Email Alert | RSS

北京大学学报（医学版） ›› 2021, Vol. 53 ›› Issue (3): 453-459. doi: 10.19723/j.issn.1671-167X.2021.03.003

• 论著 • 上一篇    下一篇

基于国际疾病分类的心血管疾病亚型的基因组学研究

郭子宁,梁志生,周仪,张娜,黄捷Δ()   

  1. 北京大学公共卫生学院全球卫生学系,北京 100191
  • 收稿日期:2021-01-22 出版日期:2021-06-18 发布日期:2021-06-16
  • 通讯作者: 黄捷 E-mail:jiehuang001@pku.edu.cn
  • 基金资助:
    国家重点研发计划项目(2020YFC2002900);中央高校基本科研业务费专项资金(BMU2018YJ009)

Genetic study of cardiovascular disease subtypes defined by International Classification of Diseases

GUO Zi-ning,LIANG Zhi-sheng,ZHOU Yi,ZHANG Na,HUANG JieΔ()   

  1. Department of Global Health, School of Public Health, Peking University 100191, China
  • Received:2021-01-22 Online:2021-06-18 Published:2021-06-16
  • Contact: Jie HUANG E-mail:jiehuang001@pku.edu.cn
  • Supported by:
    National Key Research and Development Program of China(2020YFC2002900);Peking Univerity Research Initiation Fund(BMU2018YJ009)

RICH HTML

 31   

PDF (PC)

192

摘要：

目的: 基于国际疾病分类(International Classification of Diseases,ICD)第10版(ICD-10),通过分子流行病学的方法探索心血管疾病(cardiovascular diseases,CVD)主要亚型分类的分子生物学依据。方法: 研究所采用的表型数据和基因型数据均来源于英国生物样本库(UK Biobank,UKB)。共纳入年龄在40~69岁的380 083个样本,其中对照组是没有任何心血管疾病(不具有以字母I开头的ICD-10代码)的246 437个样本,心血管疾病五大亚型分别为:(1)缺血性心脏病(ischaemic heart diseases,IHD);(2)肺源性心脏病和肺循环疾病(pulmonary heart disease and diseases of pulmonary circulation,PHD);(3)脑血管疾病(cerebrovascular diseases,CRB);(4)动脉、小动脉和毛细血管疾病(diseases of arteries, arterioles and capillaries,AAC);(5)静脉、淋巴管和淋巴结疾病,不可归类在他处者(diseases of veins, lymphatic vessels and lymph nodes, not elsewhere classified,VLL)。本研究首先对五大亚型分别进行全基因组关联分析(genome-wide association study, GWAS);然后,基于GWAS分析结果对五大亚型两两之间进行连锁不平衡回归分析(linkage disequilibrium score regression,LDSC)来计算亚型之间的遗传相关性;最后,对每一对亚型进行孟德尔随机化分析(Mendelian randomizatoin,MR)来评估亚型之间的因果联系。结果: GWAS研究新发现28个显著性基因位点。LDSC分析显示IHD分别和VLL (P=2.52×10-7)、PHD (P=3.77×10-3)、AAC (P=4.90×10-3) 这3个亚型具有显著的遗传相关性。MR分析显示IHD对VLL (P=7.40×10-5) 和AAC (P=1.50×10-3) 这两个疾病的风险增加有正向因果关系,而反向因果皆不成立。结论: 通过分子流行病学的方法,本研究发现基于ICD-10分类的一部分心血管疾病亚型之间存在遗传相关性和因果关联,对新版ICD标准的制定提供依据。

关键词: 国际疾病分类, 心血管疾病亚型, 全基因组关联分析, 基因相关性, 孟德尔随机化

Abstract:

Objective: To study the molecular connection among cardiovascular diseases (CVD) subtypes defined by the International Classification of Diseases (ICD) version 10 (ICD-10). Methods: Both phenotypic data and genotypic data used in this study were obtained from the UK Biobank. A total of 380 083 participants aged between 40 and 69 years were included. Those without any cardiovascular disease (either no ICD-10 code at all or no ICD-10 code containing letter I) were assigned to the control group. The five CVD subtypes were: ischaemic heart diseases (IHD), pulmonary heart disease and diseases of pulmonary circulation (PHD), cerebrovascular diseases (CRB), diseases of arteries, arterioles and capillaries (AAC), diseases of veins, lymphatic vessels and lymph nodes, and diseases not elsewhere classified (VLL). We first performed a genome-wide association study (GWAS) for each of the five subtypes. We summarized novel loci using genome-wide significance threshold P=5×10-8. Next, we used linkage disequilibrium score regression (LDSC) method to assess genetic correlation among the five subtypes. Lastly, we applied mendelian randomization (MR) approach to assess the causal relationship among the subtypes. The particular software that we used was generalised summary-data-based mendelian randomisation (GSMR). Results: Through GWAS, we identified hundreds of genome-wide significant SNPs: 672 for IHD, 241 for PHD, 31 for CRB, 48 for AAC, and 193 for VLL. By comparing with published literature, we found 28 novel loci, for PHD (n=14), CRB (n =7) and AAC (n =7). Eight of these 28 loci were rare, where the lead SNP had minor allele frequency (MAF) less than 1%. LDSC analyses indicated IHD had significant genetic correlation with VLL (P=2.52×10-7), PHD (P=3.77×10-3) and AAC (P=4.90×10-3), respectively. Bidrectional GSMR analyses showed that IHD had a positive causal relationship with VLL (P=7.40×10-5) and AAC (P=1.50×10-3), while reverse causality was not supported. Conclusion: This study adopted an innovative approach to study the molecular connection among CVD subtypes that are defined by ICD. We identified potentially positive genetic correlation and causal effects among some of these subtypes. Research along this line will provide scientific insights and serve as a guidance for future ICD standards.

Key words: International classification of diseases, Cardiovascular diseases, Genome-wide association studies, Genetic correlation, Mendelian randomization

中图分类号: 

  • R54

表1

CVD五大亚型组和对照组的基本特征"

Items IHD PHD CRB AAC VLL Control group
n 13 554 1 631 3 680 2 609 28 220 246 437
Age/years 60.51±6.44 59.07±7.21 59.60±7.21 59.27±7.29 57.07±7.77 55.10±8.01
Male, n(%) 8 800 (64.93) 807 (49.48) 1 987 (53.99) 1 303 (49.94) 11 813 (41.86) 105 177 (42.67)
BMI/(kg/m2) 28.80±4.73 28.79±5.18 27.77±4.68 27.12±4.83 27.58±4.83 26.70±4.41
Height/cm 169.53±9.03 169.74±9.61 168.39±9.23 168.16±8.99 168.53±9.23 168.70±9.19
Current smoker(including ex-smoker), n(%) 7 671
(56.60)		 782
(47.95)		 2 005
(54.48)		 1 678
(64.32)		 13 218
(46.84)		 104 892
(42.56)
Current drinker(including ex-drinker), n(%) 13 021
(96.07)		 1 576
(96.63)*		 3 536
(96.09)		 2 512
(96.28)*		 27 242
(96.53)		 239 343
(97.12)

图1

五大亚型GWAS的曼哈顿图"

表2

与五大CVD亚型相关联的显著性基因位点"

Items Significant SNPs Significant loci Novel loci Rare loci
IHD 672 17 0 0
PHD 241 32 14 5
CRB 31 11 7 2
AAC 48 17 7 1
VLL 193 6 0 0

表3

与五大CVD亚型相关联的新发现基因座"

Disease Chromosome Position Single nucleotide polymorphisms P A1 A2 Minor allele frequency
PHD 4 12883807 rs73215670 1.96×10-10 A G 1.10×10-3
5 118562026 rs184455971 2.58×10-8 A G 1.40×10-3
6 103119329 rs114664439 3.85×10-8 C A <1×10-5
7 38266212 rs138663704 9.90×10-11 A T 2.80×10-3
8 69402863 rs534733210 2.23×10-8 T A 2.10×10-3
8 142854164 rs12545168 2.19×10-8 A T <1×10-5
11 121066124 rs17124940 1.61×10-9 C A 1.00×10-4
11 129600984 rs115956442 3.82×10-9 T G 1.00×10-4
13 25166811 rs142279518 3.59×10-9 T G 2.00×10-4
13 77044683 rs73545476 3.22×10-8 G A 2.00×10-4
14 83677831 rs371991088 3.36×10-8 C G 1.00×10-4
14 96624944 rs566847514 3.59×10-8 T G 1.50×10-3
15 45200618 rs9989321 5.93×10-9 A C 3.00×10-4
15 98637990 rs138967775 7.21×10-9 G A 1.00×10-4
CRB 2 222233437 rs572911615 2.71×10-8 A G 1.90×10-3
8 69390845 rs113300185 7.59×10-9 T A 1.10×10-3
17 72008650 rs73998648 4.73×10-8 G A 1.00×10-4
X 41277264 rs113507059 4.85×10-8 G T 2.00×10-4
X 63179140 X:63179140 2.79×10-8 A C 4.00×10-4
X 66983983 rs5919421 1.48×10-8 A G 4.00×10-4
X 103223335 rs57674601 1.77×10-8 A T 2.00×10-4
AAC 1 245201511 rs649445 6.50×10-10 A G 6.00×10-4
10 98204792 rs558155932 2.50×10-8 G A 2.00×10-4
11 38306906 rs551810096 1.78×10-9 C T 3.00×10-4
14 19431761 rs368924711 9.44×10-9 A G 7.00×10-4
15 54487816 rs140569087 1.46×10-8 C T 4.00×10-4
17 13367363 rs114817801 6.82×10-9 G A 1.00×10-4
20 12020603 rs185329711 1.15×10-8 T C 1.30×10-3

图2

与CRB相关的X染色体区域LocusZoom图"

表4

CVD五个亚型相互之间的基因相关性"

Subtype 1 Subtype 2 Rg SE Z P h2 h2se
IHD VLL 0.30 0.059 5.2 2.52×10-7* 0.02 2.00×10-3
IHD PHD 0.40 0.137 2.9 3.77×10-3* 6.00×10-3 2.00×10-3
IHD AAC 0.74 0.263 2.8 4.90×10-3* 0.03 3.00×10-3
AAC CRB 1.93 1.609 1.2 0.23 1.00×10-3 2.00×10-3
IHD CRB 0.84 0.624 1.4 0.18 0.03 3.00×10-3
CRB PHD 0.47 0.669 0.7 0.49 5.00×10-3 2.00×10-3
AAC VLL 0.34 0.199 1.7 0.09 0.02 2.00×10-3
PHD VLL 0.14 0.120 1.2 0.24 0.02 2.00×10-3
CRB VLL 0.08 0.260 0.3 0.75 0.02 2.00×10-3
AAC PHD 0.00 0.328 0.0 0.99 5.00×10-3 2.00×10-3

表5

五个亚型相互之间的孟德尔随机化因果关系"

Subtype 1 Subtype 2 Beta SE P N Reverse-beta Reverse-SE Reverse-P Reverse-N
IHD VLL 0.10 0.03 7.40×10-5* 28 0.14 0.06 0.01 26
IHD CRB 0.19 0.05 1.80×10-4* 1 0.00 0.04 0.92 20
PHD AAC 0.12 0.04 1.50×10-3* 5 0.22 0.08 0.01 35
IHD AAC 0.18 0.06 1.80×10-3* 4 0.01 0.03 0.65 35
PHD VLL 0.03 0.01 4.10×10-3 5 0.14 0.16 0.39 26
IHD PHD 0.12 0.07 0.08 4 0.02 0.02 0.33 35
PHD CRB 0.05 0.03 0.09 5 0.11 0.11 0.32 20
AAC VLL 0.04 0.02 0.10 5 0.03 0.13 0.81 25
CRB AAC 0.13 0.08 0.14 0 0.04 0.06 0.46 35
CRB VLL 0.02 0.03 0.47 0 0.05 0.10 0.65 26
[1] Nabel EG. Cardiovascular disease[J]. N Engl J Med, 2003,349(1):60-72.
doi: 10.1056/NEJMra035098
[2] Collaborators GBDCOD. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the global burden of disease study 2017[J]. Lancet, 2018,392(10159):1736-1788.
doi: 10.1016/S0140-6736(18)32203-7
[3] Bowry AD, Lewey J, Dugani SB, et al. The burden of cardiovascular disease in low- and middle-income countries: epidemiology and management[J]. Can J Cardiol, 2015,31(9):1151-1159.
doi: 10.1016/j.cjca.2015.06.028
[4] Mccarthy MI, Abecasis GR, Cardon LR, et al. Genome-wide association studies for complex traits: consensus, uncertainty and challenges[J]. Nat Rev Genet, 2008,9(5):356-369.
[5] Aragam KG, Natarajan P. Polygenic scores to assess atheroscle-rotic cardiovascular disease risk: clinical perspectives and basic implications[J]. Circ Res, 2020,126(9):1159-1177.
doi: 10.1161/CIRCRESAHA.120.315928
[6] Hirsch JA, Nicola G, Mcginty G, et al. ICD-10: history and context[J]. Am J Neuroradiol, 2016,37(4):596-599.
doi: 10.3174/ajnr.A4696
[7] Bycroft C, Freeman C, Petkova D, et al. The UK Biobank resource with deep phenotyping and genomic data[J]. Nature, 2018,562(7726):203-209.
doi: 10.1038/s41586-018-0579-z pmid: 30305743
[8] Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses[J]. Am J Hum Genet, 2007,81(3):559-575.
pmid: 17701901
[9] Pruim RJ, Welch RP, Sanna S, et al. LocusZoom: regional visualization of genome-wide association scan results[J]. Bioinformatics, 2010,26(18):2336-2337.
doi: 10.1093/bioinformatics/btq419
[10] Bulik-Sullivan B, Finucane HK, Anttila V, et al. An atlas of genetic correlations across human diseases and traits[J]. Nat Genet, 2015,47(11):1236-1241.
doi: 10.1038/ng.3406
[11] Zhu Z, Zheng Z, Zhang F, et al. Causal associations between risk factors and common diseases inferred from GWAS summary data[J]. Nat Commun, 2018,9(1):224.
doi: 10.1038/s41467-017-02317-2
[12] Perdu B, de Freitas F, Frints SG, et al. Osteopathia striata with cranial sclerosis owing to WTX gene defect[J]. J Bone Miner Res, 2010,25(1):82-90.
doi: 10.1359/jbmr.090707
[13] Sanz-Pamplona R, Lopez-Doriga A, Paré-Brunet L, et al. Exome sequencing reveals AMER1 as a frequently mutated gene in colorectal cancer[J]. Clin Cancer Res, 2015,21(20):4709-4718.
doi: 10.1158/1078-0432.CCR-15-0159 pmid: 26071483
[14] Lloyd-Jones DM, Nam BH, D’agostino S, et al. Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring[J]. JAMA, 2004,291(18):2204-2211.
pmid: 15138242
[1] 袁园，王苹，吴雅慧，叶晓茜，黄尚志，石冰，王科，王竹青，刘冬静，王子凡，. 中国人群细胞黏附相关基因多态性与非综合征型唇腭裂的关联研究[J]. 北京大学学报(医学版), 2016, 48(3): 403-408.
[2] 秦雪英, 田君, 方凯, 李娟, 于文贞, 侯婧, 陈大方, 黎晓新, 胡永华. 高密度脂蛋白胆固醇与年龄相关性黄斑变性关联关系的孟德尔随机化研究[J]. 北京大学学报（医学版）, 2012, 44(3): 407-411.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] 张三. 中文标题测试[J]. 北京大学学报（医学版）, 2010, 42(1): 1 -10 .
[2] 赵磊, 王天龙 . 右心室舒张末期容量监测用于肝移植术中容量管理的临床研究[J]. 北京大学学报（医学版）, 2009, 41(2): 188 -191 .
[3] 万有, , 韩济生, John E. Pintar. 孤啡肽基因敲除小鼠电针镇痛作用增强[J]. 北京大学学报（医学版）, 2009, 41(3): 376 -379 .
[4] 张燕, 韩志慧, 钟延丰, 王盛兰, 李玲玲, 郑丹枫. 骨骼肌活组织检查病理诊断技术的改进及应用[J]. 北京大学学报（医学版）, 2009, 41(4): 459 -462 .
[5] 林红, 王玉凤, 吴野平. 学校生活技能教育对小学三年级学生行为问题影响的对照研究[J]. 北京大学学报（医学版）, 2007, 39(3): 319 -322 .
[6] 丰雷, 程嘉, 王玉凤. 注意缺陷多动障碍儿童的运动协调功能[J]. 北京大学学报（医学版）, 2007, 39(3): 333 -336 .
[7] 李岳玲, 钱秋瑾, 王玉凤. 儿童注意缺陷多动障碍成人期预后及其预测因素[J]. 北京大学学报（医学版）, 2007, 39(3): 337 -340 .
[8] . 书讯[J]. 北京大学学报（医学版）, 2007, 39(3): 225 -328 .
[9] 牟向东, 王广发, 刁小莉, 阙呈立. 肺黏膜相关淋巴组织型边缘区B细胞淋巴瘤一例[J]. 北京大学学报（医学版）, 2007, 39(4): 346 -350 .
[10] 张宏文, 丁洁, 王芳, 杨惠霞. 一例X连锁Alport综合征女性妊娠期随访[J]. 北京大学学报（医学版）, 2007, 39(4): 351 -354 .
ISSN 1671-167X
CN 11-4691/R
主管单位：中华人民共和国教育部
主办单位：北京大学
地址： 北京市海淀区学院路38号 北京大学医学部 《北京大学学报（医学版）》
邮编：100191
电话：010-82801551
Email： xbbjb2@bjmu.edu.cn

《北京大学学报（医学版）》
微信公众号
版权所有 © 2018 《北京大学学报（医学版）》编辑部