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Measuring molecular biomarkers in epidemiologic studies: laboratory techniques and biospecimen considerations
Author(s) -
Erickson Heidi S.
Publication year - 2012
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4485
Subject(s) - pooling , biomarker , computer science , biomarker discovery , throughput , computational biology , personalized medicine , population , sample (material) , bioinformatics , medicine , biology , proteomics , artificial intelligence , genetics , telecommunications , chemistry , environmental health , chromatography , gene , wireless
The future of personalized medicine depends on the ability to efficiently and rapidly elucidate a reliable set of disease‐specific molecular biomarkers. High‐throughput molecular biomarker analysis methods have been developed to identify disease risk, diagnostic, prognostic, and therapeutic targets in human clinical samples. Currently, high throughput screening allows us to analyze thousands of markers from one sample or one marker from thousands of samples and will eventually allow us to analyze thousands of markers from thousands of samples. Unfortunately, the inherent nature of current high throughput methodologies, clinical specimens, and cost of analysis is often prohibitive for extensive high throughput biomarker analysis. This review summarizes the current state of high throughput biomarker screening of clinical specimens applicable to genetic epidemiology and longitudinal population‐based studies with a focus on considerations related to biospecimens, laboratory techniques, and sample pooling. Copyright © 2012 John Wiley & Sons, Ltd.