Minor physical anomalies in patients with schizophrenia in a Chinese population

Minor physical anomalies in schizophrenia and first-degree relatives in comparison to healthy controls: A systematic review and meta-analysis

Minor physical anomalies (MPAs) are anatomical variations that are markers of aberrant early neurodevelopment. Schizophrenia is associated with increased MPA frequency, however, the frequency and distribution of MPAs exhibit substantial heterogeneity in schizophrenia and are not exclusive to this disorder. MPAs at different localizations might represent different developmental origins and might be related to latent genetic predisposition or vulnerability to develop full-blown psychosis. Therefore, we conducted a thorough review of minor physical anomalies (MPAs) in schizophrenia (Sch) and first-degree relatives (SchRel). Analyzing 52 studies published from January 1980 to October 2023, the meta-analysis compared MPA scores between 3780 schizophrenia patients and 3871 controls, as well as 1415 SchRel and 1569 controls. The total MPA score was significantly increased in schizophrenia compared to controls (g = 0.78 [0.63-0.93], p<0.001). In regional MPA meta-analyses, effect sizes ranged from 0.56 to 0.78. The difference between SchRel and controls was moderate (g = 0.44 [0.28-0.61], p<0.001). When individual MPA items were analyzed separately, fine electric hair, malformed ear, asymmetrical ear, curved 5th finger were anomalies that were shared between both schizophrenia and SchRel. Also, direct comparisons of the frequency of MPAs in schizophrenia and their relatives were conducted. Additionally, the early age of onset of schizophrenia was associated with mouth anomalies (Z=-2.13, p = 0.03), and ear anomalies were associated with a higher percentage of males in the schizophrenia group (Z = 2.64, p = 0.008). These findings support the notion that different MPAs might be associated with genetic susceptibility as well as vulnerability to developing full-blown psychosis. Studies investigating clinical and neurobiological correlates of MPAs in schizophrenia might be helpful in characterizing subtypes of psychoses that are associated with different developmental processes.

Machine learning for prediction of schizophrenia based on identifying the primary and interaction effects of minor physical anomalies

In the neurodevelopmental model of schizophrenia, minor physical anomalies (MPAs) are considered neurodevelopmental markers of schizophrenia. To date, there has been no research to evaluate the interaction between MPAs. Our study built and used a machine learning model to predict the risk of schizophrenia based on measurements of MPA items and to investigate the potential primary and interaction effects of MPAs. The study included 470 patients with schizophrenia and 354 healthy controls. The models used are classical statistical model, Logistic Regression (LR), and machine leaning models, Decision Tree (DT) and Random Forest (RF). We also plotted two-dimensional scatter diagrams and three-dimensional linear/quadratic discriminant analysis (LDA/QDA) graphs for comparison with the DT dendritic structure. We found that RF had the highest predictive power for schizophrenia (Full-training AUC = 0.97 and 5-fold cross-validation AUC = 0.75). We identified several primary MPAs, such as the mouth region, high palate, furrowed tongue, skull height and mouth width. Quantitative MPA analysis indicated that the higher skull height and the narrower mouth width, the higher the risk of schizophrenia. In the interaction, we further identified that skull height and mouth width, furrowed tongue and skull height, high palate and skull height, and high palate and furrowed tongue, showed significant two-item interactions with schizophrenia. A weak three-item interaction was found between high palate, skull height, and mouth width. In conclusion, we found that the two machine learning methods showed good predictive ability in assessing the risk of schizophrenia using the primary and interaction effects of MPAs.

Development and validation of a web-based prediction tool on minor physical anomalies for schizophrenia

In support of the neurodevelopmental model of schizophrenia, minor physical anomalies (MPAs) have been suggested as biomarkers and potential pathophysiological significance for schizophrenia. However, an integrated, clinically useful tool that used qualitative and quantitative MPAs to visualize and predict schizophrenia risk while characterizing the degree of importance of MPA items was lacking. We recruited a training set and a validation set, including 463 schizophrenia patients and 281 healthy controls to conduct logistic regression and the least absolute shrinkage and selection operator (Lasso) regression to select the best parameters of MPAs and constructed nomograms. Two nomograms were built to show the weights of these predictors. In the logistic regression model, 11 out of a total of 68 parameters were identified as the best MPA items for distinguishing between patients with schizophrenia and controls, including hair whorls, epicanthus, adherent ear lobes, high palate, furrowed tongue, hyperconvex fingernails, a large gap between first and second toes, skull height, nasal width, mouth width, and palate width. The Lasso regression model included the same variables of the logistic regression model, except for nasal width, and further included two items (interpupillary distance and soft ears) to assess the risk of schizophrenia. The results of the validation dataset verified the efficacy of the nomograms with the area under the curve 0.84 and 0.85 in the logistic regression model and lasso regression model, respectively. This study provides an easy-to-use tool based on validated risk models of schizophrenia and reflects a divergence in development between schizophrenia patients and healthy controls (https://www.szprediction.net/).

Morphological variability of the earlobe in a Spanish population sample

This article shows the morphological variability of the earlobe in a Spanish population of European origin. The frequencies of four lobe characteristics (attachment, contour, modeling, and size) and their degree of expression were studied. The relationship among the characteristics and the differences involving sex and laterality were also considered. The least frequent morphology, and of main use in solving forensic cases, was the very small size with triangle-pulled contour into the skin and crossed-discontinuous modeling. The most frequent morphology, and most clinically useful, was the medium-sized lobe with free-arched contour and eminent or cross-continuous modeling. The characteristics were all symmetric. Size and modeling showed sexual dimorphism. Some characteristics were associated with each other: attachment with contour and modeling and the contour with modeling and size. The least frequent peculiarities were sharp lobe and virgule. The literature is scarce on this matter, practically non-existent for some characteristics, especially modeling and peculiarities. For the first time, the associations of the ear characteristics were analyzed, and this information could be applied to forensic identification.

Improving risk assessment and familial aggregation of age at onset in schizophrenia using minor physical anomalies and craniofacial measures

Age at onset is the most important feature of schizophrenia that could indicate its origin. Minor physical anomalies (MPAs) characterize potential marker indices of disturbances in early neurodevelopment. However, the association between MPAs and age at onset of schizophrenia is still unclear. We aimed to compare risk assessment and familial aggregation in patients with early-onset schizophrenia (EOS) and adult-onset schizophrenia (AOS) with MPAs and craniofacial measures.We estimated the risk assessment of MPAs among patients with EOS (n = 68), patients with AOS (n = 183), nonpsychotic relatives (n = 147), and healthy controls (n = 241) using 3 data-mining algorithms. In addition, we assessed the magnitude of familial aggregation of MPAs with respect to the age at onset of schizophrenia.The performance of EOS was superior to that of AOS, with discrimination accuracies of 89% and 76%, respectively. Combined MPA scores as the risk assessment were significantly higher in all schizophrenia subgroups and the nonpsychotic relatives of EOS patients than in the healthy controls. The recurrence risk ratio for familial aggregation of the MPA scores of EOS families (odds ratio 9.27) was substantially higher than that of AOS families (odds ratio 2.47).The results highlight that EOS improves risk assessment and has a severe magnitude of familial aggregation of MPAs. These findings indicate that EOS might result from a stronger genetic susceptibility to neurodevelopmental deficits.

Study of minor physical anomalies in complete nuclear Mexican families. Evidence of neurodevelopmental problems in schizophrenia

Introduction

Minor physical anomalies (MPA) are dysmorphic features that reflect deviations in early development, are morphological variants that appear during the first trimester of pregnancy and could be used as a marker of disease risk in susceptible people. The literature agrees that the number of MPA is higher in patients with schizophrenia compared with their relatives and healthy subjects. The purpose of this study is to compare the MPA, assessed using the Gourion Scale, in complete nuclear families (families with a member with schizophrenia and control families) by determining the MPA mean, concordance and heritability for the total score on the MPA Gourion Scale for each anomaly.

Method

The sample consisted of 60 families with at least one schizophrenic patient (284 members) and 61 control families (249 members). Results: The mean total score for the scale was 5.72 ± 2.3 MPA in the case of families with at least one schizophrenic patient and 1.8 ± 4.46 MPA for control families. The average for families of patients without considering the patient in the analysis was 5.59 ± 2.3 MPA; for patients, the mean was 6.14 ± 2.4 MPA. In the analysis by anomaly differences were found only in eleven anomalies found no evidence of heritability or concordance.

Conclusions

MPA occur more frequently in patients, but a pattern of low consistency between them persists. It is concluded that MPA could be a marker of neurodevelopmental problems, but it is not suitable to consider them a Gourion scale as endophenotype.

Evaluation of spontaneous dense array gamma oscillatory activity and minor physical anomalies as a composite neurodevelopmental endophenotype in schizophrenia

OBJECTIVE

Minor physical anomalies (MPAs) and gamma oscillatory activity have been proposed as associated endophenotypes in schizophrenia. Combining these endophenotypes to create a composite endophenotype may help identify those at risk for schizophrenia better. The present study aims to investigate MPAs and gamma oscillatory activity in schizophrenia patients, their unaffected first degree relatives and healthy controls and appreciate whether they can be used together as a composite endophenotype.

METHODS

This was a cross sectional family study conducted at a tertiary care mental health setup. Ninety participants including schizophrenia patients, their first degree relatives and controls (thirty each) were assessed for MPAs on the Extended Waldrop Scale. All participants underwent an awake, resting 192-channel EEG recording. Spectral power and coherence in 30-100Hz gamma bands were estimated using Welch's averaged periodogram method. One-way ANOVA, chi square test were used for comparing socio-demographic-clinical variables. MANOVA supplemented by one-way ANOVAs (post hoc Tukey HSD) were done for comparison of spectral measures. Pearson's correlation, step-by-step linear discriminant functional and intra-familial correlation analysis were subsequently performed.

RESULTS

An endophenotype pattern of finding was found for MPAs in the craniofacial region, the total number of MPAs, spectral power in right temporal region on all bands and in the right parietal region in 50-70Hz and 70-100Hz gamma bands. The three groups were most accurately classified when MPA total score, right temporal 30-50Hz gamma power and right occipital 'intra hemispheric' 50-70Hz gamma coherence were considered together than when considered independently. Significant intra familial correlation was seen for MPA total score and right temporal gamma 30-50Hz power.

CONCLUSION

Composite evaluation of two developmentally linked markers i.e. MPAs and gamma spectral measures may prove useful in categorizing schizophrenia and identifying at-risk individuals.