Protein and peptide profiling as a tool for biomarker discovery in depression

Abstract

This study sought to determine whether protein and/or peptide profiles from serum were able to distinguish patients suffering from depression from healthy control subjects and thereby act as biomarker candidates with potential diagnostic value. Serum samples were collected from patients (n = 39) and controls (n = 30). A C8 magnetic bead protocol was used to prepare serum proteins, while a microextraction C18 packed tip was used to isolate serum peptides. Both protein and peptide profiles were recorded by MALDI-MS and the data were exported for further analysis. No protein signals differentiated patients from controls and principle component analysis of the entire peptide profile did not allow for distinct clustering of the two groups. Further analysis of individual peptides however identified three peptide signals whose intensities were significantly different between patients and control subjects. The efficacy of these potential biomarker candidates to identify the patients was therefore studied using a receiver operating characteristic (ROC) curve and the combined use of all three candidates together offered the most specific and sensitive identification of true positive cases of depression.

Proteomics for blood biomarker exploration of severe mental illness: pitfalls of the past and potential for the future

“…Of the articles found, 13 were studies on SZ 34 – 42 , 44 – 46 , 60 , 6 on MDD 18 , 47 – 51 , and 5 on BD-I/-II 52 – 56 patients, whereas the remaining studies < 57 – 59 , 61 – 62 , 43 included a combination of patients of the relevant diagnoses. All studies presented information on up- and down-regulated proteins (see S1 ).…”

“…Differences in patient populations and selection criteria also confounded inter-study comparisons. Moreover, multiple studies 39 , 41 ,42 , 45 – 47 failed to disclose whether critical confounders, such as diet and smoking, were considered. As blood is a highly dynamic tissue, in contact with nearly every tissue of the body, it reflects a number of external factors that need to be controlled for 13 .…”

Peripheral Biomarkers for Depression by Plasma and Serum Proteomics

“…Another recent application of MALDI-MSbased protein/peptide profiling in the analysis of serum samples from depressed patients led to the identification of three peptide signals of unidentified origin that differ significantly between cases and controls [30]. Although principal component analysis of the entire peptide profile did not allow for distinct clustering of the two groups, a receiver operating characteristic curve built with the combined use of all three candidates resulted in a sensitivity and a specificity of 100 and 86.7%, respectively.…”

Biomarkers Discovery through Multivariate Statistical Methods: A Review of Recently Developed Methods and Applications in Proteomics

“…However, the majority of applications is in the field of clinical biomarker discovery to investigate (Table 2): a) coronary syndromes [82]; b) the influence of clotting time on the protein composition of serum samples [45]; c) acute myocardial infarction [4] d) inflamed and non-inflamed colon biopsies [5] in ulcerative colitis depression [25]; e) non-small cell lung cancer [3,9]; f) whether a high intake of industrial or ruminant trans fatty acids affects the plasma proteome [8]; g) amphetamine in rats [26]; h) thyroid proliferative diseases [34]; i) idiopathic pneumonia syndrome following allogeneic stem cell transplantation [83]; j) the effect of Trichostatin A on pancreatic ductal carcinoma cells [20]; the development of a special class of aptamers [84], called SOMAmers (slow off-rate modified aptamers), which bind specifically to proteins in body fluids.…”

“…In general, we can speak of biomarkers identification whenever a pool of features differentiating two or more groups of samples has to be identified. For what concerns the particular application to proteomics, the search for biomarkers involves the identification of features responsible for sample differentiation from a quite wide range of instrumental applications: from classical proteomics , exploiting 2D-PAGE and 2D-DIGE, to mass spectrometry-based approaches based on MALDI-TOF [24][25][26][27][28][29][30] and SELDI-TOF profiling [31][32][33][34][35][36][37][38][39][40][41][42], HPLC-MS [43][44][45][46][47][48][49][50][51][52][53][54][55][56][57] or shotgun approaches [58][59].…”