System to predict bipolar disorder crises analysing massive data

Durante el desarrollo del proyecto he aprendido sobre Big Data, Android y MongoDB mientras que ayudaba a desarrollar un sistema para la predicción de las crisis del trastorno bipolar mediante el análisis masivo de información de diversas fuentes. En concreto hice una parte teórica sobre bases de datos NoSQL, Streaming Spark y Redes Neuronales y después diseñé y configuré una base de datos MongoDB para el proyecto del trastorno bipolar. También aprendí sobre Android y diseñé y desarrollé una aplicación de móvil en Android para recoger datos para usarlos como entrada en el sistema de predicción de crisis. Una vez terminado el desarrollo de la aplicación también llevé a cabo una evaluación con usuarios.

Online information seeking by patients with bipolar disorder:results from an international multisite survey

Background: Information seeking is an important coping mechanism for dealing with chronic illness. Despite a growing number of mental health websites, there is little understanding of how patients with bipolar disorder use the Internet to seek information. Methods: A 39 question, paper-based, anonymous survey, translated into 12 languages, was completed by 1222 patients in 17 countries as a convenience sample between March 2014 and January 2016. All patients had a diagnosis of bipolar disorder from a psychiatrist. Data were analyzed using descriptive statistics and generalized estimating equations to account for correlated data. Results: 976 (81 % of 1212 valid responses) of the patients used the Internet, and of these 750 (77 %) looked for information on bipolar disorder. When looking online for information, 89 % used a computer rather than a smartphone, and 79 % started with a general search engine. The primary reasons for searching were drug side effects (51 %), to learn anonymously (43 %), and for help coping (39 %). About 1/3 rated their search skills as expert, and 2/3 as basic or intermediate. 59 % preferred a website on mental illness and 33 % preferred Wikipedia. Only 20 % read or participated in online support groups. Most patients (62 %) searched a couple times a year. Online information seeking helped about 2/3 to cope (41 % of the entire sample). About 2/3 did not discuss Internet findings with their doctor. Conclusion: Online information seeking helps many patients to cope although alternative information sources remain important. Most patients do not discuss Internet findings with their doctor, and concern remains about the quality of online information especially related to prescription drugs. Patients may not rate search skills accurately, and may not understand limitations of online privacy. More patient education about online information searching is needed and physicians should recommend a few high quality websites.

Differential activation in temporal, cingulate and prefrontal cortices during response inhibition in bipolar disorder

Background: Increased impulsivity and aberrant response inhibition have been observed in bipolar disorder (BD). This study examined the functional abnormalities and underlying neural processes during response inhibition in BD, and its relationship to impulsivity. Methods: We assessed impulsivity using the Barratt Impulsiveness Scale (BIS) and, using functional magnetic resonance imaging (fMRI), measured neural activity in response to an Affective Go-NoGo Task, consisting of emotional facial stimuli (fear, happy, anger faces) and non-emotional control stimuli (neutral female and male faces) in euthymic BD (n=23) and healthy individuals (HI; n=25). Results: BD patients were significantly more impulsive, yet did not differ from HI on accuracy or reaction time on the emotional go/no-go task. Comparing neural patterns of activation when processing emotional Go versus emotional NoGo trials yielded increased activation in BD within temporal and cingulate cortices and within prefrontal-cortical regions in HI. Furthermore, higher BIS scores for BD were associated with slower reaction times, and indicative of compensatory cognitive strategies to counter increased impulsivity. Conclusions: These findings illustrate cognition-emotion interference in BD and the observed differences in neural activation indicate potentially altered emotion modulation. Increased activation in brain regions previously shown in emotion regulation and response inhibition tasks could represent a disease-specific marker for BD

Adverse Childhood Life Events and Postpartum Psychosis in Bipolar Disorder

Background Women with bipolar disorder are at increased risk of postpartum psychosis. Adverse childhood life events have been associated with depression in the postpartum period, but have been little studied in relation to postpartum psychosis. In this study we investigated whether adverse childhood life events are associated with postpartum psychosis in a large sample of women with bipolar I disorder. Methods Participants were 432 parous women with DSM-IV bipolar I disorder recruited into the Bipolar Disorder Research Network (www.BDRN.org). Diagnoses and lifetime psychopathology, including perinatal episodes, were obtained via a semi-structured interview (Schedules for Clinical Assessment in Neuropsychiatry; Wing et al., 1990) and case-notes. Adverse childhood life events were assessed via self-report and case-notes, and compared between women with postpartum psychosis (n=208) and those without a lifetime history of perinatal mood episodes (n=224). Results There was no significant difference in the rate of any adverse childhood life event, including childhood sexual abuse, or in the total number of adverse childhood life events between women who experienced postpartum psychosis and those without a lifetime history of perinatal mood episodes, even after controlling for demographic and clinical differences between the groups. Limitations Adverse childhood life events were assessed in adulthood and therefore may be subject to recall errors. Conclusions We found no evidence for an association between adverse childhood life events and the occurrence of postpartum psychosis. Our data suggest that, unlike postpartum depression, childhood adversity does not play a significant role in the triggering of postpartum psychosis in women with bipolar disorder.

Comorbid Migraine in Major Depressive Disorder Suggests a Subgroup Related to Bipolar Disorder

Aims: Previous small-scale studies suggest presence of migraine in major depressive disorder (MDD) is associated with specific clinical characteristics that may overlap with those of bipolar disorder. We aimed to compare a broad range of characteristics in participants who have MDD with and without migraine, and to explore possible similarities between those characteristics associated with the presence of migraine in MDD and those in bipolar disorder in a large UK sample. Methods: Lifetime and episodic clinical characteristics and affective temperaments in DSM-IV MDD with (n=134) and without (n=218) migraine were compared. Characteristics associated with the presence of migraine were then compared with a sample of participants with DSM-IV bipolar disorder (n=407). All participants were recruited into the Bipolar Disorder Research Network (www.bdrn.org). Results: The presence of migraine in MDD was associated with female gender (76.9% vs 56.9%, p<0.001), younger age of onset (23 vs 27 years, p=0.002), history of attempted suicide (38.3% vs 22.7%, p=0.002), and more panic/agoraphobia symptomatology (6 vs 4, p<0.001). Female gender (OR=2.44, p=0.006) and younger age of onset (OR=0.97, p=0.013) remained significant in a multivariate model. These clinical characteristics were not significantly different to those of our participants with bipolar disorder. Conclusions: The presence of migraine in MDD delineates a subgroup of individuals with a more severe illness course. The clinical presentation of this subgroup more closely resembles that of bipolar disorder than that of MDD without migraine. The presence of migraine in major depression may be a marker of a specific subgroup that could be useful in future research.

Epilepsy in Bipolar Disorder: Impact on Clinical Features, Course and Outcome

Background and Aims: It is well recognized that mood disorders and epilepsy commonly co-occur. However, the relationship between epilepsy and the clinical features and course of illness in bipolar disorder (BD) is currently unknown. Here we explore the rate of epilepsy within a large sample of individuals with BD and examine bipolar illness characteristics according to the presence or absence of epilepsy. Methods: 1596 participants recruited to the Bipolar Disorder Research Network; a well-defined sample of UK subjects with a diagnosis of BD, completed a self-report questionnaire to assess lifetime history of epilepsy (Ottman et al., 2010). A subset of participants (n = 29) completed a telephone interview assessment to determine expert-confirmed epilepsy status. Lifetime clinical characteristics of illness were compared between BD subjects with and without a history of epilepsy. Results: 127 individuals (8%) screened positively for lifetime history of epilepsy. Bipolar subjects with epilepsy experienced higher rates of: suicide attempt (64.2% vs. 47.4%, p = 0.000367); panic disorder (29.6% vs. 16.1%, p = 0.001); phobias (13.6% vs. 5.7%, 0.004); alcohol abuse (18.6% vs. 10.6%, p = 0.017); and other substance abuse (10.2% vs. 4%, p = 0.009). History of suicide attempt (OR = 1.79, p = 0.013) remained significant within a multivariate model. Similar trends were observed within bipolar subjects with well-defined, expert-confirmed epilepsy (n = 29). Conclusions: Results demonstrate an increased rate of self-reported epilepsy in the BD sample, compared to the general population, and suggest differences in the clinical course of BD according to the presence of epilepsy. Comorbid epilepsy within BD may provide an attractive opportunity for subcategorising for future genetic studies, potentially identifying common underlying mechanisms.

History of Premenstrual Mood Change and Postpartum Episodes are Associated with Perimenopausal Episodes in Women with Bipolar Disorder

Background and Aims: Reproductive life events are potential triggers of mood episodes in women with bipolar disorder. We aimed to establish whether a history of premenstrual mood change and postpartum episodes are associated with perimenopausal episodes in women who have bipolar disorder. Methods: Participants were 339 post-menopausal women with DSM-IV bipolar disorder recruited into the Bipolar Disorder Research Network (www.bdrn.org). Women self-reported presence (N = 200) or absence (N = 139) of an illness episode during the perimenopausal period. History of premenstrual mood change was measured using the self-report Premenstrual Symptoms Screening Tool (PSST), and history of postpartum episodes was measured via semi-structured interview (Schedules for Clinical Assessment in Neuropsychiatry, SCAN) and inspection of case-notes. Results: History of a postpartum episode within 6 months of delivery (OR = 2.13, p = 0.03) and history of moderate/severe premenstrual syndrome (OR = 6.33, p < 0.001) were significant predictors of the presence of a perimenopausal episode, even after controlling for demographic factors. When we narrowed the definition of premenstrual mood change to premenstrual dysphoric disorder, it remained significant (OR = 2.68, p = 0.007). Conclusions: Some women who have bipolar disorder may be particularly sensitive to reproductive life events. Previous mood episodes in relation to the female reproductive lifecycle may help clinicians predict individual risk for women with bipolar disorder approaching the menopause. There is a need for prospective longitudinal studies of women with bipolar disorder providing frequent contemporaneous ratings of their mood to overcome the limitations of retrospective self-report data.

Identifying Risk Factors for Postpartum Mood Episodes in Bipolar Disorder – A UK Prospective Study

Background and Aims: Women with bipolar disorder are vulnerable to episodes postpartum, but risk factors are poorly understood. We are exploring risk factors for postpartum mood episodes in women with bipolar disorder using a prospective longitudinal design. Methods: Pregnant women with lifetime DSM-IV bipolar disorder are being recruited into the Bipolar Disorder Research Network (www.BDRN.org). Baseline assessments during late pregnancy include lifetime psychopathology and potential risk factors for perinatal episodes such as medication use, sleep, obstetric factors, and psychosocial factors. Blood samples are taken for genetic analysis. Perinatal psychopathology is assessed via follow-up interview at 12-weeks postpartum. Interview data are supplemented by clinician questionnaires and case-note review. Potential risk factors will be compared between women who experience perinatal episodes and those who remain well. Results: 80 participants have been recruited to date. 32/61 (52%) women had a perinatal recurrence by follow-up. 16 (26%) had onset in pregnancy. 21 (34%) had postpartum onset, 19 (90%) within 6-weeks of delivery: 11 (18%) postpartum psychosis, 5 (8%) postpartum hypomania, 5 (8%) postpartum depression. Postpartum relapse was more frequent in women with bipolar-I than bipolar-II disorder (45% vs 17%). 62% women with postpartum relapse took prophylactic medication peripartum and almost all received care from secondary psychiatric services (95%). Conclusions: Rate of postpartum relapse is high, despite most women receiving specialist care and medication perinatally. A larger sample size will allow us to examine potential risk factors for postpartum episodes, which will assist in providing accurate and personalised advice to women with bipolar disorder who are considering pregnancy.

Postpartum Psychosis in Bipolar Disorder: No Association with Personality, Cognitive Style and Temperament

Background and Aims: Bipolar disorder has been associated with a number of personality traits, cognitive styles and affective temperaments. Women who have bipolar disorder are at increased risk of experiencing postpartum psychosis, however no previous research has investigated these traits in relationship to postpartum episodes. Our aim was to establish whether aspects of personality, cognitive style and affective temperament, that have been associated with bipolar disorder, confer vulnerability to postpartum psychosis over and above their known association with bipolar disorder. Methods: Participants were 552 parous women with DSM-IV bipolar I disorder recruited into the Bipolar Disorder Research Network (www.bdrn.org). Postpartum psychosis group: lifetime episode of postpartum psychosis within 6 weeks of delivery (N = 284). Non-postpartum psychosis group: no history of any perinatal mood episodes (N = 268). Bipolar disorder-associated personality traits (neuroticism, extraversion, schizotypy and impulsivity), cognitive styles (low self-esteem and dysfunctional attitudes) and affective temperaments were measured using well validated self-report questionnaire measures. Results: After controlling for key demographic, clinical and pregnancy-related variables, and measures of current mood state, there were no statistically significant differences between the postpartum psychosis group and non-postpartum psychosis group on any of the personality, cognitive style or affective temperament measures. Conclusions: Personality traits, cognitive styles and affective temperaments associated with the bipolar disorder diathesis in general were not associated with the onset of postpartum psychosis specifically. We have found no evidence that these traits should play a key role when evaluating risk of postpartum psychosis in women with bipolar I disorder considering pregnancy.

The Influence of Borderline Personality Traits on the Course of Bipolar Disorder

Background and Aims: Bipolar disorder and borderline personality disorder are commonly comorbid. Borderline personality disorder is diagnosed categorically, but personality pathology may be better characterised dimensionally. The impact of borderline personality traits (not diagnosis) on the course of bipolar disorder is unknown. We examined the presence and severity of borderline personality traits in a large UK sample of bipolar disorder, and the impact of these traits on illness course. Methods: Borderline Evaluation of Severity over Time (BEST) was used to measure presence and severity of borderline traits in 1447 individuals with DSM-IV bipolar I disorder (n = 1008) and bipolar II disorder (n = 439) recruited into the Bipolar Disorder Research Network (www.bdrn.org). Clinical course was measured via semi-structured interview (Schedules for Clinical Assessment in Neuropsychiatry) and case-notes. Results: BEST score was higher in bipolar II than bipolar I (36 v 27, p < 0.001) and 9/12 individual BEST traits were significantly more common in bipolar II than bipolar I. Within both bipolar I and bipolar II higher BEST score was associated with younger age of bipolar onset (p < 0.001), history of alcohol misuse (p < 0.010), and history of suicide attempt (p < 0.001). Conclusions: Borderline personality traits are common in bipolar disorder, and more severe in bipolar II than bipolar I disorder. Borderline trait severity was associated with more severe bipolar illness course; younger age of onset, alcohol misuse and suicidal behaviour. Clinicians should be vigilant for borderline personality traits irrespective of whether criteria for diagnosis are met, particularly in those with bipolar II disorder and younger age of bipolar onset.

Autistic and Schizotypal Traits and Global Functioning in Bipolar Disorder

Background and Aims To determine the expression of autistic and positive schizotypal traits in a large sample of adults with bipolar disorder (BD), and the effect of co-occurring autistic and positive schizotypal traits on global functioning in BD. Methods Autistic and positive schizotypal traits were assessed in 797 individuals with BD recruited by the Bipolar Disorder Research Network (BDRN), using the Autism-Spectrum Quotient and Kings Schizotypy Questionnaire (KSQ), respectively. Differences in global functioning (rated using the Global Assessment Scale) during lifetime worst depressive and manic episodes (GASD and GASM respectively) were calculated in groups with high/low autistic and positive schizotypal traits. Regression analyses assessed the interactive effect of autistic and positive schizotypal traits on global functioning. Results 47.2% (CI = 43.7–50.7%) showed clinically significant levels of autistic traits. Mean of sample on the KSQ-Positive scale was 11.98 (95% CI: 11.33–12.62). In the worst episode of mania, the high autistic, high positive schizotypal group had better global functioning than the low autistic, low positive schizotypal group (mean difference = 3.72, p = 0.004). High levels of co-occurring traits were associated with better global functioning in both mood states in individuals with a history of psychosis (GASM: p < 0.001; GASD: p = 0.055). Conclusions Expression of autistic and schizotypal traits in adults with BD is prevalent, and may be important to predict course of illness, prognosis, and in devising individualised therapies. Future work should focus on replicating these findings in independent samples, and on the biological and/or psychosocial mechanisms underlying better global functioning in those who have high levels of both autistic and positive schizotypal traits.

Validation of Electronic Health Record Phenotyping of Bipolar Disorder Cases and Controls

Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.

Seasonality Shows Evidence for Polygenic Architecture and Genetic Correlation With Schizophrenia and Bipolar Disorder

OBJECTIVE: To test common genetic variants for association with seasonality (seasonal changes in mood and behavior) and to investigate whether there are shared genetic risk factors between psychiatric disorders and seasonality. METHOD: Genome-wide association studies (GWASs) were conducted in Australian (between 1988 and 1990 and between 2010 and 2013) and Amish (between May 2010 and December 2011) samples in whom the Seasonal Pattern Assessment Questionnaire (SPAQ) had been administered, and the results were meta-analyzed in a total sample of 4,156 individuals. Genetic risk scores based on results from prior large GWAS studies of bipolar disorder, major depressive disorder (MDD), and schizophrenia were calculated to test for overlap in risk between psychiatric disorders and seasonality. RESULTS: The most significant association was with rs11825064 (P = 1.7 × 10⁻⁶, β = 0.64, standard error = 0.13), an intergenic single nucleotide polymorphism (SNP) found on chromosome 11. The evidence for overlap in risk factors was strongest for schizophrenia and seasonality, with the schizophrenia genetic profile scores explaining 3% of the variance in log-transformed global seasonality scores. Bipolar disorder genetic profile scores were also associated with seasonality, although at much weaker levels (minimum P value = 3.4 × 10⁻³), and no evidence for overlap in risk was detected between MDD and seasonality. CONCLUSIONS: Common SNPs of large effect most likely do not exist for seasonality in the populations examined. As expected, there were overlapping genetic risk factors for bipolar disorder (but not MDD) with seasonality. Unexpectedly, the risk for schizophrenia and seasonality had the largest overlap, an unprecedented finding that requires replication in other populations and has potential clinical implications considering overlapping cognitive deficits in seasonal affective disorders and schizophrenia.

Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder

Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to differentiate patients with BD from healthy individuals and from individuals at familial risk for BD who either remain well or develop other psychopathology, most commonly Major Depressive Disorder (MDD). These issues are particularly pertinent to the development of translational applications of neuroimaging as they represent challenges for which clinical observation alone is insufficient. We therefore applied pattern classification to task-based functional magnetic resonance imaging (fMRI) data of the n-back working memory task, to test their predictive value in differentiating patients with BD (n=30) from healthy individuals (n=30) and from patients' relatives who were either diagnosed with MDD (n=30) or were free of any personal lifetime history of psychopathology (n=30). Diagnostic stability in these groups was confirmed with 4-year prospective follow-up. Task-based activation patterns from the fMRI data were analyzed with Gaussian Process Classifiers (GPC), a machine learning approach to detecting multivariate patterns in neuroimaging datasets. Consistent significant classification results were only obtained using data from the 3-back versus 0-back contrast. Using contrast, patients with BD were correctly classified compared to unrelated healthy individuals with an accuracy of 83.5%, sensitivity of 84.6% and specificity of 92.3%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their relatives with MDD, were respectively 73.1%, 53.9% and 94.5%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their healthy relatives were respectively 81.8%, 72.7% and 90.9%. We show that significant individual classification can be achieved using whole brain pattern analysis of task-based working memory fMRI data. The high accuracy and specificity achieved by all three classifiers suggest that multivariate pattern recognition analyses can aid clinicians in the clinical care of BD in situations of true clinical uncertainty regarding the diagnosis and prognosis.

Novel dual D3R/GSK-3β modulators: an innovative multitarget strategy for bipolar disorder

Among the psychiatric diseases, bipolar disorder (BD) is the sixth leading cause of disability with a prevalence up to 4 % worldwide. BD is a complex neuropsychiatric condition which alternates episodes of mania with symptoms of depression. Although the neurobiological pathways are not completely clarified, the dopamine (DA) hypothesis, recognized as the leading theory explaining the pathophysiology of the malady, states that the dramatically compromised homeostatic regulation of dopaminergic circuits leads to alternated changes in DA neurotransmission. Modulation of D2 and D3 receptors (D2/3R) through partial agonists represents the first-line therapeutic strategy for psychiatric diseases. Moreover, a deregulation of the enzyme glycogen synthase kinase-3β (GSK-3β) has been reported as peculiar feature of BD. In this scenario, the concomitant modulation of D3R and GSK-3β, by employing multitarget compounds, could offer promises to achieve an effective cure of this illness. In the light of these findings, we rationally envisaged the pharmacophoric model at the basis of the design of several D3R partial agonists, suitable to be exploited for the dual D3R/GSK-3β ligand design. Thus, synthetic efforts were addressed to develop a first set of hybrid molecules able to concurrently modulate the selected targets. For a chemical structure point of view, we employed different spacers to combine a substituted aryl-piperazine moiety, reported in previously discovered D3R modulators, with a pyrazole-based fragment, already identified in GSK-3β inhibitors. A fluorescent and a cellular functional assays were carried out to assess the activity of all synthetized compounds against GSK-3β and on D3R, respectively. Most of the derivatives proved to effectively modulate both GSK-3β and D3R with potencies in the low-µM and low-nM range, respectively. The consistent biological data allowed us to identify some lead candidates worth to be further modified with the aim to optimize their biological profile and to perform a structure-activity relationship (SAR) study.