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Transcriptomic signatures of psychomotor slowing in peripheral blood of depressed patients: evidence for immunometabolic reprogramming

Abstract

Inflammation impacts basal ganglia motor circuitry in association with psychomotor retardation, a key symptom of major depression (MD). We previously reported associations between circulating protein inflammatory biomarkers and psychomotor slowing as measured by neuropsychological tests probing psychomotor speed in patients with MD. To discover novel transcriptional signatures in peripheral blood immune cells related to psychomotor slowing, microarray data were analyzed in a primary cohort of 88 medically-stable, unmedicated, ambulatory MD patients. Results were confirmed and extended in a second cohort of 57 patients with treatment resistant depression (TRD) before and after anti-inflammatory challenge with the tumor necrosis factor antagonist infliximab versus placebo. Composite scores reflecting pure motor and cognitive-motor processing speed were linearly associated with 403 and 266 gene transcripts in each cohort, respectively (|R| > 0.30, p < 0.01), that were enriched for cytokine signaling and glycolysis-related pathways (p < 0.05). Unsupervised clustering in the primary cohort revealed two psychomotor slowing-associated gene co-expression modules that were enriched for interferon, interleukin-6, aerobic glycolysis, and oxidative phosphorylation pathways (p < 0.05, q < 0.1). Transcripts were predominantly derived from monocytes, plasmacytoid dendritic cells, and natural killer cells (p’s < 0.05). In infliximab-treated TRD patients with high plasma C-reactive protein concentrations (>5 mg/L), two differential co-expression modules enriched for oxidative stress and mitochondrial degradation were associated with improvements in psychomotor reaction time (p < 0.05). These results indicate that inflammatory signaling and associated metabolic reprogramming in peripheral blood immune cells are associated with systemic inflammation in depression and may affect relevant brain circuits to promote psychomotor slowing.

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Fig. 1: Gene transcripts associated with psychomotor slowing are enriched for immune and metabolic pathways.
Fig. 2: Gene co-expression modules associated with psychomotor slowing in major depression (MD) are enriched for biological pathways related to immune response and metabolism.
Fig. 3: Gene modules co-regulated by infliximab and associated with subsequent improvements in psychomotor speed in treatment resistant depression (TRD) are enriched for pathways related to oxidative stress, mitochondrial degradation, inflammation, and cancer metabolism.

References

  1. 1.

    Carvalho AF, Miskowiak KK, Hyphantis TN, Kohler CA, Alves GS, Bortolato B, et al. Cognitive dysfunction in depression—pathophysiology and novel targets. CNS Neurol Disord Drug Targets. 2014;13:1819–35.

    PubMed  Article  Google Scholar 

  2. 2.

    Goldsmith DR, Haroon E, Woolwine BJ, Jung MY, Wommack EC, Harvey PD, et al. Inflammatory markers are associated with decreased psychomotor speed in patients with major depressive disorder. Brain Behav Immun. 2016;56:281–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  3. 3.

    Goldsmith DR, Rapaport MH, Miller BJ. A meta-analysis of blood cytokine network alterations in psychiatric patients: comparisons between schizophrenia, bipolar disorder and depression. Mol Psychiatry. 2016;21:1696–709.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  4. 4.

    Miller AH, Raison CL. The role of inflammation in depression: from evolutionary imperative to modern treatment target. Nat Rev Immunol. 2016;16:22–34.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. 5.

    Zunszain PA, Hepgul N, Pariante CM. Inflammation and depression. Curr Top Behav Neurosci. 2013;14:135–51.

    CAS  PubMed  Article  Google Scholar 

  6. 6.

    Dowlati Y, Herrmann N, Swardfager W, Liu H, Sham L, Reim EK, et al. A meta-analysis of cytokines in major depression. Biol Psychiatry. 2010;67:446–57.

    CAS  PubMed  Article  Google Scholar 

  7. 7.

    Brydon L, Harrison NA, Walker C, Steptoe A, Critchley HD. Peripheral inflammation is associated with altered substantia nigra activity and psychomotor slowing in humans. Biol Psychiatry. 2008;63:1022–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  8. 8.

    Capuron L, Gumnick JF, Musselman DL, Lawson DH, Reemsnyder A, Nemeroff CB, et al. Neurobehavioral effects of interferon-alpha in cancer patients: phenomenology and paroxetine responsiveness of symptom dimensions. Neuropsychopharmacology. 2002;26:643–52.

    CAS  PubMed  Article  Google Scholar 

  9. 9.

    Haroon E, Felger JC, Woolwine BJ, Chen X, Parekh S, Spivey JR, et al. Age-related increases in basal ganglia glutamate are associated with TNF, reduced motivation and decreased psychomotor speed during IFN-alpha treatment: preliminary findings. Brain Behav Immun. 2015;46:17–22.

    CAS  PubMed  Article  Google Scholar 

  10. 10.

    Majer M, Welberg LA, Capuron L, Pagnoni G, Raison CL, Miller AH. IFN-alpha-induced motor slowing is associated with increased depression and fatigue in patients with chronic hepatitis C. Brain Behav Immun. 2008;22:870–80.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. 11.

    Frenois F, Moreau M, O’Connor J, Lawson M, Micon C, Lestage J, et al. Lipopolysaccharide induces delayed FosB/DeltaFosB immunostaining within the mouse extended amygdala, hippocampus and hypothalamus, that parallel the expression of depressive-like behavior. Psychoneuroendocrinology. 2007;32:516–31.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  12. 12.

    Lenczowski MJ, Bluthe RM, Roth J, Rees GS, Rushforth DA, van Dam AM, et al. Central administration of rat IL-6 induces HPA activation and fever but not sickness behavior in rats. Am J Physiol. 1999;276:R652–658.

    CAS  PubMed  Google Scholar 

  13. 13.

    Bruder GE, Alvarenga JE, Alschuler D, Abraham K, Keilp JG, Hellerstein DJ, et al. Neurocognitive predictors of antidepressant clinical response. J Affect Disord. 2014;166:108–14.

    PubMed  PubMed Central  Article  Google Scholar 

  14. 14.

    Taylor BP, Bruder GE, Stewart JW, McGrath PJ, Halperin J, Ehrlichman H, et al. Psychomotor slowing as a predictor of fluoxetine nonresponse in depressed outpatients. Am J Psychiatry. 2006;163:73–8.

    PubMed  Article  Google Scholar 

  15. 15.

    Haroon E, Daguanno AW, Woolwine BJ, Goldsmith DR, Baer WM, Wommack EC, et al. Antidepressant treatment resistance is associated with increased inflammatory markers in patients with major depressive disorder. Psychoneuroendocrinology. 2018;95:43–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  16. 16.

    Capuron L, Pagnoni G, Drake DF, Woolwine BJ, Spivey JR, Crowe RJ, et al. Dopaminergic mechanisms of reduced basal ganglia responses to hedonic reward during interferon alfa administration. Arch Gen Psychiatry. 2012;69:1044–53.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  17. 17.

    Eisenberger NI, Berkman ET, Inagaki TK, Rameson LT, Mashal NM, Irwin MR. Inflammation-induced anhedonia: endotoxin reduces ventral striatum responses to reward. Biol Psychiatry. 2010;68:748–54.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  18. 18.

    Harrison NA, Brydon L, Walker C, Gray MA, Steptoe A, Critchley HD. Inflammation causes mood changes through alterations in subgenual cingulate activity and mesolimbic connectivity. Biol Psychiatry. 2009;66:407–14.

    PubMed  PubMed Central  Article  Google Scholar 

  19. 19.

    Felger JC, Li Z, Haroon E, Woolwine BJ, Jung MY, Hu X, et al. Inflammation is associated with decreased functional connectivity within corticostriatal reward circuitry in depression. Mol Psychiatry. 2016;21:1358–65.

    CAS  Article  Google Scholar 

  20. 20.

    Leday GGR, Vertes PE, Richardson S, Greene JR, Regan T, Khan S, et al. Replicable and coupled changes in innate and adaptive immune gene expression in two case-control studies of blood microarrays in major depressive disorder. Biol Psychiatry. 2018;83:70–80.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Mostafavi S, Battle A, Zhu X, Potash JB, Weissman MM, Shi J, et al. Type I interferon signaling genes in recurrent major depression: increased expression detected by whole-blood RNA sequencing. Mol Psychiatry. 2014;19:1267–74.

    CAS  PubMed  Article  Google Scholar 

  22. 22.

    Mehta D, Raison CL, Woolwine BJ, Haroon E, Binder EB, Miller AH, et al. Transcriptional signatures related to glucose and lipid metabolism predict treatment response to the tumor necrosis factor antagonist infliximab in patients with treatment-resistant depression. Brain Behav Immun. 2013;31:205–15.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  23. 23.

    Mamdani F, Berlim MT, Beaulieu MM, Labbe A, Merette C, Turecki G. Gene expression biomarkers of response to citalopram treatment in major depressive disorder. Transl Psychiatry. 2011;1:e13.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  24. 24.

    Guilloux JP, Bassi S, Ding Y, Walsh C, Turecki G, Tseng G, et al. Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression. Neuropsychopharmacology. 2015;40:701–10.

    CAS  PubMed  Article  Google Scholar 

  25. 25.

    Cattaneo A, Gennarelli M, Uher R, Breen G, Farmer A, Aitchison KJ, et al. Candidate genes expression profile associated with antidepressants response in the GENDEP study: differentiating between baseline ‘predictors’ and longitudinal ‘targets’. Neuropsychopharmacol: Off Publ Am Coll Neuropsychopharmacol. 2013;38:377–85.

    CAS  Article  Google Scholar 

  26. 26.

    Cattaneo A, Ferrari C, Uher R, Bocchio-Chiavetto L, Riva MA, Consortium MRCI, et al. Absolute measurements of macrophage migration inhibitory factor and interleukin-1-beta mRNA levels accurately predict treatment response in depressed patients. Int J Neuropsychopharmacol. 2016;19:pyw045.

  27. 27.

    Felger JC, Cole SW, Pace TW, Hu F, Woolwine BJ, Doho GH, et al. Molecular signatures of peripheral blood mononuclear cells during chronic interferon-alpha treatment: relationship with depression and fatigue. Psychol Med. 2012;42:1591–603.

    CAS  PubMed  Article  Google Scholar 

  28. 28.

    Xiao C, Beitler JJ, Higgins KA, Conneely K, Dwivedi B, Felger J, et al. Fatigue is associated with inflammation in patients with head and neck cancer before and after intensity-modulated radiation therapy. Brain Behav Immun. 2016;52:145–52.

    PubMed  Article  Google Scholar 

  29. 29.

    O’Neill LA, Kishton RJ, Rathmell J. A guide to immunometabolism for immunologists. Nat Rev Immunol. 2016;16:553–65.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  30. 30.

    Shoelson SE, Lee J, Goldfine AB. Inflammation and insulin resistance. J Clin Invest. 2006;116:1793–801.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31.

    Bekhbat M, Treadway MT, Goldsmith DR, Woolwine BJ, Haroon E, Miller AH, et al. Gene signatures in peripheral blood immune cells related to insulin resistance and low tyrosine metabolism define a sub-type of depression with high CRP and anhedonia. Brain Behav Immun. 2020;88:161–5.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  32. 32.

    Goldsmith DR, Bekhbat M, Le NA, Chen X, Woolwine BJ, Li Z, et al. Protein and gene markers of metabolic dysfunction and inflammation together associate with functional connectivity in reward and motor circuits in depression. Brain Behav Immun. 2020;88:193–202.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  33. 33.

    Raison CL, Rutherford RE, Woolwine BJ, Shuo C, Schettler P, Drake DF, et al. A randomized controlled trial of the tumor necrosis factor antagonist infliximab for treatment-resistant depression: the role of baseline inflammatory biomarkers. JAMA Psychiatry. 2013;70:31–41.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. 34.

    Chang HH, Lee IH, Gean PW, Lee SY, Chi MH, Yang YK, et al. Treatment response and cognitive impairment in major depression: association with C-reactive protein. Brain Behav Immun. 2012;26:90–5.

    PubMed  Article  CAS  Google Scholar 

  35. 35.

    Krogh J, Benros ME, Jorgensen MB, Vesterager L, Elfving B, Nordentoft M. The association between depressive symptoms, cognitive function, and inflammation in major depression. Brain Behav Immun. 2014;35:70–6.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  36. 36.

    Raison CL, Rye DB, Woolwine BJ, Vogt GJ, Bautista BM, Spivey JR, et al. Chronic interferon-alpha administration disrupts sleep continuity and depth in patients with hepatitis C: association with fatigue, motor slowing, and increased evening cortisol. Biol Psychiatry. 2010;68:942–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  37. 37.

    Grubbs FE. Procedures for detecting outlying observations in samples. Technometrics. 1969;11:1–21.

    Article  Google Scholar 

  38. 38.

    Bekhbat M, Chu K, Le NA, Woolwine BJ, Haroon E, Miller AH, et al. Glucose and lipid-related biomarkers and the antidepressant response to infliximab in patients with treatment-resistant depression. Psychoneuroendocrinology. 2018;98:222–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. 39.

    Felger JC, Haroon E, Patel TA, Goldsmith DR, Wommack EC, Woolwine BJ, et al. What does plasma CRP tell us about peripheral and central inflammation in depression? Mol Psychiatry. 2020;25:1301–11.

    CAS  PubMed  Article  Google Scholar 

  40. 40.

    Howren MB, Lamkin DM, Suls J. Associations of depression with C-reactive protein, IL-1, and IL-6: a meta-analysis. Psychosom Med. 2009;71:171–86.

    CAS  PubMed  Article  Google Scholar 

  41. 41.

    Allen JD, Chen M, Xie Y. Model-Based Background Correction (MBCB): R Methods and GUI for Illumina Bead-array Data. J Cancer Sci Ther. 2009;1:25–7.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  42. 42.

    Du P, Kibbe WA, Lin SM. lumi: a pipeline for processing Illumina microarray. Bioinformatics. 2008;24:1547–8.

    CAS  PubMed  Article  Google Scholar 

  43. 43.

    Barfield RT, Kilaru V, Smith AK, Conneely KN. CpGassoc: an R function for analysis of DNA methylation microarray data. Bioinformatics. 2012;28:1280–1.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  44. 44.

    Ross KM, Carroll JE, Dunkel Schetter C, Hobel C, Cole SW. Pro-inflammatory immune cell gene expression during the third trimester of pregnancy is associated with shorter gestational length and lower birthweight. Am J Reprod Immunol. 2019;82:e13190.

    PubMed  Article  Google Scholar 

  45. 45.

    Miller GE, Chen E, Shalowitz MU, Story RE, Leigh AKK, Ham P, et al. Divergent transcriptional profiles in pediatric asthma patients of low and high socioeconomic status. Pediatr Pulmonol. 2018;53:710–9.

    PubMed  PubMed Central  Article  Google Scholar 

  46. 46.

    Mellon SH, Wolkowitz OM, Schonemann MD, Epel ES, Rosser R, Burke HB, et al. Alterations in leukocyte transcriptional control pathway activity associated with major depressive disorder and antidepressant treatment. Transl Psychiatry. 2016;6:e821.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  47. 47.

    Cole SW, Galic Z, Zack JA. Controlling false-negative errors in microarray differential expression analysis: a PRIM approach. Bioinformatics. 2003;19:1808–16.

    CAS  PubMed  Article  Google Scholar 

  48. 48.

    Han TJ, Felger JC, Lee A, Mister D, Miller AH, Torres MA. Association of childhood trauma with fatigue, depression, stress, and inflammation in breast cancer patients undergoing radiotherapy. Psychooncology. 2016;25:187–93.

    PubMed  Article  Google Scholar 

  49. 49.

    Torres MA, Pace TW, Liu T, Felger JC, Mister D, Doho GH, et al. Predictors of depression in breast cancer patients treated with radiation: role of prior chemotherapy and nuclear factor kappa B. Cancer. 2013;119:1951–9.

    PubMed  Article  Google Scholar 

  50. 50.

    Guo L, Lobenhofer EK, Wang C, Shippy R, Harris SC, Zhang L, et al. Rat toxicogenomic study reveals analytical consistency across microarray platforms. Nat Biotechnol. 2006;24:1162–9.

    CAS  PubMed  Article  Google Scholar 

  51. 51.

    Patterson TA, Lobenhofer EK, Fulmer-Smentek SB, Collins PJ, Chu TM, Bao W, et al. Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project. Nat Biotechnol. 2006;24:1140–50.

    CAS  PubMed  Article  Google Scholar 

  52. 52.

    Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16:284–7.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  53. 53.

    Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci USA. 2003;100:9440–5.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  54. 54.

    Hulsegge I, Kommadath A, Smits MA. Globaltest and GOEAST: two different approaches for Gene Ontology analysis. BMC Proc. 2009;3:S10.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  55. 55.

    Yang Y, Han L, Yuan Y, Li J, Hei N, Liang H. Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types. Nat Commun. 2014;5:3231.

    PubMed  Article  CAS  Google Scholar 

  56. 56.

    Yang D, Li Y, Xiao H, Liu Q, Zhang M, Zhu J, et al. Gaining confidence in biological interpretation of the microarray data: the functional consistence of the significant GO categories. Bioinformatics. 2008;24:265–71.

    CAS  PubMed  Article  Google Scholar 

  57. 57.

    Jansen R, Penninx BW, Madar V, Xia K, Milaneschi Y, Hottenga JJ, et al. Gene expression in major depressive disorder. Mol Psychiatry. 2016;21:339–47.

    CAS  PubMed  Article  Google Scholar 

  58. 58.

    de Kluiver H, Jansen R, Milaneschi Y, Penninx B. Involvement of inflammatory gene expression pathways in depressed patients with hyperphagia. Transl Psychiatry. 2019;9:193.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  59. 59.

    Zhou Y, Lutz PE, Wang YC, Ragoussis J, Turecki G. Global long non-coding RNA expression in the rostral anterior cingulate cortex of depressed suicides. Transl Psychiatry. 2018;8:224.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  60. 60.

    Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma. 2008;9:559.

    Article  CAS  Google Scholar 

  61. 61.

    Cole SW, Hawkley LC, Arevalo JM, Cacioppo JT. Transcript origin analysis identifies antigen-presenting cells as primary targets of socially regulated gene expression in leukocytes. Proc Natl Acad Sci USA. 2011;108:3080–5.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  62. 62.

    Chamberlain SR, Cavanagh J, de Boer P, Mondelli V, Jones DNC, Drevets WC, et al. Treatment-resistant depression and peripheral C-reactive protein. Br J Psychiatry. 2019;214:11–9.

    PubMed  PubMed Central  Article  Google Scholar 

  63. 63.

    Hepgul N, Cattaneo A, Agarwal K, Baraldi S, Borsini A, Bufalino C, et al. Transcriptomics in interferon-alpha-treated patients identifies inflammation-, neuroplasticity- and oxidative stress-related signatures as predictors and correlates of depression. Neuropsychopharmacology. 2016;41:2502–11.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  64. 64.

    Yang J, Zhang L, Yu C, Yang XF, Wang H. Monocyte and macrophage differentiation: circulation inflammatory monocyte as biomarker for inflammatory diseases. Biomark Res. 2014;2:1.

    PubMed  PubMed Central  Article  Google Scholar 

  65. 65.

    Reizis B, Bunin A, Ghosh HS, Lewis KL, Sisirak V. Plasmacytoid dendritic cells: recent progress and open questions. Annu Rev Immunol. 2011;29:163–83.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  66. 66.

    Cheng SC, Quintin J, Cramer RA, Shepardson KM, Saeed S, Kumar V, et al. mTOR- and HIF-1alpha-mediated aerobic glycolysis as metabolic basis for trained immunity. Science. 2014;345:1250684.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  67. 67.

    Cao W, Manicassamy S, Tang H, Kasturi SP, Pirani A, Murthy N, et al. Toll-like receptor-mediated induction of type I interferon in plasmacytoid dendritic cells requires the rapamycin-sensitive PI(3)K-mTOR-p70S6K pathway. Nat Immunol. 2008;9:1157–64.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  68. 68.

    Fekete T, Suto MI, Bencze D, Mazlo A, Szabo A, Biro T, et al. Human plasmacytoid and monocyte-derived dendritic cells display distinct metabolic profile upon RIG-I activation. Front Immunol. 2018;9:3070.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  69. 69.

    Keating SE, Zaiatz-Bittencourt V, Loftus RM, Keane C, Brennan K, Finlay DK, et al. Metabolic reprogramming supports IFN-gamma production by CD56bright NK cells. J Immunol. 2016;196:2552–60.

    CAS  PubMed  Article  Google Scholar 

  70. 70.

    Kumar A, Pyaram K, Yarosz EL, Hong H, Lyssiotis CA, Giri S, et al. Enhanced oxidative phosphorylation in NKT cells is essential for their survival and function. Proc Natl Acad Sci USA. 2019;116:7439–48.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  71. 71.

    Lachmandas E, Boutens L, Ratter JM, Hijmans A, Hooiveld GJ, Joosten LA, et al. Microbial stimulation of different Toll-like receptor signalling pathways induces diverse metabolic programmes in human monocytes. Nat Microbiol. 2016;2:16246.

    PubMed  Article  CAS  Google Scholar 

  72. 72.

    Treadway MT, Cooper JA, Miller AH. Can’t or Won’t? Immunometabolic constraints on dopaminergic drive. Trends Cogn Sci. 2019;23:435–48.

    PubMed  PubMed Central  Article  Google Scholar 

  73. 73.

    Allen J, Romay-Tallon R, Brymer KJ, Caruncho HJ, Kalynchuk LE. Mitochondria and mood: mitochondrial dysfunction as a key player in the manifestation of depression. Front Neurosci. 2018;12:386.

    PubMed  PubMed Central  Article  Google Scholar 

  74. 74.

    Karabatsiakis A, Bock C, Salinas-Manrique J, Kolassa S, Calzia E, Dietrich DE, et al. Mitochondrial respiration in peripheral blood mononuclear cells correlates with depressive subsymptoms and severity of major depression. Transl Psychiatry. 2014;4:e397.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  75. 75.

    Beech RD, Lowthert L, Leffert JJ, Mason PN, Taylor MM, Umlauf S, et al. Increased peripheral blood expression of electron transport chain genes in bipolar depression. Bipolar Disord. 2010;12:813–24.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  76. 76.

    Zeng D, He S, Ma C, Wen Y, Xie Y, Zhao N, et al. Co-expression network analysis revealed that the ATP5G1 gene is associated with major depressive disorder. Front Genet. 2019;10:703.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  77. 77.

    Wang Q, Dwivedi Y. Transcriptional profiling of mitochondria associated genes in prefrontal cortex of subjects with major depressive disorder. World J Biol Psychiatry. 2016;18:592–603.

    PubMed  PubMed Central  Article  Google Scholar 

  78. 78.

    Martins-de-Souza D, Guest PC, Harris LW, Vanattou-Saifoudine N, Webster MJ, Rahmoune H, et al. Identification of proteomic signatures associated with depression and psychotic depression in post-mortem brains from major depression patients. Transl Psychiatry. 2012;2:e87.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  79. 79.

    Esteban-Martinez L, Sierra-Filardi E, McGreal RS, Salazar-Roa M, Marino G, Seco E, et al. Programmed mitophagy is essential for the glycolytic switch during cell differentiation. EMBO J. 2017;36:1688–706.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  80. 80.

    Weckmann K, Deery MJ, Howard JA, Feret R, Asara JM, Dethloff F, et al. Ketamine’s antidepressant effect is mediated by energy metabolism and antioxidant defense system. Sci Rep. 2017;7:15788.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  81. 81.

    Weckmann K, Labermaier C, Asara JM, Muller MB, Turck CW. Time-dependent metabolomic profiling of Ketamine drug action reveals hippocampal pathway alterations and biomarker candidates. Transl Psychiatry. 2014;4:e481.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  82. 82.

    Stacey D, Schubert KO, Clark SR, Amare AT, Milanesi E, Maj C, et al. A gene co-expression module implicating the mitochondrial electron transport chain is associated with long-term response to lithium treatment in bipolar affective disorder. Transl Psychiatry. 2018;8:183.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  83. 83.

    Sobin C, Sackeim HA. Psychomotor symptoms of depression. Am J Psychiatry. 1997;154:4–17.

    CAS  PubMed  Article  Google Scholar 

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Acknowledgements

This study was supported by grants R01MH087604 (Miller), R01MH109637 (Felger), R61MH121625 (Felger), R01MH107033 (Haroon), R01MH112076 (Miller/Haroon), R03MH100273 (Miller), R21MH121891 (Miller/Felger), F32MH119750 (Bekhbat), and K23MH114037 (Goldsmith) from the National Institute of Mental Health; NARSAD Distinguished Investigator Grant (Miller) from the Brain and Behavioral Research Foundation. In addition, the study was supported in part by PHS Grants UL1TR000454, UL1TR002378, KL2TR000455, and TL1TR002382 from the Clinical and Translational Science Award program, by the NIH/NCI under award number P30CA138292, R21MH077172, and the Emory Integrated Genomics Core (EIGC), which is subsidized by the Emory University School of Medicine and is one of the Emory Integrated Core Facilities.

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Collected the data: BJW, EH, AHM, and JCF. Conceived the study: DRG, AHM, and JCF. Designed the analyses: MB, DRG, AHM, and JCF. Performed data analysis: MB. Drafted and revised the paper: MB with assistance from DRG, AHM, and JCF.

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Correspondence to Jennifer C. Felger.

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All authors declare no conflicts of interest. In the past 12 months, Dr. Felger has consulted for Otsuka on a topic unrelated to this research.

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Bekhbat, M., Goldsmith, D.R., Woolwine, B.J. et al. Transcriptomic signatures of psychomotor slowing in peripheral blood of depressed patients: evidence for immunometabolic reprogramming. Mol Psychiatry (2021). https://doi.org/10.1038/s41380-021-01258-z

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