Luisa Foco

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.

Overexpression of blood microRNAs 103a, 30b, and 29a in l-dopa–treated patients with PD

Objective: The aims of the present study were to profile the expression of several candidate microRNAs (miRNAs) in blood from l-dopa-treated and drug-naive patients with Parkinson disease (PD) vs unaffected controls and to interpret the miRNA expression data in a biological context. Methods: We analyzed RNAs from peripheral blood of 36 l-dopa–treated, 10 drug-naive patients with PD and unaffected controls matched 1:1 by sex and age. We evaluated expression by reverse transcription–quantitative real-time PCR, and we analyzed data using a 2-tailed paired t test. To detect miRNA targets, several miRNA resources were combined to generate an overall score for each candidate gene using weighted rank aggregation. Results: Significant overexpression of miR-103a-3p (p < 0.0001), miR-30b-5p (p = 0.002), and miR-29a-3p (p = 0.005) in treated patients with PD was observed, and promising candidate target genes for these were revealed by an integrated in silico analysis. Conclusions: We revealed 3 candidate biomarkers for PD. miRNAs 30b-5p and 29a-3p replicated a documented deregulation in PD albeit opposite to published data, while for miR-103a-3p, we demonstrated for the first time an overexpression in treated patients with PD. Expression studies in patients and/or in isolated peripheral blood mononuclear cells before and after l-dopa administration are necessary to define the involvement of l-dopa treatment in the observed overexpression. Our in silico analysis to prioritize targets of deregulated miRNAs identified candidate target genes, including genes related to neurodegeneration and PD. Despite the preliminary character of our study, the results provide a rationale for further clarifying the role of the identified miRNAs in the pathogenesis of PD and for validating their diagnostic potential.

Identification of a set of endogenous reference genes for miRNA expression studies in Parkinson’s disease blood samples

BackgroundResearch on microRNAs (miRNAs) is becoming an increasingly attractive field, as these small RNA molecules are involved in several physiological functions and diseases. To date, only few studies have assessed the expression of blood miRNAs related to Parkinson’s disease (PD) using microarray and quantitative real-time PCR (qRT-PCR). Measuring miRNA expression involves normalization of qRT-PCR data using endogenous reference genes for calibration, but their choice remains a delicate problem with serious impact on the resulting expression levels. The aim of the present study was to evaluate the suitability of a set of commonly used small RNAs as normalizers and to identify which of these miRNAs might be considered reliable reference genes in qRT-PCR expression analyses on PD blood samples.ResultsCommonly used reference genes snoRNA RNU24, snRNA RNU6B, snoRNA Z30 and miR-103a-3p were selected from the literature. We then analyzed the effect of using these genes as reference, alone or in any possible combination, on the measured expression levels of the target genes miR-30b-5p and miR-29a-3p, which have been previously reported to be deregulated in PD blood samples.ConclusionsWe identified RNU24 and Z30 as a reliable and stable pair of reference genes in PD blood samples.

Serum iron level and kidney function: a Mendelian randomization study.

Background: Iron depletion is a known consequence of chronic kidney disease (CKD), but there is contradicting epidemiological evidence on whether iron itself affects kidney function and whether its effect is protective or detrimental in the general population. While epidemiological studies tend to be affected by confounding and reverse causation, Mendelian randomization (MR) can provide unconfounded estimates of causal effects by using genes as instruments. Methods: We performed an MR study of the effect of serum iron levels on estimated glomerular filtration rate (eGFR), using genetic variants known to be associated with iron. MR estimates of the effect of iron on eGFR were derived based on the association of each variant with iron and eGFR from two large genome‐wide meta‐analyses on 48 978 and 74 354 individuals. We performed a similar MR analysis for ferritin, which measures iron stored in the body, using variants associated with ferritin. Results: A combined MR estimate across all variants showed a 1.3% increase in eGFR per standard deviation increase in iron (95% confidence interval 0.4‐2.1%; P = 0.004). The results for ferritin were consistent with those for iron. Secondary MR analyses of the effects of iron and ferritin on CKD did not show significant associations but had very low statistical power. Conclusions: Our study suggests a protective effect of iron on kidney function in the general population. Further research is required to confirm this causal association, investigate it in study populations at higher risk of CKD and explore its underlying mechanism of action.

Plasma and White Blood Cells Show Different miRNA Expression Profiles in Parkinson’s Disease

Parkinson’s disease (PD) diagnosis is based on the assessment of motor symptoms, which manifest when more than 50% of dopaminergic neurons are degenerated. To date, no validated biomarkers are available for the diagnosis of PD. The aims of the present study are to evaluate whether plasma and white blood cells (WBCs) are interchangeable biomarker sources and to identify circulating plasma-based microRNA (miRNA) biomarkers for an early detection of PD. We profiled plasma miRNA levels in 99 l-dopa-treated PD patients from two independent data collections, in ten drug-naïve PD patients, and in unaffected controls matched by sex and age. We evaluated expression levels by reverse transcription and quantitative real-time PCR (RT-qPCR) and combined the results from treated PD patients using a fixed effect inverse-variance weighted meta-analysis. We revealed different expression profiles comparing plasma and WBCs and drug-naïve and l-dopa-treated PD patients. We observed an upregulation trend for miR-30a-5p in l-dopa-treated PD patients and investigated candidate target genes by integrated in silico analyses. We could not analyse miR-29b-3p, normally expressed in WBCs, due to the very low expression in plasma. We observed different expression profiles in WBCs and plasma, suggesting that they are both suitable but not interchangeable peripheral sources for biomarkers. We revealed miR-30a-5p as a potential biomarker for PD in plasma. In silico analyses suggest that miR-30a-5p might have a regulatory role in mitochondrial dynamics and autophagy. Further investigations are needed to confirm miR-30a-5p deregulation and targets and to investigate the influence of l-dopa treatment on miRNA expression levels.

Sequential recruitment of study participants may inflate genetic heritability estimates

After the success of genome-wide association studies to uncover complex trait loci, attempts to explain the remaining genetic heritability (h2) are mainly focused on unraveling rare variant associations and gene–gene or gene–environment interactions. Little attention is paid to the possibility that h2 estimates are inflated as a consequence of the epidemiological study design. We studied the time series of 54 biochemical traits in 4373 individuals from the Cooperative Health Research In South Tyrol (CHRIS) study, a pedigree-based study enrolling ten participants/day over several years, with close relatives preferentially invited within the same day. We observed distributional changes of measured traits over time. We hypothesized that the combination of such changes with the pedigree structure might generate a shared-environment component with consequent h2 inflation. We performed variance components (VC) h2 estimation for all traits after accounting for the enrollment period in a linear mixed model (two-stage approach). Accounting for the enrollment period caused a median h2 reduction of 4%. For 9 traits, the reduction was of >20%. Results were confirmed by a Bayesian Markov chain Monte Carlo analysis with all VCs included at the same time (one-stage approach). The electrolytes were the traits most affected by the enrollment period. The h2 inflation was independent of the h2 magnitude, laboratory protocol changes, and length of the enrollment period. The enrollment process may induce shared-environment effects even under very stringent and standardized operating procedures, causing h2 inflation. Including the day of participation as a random effect is a sensitive way to avoid overestimation.

Investigating multiple sclerosis genetic susceptibility on the founder population of east-central Sardinia via association and linkage analysis of immune-related loci

Background: A wealth of single-nucleotide polymorphisms (SNPs) responsible for multiple sclerosis (MS) susceptibility have been identified; however, they explain only a fraction of MS heritability. Objectives: We contributed to discovery of new MS susceptibility SNPs by studying a founder population with high MS prevalence. Methods: We analyzed ImmunoChip data from 15 multiplex families and 94 unrelated controls from the Nuoro Province, Sardinia, Italy. We tested each SNP for both association and linkage with MS, the linkage being explored in terms of identity-by-descent (IBD) sharing excess and using gene dropping to compute a corresponding empirical p-value. By targeting regions that are both associated and in linkage with MS, we increase chances of identifying interesting genomic regions. Results: We identified 486 MS-associated (p < 1 × 10–4) and 18,426 MS-linked (p < 0.05) SNPs. A total of 111 loci were both linked and associated with MS, 18 of them pointing to 14 non-major histocompatibility complex (MHC) genes, and 93 of them located in the MHC region. Conclusion: We discovered new suggestive signals and confirmed some previously identified ones. We believe this to represent a significant step toward an understanding of the genetic basis of MS.