Evidence from human cohorts indicates that chronic insomnia is associated with higher risk of cardiometabolic diseases (CMD), yet whether gut microbiota plays a role is unclear. Here, in a longitudinal cohort (n = 1809), we find that the gut microbiota-bile acid axis may link the positive association between chronic insomnia and CMD. Ruminococcaceae UCG-002 and Ruminococcaceae UCG-003 are the main genera mediating the positive association between chronic insomnia and CMD. These results are also observed in an independent cross-sectional cohort (n = 6122). The inverse associations between those gut microbial biomarkers and CMD are mediated by certain bile acids (isolithocholic acid, muro cholic acid and nor cholic acid). Habitual tea consumption is prospectively associated with the identified gut microbiota and bile acids in an opposite direction compared with chronic insomnia. Our work suggests that microbiota-bile acid axis may be a potential intervention target for reducing the impact of chronic insomnia on cardiometabolic health.

Background The role of different types and quantities of macronutrients on human health has been controversial, and the individual response to dietary macronutrient intake needs more investigation. Objectives We aimed to use an ‘n-of-1’ study design to investigate the individual variability in postprandial glycemic response when eating diets with different macronutrient distributions among apparently healthy adults. Methods Thirty apparently healthy young Chinese adults (women, 68%) aged between 22 and 34 y, with BMI between 17.2 and 31.9 kg/m2, were provided with high-fat, low-carbohydrate (HF-LC, 60–70% fat, 15–25% carbohydrate, 15% protein, of total energy) and low-fat, high-carbohydrate (LF-HC, 10–20% fat, 65–75% carbohydrate, 15% protein) diets, for 6 d wearing continuous glucose monitoring systems, respectively, in a randomized sequence, interspersed by a 6-d wash-out period. Three cycles were conducted. The primary outcomes were the differences of maximum postprandial glucose (MPG), mean amplitude of glycemic excursions (MAGE), and AUC24 between intervention periods of LF-HC and HF-LC diets. A Bayesian model was used to predict responders with the posterior probability of any 1 of the 3 outcomes reaching a clinically meaningful difference. Results Twenty-eight participants were included in the analysis. Posterior probability of reaching a clinically meaningful difference of MPG (0.167 mmol/L), MAGE (0.072 mmol/L), and AUC24 (13.889 mmol/L·h) between LF-HC and HF-LC diets varied among participants, and those with posterior probability >80% were identified as high-carbohydrate responders (n = 9) or high-fat responders (n = 6). Analyses of the Bayesian-aggregated n-of-1 trials among all participants showed a relatively low posterior probability of reaching a clinically meaningful difference of the 3 outcomes between LF-HC and HF-LC diets. Conclusions N-of-1 trials are feasible to characterize personal response to dietary intervention in young Chinese adults.

Background The early life risk factors of childhood obesity among preterm infants are unclear and little is known about the influence of the feeding practices. We aimed to identify early life risk factors for childhood overweight/obesity among preterm infants and to determine feeding practices that could modify the identified risk factors. Methods A total of 338,413 mother-child pairs were enrolled in the Jiaxing Birth Cohort (1999 to 2013), and 2125 eligible singleton preterm born children were included for analyses. We obtained data on health examination, anthropometric measurement, lifestyle, and dietary habits of each participant at their visits to clinics. An interpretable machine learning-based analytic framework was used to identify early life predictors for childhood overweight/obesity, and Poisson regression was used to examine the associations between feeding practices and the identified leading predictor. Results Of the eligible 2125 preterm infants (863 [40.6%] girls), 274 (12.9%) developed overweight/obesity at age 4–7 years. We summarized early life variables into 25 features and identified two most important features as predictors for childhood overweight/obesity: trajectory of infant BMI (body mass index) Z -score change during the first year of corrected age and maternal BMI at enrollment. According to the impacts of different BMI Z -score trajectories on the outcome, we classified this feature into the favored and unfavored trajectories. Compared with early introduction of solid foods (≤ 3 months of corrected age), introducing solid foods after 6 months of corrected age was significantly associated with 11% lower risk (risk ratio, 0.89; 95% CI, 0.82 to 0.97) of being in the unfavored trajectory. Conclusions The trajectory of BMI Z -score change within the first year of life is the most important predictor for childhood overweight/obesity among preterm infants. Introducing solid foods after 6 months of corrected age is a recommended feeding practice for mitigating the risk of being in the unfavored trajectory.

Personalized dietary recommendations can help with more effective disease prevention. This study aims to investigate the individual postprandial glucose response to diets with diverse macronutrient proportions at both individual level and population level and explore the potential of the novel single-patient (n-of-1) trial for personalization of diet. Secondary outcomes include individual phenotypic response and the effects of dietary ingredients on the composition of gut microbiota. Westlake N-of-1 Trials for Macronutrient Intake (WE-MACNUTR) is a multiple crossover feeding trial consisting of three successive 12-day dietary intervention pairs including a 6-day wash-out period before each 6-day isocaloric dietary intervention (a 6-day high-fat, low-carbohydrate (HF-LC) diet and a 6-day low-fat, high-carbohydrate (LF-HC) diet). The results will help provide personalized dietary recommendations on macronutrients in terms of postprandial blood glucose responses. The proposed n-of-1 trial methods may help in optimizing individual health and advancing health care. This trial was registered with clinicaltrials.gov (NCT04125602).

Background Dietary diversity is essential for human health. The gut ecosystem provides a potential link between dietary diversity, host metabolism, and health, yet this mechanism is poorly understood. Objectives Here, we aimed to investigate the relation between dietary diversity and the gut environment as well as host metabolism from a multiomics perspective. Methods Two independent longitudinal Chinese cohorts (a discovery and a validation cohort) were included in the present study. Dietary diversity was evaluated with FFQs. In the discovery cohort (n = 1916), we performed shotgun metagenomic and 16S ribosomal ribonucleic acid (rRNA) sequencing to profile the gut microbiome. We used targeted metabolomics to quantify fecal and serum metabolites. The associations between dietary diversity and the microbial composition were replicated in the validation cohort (n = 1320). Results Dietary diversity was positively associated with α diversity of the gut microbiota. We identified dietary diversity–related gut environment features, including the microbial structure (β diversity), 68 microbial genera, 18 microbial species, 8 functional pathways, and 13 fecal metabolites. We further found 332 associations of dietary diversity and related gut environment features with circulating metabolites. Both the dietary diversity and diversity-related features were inversely correlated with 4 circulating secondary bile acids. Moreover, 16 mediation associations were observed among dietary diversity, diversity-related features, and the 4 secondary bile acids. Conclusions These results suggest that high dietary diversity is associated with the gut microbial environment. The identified key microbes and metabolites may serve as hypotheses to test for preventing metabolic diseases.

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IMPORTANCE Diet and nutrition play essential roles in human health. Personalized dietary recommendations or nutritional advice tailored to each individual can help with more effective disease prevention. N-of-1 trials can provide a pragmatic clinical means of addressing individual postprandial blood glucose variation in response to different food ingredients or nutrients. OBJECTIVE To investigate the individual postprandial glucose response to diets with diverse macronutrient proportions at both individual level and population level and the potential of the novel single-patient (n-of-1) trial for the personalization of diet. DESIGN Westlake N-of-1 Trials for Macronutrient Intake (WE-MACNUTR) is a multiple crossover feeding trial. Individual response to different dietary patterns in terms of postprandial glucose response is the primary outcome. Secondary outcomes include individual phenotypic response and the effects of dietary ingredients on the composition and structure of gut microbiota. SETTING Participants experience three successive 12-day dietary intervention pairs including a 6-day wash-out period before each isocaloric dietary intervention. Two different type of diets (a 6-day high-fat, low-carbohydrate (HF-LC) diet and a 6-day low-fat, high-carbohydrate (LF-HC) diet) are assigned to an individual in a randomized sequence using block randomization with a fixed block size of two. This feeding trial takes place in Hangzhou, China. PARTICIPANTS Target enrolment is 30 healthy individuals aged between 18 and 65 years. Exclusion criteria are inability or unwillingness to approved informed consent; other serious medical conditions; food allergy; and no access to a smart phone or computer with an internet connection. DISCUSSION This trial addresses the feasibility of n-of-1 approach for personalizing dietary intervention to individuals. The results will help provide personalized dietary recommendation on macronutrients in terms of postprandial blood glucose response. Well-designed n-of-1 trial is likely to become an effective method of optimizing individual health and advancing health care. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT04125602

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