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      Proteins as Mediators of the Association Between Diet Quality and Incident Cardiovascular Disease and All‐Cause Mortality: The Framingham Heart Study

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          Abstract

          Background

          Biological mechanisms underlying the association of a healthy diet with chronic diseases remain unclear. Targeted proteomics may facilitate the understanding of mechanisms linking diet to chronic diseases.

          Methods and Results

          We examined 6360 participants (mean age 50 years; 54% women) in the Framingham Heart Study. The associations between diet and 71 cardiovascular disease (CVD)‐related proteins were examined using 3 diet quality scores: the Alternate Healthy Eating Index, the modified Mediterranean‐style Diet Score, and the modified Dietary Approaches to Stop Hypertension diet score. A mediation analysis was conducted to examine which proteins mediated the associations of diet with incident CVD and all‐cause mortality. Thirty of the 71 proteins were associated with at least 1 diet quality score ( P<0.0007) after adjustment for multiple covariates in all study participants and confirmed by an internal validation analysis. Gene ontology analysis identified inflammation‐related pathways such as regulation of cell killing and neuroinflammatory response (Bonferroni corrected P<0.05). During a median follow‐up of 13 years, we documented 512 deaths and 488 incident CVD events. Higher diet quality scores were associated with lower risk of CVD ( P≤0.03) and mortality ( P≤0.004). After adjusting for multiple potential confounders, 4 proteins (B2M [beta‐2‐microglobulin], GDF15 [growth differentiation factor 15], sICAM1 [soluble intercellular adhesion molecule 1], and UCMGP [uncarboxylated matrix Gla‐protein]) mediated the association between at least 1 diet quality score and all‐cause mortality (median proportion of mediation ranged from 8.6% to 25.9%). We also observed that GDF15 mediated the association of the Alternate Healthy Eating Index with CVD (median proportion of mediation: 8.6%).

          Conclusions

          Diet quality is associated with new‐onset CVD and mortality and with circulating CVD‐related proteins. Several proteins appear to mediate the association of diet with these outcomes.

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          Most cited references45

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          How to perform a meta-analysis with R: a practical tutorial

          Meta-analysis is of fundamental importance to obtain an unbiased assessment of the available evidence. In general, the use of meta-analysis has been increasing over the last three decades with mental health as a major research topic. It is then essential to well understand its methodology and interpret its results. In this publication, we describe how to perform a meta-analysis with the freely available statistical software environment R, using a working example taken from the field of mental health. R package meta is used to conduct standard meta-analysis. Sensitivity analyses for missing binary outcome data and potential selection bias are conducted with R package metasens. All essential R commands are provided and clearly described to conduct and report analyses. The working example considers a binary outcome: we show how to conduct a fixed effect and random effects meta-analysis and subgroup analysis, produce a forest and funnel plot and to test and adjust for funnel plot asymmetry. All these steps work similar for other outcome types. R represents a powerful and flexible tool to conduct meta-analyses. This publication gives a brief glimpse into the topic and provides directions to more advanced meta-analysis methods available in R.
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            ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

            Summary: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in. Availability: http://www.ici.upmc.fr/cluego/cluegoDownload.shtml Contact: jerome.galon@crc.jussieu.fr Supplementary information: Supplementary data are available at Bioinformatics online.
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              DNA methylation GrimAge strongly predicts lifespan and healthspan

              It was unknown whether plasma protein levels can be estimated based on DNA methylation (DNAm) levels, and if so, how the resulting surrogates can be consolidated into a powerful predictor of lifespan. We present here, seven DNAm-based estimators of plasma proteins including those of plasminogen activator inhibitor 1 (PAI-1) and growth differentiation factor 15. The resulting predictor of lifespan, DNAm GrimAge (in units of years), is a composite biomarker based on the seven DNAm surrogates and a DNAm-based estimator of smoking pack-years. Adjusting DNAm GrimAge for chronological age generated novel measure of epigenetic age acceleration, AgeAccelGrim. Using large scale validation data from thousands of individuals, we demonstrate that DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death (Cox regression P=2.0E-75), time-to-coronary heart disease (Cox P=6.2E-24), time-to-cancer (P= 1.3E-12), its strong relationship with computed tomography data for fatty liver/excess visceral fat, and age-at-menopause (P=1.6E-12). AgeAccelGrim is strongly associated with a host of age-related conditions including comorbidity count (P=3.45E-17). Similarly, age-adjusted DNAm PAI-1 levels are associated with lifespan (P=5.4E-28), comorbidity count (P= 7.3E-56) and type 2 diabetes (P=2.0E-26). These DNAm-based biomarkers show the expected relationship with lifestyle factors including healthy diet and educational attainment. Overall, these epigenetic biomarkers are expected to find many applications including human anti-aging studies.
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                Author and article information

                Contributors
                jiantao.ma@tufts.edu
                Journal
                J Am Heart Assoc
                J Am Heart Assoc
                10.1002/(ISSN)2047-9980
                JAH3
                ahaoa
                Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
                John Wiley and Sons Inc. (Hoboken )
                2047-9980
                06 September 2021
                21 September 2021
                : 10
                : 18 ( doiID: 10.1002/jah3.v10.18 )
                : e021245
                Affiliations
                [ 1 ] Nutrition Epidemiology and Data Science Friedman School of Nutrition Science and Policy Tufts University Boston MA
                [ 2 ] Health Sciences Sargent College Boston University Boston MA
                [ 3 ] Division of Cardiology Department of Medicine and Cardiovascular Research Center Massachusetts General Hospital Boston MA
                [ 4 ] Population Sciences Branch National Heart, Lung, and Blood Institute NIH Bethesda MD
                [ 5 ] Framingham Heart Study Framingham MA
                [ 6 ] Department of Ophthalmology and Visual Sciences University of Massachusetts Medical School Worcester MA
                Author notes
                [*] [* ] Correspondence to: Jiantao Ma, PhD, Nutrition Epidemiology Data Science, Friedman School of Nutrition Science and Policy, Tufts University, 150 Harrison Ave, Boston, MA 02111. E‐mail jiantao.ma@ 123456tufts.edu

                Author information
                https://orcid.org/0000-0002-2192-729X
                https://orcid.org/0000-0002-7987-4768
                https://orcid.org/0000-0002-2129-5704
                https://orcid.org/0000-0002-3944-7788
                https://orcid.org/0000-0001-5840-9413
                https://orcid.org/0000-0003-1843-8724
                https://orcid.org/0000-0001-7478-7203
                Article
                JAH36695
                10.1161/JAHA.121.021245
                8649513
                34482708
                1355f13d-70da-40ae-9f55-42933081f737
                © 2021 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 10 February 2021
                : 26 July 2021
                Page count
                Figures: 3, Tables: 2, Pages: 13, Words: 18250
                Funding
                Funded by: National Heart, Lung and Blood Institute (NHLBI)’s Framingham Heart Study
                Award ID: N01‐HC‐25195
                Funded by: NHLBI Career Transition Award
                Award ID: 1K22HL135075‐01
                Funded by: NIH , doi 10.13039/100000002;
                Award ID: R01‐HL134893
                Award ID: R01‐HL140224
                Categories
                Original Research
                Original Research
                Epidemiology
                Custom metadata
                2.0
                September 21, 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.9 mode:remove_FC converted:22.11.2021

                Cardiovascular Medicine
                cardiovascular disease,diet quality,mediator,mortality,proteomics,diet and nutrition

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