Evidence map›Paper›PMID 35988936›Full record

ArticleKidney international2022

Kidney disease progression and collider bias in GWAS.

Atlas Khan, Krzysztof Kiryluk

Abstract readComment
PubMed Publisher
In one paragraph

Article in Kidney international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 31% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  2. Article
  3. From Single-Cell Clusters to Causality: ITCH Engagement for CKD Uncovered by Integrative Analysis of MR and MAGMA.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Atlas KhanDivision of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA.
Krzysztof KirylukDivision of Nephrology, Department of Medicine, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA. Electronic address: kk473@columbia.edu.
Columbia University · US

Funding

Predictive utility of polygenic risk scores for chronic kidney disease.K25DK128563 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI KHAN, ATLAS · 2021 to 2025
$846k
NIDDK NIH HHS K25 DK128563
6 · The paper itself

Abstract

New genome-wide meta-analysis for longitudinal kidney function decline identified several genetic loci related to kidney disease progression. The study illustrated the complexity of modeling longitudinal traits in genome-wide association studies and highlighted the issue of a collider bias that can be introduced when a kidney disease progression phenotype is adjusted for baseline kidney function. Herein, we briefly outline the key findings of this study, their limitations, and implications for future studies.

Indexed as

Genome-Wide Association StudyKidney DiseasesDisease ProgressionGenetic LociHumansKidneyMeta-Analysis as TopicPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID35988936
OpenAlexW4292243093

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.