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What is PGT-A?

Course / What is PGT-A?

The Basics of PGT-A

Objective: To ground participants in the genetic and clinical concepts underlying PGT-A, and to understand the rationale for its use.

Content / Key Points:

  • Terminology and evolution: PGS → PGT-A (why the change)

  • Chromosomal abnormalities (aneuploidy, trisomy, monosomy, structural abnormalities)

  • Sources of embryonic aneuploidy (meiotic nondisjunction, mitotic errors, mosaicism)

  • Prevalence of chromosomal errors by maternal age and by embryo stage

  • Impact of aneuploidy on implantation, miscarriage, and live birth rates

  • Statistical basis: what proportion of embryos typically are euploid vs aneuploid in various age cohorts

  • Role of PGT-A as a selection tool (not a guarantee)

Learning Deliverables:

  • Chart: frequency of euploid embryos by maternal age

  • Illustration: origin of nondisjunction in meiosis I / II

  • Short quiz: define mosaicism, segmental aneuploidy

Avoiding Transfer of Abnormal Embryos

Objective: To explore how PGT-A helps reduce the risk of transferring chromosomally abnormal embryos, and to examine limitations and risk mitigation.

Content / Key Points:

  • Concept: reducing risk, not eliminating it

  • False positives / false negatives: sampling bias, mosaicism, dropout

  • Maternal contamination or DNA contamination risks

  • Embryo mosaicism: detection thresholds, classification, and clinical decision frameworks

  • Segmental aneuploidies and partial chromosomal errors

  • Embryos with “low-level mosaicism” — when to consider transfer

  • Best practices to prevent misdiagnosis: lab controls, validation, parallel assays

  • Role of replication / validation testing in ambiguous cases

  • How to counsel clinicians about residual risk despite “euploid” calls

Learning Deliverables:

  • Case examples: mosaic embryo reports and transfer decision

  • Flowchart: decision tree for borderline / mosaic results

  • Quiz: list three sources of false positives

Predictive Power of Euploid Embryos

Objective: To assess how well being labeled “euploid” predicts embryo viability, implantation, and healthy live birth.

Content / Key Points:

  • Definition of “euploid” in the PGT context

  • Metrics: implantation rate, ongoing pregnancy rate, live birth rate among euploid embryos

  • Comparative outcomes: euploid vs untested embryos, stratified by age

  • Limits to predictive power: non-genetic causes of implantation failure (endometrium, uterine anatomy, immunologic factors)

  • Mosaicism beyond biopsy: undetected mosaic changes deeper in embryo

  • Embryo competence beyond chromosomal architecture (mitochondrial health, epigenetics, metabolism)

  • Statistical caveats: cohort effect, selection bias, lab effect

  • Clinical interpretation: success probabilities vs certainty

Learning Deliverables:

  • Table: published implantation / live birth rates from euploid embryos

  • Example scenario: patient with multiple euploid embryos — how to counsel expectations

  • Quiz: what non-chromosomal factors may lead a euploid embryo to fail to implant?

What the PGT-A Process Entails

Objective: To outline, in step-wise detail, the workflow, technical methods, and logistical considerations of PGT-A in an IVF / surrogacy program.

Content / Key Points:

  • Integration of PGT-A into the IVF / surrogacy timeline

    1. Ovarian stimulation & retrieval

    2. Fertilization / embryo culture

    3. Embryo development to blastocyst stage

    4. Biopsy (trophectoderm) at Day 5/6

    5. Sample preparation, labeling, and shipping

    6. Genetic laboratory analysis (e.g. NGS, array CGH, SNP arrays)

    7. Report generation & interpretation

    8. Embryo vitrification / cryopreservation

    9. Transfer planning in subsequent cycle

  • Biopsy technical details: number of cells, technique (laser, mechanical), timing

  • Sample quality control: amplification, DNA quality, dropout, mosaic cell detection

  • Genetic assay options:
     • Array comparative genomic hybridization (aCGH)
     • Single-nucleotide polymorphism (SNP) arrays
     • Next-generation sequencing (NGS) / low-pass whole genome sequencing
     • qPCR / targeted methods

  • Turnaround times, cost drivers, lab accreditation / QC standards

  • Logistical challenges in surrogacy contexts: transporting biopsied samples, cross-lab compatibility, chain of custody

  • Workflow optimizations, backup plans for assay failure, retesting policies

Learning Deliverables:

  • Workflow diagram: PGT-A process from retrieval to transfer

  • Comparison table: advantages / disadvantages of different assay platforms

  • Case exercise: troubleshooting failed amplification in a sample

  • Quiz: name key QC steps in sample processing

Pro Tips

Objective: To offer expert-level tips, caveats, and strategic considerations to optimize use of PGT-A in real-world practice (especially in surrogacy / donor cycles).

Content / Pro Tips:

  • Always validate your lab’s assay sensitivity, specificity, and mosaic detection thresholds

  • Work with genetic lab partners that have strong QA/QC and accreditation

  • Use internal controls and replicate runs for ambiguous calls

  • Maintain clean chain-of-custody protocols especially in cross-country surrogacy transfers

  • When embryo numbers are low, weigh the added cost vs benefit of testing

  • Be cautious in interpreting mosaic calls — low-level mosaic embryos may still lead to healthy live birth

  • Use ranking algorithms (e.g. “top euploid first”) rather than binary discard-only approaches

  • For donor egg or donor embryo cycles, PGT-A adds less relative value if donor is young

  • Stay updated with non-invasive PGT developments (e.g. spent embryo media cell-free DNA)

  • Maintain close liaison between embryology, genetics, clinical, and surrogacy coordination teams

  • Document data within your program (outcomes vs PGT classification) to refine thresholds over time

  • In counseling, always present residual risks and uncertainties even with “euploid” embryos

  • Monitor literature for new definitions, reporting standards, and mosaic classification consensus