The data obtained through the experiment presented in this work would benefit the scientific community to understand the role of small molecules in the progress of healthy pregnancy. However, this particular dataset should be in its entirety in order to best benefit other researchers. Even though the authors have presented the raw data in its entirety, there are some gaps in the meta data collected. This is especially important during statistical analysis of this data, as detailed below. The experimental design shown in this paper has groups of women in 6 different classes (T1 to T6), who are at different stages in their pregnancy and hence collectively the 6 classes cover the span of the pregnancy. During statistical analysis, it is important to make sure that any differences observed between the groups are not caused by any confounding factors such as age, height, weight etc. This is even more important in this particular study because as the authors have detailed (in page 8) that the samples were not randomized in positive mode. Thus, to make sure that the differences observed between the batches (and hence the stages of pregnancy) are due to the progression and pregnancy and not due to any confounding factors, it is important that all meta data be captured and presented. The meta data that are incomplete are, (a) height and weight: In many cases these parameters are populated with “not available”. Are these true missing values? That is, were these fields not captured during the study survey? The experimental design seems to be fairly methodical and controlled. Hence, it is difficult to see why there are missing values. (b) the authors have mentioned (in page 4) that BMI has been collected. This is not present in the meta data. Is this supposed to be a separate field or is it to be derived from the height and weight parameters? Also, the authors have presented the different groups as classes (T1 to T6) as well as time points (A to F). It would be good to be consistent. Level of interest An article whose findings are important to those with closely related research interests Quality of written English Acceptable Statistical review Yes, and I have assessed the statistics in my report. Declaration of competing interests None.

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