Predictive Marker Research Articles

Platelet indices as a predictive marker in neonates with respiratory distress

BackgroundThe neonatal intensive care unit (NICU) frequently gets admissions due to respiratory distress (RD). Platelet indices are a beneficial biomarker in order to gauge the severity of neonatal RD. We aimed to assess platelet indices as a potential predictor in neonates with RD.MethodsThis prospective research involved 120 neonates who had been admitted to the NICU with evidence of RD. On admission and after respiratory support was reduced; a complete blood count (CBC) was performed to determine platelet count (PC), mean platelet volume (MPV), plateletcrit (PCT), platelet distribution width (PDW), platelet mass index (PMI), and platelet large cell ratio (PLCR).ResultsMPV and PDW were significantly higher after respiratory support reduction. PC and PMI were significantly higher in neonates exhibiting moderate and severe distress. PC of 276.5*109/L had the highest degree of predictability of RD severity (area under curve (AUC) 0.762, sensitivity 81.5%, specificity 64.3%), 95% confidence interval (0.7–0.9), while PMI of 2473.5 fL/nL was the best cut-off point to predict severity of RD (AUC 0.663, sensitivity 63%, specificity 57.1%) 95% confidence interval (0.6–0.8). There was a significant difference in the average PC between different oxygen modes.ConclusionHigher PMI and PC are associated with moderate and severe RD and can be used to predict the severity of neonatal RD.

Diagnostic performance of machine learning in systemic infection following percutaneous nephrolithotomy and identification of associated risk factors

ObjectiveThis study aims to investigate the predictive performance of machine learning in predicting the occurrence of systemic inflammatory response syndrome (SIRS) and urosepsis after percutaneous nephrolithotomy (PCNL). MethodsA retrospective analysis was conducted on patients who underwent PCNL treatment between January 2016 and July 2022. Machine learning techniques were employed to establish and select the best predictive model for postoperative systemic infection. The feasibility of using relevant risk factors as predictive markers was explored through interpretability with Machine Learning. ResultsA total of 1067 PCNL patients were included in this study, with 111 (10.4 %) patients developing SIRS and 49 (4.5 %) patients developing urosepsis. In the validation set, the risk model based on the GBM protocol demonstrated a predictive power of 0.871 for SIRS and 0.854 for urosepsis. Preoperative and postoperative platelet changes were identified as the most significant predictors. Both thrombocytopenia and thrombocytosis were found to be risk factors for SIRS or urosepsis after PCNL. Furthermore, it was observed that when the change in platelet count before and after PCNL surgery exceeded 30*109/L (whether an increase or decrease), the risk of developing SIRS or urosepsis significantly increased. ConclusionMachine learning can be effectively utilized for predicting the occurrence of SIRS or urosepsis after PCNL. The changes in platelet count before and after PCNL surgery serve as important predictors.

Longitudinal study on salivary IL-6 trajectories in postoperative OSCC patients after chemotherapy and radiotherapy

BackgroundOral squamous cell carcinoma (OSCC) poses a significant healthcare challenge globally, necessitating precise biomarkers for effective management. Interleukin-6 (IL-6) in saliva has emerged as a potential biomarker, yet its dynamics post-chemotherapy and radiotherapy remain underexplored. AimThe aim of our study is to investigate the longitudinal dynamics of salivary interleukin-6 (IL-6) expression in postoperative OSCC patients over a one-year follow-up period after chemotherapy and radiotherapy. MethodsThis longitudinal study enrolled 60 participants, including postoperative OSCC patients and controls, collecting saliva samples over one year. RT-PCR and ELISA techniques measured IL-6 expression. Statistical analyses, including repeated measures ANOVA and univariate tests, evaluated IL-6 dynamics. ResultsPre-treatment, OSCC patients exhibited elevated IL-6 levels compared to controls. Post-therapy, IL-6 levels decreased significantly with p < .0001, indicating treatment response and further result to baseline normalizing at 6-month follow-up. Significant differences were observed across treatment stages, supporting IL-6 as a diagnostic and prognostic marker for OSCC. RT-PCR and ELISA results showed the statistical significance of IL-6′s role as a predictive marker. ConclusionSalivary IL-6 emerges as a promising biomarker in OSCC management, necessitating further research to harness its diagnostic and therapeutic potential. By understanding IL-6 dynamics, personalized treatment approaches can be developed to improve patient outcomes. Longitudinal studies with larger cohorts and multi-omics approaches are warranted to validate findings and identify novel therapeutic targets.

Fractional amplitude of low-frequency fluctuations in sensory-motor networks and limbic system as a potential predictor of treatment response in patients with schizophrenia

BackgroundPrevious investigations have revealed substantial differences in neuroimaging characteristics between healthy controls (HCs) and individuals diagnosed with schizophrenia (SCZ). However, we are not entirely sure how brain activity links to symptoms in schizophrenia, and there is a need for reliable brain imaging markers for treatment prediction. MethodsIn this longitudinal study, we examined 56 individuals diagnosed with 56 SCZ and 51 HCs. The SCZ patients underwent a three-month course of antipsychotic treatment. We employed resting-state functional magnetic resonance imaging (fMRI) along with fractional Amplitude of Low Frequency Fluctuations (fALFF) and support vector regression (SVR) methods for data acquisition and subsequent analysis. ResultsIn this study, we initially noted lower fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, coupled with higher fALFF values in the left hippocampus and right putamen in SCZ patients compared to the HCs at baseline. However, when comparing fALFF values in brain regions with abnormal baseline fALFF values for SCZ patients who completed the follow-up, no significant differences in fALFF values were observed after 3 months of treatment compared to baseline data. The fALFF values in the right postcentral/precentral gyrus and left postcentral gyrus, and the left postcentral gyrus were useful in predicting treatment effects. ConclusionOur findings suggest that reduced fALFF values in the sensory-motor networks and increased fALFF values in the limbic system may constitute distinctive neurobiological features in SCZ patients. These findings may serve as potential neuroimaging markers for the prognosis of SCZ patients.

Towards Personalized Medicine in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic, incurable, multisystem, inflammatory disease characterized by synovitis and extra-articular features. Although several advanced therapies targeting inflammatory mechanisms underlying the disease are available, no advanced therapy is universally effective. Therefore, a ceiling of treatment response is currently accepted where no advanced therapy is superior to another. The current challenge for medical research is the discovery and integration of predictive markers of drug response that can be used to personalize medicine so that the patient is started on "the right drug at the right time". This review article summarizes our current understanding of predicting response to anti-rheumatic drugs in RA, obstacles impeding the development of personalized medicine approaches and future research priorities to overcome these barriers.

Immune-monitoring of myelodysplastic neoplasms: Recommendations from the i4MDS consortium.

Advancements in comprehending myelodysplastic neoplasms (MDS) have unfolded significantly in recent years, elucidating a myriad of cellular and molecular underpinnings integral to disease progression. While molecular inclusions into prognostic models have substantively advanced risk stratification, recent revelations have emphasized the pivotal role of immune dysregulation within the bone marrow milieu during MDS evolution. Nonetheless, immunotherapy for MDS has not experienced breakthroughs seen in other malignancies, partly attributable to the absence of an immune classification that could stratify patients toward optimally targeted immunotherapeutic approaches. A pivotal obstacle to establishing "immune classes" among MDS patients is the absence of validated accepted immune panels suitable for routine application in clinical laboratories. In response, we formed International Integrative Innovative Immunology for MDS (i4MDS), a consortium of multidisciplinary experts, and created the following recommendations for standardized methodologies to monitor immune responses in MDS. A central goal of i4MDS is the development of an immune score that could be incorporated into current clinical risk stratification models. This position paper first consolidates current knowledge on MDS immunology. Subsequently, in collaboration with clinical and laboratory specialists, we introduce flow cytometry panels and cytokine assays, meticulously devised for clinical laboratories, aiming to monitor the immune status of MDS patients, evaluating both immune fitness and identifying potential immune "risk factors." By amalgamating this immunological characterization data and molecular data, we aim to enhance patient stratification, identify predictive markers for treatment responsiveness, and accelerate the development of systems immunology tools and innovative immunotherapies.

Kinetics of IFNγ-Induced Cytokines and Development of Immune-Related Adverse Events in Patients Receiving PD-(L)1 Inhibitors.

Immune checkpoint inhibitors (ICI) have the potential to trigger unpredictable immune-related adverse events (irAEs), which can be severe. The underlying mechanisms of these events are not fully understood. As PD-L1 is upregulated by IFN, the heightened immune activation resulting from PD-1/PD-L1 inhibition may enhance the IFN response, triggering the expression of IFN-inducible genes and contributing to irAE development and its severity. In this study, we investigated the interplay between irAEs and the expression of IFN-inducible chemokines and cytokines in 134 consecutive patients with solid tumours treated with PD-(L)1 inhibitors as monotherapy or in combination with chemotherapy or other immunotherapy agents. We compared the plasma levels of IFN-associated cytokines (CXCL9/10/11, IL-18, IL-10, IL-6 and TGFβ) at various time points (at baseline, at the onset of irAE and previous to irAE onset) in three patient groups categorized by irAE development and severity: patients with serious irAEs, mild irAEs and without irAEs after PD-(L)1 inhibitors. No differences were observed between groups at baseline. However, patients with serious irAEs exhibited significant increases in CXCL9/10/11, IL-18 and IL-10 levels at the onset of the irAE compared to baseline. A network analysis and correlation patterns highlighted a robust relationship among these chemokines and cytokines at serious-irAE onset. Combining all of the analysed proteins in a cluster analysis, we identified a subgroup of patients with a higher incidence of serious irAEs affecting different organs or systems. Finally, an ROC analysis and a decision tree model proposed IL-18 levels ≥ 807 pg/mL and TGFβ levels ≤ 114 pg/mL as predictors for serious irAEs in 90% of cases. In conclusion, our study elucidates the dynamic changes in cytokine profiles associated with serious irAE development during treatment with PD-(L)1 inhibitors. The study's findings offer valuable insights into the intricate IFN-induced immune responses associated with irAEs and propose potential predictive markers for their severity.

Dialysate cyclophilin A as a predictive marker for historical peritonitis in patients undergoing peritoneal dialysis

IntroductionNo markers have been used to diagnose historical peritoneal dialysis (PD)-related peritonitis. Cyclophilin A (CypA) is associated with glucose toxicity and inflammation. We hypothesize that dialysate CypA can be a marker for historical peritonitis (at least 3 months free from peritonitis). MethodAn enzyme-linked immunosorbent assay kit was used to measure the concentration of dialysate CypA. Clinical and laboratory data were collected to correlate with historical peritonitis. Mann-Whitney U test and Chi-square test were used for analysis. Receiver operating characteristic (ROC) analysis was used to evaluate predictive power. ResultsOut of a total of 31 patients who had undergone PD for at least 2 years, 18 had no history of PD-related peritonitis, while 13 had experienced PD-related peritonitis at least once. Overall, the patients in this population were in good health (normal white blood cell count, no anemia, normal electrolyte and serum albumin levels). There were no significant differences between patients with and without a history of peritonitis, except for blood white blood cell count (5650.6 ± 1848.4 vs. 7154.6 ± 2056.8, p = 0.032) and dialysate CypA value (24.27 ± 22.715 vs. 54.41 ± 45.63, p = 0.020). In the univariate analysis, only the dialysate CypA level showed a statistically significant association with historical peritonitis (HR = 1.030, 95 % CI = 1.010–1.062, p = 0.046). The AUC for dialysate CypA (>34.83 ng/mL) was 0.748, with a sensitivity of 0.615 and specificity of 0.833. ConclusionPD peritonitis poses a significant threat to the long-term use of peritoneal dialysis. Based on our study, even in the absence of concurrent infection, dialysate CypA can serve as a predictive marker for historical peritonitis, demonstrating high predictive power along with fair sensitivity and good specificity.

Gene mutation profiling in microsatellite instability colorectal cancer and its association with the efficacy of immunotherapy: A retrospective study.

Microsatellite instability-high (MSI-H) colorectal cancer (CRC) is known for its heightened responsiveness to immunotherapy. However, establishing robust predictive markers for immunotherapy efficacy remains imperative. This retrospective study aimed to elucidate the genetic landscape of MSI-H CRC and correlate these genetic alterations with immunotherapy outcomes in a cohort of 121 patients. We analyzed clinical and molecular data from 121 patients with MSI-H CRC. We conducted a thorough genetic analysis of MSI-H CRC patients, with a specific emphasis on the APC, TP53, RAS, and MMR genes. We further analyzed the relationship between gene mutations and immunotherapy efficacy. The primary endpoints analyzed were objective response rate (ORR) and progression-free survival (PFS). All statistical analysis was conducted using SPSS26.0 and R 4.2.0 software. Our findings underscored the complexity of the genetic landscape in MSI-H CRC, shedding light on the intricate interplay of these genes in CRC development. Notably, mutations in MMR genes exhibited a distinctive pattern, providing insights into the underlying mechanisms of MSI-H. Furthermore, our results revealed correlations between specific genetic alterations and immunotherapy outcomes, with a particular focus on treatment response rates and progression-free survival. This study represents a significant step toward unraveling the genetic nuances of MSI-H CRC. The distinctive pattern of MMR gene mutations not only adds depth to our understanding of MSI-H CRC but also hints at potential avenues for targeted therapies. This research sets the stage for future investigations aimed at refining therapeutic strategies and improving outcomes for patients with MSI-H CRC.

In search of the ratio of miRNA expression as robust biomarkers for constructing stable diagnostic models among multi-center data.

MicroRNAs (miRNAs) are promising biomarkers for the early detection of disease, and many miRNA-based diagnostic models have been constructed to distinguish patients and healthy individuals. To thoroughly utilize the miRNA-profiling data across different sequencing platforms or multiple centers, the models accounting the batch effects were demanded for the generalization of medical application. We conducted transcription factor (TF)-mediated miRNA-miRNA interaction network analysis and adopted the within-sample expression ratios of miRNA pairs as predictive markers. The ratio of the expression values between each miRNA pair turned out to be stable across multiple data sources. A genetic algorithm-based classifier was constructed to quantify risk scores of the probability of disease and discriminate disease states from normal states in discovery, with a validation dataset for COVID-19, renal cell carcinoma, and lung adenocarcinoma. The predictive models based on the expression ratio of interacting miRNA pairs demonstrated good performances in the discovery and validation datasets, and the classifier may be used accurately for the early detection of disease.

Retrospective Analysis of Fever in Pediatric Age: Our Experience over the Last 5 Years.

Fever is one of the most frequent symptoms highlighted during medical assistance. Due to this great impact, our study has the purpose of analyzing the demographic and laboratory characteristics of patients hospitalized in our center and identifying predictive markers to make the differential diagnosis between infectious and non-infectious fever. Our population included 220 children, collected from January 2017 to August 2022, hospitalized for continuous fever (4 days or more in duration with at least one temperature peak ≥37.5 °C) and excluded cases of discharge against medical advice and/or transfer to other operating units. Demographic (mean age at the time of admission, frequency of hospitalization, and mean days of hospitalization), laboratory, and instrumental variables were analyzed in order to find correlation with fever etiology. Older age at the time of hospitalization, family history of periodic fever, fever lasting more than 8 days, and longer hospitalization are strongly associated with non-infectious fever, together with anemia, high platelet count, high CRP and ferritin, and hyponatremia at the time of admission. Paracetamol is the preferred antipyretic treatment. Echocardiogram has shown anomalies in patients with infectious fever, while ECG anomalies were detected in non-infectious fever. Our data underline the importance of predictive markers, such as clinical and laboratory parameters, to differentiate infectious from non-infectious fevers, but further studies are necessary.

Do athletic ECG changes predict athletic performance in Gurkha recruits?

IntroductionECG changes are associated with regular long-term intensive exercise due to electrical manifestations of increased vagal tone, increased ventricular wall thickness and enlarged chamber size. The aim of this study...

Vascular Endothelial Growth Factor (VEGF) and Its Role in the Progression and Development of Breast Tumor

Breast cancer is the most common type of cancer in women and is widely known. Angiogenesis is the process through which new blood vessels develop from the body's current vascular system. It is essential for tumor growth, invasiveness, and metastasis, and so plays a pivotal role in the development of carcinoma. Proteolytic and proangiogenic catalyst activators and inhibitors regulate angiogenesis in a hierarchical fashion. The angiogenic process is largely under the direction of VEGF. In a select number of malignant tumors, the VEGF gene is overexpressed. The function of VEGF in angiogenesis has been the subject of intensive study in recent years. In breast cancer patients, VEGF plasma levels are highly predictive of tumor growth and survival. Several VEGF gene polymorphisms, have been identified to affect gene expression level in prior investigations. Epidemiological studies have linked polymorphisms in the VEGF gene to altered cancer risk, tumor growth, and metastasis. Previous research on VEGF polymorphism to evaluate the association between genes and breast cancer susceptibility was scant. The current review discusses the role of VEGF in the progression of breast cancer in addition to its promising usage as a predictive marker for breast cancer.

Evaluation of the STAT1 mRNA expression in peripheral blood cells as a predictive marker of early pregnancy in Awassi ewes

The primary objective of this study was to measure the expression profile of the signal transducer activator transcription 1 (STAT1) in the circulatory leukocytes of non-pregnant/pregnant ewes and test the possibility that it could be useful for detecting early pregnancy. Whole blood was collected from 20 ewes (control) and another 5 samples were taken on days (15, 25, 35, and 50). Also, blood was collected from 30 ewes on day 15 post insemination (PI) and another 10 samples were taken on days (25, 35, and 50) PI. Total RNA was isolated from peripheral blood leukocytes (PBLs), and STAT1 expression levels were determined by quantitative real-time PCR (qRT-PCR). Gene expression for STAT1 mRNA was 5.8-fold and 5.1 times higher in gravid as opposed to non-gravid ewes. The reliable cut-off point &gt; 1.45 was established using the receiver operating characteristic (ROC) curve, and the accuracy (Acc) for detecting pregnancy was 82%, 93%, 70% and 60%, and the sensitivity (Se) was 83%, 80%, 60% and 33% and Specificity (Sp) 95% on days 15, 25, 35 and 50, respectively. The mRNA expression was lower in ewes that control non-pregnant than pregnant ewes on days 15 and 25. So The best period to detect pregnancy was 15-25 days PI.

A COMPARATIVE STUDY BETWEEN SERUM MAGNESIUM AND CALCIUM LEVELS IN PRE ECLAMPSIA VERSUS NORMOTENSIVE PATIENTS

Preelampsia is one of the most common causes of maternal and fetal morbidity and mortality. It is a recognised health challenge with devastating feto-maternal consequences. Nutritional deficiencies are commonly found in pregnant women and it is well established that the pregnant women from developing countries usually consume diets that are low in minerals and vitamins. Since the pathogenesis of preeclampsia has not been fully elucidated, the search for predictive markers and preventive strategies remains an unfulfilled issue. The study was conducted in the department of obstetrics and gynecology at Pravara Rural Hospital, Loni, Maharashtra, India to assess serum levels of calcium and magnesium in pregnant females who suffered from pre-eclampsia in comparison with normal pregnant ladies.

Absolute lymphocyte count and neutrophil-to-lymphocyte ratio as predictors of CDK 4/6 inhibitor efficacy in advanced breast cancer.

Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) are the standard agents for treating patients with estrogen receptor-positive and human epidermal growth factor receptor 2-negative advanced breast cancer (ER + HER2 - ABC). However, markers predicting the outcomes of CDK4/6i treatment have yet to be identified. This study was a single-center retrospective cohort study. We retrospectively evaluated 101 patients with ER + HER2 - ABC receiving CDK4/6i in combination with endocrine therapy at Fukuyama City Hospital between November 2017 and July 2021. We investigated the clinical outcomes and the safety of CDK4/6i treatment, and the absolute lymphocyte count (ALC) and neutrophil-to-lymphocyte ratio (NLR) as predictive markers for CDK4/6i. We defined the cut-off values as 1000/μL for ALC and 3 for NLR, and divided into "low" and "high" groups, respectively. We evaluated 43 and 58 patients who received abemaciclib and palbociclib, respectively. Patients with high ALC and low NLR had significantly longer overall survival than those with low ALC and high NLR (high vs. low; ALC: HR 0.29; 95% CI 0.12-0.70; NLR: HR 2.94; 95% CI 1.21-7.13). There was no significant difference in efficacy between abemaciclib and palbociclib and both had good safety profiles. We demonstrated that ALC and NLR might predict the outcomes of CDK4/6i treatment in patients with ER + HER2 - ABC.

Prognostic and Immunotherapeutic Predictive Value of CAD Gene in Hepatocellular Carcinoma: Integrated Bioinformatics and Experimental Analysis.

Hepatocellular carcinoma (HCC) is a common type of cancer that ranks first in cancer-associated death worldwide. Carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD) are the key components of the pyrimidine pathway, which promotes cancer development. However, the function of CAD in HCC needs to be clarified. In this study, the clinical and transcriptome data of 424 TCGA-derived HCC cases were analyzed. The results demonstrated that high CAD expression was associated with poor prognosis in HCC patients. The effect of CAD on HCC was then investigated comprehensively using GO annotation analysis, KEGG enrichment analysis, Gene Set Enrichment Analysis (GSEA), and CIBERSORT algorithm. The results showed that CAD expression was correlated with immune checkpoint inhibitors and immune cell infiltration. In addition, low CAD levels in HCC patients predicted increased sensitivity to anti-CTLA4 and PD1, while HCC patients with high CAD expression exhibited high sensitivity to chemotherapeutic and molecular-targeted agents, including gemcitabine, paclitaxel, and sorafenib. Finally, the results from clinical sample suggested that CAD expression increased remarkably in HCC compared with non-cancerous tissues. Loss of function experiments demonstrated that CAD knockdown could significantly inhibit HCC cell growth and migration both in vitro and in vivo. Collectively, the results indicated that CAD is a potential oncogene during HCC metastasis and progression. Therefore, CAD is recommended as a candidate marker and target for HCC prediction and treatment.

Hemoglobin, Ferritin, and Lactate Dehydrogenase as Predictive Markers for Neonatal Sepsis.

(1) Background: This study evaluates the predictive effectiveness of biomarkers in diagnosing newborn sepsis. (2) Methods: This was a case-control study conducted on neonates hospitalized at the Clinical Hospital "Louis Turcanu", Timisoara, Romania, from October 2018 to July 2023. Using a vacutainer collection device, venous blood was collected at admission for complete blood tests, including ferritin, hemoglobin, LDH, and blood culture analysis. Neonates were divided into two groups: sepsis-positive and sepsis-negative. The outcome of interest was a diagnosis of sepsis. (3) Results: Data from 86 neonates, 51 of whom had been confirmed to have sepsis, were analyzed. This study found no significant difference in gestational age, infant weight, fetal growth restriction, or APGAR score between neonates with and without sepsis. However, there was a higher incidence of sepsis among neonates delivered via cesarean section. Neonatal patients with sepsis showed significantly higher levels of neonatal serum ferritin and LDH compared to those without sepsis. Ferritin and LDH biomarkers demonstrated excellent discriminatory capabilities in diagnosing neonatal sepsis. Logistic regression analysis revealed a significant association between elevated ferritin and LDH levels and the likelihood of neonatal sepsis, while anemia did not show a significant association. (4) Conclusions: LDH and ferritin concentrations are found to be predictive biomarkers for neonatal sepsis, indicating a potential role in detecting susceptible neonates and implementing prompt interventions to improve patient outcomes.

Divergent Cellular Expression Patterns of PD-L1 and PD-L2 Proteins in Breast Cancer.

PD-L1 immunohistochemistry (IHC) has become an established method for predicting cancer response to targeted anti-PD1 immunotherapies, including breast cancer (BC). The alternative PD-1 ligand, PD-L2, remains understudied but may be a complementary predictive marker. Prospective analysis of 32 breast cancers revealed divergent expression patterns of PD-L1 and PD-L2. PD-L1-positivity was higher in immune cells than in cancer cells (median = 5.0% vs. 0.0%; p = 0.001), whereas PD-L2-positivity was higher in cancer cells than immune cells (median = 30% vs. 5.0%; p = 0.001). Percent positivity of PD-L1 and PD-L2 were not correlated, neither in cancer cells nor immune cells. Based on a cut-point of ≥1% positivity, ER+ tumors (n = 23) were frequently PD-L2-positive (73.9%), whereas only 40.9% were PD-L1-positive. These data suggest differential control of cellular PD-L1 and PD-L2 expression in BC and a potential role for PD-L2 IHC as a complementary marker to PD-L1 to improve selection of aggressive ER+ BC that may benefit from anti-PD-1 therapy.

Inflammatory Protein Signatures as Predictive Disease-Specific Markers for Non-Alcoholic Steatohepatitis (NASH).

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic disease worldwide, consisting of a broad spectrum of diseases such as simple steatosis (NAFL), non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and hepatocellular carcinoma. Hepatic inflammation plays a key role in the pathophysiology of NAFLD. Inflammatory mediators such as cytokines and chemokines are considered as contributing factors to NAFLD development and progression. In the present study, we aimed to investigate the inflammatory protein signatures as predictive disease-specific markers for non-alcoholic fatty liver disease (NAFLD). This cross-sectional study included healthy control (n = 64), NAFL (n = 109), and NASH (n = 60) human subjects. Serum concentrations of various cytokines and chemokines were evaluated using sensitive multiplex assays. We used principal component analysis (PCoA) to reveal distinct differences in the levels of cytokines and chemokines between each of the study groups. Further, a random forest classification model was developed to identify the panel of markers that could predict diseases. The protein-protein network analysis was performed to determine the various signaling pathways associated with the disease-specific panel of markers. Serum concentrations of TNF-α, IL-1β, IL-1ra, G-CSF, PDGF-BB, MCP-1, MIP-1a, MIP-1b, RANTES, eotaxin, IL-8 and IP-10 were significantly increased in NASH group as compared to control group. Furthermore, serum concentrations of IL-9 and IL-13 were significantly lower in the NASH group, whereas IL-2 levels were significantly decreased in the NAFL group when compared to the control group. PCoA results demonstrated statistically significant differences in cytokines and chemokines between each of the study groups (PERMANOVA p = 0.001; R2 = 0.102). RANTES, IL-1ra, MIP-1b, IL-2, and G-CSF could differentiate the NAFL group from the controls; G-CSF, IL-1ra, TNF-α, RANTES, and IL-9 could differentiate the NASH group from the controls; and G-CSF, IL-9, IL-13, eotaxin, and TNF- α could differentiate the NASH group from the NAFL group. Our protein-protein network revealed that these markers are involved in cytokine-cytokine receptor interaction, Th1 and Th2 cell differentiation, TNF, chemokine, JAK/STAT, P13K/Akt, TLR, NOD-like receptor, NF-kB, and adipocytokine signaling pathways which might be responsible for disease pathogenesis.Our study findings revealed a set of distinct cytokine and chemokine markers and they might be considered as biomarkers in distinguishing NASH from NAFL. Future multicentre studies with larger sample size are recommended to determine the potential utility of these panels of markers.