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Elucidating and targeting the mechanisms encoded in the genome of long-lived individuals to improve healthy ageing

Objective

Advancing age is the major risk factor for many serious illnesses, including cancer, cardiovascular disease, and dementia. The rising number of older individuals is thus causing a major burden of ill health. However, individuals that reach an exceptional old age often seem to escape or delay age-related diseases, and part of this trait seems to be encoded in their genome. Hence, by studying the genome of long-lived individuals, we may be able to identify mechanisms that could be targeted for healthy ageing in the general population. My previous work suggests that large genome-wide association studies (GWAS) of long-lived individuals can be used to identify genetic variants involved in longevity. However, the common genetic variants thus far identified using GWAS only explain a minor part of the genetic component of longevity. This trait, therefore, may well be mainly determined by rare genetic variants, which can be detected using whole-genome or exome sequencing of long-lived families or exceptionally long-lived individuals. The aim of the proposed project is to establish the effect of genetic variants identified in genetic studies of long-lived individuals on general health and lifespan using cellular models and, subsequently, model organisms. To this end, I will use CRISPR/Cas9 gene editing to generate transgenic cell lines and mice that harbour genetic variants in candidate genes and pathways identified through GWAS and sequencing studies of long-lived families and individuals. I will subsequently use this information to create a high-throughput screening assay to identify compounds that can pharmacologically recapitulate the observed in vitro effects. As a proof-of-principle, I will start with functional characterisation of rare variants in genes involved in insulin/insulin-like growth factor 1 (IIS) and mammalian target of rapamycin (mTOR) signalling, given the well-known role of these networks in ageing in pre-clinical model organisms.

Coordinator

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Net EU contribution
€ 1 500 000,00
Address
Hofgartenstrasse 8
80539 Munchen
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Research Organisations
Non-EU contribution
€ 0,00