Prediction of Blastulation

Prediction of Blastulation –
Does it have any clinical
relevance in IVF?
COGI Nov 2014
Simon Fishel
CEO CARE Fertility Group.
Fecundity
Macklon, et al H.R.U.(2002).
Evers, Lancet (2002).
French, et al F.S. (2010).
Gardner, et al H. R. (2000).
Arthur Durston - Fecundity
Human fecundity rates are relatively low, largely due to pre- and
post-implantation embryo loss.
In vitro, 50–70% of IVF embryos fail to reach the blastocyst
stage or implant.
How much do we know?
Dobson, et al. H.M.G.(2004),;Braude, et al Nature (1988).
Memili, et al Zygote (2000); Beaujean, et al B.R. (2004).
Fulka,et al Repdn.(2004); Duranthon et al Repdn (2008).
Vanneste, E. et al. Nat. Med. (2009)
Dobson, et al. H.M.G.(2004)
Wang, et al. Dev. Cell (2004).
Zeng & Schultz Dev. Biol.(2005).
Unique events to other species
gene-expression and epigenetic patterns
protracted period of transcriptional silence through the first 3
days
Degradation of a subset of oocyte-specific mat RNAs during
transition from zygote to embryo
High incidence of aneuploidy
Fertilization is complex
•
•
•
•
Ca channels are determinative
Cytoplasmic flows are determinative
First cleavage division determines blastocyst axis
Cell lineage fate could be determined by the first
division
Zernicka-Goetz, et al Development (2002).
Zernicka-Goetz, et al Curr. Opin. Genet. Dev. (2006)
Plusa, B. et al. Nature 434, 391–395 (2005).
Christian Patrino - Befruchtung
Cumulus cell gene expression
Compensatory approaches – cumulative preg rates
Fertility Associates…
Compensatory approaches – cumulative preg rates
Fertility Associates…
Or/(and) - - Transfer of multiple embryos to compensate
Expression of concern
“Current morphological and growth criteria that are
commonly used to assess embryo viability on day 3 in
assisted reproduction clinics may both underestimate and
overestimate embryo potential, with well-documented
consequences, such as multiple births, the need for fetal
reduction and miscarriage”
Racowsky, C. High rates of embryonic loss, yet high incidence of
multiple births in human ART: Is this paradoxical? Theriogenology
(2002).
The (long) search for alternatives
Given the incidence of aneuploidy the
cumulative approach risks
Delaying outcome
Miscarriage
Time to Pregnancy
↑↑ Cost
SET – but the most viable
From cumulus to egg to embryo
Classical embryology parameters
Morphology, growth curves, ‘Z’ scores, etc
Chromosomes
‘Omics’
Time-lapse and blastocyst prediction models
Predicating the blastocyst prediction model
Embryonic Genome Activation (EGA) is a
defining moment after D3
Many factors may contribute to abnormal
development before EGA
inherited genetic mutations,
aneuploidy,
environmental insult to germ cells,
events during fertilization and
sperm-related factors
Predicting blastocyst formation at day 2 could
↑pregnancy rates & ↓ risk of multiple
gestations.
Cytokinetic and mitotic parameters in the first
two cleavage divisions may become a clinical
application
Schatten, & Sun, Semin.
Cell Dev Biol(2010).
Ostermeier, Nature (2004)
Hammoud, et al. Nature
(2009)
Imaging patterns and gene expression – Wong et al 2010
To assess whether imaging parameters that
predict success or failure of development are
associated with transcriptional patterns
Analysed the expression of nine putative
cytokinesis-related genes in both normal and
arrested embryos
Wong et al (2010)
Aberrant cytokinesis seen in the time-lapse image data correlated
strongly with reduced expression of key cytokinesis genes.
Wong et al 2010
Conclusions from Wong et al (2010)
“results support the conclusion that some aspects of embryo
fate, especially success or failure to reach the blastocyst stage,
are determined very early in development and likely inherited
from the oocyte”
Proposed model human embryo development and
algorithm for blastocyst prediction - Wong et al 2010
Cytokinesis & chromosome anomalies – Chavez (2012)
chromosomally normal embryos display strict and tightly
clustered cell cycle parameters
chromosomally abnormal embryos exhibit more diverse
parameters that may or may not overlap those of euploid
embryos
4-cell stage of development assessed using
dynamic assessment of cell cycle parameters and
fragmentation analysis and
blastomere asymmetry
Conclude:- the time-lapse assay “Assists in
differentiation between the type of error (meiotic versus mitotic),
chromosomal duplications (trisomies) and
deletions(monosomies) and
provides a reliable readout of the degree of mitotic mosaicism (high
versus low) in human embryos”
The presence and affect of ‘micronuclei’
mitotic intermediates that are comprised of chromatin masses surrounded by
nuclear envelope, which then fuse to form a single nucleus
Chavez et al (2010) studied if the appearance of embryonic micronuclei had
any effects on developmental potential
Chavez et al 2012
Cultured an additional set of human embryos from the zygote to
approximately the four-cell stage and monitored embryonic
development by time-lapse imaging.
The cell cycle parameter values were determined for each
embryo
Embryos were then immunostained for LAMIN-B1
Blinded results were then scored for normal and abnormal
parameter timing.
In the ‘normal parameters’ group LAMIN-B1 expression was
confined to the primary nucleus of each blastomere
Multiple LAMIN-B1-encapsulated micronuclei were detected in
one or more embryonic blastomeres of all embryos with
abnormal parameter timing
Micronuclei anomalies detected by cytokinetic
algorithms - Chavez et al (2012)
Abnormal
Normal
Has the predictive model delivered?
Kirkegaard et al (2014)
Limitations of the time-lapse prediction to
blastocyst model
Evaluation of the time-lapse parameters
3 countries, 7 clinics
1519 transferred embryos with known outcome
for implantation from cycles
Kirkegaard et al (2014) - ‘KID’ embryos only
Using Conaghan et al. (2013) blastocyst prediction model:
Implantation data for embryos categorized as usable or non-usable
according to the test model.
implanted not implanted IPR (%)
usable
131
445
22.7
nonusable
134
809
14.2
entire cohort
265
1254
17.4
Usable: t3 – t2 = 9.33–11.45 h and t4 – t3 = 0–1.73 h.
Unusable: t3 – t2 - outside 9.33–11.45 h and t4 – t3 outside 0–1.73 h.
Kirkegaard et al (2014)
The model was found to predict a high chance of
usable blastocyst formation (defined as a
blastocyst suitable for either transfer or freezing)
The relative difference in implantation rate
between the entire cohort and the embryos
categorized as usable by the test model was
30.0%. The odds ratio for implantation between
usable and non-usable was 1.60.
The sensitivity was 0.50 and the specificity was 0.65
BUT - 50.6% of the embryos that resulted in
pregnancy were categorized as non-usable
Predictive Value
kirkegaard et al (2014)
0.57 – ROC curve
relying on such a model would bring a substantial
risk of deeming many viable embryos non-usable
Time-Lapse to predict blastulation - ?
A high percentage of blastocysts never
make a baby
A significant percentage of blastocysts
result in miscarriage
Some blastocysts make unhealthy babies
therefore:
embryos resulting in a healthy live birth
would constitute a subgroup of embryos
that develop into blastocysts
Time-Lapse to predict blastulation - ?
A case(s) in point..
Of the 9, 7
predicted to be
a blastocyst.
They were.
But…
All 7 were
chromosomally
abnormal!
In conclusion
Predicting blastulation is possible
but….
Any predictive model must:
Add value to predicting live birth
outcome
Minimise the rejection of viable
embryos
Prediction of Blastulation –
Does it have any clinical relevance in IVF?
It has not been proven
Potentially more harm
Robust culture to take embryos to blastocyst seemingly more
reliable
Prediction at the blastocyst stage – using PGS/Time-Lapse still
under validation so…………
How can predicting to reach blastocyst stage be more helpful?
Thank you for listening