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Professor Damian Smedley

Damian

Professor of Computational Genomics

Centre: Clinical Pharmacology and Precision Medicine

Email: d.smedley@qmul.ac.uk
Website: https://whri-phenogenomics.github.io/index.html

Profile

Professor Smedley’s research focusses on utilising clinical and model organism phenotype data to better understand human disease.

As a principal investigator for the International Mouse Phenotyping Consortium (IMPC), his team analyses the genotype to phenotype associations emerging from this comprehensive effort to produce the first catalogue of mammalian gene function by knocking out and systematically phenotyping every protein-coding gene in the mouse. A similar approach is taken in human cellular systems as a PI in the Molecular phenotypes of null alleles in cells (MorPhic) project. Utilising phenotype comparison methods developed with his co-PIs in the Monarch Initiative, his team is able to automatically identify new animal models of known disease genes as well as suggest new candidates for diseases where the causative variants have not yet been identified in human. 

This work is extended upon in the Exomiser software package, also developed in conjunction with his collaborators in the Monarch Initiative. Exomiser automates the filtering and prioritisation of coding and non-coding variants called from whole exome or genome sequencing of rare disease families using novel methodologies to prioritise the genes based on the similarity of the patient’s phenotypes to reference knowledge of genotype to phenotype associations from human disease and animal models. This software is widely used by academic researchers, diagnostic laboratories, commercial offering and in large-scale disease sequencing projects such as the US Undiagnosed Disease Network, the UK’s 100,000 Genomes Project as well as being a key component of the ISO-accredited interpretation pipeline for the NHS Genomic Medicine Service.

The team is contributing to a better understanding of the role of missense variants and post-translational modifications in rare disease as part of the MRC-funded human functional genomics initiative. Finally, as part of the Horizon Europe funded NextGen grant the team investigates federated machine learning approaches on multiomics data.

Research

Group members

  • Julius Jacobsen, Pilar Cacheiro, Valentina Cipriani, Letizia Vestito, Yasemin Bridges, Gabriel Marengo, Diego Pava, Krishna Amin

Summary 

Professor Smedley’s research focusses on utilising clinical and model organism phenotype data to better understand human disease.

As a principal investigator for the International Mouse Phenotyping Consortium (IMPC), his team analyses the genotype to phenotype associations emerging from this comprehensive effort to produce the first catalogue of mammalian gene function by knocking out and systematically phenotyping every protein-coding gene in the mouse. Utilising phenotype comparison methods developed with his co-PIs in the Monarch Initiative, his team is able to automatically identify new animal models of known disease genes as well as suggest new candidates for diseases where the causative variants have not yet been identified in human. 

This work is extended upon in the Exomiser software package, also developed in conjunction with his collaborators in the Monarch Initiative. Exomiser automates the filtering and prioritisation of coding and non-coding variants called from whole exome or genome sequencing of rare disease families using novel methodologies to prioritise the genes based on the similarity of the patient’s phenotypes to reference knowledge of genotype to phenotype associations from human disease and animal models. This software is widely used by academic researchers, diagnostic laboratories, commercial offering and in large-scale disease sequencing projects such as the US Undiagnosed Disease Network, the UK’s 100,000 Genomes Project as well as being a key component of the ISO-accredited interpretation pipeline for the NHS Genomic Medicine Service.

Publications

  • Lord J, Pagnamenta AT, Vestito L et al. (publicationYear). Blood-based RNA-Seq of 5412 individuals with rare disease identifies new candidate diagnoses in the National Genomic Research Library. nameOfConference


    QMRO: qmroHref
  • Reese JT, Chimirri L, Bridges Y et al. (2026). Systematic benchmarking demonstrates large language models have not reached the diagnostic accuracy of traditional rare-disease decision support tools. nameOfConference


    QMRO: qmroHref
  • Welch CL, McEntagart M, Moledina S et al. (2026). Expanding the phenotypic spectrum of MECOM-associated syndrome: rare variants are associated with syndromic pulmonary arterial hypertension. nameOfConference


    QMRO: qmroHref
  • Rekerle L, Danis D, Rehburg F et al. (2026). GA4GH phenopacket-driven characterization of genotype-phenotype correlations in Mendelian disorders. nameOfConference


  • Hough SH, Jhujh SS, Awwad SW et al. (2026). Loss of CTLH component MAEA impairs DNA repair and replication and leads to developmental delay. nameOfConference


  • Magavern EF, Marengo G, Megase M et al. (publicationYear). Family health history and pharmacogenomics show cross generation premature amitriptyline discontinuation is associated with CYP2C19 loss of-function enrichment. nameOfConference


  • Wilson R, Ataç TB, Cheng TK et al. (2026). International Mouse Phenotyping Consortium Portal: facilitating investigation of gene function and providing insights into human disease. nameOfConference


  • Apti E, Nicholls H, Jacobsen J et al. (2025). Genetic and drug repurposing insights into hypertrophic cardiomyopathy: a machine learning approach. nameOfConference


    QMRO: qmroHref
  • Shefchek K, Ziniel SI, McMurry JA et al. (2025). Development of self-phenotyping tools to empower patients and improve diagnostics. nameOfConference


  • Vasilevsky NA, Toro S, Matentzoglu N et al. (2026). Mondo: integrating disease terminology across communities. nameOfConference


View profile publication page

Sponsors

Collaborators

Internal

External

  • Prof Peter Robinson (Berlin Institute of Health, Germany)
  • Dr. Chris Mungall (Lawrence Berkeley National Laboratory, USA)
  • Prof. Melissa Haendel (University of Carolina, Chapel Hill, USA)
  • Dr. Helen Parkinson (EBI, UK)
  • Dr. James McLaughlin (EBI, UK)
  • Prof. Stephan Schürer (University of Miami, USA)
  • Prof. Ka Yee Yeung (University of Washington, USA)
  • Prof. Francesca Mangili (SUPSI, Switzerland)
  • Dr. Anwar Chahal (WellSpan Health)
  • Prof. Hannah Mitchinson (UCL, UK)
  • Prof. Caroline Wright (University of Exeter, UK)
  • Dr. Matthew Child (Imperial College, UK)

News

100,000 Genomes Project paper publication press (Nov 2021):

Teaching

 Undergraduate Education:

  • MBBS: OSCE examiner; PBL facilitator

Postgraduate Education:

  • MSc Genomic Medicine: Lecturer; Project supervisor
  • BHF MRes: Lecturer
  • MSc Bioinformatics: Project supervisor
  • PhD supervisor: Non-clinical (AIDD)
  • PhD examiner

External Education Activities:

  • Kings College London: Lecturer MSc Genomic Medicine
  • University of Manchester: External examiner
  • PhD examiner

Disclosures

No disclosures

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