# ¹H NMR Chemical Shifts and J‐Coupling Constants Dependence on Temperature and pH: Implications for the Quantification of Relevant Metabolites

## TL;DR

This paper studies how temperature and pH affect 1H NMR chemical shifts and J-coupling constants of metabolites, providing model functions to improve quantification accuracy in different physiological conditions.

## Contribution

The study introduces model functions to predict chemical shifts and J-coupling constants under varying temperature and pH, improving metabolite quantification in 1H MRS.

## Key findings

- Most metabolites show significant spectral changes with temperature and pH variations.
- Model functions were developed to predict chemical shifts and J-coupling constants across temperature and pH ranges.
- Lower metabolite concentrations lead to higher quantification errors when using incorrect prior knowledge.

## Abstract

1H MRS enables the non‐invasive measurement of various compounds in biological systems, both in vitro and in vivo. It thus offers the possibility of investigating characteristic metabolic processes and identifying biomarkers under both normal and pathological conditions. Therefore, a reliable quantification of important compounds is essential. Many quantification methods established for this purpose use model spectra based on prior knowledge of chemical shifts and J‐coupling constants. The broad application range of 1H MRS also allows its use at different temperatures and pH values based on the physiological conditions of the model organism. Against this background, this work aimed to investigate 15 important metabolic compounds in terms of their temperature and pH dependence of chemical shifts and J‐coupling constants. The results indicate that the majority of the compounds exhibit significant changes in their spectra in response to temperature changes. Additionally, the pH can significantly influence the spectra. Therefore, model functions were calculated to predict the chemical shift and the J‐coupling constants in the investigated range for each combination of temperature and pH. In addition, the influence of incorrect prior knowledge in quantifying the metabolite concentration was analysed. For the higher concentrated metabolites (> 2 mM), only minor errors in the quantification result from the use of incorrect prior knowledge regarding the chemical shifts and the J‐coupling constants, except for Cr and PCr. As the concentration of the metabolite decreases, the percentage error in the estimated concentration increases. Thus, the model functions can be applied to quantifying spectra for various organisms and their specific physiological properties. This optimisation is essential to avoid or minimise errors in quantifying 1H MRS data.

1H MRS, in combination with quantification methods using model functions based on prior knowledge of chemical shifts and coupling constants, allows the determination of characteristic metabolic processes in healthy and diseased tissue. Using the functional relationships δpHT and JpHT enables this prior knowledge to be optimised to ensure reliable quantification of spectra even under changing physiological conditions. The functions for the different resonances of a compound (in this case, creatine) often exhibit significant differences in their pH and temperature dependencies.