Biomarkers of Autoimmunity in Acute Psychiatric Disorders
Abstract
Objective:
Previous studies have suggested that autoantibodies associated with systemic autoimmune disorders are more prevalent in patients with psychotic and affective disorders compared with healthy control subjects. However, most positive studies addressing this issue have been limited by small sample sizes and lack of correction for confounding factors. The authors aimed to assess the prevalence of several autoantibodies in patients admitted to acute psychiatric inpatient care and investigate whether patients with psychotic and affective disorders have an increased prevalence of autoantibodies compared with psychiatric patients admitted for other reasons.
Methods:
Five hundred eighty-five patients were screened for the presence of antinuclear antibodies (ANA), anticardiolipin and antibeta2-glycoprotein, antithyroid peroxidase (anti-TPO), antitissue transglutaminase IgA, antigliadin deamidated peptide IgG, and rheumatoid factor IgM (RF). Differences in prevalence between patients with nonaffective psychoses (N=105), bipolar disorders (N=78), unipolar depressive disorders (N=146), and other reasons for admission (N=256) were assessed using chi-square tests and logistic regression models.
Results:
One or more autoantibodies were present in 26.2% of the patients, including ANA (9.4%), RF (9.2%), and anti-TPO (5.6%). Autoantibody prevalence increased with age (odds ratio=1.21, 95% CI=1.09–1.35) and smoking status (odds ratio=1.99, 95% CI=1.04–3.82) but was not associated with a diagnosis of a psychotic or affective disorder.
Conclusions:
Autoimmune autoantibodies seem to be equally prevalent in patients with acute psychiatric conditions with and without psychotic and affective disorders. This result challenges the idea that these autoantibodies have specificity for certain psychiatric disorders.
The hypothesis that autoimmunity can affect psychiatric symptomatology is intriguing, because it suggests that a subgroup of psychiatric patients might benefit from immune-modulatory rather than traditional psychopharmacological treatment (1, 2). Epidemiological studies have indicated that the number of infectious episodes and autoimmune disorders in a given patient increases the likelihood of developing psychotic and affective disorders (3, 4). In particular, autoimmune disorders associated with well-known autoantibodies such as thyroid and lupus antibodies seem to be associated with severe mental disorders (4–7). Interestingly, several studies indicate that autoantibodies associated with systemic autoimmune disorders are more prevalent in patients with severe mental disorders as compared with healthy controls (6–9).
However, not all studies examining the association of autoantibodies with psychiatric morbidity have indicated a positive correlation (10, 11). In addition, most positive studies have been limited by small sample sizes, use of healthy volunteers as controls, and lack of correction for confounding factors (7, 12). Large clinical studies with more relevant control groups are therefore needed.
In this study, we chose several clinically relevant autoantibodies (associated with systemic autoimmune disorders) previously found to be more prevalent in patients with schizophrenia or affective disorders as compared with healthy controls (6, 7). We aimed to explore the prevalence of these autoantibodies in a large sample of patients admitted to acute psychiatric inpatient care, and investigate whether the prevalence is higher in patients with nonaffective psychoses and unipolar depressive and bipolar disorders (index groups) compared with patients admitted for other reasons (control group).
Methods
This study is part of a broader study on the prevalence of autoantibodies in patients admitted to acute psychiatric inpatient care. Data on the prevalence of antineuronal antibodies in the same cohort have been presented in two previous reports (13, 14).
Setting and Patients
This cross-sectional study was performed in an acute psychiatric center (St. Olav’s Hospital, Trondheim University Hospital, Trondheim, Norway). At the time the study was conducted the center served a catchment area of 140,000 inhabitants, representing the only acute psychiatric inpatient service for people aged 18 years and above. Patients were referred to the center from general practice and medical and surgical departments. The most common referral diagnoses were suicidal ideation, onset or exacerbations of psychiatric disorder (depression, bipolar disorder, schizophrenia spectrum disorders, personality disorders), and psychiatric symptoms related to substance use.
Inclusion and Exclusion Criteria
All patients admitted to the acute psychiatric inpatient department between October 2004 and November 2006 were eligible for inclusion. The only exclusion criterion was lack of patient consent or ability to give consent.
Diagnostic Evaluation
Patients were diagnosed according to ICD-10 criteria (15) and divided into four categories: nonaffective psychoses (F20–29), bipolar affective disorders (F30–31), unipolar depressive disorders (F32–33), and other diagnoses (for a detailed overview of the specific psychiatric diagnoses in each category, see Table 1). Final diagnoses were set in a consensus meeting including at least two psychiatrists or senior clinical psychologists. If multiple diagnoses were made, we registered the clinicians’ main psychiatric diagnosis. A diagnosis of nonaffective psychosis, depression, or bipolar disorder was given priority over comorbid disorders (e.g. personality disorders or substance use disorders).
Diagnostic category | N |
---|---|
Schizophrenia spectrum disorders F20–29 (N=105) | |
Schizophrenia F20 | |
Paranoid F20.0 | 35 |
Hebephrenic F20.1 | 5 |
Catatonic F20.2 | 4 |
Undifferentiated F20.3 | 4 |
Others F20.6, F20.9 | 6 |
Schizotypal disorders F21 | 4 |
Delusional disorders F22 | 23 |
Acute and transient psychotic disorders F23 | 9 |
Schizoaffective disorders F25 | 8 |
Other or unspecified psychotic disorders F28–29 | 7 |
Depressive disorders F32–33 (N=146) | |
Depressive episode F32 | |
Mild F32.0 | 7 |
Moderate F32.1 | 31 |
Severe F32.2 | 19 |
Severe with psychosis F32.3 | 2 |
Severity unknown | 4 |
Recurrent depressive disorder, current episode F33 | |
Mild F33.0 | 13 |
Moderate F33.1 | 44 |
Severe F33.2 | 18 |
Severe with psychosis F33.3 | 4 |
In remission F33.4 | 1 |
Severity unknown | 3 |
Bipolar disorders F30–31 (N=78) | |
Manic episode F30 | |
Hypomania F30.0 | 1 |
Mania F30.1 | 2 |
Bipolar disorders, current episode F31 | |
Hypomania F31.0 | 8 |
Mania F31.1 | 12 |
Psychotic mania F31.2 | 14 |
Mild or moderate depression F31.3 | 12 |
Severe depression F31.4 | 5 |
Psychotic depression F31.5 | 4 |
Mixed episode F31.6 | 7 |
In remission F31.7 | 6 |
Other or unspecified F31.8–9 | 7 |
Control group (N=256) | |
Organic mental disorders F00–09 | 28 |
Mental disorders due to substance use F10–19 | 81 |
Other affective disorders F34–39 | 4 |
Neurotic, stress-related and somatoform disorders F40–49 | 47 |
Behavioral syndromes associated with physiological disturbances and physical factors F50–59 | 2 |
Personality disorders F60–69 | 31 |
Mental retardation F70–79 | 5 |
Behavioral and emotional disorders with onset usually occurring in childhood and adolescence F90–99 | 8 |
Z diagnosesa | 41 |
Somatic diagnoses | 3 |
X and Y diagnosesb | 6 |
TABLE 1. Number of patients in each International Classification of Diseases (ICD)–10 diagnostic categorya
Assessment of Autoimmune Comorbidity and Smoking Status
Patients completed questionnaires during the index admission assessing their smoking status and history of rheumatoid arthritis, systemic lupus erythematosus, celiac disease, or “other rheumatic disorders”.
Antibody Analyses
Serum samples were collected the first working day after admission and stored at −80° until the time of analysis. In 11 patients, samples were collected at discharge. Autoantibody analyses were performed between October and December 2016. Antinuclear antibodies (ANA) were analyzed using the ANA screen Bioplex 2200 (Bio-Rad, Hercules, Calif.), which allows for simultaneous detection of antibodies against ds-DNA, chromatin, Ribosomal P, SS-A 60, SS-A 52, SS-B, Sm, SmRNP, RNP A, RNP68, Scl-70, Jo-1, and Centromere B. The sample was considered ANA positive if any of those antibodies were detected. Antiphospholipid antibodies (anticardiolipin [IgG and IgM] and antibeta2-glycoprotein [IgG and IgM]) were analyzed using APLS IgG, IgM and IgA Bioplex 2200 (Bio-Rad). Antithyroid peroxidase (anti-TPO, IgG), antitissue transglutaminase IgA (anti-tTG IgA), and antigliadin deamidated peptide (antigliadin DP, IgG) were analyzed using the EliA method (Thermo Fisher Scientific, Uppsala, Sweden), and rheumatoid factor (RF) IgM was analyzed using ELISA (Inova Diagnostics, San Diego). In addition, we analyzed high-sensitive C-reactive protein (hs-CRP) (Roche Diagnostics, Mannheim, Germany). All analyses were performed according to the instructions from the manufacturer, and recommended cut-off values were used. Borderline values were considered negative.
Ethics
All participating patients gave written informed consent. The study was approved by the Norwegian Social Science Data Services and Regional Committee for Medical Research Ethics, Middle Norway, and registered at ClinicalTrials.gov (NCT00184418; https://clinicaltrials.gov/ct2/show/NCT00184418). Data collection and analysis were performed according to the Declaration of Helsinki.
Statistics
Antibody variables are presented as dichotomous (positive-negative), and not continuous (titers) variables. Continuous variables would have a lot of missing data because the majority of test results were below detection limits. We assessed differences in baseline characteristics and autoantibody prevalence between diagnostic categories by using chi-square test or Fisher’s exact test (if >0 cell had expected count <5) for categorical variables and Student’s t test, Mann-Whitney U test, or Kruskal-Wallis test for continuous variables. For antibodies with a sufficient number of serum positive patients we designed a logistic regression model using age, sex, and diagnostic category as independent variables. We included smoking status as an independent variable where such data were available. We performed post hoc analyses to compare the autoantibody prevalence in patients with schizophrenia to that in patients with other nonaffective psychoses. A p value <0.05 was considered to be significant. SPSS version 21.0 (IBM, Armonk, N.Y.) for Mac was used for all statistical analysis.
Results
General Patient Characteristics
Five hundred eighty-five of 832 patients (70.3%) admitted during the study period consented to participate in the study (mean age=40.6 years [SD=16.8], range, 17–94; 48.5% males). Table 2 shows demographic data, smoking status, history of autoimmune diseases, and hs-CRP for patients in the diagnostic categories. The mean age was significantly lower in the control group than in the other diagnostic categories (Kruskal-Wallis test, p<0.001). There were no significant sex differences between the diagnostic categories. The post hoc comparison of patients with nonaffective psychoses revealed that schizophrenia patients were more frequently male (p=0.03) and had a lower mean age (p=0.03) than patients with other nonaffective psychoses (Table 3). Smoking was more frequent among depressed patients as compared with the control group (χ2=8.88, p=0.01, data available for 264 patients [45.1%]). Only three patients had rheumatoid arthritis, whereas none had systemic lupus erythematosus, celiac disease, antiphospholipid syndrome, or autoimmune thyroiditis (data available for 233 patients [39.8%]). In patients with nonaffective psychoses, hs-CRP was statistical significantly elevated as compared with patients with depressive disorders (p=0.01) and other reasons for admission (p=0.03), but not bipolar disorders (p=0.54).
Characteristic | Nonaffective psychosis (N=105) | Unipolar depressive disorders (N=146) | Bipolar disorders (N=78) | Control group (N=256) | Total (N=585) | p | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
Mean | SD | Mean | SD | Mean | SD | Mean | SD | Mean | SD | ||
Age (years) | 43.6 | 15.3 | 42.4 | 17.4 | 43.7 | 15.4 | 37.5 | 16.9 | 40.6 | 16.8 | <0.001* |
N | % | N | % | N | % | N | % | N | % | ||
Sex, male | 53 | 50.5 | 61 | 41.8 | 40 | 51.3 | 130 | 50.8 | 284 | 48.5 | 0.31** |
Smoker | 23/34 | 68 | 40/81 | 49 | 18/32 | 56 | 81/117 | 69 | 162/264 | 61 | 0.03** |
Rheumatoid arthritis, systemic lupus erythematosus, celiac diseasea | 1/29 | 0/68 | 1/28 | 1/108 | 3/233 | - | |||||
Median | Interquartile range | Median | Interquartile range | Median | Interquartile range | Median | Interquartile range | Median | Interquartile range | ||
hs-CRPb | 2.37 | 0.89–6.10 | 1.42 | 0.62–3.41 | 1.93 | 0.86–5.10 | 1.41 | 0.55–4.55 | 1.69 | 0.63–4.43 | 0.04* |
TABLE 2. Demographic characteristics, smoking status, history of relevant autoimmune diseases, and high-sensitivity C-reactive protein (hs-CRP)
Variable | Schizophrenia, F20.0–F20.9 (N=54) | Other nonaffective psychoses, F21–F29 (N=51) | pb | ||
---|---|---|---|---|---|
Mean | SD | Mean | SD | ||
Age (years) | 40.5 | 14.1 | 46.9 | 16.0 | 0.03c |
N | % | N | % | ||
Sex, males | 33 | 61.1 | 20 | 39.2 | 0.03 |
Smokersd | 9 | 64.3 | 14 | 70.0 | 1.00 |
ANA | 9 | 16.7 | 6 | 11.8 | 0.58 |
APLS | 3 | 5.6 | 2 | 3.9 | 1.00 |
Anti-TPO | 4 | 7.4 | 3 | 5.9 | 1.00 |
AntitTG IgA | 0 | 0.0 | 1 | 2.0 | 0.49 |
Antigliadin DP IgG | 0 | 0.0 | 3 | 5.9 | 0.11 |
RF IgM | 9 | 16.7 | 3 | 5.9 | 0.12 |
≥1 Autoantibody | 20 | 37.0 | 15 | 29.4 | 0.54 |
Median | Interquartile range | Median | Interquartile range | ||
hs-CRPe | 2.44 | 0.96–8.13 | 2.27 | 0.81–4.40 | 0.36f |
TABLE 3. Comparison of patients with schizophrenia and other nonaffective psychosesa
Autoantibody Prevalence
One or more antibodies were detected in 26.2% of the patients. The most prevalent antibodies were ANA (9.4%), RF IgM (9.2%), and anti-TPO (5.6%). There were no significant differences in prevalence of any of the measured antibodies between the diagnostic categories and the control group in the univariate analyses (Tables 4 and 5). Antigliadin DP IgG was detected more frequently in patients with bipolar disorders as compared with unipolar depressive disorders (p=0.014, Fisher’s exact test). There were no significant differences in autoantibody prevalence between patients with schizophrenia and other nonaffective psychoses (Table 3).
Autoantibody | Nonaffective psychoses | Unipolar depressive disorder | Bipolar disorder | Control group | Total | pb | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ab. + N | Total N | % | Ab. + N | Total N | % | Ab. + N | Total N | % | Ab. + N | Total N | % | Ab. + N | Total N | % | ||
ANA | 15 | 105 | 14.3 | 10 | 146 | 6.8 | 8 | 78 | 10.3 | 22 | 256 | 8.6 | 55 | 585 | 9.4 | 0.23 |
RF IgM | 12 | 105 | 11.4 | 11 | 146 | 7.5 | 4 | 78 | 5.1 | 27 | 256 | 10.5 | 54 | 585 | 9.2 | 0.37 |
Anti-TPO | 7 | 105 | 6.7 | 7 | 146 | 4.8 | 7 | 78 | 9.0 | 12 | 256 | 4.7 | 33 | 585 | 5.6 | 0.45 |
Antigliadin DP IgG | 3 | 105 | 2.9 | 0 | 146 | 0.0 | 4 | 78 | 5.1 | 6 | 256 | 2.3 | 13 | 585 | 2.2 | 0.04 |
AntitTG IgA | 1 | 105 | 1.0 | 1 | 146 | 0.7 | 2 | 78 | 2.6 | 3 | 256 | 1.2 | 7 | 585 | 1.2 | 0.59 |
APLS | 5 | 105 | 4.8 | 2 | 146 | 1.4 | 1 | 78 | 1.3 | 7 | 256 | 2.7 | 15 | 585 | 2.6 | 0.39 |
≥ 1 autoantibody | 35 | 105 | 33.3 | 30 | 146 | 20.5 | 21 | 78 | 26.9 | 67 | 256 | 26.2 | 153 | 585 | 26.2 | 0.16 |
TABLE 4. Prevalence of autoantibodiesa
Autoantibody | Nonaffective psychoses | Depressive disorders | Bipolar disorder | Control group | Total | pb | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ab. + N | Total N | % | Ab. + N | Total N | % | Ab. + N | Total N | % | Ab. + N | Total N | % | Ab. + N | Total N | % | ||
Specific antinuclear antibodies | ||||||||||||||||
Antids-DNA | 3 | 105 | 2.9 | 1 | 146 | 0.7 | 2 | 78 | 2.6 | 4 | 256 | 1.6 | 10 | 585 | 1.7 | 0.45 |
Antichromatin | 1 | 105 | 1.0 | 1 | 146 | 0.7 | 0 | 78 | 0.0 | 4 | 256 | 1.6 | 6 | 585 | 1.0 | 0.83 |
Antiribosomal P | 0 | 105 | 0.0 | 0 | 146 | 0.0 | 0 | 78 | 0.0 | 0 | 256 | 0.0 | 0 | 585 | 0.0 | — |
Anti-SS-A 60 | 1 | 105 | 1.0 | 2 | 146 | 1.4 | 1 | 78 | 1.3 | 1 | 256 | 0.4 | 5 | 585 | 0.9 | 0.50 |
Anti-SS-A 52 | 1 | 105 | 1.0 | 0 | 146 | 0.0 | 1 | 78 | 1.3 | 1 | 256 | 0.4 | 3 | 585 | 0.5 | 0.31 |
Anti-SS-B | 0 | 105 | 0.0 | 2 | 146 | 1.4 | 3 | 78 | 3.8 | 4 | 256 | 1.6 | 9 | 585 | 1.5 | 0.22 |
Anti-Sm | 0 | 105 | 0.0 | 1 | 146 | 0.7 | 0 | 78 | 0.0 | 1 | 256 | 0.4 | 2 | 585 | 0.3 | 1.00 |
Anti-SmRNP | 0 | 105 | 0.0 | 1 | 146 | 0.7 | 0 | 78 | 0.0 | 1 | 256 | 0.4 | 2 | 585 | 0.3 | 1.00 |
Anti-RNP A | 7 | 105 | 6.7 | 2 | 146 | 1.4 | 2 | 78 | 2.6 | 7 | 256 | 2.7 | 18 | 585 | 3.1 | 0.14 |
Anti-RNP68 | 0 | 105 | 0.0 | 0 | 146 | 0.0 | 0 | 78 | 0.0 | 0 | 256 | 0.0 | 0 | 585 | 0.0 | — |
Anti-Scl 70 | 2 | 105 | 1.9 | 2 | 146 | 1.4 | 2 | 78 | 2.6 | 1 | 256 | 0.4 | 7 | 585 | 1.2 | 0.20 |
Anti-Jo–1 | 0 | 105 | 0.0 | 0 | 146 | 0.0 | 0 | 78 | 0.0 | 0 | 256 | 0.0 | 0 | 585 | 0.0 | — |
Anticentromere B | 0 | 105 | 0.0 | 1 | 146 | 0.7 | 0 | 78 | 0.0 | 0 | 256 | 0.0 | 1 | 585 | 0.2 | 0.56 |
Specific APLS antibodies | ||||||||||||||||
Anticardiolipin IgG | 1 | 105 | 1.0 | 0 | 146 | 0.0 | 0 | 78 | 0.0 | 4 | 256 | 1.6 | 5 | 585 | 0.9 | 0.46 |
Anticardiolipin IgM | 5 | 105 | 4.8 | 1 | 146 | 0.7 | 1 | 78 | 1.3 | 5 | 256 | 2.0 | 12 | 585 | 2.1 | 0.18 |
Antibeta2-glycop. IgG | 1 | 105 | 1.0 | 0 | 146 | 0.0 | 0 | 78 | 0.0 | 2 | 256 | 0.8 | 3 | 585 | 0.5 | 0.74 |
Antibeta2-glycop. IgM | 5 | 105 | 4.8 | 2 | 146 | 1.4 | 1 | 78 | 1.3 | 5 | 256 | 2.0 | 13 | 585 | 2.2 | 0.33 |
TABLE 5. Prevalence of specific antinuclear and antiphospholipid antibodiesa
Logistic regression models were designed for ANA, anti-TPO, RF, and positivity to one or more antibodies. None of the psychiatric diagnostic groups were significantly associated with the presence of autoantibodies (Table 6). Anti-TPO was more frequently present in females than men (odds ratio=2.31, 95% CI=1.08–4.97, p=0.03). For every 10-year increase in age, the odds ratio for presence of one or more antibodies increased with an odds ratio of 1.21 (95% CI=1.09–1.35, p=0.001). Being a smoker increased the likelihood of a positive test to one or more antibodies with an odds ratio of 1.99 (95% CI=1.04–3.82, p=0.04) (Table 7).
Autoantibody and independent variable | Odds ratioa | 95% CI | p |
---|---|---|---|
Antinuclear antibodies | |||
Sex (females versus males) | 1.17 | 0.67–2.06 | 0.58 |
Ageb | 1.13 | 0.96–1.33 | 0.14 |
Diagnostic category overall | 0.27 | ||
Depressive disorders | 0.72 | 0.33–1.59 | 0.42 |
Bipolar disorders | 1.13 | 0.48–2.66 | 0.78 |
Nonaffective psychoses | 1.65 | 0.81–3.35 | 0.17 |
Antithyroid peroxidase | |||
Sex (females versus males) | 2.31 | 1.08–4.97 | 0.03* |
Ageb | 1.07 | 0.87–1.32 | 0.51 |
Diagnostic category overall | 0.50 | ||
Depressive disorders | 0.92 | 0.35–2.42 | 0.86 |
Bipolar disorders | 1.93 | 0.72–5.16 | 0.19 |
Nonaffective psychoses | 1.38 | 0.52–3.67 | 0.51 |
Rheumatoid factor | |||
Sex (females versus males) | 1.13 | 0.64–1.98 | 0.68 |
Ageb | 1.16 | 0.99–1.36 | 0.07 |
Diagnostic category overall | 0.30 | ||
Depressive disorders | 0.63 | 0.30–1.33 | 0.23 |
Bipolar disorders | 0.42 | 0.14–1.24 | 0.12 |
Nonaffective psychoses | 1.00 | 0.48–2.08 | 0.99 |
≥ 1 Autoantibody | |||
Sex (females versus males) | 1.34 | 0.92–1.95 | 0.13 |
Ageb | 1.21 | 1.09–1.35 | 0.001* |
Diagnostic category overall | 0.13 | ||
Depressive disorders | 0.64 | 0.39–1.05 | 0.08 |
Bipolar disorders | 0.92 | 0.51–1.65 | 0.78 |
Nonaffective psychoses | 1.26 | 0.76–2.08 | 0.37 |
TABLE 6. Logistic regression model for antibodies with a sufficient number of serum positive patients (N=585)
Autoantibody and independent variable | Odds ratioa | 95% CI | p |
---|---|---|---|
Antinuclear antibodies | |||
Sex (females versus males) | 0.98 | 0.37–2.60 | 0.96 |
Ageb | 1.51 | 1.06–2.16 | 0.02* |
Smoking status | 2.71 | 0.82–8.94 | 0.10 |
Diagnostic category overall | 0.91 | ||
Depressive disorders | 0.90 | 0.27–2.97 | 0.86 |
Bipolar disorders | 0.69 | 0.13–3.64 | 0.67 |
Nonaffective psychoses | 0.56 | 0.11–3.00 | 0.50 |
Antithyroid peroxidase | |||
Sex (females versus males) | 2.66 | 0.82–8.70 | 0.11 |
Ageb | 1.18 | 0.80–1.74 | 0.41 |
Smoking status | 2.91 | 0.78–10.8 | 0.11 |
Diagnostic category overall | 0.83 | ||
Depressive disorders | 1.49 | 0.43–5.17 | 0.53 |
Bipolar disorders | 0.60 | 0.07–5.46 | 0.65 |
Nonaffective psychoses | 1.00 | 0.18–5.51 | 1.00 |
Rheumatoid factor | |||
Sex (females versus males) | 0.92 | 0.38–2.25 | 0.86 |
Ageb | 1.22 | 0.88–1.69 | 0.24 |
Smoking status | 1.54 | 0.57–4.18 | 0.40 |
Diagnostic category overall | 0.24 | ||
Depressive disorders | 0.42 | 0.12–1.43 | 0.16 |
Bipolar disorders | 0.24 | 0.03–2.02 | 0.19 |
Nonaffective psychoses | 1.26 | 0.39–4.07 | 0.70 |
≥ 1 Autoantibody | |||
Sex (females versus males) | 1.02 | 0.57–1.84 | 0.94 |
Ageb | 1.38 | 1.11–1.71 | 0.003* |
Smoking status | 1.99 | 1.04–3.82 | 0.04* |
Diagnostic category overall | 0.75 | ||
Depressive disorders | 0.69 | 0.33–1.44 | 0.33 |
Bipolar disorders | 0.67 | 0.25–1.80 | 0.43 |
Nonaffective psychoses | 0.80 | 0.32–2.01 | 0.64 |
TABLE 7. Logistic regression model for antibodies with a sufficient number of serum positive patients, including smoking status as an independent variable (N=264)
Discussion
In this large single-center study, the prevalence of several clinically relevant autoantibodies did not differ between patients with nonaffective psychoses and unipolar and bipolar affective disorders and patients with other psychiatric diagnoses. The prevalence of autoantibodies at admission to acute psychiatric inpatient care was more closely associated with age, sex, and smoking status than the psychiatric diagnostic categories explored.
The prevalence of ANA in our cohort did not differ significantly between the diagnostic groups. Further, the prevalence of ANA in our cohort is similar to the prevalence previously reported in healthy individuals (16). According to systematic reviews, the prevalence of ANA is increased in patients with schizophrenia (7) but not affective disorders (12). However, the authors of a more recent study reported similar prevalence of ANA in a large sample of schizophrenia patients and healthy controls (11). The authors of this study argued that previous studies were limited by small sample sizes and lack of control for confounding factors (e.g., age, sex, and use of medications). They also noted that the different methods used to detect ANA might account for some of the conflicting findings. Whereas most studies have used indirect immunofluorescence on human epidermoid cell line type 2, we employed an automated, multiplex analysis of 13 defined antigens. The indirect immunofluorescence method includes all possible human nuclear antigens, which makes it more sensitive but less specific compared with the multiplex method (17). The lack of an association between ANA and nonaffective psychotic disorders in our study is in line with two other recent studies (11, 18).
Although the prevalence of RF IgM in our cohort was somewhat higher than the prevalence among healthy individuals of 3.6% as reported from the manufacturer, there were no differences in patients with psychotic and affective disorders compared with the control group. According to a review conducted by Ezeoke et al., (7) nine studies have reported on the prevalence of RF IgM in patients with patients with schizophrenia. The pooled prevalence was 15.1% in the patient groups compared with 6.3% in the control groups (p<0.01). However, most of these studies were small, did not correct for confounding factor, and used different analytical methods than we do today. In fact, only one of the studies was performed during the last 20 years. The authors of this study presented results similar to ours (10). This study and the findings in our study contradict previous reports on the association between RF IgM and schizophrenia. Larger studies with power to correct for relevant confounding factors are needed to conclude on this matter.
Anti-TPO is frequently present in the serum of healthy individuals (19) and has previously been associated with affective disorders (6, 20, 21). We could not replicate the latter finding in our cohort. Although the patients with bipolar disorders had a higher prevalence of anti-TPO as compared with controls, the difference was not statistically significant. It is possible that a larger sample or inclusion of certain subgroups (e.g., bipolar disorder type 1) would make our results more consistent with previous reports.
The prevalence of the celiac disease markers antigliadin DP IgG and antitTG IgA were low and did not differ between the index groups and control group. There is some evidence of an increased prevalence of antigliadin DP IgG in patients with bipolar disorders (22). An intergroup comparison in the present study revealed a higher prevalence of antigliadin DP IgG in patients with bipolar disorders (4/78) as compared with those with unipolar depressive disorders (0/146) (p=0.014). This finding should be interpreted with caution, however, since significance would be lost upon correction for multiple testing.
Anticardiolipin and antibeta2-glycoprotein were not significantly associated with psychotic or affective disorders in the present study. The authors of most previous studies on the subject have reported an increased prevalence of anticardiolipin in patients with schizophrenia (23–25). In contrast, Sirota et al. (26) reported lower anticardiolipin levels in schizophrenia patients, both during first episode psychoses and acute exacerbation of chronic schizophrenia. The conflicting results may be explained by differences in inclusion criteria or assays used to detect anticardiolipin. Additionally, the primary variable in the study conducted by Sirota et al. (26) was average absolute levels of anticardiolipin, whereas most other studies, including ours, present the results as categorical variables (positive or negative). Our findings indicate that anticardiolipin and antibeta2-glycoprotein are rarely encountered in acute psychiatric disorders, and the prevalence is similar in patients with psychotic and affective disorders and patients with other acute psychiatric disorders.
The study is limited by lack of data on pharmacological treatment (a potential confounding factor) and missing data on smoking status. In addition, the clinical status regarding autoimmune history in patients is limited to a self-report questionnaire. The low prevalence of autoantibodies could make the study underpowered to detect minor differences between diagnostic groups. Most previous studies on autoantibodies in patients with nonaffective psychotic disorders have focused on schizophrenia; thus, their results are not directly comparable to our nonaffective psychosis category.
The strengths of the study are the large sample size and the high inclusion rate, which allowed correction for confounding factors (age, sex, and smoking status). Further, even though the addition of a healthy control group would have strengthened the study, our control group consisting of patients with nonpsychotic and nonaffective acute psychiatric conditions is more relevant in a clinical setting. This design is an important supplement to control groups from previous studies consisting of healthy volunteers.
In conclusion, psychotic and affective disorders were not associated with autoantibodies in our large sample of patients admitted to acute psychiatric inpatient care. The clinical significance of autoantibodies for psychiatric disorders is, however, unknown. Future studies should have a longitudinal design, include relevant psychiatric control groups, and be powered to control for important confounding factors.
1 : Inflammation in Depression and the Potential for Anti-Inflammatory Treatment. Curr Neuropharmacol 2016; 14:732–742Crossref, Medline, Google Scholar
2 : Is it time for immunopsychiatry in psychotic disorders? Psychopharmacology (Berl) 2016; 233:1651–1660Crossref, Medline, Google Scholar
3 : The epidemiologic evidence linking autoimmune diseases and psychosis. Biol Psychiatry 2014; 75:300–306Crossref, Medline, Google Scholar
4 : Autoimmune diseases and severe infections as risk factors for mood disorders: a nationwide study. JAMA Psychiatry 2013; 70:812–820Crossref, Medline, Google Scholar
5 : Autoimmune diseases and severe infections as risk factors for schizophrenia: a 30-year population-based register study. Am J Psychiatry 2011; 168:1303–1310Crossref, Medline, Google Scholar
6 : Bipolar disorder and antithyroid antibodies: review and case series. Int J Bipolar Disord 2016; 4:5Crossref, Medline, Google Scholar
7 : A systematic, quantitative review of blood autoantibodies in schizophrenia. Schizophr Res 2013; 150:245–251Crossref, Medline, Google Scholar
8 : Biomarkers of gluten sensitivity in patients with non-affective psychosis: a meta-analysis. Schizophr Res 2014; 152:521–527Crossref, Medline, Google Scholar
9 : Circulating anti-brain autoantibodies in schizophrenia and mood disorders. Psychiatry Res 2015; 230:704–708Crossref, Medline, Google Scholar
10 : Spectrum of autoantibodies in Tunisian psychiatric inpatients. Immunol Invest 2012; 41:538–549Crossref, Medline, Google Scholar
11 : The prevalence of antinuclear antibodies in patients with schizophrenia spectrum disorders: results from a large cohort study. NPJ Schizophr 2015; 1:15013Crossref, Medline, Google Scholar
12 : Are anti-nuclear antibodies common in affective disorders? A review of the past 35 years. Psychosomatics 2007; 48:286–289Crossref, Medline, Google Scholar
13 : Onconeural Antibodies in Acute Psychiatric Inpatient Care. J Neuropsychiatry Clin Neurosci 2017; 29:74–76Link, Google Scholar
14 : Prevalence of serum anti-neuronal autoantibodies in patients admitted to acute psychiatric care. Psychol Med 2016; 46:3303–3313Crossref, Medline, Google Scholar
15 : The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines. Geneva, World Health Organization, 1992Google Scholar
16 : Evaluation of the BioPlex 2200 ANA screen: analysis of 510 healthy subjects: incidence of natural/predictive autoantibodies. Ann N Y Acad Sci 2005; 1050:380–388Crossref, Medline, Google Scholar
17 : Antinuclear antibody detection by automated multiplex immunoassay in untreated patients at the time of diagnosis. Autoimmun Rev 2012; 12:137–143Crossref, Medline, Google Scholar
18 : Prevalence and clinical characteristics of serum neuronal cell surface antibodies in first-episode psychosis: a case-control study. Lancet Psychiatry 2017; 4:42–48Crossref, Medline, Google Scholar
19 : Serum TSH, T(4), and thyroid antibodies in the United States population (1988 to 1994): National Health and Nutrition Examination Survey (NHANES III). J Clin Endocrinol Metab 2002; 87:489–499Crossref, Medline, Google Scholar
20 : The prevalence of affective disorder and in particular of a rapid cycling of bipolar disorder in patients with abnormal thyroid function tests. Clin Endocrinol (Oxf) 1996; 45:215–223Crossref, Medline, Google Scholar
21 : High rate of autoimmune thyroiditis in bipolar disorder: lack of association with lithium exposure. Biol Psychiatry 2002; 51:305–311Crossref, Medline, Google Scholar
22 : Markers of gluten sensitivity and celiac disease in bipolar disorder. Bipolar Disord 2011; 13:52–58Crossref, Medline, Google Scholar
23 : Elevated IGG and IGM anticardiolipin antibodies in a subgroup of medicated and unmedicated schizophrenic patients. Biol Psychiatry 1991; 30:731–735Crossref, Medline, Google Scholar
24 : Elevated anticardiolipin antibodies in schizophrenic patients before and during neuroleptic medication. Psychiatry Res 2009; 169:51–55Crossref, Medline, Google Scholar
25 : Anticardiolipin antibodies are elevated in drug-free, multiply affected families with schizophrenia. J Clin Immunol 1994; 14:73–78Crossref, Medline, Google Scholar
26 : Reduced anticardiolipin antibodies in first episode and chronic schizophrenia. Psychiatry Res 2006; 144:211–216Crossref, Medline, Google Scholar