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PubMed2025

Association of cancers with the occurrence and 28-day mortality of sepsis: a mendelian randomization and mediator analysis.

Observational studies have indicated an association between cancer and the occurrence of sepsis, with an increased risk of mortality in cancer-related sepsis. However, whether a causal relationship exists between the two remains unknown. Summary statistics of thirteen cancers from the largest available genome-wide association studies (GWAS) of GWAS catalog and FinnGen biobank were extracted for the MR analysis. GWAS data for sepsis and its 28-day mortality were obtained from MRC-IEU. Univariable, multivariable, and reverse MR analyses were employed to explore potential associations between cancers and sepsis and its 28-day mortality. Moreover, a two-step mediation MR analysis was performed to investigate independent positive causal relationships between cancers and sepsis and its 28-day mortality. In univariable Mendelian randomization (MR) analysis, significant causal relationships were found between genetically predicted lung cancer (OR = 1.17, 95% CI = 1.08-1.26, adjusted p = 0.001), squamous cell lung carcinoma (OR = 1.10, 95% CI = 1.02-1.18, adjusted p = 0.042), lung adenocarcinoma (OR = 1.12, 95% CI = 1.03-1.21, adjusted p = 0.032), small cell lung carcinoma (OR = 1.07, 95% CI = 1.02-1.12, adjusted p = 0.031), and sepsis. Subsequent multivariable MR analysis revealed that these three types of lung cancer were independently associated with the risk of sepsis. Additionally, a causal relationship was found between lung cancer and 28-day mortality from sepsis, while no causal link was observed between non-solid tumors and the onset or death of sepsis. Reverse MR analysis did not indicate a potential for sepsis to trigger the onset of cancers. Furthermore, TRAIL was found to have promotive effects on the occurrence and mortality of sepsis. Lung cancer causally correlates with increased sepsis occurrence and 28-day mortality, as evidenced by Mendelian Randomization analysis. Genetic predispositions enhance this risk, underscoring the potential of genetic profiling to guide early, precise sepsis interventions in these patients.

Humans↗

PubMed2026

Selphi, a tool for improving genotype imputation accuracy.

Genotype imputation is a powerful tool for inferring missing genotype data in large-scale genetic studies. Over the last two decades, multiple imputation algorithms have been developed, steadily improving in speed and overall accuracy. However, accurate imputation of rare and infrequent variants remains a challenge, largely because existing methods rely on local haplotype matching within genomic windows and do not fully exploit the extended patterns of haplotype sharing that span entire chromosomes. Here we present Selphi, a new genotype imputation algorithm that combines the Positional Burrows-Wheeler Transform (PBWT) with a multi-stage haplotype selection heuristic operating across entire chromosomes. When compared to state-of-the-art methods Beagle 5.4, IMPUTE5, and Minimac4, Selphi showed higher accuracy on the 1000 Genomes Project and TOPMed datasets, across all super-populations and allele frequencies. Similarly, Selphi achieved higher accuracy than Beagle 5.4 on the UK Biobank dataset, which translated into improved concordance with hc-WGS GWAS summary statistics at known trait-associated loci and more accurate polygenic risk scores (PRS). Selphi outputs standard VCF files with genotype dosages (DS), haplotype-specific allele probabilities (AP1, AP2), and a per-variant dosage R-squared quality score (DR2), enabling direct integration with downstream analytical pipelines including standard post-imputation quality filtering.

Genome-Wide Association Study↗

PubMed2026

Genomic and phenotypic characterization of Klebsiella pneumoniae phage KP Ø1: a novel lytic Slopekvirus targeting uropathogenic multidrug-resistant Klebsiella pneumoniae.

The rise of multidrug-resistant (MDR) uropathogenic gram-negative bacteria (GNB) necessitates the development of alternative therapeutic strategies. This study aimed to isolate, phenotypically characterize, and perform whole-genome sequencing of the bacteriophage demonstrating the broadest host range against MDR uropathogens. Fifty MDR GNB isolates were screened for lytic phages. The most promising candidate, Klebsiella pneumoniae phage KP Ø1, was characterized using plaque assay, Transmission Electron Microscopy (TEM), and pH/thermal stability testing. Genomic characterization was performed via whole-genome sequencing (WGS), with functional annotation and lifestyle prediction using PhaBOX and PhageScope software. Klebsiella pneumoniae was the most prevalent MDR uropathogen. Klebsiella pneumoniae phage KP Ø1 exhibited a 50% host range and high lytic titer (10⁸ PFU/mL). TEM revealed an icosahedral head and short contractile tail. Genomic characterization by WGS revealed that Klebsiella pneumoniae phage KP Ø1 possesses a 174,591 bp double-stranded deoxyribonucleic acid (dsDNA) genome containing 274 predicted open reading frames (ORFs). No lysogeny-related genes, toxins, or antibiotic resistance markers were detected, confirming its strictly lytic nature and supporting its potential as a candidate for phage therapy applications. The phage remained stable (10⁸ PFU/mL) across temperatures of - 20 °C to 50 °C; supporting its suitability for long-term biobanking and suggesting potential activity at physiological temperature, and across a pH range of 7-9. Klebsiella pneumoniae phage KP Ø1 is a novel, obligately lytic Slopekvirus whose genomic architecture, stability profile, and absence of lysogeny-associated, virulence, and antimicrobial resistance genes ( AMR) collectively support its candidacy for further preclinical evaluation as a phage therapy agent against uropathogenic MDR Klebsiella pneumoniae.

Klebsiella pneumoniae↗

PubMed2025

Exploiting pleiotropy to enhance variant discovery with functional false discovery rates.

The cost of recruiting participants for genome-wide association studies (GWASs) can limit sample sizes and hinder the discovery of genetic variants. Here we introduce the surrogate functional false discovery rate (sfFDR) framework that integrates summary statistics of related traits to increase power. The sfFDR framework provides estimates of FDR quantities such as the functional local FDR and q value, and uses these estimates to derive a functional P value for type I error rate control and a functional local Bayes' factor for post-GWAS analyses. Compared with a standard analysis, sfFDR substantially increased power (equivalent to a 52% increase in sample size) in a study of obesity-related traits from the UK Biobank and discovered eight additional lead SNPs near genes linked to immune-related responses in a rare disease GWAS of eosinophilic granulomatosis with polyangiitis. Collectively, these results highlight the utility of exploiting related traits in both small and large studies.

Humans↗

PubMed2023

Exploring the complex spectrum of dominance and recessiveness in genetic cardiomyopathies.

Discrete categorization of Mendelian disease genes into dominant and recessive models often oversimplifies their underlying genetic architecture. Cardiomyopathies (CMs) are genetic diseases with complex etiologies for which an increasing number of recessive associations have recently been proposed. Here, we comprehensively analyze all published evidence pertaining to biallelic variation associated with CM phenotypes to identify high-confidence recessive genes and explore the spectrum of monoallelic and biallelic variant effects in established recessive and dominant disease genes. We classify 18 genes with robust recessive association with CMs, largely characterized by dilated phenotypes, early disease onset and severe outcomes. Several of these genes have monoallelic association with disease outcomes and cardiac traits in the UK Biobank, including LMOD2 and ALPK3 with dilated and hypertrophic CM, respectively. Our data provide insights into the complex spectrum of dominance and recessiveness in genetic heart disease and demonstrate how such approaches enable the discovery of unexplored genetic associations.

Cardiovascular genetics↗

PubMed2006

Approaching the shared biology of obesity and depression: the stress axis as the locus of gene-environment interactions.

Obesity and depression are serious public health problems and also constitute cardiovascular disease risk factors. Research organizations have called for efforts to explore the interrelationship between obesity and depression. A useful starting point is the fact that in both disorders there is dysregulation of stress systems. We review molecular and clinical evidence indicating that the mediators of the stress response are a key locus for gene-environment interactions in the shared biology of depression and obesity. Scientific milestones include translational paradigms such as mice knockouts, imaging and pharmacogenomic approaches that can identify new therapeutic strategies for those burdened by these two afflictions of contemporary civilization. Perspectives for the future are promising. Our ability to dissect the underpinnings of common and complex diseases with shared substrates will be greatly enhanced by the Genes and Environment Initiative, the emerging Large Scale Studies of Genes and Environment in Common Disease, and the UK Biobank Project.

Adaptation, Physiological↗

PubMed2006

[The CHU-CRLCC-UNSA tumour/tissue bank of the Nice area].

The human tissue bank of Nice associates the CHU, the Antoine Lacassagne Center, and the University of Nice Sophia Antipolis. This bank has been labelled by the French Ministery of Health in 2003, and has been open in September 2004. Two main collections have been setting up: the tumoral and non tumoral thyroid pathology and the tumoral and non tumoral pleuro-pulmonary pathology collections. Other collections will be soon incorporated in this Biobank. The main criteria of quality connected with these collections are described. These different criteria of quality have been defined before the beginning of the collect, and thus, they have been initially strictly applied. The quality of the tissue stored at low temperature, the accuracy of the clinical and histopathological data associated with the tissue specimens, and the different procedures, should allow to obtain a labellisation by different appropriate organisms. This is crucial since the different research projects developped from human tissue collections, used expensive and accurate technologies (microarray, CGH array, proteomic, real time PCR, laser capture microdissection, etc.), and the results obtained need to be reproductible. An optimal quality both for the stored tissues and for the procedures applied in a human tissue bank is obliged since some of these tissues specimens are going to be used to try to define new prognosis criteria of tumours and new therapeutic strategies for the patients.

France↗

PubMed2006

[Conditions for using human biological samples in scientific research: legal and ethical framework].

Technological progress increased our capacities in storing biological sample for longer time. The use of biological resources and related data implies that French researchers respect the legal framework including laws on bioethics, protection of individuals involved in biomedical research and related data protection. This framework aims to protect the rights of individuals involved in biomedical research and to allow the identification of biobanks by French institutions. The recent revision of the French law on bioethics offers new perspectives to broaden the use of previously collected and stored biological resources. However, the legal French framework on biological resources does not seem basically applicable to tumor cell and tissue banks with respect to the specificities of their constitution.

Biological Specimen Banks↗

PubMed2026

Privacy-Preserving Linkage of Distributed Biological, Clinical, and Imaging Data Supporting Artificial Intelligence in Pediatric Oncology.

BACKGROUND: Cancer remains the leading cause of disease-related mortality in children over the age of one in Europe, with over 35,000 new pediatric cases and more than 6,000 deaths annually. Due to the rarity of pediatric cancers, clinical trial protocols often substitute for formal treatment guidelines, resulting in many children being enrolled in multiple trials, with biological samples and genomic data stored in various biobanks. Data collection in pediatric oncology is challenging, with sparse data acquired over extended periods, underscoring the need for optimal utilization of all available information through linked, privacy-preserving datasets. METHODS: Here, we report the development of a distributed, privacy-preserving data infrastructure for the PRIMAGE project, a European initiative aimed at supporting artificial intelligence (AI)-driven image analysis for pediatric cancer prognostics. The infrastructure leverages the European Patient Identity (EUPID) Services for Privacy-Preserving Record Linkage, enabling pseudonymized data integration across clinical, biological, and imaging sources. The system incorporates EUPID's hashing and phonetic matching protocols to pseudonymize patient identifiers and link distributed datasets, facilitating secondary data use in compliance with the General Data Protection Regulation. RESULTS: Data from over 700 neuroblastoma patients from European trials and hospitals were linked and uploaded to the PRIMAGE platform, where AI models predict clinical outcomes. CONCLUSION: This infrastructure successfully facilitated AI model development, advancing pediatric oncology research, and offering a scalable framework for future European health data initiatives, such as the European Health Data Space.

Journal Article↗

PubMed2004

Clinical infrastructures to support proteomic studies of tissue and fluids in breast cancer.

The Danish Breast Cancer Cooperative Group (DBCG) was established in 1977 with the aim to ensure optimal breast cancer diagnostics and therapeutic modalities on a nationwide basis. DBCG was organized in such a way so it represents a broad interdisciplinary collaboration with established clinical databases and biobanks. This review summarizes the infrastructures, such as those of the DBCG, that are required to facilitate translational research studies aiming at further diagnostic and therapeutic improvements through interactions directed at prevention, early diagnosis, and treatment of primary breast cancer.

Body Fluids↗

PubMed2006

Bioethics in human nutrigenomics research: European Nutrigenomics Organisation workshop report.

As part of its work on setting standards and establishing guidelines for nutrigenomics research, the European Nutrigenomics Organisation (NuGO) is developing bioethical guidelines for those engaged in human nutrigenomics studies. A NuGO working group developed a set of draft guidelines addressing four areas: (1) information and consenting prior to a nutrigenomics study; (2) the generation and use of genotype information; (3) the establishment and maintenance of biobanks; (4) the exchange of samples and data. NuGO convened a workshop with a panel of invited external experts to assess the draft guidelines. The panel of experts confirmed that these areas are important and that the development of specific bioethical guidelines for nutrigenomics research would therefore enhance the application of established international guidelines in this field of biomedical research.

Biomedical Research↗

PubMed2025

The Effect of Alcohol Intake on Brain White Matter Microstructural Integrity: A New Causal Inference Framework for Incomplete Phenomic Data.

Although substance use, such as alcohol intake, is known to be associated with cognitive decline during aging, its direct influence on the central nervous system remains incompletely understood. In this study, we investigate the influence of alcohol intake frequency on reduction of brain white matter microstructural integrity in the fornix, a brain region considered a promising marker of age-related microstructural degeneration, using a large UK Biobank (UKB) cohort with extensive phenomic data reflecting a comprehensive lifestyle profile. Two major challenges arise: (a) potentially nonlinear confounding effects from phenomic variables and (b) a limited proportion of participants with complete phenomic data. To address these challenges, we develop a novel ensemble learning framework tailored for robust causal inference and introduce a data integration step to incorporate information from UKB participants with incomplete phenomic data, improving estimation efficiency. Our analysis reveals that daily alcohol intake may significantly reduce fractional anisotropy, a neuroimaging-derived measure of white matter structural integrity, in the fornix and increase systolic and diastolic blood pressure levels. Moreover, extensive numerical studies demonstrate the superiority of our method over competing approaches in terms of estimation bias, while outcome regression-based estimators may be preferred when minimizing mean squared error is prioritized. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Brain aging↗

PubMed2025

New insights into causal relationship between serum lipids, obesity, and asthma: a Mendelian randomization study.

OBJECTIVE: To identify causal risk factors for asthma using a Mendelian randomization (MR) approach. METHODS: Genetic variants associated with the exposures at the genome-wide significance level (p < 5 × 10 - 8) were obtained from corresponding genome-wide association studies. Summary-level statistical data for asthma were obtained from the UK Biobank (UKB) and the FinnGen Consortia. Univariate and multivariate MR analyses were performed to clarify causal relationships among obesity, serum lipids, and asthma. Meta-analyses were performed to combine UKB and FinnGen results using a fixed-effects model. RESULTS: In FinnGen, the odds for asthma increased for every 1-SD increase in body mass index (BMI; odds ratio [OR] 1.292, p = 1.34 × 10-7), together with body fat percentage (BF%; OR 1.449, p = 4.90×10-3), and total cholesterol level (OR = 0.949, p = 0.027). However, higher BMI and BF% were found to increase the risk for asthma in the multivariate MR analysis. In the UKB, the BMI results were replicated. Meta-analysis revealed that high-density lipoprotein cholesterol could also increase the risk for asthma, although there were no associations with other risk factors included in this study. CONCLUSION: This MR study found that genetically predicted higher BF% and BMI could increase the risk for asthma and corroborated some risk factors for asthma from previous MR studies. Moreover, the results suggest that higher BMI and BF% could serve as independent risk factors for asthma.

Humans↗

PubMed2006

Serum adiponectin concentration prior to clinical onset of preeclampsia.

OBJECTIVE: This study assesses whether the adipokine adiponectin is a useful marker in pregnant women who subsequently develop preeclampsia (PE). METHODS: A retrospective case-control study was conducted to measure the total serum levels of adiponectin, measured by radioimmunoassay kit, in serum samples stored in serological biobanks. RESULTS: Total serum adiponectin concentrations between the groups were not significantly different (p = 0.22). There were no obvious clinical signs of the preeclamptic inflammatory process at the time when samples were drawn. CONCLUSION: Using this design, total adiponectin appeared not be a useful pre-clinical marker of PE.

Adiponectin↗

PubMed2004

Human genetic banking: altruism, benefit and consent.

This article considers how we should frame the ethical issues raised by current proposals for large-scale genebanks with on-going links to medical and lifestyle data, such as the Wellcome Trust and Medical Research Council's 'UK Biobank'. As recent scandals such as Alder Hey have emphasised, there are complex issues concerning the informed consent of donors that need to be carefully considered. However, we believe that a preoccupation with informed consent obscures important questions about the purposes to which such collections are put, not least that they may be only haphazardly used for research (especially that of commercial interest)--an end that would not fairly reflect the original altruistic motivation of donors, and the trust they must invest. We therefore argue that custodians of such databases take on a weighty pro-active duty, to encourage public debate about the ends of such collections and to sponsor research that reflects publicly agreed priorities and provides public benefits.

Altruism↗

PubMed2026

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗

PubMed2004

Collaborative design for automated DNA storage that allows for rapid, accurate, large-scale studies.

Genomics Collaborative, Inc., a division of Sera Care Life Sciences, Inc. (Cambridge, MA), is among the first commercial entities in the world to enable genetic research on an industrial scale via its Large Scale Global Repository, a biobank of human specimens collected for research purposes. With the demand for large-scale DNA studies increasing, decisions about the strategic direction of sample storage and collection must be made to create a sound plan to support continued demands for drug discovery. Reported here is the approach used by Genomics Collaborative to automate its DNA processing, storage, and retrieval.

Automation↗

PubMed2006

Implications of small effect sizes of individual genetic variants on the design and interpretation of genetic association studies of complex diseases.

Accumulated evidence from searching for candidate gene-disease associations of complex diseases can offer some insights as the field moves toward discovery-oriented approaches with massive genome-wide testing. Meta-analyses of 50 non-human lymphocyte antigen gene-disease associations with documented overall statistical significance (752 studies) show summary odds ratios with a median of 1.43 (interquartile range, 1.28-1.65). Many different biases may operate in this field, for both single studies and meta-analyses, and these biases could invalidate some of these seemingly "validated" associations. Studies with a sample size of >500 show a median odds ratio of only 1.15. The median sample size required to detect the observed summary effects in each population addressed in the 752 studies is estimated to be 3,535 (interquartile range, 1,936-9,119 for cases and controls combined). These estimates are steeply inflated in the presence of modest bias. Population heterogeneity, as well as gene-gene and gene-environment interactions, could steeply increase these estimates and may be difficult to address even by very large biobanks and observational cohorts. The one visible solution is for a large number of teams to join forces on the same research platforms. These collaborative studies ideally should be designed up front to also assess more complex gene-gene and gene-environment interactions.

Alleles↗