Changes in prescribing for bipolar disorder between 2009 and 2016: national-level data linkage study in Scotland

Background: People with bipolar disorder typically require long-term pharmacological treatment to prevent episodes of depression or mania. However, evidence-based guidelines are often not followed by prescribers and, in some countries, prescribing of lithium is in decline. Polypharmacy is also common in bipolar disorder. Aims: To employ a data linkage approach to describe and evaluate prescribing patterns in bipolar disorder in Scotland between 2009 and 2016. Method: By linking prescribing data to the electronic Scottish Morbidity Records, we identified a cohort of 23 135 patients with bipolar disorder who were prescribed psychotropic medication between 2009 and 2016. We examined trends in proportions of patients prescribed each of six drug categories. Random effects logistic models examined change in prescribing over years of interest. Results: The most common form of treatment was antidepressant monotherapy (24.96%), with only 5.90% of patients receiving lithium monotherapy. Prescribing of antipsychotics and anti-epileptics increased from 2009 to 2016 (antipsychotics: odds ratio 1.16, 95% CI 1.15–1.18; anti-epileptics: odds ratio 1.34, 95% CI 1.32–1.36), whereas prescribing of lithium decreased (odds ratio 0.83, 95% CI 0.82–0.85). Prescribing of valproate decreased from 2009–2016 in women, but increased in men (women: odds ratio 0.93, 95% CI 0.90–0.97; men: odds ratio 1.11, 95% CI 1.04–1.18). Conclusions: Antidepressant monotherapy was the most common form of treatment for bipolar disorder in Scotland and prescribing of lithium has declined between 2009 and 2016. The findings are concerning and represent a gap between treatment guidelines and clinical practice. Declaration of interest: None

Interdisciplinary Research Journeys

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. Interdisciplinarity' has become a rallying cry among funders and leaders of research. Yet, while the creative potential of interdisciplinary research is great, it poses many challenges. If you don't have disciplinary boundaries, how do you decide what to include or leave out? And what are the parameters for evaluating the research? This book provides a practical guide for researchers and research managers who are seeking to develop interdisciplinary research strategies at a personal, institutional and multi-institutional level. The book draws on examples from across the social and natural sciences but also offers valuable lessons for other combinations of more proximate disciplines. At a time when interdisciplinary research is increasingly centre stage in the research agenda, this book offers a crucial practical guide for researchers, research funders and managers from all backgrounds and contexts

Phenotypic and genetic associations between anhedonia and brain structure in UK Biobank

Anhedonia is a core symptom of multiple psychiatric disorders and has been associated with alterations in brain structure. Genome-wide association studies suggest that anhedonia is heritable, with a polygenic architecture, but few studies have explored the association between genetic loading for anhedonia—indexed by polygenic risk scores for anhedonia (PRS-anhedonia)—and structural brain imaging phenotypes. Here, we investigated how anhedonia and PRS-anhedonia were associated with brain structure within the UK Biobank cohort. Brain measures (including total grey/white matter volumes, subcortical volumes, cortical thickness (CT) and white matter integrity) were analysed using linear mixed models in relation to anhedonia and PRS-anhedonia in 19,592 participants (9225 males; mean age = 62.6 years, SD = 7.44). We found that state anhedonia was significantly associated with reduced total grey matter volume (GMV); increased total white matter volume (WMV); smaller volumes in thalamus and nucleus accumbens; reduced CT within the paracentral cortex, the opercular part of inferior frontal gyrus, precentral cortex, insula and rostral anterior cingulate cortex; and poorer integrity of many white matter tracts. PRS-anhedonia was associated with reduced total GMV; increased total WMV; reduced white matter integrity; and reduced CT within the parahippocampal cortex, superior temporal gyrus and insula. Overall, both state anhedonia and PRS-anhedonia were associated with individual differences in multiple brain structures, including within reward-related circuits. These associations may represent vulnerability markers for psychopathology relevant to a range of psychiatric disorders

Interdisciplinary Research Journeys

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. Interdisciplinarity' has become a rallying cry among funders and leaders of research. Yet, while the creative potential of interdisciplinary research is great, it poses many challenges. If you don't have disciplinary boundaries, how do you decide what to include or leave out? And what are the parameters for evaluating the research? This book provides a practical guide for researchers and research managers who are seeking to develop interdisciplinary research strategies at a personal, institutional and multi-institutional level. The book draws on examples from across the social and natural sciences but also offers valuable lessons for other combinations of more proximate disciplines. At a time when interdisciplinary research is increasingly centre stage in the research agenda, this book offers a crucial practical guide for researchers, research funders and managers from all backgrounds and contexts

Polygenic Risk for Schizophrenia, Brain Structure, and Environmental Risk in UK Biobank

Schizophrenia is a heritable neurodevelopmental disorder characterized by neuroanatomical changes in the brain but exactly how increased genetic burden for schizophrenia influences brain structure is unknown. Similarly, the impact of environmental risk factors for schizophrenia on brain structure is not fully understood. We investigated how genetic burden for schizophrenia (indexed by a polygenic risk score, PRS-SCZ) was associated with cortical thickness (CT), cortical surface area (SA), cortical volume (CV) and multiple subcortical structures within 18,147 White British ancestry participants from UK Biobank. We also explored whether environmental risk factors for schizophrenia (cannabis use, childhood trauma, low birth weight and Townsend social deprivation index) exacerbated the impact of PRS-SCZ on brain structure. We found that PRS-SCZ was significantly associated with lower CT in the frontal lobe, insula lobe, lateral orbitofrontal cortex, medial orbitofrontal cortex, posterior cingulate cortex and inferior frontal cortex, as well as reduced SA and CV in the supramarginal cortex and superior temporal cortex, but not with differences in subcortical volumes. When models included environmental risk factors as covariates, PRS-SCZ was only associated with lower SA/CV within the supramarginal cortex, superior temporal cortex and inferior frontal cortex. Moreover, no interactions were observed between PRS-SCZ and each of the environmental risk factors on brain structure. Overall, we identified brain structural correlates of PRS-SCZ predominantly within frontal and temporal regions. Some of these associations were independent of environmental risk factors, suggesting that they may represent biomarkers of genetic risk for schizophrenia

The associations between self-reported depression, self-reported chronic inflammatory conditions and cognitive abilities in UK Biobank

Background: Depression and chronic inflammatory medical conditions have been linked to impaired cognitive ability. However despite frequent comorbidity, their combined association with cognitive ability has rarely been examined. Methods: This study examined associations between self-reported depression and chronic inflammatory diseases and their interaction with cognitive performance in 456,748 participants of the UK Biobank, adjusting for sociodemographic and lifestyle factors. Numbers with available data ranged from 94,899 to 453,208 depending on the cognitive test. Results: Self-reported depression was associated with poorer performance compared to controls in several cognitive tests (fully adjusted models, reaction time: B = 6.08, 95% CI = 5.09, 7.07; pairs matching: incidence rate ratio = 1.02, 95% CI = 1.02, 1.03; Trail Making Test B: B = 1.37, 95% CI = 0.88, 1.87; Digit Symbol Substitution Test (DSST): B = −0.35, 95% CI = −0.44, −0.27). Self-reported chronic inflammatory conditions were associated with slower reaction time (B = 3.79, 95% CI = 2.81, 4.78) and lower DSST scores (B = −0.21, 95% CI = −0.30, −0.13). No interaction effects were observed. Discussion: In this large, population-based study we provide evidence of lower cognitive performance in both depression and a comprehensive category of chronic inflammatory conditions. Results are consistent with additive effects of both types of disorder on cognitive ability. Clinicians should be aware of such effects, particularly as cognitive impairment is linked to poorer disease outcomes and quality of life

Subjective and objective sleep and circadian parameters as predictors of depression-related outcomes: A machine learning approach in UK Biobank

Background: Sleep and circadian disruption are associated with depression onset and severity, but it is unclear which features (e.g., sleep duration, chronotype) are important and whether they can identify individuals showing poorer outcomes. Methods: Within a subset of the UK Biobank with actigraphy and mental health data (n = 64,353), penalised regression identified the most useful of 51 sleep/rest-activity predictors of depression-related outcomes; including case-control (Major Depression (MD) vs. controls; postnatal depression vs. controls) and within-case comparisons (severe vs. moderate MD; early vs. later onset, atypical vs. typical symptoms; comorbid anxiety; suicidality). Best models (of lasso, ridge, and elastic net) were selected based on Area Under the Curve (AUC). Results: For MD vs. controls (n(MD) = 24,229; n(control) = 40,124), lasso AUC was 0.68, 95 % confidence interval (CI) 0.67–0.69. Discrimination was reasonable for atypical vs. typical symptoms (n(atypical) = 958; n(typical) = 18,722; ridge: AUC 0.74, 95 % CI 0.71–0.77) but poor for remaining models (AUCs 0.59–0.67). Key predictors across most models included: difficulty getting up, insomnia symptoms, snoring, actigraphy-measured daytime inactivity and lower morning activity (~8 am). In a distinct subset (n = 310,718), the number of these factors shown was associated with all depression outcomes. Limitations: Analyses were cross-sectional and in middle-/older aged adults: comparison with longitudinal investigations and younger cohorts is necessary. Discussion: Sleep and circadian measures alone provided poor to moderate discrimination of depression outcomes, but several characteristics were identified that may be clinically useful. Future work should assess these features alongside broader sociodemographic, lifestyle and genetic features

Precise multimodal optical control of neural ensemble activity.

Understanding brain function requires technologies that can control the activity of large populations of neurons with high fidelity in space and time. We developed a multiphoton holographic approach to activate or suppress the activity of ensembles of cortical neurons with cellular resolution and sub-millisecond precision. Since existing opsins were inadequate, we engineered new soma-targeted (ST) optogenetic tools, ST-ChroME and IRES-ST-eGtACR1, optimized for multiphoton activation and suppression. Employing a three-dimensional all-optical read-write interface, we demonstrate the ability to simultaneously photostimulate up to 50 neurons distributed in three dimensions in a 550 × 550 × 100-µm3 volume of brain tissue. This approach allows the synthesis and editing of complex neural activity patterns needed to gain insight into the principles of neural codes