ABSTRACT
Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.
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BACKGROUND: Vitamin A is essential for physiological processes like vision and immunity. Vitamin A's effect on gut microbiome composition, which affects absorption and metabolism of other vitamins, is still unknown. Here we examined the relationship between gut metagenome composition and six vitamin A-related metabolites (two retinoid: -retinol, 4 oxoretinoic acid (oxoRA) and four carotenoid metabolites, including beta-cryptoxanthin and three carotene diols). METHODS: We included 1053 individuals from the TwinsUK cohort with vitamin A-related metabolites measured in serum and faeces, diet history, and gut microbiome composition assessed by shotgun metagenome sequencing. Results were replicated in 327 women from the ZOE PREDICT-1 study. RESULTS: Five vitamin A-related serum metabolites were positively correlated with microbiome alpha diversity (r = 0.15 to r = 0.20, p < 4 × 10-6). Carotenoid compounds were positively correlated with the short-chain fatty-acid-producing bacteria Faecalibacterium prausnitzii and Coprococcus eutactus. Retinol was not associated with any microbial species. We found that gut microbiome composition could predict circulating levels of carotenoids and oxoretinoic acid with AUCs ranging from 0.66 to 0.74 using random forest models, but not retinol (AUC = 0.52). The healthy eating index (HEI) was strongly associated with gut microbiome diversity and with all carotenoid compounds, but not retinoids. We investigated the mediating role of carotenoid compounds on the effect of a healthy diet (HEI) on gut microbiome diversity, finding that carotenoids significantly mediated between 18 and 25% of the effect of HEI on gut microbiome alpha diversity. CONCLUSIONS: Our results show strong links between circulating carotene compounds and gut microbiome composition and potential links to a healthy diet pattern.
Subject(s)
Carotenoids , Gastrointestinal Microbiome , Retinoids , Vitamin A , Humans , Gastrointestinal Microbiome/drug effects , Gastrointestinal Microbiome/physiology , Vitamin A/blood , Carotenoids/blood , Carotenoids/metabolism , Female , Middle Aged , Male , Retinoids/metabolism , Aged , Diet , Feces/microbiology , AdultABSTRACT
Diet impacts human health, influencing body adiposity and the risk of developing cardiometabolic diseases. The gut microbiome is a key player in the diet-health axis, but while its bacterial fraction is widely studied, the role of micro-eukaryotes, including Blastocystis, is underexplored. We performed a global-scale analysis on 56,989 metagenomes and showed that human Blastocystis exhibits distinct prevalence patterns linked to geography, lifestyle, and dietary habits. Blastocystis presence defined a specific bacterial signature and was positively associated with more favorable cardiometabolic profiles and negatively with obesity (p < 1e-16) and disorders linked to altered gut ecology (p < 1e-8). In a diet intervention study involving 1,124 individuals, improvements in dietary quality were linked to weight loss and increases in Blastocystis prevalence (p = 0.003) and abundance (p < 1e-7). Our findings suggest a potentially beneficial role for Blastocystis, which may help explain personalized host responses to diet and downstream disease etiopathogenesis.
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Leveraging whole genome sequencing data of 1751 individuals from the UK and 2587 Qatari subjects, we suggest here an association of rare variants mapping to the sour taste-associated gene KCNJ2 with reduced low-density lipoprotein cholesterol (LDL-C, P = 2.10 × 10-12) and with a 22% decreased dietary trans-fat intake. This study identifies a novel candidate rare locus for LDL-C, adding insights into the genetic architecture of a complex trait implicated in cardiovascular disease.
ABSTRACT
The objective assessment of habitual (poly)phenol-rich diets in nutritional epidemiology studies remains challenging. This study developed and evaluated the metabolic signature of a (poly)phenol-rich dietary score (PPS) using a targeted metabolomics method comprising 105 representative (poly)phenol metabolites, analyzed in 24 h of urine samples collected from healthy volunteers. The metabolites that were significantly associated with PPS after adjusting for energy intake were selected to establish a metabolic signature using a combination of linear regression followed by ridge regression to estimate penalized weights for each metabolite. A metabolic signature comprising 51 metabolites was significantly associated with adherence to PPS in 24 h urine samples, as well as with (poly)phenol intake estimated from food frequency questionnaires and diaries. Internal and external data sets were used for validation, and plasma, spot urine, and 24 h urine samples were compared. The metabolic signature proposed here has the potential to accurately reflect adherence to (poly)phenol-rich diets, and may be used as an objective tool for the assessment of (poly)phenol intake.
Subject(s)
Diet , Polyphenols , Humans , Adult , Female , Male , Middle Aged , Polyphenols/metabolism , Polyphenols/urine , Polyphenols/administration & dosage , Young Adult , Metabolomics , Dietary PatternsABSTRACT
Large variability exists in people's responses to foods. However, the efficacy of personalized dietary advice for health remains understudied. We compared a personalized dietary program (PDP) versus general advice (control) on cardiometabolic health using a randomized clinical trial. The PDP used food characteristics, individual postprandial glucose and triglyceride (TG) responses to foods, microbiomes and health history, to produce personalized food scores in an 18-week app-based program. The control group received standard care dietary advice (US Department of Agriculture Guidelines for Americans, 2020-2025) using online resources, check-ins, video lessons and a leaflet. Primary outcomes were serum low-density lipoprotein cholesterol and TG concentrations at baseline and at 18 weeks. Participants (n = 347), aged 41-70 years and generally representative of the average US population, were randomized to the PDP (n = 177) or control (n = 170). Intention-to-treat analysis (n = 347) between groups showed significant reduction in TGs (mean difference = -0.13 mmol l-1; log-transformed 95% confidence interval = -0.07 to -0.01, P = 0.016). Changes in low-density lipoprotein cholesterol were not significant. There were improvements in secondary outcomes, including body weight, waist circumference, HbA1c, diet quality and microbiome (beta-diversity) (P < 0.05), particularly in highly adherent PDP participants. However, blood pressure, insulin, glucose, C-peptide, apolipoprotein A1 and B, and postprandial TGs did not differ between groups. No serious intervention-related adverse events were reported. Following a personalized diet led to some improvements in cardiometabolic health compared to standard dietary advice. ClinicalTrials.gov registration: NCT05273268 .
Subject(s)
Precision Medicine , Triglycerides , Humans , Female , Male , Middle Aged , Aged , Adult , Triglycerides/blood , Precision Medicine/methods , Blood Glucose/metabolism , Cholesterol, LDL/blood , Cardiovascular Diseases/prevention & control , Cardiovascular Diseases/diet therapy , DietABSTRACT
BACKGROUND: Type 2 diabetes (T2D) susceptibility is influenced by genetic and environmental factors. Previous findings suggest DNA methylation as a potential mechanism in T2D pathogenesis and progression. METHODS: We profiled DNA methylation in 248 blood samples from participants of European ancestry from 7 twin cohorts using a methylation sequencing platform targeting regulatory genomic regions encompassing 2,048,698 CpG sites. FINDINGS: We find and replicate 3 previously unreported T2D differentially methylated CpG positions (T2D-DMPs) at FDR 5% in RGL3, NGB and OTX2, and 20 signals at FDR 25%, of which 14 replicated. Integrating genetic variation and T2D-discordant monozygotic twin analyses, we identify both genetic-based and genetic-independent T2D-DMPs. The signals annotate to genes with established GWAS and EWAS links to T2D and its complications, including blood pressure (RGL3) and eye disease (OTX2). INTERPRETATION: The results help to improve our understanding of T2D disease pathogenesis and progression and may provide biomarkers for its complications. FUNDING: Funding acknowledgements for each cohort can be found in the Supplementary Note.
Subject(s)
CpG Islands , DNA Methylation , Diabetes Mellitus, Type 2 , Humans , Diabetes Mellitus, Type 2/genetics , Female , Male , Genome-Wide Association Study , Genetic Predisposition to Disease , Middle Aged , Epigenesis, Genetic , Otx Transcription Factors/genetics , Otx Transcription Factors/metabolism , Diabetes Complications/genetics , Gene Expression ProfilingABSTRACT
BACKGROUND: Some individuals experience prolonged illness after acute coronavirus disease 2019 (COVID-19). We assessed whether pre-infection symptoms affected post-acute COVID illness duration. METHODS: Survival analysis was performed in adults (n=23 452) with community-managed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8â weeks before to 12â weeks after COVID-19 onset, conditioned on presence versus absence of baseline symptoms (4-8â weeks before COVID-19). A case-control study was performed in 1350 individuals with long illness (≥8â weeks, including 906 individuals (67.1%) with illness ≥12â weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4â weeks). Baseline symptoms were compared between the two groups, and against post-COVID symptoms. RESULTS: Individuals reporting baseline symptoms had longer COVID-related symptom duration (median 15â days versus 10 days for individuals without baseline symptoms) with baseline fatigue nearly doubling duration. Two-thirds (910 (67.4%) of 1350) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, versus 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms doubled the odds ratio for long illness (2.14, 95% CI 1.78-2.57). Prior comorbidities were more common in individuals with long versus short illness. In individuals with long illness, baseline symptomatic (versus asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms, and symptom burden, correlated strongly. CONCLUSIONS: Individuals experiencing symptoms before COVID-19 had longer illness duration and increased odds of long illness. However, many individuals with long illness were well before SARS-CoV-2 infection.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , COVID-19/epidemiology , COVID-19/complications , Female , Male , Case-Control Studies , Middle Aged , Prospective Studies , Adult , Aged , Time Factors , Post-Acute COVID-19 Syndrome , Survival Analysis , Fatigue/epidemiologyABSTRACT
Chronic kidney disease (CKD) is a major public health burden, with dietary acid load (DAL) and gut microbiota playing crucial roles. As DAL can affect the host metabolome, potentially via the gut microbiota, we cross-sectionally investigated the interplay between DAL, host metabolome, gut microbiota, and early-stage CKD (TwinsUK, n = 1,453). DAL was positively associated with CKD stage G1-G2 (Beta (95% confidence interval) = 0.34 (0.007; 0.7), p = 0.046). After adjusting for covariates and multiple testing, we identified 15 serum, 14 urine, 8 stool, and 7 saliva metabolites, primarily lipids and amino acids, associated with both DAL and CKD progression. Of these, 8 serum, 2 urine, and one stool metabolites were found to mediate the DAL-CKD association. Furthermore, the stool metabolite 5-methylhexanoate (i7:0) correlated with 26 gut microbial species. Our findings emphasize the gut microbiota's therapeutic potential in countering DAL's impact on CKD through the host metabolome. Interventional and longitudinal studies are needed to establish causality.
ABSTRACT
Multiple clinical trials targeting the gut microbiome are being conducted to optimize treatment outcomes for immune checkpoint blockade (ICB). To improve the success of these interventions, understanding gut microbiome changes during ICB is urgently needed. Here through longitudinal microbiome profiling of 175 patients treated with ICB for advanced melanoma, we show that several microbial species-level genome bins (SGBs) and pathways exhibit distinct patterns from baseline in patients achieving progression-free survival (PFS) of 12 months or longer (PFS ≥12) versus patients with PFS shorter than 12 months (PFS <12). Out of 99 SGBs that could discriminate between these two groups, 20 were differentially abundant only at baseline, while 42 were differentially abundant only after treatment initiation. We identify five and four SGBs that had consistently higher abundances in patients with PFS ≥12 and <12 months, respectively. Constructing a log ratio of these SGBs, we find an association with overall survival. Finally, we find different microbial dynamics in different clinical contexts including the type of ICB regimen, development of immune-related adverse events and concomitant medication use. Insights into the longitudinal dynamics of the gut microbiome in association with host factors and treatment regimens will be critical for guiding rational microbiome-targeted therapies aimed at enhancing ICB efficacy.
Subject(s)
Gastrointestinal Microbiome , Melanoma , Microbiota , Humans , Gastrointestinal Microbiome/genetics , Melanoma/drug therapy , Immune Checkpoint Inhibitors/therapeutic use , CognitionABSTRACT
BACKGROUND: Snacking is a common diet behaviour which accounts for a large proportion of daily energy intake, making it a key determinant of diet quality. However, the relationship between snacking frequency, quality and timing with cardiometabolic health remains unclear. DESIGN: Demography, diet, health (fasting and postprandial cardiometabolic blood and anthropometrics markers) and stool metagenomics data were assessed in the UK PREDICT 1 cohort (N = 1002) (NCT03479866). Snacks (foods or drinks consumed between main meals) were self-reported (weighed records) across 2-4 days. Average snacking frequency and quality [snack diet index (SDI)] were determined (N = 854 after exclusions). Associations between snacking frequency, quality and timing with cardiometabolic blood and anthropometric markers were assessed using regression models (adjusted for age, sex, BMI, education, physical activity level and main meal quality). RESULTS: Participants were aged (mean, SD) 46.1 ± 11.9 years, had a mean BMI of 25.6 ± 4.88 kg/m2 and were predominantly female (73%). 95% of participants were snackers (≥ 1 snack/day; n = 813); mean daily snack intake was 2.28 snacks/day (24 ± 16% of daily calories; 203 ± 170 kcal); and 44% of participants were discordant for meal and snack quality. In snackers, overall snacking frequency and quantity of snack energy were not associated with cardiometabolic risk markers. However, lower snack quality (SDI range 1-11) was associated with higher blood markers, including elevated fasting triglycerides (TG (mmol/L) ß; - 0.02, P = 0.02), postprandial TGs (6hiAUC (mmol/L.s); ß; - 400, P = 0.01), fasting insulin (mIU/L) (ß; - 0.15, P = 0.04), insulin resistance (HOMA-IR; ß; - 0.04, P = 0.04) and hunger (scale 0-100) (ß; - 0.52, P = 0.02) (P values non-significant after multiple testing adjustments). Late-evening snacking (≥ 9 pm; 31%) was associated with lower blood markers (HbA1c; 5.54 ± 0.42% vs 5.46 ± 0.28%, glucose 2hiAUC; 8212 ± 5559 vs 7321 ± 4928 mmol/L.s, P = 0.01 and TG 6hiAUC; 11,638 ± 8166 vs 9781 ± 6997 mmol/L.s, P = 0.01) compared to all other snacking times (HbA1c remained significant after multiple testing). CONCLUSION: Snack quality and timing of consumption are simple diet features which may be targeted to improve diet quality, with potential health benefits. CLINICAL TRIAL REGISTRY NUMBER AND WEBSITE: NCT03479866, https://clinicaltrials.gov/ct2/show/NCT03479866?term=NCT03479866&draw=2&rank=1.
Subject(s)
Cardiovascular Diseases , Snacks , Female , Humans , Male , Diet , Energy Intake , Feeding Behavior , Glycated Hemoglobin , Adult , Middle AgedABSTRACT
Glycans are an essential structural component of immunoglobulin G (IgG) that modulate its structure and function. However, regulatory mechanisms behind this complex posttranslational modification are not well known. Previous genome-wide association studies (GWAS) identified 29 genomic regions involved in regulation of IgG glycosylation, but only a few were functionally validated. One of the key functional features of IgG glycosylation is the addition of galactose (galactosylation), a trait which was shown to be associated with ageing. We performed GWAS of IgG galactosylation (N=13,705) and identified 16 significantly associated loci, indicating that IgG galactosylation is regulated by a complex network of genes that extends beyond the galactosyltransferase enzyme that adds galactose to IgG glycans. Gene prioritization identified 37 candidate genes. Using a recently developed CRISPR/dCas9 system we manipulated gene expression of candidate genes in the in vitro IgG expression system. Upregulation of three genes, EEF1A1, MANBA and TNFRSF13B, changed the IgG glycome composition, which confirmed that these three genes are involved in IgG galactosylation in this in vitro expression system.
Subject(s)
Galactose , Genome-Wide Association Study , Gene Regulatory Networks , Immunoglobulin G/genetics , Polysaccharides/metabolismABSTRACT
Background: Continuous glucose monitors (CGMs) provide high-frequency information regarding daily glucose variation and are recognised as effective for improving glycaemic control in individuals living with diabetes. Despite increased use in individuals with non-diabetic blood glucose concentrations (euglycemia), their utility as a health tool in this population remains unclear. Objectives: To characterise variation in time in range (TIR) and glycaemic variability in large populations without diabetes or impaired glucose tolerance; describe associations between CGM-derived glycaemic metrics and metabolic and cardiometabolic health traits; identify key diet and lifestyle factors associated with TIR and glycaemic variability. Design: Glycaemic variability (coefficient of variation) and time spent in both the ADA secondary target range (TIRADA; 3.9-7.8 mmol/L) and a more stringent range (TIR3.9-5.6; 3.9-5.6 mmol/L) were calculated during free-living in PREDICT 1, PREDICT 2, and PREDICT 3 euglycaemic community-based volunteer cohorts. Associations between CGM derived glycaemic metrics, markers of cardiometabolic health, diet (food frequency questionnaire and logged diet records), diet-habits, and lifestyle were explored. Results: Data from N=4135 participants (Mean SD; Age: 47 12 y; Sex: 83% Female, BMI: 27 6 kg/m2). Median glycaemic variability was 14.8% (IQR 12.6-17.6%), median TIRADA was 95.8% (IQR 89.6-98.6%) and TIR3.9-5.6 was 75.0% (IQR 64.6-82.8%). Greater TIR3.9-5.6 was associated with lower HbA1c, ASCVD 10y risk and HOMA-IR (all p < 0.05). Lower glycaemic variability was associated with lower % energy derived from carbohydrate (rs: 0.17, p < 0.01), ultra-processed foods (NOVA 4, % EI; rs: 0.12, p = 0.01) and a longer overnight fasting duration (rs: -0.10, p = 0.01). Conclusions: A stringent TIR target provides sensitivity to detect changes in HOMA-IR, ASCVD 10 y risk and HbA1c that were not detected using ADA secondary targets. Associations among TIR, glycaemic variability, dietary intake (e.g. carbohydrate and protein) and habits (e.g. nocturnal fasting duration) highlight potential strategic targets to improve glycaemic metrics derived from continuous glucose monitors.
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The Segatella copri (formerly Prevotella copri) complex (ScC) comprises taxa that are key members of the human gut microbiome. It was previously described to contain four distinct phylogenetic clades. Combining targeted isolation with large-scale metagenomic analysis, we defined 13 distinct Segatella copri-related species, expanding the ScC complex beyond four clades. Complete genome reconstruction of thirteen strains from seven species unveiled the presence of genetically diverse large circular extrachromosomal elements. These elements are consistently present in most ScC species, contributing to intra- and inter-species diversities. The nine species-level clades present in humans display striking differences in prevalence and intra-species genetic makeup across human populations. Based on a meta-analysis, we found reproducible associations between members of ScC and the male sex and positive correlations with lower visceral fat and favorable markers of cardiometabolic health. Our work uncovers genomic diversity within ScC, facilitating a better characterization of the human microbiome.
Subject(s)
Gastrointestinal Microbiome , Microbiota , Humans , Male , Gastrointestinal Microbiome/genetics , Metagenome , Phylogeny , Prevotella , FemaleABSTRACT
Background: Throughout the literature, pain burden has been assessed by asking different questions, often cross-sectionally, different populations of interest. We know little about pain re-occurrence and how to translate knowledge between pain questions within the population of interest. We aimed to estimate the burden of musculoskeletal pain by estimating prevalence, incidence rates, and re-occurrence risk of back, hand, hip, knee, and foot pain using different questions from UK population-based samples and predict the number of affected individuals in the UK in 2030. Methods: We used two UK population-representative studies, with two eight-year-apart follow-ups and two pain questions assessing recent pain episodes and often troubled pain when walking. We estimated prevalence, 8-year incidence rates, and 8-year pain re-occurrence risk for women and men aged 50 years and older and the relation between the two pain questions. Results: Among UK individuals older than 50 years, the prevalence of musculoskeletal pain episode was 20%-50%, and the incidence was 20-40/1,000 person-years, while the prevalence of pain when walking was 10%-25%, and the incidence was 6-12/1,000 person-years. The most prevalent musculoskeletal pain types were back and knee pain; of five women experiencing back or knee pain episodes, three are expected to be often troubled by pain. Hip and foot pain had similar estimates in both questions. Hand pain peaked in women aged 50-65â years. Women had higher prevalence and incidence rates, but men had higher 8-year re-occurrence risk of all types of musculoskeletal pain. Reporting a pain episode was associated with two times higher risk, but often troubled by pain when walking was associated with four to seven times times higher risk of the same pain in 8 years. Women and men with a body mass index (BMI) of ≥27 kg/m2 were twice as likely to experience musculoskeletal pain than those with BMI<27 kg/m2. In 2030, we expect 2-7 million people older than 50 years in the United Kingdom to seek site-specific musculoskeletal pain-focused healthcare. Conclusions: In individuals older than 50 years, the experience of musculoskeletal pain at least doubles the chance of experiencing it again. Women report musculoskeletal pain more often, but men report more persistent pain. Musculoskeletal pain presents a significant burden to public health.
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Prediabetes is a metabolic condition associated with gut microbiome composition, although mechanisms remain elusive. We searched for fecal metabolites, a readout of gut microbiome function, associated with impaired fasting glucose (IFG) in 142 individuals with IFG and 1,105 healthy individuals from the UK Adult Twin Registry (TwinsUK). We used the Cooperative Health Research in the Region of Augsburg (KORA) cohort (318 IFG individuals, 689 healthy individuals) to replicate our findings. We linearly combined eight IFG-positively associated metabolites (1-methylxantine, nicotinate, glucuronate, uridine, cholesterol, serine, caffeine, and protoporphyrin IX) into an IFG-metabolite score, which was significantly associated with higher odds ratios (ORs) for IFG (TwinsUK: OR 3.9 [95% CI 3.02-5.02], P < 0.0001, KORA: OR 1.3 [95% CI 1.16-1.52], P < 0.0001) and incident type 2 diabetes (T2D; TwinsUK: hazard ratio 4 [95% CI 1.97-8], P = 0.0002). Although these are host-produced metabolites, we found that the gut microbiome is strongly associated with their fecal levels (area under the curve >70%). Abundances of Faecalibacillus intestinalis, Dorea formicigenerans, Ruminococcus torques, and Dorea sp. AF24-7LB were positively associated with IFG, and such associations were partially mediated by 1-methylxanthine and nicotinate (variance accounted for mean 14.4% [SD 5.1], P < 0.05). Our results suggest that the gut microbiome is linked to prediabetes not only via the production of microbial metabolites but also by affecting intestinal absorption/excretion of host-produced metabolites and xenobiotics, which are correlated with the risk of IFG. Fecal metabolites enable modeling of another mechanism of gut microbiome effect on prediabetes and T2D onset. ARTICLE HIGHLIGHTS: Prediabetes is a metabolic condition associated with gut microbiome composition, although mechanisms remain elusive. We investigated whether there is a fecal metabolite signature of impaired fasting glucose (IFG) and the possible underlying mechanisms of action. We identified a fecal metabolite signature of IFG associated with prevalent IFG in two independent cohorts and incident type 2 diabetes in a subanalysis. Although the signature consists of metabolites of nonmicrobial origin, it is strongly correlated with gut microbiome composition. Fecal metabolites enable modeling of another mechanism of gut microbiome effect on prediabetes by affecting intestinal absorption or excretion of host compounds and xenobiotics.
Subject(s)
Diabetes Mellitus, Type 2 , Niacin , Prediabetic State , Adult , Humans , Prediabetic State/complications , Diabetes Mellitus, Type 2/complications , Fasting , Glucose , Blood Glucose/metabolismABSTRACT
PURPOSE: In this study, we explore the relationship between social jetlag (SJL), a parameter of circadian misalignment, and gut microbial composition, diet and cardiometabolic health in the ZOE PREDICT 1 cohort (NCT03479866). METHODS: We assessed demographic, diet, cardiometabolic, stool metagenomics and postprandial metabolic measures (n = 1002). We used self-reported habitual sleep (n = 934) to calculate SJL (difference in mid-sleep time point of ≥ 1.5 h on week versus weekend days). We tested group differences (SJL vs no-SJL) in cardiometabolic markers and diet (ANCOVA) adjusting for sex, age, BMI, ethnicity, and socio-economic status. We performed comparisons of gut microbial composition using machine learning and association analyses on the species level genome bins present in at least 20% of the samples. RESULTS: The SJL group (16%, n = 145) had a greater proportion of males (39% vs 25%), shorter sleepers (average sleep < 7 h; 5% vs 3%), and were younger (38.4 ± 11.3y vs 46.8 ± 11.7y) compared to the no-SJL group. SJL was associated with a higher relative abundance of 9 gut bacteria and lower abundance of 8 gut bacteria (q < 0.2 and absolute Cohen's effect size > 0.2), in part mediated by diet. SJL was associated with unfavourable diet quality (less healthful Plant-based Diet Index), higher intakes of potatoes and sugar-sweetened beverages, and lower intakes of fruits, and nuts, and slightly higher markers of inflammation (GlycA and IL-6) compared with no-SJL (P < 0.05 adjusted for covariates); rendered non-significant after multiple testing adjustments. CONCLUSIONS: Novel associations between SJL and a more disadvantageous gut microbiome in a cohort of predominantly adequate sleepers highlight the potential implications of SJL for health.
Subject(s)
Cardiovascular Diseases , Gastrointestinal Microbiome , Humans , Male , Cardiovascular Diseases/complications , Circadian Rhythm , Diet , Jet Lag Syndrome/complications , SleepABSTRACT
Short-chain fatty acids (SCFA) are involved in immune system and inflammatory responses. We comprehensively assessed the host genetic and gut microbial contribution to a panel of eight serum and stool SCFAs in two cohorts (TwinsUK, n = 2507; ZOE PREDICT-1, n = 328), examined their postprandial changes and explored their links with chronic and acute inflammatory responses in healthy individuals and trauma patients. We report low concordance between circulating and fecal SCFAs, significant postprandial changes in most circulating SCFAs, and a heritable genetic component (average h2: serum = 14%(SD = 14%); stool = 12%(SD = 6%)). Furthermore, we find that gut microbiome can accurately predict their fecal levels (AUC>0.71) while presenting weaker associations with serum. Finally, we report different correlation patterns with inflammatory markers depending on the type of inflammatory response (chronic or acute trauma). Our results illustrate the breadth of the physiological relevance of SCFAs on human inflammatory and metabolic responses highlighting the need for a deeper understanding of this important class of molecules.
Subject(s)
Gastrointestinal Microbiome , Humans , Gastrointestinal Microbiome/genetics , Fatty Acids, Volatile/metabolism , Feces , InflammationABSTRACT
BACKGROUND: A dysregulated postprandial metabolic response is a risk factor for chronic diseases, including type 2 diabetes mellitus (T2DM). The plasma protein N-glycome is implicated in both lipid metabolism and T2DM risk. Hence, we first investigate the relationship between the N-glycome and postprandial metabolism and then explore the mediatory role of the plasma N-glycome in the relationship between postprandial lipaemia and T2DM. METHODS: We included 995 individuals from the ZOE-PREDICT 1 study with plasma N-glycans measured by ultra-performance liquid chromatography at fasting and triglyceride, insulin, and glucose levels measured at fasting and following a mixed-meal challenge. Linear mixed models were used to investigate the associations between plasma protein N-glycosylation and metabolic response (fasting, postprandial (Cmax), or change from fasting). A mediation analysis was used to further explore the relationship of the N-glycome in the prediabetes (HbA1c = 39-47 mmol/mol (5.7-6.5%))-postprandial lipaemia association. RESULTS: We identified 36 out of 55 glycans significantly associated with postprandial triglycerides (Cmax ß ranging from -0.28 for low-branched glycans to 0.30 for GP26) after adjusting for covariates and multiple testing (padjusted < 0.05). N-glycome composition explained 12.6% of the variance in postprandial triglycerides not already explained by traditional risk factors. Twenty-seven glycans were also associated with postprandial glucose and 12 with postprandial insulin. Additionally, 3 of the postprandial triglyceride-associated glycans (GP9, GP11, and GP32) also correlate with prediabetes and partially mediate the relationship between prediabetes and postprandial triglycerides. CONCLUSIONS: This study provides a comprehensive overview of the interconnections between plasma protein N-glycosylation and postprandial responses, demonstrating the incremental predictive benefit of N-glycans. We also suggest a considerable proportion of the effect of prediabetes on postprandial triglycerides is mediated by some plasma N-glycans.
Subject(s)
Diabetes Mellitus, Type 2 , Hyperlipidemias , Prediabetic State , Humans , Blood Glucose/metabolism , Triglycerides , Insulin , Polysaccharides , Blood ProteinsABSTRACT
Metabolome reflects the interplay of genome and exposome at molecular level and thus can provide deep insights into the pathogenesis of a complex disease like major depression. To identify metabolites associated with depression we performed a metabolome-wide association analysis in 13,596 participants from five European population-based cohorts characterized for depression, and circulating metabolites using ultra high-performance liquid chromatography/tandem accurate mass spectrometry (UHPLC/MS/MS) based Metabolon platform. We tested 806 metabolites covering a wide range of biochemical processes including those involved in lipid, amino-acid, energy, carbohydrate, xenobiotic and vitamin metabolism for their association with depression. In a conservative model adjusting for life style factors and cardiovascular and antidepressant medication use we identified 8 metabolites, including 6 novel, significantly associated with depression. In individuals with depression, increased levels of retinol (vitamin A), 1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1) (lecithin) and mannitol/sorbitol and lower levels of hippurate, 4-hydroxycoumarin, 2-aminooctanoate (alpha-aminocaprylic acid), 10-undecenoate (11:1n1) (undecylenic acid), 1-linoleoyl-GPA (18:2) (lysophosphatidic acid; LPA 18:2) are observed. These metabolites are either directly food derived or are products of host and gut microbial metabolism of food-derived products. Our Mendelian randomization analysis suggests that low hippurate levels may be in the causal pathway leading towards depression. Our findings highlight putative actionable targets for depression prevention that are easily modifiable through diet interventions.