Host-microbiome systems medicine of cardiometabolic disease
Today most healthy lifetime lost is due to the comorbidity nexus of cardiovascular and metabolic diseases. These are complex, involving factors of host genetics, diet and lifestyle interacting with features of the human microbiota. Progression and treatment prognosis is individually variable and reflects confounding impact of treatment regimes and indirect correlates of risk and protective factors. Mechanisms in particular involve circulating metabolite and lipid levels reflecting microbial action on nutrients from host diet, as well as complex action and reaction by the immune system.
Many questions remain unanswered qualitatively regarding the host-microbiome interaction space in the progression or reversal of disease. More importantly, high-fidelity quantitative understanding, which could be translated into personalized intervention regimes, is currently not available. The mission of the Forslund lab at the ECRC (joint cooperation of Max-Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin Berlin) is to provide this. We conduct integrative analysis of high-throughput host (metabolomic, immunomic, transcriptomic) and microbiome (metagenomic, metatranscriptomic) big data spaces, under constraints from clinical, dietary and lifestyle metadata, to try to model outcome of disease progression of treatment. The following thus are our core activities:
Multi-omics clinical cohort studies
Systems medical analysis requires large-scale data collection from clinical cohorts. As previously reported, demographics of sampling and treatment regimes, alongside intrinsically high inter-individual variability, each may substantially bias such data, so we have particular interest in strategies for managing such bias. In particular, we seek to initiate and participate in longitudinal and interventional cohort studies to complement, enrich and synergize with existing cross-sectional/case-control datasets. Technical variability and the human factor makes standardized practices for sampling, enrolment, phenotyping, logistics and processing central to the effort of being able to usefully integrate data at high fidelity. Drawing on experiences from several international research consortia and best practices established together with our collaboration partners, we consider this a major focus.
High-throughput measurement of host and microbiota
Working with core facility actors for those procedures already standardized, we can process biosamples using a variety of methods, with a particular focus on gut microbiotal quantification using deep shotgun sequencing. With these platforms established, we welcome collaborations also in pursuit of scientific and medical questions outside of our core interests, locally and globally. This also includes adding dimensions of microbiome analysis to study cohorts where such provides a meaningful extension, and we are looking into analogous methods for analysis of e.g. host immune cell populations.
Bioinformatics and systems biology
Central to our platform is the computational analysis of high-dimensional biological (“-omics”) data, especially integrating multiple data types while controlling for complex confounder profiles. Vast amounts of work done by researchers world-wide languish in “data tombs” after initial publication; we seek to remedy this waste by systematically contrasting new findings to this background. These efforts, as well as the statistical analysis and modeling of data from new cohort studies, requires substantial software infrastructure as well as the application of machine learning, data alchemy and visualization approaches. Here we develop, benchmark and deploy software tools as needed to accomplish our aims. Moreover, all such analysis is built on a foundation of detailed and systematic annotation of human, animal and microbial biological parts, especially annotation of the genetic basis for functional pathways and processes. Where most expedient, we contribute ourselves to these annotations by mobilizing and developing techniques from evolutionary bioinformatics. With these platforms in place, we are also happy to act as computational partners in collaborative projects.
Validation and translational applications
Ultimately our mission as part of the ECRC is to facilitate the eventual translation of basic science findings into diagnostic, prognostic and therapeutic tools. For this purpose, we work closely with experimentalist collaborators, including model system experts at the MDC, seeking to validate key findings at the highest level of certainty. This involves techniques such as comparative interventions in germ-free or otherwise controlled animals, and the trialing of interventions in human volunteers. We are further very happy to work with industry partners (e.g. pharmaceutical, probiotic manufacturers, manufacturers of testing kits) in discovery or optimization of compounds, agents or techniques.