Fetal Cells from the maternal circulation for Noninvasive Prenatal Diagnosis Study (FC-NIPD Study), part I

Of every 1000 pregnancies, 20 fetuses are affected by a genetic abnormality.
Around 5% of these chromosomal abnormalities are trisomy 21 or Down syndrome, a
condition for which many countries have screening programs offering testing to
all pregnant women. Many other chromosomal abnormalities occur, of which 20%
involve other aneuploidies, 25% microdeletions or - duplications, and the rest
consists of inherited or de novo Mendelian or single gene disorders.

The gold standard for fetal genetic diagnosis is genetic analysis of
amniocytes, which are fetal cells in the amniotic fluid. To obtain these cells,
amniocentesis is required, an invasive procedure whereby a needle is inserted
through the abdominal wall of the pregnant woman, through the wall of the
uterus and through the fetal membranes. Amniocentesis has inherent risks,
including rupture of the membranes, amniotic fluid loss, infection, fetal
trauma, bleeding, immature or premature delivery and fetal death. These
complications occur in 0.11-1.0% of procedures (Akolekar 2015). Furthermore,
amniocentesis causes pain and discomfort, stress and anxiety for the women, is
expensive and requires specialized skills and expertise of the operator.
Therefore, this procedure is restricted to pregnancies considered to be at high
risk for a fetal genetic disease (ACOG 2012).
Risk assessment is done by routine screening of all pregnant women. This
screening is currently done by taking the woman and her partner*s history,
including age and use of teratogens, and offering a using a non-invasive
prenatal screening test. The best currently available screenng test is called
NIPT, which uses analysis of cell-free fetal DNA (cfDNA) in maternal plasma and
has been increasingly adopted to predict aneuploidy (trisomy 21, 18 and 13)
since 2011. However, NIPT remains only a screening test, it gives a
non-definitive result, with false positives and false negatives, and therefore
needs to be confirmed by an invasive diagnostic test, usually amniocentesis
(Norton 2015, Gil 2015). cfDNA testing can also be false negative, although for
the common trisomies quite rarely (Gil 2015). The standard techniques used in
cfDNA analysis only allow quite reliable prediction for trisomy 21 and 18. For
other aneuploidies (such as sex chromosome abnormalities) and for
subchromosomal abberations, cfDNA is less reliable (Scibetta 2017, Lo 2019).
Latest technological advances, using genomic analysis of cfDNA, appear to
improve accuracy, but a recent Cochrane meta-analysis concluded that cfDNA
testing cannot replace amniocentesis (Badeau 2017). Even if cfDNA analysis
techniques further improve, this test will never achieve the same accuracy as
amniocentesis, since the DNA fragments used in cfDNA testing originate from
placental cells, and not fetal cells (Grati 2014). In addition, multiple
pregnancy (in particular dichorionic) complicates the interpretability of cfDNA
testing, and has failure rates up to 11% (Galeva 2019). In addition, maternal
obesity, an increasing problem in obstetrics in general, is associated with a
lower, and sometimes too low, fetal fraction of the DNA fragments to allow
reliable testing (Rolnik 2018)
A second type of fetal screening is done using ultrasound. Around 18-20 weeks,
and sometimes also already at 11-13 weeks, the fetus is examined for structural
anomalies. When these are found, genetic testing is offered since many of the
structural anomalies are caused by chromosomal aberrations. This genetic
testing is also done using amniocentesis.
The presence of whole fetal cells in maternal blood was first described by
Schmorl in 1893, a pathologist who found trophoblast cells in the lungs of
women who died from preeclampsia (Lapaire 2007). In 1959, Zipursky et al
described the presence of fetal red cells in maternal blood, which formed the
basis of our understanding of Rhesus alloimmunization (Zipursky 1959). Since
the late 1960s, it is known that from early in pregnancy onwards, fetal cells
are present in the blood of the pregnant woman (Beaudet 2016). Several
investigators, mainly around the 1990s, studied the potential to use these
cells for fetal genetic diagnosis, but the attempts never made it into a
clinically useful test (Bianchi 2002). There is however a renewed interest in
the in many ways ideal prenatal diagnostic method using whole fetal cells from
the maternal circulation (Rezaei 2018). Some investigators concentrated on
trying to isolate trophoblast cells from maternal blood or cervical washings
(Breman 2016, Vossaert 2018). However, since these cells are not true fetal
cells, tests using trophoblast may still be less reliable than amniocentesis.
TL Genomics (Tokyo, Japan) developed innovative methods for enrichment and
isolation of fetal nucleated red blood cells from the maternal circulation.
Together with advances in genetic analysis techniques (Wapner 2012, Lord 2019),
this could lead to replacement of cfDNA-based NIPT as well as amniocentesis, to
enable one-step, accurate and safe diagnosis of fetal genetic anomalies.

This first part of the research study aims to evaluate and optimize the Mitsui
Chemicals Inc. fetal cell-based non-invasive prenatal diagnosis test (cbNIPD),
its methodology, internal validation and quality control.

Mitsui Chemicals Inc. developed a blood-cell separator chip technology, which
can sort cells dependent on their size. This chip can isolate nucleated red
blood cells of 11-13 micrometer diameter from maternal blood. In this selected
population of cells from maternal blood, we aim to assess the percentage which
is of fetal origin, and which thus can be used for prenatal diagnosis of fetal
chromosomal abnormalities.

The collection of 20mL blood at one occasion during the pregnancy. We aim to
combine this blooddraw with other standard of care blood draws that take place
during pregnancy.

Risks are limited to the loss of non-identifiable data. These risks are
considered minimal, as data will be entered directly and de-identified into a
protected database (RedCap).