Johan Auwerx | EPFL Graph Search

Johan Auwerx is Professor at the École Polytechnique Fédérale in Lausanne, Switzerland, where he occupies the Nestle Chair in Energy Metabolism. Dr. Auwerx has been using molecular physiology and systems genetics to understand metabolism in health, aging and disease. Much of his work focused on understanding how diet, exercise and hormones control metabolism through changing the expression of genes by altering the activity of transcription factors and their associated cofactors. His work was instrumental for the development of agonists of nuclear receptors - a particular class of transcription factors - into drugs, which now are used to treat high blood lipid levels, fatty liver, and type 2 diabetes. Dr. Auwerx was amongst the first to recognize that transcriptional cofactors, which fine-tune the activity of transcription factors, act as energy sensors/effectors that influence metabolic homeostasis. His research validated these cofactors as novel targets to treat metabolic diseases, and spurred the clinical use of natural compounds, such as resveratrol, as modulators of these cofactor pathways.

Johan Auwerx was elected as a member of EMBO in 2003 and is the recipient of a dozen of international scientific prizes, including the Danone International Nutrition Award, the Oskar Minkowski Prize, and the Morgagni Gold Medal. His work is highly cited by his peers with a h-factor of over 100. He is an editorial board member of several journals, including Cell Metabolism, Molecular Systems Biology, The EMBO Journal, Journal of Cell Biology, Cell, and Science. Dr. Auwerx co-founded a handful of biotech companies, including Carex, PhytoDia, and most recently Mitobridge, and has served on several scientific advisory boards.

Dr. Auwerx received both his MD and PhD in Molecular Endocrinology at the Katholieke Universiteit in Leuven, Belgium. He was a post-doctoral research fellow in the Departments of Medicine and Genetics of the University of Washington in Seattle.

eNAMPT actions through nucleus accumbens NAD + /SIRT1 link increased adiposity with sociability deficits programmed by peripuberty stress

Simone Astori, Johan Auwerx, Lei Cao, João Pedro de Matos Rodrigues, Sriparna Ghosal, Jocelin Grosse, Wei Huang, Laia Morato Fornaguera, Maria del Carmen Sandi Perez, Ioannis Zalachoras, Olivia Zanoletti

Obesity is frequently associated with impairments in the social domain, and stress at puberty can lead to long-lasting changes in visceral fat deposition and in social behaviors. However, whether stress-induced changes in adipose tissue can affect fat-to-brain signaling, thereby orchestrating behavioral changes, remains unknown. We found that peripubertally stressed male-but not female-mice exhibit concomitant increased adiposity and sociability deficits. We show that reduced levels of the adipokine nicotinamide phosphoribosyltransferase (NAMPT) in fat and its extracellular form eNAMPT in blood contribute to lifelong reductions in sociability induced by peripubertal stress. By using a series of adipose tissue and brain region-specific loss- and gain-of-function approaches, we implicate impaired nicotinamide adenine dinucleotide (NAD+)/SIRT1 pathway in the nucleus accumbens. Impairments in sociability and accumbal neuronal excitability are prevented by normalization of eNAMPT levels or treatment with nicotinamide mononucleotide (NMN), a NAD+-boosting compound. We propose NAD+ boosters to treat social deficits of early life stress origin.

2022

Machine learning-derived gut microbiome signature predicts fatty liver disease in the presence of insulin resistance

Johan Auwerx, Dongryeol Ryu

A simple predictive biomarker for fatty liver disease is required for individuals with insulin resistance. Here, we developed a supervised machine learning-based classifier for fatty liver disease using fecal 16S rDNA sequencing data. Based on the Kangbuk Samsung Hospital cohort (n = 777), we generated a random forest classifier to predict fatty liver diseases in individuals with or without insulin resistance (n = 166 and n = 611, respectively). The model performance was evaluated based on metrics, including accuracy, area under receiver operating curve (AUROC), kappa, and F1-score. The developed classifier for fatty liver diseases performed better in individuals with insulin resistance (AUROC = 0.77). We further optimized the classifiers using genetic algorithm. The improved classifier for insulin resistance, consisting of ten microbial genera, presented an advanced classification (AUROC = 0.93), whereas the improved classifier for insulin-sensitive individuals failed to distinguish participants with fatty liver diseases from the healthy. The classifier for individuals with insulin resistance was comparable or superior to previous methods predicting fatty liver diseases (accuracy = 0.83, kappa = 0.50, F1-score = 0.89), such as the fatty liver index. We identified the ten genera as a core set from the human gut microbiome, which could be a diagnostic biomarker of fatty liver diseases for insulin resistant individuals. Collectively, these findings indicate that the machine learning classifier for fatty liver diseases in the presence of insulin resistance is comparable or superior to commonly used methods.

NATURE PORTFOLIO2022

Non-genomic activation of the AKT-mTOR pathway by the mitochondrial stress response in thyroid cancer

Johan Auwerx, Dongryeol Ryu, Kristina Schoonjans

Cancer progression is associated with metabolic reprogramming and causes significant intracellular stress; however, the mechanisms that link cellular stress and growth signalling are not fully understood. Here, we identified a mechanism that couples the mitochondrial stress response (MSR) with tumour progression. We demonstrated that the MSR is activated in a significant proportion of human thyroid cancers via the upregulation of heat shock protein D family members and the mitokine, growth differentiation factor 15. Our study also revealed that MSR triggered AKT/S6K signalling by activating mTORC2 via activating transcription factor 4/sestrin 2 activation whilst promoting leucine transporter and nutrient-induced mTORC1 activation. Importantly, we found that an increase in (mt)DNA played an essential role in MSR-induced mTOR activation and that crosstalk between MYC and MSR potentiated mTOR activation. Together, these findings suggest that the MSR could be a predictive marker for aggressive human thyroid cancer as well as a useful therapeutic target.

SPRINGERNATURE2022