Skip to content
2000
image of Development of an Inflammation-related Gene-based Diagnostic Risk Model and Immune Infiltration Analysis in Bipolar Disorder

Abstract

Objective

This study aimed to construct a diagnostic risk model for Bipolar Disorder (BD) using inflammation-related genes (IRGs) and to explore the role of immune cell infiltration in BD pathogenesis.

Methods

BD datasets (GSE23848, GSE124326, GSE39653, and GSE46449) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the edgeR package. The intersection of DEGs and IRGs was defined as differentially expressed IRGs. A LASSO regression model was used to identify optimal biomarkers, which were then utilized to construct a diagnostic risk model. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic accuracy of the biomarkers. Internal validation was performed with GSE124326, while external validation utilized GSE23848, GSE39653, and GSE46449. The xCell module in the IOBR package was employed to assess immune cell infiltration proportions. The relationship between IRGs, the diagnostic risk model, and immune cell dynamics was further analyzed.

Results

A total of 2345 DEGs were identified in GSE124326. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated that inflammatory pathways are critically involved in BD pathogenesis. A total of 69 BD-related IRGs were identified. Six key IRGs (IL33, DNASE1L3, IL2RA, CD70, CLEC5A, and SLPI) were identified through LASSO regression analysis and used to develop a diagnostic risk model. Internal and external validations confirmed the robust diagnostic performance of the risk model. Immuno-infiltration analysis showed significant differences in immune cell infiltration between BD patients and healthy controls. The diagnostic risk model and four potential biomarkers (DNASE1L3, IL2RA, CD70, and SLPI) showed strong correlations with various immune cell types.

Conclusion

A diagnostic risk model for BD was constructed based on IRGs, highlighting the critical role of immune cell infiltration in BD pathogenesis.

Loading

Article metrics loading...

/content/journals/cmc/10.2174/0109298673355842250213103507
2025-03-05
2025-06-28
Loading full text...

Full text loading...

References

  1. Miller J.N. Black D.W. Bipolar disorder and suicide: A review. Curr. Psychiatry Rep. 2020 22 2 6 10.1007/s11920‑020‑1130‑0 31955273
    [Google Scholar]
  2. Carvalho A.F. Firth J. Vieta E. Bipolar disorder. N. Engl. J. Med. 2020 383 1 58 66 10.1056/NEJMra1906193 32609982
    [Google Scholar]
  3. Cloutier M. Greene M. Guerin A. Touya M. Wu E. The economic burden of bipolar I disorder in the United States in 2015. J. Affect. Disord. 2018 226 45 51 10.1016/j.jad.2017.09.011 28961441
    [Google Scholar]
  4. Bessonova L. Ogden K. Doane M.J. O’Sullivan A.K. Tohen M. The economic burden of bipolar disorder in the united states: A systematic literature review. Clinicoecon. Outcomes Res. 2020 12 481 497 10.2147/CEOR.S259338 32982338
    [Google Scholar]
  5. Merikangas K.R. Jin R. He J.P. Kessler R.C. Lee S. Sampson N.A. Viana M.C. Andrade L.H. Hu C. Karam E.G. Ladea M. Medina-Mora M.E. Ono Y. Posada-Villa J. Sagar R. Wells J.E. Zarkov Z. Prevalence and correlates of bipolar spectrum disorder in the world mental health survey initiative. Arch. Gen. Psychiat. 2011 68 3 241 251 10.1001/archgenpsychiatry.2011.12 21383262
    [Google Scholar]
  6. Miskowiak K.W. Burdick K.E. Martinez-Aran A. Bonnin C.M. Bowie C.R. Carvalho A.F. Gallagher P. Lafer B. López-Jaramillo C. Sumiyoshi T. McIntyre R.S. Schaffer A. Porter R.J. Purdon S. Torres I.J. Yatham L.N. Young A.H. Kessing L.V. Vieta E. Assessing and addressing cognitive impairment in bipolar disorder: The international society for bipolar disorders targeting cognition task force recommendations for clinicians. Bipolar Disord. 2018 20 3 184 194 10.1111/bdi.12595 29345040
    [Google Scholar]
  7. Zimmerman M. Screening for bipolar disorder with self-administered questionnaires: A critique of the concept and a call to stop publishing studies of their performance in psychiatric samples. Depress. Anxiety 2017 34 9 779 785 10.1002/da.22644 28872771
    [Google Scholar]
  8. Hirschfeld R.M.A. Lewis L. Vornik L.A. Perceptions and impact of bipolar disorder: How far have we really come? Results of the national depressive and manic-depressive association 2000 survey of individuals with bipolar disorder. J. Clin. Psychiat. 2003 64 2 161 174 10.4088/JCP.v64n0209 12633125
    [Google Scholar]
  9. Ziani P.R. Feiten J.G. Goularte J.F. Colombo R. Antqueviezc B. Géa L.P. Rosa A.R. Potential candidates for biomarkers in bipolar disorder: A proteomic approach through systems biology. Clin. Psychopharmacol. Neurosci. 2022 20 2 211 227 10.9758/cpn.2022.20.2.211 35466093
    [Google Scholar]
  10. Rowland T. Perry B.I. Upthegrove R. Barnes N. Chatterjee J. Gallacher D. Marwaha S. Neurotrophins, cytokines, oxidative stress mediators and mood state in bipolar disorder: Systematic review and meta-analyses. Br. J. Psychiat. 2018 213 3 514 525 10.1192/bjp.2018.144 30113291
    [Google Scholar]
  11. Carvalho A.F. Köhler C.A. Fernandes B.S. Quevedo J. Miskowiak K.W. Brunoni A.R. Machado-Vieira R. Maes M. Vieta E. Berk M. Bias in emerging biomarkers for bipolar disorder. Psychol. Med. 2016 46 11 2287 2297 10.1017/S0033291716000957 27193198
    [Google Scholar]
  12. Wollenhaupt-Aguiar B. Librenza-Garcia D. Bristot G. Przybylski L. Stertz L. Burque R.K. Ceresér K.M. Spanemberg L. Caldieraro M.A. Frey B.N. Fleck M.P. Kauer-Sant’Anna M. Passos I.C. Kapczinski F. Differential biomarker signatures in unipolar and bipolar depression: A machine learning approach. Aust. N. Z. J. Psychiat. 2020 54 4 393 401 10.1177/0004867419888027 31789053
    [Google Scholar]
  13. Munkholm K. Peijs L. Vinberg M. Kessing L.V. A composite peripheral blood gene expression measure as a potential diagnostic biomarker in bipolar disorder. Transl. Psychiat. 2015 5 8 e614 10.1038/tp.2015.110 26241352
    [Google Scholar]
  14. Niu Z. Wu X. Zhu Y. Yang L. Shi Y. Wang Y. Qiu H. Gu W. Wu Y. Long X. Lu Z. Hu S. Yao Z. Yang H. Liu T. Xia Y. Chen Z. Chen J. Fang Y. Early diagnosis of bipolar disorder coming soon: Application of an oxidative stress injury biomarker (BIOS) model. Neurosci. Bull. 2022 38 9 979 991 10.1007/s12264‑022‑00871‑4 35590012
    [Google Scholar]
  15. Jones G.H. Vecera C.M. Pinjari O.F. Machado-Vieira R. Inflammatory signaling mechanisms in bipolar disorder. J. Biomed. Sci. 2021 28 1 45 10.1186/s12929‑021‑00742‑6 34112182
    [Google Scholar]
  16. Pereira A.C. Oliveira J. Silva S. Madeira N. Pereira C.M.F. Cruz M.T. Inflammation in Bipolar Disorder (BD): Identification of new therapeutic targets. Pharmacol. Res. 2021 163 105325 10.1016/j.phrs.2020.105325 33278569
    [Google Scholar]
  17. Huang M.H. Chan Y.L.E. Chen M.H. Hsu J.W. Huang K.L. Li C.T. Tsai S.J. Bai Y.M. Su T.P. Pro-inflammatory cytokines and cognitive dysfunction among patients with bipolar disorder and major depression. Psychiatry Clin. Neurosci. 2022 76 9 450 458 10.1111/pcn.13433 35674415
    [Google Scholar]
  18. Dadouli K. Janho M.B. Hatziefthimiou A. Voulgaridi I. Piaha K. Anagnostopoulos L. Ntellas P. Mouchtouri V.A. Bonotis K. Christodoulou N. Speletas M. Hadjichristodoulou C. Neutrophil-to-lymphocyte, monocyte-to-lymphocyte, platelet-to-lymphocyte ratio and systemic immune-inflammatory index in different states of bipolar disorder. Brain Sci. 2022 12 8 1034 10.3390/brainsci12081034 36009097
    [Google Scholar]
  19. Kim Y.K. Jung H.G. Myint A.M. Kim H. Park S.H. Imbalance between pro-inflammatory and anti-inflammatory cytokines in bipolar disorder. J. Affect. Disord. 2007 104 1-3 91 95 10.1016/j.jad.2007.02.018 17434599
    [Google Scholar]
  20. SayuriYamagata A. Brietzke E. Rosenblat J.D. Kakar R. McIntyre R.S. Medical comorbidity in bipolar disorder: The link with metabolic-inflammatory systems. J. Affect. Disord. 2017 211 99 106 10.1016/j.jad.2016.12.059 28107669
    [Google Scholar]
  21. Fries G.R. Walss-Bass C. Bauer M.E. Teixeira A.L. Revisiting inflammation in bipolar disorder. Pharmacol. Biochem. Behav. 2019 177 12 19 10.1016/j.pbb.2018.12.006 30586559
    [Google Scholar]
  22. Liberzon A. Subramanian A. Pinchback R. Thorvaldsdóttir H. Tamayo P. Mesirov J.P. Molecular signatures database (MSigDB) 3.0. Bioinformatics 2011 27 12 1739 1740 10.1093/bioinformatics/btr260 21546393
    [Google Scholar]
  23. Safran M. Dalah I. Alexander J. Rosen N. Stein T.I. Shmoish M. Nativ N. Bahir I. Doniger T. Krug H. Sirota-Madi A. Olender T. Golan Y. Stelzer G. Harel A. Lancet D. GeneCards Version 3: The human gene integrator. Database (Oxford) 2010 2010 baq020 10.1093/database/baq020 20689021
    [Google Scholar]
  24. Davis S. Meltzer P.S. GEOquery: A bridge between the gene expression omnibus (GEO) and bioconductor. Bioinformatics 2007 23 14 1846 1847 10.1093/bioinformatics/btm254 17496320
    [Google Scholar]
  25. Krebs C.E. Ori A.P.S. Vreeker A. Wu T. Cantor R.M. Boks M.P.M. Kahn R.S. Loohuis L.M.O. Ophoff R.A. Whole blood transcriptome analysis in bipolar disorder reveals strong lithium effect. Psychol. Med. 2020 50 15 2575 2586 10.1017/S0033291719002745 31589133
    [Google Scholar]
  26. Beech R.D. Lowthert L. Leffert J.J. Mason P.N. Taylor M.M. Umlauf S. Lin A. Lee J.Y. Maloney K. Muralidharan A. Lorberg B. Zhao H. Newton S.S. Mane S. Epperson C.N. Sinha R. Blumberg H. Bhagwagar Z. Increased peripheral blood expression of electron transport chain genes in bipolar depression. Bipolar Disord. 2010 12 8 813 824 10.1111/j.1399‑5618.2010.00882.x 21176028
    [Google Scholar]
  27. Savitz J. Frank M.B. Victor T. Bebak M. Marino J.H. Bellgowan P.S.F. McKinney B.A. Bodurka J. Teague T.K. Drevets W.C. Inflammation and neurological disease-related genes are differentially expressed in depressed patients with mood disorders and correlate with morphometric and functional imaging abnormalities. Brain Behav. Immun. 2013 31 161 171 10.1016/j.bbi.2012.10.007 23064081
    [Google Scholar]
  28. Clelland C.L. Read L.L. Panek L.J. Nadrich R.H. Bancroft C. Clelland J.D. Utilization of never-medicated bipolar disorder patients towards development and validation of a peripheral biomarker profile. PLoS One 2013 8 6 e69082 10.1371/journal.pone.0069082 23826396
    [Google Scholar]
  29. Robinson M.D. McCarthy D.J. Smyth G.K. edgeR : A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010 26 1 139 140 10.1093/bioinformatics/btp616 19910308
    [Google Scholar]
  30. Villanueva R.A.M. Chen Z.J. ggplot2: Elegant Graphics for Data Analysis. Measurement: Interdisciplinary Research and Perspectives 2nd Ed. Boca Raton Taylor & Francis 2019 17 160 167 10.1080/15366367.2019.1565254
    [Google Scholar]
  31. Chen H. Boutros P.C. VennDiagram: A package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinformatics 2011 12 1 35 10.1186/1471‑2105‑12‑35 21269502
    [Google Scholar]
  32. Wu T. Hu E. Xu S. Chen M. Guo P. Dai Z. Feng T. Zhou L. Tang W. Zhan L. Fu X. Liu S. Bo X. Yu G. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation 2021 2 3 100141 10.1016/j.xinn.2021.100141 34557778
    [Google Scholar]
  33. Friedman J. Hastie T. Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 2010 33 1 1 22 10.18637/jss.v033.i01 20808728
    [Google Scholar]
  34. Engebretsen S. Bohlin J. Statistical predictions with glmnet. Clin. Epigenetics 2019 11 1 123 10.1186/s13148‑019‑0730‑1 31443682
    [Google Scholar]
  35. Zhang L. Zhang H. Xie J. Wang X. Identification of gene co-expression modules and core genes related to immune disorders in major depression disorder. Int. J. Gen. Med. 2021 14 7983 7993 10.2147/IJGM.S336686 34785941
    [Google Scholar]
  36. Zeng D. Ye Z. Shen R. Yu G. Wu J. Xiong Y. Zhou R. Qiu W. Huang N. Sun L. Li X. Bin J. Liao Y. Shi M. Liao W. IOBR: Multi-omics immuno-oncology biological research to decode tumor microenvironment and signatures. Front. Immunol. 2021 12 687975 10.3389/fimmu.2021.687975 34276676
    [Google Scholar]
  37. Aran D. Hu Z. Butte A.J. xCell: Digitally portraying the tissue cellular heterogeneity landscape. Genome Biol. 2017 18 1 220 10.1186/s13059‑017‑1349‑1 29141660
    [Google Scholar]
  38. McIntyre R.S. Berk M. Brietzke E. Goldstein B.I. López-Jaramillo C. Kessing L.V. Malhi G.S. Nierenberg A.A. Rosenblat J.D. Majeed A. Vieta E. Vinberg M. Young A.H. Mansur R.B. Bipolar disorders. Lancet 2020 396 10265 1841 1856 10.1016/S0140‑6736(20)31544‑0 33278937
    [Google Scholar]
  39. Phillips M.L. Kupfer D.J. Bipolar disorder diagnosis: Challenges and future directions. Lancet 2013 381 9878 1663 1671 10.1016/S0140‑6736(13)60989‑7 23663952
    [Google Scholar]
  40. Khafif T.C. Belizario G.O. Silva M. Gomes B.C. Lafer B. Quality of life and clinical outcomes in bipolar disorder: An 8-year longitudinal study. J. Affect. Disord. 2021 278 239 243 10.1016/j.jad.2020.09.061 32971316
    [Google Scholar]
  41. Zimmerman M. Galione J.N. Screening for bipolar disorder with the mood disorders questionnaire: A review. Harv. Rev. Psychiat. 2011 19 5 219 228 10.3109/10673229.2011.614101 21916824
    [Google Scholar]
  42. Zimmerman M. Screening for bipolar disorder: Confusion between case-finding and screening. Psychother. Psychosom. 2014 83 5 259 262 10.1159/000362564 25116428
    [Google Scholar]
  43. McIntyre R.S. Alda M. Baldessarini R.J. Bauer M. Berk M. Correll C.U. Fagiolini A. Fountoulakis K. Frye M.A. Grunze H. Kessing L.V. Miklowitz D.J. Parker G. Post R.M. Swann A.C. Suppes T. Vieta E. Young A. Maj M. The clinical characterization of the adult patient with bipolar disorder aimed at personalization of management. World Psychiat. 2022 21 3 364 387 10.1002/wps.20997 36073706
    [Google Scholar]
  44. North H.F. Weissleder C. Fullerton J.M. Sager R. Webster M.J. Weickert C.S. A schizophrenia subgroup with elevated inflammation displays reduced microglia, increased peripheral immune cell and altered neurogenesis marker gene expression in the subependymal zone. Transl. Psychiat. 2021 11 1 635 10.1038/s41398‑021‑01742‑8 34911938
    [Google Scholar]
  45. Wang J. Ai P. Sun Y. Shi H. Wu A. Wei C. Gene signatures associated with temporal rhythm as diagnostic markers of major depressive disorder and their role in immune infiltration. Int. J. Mol. Sci. 2022 23 19 11558 10.3390/ijms231911558 36232861
    [Google Scholar]
  46. Hughes C.E. Nibbs R.J.B. A guide to chemokines and their receptors. FEBS J. 2018 285 16 2944 2971 10.1111/febs.14466 29637711
    [Google Scholar]
  47. Watson A.E.S. Goodkey K. Footz T. Voronova A. Regulation of CNS precursor function by neuronal chemokines. Neurosci. Lett. 2020 715 134533 10.1016/j.neulet.2019.134533 31629772
    [Google Scholar]
  48. Misiak B. Bartoli F. Carrà G. Małecka M. Samochowiec J. Jarosz K. Banik A. Stańczykiewicz B. Chemokine alterations in bipolar disorder: A systematic review and meta-analysis. Brain Behav. Immun. 2020 88 870 877 10.1016/j.bbi.2020.04.013 32278851
    [Google Scholar]
  49. Wang C. Wang J. Zhu Z. Hu J. Lin Y. Spotlight on pro-inflammatory chemokines: Regulators of cellular communication in cognitive impairment. Front. Immunol. 2024 15 1421076 10.3389/fimmu.2024.1421076 39011039
    [Google Scholar]
  50. Ślusarczyk J. Trojan E. Chwastek J. Głombik K. Basta-Kaim A. A potential contribution of chemokine network dysfunction to the depressive disorders. Curr. Neuropharmacol. 2016 14 7 705 720 10.2174/1570159X14666160219131357 26893168
    [Google Scholar]
  51. Barbosa I.G. Rocha N.P. Vieira E.L. Camkurt M.A. Huguet R.B. Guimarães F.T.L. de Brito-Melo G.E. Mendonça V.A. Bauer M.E. Teixeira A.L. Decreased percentage of CD4+ lymphocytes expressing chemokine receptors in bipolar disorder. Acta Neuropsychiatr. 2019 31 5 246 251 10.1017/neu.2019.5 30867081
    [Google Scholar]
  52. Naaldijk Y.M. Bittencourt M.C. Sack U. Ulrich H. Kinins and microglial responses in bipolar disorder: A neuroinflammation hypothesis. Biol. Chem. 2016 397 4 283 296 10.1515/hsz‑2015‑0257 26859499
    [Google Scholar]
  53. Milenkovic V.M. Stanton E.H. Nothdurfter C. Rupprecht R. Wetzel C.H. The role of chemokines in the pathophysiology of major depressive disorder. Int. J. Mol. Sci. 2019 20 9 2283 10.3390/ijms20092283 31075818
    [Google Scholar]
  54. Sayana P. Colpo G.D. Simões L.R. Giridharan V.V. Teixeira A.L. Quevedo J. Barichello T. A systematic review of evidence for the role of inflammatory biomarkers in bipolar patients. J. Psychiatr. Res. 2017 92 160 182 10.1016/j.jpsychires.2017.03.018 28458141
    [Google Scholar]
  55. Eyre H.A. Air T. Pradhan A. Johnston J. Lavretsky H. Stuart M.J. Baune B.T. A meta-analysis of chemokines in major depression. Prog. Neuropsychopharmacol. Biol. Psychiat. 2016 68 1 8 10.1016/j.pnpbp.2016.02.006 26903140
    [Google Scholar]
  56. Bai Y.M. Su T.P. Tsai S.J. Wen-Fei C. Li C.T. Pei-Chi T. Mu-Hong C. Comparison of inflammatory cytokine levels among type I/type II and manic/hypomanic/euthymic/depressive states of bipolar disorder. J. Affect. Disord. 2014 166 187 192 10.1016/j.jad.2014.05.009 25012430
    [Google Scholar]
  57. Rantala M.J. Luoto S. Borráz-León J.I. Krams I. Bipolar disorder: An evolutionary psychoneuroimmunological approach. Neurosci. Biobehav. Rev. 2021 122 28 37 10.1016/j.neubiorev.2020.12.031 33421542
    [Google Scholar]
  58. Powers A. Almli L. Smith A. Lori A. Leveille J. Ressler K.J. Jovanovic T. Bradley B. A genome-wide association study of emotion dysregulation: Evidence for interleukin 2 receptor alpha. J. Psychiatr. Res. 2016 83 195 202 10.1016/j.jpsychires.2016.09.006 27643478
    [Google Scholar]
  59. He D. Xu H. Zhang H. Tang R. Lan Y. Xing R. Li S. Christian E. Hou Y. Lorello P. Caldarone B. Ding J. Nguyen L. Dionne D. Thakore P. Schnell A. Huh J.R. Rozenblatt-Rosen O. Regev A. Kuchroo V.K. Disruption of the IL-33-ST2-AKT signaling axis impairs neurodevelopment by inhibiting microglial metabolic adaptation and phagocytic function. Immunity 2022 55 1 159 173.e9 10.1016/j.immuni.2021.12.001 34982959
    [Google Scholar]
  60. Barbosa I.G. Morato I.B. de Miranda A.S. Bauer M.E. Soares J.C. Teixeira A.L. A preliminary report of increased plasma levels of IL-33 in bipolar disorder: Further evidence of pro-inflammatory status. J. Affect. Disord. 2014 157 41 44 10.1016/j.jad.2013.12.042 24581826
    [Google Scholar]
  61. Whitehouse C.E. Fisk J.D. Bernstein C.N. Berrigan L.I. Bolton J.M. Graff L.A. Hitchon C.A. Marriott J.J. Peschken C.A. Sareen J. Walker J.R. Stewart S.H. Marrie R.A. Katz A. Lix L.M. Patten S.B. Singer A. El-Gabalawy R. Zarychanski R. Comorbid anxiety, depression, and cognition in MS and other immune-mediated disorders. Neurology 2019 92 5 e406 e417 10.1212/WNL.0000000000006854 30635487
    [Google Scholar]
  62. Cullen A.E. Holmes S. Pollak T.A. Blackman G. Joyce D.W. Kempton M.J. Murray R.M. McGuire P. Mondelli V. Associations between non-neurological autoimmune disorders and psychosis: A meta-analysis. Biol. Psychiat. 2019 85 1 35 48 10.1016/j.biopsych.2018.06.016 30122288
    [Google Scholar]
  63. Kayser M.S. Dalmau J. The emerging link between autoimmune disorders and neuropsychiatric disease. J. Neuropsych. Clin. Neurosci. 2011 23 1 90 97 10.1176/jnp.23.1.jnp90 21304144
    [Google Scholar]
  64. Majchrzak-Gorecka M. Majewski P. Grygier B. Murzyn K. Cichy J. Secretory leukocyte protease inhibitor (SLPI), a multifunctional protein in the host defense response. Cytokine Growth Factor Rev. 2016 28 79 93 10.1016/j.cytogfr.2015.12.001 26718149
    [Google Scholar]
  65. Hannila S.S. Secretory leukocyte protease inhibitor (SLPI). Neuroscientist 2015 21 6 630 636 10.1177/1073858414546000 25118190
    [Google Scholar]
  66. Dantzer R. Neuroimmune interactions: From the brain to the immune system and vice versa. Physiol. Rev. 2018 98 1 477 504 10.1152/physrev.00039.2016 29351513
    [Google Scholar]
  67. Huang X. Hussain B. Chang J. Peripheral inflammation and blood–brain barrier disruption: Effects and mechanisms. CNS Neurosci. Ther. 2021 27 1 36 47 10.1111/cns.13569 33381913
    [Google Scholar]
  68. Drexhage R.C. Knijff E.M. Padmos R.C. Heul-Nieuwenhuijzen L. Beumer W. Versnel M.A. Drexhage H.A. The mononuclear phagocyte system and its cytokine inflammatory networks in schizophrenia and bipolar disorder. Expert Rev. Neurother. 2010 10 1 59 76 10.1586/ern.09.144 20021321
    [Google Scholar]
  69. Becking K. Haarman B.C.M. Grosse L. Nolen W.A. Claes S. Arolt V. Schoevers R.A. Drexhage H.A. The circulating levels of CD4+ t helper cells are higher in bipolar disorder as compared to major depressive disorder. J. Neuroimmunol. 2018 319 28 36 10.1016/j.jneuroim.2018.03.004 29685287
    [Google Scholar]
  70. Pietruczuk K. Lisowska K.A. Grabowski K. Landowski J. Cubała W.J. Witkowski J.M. Peripheral blood lymphocyte subpopulations in patients with bipolar disorder type II. Sci. Rep. 2019 9 1 5869 10.1038/s41598‑019‑42482‑6 30971748
    [Google Scholar]
  71. Barbosa I.G. Rocha N.P. Assis F. Vieira E.L.M. Soares J.C. Bauer M.E. Teixeira A.L. Monocyte and lymphocyte activation in bipolar disorder: A new piece in the puzzle of immune dysfunction in mood disorders. Int. J. Neuropsychopharmacol. 2015 18 1 pyu021 10.1093/ijnp/pyu021 25539506
    [Google Scholar]
  72. Karpiński P. Samochowiec J. Frydecka D. Sąsiadek M.M. Misiak B. Further evidence for depletion of peripheral blood natural killer cells in patients with schizophrenia: A computational deconvolution study. Schizophr. Res. 2018 201 243 248 10.1016/j.schres.2018.04.026 29681501
    [Google Scholar]
  73. Berk M. Post R. Ratheesh A. Gliddon E. Singh A. Vieta E. Carvalho A.F. Ashton M.M. Berk L. Cotton S.M. McGorry P.D. Fernandes B.S. Yatham L.N. Dodd S. Staging in bipolar disorder: From theoretical framework to clinical utility. World Psychia. 2017 16 3 236 244 10.1002/wps.20441 28941093
    [Google Scholar]
/content/journals/cmc/10.2174/0109298673355842250213103507
Loading
/content/journals/cmc/10.2174/0109298673355842250213103507
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher's website along with the published article.


  • Article Type:
    Research Article
Keywords: risk model ; GEO ; immune infiltration ; IRGs ; probe ID ; Bipolar disorder
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test