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Hire Dr. Animesh Acharjee
United Kingdom
USD 50 /hr

Freelance Data Scientist I Biomarker Discovery and Statistical Bioinformatics | Expert in R

Profile Summary
Subject Matter Expertise
Services
Scientific writing Grant proposal, Journal article
Data science & analysis Simple data analysis, Complex data analysis, Statistical analysis, Data visualization
Academic research Literature search
Work Experience

The University of Birmingham

- Present

University of Birmingham

September 2017 - Present

Investigator Scientist

University of Cambridge

February 2014 - January 2017

Systems Biologist

BASF - Crop Design, Gent, Belgium

February 2012 - February 2014

Biostatistician

Synergie Lyon Cancer, Lyon, France

June 2011 - February 2012

Education

PhD

Wageningen University

July 2007 - June 2011

Certifications
  • Certification details not provided.
Publications
JOURNAL ARTICLE
Hannah Wood, Hayden Pearce, Mohammed Nabil Quraishi, Richard Powell, Amanda Rossiter, Andrew Beggs, Andrew Ewer, Paul Moss, Gergely Toldi, Animesh Acharjee(2021). Breastfeeding promotes early neonatal regulatory T‐cell expansion and immune tolerance of non‐inherited maternal antigens . Allergy. 76. (8). p. 2447--2460. Wiley
Multimorbidity prediction using link prediction @article{1f421d85990e4e3985a7b6b59659b578, title = "Multimorbidity prediction using link prediction", abstract = "Multimorbidity, frequently associated with aging, can be operationally defined as the presence of two or more chronic conditions. Predicting the likelihood of a patient with multimorbidity to develop a further particular disease in the future is one of the key challenges in multimorbidity research. In this paper we are using a network-based approach to analyze multimorbidity data and develop methods for predicting diseases that a patient is likely to develop. The multimorbidity data is represented using a temporal bipartite network whose nodes represent patients and diseases and a link between these nodes indicates that the patient has been diagnosed with the disease. Disease prediction then is reduced to a problem of predicting those missing links in the network that are likely to appear in the future. We develop a novel link prediction method for static bipartite network and validate the performance of the method on benchmark datasets. By using a probabilistic framework, we then report on the development of a method for predicting future links in the network, where links are labelled with a time-stamp. We apply the proposed method to three different multimorbidity datasets and report its performance measured by different performance metrics including AUC, Precision, Recall, and F-Score.", author = "Furqan Aziz and {Roth Cardoso}, Victor and Laura Bravo-Merodio and Dominic Russ and Samantha Pendleton and John Williams and Animesh Acharjee and Georgios Gkoutos", note = "Funding Information: The authors acknowledge support from the NIHR Birmingham ECMC, NIHR Birmingham SRMRC, Nanocom-mons H2020-EU (731032) and the NIHR Birmingham Biomedical Research Centre and the MRC Heath Data Research UK (HDRUK/CFC/01), an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and the devolved administrations, and leading medical research charities. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research, the Medical Research Council or the Department of Health. Publisher Copyright: {\textcopyright} 2021, The Author(s).", year = "2021", month = aug, day = "12", doi = "10.1038/s41598-021-95802-0", language = "English", volume = "11", journal = "Scientific Reports", issn = "2045-2322", publisher = "Nature Publishing Group", number = "1", } . Scientific Reports.
Animesh Acharjee, Vartika Bisht, Georgios V. Gkoutos(2021). NFnetFu: A novel workflow for microbiome data fusion . Computers in Biology and Medicine. 135. p. 104556. Elsevier {BV}
NFnetFu @article{fd400aaa427649cc99ef7c8782f53ab7, title = "NFnetFu: A novel workflow for microbiome data fusion", abstract = "Microbiome data analysis and its interpretation into meaningful biological insights remain very challenging for numerous reasons, perhaps most prominently, due to the need to account for multiple factors, including collinearity, sparsity (excessive zeros) and effect size, that the complex experimental workflow and subsequent downstream data analysis require. Moreover, a meaningful microbiome data analysis necessitates the development of interpretable models that incorporate inferences across available data as well as background biomedical knowledge. We developed a multimodal framework that considers sparsity (excessive zeros), lower effect size, intrinsically microbial correlations, i.e., collinearity, as well as background biomedical knowledge in the form of a cluster-infused enriched network architecture. Finally, our framework also provides a candidate taxa/Operational Taxonomic Unit (OTU) that can be targeted for future validation experiments. We have developed a tool, the term NFnetFU (Neuro Fuzzy network Fusion), that encompasses our framework and have made it freely available at https://github.com/VartikaBisht6197/NFnetFu.", keywords = "Microbiome, Fuzzy inference, Clustering, Network fusion", author = "Vartika Bisht and Animesh Acharjee and Gkoutos, {Georgios V}", year = "2021", month = aug, doi = "10.1016/j.compbiomed.2021.104556", language = "English", volume = "135", journal = "Computers in biology and medicine", issn = "0010-4825", publisher = "Elsevier", } . Computers in Biology and Medicine.
Animesh Acharjee, John A. Williams, Dominic Russ, Laura Bravo-Merodio, Victor Roth Cardoso, Samantha C. Pendleton, Furqan Aziz, Georgios V. Gkoutos (2021). A Causal Web between Chronotype and Metabolic Health Traits . Genes.
A causal web between chronotype and metabolic health traits @article{45a7ae0fbba44477805c716e3ff610a4, title = "A causal web between chronotype and metabolic health traits", abstract = "Observational and experimental evidence has linked chronotype to both psychological and cardiometabolic traits. Recent Mendelian randomization (MR) studies have investigated direct links between chronotype and several of these traits, often in isolation of outside potential mediating or moderating traits. We mined the EpiGraphDB MR database for calculated chronotype–trait associations (p-value < 5 × 10−8). We then re-analyzed those relevant to metabolic or mental health and investigated for statistical evidence of horizontal pleiotropy. Analyses passing multiple testing correction were then investigated for confounders, colliders, intermediates, and reverse intermediates using the EpiGraphDB database, creating multiple chronotype–trait interactions among each of the the traits studied. We revealed 10 significant chronotype–exposure associations (false discovery rate < 0.05) exposed to 111 potential previously known confounders, 52 intermediates, 18 reverse intermediates, and 31 colliders. Chronotype–lipid causal associations collided with treatment and diabetes effects; chronotype–bipolar associations were mediated by breast cancer; and chronotype–alcohol intake associations were impacted by confounders and intermediate variables including known zeitgebers and molecular traits. We have reported the influence of chronotype on several cardiometabolic and behavioural traits, and identified potential confounding variables not reported on in studies while discovering new associations to drugs and disease.", keywords = "circadian rhythm, chronotype, diabetes, alcohol intake, bipolar disorder, mendelian randomization", author = "Williams, {John A.} and Dominic Russ and Merodio, {Laura Bravo} and Cardoso, {Victor Roth} and Samantha Pendleton and Furqan Aziz and Animesh Acharjee and Georgios Gkoutos", year = "2021", month = jul, day = "1", doi = "10.3390/genes12071029", language = "English", volume = "12", journal = "Genes", issn = "2073-4425", publisher = "MDPI", number = "7", } . Genes.
Animesh Acharjee, John A. Williams, Dominic Russ, Laura Bravo Merodio, Victor Roth Cardoso, Samantha Pendleton, Furqan Aziz, Georgios Gkoutos (2021). A Causal Web between Chronotype and Metabolic Health Traits . Genes.
Animesh Acharjee, Tanya M. Monaghan, Rima N. Biswas, Rupam R. Nashine, Samidha S. Joshi, Benjamin Mullish, Anna M. Seekatz, Jesus Miguens Blanco, Julie A. K. McDonald, Julian Marchesi, et al. (2021). Multiomics Profiling Reveals Signatures of Dysmetabolism in Urban Populations in Central India . Microorganisms.
Animesh Acharjee, Vartika Bisht, Katrina Nash, Yuanwei Xu, Prasoon Agarwal, Sofie Bosch, Georgios V. Gkoutos(2021). Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer . International Journal of Molecular Sciences. 22. (11). p. 5763. {MDPI} {AG}
Animesh Acharjee, Marietta Iacucci, Louisa Jeffery, Olga Maria Nardone, Davide Zardo, Samuel C L Smith, Alina Bazarova, Rosanna Cannatelli, Uday N Shivaji, John Williams, et al.(2021). Ultra-high Magnification Endocytoscopy and Molecular Markers for Defining Endoscopic and Histologic Remission in Ulcerative Colitis—An Exploratory Study to Define Deep Remission . Inflammatory Bowel Diseases. Oxford University Press ({OUP})
Animesh Acharjee, Vartika Bisht, Katrina Nash, Yuanwei Xu, Prasoon Agarwal, Sofie Bosch, Georgios Gkoutos (2021). Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer . International Journal of Molecular Sciences.
Animesh Acharjee, Zsuzsanna Ament, Matthew B. Bevers, Zoe Wolcott, W. Taylor Kimberly(2021). Uric Acid and Gluconic Acid as Predictors of Hyperglycemia and Cytotoxic Injury after Stroke . Translational Stroke Research. Springer Science and Business Media {LLC}
Traumatic injury is associated with reduced deoxyribonuclease activity and dysregulation of the actin scavenging system @article{2a2437dd6a3c47b8bcf9ad45d1c6a87c, title = "Traumatic injury is associated with reduced deoxyribonuclease activity and dysregulation of the actin scavenging system", abstract = "Background: Traumatic injury is associated with increased concentrations of cell-free DNA (cfDNA) in the circulation, which contribute to post-injury complications. The endonuclease deoxyribonuclease 1 (DNase-1) is responsible for removing 90% of circulating cfDNA. Recently, DNase activity was reported to be significantly reduced following major non-traumatic brain injury (TBI), but the processes responsible were not investigated. Moreover, it is not known how quickly following injury DNase activity is reduced and whether this also occurs after TBI.Methods: At 3 post-injury time points (≤1, 4–12 and 48–72 hours), blood samples were obtained from 155 adult trauma patients that had sustained an isolated TBI (n = 21), TBI with accompanying extracranial injury (TBI+) (n = 53) or an extracranial injury only (ECI) (n = 81). In addition to measuring cfDNA levels and the activity and expression of DNase, circulating concentrations of monomeric globular action (G-actin), an inhibitor of DNase-1, and the actin scavenging proteins gelsolin (GSN) and vitamin D binding protein (VDBP) were determined and values compared to a cohort of healthy controls.Results: Significantly elevated concentrations of plasma cfDNA were seen in TBI, TBI+ and ECI patients at all study time points when compared to healthy controls. cfDNA levels were significantly higher at ≤1 hour post-injury in ECI patients who subsequently developed multiple organ dysfunction syndrome when compared to those who did not. Plasma DNase-1 protein was significantly elevated in all patient groups at all sampling time points. In contrast, DNase enzyme activity was significantly reduced, with this impaired function evident in TBI+ patients within minutes of injury. Circulating concentrations of G-actin were elevated in all patient cohorts in the immediate aftermath of injury and this was accompanied by a significant reduction in the levels of GSN and VDBP.Conclusions: The post-traumatic increase in circulating cfDNA that occurs following extracranial trauma and TBI is accompanied by reduced DNase activity. We propose that, secondary to reduced GSN and VDBP levels, elevated circulating concentrations of G-actin underlie the post-injury reduction in DNase activity. Reducing circulating cfDNA levels via therapeutic restoration of DNase-1 activity may improve clinical outcomes post-injury.", keywords = "Cell-free DNA, Deoxyribonuclease, Extracellular actin scavenging system, Pre-hospital, Trauma", author = "Jon Hazeldine and Rob Dinsdale and David Naumann and Animesh Acharjee and Jon Bishop and Janet Lord and Paul Harrison", year = "2021", month = apr, day = "1", doi = "10.1093/burnst/tkab001", language = "English", volume = "9", journal = "Burns & Trauma", issn = "2321-3868", publisher = "Springer Verlag", } . Burns & Trauma.
Unique diagnostic signatures of concussion in the saliva of male athletes @article{798b3e9296834ca3b09af4781deb8f8e, title = "Unique diagnostic signatures of concussion in the saliva of male athletes: the Study of Concussion in Rugby Union through MicroRNAs (SCRUM)", abstract = "OBJECTIVE: To investigate the role of salivary small non-coding RNAs (sncRNAs) in the diagnosis of sport-related concussion.METHODS: Saliva was obtained from male professional players in the top two tiers of England's elite rugby union competition across two seasons (2017-2019). Samples were collected preseason from 1028 players, and during standardised head injury assessments (HIAs) at three time points (in-game, post-game, and 36-48 hours post-game) from 156 of these. Samples were also collected from controls (102 uninjured players and 66 players sustaining a musculoskeletal injury). Diagnostic sncRNAs were identified with next generation sequencing and validated using quantitative PCR in 702 samples. A predictive logistic regression model was built on 2017-2018 data (training dataset) and prospectively validated the following season (test dataset).RESULTS: The HIA process confirmed concussion in 106 players (HIA+) and excluded this in 50 (HIA-). 32 sncRNAs were significantly differentially expressed across these two groups, with let-7f-5p showing the highest area under the curve (AUC) at 36-48 hours. Additionally, a combined panel of 14 sncRNAs (let-7a-5p, miR-143-3p, miR-103a-3p, miR-34b-3p, RNU6-7, RNU6-45, Snora57, snoU13.120, tRNA18Arg-CCT, U6-168, U6-428, U6-1249, Uco22cjg1,YRNA_255) could differentiate concussed subjects from all other groups, including players who were HIA- and controls, immediately after the game (AUC 0.91, 95% CI 0.81 to 1) and 36-48 hours later (AUC 0.94, 95% CI 0.86 to 1). When prospectively tested, the panel confirmed high predictive accuracy (AUC 0.96, 95% CI 0.92 to 1 post-game and AUC 0.93, 95% CI 0.86 to 1 at 36-48 hours).CONCLUSIONS: SCRUM, a large prospective observational study of non-invasive concussion biomarkers, has identified unique signatures of concussion in saliva of male athletes diagnosed with concussion.", author = "{Di Pietro}, Valentina and Patrick O'Halloran and Watson, {Callum N} and Ghazala Begum and Animesh Acharjee and Yakoub, {Kamal M} and Conor Bentley and Davies, {David J} and Paolo Iliceto and Gabriella Candilera and Menon, {David K} and Cross, {Matthew J} and Stokes, {Keith A} and Kemp, {Simon Pt} and Antonio Belli", note = "{\textcopyright} Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.", year = "2021", month = mar, day = "23", doi = "10.1136/bjsports-2020-103274", language = "English", journal = "British Journal of Sports Medicine", issn = "0306-3674", publisher = "BMJ Publishing Group", } . British Journal of Sports Medicine.
Animesh Acharjee, Hassan Sadozai, Thomas Gruber, Beat Gloor, Eva Karamitopoulou(2021). Pancreatic Cancers with High Grade Tumor Budding Exhibit Hallmarks of Diminished Anti-Tumor Immunity . Cancers. 13. (5). p. 1090. {MDPI} {AG}
Sadozai H, Acharjee A, Gruber T, Gloor B, Karamitopoulou E, Lin H(2021). Pancreatic Cancers with High Grade Tumor Budding Exhibit Hallmarks of Diminished Anti-Tumor Immunity . Cancers.
Animesh Acharjee, Hassan Sadozai, Thomas Gruber, Beat Gloor, Eva Karamitopoulou (2021). Pancreatic Cancers with High Grade Tumor Budding Exhibit Hallmarks of Diminished Anti-Tumor Immunity . Cancers.
Breastfeeding promotes early neonatal regulatory T-cell expansion and immune tolerance of non-inherited maternal antigens @article{98fa6b7b19c742889d5c70091df25e38, title = "Breastfeeding promotes early neonatal regulatory T-cell expansion and immune tolerance of non-inherited maternal antigens", abstract = "Background: Breastfeeding is associated with long‐term health benefits, such as a lower incidence of childhood infections, asthma, obesity and autoimmune disorders. However, little is known regarding how the maternal and neonatal immune systems interact after parturition when the neonate receives nutrition from maternal breast milk.Methods: We undertook a comparative analysis of immune repertoire and function at birth and 3 weeks of age in a cohort of 38 term neonates born by caesarean section grouped according to feeding method (breast milk versus formula). We used flow cytometry to study the immune phenotype in neonatal and maternal blood samples and mixed lymphocyte reactions to establish the proliferation response of neonatal versus maternal lymphocytes and vice versa. The microbiome of neonatal stool samples was also investigated using 16S rRNA sequencing.Results: We show that the proportion of regulatory T cells (Tregs) increases in this period and is nearly twofold higher in exclusively breastfed neonates compared with those who received formula milk only. Moreover, breastfed neonates show a specific and Treg‐dependent reduction in proliferative T‐cell responses to non‐inherited maternal antigens (NIMA), associated with a reduction in inflammatory cytokine production. We also observed the enrichment of short chain fatty acid producing taxa (Veillonella and Gemella) in stool samples of exclusively breastfed neonates.Conclusions: These data indicate that exposure of the neonate to maternal cells through breastfeeding acts to drive the maturation of Tregs and {\textquoteleft}tolerizes{\textquoteright} the neonate towards NIMA.", keywords = "Th17, breastfeeding, microbiome, neonate, non-inherited maternal antigen, regulatory T cell", author = "Hannah Wood and Animesh Acharjee and Hayden Pearce and Quraishi, {Mohammed Nabil} and Richard Powell and Amanda Rossiter and Andrew Beggs and Andrew Ewer and Paul Moss and Gergely Toldi", note = "Funding Information: We are grateful for the guidance of our late colleague, mentor and friend, Shree Vishna Rasiah, and dedicate this work to his memory. We wish to thank Diane Mellers for coordinating the enrolment of study participants and the research midwives at Birmingham Women{\textquoteright}s Hospital for their support. We are also grateful for the technical support of Sam Nicol and Kriti Verma. A.A. was supported by the National Institute for Health Research (NIHR) Surgical Reconstruction and Microbiology Research Centre (SRMRC), Birmingham, UK. The views expressed in this publication are those of the authors and not necessarily those of the National Health Service or the National Institute for Health Research. Publisher Copyright: {\textcopyright} 2021 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.", year = "2021", month = jan, day = "12", doi = "10.1111/all.14736", language = "English", journal = "Allergy", issn = "0105-4538", publisher = "Wiley", } . Allergy.
Animesh Acharjee, Jon Hazeldine, Robert J Dinsdale, David N Naumann, Jonathan R B Bishop, Janet M Lord, Paul Harrison(2021). Traumatic injury is associated with reduced deoxyribonuclease activity and dysregulation of the actin scavenging system . Burns & Trauma. 9. Oxford University Press ({OUP})
Koch M, Acharjee A, Ament Z, Schleicher R, Bevers M, Stapleton C, Patel A, Kimberly WT(2021). Machine Learning-Driven Metabolomic Evaluation of Cerebrospinal Fluid: Insights Into Poor Outcomes After Aneurysmal Subarachnoid Hemorrhage . Neurosurgery.
Animesh Acharjee, Saraswati Koppad, Annappa B, Georgios V Gkoutos(2021). Cloud Computing Enabled Big Multi-Omics Data Analytics . Bioinformatics and Biology Insights. 15. p. 117793222110359. {SAGE} Publications
Animesh Acharjee, Joseph Larkman, Yuanwei Xu, Victor Roth Cardoso, Georgios V. Gkoutos(2020). A random forest based biomarker discovery and power analysis framework for diagnostics research . BMC Medical Genomics. 13. (1). Springer Science and Business Media {LLC}
A random forest based biomarker discovery and power analysis framework for diagnostics research @article{1b9b958c51804e10a44a4010e38da2d6, title = "A random forest based biomarker discovery and power analysis framework for diagnostics research", abstract = "BACKGROUND: Biomarker identification is one of the major and important goal of functional genomics and translational medicine studies. Large scale -omics data are increasingly being accumulated and can provide vital means for the identification of biomarkers for the early diagnosis of complex disease and/or for advanced patient/diseases stratification. These tasks are clearly interlinked, and it is essential that an unbiased and stable methodology is applied in order to address them. Although, recently, many, primarily machine learning based, biomarker identification approaches have been developed, the exploration of potential associations between biomarker identification and the design of future experiments remains a challenge.METHODS: In this study, using both simulated and published experimentally derived datasets, we assessed the performance of several state-of-the-art Random Forest (RF) based decision approaches, namely the Boruta method, the permutation based feature selection without correction method, the permutation based feature selection with correction method, and the backward elimination based feature selection method. Moreover, we conducted a power analysis to estimate the number of samples required for potential future studies.RESULTS: We present a number of different RF based stable feature selection methods and compare their performances using simulated, as well as published, experimentally derived, datasets. Across all of the scenarios considered, we found the Boruta method to be the most stable methodology, whilst the Permutation (Raw) approach offered the largest number of relevant features, when allowed to stabilise over a number of iterations. Finally, we developed and made available a web interface ( https://joelarkman.shinyapps.io/PowerTools/ ) to streamline power calculations thereby aiding the design of potential future studies within a translational medicine context.CONCLUSIONS: We developed a RF-based biomarker discovery framework and provide a web interface for our framework, termed PowerTools, that caters the design of appropriate and cost-effective subsequent future omics study.", keywords = "Biomarker, Feature selection, Power study, Random forest", author = "Animesh Acharjee and Joseph Larkman and Yuanwei Xu and Cardoso, {Victor Roth} and Gkoutos, {Georgios V}", year = "2020", month = nov, day = "23", doi = "10.1186/s12920-020-00826-6", language = "English", volume = "13", journal = "BMC Medical Genomics", issn = "1755-8794", publisher = "BioMed Central", number = "1", } . BMC Medical Genomics.
Animesh Acharjee, Furqan Aziz, John A. Williams, Dominic Russ, Laura Bravo-Merodio, Georgios V. Gkoutos(2020). Biomarker Prioritisation and Power Estimation Using Ensemble Gene Regulatory Network Inference . International Journal of Molecular Sciences. 21. (21). p. 7886. {MDPI} {AG}
Biomarker Prioritisation and Power Estimation Using Ensemble Gene Regulatory Network Inference @article{d8208be7bd7940028849f7ceeb1307de, title = "Biomarker Prioritisation and Power Estimation Using Ensemble Gene Regulatory Network Inference", abstract = "Inferring the topology of a gene regulatory network (GRN) from gene expression data is a challenging but important undertaking for gaining a better understanding of gene regulation. Key challenges include working with noisy data and dealing with a higher number of genes than samples. Although a number of different methods have been proposed to infer the structure of a GRN, there are large discrepancies among the different inference algorithms they adopt, rendering their meaningful comparison challenging. In this study, we used two methods, namely the MIDER (Mutual Information Distance and Entropy Reduction) and the PLSNET (Partial least square based feature selection) methods, to infer the structure of a GRN directly from data and computationally validated our results. Both methods were applied to different gene expression datasets resulting from inflammatory bowel disease (IBD), pancreatic ductal adenocarcinoma (PDAC), and acute myeloid leukaemia (AML) studies. For each case, gene regulators were successfully identified. For example, for the case of the IBD dataset, the UGT1A family genes were identified as key regulators while upon analysing the PDAC dataset, the SULF1 and THBS2 genes were depicted. We further demonstrate that an ensemble-based approach, that combines the output of the MIDER and PLSNET algorithms, can infer the structure of a GRN from data with higher accuracy. We have also estimated the number of the samples required for potential future validation studies. Here, we presented our proposed analysis framework that caters not only to candidate regulator genes prediction for potential validation experiments but also an estimation of the number of samples required for these experiments.", keywords = "Causal modelling, Experimental design, Gene regulatory network, Omics integration", author = "Furqan Aziz and Animesh Acharjee and John Williams and Dominic Russ and Laura Bravo-Merodio and Georgios Gkoutos", year = "2020", month = oct, day = "23", doi = "10.3390/ijms21217886", language = "English", volume = "21", pages = "1--22", journal = "International Journal of Molecular Sciences", issn = "1661-6596", publisher = "MDPI", number = "21", } . International Journal of Molecular Sciences.
Animesh Acharjee, Furqan Aziz, John A. Williams, Dominic Russ, Laura Bravo-Merodio, Georgios V. Gkoutos (2020). Biomarker Prioritisation and Power Estimation Using Ensemble Gene Regulatory Network Inference . International Journal of Molecular Sciences.
Liu KD, Acharjee A, Hinz C, Liggi S, Murgia A, Denes J, Gulston MK, Wang X, Chu Y, West JA, et al.(2020). Consequences of Lipid Remodeling of Adipocyte Membranes Being Functionally Distinct from Lipid Storage in Obesity . Journal of proteome research.
(2020). The Consequences of Lipid Remodelling of Adipocyte Membranes Being Functionally Distinct From Lipid Storage in Obesity. Journal of Proteome Research.
A pilot integrative analysis of colonic gene expression, gut microbiota, and immune infiltration in primary sclerosing cholangitis-inflammatory bowel disease @article{e4d2f44eb3604b9a9e9f8c117c5864c5, title = "A pilot integrative analysis of colonic gene expression, gut microbiota, and immune infiltration in primary sclerosing cholangitis-inflammatory bowel disease: association of disease with bile acid pathways", abstract = "BACKGROUND: Although a majority of patients with PSC have colitis [PSC-IBD; primary sclerosing cholangitis-inflammatory bowel disease], this is phenotypically different from ulcerative colitis [UC]. We sought to define further the pathophysiological differences between PSC-IBD and UC, by applying a comparative and integrative approach to colonic gene expression, gut microbiota and immune infiltration data. METHODS: Colonic biopsies were collected from patients with PSC-IBD [n = 10], UC [n = 10], and healthy controls [HC; n = 10]. Shotgun RNA-sequencing for differentially expressed colonic mucosal genes [DEGs], 16S rRNA analysis for microbial profiling, and immunophenotyping were performed followed by multi-omic integration. RESULTS: The colonic transcriptome differed significantly between groups [p = 0.01]. Colonic transcriptomes from HC were different from both UC [1343 DEGs] and PSC-IBD [4312 DEGs]. Of these genes, only 939 had shared differential gene expression in both UC and PSC-IBD compared with HC. Imputed pathways were predominantly associated with upregulation of immune response and microbial defense in both disease cohorts compared with HC. There were 1692 DEGs between PSC-IBD and UC. Bile acid signalling pathways were upregulated in PSC-IBD compared with UC [p = 0.02]. Microbiota profiles were different between the three groups [p = 0.01]; with inferred function in PSC-IBD also being consistent with dysregulation of bile acid metabolism. Th17 cells and IL17-producing CD4 cells were increased in both PSC-IBD and UC when compared with HC [p < 0.05]. Multi-omic integration revealed networks involved in bile acid homeostasis and cancer regulation in PSC-IBD. CONCLUSIONS: Colonic transcriptomic and microbiota analysis in PSC-IBD point toward dysregulation of colonic bile acid homeostasis compared with UC. This highlights important mechanisms and suggests the possibility of novel approaches in treating PSC-IBD.", keywords = "Autoimmune liver disease, bioinformatics, colitis, dysbiosis", author = "Quraishi, {Mohammed Nabil} and Animesh Acharjee and Beggs, {Andrew D} and Richard Horniblow and Chris Tselepis and Georgios Gkoutos and Subrata Ghosh and Amanda Rossiter and Nicholas Loman and {van Schaik}, Willem and David Withers and Walters, {Julian R F} and Hirschfield, {Gideon M} and Iqbal, {Tariq H}", year = "2020", month = jul, doi = "10.1093/ecco-jcc/jjaa021", language = "English", volume = "14", pages = "935--947", journal = "Journal of Crohn's & Colitis", issn = "1873-9946", publisher = "Oxford University Press", number = "7", } . Journal of Crohn's & Colitis.
Animesh Acharjee, Veronica Lolli, Donato Angelino, Michele Tassotti, Daniele Del Rio, Pedro Mena, Augusta Caligiani (2020). Chemical Characterization of Capsule-Brewed Espresso Coffee Aroma from the Most Widespread Italian Brands by HS-SPME/GC-MS . Molecules.
Animesh Acharjee, Veronica Lolli, Donato Angelino, Michele Tassotti, Daniele Del Rio, Pedro Mena, Augusta Caligiani (2020). Chemical Characterization of Capsule-Brewed Espresso Coffee Aroma from the Most Widespread Italian Brands by HS-SPME/GC-MS . Molecules.
Quraishi MN, Acharjee A, Beggs AD, Horniblow R, Tselepis C, Gkoutus G, Ghosh S, Rossiter A, Loman N, van Schaik W, et al.(2020). A pilot integrative analysis of colonic gene expression, gut microbiota and immune infiltration in primary sclerosing cholangitis-inflammatory bowel disease: association of disease with bile acid pathways . Journal of Crohn's & colitis.
Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction @article{2e88efd2f02b47ca9368441fb2439154, title = "Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction", abstract = "The immune response to major trauma has been analysed mainly within post-hospital admission settings where the inflammatory response is already underway and the early drivers of clinical outcome cannot be readily determined. Thus, there is a need to better understand the immediate immune response to injury and how this might influence important patient outcomes such as multi-organ dysfunction syndrome (MODS). In this study, we have assessed the immune response to trauma in 61 patients at three different post-injury time points (ultra-early (<=1h), 4-12h, 48-72h) and analysed relationships with the development of MODS. We developed a pipeline using Absolute Shrinkage and Selection Operator and Elastic Net feature selection methods that were able to identify 3 physiological features (decrease in neutrophil CD62L and CD63 expression and monocyte CD63 expression and frequency) as possible biomarkers for MODS development. After univariate and multivariate analysis for each feature alongside a stability analysis, the addition of these 3 markers to standard clinical trauma injury severity scores yields a Generalized Liner Model (GLM) with an average Area Under the Curve value of 0.92±0.06. This performance provides an 8% improvement over the Probability of Survival (PS14) outcome measure and a 13% improvement over the New Injury Severity Score (NISS) for identifying patients at risk of MODS.", author = "Laura Bravo and Animesh Acharjee and Jon Hazeldine and Conor Bentley and Mark Foster and Georgios Gkoutos and Janet Lord", year = "2019", month = dec, day = "19", doi = "10.1038/s41597-019-0337-6", language = "English", volume = "6", pages = "1--10", journal = "Scientific Data", issn = "2052-4463", publisher = "Nature Publishing Group", } . Scientific Data.
Animesh Acharjee, Laura Bravo-Merodio, John A. Williams, Georgios V. Gkoutos(2019). -Omics biomarker identification pipeline for translational medicine . Journal of Translational Medicine. 17. (1). Springer Science and Business Media {LLC}
Animesh Acharjee, Laura Bravo-Merodio, Jon Hazeldine, Conor Bentley, Mark Foster, Georgios V. Gkoutos, Janet M. Lord(2019). Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction . Scientific Data. 6. (1). Springer Science and Business Media {LLC}
High-throughput metabolite profiling @article{bc9b829c15444299bc4d8fc1a4e8e1af, title = "High-throughput metabolite profiling: identification of plasma taurine as a potential biomarker of functional outcome after aneurysmal subarachnoid hemorrhage", abstract = "OBJECTIVEMetabolite profiling (or metabolomics) can identify candidate biomarkers for disease and potentially uncover new pathways for intervention. The goal of this study was to identify potential biomarkers of functional outcome after subarachnoid hemorrhage (SAH).METHODSThe authors performed high-throughput metabolite profiling across a broad spectrum of chemical classes (163 metabolites) on plasma samples taken from 191 patients with SAH who presented to Massachusetts General Hospital between May 2011 and October 2016. Samples were drawn at 3 time points following ictus: 0–5, 6–10, and 11–14 days. Elastic net (EN) and LASSO (least absolute shrinkage and selection operator) machine learning analyses were performed to identify metabolites associated with 90-day functional outcomes as assessed by the modified Rankin Scale (mRS). Additional univariate and multivariate analyses were then conducted to further examine the relationship between metabolites and clinical variables and 90-day functional outcomes.RESULTSOne hundred thirty-seven (71.7%) patients with aneurysmal SAH met the criteria for inclusion. A good functional outcome (mRS score 0–2) at 90 days was found in 79 (57.7%) patients. Patients with good outcomes were younger (p = 0.002), had lower admission Hunt and Hess grades (p < 0.0001) and modified Fisher grades (p < 0.0001), and did not develop hydrocephalus (p < 0.0001) or delayed cerebral ischemia (DCI) (p = 0.049). EN and LASSO machine learning methods identified taurine as the leading metabolite associated with 90-day functional outcome (p < 0.0001). Plasma concentrations of the amino acid taurine from samples collected between days 0 and 5 after aneurysmal SAH were 21.9% (p = 0.002) higher in patients with good versus poor outcomes. Logistic regression demonstrated that taurine remained a significant predictor of functional outcome (p = 0.013; OR 3.41, 95% CI 1.28–11.4), after adjusting for age, Hunt and Hess grade, modified Fisher grade, hydrocephalus, and DCI.CONCLUSIONSElevated plasma taurine levels following aneurysmal SAH predict a good 90-day functional outcome. While experimental evidence in animals suggests that this effect may be mediated through downregulation of pro-inflammatory cytokines, additional studies are required to validate this hypothesis in humans.", keywords = "aneurysm, biomarker, machine learning, metabolomics, subarachnoid hemorrhage, vascular disorders", author = "Stapleton, {Christopher J.} and Animesh Acharjee and Irvine, {Hannah J.} and Wolcott, {Zoe C.} and Patel, {Aman B.} and Kimberly, {W. Taylor}", year = "2019", month = nov, day = "22", doi = "10.3171/2019.9.JNS191346", language = "English", pages = "1--8", journal = "Journal of Neurosurgery", issn = "0022-3085", publisher = "American Association of Neurological Surgeons", } . Journal of Neurosurgery.
Animesh Acharjee, Pedro Mena, Iziar A. Ludwig, Virginia B. Tomatis, Luca Calani, Alice Rosi, Furio Brighenti, Sumantra Ray, Julian L. Griffin, Les J. Bluck, et al.(2019). Inter-individual variability in the production of flavan-3-ol colonic metabolites: preliminary elucidation of urinary metabotypes . European Journal of Nutrition. 58. (4). p. 1529--1543. Springer Science and Business Media {LLC}
Inter-individual variability in the production of flavan-3-ol colonic metabolites @article{3cb963f34413403e91bbd14d0ce15fec, title = "Inter-individual variability in the production of flavan-3-ol colonic metabolites: preliminary elucidation of urinary metabotypes", abstract = "PurposeThere is much information on the bioavailability of (poly)phenolic compounds following acute intake of various foods. However, there are only limited data on the effects of repeated and combined exposure to specific (poly)phenol food sources and the inter-individual variability in their bioavailability. This study evaluated the combined urinary excretion of (poly)phenols from green tea and coffee following daily consumption by healthy subjects in free-living conditions. The inter-individual variability in the production of phenolic metabolites was also investigated.MethodsEleven participants consumed both tablets of green tea and green coffee bean extracts daily for 8 weeks and 24-h urine was collected on five different occasions. The urinary profile of phenolic metabolites and a set of multivariate statistical tests were used to investigate the putative existence of characteristic metabotypes in the production of flavan-3-ol microbial metabolites.Results(Poly)phenolic compounds in the green tea and green coffee bean extracts were absorbed and excreted after simultaneous consumption, with green tea resulting in more inter-individual variability in urinary excretion of phenolic metabolites. Three metabotypes in the production of flavan-3-ol microbial metabolites were tentatively defined, characterized by the excretion of different amounts of trihydroxyphenyl-γ-valerolactones, dihydroxyphenyl-γ-valerolactones, and hydroxyphenylpropionic acids.ConclusionsThe selective production of microbiota-derived metabolites from flavan-3-ols and the putative existence of characteristic metabotypes in their production represent an important development in the study of the bioavailability of plant bioactives. These observations will contribute to better understand the health effects and individual differences associated with consumption of flavan-3-ols, arguably the main class of flavonoids in the human diet.", keywords = "polyphenols, green tea catechins, coffee caffeoylquinic acids, colonic microbiota, urinary phenotype, metabotypes", author = "Pedro Mena and Ludwig, {Iziar A.} and Tomatis, {Virginia B.} and Animesh Acharjee and Luca Calani and Alice Rosi and Furio Brighenti and Sumantra Ray and Griffin, {Julian L.} and Bluck, {Les J.} and {Del Rio}, {Daniele Del Rio}", year = "2019", month = jun, doi = "10.1007/s00394-018-1683-4", language = "English", volume = "58", pages = "1529--1543", journal = "European Journal of Nutrition", issn = "1436-6207", publisher = "D. Steinkopff-Verlag", number = "4", } . European Journal of Nutrition.
-Omics biomarker identification pipeline for translational medicine @article{2c70f97cda184bd486c49231c82ca73a, title = "-Omics biomarker identification pipeline for translational medicine", abstract = "BACKGROUND: Translational medicine (TM) is an emerging domain that aims to facilitate medical or biological advances efficiently from the scientist to the clinician. Central to the TM vision is to narrow the gap between basic science and applied science in terms of time, cost and early diagnosis of the disease state. Biomarker identification is one of the main challenges within TM. The identification of disease biomarkers from -omics data will not only help the stratification of diverse patient cohorts but will also provide early diagnostic information which could improve patient management and potentially prevent adverse outcomes. However, biomarker identification needs to be robust and reproducible. Hence a robust unbiased computational framework that can help clinicians identify those biomarkers is necessary.METHODS: We developed a pipeline (workflow) that includes two different supervised classification techniques based on regularization methods to identify biomarkers from -omics or other high dimension clinical datasets. The pipeline includes several important steps such as quality control and stability of selected biomarkers. The process takes input files (outcome and independent variables or -omics data) and pre-processes (normalization, missing values) them. After a random division of samples into training and test sets, Least Absolute Shrinkage and Selection Operator and Elastic Net feature selection methods are applied to identify the most important features representing potential biomarker candidates. The penalization parameters are optimised using 10-fold cross validation and the process undergoes 100 iterations and a combinatorial analysis to select the best performing multivariate model. An empirical unbiased assessment of their quality as biomarkers for clinical use is performed through a Receiver Operating Characteristic curve and its Area Under the Curve analysis on both permuted and real data for 1000 different randomized training and test sets. We validated this pipeline against previously published biomarkers.RESULTS: We applied this pipeline to three different datasets with previously published biomarkers: lipidomics data by Acharjee et al. (Metabolomics 13:25, 2017) and transcriptomics data by Rajamani and Bhasin (Genome Med 8:38, 2016) and Mills et al. (Blood 114:1063-1072, 2009). Our results demonstrate that our method was able to identify both previously published biomarkers as well as new variables that add value to the published results.CONCLUSIONS: We developed a robust pipeline to identify clinically relevant biomarkers that can be applied to different -omics datasets. Such identification reveals potentially novel drug targets and can be used as a part of a machine-learning based patient stratification framework in the translational medicine settings.", keywords = "Biomarker, -Omics, Regularization, Feature selection, Translational medicine", author = "Laura Bravo-Merodio and Williams, {John A} and Gkoutos, {Georgios V} and Animesh Acharjee", year = "2019", month = may, day = "14", doi = "10.1186/s12967-019-1912-5", language = "English", volume = "17", journal = "Journal of translational medicine", issn = "1479-5876", publisher = "Springer", number = "1", } . Journal of translational medicine.
Animesh Acharjee, Hannah J Irvine, Zoe Wolcott, Zsuzsanna Ament, Holly Hinson, Bradley J Molyneaux, J Marc Simard, Kevin N Sheth, W Taylor Kimberly(2019). Abstract TMP18: Intravenous Glibenclamide Reduces Hypoxanthine, a Novel Predictor of Brain Edema Formation: An Exploratory Analysis of GAMES-RP . Stroke. 50. (Suppl{\_}1). Ovid Technologies (Wolters Kluwer Health)
Animesh Acharjee, Jonathan P. Segal, Benjamin H. Mullish, Mohammed Nabil Quraishi, Horace R. T. Williams, Tariq Iqbal, Ailsa L. Hart, Julian R. Marchesi(2019). The application of omics techniques to understand the role of the gut microbiota in inflammatory bowel disease . Therapeutic Advances in Gastroenterology. 12. p. 175628481882225. {SAGE} Publications
Hepatic steatosis risk is partly driven by increased de novo lipogenesis following carbohydrate consumption @article{6c27c051b9b748899e8d8f460487758c, title = "Hepatic steatosis risk is partly driven by increased de novo lipogenesis following carbohydrate consumption", abstract = "BackgroundDiet is a major contributor to metabolic disease risk, but there is controversy as to whether increased incidences of diseases such as non-alcoholic fatty liver disease arise from consumption of saturated fats or free sugars. Here, we investigate whether a sub-set of triacylglycerols (TAGs) were associated with hepatic steatosis and whether they arise from de novo lipogenesis (DNL) from the consumption of carbohydrates.ResultsWe conduct direct infusion mass spectrometry of lipids in plasma to study the association between specific TAGs and hepatic steatosis assessed by ultrasound and fatty liver index in volunteers from the UK-based Fenland Study and evaluate clustering of TAGs in the National Survey of Health and Development UK cohort. We find that TAGs containing saturated and monounsaturated fatty acids with 16–18 carbons are specifically associated with hepatic steatosis. These TAGs are additionally associated with higher consumption of carbohydrate and saturated fat, hepatic steatosis, and variations in the gene for protein phosphatase 1, regulatory subunit 3b (PPP1R3B), which in part regulates glycogen synthesis. DNL is measured in hyperphagic ob/ob mice, mice on a western diet (high in fat and free sugar) and in healthy humans using stable isotope techniques following high carbohydrate meals, demonstrating the rate of DNL correlates with increased synthesis of this cluster of TAGs. Furthermore, these TAGs are increased in plasma from patients with biopsy-confirmed steatosis.ConclusionA subset of TAGs is associated with hepatic steatosis, even when correcting for common confounding factors. We suggest that hepatic steatosis risk in western populations is in part driven by increased DNL following carbohydrate rich meals in addition to the consumption of saturated fat.", keywords = "non-alcoholic fatty liver disease, direct infusion mass spectrometry, de novo lipogenesis, triacylglycerols, triglycerides", author = "Sanders, {Francis W B} and Animesh Acharjee and Celia Walker and Luke Marney and Roberts, {Lee D} and Fumiaki Imamura and Benjamin Jenkins and Jack Case and Sumantra Ray and Samuel Virtue and Antonio Vidal-Puig and Diana Kuh and Rebecca Hardy and Michael Allison and Nita Forouhi and Murray, {Andrew J} and Nick Wareham and Michele Vacca and Albert Koulman and Griffin, {Julian L}", year = "2018", month = jun, day = "20", doi = "10.1186/s13059-018-1439-8", language = "English", volume = "19", pages = "1--15", journal = "Genome Biology", issn = "1474-7596", publisher = "BioMed Central", } . Genome Biology.
Animesh Acharjee, Francis W. B. Sanders, Celia Walker, Luke Marney, Lee D. Roberts, Fumiaki Imamura, Benjamin Jenkins, Jack Case, Sumantra Ray, Samuel Virtue, et al.(2018). Hepatic steatosis risk is partly driven by increased de novo lipogenesis following carbohydrate consumption . Genome Biology. 19. (1). Springer Nature
Metabolomics and lipidomics study of mouse models of type 1 diabetes highlights divergent metabolism in purine and tryptophan metabolism prior to disease onset @article{a91bd533fbdf4d6993e58fc290e89bc0, title = "Metabolomics and lipidomics study of mouse models of type 1 diabetes highlights divergent metabolism in purine and tryptophan metabolism prior to disease onset", abstract = "With the increase in incidence of type 1 diabetes (T1DM), there is an urgent need to understand the early molecular and metabolic alterations that accompany the autoimmune disease. This is not least because in murine models early intervention can prevent the development of disease. We have applied a liquid chromatography (LC−) and gas chromatography (GC−) mass spectrometry (MS) metabolomics and lipidomics analysis of blood plasma and pancreas tissue to follow the progression of disease in three models related to autoimmune diabetes: the nonobese diabetic (NOD) mouse, susceptible to the development of autoimmune diabetes, and the NOD-E (transgenic NOD mice that express the I-E heterodimer of the major histocompatibility complex II) and NOD-severe combined immunodeficiency (SCID) mouse strains, two models protected from the development of diabetes. All three analyses highlighted the metabolic differences between the NOD-SCID mouse and the other two strains, regardless of diabetic status indicating that NOD-SCID mice are poor controls for metabolic changes in NOD mice. By comparing NOD and NOD-E mice, we show the development of T1DM in NOD mice is associated with changes in lipid, purine, and tryptophan metabolism, including an increase in kynurenic acid and a decrease in lysophospholipids, metabolites previously associated with inflammation.", keywords = "nonobese diabetic (NOD) mouse, NOD-severe combined immunodeficiency (SCID) mouse, mass spectrometry, xanthinine, kynurenic acid", author = "Murfitt, {Steven A.} and Paola Zaccone and Xinzhu Wang and Animesh Acharjee and Yvonne Sawyer and Albert Koulman and Roberts, {Lee D} and Anne Cooke and Griffin, {Julian Leether}", year = "2018", month = mar, day = "2", doi = "https://doi.org/10.1021/acs.jproteome.7b00489", language = "English", volume = "17", pages = "946−960", journal = "Journal of Proteome Research", issn = "1535-3893", publisher = "American Chemical Society", number = "3", } . Journal of Proteome Research.
Animesh Acharjee, Steven A. Murfitt, Paola Zaccone, Xinzhu Wang, Yvonne Sawyer, Albert Koulman, Lee D. Roberts, Anne Cooke, Julian Leether Griffin(2018). Metabolomics and Lipidomics Study of Mouse Models of Type 1 Diabetes Highlights Divergent Metabolism in Purine and Tryptophan Metabolism Prior to Disease Onset . Journal of Proteome Research. 17. (3). p. 946--960. American Chemical Society ({ACS})
Genetical genomics of quality related traits in potato tubers using proteomics @article{5496734c6e184ebaa29abd1de76574a3, title = "Genetical genomics of quality related traits in potato tubers using proteomics", abstract = "BackgroundRecent advances in ~omics technologies such as transcriptomics, metabolomics and proteomics along with genotypic profiling have permitted the genetic dissection of complex traits such as quality traits in non-model species. To get more insight into the genetic factors underlying variation in quality traits related to carbohydrate and starch metabolism and cold sweetening, we determined the protein content and composition in potato tubers using 2D–gel electrophoresis in a diploid potato mapping population. Upon analyzing we made sure that the proteins from the patatin family were excluded to ensure a better representation of the other proteins.ResultsWe subsequently performed pQTL analyses for all other proteins with a sufficient representation in the population and established a relationship between proteins and 26 potato tuber quality traits (e.g. flesh colour, enzymatic discoloration) by co-localization on the genetic map and a direct correlation study of protein abundances and phenotypic traits. Over 1643 unique protein spots were detected in total over the two harvests. We were able to map pQTLs for over 300 different protein spots some of which co-localized with traits such as starch content and cold sweetening. pQTLs were observed on every chromosome although not evenly distributed over the chromosomes. The largest number of pQTLs was found for chromosome 8 and the lowest for chromosome number 10. For some 20 protein spots multiple QTLs were observed.ConclusionsFrom this analysis, hotspot areas for protein QTLs were identified on chromosomes three, five, eight and nine. The hotspot on chromosome 3 coincided with a QTL previously identified for total protein content and had more than 23 pQTLs in the region from 70 to 80 cM. Some of the co-localizing protein spots associated with some of the most interesting tuber quality traits were identified, albeit far less than we had anticipated at the onset of the experiments.", keywords = "genetical genomics, proteomics, protein QTL, potato quality traits", author = "Animesh Acharjee and Pierre-Yves Chibon and Bjorn Kloosterman and Twan America and Jenny Renaut and Chris Maliepaard and Visser, {Richard G. F.}", year = "2018", month = jan, day = "23", doi = "https://doi.org/10.1186/s12870-018-1229-1", language = "English", volume = "18", pages = "1--10", journal = "BMC Plant Biology", issn = "1471-2229", publisher = "Springer", } . BMC Plant Biology.
Animesh Acharjee, Pierre-Yves Chibon, Bjorn Kloosterman, Twan America, Jenny Renaut, Chris Maliepaard, Richard G. F. Visser(2018). Genetical genomics of quality related traits in potato tubers using proteomics . BMC Plant Biology. 18. (1). Springer Nature
Animesh Acharjee, Biplab Bhattacharjee, Muhammad Shafi(2017). Network mining based elucidation of the dynamics of cross-market clustering and connectedness in Asian region: An MST and hierarchical clustering approach . Journal of King Saud University - Computer and Information Sciences. Elsevier {BV}
Animesh Acharjee, Philippa Prentice, Carlo Acerini, James Smith, Ieuan A. Hughes, Ken Ong, Julian L. Griffin, David Dunger, Albert Koulman(2017). The translation of lipid profiles to nutritional biomarkers in the study of infant metabolism . Metabolomics. 13. (3). Springer Nature
Animesh Acharjee, Zsuzsanna Ament, James A. West, Elizabeth Stanley, Julian L. Griffin(2016). Integration of metabolomics, lipidomics and clinical data using a machine learning method . BMC Bioinformatics. 17. (S15). Springer Nature
Animesh Acharjee, Biplab Bhattacharjee, Muhammad Shafi, Wei-Xing Zhou(2016). Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study . PLOS ONE. 11. (11). p. e0166087. Public Library of Science ({PLoS})
Animesh Acharjee, Bjorn Kloosterman, Richard G. F. Visser, Chris Maliepaard(2016). Integration of multi-omics data for prediction of phenotypic traits using random forest . BMC Bioinformatics. 17. (S5). Springer Nature
Animesh Acharjee(2012). Comparison of Regularized Regression Methods for ~Omics Data . Journal of Postgenomics Drug & Biomarker Development. 03. (03). {OMICS} Publishing Group
Carreno-Quintero, N., Acharjee, A., Maliepaard, C., Bachem, C.W.B., Mumm, R., Bouwmeester, H., Visser, R.G.F., Keurentjes, J.J.B.(2012). Untargeted metabolic quantitative trait loci analyses reveal a relationship between primary metabolism and potato tuber quality . Plant Physiology. 158. (3). p. 1306-1318.
Animesh Acharjee, Bjorn Kloosterman, Ric C.H. de Vos, Jeroen S. Werij, Christian W.B. Bachem, Richard G.F. Visser, Chris Maliepaard(2011). Data integration and network reconstruction with ∼omics data using Random Forest regression in potato . Analytica Chimica Acta. 705. (1-2). p. 56--63. Elsevier {BV}
BOOK CHAPTER
(2020). Translational biomarkers in the era of precision medicine . Advances in Clinical Chemistry.
OTHER
Animesh Acharjee, Joseph Larkman, Victor Roth Cardoso, Georgios V. Gkoutos(2020). Effect of biomarker identification on power analysis for diagnostics research . Research Square
Animesh Acharjee, Joseph Larkman, Victor Roth Cardoso, Georgios V. Gkoutos(2020). PowerTools: A web based user-friendly tool for future translational study design . Research Square
P005 Regulators of the guanylate cyclase pathway are potential novel markers of mucosal healing in IBD @article{8fb07d01e558493d8a589a52093ae517, title = "P005 Regulators of the guanylate cyclase pathway are potential novel markers of mucosal healing in IBD", abstract = "Background: Intestinal guanylate cyclase C (GC-C) present in epithelial cells has been shown to have a role in gut homeostasis. The downstream effects of activation of GC-C are due to production of cyclic-GMP. GC-C is encoded by the gene GUCY2C, mutations in which are implicated in Familial Diarrhoea Syndrome and noted as risk factors for Crohn{\textquoteright}s disease. GUCY2C and its activator, GUCA2A have been shown to be downregulated in IBD. We hypothesised that regulation of this pathway might be important in remission and response to therapy.Methods: Forty-four patients with IBD and 7 patients with polyps (controls) at University Hospitals Birmingham, UK were recruited under ethical consent. Relevant demographic and clinical data were extracted from the hospital EMR. All patients had disease activity recorded on endoscopic examination of mucosa and intestinal biopsies collected for analysis. Mucosal healing was defined as MES = 0 (UC) and SES-CD <6 (CD). Of 44 patients, 14 had matched baseline and 12-week post-biologic therapy assessment and had tissues collected. Intestinal biopsies were analysed by 3{\textquoteright}RNA-sequencing using the Illumina Nextseq sequencer. FASTQ files were generated through BaseSpace and reads de-multiplexed, trimmed, aligned, and quantified using the GeneGlobe (Qiagen) workflow. Expression was compared between groups using either Wilcoxon tests or Kruskal–Wallis with Dunn post-hoc analysis as appropriate.Results: Expression of Guanylate cyclase activators GUCA2A and GUCA2B in patients who showed mucosal healing was equivalent to controls, but GUCA2A was down-regulated in those with active disease (non-healing) (p = 0.006). The same pattern was observed for transcriptional regulators of GUCY2C, including HNF4A (p = 0.0248) and CDX2 (0.0062). Correspondingly, GUCY2C was reduced in non-healing mucosa, although the difference was not significant (Figure 1). In patients who responded to biologic therapy, both GUCA2A (p = 0.0234) and GUCA2B (p = 0.0117) were increased at follow-up but no change was observed for those who did not respond. Change in GUCY2C expression did not reach statistical significance in either group, although an increase was observed for a large proportion of responders.Conclusion: Our findings suggest that regulation of the Guanylate Cyclase pathway may be involved in the restoration of a stable mucosa in IBD and that expression of its regulators may be used to indicate response to treatment.", author = "Jeffery, {L E} and Shivaji, {U N} and D Zardo and A Acharjee and Nardone, {O M} and Smith, {S C} and G Gkoutos and Visweswariah, {S S} and S Ghosh and M Iacucci", year = "2020", month = jan, day = "15", doi = "10.1093/ecco-jcc/jjz203.134", language = "English", volume = "14", pages = "S131–S132", journal = "Journal of Crohn's & Colitis", issn = "1873-9946", publisher = "Oxford University Press", number = "Supplement_1", } . Journal of Crohn's & Colitis.
Sedlackova L, Otten EG, Scialo F, Shapira D, Kataura T, Carroll B, Seranova E, Rabanal-Ruiz Y, Kelly G, Stefanatos R, et al.(2020). Autophagy promotes cell and organismal survival by maintaining NAD(H) pools .
Pal N, Acharjee A, Ament Z, Dent T, Yavari A, Mahmod M, Ariga R, West J, Steeples V, Cassar M, et al.(2019). Metabolic Profiling of Aortic Stenosis and Hypertrophic Cardiomyopathy Identifies Mechanistic Contrasts in Substrate Utilisation .
Liu K, Acharjee A, Hinz C, Liggi S, Murgia A, Denes J, Gulston MK, Wang X, Chu Y, West JA, et al.(2019). The consequences of lipid remodelling of adipocyte cell membranes being functionally distinct from global lipid storage during obesity .
Animesh Acharjee, Argyris Zardilis, Jo&#227;o Dias, James Smith(2014). Extensible and Executable Stochastic Models of Fatty Acid and Lipid Metabolism . Computational Methods in Systems Biology. p. 244--247. Springer International Publishing
Animesh Acharjee, Argyris Zardilis, Jo&#227;o Dias, James Smith(2014). Extensible and Executable Stochastic Models of Fatty Acid and Lipid Metabolism . Computational Methods in Systems Biology. p. 244--247. Springer International Publishing
BOOK
Zardilis, A., Dias, J., Acharjee, A., Smith, J.(2014). Extensible and executable stochastic models of fatty acid and lipid metabolism . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8859. p. 244-247.