Published June 19, 2025 | Version v1
Dataset Open

MAMSI Supplementary Dataset

Creators

  • 1. ROR icon Imperial College London
  • 2. National Phenome Centre
  • 3. ROR icon Imperial College Healthcare NHS Trust

Description

Supplementary dataset for the "MAMSI: Integration of multi-assay liquid chromatography – mass spectrometry metabolomics data using multi-view machine learning" publication.

This repository contains 3 dataset originating from 2 studies that were run at the UK National Phenome Centre (NPC). All of these datasets contain multi-assay metabolomics data: 

The AddNeuroMed study dataset was collected as part of the “European Collaboration for the Discovery of Novel Biomarkers for Alzheimer’s Disease (AD)” [1]. There are three LC-MS serum assays available: HILIC positive ionization assay (HILIC +), and lipidomic RPC positive ionization (Lipid RPC +) and negative ionization (Lipid RPC -) assays [2]. These data were converted to mzML format using ProteoWizard [3], pre-processed using XCMS [4] and nPYc toolbox [5] software resulting in 681, 4886 and 2091 features for HILIC +, lipid RPC +, and lipid RPC - respectively. A total of 577 subjects were available, 294 of those were female and 283 were male.

The MY DIABETES study [6] comprises individuals of White, South Asian and African-Caribbean ancestry, mostly diagnosed with type 1 diabetes under the age of 30. Three LC-MS serum assays are available: HILIC +, Lipid RPC + and Lipid RPC -, containing 613, 1771 and 907 features respectively. There are also three urine assays: HILIC +, and RPC for small molecule separation in both positive ionization (SmMol RPC +) and negative ionization (SmMol RPC +) containing 2600, 12817 and 7142 features respectively [2]. All assays were pre-processed using ProteoWizard, XCMS and the nPYc toolbox software. A total of 984 subjects were available in this study, 540 of those were female and 444 were male.

Table 1: National Phenome Centre LC-MS assay names and descriptions. 

NPC Assay Name CSV File Name Description
HILIC + hpos HILIC positive ionisation assay
Lipid RPC + lpos Lipidomic RPC  positive ionisation assay 
Lipid RPC - lneg Lipidomic RPC negative ionisation assay
SmMol RPC + rpos Small molecule separation positive ionisation assay
SmMol RPC + rneg Small molecule separation negative ionisation assay

 

Files

AddNeuroMed Serum.zip

Files (212.6 MB)

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Additional details

Dates

Available
2025-06-20

References

  • [1] S. Lovestone et al., "AddNeuroMed—The European Collaboration for the Discovery of Novel Biomarkers for Alzheimer's Disease," Ann. N. Y. Acad. Sci, vol. 1180, no. 1, pp. 36-46, 2009, doi: 10.1111/j.1749-6632.2009.05064.x.
  • [2] M. R. Lewis et al., "An Open Platform for Large Scale LC-MS-Based Metabolomics," ChemRxiv, 2022, doi: 10.26434/chemrxiv-2022-nq9k0.
  • [3] M. C. Chambers et al., "A cross-platform toolkit for mass spectrometry and proteomics," (in eng), Nat. Biotechnol., vol. 30, no. 10, pp. 918-20, Oct 2012, doi: 10.1038/nbt.2377.
  • [4] C. A. Smith, E. J. Want, G. O'Maille, R. Abagyan, and G. Siuzdak, "XCMS:  Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification," Anal. Chem., vol. 78, no. 3, pp. 779-787, 2006/02/01 2006, doi: 10.1021/ac051437y.
  • [5] C. J. Sands et al., "The nPYc-Toolbox, a Python module for the pre-processing, quality-control and analysis of metabolic profiling datasets," Bioinformatics, vol. 35, no. 24, pp. 5359-5360, 2019, doi: 10.1093/bioinformatics/btz566.
  • [6] S. Misra et al., "Systematic screening for monogenic diabetes in people of South Asian and African Caribbean ethnicity: Preliminary results from the MY DIABETES study," presented at the Diabet. Med., MAR, 2018.