Cedars-sinai Medical Center

Johns Hopkins University

Abbott Laboratories Corporation

Vidya Venkatraman

Jennifer E Van Eyk

Qin Fu

Saul A Datwyler

Beth McQuiston

Raj Chandran

Zongming Fu

Eric Grote

Shenyan Zhang

Josef Coresh

Described herein are methods for identification/discovery of protein biomarkers for chronic kidney disease (CKD) and diagnosing and/or prognosing and/or predicting progression of and/or treating chronic kidney disease (CKD).

Prognosis and progression biomarkers for chronic kidney disease

The present disclosure relates to methods for diagnosing and evaluating a subject that has sustained or may have sustained an injury to the head, such as a traumatic brain injury (TBI). In particular, the present disclosure identifies various biomarkers, the detection and/or differential expression of which can be used to assess the presence or absence of a TBI in a subject, and can be used as a basis for diagnosing a subject as having a specific type of TBI (e.g., severe TBI or subclasses of mild TBI). The various TBI biomarkers can be detected individually or in combination and can be used as an important diagnostic, prognostic, and/or TBI risk stratification tool as part of assessing a subject's TBI status.

Biomarkers and methods for diagnosing and evaluating traumatic brain injury

The present invention relates to the field of myocardial injury. More specifically, the present invention provides methods and compositions useful in the diagnosis, prognosis and/or assessment of myocardial injury. In a specific embodiment, a method comprises the steps of (a) diagnosing a subject as having myocardial injury based on the statistically significant over expression of one or more markers described herein compared to a baseline value, wherein the markers are measured in a biological sample obtained from the subject; and (b) treating the subject with one or more of an anti-thrombolysis agent, coronary bypass surgery or angioplasty.

Biomarkers of myocardial injury

Described herein are methods for identifying signature peptides for quantifying a polypeptide of interest in a sample. The methods include cleaving the polypeptide into peptides; detecting a multiplicity of the peptides with a quantitative analytical instrument; comparing the linearity of signals attributable to pairs of the peptides in a multiplicity of samples; and selecting signature peptides from a group of peptides with more highly correlated signals.

Correlated peptides for quantitative mass spectrometry

Growing community of inventors

Los Angeles, CA, United States of America

Vidya Venkatraman