Evidence map›Paper›PMID 39850426›Full record

ArticleHeliyon2025

Analysis of fetal fraction in non-invasive prenatal testing with low-depth whole genome sequencing.

Xiaolei Xie, Weiguo Yin, Fuguang Li, Suxia Xuan, Yu Ouyang

Abstract read
In one paragraph

Article in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

  1. Article
  2. Article
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

5 authors.

Xiaolei XieMolecular Diagnosis Center, Affiliated Qingyuan Hospital, Guangzhou Medical University (Qingyuan People's Hospital), 511518, Qingyuan, China.
Weiguo YinMolecular Diagnosis Center, Affiliated Qingyuan Hospital, Guangzhou Medical University (Qingyuan People's Hospital), 511518, Qingyuan, China.
Fuguang LiMolecular Diagnosis Center, Affiliated Qingyuan Hospital, Guangzhou Medical University (Qingyuan People's Hospital), 511518, Qingyuan, China.
Suxia XuanMolecular Diagnosis Center, Affiliated Qingyuan Hospital, Guangzhou Medical University (Qingyuan People's Hospital), 511518, Qingyuan, China.
Yu OuyangMolecular Diagnosis Center, Affiliated Qingyuan Hospital, Guangzhou Medical University (Qingyuan People's Hospital), 511518, Qingyuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The fetal fraction (FF) is a critical factor influencing the performance of non-invasive prenatal testing (NIPT). Different NIPT methods and sequencing depths can lead to distinct minimum FF thresholds for Trisomy 21 (T21). This study aims to analyze the minimum FF thresholds for detecting T21 in PCR-free NIPT using a low-depth whole genome sequencing method. Methods: A total of 71 non-pregnant women and 4827 pregnant women were enrolled for a study investigating the impact of FF on NIPT testing. Results: The results showed a weak negative correlation between cfDNA levels and age in non-pregnant women. There was no statistically significant difference in the ratio of chromosome 13, 18, and 21 between pregnant and non-pregnant women. The minimum FF required for 100 % detection of trisomy 21 was determined to be 5 % in PCR-free NIPT using a low-depth whole genome sequencing method. Analysis of a large sample revealed that 4.43 % of pregnant women exhibited FF below 5 %, with those having lower FF showing significantly higher maternal weight compared to those near the median. Furthermore, FF demonstrated a significant negative correlation with the weight of pregnant women; specifically, an FF of 5 % at 12-19 weeks corresponded to a weight of 96 kg, while at 20-22 weeks it corresponded to a weight of 93 kg. Conclusions: These results suggest that the FF below 5 %, or pregnant women weighing over 93 kg, should be given more attention in clinical genetic counseling.

Indexed as

Cell-free DNAFetal fractionMaternal weightNIPTTrisomy 21

Identifiers

PMID39850426
PMCPMC11755048

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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.