The human microbiota is thought to have a tremendous influence on human health and diseases. Although it was virtually impossible to study them until a few years ago, next generation sequencing technologies have enabled us to access and characterize the microbiota in a culture-free manner. Cross-sectional studies have shown associations between changes in human gut microbiota and several diseases. For most of these associations though, whether the relationship is causality or reverse causality still remains to be elucidated. This is only the beginning of a new trend to elucidate the role of host-associated microbiota in diseases, and bioinformatics is becoming increasingly important in this endeavor. Over the last 15 years, my research has focused on analyzing human microbiome data to improve our understanding of their importance in human health. In this talk, I will present examples of our discoveries in (i) higher level trends in human microbiome composition, (ii) microbiome-derived diagnostic biomarkers for colorectal cancer, and (iii) resilience of healthy gut microbiome against antibiotic treatment. Finally, I will show some examples from our approaches to integrate microbiome multi-omics data to enable understanding at the molecular level.

Methyl-Cobalamin (Cbl) derives from dietary vitamin B12 and acts as cofactor of methionine synthase (MS) in mammals. MS encoded by MTR catalyzes the remethylation of homocysteine to generate methionine and tetrahydrofolate, which fuel methionine and cytoplasmic folate cycles, respectively. Methionine is the precursor of S-adenosyl methionine (SAM), the universal methyl donor of transmethylation reactions. Impaired MS activity results from inadequate dietary intake or malabsorption of B12 and inborn errors of Cbl metabolism (IECM). The mechanisms at the origin of the high variability of clinical presentation of impaired MS activity are classically considered as the consequence of the dysruption  of folate cycle and related synthesis of purines and pyrimidines and the decreased synthesis of endogenous methionine and SAM. Since one decade, data on cellular and animal models of B12 deficiency and IECM have highlighted other key pathomechanisms, including altered interactome of MS with methionine synthase reductase, MMACHC and MMADHC, endoplasmic reticulum stress, altered cell signaling and genomic/epigenomic dysregulations. Decreased MS activity increases catalytic protein phosphatase 2A (PP2A) and produces imbalanced phosphorylation/methylation  of nucleocytoplasmic RNA binding proteins, including ELAVL1/HuR protein, with subsequent nuclear sequestration of mRNAs and dramatic alteration of gene expression, including SIRT 1. Decreased SAM and SIRT1 activity induce ER stress through impaired SIRT1-deacetylation of HSF1 and hypomethylation/hyperacetylation of peroxisome proliferator-activated receptor-γ coactivator-1α (PGC1α), which deactivate nuclear receptors and lead to impaired energy metabolism and neuroplasticity.  The reversibility of these pathomechanisms by SIRT1 agonists opens promising perspectives in the treatment of IECM outcomes resistant to conventional supplementation  therapies.

To date, no causative treatments are available for common neurodegenerative diseases like Parkinson’s disease (PD). Previously failed trials did not account for the clinical and pathophysiological heterogeneity of PD. Genetics of PD provided first insight into the complexity of this most common neurodegenerative movement disorder and delineated relevant subgroups of patients, who share an underlying molecular pathology. Novel patient-based models from monogenic forms of PD allowed to dissect mechanisms of neurodegeneration and define prototypes for stratification of the more common sporadic form of PD. These strategies hold promise to translate into novel disease-modifying compounds for more targeted therapies using mechanism-based interventions in subgroups of PD patients. Moreover, due to the rapid evolution of novel technologies, e.g. next generation sequencing technologies or device-assisted registrations of clinical symptoms of PD. This is linked with a dramatic increase in multiscale high quality data characterizing PD at different levels and enables novel strategies for patient stratification and identification of markers for therapeutic outcome, that can be translated into clinical decision support, e.g. genetic predictors of therapeutic outcomes in PD. The implementation of these novel strategies and technologies allows for a more direct participation of patients in ongoing research and integrated care efforts and strengthen patient’s autonomy and responsibility for future research.

Protein misfolding and aggregation are common events in a wide variety of neurodegenerative disorders, such as Alzheimer’s or Parkinson’s disease (PD). Aging is the major known risk factor for the development of neurodegenerative diseases, but mutations in several genes are associated with familial forms. In PD, aggregation of alpha-synuclein (ASYN) in Lewy bodies and the loss of dopaminergic neurons from the substantia nigra, are typical pathological hallmarks. Our limited understanding of the molecular mechanisms underlying protein aggregation and neurodegeneration has complicated the development of novel therapeutic approaches. In our studies, we exploit different model organisms and employ diverse molecular approaches to unravel the molecular basis of neurodegenerative disorders. We are using novel cellular models where central aspects associated with ASYN dysfunction are recapitulated and we are now using powerful imaging approaches to investigate how different types of protein-protein interactions influence conformational changes in ASYN and how those relate to the initial oligomerization events associated with its toxicity. Altogether, our approaches will contribute for the development of novel strategies for therapeutic intervention in protein misfolding disorders.

The technique and discoveries of genome-wide association studies (GWASs) have revolutionized the field of genetic epidemiology prompting the development and application of a range of new tools offering new insights into old questions. Since the first successful GWAS in 2007 many genetic markers (so called single nucleotide polymorphisms or SNPs) have been identified for almost every common disease or trait. Those discovered SNPs themselves can be combined in multi-SNP genetic risk scores. This integrated measure of genetic susceptibility offers an ideal opportunity to investigate to what extent the development of the disease or trait depends on the environment (i.e., gene-environment interaction). The advent of genome-wide methylation arrays (or epigenome-wide association studies or EWAS) has provided yet another tool to investigate gene-environment interaction in complex traits as the epigenome provides an interface between the environment and the genome and can be influenced by dietary, lifestyle, behavioral, and social factors. The current presentation will review these methodological advances and illustrate the promise of genetic and epigenetic risk scores for personalized risk prediction ultimately impacting prevention of our common complex diseases.