Evidence map›Paper›PMID 36494812›Full record

ArticleCardiovascular diabetology2022

Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture.

Han Xiao, Yujia Ma, Zechen Zhou, Xiaoyi Li, Kexin Ding, Yiqun Wu, Tao Wu, Dafang Chen

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 10% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

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  6. [Spousal correlations of blood lipid based on a family design].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2025
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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

8 authors at 1 institution in 1 country.

Han XiaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Yujia MaDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Zechen ZhouDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Xiaoyi LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Kexin DingDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Yiqun WuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Tao WuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Dafang ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China. dafangchen@bjmu.edu.cn.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D.

methodA data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets.

resultsWe identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy).

conclusionThe SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Indexed as

Coronary DiseaseDiabetes Mellitus, Type 2Gene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPolymorphism, Single NucleotideCoronary heart diseaseGenetic architectureSNP-set approachType 2 diabetes

Identifiers

PMID36494812
PMCPMC9738029
OpenAlexW4311664748

What OpenQuestion holds

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LicenceCC BY
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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.