Bot M, Chan M, Jansen R, Lamers F, Vogelzangs N, Steiner J, et al. Serum proteomic profiling of major depressive disorder. Transl Psychiatry. 2015;5:e599.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Young JJ, Silber T, Bruno D, Galatzer-Levy IR, Pomara N, Marmar CR. Is there Progress? An Overview of Selecting Biomarker Candidates for Major Depressive Disorder. Front Psychiatry. 2016;7:72.

Article  PubMed  PubMed Central  Google Scholar 

Jeffrey M Lyness. Unipolar depression in adults: Assessment and diagnosis - UpToDate. Unipolar depression in adults: Assessment and diagnosis - UpToDate. 2021 [cited 2021 Oct 21]. Available from: https://www.uptodate.com/contents/unipolar-depression-in-adults-assessment-and-diagnosis

Mendez-David I, Boursier C, Domergue V, Colle R, Falissard B, Corruble E, et al. Differential Peripheral Proteomic Biosignature of Fluoxetine Response in a Mouse Model of Anxiety/Depression. Front Cell Neurosci. 2017;11:1–16.

Article  Google Scholar 

Xu HB, Zhang RF, Luo D, Zhou Y, Wang Y, Fang L, et al. Comparative proteomic analysis of plasma from major depressive patients: identification of proteins associated with lipid metabolism and immunoregulation. Int J Neuropsychopharmacol. 2012;15:1413–25.

Article  PubMed  CAS  Google Scholar 

Sajic T, Liu Y, Aebersold R. Using data-independent, high-resolution mass spectrometry in protein biomarker research: Perspectives and clinical applications. Proteomics Clin Appl. 2015;9:307–21.

Article  PubMed  CAS  Google Scholar 

Strawbridge R, Young AH, Cleare AJ. Biomarkers for depression: Recent insights, current challenges and future prospects. Neuropsychiatr Dis Treat. 2017;13:1245–62.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Song X, Liu Y, Pu J, Gui S, Zhong X, Chen X, Chen W, Chen X, Chen Y, Wang H, Cheng K, Zhao L, Xie P. Transcriptomics Analysis Reveals Shared Pathways in Peripheral Blood Mononuclear Cells and Brain Tissues of Patients With Schizophrenia. Front Psychiatry. 2021;22(12):716722. https://doi.org/10.3389/fpsyt.2021.716722.PMID:34630179;PMCID:PMC8492981.

Article  Google Scholar 

McAlister GC, Nusinow DP, Jedrychowski MP, Wühr M, Huttlin EL, Erickson BK, et al. MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal Cheml. 2014;86:7150–8.

Article  CAS  Google Scholar 

Eng JK, McCormack AL, Yates JR. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectrom. 1994;5:976–89.

Article  PubMed  CAS  Google Scholar 

Consortium TU, Bateman A, Martin M-J, Orchard S, Magrane M, Agivetova R, et al. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 2021 [cited 2021 Oct 20];49:D480–9. Available from: https://academic.oup.com/nar/article/49/D1/D480/6006196

L K, JD C, J W, WS N, MJ M. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat Methods. 2007 [cited 2021 Oct 20];4:923–5. Available from: https://pubmed.ncbi.nlm.nih.gov/17952086/

Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS [Internet]. 2012 [cited 2021 Nov 16];16:284–7. Available from: https://pubmed.ncbi.nlm.nih.gov/22455463/

Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet [Internet]. 2000 [cited 2021 Nov 16];25:25–9. Available from: https://pubmed.ncbi.nlm.nih.gov/10802651/

Piñero J, Saüch J, Sanz F, Furlong LI. The DisGeNET cytoscape app: Exploring and visualizing disease genomics data. Comput Struct Biotechnol J. 2021;19:2960–7.

Article  PubMed  PubMed Central  Google Scholar 

Livak K, Schmittgen T. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001 [cited 2021 Oct 20];25:402–8. Available from: https://pubmed.ncbi.nlm.nih.gov/11846609/

Huang Z, Ung T. Effect of Alpha-1-Acid Glycoprotein Binding on Pharmacokinetics and Pharmacodynamics. Curr Drug Metab. 2013;14:226–38.

PubMed  CAS  Google Scholar 

Sluzewska A, Rybakowski J, Bosmans E, Sobieska M, Berghmans R, Maes M, et al. Indicators of immune activation in major depression. Psychiatry Res. 1996;64:161–7. Available from: https://pubmed.ncbi.nlm.nih.gov/8944394/

Healy D, Calvin J, Whitehouse AM, White W, Wilton-Cox H, Theodorou AE, et al. Alpha-1-acid glycoprotein in major depressive and eating disorders. J Affect Disord. 1991;22:13–20. Available from: https://pubmed.ncbi.nlm.nih.gov/1652602/

Adeoye OM, Ferrell RE, Kirshner MA, Mulsant BH, Seligman K, Begley AE, et al. alpha1-acid glycoprotein in late-life depression: relationship to medical burden and genetics. J Geriatr Psychiatry Neurol. 2003;16:235–9. Available from: https://pubmed.ncbi.nlm.nih.gov/14653433/

Beasley CL, Pennington K, Behan A, Wait R, Dunn MJ, Cotter D. Proteomic analysis of the anterior cingulate cortex in the major psychiatric disorders: Evidence for disease-associated changes. Proteomics. 2006;6:3414–25. Available from: https://pubmed.ncbi.nlm.nih.gov/16637010/

Johnston-Wilson NL, Sims CD, Hofmann JP, Anderson L, Shore AD, Torrey EF, et al. Disease-specific alterations in frontal cortex brain proteins in schizophrenia, bipolar disorder, and major depressive disorder. Molecular Psychiatry 2000 5:2. 2000;5:142–9. Available from: https://www.nature.com/articles/4000696

Ren J, Zhao G, Sun X, Liu H, Jiang P, Chen J, et al. Identification of plasma biomarkers for distinguishing bipolar depression from major depressive disorder by iTRAQ-coupled LC-MS/MS and bioinformatics analysis. Psychoneuroendocrinology. 2017;86:17–24. Available from: https://pubmed.ncbi.nlm.nih.gov/28910601/

Wirtz PH, Hong S, Redwine LS, Tafur J, Rutledge T, Ziegler MG, et al. Depressive Symptoms Are Associated with Soluble P-Selectin Reactivity to Acute Exercise in Heart Failure. Biol Psychiatry. 2009;65:801–7.

Article  PubMed  CAS  Google Scholar 

Eyre HA, Eskin A, Nelson SF, St Cyr NM, Siddarth P, Baune BT, et al. Genomic predictors of remission to antidepressant treatment in geriatric depression using genome-wide expression analyses: a pilot study. Int J Geriatr Psychiatry. 2016;31:510–7. Available from: https://pubmed.ncbi.nlm.nih.gov/26471432/

Henningsen K, Palmfeldt J, Christiansen S, Baiges I, Bak S, Jensen ON, et al. Candidate hippocampal biomarkers of susceptibility and resilience to stress in a rat model of depression. Mol Cell Proteomics. 2012;11. Available from: https://pubmed.ncbi.nlm.nih.gov/22311638/

Rotter A, Lenz B, Pitsch R, Richter-Schmidinger T, Kornhuber J, Rhein C. Alpha-Synuclein RNA Expression is Increased in Major Depression. Int J Mol Sci. 2019;20. Available from: https://pubmed.ncbi.nlm.nih.gov/31027150/

Shibata T, Yamagata H, Uchida S, Otsuki K, Hobara T, Higuchi F, et al. The alteration of hypoxia inducible factor-1 (HIF-1) and its target genes in mood disorder patients. Prog Neuropsychopharmacol Biol Psychiatry. 2013;43:222–9. Available from: https://pubmed.ncbi.nlm.nih.gov/23333658/

Piletz JE, Zhu H, Madakasira S, Pazzaglia P, Lindsay DeVane C, Goldman N, et al. Elevated P-selectin on platelets in depression: response to bupropion. J Psychiatr Res. 2000;34:397–404. Available from: https://pubmed.ncbi.nlm.nih.gov/11165307/

Aschbacher K, Mills PJ, Känel R von, Hong S, Mausbach BT, Roepke SK, et al. Effects of depressive and anxious symptoms on norepinephrine and platelet P-selectin responses to acute psychological stress among elderly caregivers. Brain Behav Immun. 2008;22:493–502. Available from: https://pubmed.ncbi.nlm.nih.gov/18054198/

Hennings JM, Uhr M, Klengel T, Weber P, Pütz B, Touma C, et al. RNA expression profiling in depressed patients suggests retinoid-related orphan receptor alpha as a biomarker for antidepressant response. Transl Psychiatry. 2015;5. Available from: https://pubmed.ncbi.nlm.nih.gov/25826113/

Lee SA, Tsao TT, Yang KC, Lin H, Kuo YL, Hsu CH, et al. Construction and analysis of the protein-protein interaction networks for schizophrenia, bipolar disorder, and major depression. BMC Bioinformatics. 2011;12:1–15. Available from: https://bmcbioinformatics.biomedcentral.com/articles/https://doi.org/10.1186/1471-2105-12-S13-S20

Pettai K, Milani L, Tammiste A, Võsa U, Kolde R, Eller T, et al. Whole-genome expression analysis reveals genes associated with treatment response to escitalopram in major depression. Eur Neuropsychopharmacol. 2016;26:1475–83.

Article  PubMed  CAS  Google Scholar 

Luo X, Fang Z, Lin L, Xu H, Huang Q, Zhang H. Plasma complement C3 and C3a are increased in major depressive disorder independent of childhood trauma. BMC Psychiatry. 2022;22. Available from: https://pubmed.ncbi.nlm.nih.gov/36447174/

Ishii T, Hattori K, Miyakawa T, Watanabe K, Hidese S, Sasayama D, et al. Increased cerebrospinal fluid complement C5 levels in major depressive disorder and schizophrenia. Biochem Biophys Res Commun. 2018;497:683–8. Available from: https://pubmed.ncbi.nlm.nih.gov/29454970/

Wei J, Liu Y, Zhao L, Yang X, Ni P, Wang Y, et al. Plasma complement component 4 increases in patients with major depressive disorder. Neuropsychiatr Dis Treat. 2017;14:37–41. Available from: https://www.dovepress.com/plasma-complement-component-4-increases-in-patients-with-major-depress-peer-reviewed-fulltext-article-NDT

Ikubo K, Yamanishi K, Doe N, Hashimoto T, Sumida M, Watanabe Y, et al. Molecular analysis of the mouse brain exposed to chronic mild stress: The influence of hepatocyte nuclear factor 4a on physiological homeostasis. Mol Med Rep. 2017;16:301–9. Available from: http://www.spandidos-publications.com/https://doi.org/10.3892/mmr.2017.6577/abstract

Germain A, Kupfer DJ. Circadian rhythm disturbances in depression. Human Psychopharmacology: Clinical and Experimental. 2008;23:571–85. Available from: https://onlinelibrary.wiley.com/doi/full/https://doi.org/10.1002/hup.964

Kovanen L, Donner K, Kaunisto M, Partonen T. PRKCDBP (CAVIN3) and CRY2 associate with major depressive disorder. J Affect Disord. 2017;207:136–40. Available from: https://pubmed.ncbi.nlm.nih.gov/27721187/

Gong H, Su WJ, Cao ZY, Lian YJ, Peng W, Liu YZ, et al. Hippocampal Mrp8/14 signaling plays a critical role in the manifestation of depressive-like behaviors in mice. J Neuroinflammation. 2018;15:252.

Article  PubMed  PubMed Central  Google Scholar 

Dmytriyeva O, Pankratova S, Owczarek S, Sonn K, Soroka V, Ridley CM, et al. The metastasis-promoting S100A4 protein confers neuroprotection in brain injury. Nat Commun. 2012;3. Available from: https://pubmed.ncbi.nlm.nih.gov/23149742/

Holzinger D, Foell D, Kessel C. The role of S100 proteins in the pathogenesis and monitoring of autoinflammatory diseases. Mol Cell Pediatr. 2018;5:5–9.

Article  Google Scholar 

Yang J, Anholts J, Kolbe U, Stegehuis-Kamp JA, Claas FHJ, Eikmans M. Calcium-binding proteins S100A8 and S100A9: Investigation of their immune regulatory effect in myeloid cells. Int J Mol Sci. 2018;19:1833.

Article  PubMed  PubMed Central  Google Scholar 

Wu M, Xu L, Wang Y, Zhou N, Zhen F, Zhang Y, et al. S100A8/A9 induces microglia activation and promotes the apoptosis of oligodendrocyte precursor cells by activating the NF-κB signaling pathway. Brain Res Bull. 2018;143:234–45.

Article  PubMed  CAS  Google Scholar 

Hu WGG, Lin cai M. S100a8 silencing attenuates inflammation, oxidative stress and apoptosis in BV2 cells induced by oxygen-glucose deprivation and reoxygenation by upregulating GAB1 expression. Mol Med Rep. 2021;23:1–10.

Google Scholar 

Gong H, Su WJ, Cao ZY, Lian YJ, Peng W, Liu YZ, et al. Hippocampal Mrp8/14 signaling plays a critical role in the manifestation of depressive-like behaviors in mice. J Neuroinflammation. 2018;15:1–13.

Article  Google Scholar 

Stankiewicz AM, Goscik J, Majewska A, Swiergiel AH, Juszczak GR. The effect of acute and chronic social stress on the hippocampal transcriptome in Mice. PLoS ONE. 2015;10:1–25.

Article  Google Scholar 

Charles E, Hammadi M, Kischel P, Delcroix V, Demaurex N, Castelbout C, et al. The antidepressant fluoxetine induces necrosis by energy depletion and mitochondrial calcium overload. Oncotarget. 2017;8:3181–96.

Article  PubMed  Google Scholar 

Then CK, Liu KH, Liao MH, Chung KH, Wang JY, Shen SC. Antidepressants, sertraline and paroxetine, increase calcium influx and induce mitochondrial damage-mediated apoptosis of astrocytes. Oncotarget. 2017;8:115490.

Article  PubMed  PubMed Central  Google Scholar 

Moz S, Lorenzin M, Ramonda R, Aneloni V, La Raja M, Plebani M, et al. Emerging role of monocytes and their intracellular calcium pattern in spondyloarthritis. Clin Chim Acta. 2020;500:180–8.

Article  PubMed  CAS  Google Scholar 

Izzi B, Tirozzi A, Cerletti C, Donati MB, de Gaetano G, Hoylaerts MF, et al. Beyond Haemostasis and Thrombosis: Platelets in Depression and Its Co-Morbidities. Int J Mol Sci. 2020;21:1–32. Available from: https://pubmed.ncbi.nlm.nih.gov/33233416/

Hare DL, Toukhsati SR, Johansson P, Jaarsma T. Depression and cardiovascular disease: a clinical review. Eur Heart J. 2014;35:1365–72. Available from: https://academic.oup.com/eurheartj/article/35/21/1365/582931

O’Connor CM, Gurbel PA, Serebruany VL. Depression and ischemic heart disease. Am Heart J. 2000;140. Available from: https://pubmed.ncbi.nlm.nih.gov/11011350/

Jiang W, Babyak MA, Rozanski A, Sherwood A, O’Connor CM, Waugh RA, et al. Depression and increased myocardial ischemic activity in patients with ischemic heart disease. Am Heart J. 2003;146:55–61. Available from: https://pubmed.ncbi.nlm.nih.gov/12851608/

Metoki N, Sugawara N, Hagii J, Saito S, Shiroto H, Tomita T, et al. Relationship between the lesion location of acute ischemic stroke and early depressive symptoms in Japanese patients. Ann Gen Psychiatry. 2016;15:1–6. Available from: https://annals-general-psychiatry.biomedcentral.com/articles/https://doi.org/10.1186/s12991-016-0099-x

Wei J, Pimple P, Shah AJ, Rooks C, Bremner JD, Nye JA, et al. Depressive symptoms are associated with mental stress-induced myocardial ischemia after acute myocardial infarction. PLoS One. 2014;9:e102986.

Article  PubMed  PubMed Central  Google Scholar 

Pan SJ, Tan YL, Yao SW, Xin Y, Yang X, Liu J, et al. Fluoxetine induces lipid metabolism abnormalities by acting on the liver in patients and mice with depression. Acta Pharmacol Sin. 2018;39:1463.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Meneses MJ, Silvestre R, Sousa-Lima I, Macedo MP. Paraoxonase-1 as a Regulator of Glucose and Lipid Homeostasis: Impact on the Onset and Progression of Metabolic Disorders. Int J Mol Sci. 2019;20:4049.

Article  PubMed  PubMed Central