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. 2021 Jan;8(24):e14659.
doi: 10.14814/phy2.14659.

The influence of interstitial cells of Cajal loss and aging on slow wave conduction velocity in the human stomach

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The influence of interstitial cells of Cajal loss and aging on slow wave conduction velocity in the human stomach

Tim Hsu-Han Wang et al. Physiol Rep. 2021 Jan.

Abstract

Loss of interstitial cells of Cajal (ICC) has been associated with gastric dysfunction and is also observed during normal aging at ~13% reduction per decade. The impact of ICC loss on gastric slow wave conduction velocity is currently undefined. This study correlated human gastric slow wave velocity with ICC loss and aging. High-resolution gastric slow wave mapping data were screened from a database of 42 patients with severe gastric dysfunction (n = 20) and controls (n = 22). Correlations were performed between corpus slow wave conduction parameters (frequency, velocity, and amplitude) and corpus ICC counts in patients, and with age in controls. Physiological parameters were further integrated into computational models of gastric mixing. Patients: ICC count demonstrated a negative correlation with slow wave velocity in the corpus (i.e., higher velocities with reduced ICC; r2 = .55; p = .03). ICC count did not correlate with extracellular slow wave amplitude (p = .12) or frequency (p = .84). Aging: Age was positively correlated with slow wave velocity in the corpus (range: 25-74 years; r2 = .32; p = .02). Age did not correlate with extracellular slow wave amplitude (p = .40) or frequency (p = .34). Computational simulations demonstrated that the gastric emptying rate would increase at higher slow wave velocities. ICC loss and aging are associated with a higher slow wave velocity. The reason for these relationships is unexplained and merit further investigation. Increased slow wave velocity may modulate gastric emptying higher, although in gastroparesis other pathological factors must dominate to prevent emptying.

Keywords: aging; computational simulation; human; interstitial cells of Cajal (ICC); slow wave velocity; stomach.

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Conflict of interest statement

TRA, PD, AG, NP, LKC, GOG hold intellectual property in the field of gastric electrophysiology evaluation of FlexiMap Ltd. TRA, PD, NP, LKC, GOG are shareholders of FlexiMap Ltd.

Figures

FIGURE 1
FIGURE 1
Electrograms (left) of control patients with younger (25 years old) and older age (46 years old), along with their respective activation (middle) and velocity field maps (right). Each small dot on the maps represents a single electrode. Individual electrodes were selected along the path of propagation. The inter‐electrode distance shown is 4 mm. Each color band in the activation maps represent the area of slow wave propagation per unit of time. The difference in map scales reflects the slow wave velocity differences
FIGURE 2
FIGURE 2
Velocity of peristaltic contraction as a function of the distance from the pylorus, as applied in computational simulations of gastric mixing and emptying
FIGURE 3
FIGURE 3
Negative linear correlation between slow wave velocity and ICC count (r 2 = .55, p = .03). With multiple regression R 2 = 0.60. Red plots represent patients with gastroparesis. Blue plots represent patients with chronic nausea and vomiting. Some error bars are not shown due to the margin of error being smaller than the physical size of the mean plots
FIGURE 4
FIGURE 4
Positive linear correlation between slow wave velocity and age (r 2 = .32, p = .02). With multiple regression R 2 = 0.32. Some error bars are not shown due to the margin of error being smaller than the physical size of the mean plots
FIGURE 5
FIGURE 5
Activation and velocity field maps of five control subjects, showing a spectrum of gastric slow wave velocities observed in our cohort. The respective ages are 25, 39, 45, 58, and 74 years old (left to right). Proximal stomach is indicated at the top of all maps and the distal stomach is indicated at the bottom of all maps. The differences in both the activation and velocity map scales reflect the slow wave velocity differences
FIGURE 6
FIGURE 6
Snapshots of numerical results from the gastric contraction simulations for (a) v = 1.0 mm/s, (b) 2.5 mm/s, and (c) 5.0 mm/s
FIGURE 7
FIGURE 7
Computational simulation for (a) mixing efficiency and (b) emptying rate for a liquid content with μ = 1.25 Pa·s

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