Evidence map›Paper›PMID 38496585›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Multi-omics Integration Identifies Genes Influencing Traits Associated with Cardiovascular Risks: The Long Life Family Study.

Sandeep Acharya, Shu Liao, Wooseok J Jung, Yu S Kang, Vaha A Moghaddam, Mary Feitosa, Mary Wojczynski, Shiow Lin, Jason A Anema, Karen Schwander and 3 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
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, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Sandeep AcharyaDivision of Computational and Data Sciences, Washington University, St Louis, MO.ORCID 0000-0001-8046-0688
Shu LiaoDepartment of Computer Science and Engineering, Washington University, St Louis, MO.ORCID 0000-0001-7740-8096
Wooseok J JungDepartment of Computer Science and Engineering, Washington University, St Louis, MO.ORCID 0000-0001-8439-2133
Yu S KangDepartment of Computer Science and Engineering, Washington University, St Louis, MO.ORCID 0009-0009-4605-6353
Vaha A MoghaddamDivision of Statistical Genomics, Washington University School of Medicine, St Louis, MO.ORCID 0000-0002-9910-0161
Mary FeitosaDivision of Statistical Genomics, Washington University School of Medicine, St Louis, MO.ORCID 0000-0002-0933-2410
Mary WojczynskiDivision of Statistical Genomics, Washington University School of Medicine, St Louis, MO.
Shiow LinDivision of Statistical Genomics, Washington University School of Medicine, St Louis, MO.
Jason A AnemaDivision of Statistical Genomics, Washington University School of Medicine, St Louis, MO.ORCID 0000-0002-1529-8968
Karen SchwanderDivision of Statistical Genomics, Washington University School of Medicine, St Louis, MO.
Jeff O ConnellDepartment of Medicine, University of Maryland, Baltimore, MD.
Mike ProvinceDivision of Statistical Genomics, Washington University School of Medicine, St Louis, MO.ORCID 0000-0001-6102-774X
Michael R BrentDepartment of Computer Science and Engineering, Washington University, St Louis, MO.ORCID 0000-0002-8689-0299
Washington University in St. Louis · USUniversity of Maryland, Baltimore · US

Funding

The Long Life Family StudyU19AG063893 · NIA · WASHINGTON UNIVERSITY · PI THOMAS T PERLS · 2019 to 2026
$125.4M
FRAMINGHAM HEART STUDY - YEAR 5 EXAM75N92019D00031 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · 2019 to 2024
$29.8M
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NHLBI NIH HHS 75N92019D00031NHLBI NIH HHS HHSN268201500001CNHLBI NIH HHS HHSN268201500001INHLBI NIH HHS N01 HC025195NIA NIH HHS U19 AG063893
6 · The paper itself

Abstract

The Long Life Family Study (LLFS) enrolled 4,953 participants in 539 pedigrees displaying exceptional longevity. To identify genetic mechanisms that affect cardiovascular risks in the LLFS population, we developed a multi-omics integration pipeline and applied it to 11 traits associated with cardiovascular risks. Using our pipeline, we aggregated gene-level statistics from rare-variant analysis, GWAS, and gene expression-trait association by Correlated Meta-Analysis (CMA). Across all traits, CMA identified 64 significant genes after Bonferroni correction (p ≤ 2.8×10

Identifiers

PMID38496585
PMCPMC10942516
OpenAlexW4392467918

What OpenQuestion holds

Textmetadata
LicenceCC BY-ND
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.