Biological age (BA), derived from molecular and physiological measurements, has been proposed to better predict mortality and disease than chronological age (CA). In the present study, a computed estimate of BA was investigated longitudinally in 3,558 individuals using deep phenotyping, which encompassed a broad range of biological processes. The Klemera–Doubal algorithm was applied to longitudinal data consisting of genetic, clinical laboratory, metabolomic, and proteomic assays from individuals undergoing a wellness program. BA was elevated relative to CA in the presence of chronic diseases. We observed a significantly lower rate of change than the expected ~1 year/year (to which the estimation algorithm was constrained) in BA for individuals participating in a wellness program. This observation suggests that BA is modifiable and suggests that a lower BA relative to CA may be a sign of healthy aging. Measures of metabolic health, inflammation, and toxin bioaccumulation were strong predictors of BA. BA estimation from deep phenotyping was seen to change in the direction expected for both positive and negative health conditions. We believe BA represents a general and interpretable “metric for wellness” that may aid in monitoring aging over time.

Overcoming systemic dormancy and initiating secondary tumor grow under unique microenvironmental conditions is a major rate-limiting step in metastatic progression. Disseminated tumor cells encounter major changes in nutrient supplies and oxidative stresses compared to the primary tumor and must demonstrate significant metabolic plasticity to adapt to specific metastatic sites. Recent studies suggest that differential utilization of pyruvate sits as a critical node in determining the organotropism of metastatic breast cancer. Pyruvate carboxylase (PC) is key enzyme that converts pyruvate into oxaloacetate for utilization in gluconeogenesis and replenishment of the TCA cycle. Patient survival was analyzed with respect to gene copy number alterations and differential mRNA expression levels of PC. Expression of PC was analyzed in the MCF-10A, D2-HAN and the 4 T1 breast cancer progression series under in vitro and in vivo growth conditions. PC expression was depleted via shRNAs and the impact on in vitro cell growth, mammary fat pad tumor growth, and pulmonary and non-pulmonary metastasis was assessed by bioluminescent imaging. Changes in glycolytic capacity, oxygen consumption, and response to oxidative stress were quantified upon PC depletion. Genomic copy number increases in PC were observed in 16–30% of metastatic breast cancer patients. High expression of PC mRNA was associated with decreased patient survival in the MCTI and METABRIC patient datasets. Enhanced expression of PC was not recapitulated in breast cancer progression models when analyzed under glucose-rich in vitro culture conditions. In contrast, PC expression was dramatically enhanced upon glucose deprivation and in vivo in pulmonary metastases. Depletion of PC led to a dramatic decrease in 4 T1 pulmonary metastasis, but did not affect orthotopic primary tumor growth. Tail vein inoculations confirmed the role of PC in facilitating pulmonary, but not extrapulmonary tumor initiation. PC-depleted cells demonstrated a decrease in glycolytic capacity and oxygen consumption rates and an enhanced sensitivity to oxidative stress. Our studies indicate that PC is specifically required for the growth of breast cancer that has disseminated to the lungs. Overall, these findings point to the potential of targeting PC for the treatment of pulmonary metastatic breast cancer.

The Pioneer 100 Wellness Project involved quantitatively profiling 108 participants’ 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. Significance Deep molecular phenotyping of individuals provides the opportunity for biological insight into host physiology. As the human microbiome is increasingly being recognized as an important determinant of host health, understanding the host–microbiome relationship in a multiomics context may pave the way forward for targeted interventions. In this study, we analyze gut microbial composition of 101 individuals over the course of a year, alongside clinical markers and serum metabolomics. We establish association between specific gut compositional states and host health biomarkers (e.g., of inflammation). Finally, we provide evidence for an apparent transition barrier between these compositional states. A deeper understanding of microbiome dynamics and the associated variation in host phenotypes furthers our ability to engineer effective interventions that optimize wellness.

Many studies link the composition of the human gut microbiome to aberrant health states. However, our understanding of what constitutes a ‘healthy’ gut ecosystem, and how to effectively monitor and maintain it, are only now emerging. Here, we review current approaches to defining and monitoring gut microbiome health, and outline directions for developing targeted ecological therapeutics. We emphasize the importance of identifying which ecological features of the gut microbiome are most resonant with host molecular phenotypes, and highlight certain gut microbial metabolites as potential biomarkers of gut microbiome health. We further discuss how multi-omic measurements of host phenotypes, dietary information, and gut microbiome profiles can be integrated into increasingly sophisticated host-microbiome mechanistic models that can be leveraged to design personalized interventions. Overall, we summarize current progress on defining microbiome health and highlight a number of paths forward for engineering the ecology of the gut to promote wellness.