Amadou Gaye

DataSHIELD: taking the analysis to the data, not the data to the analysis

Background: Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK’s proposed ‘care.data’ initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Methods: Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Results: Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. Conclusions: DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property—the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis.

Data harmonization and federated analysis of population-based studies: the BioSHaRE project

AbstractsBackgroundIndividual-level data pooling of large population-based studies across research centres in international research projects faces many hurdles. The BioSHaRE (Biobank Standardisation and Harmonisation for Research Excellence in the European Union) project aims to address these issues by building a collaborative group of investigators and developing tools for data harmonization, database integration and federated data analyses.MethodsEight population-based studies in six European countries were recruited to participate in the BioSHaRE project. Through workshops, teleconferences and electronic communications, participating investigators identified a set of 96 variables targeted for harmonization to answer research questions of interest. Using each study’s questionnaires, standard operating procedures, and data dictionaries, harmonization potential was assessed. Whenever harmonization was deemed possible, processing algorithms were developed and implemented in an open-source software infrastructure to transform study-specific data into the target (i.e. harmonized) format. Harmonized datasets located on server in each research centres across Europe were interconnected through a federated database system to perform statistical analysis.ResultsRetrospective harmonization led to the generation of common format variables for 73% of matches considered (96 targeted variables across 8 studies). Authenticated investigators can now perform complex statistical analyses of harmonized datasets stored on distributed servers without actually sharing individual-level data using the DataSHIELD method.ConclusionNew Internet-based networking technologies and database management systems are providing the means to support collaborative, multi-center research in an efficient and secure manner. The results from this pilot project show that, given a strong collaborative relationship between participating studies, it is possible to seamlessly co-analyse internationally harmonized research databases while allowing each study to retain full control over individual-level data. We encourage additional collaborative research networks in epidemiology, public health, and the social sciences to make use of the open source tools presented herein.

A rare variant in APOC3 is associated with plasma triglyceride and VLDL levels in Europeans

The analysis of rich catalogues of genetic variation from population-based sequencing provides an opportunity to screen for functional effects. Here we report a rare variant in APOC3 (rs138326449-A, minor allele frequency ~0.25% (UK)) associated with plasma triglyceride (TG) levels (−1.43 s.d. (s.e.=0.27 per minor allele (P-value=8.0 × 10−8)) discovered in 3,202 individuals with low read-depth, whole-genome sequence. We replicate this in 12,831 participants from five additional samples of Northern and Southern European origin (−1.0 s.d. (s.e.=0.173), P-value=7.32 × 10−9). This is consistent with an effect between 0.5 and 1.5 mmol l−1 dependent on population. We show that a single predicted splice donor variant is responsible for association signals and is independent of known common variants. Analyses suggest an independent relationship between rs138326449 and high-density lipoprotein (HDL) levels. This represents one of the first examples of a rare, large effect variant identified from whole-genome sequencing at a population scale.

Data Safe Havens in health research and healthcare.

Motivation: The data that put the ‘evidence’ into ‘evidence-based medicine’ are central to developments in public health, primary and hospital care. A fundamental challenge is to site such data in repositories that can easily be accessed under appropriate technical and governance controls which are effectively audited and are viewed as trustworthy by diverse stakeholders. This demands socio-technical solutions that may easily become enmeshed in protracted debate and controversy as they encounter the norms, values, expectations and concerns of diverse stakeholders. In this context, the development of what are called ‘Data Safe Havens’ has been crucial. Unfortunately, the origins and evolution of the term have led to a range of different definitions being assumed by different groups. There is, however, an intuitively meaningful interpretation that is often assumed by those who have not previously encountered the term: a repository in which useful but potentially sensitive data may be kept securely under governance and informatics systems that are fit-for-purpose and appropriately tailored to the nature of the data being maintained, and may be accessed and utilized by legitimate users undertaking work and research contributing to biomedicine, health and/or to ongoing development of healthcare systems. Results: This review explores a fundamental question: ‘what are the specific criteria that ought reasonably to be met by a data repository if it is to be seen as consistent with this interpretation and viewed as worthy of being accorded the status of ‘Data Safe Haven’ by key stakeholders’? We propose 12 such criteria. Contact: paul.burton@bristol.ac.uk

Ambient air pollution, traffic noise and adult asthma prevalence: a BioSHaRE approach

We investigated the effects of both ambient air pollution and traffic noise on adult asthma prevalence, using harmonised data from three European cohort studies established in 2006–2013 (HUNT3, Lifelines and UK Biobank). Residential exposures to ambient air pollution (particulate matter with aerodynamic diameter ≤10 µm (PM10) and nitrogen dioxide (NO2)) were estimated by a pan-European Land Use Regression model for 2007. Traffic noise for 2009 was modelled at home addresses by adapting a standardised noise assessment framework (CNOSSOS-EU). A cross-sectional analysis of 646 731 participants aged ≥20 years was undertaken using DataSHIELD to pool data for individual-level analysis via a “compute to the data” approach. Multivariate logistic regression models were fitted to assess the effects of each exposure on lifetime and current asthma prevalence. PM10 or NO2 higher by 10 µg·m−3 was associated with 12.8% (95% CI 9.5–16.3%) and 1.9% (95% CI 1.1–2.8%) higher lifetime asthma prevalence, respectively, independent of confounders. Effects were larger in those aged ≥50 years, ever-smokers and less educated. Noise exposure was not significantly associated with asthma prevalence. This study suggests that long-term ambient PM10 exposure is associated with asthma prevalence in western European adults. Traffic noise is not associated with asthma prevalence, but its potential to impact on asthma exacerbations needs further investigation. Long-term ambient PM10 exposure is associated with asthma prevalence in three European adult cohorts http://ow.ly/En4b3049S7X

Understanding the impact of pre-analytic variation in haematological and clinical chemistry analytes on the power of association studies

Background: Errors, introduced through poor assessment of physical measurement or because of inconsistent or inappropriate standard operating procedures for collecting, processing, storing or analysing haematological and biochemistry analytes, have a negative impact on the power of association studies using the collected data. A dataset from UK Biobank was used to evaluate the impact of pre-analytical variability on the power of association studies. Methods: First, we estimated the proportion of the variance in analyte concentration that may be attributed to delay in processing using variance component analysis. Then, we captured the proportion of heterogeneity between subjects that is due to variability in the rate of degradation of analytes, by fitting a mixed model. Finally, we evaluated the impact of delay in processing on the power of a nested case-control study using a power calculator that we developed and which takes into account uncertainty in outcome and explanatory variables measurements. Results: The results showed that (i) the majority of the analytes investigated in our analysis, were stable over a period of 36 h and (ii) some analytes were unstable and the resulting pre-analytical variation substantially decreased the power of the study, under the settings we investigated. Conclusions: It is important to specify a limited delay in processing for analytes that are very sensitive to delayed assay. If the rate of degradation of an analyte varies between individuals, any delay introduces a bias which increases with increasing delay. If pre-analytical variation occurring due to delays in sample processing is ignored, it affects adversely the power of the studies that use the data.

Road traffic noise, blood pressure and heart rate : Pooled analyses of harmonized data from 88,336 participants

INTRODUCTION Exposure to road traffic noise may increase blood pressure and heart rate. It is unclear to what extent exposure to air pollution may influence this relationship. We investigated associations between noise, blood pressure and heart rate, with harmonized data from three European cohorts, while taking into account exposure to air pollution. METHODS Road traffic noise exposure was assessed using a European noise model based on the Common Noise Assessment Methods in Europe framework (CNOSSOS-EU). Exposure to air pollution was estimated using a European-wide land use regression model. Blood pressure and heart rate were obtained by trained clinical professionals. Pooled cross-sectional analyses of harmonized data were conducted at the individual level and with random-effects meta-analyses. RESULTS We analyzed data from 88,336 participants, across the three participating cohorts (mean age 47.0 (±13.9) years). Each 10dB(A) increase in noise was associated with a 0.93 (95% CI 0.76;1.11) bpm increase in heart rate, but with a decrease in blood pressure of 0.01 (95% CI -0.24;0.23) mmHg for systolic and 0.38 (95% CI -0.53; -0.24) mmHg for diastolic blood pressure. Adjustments for PM10 or NO2 attenuated the associations, but remained significant for DBP and HR. Results for BP differed by cohort, with negative associations with noise in LifeLines, no significant associations in EPIC-Oxford, and positive associations with noise >60dB(A) in HUNT3. CONCLUSIONS Our study suggests that road traffic noise may be related to increased heart rate. No consistent evidence for a relation between noise and blood pressure was found.

DataSHIELD: An Ethically Robust Solution to Multiple-Site Individual-Level Data Analysis

Background: DataSHIELD (Data Aggregation Through Anonymous Summary-statistics from Harmonised Individual levEL Databases) has been proposed to facilitate the co-analysis of individual-level data from multiple studies without physically sharing the data. In a previous paper, we investigated whether DataSHIELD could protect participant confidentiality in accordance with UK law. In this follow-up paper, we investigate whether DataSHIELD addresses a broader range of ethics-related data-sharing concerns. Methods: Ethics-related data-sharing concerns of Institutional Review Boards, ethics experts, international research consortia and research participants were identified through a literature search and systematically examined at a multidisciplinary workshop to determine whether DataSHIELD proposes mechanisms which can address these concerns. Results: DataSHIELD addresses several ethics-related data-sharing concerns related to privacy, confidentiality, and the protection of the research participants rights while sharing data and after the data have been shared. The data remain entirely under the direct management of the study that collected them. Data processing commands are strictly supervised, and the data are queried in a protected environment. Issues related to the return of individual research results when data are shared are eliminated; the responsibility for return remains at the study of origin. Conclusion: DataSHIELD can provide an innovative and robust solution for addressing commonly encountered ethics-related data-sharing concerns.

Vitamin D Receptor Gene Polymorphisms Are Associated with Abdominal Visceral Adipose Tissue Volume and Serum Adipokine Concentrations but Not with Body Mass Index or Waist Circumference in African Americans: The Jackson Heart Study

BACKGROUND The biological actions of vitamin D are mediated through the vitamin D receptor (VDR). Single-nucleotide polymorphisms (SNPs) in the VDR gene have been previously associated with adiposity traits. However, to our knowledge, few studies have included direct measures of adiposity and adipokine concentrations. OBJECTIVE We examined the association of tagging SNPs in the VDR gene with multiple adiposity measures, including waist circumference (WC), body mass index (BMI), body fat percentage, subcutaneous and visceral adipose tissue (VAT) volume, and serum adipokine (adiponectin and leptin) concentrations in adult African Americans (AAs). METHODS Data from 3020 participants (61.9% women; mean age, 54.6 y) from the Jackson Heart Study were used for this analysis. Forty-five tag SNPs were chosen with the use of genotype data from the International HapMap project. We used linear regression to test the associations of imputed VDR SNPs with each of the traits, adjusted for age, sex, educational status, physical activity, smoking, alcohol intake, serum vitamin D concentration, European ancestry, and multiple testing. RESULTS The G allele of the SNP rs4328262 remained associated with increased VAT volume after multiple testing correction (β = 45.7; P < 0.001). The A allele of another SNP (rs11574070) was nominally associated with body fat percentage (β = 0.96; P = 0.002). None of the VDR SNPs analyzed showed any link with WC or BMI. The A allele of rs2228570 (β = 0.08; P = 0.001) for men and the T allele of rs2853563 (β = 0.04; P < 0.001) for women remained positively associated with serum adiponectin concentrations after multiple testing correction. CONCLUSION Although we did not find any association for anthropometric measures, we did observe associations of VDR variants with serum adipokines and with the more metabolically active fat, VAT. Therefore, our findings demonstrate a possible role of VDR variants in regulating adipose tissue activity and adiposity among AAs.

Perceived neighborhood problems are associated with shorter telomere length in African American women

OBJECTIVES African Americans (AA) experience higher levels of stress related to living in racially segregated and poor neighborhoods. However, little is known about the associations between perceived neighborhood environments and cellular aging among adult AA. This study examined whether perceived neighborhood environments were associated with telomere length (TL) in AA after adjustment for individual-level risk factors. METHODS The analysis included 158 women and 75 men AA aged 30-55 years from the Morehouse School of Medicine Study. Relative TL (T/S ratio) was measured from peripheral blood leukocytes using quantitative real-time polymerase chain reaction. Multivariable linear regression models were used to examine the associations of perceived neighborhood social cohesion, problems, and overall unfavorable perceptions with log-TL. RESULTS Women had significantly longer TL than men (0.59 vs. 0.54, p=0.012). After controlling for sociodemographic, and biomedical and psychosocial factors, a 1-SD increase in perceived neighborhood problems was associated with 7.3% shorter TL in women (Mean Difference [MD]=-0.073 (Standard Error=0.03), p=0.012). Overall unfavorable perception of neighborhood was also associated with 5.9% shorter TL among women (MD=-0.059(0.03), p=0.023). Better perceived social cohesion were associated with 2.4% longer TL, but did not reach statistical significance (MD=0.024(0.02), p=0.218). No association was observed between perceived neighborhood environments and TL in men. CONCLUSIONS Our findings suggest that perceived neighborhood environments may be predictive of cellular aging in AA women even after accounting for individual-level risk factors. Additional research with a larger sample is needed to determine whether perceived neighborhood environments are causally related to TL.