Evidence map›Paper›PMID 35737188›Full record

ArticleGeroScience2023

The association between aging-related monocyte transcriptional networks and comorbidity burden: the Multi-Ethnic Study of Atherosclerosis (MESA).

Jingzhong Ding, Kurt Lohman, Anthony Molina, Osvaldo Delbono, Alain Bertoni, Steven Shea, Wendy Post, Xiuqing Guo, R Graham Barr, Ani W Manichaikul and 5 more

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in GeroScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
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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

15 authors at 9 institutions in 1 country.

Jingzhong DingDepartment of Internal Medicine, Wake Forest School of Medicine, Medical Center Blvd., Winston-Salem, NC, 27157, USA. jding@wakehealth.edu.
Kurt LohmanDepartment of Medicine, Duke University School of Medicine, Durham, NC, 27701, USA.
Anthony MolinaDepartment of Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, 92093, USA.
Osvaldo DelbonoDepartment of Internal Medicine, Wake Forest School of Medicine, Medical Center Blvd., Winston-Salem, NC, 27157, USA.
Alain BertoniDepartment of Epidemiology & Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA.
Steven SheaDepartments of Medicine and Epidemiology, Columbia University, New York, NY, 10032, USA.
Wendy PostDepartments of Pathology and Cardiology, Johns Hopkins University, Baltimore, MD, 21205, USA.
Xiuqing GuoThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
R Graham BarrDepartment of Medicine, Columbia University, New York, NY, 10032, USA.
Ani W ManichaikulCenter for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908, USA.
James S PankowDivision of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, 55454, USA.
Jerome I RotterThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.
Ina HoescheleBiocomplexity Institute, Virginia Tech, Blacksburg, VA, 24061, USA.
Stephen B KritchevskyDepartment of Internal Medicine, Wake Forest School of Medicine, Medical Center Blvd., Winston-Salem, NC, 27157, USA.
Yongmei LiuDepartment of Medicine, Duke University School of Medicine, Durham, NC, 27701, USA.
Wake Forest University · USColumbia University · USDuke University · USHarbor–UCLA Medical Center · USJohns Hopkins University · USUniversity of California, San Diego · USUniversity of Minnesota · USUniversity of Virginia · USVirginia Tech · US

Funding

UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
SUBCLINICAL CARDIOVASCULAR DISEASE COORDINATING CENTERN01HC95159 · NHLBI · UNIVERSITY OF WASHINGTON · PI KRONMAL, RICHARD A · 2007 to 2014
$19.6M
Task Area A Core Study Operations.Task Area A shall encompass annual follow-up of cohort members, clinical endpoints ascertainment, study coordination activities, maintenance of the database and biosp75N92020D00001 · NHLBI · UNIVERSITY OF WASHINGTON · PI MCCLELLAND, ROBYN LEAGH · 2020 to 2025
$17.2M
CHARGE Consortium: Omics Discovery for CVD and Aging PhenotypesR01HL105756 · NHLBI · UNIVERSITY OF WASHINGTON · PI Bruce M Psaty, NICHOLAS L SMITH · 2011 to 2026
$9.5M
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC95160 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WATSON, KAROL · 2007 to 2015
$7.7M
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY-FIELD CENTERN01HC95164 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI LIU, KIANG · 2007 to 2015
$7.0M
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC95161 · NHLBI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI SHEA, STEVEN · 2007 to 2014
$6.4M
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC95165 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI BURKE, GREGORY L · 2007 to 2014
$6.3M
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY--FIELD CENTERN01HC95163 · NHLBI · UNIVERSITY OF MINNESOTA · PI FOLSOM, AARON R · 2007 to 2014
$6.1M
NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001881NHLBI NIH HHS 75N92020D00001NHLBI NIH HHS 75N92020D00002NHLBI NIH HHS 75N92020D00003NHLBI NIH HHS 75N92020D00004NHLBI NIH HHS 75N92020D00005NHLBI NIH HHS 75N92020D00006NHLBI NIH HHS 75N92020D00007NHLBI NIH HHS HHSN268201500003INHLBI NIH HHS N01HC95159NHLBI NIH HHS N01HC95160NHLBI NIH HHS N01HC95161NHLBI NIH HHS N01HC95162NHLBI NIH HHS N01HC95163NHLBI NIH HHS N01HC95164NHLBI NIH HHS N01HC95165NHLBI NIH HHS N01HC95166NHLBI NIH HHS N01HC95167NHLBI NIH HHS N01HC95168NHLBI NIH HHS N01HC95169NHLBI NIH HHS R01 HL101250NHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01 HL119962NHLBI NIH HHS R01 HL135009NIA NIH HHS R01 AG054523NIA NIH HHS RF1 AG054474NIA NIH HHS U01 AG060897NIDDK NIH HHS R01 DK101921
6 · The paper itself

Abstract

Translating our knowledge of the biological aging from animal models to humans may give rise to novel approaches of targeting multiple aging-related diseases simultaneously and increasing health span. Here, for the first time, we use transcriptomic signatures of monocytes to identify biological aging pathways underlying multiple aging-related diseases in humans. The ordinal logistic regression was used to cross-sectionally investigate transcriptomics of the comorbidity index in 1264 community-based Multi-Ethnic Study of Atherosclerosis (MESA) adults, 47% Caucasian, 32% Hispanic, 21% African American, and 51% female, aged 55-94 years. The comorbidity index was defined as the number of prevalent aging-related diseases including cardiovascular disease, type-2 diabetes, hypertension, cancer, dementia, chronic kidney disease, chronic obstructive pulmonary disease, and hip fracture. We identified 708 gene transcripts associated with the comorbidity index (FDR < 0.05) after adjusting for age, sex, ethnicity, and study site. In a weighted gene co-expression network analysis, as postulated, aging-related declines in apoptosis/autophagy (OR = 1.21 per SD increment, p = 0.0006) and ribosome/mitochondrion (OR = 0.90 per SD increment, p = 0.05) were positively associated with the comorbidity index. After adjusting for multiple comparisons, we identified 10 comorbidity-associated modules (FDR < 0.05), including the module of apoptosis/autophagy. There were three inter-correlated modules of these 10 involved in the complement subcomponent C1q, Fc gamma receptor I, and Fc gamma receptor III of the immune system, respectively. Aging-related upregulation of these three modules was positively associated with the comorbidity index. The odds of comorbidity increased with more of these modules acting together in a dose-response fashion. In conclusion, transcriptomic analysis of human immune cells may identify biomarker panels indicative of comprehensive biological mechanisms, especially immune signaling pathways, contributing to health aging.

Indexed as

AtherosclerosisMonocytesAgingComorbidityFemaleGene Regulatory NetworksHumansMaleReceptors, IgGReceptors, IgGAgingComorbidityMonocyteTranscriptomic

Identifiers

PMID35737188
PMCPMC9886705
OpenAlexW4283391599

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.