Biomarkers

Introduction – Why do we need ‘biomarkers? Biomarkers of protein oxidation Introduction Major issues/questions Protein carbonyl biomarkers Biochemistry Methods of measurement Storage, stability and limitations in use Protein thiol biomarkers Biochemistry Methods of measurement Storage, stability and limitations on use Aliphatic amino acid biomarkers Biochemistry Methods of measurement Storage, stability and limitations on use Oxidised Tryptophan Biomarkers Biochemistry Method of measurement Storage, stability and limitations on use Oxidised tyrosine biomarkers Biochemistry Methods of measurement Storage, stability and limitations on use Formation of neoepitopes on oxidised proteins Validation of assays for protein oxidation biomarkers Relationship of protein oxidation to disease Modulation of protein oxidation biomarkers by antioxidants Future perspectives Introduction to lipid peroxidation biomarkers Introduction: biochemistry of lipid peroxidation Malondialdehyde Methods of measurement Storage, stability and limitations on use Conjugated dienes Method of measurement Storage, stability and limitations of use LDL lag phase Method of measurement Storage, stability and limitations of use Hydrocarbon gases Biochemistry Method of measurement Storage, stability and limitations on use Lipofuscin Biochemistry Method of measurement Storage, stability and limitation on use Lipid peroxides Biochemistry Method of measurement Storage, stability and limitations on use Isoprostanes Biochemistry Method of measurement Storage, stability and limitations on use Possible new biomarkers of lipid oxidation Relationship of lipid peroxidation to disease Modulation of lipid peroxidation biomarkers by antioxidants Functional consequences of lipid peroxidation Contribution of dietary intake to lipid peroxidation products Biomarkers of DNA oxidation Introduction Confounding factors Units and terminology Nuclear and mitochondrial DNA damage Lymphocytes as surrogate tissues Measurement of DNA damage with the comet assay Practical details Storage, stability, and limitations of the assay Measurement of DNA base oxidation by HPLC Practical details Storage, stability and limitations of the method Measurement of DNA base oxidation by GC–MS Biochemistry of 8-oxoguanine, adenine and fapy derivatives Methods of measurement Storage, stability and limitations of the method Analysis of guanine oxidation products in urine Method of measurement Limitations and criticisms Immunochemical methods Methods of measurement Storage, stability, and limitations of the assay 32P post-labelling Method of measurement Limitations and criticisms Validation of assays for DNA oxidation Oxo-dGuo in lymphocyte DNA Urinary measurements DNA–aldehyde adducts Biochemistry Method of measurement Products of reactive nitrogen species Endpoints arising from oxidative DNA damage Mutations Chromosome aberrations Micronuclei Site-specific DNA damage Relationship of DNA oxidation to disease Modulation of DNA oxidation biomarkers by antioxidants Direct and indirect effects of oxidative stress: measures of total oxidant/antioxidant levels Visualisation of cellular oxidants Biochemistry: histochemical detection of ROS Method of measurement Limitations, storage and stability Measurement of hydrogen peroxide Biochemistry Methods of measurement Storage, stability and limitations on use Measurement of the ratio of antioxidant/oxidised antioxidant Biochemistry Method of measurement Storage, stability and limitations on use Total antioxidant capacity Biochemistry Terminology Methods of measurement Storage, stability and limitations on use Validation of assays for direct oxidant and antioxidant biomarkers Relationship of oxidant/antioxidant measurement to disease Modulation of oxidant/antioxidant biomarkers by dietary antioxidants Induction of genes in response to oxidative stress Background Measurement of antioxidant responsive genes and proteins Effects of antioxidant intake on the activity of antioxidant enzymes

Urinary proteomic biomarkers in coronary artery disease

Urinary proteomics is emerging as a powerful non-invasive tool for diagnosis and monitoring of variety of human diseases. We tested whether signatures of urinary polypeptides can contribute to the existing biomarkers for coronary artery disease (CAD). We examined a total of 359 urine samples from 88 patients with severe CAD and 282 controls. Spot urine was analyzed using capillary electrophoresis on-line coupled to ESI-TOF-MS enabling characterization of more than 1000 polypeptides per sample. In a first step a "training set" for biomarker definition was created. Multiple biomarker patterns clearly distinguished healthy controls from CAD patients, and we extracted 15 peptides that define a characteristic CAD signature panel. In a second step, the ability of the CAD-specific panel to predict the presence of CAD was evaluated in a blinded study using a "test set." The signature panel showed sensitivity of 98% (95% confidence interval, 88.7-99.6) and 83% specificity (95% confidence interval, 51.6-97.4). Furthermore the peptide pattern significantly changed toward the healthy signature correlating with the level of physical activity after therapeutic intervention. Our results show that urinary proteomics can identify CAD patients with high confidence and might also play a role in monitoring the effects of therapeutic interventions. The workflow is amenable to clinical routine testing suggesting that non-invasive proteomics analysis can become a valuable addition to other biomarkers used in cardiovascular risk assessment.

Discovering biomarkers for antidepressant response:protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. Trial registration: ClinicalTrials.gov identifier NCT01655706. Registered July 27, 2012.