02679nas a2200337 4500008004100000022001400041245011500055210006900170260001600239520155800255100001601813700001901829700002001848700001901868700003101887700002201918700002501940700001701965700001701982700001901999700002102018700002702039700002002066700002202086700002202108700001902130700002002149700002102169710002002190856013102210 2022 eng d a1399-000400aCIBERER: Spanish National Network for Research on Rare Diseases: a highly productive collaborative initiative.0 aCIBERER Spanish National Network for Research on Rare Diseases a c2022 Jan 203 a
CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on Rare Diseases currently consists of 75 research groups belonging to universities, research centers and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical and cellular research of rare diseases. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this paper, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions towards the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to rare disease research. This article is protected by copyright. All rights reserved.
1 aLuque, Juan1 aMendes, Ingrid1 aGómez, Beatriz1 aMorte, Beatriz1 ade Heredia, Miguel, López1 aHerreras, Enrique1 aCorrochano, Virginia1 aBueren, Juan1 aGallano, Pia1 aArtuch, Rafael1 aFillat, Cristina1 aPérez-Jurado, Luis, A1 aMontoliu, Lluis1 aCarracedo, Ángel1 aMillán, José, M1 aWebb, Susan, M1 aPalau, Francesc1 aLapunzina, Pablo1 aCIBERER Network uhttps://www.clinbioinfosspa.es/content/ciberer-spanish-national-network-research-rare-diseases-highly-productive-collaborative08213nas a2202125 4500008004100000022001400041245005800055210005600113260001600169520175300185100001701938700002901955700002801984700002002012700002702032700002002059700003002079700003402109700002902143700002702172700003102199700002002230700002502250700002002275700002802295700002302323700002102346700001902367700002902386700002302415700001802438700002202456700002402478700002902502700002902531700002902560700002102589700002502610700002302635700001802658700002002676700002002696700002602716700002402742700001802766700002202784700002402806700003102830700002802861700001802889700002102907700003202928700002502960700003102985700003003016700002403046700001903070700003303089700002903122700002903151700003403180700002803214700002503242700002503267700003303292700003203325700002903357700003303386700002703419700003003446700002903476700002803505700002503533700002903558700002003587700002803607700002103635700002603656700002603682700003303708700002703741700002303768700003103791700001903822700002703841700002403868700002603892700002203918700002003940700002203960700002103982700002804003700002004031700002504051700002004076700002904096700002604125700003004151700001804181700002604199700002104225700002704246700002804273700003304301700003104334700002804365700002704393700001604420700002504436700002404461700002004485700002704505700003704532700002104569700002504590700002004615700002504635700002104660700001704681700002204698700002004720700002304740700003004763700002404793700001804817700002204835700001904857700002204876700002804898700001904926700001904945700001704964700002004981700002605001700001905027700002005046700002205066700001905088700003105107700002205138700002205160700002105182700001805203700002105221700002605242700002605268700003005294700002105324700002305345700002405368700002005392700002305412700001605435700002005451700003205471700002005503700001805523700002005541700001805561700001705579700002005596700001805616700001805634700001805652700001905670700002205689700002305711700003005734700001805764700002605782700002205808700002805830700001905858700002105877700002205898710002505920710002505945710002405970856009305994 2022 eng d a1460-208300aNovel genes and sex differences in COVID-19 severity.0 aNovel genes and sex differences in COVID19 severity c2022 Jun 163 aHere we describe the results of a genome-wide study conducted in 11 939 COVID-19 positive cases with an extensive clinical information that were recruited from 34 hospitals across Spain (SCOURGE consortium). In sex-disaggregated genome-wide association studies for COVID-19 hospitalization, genome-wide significance (p < 5x10-8) was crossed for variants in 3p21.31 and 21q22.11 loci only among males (p = 1.3x10-22 and p = 8.1x10-12, respectively), and for variants in 9q21.32 near TLE1 only among females (p = 4.4x10-8). In a second phase, results were combined with an independent Spanish cohort (1598 COVID-19 cases and 1068 population controls), revealing in the overall analysis two novel risk loci in 9p13.3 and 19q13.12, with fine-mapping prioritized variants functionally associated with AQP3 (p = 2.7x10-8) and ARHGAP33 (p = 1.3x10-8), respectively. The meta-analysis of both phases with four European studies stratified by sex from the Host Genetics Initiative confirmed the association of the 3p21.31 and 21q22.11 loci predominantly in males and replicated a recently reported variant in 11p13 (ELF5, p = 4.1x10-8). Six of the COVID-19 HGI discovered loci were replicated and an HGI-based genetic risk score predicted the severity strata in SCOURGE. We also found more SNP-heritability and larger heritability differences by age (<60 or ≥ 60 years) among males than among females. Parallel genome-wide screening of inbreeding depression in SCOURGE also showed an effect of homozygosity in COVID-19 hospitalization and severity and this effect was stronger among older males. In summary, new candidate genes for COVID-19 severity and evidence supporting genetic disparities among sexes are provided.
1 aCruz, Raquel1 ade Almeida, Silvia, Diz-1 aHeredia, Miguel, López1 aQuintela, Inés1 aCeballos, Francisco, C1 aPita, Guillermo1 aLorenzo-Salazar, José, M1 aGonzález-Montelongo, Rafaela1 aGago-Domínguez, Manuela1 aPorras, Marta, Sevilla1 aCastaño, Jair, Antonio Te1 aNevado, Julián1 aAguado, Jose, María1 aAguilar, Carlos1 aAguilera-Albesa, Sergio1 aAlmadana, Virginia1 aAlmoguera, Berta1 aAlvarez, Nuria1 aAndreu-Bernabeu, Álvaro1 aArana-Arri, Eunate1 aArango, Celso1 aArranz, María, J1 aArtiga, Maria-Jesus1 aBaptista-Rosas, Raúl, C1 aBarreda-Sánchez, María1 aBelhassen-Garcia, Moncef1 aBezerra, Joao, F1 aBezerra, Marcos, A C1 aBoix-Palop, Lucía1 aBrión, Maria1 aBrugada, Ramón1 aBustos, Matilde1 aCalderón, Enrique, J1 aCarbonell, Cristina1 aCastano, Luis1 aCastelao, Jose, E1 aConde-Vicente, Rosa1 aCordero-Lorenzana, Lourdes1 aCortes-Sanchez, Jose, L1 aCorton, Marta1 aDarnaude, Teresa1 aDe Martino-Rodríguez, Alba1 aCampo-Pérez, Victor1 aBustamante, Aranzazu, Diaz1 aDomínguez-Garrido, Elena1 aLuchessi, André, D1 aEirós, Rocío1 aSanabria, Gladys, Mercedes E1 aFariñas, María, Carmen1 aFernández-Robelo, Uxía1 aFernández-Rodríguez, Amanda1 aFernández-Villa, Tania1 aGil-Fournier, Belén1 aGómez-Arrue, Javier1 aÁlvarez, Beatriz, González1 aQuirós, Fernan, Gonzalez B1 aGonzález-Peñas, Javier1 aGutiérrez-Bautista, Juan, F1 aHerrero, María, José1 aHerrero-Gonzalez, Antonio1 aJimenez-Sousa, María, A1 aLattig, María, Claudia1 aBorja, Anabel, Liger1 aLopez-Rodriguez, Rosario1 aMancebo, Esther1 aMartín-López, Caridad1 aMartín, Vicente1 aMartinez-Nieto, Oscar1 aMartinez-Lopez, Iciar1 aMartinez-Resendez, Michel, F1 aMartinez-Perez, Ángel1 aMazzeu, Juliana, A1 aMacías, Eleuterio, Merayo1 aMinguez, Pablo1 aCuerda, Victor, Moreno1 aSilbiger, Vivian, N1 aOliveira, Silviene, F1 aOrtega-Paino, Eva1 aParellada, Mara1 aPaz-Artal, Estela1 aSantos, Ney, P C1 aPérez-Matute, Patricia1 aPerez, Patricia1 aPérez-Tomás, Elena1 aPerucho, Teresa1 aPinsach-Abuin, Mel, Lina1 aPompa-Mera, Ericka, N1 aPorras-Hurtado, Gloria, L1 aPujol, Aurora1 aLeón, Soraya, Ramiro1 aResino, Salvador1 aFernandes, Marianne, R1 aRodríguez-Ruiz, Emilio1 aRodriguez-Artalejo, Fernando1 aRodriguez-Garcia, José, A1 aRuiz-Cabello, Francisco1 aRuiz-Hornillos, Javier1 aRyan, Pablo1 aSoria, José, Manuel1 aSouto, Juan, Carlos1 aTamayo, Eduardo1 aTamayo-Velasco, Alvaro1 aTaracido-Fernandez, Juan, Carlos1 aTeper, Alejandro1 aTorres-Tobar, Lilian1 aUrioste, Miguel1 aValencia-Ramos, Juan1 aYáñez, Zuleima1 aZarate, Ruth1 aNakanishi, Tomoko1 aPigazzini, Sara1 aDegenhardt, Frauke1 aButler-Laporte, Guillaume1 aMaya-Miles, Douglas1 aBujanda, Luis1 aBouysran, Youssef1 aPalom, Adriana1 aEllinghaus, David1 aMartínez-Bueno, Manuel1 aRolker, Selina1 aAmitrano, Sara1 aRoade, Luisa1 aFava, Francesca1 aSpinner, Christoph, D1 aPrati, Daniele1 aBernardo, David1 aGarcía, Federico1 aDarcis, Gilles1 aFernández-Cadenas, Israel1 aHolter, Jan, Cato1 aBanales, Jesus, M1 aFrithiof, Robert1 aDuga, Stefano1 aAsselta, Rosanna1 aPereira, Alexandre, C1 aRomero-Gómez, Manuel1 aNafría-Jiménez, Beatriz1 aHov, Johannes, R1 aMigeotte, Isabelle1 aRenieri, Alessandra1 aPlanas, Anna, M1 aLudwig, Kerstin, U1 aButi, Maria1 aRahmouni, Souad1 aAlarcón-Riquelme, Marta, E1 aSchulte, Eva, C1 aFranke, Andre1 aKarlsen, Tom, H1 aValenti, Luca1 aZeberg, Hugo1 aRichards, Brent1 aGanna, Andrea1 aBoada, Mercè1 aRojas, Itziar1 aRuiz, Agustín1 aSánchez, Pascual1 aReal, Luis, Miguel1 aGuillén-Navarro, Encarna1 aAyuso, Carmen1 aGonzález-Neira, Anna1 aRiancho, José, A1 aRojas-Martinez, Augusto1 aFlores, Carlos1 aLapunzina, Pablo1 aCarracedo, Ángel1 aSCOURGE Cohort Group1 aHOSTAGE Cohort Group1 aGRA@CE Cohort Group uhttps://www.clinbioinfosspa.es/content/novel-genes-and-sex-differences-covid-19-severity03508nas a2200709 4500008004100000022001400041245008200055210006900137260001500206300001600221490000700237520139500244653001201639653002301651653001801674653002301692653001001715653001901725653002201744653002501766653001801791653001301809653001101822653001301833653002301846653001301869653001001882100002401892700001801916700002601934700002501960700002101985700002102006700002602027700002002053700002902073700002302102700002902125700002602154700002002180700002702200700002702227700001802254700001902272700003002291700001802321700003402339700001902373700002902392700002702421700001902448700002502467700001702492700002802509700002802537700001902565700002202584700001902606700002002625710004302645856011002688 2021 eng d a1362-496200aCSVS, a crowdsourcing database of the Spanish population genetic variability.0 aCSVS a crowdsourcing database of the Spanish population genetic c2021 01 08 aD1130-D11370 v493 aThe knowledge of the genetic variability of the local population is of utmost importance in personalized medicine and has been revealed as a critical factor for the discovery of new disease variants. Here, we present the Collaborative Spanish Variability Server (CSVS), which currently contains more than 2000 genomes and exomes of unrelated Spanish individuals. This database has been generated in a collaborative crowdsourcing effort collecting sequencing data produced by local genomic projects and for other purposes. Sequences have been grouped by ICD10 upper categories. A web interface allows querying the database removing one or more ICD10 categories. In this way, aggregated counts of allele frequencies of the pseudo-control Spanish population can be obtained for diseases belonging to the category removed. Interestingly, in addition to pseudo-control studies, some population studies can be made, as, for example, prevalence of pharmacogenomic variants, etc. In addition, this genomic data has been used to define the first Spanish Genome Reference Panel (SGRP1.0) for imputation. This is the first local repository of variability entirely produced by a crowdsourcing effort and constitutes an example for future initiatives to characterize local variability worldwide. CSVS is also part of the GA4GH Beacon network. CSVS can be accessed at: http://csvs.babelomics.org/.
10aAlleles10aChromosome Mapping10aCrowdsourcing10aDatabases, Genetic10aExome10aGene Frequency10aGenetic Variation10aGenetics, Population10aGenome, Human10aGenomics10aHumans10aInternet10aPrecision Medicine10aSoftware10aSpain1 aPeña-Chilet, Maria1 aRoldán, Gema1 aPerez-Florido, Javier1 aOrtuno, Francisco, M1 aCarmona, Rosario1 aAquino, Virginia1 aLópez-López, Daniel1 aLoucera, Carlos1 aFernandez-Rueda, Jose, L1 aGallego, Asunción1 aGarcia-Garcia, Francisco1 aGonzález-Neira, Anna1 aPita, Guillermo1 aNúñez-Torres, Rocío1 aSantoyo-López, Javier1 aAyuso, Carmen1 aMinguez, Pablo1 aAvila-Fernandez, Almudena1 aCorton, Marta1 aMoreno-Pelayo, Miguel, Ángel1 aMorin, Matías1 aGallego-Martinez, Alvaro1 aLopez-Escamez, Jose, A1 aBorrego, Salud1 aAntiňolo, Guillermo1 aAmigo, Jorge1 aSalgado-Garrido, Josefa1 aPasalodos-Sanchez, Sara1 aMorte, Beatriz1 aCarracedo, Ángel1 aAlonso, Ángel1 aDopazo, Joaquin1 aSpanish Exome Crowdsourcing Consortium uhttps://www.clinbioinfosspa.es/content/csvs-crowdsourcing-database-spanish-population-genetic-variability01585nas a2200505 4500008004100000245010600041210007100147260001600218300000800234490000700242100002700249700001900276700002000295700002800315700002900343700002700372700002800399700002500427700002000452700001700472700001900489700001900508700002000527700002100547700002900568700002600597700002700623700002200650700002700672700001800699700002200717700001500739700001800754700002100772700001900793700002100812700001800833700001800851700002400869700002200893700002100915710003200936710002400968856008700992 2021 eng d00aSchuurs–Hoeijmakers Syndrome (PACS1 Neurodevelopmental Disorder): Seven Novel Patients and a Review0 aSchuurs–Hoeijmakers Syndrome PACS1 Neurodevelopmental Disorder S cJan-05-2021 a7380 v121 aTenorio-Castaño, Jair1 aMorte, Beatriz1 aNevado, Julián1 aMartínez-Glez, Víctor1 aSantos-Simarro, Fernando1 aGarcía-Miñaur, Sixto1 aPalomares-Bralo, María1 aPacio-Míguez, Marta1 aGómez, Beatriz1 aArias, Pedro1 aAlcochea, Alba1 aCarrión, Juan1 aArias, Patricia1 aAlmoguera, Berta1 aLópez-Grondona, Fermina1 aLorda-Sanchez, Isabel1 aGalán-Gómez, Enrique1 aValenzuela, Irene1 aPerez, María, Méndez1 aCuscó, Ivón1 aBarros, Francisco1 aPié, Juan1 aRamos, Sergio1 aRamos, Feliciano1 aKuechler, Alma1 aTizzano, Eduardo1 aAyuso, Carmen1 aKaiser, Frank1 aPérez-Jurado, Luis1 aCarracedo, Ángel1 aLapunzina, Pablo1 aThe ENoD-CIBERER Consortium1 aThe SIDE Consortium uhttps://www.mdpi.com/2073-4425/12/5/738https://www.mdpi.com/2073-4425/12/5/738/pdf02426nas a2200325 4500008004100000022001400041245006600055210006400121260001300185300001000198490000700208520140200215653002501617653003401642653003701676653001101713653002201724653002101746653003601767653002301803100002101826700001701847700002001864700002201884700003201906700001901938700002201957700002101979856010002000 2016 eng d a2363-891500aProgress in pharmacogenetics: consortiums and new strategies.0 aProgress in pharmacogenetics consortiums and new strategies c2016 Mar a17-230 v313 aPharmacogenetics (PGx), as a field dedicated to achieving the goal of personalized medicine (PM), is devoted to the study of genes involved in inter-individual response to drugs. Due to its nature, PGx requires access to large samples; therefore, in order to progress, the formation of collaborative consortia seems to be crucial. Some examples of this collective effort are the European Society of Pharmacogenomics and personalized Therapy and the Ibero-American network of Pharmacogenetics. As an emerging field, one of the major challenges that PGx faces is translating their discoveries from research bench to bedside. The development of genomic high-throughput technologies is generating a revolution and offers the possibility of producing vast amounts of genome-wide single nucleotide polymorphisms for each patient. Moreover, there is a need of identifying and replicating associations of new biomarkers, and, in addition, a greater effort must be invested in developing regulatory organizations to accomplish a correct standardization. In this review, we outline the current progress in PGx using examples to highlight both the importance of polymorphisms and the research strategies for their detection. These concepts need to be applied together with a proper dissemination of knowledge to improve clinician and patient understanding, in a multidisciplinary team-based approach.
10aCooperative Behavior10aGenome-Wide Association Study10aHigh-Throughput Screening Assays10aHumans10aPatient Care Team10apharmacogenetics10aPolymorphism, Single Nucleotide10aPrecision Medicine1 aMaroñas, Olalla1 aLatorre, Ana1 aDopazo, Joaquin1 aPirmohamed, Munir1 aRodríguez-Antona, Cristina1 aSiest, Gérard1 aCarracedo, Ángel1 aLLerena, Adrián uhttps://www.clinbioinfosspa.es/content/progress-pharmacogenetics-consortiums-and-new-strategies02957nas a2200481 4500008004100000022001400041245013400055210006900189260001600258300001100274490000800285520141700293653002801710653002501738653001001763653001501773653001601788653002001804653002001824653003001844653001101874653000901885653001601894653004401910653001901954653001801973100002401991700002402015700002602039700002502065700002402090700002202114700001802136700002002154700002902174700002902203700001802232700002402250700002402274700002502298700002102323856013102344 2013 eng d a1873-349200aNovel genes detected by transcriptional profiling from whole-blood cells in patients with early onset of acute coronary syndrome.0 aNovel genes detected by transcriptional profiling from wholebloo c2013 Jun 05 a184-900 v4213 aBACKGROUND: Genome-wide expression analysis using microarrays has been used as a research strategy to discovery new biomarkers and candidate genes for a number of diseases. We aim to find new biomarkers for the prediction of acute coronary syndrome (ACS) with a differentially expressed mRNA profiling approach using whole genomic expression analysis in a peripheral blood cell model from patients with early ACS.
METHODS AND RESULTS: This study was carried out in two phases. On phase 1 a restricted clinical criteria (ACS-Ph1, n=9 and CG-Ph1, n=6) was used in order to select potential mRNA biomarkers candidates. A subsequent phase 2 study was performed using selected phase 1 markers analyzed by RT-qPCR using a larger and independent casuistic (ACS-Ph2, n=74 and CG-Ph2, n=41). A total of 549 genes were found to be differentially expressed in the first 48 h after the ACS-Ph1. Technical and biological validation further confirmed that ALOX15, AREG, BCL2A1, BCL2L1, CA1, COX7B, ECHDC3, IL18R1, IRS2, KCNE1, MMP9, MYL4 and TREML4, are differentially expressed in both phases of this study.
CONCLUSIONS: Transcriptomic analysis by microarray technology demonstrated differential expression during a 48 h time course suggesting a potential use of some of these genes as biomarkers for very early stages of ACS, as well as for monitoring early cardiac ischemic recovery.
10aAcute Coronary Syndrome10aAcute-Phase Proteins10aAdult10abiomarkers10aBlood Cells10aEarly Diagnosis10agene expression10aGene Expression Profiling10aHumans10aMale10aMiddle Aged10aOligonucleotide Array Sequence Analysis10aRNA, Messenger10aTranscriptome1 aSilbiger, Vivian, N1 aLuchessi, André, D1 aHirata, Rosário, D C1 aLima-Neto, Lídio, G1 aCavichioli, Débora1 aCarracedo, Ángel1 aBrión, Maria1 aDopazo, Joaquin1 aGarcia-Garcia, Francisco1 aSantos, Elizabete, S Dos1 aRamos, Rui, F1 aSampaio, Marcelo, F1 aArmaganijan, Dikran1 aSousa, Amanda, G M R1 aHirata, Mario, H uhttps://www.clinbioinfosspa.es/content/novel-genes-detected-transcriptional-profiling-whole-blood-cells-patients-early-onset-001640nas a2200289 4500008004100000022001400041245018800055210006900243260001600312520053300328100002400861700002400885700002600909700002500935700002400960700002200984700001801006700002101024700002901045700002901074700001801103700002401121700002401145700002501169700002101194856013501215 2013 eng d a1873-349200aNovel genes detected by transcriptional profiling from whole-blood cells in patients with early onset of acute coronary syndrome: Transcriptional profiling of acute coronary syndrome.0 aNovel genes detected by transcriptional profiling from wholebloo c2013 Mar 243 a{BACKGROUND: Genome-wide expression analysis using microarrays has been used as a research strategy to discovery new biomarkers and candidate genes for a number of diseases. We aim to find new biomarkers for the prediction of acute coronary syndrome (ACS) with a differentially expressed mRNA profiling approach using whole genomic expression analysis in a peripheral blood cell model from patients with early ACS. METHODS AND RESULTS: This study was carried out in two phases. On phase 1 a restricted clinical criteria (ACS-Ph11 aSilbiger, Vivian, N1 aLuchessi, André, D1 aHirata, Rosário, D C1 aLima-Neto, Lídio, G1 aCavichioli, Débora1 aCarracedo, Ángel1 aBrión, Maria1 aDopazo, Joaquín1 aGarcia-Garcia, Francisco1 aSantos, Elizabete, S Dos1 aRamos, Rui, F1 aSampaio, Marcelo, F1 aArmaganijan, Dikran1 aSousa, Amanda, G M R1 aHirata, Mario, H uhttps://www.clinbioinfosspa.es/content/novel-genes-detected-transcriptional-profiling-whole-blood-cells-patients-early-onset-acute00912nas a2200265 4500008004100000245010100041210006900142260000700211100002100218700002100239700002000260700002200280700001800302700002200320700002200342700002000364700002000384700001400404700001900418700001900437700001800456700002400474700001800498856013000516 2009 eng d00aPeripheral blood cells transcriptome to study new biomarkers for myocardial infarction follow up0 aPeripheral blood cells transcriptome to study new biomarkers for c061 aSilbiger, Vivian1 aLuchessi, André1 aHirata, Rosario1 aCarracedo, Ángel1 aBrión, Maria1 aNeto, Lidio, Lima1 aPastorelli, C, P.1 aDopazo, Joaquin1 aMontaner, David1 aGarcia, F1 aSampaio, M, P.1 aPereira, M, P.1 aSantos, E, S.1 aArmaganijan, Dikran1 aHirata, Mario uhttps://www.clinbioinfosspa.es/content/peripheral-blood-cells-transcriptome-study-new-biomarkers-myocardial-infarction-follow