Multiple functional variants in the IL1RL1 region are pretransplant markers for risk of GVHD and infection deaths

Whole-Genome Sequencing Analyses Reveal the Whip-like Tail Formation, Innate Immune Evolution, and DNA Repair Mechanisms of Eupleurogrammus muticus

Smallhead hairtail (Eupleurogrammus muticus) is an important marine economic fish distributed along the northern Indian Ocean and the northwest Pacific coast; however, little is known about the mechanism of its genetic evolution. This study generated the first genome assembly of E. muticus at the chromosomal level using a combination of PacBio SMRT, Illumina Nova-Seq, and Hi-C technologies. The final assembled genome size was 709.27 Mb, with a contig N50 of 25.07 Mb, GC content of 40.81%, heterozygosity rate of 1.18%, and repetitive sequence rate of 35.43%. E. muticus genome contained 21,949 protein-coding genes (97.92% of the genes were functionally annotated) and 24 chromosomes. There were 143 expansion gene families, 708 contraction gene families, and 4888 positively selected genes in the genome. Based on the comparative genomic analyses, we screened several candidate genes and pathways related to whip-like tail formation, innate immunity, and DNA repair in E. muticus. These findings preliminarily reveal some molecular evolutionary mechanisms of E. muticus at the genomic level and provide important reference genomic data for the genetic studies of other trichiurids.

Associations of minor histocompatibility antigens with outcomes following allogeneic hematopoietic cell transplantation

The role of minor histocompatibility antigens (mHAs) in mediating graft versus leukemia and graft versus host disease (GvHD) following allogeneic hematopoietic cell transplantation (alloHCT) is recognized but not well-characterized. By implementing improved methods for mHA prediction in two large patient cohorts, this study aimed to comprehensively explore the role of mHAs in alloHCT by analyzing whether (1) the number of predicted mHAs, or (2) individual mHAs are associated with clinical outcomes. The study population consisted of 2249 donor-recipient pairs treated for acute myeloid leukemia and myelodysplastic syndrome with alloHCT. A Cox proportional hazard model showed that patients with a class I mHA count greater than the population median had an increased hazard of GvHD mortality (hazard ratio [HR] = 1.39, 95% confidence interval [CI] = 1.01, 1.77, p = .046). Competing risk analyses identified the class I mHAs DLRCKYISL (GSTP), WEHGPTSLL (CRISPLD2), and STSPTTNVL (SERPINF2) were associated with increased GVHD mortality (HR = 2.84, 95% CI = 1.52, 5.31, p = .01), decreased leukemia-free survival (LFS) (HR = 1.94, 95% CI = 1.27, 2.95, p = .044), and increased disease-related mortality (DRM) (HR = 2.32, 95% CI = 1.5, 3.6, p = .008), respectively. One class II mHA YQEIAAIPSAGRERQ (TACC2) was associated with increased risk of treatment-related mortality (TRM) (HR = 3.05, 95% CI = 1.75, 5.31, p = .02). WEHGPTSLL and STSPTTNVL were both present within HLA haplotype B*40:01-C*03:04 and showed a positive dose-response relationship with increased all-cause mortality and DRM and decreased LFS, indicating these two mHAs contribute to the risk of mortality in an additive manner. Our study reports the first large-scale investigation of the associations of predicted mHA peptides with clinical outcomes following alloHCT.

Decoding the genetic and epigenetic basis of asthma

Asthma is a complex and heterogeneous chronic inflammatory disease of the airways. Alongside environmental factors, asthma susceptibility is strongly influenced by genetics. Given its high prevalence and our incomplete understanding of the mechanisms underlying disease susceptibility, asthma is frequently studied in genome-wide association studies (GWAS), which have identified thousands of genetic variants associated with asthma development. Virtually all these genetic variants reside in non-coding genomic regions, which has obscured the functional impact of asthma-associated variants and their translation into disease-relevant mechanisms. Recent advances in genomics technology and epigenetics now offer methods to link genetic variants to gene regulatory elements embedded within non-coding regions, which have started to unravel the molecular mechanisms underlying the complex (epi)genetics of asthma. Here, we provide an integrated overview of (epi)genetic variants associated with asthma, focusing on efforts to link these disease associations to biological insight into asthma pathophysiology using state-of-the-art genomics methodology. Finally, we provide a perspective as to how decoding the genetic and epigenetic basis of asthma has the potential to transform clinical management of asthma and to predict the risk of asthma development.

Post-haematopoietic cell transplantation outcomes: why ST2 became a 'golden nugget' biomarker

Immunotherapies have emerged as highly promising approaches to treat cancer patients. Allogeneic haematopoietic cell transplantation (HCT) is the most validated tumour immunotherapy available to date but its clinical efficacy is limited by toxicities, such as graft-versus-host disease (GVHD) and treatment resistance leading to relapse. The problems with new cellular therapies and checkpoint inhibitors are similar. However, development of biomarkers post-HCT, particularly for toxicities, has taken off in the last decade and has expanded greatly. Thanks to the advances in genomics, transcriptomics, proteomics and cytomics technologies, blood biomarkers have been identified and validated in promising diagnostic tests, prognostic tests stratifying for future occurrence of GVHD, and predictive tests for responsiveness to GVHD therapy and non-relapse mortality. These biomarkers may facilitate timely and selective therapeutic intervention. This review outlines a path from biomarker discovery to first clinical correlation, focusing on soluble STimulation-2 (sST2) - the interleukin (IL)-33-decoy receptor - which is the most validated biomarker.

Biomarkers for acute and chronic graft versus host disease: state of the art

INTRODUCTION

Despite significant advances in treatment and prevention, graft-versus-host disease (GVHD) still represents the main cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation. Thus, considerable research efforts have been made to find and validate reliable biomarkers for diagnosis, prognosis, and risk stratification of GVHD.

AREAS COVERED

In this review the most recent evidences on different types of biomarkers studied for GVHD, such as genetic, plasmatic, cellular markers, and those associated with microbiome, were summarized. A comprehensive search of peer-review literature was performed in PubMed including meta-analysis, preclinical and clinical trials, using the terms: cellular and plasma biomarkers, graft-versus-host disease, cytokines, and allogeneic hematopoietic stem cell transplantation.

EXPERT OPINION

In the near future, several validated biomarkers will be available to help clinicians in the diagnosis of GVHD, the identification of patients at high risk of GVHD development and in patients' stratification according to its severity. Then, immunosuppressive treatment could be tailored to each patient's real needs. However, more efforts are needed to achieve this goal. Although most of the proposed biomarkers currently lack validation with large-scale clinical data, their study led to improved knowledge of the biological basis of GVHD, and ultimately to implementation of GHVD treatment.

Biomarkers for Allogeneic HCT Outcomes

Allogeneic hematopoietic cell transplantation (HCT) remains the only curative therapy for many hematological malignant and non-malignant disorders. However, key obstacles to the success of HCT include graft-versus-host disease (GVHD) and disease relapse due to absence of graft-versus-tumor (GVT) effect. Over the last decade, advances in "omics" technologies and systems biology analysis, have allowed for the discovery and validation of blood biomarkers that can be used as diagnostic test and prognostic test (that risk-stratify patients before disease occurrence) for acute and chronic GVHD and recently GVT. There are also predictive biomarkers that categorize patients based on their likely to respond to therapy. Newer mathematical analysis such as machine learning is able to identify different predictors of GVHD using clinical characteristics pre-transplant and possibly in the future combined with other biomarkers. Biomarkers are not only useful to identify patients with higher risk of disease progression, but also help guide treatment decisions and/or provide a basis for specific therapeutic interventions. This review summarizes biomarkers definition, omics technologies, acute, chronic GVHD and GVT biomarkers currently used in clinic or with potential as targets for existing or new drugs focusing on novel published work.