Dr. Nicholas Gleadall
Assistant Professor, Department of Haematology
Email: ng384@cam.ac.uk
LinkedIn: https://www.linkedin.com/in/nicholas-gleadall-b2b833119/
Mastodon/other social media:
Biography :
Nick is an Assistant Professor in the Department of Haematology at the University of Cambridge. He holds honorary appointments with Cambridge University Hospitals, University College London Hospitals and NHS Blood and Transplant. He is also a founding member and chief analyst of the Blood Transfusion Genomics Consortium and a founding member and principal investigator of the BloodCounts! consortium.
Research Approach:
I am interested in the development and application of computational and statistical methods for using large-scale genomics and electronic healthcare record (EHR) data to answer research questions, which ultimately may lead to improvements in care for patients. My recent focus has been on: i) The development and accreditation of a DNA microarray-based test for genotyping Erythrocyte (HEA, or blood group), Platelet (HPA) and Leukocyte (HLA) antigens in donors and patients at scale, ii) Using large scale genomics data to investigate the genetic basis of alloimmunisation and antibody production, iii) Detection of infectious disease outbreaks and other diseases using machine learning and population scale full blood count data.
Current projects:
The Blood Transfusion Genomics Consortium (https://www.bgc.io) – An international project which aims to improve the safety and efficiency of blood and platelet transfusion by development and international accreditation of a DNA microarray-based test capable of typing HEA, HPA and HLA to diagnostic standard. As part of the project genotyping infrastructure has been successfully installed into the clinical laboratories of NHS Blood and Transplant (London, UK), The New York Blood Centre (NY, USA) and Sanquin (Amsterdam, NL) and validation of the technology is being carried out via in-triplicate genotyping of 16,000 DNA samples from blood donors submitted by seven blood services. Results from this study will be submitted to international regulators for approval to label blood cell concentrates using antigen typing results produced by the test.
HaemMatch (https://www.haemmatch.co.uk) – A project which aims to use machine learning and at-scale blood genotyping data from patients and donors to improve transfusion outcomes for patients and optimise the logistics of blood delivery. The project will culminate in a proof of principle study in which blood will be transfused to individuals with sickle cell disorder based on genotype data.
BloodCounts! (https://www.bloodcounts.org) – Machine learning-based analysis of full blood count data for detection of infectious disease outbreaks at population level, in a pathogen-agnostic manner and quantitative interpretation of results at individual level for diagnostic decision support in a range of other diseases.
Genome-Wide Association Studies – AIR: a case-control GWAS to investigate the genetic basis of alloimmunisation against HEA antigens during pregnancy. Anti-A/B: A GWAS to investigate the genetic basis of anti-A and anti-B levels in blood donors enrolled in the INTERVAL, COMPARE and STRIDES NIHR BioResource donor health studies.
Selected Publications
- Development and validation of a universal blood donor genotyping platform: a multinational prospective study. Gleadall NS, Veldhuisen B, Gollub J, Butterworth AS, Ord J, Penkett CJ, Timmer TC, Sauer CM, van der Bolt N, Brown C, Brugger K, Dilthey AT, Duarte D, Grimsley S, van den Hurk K, Jongerius JM, Luken J, Megy K, Miflin G, Nelson CS, Prinsze FJ, Sambrook J, Simeoni I, Sweeting M, Thornton N, Trompeter S, Tuna S, Varma R, Walker MR; NIHR BioResource; Danesh J, Roberts DJ, Ouwehand WH, Stirrups KE, Rendon A, Westhoff CM, Di Angelantonio E, van der Schoot CE, Astle WJ, Watkins NA, Lane WJ.
- Multiple GYPB gene deletions associated with the U- phenotype in those of African ancestry. Lane WJ, Gleadall NS, Aeschlimann J, Vege S, Sanchis-Juan A, Stephens J, Sullivan JC, Mah HH, Aguad M, Smeland-Wagman R, Lebo MS, Vijay Kumar PK, Kaufman RM, Green RC, Ouwehand WH, Westhoff CM
- Automated typing of red blood cell and platelet antigens: a whole-genome sequencing study. Lane WJ, Westhoff CM, Gleadall NS, Aguad M, Smeland-Wagman R, Vege S, Simmons DP, Mah HH, Lebo MS, Walter K, Soranzo N, Di Angelantonio E, Danesh J, Roberts DJ, Watkins NA, Ouwehand WH, Butterworth AS, Kaufman RM, Rehm HL, Silberstein LE, Green RC; MedSeq Project. Lancet Haematol. 2018 Jun;5(6):e241-e251. doi: 10.1016/S2352-3026(18)30053-X. Epub 2018 May 17.
