Gut microbiome features and metabolites in non-alcoholic fatty liver disease among community-dwelling middle-aged and older adults.

BACKGROUND: The specific microbiota and associated metabolites linked to non-alcoholic fatty liver disease (NAFLD) are still controversial. Thus, we aimed to understand how the core gut microbiota and metabolites impact NAFLD. METHODS: The data for the discovery cohort were collected from the Guangzhou Nutrition and Health Study (GNHS) follow-up conducted between 2014 and 2018. We collected 272 metadata points from 1546 individuals. The metadata were input into four interpretable machine learning models to identify important gut microbiota associated with NAFLD. These models were subsequently applied to two validation cohorts [the internal validation cohort (n = 377), and the prospective validation cohort (n = 749)] to assess generalizability. We constructed an individual microbiome risk score (MRS) based on the identified gut microbiota and conducted animal faecal microbiome transplantation experiment using faecal samples from individuals with different levels of MRS to determine the relationship between MRS and NAFLD. Additionally, we conducted targeted metabolomic sequencing of faecal samples to analyse potential metabolites. RESULTS: Among the four machine learning models used, the lightGBM algorithm achieved the best performance. A total of 12 taxa-related features of the microbiota were selected by the lightGBM algorithm and further used to calculate the MRS. Increased MRS was positively associated with the presence of NAFLD, with odds ratio (OR) of 1.86 (1.72, 2.02) per 1-unit increase in MRS. An elevated abundance of the faecal microbiota (f__veillonellaceae) was associated with increased NAFLD risk, whereas f__rikenellaceae, f__barnesiellaceae, and s__adolescentis were associated with a decreased presence of NAFLD. Higher levels of specific gut microbiota-derived metabolites of bile acids (taurocholic acid) might be positively associated with both a higher MRS and NAFLD risk. FMT in mice further confirmed a causal association between a higher MRS and the development of NAFLD. CONCLUSIONS: We confirmed that an alteration in the composition of the core gut microbiota might be biologically relevant to NAFLD development. Our work demonstrated the role of the microbiota in the development of NAFLD.

Risk stratification of papillary thyroid cancers using multidimensional machine learning.

BACKGROUND: Papillary thyroid cancer (PTC) is one of the most common endocrine malignancies with different risk levels. However, preoperative risk assessment of PTC is still a challenge in the worldwide. Here, the authors first report a Preoperative Risk Assessment Classifier for PTC (PRAC-PTC) by multidimensional features including clinical indicators, immune indices, genetic feature, and proteomics. MATERIALS AND METHODS: The 558 patients collected from June 2013 to November 2020 were allocated to three groups: the discovery set [274 patients, 274 formalin-fixed paraffin-embedded (FFPE)], the retrospective test set (166 patients, 166 FFPE), and the prospective test set (118 patients, 118 fine-needle aspiration). Proteomic profiling was conducted by FFPE and fine-needle aspiration tissues from the patients. Preoperative clinical information and blood immunological indices were collected. The BRAFV600E mutation were detected by the amplification refractory mutation system. RESULTS: The authors developed a machine learning model of 17 variables based on the multidimensional features of 274 PTC patients from a retrospective cohort. The PRAC-PTC achieved areas under the curve (AUC) of 0.925 in the discovery set and was validated externally by blinded analyses in a retrospective cohort of 166 PTC patients (0.787 AUC) and a prospective cohort of 118 PTC patients (0.799 AUC) from two independent clinical centres. Meanwhile, the preoperative predictive risk effectiveness of clinicians was improved with the assistance of PRAC-PTC, and the accuracies reached at 84.4% (95% CI: 82.9-84.4) and 83.5% (95% CI: 82.2-84.2) in the retrospective and prospective test sets, respectively. CONCLUSION: This study demonstrated that the PRAC-PTC that integrating clinical data, gene mutation information, immune indices, high-throughput proteomics and machine learning technology in multicentre retrospective and prospective clinical cohorts can effectively stratify the preoperative risk of PTC and may decrease unnecessary surgery or overtreatment.

Continuous glucose monitoring-derived glycemic metrics and adverse pregnancy outcomes among women with gestational diabetes: a prospective cohort study.

Background: Continuous glucose monitoring (CGM) has shown potential in improving maternal and neonatal outcomes in individuals with type 1/2 diabetes, but data in gestational diabetes mellitus (GDM) is limited. We aimed to explore the relationship between CGM-derived metrics during pregnancy and pregnancy outcomes among women with GDM. Methods: We recruited 1302 pregnant women with GDM at a mean gestational age of 26.0 weeks and followed them until delivery. Participants underwent a 14-day CGM measurement upon recruitment. The primary outcome was any adverse pregnancy outcome, defined as having at least one of the outcomes: preterm birth, large-for-gestational-age (LGA) birth, fetal distress, premature rupture of membranes, and neonatal intensive care unit (NICU) admission. The individual outcomes included in the primary outcome were considered as secondary outcomes. We conducted multivariable logistic regression to evaluate the association of CGM-derived metrics with these outcomes. Findings: Per 1-SD difference in time above range (TAR), glucose area under the curve (AUC), nighttime mean blood glucose (MBG), daytime MBG, and daily MBG was associated with higher risk of any adverse pregnancy outcome, with odds ratio: 1.22 (95% CI 1.08-1.36), 1.22 (95% CI 1.09-1.37), 1.18 (95% CI 1.05-1.32), 1.21 (95% CI 1.07-1.35), and 1.22 (95% CI 1.09-1.37), respectively. Time in range, TAR, AUC, nighttime MBG, daytime MBG, daily MBG, and mean amplitude of glucose excursions were positively associated, while time blow range was inversely associated with the risk of LGA. Additionally, higher value for TAR was associated with higher risk of NICU admission. We further summarized the potential thresholds of TAR (2.5%) and daily MBG (4.8 mmol/L) to distinguish individuals with and without any adverse pregnancy outcome. Interpretation: The CGM-derived metrics may help identify individuals at higher risk of adverse pregnancy outcomes. These CGM biomarkers could serve as potential new intervention targets to maintain a healthy pregnancy status among women with GDM. Funding: National Key R&D Program of China, National Natural Science Foundation of China, and Westlake Laboratory of Life Sciences and Biomedicine.

Early-life exposure to the Great Chinese Famine and gut microbiome disruption across adulthood for type 2 diabetes: three population-based cohort studies.

BACKGROUND: The early life stage is critical for the gut microbiota establishment and development. We aimed to investigate the lifelong impact of famine exposure during early life on the adult gut microbial ecosystem and examine the association of famine-induced disturbance in gut microbiota with type 2 diabetes. METHODS: We profiled the gut microbial composition among 11,513 adults (18-97 years) from three independent cohorts and examined the association of famine exposure during early life with alterations of adult gut microbial diversity and composition. We performed co-abundance network analyses to identify keystone taxa in the three cohorts and constructed an index with the shared keystone taxa across the three cohorts. Among each cohort, we used linear regression to examine the association of famine exposure during early life with the keystone taxa index and assessed the correlation between the keystone taxa index and type 2 diabetes using logistic regression adjusted for potential confounders. We combined the effect estimates from the three cohorts using random-effects meta-analysis. RESULTS: Compared with the no-exposed control group (born during 1962-1964), participants who were exposed to the famine during the first 1000 days of life (born in 1959) had consistently lower gut microbial alpha diversity and alterations in the gut microbial community during adulthood across the three cohorts. Compared with the no-exposed control group, participants who were exposed to famine during the first 1000 days of life were associated with consistently lower levels of keystone taxa index in the three cohorts (pooled beta - 0.29, 95% CI - 0.43, - 0.15). Per 1-standard deviation increment in the keystone taxa index was associated with a 13% lower risk of type 2 diabetes (pooled odds ratio 0.87, 95% CI 0.80, 0.93), with consistent results across three individual cohorts. CONCLUSIONS: These findings reveal a potential role of the gut microbiota in the developmental origins of health and disease (DOHaD) hypothesis, deepening our understanding about the etiology of type 2 diabetes.

Population serum proteomics uncovers a prognostic protein classifier for metabolic syndrome.

Metabolic syndrome (MetS) is a complex metabolic disorder with a global prevalence of 20%-25%. Early identification and intervention would help minimize the global burden on healthcare systems. Here, we measured over 400 proteins from ∼20,000 proteomes using data-independent acquisition mass spectrometry for 7,890 serum samples from a longitudinal cohort of 3,840 participants with two follow-up time points over 10 years. We then built a machine-learning model for predicting the risk of developing MetS within 10 years. Our model, composed of 11 proteins and the age of the individuals, achieved an area under the curve of 0.774 in the validation cohort (n = 242). Using linear mixed models, we found that apolipoproteins, immune-related proteins, and coagulation-related proteins best correlated with MetS development. This population-scale proteomics study broadens our understanding of MetS and may guide the development of prevention and targeted therapies for MetS.

The Short-Term Variation of Human Gut Mycobiome in Response to Dietary Intervention of Different Macronutrient Distributions.

While the human gut is home to a complex and diverse community of microbes, including bacteria and fungi, research on the gut microbiome has largely focused on bacteria, with relatively little attention given to the gut mycobiome. This study aims to investigate how diets with different dietary macronutrient distributions impact the gut mycobiome. We investigated gut mycobiome response to high-carbohydrate, low-fat (HC) and low-carbohydrate high-fat (LC) diet interventions based on a series of 72-day feeding-based n-of-1 clinical trials. A total of 30 participants were enrolled and underwent three sets of HC and LC dietary interventions in a randomized sequence. Each set lasted for 24 days with a 6-day washout period between dietary interventions. We collected and analyzed the fungal composition of 317 stool samples before and after each intervention period. To account for intra-individual variation across the three sets, we averaged the mycobiome data from the repeated sets for analysis. Of the 30 participants, 28 (aged 22-34 years) completed the entire intervention. Our results revealed a significant increase in gut fungal alpha diversity (p < 0.05) and significant changes in fungal composition (beta diversity, p < 0.05) after the HC dietary intervention. Specifically, we observed the enrichment of five fungal genera (Pleurotus, Kazachstania, Auricularia, Paraphaeosphaeria, Ustilaginaceae sp.; FDR < 0.052) and depletion of one fungal genus (Blumeria; FDR = 0.03) after the HC intervention. After the LC dietary intervention, one fungal genus was enriched (Ustilaginaceae sp.; FDR = 0.003), and five fungal genera were depleted (Blumeria, Agaricomycetes spp., Malassezia, Rhizopus, and Penicillium; FDR < 0.1). This study provides novel evidence on how the gut mycobiome structure and composition change in response to the HC and LC dietary interventions and reveals diet-specific changes in the fungal genera.

The Association between Circulating 25-Hydroxyvitamin D and Carotid Intima-Media Thickness Is Mediated by Gut Microbiota and Fecal and Serum Metabolites in Adults.

SCOPE: Vitamin D is vital to cardiovascular health. This study examines the association between plasma 25-hydroxyvitamin D (25[OH]D) and the progression of carotid intima-media thickness (cIMT) and identifies the potential mediating biomarkers of gut microbiota and metabolites in adults. METHODS AND RESULTS: This 9-year prospective study includes 2975 subjects with plasma 25(OH)D at baseline and determined cIMT every 3 years. Higher circulating 25(OH)D is associated with decreased odds of higher (≥median) 9-year cIMT changes at the common carotid artery (hΔCCA-cIMT) (p-trend < 0.001). Multivariable-adjusted OR (95%CI) of hΔCCA-cIMT for tertiles 2 and 3 (vs. 1) of 25(OH)D is 0.87 (0.73-1.04) and 0.68 (0.57-0.82). Gut microbiome and metabolome analysis identify 18 biomarkers significantly associated with both 25(OH)D and hΔCCA-cIMT, including three microbial genera, seven fecal metabolites, eight serum metabolites, and pathway of synthesis and degradation of ketone bodies. Mediation/path analyses show the scores generated from the overlapped differential gut microbiota, fecal and serum metabolites, and serum acetoacetic acid alone could mediate the beneficial association between 25(OH)D and hΔCCA-cIMT by 10.8%, 23.1%, 59.2%, and 62.0% (all p < 0.05), respectively. CONCLUSIONS: These findings show a beneficial association between plasma 25(OH)D and the CCA-cIMT progression. The identified multi-omics biomarkers provide novel mechanistic insights for the epidemiological association.

Nutri-microbiome epidemiology, an emerging field to disentangle the interplay between nutrition and microbiome for human health.

Diet and nutrition have a substantial impact on the human microbiome, and interact with the microbiome, especially gut microbiome, to modulate various diseases and health status. Microbiome research has also guided the nutrition field to a more integrative direction, becoming an essential component of the rising area of precision nutrition. In this review, we provide a broad insight into the interplay among diet, nutrition, microbiome, and microbial metabolites for their roles in the human health. Among the microbiome epidemiological studies regarding the associations of diet and nutrition with microbiome and its derived metabolites, we summarize those most reliable findings and highlight evidence for the relationships between diet and disease-associated microbiome and its functional readout. Then, the latest advances of the microbiome-based precision nutrition research and multidisciplinary integration are described. Finally, we discuss several outstanding challenges and opportunities in the field of nutri-microbiome epidemiology.

Plasma protein and venous thromboembolism: prospective cohort and mendelian randomisation analyses.

We conducted cohort and Mendelian randomisation (MR) analyses to examine the associations of circulating proteins with risk of venous thromboembolism (VTE) to provide evidence basis for disease prevention and drug development. Cohort analysis was performed in 11 803 participants without baseline VTE. Cox regression was used to estimate the associations between 257 proteins and VTE risk. A machine-learning model was constructed to compare the importance of identified proteins and traditional risk factors. Genetic association data on VTE were obtained from a genome-wide meta-analysis (26 066 cases and 624 053 controls) and FinnGen (14 454 cases and 294 700 controls). The cohort analysis, including 353 incident VTE cases diagnosed during a 6.6-year follow-up, identified 21 proteins associated with VTE risk after false discovery rate correction. The machine-learning model indicated that body mass index and von Willebrand factor (vWF) made the same as well as most of the contributions to the overall model prediction. MR analysis found that genetically predicted levels of vWF, SERPINE1 (plasminogen activator inhibitor 1, known as PAI-1), EPHB4 (ephrin type-B receptor 4), TYRO3 (tyrosine-protein kinase receptor TYRO3), TNFRSF11A (tumour necrosis factor receptor superfamily member 11A), and BOC (brother of CDO) were causally associated with VTE risk.

Genome-wide genotype-serum proteome mapping provides insights into the cross-ancestry differences in cardiometabolic disease susceptibility.

Identification of protein quantitative trait loci (pQTL) helps understand the underlying mechanisms of diseases and discover promising targets for pharmacological intervention. For most important class of drug targets, genetic evidence needs to be generalizable to diverse populations. Given that the majority of the previous studies were conducted in European ancestry populations, little is known about the protein-associated genetic variants in East Asians. Based on data-independent acquisition mass spectrometry technique, we conduct genome-wide association analyses for 304 unique proteins in 2,958 Han Chinese participants. We identify 195 genetic variant-protein associations. Colocalization and Mendelian randomization analyses highlight 60 gene-protein-phenotype associations, 45 of which (75%) have not been prioritized in Europeans previously. Further cross-ancestry analyses uncover key proteins that contributed to the differences in the obesity-induced diabetes and coronary artery disease susceptibility. These findings provide novel druggable proteins as well as a unique resource for the trans-ancestry evaluation of protein-targeted drug discovery.

Comparison of fecal and blood metabolome reveals inconsistent associations of the gut microbiota with cardiometabolic diseases.

Blood metabolome is commonly used in human studies to explore the associations of gut microbiota-derived metabolites with cardiometabolic diseases. Here, in a cohort of 1007 middle-aged and elderly adults with matched fecal metagenomic (149 species and 214 pathways) and paired fecal and blood targeted metabolomics data (132 metabolites), we find disparate associations with taxonomic composition and microbial pathways when using fecal or blood metabolites. For example, we observe that fecal, but not blood butyric acid significantly associates with both gut microbiota and prevalent type 2 diabetes. These findings are replicated in an independent validation cohort involving 103 adults. Our results suggest that caution should be taken when inferring microbiome-cardiometabolic disease associations from either blood or fecal metabolome data.

Characterization of the Composition Variation of Healthy Human Gut Microbiome in Correlation with Antibiotic Usage and Yogurt Consumption.

Antibiotic usage and yogurt consumption are the major interventions for gut microbiota, yet their shared characteristics and disparities in healthy human gut microbiome remain unclear. This study aimed to decipher the composition changes among healthy humans, comparing antibiotic usage and yogurt consumption. The relative bacterial abundances of 1113 fecal samples were collected from an ongoing, population-based longitudinal cohort study in China that covered lifestyle, diet, disease status and physical measurements, and biological indicators of participants were obtained by the sequencing of 16S rRNA. The samples were divided into three groups, which were antibiotic users (122), yogurt consumers (497) and controls (494), where data visualization, alpha diversity, beta diversity and LEfSe analysis were conducted. At the family level, the relative abundances of Streptococcaceae, Enterobacteriaceae and Enterococcaceae families in antibiotic users increased almost 50%, 70% and 200%, respectively, while yogurt consumption also increased relative abundances of Streptococcaceae and Enterococcaceae, but not Enterobacteriaceae. Alpha diversity analyses suggested that the microbiome of the antibiotic usage and yogurt consumption groups exhibited an alpha diversity lower than that of the control. LEfSe analysis showed that, at the family level, the number of biomarkers in the yogurt consumption and antibiotic usage group were respectively 5 and 7, lower than that of the control (13). This study demonstrated the importance in considering the potential assistance of yogurt consumption on ARG gene transfer from commensal bacteria to pathogens in the human gut, which may pose a risk for human health. Antibiotic usage and yogurt consumption share more identical changes on healthy human gut flora than disparities. Therefore, in order to understand the potential risks of antibiotic usage and yogurt consumption on antibiotic resistance transmission in human gut microbiota, further research needs to be undertaken.

Gut microbiome, cognitive function and brain structure: a multi-omics integration analysis.

BACKGROUND: Microbiome-gut-brain axis may be involved in the progression of age-related cognitive impairment and relevant brain structure changes, but evidence from large human cohorts is lacking. This study was aimed to investigate the associations of gut microbiome with cognitive impairment and brain structure based on multi-omics from three independent populations. METHODS: We included 1430 participants from the Guangzhou Nutrition and Health Study (GNHS) with both gut microbiome and cognitive assessment data available as a discovery cohort, of whom 272 individuals provided fecal samples twice before cognitive assessment. We selected 208 individuals with baseline microbiome data for brain magnetic resonance imaging during the follow-up visit. Fecal 16S rRNA and shotgun metagenomic sequencing, targeted serum metabolomics, and cytokine measurements were performed in the GNHS. The validation analyses were conducted in an Alzheimer's disease case-control study (replication study 1, n = 90) and another community-based cohort (replication study 2, n = 1300) with cross-sectional dataset. RESULTS: We found protective associations of specific gut microbial genera (Odoribacter, Butyricimonas, and Bacteroides) with cognitive impairment in both the discovery cohort and the replication study 1. Result of Bacteroides was further validated in the replication study 2. Odoribacter was positively associated with hippocampal volume (ß, 0.16; 95% CI 0.06-0.26, P = 0.002), which might be mediated by acetic acids. Increased intra-individual alterations in gut microbial composition were found in participants with cognitive impairment. We also identified several serum metabolites and inflammation-associated metagenomic species and pathways linked to impaired cognition. CONCLUSIONS: Our findings reveal that specific gut microbial features are closely associated with cognitive impairment and decreased hippocampal volume, which may play an important role in dementia development.

Gut microbiota and acylcarnitine metabolites connect the beneficial association between equol and adiposity in adults: a prospective cohort study.

BACKGROUND: Many studies have investigated the effects of soy isoflavones on weight control, but few have focused on the role of equol, a gut-derived metabolite of daidzein with greater bioavailability than other soy isoflavones. OBJECTIVES: This study examined the association of equol production with obesity and explored the mediating roles of equol-related gut microbiota and microbial carnitine metabolites. METHODS: This 6.6-y prospective study included 2958 Chinese adults (2011 females and 947 males) aged 60.6 ± 6.0 y (mean ± SD) at baseline. Urinary equol and isoflavones were measured using HPLC-tandem MS. BMI, percentage fat mass (%FM), and serum triglycerides (TGs) were assessed every 3 y. Metagenomics sequencing and assessment of carnitine metabolites in feces were performed in a subsample of 897 participants. RESULTS: Urinary equol, but not daidzein and genistein, was independently and inversely associated with the obesity-related indicators of BMI, %FM, and a biomarker (TGs). Equol producers (EPs) had lower odds of adiposity conditions and a reduced risk of 6.6-y obesity progression than non-EPs among total participants. Gut microbial analyses indicated that EPs had higher microbiome species richness (P = 3.42 × 10-5) and significantly different ß-diversity of gut microbiota compared with the non-EP group (P = 0.001), with 20 of 162 species differing significantly. EPs (compared with non-EPs) had higher abundances of Alistipes senegalensis and Coprococcus catus but lower abundances of Ruminococcus gnavus (false discovery rate <0.05). Among the 7 determined fecal acylcarnitine metabolites, palmitoylcarnitine, oleylcarnitine 18:1, and stearylcarnitine were inversely associated with EPs but positively correlated with obesity conditions and progression. Path analyses indicated that the beneficial association between equol and obesity might be mediated by gut microbiota and decreased production of 3 acylcarnitines in feces. CONCLUSIONS: This study suggests a beneficial association between equol and obesity, mediated by the gut microbiome and acylcarnitines, in adults.This trial was registered at clinicaltrials.gov as NCT03179657.

Associations of dietary diversity with the gut microbiome, fecal metabolites, and host metabolism: results from 2 prospective Chinese cohorts.

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 (ß 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.

Interaction of n-3 polyunsaturated fatty acids with host CD36 genetic variant for gut microbiome and blood lipids in human cohorts.

BACKGROUND & AIMS: Previous studies suggest an interaction of CD36 genetic variant rs1527483 with n-3 polyunsaturated fatty acids (PUFAs) to modulate blood lipids. However, successful replication is lacking and the role of gut microbiome remains unclear. Here, we aimed to replicate these gene-diet interactions on blood lipids and investigate their possible associations with gut microbiome. METHODS: We evaluated the n-3 PUFA-rs1527483 interaction on blood lipids in two population-based cohorts (n = 4,786). We profiled fecal microbiome and short-chain fatty acids among 1,368 participants. The associations between n-3 PUFAs and bacterial alpha-diversity, taxonomies and short-chain fatty acids by rs1527483 genotypes were analyzed using regression models. RESULTS: CD36 rs1527483-GG carriers responded better to high n-3 PUFA exposure; higher blood HDL-C (beta (95% CI): 0.05 (0.01, 0.08) mmol/L) and lower TG (log-transformed, beta (95% CI): -0.08 (-0.14, -0.02)) were observed among participants whose n-3 PUFA exposure ranked in the top quartile comparing with those in the bottom quartile. We identified docosahexaenoic acid (DHA) as the driven individual n-3 PUFA biomarker, which showed interaction with rs1527483. Among the rs1527483-GG carriers, but not other genotype groups, DHA exposure was positively associated with bacterial Faith's phylogenetic diversity, Observed OTUs, Shannon's diversity index, Dorea, Coriobacteriales Incertae Sedis spp, and fecal propionic acid levels. Another independent longitudinal cohort validated the DHA-rs1527483 interaction on gut microbiome. The identified microbial features were correlated with blood lipids, and the host biosynthesis and metabolism pathways of bile acids and aromatic amino acids. CONCLUSIONS: The present study found that higher n-3 PUFAs were associated with improved blood lipids and gut microbial features only among rs1527483-GG carriers. These findings highlight a potential role of gut microbiome to link the CD36 genetic variant, n-3 PUFAs and blood lipids, revealing a new research direction to interpret the gene-diet interaction for cardiometabolic health.

Gut microbiota signatures of long-term and short-term plant-based dietary pattern and cardiometabolic health: a prospective cohort study.

BACKGROUND: The interplay among the plant-based dietary pattern, gut microbiota, and cardiometabolic health is still unclear, and evidence from large prospective cohorts is rare. We aimed to examine the association of long-term and short-term plant-based dietary patterns with gut microbiota and to assess the prospective association of the identified microbial features with cardiometabolic biomarkers. METHODS: Using a population-based prospective cohort study: the China Health and Nutrition Survey, we included 3096 participants from 15 provinces/megacities across China. We created an overall plant-based diet index (PDI), a healthful plant-based diet index (hPDI), and an unhealthful plant-based diet index (uPDI). The average PDIs were calculated using repeat food frequency questionnaires collected in 2011 and 2015 to represent a long-term dietary pattern. Short-term dietary pattern was estimated using 3-day 24-h dietary recalls collected in 2015. Fecal samples were collected in 2015 and measured using 16S rRNA sequencing. We investigated the association of long-term and short-term plant-based dietary patterns with gut microbial diversity, taxonomies, and functional pathways using linear mixed models. Furthermore, we assessed the prospective associations between the identified gut microbiome signatures and cardiometabolic biomarkers (measured in 2018) using linear regression. RESULTS: We found a significant association of short-term hPDI with microbial alpha-diversity. Both long-term and short-term plant-based diet indices were correlated with microbial overall structure, whereas long-term estimates explained more variance. Long-term and short-term PDIs were differently associated with microbial taxonomic composition, yet only microbes related to long-term estimates showed association with future cardiometabolic biomarkers. Higher long-term PDI was associated with the lower relative abundance of Peptostreptococcus, while this microbe was positively correlated with the high-sensitivity C-reactive protein and inversely associated with high-density lipoprotein cholesterol. CONCLUSIONS: We found shared and distinct gut microbial signatures of long-term and short-term plant-based dietary patterns. The identified microbial genera may provide insights into the protective role of long-term plant-based dietary pattern for cardiometabolic health, and replication in large independent cohorts is needed.

Association between postterm pregnancy and adverse growth outcomes in preschool-age children.

BACKGROUND: Postterm pregnancy has been associated with higher risk of perinatal mortality and morbidity, but its long-term health effects on offspring are poorly understood. OBJECTIVES: The aim of the study was to investigate the prospective associations between maternal postterm pregnancy and adverse growth outcomes in children. METHODS: The Jiaxing Birth Cohort is part of a large population-based health surveillance system in China and recruited pregnant females resident in the Jiaxing area between 1999 and 2013; newborns were followed up for a median duration of 5.8 y until they went to school. Mother-child pairs with maternal gestational information and offspring's anthropometric data at 4-7 y old were included. Postterm pregnancy was defined as maternal gestational age ≥42 and <47 wk, and its associations with offspring obesity, overweight/obesity, and thinness during childhood were determined by using Poisson regression models. RESULTS: Of the 101,505 included mother-child pairs, 2369 (2.3%) children were born at postterm. Children born at postterm had significantly lower BMI-for-age z score, weight-for-age z score, and height-for-age z score than those born at term; the mean difference (95% CI) was -0.11 (-0.15, -0.06), -0.17 (-0.21, -0.13), and -0.16 (-0.20, -0.12), respectively. When comparing postterm with term pregnancy, the multivariable-adjusted RRs and 95% CIs among preschool-age children were 0.87 (0.68, 1.11) for obesity, 0.82 (0.72, 0.94) for overweight/obesity, and 1.18 (1.09, 1.28) for thinness, respectively. These risk estimates were robust in sensitivity analyses, but were attenuated in several subgroups stratified by age, sex, mode of delivery, and fetal distress. CONCLUSIONS: Postterm pregnancy was associated with a higher risk of thinness, and a lower risk of overweight/obesity, as well as lower growth parameters in preschool-age children. These findings imply that postterm pregnancy may impede the long-term growth of offspring.

The gut microbiota-bile acid axis links the positive association between chronic insomnia and cardiometabolic diseases.

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.