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Aims/hypothesis The use of oral glucose-lowering drugs, particularly those designed to target the gut ecosystem, is often observed in association with altered gut microbial composition or functional capacity in individuals with type 2 diabetes. The gut microbiota, in turn, plays crucial roles in the modulation of drug efficacy. We aimed to assess the impacts of acarbose and vildagliptin on human gut microbiota and the relationships between pre-treatment gut microbiota and therapeutic responses. Methods This was a randomised, open-labelled, two-arm trial in treatment-naive type 2 diabetes patients conducted in Beijing between December 2016 and December 2017. One hundred participants with overweight/obesity and newly diagnosed type 2 diabetes were recruited from the Pinggu Hospital and randomly assigned to the acarbose (n=50) or vildagliptin (n=50) group using sealed envelopes. The treatment period was 6 months. Blood, faecal samples and visceral fat data from computed tomography images were collected before and after treatments to measure therapeutic outcomes and gut microbiota. Metagenomic datasets from a previous type 2 diabetes cohort receiving acarbose or glipizide for 3 months were downloaded and processed. Statistical analyses were applied to identify the treatment-related changes in clinical variables, gut microbiota and associations. Results Ninety-two participants were analysed. After 6 months of acarbose (n=44) or vildagliptin (n=48) monotherapy, both groups achieved significant reductions in HbA1c (from 60 to 46 mmol/mol [from 7.65% to 6.40%] in the acarbose group and from 59 to 44 mmol/mol [from 7.55% to 6.20%] in the vildagliptin group) and visceral fat areas (all adjusted p values for pre–post comparisons Bacteroidetes species. Three months and 6 months of acarbose-induced changes in microbial composition were highly similar in type 2 diabetes patients from the two independent studies. Vildagliptin treatment significantly enhanced fasting active glucagon-like peptide-1 (GLP-1) levels. Baseline gut microbiota, rather than baseline GLP-1 levels, were strongly associated with GLP-1 response to vildagliptin, and to a lesser extent with GLP-1 response to acarbose. Conclusions/interpretation This study reveals common microbial responses in type 2 diabetes patients treated with two glucose-lowering drugs targeting the gut differently and acceptable performance of baseline gut microbiota in classifying individuals with different GLP-1 responses to vildagliptin. Our findings highlight bidirectional interactions between gut microbiota and glucose-lowering drugs. Trial registration ClinicalTrials.gov NCT02999841 Funding National Key Research and Development Project: 2016YFC1304901. Graphical abstract

Lifelong sex- and age-related trajectories of the human gut microbiota remain largely unexplored. Using metagenomics, we derived the gut microbial composition of 2,338 adults (26–76 years) from a Han Chinese population-based cohort where metabolic health, hormone levels and aspects of their lifestyles were also recorded. In this cohort, and in three independent cohorts distributed across China, Israel and the Netherlands, we observed sex differences in the gut microbial composition and a shared age-related decrease in sex-dependent differences in gut microbiota. Compared to men, the gut microbiota of premenopausal women exhibited higher microbial diversity and higher abundances of multiple species known to have beneficial effects on host metabolism. We also found consistent sex-independent, age-related gut microbial characteristics across all populations, with the presence of members of the oral microbiota being the strongest indicator of older chronological age. Our findings highlight the existence of sex- and age-related trajectories in the human gut microbiota that are shared between populations of different ethnicities and emphasize the pivotal links between sex hormones, gut microbiota and host metabolism. Using metagenomics sequencing, Zhang et al. examined sex- and age-dependent trajectories of the gut microbiota in four cohorts across China, Israel and the Netherlands. The authors found age-related gut microbial trajectories common across all populations, with the abundance of Streptococcus gordonii predicting chronological age.

Human gut microbiome is a promising target for managing type 2 diabetes (T2D). Measures altering gut microbiota like oral intake of probiotics or berberine (BBR), a bacteriostatic agent, merit metabolic homoeostasis. We hence conducted a randomized, double-blind, placebo-controlled trial with newly diagnosed T2D patients from 20 centres in China. Four-hundred-nine eligible participants were enroled, randomly assigned (1:1:1:1) and completed a 12-week treatment of either BBR-alone, probiotics+BBR, probiotics-alone, or placebo, after a one-week run-in of gentamycin pretreatment. The changes in glycated haemoglobin, as the primary outcome, in the probiotics+BBR (least-squares mean [95% CI], −1.04[−1.19, −0.89]%) and BBR-alone group (−0.99[−1.16, −0.83]%) were significantly greater than that in the placebo and probiotics-alone groups (−0.59[−0.75, −0.44]%, −0.53[−0.68, −0.37]%, P, The gut microbiome affects systemic metabolism and is a therapeutic target for type 2 diabetes. Here the authors demonstrate in a randomized controlled trial that effects of berberine, a plant alkaloid known to lower blood glucose, may be explained by the inhibition of Ruminococcus bromii mediated biotransformation of the bile acid deoxycholic acid.

Background COVID-19 (coronavirus disease 2019) has caused a major epidemic worldwide; however, much is yet to be known about the epidemiology and evolution of the virus partly due to the scarcity of full-length SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) genomes reported. One reason is that the challenges underneath sequencing SARS-CoV-2 directly from clinical samples have not been completely tackled, i.e., sequencing samples with low viral load often results in insufficient viral reads for analyses. Methods We applied a novel multiplex PCR amplicon (amplicon)-based and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of SARS-CoV-2 from serials dilutions of a cultured isolate, and eight clinical samples covering a range of sample types and viral loads. We also examined and compared the sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. Results We demonstrated that both amplicon and capture methods efficiently enriched SARS-CoV-2 content from clinical samples, while the enrichment efficiency of amplicon outran that of capture in more challenging samples. We found that capture was not as accurate as meta and amplicon in identifying between-sample variations, whereas amplicon method was not as accurate as the other two in investigating within-sample variations, suggesting amplicon sequencing was not suitable for studying virus-host interactions and viral transmission that heavily rely on intra-host dynamics. We illustrated that meta uncovered rich genetic information in the clinical samples besides SARS-CoV-2, providing references for clinical diagnostics and therapeutics. Taken all factors above and cost-effectiveness into consideration, we proposed guidance for how to choose sequencing strategy for SARS-CoV-2 under different situations. Conclusions This is, to the best of our knowledge, the first work systematically investigating inter- and intra-individual variations of SARS-CoV-2 using amplicon- and capture-based whole-genome sequencing, as well as the first comparative study among multiple approaches. Our work offers practical solutions for genome sequencing and analyses of SARS-CoV-2 and other emerging viruses.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of Coronavirus disease 2019 (COVID-19). However, the microbial composition of the respiratory tract and other infected tissues as well as their possible pathogenic contributions to varying degrees of disease severity in COVID-19 patients remain unclear. Between 27 January and 26 February 2020, serial clinical specimens (sputum, nasal and throat swab, anal swab and feces) were collected from a cohort of hospitalized COVID-19 patients, including 8 mildly and 15 severely ill patients in Guangdong province, China. Total RNA was extracted and ultra-deep metatranscriptomic sequencing was performed in combination with laboratory diagnostic assays. We identified distinct signatures of microbial dysbiosis among severely ill COVID-19 patients on broad spectrum antimicrobial therapy. Co-detection of other human respiratory viruses (including human alphaherpesvirus 1, rhinovirus B, and human orthopneumovirus) was demonstrated in 30.8% (4/13) of the severely ill patients, but not in any of the mildly affected patients. Notably, the predominant respiratory microbial taxa of severely ill patients were Burkholderia cepacia complex (BCC), Staphylococcus epidermidis, or Mycoplasma spp. (including M. hominis and M. orale). The presence of the former two bacterial taxa was also confirmed by clinical cultures of respiratory specimens (expectorated sputum or nasal secretions) in 23.1% (3/13) of the severe cases. Finally, a time-dependent, secondary infection of B. cenocepacia with expressions of multiple virulence genes was demonstrated in one severely ill patient, which might accelerate his disease deterioration and death occurring one month after ICU admission. Our findings point to SARS-CoV-2-related microbial dysbiosis and various antibiotic-resistant respiratory microbes/pathogens in hospitalized COVID-19 patients in relation to disease severity. Detection and tracking strategies are needed to prevent the spread of antimicrobial resistance, improve the treatment regimen and clinical outcomes of hospitalized, severely ill COVID-19 patients.

BJT2D study was designed as an exploratory, randomized, controlled, open-labeled, interventional trial. One hundred newly diagnosed overweight/obese T2D patients were recruited for the study and were randomly assigned to the acarbose or vildagliptin group in a 1:1 ratio. During the 24-week intervention, lifestyle guidance was provided by the investigators at baseline, 12-week, and 24-week (endpoint) visits to assess medication adherence. And fecal samples were selected and sequenced at baseline and 24-week.

High-quality and comprehensive reference gene catalogs are essential for metagenomic research. The rather low diversity of samples used to construct existing catalogs of mouse gut metagenomes limits the size and numbers of identified genes in existing catalogs. We therefore established an expanded gene catalog of genes in the mouse gut metagenomes (EMGC) containing >5.8 million genes by integrating 88 newly sequenced samples, 86 mouse-gut-related bacterial genomes and 3 existing gene catalogs. EMGC increases the number on non-redundant genes by more than one million genes compared to the so far most extensive catalog. More than 50% of the genes in EMGC were taxonomically assigned and 30% were functionally annotated. 902 Metagenomic species (MGS) assigned to 122 taxa are identified based on the EMGC. The EMGC-based analysis of samples from groups of mice originating from different animal providers, housing laboratories and genetic strains substantiated that diet is a major contributor to differences in composition and functional potential of the gut microbiota irrespective of differences in environment and genetic background. We envisage that EMGC will serve as an efficient and resource-saving reference dataset for future metagenomic studies in mice.

Background Shotgun metagenomic sequencing has improved our understanding of the human gut microbiota. Various DNA extraction methods have been compared to find protocols that robustly and most accurately reflect the original microbial community structures. However, these recommendations can be further refined by considering the time and cost demands in dealing with samples from very large human cohorts. Additionally, fungal DNA extraction performance has so far been little investigated. Results We compared 6 DNA extraction protocols, MagPure Fast Stool DNA KF Kit B, Macherey Nagel™ NucleoSpin™®Soil kit, Zymo Research Quick-DNA™ Fecal/Soil Microbe kit, MOBIO DNeasy PowerSoil kit, the manual non-commercial protocol MetaHIT, and the recently published protocol Q using 1 microbial mock community (MMC) (containing 8 bacterial and 2 fungal strains) and fecal samples. All samples were manually extracted and subjected to shotgun metagenomics sequencing. Extracting DNA revealed high reproducibility within all 6 protocols, but microbial extraction efficiencies varied. The MMC results demonstrated that bead size was a determining factor for fungal and bacterial DNA yields. In human fecal samples, the MagPure bacterial extraction performed as well as the standardized protocol Q but was faster and more cost-effective. Extraction using the PowerSoil protocol resulted in a significantly higher ratio of gram-negative to gram-positive bacteria than other protocols, which might contribute to reported gut microbial differences between healthy adults. Conclusions We emphasize the importance of bead size selection for bacterial and fungal DNA extraction. More importantly, the performance of the novel protocol MP matched that of the recommended standardized protocol Q but consumed less time, was more cost-effective, and is recommended for further large-scale human gut metagenomic studies.

COVID-19 has caused a major epidemic worldwide, however, much is yet to be known about the epidemiology and evolution of the virus. One reason is that the challenges underneath sequencing HCoV-19 directly from clinical samples have not been completely tackled. Here we illustrate the application of amplicon and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of HCoV-19 from clinical samples covering a range of sample types and viral load. We also examine and compare the bias, sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. This is, to date, the first work systematically implements amplicon and capture approaches in sequencing HCoV-19, as well as the first comparative study across methods. Our work offers practical solutions for genome sequencing and analyses of HCoV-19 and other emerging viruses.

Adequate calorie restriction (CR) as a healthy lifestyle is recommended not only for people with metabolic disorders but also for healthy adults. Previous studies have mainly focused on the beneficial metabolic effects of CR on obese subjects, while its effects on non-obese subjects are still scarce. Here, we conducted a three-week non-controlled CR intervention in 41 subjects, with approximately 40% fewer calories than the recommended daily energy intake. We measured BMI, and applied targeted metabolic profiling on fasting blood samples and shotgun metagenomic sequencing on fecal samples, before and after intervention. Subjects were stratified into two enterotypes according to their baseline microbial composition, including 28 enterotype Bacteroides (ETB) subjects and 13 enterotype Prevotella (ETP) subjects. CR decreased BMI in most subjects, and ETP subjects exhibited a significantly higher BMI loss ratio than the ETB subjects. Additionally, CR induced limited changes in gut microbial composition but substantial microbial-independent changes in blood AAs, including a significant increase in 3-methylhistidine, a biomarker of the skeletal muscle protein turnover. Finally, baseline abundances of seven microbial species, rather than baseline AA levels, could well predict CR-induced BMI loss. This non-controlled intervention study revealed associations between baseline gut microbiota and CR-induced BMI loss and provided evidence to accelerate the application of microbiome stratification in future personalized nutrition intervention.

Antidiabetic medication may modulate the gut microbiota and thereby alter plasma and faecal bile acid (BA) composition, which may improve metabolic health. Here we show that treatment with Acarbose, but not Glipizide, increases the ratio between primary BAs and secondary BAs and plasma levels of unconjugated BAs in treatment-naive type 2 diabetes (T2D) patients, which may beneficially affect metabolism. Acarbose increases the relative abundances of Lactobacillus and Bifidobacterium in the gut microbiota and depletes Bacteroides, thereby changing the relative abundance of microbial genes involved in BA metabolism. Treatment outcomes of Acarbose are dependent on gut microbiota compositions prior to treatment. Compared to patients with a gut microbiota dominated by Prevotella, those with a high abundance of Bacteroides exhibit more changes in plasma BAs and greater improvement in metabolic parameters after Acarbose treatment. Our work highlights the potential for stratification of T2D patients based on their gut microbiota prior to treatment., The authors examine the effects of antidiabetic medication on the gut microbiome and bile acid composition and show that these data can be used to stratify treatment regimens for type 2 diabetes.

BackgroundThe gut microbiota plays important roles in modulating host metabolism. Previous studies have demonstrated differences in the gut microbiome of T2D and prediabetic individuals compared to healthy individuals, with distinct disease-related microbial profiles being reported in groups of different age and ethnicity. However, confounding factors such as anti-diabetic medication hamper identification of the gut microbial changes in disease development.MethodWe used a combination of in-depth metagenomics and metaproteomics analyses of faecal samples from treatment-naïve type 2 diabetic (TN-T2D, n=77), pre-diabetic (Pre-DM, n=80), and normal glucose tolerant (NGT, n=97) individuals to investigate compositional and functional changes of the gut microbiota and the faecal content of microbial and host proteins in Pre-DM and treatment-naïve T2D individuals to elucidate possible host-microbial interplays characterising different disease stages.FindingsWe observed distinct differences characterizing the gut microbiota of these three groups and validated several key features in an independent TN-T2D cohort. We also demonstrated that the content of several human antimicrobial peptides and pancreatic enzymes differed in faecal samples between three groups, such as reduced faecal level of antimicrobial peptides and pancreatic enzymes in TN-T2D.InterpretationOur findings suggest a complex, disease stage-dependent interplay between the gut microbiota and the host and emphasize the value of metaproteomics to gain further insight into interplays between the gut microbiota and the host.FundingNational Key Research and Development Program of China, No. 2017YFC0909703, Shenzhen Municipal Government of China, No. JCYJ20170817145809215, and National Natural Science Foundation of China, No. 31601073.

Calorie restriction (CR), which has the potential effect to weight loss and blood amino acids, has been demonstrated to associate with gut microbiota in human, especially in obese individuals. However, studies for simultaneously evaluating enterotype-dependent impacts of CR on the gut microbiota and blood amino acids in nonobese individuals are still limited.Here, 41 nonobese individuals received a 3-week CR diet with approximately 50% fewer calories than normal diet. We measured their BMI and blood amino acid concentration, along with the gut microbiota before and after the intervention. In this trial, 28 Enterotype Bacteroides (ETB) subjects and 13 Enterotype Prevotella (ETP) subjects were identified before the intervention. Short-term CR dietary intervention decreased the body mass index (BMI) in most subjects but varied in subjects with different enterotypes. ETP subjects exhibited significantly higher BMI loss ratio than the ETB subjects. CR additionally induced substantial enterotype-independent changes in blood amino acids, but only minor changes in gut microbial composition.We further built a prediction model based on baseline relative abundances of 7 gut microbial species showing high performance in predicting CR-associated BMI loss ratio. Among them, the relative abundance of ETB-enriched Clostridium bolteae and C. ramosum were negatively correlated with BMI loss ratio while the relative abundance of Dorea longicatena which was slightly enriched in ETP subjects, was positively correlated with BMI loss ratio.Together, our work points out that the individual variation of BMI loss after CR could be partially correlated with different microbial composition and highlights the potential application for microbiome stratification in personalized nutrition intervention.

Background The gut microbiota evolves from birth and is in early life influenced by events such as birth mode, type of infant feeding, and maternal and infant antibiotics use. However, we still have a gap in our understanding of gut microbiota development in older children, and to what extent early events and pre-school lifestyle modulate the composition of the gut microbiota, and how this impinges on whole body metabolic regulation in school-age children. Results Taking advantage of the KOALA Birth Cohort Study, a long-term prospective birth cohort in the Netherlands with extensive collection of high-quality host metadata, we applied shotgun metagenomics sequencing and systematically investigated the gut microbiota of children at 6–9 years of age. We demonstrated an overall adult-like gut microbiota in the 281 Dutch school-age children and identified 3 enterotypes dominated by the genera Bacteroides, Prevotella, and Bifidobacterium, respectively. Importantly, we found that breastfeeding duration in early life and pre-school dietary lifestyle correlated with the composition and functional competences of the gut microbiota in the children at school age. The correlations between pre-school dietary lifestyle and metabolic phenotypes exhibited a striking enterotype dependency. Thus, an inverse correlation between high dietary fiber consumption and low plasma insulin levels was only observed in individuals with the Bacteroides and Prevotella enterotypes, but not in Bifidobacterium enterotype individuals in whom the gut microbiota displayed overall lower microbial gene richness, alpha-diversity, functional potential for complex carbohydrate fermentation, and butyrate and succinate production. High total fat consumption and elevated plasma free fatty acid levels in the Bifidobacterium enterotype are associated with the co-occurrence of Streptococcus. Conclusions Our work highlights the persistent effects of breastfeeding duration and pre-school dietary lifestyle in affecting the gut microbiota in school-age children and reveals distinct compositional and functional potential in children according to enterotypes. The findings underscore enterotype-specific links between the host metabolic phenotypes and dietary patterns, emphasizing the importance of microbiome-based stratification when investigating metabolic responses to diets. Future diet intervention studies are clearly warranted to examine gut microbe-diet-host relationships to promote knowledge-based recommendations in relation to improving metabolic health in children. Electronic supplementary material The online version of this article (10.1186/s40168-018-0608-z) contains supplementary material, which is available to authorized users.

Figure S2. Gene count distribution in Dutch children. Black indicates all individuals, n = 281; red indicates lean children (BMI z-score

Figure S1. Compositional and functional comparison between Dutch children and adults. Relative abundance of major phyla in Dutch children (a) and adults (b). (c) Relative abundance of COG (clusters of orthologous groups) categories across each sample in Dutch children and adults. (PDF 298 kb)

Figure S4. Comparison of gut microbial functional potentials between enterotypes. (a) Differentially enrichment of KEGG modules between enterotypes. Dashed lines indicate a reporter score of 1.96, corresponding to 95% confidence in a normal distribution. (b) Heatmap showing that the relative abundance profiles of 8 selected KOs involved in key functions of metabolic pathways for carbohydrate metabolism (K00845, K01051 and K00873) and amino acid biosynthesis (K01738, K00928, K00058, K00651and K00765) distinguishes E3 from E1 and E2. (PDF 358 kb)

Figure S6. Correlations between continuous phenotypic parameters. (a) Spearman’s rank correlations between continuous phenotypic parameters in the entire cohort (n = 281). (b) Spearman’s correlations between continuous phenotypic parameters in E1 (n = 143). (c) Spearman’s rank correlations between continuous phenotypic parameters in E2 (n = 74). (d) Spearman’s rank correlations between continuous phenotypic parameters in E3 (n = 64). The “*” indicates significant correlation with adjusted P

Figure S8. Evaluation of enterotying protocols for Dutch children. (a-c) Evaluation of optimal cluster number by using the DMM protocol (a), the PAM-JSD protocol (b) and the PAM-BC protocol (c). The optimal number of clusters was calculated using Laplace approximation for the DMM protocol (a) and the Calinskiâ Harabasz index for the PAM-based protocols (b-c). Cluster stability using the DMM (d), the PAM-JSD (e) and the PAM-BC protocols (f). The X axis indicates resampling number and the Y axis indicates the consistency of resampling relative to the original result based on 281 samples. (PDF 221 kb)

Figure S5. Correlations between continuous phenotypic parameters and species profile in the entire cohort. (a) Spearman’s rank correlations between early events, pre-school lifestyle and species profile (n = 281). (b) Spearman’s rank correlations between blood parameters and species profiles (n = 281). P values were adjusted for each parameter. The “*” indicates significant correlation with adjusted P

Figure S7. Correlations between Streptococcus species profile and selected phenotypic parameters in enterotypes. Heatmap showing the Spearman’s rank correlations between Streptococcus species and selected phenotypic parameters including free fatty acids levels and the intake of total carbohydrate, total fat, dietary fiber, and plant-based protein. P values were adjusted for each parameter. The “*” indicates significant correlation with adjusted P 0.05. FFA, free fatty acids. (PDF 197 kb)

Figure S3. Comparison of gut microbial compositional and functional structure between enterotypes. (a-c) Comparison of gene count, gene-based Shannon diversity and reads mapping ratio to the taxonomic annotated genes between enterotypes. (d-f) Comparison of gene count, KO-based Shannon diversity and reads mapping ratio to the KO annotated genes between enterotypes. Dunn’s post hoc test, *, P

The gut microbiota has been linked to cardiovascular diseases. However, the composition and functional capacity of the gut microbiome in relation to cardiovascular diseases have not been systematically examined. Here, we perform a metagenome-wide association study on stools from 218 individuals with atherosclerotic cardiovascular disease (ACVD) and 187 healthy controls. The ACVD gut microbiome deviates from the healthy status by increased abundance of Enterobacteriaceae and Streptococcus spp. and, functionally, in the potential for metabolism or transport of several molecules important for cardiovascular health. Although drug treatment represents a confounding factor, ACVD status, and not current drug use, is the major distinguishing feature in this cohort. We identify common themes by comparison with gut microbiome data associated with other cardiometabolic diseases (obesity and type 2 diabetes), with liver cirrhosis, and rheumatoid arthritis. Our data represent a comprehensive resource for further investigations on the role of the gut microbiome in promoting or preventing ACVD as well as other related diseases., The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease.

The relationship between dyslipidemia and type 2 diabetes mellitus (T2D) has been extensively reported, but the global lipid profiles, especially in the East Asia population, associated with the development of T2D remain to be characterized. Liquid chromatography coupled to tandem mass spectrometry was applied to detect the global lipidome in the fasting plasma of 293 Chinese individuals, including 114 T2D patients, 81 prediabetic subjects, and 98 individuals with normal glucose tolerance (NGT). Both qualitative and quantitative analyses revealed a gradual change in plasma lipid features with T2D patients exhibiting characteristics close to those of prediabetic individuals, whereas they differed significantly from individuals with NGT. We constructed and validated a random forest classifier with 28 lipidomic features that effectively discriminated T2D from NGT or prediabetes. Most of the selected features significantly correlated with diabetic clinical indices. Hydroxybutyrylcarnitine was positively correlated with fasting plasma glucose, 2-hour postprandial glucose, glycated hemoglobin, and insulin resistance index (HOMA-IR). Lysophosphatidylcholines such as lysophosphatidylcholine (18:0), lysophosphatidylcholine (18:1), and lysophosphatidylcholine (18:2) were all negatively correlated with HOMA-IR. The altered plasma lipidome in Chinese T2D and prediabetic subjects suggests that lipid features may play a role in the pathogenesis of T2D and that such features may provide a basis for evaluating risk and monitoring disease development.