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BioRxiv : the Preprint Server For... Jun 2024Kidney disease is highly heritable; however, the causal genetic variants, the cell types in which these variants function, and the molecular mechanisms underlying kidney...
Kidney disease is highly heritable; however, the causal genetic variants, the cell types in which these variants function, and the molecular mechanisms underlying kidney disease remain largely unknown. To identify genetic loci affecting kidney function, we performed a GWAS using multiple kidney function biomarkers and identified 462 loci. To begin to investigate how these loci affect kidney function, we generated single-cell chromatin accessibility (scATAC-seq) maps of the human kidney and identified candidate -regulatory elements (cCREs) for kidney podocytes, tubule epithelial cells, and kidney endothelial, stromal, and immune cells. Kidney tubule epithelial cCREs explained 58% of kidney function SNP-heritability and kidney podocyte cCREs explained an additional 6.5% of SNP-heritability. In contrast, little kidney function heritability was explained by kidney endothelial, stromal, or immune cell-specific cCREs. Through functionally informed fine-mapping, we identified putative causal kidney function variants and their corresponding cCREs. Using kidney scATAC-seq data, we created a deep learning model (which we named ChromKid) to predict kidney cell type-specific chromatin accessibility from sequence. ChromKid and allele specific kidney scATAC-seq revealed that many fine-mapped kidney function variants locally change chromatin accessibility in tubule epithelial cells. Enhancer assays confirmed that fine-mapped kidney function variants alter tubule epithelial regulatory element function. To map the genes which these regulatory elements control, we used CRISPR interference (CRISPRi) to target these regulatory elements in tubule epithelial cells and assessed changes in gene expression. CRISPRi of enhancers harboring kidney function variants regulated and expression. Thus, inherited differences in tubule epithelial and expression may predispose to kidney disease in humans. We conclude that genetic variants affecting tubule epithelial regulatory element function account for most SNP-heritability of human kidney function. This work provides an experimental approach to identify the variants, regulatory elements, and genes involved in polygenic disease.
PubMed: 38948875
DOI: 10.1101/2024.06.18.599625 -
BioRxiv : the Preprint Server For... Jun 2024A single arm trial (NCT007773097) and a double-blind, placebo controlled randomized trial ( NCT02134925 ) were conducted in individuals with a history of advanced...
A single arm trial (NCT007773097) and a double-blind, placebo controlled randomized trial ( NCT02134925 ) were conducted in individuals with a history of advanced colonic adenoma to test the safety and immunogenicity of the MUC1 tumor antigen vaccine and its potential to prevent new adenomas. These were the first two trials of a non-viral cancer vaccine administered in the absence of cancer. The vaccine was safe and strongly immunogenic in 43% (NCT007773097) and 25% ( NCT02134925 ) of participants. The lack of response in a significant number of participants suggested, for the first time, that even in a premalignant setting, the immune system may have already been exposed to some level of suppression previously reported only in cancer. Single-cell RNA-sequencing (scRNA-seq) on banked pre-vaccination peripheral blood mononuclear cells (PBMCs) from 16 immune responders and 16 non-responders identified specific cell types, genes, and pathways of a productive vaccine response. Responders had a significantly higher percentage of CD4+ naive T cells pre-vaccination, but a significantly lower percentage of CD8+ T effector memory (TEM) cells and CD16+ monocytes. Differential gene expression (DGE) and transcription factor inference analysis showed a higher level of expression of T cell activation genes, such as Fos and Jun, in CD4+ naive T cells, and pathway analysis showed enriched signaling activity in responders. Furthermore, Bayesian network analysis suggested that these genes were mechanistically connected to response. Our analyses identified several immune mechanisms and candidate biomarkers to be further validated as predictors of immune responses to a preventative cancer vaccine that could facilitate selection of individuals likely to benefit from a vaccine or be used to improve vaccine responses.
PubMed: 38948837
DOI: 10.1101/2024.06.14.598031 -
BioRxiv : the Preprint Server For... Jun 2024Cirrhosis, advanced liver disease, affects 2-5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and...
UNLABELLED
Cirrhosis, advanced liver disease, affects 2-5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and experience life-threatening complications such as gastrointestinal bleeding, confusion (hepatic encephalopathy), and ascites, reducing life expectancy from 12 to less than 2 years. Among patients with compensated cirrhosis, identifying patients at high risk of decompensation is critical to optimize care and reduce morbidity and mortality. Therefore, it is important to preferentially direct them towards specialty care which cannot be provided to all patients with cirrhosis. We used discovery Top-down Proteomics (TDP) to identify differentially expressed proteoforms (DEPs) in the plasma of patients with progressive stages of liver cirrhosis with the ultimate goal to identify candidate biomarkers of disease progression. In this pilot study, we identified 209 DEPs across three stages of cirrhosis (compensated, compensated with portal hypertension, and decompensated), of which 115 derived from proteins enriched in the liver at a transcriptional level and discriminated the three stages of cirrhosis. Enrichment analyses demonstrated DEPs are involved in several metabolic and immunological processes known to be impacted by cirrhosis progression. We have preliminarily defined the plasma proteoform signatures of cirrhosis patients, setting the stage for ongoing discovery and validation of biomarkers for early diagnosis, risk stratification, and disease monitoring.
HIGHLIGHTS
Performed a pilot top-down LC-MS/MS analysis to identify proteoforms (PFRs) in the plasma of patients with 3 progressive stages of liver cirrhosis.Identified 2867 proteoforms (PFRs) and 209 differentially regulated proteoforms (DRPs) in the different stages of the disease.Identified DRP profiles able to potentially distinguish early from late stages of the disease, including 115 liver-derived DRPs.Fibrinogen alpha chain, haptoglobin, and Apo A-I are the proteins with the highest number of DRPs and represent potential candidate biomarkers of liver cirrhosis progression.
PubMed: 38948836
DOI: 10.1101/2024.06.19.599662 -
BioRxiv : the Preprint Server For... Jun 2024HIV-induced persistent immune activation is a key mediator of inflammatory comorbidities such as cardiovascular disease (CVD) and neurocognitive disorders. While a...
HIV-induced persistent immune activation is a key mediator of inflammatory comorbidities such as cardiovascular disease (CVD) and neurocognitive disorders. While a preponderance of data indicate that gut barrier disruption and microbial translocation are drivers of chronic immune activation, the molecular mechanisms of this persistent inflammatory state remain poorly understood. Here, utilizing the nonhuman primate model of HIV infection with suppressive antiretroviral therapy (ART), we investigated activation of inflammasome pathways and their association with intestinal epithelial barrier disruption and CVD pathogenesis. Longitudinal blood samples obtained from rhesus macaques with chronic SIV infection and long-term suppressive ART were evaluated for biomarkers of intestinal epithelial barrier disruption (IEBD), inflammasome activation (IL-1β and IL-18), inflammatory cytokines, and triglyceride (TG) levels. Activated monocyte subpopulations and glycolytic potential were investigated in peripheral blood mononuclear cells (PBMCs). Higher plasma levels of IL-1β and IL-18 were observed following the hallmark increase in IEBD biomarkers, intestinal fatty acid-binding protein (IFABP) and LPS-binding protein (LBP), during the chronic phase of treated SIV infection. Further, significant correlations of plasma IFABP levels with IL-1β and IL-18 were observed between 10-12 months of ART. Higher levels of sCD14, IL-6, and GM-CSF, among other inflammatory mediators, were also observed only during the long-term SIV+ART phase along with a trend of increase in frequencies of activated CD14 CD16 intermediate monocyte subpopulations. Lastly, we found elevated levels of blood TG and higher glycolytic capacity in PBMCs of chronic SIV-infected macaques with long-term ART. The increase in circulating IL-18 and IL-1β following IEBD and their significant positive correlation with IFABP suggest a connection between gut barrier disruption and inflammasome activation during chronic SIV infection, despite viral suppression with ART. Additionally, the increase in markers of monocyte activation, along with elevated TG and enhanced glycolytic pathway activity, indicates metabolic remodeling that could accelerate CVD pathogenesis. Further research is needed to understand mechanisms by which gut dysfunction and inflammasome activation contribute to HIV-associated CVD and metabolic complications, enabling targeted interventions in people with HIV.
PubMed: 38948748
DOI: 10.1101/2024.06.14.599106 -
BioRxiv : the Preprint Server For... Jun 2024Early diagnosis and biomarker discovery to bolster the therapeutic pipeline for Parkinson's disease (PD) are urgently needed. In this study, we leverage the large-scale...
UNLABELLED
Early diagnosis and biomarker discovery to bolster the therapeutic pipeline for Parkinson's disease (PD) are urgently needed. In this study, we leverage the large-scale whole-blood total RNA-seq dataset from the Accelerating Medicine Partnership in Parkinson's Disease (AMP PD) program to identify PD-associated RNAs, including both known genes and novel circular RNAs (circRNA) and enhancer RNAs (eRNAs). There were 1,111 significant marker RNAs, including 491 genes, 599 eRNAs, and 21 circRNAs, that were first discovered in the PPMI cohort (FDR < 0.05) and confirmed in the PDBP/BioFIND cohorts (nominal < 0.05). Functional enrichment analysis showed that the PD-associated genes are involved in neutrophil activation and degranulation, as well as the TNF-alpha signaling pathway. We further compare the PD-associated genes in blood with those in post-mortem brain dopamine neurons in our BRAINcode cohort. 44 genes show significant changes with the same direction in both PD brain neurons and PD blood, including neuroinflammation-associated genes , , and . Finally, we built a novel multi-omics machine learning model to predict PD diagnosis with high performance (AUC = 0.89), which was superior to previous studies and might aid the decision-making for PD diagnosis in clinical practice. In summary, this study delineates a wide spectrum of the known and novel RNAs linked to PD and are detectable in circulating blood cells in a harmonized, large-scale dataset. It provides a generally useful computational framework for further biomarker development and early disease prediction.
SIGNIFICANCE STATEMENT
Early and accurate diagnosis of Parkinson's disease (PD) is urgently needed. However, biomarkers for early detection of PD are still lacking. Also, the limit of sample size remains one of the main pitfalls of current PD biomarker studies. We employed an analysis of large-scale whole-blood RNA-seq data. By identifying 1,111 significant marker RNAs, we establish a robust foundation for early PD detection, which implicated in neutrophil activation, degranulation, and TNF-alpha signaling, offer unprecedented insights into PD pathogenesis. Our multi-omics machine learning model, boasting an AUC of 0.89, outperforms previous studies, promising a transformative tool for precise PD diagnosis in clinical settings. This study marks a pivotal step toward enhanced biomarker development and early disease prediction.
PubMed: 38948706
DOI: 10.1101/2024.06.18.599639 -
Cancer Management and Research 2024As one of the most important breakthroughs in cancer therapy, immune checkpoint inhibitors have greatly prolonged survival of patients with breast cancer. However, their...
Efficacy and Safety of Chidamide in Combination with PD-1 Inhibitor and Radiotherapy for HER2-Negative Advanced Breast Cancer: Study Protocol of a Single Arm Prospective Study.
PURPOSE
As one of the most important breakthroughs in cancer therapy, immune checkpoint inhibitors have greatly prolonged survival of patients with breast cancer. However, their application and efficacy are limited, especially for advanced HER2-negative breast cancer. It has been reported that epigenetic modulation of the histone deacetylase (HDAC) inhibitor chidamide, as well as immune microenvironment modulation of radiotherapy are potentially synergistic with immunotherapy. Thus, the combination of chidamide, radiotherapy and immunotherapy is expected to improve prognosis of patients with advanced HER2-negative breast cancer.
PATIENTS AND METHODS
This is a single-arm, open, prospective clinical trial investigating the efficacy and safety of the combination of HDAC inhibitor chidamide, anti-PD-1 antibody sintilimab, and the novel immuno-radiotherapy, which aims to enhance efficacy of immunotherapy, in subsequent lines of therapy of HER2-negative breast cancer. Our study will include 35 patients with advanced breast cancer that has failed endocrine therapy and first-line chemotherapy. Participants will receive 30 mg of chidamide twice a week, 200 mg of sintilimab once every 3 weeks, combined with immuno-radiotherapy. Radiotherapy will be centrally 8 Gy for at least one lesion, and at least 1 Gy for the other lesions. We will complete three fractions of radiotherapy in one cycle. The primary endpoint is progression-free survival, and secondary endpoints are objective response rate, disease control rate and safety. Moreover, biomarkers including cytokines and lymphocyte subgroups will be explored.
CONCLUSION
As a single-arm clinical trial, the analysis of the influence of each single treatment is limited. Besides, our study is an open study, which involves neither randomization nor blinding. In spite of the abovementioned limitations, this prospective clinical trial will give an insight into subsequent lines of therapy of HER2-negative advanced breast cancer, prolong the survival or achieve long remission for these participants, and identify potential responders.
PubMed: 38948681
DOI: 10.2147/CMAR.S464677 -
Journal of Family Medicine and Primary... May 2024The severity of laboratory and imaging finding was found to be inconsistent with clinical symptoms in COVID-19 patients, thereby increasing casualties. As compared to...
Machine learning-aided algorithm design for prediction of severity from clinical, demographic, biochemical and immunological parameters: Our COVID-19 experience from the pandemic.
BACKGROUND
The severity of laboratory and imaging finding was found to be inconsistent with clinical symptoms in COVID-19 patients, thereby increasing casualties. As compared to conventional biomarkers, machine learning algorithms can learn nonlinear and complex interactions and thus improve prediction accuracy. This study aimed at evaluating role of biochemical and immunological parameters-based machine learning algorithms for severity indexing in COVID-19.
METHODS
Laboratory biochemical results of 5715 COVID-19 patients were mined from electronic records including 509 admitted in COVID-19 ICU. Random Forest Classifier (RFC), Support Vector Machine (SVM), Naive Bayesian Classifier (NBC) and K-Nearest Neighbours (KNN) classifier models were used. Lasso regression helped in identifying the most influential parameter. A decision tree was made for subdivided data set, based on randomization.
RESULTS
Accuracy of SVM was highest with 94.18% and RFC with 94.04%. SVM had highest PPV (1.00), and NBC had highest NPV (0.95). QUEST modelling ignored age, urea and total protein, and only C-reactive protein and lactate dehydrogenase were considered to be a part of decision-tree algorithm. The overall percentage of correct classification was 78.31% in the overall algorithm with a sensitivity of 87.95% and an AUC of 0.747.
CONCLUSION
C-reactive protein and lactate dehydrogenase being routinely performed tests in clinical laboratories in peripheral setups, this algorithm could be an effective predictive tool. SVM and RFC models showed significant accuracy in predicting COVID-19 severity and could be useful for future pandemics.
PubMed: 38948617
DOI: 10.4103/jfmpc.jfmpc_1752_23 -
Journal of Family Medicine and Primary... May 2024Symptoms for severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) appear 2-3 days after exposure to the virus. Being a virus, detection is primarily by...
BACKGROUND
Symptoms for severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) appear 2-3 days after exposure to the virus. Being a virus, detection is primarily by polymerase chain reaction as this offers superior sensitivity and specificity. There was a misconception that patients with low cycle threshold (Ct) have severe coronavirus disease (COVID), and for individuals with higher Ct, it is the other way around. The prognosis for COVID was derived from various biomarkers and physicians heavily relied on them.
MATERIALS AND METHODS
A cross-sectional study spanning a duration of 2 years was conducted at a tertiary care centre in western India. A total of 201 individuals were included and the correlation between Ct, clinical features and biomarkers was studied.
RESULTS
In the E-gene, 43.28% had lower Ct values and 40.79% had low Ct values in the RdRp gene. 50% of all patients had diabetes, with 60% being between the ages of 61 and 80. 54.1% of hypertension patients belonged to ages between 61 and 80. 90.54% of COVID-positive individuals had lactose dehydrogenase levels ranging from 440 to 760. 79% of patients had a procalcitonin value of more than one but less than six. 79.1% of patients had an erythrocyte sedimentation rate between 36 and 90.
CONCLUSION
Ct value though has a research value; it is a poor prognostic marker when compared to the various biomarkers that have been studied earlier. We cannot conclusively state that all our findings are accurate due to a lack of data but further research into the prognostic value of Ct should be conducted which will help in the ongoing scenario.
PubMed: 38948616
DOI: 10.4103/jfmpc.jfmpc_967_23 -
Journal of Family Medicine and Primary... May 2024Biomarkers to predict the onset and progression of chronic kidney disease (CKD) in children are lacking, and no such definite biomarkers have been implicated in the...
BACKGROUND
Biomarkers to predict the onset and progression of chronic kidney disease (CKD) in children are lacking, and no such definite biomarkers have been implicated in the diagnosis of CKD. We conducted this study to evaluate copeptin as a CKD marker and predict the disease progression by estimating the copeptin levels at baseline and 12 months follow-up in children with CKD stage 2 and above.
MATERIALS AND METHODS
This prospective single-centre cohort study was conducted in children under 14 years with CKD stages 2-4. Blood and urine samples were collected at enrolment and 1-year follow-up for routine investigations and serum copeptin, cystatin C and urinary neutrophil gelatinase-associated lipocalcin (uNGAL) estimation.
RESULTS
A total of 110 children (60 cases and 50 controls) were enrolled in the study. The mean estimated glomerular filtration rate (eGFR) of cases was 58.3 ± 18.7 ml/min/1.73 m. Among the cases, there was a significant rise in the serum copeptin levels from baseline 483.08 ± 319.2 pg/ml to follow-up at 1 year, that is, 1046.82 ± 823.53 pg/ml ( < 0.0001). A significant difference was noted in the baseline values of serum cystatin C, that is, 1512.98 ± 643.77 ng/ml and 719.68 ± 106.96 ng/ml ( < 0.0001), and uNGAL, that is, 13.53 ± 11.72 and 1.76 ± 2.37 ng/ml ( < 0.0001) between the cases and controls. There was no significant correlation (correlation coefficient = 0.10) between change in eGFR and copeptin levels during 12 months of follow-up.
CONCLUSION
No significant correlation was found between the change in eGFR and copeptin levels during 12 months of follow-up. This can be due to the slow deterioration of renal functions, as most of the cases had underlying congenital anomalies of the kidney and urinary tract (CAKUT), which is known to have a slow progression of CKD and a small sample size.
PubMed: 38948594
DOI: 10.4103/jfmpc.jfmpc_1707_23 -
Cancer Innovation Feb 2024In recent years, the three-dimensional (3D) culture system has emerged as a promising preclinical model for tumor research owing to its ability to replicate the tissue... (Review)
Review
In recent years, the three-dimensional (3D) culture system has emerged as a promising preclinical model for tumor research owing to its ability to replicate the tissue structure and molecular characteristics of solid tumors in vivo. This system offers several advantages, including high throughput, efficiency, and retention of tumor heterogeneity. Traditional Matrigel-submerged organoid cultures primarily support the long-term proliferation of epithelial cells. One solution for the exploration of the tumor microenvironment is a reconstitution approach involving the introduction of exogenous cell types, either in dual, triple or even multiple combinations. Another solution is a holistic approach including patient-derived tumor fragments, air-liquid interface, suspension 3D culture, and microfluidic tumor-on-chip models. Organoid co-culture models have also gained popularity for studying the tumor microenvironment, evaluating tumor immunotherapy, identifying predictive biomarkers, screening for effective drugs, and modeling infections. By leveraging these 3D culture systems, it is hoped to advance the clinical application of therapeutic approaches and improve patient outcomes.
PubMed: 38948532
DOI: 10.1002/cai2.101