Tropomyosin 3 (TPM3) function in skeletal muscle and in myopathy

Lambert, Matthias R.; Gussoni, Emanuela

doi:10.1186/s13395-023-00327-x

Cited by 6 publications

(1 citation statement)

References 151 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mutations in PTPRC, also known as CD45, have been associated with RA patient response to anti-TNF therapy [22,23]. TPM3 has been reported as an autoantigen in in RA, and also to involved in myopathy and renal cancer [24,25,26]. ARHGDIB expression has been reported to be upregulated in RA, whereas SIAH1 is downregulated [28,29].…”

Section: Discussionmentioning

confidence: 99%

AI based on evolutionary computation yields algorithmic biomarker summary of a randomized rheumatoid arthritis clinical trial, accurately predicting individual patient outcomes, enabling precision medicine

Horgan,

McDermott,

Harrington

et al. 2024

Preprint

View full text Add to dashboard Cite

Background Producing transparent interpretable algorithms summarizing clinical trial outcomes to accurately predict individual patient’s responses would be a significant advance. We hypothesized that software designed to analyze biomedical data, based on evolutionary computation (EC), could produce summary algorithmic biomarkers from a clinical trial, predictive of individual responses to therapy. Methods and Findings A previously published randomized double-blind placebo controlled clinical trial was analyzed. Patients with active rheumatoid arthritis on a stable dose of methotrexate and naive to anti-tumor necrosis factor biologic therapy, were randomized to receive infliximab or placebo. The primary endpoint was synovial disease activity assessed by magnetic resonance imaging. Secondary endpoints included the Disease Activity Score 28 (DAS28). Baseline peripheral blood gene expression variable data were available for 59 patients, plus the treatment variable, infliximab or placebo, yielding a total of 52,379 baseline variables. The binary dependent variable for analysis was DAS28 response, defined by a decrease in DAS28 score of ≥1.2, at 14 weeks. At 14 weeks, 20 of the 30 patients receiving infliximab had responded, and ten of the 29 patients receiving placebo had responded. The software derived an algorithm, with 4 gene expression variables plus treatment assignment and 12 mathematical operations, that correctly predicted responders versus non-responders for all 59 patients with available gene expression data, giving 100% accuracy, 100% sensitivity and 100% specificity. We present the algorithm to provide transparency and to enable verification. Excluding the 4 gene expression variables, we then derived similarly predictive algorithms with 4 other gene expression variables. We hypothesized that the software could derive algorithms as predictors of treatment response to anti-tumor necrosis factor biologic therapy using just these 8 gene expression variables using previously published independent datasets from 6 rheumatoid arthritis studies. In each validation analysis the accuracy of the predictors we derived surpassed those previously reported by the original study authors. Conclusions and Relevance Software based on EC summarized the outcome of a clinical trial, with transparent biomarker algorithms correctly predicted the clinical outcome for all 59 RA patients. The biomarker variables were validated in 6 independent RA cohorts. This approach simplifies and expedites the development of algorithmic biomarkers accurately predicting individual treatment response, thereby enabling the deployment of precision medicine, and, in the future, providing a basis for dynamic labeling of prescription drugs. Original Trial Registration used for analysis: ClinicalTrials.gov registration:NCT01313520

show abstract

Section: Discussionmentioning

confidence: 99%

AI based on evolutionary computation yields algorithmic biomarker summary of a randomized rheumatoid arthritis clinical trial, accurately predicting individual patient outcomes, enabling precision medicine

Horgan,

McDermott,

Harrington

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Mechanisms of tropomyosin 3 in the development of malignant tumors

Chen,

Li,

Gui

et al. 2024

Heliyon

View full text Add to dashboard Cite

High resolution kinematic approach for quantifying impaired mobility of dystrophic zebrafish larvae

Widrick,

Lambert,

de Souza Leite

et al. 2024

Preprint

View full text Add to dashboard Cite

Dystrophin-deficient zebrafish larvae are a small, genetically tractable vertebrate model of Duchenne muscular dystrophy well suited for early stage therapeutic development. However, current approaches for evaluating their impaired mobility, a physiologically relevant therapeutic target, are characterized by low resolution and high variability. To address this, we used high speed videography and deep learning-based markerless motion capture to develop linked-segment models of larval escape response (ER) swimming. Kinematic models provided repeatable, high precision estimates of larval ER performance. Effect sizes for ER peak instantaneous acceleration and speed, final displacement, and ER distance were 2 to 3.5 standard deviations less for dystrophin-deficient mutants vs. wild-types. Further analysis revealed that mutants swam slower because of a reduction in their tail stroke frequency with little change in tail stroke amplitude. Kinematic variables were highly predictive of the dystrophic phenotype with ≤ 3% of larvae misclassified by random forest and support vector machine models. Tail kinematics also performed as well as in vitro assessments of tail muscle contractility in classifying larvae as mutants or wild-type, suggesting that ER kinematics could serve as a non-lethal proxy for direct measurements of muscle function. In summary, ER kinematics can be used as precise, physiologically relevant, non-lethal biomarkers of the dystrophic phenotype. The open-source approach described here may have applications not only for studies of skeletal muscle disease but for other disciplines that use larval mobility as an experimental outcome.

show abstract

Tropomyosin 3 (TPM3) function in skeletal muscle and in myopathy

Cited by 6 publications

References 151 publications

AI based on evolutionary computation yields algorithmic biomarker summary of a randomized rheumatoid arthritis clinical trial, accurately predicting individual patient outcomes, enabling precision medicine

AI based on evolutionary computation yields algorithmic biomarker summary of a randomized rheumatoid arthritis clinical trial, accurately predicting individual patient outcomes, enabling precision medicine

Mechanisms of tropomyosin 3 in the development of malignant tumors

High resolution kinematic approach for quantifying impaired mobility of dystrophic zebrafish larvae

Contact Info

Product

Resources

About