Evidence map›Paper›PMID 38947020›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Sex and aging signatures of proteomics in human cerebrospinal fluid identify distinct clusters linked to neurodegeneration.

Dahun Seo, Cheolmin Matthew Lee, Catherine Apio, Gyujin Heo, Jigyasha Timsina, Pat Kohlfeld, Merce Boada, Adelina Orellana, Maria Victoria Fernandez, Agustin Ruiz and 5 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Dahun Seo
Cheolmin Matthew Lee
Catherine Apio
Gyujin Heo
Jigyasha Timsina
Pat Kohlfeld
Merce Boada
Adelina Orellana
Maria Victoria Fernandez
Agustin Ruiz
John C Morris
Suzanne E Schindler
Taesung Park
Carlos Cruchaga
Yun Ju Sung

Funding

Sex-specific Molecular Profiling to Understand Pathology and Identify Causal Genes and Drug Targets for Alzheimer's DiseaseRF1AG074007 · NIA · WASHINGTON UNIVERSITY · PI SUNG, YUNJU · 2021 to 2021
$2.7M
Sex-specific Molecular Profiling to Understand Pathology and Identify Causal Genes and Drug Targets forAlzheimer's DiseaseR01AG074007 · NIA · WASHINGTON UNIVERSITY · PI YunJu Sung · 2024 to 2026
$2.4M
NIA NIH HHS R01 AG074007NIA NIH HHS RF1 AG074007
6 · The paper itself

Abstract

Sex and age are major risk factors for chronic diseases. Recent studies examining age-related molecular changes in plasma provided insights into age-related disease biology. Cerebrospinal fluid (CSF) proteomics can provide additional insights into brain aging and neurodegeneration. By comprehensively examining 7,006 aptamers targeting 6,139 proteins in CSF obtained from 660 healthy individuals aged from 43 to 91 years old, we subsequently identified significant sex and aging effects on 5,097 aptamers in CSF. Many of these effects on CSF proteins had different magnitude or even opposite direction as those on plasma proteins, indicating distinctive CSF-specific signatures. Network analysis of these CSF proteins revealed not only modules associated with healthy aging but also modules showing sex differences. Through subsequent analyses, several modules were highlighted for their proteins implicated in specific diseases. Module 2 and 6 were enriched for many aging diseases including those in the circulatory systems, immune mechanisms, and neurodegeneration. Together, our findings fill a gap of current aging research and provide mechanistic understanding of proteomic changes in CSF during a healthy lifespan and insights for brain aging and diseases.

Identifiers

PMID38947020
PMCPMC11213043

What OpenQuestion holds

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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.