Several studies have reported on the feasibility and impact of e-monitoring using computers, or smartphones, in patients with mental disorders, including Bipolar Disorder (BD). Despite some promising early results, concerns have been raised about the motivation and ability of patients with BD to adhere to e-monitoring, in particular when they are depressed or manic. While studies on e-monitoring have examined the role of demographic factors, such as age, gender, or socioeconomic status and use of health apps, to our knowledge, no study has examined clinical characteristics that might impact adherence with e-monitoring of patients with BD.

We analyzed adherence to e-monitoring in patients with BD who participated in an ongoing e-monitoring study and evaluated whether demographic and clinical factors would predict adherence.

Eighty-seven participants with BD in different phases of the illness were included. Patterns of adherence for wearable use, daily and weekly self-rating scales over 15 months were analyzed to identify adherence trajectories using growth mixture models (GMM). Multinomial logistic regression models and Multiple Component Analyses were fitted to compute the effects of predictors on GMM classes.

Adherence rates were 79.5% for the wearable; 78.5% for weekly self-ratings; and 74.6% for daily self-ratings. GMM identified three latent class subgroups: (i) participants with good adherence with the protocol; (ii) participants with partial adherence; (iii) participants with poor adherence. Women, participants with a history of suicide attempt, and those with a history of inpatient admission were more likely to belong to the group with good adherence.

Participants with higher illness burden (e.g., history of admission to hospital, history of suicide attempts) have higher adherence rates to e-monitoring. This is important because our findings debunk myths around illness burden as an obstacle to adhere to e-monitoring studies. Participants might have seen e-monitoring as a tool for better documenting symptom change and better managing their illness, thus motivating their engagement.

None Declared

Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

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.

Bipolar disorder (BD) is associated with premature death and ischemic heart disease is the main cause of excess mortality. The predictive power of heart rate variability (HRV) for mortality has been confirmed in patients with or without cardiovascular disease. While several studies have analyzed the association between HRV and BD, their results are incongruent; and none has analyzed the effect of the clinical factors characterizing illness burden on HRV.

To assess the association between HRV and the following factors characterizing illness burden: illness duration, number and type of previous episode(s), duration of the most severe depressive or hypomanic/manic episode, severity of episodes, co-morbid psychiatric disorders, family history of BD or suicide, and duration and polarity of current episode in participants experiencing one.

We used a wearable device in 53 BD participants to assess the association between HRV using 4 measures (RMSSD, SDANN, SDNN and RR Triangular Index) and the abovementioned clinical factors characterizing illness burden. For each of the 4 HRV measures we ran 11 models, one for each burden of illness clinical factor as an independent variable.

Longer illness duration, higher number of depressive episodes, and family history of suicide were negatively correlated with HRV; in the 14 participants experiencing a depressive episode, the MADRS score was negatively correlated with HRV

Our study analyzed the association between burden of illness and HRV in BD, while controlling for functional cardiovascular status, age, sex, BMI, education, and treatment. Our results showed that high illness burden is associated with reduced HRV.

No significant relationships.

Offspring of parents with major mood disorders (MDDs) are at increased risk for early psychopathology. We aim to compare the rates of neurodevelopmental disorders in offspring of parents with bipolar disorder, major depressive disorder, and controls.

We established a lifetime diagnosis of neurodevelopmental disorders [attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disabilities, specific learning disorders, and motor disorders] using the Kiddie Schedule for Affective Disorders and Schizophrenia, Present and Lifetime Version in 400 participants (mean age 11.3 + s.d. 3.9 years), including 93 offspring of parents with bipolar disorder, 182 offspring of parents with major depressive disorder, and 125 control offspring of parents with no mood disorder.

Neurodevelopmental disorders were elevated in offspring of parents with bipolar disorder [odds ratio (OR) 2.34, 95% confidence interval (CI) 1.23–4.47, p = 0.010] and major depressive disorder (OR 1.87, 95% CI 1.03–3.39, p = 0.035) compared to controls. This difference was driven by the rates of ADHD, which were highest among offspring of parents with bipolar disorder (30.1%), intermediate in offspring of parents with major depressive disorder (24.2%), and lowest in controls (14.4%). There were no significant differences in frequencies of other neurodevelopmental disorders between the three groups. Chronic course of mood disorder in parents was associated with higher rates of any neurodevelopmental disorder and higher rates of ADHD in offspring.

Our findings suggest monitoring for ADHD and other neurodevelopmental disorders in offspring of parents with MDDs may be indicated to improve early diagnosis and treatment.

The underlying genetic heterogeneity in Bipolar Disorder (BD) has led to the search of potential markers associated with subtypes of the disorder; as such, age at onset (AAO) could be considered as a factor that defines more genetically homogeneous subgroups.

To analyze the modal distribution of a BD population according to the AAO of the disorder, as well as the clinical characteristics related to the distribution findings.

357 patients with a BD diagnosis were included in the study. AAO was defined as the age when the patient first met DSM-IV criteria for a major mood episode. Using an admixture analysis, patients were distributed among different parameters; and parametric analyses were conducted in order to compare the demographic and clinical characteristics between groups.

The model that best fit the observed distribution was a mixture of three Gaussian distributions (mean ± SD): 17±3.7 years, 26±8.8 years, and 35.5±12.54 years. Statistically significant differences were found with respect to social status, course of illness, suicidal behavior, rapid cycling, medical co-morbidities and lithium response (p<0.05).

Our results support the existence of a tri-modal distribution in BD defined by AAO, each one with different clinical characteristics; and suggest that early-onset and late-onset BD reflect an underlying genetic heterogeneity in bipolar disorder, being early-onset BD implicitly a more serious subtype of disorder.

Borrelia burgdorferi (Bb) infection can affect the central nervous system and possibly lead to psychiatric disorders. We compared clinical and demographic variables in Bb seropositive and seronegative psychiatric patients and healthy controls.

Nine hundred and twenty-six consecutive psychiatric patients were screened for antibodies to Bb and compared with 884 simultaneously recruited healthy subjects.

Contrary to healthy controls, seropositive psychiatric patients were significantly younger than seronegative ones. None of the studied psychiatric diagnostic categories exhibited stronger association with seropositivity. There were no differences between seropositive and seronegative psychiatric patients in hospitalization length, proportion of previously hospitalized patients and proportion of subjects with family history of psychiatric disorders.

These findings elaborate on potential association between Bb infection and psychiatric morbidity, but fail to identify any specific clinical ‘signature’ of Bb infection.

About 25 000 serious methamphetamine abusers live in the Czech Republic among the total population of 10 million. Dependence on methamphetamine is markedly related to the brain neurotransmitter dopamine, metabolised by catechol-O-methyltransferase enzyme.

The objective of our study was to deepen our knowledge on the genetic background of methamphetamine dependence.

The main aim of the study was to ascertain whether the Val158Met catechol-O-methyltransferase gene polymorphism is associated with methamphetamine dependence in the Czech Republic.

One hundred and twenty-three subjects dependent on methamphetamine (women N = 44), parents of sixty-seven dependent individuals, and four hundred healthy controls (women N = 250) were involved into the study. We performed a population-based as well as family-based genetic association studies.

We did not find any significant association between the Val158Met catechol-O-methyltransferase gene polymorphism and methamphetamine dependence using the population-based or family-based design (P = 0.41-0.66; Chi-Square Test or UNPHASED program, Version 3.1.4, respectively). We found a trend toward a statistically significant difference between the Val allele carriers and Met/Met homozygotes in the frequence of psychotic symptoms induced by methamphetamine (more frequent in Val carriers; P = 0.062; Chi-Square Test).

Further research involving haplotype analysis and other dopamine-related genetic polymorphisms in large populations is needed. More attention should also be paid to possible role of the Val158Met catechol-O-methyltransferase gene polymorphism in individual clinical subtypes of dependence on methamphetamine involving e.g. psychotic features or violence.

Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.

The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.

There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.

These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.

To quantify knowledge among the general Spanish population of attention deficit hyperactivity disorder (ADHD).

We developed a telephone-administered questionnaire to ask about ADHD (acronym and full name) on a spontaneous and suggested basis. Questions were asked relating to myths, symptoms, treatment, implications and healthcare professionals involved in the disease.The study sample was 770 adults (sample precision at national level 3.5) with no personal, familial or professional relationship to ADHD.

Only 4% of the subjects spontaneously answered the question about what ADHD means, while 85.3% identified the disease after we suggested what “ADHD” meant. Only 50% admitted that the disease represents a probably genetic brain disorder. A total of 39.6% believed that there was no treatment or healthcare intervention for ADHD. the intervention most often cited as being adequate was psychological treatment (48%), followed by multimodal therapy (44%). Only 12% mentioned medication. Thus, psychological intervention was regarded as the most effective option, followed by psychoeducational measures. Most of the subjects identified the psychologist as the professional indicated to treat ADHD, followed by the pediatrician, psychiatrist and neuropediatrician. Reasonable knowledge was observed in reference to affirmations / myths in ADHD (78.3–95.3%).

There are areas for improvement among the general population regarding knowledge of ADHD, its implications and treatment.

Neuroprotective effects of lithium have been well documented in tissue cultures and animal models. The evidence for lithium related neuroprotection in human subjects is limited and inconsistent, likely due to methodological heterogeneity.

To investigate the effects of lithium on brain chemistry and structure, we recruited bipolar patients selected for substantial illness burden and varied the exposure to lithium by using strict inclusion criteria.

We obtained 1.5T magnetic resonance imaging data from 27 bipolar patients with at least 2 years of ongoing lithium treatment (Li group), 16 subjects with < 3 months lifetime exposure to lithium >2 years ago (non-Li group) and 21 healthy controls. Patient groups had to have at least 10 years of illness and 5 episodes.

The non-Li group had significantly lower hippocampal volumes (t = 4.68,corrected p < 0.05) and prefrontal cortex N-acetyl aspartate (NAA) levels (t = −2.91,corrected p < 0.05) than controls, who showed comparable hippocampal volumes and NAA levels to the Li treated subjects. Duration of illness was negatively associated with NAA levels only in the non-Li, but not the Li group.

Among patients selected for substantial illness burden, only those with no or minimal lifetime Li exposure had significantly lower prefrontal NAA levels and hippocampal volumes than controls. Patients with at least 2 years of ongoing Li treatment showed no such changes, despite substantial burden of illness. These findings provide indirect support for neuroprotective effects of lithium and negative effects of illness burden on brain chemistry and structure in patients with bipolar disorders.

Brain changes in bipolar disorders (BD) may represent inherited risk factors or consequences of the illness (brain plasticity). Neuroanatomical changes, which predispose for BD could aid in early diagnosis, whereas the neuronal sequellae of BD could yield biological outcome measures for prevention and treatment.

To separate neuroanatomical changes into those that increase the risk of BD versus those that result from it, we acquired MRI/clinical data from participants at different stages of BD, including: (1) affected and unaffected offspring of bipolar parents (n = 86); (2) participants with substantial illness burden who had had at least 2 years of current Li treatment (n = 37) or were Li naive (n = 19). We also recruited 99 healthy controls matched to the above-mentioned cohorts by age and sex.

Relative to controls, both the affected and unaffected offpring of bipolar probands showed increased right inferior frontal gyrus (rIFG) volume, but comparable hippocampal volumes and prefrontal N-acetyl aspartate (NAA) levels. Larger rIFG volume was associated with an increased risk of conversion to psychiatric disorders within 4 years following the MRI scanning (hazard ratio = 4.5). In contrast, Li naive patients with substantial illness burden had smaller rIFG, hippocampal volumes and prefrontal NAA levels than controls, who were comparable in these indices to the the Li treated subjects with substantial illness burden.

Brain structural changes in BD may not be static, but may instead result from an interplay between illness burden and compensatory processes. This illness related brain plasticity may be modulated by lithium treatment.

The authors have not supplied his declaration of competing interest.

The association between parental severe mental illness (SMI) and depression in offspring may be due to genetic liability or adverse environments. We investigated the effect of parental SMI, SES, and adversity on depression in a sample of youth enriched for familial risk of mental illness.

We assessed 217 youth (mean age 11.95, SD 4.14, range 6–24), including 167 (77%) offspring of parents with SMI. We measured exposure to childhood maltreatment and bullying with the Juvenile Victimization Questionnaire (JVQ) and Childhood Experiences of Care and Abuse (CECA) interview.

In total, 13.36% participants reported significant bullying and 40.76% had a history of childhood maltreatment. Rates of bullying and maltreatment were similar in offspring of parents with and without SMI. Maltreatment likelihood increased with decreasing socioeconomic status. Exposure to bullying (OR = 3.11, 95%CI 1.08–8.88, P = 0.03) predicted depression in offspring more strongly than family history of SMI in parents.

Adversity, such as maltreatment and bullying, has a stronger impact on the risk of developing depression than family history of mental illness in parents. These adverse experiences are associated with socioeconomic status rather than parental mental illness.

The authors have not supplied their declaration of competing interest.

Children of parents with mood and psychotic disorders are at elevated risk for a range of behavioral and emotional problems. However, as the usual reporter of psychopathology in children is the parent, reports of early problems in children of parents with mood and psychotic disorders may be biased by the parents' own experience of mental illness and their mental state.

Independent observers rated psychopathology using the Test Observation Form in 378 children and youth between the ages of 4 and 24 (mean = 11.01, s.d. = 4.40) who had a parent with major depressive disorder, bipolar disorder, schizophrenia, or no history of mood and psychotic disorders.

Observed attentional problems were elevated in offspring of parents with major depressive disorder, bipolar disorder and schizophrenia (effect sizes ranging between 0.31 and 0.56). Oppositional behavior and language/thought problems showed variable degrees of elevation (effect sizes 0.17 to 0.57) across the three high-risk groups, with the greatest difficulties observed in offspring of parents with bipolar disorder. Observed anxiety was increased in offspring of parents with major depressive disorder and bipolar disorder (effect sizes 0.19 and 0.25 respectively) but not in offspring of parents with schizophrenia.

Our results suggest that externalizing problems and cognitive and language difficulties may represent a general manifestation of familial risk for mood and psychotic disorders, while anxiety may be a specific marker of liability for mood disorders. Observer assessment may improve early identification of risk and selection of youth who may benefit from targeted prevention.