Evidence map›Paper›PMID 39281736›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Analysis of C-reactive protein omics-measures associates methylation risk score with sleep health and related health outcomes.

Ziqing Wang, Danielle A Wallace, Brian W Spitzer, Tianyi Huang, Kent Taylor, Jerome I Rotter, Stephen S Rich, Peter Y Liu, Martha L Daviglus, Lifang Hou and 8 more

Abstract 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.

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0cells of the map it votes in
0citing papers in PubMed
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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

18 authors.

Ziqing WangCardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Danielle A WallaceCardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Brian W SpitzerCardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Tianyi HuangLaboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Baltimore, MD, USA.
Kent TaylorThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 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, USA.
Stephen S RichCenter for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA.
Peter Y LiuDivision of Genetics, Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA.
Martha L DaviglusDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Lifang HouDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Alberto R RamosDepartment of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA.
Sonya KaurDepartment of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA.
J Peter DurdaDepartment of Pathology and Laboratory Medicine, University of Vermont, Burlington, Vermont, USA.
Hector M GonzálezDepartment of Neurosciences and Shiley-Marcos Alzheimer's Disease Center, University of California, San Diego, La Jolla, CA, USA.
Myriam FornageHuman Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.ORCID 0000-0003-0677-8158
Susan RedlineDepartment of Medicine, Harvard Medical School, Boston, MA, USA.
Carmen R IsasiDepartment of Epidemiology & Population Health, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA.
Tamar SoferCardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.ORCID 0000-0001-8520-8860

Funding

Large Scale Sequencing and Analysis of GenomesU54HG003067 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GABRIEL, STACEY, LANDER, ERIC S · 2004 to 2015
$568.6M
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
Transgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ALAN R. SALTIEL · 2003 to 2026
$40.4M
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
Study of Latinos-Investigation of Neurocognitive Aging-Alzheimer's diseaseR01AG075758 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Charles DeCarli, Hector M Gonzalez · 2022 to 2026
$21.7M
UCLA CLINICAL AND TRANSLATIONAL SCIENCE INSTITUTEUL1RR033176 · NCRR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2011 to 2011
$15.5M
Studies of Rare Genetic Variation in the Isolated Population of SardiniaR01HL117626 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2013 to 2016
$10.5M
Multi-Ethnic Study of Atherosclerosis (MESA) StudyR01HL071205 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI ROTTER, JEROME I · 2003 to 2007
$10.4M
Rare variants and NHLBI traits in deeply phenotyped cohortsR01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2014 to 2016
$8.9M
Study of Latinos Investigation of Neurocognitive Aging 2R56AG048642 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DECARLI, CHARLES, GONZALEZ, HECTOR M · 2020 to 2021
$8.7M
NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001881NCRR NIH HHS UL1 RR033176NHGRI NIH HHS HHSN268201300003CNHGRI NIH HHS U54 HG003067NHLBI NIH HHS HHSN268201300001CNHLBI NIH HHS HHSN268201300003INHLBI NIH HHS HHSN268201300004CNHLBI NIH HHS HHSN268201300005CNHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS HHSN268201500014CNHLBI NIH HHS HHSN268201800001CNHLBI NIH HHS K99 HL166700NHLBI NIH HHS N01 HC065233NHLBI NIH HHS N01 HC065234NHLBI NIH HHS N01 HC065235NHLBI NIH HHS N01 HC065236NHLBI NIH HHS N01 HC065237NHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NHLBI NIH HHS R01 HL071051NHLBI NIH HHS R01 HL071205NHLBI NIH HHS R01 HL071250NHLBI NIH HHS R01 HL071251NHLBI NIH HHS R01 HL071258NHLBI NIH HHS R01 HL071259NHLBI NIH HHS R01 HL117626NHLBI NIH HHS R01 HL120393NHLBI NIH HHS R01 HL161012NHLBI NIH HHS U01 HL120393NIA NIH HHS R01 AG048642NIA NIH HHS R01 AG075758NIA NIH HHS R01 AG080598NIA NIH HHS R56 AG048642NIA NIH HHS RF1 AG061022NIDDK NIH HHS P30 DK063491
6 · The paper itself

Abstract

Introduction: DNA methylation (DNAm) predictors of high sensitivity C-reactive protein (CRP) offer a stable and accurate means of assessing chronic inflammation, bypassing the CRP protein fluctuations secondary to acute illness. Poor sleep health is associated with elevated inflammation (including elevated blood CRP levels) which may explain associations of sleep insufficiency with metabolic, cardiovascular and neurological diseases. Our study aims to characterize the relationships among sleep health phenotypes and CRP markers -blood, genetic, and epigenetic indicators-within the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Methods: In HCHS/SOL, methylation risk scores (MRS)-CRP and polygenetic risk score (PRS)-CRP were constructed separately as weighted sums of methylation beta values or allele counts, respectively, for each individual. Sleep health phenotypes were measured using self-reported questionnaires and objective measurements. Survey-weighted linear regression established the association between the multiple sleep phenotypes (obstructive sleep apnea (OSA), sleep duration, insomnia and excessive sleepiness symptom), cognitive assessments, diabetes and hypertension with CRP markers while adjusting for age, sex, BMI, study center, and the first five principal components of genetic ancestry in HCHS/SOL. Results: We included 2221 HCHS/SOL participants (age range 37-76 yrs, 65.7% female) in the analysis. Both the MRS-CRP (95% confidence interval (CI): 0.32-0.42, p = 3.3 × 10 Conclusions: MRS-CRP is a promising estimate for systemic and chronic inflammation as reflected by circulating CRP levels, which either mediates or serves as a common cause of the association between sleep phenotypes and related comorbidities, especially in the presence of diabetes.

Identifiers

PMID39281736
PMCPMC11398435

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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 Socratic graph.