Title: Relationships between nine neuropsychiatric disorders and cervical cancer: Insights from
genetics, causality and shared gene expression patterns
Version: 0 Date: 24 Apr 2024
Reviewer:  Rafael Tabarés-Seisdedos
Reviewer's report:
“Relationship between nine mental disorders and cervical cancer: Insights from genetics,
causality and shared gene expression patterns”.
This study's main objective is to identify mental disorders that are genetically and causally
related to cervical cancer and to investigate the molecular mechanisms underlying these
associations.
The entire process they follow is carefully written, but information related to the methods or
data used is missing:
• All the data related to the GWAS catalogue have a broken link, and the disease identifiers
(EFOtraits) are not mentioned, so not even the possible datasets can be found.
• The data used for replication is poorly documented, and data from the UK Biobank, 23andMe,
and PGC are mentioned.
# The UK Biobank data is disproportionate, with 1,889 cases vs 461,044 controls. The data is
available for download, but there are different datasets (imputed, binary and WES). It can be
understood that the data they have used is what they call “imputed”, but it is not mentioned
explicitly. The reference article for this data is closed to the public and without institutional
access. The platform is unclear when used and gives many connection errors, so I have not seen
the data.
# Articles often use 23andMe data, but no further details are given. Since 23andMe is a private
company, it can be assumed that they requested the data directly from the company. Since it is not
public, it cannot be referenced, but this invalidates the replication for the rest of the researchers
who want to follow the methodology.
# Regarding the use of PGC data, the case data are initially well-referenced since the reference
paper precisely details which studies from the repository have been used. However, it is not
clear what data has been used for the replication part.
• At the level of procedure and justification, the article's content seems correct to me:
downloading datasets, analysis with LDSC, Mendelian randomisation for causality, RNA-Seq
analysis and Path Enrichment. I agree with the procedure and have no problem with it.
• More comments, some things catch my attention: the Availability of the Data section: several
of the datasets are hosted in the GWAS catalogue (the link to the document is incorrectly placed,
the comma at the end is left over and if you don't notice you get an error). The link takes you to
the generic download page, so it isn't easy to find the source since it does not have an identifier.
I have looked for references for some (23 and 26), and the data has been uploaded to a different
place. I don't know if it is a temporary placeholder or something common. Still, it would not
allow me to safely identify the data used if there was more than one for the disease in question,
and if I now wanted to replicate the article based on only the article, I would not be able to
access the data. It occurs in several of the links in this section. They mention that it is detailed
in supplementary material 1, which I do not have and cannot verify, but I still think they should
put the full access link and not to the database to allow direct access to the data. There is also
the 23andMe dataset that is not referenced (nor does it seem to be published because they do
not mention how to get it either)
• The methods are well-defined, but details about the methodology (software) and the code used
are missing. i.e., which program/script was used for data cleaning (exclusion of SNPs) in ldsc
is not mentioned.
• I don't see much problem in the information of the datasets that have been used, removing
some in which there are few cases, which I see as difficult to avoid. The graphs used in the
explanations seem correct for this information from enough datasets to show their correlations.
• Regarding Mendelian randomisation, six models are used to estimate causality, which is an
exciting idea to apply in our case, comparing different models to demonstrate the robustness
of the results. The process is better described than in the case of LDSC since each model is
referenced. However, the procedure for Mendelian Randomization and RNA-Seq analysis is the
standard. Still, just like when I mentioned the code, they only describe it, causing a leap of faith
to trust or not. In some cases, such as differential expression within RNA-seq, many methods of
analysing it may differ from the results, but they do not mention how they have done it.
• The section studying genes that overlap in conditions and functional enrichment has
information only found in the additional material. It could be replicated, but the results would
likely differ.
• The results are well explained and clear, the discussion and conclusion are direct, and the
findings are well summarised.
• In summary, I do not have great things to criticise about the procedure itself: at first glance,
it falls within the standards of both procedure and data analysis, but in my opinion, the poor
referencing of the data, the lack of code and the scarce description of the analysis methods
make reproducibility very complicated, which seems essential to me. They mention that there
are things in the supplements, but I think those kinds of things I mentioned should be in the
main article.