Association Between Per- and Polyfluoroalkyl Substances and All-Cause Mortality in Diabetic Patients: Insights from a National Cohort Study and Toxicogenomic Analysis
Abstract
1. Introduction
2. Methods
2.1. Population-Based Cohort Study Analysis
2.1.1. Research Population
2.1.2. Measurement of Serum PFAS Compounds
2.1.3. Definition of Outcome
2.1.4. The Use of Covariates
2.1.5. Statistical Analysis
2.2. Toxicogenomic Analysis
2.2.1. Identification of Potential Target Genes for PFAS Using Databases
2.2.2. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Enrichment Analysis
2.2.3. Construction of PPI Network and Identification of Hub Genes
2.2.4. Chemical–Gene Interaction Patterns
3. Results
3.1. Baseline Characteristics
3.2. Logistic Regression Analysis of PFAS Compounds and Death in the DM Population
3.3. Assessing the Predictive Value of PFAS Compounds for All-Cause Mortality in DM Patients
3.4. Investigating the Link Between Three PFAS Compounds and All-Cause Mortality in Diabetic Individuals
3.5. Results of Toxicogenomic Analysis
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Characteristics | Total (N = 1256) | Alive (N = 1044) | Death (N = 212) | p-Value |
---|---|---|---|---|
Age, n (%) | <0.0001 | |||
18–59 | 621 (61.685) | 572 (65.930) | 49 (34.308) | |
≥60 | 635 (38.315) | 472 (34.070) | 163 (65.692) | |
Sex, n (%) | 0.14 | |||
Male | 627 (49.053) | 507 (48.039) | 120 (55.598) | |
Female | 629 (50.947) | 537 (51.961) | 92 (44.402) | |
Race/Ethnicity, n (%) | 0.016 | |||
White | 386 (57.654) | 285 (56.043) | 101 (68.044) | |
Black | 324 (15.475) | 274 (15.495) | 50 (15.346) | |
Other | 546 (26.872) | 485 (28.463) | 61 (16.610) | |
PIR, n (%) | <0.0001 | |||
<1.3 | 421 (24.454) | 344 (23.788) | 77 (28.748) | |
1.3–3.5 | 517 (40.072) | 412 (37.784) | 105 (54.830) | |
>3.5 | 318 (35.473) | 288 (38.428) | 30 (16.422) | |
Educational attainment, n (%) | 0.021 | |||
Below high school | 235 (9.638) | 177 (8.699) | 58 (15.694) | |
High school | 507 (40.107) | 415 (39.418) | 92 (44.553) | |
Above high school | 514 (50.255) | 452 (51.884) | 62 (39.753) | |
Smoking status, n (%) | 0.02 | |||
Never | 677 (55.467) | 586 (57.263) | 91 (43.886) | |
Former | 365 (27.707) | 286 (26.853) | 79 (33.212) | |
Now | 214 (16.826) | 172 (15.884) | 42 (22.901) | |
Alcohol consumption, n (%) | <0.0001 | |||
Never | 225 (15.002) | 182 (14.296) | 43 (19.559) | |
Moderate | 151 (14.672) | 142 (16.275) | 9 (4.335) | |
Mild | 393 (37.568) | 347 (39.372) | 46 (25.938) | |
Former | 302 (19.342) | 211 (16.207) | 91 (39.560) | |
Heavy | 185 (13.416) | 162 (13.851) | 23 (10.608) | |
BMI, n (%) | 0.02 | |||
<18 | 169 (11.641) | 124 (10.641) | 45 (18.094) | |
18–25 | 363 (25.341) | 301 (24.985) | 62 (27.635) | |
>25 | 724 (63.018) | 619 (64.374) | 105 (54.271) | |
Hypertension, n (%) | 0.049 | |||
No | 526 (41.110) | 448 (42.290) | 78 (33.503) | |
Yes | 730 (58.890) | 596 (57.710) | 134 (66.497) | |
Total cholesterol, (mean ± SD), mg/dl | 194.183 ± 1.782 | 193.331 ± 1.801 | 199.675 ± 5.020 | 0.215 |
HEI-2015 score, (mean ± SD) | 50.129 ± 0.584 | 50.251 ± 0.633 | 49.341 ± 1.131 | 0.464 |
Taking anti-diabetic medication | 0.55 | |||
No | 552 (42.863) | 462 (43.243) | 90 (40.414) | |
Yes | 704 (57.137) | 582 (56.757) | 122 (59.586) | |
PFOS, median (IQR), ng/mL | 11.01 (5.40, 20.53) | 10.10 (5.00, 17.93) | 17.95 (10.10, 32.23) | <0.0001 |
PFOA, median (IQR), ng/mL | 2.60 (1.57, 4.20) | 2.40 (1.47, 4.00) | 3.30 (2.3, 5.05) | 0.008 |
PFNA, median (IQR), ng/mL | 0.91 (0.50, 1.40) | 0.90 (0.50, 1.40) | 0.91 (0.57, 1.48) | 0.53 |
PFHS, median (IQR), ng/mL | 1.59 (0.90, 2.60) | 1.50 (0.80, 2.50) | 1.90 (1.19, 3.00) | 0.175 |
PFDE, median (IQR), ng/mL | 0.20 (0.14, 0.40) | 0.19 (0.14, 0.40) | 0.20 (0.19, 0.33) | 0.472 |
PFUA, median (IQR), ng/mL | 0.14 (0.07, 0.20) | 0.14 (0.07, 0.20) | 0.18 (0.14, 0.20) | 0.121 |
MPAH, median (IQR), ng/mL | 0.20 (0.07, 0.40) | 0.20 (0.07, 0.37) | 0.37 (0.20, 0.63) | 0.003 |
Crude Model | Model 1 | Model 2 | Model 3 | |||||
---|---|---|---|---|---|---|---|---|
PFAS | OR (95%CI) | p-Value | OR (95%CI) | p-Value | OR (95%CI) | p-Value | OR (95%CI) | p-Value |
PFOS | 1.03 (1.02, 1.04) | <0.0001 | 1.03 (1.01, 1.04) | <0.001 | 1.03 (1.01, 1.04) | <0.001 | 1.03 (1.01, 1.04) | <0.001 |
PFOA | 1.09 (1.03, 1.14) | 0.002 | 1.07 (1.00, 1.15) | 0.04 | 1.10 (1.02, 1.18) | 0.01 | 1.11 (1.03, 1.19) | 0.01 |
PFNA | 1.05 (0.90, 1.23) | 0.52 | 1.03 (0.85, 1.25) | 0.75 | 1.07 (0.90, 1.27) | 0.45 | 1.07 (0.90, 1.26) | 0.44 |
PFHS | 1.05 (0.98, 1.12) | 0.16 | 1.00 (0.93, 1.09) | 0.92 | 1.00 (0.93, 1.08) | 0.97 | 1.00 (0.93, 1.08) | 0.96 |
PFDE | 1.26 (0.72, 2.20) | 0.41 | 1.24 (0.63, 2.42) | 0.53 | 1.33 (0.70, 2.50) | 0.38 | 1.23 (0.65, 2.33) | 0.52 |
PFUA | 1.60 (0.89, 2.85) | 0.11 | 1.56 (0.83, 2.94) | 0.17 | 1.82 (0.98, 3.38) | 0.06 | 1.77 (0.96, 3.24) | 0.07 |
MPAH | 2.51 (1.86, 3.39) | <0.0001 | 2.09 (1.55, 2.83) | <0.0001 | 2.13 (1.50, 3.02) | <0.0001 | 1.97 (1.39, 2.81) | <0.001 |
Character | Se | p-Value | HR (95% CI) * |
---|---|---|---|
PFOS | |||
Low level | ref | ref | ref |
High level | 0.172 | 0.025 | 1.554 (1.056, 2.287) |
Age | |||
18–59 | ref | ref | ref |
≥60 | 0.19 | <0.0001 | 3.639 (2.442, 5.424) |
Sex | |||
Male | ref | ref | ref |
Female | 0.171 | 0.051 | 0.672 (0.450, 1.001) |
Race/Ethnicity | |||
White | ref | ref | ref |
Black | 0.223 | 0.225 | 0.795 (0.548, 1.152) |
Other | 0.239 | 0.022 | 0.530 (0.308, 0.912) |
Education | |||
Below high school | ref | ref | ref |
High school | 0.25 | 0.227 | 0.715 (0.415, 1.232) |
Above high school | 0.266 | 0.78 | 1.085 (0.614, 1.916) |
PIR | |||
<1.3 | ref | ref | ref |
1.3–3.5 | 0.19 | 0.935 | 1.016 (0.697, 1.479) |
>3.5 | 0.268 | 0.011 | 0.467 (0.259, 0.842) |
BMI | |||
<18 | ref | ref | ref |
18–25 | 0.242 | 0.005 | 0.512 (0.322, 0.817) |
>25 | 0.23 | 0.02 | 0.559 (0.342, 0.914) |
Smoking status | |||
never | ref | ref | ref |
former | 0.199 | 0.613 | 1.116 (0.728, 1.711) |
now | 0.228 | 0.049 | 1.688 (1.003, 2.840) |
Alcohol consumption | |||
never | ref | ref | ref |
moderate | 0.426 | 0.005 | 0.255 (0.098, 0.663) |
mild | 0.254 | 0.078 | 0.576 (0.312, 1.064) |
former | 0.243 | 0.937 | 0.979 (0.576, 1.665) |
heavy | 0.335 | 0.223 | 0.619 (0.286, 1.339) |
HEI-2015 score | 0.006 | 0.014 | 0.984 (0.972, 0.997) |
Hypertension | |||
No | ref | ref | ref |
Yes | 0.179 | 0.251 | 1.277 (0.841, 1.941) |
Total cholesterol | 0.002 | 0.56 | 1.001 (0.998, 1.004) |
Taking anti-diabetic medication | |||
No | ref | ref | ref |
Yes | 0.166 | 0.267 | 1.200 (0.870, 1.656) |
Chemical–Gene Interaction | AKT1 | BCL2 | CASP3 | IL6 | TNF | PPARG | SIRT1 | INS | NFKB1 | EGFR | |
---|---|---|---|---|---|---|---|---|---|---|---|
PFOS | mRNA expression | - | ↓↓↓↓ | ↑ | ↑ | ↓ | ↑↑↑↑↓ | ↓ | - | ↓ | - |
Protein expression | - | ↓↓↓ | - | - | - | - | ↓ | ↑ | - | - | |
Protein activity | - | - | ↑↑ | - | - | ↑↑ | - | - | - | - |
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Wei, Z.; Chen, J.; Mei, X.; Yu, Y. Association Between Per- and Polyfluoroalkyl Substances and All-Cause Mortality in Diabetic Patients: Insights from a National Cohort Study and Toxicogenomic Analysis. Toxics 2025, 13, 168. https://doi.org/10.3390/toxics13030168
Wei Z, Chen J, Mei X, Yu Y. Association Between Per- and Polyfluoroalkyl Substances and All-Cause Mortality in Diabetic Patients: Insights from a National Cohort Study and Toxicogenomic Analysis. Toxics. 2025; 13(3):168. https://doi.org/10.3390/toxics13030168
Chicago/Turabian StyleWei, Zhengxiao, Jinyu Chen, Xue Mei, and Yi Yu. 2025. "Association Between Per- and Polyfluoroalkyl Substances and All-Cause Mortality in Diabetic Patients: Insights from a National Cohort Study and Toxicogenomic Analysis" Toxics 13, no. 3: 168. https://doi.org/10.3390/toxics13030168
APA StyleWei, Z., Chen, J., Mei, X., & Yu, Y. (2025). Association Between Per- and Polyfluoroalkyl Substances and All-Cause Mortality in Diabetic Patients: Insights from a National Cohort Study and Toxicogenomic Analysis. Toxics, 13(3), 168. https://doi.org/10.3390/toxics13030168