Biology subjects

Christle, J. W.

Publications and source records attributed to Christle, J. W..

3 recordsLinked to original sources

bioRxiv2026

Molecular Transducers of Physical Activity Consortium (MoTrPAC): Initial Insights into the Dynamic Human Responses to Exercise

The goal of the Molecular Transducers of Physical Activity Consortium (MoTrPAC) is to examine the physiological and molecular basis for health benefits in response to acute and chronic exercise. Prior to COVID-19 suspension, healthy, sedentary participants (N=206, 18-74y) were randomized to endurance exercise (N=80), resistance exercise (N=81), or non-exercise control (N=45) interventions. The prescribed vigorous acute endurance and resistance exercise bouts induced physiological and metabolic perturbations relative to resting homeostasis. The supervised chronic (3d/wk, 12wk) endurance or resistance training programs robustly improved several physiological parameters (i.e., VO2peak, muscular strength). Temporal biospecimen (blood, muscle, and adipose) collections and processing coupled to the acute exercise bouts were highly successful. In most cases, over 90% success was achieved for blood, muscle, and adipose samples. Endurance and resistance exercise induced distinct acute and chronic physiological responses, which provide a framework to interrogate the molecular basis for health adaptations to these two popular exercise modalities. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/705347v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@554ee9org.highwire.dtl.DTLVardef@afb28dorg.highwire.dtl.DTLVardef@f381cdorg.highwire.dtl.DTLVardef@cef19c_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2020

Molecular Choreography of Acute Exercise

Exercise testing is routinely used in clinical practice to assess fitness - a strong predictor of survival - as well as causes of exercise limitations. While these studies often focus on cardiopulmonary response and selected molecular pathways, the dynamic system-wide molecular response to exercise has not been fully characterized. We performed a longitudinal multi-omic profiling of plasma and peripheral blood mononuclear cells including transcriptome, immunome, proteome, metabolome and lipidome in 36 well-characterized volunteers before and after a controlled bout of acute exercise (2, 15, 30 min and 1 hour in recovery). Integrative analysis revealed an orchestrated choreography of biological processes across key tissues. Most of these processes were dampened in insulin resistant participants. Finally, we discovered biological pathways involved in exercise capacity and developed prediction models revealing potential resting blood-based biomarkers of fitness.

systems biology↗

bioRxiv2016

Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort

BackgroundThe ability to measure activity and physiology through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown.\n\nObjectiveTo assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework.\n\nMethodsWe evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 {+/-} 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination.\n\nResultsDevices reported the lowest error for cycling and the highest for walking. Device error was higher for males,greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest.\n\nConclusionsMost wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).\n\nAbbreviations

bioinformatics↗