Sara Marsal

Genetic Structure of Europeans: A View from the North–East

Using principal component (PC) analysis, we studied the genetic constitution of 3,112 individuals from Europe as portrayed by more than 270,000 single nucleotide polymorphisms (SNPs) genotyped with the Illumina Infinium platform. In cohorts where the sample size was >100, one hundred randomly chosen samples were used for analysis to minimize the sample size effect, resulting in a total of 1,564 samples. This analysis revealed that the genetic structure of the European population correlates closely with geography. The first two PCs highlight the genetic diversity corresponding to the northwest to southeast gradient and position the populations according to their approximate geographic origin. The resulting genetic map forms a triangular structure with a) Finland, b) the Baltic region, Poland and Western Russia, and c) Italy as its vertexes, and with d) Central- and Western Europe in its centre. Inter- and intra- population genetic differences were quantified by the inflation factor lambda (λ) (ranging from 1.00 to 4.21), fixation index (Fst) (ranging from 0.000 to 0.023), and by the number of markers exhibiting significant allele frequency differences in pair-wise population comparisons. The estimated lambda was used to assess the real diminishing impact to association statistics when two distinct populations are merged directly in an analysis. When the PC analysis was confined to the 1,019 Estonian individuals (0.1% of the Estonian population), a fine structure emerged that correlated with the geography of individual counties. With at least two cohorts available from several countries, genetic substructures were investigated in Czech, Finnish, German, Estonian and Italian populations. Together with previously published data, our results allow the creation of a comprehensive European genetic map that will greatly facilitate inter-population genetic studies including genome wide association studies (GWAS).

Analytical Methods in Untargeted Metabolomics: State of the Art in 2015

Metabolomics comprises the methods and techniques that are used to measure the small molecule composition of biofluids and tissues, and is actually one of the most rapidly evolving research fields. The determination of the metabolomic profile – the metabolome – has multiple applications in many biological sciences, including the developing of new diagnostic tools in medicine. Recent technological advances in nuclear magnetic resonance and mass spectrometry are significantly improving our capacity to obtain more data from each biological sample. Consequently, there is a need for fast and accurate statistical and bioinformatic tools that can deal with the complexity and volume of the data generated in metabolomic studies. In this review, we provide an update of the most commonly used analytical methods in metabolomics, starting from raw data processing and ending with pathway analysis and biomarker identification. Finally, the integration of metabolomic profiles with molecular data from other high-throughput biotechnologies is also reviewed.

Genome‐wide association study of rheumatoid arthritis in the Spanish population: KLF12 as a risk locus for rheumatoid arthritis susceptibility

OBJECTIVE To identify new genes associated with susceptibility to rheumatoid arthritis (RA), using a 2-stage genome-wide association study. METHODS Following a liability-based study design, we analyzed 317,503 single-nucleotide polymorphisms (SNPs) in 400 patients with RA and 400 control subjects. We selected a group of candidate SNPs for replication in an independent group of 410 patients with RA and 394 control subjects. Using data from the 3 previous genome-wide association studies in RA, we also looked for genomic regions showing evidence of common association signals. Finally, we analyzed the presence of genome-wide epistasis using the binary test implemented in the PLINK program. RESULTS We identified several genomic regions showing evidence of genome-wide association (P < 1 x 10(-5)). In the replication analysis, we identified KLF12 SNP rs1324913 as the most strongly associated SNP (P = 0.01). In our study, we observed that this SNP showed higher significance than PTPN22 SNP rs2476601, in both the genome-wide association studies and the replication analyses. Furthermore, the integration of our data with those from previous genome-wide association studies showed that KLF12 and PTPRT are the unique loci that are commonly associated in 3 different studies (P = 0.004 and P = 0.002 for KLF12 in the Wellcome Trust Case Control Consortium study and the Brigham and Womens Rheumatoid Arthritis Sequential Study genome-wide association study, respectively). The genome-wide epistasis analysis identified several SNP pairs close to significance after multiple test correction. CONCLUSION The present genome-wide association study identified KLF12 as a new susceptibility gene for RA. The joint analysis of our results and those from previous genome-wide association studies showed genomic regions with a higher probability of being genuine susceptibility loci for RA.

An Eight-Gene Blood Expression Profile Predicts the Response to Infliximab in Rheumatoid Arthritis

Background TNF alpha blockade agents like infliximab are actually the treatment of choice for those rheumatoid arthritis (RA) patients who fail standard therapy. However, a considerable percentage of anti-TNF alpha treated patients do not show a significant clinical response. Given that new therapies for treatment of RA have been recently approved, there is a pressing need to find a system that reliably predicts treatment response. We hypothesized that the analysis of whole blood gene expression profiles of RA patients could be used to build a robust predictor to infliximab therapy. Methods and Findings We performed microarray gene expression analysis on whole blood RNA samples from RA patients starting infliximab therapy (n = 44). The clinical response to infliximab was determined at week 14 using the EULAR criteria. Blood cell populations were determined using flow cytometry at baseline, week 2 and week 14 of treatment. Using complete cross-validation and repeated random sampling we identified a robust 8-gene predictor model (96.6% Leave One Out prediction accuracy, P = 0.0001). Applying this model to an independent validation set of RA patients, we estimated an 85.7% prediction accuracy (75–100%, 95% CI). In parallel, we also observed a significantly higher number of CD4+CD25+ cells (i.e. regulatory T cells) in the responder group compared to the non responder group at baseline (P = 0.0009). Conclusions The present 8-gene model obtained from whole blood expression efficiently predicts response to infliximab in RA patients. The application of the present system in the clinical setting could assist the clinician in the selection of the optimal treatment strategy in RA.

Actualización del Documento de Consenso de la Sociedad Española de Reumatología sobre el uso de terapias biológicas en la artritis reumatoide

OBJECTIVE To provide a reference to rheumatologists and to those involved in the treatment of RA who are using, or about to use biologic therapy. METHODS Recommendations were developed following a nominal group methodology and based on systematic reviews. The level of evidence and grade of recommendation were classified according to the model proposed by the Center for Evidence Based Medicine at Oxford. The level of agreement was established through Delphi technique. RESULTS We have produced recommendations on the use of the seven biologic agents available for RA in our country. The objective of treatment is to achieve the remission of the disease as quickly as possible. Indications and nuances regarding the use of biologic therapy were reviewed as well as the evaluation that should be performed prior to administration and the follow up of patients undergoing this therapy. CONCLUSIONS We present an update on the SER recommendations for the use of biologic therapy in patients with RA.

Clinical significance of synovial lymphoid neogenesis and its reversal after anti-tumour necrosis factor α therapy in rheumatoid arthritis

Objective: To investigate the clinical significance of lymphoid neogenesis (LN) in rheumatoid arthritis (RA), the clinicopathological correlates of this process and its evolution after anti-tumour necrosis factor (TNF)α therapy in a large series of synovial tissues were analysed. Methods: Arthroscopic synovial biopsies from 86 patients with RA were analysed by immunohistochemistry. LN was defined as the presence of large aggregates of lymphocytes with T/B cell compartmentalisation and peripheral node addressin (PNAd) positive high endothelial venules. Clinical variables at baseline and after prospective follow-up were compared in LN positive and negative RA subsets. The evolution of LN and its correlation with the clinical course in a subgroup of 24 patients that underwent a second arthroscopic biopsy after anti-TNFα therapy was also analysed. Results: LN was present in 49% of RA synovial tissues. Patients with LN had a significantly higher disease duration and a higher previous use of anti-TNFα agents. During prospective follow-up, the proportion of patients achieving good or moderate European League Against Rheumatism (EULAR) 28-joint Disease Activity Score (DAS28) responses was significantly lower in patients who were LN positive despite a significantly higher use of anti-TNFα agents. By multivariate logistic regression analysis, LN remained as an independent negative predictor of response to therapy. In the subgroup of patients rebiopsied after anti-TNFα therapy, reversal of LN features occurred in 56% of the patients and correlated with good clinical responses. Conclusions: Synovial LN in RA predicts a lower response to therapy. LN features can be reversed after a short period of anti-TNFα therapy in parallel to good clinical responses.

Clinical significance of synovial lymphoid neogenesis and its reversal after anti-TNF-α therapy in rheumatoid arthritis

Objective: To investigate the clinical significance of lymphoid neogenesis (LN) in rheumatoid arthritis (RA), the clinicopathological correlates of this process and its evolution after anti-tumour necrosis factor (TNF)α therapy in a large series of synovial tissues were analysed. Methods: Arthroscopic synovial biopsies from 86 patients with RA were analysed by immunohistochemistry. LN was defined as the presence of large aggregates of lymphocytes with T/B cell compartmentalisation and peripheral node addressin (PNAd) positive high endothelial venules. Clinical variables at baseline and after prospective follow-up were compared in LN positive and negative RA subsets. The evolution of LN and its correlation with the clinical course in a subgroup of 24 patients that underwent a second arthroscopic biopsy after anti-TNFα therapy was also analysed. Results: LN was present in 49% of RA synovial tissues. Patients with LN had a significantly higher disease duration and a higher previous use of anti-TNFα agents. During prospective follow-up, the proportion of patients achieving good or moderate European League Against Rheumatism (EULAR) 28-joint Disease Activity Score (DAS28) responses was significantly lower in patients who were LN positive despite a significantly higher use of anti-TNFα agents. By multivariate logistic regression analysis, LN remained as an independent negative predictor of response to therapy. In the subgroup of patients rebiopsied after anti-TNFα therapy, reversal of LN features occurred in 56% of the patients and correlated with good clinical responses. Conclusions: Synovial LN in RA predicts a lower response to therapy. LN features can be reversed after a short period of anti-TNFα therapy in parallel to good clinical responses.

GWAS replication study confirms the association of PDE3A–SLCO1C1 with anti-TNF therapy response in rheumatoid arthritis

AIM The present study was undertaken to replicate the association of candidate genes for anti-TNF response in rheumatoid arthritis. Candidate genes were selected from a recent genome-wide association study on anti-TNF response performed in a population from Denmark. MATERIALS & METHODS Genomic DNA was obtained from 315 Spanish rheumatoid arthritis patients having received an anti-TNF agent as their first biological therapy. SNPs from NR2FR2, MAP2K6, CBLN2 and PDE3A-SLCO1C1 candidate loci were genotyped. RESULTS The PDE3A-SLCO1C1 locus rs3794271 SNP showed a highly significant association with anti-TNF treatment response (p = 1.74 × 10⁻⁵). Combining the statistical evidence from the Spanish and Danish rheumatoid arthritis cohorts, the associated rs3794271 SNP reached a genome-wide significance level of association (p = 3.3 × 10⁻¹⁰). CONCLUSION The present findings establish the PDE3A-SLCO1C1 locus as a strong genetic marker of anti-TNF therapy response.

Genetic characterization of northeastern Italian population isolates in the context of broader European genetic diversity

Population genetic studies on European populations have highlighted Italy as one of genetically most diverse regions. This is possibly due to the country’s complex demographic history and large variability in terrain throughout the territory. This is the reason why Italy is enriched for population isolates, Sardinia being the best-known example. As the population isolates have a great potential in disease-causing genetic variants identification, we aimed to genetically characterize a region from northeastern Italy, which is known for isolated communities. Total of 1310 samples, collected from six geographically isolated villages, were genotyped at >145 000 single-nucleotide polymorphism positions. Newly genotyped data were analyzed jointly with the available genome-wide data sets of individuals of European descent, including several population isolates. Despite the linguistic differences and geographical isolation the village populations still show the greatest genetic similarity to other Italian samples. The genetic isolation and small effective population size of the village populations is manifested by higher levels of genomic homozygosity and elevated linkage disequilibrium. These estimates become even more striking when the detected substructure is taken into account. The observed level of genetic isolation in Friuli-Venezia Giulia region is more extreme according to several measures of isolation compared with Sardinians, French Basques and northern Finns, thus proving the status of an isolate.

Synovial fibroblast hyperplasia in rheumatoid arthritis: Clinicopathologic correlations and partial reversal by anti–tumor necrosis factor therapy

OBJECTIVE Synovial fibroblast (SF) hyperplasia contributes to the pathogenesis of rheumatoid arthritis (RA), but quantitative information on this process is scarce. This study was undertaken to evaluate the fibroblast-specific marker Hsp47 as a quantitative marker for SFs and to analyze its clinicopathologic correlates and evolution after anti-tumor necrosis factor α (anti-TNFα) therapy. METHODS Synovial biopsy samples were obtained from 48 patients with RA and 20 controls who were healthy or had osteoarthritis (OA). Twenty-five RA patients who had active disease at the time of biopsy underwent a second biopsy after anti-TNFα therapy. Immunolabeling for Hsp47, inflammatory cells, and vascular cell markers was performed. Hsp47-positive lining and sublining fractional areas were quantified, and their correlation with clinicopathologic variables was analyzed. RESULTS In normal and diseased synovial tissue, Hsp47 was specifically and uniformly expressed by lining, sublining, and perivascular fibroblasts. Lining SF area was significantly increased in both RA and late OA tissue compared to normal tissue. Sublining SF area was increased in RA tissue but not in late OA tissue compared to normal tissue. Lining SF area was positively correlated with macrophage density, Disease Activity Score in 28 joints, and RA disease duration. In contrast, sublining SF area was negatively correlated with RA disease duration and activity. A significant reduction in lining SF area but not sublining SF area was observed after anti-TNFα therapy. CONCLUSION Our findings indicate that Hsp47 is a reliable marker for quantifying SFs in human synovial tissue. Our data suggest that lining and sublining SFs undergo different dynamics during the course of the disease. Lining SF expansion parallels the activity and temporal progression of RA and can be partially reversed by anti-TNFα therapy.