Hierarchical Inflammatory Phenotypes of Depression: A Novel Approach across Five Independent Samples and 27,730 Adults



      Although characterizing associations between inflammation and depression may prove critical for informing theory, research, and treatment decisions, extant research has been limited by ignoring the possibility that inflammation may be simultaneously associated with depression broadly and with a subset of symptoms. This lack of direct comparison has hampered attempts to understand inflammatory phenotypes of depression and, critically, fails to consider that inflammation might be uniquely associated with both depression broadly and individual symptoms.


      We used moderated nonlinear factor analysis in five NHANES cohorts (N=27,730, 51% female, mean age=46 years).


      C-reactive protein (CRP) is simultaneously associated with latent depression, appetite, and fatigue. Specifically, CRP was associated with latent depression in all five samples (rs: .044-.089; ps: <.001-.002) and was associated with both appetite (significant rs: .031-.049, significant ps: .001-.007) and fatigue (significant rs: .030-.054, significant ps: <.001-.029) in four samples. These results were largely robust to covariates.


      Methodologically, these models indicate that the PHQ-9 is scalar noninvariant as a function of CRP (i.e., identical PHQ-9 scores may represent different constructs in those with high vs. low CRP). Therefore, mean-comparisons of depression total scores and CRP might be misleading without accounting for symptom-specific associations. Conceptually, these findings indicate that studies investigating inflammatory phenotypes of depression should examine how inflammation is simultaneously related to both depression broadly and specific symptoms, and whether these relations function via different mechanisms. This has the potential to yield new theoretical insights and may lead to novel therapies for reducing inflammation-related symptoms of depression.


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        • Dooley L.N.
        • Kuhlman K.R.
        • Robles T.F.
        • Eisenberger N.I.
        • Craske M.G.
        • Bower J.E.
        The role of inflammation in core features of depression: Insights from paradigms using exogenously-induced inflammation.
        Neurosci Biobehav Rev. 2018; 94: 219-237
        • Majd M.
        • Saunders E.F.H.
        • Engeland C.G.
        Inflammation and the dimensions of depression: A review.
        Front Neuroendocrinol. 2020; 56
        • Hilland E.
        • Landrø N.I.
        • Kraft B.
        • Tamnes C.K.
        • Fried E.I.
        • Maglanoc L.A.
        • Jonassen R.
        Exploring the links between specific depression symptoms and brain structure: A network study.
        Psychiatry Clin Neurosci. 2020; 74: 220-221
        • Kappelmann N.
        • Arloth J.
        • Georgakis M.K.
        • Czamara D.
        • Rost N.
        • Ligthart S.
        • et al.
        Dissecting the association between inflammation, metabolic dysregulation, and specific depressive symptoms: A genetic correlation and 2-sample mendelian randomization study.
        JAMA Psychiatry. 2020;
        • Horn S.R.
        • Long M.M.
        • Nelson B.W.
        • Allen N.B.
        • Fisher P.A.
        • Byrne M.L.
        Replication and reproducibility issues in the relationship between C-reactive protein and depression: A systematic review and focused meta-analysis.
        Brain Behav Immun. 2018; 73: 85-114
        • Osimo E.F.
        • Baxter L.J.
        • Lewis G.
        • Jones P.B.
        • Khandaker G.M.
        Prevalence of low-grade inflammation in depression: A systematic review and meta-analysis of CRP levels.
        Psychol Med. 2019; 49: 1958-1970
        • Fried E.I.
        • von Stockert S.
        • Haslbeck J.M.B.
        • Lamers F.
        • Schoevers R.A.
        • Penninx B.W.J.H.
        Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates.
        Psychol Med. 2019;
        • Moriarity D.P.
        • Horn S.R.
        • Kautz M.M.
        • Haslbeck J.M.
        • Alloy L.B.
        How handling extreme C-reactive protein (CRP) values and regularization influences CRP and depression criteria associations in network analyses.
        Brain Behav Immun. 2021; 91: 393-403
        • Frank P.
        • Jokela M.
        • Batty G.D.
        • Cadar D.
        • Steptoe A.
        • Kivimäki M.
        Association Between Systemic Inflammation and Individual Symptoms of Depression: A Pooled Analysis of 15 Population-Based Cohort Studies.
        Am J Psychiatry. 2021; 178: 1107-1118
        • Lamers F.
        • Milaneschi Y.
        • De Jonge P.
        • Giltay E.J.
        • Penninx B.W.J.H.
        Metabolic and inflammatory markers: Associations with individual depressive symptoms.
        Psychol Med. 2018; 48: 1102-1110
        • Milaneschi Y.
        • Lamers F.
        • Berk M.
        • Penninx B.W.J.H.
        Depression Heterogeneity and Its Biological Underpinnings: Toward Immunometabolic Depression.
        Biol Psychiatry. 2020; 88: 369-380
        • Milaneschi Y.
        • Kappelmann N.
        • Ye Z.
        • Lamers F.
        • Moser S.
        • Jones P.B.
        • et al.
        Association of Inflammation with Depression and Anxiety: Evidence for Symptom-Specificity and Potential Causality from UK Biobank and NESDA Cohorts.
        Mol Psychiatry. 2021; : 1-10
      1. Moriarity DP (2021): Building a replicable and clinically-impactful immunopsychiatry: Methods, phenotyping, and theory integration. Brain, Behav Immun - Heal 16.

        • Bauer D.
        A More General Model for Testing Measurement Invariance and Differential Item Functioning.
        Psychol Methods. 2017; 22: 507-526
      2. Centers for Disease Control and Prevention (2009): National Health and Nutrition Examination Survey (NHANES) Stored Biologic Specimens: Guidelines for Proposals to Use Samples and Proposed Cost Schedule.

      3. Zipf G, Chiappa M, Porter KS, Ostchega Y, Lewis BG, Dostal J (2013): National Health and Nutrition Examination Survey: Plan and Operations, 1999 – 2010.

      4. Chen TC, Clark J, Riddles MK, Mohadjer LK, Fakhouri THI (2018): Vital and Health Statistics National Health and Nutrition Examination Survey , 2015 − 2018 : Sample Design and Estimation Procedures.

        • Kroenke K.
        • Spitzer R.L.
        • Williams J.B.
        The PHQ‐9: validity of a brief depression severity measure.
        J Gen Intern Med. 2001; 16: 606-613
        • Manea L.
        • Gilbody S.
        • McMillan D.
        Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): a meta-analysis.
        Can Med Assoc J. 2012; 184: 191-196
        • Moriarity D.P.
        • Mac Giollabhui N.
        • Ellman L.M.
        • Klugman J.
        • Coe C.L.
        • Abramson L.Y.
        • Alloy L.B.
        Inflammatory proteins predict change in depressive symptoms in male and female adolescents.
        Clin Psychol Sci. 2019; 7: 754-767
        • Khera A.
        • Ms C.
        • Mcguire D.K.
        • Mhs C.
        • Murphy S.A.
        • Stanek H.G.
        • et al.
        Race and Gender Differences in C-Reactive Protein Levels.
        J Am Coll Cardiol. 2005; 46: 464-469
        • O’Connor M.F.
        • Bower J.E.
        • Cho H.J.
        • Creswell J.D.
        • Dimitrov S.
        • Hamby M.E.
        • et al.
        To assess, to control, to exclude: Effects of biobehavioral factors on circulating inflammatory markers.
        Brain Behav Immun. 2009; 23: 887-897
        • Fiske A.
        • Gatz M.
        • Pedersen N.L.
        Depressive Symptoms and Aging: The Effects of Illness and Non-Health-Related Events.
        Journals Gerontol - Ser B Psychol Sci Soc Sci. 2003; 58: 320-328
        • DuBrock H.M.
        • AbouEzzeddine O.F.
        • Redfield M.M.
        High-sensitivity C-reactive protein in heart failure with preserved ejection fraction.
        PLoS One. 2018; 13: 1-16
      5. Dunlop DD, Song J, Lyons JS, Manheim LM, Chang RW (2003): Racial/Ethnic Differences in Rates of Depression Among Preretirement Adults. 93: 30–32.

        • Deverts D.J.
        • Cohen S.
        • Kalra P.
        • Matthews K.A.
        The prospective association of socioeconomic status with C-reactive protein levels in the CARDIA study.
        Brain Behav Immun. 2012; 26: 1128-1135
      6. Gilman SE, Kawachi I, Fitzmaurice M, Buka SL (2002): Socioeconomic status in childhood and the lifetime risk of major depression. 359–367.

        • Mac Giollabhui N.
        • Swistun D.
        • Murray S.
        • Moriarity D.
        • Kautz M.
        • Ellman L.
        • et al.
        Executive dysfunction in depression in adolescence: The role of inflammation and higher body mass.
        Psychol Med. 2020; 50: 683-691
        • Del Giudice M.
        • Gangestad S.W.
        A Traveler’s Guide to the Multiverse: Promises, Pitfalls, and a Framework for the Evaluation of Analytic Decisions.
        Adv Methods Pract Psychol Sci. 2021; 4
      7. Muthén B, Muthén L (2017): Mplus User’s Guide, 6th Editio ((M. & Muthén, editor)). Los Angeles, CA.

        • Hallquist M.
        • Wiley J.
        MplusAutomation: An R package for facilitating large-scale latent variable analyses in Mplus.
        Struct Equ Model A Multidiscip J. 2018; 25: 621-638
      8. Team RC (2013): R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. Retrieved from

        • Flora D.B.
        • Curran P.J.
        An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data.
        Psychol Methods. 2004; 9: 466-491
        • Bentler P.M.
        Quantitative methods in psychology: Comparative fit indexes in structural models.
        Psychol Bull. 1990; 107: 238-246
        • Steiger J.H.
        Structural Model Evaluation and Modification: An Interval Estimation Approach.
        Multivariate Behav Res. 1990; 25: 173-180
      9. Bollen KA (1989): Structural Equations with Latent Variables. New York, NY: Wiley.

        • Pariante C.M.
        Increased Inflammation in Depression: A Little in All, or a Lot in a Few?.
        Am J Psychiatry. 2021; 178: 1077-1079
        • Raison C.L.
        • Miller A.H.
        Is depression an inflammatory disorder?.
        Curr Psychiatry Rep. 2011; 13: 467-475
      10. Mathers C, Fat DM, Boerma JY (2008): The Global Burden of Disease: 2004 Update. Geneva, Switzerland.

        • Jacka F.N.
        • Kremer P.J.
        • Leslie E.R.
        • Berk M.
        • Patton G.C.
        • Toumbourou J.W.
        • Williams J.W.
        Associations between diet quality and depressed mood in adolescents: Results from the Australian Healthy Neighbourhoods Study.
        Aust N Z J Psychiatry. 2010; 44: 435-442
        • Miller G.E.
        • Rohleder N.
        • Stetler C.
        • Kirschbaum C.
        Clinical depression and regulation of the inflammatory response during acute stress.
        Psychosom Med. 2005; 67: 679-687
        • Hart B.L.
        Biological basis of the behavior of sick animals.
        Neurosci Biobehav Rev. 1988; 12: 123-137
        • Krzyszton C.P.
        • Sparkman N.L.
        • Grant R.W.
        • Buchanan J.B.
        • Broussard S.R.
        • Woods J.
        • Johnson R.W.
        Exacerbated fatigue and motor deficits in interleukin-10-deficient mice after peripheral immune stimulation.
        Am J Physiol - Regul Integr Comp Physiol. 2008; 295: 1109-1114
        • Simmons W.K.
        • Burrows K.
        • Avery J.A.
        • Kerr K.L.
        • Taylor A.
        • Bodurka J.
        • et al.
        Appetite changes reveal depression subgroups with distinct endocrine, metabolic, and immune states.
        Mol Psychiatry. 2018; : 1-12
        • Glaus J.
        • Vandeleur C.L.
        • von Känel R.
        • Lasserre A.M.
        • Strippoli M.P.F.
        • Gholam-Rezaee M.
        • et al.
        Associations between mood, anxiety or substance use disorders and inflammatory markers after adjustment for multiple covariates in a population-based study.
        J Psychiatr Res. 2014; 58: 36-45
        • Hickman R.J.
        • Khambaty T.
        • Stewart J.C.
        C-reactive protein is elevated in atypical but not nonatypical depression: Data from the National Health and Nutrition Examination Survey (NHANES) 1999-2004.
        J Behav Med. 2014; 37: 621-629
        • Duivis H.E.
        • Kupper N.
        • Vermunt J.K.
        • Penninx B.W.
        • Bosch N.M.
        • Riese H.
        • et al.
        Depression trajectories, inflammation, and lifestyle factors in adolescence: The Tracking Adolescents’ Individual Lives Survey.
        Heal Psychol. 2015; 34: 1047-1057
        • Elovainio M.
        • Aalto A.M.
        • Kivimäki M.
        • Pirkola S.
        • Sundvall J.
        • Lönnqvist J.
        • Reunanen A.
        Depression and C-reactive protein: Population-based health 2000 study.
        Psychosom Med. 2009; 71: 423-430
        • Andréasson A.
        • Arborelius L.
        • Erlanson-Albertsson C.
        • Lekander M.
        A putative role for cytokines in the impaired appetite in depression.
        Brain Behav Immun. 2007; 21: 147-152
        • Moriarity D.P.
        • Slavich G.
        • Joyner K.
        • Alloy L.B.
        Unconsidered Issues of Measurement Noninvariance in Biological Psychiatry: A Focus on Biological Phenotypes of Psychopathology.
        Mol Psychiatry. 2022;
        • Putnick D.L.
        • Bornstein M.H.
        Measurement invariance conventions and reporting: The state of the art and future directions for psychological research.
        Dev Rev. 2016; 41: 71-90
        • Mac Giollabhui N.
        • Ng T.H.
        • Ellman L.M.
        • Alloy L.B.
        The longitudinal associations of inflammatory biomarkers and depression revisited: Systematic review, meta-analysis, and meta-regression.
        Mol Psychiatry. 2020; : 1-13
        • Moriarity D.P.
        • Alloy L.B.
        Back to basics: The importance of measurement properties in biological psychiatry.
        Neurosci Biobehav Rev. 2021; 123: 72-82
        • Segerstrom S.C.
        • Boggero I.A.
        Expected Estimation Errors in Studies of the Cortisol Awakening Response: A Simulation.
        Psychosom Med. 2020; 82: 751-756
        • Moriarity D.P.
        • Kautz M.M.
        • Mac Giollabhui N.
        • Klugman J.
        • Coe C.L.
        • Ellman L.M.
        • et al.
        Bidirectional associations between inflammatory biomarkers and depressive symptoms in adolescents: Potential causal relationships.
        Clin Psychol Sci. 2020; 8: 690-703
        • Moriarity D.P.
        • Alloy L.B.
        Beyond diagnoses and total symptom scores: Diversifying the level of analysis in psychoneuroimmunology research.
        Brain Behav Immun. 2020; 89: 1-2
        • Graham-Engeland J.E.
        • Sin N.L.
        • Smyth J.M.
        • Jones D.R.
        • Knight E.L.
        • Sliwinski M.J.
        • et al.
        Negative and positive affect as predictors of inflammation: Timing matters.
        Brain Behav Immun. 2018; 74: 222-230
      11. Rodríguez MR, Nuevo R, Chatterji S, Ayuso-mateos JL (2012): Definitions and factors associated with subthreshold depressive conditions : a systematic review.

      12. Sherbourne C, Ph D, Duan N, Ph D, Unützer J, Miranda J, et al. (n.d.): Quality Improvement for Depression in Primary Care : Do Patients With Subthreshold Depression Benefit in the Long Run ? 1149–1157.