Literature DB >> 25739849

Cross-Disciplinary Biomarkers Research: Lessons Learned by the CKD Biomarkers Consortium.

Chi-Yuan Hsu1, Shawn Ballard2, Daniel Batlle3, Joseph V Bonventre4, Erwin P Böttinger5, Harold I Feldman2, Jon B Klein6, Josef Coresh7, John H Eckfeldt8, Lesley A Inker9, Paul L Kimmel10, John W Kusek10, Kathleen D Liu1, Michael Mauer8, Theodore E Mifflin2, Mark E Molitch3, Gary L Nelsestuen8, Casey M Rebholz7, Brad H Rovin11, Venkata S Sabbisetti4, Jennifer E Van Eyk12, Ramachandran S Vasan13, Sushrut S Waikar4, Krista M Whitehead2, Robert G Nelson14.   

Abstract

Significant advances are needed to improve the diagnosis, prognosis, and management of persons with CKD. Discovery of new biomarkers and improvements in currently available biomarkers for CKD hold great promise to achieve these necessary advances. Interest in identification and evaluation of biomarkers for CKD has increased substantially over the past decade. In 2009, the National Institute of Diabetes and Digestive and Kidney Diseases established the CKD Biomarkers Consortium (http://www.ckdbiomarkersconsortium.org/), a multidisciplinary, collaborative study group located at over a dozen academic medical centers. The main objective of the consortium was to evaluate new biomarkers for purposes related to CKD in established prospective cohorts, including those enriched for CKD. During the first 5 years of the consortium, many insights into collaborative biomarker research were gained that may be useful to other investigators involved in biomarkers research. These lessons learned are outlined in this Special Feature and include a wide range of issues related to biospecimen collection, storage, and retrieval, and the internal and external quality assessment of laboratories that performed the assays. The authors propose that investigations involving biomarker discovery and validation are greatly enhanced by establishing and following explicit quality control metrics, including the use of blind replicate and proficiency samples, by carefully considering the conditions under which specimens are collected, handled, and stored, and by conducting pilot and feasibility studies when there are concerns about the condition of the specimens or the accuracy or reproducibility of the assays.
Copyright © 2015 by the American Society of Nephrology.

Entities:  

Keywords:  CKD; biomarkers; epidemiology; outcomes; quality control; risk factors

Mesh:

Substances:

Year:  2015        PMID: 25739849      PMCID: PMC4422251          DOI: 10.2215/CJN.11541114

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN: 1555-9041            Impact factor:   8.237


  4 in total

Review 1.  Biomarkers and surrogate endpoints: preferred definitions and conceptual framework.

Authors: 
Journal:  Clin Pharmacol Ther       Date:  2001-03       Impact factor: 6.875

2.  Decreases in albumin/creatinine and N-acetylglucosaminidase/creatinine ratios in urine samples stored at -20 degrees C.

Authors:  S E Manley; M E Burton; K E Fisher; C A Cull; R C Turner
Journal:  Clin Chem       Date:  1992-11       Impact factor: 8.327

3.  Freezing method affects the concentration and variability of urine proteins and the interpretation of data on microalbuminuria. The Oxford Regional Prospective Study Group.

Authors:  C J Schultz; R N Dalton; C Turner; H A Neil; D B Dunger
Journal:  Diabet Med       Date:  2000-01       Impact factor: 4.359

4.  Reliability of urinary albumin, total protein, and creatinine assays after prolonged storage: the Family Investigation of Nephropathy and Diabetes.

Authors:  Rulan S Parekh; W H Linda Kao; Lucy A Meoni; Eli Ipp; Paul L Kimmel; Janine La Page; Carol Fondran; William C Knowler; Michael J Klag
Journal:  Clin J Am Soc Nephrol       Date:  2007-10-10       Impact factor: 8.237

  4 in total
  12 in total

1.  Relationship of proximal tubular injury to chronic kidney disease as assessed by urinary kidney injury molecule-1 in five cohort studies.

Authors:  Sushrut S Waikar; Venkata Sabbisetti; Johan Ärnlöv; Axel C Carlsson; Josef Coresh; Harold I Feldman; Meredith C Foster; Gudeta D Fufaa; Johanna Helmersson-Karlqvist; Chi-Yuan Hsu; Paul L Kimmel; Anders Larsson; Yumin Liu; Lars Lind; Kathleen D Liu; Theodore E Mifflin; Robert G Nelson; Ulf Risérus; Ramachandran S Vasan; Dawei Xie; Xiaoming Zhang; Joseph V Bonventre
Journal:  Nephrol Dial Transplant       Date:  2016-06-07       Impact factor: 5.992

2.  The power of proteomics to monitor senescence-associated secretory phenotypes and beyond: toward clinical applications.

Authors:  Nathan Basisty; Abhijit Kale; Sandip Patel; Judith Campisi; Birgit Schilling
Journal:  Expert Rev Proteomics       Date:  2020-05-19       Impact factor: 3.940

3.  The Urine Preservative Acetic Acid Degrades Urine Protein: Implications for Urine Biorepositories and the AASK Cohort Study.

Authors:  Salem Almaani; Lee A Hebert; Brad H Rovin; Daniel J Birmingham
Journal:  J Am Soc Nephrol       Date:  2017-01-19       Impact factor: 10.121

4.  Urine RAS components in mice and people with type 1 diabetes and chronic kidney disease.

Authors:  Jan Wysocki; Anne Goodling; Mar Burgaya; Kathryn Whitlock; John Ruzinski; Daniel Batlle; Maryam Afkarian
Journal:  Am J Physiol Renal Physiol       Date:  2017-05-03

5.  Urine Kidney Injury Biomarkers and Risks of Cardiovascular Disease Events and All-Cause Death: The CRIC Study.

Authors:  Meyeon Park; Chi-Yuan Hsu; Alan S Go; Harold I Feldman; Dawei Xie; Xiaoming Zhang; Theodore Mifflin; Sushrut S Waikar; Venkata S Sabbisetti; Joseph V Bonventre; Josef Coresh; Robert G Nelson; Paul L Kimmel; John W Kusek; Mahboob Rahman; Jeffrey R Schelling; Ramachandran S Vasan; Kathleen D Liu
Journal:  Clin J Am Soc Nephrol       Date:  2017-03-02       Impact factor: 8.237

6.  Urine biomarkers of tubular injury do not improve on the clinical model predicting chronic kidney disease progression.

Authors:  Chi-Yuan Hsu; Dawei Xie; Sushrut S Waikar; Joseph V Bonventre; Xiaoming Zhang; Venkata Sabbisetti; Theodore E Mifflin; Josef Coresh; Clarissa J Diamantidis; Jiang He; Claudia M Lora; Edgar R Miller; Robert G Nelson; Akinlolu O Ojo; Mahboob Rahman; Jeffrey R Schelling; Francis P Wilson; Paul L Kimmel; Harold I Feldman; Ramachandran S Vasan; Kathleen D Liu
Journal:  Kidney Int       Date:  2016-10-28       Impact factor: 10.612

Review 7.  Lessons Learned from EVOLVE for Planning of Future Randomized Trials in Patients on Dialysis.

Authors:  Patrick S Parfrey; Geoffrey A Block; Ricardo Correa-Rotter; Tilman B Drüeke; Jürgen Floege; Charles A Herzog; Gerard M London; Kenneth W Mahaffey; Sharon M Moe; David C Wheeler; Glenn M Chertow
Journal:  Clin J Am Soc Nephrol       Date:  2015-11-27       Impact factor: 8.237

8.  Kidney Biomarkers and Decline in eGFR in Patients with Type 2 Diabetes.

Authors:  Katherine G Garlo; William B White; George L Bakris; Faiez Zannad; Craig A Wilson; Stuart Kupfer; Muthiah Vaduganathan; David A Morrow; Christopher P Cannon; David M Charytan
Journal:  Clin J Am Soc Nephrol       Date:  2018-01-16       Impact factor: 8.237

Review 9.  The Extracellular RNA Communication Consortium: Establishing Foundational Knowledge and Technologies for Extracellular RNA Research.

Authors:  Saumya Das; K Mark Ansel; Markus Bitzer; Xandra O Breakefield; Alain Charest; David J Galas; Mark B Gerstein; Mihir Gupta; Aleksandar Milosavljevic; Michael T McManus; Tushar Patel; Robert L Raffai; Joel Rozowsky; Matthew E Roth; Julie A Saugstad; Kendall Van Keuren-Jensen; Alissa M Weaver; Louise C Laurent
Journal:  Cell       Date:  2019-04-04       Impact factor: 66.850

10.  Variability of Two Metabolomic Platforms in CKD.

Authors:  Eugene P Rhee; Sushrut S Waikar; Casey M Rebholz; Zihe Zheng; Regis Perichon; Clary B Clish; Anne M Evans; Julian Avila; Michelle R Denburg; Amanda Hyre Anderson; Ramachandran S Vasan; Harold I Feldman; Paul L Kimmel; Josef Coresh
Journal:  Clin J Am Soc Nephrol       Date:  2018-12-20       Impact factor: 10.614

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