Exploring professionals' understanding, interpretation and implementation of the 'appropriate medical treatment test' in the 2007 amendment of the Mental Health Act 1983.

BACKGROUND: The appropriate medical treatment test (ATT), included in the Mental Health Act (MHA) (1983, as amended 2007), aims to ensure that detention only occurs when treatment with the purpose of alleviating a mental disorder is available. AIMS: As part of the Assessing the Impact of the Mental Health Act (AMEND) project, this qualitative study aimed to assess professionals' understanding of the ATT, and its impact on clinical practice. METHOD: Forty-one professionals from a variety of mental health subspecialties were interviewed. Interviews were coded related to project aims, and themes were generated in an inductive process. RESULTS: We found that clinicians are often wholly relied upon for the ATT. Considered treatment varied depending on the patient's age rather than diagnosis. The ATT has had little impact on clinical practice. CONCLUSIONS: Our findings suggest the need to review training and support for professionals involved in MHA assessments, with better-defined roles. This may enable professionals to implement the ATT as its designers intended. DECLARATION OF INTEREST: None. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license

Compulsory admission at first presentation to services for psychosis: does ethnicity still matter? Findings from two population-based studies of first episode psychosis

Objectives Compared with the majority population, those from minority ethnic groups in the UK are more likely to be admitted compulsorily during a first episode of psychosis (FEP). We investigated whether these disparities in pathways in to care continue. Methods We analysed data from two first episode psychosis studies, conducted in the same geographical area in south London 15 years apart: the Aetiology and Ethnicity in Schizophrenia and Other Psychosis (AESOP) and the Clinical Record Interactive Search-First Episode Psychosis (CRIS-FEP) studies. The inclusion/exclusion criteria for case ascertainment for first episode psychosis were identical across the two studies. We performed multivariable logistic regression to estimate odds of compulsory admission by ethnic group, controlling for confounders. Participants Two hundred sixty-six patients with first episode psychosis, aged 18–64 years, who presented to mental health services in south London in 1997–1999 and 446 with FEP who presented in 2010–2012. Results When the two samples were compared, ethnic differences in compulsory admission appear to have remained the same for black African patients, i.e. three times higher than white British in both samples: AESOP (adj. OR = 3.96; 95% CI = 1.80–8.71) vs. CRIS-FEP (adj. OR = 3.12; 95% CI = 1.52–6.35). Black Caribbean patients were three times more likely to be compulsorily admitted in AESOP (adj. OR = 3.20; 95% CI = 1.56–6.54). This was lower in the CRIS-FEP sample (adj. OR = 1.68; 95% CI = 0.71–3.98) and did not meet conventional levels for statistical significance. Conclusion Ethnicity is strongly associated with compulsory admissions at first presentation for psychosis with evidence of heterogeneity across groups, which deserves further research

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Outcome of crisis intervention for borderline personality disorder and post traumatic stress disorder: a model for modification of the mechanism of disorder in complex post traumatic syndromes

<p>Abstract</p> <p>Background</p> <p>This study investigates the outcome of crisis intervention for chronic post traumatic disorders with a model based on the theory that such crises manifest trauma in the present. The sufferer's behavior is in response to the current perception of dependency and entrapment in a mistrusted relationship. The mechanism of disorder is the sufferer's activity, which aims to either prove or disprove the perception of entrapment, but, instead, elicits more semblances of it in a circular manner. Patients have reasons to keep such activity private from therapy and are barely aware of it as the source of their symptoms.</p> <p>Methods</p> <p>The hypothesis is that the experimental intervention will reduce symptoms broadly within 8 to 24 h from initiation of treatment, compared to treatment as usual. The experimental intervention sidesteps other symptoms to engage patients in testing the trustworthiness of the troubled relationship with closure, thus ending the circularity of their own ways. The study compares 32 experimental subjects with 26 controls at similar crisis stabilization units.</p> <p>Results</p> <p>The results of the Brief Psychiatric Rating Scale (BPRS) supported the hypothesis (both in total score and for four of five subscales), as did results with Client Observation, a pilot instrument designed specifically for the circular behavior targeted by the experimental intervention. Results were mostly non-significant from two instruments of patient self-observation, which provided retrospective pretreatment scores.</p> <p>Conclusions</p> <p>The discussion envisions further steps to ascertain that this broad reduction of symptoms ensues from the singular correction that distinguishes the experimental intervention.</p> <p>Trial registration</p> <p>Protocol Registration System NCT00269139. The PRS URL is <url>https://register.clinicaltrials.gov</url></p

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization

PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS

Background: The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study.Methods: We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T&gt;G and c.3113G&gt;A, CHEK2c.349A&gt;G, c.538C&gt;T, c.715G&gt;A, c.1036C&gt;T, c.1312G&gt;T, and c.1343T&gt;G and ATM c.7271T&gt;G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant.Results: For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G&gt;A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T&gt;G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A&gt;G OR 2.26 (95% CI 1.29 to 3.95), c.1036C&gt;T OR 5.06 (95% CI 1.09 to 23.5) and c.538C&gt;T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T&gt;G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G&gt;T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants.Conclusions: This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.</p

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC

Mining the human phenome using allelic scores that index biological intermediates

J. Kaprio ja M-L. Lokki työryhmien jäseniä.It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.Peer reviewe