Fengping shao
Department of Obstetrics and Gynecology, The First Affiliated Hospital,
Sun Yat-sen University, Zhongshan Second Road 58, Guangzhou 510080,
Guangdong, China
Objective : To explore the potential factors that contribute to
the occurrence of medical abortion(MA) through a Mendelian
randomization(MR) study.
Design: Univariate MR(UVMR) and multivariate MR(MVMR) analyses.
Setting: Genetic variants from European populations.
Population or Sample: Instrumental variants for MA were
obtained from FinnGen with 36,232 cases and 149,622 controls.
Methods: The inverse variance weighting method was adopted as
the primary analysis.
Main outcome measures: The associations of MA with household
income(HI), education attainment(EA), cognitive performance(CP), risky
behaviors: smoking behavior(SB), alcohol consumption(AC), and
reproductive traits: age at first sexual intercourse(AFS), lifetime
number of sexual partners(LNSP), age at first birth(AFB), age at last
birth(ALB).
Results: In the UVMR, increasing HI, EA, AFS and AFB appeared
to reduce MA risk(HI, OR=0.569, P = 7.93E-08; EA, OR=0.875, P =
6.02E-21; AFS, OR=0.439, P = 5.17E-25; AFB, OR=0.815, P = 5.46E-12),
whereas SB and LNSP appeared to add to MA risk((SB, OR=1.424, P
=8.32E-11; LNSP, OR=2.777, P =2.14E-11). In the MVMR, EA, SB, LNSP and
AFS seems to be the predominant risk factor for MA risk with the
independent effect, while HI had no effect after controlling EA(HI in
model 1, OR=0.890, Pā=ā5.78E-01). AFB functioned as mediators in the
causal chain of MA risk reduction by EA, with the mediated proportion of
AFS and AFB being 57.8%.
Conclusions: Our MR study demonstrated the causal potential of
the associations of HI, EA, SB, LNSP, AFS and AFB with medical abortion.
Keywords: medical abortion, risk, causality, Mendelian
randomization.
Introduction
Abortion is a common healthcare intervention for unintended pregnancy.
Changes in abortion knowledge and attitudes over time that are perceived
as safer rather than more dangerous, easier as opposed to more difficult
to access, acceptable as opposed to wrong, or self-identifying as
pro-choice as opposed to pro-life[1]. It was estimated that there is
a global average of 73.3 million abortions per year, which corresponded
to 39 abortions for every 1,000 women aged 15-49 years[2]. However,
abortion may be associated with a series of immediate complications(e.g.
failed attempted abortion, hemorrhage, uterine perforation, cervical
trauma, repeat aspiration, disseminated intravascular coagulation), late
complications(e.g. pelvic inflammatory diseases, retained products of
conception, continuing pregnancy) and poor reproductive outcomes (e.g.
asherman syndrome, subfertility, ectopic pregnancy, miscarriage, preterm
birth and low birth weight)[3].
It is particularly important to prevent abortions among minors and
adults to the maximum extent possible, which requires extensive
education, improvement of lifestyles and psychological conditions, and a
focus on medical, legal and economic, key direction in health protection
strategy not only of adolescents and the youth, but also of population
as a whole[4]. Thus, reducing unintended pregnancy and abortion is
an urgently need. Consequently, the risk factors for abortion need to be
explored. Bearak J et al. estimated the relationship between income,
region or legal status of abortion and rate of abortion or unintended
pregnancy by a new statistical model[2].
Household income(HI), education attainment(EA), cognition
performance(CP), risky behaviors: smoking behavior(SB), alcohol
consumption(AC), and reproductive traits: age at first sexual
intercourse(AFS), lifetime number of sexual partners(LNSP), age at first
birth(AFB), age at last birth(ALB) may contribute to the occurrence of
unintended pregnancies and may be responsible for forcing women to
choose medical abortion(MA).
Mendelian randomization(MR), using genetic variants as instrumental
variables (IV) from genome-wide association studies(GWAS), provides a
more robust method for assessing a causal effect between a risk factor
and an outcome than does much conventional observational
epidemiology[5]. Furthermore, a two-sample MR design utilizing
existing genetic data or DNA samples from large-scale genetic
association studies increase the feasibility and cost-efficiency of MR
studies[6]. MR studies are less susceptible to confounding factors
and reverse causality based on the principle of genetic variants being
randomly distributed at meiosis and fixed at conception.
Multivariable MR (MVMR) is a recent extension to MR, retaining the
benefits of using genetic instruments for causal inference, such as
avoiding bias due to confounding. This approach can be used to estimate
the effect of multiple exposures on an outcome and/or the genetic
variants associated with multiple, potentially related exposures on a
single outcome[7].
MR studies have been successfully applied to various causal relationship
analyses between individual behaviors, cognition, education, household
income with various diseases[8-11]. Hence, we performed univariate
MR(UVMR) and MVMR to explore the causal associations between income,
education, cognition, risky behaviors, reproductive traits and MA by
using newly published summary genetic association statistics from
large-scale genome-wide association studies.
Materials and methods