Health and disease markers correlate with gut microbiome composition across thousands of people.

Variation in the human gut microbiome can reflect host lifestyle and behaviors and influence disease biomarker levels in the blood. Understanding the relationships between gut microbes and host phenotypes are critical for understanding wellness and disease. Here, we examine associations between the gut microbiota and ~150 host phenotypic features across ~3,400 individuals. We identify major axes of taxonomic variance in the gut and a putative diversity maximum along the Firmicutes-to-Bacteroidetes axis. Our analyses reveal both known and unknown associations between microbiome composition and host clinical markers and lifestyle factors, including host-microbe associations that are composition-specific. These results suggest potential opportunities for targeted interventions that alter the composition of the microbiome to improve host health. By uncovering the interrelationships between host diet and lifestyle factors, clinical blood markers, and the human gut microbiome at the population-scale, our results serve as a roadmap for future studies on host-microbe interactions and interventions

Genetic Predisposition Impacts Clinical Changes in a Lifestyle Coaching Program.

Both genetic and lifestyle factors contribute to an individual\u27s disease risk, suggesting a multi-omic approach is essential for personalized prevention. Studies have examined the effectiveness of lifestyle coaching on clinical outcomes, however, little is known about the impact of genetic predisposition on the response to lifestyle coaching. Here we report on the results of a real-world observational study in 2531 participants enrolled in a commercial Scientific Wellness program, which combines multi-omic data with personalized, telephonic lifestyle coaching. Specifically, we examined: 1) the impact of this program on 55 clinical markers and 2) the effect of genetic predisposition on these clinical changes. We identified sustained improvements in clinical markers related to cardiometabolic risk, inflammation, nutrition, and anthropometrics. Notably, improvements in HbA1c were akin to those observed in landmark trials. Furthermore, genetic markers were associated with longitudinal changes in clinical markers. For example, individuals with genetic predisposition for higher LDL-C had a lesser decrease in LDL-C on average than those with genetic predisposition for average LDL-C. Overall, these results suggest that a program combining multi-omic data with lifestyle coaching produces clinically meaningful improvements, and that genetic predisposition impacts clinical responses to lifestyle change

Longitudinal analysis reveals transition barriers between dominant ecological states in the gut microbiome.

The Pioneer 100 Wellness Project involved quantitatively profiling 108 participants\u27 molecular physiology over time, including genomes, gut microbiomes, blood metabolomes, blood proteomes, clinical chemistries, and data from wearable devices. Here, we present a longitudinal analysis focused specifically around the Pioneer 100 gut microbiomes. We distinguished a subpopulation of individuals with reduced gut diversity, elevated relative abundance of the genus Prevotella, and reduced levels of the genus Bacteroides We found that the relative abundances of Bacteroides and Prevotella were significantly correlated with certain serum metabolites, including omega-6 fatty acids. Primary dimensions in distance-based redundancy analysis of clinical chemistries explained 18.5% of the variance in bacterial community composition, and revealed a Bacteroides/Prevotella dichotomy aligned with inflammation and dietary markers. Finally, longitudinal analysis of gut microbiome dynamics within individuals showed that direct transitions between Bacteroides-dominated and Prevotella-dominated communities were rare, suggesting the presence of a barrier between these states. One implication is that interventions seeking to transition between Bacteroides- and Prevotella-dominated communities will need to identify permissible paths through ecological state-space that circumvent this apparent barrier

Sulfatide Preserves Insulin Crystals Not by Being Integrated in the Lattice but by Stabilizing Their Surface

Background. Sulfatide is known to chaperone insulin crystallization within the pancreatic beta cell, but it is not known if this results from sulfatide being integrated inside the crystal structure or by binding the surface of the crystal. With this study, we aimed to characterize the molecular mechanisms underlying the integral role for sulfatide in stabilizing insulin crystals prior to exocytosis. Methods. We cocrystallized human insulin in the presence of sulfatide and solved the structure by molecular replacement. Results. The crystal structure of insulin crystallized in the presence of sulfatide does not reveal ordered occupancy representing sulfatide in the crystal lattice, suggesting that sulfatide does not permeate the crystal lattice but exerts its stabilizing effect by alternative interactions such as on the external surface of insulin crystals. Conclusions. Sulfatide is known to stabilize insulin crystals, and we demonstrate here that in beta cells sulfatide is likely coating insulin crystals. However, there is no evidence for sulfatide to be built into the crystal lattice

A wellness study of 108 individuals using personal, dense, dynamic data clouds.

Personal data for 108 individuals were collected during a 9-month period, including whole genome sequences; clinical tests, metabolomes, proteomes, and microbiomes at three time points; and daily activity tracking. Using all of these data, we generated a correlation network that revealed communities of related analytes associated with physiology and disease. Connectivity within analyte communities enabled the identification of known and candidate biomarkers (e.g., gamma-glutamyltyrosine was densely interconnected with clinical analytes for cardiometabolic disease). We calculated polygenic scores from genome-wide association studies (GWAS) for 127 traits and diseases, and used these to discover molecular correlates of polygenic risk (e.g., genetic risk for inflammatory bowel disease was negatively correlated with plasma cystine). Finally, behavioral coaching informed by personal data helped participants to improve clinical biomarkers. Our results show that measurement of personal data clouds over time can improve our understanding of health and disease, including early transitions to disease states

Modulation of Bax and mTOR for Cancer Therapeutics.

A rationale exists for pharmacologic manipulation of the serine (S)184 phosphorylation site of the proapoptotic Bcl2 family member Bax as an anticancer strategy. Here, we report the refinement of the Bax agonist SMBA1 to generate CYD-2-11, which has characteristics of a suitable clinical lead compound. CYD-2-11 targeted the structural pocket proximal to S184 in the C-terminal region of Bax, directly activating its proapoptotic activity by inducing a conformational change enabling formation of Bax homooligomers in mitochondrial membranes. In murine models of small-cell and non-small cell lung cancers, including patient-derived xenograft and the genetically engineered mutant KRAS-driven lung cancer models, CYD-2-11 suppressed malignant growth without evident significant toxicity to normal tissues. In lung cancer patients treated with mTOR inhibitor RAD001, we observed enhanced S184 Bax phosphorylation in lung cancer cells and tissues that inactivates the propaoptotic function of Bax, contributing to rapalog resistance. Combined treatment of CYD-2-11 and RAD001 in murine lung cancer models displayed strong synergistic activity and overcame rapalog resistanc