Association of Dietary Patterns and Type-2 Diabetes Mellitus in Metabolically Homogeneous Subgroups in the KORA FF4 Study

Sex-specific associations of environmental exposures with prevalent diabetes and obesity - Results from the KORA Fit study

Promising evidence suggests a link between environmental factors, particularly air pollution, and diabetes and obesity. However, it is still unclear whether men and women are equally susceptible to environmental exposures. Therefore, we aimed to assess sex-specific long-term effects of environmental exposures on metabolic diseases. We analyzed cross-sectional data from 3,034 participants (53.7% female, aged 53-74 years) from the KORA Fit study (2018/19), a German population-based cohort. Environmental exposures, including annual averages of air pollutants [nitrogen oxides (NO2, NOx), ozone, particulate matter of different diameters (PM10, PMcoarse, PM2.5), PM2.5abs, particle number concentration], air temperature and surrounding greenness, were assessed at participants' residences. We evaluated sex-specific associations of environmental exposures with prevalent diabetes, obesity, body-mass-index (BMI) and waist circumference using logistic or linear regression models with an interaction term for sex, adjusted for age, lifestyle factors and education. Further effect modification, in particular by urbanization, was assessed in sex-stratified analyses. Higher annual averages of air pollution, air temperature and greenness at residence were associated with diabetes prevalence in men (NO2: Odds Ratio (OR) per interquartile range increase in exposure: 1.49 [95% confidence interval (CI): 1.13, 1.95], air temperature: OR: 1.48 [95%-CI: 1.15, 1.90]; greenness: OR: 0.78 [95%-CI: 0.59, 1.01]) but not in women. Conversely, higher levels of air pollution, temperature and lack of greenness were associated with lower obesity prevalence and BMI in women. After including an interaction term for urbanization, only higher greenness was associated with higher BMI in rural women, whereas higher air pollution was associated with higher BMI in urban men. To conclude, we observed sex-specific associations of environmental exposures with metabolic diseases. An additional interaction between environmental exposures and urbanization on obesity suggests a higher susceptibility to air pollution among urban men, and higher susceptibility to greenness among rural women, which needs corroboration in future studies.

Differential association of dietary scores with the risk of type 2 diabetes by metabotype

PURPOSE

We aimed to examine the association between dietary patterns and type 2 diabetes mellitus (T2DM) while considering the potential effect modification by metabolic phenotypes (metabotypes). Additionally, we aimed to explore the association between dietary scores and prediabetes.

METHODS

A total of 1460 participants (11.8% with T2DM) from the cross-sectional population-based KORA FF4 study were included. Participants, classified into three metabotype subgroups, had both their FSAm-NPS dietary index (underpinning the Nutri-Score) and ultra-processed foods (UPF) intake (using NOVA classification) calculated. Glucose tolerance status was assessed via oral glucose tolerance tests (OGTT) in non-diabetic participants and was classified according to the American Diabetes Association criteria. Logistic regression models were used for both the overall and metabotype-stratified analyses of dietary scores' association with T2DM, and multinomial probit models for their association with prediabetes.

RESULTS

Participants who had a diet with a higher FSAm-NPS dietary index (i.e., a lower diet quality) or a greater percentage of UPF consumption showed a positive association with T2DM. Stratified analyses demonstrated a strengthened association between UPF consumption and T2DM specifically in the metabolically most unfavorable metabotype (Odds Ratio, OR 1.92; 95% Confidence Interval, CI 1.35, 2.73). A diet with a higher FSAm-NPS dietary index was also positively associated with prediabetes (OR 1.19; 95% CI 1.04, 1.35).

CONCLUSION

Our study suggests different associations between poorer diet quality and T2DM across individuals exhibiting diverse metabotypes, pointing to the option for stratified dietary interventions in diabetes prevention.

Association of the habitual dietary intake with the fatty liver index and effect modification by metabotypes in the population-based KORA-Fit study

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is an emerging threat for public health with diet being a major risk factor in disease development and progression. However, the effects of habitual food consumption on fatty liver are still inconclusive as well as the proposed role of the individuals' metabolic profiles. Therefore, the aim of our study is to examine the associations between diet and NAFLD with an emphasis on the influence of specific metabotypes in the general population.

METHODS

A total of 689 participants (304 men and 385 women) of the KORA-Fit (S4) survey, a follow-up study of the population-based KORA cohort study running in the Region of Augsburg, Germany, were included in this analysis. Dietary information was derived from repeated 24-h food lists and a food frequency questionnaire. The intake of energy and energy-providing nutrients were calculated using the national food composition database. The presence of fatty liver was quantified by the fatty liver index (FLI), and metabotypes were calculated using K-means clustering. Multivariable linear regression models were used for the analysis of habitual food groups and FLI; for the evaluation of macronutrients, energy substitution models were applied.

RESULTS

A higher consumption of nuts and whole grains, and a better diet quality (according to Alternate Healthy Eating Index and Mediterranean Diet Score) were associated with lower FLI values, while the intake of soft drinks, meat, fish and eggs were associated with a higher FLI. The isocaloric substitution of carbohydrates with polyunsaturated fatty acids was associated with a decreased FLI, while substitution with monounsaturated fatty acids and protein showed increased FLI. Statistically significant interactions with the metabotype were observed for most food groups.

CONCLUSION

The consumption of plant-based food groups, including nuts and whole grains, and diet quality, were associated with lower FLI values, whereas the intake of soft drinks and products of animal origin (meat, fish, eggs) were associated with a higher FLI. The observed statistically significant interactions with the metabotype for most food groups could help to develop targeted prevention strategies on a population-based level if confirmed in independent prospective studies.

Gene-diet interaction analysis using novel weighted food scores discovers the adipocytokine signaling pathway associated with the development of type 2 diabetes

Introduction

The influence of dietary patterns measured using Recommended Food Score (RFS) with foods with high amounts of antioxidant nutrients for Type 2 diabetes (T2D) was analyzed. Our analysis aims to find associations between dietary patterns and T2D and conduct a gene-diet interaction analysis related to T2D.

Methods

Data analyzed in the current study were obtained from the Korean Genome and Epidemiology Study Cohort. The dietary patterns of 46 food items were assessed using a validated food frequency questionnaire. To maximize the predictive power of the RFS, we propose two weighted food scores, namely HisCoM-RFS calculated using the novel Hierarchical Structural Component model (HisCoM) and PLSDA-RFS calculated using Partial Least Squares-Discriminant Analysis (PLS-DA) method.

Results

Both RFS (OR: 1.11; 95% CI: 1.03- 1.20; P = 0.009) and PLSDA-RFS (OR: 1.10; 95% CI: 1.02-1.19, P = 0.011) were positively associated with T2D. Mapping of SNPs (P < 0.05) from the interaction analysis between SNPs and the food scores to genes and pathways yielded some 12 genes (CACNA2D3, RELN, DOCK2, SLIT3, CTNNA2, etc.) and pathways associated with T2D. The strongest association was observed with the adipocytokine signalling pathway, highlighting 32 genes (STAT3, MAPK10, MAPK8, IRS1, AKT1-3, ADIPOR2, etc.) most likely associated with T2D. Finally, the group of the subjects in low, intermediate and high using both the food scores and a polygenic risk score found an association between diet quality groups with issues at high genetic risk of T2D.

Conclusion

A dietary pattern of poor amounts of antioxidant nutrients is associated with the risk of T2D, and diet affects pathway mechanisms involved in developing T2D.

Effects of Short- And Medium-Term Exposures to Lower Air Temperature on 71 Novel Biomarkers of Subclinical Inflammation: Results from the KORA F4 Study

Increasing evidence has revealed that exposure to low temperatures is linked to a higher risk of chronic diseases and death; however, the mechanisms underlying the observed associations are still poorly understood. We performed a cross-sectional analysis with 1115 participants from the population-based KORA F4 study, which was conducted in Augsburg, Germany, from 2006 to 2008. Seventy-one inflammation-related protein biomarkers were analyzed in serum using proximity extension assay technology. We employed generalized additive models to explore short- and medium-term effects of air temperature on biomarkers of subclinical inflammation at cumulative lags of 0-1 days, 2-6 days, 0-13 days, 0-27 days, and 0-55 days. We found that short- and medium-term exposures to lower air temperature were associated with higher levels in 64 biomarkers of subclinical inflammation, such as Protein S100-A12 (EN-RAGE), Interleukin-6 (IL-6), Interleukin-10 (IL-10), C-C motif chemokine 28 (CCL28), and Neurotrophin-3 (NT-3). More pronounced associations between lower air temperature and higher biomarker of subclinical inflammation were observed among older participants, people with cardiovascular disease or prediabetes/diabetes, and people exposed to higher levels of air pollution (PM2.5, NO2, and O3). Our findings provide intriguing insight into how low air temperature may cause adverse health effects by activating inflammatory pathways.

Associations between medium- and long-term exposure to air temperature and epigenetic age acceleration

Climate change poses a serious threat to human health worldwide, while aging populations increase. However, no study has ever investigated the effects of air temperature on epigenetic age acceleration. This study involved 1,725 and 1,877 participants from the population-based KORA F4 (2006-2008) and follow-up FF4 (2013-2014) studies, respectively, conducted in Augsburg, Germany. The difference between epigenetic age and chronological age was referred to as epigenetic age acceleration and reflected by Horvath's epigenetic age acceleration (HorvathAA), Hannum's epigenetic age acceleration (HannumAA), PhenoAge acceleration (PhenoAA), GrimAge acceleration (GrimAA), and Epigenetic Skin and Blood Age acceleration (SkinBloodAA). Daily air temperature was estimated using hybrid spatiotemporal regression-based models. To explore the medium- and long-term effects of air temperature modeled in time and space on epigenetic age acceleration, we applied generalized estimating equations (GEE) with distributed lag non-linear models, and GEE, respectively. We found that high temperature exposure based on the 8-week moving average air temperature (97.5th percentile of temperature compared to median temperature) was associated with increased HorvathAA, HannumAA, GrimAA, and SkinBloodAA: 1.83 (95% CI: 0.29-3.37), 11.71 (95% CI: 8.91-14.50), 2.26 (95% CI: 1.03-3.50), and 5.02 (95% CI: 3.42-6.63) years, respectively. Additionally, we found consistent results with high temperature exposure based on the 4-week moving average air temperature was associated with increased HannumAA, GrimAA, and SkinBloodAA: 9.18 (95% CI: 6.60-11.76), 1.78 (95% CI: 0.66-2.90), and 4.07 (95% CI: 2.56-5.57) years, respectively. For the spatial variation in annual average temperature, a 1 °C increase was associated with an increase in all five measures of epigenetic age acceleration (HorvathAA: 0.41 [95% CI: 0.24-0.57], HannumAA: 2.24 [95% CI: 1.95-2.53], PhenoAA: 0.32 [95% CI: 0.05-0.60], GrimAA: 0.24 [95%: 0.11-0.37], and SkinBloodAA: 1.17 [95% CI: 1.00-1.35] years). In conclusion, our results provide first evidence that medium- and long-term exposures to high air temperature affect increases in epigenetic age acceleration.

Association of dietary intake with body mass index and glycemic profile among newly diagnosed patients with type 2 diabetes mellitus

INTRODUCTION

Dietary intake plays an important role in determining body mass index (BMI) and glycemic profile in patients with type 2 diabetes mellitus (T2DM). Our aim was to describe habitual dietary intake and its associations with BMI and glycemic profile in a cohort of patients with newly diagnosed T2DM in Sri Lanka.

METHODS

A cross-sectional study was carried out among 158 patients with newly diagnosed T2DM in Galle, Sri Lanka. Data on demographic, lifestyle, and family history of diabetes mellitus, and clinical measures were collected. The dietary information was collected using a 24-h dietary recall.

RESULTS

Among the total number of study subjects, only 12.0%, 5.7% and 1.3% met the recommended daily consumption value of protein, fat, and fiber, respectively, whereas 99.4% of subjects had taken carbohydrates that exceeded the recommended consumption. There was a positive association between carbohydrate intake and BMI (0.004, [0.002], p = .048) and carbohydrate intake and glycated hemoglobin (HbA1C ) (0.001, [0.000], p = .049). Fat intake showed positive associations with BMI (0.029, [0.011], p = .006) and HbA1C (0.005, [0.002], p = .050). Protein intake showed a positive association with HbA1C (0.006, [0.003], p = .023). The aforementioned associations were observed after adjusting for demographic, lifestyle, and history of diabetes among the first-degree family members. The carbohydrate intake was positively associated with BMI (0.010, [0.003], p = .003) and HbA1C (0.001, [0.000], p = .050) with further adjustment in nutrient intake (except when used as an independent variable). Furthermore, the fat intake was associated with BMI (0.031, [0.011], p = .004) and HbA1C (0.005 [0.002], p = .050) with additional adjustments.

CONCLUSIONS

The diet of the majority of newly diagnosed T2DM patients in this cohort consisted of a higher carbohydrate intake than the recommended level. However, they did not meet the recommended daily intake of protein, fat, and fiber. Both carbohydrate and fat intake were significantly and positively associated with BMI and HbA1C in patients with newly diagnosed T2DM.

Urolithins: a Comprehensive Update on their Metabolism, Bioactivity, and Associated Gut Microbiota

Urolithins, metabolites produced by the gut microbiota from the polyphenols ellagitannins and ellagic acid, are discovered by the research group in humans almost 20 years ago. Pioneering research suggests urolithins as pleiotropic bioactive contributors to explain the health benefits after consuming ellagitannin-rich sources (pomegranates, walnuts, strawberries, etc.). Here, this study comprehensively updates the knowledge on urolithins, emphasizing the review of the literature published during the last 5 years. To date, 13 urolithins and their corresponding conjugated metabolites (glucuronides, sulfates, etc.) have been described and, depending on the urolithin, detected in different human fluids and tissues (urine, blood, feces, breastmilk, prostate, colon, and breast tissues). There has been a substantial advance in the research on microorganisms involved in urolithin production, along with the compositional and functional characterization of the gut microbiota associated with urolithins metabolism that gives rise to the so-called urolithin metabotypes (UM-A, UM-B, and UM-0), relevant in human health. The design of in vitro studies using physiologically relevant assay conditions (molecular forms and concentrations) is still a pending subject, making some reported urolithin activities questionable. In contrast, remarkable progress has been made in the research on the safety, bioactivity, and associated mechanisms of urolithin A, including the first human interventions.

Evaluation of the metabotype concept after intervention with oral glucose tolerance test and dietary fiber-enriched food: An enable study

BACKGROUND AND AIMS

Evidence suggests that people react differently to the same diet due to inter-individual differences. However, few studies have investigated variation in response to dietary interventions based on individuals' baseline metabolic characteristics. This study aims to examine the differential reaction of metabotype subgroups to an OGTT and a dietary fiber intervention.

METHODS AND RESULTS

We assigned 356 healthy participants of an OGTT sub-study and a 12-week dietary fiber intervention sub-study within the enable cluster to three metabotype subgroups previously identified in the KORA F4 study population. To explore the association between plasma glucose level and metabotype subgroups, we used linear mixed models adjusted for age, sex, and physical activity. Individuals in different metabotype subgroups showed differential responses to OGTT. Compared to the healthy metabotype (metabotype 1), participants in intermediate metabotype (metabotype 2) and unfavorable metabotype (metabotype 3) had significantly higher plasma glucose concentrations at 120 min after glucose bolus (β = 7.881, p = 0.005; β = 32.79, p < 0.001, respectively). Additionally, the linear regression model showed that the Area under the curve (AUC) of plasma glucose concentrations was significantly different across the metabotype subgroups. The associations between metabotype subgroups and metabolic parameters among fiber intervention participants remained insignificant in the multivariate-adjusted linear model. However, the metabotype 3 had the highest mean reduction in insulin, cholesterol parameters (TC, LDLc, and non-HDLc), and systolic and diastolic blood pressure at the end of the intervention period.

CONCLUSION

This study supports the use of the metabotype concept to identify metabolically similar subgroups and to develop targeted dietary interventions at the metabotype subgroup level for the primary prevention of diet-related diseases.

Optimized Metabotype Definition Based on a Limited Number of Standard Clinical Parameters in the Population-Based KORA Study

The aim of metabotyping is to categorize individuals into metabolically similar groups. Earlier studies that explored metabotyping used numerous parameters, which made it less transferable to apply. Therefore, this study aimed to identify metabotypes based on a set of standard laboratory parameters that are regularly determined in clinical practice. K-means cluster analysis was used to group 3001 adults from the KORA F4 cohort into three clusters. We identified the clustering parameters through variable importance methods, without including any specific disease endpoint. Several unique combinations of selected parameters were used to create different metabotype models. Metabotype models were then described and evaluated, based on various metabolic parameters and on the incidence of cardiometabolic diseases. As a result, two optimal models were identified: a model composed of five parameters, which were fasting glucose, HDLc, non-HDLc, uric acid, and BMI (the metabolic disease model) for clustering; and a model that included four parameters, which were fasting glucose, HDLc, non-HDLc, and triglycerides (the cardiovascular disease model). These identified metabotypes are based on a few common parameters that are measured in everyday clinical practice. These metabotypes are cost-effective, and can be easily applied on a large scale in order to identify specific risk groups that can benefit most from measures to prevent cardiometabolic diseases, such as dietary recommendations and lifestyle interventions.

Association between Habitual Diet and the Postprandial Glucose Response-An Enable Study

SCOPE

It is inconclusive which factors influence inter-individual variations of postprandial glucose response (PPGR). This study investigates whether the habitual diet is associated with PPGR.

METHODS AND RESULTS

Data from healthy adults (young adults with 18-25 years, middle-aged adults with 40-65 years, and older adults with 75-85 years) is collected at baseline and during an oral glucose tolerance test (OGTT) collected. Habitual diet is assessed by a food frequency questionnaire and two 24-h food lists. Associations between habitual diet and glucose incremental area under the curve (iAUC_min ) are examined by regression models. The intake of cereals and cereal products is negatively associated with glucose iAUC_min (p = 0.002) in the total cohort (N = 459, 50% women, 55 ± 21 years, BMI 26 ± 5 kg m^{- 2} ). Up to 9% of the variance in the glycemic response is explained by the respective dietary parameters identified in the models of the specific age groups.

CONCLUSION

There are age-specific diet-related effects on PPGR. The usual intake of cereals and cereal products seems to play a greater role in PPGR in more than one age group. Further research is needed, to establish how diet can be optimized based on age and PPGR.

Mediterranean dietary pattern and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of prospective cohort studies

PURPOSE

Previous meta-analyses assessed the association of adherence to the Mediterranean dietary pattern (MedDiet) with the risk of type 2 diabetes (T2D). Since then, new large-scale cohort studies have been published. In addition, dose-response relation was not previously investigated and the certainty of evidence was not assessed. We aimed to explore the dose-response relationship between adherence to the MedDiet and the risk of T2D.

METHODS

We did a systematic search using PubMed, Scopus, and ISI Web of Science upto April 2021 for prospective cohort studies of the relationship between adherence to the MedDiet and the risk of T2D in the general population. The summary relative risks (RR) and 95%CI were estimated by applying a random-effects model.

RESULTS

Fourteen prospective cohort studies (410,303 participants and 41,466 cases) were included. There was an inverse association for the highest versus lowest category of adherence to the MedDiet (RR: 0.79, 95%CI 0.72, 0.88; I² = 82%, n = 14; Risk difference:  - 21 per 1000 person, 95%CI  - 28,  - 12; GRADE = moderate certainty), and for a 2-point increment in the MedDiet adherence score (RR: 0.86, 95%CI 0.82, 0.91; n = 13). The RR remained significant after controlling for important confounders and in almost all subgroups, especially subgroups defined by geographical region. We observed an inverse linear association between MedDiet adherence score and T2D incidence.

CONCLUSION

Adherence to the MedDiet was inversely related to T2D risk in a dose-response manner. Adherence to a Mediterranean-style diet may be a good advice for the primary prevention of T2D.

REGISTRY AND REGISTRY NUMBER

PROSPERO (CRD42021246589).

Correlation of Triglyceride-Rich Lipoprotein Cholesterol and Diabetes Mellitus in Stroke Patients

BACKGROUND

Previous studies have revealed that triglyceride-rich lipoprotein cholesterol (TRL-c) is closely related to diabetes mellitus (DM) in hypertensive patients. However, this relationship in stroke patients has not been reported. The aims of this study are to investigate the relationship between TRL-c and diabetes in adult Chinese stroke.

METHODS

Patients with stroke treated in the Department of Neurology of the Second Affiliated Hospital of Nanchang University from January 2019 to January 2021 were selected. TRL-c was calculated from total cholesterol minus (high-density and low-density lipoprotein). DM was diagnosed based on previous medical history (diagnosed by secondary hospitals or above) and/or current use of hypoglycemic drugs and/or intravenous blood glucose measurement (fasting blood glucose ≥7.0 mmol/L or nonfasting blood glucose > 11.1 mmol/L). The relationship between the TRL-c and DM was determined using multivariate logistic regression, smoothing curve fitting (penalized spline method), and subgroup analysis.

RESULTS

A total of 890 patients with stroke (age, 66.1 ± 11.8 years) were enrolled, including 329 females. Multivariate logistic regression analysis demonstrated that TRL-c had a positive association with DM (OR 1.88; 95% CI: 1.22 to 2.89). Strong linear associations of TRL-c with DM were confirmed by restricted cubic spline analysis. And the association between TRL-c and DM was consistent in the different subgroups.

CONCLUSION

Positive associations were found between TRL-c and DM in patients with stroke.

Main drivers of (poly)phenol effects on human health: metabolite production and/or gut microbiota-associated metabotypes?

Despite the high human interindividual variability in response to (poly)phenol consumption, the cause-and-effect relationship between some dietary (poly)phenols (flavanols and olive oil phenolics) and health effects (endothelial function and prevention of LDL oxidation, respectively) has been well established. Most of the variables affecting this interindividual variability have been identified (food matrix, gut microbiota, single-nucleotide-polymorphisms, etc.). However, the final drivers for the health effects of (poly)phenol consumption have not been fully identified. At least partially, these drivers could be (i) the (poly)phenols ingested that exert their effect in the gastrointestinal tract, (ii) the bioavailable metabolites that exert their effects systemically and/or (iii) the gut microbial ecology associated with (poly)phenol metabolism (i.e., gut microbiota-associated metabotypes). However, statistical associations between health effects and the occurrence of circulating and/or excreted metabolites, as well as cross-sectional studies that correlate gut microbial ecologies and health, do not prove a causal role unequivocally. We provide a critical overview and perspective on the possible main drivers of the effects of (poly)phenols on human health and suggest possible actions to identify the putative actors responsible for the effects.

Significant Impact of Coffee Consumption on MR-Based Measures of Cardiac Function in a Population-Based Cohort Study without Manifest Cardiovascular Disease

Subclinical effects of coffee consumption (CC) with regard to metabolic, cardiac, and neurological complications were evaluated using a whole-body magnetic resonance imaging (MRI) protocol. A blended approach was used to estimate habitual CC in a population-based study cohort without a history of cardiovascular disease. Associations of CC with MRI markers of gray matter volume, white matter hyperintensities, cerebral microhemorrhages, total and visceral adipose tissue (VAT), hepatic proton density fat fraction, early/late diastolic filling rate, end-diastolic/-systolic and stroke volume, ejection fraction, peak ejection rate, and myocardial mass were evaluated by linear regression. In our analysis with 132 women and 168 men, CC was positively associated with MR-based cardiac function parameters including late diastolic filling rate, stroke volume (p < 0.01 each), and ejection fraction (p < 0.05) when adjusting for age, sex, smoking, hypertension, diabetes, Low-density lipoprotein (LDL), triglycerides, cholesterol, and alcohol consumption. CC was inversely associated with VAT independent of demographic variables and cardiovascular risk factors (p < 0.05), but this association did not remain significant after additional adjustment for alcohol consumption. CC was not significantly associated with potential neurodegeneration. We found a significant positive and independent association between CC and MRI-based systolic and diastolic cardiac function. CC was also inversely associated with VAT but not independent of alcohol consumption.

Associations between habitual diet, metabolic disease, and the gut microbiota using latent Dirichlet allocation

BACKGROUND

The gut microbiome impacts human health through various mechanisms and is involved in the development of a range of non-communicable diseases. Diet is a well-known factor influencing microbe-host interaction in health and disease. However, very few findings are based on large-scale analysis using population-based studies. Our aim was to investigate the cross-sectional relationship between habitual dietary intake and gut microbiota structure in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study.

RESULTS

Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. Each participant's gut microbiota was subsequently described by a unique composition of these 20 subgroups. Associations between habitual dietary intake, assessed via repeated 24-h food lists and a Food Frequency Questionnaire, and the 20 subgroups, as well as between prevalence of metabolic diseases/risk factors and the subgroups, were assessed with multivariate-adjusted Dirichlet regression models. After adjustment for multiple testing, eight of 20 microbial subgroups were significantly associated with habitual diet, while nine of 20 microbial subgroups were associated with the prevalence of one or more metabolic diseases/risk factors. Subgroups 5 (Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, Roseburia) and 14 (Coprococcus, Bacteroides, Faecalibacterium, Ruminococcus) were particularly strongly associated with diet. For example, participants with a high probability for subgroup 5 were characterized by a higher Alternate Healthy Eating Index and Mediterranean Diet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, while participants with prevalent type 2 diabetes mellitus were characterized by a lower probability for subgroup 5.

CONCLUSIONS

The associations between habitual diet, metabolic diseases, and microbial subgroups identified in this analysis not only expand upon current knowledge of diet-microbiota-disease relationships, but also indicate the possibility of certain microbial groups to be modulated by dietary intervention, with the potential of impacting human health. Additionally, LDA appears to be a powerful tool for interpreting latent structures of the human gut microbiota. However, the subgroups and associations observed in this analysis need to be replicated in further studies. Video abstract.