Limitations of currently available <i>in vitro</i> oestrogenicity bioassays for effect-based testing of whole foods as the basis for decision making

The idea that previously unknown hazards can be readily revealed in complex mixtures such as foods is a seductive one, giving rise to the hope that data from effect-based assays of food products collected in market surveys is of suitable quality to be the basis for data-driven decision-making. To study this, we undertook a comparative study of the oestrogenicity of blinded cereal samples, both in a number of external testing laboratories and in our own facility. The results clearly showed little variance in the activities of 9 samples when using a single method, but great differences between the activities from each method. Further exploration of these findings suggest that the oestrogenic activity is likely an inherent part of the natural food matrix which the varying sample preparation methods are able to release and extract to differing degrees. These issues indicate the current poor suitability of these types of datasets to be used as the basis for consumer advice or food decision-making. Data quality must be improved before such testing is used in practice.此前未知的危害可在食品等复杂混合物中被轻易检出这一观点颇具吸引力，由此催生了一种期望：通过市场调研收集的食品效应导向检测法(effect-based assays)所得数据，其质量足以支撑数据驱动型决策。为验证这一设想，我们开展了一项对比研究：对多家外部检测实验室及本实验室中的盲法谷物样品的雌激素活性(oestrogenicity)进行了对比检测分析。研究结果清晰显示：采用单一检测方法时，9份样品的活性差异极小；但不同检测方法得到的活性结果却存在显著差异。对上述结果的进一步探究表明，雌激素活性大概率是天然食品基质(food matrix)的固有组成部分，而不同的样品前处理方法可在不同程度上对其进行释放与提取。上述问题表明，当前此类数据集并不适合作为消费者膳食建议或食品相关决策的依据。在将此类检测手段投入实际应用之前，必须先提升相关数据的质量。