Serotonin 5-HT_1A receptor binding and self-transcendence in healthy control subjects—a replication study using Bayesian hypothesis testing

Abstract

ObjectiveA putative relationship between markers for the serotonin system and the personality scale self-transcendence (ST) and its subscale spiritual acceptance (SA) has been demonstrated in a previous PET study of 5-HT1A receptor binding in healthy control subjects. The results could however not be replicated in a subsequent PET study at an independent centre. In this study, we performed a replication of our original study in a larger sample using Bayesian hypothesis testing to evaluate relative evidence both for and against this hypothesis.MethodsRegional 5-HT1A receptor binding potential (BPND) was examined in 50 healthy male subjects using PET with the radioligand [11C]WAY100635. 5-HT1Aavailability was calculated using the simplified reference tissue model (SRTM) yielding regional BPND. ST and SA were measured using the Temperament and Character Inventory (TCI) questionnaire. Correlations between ST/SA scores and 5-HT1ABPND in frontal cortex, hippocampus and raphe nuclei were examined by calculation of default correlation Bayes factors (BFs) and replication BFs.ResultsThere were no significant correlations between 5-HT1A receptor binding and ST/SA scores. Rather, five of six replication BFs provided moderate to strong evidence for no association between 5-HT1A availability and ST/SA, while the remaining BF provided only weak evidence.ConclusionWe could not replicate our previous findings of an association between 5-HT1A availability and the personality trait ST/SA. Rather, the Bayesian analysis provided evidence for a lack of correlation. Further research should focus on whether other components of the serotonin system may be related to ST or SA. This study also illustrates how Bayesian hypothesis testing allows for greater flexibility and more informative conclusions than traditional p-values, suggesting that this approach may be advantageous for analysis of molecular imaging data.

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“…complement reported p-values, as a stand-alone metric to quantify the evidence of stated hypotheses, or to assess the replicability of previously published results. 24 – 26 Of particular interest for this tutorial, the BF first lends itself naturally to sequential testing of data 12 , 13 ; and second, it quantifies evidence in favour of either H 1 and H 0 , meaning that the null-hypothesis also can gain, or lose, support by the data and hence be formally accepted or rejected. 14 , 22 However, as with all metrics used for statistical inference, the BF is not without limitations and criticism.…”