Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach.

Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.

A crowdsourcing database for the copy-number variation of the Spanish population.

BACKGROUND: Despite being a very common type of genetic variation, the distribution of copy-number variations (CNVs) in the population is still poorly understood. The knowledge of the genetic variability, especially at the level of the local population, is a critical factor for distinguishing pathogenic from non-pathogenic variation in the discovery of new disease variants. RESULTS: Here, we present the SPAnish Copy Number Alterations Collaborative Server (SPACNACS), which currently contains copy number variation profiles obtained from more than 400 genomes and exomes of unrelated Spanish individuals. By means of a collaborative crowdsourcing effort whole genome and whole exome sequencing data, produced by local genomic projects and for other purposes, is continuously collected. Once checked both, the Spanish ancestry and the lack of kinship with other individuals in the SPACNACS, the CNVs are inferred for these sequences and they are used to populate the database. A web interface allows querying the database with different filters that include ICD10 upper categories. This allows discarding samples from the disease under study and obtaining pseudo-control CNV profiles from the local population. We also show here additional studies on the local impact of CNVs in some phenotypes and on pharmacogenomic variants. SPACNACS can be accessed at: http://csvs.clinbioinfosspa.es/spacnacs/ . CONCLUSION: SPACNACS facilitates disease gene discovery by providing detailed information of the local variability of the population and exemplifies how to reuse genomic data produced for other purposes to build a local reference database.

Evaluation of a combined detection of SARS-CoV-2 and its variants using real-time allele-specific PCR strategy: an advantage for clinical practice.

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.

CSVS, a crowdsourcing database of the Spanish population genetic variability.

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/.

Detection of High Level of Co-Infection and the Emergence of Novel SARS CoV-2 Delta-Omicron and Omicron-Omicron Recombinants in the Epidemiological Surveillance of Andalusia.

Recombination is an evolutionary strategy to quickly acquire new viral properties inherited from the parental lineages. The systematic survey of the SARS-CoV-2 genome sequences of the Andalusian genomic surveillance strategy has allowed the detection of an unexpectedly high number of co-infections, which constitute the ideal scenario for the emergence of new recombinants. Whole genome sequence of SARS-CoV-2 has been carried out as part of the genomic surveillance programme. Sample sources included the main hospitals in the Andalusia region. In addition to the increase of co-infections and known recombinants, three novel SARS-CoV-2 delta-omicron and omicron-omicron recombinant variants with two break points have been detected. Our observations document an epidemiological scenario in which co-infection and recombination are detected more frequently. Finally, we describe a family case in which co-infection is followed by the detection of a recombinant made from the two co-infecting variants. This increased number of recombinants raises the risk of emergence of recombinant variants with increased transmissibility and pathogenicity.

PAX4 preserves endoplasmic reticulum integrity preventing beta cell degeneration in a mouse model of type 1 diabetes mellitus.

AIMS/HYPOTHESIS: A strategy to enhance pancreatic islet functional beta cell mass (BCM) while restraining inflammation, through the manipulation of molecular and cellular targets, would provide a means to counteract the deteriorating glycaemic control associated with diabetes mellitus. The aims of the current study were to investigate the therapeutic potential of such a target, the islet-enriched and diabetes-linked transcription factor paired box 4 (PAX4), to restrain experimental autoimmune diabetes (EAD) in the RIP-B7.1 mouse model background and to characterise putative cellular mechanisms associated with preserved BCM. METHODS: Two groups of RIP-B7.1 mice were genetically engineered to: (1) conditionally express either PAX4 (BPTL) or its diabetes-linked mutant variant R129W (mutBPTL) using doxycycline (DOX); and (2) constitutively express luciferase in beta cells through the use of RIP. Mice were treated or not with DOX, and EAD was induced by immunisation with a murine preproinsulin II cDNA expression plasmid. The development of hyperglycaemia was monitored for up to 4 weeks following immunisation and alterations in the BCM were assessed weekly by non-invasive in vivo bioluminescence intensity (BLI). In parallel, BCM, islet cell proliferation and apoptosis were evaluated by immunocytochemistry. Alterations in PAX4- and PAX4R129W-mediated islet gene expression were investigated by microarray profiling. PAX4 preservation of endoplasmic reticulum (ER) homeostasis was assessed using thapsigargin, electron microscopy and intracellular calcium measurements. RESULTS: PAX4 overexpression blunted EAD, whereas the diabetes-linked mutant variant PAX4R129W did not convey protection. PAX4-expressing islets exhibited reduced insulitis and decreased beta cell apoptosis, correlating with diminished DNA damage and increased islet cell proliferation. Microarray profiling revealed that PAX4 but not PAX4R129W targeted expression of genes implicated in cell cycle and ER homeostasis. Consistent with the latter, islets overexpressing PAX4 were protected against thapsigargin-mediated ER-stress-related apoptosis. Luminal swelling associated with ER stress induced by thapsigargin was rescued in PAX4-overexpressing beta cells, correlating with preserved cytosolic calcium oscillations in response to glucose. In contrast, RNA interference mediated repression of PAX4-sensitised MIN6 cells to thapsigargin cell death. CONCLUSIONS/INTERPRETATION: The coordinated regulation of distinct cellular pathways particularly related to ER homeostasis by PAX4 not achieved by the mutant variant PAX4R129W alleviates beta cell degeneration and protects against diabetes mellitus. The raw data for the RNA microarray described herein are accessible in the Gene Expression Omnibus database under accession number GSE62846.

Transcriptional profiling of peripheral blood in pancreatic adenocarcinoma patients identifies diagnostic biomarkers.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy associated with poor survival rates. Fast detection of PDAC appears to be the most relevant strategy to improve the long-term survival of patients. AIMS: Our objective was to identify new markers in peripheral blood that differentiates between PDAC patients and healthy controls. METHODS: Peripheral blood samples from PDAC patients (n = 18) and controls (n = 18) were analyzed by whole genome cDNA microarray hybridization. The most relevant genes were validated by quantitative real-time PCR (RT-qPCR) in the same set of samples. Finally, our gene prediction set was tested in a blinded set of new peripheral blood samples (n = 30). RESULTS: Microarray studies identified 87 genes differentially expressed in peripheral blood samples from PDAC patients. Four of these genes were selected for analysis by RT-qPCR, which confirmed the previously observed changes. In our blinded validation study, the combination of CLEC4D and IRAK3 predicted the diagnosis of PDAC with 93 % accuracy, with a sensitivity of 86 % and specificity of 100 %. CONCLUSIONS: Peripheral blood gene expression profiling is an useful tool for the diagnosis of PDAC. We present a validated four-gene predictor set (ANKRD22, CLEC4D, VNN1, and IRAK3) that may be useful in PDAC diagnosis.

Molecular and phylogenetic characterization of the monkeypox outbreak in the South of Spain.

Background and Aim: Until the May 2022 Monkeypox (MPXV) outbreak, which spread rapidly to many non-endemic countries, the virus was considered a viral zoonosis limited to some African countries. The Andalusian circuit of genomic surveillance was rapidly applied to characterize the MPXV outbreak in the South of Spain. Methods: Whole genome sequencing was used to obtain the genomic profiles of samples collected across the south of Spain, representative of all the provinces of Andalusia. Phylogenetic analysis was used to study the relationship of the isolates and the available sequences of the 2022 outbreak. Results: Whole genome sequencing of a total of 160 MPXV viruses from the different provinces that reported cases were obtained. Interestingly, we report the sequences of MPXV viruses obtained from two patients who died. While one of the isolates bore no noteworthy mutations that explain a potential heightened virulence, in another patient the second consecutive genome sequence, performed after the administration of tecovirimat, uncovered a mutation within the A0A7H0DN30 gene, known to be a prime target for tecovirimat in its Vaccinia counterpart. In general, a low number of mutations were observed in the sequences reported, which were very similar to the reference of the 2022 outbreak (OX044336), as expected from a DNA virus. The samples likely correspond to several introductions of the circulating MPXV viruses from the last outbreak. The virus sequenced from one of the two patients that died presented a mutation in a gene that bears potential connections to drug resistance. This mutation was absent in the initial sequencing before treatment.

Characterization of the Common Genetic Variation in the Spanish Population of Navarre.

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.

The integrated genomic surveillance system of Andalusia (SIEGA) provides a One Health regional resource connected with the clinic.

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.

Case report: Analysis of phage therapy failure in a patient with a Pseudomonas aeruginosa prosthetic vascular graft infection.

Clinical case of a patient with a Pseudomonas aeruginosa multidrug-resistant prosthetic vascular graft infection which was treated with a cocktail of phages (PT07, 14/01, and PNM) in combination with ceftazidime-avibactam (CZA). After the application of the phage treatment and in absence of antimicrobial therapy, a new P. aeruginosa bloodstream infection (BSI) with a septic residual limb metastasis occurred, now involving a wild-type strain being susceptible to ß-lactams and quinolones. Clinical strains were analyzed by microbiology and whole genome sequencing techniques. In relation with phage administration, the clinical isolates of P. aeruginosa before phage therapy (HE2011471) and post phage therapy (HE2105886) showed a clonal relationship but with important genomic changes which could be involved in the resistance to this therapy. Finally, phenotypic studies showed a decrease in Minimum Inhibitory Concentration (MIC) to ß-lactams and quinolones as well as an increase of the biofilm production and phage resistant mutants in the clinical isolate of P. aeruginosa post phage therapy.

Protein and functional isoform levels and genetic variants of the BAFF and APRIL pathway components in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is the prototype of an autoimmune disease. Belimumab, a monoclonal antibody targets BAFF, is the only biologic approved for SLE and active lupus nephritis. BAFF is a cytokine with a key-regulatory role in the B cell homeostasis, which acts by binding to three receptors: BAFF-R, TACI and BCMA. TACI and BCMA also bind APRIL. Many studies reported elevated soluble BAFF and APRIL levels in the sera of SLE patients, but other questions about the role of this system in the disease remain open. The study aimed to investigate the utility of the cytokine levels in serum and urine as biomarkers, the role of non-functional isoforms, and the association of gene variants with the disease. This case-control study includes a cohort (women, 18-60 years old) of 100 patients (48% with nephritis) and 100 healthy controls. We used ELISA assays to measure the cytokine concentrations in serum (sBAFF and sAPRIL) and urine (uBAFF and uAPRIL); TaqMan Gene Expression Assays to quantify the relative mRNA expression of ΔBAFF, ßAPRIL, and εAPRIL, and next-generation sequencing to genotype the cytokine (TNFSF13 and TNFSF13B) and receptor (TNFRSF13B, TNFRSF17 and TNFRSF13C) genes. The statistical tests used were: Kruskal-Wallis (qualitative variables), the Spearman Rho coefficient (correlations), the Chi-square and SKAT (association of common and rare genetic variants, respectively). As expected, sBAFF and sAPRIL levels were higher in patients than in controls (p ≤ 0.001) but found differences between patient subgroups. sBAFF and sAPRIL significantly correlated only in patients with nephritis (rs = 0.67, p ≤ 0.001) and ßAPRIL levels were lower in patients with nephritis (p = 0.04), and ΔBAFF levels were lower in patients with dsDNA antibodies (p = 0.04). Rare variants of TNFSF13 and TNFRSF13B and TNFSF13 p.Gly67Arg and TNFRSF13B p.Val220Ala were associated with SLE. Our study supports differences among SLE patient subgroups with diverse clinical features in the BAFF/APRIL pathway. In addition, it suggests the involvement of genetic variants in the susceptibility to the disease.

Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival.

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.

Phylogenetic Analysis of the 2020 West Nile Virus (WNV) Outbreak in Andalusia (Spain).

During recent decades West Nile Virus (WNV) outbreaks have continuously occurred in the Mediterranean area. In August 2020 a new WNV outbreak affected 71 people with meningoencephalitis in Andalusia and six more cases were detected in Extremadura (south-west of Spain), causing a total of eight deaths. The whole genomes of four viruses were obtained and phylogenetically analyzed in the context of recent outbreaks. The Andalusian viral samples belonged to lineage 1 and were relatively similar to those of previous outbreaks which occurred in the Mediterranean region. Here we present a detailed analysis of the outbreak, including an extensive phylogenetic study. As part on this effort, we implemented a local Nextstrain server, which has become a constituent piece of regional epidemiological surveillance, wherein forthcoming genomes of environmental samples or, eventually, future outbreaks, will be included.

Highly accurate whole-genome imputation of SARS-CoV-2 from partial or low-quality sequences.

BACKGROUND: The current SARS-CoV-2 pandemic has emphasized the utility of viral whole-genome sequencing in the surveillance and control of the pathogen. An unprecedented ongoing global initiative is producing hundreds of thousands of sequences worldwide. However, the complex circumstances in which viruses are sequenced, along with the demand of urgent results, causes a high rate of incomplete and, therefore, useless sequences. Viral sequences evolve in the context of a complex phylogeny and different positions along the genome are in linkage disequilibrium. Therefore, an imputation method would be able to predict missing positions from the available sequencing data. RESULTS: We have developed the impuSARS application, which takes advantage of the enormous number of SARS-CoV-2 genomes available, using a reference panel containing 239,301 sequences, to produce missing data imputation in viral genomes. ImpuSARS was tested in a wide range of conditions (continuous fragments, amplicons or sparse individual positions missing), showing great fidelity when reconstructing the original sequences, recovering the lineage with a 100% precision for almost all the lineages, even in very poorly covered genomes (<20%). CONCLUSIONS: Imputation can improve the pace of SARS-CoV-2 sequencing production by recovering many incomplete or low-quality sequences that would be otherwise discarded. ImpuSARS can be incorporated in any primary data processing pipeline for SARS-CoV-2 whole-genome sequencing.

Antibiotic resistance and metabolic profiles as functional biomarkers that accurately predict the geographic origin of city metagenomics samples.

BACKGROUND: The availability of hundreds of city microbiome profiles allows the development of increasingly accurate predictors of the origin of a sample based on its microbiota composition. Typical microbiome studies involve the analysis of bacterial abundance profiles. RESULTS: Here we use a transformation of the conventional bacterial strain or gene abundance profiles to functional profiles that account for bacterial metabolism and other cell functionalities. These profiles are used as features for city classification in a machine learning algorithm that allows the extraction of the most relevant features for the classification. CONCLUSIONS: We demonstrate here that the use of functional profiles not only predict accurately the most likely origin of a sample but also to provide an interesting functional point of view of the biogeography of the microbiota. Interestingly, we show how cities can be classified based on the observed profile of antibiotic resistances. REVIEWERS: Open peer review: Reviewed by Jin Zhuang Dou, Jing Zhou, Torsten Semmler and Eran Elhaik.

Draft Genome Sequences of Seven Multidrug-Resistant Acinetobacter baumannii Strains, Isolated from Respiratory Samples in Spain.

The draft genome sequences of seven multidrug-resistantAcinetobacter baumanniiclinical strains belonging to sequence types ST-208 and ST-218 are reported in this study. They were isolated from tracheobronchial aspirate of mechanically ventilated adult patients admitted to the intensive care unit of a Spanish tertiary hospital during 2010 to 2011.