Gene Set Analysis Research Articles

#6456 DSA-NEGATIVE MICROVASCULAR INFLAMMATION IN KIDNEY TRANSPLANT BIOPSIES: GENE EXPRESSION COMPARISON WITH NATIVE AND TRANSPLANT KIDNEY CONTROLS

Abstract Background and Aims Microvascular inflammation (MVI) in kidney transplant (KT) biopsies from patients without detectable anti-HLA donor-specific antibodies (DSA) presents a diagnostic and therapeutic dilemma. This study aimed to further understand the significance of these changes by characterizing their molecular phenotype compared to other native and transplant kidney biopsies. Method The NanoString B-HOT panel (770 genes) was used to measure the expression of six literature-derived gene sets in 195 archival FFPE kidney biopsies from four centers, including transplant biopsies with MVI (g+ptc>1) but no detectable DSA (MVI, n = 47), antibody-mediated rejection with DSA (ABMR, n = 42), pure T-cell mediated rejection without DSA (TCMR, n = 25), mixed MVI and TCMR without DSA (MVI+TCMR, n = 47), normal implant biopsies (Normal, n = 11), and native kidney biopsies with either endocapillary proliferative glomerulonephritis (GN, n = 12) or minimal change disease (MCD, n = 11). The evaluated gene sets included transcripts previously associated with ABMR, DSA (DSAST), endothelial injury (ENDAT), TCMR, early injury, and late injury. Gene expression was compared between groups using principal component and class comparison analyses. Results Principal component analysis demonstrated significant molecular overlap between sample groups (Fig. 1A). However, gene set analysis showed lower expression of ABMR-related, DSAST (Fig. 1B), and ENDAT gene sets in DSA-negative MVI compared to ABMR. DSAST and ENDAT gene set expression was similar between MVI, MVI+TCMR, and TCMR groups; but higher than native biopsies (p ≤ 0.002). TCMR and early injury gene set expression was higher in TCMR than all other groups (p ≤ 0.002), except MVI+TCMR. Late injury gene set expression was lower in MVI compared to ABMR, MVI+TCMR, and TCMR groups (p ≤ 0.031); but higher than the Normal and MCD groups (p ≥ 0.016). Conclusion These results suggest that DSA-negative MVI displays a lower expression of ABMR-related genes than ABMR, but similar to MVI+TCMR and higher than native kidney biopsies with or without glomerulonephritis. Further work is underway to evaluate the potential role of non-HLA DSA and recognition of missing self in these cases.

#6352 CLINICAL AND MOLECULAR SPECTRUM OF V-LESION

Abstract Background and Aims Isolated v-lesion is an increasingly recognized but clinically challenging entity. Some studies suggest that isolated v+ early post-transplant may be caused by non-alloimmune etiologies such as ischemic injury. We aimed to characterize the allograft outcomes of isolated v-lesions according to post-transplant time (early: ≤1 month vs. late: >1 month) and further understand the significance of this lesion by characterizing its molecular phenotype in comparison with other forms of rejection v+. Method The NanoString B-HOT panel (770 genes) was used to measure the expression of six literature-derived gene sets in 92 archival FFPE kidney biopsies from two centers, including transplant biopsies with isolated v-lesion (n = 23), antibody-mediated rejection (ABMR) with v+ (n = 26), pure T-cell mediated rejection (TCMR) with v+ (n = 10), mixed rejection v+ (n = 23), and normal implant biopsies (Normal, n = 10). The evaluated gene sets included transcripts previously associated with ABMR, DSA (DSAST), endothelial injury (ENDAT), TCMR, early injury, and late injury. Gene expression was compared between groups using principal component and class comparison analyses. Death-censored graft survival according to diagnosis and time after KT was assessed. Results Isolated v+ early conferred the worst death-censored graft survival one year after the biopsy (40%) when compared to isolated v+ late (100%) or other forms of rejection (≥82%, p = 0.034). The principal component analysis demonstrated significant molecular overlap between sample groups (PC1: 29.4%, PC2: 8.1%). However, gene set analysis showed lower expression of TCMR-related genes in isolated v+ groups compared to TCMR and mixed rejection (p<0.001). Both Isolated v+ early and late had lower ABMR-related genes than ABMR, mixed rejection, and TCMR groups (p ≤ 0.022). Moreover, isolated v+ late showed lower DSAST and ENDAT gene set expression than ABMR (p ≤ 0.046); and lower early injury gene set expression than isolated v+ early, ABMR, TCMR, and mixed rejection (p ≤ 0.026). Late injury gene set expression was highest in TCMR and mixed rejection compared to the other groups (p ≥ 0.034). Conclusion These results suggest that early and late isolated v+ lesions display lower expression of TCMR-related genes than TCMR and mixed rejection and lower expression of ABMR-related genes than ABMR. Isolated v+ early confers a bad prognosis and is associated with higher expression of early injury genes compared to isolated v+ late, suggesting a different ethology.

Identification of autoantigens and their potential post-translational modification in EGPA and severe eosinophilic asthma.

The chronic airway inflammation in severe eosinophilic asthma (SEA) suggests potential autoimmune aetiology with unidentified autoantibodies analogous to myeloperoxidase (MPO) in ANCA-positive EGPA (eosinophilic granulomatosis with polyangiitis). Previous research has shown that oxidative post-translational modification (oxPTM) of proteins is an important mechanism by which autoantibody responses may escape immune tolerance. Autoantibodies to oxPTM autoantigens in SEA have not previously been studied. Patients with EGPA and SEA were recruited as well as healthy control participants. Autoantigen agnostic approach: Participant serum was incubated with slides of unstimulated and PMA-stimulated neutrophils and eosinophils, and autoantibodies to granulocytes were identified by immunofluorescence with anti-human IgG FITC antibody. Target autoantigen approach: Candidate proteins were identified from previous literature and FANTOM5 gene set analysis for eosinophil expressed proteins. Serum IgG autoantibodies to these proteins, in native and oxPTM form, were detected by indirect ELISA. Immunofluorescence studies showed that serum from patients with known ANCA stained for IgG against neutrophils as expected. In addition, serum from 9 of 17 tested SEA patients stained for IgG to PMA-stimulated neutrophils undergoing NETosis. Immunofluorescent staining of eosinophil slides was evident with serum from all participants (healthy and with eosinophilic disease) with diffuse cytoplasmic staining except for one SEA individual in whom subtle nuclear staining was evident. FANTOM5 gene set analysis identified TREM1 (triggering receptor expressed on myeloid cells 1) and IL-1 receptor 2 (IL1R2) as eosinophil-specific targets to test for autoantibody responses in addition to MPO, eosinophil peroxidase (EPX), and Collagen-V identified from previous literature. Indirect ELISAs found high concentrations of serum autoantibodies to Collagen-V, MPO, and TREM1 in a higher proportion of SEA patients than healthy controls. High concentrations of serum autoantibodies to EPX were evident in serum from both healthy and SEA participants. The proportion of patients with positive autoantibody ELISAs was not increased when examining oxPTM compared to native proteins. Although none of the target proteins studied showed high sensitivity for SEA, the high proportion of patients positive for at least one serum autoantibody shows the potential of more research on autoantibody serology to improve diagnostic testing for severe asthma. ClinicalTrials.gov, identifier, NCT04671446.

Racial and genetic ancestry associations with gene expression patterns in a real-world cohort of colorectal cancer patients.

3541 Background: There is a growing incidence of colorectal cancer (CRC) among young adults and persistent disparities in outcomes by race/ethnicity across all ages. Gene expression signatures, as well as consensus molecular subtypes (CMS) derived from these, have been proposed to predict prognosis and therapy response in CRC. However, it is unclear whether gene expression or CMS are associated with racial disparities observed in CRC. We assessed whether race or genetic ancestry are associated with CMS or gene expression patterns in a deidentified cohort of 1,768 CRC patients. Methods: Patients tumors’ underwent tumor profiling with the Tempus xT NGS 648-gene assay as well as full-transcriptome RNA sequencing. We used a set of 654 ancestry-informative markers to infer genetic ancestry likelihoods for Africa (AFR), America (AMR), East Asia (EAS), Europe (EUR), and South Asia (SAS). Race/ethnicity labels, often missing in real-world data, were imputed using ancestry proportions from the literature and adjusted based on observed metadata. Gene expression data was used to assign CMS to all patients (CMS1, 2, 3, 4 and indeterminate) using CMScaller, and multinomial logistic regression was used to assess associations with race/ethnicity imputed labels and ancestry proportions. We then assessed differential expression (DE) in the MSigDB hallmark and C2 BioCarta gene sets using four separate workflows. The first two workflows used limma-voom followed by ROAST to assess DE among the imputed labels and then among the ancestry proportions (isometric log ratio transformed). The second two workflows used GSVA followed by limma. Results: Among 1,768 patients, 240 were imputed non-Hispanic (NH) Black, 94 NH Asian, 261 Hispanic/Latino/Native American (HLN), and 1,173 NH White. NH Black patients had higher odds of CMS3 vs CMS1 (OR = 2.66, p < 0.001) and HLN patients had higher odds of indeterminate CMS vs CMS1 (OR = 1.90, p = 0.020), compared to NH White. AFR ancestry was significantly associated with CMS3 (OR = 1.05 per doubling in AFR proportion, p = 0.047) and indeterminate CMS (OR = 1.07, p = 0.023). In the gene set analysis, NH Black race/ethnicity was associated with over-expression of the BioCarta WNT pathway gene set. Both AFR ancestry and NH Black race/ethnicity were associated with under-expression of the MSigDB hallmark coagulation and BioCarta alternative complement gene sets and over-expression of the PITX2 pathway gene set (all significant with both ROAST and GSVA). Conclusions: We found that NH Black patients and AFR ancestry were associated with higher rates of CMS3, which is associated with KRAS mutation and was previously reported to be more common among Black patients. Indeterminate CMS associations with AFR ancestry and HLN highlights the need to use diverse patient cohorts when training unsupervised learning models to improve prognosis prediction in non-White patients.

Unique molecular underpinnings by genetic ancestry in localized clear cell renal cell carcinoma.

4536 Background: Clinical studies evaluating the impact of race on outcomes in renal cell carcinoma (RCC) are inconsistent and conceivably influenced by both biological and socioeconomic factors. Self-reported African Americans (AA) are also largely underrepresented in clinical trials and molecular studies of clear cell (cc) RCC compared to their White (W) counterparts. Herein, we sought to comprehensively characterize molecular differences by genetic ancestry in localized ccRCC. Methods: We performed whole exome (WES) and transcriptome (RNAseq) sequencing on a case-matched cohort of AA and W patients (pts) who underwent nephrectomy for localized ccRCC at our institution. Germline single nucleotide polymorphisms were combined with reference panels from the 1000 Genomes Project, and ancestry was estimated using ADMIXTURE. Molecular subtypes were defined according to the IMmotion151 (IMm151) subtypes, and a random forest model was trained to predict subgroups. Results: From an initial selected cohort of 84 pts, WES and RNAseq data of adequate quality were available for 61 pts including 28 of African (AFR) and 33 of European (EUR) descent. We augmented our institutional cohort with a 3:1 EUR:AFR matched subset of the TCGA KIRC by stage, nuclear grade (NG), and gender. The final analytic cohort contained 75 pts of AFR and 177 pts of EUR descent. There were no significant differences in stage, NG, or gender between AFR and EUR groups. We observed that VHL [OR 0.22, CI [0.11-0.43], p <0.001) and PBRM1 (OR 0.4, CI [0.19-0.79], p = 0.005) mutations are enriched in pts with EUR ancestry and identified a unique association of KMT2C somatic mutations (OR 3.7, CI [1.1-13.5], p = 0.027) with AFR ancestry. Consistent with a lower frequency of VHL mutations, gene-set variation analysis revealed lower enrichment for angiogenesis (-0.23 vs 0.045; p < 0.001) in AFR vs EUR ancestry, respectively. AFR ancestry was associated with an increased proportion of the “Proliferative” IMm151 subtype (14.9% [n = 11/74] vs 3.4% [n = 6/177], p = 0.002). There was no association between overall survival (OS) and ancestry; however, IMm151 subtypes stratified OS with longest survival in the “Angiogenic/Stromal” group (median OS NR) and shortest OS in the T-Effector/Proliferative subtype (5.5yrs CI [2.3 - NR], p = 0.01). Conclusions: Our findings indicate that genetic ancestry is associated with distinct molecular subtypes of ccRCC. Biological drivers of ccRCC pathogenesis and therapeutic response may vary by ancestry, underscoring the need for racially diverse representation in future studies.

Genome-wide association studies categorized by class of anti-hypertensive drugs reveal complex pathogenesis of hypertension with drug resistance.

Resistant hypertension is defined as uncontrolled blood pressure despite the use of three or more anti-hypertensive drugs of different classes. Though genetic factors may greatly contribute to hypertension with resistance to multiple drug classes, more than for general hypertension, its pathogenesis remains unknown. To reveal the genetic background of resistant hypertension, we categorized 32,239 patients whose data were obtained from the BioBank Japan Project, by prescription of seven classes of anti-hypertensive drugs and performed genome-wide association studies. Our genome-wide association studies identified four loci with significant association (P < 5×10-8 ): rs6445583 in CACNA1D and rs12308051 in the intergenic region on chromosome 12 for ARBs, rs35497065 in FOXA3 for CCBs, and rs11066280 in HECTD4 for α-blockers. Since these loci are known to be susceptibility loci for hypertension and/or blood pressure, our results indicate that resistant hypertension is caused by a combination of excessive blood pressure and drug resistance to each anti-hypertensive pharmacological class. Furthermore, to investigate the genetic difference between BP traits and the treatment effectiveness of anti-hypertensive drugs, we performed gene-set analysis and calculated the genetic correlation continuously. Most of the genetic factors were in common between BP traits and anti-hypertensive effectiveness, but it seems that the genetic architecture of the drug response to anti-hypertensive treatment is more complicated than BP traits. This corresponds to the well-known mosaic theory of hypertension. Our findings reveal the complex pathogenesis of hypertension with resistance to multiple classes of anti-hypertensive drugs.

Transcriptome data analysis of primary cardiomyopathies reveals perturbations in arachidonic acid metabolism.

Cardiomyopathies are complex heart diseases with significant prevalence around the world. Among these, primary forms are the major contributors to heart failure and sudden cardiac death. As a high-energy demanding engine, the heart utilizes fatty acids, glucose, amino acid, lactate and ketone bodies for energy to meet its requirement. However, continuous myocardial stress and cardiomyopathies drive towards metabolic impairment that advances heart failure (HF) pathogenesis. So far, metabolic profile correlation across different cardiomyopathies remains poorly understood. In this study, we systematically explore metabolic differences amongst primary cardiomyopathies. By assessing the metabolic gene expression of all primary cardiomyopathies, we highlight the significantly shared and distinct metabolic pathways that may represent specialized adaptations to unique cellular demands. We utilized publicly available RNA-seq datasets to profile global changes in the above diseases (|log2FC| ≥ 0.28 and BHadjusted p-val 0.1) and performed gene set analysis (GSA) using the PAGE statistics on KEGG pathways. Our analysis demonstrates that genes in arachidonic acid metabolism (AA) are significantly perturbed across cardiomyopathies. In particular, the arachidonic acid metabolism gene PLA2G2A interacts with fibroblast marker genes and can potentially influence fibrosis during cardiomyopathy. The profound significance of AA metabolism within the cardiovascular system renders it a key player in modulating the phenotypes of cardiomyopathies.

Identifying genetic loci and phenomic associations of substance use traits: A multi-trait analysis of GWAS (MTAG) study.

Genome-wide association studies (GWAS) of opioid use disorder (OUD) and cannabis use disorder (CUD) have lagged behind those of alcohol use disorder (AUD) and smoking, where many more loci have been identified. We sought to identify novel loci for substance use traits (SUTs) in both African- (AFR) and European- (EUR) ancestry individuals to enhance our understanding of the traits' genetic architecture. We used multi-trait analysis of GWAS (MTAG) to analyze four SUTs in EUR subjects (OUD, CUD, AUD and smoking initiation [SMKinitiation]), and three SUTs in AFR subjects (OUD, AUD and smoking trajectory [SMKtrajectory]). We conducted gene-set and protein-protein interaction analyses and calculated polygenic risk scores (PRS) in two independent samples. This study was conducted in the United States. A total of 5692 EUR and 4918 AFR individuals in the Yale-Penn sample and 29 054 EUR and 10 265 AFR individuals in the Penn Medicine BioBank sample. MTAG identified genome-wide significant (GWS) single nucleotide polymorphisms (SNPs) for all four traits in EUR: 41 SNPs in 36 loci for OUD; 74 SNPs in 60 loci for CUD; 63 SNPs in 52 loci for AUD; and 183 SNPs in 144 loci for SMKinitiation. MTAG also identified GWS SNPs in AFR: 2 SNPs in 2 loci for OUD; 3 SNPs in 3 loci for AUD; and 1 SNP in 1 locus for SMKtrajectory. In the Yale-Penn sample, the MTAG-derived PRS consistently yielded more significant associations with both the corresponding substance use disorder diagnosis and multiple related phenotypes than the GWAS-derived PRS. Multi-trait analysis of genome-wide association studies boosted the number of loci found for substance use traits, identifying genes not previously linked to any substance, and increased the power of polygenic risk scores. Multi-trait analysis of genome-wide association studies can be used to identify novel associations for substance use, especially those for which the samples are smaller than those for historically legal substances.

Epigenetic Association Analyses and Risk Prediction of RLS.

As opposed to other neurobehavioral disorders, epigenetic analyses and biomarkers are largely missing in the case of idiopathic restless legs syndrome (RLS). Our aims were to develop a biomarker for RLS based on DNA methylation in blood and to examine DNA methylation in brain tissues for dissecting RLS pathophysiology. Methylation of blood DNA from three independent cohorts (n = 2283) and post-mortem brain DNA from two cohorts (n = 61) was assessed by Infinium EPIC 850 K BeadChip. Epigenome-wide association study (EWAS) results of individual cohorts were combined by random-effect meta-analysis. A three-stage selection procedure (discovery, n = 884; testing, n = 520; validation, n = 879) established an epigenetic risk score including 30 CpG sites. Epigenetic age was assessed by Horvath's multi-tissue clock and Shireby's cortical clock. EWAS meta-analysis revealed 149 CpG sites linked to 136 genes (P < 0.05 after Bonferroni correction) in blood and 23 CpG linked to 18 genes in brain (false discovery rate [FDR] < 5%). Gene-set analyses of blood EWAS results suggested enrichments in brain tissue types and in subunits of the kainate-selective glutamate receptor complex. Individual candidate genes of the brain EWAS could be assigned to neurodevelopmental or metabolic traits. The blood epigenetic risk score achieved an area under the curve (AUC) of 0.70 (0.67-0.73) in the validation set, comparable to analogous scores in other neurobehavioral disorders. A significant difference in biological age in blood or brain of RLS patients was not detectable. DNA methylation supports the notion of altered neurodevelopment in RLS. Epigenetic risk scores are reliably associated with RLS but require even higher accuracy to be useful as biomarkers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Gene Expression Profiling of Fibroepithelial Lesions of the Breast.

Fibroepithelial lesions of the breast (FELs) are a heterogeneous group of neoplasms exhibiting a histologic spectrum ranging from fibroadenomas (FAs) to malignant phyllodes tumors (PTs). Despite published histologic criteria for their classification, it is common for such lesions to exhibit overlapping features, leading to subjective interpretation and interobserver disagreements in histologic diagnosis. Therefore, there is a need for a more objective diagnostic modality to aid in the accurate classification of these lesions and to guide appropriate clinical management. In this study, the expression of 750 tumor-related genes was measured in a cohort of 34 FELs (5 FAs, 9 cellular FAs, 9 benign PTs, 7 borderline PTs, and 4 malignant PTs). Differentially expressed gene analysis, gene set analysis, pathway analysis, and cell type analysis were performed. Genes involved in matrix remodeling and metastasis (e.g., MMP9, SPP1, COL11A1), angiogenesis (VEGFA, ITGAV, NFIL3, FDFR1, CCND2), hypoxia (ENO1, HK1, CYBB, HK2), metabolic stress (e.g., UBE2C, CDKN2A, FBP1), cell proliferation (e.g., CENPF, CCNB1), and the PI3K-Akt pathway (e.g., ITGB3, NRAS) were highly expressed in malignant PTs and less expressed in borderline PTs, benign PTs, cellular FAs, and FAs. The overall gene expression profiles of benign PTs, cellular FAs, and FAs were very similar. Although a slight difference was observed between borderline and benign PTs, a higher degree of difference was observed between borderline and malignant PTs. Additionally, the macrophage cell abundance scores and CCL5 were significantly higher in malignant PTs compared with all other groups. Our results suggest that the gene-expression-profiling-based approach could lead to further stratification of FELs and may provide clinically useful biological and pathophysiological information to improve the existing histologic diagnostic algorithm.

The circadian rhythm key gene ARNTL2: a novel prognostic biomarker for immunosuppressive tumor microenvironment identification and immunotherapy outcome prediction in human cancers.

Aryl hydrocarbon receptor nuclear translocator-like 2 (ARNTL2) belongs to the b HLH- PAS domain transcription factor family and is one of the key clock genes that control the circadian rhythm. ARNTL2 plays an important role in human biological functions. However, its role in various tumors, especially in the tumor immune microenvironment (TIME) and immunotherapy, remains unclear. We integrated data from cancer patients from multiple databases, including the Cancer Genome Atlas, Cancer Cell Lineage Encyclopedia, Genotype Tissue Expression, Human Protein Atlas, cBioPortal, TIMER, and ImmuCellAI, with data from a large clinical study, three immunotherapy cohorts, and in vitro experiments to investigate the involvement of ARNTL2 expression in cancer prognosis and immune response. ARNTL2 displayed abnormal expression within most malignant tumors, and is significantly associated with poorer survival and pathologic staging. Through gene-set enrichment analysis (GSEA) and gene-set variation analysis (GSVA), we found that ARNTL2 not only regulates cell cycle-related functions to promote cell proliferation but also regulates autoimmunity-related functions of the innate and adaptive immune systems, and other immune-related signaling pathways. In addition, ARNTL2 overexpression contributes to an immunosuppressive tumor microenvironment that plays a key role in immunosuppression-related features, such as the expression of immunosuppression-related genes and pathways and the number of immunosuppressive-infiltrating cells, including regulatory T cells (Tregs), tumor-associated macrophages (TAMs), and cancer-associated fibroblasts (CAFs). The group of patients with low ARNTL2 expression who received immune checkpoint inhibitors (ICI) therapy had better response rates and longer survival when compared to those with high ARNTL2 expression. The findings of this study suggest that ARNTL2 is a potential human oncogene that plays an important role in tumorigenesis and cancer immunity. Elevated ARNTL2 expression indicates an immunosuppressive tumor microenvironment. Targeting ARNTL2 in combination with ICI therapy could bring more significant therapeutic benefits to patients with cancer. Our study sheds light on the remarkable potential of ARNTL2 in tumor immunity and provides a novel perspective for anti-tumor strategies.

Maternal and fetal mitochondrial gene dysregulation in hypertensive disorders of pregnancy.

Mitochondrial dysfunction has been implicated in pregnancy-induced hypertension (PIH). The role of mitochondrial gene dysregulation in PIH, and consequences for maternal-fetal interactions, remain elusive. Here, we investigated mitochondrial gene expression and dysregulation in maternal and placental tissues from pregnancies with and without PIH; further, we measured circulating mitochondrial DNA (mtDNA) mutational load, an index of mtDNA integrity. Differential gene expression analysis followed by Time Course Gene Set Analysis (TcGSA) was conducted on publicly available high throughput sequencing transcriptomic data sets. Mutational load analysis was carried out on peripheral mononuclear blood cells from healthy pregnant individuals and individuals with preeclampsia. Thirty mitochondrial differentially expressed genes (mtDEGs) were detected in the maternal cell-free circulating transcriptome, whereas nine were detected in placental transcriptome from pregnancies with PIH. In PIH pregnancies, maternal mitochondrial dysregulation was associated with pathways involved in inflammation, cell death/survival, and placental development, whereas fetal mitochondrial dysregulation was associated with increased production of extracellular vesicles (EVs) at term. Mothers with preeclampsia did not exhibit a significantly different degree of mtDNA mutational load. Our findings support the involvement of maternal mitochondrial dysregulation in the pathophysiology of PIH and suggest that mitochondria may mediate maternal-fetal interactions during healthy pregnancy.NEW & NOTEWORTHY This study identifies aberrant maternal and fetal expression of mitochondrial genes in pregnancies with gestational hypertension and preeclampsia. Mitochondrial gene dysregulation may be a common etiological factor contributing to the development of de novo hypertension in pregnancy-associated hypertensive disorders.

756 Effects of Bioengineered Allogeneic Cellular Constructs on Macrophage Phenotype in the Context of Burns

Abstract Introduction The persistent inflammatory and stress responses generate in burn patients have a strong effect on the immune system. Macrophages that are activated in response to burn injuries polarize towards an immunosuppressive phenotype commonly known as M2b. Furthermore, due to sepsis, the chronic exposure to the pro-inflammatory environment also leads to an exhausted macrophage phenotype. Together these effects compromise macrophage behavior that influences the healing outcome. In clinical trials, bioengineered allogeneic cellular constructs (BACCs) have shown potential in promoting healing in patients with deep partial thickness burns. However, the mechanism(s) behind these successful effects are not totally understood yet. For this reason, the aim of this study is to investigate how the crosstalk with the BACC influence different burn-related macrophage phenotype. Methods Primary human macrophages (N=4 healthy donors) were co-cultured with the BACC or collagen controls. Macrophages were isolated over 6 days of co-culture and their RNA was extracted for gene expression analysis, and conditioned media was collected to analyze the secretion of proteins. To assess phenotype changes, we performed gene set analysis using single sample gene set enrichment. To investigate changes in the phenotype of macrophages relevant to burn wounds macrophages were polarized to the immune suppressive M2b phenotype or LPS-exhausted phenotypes before co-culturing them with the BACC. Undifferentiated macrophages (M0) were used as controls. Results Gene expression analysis revealed a shift in undifferentiated macrophage phenotype towards an M2 phenotype by day 3 and 6 in co-culture as demonstrated by an increase in the expression of multiple M2 genes, including MRC1 and CCL18. Secretory analysis revealed a decrease in the secretory of inflammatory proteins, like interleukin 6. Conclusions Collectively these results demonstrate that BACCs promote the transition of macrophage phenotype towards a pro-reparative M2 phenotype which may contribute to the construct’s pro-healing capabilities. Applicability of Research to Practice This study provides insight into the mechanism by which BACCs promote healing in the burn wound environment.

Establishment of leukemia cell model with inducible AML1-ETO expression and its effect on fatty acid metabolism in leukemia cells

Objective: To investigate the effect of the AML1-ETO (AE) fusion gene on the biological function of U937 leukemia cells by establishing a leukemia cell model that induces AE fusion gene expression. Methods: The doxycycline (Dox) -dependent expression of the AE fusion gene in the U937 cell line (U937-AE) were established using a lentivirus vector system. The Cell Counting Kit 8 methods, including the PI and sidanilide induction, were used to detect cell proliferation, cell cycle-induced differentiation assays, respectively. The effect of the AE fusion gene on the biological function of U937-AE cells was preliminarily explored using transcriptome sequencing and metabonomic sequencing. Results: ①The Dox-dependent Tet-on regulatory system was successfully constructed to regulate the stable AE fusion gene expression in U937-AE cells. ②Cell proliferation slowed down and the cell proliferation rate with AE expression (3.47±0.07) was lower than AE non-expression (3.86 ± 0.05) after inducing the AE fusion gene expression for 24 h (P<0.05). The proportion of cells in the G(0)/G(1) phase in the cell cycle increased, with AE expression [ (63.45±3.10) %) ] was higher than AE non-expression [ (41.36± 9.56) %] (P<0.05). The proportion of cells expressing CD13 and CD14 decreased with the expression of AE. The AE negative group is significantly higher than the AE positive group (P<0.05). ③The enrichment analysis of the transcriptome sequencing gene set revealed significantly enriched quiescence, nuclear factor kappa-light-chain-enhancer of activated B cells, interferon-α/γ, and other inflammatory response and immune regulation signals after AE expression. ④Disorder of fatty acid metabolism of U937-AE cells occurred under the influence of AE. The concentration of the medium and short-chain fatty acid acylcarnitine metabolites decreased in cells with AE expressing, propionyl L-carnitine, wherein those with AE expression (0.46±0.13) were lower than those with AE non-expression (1.00±0.27) (P<0.05). The metabolite concentration of some long-chain fatty acid acylcarnitine increased in cells with AE expressing tetradecanoyl carnitine, wherein those with AE expression (1.26±0.01) were higher than those with AE non-expression (1.00±0.05) (P<0.05) . Conclusion: This study successfully established a leukemia cell model that can induce AE expression. The AE expression blocked the cell cycle and inhibited cell differentiation. The gene sets related to the inflammatory reactions was significantly enriched in U937-AE cells that express AE, and fatty acid metabolism was disordered.

VissE.cloud: a webserver to visualise higher order molecular phenotypes from enrichment analysis.

Gene-set analysis (GSA) dominates the functional interpretation of omics data and downstream hypothesis generation. Despite its ability to summarise thousands of measurements into semantically interpretable components, GSA often results in hundreds of significantly enriched gene-sets. However, summarisation and effective visualisation of GSA results to facilitate hypothesis generation is still lacking. While some webservers provide gene-set visualization tools, there is still a need for tools that can effectively summarize and guide exploration of GSA results. To enable versatility, webservers accept gene lists as input, however, none provide end-to-end solutions for emerging data types such as single-cell and spatial omics. Here, we present vissE.Cloud, a webserver for end-to-end gene-set analysis, offering gene-set summarisation and highly interactive visualisation. vissE.Cloud uses algorithms from our earlier R package vissE to summarise GSA results by identifying biological themes. We maintain versatility by allowing analysis of gene lists, as well as, analysis of raw single-cell and spatial omics data, including CosMx and Xenium data, making vissE.Cloud the first webserver to provide end-to-end gene-set analysis of sub-cellular localised spatial data. Structuring the results hierarchically allows swift interactive investigations of results at the gene, gene-set, and clusters level. vissE.Cloud is freely available at https://www.vissE.Cloud.

The genetic architecture of the corpus callosum and its genetic overlap with common neuropsychiatric diseases

BackgroundThe corpus callosum (CC) is the main structure transferring information between the cerebral hemispheres. Although previous large-scale genome-wide association study (GWAS) has illustrated the genetic architecture of white matter integrity of CC, CC volume is less stressed. MethodsUsing MRI data from 33,861 individuals in UK Biobank, we conducted univariate and multivariate GWAS for CC fractional anisotropy (FA) and volume with PLINK 2.0 and MOSTest. All discovered SNPs in the multivariate framework were functionally annotated in FUMA v1.3.8. In the meanwhile, a series of gene property analyses was conducted simultaneously. In addition, we estimated genetic relationship between CC metrics and other neuropsychiatric traits and diseases. ResultsWe identified a total of 36 and 82 significant genomic loci for CC FA and volume (P < 5 × 10−8). And 53 and 27 genes were respectively mapped by four mapping strategies. For CC volume, gene-set analysis revealed pathways mainly relating to cell migration; cell-type analysis found the top enrichment in neuroglia while for CC FA in GABAergic neurons. Furthermore, we found a lot of genetic overlap and shared loci between CC FA and volume and common neuropsychiatric diseases. DiscussionCollectively, this study helps to better understand the genetic architecture of whole CC and CC subregions. However, the way to divide CC FA and volume in our study restricts the interpretations of our results. Future work will be needed to pay attention to the genetic structure of white matter volume, and an appropriate division of CC may help to better understand CC structure.

Gene Set Based Integrated Methylome and Transcriptome Analysis Reveals Potential Molecular Mechanisms Linking Cigarette Smoking and Related Diseases.

Advanced integrative analysis of DNA methylation and transcriptomics data may provide deeper insights into smoke-induced epigenetic alterations, their effects on gene expression and related biological processes, linking cigarette smoking and related diseases. We hypothesize that accumulation of DNA methylation changes in CpG sites across genomic locations of different genes might have biological significance. We tested the hypothesis by performing gene set based integrative analysis of blood DNA methylation and transcriptomics data to identify potential transcriptomic consequences of smoking via changes in DNA methylation in the Young Finns Study (YFS) participants (n = 1114, aged 34-49 years, women: 54%, men: 46%). First, we performed epigenome-wide association study (EWAS) of smoking. We then defined sets of genes based on DNA methylation status within their genomic regions, for example, sets of genes containing hyper- or hypomethylated CpG sites in their body or promoter regions. Gene set analysis was performed using transcriptomics data from the same participants. Two sets of genes, one containing 49 genes with hypomethylated CpG sites in their body region and the other containing 33 genes with hypomethylated CpG sites in their promoter region, were differentially expressed among the smokers. Genes in the two gene sets are involved in bone formation, metal ion transport, cell death, peptidyl-serine phosphorylation, and cerebral cortex development process, revealing epigenetic-transcriptomic pathways to smoking-related diseases such as osteoporosis, atherosclerosis, and cognitive impairment. These findings contribute to a deeper understanding of the pathophysiology of smoking-related diseases and may provide potential therapeutic targets.

XAI-CNVMarker: Explainable AI-based copy number variant biomarker discovery for breast cancer subtypes

Breast cancer is a leading cause of cancer-related deaths among women. The multi-omic data has revolutionized the methodology to unravel molecular heterogeneity in breast cancer. As genetic variations captured from Copy Number Variation (CNV) data are considered the most stable amongst the multi-omic data, it leads to robust biomarkers. Thus, this paper targets the discovery of a set of CNV biomarkers for dissecting this heterogeneity. The existing algorithms yield biomarkers, too huge to be interpreted clinically. So, in this paper, we have proposed XAI-CNVMarker—an explainable AI-based post-hoc biomarker discovery framework to discover a small set of interpretable biomarkers. We exploit the power of deep learning to build DLmodel—a deep learning model for breast cancer classification. Subsequently, the trained model is analyzed using different explainable AI methods to arrive at a set of 44 CNV biomarkers. Using 5-fold cross-validation, we obtained a classification accuracy of 0.712 (± 0.048) at a 95% confidence interval. Gene set analysis revealed 37 subtype-specific enriched Reactome and Kegg pathways, 21 druggable genes, and 13 biomarkers linked with the prognostic outcome. Finally, we validated the efficacy of the identified biomarkers on METABRIC. Thus, the proposed framework demonstrates the role of explainable AI in discovering clinically reliable biomarkers.

Global transcriptome analysis of allopolyploidization reveals large-scale repression of the D-subgenome in synthetic hexaploid wheat

Synthetic hexaploid wheat (SHW) lines are created as pre-breeding germplasm to diversify the D subgenome of hexaploid wheat and capitalize upon the untapped genetic diversity of the Aegilops tauschii gene pool. However, the phenotypes observed in the Ae. tauschii parents are not always recovered in the SHW lines, possibly due to inter-subgenome interactions. To elucidate this post-polyploidization genome reprogramming phenomenon, we performed RNA-seq of four SHW lines and their corresponding tetraploid and diploid parents, across ten tissues and three biological replicates. Homoeologue expression bias (HEB) analysis using more than 18,000 triads suggests massive suppression of homoeoalleles of the D subgenome in SHWs. Comparative transcriptome analysis of the whole-genome gene set further corroborated this finding. Alternative splicing analysis of the high-confidence genes indicates an additional layer of complexity where all five splice events are identified, and retained intron is predominant. Homoeologue expression upon resynthesis of hexaploid wheat has implications to the usage and handling of this germplasm in breeding as it relates to capturing the effects of epistatic interaction across subgenomes upon polyploidization. Special considerations must be given to this germplasm in pre-breeding activities to consider the extent of the inter-subgenome interactions on gene expression and their impact on traits for crop improvement.

Exploring the genetic and genomic connection underlying neurodegeneration with brain iron accumulation and the risk for Parkinson’s disease

Neurodegeneration with brain iron accumulation (NBIA) represents a group of neurodegenerative disorders characterized by abnormal iron accumulation in the brain. In Parkinson’s Disease (PD), iron accumulation is a cardinal feature of degenerating regions in the brain and seems to be a key player in mechanisms that precipitate cell death. The aim of this study was to explore the genetic and genomic connection between NBIA and PD. We screened for known and rare pathogenic mutations in autosomal dominant and recessive genes linked to NBIA in a total of 4481 PD cases and 10,253 controls from the Accelerating Medicines Partnership Parkinsons’ Disease Program and the UKBiobank. We examined whether a genetic burden of NBIA variants contributes to PD risk through single-gene, gene-set, and single-variant association analyses. In addition, we assessed publicly available expression quantitative trait loci (eQTL) data through Summary-based Mendelian Randomization and conducted transcriptomic analyses in blood of 1886 PD cases and 1285 controls. Out of 29 previously reported NBIA screened coding variants, four were associated with PD risk at a nominal p value < 0.05. No enrichment of heterozygous variants in NBIA-related genes risk was identified in PD cases versus controls. Burden analyses did not reveal a cumulative effect of rare NBIA genetic variation on PD risk. Transcriptomic analyses suggested that DCAF17 is differentially expressed in blood from PD cases and controls. Due to low mutation occurrence in the datasets and lack of replication, our analyses suggest that NBIA and PD may be separate molecular entities.