Genomics for human health

Prenatal analysis (qChip Pre®)

"The analysis with aCGH microarrays, combined with the conventional karyotype represents, nowadays, the most comprehensive available prenatal genetic analysis, allowing to inspect the fetal genome with high accuracy and a relatively short time"

qChip Pre®

After the experience accumulated over years of research and service, following the analysis of thousands of prenatal samples using different microarray platforms, we can offer an excellent prenatal analysis, using a own innovative and widely tested microarray design (qChip PRE®).

The design of the qChip PRE® interrogates the presence of submicroscopic copy number alterations known to have effects on fetal development (leading to intellectual disability and / or congenital malformations in the baby).

This design is suitable for

  • Detecting copy number alterations visible in the cytogenetic karyotype, as well as submicroscopic ones.
  • Identifying and characterizing small supernumerary marker chromosomes (sSMCs) containing euchromatin (Tsuchiya 2008 Mol Cytog; EJMG Sheth 2011).

For what cases is it indicated?

Each case grants an individualized analysis, but the published literature has demonstrated its clinical utility and an increase in the detection rate of clinically relevant genetic alterations when compared to other standard techniques, so it might be indicated in cases of:

  • Familial history of chromosomal abnormalities
  • Gestation with elevated risk values after biochemical screening  (triple screening)
  • Pregnancy with congenital anomalies detected by ultrasound
  • Gestation with abnormal karyotype requiring deeper molecular characterization
  • Maternal Anxiety
  • ... any indication that requires a study of the fetal karyotype.

Technical Information

  • Targeted microarray, with approximately 60.000 oligonucleotide probes
  • Interrogates 150+ known genetic syndromes (see list of diseases detected in the right menu)
  • High coverage of clinically relevant regions (1 probe/10Kb on average).
  • Low coverage in the rest of the genome (backbone) to minimize the identification of variants of uncertain significance (VOUS), while maintaining the potential to identify large copy number alterations outside the disease hotspots.