- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05687578
PUER ("Previously Unrecognized Emerging Risks") Life Clinical Study (PUER)
A Prospective, Non-Randomized, Multi-Center Observational Study to Establish a Physical Baseline Profile for Individual Study Subjects Using Various Modalities and Identify Deviations Via Longitudinal Monitoring That May Develop Over Time
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
The two key elements of the PUER Research protocol include (1) molecular and laboratory profiling and (2) non-invasive imaging and wearables/ "quantified self" measurements. All elements are optional. Molecular assessments will be conducted using peripheral blood samples, and potentially urine, stool or saliva samples. Non-invasive imaging assessment will consist of magnetic resonance imaging (MRI) and computerized tomography (CT) scans, ultrasound, and x-ray. All imaging modalities are optional. Other functional assessments, including respiratory, cardiac and other functions, as well as self-quantifiable assessments via wearables, may also be conducted and are optional.
The study will result in longitudinal data collection to inform if any modalities employed here can inform of baseline deviations for individuals. Researchers at study sites will not be blinded to the data being collected during this study.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Locations
-
-
Georgia
-
Atlanta, Georgia, United States, 30350
- Puer Research, LLC
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-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Male or non-pregnant female; age 18 to 90
- Absence or presence of any medical history or any signs or symptoms of any disease
- Women of childbearing potential (WOCBP) must have a negative urine pregnancy test (UPT) at all visits
Exclusion Criteria:
- Unwillingness or inability to participate in the study
- Unwillingness or inability to provide written Informed Consent Form
- WOCBP with positive pregnancy test at enrollment or at any visit
Study Plan
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Prospective
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Biomarkers that exhibit significant change
Time Frame: 12 Months
|
The number of biomarkers that exhibit significant change from baseline to any follow-up timepoint, if obtained.
|
12 Months
|
Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Szilard Voros, MD, Puer Life
Publications and helpful links
General Publications
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- Amendola LM, Dorschner MO, Robertson PD, Salama JS, Hart R, Shirts BH, Murray ML, Tokita MJ, Gallego CJ, Kim DS, Bennett JT, Crosslin DR, Ranchalis J, Jones KL, Rosenthal EA, Jarvik ER, Itsara A, Turner EH, Herman DS, Schleit J, Burt A, Jamal SM, Abrudan JL, Johnson AD, Conlin LK, Dulik MC, Santani A, Metterville DR, Kelly M, Foreman AK, Lee K, Taylor KD, Guo X, Crooks K, Kiedrowski LA, Raffel LJ, Gordon O, Machini K, Desnick RJ, Biesecker LG, Lubitz SA, Mulchandani S, Cooper GM, Joffe S, Richards CS, Yang Y, Rotter JI, Rich SS, O'Donnell CJ, Berg JS, Spinner NB, Evans JP, Fullerton SM, Leppig KA, Bennett RL, Bird T, Sybert VP, Grady WM, Tabor HK, Kim JH, Bamshad MJ, Wilfond B, Motulsky AG, Scott CR, Pritchard CC, Walsh TD, Burke W, Raskind WH, Byers P, Hisama FM, Rehm H, Nickerson DA, Jarvik GP. Actionable exomic incidental findings in 6503 participants: challenges of variant classification. Genome Res. 2015 Mar;25(3):305-15. doi: 10.1101/gr.183483.114. Epub 2015 Jan 30.
- Ganz P, Heidecker B, Hveem K, Jonasson C, Kato S, Segal MR, Sterling DG, Williams SA. Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients With Stable Coronary Heart Disease. JAMA. 2016 Jun 21;315(23):2532-41. doi: 10.1001/jama.2016.5951.
- Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S). Lancet. 1994 Nov 19;344(8934):1383-9.
- Arnoldi E, Gebregziabher M, Schoepf UJ, Goldenberg R, Ramos-Duran L, Zwerner PL, Nikolaou K, Reiser MF, Costello P, Thilo C. Automated computer-aided stenosis detection at coronary CT angiography: initial experience. Eur Radiol. 2010 May;20(5):1160-7. doi: 10.1007/s00330-009-1644-7. Epub 2009 Nov 5.
- Assarsson E, Lundberg M, Holmquist G, Bjorkesten J, Thorsen SB, Ekman D, Eriksson A, Rennel Dickens E, Ohlsson S, Edfeldt G, Andersson AC, Lindstedt P, Stenvang J, Gullberg M, Fredriksson S. Homogenous 96-plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability. PLoS One. 2014 Apr 22;9(4):e95192. doi: 10.1371/journal.pone.0095192. eCollection 2014.
- Bennuru S, Lustigman S, Abraham D, Nutman TB. Metabolite profiling of infection-associated metabolic markers of onchocerciasis. Mol Biochem Parasitol. 2017 Jul;215:58-69. doi: 10.1016/j.molbiopara.2017.01.008. Epub 2017 Feb 8.
- Bromberg Y. Building a genome analysis pipeline to predict disease risk and prevent disease. J Mol Biol. 2013 Nov 1;425(21):3993-4005. doi: 10.1016/j.jmb.2013.07.038. Epub 2013 Aug 5.
- Chong CA, Tomlinson G, Chodirker L, Figdor N, Uster M, Naglie G, Krahn MD. An unadjusted NNT was a moderately good predictor of health benefit. J Clin Epidemiol. 2006 Mar;59(3):224-33. doi: 10.1016/j.jclinepi.2005.08.005.
- Crick F. Central dogma of molecular biology. Nature. 1970 Aug 8;227(5258):561-3. doi: 10.1038/227561a0. No abstract available.
- David CEB, Lucas AMB, Cunha PLO, Viana YIP, Yoshinaga MY, Miyamoto S, Filho ABC, Varela ALN, Kowaltowski AJ, Facundo HT. Calorie restriction changes lipidomic profiles and maintains mitochondrial function and redox balance during isoproterenol-induced cardiac hypertrophy. J Physiol Biochem. 2022 Feb;78(1):283-294. doi: 10.1007/s13105-021-00863-4. Epub 2022 Jan 13.
- Design and baseline results of the Scandinavian Simvastatin Survival Study of patients with stable angina and/or previous myocardial infarction. Am J Cardiol. 1993 Feb 15;71(5):393-400. doi: 10.1016/0002-9149(93)90438-i.
- Dorschner MO, Amendola LM, Turner EH, Robertson PD, Shirts BH, Gallego CJ, Bennett RL, Jones KL, Tokita MJ, Bennett JT, Kim JH, Rosenthal EA, Kim DS; National Heart, Lung, and Blood Institute Grand Opportunity Exome Sequencing Project; Tabor HK, Bamshad MJ, Motulsky AG, Scott CR, Pritchard CC, Walsh T, Burke W, Raskind WH, Byers P, Hisama FM, Nickerson DA, Jarvik GP. Actionable, pathogenic incidental findings in 1,000 participants' exomes. Am J Hum Genet. 2013 Oct 3;93(4):631-40. doi: 10.1016/j.ajhg.2013.08.006. Epub 2013 Sep 19.
- Fest J, Vijfhuizen LS, Goeman JJ, Veth O, Joensuu A, Perola M, Mannisto S, Ness-Jensen E, Hveem K, Haller T, Tonisson N, Mikkel K, Metspalu A, van Duijn CM, Ikram A, Stricker BH, Ruiter R, van Eijck CHJ, van Ommen GB, 't Hoen PAC. Search for Early Pancreatic Cancer Blood Biomarkers in Five European Prospective Population Biobanks Using Metabolomics. Endocrinology. 2019 Jul 1;160(7):1731-1742. doi: 10.1210/en.2019-00165.
- Gold L, Ayers D, Bertino J, Bock C, Bock A, Brody EN, Carter J, Dalby AB, Eaton BE, Fitzwater T, Flather D, Forbes A, Foreman T, Fowler C, Gawande B, Goss M, Gunn M, Gupta S, Halladay D, Heil J, Heilig J, Hicke B, Husar G, Janjic N, Jarvis T, Jennings S, Katilius E, Keeney TR, Kim N, Koch TH, Kraemer S, Kroiss L, Le N, Levine D, Lindsey W, Lollo B, Mayfield W, Mehan M, Mehler R, Nelson SK, Nelson M, Nieuwlandt D, Nikrad M, Ochsner U, Ostroff RM, Otis M, Parker T, Pietrasiewicz S, Resnicow DI, Rohloff J, Sanders G, Sattin S, Schneider D, Singer B, Stanton M, Sterkel A, Stewart A, Stratford S, Vaught JD, Vrkljan M, Walker JJ, Watrobka M, Waugh S, Weiss A, Wilcox SK, Wolfson A, Wolk SK, Zhang C, Zichi D. Aptamer-based multiplexed proteomic technology for biomarker discovery. PLoS One. 2010 Dec 7;5(12):e15004. doi: 10.1371/journal.pone.0015004.
- Guttmacher AE, Collins FS. Welcome to the genomic era. N Engl J Med. 2003 Sep 4;349(10):996-8. doi: 10.1056/NEJMe038132. No abstract available.
- Han X, Aslanian A, Yates JR 3rd. Mass spectrometry for proteomics. Curr Opin Chem Biol. 2008 Oct;12(5):483-90. doi: 10.1016/j.cbpa.2008.07.024.
- Hayden EC. Technology: The $1,000 genome. Nature. 2014 Mar 20;507(7492):294-5. doi: 10.1038/507294a. No abstract available.
- Lemaitre G, Marti R, Freixenet J, Vilanova JC, Walker PM, Meriaudeau F. Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: a review. Comput Biol Med. 2015 May;60:8-31. doi: 10.1016/j.compbiomed.2015.02.009. Epub 2015 Feb 20.
- Li J, Huang A, Yao J, Liu J, Van Uitert RL, Petrick N, Summers RM. Optimizing computer-aided colonic polyp detection for CT colonography by evolving the Pareto fronta. Med Phys. 2009 Jan;36(1):201-12. doi: 10.1118/1.3040177.
- Netto, G., & Kaul, K, e. (2019). Genomic Applications in Pathology. Springer International Publishing
- Onal S, Lai-Yuen S, Bao P, Weitzenfeld A, Hart S. Fully automated localization of multiple pelvic bone structures on MRI. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:3353-6. doi: 10.1109/EMBC.2014.6944341.
- Rosenberg S, Elashoff MR, Beineke P, Daniels SE, Wingrove JA, Tingley WG, Sager PT, Sehnert AJ, Yau M, Kraus WE, Newby LK, Schwartz RS, Voros S, Ellis SG, Tahirkheli N, Waksman R, McPherson J, Lansky A, Winn ME, Schork NJ, Topol EJ; PREDICT (Personalized Risk Evaluation and Diagnosis in the Coronary Tree) Investigators. Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients. Ann Intern Med. 2010 Oct 5;153(7):425-34. doi: 10.7326/0003-4819-153-7-201010050-00005.
- Scaria V. Personal genomes to precision medicine. Mol Cytogenet. 2014 Jan 21;7(Suppl 1 Proceedings of the International Conference on Human):I28. doi: 10.1186/1755-8166-7-S1-I28. eCollection 2014. No abstract available.
- Uppot, R.N., Boas, G., & Flores, E. (2018). Current Developments in Artificial Intelligence and Diagnostic Imaging
- Yang Q, Li L, Zhang J, Shao G, Zhang C, Zheng B. Computer-aided diagnosis of breast DCE-MRI images using bilateral asymmetry of contrast enhancement between two breasts. J Digit Imaging. 2014 Feb;27(1):152-60. doi: 10.1007/s10278-013-9617-4.
- Yet I, Menni C, Shin SY, Mangino M, Soranzo N, Adamski J, Suhre K, Spector TD, Kastenmuller G, Bell JT. Genetic Influences on Metabolite Levels: A Comparison across Metabolomic Platforms. PLoS One. 2016 Apr 13;11(4):e0153672. doi: 10.1371/journal.pone.0153672. eCollection 2016.
- Zhu B, Liu JZ, Cauley SF, Rosen BR, Rosen MS. Image reconstruction by domain-transform manifold learning. Nature. 2018 Mar 21;555(7697):487-492. doi: 10.1038/nature25988.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
- PLI001
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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