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Machine learning identifying peripheral circulating metabolites associated with intraocular pressure alterations
  1. Chaoxu Qian1,2,
  2. Simon Nusinovici1,3,
  3. Sahil Thakur1,
  4. Zhi Da Soh1,
  5. Shivani Majithia1,
  6. Miao Li Chee1,
  7. Hua Zhong2,
  8. Yih-Chung Tham1,3,4,
  9. Charumathi Sabanayagam1,3,4,
  10. Pirro G Hysi5,
  11. Ching-Yu Cheng1,3,4
  1. 1 Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
  2. 2 Department of Ophthalmology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
  3. 3 Ophthalmology and Visual Sciences Academic Clinical Programme, Duke-NUS Medical School, Singapore
  4. 4 Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
  5. 5 Twin Research and Genetic Epidemiology, King's College London, London, UK
  1. Correspondence to Dr Ching-Yu Cheng, Singapore Eye Research Institute, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore 169856, Singapore; chingyu.cheng{at}


Aims To identify blood metabolite markers associated with intraocular pressure (IOP) in a population-based cross-sectional study.

Methods This study was conducted in a multiethnic Asian population (Chinese, n=2805; Indians, n=3045; Malays, n=3041 aged 40–80 years) in Singapore. All subjects underwent standardised systemic and ocular examinations, and biosamples were collected. Selected metabolites (n=228) in either serum or plasma were analysed and quantified using nuclear magnetic resonance spectroscopy. Least absolute shrinkage and selection operator regression was used for metabolites selection. Multivariable linear regression was used to evaluate the relationship between metabolites and IOP in each of the three ethnic groups, followed by a meta-analysis combining the three cohorts.

Results Six metabolites, including albumin, glucose, lactate, glutamine, ratio of saturated fatty acids to total fatty acids (SFAFA) and cholesterol esters in very large high-density lipoprotein (HDL), were significantly associated with IOP in all three cohorts. Higher levels of albumin (per SD, beta=0.24, p=0.002), lactate (per SD, beta=0.27, p=0.008), glucose (per SD, beta=0.11, p=0.010) and cholesterol esters in very large HDL (per SD, beta=0.47, p=0.006), along with lower levels of glutamine (per SD, beta=0.17, p<0.001) and SFAFA (per SD, beta=0.21, p=0.008) were associated with higher IOP levels.

Conclusion We identify several novel blood metabolites associated with IOP. These findings may provide insight into the physiological and pathological processes underlying IOP control.

  • Intraocular pressure
  • Glaucoma

Data availability statement

Data are available upon reasonable request.

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Data availability statement

Data are available upon reasonable request.

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  • Contributors CQ: conceptualisation, data processing, formal analysis, writing original draft, reviewing and editing. SN: data curation, formal analysis, methodology, software, writing review and editing. ST: writing review and editing. Z-DS: writing review and editing. SM: writing review and editing. MLC: data processing, clinical data analysis. HZ: supervision. Y-CT: supervision, writing review and editing. CS: supervision, writing review and editing. PGH: validation, writing review and editing. C-YC: conceptualisation, writing review and editing, funding acquisition, project administration, supervision. C-YC is responsible for the overall content as guarantor.

  • Funding This study was supported by the National Medical Research Council (NMRC), Singapore (grant nos.: NMRC/CIRG/1417/2015, NMRC/CIRG/1488/2018 and NMRC/OFLCG/004a a/2018). C-YC is supported by an award from NMRC (CSA-SI/0012/2017).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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