Review for 10.1186/s12876-024-03456-9 (2024)

Title: Host cytokine genetic polymorphisms in a selected population of persons living with
hepatitis B virus infection in the Central Region of Ghana
Version: 2 Date: 20 Jul 2024
Reviewer's report:
The aim of this study was to profile for polymorphisms in cytokines including IL-2, IL-10,
IL-18, INF-#, and TNF-# implicated in immunomodulation of HBV infection and understand
how these polymorphisms influence hepatitis B virus infection prognoses.
Results show that IL2 rs1479920 GG carriers ((1258.93; 0.00-5011.87) IU/mL had reduced
HBV DNA in comparison to IL2 rs1479920 AA ((5011.87; 2113.49-5956.62) /AG (3548.13;
0.00-6309.57) IU/mL carriers.  TNF-# rs1800629 AA carriers (1258.93; 0.00-3981.07) IU/mL
had a reduction in HBV DNA levels in comparison to TNF-# rs1800629 GG carriers (1584.89;
0.00-5011.87) IU/mL.
The present study has a certain scientific interest but the manuscript needs to be improved. Major
comments
1. Methodology
# The study is not a prevalence study, so the size of the study population should be calculated by
taking into account the frequency of the exposure factors studied. The lowest genotypic or allelic
frequency among the polymorphisms studied (in the Ghanaian population or a close population)
should be considered, failing that, use a frequency of 0.5 for the calculations.
# The main objective of the study is to understand how variations in cytokines could influence
the prognosis of HBV infection and given that the negative controls are not in sufficient number
(not representative), it would be good to consider only patients infected with HBV for the study.
# The methodology should be better detailed. Did you use a questionnaire to collect the data?
What equipment was used to measure height, weight and how did you calculate the BMI? On
what basis did you define the different BMI groups (overweight, obesity, etc.)? How did you
select negative control, chronic and acute hepatitis? For the univariate and multivariate analysis,
it would be good to mention the thresholds that were used to define the high HBV DNA levels
and FIB score.
2. Results
# We have too many tables in the manuscript. For example you used three tables to describe the
study population (table 1, table 2 and table 3). It would be desirable to use a single table named
“general characteristics of the study population” to present only the important data from these
first three tables. However, if you wish to highlight other data, you can put them in another table
and add them to the additional files.
# The polymorphisms rs1479922 T>C and rs11914 A>C are not in Hardy Weinberg equilibrium
(HWE). What explanation can you give for these results? In genetics, deviation from Hardy
Weinberg equilibrium highlights a real problem of homogeneity of the study population and this
can hide major biases in the analyses.
# The presentation of the univariate and multivariate analysis (results of Table 6) needs to
be improved. The result of the univariate analysis should show whether carriers of a specific
genotype were more or less likely to have a high FIB Score or a high HBV DNA levels compared
to others genotypes. The multivariate analysis allows confirming or not the association, taking
into account the confounding effects (covariates).
2. Discussion
The discussion needs to be improved. The first part of the discussion on the general
characteristics of the study population should be summarized and the second part on genetic and
non-genetic risk factors should be better discussed.
Minor comments
# In the abstract, the results of table 6 (univariate and multivariate analysis) are not shown. These
results which highlight some genetic and non-genetic risk factors for a high FIB Score or a high
HBV DNA levels are the most important in my opinion.
# For a cross-sectional study, the study period should be clearly defined.
# For genotyping, you used RFLP PCR for the TNF-# rs1800629 polymorphism, so it would be
good to show in a figure, the images of the gels before and after enzymatic digestion.
# What do the dashes and empty boxes mean in table 1 and table 2? If they represent zero, please
put 0(0.00) in the tables. Also the first columns of numbers and frequencies are not named. If
it is the total, put “total population”.
# In the table 4, are the HWE p values of the different polymorphisms for the total population? It
would be good to calculate also for each group separately (Acute HBV, Chronic HBV and HBV-
negative Control group). For some polymorphisms (rs1799724, rs121913163, rs188741...),
genotypes are missing and should be added even if they were not detected in the study population
(put zero as number and frequency in the corresponding boxes (0.00)). The title of the table
could be also changed to“genotypic distribution of polymorphisms”.
# Table 5 does not contain data from the study as such, so it should be added to the supplementary
files and not presented in the manuscript.
# You should always mention below tables, what types of analysis were done and the groups
concerned by comparison.
# In general, the figures are not readable. In addition to figure 1 have you also done a statistical
comparison of the HBV DNA means between the different genotypes? If not, it would be
interesting to do it.
# Linkage disequilibrium analyses are additive information to understand haplotype distribution,
however this is not the purpose of the study and the figure 2 should be placed towards the end
of the results. The title of figure 2 seems to be confused with the legend.
# You should avoid the expressions "significant association, significant correlation" in the
manuscript. In statistical analysis, there is association or no association and correlation or no
correlation.
# There are some spelling mistakes in the manuscript and the English also needs to be improved.