Luis Rodriguez-Rodriguez

Bio: Luis Rodriguez-Rodriguez is an academic researcher from Hospital Clínico San Carlos. The author has contributed to research in topics: Single-nucleotide polymorphism & Rheumatoid arthritis. The author has an hindex of 25, co-authored 137 publications receiving 4483 citations. Previous affiliations of Luis Rodriguez-Rodriguez include Spanish National Research Council & Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico.

Genetics of rheumatoid arthritis contributes to biology and drug discovery

Abstract: A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis

Abstract: Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

A genetic study on C5-TRAF1 and progression of joint damage in rheumatoid arthritis

Abstract: The severity of joint damage progression in rheumatoid arthritis (RA) is heritable. Several genetic variants have been identified, but together explain only part of the total genetic effect. Variants in Interleukin-6 (IL-6), Interleukin-10 (IL-10), C5-TRAF1, and Fc-receptor-like-3 (FCRL3) have been described to associate with radiographic progression, but results of different studies were incongruent. We aimed to clarify associations of these variants with radiographic progression by evaluating six independent cohorts. In total 5,895 sets of radiographs of 2,493 RA-patients included in six different independent datasets from the Netherlands, Sweden, Spain and North-America were studied in relation to rs1800795 (IL-6), rs1800896 (IL-10), rs2900180 (C5-TRAF1) and rs7528684 (FCRL3). Associations were tested in the total RA-populations and in anti-citrullinated peptide antibodies (ACPA)-positive and ACPA-negative subgroups per cohort, followed by meta-analyses. Furthermore, the associated region C5-TRAF1 was fine-mapped in the ACPA-negative Dutch RA-patients. No associations were found for rs1800795 (IL-6), rs1800896 (IL-10) and rs7528684 (FCRL3) in the total RA-population and after stratification for ACPA. Rs2900180 in C5-TRAF1 was associated with radiographic progression in the ACPA-negative population (P-value meta-analysis = 5.85 × 10−7); the minor allele was associated with more radiographic progression. Fine-mapping revealed a region of 66Kb that was associated; the lowest P-value was for rs7021880 in TRAF1. The P-value for rs7021880 in meta-analysis was 6.35 × 10−8. Previous studies indicate that the region of rs7021880 was associated with RNA expression of TRAF1 and C5. Variants in IL-6, IL-10 and FCRL3 were not associated with radiographic progression. Rs2900180 in C5-TRAF1 and linked variants in a 66Kb region were associated with radiographic progression in ACPA-negative RA.

Risk factors for hospital admissions related to COVID-19 in patients with autoimmune inflammatory rheumatic diseases.

Abstract: Objectives To describe patients with autoimmune inflammatory rheumatic diseases (AIRD) who had COVID-19 disease; to compare patients who required hospital admission with those who did not and assess risk factors for hospital admission related to COVID-19. Methods An observational longitudinal study was conducted during the pandemic peak of severe acute respiratory syndrome coronavirus 2 (1 March 2020 to 24 April). All patients attended at the rheumatology outpatient clinic of a tertiary hospital in Madrid, Spain with a medical diagnosis of AIRD and with symptomatic COVID-19 were included. The main outcome was hospital admission related to COVID-19. The covariates were sociodemographic, clinical and treatments. We ran a multivariable logistic regression model to assess risk factors for the hospital admission. Results The study population included 123 patients with AIRD and COVID-19. Of these, 54 patients required hospital admission related to COVID-19. The mean age on admission was 69.7 (15.7) years, and the median time from onset of symptoms to hospital admission was 5 (3–10) days. The median length of stay was 9 (6–14) days. A total of 12 patients died (22%) during admission. Compared with outpatients, the factors independently associated with hospital admission were older age (OR: 1.08; p=0.00) and autoimmune systemic condition (vs chronic inflammatory arthritis) (OR: 3.55; p=0.01). No statistically significant findings for exposure to disease-modifying antirheumatic drugs were found in the final model. Conclusion Our results suggest that age and having a systemic autoimmune condition increased the risk of hospital admission, whereas disease-modifying antirheumatic drugs were not associated with hospital admission.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

10 Years of GWAS Discovery: Biology, Function, and Translation

Abstract: Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.

Five years of GWAS discovery

Abstract: The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section.

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.