A genomic strategy for precision medicine in rare diseases: integrating customized algorithms into clinical practice. - Méndez-Vidal, Cristina; Bravo-Gil, Nereida; Perez-Florido, Javier; Marcos-Luque, Irene; Fernández, Raquel M; Fernandez-Rueda, Jose Luis; González-del Pozo, María; Martín-Sánchez, Marta; Fernández-Suárez, Elena; Mena, Marcela; Carmona, Rosario; Dopazo, Joaquin; et al. (J Transl Med, 2025)
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

Characterization of the Common Genetic Variation in the Spanish Population of Navarre. - Maillo, Alberto; Huergo, Estefania; Apellániz-Ruiz, María; Urrutia-Lafuente, Edurne; Miranda, María; Salgado, Josefa; Pasalodos-Sanchez, Sara; Delgado-Mora, Luna; Teijido, Óscar; Goicoechea, Ibai; Carmona, Rosario; Perez-Florido, Javier; et al. (Genes (Basel), 2024)
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

Primary Ciliary Dyskinesia and Retinitis Pigmentosa: Novel Variant and Possible Modifier Gene. - Baz-Redón, Noelia; Sánchez-Bellver, Laura; Fernández-Cancio, Mónica; Rovira-Amigo, Sandra; Burgoyne, Thomas; Ranjit, Rai; Aquino, Virginia; Toro-Barrios, Noemí; Carmona, Rosario; Polverino, Eva; Cols, Maria; Moreno-Galdó, Antonio; et al. (Cells, 2024)
We report a novel missense variant co-segregated with a familial X-linked retinitis pigmentosa (XLRP) case. The brothers were hemizygous for this variant, but only the proband presented with primary ciliary dyskinesia (PCD). Thus, we aimed to elucidate the role of the variant and other modifier genes in the phenotypic variability observed in the family and its impact on motile cilia. The pathogenicity of the variant on the RPGR protein was evaluated by in vitro studies transiently transfecting the mutated gene, and immunofluorescence analysis on nasal brushing samples. Whole-exome sequencing was conducted to identify potential modifier variants. In vitro studies showed that the mutated RPGR protein could not localise to the cilium and impaired cilium formation. Accordingly, RPGR was abnormally distributed in the siblings' nasal brushing samples. In addition, a missense variant in was identified. The concurrent variant influenced ciliary mislocalisation of the protein. We provide a comprehensive characterisation of motile cilia in this XLRP family, with only the proband presenting PCD symptoms. The variant's pathogenicity was confirmed, although it alone does not explain the respiratory symptoms. Finally, the gene may be a potential modifier for respiratory symptoms in patients with mutations.
Keywords: Ciliary Motility Disorders; Eye Proteins; Genes, Modifier; Humans; Male; mutation; Retinitis pigmentosa

Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival. - Loucera, Carlos; Perez-Florido, Javier; Casimiro-Soriguer, Carlos S; Ortuno, Francisco M; Carmona, Rosario; Bostelmann, Gerrit; Martínez-González, L Javier; Muñoyerro-Muñiz, Dolores; Villegas, Román; Rodríguez-Baño, Jesús; Romero-Gómez, Manuel; Lorusso, Nicola; et al. (Viruses, 2022)
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

CSVS, a crowdsourcing database of the Spanish population genetic variability. - Peña-Chilet, Maria; Roldán, Gema; Perez-Florido, Javier; Ortuno, Francisco M; Carmona, Rosario; Aquino, Virginia; López-López, Daniel; Loucera, Carlos; Fernandez-Rueda, Jose L; Gallego, Asunción; Garcia-Garcia, Francisco; González-Neira, Anna; et al. (Nucleic Acids Res, 2021)
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

SMN1 copy-number and sequence variant analysis from next-generation sequencing data. - López-López, Daniel; Loucera, Carlos; Carmona, Rosario; Aquino, Virginia; Salgado, Josefa; Pasalodos, Sara; Miranda, María; Alonso, Ángel; Dopazo, Joaquin (Hum Mutat, 2020)
Spinal muscular atrophy (SMA) is a severe neuromuscular autosomal recessive disorder affecting 1/10,000 live births. Most SMA patients present homozygous deletion of SMN1, while the vast majority of SMA carriers present only a single SMN1 copy. The sequence similarity between SMN1 and SMN2, and the complexity of the SMN locus makes the estimation of the SMN1 copy-number by next-generation sequencing (NGS) very difficult. Here, we present SMAca, the first python tool to detect SMA carriers and estimate the absolute SMN1 copy-number using NGS data. Moreover, SMAca takes advantage of the knowledge of certain variants specific to SMN1 duplication to also identify silent carriers. This tool has been validated with a cohort of 326 samples from the Navarra 1000 Genomes Project (NAGEN1000). SMAca was developed with a focus on execution speed and easy installation. This combination makes it especially suitable to be integrated into production NGS pipelines. Source code and documentation are available at https://www.github.com/babelomics/SMAca.
Keywords: Base Sequence; DNA Copy Number Variations; High-Throughput Nucleotide Sequencing; Humans; Reproducibility of Results; Software; Survival of Motor Neuron 1 Protein