Effects of Long-Term Storage Time and Original Sampling Month on Biobank Plasma Protein Concentrations

Abstract

The quality of clinical biobank samples is crucial to their value for life sciences research. A number of factors related to the collection and storage of samples may affect the biomolecular composition. We have studied the effect of long-time freezer storage, chronological age at sampling, season and month of the year and on the abundance levels of 108 proteins in 380 plasma samples collected from 106 Swedish women. Storage time affected 18 proteins and explained 4.8–34.9% of the observed variance. Chronological age at sample collection after adjustment for storage-time affected 70 proteins and explained 1.1–33.5% of the variance. Seasonal variation had an effect on 15 proteins and month (number of sun hours) affected 36 proteins and explained up to 4.5% of the variance after adjustment for storage-time and age. The results show that freezer storage time and collection date (month and season) exerted similar effect sizes as age on the protein abundance levels. This implies that information on the sample handling history, in particular storage time, should be regarded as equally prominent covariates as age or gender and need to be included in epidemiological studies involving protein levels.

Highlights

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  Storage time explains up to 35 % of plasma protein concentration variation in frozen biobank samples from healthy women.

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  Storage time exert similar effect sizes as individual age and should be included as a covariate in epidemiological studies.

One basic requirement of life science research is the quality of samples. Proper handling and rigorous biobanking of clinical samples is crucial for collection of samples for rare diseases, for monitoring individual variation in longitudinal studies and for prospective studies of biomarkers and risk of developing for instance cardiovascular disease. We have studied the effect of long-time storage, individual age and sampling month and conclude that storage-time has similar impact on protein levels as age. The results emphasize the need to include sample parameters as covariates in future epidemiological studies, which may facilitate future discoveries of novel biomarkers for disease.