An integrative multi-omics approach to targeting cellular senescence as a drug repurposing strategy for age-related morbidities

Summary

Age is a major risk factor for various human diseases including cancers, dementia, and cardiovascular diseases. Senescence is a process where cells cease dividing and undergo distinctive phenotypic changes. Senescence has a key role in the aging process and has also been implicated as a major cause of age-related disease. The recent COVID-19 pandemic also clearly showed that age is a prominent risk factor for the severity of the disease.  Indeed SARS-CoV-2 induced senescence is not only a driver but also a therapeutic target in COVID-19. Targeting cellular senescence could potentially alleviate many age-related pathologies.

In this project, we aim to identify therapeutic candidates that could selectively eliminate senescent cells. Such drugs are often referred to as senolytics, which could contribute to the treatment of specific age-related diseases, and potentially could also improve the life and health span of aged individuals.  We propose to deploy an integrative multi-omics connectivity mapping approach to targeting cellular senescence as a drug repurposing strategy for potential applications in age-related diseases.

Our team have extensive experience and expertise in applying this data-intensive approach to several human diseases, with a catalogue of successes, in cancer [Ramsey et al2013; Wen et al2016] and cystic fibrosis [Malcomson et al 2016,PNAS]. Our innovations include a robust framework for gene expression connectivity mapping, a similarity metric ‘ZhangScore’ with superior performance [De Wolf et al 2018,PMID:29658791], and a series of computational techniques for constructing disease query gene signatures, e.g. gene signature perturbation (McArt&Zhang2011), gene signature progression (Wen et al2016), and related software tools including sscMap (Zhang&Gant2009), cudaMap (McArt et al2013) and QUADrATiC (O'Reilly et al2016). New combinations of these innovative elements and their novel applications to senescence and aging as a new area represents a big step forward in our methodological innovation and drug repurposing research.

Objectives of the research

The objectives of the research include:

1) Integration of multiple streams and categories of data in public data repositories from cellular senescence and aging related studies, as well as in-house multi-omics datasets including WGS, proteomics, and transcriptomics for 500 COVID-19 patients.

2) Construction of robust gene signatures for cellular senescence based on the integrative analysis of the multi-omics datasets.

3) Application of our established gene expression connectivity mapping framework to computationally screen a collection of over 1500 approved drugs for the identification of senolytics candidates.

Methods to be used

This is primarily a desk-based computational and bioinformatics project. The datasets to be used for integrative analysis are either from public data repositories or have already been generated in the labs of the supervisory teams.  Successful completion of this project will lay the solid foundation for a future lab-based experimental project to validate the computational findings. Bioinformatics methodology to be employed includes differential expression analysis of transcriptomics and proteomics data; Seed gene-based expression correlation analysis using known senescence genes as the seeds; Gene network and functional enrichment analysis; Gene expression connectivity mapping for computational drug screening.

Skills required of applicant

This is mainly a computational project involving the use of the state-of-art bioinformatics techniques in the processing and analysis of multi-omics datasets. The student will gain valuable exposure to basic statistics ideas as well as to useful computing techniques and tools, which are becoming increasing important for biomedical scientists in personalised medicine research.

The student is expected to have:

1.         An understanding of basic statistics ideas.

2.         Good IT skills in working with common Spreadsheet Applications, eg MS Excel

3.         Some experience with a programming language is required, preferably R or Python.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Experience using research methods or other approaches relevant to the subject domain
• A comprehensive and articulate personal statement
• A demonstrable interest in the research area associated with the studentship

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Use of personal initiative as evidenced by record of work above that normally expected at career stage.
• Applicants will be shortlisted if they have an average of 75% or greater in a first (honours) degree (or a GPA of 8.75/10). For applicants with a first degree average in the range of 70% to 74% (GPA 3.3): If they are undertaking an Masters, then the average of their first degree marks and their Masters marks will be used for shortlisting.
• Relevant professional qualification and/or a Degree in a Health or Health related area

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility