The impact of DNA methylation as a factor of Adverse Pregnancy and Birth Outcomes (APBOs): a systematic review protocol

Abstract

Background
Deoxyribonucleic acid (DNA) methylation is one of the epigenetic modifications that has gained a lot of interest as a factor influencing fetal programming and as a biomarker for adverse pregnancy and birth outcomes (APBOs). Epidemiological studies have demonstrated that DNA methylation can result in adverse pregnancy and birth outcomes (APBOs) including miscarriage, intrauterine growth restriction (IUGR), low birth weight (LBW), sepsis, and preterm birth (PTB), which may later result in diseases in adulthood. However, the mechanism by which DNA methylation influences these APBOs remains unclear. The systematic review will assess the association between global and gene-specific DNA methylation with adverse pregnancy outcomes.

Method
The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 checklist will be followed when conducting this systematic review. To develop the search strategy the PI(E)COS (population, intervention/exposure, comparator/control, outcome, and study designs) framework will be followed. Thus far, the research team has retrieved 4721 from Cochrane Library, PubMed, Web of Sciences, and MEDLINE. Out of these, 584 studies have been screened for eligibility, and approximately 124 studies meet the inclusion criteria. Pending the search results identified from the grey literature. For identification of unpublished studies in journals indexed in electronic databases, Google Scholar will be used. I.M and A.S will separately extract data from the articles and screen them, if there are any disagreements between I.M and A.S, then the L.M will resolve them. The methodological quality and bias risk of the included studies will be evaluated using the Critical Appraisal Skill Programme CASP) checklist. I2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${I}^{2}$$\end{document} and χ2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\chi 2{}$$\end{document} alpha = 0.10 statistic will be used for assessing statistical heterogeneity between studies. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach will be used to assess and grade the overall quality of extracted data.

Ethics and dissemination
Ethical approval is not required. The systematic review will assess available literature on possible associations between DNA methylation with adverse pregnancy and birth outcomes (APBOs) including LBW, IUGR, miscarriage, sepsis, and PTB. The findings could help guide future research assessing DNA methylation and other APBOs.

Systematic review registration
PROSPERO CRCRD42022370647.

Full text

Moagietal. Systematic Reviews (2024) 13:4
https://doi.org/10.1186/s13643-023-02416-w
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Systematic Reviews
The impact ofDNA methylation asafactor
ofAdverse Pregnancy andBirth Outcomes
(APBOs): asystematic review protocol
Innocent Moagi1* , Lawrence Mabasa2, Sonto Maria Maputle3, Duduzile Ndwandwe4,
Ndidzulafhi Selina Raliphaswa3, Lizzy Mutshinyalo Netshikweta3, Thivhulawi Malwela3 and Amidou Samie1*
Abstract
Background Deoxyribonucleic acid (DNA) methylation is one of the epigenetic modifications that has gained
a lot of interest as a factor influencing fetal programming and as a biomarker for adverse pregnancy and birth
outcomes (APBOs). Epidemiological studies have demonstrated that DNA methylation can result in adverse preg-
nancy and birth outcomes (APBOs) including miscarriage, intrauterine growth restriction (IUGR), low birth weight
(LBW), sepsis, and preterm birth (PTB), which may later result in diseases in adulthood. However, the mechanism
by which DNA methylation influences these APBOs remains unclear. The systematic review will assess the association
between global and gene-specific DNA methylation with adverse pregnancy outcomes.
Method The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 checklist will be
followed when conducting this systematic review. To develop the search strategy the PI(E)COS (population, interven-
tion/exposure, comparator/control, outcome, and study designs) framework will be followed. Thus far, the research
team has retrieved 4721 from Cochrane Library, PubMed, Web of Sciences, and MEDLINE. Out of these, 584 studies
have been screened for eligibility, and approximately 124 studies meet the inclusion criteria. Pending the search
results identified from the grey literature. For identification of unpublished studies in journals indexed in electronic
databases, Google Scholar will be used. I.M and A.S will separately extract data from the articles and screen them,
if there are any disagreements between I.M and A.S, then the L.M will resolve them. The methodological quality
and bias risk of the included studies will be evaluated using the Critical Appraisal Skill Programme CASP) checklist.
I2
and
χ2
alpha = 0.10 statistic will be used for assessing statistical heterogeneity between studies. The Grading of Rec-
ommendations, Assessment, Development, and Evaluation (GRADE) approach will be used to assess and grade
the overall quality of extracted data.
Ethics anddissemination Ethical approval is not required. The systematic review will assess available literature
on possible associations between DNA methylation with adverse pregnancy and birth outcomes (APBOs) includ-
ing LBW, IUGR, miscarriage, sepsis, and PTB. The findings could help guide future research assessing DNA methylation
and other APBOs.
Systematic review registration PROSPERO CRCRD42022370647.
*Correspondence:
Innocent Moagi
moagiinnocent610@gmail.com
Amidou Samie
samie.amidou@univen.ac.za
Full list of author information is available at the end of the article
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 2 of 8
Moagietal. Systematic Reviews (2024) 13:4
Keywords Epigenetics, DNA methylation, Preterm birth (PTB), Low birth weight (LBW), Sepsis, Adverse pregnancy
outcomes, Intrauterine growth restriction (IUGR)
Background
Adverse pregnancy and birth outcomes (APBOs) includ-
ing miscarriage, Low birth weight (LBW), preterm birth
(PTB), sepsis, and intrauterine growth restriction (IUGR)
are major public health problems and have been linked
with a high risk of mortality and morbidities during both
the neonatal period and later in life [1–4]. e majority
of these APBOs are associated with maternal exposure
to genetic and environmental factors during pregnancy.
Pregnancy is a vital period of plasticity wherein mater-
nal exposure to multiple environmental, behavioral, and
hereditary factors may significantly affect fetal develop-
ment as well as the mother’s health [5, 6].
Epidemiological studies have shown that intrauterine
exposure to adverse environmental factors is associated
with adverse pregnancy and birth outcomes, which may
increase the risk of developing chronic diseases later in
life [7] ese studies were inconsistent with the Develop-
mental Origins of Health and Disease (DOHaD) hypoth-
esis. Intrauterine exposure to these factors may also
influence offspring’s health later in adulthood, thus influ-
encing susceptibility to long-term risk of chronic diseases
from the neonatal period to adulthood [8–11]. Hence,
the idea of fetal programming [12–14]. Researchers have
shown that perinatal nutrition has a significant impact on
fetal programming and pregnancy and birth outcomes
[15, 16].
e accurate diagnosis and prognosis of the adverse
pregnancy and birth outcomes (APBOs) including PTB,
LBW, sepsis, IUGR, and miscarriage remain a big chal-
lenge or difficulty, as the majority of these APBOs may
share similar clinical signs and symptoms [17–20].
erefore, there is a need for understanding the etiol-
ogy and the underlying molecular mechanism behind
these APBOs as well as identifying the biomarkers that
could be useful for the diagnosis of APBOs during early
pregnancy [21, 22]. Molecular mechanisms such as epi-
genetic modifications, have gained a lot of interest in the
identification of potential diagnostic biomarkers for an
increased risk of experiencing these adverse pregnancy
and birth outcomes (APBOs). is is due to their speci-
ficity, prognostic efficacy, and sensitivity when compared
to protein expression-based techniques [23, 24].
Epigenetics is the study of inheritable genetic
changes that can affect gene expression, without alter-
ing DNA sequence. These alterations include DNA
methylation, non-coding Ribonucleic acid (RNA)
regulation, histone modification as well as chromatin
remodeling [1, 9, 13]. Among epigenetic modification,
DNA methylation (DNAm) which involves the addi-
tion of a methyl group to the cytosine nucleotide of
the cytosine-guanine (CpG) dinucleotides, is the well-
researched epigenetic mechanism [10, 25]. Enzymes
known as DNA methyltransferase act as catalysts and
S-adenosyl-methionine as the methyl donor during
this process of DNA methylation [23, 26].
Studies recently have made a huge breakthrough on
how DNA methylation influences fetal programming
and APBOs [1, 27]. For instance, studies have reported
on the association of both global and specific-gene
DNA methylation with APBOs including IUGR, PTB,
LWB, miscarriage, and sepsis separately [20, 22, 28].
In these studies, APBOs were associated with either
hypermethylation or hypomethylation of certain genes
[21, 28]. Furthermore, studies demonstrated the asso-
ciation between DNA methylation of nuclear receptor
subfamily 3 group C member 1(NR3C1), long inter-
spersed nuclear element (LINE-1), calcitonin-related
polypeptide alpha (CALCA), and insulin-like factor 2
(IGF2) genes with APBOs [10, 19, 29].
Systematic reviews have explored the associations
between gene-specific epigenetic modifications of IGF-
related genes, NR3C1, and Hydroxysteroid 11-beta
dehydrogenase type 1/2 (HSD11 B1/2) and several
APBOs. Notably, these reviews did not examine the
impacts of global DNA methylation on APBOs [30, 31].
Furthermore, a systematic review has comprehensively
analyzed the literature on the association between DNA
methylation signature with PTB in black American
women but has not extended to the global population
[32]. However, to our knowledge, there are no exist-
ing systematic reviews and meta-analyses that have
aimed to evaluate the association between both global
and gene-specific DNA methylation with APBOs as
well as sepsis, all at once. erefore, the reason for this
review is to search for studies addressing the association
between DNA methylation and specific APBOs, includ-
ing LBW, PTB, miscarriage, sepsis, and IUGR. us,
exploring the impact of environmental factors on DNA
methylation, investigating the underlying molecular
mechanism by which DNA methylation modifications
contribute to the occurrence of APBOs, and identify-
ing potential DNA methylation biomarkers associ-
ated with these specific APBOs. e findings from this
review will not only contribute to the ongoing efforts to
improve both maternal and neonatal health outcomes
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Moagietal. Systematic Reviews (2024) 13:4
by shedding light on genetic factors that may influence
APBOs but will also provide the knowledge necessary
to guide future research and inform clinical strategies
aimed at preventing the impact of APBOs.
Primary objective
is systematic review’s main objective is to assess the
relationship of both global and gene-specific methyla-
tion status with adverse pregnancy and birth outcomes
including intrauterine growth restriction, miscarriage,
sepsis, preterm birth, and low birth weight.
Specic objective
To investigate the association between both neonatal and
maternal DNA Methylation status at birth with adverse
pregnancy and birth outcomes.
Methods
Protocol andregistration
e Preferred Reporting Items Systematic Review and
Meta-Analysis Protocol (PRISMA-P 2015) guideline
will be followed when conducting this systematic review
and meta-analysis, which is very crucial in improv-
ing the integrity of this review [33]. For this systematic
review protocol, a filled-out PRISMA checklist has been
provided in the form of a Word document. e proto-
col used in this systematic review was adopted from the
already published systematic review protocol by Vanter-
pool et al. (2016) and it was submitted for registration
in the international prospective register of systematic
review PROSPERO (CRD42022370647) [34].
Eligibility criteria
For inclusion in the review, studies will be screened based
on the criteria outlined below. Inclusion will be deter-
mined by adherence to the PI(E)COS framework: types
of studies, study population, intervention/exposure(s),
comparator, and outcomes.
Types ofstudies
Observational studies such as cross-sectional studies,
prospective cohorts, case–control, and retrospective
cohorts focusing on the association between DNA meth-
ylation with APBOs will both be considered for the sys-
tematic review and meta-analysis. e systematic review
will include studies that used either placental samples,
the mother’s peripheral blood, neonatal cord blood, or
urine samples. Studies published with any language that
Google can translate to English will be considered as well
as systematic reviews and meta-analyses meeting the
inclusion criteria.
Population ofinterest
For inclusion in the review, only studies that examined
the association between DNA methylation with either
LBW, PTB, sepsis, miscarriage, and IUGR in women
who are pregnant and their newborns regardless of
gender and ethnicity will be considered.
Intervention/exposure (s)
e exposure of interest will be the DNA methylation
status of the participants. ere are no interventions
that will be reviewed.
Comparator
e comparison group will include neonates without
any complications after birth and women not known
for possible confounders (smoking, age, and alcohol).
Outcomes
e main purpose of this systematic review is to deter-
mine whether DNA methylation is associated with
adverse pregnancy outcomes. Adverse pregnancy
outcomes are any complications that occur during
pregnancy, labor, delivery, or 6 weeks after delivery
(postpartum period) [35]. For the interest of the sys-
tematic review, the following primary and secondary
pregnancy and birth outcomes will be taken into con-
sideration based on their occurrence:
Primary outcomes
DNA methylation level of the specific gene in pregnant
women and neonates.
Preterm birth is birth before 37 complete weeks of
gestation (this includes very preterm, moderate pre-
term, and extremely preterm) [36].
Miscarriage, which is a spontaneous loss of preg-
nancy before 20weeks [33].
Secondary outcomes
Low birth weight less than 2500g (LBW) [36].
When the fetus in the womb is not developing or
growing as expected or when the anticipated fetal
weight is less than the 10th percentile at birth. is
condition is known as intrauterine growth restriction
(IUGR) [33].
Neonatal sepsis is a systemic condition usually caused
by bloodstream bacterial pathogens which is charac-
terized by pro-inflammatory and anti-inflammatory
responses, occurring in neonates (particularly PTB and
LBW). It is divided into two categories based on the tim-
ing of the infection. us, early onset sepsis (EOS) which
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Moagietal. Systematic Reviews (2024) 13:4
occurs within 72 h of life, and late-onset sepsis (LOS)
which occurs after 72h of life [17–19].
Settings
ere will not be any time and geographical restraints.
Exclusion criteria
Studies focusing on animals as well as narrative reviews
will be excluded from the systematic review. Studies that
did not adhere to any PI(E)COS framework will not be
considered in the systematic review. Studies examining
the relationship between DNA methylation and APBOs
in animals.
Information source andsearch strategy
For inclusion in this review, the literature search
for systematic review will be conducted on the fol-
lowing electronic databases: MEDLINE, Cochrane
Library, and PubMed. To ensure comprehensive cov-
erage, reference lists as well as screening citations of
the included studies will be manually searched using
search engines such as Google Scholar and Web of Sci-
ences. Searching for grey literature, Google Scholar
will also be used to identify published articles. The
first search approach in PubMed will involve the mix-
ture of Medical Subject Headings (MeSH) and free text
search words relating to birth and pregnancy, DNA
methylation, epigenetics, intrauterine growth restric-
tion/retardation, low birth weight, miscarriage, and
preterm birth. For search in other electronic data-
bases including Cochrane Library and MEDLINE, we
will adapt the search strategy used in PubMed with
some adjustments. Thus, to remove any contradictions
that can affect data extraction. The search terms will
be then combined using Boolean operators. The sec-
ond search technique will focus on the grey literature
thus identifying more studies that are not published
in journals indexed in Cochrane Library, MEDLINE,
and PubMed. The following is the search strategy
conducted on PubMed that will be adopted by the
reviewer for searching in other databases:
("infant, newborn"[MeSH Terms] OR "fetus"[MeSH
Terms] OR "pregnancy"[MeSH Terms] OR "fetal"[Text
Word]) AND ("epigenomics"[MeSH Terms] OR
"epigenomics"[MeSH Terms] OR "dna methylation"[MeSH
Terms]) AND ("pregnancy complications"[MeSH Terms]
OR "adverse pregnancy outcomes"[Text Word] OR
"premature birth"[MeSH Terms] OR "infant, low birth
weight"[MeSH Terms] OR "premature"[Text Word] OR
"fetal growth retardation"[MeSH Terms] OR "abortion,
spontaneous"[MeSH Terms] OR "sepsis"[MeSH Terms] OR
"neonatal sepsis"[Text Word]).
Study selection
All studies identified from electronic databases (Pub-
Med, Web of Sciences, MEDLINE, and Cochrane
Library) were combined and imported onto a Men-
deley Desktop file. us far the researchers have
retrieved 4721 from the above-mentioned electronic
databases, 584 studies have been screened for eligibil-
ity, and approximately 124 studies may be included in
the review. Pending the search results from the grey
literature. Hence, grey literature studies will be manu-
ally entered into the Mendeley Desktop file. e dupli-
cate publications will be first detected and removed
automatically using the Mendeley reference manager.
For the screening, two reviewers will screen titles and
abstracts and the full text of potentially relevant articles.
If there are any disagreements between I.M and A.S
whether the study is to be included, a discussion will be
made with the L.M to resolve the differences. Figure1
shows the PRISMA flowchart that will be used in sum-
marizing the whole process of study selection, including
preliminary results.
Data collection process
To ensure that the appropriate data for the systematic
review is gathered, a structured form with the follow-
ing descriptive details: author’s information (name
and publication year), country of author, type of study,
types of samples, characteristics of the participant,
investigated genes, DNA methylation techniques, preg-
nancy outcomes as well as the statistical method used
to analyze data will be created. en if there are any
disagreements and conflicts between I.M and A.S, they
will be resolved by discussing with the L.M. In case
some information is missing from the individual study,
there will be efforts to contact the primary author (with
a maximum of three email attempts) to obtain the
missing data.
Risk ofbias inindividual studies
e first and second reviewers will evaluate the study’s
methodological quality and bias risk of the studies
using the Critical Appraisal Skill Programme (CASP)
tool [37]. CASP learning and development opportuni-
ties tool that is a part of the Oxford Centre for Triple
Value Health Ltd (3v) portfolio that aims to support the
development of critical appraisal skills in the United
Kingdom [37]. It is recommended for new qualitative
researchers to use CAPS which provides an appraisal
checklist for analyzing systematic reviews, cohort
studies, clinical prediction rules, economic evalua-
tion, case–control studies, observational studies, rand-
omized control trials as well as diagnostic studies and
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Moagietal. Systematic Reviews (2024) 13:4
it is recommended for new qualitative researchers [38].
e World Health Organization (WHO) and Cochrane
also support CAPS for qualitative evidence synthe-
sis. In case reviewers one and two disagree, the third
reviewer will resolve the discrepancies.
Data synthesis andanalysis
For this review data synthesis and analysis will be con-
ducted separately: (1) narrative synthesis wherein the
studies meeting the inclusion criteria will be summa-
rized and discussed and (2) statistical analysis wherein
the relationship between DNA methylation and APBOs
will be investigated.
Narrative synthesis
Regardless of whether the meta-analysis is appropri-
ate or not, studies meeting the inclusion criteria will be
narratively synthesized. A table summarizing the PI(E)
CO characteristics and results of the included studies,
thus author name, year of study, study design, partici-
pants characteristics, definition of exposure, and out-
comes will be developed [39]. Lastly, the bias risk will
be assessed for each of the included studies.
Fig. 1 The PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) flowchart for study selection, including preliminary results
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Moagietal. Systematic Reviews (2024) 13:4
Statistical analysis
For the purpose of the systematic review, it is predicted
that there will be variation amongst the included stud-
ies based on methodological variability (diversity in
risk of bias and study design) and clinical variability
(diversity in PI(E)CO) [34]. erefore, inverse variance
weighting will be used in a meta-analysis to calculate
pooled effect estimates [26]. For the assessment of the
degree of inconsistency, forest plot for a pooled esti-
mate of the outcomes will be used first. In prospec-
tive cohorts, retrospective cohorts, and cross-sectional
studies, the risk ratio (RR with 95% CI) will be used to
measure the relationship between gene-specific DNA
methylation with APOs while the odd ratio (OR with
95% CI) will be used in case–control (Ahn and Kang.,
2018). Chi-square (
χ2
) alpha = 0.10 and
I2
statistic will
be used for assessing statistical heterogeneity between
studies. Adding to χ2 and I2 statistics, T2 statistics will
be reported thus, to determine how widely distributed
the true effects are, especially in the case of meta-anal-
yses with a small number of studies.
I2
of 50% as a moderate or substantial heterogeneity
as a guide will be considered in the systematic review
[26]. For a meta-analysis with absent or low hetero-
geneity (I2 < 50%), a fixed-effected model will be used
whereas for moderate or severe heterogeneity, random-
effects will be performed [23]. e cause of heteroge-
neity will be investigated using the meta-regression and
subgroup analysis. Variables such as study design, study
population, sample size, and outcomes will be used to
identify the source of heterogeneity [36]. Meta-analyses
will be performed using Comprehensive Meta-analysis
(CMA) software Version 3.
Meta‑biases assessment
A funnel plot will be used to assess the probability of
publication bias in case there are more than 10 publi-
cations looking at the association between DNA meth-
ylation status with pregnancy and birth outcomes. For
the purpose of evaluating potential publication bias in
meta-analysis, Egger’s test for funnel plot will be used
[40]. In case of less than 10 studies, a cumulative meta-
analysis will be performed, with the studies arranged
from the largest to the smallest.
Condence incumulative evidence
e overall quality of extracted data will be assessed and
graded using the Grading of Recommendations, Assess-
ment, Development, and Evaluation (GRADE) method
considering the following factors: limitation in study
design, unexplained heterogeneity, inaccuracy of effect
estimates, and risk of publication of bias [26, 34, 36].
Expected outcomes
Several studies have been published on the association
between DNAm with pregnancy and birth outcomes. To
our knowledge, there are evidence-based and comprehen-
sive reviews published on the association between both
gene-specific and global DNAm during pregnancy with
pregnancy and birth complications such as PTB, LBW,
IUGR, sepsis, and miscarriage all at once. ese call out
for the need of comprehensive and systematic information
about this association, and to identify the knowledge gaps
and to guide future research that will explain how epigenet-
ics affect pregnancy outcomes. erefore, the main reason
for the systematic review and meta-analysis will be to com-
pile data or information from the published studies on the
association between DNA methylation with APBOs.
Dissemination
e Preferred Reporting Items Systematic Review and
Meta-Analysis Protocol (PRISMA) guideline will be fol-
lowed in reporting the systematic review protocol. Both
the systematic review and the protocol will be part of
Moagi’s MSc research dissertation in which A Samie is
the main supervisor, L Mabasa and M.S Maputle are the
co-supervisors. Before being submitted for publication in
a peer-reviewed journal, the findings from the systematic
review will be presented at conferences.
Authors’ contributions
IM, AS, and LM helped design the study and conceived the idea. IM drafted
the systematic review protocol revised by AS and SMM with input from MT,
NML, and RNS. The search strategies were developed by IM, AS, DN, and LM
and they will conduct the study selection as well. IM, AS, and DN will oversee
data extraction and will also perform statistical analysis. All co-authors read
and approved the final manuscript.
Funding
The research reported herein was made possible through funding/partial
funding by the South African Medical Research Council through its Division of
Research Capacity Development under the Research Capacity Development
Initiative. The content hereof is the sole responsibility of the authors and does
not necessarily represent the official views and sentiments of the funders.
Declarations
Ethics approval and consent to participate
There are no individual person’s data used in this manuscript, therefore ethical
approval and consent are not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Faculty of Sciences, Engineering and Agriculture, Department of Biochemistry
and Microbiology, University of Venda, Private Bag X5050, Thohoyandou 0950,
South Africa. 2 Biomedical Research and Innovation Platform (BRIP), South
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Moagietal. Systematic Reviews (2024) 13:4
Africa Medical Research Council, Tygerberg, P.O Box 19070, Cape Town 7505,
South Africa. 3 Faculty of Health Sciences, Department of Advanced Nursing
Sciences, University of Venda, Private Bag X5050, Thohoyandou 0950, South
Africa. 4 Cochrane South Africa, South Africa Medical Research Council, Parow
Valley, Cape Town 7501, South Africa.
Received: 17 February 2023 Accepted: 5 December 2023
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