Choline consumption reduces CVD risk via body composition modification

Abstract

Despite extensive research on the relationship between choline and cardiovascular disease (CVD), conflicting findings have been reported. We aim to investigate the relationship between choline and CVD. Our analysis screened a retrospective cohort study of 14,663 participants from the National Health and Nutrition Examination Survey conducted between 2013 and 2018. Propensity score matching and restricted cubic splines was used to access the association between choline intake and the risk of CVD. A two-sample Mendelian randomization (MR) analysis was conducted to examine the potential causality. Additionally, sets of single cell RNA-sequencing data were extracted and analyzed, in order to explore the role of choline metabolism pathway in the progression and severity of the CVD and the underlying potential mechanisms involved. The adjusted odds ratios and 95% confidence intervals for stroke were 0.72 (0.53-0.98; p = 0.035) for quartile 3 and 0.54 (0.39-0.75; p < 0.001) for quartile 4. A stratified analysis revealed that the relationship between choline intake and stroke varied among different body mass index and waist circumference groups. The results of MR analysis showed that choline and phosphatidylcholine had a predominantly negative causal effect on fat percentage, fat mass, and fat-free mass, while glycine had opposite effects. Results from bioinformatics analysis revealed that alterations in the choline metabolism pathway following stroke may be associated with the prognosis. Our study indicated that the consumption of an appropriate quantity of choline in the diet may help to protect against CVD and the effect may be choline-mediated, resulting in a healthier body composition. Furthermore, the regulation of the choline metabolism pathway following stroke may be a promising therapeutic target.

Figure 1

Forest plots of stroke risk factors before and after propensity score matching (PSM). (a) The forest plot of stroke risk factors before matching. (b) The distribution of propensity scores is examined for both the matched and unmatched stroke and control subjects, with a ratio of 1:2. (c) The forest plot of stroke risk factors after matching.

Figure 2

Restricted cubic spline (RCS) models adjusting for sex, age, race, education, smoking, hypertension, and diabetes.. The 95% confidence intervals of the adjusted odds ratios are visually depicted by the light purple-shaded region. including.

Figure 3

Causal relationship between genetically predicted choline metabolites and the risk of stroke and the body composition. (a) A schematic representation illustrating the relationship between choline metabolites and body composition. (b) Causal effects of choline metabolites on stroke and body composition. The effects are exhibited in heatmap with odds ratio. Choline metabolites encompass choline, phosphatidylcholine, and glycine. Stroke is classified into five distinct types, namely any stroke, ischemic stroke, cardioembolic stroke, small vessel stroke, and large artery stroke. Body composition encompasses lean body mass, appendicular lean body mass, body fat percentage, body fat mass, and body fat-free mass. (c) Causal effects of choline metabolites on body fat composition. The effects are exhibited in heatmap with odds ratio. Choline metabolites encompass choline, phosphatidylcholine, and glycine. Body fat composition encompasses fat percentage, mass, and fat-free mass of right/left arm/leg and trunk.

Figure 4

Single-cell transcriptomic analysis and the assessment of choline pathway score in post-stroke brain samples. (a) The uniform manifold approximation and projection (UMAP) plot of the identified cell clusters in brain tissue from healthy control, ischemic stroke, and hemorrhagic stroke groups. (b) Relative proportion of each cell cluster of healthy control group, ischemic stroke group, and hemorrhagic stroke group. (c) UCell scores of choline metabolism gene signature of single cell from the total of healthy control group, ischemic stroke group, and hemorrhagic stroke group. (d) UCell scores of choline metabolism gene signature of single cell from healthy control (Control) group, ischemic stroke (IS) group, and hemorrhagic stroke (HS) group, respectively. (e) Bar plot showing the choline metabolism gene signature UCell scores of control group and ischemic stroke group. (f) Bar plot showing the choline metabolism gene signature UCell scores of control group and hemorrhagic stroke group. p values were determined by a two-tailed Student's t-test. *, p < 0.05; **, p < 0.01; ***, p < 0.001 ****, p < 0.0001.

Figure 5

Single-cell transcriptomic analysis and the assessment of choline pathway score in adipose tissue from high-fat diet (HFD) fed mice and low-fat diet (LFD) fed mice. (a) The uniform manifold approximation and projection (UMAP) plot of the identified cell clusters in adipose tissues from high-fat diet fed group and low-fat diet fed group. (b) Relative proportion of each cell cluster of high-fat diet fed group and low-fat diet fed group. (c) UCell scores of choline metabolism gene signature of single cell from both high-fat diet fed group and low-fat diet fed group. (d) UCell scores of choline metabolism gene signature of single cell from high-fat diet fed group and low-fat diet fed group, respectively. (e) Bar plot showing the choline metabolism gene signature UCell scores of adipose tissues from high-fat diet fed group and low-fat diet fed group. (f) Bar plot showing the choline metabolism gene signature UCell scores of adipocytes from high-fat diet fed group and low-fat diet fed group. p values were determined by a two-tailed Student's t-test. *, p < 0.05; **, p < 0.01; ***, p < 0.001 ****, p < 0.0001.

Figure 6

Identification of adipocyte functionality under high-fat diet (HFD) and low-fat diet (LFD) conditions. (a) A schematic representation illustrating the relationship between choline, functionality of adipocyte, and cardiovascular disease incidence. (b) Gene ontology (GO) enrichment of differentially expressed genes in adipocyte between low-fat diet fed group and high-fat diet fed group. (c) Volcano plot showing differentially expressed genes encoding secreted proteins in adipocyte compared to other cell clusters. (d) Gene ontology enrichment of differentially expressed genes encoding secreted proteins in adipocyte compared to other cell clusters.