In silico validation of the autoinflammatory disease damage index

Introduction Autoinflammatory diseases can cause irreversible tissue damage due to systemic inflammation. Recently, the Autoinflammatory Disease Damage Index (ADDI) was developed. The ADDI is the first instrument to quantify damage in familial Mediterranean fever, cryopyrin-associated periodic syndromes, mevalonate kinase deficiency and tumour necrosis factor receptor-associated periodic syndrome. The aim of this study was to validate this tool for its intended use in a clinical/research setting. Methods The ADDI was scored on paper clinical cases by at least three physicians per case, independently of each other. Face and content validity were assessed by requesting comments on the ADDI. Reliability was tested by calculating the intraclass correlation coefficient (ICC) using an â observer-nested-within-subject\u27 design. Construct validity was determined by correlating the ADDI score to the Physician Global Assessment (PGA) of damage and disease activity. Redundancy of individual items was determined with Cronbach\u27s alpha. Results The ADDI was validated on a total of 110 paper clinical cases by 37 experts in autoinflammatory diseases. This yielded an ICC of 0.84 (95% CI 0.78 to 0.89). The ADDI score correlated strongly with PGA-damage (r=0.92, 95% CI 0.88 to 0.95) and was not strongly influenced by disease activity (r=0.395, 95% CI 0.21 to 0.55). After comments from disease experts, some item definitions were refined. The interitem correlation in all different categories was lower than 0.7, indicating that there was no redundancy between individual damage items. Conclusion The ADDI is a reliable and valid instrument to quantify damage in individual patients and can be used to compare disease outcomes in clinical studies

Practice and consensus-based strategies in diagnosing and managing systemic juvenile idiopathic arthritis in Germany

Background: Systemic juvenile idiopathic arthritis (SJIA) is an autoinflammatory disease associated with chronic arthritis. Early diagnosis and effective therapy of SJIA is desirable, so that complications are avoided. The PRO-KIND initiative of the German Society for Pediatric Rheumatology (GKJR) aims to define consensus-based strategies to harmonize diagnostic and therapeutic approaches in Germany. Methods: We analyzed data on patients diagnosed with SJIA from 3 national registries in Germany. Subsequently, via online surveys and teleconferences among pediatric rheumatologists with a special expertise in the treatment of SJIA, we identified current diagnostic and treatment approaches in Germany. Those were harmonized via the formulation of statements and, supported by findings from a literature search. Finally, an in-person consensus conference using nominal group technique was held to further modify and consent the statements. Results: Up to 50% of patients diagnosed with SJIA in Germany do not fulfill the International League of Associations for Rheumatology (ILAR) classification criteria, mostly due to the absence of chronic arthritis. Our findings suggest that chronic arthritis is not obligatory for the diagnosis and treatment of SJIA, allowing a diagnosis of probable SJIA Malignant, infectious and hereditary autoinflammatory diseases should be considered before rendering a diagnosis of probable SJIA There is substantial variability in the initial treatment of SJIA. Based on registry data, most patients initially receive systemic glucocorticoids, however, increasingly substituted or accompanied by biological agents, i.e. interleukin (IL)-1 and IL-6 blockade (up to 27.2% of patients). We identified preferred initial therapies for probable and definitive SJIA, including step-up patterns and treatment targets for the short-term (resolution of fever, decrease in C-reactive protein by 50% within 7 days), the mid-term (improvement in physician global and active joint count by at least 50% or a JADAS-10 score of maximally 5.4 within 4 weeks) and the long-term (glucocorticoid-free clinically inactive disease within 6 to 12 months), and an explicit treat-to-target strategy. Conclusions: We developed consensus-based strategies regarding the diagnosis and treatment of probable or definitive SJIA in Germany

Gain-of-function human STAT1 mutations impair IL-17 immunity and underlie chronic mucocutaneous candidiasis

Chronic mucocutaneous candidiasis disease (CMCD) may be caused by autosomal dominant (AD) IL-17F deficiency or autosomal recessive (AR) IL-17RA deficiency. Here, using whole-exome sequencing, we identified heterozygous germline mutations in STAT1 in 47 patients from 20 kindreds with AD CMCD. Previously described heterozygous STAT1 mutant alleles are loss-of-function and cause AD predisposition to mycobacterial disease caused by impaired STAT1-dependent cellular responses to IFN-γ. Other loss-of-function STAT1 alleles cause AR predisposition to intracellular bacterial and viral diseases, caused by impaired STAT1-dependent responses to IFN-α/β, IFN-γ, IFN-λ, and IL-27. In contrast, the 12 AD CMCD-inducing STAT1 mutant alleles described here are gain-of-function and increase STAT1-dependent cellular responses to these cytokines, and to cytokines that predominantly activate STAT3, such as IL-6 and IL-21. All of these mutations affect the coiled-coil domain and impair the nuclear dephosphorylation of activated STAT1, accounting for their gain-of-function and dominance. Stronger cellular responses to the STAT1-dependent IL-17 inhibitors IFN-α/β, IFN-γ, and IL-27, and stronger STAT1 activation in response to the STAT3-dependent IL-17 inducers IL-6 and IL-21, hinder the development of T cells producing IL-17A, IL-17F, and IL-22. Gain-of-function STAT1 alleles therefore cause AD CMCD by impairing IL-17 immunity

Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease.

BACKGROUND: The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS: Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes. RESULTS: We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7)). CONCLUSIONS: We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).Supported by a career development award from the National Heart, Lung, and Blood Institute, National Institutes of Health (NIH) (K08HL114642 to Dr. Stitziel) and by the Foundation for Barnes–Jewish Hospital. Dr. Peloso is supported by the National Heart, Lung, and Blood Institute of the NIH (award number K01HL125751). Dr. Kathiresan is supported by a Research Scholar award from the Massachusetts General Hospital, the Donovan Family Foundation, grants from the NIH (R01HL107816 and R01HL127564), a grant from Fondation Leducq, and an investigator-initiated grant from Merck. Dr. Merlini was supported by a grant from the Italian Ministry of Health (RFPS-2007-3-644382). Drs. Ardissino and Marziliano were supported by Regione Emilia Romagna Area 1 Grants. Drs. Farrall and Watkins acknowledge the support of the Wellcome Trust core award (090532/Z/09/Z), the British Heart Foundation (BHF) Centre of Research Excellence. Dr. Schick is supported in part by a grant from the National Cancer Institute (R25CA094880). Dr. Goel acknowledges EU FP7 & Wellcome Trust Institutional strategic support fund. Dr. Deloukas’s work forms part of the research themes contributing to the translational research portfolio of Barts Cardiovascular Biomedical Research Unit, which is supported and funded by the National Institute for Health Research (NIHR). Drs. Webb and Samani are funded by the British Heart Foundation, and Dr. Samani is an NIHR Senior Investigator. Dr. Masca was supported by the NIHR Leicester Cardiovascular Biomedical Research Unit (BRU), and this work forms part of the portfolio of research supported by the BRU. Dr. Won was supported by a postdoctoral award from the American Heart Association (15POST23280019). Dr. McCarthy is a Wellcome Trust Senior Investigator (098381) and an NIHR Senior Investigator. Dr. Danesh is a British Heart Foundation Professor, European Research Council Senior Investigator, and NIHR Senior Investigator. Drs. Erdmann, Webb, Samani, and Schunkert are supported by the FP7 European Union project CVgenes@ target (261123) and the Fondation Leducq (CADgenomics, 12CVD02). Drs. Erdmann and Schunkert are also supported by the German Federal Ministry of Education and Research e:Med program (e:AtheroSysMed and sysINFLAME), and Deutsche Forschungsgemeinschaft cluster of excellence “Inflammation at Interfaces” and SFB 1123. Dr. Kessler received a DZHK Rotation Grant. The analysis was funded, in part, by a Programme Grant from the BHF (RG/14/5/30893 to Dr. Deloukas). Additional funding is listed in the Supplementary Appendix.This is the author accepted manuscript. The final version is available from the Massachusetts Medical Society via http://dx.doi.org/10.1056/NEJMoa150765

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.Peer reviewe

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis

Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P <10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P <5 x 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.Peer reviewe

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 x 10(-8)) or suggestively genome wide (p < 2.3 x 10(-6)). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/ near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/ near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass