223 research outputs found

    Large-scale Roll Out of Electronic Longitudinal Mood-Monitoring for Research in Affective Disorders: Report From the UK Bipolar Disorder Research Network

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    Background Electronic longitudinal mood monitoring has been shown to be acceptable to patients with affective disorders within clinical settings, but its use in large-scale research has not yet been established. Methods Using both postal and email invitations, we invited 4080 past research participants with affective disorders who were recruited into the Bipolar Disorder Research Network (BDRN) over a 10 year period to participate in online weekly mood monitoring. In addition, since January 2015 we have invited all newly recruited BDRN research participants to participate in mood monitoring at the point they were recruited into BDRN. Results Online mood monitoring uptake among past participants was 20, and among new participants to date was 46 with participants recruited over the last year most likely to register (61). More than 90 mood monitoring participants engaged for at least one month, with mean engagement period greater than one year (58 weeks) and maximum engagement for longer than three years (165 weeks). There were no significant differences in the proportion of past and new BDRN participants providing data for at least 4 weeks (91, 92 respectively), 3 months (78, 82), 6 months (65, 54) or one year (51, 44). Limitations Our experiences with recruiting participants for electronic prospective mood monitoring may not necessarily generalise fully to research situations that are very different from those we describe. Conclusions Large-scale electronic longitudinal mood monitoring in affective disorders for research purposes is feasible with uptake highest among newly recruited participants

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

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    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

    Measurement of the electron electric dipole moment using YbF molecules

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    The most sensitive measurements of the electron electric dipole moment d_e have previously been made using heavy atoms. Heavy polar molecules offer a greater sensitivity to d_e because the interaction energy to be measured is typically 10^3 times larger than in a heavy atom. We report the first measurement of this kind, for which we have used the molecule YbF. Together, the large interaction energy and the strong tensor polarizability of the molecule make our experiment essentially free of the systematic errors that currently limit d_e measurements in atoms. Our first result d_e = (- 0.2 \pm 3.2) x 10^-26 e.cm is less sensitive than the best atom measurement, but is limited only by counting statistics and demonstrates the power of the method.Comment: 4 pages, 4 figures. v2. Minor corrections and clarifications made in response to referee comment

    Transnational social capital: the socio‐spatialities of civil society

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    Civil society remains a contested concept, but one that is widely embedded in global development processes. Transnationalism within civil society scholarship is often described dichotomously, either through hierarchical dependency relations or as a more amorphous networked global civil society. These two contrasting spatial imaginaries produce very particular ideas about how transnational relations contribute to civil society. Drawing on empirical material from research with civil society organizations in Barbados and Grenada, in this article I contend that civil society groups use forms of transnational social capital in their work. This does not, however, resonate with the horizontal relations associated with grassroots globalization or vertical chains of dependence. These social relations are imbued with power and agency and are entangled in situated historical, geographical and personal contexts. I conclude that the diverse transnational social relations that are part of civil society activity offer hope and possibilities for continued civil society action in these unexpected spatial arrangements

    When Too Much Is Not Enough: Obsessive-Compulsive Disorder as a Pathology of Stopping, Rather than Starting

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    Background: In obsessive-compulsive disorder (OCD), individuals feel compelled to repeatedly perform security-related behaviors, even though these behaviours seem excessive and unwarranted to them. The present research investigated two alternative ways of explaining such behavior: (1) a dysfunction of activation—a starting problem—in which the level of excitation in response to stimuli suggesting potential danger is abnormally strong; versus (2) a dysfunction of termination— a stopping problem—in which the satiety-like process for shutting down security-related thoughts and actions is abnormally weak. Method: In two experiments, 70 patients with OCD (57 with washing compulsions, 13 with checking compulsions) and 72 controls were exposed to contamination cues—immersing a hand in wet diapers —and later allowed to wash their hands, first limited to 30 s and then for as long as desired. The intensity of activation of security motivation was measured objectively by change in respiratory sinus arrythmia. Subjective ratings (e.g., contamination) and behavioral measures (e.g., duration of hand washing) were also collected. Results: Compared to controls, OCD patients with washing compulsions did not differ significantly in their levels of initial activation to the threat of contamination; however, they were significantly less able to reduce this activation by engaging in the corrective behavior of hand-washing. Further, the deactivating effect of hand-washing in OCD patients with checkin

    An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression

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    Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection

    An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression.

    Get PDF
    Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection

    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

    Genetic mechanisms of critical illness in COVID-19.

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    Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice
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