Rapid Low-Cost Microarray-Based Genotyping for Genetic Screening in Primary Immunodeficiency

Background: Genetic tests for primary immunodeficiency disorders (PIDs) are expensive, time-consuming, and not easily accessible in developing countries. Therefore, we studied the feasibility of a customized single nucleotide variant (SNV) microarray that we developed to detect disease-causing variants and copy number variation (CNV) in patients with PIDs for only 40 Euros. Methods: Probes were custom-designed to genotype 9,415 variants of 277 PID-related genes, and were added to the genome-wide Illumina Global Screening Array (GSA). Data analysis of GSA was performed using Illumina GenomeStudio 2.0, Biodiscovery Nexus 10.0, and R-3.4.4 software. Validation of genotype calling was performed by comparing the GSA with whole-genome sequencing (WGS) data of 56 non-PID controls. DNA samples of 95 clinically diagnosed PID patients, of which 60 patients (63%) had a genetically established diagnosis (by Next-Generation Sequencing (NGS) PID panels or Sanger sequencing), w

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Obesity and Gastroesophageal Reflux: Quantifying the Association Between Body Mass Index, Esophageal Acid Exposure, and Lower Esophageal Sphincter Status in a Large Series of Patients with Reflux Symptoms

Obesity and gastroesophageal reflux disease (GERD) are increasingly important health problems. Previous studies of the relationship between obesity and GERD focus on indirect manifestations of GERD. Little is known about the association between obesity and objectively measured esophageal acid exposure. The aim of this study is to quantify the relationship between body mass index (BMI) and 24-h esophageal pH measurements and the status of the lower esophageal sphincter (LES) in patients with reflux symptoms. Data of 1,659 patients (50% male, mean age 51 ± 14) referred for assessment of GERD symptoms between 1998 and 2008 were analyzed. These subjects underwent 24-h pH monitoring off medication and esophageal manometry. The relationship of BMI to 24-h esophageal pH measurements and LES status was studied using linear regression and multiple regression analysis. The difference of each acid exposure component was also assessed among four BMI subgroups (underweight, normal weight, overweight, and obese) using analysis of variance and covariance. Increasing BMI was positively correlated with increasing esophageal acid exposure (adjusted R 2 = 0.13 for the composite pH score). The prevalence of a defective LES was higher in patients with higher BMI (p < 0.0001). Compared to patients with normal weight, obese patients are more than twice as likely to have a mechanically defective LES [OR = 2.12(1.63–2.75)]. An increase in body mass index is associated with an increase in esophageal acid exposure, whether BMI was examined as a continuous or as a categorical variable; 13% of the variation in esophageal acid exposure may be attributable to variation in BMI

Dissecting the shared genetic basis of migraine and mental disorders using novel statistical tools

Migraine is three times more prevalent in people with bipolar disorder or depression. The relationship between schizophrenia and migraine is less certain although glutamatergic and serotonergic neurotransmission are implicated in both. A shared genetic basis to migraine and mental disorders has been suggested but previous studies have reported weak or non-significant genetic correlations and five shared risk loci. Using the largest samples to date and novel statistical tools, we aimed to determine the extent to which migraine’s polygenic architecture overlaps with bipolar disorder, depression and schizophrenia beyond genetic correlation, and to identify shared genetic loci. Summary statistics from genome-wide association studies were acquired from large-scale consortia for migraine (n cases = 59 674; n controls = 316 078), bipolar disorder (n cases = 20 352; n controls = 31 358), depression (n cases = 170 756; n controls = 328 443) and schizophrenia (n cases = 40 675, n controls = 64 643). We applied the bivariate causal mixture model to estimate the number of disorder-influencing variants shared between migraine and each mental disorder, and the conditional/conjunctional false discovery rate method to identify shared loci. Loci were functionally characterized to provide biological insights. Univariate MiXeR analysis revealed that migraine was substantially less polygenic (2.8 K disorder-influencing variants) compared to mental disorders (8100–12 300 disorder-influencing variants). Bivariate analysis estimated that 800 (SD = 300), 2100 (SD = 100) and 2300 (SD = 300) variants were shared between bipolar disorder, depression and schizophrenia, respectively. There was also extensive overlap with intelligence (1800, SD = 300) and educational attainment (2100, SD = 300) but not height (1000, SD = 100). We next identified 14 loci jointly associated with migraine and depression and 36 loci jointly associated with migraine and schizophrenia, with evidence of consistent genetic effects in independent samples. No loci were associated with migraine and bipolar disorder. Functional annotation mapped 37 and 298 genes to migraine and each of depression and schizophrenia, respectively, including several novel putative migraine genes such as L3MBTL2, CACNB2 and SLC9B1. Gene-set analysis identified several putative gene sets enriched with mapped genes including transmembrane transport in migraine and schizophrenia. Most migraine-influencing variants were predicted to influence depression and schizophrenia, although a minority of mental disorder-influencing variants were shared with migraine due to the difference in polygenicity. Similar overlap with other brain-related phenotypes suggests this represents a pool of ‘pleiotropic’ variants that influence vulnerability to diverse brain-related disorders and traits. We also identified specific loci shared between migraine and each of depression and schizophrenia, implicating shared molecular mechanisms and highlighting candidate migraine genes for experimental validation

Improving the effectiveness of psychological interventions for depression and anxiety in the cardiac rehabilitation pathway using group-based metacognitive therapy (PATHWAY Group MCT) : study protocol for a randomised controlled trial

BACKGROUND: Anxiety and depression are prevalent among cardiac rehabilitation patients but pharmacological and psychological treatments have limited effectiveness in this group. Furthermore, psychological interventions have not been systematically integrated into cardiac rehabilitation services despite being a strategic priority for the UK National Health Service. A promising new treatment, metacognitive therapy, may be well-suited to the needs of cardiac rehabilitation patients and has the potential to improve outcomes. It is based on the metacognitive model, which proposes that a thinking style dominated by rumination, worry and threat monitoring maintains emotional distress. Metacognitive therapy is highly effective at reducing this thinking style and alleviating anxiety and depression in mental health settings. This trial aims to evaluate the effectiveness and cost-effectiveness of group-based metacognitive therapy for cardiac rehabilitation patients with elevated anxiety and/or depressive symptoms. METHODS/DESIGN: The PATHWAY Group-MCT trial is a multicentre, two-arm, single-blind, randomised controlled trial comparing the clinical- and cost-effectiveness of group-based metacognitive therapy plus usual cardiac rehabilitation to usual cardiac rehabilitation alone. Cardiac rehabilitation patients (target sample n = 332) with elevated anxiety and/or depressive symptoms will be recruited across five UK National Health Service Trusts. Participants randomised to the intervention arm will receive six weekly sessions of group-based metacognitive therapy delivered by either cardiac rehabilitation professionals or research nurses. The intervention and control groups will both be offered the usual cardiac rehabilitation programme within their Trust. The primary outcome is severity of anxiety and depressive symptoms at 4-month follow-up measured by the Hospital Anxiety and Depression Scale total score. Secondary outcomes are severity of anxiety/depression at 12-month follow-up, health-related quality of life, severity of post-traumatic stress symptoms and strength of metacognitive beliefs at 4- and 12-month follow-up. Qualitative interviews will help to develop an account of barriers and enablers to the effectiveness of the intervention. DISCUSSION: This trial will evaluate the effectiveness and cost-effectiveness of group-based metacognitive therapy in alleviating anxiety and depression in cardiac rehabilitation patients. The therapy, if effective, offers the potential to improve psychological wellbeing and quality of life in this large group of patients. TRIAL REGISTRATION: UK Clinical Trials Gateway, ISRCTN74643496 , Registered on 8 April 2015

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Correction to: Cluster identification, selection, and description in Cluster randomized crossover trials: the PREP-IT trials

An amendment to this paper has been published and can be accessed via the original article

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)