Association between interleukin-1B-511C/T gene polymorphism and coronary atherosclerotic heart disease: a meta-analysis

doi:10.3969/j.issn.1674-8115.2022.02.010

Abstract

Abstract: Objective

·To evaluate the association between interleukin-1B (IL-1B)-511C/T gene polymorphism and the risk of coronary atherosclerotic heart disease (CHD).

Methods

·Published case-control studies on IL-1B-511C/T gene polymorphism and CHD in PubMed, Web of Science, Scopus and Embase databases were retrieved from the establishment of each database to June 2021. Two researchers independently conducted literature screening and data extraction. The extracted data included the name of the first author, the year of publication, the race of the research objects, matching factors, the source of the control group, genotyping method, sample size, genotype frequency, allele frequency, and whether to meet Hardy-Weinberg equilibrium. Meta-analysis was performed by using Stata 16.0 software.

Results

·A total of 9 literatures were included, including 2 190 patients with CHD and 2 385 controls. Meta-analysis showed that there was no significant correlation between IL-1B -511C/T gene polymorphism and the risk of CHD (T vs C: OR =1.21, 95% CI 0.91?1.61; TT+CT vs CC: OR=1.24, 95% CI 0.88?1.75; CC+CT vs TT: OR=1.28, 95% CI 0.86?1.90). Subgroup analysis showed that compared with individuals with C allele and CC genotype in the Chinese population, the individuals with T allele and TT+CT genotype had a 85% and 116% increased risk of CHD, respectively (T vs C: OR=1.85, 95% CI 1.02?3.36; TT+CT vs CC: OR=2.16, 95% CI 1.10?4.24). In hospital-based case-control studies, compared with individuals with CC+CT genotype, the individuals with TT genotype had a 59% increased risk of CHD (OR=1.59, 95% CI 1.03?2.47).

Conclusion

·There is no significant association between IL-1B-511C/T gene polymorphism and the risk of CHD. In the Chinese population, individuals with T allele and TT+TC genotype have a higher risk of CHD.

Key words: interleukin-1, gene polymorphism, -511C/T, coronary atherosclerotic heart disease (CHD), meta-analysis

CLC Number:

R541.4

Yingchao TAN, Junyue YANG, Lina WANG. Association between interleukin-1B-511C/T gene polymorphism and coronary atherosclerotic heart disease: a meta-analysis[J]. JOURNAL OF SHANGHAI JIAOTONG UNIVERSITY (MEDICAL SCIENCE), 2022, 42(2): 197-204.

Figures/Tables 7

TrendMD

References 29

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Study included	Year	Area	Race	Source of control group	Genotype method	Matching（Y/N）	HWE（Y/N）	NOS score
LICASTRO， et al^［17］	2004	Italy	Caucasian	PB	PCR-RFLP	Y	Y	≥7
IACOVIELLO， et al^［18］	2005	Italy	Caucasian	PB	Not PCR-RFLP	Y	Y	≥7
ZEE， et al^［19］	2008	US	Caucasian	PB	Not PCR-RFLP	Y	Y	≥7
RIOS， et al^［15］	2010	Brazil	Caucasian	HB	PCR-RFLP	N	Y	≥7
COKER， et al^［20］	2011	Turkish	Caucasian	HB	PCR-RFLP	N	Y	≥7
REN， et al^［21］	2015	China	Chinese	HB	Not PCR-RFLP	N	Y	≥7
TABREZ， et al^［13］	2017	Saudi	Caucasian	HB	PCR-RFLP	N	Y	<7
CHEN， et al^［22］	2018	China	Chinese	HB	Not PCR-RFLP	N	N	≥7
MA， et al^［23］	2020	China	Chinese	HB	PCR-RFLP	Y	Y	≥7

Study included	Year	Area	Race	Source of control group	Genotype method	Matching（Y/N）	HWE（Y/N）	NOS score
LICASTRO， et al^［17］	2004	Italy	Caucasian	PB	PCR-RFLP	Y	Y	≥7
IACOVIELLO， et al^［18］	2005	Italy	Caucasian	PB	Not PCR-RFLP	Y	Y	≥7
ZEE， et al^［19］	2008	US	Caucasian	PB	Not PCR-RFLP	Y	Y	≥7
RIOS， et al^［15］	2010	Brazil	Caucasian	HB	PCR-RFLP	N	Y	≥7
COKER， et al^［20］	2011	Turkish	Caucasian	HB	PCR-RFLP	N	Y	≥7
REN， et al^［21］	2015	China	Chinese	HB	Not PCR-RFLP	N	Y	≥7
TABREZ， et al^［13］	2017	Saudi	Caucasian	HB	PCR-RFLP	N	Y	<7
CHEN， et al^［22］	2018	China	Chinese	HB	Not PCR-RFLP	N	N	≥7
MA， et al^［23］	2020	China	Chinese	HB	PCR-RFLP	Y	Y	≥7

Study included	Sample size/n		Genotype and allele frequency in case group/n					Genotype and allele frequency in control group/n
Study included	Case group	Control group	CC	CT	TT	C	T	CC	CT	TT	C	T
LICASTRO， et al^［17］	139	122	65	60	14	190	88	46	65	11	157	87
IACOVIELLO， et al^［18］	406	419	195	180	31	570	242	174	187	58	535	303
ZEE， et al^［19］	340	341	148	153	39	449	231	164	137	40	465	217
RIOS， et al^［15］	276	138	80	130	66	290	262	47	69	22	163	113
COKER， et al^［20］	167	235	59	72	36	190	144	77	113	45	267	203
REN， et al^［21］	325	342	95	152	78	342	308	114	155	73	383	301
TABREZ， et al^［13］	152	75	58	63	31	179	125	27	33	15	87	63
CHEN， et al^［22］	251	200	134	80	37	348	154	143	37	20	323	77
MA， et al^［23］	134	513	35	65	34	135	133	298	179	36	775	251

Study included	Sample size/n		Genotype and allele frequency in case group/n					Genotype and allele frequency in control group/n
Study included	Case group	Control group	CC	CT	TT	C	T	CC	CT	TT	C	T
LICASTRO， et al^［17］	139	122	65	60	14	190	88	46	65	11	157	87
IACOVIELLO， et al^［18］	406	419	195	180	31	570	242	174	187	58	535	303
ZEE， et al^［19］	340	341	148	153	39	449	231	164	137	40	465	217
RIOS， et al^［15］	276	138	80	130	66	290	262	47	69	22	163	113
COKER， et al^［20］	167	235	59	72	36	190	144	77	113	45	267	203
REN， et al^［21］	325	342	95	152	78	342	308	114	155	73	383	301
TABREZ， et al^［13］	152	75	58	63	31	179	125	27	33	15	87	63
CHEN， et al^［22］	251	200	134	80	37	348	154	143	37	20	323	77
MA， et al^［23］	134	513	35	65	34	135	133	298	179	36	775	251

Subgroup	Genetic model	Number of study	OR （95% CI）	I² value	P_Hvalue
Race
Chinese	T vs C	3	1.85 （1.02-3.36）	93.3%	0.000
	TT+CT vs CC	3	2.16 （1.10-4.24）	89.4%	0.000
	CC+CT vs TT	3	1.99 （0.87-4.58）	88.9%	0.000
Caucasian	T vs C	6	0.97 （0.82-1.16）	57.6%	0.038
	TT+CT vs CC	6	0.94 （0.80-1.09）	37.2%	0.158
	CC+CT vs TT	6	1.00 （0.70-1.42）	57.8%	0.037
Source of control
PB	T vs C	3	0.89 （0.68-1.15）	67.8%	0.045
	TT+CT vs CC	3	0.88 （0.63-1.24）	66.2%	0.052
	CC+CT vs TT	3	0.78 （0.48-1.29）	57.7%	0.094
HB	T vs C	6	1.42 （1.00-2.03）	89.0%	0.000
	TT+CT vs CC	6	1.50 （0.96-2.34）	85.5%	0.000
	CC+CT vs TT	6	1.59 （1.03-2.47）	76.9%	0.000
Genotype method
PCR-RFLP	T vs C	5	1.27 （0.78-2.06）	91.4%	0.000
	TT+CT vs CC	5	1.24 （0.66-2.33）	89.2%	0.000
	CC+CT vs TT	5	1.63 （0.91-2.90）	79.0%	0.000
Not PCR-RFLP	T vs C	4	1.14 （0.82-1.58）	87.4%	0.000
	TT+CT vs CC	4	1.23 （0.82-1.84）	83.9%	0.000
	CC+CT vs TT	4	0.97 （0.62-1.49）	72.3%	0.000
Matching （Y/N）
Y	T vs C	4	1.20 （0.66-2.21）	95.5%	0.000
	TT+CT vs CC	4	1.25 （0.63-2.50）	93.3%	0.000
	CC+CT vs TT	4	1.26 （0.47-3.36）	92.4%	0.000
N	T vs C	5	1.22 （0.99-1.51）	62.8%	0.030
	TT+CT vs CC	5	1.24 （0.91-1.71）	65.0%	0.022
	CC+CT vs TT	5	1.28 （1.03-1.59）	0	0.707
NOS score
≥7	T vs C	8	1.24 （0.91-1.69）	90.9%	0.000
	TT+CT vs CC	8	1.28 （0.89-1.86）	87.5%	0.000
	CC+CT vs TT	8	1.31 （0.85-2.02）	83.0%	0.000
<7	T vs C	1	0.96 （0.65-1.43）	‒	‒
	TT+CT vs CC	1	0.91 （0.51-1.62）	‒	‒
	CC+CT vs TT	1	1.02 （0.51-2.04）	‒	‒
HWE （Y/N）
Y	T vs C	8	1.15 （0.85-1.55）	89.8%	0.000
	TT+CT vs CC	8	1.16 （0.81-1.64）	85.1%	0.000
	CC+CT vs TT	8	1.25 （0.80-1.93）	82.8%	0.000
N	T vs C	1	1.86 （1.36-2.54）	‒	‒
	TT+CT vs CC	1	2.19 （1.48-3.25）	‒	‒
	CC+CT vs TT	1	1.56 （0.87-2.78）	‒	‒