Stratified genome-wide association analysis of type 2 diabetes reveals subgroups with genetic and environmental heterogeneity

Type 2 diabetes (T2D) is a heterogeneous illness caused by genetic and environmental factors. Previous genome wide association studies (GWAS) have identified many genetic variants associated with T2D and found evidence of differing genetic profiles by age-at-onset. This study seeks to explore further the genetic and environmental drivers of T2D by analysing subgroups based on age-at-onset of diabetes and body mass index (BMI). In UK Biobank, 36 494 T2D cases were stratified into 3 subgroups and GWAS performed for all T2D cases and for each subgroup relative to 421 021 controls. Altogether, 18 SNPs significantly associated genome-wide with T2D in one or more subgroups also showed evidence of heterogeneity between the subgroups, (Cochrane's Q p < 0.01) with 2 remaining significant after multiple testing (in CDKN2B and CYTIP). Combined risk scores, based on genetic profile, BMI and age, resulted in excellent diabetes prediction (AUC = 0.92). A modest improvement in prediction (AUC = 0.93) was seen when the contribution of genetic and environmental factors was evaluated separately for each subgroup. Increasing sample sizes of genetic studies enables us to stratify disease cases into subgroups which have sufficient power to highlight areas of genetic heterogeneity. Despite some evidence that optimising combined risk scores by subgroup improves prediction, larger sample sizes are likely needed for prediction when using a stratification approach

Stratified genome-wide association analysis of Type 2 Diabetes reveals subgroups with genetic and environmental heterogeneity

Type 2 diabetes (T2D) is a heterogeneous illness caused by genetic and environmental factors. Previous genome wide association studies (GWAS) have identified many genetic variants associated with T2D and found evidence of differing genetic profiles by age-at-onset. This study seeks to explore further the genetic and environmental drivers of T2D by analysing subgroups based on age-at-onset of diabetes and body mass index (BMI). In UK Biobank, 36 494 T2D cases were stratified into 3 subgroups and GWAS performed for all T2D cases and for each subgroup relative to 421 021 controls. Altogether, 18 SNPs significantly associated genome-wide with T2D in one or more subgroups also showed evidence of heterogeneity between the subgroups, (Cochrane’s Q p < 0.01) with 2 remaining significant after multiple testing (in CDKN2B and CYTIP). Combined risk scores, based on genetic profile, BMI and age, resulted in excellent diabetes prediction (AUC = 0.92). A modest improvement in prediction (AUC = 0.93) was seen when the contribution of genetic and environmental factors was evaluated separately for each subgroup. Increasing sample sizes of genetic studies enables us to stratify disease cases into subgroups which have sufficient power to highlight areas of genetic heterogeneity. Despite some evidence that optimising combined risk scores by subgroup improves prediction, larger sample sizes are likely needed for prediction when using a stratification approach

The functional status and well being of people with myalgic encephalomyelitis/chronic fatigue syndrome and their carers

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background Diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome or ME/CFS is largely based on clinical history, and exclusion of identifiable causes of chronic fatigue. Characterization of cases and the impact of interventions have been limited due to clinical heterogeneity and a lack of reliable biomarkers for diagnosis and outcome measures. People with ME/CFS (PWME) often report high levels of disability, which are difficult to measure objectively. The well being of family members and those who care for PWME are also likely to be affected. This study aimed to investigate the functional status and well being of PWME and their lay carers, and to compare them with people with other chronic conditions. Methods We used a cross sectional design to study 170 people aged between 18 and 64 years with well characterized ME/CFS, and 44 carers, using SF-36 v2™. Mean physical and mental domains scores (scales and component summaries) were calculated and compared internally and externally with reference standards for the general population and for population groups with 10 chronic diseases. Results SF-36 scores in PWME were significantly reduced, especially within the physical domain (mean norm-based Physical Component Summary (PCS) score = 26.8), but also within the mental domain (mean norm-based score for Mental Component Summary (MCS) = 34.1). The lowest and highest scale scores were for "Role-Physical" (mean = 25.4) and "Mental Health" (mean = 36.7) respectively. All scores were in general lower than those for the general population and diseased-specific norms for other diseases. Carers of those with ME/CFS tended to have low scores in relation to population norms, particularly within the mental domain (mean = 45.4). Conclusions ME/CFS is disabling and has a greater impact on functional status and well being than other chronic diseases such as cancer. The emotional burden of ME/CFS is felt by lay carers as well as by people with ME/CFS. We suggest the use of generic instruments such as SF-36, in combination of other objective outcome measurements, to describe patients and assess treatments.Published versio

Stratified genome-wide association analysis of type 2 diabetes reveals subgroups with genetic and environmental heterogeneity

Type 2 diabetes (T2D) is a heterogeneous illness caused by genetic and environmental factors. Previous genome wide association studies (GWAS) have identified many genetic variants associated with T2D and found evidence of differing genetic profiles by age-at-onset. This study seeks to explore further the genetic and environmental drivers of T2D by analysing subgroups based on age-at-onset of diabetes and body mass index (BMI). In UK Biobank, 36 494 T2D cases were stratified into 3 subgroups and GWAS performed for all T2D cases and for each subgroup relative to 421 021 controls. Altogether, 18 SNPs significantly associated genome-wide with T2D in one or more subgroups also showed evidence of heterogeneity between the subgroups, (Cochrane’s Q p < 0.01) with 2 remaining significant after multiple testing (in CDKN2B and CYTIP). Combined risk scores, based on genetic profile, BMI and age, resulted in excellent diabetes prediction (AUC = 0.92). A modest improvement in prediction (AUC = 0.93) was seen when the contribution of genetic and environmental factors was evaluated separately for each subgroup. Increasing sample sizes of genetic studies enables us to stratify disease cases into subgroups which have sufficient power to highlight areas of genetic heterogeneity. Despite some evidence that optimising combined risk scores by subgroup improves prediction, larger sample sizes are likely needed for prediction when using a stratification approach

Suboptimal gastroprotective coverage of NSAID use and the risk of upper gastrointestinal bleeding and ulcers: An observational study using three European databases

Background: Gastro-protective agents (GPA) are co-prescribed with non-steroidal anti-inflammatory drugs (NSAID) to lower the risk of upper gastrointestinal (UGI) events. It is unknown to what extent the protective effect is influenced by therapy adherence. Aim: To study the association between GPA adherence and UGI events among non-selective (ns) NSAID users. Methods: The General Practice Research Database (UK 1998e2008), the Integrated Primary Care Information database (the Netherlands 1996-2007) and the Health Search/CSD Longitudinal Patient Database (Italy 2000-2007) were used. A nested case-control design was employed within a cohort of nsNSAID users aged ≥50 years, who also used a GPA. UGI event cases (UGI bleeding and/or symptomatic ulcer with/without obstruction/perforation) were matched to event-free members of the cohort for age, sex, database and calendar time. Adherence to GPA was calculated as the proportion of nsNSAID treatment days covered by a GPA prescription. Adjusted OR with 95% CI were calculated. Results: The cohort consisted of 618 684 NSAID users, generating 1 107 266 nsNSAID episodes. Of these, 117 307 (10.6%) were (partly) covered by GPA, 4.9% of which with a GPA coverage 80% (full adherence). 339 patients experienced an event. Among non-adherers, the OR was 2.39 (95% CI 1.66 to 3.44) for all UGI events and 1.89 (95% CI 1.09 to 3.28) for UGI bleeding alone, compared to full adherers. Conclusions: The risk of UGI events was significantly higher in nsNSAID users with GPA non-adherence. This underlines the importance of strategies to improve GPA adherence. Copyright Article author (or their employer) 2011

Using Electronic Health Care Records for Drug Safety Signal Detection A Comparative Evaluation of Statistical Methods

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Genomewide Association Study of Statin-Induced Myopathy in Patients Recruited Using the UK Clinical Practice Research Datalink.

Statins can be associated with myopathy. We have undertaken a genomewide association study (GWAS) to discover and validate genetic risk factors for statin-induced myopathy in a "real-world" setting. One hundred thirty-five patients with statin myopathy recruited via the UK Clinical Practice Research Datalink were genotyped using the Illumina OmniExpress Exome version 1.0 Bead Chip and compared with the Wellcome Trust Case-Control Consortium (n = 2,501). Nominally statistically significant single nucleotide polymorphism (SNP) signals in the GWAS (P T in the SLCO1B1 gene) SNP was genomewide significant in the severe myopathy (creatine kinase > 10 × upper limit of normal or rhabdomyolysis) group (P = 2.55 × 10-9 ; odds ratio 5.15; 95% confidence interval 3.13-8.45). The association with SLCO1B1 was present for several statins and replicated in the independent validation cohorts. The data highlight the role of SLCO1B1 c.521C>T SNP as a replicable genetic risk factor for statin myopathy. No other novel genetic risk factors with a similar effect size were identified

Systemic antibiotic prescribing to paediatric outpatients in 5 European countries: A population-based cohort study

Background: To describe the utilisation of antibiotics in children and adolescents across 5 European countries based on the same drug utilisation measures and age groups. Special attention was given to age-group-specific distributions of antibiotic subgroups, since comparison in this regard between countries is lacking so far.Methods: Outpatient paediatric prescriptions of systemic antibiotics during the years 2005-2008 were analysed using health care databases from the UK, the Netherlands, Denmark, Italy and Germany. Annual antibiotic prescription rates per 1,000 person years were estimated for each database and stratified by age (≤4, 5-9, 10-14, 15-18 years). Age-group-specific distributions of antibiotic subgroups were calculated for 2008.Results: With 957 prescriptions per 1000 person years, the highest annual prescription rate in the year 2008 was found in the Italian region Emilia Romagna followed by Germany (561), the UK (555), Denmark (481) and the Netherlands (294). Seasonal peaks during winter months were most pronounced in countries with high utilisation. Age-group-specific use varied substantially between countries with regard to total prescribing and distributions of antibiotic subgroups. However, prescription rates were highest among children in the age group ≤4 years in all countries, predominantly due to high use of broad s

Drug-Induced Liver Injury due to Flucloxacillin:Relevance of Multiple Human Leukocyte Antigen Alleles

© 2019 The Authors Clinical Pharmacology & Therapeutics © 2019 American Society for Clinical Pharmacology and Therapeutics Some patients prescribed flucloxacillin (~0.01%) develop drug-induced liver injury (DILI). HLA-B*57:01 is an established genetic risk factor for flucloxacillin DILI. To consolidate this finding, identify additional genetic factors, and assess relevance of risk factors for flucloxacillin DILI in relation to DILI due to other penicillins, we performed a genomewide association study involving 197 flucloxacillin DILI cases and 6,835 controls. We imputed single-nucleotide polymorphism and human leukocyte antigen (HLA) genotypes. HLA-B*57:01 was the major risk factor (allelic odds ratio (OR)=36.62; P=2.67×10−97). HLA-B*57:03 also showed an association (OR=79.21; P=1.2×10−6). Within the HLA-B protein sequence, imputation showed valine97, common to HLA-B*57:01 and HLA-B*57:03, had the largest effect (OR=38.1; P=9.7×10−97). We found no HLA-B*57 association with DILI due to other isoxazolyl penicillins (n=6) or amoxicillin (n=15) and no significant non-HLA signals for any penicillin-related DILI

Statin Induced Myopathy and Myalgia: Time Trend Analysis and Comparison of Risk Associated with Statin Class from 1991–2006

BACKGROUND: Statins are widely used as a cholesterol lowering medication, reduce cardiovascular mortality and morbidity in high risk patients; and only rarely cause serious adverse drug reactions (ADRs). UK primary care databases of morbidity and prescription data, which now cover several million people, have potential for more powerful analytical approaches to study ADRs including adjusting for confounders and examining temporal effects. METHODS: Case-crossover design in detecting statin associated myopathy ADR in 93, 831 patients, using two independent primary care databases (1991-2006). We analysed risk by drug class, by disease code and cumulative year, exploring different cut-off exposure times and confounding by temporality. RESULTS: Using a 12 and 26 week exposure period, large risk ratios (RR) are associated with all classes of statins and fibrates for myopathy: RR 10.6 (9.8-11.4) and 19.9 (17.6-22.6) respectively. At 26 weeks, the largest risks are with fluvastatin RR 33.3 (95% CI 16.8-66.0) and ciprofibrate (with previous statin use) RR 40.5 (95% CI 13.4-122.0). AT 12 weeks the differences between cerivastatin and atorvastatin RR for myopathy were found to be significant, RR 2.05 (95% CI 1.2-3.5), and for rosuvastatin and fluvastatin RR 3.0 (95% CI 1.6-5.7). After 12 months of statin initiation, the relative risk for myopathy for all statins and fibrates increased to 25.7 (95% CI 21.8-30.3). Furthermore, this signal was detected within 2 years of first events being recorded. Our data suggests an annual incidence of statin induced myopathy or myalgia of around 11.4 for 16, 591 patients or 689 per million per year. CONCLUSION: There may be differential risks associated with some classes of statin and fibrate. Myopathy related to statin or fibrate use may persist after a long exposure time (12 months or more). These methods could be applied for early detection of harmful drug side effects, using similar primary care diagnostic and prescribing data