Distinct Biological Processes Research Articles

Biochemical markers in hand osteoarthritis: a path to precision medicine.

Hand osteoarthritis (HOA) is a heterogeneous joint disease with high radiographic and symptomatic prevalence. The diagnosis of HOA is based on clinical and radiographic features. The identification of potential biomarkers for diagnosis, prognosis, disease severity assessment, and therapeutic efficacy evaluation of НОА remains an active area of research. To summarize the eligible biomarker data, a comprehensive narrative review was performed using the PubMed and Scopus databases covering publications from inception to December 2024. Our search uncovered five distinct groups of biomarkers associated with HOA, categorized based on their origin and involvement in distinct biological processes: (1) cartilage synthesis and catabolism, (2) bone remodeling, (3) inflammation, (4) adipokines, and (5) others classified separately. Each biomarker was evaluated in accordance with the Burden of disease, Investigative, Prognostic, Efficacy of intervention, and Diagnostic (BIPED) criteria. In conclusion, no biomarker has yet demonstrated sufficient sensitivity, specificity, or reproducibility to meet the BIPED criteria for classification. The early diagnosis and treatment of HOA require the development of more sensitive assays, advanced platforms, and rigorous bio-clinical trials to stratify previously studied biomarkers and identify novel ones. Precision medicine in HOA demands reliable biomarkers, cost-effective assays, and standardized, reproducible methodologies for global applicability.

Prediction of clinical prognosis and drug sensitivity in hepatocellular carcinoma through the combination of multiple cell death pathways.

Hepatocellular carcinoma (HCC) is the sixth most common malignant tumor, highlighting a significant need for reliable predictive models to assess clinical prognosis, disease progression, and drug sensitivity. Recent studies have highlighted the critical role of various programmed cell death pathways, including apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, NETotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, in tumor development. Therefore, by investigating these pathways, we aimed to develop a predictive model for HCC prognosis and drug sensitivity. We analyzed transcriptome, single-cell transcriptome, genomic, and clinical information using data from the TCGA-LIHC, GSE14520, GSE45436, and GSE166635 datasets. Machine learning algorithms were used to establish a cell death index (CDI) with seven gene signatures, which was validated across three independent datasets, showing that high CDI correlates with poorer prognosis. Unsupervised clustering revealed three molecular subtypes of HCC with distinct biological processes. Furthermore, a nomogram integrating CDI and clinical information demonstrated good predictive performance. CDI was associated with immune checkpoint genes and tumor microenvironment components using single-cell transcriptome analysis. Drug sensitivity analysis indicated that patients with high CDI may be resistant to oxaliplatin and cisplatin but sensitive to axitinib and sorafenib. In summary, our model offers a precise prediction of clinical outcomes and drug sensitivity for patients with HCC, providing valuable insights for personalized treatment strategies.

Biological sex, microglial signaling pathways, and radiation exposure shape cortical proteomic profiles and behavior in mice

Patients receiving cranial radiation therapy experience tissue damage and cognitive deficits that severely decrease their quality of life. Experiments in rodent models show that these adverse neurological effects are in part due to functional changes in microglia, the resident immune cells of the central nervous system. Increasing evidence suggests that experimental manipulation of microglial signaling can regulate radiation-induced changes in the brain and behavior. Furthermore, many studies show sex-dependent neurological effects of radiation exposure. Despite this, few studies have used both males and females to explore how sex and microglial function interact to influence radiation effects on the brain. Here, we used a system levels approach to examine how deficiencies in purinergic and fractalkine signaling, two important microglial signaling pathways, impact brain proteomic and behavioral profiles in irradiated and control male and female mice. We performed a comprehensive analysis of the cortical proteomes from irradiated and control C57BL/6J, P2Y12−/−, and CX3CR1−/− mice of both sexes using multiple bioinformatics methods. We identified distinct proteins and biological processes, as well as behavioral profiles, regulated by sex, genotype, radiation exposure, and their interactions. Disrupting microglial signaling, had the greatest impact on proteomic expression, with CX3CR1−/− mice showing the most distinct proteomic profile characterized by upregulation of CX3CL1. Surprisingly, radiation exposure caused relatively smaller proteomic changes in glial and synaptic proteins, including Rgs10, Crybb1, C1qa, and Hexb. While we observed some radiation effects on locomotor behavior, biological sex as well as loss of P2Y12 and CX3CR1 signaling had a stronger influence on locomotor outcomes in our model. Lastly, loss of P2Y12 and CX3CR1 strongly regulated exploratory behaviors. Overall, our findings provide novel insights into the molecular pathways and proteins that are linked to P2Y12 and CX3CR1 signaling, biological sex, radiation exposure, and their interactions.

Prediction of the Survival Status, Immunotherapy Response, and Medication of Lung Adenocarcinoma Patients Based on Hypoxia- and Apoptosis-Related Genes.

To predict patient survival prognosis, we aimed to establish a novel set of gene features associated with hypoxia and apoptosis. RNA-seq and clinical data of LUAD were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, while hypoxia and apoptosis-related genes were obtained from the Molecular Signatures Database (MsigDB). A 13-gene-prognostic model incorporating hypoxia and apoptosis genes was developed using univariate/multivariate Cox regression, Nonnegative Matrix Factorization (NMF) clustering, and LASSO regression. Patients were divided into high-risk (HR) and low-risk (LR) groups according to the median risk score. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed distinct biological processes between HR and LR groups, including hormone regulation and lipid metabolism pathways. Single sample gene set enrichment analysis (ssGSEA) indicated elevated cell infiltration levels of Neutrophils and T_helper_cells in the LR group, while NK cells and Th1cells were higher in the HR group. Immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) analyses suggested potential benefits of immunotherapy for LR group patients. In conclusion, this prognostic feature integrating hypoxia- and apoptosis-related genes offers insights into predicting survival, immune status, and treatment response in LUAD patients, paving the way for personalized treatment strategies.

Integration of Single-Cell and Spatial Transcriptomic Data Reveals Spatial Architecture and Potential Biomarkers in Alzheimer's Disease.

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by the gradual loss of neurons and the accumulation of amyloid plaques and neurofibrillary tangles. Despite advancements in the understanding of AD's pathophysiology, the cellular organization and interactions in the prefrontal cortex (PFC) remain elusive. Eight single-cell RNA sequencing (scRNA-seq) datasets from both normal controls and individuals with AD were harmonized. Stringent preprocessing protocols were implemented to uphold dataset integrity. Unsupervised clustering and annotation revealed 22 distinct cell clusters corresponding to 19 unique cell types. The spatial architecture of the PFC region was constructed using the CARD tool. Further analyses encompassed trajectory examination of Oligodendrocyte subtypes, evaluation of regulon activity scores, and spot clustering within white matter regions (WM). Differential expression analysis and functional enrichment assays unveiled molecular signatures linked to AD progression and were validated using microarray data sourced from neurodegenerative disorder patients. Our investigation employs scRNA-seq and spatial transcriptomics to uncover the cellular atlas and spatial architecture of the human PFC in AD. Moreover, our results indicate that Oligodendrocytes are more prevalent in AD patients, showcasing diverse subtypes and spatial organization within WM regions. Each subtype appears to be associated with distinct biological processes and transcriptional regulators, shedding light on their involvement in AD pathology. Notably, the Oligodendrocyte_C6 subtype is linked to neurological damage in AD patients, characterized by heightened expression of genes involved in cell-cell connections, cell membrane stability, and myelination. Additionally, 12 target genes regulated by NFIA were identified, which are upregulated in AD patients and associated with disease progression. Elevated PLXDC2 expression in peripheral blood was also identified, suggesting its potential as a non-invasive biomarker for early AD detection. Our study provides novel insights into the role of Oligodendrocytes in AD and highlights the potential of PLXDC2 as a blood biomarker for non-invasive diagnosis and monitoring of AD patients.

Effect of Sulfur Contents on Polycyclic Aromatic Compounds in Low-Rank Bituminous Coals

Different coal seams go through distinct biological, physical, and chemical processes. Polycyclic aromatic compounds (PACs) in coal may retain information about these processes, especially in low-rank bituminous coals. Three coal seams with different sulfur contents from the Ningwu Coalfield were studied to understand the relation of different sulfur contents with PAC formation in low-rank bituminous coals. Coal samples were extracted by solvent and separated using liquid chromatography. The collected aromatic hydrocarbon fractions were analyzed by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS). A total of 27 sulfur-containing PACs (SPACs) were identified in the high-sulfur samples, whereas only 8 SPACs were found in the low-sulfur coal and middle-sulfur coal. The total SPACs to total PACs ratios (T-SPACs/T-PACs) are 1.15%, 2.17%, and 10.65% in the low-sulfur, middle-sulfur, and high-sulfur coal, respectively. The variations of SPAC species and their content ratios indicate that SPAC formation is controlled by the sulfur contents in the low-rank bituminous coals. A total of 18 oxygen-containing PACs (OPACs) were identified in the low-sulfur coal and middle-sulfur coal, whereas only 11 OPACs were found in the high-sulfur samples. The average ratios of OPACs to the identified aromatic compounds (T-OPACs/T-PACs) are 9.81%, 9.62%, and 6.91% in the low-, middle-, and high-sulfur coals, exhibiting a negative correlation with sulfur contents and indicating that OPACs were also influenced by sulfur contents in low-rank bituminous coals. The ratios of total contents of polycyclic aromatic hydrocarbons (PAHs) to total PACs (T-PAHs/T-PACs) are 89.1%, 88.2%, and 82.0% in the low-, middle-, and high-sulfur coals, respectively, indicating a decreasing trend from low- and middle-sulfur coal to high-sulfur coal. This variation could be caused by the reaction of PAHs and sulfur to form SPACs.

Alternative splicing perspective to prey preference of environmentally friendly biological agent Cryptolaemus montrouzieri

BackgroundCryptolaemus montrouzieri (Coccinellidae) is widely utilized as biological control agents in modern agriculture. A comprehensive understanding of its food preference can help guide mass rearing and safety management during field application of pest control. Although some studies have paid attentions to the impacts of prey shift on C. montrouzieri, little is known regarding the role of post-transcriptional regulations in its acclimation to unnatural preys.ResultsWe performed a genome-wide investigation on alternative splicing dynamics in C. montrouzieri in response to the predation transition from natural prey to unnatural ones. When feeding on undesired diets, 402–764 genes were differentially alternative spliced in C. montrouzieri. It is noteworthy that the majority of these genes (> 87%) were not differentially expressed, and these differentially spliced genes regulated distinct biological processes from differentially expressed genes, such as organ development and morphogenesis, locomotory behavior, and homeostasis processes. These suggested the functionally nonredendant role of alternative splicing in modulating physiological and metabolic responses of C. montrouzieri to the shift to undesired preys. In addition, the individuals feeding on aphids were subject to a lower level of changes in splicing than other alternative diets, which might be because of the similar chemical and microbial compositions. Our study further suggested a putative coupling of alternative splicing and nonsense-mediated decay (AS-NMD), which may play an important role in fine-tuning the protein repertoire of C. montrouzieri, and promoting its acclimation to predation changes.ConclusionThese findings highlight the key role of alternative splicing in modulating the acclimation of ladybirds to prey shift and provide new genetic clues for the future application of ladybirds in biocontrol.

Chromatin remodeling in tissue stem cell fate determination.

Tissue stem cells (TSCs), which reside in specialized tissues, constitute the major cell sources for tissue homeostasis and regeneration, and the contribution of transcriptional or epigenetic regulation of distinct biological processes in TSCs has been discussed in the past few decades. Meanwhile, ATP-dependent chromatin remodelers use the energy from ATP hydrolysis to remodel nucleosomes, thereby affecting chromatin dynamics and the regulation of gene expression programs in each cell type. However, the role of chromatin remodelers in tissue stem cell fate determination is less well understood. In this review, we systematically discuss recent advances in epigenetic control by chromatin remodelers of hematopoietic stem cells, intestinal epithelial stem cells, neural stem cells, and skin stem cells in their fate determination and highlight the importance of their essential role in tissue homeostasis, development, and regeneration. Moreover, the exploration of the molecular and cellular mechanisms of TSCs is crucial for advancing our understanding of tissue maintenance and for the discovery of novel therapeutic targets.

Multi‑omics identification of a signature based on malignant cell-associated ligand–receptor genes for lung adenocarcinoma

PurposeLung adenocarcinoma (LUAD) significantly contributes to cancer-related mortality worldwide. The heterogeneity of the tumor immune microenvironment in LUAD results in varied prognoses and responses to immunotherapy among patients. Consequently, a clinical stratification algorithm is necessary and inevitable to effectively differentiate molecular features and tumor microenvironments, facilitating personalized treatment approaches.MethodsWe constructed a comprehensive single-cell transcriptional atlas using single-cell RNA sequencing data to reveal the cellular diversity of malignant epithelial cells of LUAD and identified a novel signature through a computational framework coupled with 10 machine learning algorithms. Our study further investigates the immunological characteristics and therapeutic responses associated with this prognostic signature and validates the predictive efficacy of the model across multiple independent cohorts.ResultsWe developed a six-gene prognostic model (MYO1E, FEN1, NMI, ZNF506, ALDOA, and MLLT6) using the TCGA-LUAD dataset, categorizing patients into high- and low-risk groups. This model demonstrates robust performance in predicting survival across various LUAD cohorts. We observed distinct molecular patterns and biological processes in different risk groups. Additionally, analysis of two immunotherapy cohorts (N = 317) showed that patients with a high-risk signature responded more favorably to immunotherapy compared to those in the low-risk group. Experimental validation further confirmed that MYO1E enhances the proliferation and migration of LUAD cells.ConclusionWe have identified malignant cell-associated ligand–receptor subtypes in LUAD cells and developed a robust prognostic signature by thoroughly analyzing genomic, transcriptomic, and immunologic data. This study presents a novel method to assess the prognosis of patients with LUAD and provides insights into developing more effective immunotherapies.

TEX264 drives selective autophagy of DNA lesions to promote DNA repair and cell survival

DNA repair and autophagy are distinct biological processes vital for cell survival. Although autophagy helps maintain genome stability, there is no evidence of its direct role in the repair of DNA lesions. We discovered that lysosomes process topoisomerase 1 cleavage complexes (TOP1cc) DNA lesions in vertebrates. Selective degradation of TOP1cc by autophagy directs DNA damage repair and cell survival at clinically relevant doses of topoisomerase 1 inhibitors. TOP1cc are exported from the nucleus to lysosomes through a transient alteration of the nuclear envelope and independent of the proteasome. Mechanistically, the autophagy receptor TEX264 acts as a TOP1cc sensor at DNA replication forks, triggering TOP1cc processing by the p97 ATPase and mediating the delivery of TOP1cc to lysosomes in an MRE11-nuclease- and ATR-kinase-dependent manner. We found an evolutionarily conserved role for selective autophagy in DNA repair that enables cell survival, protects genome stability, and is clinically relevant for colorectal cancer patients.

APOBEC family reshapes the immune microenvironment and therapy sensitivity in clear cell renal cell carcinoma

Emerging evidence suggests that the APOBEC family is implicated in multiple cancers and might be utilized as a new target for cancer detection and treatment. However, the dysregulation and clinical implication of the APOBEC family in clear cell renal cell cancer (ccRCC) remain elusive. TCGA multiomics data facilitated a comprehensive exploration of the APOBEC family across cancers, including ccRCC. Remodeling analysis classified ccRCC patients into two distinct subgroups: APOBEC family pattern cancer subtype 1 (APCS1) and subtype 2 (APCS2). The study investigated differences in clinical parameters, tumor immune microenvironment, therapeutic responsiveness, and genomic mutation landscapes between these subtypes. An APOBEC family-related risk model was developed and validated for predicting ccRCC patient prognosis, demonstrating good sensitivity and specificity. Finally, the overview of APOBEC3B function was investigated in multiple cancers and verified in clinical samples. APCS1 and APCS2 demonstrated considerably distinct clinical features and biological processes in ccRCC. APCS1, an aggressive subtype, has advanced clinical stage and a poor prognosis. APCS1 exhibited an oncogenic and metabolically active phenotype. APCS1 also exhibited a greater tumor mutation load and immunocompromised condition, resulting in immunological dysfunction and immune checkpoint treatment resistance. The genomic copy number variation of APCS1, including arm gain and loss, was much more than that of APCS2, which may help explain the tired immune system. Furthermore, the two subtypes have distinct drug sensitivity patterns in clinical specimens and matching cell lines. Finally, we developed a predictive risk model based on subtype biomarkers that performed well for ccRCC patients and validated the clinical impact of APOBEC3B. Aberrant APOBEC family expression patterns might modify the tumor immune microenvironment by increasing the genome mutation frequency, thus inducing an immune-exhausted phenotype. APOBEC family-based molecular subtypes could strengthen the understanding of ccRCC characterization and guide clinical treatment. Targeting APOBEC3B may be regarded as a new therapeutic target for ccRCC.

A scoping review regarding reproductive capacity modulation based on alpha-ketoglutarate supplementation.

Alpha-ketoglutarate is a common metabolite in the tricarboxylic acid cycle and is central in modulating the reproductive potential in animal models. The present scoping review systematically covers the spectrum of a wide range of evidence from different viewpoints, focusing on the underlying processes and mechanisms of the developmental framework, aiming to fill the gaps within the existing literature. Alpha-ketoglutarate is an important intermediate molecule in the tricarboxylic acid cycle with a prominent role in distinct biological processes such as cellular energy metabolism, epigenetic regulation, and signaling pathways. We conducted a registered scoping review (OSF: osf.io/b8nyt) to explore the impact of exogenous supplementation on reproductive capabilities. Our strategy included evaluating the main research literature from different databases like PubMed-MEDLINE, Web of ScienceTM, Scopus, and Excerpta Medica dataBASE using a specific systematic layout to encompass all investigations based on experimental models and critically compare the results. Twenty-one studies were included in the main body of this manuscript, which revealed that exogenous supplementation induced dose- and sex-dependent modifications. This metabolite modulates the expression of pluripotency genes, thus controlling stem cells' self-renewal, differentiation, and reprogramming dynamics, while also alleviating structural transformations induced by exposure to heavy metals and other inhibitors. This significantly demonstrated a direct influence of alpha-ketoglutarate in mitigating oxidative stress and prolonging the lifespan, consequently supporting metabolic and endocrine adjustments. It influences oocyte quality and quantity, delays reproductive aging, and establishes an optimal competence framework for development with minimal risk of failure. Therefore, alpha-ketoglutarate is linked to improving reproductive performance, but further studies are needed due to a lack of studies on humans.

Decomposition of phenotypic heterogeneity in autism reveals distinct and coherent genetic programs.

Unraveling the phenotypic and genetic complexity of autism is extremely challenging yet critical for understanding the biology, inheritance, trajectory, and clinical manifestations of the many forms of the condition. Here, we leveraged broad phenotypic data from a large cohort with matched genetics to characterize classes of autism and their patterns of core, associated, and co-occurring traits, ultimately demonstrating that phenotypic patterns are associated with distinct genetic and molecular programs. We used a generative mixture modeling approach to identify robust, clinically-relevant classes of autism which we validate and replicate in a large independent cohort. We link the phenotypic findings to distinct patterns of de novo and inherited variation which emerge from the deconvolution of these genetic signals, and demonstrate that class-specific common variant scores strongly align with clinical outcomes. We further provide insights into the distinct biological pathways and processes disrupted by the sets of mutations in each class. Remarkably, we discover class-specific differences in the developmental timing of genes that are dysregulated, and these temporal patterns correspond to clinical milestone and outcome differences between the classes. These analyses embrace the phenotypic complexity of children with autism, unraveling genetic and molecular programs underlying their heterogeneity and suggesting specific biological dysregulation patterns and mechanistic hypotheses.

DNA damage-associated protein co-expression network in cardiomyocytes informs on tolerance to genetic variation and disease.

Cardiovascular disease (CVD) is associated with both genetic variants and environmental factors. One unifying consequence of the molecular risk factors in CVD is DNA damage, which must be repaired by DNA damage response proteins. However, the impact of DNA damage on global cardiomyocyte protein abundance, and its relationship to CVD risk remains unclear. We therefore treated induced pluripotent stem cell-derived cardiomyocytes with the DNA-damaging agent Doxorubicin (DOX) and a vehicle control, and identified 4,178 proteins that contribute to a network comprising 12 co-expressed modules and 403 hub proteins with high intramodular connectivity. Five modules correlate with DOX and represent distinct biological processes including RNA processing, chromatin regulation and metabolism. DOX-correlated hub proteins are depleted for proteins that vary in expression across individuals due to genetic variation but are enriched for proteins encoded by loss-of-function intolerant genes. While proteins associated with genetic risk for CVD, such as arrhythmia are enriched in specific DOX-correlated modules, DOX-correlated hub proteins are not enriched for known CVD risk proteins. Instead, they are enriched among proteins that physically interact with CVD risk proteins. Our data demonstrate that DNA damage in cardiomyocytes induces diverse effects on biological processes through protein co-expression modules that are relevant for CVD, and that the level of protein connectivity in DNA damage-associated modules influences the tolerance to genetic variation.

ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities.

High-throughput technologies yield a broad spectrum of multi-omics datasets, which offer unparalleled insights into complex biological systems. However, effectively analyzing this diverse array of data presents challenges, considering factors such as species diversity, data types, costs, and limitations of the available tools. Herein, we present ExpOmics, a comprehensive web platform featuring 7 applications and 4 toolkits, with 28 customizable analysis functions spanning various analyses of differential expression, co-expression, Weighted Gene Co-expression Network Analysis (WGCNA), feature selection, and functional enrichment. ExpOmics allows users to upload and explore multi-omics data without organism restrictions, supporting various expression data, including genes, mRNAs, lncRNAs, miRNAs, circRNAs, piRNAs, and proteins and is compatible with diverse gene nomenclatures and expression values. Moreover, ExpOmics enables users to analyze 22427 transcriptomic datasets of 196 cancer subtypes sourced from 63 projects of The Cancer Genome Atlas Program (TCGA) to identify cancer biomarkers. The analysis results from ExpOmics are presented in high-quality graphical formats suitable for publication and are available for free download. A case study using ExpOmics identified two potential oncogenes, SERPINE1 and SLC43A1, that may regulate colorectal cancer through distinct biological processes. In summary, ExpOmics can serves as a robust platform for global researchers to explore multi-omics data, gain biological insights, and formulate testable hypotheses. ExpOmics is available at http://www.biomedical-web.com/expomics.

Molecular mechanisms underlying stress vulnerability and resilience in the chronic mild stress model: New insights from mRNA and miRNAs data combining

Stress is a major risk factor for the development of psychiatric disorders, including depression. However, its effects are not the same in all the subjects as only a portion of individuals exposed to stress will eventually develop negative mental outcomes, while others can be considered resilient. However, the biological processes underlying the development of a vulnerable or resilient phenotype are still poor understood. In order to cover this, we here used both transcriptomic and miRNomic based approaches in the ventral hippocampus of control (CON) and rats exposed to the chronic mild stress (CMS) paradigm, which were then divided into vulnerable (VULN) or resilient (RES) animals according to the sucrose consumption test.Transcriptomic analyses in VULN rats, compared to both the group of CON and RES animals, revealed the activation of inflammatory/immune-related pathways, specifically involved in antibodies and cytokine production, and the inhibition of pathways involved in protein synthesis. Conversely, transcriptomic data in RES animals suggested the activation of several pathways involved in neurotransmission.We then performed a mRNA-miRNA integration analysis by using miRComb R package, and we found that the most significant mRNA-miRNA pairs were involved in promoting the inflammatory status in VULN animals and, vice versa, by decreasing it in RES rats. Moreover, in VULN animals, the mRNA-miRNA combining analyses revealed the modulation of the olfactory sensory system, a key biological process that has been already found involved in the etiology of stress related disorders such as depression.Overall, our mRNA-miRNA integration-based approach identified distinct biological processes that are relevant for the development of a vulnerable or resilient phenotype in response to the negative effects of CMS exposure, which could allow the identification of novel targets for prevention or treatment.

Enhanced Genomic and Transcriptomic Resources for Trichinella pseudospiralis and T. spiralis to Underpin the Discovery of Molecular Differences between Stages and Species.

Nematodes of the genus Trichinella are important pathogens of humans and animals. This study aimed to enhance the genomic and transcriptomic resources for T. pseudospiralis (non-encapsulated phenotype) and T. spiralis (encapsulated phenotype) and to explore transcriptional profiles. First, we improved the assemblies of the genomes of T. pseudospiralis (code ISS13) and T. spiralis (code ISS534), achieving genome sizes of 56.6 Mb (320 scaffolds, and an N50 of 1.02 Mb) and 63.5 Mb (568 scaffolds, and an N50 value of 0.44 Mb), respectively. Then, for each species, we produced RNA sequence data for three key developmental stages (first-stage muscle larvae [L1s], adults, and newborn larvae [NBLs]; three replicates for each stage), analysed differential transcription between stages, and explored enriched pathways and processes between species. Stage-specific upregulation was linked to cellular processes, metabolism, and host-parasite interactions, and pathway enrichment analysis showed distinctive biological processes and cellular localisations between species. Indeed, the secreted molecules calmodulin, calreticulin, and calsyntenin-with possible roles in modulating host immune responses and facilitating parasite survival-were unique to T. pseudospiralis and not detected in T. spiralis. These insights into the molecular mechanisms of Trichinella-host interactions might offer possible avenues for developing new interventions against trichinellosis.

Distinct genetic liability profiles define clinically relevant patient strata across common diseases

Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms.

Genetic drivers and cellular selection of female mosaic X chromosome loss.

Mosaic loss of the X chromosome (mLOX) is the most common clonal somatic alteration in leukocytes of femaleindividuals1,2, but little is known about its genetic determinants or phenotypic consequences. Here, to address this, we used data from 883,574 female participants across 8 biobanks; 12% of participants exhibited detectable mLOX in approximately 2% of leukocytes. Female participants with mLOX had an increased risk of myeloid and lymphoid leukaemias. Genetic analyses identified 56 common variants associated with mLOX, implicating genes with roles in chromosomal missegregation, cancer predisposition and autoimmune diseases. Exome-sequence analyses identified rare missense variants in FBXO10 that confer a twofold increased risk of mLOX. Only a small fraction of associations was shared with mosaic Y chromosome loss, suggesting that distinct biological processes drive formation and clonal expansion of sex chromosome missegregation. Allelic shift analyses identified X chromosome alleles that are preferentially retained in mLOX, demonstrating variation at many loci under cellular selection. A polygenic score including 44 allelic shift loci correctly inferred the retained X chromosomes in 80.7% of mLOX cases in the top decile. Our results support a model in which germline variants predispose femaleindividuals to acquiring mLOX, with the allelic content of the X chromosome possibly shaping the magnitude of clonal expansion.

Comparative analysis of centrally mediated and inflammatory pain experiences amongst patients diagnosed with rheumatoid arthritis: A multimethods study.

The identification of pain originating from distinct biological processes may lead to individualised pain treatment. In this study, we aimed to explore the pain experiences of patients with rheumatoid arthritis (RA), differentiating between those predominantly exhibiting features of peripheral inflammatory versus centrally mediated pain. Through a multimethods approach we (i) quantitatively analysed the differences in pain descriptors between patients diagnosed with RA experiencing peripheral inflammatory and centrally mediated pain, utilising the Short Form-McGill Pain Questionnaire which includes the pain visual analogue scale (VAS) and (ii) qualitatively explored their subjective pain experiences grounded in the biopsychosocial model, commonly applied in chronic pain. Participants with centrally mediated pain reported higher pain scores on the VAS, used a wider range of pain descriptors, and a higher proportion selected each descriptor compared to those with inflammatory pain (p < .001). The qualitative analysis revealed the centrally mediated pain group's experiences were overwhelming and relentless, struggling to precisely articulate the nature of their pain. In contrast, individuals with inflammatory pain expressed their pain in more tangible terms and shared their adaptive and coping strategies. Importantly, both groups revealed the substantial psychological, functional and social impacts of their pain, highlighting the often 'invisible' and misunderstood nature of their symptoms. This study has gained a deeper insight into the pain experiences of patients living with RA, particularly in differentiating between centrally mediated and inflammatory types of pain, potentially facilitating a more individualised approach to pain treatment. Patients actively participated in the study conception and design. This engagement includes collaboration with key stakeholders, such as members of the National Rheumatoid Arthritis Society and Patient Research Partners (PRPs), who provided continuous feedback and guidance throughout the research process. Specifically, the qualitative element was coproduced with two PRPs, who were involved in co-leading the focus groups and data analysis.