Evidence map›Paper›PMID 30940890›Full record

ArticleScientific reports2019

Mendelian Randomization Analysis Support Causal Associations of HbA1c with Circulating Triglyceride, Total and Low-density Lipoprotein Cholesterol in a Chinese Population.

Xu Jia, Yanan Hou, Min Xu, Zhiyun Zhao, Liping Xuan, Tiange Wang, Mian Li, Yu Xu, Jieli Lu, Yufang Bi and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.5field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

12 authors at 1 institution in 2 countries.

Xu JiaState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Yanan HouState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.ORCID http://orcid.org/0000-0003-3930-8718
Min XuState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Zhiyun ZhaoState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Liping XuanState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Tiange WangState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Mian LiState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Yu XuState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Jieli LuState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Yufang BiState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Weiqing WangState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.
Yuhong ChenState Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China. chenyh70@126.com.
Shanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous observational studies supported a positive association of glycated hemoglobin A1c (HbA1c) level with serum triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). However, the causal relationship between HbA1c and either one of them was unclear in the East Asians. We performed a Mendelian Randomization (MR) analysis in a community-based study sample in Shanghai, China (n = 11,935). To clarify the cause-and-effect relationships of HbA1c with the four interested lipids, an Expanded HbA1c genetic risk score (GRS) with 17 HbA1c-related common variants and a Conservative score by excluding 11 variants were built and adopted as the Instrumental Variables (IVs), respectively. The Expanded HbA1c-GRS was associated with 0.19 unit increment in log-TG (P = 0.009), 0.42 mmol/L TC (P = 0.01), and 0.33 mmol/L LDL-C (P = 0.01); while the Conservative HbA1c-GRS was associated with 0.22 unit in log-TG (P = 0.03), 0.60 mmol/L TC (P = 0.01), and 0.51 mmol/L LDL-C (P = 0.007). No causal relationship was detected for HDL-C. Sensitivity analysis supported the above findings. In conclusions, MR analysis supports a causal role of increased HbA1c level in increment of circulating TG, TC, and LDL-C in a Chinese population.

Indexed as

AgedChinaCholesterol, LDLFemaleGenetic VariationGlycated HemoglobinHumansLongitudinal StudiesMaleMendelian Randomization AnalysisMiddle AgedTriglyceridesCholesterol, LDLGlycated HemoglobinTriglycerides

Identifiers

PMID30940890
PMCPMC6445078
OpenAlexW2933294739

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.