Megan Pritchard

Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register : current status and recent enhancement of an Electronic Mental Health Record-derived data resource.

Purpose The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this registers descriptive data, and describe the substantial expansion and extension of the data resource since its original development. Participants Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250 000 patient records accessed through CRIS. Findings to date Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education, social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendances and cancer registrations. Future plans Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20 000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities to enhance this type of research resource further, achieving both volume and depth of data. However, research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.

Inflammatory proteins in plasma are associated with severity of Alzheimer's disease.

Markers of Alzheimer’s disease (AD) are being widely sought with a number of studies suggesting blood measures of inflammatory proteins as putative biomarkers. Here we report findings from a panel of 27 cytokines and related proteins in over 350 subjects with AD, subjects with Mild Cognitive Impairment (MCI) and elderly normal controls where we also have measures of longitudinal change in cognition and baseline neuroimaging measures of atrophy. In this study, we identify five inflammatory proteins associated with evidence of atrophy on MR imaging data particularly in whole brain, ventricular and entorhinal cortex measures. In addition, we observed six analytes that showed significant change (over a period of one year) in people with fast cognitive decline compared to those with intermediate and slow decline. One of these (IL-10) was also associated with brain atrophy in AD. In conclusion, IL-10 was associated with both clinical and imaging evidence of severity of disease and might therefore have potential to act as biomarker of disease progression.

Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease.

There is an urgent need for the identification of Alzheimer’s disease (AD) biomarkers. Studies have now suggested the promising use of associations with blood metabolites as functional intermediate phenotypes in biomedical and pharmaceutical research. The aim of this study was to use lipidomics to identify a battery of plasma metabolite molecules that could predict AD patients from controls. We performed a comprehensive untargeted lipidomic analysis, using ultra-performance liquid chromatography/mass spectrometry on plasma samples from 35 AD patients, 40 elderly controls and 48 individuals with mild cognitive impairment (MCI) and used multivariate analysis methods to identify metabolites associated with AD status. A combination of 10 metabolites could discriminate AD patients from controls with 79.2% accuracy (81.8% sensitivity, 76.9% specificity and an area under curve of 0.792) in a novel test set. Six of the metabolites were identified as long chain cholesteryl esters (ChEs) and were reduced in AD (ChE 32:0, odds ratio (OR)=0.237, 95% confidence interval (CI)=0.10–0.48, P=4.19E−04; ChE 34:0, OR=0.152, 95% CI=0.05–0.37, P=2.90E−04; ChE 34:6, OR=0.126, 95% CI=0.03–0.35, P=5.40E−04; ChE 32:4, OR=0.056, 95% CI=0.01–0.24, P=6.56E−04 and ChE 33:6, OR=0.205, 95% CI=0.06–0.50, P=2.21E−03, per (log2) metabolite unit). The levels of these metabolites followed the trend control>MCI>AD. We, additionally, found no association between cholesterol, the precursor of ChE and AD. This study identified new ChE molecules, involved in cholesterol metabolism, implicated in AD, which may help identify new therapeutic targets; although, these findings need to be replicated in larger well-phenotyped cohorts.

Smell identification function as a severity and progression marker in Alzheimer's disease.

BACKGROUND Olfactory dysfunction, impaired smell identification in particular, is known as a diagnostic and a marker of conversion in Alzheimers disease (AD). We aimed to evaluate the associations of olfactory identification impairments with cognition, illness severity, and progression in AD patients. METHODS Fifty-seven outpatients with late onset mild to moderate AD and 24 elderly non-demented controls (NDC) were assessed, at baseline and after three months, for Mini-Mental State Examination (MMSE), University of Pennsylvania Smell Identification Test (UPSIT), and Bristol Activities of Daily Living and Neuropsychiatry Inventory. AD participants were classified as Rapid Cognitive Decliners (RCD) defined on a priori with a loss of ≥2 points in MMSE within the previous six months. RESULTS AD participants had lower olfactory scores than NDC. RCD had lower olfaction scores compared with Non-Rapid Cognitive Decliners (NRCD). Although the baseline UPSIT scores were associated with baseline MMSE scores, it did not interact significantly with change in MMSE over the follow-up period. Using a median split for olfactory scores, the AD participants were classified as Rapid Olfactory Progressors (ROP) (UPSIT ≤ 15) and Slow Olfactory Progressors correlating significantly with RCD/NRCD groups. The ROP group with higher olfactory impairment indicated more symptomatic illness or severity, i.e. lower cognition, higher functional dependence, and presence of behavioral symptoms. CONCLUSIONS Our study supports association of smell identification function with cognition and its utility as an adjunct clinical measure to assess severity in AD. Further work, including larger longitudinal studies, is needed to explore its value in predicting AD progression.

Alzheimer's disease and age-related macular degeneration have different genetic models for complement gene variation

Alzheimers disease (AD) and age-related macular degeneration (AMD) are both neurodegenerative disorders which share common pathological and biochemical features of the complement pathway. The aim of this study was to investigate whether there is an association between well replicated AMD genetic risk factors and AD. A large cohort of AD (n = 3898) patients and controls were genotyped for single nucleotide polymorphisms (SNPs) in the complement factor H (CFH), the Age-related maculopathy susceptibility protein 2 (ARMS2) the complement component 2 (C2), the complement factor B (CFB), and the complement component 3 (C3) genes. While significant but modest associations were identified between the complement factor H, the age-related maculopathy susceptibility protein 2, and the complement component 3 single nucleotide polymorphisms and AD, these were different in direction or genetic model to that observed in AMD. In addition the multilocus genetic model that predicts around a half of the sibling risk for AMD does not predict risk for AD. Our study provides further support to the hypothesis that while activation of the alternative complement pathway is central to AMD pathogenesis, it is less involved in AD.

Deep Sequencing of the Nicastrin Gene in Pooled DNA, the Identification of Genetic Variants That Affect Risk of Alzheimer's Disease

Nicastrin is an obligatory component of the γ-secretase; the enzyme complex that leads to the production of Aβ fragments critically central to the pathogenesis of Alzheimers disease (AD). Analyses of the effects of common variation in this gene on risk for late onset AD have been inconclusive. We investigated the effect of rare variation in the coding regions of the Nicastrin gene in a cohort of AD patients and matched controls using an innovative pooling approach and next generation sequencing. Five SNPs were identified and validated by individual genotyping from 311 cases and 360 controls. Association analysis identified a non-synonymous rare SNP (N417Y) with a statistically higher frequency in cases compared to controls in the Greek population (OR 3.994, CI 1.105–14.439, p = 0.035). This finding warrants further investigation in a larger cohort and adds weight to the hypothesis that rare variation explains some of genetic heritability still to be identified in Alzheimers disease.

Pattern of Smell Identification Impairment in Alzheimer’s Disease

Olfactory dysfunction in general, and impaired odor identification in particular, have been reported in Alzheimers disease (AD). Olfactory testing may be a useful diagnostic aid for AD, but the types of odor most commonly affected need to be identified. This study aimed to determine pattern and types of odor affected in AD with the goal of improving clinical applicability. 54 outpatients with mild to moderate AD and 40 age and gender-matched non-demented controls (NDC) were tested using British version of University of Pennsylvania Smell Identification Test (UPSIT; Sensonics, Inc., Haddon Heights, NJ) and data analyzed to identify an optimal subset of UPSIT to best differentiate AD patients from controls. AD subjects had significantly lower UPSIT total scores than NDC. Random Forest with backward elimination identified 12 UPSIT items which accurately differentiated AD patients compared to controls (sensitivity, 0.89 and specificity, 0.83, positive predictive value of 0.889, and negative predictive value of 0.833). The 12 smell items found to be most affected in AD subjects reflects important attributes such as safety and food, known to be affected in people with AD and that has the potential to impair activities of daily living. The 12 items of British UPSIT most affected in AD subjects provides a potential brief scale for early detection of AD in clinical settings. Independent replication is needed to validate these findings.

Inpatient use and area-level socio-environmental factors in people with psychosis

PurposeThere is consistent evidence that socio-environmental factors measured at an area-level, such as ethnic density, urban environment and deprivation are associated with psychosis risk. However, whether area-level socio-environmental factors are associated with outcomes following psychosis onset is less clear. This study aimed to examine whether the number of inpatient days used by people presenting to mental health services for psychosis was associated with five key area-level socio-environmental factors: deprivation, ethnic density, social capital, population density and social fragmentation.MethodsUsing a historical cohort design based on electronic health records from the South London and Maudsley NHS Trust Foundation electronic Patient Journey System, people who presented for the first time to SLAM between 2007 and 2010 with psychosis were included. Structured data were extracted on age at presentation, gender, ethnicity, residential area at first presentation and number of inpatient days over 5 years of follow-up. Data on area-level socio-environmental factors taken from published sources were linked to participants’ residential addresses. The relationship between the number of inpatient days and each socio-environmental factor was investigated in univariate negative binomial regression models with time in contact with services treated as an offset variable.ResultsA total of 2147 people had full data on area level outcomes and baseline demographics, thus, could be included in the full analysis. No area-level socio-environmental factors were associated with inpatient days.ConclusionAlthough a robust association exists between socio-environmental factors and psychosis risk, in this study we found no evidence that neighbourhood deprivation was linked to future inpatient admissions following the onset of psychosis. Future work on the influence of area-level socio-environmental factors on outcome should examine more nuanced outcomes, e.g. recovery, symptom trajectory, and should account for key methodological challenges, e.g. accounting for changes in address.

O1.2 PERIPHERAL INFLAMMATORY MARKERS ARE PREDICTIVE OF CLINICAL CHARACTERISTICS AND OUTCOME IN PSYCHOSIS

Abstract Background Dysregulation of the immune system represents an important vulnerability factor for schizophrenia. A rise in peripheral inflammatory markers has previously been demonstrated in psychosis; however, its significance remains uncertain. Characterising this relationship aids our understanding of the role of immunological factors in psychosis, as well as potentially identifying candidate biomarkers to guide diagnosis, treatment and prognosis. Whilst specialized inflammatory marker assays have been found to be associated with outcome and treatment, these tests are not typically available in clinical practice. We sought to establish whether routine inflammatory markers are associated with clinical characteristics and outcomes in patients with schizophrenia and related disorders. Methods A multi-site cohort study of patients admitted to an acute psychiatric ward between January 2013 and December 2016 within a large Mental Health Trust was undertaken. Cases were identified from an electronic database containing full clinical records. Inclusion criteria were patients aged 18 and 65 years with a discharge diagnosis of schizophrenia, or related disorder and a routine blood test within 3 days of admission. Exclusion criteria were diagnoses of drug-induced psychosis, organic brain disorder, or admission during the perinatal period. Pro-inflammatory (white blood cell total and differential count, C-reactive protein) and anti-inflammatory markers (albumin) recorded during the admission were extracted. Clinical characteristics were based upon the Health of the Nation Outcome Scale, a 12-item clinician rated tool contemporaneously rated at admission and discharge. Results A total of 968 patients met the inclusion criteria. 309 patients were female and mean age was 38 years. The most frequent ethnicities were White, Black African, Black Other and Black Caribbean and the commonest diagnoses were schizophrenia, unspecified non-organic psychosis and schizoaffective disorder. Mean interval from admission to admission blood test was 0.8 days. Patients with affective psychosis had a significantly higher white cell count, monocyte count and lymphocyte count than patients with non-affective psychosis on admission. Furthermore, among patients with affective psychosis, a partial correlation controlling for age, body mass index, blood pressure, physical health and smoking status found a significant association between symptom severity and monocyte count. There was a highly significant association between both neutrophil count and white cell count with hallucinatory symptoms. There was also a highly significant positive association between C-reactive protein and self-injurious behaviour, replicating recently published findings in smaller samples. There was a significant reduction in overall psychiatric symptoms over the course of admission, which was significantly associated with admission monocyte count. A partial correlation found white cell count and neutrophil count at admission were associated with reductions in hallucinatory symptoms. Eosinophil count was significantly associated with admission length. Discussion In a large cohort of patients admitted due to psychotic disorder, pro-inflammatory markers were associated with affective psychosis and overall symptom severity, and predicted admission length and reduction in symptom severity. The study supports an association between immune dysregulation and psychosis. Furthermore, the study highlights the role of routinely and inexpensively measured peripheral inflammatory markers as potential diagnostic and prognostic biomarkers in psychosis.

Effectiveness of automated appointment reminders in Psychosis Community Services: A randomised controlled trial

Summary We report on the first open-label, parallel group randomised controlled trial of automated appointment reminders in a psychosis community service in the UK. Ninety-five patients were randomly allocated to receiving/not receiving automated messaging reminders 7 days and 1 day before appointments. All ‘Attended’ and ‘Missed’ appointment outcomes over 6 months were analysed using cluster regression analysis. Reminded appointments were significantly more frequently attended than non-reminded appointments (unadjusted odds ratio (OR) = 3.54, 95% CI 1.36–9.22, P = 0.01; adjusted OR = 2.95, 95% CI 1.05–8.85, P < 0.05). Automated messaging reminders can provide a robust strategy for promoting engagement with psychosis services. Declaration of interest The authors have no competing financial interests to declare in relation to the current work. Sarah McAllister was supported by a Kings Undergraduate Research Fellowship.