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Journal of Peking University (Health Sciences) ›› 2024, Vol. 56 ›› Issue (3): 375-383. doi: 10.19723/j.issn.1671-167X.2024.03.001

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A ssociations of short-term ambient particulate matter exposure and MTNR1B gene with triglyceride-glucose index: A family-based study

Huangda GUO1,Hexiang PENG1,Siyue WANG1,Tianjiao HOU1,Yixin LI1,Hanyu ZHANG1,Mengying WANG2,3,Yiqun WU1,3,Xueying QIN1,3,Xun TANG1,3,Jing LI1,3,Dafang CHEN1,3,Yonghua HU1,3,Tao WU1,3,*()   

  1. 1. Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
    2. Department of Nutrition and Food Hygiene, Peking University School of Public Health, Beijing, 100191, China
    3. Key Laboratory of Epidemiology of Major Diseases(Peking University), Ministry of Education, Beijing 100191, China
  • Received:2024-02-17 Online:2024-06-18 Published:2024-06-12
  • Contact: Tao WU E-mail:twu@bjmu.edu.cn
  • Supported by:
    Supported by the National Natural Science Foundation of China(82204135);Beijing Natural Science Foundation(7232237);China Postdoctoral Science Foundation(BX2021021);China Postdoctoral Science Foundation(2022M710249)

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Abstract:

Objective: To explore the effects of short-term particulate matter (PM) exposure and the melatonin receptor 1B (MTNR1B) gene on triglyceride-glucose (TyG) index utilizing data from Fang-shan Family-based Ischemic Stroke Study in China (FISSIC). Methods: Probands and their relatives from 9 rural areas in Fangshan District, Beijing, were included in the study. PM data were obtained from fixed monitoring stations of the National Air Pollution Monitoring System. TyG index was calculated by fasting triglyceride and glucose concentrations. The associations of short-term PM exposure and rs10830963 polymorphism of the MTNR1B gene with the TyG index were assessed using mixed linear models, in which covariates such as age, sex, and lifestyles were adjusted for. Gene-environment inter-action analysis was furtherly performed using the maximum likelihood methods to explore the potential effect modifier role of rs10830963 polymorphism in the association of PM with TyG index. Results: A total of 4 395 participants from 2 084 families were included in the study, and the mean age of the study participants was (58.98±8.68) years, with 53. 90% females. The results of association analyses showed that for every 10 μg/m3 increase in PM2.5 concentration, TyG index increased by 0.017 (95%CI: 0.007-0.027), while for per 10 μg/m3 increment in PM10, TyG index increased by 0.010 (95%CI: 0.003-0.017). And the associations all had lagged effects. In addition, there was a positive association between the rs10830963 polymorphism and the TyG index. For per increase in risk allele G, TyG index was elevated by 0.040 (95%CI: 0.004-0.076). The TyG index was 0.079 (95%CI: 0.005-0.152) higher in carriers of the GG genotype compared with carriers of the CC genotype. The interaction of rs10830963 polymorphism with PM exposure had not been found to be statistically significant in the present study. Conclusion: Short-term exposure to PM2.5 and PM10 were associated with higher TyG index. The G allele of rs10830963 polymorphism in the MTNR1B gene was associated with the elevated TyG index.

Key words: Particulate matter, Inhalation exposure, Triglyceride-glucose index, MTNR1B gene, Family-based study

CLC Number: 

  • R122.2

Table 1

Baseline characteristics of participants"

Characteristics Total (n=4 395) Female (n=2 369) Male (n=2 026) P
Age/years, ${\bar x}$±s 58.98±8.68 59.00±8.38 58.95±9.01 0.824
Educational levels, n(%) <0.001
  Primary school or less 1 981 (45.07) 1 258 (53.10) 723 (35.69)
  Junior and senior high school 2 341 (53.27) 1 079 (45.55) 1 262 (62.29)
  College and above 73 (1.66) 32 (1.35) 41 (2.02)
BMI/(kg/m2), ${\bar x}$±s 26.27±4.58 26.65±5.30 25.82±3.51 <0.001
Smoke status, n(%) <0.001
  Never 2 474 (56.29) 2 005 (84.63) 469 (23.15)
  Former 660 (15.02) 153 (6.46) 507 (25.02)
  Current 1 261 (28.69) 211 (8.91) 1 050 (51.83)
Drinking status, n(%) <0.001
  Never 2 756 (62.71) 2 080 (87.80) 676 (33.37)
  Former 389 (8.85) 55 (2.32) 334 (16.49)
  Current 1 250 (28.44) 234 (9.88) 1 016 (50.15)
Physical activity per weeka, $\bar x \pm s$ 137.18±158.41 149.98±157.09 122.22±158.67 <0.001
Healthy diet score, ${\bar x}$±s 17.68±1.92 18.05±1.97 17.25±1.77 <0.001
Sleep duration per day, n(%) <0.001
  <7 h 937 (21.32) 554 (23.39) 383 (18.90)
  7-8 h 2 345 (53.36) 1 235 (52.13) 1 110 (54.79)
  >8 h 1 113 (25.32) 580 (24.48) 533 (26.31)
Coronary heart disease, n(%) 970 (22.07) 592 (24.99) 378 (18.66) <0.001
Type 2 diabetes, n(%) 2 337 (53.17) 1 362 (57.49) 975 (48.12) <0.001
Hypertension, n(%) 2 642 (60.11) 1 465 (61.84) 1 177 (58.09) <0.013
Antihypertensive treatment, n(%) 2 307 (52.49) 1 322 (55.80) 985 (48.62) <0.001
Antihyperglycemic treatment, n(%) 1 877 (42.71) 1 122 (47.36) 755 (37.27) <0.001
Antihyperlipidemic treatment, n(%) 801 (18.23) 431 (18.19) 370 (18.26) 0.984

Table 2

Summary statistics for air pollutants and meteorological variables"

Air pollutants $\bar x \pm s$ Minimum Median (P25, P75) Maximum
PM2.5/(μg/m3) 57.9±37.6 3.1 50.4 (27.0, 85.2) 189.1
PM10/(μg/m3) 91.2±49.7 14.4 88.9 (56.1, 118.2) 463.8
NO2/(μg/m3) 42.3±14.9 13.1 39.5 (32.8, 48.9) 115.0
SO2/(μg/m3) 4.3±3.2 2.0 3.6 (2.1, 5.2) 41.0
CO/(mg/m3) 0.8±0.3 0.1 0.8 (0.6, 1.0) 2.2
Temperature/℃ 26.1±3.6 -3.3 26.9 (24.7, 28.5) 32.6
Relative humidity/% 64.6±12.8 19.0 66.0 (57.0, 75.0) 95.0

Figure 1

Association of particulate matter (PM2.5, PM10) and TyG index lag0, average concentration on the day of the survey; mv01, average concentration from the day before to the day of the survey; mv02, average concentrations from two days prior to the survey to the day of the survey; mv03, average concentrations from three days prior to the survey to the day of the survey; Model 1 adjusted for age, sex, educational level, BMI, smoking, drinking status, physical activity, dietary scores, sleep duration, disease history, and medication history, and included family structure as a randomized term; Model 2 adjusted the temperature and relative humidity based on Model 1; Model 3 additionally adjusted NO2 and SO2 concentration levels from Model 2; Model 4 further considered the additive effect of the rs10830963 polymorphism based on Model 3."

Table 3

Association of rs10830963 polymorphism and TyG index"

Model Inheritance mode Group β (95%CI) P
Model 1 Addictive mode Per increase in the G allele 0.043 (0.004, 0.082) 0.033
Dominant mode CC Reference
CG/GG 0.048 (-0.010, 0.105) 0.104
Recessive mode CC/CG Reference
GG 0.055 (-0.008, 0.117) 0.088
Co-dominant mode CC Reference
CG 0.036 (-0.024, 0.095) 0.241
GG 0.087 (0.008, 0.167) 0.031
Model 2 Addictive mode Per increase in the G allele 0.049 (0.010, 0.087) 0.013
Dominant mode CC Reference
CG/GG 0.055 (-0.002, 0.112) 0.058
Recessive mode CC/CG Reference
GG 0.062 (0.000, 0.124) 0.050
Co-dominant mode CC Reference
CG 0.042 (-0.017, 0.101) 0.168
GG 0.100 (0.021, 0.179) 0.013
Model 3 Addictive mode Per increase in the G allele 0.040 (0.004, 0.076) 0.032
Dominant mode CC Reference
CG/GG 0.050 (-0.003, 0.103) 0.064
Recessive mode CC/CG Reference
GG 0.049 (-0.009, 0.107) 0.097
Co-dominant mode CC Reference
CG 0.042 (-0.013, 0.097) 0.136
GG 0.079 (0.005, 0.152) 0.036

Figure 2

Interaction analysis of particulate matter (PM2.5, PM10) with rs10830963 lag0, average concentration on the day of the survey; mv01, average concentration from the day before to the day of the survey; mv02, average concentrations from two days prior to the survey to the day of the survey; mv03, average concentrations from three days prior to the survey to the day of the survey; The model adjusted for age, sex, educational level, BMI, smoking, drinking, physical activity, dietary scores, sleep duration, history of disease and medication, temperature and relative humidity, and concentration levels of NO2 and SO2, and included family structure as a randomized term."

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