Impact of dietary interventions on pre-diabetic oral and gut microbiome, metabolites and cytokines

Diabetes and associated comorbidities are a global health threat on the rise. We conducted a six-month dietary intervention in pre-diabetic individuals (NCT03222791), to mitigate the hyperglycemia and enhance metabolic health. The current work explores early diabetes markers in the 200 individuals who completed the trial. We find 166 of 2,803 measured features, including oral and gut microbial species and pathways, serum metabolites and cytokines, show significant change in response to a personalized postprandial glucose-targeting diet or the standard of care Mediterranean diet. These changes include established markers of hyperglycemia as well as novel features that can now be investigated as potential therapeutic targets. Our results indicate the microbiome mediates the effect of diet on glycemic, metabolic and immune measurements, with gut microbiome compositional change explaining 12.25% of serum metabolites variance. Although the gut microbiome displays greater compositional changes compared to the oral microbiome, the oral microbiome demonstrates more changes at the genetic level, with trends dependent on environmental richness and species prevalence in the population. In conclusion, our study shows dietary interventions can affect the microbiome, cardiometabolic profile and immune response of the host, and that these factors are well associated with each other, and can be harnessed for new therapeutic modalities.

Wearable and digital devices to monitor and treat metabolic diseases

Cardiometabolic diseases are a major public-health concern owing to their increasing prevalence worldwide. These diseases are characterized by a high degree of interindividual variability with regards to symptoms, severity, complications and treatment responsiveness. Recent technological advances, and the growing availability of wearable and digital devices, are now making it feasible to profile individuals in ever-increasing depth. Such technologies are able to profile multiple health-related outcomes, including molecular, clinical and lifestyle changes. Nowadays, wearable devices allowing for continuous and longitudinal health screening outside the clinic can be used to monitor health and metabolic status from healthy individuals to patients at different stages of disease. Here we present an overview of the wearable and digital devices that are most relevant for cardiometabolic-disease-related readouts, and how the information collected from such devices could help deepen our understanding of metabolic diseases, improve their diagnosis, identify early disease markers and contribute to individualization of treatment and prevention plans.

Impact of Valve Size on Paravalvular Leak and Valve Hemodynamics in Patients With Borderline Size Aortic Valve Annulus

Background

Transcatheter heart valve (THV) selection for transcatheter aortic valve implantation (TAVI) is crucial to achieve procedural success. Borderline aortic annulus size (BAAS), which allows a choice between two consecutive valve sizes, is a common challenge during device selection. In the present study, we evaluated TAVI outcomes in patients with BAAS according to THV size selection.

Methods

We performed a retrospective study including patients with severe aortic stenosis (AS) and BAAS, measured by multi-detector computed tomography (MDCT), undergoing TAVI with self-expandable (SE) or balloon-expandable (BE) THV from the Israeli multi-center TAVI registry. The aim was to evaluate outcomes of TAVI, mainly paravalvular leak (PVL) and valve hemodynamics, in patients with BAAS (based on MDCT) according to THV sizing selection in between 2 valve sizes. In addition, to investigate the benefit of shifting between different THV types (BE and SE) to avoid valve size selection in BAAS.

Results

Out of 2,352 patients with MDCT measurements, 598 patients with BAAS as defined for at least one THV type were included in the study. In BAAS patients treated with SE-THV, larger THV selection was associated with lower rate of PVL, compared to smaller THV (45.3 vs. 64.5%; pv = 0.0038). Regarding BE-THV, larger valve selection was associated with lower post-procedural transvalvular gradients compared to smaller THV (mean gradient: 9.9 ± 3.7 vs. 12.5 ± 7.2 mmHg; p = 0.019). Of note, rates of mortality, left bundle branch block, permanent pacemaker implantation, stroke, annular rupture, and/or coronary occlusion did not differ between groups.

Conclusion

BAAS is common among patients undergoing TAVI. Selection of a larger THV in these patients is associated with lower rates of PVL and optimized THV hemodynamics with no effect on procedural complications. Additionally, shift from borderline THV to non-borderline THV modified both THV hemodynamics and post-dilatation rates.

The Gut Microbiome of Adults With Type 1 Diabetes and Its Association With the Host Glycemic Control

OBJECTIVE

Previous studies have demonstrated an association between gut microbiota composition and type 1 diabetes (T1D) pathogenesis. However, little is known about the composition and function of the gut microbiome in adults with longstanding T1D or its association with host glycemic control.

RESEARCH DESIGN AND METHODS

We performed a metagenomic analysis of the gut microbiome obtained from fecal samples of 74 adults with T1D, 14.6 ± 9.6 years following diagnosis, and compared their microbial composition and function to 296 age-matched healthy control subjects (1:4 ratio). We further analyzed the association between microbial taxa and indices of glycemic control derived from continuous glucose monitoring measurements and blood tests and constructed a prediction model that solely takes microbiome features as input to evaluate the discriminative power of microbial composition for distinguishing individuals with T1D from control subjects.

RESULTS

Adults with T1D had a distinct microbial signature that separated them from control subjects when using prediction algorithms on held-out subjects (area under the receiver operating characteristic curve = 0.89 ± 0.03). Linear discriminant analysis showed several bacterial species with significantly higher scores in T1D, including Prevotella copri and Eubacterium siraeum, and species with higher scores in control subjects, including Firmicutes bacterium and Faecalibacterium prausnitzii (P < 0.05, false discovery rate corrected for all). On the functional level, several metabolic pathways were significantly lower in adults with T1D. Several bacterial taxa and metabolic pathways were associated with the host's glycemic control.

CONCLUSIONS

We identified a distinct gut microbial signature in adults with longstanding T1D and associations between microbial taxa, metabolic pathways, and glycemic control indices. Additional mechanistic studies are needed to identify the role of these bacteria for potential therapeutic strategies.

Prediction of Personal Glycemic Responses to Food for Individuals With Type 1 Diabetes Through Integration of Clinical and Microbial Data

OBJECTIVE

Despite technological advances, results from various clinical trials have repeatedly shown that many individuals with type 1 diabetes (T1D) do not achieve their glycemic goals. One of the major challenges in disease management is the administration of an accurate amount of insulin for each meal that will match the expected postprandial glycemic response (PPGR). The objective of this study was to develop a prediction model for PPGR in individuals with T1D.

RESEARCH DESIGN AND METHODS

We recruited individuals with T1D who were using continuous glucose monitoring and continuous subcutaneous insulin infusion devices simultaneously to a prospective cohort and profiled them for 2 weeks. Participants were asked to report real-time dietary intake using a designated mobile app. We measured their PPGRs and devised machine learning algorithms for PPGR prediction, which integrate glucose measurements, insulin dosages, dietary habits, blood parameters, anthropometrics, exercise, and gut microbiota. Data of the PPGR of 900 healthy individuals to 41,371 meals were also integrated into the model. The performance of the models was evaluated with 10-fold cross validation.

RESULTS

A total of 121 individuals with T1D, 75 adults and 46 children, were included in the study. PPGR to 6,377 meals was measured. Our PPGR prediction model substantially outperforms a baseline model with emulation of standard of care (correlation of R = 0.59 compared with R = 0.40 for predicted and observed PPGR respectively; P < 10-10). The model was robust across different subpopulations. Feature attribution analysis revealed that glucose levels at meal initiation, glucose trend 30 min prior to meal, meal carbohydrate content, and meal's carbohydrate-to-fat ratio were the most influential features for the model.

CONCLUSIONS

Our model enables a more accurate prediction of PPGR and therefore may allow a better adjustment of the required insulin dosage for meals. It can be further implemented in closed loop systems and may lead to rationally designed nutritional interventions personally tailored for individuals with T1D on the basis of meals with expected low glycemic response.

Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease

Complex diseases, such as coronary artery disease (CAD), are often multifactorial, caused by multiple underlying pathological mechanisms. Here, to study the multifactorial nature of CAD, we performed comprehensive clinical and multi-omic profiling, including serum metabolomics and gut microbiome data, for 199 patients with acute coronary syndrome (ACS) recruited from two major Israeli hospitals, and validated these results in a geographically distinct cohort. ACS patients had distinct serum metabolome and gut microbial signatures as compared with control individuals, and were depleted in a previously unknown bacterial species of the Clostridiaceae family. This bacterial species was associated with levels of multiple circulating metabolites in control individuals, several of which have previously been linked to an increased risk of CAD. Metabolic deviations in ACS patients were found to be person specific with respect to their potential genetic or environmental origin, and to correlate with clinical parameters and cardiovascular outcomes. Moreover, metabolic aberrations in ACS patients linked to microbiome and diet were also observed to a lesser extent in control individuals with metabolic impairment, suggesting the involvement of these aberrations in earlier dysmetabolic phases preceding clinically overt CAD. Finally, a metabolomics-based model of body mass index (BMI) trained on the non-ACS cohort predicted higher-than-actual BMI when applied to ACS patients, and the excess BMI predictions independently correlated with both diabetes mellitus (DM) and CAD severity, as defined by the number of vessels involved. These results highlight the utility of the serum metabolome in understanding the basis of risk-factor heterogeneity in CAD.

10 K: a large-scale prospective longitudinal study in Israel

The 10 K is a large-scale prospective longitudinal cohort and biobank that was established in Israel. The primary aims of the study include development of prediction models for disease onset and progression and identification of novel molecular markers with a diagnostic, prognostic and therapeutic value. The recruitment was initiated in 2018 and is expected to complete in 2021. Between 28/01/2019 and 13/12/2020, 4,629 from the expected 10,000 participants were recruited (46 %). Follow-up visits are scheduled every year for a total of 25 years. The cohort includes individuals between the ages of 40 and 70 years. Predefined medical conditions were determined as exclusions. Information collected at baseline includes medical history, lifestyle and nutritional habits, vital signs, anthropometrics, blood tests results, Electrocardiography, Ankle-brachial pressure index (ABI), liver US and Dual-energy X-ray absorptiometry (DXA) tests. Molecular profiling includes transcriptome, proteome, gut and oral microbiome, metabolome and immune system profiling. Continuous measurements include glucose levels using a continuous glucose monitoring device for 2 weeks and sleep monitoring by a home sleep apnea test device for 3 nights. Blood and stool samples are collected and stored at - 80 °C in a storage facility for future research. Linkage is being established with national disease registries.

Potential role of indolelactate and butyrate in multiple sclerosis revealed by integrated microbiome-metabolome analysis

Multiple sclerosis (MS) is an immune-mediated disease whose precise etiology is unknown. Several studies found alterations in the microbiome of individuals with MS, but the mechanism by which it may affect MS is poorly understood. Here we analyze the microbiome of 129 individuals with MS and find that they harbor distinct microbial patterns compared with controls. To study the functional consequences of these differences, we measure levels of 1,251 serum metabolites in a subgroup of subjects and unravel a distinct metabolite signature that separates affected individuals from controls nearly perfectly (AUC = 0.97). Individuals with MS are found to be depleted in butyrate-producing bacteria and in bacteria that produce indolelactate, an intermediate in generation of the potent neuroprotective antioxidant indolepropionate, which we found to be lower in their serum. We identify microbial and metabolite candidates that may contribute to MS and should be explored further for their causal role and therapeutic potential.

Myocardial extracellular volume quantification by computed tomography predicts outcomes in patients with severe aortic stenosis

BACKGROUND

The extent of myocardial fibrosis in patients with severe aortic stenosis might have an important prognostic value. Non-invasive imaging to quantify myocardial fibrosis by measuring extracellular volume fraction might have an important clinical utility prior to aortic valve intervention.

METHODS

Seventy-five consecutive patients with severe aortic stenosis, and 19 normal subjects were prospectively recruited and underwent pre- and post-contrast computed tomography for estimating myocardial extracellular volume fraction. Serum level of galectin-3 was measured and 2-dimensional echocardiography was performed to characterize the extent of cardiac damage using a recently published aortic stenosis staging classification.

RESULTS

Extracellular volume fraction was higher in patients with aortic stenosis compared to normal subjects (40.0±11% vs. 21.6±5.6%; respectively, p<0.001). In patients with aortic stenosis, extracellular volume fraction correlated with markers of left ventricular decompensation including New York Heart Association functional class, left atrial volume, staging classification of aortic stenosis and lower left ventricular ejection fraction. Out of 75 patients in the AS group, 49 underwent TAVI, 6 surgical AVR, 2 balloon valvuloplasty, and 18 did not undergo any type of intervention. At 12-months after aortic valve intervention, extracellular volume fraction predicted the combined outcomes of stroke and hospitalization for heart failure with an area under the curve of 0.77 (95% confidence interval: 0.65-0.88). A trend for correlation between serum galectin-3 and extracellular volume was noted.

CONCLUSION

In patients with severe aortic stenosis undergoing computed tomography before aortic valve intervention, quantification of extracellular volume fraction correlated with functional status and markers of left ventricular decompensation, and predicted the 12-months composite adverse clinical outcomes. Implementation of this novel technique might aid in the risk stratification process before aortic valve interventions.

Longitudinal Multi-omics Reveals Subset-Specific Mechanisms Underlying Irritable Bowel Syndrome

The gut microbiome has been implicated in multiple human chronic gastrointestinal (GI) disorders. Determining its mechanistic role in disease has been difficult due to apparent disconnects between animal and human studies and lack of an integrated multi-omics view of disease-specific physiological changes. We integrated longitudinal multi-omics data from the gut microbiome, metabolome, host epigenome, and transcriptome in the context of irritable bowel syndrome (IBS) host physiology. We identified IBS subtype-specific and symptom-related variation in microbial composition and function. A subset of identified changes in microbial metabolites correspond to host physiological mechanisms that are relevant to IBS. By integrating multiple data layers, we identified purine metabolism as a novel host-microbial metabolic pathway in IBS with translational potential. Our study highlights the importance of longitudinal sampling and integrating complementary multi-omics data to identify functional mechanisms that can serve as therapeutic targets in a comprehensive treatment strategy for chronic GI diseases. VIDEO ABSTRACT.

Tumor diversity and the trade-off between universal cancer tasks

Recent advances have enabled powerful methods to sort tumors into prognosis and treatment groups. We are still missing, however, a general theoretical framework to understand the vast diversity of tumor gene expression and mutations. Here we present a framework based on multi-task evolution theory, using the fact that tumors need to perform multiple tasks that contribute to their fitness. We find that trade-offs between tasks constrain tumor gene-expression to a continuum bounded by a polyhedron whose vertices are gene-expression profiles, each specializing in one task. We find five universal cancer tasks across tissue-types: cell-division, biomass and energy, lipogenesis, immune-interaction and invasion and tissue-remodeling. Tumors that specialize in a task are sensitive to drugs that interfere with this task. Driver, but not passenger, mutations tune gene-expression towards specialization in specific tasks. This approach can integrate additional types of molecular data into a framework of tumor diversity grounded in evolutionary theory.

Structural variation in the gut microbiome associates with host health

Differences in the presence of even a few genes between otherwise identical bacterial strains may result in critical phenotypic differences. Here we systematically identify microbial genomic structural variants (SVs) and find them to be prevalent in the human gut microbiome across phyla and to replicate in different cohorts. SVs are enriched for CRISPR-associated and antibiotic-producing functions and depleted from housekeeping genes, suggesting that they have a role in microbial adaptation. We find multiple associations between SVs and host disease risk factors, many of which replicate in an independent cohort. Exploring genes that are clustered in the same SV, we uncover several possible mechanistic links between the microbiome and its host, including a region in Anaerostipes hadrus that encodes a composite inositol catabolism-butyrate biosynthesis pathway, the presence of which is associated with lower host metabolic disease risk. Overall, our results uncover a nascent layer of variability in the microbiome that is associated with microbial adaptation and host health.

Determination of acidity constants of enolisable compounds by capillary electrophoresis

Research on the structure-activity relationships of molecules with acidic carbon atoms led us to undertake a feasibility study on the determination of their acidity constants by capillary electrophoresis (CE). The studied molecules had diverse structures and were tetronic acid, acetylacetone, diethylmalonate, Meldrum's acid, 3-methylrhodanine, nitroacetic acid ethyl ester, pyrimidine-2,4,6-trione, 3-oxo-3-phenylpropionic acid ethyl ester, 1-phenylbutan-1,3-dione, 5,5-dimethylcyclohexan-1,3-dione and homophthalic anhydride. The p Ka range explored by CE was therefore very large (from 3 to 12) and p Ka values near 12 were evaluated by mathematical extrapolations. The analyses were carried out in CZE mode using a fused silica capillary grafted (or not) with hexadimethrine. Owing to the electrophoretic behaviour of these compounds according to the pH, their acidity constants could be evaluated and appeared in perfect agreement with the literature data obtained, a few decades ago, by means of potentiometry, spectrometry or conductimetry. The p Ka of homophthalic anhydride and 3-methylrhodanine were evaluated for the first time.