Profile
I am a genetic epidemiologist with an interest in precision medicine for cardiometabolic conditions across diverse populations. My research focusses on comparisons across ancestries, with a particular focus on south Asian populations. My group uses genetics and multi-omics methods to understand the heterogenous presentation of type 2 diabetes in south Asians, particularly the presentation of young onset diabetes. At QMUL, I work closely with the Genes & Health cohort of British Bangladeshis and Pakistanis in East London.
Previously, I was Principal Investigator in precision medicine at the University of Dundee, where I also led research in pharmacogenetics and type 2 diabetes. I am co-investigator of the India-Scotland Partnership for Precision Medicine in Diabetes (INSPIRED), a cohort based in south India.
At QMUL, I work in the Clinical Effectiveness Group as part of the Precision Medicine Part 2 program funded by Barts Charity. I serve as Associate Director of the Health Data in Practice PhD programme. I am a Fellow of the Digital Environment Research Institute (DERI) where I am helping to develop cross-disciplinary translational clinical research.
External roles include:
Member the Diabetes UK Steering Group on Causes of Diabetes.
Honorary consulting scientist at the Madras Diabetes Research Foundation (MDRF) headquartered in Chennai India
Honorary Lecturer on Population Health and Genomics at the University of Dundee.
Research
Research Interests:
Genetic epidemiology of type 2 diabetes in south Asian populations; diverse populations; young and lean onset T2D; precision medicine; multi-omics to study disease aetiology.
Publications
Please click through to see a complete list of Moneeza's publications
Siddiqui, M.K., Anjana, R.M., Dawed, A.Y. et al. Young-onset diabetes in Asian Indians is associated with lower measured and genetically determined beta cell function. Diabetologia 65, 973–983 (2022). https://doi.org/10.1007/s00125-022-05671-z
Sundararajan Srinivasan, Samuel Liju, Natarajan Sathish, Moneeza K. Siddiqui, Ranjit Mohan Anjana, Ewan R. Pearson, Alexander S.F. Doney, Viswanathan Mohan, Venkatesan Radha, Colin N.A. Palmer; Common and Distinct Genetic Architecture of Age at Diagnosis of Diabetes in South Indian and European Populations. Diabetes Care 1 August 2023; 46 (8): 1515–1523. https://doi.org/10.2337/dc23-0243
Anjana RM, Baskar V, Nair ATN, et al. Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study BMJ Open Diabetes Research and Care 2020;8:e001506. doi: 10.1136/bmjdrc-2020-001506
Margherita Bigossi, Cyrielle Maroteau, Adem Y Dawed, Alasdair Taylor, Sundararajan Srinivasan, Alaa’ Lufti Melhem, Ewan R Pearson, Roberto Pola, Colin N A Palmer, Moneeza K Siddiqui, A gene risk score using missense variants in SLCO1B1 is associated with earlier onset statin intolerance, European Heart Journal - Cardiovascular Pharmacotherapy, Volume 9, Issue 6, September 2023, Pages 536–545, https://doi.org/10.1093/ehjcvp/pvad040
Moneeza K Siddiqui, Cyrielle Maroteau, Abirami Veluchamy, Aleksi Tornio, Roger Tavendale, Fiona Carr, Ngu-Uma Abelega, Dan Carr, Katyrzyna Bloch, Par Hallberg, Qun-Ying Yue, Ewan R Pearson, Helen M Colhoun, Andrew D Morris, Eleanor Dow, Jacob George, Munir Pirmohamed, Paul M Ridker, Alex S F Doney, Ana Alfirevic, Mia Wadelius, Anke-Hilse Maitland-van der Zee, Daniel I Chasman, Colin N A Palmer, PREDICTION-ADR Consortium, A common missense variant of LILRB5 is associated with statin intolerance and myalgia, European Heart Journal, Volume 38, Issue 48, 21 December 2017, Pages 3569–3575, https://doi.org/10.1093/eurheartj/ehx467
Moneeza K. Siddiqui, Christopher Hall, Scott G. Cunningham, Rory McCrimmon, Andrew Morris, Graham P. Leese, Ewan R. Pearson; Using Data to Improve the Management of Diabetes: The Tayside Experience. Diabetes Care 1 December 2022; 45 (12): 2828–2837. https://doi.org/10.2337/dci22-0003
Supervision
Binur Orazumbekova, Wellcome Trust, Ethnic variations in risk trajectories for type 2 diabetes: an observational research study combining genetic, cohort, and electronic health record data in the UK.
