The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Noninvasive prenatal diagnosis of fetal chromosomal aneuploidy by massively parallel genomic sequencing of DNA in maternal plasma
Open accessAbstract
Chromosomal aneuploidy is the major reason why couples opt for prenatal diagnosis. Current methods for definitive diagnosis rely on invasive procedures, such as chorionic villus sampling and amniocentesis, and are associated with a risk of fetal miscarriage. Fetal DNA has been found in maternal plasma but exists as a minor fraction among a high background of maternal DNA. Hence, quantitative perturbations caused by an aneuploid chromosome in the fetal genome to the overall representation of sequences from that chromosome in maternal plasma would be small. Even with highly precise single molecule counting methods such as digital PCR, a large number of DNA molecules and hence maternal plasma volume would need to be analyzed to achieve the necessary analytical precision. Here we reasoned that instead of using approaches that target specific gene loci, the use of a locus-independent method would greatly increase the number of target molecules from the aneuploid chromosome that could be analyzed within the same fixed volume of plasma. Hence, we used massively parallel genomic sequencing to quantify maternal plasma DNA sequences for the noninvasive prenatal detection of fetal trisomy 21. Twenty-eight first and second trimester maternal plasma samples were tested. All 14 trisomy 21 fetuses and 14 euploid fetuses were correctly identified. Massively parallel plasma DNA sequencing represents a new approach that is potentially applicable to all pregnancies for the noninvasive prenatal diagnosis of fetal chromosomal aneuploidies.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Direct multiplexed measurement of gene expression with color-coded probe pairs
Geiss, G. K., Bumgarner, R. E., Birditt, B., Dahl, T., Dowidar, N., Dunaway, D. L., Fell, H. P., Ferree, S., George, R. D., Grogan, T., et al. (2008) · Nature Biotechnology · doi:10.1038/nbt1385 · Cited by 2,066
Cited by
Detection and quantification of rare mutations with massively parallel sequencing
Kinde, I., Wu, J., Papadopoulos, N., Kinzler, K. W., & Vogelstein, B. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1105422108 · Cited by 1,144
Counting absolute numbers of molecules using unique molecular identifiers
Kivioja, T., Vähärautio, A., Karlsson, K., Bonke, M., Enge, M., Linnarsson, S., & Taipale, J. (2012) · Nature Methods · doi:10.1038/nmeth.1778 · Cited by 1,010
Palomaki, G. E., Kloza, E. M., Lambert-Messerlian, G. M., Haddow, J. E., Neveux, L. M., Ehrich, M., van den Boom, D., Bombard, A. T., Deciu, C., Grody, W. W., et al. (2011) · Genetics in Medicine · doi:10.1097/gim.0b013e3182368a0e · Cited by 939
Chiu, R. W. K., Akolekar, R., Zheng, Y. W. L., Leung, T. Y., Sun, H., Chan, K. C. A., Lun, F. M. F., Go, A. T. J. I., Lau, E. T., To, W. W. K., et al. (2011) · BMJ · doi:10.1136/bmj.c7401 · Cited by 774
Self-citationHeitzer, E., Ulz, P., Belic, J., Gutschi, S., Quehenberger, F., Fischereder, K., Benezeder, T., Auer, M., Pischler, C., Mannweiler, S., et al. (2013) · Genome Medicine · doi:10.1186/gm434 · Cited by 357
Metadata
- Authors
- Chiu, R. W. K., Chan, K. C. A., Gao, Y., Lau, V. Y. M., Zheng, W., Leung, T. Y., Foo, C. H. F., Xie, B., Tsui, N. B. Y., Lun, F. M. F., Zee, B. C. Y., Lau, T. K., Cantor, C. R., & Lo, Y. M. D.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2008-12-23
- Volume
- 105
- Issue
- 51
- Pages
- 20458-20463
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2156283009
- Cited by
- 942
- References
- 1
- FWCI
- 29.66
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Noninvasive prenatal diagnosis of fetal chromosomal aneuploidy by massively parallel genomic sequencing of DNA in maternal plasma. https://app.cochat.ai/papers/10.1073/pnas.0810641105
- The paper
- Chiu, R. W. K., Chan, K. C. A., Gao, Y., Lau, V. Y. M., Zheng, W., Leung, T. Y., Foo, C. H. F., Xie, B., Tsui, N. B. Y., Lun, F. M. F., Zee, B. C. Y., Lau, T. K., Cantor, C. R., & Lo, Y. M. D. (2008). Noninvasive prenatal diagnosis of fetal chromosomal aneuploidy by massively parallel genomic sequencing of DNA in maternal plasma. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0810641105
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.