Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data

BackgroundPeople with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI.Methods and findingsWe performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval [CI]: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; while 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions.ConclusionsIn this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.

In an observational analysis of primary care data from the UK, Naomi Launders and colleagues study the prevalence and clustering of physical health conditions and multimorbidity in individuals with severe mental illnesses.     

Pathway analysis in metabolomics: Recommendations for the use of over-representation analysis

Over-representation analysis (ORA) is one of the commonest pathway analysis approaches used for the functional interpretation of metabolomics datasets. Despite the widespread use of ORA in metabolomics, the community lacks guidelines detailing its best-practice use. Many factors have a pronounced impact on the results, but to date their effects have received little systematic attention. Using five publicly available datasets, we demonstrated that changes in parameters such as the background set, differential metabolite selection methods, and pathway database used can result in profoundly different ORA results. The use of a non-assay-specific background set, for example, resulted in large numbers of false-positive pathways. Pathway database choice, evaluated using three of the most popular metabolic pathway databases (KEGG, Reactome, and BioCyc), led to vastly different results in both the number and function of significantly enriched pathways. Factors that are specific to metabolomics data, such as the reliability of compound identification and the chemical bias of different analytical platforms also impacted ORA results. Simulated metabolite misidentification rates as low as 4% resulted in both gain of false-positive pathways and loss of truly significant pathways across all datasets. Our results have several practical implications for ORA users, as well as those using alternative pathway analysis methods. We offer a set of recommendations for the use of ORA in metabolomics, alongside a set of minimal reporting guidelines, as a first step towards the standardisation of pathway analysis in metabolomics.     

RepSeq – A database of amino acid repeats present in lower eukaryotic pathogens

Background  

Amino acid repeat-containing proteins have a broad range of functions and their identification is of relevance to many experimental biologists. In human-infective protozoan parasites (such as the Kinetoplastid and Plasmodium species), they are implicated in immune evasion and have been shown to influence virulence and pathogenicity. RepSeq is a new database of amino acid repeat-containing proteins found in lower eukaryotic pathogens. The RepSeq database is accessed via a web-based application which also provides links to related online tools and databases for further analyses.     

Ultrasound enhanced prehospital thrombolysis using microbubbles infusion in patients with acute ST elevation myocardial infarction: Rationale and design of the Sonolysis study

Background

The CONSORT Statement provides recommendations for reporting randomized controlled trials. We assessed the extent to which leading medical journals that publish reports of randomized trials incorporate the CONSORT recommendations into their journal and editorial processes.

Methods

This article reports on two observational studies. Study 1: We examined the online version of 'Instructions to Authors' for 165 high impact factor medical journals and extracted all text mentioning the CONSORT Statement or CONSORT extension papers. Any mention of the International Committee of Medical Journal Editors (ICMJE) or clinical trial registration were also sought and extracted. Study 2: We surveyed the editor-in-chief, or editorial office, for each of the 165 journals about their journal's endorsement of CONSORT recommendations and its incorporation into their editorial and peer-review processes.

Results

Study 1: Thirty-eight percent (62/165) of journals mentioned the CONSORT Statement in their online 'Instructions to Authors'; of these 37% (23/62) stated this was a requirement, 63% (39/62) were less clear in their recommendations. Very few journals mentioned the CONSORT extension papers. Journals that referred to CONSORT were more likely to refer to ICMJE guidelines (RR 2.16; 95% CI 1.51 to 3.08) and clinical trial registration (RR 3.67; 95% CI 2.36 to 5.71) than those journals which did not. Study 2: Thirty-nine percent (64/165) of journals responded to the on-line survey, the majority were journal editors. Eighty-eight percent (50/57) of journals recommended authors comply with the CONSORT Statement; 62% (35/56) said they would require this. Forty-one percent (22/53) reported incorporating CONSORT into their peer-review process and 47% (25/53) into their editorial process. Eighty-one percent (47/58) reported including CONSORT in their 'Instructions to Authors' although there was some inconsistency when cross checking information on the journal's website. Sixty-nine percent (31/45) of journals recommended authors comply with the CONSORT extension for cluster trials, 60% (27/45) for harms and 42% (19/45) for non-inferiority and equivalence trials. Few journals mentioned these extensions in their 'Instructions to Authors'.

Conclusion

Journals should be more explicit in their recommendations and expectations of authors regarding the CONSORT Statement and related CONSORT extensions papers.     

The Short-Term Effects of A Single Injection of Isoproterenol On Proliferation In the Submandibular Gland, Parotid Gland and Oesophagus In Vivo

Abstract. Mitotic and labelling indices were studied in the submandibular, parotid and oesophageal cells of male mice within the first 6 hr (but particularly within the 1st hr) of a single injection of isoproterenol or saline, using the metaphase arrest agent (vincristine) which was previously tested for efficacy in submandibular gland. There was a significant increase in the metaphase index of the salivary glands over control values 5, 15, 30, 45 and 60 min after isoproterenol. In contrast, there were no significant changes in the metaphase index of basal cells of the oesophagus. There was no significant change in the labelling index in isoproterenol-treated mice in comparison with saline-injected control animals. Possible explanations for the rapid mitotic response in murine salivary glands are considered; a rapid efflux from G₂ into mitosis is thought to be the most likely.     

Differentiation of adult-type Leydig cells occurs in gonadotrophin-deficient mice

During mammalian testis development distinct generations of fetal and adult Leydig cells arise. Luteinising hormone (LH) is required for normal adult Leydig cell function and for the establishment of normal adult Leydig cell number but its role in the process of adult Leydig cell differentiation has remained uncertain. In this study we have examined adult Leydig cell differentiation in gonadotrophin-releasing hormone (GnRH)-null mice which are deficient in circulating gonadotrophins. Adult Leydig cell differentiation was assessed by measuring expression of mRNA species encoding four specific markers of adult Leydig cell differentiation in the mouse. Each of these markers (3β-hydroxysteroid dehydrogenase type VI (3βHSD VI), 17β-hydroxysteroid dehydrogenase type III (17βHSD III), prostaglandin D (PGD)-synthetase and oestrogen sulphotransferase (EST)) is expressed only in the adult Leydig cell lineage in the normal adult animal. Real-time PCR studies showed that all four markers are expressed in adult GnRH-null mice. Localisation of 3βHSD VI and PGD-synthetase expression by in situ hybridisation confirmed that these genes are expressed in the interstitial tissue of the GnRH-null mouse. Treatment of animals with human chorionic gonadotrophin increased expression of 3βHSD VI and 17βHSD III within 12 hours further indicating that differentiated, but unstimulated cells already exist in the GnRH-null mouse. Thus, while previous studies have shown that LH is required for adult Leydig cell proliferation and activity, results from the present study show that adult Leydig cell differentiation will take place in animals deficient in LH.     

Extracting information from imaging cytometry: a review

The extraction of statistically meaningful quantitative information from microscopy images is increasingly important for modern biological research. Obtaining accurate, quantitative information from biological specimens, however, is a complex process that requires optimization of several parameters. One must consider the number of probes, fluorescent channels required, type of plate to be used, number of fields to be acquired and optimal resolution for image acquisition. The extraction of information from images is dependent on and can be aided greatly by careful consideration of the factors involved in the image acquisition process. I summarize here the general principles behind the imaging and software technology that is used to quantify images and highlight particular issues of concern for critically applying image quantitation techniques for research.     

The European Renal Genome Project: An Integrated Approach Towards Understanding the Genetics of Kidney Development and Disease

Rapid progress in genome research creates a wealth of information on the functional annotation of mammalian genome sequences. However, as we accumulate large amounts of scientific information we are facing problems of how to integrate and relate the data produced by various genomic approaches. Here, we propose the novel concept of an organ atlas where diverse data from expression maps to histological findings to mutant phenotypes can be queried, compared and visualized in the context of a three-dimensional reconstruction of the organ. We will seek proof of concept for the organ atlas by elucidating genetic pathways involved in development and pathophysiology of the kidney. Such a kidney atlas may provide a paradigm for a new systems-biology approach in functional genome research aimed at understanding the genetic bases of organ development, physiology and disease.Key Words: EuReGene, kidney, genome, development, pathophysiology, genetics