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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 (47). 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 (69).

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).

TABLE 1. Number of patients in each International Classification of Diseases (ICD)–10 diagnostic categorya

Diagnostic categoryN
Schizophrenia spectrum disorders F20–29 (N=105)
 Schizophrenia F20
  Paranoid F20.035
  Hebephrenic F20.15
  Catatonic F20.24
  Undifferentiated F20.34
  Others F20.6, F20.96
 Schizotypal disorders F214
 Delusional disorders F2223
 Acute and transient psychotic disorders F239
 Schizoaffective disorders F258
 Other or unspecified psychotic disorders F28–297
Depressive disorders F32–33 (N=146)
 Depressive episode F32
  Mild F32.07
  Moderate F32.131
  Severe F32.219
  Severe with psychosis F32.32
  Severity unknown4
 Recurrent depressive disorder, current episode F33
  Mild F33.013
  Moderate F33.144
  Severe F33.218
  Severe with psychosis F33.34
  In remission F33.41
  Severity unknown3
Bipolar disorders F30–31 (N=78)
 Manic episode F30
  Hypomania F30.01
  Mania F30.12
 Bipolar disorders, current episode F31
  Hypomania F31.08
  Mania F31.112
  Psychotic mania F31.214
  Mild or moderate depression F31.312
  Severe depression F31.45
  Psychotic depression F31.54
  Mixed episode F31.67
  In remission F31.76
  Other or unspecified F31.8–97
Control group (N=256)
 Organic mental disorders F00–0928
 Mental disorders due to substance use F10–1981
 Other affective disorders F34–394
 Neurotic, stress-related and somatoform disorders F40–4947
 Behavioral syndromes associated with physiological disturbances and physical factors F50–592
 Personality disorders F60–6931
 Mental retardation F70–795
 Behavioral and emotional disorders with onset usually occurring in childhood and adolescence F90–998
 Z diagnosesa41
 Somatic diagnoses3
 X and Y diagnosesb6

aZ00–Z99 factors influencing health status and contact with health services.

bIntentional self-harm with medication or sharp objects.

TABLE 1. Number of patients in each International Classification of Diseases (ICD)–10 diagnostic categorya

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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).

TABLE 2. Demographic characteristics, smoking status, history of relevant autoimmune diseases, and high-sensitivity C-reactive protein (hs-CRP)

CharacteristicNonaffective psychosis (N=105)Unipolar depressive disorders (N=146)Bipolar disorders (N=78)Control group (N=256)Total (N=585)p
MeanSDMeanSDMeanSDMeanSDMeanSD
Age (years)43.615.342.417.443.715.437.516.940.616.8<0.001*
N%N%N%N%N%
Sex, male5350.56141.84051.313050.828448.50.31**
Smoker23/346840/814918/325681/11769162/264610.03**
Rheumatoid arthritis, systemic lupus erythematosus, celiac diseasea1/290/681/281/1083/233-
MedianInterquartile rangeMedianInterquartile rangeMedianInterquartile rangeMedianInterquartile rangeMedianInterquartile range
hs-CRPb2.370.89–6.101.420.62–3.411.930.86–5.101.410.55–4.551.690.63–4.430.04*

aThere were three participants with rheumatoid arthritis and none with systemic lupus erythematosus or celiac disease.

bData were available for 476/585 participants (nonaffective psychoses; N=84/105; depressive disorders: N=114/146; bipolar disorders: N=65/78; and other disorders: N=213/256).

* Kruskal-Wallis test. ** chi-square test.

TABLE 2. Demographic characteristics, smoking status, history of relevant autoimmune diseases, and high-sensitivity C-reactive protein (hs-CRP)

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TABLE 3. Comparison of patients with schizophrenia and other nonaffective psychosesa

VariableSchizophrenia, F20.0–F20.9 (N=54)Other nonaffective psychoses, F21–F29 (N=51)pb
MeanSDMeanSD
Age (years)40.514.146.916.00.03c
N%N%
Sex, males3361.12039.20.03
Smokersd964.31470.01.00
ANA916.7611.80.58
APLS35.623.91.00
Anti-TPO47.435.91.00
AntitTG IgA00.012.00.49
Antigliadin DP IgG00.035.90.11
RF IgM916.735.90.12
≥1 Autoantibody2037.01529.40.54
MedianInterquartile rangeMedianInterquartile range
hs-CRPe2.440.96–8.132.270.81–4.400.36f

aANA=antinuclear antibodies, antitTG=antitissue transglutaminase, anti-TPO=antithyroid peroxidase, APLS=antiphospholipid antibodies, DP=deaminated protein, hs-CRP=high-sensitivity C-reactive protein, Ig=immunoglobulin, RF=rheumatoid factor.

bChi-square test or Fisher’s exact test was used unless specified otherwise.

cStudent’s t-test was used.

dData were available for 34/105 patients (schizophrenia, N=14/54; other nonaffective psychoses, N=20/51).

eData were available for 84/105 patients (schizophrenia, N=42/54; other nonaffective psychoses, N=42/51).

fMann-Whitney U test was used.

TABLE 3. Comparison of patients with schizophrenia and other nonaffective psychosesa

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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).

TABLE 4. Prevalence of autoantibodiesa

AutoantibodyNonaffective psychosesUnipolar depressive disorderBipolar disorderControl groupTotalpb
Ab. + NTotal N%Ab. + NTotal N%Ab. + NTotal N%Ab. + NTotal N%Ab. + NTotal N%
ANA1510514.3101466.887810.3222568.6555859.40.23
RF IgM1210511.4111467.54785.12725610.5545859.20.37
Anti-TPO71056.771464.87789.0122564.7335855.60.45
Antigliadin DP IgG31052.901460.04785.162562.3135852.20.04
AntitTG IgA11051.011460.72782.632561.275851.20.59
APLS51054.821461.41781.372562.7155852.60.39
≥ 1 autoantibody3510533.33014620.5217826.96725626.215358526.20.16

aAb. +=antibody positive, ANA=antinuclear antibodies, APLS=antiphospholipid antibodies, anti-TPO=antithyroid peroxidase, antitTG=antitissue transglutaminase, DP=deaminated protein, Ig=immunoglobulin, RF=rheumatoid factor.

bChi-square test or Fisher’s exact test was used for group comparison (2×4).

TABLE 4. Prevalence of autoantibodiesa

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TABLE 5. Prevalence of specific antinuclear and antiphospholipid antibodiesa

AutoantibodyNonaffective psychosesDepressive disordersBipolar disorderControl groupTotalpb
Ab. + NTotal N%Ab. + NTotal N%Ab. + NTotal N%Ab. + NTotal N%Ab. + NTotal N%
Specific antinuclear antibodies
 Antids-DNA31052.911460.72782.642561.6105851.70.45
 Antichromatin11051.011460.70780.042561.665851.00.83
 Antiribosomal P01050.001460.00780.002560.005850.0
 Anti-SS-A 6011051.021461.41781.312560.455850.90.50
 Anti-SS-A 5211051.001460.01781.312560.435850.50.31
 Anti-SS-B01050.021461.43783.842561.695851.50.22
 Anti-Sm01050.011460.70780.012560.425850.31.00
 Anti-SmRNP01050.011460.70780.012560.425850.31.00
 Anti-RNP A71056.721461.42782.672562.7185853.10.14
 Anti-RNP6801050.001460.00780.002560.005850.0
 Anti-Scl 7021051.921461.42782.612560.475851.20.20
 Anti-Jo–101050.001460.00780.002560.005850.0
 Anticentromere B01050.011460.70780.002560.015850.20.56
Specific APLS antibodies
 Anticardiolipin IgG11051.001460.00780.042561.655850.90.46
 Anticardiolipin IgM51054.811460.71781.352562.0125852.10.18
 Antibeta2-glycop. IgG11051.001460.00780.022560.835850.50.74
 Antibeta2-glycop. IgM51054.821461.41781.352562.0135852.20.33

aAb. +=antibody positive, APLS=antiphospholipid syndrome, ds-DNA=doubled-stranded deoxyribonucleic acid, glycop=glycoprotein, Ig=immunoglobulin, SS-A/B: Sjogren’s syndrome-related antigen A and B, Scl=scleroderma, Sm=Smith, RNP=ribonucleoprotein.

bFisher’s exact test was used.

TABLE 5. Prevalence of specific antinuclear and antiphospholipid antibodiesa

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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).

TABLE 6. Logistic regression model for antibodies with a sufficient number of serum positive patients (N=585)

Autoantibody and independent variableOdds ratioa95% CIp
Antinuclear antibodies
 Sex (females versus males)1.170.67–2.060.58
 Ageb1.130.96–1.330.14
 Diagnostic category overall0.27
 Depressive disorders0.720.33–1.590.42
 Bipolar disorders1.130.48–2.660.78
 Nonaffective psychoses1.650.81–3.350.17
Antithyroid peroxidase
 Sex (females versus males)2.311.08–4.970.03*
 Ageb1.070.87–1.320.51
 Diagnostic category overall0.50
 Depressive disorders0.920.35–2.420.86
 Bipolar disorders1.930.72–5.160.19
 Nonaffective psychoses1.380.52–3.670.51
Rheumatoid factor
 Sex (females versus males)1.130.64–1.980.68
 Ageb1.160.99–1.360.07
 Diagnostic category overall0.30
 Depressive disorders0.630.30–1.330.23
 Bipolar disorders0.420.14–1.240.12
 Nonaffective psychoses1.000.48–2.080.99
≥ 1 Autoantibody
 Sex (females versus males)1.340.92–1.950.13
 Ageb1.211.09–1.350.001*
 Diagnostic category overall0.13
 Depressive disorders0.640.39–1.050.08
 Bipolar disorders0.920.51–1.650.78
 Nonaffective psychoses1.260.76–2.080.37

aThe control group is the reference standard for the odds ratio for diagnostic categories.

bThe data represent the odds ratio for every 10-year increase in age.

* p<0.05.

TABLE 6. Logistic regression model for antibodies with a sufficient number of serum positive patients (N=585)

Enlarge table

TABLE 7. Logistic regression model for antibodies with a sufficient number of serum positive patients, including smoking status as an independent variable (N=264)

Autoantibody and independent variableOdds ratioa95% CIp
Antinuclear antibodies
 Sex (females versus males)0.980.37–2.600.96
 Ageb1.511.06–2.160.02*
 Smoking status2.710.82–8.940.10
 Diagnostic category overall0.91
 Depressive disorders0.900.27–2.970.86
 Bipolar disorders0.690.13–3.640.67
 Nonaffective psychoses0.560.11–3.000.50
Antithyroid peroxidase
 Sex (females versus males)2.660.82–8.700.11
 Ageb1.180.80–1.740.41
 Smoking status2.910.78–10.80.11
 Diagnostic category overall0.83
 Depressive disorders1.490.43–5.170.53
 Bipolar disorders0.600.07–5.460.65
 Nonaffective psychoses1.000.18–5.511.00
Rheumatoid factor
 Sex (females versus males)0.920.38–2.250.86
 Ageb1.220.88–1.690.24
 Smoking status1.540.57–4.180.40
 Diagnostic category overall0.24
 Depressive disorders0.420.12–1.430.16
 Bipolar disorders0.240.03–2.020.19
 Nonaffective psychoses1.260.39–4.070.70
≥ 1 Autoantibody
 Sex (females versus males)1.020.57–1.840.94
 Ageb1.381.11–1.710.003*
 Smoking status1.991.04–3.820.04*
 Diagnostic category overall0.75
 Depressive disorders0.690.33–1.440.33
 Bipolar disorders0.670.25–1.800.43
 Nonaffective psychoses0.800.32–2.010.64

aThe control group is the reference standard for the odds ratio for diagnostic categories.

bThe data represent the odds ratio for every 10-year increase in age.

* p<0.05.

TABLE 7. Logistic regression model for antibodies with a sufficient number of serum positive patients, including smoking status as an independent variable (N=264)

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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 (2325). 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.

The St. Olavs Hospital, Trondheim University Hospital, Division of Mental Health Care, Trondheim, Norway (Sæther, Larsen, Vaaler, Reitan); the Norwegian University of Science and Technology, Faculty of Medicine and Health Science, Department of Mental Health, Trondheim, Norway (Sæther, Larsen, Vaaler, Kondziella, Reitan); the St. Olav’s Hospital, Trondheim University Hospital, Department of Immunology and Transfusion Medicine, Trondheim, Norway (Rø); the Norwegian University of Science and Technology, Faculty of Medicine and Health Science, Department of Public Health and Nursing, Trondheim, Norway (Rø); the Rigshospitalet, Copenhagen University Hospital, Department of Neurology, Copenhagen, Denmark (Kondziella), and the University of Copenhagen, Faculty of Health and Medical Sciences, Copenhagen, Denmark (Kondziella).
Send correspondence to Dr. Sæther ().

The authors report no financial relationships with commercial interests.

The authors thank the following departments at St. Olav’s Hospital, Trondheim University Hospital, for financing the analyses performed in this study: Østmarka Department of Psychiatry, Tiller District Psychiatry Center and Clinic of Laboratory Medicine, and the Department of Immunology and Transfusion.

The authors also thank biomedical laboratory scientists Øyvind Husøy and Marit Vik for drawing blood and preparing serum and biomedical laboratory scientists Marit Aarhaug, Mona Hårberg, and Maria Camilla Flormælen for performing all autoantibody analyses and Biobank1 for handling, registering, and storing blood samples.

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