Dr Eirini Marouli

Profile

Dr Eirini Marouli is a Reader in Computational Biology at the William Harvey Research Institute, Queen Mary University of London. Dr Marouli’s research interests lie in the interface of genetics, bioinformatics and artificial intelligence. She has developed a BBC Documentary Reel on Adult height. 

Dr Marouli is the Deputy Lead for the MSc Genomic Medicine, WHRI Post-Graduate Taught Course (PGT) Lead and Deputy Equality Diversity and Inclusion (EDI) Academic Lead, and Fellow at the Digital Environment Research Institute (DERI).

Dr Marouli boasts coherent and multidisciplinary research experience with high quality outputs across her research career. She has leading work in international consortia, working on cutting-edge research on complex traits and disease, thyroid function and thyroid cancer.

She graduated with a BSc in Biology and a MSc in Clinical Biochemistry from the University of Athens, Greece. Dr Marouli was awarded a PhD in Genetics from the University of Athens studying the genetic overlap between type 2 diabetes and psychiatric disease. Eirini joined the William Harvey Research Institute in July 2014, as a Greek State Scholarships Foundation Fellow. She completed her postdoctoral training with Professor Panos Deloukas. During this period, she had a leading role in the GIANT (Genetic Investigation of Anthropometric Traits) consortium, investigating the role of rare and low-frequency coding variants in human adult height (Marouli et al., Nature 2017).

She is running the Book Club at QMUL, focusing on topics related to Equality, Diversity, Inclusion and Mental Health.

Awards

• Early Career Researcher of the Year – UK Biobank 2019 meeting
• Nomination: American Society of Human Genetic’s Trainee Paper Spotlight 2018, for the paper: “Rare and low-frequency coding variants alter human adult height", Nature, 2017
• 2016 ASHG/Charles J. Epstein Trainee Award for Excellence in Human Genetics Research -Semifinalist
• The Genomics of Common Diseases congress, 2015, Wellcome Genome Campus, Hinxton, Cambridge (Travel Grant)

Find me on: 

• Researchgate
• Google Scholar
• ORCID ID: 0000-0001-6179-1609
• LinkedIn

Research

Dr Marouli brings multi-disciplinary expertise involving her excellent background in both laboratory skills and bioinformatics expertise encompassing the biology of the thyroid gland and cancer, along with big data and multi-modal data analysis incorporating genetics. Dr Marouli’s leadership skills are reflected in the successful management of international projects and collaborations. Her work focuses on using human genetics to identify genes that influence common diseases and quantitative traits, including height and adiposity. Dr Marouli implements novel computational methods, including machine learning, to gain biological insights from human genetics and phenotypic data.

She has a leading role in the large international consortium (GIANT) that has discovered almost all of the genetic variants that are known to influence human height and obesity related traits. She also has leading role in projects collaborating with ThyroidOMICS consortium working on cutting-edge research on thyroid function. Dr Marouli specialises on the genetics of thyroid function and disease. Her recent work integrates the use of genetic data and a battery of state-of-the-art approaches, for causal inference and mendelian randomisation and machine learning to elucidate the genetic interplay between risk factors and disease. Dr Marouli has also leading work and contributions in global consortia (GLGC, CHARGE CARDIoGRAMplusC4D) for complex traits and diseases. In addition to gene discovery efforts, Dr Marouli is also interested in genetic-epigenetic approaches to complex phenotypes.

Publications

• Richard D, Muthuirulan P, Young M et al. (2024). Functional genomics of human skeletal development and the patterning of height heritability.

  
  

  DOI: 10.1016/j.cell.2024.10.040

  
  

  QMRO:
• Ellervik C, Boulakh L, Teumer A et al. (2024). Thyroid Function, Diabetes, and Common Age-Related Eye Diseases: A Mendelian Randomization Study.

  
  

  DOI: 10.1089/thy.2024.0257

  
  

  QMRO:
• Papadopoulou A, Harding D, Slabaugh G et al. (2024). Prediction of atrial fibrillation and stroke using machine learning models in UK Biobank.

  
  

  DOI: 10.1016/j.heliyon.2024.e28034

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/95921
• Babajide O, Kjaergaard AD, Deng W et al. . The role of thyroid function in borderline personality disorder and schizophrenia: a Mendelian Randomisation study.

  
  

  DOI: 10.1186/s40479-024-00246-3

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/95724
• Sterenborg RBTM, Steinbrenner I, Li Y et al. . Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications.

  
  

  DOI: 10.1038/s41467-024-44701-9

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/95973
• Slabaugh G, Beltran L, Rizvi H et al. . Applications of machine and deep learning to thyroid cytology and histopathology: a review.

  
  

  DOI: 10.3389/fonc.2023.958310

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/94545
• Papadopoulou A, Åsvold BO, Burgess S et al. (2023). Height, Autoimmune Thyroid Disease, and Thyroid Cancer: A Mendelian Randomization Study.

  
  

  DOI: 10.1089/thy.2023.0272

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/93832
• Willems SM, Ng NHJ, Fernandez J et al. . Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization.

  
  

  DOI: 10.12688/wellcomeopenres.18754.1

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/103110
• Hawkes G, Yengo L, Vedantam S et al. . Identification and analysis of individuals who deviate from their genetically-predicted phenotype.

  
  

  DOI: 10.1371/journal.pgen.1010934

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/93824
• L Y, S V, E M et al. . A saturated map of common genetic variants associated with human height.

  
  

  DOI: 10.1530/ey.20.3.16

  
  

  QMRO:

Collaborators

Internal

• Panos Deloukas
• Patricia Munroe
• Greg Slabaugh
• Federica Marelli-Berg
• Julia Ramirez
• Simon Lucas
• Jane Batchelor
• Márta Korbonits
• Daniel Harding

External

• GIANT consortium collaborators
• ThyroidOMICS consortium collaborators: Joel Hirschhorn (Harvard); Tim Frayling (Exeter); Zoltan Kutalik (Switzerland); Adam E. Locke (Washington University); Sailaja Vedantam (Harvard); Loïc Yengo (University of Queensland); Marco Medici (Erasmus; The Netherlands); Aleksander Kus (Poland); Alexander Teumer (Germany); Sonja Berndt (NIH)

News

• Why are the dutch so tall? (BBC Documentary Reel)
• Mild Thyroid variation may predict stroke risk (Healio.com)
• Poor lung function in shorter people linked to increased risk of heart disease (MedicalResearch.com)
• Researchers Find New Genetic Variants that Influence Human Adult Height (sci-news.com)
• Trainee Paper Spotlight 2018 (Ashg.org)