ARMC 5 Variants and Risk of Hypertension in Blacks: MH- GRID Study.

Background We recently found that ARMC 5 variants may be associated with primary aldosteronism in blacks. We investigated a cohort from the MH - GRID (Minority Health Genomics and Translational Research Bio-Repository Database) and tested the association between ARMC 5 variants and blood pressure in black s. Methods and Results Whole exome sequencing data of 1377 black s were analyzed. Target single-variant and gene-based association analyses of hypertension were performed for ARMC 5, and replicated in a subset of 3015 individuals of African descent from the UK Biobank cohort. Sixteen rare variants were significantly associated with hypertension ( P=0.0402) in the gene-based (optimized sequenced kernel association test) analysis; the 16 and one other, rs116201073, together, showed a strong association ( P=0.0003) with blood pressure in this data set. The presence of the rs116201073 variant was associated with lower blood pressure. We then used human embryonic kidney 293 and adrenocortical H295R cells transfected with an ARMC 5 construct containing rs116201073 (c.*920T>C). The latter was common in both the discovery ( MH - GRID ) and replication ( UK Biobank) data and reached statistical significance ( P=0.044 [odds ratio, 0.7] and P=0.007 [odds ratio, 0.76], respectively). The allele carrying rs116201073 increased levels of ARMC5 mRNA , consistent with its protective effect in the epidemiological data. Conclusions ARMC 5 shows an association with hypertension in black s when rare variants within the gene are considered. We also identified a protective variant of the ARMC 5 gene with an effect on ARMC 5 expression confirmed in vitro. These results extend our previous report of ARMC 5's possible involvement in the determination of blood pressure in blacks

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

A national registry for juvenile dermatomyositis and other paediatric idiopathic inflammatory myopathies: 10 years' experience; the Juvenile Dermatomyositis National (UK and Ireland) Cohort Biomarker Study and Repository for Idiopathic Inflammatory Myopathies

Objectives: The paediatric idiopathic inflammatory myopathies (IIMs) are a group of rare chronic inflammatory disorders of childhood, affecting muscle, skin and other organs. There is a severe lack of evidence base for current treatment protocols in juvenile myositis. The rarity of these conditions means that multicentre collaboration is vital to facilitate studies of pathogenesis, treatment and disease outcomes. We have established a national registry and repository for childhood IIM, which aims to improve knowledge, facilitate research and clinical trials, and ultimately to improve outcomes for these patients. Methods: A UK-wide network of centres and research group was established to contribute to the study. Standardized patient assessment, data collection forms and sample protocols were agreed. The Biobank includes collection of peripheral blood mononuclear cells, serum, genomic DNA and biopsy material. An independent steering committee was established to oversee the use of data/samples. Centre training was provided for patient assessment, data collection and entry. Results: Ten years after inception, the study has recruited 285 children, of which 258 have JDM or juvenile PM; 86% of the cases have contributed the biological samples. Serial sampling linked directly to the clinical database makes this a highly valuable resource. The study has been a platform for 20 sub-studies and attracted considerable funding support. Assessment of children with myositis in contributing centres has changed through participation in this study. Conclusions: This establishment of a multicentre registry and Biobank has facilitated research and contributed to progress in the management of a complex group of rare muscloskeletal conditions

Genetic Evidence for a Link Between Favorable Adiposity and Lower Risk of Type 2 Diabetes, Hypertension, and Heart Disease.

Recent genetic studies have identified some alleles that are associated with higher BMI but lower risk of type 2 diabetes, hypertension, and heart disease. These "favorable adiposity" alleles are collectively associated with lower insulin levels and higher subcutaneous-to-visceral adipose tissue ratio and may protect from disease through higher adipose storage capacity. We aimed to use data from 164,609 individuals from the UK Biobank and five other studies to replicate associations between a genetic score of 11 favorable adiposity variants and adiposity and risk of disease, to test for interactions between BMI and favorable adiposity genetics, and to test effects separately in men and women. In the UK Biobank, the 50% of individuals carrying the most favorable adiposity alleles had higher BMIs (0.120 kg/m(2) [95% CI 0.066, 0.174]; P = 1E-5) and higher body fat percentage (0.301% [0.230, 0.372]; P = 1E-16) compared with the 50% of individuals carrying the fewest alleles. For a given BMI, the 50% of individuals carrying the most favorable adiposity alleles were at lower risk of type 2 diabetes (odds ratio [OR] 0.837 [0.784, 0.894]; P = 1E-7), hypertension (OR 0.935 [0.911, 0.958]; P = 1E-7), and heart disease (OR 0.921 [0.872, 0.973]; P = 0.003) and had lower blood pressure (systolic -0.859 mmHg [-1.099, -0.618]; P = 3E-12 and diastolic -0.394 mmHg [-0.534, -0.254]; P = 4E-8). In women, these associations could be explained by the observation that the alleles associated with higher BMI but lower risk of disease were also associated with a favorable body fat distribution, with a lower waist-to-hip ratio (-0.004 cm [95% CI -0.005, -0.003] 50% vs. 50%; P = 3E-14), but in men, the favorable adiposity alleles were associated with higher waist circumference (0.454 cm [0.267, 0.641] 50% vs. 50%; P = 2E-6) and higher waist-to-hip ratio (0.0013 [0.0003, 0.0024] 50% vs. 50%; P = 0.01). Results were strengthened when a meta-analysis with five additional studies was conducted. There was no evidence of interaction between a genetic score consisting of known BMI variants and the favorable adiposity genetic score. In conclusion, different molecular mechanisms that lead to higher body fat percentage (with greater subcutaneous storage capacity) can have different impacts on cardiometabolic disease risk. Although higher BMI is associated with higher risk of diseases, better fat storage capacity could reduce the risk.This is the author accepted manuscript. The final version is available from the American Diabetes Association via http://dx.doi.org/10.2337/db15-167

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

Genome-wide analysis in UK Biobank identifies four loci associated with mood instability and genetic correlation with MDD, anxiety disorder and schizophrenia

Mood instability is a core clinical feature of affective and psychotic disorders. In keeping with the Research Domain Criteria approach, it may be a useful construct for identifying biology that cuts across psychiatric categories. We aimed to investigate the biological validity of a simple measure of mood instability and evaluate its genetic relationship with several psychiatric disorders, including major depressive disorder (MDD), bipolar disorder (BD), schizophrenia, attention deficit hyperactivity disorder (ADHD), anxiety disorder and post-traumatic stress disorder (PTSD). We conducted a genome-wide association study (GWAS) of mood instability in 53,525 cases and 60,443 controls from UK Biobank, identifying four independently associated loci (on chromosomes 8, 9, 14 and 18), and a common single-nucleotide polymorphism (SNP)-based heritability estimate of ~8%. We found a strong genetic correlation between mood instability and MDD (r g = 0.60, SE = 0.07, p = 8.95 × 10−17) and a small but significant genetic correlation with both schizophrenia (r g = 0.11, SE = 0.04, p = 0.01) and anxiety disorders (r g = 0.28, SE = 0.14, p = 0.04), although no genetic correlation with BD, ADHD or PTSD was observed. Several genes at the associated loci may have a role in mood instability, including the DCC netrin 1 receptor (DCC) gene, eukaryotic translation initiation factor 2B subunit beta (eIF2B2), placental growth factor (PGF) and protein tyrosine phosphatase, receptor type D (PTPRD). Strengths of this study include the very large sample size, but our measure of mood instability may be limited by the use of a single question. Overall, this work suggests a polygenic basis for mood instability. This simple measure can be obtained in very large samples; our findings suggest that doing so may offer the opportunity to illuminate the fundamental biology of mood regulation

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors