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. 2016 Jul 14;6(10):e00516. doi: 10.1002/brb3.516

Immunomodulation of inflammatory leukocyte markers during intravenous immunoglobulin treatment associated with clinical efficacy in chronic inflammatory demyelinating polyradiculoneuropathy

Wayne B Dyer 1,2,✉, Joanne C G Tan 1,2, Timothy Day 3,4, Lynette Kiers 4, Matthew C Kiernan 2,5, Con Yiannikas 6, Stephen Reddel 2,7, Karl Ng 2,8, Phillip Mondy 1, Peta M Dennington 1, Melinda M Dean 9, Halina M Trist 10, Cristobal dos Remedios 2, P Mark Hogarth 10, Steve Vucic 2,11, David O Irving 1,12
PMCID: PMC5064330  PMID: 27781132

Abstract

Objective

The objective of the study was to profile leukocyte markers modulated during intravenous immunoglobulin (IVIg) treatment, and to identify markers and immune pathways associated with clinical efficacy of IVIg for chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) with potential for monitoring treatment efficacy.

Methods

Response to IVIg treatment in newly diagnosed IVIg‐naïve and established IVIg‐experienced patients was assessed by changes in expression of inflammatory leukocyte markers by flow cytometry. The adjusted INCAT disability and Medical Research Council sum scores defined clinical response.

Results

Intravenous immunoglobulin modulated immunopathogenic pathways associated with inflammatory disease in CIDP. Leukocyte markers of clinical efficacy included reduced CD185+ follicular helper T cells, increased regulatory markers (CD23 and CD72) on B cells, and reduction in the circulating inflammatory CD16+ myeloid dendritic cell (mDC) population and concomitant increase in CD62L and CD195 defining a less inflammatory lymphoid homing mDC phenotype. A decline in inflammatory CD16+ dendritic cells was associated with clinical improvement or stability, and correlated with magnitude of improvement in neurological assessment scores, but did not predict relapse. IVIg also induced a nonspecific improvement in regulatory and reduced inflammatory markers not associated with clinical response.

Conclusions

Clinically effective IVIg modulated inflammatory and regulatory pathways associated with ongoing control or resolution of CIDP disease. Some of these markers have potential for monitoring outcome.

Keywords: autoimmune neuropathies, chronic inflammatory demyelinating polyradiculoneuropathy, dendritic cells, disease pathways, Fc‐gamma receptors, immunophenotyping, intravenous immunoglobulin G

1. Introduction

Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is an immunologically heterogeneous autoimmune inflammatory disease resulting in peripheral nerve demyelination, causing profound disability in more than 50% of cases (Franssen & Straver, 2014; Mathey et al., 2015). High‐dose intravenous immunoglobulin (IVIg), with a superior safety profile to steroids (Dalakas, 2012), is a preferred first‐line treatment with established evidence of efficacy (Hughes et al., 2008). The kinetics of response to IVIg in CIDP is similar to plasma exchange (Dalakas, 2012) and is faster than that reported for corticosteroids (Van den Bergh et al., 2010). Short‐term prednisolone or pulsed dexamethasone may induce long‐term remission (Eftimov, Vermeulen, van Doorn, Brusse, & van Schaik, 2012), whereas IVIg does not eliminate the underlying cause of disease and ongoing IVIg is required to prevent relapse. Individual optimization of IVIg dosing is required because of individual rates of IgG catabolism in order to achieve a pharmacokinetic profile supporting treatment efficacy (Kuitwaard et al., 2013; Rajabally, Wong, & Kearney, 2013). To accommodate patient‐specific metabolism of IVIg, early high‐dose IVIg is recommended for initial recovery followed by titration to the minimal effective dose (Mathey & Pollard, 2013), whereas low‐dose initial treatment may be insufficient to prevent irreversible axonal loss in some CIDP variants (Dalakas, 2011, 2012; Mathey & Pollard, 2013). However, there are no definitive strategies to predict the optimal IVIg dose nor the response to treatment, suggesting frequent monitoring is required to establish optimal treatment in new patients.

Immunomodulatory effects of IVIg have been observed across diverse leukocyte populations, including immunopathogenic disease pathways characteristic of CIDP (Dalakas, 2011; Ephrem et al., 2005; Mathey & Pollard, 2013; Mathey et al., 2015). Based on preliminary phenotyping of activated leukocytes cultured with IVIg, we hypothesized that biomarkers of efficacy of IVIg may be found on multiple leukocyte populations detected in peripheral blood. This study reports immunophenotyping of major leukocyte populations aimed at identifying changes in leukocyte surface marker expression during IVIg treatment. Markers altered by IVIg treatment were then tested for association with clinical efficacy. The data provide evidence that immune phenotyping before and after IVIg treatment can be used to distinguish responders from nonresponders, and suggest targeting‐specific markers and pathways for monitoring clinical response to IVIg in CIDP is feasible.

2. Methods

2.1. Ethical review

Recruitment of CIDP patients in New South Wales was approved by the Sydney Local Health District (RPAH Zone) HREC, and in Victoria by individual institutional HRECs. All study participants gave informed consent.

2.2. CIDP patients

Newly diagnosed (IVIg‐naïve) patients (n = 7) and established (IVIg‐experienced) patients (n = 14) were examined over the course of two consecutive IVIg treatment cycles. Diagnosis was by clinical and electrophysiological criteria (typical or atypical, sensory and motor, pure motor, or sensory ataxic) according to European Federation of Neurological Societies/Peripheral Nerve Society guidelines (Van den Bergh et al., 2010). Inclusion and exclusion criteria for newly diagnosed CIDP were as used for the ICE trial (Hughes et al., 2008), excepting patient N9 with sensory CIDP. One patient (E14) received low‐dose prednisolone (12 mg/day) and methotrexate (20 mg/week); no other patient received steroids.

2.3. IVIg treatment

The two treatment cycles were included, according to patient group: (1) induction and initial maintenance cycles in newly diagnosed patients and (2) two maintenance cycles in patients on established dose‐titrated regimens. Standard‐of‐care IVIg induction dosing was 2 g/kg over 3–5 consecutive days; individually optimized maintenance doses ranged from 0.4 to 1 g/kg every 2–4 weeks according to the Australian guidelines (National IVIg Criteria Review Working Group, 2012).

2.4. Blood collection and clinical assessment

Blood samples were collected prior to IVIg infusion (day 0) and on day 7 during each cycle, and leukocyte marker expression was quantified by flow cytometry. Clinical scores were measured at the start and end of each treatment cycle. For the adjusted INCAT disability score (Hughes et al., 2001), a clinically meaningful change was defined as one point (change between 0 and 1 for upper limb function was not clinically significant in the adjusted INCAT scale). For the Medical Research Council (MRC) sum score (Kleyweg, van der Meche, & Schmitz, 1991), a two‐point change was determined to be clinically meaningful. Response in newly diagnosed patients was defined as at least 1 INCAT point improvement during the induction cycle and stable or improved in the second. Patient N9, with a predominantly sensory deficit, was also assessed by the INCAT sensory sum score (Merkies, Schmitz, van der Meche, & van Doorn, 2000). Patients responding to established IVIg regimens were scrutinized for response versus relapse during individual treatment cycles, according to stable versus a clinically meaningful deterioration in either neurological score as defined above.

2.5. Full blood counts and flow cytometry panels

Full blood counts were performed on a CellDyn Ruby automated counter (Abbott Diagnostics, Lane Cove, NSW, Australia) using EDTA‐anticoagulated blood. Whole blood flow cytometry was performed on heparinized blood. Antibody clones chosen for the leukocyte markers are listed in Table 3, and all flow cytometry reagents were sourced from BD Biosciences (North Ryde, NSW, Australia) unless indicated. A large number of markers were screened in order to identify potential changes in population and functional markers, with the expectation that only a few markers would have changes detected in peripheral blood. Flow cytometry was performed by two scientists at a single site using the same flow cytometer and standardized procedures. Antibodies were incubated with blood (100 μL/test) for 15 min before treating with FacsLyse. Tubes for intracellular markers in Treg cells were treated with FacsPerm, washed, and incubated with antibodies for 30 min. Washed leukocytes were run on a BD FACS Canto II, with appropriate compensation settings. Raw.fcs files were analyzed with Flow‐Jo software (Tree Star Inc, Ashland, OR, USA), gates were set against appropriate isotype controls. Marker expression refers to % positive cells in the parent leukocyte population.

Table 3.

Leukocyte populations and effect of intravenous immunoglobulin (IVIg) treatment on surface marker expression

Leukocyte population (phenotype) Investigational markers Mab clone Changed in marker expressiona
T cells (CD45+CD3+CD4±) CD4+ CD4−
CD25 M‐A251 0.819 0.330
CD26 M‐A261 1.000 1.000
CD27 M‐T271 1.000 0.750
CD28 CD28.2 0.160 0.164
CD38 HIT2 0.895 0.090
CD69 L78 0.055 0.055
CD71 M‐A712 0.313 0.742
CD95 CX2 0.755 0.319
CD103 Ber‐ACT8 0.844 0.469
CD120b hTNFR‐M1 0.859 0.190
CD184 12G5 0.335 0.516
CD185 b 51505 0.042 0.213 Decrease
CD195 2D7/CCR5 0.960 0.402
CD197 150503 0.282 0.013 Decrease
Regulatory T cells (CD45+CD4+CD25HI CD127LO) Total population surface:
CD62L DREG‐56 0.192
CD184 12G5 0.034 Decrease
CD195 2D7/CCR5 0.140
HLA‐DR G46‐6 0.011 Increase
Intracellular
CD152 BNI3 0.470
FoxP3 259D/C7 0.110
TGFβ 9016 0.695
Naïve and memory B cells (CD19+ CD27±) Naïve Memory
CD23 M‐L233 0.0097 0.976 Increase
CD32/32b d FLI8.26/X63 0.012 0.0004 Decrease
CD32a IV 0.899 0.577
CD40 5C3 0.967 0.095
CD69 L78 0.599 0.969
CD70 Ki‐24 0.898 0.247
CD72 J4‐117 0.007 0.375 Increase
CD80 L307.4 0.641 0.358
CD86 2331 FUN‐1 0.979 0.360
HLA‐DR G46‐6 0.054 0.437
Myeloid dendritic cells (CD45+HLA‐DR+CD11c+ lineage‐neg)e CD16 3G8 0.0017 Decrease
CD32/32ad FLI8.26/IV.3 0.468
CD32b X63 0.946
CD40 5C3
CD62L DREG‐56 0.0006 Increase
CD64 10.1 0.368
CD83 HB15e 0.091
CD86 2331 FUN‐1 0.814
CD184 12G5 0.995
CD195 2D7/CCR5 0.0077 Increase
CD300f UP‐D2 0.356
Monocytes (CD45+CD14+) CD16 B73.1 0.528
CD32/32a d FLI8.26/IV.3 0.0057 Decrease
CD32b X63 0.050 Decrease
CD38 HIT2 0.149
CD40 5C3 0.179
CD64 10.1 0.229
CD69 L78 0.632
CD80 L307.4 0.549
CD86 2331 FUN‐1 0.843
CD163 GHI/61 0.872
CD184 12G5 0.159
CD195 2D7/CCR5 0.547
CD204b SR‐AI/MSR1 0.139
CD206 19.2 0.484
CD300fc UP‐D2 0.077
HLA‐DR G46‐6 0.547
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aChange in expression was determined by Wilcoxons signed‐rank test; significant changes (p ≤ 0.05) are in bold font.

All antibodies were from BD Pharmingen unless indicated: bR&D Systems; cBiolegend; and dCD32 was replaced during the study with isoform‐specific CD32a and CD32b antibodies produced by HMT and PMH (Ramsland et al., 2011). CD32 expression on dendritic cells and monocytes is equivalent to CD32a, and CD32 on B cells is equivalent to CD32b, and therefore data were pooled where appropriate.

eGated on cells negative for lineage markers CD3, CD14, CD19, CD20, CD34, CD56, and CD66.

2.6. Statistical analysis

Statistical analysis was performed using Prism software (GraphPad, San Diego, CA, USA). An initial screen of markers influenced by IVIg treatment was determined by the Wilcoxon signed‐rank test, with significance defined by p < .05. Markers that changed after IVIg treatment were associated with clinical efficacy after segregating data from responder versus nonresponse/relapse cycles, reporting mean ± SD and paired t tests to determine the magnitude of change in marker expression associated with clinical efficacy. Correction for multiple markers associated with clinical efficacy was applied within each leukocyte population. Difference in maker expression before IVIg treatment between response and relapse cycles was determined by two‐tailed Mann–Whitney test. Association between change in marker expression and clinical outcome used Fisher's exact test. Association between the magnitude of change in marker expression and change in neurology scores was tested by Spearman's rank correlation coefficient.

3. Results

3.1. Clinical response to IVIg treatment

On the expectation that clinical response could be determined in new CIDP patients after only two IVIg treatment cycles (Hughes et al., 2008), the two initial treatment cycles were used to determine clinical response defined by the disability scores. Two consecutive treatment cycles from patients on established IVIg regimens were studied to compare marker responses with new patients, to determine the stability of markers of clinical response, and to identify markers associated with potential episodes of clinical relapse. Patient details, IVIg regimens, and clinical scores for each treatment cycle are listed in Table 1. Clinically effective IVIg treatment was recorded in 11 of 17 treatment cycles in newly diagnosed and 27 of 32 cycles in established patients. Isolated cycles characterized by clinical relapse were recorded, suggesting that some IVIg doses may have been at the threshold of clinical efficacy in some patients. Clinical response to each treatment cycle was not associated with IVIg dose, pretreatment variables including disability scores, or leukocyte counts (Table 2), although mean lymphocyte count tended to be higher in established patients that relapsed.

Table 1.

Patient details, intravenous immunoglobulin (IVIg) dose, and neurological response for each treatment cycle

Patient Age Gender IVIg regimena Neurological response to IVIgb Observed relapse or nonresponse
Cycle 1 Cycle 2 Clinical score Pre‐IVIg Post cycle 1 Post cycle 2
Newly diagnosed (IVIg‐naïve) patients
N1 43 F 2.0/4 W ND NCATc 3 2 NDd
MRC 52 57
N2 70 M 2.0/4 W 0.4/4 W INCAT 9 5 5
MRC 44 44 44
N3 56 M 2.0/4 W 0.4/4 W INCAT 5 3 4 d Relapse cycle 2
MRC 60 60 60
N4 56 F 2.0/4 W 0.4/4 W INCAT 3 2 1
MRC 55 58 56.5
N5 78 M 2.0/3 W 1.0/3 W INCAT 5 5 5 Nonresponse
MRC 54 54 54
N6 78 M 2.0/3 W 1.0/3 W INCAT 7 2 2
MRC 42 56 56
N7 65 M 2.0/3 W 1.0/3 W INCAT 5 5 4 Cycle 1 nonresponse
MRC 54 54 52
N8 35 M 1.0/4 W 0.4/4 W INCAT 2 3 3 Nonresponse
MRC 59 59 56
N9 75 M 2.0/4 W 0.4/4 W INCAT 1 1 1
MRC 60 60 60
INCAT‐S 8 7 6
Established (IVIg‐experienced) CIDP patients
E1 76 F 0.2/4 W 0.4/4 W INCAT 2 2 1
MRC 56 56 58
E2 68 F 1.0/3 W 1.0/3 W INCAT 3 3 3
MRC 52 52 54
E3 52 M 0.7/4 W 0.7/4 W INCAT 2 1 2 Relapse cycle 2
MRC 60 60 60
E4 77 F 0.4/4 W 0.4/4 W INCAT 1 1 0
MRC 58 60 60
E5 67 F 0.9/4 W 0.9/4 W INCAT 6 6 6 Relapse cycle 2
MRC 44 44 41
E6 67 M 0.4/4 W 0.4/4 W INCAT 2 2 4 Relapse cycle 2
MRC 60 60 60
E7 70 M 0.8/4 W 0.8/4 W INCAT 4 3 3
MRC 46 60 60
E8 76 M 0.4/4 W 0.4/4 W INCAT 6 5 5
MRC 42 52 56
E9 67 M 0.8/3 W 0.8/3 W INCAT 2 2 2
MRC 56 57 58
E10 73 F 1.0/3 W 1.0/3 W INCAT 2 2 2
MRC 44 46 46
E11 37 F 1.0/3 W 1.0/3 W INCAT 3 3 3
MRC 52 54 58
E12 80 M 0.4/4 W 0.4/4 W INCAT 2 2 2
MRC 54 56 56
E13 66 M 0.4/2 W 0.4/2 W INCAT 3 3 3 Relapse cycle 1
MRC 54 50 52
E14 72 M 0.7/3 W 0.7/3 W INCAT 3 3 3 Relapse cycle 2
MRC 54 54 52
E15 70 M 0.4/4 W 0.4/4 W INCAT 3 3 3
MRC 59 59 59
E16 52 M 0.4/4 W 0.4/4 W INCAT 2 2 1
MRC 60 60 60
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ND, second treatment cycle not given.

a

IVIg dose (g/kg) and cycle length in weeks (W).

b

Neurological scores that defined relapse or nonresponse are given in bold.

c

INCAT disability score (0–10; 0 = normal function), MRC sum score (max. 60 = normal function), and INCAT‐S (sensory sum score) (0–20; 0 = normal function).

d

Missing data: N1 withdrew from the study after the first cycle and blood samples were not collected from the second cycle of N3.

Table 2.

Pretreatment variables, disability scores, and leukocyte counts were not associated with clinical response

Pretreatment variables Newly diagnosed (IVIg‐naïve) CIDP Established (IVIg‐experienced) CIDP
Responsea Nonresponsea p a Response Relapse p
IVIg cycles (n) 11 6 27 5
IVIg dose 1.35 ± 0.73 1.35 ± 0.79 1.000 0.59 ± 0.26 0.61 ± 0.22 .880
Steroid use Nil (Patient E14: prednisolone 12 mg/day)
Age at treatment 66.1 ± 9.4 69.3 ± 10.8 .641 68.0 ± 11.6 64.8 ± 7.5 .415
INCAT disability 4.6 ± 2.4 4.5 ± 1.0 .903 2.8 ± 1.3 3.0 ± 1.9 .815
MRC sum score 51.6 ± 7.1 55.5 ± 3.0 .216 53.0 ± 5.5 54.4 ± 6.6 .692
Lymphocytes (109/L) 1.77 ± 0.32 1.64 ± 0.64 .713 2.03 ± 0.81 3.07 ± 0.95 .070
Monocytes (109/L) 0.54 ± 0.13 0.71 ± 0.48 .522 0.64 ± 0.45 0.79 ± 0.53 .580
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a

Mean ± SD and Mann–Whitney test.

3.2. Leukocyte markers influenced by IVIg treatment

The effect of IVIg treatment on circulating leukocyte populations was screened across a wide range of surface antigens representing both subpopulation and functional markers. Multiple redundant markers were tested because it was not known which would be detectable in peripheral blood during an in vivo response to IVIg, compared to our preliminary data from cultured leukocytes. For example, changed expression of CD25, CD38, CD69, CD71, and CD95 were identified after in vitro T‐cell activation and subsequent exposure to IVIg. Therefore, only one or two robust markers representing T‐cell responses, identified by the initial screen of response to IVIg, were needed for evaluation of clinical efficacy of IVIg treatment. Despite broad changes in markers representing diverse leukocyte populations in our preliminary in vitro cultures, only a few markers changed in peripheral blood sampled after IVIg treatment (Table 3). However, changes in marker expression 7 days after IVIg treatment, measured during two treatment cycles per patient, were found in each major leukocyte population. These changes included decreased follicular helper T cells (CD185+ CD4 T cells), increased Treg cell circulation (reduced CD184) and increased activation (HLA‐DR), and naïve B cells with increased inhibitory and regulatory markers (CD23+ and CD72+), but reduced inhibitory CD32b+ B cells. IVIg treatment resulted in a decrease in the inflammatory CD16+ myeloid dendritic cell (mDC) population and a corresponding increase in markers defining a noninflammatory mDC population (CD62L and CD195), whereas monocytes responded with reduced CD32a and CD32b expression.

The rationale to analyze both newly treated and patients on established IVIg regimens together was the need to first identify markers influenced by IVIg, and also IVIg treatment is required to maintain clinical effect through frequent modulation of pathogenic processes. After segregating responder from nonresponse/relapse data, markers associated with clinical efficacy were determined according to increased significance of association (lower p values) compared with the combined data or opposing direction of change in marker expression between responder and nonresponse/relapse cycles. From the 13 markers found in 7 leukocyte populations that were influenced by IVIg treatment, only 6 markers were specifically associated with clinical efficacy of IVIg treatment in CIDP (Table 4). Correction for multiple testing in these markers using Bonferroni correction within each leukocyte population resulted in an adjusted level of significance, indicated in Table 4. If a conservative correction was based on all 13 markers, the adjusted level required for significance was p = .0038, and only four markers remained significant (Table 4). We decided to apply Bonferroni correction within leukocyte populations, because it is immunologically implausible to classify follicular helper T cells and CD16+ mDCs as linked variables, whereas CD16, CD62L, and CD195 were linked markers on mDCs and required appropriate correction. These markers associated with clinical efficacy signified a change away from an inflammatory profile. But none of these markers were capable of predicting clinical outcome before IVIg treatment. Baseline CD184 expression on Treg cells was higher in nonresponders, but this marker was not specifically associated with clinical efficacy (Table 4).

Table 4.

Effect of intravenous immunoglobulin (IVIg) treatment on leukocyte populations and markers associated with clinical efficacy in chronic inflammatory demyelinating polyradiculoneuropathy

Population Marker Wilcoxon testa Response to IVIg (all patients) Responders (clinical efficacy) Nonresponse/relapse Pre‐IVIg predictor (response vs. relapse)cMann–Whitney
Pre‐IVIg Post IVIg Paired t testb Pre‐IVIg Post IVIg Pairedt test Pre‐IVIg Post IVIg Pairedt test
CD4T cells CD185 0.042 19.2 ± 7.4 17.5 ± 7.3 0.013 19.4 ± 8.0 17.2 ± 7.9 0.008 d 18.4 ± 4.8 18.8 ± 4.1 0.645 0.616
CD8T cells CD197 0.013 27.7 ± 14.7 25.4 ± 14.8 0.020 27.6 ± 15.2 25.9 ± 15.9 0.120 28.3 ± 13.5 23.5 ± 10.1 0.059 0.885
Tregs CD184 0.034 64.6 ± 19.6 59.0 ± 20.8 0.033 61.1 ± 20.8 55.9 ± 20.4 0.097 74.7 ± 12.0 68.1 ± 20.3 0.190 0.029
HLA‐DR 0.011 33.8 ± 14.7 36.1 ± 13.5 0.016 34.0 ± 15.1 35.9 ± 13.6 1.000 33.2 ± 14.5 36.4 ± 13.9 0.026 0.914
NaïveB cells CD23 0.010 54.8 ± 23.9 60.3 ± 19.6 0.008 54.2 ± 25.0 61.6 ± 20.8 0.0009* 56.6 ± 20.6 55.7 ± 14.8 0.884 0.811
CD72 0.007 84.2 ± 12.9 86.1 ± 11.4 0.159 83.9 ± 13.2 87.3 ± 11.3 0.010 85.4 ± 12.4 86.1 ± 11.6 0.426 0.739
CD32b 0.020 43.0 ± 20.3 36.6 ± 22.5 0.012 43.2 ± 20.4 36.3 ± 22.7 0.031 42.4 ± 19.6 37.3 ± 23.1 0.202 0.918
MemoryB cells CD32b 0.0002 54.0 ± 21.7 44.8 ± 24.5 0.0004 55.1 ± 22.2 46.9 ± 25.4 0.002 49.9 ± 20.3 37.6 ± 20.6 0.082 0.521
Myeloid dendritic cells CD16 0.002 57.1 ± 18.1 48.5 ± 20.9 0.0004 58.0 ± 18.4 46.4 ± 21.7 <0.00001* 53.8 ± 17.2 56.5 ± 16.0 0.433 0.500
CD62L 0.0006 26.0 ± 14.6 32.5 ± 15.8 0.0003 27.4 ± 15.4 35.0 ± 16.7 0.0005* 20.7 ± 10.1 23.4 ± 6.7 0.315 0.117
CD195 0.008 13.1 ± 11.1 17.5 ± 10.3 0.002 13.4 ± 10.7 18.8 ± 14.8 0.001* 12.1 ± 13.0 12.7 ± 10.3 0.823 0.777
Monocytes CD32a 0.006 74.0 ± 30.9 67.0 ± 35.9 0.014 75.4 ± 29.8 67.8 ± 35.8 0.026 69.8 ± 35.1 64.5 ± 37.8 0.338 0.657
CD32b 0.050 50.8 ± 38.9 40.7 ± 36.7 0.079 53.7 ± 36.9 38.1 ± 36.5 0.032 42.2 ± 47.9 48.7 ± 40.5 0.148 0.642
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a

Significance of paired data based on the direction of change from initial screen of IVIg response.

b

Significance of paired data based on the mean difference in expression before and after treatment.

c

Expression of markers before IVIg treatment were compared (responders vs. nonresponders/relapse) to identify any markers capable of predicting clinical response.

d

Correction for multiple testing according to Bonferroni was based on the number of markers analyzed in each leukocyte population (two markers per population: p = .025; three markers per population: p = .017; conservative correction for all 13 markers: p = .0038). Bold markers were associated with clinical efficacy and passed correction at the population level; an asterisk identified markers that passed conservative Bonferroni correction.

3.3. Decreased CD16+ mDC population is associated with clinical outcome

We next investigated the suitability of these markers to provide early indication of outcome from a treatment cycle, aimed at monitoring efficacy when comparing treatment options, including dose titration. Six markers associated with clinical efficacy were observed during two treatment cycles per patient. A single treatment cycle that defined clinical outcome for each patient was selected (the relapse cycle was chosen in response‐discordant patients), and increase versus decrease in marker expression was tested for predicting clinical outcome measured at the end of that cycle (Fisher's exact test). Of these six markers, only CD16+ mDCs were directly associated with clinical outcome using Fisher's exact test for sensitivity and specificity (Fig. 1). Decreased CD16+ mDCs in responders provided sensitivity for predicting outcome (100%; 95% CI = 80.5–100), but specificity was weak (Fig. 1B), also driving down expression in some relapsing patients. However, the magnitude of decreased CD16+ mDCs correlated with improved neurological disability scores (MRC and INCAT; Fig. 1C). The MRC sum score defined relapse in established patients, whereas the INCAT generally defined nonresponse in new patients (Table 1).

Figure 1.

Figure 1

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Decreased CD16+ myeloid dendritic cell population after intravenous immunoglobulin (IVIg) was associated with clinical efficacy. (A) Change in CD16+ mDCs during the treatment cycle that defined response from relapse or nonresponse in each patient. (B) Predictability of decreased CD16+ mDCs on clinical outcome was supported by sensitivity but not specificity (Fisher's exact test). (C) The magnitude of CD16 downregulation on mDCs correlated with increased MRC sum scores, and decreased INCAT disability scores (Spearman's rank correlation). Decreased CD16 expression was associated with loss of the HLA‐DR low CD16+ mDC population after IVIg in a responder patient (D), but retention of this population after IVIg in a relapsing patient (E). The HLA − DR low CD11c+ population is outlined by the elliptical gate in the middle panels, and the CD16/HLA‐DR gate was set according to this HLA‐DR low population and isotype control for CD16. The pre‐IVIg phenotype of this HLA‐DR low CD11c+ population was the same for both responding patient (F) and relapsing patient (G), which defined an activated mature but circulating inflammatory mDC population that declined after clinically effective therapy

The immunological relevance of reduced CD16+ mDCs was further investigated. The CD16+ mDC population was also characterized as HLA‐DRlow. Stable clinical response was associated with loss of this population after IVIg, along with a reduced proportion of HLA‐DR++ cells expressing CD16 (Fig. 1D). Clinical relapse was associated with either no change or an increase in the CD16+HLA‐DRlow population (Fig. 1E). Phenotypic profiling of the CD16+HLA‐DRlow and the CD16−HLA‐DR++ populations suggested that clinically effective IVIg treatment decreased an activated (CD40+CD86+), nonlymphoid (CD62L−, CD195−, CD197−) circulating population that expressed activating Fcγ receptors CD16 and CD32a, but not the inhibitory CD32b. This CD16+HLA‐DRlow population lacked the activating FcγR CD64 associated with monocyte‐derived DCs. Although decreased after clinically effective IVIg treatment, this CD16+ mDC population cycled back to baseline levels measured immediately prior to the following treatment cycle. This suggests de novo regeneration of new inflammatory mDCs between treatment cycles is a possible cause of ongoing inflammation in CIDP requiring life‐long IVIg treatment.

4. Discussion

This study confirmed some of the known immunomodulatory action of IVIg on disease pathways of inflammatory neuropathies, and identified markers associated with clinical outcome. Changes in disease pathways associated with clinical efficacy included reduced capacity for autoantibody production associated with decreased follicular helper T cells and increased expression of regulatory and tolerance markers on B cells. A decrease in circulating inflammatory CD16+ mDCs was associated with clinical efficacy. In addition, markers associated with a reduced inflammatory profile, independent of clinical response, may signify the overall nonspecific anti‐inflammatory effects of IVIg which in combination may contribute to clinical efficacy. Although IVIg may induce long‐term immunomodulatory changes, including inhibitory Fcγ receptor expression, or autoreactive T‐cell populations (Klehmet et al., 2015), most of the anti‐inflammatory effects of IVIg observed in our study were short‐lived, suggesting the underlying causes of CIDP are modulated but not removed by IVIg in most patients. It is thought that the transitory effect of IVIg on clinical outcome may be a consequence of catabolism of infused IgG, impacting on direct competition with pathogenic autoantibodies and complement inactivation (Berger, McCallus, & Lin, 2013). The transitory effect of IVIg treatment on markers identified in this study may likewise reflect the decline in IVIg interactions with Fcγ receptors and the downstream regulation of B cell, mDC and follicular helper T‐cell‐mediated responses.

The phenotypic profile of the CD16+HLA‐DRlow mDC population suggests these were mature (CD195−) and inflammatory (CD40+CD86+), but unlike conventional mature mDCs, locked in peripheral circulation with impaired lymphoid migration (CD62L−CD184lowCD197−; Kim & Diamond, 2015; Lutz & Schuler, 2002; Martin‐Fontecha, Lanzavecchia, & Sallusto, 2009; Sallusto et al., 1998). Furthermore, these CD16+HLA‐DRlow mDCs had receptors for inflammatory (CD16, CD32a) but not regulatory (CD32b) antibody interaction. Reduction of this CD16+HLA‐DRlow mDC population resulted in a relative increase of lymph‐node homing markers (CD62L and CD195) in the remaining CD16−HLA‐DR++‐enriched mDC population, conferring reduced inflammatory potential (Wildenberg et al., 2008). The origin of this CD16+HLA‐DRlow population is controversial, some suggesting a monocytic origin (Kim & Diamond, 2015; Randolph, Sanchez‐Schmitz, Liebman, & Schakel, 2002). However, low CD205 expression and lack of CD64 on this population suggest otherwise. Regardless of the source, accumulation between treatment cycles of a circulating activated inflammatory mDC population deficient for lymph‐node homing markers may be a major immunopathogenic pathway of CIDP disease, and depletion of this population may be a critical immunoregulatory action of IVIg. The relative increase in CD195 and CD62L defining the CD16−HLA‐DR++ mDC population after clinically effective IVIg suggests increased lymph‐node homing and reduced peripheral tissue inflammation is another immunoregulatory action of IVIg. However, lack of key homing markers on the CD16+HLA‐DRlow mDC population does not explain removal from circulation after IVIg.

B‐cell activation and generation of autoantibodies are considered critical immunopathogenic pathways in CIDP and other autoimmune neuropathies. Data from this study showed that IVIg increased both regulatory (CD23) and peripheral tolerance (CD72) markers on naïve B cells. The inhibitory Fcγ receptor CD32b was expressed on more memory B cells before IVIg treatment in responders than nonresponders, but was not directly associated with clinical outcome. CD185 expression defines follicular helper T cells with increased homing for B‐cell germinal centers and is elevated in a number of autoimmune diseases (Park et al., 2014). The observed decrease in follicular helper T cells after IVIg may reduce autoantibody production as well as macrophage activation pathways (Schmitt, Bentebibel, & Ueno, 2014; Slight et al., 2013).

Inhibitory Fcγ receptor‐mediated pathways of immunomodulation in B cells and monocytes are considered primary mechanisms of IVIg immunomodulation (Tackenberg et al., 2009), and was confirmed by data from this study. Expression of CD32b decreased after IVIg on both monocytes and memory B cells, as reported on monocytes in IVIg‐treated immune thrombocytopenia (Shimomura et al., 2012). Downregulation of CD32b on B cells may result from increased CD40 ligation (Zhang et al., 2013). Alternatively, an increase in the balance of type‐2 and regulatory cytokines induced by IVIg treatment may promote CD32b expression (Boruchov et al., 2005), and transitory CD32b downregulation observed in this study may be a temporary effect of cytokine neutralization after IVIg infusion.

In searching for biomarkers to monitor and predict outcome of IVIg therapy, an ideal biomarker should be sensitive to changes in IVIg dosing and predict clinical outcome soon after treatment, as measured 7 days after infusion in this study. Useful biomarkers should be able to guide optimal IVIg dosing for new CIDP patients, and provide early warning of relapse when performing dose tapering or testing for IVIg dependence when in remission. The six markers associated with clinical efficacy identified in this study may be suitable for monitoring therapeutic response in combination. They signified a reduced inflammatory profile and correlated with clinical outcome, albeit a temporary change for most markers, reverting toward baseline before the next IVIg infusion. A decreased CD16+ mDC population was associated with response to IVIg and demonstrates the feasibility of using this marker in a test to establish optimal IVIg dosing for new CIDP patients, although specificity was insufficient to predict relapse during dose tapering. Additionally, the small number of patients in this study means that these data cannot be used to guide clinical decisions on IVIg dosing. Confirmation of the critical components of these immunomodulatory pathways may facilitate development of novel therapeutics aimed at replacing this expensive and nonspecific anti‐inflammatory treatment, and such markers may provide the means to test efficacy.

Funding Information

The study was funded by the Australian Red Cross Blood Service. The Australian Government funds the Australian Red Cross Blood Service to provide blood, blood products, and services to the Australian community.

Conflict of Interest

None declared.

Acknowledgments

The authors thank Therese Burke, Kerry Lenton, Prudence Gatt, Eleanor Ramsey and John Carey for patient specimen logistics, Dr Andrew Lim (BD Biosciences) for advice on flow cytometry, Dr Stephen Wright (Australian Red Cross Blood Service) for statistical advice, and the patients who consented to the study. Critical review of the manuscript was provided by Denese Marks, PhD, Alison Gould, PhD, and Janet Wong (Australian Red Cross Blood Service).

Dyer, W. B. , Tan, J. C. G. , Day, T. , Kiers, L. , Kiernan, M. C. , Yiannikas, C. , Reddel, S. , Ng, K. , Mondy, P. , Dennington, P. M. , Dean, M. M. , Trist, H. M. , dos Remedios, C. , Hogarth, P. M. , Vucic, S. and Irving, D. O. (2016), Immunomodulation of inflammatory leukocyte markers during intravenous immunoglobulin treatment associated with clinical efficacy in chronic inflammatory demyelinating polyradiculoneuropathy. Brain and Behavior, 6: 1–11. e00516, doi: 10.1002/brb3.516

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