Yanqiao Lu

Dr. Yanqiao Lu

Shanghai Jiaotong University School of medicine, Shanghai, China
orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 October 2023 in Biomedicines
Verified
Journal Article
Open access
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YLYanqiao Lu
Yanqiao Lu
HHHuanhuan Huo
Huanhuan Huo
FLFeng Liang
Feng Liang
JXJieyuan Xue
Jieyuan Xue
LFLiang Fang
Liang Fang
Ben HeBen He
Ben He
Acute myocardial infarction (AMI) is one of the leading causes of cardiovascular death worldwide. AMI with cardiomyopathy is accompanied by a poor long-term prognosis. However, limited studies have focused on the mechanism of cardiomyopathy associated with AMI. Pericytes are important to the microvascular function in the heart, yet little attention has been paid to their function in myocardial infarction until now. In this study, we integrated single-cell data from individuals with cardiomyopathy and myocardial infarction (MI) GWAS data to reveal the potential function of pericytes in cardiomyopathy-associated MI. We found that pericytes were concentrated in the left atrium and left ventricle tissues. DLC1/GUCY1A2/EGFLAM were the top three uniquely expressed genes in pericytes (p < 0.05). The marker genes of pericytes were enriched in renin secretion, vascular smooth muscle contraction, gap junction, purine metabolism, and diabetic cardiomyopathy pathways (p < 0.05). Among these pathways, the renin secretion and purine metabolism pathways were also found in the process of MI. In cardiomyopathy patients, the biosynthesis of collagen, modulating enzymes, and collagen formation were uniquely negatively regulated in pericytes compared to other cell types (p < 0.05). COL4A2/COL4A1/SMAD3 were the hub genes in pericyte function involved in cardiomyopathy and AMI. In conclusion, this study provides new evidence about the importance of pericytes in the pathogenesis of cardiomyopathy-associated MI. DLC1/GUCY1A2/EGFLAM were highly expressed in pericytes. The hub genes COL4A2/COL4A1/SMAD3 may be potential research targets for cardiomyopathy-associated MI.

24 June 2025 in Biomedicines
Verified
Journal Article
Open access
PDF file
YLYanqiao Lu
Yanqiao Lu
YSYujun Sun
Yujun Sun
YMYutong Miao
Yutong Miao
ZLZhitong Liu
Zhitong Liu
LSLan Shen
Lan Shen
BHBen He
Ben He
Background: Low-density lipoprotein cholesterol (LDL-C) is considered an important risk factor for acute coronary syndrome (ACS). Recent studies have revealed high mortality in ACS patients with low LDL-C levels. However, the association between spontaneously very low LDL-C levels and the prognosis in ACS remains unknown. Methods: A total of 1882 consecutive statin-null ACS patients were analyzed and categorized into four groups according to their on-admission LDL-C level: very low <70 mg/dL, low 70–99 mg/dL, high 100–129 mg/dL, and very high ≥130 mg/dL. In-hospital mortality and 3-year mortality were assessed. Among them, 1009 patients were further grouped according to the hs-CRP value (<2 mg/L and ≥2 mg/L). Results: Over one-third of the patients had an initially lower LDL-C concentration. Higher in-hospital mortality (9.7%, 4.5%, 2.7%, and 3.5%, p = 0.001), long-term mortality (20.8%, 13.1%, 8.0%, and 7.8%, p < 0.001), and lower survival rate (KM: HR = 3.15, 95% CI 1.40–7.12, p < 0.001; Cox: HR = 2.09, 95% CI 1.30 to 3.36) were observed in the very low LDL-C group compared with other groups. Patients in the low LDL-C high CRP subgroup had the worst prognosis compared with other subgroups (in-hospital: 7.7%, 1.2%, 0.5%, and 4.3%, p = 0.031; long-term: 15.5%, 1.2%, 2.6%, and 9.4%, p = 0.018). Lower LDL-C levels were accompanied by higher CRP levels (p = 0.003). The CRP–LDL-C ratio had good predictive ability on short-term and long-term outcomes (AUC: 0.630 and 0.738). Conclusions: Spontaneously very low LDL-C level was independently associated with poor long-term survival in patients with ACS. Lower LDL-C level was related to higher CRP level, while the CRP–LDL-C ratio may be a potential risk prediction factor.