Jemmyson Romário de Jesus1, Rodrigo Moretto Galazzi1, Tatiani Brenelli de Lima2, Cláudio Eduardo Muller Banzato3, Luiz Fernando de Almeida Lima E Silva3, Clarissa de Rosalmeida Dantas3, Fábio Cézar Gozzo2, Marco Aurélio Zezzi Arruda4. 1. Spectrometry, Sample Preparation and Mechanization Group - GEPAM, Institute of Chemistry, University of Campinas - UNICAMP, Campinas, Brazil; National Institute of Science and Technology for Bioanalytics, Institute of Chemistry, University of Campinas - UNICAMP, Campinas, Brazil. 2. Dalton Mass Spectrometry Group, Institute of Chemistry, University of Campinas - UNICAMP, Campinas, Brazil. 3. Department of Psychiatry, Faculty of Medical Sciences, University of Campinas - UNICAMP, Campinas, Brazil. 4. Spectrometry, Sample Preparation and Mechanization Group - GEPAM, Institute of Chemistry, University of Campinas - UNICAMP, Campinas, Brazil; National Institute of Science and Technology for Bioanalytics, Institute of Chemistry, University of Campinas - UNICAMP, Campinas, Brazil. Electronic address: zezzi@iqm.unicamp.br.
Abstract
PURPOSE: An exploratory analysis using proteomic strategies in blood serum of patients with bipolar disorder (BD), and with other psychiatric conditions such as Schizophrenia (SCZ), can provide a better understanding of this disorder, as well as their discrimination based on their proteomic profile. METHODS: The proteomic profile of blood serum samples obtained from patients with BD using lithium or other drugs (N=14), healthy controls, including non-family (HCNF; N=3) and family (HCF; N=9), patients with schizophrenia (SCZ; N=23), and patients using lithium for other psychiatric conditions (OD; N=4) were compared. Four methods for simplifying the serum samples proteome were evaluated for both removing the most abundant proteins and for enriching those of lower-abundance: protein depletion with acetonitrile (ACN), dithiothreitol (DTT), sequential depletion using DTT and ACN, and protein equalization using commercial ProteoMiner® kit (PM). For proteomic evaluation, 2-D DIGE and nanoLC-MS/MS analysis were employed. RESULTS: PM method was the best strategy for removing proteins of high abundance. Through 2-D DIGE gel image comparison, 37 protein spots were found differentially abundant (p<0.05, Student's t-test), which exhibited ≥2.0-fold change of the average value of normalized spot intensities in the serum of SCZ, BD and OD patients compared to subject controls (HCF and HCNF). From these spots detected, 13 different proteins were identified: ApoA1, ApoE, ApoC3, ApoA4, Samp, SerpinA1, TTR, IgK, Alb, VTN, TR, C4A and C4B. CONCLUSIONS: Proteomic analysis allowed the discrimination of patients with BD from patients with other mental disorders, such as SCZ. The findings in this exploratory study may also contribute for better understanding the pathophysiology of these disorders and finding potential serum biomarkers for these conditions.
PURPOSE: An exploratory analysis using proteomic strategies in blood serum of patients with bipolar disorder (BD), and with other psychiatric conditions such as Schizophrenia (SCZ), can provide a better understanding of this disorder, as well as their discrimination based on their proteomic profile. METHODS: The proteomic profile of blood serum samples obtained from patients with BD using lithium or other drugs (N=14), healthy controls, including non-family (HCNF; N=3) and family (HCF; N=9), patients with schizophrenia (SCZ; N=23), and patients using lithium for other psychiatric conditions (OD; N=4) were compared. Four methods for simplifying the serum samples proteome were evaluated for both removing the most abundant proteins and for enriching those of lower-abundance: protein depletion with acetonitrile (ACN), dithiothreitol (DTT), sequential depletion using DTT and ACN, and protein equalization using commercial ProteoMiner® kit (PM). For proteomic evaluation, 2-D DIGE and nanoLC-MS/MS analysis were employed. RESULTS: PM method was the best strategy for removing proteins of high abundance. Through 2-D DIGE gel image comparison, 37 protein spots were found differentially abundant (p<0.05, Student's t-test), which exhibited ≥2.0-fold change of the average value of normalized spot intensities in the serum of SCZ, BD and OD patients compared to subject controls (HCF and HCNF). From these spots detected, 13 different proteins were identified: ApoA1, ApoE, ApoC3, ApoA4, Samp, SerpinA1, TTR, IgK, Alb, VTN, TR, C4A and C4B. CONCLUSIONS: Proteomic analysis allowed the discrimination of patients with BD from patients with other mental disorders, such as SCZ. The findings in this exploratory study may also contribute for better understanding the pathophysiology of these disorders and finding potential serum biomarkers for these conditions.
Authors: João E Rodrigues; Ana Martinho; Catia Santa; Nuno Madeira; Manuel Coroa; Vítor Santos; Maria J Martins; Carlos N Pato; Antonio Macedo; Bruno Manadas Journal: Int J Mol Sci Date: 2022-04-28 Impact factor: 6.208
Authors: Joao E Rodrigues; Ana Martinho; Vítor Santos; Catia Santa; Nuno Madeira; Maria J Martins; Carlos N Pato; Antonio Macedo; Bruno Manadas Journal: Int J Mol Sci Date: 2022-05-13 Impact factor: 6.208