Jian Guo

Dr. Jian Guo

orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

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

Representative Publications

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29 September 2009 in Human Molecular Genetics
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Journal Article
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YLYang Li
Yang Li
WWWen-Jing Wang
Wen-Jing Wang
HCHuiqing Cao
Huiqing Cao
JLJiehua Lu
Jiehua Lu
CWChong Wu
Chong Wu
Xiao-Li TianXiao-Li Tian
Xiao-Li Tian
FOXO1A and FOXO3A are two members of the FoxO family. FOXO3A has recently been linked to human longevity in Japanese, German and Italian populations. Here we tested the genetic contribution of FOXO1A and FOXO3A to the longevity phenotype in Han Chinese population. Six tagging SNPs from FOXO1A and FOXO3A were selected and genotyped in 1817 centenarians and younger individuals. Two SNPs of FOXO1A were found to be associated with longevity in women (P = 0.01–0.005), whereas all three SNPs of FOXO3A were associated with longevity in both genders (P = 0.005–0.001). One SNP from FOXO1A was found not to be associated with longevity. In haplotype association tests, the OR (95% CI) for haplotypes TTG and CCG of FOXO1A in association with female longevity were 0.72 (0.58–0.90) and 1.38 (1.08–1.76), P = 0.0033 and 0.0063, respectively. The haplotypes of FOXO3A were associated with longevity in men [GTC: OR (95% CI) = 0.67 (0.51–0.86), P = 0.0014; CGT: OR (95% CI) = 1.48 (1.12–1.94), P = 0.0035] and in women [GTC: OR (95% CI) = 0.75 (0.60–0.94), P = 0.0094; CGT: OR (95% CI) = 1.47 (1.16–1.86), P = 0.0009]. The haplotype association tests were validated by permutation analysis. The association of FOXO1A with female longevity was replicated in 700 centenarians and younger individuals that were sampled geographically different from the original population. Thus, we demonstrate that, unlike FOXO3A, FOXO1A is more closely associated with human female longevity, suggesting that the genetic contribution to longevity trait may be affected by genders.

27 February 2019 in Journal of Clinical Laboratory Analysis
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HZHaoqing Zhang
Haoqing Zhang
CLCaiyun Li
Caiyun Li
JLJianbiao Li
Jianbiao Li
SHShuai Hou
Shuai Hou
DCDanjing Chen
Danjing Chen
DLDongzhu Lei
Dongzhu Lei
Objectives: Thalassemia is a highly prevalent monogenic inherited disease in southern China. It is important to collect epidemiological data comprehensively for proper prevention and treatment.Methods: In this study, blood samples collected from 15 807 residents of Chenzhou were primarily screened by hematological tests. A total of 3973 samples of suspected thalassemia carriers were further characterized by combined next‐generation sequencing (NGS) and Gap‐PCR.Results: In total, 1704 subjects were diagnosed as thalassemia carriers with a total prevalence rate of 10.78%, including 943 α‐thalassemia carriers, 708 β‐thalassemia carriers, and 53 composite α and β‐thalassemia carriers. The prevalence rates of α‐thalassemia, β‐thalassemia, and composite α and β‐thalassemia were 5.97%, 4.48%, and 0.34%, respectively. Meanwhile, we characterized 19 α‐thalassemia variations and 21 β‐thalassemia variations in thalassemia carriers. Approximately 2.88% of thalassemia carriers would be missed by traditional genetic analysis. In addition, four novel thalassemia mutations and one novel abnormal hemoglobin mutation were identified.Conclusions: Our data suggest a high prevalence of thalassemia and a diverse spectrum of thalassemia‐associated variations in Chenzhou. Also, combined NGS and Gap‐PCR is an effective thalassemia screening method. Our findings might be helpful for prevention and treatment of thalassemia in this region.

1 April 2018 in Arteriosclerosis, Thrombosis, and Vascular Biology
Verified
Journal Article
Closed access
YLYang Li
Yang Li
DWDao Wen Wang
Dao Wen Wang
YCYundai Chen
Yundai Chen
CCCan Chen
Can Chen
JGJian Guo
Jian Guo
Xiao-Li TianXiao-Li Tian
Xiao-Li Tian
Objective—: The genetic contribution to coronary artery disease (CAD) remains largely unclear. We combined genetic screening with functional characterizations to identify novel loci and candidate genes for CAD. Approach and Results—: We performed genome-wide screening followed by multicenter validation in 8 cohorts consisting of 21 828 participants of Han ethnicity and identified 3 novel intragenic SNPs (single nucleotide polymorphisms), rs9486729 ( SCML4 [Scm polycomb group protein-like 4]; odds ratio, 1.25; 95% CI, 1.17–1.34; P =3.51×10 −11 ), rs17165136 ( THSD7A [thrombospondin type 1 domain-containing 7A]; odds ratio 1.28; 95% CI, 1.21–1.35; P <1.00×10 −25 ), and rs852787 ( DAB1 [disabled-1]; odds ratio, 1.29; 95% CI, 1.21–1.38; P =2.02×10 −14 ), associated with CAD with genome-wide significance. The risk allele of rs9486729 and protective allele of rs17165136 were associated with the decreased expression of their host genes, SCML4 and THSD7A , respectively, whereas rs852787 did not have transcriptional effects on any gene. Knockdown of SCML4 activated endothelial cells by increasing the expression of IL-6 , E-selectin , and ICAM and weakened their antiapoptotic activity, whereas the knockdown of THSD7A had little effect on these endothelial cell functions but attenuated monocyte adhesion via decreasing the expression of ICAM , L-selectin , and ITGB2 . We further showed that inhibiting the expression of SCML4 exacerbated endothelial dysfunction and vascular remodeling in a rat model with partial carotid ligation. Conclusions—: We identify 3 novel loci associated with CAD and show that 2 genes, SCML4 and THSD7A , make functional contributions to atherosclerosis. How rs852787 and its host gene DAB1 are linked to CAD needs further studies.

19 June 2021 in Brain
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DZDongfang Zou
Dongfang Zou
LWLin Wang
Lin Wang
JLJianxiang Liao
Jianxiang Liao
HXHongdou Xiao
Hongdou Xiao
JDJing Duan
Jing Duan
JGJian Guo
Jian Guo
The aim of this study is to evaluate the diagnostic value of genome sequencing in children with epilepsy, and to provide genome sequencing-based insights into the molecular genetic mechanisms of epilepsy to help establish accurate diagnoses, design appropriate treatments and assist in genetic counselling. We performed genome sequencing on 320 Chinese children with epilepsy, and interpreted single-nucleotide variants and copy number variants of all samples. The complete pedigree and clinical data of the probands were established and followed up. The clinical phenotypes, treatments, prognoses and genotypes of the patients were analysed. Age at seizure onset ranged from 1 day to 17 years, with a median of 4.3 years. Pathogenic/likely pathogenic variants were found in 117 of the 320 children (36.6%), of whom 93 (29.1%) had single-nucleotide variants, 22 (6.9%) had copy number variants and two had both single-nucleotide variants and copy number variants. Single-nucleotide variants were most frequently found in SCN1A (10/95, 10.5%), which is associated with Dravet syndrome, followed by PRRT2 (8/95, 8.4%), which is associated with benign familial infantile epilepsy, and TSC2 (7/95, 7.4%), which is associated with tuberous sclerosis. Among the copy number variants, there were three with a length <25 kilobases. The most common recurrent copy number variants were 17p13.3 deletions (5/24, 20.8%), 16p11.2 deletions (4/24, 16.7%), and 7q11.23 duplications (2/24, 8.3%), which are associated with epilepsy, developmental retardation and congenital abnormalities. Four particular 16p11.2 deletions and two 15q11.2 deletions were considered to be susceptibility factors contributing to neurodevelopmental disorders associated with epilepsy. The diagnostic yield was 75.0% in patients with seizure onset during the first postnatal month, and gradually decreased in patients with seizure onset at a later age. Forty-two patients (13.1%) were found to be specifically treatable for the underlying genetic cause identified by genome sequencing. Three of them received corresponding targeted therapies and demonstrated favourable prognoses. Genome sequencing provides complete genetic diagnosis, thus enabling individualized treatment and genetic counselling for the parents of the patients. Genome sequencing is expected to become the first choice of methods for genetic testing of patients with epilepsy.

13 May 2022 in npj Genomic Medicine
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YYYing Yang
Ying Yang
SZSheng Zhao
Sheng Zhao
GSGuoqiang Sun
Guoqiang Sun
FCFang Chen
Fang Chen
TZTongda Zhang
Tongda Zhang
XCXinlin Chen
Xinlin Chen
Structural anomalies of the central nervous system (CNS) are one of the most common fetal anomalies found during prenatal imaging. However, the genomic architecture of prenatal imaging phenotypes has not yet been systematically studied in a large cohort. Patients diagnosed with fetal CNS anomalies were identified from medical records and images. Fetal samples were subjected to low-pass and deep whole-genome sequencing (WGS) for aneuploid, copy number variation (CNV), single-nucleotide variant (SNV, including insertions/deletions (indels)), and small CNV identification. The clinical significance of variants was interpreted based on a candidate gene list constructed from ultrasound phenotypes. In total, 162 fetuses with 11 common CNS anomalies were enrolled in this study. Primary diagnosis was achieved in 62 cases, with an overall diagnostic rate of 38.3%. Causative variants included 18 aneuploids, 17 CNVs, three small CNVs, and 24 SNVs. Among the 24 SNVs, 15 were novel mutations not reported previously. Furthermore, 29 key genes of diagnostic variants and critical genes of pathogenic CNVs were identified, including five recurrent genes: i.e., TUBA1A, KAT6B, CC2D2A, PDHA1, and NF1. Diagnostic variants were present in 34 (70.8%) out of 48 fetuses with both CNS and non-CNS malformations, and in 28 (24.6%) out of 114 fetuses with CNS anomalies only. Hypoplasia of the cerebellum (including the cerebellar vermis) and holoprosencephaly had the highest primary diagnosis yields (>70%), while only four (11.8%) out of 34 neural tube defects achieved genetic diagnosis. Compared with the control group, rare singleton loss-of-function variants (SLoFVs) were significantly accumulated in the patient cohort.

8 July 2012 in Journal of Molecular Medicine
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WWWen-Jing Wang
Wen-Jing Wang
PHPeili Han
Peili Han
JZJun Zheng
Jun Zheng
FHFang-Yuan Hu
Fang-Yuan Hu
YZYun Zhu
Yun Zhu
Xiao-Li TianXiao-Li Tian
Xiao-Li Tian