Non-invasive fetal genotyping by droplet digital PCR to identify maternally-inherited monogenic diabetes variants
dc.contributor.author | Caswell, R | |
dc.contributor.author | Snowsill, T | |
dc.contributor.author | Houghton, J | |
dc.contributor.author | Chakera, A | |
dc.contributor.author | Shepherd, M | |
dc.contributor.author | Laver, T | |
dc.contributor.author | Knight, BA | |
dc.contributor.author | Hattersley, AT | |
dc.contributor.author | Ellard, S | |
dc.date.accessioned | 2020-06-01T10:56:48Z | |
dc.date.issued | 2020-06-12 | |
dc.description.abstract | Background. Babies of women with heterozygous pathogenic glucokinase (GCK) variants causing mild fasting hyperglycemia are at risk of macrosomia if they do not inherit the variant. Conversely, babies who inherit a pathogenic hepatocyte nuclear factor 4α (HNF4A) diabetes variant are at increased risk of high birth weight. Non30 invasive fetal genotyping for maternal pathogenic variants would inform pregnancy management. Methods. Droplet digital PCR was used to quantify reference and variant alleles in cell-free DNA extracted from blood from 38 pregnant women heterozygous for a GCK or HNF4A variant, and to determine fetal fraction by measurement of informative maternal and paternal variants. Droplet numbers positive for the reference/alternate allele together with the fetal fraction were used in a Bayesian analysis to derive a probability for the fetal genotype. The babies’ genotypes were ascertained postnatally by Sanger sequencing. Results. Droplet digital PCR assays for GCK or HNF4A variants were validated for testing in all 38 pregnancies. Fetal fraction of 2% was demonstrated in at least one cell-free DNA sample from 33 pregnancies. A threshold of ≥0.95 for calling homozygous reference genotypes and ≤0.05 for heterozygous fetal genotypes allowed correct genotype calls for all 33 pregnancies with no false positive results. In 30/33 pregnancies a result was obtained from a single blood sample. Conclusions. This assay can used to identify pregnancies at risk of macrosomia due to maternal monogenic diabetes variants. | en_GB |
dc.description.sponsorship | University of Exeter | en_GB |
dc.description.sponsorship | Royal Devon and Exeter NHS Foundation Trust | en_GB |
dc.description.sponsorship | NIHR | en_GB |
dc.identifier.citation | Published online 12 June 2020 | en_GB |
dc.identifier.doi | 10.1093/clinchem/hvaa104 | |
dc.identifier.grantnumber | NIHR4-SNMRL058 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/121235 | |
dc.language.iso | en | en_GB |
dc.publisher | American Association for Clinical Chemistry | en_GB |
dc.rights | © American Association for Clinical Chemistry 2020. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. | |
dc.subject | monogenic diabetes | en_GB |
dc.subject | non-invasive prenatal diagnosis | en_GB |
dc.subject | droplet digital PCR | en_GB |
dc.subject | Bayesian analysis | en_GB |
dc.title | Non-invasive fetal genotyping by droplet digital PCR to identify maternally-inherited monogenic diabetes variants | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-06-01T10:56:48Z | |
dc.identifier.issn | 0009-9147 | |
dc.description | This is the final version. Available on open access from the American Association for Clinical Chemistry via the DOI in this record | en_GB |
dc.identifier.journal | Clinical Chemistry | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2020-04-09 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2020-04-09 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-06-01T09:18:21Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-06-15T14:17:55Z | |
refterms.panel | A | en_GB |
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This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.