ClustAll: An R package for patient stratification in complex diseases.

In the era of precision medicine, it is necessary to understand heterogeneity among patients with complex diseases to improve personalized prevention and management strategies. Here, we introduce ClustAll, a Bioconductor package designed for unsupervised patient stratification using clinical data. ClustAll is based on the previously validated methodology ClustAll, a clustering framework that effectively handles intricacies in clinical data, including mixed data types, missing values, and collinearity.

Reviewability and supportability: New complementary principles to empower research software practices.

In today's scientific landscape, research software has evolved from being a supportive tool to becoming a fundamental driver of discovery, particularly in life sciences. Beyond its roots in software engineering, research software now plays a crucial role in facilitating efficient data analysis and enabling the exploration of complex natural phenomena. The advancements in simulations and modeling through research software have significantly accelerated the pace of scientific research while reducing associated costs.

A comparative analysis of blastoid models through single-cell transcriptomics.

Pluripotent-stem-cell-derived blastocyst-like structures (blastoids) offer insights into early human embryogenesis (5-10 days post-fertilization). The similarity between blastoids and human blastocysts remains uncertain. To investigate, we evaluated single-cell RNA sequencing (scRNAseq) data from seven blastoid models, comparing them to peri-implantation blastocysts.

Competition shapes the landscape of X-chromosome-linked genetic diversity.

X chromosome inactivation (XCI) generates clonal heterogeneity within XX individuals. Combined with sequence variation between human X chromosomes, XCI gives rise to intra-individual clonal diversity, whereby two sets of clones express mutually exclusive sequence variants present on one or the other X chromosome. Here we ask whether such clones merely co-exist or potentially interact with each other to modulate the contribution of X-linked diversity to organismal development.

Global compositional and functional states of the human gut microbiome in health and disease.

The human gut microbiota is of increasing interest, with metagenomics a key tool for analyzing bacterial diversity and functionality in health and disease. Despite increasing efforts to expand microbial gene catalogs and an increasing number of metagenome-assembled genomes, there have been few pan-metagenomic association studies and in-depth functional analyses across different geographies and diseases. Here, we explored 6014 human gut metagenome samples across 19 countries and 23 diseases by performing compositional, functional cluster, and integrative analyses.

A robust clustering strategy for stratification unveils unique patient subgroups in acutely decompensated cirrhosis.

Background: Patient heterogeneity poses significant challenges for managing individuals and designing clinical trials, especially in complex diseases. Existing classifications rely on outcome-predicting scores, potentially overlooking crucial elements contributing to heterogeneity without necessarily impacting prognosis.

Methods: To address patient heterogeneity, we developed ClustALL, a computational pipeline that simultaneously faces diverse clinical data challenges like mixed types, missing values, and collinearity.

HLA-based banking of induced pluripotent stem cells in Saudi Arabia.

Background: Human iPSCs' derivation and use in clinical studies are transforming medicine. Yet, there is a high cost and long waiting time associated with autologous iPS-based cellular therapy, and the genetic engineering of hypo-immunogenic iPS cell lines is hampered with numerous hurdles. Therefore, it is increasingly interesting to create cell stocks based on HLA haplotype distribution in a given population.

Microbiome-based risk prediction in incident heart failure: a community challenge.

Heart failure (HF) is a major public health problem. Early identification of at-risk individuals could allow for interventions that reduce morbidity or mortality. The community-based FINRISK Microbiome DREAM challenge (synapse.

Serum methylation of GALNT9, UPF3A, WARS, and LDB2 as noninvasive biomarkers for the early detection of colorectal cancer and advanced adenomas.

Background: Early detection has proven to be the most effective strategy to reduce the incidence and mortality of colorectal cancer (CRC). Nevertheless, most current screening programs suffer from low participation rates. A blood test may improve both the adherence to screening and the selection to colonoscopy.

Preclinical models for prediction of immunotherapy outcomes and immune evasion mechanisms in genetically heterogeneous multiple myeloma.

The historical lack of preclinical models reflecting the genetic heterogeneity of multiple myeloma (MM) hampers the advance of therapeutic discoveries. To circumvent this limitation, we screened mice engineered to carry eight MM lesions (NF-κB, KRAS, MYC, TP53, BCL2, cyclin D1, MMSET/NSD2 and c-MAF) combinatorially activated in B lymphocytes following T cell-driven immunization. Fifteen genetically diverse models developed bone marrow (BM) tumors fulfilling MM pathogenesis.

Palidis: fast discovery of novel insertion sequences.

The diversity of microbial insertion sequences, crucial mobile genetic elements in generating diversity in microbial genomes, needs to be better represented in current microbial databases. Identification of these sequences in microbiome communities presents some significant problems that have led to their underrepresentation. Here, we present a bioinformatics pipeline called Palidis that recognizes insertion sequences in metagenomic sequence data rapidly by identifying inverted terminal repeat regions from mixed microbial community genomes.

scAEGAN: Unification of single-cell genomics data by adversarial learning of latent space correspondences.

Recent progress in Single-Cell Genomics has produced different library protocols and techniques for molecular profiling. We formulate a unifying, data-driven, integrative, and predictive methodology for different libraries, samples, and paired-unpaired data modalities. Our design of scAEGAN includes an autoencoder (AE) network integrated with adversarial learning by a cycleGAN (cGAN) network.

Uncovering perturbations in human hematopoiesis associated with healthy aging and myeloid malignancies at single-cell resolution.

Early hematopoiesis is a continuous process in which hematopoietic stem and progenitor cells (HSPCs) gradually differentiate toward specific lineages. Aging and myeloid malignant transformation are characterized by changes in the composition and regulation of HSPCs. In this study, we used single-cell RNA sequencing (scRNA-seq) to characterize an enriched population of human HSPCs obtained from young and elderly healthy individuals.

RNA-sequencing and mass-spectrometry proteomic time-series analysis of T-cell differentiation identified multiple splice variants models that predicted validated protein biomarkers in inflammatory diseases.

Profiling of mRNA expression is an important method to identify biomarkers but complicated by limited correlations between mRNA expression and protein abundance. We hypothesised that these correlations could be improved by mathematical models based on measuring splice variants and time delay in protein translation. We characterised time-series of primary human naïve CD4 T cells during early T helper type 1 differentiation with RNA-sequencing and mass-spectrometry proteomics.

Epigenetic clock indicates accelerated aging in glial cells of progressive multiple sclerosis patients.

Background: Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative disease of the central nervous system (CNS) characterized by irreversible disability at later progressive stages. A growing body of evidence suggests that disease progression depends on age and inflammation within the CNS. We aimed to investigate epigenetic aging in bulk brain tissue and sorted nuclei from MS patients using DNA methylation-based epigenetic clocks.

The Regulators of Peroxisomal Acyl-Carnitine Shuttle CROT and CRAT Promote Metastasis in Melanoma.

Circulating tumor cells are the key link between a primary tumor and distant metastases, but once in the bloodstream, loss of adhesion induces cell death. To identify the mechanisms relevant for melanoma circulating tumor cell survival, we performed RNA sequencing and discovered that detached melanoma cells and isolated melanoma circulating tumor cells rewire lipid metabolism by upregulating fatty acid (FA) transport and FA beta-oxidation‒related genes. In patients with melanoma, high expression of FA transporters and FA beta-oxidation enzymes significantly correlates with reduced progression-free and overall survival.

Alterations in the Oral Microbiome Associated With Diabetes, Overweight, and Dietary Components.

The Mediterranean diet (MedDiet) represents the traditional food consumption patterns of people living in countries bordering the Mediterranean Sea and is associated with a reduced incidence of obesity and type-2 diabetes mellitus (T2DM). The objective of this study was to examine differences in the composition of the oral microbiome in older adults with T2DM and/or high body mass index (BMI) and whether the microbiome was influenced by elements of a MedDiet. Using a nested case-control design individuals affected by T2DM were selected from the Seniors-ENRICA-2 cohort concurrently with non-diabetic controls.

Deconvolution of the hematopoietic stem cell microenvironment reveals a high degree of specialization and conservation.

Understanding the regulation of normal and malignant human hematopoiesis requires comprehensive cell atlas of the hematopoietic stem cell (HSC) regulatory microenvironment. Here, we develop a tailored bioinformatic pipeline to integrate public and proprietary single-cell RNA sequencing (scRNA-seq) datasets. As a result, we robustly identify for the first time 14 intermediate cell states and 11 stages of differentiation in the endothelial and mesenchymal BM compartments, respectively.

Data-driven bioinformatics to disentangle cells within a tissue microenvironment.

Molecular profiling of clinical tissue samples is at the core of precision medicine. Yet, to elucidate the contribution of mixed cell types and detect changes in cell populations in response to infections or drugs is challenging. Recent advances using machine learning promise to learn explanatory models directly from data.

DNA methylation changes in glial cells of the normal-appearing white matter in Multiple Sclerosis patients.

Multiple Sclerosis (MS), the leading cause of non-traumatic neurological disability in young adults, is a chronic inflammatory and neurodegenerative disease of the central nervous system (CNS). Due to the poor accessibility to the target organ, CNS-confined processes underpinning the later progressive form of MS remain elusive thereby limiting treatment options. We aimed to examine DNA methylation, a stable epigenetic mark of genome activity, in glial cells to capture relevant molecular changes underlying MS neuropathology.

Deep characterization of paired chromatin and transcriptomes in four immune cell types from multiple sclerosis patients.

The putative involvement of chromatin states in multiple sclerosis (MS) is thus far unclear. Here we determined the association of chromatin-accessibility with concurrent genetic, epigenetic and transcriptional events. We generated paired assay for transposase-accessible chromatin sequencing and RNA-sequencing profiles from sorted blood immune CD4 and CD8 T cells, CD14 monocytes and CD19 B cells from healthy controls (HCs) and MS patients.