My Recent Publications

Systems biology-based approaches to summarize and identify novel genes and pathways associated with acute and chronic postsurgical pain

Sat, 2020-02-15 06:00

J Clin Anesth. 2020 Jun;62:109738. doi: 10.1016/j.jclinane.2020.109738. Epub 2020 Feb 12.

ABSTRACT

STUDY OBJECTIVE: To employ systems biology-based machine learning to identify biologic processes over-represented with genetic variants (gene enrichment) implicated in post-surgical pain.

DESIGN: Informed systems biology based integrative computational analyses.

SETTING: Pediatric research and teaching institution.

INTERVENTIONS: Pubmed search (01/01/2001-10/31/2017) was performed to identify "training" genes associated with postoperative pain in humans. Candidate genes were identified and prioritized using Toppgene suite, based on functional enrichment using several gene ontology annotations, and curated gene sets associated with mouse phenotype-knockout studies.

MEASUREMENTS: Computationally top-ranked candidate genes and literature-curated genes were included in pathway enrichment analyses. Hierarchical clustering was used to visualize select functional enrichment results between the two phenotypes.

MAIN RESULTS: Literature review identified 38 training genes associated with postoperative pain and 31 with CPSP. We identified 2610 prioritized novel candidate genes likely associated with acute and chronic postsurgical pain, the top 10th percentile jointly enriched (p 0.05; Benjamini-Hochberg correction) several pathways, topmost being cAMP response element-binding protein and ion channel pathways. Heat maps demonstrated enrichment of inflammatory/drug metabolism processes in acute postoperative pain and immune mechanisms in CPSP.

CONCLUSION: High interindividual variability in pain responses immediately after surgery and risk for CPSP suggests genetic susceptibility. Lack of large homogenous sample sizes have led to underpowered genetic association studies. Systems biology can be leveraged to integrate genetic-level data with biologic processes to generate prioritized candidate gene lists and understand novel biological pathways involved in acute postoperative pain and CPSP. Such data would be key to informing future polygenic studies with targeted genome wide profiling. This study demonstrates the utility of functional annotation - based prioritization and enrichment approaches and identifies novel genes and unique/shared biological processes involved in acute and chronic postoperative pain. Results provide framework for future targeted genetic profiling of CPSP risk, to enable preventive and therapeutic approaches.

PMID:32058259 | PMC:PMC7276001 | DOI:10.1016/j.jclinane.2020.109738

Tsg101 positively regulates P62-Keap1-Nrf2 pathway to protect hearts against oxidative damage

Sat, 2020-02-15 06:00

Redox Biol. 2020 May;32:101453. doi: 10.1016/j.redox.2020.101453. Epub 2020 Feb 6.

ABSTRACT

Currently, most antioxidants do not show any favorable clinical outcomes in reducing myocardial ischemia-reperfusion (I/R) injury, suggesting an urgent need for exploring a new regulator of redox homeostasis in I/R hearts. Here, using heart-specific transgenic (TG) and knockdown (KD) mouse models, tumor susceptibility gene 101 (Tsg101) is defined as a novel cardiac-protector against I/R-triggered oxidative stress. RNA sequencing and bioinformatics data surprisingly reveal that most upregulated genes in Tsg101-TG hearts are transcribed by Nrf2. Accordingly, pharmacological inhibition of Nrf2 offsets Tsg101-elicited cardio-protection. Mechanistically, Tsg101 interacts with SQSTM1/p62 through its PRR domain, and promotes p62 aggregation, leading to recruitment of Keap1 for degradation by autophagosomes and release of Nrf2 to the nucleus. Furthermore, knockout of p62 abrogates Tsg101-induced cardio-protective effects during I/R. Hence, our findings uncover a previously unrecognized role of Tsg101 in the regulation of p62/Keap1/Nrf2 signaling cascades and provide a new strategy for the treatment of ischemic heart disease.

PMID:32057709 | PMC:PMC7264471 | DOI:10.1016/j.redox.2020.101453

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