PLOS ONE
STUDY PROTOCOL
APOL1 genotype associated risk for
preeclampsia in African populations:
Rationale and protocol design for studies in
women of African ancestry in resource limited
settings
Charlotte Osafo 1,2ID *, Nicholas Ekow Thomford3,4, Jerry Coleman5‡, Abraham Carboo6‡,
a1111111111 Chris Guure7‡, Perditer Okyere7‡, Dwomoa Adu1☯, Richard Adanu8☯, Rulan S. Parekh9☯,
a1111111111 David Burke10☯
a1111111111
1 Department of Medicine and Therapeutics, School of Medicine and Dentistry, College of Health Sciences,
a1111111111
University of Ghana, Accra, Ghana, 2 The Bank Hospital, Cantonment, Accra, Ghana, 3 Pharmacogenomics
a1111111111 and Genomic Medicine Group, Department of Medical Biochemistry, School of Medical Sciences, College of
Health and Allied Sciences, University of Cape Coast, Cape Coast, Ghana, 4 Division of Human Genetics,
Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa,
5 Department of Obstetrics and Gynecology, Korle Bu Teaching Hospital, Accra, Ghana, 6 School of Public
Health, College of Health Sciences, University of Ghana, Accra, Ghana, 7 School of Medical Sciences,
OPEN ACCESS KNUST, Kumasi, Ghana, 8 Ghana College of Physicians and Surgeon, Accra, Ghana, 9 Departments of
Pediatrics and Medicine, Hospital for Sick Children, University of Health Network, University of Toronto,
Citation: Osafo C, Thomford NE, Coleman J, Toronto, Canada, 10 Department of Human Genetics, University of Michigan Medical School, Ann Arbor,
Carboo A, Guure C, Okyere P, et al. (2022) APOL1 Michigan, United States of America
genotype associated risk for preeclampsia in
☯ These authors contributed equally to this work.
African populations: Rationale and protocol design
‡ JC, AC, CG and PO also contributed equally to this work.
for studies in women of African ancestry in
* charlotte.osafo@thebankhospital.com
resource limited settings. PLoS ONE 17(12):
e0278115. https://doi.org/10.1371/journal.
pone.0278115
Abstract
Editor: Vicente Sperb Antonello, Hospital Femina,
BRAZIL
Received: April 10, 2022 Background
Accepted: November 9, 2022 Women of African ancestry are highly predisposed to preeclampsia which continues to be a
Published: December 29, 2022 major cause of maternal death in Africa. Common variants in the APOL1 gene are potent
risk factor for a spectrum of kidney disease. Recent studies have shown that APOL1 risk
Peer Review History: PLOS recognizes the
benefits of transparency in the peer review variants contribute to the risk of preeclampsia. The aim of the study is to understand the con-
process; therefore, we enable the publication of tribution of APOL1 risk variants to the development of preeclampsia in pregnant women in
all of the content of peer review and author
Ghana.
responses alongside final, published articles. The
editorial history of this article is available here:
https://doi.org/10.1371/journal.pone.0278115 Methods
Copyright: © 2022 Osafo et al. This is an open The study is a case-control design which started recruitment in 2019 at the Korle Bu Teach-
access article distributed under the terms of the ing Hospital in Ghana. The study will recruit pregnant women with a target recruitment of
Creative Commons Attribution License, which
700 cases of preeclampsia and 700 normotensives. Clinical and demographic data of
permits unrestricted use, distribution, and
reproduction in any medium, provided the original mother- baby dyad, with biospecimens including cord blood and placenta will be collected to
author and source are credited. assess clinical, biochemical and genetic markers of preeclampsia. The study protocol was
Data Availability Statement: All relevant data are approved by Korle Bu Teaching Hospital Institutional Review Board (Reference number:
within the paper. KBTH-IRB/000108/2018) on October 11, 2018.
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PLOS ONE Preeclampsia and APOL1
Funding: CO- Fogarty International Center of the Preliminary results
National Institutes of Health under Award Number
K43TW011160. The funders had and will not have As of December 2021, a total of 773 mother-baby pairs had been recruited and majority of
a role in study design, data collection and analysis, them had complete entry of data for analysis. The participants are made up of 384 pre-
decision to publish, or preparation of the eclampsia cases and 389 normotensive mother-baby dyad. The mean age of participants is
manuscript.
30.69 ± 0.32 years for cases and 29.95 ± 0.32 for controls. Majority (85%) of the participants
Competing interests: The authors have declared are between 20-30years. At booking, majority of cases had normal blood pressure com-
that no competing interests exist.
pared to the time of diagnosis where 85% had a systolic BP greater than 140mmHg and a
corresponding 82% had diastolic pressure greater than 90mmHg.
Conclusion
Our study will ultimately provide clinical, biochemical and genotypic data for risk stratification
of preeclampsia and careful monitoring during pregnancy to improve clinical management
and outcomes.
Introduction
Up to 8% of pregnancies are complicated by hypertensive disorders [1] resulting in maternal
and neonatal morbidity and mortality particularly in developing countries [1, 2]. Pregnancy-
related hypertensive disorder is referred to as preeclampsia which is characterized by new
onset of hypertension (blood pressure�140/90mmHg) and proteinuria (greater than 1+ or
300mg per 24hours) after 20 weeks gestation [3, 4]. This definition has been expanded to
include renal, liver, hematological and neurological dysfunction and fetal growth restriction
[5]. The prevalence of preeclampsia in sub-Saharan Africa is high with an incidence rate of
over 15% [6]. In sub-Saharan regions such as West Africa and especially Ghana, there is a
reported incidence of approximately 8% [7]. A systematic analysis of prevalence of preeclamp-
sia across sub-Saharan Africa has seen an increase over the past decade [6]. Women of African
ancestry are highly predisposed to preeclampsia with a greater propensity to develop into a
more complicated form known as HELLP (H = Haemolysis, EL = Elevated Liver enzymes,
LP = Low Platelets) syndrome [8–11]. It is estimated that the prevalence of preeclampsia is
higher in indigenous African women and those of African ancestry diaspora [8] than any
other racial groups. This susceptibility to preeclampsia appears independent of socioeconomic
status and may potentially be due to genetic factors [12, 13].
Genetic susceptibility to preeclampsia has for several decades been suspected but there is
very limited research in this area especially among women of African ancestry. Predominant
functional candidate genes studies in pre-eclampsia have targeted mechanisms such as throm-
bophilia (F5, MTHFR, F2, SERPINE1), Endothelial function (eNOS3, VEGFR1), vasoactive
proteins (AGT, ACE), oxidative stress and lipid metabolism (APOE, EPHX, GST) and immu-
nogenetics (TNF, IL10). Such studies have mostly been conducted in other populations and
often target only maternal genotype.
Despite the long-term sequelae of preeclampsia, which includes increased risk of hyperten-
sion, cardiovascular disease, chronic kidney disease (CKD) and end stage renal disease (ESRD)
among women of African descent, little is known about genetic risk factors such as apolipo-
protein L1 (APOL1) risk. Common variants in the apolipoprotein L-1 gene (APOL1) only
found predominantly in West Africans, make up the 2 risk haplotypes termed G1 and G2,
which are potent risk factors for a spectrum of kidney diseases [14] but very rare in European
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PLOS ONE Preeclampsia and APOL1
ancestry individuals. There is a strong relationship between kidney function and hypertension
[15, 16] and considering the importance of the APOL1 gene to people of African descent, an
in-depth understanding of the role of this gene in preeclampsia in indigenous African women
will be key to understanding preeclampsia genetics and advance biomarker innovations.
APOL1 high risk variants [17] are present at high frequencies in populations of West Afri-
can descent and account for much of increased risk of non-diabetic chronic kidney disease
[18, 19]. Among populations from Nigeria and Ghana, the APOL1 high-risk genotype fre-
quency approaches 25% and 13% in African Americans who share west African ancestry. The
frequencies are enriched among those with chronic kidney disease [18, 19]. It is known that
preeclampsia results in part from microangiopathy in the glomerulus of the kidney suggesting
a potentially important role of APOL1 in preeclampsia [20, 21]. Evidence from previous stud-
ies have found associations of APOL1 risk variants with microangiopathy in HIV positive
patients [22, 23]. In a transgenic mouse model, a pregnancy-associated phenotype that encom-
passed eclampsia, preeclampsia, fetal wasting occurred in some Tg-G0 mice and Tg-G2 mice.
Placentas of Tg mice expressed APOL1, similar to human placenta, suggesting a role for
APOL1 in preeclampsia [24]. Small sample sized studies have looked at the genotype associ-
ated risk for preeclampsia in women of African ancestry [25, 26] mostly looking at African
Americans. APOL1 conferred a 2-fold increased risk of preeclampsia for fetuses carrying
homozygotes or compound heterozygotes (G1/G1, G2/G2, or G1/G2), termed the high-risk
genotypes. In addition, high-risk APOL1 genotypes may present a higher proportion in infants
born from birth complications by preeclampsia and may have poor perinatal outcomes [27].
These studies thus suggest there is an interaction between the fetus and/or placenta resulting
in causal effects for preeclampsia resulting in a potential long-term effect on CKD develop-
ment in women [26]. It is also conceivable that APOL1 expression in the placenta may play a
causal role in preeclampsia, which may be modulated by either maternal or infant APOL1
genotype.
To date there has been no studies in indigenous women of African ancestry specifically
focusing on APOL1 associated risk factors with a highly powered sample size. Most studies
have been in African Americans without sufficiently large sample size, which has been mostly
the challenge. Developing a study that is aimed specifically at genotype associated risk pre-
eclampsia allows for accurate biomedical and clinical phenotyping and identification of geno-
type-phenotype associated risk factors with clinical and birth outcomes. There still remains a
gap in differential impact of APOL1 status of mother and child with either maternal or perina-
tal outcomes. This study would give some idea about the penetrance of APOL1 in African pop-
ulations experiencing different demographics and environmental stressors than African
descendants living in the USA. The overarching objective for the APOL1 characterization in
preeclampsia is to undertake a comprehensive genotype-phenotype of a cohort with transla-
tional potential. This study involves a team of clinicians with various specialties, scientists and
has capacity building component as part of the study.
Aims and objectives
The overall aim is to understand the influence of APOL1 on preeclampsia and its sequelae on
both perinatal and maternal outcomes using a case- control design. The study will: (1) examine
the association of APOL1 risk variants in pregnant women with preeclampsia compared to nor-
motensive pregnant women, (2) determine the risk of perinatal outcomes among infants from
mothers with pre-eclampsia compared to infants from normotensive mothers by APOL1 risk
variant status and (3) Undertake a longitudinal follow up of both the preeclamptic and normo-
tensive mothers recruited into the study to determine the incidence of non-communicable
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Box 1. Impact and innovation of study
• Determination of risk of both maternal and infant APOL1 risk variants and associa-
tion with preeclampsia.
• Have novel insights into genetic factors that increase risk for worse perinatal
outcomes.
• Create a research platform with a well characterized cohort and specimen repository
for clinical and translational studies in preeclampsia among women of African ances-
try for African investigators.
• Harness a simple genotyping platform to develop a preconception screening platform
for high-risk women who present at a health facility.
• Developing genetic tools to predict risk of preeclampsia in women of African ancestry
with direct impact on the clinical care during pregnancy and perinatal outcomes, as
well as reducing maternal fatality.
diseases including Chronic Kidney Disease (CKD), Hypertension, Stroke, Mental Health and
Cardiovascular diseases among the women with preeclampsia versus normotensive women
stratified by APOL1 status.
Impact and innovation
This study is key to addressing an important disease related to pregnancy with a potential for
biomarker innovation. One unique aspect of this study is the population cohort of black Afri-
can women. Outcome from the study will provide data on risk stratification for preeclampsia
and information on careful monitoring during pregnancy with clinical correlation (Box 1).
This study is timely and addresses an important public health issue as maternal health
improves the health and welfare of entire communities.
Methods
Study design/population
The work describes a case-control study design with a target number of 700 cases of pre-
eclampsia and 700 cases of normotensive pregnant women, prospectively enrolled. Recruit-
ment started in May 2019 involving women who are diagnosed with preeclampsia for the very
first time as cases. The target population are African women; however, the only recruiting
facility is KBTH in Ghana. The work will capture a significant number of Ghanaian women
with longitudinal follow-up over 3 years. All pregnant women will be eligible for recruitment.
Eligible women will be screened and enrolled into the study after provision of informed
consent.
Ethical consideration
The study protocol was approved by the Korle Bu Teaching Hospital Scientific and Technical
committee/ Institutional Review Board (reference number: KBTH-STC/IRB/000108/2018).
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PLOS ONE Preeclampsia and APOL1
Table 1. Inclusion and exclusion criteria.
Inclusion criteria Exclusion criteria
Cases
Preeclampsia will be defined as women with new onset Prior history of preeclampsia
of hypertension (blood pressure�140/90mmHg) and
proteinuria (greater than 1+ or 300mg per 24hours)
after 20 weeks gestation
Patients with preeclampsia, who develop eclampsia and Patients with prior chronic hypertension defined as
HELLP syndrome hypertension that precedes pregnancy or occurs in the first
half of pregnancy
Controls Patients with existing co-morbid conditions such as
diabetes, antepartum hemorrhage, other endocrine
conditions or any secondary hypertension
Participants who did not have a diagnosis of Patients who have had blood transfusion in the last three
preeclampsia at any time during the pregnancy months
Patients who sign informed consent Patients who do not sign informed consent
https://doi.org/10.1371/journal.pone.0278115.t001
Written informed consent was obtained from participants after explaining to them about the
study with the option of discontinuing without any consequences. The inclusion and exclusion
criteria are shown in Table 1.
Overview of data collection
Participants involved in the study went through a comprehensive clinical assessment, an over-
view of which is shown in Fig 1. This assessment also included each baby that was born.
Recruitment strategy. The recruitment team which is made up of nurses, doctors and
medical laboratory scientists underwent training and familiarization with the goals of the proj-
ect at the maternity block of Korle Bu Teaching Hospital (KBTH), which is a university affili-
ated teaching hospital. The team was then trained on how to obtain informed consent, and
how to use the Redcap app to collect data. In addition, the team was taken through a practical
session on how to take cord blood and placenta sample, how to snap freeze placenta sample
Fig 1. Overview of the clinical assessment.
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PLOS ONE Preeclampsia and APOL1
and cord blood and how to package maternal samples for collection and processing by the lab-
oratory technician.
To ensure efficient patient recruitment and improve communication among team mem-
bers, a WhatsApp group was created for the team members to alert members of potential
patients for recruitment and to report issues that needed urgent attention.
Our data collection instrument was transferred onto the redcap app which was initially
implemented on three android tablets. After an initial pilot, we noticed that it was easier on
phone so the app was installed on the phone. Each member of the recruitment team was given
a unique identifier available for use from an earlier project that had been completed.
Patients were assessed as potential candidates for recruitment based on their medical his-
tory. The clinical team talked to the patient in the language the patients understood and then
sought consent. Once consent was given, patients were recruited into the study, given a unique
code and a comprehensive questionnaire administered. Clinical information was taken from
patients’ folders and then study visits scheduled based on patient’s appointment at the facility.
Since study participants attended antenatal clinics, study related data collection was sched-
uled to coincide with the hospital visit so as not to inconvenience them. The schedules of all
antenatal visits were maintained and the estimated time of delivery kept. On the day of deliv-
ery, samples were collected and newborn baby assessed.
Data collection and quality control. The target participants for this study include a
minimum of 1400 participants of age-matched cases of patients with preeclampsia and con-
trols of normotensive patients. The sample size has enough statistical power to allow a robust
interpretation of the variables that will be collected as part of the cohort and clinical out-
comes which will serve as our phenotypes. The data collected is collated and entered into
Redcap by a team of clinicians, research scientists, laboratory technicians and data entry
clerks. To maintain data validity and quality control, regular meetings were held with the
study coordinator and recruitment team to review enrollment, data entry, missing informa-
tion and specimen collection. The data are stored in a database that provides detailed
recording of clinical, demographic and phenotyping characteristics of the cohort. Access
to Redcap is limited to key personnel of the research team that ensures data quality and
reconciliation.
Sample collection and laboratory assays. During the course of the study, we established
an accompanying biorepository which will be available for future study. Samples collected
from pregnant mothers included whole blood and urine on the day of recruitment. All samples
collected are barcoded for both mother and child and stored at -80 degrees Celsius. At delivery,
placenta and cord blood were collected. Placental samples were collected from a standardized
location approximately 2cm beside the umbilical cord insertion, from the middle layer of pla-
centa midway between maternal and fetal surfaces. The samples were cut into 1cm cubes and
snap frozen in liquid nitrogen. Cord blood was snap frozen within 10mins of collection and
then stored at -80 degree Celsius. Blood samples were processed by MDS laboratory. Labora-
tory tests were conducted according to local laboratory protocols. All biochemical tests were
undertaken with automated analysers at the research lab of MDS Lancet laboratories, Ghana
(https://www.cerbalancetafrica.com.gh/). All patients recruited into the study underwent an
initial laboratory testing to obtain a baseline hematological and kidney function tests. For the
mothers, hemoglobin, white blood cell and platelet counts, liver function tests, serum creati-
nine and urine albumin creatinine ratio were conducted. Several biomarkers have been used
to diagnose preeclampsia and serve as valuable indicators. These include (i) renal impairment
markers (serum creatinine, urine albumin creatinine ratio) (ii) liver dysfunction markers
(AST, ALT) (iii) hypertension markers, and (iv) reduced platelets. These markers were
used for phenotyping of preeclampsia and interpreted through the genetic model that will be
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PLOS ONE Preeclampsia and APOL1
Table 2. Biomarkers and time points for collection.
Preeclampsia Renal function Inflammation
Biomarker Time Point for Collection Biomarker Time Point for Collection Biomarker Time Point for Collection
VEGF At recruitment SCr At recruitment and annually CRP At recruitment
PIGF UACR IL-6
s-FLT-1 - IL-8
s-Eng - TNF-alpha
VEGF: Vascular Endothelial Growth Factor; PIGF: Placenta Growth Factor; s-FLT-1: Soluble fms-like tyrosine kinase; s-Eng: Soluble Endoglin; sCr: Serum Creatinine;
UACR: Urine Albumin Creatinine Ratio; CRP: C-reactive protein; IL-6: Interleukin 6; IL-8: Interleukin 8; TNF-alpha: Tumour Necrosis Factor alpha.
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generated. Random duplicate samples will be taken for validation of laboratory measurements
periodically. We plan to measure biomarkers for preeclampsia (Table 2), conduct placental
histology and also follow up both babies and their mothers to determine the incidence of
chronic kidney disease and other non-communicable diseases. Preeclampsia is not an easy
condition to diagnose and thus physicians typically rely on several symptoms to guide diagno-
sis (Fig 2).
Genetic analysis
DNA has been isolated and currently samples are being prepared for APOL1 genotyping. In
this study multiple SNP analysis will be performed to further explore the genetic predisposi-
tion to preeclampsia in West African women. Selected APOL1 SNPs to be considered are
G1: rs73885319, rs60910145, and G2:rs71785313, rs12106505. Several studies on the genetic
predisposition to preeclampsia have attempted to use candidate gene approach. These can-
didate gene approach have often focused on maternal genes as causative genes. Preeclamp-
sia appears to be associated with APOL1 variants G1 and G2 [28, 29]. However APOL1
variants in preeclampsia are complex, as some studies have linked disease with maternal
APOL1 [30], while others with fetal APOL1 variants [25, 27]. Genotyping will be undertaken
in Ghana using predesigned TaqMan assays in the Pharmacogenomics and Genomic
Medicine laboratory (www.pgmg-lab.com), School of Medical Sciences, University of Cape
Coast.
Fig 2. Summarized pathogenesis of preeclampsia.
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Current status of the study
Preliminary data and current status of study
Recruitment is currently on going, with a target goal of 1400 participants. however as of 2021, a
total of 773 mother baby dyad have been recruited making more than half of each recruitment
group. These were made up of 384 pre-eclampsia individuals and 389 normotensive mother-
baby dyad. Preliminary data and baseline characteristics of the participants are shown in Table 3.
The mean age of the preeclampsia patients is 30.69 ± 0.32 years, while that of normotensive
controls is 29.95 ± 0.32 years. The majority (~85%) of the participants are between 20–30
years, with 70% of them being married. At recruitment, 82% of the preeclampsia participants
were having normal systolic blood with a corresponding 77% diastolic blood pressure
(Table 2). After 20 weeks 85% had systolic blood pressure of more than 140mmHg for pre-
eclampsia participants with 82% having a diastolic blood pressure of greater than 90mmHg.
Normotensive controls had more than 90% of the participants having a systolic blood pressure
of less than 140mmHg and a diastolic blood pressure of less than 90mmHg.
Clinical and biochemical indicators of preeclampsia is shown in Table 4. The preliminary
results indicate variations in the various biochemical parameter of susceptibility to preeclamp-
sia and phenotyping.
Table 5 shows family history of diseases that could predispose mothers to preeclampsia.
Majority of participants had no family history of diabetes mellitus, sickle cell disease, asthma,
preeclampsia, birth defects or multiple pregnancies.
Discussion and study challenges
Preeclampsia is a significant complication in pregnant women with consequences of morbidity
and mortality for both the mother and the child. Despite several decades of research and an eti-
ology leading to disease, clinicians are unable to predict and manage preeclampsia prior to
symptom onset. Traditionally, clinicians have relied on maternal risk factors such as age, fam-
ily history and comorbidities in trying to identify “at-risk” women. These traditional risk fac-
tors are generalized and non-modifiable in several conditions and thus affects accuracy in
classifying women. Several angiogenic biomarkers are being developed in several populations
to improve prediction [30–32].
Though angiogenic markers may be helpful in diagnosis and eventual management of pre-
eclampsia, identifying genetic biomarkers in preeclampsia will increase the prediction of
genetic predisposition and associated triggers and environments. Genetic predisposition to
preeclampsia plays a significant role in the condition and identifying “at risk” women may
prevent preeclampsia-related complications. The gene APOL1 has been implicated in pre-
eclampsia, consequently, the role of APOL1 in populations of African origin may achieve
opportunities for improved diagnosis and management. Given the utility of genetic screening
in medical genetics practice, the uniqueness and potential for APOL1 screening to identify “at
risk” women will be very useful. The current study has a recruitment target of 1400 mother-
baby dyad in a longitudinal study design that includes comprehensive clinical assessments at
sequential pre-birth timepoints and post-delivery clinical and morphologic assessment. There
is a comprehensive plan to follow up on both mother and baby to observe for any complica-
tions arising from preeclampsia during birth.
Our preliminary data so far have shown distinct characteristics among the preeclampsia
patients and controls. During antenatal visits, an increase in blood pressure of�140/90mmHg
after 20 weeks were observed in our preeclampsia patients. Biochemical and clinical parameters
of preeclampsia were also observed in several of diagnosed preeclampsia patients. The majority
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Table 3. Characteristic of recruited patients with and without preeclampsia.
Variable Enrolled pairs
Cases n (%) Control n (%)
N 773 384 389
Maternal age (years)
mean ± SE 30.69 ± 0.32 29.95 ± 0.32
10–19 12 (3.13) 29 (7.46)
20–29 167 (43.49) 142 (36.50)
30–39 176 (45.83) 194 (49.87)
40–49 28 (7.29) 23 (5.91)
Missing 1 (0.26) 1 (0.26)
Marital status
Married 278 (72.40) 274 (70.44)
Single 92 (23.96) 110 (28.28)
Co-habiting 7 (1.82) 1 (0.26)
Missing 7 (1.82) 3 (0.77)
Maternal BMI (kg/m2)
@booking <18.5 22 (5.73) 14 (3.60)
18.5–24.9 73 (19.01) 121 (31.11)
25.0–29.9 108 (28.13) 108 (27.76)
30–39.9 92 (23.96) 79 (20.31)
�40 16 (4.17) 10 (2.57)
Missing 73 (19.01) 57 (14.65)
@20 weeks
<18.5 0 (0) 0 (0)
18.5–24.9 0 (0) 1 (0.26)
25.0–29.9 1 (0.26) 0 (0)
30–39.9 0 (0) 0 (0)
�40 175 (45.57) 156 (40.10)
Missing 208 (54.17) 232 (59.64)
@ after 30weeks
<18.5 112 (29.17) 97 (24.94)
18.5–24.9 13 (3.39) 28 (7.20)
25.0–29.9 46 (11.98) 83 (21.34)
30–39.9 114 (29.69) 106 (27.25)
�40
Missing 73 (19.01) 57 (14.65)
Ethnicity
Akan 180 (46.88) 173 (44.47)
Ewe 42 (10.94) 43 (11.05)
Ga 70 (18.23) 95 (24.42)
Hausa 31 (8.07) 24 (6.17)
Ga-Adangbe 9 (2.34) 3 (0.77)
Others 31 (8.07) 30 (7.71)
Missing 21 (5.47) 21 (5.40)
Education
No formal education 25 (6.51) 18 (4.63)
Primary 35 (9.11) 55 (14.14)
Junior High School 133 (34.64) 103 (26.48)
Senior High School 109 (28.39) 118 (30.33)
Vocational School 0 (0.00) 3 (0.77)
Tertiary 60 (15.63) 77 (19.79)
Missing 19 (4.95) 1 (0.26)
(Continued)
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PLOS ONE Preeclampsia and APOL1
Table 3. (Continued)
Variable Enrolled pairs
Cases n (%) Control n (%)
Alcohol usage
Gave up before pregnancy 33 (8.59) 24 (6.17)
Gave during Pregnancy 13 (3.39) 8 (2.06)
Never 334 (86.98) 355 (91.26)
Missing 4 (1.04) 2 (0.51)
Systolic BP (mmHg)
@booking 60–139 315 (82.03) 362 (93.06)
>140 41 (10.68) 2 (0.51)
missing 28 (7.2) 25 (6.43)
@diagnosis 60–139 42 (10.94) 358 (92.03)
>140 332 (85.35) 22 (5.66)
missing 10 (2.60) 9 (2.31)
Diastolic BP (mmHg)
@booking 10–89 296 (77.08) 352 (90.49)
>90 60 (15.63) 10 (2.57)
Missing 28 (7.29) 27 (6.94)
@diagnosis.
10–89 54 (14.06) 347 (89.20)
>90 318 (82.81) 33(8.48)
Missing 12 (3.13) 9 (2.31)
Gravidity
1 91 (23.70) 87 (22.37)
2 77 (20.05) 1 (0.26)
3 61 (15.89) 1 (0.26)
4 57 (14.84) 1 (0.26)
5 45 (11.72) 102 (26.22)
6 19 (4.95) 74 (19.02)
7 19 (4.95) 61 (15.68)
8 4 (1.04) 34 (8.74)
9 4 (1.04) 15 (8.74)
10 4 (1.04) 5 (1.29)
Missing 3 (0.78) 2 (0.51)
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of patients had no family history of disease, preexisting hypertension, sickle cell disease, or
prior preeclampsia. Our methodology and recruitment strategies have been designed with an
aim to addressing and standardizing evidential gaps especially in phenotyping. Data collection
has been comprehensive and 1033 data collection tools capturing clinical and treatment his-
tory, biochemical markers and clinical features of both mother and babies have been obtained.
There is a limitation to our study. Our sample was limited to women without a prior history
of preeclampsia. This removes from our study population women who might have recurrent
preeclampsia due to their (or their fetus’) APOL1 status. This may result in an underestimate
of the relationship between APOL1 and preeclampsia.
Challenges
Protocol, recruitment, and patient attrition. There have been several challenges during
the implementation of the project. A primary challenge is the attrition rate of recruitment
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PLOS ONE Preeclampsia and APOL1
Table 4. Clinical parameters and hematological indicators of preeclampsia.
Variable Enrolled pairs
Cases n (%) Control n (%)
N 773 384 389
Hb (g/dL) 0–11 212 (54.95) 236 (60.67)
12–16 123 (32.03) 103 (26.48)
Missing 49 (12.76) 50 (12.85)
PLT (x 109/L 5–150 46 (11.98) 22 (5.66)
151–450 135 (34.70) 159 (40.87)
451–600 1 (0.26) 0 (0.00)
Missing 202 (52.60) 208 (53.47)
eGFR (ml/min/1.73m2) 0–15 1 (0.26) 0 (0.00)
16–29 5 (1.30) 1 (0.26)
30–59 18 (4.69) 2 (0.51)
60–89 199 (51.82) 179 (46.02)
Missing 161 (41.93) 207 (53.21)
HCT (L/L) 0–0.47 205 (53.39) 194 (49.87)
>0.47 1 (0.26) 0 (0.00)
Missing 178 (46.35) 195 (50.13)
UACR (mg/mmol) <3 10 (2.60) 51 (13.11)
3–30 34 (8.85) 101 (25.96)
>30 160 (41.67) 40 (10.28)
Missing 180 (46.88) 197 (50.64)
https://doi.org/10.1371/journal.pone.0278115.t004
nurses from the project in pursuit of other ventures. At the commencement of the project, we
had several meetings and training activities with the nursing staff to map out strategies and the
recruitment plan. Recruitment began appropriately, with approximately 30 patients (cases and
controls) per month. However, as the trained nurses left, recruitment dropped while the
replacement nurses were recruited and trained to tasks. Multiple cases and fetal samples were
missed by newly-trained staff. Delivery times at late night and early mornings resulted in miss-
ing samples. Frequently, patients are in labor for several hours. During late evenings, trained
team recruitment nurses complete their shifts and hand over to a colleague. Even with clear
instructions, the take-over nurses fail to obtain samples. We solved this issue by employing a
recruitment nurse during the night shift to assist in night recruitment and to reduce sample
collection losses.
Table 6 summarizes the major challenges encountered in the project and interventions
implemented and Fig 3 shows the change in cord sample numbers per year after intervention.
The total percentage of cord blood and placental samples missed in 2021 was 8.41% compared
with 17.92% in 2020.
Data entry and integrity. Our data is collected using the web-based Research Electronic
Data Capture (REDCap) management system. Data quality was captured using a standard
data entry interface. Records are updated regularly and the integrity checked weekly. Data
entry has been allocated to specific data collectors and scientists to ensure accuracy. How-
ever, some missing data can be observed in the preliminary data shown in Tables 2–4. Miss-
ing data is primarily the result of: (1) missing research IDs for patients, (2) biochemical
data lost at the testing laboratory, and (3) loss of Internet connectivity from field data
collectors.
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PLOS ONE Preeclampsia and APOL1
Table 5. Family History of risk factors for participants with and without preeclampsia.
Variable Enrolled pairs
Cases n (%) Control n (%)
N 773 384 389
Diabetes mellitus No 362 (94.27) 365 (93.83)
Yes 12 (3.13) 17 (4.37)
Unknown 4 (1.04) 3 (0.77)
Missing 6 (1.56) 4 (1.03)
Sickle Cell Disease No 359 (92.29) 363 (93.32)
Yes 12 (3.13) 16 (4.11)
Unknown 8 (2.08) 6 (1.54)
Missing 5 (1.30) 4 (1.03)
Asthma No 363 (94.53) 368 (94.60)
Yes 9 (2.34) 6 (1.54)
Unknown 5 (1.30) 8 (2.06)
Missing 7 (1.82) 7 (1.80)
preeclampsia No 361 (94.01) 361 (92.80)
Yes 2 (0.52) 1 (0.25)
Unknown 17 (4.43) 18 (4.46)
Missing 4 (1.04) 9 (2.31)
Birth defects No 374 (97.40) 379 (97.43)
Yes 3 (0.78) 4 (1.03)
Unknown 3 (0.78) 3 (0.77)
Missing 4 (1.04) 3 (0.77)
Multiple pregnancies No 272 (70.83) 271 (69.67)
Yes 104 (27.08) 111 (28.53)
Unknown 4 (1.04) 3 (0.77)
Missing 4 (1.04) 4 (1.03)
https://doi.org/10.1371/journal.pone.0278115.t005
Genotyping and infrastructure development. Preeclampsia and its associated health out-
come phenotype measures must be supported by the acquiring of relevant genotype data. The
global COVID-19 pandemic has disrupted local African research laboratory genotyping. Once
a robust and consistent genotyping infrastructure is re-activated, we will complete the geno-
typing of these study samples. In tandem with the clinical research capacity demonstrated in
this work, we continue to build local expertise in molecular genetics, clinical research skills,
data analysis, and a biorepository for patient cohort samples.
Conclusion
Our study addresses an important disease in pregnancy with significant morbidity and mortal-
ity that has not been well studied in large populations in Africans with a high burden of
preeclampsia and APOL1 high risk genotypes. Despite the difficulties in the recruitment of
mother-baby dyad in a low middle income country as well as the sudden emergence of
COVID-19 pandemic which brought recruitment to a standstill, our study has been successful
in recruiting more than 700 participants within the last 26 months. The results obtained from
our study will assist in developing genetic tools to predict risk of preeclampsia in women of
African ancestry worldwide, with direct impact on the clinical care during pregnancy and peri-
natal outcomes as well as reducing maternal fatality.
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PLOS ONE Preeclampsia and APOL1
Table 6. Timelines of major challenges encountered and interventions implemented.
Challenge Period of facing challenge/ Effect of Challenge Intervention Effect of new intervention
implementation (months)
Loss of trained recruitment 18 months Affected recruitment Increased the number of Reduction in the loss of samples (Fig
nurses numbers and missed recruitment nurses per ward or 3)
samples floor and robust backup plans
Parallel research projects 24 months Reduction in recruitment Division of recruitment floors Improvement in recruitment
competing for the same numbers and obtaining and patient management numbers and adequate blood
patients enough blood volumes volumes for further downstream
analysis
Patients had difficult veins 6 months Inadequate blood volumes Use of vacutainer apparatus to Volumes of blood increased
which meant we couldn’t get during recruitment increase blood volume
enough blood volumes
Hemolysis of blood samples 6 months Negatively affected Immediate separation of samples number of hemolysed samples
biochemical analysis after collection reduced
Recruitment during early 12 months Loss to follow up and Recruitment was planned to Reduction in loss of participants
stages of pregnancy emergency deliveries reduce the time between
recruitment and delivery
https://doi.org/10.1371/journal.pone.0278115.t006
Fig 3. Number of cord blood samples missed over the period of recruitment.
https://doi.org/10.1371/journal.pone.0278115.g003
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PLOS ONE Preeclampsia and APOL1
Acknowledgments
We are grateful to all research assistants, nurses and laboratory technicians for their contribu-
tion to the study, especially Portia Antwi, Richard Darko, Nancy Yeboah, Alberta Nimako,
Theresa Quartey, Joshua Quarshie, Mario Rashid Kadiah and Millicent Arhen. We also would
like to thank the patients for their help.
Author Contributions
Conceptualization: Charlotte Osafo, Dwomoa Adu, Rulan S. Parekh.
Data curation: Charlotte Osafo, Nicholas Ekow Thomford, Abraham Carboo, Chris Guure.
Formal analysis: Charlotte Osafo, Nicholas Ekow Thomford, Chris Guure.
Funding acquisition: Charlotte Osafo, Rulan S. Parekh, David Burke.
Investigation: Charlotte Osafo, Nicholas Ekow Thomford, Jerry Coleman, Abraham Carboo.
Methodology: Charlotte Osafo, Nicholas Ekow Thomford, Jerry Coleman, Abraham Carboo,
Perditer Okyere.
Project administration: Charlotte Osafo, Nicholas Ekow Thomford, Jerry Coleman, Perditer
Okyere, Richard Adanu, David Burke.
Resources: Charlotte Osafo, Nicholas Ekow Thomford, Jerry Coleman, Abraham Carboo, Per-
diter Okyere, Dwomoa Adu.
Supervision: Charlotte Osafo, Dwomoa Adu, Richard Adanu, Rulan S. Parekh, David Burke.
Validation: Nicholas Ekow Thomford, Abraham Carboo, Chris Guure.
Visualization: Chris Guure.
Writing – original draft: Charlotte Osafo, Nicholas Ekow Thomford.
Writing – review & editing: Charlotte Osafo, Nicholas Ekow Thomford, Jerry Coleman,
Abraham Carboo, Perditer Okyere, Dwomoa Adu, Richard Adanu, Rulan S. Parekh, David
Burke.
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