RNA integrity in post-mortem samples: influencing parameters and implications on RT-qPCR assays

Messenger RNA (mRNA) profiling in post-mortem human tissue might reveal information about gene expression at the time point of death or close to it. When working with post-mortem human tissue, one is confronted with a natural RNA degradation caused by several parameters which are not yet fully understood. The aims of the present study were to analyse the influence of impaired RNA integrity on the reliability of quantitative gene expression data and to identify ante- and post-mortem parameters that might lead to reduced RNA integrities in post-mortem human brain, cardiac muscle and skeletal muscle tissues. Furthermore, this study determined the impact of several parameters like type of tissue, age at death, gender and body mass index (BMI), as well as duration of agony, cause of death and post-mortem interval on the RNA integrity. The influence of RNA integrity on the reliability of quantitative gene expression data was analysed by generating degradation profiles for three gene transcripts. Based on the deduced cycle of quantification data, this study shows that reverse transcription quantitative polymerase chain reaction (RT-qPCR) performance is affected by impaired RNA integrity. Depending on the transcript and tissue type, a shift in cycle threshold values of up to two cycles was observed. Determining RNA integrity number of 136 post-mortem samples revealed significantly different RNA qualities among the three tissue types with brain revealing significantly lower integrities compared to skeletal and cardiac muscle. The body mass index was found to influence RNA integrity in skeletal muscle tissue (M. iliopsoas). Samples originating from deceased with a BMI > 25 were of significantly lower integrity compared to samples from normal weight donors. Correct data normalisation was found to partly diminish the effects caused by impaired RNA quality. Nevertheless, it can be concluded that in post-mortem tissue with low RNA integrity numbers, the detection of large differences in gene expression activities might still be possible, whereas small expression differences are prone to misinterpretation due to degradation. Thus, when working with post-mortem samples, we recommend generating degradation profiles for all transcripts of interest in order to reveal detection limits of RT-qPCR assays.

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