An investigation of set shifting in anorexia nervosa and clinical research portfolio

Background: Recent research has examined the possibilities that deficits in cognitive processes, in particular set shifting, might contribute to the development and maintenance of anorexia nervosa (AN). Results of studies of set shifting have been mixed. There has been considerable variability in tests used to measure set shifting and a lack of homogeneity of populations sampled. Methods: This study investigated set shifting abilities within a restrictive sub type AN population using the intra-extra dimensional set shift (IED) sub-test of the Cambridge Neuropsychological Test Automated Battery (CANTAB) and the Brixton Spatial Anticipation Test (BSAT). Participants with AN were matched with healthy controls. Results: There was no significant difference found between the groups on the BSAT or the number of stages that were completed on the IED. The AN group made significantly more errors on the IED. Anxiety scores for the AN group were significantly correlated with this error measure The two measures of set shifting were not significantly correlated. Conclusion: Possible explanations were considered for the significant difference on only one of the measures, including that the IED may be a more difficult test or that the tests may be measuring different cognitive abilities. The role of anxiety on the results was also acknowledged. The possibility that previous, contradictory, research has captured aspects from different AN subgroups and the usefulness of the diagnosis of AN was discussed. Whilst it appears that patients with AN made significantly more errors on the IED, there is not currently enough conclusive evidence to support the idea that this is indicative of a deficit in set shifting

Cross-platform genetic discovery of small molecule products of metabolism and application to clinical outcomes

Circulating levels of small molecules or metabolites are highly heritable, but the impact of genetic differences in metabolism on human health is not well understood. In this cross-platform, genome-wide meta-analysis of 174 metabolite levels across six cohorts including up to 86,507 participants (70% unpublished data), we identify 499 (362 novel) genome-wide significant associations (p<4.9×10 -10 ) at 144 (94 novel) genomic regions. We show that inheritance of blood metabolite levels in the general population is characterized by pleiotropy, allelic heterogeneity, rare and common variants with large effects, non-linear associations, and enrichment for nonsynonymous variation in transporter and enzyme encoding genes. The majority of identified genes are known to be involved in biochemical processes regulating metabolite levels and to cause monogenic inborn errors of metabolism linked to specific metabolites, such as ASNS (rs17345286, MAF=0.27) and asparagine levels. We illustrate the influence of metabolite-associated variants on human health including a shared signal at GLP2R (p.Asp470Asn) associated with higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes risk, and demonstrate beta-arrestin signalling as the underlying mechanism in cellular models. We link genetically-higher serine levels to a 95% reduction in the likelihood of developing macular telangiectasia type 2 [odds ratio (95% confidence interval) per standard deviation higher levels 0.05 (0.03-0.08; p=9.5×10 -30 )]. We further demonstrate the predictive value of genetic variants identified for serine or glycine levels for this rare and difficult to diagnose degenerative retinal disease [area under the receiver operating characteristic curve: 0.73 (95% confidence interval: 0.70-0.75)], for which low serine availability, through generation of deoxysphingolipids, has recently been shown to be causally relevant. These results show that integration of human genomic variation with circulating small molecule data obtained across different measurement platforms enables efficient discovery of genetic regulators of human metabolism and translation into clinical insights.M.P. was supported by a fellowship from the German Research Foundation (DFG PI 1446/2-1). C.O. was founded by an early career fellowship at Homerton College, University of Cambridge. L. B. L. W. acknowledges funding by the Wellcome Trust (WT083442AIA). J.G. was supported by grants from the Medical Research Council (MC_UP_A090_1006, MC_PC_13030, MR/P011705/1 and MR/P01836X/1). Work in the Reimann/Gribble laboratories was supported by the Wellcome Trust (106262/Z/14/Z and 106263/Z/14/Z), UK Medical Research Council (MRC_MC_UU_12012/3) and PhD funding for EKB from MedImmune/AstraZeneca. Praveen Surendran is supported by a Rutherford Fund Fellowship from the Medical Research Council grant MR/S003746/1. A. W. is supported by a BHF-Turing Cardiovascular Data Science Award and by the EC-Innovative Medicines Initiative (BigData@Heart). J.D. is funded by the National Institute for Health Research [Senior Investigator Award] [*]. The EPIC-Norfolk study (https://doi.org/10.22025/2019.10.105.00004) has received funding from the Medical Research Council (MR/N003284/1 and MC-UU_12015/1) and Cancer Research UK (C864/A14136). The genetics work in the EPIC-Norfolk study was funded by the Medical Research Council (MC_PC_13048). Metabolite measurements in the EPIC-Norfolk study were supported by the MRC Cambridge Initiative in Metabolic Science (MR/L00002/1) and the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement no. 115372. We are grateful to all the participants who have been part of the project and to the many members of the study teams at the University of Cambridge who have enabled this research. The Fenland Study is supported by the UK Medical Research Council (MC_UU_12015/1 and MC_PC_13046). Participants in the INTERVAL randomised controlled trial were recruited with the active collaboration of NHS Blood and Transplant England (www.nhsbt.nhs.uk), which has supported field work and other elements of the trial. DNA extraction and genotyping was co-funded by the National Institute for Health Research (NIHR), the NIHR BioResource (http://bioresource.nihr.ac.uk) and the NIHR [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust] [*]. Nightingale Health NMR assays were funded by the European Commission Framework Programme 7 (HEALTH-F2-2012-279233). Metabolon Metabolomics assays were funded by the NIHR 26 BioResource and the National Institute for Health Research [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust] [*]. The academic coordinating centre for INTERVAL was supported by core funding from: NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024), UK Medical Research Council (MR/L003120/1), British Heart Foundation (SP/09/002; RG/13/13/30194; RG/18/13/33946) and the NIHR [Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust] [*].The academic coordinating centre would like to thank blood donor centre staff and blood donors for participating in the INTERVAL trial. This work was supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome. *The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. UK Biobank: This research has been conducted using the UK Biobank resource under Application Number 44448

Development of a measure of model fidelity for mental health Crisis Resolution Teams

Background Crisis Resolution Teams (CRTs) provide short-term intensive home treatment to people experiencing mental health crisis. Trial evidence suggests CRTs can be effective at reducing hospital admissions and increasing satisfaction with acute care. When scaled up to national level however, CRT implementation and outcomes have been variable. We aimed to develop and test a fidelity scale to assess adherence to a model of best practice for CRTs, based on best available evidence. Methods A concept mapping process was used to develop a CRT fidelity scale. Participants (n = 68) from a range of stakeholder groups prioritised and grouped statements (n = 72) about important components of the CRT model, generated from a literature review, national survey and qualitative interviews. These data were analysed using Ariadne software and the resultant cluster solution informed item selection for a CRT fidelity scale. Operational criteria and scoring anchor points were developed for each item. The CORE CRT fidelity scale was then piloted in 75 CRTs in the UK to assess the range of scores achieved and feasibility for use in a 1-day fidelity review process. Trained reviewers (n = 16) rated CRT service fidelity in a vignette exercise to test the scale’s inter-rater reliability. Results There were high levels of agreement within and between stakeholder groups regarding the most important components of the CRT model. A 39-item measure of CRT model fidelity was developed. Piloting indicated that the scale was feasible for use to assess CRT model fidelity and had good face validity. The wide range of item scores and total scores across CRT services in the pilot demonstrate the measure can distinguish lower and higher fidelity services. Moderately good inter-rater reliability was found, with an estimated correlation between individual ratings of 0.65 (95% CI: 0.54 to 0.76). Conclusions The CORE CRT Fidelity Scale has been developed through a rigorous and systematic process. Promising initial testing indicates its value in assessing adherence to a model of CRT best practice and to support service improvement monitoring and planning. Further research is required to establish its psychometric properties and international applicability

Physiological Correlates of Volunteering

We review research on physiological correlates of volunteering, a neglected but promising research field. Some of these correlates seem to be causal factors influencing volunteering. Volunteers tend to have better physical health, both self-reported and expert-assessed, better mental health, and perform better on cognitive tasks. Research thus far has rarely examined neurological, neurochemical, hormonal, and genetic correlates of volunteering to any significant extent, especially controlling for other factors as potential confounds. Evolutionary theory and behavioral genetic research suggest the importance of such physiological factors in humans. Basically, many aspects of social relationships and social activities have effects on health (e.g., Newman and Roberts 2013; Uchino 2004), as the widely used biopsychosocial (BPS) model suggests (Institute of Medicine 2001). Studies of formal volunteering (FV), charitable giving, and altruistic behavior suggest that physiological characteristics are related to volunteering, including specific genes (such as oxytocin receptor [OXTR] genes, Arginine vasopressin receptor [AVPR] genes, dopamine D4 receptor [DRD4] genes, and 5-HTTLPR). We recommend that future research on physiological factors be extended to non-Western populations, focusing specifically on volunteering, and differentiating between different forms and types of volunteering and civic participation

TCTEX1D2 mutations underlie Jeune asphyxiating thoracic dystrophy with impaired retrograde intraflagellar transport

Tiina Paunio on työryhmän UK10K jäsen.The analysis of individuals with ciliary chondrodysplasias can shed light on sensitive mechanisms controlling ciliogenesis and cell signalling that are essential to embryonic development and survival. Here we identify TCTEX1D2 mutations causing Jeune asphyxiating thoracic dystrophy with partially penetrant inheritance. Loss of TCTEX1D2 impairs retrograde intraflagellar transport (IFT) in humans and the protist Chlamydomonas, accompanied by destabilization of the retrograde IFT dynein motor. We thus define TCTEX1D2 as an integral component of the evolutionarily conserved retrograde IFT machinery. In complex with several IFT dynein light chains, it is required for correct vertebrate skeletal formation but may be functionally redundant under certain conditions.Peer reviewe

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p&lt;0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p&lt;0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p&lt;0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP &gt;5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Characterization of Silicon Nanocrystal Surfaces by Multidimensional Solid-State NMR Spectroscopy

The chemical and photophysical properties of silicon nanocrystals (Si NCs) are strongly dependent on the chemical composition and structure of their surfaces. Here we use fast magic angle spinning (MAS) and proton detection to enable the rapid acquisition of dipolar and scalar 2D ¹H–²⁹Si heteronuclear correlation (HETCOR) solid-state NMR spectra and reveal a molecular picture of hydride-terminated and alkyl-functionalized surfaces of Si NCs produced in a nonthermal plasma. 2D ¹H–²⁹Si HETCOR and dipolar 2D ¹H–¹H multiple-quantum correlation spectra illustrate that resonances from surface mono-, di-, and trihydride groups cannot be resolved, contrary to previous literature assignments. Instead the 2D NMR spectra illustrate that there is large distribution of ¹H and ²⁹Si chemical shifts for the surface hydride species in both the as-synthesized and functionalized Si NCs. However, proton-detected ¹H–²⁹Si refocused INEPT experiments can be used to unambiguously differentiate NMR signals from the different surface hydrides. Varying the ²⁹Si evolution time in refocused INEPT experiments and fitting the oscillation of the NMR signals allows for the relative populations of the different surface hydrides to be estimated. This analysis confirms that monohydride species are the predominant surface species on the as-synthesized Si NCs. A reduction in the populations of the di- and trihydrides is observed upon functionalization with alkyl groups, consistent with our previous hypothesis that the trihydride, or silyl (*SiH₃), group is primarily responsible for initiating surface functionalization reactions. Density functional theory (DFT) calculations were used to obtain quantum chemical structural models of the Si NC surface and reproduce the observed ¹H and ²⁹Si chemical shifts. The approaches outlined here will be useful to obtain a more detailed picture of surface structures for Si NCs and other hydride-passivated nanomaterials

Crisis resolution and home treatment in the UK: A survey of model fidelity using a novel review methodology

Crisis resolution teams (CRTs) provide treatment at home to people experiencing mental health crises, as an alternative to hospital admission. Previous UK research, based on self‐report surveys, suggests that a loosely specified model has resulted in wide variations in CRTs’ service delivery, organization and outcomes. A fidelity scale (developed through evidence review and stakeholder consensus) provided a means of objectively measuring adherence to a model of good practice for CRTs, via one‐day fidelity reviews of UK crisis teams. Reviews included interviews with service users, carers, staff and managers, and examination of data, policies, protocols and anonymized case notes. Of the 75 teams reviewed, 49 (65%) were assessed as being moderate fidelity and the rest as low fidelity, with no team achieving high fidelity. The median score was 122 (range: 73–151; inter‐quartile range: 111–132). Teams achieved higher scores on items about structure and organization, for example ease of referral, medication and safety systems, but scored poorly on items about the content of care and interventions. Despite a national mandate to implement the CRT model, there are wide variations in implementation in the UK and no teams in our sample achieved overall high fidelity. This suggests that a mandatory national policy is not in itself sufficient to achieve good quality implementation of a service model. The CRT Fidelity Scale provides a feasible and acceptable means to objectively assess model fidelity in CRTs. There is a need for development and testing of interventions to enhance model fidelity and facilitate improvements to these services

A cross-platform approach identifies genetic regulators of human metabolism and health.

In cross-platform analyses of 174 metabolites, we identify 499 associations (P < 4.9 × 10-10) characterized by pleiotropy, allelic heterogeneity, large and nonlinear effects and enrichment for nonsynonymous variation. We identify a signal at GLP2R (p.Asp470Asn) shared among higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes, with β-arrestin signaling as the underlying mechanism. Genetically higher serine levels are shown to reduce the likelihood (by 95%) and predict development of macular telangiectasia type 2, a rare degenerative retinal disease. Integration of genomic and small molecule data across platforms enables the discovery of regulators of human metabolism and translation into clinical insights