Case-only Design Research Articles

The Effects of Physical Activity and Omega 3 Fatty Acids on Glucose Levels and Neuropathy Symptoms in Hispanic Diabetics in the “En Balancé Plus” Study

BackgroundDiabetes is an important global public health burden. In the U.S., 8.3% of the population (i.e. 25.8 million individuals) have diabetes. Hispanic Americans have a higher prevalence of diabetes at 11.8% compared to non‐Hispanic whites. People with type‐2 diabetes often have developed an intolerance to insulin. For these individuals, healthy dieting and exercise, insulin therapy and proper medication will help to control and treat their diabetes. If not treated early, then diabetes affects many major organs, including the heart, blood vessels, nerves, eyes and kidneys. Controlling blood sugar levels can help prevent these complications. Aerobic and resistance exercise have been shown to be the most effective exercise regimen for diabetics to reduce neuropathy symptoms and lower glycemic levels, and slow down the damage to other organs. Omega 3 fatty acids have been shown to be effective in decreasing glucose levels as well. The purpose of this study was to assess the effects of physical activity and omega 3 fatty acid intake on the hemoglobin A1C levels and neuropathy symptoms in Hispanic diabetic patients.MethodsProspective three‐month study with 40 participants (male=16, female= 24). To evaluate the physical activity, participants were surveyed using the Arizona Physical Activity Frequency questionnaire at baseline and three months. The pain intensity of the participants was measured at baseline and three month using the short form of the McGill pain questionnaire which displayed a pain diagram. Both questionnaires were administered in Spanish. A 12‐hour fasting was required for the blood glucose concentration and lipid profiles which were analyzed. The fasting glucose levels and hemoglobin A1C levels were evaluated at the blood draw clinic and later analyzed at the Loma Linda University Medical Center. The participants attended a total of six nutritional and exercise classes conducted in Spanish for a total contact time of approximately 12 hours. The participants were followed up at 3 months. This case‐only design was funded by NIH and approved by the Loma Linda University Institutional Review Board (IRB).ResultsThere was a significant reduction in Hb A1C level (mean= −0.55%, p=0.01), neuropathy pain intensity (mean= −0.29%, p=0.004), glucose intake (mean=−20.67%, p=0.025), and LDL level (mean=−7.2%, p= 0.042), There was a significant reduction in triglyceride values (mean= −4.45%, P=0.06). Total met hours activities were also increase by 0.65%.ConclusionPhysical activity was associated with a decrease in A1C levels as well as a decrease in pain intensity and neuropathy symptoms. After the intervention, the glucose levels decreased and the reported neuropathy symptoms had lessened in severity according to the McGill's pain questionnaire. Physical Activity with the combination of omega 3 fatty acid pills could be associated with the decrease in neuropathy symptoms and glucose levels.Support or Funding InformationThis case‐only design was funded by NIH and approved by the Loma Linda University Institutional Review Board (IRB).This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

The interaction between cannabis use and the Val158Met polymorphism of the COMT gene in psychosis: A transdiagnostic meta - analysis.

BackgroundNeither environmental nor genetic factors are sufficient to predict the transdiagnostic expression of psychosis. Therefore, analysis of gene-environment interactions may be productive.ObjectiveA meta-analysis was performed using papers investigating the interaction between cannabis use and catechol-O-methyl transferase (COMT) polymorphism Val158Met (COMTVal158Met).Data sourcesPubMed, Embase, PsychInfo.Study eligibility criteriaAll observational studies assessing the interaction between COMTVal158Met and cannabis with any psychosis or psychotic symptoms measure as an outcome.Study appraisal and synthesis methodsA meta-analysis was performed using the Meta-analysis of Observational Studies in Epidemiology guidelines and forest plots were generated. Thirteen articles met the selection criteria: 7 clinical studies using a case-only design, 3 clinical studies with a dichotomous outcome, and 3 studies analysing a continuous outcome of psychotic symptoms below the threshold of psychotic disorder. The three study types were analysed separately. Validity of the included studies was assessed using "A Cochrane Risk of Bias Assessment Tool: for Non-Randomized Studies of Interventions".ResultsFor case-only studies, a significant interaction was found between cannabis use and COMTVal158Met, with an OR of 1.45 (95% Confidence Interval = 1.05–2.00; Met/Met as the risk genotype). However, there was no evidence for interaction in either the studies including dichotomous outcomes (B = -0.51, 95% Confidence Interval -1.72, 0.70) or the studies including continuous outcomes (B = -0.04 95% Confidence Interval -0.16–0.08).LimitationA substantial part of the included studies used the case-only design, which has lower validity and tends to overestimate true effects.ConclusionThe interaction term between cannabis use and COMTVal158Met was only statistically significant in the case-only studies, but not in studies using other clinical or non-clinical psychosis outcomes. Future additional high quality studies might change current perspectives, yet currently evidence for the interaction remains unconvincing.

Review of Statistical Methods for Gene-Environment Interaction Analysis

Complex diseases are caused by a combination of genetic and environmental factors, creating a challenge for understanding the disease mechanisms. Understanding the interplay between genes and environmental factors is important, as genes do not operate in isolation but rather in complex networks and pathways influenced by environmental factors. The advent of new technologies has made a massive amount of genetic data available, and various statistical methods have been developed to analyze genetic data and to identify interactions between genes and the environment, i.e., gene-environment (G-E) interactions. In this review article, we introduce various statistical methods for identifying G-E interactions using case-control designs. We review a range of disease risk models for modeling the joint effects of genetic and environmental factors such as multiplicative and additive models. We then introduce various inference methods under these disease risk models, which include a standard prospective likelihood, case-only designs, a retrospective likelihood that exploits a gene-environment independence assumption to boost power, and an empirical Bayes type approach that uses the independence assumption in a data-adaptive way. Several tests for detecting genetic associations in the presence of G-E interactions are also introduced, which include a joint test and a maximum score test that provides a unified approach by integrating a class of disease risk models to maximize over a class of score tests. There are several challenges of G-E interaction analysis that include replication issues. While more powerful statistical methods for detecting interactions are helpful, ultimately studies with larger sample sizes are needed to identify interactions through consortium-based studies to achieve adequate power for G-E analysis.

AdmixPower: Statistical Power and Sample Size Estimation for Mapping Genetic Loci in Admixed Populations.

Admixed populations result from recent admixture of two or more ancestral populations with divergent allele frequencies. The genome of each admixed individual is a mosaic of haplotypes inherited from the ancestral populations. Despite the substantial work to assess power and sample size requirements for association mapping in genetically homogeneous populations of European ancestry, power and sample size estimation methods for mapping genes in genetically heterogeneous admixed populations such as African Americans are lacking. Admixture mapping is a method that traces the ancestral origin of disease-susceptibility genetic loci in the admixed population. We developed AdmixPower, a freely available tool set based on the open-source R software, to perform power and sample size analysis for genetically heterogeneous admixed populations considering continuous or dichotomous outcomes with a case-only or case-control study design. AdmixPower can be used to compute the sample size required to achieve investigator-specified statistical power under several key parameters including ancestry odds ratio, genotype risk ratio, parental risk ratio, an underlying genetic risk model, trait type, and admixture model (hybrid-isolation or continuous gene flow model). We demonstrate that differences in the key parameters in the admixed population results in substantial differences in the sample size required to achieve adequate power in admixture mapping studies. Our tool provides a resource for researchers to develop a strategy to minimize cost and maximize the success of identifying disease-susceptibility loci in an admixed population. R code used in the sample size and power analysis is freely available from https://research.cchmc.org/mershalab/Tools.html.

Identification of Genetic Interaction with Risk Factors Using a Time-To-Event Model.

Background: Certain diseases can occur with and without a trigger. We use Venous Thromboembolism (VTE) as our example to identify genetic interaction with pregnancy in women with VTE during pre- or postpartum. Pregnancy is one of the major risk factors for VTE as it accounts for 10% of maternal deaths. Methods: We performed a whole genome association analysis using the Cox Proportional Hazard (CoxPH) model adjusted for covariates to identify genetic variants associated with the time-to-event of VTE related to pre- or postpartum during the childbearing age of 18–45 years using a case-only design in a cohort of women with VTE. Women with a VTE event after 45 years of age were censored and contributed only follow-up time. Results: We identified two intragenic single nucleotide polymorphisms (SNPs) at genome-wide significance in the PURB gene located on chromosome 7, and two additional intragenic SNPs, one in the LINGO2 gene on chromosome 9 and one in RDXP2 on chromosome X. Conclusions: We showed that the time-to-event model is a useful approach for identifying potential hazard-modification of the genetic variants when the event of interest (VTE) occurs due to a risk factor (pre- or post-partum).

Exposure enriched outcome dependent designs for longitudinal studies of gene-environment interaction.

Joint effects of genetic and environmental factors have been increasingly recognized in the development of many complex human diseases. Despite the popularity of case-control and case-only designs, longitudinal cohort studies that can capture time-varying outcome and exposure information have long been recommended for gene-environment (G×E) interactions. To date, literature on sampling designs for longitudinal studies of G×E interaction is quite limited. We therefore consider designs that can prioritize a subsample of the existing cohort for retrospective genotyping on the basis of currently available outcome, exposure, and covariate data. In this work, we propose stratified sampling based on summaries of individual exposures and outcome trajectories and develop a full conditional likelihood approach for estimation that adjusts for the biased sample. We compare the performance of our proposed design and analysis with combinations of different sampling designs and estimation approaches via simulation. We observe that the full conditional likelihood provides improved estimates for the G×E interaction and joint exposure effects over uncorrected complete-case analysis, and the exposure enriched outcome trajectory dependent design outperforms other designs in terms of estimation efficiency and power for detection of the G×E interaction. We also illustrate our design and analysis using data from the Normative Aging Study, an ongoing longitudinal cohort study initiated by the Veterans Administration in 1963. Copyright © 2017 John Wiley & Sons, Ltd.

A childhood acute lymphoblastic leukemia genome-wide association study identifies novel sex-specific risk variants.

Childhood acute lymphoblastic leukemia (ALL) occurs more frequently in males. Reasons behind sex differences in childhood ALL risk are unknown. In the present genome-wide association study (GWAS), we explored the genetic basis of sex differences by comparing genotype frequencies between male and female cases in a case-only study to assess effect-modification by sex.The case-only design included 236 incident cases of childhood ALL consecutively recruited at the Texas Children's Cancer Center in Houston, Texas from 2007 to 2012. All cases were non-Hispanic whites, aged 1 to 10 years, and diagnosed with confirmed B-cell precursor ALL. Genotyping was performed using the Illumina HumanCoreExome BeadChip on the Illumina Infinium platform. Besides the top 100 statistically most significant results, results were also analyzed by the top 100 highest effect size with a nominal statistical significance (P <0.05).The statistically most significant sex-specific association (P = 4 × 10) was with the single nucleotide polymorphism (SNP) rs4813720 (RASSF2), an expression quantitative trait locus (eQTL) for RASSF2 in peripheral blood. rs4813720 is also a strong methylation QTL (meQTL) for a CpG site (cg22485289) within RASSF2 in pregnancy, at birth, childhood, and adolescence. cg22485289 is one of the hypomethylated CpG sites in ALL compared with pre-B cells. Two missense SNPs, rs12722042 and 12722039, in the HLA-DQA1 gene yielded the highest effect sizes (odds ratio [OR] ∼ 14; P <0.01) for sex-specific results. The HLA-DQA1 SNPs belong to DQA1*01 and confirmed the previously reported male-specific association with DQA1*01. This finding supports the proposed infection-related etiology in childhood ALL risk for males. Further analyses revealed that most SNPs (either direct effect or through linkage disequilibrium) were within active enhancers or active promoter regions and had regulatory effects on gene expression levels.Cumulative data suggested that RASSF2 rs4813720, which correlates with increased RASSF2 expression, may counteract the suppressor effect of estrogen-regulated miR-17-92 on RASSF2 resulting in protection in males. Given the amount of sex hormone-related mechanisms suggested by our findings, future studies should examine prenatal or early postnatal programming by sex hormones when hormone levels show a large variation.

Implication of Socio-Demographics on Cognitive-Related Symptoms in Sports Concussion Among Children.

BackgroundSports-related concussion remains a public health challenge due to its morbidity and mortality. One of the consequences of concussion is cognitive impairment (CI) and cognitive-related symptoms (CRS) which determine, to some extent, physical and behavioral functioning of children who sustain concussion. Despite the high prevalence of CI and CRS associated with concussion, the risk factors are not fully understood. We aimed to characterize CRS and to examine its relationship with race, ethnicity, age, insurance, and sex in a pediatric population.MethodsA retrospective cohort (case-only) design was used to assess CRS prevalence and its relationship with race and sex using a pediatric hospital’s electronic medical records. A consecutive sample was used with 1429 cases between 2007 and 2014. Study characteristics were examined using chi-square and log binomial regression for hypothesis-specific testing.ResultsOf the 1429 cases, 872 (61.0 %) were boys and 557 (39.0 %) were girls. The racial distribution indicated 1146 (80.2 %) Whites, 170 (11.9 %) Blacks/African Americans, and 113 (7.9 %) others. The prevalence of CRS was 78.0 %. Whereas boys had sustained more concussions, girls were more likely to present with CRS; prevalence risk ratio = 1.07, 95 % CI 1.01–1.13, p = 0.02. The crude analysis indicated no racial disparities in CRS prevalence, but the multivariable analysis did, comparing White to Black/African American children; adjusted prevalence risk ratio (aPRR) = 1.77, 99 % CI 1.02–3.08, p = 0.008.ConclusionsRacial disparities exist in CRS among children with sports-related concussion, and Black/African American children are more likely, relative to Whites, to suffer CRS. Due to uncertainty in causal inference, we caution the interpretation and application of these data in risk-adapted concussion prevention.

In the Wrong Place with the Wrong SNP: The Association Between Stressful Neighborhoods and Cardiac Arrest Within Beta-2-adrenergic Receptor Variants.

Sudden cardiac arrest has been linked independently both to stressful neighborhood conditions and to polymorphisms in the ADRB2 gene. The ADRB2 gene mediates sympathetic activation in response to stress. Therefore, if neighborhood conditions cause cardiac arrest through the stress pathway, the ADRB2 variant may modify the association between neighborhood conditions, such as socioeconomic deprivation and incidence of cardiac arrest. The Cardiac Arrest Blood Study Repository is a population-based repository of specimens and other data from adult cardiac arrest patients residing in King County, Washington. Cases (n = 1,539) were 25- to 100-year-old individuals of European descent who experienced out-of-hospital cardiac arrest from 1988 to 2004. Interactions between neighborhood conditions and the ADRB2 genotype on cardiac arrest risk were assessed in a case-only study design. Gene-environment independence was assessed in blood samples obtained from King County residents initially contacted by random-digit dialing. Fewer than 4% of study subjects resided in socioeconomically deprived neighborhoods. Nonetheless, the case-only analysis indicated the presence of supramultiplicative interaction of socioeconomic deprivation and the homozygous Gln27Glu variant (case-only odds ratio: 1.8 [95% confidence interval: 1.0, 2.9]). Interactions between population density and the homozygous Gln27Glu variant were weaker (case-only odds ratio: 1.2 [95% confidence interval: 0.97, 1.5]). Findings support a supramultiplicative interaction between the Gln27Glu ADRB2 variant and socioeconomic deprivation among individuals of European descent. This result is consistent with the hypothesis that the elevation in cardiac arrest risk associated with socioeconomic deprivation operates through the stress pathway.

TwoPhaseInd: an R package for estimating gene-treatment interactions and discovering predictive markers in randomized clinical trials.

The R package TwoPhaseInd is available from http://cran.r-project.org/web/packages CONTACT: jdai@fredhutch.org.

Associations of Breast Cancer Risk Prediction Tools With Tumor Characteristics and Metastasis.

The association between established risk factors for breast cancer and subtypes or prognosis of the disease is not well known. We analyzed whether the Tyrer-Cuzick-predicted 10-year breast cancer risk score (TCRS), mammographic density (MD), and a 77-single nucleotide polymorphism polygenic risk score (PRS) were associated with breast cancer tumor prognosticators and risk of distant metastasis. We used a case-only design in a population-based cohort of 5,500 Swedish patients with breast cancer. Logistic and multinomial logistic regression of outcomes, estrogen receptor (ER) status, lymph node involvement, tumor size, and grade was performed with TCRS, PRS, and percent MD as exposures. Cox proportional hazard models were used to estimate hazard ratios (HRs) of distant metastasis. Women at high risk for breast cancer based on PRS and/or TCRS were significantly more likely to be diagnosed with favorable prognosticators, such as ER-positive and low-grade tumors. In contrast, PRS weighted on ER-negative disease was associated with ER-negative tumors. When stratifying by age, the associations of TCRS with favorable prognosticators were restricted to women younger than age 50. Women scoring high in both TCRS and PRS had a lower risk of distant metastasis (HR, 0.69; 95% CI, 0.49 to 0.98). MD was not associated with any of the examined prognosticators. Women at high risk for breast cancer based on genetic and lifestyle factors were significantly more likely to be diagnosed with breast cancers with a favorable prognosis. Better knowledge of subtype-specific risk factors could be vital for the success of prevention programs aimed at lowering mortality.

Moderate concordance was found between case-only and parallel group designs in systematic comparison

ObjectivesTo empirically evaluate the concordance of effect estimates between case-only and parallel group designs and to identify predictors of discrepancies. Study Design and SettingMEDLINE and EMBASE databases were searched through June 31, 2013. Studies that used both a case-only (case crossover or self-controlled case series) and a parallel group design (cohort or case–control) were identified. Spearman correlation coefficient was used to evaluate the concordance between designs. Z-scores were used to assess whether differences in the effect estimates were common, using an absolute threshold value of 1.96. A prediction model was built to identify predictors of discrepancies. ResultsThe search identified 1,367 articles of which 53 were included for analysis. In total, 519 comparisons were made. The correlation coefficient between case-only vs. parallel group studies was 0.64 (P < .001). In 221 of the 519 comparisons (43%), the difference between both study designs was larger than the predetermined threshold. The following predictors of discrepancy were found: intermittent exposure, rare event, acute outcome, length of hazard period, type of case-only design, and sample size (C statistic of 0.783). ConclusionThe concordance between effect estimates of case-only and parallel group designs is moderate. Such discrepancies could be predicted by failure to meet assumptions of case-only designs.

Augmented case-only designs for randomized clinical trials with failure time endpoints.

Under suitable assumptions and by exploiting the independence between inherited genetic susceptibility and treatment assignment, the case-only design yields efficient estimates for subgroup treatment effects and gene-treatment interaction in a Cox model. However it cannot provide estimates of the genetic main effect and baseline hazards, that are necessary to compute the absolute disease risk. For two-arm, placebo-controlled trials with rare failure time endpoints, we consider augmenting the case-only design with random samples of controls from both arms, as in the classical case-cohort sampling scheme, or with a random sample of controls from the active treatment arm only. The latter design is motivated by vaccine trials for cost-effective use of resources and specimens so that host genetics and vaccine-induced immune responses can be studied simultaneously in a bigger set of participants. We show that these designs can identify all parameters in a Cox model and that the efficient case-only estimator can be incorporated in a two-step plug-in procedure. Results in simulations and a data example suggest that incorporating case-only estimators in the classical case-cohort design improves the precision of all estimated parameters; sampling controls only in the active treatment arm attains a similar level of efficiency.

Allowing for population stratification in case-only studies of gene-environment interaction, using genomic control.

Gene-environment interactions (G × E) have attracted considerable research interest in the past owing to their scientific and public health implications, but powerful statistical methods are required to successfully track down G × E, particularly at a genome-wide level. Previously, a case-only (CO) design has been proposed as a means to identify G × E with greater efficiency than traditional case-control or cohort studies. However, as with genotype-phenotype association studies themselves, hidden population stratification (PS) can impact the validity of G × E studies using a CO design. Since this problem has been subject to little research to date, we used comprehensive simulation to systematically assess the type I error rate, power and effect size bias of CO studies of G × E in the presence of PS. Three types of PS were considered, namely genetic-only (PSG), environment-only (PSE), and joint genetic and environmental stratification (PSGE). Our results reveal that the type I error rate of an unadjusted Wald test, appropriate for the CO design, would be close to its nominal level (0.05 in our study) as long as PS involves only one interaction partner (i.e., either PSG or PSE). In contrast, if the study population is stratified with respect to both G and E (i.e., if there is PSGE), then the type I error rate is seriously inflated and estimates of the underlying G × E interaction are biased. Comparison of CO to a family-based case-parents design confirmed that the latter is more robust against PSGE, as expected. However, case-parent trios may be particularly unsuitable for G × E studies in view of the fact that they require genotype data from parents and that many diseases with an environmental component are likely to be of late onset. An alternative approach to adjusting for PS is principal component analysis (PCA), which has been widely used for this very purpose in past genome-wide association studies (GWAS). However, resolving genetic PS properly by PCA requires genetic data at the population level, the availability of which would conflict with the basic idea of the CO design. Therefore, we explored three modified Wald test statistics, inspired by the genomic control (GC) approach to GWAS, as an alternative means to allow for PSGE. The modified statistics were benchmarked against a stratified Wald test assuming known population affiliation, which should provide maximum power under PS. Our results confirm that GC is capable of successfully and efficiently correcting the PS-induced inflation of the type I error rate in CO studies of G × E.

The role of genetic variants in CRP in radiographic severity in African Americans with early and established rheumatoid arthritis.

This study investigates the association of CRP (C-reactive protein) single-nucleotide polymorphisms (SNPs) with plasma CRP levels and radiographic severity in African Americans with early and established rheumatoid arthritis (RA). Using a cross-sectional case-only design, CRP SNPs were genotyped in two independent sets of African Americans with RA: Consortium for the Longitudinal Evaluation of African Americans with RA (CLEAR 1) and CLEAR 2. Radiographic data and CRP measurements were available for 294 individuals from CLEAR 1 (median (interquartile range (IQR) 25-75) disease duration of 1 (0.6-1.6) year) and in 407 persons from CLEAR 2 (median (IQR 25-75) disease duration of 8.9 (3.5-17.7) years). In CLEAR 1, in adjusted models, the minor allele of rs2808630 was associated with total radiographic score (incident rate ratio 0.37 (95% confidence interval (CI) 0.19-0.74), P-value=0.0051). In CLEAR 2, the minor allele of rs3093062 was associated with increased plasma CRP levels (P-value=0.002). For each rs3093062 minor allele, the plasma CRP increased by 1.51 (95% CI 1.15-1.95) mg dl(-1) when all the other covariates remained constant. These findings have important implications for assessment of the risk of joint damage in African Americans with RA.

Do case-only designs yield consistent results across design and different databases? A case study of hip fractures and benzodiazepines.

BackgroundThe case‐crossover (CXO) and self‐controlled case series (SCCS) designs are increasingly used in pharmacoepidemiology. In both, relative risk estimates are obtained within persons, implicitly controlling for time‐fixed confounding variables.ObjectivesTo examine the consistency of relative risk estimates of hip/femur fractures (HFF) associated with the use of benzodiazepines (BZD) across case‐only designs in two databases (DBs), when a common protocol was applied.MethodsCXO and SCCS studies were conducted in BIFAP (Spain) and CPRD (UK). Exposure to BZD was divided into non‐use, current, recent and past use. For CXO, odds ratios (OR; 95%CI) of current use versus non‐use/past were estimated using conditional logistic regression adjusted for co‐medications (AOR). For the SCCS, conditional Poisson regression was used to estimate incidence rate ratios (IRR; 95%CI) of current use versus non/past‐use, adjusted for age. To investigate possible event‐exposure dependence the relative risk in the 30 days prior to first BZD exposure was also evaluated.ResultsIn the CXO current use of BZD was associated with an increased risk of HFF in both DBs, AORBIFAP = 1.47 (1.29–1.67) and AORCPRD = 1.55 (1.41–1.70). In the SCCS, IRRs for current exposure was 0.79 (0.72–0.86) in BIFAP and 1.21 (1.13–1.30) in CPRD. However, when we considered separately the 30‐day pre‐exposure period, the IRR for current period was 1.43 (1.31–1.57) in BIFAP and 1.37 (1.27–1.47) in CPRD.ConclusionsCXO designs yielded consistent results across DBs, while initial SCCS analyses did not. Accounting for event‐exposure dependence, estimates derived from SCCS were more consistent across DBs and designs. © 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.

Red blood cell transfusion, hyperkalemia, and heart failure in advanced chronic kidney disease.

In recent years, the use of red blood cell (RBC) transfusion for the treatment of chronic kidney disease (CKD)-related anemia has increased. We used the OptumInsight medical claims database to study the association between receiving a transfusion and hyperkalemia and heart failure events. Persons 18-64 years of age with diagnosed stage 4 or 5 CKD (not requiring dialysis) between 2006 and 2010 were followed until their first hospitalization or emergency room visit with a diagnosis of hyperkalemia or heart failure, termination of insurance coverage, or death. We used a case-only design and conditional logistic regression to estimate rate ratios (RR) and 95% confidence intervals (CIs) describing associations between RBC transfusion and the risks of hyperkalemia or heart failure. We used single (1:1) and variable (1:m) self-control matching intervals, with adjustment for time-varying confounders. Seven thousand eight hundred twenty-nine individuals met our inclusion criteria; two-thirds were age 50 years or older; 43% were women and 51% had diabetes. Rates of hyperkalemia and heart failure were 7.9/100 person-years (95%CI: 7.3, 8.5) and 16.3/100 person-years (95%CI: 15.5, 17.2), respectively. RBC transfusion was associated with an increased risk of both hyperkalemia (single interval matched RR = 12.0, 95%CI: 1.3, 109; multiple interval matched RR = 6.1, 95%CI: 2.5, 15.1) and heart failure (single interval matched RR = 1.7, 95%CI: 0.3, 9.2; multiple interval matched RR = 3.8, 95%CI: 1.4, 10.3). In patients with advanced CKD, RBC transfusion appears to be associated with an elevated risk of hyperkalemia and heart failure; further investigation into these risks is warranted.

Injury prevention by medication among children with attention-deficit/hyperactivity disorder: a case-only study.

Children and adolescents with attention-deficit/hyperactivity disorder (ADHD) have an increased risk of injuries. Attention-deficit/hyperactivity disorder is often treated with medication, but the evidence regarding prevention of injuries is inconclusive. To determine via a case-only design whether the use of methylphenidate hydrochloride or atomoxetine hydrochloride reduces the risk of injuries among children and adolescents with ADHD. We used the German Pharmacoepidemiological Research Database, which includes records from about 17 million insurees (approximately 20% of the population) from 4 statutory health insurance providers in Germany to identify children aged 3 to 17 years with new diagnoses of ADHD in 2005 and 2006. We identified 37,650 children with ADHD based on inpatient and outpatientdiagnostic codes (F90.0, F90.1, and F90.9) from the German modification of the International Statistical Classification of Diseases and Related Health Problems, 10th Revision. Among them, we identified those with an inpatient injury diagnosis during follow-up until 2009. A total of 2128 children with any injury diagnosis at hospitalization, 821 of whom had a brain injury diagnosis, were included in the analysis. We applied the self-controlled case series design to control for time-invariant characteristics of the patients and time trends in the exposure. Treatment with methylphenidate or atomoxetine based on prescription data. Hospitalization because of any injury or brain injury according to the injury mortality diagnosis matrix. Incidence rate ratios for the periods with medication compared with nonmedicated periods were 0.87 (95% CI, 0.74-1.02) for hospitalization with any injuries and 0.66 (95% CI, 0.48-0.91) for brain injuries only in the full sample. These estimates remained stable in sensitivity analyses restricting the sample to a narrower age range or to patients with a single hospitalization. There was no indication that medication prescriptions are increased after hospitalizations. No significant risk reduction for hospitalizations with injury diagnoses was observed during periods of ADHD medication, but there was a preventive effect on the risk of brain injuries (34% risk reduction). The effects were controlled for time-invariant characteristics of the patients by the study design.

ARID5B, IKZF1 and non-genetic factors in the etiology of childhood acute lymphoblastic leukemia: the ESCALE study.

Genome-wide association studies (GWAS) have identified that frequent polymorphisms in ARID5B and IKZF1, two genes involved in lymphoid differentiation, increase the risk of childhood acute lymphoblastic leukemia (ALL). These findings markedly modified the current field of research on the etiology of ALL. In this new context, the present exploratory study investigated the possible interactions between these at-risk alleles and the non-genetic suspected ALL risk factors that were of sufficient prevalence in the French ESCALE study: maternal use of home insecticides during pregnancy, preconception paternal smoking, and some proxies for early immune modulation, i.e. breastfeeding, history of common infections before age one year, and birth order. The analyses were based on 434 ALL cases and 442 controls of European origin, drawn from the nationwide population-based case-control study ESCALE. Information on non-genetic factors was obtained by standardized telephone interview. Interactions between rs10740055 in ARID5B or rs4132601 in IKZF1 and each of the suspected non-genetic factors were tested, with the SNPs coded as counts of minor alleles (trend variable). Statistical interactions were observed between rs4132601 and maternal insecticide use (p = 0.012), breastfeeding p = 0.017) and repeated early common infections (p = 0.0070), with allelic odds ratios (OR) which were only increased among the children not exposed to insecticides (OR = 1.8, 95%CI: 1.3, 2.4), those who had been breastfed (OR = 1.8, 95%CI: 1.3, 2.5) and those who had had repeated early common infections (OR = 2.4, 95%CI: 1.5, 3.8). The allelic ORs were close to one among children exposed to insecticides, who had not been breastfed and who had had no or few common infections. Repeated early common infections interacted with rs10740055 (p = 0.018) in the case-only design. Further studies are needed to evaluate whether these observations of a modification of the effect of the at-risk alleles by non-genetic factors are chance findings or reflect true underlying mechanisms.

Breast cancer genetic risk profile is differentially associated with interval and screen-detected breast cancers

Polygenic risk profiles computed from multiple common susceptibility alleles for breast cancer have been shown to identify women at different levels of breast cancer risk. We evaluated whether this genetic risk stratification can also be applied to discriminate between screen-detected and interval cancers, which are usually associated with clinicopathological and survival differences. A 77 single-nucleotide polymorphism polygenic risk score (PRS) was constructed for breast cancer overall and by estrogen receptor (ER) status. PRS was inspected as a continuous (per standard deviation increment) variable in a case-only design. Modification of the PRS by mammographic density was evaluated by fitting an additional interaction term. PRS weighted by breast cancer overall estimates was found to be differentially associated with 1865 screen-detected and 782 interval cancers in the LIBRO-1 study {age-adjusted odds ratio (OR)perSD [95% confidence interval (CI)] 0.91 [0.83-0.99], P = 0.023}. The association was found to be more significant for PRS weighted by ER-positive breast cancer estimates [ORperSD = 0.90 (0.82-0.98), P = 0.011]. This result was corroborated by two independent studies [combined ORperSD = 0.87 (0.76-1.00), P = 0.058] with no evidence of heterogeneity. When enriched for 'true' interval cancers among nondense breasts, the difference in the association with PRS in screen-detected and interval cancers became more pronounced [ORperSD = 0.74 (0.62-0.89), P = 0.001], with a significant interaction effect between PRS and mammographic density (Pinteraction = 0.017). To our knowledge, this is the first report looking into the genetic differences between screen-detected and interval cancers. It is an affirmation that the two types of breast cancer may have unique underlying biology.