classifies EEC patients as molecular risk (MR) high or low (MR-high, MR-low). The GEP MR test was then evaluated on a de-identified cohort of EEC patients (N=1037) from Tempus to test associations with known pathologic or molecular prognostic features. The GEP-MR risk predictor showed significant enrichment of MR high-risk in G3 versus G1/2 histology (p-value < 5e-8). A high correlation was found between the MR score and copy number alteration score (t-test p-value < 1e-5). Next, a clinical evaluation was performed in an early-stage EEC case-control cohort of patients with documented recurrence or no recurrence event at four years (N=109), from Stanford. In the entire cohort, the MR-high group had a significantly higher rate of distant recurrence in comparison to the MR-low group (HR=4.8, N=109). Next, we performed a subgroup analysis in the clinically important HIR patients. In this subgroup, the MR-high group had a significantly higher rate of distant recurrence in comparison to the MR-low group (HR=8.0, N=56). Lastly, given the significance of genomic biomarkers in the evolution of EEC FIGO staging, we stratified outcomes by the established TCGA subtypes as a reference standard and performed a subgroup analysis in patients classified as having no specific molecular profile (NSMP). Among patients who were NSMP, the MR-high group showed a significantly higher rate of distant recurrence in comparison to the MR-low group (HR=7.92, N=67). These evaluation studies demonstrate the performance of the GEP MR test in early-stage EEC distant recurrence risk stratification, specifically HIR patients, necessitating further studies to validate the test for clinical use in informing adjuvant clinical management. Citation Format: Rafi Pelossof, Talal Ahmed, Seung Won Hyun, Chithra Sangali, Ben Terdich, Calvin Chao, Michael Toboni, Casey Cosgrove, Elizabeth Kidd, Brook Howitt, Timothy Taxter. Early stage endometrioid endometrial cancer recurrence risk stratification using a machine learning RNA-seq gene expression signature [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6416.

On the Feasibility of Using Behavioral Listening Effort Test Methods to Evaluate Auditory Performance in Cochlear Implant Users.

Realistic outcome measures that reflect everyday hearing challenges are needed to assess hearing aid and cochlear implant (CI) fitting. Literature suggests that listening effort measures may be more sensitive to differences between hearing-device settings than established speech intelligibility measures when speech intelligibility is near maximum. Which method provides the most effective measurement of listening effort for this purpose is currently unclear. This study aimed to investigate the feasibility of two tests for measuring changes in listening effort in CI users due to signal-to-noise ratio (SNR) differences, as would arise from different hearing-device settings. By comparing the effect size of SNR differences on listening effort measures with test-retest differences, the study evaluated the suitability of these tests for clinical use. Nineteen CI users underwent two listening effort tests at two SNRs (+4 and +8 dB relative to individuals' 50% speech perception threshold). We employed dual-task paradigms-a sentence-final word identification and recall test (SWIRT) and a sentence verification test (SVT)-to assess listening effort at these two SNRs. Our results show a significant difference in listening effort between the SNRs for both test methods, although the effect size was comparable to the test-retest difference, and the sensitivity was not superior to speech intelligibility measures. Thus, the implementations of SVT and SWIRT used in this study are not suitable for clinical use to measure listening effort differences of this magnitude in individual CI users. However, they can be used in research involving CI users to analyze group data.

Free‐listing and semantic knowledge: A diagnostic tool for detecting Alzheimer’s disease?

AbstractBackgroundA semantic memory impairment figures prominently among the manifestations of Alzheimer’s disease (AD). That impairment manifests itself relatively early in the disease trajectory with longitudinal studies showing evidence in patients with mild cognitive impairment and preclinical AD. We investigate the impact of AD on specific semantic categories integral to daily function: living kinds and artefacts.MethodWe relied on a “free‐listing task” as developed in cultural domain analysis, and assessed its relationship with other cognitive and functional tests in clinical use. We chose the written version for the elicitation of the free‐lists that we analyze here. A written format leads to the generation of longer lists than an oral elicitation. The participant pool was comprised of 19 AD patients and a control group, 15 cognitively normal age‐matched adults.ResultThe median number of items generated in each list for the patients was 12 for living things and 18 for man‐made objects, for the control group, 39 and 45, respectively. Controlling for age, education, estimate of premorbid intellectual ability, and sex, group membership (AD or control) predicts performance in the free‐listing in the two categories. Holding demographic variables constant, functional status is inversely related to the performance on free‐listing.ConclusionEven when provided the modality (written) to generate longer lists, individuals with AD still performed worse than controls. Our findings confirm previous observations identifying an impairment of semantic knowledge in AD. Free‐listing is effective at detecting this impairment. This easy‐to‐administer, cost‐effective tool could facilitate the fast preliminary characterization of AD in distinct cultural environments.

A-149 Performance Characteristics of VerifyNow PRU and ARU Tests During a Clinical Method Verification Exercise

Abstract Background Dual antiplatelet therapy with aspirin and a platelet P2Y12 receptor antagonist is indicated for the prevention of atherothrombotic events in patients with acute coronary syndromes and for those undergoing percutaneous coronary intervention procedure. Two different assays are available in the VerifyNow Test device for monitoring the anti-platelet therapy response. The aspirin assay (ARU Test) utilizes arachidonic acid as an agonist and is sensitive to acyl salicylic acid. The P2Y12 assay (PRU test) is sensitive to thienopyridines (such as clopidogrel, prasugrel, ticagrelor) and uses adenosine diphosphate (ADP) as an agonist. The PRU test is a non-waived test and ARU test is a waived test. A comprehensive method performance verification is required for the PRU test. We evaluated performance characteristics of the VerifyNow PRU Test and ARU Test for clinical use. Methods The standard precision and accuracy study using two levels (low and high) of quality control materials were performed (N = 10) for both the assays. Alternative qualitative method comparison was carried out (N = 49) using the VerifyNow PRU Test in a reference lab and in-house. The in-house inter-instrument comparisons were carried out (N = 42). The blood samples were obtained from patients taking P2Y12 inhibitors and from normal donors not on any drugs. The results of the PRU Test are expressed in P2YI2 reaction units (PRU). The VerifyNow-Aspirin assay results are expressed as aspirin reaction units (ARU). The statistical analysis to evaluate performance characteristics was carried out using the EP Evaluator. Results The VerifyNow device 1561 precision characteristics for low QC (Obs Mean = 1.5 PRU (N = 10), SD = 0.2; 95% CI for Obs Mean 1.0 to 2.0 PRU) and high QC (Obs Mean = 258.3 PRU (N = 10), SD = 8.2; 95% CI for Obs Mean 252.4 to 264.2 PRU) were within acceptable performance limits. The CV for high QC was 3.2%. The ARU test also demonstrated high precision for two levels (Low QC Obs Mean = 350ARU (N = 10), SD = 0.0); High QC Obs Mean = 583.3 (N = 10), SD = 7.2; 95% CI for Obs Mean = 578.1–588.5) with a CV of 1.2%. The PRU Test Method PRU 1561 In House vs Ref Method Verify Now PRU Test (N = 49) demonstrated overall agreement of 93.9% with positive agreement (intended use population on drugs, N = 27) of 92% and negative agreement (normal non-drug group, N = 22) of 95.8% (Cohen’s Kappa = 87.8%; Kappa >75% indicates “"high” agreement). The McNemar Test for Symmetry passed (P > 0.999, Fisher’s Exact test) in this qualitative method comparison. A value of P < 0.05 would suggest the methods are significantly different. The other in-house instrument 1562 also demonstrated comparable or better performance characteristics. Conclusion It is important to confirm the medical decision limit for the intended use population and determine acceptance criteria while considering biologic variability. However, the reference range verifications with drug responders and non-responders are not always feasible and cost-effective. Based on the qualitative method comparison in this study, we have transferred the medical decision limits from the peer group. The in-house multi-instrument comparison should be repeated every six months to monitor the performance of the instruments.

Alzheimer Disease Biomarkers: Moving from CSF to Plasma for Reliable Detection of Amyloid and tau Pathology.

Development of validated biomarkers to detect early Alzheimer disease (AD) neuropathology is needed for therapeutic AD trials. Abnormal concentrations of "core" AD biomarkers, cerebrospinal fluid (CSF) amyloid beta1-42, total tau, and phosphorylated tau correlate well with neuroimaging biomarkers and autopsy findings. Nevertheless, given the limitations of established CSF and neuroimaging biomarkers, accelerated development of blood-based AD biomarkers is underway. Here we describe the clinical significance of CSF and plasma AD biomarkers to detect disease pathology throughout the Alzheimer continuum and correlate with imaging biomarkers. Use of the AT(N) classification by CSF and imaging biomarkers provides a more objective biologically based diagnosis of AD than clinical diagnosis alone. Significant progress in measuring CSF AD biomarkers using extensively validated highly automated assay systems has facilitated their transition from research use only to approved in vitro diagnostics tests for clinical use. We summarize development of plasma AD biomarkers as screening tools for enrollment and monitoring participants in therapeutic trials and ultimately in clinical care. Finally, we discuss the challenges for AD biomarkers use in clinical trials and precision medicine, emphasizing the possible ethnocultural differences in the levels of AD biomarkers. CSF AD biomarker measurements using fully automated analytical platforms is possible. Building on this experience, validated blood-based biomarker tests are being implemented on highly automated immunoassay and mass spectrometry platforms. The progress made developing analytically and clinically validated plasma AD biomarkers within the AT(N) classification scheme can accelerate use of AD biomarkers in therapeutic trials and routine clinical practice.

Advancements in portable instruments based on affinity-capture-migration and affinity-capture-separation for use in clinical testing and life science applications

The shift from testing at centralized diagnostic laboratories to remote locations is being driven by the development of point-of-care (POC) instruments and represents a transformative moment in medicine. POC instruments address the need for rapid results that can inform faster therapeutic decisions and interventions. These instruments are especially valuable in the field, such as in an ambulance, or in remote and rural locations. The development of telehealth, enabled by advancements in digital technologies like smartphones and cloud computing, is also aiding in this evolution, allowing medical professionals to provide care remotely, potentially reducing healthcare costs and improving patient longevity. One notable POC device is the lateral flow immunoassay (LFIA), which played a major role in addressing the COVID-19 pandemic due to its ease of use, rapid analysis time, and low cost. However, LFIA tests exhibit relatively low analytical sensitivity and provide semi-quantitative information, indicating either a positive, negative, or inconclusive result, which can be attributed to its one-dimensional format. Immunoaffinity capillary electrophoresis (IACE), on the other hand, offers a two-dimensional format that includes an affinity-capture step of one or more matrix constituents followed by release and electrophoretic separation. The method provides greater analytical sensitivity, and quantitative information, thereby reducing the rate of false positives, false negatives, and inconclusive results. Combining LFIA and IACE technologies can thus provide an effective and economical solution for screening, confirming results, and monitoring patient progress, representing a key strategy in advancing diagnostics in healthcare.

Obstructive sleep apnea detection with nonlinear analysis of speech

Studies on the detection of Obstructive Sleep Apnea (OSA) from speech recording have brought an important innovation to this field. This study is based on the hypothesis that the deterioration of the muscles and tissues in the vocal tract in OSA patients changes the nonlinear properties of voice. In this study, the features that reveal the nonlinear structure of the speech for OSA detection were investigated. The nonlinear characteristics were evaluated for vowels and consonants, and it was tried to find out in which voice group the nonlinear features were more distinctive in OSA. The nonlinear analysis was applied to a wide variety of voice samples having vocal tract components affected by OSA, and OSA/healthy classifications were realized. The results revealed that nonlinear analysis gives considerable findings in OSA detection, and consonants are more successful than vowels. For classifications, K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) classifiers, 5-fold cross validation procedure and Minimum Redundancy Maximum Relevance (MRMR) feature selection method were used. Using the whole dataset, OSA detection performance for vowels was found as 83.5% with KNN, and 96% with SVM for consonants. Additionally, the test process was carried out by using a distinct group, and 82.5% test accuracy was achieved with only 6 features for consonants. The results indicated that the proposed study supports the hypothesis that the nonlinear behavior of vocal tract changes in subjects with OSA, especially for consonants, and has considerable potential for OSA detection as the pre-diagnosis or screening test in clinical use.

The Clinical Laboratory Is an Integral Component to Health Care Delivery : An Expanded Representation of the Total Testing Process.

Developing an expanded representation of the total testing process that includes contemporary elements of laboratory practice can be useful to understanding and optimizing testing workflows across clinical laboratory and patient care settings. Published literature and meeting reports were used by the coauthors to inform the development of the expanded representation of the total testing process and relevant examples describing its uses. A visual representation of the total testing process was developed and contextualized to patient care scenarios using a number of examples covering the detection of blood culture contamination, use of next-generation sequencing, and pharmacogenetic testing. The expanded representation of the total testing process can serve as a model and framework to document and improve the use of clinical testing within the broader context of health care delivery. This representation recognizes increased engagement among clinical laboratory professionals with patients and other health care providers as essential to making informed decisions. The increasing use of data is highlighted as important to ensuring quality, appropriate test utilization, and sustaining an efficient workflow across clinical laboratory and patient care settings. Maintaining a properly resourced and competent workforce is also featured as an essential component to the testing process.

Radiometal chelators for infection diagnostics.

Infection of native tissues or implanted devices is common, but clinical diagnosis is frequently difficult and currently available noninvasive tests perform poorly. Immunocompromised individuals (for example transplant recipients, or those with cancer) are at increased risk. No imaging test in clinical use can specifically identify infection, or accurately differentiate bacterial from fungal infections. Commonly used [18F]fluorodeoxyglucose (18FDG) positron emission computed tomography (PET/CT) is sensitive for infection, but limited by poor specificity because increased glucose uptake may also indicate inflammation or malignancy. Furthermore, this tracer provides no indication of the type of infective agent (bacterial, fungal, or parasitic). Imaging tools that directly and specifically target microbial pathogens are highly desirable to improve noninvasive infection diagnosis and localization. A growing field of research is exploring the utility of radiometals and their chelators (siderophores), which are small molecules that bind radiometals and form a stable complex allowing sequestration by microbes. This radiometal-chelator complex can be directed to a specific microbial target in vivo, facilitating anatomical localization by PET or single photon emission computed tomography. Additionally, bifunctional chelators can further conjugate therapeutic molecules (e.g., peptides, antibiotics, antibodies) while still bound to desired radiometals, combining specific imaging with highly targeted antimicrobial therapy. These novel therapeutics may prove a useful complement to the armamentarium in the global fight against antimicrobial resistance. This review will highlight current state of infection imaging diagnostics and their limitations, strategies to develop infection-specific diagnostics, recent advances in radiometal-based chelators for microbial infection imaging, challenges, and future directions to improve targeted diagnostics and/or therapeutics.

A Longitudinal Analysis of the Internal Rotation and Shift (IRO/Shift) Test Following Arthroscopic Repair of Superior Rotator Cuff Lesions.

Although the use of clinical tests to diagnose superior rotator cuff pathology is common, there is paucity in the research regarding the accuracy of such tests following arthroscopic repair. The aim of this study was to determine the accuracy of the IRO/Shift test compared to the Jobe test at 3 months and 6 months post-surgery for superior rotator cuff repair. Arthroscopic repair was conducted on 51 patients who were subsequently seen for clinical evaluation at 3 and 6 months following surgery. At 3 months post-surgery only 27% of the patients had a negative IRO/Shift test and 18% had a negative Jobe test. However, at 6 months 88% of the patients presented with a negative IRO/Shift test and 61% a negative Jobe test. When compared to each other, the IRO/Shift test and the Jobe test had 90% agreement pre-operatively, 71% agreement at 3 months post-surgery, and 67% agreement at 6 months. These results demonstrate that the accuracy of the IRO/Shift test and the Jobe test improved between 3 and 6 months following arthroscopic surgery of the superior rotator cuff, with the IRO/Shift test having better accuracy.

Plasma p‐tau181 concentration accurately predicts clinically diagnosed Alzheimer’s Disease cases

AbstractBackgroundThe feasibility of detecting tau phosphorylated at threonine‐181(p‐tau181) in CSF makes it a valuable biomarker for diagnosis in the field of Alzheimer’s Disease (AD). Recently, the novel technologies accurately measuring biomarkers directly in blood offer a unique advantage for use in clinical testing and trials. This study describes the performance testing of a novel plasma p‐tau181 Simoa assay to predict clinical AD.MethodThe presented data were obtained after analysis of EDTA plasma from cases with clinical AD who had been referred to the UBC Hospital Clinic with complaint of cognitive impairment and were assessed for dementia and AD between 2008 – 2018.We also analysed serum of 50 random healthy donors and 50 aged ‐ matched controls with normal cognition. The samples were assayed using an ADx Neurosciences developed p‐tau181 specific Simoa assay. Analytical performance (precision, detection limit, parallelism) and analyte stability was evaluated using healthy‐donor samples. Finally, the p‐tau181 specificity was assessed using synthetic peptides.Result254 AD patients (female = 125) and 100 controls (female = 39) were included. The average of plasma p‐tau181 was 72.9 ±36.8 ng/L in AD cases and the average of serum p‐tau181 was 8.1± 10.5 ng/L in controls.The concentration of plasma p‐tau181 in patients with AD was significantly increased with at‐least 9‐fold versus controls (p=<0.001). ROC analysis demonstrated an AUC of 0.92 and a suitable clinical cut‐off of 34.3 ng/L. Analytical performance testing: 1 of the 254 AD samples tested were below the LLOQ of 1.38 ng/L. The intra‐ and inter‐ assay variability was 8.2% CV and 11.8 % CV, respectively. Sample dilution (df 2‐4‐5‐6) resulted in mean parallelism of 93.5 %. P‐tau181 levels were stable up to 5 Freeze/Thaw cycle (mean 98.9%) and up to 24h at 4°C or RT. The assay was found to be highly specific towards p‐tau181 and nonreactive to p‐tau175.ConclusionThe plasma p‐tau181 concentration in AD cases were significantly higher than controls with limited overlap and in line with published data. The specific measurement of plasma p‐tau181 shows good promise in offering a non‐biased measurement and help in the clinical assessment of AD patients and clinical trials.

A Serodiagnostic IgM ELISA to Detect Acute Cytauxzoonosis.

Cytauxzoonosis is a tick-borne infectious disease affecting domestic cats with high mortality and limited treatment modalities. Because early diagnosis and therapeutic intervention are crucial to survival of infected cats, the objective of this study was to develop an ELISA capable of detecting cytauxzoonosis and differentiating acute vs. chronic infection in clinical feline blood samples. A microsphere immunoassay (MIA) was developed to evaluate the production of Cytauxzoon felis-specific IgM and IgG antibodies in serial plasma samples from cats with experimental C. felis infection by targeting a C. felis-specific transmembrane protein (c88). Recombinant c88 protein was utilized to develop indirect ELISAs to detect IgM and IgG antibodies in clinical plasma samples from: PCR-positive cats with acute C. felis infection (n = 36), C. felis-negative cats with pyrexia (n = 10), healthy C. felis-negative cats (n = 22), and chronic C. felis carriers (n = 4). Anti-c88 IgM antibodies were detectable at day 12 post-tick infestation in cats with experimental C. felis infection (within 24 hours of developing clinical signs), while anti-c88 IgG was detectable at day 15 post-tick infestation – indicating IgM could be used to detect early infection. Using a cut-off value of 19.85 percent positive, the C. felis IgM ELISA detected acute cytauxzoonosis in 94.44% (34/36) of cats presented with clinical signs of acute cytauxzoonosis with 100% specificity (indicating a “Strong Positive” result). When a lower cutoff of 8.60 percent positive was used, cytauxzoonosis was detected in the 2 remaining PCR-positive cats with 87.88% specificity (indicating of a “Weak Positive” result). One C. felis-negative, febrile cat had high IgG, and chronic carriers had variable IgM and IgG results. Combined interpretation of IgM and IgG ELISAs did not reliably differentiate acute vs. chronic infection. While further validation on assay performance is needed, the C. felis IgM ELISA is a promising test to detect acute cytauxzoonosis and can be utilized to develop a point-of-care test for clinical use.

Development and characterization of anti-HPV16 monoclonal antibodies for assembly of an HPV16 detection kit.

Quality control is very important during the development of 3-valent (16/18/58), 9-valent (6/11/16/18/31/33/45/52/58), and 15-valent human papillomavirus (HPV) vaccines (6/11/16/18/31/33/35/39/45/52/56/58/59/68). All 3-valent, 9-valent, and 15-valent HPV vaccines contain the HPV16 antigen; therefore, a detection method that can specifically identify HPV16 in vaccines is urgently required. This study aimed to develop and characterize monoclonal antibodies to assemble a highly specific HPV16 detection kit. The HPV16 L1 pentameric protein developed as an immunogen was used to prepare monoclonal antibodies. From the pool of prepared monoclonal antibodies, we selected 4G12 and 5A6 to screen and evaluate their subtypes, specificity, neutralizing activity, serum competition, binding affinity, and gene sequencing. After these characterizations, an enzyme-linked immunosorbent assay kit for these monoclonal antibodies was developed, and excellent quality was demonstrated in the assessment of linearity, repeatability, and specificity. The developed detection kit has great potential for wide use in clinical testing and quality control in vaccine production processes.

Multi-Omics Interdisciplinary Research Integration to Accelerate Dementia Biomarker Development (MIRIADE).

Proteomics studies have shown differential expression of numerous proteins in dementias but have rarely led to novel biomarker tests for clinical use. The Marie Curie MIRIADE project is designed to experimentally evaluate development strategies to accelerate the validation and ultimate implementation of novel biomarkers in clinical practice, using proteomics-based biomarker development for main dementias as experimental case studies. We address several knowledge gaps that have been identified in the field. First, there is the technology-translation gap of different technologies for the discovery (e.g., mass spectrometry) and the large-scale validation (e.g., immunoassays) of biomarkers. In addition, there is a limited understanding of conformational states of biomarker proteins in different matrices, which affect the selection of reagents for assay development. In this review, we aim to understand the decisions taken in the initial steps of biomarker development, which is done via an interim narrative update of the work of each ESR subproject. The results describe the decision process to shortlist biomarkers from a proteomics to develop immunoassays or mass spectrometry assays for Alzheimer's disease, Lewy body dementia, and frontotemporal dementia. In addition, we explain the approach to prepare the market implementation of novel biomarkers and assays. Moreover, we describe the development of computational protein state and interaction prediction models to support biomarker development, such as the prediction of epitopes. Lastly, we reflect upon activities involved in the biomarker development process to deduce a best-practice roadmap for biomarker development.

P432: RISK STRATIFICATION IN ACUTE MYELOID LEUKEMIA: EXTERNAL VALIDATION OF THE STELLAE-123 GENE EXPRESSION MODEL AND COMPARISON WITH CURRENT PROGNOSTIC SCORES

Background: The identification of recurrently mutated genes and cytogenetic anomalies has provided high prognostic and therapeutic significance in patients diagnosed with AML. Currently, some of this information has been incorporated into risk stratification guidelines, such as those of the European Leukemia Net (ELN). However, these guidelines are based on cytogenetic analyses and a limited number of mutations, and they don’t consider the genomic complexity of AML. Recently, we presented a new prognostic score based on gene expression analysis (Stellae-123) which achieved high discriminative power in survival prediction of AML patients, particularly among those bearing high-risk mutations. It is necessary to evaluate this signature in new AML cohorts and to test its performance compared with standard risk stratification scores. Aims: To validate the prognostic precision and discriminative power of the Stellae-123 gene expression signature in external cohorts and to compare its performance with standard prognostic scores: ELN-2017 in adult patients and clinical risk score in pediatric patients. Methods: RNA-seq data from 2 adult cohorts and one pediatric AML cohort was retrieved. The BeatAML (N=334) and the AMLCG-2008 (N=199) cohorts consisted of adult AML patients, whereas the TARGET AML cohort (N=144) was composed solely of pediatric patients. Gene expression estimates (FPKM) were normalized between cohorts using ComBat. Common genes were retrieved, and we selected those included in the Stellae-123 predictor, reaching a total of 69 genes. Random forests were built to predict survival in the largest cohort (BeatAML). The precision of the predictors was evaluated using cross-validated time-dependent AUCs derived from cox models. In the particular case of BeatAML, gene expression survival models were based on out-of-bag predictions in order to reduce the risk of overfitting during the training phase of the model. Results: We initially built a survival predictor using random forests based on the expression of the 69 genes incorporated in Stellae-123. This predictor was trained in the BeatAML cohort, and external validation was performed on the remaining two cohorts. The model achieved c-indexes of 0.635, 0.645 and 0.598 in the BeatAML, AMLCG-2008 and TARGEL AML cohorts, respectively. We then evaluated the precision of this signature to predict survival at 6 months, 1 year and 2 years after diagnosis using cross-validated cox models. The results indicated that this model achieved greater precision than the ELN-2017 and the pediatric clinical risk score in the majority of evaluated time points (Figure 1). Since age is a variable deeply associated with survival in AML, we evaluated the performance of the models including this covariate. We observed clear improvements in AUCs for the BeatAML and TargetAML, but not for the AMLCG-2008 cohort, a finding which is probably related to the fact that these were fit adult patients recruited in a clinical trial. Notably, we also observed an improved performance of the gene expression signature plus age model compared with the ELN-2017 and pediatric clinical risk scores plus age models, particularly in the prediction of survival within the first year after diagnosis. Image:Summary/Conclusion: The Stellae-123 gene expression signature can predict overall survival in AML with greater precision than the ELN-2017 and the pediatric clinical risk score. Therefore, gene expression profiling emerges as a powerful tool to optimize patient risk stratification. There is a growing need to standardize these tests for clinical use.