Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

In the published version of this paper, the name of author Emanuele Di Angelantonio was misspelled. This error has now been corrected in the HTML and PDF versions of the article.

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

Large-Scale Analysis of Determinants, Stability, and Heritability of High-Density Lipoprotein Cholesterol Efflux Capacity.

OBJECTIVE: Cholesterol efflux capacity (CEC) has emerged as a biomarker of coronary artery disease risk beyond plasma high-density lipoprotein (HDL) cholesterol (HDL-C) level. However, the determinants of CEC are incompletely characterized. We undertook a large-scale family-based population study to identify clinical, biochemical, and HDL particle parameter determinants of CEC, characterize reasons for the discordancy with HDL-C, quantify its heritability, and assess its stability over 10 to 12 years. APPROACHES AND RESULTS: CEC was quantified in 1988 individuals from the GRAPHIC (Genetic Regulation of Arterial Pressure of Humans in the Community) cohort, comprising individuals from 2 generations from 520 white nuclear families. Serum lipid and lipoprotein levels were determined by ultracentrifugation or nuclear magnetic resonance and HDL particle size and number quantified by nuclear magnetic resonance. Ninety unrelated individuals had repeat CEC measurements in samples collected after 10 to 12 years. CEC was positively correlated with HDL-C (R=0.62; P<0.0001). Among clinical and biochemical parameters, age, systolic blood pressure, alcohol consumption, serum albumin, triglycerides, phospholipids, and lipoprotein(a) were independently associated with CEC. Among HDL particle parameters, HDL particle number, particle size, and apolipoprotein A-II level were independently associated with CEC. Serum triglyceride level partially explained discordancy between CEC and HDL-C. CEC measurements in samples collected 10 to 12 years apart were strongly correlated (r=0.73; P<0.0001). Heritability of CEC was 0.31 (P=3.89×10-14) without adjustment for HDL-C and 0.13 (P=1.44×10-3) with adjustment. CONCLUSIONS: CEC is a stable trait over time, is influenced by specific clinical, serum, and HDL particle parameters factors beyond HDL-C, can be maintained in persons with a low plasma HDL-C by elevated serum triglyceride level, and is modestly independently heritable.

Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease.

BACKGROUND: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. OBJECTIVES: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci. METHODS: In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs. RESULTS: We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 × 10-4 with a range of other diseases/traits. CONCLUSIONS: We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk.

Rare and low-frequency coding variants alter human adult height.

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension.

High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to 192,763 individuals and used ∼155,063 samples for independent replication. We identified 30 new blood pressure- or hypertension-associated genetic regions in the general population, including 3 rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5 mm Hg/allele) than common variants. Multiple rare nonsense and missense variant associations were found in A2ML1, and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention.

Analysis with the exome array identifies multiple new independent variants in lipid loci.

It has been hypothesized that low frequency (1-5% minor allele frequency (MAF)) and rare (<1% MAF) variants with large effect sizes may contribute to the missing heritability in complex traits. Here, we report an association analysis of lipid traits (total cholesterol, LDL-cholesterol, HDL-cholesterol triglycerides) in up to 27 312 individuals with a comprehensive set of low frequency coding variants (ExomeChip), combined with conditional analysis in the known lipid loci. No new locus reached genome-wide significance. However, we found a new lead variant in 26 known lipid association regions of which 16 were >1000-fold more significant than the previous sentinel variant and not in close LD (six had MAF <5%). Furthermore, conditional analysis revealed multiple independent signals (ranging from 1 to 5) in a third of the 98 lipid loci tested, including rare variants. Addition of our novel associations resulted in between 1.5- and 2.5-fold increase in the proportion of heritability explained for the different lipid traits. Our findings suggest that rare coding variants contribute to the genetic architecture of lipid traits.

Three-dimensional dominant frequency mapping using autoregressive spectral analysis of atrial electrograms of patients in persistent atrial fibrillation.

BACKGROUND: Areas with high frequency activity within the atrium are thought to be 'drivers' of the rhythm in patients with atrial fibrillation (AF) and ablation of these areas seems to be an effective therapy in eliminating DF gradient and restoring sinus rhythm. Clinical groups have applied the traditional FFT-based approach to generate the three-dimensional dominant frequency (3D DF) maps during electrophysiology (EP) procedures but literature is restricted on using alternative spectral estimation techniques that can have a better frequency resolution that FFT-based spectral estimation. METHODS: Autoregressive (AR) model-based spectral estimation techniques, with emphasis on selection of appropriate sampling rate and AR model order, were implemented to generate high-density 3D DF maps of atrial electrograms (AEGs) in persistent atrial fibrillation (persAF). For each patient, 2048 simultaneous AEGs were recorded for 20.478 s-long segments in the left atrium (LA) and exported for analysis, together with their anatomical locations. After the DFs were identified using AR-based spectral estimation, they were colour coded to produce sequential 3D DF maps. These maps were systematically compared with maps found using the Fourier-based approach. RESULTS: 3D DF maps can be obtained using AR-based spectral estimation after AEGs downsampling (DS) and the resulting maps are very similar to those obtained using FFT-based spectral estimation (mean 90.23 %). There were no significant differences between AR techniques (p = 0.62). The processing time for AR-based approach was considerably shorter (from 5.44 to 5.05 s) when lower sampling frequencies and model order values were used. Higher levels of DS presented higher rates of DF agreement (sampling frequency of 37.5 Hz). CONCLUSION: We have demonstrated the feasibility of using AR spectral estimation methods for producing 3D DF maps and characterised their differences to the maps produced using the FFT technique, offering an alternative approach for 3D DF computation in human persAF studies.

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.).

RIPOSTE: a framework for improving the design and analysis of laboratory-based research.

Lack of reproducibility is an ongoing problem in some areas of the biomedical sciences. Poor experimental design and a failure to engage with experienced statisticians at key stages in the design and analysis of experiments are two factors that contribute to this problem. The RIPOSTE (Reducing IrreProducibility in labOratory STudiEs) framework has been developed to support early and regular discussions between scientists and statisticians in order to improve the design, conduct and analysis of laboratory studies and, therefore, to reduce irreproducibility. This framework is intended for use during the early stages of a research project, when specific questions or hypotheses are proposed. The essential points within the framework are explained and illustrated using three examples (a medical equipment test, a macrophage study and a gene expression study). Sound study design minimises the possibility of bias being introduced into experiments and leads to higher quality research with more reproducible results.

Intertechnique agreement and interstudy reproducibility of strain and diastolic strain rate at 1.5 and 3 Tesla: a comparison of feature-tracking and tagging in patients with aortic stenosis.

PURPOSE: To determine the interstudy reproducibility of myocardial strain and peak early-diastolic strain rate (PEDSR) measurement on cardiovascular magnetic resonance imaging (MRI) assessed with feature tracking (FT) and tagging, in patients with aortic stenosis (AS). MATERIALS AND METHODS: Cardiac MRI was performed twice (1-14 days apart) in 18 patients (8 at 1.5 Tesla [T], 10 at 3T) with moderate-severe AS. Circumferential peak systolic strain (PSS) and PEDSR were measured in all patients. Longitudinal PSS and PEDSR were assessed using FT in all patients, and tagging in the 3T sub-group. RESULTS: PSS was higher with FT than tagging (21.0 ± 1.9% versus 17.0 ± 3.4% at 1.5T, 21.4 ± 4.0% versus 17.7 ± 3.0% at 3T, P < 0.05), as was PEDSR (1.3 ± 0.3 s(-1) versus 1.0 ± 0.3 s(-1) , P = 0.10 at 1.5T and 1.3 ± 0.4 s(-1) versus 0.8 ± 0.3 s(-1) , P < 0.05 at 3T). The reproducibility of PSS was excellent with FT (coefficient of variation [CoV] 9-10%) and good with tagging at 1.5T (13-19%). Reproducibility of circumferential PEDSR was best at 1.5T when only basal/mid slices were included (CoV 12%), but moderate to poor at 3T (29-35%). Reproducibility of longitudinal strain was good with FT (10-16%) but moderate for PEDSR (∼30%). CONCLUSION: In patients with AS, FT consistently produces higher values compared with tagging. The interstudy reproducibility of PSS is excellent with FT and good with tagging. The reproducibility of circumferential PEDSR at 1.5T is good when only basal and mid slices are used.

Two further blood pressure loci identified in ion channel genes with a gene-centric approach.

BACKGROUND: Blood pressure (BP) is highly heritable, but our understanding of the genetic causes underlying variations in BP is incomplete. In this study, we explored whether novel loci associated with BP could be identified using a genecentric approach in 3 community-based cohorts with accurate BP measurements. METHODS AND RESULTS: Genotyping of 1857 single nucleotide polymorphisms (SNPs) in 91 ion channel genes was performed in a discovery cohort (n=358). Thirty-four SNPs associated with BP traits (P≤0.01) were followed up in an independent population (n=387); significant SNPs from this analysis were looked up in another independent population (n=1010) and meta-analyzed. Repeated clinic and ambulatory measurements were available for all but the discovery cohort (clinic only). Association analyses were performed, with systolic, diastolic, and pulse pressures as quantitative traits, adjusting for age and sex. Quantile-quantile plots indicated that the genecentric approach resulted in an inflation of association signals. Of the 29 SNPs taken forward from the discovery cohort, 2 SNPs were associated with BP phenotypes with the same direction of effect, with experiment-wide significance, in follow-up cohort I. These were rs2228291, in the chloride channel gene CLCN2, and rs10513488, in the potassium channel gene KCNAB1. Both associations were subsequently replicated in follow-up cohort II. CONCLUSIONS: Using a genecentric design and 3 well-phenotyped populations, this study identified 2 previously unreported, biologically plausible, genetic associations with BP. These results suggest that dense genotyping of genes, in pathways known to influence BP, could add to candidate-gene and Genome Wide Association studies in further explaining BP heritability.

Loss-of-function mutations in APOC3, triglycerides, and coronary disease.

BACKGROUND: Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype. METHODS: We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons. RESULTS: An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10(-6)). CONCLUSIONS: Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).

Prevalence and extent of infarct and microvascular obstruction following different reperfusion therapies in ST-elevation myocardial infarction.

BACKGROUND: Microvascular obstruction (MVO) describes suboptimal tissue perfusion despite restoration of infarct-related artery flow. There are scarce data on Infarct Size (IS) and MVO in relation to the mode and timing of reperfusion. We sought to characterise the prevalence and extent of microvascular injury and IS using Cardiovascular magnetic resonance (CMR), in relation to the mode of reperfusion following acute ST-Elevation Myocardial Infarction (STEMI). METHODS: CMR infarct characteristics were measured in 94 STEMI patients (age 61.0 ± 13.1 years) at 1.5 T. Seventy-three received reperfusion therapy: primary percutaneous coronary-intervention (PPCI, n = 47); thrombolysis (n = 12); rescue PCI (R-PCI, n = 8), late PCI (n = 6). Twenty-one patients presented late (>12 hours) and did not receive reperfusion therapy. RESULTS: IS was smaller in PPCI (19.8 ± 13.2% of LV mass) and thrombolysis (15.2 ± 10.1%) groups compared to patients in the late PCI (40.0 ± 15.6%) and R-PCI (34.2 ± 18.9%) groups, p <0.001. The prevalence of MVO was similar across all groups and was seen at least as frequently in the non-reperfused group (15/21, [76%] v 33/59, [56%], p = 0.21) and to a similar magnitude (1.3 (0.0-2.8) v 0.4 [0.0-2.9]% LV mass, p = 0.36) compared to patients receiving early reperfusion therapy. In the 73 reperfused patients, time to reperfusion, ischaemia area at risk and TIMI grade post-PCI were the strongest independent predictors of IS and MVO. CONCLUSIONS: In patients with acute STEMI, CMR-measured MVO is not exclusive to reperfusion therapy and is primarily related to ischaemic time. This finding has important implications for clinical trials that use CMR to assess the efficacy of therapies to reduce reperfusion injury in STEMI.

High rates of non-adherence to antihypertensive treatment revealed by high-performance liquid chromatography-tandem mass spectrometry (HP LC-MS/MS) urine analysis.

OBJECTIVES: Non-adherence to therapy is an important cause of suboptimal blood pressure control but few practical tools exist to accurately and routinely detect it. We used a simple urine-based assay to evaluate the prevalence of antihypertensive treatment non-adherence and its impact on blood pressure in a specialist hypertension centre. METHODS: 208 hypertensive patients (125 new referrals, 66 follow-up patients with inadequate blood pressure control and 17 renal denervation referrals) underwent assessment of antihypertensive drug intake using high-performance liquid chromatography-tandem mass spectrometry (HP LC-MS/MS) urine analysis at the time of clinical appointment. A total of 40 most commonly prescribed antihypertensive medications (or their metabolites) were screened for in spot urine samples. RESULTS: Overall, 25% of patients were totally or partially non-adherent to antihypertensive treatment (total non-adherence 10.1%, partial non-adherence 14.9%). The highest prevalence of partial and total non-adherence was among follow-up patients with inadequate blood pressure control (28.8%) and those referred for consideration of renal denervation (23.5%), respectively. There was a linear relationship between blood pressure and the numerical difference in detected/prescribed antihypertensive medications-every unit increase in this difference was associated with 3.0 (1.1) mm Hg, 3.1 (0.7) mm Hg and 1.9 (0.7) mm Hg increase in adjusted clinic systolic blood pressure, clinic diastolic blood pressure (DBP) and 24 h mean daytime DBP (p=0.0051, p=8.62 × 10(-6), p=0.0057), respectively. CONCLUSIONS: Non-adherence to blood pressure lowering therapy is common, particularly in patients with suboptimal blood pressure control and those referred for renal denervation. HP LC-MS/MS urine analysis could be used to exclude non-adherence and better stratify further investigations and intervention.

Participant identification in genetic association studies: improved methods and practical implications.

BACKGROUND: In a recent paper by Homer et al. (Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet 2008;4:e1000167), a method for detecting whether a given individual is a contributor to a particular genomic mixture was proposed. This prompted grave concern about the public dissemination of aggregate statistics from genome-wide association studies. It is of clear scientific importance that such data be shared widely, but the confidentiality of study participants must not be compromised. The issue of what summary genomic data can safely be posted on the web is only addressed satisfactorily when the theoretical underpinnings of the proposed method are clarified and its performance evaluated in terms of dependence on underlying assumptions. METHODS: The original method raised a number of concerns and several alternatives have since been proposed, including a simple linear regression approach. In our proposed generalized estimating equation approach, we maintain the simplicity of the linear regression model but obtain inferences that are more robust to approximation of the variance/covariance structure and can accommodate linkage disequilibrium. RESULTS: We affirm that, in principle, it is possible to determine that a 'candidate' individual has participated in a study, given a subset of aggregate statistics from that study. However, the methods depend critically on a number of key factors including: the ancestry of participants in the study; the absolute and relative numbers of cases and controls; and the number of single nucleotide polymorphisms. CONCLUSIONS: Simple guidelines for publication that are based on a single criterion are therefore unlikely to suffice. In particular, 'directed' summary statistics should not be posted openly on the web but could be protected by an internet-based access check as proposed by the P3G_Consortium et al. (Public access to genome-wide data: five views on balancing research with privacy and protection. PLoS Genet 2009;5:e1000665).

Pharmacogenetic interactions and their potential effects on genetic analyses of blood pressure.

BACKGROUND: In observational studies, analyses of blood pressure (BP) typically require some correction for the use of antihypertensive medications by study participants. Different approaches to correcting for treatment have been compared, but the impact of pharmacogenetic interactions that influence the efficacy of antihypertensive treatments on estimates of genetic main effects has not been considered. This work demonstrates the potential influence of pharmacogenetic interactions in genetic analyses of BP. METHODS: A simulation study is conducted to test the influence of pharmacogenetic interactions on approaches to the analysis of BP. Results from three plausible scenarios are presented. RESULTS: Informative BP approaches (Fixed Treatment Effect, Non-parametric adjustment, Censored Normal Regression) perform well when there is no pharmacogenetic interaction, but yield biased estimates of the main effects of particular genetic variants when pharmacogenetic interactions exist. Substitution approaches (Binary Trait, Fixed Substitution, Random Substitution, Median Method) are unaffected by pharmacogenetic interactions, but consistently perform sub-optimally. CONCLUSIONS: We recommend that the Informative BP approaches remain the most appropriate methods to use in practice, but stress that caution is required in the interpretation of their results-especially when an interaction between treatment and a genetic variant of interest is suspected. We make some suggestions as to how to check for possible interactions and confirm the results from genetic analyses of BP, but warn that these should be reviewed when data on real pharmacogenetic interactions become available.

DataSHIELD: resolving a conflict in contemporary bioscience--performing a pooled analysis of individual-level data without sharing the data.

BACKGROUND: Contemporary bioscience sometimes demands vast sample sizes and there is often then no choice but to synthesize data across several studies and to undertake an appropriate pooled analysis. This same need is also faced in health-services and socio-economic research. When a pooled analysis is required, analytic efficiency and flexibility are often best served by combining the individual-level data from all sources and analysing them as a single large data set. But ethico-legal constraints, including the wording of consent forms and privacy legislation, often prohibit or discourage the sharing of individual-level data, particularly across national or other jurisdictional boundaries. This leads to a fundamental conflict in competing public goods: individual-level analysis is desirable from a scientific perspective, but is prevented by ethico-legal considerations that are entirely valid. METHODS: Data aggregation through anonymous summary-statistics from harmonized individual-level databases (DataSHIELD), provides a simple approach to analysing pooled data that circumvents this conflict. This is achieved via parallelized analysis and modern distributed computing and, in one key setting, takes advantage of the properties of the updating algorithm for generalized linear models (GLMs). RESULTS: The conceptual use of DataSHIELD is illustrated in two different settings. CONCLUSIONS: As the study of the aetiological architecture of chronic diseases advances to encompass more complex causal pathways-e.g. to include the joint effects of genes, lifestyle and environment-sample size requirements will increase further and the analysis of pooled individual-level data will become ever more important. An aim of this conceptual article is to encourage others to address the challenges and opportunities that DataSHIELD presents, and to explore potential extensions, for example to its use when different data sources hold different data on the same individuals.