Background: Previous reports have suggested that there may be gene×gender interaction for bipolar disorder (BD)-associated genes/loci at 22q11-13. This study aimed to investigate the associations of SEZ6L genetic variants with bipolar disorder I (BD-I) and to examine gender-specific genetic associations. Methods: 605 BD-I Caucasian cases and 1034 controls were selected from the publicly available data of the Whole Genome Association Study of BD. To increase power, an additional 362 Caucasian controls were added to this study from the Genome-Wide Association Study of Schizophrenia. In total, 605 BD-I cases and 1396 controls (934 males and 1067 females) were available for genetic association analysis of 118 SNPs within the SEZ6L gene using PLINK software. Results: 16 SNPs showed significant gene x gender interactions influencing BD-I (P<0.01). In addition, significant differences in the distribution of the alleles for these 16 SNPs were observed between the female BD-I patients and healthy controls (P<0.015) but no significant associations were found for the male sample (P>0.05). The SNP rs4822691 showed the strongest association with BD-I in the female sample (P=2.18×10-4) and the strongest gene×gender interaction in influencing BD-I (P=9.16×10 -5). Limitations: The findings of this study need to be replicated in independent samples. Conclusions: This is the first demonstration that genetic variants in the SEZ6L gene are associated with BD-I in female patients and provides additional compelling evidence for genetic variation at 22q11-13 that influences BD-I risk. The present findings highlight the gene x gender interactions modifying BD-I susceptibility.

In Tennessee, several medical library outreach projects have involved collaborative work with health-care professionals, public librarians, consumers, faith-based organizations and community service agencies. The authors are medical librarians who worked as consultants, trainers and project directors to promote health literacy using PubMed medline and other health information resources in the several funding projects described here. We explain the programmes briefly, focusing on lessons learned and suggestions for those who follow us.

Bakgrund: År 2019 var det globalt sett 40 miljoner personer som hade diagnosen bipolär sjukdom. Det är betydligt fler personer med denna diagnos som avlider genom självmord, jämfört med individer utan den. Sjukdomen påverkar många delar av den drabbades liv. Vidare är närstående viktiga i omvårdnaden men upplever också en stor börda.  Syfte: Att beskriva erfarenheter av att vara närstående till en person med bipolär sjukdom. Metod: En kvalitativ litteraturstudie med elva empiriska studier har gjorts. Sökningarna gjordes i Cinahl och PubMed. Studierna analyserades med en innehållsanalys.  Resultat: Analysen resulterade i fyra kategorier och tolv underkategorier. De fyra kategorierna var: ”Vikten av copingstrategier”, ”Erfarenheter av vården - ett spektrum mellan vägledning och uteblivet stöd”, ”Gå igenom svåra känslor” och ”Sjukdomen för med sig utmaningar”.  Konklusion: Resultatet visar de utmaningar och konsekvenser närstående till personer med bipolär sjukdom upplever. Närstående tar ett stort ansvar och deras psykiska och fysiska hälsa påverkas. Sjuksköterskan bör vara medveten om detta för att på bästa sätt kunna stödja patienter och närstående. / Background: In 2019, 40 million people were diagnosed with bipolar disorder around the world. These individuals have a higher suicide rate compared to the rest of the population. Bipolar disorder affects several parts of a person's life, but also the lives of the people around them. Furthermore, close relatives have shown to be significant in the care, however, these people also experience a burden. Aim: To describe the experiences of being a close relative of a person with bipolar disorder. Methods: A qualitative literature study with 11 empirical studies has been done. These were obtained by using the databases Cinahl and PubMed. The studies were analyzed using content analysis. Results: The analysis resulted in 4 categories and 12 subcategories. The 4 categories were: “The importance of coping strategies”, “Experiences of healthcare – a spectrum between guidance and lack of support”, “Going through difficult feelings” and “Many challenges come with the disease”. Conclusion: The result shows the challenges and consequences experienced by relatives of people with bipolar disorder. Relatives take great responsibility, and their mental and physical health is affected. Nurses should be aware of this in order to best support patients and relatives.

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Depression and bipolar disorder are two mental disorders which left untreated can have a devastating effect on a persons life as they are considered both chronic and disabling. Seeking help is often a big step that can be procrastinated for years, and misdiagnosis is a very common problem once contact with psychiatric care has finally been established. This paper investigates the correlation between posting patterns on Twitter and suffering from these diagnoses. For each day of the past year we quantify cues for emotional intensity and polarity, involvement with their social network and activity as well as metrics previously shown to be associated with depression. A number of statistical tests, including Anova, t-testing and Covariance analysis, are then constructed and fitted over our data. Our results show a significant difference between our groups in affective language use tied to emotional polarity as well as an elevated use of first person personal pronouns for both the depressed and bipolar group. These findings indicate strongly that our approach is valid for finding cues about mental illness, however the strong limitations in our data collections approach needs to be addressed in order for our results to have real scientific merit. This study is motivated by the need for finding predictive models for mental disorders, and to better understand the disorders themselves. Predictive models can be helpful for proper diagnosis by a clinical psychologist as well as for helping more people seek treatment. / Depression och bipolär sjukdom är två psykiska sjukdomar som obehandlade kan ha en förödande effekt på en persons liv eftersom de anses både kroniska och förlamande. Att söka hjälp är ofta ett väldigt stort steg som kan prokrastineras i flera år, och dessutom är feldiagnosticering ett väldigt stort problem när en kontakt med psykiatrin väl har upprättats. Denna rapport undersöker korrelationen mellan inläggsmönster på Twitter och dessa två diagnoser. Vi kvantifierar varje enskild dag av det senaste året i termer av kännetäcken för en människas emotionella intensitet och polaritet, engagemang med sitt sociala nätverk och aktivitet, såväl som parametrar som i tidigare forskning visat sig associerade med depression. Vi använder sedan statistiska modeller såsom variansanalys, t-test och kovariansanalys över vår data. Våra resultat visar på en signifikant skillnad mellan våra grupper i affekterat språkbruk och hur det kopplas till emotionell polaritet. Vi visar även på ökat användande av pronomen i första person singular hos våra bipolära och deprimerade grupper. Dessa resultat tyder på att vår metod är giltig för att hitta indikationer för mental ohälsa, men begränsningar i vår datainsamling behöver adresseras innan våra resultat kan ha riktig vetenskaplig betydelse. Den här studien är motiverad av behovet av att finna modeller med prediktiv kraft för psykisk ohälsa, och att bättre förstå depression och bipolar sjukdom som helhet. Prediktiva modeller kan vara hjälpsamma för korrekt diagnossättning av en klinisk psykolog samt att hjälpa individer att söka behandling.

This MFA thesis uses the medium of computer language to explore the chaos underlying Bipolar I Disorder, an enigmatic and disruptive illness. Using creative coding to generate a series of abstract systems representing human traits, I explore the common truth that pervades the seemingly randomness of mental illness: we all break the same. / Master of Fine Arts

Comorbid substance use disorders (SUDs) are highly prevalent in bipolar disorder (BD), with up to 60% of individuals with BD developing an SUD at some point in their lifetime. In addition, research suggests that individuals with this comorbid presentation (BD+SUD) typically have worse outcomes -- including increased mortality, morbidity, and functional impairment -- than individuals with BD alone. Given the increased illness burden associated with BD+SUD, I conducted a systematic review evaluating existing psychosocial treatments for individuals with these comorbidities. Results from this review indicated that no existing psychosocial treatments for these comorbid conditions effectively target both the substance use and mood domain of symptoms. An alternative path to treatment development is to identify mechanisms that underlie BD+SUD that can subsequently be targeted in treatment. Accordingly, I evaluated impairments in risk avoidance (a tendency to engage in a persistent pattern of problematic behaviors despite negative outcomes resulting from such behaviors) as a potential mechanism underlying negative illness outcomes in BD+SUD. Participants with BD (n = 45) or BD+SUD (n = 31) in a relatively euthymic mood state completed clinical risk behavior assessments, laboratory-based risk avoidance assessments, and neurocognitive assessments in a single study session. I hypothesized that the BD+SUD group would exhibit increased clinical risk behaviors, increased impairments on laboratory-based measures of risk avoidance, and increased deficits on neurocognitive assessments relative to the bipolar disorder alone group. Contrary to my hypotheses, results indicated a lack of notable between-group differences in clinical risk behaviors, laboratory-based risk avoidance assessments, and neurocognitive assessments, with the exception of self-reported executive dysfunction which was elevated among individuals with BD+SUD. Collapsing across group, I found that increased discounting of delayed rewards, older age, and an earlier age of (hypo)mania onset predicted increased clinical risk behaviors. These findings underscore the potential importance of delay discounting as a mechanistic target for reducing clinical risk behaviors among individuals with BD both with and without comorbid SUDs. I also discuss the neurocognitive correlates of delay discounting and interventions for addressing delay discounting as potential new directions for treating the disability associated with BD.