Evidence map›Paper›PMID 34772814›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Haplotype-aware inference of human chromosome abnormalities.

Daniel Ariad, Stephanie M Yan, Andrea R Victor, Frank L Barnes, Christo G Zouves, Manuel Viotti, Rajiv C McCoy

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
9.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 33 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Daniel AriadDepartment of Biology, Johns Hopkins University, Baltimore, MD 21218; daniel@ariad.org rajiv.mccoy@jhu.edu.ORCID 0000-0002-7427-6435
Stephanie M YanDepartment of Biology, Johns Hopkins University, Baltimore, MD 21218.ORCID 0000-0002-6880-465X
Andrea R VictorZouves Fertility Center, Foster City, CA 94131.
Frank L BarnesZouves Fertility Center, Foster City, CA 94131.ORCID 0000-0002-2645-9261
Christo G ZouvesZouves Fertility Center, Foster City, CA 94131.
Manuel ViottiZouves Foundation for Reproductive Medicine, Foster City, CA 94131.ORCID 0000-0003-1844-2571
Rajiv C McCoyDepartment of Biology, Johns Hopkins University, Baltimore, MD 21218; daniel@ariad.org rajiv.mccoy@jhu.edu.ORCID 0000-0003-0615-146X
Johns Hopkins University · USFoundation for Reproductive Medicine · US

Funding

Function and fitness consequences of human genetic variationR35GM133747 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Rajiv Champion McCoy · 2019 to 2026
$3.3M
NIGMS NIH HHS R35 GM133747
6 · The paper itself

Abstract

Extra or missing chromosomes-a phenomenon termed aneuploidy-frequently arise during human meiosis and embryonic mitosis and are the leading cause of pregnancy loss, including in the context of in vitro fertilization (IVF). While meiotic aneuploidies affect all cells and are deleterious, mitotic errors generate mosaicism, which may be compatible with healthy live birth. Large-scale abnormalities such as triploidy and haploidy also contribute to adverse pregnancy outcomes, but remain hidden from standard sequencing-based approaches to preimplantation genetic testing for aneuploidy (PGT-A). The ability to reliably distinguish meiotic and mitotic aneuploidies, as well as abnormalities in genome-wide ploidy, may thus prove valuable for enhancing IVF outcomes. Here, we describe a statistical method for distinguishing these forms of aneuploidy based on analysis of low-coverage whole-genome sequencing data, which is the current standard in the field. Our approach overcomes the sparse nature of the data by leveraging allele frequencies and linkage disequilibrium (LD) measured in a population reference panel. The method, which we term LD-informed PGT-A (LD-PGTA), retains high accuracy down to coverage as low as 0.05 × and at higher coverage can also distinguish between meiosis I and meiosis II errors based on signatures spanning the centromeres. LD-PGTA provides fundamental insight into the origins of human chromosome abnormalities, as well as a practical tool with the potential to improve genetic testing during IVF.

Indexed as

Abortion, SpontaneousAneuploidyBlastocystChromosome AberrationsChromosomes, HumanFemaleFertilization in VitroGenetic TestingHaplotypesHumansLive BirthMeiosisMosaicismPregnancyPreimplantation Diagnosishaploidyin vitro fertilizationmosaicismtriploidytrisomy

Identifiers

PMID34772814
PMCPMC8609623
OpenAlexW3214072301

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.