The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape : A Large-Scale Genome-Wide Interaction Study

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age-and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to similar to 2.8M SNPs with BMI and WHRadjBMI in four strata (men 50y, women 50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR= 50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may providefurther insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.Peer reviewe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Use and Safety Profile of Antiepileptic Drugs in Italy.

OBJECTIVE: To analyse and discuss the use and the safety profile of individual antiepileptic drugs (AEDs) in Italy. METHODS: The AED safety data referred to the period January 1988-June 2005 and were obtained from the database of the Italian Interregional Group of Pharmacovigilance (GIF). This database collects all spontaneous reports of suspected adverse drug reactions (ADRs) from six Italian regions which are the main contributors to the Italian spontaneous reporting system. Individual AED consumption data (defined daily dose/1,000 inhabitants per day) in the GIF area and in the whole of Italy referred to the period January 2003-June 2005 and were derived from drug sales data (Institute for Medical Statistics Health). RESULTS: Phenobarbital was the most frequently used AED in the GIF area (4.26 DDD/1,000 inhabitants per day) followed by carbamazepine (1.97), valproic acid (1.33) and gabapentin (1.10). AED consumption in the whole of Italy showed a similar pattern. Gabapentin was the most frequently used AED among newer AEDs. In the GIF database 37,906 reports (up to June 2005) were present; 666 of them (1.76%) were associated with at least one AED (Anatomical Therapeutic Chemical code N03A). The AED with the highest number of reports was carbamazepine (208 reports) followed by phenobarbital (98), gabapentin (80), phenytoin (56), valproic acid (55), lamotrigine (51), oxcarbazepine (43) and vigabatrin (35). Use and toxicity profile were evaluated only for AEDs associated with at least 30 reports. Skin reactions were the most frequently reported ADRs, followed by haematological, general condition, hepatic, neurological and gastrointestinal adverse reactions. Phenobarbital, lamotrigine, carbamazepine and phenytoin had the highest percentage of skin reactions (69, 67, 60 and 54%, respectively). Many haematological reactions were reported for each AED; the highest percentage was related to valproic acid (25%). Vigabatrin was associated with the highest percentage of reactions related to hearing, vision and other senses (97%). Phenytoin and valproic acid had the highest percentage of hepatic reactions (30 and 20%), whereas gabapentin of nervous system, psychiatric, gastrointestinal and urinary reactions (26, 21, 21 and 14%, respectively) and phenobarbital of musculoskeletal reactions (13%). CONCLUSIONS: In Italy antiepileptic drug therapy appears to be still dominated by traditional drugs. Our analysis showed a different safety profile related to each AED. Some of the drug-adverse reaction associations discussed are not included in the Italian drug leaflets or have not been reported before in the literature

FarmaREL : an Italian pharmacovigilance project to monitor and evaluate adverse drug reactions in haematologic patients

Adverse drug reactions (ADRs) reduce patients' quality of life, increase mortality and morbidity, and have a negative economic impact on healthcare systems. Nevertheless, the importance of ADR reporting is often underestimated. The project "FarmaREL" has been developed to monitor and evaluate ADRs in haematological patients and to increase pharmacovigilance culture among haematology specialists. In 13 haematology units, based in Lombardy, Italy, a dedicated specialist with the task of encouraging ADRs reporting and sensitizing healthcare professionals to pharmacovigilance has been assigned. The ADRs occurring in haematological patients were collected electronically and then analysed with multiple logistic regression. Between January 2009 and December 2011, 887 reports were collected. The number of ADRs was higher in older adults (528; 59%), in male (490; 55%), and in non-Hodgkin lymphoma patients (343; 39%). Most reactions were severe (45% required or prolonged hospitalization), but in most cases, they were fully resolved at the time of reporting. According to Schumock and Thornton criteria, a percentage of ADRs as high as 7% was found to be preventable versus 2% according to reporter opinion. Patients' haematological diagnosis, not age or gender, resulted to be the variable that most influenced ADR, in particular severity and outcome. The employment of personnel specifically dedicated to pharmacovigilance is a successful strategy to improve the number and quality of ADR reports. "FarmaREL", the first programme of active pharmacovigilance in oncohaematologic patients, significantly contributed to reach the WHO "Gold Standard" for pharmacovigilance in Lombardy, Italy

Incidence, causative factors and mortality rates of Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) in northern Italy: data from the REACT registry

Purpose: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare but severe cutaneous adverse drug reactions. We assessed incidence, drug exposure and mortality, analysing data obtained from the Lombardy Registry of Severe Cutaneous Reactions (REACT). Methods: Data were collected from hospitals in the Italian Lombardy region (9502272 people). A trained monitor was sent to the reporting hospital to collect data on drug exposure and clinical features. The algorithm for drug causality for epidermal necrolysis algorithm was applied to assess drug causality. Defined Daily Dose (DDD) was used to express drug consumption. Results: From April 2009 to November 2014, 17 cases of TEN and 59 cases of SJS were collected. The overall incidence rate was 1.40 cases (95%CI, 1.12-1.76) per million people per year. A total of 15 cases died during hospitalization with a mortality rate of 16.9% for SJS and 29.4% for TEN. Overall, 55.4% of cases had a probable or very probable relation with drug exposure. In a total of five patients (6.6%), no causative drug for the reaction was identifiable. Allopurinol contributed to the highest number of cases (23 cases), while the highest incidence based on more than one case reported was observed for cotrimoxazole and lamotrigine, with 5.37 cases (95%CI, 2.09-13.80) and 3.54 (95%CI, 1.21-10.42) per 10million DDD/year, respectively. Conclusions: We confirmed that SJS and TEN are rare adverse cutaneous reactions. As expected, mortality was influenced by the degree of skin detachment. The profile of drugs associated with the reactions was in agreement with data from other surveillance systems

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease