1. Research Background:

Advancing age is the major risk factor for many chronic diseases. Instead of tackling each of these diseases one by one, we should focus on the identification of shared mechanisms that compress multimorbidity and thereby contribute to healthy ageing.

In our group, we use two different approaches to find out why some people age more healthily than others. The first approach is aimed at elucidating the genetic mechanisms underlying healthy ageing and extended lifespan in humans. The second approach is the identification of biomarkers of ageing that can subsequently be used as surrogate endpoints in clinical trials or intervention studies that are aimed at improving general health.

2. Research questions addresses by the group:

One of the main aims of our research group is to study the functional effect of common genetic variants (identified using large-scale genetic association studies of healthy ageing) (Timmers et al. Nature Communications 2020) and rare protein- altering genetic variants (identified using sequencing data of long-lived individuals). To this end, we make use of the CRISPR/Cas9 system to generate transgenic cell lines and animals harbouring the variants in question. We subsequently measure the in vitro (mouse embryonic stem cells) and in vivo (mice) effects of the genetic variants on the functioning of the genes (Baghdadi, Hinterding et al. Brief Funct Genomics 2021 / Hinterding et al. bioRxiv 2023). This work is supported by both an ERC Starting Grant and a Longevity Impetus Grant.

Another main aim of our research group is to establish novel human ageing studies in Cologne to determine the efficacy of previously reported biomarkers of ageing in clinical studies. The main focus is on biomarkers that have been identified in large- scale international collaborations of human studies using omics-based approaches, such as metabolomics (Deelen et al. Nature Communications 2019). In addition, we include biomarkers originating from studies in model organisms to determine their translatability.

3. Possible projects:

The possible project will be based on the first aim of our group; functional characterisation of genetic variants. We have already generated several omics datasets, i.e. transcriptomics and proteomics, based on our transgenic mESCs, which we plan to extend with datasets of various relevant tissues of the corresponding transgenic mouse lines at different time points and for both sexes. We want to use these datasets to identify interesting genes/proteins to focus on in our follow-up wet-lab experiments. Moreover, we would like to revisit published genetic datasets to identify novel genes/pathways to focus on for our in vitro functional characterisation. The PhD student will likely also be involved in one or multiple side projects related to the second aim of our group, i.e. identification and validation of biomarkers of ageing.

The exact content of the PhD project is open for discussion to match the candidate’s interests and skills. The PhD project will be bioinformatic-based, but can be combined with a wet-lab part.

4. Applied Methods and model organisms:

For our research on the functional effects of genetic variants, we currently use both cellular models and mice. We use a wide variety of methodologies to generate and characterise the transgenic cell lines/mice harbouring our genetic variants of interest, including:

• CRISPR/Cas9-based gene editing
• Mammalian cell culture
• FACS
• State-of-the-art molecular biology and biochemistry
• Viability assays
• Mouse metabolic phenotyping
• Bioinformatics (transcriptomics and proteomics)

5. Desirable skills and qualifications:

We seek a creative and highly motivated young scientist to join our small, enthusiastic, and collaborative research group. Experience in bioinformatics is expected, while experience with wet-lab techniques is desirable, but not required.

6. References:

• Baghdadi M, Hinterding HM, Partridge L, Deelen J. From mutation to mechanism: deciphering the molecular function of genetic variants linked to human ageing. Brief Funct Genomics 21:13-23, doi: 10.1093/bfgp/elab005 (2022).
• Deelen J, Kettunen J, Fischer K, van der Spek A, Trompet S, Kastenmüller G, Boyd A, Zierer J, van denAkker EB, Ala-Korpela M, Amin N, Demirkan A, Ghanbari M, van Heemst D, Ikram MA, van Klinken JB, Mooijaart SP, Peters A, Salomaa V, Sattar N, Spector TD, Tiemeier H, Verhoeven A, Waldenberger M, Würtz P, Davey Smith G, Metspalu A, Perola M, Menni C, Geleijnse JM, Drenos F, Beekman M, Jukema JW, van Duijn CM, Slagboom PE. A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals. Nat Commun 10:3346, doi: 10.1038/s41467-019-11311-9 (2019).
• Hinterding H, Baghdadi M, Gehrmann T, Putter P, Lakenberg N, van den Akker EB, Slagboom PE, Deelen J, Partridge L. Functional characterisation of rare variants in genes encoding the MAPK/ERK signalling pathway identified in long-lived Leiden Longevity Study participants. bioRxiv, doi: 10.1101/2023.06.01.541708 (2023).
• Timmers PRHJ, Wilson JF, Joshi PK, Deelen J. Multivariate genomic scan implicates novel loci and haem metabolism in human ageing. Nat Commun 11:3570, doi: 10.1038/s41467-020-17312-3 (2020).