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Preanalytical Workflow Establishment for Reproducible Clinical Blood-Based Infrared Molecular Fingerprinting.

Katharina E Dietmann^1,2,3, Guanting Guo¹, Jacqueline Aschauer^1,4

¹Department of Experimental Physics-Laser Physics, Ludwig-Maximilians-Universität München, 85748 Garching, Germany.

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|June 17, 2026

Summary

Standardizing preanalytical sample handling is crucial for reliable molecular analytics. This study quantifies how blood sample variables impact infrared molecular fingerprinting (IMF), finding harmonization is feasible for clinical settings.

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Area of Science:

Biochemistry
Analytical Chemistry
Spectroscopy

Background:

Standardized preanalytical sample handling is essential for reliable molecular analytics.
Variations in blood sample processing workflows can limit study comparability and complicate evaluations.
The influence of individual technical parameters on molecular profiling remains poorly quantified.

Purpose of the Study:

To systematically investigate the effects of major preanalytical variables on infrared molecular fingerprinting (IMF) of blood serum and plasma.
To examine impacts of tube types, fill volumes, delays, centrifugation, and freeze-thaw cycles on IMF.
To provide guidance for harmonizing preanalytical workflows in IMF-based biofluid analysis.

Main Methods:

Fourier transform infrared (FTIR) spectroscopy was used for infrared molecular fingerprinting.
Systematic investigation of variables including blood draw tube types, fill volumes, pre-centrifugation delays, centrifugation conditions, freeze-thaw cycles, and post-preparation delays.
Multivariate analysis and machine learning were employed to detect spectral variations.

Main Results:

Blood collection tube type, fill volume, pre-centrifugation delay (>4 h), >2 freeze-thaw cycles, and pre-measurement delays cause systematic changes in infrared fingerprints.
These spectral variations are detectable using multivariate analysis and machine learning.
Parameter-related spectral variation is generally smaller than intrinsic biological variability, supporting IMF feasibility.

Conclusions:

Preanalytical variables significantly impact IMF of blood serum and plasma.
Harmonizing preanalytical workflows is crucial for reducing confounding and improving cross-study comparability in IMF.
The findings support the feasibility of IMF in clinical settings and may generalize to other molecular profiling technologies.