Publications by authors named "Natalia Blay"

Background: The joint impact of exposure to multiple urban environmental factors on asthma remains unclear.

Methods: We analysed data from 14 European cohorts to assess the impact of the urban exposome on asthma incidence across the life course. We linked three external exposome domains (air pollution, built environment, ambient temperature) to the participants' home addresses at baseline.

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Population-based cohorts play a key role in personalized medicine. However, it is known that cohorts are affected by the "healthy volunteer bias" where participants are generally healthier than the broader population, compromising its representativeness. Here, we assess the healthy bias, identifying bias key indicators for representativeness of the GCAT cohort, encompassing 20,000 adult participants of Catalonia, and generating survey raked weights to enhance the cohort's comparability.

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The CORDELIA Study (Collaborative Cohorts Reassembled Data to Study Mechanisms and Long-term Incidence of Chronic Diseases) combines 35 Spanish population cohorts to investigate the clinical, environmental, genetic, and omics determinants of cardiovascular disease in the Southern European population. It aims to conduct the largest genome-wide association study to date on cardiovascular disease in this population, improve predictions of cardiovascular incidence using genomic and clinical data, and identify subgroups that would benefit most from targeted pharmacological and lifestyle interventions. CORDELIA includes 196,632 individuals (ages 18-84, 54% female, 96% born in Spain, 20% with higher education, recruited from 1989 to 2020, with follow-up periods ranging from 5 to 30 years), with DNA samples available for 117,342 participants (60%).

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Background: Long-COVID has mostly been investigated in clinical settings. We aimed to assess the risk, subtypes, persistence, and determinants of long-COVID in a prospective population-based study of adults with a history of SARS-CoV-2 infection in Catalonia.

Methods: We examined 2764 infected individuals from a population-based cohort (COVICAT) established before the pandemic and followed up three times across the pandemic (2020, 2021, 2023).

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Unlabelled: Background Mental illnesses have been overlooked as a potential factor influencing antibody responses to COVID-19 vaccine. Associations between mental disorders and antibody response might vary by specific disorders, depend on the long-term course of the illness and relate to psychotropic treatment.

Methods: The association between mental illness diagnoses (mood affective disorders, anxiety disorders, other) over ten years and psychotropic drug prescription based on electronic health records with antibody levels (IgG and IgA) post COVID-19 vaccination was assessed in 939 vaccinated adults from Catalonia, Spain.

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Background: Understanding genetic-metabolite associations has translational implications for informing cardiovascular risk assessment. Interrogating functional genetic variants enhances our understanding of disease pathogenesis and the development and optimization of targeted interventions.

Methods: In this study, a total of 187 plasma metabolite levels were profiled in 4974 individuals of European ancestry of the GCAT| Genomes for Life cohort.

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Article Synopsis
  • Mental health disorders have become a major public health issue, exacerbated by the COVID-19 pandemic, which revealed gaps in identifying and addressing at-risk populations.
  • * The study developed a machine learning-based risk assessment tool to predict anxiety, depression, and self-perceived stress using data from over 9,200 individuals from Northern Spain, utilizing novel interpretative methods to enhance understanding of risk factors.
  • * Results showed predictive accuracy in identifying high-risk groups, with significant factors like poor health and lack of social support, suggesting that such data-driven strategies could improve mental health interventions in future public health crises.
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Background: Ischemic stroke (IS) represents a significant health burden globally, necessitating a better understanding of its genetic underpinnings to improve prevention and treatment strategies. Despite advances in IS genetics, studies focusing on the Spanish population and sex-stratified analyses are lacking.

Methods: A case-control genome-wide association study was conducted with 9081 individuals (3493 IS cases and 5588 healthy controls).

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Socioeconomic inequalities in the exposome have been found to be complex and highly context-specific, but studies have not been conducted in large population-wide cohorts from multiple countries. This study aims to examine the external exposome, encompassing individual and environmental factors influencing health over the life course, and to perform dimension reduction to derive interpretable characterization of the external exposome for multicountry epidemiological studies. Analyzing data from over 25 million individuals across seven European countries including 12 administrative and traditional cohorts, we utilized domain-specific principal component analysis (PCA) to define the external exposome, focusing on air pollution, the built environment, and air temperature.

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We investigated the association between outdoor artificial light-at-night (ALAN) exposure and cardiometabolic risk in the GCAT study. We included 9752 participants from Barcelona (59% women) and used satellite images (30 m resolution) and estimated photopic illuminance and the circadian regulation-relevant melanopic equivalent daylight illuminance (melanopic EDI). We explored the association between ALAN exposure and prevalent obesity, hypertension, and diabetes with logistic regressions and assessed the relationship with incident cardiometabolic diseases ascertained through electronic health records (mean follow-up 6.

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Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.

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Risk of depression increased in the general population after the COVID-19 pandemic outbreak. By examining the interplay between genetics and individual environmental exposures during the COVID-19 lockdown, we have been able to gain an insight as to why some individuals are more vulnerable to depression, while others are more resilient. This study, conducted on a Spanish cohort of 9218 individuals (COVICAT), includes a comprehensive non-genetic risk analysis, the exposome, complemented by a genomics analysis in a subset of 2442 participants.

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Background: The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined.

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Human pigmentation has largely been associated with different disease prevalence among populations, but most of these studies are observational and inconclusive. Known to be genetically determined, pigmentary traits have largely been studied by Genome-Wide Association Study (GWAS), mostly in Caucasian ancestry cohorts from North Europe, identifying robustly, several loci involved in many of the pigmentary traits. Here, we conduct a detailed analysis by GWAS and Polygenic Risk Score (PRS) of 13 pigmentary-related traits in a South European cohort of Caucasian ancestry (n = 20,000).

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Article Synopsis
  • The study examines the antibody responses to SARS-CoV-2 among 1,076 adults in Catalonia, measuring IgM, IgA, and IgG levels before and after vaccination between June 2020 and July 2021.
  • Key findings show that 35.8% of unvaccinated, previously infected individuals experienced antibody decline, with age, asymptomatic infections, and smoking as contributing factors; vaccinated individuals had higher antibody levels and a recorded increase in responses after the second vaccine dose.
  • Vaccination significantly boosts immune responses, especially evident in those previously infected, with different mRNA vaccines showing varied effectiveness in generating antibody levels post-vaccination.
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Background: Occult atrial fibrillation (AF) is one of the major causes of embolic stroke of undetermined source (ESUS). Knowing the underlying etiology of an ESUS will reduce stroke recurrence and/or unnecessary use of anticoagulants. Understanding cardioembolic strokes (CES), whose main cause is AF, will provide tools to select patients who would benefit from anticoagulants among those with ESUS or AF.

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Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.

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The combined analysis of haplotype panels with phenotype clinical cohorts is a common approach to explore the genetic architecture of human diseases. However, genetic studies are mainly based on single nucleotide variants (SNVs) and small insertions and deletions (indels). Here, we contribute to fill this gap by generating a dense haplotype map focused on the identification, characterization, and phasing of structural variants (SVs).

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Analysis of RNA sequencing (RNA-seq) data from related individuals is widely used in clinical and molecular genetics studies. Prediction of kinship from RNA-seq data would be useful for confirming the expected relationships in family based studies and for highlighting samples from related individuals in case-control or population based studies. Currently, reconstruction of pedigrees is largely based on SNPs or microsatellites, obtained from genotyping arrays, whole genome sequencing and whole exome sequencing.

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