Research ArticleBIOMARKERS

Distinct plasma immune signatures in ME/CFS are present early in the course of illness

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Science Advances  27 Feb 2015:
Vol. 1, no. 1, e1400121
DOI: 10.1126/sciadv.1400121
  • Fig. 1 Comparison of plasma cytokine levels in short-duration ME/CFS, long-duration ME/CFS, and control subjects.

    (A) Proinflammatory cytokines. (B) Anti-inflammatory cytokines. The means ± SEM for each cytokine are shown. Only cytokines meeting significance criteria (P < 0.05) in either the one-way or the two-way GLM are represented. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001 by two-sample t-test comparisons.

  • Fig. 2 Network cytokine-cytokine associations differ for short-duration versus long-duration ME/CFS versus control subjects.

    (A to C) Network diagrams for short-duration ME/CFS subjects (A, n = 52), long-duration ME/CFS subjects (B, n = 246), and healthy controls (C, n = 348). Network diagrams of the 51 measured cytokines were created in NodeXL (http://nodexl.codeplex.com) using a 0.01 family-wise false discovery rate (FDR) to adjust for multiple comparisons (A, short-duration group, P = 0.0065; B, long-duration group, P = 0.0081; C, control group, P = 0.0075). Red lines (edges) indicate negative correlations, and gray lines indicate positive cytokine-cytokine correlations with associated P values that fall below the corrected P value criterion for each group. Note that whereas CD40L drives most of the inverse relationships with other immune molecules in both the long-duration ME/CFS and the control groups, CD40L is only related to five other cytokines in the short-duration ME/CFS group, and only one of these associations is negative (inverse relationship with IL-12p40). Similarly, PDGFBB is a negative driver of many other cytokines in both long-duration ME/CFS and control subjects, but shows no negative correlations with other cytokines in the short-duration subset.

  • Fig. 3 CART analysis of cytokine and clinical predictors in subjects with short- and long-duration ME/CFS.

    The CART decision tree machine learning method was applied to plasma cytokine and clinical covariate data to derive predictors associated with ME/CFS of short (≤3 years, n = 52) versus long (>3 years, n = 246) duration. Predictor variables and cutoffs at each of the nodes in the decision tree are those with the maximum capacity to differentiate between the different levels of the dependent variable (here, short versus long duration of illness). Resulting cytokine classifiers are highly dependent on subject age within both the short-duration and long-duration ME/CFS subgroups, but predictor patterns are shown to vary differently with age across different cytokines. These data provide evidence that cytokine differences are not solely due to the older mean age of the long-duration ME/CFS subgroup.

  • Table 1 Characteristics of study population.
    VariableAll ME/CFS
    (n = 298)
    Short-duration
    ME/CFS
    (≤3 years)
    (n = 52)
    Long-duration
    ME/CFS
    (>3 years)
    (n = 246)
    Control
    (n = 348)
    All ME/CFS
    versus control
    Short- versus
    long-duration
    ME/CFS
    versus control
    P*P
    Sex, n (%)0.800.95
      Female220 (73.8)39 (75.0)181 (73.6)260 (74.7)
      Male78 (26.2)13 (25.0)65 (26.4)88 (25.3)
    Age [mean (SD)]48.5 (12.4)40.5 (13.6)50.2 (11.4)48.5 (12.0)0.95<0.0001
    Illness duration, years [mean (SD)]13.2 (9.2)1.7 (0.8)15.6 (8.2)
    MFI mental fatigue subscale score [mean (SD)]15.3 (3.6)15.2 (3.7)15.3 (3.6)6.2 (2.7)§<0.0001<0.0001
    Race, n (%)0.540.77
      White292 (98.0)52 (100.0)240 (97.6)337 (96.8)
      African American1 (0.3)0 (0.0)1 (0.4)5 (1.4)
      Asian3 (1.0)0 (0.0)3 (1.2)4 (1.1)
      Other2 (0.7)0 (0.0)2 (0.8)2 (0.6)
    Site, n (%)0.800.22
      Boston, MA54 (18.1)4 (7.7)50 (20.3)55 (15.8)
      Miami, FL57 (19.1)9 (17.3)48 (19.5)67 (19.3)
      New York, NY67 (22.5)15 (28.8)52 (21.1)72 (20.7)
      Palo Alto, CA23 (7.7)1 (1.9)22 (8.9)23 (6.6)
      Salt Lake City, UT46 (15.4)11 (21.2)35 (14.2)65 (18.7)
      Sierra, NV51 (17.1)12 (23.1)39 (15.9)66 (19.0)
    Months of sample acquisition, n (%)||0.02<0.0001**
      January to March77 (25.9)11 (21.2)66 (26.9)95 (27.3)
      April to June72 (24.2)17 (32.7)55 (22.4)90 (25.9)
      July to September26 (8.8)11 (21.2)15 (6.1)53 (15.2)
      October to December122 (41.1)13 (25.0)109 (44.5)110 (31.6)

    *Sex, race, site, and months of sample acquisition, χ2 test; age and MFI, Kruskal-Wallis test (three-group comparisons) and Mann-Whitney U tests (two-group comparisons).

    †Significant intergroup comparisons for age: short versus long duration and short duration versus control, both P < 0.0001.

    n = 238 (MFI scores missing for 8 long-duration subjects).

    §n = 341 (MFI scores missing for 7 control subjects).

    ¶Significant intergroup comparisons for MFI subscale: short duration versus control and long duration versus control, both P < 0.0001.

    ||Blood draw date missing for one ME/CFS case.

    **Significant intergroup comparisons for months of sample acquisition: short versus long duration, P = 0.001.

    • Table 2 Final logistic regression model for association of plasma cytokines and covariates with short-duration versus long-duration ME/CFS.

      Final model includes cytokines meeting LASSO and/or PCA/PLS criteria (see Materials and Methods and Supplementary Materials and Methods). Bold text indicates P values <0.05.

      VariableOR95% CIP
      Age0.9530.926–0.9810.001
      Sex0.6690.296–1.5120.334
      IL-12p401.5011.075–2.0960.017
      IL-12p700.7830.650–0.9420.010
      IL-17A0.9880.866–1.1270.857
      IFNγ104.7776.975–1574.0210.001
      TNFα (TNFSF2)0.8660.765–0.9800.023
      sFasL0.9810.856–1.1260.789
      CCL11 (eotaxin)0.9660.929–1.0040.075
      CSF1 (M-CSF)1.0680.901–1.2670.448
      CSF2 (GM-CSF)0.9700.947–0.9950.017
      PDGFBB0.9980.994–1.0020.370

    Supplementary Materials

    • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/1/1/e1400121/DC1

      Materials and Methods

      Table S1. Comparison of plasma immune analytes in ME/CFS subjects versus controls.

      Table S2. Comparison of plasma immune analytes in ME/CFS subjects versus controls.

      Table S3. Comparison of plasma immune markers in ME/CFS subjects versus controls.

      Table S4. Comparison of plasma immune analytes in short-duration versus long-duration ME/CFS subjects versus controls.

      Table S5. Comparison of plasma immune analytes in short-duration versus long-duration ME/CFS subjects versus controls.

      Table S6. Comparison of plasma immune markers in short-duration versus long-duration ME/CFS versus controls.

      Table S7. Spearman correlations of levels of plasma immune markers with duration of illness in ME/CFS.

      Table S8. Feature selection data for logistic regression predicting short-duration versus long-duration ME/CFS.

      Reference (73)

    • Supplementary Materials

      This PDF file includes:

      • Materials and Methods
      • Table S1. Comparison of plasma immune analytes in ME/CFS subjects versus controls.
      • Table S2. Comparison of plasma immune analytes in ME/CFS subjects versus controls.
      • Table S3. Comparison of plasma immune markers in ME/CFS subjects versus controls.
      • Table S4. Comparison of plasma immune analytes in short-duration versus longduration ME/CFS subjects versus controls.
      • Table S5. Comparison of plasma immune analytes in short-duration versus longduration ME/CFS subjects versus controls.
      • Table S6. Comparison of plasma immune markers in short-duration versus longduration ME/CFS versus controls.
      • Table S7. Spearman correlations of levels of plasma immune markers with duration of illness in ME/CFS.
      • Table S8. Feature selection data for logistic regression predicting short-duration versus longduration ME/CFS.
      • Reference (73)

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