Aberrant Complement Activation Is Associated With Structural Brain Damage in Multiple Sclerosis

Johanna Oechtering; Sabine Anna Schaedelin; Kerstin Stein; Aleksandra Maleska Maceski; Lester Melie-Garcia; Pascal Benkert; Alessandro Cagol; Selina Leber; Riccardo Galbusera; Esther Ruberte; Wayne Hu; Ferhan Qureshi; Annette Orleth; Lilian Demuth; Eline Willemse; Ingmar Heijnen; Axel Regeniter; Tobias J Derfuss; Bettina Fischer-Barnicol; Lutz Achtnichts; Stefanie Mueller; Robert Hoepner; Patrice H Lalive; Claire Bridel; Marcus D'Souza; Caroline Pot; Renaud A Du Pasquier; Claudio Gobbi; Chiara Zecca; Heinz Wiendl; Johanna Maria Lieb; Christina Lamers; Ludwig Kappos; Marten Trendelenburg; David Leppert; Cristina Granziera; Jens Kuhle; Jan D Lünemann; and the Swiss MS Cohort Study

doi:10.1212/NXI.0000000000200361

. 2025 Jan 3;12(2):e200361. doi: 10.1212/NXI.0000000000200361

Aberrant Complement Activation Is Associated With Structural Brain Damage in Multiple Sclerosis

Johanna Oechtering ^1,², Sabine Anna Schaedelin ^2,³, Kerstin Stein ⁴, Aleksandra Maleska Maceski ^1,², Lester Melie-Garcia ^2,⁵, Pascal Benkert ^2,³, Alessandro Cagol ^2,⁵, Selina Leber ^2,⁵, Riccardo Galbusera ^1,^2,⁵, Esther Ruberte ^2,⁵, Wayne Hu ⁶, Ferhan Qureshi ⁶, Annette Orleth ^1,², Lilian Demuth ^1,², Eline Willemse ^1,², Ingmar Heijnen ⁷, Axel Regeniter ⁸, Tobias J Derfuss ^1,², Bettina Fischer-Barnicol ^1,², Lutz Achtnichts ⁹, Stefanie Mueller ¹⁰, Robert Hoepner ¹¹, Patrice H Lalive ^12,^13,¹⁴, Claire Bridel ¹², Marcus D'Souza ^1,², Caroline Pot ¹⁵, Renaud A Du Pasquier ¹⁵, Claudio Gobbi ^16,¹⁷, Chiara Zecca ^16,¹⁷, Heinz Wiendl ⁴, Johanna Maria Lieb ¹⁸, Christina Lamers ¹⁹, Ludwig Kappos ^1,², Marten Trendelenburg ²⁰, David Leppert ^1,², Cristina Granziera ^1,^2,⁵, Jens Kuhle ^1,^2,^*,^✉, Jan D Lünemann ^4,^*,^✉; and the Swiss MS Cohort Study

¹Department of Neurology, University Hospital and University of Basel;

²Multiple Sclerosis Centre and Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), Departments of Biomedicine and Clinical Research, University Hospital and University of Basel;

³Clinical Trial Unit, Department of Clinical Research, University Hospital Basel, University of Basel, Switzerland;

⁴Department of Neurology with Institute of Translational Neurology, University Hospital 4 Münster, Germany;

⁵Department of Biomedical Engineering, Faculty of Medicine, Translational Imaging in Neurology (ThINk) Basel, University Hospital Basel and University of Basel, Switzerland;

⁶Octave Bioscience, Menlo Park, CA;

⁷Division of Medical Immunology, Laboratory Medicine, University Hospital Basel, Basel;

⁸Medica Laboratory, Zürich;

⁹Department of Neurology, Cantonal Hospital, Aarau;

¹⁰Department of Neurology, Cantonal Hospital St. Gallen;

¹¹Department of Neurology, Inselspital, Bern University Hospital and University of Bern;

¹²Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospital;

¹³Division of Laboratory Medicine, Diagnostic Department, Geneva University Hospital;

¹⁴Department of Pathology and Immunology, Faculty of Medicine, University of Geneva;

¹⁵Division of Neurology, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne;

¹⁶Neurocentre of Southern Switzerland, Multiple Sclerosis Centre, Ospedale Civico;

¹⁷Faculty of Biomedical Sciences, Università della Svizzera Italiana (USI), Lugano;

¹⁸Division of Neuroradiology, University Hospital Basel, Switzerland;

¹⁹Institute for Drug Discovery, Faculty of Medicine, Leipzig University, Germany; and

²⁰Division of Internal Medicine, Department of Biomedicine, University Hospital Basel and Clinical Immunology, University of Basel, Switzerland.

^✉

Correspondence Prof. Kuhle jens.kuhle@usb.ch or Dr. Lünemann jan.luenemann@ukmuenster.de

The Article Processing Charge was funded by the authors.

Submitted and externally peer reviewed. The handling editor was Editor Josep O. Dalmau, MD, PhD, FAAN.

These authors are co-senior authors and contributed equally to this work.

^✉

Corresponding author.

PMCID: PMC11702906 PMID: 39752618

Abstract

Background and Objectives

Levels of activated complement proteins in the CSF are increased in people with multiple sclerosis (MS) and are associated with clinical disease severity. In this study, we determined whether complement activation profiles track with quantitative MRI metrics and liquid biomarkers indicative of disease activity and progression.

Methods

Complement components and activation products (Factor H and I, C1q, C3, C4, C5, Ba, Bb, C3a, C4a, C5a, and sC5b-9) and liquid biomarkers (neurofilament light chain, glial fibrillary acidic protein [GFAP], CXCL-13, CXCL-9, and IL-12b) were quantified in the CSF of 112 patients with clinically isolated syndromes and 127 patients with MS; longitudinal MRIs according to a standardized protocol of the Swiss MS cohort were assessed. We used multivariable models to analyze associations of the 12 complement parameters as individual independent variables and longitudinal brain volumes, T2-weighted (T2w) lesion volumes, contrast-enhancing (CELs) and paramagnetic rim lesions (PRLs), and molecular biomarkers as dependent variables, respectively.

Results

Strongest associations with accelerated brain atrophy were found for C4a: doubling of C4a CSF levels was associated with an additional brain volume loss of −0.24% (95% CI −0.31% to −0.16%; p < 0.0001) per year, followed by Ba and C3a (−0.22% [−0.29% to −0.15%]) and −0.13% ([−0.21 to −0.06]; both p < 0.001). Doubling of C3a, Ba, and C4a levels correlated with 2.2- (1.6–3.0; p < 0.0001), 2.0- (1.3–3.1; p = 0.0038), and 1.8-fold (1.2–2.6; p = 0.0029) increased longitudinal T2w lesion volumes; C3a and Ba were associated with 2.5- (1.4–4.6; p = 0.0022) and 3.3-fold (1.5–7.2; p = 0.0024) higher odds for CELs and 2.6- (1.7–4.0; p < 0.0001) and 2.3-fold (1.3–4.3; p = 0.006) increased PRL incidence rates. C1q, C3a, and C4a were associated with higher GFAP levels, and CXCL-13, CXCL-9, and IL-12b analyses showed consistent patterns with strongest associations for C1q, followed by Ba, C3a, and C4a.

Discussion

Intrathecal complement activation is consistently associated with MRI metrics and liquid biomarkers indicative for MS disease activity and progression. Our results demonstrate that aberrant complement activation is strongly associated with structural brain damage in MS. Therapeutic targeting of the complement system might limit disability accumulation due to MS.

Introduction

In multiple sclerosis (MS), complex immune mechanisms involving T and B cells, antibodies and other humoral factors, activated macrophages, and microglia along with the vulnerability of the target tissue account for the cascade of events that leads to neurodegenerative processes that manifest clinically as progression.¹ Complement components (CCs) and complement activation products (CAPs) in combination with immunoglobulin deposits are present both in the affected gray and white matter of patients with MS, suggesting their pathophysiologic function for tissue damage.^2-5

Previously, conflicting results for plasma and serum levels of individual CC and CAP in persons with MS (when compared with healthy controls) and their associations with surrogate markers of disease state were reported.^6-9 We have recently shown by use of high sensitivity multiplex assays that mainly early cascade CAPs are increased in the CSF, but not plasma, of persons with clinically isolated syndrome (CIS) and MS. CSF CAP levels (C3a, C4a, Ba, and Bb) were highest in individuals with intrathecal IgM synthesis, in line with the fact that the pentameric IgM is the strongest complement-activating immunoglobulin. Accordingly, CAPs were associated with measures of disease severity and neuroaxonal damage.¹⁰

The complement system is increasingly recognized for its multiple physiologic and homeostatic functions, supporting CNS development, maintenance, and tissue remodeling after injury.¹¹ In the context of MS, activated CC might have a “double-edged sword” effect: on the one hand, restoring tissue homeostasis through phagocytic clearance of opsonized myelin degradation products and other debris or on the other hand, promoting tissue injury through amplifying local inflammation and direct complement-mediated damage.¹²

To better understand whether complement activation in MS is associated with structural CNS tissue damage, we investigated associations of CSF CC and CAP with MRI metrics reflecting disease activity, severity, or progression; molecular biomarkers for CNS injury; and complement activation-associated relevant cytokines.^13-15

Methods

Patients, Inclusion Criteria, and Data Collection

CSF samples were obtained from the CSF biobank of the University Hospital Basel, a subset of patients who were prospectively recruited into the Swiss multiple sclerosis cohort (SMSC)¹⁶ between 2012 and 2021. We included all eligible CIS/MS patients with a CSF sample without erythrocyte contamination available. Patients were included with a CIS, relapsing remitting multiple sclerosis (RRMS),¹⁷ secondary progressive multiple sclerosis (SPMS),¹⁸ or primary progressive multiple sclerosis (PPMS).¹⁹ First symptoms were defined as neurologic symptoms that lasted for ≥24 hours without fever, infection, or adverse reaction to a prescribed medication.¹⁹ RRMS had to have experienced at least 2 relapses before the lumbar puncture (LP).¹⁹ Demographic and clinical variables collected included sex, date of birth, patients onset of first symptoms, Expanded Disability Status Scale Score (EDSS) at LP, and disease-modifying treatments history.

Standard Protocol Approvals, Registrations, and Patient Consents

We included patients from the CSF biobank study of the Department of Neurology, University Hospital Basel, which were prospectively recruited into the SMSC. These studies were approved by the local ethical committee, and patients were included after written informed consent.

MRI Data and Analysis

We included all annual brain MRI scans performed prospectively in 1.5 or 3T scanners as part of the SMSC.¹⁶ MRI scans were acquired according to a standardized protocol optimized for a homogeneous signal-to-noise ratio and included precontrast and postcontrast 3D T1-weighted, 1 mm isotropic magnetization-prepared rapid gradient-echo, and 3D 1 mm isotropic fluid-attenuated inversion recovery (FLAIR) images. MRI protocol details are reported in eTable 1. T2-weighted (T2w) lesion volume was calculated automatically on FLAIR images using the multidimensional gated recurrent units algorithm, and results were manually reviewed.²⁰ The presence of contrast-enhancing lesions (CELs) on T1 postcontrast images was evaluated manually. Brain volumetric analysis was performed by a SPM12 toolbox using the lesion-filled T1-weighted image.²¹ Reconstructions were visually assessed for sufficient quality. Brain parenchymal fraction (BPF) is defined as whole-brain volume normalized for total intracranial volume. In those patients with susceptibility-weighted T2* sequences during follow-up, paramagnetic rim lesions (PRLs) were detected as previously described.¹⁴

Samples and Measurements of CC and Activation Products

CSF was centrifuged (400 g for 10 minutes) within 30 minutes of collection, and the supernatant frozen at −80°C. The integrity of the blood-CSF barrier was determined by calculating the CSF/serum ratio for albumin (Q_alb).²² CSF samples were sent to the University Hospital of Münster (Münster, Germany) on dry ice and CAPs and components determined as described before.¹⁰ Briefly, for the quantification of CAP (C4a, C3a, C5a, s-C5b9, Ba, and Bb) and CC (C1q, C4, C3, C5, Factor H and I) levels, samples were thawed on ice and immediately processed. Multiplex ELISAs based on chemiluminescence were performed according to the manufacturer's recommendations (Quidel, San Diego, CA; catalogue number: A900, A917). The mean intra-assay coefficients of variation (CVs) of duplicate determinations for a high-value and low-value quality control (QC) sample, respectively, were as follows: Ba: 1.9%/1.7%; Bb: 2.1%/2.6%; C3a: 0.2%/2.2%; C4a: 5.5%/3.1%; C5a: 4.3%/3.5%; Factor H: 1.1%/2.5%; Factor I: 6.0%/5.2%; s-C5b9: 2.6%/3.6%; C1q: 6.1%/7.9%; C3: 7.4%/3.8%; C4: 5.4%/7.9%; and C5: 5.3%/4.1%. The interassay CVs for the high-value/low-value QC samples, respectively, were for Ba: 5.3%/9.3%; Bb: 2.0%/6.8%; C3a: 18.3%/9.4%; C4a: 6.2%/6.6%; C5a: 4.4%/3.8%; Factor H: 1.9%/9.5%; Factor I: 10.1%/9.9%; s-C5b-9: 5.2%/7.8%; C1q: 13.0%/7.9%; C3: 7.4%/8.8%; C4: 5.2%/9.8%; and C5: 12.8%/8.5%.

Measurements of GFAP Levels

CSF glial fibrillary acidic protein (GFAP) levels were measured in duplicate with the Neurology 2-PLEX B assay (Quanterix, Billerica, MA). The mean intra-assay CV of duplicate determinations for CSF GFAP was 2.3%. The interassay CVs of internal QCs for GFAP were 8.0% (73.6 pg/mL), 6.7% (127.3 pg/mL), and 6.9% (325.9 pg/mL).

Measurements of Cytokines

CXCL-13, CXCL-9, and IL-12b were measured in CSF samples by use of the Octave custom assay, a multiprotein, biomarker assay developed using Olink proximity extension assay methodology.²³ The mean intra-assay CV of duplicate determinations for CXCL-13 was 11.4%, for CXCL-9 5.5% and for IL-12b 17.6%. The interassay CVs of 4 internal quality controls (serum) (QC) for CXCL-13 were 8.9% (52.1 pg/mL), 7.6% (43.0 pg/mL), 8.6% (66.4 pg/mL), and 11.0% (49.1 pg/mL); for CXCL-9: 8.6% (29.1 pg/mL), 7.7% (60.2 pg/mL), 8.8% (107.8 pg/mL), and 9.6% (27.3 pg/mL); and for IL-12b were 8.8% (107.8 pg/mL), 7.8% (126.4 pg/mL), 7.5% (121.2 pg/mL), and 10.2% (75.1 pg/mL).

For data points below the lower limit of quantification (LLOQ) (CXCL-13: n = 57 (23.8%); CXCL-9: 25.5%; IL-12b: 0) a random value between zero and LLOQ was imputed to a uniform distribution, no data points were above upper limit of quantification (eTable 2).

Statistics

Data are presented as median and interquartile range (IQR) and as absolute and relative frequencies in case of categorical data. Statistical analyses were performed using R (version 4.1.2).

Distribution of data was inspected using QQplots. All used CSF and blood parameters (CC, CAP, cytokines, GFAP, and Q_alb) were logarithm (log)-normally distributed. Accordingly, all these parameters were log-transformed before analysis. If these parameters, as well as BPF, served as dependent variable in a linear regression model, a natural log was used. The estimates were then back-transformed before presentation and thus indicate a multiplicative effect. For CC and CAP functioning as independent variables and for covariables, we used a binary logarithm. Accordingly, the presented estimate corresponds to the expected change in the dependent variable if the CC or CAP was doubled.

Associations of CC and CAP With Different Outcome Parameters

Atrophy

Associations of the log-transformed CSF concentrations of each CC or CAP (separate independent variables) with the log-transformed longitudinal BPF at time point of each scan (dependent variable) were analyzed by separate linear mixed models. Time since first scan (independent variable) was included to quantify atrophy, and the association between each CC or CAP and atrophy was modeled as the interaction between these 2 terms. They were adjusted for age at first scan, sex, MRI magnetic field strength (1.5 vs 3T), log-transformed Q_alb, MS subtype (RRMS, SPMS, PPMS vs CIS, respectively), and dominant disease-modifying treatment category during follow-up (platform, orals, monoclonal antibodies vs untreated, respectively, compare eTable 3). Estimates were log-transformed to present them in percentage change, and the resulting multiplicative effect was subtracted −1 and divided by 100.

Longitudinal T2-Weighted Lesion Volumes and CELs

Separate linear mixed-effects models were calculated with the log-transformed CC/CAP levels as individual independent variables and the T2-weighted lesion volumes as dependent variables by including all longitudinal data points, respectively. We adjusted for age, sex, log-transformed Q_alb, disease duration, and dominant treatment categories (platform, orals, monoclonal antibodies vs untreated, respectively) between the respective 2 MRIs during follow-up. For analyzing associations with CELs, separate logistic mixed-effects models with the log-transformed CC/CAP levels as individual independent variables and the occurrence of any CEL as dependent variables were used. These were adjusted for age, sex, log-transformed Q_alb, and active treatment (platform, orals, monoclonal antibodies vs untreated) at the respective MRI.

PRLs

We used separate negative binomial models with log-transformed CC/CAP levels as individual independent variables and the PRL count as dependent variable with adjustment for age at MRI, sex, log-transformed Q_alb, and dominant treatment categories (platform, orals, monoclonal antibodies vs untreated, respectively) during follow-up.

GFAP and Complement Activation-Associated Cytokine Levels

We used separate linear regression models with the 12 log-transformed CC/CAP levels as independent variables and the log-transformed cytokine (CXCL-13, CXCL-9, IL-12b) and GFAP levels as dependent variables, respectively, adjusted for age, sex, log-transformed Q_alb, and treatment category at LP (vs untreated, respectively): platform (glatirameracetate, interferons), orals (fingolimod, dimethylfumarate), and monoclonal antibodies (natalizumab, ocrelizumab, rituximab) (eTable 3).

Data Availability

Data are available on reasonable request.

Results

Patients and Clinical Data

Two hundred thirty-nine patients with CIS/MS met the inclusion criteria. Patients with SPMS were significantly older, had a longer disease duration and higher EDSS scores at LP than CIS/RRMS patients. MRI follow-up data were available in 134 (56.1%) of patients with a median follow-up of 6.9 years and 7 (IQR 5–9) MRIs per patient (Table 1). Concentrations of uncleaved and activated CCs along with complement-associated cytokines and soluble molecules indicative for CNS tissue injury were determined in CSF samples obtained at baseline.

Table 1.

Demographic, Clinical, and Routine CSF Characteristics at Lumbar Puncture and Follow-Up MRI Data

	CIS	RRMS	SPMS	PPMS	All
n	112	90	23	14	239
Demographic and clinical data
Female, n (%)	80 (71.4)	64 (71.1)	13 (56.5)	8 (57.1)	165 (69)
Age at LP (y)	34.4 (26.7–43.8)	38.0 (31.4–48.1)	53.7 (48.9–59.6)	48.5 (46.7–57.8)	38.5 (29.7–49.1)
EDSS at LP	2.0 (1.5–2.5)	2.5 (2.0–3.5)	6.0 (4.0–7.0)	3.5 (3.0–4.0)	2.5 (2.0–3.5)
Untreated, n (%)	111 (99.1)	70 (77.8)	15 (65.2)	13 (92.9)	209 (87.4)
Disease duration at LP (m)	0.6 (0.3–1.8)	56.1 (15.6–91.7)	253.1 (147.0–332.1)	50.0 (15.2–81.3)	7.8 (0.7–67.3)
McDonald criteria 2017 met at LP, n (%)	71 (63.4)	90 (100)	23 (100)	14 (100)	198 (82.8)
CSF data
Cell count (cells/mcl)	4.3 (2.0–9.0)	3.0 (1.0–6.0)	1.0 (0.3–2.2)	1.7 (1.1–2.9)	3.0 (1.3–6.6)
Q_alb	4.5 (3.6–6.4)	5.4 (3.9–7.3)	5.5 (3.8–7.7)	5.0 (4.4–7.2)	5.0 (3.8–6.8)
OCGB^a (%)	90 (80.4)	73 (82.0)	17 (85.0)	11 (78.6)	191 (81.3)
IgG_IF^a (%)	66 (58.9)	53 (59.6)	9 (45.0)	8 (57.1)	136 (57.9)
IgM_IF^a (%)	31 (27.7)	24 (27.0)	2 (10.0)	3 (21.4)	60 (25.5)
IgA_IF^a (%)	5 (4.5)	7 (7.9)	1 (5.0)	1 (7.1)	14 (6.0)
MRI data
MRI follow-up available, n (%)	61 (54.5)	52 (57.8)	13 (56.5)	8 (57.1)	134 (56.1)
Follow-up time MRI (mean, SD, y)	6.9 (3.2)	7.0 (3.2)	7.1 (3.2)	7.2 (4.3)	7.0 (3.2)
MRIs per patient	7 (6, 9.25)	8 (5, 9)	5 (2.75, 8)	6.5 (3.5, 7.25)	7 (5, 9)

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Abbreviations: CIS = clinically isolated syndrome; EDSS = Expanded Disability Status Scale Score; Ig G/M/A_IF = immunoglobulin G/M/A intrathecal fraction; IQR = interquartile range; LP = lumbar puncture; OCGB = oligoclonal IgG bands; PPMS = primary progressive MS; Q_alb = albumin quotient; RRMS = relapsing-remitting MS; SPMS = secondary progressive MS.

Median and IQR are displayed if not mentioned otherwise.

Presence of OCGB or IgG_IF/IgM_IF/IgA_IF.

Atrophy

The most prominent effect on accelerated brain atrophy was found for the complement product C4a, which can be generated through activation of both the classical and lectin pathways: doubling of C4a CSF levels was associated with an independent additional annual reduction of BPF by −0.24% (p < 0.0001) per year. Similar results were found for Ba with a reduction by −0.22% (p < 0.0001), followed by C3a (−0.13%; p = 0.0002) and Bb (−0.12%; p < 0.0001) (Table 2; Figure 1).

Table 2.

Multivariable Associations of CSF Complement Components and Activation Products With MRI Parameters

	Longitudinal brain atrophy (BPF) n = 829 MRIs/120 pat			Longitudinal total T2-weighted lesion volume n = 930 MRIs/128 pat			CE lesions n = 996 MRIs/133 pat			PRLs n = 101 MRIs/pat
	Est (%)	CI	p Value	ME	CI	p Value	OR	CI	p Value	IRR	CI	p Value
C4a	−0.24	−0.31 to −0.16	<1e-04	1.79	1.23–2.60	0.00292	1.81	0.97–3.36	0.0623	1.52	0.94–2.47	0.0906
C4	−0.05	−0.15 to 0.05	0.3607	0.93	0.59–1.46	0.75055	1.46	0.59–3.60	0.4126	0.75	0.44–1.28	0.2896
C3a	−0.13	−0.21 to −0.06	0.00024	2.19	1.58–3.04	<1e-04	2.54	1.40–4.61	0.00224	2.58	1.66–4.03	<0.01
C3	−0.12	−0.16 to −0.07	<1e-04	1.14	0.92–1.41	0.22440	1.26	0.88–1.82	0.2041	1.16	0.90–1.49	0.2605
C5a	−0.07	−0.11 to −0.04	<1e-04	1.16	0.98–1.38	0.07889	1.40	1.03–1.91	0.03323	1.25	1.03–1.52	0.0264
s-C5b9	−0.06	−0.09 to −0.03	<1e-04	1.20	1.04–1.38	0.01415	1.23	0.92–1.64	0.1550	1.17	0.98–1.40	0.0863
C5	−0.07	−0.13 to −0.01	0.0332	0.82	0.56–1.21	0.31617	0.68	0.31–1.49	0.3360	0.59	0.35–1.00	0.0518
Ba	−0.22	−0.29 to −0.15	<1e-04	1.97	1.26–3.08	0.00376	3.32	1.53–7.21	0.00240	2.33	1.27–4.26	<0.01
Bb	−0.12	−0.17 to −0.07	<1e-04	1.15	0.85–1.56	0.35397	1.51	0.89–2.57	0.1263	1.30	0.90–1.86	0.1609
C1q	+0.05	0.10 to 0.19	0.5141	0.78	0.42–1.47	0.44894	0.91	0.31–2.66	0.8674	0.51	0.24–1.10	0.0878
Factor H	−0.13	−0.31 to 0.06	0.1714	1.00	0.35–2.87	0.99970	0.64	0.08–5.28	0.6809	2.85	0.63–12.86	0.173
Factor I	−0.05	−0.13 to 0.03	0.24133	1.17	0.72–1.90	0.51989	0.95	0.41–2.23	0.9121	1.72	0.93–3.19	0.0826

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Abbreviations: BPF = brain parenchymal fraction; CAP = complement activation product; CC = complement component; CE = contrast-enhancing; Est. = estimate; IRR = incidence rate ratio; ME = multiplicative effect; OR = odds ratio; pat = patients; PRLs = paramagnetic rim lesions.

Reading example: effect of CC/CAP concentration doubling: per doubling of CSF C3a levels longitudinal total T2-weighted lesion volume is 119% higher.

Higher CSF levels of complement activation products Ba, C3a, and C4a in persons with CIS/MS are associated with an accelerated brain volume loss and higher PRL counts: (A) Top: The additional brain volume loss in a person with a Ba level corresponding to the 80th percentile (12.8 ng/mL; red line) within the CIS/MS cohort is −0.22% (p < 0.0001) as compared with a patient with a CSF Ba level corresponding to the 20th percentile (6.3 ng/mL; blue line). Middle: A patient with a Ba level (6.3 ng/mL) corresponding to the 20th percentile would have an estimated PRL count of 2.4 (blue), while one with an 80th percentile value (12.8 ng/mL) would correspond to 5.6 PRLs (red) (p < 0.0001). Bottom: The distribution of the percentiles within the CIS/MS cohort for the Ba concentration is expressed in this figure: the 20th percentile value is represented by the blue line and the 80th percentile level by the red line. (B) CSF C3a levels corresponding to the 80th percentile (5.1 ng/mL; red line) are associated with −0.13% (p = 0.0002) increased brain volume loss as compared with the 20th percentile (2.4 ng/mL; blue line) and correspond to estimated 7.9 for the 80th vs 2.8 PRLs (p < 0.0001) for the 20th percentile. (C) An 80th percentile C4a level (33.4 ng/mL) is associated with −0.24% (p < 0.0001) increased brain atrophy in comparison with a 20th percentile value (15.6 ng/mL) and with estimated 2.8 vs 1.8 PRLs (p = 0.0906). CIS = clinically isolated syndrome; MS = multiple sclerosis; PRL = paramagnetic rim lesion.

However, also for later cascade activation products, less pronounced effects on brain atrophy were seen: doubling of C5a levels showed a BPF reduction by −0.07%, and similarly for the terminal complement complex (s-C5b9), we observed an accelerated brain volume loss by −0.06% (both p < 0.0001) per year.

From the covariables used in the multivariable analysis older age, male (vs female) sex, MRI magnetic field strength (3 vs 1.5T), and disease subtype SPMS (vs CIS) were associated with a higher degree of brain volume loss (eTable 4).

Longitudinal T2w Lesion Volumes and CELs

Doubling of C4a levels was associated with 1.8-fold (p = 0.0029) higher T2w lesion volumes during follow-up; likewise, C3a and Ba correlated with 2.2- (p < 0.0001) and 2.0-fold (p = 0.0038) increased T2w lesion volumes and 2.5- (p = 0.0022) and 3.3-fold (p = 0.0024) higher odds for the occurrence of CEL. The later cascade activation product s-C5b9 was associated with 1.2-fold (p = 0.0142) increased T2-weighted lesion volumes, and C5a showed a 1.4-fold (p = 0.0332) higher probability for the occurrence of CELs (Table 2; eTables 5 and 6).

PRLs

Complement activation products C3a, Ba, and C5a were associated with higher PRL counts: for doubling of C3a, CSF levels we found an incidence rate ratio of 2.58 (p < 0.0001), followed by Ba with 2.33 (p = 0.006) and C5a with 1.25 (p = 0.0264) (Table 2; eTable 7; Figure 1).

GFAP

GFAP is associated with disease progression in MS and structural CNS damage, especially of gray matter.²⁴ CSF levels of C4a and C3a were associated with 14% (p = 0.0021) and 17% (p < 0.0001) increased GFAP concentrations, and for component C1q 40%, higher GFAP levels were found (p < 0.0001) (Table 3; eTable 8; Figure 2).

Table 3.

Multivariable Associations of CSF Complement Components and Activation Products With GFAP and Cytokine Levels in CSF

n = 235	GFAP			CXCL-13			CXCL-9			IL-12b
n = 235	ME	CI	p Value	ME	CI	p Value	ME	CI	p Value	ME	CI	p Value
C4a	1.14	1.05–1.25	0.0021	1.63	1.21–2.19	0.0014	1.50	1.23–1.82	<1e-04	1.38	1.17–1.64	0.0003
C4	1.00	0.89–1.13	0.9629	0.60	0.40–0.90	0.0146	0.81	0.62–1.07	0.1422	0.72	0.57–0.92	0.0083
C3a	1.17	1.09–1.26	<1e-04	2.12	1.65–2.70	<1e-04	1.85	1.59–2.16	<1e-04	1.79	1.57–2.04	<1e-04
C3	1.02	0.97–1.07	0.4313	1.21	1.03–1.43	0.0252	1.11	0.99–1.24	0.0628	1.05	0.95–1.16	0.3036
C5a	0.98	0.95–1.02	0.3536	1.21	1.06–1.38	0.0042	1.12	1.03–1.22	0.0086	1.09	1.01–1.18	0.0235
s-C5b9	0.98	0.95–1.02	0.3029	1.14	1.01–1.29	0.0328	1.11	1.02–1.20	0.0114	1.04	0.97–1.12	0.2488
C5	1.05	0.95–1.15	0.3584	0.98	0.70–1.36	0.8840	1.33	1.07–1.66	0.0101	1.17	0.97–1.42	0.1062
Ba	1.03	0.92–1.14	0.6203	2.29	1.60–3.28	<1e-04	2.07	1.65–2.60	<1e-04	1.73	1.41–2.12	<1e-04
Bb	1.01	0.95–1.07	0.8348	1.42	1.15–1.75	0.0013	1.36	1.18–1.56	<1e-04	1.27	1.12–1.43	0.0002
C1q	1.40	1.22–1.60	<1e-04	2.43	1.49–3.98	0.0005	2.13	1.55–2.94	<1e-04	1.77	1.33–2.35	0.0001
Factor H	1.23	0.97–1.55	0.0824	1.03	0.45–2.35	0.9454	1.26	0.73–2.17	0.4067	0.95	0.59–1.54	0.8429
Factor I	1.11	0.99–1.23	0.0663	1.02	0.70–1.49	0.9204	1.30	1.01–1.66	0.0424	1.12	0.89–1.39	0.3325

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Abbreviations: CAP = complement activation product; CC = complement component; DMT = disease-modifying treatment; GFAP = glial fibrillary acidic protein; LP = lumbar puncture; ME = multiplicative effect; Qalb = albumin-quotient.

Reading example: effect of CC/CAP concentration doubling: per doubling of CSF C4a levels CXCL-13 levels are increased by 63% (after adjustment for age, sex, Qalb, and DMT category at LP).

In CIS/MS (n = 235), doubling of CSF C3a levels was associated with by 17%, C4a 14% and C1q 40% increased GFAP CSF levels (compare Table 3). CAP = complement activation product; CC = complement component; CIS = clinically isolated syndrome; GFAP = glial fibrillary acidic protein; MS = multiple sclerosis.

Complement Activation-Associated Cytokines

CSF cytokines previously associated with MS disease activity and severity such as CXCL-13, CXCL-9, and IL-12b^25,26 are produced by complement-receptor–positive cells of the innate immune system and can amplify B-cell and T-cell autoreactivity.^27-30Doubling of C4a, C3a, and C5a levels was associated with higher CXCL-13 (C4a: 63%, p = 0.0014; C3a: 112%, p < 0.0001; C5a: 21%, p = 0.0042 increase), CXCL-9 (C4a: 50%, p < 0.0001; C3a: 85%, p < 0.0001; C5a: 12%, p = 0.0086), and IL-12b levels (C4a: 38%, p = 0.003; C3a: 79%, p < 0.0001; C5a: 9%, p = 0.0235), respectively. In return for nonactivated complement component C4, 40% lower CXCL-13 (p = 0.0146) and 28% lower IL-12b (p = 0.0083) levels were found, while there were no clear patterns for C3 and C5 (Table 3).

Regarding the alternative pathway, doubling of activation product Ba and Bb CSF levels was associated with 129% (p < 0.0001)/42% (p = 0.0013) higher CXCL-13, 107% (p < 0.0001)/36% (p < 0.0001) CXCL-9, and 73% (p < 0.0001)/27% (p = 0.0002) higher IL-12b levels, respectively. Most pronounced effects were observed for complement component C1q: per doubling of C1q levels, CXCL-13 concentrations were increased by 143% (p = 0.0005): CXCL-9 113% (p <0.0001) and IL-12b by 77% (p = 0.0001) (Table 3; eTable 9; Figure 3).

Strong multivariable associations of C4a, C3a, Ba, and C1q with higher IL-12b, CXCL-9, and CXCL-13 CSF levels in a homogenous and consistent pattern are displayed. Reading example: doubling of C4a CSF levels was associated with by 38% higher IL-12b levels (red bar), by 50% increased CXCL-9 levels (orange bar), and 63% higher CXCL13 levels (yellow bar) (compare Table 3).

Discussion

Our study demonstrates that CSF complement activation in MS is consistently associated with MRI endpoints reflecting structural tissue damage, focal inflammation, and neurodegeneration: Earlier (C3a, Ba, C4a) and to a lesser extent later cascade CAP (C5a, s-C5b9) in the CSF were associated with longitudinal total T2 lesion volumes, atrophy, CELs, and PRLs. We consistently found strong associations of CSF C1q levels with earlier cascade (Ba, C3a, C4a, Bb) and, also to a lesser extent, later cascade CAP (C5a, s-C5b9) with cytokine levels of CXCL-13, CXCL-9, and Il-12b and with GFAP levels.

These results are in line with our previous study reporting that earlier cascade CAP (C3a, C4a, Ba, Bb) are associated with outcomes reflecting disease severity such as the MS Severity Score, EDSS score, and neurofilament light chain (NfL) levels, reflecting neuroaxonal damage.¹⁰ Moreover, several neuropathologic studies are consistent with our findings: lesion-associated complement activation was observed in a large subgroup of patients with early MS.³¹ IgG and IgM colocalizing with C3b on demyelinated axons and oligodendrocytes and antibody-antigen immunocomplexes were detected in foamy macrophages in active lesion areas.³² In patients with longer disease duration, perivascular inflammatory infiltrates, astrocytic gliosis, diffuse axonal injury, and microglial activation as well as clusters of microglia around damaged axons coated with complement, especially C3 activation products, were consistently present in the normal-appearing white matter or in the periplaque of MS brains.^2,3,33 In addition, in the cortical gray matter of progressive MS, C1q depositions and complement activation fragments (Bb, C3b, s-C5b9) were increased, especially in those areas with elevated numbers of complement-receptor–positive microglia.⁵ These data are in line with the observation that increased immunoreactivity for C1q, C4d, Bb, and C3b occurs in thalamic lesions with an active inflammatory pathology in patients with progressive MS.³⁴

The complement system not only opsonizes targets for phagocytosis but also activates the immune system through soluble anaphylatoxins.^4,12 Activated complement proteins link innate with adaptive immune responses by acting directly on receptors expressed on T cells, B cells, or myeloid immune cells.^35-38 We found a homogenous association pattern of mainly proximal CC and CAP with cytokines such as CXCL-13, CXCL-9, and IL-12b. CXCL-9 and IL-12b are in general secreted by complement-receptor–positive cells such as macrophages and dendritic cells and regulate migration, differentiation, and activation of TH1-lymphocytes and natural killer cells.^29,27 CXCL-13 is produced by complement-receptor rich follicular dendritic cells³⁹ in B-cell follicles and is the only known ligand of the CXCR5-receptor. This “B-cell–attracting chemokine” is supposed to be one of the key players involved in the organization of lymphoid tissue and regulates homing of B cells and subsets of T cells to the follicles.²⁸ Formation of leptomeningeal ectopic lymphoid follicles comprising germinal centers (GC) and chronic active lesions with activated microglia is supposed to be involved in clinical deterioration in MS.^13,40,41 Signaling of activated complement through complement receptors C3aR/C5aR is crucial for GC formation and function because it promotes affinity maturation, plasma cell and memory B-cell production.^42,43

We found that C1q, and to a lesser extent C3a and C4a were associated with GFAP levels. NfL as a marker of neuroaxonal damage was strongly associated with CAP (C4a, C3a, Ba, Bb) but in contrast to GFAP not with C1q levels. GFAP is supposed to indicate either activation or damage of inflamed astrocytes and is associated with progression in MS and accelerated gray matter loss.²⁴ Our results are in line with a recent study postulating that C1q is upregulated and expressed by inflamed microglia in MS, whereas inflamed astrocytes were found to have 20-fold upregulation (relative to nonreactive astrocytes) of C1q-complex activators and C1q-receptors as well as an upregulation of complement component C3. Microglia expressed C3 receptors, implicating early complement compounds as mediators of crosstalk between inflamed astrocytes and microglia.⁴⁴ In another neuropathologic study, C1q expression and C3 activation were increased in hippocampal neurons of patients with MS, showing a marked decrease of synaptic density; also, these authors concluded that the C1q-C3 complement axis might play an important role in MS.⁴⁵

Mechanisms how complement activation contributes to CNS tissue damage and disability accumulation in human MS remain to be clarified, but there are results from experimental autoimmune encephalomyelitis (EAE) models: it was shown that a C1q-blocking antibody efficiently reduced C1q intensity staining in the brain of an EAE model and microglia reflecting reactive gliosis in the white matter were significantly reduced. This suggested that pharmacologic inhibition especially of C1q might be a potential therapeutic avenue to address chronic inflammation in the white matter.⁴⁴ Local intraparenchymal inhibition of C3 in MOG35-55-induced EAE mice models resulted in synaptic preservation, which means that these mice were protected from complement-mediated synaptic pruning by microglia. It also blocked loss of visual acuity.⁴⁶ Treatment with recombinant soluble human complement receptor-1 (CR1), blocking C3- and C5-convertase, significantly reduced clinical disease severity, inhibited CNS inflammation, almost blocked demyelination, and markedly reduced tissue deposition of C1, C3, and C9 in an antibody-mediated demyelinating EAE rat model.⁴⁷ Focusing specifically on the later cascade, C6-deficient rats developed significantly milder acute EAE after myelin basic protein immunization⁴⁸ and no demyelination, decreased T-cell and macrophage infiltration and no C9 detection was found.⁴⁹ In line with this study, mice deficient in terminal complement complex regulator CD59a developed a more severe disease with substantial demyelination in the acute phase of EAE MOG35-55.⁵⁰ However, in the chronic phase, C5 deficiency was reported to be associated with more inflammatory demyelination and Wallerian degeneration, while in C5-sufficient mice, axonal sparing and extensive remyelination were found.⁵¹ Overall, these data suggest that activation of the distal complement cascade might represent a double-edge sword with effects both on damage and repair, also depending on the timing. From a translational perspective, these data suggest that treatment with inhibitors of the early complement cascade might have a higher therapeutic potential in MS, while conventional C5-inhibitors could even worsen disease severity and progression in MS.

One limitation of our study is the lack of longitudinal CSF complement and cytokine data. In particular, sC5b-9 had a high percentage of samples below the sensitivity of the assay used, which necessitated imputation to include low levels of respective analytes in the analysis. Another limitation was a relatively small number of patients with progressive MS in this data set.

Taken together, aberrant complement activation in the CSF is prominently associated with biomarkers indicative for structural brain damage relevant to disability accumulation in MS. Although mechanistic underpinnings of these associations remain to be further investigated and clarified, our data suggest that complement inhibition is a potential future therapeutic avenue to address disease progression and disability accumulation in MS.

Acknowledgment

The authors express their deep thankfulness to the patients and their relatives for their participation and support, to the study nurses for their motivated collaboration and recruitment efforts, and to the administrative personnel of the CSF databank study and the Swiss Multiple Sclerosis Cohort study.

Glossary

CIS: clinically isolated syndrome
EDSS: Expanded Disability Status Scale Score
Est: estimate
FLAIR: fluid-attenuated inversion recovery
GC: germinal center
GFAP: glial fibrillary acidic protein
IQR: interquartile range
LLOQ: lower limit of quantification
LP: lumbar puncture
MS: multiple sclerosis
NfL: neurofilament light chain
PPMS: primary progressive multiple sclerosis
PRL: paramagnetic rim lesion
QC: quality control
RRMS: relapsing-remitting multiple sclerosis
SMSC: Swiss multiple sclerosis cohort
SPMS: secondary progressive multiple sclerosis
T2w: T2-weighted

Author Contributions

J. Oechtering: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data. S.A. Schaedelin: drafting/revision of the manuscript for content, including medical writing for content; analysis or interpretation of data. K. Stein: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. A. Maleska Maceski: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. L. Melie-Garcia: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. P. Benkert: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. A. Cagol: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. S. Leber: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. R. Galbusera: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. E. Ruberte: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. W. Hu: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. F. Qureshi: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. A. Orleth: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. L. Demuth: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. E. Willemse: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. I. Heijnen: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. A. Regeniter: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. T.J. Derfuss: drafting/revision of the manuscript for content, including medical writing for content. B. Fischer-Barnicol: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. L. Achtnichts: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. S. Mueller: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. R. Hoepner: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. P.H. Lalive: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. C. Bridel: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. M. D'Souza: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. C. Pot: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. R.A. Du Pasquier: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. C. Gobbi: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. C. Zecca: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. H. Wiendl: drafting/revision of the manuscript for content, including medical writing for content. J.M. Lieb: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. C. Lamers: drafting/revision of the manuscript for content, including medical writing for content. L. Kappos: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. M. Trendelenburg: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. D. Leppert: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. C. Granziera: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. J. Kuhle: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data. J.D. Lünemann: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; analysis or interpretation of data.

Study Funding

This investigation was supported by the Swiss Multiple Sclerosis Society (research grant 2021/10). The Swiss MS Cohort study received funding from the Swiss Multiple Sclerosis Society and grant funding from Biogen, Bristol Myers Squibb, Celgene, Merck, Novartis, Roche, and Sanofi. The authors acknowledge support by the German Research Foundation (LU 900/3-1 to J.D. Lünemann. and through the Collaborative Research Centre SFB-TRR128 “Initiating/Effector vs Regulatory Mechanisms in Multiple Sclerosis – Progress towards Tackling the Disease” SFB/TR128 to H. Wiendl and J.D. Lünemann).

Disclosure

S.A. Schaedelin, K. Stein, A. Maleska Maceski, P. Benkert, S. Leber, E. Ruberte, A. Orleth, L. Demuth, I. Heijnen, A. Regeniter, E. Willemse, C. Lamers, L. Melie-Garcia, A. Cagol, R. Galbusera, J.D. Lünemann, and R. Hoepner report no conflicts of interest. J. Oechtering received research support by the Swiss MS Society and served on advisory boards for Roche and Merck. W. Hu and F. Qureshi are employees of Octave Bioscience, Inc., T.J. Derfuss received speaker fees, research support, travel support, and/or served on Advisory Boards, data safety monitoring boards, or Steering Committees of Alexion, Celgene, Polyneuron, Novartis Pharma, Merck Serono, Biogen, Teva, GeNeuro, Roche, and Sanofi Genzyme. B. Fischer-Barnicol served on an advisory board for Biogen. L. Achtnichts served on scientific advisory boards for Celgene, Novartis Pharmaceuticals, Merck, Biogen, Sanofi Genzyme, Roche, and Bayer; received funding for travel and/or speaker honoraria from Celgene, Biogen, Sanofi Genzyme, Novartis, Merck Serono, Roche, Teva, and the Swiss MS Society; and research support from Biogen, Sanofi, Genzyme, and Novartis. SM received speaker fees, research support, travel support, and/or served on advisory boards by Almirall, Alexion, Bayer, Biogen, Bristol Myers Squibb, Celgene, Genzyme, Merck-Serono, Teva, Novartis, and Roche. P.H. Lalive received honoraria for speaking and/or travel expenses from Biogen, Merck, Novartis, and Roche; consulting fees from Biogen, GeNeuro, Merck, Novartis, and Roche; research support from Biogen, Merck, and Novartis. None were related to this work. C. Bridel served on scientific advisory boards for Biogen, Novartis, and BMS. M.D'Souza has received travel support from Bayer AG, Biogen, Teva Pharmaceuticals, and Sanofi Genzyme and research support from the University Hospital Basel. C. Pot received consulting fees and/or travel compensation, used exclusively for research support, for activities with Biogen, Merck, Novartis, Roche, and Sanofi Genzyme. R.A. Du Pasquierhas served on scientific advisory boards for Biogen, Celgene, Merck, Novartis, Roche, and Sanofi. He has received funding for travel or speaker honoraria from Roche. C. Gobbi Ente Ospedaliero Cantonale (employer) received compensation for C. Gobbi's speaking activities, consulting fees, or grants from Abbvie, Almirall, Biogen, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sandoz, Sanofi, Teva Pharma, and Roche. C. Zecca Ente Ospedaliero Cantonale (employer) received compensation for C. Zecca's speaking activities, consulting fees, or grants from Abbvie, Almirall, Biogen, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sandoz, Sanofi, Teva Pharma, and Roche. C. Zecca is a recipient of a grant for senior researchers provided by AFRI (Area Formazione accademica, Ricerca e Innovazione), EOC. H. Wiendl receives honoraria for acting as a member of Scientific Advisory Boards for Janssen, Merck, and Novartis as well as speaker honoraria and travel support from Alexion, Amicus Therapeuticus, Biogen, Biologix, Bristol Myers Squibb, Cognomed, F. Hoffmann-La Roche Ltd., Gemeinnützige Hertie-Stiftung, Medison, Merck, Novartis, Roche Pharma AG, Genzyme, TEVA, and WebMD Global. Prof. Wiendl is acting as a paid consultant for Biogen, Bristol Myers Squibb, EMD Serono, Idorsia, Immunic, Novartis, Roche, Sanofi, the Swiss MS Society, and UCB. His research is funded by the German Ministry for Education and Research (BMBF), Deutsche Forschungsgesellschaft (DFG), Deutsche Myasthenie Gesellschaft e.V., Alexion, Amicus Therapeutics Inc., Argenx, Biogen, CSL Behring, F. Hoffmann—La Roche, Genzyme, Merck KgaA, Novartis Pharma, Roche Pharma, and UCB Biopharma. L. Kappos's: employer (University Hospital Basel) has received and dedicated to research support steering committee, advisory board, and consultancy fees (Abbvie, Actelion, Almirall, Auriga Vison AG, Bayer HealthCare, Biogen, Eisai, EMD Derono Inc., Genzyme, Genentech Inc., F. Hoffmann-La Roche, Japan Tobacco, Janssen Pharmaceuticals Inc., Merck, Minoryx Therapeutics SL, Novartis, Sanofi, Santhera, Senda Biosciences, Shionogi BV, and TG Therapeutics); speaker fees (Bayer HealthCare, Biogen, Celgene, Genzyme, Janssen Pharmaceuticals Inc., Merck, Novartis, Roche, and Sanofi); support of educational activities (Allergan, Bayer HealthCare, Biogen, CSL Behring, Genzyme, Merck, Novartis, Roche, Pfizer, Sanofi, Shire, and Teva); license fees for Neurostatus products; and grants (Bayer HealthCare, Biogen, European Union, Innosuisse, Merck, Novartis, Roche Research Foundation, Swiss MS Society, and Swiss National Research Foundation). M. Trendelenburg has research collaborations with Roche, Novartis, and Idorsia (all Switzerland). D. Leppert is a Chief Medical Officer of GeNeuro. C. Granziera: The University Hospital Basel (USB), as the employer of Cristina Granziera has received the following fees which were used exclusively for research support: (1) advisory board and consultancy fees from Actelion, Novartis, Genzyme, and F. Hoffmann-La Roche; (2) speaker fees from Biogen and Genzyme-Sanofi; (3) research support from F. Hoffmann-La Roche Ltd.; Before her employment at USB, she has also received speaker honoraria and travel funding by Novartis. J. Kuhle received speaker fees, research support, travel support, and/or served on advisory boards by Swiss MS Society, Swiss National Research Foundation (320030_189140/1), University of Basel, Progressive MS Alliance, Bayer, Biogen, Bristol Myers Squibb, Celgene, Merck, Novartis, Octave Bioscience, Roche, and Sanofi. JDL received speaker fees, research support, travel support, and/or served on advisory boards by the EU Framework Programme Horizon Europe, The German Research Foundation (LU 9001-1; LU 900-4; and the Collaborative Research Centre SFB-TRR128 “Initiating/Effector vs Regulatory Mechanisms in MS—Progress towards Tackling the Disease”), Abbvie, Alexion, Argenx, Biogen, Merck, Novartis, Roche, Sanofi, and Takeda. Go to Neurology.org/N for full disclosures.

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20.Andermatt S, Pezold S, Cattin PC. Automated segmentation of multiple sclerosis lesions using multi-dimensional gated recurrent units. Lecture Notes Comp Sci. 2018;10670:31-42. doi: 10.1007/978-3-319-75238-9_3 [DOI] [Google Scholar]
21.Palumbo L, Bosco P, Fantacci ME, et al. Evaluation of the intra- and inter-method agreement of brain MRI segmentation software packages: a comparison between SPM12 and FreeSurfer v6.0. Phys Med. 2019;64:261-272. doi: 10.1016/j.ejmp.2019.07.016 [DOI] [PubMed] [Google Scholar]
22.Andersson M, Alvarez-Cermeno J, Bernardi G, et al. Cerebrospinal fluid in the diagnosis of multiple sclerosis: a consensus report. J Neurol Neurosurg Psychiatry. 1994;57(8):897-902. doi: 10.1136/jnnp.57.8.897 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Qureshi F, Hu W, Loh L, et al. Analytical validation of a multi-protein, serum-based assay for disease activity assessments in multiple sclerosis. Proteomics Clin Appl. 2023;17(3):e2200018. doi: 10.1002/prca.202200018 [DOI] [PubMed] [Google Scholar]
24.Meier S, Willemse E, Schaedelin S, et al. Serum glial fibrillary acidic protein compared with neurofilament light chain as biomarker for multiple sclerosis disease progression. JAMA Neurol. 2023;80(3):287-297. doi: 10.1001/jamaneurol.2022.5250 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Huang J, Khademi M, Fugger L, et al. Inflammation-related plasma and CSF biomarkers for multiple sclerosis. Proc Natl Acad Sci U S A. 2020;117(23):12952-12960. doi: 10.1073/pnas.1912839117 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Magliozzi R, Howell OW, Nicholas R, et al. Inflammatory intrathecal profiles and cortical damage in multiple sclerosis. Ann Neurol. 2018;83(4):739-755. doi: 10.1002/ana.25197 [DOI] [PubMed] [Google Scholar]
27.Henry CJ, Ornelles DA, Mitchell LM, Brzoza-Lewis KL, Hiltbold EM. IL-12 produced by dendritic cells augments CD8+ T cell activation through the production of the chemokines CCL1 and CCL17. J Immunol. 2008;181(12):8576-8584. doi: 10.4049/jimmunol.181.12.8576 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Pan Z, Zhu T, Liu Y, Zhang N. Role of the CXCL13/CXCR5 Axis in autoimmune diseases. Front Immunol. 2022;13:850998. doi: 10.3389/fimmu.2022.850998 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Tokunaga R, Zhang W, Naseem M, et al. CXCL9, CXCL10, CXCL11/CXCR3 axis for immune activation - a target for novel cancer therapy. Cancer Treat Rev. 2018;63:40-47. doi: 10.1016/j.ctrv.2017.11.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Vandendriessche S, Cambier S, Proost P, Marques PE. Complement receptors and their role in leukocyte recruitment and phagocytosis. Front Cel Dev Biol. 2021;9:624025. doi: 10.3389/fcell.2021.624025 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Lucchinetti C, Bruck W, Parisi J, Scheithauer B, Rodriguez M, Lassmann H. Heterogeneity of multiple sclerosis lesions: implications for the pathogenesis of demyelination. Ann Neurol. 2000;47(6):707-717. doi: [DOI] [PubMed] [Google Scholar]
32.Sadaba MC, Tzartos J, Paino C, et al. Axonal and oligodendrocyte-localized IgM and IgG deposits in MS lesions. J Neuroimmunol. 2012;247(1-2):86-94. doi: 10.1016/j.jneuroim.2012.03.020 [DOI] [PubMed] [Google Scholar]
33.Loveless S, Neal JW, Howell OW, et al. Tissue microarray methodology identifies complement pathway activation and dysregulation in progressive multiple sclerosis. Brain Pathol. 2018;28(4):507-520. doi: 10.1111/bpa.12546 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Cooze BJ, Dickerson M, Loganathan R, et al. The association between neurodegeneration and local complement activation in the thalamus to progressive multiple sclerosis outcome. Brain Pathol. 2022;32(5):e13054. doi: 10.1111/bpa.13054 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Arvieux J, Yssel H, Colomb MG. Antigen-bound C3b and C4b enhance antigen-presenting cell function in activation of human T-cell clones. Immunology. 1988;65(2):229-235. [PMC free article] [PubMed] [Google Scholar]
36.Dempsey PW, Allison MED, Akkaraju S, Goodnow CC, Fearon DT. C3d of complement as a molecular adjuvant: bridging innate and acquired immunity. Science. 1996;271(5247):348-350. doi: 10.1126/science.271.5247.348 [DOI] [PubMed] [Google Scholar]
37.Kemper C, Atkinson JP. T-cell regulation: with complements from innate immunity. Nat Rev Immunol. 2007;7(1):9-18. doi: 10.1038/nri1994 [DOI] [PubMed] [Google Scholar]
38.Kemper C, Mitchell LM, Zhang L, Hourcade DE. The complement protein properdin binds apoptotic T cells and promotes complement activation and phagocytosis. Proc Natl Acad Sci U S A. 2008;105(26):9023-9028. doi: 10.1073/pnas.0801015105 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Cinti I, Denton AE. Lymphoid stromal cells-more than just a highway to humoral immunity. Oxf Open Immunol. 2021;2(1):iqab011. doi: 10.1093/oxfimm/iqab011 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Elliott C, Belachew S, Wolinsky JS, et al. Chronic white matter lesion activity predicts clinical progression in primary progressive multiple sclerosis. Brain. 2019;142(9):2787-2799. doi: 10.1093/brain/awz212 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Magliozzi R, Howell O, Vora A, et al. Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology. Brain. 2007;130(Pt 4):1089-1104. doi: 10.1093/brain/awm038 [DOI] [PubMed] [Google Scholar]
42.Cumpelik A, Heja D, Hu Y, et al. Dynamic regulation of B cell complement signaling is integral to germinal center responses. Nat Immunol. 2021;22(6):757-768. doi: 10.1038/s41590-021-00926-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Robinson MJ, Quast I, Tarlinton DM. Complement-in' the germinal center response. Nat Immunol. 2021;22(6):673-674. doi: 10.1038/s41590-021-00946-w [DOI] [PubMed] [Google Scholar]
44.Absinta M, Maric D, Gharagozloo M, et al. A lymphocyte-microglia-astrocyte axis in chronic active multiple sclerosis. Nature. 2021;597(7878):709-714. doi: 10.1038/s41586-021-03892-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Michailidou I, Willems JG, Kooi EJ, et al. Complement C1q-C3-associated synaptic changes in multiple sclerosis hippocampus. Ann Neurol. 2015;77(6):1007-1026. doi: 10.1002/ana.24398 [DOI] [PubMed] [Google Scholar]
46.Werneburg S, Jung J, Kunjamma RB, et al. Targeted complement inhibition at synapses prevents microglial synaptic engulfment and synapse loss in demyelinating disease. Immunity. 2020;52(1):167-182.e7. doi: 10.1016/j.immuni.2019.12.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Piddlesden SJ, Storch MK, Hibbs M, Freeman AM, Lassmann H, Morgan BP. Soluble recombinant complement receptor 1 inhibits inflammation and demyelination in antibody-mediated demyelinating experimental allergic encephalomyelitis. J Immunol. 1994;152(11):5477-5484. doi: 10.4049/jimmunol.152.11.5477 [DOI] [PubMed] [Google Scholar]
48.Mead RJ, Singhrao SK, Neal JW, Lassmann H, Morgan BP. The membrane attack complex of complement causes severe demyelination associated with acute axonal injury. J Immunol. 2002;168(1):458-465. doi: 10.4049/jimmunol.168.1.458 [DOI] [PubMed] [Google Scholar]
49.Tran GT, Hodgkinson SJ, Carter N, Killingsworth M, Spicer ST, Hall BM. Attenuation of experimental allergic encephalomyelitis in complement component 6-deficient rats is associated with reduced complement C9 deposition, P-selectin expression, and cellular infiltrate in spinal cords. J Immunol. 2002;168(9):4293-4300. doi: 10.4049/jimmunol.168.9.4293 [DOI] [PubMed] [Google Scholar]
50.Mead RJ, Neal JW, Griffiths MR, et al. Deficiency of the complement regulator CD59a enhances disease severity, demyelination and axonal injury in murine acute experimental allergic encephalomyelitis. Lab Invest. 2004;84(1):21-28. doi: 10.1038/labinvest.3700015 [DOI] [PubMed] [Google Scholar]
51.Weerth SH, Rus H, Shin ML, Raine CS. Complement C5 in experimental autoimmune encephalomyelitis (EAE) facilitates remyelination and prevents gliosis. Am J Pathol. 2003;163(3):1069-1080. doi: 10.1016/S0002-9440(10)63466-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data are available on reasonable request.

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[R27] 27.Henry CJ, Ornelles DA, Mitchell LM, Brzoza-Lewis KL, Hiltbold EM. IL-12 produced by dendritic cells augments CD8+ T cell activation through the production of the chemokines CCL1 and CCL17. J Immunol. 2008;181(12):8576-8584. doi: 10.4049/jimmunol.181.12.8576 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R28] 28.Pan Z, Zhu T, Liu Y, Zhang N. Role of the CXCL13/CXCR5 Axis in autoimmune diseases. Front Immunol. 2022;13:850998. doi: 10.3389/fimmu.2022.850998 [DOI] [PMC free article] [PubMed] [Google Scholar]

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[R32] 32.Sadaba MC, Tzartos J, Paino C, et al. Axonal and oligodendrocyte-localized IgM and IgG deposits in MS lesions. J Neuroimmunol. 2012;247(1-2):86-94. doi: 10.1016/j.jneuroim.2012.03.020 [DOI] [PubMed] [Google Scholar]

[R33] 33.Loveless S, Neal JW, Howell OW, et al. Tissue microarray methodology identifies complement pathway activation and dysregulation in progressive multiple sclerosis. Brain Pathol. 2018;28(4):507-520. doi: 10.1111/bpa.12546 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R34] 34.Cooze BJ, Dickerson M, Loganathan R, et al. The association between neurodegeneration and local complement activation in the thalamus to progressive multiple sclerosis outcome. Brain Pathol. 2022;32(5):e13054. doi: 10.1111/bpa.13054 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R35] 35.Arvieux J, Yssel H, Colomb MG. Antigen-bound C3b and C4b enhance antigen-presenting cell function in activation of human T-cell clones. Immunology. 1988;65(2):229-235. [PMC free article] [PubMed] [Google Scholar]

[R36] 36.Dempsey PW, Allison MED, Akkaraju S, Goodnow CC, Fearon DT. C3d of complement as a molecular adjuvant: bridging innate and acquired immunity. Science. 1996;271(5247):348-350. doi: 10.1126/science.271.5247.348 [DOI] [PubMed] [Google Scholar]

[R37] 37.Kemper C, Atkinson JP. T-cell regulation: with complements from innate immunity. Nat Rev Immunol. 2007;7(1):9-18. doi: 10.1038/nri1994 [DOI] [PubMed] [Google Scholar]

[R38] 38.Kemper C, Mitchell LM, Zhang L, Hourcade DE. The complement protein properdin binds apoptotic T cells and promotes complement activation and phagocytosis. Proc Natl Acad Sci U S A. 2008;105(26):9023-9028. doi: 10.1073/pnas.0801015105 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R39] 39.Cinti I, Denton AE. Lymphoid stromal cells-more than just a highway to humoral immunity. Oxf Open Immunol. 2021;2(1):iqab011. doi: 10.1093/oxfimm/iqab011 [DOI] [PMC free article] [PubMed] [Google Scholar]

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[R41] 41.Magliozzi R, Howell O, Vora A, et al. Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology. Brain. 2007;130(Pt 4):1089-1104. doi: 10.1093/brain/awm038 [DOI] [PubMed] [Google Scholar]

[R42] 42.Cumpelik A, Heja D, Hu Y, et al. Dynamic regulation of B cell complement signaling is integral to germinal center responses. Nat Immunol. 2021;22(6):757-768. doi: 10.1038/s41590-021-00926-0 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R43] 43.Robinson MJ, Quast I, Tarlinton DM. Complement-in' the germinal center response. Nat Immunol. 2021;22(6):673-674. doi: 10.1038/s41590-021-00946-w [DOI] [PubMed] [Google Scholar]

[R44] 44.Absinta M, Maric D, Gharagozloo M, et al. A lymphocyte-microglia-astrocyte axis in chronic active multiple sclerosis. Nature. 2021;597(7878):709-714. doi: 10.1038/s41586-021-03892-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R45] 45.Michailidou I, Willems JG, Kooi EJ, et al. Complement C1q-C3-associated synaptic changes in multiple sclerosis hippocampus. Ann Neurol. 2015;77(6):1007-1026. doi: 10.1002/ana.24398 [DOI] [PubMed] [Google Scholar]

[R46] 46.Werneburg S, Jung J, Kunjamma RB, et al. Targeted complement inhibition at synapses prevents microglial synaptic engulfment and synapse loss in demyelinating disease. Immunity. 2020;52(1):167-182.e7. doi: 10.1016/j.immuni.2019.12.004 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R47] 47.Piddlesden SJ, Storch MK, Hibbs M, Freeman AM, Lassmann H, Morgan BP. Soluble recombinant complement receptor 1 inhibits inflammation and demyelination in antibody-mediated demyelinating experimental allergic encephalomyelitis. J Immunol. 1994;152(11):5477-5484. doi: 10.4049/jimmunol.152.11.5477 [DOI] [PubMed] [Google Scholar]

[R48] 48.Mead RJ, Singhrao SK, Neal JW, Lassmann H, Morgan BP. The membrane attack complex of complement causes severe demyelination associated with acute axonal injury. J Immunol. 2002;168(1):458-465. doi: 10.4049/jimmunol.168.1.458 [DOI] [PubMed] [Google Scholar]

[R49] 49.Tran GT, Hodgkinson SJ, Carter N, Killingsworth M, Spicer ST, Hall BM. Attenuation of experimental allergic encephalomyelitis in complement component 6-deficient rats is associated with reduced complement C9 deposition, P-selectin expression, and cellular infiltrate in spinal cords. J Immunol. 2002;168(9):4293-4300. doi: 10.4049/jimmunol.168.9.4293 [DOI] [PubMed] [Google Scholar]

[R50] 50.Mead RJ, Neal JW, Griffiths MR, et al. Deficiency of the complement regulator CD59a enhances disease severity, demyelination and axonal injury in murine acute experimental allergic encephalomyelitis. Lab Invest. 2004;84(1):21-28. doi: 10.1038/labinvest.3700015 [DOI] [PubMed] [Google Scholar]

[R51] 51.Weerth SH, Rus H, Shin ML, Raine CS. Complement C5 in experimental autoimmune encephalomyelitis (EAE) facilitates remyelination and prevents gliosis. Am J Pathol. 2003;163(3):1069-1080. doi: 10.1016/S0002-9440(10)63466-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Aberrant Complement Activation Is Associated With Structural Brain Damage in Multiple Sclerosis

Johanna Oechtering

Sabine Anna Schaedelin

Kerstin Stein

Aleksandra Maleska Maceski

Lester Melie-Garcia

Pascal Benkert

Alessandro Cagol

Selina Leber

Riccardo Galbusera

Esther Ruberte

Wayne Hu

Ferhan Qureshi

Annette Orleth

Lilian Demuth

Eline Willemse

Ingmar Heijnen

Axel Regeniter

Tobias J Derfuss

Bettina Fischer-Barnicol

Lutz Achtnichts

Stefanie Mueller

Robert Hoepner

Patrice H Lalive

Claire Bridel

Marcus D'Souza

Caroline Pot

Renaud A Du Pasquier

Claudio Gobbi

Chiara Zecca

Heinz Wiendl

Johanna Maria Lieb

Christina Lamers

Ludwig Kappos

Marten Trendelenburg

David Leppert

Cristina Granziera

Jens Kuhle

Jan D Lünemann

Abstract

Background and Objectives

Methods

Results

Discussion

Introduction

Methods

Patients, Inclusion Criteria, and Data Collection

Standard Protocol Approvals, Registrations, and Patient Consents

MRI Data and Analysis

Samples and Measurements of CC and Activation Products

Measurements of GFAP Levels

Measurements of Cytokines

Statistics

Associations of CC and CAP With Different Outcome Parameters

Atrophy

Longitudinal T2-Weighted Lesion Volumes and CELs

PRLs

GFAP and Complement Activation-Associated Cytokine Levels

Data Availability

Results

Patients and Clinical Data

Table 1.

Atrophy

Table 2.

Figure 1. Multivariable Associations of CSF Ba, C3a, and C4a Levels With Brain Volume Loss and PRL Counts.

Longitudinal T2w Lesion Volumes and CELs

PRLs

GFAP

Table 3.

Figure 2. Multivariable Associations of CSF CC or CAP With GFAP Levels.

Complement Activation-Associated Cytokines

Figure 3. Multivariable Associations of CSF C4a, C3a, Ba, and C1q Levels With Cytokines.

Discussion

Acknowledgment

Glossary

Author Contributions

Study Funding

Disclosure

References