Evidence map›Paper›PMID 38933389›Full record

ReviewFundamental research2022

Precision medicine via the integration of phenotype-genotype information in neonatal genome project.

Xinran Dong, Tiantian Xiao, Bin Chen, Yulan Lu, Wenhao Zhou

Abstract readReview
In one paragraph

Review in Fundamental research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

7 citing papers in PubMed.

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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

5 authors.

Xinran DongCenter for Molecular Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China.
Tiantian XiaoDivision of Neonatology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China.
Bin ChenCenter for Molecular Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China.
Yulan LuCenter for Molecular Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China.
Wenhao ZhouCenter for Molecular Medicine, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai 201102, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The explosion of next-generation sequencing (NGS) has enabled the widespread use of genomic data in precision medicine. Currently, several neonatal genome projects have emerged to explore the advantages of NGS to diagnose or screen for rare genetic disorders. These projects have made remarkable achievements, but still the genome data could be further explored with the assistance of phenotype collection. In contrast, longitudinal birth cohorts are great examples to record and apply phenotypic information in clinical studies starting at the neonatal period, especially the trajectory analyses for health development or disease progression. It is obvious that efficient integration of genotype and phenotype benefits not only the clinical management of rare genetic disorders but also the risk assessment of complex diseases. Here, we first summarize the recent neonatal genome projects as well as some longitudinal birth cohorts. Then, we propose two simplified strategies by integrating genotypic and phenotypic information in precision medicine based on current studies. Finally, research collaborations, sociological issues, and future perspectives are discussed. How to maximize neonatal genomic information to benefit the pediatric population remains an area in need of more research and effort.

Indexed as

Genotype and phenotype integrationLongitudinal birth cohortNeonatal genome projectPrecision medicineRare genetic disorders

Identifiers

PMID38933389
PMCPMC11197532

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Registered trials

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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.