Academic literature on the topic 'Longitudinal biomarker analysis'
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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.
Full textDissertations / Theses on the topic "Longitudinal biomarker analysis"
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Carney, Caroline. "Social patterning in biomarkers of health : an analysis of health inequalities using 'Understanding Society: the UK Household Longitudinal Study'." Thesis, University of Essex, 2017. http://repository.essex.ac.uk/20623/.
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Health inequalities are known to be prevalent in Britain. Though testing hypothesised pathways between socio-economic position and biological markers of health, this thesis aims to improve understanding of how socio-economic inequality becomes health inequality and how physiology is affected by socio-economic position. Using Understanding Society data, access is gained to a range of biomarkers collected cross-sectionally from an adult age range. Methods such as regressions, decompositions and mixed-models are used to identify mediators of SEP’s association with grip strength, self-reported type two diabetes, glycated haemoglobin and lung function. The mediators explored are material deprivation and exposures, psychosocial stress and health behaviours. Using retrospective socio-economic position measures, consideration is paid to the timing of disadvantage, while the wide age range enables identification of when inequalities emerge. Disadvantaged socio-economic position in childhood and adulthood were negatively associated with grip strength, though the gradient does not emerge until mid-adulthood. Health behaviours only slightly mediated this association and childhood socio-economic position continued to be important in adulthood. Support was found for mediation of socio-economic position’s association with self-reported type two diabetes, but not with glycated haemoglobin. The mediation was mainly via obesity with no significant mediation through material deprivation, psychosocial stress or health behaviours. Inequalities in lung function were observable at all adult ages and appeared to worsen with increasing age. Material exposures and health behaviours mediated this. Childhood socio-economic position was important in adulthood and moderated the effect of some exposures and health behaviours. This thesis finds that early disadvantage can have lasting effects. The lack of support for mediation in some outcomes suggests the need to address social inequalities directly, while the identification of mediating mechanisms in other outcomes indicates ways to alleviate these processes.
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Mahoney, Liam George Smith. "Assessment of the transitional circulation in late preterm and term neonates using non-invasive biomarkers : a longitudinal analysis and evaluation of repeatability." Thesis, University of Brighton, 2016. https://research.brighton.ac.uk/en/studentTheses/762746a5-b8af-45d1-82f8-de0ab57c6cad.
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Neonatal circulatory adaptation at birth is unique. If the transition from an in- to ex-utero circulatory system is unsuccessful, circulatory failure ensues resulting in anaerobic respiration and eventual tissue death. This thesis explores the use of novel non-invasive techniques to assess neonatal circulatory adaptation. Data are reported from three observational cohort studies including infants aged less than 72 hours of age and greater than 33 weeks’ gestational age (GA) who received special care (n=50), intensive care (n=25) or total body cooling (n=14). For the first three days of life infants had routine daily clinical assessments (e.g. blood pressure), echocardiographic (superior vena cava flow and right ventricular outflow) and plethysmographic measurements (modified pleth variability index and pulse transit time). Daily longitudinal, comparative and correlational analysis of these measures within and between cohorts of neonates were performed. In addition, their relationships to assessments of short term neurological outcomes and cardiovascular treatment were explored. Bland Altman plots were used to explore the repeatability of plethysmographic and echocardiographic measures. The results indicate that the cardiovascular systems of between the three cohorts of neonates studied adapt differently over the first three days of life. Specifically, neonates who receive total body cooling exhibited significantly lower blood pressures, heart rates and measures systemic blood flow compared to neonates who are healthy or receiving intensive care. Healthy neonates aged between 33 to < 37 weeks GA exhibited daily significant shortening of modified pulse transit time and increased measures of systemic blood flow indicating these neonate’s systemic vascular resistances increase more gradually compared to term neonates with end organ perfusion maintained through increased cardiac output. The intra- and inter-observer repeatability of echocardiographic and plethysmographic assessments was poor and excellent respectively (repeatability index range 26-64% vs. 3-13%). Future studies should focus on the use of these biomarkers in the identification of neonates at risk of circulatory failure.
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Fiot, Jean-Baptiste. "Méthodes mathématiques d’analyse d’image pour les études de population transversales et longitudinales." Thesis, Paris 9, 2013. http://www.theses.fr/2013PA090053/document.
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En médecine, les analyses de population à grande échelle ont pour but d’obtenir des informations statistiques pour mieux comprendre des maladies, identifier leurs facteurs de risque, développer des traitements préventifs et curatifs et améliorer la qualité de vie des patients.Dans cette thèse, nous présentons d’abord le contexte médical de la maladie d’Alzheimer, rappelons certains concepts d’apprentissage statistique et difficultés rencontrées lors de l’application en imagerie médicale. Dans la deuxième partie,nous nous intéressons aux analyses transversales, c-a-d ayant un seul point temporel.Nous présentons une méthode efficace basée sur les séparateurs à vaste marge (SVM)permettant de classifier des lésions dans la matière blanche. Ensuite, nous étudions les techniques d’apprentissage de variétés pour l’analyse de formes et d’images, et présentons deux extensions des Laplacian eigenmaps améliorant la représentation de patients en faible dimension grâce à la combinaison de données d’imagerie et cliniques. Dans la troisième partie, nous nous intéressons aux analyses longitudinales, c-a-d entre plusieurs points temporels. Nous quantifions les déformations des hippocampus de patients via le modèle des larges déformations par difféomorphismes pour classifier les évolutions de la maladie. Nous introduisons de nouvelles stratégies et des régularisations spatiales pour la classification et l’identification de marqueurs biologiquesIn medicine, large scale population analysis aim to obtain statistical information in order to understand better diseases, identify their risk factors, develop preventive and curative treatments and improve the quality of life of the patients.In this thesis, we first introduce the medical context of Alzheimer’s disease, recall some concepts of statistical learning and the challenges that typically occurwhen applied in medical imaging. The second part focus on cross-sectional studies,i.e. at a single time point. We present an efficient method to classify white matter lesions based on support vector machines. Then we discuss the use of manifoldlearning techniques for image and shape analysis. Finally, we present extensions ofLaplacian eigenmaps to improve the low-dimension representations of patients usingthe combination of imaging and clinical data. The third part focus on longitudinalstudies, i.e. between several time points. We quantify the hippocampus deformations of patients via the large deformation diffeomorphic metric mapping frameworkto build disease progression classifiers. We introduce novel strategies and spatialregularizations for the classification and identification of biomarkers
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Wang, Q. (Qin). "Epidemiological applications of quantitative serum NMR metabolomics:causal inference from observational studies." Doctoral thesis, Oulun yliopisto, 2017. http://urn.fi/urn:isbn:9789526215082.
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Abstract Cardiovascular diseases are the leading cause of death worldwide and type 2 diabetes is reaching a global epidemic. Epidemiological studies have identified numerous risk factors and pharmacotherapies in relation to these cardiometabolic diseases. However, the detailed molecular mechanisms of these risk factors and drug therapies generally remain incompletely understood. Elucidating the underlying molecular effects would be essential for better understanding of the disease pathogenesis and also for discovering new therapeutic targets. Quantitative serum metabolomics, which allows for simultaneous quantification of multiple circulating metabolic measures, provides a hypothesis-free approach to systematically inspect the metabolic changes in response to endogenous and exogenous stimuli. Metabolomics thus presents a valuable tool to study the detailed molecular effects of disease risk factors and drug therapies. However, current metabolomics studies are mostly conducted in small cross-sectional studies and the causal relations of the risk factors on the metabolic measures are generally unclear, providing limited public health impact. The present thesis serves as a proof-of-concept to illustrate that well-designed observational studies can be used to infer causality. With the exemplars of assessing molecular effects of two risk factors (body mass index and sex hormone-binding globulin) and two drug therapies (statins and oral contraceptives), the thesis demonstrates that an improved causal inference can be achieved in observational studies via the combination of multiple study designs, including cross-sectional, longitudinal and Mendelian randomization analysis. This robust study design approach together with metabolomics data can be also extended to study the molecular effects of other risk factors and drug therapies. With an improved molecular understanding of a wide range of risk factors and therapies, better understanding of disease pathogenesis is ensuredTiivistelmä Sydän- ja verisuonitaudit ovat johtava kuolinsyy maailmassa ja tyypin 2 diabetes on saavuttamassa globaalin epidemian mittasuhteet. Epidemiologiset tutkimukset ovat löytäneet useita riskitekijöitä ja lääkehoitoja edellä mainituille yleisille taudeille. Tyypin 2 diabetekseen ja sydän- ja verisuonitauteihin liittyvät yksityiskohtaiset molekylaariset mekanismit ymmärretään kuitenkin puutteellisesti. Molekylaaristen yksityiskohtien tarkempi ymmärtäminen olisi siten erittäin merkittävää sekä tautiprosessien ymmärtämiseksi että lääkehoitojen kehittämiseksi. Seerumin kvantitatiivinen metabolomiikka mahdollistaa useiden metabolisten suureiden samanaikaisen määrittämisen verenkierrosta ja tarjoaa siten hypoteesittoman lähestymistavan sekä sisäisten että ulkoisten ärsykkeiden aiheuttamien metabolisten muutosten systemaattiseen tutkimukseen. Metabolomiikka on siten arvokas työkalu yksityiskohtaisten molekylaaristen mekanismien tutkimuksessa, olipa kyseessä taudin riskitekijät tai lääkehoito. Metabolomiikkatutkimuksia on kuitenkin pääasiassa tehty pienissä poikittaistutkimuksissa ja riskitekijöihin liittyvien metabolisten suureiden syy- ja seuraussuhteet ovat yleisesti epäselviä, josta johtuen metabolisten suureiden kansanterveydellinen sovellettavuus on ollut heikkoa. Tämä väitöskirja esittelee tutkimuskonseptin hyvin suunniteltujen havaintotutkimuksien soveltamiseksi syy- ja seuraussuhteiden arvioinnissa. Työ sisältää esimerkit kahden riskitekijän (painoindeksi ja sukupuolihormoneja sitova globuliini) ja kahden lääkehoidon (statiinit ja ehkäisypillerit) molekylaaristen vaikutusten kausaalisista tutkimuksista. Tulokset havainnollistavat, että kausaalisten johtopäätösten luotettavuutta voidaan parantaa yhdistämällä useita tutkimusasetelmia, kuten poikittais- ja pitkittäistutkimuksia sekä Mendelististä satunnaistamista. Esitettyjä luotettavia tutkimusasetelmia, yhdessä metabolomiikkadatan kanssa, voidaan laajentaa muiden riskitekijöiden ja lääkehoitojen molekylaaristen vaikutusten tutkimuksiin. Parantunut molekyylitason ymmärrys useista riskitekijöistä ja lääkehoidoista johtaa myös parempaan tautiprosessien ymmärtämiseen
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眞野, 智生, and Tomoo Mano. "CROSS-SECTIONAL AND LONGITUDINAL ANALYSIS OF AN OXIDATIVE STRESS BIOMARKER FOR SPINAL AND BULBAR MUSCULAR ATROPHY." Thesis, 2014. http://hdl.handle.net/2237/20393.
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Greenberg, Alexandra Rachel. "Longitudinal histopathological, immunohistochemical, and In Situ hybridization analysis of host and viral biomarkers in liver tissue sections of Ebola (EBOV) infected rhesus macaques." Thesis, 2019. https://hdl.handle.net/2144/36565.
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INTRODUCTION: Ebola virus (EBOV) is a highly infectious and often lethal filovirus that causes hemorrhagic fever, with a reported case fatality rate of 40-90%. There are currently no Food and Drug Administration (FDA) approved medical countermeasures (MCMs) for EBOV. Non-human primates (NHPs) remain the gold standard animal model for EBOV research as they most accurately recapitulate human disease.
OBJECTIVE: This study aimed to characterize the temporal viral pathogenesis of EBOV in the liver of infected rhesus macaques using routine histopathology, multiplex immunohistochemistry (mIHC) and multiplex fluorescent In Situ Hybridization (mFISH), refined by digital pathology (DP) and image analysis (DIA).
METHODS: 21 FFPE liver sections from EBOV-infected rhesus macaques were examined microscopically (Uninfected controls n=3; 3 DPE n=3; 4 DPE n=3; 5 DPE n=3; 6 DPE n=3; Terminal n=6). Tissues were stained with H&E and PTAH for histopathological scoring. Three serial sections were fluorescently immunolabeled or hybridized under three independent conditions (1.EBOV VP35, Tissue Factor, CD68; 2.EBOV VP35, Heppar, Myeloperoxidase (MPO); 3.EBOV VP35, IL-6, ISG-15). Slides were digitized by a Vectra PolarisTM fluorescent whole slide scanner and DIA was conducted using HaloTM image analysis software. Statistical analysis was conducted using GraphPad PrismTM 8.0.
RESULTS: Comparing peracute (3-4 DPE) to acute (5-6 DPE) and terminal (6-8 DPE) EBOV infection, there is a statistically significant (p < 0.05) increase in hepatic inflammation and fibrin thrombi, correlating with an absolute increase in macrophages (CD68), neutrophils (MPO), and total % of Tissue Factor in the liver. There is also a significant increase in the severity of necrosis, which correlates with a decrease in Heppar. While there was significant colocalization of VP35 and CD68 starting at 4 DPE, there was only rare colocalization of VP35 with Heppar, even in terminal animals. Similar to mIHC, progressive and statistically significant differences were observed in gene expression when comparing peracute to acute and terminal EBOV infection. IL-6 predominated within periportal fibrovascular compartments, but also colocalized within cells concurrently expressing EBOV VP35. EBOV VP35 expression was observed within histiocytes, endothelial cells, and less commonly hepatocytes. ISG-15 expression was observed in periportal regions and in proximity to cells expressing EBOV VP35, but colocalization within EBOV VP35 expressing cells was an extremely rare event.
CONCLUSION: Qualitative tools are well suited for confirming virulence and viral tissue tropism, but do little to build on our current understanding of disease. Using DIA in partnership with mIHC and mFISH, this study quantified statistically significant temporal changes in the immunoreactivity and hybridization of host and viral biomarkers that have previously been linked to the pathogenesis of EBOV. Taken together, these tools have enabled us to characterize minute changes that reflect magnitudes of biological variability simply not feasible to detect with the human eye. Furthermore, spatial context has refined our current understanding of differential gene expression of EBOV, which has the potential to aid in development of host-directed therapies. The establishment of these benchmarks will serve as a guide for the validation of cross-institutional EBOV animal models.
Book chapters on the topic "Longitudinal biomarker analysis"
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Di Maso, Matteo, Monica Ferraroni, Pasquale Ferrante, Serena Delbue, and Federico Ambrogi. "Longitudinal profile of a set of biomarkers in predicting Covid-19 mortality using joint models." In Proceedings e report, 191–96. Florence: Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-461-8.36.
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In survival analysis, time-varying covariates are endogenous when their measurements are directly related to the event status and incomplete information occur at random points during the follow-up. Consequently, the time-dependent Cox model leads to biased estimates. Joint models (JM) allow to correctly estimate these associations combining a survival and longitudinal sub-models by means of a shared parameter (i.e., random effects of the longitudinal sub-model are inserted in the survival one). This study aims at showing the use of JM to evaluate the association between a set of inflammatory biomarkers and Covid-19 mortality. During Covid-19 pandemic, physicians at Istituto Clinico di Città Studi in Milan collected biomarkers (endogenous time-varying covariates) to understand what might be used as prognostic factors for mortality. Furthermore, in the first epidemic outbreak, physicians did not have standard clinical protocols for management of Covid-19 disease and measurements of biomarkers were highly incomplete especially at the baseline. Between February and March 2020, a total of 403 COVID-19 patients were admitted. Baseline characteristics included sex and age, whereas biomarkers measurements, during hospital stay, included log-ferritin, log-lymphocytes, log-neutrophil granulocytes, log-C-reactive protein, glucose and LDH. A Bayesian approach using Markov chain Monte Carlo algorithm were used for fitting JM. Independent and non-informative priors for the fixed effects (age and sex) and for shared parameters were used. Hazard ratios (HR) from a (biased) time-dependent Cox and joint models for log-ferritin levels were 2.10 (1.67-2.64) and 1.73 (1.38-2.20), respectively. In multivariable JM, doubling of biomarker levels resulted in a significantly increase of mortality risk for log-neutrophil granulocytes, HR=1.78 (1.16-2.69); for log-C-reactive protein, HR=1.44 (1.13-1.83); and for LDH, HR=1.28 (1.09-1.49). Increasing of 100 mg/dl of glucose resulted in a HR=2.44 (1.28-4.26). Age, however, showed the strongest effect with mortality risk starting to rise from 60 years.
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Müller, Andreas, and Martin Meier. "Assessment of Renal Volume with MRI: Experimental Protocol." In Methods in Molecular Biology, 369–82. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_21.
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AbstractRenal length and volume are important parameters in the clinical assessment of patients with diabetes mellitus, kidney transplants, or renal artery stenosis. Kidney size is used in primary diagnostics to differentiate between acute (rather swollen kidneys) and chronic (rather small kidney) pathophysiology. Total kidney volume is also an established biomarker in studies for the treatment of autosomal dominant polycystic kidney disease (ADPKD). There are several factors influencing kidney size, and there is still a debate on the value of the measured kidney size in terms of renal function or cardiovascular risk. The renal volume is most often calculated by measuring the three axes of the kidney, on the assumption that the organ resembles an ellipsoid. By default, the longitudinal and transverse diameters of the kidney are measured. In animal models renal length and volume1 are also important parameters in the assessment of organ rejection after transplantation and in determination of kidney failure due to renal artery stenosis, recurrent urinary tract infections, or diabetes mellitus. In general total kidney volume (TKV) is a valuable parameter for predicting prognosis and monitoring disease progression in animal models of human diseases like polycystic kidney disease (PKD) or acute kidney injury (AKI) and chronic kidney disease (CKD).This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol is complemented by two separate chapters describing the basic concept and experimental procedure.
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Chuang, Kai-Hsiang, Martin Meier, María A. Fernández-Seara, Frank Kober, and Min-Chi Ku. "Renal Blood Flow Using Arterial Spin Labeling (ASL) MRI: Experimental Protocol and Principles." In Methods in Molecular Biology, 443–53. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_26.
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AbstractA noninvasive, robust, and reproducible method to measure renal perfusion is important to understand the physiology of kidney. Arterial spin labeling (ASL) MRI technique labels the endogenous blood water as freely diffusible tracers to measure perfusion quantitatively without relying on exogenous contrast agent. Therefore, it alleviates the safety concern involving gadolinium chelates. To obtain quantitative tissue perfusion information is particularly relevant for multisite and longitudinal imaging of living subjects.This chapter is based upon work from the PARENCHIMA COST Action, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This experimental protocol chapter is complemented by two separate chapters describing the basic concept and data analysis.
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Garteiser, Philippe, Octavia Bane, Sabrina Doblas, Iris Friedli, Stefanie Hectors, Gwenaël Pagé, Bernard E. Van Beers, and John C. Waterton. "Experimental Protocols for MRI Mapping of Renal T1." In Methods in Molecular Biology, 383–402. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_22.
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AbstractThe water proton longitudinal relaxation time, T1, is a common and useful MR parameter in nephrology research. Here we provide three step-by-step T1-mapping protocols suitable for different types of nephrology research. Firstly, we provide a single-slice 2D saturation recovery protocol suitable for studies of global pathology, where whole-kidney coverage is unnecessary. Secondly, we provide an inversion recovery type imaging protocol that may be optimized for specific kidney disease applications. Finally, we also provide imaging protocol for small animal kidney imaging in a clinical scanner.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concept and experimental procedure.
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Ramos Delgado, Paula, Ekkehard Küstermann, André Kühne, Jason M. Millward, Thoralf Niendorf, Andreas Pohlmann, and Martin Meier. "Hardware Considerations for Preclinical Magnetic Resonance of the Kidney." In Methods in Molecular Biology, 131–55. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-0978-1_8.
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AbstractMagnetic resonance imaging (MRI) is a noninvasive imaging technology that offers unparalleled anatomical and functional detail, along with diagnostic sensitivity. MRI is suitable for longitudinal studies due to the lack of exposure to ionizing radiation. Before undertaking preclinical MRI investigations of the kidney, the appropriate MRI hardware should be carefully chosen to balance the competing demands of image quality, spatial resolution, and imaging speed, tailored to the specific scientific objectives of the investigation. Here we describe the equipment needed to perform renal MRI in rodents, with the aim to guide the appropriate hardware selection to meet the needs of renal MRI applications.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This chapter on hardware considerations for renal MRI in small animals is complemented by two separate publications describing the experimental procedure and data analysis.
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Yue, Mu. "Sparse Boosting Based Machine Learning Methods for High-Dimensional Data." In Computational Statistics and Applications. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.100506.
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In high-dimensional data, penalized regression is often used for variable selection and parameter estimation. However, these methods typically require time-consuming cross-validation methods to select tuning parameters and retain more false positives under high dimensionality. This chapter discusses sparse boosting based machine learning methods in the following high-dimensional problems. First, a sparse boosting method to select important biomarkers is studied for the right censored survival data with high-dimensional biomarkers. Then, a two-step sparse boosting method to carry out the variable selection and the model-based prediction is studied for the high-dimensional longitudinal observations measured repeatedly over time. Finally, a multi-step sparse boosting method to identify patient subgroups that exhibit different treatment effects is studied for the high-dimensional dense longitudinal observations. This chapter intends to solve the problem of how to improve the accuracy and calculation speed of variable selection and parameter estimation in high-dimensional data. It aims to expand the application scope of sparse boosting and develop new methods of high-dimensional survival analysis, longitudinal data analysis, and subgroup analysis, which has great application prospects.
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Ping Lin, Peter. "Liquid Biopsy Analysis of Circulating Tumor Biomarkers in Lung Cancer." In Lung Cancer - Modern Multidisciplinary Management [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.95422.
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Risk stratification, prognostication and longitudinal monitoring of therapeutic efficacy in lung cancer patients remains highly challenging. It is imperative to establish robust surrogate biomarkers for identifying eligible patients, predicting and effectively monitoring clinical response as well as timely detecting emerging resistance to therapeutic regimens. Circulating tumor biomarkers, analyzed by liquid biopsy, are primarily composed of nucleic acid-based circulating tumor DNA (ctDNA) and an aneuploid cell-based category of circulating tumor cells (CTCs) and circulating tumor-derived endothelial cells (CTECs). Unlike ctDNA, cancer cells are the origin of all categories of various tumor biomarkers. Involvement of aneuploid CTCs and CTECs in tumorigenesis, neoangiogenesis, tumor progression, cancer metastasis and post-therapeutic recurrence has been substantially investigated. Both CTCs and CTECs possessing an active interplay and crosstalk constitute a unique category of cellular circulating tumor biomarkers. These cells concurrently harbor the intact cancer-related genetic signatures and full tumor marker expression profiles in sync with disease progression and therapeutic process. Recent progress in clinical implementation of non-invasive liquid biopsy has made it feasible to frequently carry out ctDNA analysis and unbiased detection of a full spectrum of non-hematologic circulating rare cells including CTCs and CTECs in lung cancer patients, regardless of variation in heterogeneous cell size and cancer cell surface anchor protein expression. In situ phenotypic and karyotypic comprehensive characterization of aneuploid CTCs and CTECs, in combination with single cell-based genotyping and improved ctDNA analyses, will facilitate and benefit multidisciplinary management of lung cancer.
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Vinković, Maja, Andrijana Kopić, and Tvrtka Benašić. "Anti-VEGF Treatment and Optical Coherence Tomography Biomarkers in Wet Age-Related Macular Degeneration." In Recent Advances and New Perspectives in Managing Macular Degeneration [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97689.
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Age-related macular degeneration (AMD) is one of the most common causes of severe visual loss in middle and old-age population, and often leads to serious deterioration in quality of life. Currently, the first-line treatment for neovascular AMD (nAMD) are intravitreal injections of anti-vascular endothelial growth factor (VEGF) medications, including bevacizumab, ranibizumab, and aflibercept and also latest commercially available drug, brolucizumab. During initial examination and imaging and treatment follow-up for patients with nAMD, optical coherence tomography (OCT) is used to predict and assess the therapeutic response and guide the treatment. Several OCT-based biomarkers, including the central subfoveal thickness (CSFT), the presence of intraretinal cysts (IRCs) or subretinal fluid (SRF), and the presence of pigment epithelial detachment (PED), were found to influence baseline visual acuity or visual improvements. Recent analyses of large randomized control trials (RCTs) summarized the usefulness of these OCT-based biomarkers. However, many of these early studies relied on time-domain OCT to evaluate the retinal structures thus providing less precise evaluation of the retinal details. After introduction of spectral-domain OCT (SD-OCT) which provided high resolution images, recent studies offered new insights in specific morphological changes and their different impact on visual function in nAMD. For example, these advancement in resolution offered new classification of IRCs into degenerative and exudative which impacts treatment strategy and final outcome in the treatment of nAMD. Moreover, the recent data disclose a substantial difference between RCTs and real-world studies regarding the response to anti-VEGF therapy. In conclusions, IRCs and PED are associated with poor visual improvement in nAMD in a realworld setting. Both IRCs and SRF responded better than PED to anti-VEGF therapy. These observations mandate large longitudinal studies focusing on the usefulness of these high resolution SD-OCT biomarkers in real-world situations.
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Hood, Leroy, Nathan D. Price, and Simon J. Evans. "What 21st century medicine should be—history, vision, implementation, and opportunities." In Can precision medicine be personal; Can personalized medicine be precise?, 21–46. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780198863465.003.0003.
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P4 medicine will employ longitudinal, high-dimensional analyses of individuals, integrating molecular, digital, electronic health record, and self-monitoring data. This will classify patients, diseases, and drugs, and continually convert data into knowledge through iterative hypothesis testing to inform systems approaches to both wellness and disease. Two preliminary trials have been carried out to validate this approach, one involving 100 individuals over nine months in 2014 and a second recruiting 5,000 individuals over four years from 2015 until 2019. These trials (i) validated scientific (quantitative) wellness, using personal, high-dimensional data to improve one’s wellness, and (ii) demonstrated the power of longitudinal data clouds to bring fundamental new insights into wellness and disease. These led to a vision of 21st century n = 1 medicine which optimizes the health trajectories of each individual. Each health trajectory has three states: (1) a wellness state that will be extended and optimized through scientific wellness and healthy ageing; (2) a wellness-to-disease transition state where early biomarkers will be identified and used to design therapies employing the identification of the earliest disease-perturbed networks to reverse disease before it manifests as a clinical entity; and (3) a progressive disease state for which physicians and scientists will use data-driven systems approaches to find therapies that ameliorate or reverse disease. This chapter discusses the promotion of a million person genome/phenome project with a major healthcare system to initiate the implementation of 21st century medicine in the US healthcare system. The challenges and opportunities associated with the realization of 21st century medicine are also discussed.
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Muñoz, Alvaro, and F. Javier Nieto. "Cohort studies." In Oxford Textbook of Global Public Health, edited by Roger Detels, Quarraisha Abdool Karim, Fran Baum, Liming Li, and Alastair H. Leyland, 85–100. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780198816805.003.0030.
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The simplest cohort design is to obtain exposure data at baseline and follow-up individuals to obtain data up to the point when the event of interest occurs. A richer design includes regularly scheduled visits at which data on exposures are updated. The exposures can be either fixed over time (e.g. race), change directly with time (e.g. age and calendar), or change at their own pace (e.g. biological markers). According to the scientific aims of a cohort study, disease occurrence can be measured as an event in person-time, time-to-endpoint of interest, or change in a biomarker repeatedly measured at follow-up visits. Analytical methods include survival analyses to handle censored observations and late entries due to incomplete observation of the development of events and origin, and longitudinal data analyses for the trajectories of markers of disease progression. Stratification, multivariate regression, and causal inference methods are key tools to accomplish comparability among exposed and unexposed groups. Identification of exposures and risk factors for disease provides a basis for prevention strategies. Data from cohort studies can be used to assess the effects of interventions by using data at the individual level to determine individual effectiveness or by comparing occurrence of disease in the population when typically none or only a few are intervened to determine population effectiveness.
Conference papers on the topic "Longitudinal biomarker analysis"
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Brum, Wagner, Andrei Bieger, Joao Pedro Ferrari Souza, Marco de Bastiani, Andrea Benedet, Nicholas Ashton, Tharick Pascoal, et al. "A THREE-RANGE APPROACH ENHANCES PROGNOSTIC UTILITY OF CSF BIOMARKERS IN ALZHEIMER’S DISEASE." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda022.
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Background: Alzheimer’s disease (AD) was biologically defined by the 2018 NIA-AA Research Framework (RF), which recommends dichotomously defining biomarker status as normal or abnormal with single cutpoints. However, a three-range approach remains unexplored in AD fluid biomarkers. Objective: To assess the prognostic utility of a three-range approach for CSF biomarkers in AD. Methods: We included 1278 non-demented individuals (CU: n=575; MCI: n=703) from the ADNI with baseline CSF Elecsys® biomarkers. Within it, we defined three-range cutpoints with two-graph receiver operating characteristics (TGROC) for each CSF biomarker (Aβ1-42, p-tau, p-tau/Aβ1-42), based on amyloid PET positivity. Then, linear mixed-effects and Cox proportional hazards models were used to estimate longitudinal cognitive trajectories and risk of clinical progression based on CSF biomarker status. Hereby derived three-range cutpoints were compared to previously described binary thresholds for the same biomarkers. Power analyses for simulated trials were also carried. Results: We observed dynamic amyloid-PET changes for participants in the intermediate range, while a static profile for clearly normal and abnormal groups. Longitudinally, our approach revealed a divergent intermediate cognitive trajectory undetected by dichotomization, with power analyses demonstrating potential applications for trial enrichment. Conclusion: The proposed approach can improve CSF-based diagnosis, refine prognostic assessment and enhance clinical trial recruitment.
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Ciosi, Marc, Robin Young, Seung Kwak, and Darren G. Monckton. "D01 Longitudinal analysis of somatic expansion of the HTT repeat in blood as a potential biomarker of somatic instability in Huntingon disease." In EHDN 2022 Plenary Meeting, Bologna, Italy, Abstracts. BMJ Publishing Group Ltd, 2022. http://dx.doi.org/10.1136/jnnp-2022-ehdn.57.
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Pinto-Plata, Victor M., Hana Mullerova, Ciro Casanova, Juan Pablo de Torres, Henneth Corado, Nerea Varo, Elizabeth Cordoba, et al. "Serum Biomarkers In COPD Survivors And Controls. Longitudinal Analysis." In American Thoracic Society 2012 International Conference, May 18-23, 2012 • San Francisco, California. American Thoracic Society, 2012. http://dx.doi.org/10.1164/ajrccm-conference.2012.185.1_meetingabstracts.a4507.
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Rocha, Andreia, Bruna Bellaver, Luiza Machado, Carolina Soares, Pâmela C. L. Ferreira, Samuel Greggio Gianina T. Venturin, Jaderson C. da Costa, Diogo O. Souza, and Eduardo R. Zimmer. "TEMPORAL CHANGES IN ASTROCYTES ON A TRANSGENIC RAT MODEL OF AD." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda023.
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Background: Recent evidences have pointed to astrocytes as important players in the Alzheimer’s Disease (AD) pathogenesis. Objective: With this in mind, we aim to longitudinally investigate astrocyte changes in a new important AD transgenic model, the TgF344-AD rat, the first animal model harboring human APP/PS1 mutations which presents age-dependent amyloid and tau pathology. Methods: TgF344-AD rats and wild type littermates were evaluated in three time points: 3, 6 and 9 months of age. Rats underwent a [18F]FDG-microPET, a spatial-memory, an astrocytes CSF biomarkers (ELISA multiplex) and a glutamate uptake (ex-vivo slices) analysis. Examination of further time-points are being conducted at the moment. Results: At 9 months of age, TgF344-AD animals presented an increase in the cortical [18F]FDG uptake and a decline in their alternance performance in the Y-maze task. In the CSF analysis, GFAP was elevated at both 6 months and 9 months, while S100B presented a decrease at 6mo. Additionally, the cortical glutamate uptake was increased at 9 months. Conclusion: This study is the first to longitudinally investigate the in vivo brain glucose metabolism in the TgF344-AD rat model. Our results suggest that this model presents an early increase on glucose metabolism which may be related to astrocytes activation and the increase of glutamate uptake by these cells. Furthermore, we also identified a spatial memory impairment at the same age.
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"The analysis of different longitudinal biomarkers association with the overall survival in non-small cell lung cancer by means of joint modeling." In Bioinformatics of Genome Regulation and Structure/ Systems Biology. institute of cytology and genetics siberian branch of the russian academy of science, Novosibirsk State University, 2020. http://dx.doi.org/10.18699/bgrs/sb-2020-324.
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Esteves, Filipa, Joana Madureira, João Paulo Teixeira, and Solange Costa. "Assessment of Potential Health Risks of Portuguese Wildland Firefighters’ Occupational Exposure: Biomonitoring Approach." In 4th Symposium on Occupational Safety and Health. FEUP, 2021. http://dx.doi.org/10.24840/978-972-752-279-8_0031-0036.
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Introduction:Worldwide, forest fires are among the most common forms of natural disasters. In the closing years of the last century there was an increase of the burned area in some parts of the globe, including in Europe. Portugal has been particularly affected by large forest fires and megafires, which have been occurred mainly in the central and northern regions. The proximity of firefighters to fire exposes them to high levels of toxic compounds making this occupation one of the most dangerous and leading International Agency for Research on Cancer to classified occupational firefighting activity as possibly carcinogenic to humans. Up to date, the existing studies are mainly focused on environmental monitoring, existing limited information regarding biomonitoring assessments during real scenarios of wildland fires combat. This study aims to evaluate the impact of firefighting occupational exposure at molecular and cellular levels, considering personal exposure levels. Early-effect biomarkers (e.g., micronucleus, DNA strand breaks and oxidative DNA damage) will be analyzed in order to understand the mechanisms of action through which woodsmoke may impact firefighters’ health, including the risk of cancer. Methodology:This ongoing prospective longitudinal study will comprise three different stages, specifically pre-exposure, exposure, and post-exposure to fire season. Around 200 wildland northern Portuguese firefighters will be involved in this study. Characterization of the study population will be conducted via questionnaires. Firefighters’ personal exposurelevels will be assessed by means of metabolites in exhaled breath, using an artificial olfactory system (e-nose technology). Buccal and urine samples will be used to measure genomic instability through micronucleus test in buccal epithelial cells and urothelial cells. DNA damage and oxidative DNA damage will be evaluated in peripheral blood lymphocytes using the comet assay. Statistical analysis will be performed to determine the relationship between personal exposure levels to toxic compounds and the early-effect biomarkers over the three different phases of the study. Expected results: The obtained results will support a more accurate and comprehensive assessment of occupational risks among wildland firefighters, crucial to prevent/reduce the associated health impacts. This work will contribute tothe establishment of recommendations/good practices to improve firefighters’ working conditions, allowing better definitions of policies and prevention strategies highly needed in this sector.
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Barbosa, Breno, Juliana de Souza Talarico, Ricardo Nitrini, Sônia Brucki, and Maira de Oliveira. "CORTISOL LEVELS AND COGNITIVE STATUS IN ELDERLY SUBJECTS: PRELIMINARY RESULTS FROM A MEMORY COHORT." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda065.
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Background: There’s a growing body of research evaluating chronic stress as potentially preventable risk factor for dementia. Objective: To investigate whether chronic stress or cortisol measures are associated with cognitive status and dementia biomarkers. Methods: Transversal analysis to evaluate the relation between cortisol levels, amyloid pathology and cognitive status in a subset subjects with subjective cognitive decline (SCD), mild cognitive impairment (MCI) and controls. Chronic stress evaluation involved anthropometric measures, serum cortisol and DHEA-sulfate, glycated hemoglobin, total and HDL cholesterol, creatinine, fibrinogen and reactive protein-C. Exclusion criteria included dementia and corticosteroids use. Results: 50 participants with serum cortisol levels available were included for analysis. Mean age was 71.8 years (SD + 5.2), with 36 female patients (50%), 11.3 years of education (SD + 5). Amnestic MCI was the most prevalent cognitive status (40%), followed by non-amnestic MCI (28%) and SCD (21%). 24 subjects had access to amyloid status assessment with PET-PiB (9 positive, 15 negative). In our sample the mean serum cortisol level was 9.09 mg/dL (+SD 4.1), with 12 individuals in the first tercile (24%), 30 in the middle tercile (60%) and 8 in the upper tercile (16%). Individuals in the lower cortisol tercile had more positive PET-PiB scans, while in the middle cortisol tercile all individuals had negative scans (p = 0.007 | Fisher’s test). Conclusion: Despite the modest sample size, there was a significant inverse association between cortisol terciles and amyloid status. More longitudinal cortisol measures (ie. salivary, urinary or hair) and a larger sample size could give us more information.
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Raimondi, Lucrezia, Laura Di Benedetto, Paolo Ciracì, Rachele Lazzeroni, Filippo Maria Raimondi, Gian Paolo Spinelli, and Giuseppe Naso. "CIRCULATING TUMOR DNA OF CEREBROSPINAL FLUID SAMPLES IN TRIPLE-NEGATIVE BREAST CANCER: USEFULNESS OF LONGITUDINAL ASSESSMENT FOR EARLY DETECTION OF BRAIN METASTASIS." In Abstracts from the Brazilian Breast Cancer Symposium - BBCS 2021. Mastology, 2021. http://dx.doi.org/10.29289/259453942021v31s2008.
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Objectives: Triple-negative breast cancer (TNBC) still has poor prognosis for a higher rate of relapse and a greater tendency of developing brain metastasis (BrM) compared with other major breast cancer subtypes. Circulating tumor DNA (ctDNA) represents a valuable tool associated with the outcome and the aggressiveness of breast cancer. Biomarkers allowing to predict the development of BrM in TNBC are needed. We studied the usefulness of assessment of CSF-ctDNA for identification early at-risk patients to develop BrM in TNBC. Methodology: A total of 323 newly diagnosed nonmetastatic TNBC patients who underwent neoadjuvant therapy + surgery (NACT) with complete response (CR) were prospectively enrolled. After surgery, CSF-ctDNA collected from all patients enrolled was extracted and assessed using the QIAamp Circulating Nucleic Acid Kit. Survival curves were estimated by using Kaplan–Meier method and compared with the log-rank test. Multivariate Cox regression was used to identify the risk of mortality at 3 years. Results: After NACT, CSF-ctDNA was detectable in 126/323 (39%) patients, 101/126 (80%) were diagnosed at Stage 3. A total of 124 out of 126 (98.4%) ctDNA+ patients subsequently developed BrM. In contrast, only 2 (2/197, 1%) ctDNA− patients subsequently developed BrM and 195 other patients remain in a CR (p <0.001, Fisher’s exact test). CSF-ctDNA did associate with PFS and OS: undetectable ctDNA was associated with superior PFS (HR 0.3; p=0.002) and OS (HR 0.2; p<0.01), indicating survival is largely determined by the onset of BrM. With a median follow-up of 3 years, median PFS of ctDNA+ versus ctDNA− patients was 13 months versus not reach, p=0.004 (log-rank test). Median OS for ctDNA+ versus ctDNA− patients was 16 months after NACT versus not reach, p=0.0016 (log-rank test). At multivariate analysis, detectable CSF-ctDNA emerged as the best predictor of the development of BrM and 24-month mortality (HR: 3.62; p <0.0001). Age, stage, Ki67%, and response to chemotherapy were not significantly associated with the prognosis. Conclusion: After NACT, detectable CSF-ctDNA significantly associated with PFS and OS, identifying early at-risk patients to develop BrM in TNBC who should take advantage from appropriate additional treatment, remains a critical problem.
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Scharm, Sarah, Sabine Dettmer, Jens Vogel-Claussen, Antje Prasse, Lars Knudsen, Frank Wacker, Jan Fuge, and Hoen-Oh Shin. "Combined assessment of regional lung function and morphology using a contrast enhanced Dual-Energy CT protocol: Prospective value of functional imaging biomarkers in longitudinal analysis of patients with Interstitial Lung Disease." In ERS International Congress 2020 abstracts. European Respiratory Society, 2020. http://dx.doi.org/10.1183/13993003.congress-2020.4575.
Full textReports on the topic "Longitudinal biomarker analysis"
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Ma, Yunxing, Julia Brettschneider, and Joanna Collingwood. A systematic review and meta-analysis of cerebrospinal fluid amyloid and tau levels in patients progressing from Mild Cognitive Impairment to Alzheimer’s Disease. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, July 2022. http://dx.doi.org/10.37766/inplasy2022.7.0020.
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Review question / Objective: Reported levels of amyloid-beta and tau in human cerebrospinal fluid (CSF) are evaluated to discover if these biochemical markers can predict the transition from Mild Cognitive Impairment (MCI) to Alzheimer’s disease (AD). A systematic review and quantitative meta-analyses are performed to test relationships between three potential biomarkers in CSF (Aβ(1-42), T-tau, and P-tau181) and the evolution of AD in longitudinal evaluations of levels relative to baseline, using prior-published experimental data. The primary focus of the analysis is on the period describing the transition of a patient from MCI to AD, where it is critical to discover the main biomarker characteristics that differentiate patient outcomes for those who have a stable form of MCI, and those who progress to a confirmed diagnosis of AD. A secondary purpose of the review was to examine the status of iron in CSF as a function of disease status.