• Abstract and Figures
• Public Full-text

1

Schizophrenia cannot be reliably distinguished from bipolar I disorder by yet another valid biological marker in psychiatry: predictive value of total minor physical anomalies in the schizophrenia-bipolar I status.

Stefan Todorov Sivkov1, Mladen Yordanov Mantarov2, Pavel Vesselinov Nonchev2,

Ferihan Ahmed-Popova1, Valentin Hristov Akabaliev2,

1Department of Anatomy, Histology and Embryology, Medical University, Plovdiv,

Bulgaria

2Department of Psychiatry and Medical Psychology, Medical University, Plovdiv, Bulgaria

Corresponding author:

Mladen Yordanov Mantarkov

Department of Psychiatry and Medical Psychology, Medical University, Plovdiv

15A V. Aprilov Blvd, 4002, Plovdiv, Bulgaria

E-mail: [email protected]

Tel/Fax: +35932641599 2

Number of words in the abstract: 227

Number of words in the manuscript: 3722

Tables: 5

Field: General topics in psychiatry and related fields

Running Title: SZ and BPI not discriminated by MPA-T

ABSTRACT

Aim: Minor physical anomalies are slight structural aberrations in ectodermal structures that reflect abnormal neurodevelopment. Though extensively investigated in schizophrenia, they have rarely been studied in bipolar disorder and direct comparisons are limited.

Currently, there is little consensus on the specificity of minor physical anomalies to schizophrenia. We attempted to assess the potential value of minor physical anomalies as a classifying test in the status schizophrenia versus bipolar I disorder.

Methods: 128 schizophrenia and 61 bipolar I patients were assessed using a slightly modified version of the Waldrop Physical Anomaly Scale. We calculated the specificity, sensitivity, positive and negative predictive value of each discrete total MPA score with which the patients presented. The percentage of outliers (subjects with numerous minor physical anomalies) was compared in the two groups. ROC-analyses with the most balanced total scores were performed in an attempt to differentiate between the two conditions. 3

Results: We found no cut-off total minor physical anomaly scores that discriminated reliably between schizophrenia and bipolar I patients (exhibiting balanced sets of sensitivity, specificity, positive and negative predictive values). The percentage of outliers did not differ significantly between schizophrenia and bipolar I patients. ROC-analyses with the most balanced cut-off scores found an unreliable area under the curve.

Conclusion: Our data suggest that total minor physical anomaly scores cannot be used as a reliable index in distinguishing between schizophrenia and bipolar I patients. In our sample the cumulative prevalence of total minor physical anomalies is not specific to schizophrenia or bipolar I disorder.

Key words: schizophrenia, bipolar disorder, minor physical anomalies, sensitivity, specificity

INTRODUCTION 4

Minor physical anomalies (MPAs) are a heterogeneous group of subtle, clinically and cosmetically insignificant errors in the development of morphological structures of ectodermal origin. They may be due to genetic (and epigenetic) variation or to environmental insults during the prenatal period. As the structures that express MPAs have the same embryonic origin as the central nervous system, MPAs are of considerable value as biological markers of abnormal brain development.

The consistently replicated higher prevalence of MPAs in schizophrenia (SZ) has provided confirmation for the neurodevelopmental hypothesis of SZ and has led to the suggestion that MPAs may represent a risk marker or even a possible endophenotype for the disorder. However, MPAs have also been reported with increased frequency in a number of other putative neurodevelopmental conditions such as autism, epilepsy, learning disabilities, speech and hearing impairments, mental retardation, poor motor coordination, attention deficit hyperactivity disorder, fetal alcohol syndrome, cerebral palsy and bipolar disorder. These findings raise the issue of specificity in the link between MPAs and SZ.

To date only two published studies have compared directly the prevalence of MPAs in SZ and bipolar disorder. They have found significantly more MPAs in SZ patients than in bipolar patients and normal controls and no significant differences between bipolar patients and controls, suggesting that MPAs may have some degree of specificity to SZ. To our knowledge no previous research has addressed explicitly the specificity and sensitivity of discrete values of the total MPA (MPA-T) score in the distinction between the two disorders. 5

As part of a larger research project on the neurodevelopmental basis of bipolar I disorder (BPI) and SZ, including subjects with SZ, BPI and normal controls, the present study aimed to determine the optimal discriminating value of MPA-T between SZ and BPI patients with regard to sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). In view of earlier findings on differences in the prevalence of

MPAs in SZ and bipolar disorder we hypothesized that specific MPA-T scores could be a reliable index for discriminating between SZ and BPI patients.

METHODS

Subjects

The subjects for this study were patients with SZ and BPI.

The SZ group consisted of 128 patients (66 men, 62 women), consecutively admitted to the Clinic of Psychiatry in Plovdiv, Bulgaria with mean age 32.09 years (SD =

9.73), mean duration of illness 8.02 (SD = 7.33) and mean number of hospitalizations 4.98

(SD = 5.36).

The BPI group comprised 61 patients (25 men, 36 women), consecutively admitted to the same clinic with mean age 38.15 years (SD = 14.81), mean duration of illness 10.57

(SD = 11.16) and mean number of hospitalizations 4.75 (SD = 4.32). Patients satisfied 6

DSM 5 criteria for a diagnosis of SZ and BPI, respectively, on the basis of case records review, a semi-structured interview based on a checklist of items from DSM 5 (performed by one of the study psychiatrists) and collateral information obtained from relatives to enhance the validity of the diagnosis. Potential subjects were excluded if they had any signs of mental retardation, a history of drug or alcohol abuse, an identifiable neurological disorder (seizure disorder, head injury, multiple sclerosis etc.) or a general medical condition with direct effects on the central nervous system.

All patients and controls were of Bulgarian origin in order to avoid the potential confounding effects of racial and ethnic variation in the expression of MPAs; individuals were excluded if their parental or grandparental ethnic group was other than Bulgarian.

The study was approved by the local Ethics Committee and all subjects gave written informed consent to participate.

Assessment of MPAs

The subjects were examined with a slightly modified version of the Waldrop Physical

Anomaly Scale. The original scale includes 18 morphological abnormalities from six body regions: head, eyes, ears, mouth, hands, and feet. Most of the abnormalities are scored qualitatively as present (1) or absent (0). The variables fine electric hair, head circumference, epicanthus, intercanthal distance, low-seated ears, adherent ear lobes /lower 7

edges of the ears that extend back or upward, high/steepled palate, curved 5th finger, 3rd toe

≥ 2nd are scored in a graded manner - 1 or 2, according to severity. We introduced the following modifications. The categories adherent ear lobes and lower edges of the ears that extend back or upward (two grades of a single item in the original scale) were defined as separate items because of the high prevalence of the former and only occasional occurrence of the latter. As a result of this distinction, our modification of the scale consisted of 19 items (Table 1). Furrowed tongue was graded by scoring 1 for randomly furrowed tongue

(a normal variant) and scoring 2 for transversely furrowed tongue (frequently observed in pathological conditions). In the original scale both types are scored 1. To determine the variable low-seated ears we verified the ear canal position by the level of the ear canal on the head in relation to the midface with the head of the subject placed in the Frankfurt horizontal line. Intercanthal distance abnormality was also determined in cases of hypotelorism. Intercanthal distance as well as head circumference were scored 1 if they differed from the same-sex mean for normal controls by 1.5 - 2 SD and 2 if they differed by more than 2 SD in both directions. Gap between 1st and 2nd toe was scored 1 if it was between 0.1 and 0.5 cm and as 2 if bigger than 0.6 cm.

All examinations were performed by one of the study anatomists, who had no formal training in psychiatry. In order to minimize potential scorer bias, he was not given access to patient records. All patient assessments were performed following adequate drug treatment to avoid the effect of evident signs of psychopathology on rater blindness.

Reliability studies using a second assessor were conducted previously in a study of SZ patients and normal controls. The two raters examined separately 30 patients with SZ (15 men, 15 women) and 20 normal controls (10 men, 10 women). Since an acceptable level of 8

reliability was not reached for the first and second grade of curved 5th finger, another modification to the scale was introduced. The item was scored only as present (1) or absent

(0), while in the original scale its presence is weighted (1 or 2).

Statistical Analyses

The data were analyzed with SPSS 22 using descriptive statistics; likelihood-ratio

2-test, Pearson 2-test (in 2х2 table with Yates’ correction for continuity) or Fisher's exact probability test: two-tailed for comparing categorical data. Two subjects (one from each group) were excluded from the analysis as we could not ascertain all the variables from the scale for the particular subjects.

Sensitivity, specificity, PPV and NPV of all MPA-T scores for the status SZ vs. BPI patients were calculated using the following formulas:

Sensitivity = true positives / (true positive + false negatives)

Specificity = true negatives / (true negatives + false positives)

PPV = true positives / (true positives + false positives)

NPV = true negatives / (true negatives + false negatives) 9

ROC-analyses with total MPA score≥5 and total MPA≥6 were performed to test the

specificity of the total MPA score in the differentiation between schizophrenia and

bipolar I disorder.

The level of statistical significance was set at P < 0.05.

RESULTS

Comparison of MPA-T scores between SZ and BPI patients

In both groups no case was scored 0 or 1. In SZ patients MPA-T ranged from 2 to

13, the mode was 5 (23.6%) and 17.4% of subjects had MPA-T ≥ 8. In BPI patients MPA-T ranged from 2 to 10, the mode was 4 (25.0%) and only 5.1% of subjects had MPA-T ≥ 8.

Generally, at higher MPA-T scores the percentage of cases was higher in the SZ group, while at lower MPA-T scores the percentage of cases was higher found among BPI patients. This trend however was not regular and systematic, and exceptions were observed in both directions. As a result, the difference in MPA-T distribution between the two groups was not statistically significant (P = 0.160; Table 2).

Discriminating effect, sensitivity, specificity and predictive value of MPA-T scores 10

The discriminating effect of MPA-T score for the SZ vs. BPI status was assessed by comparing the two groups at each step of the MPA-T hierarchical scoring. At steps above

MPA-T = 2 the percentage of SZ cases was greater than the percentage of BPI cases but the difference was statistically significant only for MPA-T  8 (P < 0.05). Thus MPA-T ≥ 8 was the only value that discriminated between SZ and BPI patients. Arguably, at higher steps of the MPA-T hierarchical scoring, the absolute number of cases was too small to detect significant differences. As a whole, our data suggest only moderate quantitative difference in MPA-T scores in favor of SZ that cannot be used to discriminate reliably between the two disorders (Table 3).

We calculated sensitivity, specificity, positive and negative predictive values of the different MPA-T scores to evaluate MPA-T as a classifying test in the status SZ vs. BPI patients (Table 4). In our model the test was the MPA-T score and the tested condition was

SZ.

The sensitivity of a test is the percentage of individuals with the tested condition, who are classified as having the condition. With the increase of MPA-T, its sensitivity as a test for SZ declined as the number of SZ cases (true positives) decreased at each step of the hierarchical scoring.

The specificity of a test is the percentage of individuals without the tested condition, who are classified as not having the condition. With the increase of MPA-T, its specificity 11

as a test for SZ improved as the number of BPI cases (false positives) decreased at higher steps of the hierarchical scoring.

The positive predictive value is the percentage of individuals with a positive test, who have the tested condition. Consequently, the increase in MPA-T was generally associated with an increase in its positive predictive value for SZ, because the percentage of

SZ patients (true positives) among the individuals with higher MPA-T values increased.

The negative predictive value is the percentage of individuals with a negative test, who do not have the tested condition. Hence, with the increase of MPA-T values, its negative predictive value for SZ generally decreased because the percentage of BPI patients

(true negatives) among all subjects with lower MPA-T values decreased.

The trends for the four test parameters (Table 4) were used to search for cut-off scores that discriminated reliably between SZ and BPI patients (presenting with balanced sets of sensitivity, specificity, PPV and NPV, in which the value of each test parameter is greater than 50%). Among all MPA-T scores, MPA-T  5 and MPA-T  6 were closest to meeting these requirements as they presented with the most balanced sets of values for the four test parameters.

MPA-T  5 classified as SZ patients 85 out of all 127 SZ patients (sensitivity –

66.9%) and as BPI patients 28 of all 60 BPI patients in the sample (specificity – 46.7%).

The same score assigned 85 SZ patients to the group of 117 subjects who tested positive for

MPA-T score  5 as a test value (positive predictive value – 72.6%) and 28 BPI patients to 12

the total of 70 subjects who tested negative for MPA-T score  5 as a test value (negative predictive value – 40.0%).

MPA-T  6 classified as SZ patients 55 out of all 127 SZ patients (sensitivity –

43.3%) and as BPI patients 37 out of all 60 BPI patients in the sample (specificity –

61.7%). 55 SZ patients were assigned to the group of 78 subjects who tested positive for

MPA-T score  6 as test value for SZ (positive predictive value – 70.5%). 37 BPI patients were assigned to the 109 subjects in the sample who tested negative for MPA-T score  6 as a test value (negative predictive value – 33.9%).

Thus, even the most “balanced” tests (MPA-T  5 and MPA-T  6) presented with test parameters that failed to meet the requirements for a satisfactory test: MPA-T  5 had low values (less than 50%) for specificity – 46.7% and negative predictive value – 40.0%) and MPA-T  6 had low values (under 50%) for sensitivity – 43.3% and negative predictive value – 33.9%).

Outliers

The specificity of MPAs was further evaluated by comparing the percentage of subjects with numerous MPAs (outliers) in the two groups. MPA-T  7, which was approximately 2 SD above the mean MPA-T score of normal controls (mean = 3.07, SD =

1.83) was accepted as a cut-off point for outliers. 29.9% of SZ patients 18.3% of BPI 13

patients presented with MPA-T scores ≥ 7. The difference between the two groups was not statistically significant (P = 0.133; Table 5).

ROC-analyses

Roc-analyses with total MPA scores equal or greater than five and six both found unacceptable areas under the curve (0.531 and 0.552, respectively) (Figures 1 and 2).

DISCUSSION

Our finding of a higher mean MPA-T score in SZ than in BPI (5.61 vs. 4.85, P =

0.022; Table 2) is in accordance with earlier studies and supports the hypothesis that patients with SZ may suffer from greater developmental adversity in comparison to BPI patients. However, it is worth noting that in contrast to these studies in our sample both SZ and BPI are characterized by a significant excess of MPAs compared to normal controls

(5.61, 4.85 and 3.07, respectively) . In fact the absolute values of the mean MPA-T scores imply that neurodevelopmental adversity may be more common in BPI than generally considered. Furthermore, the difference in MPA-T distribution between SZ and BPI patients falls short of statistical significance, while MPA-T distribution differences were highly significant in the comparisons of both SZ and BPI patients vs. normal controls (P <

0.001). If MPAs can be regarded as “fossilized imprints of early disturbance in embryonic 14

development“, their overrepresentation in SZ and BPI suggests a prenatal injury that increases the risk of both disorders in later phases of life. The two disorders may share more neurodevelopmental antecedents in their etiology than previously held.

MPA-T scores fail to discriminate reliably between SZ and BPI patients. Even the

“most balanced” tests present with unsatisfactory test parameters. MPA-T  5 has low specificity (46.7%) and NPV (40.0%) that result in an unacceptably high rate of false positive diagnoses (BPI patients classified as SZ patients). MPA-T  6 suffers from low sensitivity (43.3%) and PPV (33.9%) that cause a high rate of false-negative diagnoses (SZ patients classified as BPI patients). The two scores fail to define a border zone in which SZ patients begin to prevail definitely over BPI patients. We have found MPA-T cut-off scores with acceptable test parameters in the distinction between SZ patients and normal controls where MPA-T  4 and MPA-T  5 show balanced sets of sensitivity (76.3%, 56.6%), specificity (72.0%, 86.6%), PPV (71.6%, 79.6%) and NPV (76.6%, 68.3%, respectively).

In the distinction between BPI patients and normal controls MPA-T  4 and MPA-T  5 also present with acceptable test parameters for sensitivity (78.3, 53.3%), specificity

(63.1%, 79.6%), PPV (55.3%, 60.4%) and NPV (83.3%, 74.5%, respectively). It is notable that the cut-off scores which discriminate optimally SZ and BPI patients from normal controls are the same for the both disorders. They define a “border zone” that discernibly separates both SZ and BPI patients from controls. Thus MPA-T scores clearly tell both SZ and BPI from normality but appear to be of little value in the discrimination between the two disorders. 15

The proportion of outliers does not differ significantly between the two disorders, while both SZ and BPI patients include a significantly greater percentage of outliers than controls (P < 0.05). It may be speculated that comparable proportions of SZ and BPI patients suffer harsh prenatal insults resulting in numerous MPAs.

Finally, one caveat needs to be discussed. The study addressed only one aspect of

MPAs: their group discriminating effect between SZ and BPI patients. The use of total scores on the Waldrop scale has been criticized as the scale combines minor malformations and phenogenetic variants. As these two types of MPAs reflect the impact of prenatal insults at different stages of prenatal development (during and after organogenesis, respectively), their specificity for psychiatric disorders may vary. Besides, MPAs of the craniofacial region form concurrently with the in utero structural brain changes associated with SZ and may be more informative than the total MPA score. A growing body of research suggests that specific anomalies of the mouth and palate are more relevant to neurodevelopmental abnormalities than is the cumulative prevalence of MPAs.. Тези

резултати съответстват и на изследвания, получени при сравнителната

характеристика на други антропометрични показатели за дисонтогенеза при двете

заболявания (Umraniya YN, Modi HH, Prajapati HK. Sexual Dimorphism in

Dermatoglyphic Pattern Study, Medical Science 2013; 1 (1): 24-26; Arnone D, Cavanagh

J, Gerber D, Lawrie SM, Ebmeier KP, McIntosh AM. Magnetic resonance imaging studies in bipolar disorder and schizophrenia: meta-analysis. Br J Psychiatry 2009; 195: 194-

201). It is suggested that second trimester prenatal adversity can actually trigger both SZ and BPI later in life and the effect of these adversities may be gender-specific (Green M, 16

Bracha S, Satz P, Christensen C. Preliminary evidence for an association between minor physical anomalies and second trimester neurodevelopment in schizophrenia. Psychiatry

Res 1994; 53: 119-127). Половите различия относно дерматоглифите, например, биха

могли да се дължат и на половите особености в анатомичните структури на опорно-

двигателния апарат, които нормално разграничават двата пола. Babler допуска връзка

между изявата на определени хребетни изображения и развитието на скелетната

система на ръцете (Babler W. Prenatal development of dermatoglyphic patterns:

Associations with epidermal ridge, volar pad and bone morphology.Coll Antropol II 1987;

297-304). В този смисъл, изразените различия между двата пола биха могли да

определят мъжкия пол като по-податлив на отклонения в развитието на

ектодермалните производни (Akabaliev V, Sivkov S. Sexual dimorphism in minor physical anomalies in schizophrenic patients and normal controls. Comprehensive

Psychiatry 2003; 44 (4): 341-348).

MPAs are indicative of neurodevelopmental adversity as a non-specific risk factor that interacts with other genetic and environmental causes to produce severe mental illness in at least some SZ and BPI patients. MPA-T scores fail to discriminate reliably between

SZ and BPI. Further head-to-head comparisons are needed to evaluate the specificity of particular MPAs to either disorder. Our findings suggest that although MPAs may be sensitive for developmental abnormality, as a group, they do not show specificity for SZ,

BPI or, most probably, any other and mental condition. Composite biomarkers may be more sensitive to psychiatric diagnosis and gender differences need to be taken in consideration. 17

ACKNOWLEDGEMENTS

The authors received no funding for the design of the study, the collection, analysis and interpretation of the data, the writing of the report and the decision to submit the paper for publication. The authors report no biomedical financial interests or potential conflicts of interest in relation with the manuscript. All authors wish to thank Dr Todor Atanasov, MD,

Petya Krasteva and Yordan Kichekov for the graphical design and proof-reading of the manuscript.

REFERENCES 18

Table 1. Minor physical anomalies included in the modified Waldrop Physical Anomaly Scale 19

†Verified by the position of the ear canal (porion-orbitale) in relation to the midface.

HEAD MOUTH 1. Fine electric hair 12. High/steepled palate 1) Awry soon after combing 1) Flat and narrow at the top 2) Does not comb down 2) Definitely steepled 2. Hair whorls ≥ 2 13. Furrowed tongue 3. Head circumference 1) Randomly furrowed 1) 1.5 - 2.0 SD 2) Transversely furrowed 2) > 2 SD 14. Tongue with smooth/rough spots EYES HANDS 4. Epicanthus 15. Curved 5th finger 5. Intercanthal distance 16. Single transverse palmar crease 1) 1.5 - 2.0 SD 2) > 2 SD EARS FEET 6. Low-seated ears† 17. 3rd toe 1) ≤ 0.5cm below the outer corner of the eye 1) = 2nd 2) > 0.5 cm below the outer corner of the eye 2) > 2nd 7. Adherent ear lobes 18. Partial syndactyly of 2nd and 3rd toe 8. Lower edges extend back or upward 19. Big gap between 1st and 2nd toe 9. Malformed ears 1) 0.1 - 0.5 cm 10. Asymmetrical ears 2)  0.6 cm 11. Soft and pliable ears

Table 2. Frequency distribution of MPA-T in SZ

and BPI patients

SZ BPI Statistical

n % n % Value df P

MPA-T 15.53 † 11 0.160 0 score 0 0.0 0 0.0 1 0 0.0 0 0.0 20

2 6 4.7 8 13.3 3 11 8.7 5 8.3 4 25 19.7 15 25.0 5 30 23.6 9 15.0 6 17 13.4 12 20.0 7 16 12.6 8 13.3 8 10 7.9 1 1.7 9 6 4.7 1 1.7 10 1 0.8 1 1.7 11 2 1.6 0 0.0 12 2 1.6 0 0.0 13 1 0.8 0 0.0 Mean (SD)5.61 (2.19) 4.85 (1.84) - 2.32 ‡ 185 0.022 †Likelihood ratio 2- test; ‡Student’s t-test: two-tailed

MPA-T, total minor physical anomaly score;

SZ, schizophrenia; BPI, bipolar I disorder.

Table 3. Percentage of subjects with SZ and BPI

in each step of the MPA-T hierarchical scoring

SZ BPI Statistical

(n = 127) (n = 60) significance MPA-T n % n % Value df Р MPA-T  1 127 100.0 60 100.0 MPA-T  2 127 100.0 60 100.0 MPA-T  3 121 95.3 52 86.7 0.069† MPA-T  4 110 86.6 47 78.3 1.505 1 0.220‡ MPA-T  5 85 66.9 32 53.3 2.662 1 0.103‡ MPA-T  6 55 43.3 23 38.3 0.235 1 0.628‡ MPA-T  7 38 29.9 11 18.3 2.262 1 0.133‡ MPA-T  8 22 17.3 3 5.0 4.332 1 0.037‡ MPA-T  9 12 9.4 2 3.3 0.232† MPA-T  10 6 4.7 1 1.7 0.433† MPA-T  11 5 3.9 0 0.0 0.178† MPA-T  12 3 2.4 0 0.0 0.552† MPA-T  13 1 0.8 0 0.0 1.000† 21

†Fisher's Exact Test: two-tailed

‡2- test (2 х 2 tables with Yates’ correction for continuity)

MPA-T, total minor physical anomaly score;

SZ, schizophrenia; BPI, bipolar I disorder.

Table 4. Sensitivity, specificity, positive and negative predictive values of MPA-T in the status SZ versus BPI patients

MPA-T SZ BPI Sensitivity Specificity Positive predictive Negative predictive

(n = 127) (n = 60) (%) (%) value (%) value (%) МPA-T  1 127 60 МPA-T  2 127 60 МPA-T  3 121 52 95.3 13.3 69.9 57.1 МPA-T  4 110 47 86.6 21.7 70.1 43.3 МPA-T  5 85 32 66.9 46.7 72.6 40.0 МPA-T  6 55 23 43.3 61.7 70.5 33.9 МPA-T  7 38 11 29.9 81.7 77.6 35.5 МPA-T  8 22 3 17.3 95.0 88.0 35.2 МPA-T  9 12 2 9.4 96.7 85.7 33.5 МPA-T  10 6 1 4.7 98.3 85.7 32.8 МPA-T  11 5 3.9 100.0 100.0 33.0 МPA-T  12 3 2.4 100.0 100.0 32.6 МPA-T  1 3 1 0.8 100.0 100.0 32.3 MPA-T, total minor physical anomaly score; SZ, schizophrenia; BPI, bipolar I disorder. 22

Table 5. Comparison of outliers (MPA-T  7)

between SZ and BPI patients

SZ BPI Statistical MPA-T (n = 127) (n = 60) significance†

n % n % 2 df P 2.26 1 0.133 MPA-T < 7 89 70.1 49 81.7 2 MPA-T  7 38 29.9 11 18.3 76 †2 - test (2 х 2 tables with Yates’ correction for continuity)

SZ, schizophrenia; BPI, bipolar I disorder; MPA-

T, total minor physical anomaly score. 23

Figure 1. ROC-analysis with tMPA-score≥5 24

Schizophrenia patients represented in blue.

Bipolar I patients represented in green.

AUC=0.531 25

Figure 2. ROC-analysis with tMPA-score≥6

Schizophrenia patients represented in blue.

Bipolar I patients represented in green. 26

AUC=0.552

Load more

  26

Copy Link