Evidence map›Paper›PMID 34136649›Full record

ReviewWellcome open research2020

Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light?

Yan V Sun, Chang Liu, Lisa Staimez, Mohammed K Ali, Howard Chang, Dimple Kondal, Shivani Patel, Dean Jones, Viswanathan Mohan, Nikhil Tandon and 4 more

Open access · goldAbstract readReview
In one paragraph

Review in Wellcome open research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 20% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Illuminating diabetesWorld journal of diabetes · 2025
    Review
  3. Review
  4. Article
  5. Article
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

14 authors at 5 institutions in 2 countries.

Yan V SunDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.ORCID https://orcid.org/0000-0002-2838-1824
Chang LiuDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.ORCID https://orcid.org/0000-0002-8918-7224
Lisa StaimezHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.
Mohammed K AliHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.ORCID https://orcid.org/0000-0001-7266-2503
Howard ChangDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.
Dimple KondalPublic Health Foundation of India, New Delhi, India.
Shivani PatelHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.
Dean JonesDivision of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, School of Medicine, Emory University, Atlanta, GA, 30322, USA.
Viswanathan MohanMadras Diabetes Research Foundation, Chennai, India.ORCID https://orcid.org/0000-0001-5038-6210
Nikhil TandonAll India Institute of Medical Sciences, New Delhi, India.
Dorairaj PrabhakaranPublic Health Foundation of India, New Delhi, India.
Arshed A QuyyumiDepartment of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA, 30322, USA.
K M Venkat NarayanHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.
Anurag AgrawalInstitute of Genomics and Integrative Biology, Council of Scientific and Industrial Research, New Delhi, India.ORCID https://orcid.org/0000-0002-0340-5252
Emory University · USPublic Health Foundation of India · INAll India Institute of Medical Sciences · INInstitute of Genomics and Integrative Biology · INMadras Diabetes Research Foundation · IN

Funding

Implementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE)UL1TR002378 · NCATS · EMORY UNIVERSITY · PI Andres J Garcia, Elizabeth O. Ofili · 2017 to 2026
$92.1M
Institutional Career Development CoreKL2TR002381 · NCATS · EMORY UNIVERSITY · PI HENRY M BLUMBERG, Anandi Nayan Sheth · 2017 to 2026
$14.1M
NCATS NIH HHS KL2 TR002381NCATS NIH HHS UL1 TR002378
6 · The paper itself

Abstract

Cardiovascular disease (CVD) is the leading cause of mortality in South Asia, with rapidly increasing prevalence of hypertension, type 2 diabetes (T2DM) and hyperlipidemia over the last two decades. Atherosclerotic CVD (ASCVD) affects South Asians earlier in life and at lower body weights, which is not fully explained by differential burden of conventional risk factors. Heart failure (HF) is a complex clinical syndrome of heterogeneous structural phenotypes including two major clinical subtypes, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF). The prevalence of HF in South Asians is also rising with other metabolic diseases, and HFpEF develops at younger age and leaner body mass index in South Asians than in Whites. Recent genome-wide association studies, epigenome-wide association studies and metabolomic studies of ASCVD and HF have identified genes, metabolites and pathways associated with CVD traits. However, these findings were mostly driven by samples of European ancestry, which may not accurately represent the CVD risk at the molecular level, and the unique risk profile of CVD in South Asians. Such bias, while formulating hypothesis-driven research studies, risks missing important causal or predictive factors unique to South Asians. Importantly, a longitudinal design of multi-omic markers can capture the life-course risk and natural history related to CVD, and partially disentangle putative causal relationship between risk factors, multi-omic markers and subclinical and clinical ASCVD and HF. In conclusion, combining high-resolution untargeted metabolomics with epigenomics of rigorous, longitudinal design will provide comprehensive unbiased molecular characterization of subclinical and clinical CVD among South Asians. A thorough understanding of CVD-associated metabolomic profiles, together with advances in epigenomics and genomics, will lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health.

Indexed as

atherosclerosisdiabetesheart failureHFpEFHFrEFmulti-omicsSouth Asianssubclinical CVD

Identifiers

PMID34136649
PMCPMC8176264
OpenAlexW3096711277

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.