Academic Profile

Assistant Professor Sarah R Langley
Nanyang Assistant Professor
Principal Investigator, Integrative Biology of Disease


Assistant Professor Sarah Raye Langley is a Nanyang Assistant Professor in Lee Kong Chian School of Medicine, Nanyang Technological University, and an awardee of the 2018 Nanyang Assistant Professorship. She obtained her PhD in Bioinformatics and Statistical Genetics and her MSc in Bioinformatics and Theoretical Systems Biology from Imperial College London and her BA in Physics and Mathematical Sciences from Colby College. Prior to joining the Lee Kong Chian School of Medicine, she worked in the areas of systems genetics and genomics at Duke-NUS Medical School and Imperial College London and in the area of vascular proteomics at the BHF Centre of Excellence, King’s College London.

Asst. Prof. Langley is a computational biologist whose research focuses on using large-scale omics data to understand dysregulated transcriptional and translational processes in human disease, with a focus on neurological and cardiometabolic disorders. She has contributed to more than 30 publications in journals such as JCI, Nature Neuroscience, and Nature and is involved in several international and domestic collaborations.
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Asst Prof Sarah Raye Langley
Nanyang Assistant Professor, Lee Kong Chian School of Medicine

Research Focus

We use a combination of high-throughput omics data to study dysregulated transcriptional and translational processes in human disease. The lab has a focus on neurological disorders (e.g. Huntington disease, Alzheimer’s disease, epilepsy) but also works in the areas of cardiovascular and metabolic disease (atherosclerosis, hypertension, diabetes). There are three broad areas of investigation - disease mechanisms, pharmaco -genomics and -transcriptomics, and computational methods development.

Disease mechanisms

To investigate disease mechanisms and dysregulated molecular processes, we utilize large scale omics datasets – primarily DNA- and RNA-sequencing and mass spectrometry proteomics –coupled with cutting edge analytical techniques. By integrating these different omics datasets in systems-level approach, we aim to interrogate the role that molecular processes play in the development and progression of human disease.

Pharmaco-genomics and -transcriptomics

We investigate the interactions between molecular phenotypes and small molecule/drug perturbations through the use of genetic-drug response association studies and large-scale transcriptomic screens. By elucidating these interactions, our goal is to understand the effect of genetic backgrounds on drug response in diseases with current treatment options as well as to identify putative compounds for repurposing efforts for those diseases with poor or no therapeutic options.

Computational Methods Development

We also develop computational methodologies and pipelines for elucidating insight into large biological datasets. The selection of these methodologies for development is determined by the biological questions of interest and our current ability to answer them. This involves a combination of statistics, programming, machine learning and the use of high-performance computing resources.

Current Lab Members

Dr. Giuseppe D'Agostino - Dean's Postdoctoral Research Fellow
Dr. Vincent Tano - Research Fellow
Nevin Tham - PhD Candidate
  • A Proteogenomics Approach for Complex Disease

  • Assessing in type 2 diabetes mellitus associated risk factors for cognitive impairment in European and multi-ethnic Singaporean populations

  • Next-generation human organoids: Characterization, isolation and combinatorial re-assembly of niche components

  • Next-generation human organoids: Characterization, isolation and combinatorial re-assembly of niche components (Foo Jia Nee)

  • Next-generation human organoids: Characterization, isolation and combinatorial re-assembly of niche components (Philip Ingham)

  • Next-generation human organoids: Characterization, isolation and combinatorial re-assembly of niche components (Yen Choo)
  • Tan ALM*, Langley SR*, et al. Ethnicity-specific skeletal muscle transcriptional signatures and their relevance to insulin resistance in Singapore. JCEM. 2018. Advance Access. doi:10.1210/jc.2018-00309.

    Langley SR, Willeit K, Didangelos A, et al. Extracellular matrix proteomics identifies molecular signature of symptomatic carotid plaques. JCI. 2017. 127(4):1546. doi:10.1172/JCI86924

    Delahaye-Duriez A, Shkura K, Langley SR, et al. Rare and common epilepsies converge to a single gene regulatory network: opportunities for novel antiepileptic drug discovery. Genome Biol. 2016. 17(1): 245. doi:10.1186/s13059-016-1097-7

    Johnson MR, Shkura K, Langley SR, et al. Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease. Nat. Neurosci. 2016. 19(2): 223-232. doi:10.1038/nn.4205

    Langley SR and Mayr M. Comparative analysis of statistical methods used for detecting differential expression in label-free mass spectrometry proteomics. J. Proteomics. 2015. 129:83-92. doi:10.1016/j.jprot.2015.07.012

    Langley SR, et al. Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans. Cardiovasc. Res. 2013. 97(4): 653-665. doi:10.1093/cvr/cvs329

    Heinig M, Petretto E, Wallace C, Bottolo L, Rotival M, Lu H, Li Y, Sarwar R, Langley SR, et al. A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk. Nature. 2010. 467(7314): 460-464. doi:10.1038/nature09386

    Nishihara E*, Tsaih S*, Tsukahara C*, Langley S*, et al. Quantitative trait loci associated with blood pressure of metabolic syndrome in the progeny of NZO/HILtJ x C3H/HeJ intercrosses. Mamm. Genome. 2007. 18(8): 573-583. doi:10.1007/s00335-007-9033-5