A Proactive Intervention Study in Metabolic Syndrome High-Risk Populations Using Phenome-Based Actionable P4 Medicine Strategy

Abstract

The integration of predictive, preventive, personalized, and participatory (P4) healthcare advocates proactive intervention, including dietary supplements and lifestyle interventions for chronic disease. Personal profiles include deep phenotypic data and genetic information, which are associated with chronic diseases, can guide proactive intervention. However, little is known about how to design an appropriate intervention mode to precisely intervene with personalized phenome-based data. Here, we report the results of a 3-month study on 350 individuals with metabolic syndrome high-risk that we named the Pioneer 350 Wellness project (P350). We examined: (1) longitudinal (two times) phenotypes covering blood lipids, blood glucose, homocysteine (HCY), and vitamin D₃ (VD₃), and (2) polymorphism of genes related to folic acid metabolism. Based on personalized data and questionnaires including demographics, diet and exercise habits information, coaches identified 'actionable possibilities', which combined exercise, diet, and dietary supplements. After a 3-month proactive intervention, two-thirds of the phenotypic markers were significantly improved in the P350 cohort. Specifically, we found that dietary supplements and lifestyle interventions have different effects on phenotypic improvement. For example, dietary supplements can result in a rapid recovery of abnormal HCY and VD₃ levels, while lifestyle interventions are more suitable for those with high body mass index (BMI), but almost do not help the recovery of HCY. Furthermore, although people who implemented only one of the exercise or diet interventions also benefited, the effect was not as good as the combined exercise and diet interventions. In a subgroup of 226 people, we examined the association between the polymorphism of genes related to folic acid metabolism and the benefits of folate supplementation to restore a normal HCY level. We found people with folic acid metabolism deficiency genes are more likely to benefit from folate supplementation to restore a normal HCY level. Overall, these results suggest: (1) phenome-based data can guide the formulation of more precise and comprehensive interventions, and (2) genetic polymorphism impacts clinical responses to interventions. Notably, we provide a proactive intervention example that is operable in daily life, allowing people with different phenome-based data to design the appropriate intervention protocol including dietary supplements and lifestyle interventions.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-023-00115-z.

Keywords: Dietary supplements; Exercise; Personalized; Wellness.

Fig. 1

The experimental pipeline and grouping methods. a A total of 350 individuals participated in the P350 project. Physical examination and clinical and genetic tests were performed two weeks before the intervention and data were collected. Afterward, each received health science education and a survey on family disease backgrounds, diet, medicine and supplements, daily activities, etc. Then each individual underwent a 3-month intervention with the guidance of the coach. At the end of the intervention, we performed the metabolic and phenotypic tests on all of them again. b After the intervention, participants were divided into groups SL (dietary supplements and lifestyle), group S (dietary supplements), and group L (lifestyle) according to each individual's actual implementation. There were 267 individuals in the SL group, 26 in the S group, and 55 people in the L group. Of the 267 in the SL group, a subset of participants who performed lifestyle interventions including diet and exercise was termed the D&E group (N = 193). The rest with either diet or exercise were classified as the D|E group (N = 74)

Fig. 2

Overview of health status before and after the intervention in the overall cohort. a Proportions of participants with different levels of phenotypic features before the intervention. Blue, green, and red indicate that the expression level of markers is lower than the normal value, within the normal range, and higher than the normal value, respectively. b Percentage of all participants in the cohort with different MTHFR and MTRR gene polymorphisms. (Dark green: wild type; green: heterozygote; light green: homozygote. c The proportions of abnormal features at the time of enrollment for different phenotypic features. Percentages labeled in vertices are proportions of the abnormal population for phenotypic features. Note that blood lipids include TC, TG, HDL-C, and LDL-C. Blood glucose includes FPG and HbA1C. Scatter plots of levels of TC (d), LDL-C (e), HDL-C (f), HbA1C (g), HCY (h), and VD₃ (i) of participants before (0 months) and after (3 months) the intervention. The significance of the difference is shown above the scatter points (*p < 0.05, **p < 0.01) by the two-sided t-test (normal distribution) or Wilcoxon test (non-normal distribution). The lines in the middle represent the median, and the lines above and below represent the first and third quartiles

Fig. 3

Levels of phenotypic features before and after the intervention in the SL, S, and L groups as well as the relationship between folate metabolism-related genes and HCY level changes. Scatter plots for the levels of TC (a), LDL-C (b), FPG (c), HCY (d), and VD₃ (e) of participants of the SL group, levels of TC (f), HDL-C (g), FPG (h), HCY (i), and VD₃ (j) of participants of the S group and values of BMI (k), FPG (l), and VD₃ (m) of participants of the L group before (0 month) and after (3 month) the intervention. n HCY changes by the intervention for individuals with different MTHFR C677T polymorphisms. The numbers of participants of the three MTHFR C677T polymorphisms are homozygotes (TT, N = 63), heterozygotes (CT, N = 117), and wild type (CC, N = 46). o HCY changes by the intervention for individuals with different folic acid utilization abilities based on MTRR A66G, MTHFR C677T, and A1298C polymorphisms. The WEAKER group (N = 80) contained at least one homozygote for the three gene polymorphisms, and the population of the STRONGER group (N = 146) contained no homozygous mutations in the three gene polymorphisms. The line in the middle represents the median, and the lines above and below represent the first and third quartiles. Results of pairwise comparisons of zero and three months by two-sided t-test (normal distribution) or Wilcoxon test (non-normal distribution) were presented above the scatter points with *p < 0.05, and **p < 0.01. When comparing three groups in panel n, two-sided single-factor ANOVA (following the homogeneity of variance) or Kruskal–Wallis H test (not following the homogeneity of variance) was used

Fig. 4

Differences in the level changes of phenotypic features after the intervention among groups. Scatter plots for the changes in plasma levels of BMI (a), FPG (b), and HCY (c) of participants in the SL, S, and L groups that numbers of participants in each group are: SL (N = 267), S (N = 28), and L (N = 55). When dividing the participants in the SL group into D&E groups who performed both diet and exercise interventions and D|E groups who received either diet or exercise intervention, the changes in BMI (d), FPG (e), and HbA1C (f) levels were plotted. The line in the middle represents the median, and the lines above and below represent the first and third quartiles. Two-sided single-factor ANOVA (following the homogeneity of variance) or Kruskal–Wallis H test (not following the homogeneity of variance) was used and p-values are: *p < 0.05, and **p < 0.01

Fig. 5

Overview of the intervention effects of the cohort. a Numbers of improved phenotypes in the post-intervention cohort (negative numbers represent deterioration). The green gradient part of the pie chart represents the proportion of the total population who improved by one phenotype marker or more, and the percentage of the improved population reached 59.14%. The more phenotypes that improve, the greener it becomes. The red gradient part of the pie chart represents the proportion of the total population with worsening of one phenotype marker or more, and the percentage of the worsening population is 22.00%. The more deteriorating phenotypes, the redder it becomes. The gray part in of the pie chart represents the proportion of the total population with neither improvement nor deterioration, and the percentage of the stable population is only 18.86%. b Histogram showing the proportion of each phenotypic feature improved from abnormal to normal