Molecular aging in the Rasmussen Group

The Rasmussen Group explores the interaction between the hallmarks of aging: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication.

Molecular aging in the Rasmussen Group

Research focus

The Rasmussen Group seeks to understand the interconnectedness between the hallmarks of aging and their relative contributions to aging. Our goal is to identify pharmaceutical targets to improve human health during aging.

The correct functioning of these processes is important for avoiding many life-threatening pathologies that can arise because of genetic changes. However, a comprehensive understanding of the scope, dynamics and functions of these complex biological responses is lacking. A particular focus of the group is to elucidate how signaling by unrepaired DNA damage and replication stress promote and regulate mitochondrial function.

“We provide advanced molecular insights into the interplay between cellular pathways that protect against accelerated aging, which is of strong relevance for the design of better treatment strategies for age-related disorders”, says Professor and Group Leader Lene Juel Rasmussen.

The group is excellently positioned to address this challenge due to its expertise in dissection of cellular signaling mechanisms by means of cell biology-, biochemistry- and microscopy-driven approaches. We collaborate with leading experts in human physiology, model organisms and neuroscience, and employ innovative strategies to illuminate the molecular mechanisms promoting healthy aging on both a systems-wide and mechanistic level.

Main findings

In 2000, our group identified the enzyme exonuclease 1 (EXO1) as a novel component of the human MMR pathway. Our subsequent studies on human EXO1 helped elucidate the molecular mechanism of human MMR and provided insight into the role of MMR defects in human cancer (Liu et al., 2017; Keijzers et al., 2016; Liberti et al., 2011; Knudsen et al., 2007; Nielsen et al., 2004; Jäger et al., 2001; Drost et al., 2013; Thompson et al., 2014; Drost et al., 2018).

Recently, we have shown, for the first time, that replication stress caused by Rev1-deficiency causes mitochondrial dysfunction and this can be reversed by NR supplementation (Fakouri et al., 2017; Martín-Pardillos et al., 2017). A finding that provides valuable insight into mechanisms of human aging and could lead in future to novel therapies for clinically-relevant human diseases.

Selected projects

The hallmarks of aging

Nordea-fonden supports a research program on molecular aging that aims to understand the interconnectedness between the hallmarks of aging and their relative contributions to aging, with the final goal of identifying pharmaceutical targets to improve human health during aging.

Role of mitochondrial dysfunction in Alzheimer's Disease: a search for therapeutic strategies

The Olav Thon Foundation has granted money to research on how to explain why defects in DNA repair, and resulting cellular oxidative stress and mitochondrial dysfunction are primary molecular mechanisms in late onset sporadic Alzheimer’s (AD). The study will improve our understanding of the molecular basis of AD, laying the groundwork for effective treatment and/or prevention of AD.

Harnessing the power of Big Data to address the societal challenge of aging

The Novonordisk Foundation has granted money to support a program that (i) delivers novel methods to make optimal use of the available big data across three foci of research, (ii) performs analyses to enhance our ability to explain and predict trajectories of aging and health, and (iii) trains a cadre of physicians, statisticians and life science researchers in the use of big data in biomedicine. To do so, we integrate the systematic exploration of population data with a comprehensive interrogation of biological samples, complemented by experimental validation of data-driven explanatory models.