The success of mass spectrometry (MS) in proteomics is mainly due to its specificity and sensitivity, which are attributable to advances in liquid chromatography coupled to tandem MS (LC-MS/MS) approaches, and the development of statistical tools that allow the useapplication of Big Data analysis strategies to extract meaningful biologicalthe obtained MS information obtained by MS-based methods. This type of technology can reveal proteome insights at the composition, structure, and function level. Proteomics tools make it possible to evaluate the proteins in complex biological samples qualitatively and quantitatively (either relative or absolute). Based on the meta-analysis results, the uThe upregulation of FCN3 and downregulation of APOA1, APOA2, APOC1, and APOC3 in schizophrenia (SCZ) patients is suggested. Despite the proven ability of MS proteomics to characterize SCZ, several confounding factors contribute to the heterogeneity of the findings.
To evaluate the efficacy of MS proteomics applied to human peripheral fluids to assess SCZ biomarkers and identify relevant networks of biological pathways, a systematic review (following PRISMA Guidelines) and meta-analysis were performed. To do so, a search for studies using MS proteomics to identify proteomic differences between SCZ patients and healthy controls was performed. Overall, nineteen articles fulfilled the inclusion criteria, allowing a total of total of 217 proteins to bwere identified as altered between SCZ and healthy control groups in peripheral fluids, including serum, plasma, PBMCs, sweat, and saliva.
Apolipoproteins (APOs) were the group of proteins mostly reported in SCZ vs. control studies as differentially expressed. In fact, ten studies reported the dysregulation of apolipoproteins [46][47][48][49][50][51][52][53][54][55]. APOs are very important in lipid homeostasis by transporting cholesterol and lipids between cells, having a well-established role in the transport and metabolism of lipids, and in inflammatory and immune response regulation [56][57]. This group of compounds has been indicated as potential candidates for psychiatric biomarkers, with several studies reporting altered levels of cholesterol and APOs in psychiatric disorders [57][58][59][92,93,94]. Accordingly, APOs alterations were associated with inflammatory response [49][54][55], immune system [46][53], lipid metabolism [49][53], cardiovascular system [48], retinoid transport [55], and cognitive decline and underlying morphological changes [50].
APOA1 is the major protein component of the HDL fraction in plasma. Together with APOA2, APOA4, APOC1, and APOD, APOA1 is recognized for regulating the plasma levels of free fatty acids, having an important role in HDL and triglyceride-rich lipoprotein metabolism in the reverse cholesterol transport pathway [60]. APOA1 is also reported as having pro-immune and anti-inflammatory potential [56]. In all selected studies where it was identified as altered, ApoA1 level was reported to be reduced in schizophrenia patients compared to healthy subjects [50][53][54][55].
APOA2, the second most abundant protein in HDL fraction, is a key regulator of HDL metabolism [60], although its inflammation role is not clearly defined, with different studies reporting it as having pro- and anti-inflammatory effects [61]. APOA2 was identified as differentially expressed in four studies, being downregulated in SCZ patients in all studies [49][50][53][54]. APOA4, a lipid-binding protein, is known to be involved in a broad spectrum of biological processes, including lipid metabolism, reverse cholesterol transport, atherosclerosis protection, and glucose hemostasis [62]. APOA4 was identified as differentially expressed in four studies; however, it showed a heterogeneous behavior: downregulated in three studies [49][50][54] and upregulated in only one study [51]. The apolipoproteins APOC1, APOC2, APOC3, APOD, and APOE were identified in three studies as differently expressed, showing a general tendency of downregulation in SCZ patients except for APOE, which has a trend for upregulation. Of these, only for APOD, a soluble carrier protein of lipophilic molecules that is mostly expressed in neurons and glial cells within the central and peripheral nervous system [63], the results were consistent in all three studies, and it was identified as decreased in SCZ patients [64][47][65]. A trend of downregulated behavior was identified for APOC1 (the smallest of all APOs, participating in lipid transport and metabolism) [49][54], APOC2 (a small exchangeable apolipoprotein found on triglyceride-rich lipoprotein particles) [51][54], and APOC3 (an APO capable of inhibiting lipoprotein lipase and hepatic lipase) [49][51], in two out of three studies. APOF [50][52], APOH [47][49], and APOL1 [50][52] had a similar behavior: upregulated in the two studies. For APOB, no clear trend was observed, with one study reporting its increase [48] and another a decrease [50] in SCZ patients. RET4 is mainly expressed in the liver with a primary function tof transporting retinol (vitamin A) from the liver to peripheral tissues, with retinol being essential for the brain to facilitate learning, memory, and cognition [66]. Retinoid signaling plays a vital role in immune cell function. Accordingly, it is suggested that factors that affect this system could have important implications for SCZ and other psychiatric disorders-associated inflammatory stress [67]. ANT3, a glycoprotein anticoagulant mainly produced in the liver that exerts anticoagulant and anti-inflammatory effects by targeting activated thrombin and other blood coagulation factors [68], was identified as being increased in SCZ patients [49][50][55]. FCN3 is a ficolin, a protein containing both a collagen-like domain and a fibrinogen-like domain with a specific binding affinity for N-acetylglucosamine. FCN3 can complex with mannose-associated serine proteases to activate the complement pathway [69], being ficolins’ activation already reported as a potential biomarker of the severity of schizophrenia [70]. In the selected studies, FCN3 was also identified in three studies as upregulated FC [49][50][71]. The immune system and inflammatory response were the most identified biological processes altered in SCZ patients [46][49][72][73][71][54][74]. These results agree with current knowledge about SCZ, associating the immune system and inflammatory response with the SCZ pathophysiology [75][76][77]. In fact, a wide range of immune alterations has been reported in SCZ patients, such as elevated levels of cytokines and inflammation markers, abnormalities of the blood-brain barrier, CNS inflammation, and increased autoantibody reactivity [76]. Several other mechanisms have also been linked to SCZ, including mitochondrial dysfunction, energy metabolism processes, complement and coagulation cascades, oxidative stress, transport, morphological changes, cognitive impairment, lipid metabolism, and hypothalamic–pituitary–adrenal (HPA) axis over-activation [77][78].The recent advances in MS proteomics strategies applied to human peripheral fluids allow the establishment of a robust platform for proteome profiling of clinical samples with an unprecedented depth. In fact, the MS's ability to generate different levels of information about the individual proteome may lead to the comprehensive characterization of the biological network of pathways involved in SCZ, seeking the identification of reliable biomarkers of the disorder to improve prediction and diagnosis towards the ultimate goal of improving patient care and outcome.
However, a standardization of the studies’ characteristics is required for more specific clinical proteomics studies. In fact, a precise definition of the study’s objectives and standardization of sociodemographic, clinical, and cognitive variables across the studied groups would make them more objective and specific, allowing a more comprehensive understanding of SCZ pathophysiology and increasing the possibility of identifying specific biomarkers of SCZ. This will minimize the confounding factors, leading to improvements in the statistical power and, consequently, the efficiency of translating biomarker candidates and drug targets to the clinical application associated with the disorder.
The use of MS proteomics pipelines combining (i) standardized conditions; (ii) high-throughput sample preparation techniques; (iii) high computational power for data processing and analysis will lead to a rapid expansion of clinical cohort sizes and consequently to more robust studies. An extra effort should be made to provide data in an open format so the community can re-analyze and perform more extensive studies based on data analysis from multiple centers. After full implementation of those proteomics pipelines, their application in extended clinical cohorts will allow taking into account the different variables (such as gender, comorbidities, illness duration, and treatment), leading to a more comprehensive understanding of SCZ pathophysiology and, consequently, increasing the possibility of identifying specific biomarkers of SCZ, seeking to improve prediction and diagnosis towards the ultimate goal of improving patient care and outcome.