Journal articles on the topic 'Longitudinal biomarker analysis'
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Pineau, Fanny, Davide Caimmi, Sylvie Taviaux, Maurane Reveil, Laura Brosseau, Isabelle Rivals, Margot Drevait, et al. "DNA Methylation at ATP11A cg11702988 Is a Biomarker of Lung Disease Severity in Cystic Fibrosis: A Longitudinal Study." Genes 12, no. 3 (March 19, 2021): 441. http://dx.doi.org/10.3390/genes12030441.
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Cystic fibrosis (CF) is a chronic genetic disease that mainly affects the respiratory and gastrointestinal systems. No curative treatments are available, but the follow-up in specialized centers has greatly improved the patient life expectancy. Robust biomarkers are required to monitor the disease, guide treatments, stratify patients, and provide outcome measures in clinical trials. In the present study, we outline a strategy to select putative DNA methylation biomarkers of lung disease severity in cystic fibrosis patients. In the discovery step, we selected seven potential biomarkers using a genome-wide DNA methylation dataset that we generated in nasal epithelial samples from the MethylCF cohort. In the replication step, we assessed the same biomarkers using sputum cell samples from the MethylBiomark cohort. Of interest, DNA methylation at the cg11702988 site (ATP11A gene) positively correlated with lung function and BMI, and negatively correlated with lung disease severity, P. aeruginosa chronic infection, and the number of exacerbations. These results were replicated in prospective sputum samples collected at four time points within an 18-month period and longitudinally. To conclude, (i) we identified a DNA methylation biomarker that correlates with CF severity, (ii) we provided a method to easily assess this biomarker, and (iii) we carried out the first longitudinal analysis of DNA methylation in CF patients. This new epigenetic biomarker could be used to stratify CF patients in clinical trials.
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Dodd, Lori E., Reed F. Johnson, Joseph E. Blaney, and Dean Follmann. "Matched Longitudinal Analysis of Biomarkers Associated with Survival." Clinical and Vaccine Immunology 21, no. 8 (June 18, 2014): 1145–52. http://dx.doi.org/10.1128/cvi.00252-14.
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ABSTRACTThe identification of host or pathogen factors linked to clinical outcome is a common goal in many animal studies of infectious diseases. When the disease is fatal, statistical analysis of such factors may be biased from missing observations due to deaths. For example, when observations of a subject are censored before completing the intended study period, the complete trajectory will not be observed. Even if the factor is not associated with outcome, comparisons of data from survivors with those from nonsurvivors may lead to the wrong conclusions regarding associations with survival. Comparisons between subjects must account for differing observation lengths for those who survive relative to those who do not. Analyzing data over an interval common to all subjects provides one solution but requires eliminating data, some of which may be informative about the differences between groups. Here, we present a novel approach, matched longitudinal analysis (MLA), for analyzing such data based on matching biomarker intervals for survivors and nonsurvivors. We describe the results from simulation studies and from a study of monkeypox virus infection in nonhuman primates. In our application, MLA identified low monocyte chemoattractant protein-1 (MCP-1) levels as having a statistically significant association with survival, whereas the alternative methods did not identify an association. The method has general application to longitudinal studies that seek to find associations of biomarker changes with survival.
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Corzett, Todd H., Imola K. Fodor, Megan W. Choi, Vicki L. Walsworth, Kenneth W. Turteltaub, Sandra L. McCutchen-Maloney, and Brett A. Chromy. "Statistical Analysis of Variation in the Human Plasma Proteome." Journal of Biomedicine and Biotechnology 2010 (2010): 1–12. http://dx.doi.org/10.1155/2010/258494.
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Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.
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Winkel, Per, Jørgen Hilden, Janus Christian Jakobsen, Jane Lindschou, Gorm Boje Jensen, Erik Kjøller, Ahmad Sajadieh, et al. "A screening method to spot biomarkers that may warn of serious events in a chronic disease – illustrated by cardiological CLARICOR trial data." Clinical Chemistry and Laboratory Medicine (CCLM) 59, no. 11 (August 12, 2021): 1852–60. http://dx.doi.org/10.1515/cclm-2021-0333.
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Abstract Objectives To develop a crude screening method for detecting biomarkers which frequently exhibit a rise (or fall) in level prior to a serious event (e.g. a stroke) in patients with a chronic disease, signalling that the biomarker may have an alarm-raising or prognostic potential. The subsequent assessment of the marker’s clinical utility requires costly, difficult longitudinal studies. Therefore, initial screening of candidate-biomarkers is desirable. Methods The method exploits a cohort of patients with biomarkers measured at entry and with recording of first serious event during follow-up. Copying those individual records onto a common timeline where a specific event occurs on the same day (Day 0) for all patients, the baseline biomarker level, when plotted against the patient’s entry time on the revised timeline, will have a positive (negative) regression slope if biomarker levels generally rise (decline) the closer one gets to the event. As an example, we study 1,958 placebo-treated patients with stable coronary artery disease followed for nine years in the CLARICOR trial (NCT00121550), examining 11 newer biomarkers. Results Rising average serum levels of cardiac troponin T and of N-terminal pro-B-type natriuretic peptide were seen prior to a fatal cardiovascular outcome. C-reactive protein rose prior to non-cardiovascular death. Glomerular filtration rate, seven lipoproteins, and nine newer cardiological biomarkers did not show convincing changes. Conclusions For early detection of biomarkers with an alarm-raising potential in chronic diseases, we proposed the described easy procedure. Using only baseline biomarker values and clinical course of participants with coronary heart disease, we identified the same cardiovascular biomarkers as those previously found containing prognostic information using longitudinal or survival analysis.
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Schluchter, Mark D., and Annalisa V. Piccorelli. "Shared parameter models for joint analysis of longitudinal and survival data with left truncation due to delayed entry – Applications to cystic fibrosis." Statistical Methods in Medical Research 28, no. 5 (April 4, 2018): 1489–507. http://dx.doi.org/10.1177/0962280218764193.
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Many longitudinal studies observe time to occurrence of a clinical event such as death, while also collecting serial measurements of one or more biomarkers that are predictive of the event, or are surrogate outcomes of interest. Joint modeling can be used to examine the relationship between the biomarker and the event, and also as a way of adjusting analyses of the biomarker for non-ignorable dropout. In settings such as registry studies, an additional complexity is caused when follow-up of subjects is delayed, referred to as left-truncation of follow-up in the survival analysis setting. If not adjusted for, this can cause bias in estimation of parameters of the survival distribution for the clinical event and in parameters of the longitudinal outcome such as the profile or rate of change over time because subjects may die or have the clinical event before follow-up starts. This paper illustrates how a broad class of shared parameter models can be used to jointly model a time to event outcome along with a longitudinal marker using available nonlinear mixed modeling software, when follow-up times are left truncated. Methods are applied to jointly model survival and decline in lung function in cystic fibrosis patients.
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Hyun, Jae-Won, Yeseul Kim, Gayoung Kim, Su-Hyun Kim, and Ho Jin Kim. "Longitudinal analysis of serum neurofilament light chain: A potential therapeutic monitoring biomarker for multiple sclerosis." Multiple Sclerosis Journal 26, no. 6 (March 26, 2019): 659–67. http://dx.doi.org/10.1177/1352458519840757.
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Objectives: Serum neurofilament light chain (sNfL) has been proposed a potential biomarker in multiple sclerosis (MS) based on mainly cross-sectional observations in Western population. To clarify clinical implication of sNfL, we longitudinally analysed sNfL levels at multiple time points in Korean MS patients undergoing alemtuzumab therapy. Methods: Between 2016 and 2018, 144 sera from 17 MS patients treated with alemtuzumab at National Cancer Centre and 35 sera from 35 age- and gender-matched healthy controls (HCs) were collected for a longitudinal study with a mean 21-month follow-up. The sera were measured for sNfL levels using single molecule array. Patients were classified into two groups: evidence of disease activity (EDA) or no evidence of disease activity (NEDA). Results: During alemtuzumab therapy, sNfL levels in EDA patients were significantly higher than those in NEDA patients and HCs ( p < 0.001). In longitudinal analysis, the sNfL levels were consistently low in NEDA patients, while it consistently increased in radiologically and/or clinically active status in EDA patients. All sNfL levels in radiologically and/or clinically active status samples were higher than those in inactive status samples. Conclusion: These results suggest that sNfL is a promising monitoring biomarker for personalized therapeutics in MS patients.
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Stubbings, Garrett, Spencer Farrell, Arnold Mitnitski, Kenneth Rockwood, and Andrew Rutenberg. "The Quantile Frailty Index: A Cutpoint-Free Approach to Biomarker-Based Health Assessment." Innovation in Aging 4, Supplement_1 (December 1, 2020): 180. http://dx.doi.org/10.1093/geroni/igaa057.582.
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Abstract We develop a frailty index (FI) from continuous valued biomarker measurements that does not use thresholds to binarize deficits. In this work we construct a quantile frailty index (FI-Q) directly from risk quantiles, without binarizing the deficits. FI-Q is the average risk quantile for an individual in the population with respect to the set of measured biomarkers. We show that FI-Q predicts adverse health outcomes better than either a quantile-based cutpoint approach or an FI-Lab method used in previous studies. We also address practical questions such as how to use longitudinal data. We use data from the English Longitudinal Study of Ageing (ELSA) for longitudinal analysis and data from the National Health and Nutrition Examination Survey (NHANES) and the Canadian Study of Health and Aging (CSHA) to compare predictive value of FI-QM with previous FI-Lab studies.
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Li, Menghan, Ching-Wen Lee, and Lan Kong. "A latent class approach for joint modeling of a time-to-event outcome and multiple longitudinal biomarkers subject to limits of detection." Statistical Methods in Medical Research 29, no. 6 (August 30, 2019): 1624–38. http://dx.doi.org/10.1177/0962280219871679.
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Multiple biomarkers on different biological pathways are often measured over time to investigate the complex mechanism of disease development and progression. Identification of informative subpopulation patterns of longitudinal biomarkers and clinical endpoint may assist in risk stratification and provide insights into new therapeutic targets. Motivated by a multicenter study to assess the inflammatory markers of sepsis in patients with community-acquired pneumonia, we propose a joint latent class analysis of multiple biomarkers and a time-to-event outcome while accounting for censored biomarker measurements due to detection limits. The interrelationship between biomarker trajectories and clinical endpoint is fully captured by a latent class structure, which reveals the subpopulation profiles of biomarkers and clinical outcome. The estimation of joint latent class models becomes more complicated when biomarkers are subject to detection limits. Based on a Metropolis–Hastings method, we develop a Monte Carlo Expectation–Maximization (MCEM) algorithm to estimate model parameters. We demonstrate the satisfactory performance of our MCEM algorithm using simulation studies, and apply our method to the motivating study to examine the heterogeneous patterns of cytokine responses to pneumonia and associated mortality risks.
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DiGregorio, J., A. Gibicar, H. Khosravani, P. Jabehdar Maralani, J. C. Tardif, P. N. Tyrrell, A. R. Moody, and A. Khademi. "Cross-sectional and longitudinal Biomarker extraction and analysis for multicentre FLAIR brain MRI." Neuroimage: Reports 2, no. 2 (June 2022): 100091. http://dx.doi.org/10.1016/j.ynirp.2022.100091.
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Lin, Haiqun, Bruce W. Turnbull, Charles E. McCulloch, and Elizabeth H. Slate. "Latent Class Models for Joint Analysis of Longitudinal Biomarker and Event Process Data." Journal of the American Statistical Association 97, no. 457 (March 2002): 53–65. http://dx.doi.org/10.1198/016214502753479220.
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Schröter, Katrin, Murielle Brum, Nathalie Brunkhorst-Kanaan, Franziska Tole, Christiane Ziegler, Katharina Domschke, Andreas Reif, and Sarah Kittel-Schneider. "Longitudinal multi-level biomarker analysis of BDNF in major depression and bipolar disorder." European Archives of Psychiatry and Clinical Neuroscience 270, no. 2 (March 30, 2019): 169–81. http://dx.doi.org/10.1007/s00406-019-01007-y.
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Hendrix, James A., David C. Airey, Angela Britton, Anna D. Burke, George T. Capone, Ronelyn Chavez, Jacqueline Chen, et al. "Cross-Sectional Exploration of Plasma Biomarkers of Alzheimer’s Disease in Down Syndrome: Early Data from the Longitudinal Investigation for Enhancing Down Syndrome Research (LIFE-DSR) Study." Journal of Clinical Medicine 10, no. 9 (April 28, 2021): 1907. http://dx.doi.org/10.3390/jcm10091907.
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With improved healthcare, the Down syndrome (DS) population is both growing and aging rapidly. However, with longevity comes a very high risk of Alzheimer’s disease (AD). The LIFE-DSR study (NCT04149197) is a longitudinal natural history study recruiting 270 adults with DS over the age of 25. The study is designed to characterize trajectories of change in DS-associated AD (DS-AD). The current study reports its cross-sectional analysis of the first 90 subjects enrolled. Plasma biomarkers phosphorylated tau protein (p-tau), neurofilament light chain (NfL), amyloid β peptides (Aβ1-40, Aβ1-42), and glial fibrillary acidic protein (GFAP) were undertaken with previously published methods. The clinical data from the baseline visit include demographics as well as the cognitive measures under the Severe Impairment Battery (SIB) and Down Syndrome Mental Status Examination (DS-MSE). Biomarker distributions are described with strong statistical associations observed with participant age. The biomarker data contributes to understanding DS-AD across the spectrum of disease. Collectively, the biomarker data show evidence of DS-AD progression beginning at approximately 40 years of age. Exploring these data across the full LIFE-DSR longitudinal study population will be an important resource in understanding the onset, progression, and clinical profiles of DS-AD pathophysiology.
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Barnard, Alison M., Rebecca J. Willcocks, William T. Triplett, Sean C. Forbes, Michael J. Daniels, Saptarshi Chakraborty, Donovan J. Lott, et al. "MR biomarkers predict clinical function in Duchenne muscular dystrophy." Neurology 94, no. 9 (February 5, 2020): e897-e909. http://dx.doi.org/10.1212/wnl.0000000000009012.
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ObjectiveTo investigate the potential of lower extremity magnetic resonance (MR) biomarkers to serve as endpoints in clinical trials of therapeutics for Duchenne muscular dystrophy (DMD) by characterizing the longitudinal progression of MR biomarkers over 48 months and assessing their relationship to changes in ambulatory clinical function.MethodsOne hundred sixty participants with DMD were enrolled in this longitudinal, natural history study and underwent MR data acquisition of the lower extremity muscles to determine muscle fat fraction (FF) and MRI T2 biomarkers of disease progression. In addition, 4 tests of ambulatory function were performed. Participants returned for follow-up data collection at 12, 24, 36, and 48 months.ResultsLongitudinal analysis of the MR biomarkers revealed that vastus lateralis FF, vastus lateralis MRI T2, and biceps femoris long head MRI T2 biomarkers were the fastest progressing biomarkers over time in this primarily ambulatory cohort. Biomarker values tended to demonstrate a nonlinear, sigmoidal trajectory over time. The lower extremity biomarkers predicted functional performance 12 and 24 months later, and the magnitude of change in an MR biomarker over time was related to the magnitude of change in function. Vastus lateralis FF, soleus FF, vastus lateralis MRI T2, and biceps femoris long head MRI T2 were the strongest predictors of future loss of function, including loss of ambulation.ConclusionsThis study supports the strong relationship between lower extremity MR biomarkers and measures of clinical function, as well as the ability of MR biomarkers, particularly those from proximal muscles, to predict future ambulatory function and important clinical milestones.ClinicalTrials.gov identifierNCT01484678.
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Longobardi, Lara, Hope Davis-Wilson, Brian Pietrosimone, R. Alexander Creighton, Joanne Jordan, Richard Loeser, Ganesh Kamath, and Jeffrey Spang. "Longitudinal Analysis of Serum Biochemical Changes following Anterior Cruciate Ligament Injury and Reconstruction: A Matched Comparison-Control Analysis." Orthopaedic Journal of Sports Medicine 8, no. 7_suppl6 (July 1, 2020): 2325967120S0035. http://dx.doi.org/10.1177/2325967120s00354.
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Objectives: Individuals with an anterior cruciate ligament (ACL) injury are at high risk of developing posttraumatic osteoarthritis (PTOA). A comprehensive study is needed to determine the time course of joint tissue metabolic changes occurring following ACL injury and reconstruction (ACLR). The purpose of this longitudinal nested comparison-control study was to simultaneously evaluate serum biomarkers of inflammation and cartilage matrix damage in ACL injured patients prior to ACLR and 6 and 12 months post-ACLR, as well as in matched uninjured controls. Methods: Serum was collected from 34 ACL injured individuals (53% female, 20.7±2.4 years old, 24.2±4.1 body mass index [BMI]) within 14 days of primary ACL injury (baseline), as well as at 6 and 12 months following bone-patellar-tendon-bone autograft ACLR. Serum was also collected from 34 uninjured matched controls (53% Female, 20.5±2.4 years old, 24.1±3.5 BMI) at a single timepoint. Blood was collected from the antecubital fossa, centrifuged and stored at -80°C prior to batch analysis. Commercial enzyme-linked immunosorbent assays were used to evaluate concentrations of: 1) a pro-inflammatory cytokine [Monocyte Chemoattractant Protein; MCP-1]; 2) a matrix degrading enzyme [matrix metalloproteinase-3; MMP-3]; 3) a cartilage breakdown biomarker [cartilage oligomeric matrix protein; COMP]; and type-II collagen turnover [type-II collagen cleavage: synthesis; C2C:CPII]. Separate Bonferroni-corrected independent t-tests were used to determine differences between the ACL injured group at each timepoint and uninjured controls for each biomarker (P ≤ 0.015). Similarly, separate Bonferroni-corrected dependent t-tests were used to determine differences in biomarker concentrations over time for the ACLR group. Results: Serum concentrations of MCP-1 and COMP were greater in the ACL injured individuals at all timepoints compared to the controls (P ≤ 0.015, Table 1), yet no differences were found over time in the ACL injured group. MMP-3 concentrations increased between baseline and 6 months post-ACLR (P ≤ 0.015, see Table), yet no differences were found between 6 and 12 months post-ACLR, between baseline and 12 months, or between ACLR and controls at any of the time points. C2C:CPII was not different between ACL injured individuals and controls at baseline or 6 months post-ACLR. C2C:CPII was significantly increased between 6 and 12 months-post ACLR, and was found to be greater than baseline and greater than controls at 12 months post-ACLR (P ≤ 0.015, see Table). Conclusion: Our study is critical in demonstrating the time course of multiple joint tissue metabolic changes following ACL injury and ACLR. Elevated serum MCP-1 and COMP concentrations, linked to early deleterious metabolic processes associated with PTOA development, are evident soon after ACL injury and persist at 12 months post-ACLR. Serum MMP-3 concentrations were elevated 6 months post-ACLR compared to the baseline measurements, suggesting factors occurring after ACLR initiate upregulation of matrix degrading enzymes. Furthermore, elevated C2C:CPII occurs within the first 12 months post ACLR but not until after the 6-month post-ACLR timepoint. Further studies are needed to determine how long these joint tissue metabolic changes persist after ACL injury and ACLR, as well as how joint tissue metabolism is affected by the type and timing of different surgical and nonsurgical treatments.
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Riddell, Dominique O., John C. W. Hildyard, Rachel C. M. Harron, Dominic J. Wells, and Richard J. Piercy. "Longitudinal assessment of blood-borne musculoskeletal disease biomarkers in the DE50-MD dog model of Duchenne muscular dystrophy." Wellcome Open Research 6 (August 17, 2022): 354. http://dx.doi.org/10.12688/wellcomeopenres.17398.2.
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Background: Duchenne muscular dystrophy (DMD) is a fatal muscle wasting disease caused by mutations in the dystrophin gene. Due to their phenotypic similarity to human patients, large animal models are invaluable tools for pre-clinical trials. The DE50-MD dog is a relatively new model of DMD, and carries a therapeutically-tractable mutation lying within the hotspot for human patients, making it especially valuable. Prior to conducting therapeutic trials using this novel animal model, it is essential to establish a panel of viable biomarkers. Methods: We evaluated a panel of blood-borne biomarkers of musculoskeletal disease in the DE50-MD dog. Venous blood samples were obtained monthly throughout an 18-month study period in DE50-MD (N=18) and wild-type (WT) control (N=14) dogs. A panel of potential plasma/serum biomarkers of DMD was measured and their theoretical utility in future clinical trials determined using sample size calculations. Results: Compared to WT dogs, DE50-MD dogs had substantially higher circulating creatine kinase (CK) activities, myomesin-3 (MYOM3), and the dystromiRs miR-1, miR-133a and miR-206, but significantly lower serum myostatin concentrations. An age-associated pattern, similar to that observed in DMD patients, was seen for CK and MYOM3. Sample size calculations suggested that low cohort sizes (N≤3) could be used to detect up to a 50% improvement in DE50-MD results towards WT levels for each biomarker or a combination thereof (via principal component analysis); as few as N=3 animals should enable detection of a 25% improvement using a combined biomarker approach (alpha 0.05, power 0.8). Conclusions: We have established a panel of blood-borne biomarkers that could be used to monitor musculoskeletal disease or response to a therapeutic intervention in the DE50-MD dog using low numbers of animals. The blood biomarker profile closely mimics that of DMD patients, supporting the hypothesis that this DMD model would be suitable for use in pre-clinical trials.
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Riddell, Dominique O., John C. W. Hildyard, Rachel C. M. Harron, Dominic J. Wells, and Richard J. Piercy. "Longitudinal assessment of blood-borne musculoskeletal disease biomarkers in the DE50-MD dog model of Duchenne muscular dystrophy." Wellcome Open Research 6 (December 20, 2021): 354. http://dx.doi.org/10.12688/wellcomeopenres.17398.1.
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Background: Duchenne muscular dystrophy (DMD) is a fatal muscle wasting disease caused by mutations in the dystrophin gene. Due to their phenotypic similarity to human patients, large animal models are invaluable tools for pre-clinical trials. The DE50-MD dog is a relatively new model of DMD, and carries a therapeutically-tractable mutation lying within the hotspot for human patients, making it especially valuable. Prior to conducting therapeutic trials using this novel animal model, it is essential to establish a panel of viable biomarkers. Methods: We evaluated a panel of blood-borne biomarkers of musculoskeletal disease in the DE50-MD dog. Venous blood samples were obtained monthly throughout an 18-month study period in DE50-MD (N=18) and wild-type (WT) control (N=14) dogs. A panel of potential plasma/serum biomarkers of DMD was measured and their theoretical utility in future clinical trials determined using sample size calculations. Results: Compared to WT dogs, DE50-MD dogs had substantially higher circulating creatine kinase (CK) activities, myomesin-3 (MYOM3), and the dystromiRs miR-1, miR-133a and miR-206, but significantly lower serum myostatin concentrations. An age-associated pattern, similar to that observed in DMD patients, was seen for CK and MYOM3. Sample size calculations suggested that low cohort sizes (N≤3) could be used to detect up to a 50% improvement in DE50-MD results towards WT levels for each biomarker or a combination thereof (via principal component analysis); as few as N=3 animals should enable detection of a 25% improvement using a combined biomarker approach (alpha 0.05, power 0.8). Conclusions: We have established a panel of blood-borne biomarkers that could be used to monitor musculoskeletal disease or response to a therapeutic intervention in the DE50-MD dog using low numbers of animals. The blood biomarker profile closely mimics that of DMD patients, supporting the hypothesis that this DMD model would be suitable for use in pre-clinical trials.
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Buscher, Konrad, Barbara Heitplatz, Veerle van Marck, Jian Song, Sophie Loismann, Rebecca Rixen, Birte Hüchtmann, et al. "Data-Driven Kidney Transplant Phenotyping as a Histology-Independent Framework for Biomarker Discovery." Journal of the American Society of Nephrology 32, no. 8 (June 2, 2021): 1933–45. http://dx.doi.org/10.1681/asn.2020121685.
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BackgroundIn transplant medicine, clinical decision making largely relies on histology of biopsy specimens. However, histology suffers from low specificity, sensitivity, and reproducibility, leading to suboptimal stratification of patients. We developed a histology-independent immune framework of kidney graft homeostasis and rejection.MethodsWe applied tailored RNA deconvolution for leukocyte enumeration and coregulated gene network analysis to published bulk human kidney transplant RNA transcriptomes as input for unsupervised, high-dimensional phenotype clustering. We used framework-based graft survival analysis to identify a biomarker that was subsequently characterized in independent transplant biopsy specimens.ResultsWe found seven immune phenotypes that confirm known rejection types and uncovered novel signatures. The molecular phenotypes allow for improved graft survival analysis compared with histology, and identify a high-risk group in nonrejecting transplants. Two fibrosis-related phenotypes with distinct immune features emerged with reduced graft survival. We identified lysyl oxidase-like 2 (LOXL2)–expressing peritubular CD68+ macrophages as a framework-derived biomarker of impaired allograft function. These cells precede graft fibrosis, as demonstrated in longitudinal biopsy specimens, and may be clinically useful as a biomarker for early fibrogenesis.ConclusionsThis study provides a comprehensive, data-driven atlas of human kidney transplant phenotypes and demonstrates its utility to identify novel clinical biomarkers.
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Cho, Hyung Joon, Philip Schulz, Lalitha Venkataraman, Richard J. Caselli, and Michael R. Sierks. "Sex-Specific Multiparameter Blood Test for the Early Diagnosis of Alzheimer’s Disease." International Journal of Molecular Sciences 23, no. 24 (December 10, 2022): 15670. http://dx.doi.org/10.3390/ijms232415670.
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Blood-based biomarkers are needed for the early diagnosis of Alzheimer’s disease (AD). We analyzed longitudinal human plasma samples from AD and control cases to identify biomarkers for the early diagnosis of AD. Plasma samples were grouped based on clinical diagnosis at the time of collection: AD, mild cognitive impairment (MCI), and pre-symptomatic (preMCI). Samples were analyzed by ELISA using a panel of reagents against nine different AD-related amyloid-β (Aβ), tau, or TDP-43 variants. Receiver operating characteristic (ROC) curves of different biomarker panels for different diagnostic sample groups were determined. Analysis of all of the samples gave a sensitivity of 92% and specificity of 76% for the diagnosis of AD. Early-stage diagnosis of AD, utilizing only the preMCI and MCI samples, identified 88% of AD cases. Using sex-biased biomarker panels, early diagnosis of AD cases improved to 96%. Using the sex-biased panels, we also identified 6 of the 25 control group cases as being at high risk of AD, which is consistent with what is expected given the advanced age of the control cases. Specific AD-associated protein variants are effective blood-based biomarkers for the early diagnosis of AD. Notably, significant differences were observed in biomarker profiles for the early detection of male and female AD cases.
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Li, Menghan, and Lan Kong. "Joint analysis of left-censored longitudinal biomarker and binary outcome via latent class modeling." Statistics in Medicine 37, no. 13 (April 2, 2018): 2162–73. http://dx.doi.org/10.1002/sim.7642.
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Narayanan, Ram P., Bo Fu, Adrian H. Heald, Kirk W. Siddals, Robert L. Oliver, Julie E. Hudson, Antony Payton, et al. "IGFBP2 is a biomarker for predicting longitudinal deterioration in renal function in type 2 diabetes." Endocrine Connections 1, no. 2 (November 2012): 95–102. http://dx.doi.org/10.1530/ec-12-0053.
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ObjectiveInsulin-like growth factors are implicated in the development of diabetic nephropathy. IGF-binding protein 2 (IGFBP2) and IGF2 are expressed in the kidney, but their associations with diabetic nephropathy are unclear. We therefore tested the hypothesis that circulating levels of IGF2 and IGFBP2 predict longitudinal renal function in individuals with type 2 diabetes.Design and methodsIGFBP2 and IGF2 measurements were performed in 436 individuals (263 males) with type 2 diabetes. Linear mixed-effect regression analysis was used to model the relationship between plasma IGFBP2 concentration and longitudinal changes in estimated glomerular filtration rate (eGFR) over an 8-year period. Analyses were also performed for IGF1, IGF2, IGFBP1 and IGFBP3 concentrations as predictors of longitudinal renal outcomes.ResultsHigh IGFBP2 concentration at baseline was associated with a decreased eGFR over an 8-year period (β=−0.02, (95% confidence interval −0.03 to −0.01), P<0.001). High IGFBP1, IGFBP2 and IGFBP3 were also associated with low baseline eGFR concentration.ConclusionThis study demonstrates that IGFBP2 is a predictor of longitudinal deterioration of renal function in type 2 diabetes.
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Chapman, Laura, Stephanie Shepheard, Nick Verber, Martin Turner, Andrea Malaspina, Mary-Louise Rogers, and Pamela Shaw. "171 Urinary P75: a novel biomarker for motor neuron disease?" Journal of Neurology, Neurosurgery & Psychiatry 93, no. 9 (August 12, 2022): e2.130. http://dx.doi.org/10.1136/jnnp-2022-abn2.215.
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Motor neuron disease (MND is a progressive and fatal disease. The urinary neurotrophin receptor p75 extracellular domain (p75ECD) has previously been reported as a potential disease biomarker.This study measured urinary p75ECD using an enzyme-linked immunoassay and normalised the results against urinary creatinine. Participants were recruited via the Multicentre Biomarker Resource Strategy in ALS (AMBroSIA) programme. Study participants included 97 MND patients, 24 of whom were studied longitudinally, and 27 healthy controls. The longitudinal changes in disease severity and survival in com- parison to urinary p75ECD were examined using mixed-model analysis on SPSS.Confirming previous findings, urinary p75ECD levels were significantly higher in patients with MND (median 6.78ng/mg) compared to controls (4.57ng/mg) at first study visit (p=0.013). There was a significant negative correlation between ALSFRS-R rating and p75ECD levels (p=<0.001), indicating that an increase in the severity of motor neuron injury correlated with an increase in p75ECD levels. There was a significant increase in p75ECD between first and second samples in the same participants, indicating an increase in the level of this biomarker longitudinally during the disease course (p=0.011).Urinary p75ECD is a strong candidate as a biomarker which increases with disease progression, and which has potential as a pharmacodynamic biomarker.
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Ponzetto, Federico, Julien Boccard, Raul Nicoli, Tiia Kuuranne, Martial Saugy, and Serge Rudaz. "Steroidomics for highlighting novel serum biomarkers of testosterone doping." Bioanalysis 11, no. 12 (June 2019): 1169–85. http://dx.doi.org/10.4155/bio-2019-0079.
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Aim: Quantification of testosterone (T) and 5α-dihydrotestosterone serum concentrations proved to be an efficient alternative to urinary steroid profiling for the detection of T doping. In this context, additional serum markers could be discovered by exploratory untargeted steroidomics studies. Results: Endogenous steroid metabolites were monitored by ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry in serum samples collected during a T administration clinical trial. A three-step workflow for accurate review of annotation was used and multifactorial data analysis allowed highlighting promising serum biomarkers. Longitudinal monitoring of selected compounds was performed to assess T abuse detection capabilities. Conclusion: Application of serum steroidomics showed high potential for biomarker discovery of T doping, suggesting longitudinal monitoring of steroid hormones in serum as a significant improvement in detection of endogenous steroids abuse.
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Hamedani, Ali G., Lauren A. Hauser, Susan Perlman, Katherine Mathews, George R. Wilmot, Theresa Zesiewicz, S. H. Subramony, et al. "Longitudinal analysis of contrast acuity in Friedreich ataxia." Neurology Genetics 4, no. 4 (July 23, 2018): e250. http://dx.doi.org/10.1212/nxg.0000000000000250.
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ObjectiveTo determine the natural history of contrast acuity in Friedreich ataxia.MethodsIn the Friedreich Ataxia–Clinical Outcome Measures Study, participants (n = 764) underwent binocular high- and low-contrast visual acuity testing at annual study visits. Mixed-effects linear regression was used to model visual acuity as a function of time, with random intercepts and slopes to account for intraindividual correlation of repeated measurements. A time-varying covariate was used to adjust for diabetes, and interaction terms were used to assess for effect modification by GAA repeat length, disease duration, and other variables.ResultsAcross a median of 4.4 years of follow-up, visual acuity decreased significantly at 100% contrast (−0.37 letters/y, 95% confidence interval [CI]: −0.52 to −0.21), 2.5% contrast (−0.81 letters/year, 95% CI: −0.99 to −0.65), and 1.25% contrast (−1.12 letters/y, 95% CI: −1.29 to −0.96 letters/year). There was a significant interaction between time and GAA repeat length such that the rate of decrease in visual acuity was greater for patients with higher GAA repeat lengths at 2.5% contrast (p = 0.018) and 1.25% contrast (p = 0.043) but not 100% contrast. There was no effect modification by age at onset after adjusting for GAA repeat length.ConclusionsLow-contrast visual acuity decreases linearly over time in Friedreich ataxia, and the rate of decrease is greater at higher GAA repeat lengths. Contrast sensitivity has the potential to serve as a biomarker and surrogate outcome in future studies of Friedreich ataxia.
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Hijikata, Yasuhiro, Atsushi Hashizume, Shinichiro Yamada, Tomonori Inagaki, Daisuke Ito, Akihiro Hirakawa, Keisuke Suzuki, et al. "Biomarker-based analysis of preclinical progression in spinal and bulbar muscular atrophy." Neurology 90, no. 17 (March 23, 2018): e1501-e1509. http://dx.doi.org/10.1212/wnl.0000000000005360.
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ObjectiveTo identify a candidate biomarker reflecting biological changes during the preclinical progression of spinal and bulbar muscular atrophy (SBMA).MethodsWe analyzed longitudinal changes in biochemical parameters obtained during health examinations before and after the diagnosis of SBMA. We estimated trajectories of clinical markers across years from the onset of weakness using linear mixed models and compared these trajectories with those estimated for male healthy controls and patients with amyotrophic lateral sclerosis (ALS) and Parkinson disease (PD). Moreover, we examined the relationship between serum creatinine level and the onset of symptoms using Kaplan-Meier curves.ResultsBetween October 2014 and October 2017, we enrolled 40 patients with genetically confirmed SBMA, 48 healthy controls, 25 patients with ALS, and 20 patients with PD. In patients with SBMA, we evaluated the patients' data for a period of 17.3 ± 7.5 years, including 11.4 ± 7.1 years of preclinical phase. Decreases in serum creatinine occurred >10 years before the onset. The mean serum creatinine concentration was 0.56 mg/dL at the onset of weakness in patients with SBMA compared to 0.88 ± 0.10 mg/dL on final evaluation in healthy controls. Serum levels of alanine transaminase and aspartate transaminase showed tendencies to increase in preclinical SBMA. These preclinical changes of biomarkers were not observed in either ALS or PD.ConclusionsOur findings suggest that serum creatinine begins to decrease before the onset of clinical symptoms and is a biomarker for disease progression and the efficacy of therapeutics in preclinical SBMA.
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Dreger, Marie, Robert Steinbach, Markus Otto, Martin R. Turner, and Julian Grosskreutz. "Cerebrospinal fluid biomarkers of disease activity and progression in amyotrophic lateral sclerosis." Journal of Neurology, Neurosurgery & Psychiatry 93, no. 4 (February 1, 2022): 422–35. http://dx.doi.org/10.1136/jnnp-2021-327503.
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Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive neurodegenerative disease, and only modest disease-modifying strategies have been established to date. Numerous clinical trials have been conducted in the past years, but have been severely hampered by the wide-ranging heterogeneity of both the biological origins and clinical characteristics of the disease. Thus, reliable biomarkers of disease activity are urgently needed to stratify patients into homogenous groups with aligned disease trajectories to allow a more effective design of clinical trial. In this review, the most promising candidate biomarkers in the cerebrospinal fluid (CSF) of patients with ALS will be summarised. Correlations between biomarker levels and clinical outcome parameters are discussed, while highlighting potential pitfalls and intercorrelations of these clinical parameters. Several CSF molecules have shown potential as biomarkers of progression and prognosis, but large, international, multicentric and longitudinal studies are crucial for validation. A more standardised choice of clinical endpoints in these studies, as well as the application of individualised models of clinical progression, would allow the quantification of disease trajectories, thereby allowing a more accurate analysis of the clinical implications of candidate biomarkers. Additionally, a comparative analysis of several biomarkers and ideally the application of a multivariate analysis including comprehensive genotypic, phenotypic and clinical characteristics collectively contributing to biomarker levels in the CSF, could promote their verification. Thus, reliable prognostic markers and markers of disease activity may improve clinical trial design and patient management in the direction of precision medicine.
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Volz, Kevin R., Kevin D. Evans, Christopher D. Kanner, John A. Buford, Miriam Freimer, Carolyn M. Sommerich, and D. Michele Basso. "Molecular Ultrasound Imaging for the Detection of Neural Inflammation: A Longitudinal Dosing Pilot Study." Journal of Diagnostic Medical Sonography 33, no. 6 (October 26, 2017): 466–78. http://dx.doi.org/10.1177/8756479317736250.
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Molecular ultrasound imaging provides the ability to detect physiologic processes noninvasively by targeting a variety of biomarkers in vivo. The current study was performed by exploiting an inflammatory biomarker, P-selectin, known to be present following spinal cord injury. Using a murine model (n = 6), molecular ultrasound imaging was performed using contrast microbubbles modified to target and adhere to P-selectin, prior to spinal cord injury (0D), acute stage postinjury (7D), and chronic stage (42D). Additionally, two imaging sessions were performed on each subject at specific time points, using doses of 30 μL and 100 μL. Upon analysis, targeted contrast analysis parameters were appreciably increased during the 7D scan compared with the 42D scan, without statistical significance. When examining the dose levels, the 30-μL dose demonstrated greater values than the 100-μL dose but lacked statistical significance. These findings provide additional preclinical evidence for the use of molecular ultrasound imaging for the possible detection of inflammation.
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Oye, Monique, Aaron Richardson, Edin Sadic, Ahmad Alkhasawneh, and Gladys Velarde. "Cardiac Amyloidosis Presenting as Biventricular Systolic Heart Failure." Case Reports in Cardiology 2021 (April 1, 2021): 1–6. http://dx.doi.org/10.1155/2021/6671469.
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A previously healthy octogenarian presented with new onset heart failure symptoms. Comprehensive multimodality imaging including complete echocardiography with longitudinal strain analysis, cardiac magnetic resonance imaging (cMRI), nuclear medicine pyrophosphate (99-mcTcPYP) scan along with biomarker, monoclonal protein analysis, and fat pad biopsy confirmed diagnosis of transthyretin cardiac amyloidosis.
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Pricola Fehnel, Katie, Micah Duggins-Warf, David Zurakowski, Maxwell McKee-Proctor, Rajarshi Majumder, Michael Raber, Xuezhe Han, and Edward R. Smith. "Using urinary bFGF and TIMP3 levels to predict the presence of juvenile pilocytic astrocytoma and establish a distinct biomarker signature." Journal of Neurosurgery: Pediatrics 18, no. 4 (October 2016): 396–407. http://dx.doi.org/10.3171/2015.12.peds15448.
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OBJECTIVE The authors report the use of urinary biomarkers as a novel, noninvasive technique to detect juvenile pilocytic astrocytomas (JPAs), capable of distinguishing JPAs from other CNS diseases, including other brain tumors. Preliminary screening of an array of tumors implicated proteases (including matrix metalloproteinases [MMPs]) and their inhibitors (tissue inhibitors of metalloproteinase [TIMPs]) as well as growth factors (including basic fibroblast growth factor [bFGF]) as candidate biomarkers. These data led the authors to hypothesize that tissue inhibitor of metalloproteinase 3 (TIMP3) and bFGF would represent high-probability candidates as JPA-specific biomarkers. METHODS Urine was collected from 107 patients, which included children with JPA (n = 21), medulloblastoma (n = 17), glioblastoma (n = 9), arteriovenous malformations (n = 25), moyamoya (n = 14), and age- and sex-matched controls (n = 21). Biomarker levels were quantified with enzyme-linked immunosorbent assay, tumor tissue expression was confirmed with immunohistochemical analysis, and longitudinal biomarker expression was correlated with imaging. Results were subjected to univariate and multivariate statistical analyses. RESULTS Using optimal urinary cutoff values of bFGF > 1.0 pg/μg and TIMP3 > 3.5 pg/μg, multiplexing bFGF and TIMP3 predicts JPA presence with 98% accuracy. Multiplexing bFGF and MMP13 distinguishes JPA from other brain tumor subtypes with up to 98% accuracy. Urinary biomarker expression correlated with both tumor immunohistochemistry and in vitro tumor levels. Urinary bFGF and TIMP3 decrease following successful tumor treatment and correlate with changes in tumor size. CONCLUSIONS This study identifies 2 urinary biomarkers—bFGF and TIMP3—that successfully detect one of the most common pediatric brain tumors with high accuracy. These data highlight potential benefits of urinary biomarkers and support their utility as diagnostic tools in the treatment of children with JPA.
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Jonsson, Pär, Henrik Antti, Florentin Späth, Beatrice Melin, and Benny Björkblom. "Identification of Pre-Diagnostic Metabolic Patterns for Glioma Using Subset Analysis of Matched Repeated Time Points." Cancers 12, no. 11 (November 12, 2020): 3349. http://dx.doi.org/10.3390/cancers12113349.
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Here, we present a strategy for early molecular marker pattern detection—Subset analysis of Matched Repeated Time points (SMART)—used in a mass-spectrometry-based metabolomics study of repeated blood samples from future glioma patients and their matched controls. The outcome from SMART is a predictive time span when disease-related changes are detectable, defined by time to diagnosis and time between longitudinal sampling, and visualization of molecular marker patterns related to future disease. For glioma, we detect significant changes in metabolite levels as early as eight years before diagnosis, with longitudinal follow up within seven years. Elevated blood plasma levels of myo-inositol, cysteine, N-acetylglucosamine, creatinine, glycine, proline, erythronic-, 4-hydroxyphenylacetic-, uric-, and aceturic acid were particularly evident in glioma cases. We use data simulation to ensure non-random events and a separate data set for biomarker validation. The latent biomarker, consisting of 15 interlinked and significantly altered metabolites, shows a strong correlation to oxidative metabolism, glutathione biosynthesis and monosaccharide metabolism, linked to known early events in tumor development. This study highlights the benefits of progression pattern analysis and provide a tool for the discovery of early markers of disease.
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Winkelman, Daniel F., Amir Forouzan, Mike Lavin, Tanuja Tangudu, Kristopher Custer, and Anise Kachadourian. "Patient’s insurance status impact on biomarker testing in the United States market." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): e18114-e18114. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e18114.
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e18114 Background: Precision medicine in cancer treatment is driven by biomarker testing. If a patient is not biomarker tested, he or she may not receive access to targeted therapies that often offer greater efficacy. The purpose of this research study is to examine the insurance type of patients that are untested for biomarkers in the United States. Methods: BrandImpact is a longitudinal panel of 450 Oncologists who continuously report cancer treatment decisions from the point-of-care. The BrandImpact data set includes 60,465 patient visits reported in 2018. This study followed market research best practices. This research included visits by patients diagnosed with metastatic: NSCLC, melanoma and ovarian cancer who were either tested or untested for the following biomarkers: EGFR, ALK, ROS1, PD-L1, BRAF and BRCA. Results: The baseline measure for this analysis is that 18% of the patient visits reported that were not biomarker tested. The table at the end of document outlines the untested patient visits by insurance type for comparison purposes. Conclusions: The rate of biomarker testing for metastatic cancer patients treated by Oncologists differs by insurance type. Patients with Medicare Only insurance (25%) are untested at a statistically significantly higher rate than the baseline All category. It should be noted that patients without insurance or who were cash-paying had the highest rates of being non-biomarker tested. It is recommended that further research be conducted into the reasons behind the significantly higher rate of non-testing for Medicare Only patients. It seems counter intuitive that this patient population is treated less than optimally due to limited access to targeted therapies. [Table: see text]
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Bowick, Gavin C., Kizhake V. Soman, He Wang, Judith F. Aronson, Bruce A. Luxon, Lee O. Lomas, David G. Gorenstein, and Norbert K. Herzog. "Proteomic Analysis ofPichindé virusInfection Identifies Differential Expression of Prothymosin-α." Journal of Biomedicine and Biotechnology 2010 (2010): 1–9. http://dx.doi.org/10.1155/2010/956823.
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The arenaviruses include a number of important pathogens includingLassa virusandJunin virus. Presently, the only treatment is supportive care and the antiviral Ribavirin. In the event of an epidemic, patient triage may be required to more effectively manage resources; the development of prognostic biomarker signatures, correlating with disease severity, would allow rational triage. Using a pair of arenaviruses, which cause mild or severe disease, we analyzed extracts from infected cells using SELDI mass spectrometry to characterize potential biomarker profiles. EDGE analysis was used to analyze longitudinal expression differences. Extracts from infected guinea pigs revealed protein peaks which could discriminate between mild or severe infection and between times post-infection. Tandem mass-spectrometry identified several peaks, including the transcriptional regulator prothymosin-α. Further investigation revealed differences in secretion of this peptide. These data show proof of concept that proteomic profiling of host markers could be used as prognostic markers of infectious disease.
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Veys, Koenraad R. P., Mohamed A. Elmonem, Maria Van Dyck, Mirian C. Janssen, Elisabeth A. M. Cornelissen, Katharina Hohenfellner, Giusi Prencipe, Lambertus P. van den Heuvel, and Elena Levtchenko. "Chitotriosidase as a Novel Biomarker for Therapeutic Monitoring of Nephropathic Cystinosis." Journal of the American Society of Nephrology 31, no. 5 (April 9, 2020): 1092–106. http://dx.doi.org/10.1681/asn.2019080774.
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BackgroundNephropathic cystinosis, a hereditary lysosomal storage disorder caused by dysfunction of the lysosomal cotransporter cystinosin, leads to cystine accumulation and cellular damage in various organs, particularly in the kidney. Close therapeutic monitoring of cysteamine, the only available disease-modifying treatment, is recommended. White blood cell cystine concentration is the current gold standard for therapeutic monitoring, but the assay is technically demanding and is available only on a limited basis. Because macrophage-mediated inflammation plays an important role in the pathogenesis of cystinosis, biomarkers of macrophage activation could have potential for the therapeutic monitoring of cystinosis.MethodsWe conducted a 2-year prospective, longitudinal study in which 61 patients with cystinosis who were receiving cysteamine therapy were recruited from three European reference centers. Each regular care visit included measuring four biomarkers of macrophage activation: IL-1β, IL-6, IL-18, and chitotriosidase enzyme activity.ResultsA multivariate linear regression analysis of the longitudinal data for 57 analyzable patients found chitotriosidase enzyme activity and IL-6 to be significant independent predictors for white blood cell cystine levels in patients of all ages with cystinosis; a receiver operating characteristic analysis ranked chitotriosidase as superior to IL-6 in distinguishing good from poor therapeutic control (on the basis of white blood cell cystine levels of <2 nmol 1/2 cystine/mg protein or ≥2 nmol 1/2 cystine/mg protein, respectively). Moreover, in patients with at least one extrarenal complication, chitotriosidase significantly correlated with the number of extrarenal complications and was superior to white blood cell cystine levels in predicting the presence of multiple extrarenal complications.ConclusionsChitotriosidase enzyme activity holds promise as a biomarker for use in therapeutic monitoring of nephropathic cystinosis.
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Bjornevik, Kjetil, Marianna Cortese, Brian C. Healy, Jens Kuhle, Michael J. Mina, Yumei Leng, Stephen J. Elledge, et al. "Longitudinal analysis reveals high prevalence of Epstein-Barr virus associated with multiple sclerosis." Science 375, no. 6578 (January 21, 2022): 296–301. http://dx.doi.org/10.1126/science.abj8222.
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Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system of unknown etiology. We tested the hypothesis that MS is caused by Epstein-Barr virus (EBV) in a cohort comprising more than 10 million young adults on active duty in the US military, 955 of whom were diagnosed with MS during their period of service. Risk of MS increased 32-fold after infection with EBV but was not increased after infection with other viruses, including the similarly transmitted cytomegalovirus. Serum levels of neurofilament light chain, a biomarker of neuroaxonal degeneration, increased only after EBV seroconversion. These findings cannot be explained by any known risk factor for MS and suggest EBV as the leading cause of MS.
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Derungs, Adrian, Corina Schuster-Amft, and Oliver Amft. "Wearable motion sensors and digital biomarkers in stroke rehabilitation." Current Directions in Biomedical Engineering 6, no. 3 (September 1, 2020): 229–32. http://dx.doi.org/10.1515/cdbme-2020-3058.
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AbstractWe propose three novel digital biomarkers for the longitudinal performance monitoring and movement evaluation of hemiparetic patients, e.g. after stroke. We devised convergence points (CP) for the bilateral walking analysis based on gait parameters, e.g. stride duration using regression- modelling to estimate similarity between body sides. The physical activity (PA) was devised to evaluate the energy expenditure of all extremities during training and free-living. The functional range of motion (fROM) is a digital biomarker to quantify the upper arm reaching ability, represented in 3D visualisations. In this work, we detail CP, PA, and fROM to derive rehabilitation insights for personalising therapies. We evaluated the proposed digital biomarkers in a clinical observation study with 11 patients after stroke during their rehabilitation including therapy and self-paced daily routines.
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Grund, Eric M., A. James Moser, Corinne L. DeCicco, Nischal M. Chand, Genesis L. Perez-Melara, Gregory M. Miller, Punit Shah, et al. "Abstract 5145: Project Survival®: Discovery of a molecular-clinical phenome biomarker panel to detect pancreatic ductal adenocarcinoma among at risk populations using high-fidelity longitudinal phenotypic and multi-omic analysis." Cancer Research 82, no. 12_Supplement (June 15, 2022): 5145. http://dx.doi.org/10.1158/1538-7445.am2022-5145.
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Abstract Delayed diagnosis and rapid progression are major drivers of poor survival outcomes for pancreatic ductal adenocarcinoma (PDAC). PDAC is expected to be the second leading cause of cancer death and has a dismal 5 year survival rate of 10%. There is an urgent unmet need to detect the disease at an early stage and stratify patients into more effective treatment regimens within clinically meaningful timeframes. To accomplish this, robust quality controlled OMIC molecular profiling platforms and analytic solutions need to be deployed into precision medicine protocols to discover actionable biomarkers. Project Survival® is a multicenter (n=6), prospective biomarker study (NCT 02781012) of PDAC and relevant controls combining high-fidelity longitudinal phenotypic characterization, multi-omic profiling (proteomics, signaling lipidomics, structural lipidomics, and metabolomics), and agnostic Bayesian artificial intelligence network inference (bAIcis®) to discover biomarkers with diagnostic and therapeutic utility. This study utilizes a systems medicine approach for translational biomarker discovery by performing analysis of matched subject sera, plasma, buffy coat, saliva, urine, and tumor/adjacent normal tissues and integrating them with the respective full clinical annotation using the BERG Interrogative Biology® platform. Multiple longitudinal time points were taken over the course of the six-year timeline enabling dynamic modeling. Utilizing the Project Survival® molecular and clinical data, we have analyzed and integrated baseline samples from 121 at risk patients and 279 patients with PDAC. Samples were randomized and analyzed over the course of recruitment allowing for agnostic discovery and integration to determine diagnostic utility. Discovery analysis identified 123 potential molecular markers, of which, four demonstrated a combined AUC of 0.85, PPV 0.83, NPV 0.72, and OR 13.1. In parallel, 4 non-canonical clinical measurements were assessed for diagnostic utility providing an AUC 0.79, PPV 0.84, NPV 0.72 and OR 13.2. Combining molecular and clinical features demonstrated an AUC of 0.9, PPV 0.9, NPV 0.77, OR 29.2, and p-value 1.4 E-40. Molecular markers revealed no treatment associated expression effects. Taken together, these marker panels demonstrate diagnostic utility to detect PDAC and will be further validated using robust bioanalysis methods as well as in an independent cohort of samples to provide enhanced insight into their positioning in the diagnostic landscape for PDAC. Citation Format: Eric M. Grund, A. James Moser, Corinne L. DeCicco, Nischal M. Chand, Genesis L. Perez-Melara, Gregory M. Miller, Punit Shah, Valarie Bussberg, Vladimir Tolstikov, Rangaprasad Sarangarajan, Elder Granger, Niven Narian, Michael A. Kiebish. Project Survival®: Discovery of a molecular-clinical phenome biomarker panel to detect pancreatic ductal adenocarcinoma among at risk populations using high-fidelity longitudinal phenotypic and multi-omic analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5145.
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Whiteside, Ellen. "A Longitudinal Study to Evaluate Biomarkers in Brain Tumour Patients." Neuro-Oncology 24, Supplement_4 (October 1, 2022): iv20. http://dx.doi.org/10.1093/neuonc/noac200.090.
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Abstract AIMS To monitor brain tumour patient blood for predictive and prognostic biomarkers, in a prospective longitudinal study. Continuing the research of Dr. Abel the results may be used to predict tumour recurrence and progression from low- to high-grade. The results may be useful in the clinical management of malignant glioma patients. METHOD A patented panel of biomarkers will be investigated using FFPE tissue and blood components from adult brain tumour patients in the North West region. Biomarker expression will be analysed in different molecular sub-types of glioma, grouped by IDH and methylation status. An evaluation will be conducted to determine if reference ranges can be created to distinguish between high-and low-grade tumours. Spectroscopic analysis of blood samples will be tested to determine if cancerous and non-cancerous can be differentiated from each other. There will be testing of selected miRNA’s for up and down regulation patterns. Sample Intervals: Initial diagnosis, 24 hours post-surgery, pre-therapy, post-radiotherapy, after adjuvant therapy, at 3 then 6 monthly post therapy, at recurrence or suspected recurrence and at intervals during further therapy and follow up. RESULTS There are no results to report at this point in the study time line. Testing to start in April 2022. CONCLUSION The potential impact of research would work towards lower patient risk and less invasive procedures. If used as a screening tool could allow high NHS savings. There could be an impact on patient experience and survival if recurrence could be detected [NICE guideline NG99] recommendation for research.
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Higgins-Chen, Albert, Kyra Thrush, Tina Hu-Seliger, Yunzhang Wang, Sara Hagg, and Morgan Levine. "A Computational Solution to Bolster Epigenetic Clock Reliability for Clinical Trials and Longitudinal Tracking." Innovation in Aging 5, Supplement_1 (December 1, 2021): 5. http://dx.doi.org/10.1093/geroni/igab046.015.
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Abstract Epigenetic clocks are widely used aging biomarkers, but they are calculated from methylation data for individual CpGs that can be surprisingly unreliable. We report that technical noise causes six major epigenetic clocks to deviate by 3 to 9 years between replicates. We present a novel computational solution: we perform principal component analysis followed by biological age prediction using principal components, extracting shared age-related changes across CpGs while ignoring noise from individual CpGs. Our novel principal-component versions of six clocks show agreement between most technical replicates within 1 year, and increased stability in short- and long-term longitudinal studies. This requires only one additional step compared to traditional clocks, does not require prior knowledge of CpG reliabilities, and can improve the reliability of any existing or future epigenetic biomarker. The extremely high reliability of principal component epigenetic clocks makes them particularly useful for personalized medicine and clinical trials evaluating novel aging interventions.
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Mouiha, Abderazzak, and Simon Duchesne. "P2-245: Dynamic biomarker model in Alzheimer's disease: Longitudinal analysis of hippocampal volume shows linear decline." Alzheimer's & Dementia 8, no. 4S_Part_9 (July 2012): P346—P347. http://dx.doi.org/10.1016/j.jalz.2012.05.952.
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Mano, Tomoo, Masahisa Katsuno, Haruhiko Banno, Keisuke Suzuki, Noriaki Suga, Atsushi Hashizume, Fumiaki Tanaka, and Gen Sobue. "Cross-sectional and longitudinal analysis of an oxidative stress biomarker for spinal and bulbar muscular atrophy." Muscle & Nerve 46, no. 5 (August 31, 2012): 692–97. http://dx.doi.org/10.1002/mus.23413.
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Mitsides, Nicos, Tom Cornelis, Natascha J. H. Broers, Nanda M. P. Diederen, Paul Brenchley, Frank M. van der Sande, Casper Schalkwijk, Jeroen P. Kooman, and Sandip Mitra. "Cardiovascular and Patient Phenotype of Extended Haemodialysis: A Critical Analysis of Studying a Unique Patient Population." Blood Purification 45, no. 4 (2018): 356–63. http://dx.doi.org/10.1159/000485231.
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Background: Extended haemodialysis (EHD) has been associated with better outcomes compared to conventional (CHD) regimes. The cardiovascular (CV) profile of these patients has not been assessed in detail. Methods: We report baseline demographic and CV phenotype of 36 CHD and 36 EHD participants to a longitudinal multicentre study. We measured pulse wave velocity (PWV), 24-h ambulatory blood pressure, sublingual dark-field capillaroscopy and vascular biomarkers. Results: EHD patients were younger (p < 0.01), with less CV comorbidity (p = 0.04) and higher dialysis vintage (p < 0.01). Higher PWV in CHD (p = 0.02) was not independent of demographic differences in the 2 groups. Biomarker profiles were similar in EHD and CHD but abnormal compared to healthy controls. Conclusion: Although CV profiles in these 2 cohorts were similar, EHD patients were distinct from the CHD population in terms of age and dialysis vintage and appear to comprise a unique group. Direct comparison of outcomes in these groups is challenging due to clinical bias.
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Costa, Clotilde, Laura Muinelo-Romay, Victor Cebey-López, Thais Pereira-Veiga, Inés Martínez-Pena, Manuel Abreu, Alicia Abalo, et al. "Analysis of a Real-World Cohort of Metastatic Breast Cancer Patients Shows Circulating Tumor Cell Clusters (CTC-clusters) as Predictors of Patient Outcomes." Cancers 12, no. 5 (April 29, 2020): 1111. http://dx.doi.org/10.3390/cancers12051111.
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Circulating tumor cell (CTC) enumeration has emerged as a powerful biomarker for the assessment of prognosis and the response to treatment in metastatic breast cancer (MBC). Moreover, clinical evidences show that CTC-cluster counts add prognostic information to CTC enumeration, however, their significance is not well understood, and more clinical evidences are needed. We aim to evaluate the prognostic value of longitudinally collected single CTCs and CTC-clusters in a heterogeneous real-world cohort of 54 MBC patients. Blood samples were longitudinally collected at baseline and follow up. CTC and CTC-cluster enumeration was performed using the CellSearch® system. Associations with progression-free survival (PFS) and overall survival (OS) were evaluated using Cox proportional hazards modelling. Elevated CTC counts and CTC-clusters at baseline were significantly associated with a shorter survival time. In joint analysis, patients with high CTC counts and CTC-cluster at baseline were at a higher risk of progression and death, and longitudinal analysis showed that patients with CTC-clusters had significantly shorter survival compared to patients without clusters. Moreover, patients with CTC-cluster of a larger size were at a higher risk of death. A longitudinal analysis of a real-world cohort of MBC patients indicates that CTC-clusters analysis provides additional prognostic value to single CTC enumeration, and that CTC-cluster size correlates with patient outcome.
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Evans, Joanne, Caroline Ward, Madhava Pai, and Rohini Sharma. "Longitudinal monitoring of cell-free DNA to predict for transarterial chemo-embolization failure in hepatocellular carcinoma." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): e14544-e14544. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e14544.
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e14544 Background: Transarterial chemo-embolization (TACE) is the standard of care for patients with intermediate stage hepatocellular carcinoma (HCC) with adequate synthetic function, and as bridging treatment in early stage disease. Survival outcomes are heterogeneous, and improved biomarkers are needed for detection of early relapse. Current practice relies on monitoring of alpha-foetoprotein (AFP) and serial imaging. Circulating cell-free DNA (cfDNA) is a compelling emergent biomarker. Here, we describe the first study of cfDNA as prognostic biomarker in HCC following TACE. Methods: 34 patients treated with TACE (2012-2018) who had full demographic information and longitudinal stored plasma available were identified. Samples were retrieved and cfDNA extracted using the QIAamp Circulating Nucleic Acid Kit. cfDNA yields were quantified by high-sensitivity Qubit analysis. Results: 74% of patients were male, 66% had Childs Pugh A disease, and 56% of patients secreted AFP ( > 10ng/mL). Aetiologies of liver diseases were varied: viral hepatitis (44%), alcoholic or non-alcoholic steatohepatitis/cirrhosis (29%), hereditary or auto-immune (12%), and unexplained (15%). 79% of patients saw a fall in cfDNA titre following TACE. Where no reduction was seen, patients had a poorer median overall survival than those who did: 20 months (range 5.13 – 66.7 months) compared to 37 months (9.9 – 79.3 months). Of note, 44% of patients were AFP non-secretors. Here, cfDNA had a clear advantage in disease monitoring, with mean cfDNA titres in this group falling post treatment: from 1605.1 (range 185.9 – 6830) ng/mL to 693.7 (range undetectable - 2300) ng/mL and rising again with subsequent progression (mean of 1329.2 - range 616 – 3341 - ng/mL). Conclusions: These findings support a cost-effective monitoring role for plasma cfDNA analysis following treatment with TACE, with an added advantage in AFP non-secretors. Prospective validation is suggested to fully assess clinical utility.
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Salagre, E., A. F. Vizuete, M. Leite, D. J. Brownstein, A. McGuinness, F. Jacka, S. Dodd, et al. "Homocysteine as a peripheral biomarker in bipolar disorder: A meta-analysis." European Psychiatry 43 (June 2017): 81–91. http://dx.doi.org/10.1016/j.eurpsy.2017.02.482.
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AbstractBackground:Bipolar disorder (BD) is a psychiatric disorder with an uncertain aetiology. Recently, special attention has been given to homocysteine (Hcy), as it has been suggested that alterations in 1-carbon metabolism might be implicated in diverse psychiatric disorders. However, there is uncertainty regarding possible alterations in peripheral Hcy levels in BD.Methods:This study comprises a meta-analysis comparing serum and plasma Hcy levels in persons with BD and healthy controls. We conducted a systematic search for all eligible English and non-English peer-reviewed articles.Results:Nine cross-sectional studies were included in the meta-analyses, providing data on 1547 participants. Random-effects meta-analysis showed that serum and plasma levels of Hcy were increased in subjects with BD in either mania or euthymia when compared to healthy controls, with a large effect size in the mania group (g= 0.98, 95% CI: 0.8–1.17,P< 0.001,n= 495) and a small effect in the euthymia group (g= 0.3, 95% CI: 0.11–0.48,P= 0.002,n= 1052).Conclusions:Our meta-analysis provides evidence that Hcy levels are elevated in persons with BD during mania and euthymia. Peripheral Hcy could be considered as a potential biomarker in BD, both of trait (since it is increased in euthymia), and also of state (since its increase is more accentuated in mania). Longitudinal studies are needed to clarify the relationship between bipolar disorder and Hcy, as well as the usefulness of peripheral Hcy as both a trait and state biomarker in BD.
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Borgmästars, Emmy, Erik Lundberg, Daniel Öhlund, Hanna Nyström, Oskar Franklin, Christina Lundin, Pär Jonsson, and Malin Sund. "Circulating Tissue Polypeptide-Specific Antigen in Pre-Diagnostic Pancreatic Cancer Samples." Cancers 13, no. 21 (October 23, 2021): 5321. http://dx.doi.org/10.3390/cancers13215321.
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Early detection of pancreatic ductal adenocarcinoma (PDAC) is challenging, and late diagnosis partly explains the low 5-year survival. Novel and sensitive biomarkers are needed to enable early PDAC detection and improve patient outcomes. Tissue polypeptide specific antigen (TPS) has been studied as a biomarker in PDAC diagnostics, and it has previously been shown to reflect clinical status better than the ‘golden standard’ biomarker carbohydrate antigen 19-9 (CA 19-9) that is most widely used in the clinical setting. In this cross-sectional case-control study using pre-diagnostic plasma samples, we aim to evaluate the potential of TPS as a biomarker for early PDAC detection. Furthermore, in a subset of individuals with multiple samples available at different time points before diagnosis, a longitudinal analysis was used. We assessed plasma TPS levels using enzyme-linked immunosorbent assay (ELISA) in 267 pre-diagnostic PDAC plasma samples taken up to 18.8 years before clinical PDAC diagnosis and in 320 matched healthy controls. TPS levels were also assessed in 25 samples at PDAC diagnosis. Circulating TPS levels were low both in pre-diagnostic samples of future PDAC patients and in healthy controls, whereas TPS levels at PDAC diagnosis were significantly increased (odds ratio 1.03; 95% confidence interval: 1.01–1.05) in a logistic regression model adjusted for age. In conclusion, TPS levels increase late in PDAC progression and hold no potential as a biomarker for early detection.
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Long, Xiaojing, Chunxiang Jiang, and Lijuan Zhang. "Morphological Biomarker Differentiating MCI Converters from Nonconverters: Longitudinal Evidence Based on Hemispheric Asymmetry." Behavioural Neurology 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/3954101.
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Identifying subjects with mild cognitive impairment (MCI) who may probably progress to Alzheimer’s disease (AD) is important for better understanding the disease mechanisms and facilitating early treatments. In addition to the direct volumetric and thickness measurement based on high-resolution magnetic resonance imaging (MRI), hemispheric asymmetry could be a potential index to detect morphological variations in MCI patients with a high risk of conversion to AD. The present study collected a set of longitudinal MRI data from 53 MCI converters and nonconverters and investigated the asymmetry differences between groups. Asymmetry variation was observed in the medial temporal lobe, especially in the entorhinal cortex, between converters and nonconverters 3 years before the former developed AD. The proposed asymmetry analysis was observed to be sensitive to detect morphological changes between groups as compared to the methods of voxel-based morphometry (VBM) and thickness measurement. Hemispheric asymmetry in specific brain regions as a neuroimaging biomarker can provide helpful information for prediction of MCI conversion.
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Riviere-Cazaux, Cecile, and Terry Burns. "Glioma Espionage From Longitudinal CSF Proteomics." Neuro-Oncology 24, Supplement_4 (October 1, 2022): iv11—iv12. http://dx.doi.org/10.1093/neuonc/noac200.052.
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Abstract AIMS Rapid, detailed feedback is needed to understand the individualized biological impacts of novel glioma therapies. We are performing glioma biomarker discovery by serial cerebrospinal fluid (CSF) sampling from Ommaya reservoirs to determine how the CSF proteome can reveal early longitudinal intelligence regarding glioma status, biology, and therapeutic response. METHOD Global proteomic analysis of CSF was performed on the Somalogic platform – an aptamer-based technology for highly sensitive and specific analysis of over 7,000 proteins. Discovery analysis comprised of the top-500 ranked proteins in CSF from seven patients with high-grade gliomas (HGG) versus non-glioma controls. The top-500 HGG proteins were then preliminarily filtered to include only proteins that met two additional criteria of decrease with resection and increase with recurrence in individual paired patient samples. RESULTS Proteomic enrichment analysis revealed a conserved HGG CSF proteomic signature defined by 79 proteins, including ones known to be over-expressed in solid tumor malignancies, such as retinoblastoma binding protein 4, heat shock protein 90, and sorcin. The HGG proteomic signature was consistently enriched in an independent validation cohort consisting of 13 gliomas diverse in primary versus recurrent status, subtype, and grade, when compared to control CSF samples. Encouragingly, proteins in the HGG signature decreased in the two patients for whom CSF was collected prior to and after resection (both at POD16 and POD18) with decreased tumor burden. CONCLUSION Our data demonstrate the ability to gain detailed, individualized insights regarding glioma biology, tumor burden, and evolution through global CSF proteomics acquired from longitudinal access to gliomas via Ommaya reservoirs.
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You, Benoit, Eric Assenat, Olivier Glehen, Delphine Maucort-Boulch, Lea Francoise Payen, Vahan Kepenekian, Marie Dupuy, et al. "Progastrin, a novel ubiquitous cancer blood biomarker for early detection and monitoring." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): 3037. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.3037.
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3037 Background: The successes of recent publications on “multi-tumor” circulating markers highlight the relevance of novel universal diagnostic cancer serum biomarkers. Since the Wnt/ß-catenin/Tcf4 pathway, activated in many tumors, induces the GAST Gene encoding progastrin synthesis, we hypothesized that progastrin, easily measurable in the blood, might be a “multi-tumor” diagnostic biomarker. Methods: Progastrin levels were measured in the blood samples of 1319 patients with 12 different cancer origins, and compared to those of 557 asymptomatic 18-75 years old blood donors. Moreover the longitudinal kinetics of progastrin concentrations were serially assessed during treatments in 168 patients with ovarian cancers enrolled in the randomized CHIVA trial (NCT01583322, GINECO), 191 patients with peritoneal involvement from gastro-intestinal cancers enrolled in BIG-RENAPE trial (NCT03787056), and in 95 HCC patients. The progastrin was measured using an ELISA test developed by ECS Progastrin (Prilly, Switzerland). Results: Compared to healthy blood donors, progastrin was found at higher concentrations in the plasma of cancer patients: median 4.47 vs 0.20 pM, P < 0.0001; diagnostic discriminative power, ROC analysis AUC = 0.86 (95% CI, 0.83-0.89; P < 0.0001). Progastrin levels were found elevated in all cancer groups, regardless of disease stages, and of pathology origins: ROC AUCs ranged from 0.71 to 0.93, all P < 0.0001 (Table). The longitudinal progastrin changes during treatments, suggest relationships to tumor burden, and potential monitoring value. Conclusions: Progastrin is a novel ubiquitous cancer biomarker, easily detectable in the blood using an affordable ELISA test (CancerRead Lab test(R)). It may change the future paradigms about screening (in particular for populations at higher or lower risks of cancer), cancer diagnostic & monitoring. [Table: see text]
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Vallania, Francesco, Karen Assayag, Hayley Warsinske, Peter Ulz, John St John, Carrie Brachmann, Scott D. Patterson, et al. "Exploratory longitudinal analysis of cfDNA to reveal potential biomarkers of CRC progression and treatment response." Journal of Clinical Oncology 38, no. 4_suppl (February 1, 2020): 207. http://dx.doi.org/10.1200/jco.2020.38.4_suppl.207.
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207 Background: Blood-based tests can predict drug response and disease progression. Many tests rely on detecting tumor DNA, which represents only a fraction of all cell-free DNA (cfDNA). Here, we used a novel methodology to infer gene activation from cfDNA. This unique platform offers the ability to identify potential non-tumor derived biomarkers that may be associated with clinical outcomes in colorectal cancer (CRC). Methods: Longitudinal plasma samples from metastatic CRC patients enrolled in NCT01803282 (andecaliximab/chemotherapy/bevacizumab; 92 samples from 12 patients) were evaluated. Patients were classified as progressors (SD+PD) or responders (CR+PR) based on best objective response. Gene activation was inferred from cfDNA fragment length and counts around transcription start sites using whole-genome sequencing. Transcription factor activity was estimated by measuring binding site accessibility across the genome. Tumor fraction (TF) was estimated using ichorCNA. Results: Gene activation profiles inferred from cfDNA across the entire genome identified several genes differentially expressed in progressors or responders. Specifically, all patients with elevated KIR2DL1, an inhibitory NK cell receptor, progressed (p = 6.35e-14). Additionally, BMPR1A activation decreased in responders (p = 0.002) while the DNA- binding activity of SMAD1, which functions directly downstream of BMPR1A in the BMP2 pathway, increased in responders post-therapy (p = 0.03). These 3 genes (i.e., KIR2DL1, BMPR1A and SMAD1) are related to NK cell maturation, suggesting an immunological mechanism. Notably, pre-therapy TF did not predict response. Conclusions: In this pilot study, we demonstrated the ability of a unique cfDNA platform to interrogate multiple features to reveal genes associated with drug response and their underlying mechanism. We identified that KIR2DL1 is associated with progression, and BMPR1A and SMAD1 are associated with response. This work highlights the potential of cfDNA to provide biological insights beyond TF and that identification of non-tumor-derived signals may benefit biomarker discovery and drug target identification.
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Erickson, Claire, Nate Chin, Erin Jonaitis, Fred Ketchum, Carey Gleason, and Lindsay Clark. "Predictors of positive or negative reactions to learning Alzheimer’s biomarker results." Innovation in Aging 5, Supplement_1 (December 1, 2021): 949. http://dx.doi.org/10.1093/geroni/igab046.3426.
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Abstract With improved detection of Alzheimer’s disease and biomarker accessibility, more adults with no or mild symptoms may learn their AD biomarker results. Yet, potential psychosocial impact of learning AD biomarkers is not well understood. In a phone survey, we assessed potential reactions after learning about a hypothetical positive AD biomarker result. Data were collected from cognitively healthy participants (n=334, mean age=64.8±7.7) enrolled in longitudinal AD studies. Exploratory factor analysis identified five latent factors following a hypothetical positive biomarker result: advanced care planning, lifestyle changes to reduce dementia risk factors, psychological distress, subjective cognitive complaints, and stigma. Using linear regression, we found that predictors of potential pessimistic reactions (distress, cognitive complaints, stigma) included higher trust in research (Distress:b:0.04, p:0.04), no dementia family history (Stigma:b:-0.30,p:0.04), poorer memory self-rating (Cognitive complaints:b:-0.19,p:0.02), and Black racial identity (Cognitive complaints:b:0.30,p:0.02, Stigma:b:0.40,p:0.003). Predictors of potential optimistic reactions (advanced care planning, lifestyle changes) included more trust in research (Planning:b:0.07,p<0.0001) and Black racial identity (Planning:b:0.38,p:0.003), as well as younger age (Lifestyle:b:-0.02,p:0.02) and belief in AD controllability (Planning:b:0.22,p:0.003, Lifestyle:b:0.23,p:0.002). Concern about developing AD was associated with increased likelihood of all potential reactions. While AD concern associates with optimistic and pessimistic potential reactions, specific factors of family history, racial identity, trust, belief in AD controllability, and memory rating differentially predict each of the potential outcomes of learning AD biomarker results. These findings may help target education efforts to prepare and reduce risk of negative reactions for cognitively healthy adults who learn their AD biomarker results.
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Upreti, Deepak, Man-li Zhang, Elena Bykova, Alok Pathak, and Sam Kung. "Longitudinal analyses of CD3ζ-chain expression in the correlation of the disease status in a cohort of head and neck cancer patients (TUM2P.1033)." Journal of Immunology 194, no. 1_Supplement (May 1, 2015): 69.30. http://dx.doi.org/10.4049/jimmunol.194.supp.69.30.
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Abstract Purpose: Despite advances in multimodality treatment, the 5-year survival rate of Head and neck squamous cancer (HNSCC) patients has unimproved over the last 4 decades. CD3ζ has emerged as a clinically important immunological molecule in HNSCC. Its relevance as a prognostic biomarker of HNSCC, however, has not been formally addressed in a longitudinal study. Methods: Peripheral blood mononuclear cells (PBMC) were collected from 46 patients and 53 controls at the time of diagnosis and post treatments (upto 2 year period). Expression of CD3ζ in the T cells of the PBMC samples were analyzed in flow cytometry. Results: We standardized a method for longitudinal analyses of intracellular CD3z expressions in the PBMC samples. We considered a <10% baseline increase in the normalized MFI of CD3ζ expression as a predictor of disease status in evaluating the follow-up samples of the HNSCC patients. Correlation analysis showed that 27/29 HNSCC patients who showed an increase in the CD3ζ expression relative to their baselines were disease free (negative predictive value. 93.1%). 10/17 HNSCC patients who showed a reduced/no change in the CD3ζ expression died or had recurrent disease (positive predictive value, 58.8 %). Overall accuracy of the assay was 80.43%. The sensitivity and specificity were respectively 83.3% and 79.41%. Conclusion: Our longitudinal analyses supported that a >10% increase in the CD3ζ expression against baseline could be a good prognostic biomarker in HNSCC patients.