Biology subjects

Milieu Interieur Consortium,

Publications and source records attributed to Milieu Interieur Consortium,.

4 recordsLinked to original sources

bioRxiv2026

Taxonomic-free metagenome GWAS to identify gut microbiome functions influencing host phenotypes

Genome-wide association studies (GWAS) have been pivotal for uncovering the genetics of human phenotypes, and there is now growing interest in applying GWAS-like methods to explore the role of the microbiome in human health. Here, we developed a taxonomy free GWAS approach that uses k-mers, i.e. DNA words of length k that can capture single nucleotide polymorphisms, insertion or deletion events, and gene presence-absence, to interrogate the gut microbiome. We applied this method to 26 traits spanning demographics, physiological measurements, health, and lifestyle in 938 healthy participants from the Milieu Interieur cohort. We generated a k-mer abundance matrix encompassing 97 million distinct k-mers. GWAS of the 26 traits identified significant associations for seven of them: age, sex, depression, appetite, cooked meat consumption, soda intake, and smoking. By modeling the correlation structure among k-mers, we identified a modest number of independent signals and conducted a comprehensive in silico functional annotation of these signals, revealing potential mechanisms of host-microbiota interaction. Overall, our analyses demonstrate that k-mers can capture biologically relevant functions shared across multiple taxa and provide a refined modeling framework that complements the standard taxonomic-based screening approach.

microbiology↗

bioRxiv2025

Identification and Functional Characterization of Regulatory Variants in DPP9 Associated with COVID-19 Severity

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to a wide-range of clinical outcomes, which have been extensively studied through genome-wide association studies (GWAS). Starting from lead genetic variants associated with COVID-19 infection and severity, we identified a subset of non-coding candidate variants with potential regulatory functions. Using bioinformatics analysis and functional screening in three cell lines, we prioritized two DPP9 variants within a haplotype that increases the risk of severe COVID-19. This haplotype exhibited increased regulatory activity and altered transcription factor binding, suggesting its role in influencing COVID-19 severity through modulation of DPP9 expression in immune and lung cell types. The interest of our study lies in the functional characterization of regulatory variants responsible for the higher levels of DPP9 and lung damage observed in patients with severe COVID-19. These findings advance our understanding of genetic risk factors for COVID-19 and highlight functional SNPs that may guide future therapeutic research.

genetics↗

bioRxiv2023

A multivariate outcome test of covariance

Multivariate analysis is becoming central in studies investigating high-throughput molecular data, yet, some important features of these data are seldom explored. Here, we present MANOCCA (Multivariate Analysis of Conditional CovAriance), a powerful method to test for the effect of a predictor on the covariance matrix of a multivariate outcome. The proposed test is by construction orthogonal to tests based on the mean and variance, and is able to capture effects that are missed by both approaches. We first compare the performances of MANOCCA with existing correlation-based methods and show that MANOCCA is the only test correctly calibrated in simulation mimicking omics data. We then investigate the impact of reducing the dimensionality of the data using principal component analysis when the sample size is smaller than the number of pairwise covariance terms analysed. We show that, in many realistic scenarios, the maximum power can be achieved with a limited number of components. Finally, we apply MANOCCA to 1,000 healthy individuals from the Milieu Interieur cohort, to assess the effect of health, lifestyle and genetic factors on the covariance of two sets of phenotypes, blood biomarkers and flow cytometry-based immune phenotypes. Our analyses identify significant associations between multiple factors and the covariance of both omics data.

bioinformatics↗

bioRxiv2023

High-dimensional spectral cytometry panels for whole blood immune phenotyping

The need to understand the mechanisms and pathways of immune responses in pathogenic conditions such as cancer and autoimmunity requires awareness of natural immune variability in healthy subjects. To this end, various systems immunology studies have been established. Among them, the Milieu Interieur (MI) study was established to define the boundaries of a healthy immune response and identify determinants of immune response variation. MI used immunophenotyping of a 1000 healthy donor cohort by flow cytometry as a principal outcome for immune variance at steady state. For the 10-year longitudinal MI study, we have developed two high-dimensional spectral flow cytometry panels that allow deep characterization of innate and adaptive whole blood immune cells (35 and 34 fluorescent markers, respectively) and standardized the protocol for sample handling, staining, acquisition, and data analysis. This permits the reproducible quantification of over 182 immune cell phenotypes through robust immunophenotyping at a single site. This highly standardized protocol was applied to samples from patients with autoimmune/inflammatory diseases. It is currently used for characterization of the impact of age and environmental factors on peripheral blood immune phenotypes of >400 donors from the initial MI cohort.

immunology↗