Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

The intestinal microbiota has been indicated to have a role in the pathophysiology of AN.

Aim of this study was to analyze fecal microbiome profiles of AN women before and after weight restoration and to combine them with fecal metabolomic profiles according to a multi-omics approach.

The gut microbiome and fecal metabolites were characterized in 21 underweight AN women and after weight restoration and compared with those of 20 healthy women. Microbiome data were correlated with the relevant fecal metabolites.

AN subjects showed a decreased intra-individual bacterial richness, an increased Bacteroidetes-to-Firmicutes abundance ratio and significant changes in the relative abundances of several bacteria at different order levels in both the underweight and weight-restored condition compared to healthy women. The untargeted metabolomic procedure allowed the characterization of 224 metabolites involved in energy, lipid and amino acid metabolism. A genetic algorithm identified 49 relevant metabolites. The relationships among these fecal metabolites and bacteria genera showed structures of different complexity in the 3 groups. In particular, a quarter of those relationships showed a divergent direction in the acute phase of AN than in the weight-restored phase or normal controls. Finally, in acute AN 70% of those correlations showed a negative sign suggesting a prevalent metabolites consummation by gut microbiome.

Our results provide a picture of the connections between gut bacteria and fecal metabolites in both the acute phase of AN and after short-term weight restoration. Further studies should aim to investigate the significance of gut microbiome perturbations in development and treatment of AN.

The coronavirus disease 2019 (COVID-19) pandemic and the resulting containment measures, such as “lockdown” and “social distancing”, have had important consequences on people’s mental and physical health.

We aimed to study the effect of social isolation and subsequent re- exposure and eventual changes in general and ED-specific psychopathology in people with Eating Disorders (EDs).

Three-hundred twelve Italian people with EDs (179 Anorexia Nervosa, 83 Bulimia Nervosa, 48 Binge Eating Disorder and 22 Other Specific Feeding Eating Disorder) were asked to fill-in an online survey to explore several dimensions such as: anxiety, depression, panic, insomnia, suicide ideation, stress, post-traumatic stress and obsessive-compulsive symptoms. Differences in ED specific and general symptoms among the 3 investigated time periods (before, during and after the end of lockdown) were assessed with a one-way ANOVA with repeated measures. Subsequently, ED diagnosis was introduced as covariate in the analysis in order to investigate the possible contribution on psychopathological changes.

ED core symptoms increased during the lockdown but most of them returned to pre-COVID19 levels at re-opening. The severity of general psychopathology also increased during the lockdown and persisted high in the following phase, except for depression and suicide ideation. None of this symptoms was affected by ED diagnosis, participants’age and illness duration.

People with EDs showed worsening of both general and specific psychopathology; moreover, changes in general psychopathology persisted in the re-opening period suggesting a higher stress vulnerability in this kind of patients.

No significant relationships.

COVID19 and Eating Disorders

Despite innovative treatments, the impairment in real-life functioning in subjects with schizophrenia (SCZ) remains an unmet need in the care of these patients. Recently, real-life functioning in SCZ was associated with abnormalities in different electrophysiological indices. It is still not clear whether this relationship is mediated by other variables, and how the combination of different EEG abnormalities influences the complex outcome of schizophrenia.

The purpose of the study was to find EEG patterns which can predict the outcome of schizophrenia and identify recovered patients.

Illness-related and functioning-related variables were measured in 61 SCZ at baseline and after four-years follow-up. EEGs were recorded at the baseline in resting-state condition and during two auditory tasks. We performed Sparse Partial Least Square (SPLS) Regression, using EEG features, age and illness duration to predict clinical and functional features at baseline and follow up. Through a Linear Support Vector Machine (Linear SVM) we used electrophysiological and clinical scores derived from SPLS regression, in order to classify recovered patients at follow-up.

We found one significant latent variable (p<0.01) capturing correlations between independent and dependent variables at follow-up (RHO=0.56). Among individual predictors, age and illness-duration showed the highest scores; however, the score for the combination of the EEG features was higher than all other predictors. Within dependent variables, negative symptoms showed the strongest correlation with predictors. Scores resulting from SPLS Regression classified recovered patients with 90.1% of accuracy.

A combination of electrophysiological markers, age and illness-duration might predict clinical and functional outcome of schizophrenia after 4 years of follow-up.

Alexithymia, that is the inability to recognize and describe one’s own emotions, is a transdiagnostic feature across eating disorders (EDs) and it has been associated to a prolonged stress exposure.

Therefore, we evaluated whether alexithymia affects the hypothalamus-pituitary-adrenal (HPA) axis functioning in patients with anorexia nervosa (AN) or bulimia nervosa (BN).

Twenty-six women with AN and 26 with BN participated in the study. Alexithymia was evaluated by the Toronto Alexithymia Scale–20 and eating-related psychopathology was measured by the Eating Disorder Inventory-2. The activity of the HPA axis was assessed by the salivary cortisol awakening response (CAR). Group differences in saliva CAR were tested by repeated measures 3-way ANOVA with diagnosis and alexithymia as between-subject factors.

The prevalence of alexithymia did not differ significantly between the two diagnostic groups (c2=1.24, p=0.26). Alexithymia was associated with more severe eating-related psychopathology in AN women but not in BN women. A significant reduction in the magnitude of CAR occurred in alexithymic patients with BN compared to non-alexithymic patients with BN (t = 3.39, p = 0.008), but not in alexithymic women with AN (t = 0.67, p = 0.54).

These results confirm the presence of a more severe eating-related psychopathology in alexithymic individuals with AN and show, for the first time, an association between alexithymia and a dampened basal activity of the HPA axis in BN.

No significant relationships.

Different electrophysiological indices have been investigated to identify diagnostic and prognostic markers of schizophrenia (SCZ). However, these indices have limited use in clinical practice, since both specificity and association with illness outcome remain unclear. In recent years, machine learning techniques, through the combination of multidimensional data, have been used to better characterize SCZ and to predict illness course.

The aim of the present study is to identify multimodal electrophysiological biomarkers that could be used in clinical practice in order to improve precision in diagnosis and prognosis of SCZ.

Illness-related and functioning-related variables were measured at baseline in 113 subjects with SCZ and 57 healthy controls (HC), and after four-year follow-up in 61 SCZ. EEGs were recorded at baseline in resting-state condition and during two auditory tasks (MMN-P3a and N100-P3b). Through a Linear Support Vector Machine, using EEG data as predictors, four models were generated in order to classify SCZ and HC. Then, we combined unimodal classifiers’ scores through a stacking procedure. Pearson’s correlations between classifiers score with illness-related and functioning-related variables, at baseline and follow-up, were performed.

Each EEG model produced significant classification (p < 0.05). Global classifier discriminated SCZ from HC with accuracy of 75.4% (p < 0.01). A significant correlation (r=0.40, p=0.002) between the global classifier scores with negative symptoms at follow-up was found. Within negative symptoms, blunted affect showed the strongest correlation.

Abnormalities in electrophysiological indices might be considered trait markers of schizophrenia. Our results suggest that multimodal electrophysiological markers might have prognostic value for negative symptoms.

Eating disorders (EDs) exist on a continuum ranging from innocuous but persisting dieting, through subthreshold states of uncertain significance, to full-blown cases of anorexia nervosa (AN) and bulimia nervosa (BN). Subthreshold EDs resemble AN or BN, but do not meet all their diagnostic criteria. The terms “partial syndromes” and “atypical EDs” are also used to identify these conditions.Objectives. To verify whether atypical syndromes are less severe forms of EDs or represent starting phases of EDs, we designed a two-step prospective study assessing the natural outcome of those syndromes over a 4-year time period.

In the first step, we screened 495 female students attending the first year of their high school by means of ad hoc rating questionnaires. Those students identified to being at risk for an ED underwent a psychiatric diagnostic interview. In the second step, 4 years later, we reassessed 140 of those schoolgirls who had participated in the first step.

In the first step, we identified 1 subject with full-blown BN, 1 with partial-syndrome BN, 2 with subclinical BN and 8 with subclinical AN. At the reassessment 4 years later, none of the girls had received any form of help. The full-blown BN case, the partial-syndrome BN case and 1 of the subclinical AN cases persisted unchanged; 1 of the subclinical BN cases shifted to subclinical AN; the remaining subclinical cases remitted spontaneously.

Present findings provide the evidence that subclinical AN and subclinical BN represent unstable states that can spontaneously remit over time.

Cognitive impairment in patients with eating disorders was reported by the majority of studies addressing this issue. However, heterogeneous patterns of cognitive dysfunctions were observed and, in a minority of studies, no impairment was found. The present study was aimed to define the pattern of neurocognitive impairment in a large sample of bulimia nervosa (BN) patients and to demonstrate that neuroendocrine, personality and clinical characteristics influence neurocognitive performance in BN.

Attention, executive control, conditional and incidental learning were evaluated in 83 untreated female patients with BN and 77 healthy controls. Cortisol and 17β-estradiol plasma levels were assessed. Cloninger's Temperament and Character Inventory-Revised (TCI-R), the Eating Disorder Inventory-2 and the Montgomery-Asberg Depression Rating Scale were administered.

No impairment of cognitive performance was found in subjects with BN vs. healthy controls. The higher the cortisol level and “Self-directedness” scores the better the performance on conditional learning, while 17β-estradiol levels showed an opposite pattern of association; “Reward dependence” scores were associated to a worse performance on incidental learning; depressive symptomatology negatively influenced the performance on the WCST.

No cognitive impairment was found in untreated patients with BN in the explored cognitive domains. An influence of neuroendocrine, personality and clinical variables on neurocognitive functioning was found, which might explain discrepancies in literature findings.

Accumulating evidence proposes BDNF as a candidate molecule in the pathophysiology of affective disorders. Reduced levels of peripheral BDNF have been found in drug-free patients with major depressive disorder (MDD), in drug-treated depressed or manic patients with bipolar disorder type I (BD-I), but not in drug-treated euthymic BD-I individuals. No study explored BDNF serum levels in patients with bipolar disorder type II (BD-II). Our aims were to confirm previous findings on peripheral BDNF in MDD and BD-I patients; to explore circulating BDNF also in patients with BD-II; to exclude the influence of comorbid psychiatric disorders on BDNF levels in affective patients.

We measured serum BDNF concentrations in 85 subjects, including 24 euthymic patients with unipolar depression (UD), 17 euthymic patients with BD-I, 11 euthymic patients with BD-II, 11 UD patients with a current major depressive episode and 22 drug-free healthy controls. At the assessment time, 15 patients were drug-treated; the remaining ones were drug-free for at least 4 weeks.

As compared to healthy controls, serum BDNF concentrations were significantly reduced in all the patient groups with no significant inter-group differences. Drug treatments and comorbid psychiatric disorders had no effect on lowered circulating BDNF levels in affective patients.

Present results confirm previous findings of reduced BDNF in patients with MDD and reveal, for the first time, that serum BDNF levels are decreased also in euthymic patients with UD, BD-I and BD-II, independently from drug treatment status and concomitant Axis I psychiatric disorders.