Identification of Novel Loci Involved in Adalimumab Response in Crohn’s Disease Patients Using Integration of Genome Profiling and Isoform-Level Immune-Cell Deconvoluted Transcriptome Profiling of Colon Tissue

Gorenjak, Mario; Jezernik, Gregor; Krušič, Martina; Skok, Pavel; Potočnik, Uroš

doi:10.3390/pharmaceutics14091893

Cited by 3 publications

(2 citation statements)

References 71 publications

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“…All identified genes were further divided into up- and downregulated modules and subjected to GO enrichment analysis, which acted as a sieve for the stringent selection of genes with known and meaningful biological functions. This, in turn, yielded 33 genes, which were further analyzed using a modified integration approach with genomic profiling, as previously described [ 30 , 82 , 83 ]. Genomic profiling was carried out using an association analysis of genomic data obtained from an independent Slovenian CD cohort.…”

Section: Discussionmentioning

confidence: 99%

Single-Cell Transcriptomic and Targeted Genomic Profiling Adjusted for Inflammation and Therapy Bias Reveal CRTAM and PLCB1 as Novel Hub Genes for Anti-Tumor Necrosis Factor Alpha Therapy Response in Crohn’s Disease

Gorenjak,

Gole,

Goričan

et al. 2024

Pharmaceutics

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Background: The lack of reliable biomarkers in response to anti-TNFα biologicals hinders personalized therapy for Crohn’s disease (CD) patients. The motivation behind our study is to shift the paradigm of anti-TNFα biomarker discovery toward specific immune cell sub-populations using single-cell RNA sequencing and an innovative approach designed to uncover PBMCs gene expression signals, which may be masked due to the treatment or ongoing inflammation; Methods: The single-cell RNA sequencing was performed on PBMC samples from CD patients either naïve to biological therapy, in remission while on adalimumab, or while on ustekinumab but previously non-responsive to adalimumab. Sieves for stringent downstream gene selection consisted of gene ontology and independent cohort genomic profiling. Replication and meta-analyses were performed using publicly available raw RNA sequencing files of sorted immune cells and an association analysis summary. Machine learning, Mendelian randomization, and oligogenic risk score methods were deployed to validate DEGs highly relevant to anti-TNFα therapy response; Results: This study found PLCB1 in CD4+ T cells and CRTAM in double-negative T cells, which met the stringent statistical thresholds throughout the analyses. An additional assessment proved causal inference of both genes in response to anti-TNFα therapy; Conclusions: This study, jointly with an innovative design, uncovered novel candidate genes in the anti-TNFα response landscape of CD, potentially obscured by therapy or inflammation.

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Section: Discussionmentioning

confidence: 99%

Single-Cell Transcriptomic and Targeted Genomic Profiling Adjusted for Inflammation and Therapy Bias Reveal CRTAM and PLCB1 as Novel Hub Genes for Anti-Tumor Necrosis Factor Alpha Therapy Response in Crohn’s Disease

Gorenjak,

Gole,

Goričan

et al. 2024

Pharmaceutics

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“…KLF5 was identified by Dong et al [ 70 ] as one of the genes downregulated in IBD. Gorenjak et al [ 71 ] linked HSPA9 with IBD.…”

Section: Discussionmentioning

confidence: 99%

Gene Identification in Inflammatory Bowel Disease via a Machine Learning Approach

Perez

Castillo

2023

Medicina

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Inflammatory bowel disease (IBD) is an illness with increasing prevalence, particularly in emerging countries, which can have a substantial impact on the quality of life of the patient. The illness is rather heterogeneous with different evolution among patients. A machine learning approach is followed in this paper to identify potential genes that are related to IBD. This is done by following a Monte Carlo simulation approach. In total, 23 different machine learning techniques were tested (in addition to a base level obtained using artificial neural networks). The best model identified 74 genes selected by the algorithm as being potentially involved in IBD. IBD seems to be a polygenic illness, in which environmental factors might play an important role. Following a machine learning approach, it was possible to obtain a classification accuracy of 84.2% differentiating between patients with IBD and control cases in a large cohort of 2490 total cases. The sensitivity and specificity of the model were 82.6% and 84.4%, respectively. It was also possible to distinguish between the two main types of IBD: (1) Crohn’s disease and (2) ulcerative colitis.

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Nanoparticles for cancer therapy: a review of influencing factors and evaluation methods for biosafety

Wu²,

Li³

et al. 2023

Clin Transl Oncol

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Identification of Novel Loci Involved in Adalimumab Response in Crohn’s Disease Patients Using Integration of Genome Profiling and Isoform-Level Immune-Cell Deconvoluted Transcriptome Profiling of Colon Tissue

Cited by 3 publications

References 71 publications

Single-Cell Transcriptomic and Targeted Genomic Profiling Adjusted for Inflammation and Therapy Bias Reveal CRTAM and PLCB1 as Novel Hub Genes for Anti-Tumor Necrosis Factor Alpha Therapy Response in Crohn’s Disease

Single-Cell Transcriptomic and Targeted Genomic Profiling Adjusted for Inflammation and Therapy Bias Reveal CRTAM and PLCB1 as Novel Hub Genes for Anti-Tumor Necrosis Factor Alpha Therapy Response in Crohn’s Disease

Gene Identification in Inflammatory Bowel Disease via a Machine Learning Approach

Nanoparticles for cancer therapy: a review of influencing factors and evaluation methods for biosafety

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