Evidence map›Paper›PMID 38884057›Full record

ArticlePhenomics (Cham, Switzerland)2024

Clinical Application of Polygenic Risk Score in IgA Nephropathy.

Linlin Xu, Ting Gan, Pei Chen, Yang Liu, Shu Qu, Sufang Shi, Lijun Liu, Xujie Zhou, Jicheng Lv, Hong Zhang

Abstract read
In one paragraph

Article in Phenomics (Cham, Switzerland), 2024. 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.

  1. Article
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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

10 authors.

Linlin XuRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.ORCID 0009-0004-1434-4944
Ting GanRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.
Pei ChenRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.
Yang LiuRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.
Shu QuRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.
Sufang ShiRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.
Lijun LiuRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.
Xujie ZhouRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.ORCID 0000-0002-7215-707X
Jicheng LvRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.
Hong ZhangRenal Division, Peking University First Hospital, No. 8, Xishiku Street, Xicheng District, Beijing, 100034 People's Republic of China.ORCID 0000-0003-1690-033X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWASs) have identified 30 independent genetic variants associated with IgA nephropathy (IgAN). A genetic risk score (GRS) represents the number of risk alleles carried and thus captures an individual's genetic risk. However, whether and which polygenic risk score crucial for the evaluation of any potential personal or clinical utility on risk and prognosis are still obscure. We constructed different GRS models based on different sets of variants, which were top single nucleotide polymorphisms (SNPs) reported in the previous GWASs. The case-control GRS analysis included 3365 IgAN patients and 8842 healthy individuals. The association between GRS and clinical variability, including age at diagnosis, clinical parameters, Oxford pathology classification, and kidney prognosis was further evaluated in a prospective cohort of 1747 patients. Three GRS models (15 SNPs, 21 SNPs, and 55 SNPs) were constructed after quality control. The patients with the top 20% GRS had 2.42-(15 SNPs, Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-023-00138-6.

Indexed as

GenomicsIgA nephropathyPolygenic scorePrognosisRisk prediction

Identifiers

PMID38884057
PMCPMC11169313

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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.