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Extracting meaningful features from time series analysis of plasma analytes in clinical research.

Created on 25 Oct 2026

Authors

Paul S Blank, Adriana E Golding, Ivonne Morales, Hang Waters, Elena Mekhedov, Ludmila Bezrukov, Rebecca D Wachter, Irina Mikhailenko, Robert H Brown, Carsten G Bönnemann, Andrew P Demidowich, Minal S Jain, Jack A Yanovski, Joshua Zimmerberg

Published in

medRxiv : the preprint server for health sciences. Oct 11, 2026. Epub Oct 11, 2026.

Abstract

While absolute blood biomarkers have long guided diagnosis, their rate of change often provides greater diagnostic value. For the Limb Girdle Muscular Dystrophies studied here, increased muscle weakness is associated with abnormal sarcolemma repair. Time course analyses were made to changes in muscle-derived plasma enzymes after modest physical activity of ambulatory inpatients. Blood samples at 20 selected time points at variable intervals were obtained at rest, and before and after routine morning activities and motor function testing. After these activities, plasma enzyme levels increased in a similar way, suggesting damage and leakage from skeletal muscle. The levels then decreased in a similar way, suggesting that muscle cells stopped leaking and enzymes were subsequently cleared from the blood. The complex temporal changes were modeled using both continuous time and data features to reduce the number of parameters required to describe the irregularly sampled, interrupted, time series data. Unlike individuals with cardiac muscle ischemia or following intense exercise, there was no extended post-injury rising phase of enzyme levels. In contradistinction, levels fell once activity ceased. Time series analyses of blood biomarkers most likely provide an assay and index of sarcolemma fragility and by extension skeletal muscle damage.

PMID:
42926978
Bibliographic data and abstract were imported from PubMed on 25 Oct 2026.

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