Introducing the importance and difficulties of a three-step approach to improve nonadherence to antihypertensive drugs:A case series

Nonadherence to antihypertensive drugs is an important reason for not reaching blood pressure goals. A possible method to improve nonadherence involves three essential steps: identification of nonadherent patients (step 1), determination of underlying causes (step 2) and a personalized solution (step 3). We present three unique cases to show the importance and difficulties of this three-step approach. Patients participated in a randomized controlled trial to improve nonadherence to antihypertensive drugs (RHYME-RCT, Dutch Trial Register NL6736). Drug level measurements were used to identify nonadherence to antihypertensive drugs and communication on drug levels was supported by a tailored feedback tool in these patients. These cases showed that a three-step approach of identifying nonadherence and determination of the underlying cause, can lead to a personalized solution to improve therapy even when nonadherence was excluded. Open communication with patients remains an essential part when improving nonadherence

Red blood cells from patients with sitosterolemia exhibit impaired membrane lipid composition and distribution and decreased deformability

Sitosterolemia is a metabolic disorder leading to excessive accumulation of phytosterols. Hemolytic stomatocytosis and macrothrombocytopenia are part of the clinical picture. However, the impact of phytosterols on red blood cell (RBC) deformability, membrane lipid composition and distribution and the efficiency of the reference treatment, Ezetimibe, are largely unknown. This study addresses these issues using RBCs from three patients with sitosterolemia and healthy RBCs exposed to β-sitosterol. Patients presented an increased proportion of stomatocytes, decreased RBC deformability and increased RBC hydration and osmotic fragility compared to healthy donors. At the membrane level, patient RBCs showed (i) very high content in β-sitosterols, (ii) increased proportions of saturated fatty acids and polyunsaturated fatty acid species with long and unsaturated carbon chains, and (iii) decreased content in phosphatidylethanolamine species. These lipid changes were accompanied by an almost complete abrogation of cholesterol-enriched domains, which could result from: (i) the reduced phosphatidylethanolamine content which positively correlated with domain abundance; and (ii) the fatty acid modifications and increased phytosterol content, both compatible with higher membrane stiffness. The role of β-sitosterol was supported by comparable changes in RBC morphology and cholesterol-enriched domains upon β-sitosterol integration at the healthy RBC membrane. Finally, Ezetimibe treatment combined with a sterol restricted diet lowered phytosterols and improved anemia and RBC deformability and hydration. However, this treatment had no or limited effect on RBC morphology and cholesterol-enriched domain abundance. This study reveals for the first time that phytosterols affect RBC membrane lipid composition and distribution but also RBC morphology, hydration, deformability and fragility

Regulatory cell therapy in kidney transplantation (The ONE Study): a harmonised design and analysis of seven non-randomised, single-arm, phase 1/2A trials.

BackgroundUse of cell-based medicinal products (CBMPs) represents a state-of-the-art approach for reducing general immunosuppression in organ transplantation. We tested multiple regulatory CBMPs in kidney transplant trials to establish the safety of regulatory CBMPs when combined with reduced immunosuppressive treatment.MethodsThe ONE Study consisted of seven investigator-led, single-arm trials done internationally at eight hospitals in France, Germany, Italy, the UK, and the USA (60 week follow-up). Included patients were living-donor kidney transplant recipients aged 18 years and older. The reference group trial (RGT) was a standard-of-care group given basiliximab, tapered steroids, mycophenolate mofetil, and tacrolimus. Six non-randomised phase 1/2A cell therapy group (CTG) trials were pooled and analysed, in which patients received one of six CBMPs containing regulatory T cells, dendritic cells, or macrophages; patient selection and immunosuppression mirrored the RGT, except basiliximab induction was substituted with CBMPs and mycophenolate mofetil tapering was allowed. None of the trials were randomised and none of the individuals involved were masked. The primary endpoint was biopsy-confirmed acute rejection (BCAR) within 60 weeks after transplantation; adverse event coding was centralised. The RTG and CTG trials are registered with ClinicalTrials.gov, NCT01656135, NCT02252055, NCT02085629, NCT02244801, NCT02371434, NCT02129881, and NCT02091232.FindingsThe seven trials took place between Dec 11, 2012, and Nov 14, 2018. Of 782 patients assessed for eligibility, 130 (17%) patients were enrolled and 104 were treated and included in the analysis. The 66 patients who were treated in the RGT were 73% male and had a median age of 47 years. The 38 patients who were treated across six CTG trials were 71% male and had a median age of 45 years. Standard-of-care immunosuppression in the recipients in the RGT resulted in a 12% BCAR rate (expected range 3·2-18·0). The overall BCAR rate for the six parallel CTG trials was 16%. 15 (40%) patients given CBMPs were successfully weaned from mycophenolate mofetil and maintained on tacrolimus monotherapy. Combined adverse event data and BCAR episodes from all six CTG trials revealed no safety concerns when compared with the RGT. Fewer episodes of infections were registered in CTG trials versus the RGT.InterpretationRegulatory cell therapy is achievable and safe in living-donor kidney transplant recipients, and is associated with fewer infectious complications, but similar rejection rates in the first year. Therefore, immune cell therapy is a potentially useful therapeutic approach in recipients of kidney transplant to minimise the burden of general immunosuppression.FundingThe 7th EU Framework Programme

Genome-Based Prediction of Breast Cancer Risk in the General Population: A Modeling Study Based on Meta-Analyses of Genetic Associations

Abstract Background: Genome-wide association studies identified novel breast cancer susceptibility variants that could be used to predict breast cancer in asymptomatic women. This review and modeling study aimed to investigate the current and potential predictive performance of genetic risk models. Methods: Genotypes and disease status were simulated for a population of 10,000 women. Genetic risk models were constructed from polymorphisms from meta-analysis including, in separate scenarios, all polymorphisms or statistically significant polymorphisms only. We additionally investigated the magnitude of the odds ratios (OR) for 1 to 100 hypothetical polymorphisms that would be needed to achieve similar discriminative accuracy as available prediction models [modeled range of area under the receiver operating characteristic curve (AUC) 0.70–0.80]. Results: Of the 96 polymorphisms that had been investigated in meta-analyses, 41 showed significant associations. AUC was 0.68 for the genetic risk model based on all 96 polymorphisms and 0.67 for the 41 significant polymorphisms. Addition of 50 additional variants, each with risk allele frequencies of 0.30, requires per-allele ORs of 1.2 to increase this AUC to 0.70, 1.3 to increase AUC to 0.75, and 1.5 to increase AUC to 0.80. To achieve AUC of 0.80, even 100 additional variants would need per-allele ORs of 1.3 to 1.7, depending on risk allele frequencies. Conclusion: The predictive ability of genetic risk models in breast cancer has the potential to become comparable to that of current breast cancer risk models. Impact: Risk prediction based on low susceptibility variants becomes a realistic tool in prevention of nonfamilial breast cancer. Cancer Epidemiol Biomarkers Prev; 20(1); 9–22. ©2011 AACR.</jats:p

Hypothesis/Commentary for This Article from Genome-Based Prediction of Breast Cancer Risk in the General Population: A Modeling Study Based on Meta-Analyses of Genetic Associations

Hypothesis/Commentary for This Article from Genome-Based Prediction of Breast Cancer Risk in the General Population: A Modeling Study Based on Meta-Analyses of Genetic Association

5-Lipoxygenase activating protein (ALOX5AP) gene variants associate with the presence of xanthomas in familial hypercholesterolemia

Background: Tendon xanthomas are characteristic for familial hypercholesterolemia (FH), and are associated with a higher risk of coronary heart disease (CHD). They often present with local inflammation. Inflammation may therefore be involved in their pathogenesis, as it is in the pathogenesis of CHD. A key role in the inflammatory pathway is played by the 5-lipoxygenase activating protein (ALOX5AP), which is known to influence the risk of CHD in FH. To test our hypothesis that ALOX5AP contributes to the development of xanthomas, we studied whether variants in the ALOX5AP gene influence the risk of xanthomas. Methods: We examined 945 patients with genetically confirmed heterozygous FH to determine whether they had tendon xanthomas. We genotyped seven polymorphisms in the ALOX5AP gene and constructed haplotypes of these polymorphisms. Results: The A allele of the rs9551963 polymorphism was associated with an increased risk of xanthomas (OR 1.52, 95% CI 1.11-2.07, p=0.01), while the A allele of rs17222842 was protective (OR 0.62, 95% Cl 0.43-0.90, p = 0.01). These two polymorphisms fully explained the risk estimates of all haplotypes. Individual haplotypes, however, were not significantly associated with xanthomas. Conclusion: Variants in the ALOX5AP gene are associated with the presence of xanthomas in FH patients. This result supports our hypothesis that inflammation is a pathogenetic factor of xanthomas. (C) 2009 Elsevier Ireland Ltd. All rights reserve

Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association studies

Cross-sectional genetic association studies can be analyzed using Cox proportional hazards models with age as time scale, if age at onset of disease is known for the cases and age at data collection is known for the controls. We assessed to what degree and under what conditions Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association analyses. Analyses were conducted in an empirical study on the association of 65 polymorphisms and risk of coronary heart disease among 2400 familial hypercholesterolemia patients, and in a simulation study that considered various combinations of sample size, genotype frequency, and strength of association between the genotype and coronary heart disease. We applied Cox proportional hazards models and logistic regression models, and compared effect estimates ( hazard ratios and odds ratios) and statistical power. In the empirical study, Cox proportional hazards models generally showed lower P-values for polymorphisms than logistic regression models. In the simulation study, Cox proportional hazards models had higher statistical power in all scenarios. Absolute differences in power did depend on the effect estimate, genotype frequency and sample size, and were most prominent for genotypes with minor effects. For example, when the genotype frequency was 30% in a sample with size n = 2000 individuals, the absolute differences were the largest for effect estimates between 1.1 and 1.5. In conclusion, Cox proportional hazards models can increase statistical power in cross-sectional genetic association studies, especially in the range of effect estimates that are expected for genetic associations in common disease