Reporting of clinically diagnosed dementia on death certificates:retrospective cohort study

Background: mortality statistics are a frequently used source of information on deaths in dementia but are limited by concerns over accuracy. Objective: to investigate the frequency with which clinically diagnosed dementia is recorded on death certificates, including predictive factors. Methods: a retrospective cohort study assembled using a large mental healthcare database in South London, linked to Office for National Statistics mortality data. People with a clinical diagnosis of dementia, aged 65 or older, who died between 2006 and 2013 were included. The main outcome was death certificate recording of dementia. Results: in total, 7,115 people were identified. Dementia was recorded on 3,815 (53.6%) death certificates. Frequency of dementia recording increased from 39.9% (2006) to 63.0% (2013) (odds ratio (OR) per year increment 1.11, 95% CI 1.07–1.15). Recording of dementia was more likely if people were older (OR per year increment 1.02, 95% CI 1.01–1.03), and for those who died in care homes (OR 1.89, 95% CI 1.50–2.40) or hospitals (OR 1.14, 95% CI 1.03–1.46) compared with home, and less likely for people with less severe cognitive impairment (OR 0.95, 95% CI 0.94–0.96), and if the diagnosis was Lewy body (OR 0.30, 95% CI 0.15–0.62) or vascular dementia (OR 0.79, 95% CI 0.68–0.93) compared with Alzheimer's disease. Conclusions: changes in certification practices may have contributed to the rise in recorded prevalence of dementia from mortality data. However, mortality data still considerably underestimate the population burden of dementia. Potential biases affecting recording of dementia need to be taken into account when interpreting mortality data

Synthetic reconstruction of extreme high hydrostatic pressure resistance in Escherichia coli

Although high hydrostatic pressure (HHP) is an interesting parameter to be applied in bioprocessing, its potential is currently limited by the lack of bacterial chassis capable of surviving and maintaining homeostasis under pressure. While several efforts have been made to genetically engineer microorganisms able to grow at sublethal pressures, there is little information for designing backgrounds that survive more extreme pressures. In this investigation, we analyzed the genome of an extreme HHP-resistant mutant of E. coli MG1655 (designated as DVL1), from which we identified four mutations (in the cra, cyaA, aceA and rpoD loci) causally linked to increased HHP resistance. Analysing the functional effect of these mutations we found that the coupled effect of downregulation of cAMP/CRP, Cra and the glyoxylate shunt activity, together with the upregulation of RpoH and RpoS activity, could mechanistically explain the increased HHP resistance of the mutant. Using combinations of three mutations, we could synthetically engineer E. coli strains able to comfortably survive pressures of 600-800 MPa, which could serve as genetic backgrounds for HHP-based biotechnological applications

Trapezius contracture and loss of strength

Musculoskeletal pathology is common in primary care, but not always have a trivial origin. According to the symptoms and comorbidities of the patient, these pathologies have to make us think if is possible to be a guiding symptom of a more severe pathology. That is why we present the case of a young woman with cardiovascular risk factors (hypertension, smoking, obesity and sleep apnea-hypopnea syndrome) with pain at left trapezius and motor and sensory clinical alterations in left upper extremity. These comorbidities have in common their relationship with cerebrovascular pathology so, given the concomitant clinical musculoskeletal, we need to suspect this cause, as was in this case

Copper-Heparin Inhalation Therapy To Repair Emphysema:A Scientific Rationale

Current pharmacotherapy of chronic obstructive pulmonary disease (COPD) aims at reducing respiratory symptoms and exacerbation frequency. Effective therapies to reduce disease progression, however, are still lacking. Furthermore, COPD medications showed less favorable effects in emphysema than in other COPD phenotypes. Elastin fibers are reduced and disrupted, whereas collagen levels are increased in emphysematous lungs. Protease/antiprotease imbalance has historically been regarded as the sole cause of emphysema. However, it is nowadays appreciated that emphysema may also be provoked by perturbations in the sequential repair steps following elastolysis. Essentiality of fibulin-5 and lysyl oxidase-like 1 in the elastin restoration process is discussed, and it is argued that copper deficiency is a plausible reason for failing elastin repair in emphysema patients. Since copper-dependent lysyl oxidases crosslink elastin as well as collagen fibers, copper supplementation stimulates accumulation of both proteins in the extracellular matrix. Restoration of abnormal elastin fibers in emphysematous lungs is favorable, whereas stimulating pulmonary fibrosis formation by further increasing collagen concentrations and organization is detrimental. Heparin inhibits collagen crosslinking while stimulating elastin repair and might therefore be the ideal companion of copper for emphysema patients. Efficacy and safety considerations may lead to a preference of pulmonary administration of copper-heparin over systemic administration

Genetic and environmental influences on the relation between attention problems and Attention Deficit Hyperactivity Disorder.

Objective: The assessment of symptoms of ADHD in children is usually based on a clinical interview or a behavior checklist. The aim of the present study is to investigate the extent to which these instruments measure an underlying construct and to estimate the genetic and environmental influences on individual differences in ADHD. Methods: Maternal ratings were collected on 10,916 twins from 5,458 families. Child Behavior Checklist (CBCL) ratings were available for 10,018, 6,565, and 5,780 twins at the ages 7, 10, and 12, respectively. The Conners Rating Scale (4,887 twins) and the DSM interview (1,006 twins) were completed at age 12. The magnitude of genetic and environmental influences on the variance of the three measures of ADHD and the covariance among the three measures of ADHD was obtained. Results: Phenotypic correlations range between .45 and .77. Variances and covariances of the measurements were explained mainly by genetic influences. The model that provided the best account of the data included an independent pathway for additive and dominant genetic effects. The genetic correlations among the measures collected at age 12 varied between .63 and 1.00. Conclusions: The genetic overlap between questionnaire ratings and the DSM-IV diagnosis of ADHD is high. Clinical and research implications of these findings are presented

Comparison of Strategies to Detect Epistasis from eQTL Data

Genome-wide association studies have been instrumental in identifying genetic variants associated with complex traits such as human disease or gene expression phenotypes. It has been proposed that extending existing analysis methods by considering interactions between pairs of loci may uncover additional genetic effects. However, the large number of possible two-marker tests presents significant computational and statistical challenges. Although several strategies to detect epistasis effects have been proposed and tested for specific phenotypes, so far there has been no systematic attempt to compare their performance using real data. We made use of thousands of gene expression traits from linkage and eQTL studies, to compare the performance of different strategies. We found that using information from marginal associations between markers and phenotypes to detect epistatic effects yielded a lower false discovery rate (FDR) than a strategy solely using biological annotation in yeast, whereas results from human data were inconclusive. For future studies whose aim is to discover epistatic effects, we recommend incorporating information about marginal associations between SNPs and phenotypes instead of relying solely on biological annotation. Improved methods to discover epistatic effects will result in a more complete understanding of complex genetic effects

High-Content Chemical and RNAi Screens for Suppressors of Neurotoxicity in a Huntington's Disease Model

To identify Huntington's Disease therapeutics, we conducted high-content small molecule and RNAi suppressor screens using a Drosophila primary neural culture Huntingtin model. Drosophila primary neurons offer a sensitive readout for neurotoxicty, as their neurites develop dysmorphic features in the presence of mutant polyglutamine-expanded Huntingtin compared to nonpathogenic Huntingtin. By tracking the subcellular distribution of mRFP-tagged pathogenic Huntingtin and assaying neurite branch morphology via live-imaging, we identified suppressors that could reduce Huntingtin aggregation and/or prevent the formation of dystrophic neurites. The custom algorithms we used to quantify neurite morphologies in complex cultures provide a useful tool for future high-content screening approaches focused on neurodegenerative disease models. Compounds previously found to be effective aggregation inhibitors in mammalian systems were also effective in Drosophila primary cultures, suggesting translational capacity between these models. However, we did not observe a direct correlation between the ability of a compound or gene knockdown to suppress aggregate formation and its ability to rescue dysmorphic neurites. Only a subset of aggregation inhibitors could revert dysmorphic cellular profiles. We identified lkb1, an upstream kinase in the mTOR/Insulin pathway, and four novel drugs, Camptothecin, OH-Camptothecin, 18β-Glycyrrhetinic acid, and Carbenoxolone, that were strong suppressors of mutant Huntingtin-induced neurotoxicity. Huntingtin neurotoxicity suppressors identified through our screen also restored viability in an in vivo Drosophila Huntington's Disease model, making them attractive candidates for further therapeutic evaluation.National Institutes of Health (U.S.) (grant R01 EB007042)National Institutes of Health (U.S.

A Novel Statistic for Genome-Wide Interaction Analysis

Although great progress in genome-wide association studies (GWAS) has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked). The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001<FDR<0.003, respectively, which were seen in two independent studies of psoriasis. These included five interacting pairs of SNPs in genes LST1/NCR3, CXCR5/BCL9L, and GLS2, some of which were located in the target sites of miR-324-3p, miR-433, and miR-382, as well as 15 pairs of interacting SNPs that had nonsynonymous substitutions. Our results demonstrated that genome-wide interaction analysis is a valuable tool for finding remaining missing heritability unexplained by the current GWAS, and the developed novel statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies

Life Expectancy at Birth for People with Serious Mental Illness and Other Major Disorders from a Secondary Mental Health Care Case Register in London

Despite improving healthcare, the gap in mortality between people with serious mental illness (SMI) and general population persists, especially for younger age groups. The electronic database from a large and comprehensive secondary mental healthcare provider in London was utilized to assess the impact of SMI diagnoses on life expectancy at birth.People who were diagnosed with SMI (schizophrenia, schizoaffective disorder, bipolar disorder), substance use disorder, and depressive episode/disorder before the end of 2009 and under active review by the South London and Maudsley NHS Foundation Trust (SLAM) in southeast London during 2007-09 comprised the sample, retrieved by the SLAM Case Register Interactive Search (CRIS) system. We estimated life expectancy at birth for people with SMI and each diagnosis, from national mortality returns between 2007-09, using a life table method.A total of 31,719 eligible people, aged 15 years or older, with SMI were analyzed. Among them, 1,370 died during 2007-09. Compared to national figures, all disorders were associated with substantially lower life expectancy: 8.0 to 14.6 life years lost for men and 9.8 to 17.5 life years lost for women. Highest reductions were found for men with schizophrenia (14.6 years lost) and women with schizoaffective disorders (17.5 years lost).The impact of serious mental illness on life expectancy is marked and generally higher than similarly calculated impacts of well-recognised adverse exposures such as smoking, diabetes and obesity. Strategies to identify and prevent causes of premature death are urgently required

Genome-Wide Interaction-Based Association Analysis Identified Multiple New Susceptibility Loci for Common Diseases

Genome-wide interaction-based association (GWIBA) analysis has the potential to identify novel susceptibility loci. These interaction effects could be missed with the prevailing approaches in genome-wide association studies (GWAS). However, no convincing loci have been discovered exclusively from GWIBA methods, and the intensive computation involved is a major barrier for application. Here, we developed a fast, multi-thread/parallel program named “pair-wise interaction-based association mapping” (PIAM) for exhaustive two-locus searches. With this program, we performed a complete GWIBA analysis on seven diseases with stringent control for false positives, and we validated the results for three of these diseases. We identified one pair-wise interaction between a previously identified locus, C1orf106, and one new locus, TEC, that was specific for Crohn's disease, with a Bonferroni corrected P<0.05 (P = 0.039). This interaction was replicated with a pair of proxy linked loci (P = 0.013) on an independent dataset. Five other interactions had corrected P<0.5. We identified the allelic effect of a locus close to SLC7A13 for coronary artery disease. This was replicated with a linked locus on an independent dataset (P = 1.09×10−7). Through a local validation analysis that evaluated association signals, rather than locus-based associations, we found that several other regions showed association/interaction signals with nominal P<0.05. In conclusion, this study demonstrated that the GWIBA approach was successful for identifying novel loci, and the results provide new insights into the genetic architecture of common diseases. In addition, our PIAM program was capable of handling very large GWAS datasets that are likely to be produced in the future