Genomics and Bioinformatics

Line 1: Genetic Architecture of Neurodevelopmental and Complex Disorders

The five publications presented address, from different genomic perspectives, the molecular basis of psychiatric and neurodevelopmental disorders, with particular emphasis on obsessive-compulsive disorder (OCD), autism spectrum disorder (ASD), and other related conditions.

The first paper, published in Nature (2026) by Grotzinger and colleagues, represents one of the most ambitious analyses conducted to date in psychiatric genomics. By studying 14 distinct psychiatric disorders, including schizophrenia, major depression, ADHD, bipolar disorder, PTSD, and anxiety disorders, among others ,the authors map the shared and disorder-specific genetic landscape of each condition. Using large cohorts from the Psychiatric Genomics Consortium (PGC), they identify transdiagnostic and disorder-specific genomic risk regions, enabling a better understanding of how these conditions genetically overlap or diverge. This genetic map constitutes a fundamental advance in understanding the polygenic architecture of psychiatric disorders.

The second article, published in Nature Genetics (2025)  represents the largest genome-wide association study (GWAS) conducted to date in OCD analyzing a combined dataset of over 2.1 million individuals (53,660 cases and over 2 million controls). The authors identified 30 genomic loci associated with this disorder, substantially expanding on previous findings and narrowed down 250 potential genes to 25 highly likely causal candidates, including WDR6, DALRD3, and CTNND1. This result not only broadens knowledge of the biological mechanisms underlying OCD, but also opens the door to future functional studies and the development of new therapeutic targets.

The third and fourth works, both focused on ASD, approach the disorder from complementary angles. The study published in Scientific Reports (2025) analyzes alternative splicing in a Spanish ASD cohort, combining bioinformatic prediction with functional characterization. The results reveal differential splicing events that may contribute to the etiology of the disorder, highlighting the importance of post-transcriptional mechanisms in neurodevelopment. Meanwhile, the paper published in Translational Psychiatry (2023) applies expression quantitative trait loci (eQTL) colocalization analysis to identify novel susceptibility genes in ASD, integrating genetic data with gene expression patterns in brain tissue. This approach allows for the prioritization of functionally relevant genes among association signals previously identified in GWAS.

Finally, the fifth article, published in Neurogenetics (2024), reviews the role of the three-dimensional genome architecture in neurodevelopmental disorders. The spatial organization of DNA within the cell nucleus. through topologically associating domains (TADs), A/B compartments, and chromatin loops, critically regulates gene expression. The authors synthesize available evidence on how alterations in this 3D organization may contribute to conditions such as ASD, intellectual disability, and ADHD. 

Line 2: Functional Genomics and Disease Modelling

The Functional Genomics and Disease Modelling line combines cutting-edge genome editing technologies with human cellular models to investigate the molecular and cellular basis of rare and complex diseases, with the ultimate goal of advancing towards personalized therapeutic strategies.

A central focus is the modelling of rare neurodevelopmental disorders (NDDs). Using human induced pluripotent stem cells (hiPSCs) derived from patients or generated through CRISPR-based genome editing, the group models conditions such as pharmacoresistant epilepsies and rare genetic variants associated with autism spectrum disorder (ASD). These hiPSCs are differentiated into disease-relevant cell types (including cortical neurons, forebrain organoids and other specialized neural populations) enabling the functional characterization of pathogenic variants, the dissection of underlying disease mechanisms, and the identification of candidate therapeutic targets in a human cellular context. Advanced therapies such as mRNA therapeutics or genome editing strategies (including Base Editing and Prime Editing), are applied both to generate precise cellular models and to explore potential therapeutic corrections in vitro.

The group is also actively engaged in the preclinical development of CAR-based cell immunotherapies for solid tumours, including head and neck cancer and ovarian cancer. Given the limitations of conventional CAR-T approaches in the immunosuppressive solid tumour microenvironment, the group focuses on optimizing alternative effector cell platforms — particularly CAR-NK (natural killer) and CAR-macrophage (CAR-M) strategies — as more versatile and effective options for hard-to-treat tumour types. This research has also driven the development of CARTAR (CAR Target Analysis Resource), a bioinformatics platform designed to support the rational identification and prioritization of candidate CAR target antigens. By integrating large-scale transcriptomic data from TCGA and GTEx, CARTAR enables researchers to systematically evaluate potential targets that maximize anti-tumour efficacy while minimizing off-tumour toxicity, addressing one of the most critical bottlenecks in CAR therapy design.

The depth of expertise accumulated across these research activities (in genome editing, hiPSC-based disease modelling, functional genomics and advanced cell therapy development) led to the establishment of SITEpermed (Service for Innovation in Advanced Therapies and Genome Editing towards Personalized Medicine). Coordinated by Dr. Catarina Allegue, SITEpermed was created to make this know-how accessible to the broader scientific, clinical and industrial community, offering expert support from experimental design and model generation through to functional characterization and preclinical evaluation of therapeutic candidates.

Line 3: Pharmacogenomics and Drug Discovery

These five publications reflect a translational research programme focused on the generation and implementation of evidence to advance precision medicine, particularly in psychopharmacology, while extending these principles to other therapeutic areas. Together, they illustrate a progression of personalized medicine to its translation into clinical recommendations, biomarker-guided treatment strategies and pharmacogenetic implementation in routine healthcare.

This overarching framework is established in the article of Pharmacological Research (2024), which provides a comprehensive analysis of the evolution of pharmacogenetics, pharmacogenomics and personalised medicine from discovery research to clinical implementation. Rather than merely summarising the field, the article identifies key scientific, regulatory and organisational barriers that continue to limit the integration of genomic biomarkers into healthcare systems. As part of a multidisciplinary national collaboration, this work situates research within the broader challenge of translating precision medicine into clinical reality and highlights the need for robust evidence capable of informing both clinical practice and healthcare policy.

The translational potential of this approach is exemplified by the European Clozapine Task Force statement (European Psychiatry), a landmark initiative aimed at reassessing European requirements for haematological monitoring during clozapine treatment. By critically reviewing the available evidence, the Task Force demonstrated that the risk of agranulocytosis decreases substantially after the first year of treatment and proposed evidence-based recommendations to optimize monitoring protocols, improve access to clozapine and reduce unnecessary healthcare burden. This work exemplifies how rigorous evidence generation and critical synthesis can translate into tangible changes in health policy, as reflected in the update of haematological monitoring recommendations issued by the Spanish Agency of Medicines and Medical Devices (AEMPS) in July 2025. Scientifically, its impact has been exceptional, being recognised as a Highly Cited Paper by Web of Science and ranking among the top 1% of publications worldwide in Psychiatry/Psychology according to field- and year-normalised citation indicators.

Building upon this focus on improving treatment outcomes in psychiatric disorders, the systematic review published in Pharmaceuticals (2025) addresses one of the major challenges in addiction medicine: the marked interindividual variability in response to methadone treatment. By synthesising the available evidence on pharmacokinetic biomarkers, the study identifies the biological determinants that may influence treatment response and supports the development of biomarker-guided therapeutic strategies for opioid use disorder. Beyond its immediate clinical relevance, this work consolidates a competitive and externally funded research line (PI22/01166) on methadone pharmacogenetics and reinforces the broader objective of integrating precision medicine approaches into mental health care.

The same translational principles are subsequently applied to oncology through research focused on fluoropyrimidine safety. In the first study (Pharmaceuticals (Basel)), original evidence was generated on the frequencies of clinically relevant variants in the Galician population. The findings demonstrated that pharmacogenetic frequencies observed in European or national reference populations may not adequately represent regional populations, highlighting the importance of generating local evidence to support implementation strategies and clinical decision-making. This work contributes to the development of population-informed precision medicine and provides a stronger basis for optimising fluoropyrimidine safety programmes.

Finally, Int. J. of Molecular Sciences (2025) challenged a fundamental assumption underlying current European pharmacogenetic recommendations by demonstrating the absence of complete linkage disequilibrium between two variants included in EMA and AEMPS guidelines. These findings have direct implications for the interpretation of pharmacogenetic testing and the selection of biomarkers used in clinical practice, supporting the need to reassess existing testing strategies. Collectively, these studies demonstrate a sustained contribution to the generation of evidence that not only advances scientific knowledge but also shapes clinical practice, implementation strategies and healthcare policy in precision medicine.

Line 4: Neurodevelopment, Clinical Heterogeneity and Precision Psychiatry

The Neurodevelopment, Clinical Heterogeneity and Precision Psychiatry line focuses on understanding the variability of clinical presentation and cognitive profiles across neurodevelopmental and psychiatric conditions. This line aims to identify phenotypic dimensions and biomarkers, based on integrating behavioural, neuropsychological and genetic perspectives, to support more individualized approaches to diagnosis, prognosis and intervention.

Fernandez-Prieto et al. (2021) examined the relationship between sensory processing, executive functioning and behavioural manifestations in autism spectrum disorder (ASD). The findings demonstrated that executive functioning acts as a significant mediator between atypical sensory processing and behavioural difficulties, suggesting that cognitive mechanisms may partially explain the heterogeneity observed in autistic presentations. These results highlight executive functioning as a potential target for intervention and reinforce the importance of multidimensional assessment strategies in ASD.

Addressing sex-related heterogeneity, the systematic review by Tubío-Fungueiriño et al. (2021) synthesized the evidence on social camouflaging among autistic females. The review showed that autistic females frequently engage in compensatory social strategies that may mask core autistic characteristics, contributing to delayed or missed diagnoses and potentially increasing psychological distress. These findings have had important implications for improving the recognition of female autism phenotypes and promoting more equitable diagnostic practices sensitive to gender differences.

In the field of precision psychopharmacology, Recarey-Rama et al. (2025) explored the interplay between sensory processing characteristics and pharmacogenetic biomarkers associated with methylphenidate response in children and adolescents with attention-deficit/hyperactivity disorder (ADHD). The authors identified emerging evidence suggesting that both sensory profiles and genetic variability may contribute to the marked interindividual differences observed in treatment effectiveness and tolerability. These findings support the future integration of behavioural and biological markers to guide personalized treatment strategies in ADHD.

Precision approaches were also applied to the study of obsessive-compulsive disorder (OCD). Using machine learning techniques in a prospective cohort, Segalàs et al. (2024) identified cognitive and clinical predictors associated with long-term disease trajectories. The study demonstrated that combining neuropsychological measures with clinical variables improves the prediction of illness course, illustrating the potential of computational approaches to stratify patients according to prognosis and support individualized clinical decision-making.

The exome sequencing study conducted by Satterstrom et al. (2020) substantially advanced the understanding of autism neurobiology by demonstrating that both developmental and functional pathways contribute to ASD risk. Through the analysis of more than 35,000 individuals, the study identified high-confidence ASD genes involved in synaptic function, gene regulation and neuronal development, providing a robust biological framework for interpreting phenotypic diversity and facilitating the transition towards biologically informed precision psychiatry.

These contributions illustrate how integrating cognitive phenotyping, sex-sensitive approaches, computational modelling and genomic evidence can help disentangle the substantial heterogeneity characterizing neurodevelopmental and psychiatric disorders. This multidimensional perspective provides important insights for the development of precision psychiatry, aiming to move beyond categorical diagnoses towards individualized prevention, prognosis and intervention strategies.

Line 5: Computational Genomics and Bioinformatics Development

These are the most relevant scientific contributions within this research line, focused on the development of advanced analytical pipelines and statistical modeling to decipher the genetic architecture of complex diseases across diverse populations. A cornerstone of this work is the integration of massive multi-omic datasets to move from association to therapeutic translation. 

A major milestone was the participation in the international study published in Nature (2023). This massive meta-analysis of over 24,000 critical cases identified 49 genetic variants underlying severe COVID-19, 16 of which were new discoveries. Our team actively collaborated by contributing the genomic data and results from the SCOURGE consortium, significantly enhancing the study's statistical power. Integrating monocyte gene expression and Mendelian randomization allowed for the identification of key druggable targets such as JAK1, supporting the clinical use of inhibitors in treating critically ill patients.

Focusing on genetic diversity, the work published in eLife (2024) represents the largest GWAS meta-analysis to date for COVID-19 hospitalization in admixed American populations. This research uncovered two novel risk loci, the genes BAZ2B and DDIAS, which remained undetectable in studies limited to European populations. A highlighted finding was a sentinel variant in DDIAS that shows a massive effect size (OR = 2.27) but is nearly monomorphic in Europeans, emphasizing the critical need for ancestry-specific research to avoid masking population-specific risks.

Bioinformatic innovation is further demonstrated in the study from Communications Biology (2025), which developed a machine learning model based on Random Forest to identify mitochondrial haplogroups from standard genotyping arrays. Achieving extremely high diagnostic precision ($\kappa = 0.98$), the model was applied to thousands of patients to show that the mitochondrial HV branch acts as an independent protective factor against critical COVID-19. This suggests that mitochondrial metabolic fitness directly influences the host response to severe infection.

In the field of precision psychiatry, research in Translational Psychiatry (2023) explored the genetic overlap between mental disorders and COVID-19. It determined that genetic liability for schizophrenia, measured via Polygenic Risk Scores (PRS), is a significant predictor of SARS-CoV-2 infection and hospitalization risk, with the effect being particularly pronounced in women.

Finally, in the study of complex inflammatory diseases, the work in Journal of Clinical Periodontology (2023) identified new risk factors for severe periodontitis in young individuals. Through a meta-analysis of European samples, the FCER1G gene was discovered as a genome-wide significant risk locus. These results link oral barrier stability and tissue regeneration mechanisms to disease susceptibility, providing new insights into its etiology and potential therapeutic targets.