@article {818, title = {A genomic strategy for precision medicine in rare diseases: integrating customized algorithms into clinical practice.}, journal = {J Transl Med}, volume = {23}, year = {2025}, month = {2025 Jan 20}, pages = {86}, abstract = {

BACKGROUND: Despite the use of Next-Generation Sequencing (NGS) as the gold standard for the diagnosis of rare diseases, its clinical implementation has been challenging, limiting the cost-effectiveness of NGS and the understanding, control and safety essential for decision-making in clinical applications. Here, we describe a personalized NGS-based strategy integrating precision medicine into a public healthcare system and its implementation in the routine diagnosis process during a five-year pilot program.

METHODS: Our approach involved customized probe designs, the generation of virtual panels and the development of a personalized medicine module (PMM) for variant prioritization. This strategy was applied to 6500 individuals including 6267 index patients and 233 NGS-based carrier screenings.

RESULTS: Causative variants were identified in 2061 index patients (average 32.9\%, ranging from 12 to 62\% by condition). Also, 131 autosomal-recessive cases could be partially genetically diagnosed. These results led to over 5000 additional studies including carrier, prenatal and preimplantational tests or pharmacological and gene therapy treatments.

CONCLUSION: This strategy has shown promising improvements in the diagnostic rate, facilitating timely diagnosis and gradually expanding our services portfolio for rare diseases. The steps taken towards the integration of clinical and genomic data are opening new possibilities for conducting both retrospective and prospective healthcare studies. Overall, this study represents a major milestone in the ongoing efforts to improve our understanding and clinical management of rare diseases, a crucial area of medical research and care.

}, keywords = {Algorithms, Female, Genomics, High-Throughput Nucleotide Sequencing, Humans, Precision Medicine, rare diseases}, issn = {1479-5876}, doi = {10.1186/s12967-025-06069-2}, author = {M{\'e}ndez-Vidal, Cristina and Bravo-Gil, Nereida and Perez-Florido, Javier and Marcos-Luque, Irene and Fern{\'a}ndez, Raquel M and Fernandez-Rueda, Jose Luis and Gonz{\'a}lez-del Pozo, Mar{\'\i}a and Mart{\'\i}n-S{\'a}nchez, Marta and Fern{\'a}ndez-Su{\'a}rez, Elena and Mena, Marcela and Carmona, Rosario and Dopazo, Joaquin and Borrego, Salud and Anti{\v n}olo, Guillermo} } @article {816, title = {Characterization of the Common Genetic Variation in the Spanish Population of Navarre.}, journal = {Genes (Basel)}, volume = {15}, year = {2024}, month = {2024 May 04}, abstract = {

Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants in the population of Navarre (Spain), utilizing whole genome sequencing data from 358 unrelated individuals of Spanish origin. Our analysis revealed 61,410 biallelic single nucleotide variants (SNV) within the Navarrese cohort, with 35\% classified as common (MAF > 1\%). By comparing allele frequency data from 1000 Genome Project (excluding the Iberian cohort of Spain, IBS), Genome Aggregation Database, and a Spanish cohort (including IBS individuals and data from Medical Genome Project), we identified 1069 SNVs common in Navarre but rare (MAF <= 1\%) in all other populations. We further corroborated this observation with a second regional cohort of 239 unrelated exomes, which confirmed 676 of the 1069 SNVs as common in Navarre. In conclusion, this study highlights the importance of population-specific characterization of genetic variation to improve allele frequency filtering in sequencing data analysis to identify disease-causing variants.

}, keywords = {Cohort Studies, Exome, Female, Gene Frequency, Genetic Variation, Genetics, Population, Genome, Human, Humans, Male, Polymorphism, Single Nucleotide, Spain, Whole Genome Sequencing}, issn = {2073-4425}, doi = {10.3390/genes15050585}, author = {Maillo, Alberto and Huergo, Estefania and Apell{\'a}niz-Ruiz, Mar{\'\i}a and Urrutia-Lafuente, Edurne and Miranda, Mar{\'\i}a and Salgado, Josefa and Pasalodos-Sanchez, Sara and Delgado-Mora, Luna and Teijido, {\'O}scar and Goicoechea, Ibai and Carmona, Rosario and Perez-Florido, Javier and Aquino, Virginia and L{\'o}pez-L{\'o}pez, Daniel and Pe{\~n}a-Chilet, Maria and Beltran, Sergi and Dopazo, Joaquin and Lasa, I{\~n}igo and Beloqui, Juan Jos{\'e} and Alonso, {\'A}ngel and Gomez-Cabrero, David} } @article {813, title = {The integrated genomic surveillance system of Andalusia (SIEGA) provides a One Health regional resource connected with the clinic.}, journal = {Sci Rep}, volume = {14}, year = {2024}, month = {2024 Aug 19}, pages = {19200}, abstract = {

The One Health approach, recognizing the interconnectedness of human, animal, and environmental health, has gained significance amid emerging zoonotic diseases and antibiotic resistance concerns. This paper aims to demonstrate the utility of a collaborative tool, the SIEGA, for monitoring infectious diseases across domains, fostering a comprehensive understanding of disease dynamics and risk factors, highlighting the pivotal role of One Health surveillance systems. Raw whole-genome sequencing is processed through different species-specific open software that additionally reports the presence of genes associated to anti-microbial resistances and virulence. The SIEGA application is a Laboratory Information Management System, that allows customizing reports, detect transmission chains, and promptly alert on alarming genetic similarities. The SIEGA initiative has successfully accumulated a comprehensive collection of more than 1900 bacterial genomes, including Salmonella enterica, Listeria monocytogenes, Campylobacter jejuni, Escherichia coli, Yersinia enterocolitica and Legionella pneumophila, showcasing its potential in monitoring pathogen transmission, resistance patterns, and virulence factors. SIEGA enables customizable reports and prompt detection of transmission chains, highlighting its contribution to enhancing vigilance and response capabilities. Here we show the potential of genomics in One Health surveillance when supported by an appropriate bioinformatic tool. By facilitating precise disease control strategies and antimicrobial resistance management, SIEGA enhances global health security and reduces the burden of infectious diseases. The integration of health data from humans, animals, and the environment, coupled with advanced genomics, underscores the importance of a holistic One Health approach in mitigating health threats.

}, keywords = {Animals, Drug Resistance, Bacterial, Genome, Bacterial, Genomics, Humans, One Health, Virulence Factors, Whole Genome Sequencing}, issn = {2045-2322}, doi = {10.1038/s41598-024-70107-0}, author = {Casimiro-Soriguer, Carlos S and Perez-Florido, Javier and Robles, Enrique A and Lara, Mar{\'\i}a and Aguado, Andrea and Rodr{\'\i}guez Iglesias, Manuel A and Lepe, Jose A and Garc{\'\i}a, Federico and P{\'e}rez-Alegre, M{\'o}nica and And{\'u}jar, Elo{\'\i}sa and Jim{\'e}nez, Victoria E and Camino, Lola P and Loruso, Nicola and Ameyugo, Ulises and Vazquez, Isabel Mar{\'\i}a and Lozano, Carlota M and Chaves, J Alberto and Dopazo, Joaquin} } @article {801, title = {Evaluation of a combined detection of SARS-CoV-2 and its variants using real-time allele-specific PCR strategy: an advantage for clinical practice.}, journal = {Epidemiol Infect}, volume = {151}, year = {2023}, month = {2023 Nov 24}, pages = {e201}, abstract = {

This study aimed to assess the ability of a real-time reverse transcription polymerase chain reaction (RT-PCR) with multiple targets to detect SARS-CoV-2 and its variants in a single test. Nasopharyngeal specimens were collected from patients in Granada, Spain, between January 2021 and December 2022. Five allele-specific RT-PCR kits were used sequentially, with each kit designed to detect a predominant variant at the time. When the Alpha variant was dominant, the kit included the HV69/70 deletion, E and N genes. When Delta replaced Alpha, the kit incorporated the L452R mutation in addition to E and N genes. When Omicron became dominant, L452R was replaced with the N679K mutation. Before incorporating each variant kit, a comparative analysis was carried out with SARS-CoV-2 whole genome sequencing (WGS). The results demonstrated that RT-PCR with multiple targets can provide rapid and effective detection of SARS-CoV-2 and its variants in a single test. A very high degree of agreement (96.2\%) was obtained between the comparison of RT-PCR and WGS. Allele-specific RT-PCR assays make it easier to implement epidemiological surveillance systems for effective public health decision making.

}, keywords = {Alleles, COVID-19, COVID-19 Testing, Humans, Real-Time Polymerase Chain Reaction, SARS-CoV-2, Sensitivity and Specificity}, issn = {1469-4409}, doi = {10.1017/S095026882300184X}, author = {Chaves-Blanco, Luc{\'\i}a and de Salazar, Adolfo and Fuentes, Ana and Vi{\~n}uela, Laura and Perez-Florido, Javier and Dopazo, Joaquin and Garc{\'\i}a, Federico} } @article {762, title = {Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival.}, journal = {Viruses}, volume = {14}, year = {2022}, month = {2022 Aug 27}, abstract = {

OBJECTIVES: More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain.

METHODS: A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis.

RESULTS: A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins.

CONCLUSIONS: This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.

}, keywords = {COVID-19, Genome, Viral, Humans, mutation, Pandemics, Phylogeny, SARS-CoV-2}, issn = {1999-4915}, doi = {10.3390/v14091893}, author = {Loucera, Carlos and Perez-Florido, Javier and Casimiro-Soriguer, Carlos S and Ortuno, Francisco M and Carmona, Rosario and Bostelmann, Gerrit and Mart{\'\i}nez-Gonz{\'a}lez, L Javier and Mu{\~n}oyerro-Mu{\~n}iz, Dolores and Villegas, Rom{\'a}n and Rodr{\'\i}guez-Ba{\~n}o, Jes{\'u}s and Romero-G{\'o}mez, Manuel and Lorusso, Nicola and Garcia-Le{\'o}n, Javier and Navarro-Mar{\'\i}, Jose M and Camacho-Martinez, Pedro and Merino-Diaz, Laura and Salazar, Adolfo de and Vi{\~n}uela, Laura and Lepe, Jose A and Garc{\'\i}a, Federico and Dopazo, Joaquin} } @article {701, title = {CSVS, a crowdsourcing database of the Spanish population genetic variability.}, journal = {Nucleic Acids Res}, volume = {49}, year = {2021}, month = {2021 01 08}, pages = {D1130-D1137}, abstract = {

The 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/.

}, keywords = {Alleles, Chromosome Mapping, Crowdsourcing, Databases, Genetic, Exome, Gene Frequency, Genetic Variation, Genetics, Population, Genome, Human, Genomics, Humans, Internet, Precision Medicine, Software, Spain}, issn = {1362-4962}, doi = {10.1093/nar/gkaa794}, author = {Pe{\~n}a-Chilet, Maria and Rold{\'a}n, Gema and Perez-Florido, Javier and Ortuno, Francisco M and Carmona, Rosario and Aquino, Virginia and L{\'o}pez-L{\'o}pez, Daniel and Loucera, Carlos and Fernandez-Rueda, Jose L and Gallego, Asunci{\'o}n and Garcia-Garcia, Francisco and Gonz{\'a}lez-Neira, Anna and Pita, Guillermo and N{\'u}{\~n}ez-Torres, Roc{\'\i}o and Santoyo-L{\'o}pez, Javier and Ayuso, Carmen and Minguez, Pablo and Avila-Fernandez, Almudena and Corton, Marta and Moreno-Pelayo, Miguel {\'A}ngel and Morin, Mat{\'\i}as and Gallego-Martinez, Alvaro and Lopez-Escamez, Jose A and Borrego, Salud and Anti{\v n}olo, Guillermo and Amigo, Jorge and Salgado-Garrido, Josefa and Pasalodos-Sanchez, Sara and Morte, Beatriz and Carracedo, {\'A}ngel and Alonso, {\'A}ngel and Dopazo, Joaquin} }