Exploiting chemical shift variability enables recovery of overlapping metabolites from 1H nuclear magnetic resonance spectra
Jesper Løve Hinrich, Pia Susan Mayer, Bekzod Khakimov, Søren Balling Engelsen, Morten Mørup
q-bio.QM, cs.LG
Submitted: 2026-08-06
Updated: 2026-08-11
Code: https://github.com/JesperLH/bsi-nmf
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
The gist: Overlapping peaks and sample-dependent chemical shift variability prevent reliable metabolite recovery from complex biological spectra.
Terminology
Abstract
Overlapping peaks and sample-dependent chemical shift variability prevent reliable metabolite recovery from complex biological spectra. This problem is critical in one-dimensional proton (1D 1H) NMR which has become the standard method providing fast acquisition and information-rich spectra in metabolomics and foodomics. This study demonstrates how chemical shifts can be utilised as a strength in 1D 1H NMR, when suitably modeled through the proposed Bayesian Shift-Invariant Non-negative Matrix Factorization (BSI-NMF) procedure. We find that BSI-NMF accurately recovers the underlying chemical signals in 1D 1H NMR spectra missed by existing analyses approaches across simulations, laboratory created datasets, and a large urine dataset obtained from 2439 people across Europe. Our study highlights how shifts in the chemical signatures - until now perceived as a nuisance - can in fact when suitably modelled be instrumental for unique recovery of metabolites. This creates an opportunity to experimentally induce chemical shifts changes to facilitate unique recovery of spectra.
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