Anti-aquaporin 4 IgG Is Not Associated With Any Clinical Disease Characteristics in Neuromyelitis Optica Spectrum Disorder

Abstract

Background: Neuromyelitis optica spectrum disorder (NMOSD) is a clinically defined, inflammatory central nervous system (CNS) disease of unknown cause, associated with humoral autoimmune findings such as anti-aquaporin 4 (AQP4)-IgG. Recent clinical trials showed a benefit of anti-B cell and anti-complement-antibodies in NMOSD, suggesting relevance of anti-AQP4-IgG in disease pathogenesis. Objective: AQP4-IgG in NMOSD is clearly defined, yet up to 40% of the patients are negative for AQP4-IgG. This may indicate that AQP4-IgG is not disease-driving in NMOSD or defines a distinct patient endotype. Methods: We established a biobank of 63 clinically well-characterized NMOSD patients with an extensive annotation of 351 symptoms, patient characteristics, laboratory results and clinical scores. We used phylogenetic clustering, heatmaps, principal component and longitudinal causal interference analyses to test for the relevance of anti-AQP4-IgG. Results: Anti-AQP4-IgG was undetectable in 29 (46%) of the 63 NMOSD patients. Within anti-AQP4-IgG-positive patients, anti-AQP4-IgG titers did not correlate with clinical disease activity. Comparing anti-AQP4-IgG-positive vs. -negative patients did not delineate any clinically defined subgroup. However, anti-AQP4-IgG positive patients had a significantly (p = 0.022) higher rate of additional autoimmune diagnoses. Conclusion: Our results challenge the assumption that anti-AQP4-IgG alone plays a disease-driving role in NMOSD. Anti-AQP4-IgG might represent an epiphenomenon associated with NMOSD, may represent one of several immune mechanisms that collectively contribute to the pathogenesis of this disease or indeed, anti-AQP4-IgG might be the relevant factor in only a subgroup of patients.

Keywords: AQP4; anti-AQP4-IgG; aquaporin; autoimmunity; channelopathies; immunology; neuromyelitis optica.

Figure 1

Anti-aquaporin 4 (AQP4)-IgG status does not define distinct subgroups of patients by principle-component analyses (PCA) independent by model, number or type of markers used. Anti-AQP4-IgG status does not define a subgroup (such as anti-AQP4-IgG positive and -negative patients) as demonstrated by the full overlap of the 95% prediction ellipses in principle-component analyses (PCA). This is irrespective of how many and which markers are, or which model is used. Patients with Neuromyelitis optica spectrum disorder (NMOSD) were colored according to their anti-AQP4-IgG-status (A,B) or the second pain variable, describing levels of pain disturbing work during the last 4 weeks (question 22 from the “36-item containing short form health survey,” SF-36 score; in C). Singular value decomposition (SVD) with imputation was used here in all PCAs to calculate principal components (PC). Prediction ellipses are such that with a probability of 0.95, a new observation from the same group will fall inside the ellipse. (A) A PCA was performed with all variables (but not anti-AQP4 statuses) and the patients were marked according to their anti-AQP4-IgG status. The PCA-plot shows PC1 and PC2, explaining 24 and 15% of the total variance, respectively, and was performed using only a limited number of key variables (N = 20) such as the Expanded Disability Status Scale (EDSS), disease activity and severity, sex and age. Prediction ellipses were drawn such that a new observation from the same group will fall inside the ellipse with a probability of 0.95. However, those prediction ellipses as well as the data points completely overlap. No difference based on anti-AQP4-IgG status is visible. (B) As in A, but all 351 variables (symptoms, disabilities, lab values, anamnestic, psychosomatic scores, and clinical markers) which have been recorded for the patients are included in the analysis, except for the anti-AQP4 statuses. Again, no difference based on anti-AQP4-IgG status is visible, in marked contrast to (C): Same as in A but shown are patients having high vs. low levels of interference of pain with normal work (including work outside the home and housework) during the past 4 weeks. A PCA based on the remaining 35 variables from the SF-36 score (except the mentioned pain variable two, for which the patient cases have been colored) is shown. Here, the prediction ellipses for a probability of 0.95, as well as the dots per se, show a remarkable difference between the two groups. AQP4, aquaporin 4; EDSS, Expanded Disability Status Scale; NMOSD, neuromyelitis optica spectrum disorder; PC, principal components; PCA, principle-component analysis; SF-36, 36-item short form health survey; SVD, singular value decomposition.

Figure 2

The anti-aquaporin 4 (AQP4)-IgG status does not define a subgroup that would be detectable in heatmap-based clustering analyses. In addition to the PCAs, the same data sets as in Figure 1 were used to perform calculations based on phylogenetic clustering analyses using heatmaps. As before, no difference based on anti-AQP4-IgG status were identifiable. This is in contrast to the two clearly visible different groups, which are based on the second pain variable taken from the 36-item short form health survey (SF-36). (A,B) Patients with Neuromyelitis optica spectrum disorder (NMOSD; N = 63) were clustered in columns using correlation distance and average linkage based either on only a limited number of key variables, such disease activity, severity, sex and age etc. (A; N = 20) or based on up to 351 symptoms and clinical markers (B; shown here in rows) were clustered. Unit variance scaling is applied to the symptoms and the clinical markers. On top of the rows, anti-AQP4 status is shown. No group based on anti-AQP4-IgG status is visible. (C) As in (A,B), only the 35 variables of the SF-36 score were used and the same patients were clustered. In contrast to anti-AQP4-IgG, on the left side of the dendrogram, clearly visible a major group based on a high pain variable was formed. A difference to the anti-AQP4-IgG status can be seen due to the cluster on the left, formed by the residual variables of the SF-36 score. All patients are positive for a high second pain variable. On top of the rows, the second pain variable taken from the SF-36 score is color encoded shown.

Figure 3

Longitudinal causal interference analysis: anti-AQP4-IgG-Titer does not correlate with disease activity or progression. The level of anti-AQP4-IgG antibody titers remain unchanged after increased number of attacks (A,B). Also, the number of relapses per year (ARR) do not correlate with the anti-AQP4-IgG status (C). The level of anti-AQP4-IgG titers are not increased if more symptom areas are affected (D). A dichotomy can be seen if the level of anti-AQP4-IgG is plotted vs. the anti-MOG-IgG titer (E): NMOSD patients which are anti-MOG-IgG positive do not have anti-AQP4-IgG and vice versa. AU, arbitrary unit.

Figure 4

A positive anti-aquaporin 4 (AQP4)-IgG status is associated with the presence of other autoimmune diseases in addition to NMOSD, while a negative status is associated with malignancies. A chord plot, based on the 59 patients for which we had both, anti-AQP4- and anti-MOG-IgG test results, is shown (A). The patients were sorted according to these results into four groups, shown on the left side of the chord plot: anti-AQP4-IgG⁺ and anti-MOG-IgG⁺: double AQP4+MOG-IgG positive anti-AQP4-IgG⁻ and anti-MOG-IgG⁺: single MOG-IgG positive anti-AQP4-IgG⁺ and anti-MOG-IgG⁻: single AQP4-IgG positive anti-AQP4-IgG⁻ and anti-MOG-IgG⁻: no aAb. On the right side, key findings such as: number of relapses; any other autoimmune disease (thyroiditis; SLE; myasthenia; Sjogren's and other); diabetes; hypertension; any malignancy and traumatic injury are show. The thickness of the connecting chords between the four patient subgroups and the key findings represents the number of patients with each of those conditions. The chords connecting the patients with “any malignancy” have been colored red, however there is only one chord present, connecting “any malignancy” with the “anti-AQP4-IgG⁻ and anti-MOG-IgG⁻: no aAb” group. Therefore, all patients with malignancy do not have any of the aAbs. In contrast, the chords connecting patients with “any other autoimmune disease” have been colored blue. The thickest chord, representing about 80% of the autoimmune group, is connected to the “single AQP4-IgG positive” patients. Vice versa, in this “single AQP4-IgG positive” group, the connection to the autoimmune group represents about 40% of all its connections. Therefore, 80% of all patients with a second autoimmune condition were single AQP4-IgG positive and in this group, it was the largest contributing factor and showed a significant difference related to the AQP4-IgG status (B).