Epidemiologic Design and Analysis for Proteomic Studies: A Primer on -Omic Technologies

Epidemiologic Design and Analysis for Proteomic Studies: A Primer on -Omic Technologies

1. Harald Mischak, 
2. Elena Critselis, 
3. Samir Hanash, 
4. William M. Gallagher, 
5. Antonia Vlahou and
6. John P. A. Ioannidis*

1. ↵*Correspondence to Dr. John P. A. Ioannidis, Stanford Prevention Research Center, Stanford University School of Medicine, Medical School Office Building, Room X306, 1265 Welch Road, Stanford, CA 94305 (e-mail: jioannid@stanford.edu).

1. Abbreviations: CE, capillary electrophoresis; LC, liquid chromatography; MS, mass spectrometry; MS/MS, tandem mass spectrometry; PRIORITY, Proteomic Prediction and Renin Angiotensin Aldosterone System Inhibition Prevention of Early Diabetic Nephropathy in Type 2 Diabetic Patients with Normoalbuminuria.

• Received August 25, 2014.
• Accepted December 15, 2014.

Abstract

Proteome analysis is increasingly being used in investigations elucidating the molecular basis of disease, identifying diagnostic and prognostic markers, and ultimately improving patient care. We appraised the current status of proteomic investigations using human samples, including the state of the art in proteomic technologies, from sample preparation to data evaluation approaches, as well as key epidemiologic, statistical, and translational issues. We systematically reviewed the most highly cited clinical proteomic studies published between January 2009 and March 2014 that included a minimum of 100 samples, as well as strategies that have been successfully implemented to enhance the translational relevance of proteomic investigations. Limited comparability between studies and lack of specification of biomarker context of use are frequently observed. Nevertheless, there are initial examples of successful biomarker discovery in cross-sectional studies followed by validation in high-risk longitudinal cohorts. Translational potential is currently hindered, as limitations in proteomic investigations are not accounted for. Interdisciplinary communication between proteomics experts, basic researchers, epidemiologists, and clinicians, an orchestrated assimilation of required resources, and a more systematic translational outlook for accumulation of evidence may augment the public health impact of proteomic investigations.

Key words

• biomarkers
 
• epidemiologic methods
 
• proteomics
 
• research design
• statistics
 
• translational medical research

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