Biological basis of extensive pleiotropy between blood traits and cancer risk.

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. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations. METHODS: Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis. RESULTS: The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood-cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis. CONCLUSIONS: This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk.

Identification of intergenerational epigenetic inheritance by whole genome DNA methylation analysis in trios.

Genome-wide association studies have identified thousands of loci associated with common diseases and traits. However, a large fraction of heritability remains unexplained. Epigenetic modifications, such as the observed in DNA methylation have been proposed as a mechanism of intergenerational inheritance. To investigate the potential contribution of DNA methylation to the missing heritability, we analysed the methylomes of four healthy trios (two parents and one offspring) using whole genome bisulphite sequencing. Of the 1.5 million CpGs (19%) with over 20% variability between parents in at least one family and compatible with a Mendelian inheritance pattern, only 3488 CpGs (0.2%) lacked correlation with any SNP in the genome, marking them as potential sites for intergenerational epigenetic inheritance. These markers were distributed genome-wide, with some preference to be located in promoters. They displayed a bimodal distribution, being either fully methylated or unmethylated, and were often found at the boundaries of genomic regions with high/low GC content. This analysis provides a starting point for future investigations into the missing heritability of simple and complex traits.

Mechanisms by which the cystic fibrosis transmembrane conductance regulator may influence SARS-CoV-2 infection and COVID-19 disease severity.

Patients with cystic fibrosis (CF) exhibit pronounced respiratory damage and were initially considered among those at highest risk for serious harm from SARS-CoV-2 infection. Numerous clinical studies have subsequently reported that individuals with CF in North America and Europe-while susceptible to severe COVID-19-are often spared from the highest levels of virus-associated mortality. To understand features that might influence COVID-19 among patients with cystic fibrosis, we studied relationships between SARS-CoV-2 and the gene responsible for CF (i.e., the cystic fibrosis transmembrane conductance regulator, CFTR). In contrast to previous reports, we found no association between CFTR carrier status (mutation heterozygosity) and more severe COVID-19 clinical outcomes. We did observe an unexpected trend toward higher mortality among control individuals compared with silent carriers of the common F508del CFTR variant-a finding that will require further study. We next performed experiments to test the influence of homozygous CFTR deficiency on viral propagation and showed that SARS-CoV-2 production in primary airway cells was not altered by the absence of functional CFTR using two independent protocols. On the contrary, experiments performed in vitro strongly indicated that virus proliferation depended on features of the mucosal fluid layer known to be disrupted by absent CFTR in patients with CF, including both low pH and increased viscosity. These results point to the acidic, viscous, and mucus-obstructed airways in patients with cystic fibrosis as unfavorable for the establishment of coronaviral infection. Our findings provide new and important information concerning relationships between the CF clinical phenotype and severity of COVID-19.

Resilience characterized and quantified from physical activity data: A tutorial in R.

Consistent physical activity is key for health and well-being, but it is vulnerable to stressors. The process of recovering from such stressors and bouncing back to the previous state of physical activity can be referred to as resilience. Quantifying resilience is fundamental to assess and manage the impact of stressors on consistent physical activity. In this tutorial, we present a method to quantify the resilience process from physical activity data. We leverage the prior operationalization of resilience, as used in various psychological domains, as area under the curve and expand it to suit the characteristics of physical activity time series. As use case to illustrate the methodology, we quantified resilience in step count time series (length = 366 observations) for eight participants following the first COVID-19 lockdown as a stressor. Steps were assessed daily using wrist-worn devices. The methodology is implemented in R and all coding details are included. For each person's time series, we fitted multiple growth models and identified the best one using the Root Mean Squared Error (RMSE). Then, we used the predicted values from the selected model to identify the point in time when the participant recovered from the stressor and quantified the resulting area under the curve as a measure of resilience for step count. Further resilience features were extracted to capture the different aspects of the process. By developing a methodological guide with a step-by-step implementation, we aimed at fostering increased awareness about the concept of resilience for physical activity and facilitate the implementation of related research.

Genome-wide epistasis study highlights genetic interactions influencing severity of COVID-19.

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may lead to life-threatening respiratory symptoms. Understanding the genetic basis of the prognosis of COVID-19 is important for risk profiling of potentially severe symptoms. Here, we conducted a genome-wide epistasis study of COVID-19 severity in 2243 patients with severe symptoms and 12,612 patients with no or mild symptoms from the UK Biobank, followed by a replication study in an independent Spanish cohort (1416 cases, 4382 controls). Our study highlighted 3 interactions with genome-wide significance in the discovery phase, nominally significant in the replication phase, and enhanced significance in the meta-analysis. For example, the lead interaction was found between rs9792388 upstream of PDGFRL and rs3025892 downstream of SNAP25, where the composite genotype of rs3025892 CT and rs9792388 CA/AA showed higher risk of severe disease than any other genotypes (P = 2.77 × 10-12, proportion of severe cases = 0.24 ~ 0.29 vs. 0.09 ~ 0.18, genotypic OR = 1.96 ~ 2.70). This interaction was replicated in the Spanish cohort (P = 0.002, proportion of severe cases = 0.30 ~ 0.36 vs. 0.14 ~ 0.25, genotypic OR = 1.45 ~ 2.37) and showed enhanced significance in the meta-analysis (P = 4.97 × 10-14). Notably, these interactions indicated a possible molecular mechanism by which SARS-CoV-2 affects the nervous system. The first exhaustive genome-wide screening for epistasis improved our understanding of genetic basis underlying the severity of COVID-19.

Long-Term Exposure to Air Pollution and COVID-19 Vaccine Antibody Response in a General Population Cohort (COVICAT Study, Catalonia).

BACKGROUND: Ambient air pollution has been associated with COVID-19 disease severity and antibody response induced by infection. OBJECTIVES: We examined the association between long-term exposure to air pollution and vaccine-induced antibody response. METHODS: This study was nested in an ongoing population-based cohort, COVICAT, the GCAT-Genomes for Life cohort, in Catalonia, Spain, with multiple follow-ups. We drew blood samples in 2021 from 1,090 participants of 2,404 who provided samples in 2020, and we included 927 participants in this analysis. We measured immunoglobulin M (IgM), IgG, and IgA antibodies against five viral-target antigens, including receptor-binding domain (RBD), spike-protein (S), and segment spike-protein (S2) triggered by vaccines available in Spain. We estimated prepandemic (2018-2019) exposure to fine particulate matter [PM ≤2.5µm in aerodynamic diameter (PM2.5)], nitrogen dioxide (NO2), black carbon (BC), and ozone (O3) using Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) models. We adjusted estimates for individual- and area-level covariates, time since vaccination, and vaccine doses and type and stratified by infection status. We used generalized additive models to explore the relationship between air pollution and antibodies according to days since vaccination. RESULTS: Among vaccinated persons not infected by SARS-CoV-2 (n=632), higher prepandemic air pollution levels were associated with a lower vaccine antibody response for IgM (1 month post vaccination) and IgG. Percentage change in geometric mean IgG levels per interquartile range of PM2.5 (1.7 µg/m3) were -8.1 (95% CI: -15.9, 0.4) for RBD, -9.9 (-16.2, -3.1) for S, and -8.4 (-13.5, -3.0) for S2. We observed a similar pattern for NO2 and BC and an inverse pattern for O3. Differences in IgG levels by air pollution levels persisted with time since vaccination. We did not observe an association of air pollution with vaccine antibody response among participants with prior infection (n=295). DISCUSSION: Exposure to air pollution was associated with lower COVID-19 vaccine antibody response. The implications of this association on the risk of breakthrough infections require further investigation. https://doi.org/10.1289/EHP11989.

Skin Phototype and Disease: A Comprehensive Genetic Approach to Pigmentary Traits Pleiotropy Using PRS in the GCAT Cohort.

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). We observed fair phototype strongly associated with non-melanoma skin cancer and other dermatoses and confirmed by PRS-approach the shared genetic basis with skin and eye diseases, such as melanoma (OR = 0.95), non-melanoma skin cancer (OR = 0.93), basal cell carcinoma (OR = 0.97) and darker phototype with vitiligo (OR = 1.02), cataracts (OR = 1.04). Detailed genetic analyses revealed 37 risk loci associated with 10 out of 13 analyzed traits, and 16 genes significantly associated with at least two pigmentary traits. Some of them have been widely reported, such as MC1R, HERC2, OCA2, TYR, TYRP1, SLC45A2, and some novel candidate genes C1QTNF3, LINC02876, and C1QTNF3-AMACR have not been reported in the GWAS Catalog, with regulatory potential. These results highlight the importance of the assess phototype as a genetic proxy of skin functionality and disease when evaluating open mixed populations.

Changes in Population Health-Related Behaviors During a COVID-19 Surge: A Natural Experiment.

BACKGROUND: The study of impact of lockdowns on individual health-related behaviors has produced divergent results. PURPOSE: To identify patterns of change in multiple health-related behaviors analyzed as a whole, and their individual determinants. METHODS: Between March and August 2020, we collected data on smoking, alcohol, physical activity, weight, and sleep in a population-based cohort from Catalonia who had available pre-pandemic data. We performed multiple correspondence and cluster analyses to identify patterns of change in health-related behaviors and built multivariable multinomial logistic regressions to identify determinants of behavioral change. RESULTS: In 10,032 participants (59% female, mean (SD) age 55 (8) years), 8,606 individuals (86%) modified their behavior during the lockdown. We identified five patterns of behavioral change that were heterogeneous and directed both towards worsening and improvement in diverse combinations. Patterns ranged from "global worsening" (2,063 participants, 21%) characterized by increases in smoking, alcohol consumption, and weight, and decreases in physical activity levels and sleep time, to "improvement" (2,548 participants, 25%) characterized by increases in physical activity levels, decreases in weight and alcohol consumption, and both increases and decreases in sleep time. Being female, of older age, teleworking, having a higher education level, assuming caregiving responsibilities, and being more exposed to pandemic news were associated with changing behavior (all p < .05), but did not discriminate between favorable or unfavorable changes. CONCLUSIONS: Most of the population experienced changes in health-related behavior during lockdowns. Determinants of behavior modification were not explicitly associated with the direction of changes but allowed the identification of older, teleworking, and highly educated women who assumed caregiving responsibilities at home as susceptible population groups more vulnerable to lockdowns.

Lockdowns implemented during the first surge of the COVID-19 pandemic created highly disruptive scenarios impacting many aspects of life, including health-related behaviors. While early studies on isolated health-related behaviors partly aid in the understanding of changes in some of these behaviors, there is robust evidence supporting the idea that health-related behaviors and their changes often co-occur and should be studied and analyzed as a whole. Hence, in this study, we used hypothesis-free methods to identify inter-dependent patterns of change in health-related behaviors including tobacco smoking, alcohol consumption, physical activity, sleep, and weight in a population-based sample of 10,032 adults from Catalonia, Spain. We found that 86% of participants modified their health-related behavior during the lockdown as we identified five patterns of behavioral change, ranging from general worsening to improvement, in diverse combinations. Additionally, we found that being female, older age, teleworking, highly educated, assuming caregiving responsibilities, and having a high exposure to pandemic news were main the determinants of patterns characterized by changing behaviors (both worsening and improving). Overall, our results highlight the heterogeneity, co-occurrence, and inter-play between health-related behaviors under a natural experiment, and identify common demographic, socio-environmental and behavioral factors that might predict changes in behavior.

Y-chromosome target enrichment reveals rapid expansion of haplogroup R1b-DF27 in Iberia during the Bronze Age transition.

The Y chromosome can yield a unique perspective into the study of human demographic history. However, due to the repetitive nature of part of its sequence, only a small set of regions are suitable for variant calling and discovery from short-read sequencing data. These regions combined represent 8.9 Mbp or 0.14% of a diploid human genome. Consequently, investing in whole-genome sequencing to resolve Y-chromosome questions is poorly efficient. Here we use, as an alternative, target enrichment technology to greatly increase sequencing effectiveness, validating and applying the technique to 181 males, for 162 of whom we obtained a positive result. Additionally, 75 samples sequenced for the whole genome were also included, for a total sample size of 237. These samples were chosen for their Y chromosome haplogroup: R1b-DF27. In the context of European populations, and particularly in Iberia, this haplogroup stands out for its high frequency and its demographic history. Current evidence indicates that the diffusion of this haplogroup is related to the population movements that mark the cultural Bronze Age transition, making it remarkably interesting for population geneticists. The results of this study show the effects of the rapid radiation of the haplogroup in Spain, as even with the higher discriminating power of whole sequences, most haplotypes still fall within the R1b-DF27* paragroup rather than in the main derived branches. However, we were able to refine the ISOGG 2019-2020 phylogeny, and its two main subbranches, namely L176.2 and Z272, which present geographical differentiation between the Atlantic and Mediterranean coasts of Iberia.

Sequence diversity of the uniparentally transmitted portions of the genome in the resident population of Catalonia.

Genomic reference databases of residing populations are available in different countries and regions. Since they represent the whole genetic diversity of a geographical region, they have wide applications, from biomedical studies to forensic identifications. Uniparentally transmitted portions of the genome specifically are highly suitable for kinship analyses, mixed DNA cases and geographical ancestry inferences. We have sampled 808 individuals currently residing in Catalonia within the GCAT cohort, from which we have generated 808 high-quality whole mitochondrial DNA (mtDNA) genomes and 399 sequences of the male-specific part of the Y chromosome (MSY). We observe higher genetic diversity than in classical population genetics datasets. We test the robustness of whole sequences for unequivocal identifications, and we found that they have higher resolution than mitochondrial control region and Y chromosome short tandem repeats (Y-STRs), and that most of the variants they present are at low frequencies, increasing the discrimination capacity between individuals. These results confirm the forensic applicability of whole uniparental sequences and provide one of the largest high-quality reference datasets ever published.

SARS-CoV-2 infection, vaccination, and antibody response trajectories in adults: a cohort study in Catalonia.

BACKGROUND: Heterogeneity of the population in relation to infection, COVID-19 vaccination, and host characteristics is likely reflected in the underlying SARS-CoV-2 antibody responses. METHODS: We measured IgM, IgA, and IgG levels against SARS-CoV-2 spike and nucleocapsid antigens in 1076 adults of a cohort study in Catalonia between June and November 2020 and a second time between May and July 2021. Questionnaire data and electronic health records on vaccination and COVID-19 testing were available in both periods. Data on several lifestyle, health-related, and sociodemographic characteristics were also available. RESULTS: Antibody seroreversion occurred in 35.8% of the 64 participants non-vaccinated and infected almost a year ago and was related to asymptomatic infection, age above 60 years, and smoking. Moreover, the analysis on kinetics revealed that among all responses, IgG RBD, IgA RBD, and IgG S2 decreased less within 1 year after infection. Among vaccinated, 2.1% did not present antibodies at the time of testing and approximately 1% had breakthrough infections post-vaccination. In the post-vaccination era, IgM responses and those against nucleoprotein were much less prevalent. In previously infected individuals, vaccination boosted the immune response and there was a slight but statistically significant increase in responses after a 2nd compared to the 1st dose. Infected vaccinated participants had superior antibody levels across time compared to naïve-vaccinated people. mRNA vaccines and, particularly the Spikevax, induced higher antibodies after 1st and 2nd doses compared to Vaxzevria or Janssen COVID-19 vaccines. In multivariable regression analyses, antibody responses after vaccination were predicted by the type of vaccine, infection age, sex, smoking, and mental and cardiovascular diseases. CONCLUSIONS: Our data support that infected people would benefit from vaccination. Results also indicate that hybrid immunity results in superior antibody responses and infection-naïve people would need a booster dose earlier than previously infected people. Mental diseases are associated with less efficient responses to vaccination.

A Polygenic Risk Score Based on a Cardioembolic Stroke Multitrait Analysis Improves a Clinical Prediction Model for This Stroke Subtype.

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. We aimed to discover novel loci associated with CES and create a polygenetic risk score (PRS) for a more efficient CES risk stratification. Methods: Multitrait analysis of GWAS (MTAG) was performed with MEGASTROKE-CES cohort (n = 362,661) and AF cohort (n = 1,030,836). We considered significant variants and replicated those variants with MTAG p-value < 5 × 10-8 influencing both traits (GWAS-pairwise) with a p-value < 0.05 in the original GWAS and in an independent cohort (n = 9,105). The PRS was created with PRSice-2 and evaluated in the independent cohort. Results: We found and replicated eleven loci associated with CES. Eight were novel loci. Seven of them had been previously associated with AF, namely, CAV1, ESR2, GORAB, IGF1R, NEURL1, WIPF1, and ZEB2. KIAA1755 locus had never been associated with CES/AF, leading its index variant to a missense change (R1045W). The PRS generated has been significantly associated with CES improving discrimination and patient reclassification of a model with age, sex, and hypertension. Conclusion: The loci found significantly associated with CES in the MTAG, together with the creation of a PRS that improves the predictive clinical models of CES, might help guide future clinical trials of anticoagulant therapy in patients with ESUS or AF.

GCAT|Panel, a comprehensive structural variant haplotype map of the Iberian population from high-coverage whole-genome sequencing.

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). By integrating multiple variant identification methods and Logistic Regression Models (LRMs), we present a catalogue of 35 431 441 variants, including 89 178 SVs (≥50 bp), 30 325 064 SNVs and 5 017 199 indels, across 785 Illumina high coverage (30x) whole-genomes from the Iberian GCAT Cohort, containing a median of 3.52M SNVs, 606 336 indels and 6393 SVs per individual. The haplotype panel is able to impute up to 14 360 728 SNVs/indels and 23 179 SVs, showing a 2.7-fold increase for SVs compared with available genetic variation panels. The value of this panel for SVs analysis is shown through an imputed rare Alu element located in a new locus associated with Mononeuritis of lower limb, a rare neuromuscular disease. This study represents the first deep characterization of genetic variation within the Iberian population and the first operational haplotype panel to systematically include the SVs into genome-wide genetic studies.

Evidence for shared genetic risk factors between lymphangioleiomyomatosis and pulmonary function.

INTRODUCTION: Lymphangioleiomyomatosis (LAM) is a rare low-grade metastasising disease characterised by cystic lung destruction. The genetic basis of LAM remains incompletely determined, and the disease cell-of-origin is uncertain. We analysed the possibility of a shared genetic basis between LAM and cancer, and LAM and pulmonary function. METHODS: The results of genome-wide association studies of LAM, 17 cancer types and spirometry measures (forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC ratio and peak expiratory flow (PEF)) were analysed for genetic correlations, shared genetic variants and causality. Genomic and transcriptomic data were examined, and immunodetection assays were performed to evaluate pleiotropic genes. RESULTS: There were no significant overall genetic correlations between LAM and cancer, but LAM correlated negatively with FVC and PEF, and a trend in the same direction was observed for FEV1. 22 shared genetic variants were uncovered between LAM and pulmonary function, while seven shared variants were identified between LAM and cancer. The LAM-pulmonary function shared genetics identified four pleiotropic genes previously recognised in LAM single-cell transcriptomes: ADAM12, BNC2, NR2F2 and SP5. We had previously associated NR2F2 variants with LAM, and we identified its functional partner NR3C1 as another pleotropic factor. NR3C1 expression was confirmed in LAM lung lesions. Another candidate pleiotropic factor, CNTN2, was found more abundant in plasma of LAM patients than that of healthy women. CONCLUSIONS: This study suggests the existence of a common genetic aetiology between LAM and pulmonary function.

Revisiting the UK Genetic Severity Score for NF2: a proposal for the addition of a functional genetic component.

BACKGROUND: Neurofibromatosis type 2 (NF2) is an autosomal dominant disorder characterised by the development of multiple schwannomas, especially on vestibular nerves, and meningiomas. The UK NF2 Genetic Severity Score (GSS) is useful to predict the progression of the disease from germline NF2 pathogenic variants, which allows the clinical follow-up and the genetic counselling offered to affected families to be optimised. METHODS: 52 Spanish patients were classified using the GSS, and patients' clinical severity was measured and compared between GSS groups. The GSS was reviewed with the addition of phenotype quantification, genetic variant classification and functional assays of Merlin and its downstream pathways. Principal component analysis and regression models were used to evaluate the differences between severity and the effect of NF2 germline variants. RESULTS: The GSS was validated in the Spanish NF2 cohort. However, for 25% of mosaic patients and patients harbouring variants associated with mild and moderate phenotypes, it did not perform as well for predicting clinical outcomes as it did for pathogenic variants associated with severe phenotypes. We studied the possibility of modifying the mutation classification in the GSS by adding the impact of pathogenic variants on the function of Merlin in 27 cases. This revision helped to reduce variability within NF2 mutation classes and moderately enhanced the correlation between patient phenotype and the different prognosis parameters analysed (R2=0.38 vs R2=0.32, p>0001). CONCLUSIONS: We validated the UK NF2 GSS in a Spanish NF2 cohort, despite the significant phenotypic variability identified within it. The revision of the GSS, named Functional Genetic Severity Score, could add value for the classification of mosaic patients and patients showing mild and moderate phenotypes once it has been validated in other cohorts.

RNA assay identifies a previous misclassification of BARD1 c.1977A>G variant.

Case-control studies have shown an association of BARD1 with hereditary breast and/or ovarian cancer (HBOC) predisposition. BARD1 alternatively spliced isoforms are abundant and some are highly expressed in different cancer types. In addition, a number of BARD1 germline pathogenic variants have been reported among HBOC patients. In previous reports, BARD1 c.1977A>G variant has been classified as pathogenic since it produces a frameshift transcript lacking exons 2 to 9. In the present study, we sought to validate the mRNA splicing results previously published and to contribute with new evidence to refine the classification of this substitution according to ACMG/AMP guidelines. The presence of the variant was screened in patients and controls. RT-PCR was performed in order to compare the transcriptional profiles of two variant carriers and ten non-carrier controls. In addition, allele-specific expression was assessed. No differences in variant frequency were detected between patients and controls. The RNA assay confirmed the presence of the shorter transcript lacking exons 2-9, but it was detected both in carriers and non-carriers. Furthermore, allelic imbalance was discarded and no significant differences in the proportion of full-length and shorter transcript were detected between carriers and controls. The shorter transcript detected corresponds to BARD1 isoform η, constituted by exons 1, 10 and 11. Our results support that this transcript is a constitutive splicing product rather than an aberrant transcript caused by BARD1 c.1977A>G variant, and for this reason this variant should be considered as likely benign following ACMG/AMP guidelines.

Ambient Air Pollution in Relation to SARS-CoV-2 Infection, Antibody Response, and COVID-19 Disease: A Cohort Study in Catalonia, Spain (COVICAT Study).

BACKGROUND: Emerging evidence links ambient air pollution with coronavirus 2019 (COVID-19) disease, an association that is methodologically challenging to investigate. OBJECTIVES: We examined the association between long-term exposure to air pollution with SARS-CoV-2 infection measured through antibody response, level of antibody response among those infected, and COVID-19 disease. METHODS: We contacted 9,605 adult participants from a population-based cohort study in Catalonia between June and November 2020; most participants were between 40 and 65 years of age. We drew blood samples from 4,103 participants and measured immunoglobulin M (IgM), IgA, and IgG antibodies against five viral target antigens to establish infection to the virus and levels of antibody response among those infected. We defined COVID-19 disease using self-reported hospital admission, prior positive diagnostic test, or more than three self-reported COVID-19 symptoms after contact with a COVID-19 case. We estimated prepandemic (2018-2019) exposure to fine particulate matter [PM with an aerodynamic diameter of ≤2.5µm (PM2.5)], nitrogen dioxide (NO2), black carbon (BC), and ozone (O3) at the residential address using hybrid land-use regression models. We calculated log-binomial risk ratios (RRs), adjusting for individual- and area-level covariates. RESULTS: Among those tested for SARS-CoV-2 antibodies, 743 (18.1%) were seropositive. Air pollution levels were not statistically significantly associated with SARS-CoV-2 infection: Adjusted RRs per interquartile range were 1.07 (95% CI: 0.97, 1.18) for NO2, 1.04 (95% CI: 0.94, 1.14) for PM2.5, 1.00 (95% CI: 0.92, 1.09) for BC, and 0.97 (95% CI: 0.89, 1.06) for O3. Among infected participants, exposure to NO2 and PM2.5 were positively associated with IgG levels for all viral target antigens. Among all participants, 481 (5.0%) had COVID-19 disease. Air pollution levels were associated with COVID-19 disease: adjusted RRs=1.14 (95% CI: 1.00, 1.29) for NO2 and 1.17 (95% CI: 1.03, 1.32) for PM2.5. Exposure to O3 was associated with a slightly decreased risk (RR=0.92; 95% CI: 0.83, 1.03). Associations of air pollution with COVID-19 disease were more pronounced for severe COVID-19, with RRs=1.26 (95% CI: 0.89, 1.79) for NO2 and 1.51 (95% CI: 1.06, 2.16) for PM2.5. DISCUSSION: Exposure to air pollution was associated with a higher risk of COVID-19 disease and level of antibody response among infected but not with SARS-CoV-2 infection. https://doi.org/10.1289/EHP9726.

Infection induced SARS-CoV-2 seroprevalence and heterogeneity of antibody responses in a general population cohort study in Catalonia Spain.

Sparse data exist on the complex natural immunity to SARS-CoV-2 at the population level. We applied a well-validated multiplex serology test in 5000 participants of a general population study in Catalonia in blood samples collected from end June to mid November 2020. Based on responses to fifteen isotype-antigen combinations, we detected a seroprevalence of 18.1% in adults (n = 4740), and modeled extrapolation to the general population of Catalonia indicated a 15.3% seroprevalence. Antibodies persisted up to 9 months after infection. Immune profiling of infected individuals revealed that with increasing severity of infection (asymptomatic, 1-3 symptoms, ≥ 4 symptoms, admitted to hospital/ICU), seroresponses were more robust and rich with a shift towards IgG over IgA and anti-spike over anti-nucleocapsid responses. Among seropositive participants, lower antibody levels were observed for those ≥ 60 years vs < 60 years old and smokers vs non-smokers. Overweight/obese participants vs normal weight had higher antibody levels. Adolescents (13-15 years old) (n = 260) showed a seroprevalence of 11.5%, were less likely to be tested seropositive compared to their parents and had dominant anti-spike rather than anti-nucleocapsid IgG responses. Our study provides an unbiased estimate of SARS-CoV-2 seroprevalence in Catalonia and new evidence on the durability and heterogeneity of post-infection immunity.

Single nucleotide polymorphisms in PNPLA3, ADAR-1 and IFIH1 are associated with advanced liver fibrosis in patients co-infected with HIV-1//hepatitis C virus.

OBJECTIVE: Nonalcoholic fatty liver disease (NAFLD), insulin resistance and liver fibrosis are prevalent in individuals co-infected with HIV type 1 (HIV-1)/hepatitis C virus (HCV), even after HCV eradication. Our aim was to evaluate single nucleotide polymorphisms (SNPs) associated with advanced liver fibrosis in HIV-1/HCV co-infected patients. DESIGN/METHODS: In a cohort of 102 participants, we genotyped 16 SNPs in 10 genes previously associated with NAFLD and the innate immune response and correlated the genotypes with liver fibrosis and fat accumulation. RESULTS: Multinomial logistic regression analysis identified three metabolic parameters that were significantly associated with advanced liver fibrosis (stage F3-F4): albumin [odds ratio (OR) 0.80, 95% confidence interval (CI) 0.69-0.91, P = 0.001], percentage of visceral fat area (PVFA) (OR 1.06, 95% CI 1.01-1.12, P = 0.03) and BMI (OR 1.47, 95% CI 1.22-1.77, P < 0.0001). After adjustment for sex, albumin, PVFA and BMI, we found that three SNPs were significantly associated with advanced fibrosis, one each in PNPLA3/rs738409 (P = 0.016), ADAR-1/rs1127313 (P = 0.029) and IFIH1/rs1990760 (P = 0.033). CONCLUSION: Our results indicate that genotyping for these SNPs can be a useful predictive tool for liver fibrosis progression and liver fat accumulation in patients co-infected with HIV-1/HCV.

A likelihood ratio approach for identifying three-quarter siblings in genetic databases.

The detection of family relationships in genetic databases is of interest in various scientific disciplines such as genetic epidemiology, population and conservation genetics, forensic science, and genealogical research. Nowadays, screening genetic databases for related individuals forms an important aspect of standard quality control procedures. Relatedness research is usually based on an allele sharing analysis of identity by state (IBS) or identity by descent (IBD) alleles. Existing IBS/IBD methods mainly aim to identify first-degree relationships (parent-offspring or full siblings) and second degree (half-siblings, avuncular, or grandparent-grandchild) pairs. Little attention has been paid to the detection of in-between first and second-degree relationships such as three-quarter siblings (3/4S) who share fewer alleles than first-degree relationships but more alleles than second-degree relationships. With the progressively increasing sample sizes used in genetic research, it becomes more likely that such relationships are present in the database under study. In this paper, we extend existing likelihood ratio (LR) methodology to accurately infer the existence of 3/4S, distinguishing them from full siblings and second-degree relatives. We use bootstrap confidence intervals to express uncertainty in the LRs. Our proposal accounts for linkage disequilibrium (LD) by using marker pruning, and we validate our methodology with a pedigree-based simulation study accounting for both LD and recombination. An empirical genome-wide array data set from the GCAT Genomes for Life cohort project is used to illustrate the method.