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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (8): 98-106    DOI: 10.11925/infotech.2096-3467.2018.0142
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Finding Association Between Diseases and Genes from Literature Abstracts
Mu Dongmei(), Jin Shan, Ju Yuanhong
School of Public Health, Jilin University, Changchun 130021, China
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Abstract  

[Objective] This study tries to find association between genes and diseases from literature abstracts, aiming to provide evidence for the prevention and treatment of diseases. [Methods] First, we established the entity extraction rules with the help of recognition techniques based on thesaurus. Then, we proposed a model to discover the association between disease and gene entities. Finally, we validated the new model with abstracts of diabete nephropathy studies. [Results] A total of 656 diabetic nephropathy associated genes were obtained, which included high frequency, mid frequency and low frequency genes. [Limitations] More research is needed to explore other diabete complications with the proposed model. [Conclusions] (I)The high frequency associated genes of disease are possibly the theoretical foundations of current research. (II)Intermediate frequency associated genes are the focus of current research. (III) Low frequency associated genes could become new fields for knowledge discovery.
Key words： Entity Recognition      Information Extraction      Cluster Analysis      Genes Association Relationship     
Received: 02 February 2018      Published: 08 September 2018
ZTFLH:  G350  
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Dongmei Mu
Shan Jin
Yuanhong Ju

Cite this article:

Mu Dongmei,Jin Shan,Ju Yuanhong. Finding Association Between Diseases and Genes from Literature Abstracts. Data Analysis and Knowledge Discovery, 2018, 2(8): 98-106.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0142     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I8/98

序号 ID 基因符号 频次
1 618 APOL1 26
2 12679 VDR 19
3 333 AGT 18
4 1662 CD34 17
5 11850 TLR4 15
6 634 AQP2 14
7 2500 CTGF 14
8 6769 SMAD3 14
9 14929 SIRT1 12
10 613 APOE 11
PMID 涉及内容
27054572 非裔人群中APOL1肾风险变异与终末期肾脏病密切相关
26776194 终末期肾病的非裔美国人的基因变异与邻近的APOL1
强连锁不平衡密切相关
26668025 APOL1的风险等位基因与HIV阳性黑人的肾病和局灶性节段性肾小球硬化症关联
26343748 非裔美国人APOL1肾病危险变异体呈常染色体隐性遗传模式
26215860 APOL1的遗传变异引起慢性终末期肾脏疾病的风险
26180129 APOL1基因变异与黑人肾脏疾病相关
26150607 APOL1变异与黑人肾脏表型相关
26112018 非裔人群中APOL1变异与慢性肾脏疾病关联
25573908 APOL1变异引起肾脏疾病的风险
25549121 非裔美国人群中APOL1与慢性肾病和终末期肾脏疾病的发病率增加相关
基因名称 PMID 涉及内容
TLR4 26568190 TLR4可诱导多种炎性细胞因子的生产, 因此认为TLR4有益于治疗糖尿病肾病。
TLR4 26497229 发现维生素D3在糖尿病肾病尿毒症的炎症免疫反应与TLR4相关。
TLR4 26398934 发现TLR4的内源性配体和核因子-kb启动子活性在糖尿病小鼠肾脏中明显升高。
SMAD3 26449625 发现尿SMAD3与肾小球滤过率双相变化显著相关, 可作为一种新型的标志物筛查2型糖尿病患者的肾病。
SMAD3 26052839 发现灭活TGF-β/SMAD3的通路引起细胞外基质蛋白降低, 进而抑制糖尿病肾病。
SMAD3 26041445 发现高血糖增加SMAD3磷酸化, 进而导致肾功能衰竭。
SIRT1 27470548 发现SIRT1/p53轴在高血糖条件下可诱导肾近曲小管上皮细胞凋亡。
SIRT1 26588494 综述了SIRT1在糖尿病肾病中的作用机制。
SIRT1 25386563 SIRT1可抑制肾细胞, 它的激活可能成为糖尿病肾病的新的治疗靶点。
基因名称 PMID 涉及内容
ABCA1 26379423 胆固醇紊乱可致糖尿病肾病, 实验发现花青素加强ABCA1表达和胆固醇流出。
ABCA1 25181357 发现ABCA1表达降低可能促进胆固醇的积累, 可能促进糖尿病肾病的发展。
RhoA 25641678 发现PTEN引起RhoA活化失衡, 引起足细胞损伤, 进而可促进糖尿病肾病的发展。
RhoA 24925721 SMPDL3b的表达增加RhoA的活性, 使足细胞更易发生凋亡, 促进糖尿病肾病的发展。
CCR2 27926736 CCR2及其配体与糖尿病肾病相关。
CCR2 26268910 实验数据表明CCR2在2型糖尿病肾病患者治疗中具有肾脏保护作用。
CYP11B2 27009287 研究表明CYP11B2基因多态性可能有助于糖尿病肾病的发展, 尤其是在亚洲人群中。
CYP11B2 25957425 发现CYP11B2基因多态性可能对糖尿病患者的慢性肾病发展产生影响。
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