The association between cadmium exposure and axonal injury biomarker, serum neurofilament light chain levels in US adults

The association between cadmium exposure and axonal injury biomarker, serum neurofilament light chain levels in US adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The association between cadmium exposure and axonal injury biomarker, serum neurofilament light chain levels in US adults Jing Luo, Song Lin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3841618/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and Aims: Cadmium exposure has been shown a toxic effect on the nervous system, but little is known regarding the link between cadmium exposure and axonal injury. Therefore, we aim to investigate whether there is a relationship between blood cadmium and serum neurofilament light chain (NfL) levels in the general population. Methods and Results: In the National Health and Nutrition Examination Survey 2013–2014, 1,040 participants with a median (IQR) age of 47 (35–60) years are enrolled. Serum NfL levels are measured using a highly sensitive immunoassay. Whole blood cadmium concentrations are detected using inductively coupled plasma mass spectrometry. Linear regression and restricted cubic spline models are used to analyze the strength and shape of the relationship between blood cadmium and serum NfL levels. In full adjusted model, blood cadmium levels are positively associated with serum NfL levels (Q4 vs Q1, β = 3.35, 95%CI: 0.41, 6.30, p for trend = 0.014). A potential linear positive dose-effect relationship is found between blood cadmium and serum NfL levels ( p for non-linearity = 0.15), and the potential threshold dose of blood cadmium is 0.7 µg/L. The stratified analysis shows a significant positive relationship between blood cadmium and serum NfL levels is limited to middle-aged and older adults. Conclusion: The present study suggests a positive association between blood cadmium and serum NfL levels in the general US population. This study is expected to provide new ideas for the primary prevention and mechanism exploration of neurodegenerative diseases. cadmium neurofilament axonal injury neurodegenerative diseases Figures Figure 1 Figure 2 Figure 3 1. Introduction Cadmium is a heavy metal and widely present in food, water, air, and tobacco due to industrial and agricultural activities [ 1 ]. Cadmium cannot be degraded in the natural environment and has high mobility, bioaccumulation, and toxicity [ 2 ]. Animal studies have indicated that cadmium can cross the blood-brain barrier [ 3 , 4 ] and induced neuronal swelling, degeneration, and death via oxidative stress, inflammation, autophagy, and apoptosis pathways [ 5 – 8 ]. Some epidemiological studies have shown that long-term, even low levels of cadmium exposure are closely associated with neurological diseases, including multiple sclerosis [ 9 ], ischemic stroke [ 10 ], and cognitive decline [ 11 – 14 ]. Additionally, higher cadmium exposure is associated with increased risk of Alzheimer's disease mortality [ 15 – 17 ]. However, several studies show there is no relationship between cadmium exposure and cognitive function [ 18 – 20 ]. Notably, a latest nested case-control study from a prospective European cohort suggests a negative association between blood cadmium and Parkinson's disease risk [ 21 ]. In view of the inconsistent evidence, more evidence is needed to explore the potential effects of cadmium on nerve cells. Neurofilaments are neuron-specific type IV intermediate filament heteropolymers composed of light, medium, and heavy chains [ 22 ]. Neurofilaments are synthesized in the neuronal perikaryon and are integrated into the axonal cytoskeleton [ 23 ]. In physiological conditions, neurofilaments are primarily cleared by the proteasomes [ 24 ] and autophagic lysosomes [ 25 ]. However, after neuro-axonal damage, neurofilaments are released into cerebrospinal fluid and blood in turn [ 26 ]. Among these neurofilaments, neurofilament light chain (NfL) can self-assemble and constitute the backbone of nerve fibers, and has a small molecular weight and high solubility, and has thus been proposed as a putative biomarker of neuro-axonal injury [ 27 , 28 ]. Nowadays, NfL levels has been extensively validated as a sensitive diagnostic biomarker in several neurological disorders, including multiple system atrophy, multiple sclerosis [ 29 ], Alzheimer’s disease [ 30 ], and stroke [ 31 ]. NfL levels can also predict disease progression and therapeutic effects in some neurologic conditions [ 32 – 34 ]. To date, seldom study investigates the association between cadmium exposure and NfL levels in the general population. In the present study, we aim to determine the potential association between blood cadmium and NfL levels in a large population-based survey of US adults. This study may provide a new idea for the early prevention and mechanism exploration of neurodegenerative diseases. 2. Materials and Methods 2.1. Study Population The National Health and Nutritional Health Survey (NHANES) is an ongoing cross-sectional study that assesses the nutritional and health status of the general civilians in the United States every two years. To obtain a representative sample, NHANES program uses the multi-stage stratified design with oversampling of the non-Hispanic Asians, Hispanics, non-Hispanic blacks, older adults, and low-income individuals. Detailed information about the NHANES has been reported in other study [ 35 ]. The protocol of NHANES is approved by the Centers for Disease Control and Prevention Research Ethics Review Board and documented signed consents are obtained from all participants. 2.2. Blood Cadmium One-half sample from participants aged 12 years and older are eligible. Whole blood cadmium concentrations are detected using inductively coupled plasma mass spectrometry (PerkinElmer ELAN DRC II, Norwalk, CT) after appropriate sample collection and dilution steps. Random duplicate testing is performed on 2.0% of all samples. The limit of detection (LOD) for blood cadmium is 0.1µg/L, which is defined as three times the standard deviation at zero analyte concentration. For data below the LOD, an imputed value is equal to the LOD/√2, and 137 participants have values below the LOD. 2.3. Serum Neurofilament Light Chain In the 2013–2014 cycle of NHANES, serum NfL levels are detected using a highly sensitive immunoassay developed by Siemens Healthineers. Its principle is the use of acridinium ester chemiluminescence and paramagnetic particles. All the measurement steps are performed on the automated Attelica immunoassay system. The lower limit of quantification (LLOQ) and the upper limit of quantification (ULOQ) of serum NfL is 3.9pg/mL and 500pg/mL, respectively. The LLOQ is determined by replicate testing of low concentration samples (n = 44) and defined as the coefficient of variation (CV) ≤ 20%. For data below the LLOQ or above the ULOQ, an imputed value is equal to the LLOQ/√2 or ULOQ×√2, respectively. 22 participants have values below the LLOQ. No participants have values above ULOQ. 2.4. Other variables Participants’ self-reported information includes age (years), gender (men and women), race (Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, and other races), education level (the highest grade), smoking status, alcohol drinking status, and medical history. In the present study, education level is classified as less than high school grade, high school grade, and college graduate or above grade. Smokers are defined as those who have smoked at least 100 cigarettes in life. Alcohol drinkers are defined as those who have consumed alcohol at least 12 times per year. Body mass index (BMI) is calculated as weight in kilograms divided by height in meters squared, and classified as normal (< 25 kg/m 2 ), overweight (25 to 30 kg/m 2 ), and obesity (≥ 30 kg/m 2 ). Diabetes is defined as someone who met one of the following items: 1) fasting plasma glucose ≥ 126 mg/dL; 2) hemoglobin A1c ≥ 6.5%; 3) self-reported physician diagnosis of diabetes or current taking anti-diabetic drugs. Cardiovascular disease (CVD) is defined as participants who are self-reported physician diagnosis of either congestive heart failure, coronary heart disease, angina pectoris, heart attack, or stroke. 2.5. Statistical Analysis All analyses are performed using Stata version 15.1 (Stata Corporation, College Station, TX, USA). Given the multi-stage design of NHANES, appropriate weight and sampling unit variables are designated according to the NHANES analytic guidelines. Qualitative variables are expressed by frequency distributions. Continuous variables are expressed by medians and inter-quartile range (IQR). General characteristics and serum NfL according to blood cadmium are evaluated using the chi-square test for categorical variables and linear regression for continuous variables. Linear regression models are fitted to explore the potential relationship between blood cadmium and serum NfL levels. The selection of covariates is based on previous studies. The first model is a crude model without any adjustment. The second model adjusts for age, sex, and race. The third model further adjusts for educational level, BMI, smoking status, alcohol drinking status, diabetes, and CVD. Linear trends and interaction effects are tested using blood cadmium as continuous variable in logistic regression models. The restricted cubic spline (RCS) model is applied to explore the potential dose-effect relationship between blood cadmium and serum NfL levels. A two-tailed value of p < 0.05 is considered statistically significant. 3. Results We exclude participants without data on blood cadmium and serum NfL, leaving 1,040 participants with a median (IQR) age of 47 (35–60) years included in the following analyses (Fig. 1 ). The histogram shows a non-normal distribution of blood cadmium levels (Fig. 2 ). The median (IQR) blood cadmium levels are 0.30 (0.18–0.63) µg/L. Compared with participants in the lowest quintile of blood cadmium levels, those in the highest quartile are more likely to be elderly, female, non-Hispanic Black, smokers, and CVD patients, to have a lower degree of education, BMI, and serum NfL levels (Table 1 ). Table 1 Characteristics of study population Blood cadmium levels, µg/L P Q1 (0.05–0.18) Q2 (0.19–0.30) Q3 (0.31–0.63) Q4 (≥0.64) Number of subjects 281 (27.1) 253 (24.3) 253 (24.3) 253 (24.3) Age (years), % < 0.001 20–49 197 (70.1) 144 (56.9) 98 (38.7) 130 (51.4) 50–75 84 (29.9) 109 (43.1) 155 (61.3) 123 (48.6) Gender, % < 0.001 Male 167 (59.4) 114 (45.1) 99 (39.1) 120 (47.4) Female 114 (40.6) 139 (54.9) 154 (60.9) 133 (52.6) Race/Ethnicity, % < 0.001 Mexican American 42 (14.9) 51 (20.1) 43 (17.0) 12 (4.7) Other Hispanic 37 (13.2) 24 (9.5) 27 (10.7) 20 (7.9) Non-Hispanic White 139 (49.5) 105 (41.5) 97 (38.3) 117 (46.3) Non-Hispanic Black 41 (14.6) 44 (17.4) 41 (16.2) 62 (24.5) Other Race 22 (7.8) 29 (11.5) 45 (17.8) 42 (16.6) Education, % < 0.001 High school 167 (59.4) 156 (61.6) 160 (63.2) 106 (41.9) BMI, % < 0.001 Normal 77 (27.5) 63 (25.0) 75 (29.8) 101 (40.6) Overweight 78 (27.9) 102 (40.5) 79 (31.3) 75 (30.1) Obesity 125 (44.6) 87 (34.5) 98 (38.9) 73 (29.3) Smoker, % 50 (17.8) 83 (32.8) 115 (45.4) 207 (81.8) < 0.001 Alcohol drinker, % 206 (76.9) 166 (71.8) 167 (74.2) 174 (76.6) 0.549 Diabetes, % 40 (14.2) 39 (15.4) 43 (17.0) 42 (16.6) 0.816 CVD, % 11 (3.9) 17 (6.7) 15 (5.9) 33 (13.0) < 0.001 Serum NfL (pg/ml) 9.8 (6.9, 14.3) 12.0 (8.0, 18.1) 13.6 (9.1, 21.4) 13.1 (8.8, 20.3) < 0.001 We find a positive association between blood cadmium and serum NfL levels (Table 2 ). In the crude model (model 1), compared with participants in quartile 1, blood cadmium levels in quintile 4 is positively associated with serum NfL levels ( β = 3.62, 95%CI: 1.05, 6.18, p for trend = 0.001). This association persisted after adjustment for age, sex, and race (model 2, p for trend = 0.006) and even after further adjustment for education level, BMI, smoking status, alcohol drinking status, diabetes, and CVD (model 3, p for trend = 0.014). Table 2 Association of blood cadmium with serum neurofilament light chain levels Model 1 P Model 2 P Model 3 P Quartile 1 Ref. Ref. Ref. Quartile 2 2.18 (-0.54, 4.91) 0.108 0.70 (-1.51, 2.90) 0.512 0.59 (-1.24, 2.42) 0.503 Quartile 3 6.90 (1.14, 12.67) 0.022 4.60 (-0.68, 9.89) 0.083 4.93 (-0.02, 9.88) 0.051 Quartile 4 4.15 (1.81, 6.50) 0.002 3.62 (1.05, 6.18) 0.009 3.35 (0.41, 6.30) 0.028 P for trend 0.001 0.006 0.014 Model 1 crude model without any adjustment; model 2 adjusted for age, gender, and race; model 3 adjusted for all covariates in model 2 plus education level, BMI, smoking status, alcohol drinking status, diabetes, and cardiovascular diseases. The RCS analysis show a potential linearity dose-effect relationship between blood cadmium and serum NfL levels (chi2 = 2.07, p for non-linearity = 0.15). When blood cadmium exceeds 0.7µg/L, there is a significant positive relationship between blood cadmium and serum NfL levels; however, the strength of this correlation seems to reach a plateau beyond this concentration (Fig. 3 ). Our study shows an interaction between age and blood cadmium levels ( p for interaction = 0.013). The results of stratified analysis by age show a significant positive relationship between blood cadmium and serum NfL levels only in individuals aged 50 to 75 years old (Table 3 ). No significant interactions are found between blood cadmium levels and sex ( p for interaction = 0.596), race ( p for interaction = 0.779), education levels ( p for interaction = 0.934), BMI ( p for interaction = 0.291), smoking status ( p for interaction = 0.246), alcohol drinking status ( p for interaction = 0.280), diabetes ( p for interaction = 0.978), and CVD ( p for interaction = 0.811). Table 3 Association of blood cadmium with serum neurofilament light chain levels stratified by age Quartile 1 Quartile 2 Quartile 3 Quartile 4 P for trend 20–49 years Ref. -0.17 (-2.93, 2.59) 1.36 (-2.86, 5.58) 1.04 (-4.58, 6.66) 0.610 50–75 years Ref. 2.72 (-2.19, 7.63) 10.04 (3.44, 16.65) 9.00 (2.25, 15.75) < 0.001 4. Discussion We investigate the potential association between blood cadmium and serum NfL levels in a large representative population-based survey of US individuals using the data from the 2013–2014 cycle of NHANES. Our study shows a positive relationship between blood cadmium and serum NfL levels. This association still exist after adjusting potential confounding factors, including age, sex, race, education level, BMI, smoking status, alcohol drinking status, diabetes, and CVD. As far as we known, only one published study explores the correlation between blood cadmium and serum NfL levels. The Beaver Dam Offspring Study (1,516 midlife participants) show that a doubling in baseline cadmium level is associated with a 0.2% (95% CI: 0.0, 0.3) higher increase per year in NfL concentrations [ 36 ]. Additionally, many studies have shown that cadmium exposure is toxic to the nervous system. Studies using NHANES data show that increased blood cadmium is associated with worse cognitive function in adults aged 60 years or older [ 37 , 38 ]. Similarly, a study conducted in Chinese adults aged 65 or older also report that higher cadmium exposure is associated with greater cognitive decline [ 11 ]. However, the Health Outcomes and Measures of the Environment study, which measure maternal urinary cadmium concentrations at 26 weeks of gestation and assess cognitive function of children at ages 1, 2, 3, 4, 5, and 8 years, its result show no significant association between maternal cadmium exposure and cognitive function of children [ 39 ]. The Mothers and Children's Environmental Health study shows that prenatal cadmium levels during either early or late pregnancy period show no relationship with neurodevelopment at 6 months of age [ 40 ]. The above findings suggest that the potential effects of cadmium exposure on the nervous system may be influenced by age, which is closely related to cumulative exposure of cadmium. In the present study, we find an interaction between age and blood cadmium, and the stratified analysis shows a significant positive relationship between blood cadmium and serum NfL levels is limited to individuals aged 50 to 75 years. Our study indicates a linearity dose-effect relationship between blood cadmium and serum NfL levels, and the potential threshold dose of blood cadmium associated neuro-axonal injury is 0.7 µg/L. However, when the blood cadmium concentration continued to increase, the strength of its association with serum NfL levels do not increase. In the present study, the subjects are the general population rather than occupationally exposed people, and median blood cadmium concentrations are at a low level, thus the neurological effects of higher doses of cadmium exposure cannot be ascertained. In an animal study, transmission electron microscopy shows degenerative changes in myelinated fibers in cadmium intervention groups, with swollen axons, irregular outlines, disordered arrangement of neurofilaments, swelling of many mitochondria, and destruction of cartridges [ 41 ]. Although the exact molecular mechanism has not been fully elucidated, the toxic effects of cadmium on nerve cells may rely on inflammation, oxidative stress, sphingolipid disturbance [ 42 ], mitochondrial damage, interference with neurotransmitter transmission, and induction of cell autophagy and apoptosis[ 25 , 43 ]. Many chemicals with anti-inflammatory and antioxidant properties can protect against cadmium-induced neurotoxicity [ 43 , 44 , 41 ]. Our study has several strengths. Firstly, this study is based on a representative sample, which allows for avoidance of selection bias and extrapolation of the results to the general population. Secondly, according to the dose-effect relationship identified in this study, the potential threshold of nerve cell damage induced by cadmium exposure can be further explored. Thirdly, after adjusting for potential confounding factors, the result remains robust. Finally, subgroup analysis provides clue to identify potential high-risk individuals. Meanwhile, several limitations exist in our study. Firstly, the study is cross-sectional design and the causal relationship cannot be ascertained. Secondly, the range of blood cadmium concentrations of this study population is in the low range, thus the neurological effects of higher cadmium exposure (e.g., occupational exposure) could not be determined. Finally, blood cadmium should not be equivalent to levels in nerve cells because the affinity for cadmium varies between tissues and the effect of cadmium on nerves may be tissue-specific. 5. Conclusion In this large representative population-based survey of US individuals, we find a positive linear association between blood cadmium and serum NfL levels, and the potential threshold dose of blood cadmium is 0.7 µg/L. These findings need to be further confirmed in well-designed prospective cohort and toxicological studies. This study may provide a novel idea for the primary prevention of neurodegenerative diseases. Declarations Acknowledgment Thanks to all participants who collected data and making the NHANES datasets available on the website. Funding None. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author Contributions: S.L designed the study. S.L and J.L performed the statistical analysis, drafted the manuscript, revised the manuscript, and supervised the study. Both authors contributed to the final submitted version and agree to be responsible for all the work. Data Availability The datasets can be found in online repositories (https://wwwn.cdc.gov/nchs/nhanes/). This study was available from corresponding author upon reasonable request. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the United States National Center for Health Statistics. Consent to participate Written informed consent was obtained from the parents. References Wang M, Chen Z, Song W, Hong D, Huang L, Li Y (2021) A review on Cadmium Exposure in the Population and Intervention Strategies Against Cadmium Toxicity. Bulletin of environmental contamination and toxicology 106(1):65-74. https://doi:10.1007/s00128-020-03088-1 Buha A, Đukić-Ćosić D, Ćurčić M, Bulat Z, Antonijević B, Moulis JM, Goumenou M, Wallace D (2020) Emerging Links between Cadmium Exposure and Insulin Resistance: Human, Animal, and Cell Study Data. Toxics 8(3). https://doi:10.3390/toxics8030063 Zhang T, Xu Z, Wen L, Lei D, Li S, Wang J, Huang J, Wang N, Durkan C, Liao X, Wang G (2021) Cadmium-induced dysfunction of the blood-brain barrier depends on ROS-mediated inhibition of PTPase activity in zebrafish. Journal of hazardous materials 412:125198. https://doi:10.1016/j.jhazmat.2021.125198 Li CX, Talukder M, Xu YR, Zhu SY, Zhao YX, Li JL (2023) Cadmium aggravates the blood-brain barrier disruption via inhibition of the Wnt7A/β-catenin signaling axis. Environmental pollution (Barking, Essex : 1987 324:121400. https://10.1016/j.envpol.2023.121400 Wang T, Wang Q, Song R, Zhang Y, Zhang K, Yuan Y, Bian J, Liu X, Gu J, Liu Z (2015) Autophagy Plays a Cytoprotective Role During Cadmium-Induced Oxidative Damage in Primary Neuronal Cultures. Biological trace element research 168(2):481-9. https://doi:10.1007/s12011-015-0390-8 Phuagkhaopong S, Ospondpant D, Kasemsuk T, Sibmooh N, Soodvilai S, Power C, Vivithanaporn P (2017) Cadmium-induced IL-6 and IL-8 expression and release from astrocytes are mediated by MAPK and NF-κB pathways. Neurotoxicology 60:82-91. https://doi:10.1016/j.neuro.2017.03.001 Wang T, Zhu Q, Cao B, Cai Y, Wen S, Bian J, Zou H, Song R, Gu J, Liu X, Liu Z, Yuan Y (2022) Ca(2+) transfer via the ER-mitochondria tethering complex in neuronal cells contribute to cadmium-induced autophagy. Cell biology and toxicology 38(3):469-85. https://doi:10.1007/s10565-021-09623-y Talukder M, Bi SS, Lv MW, Ge J, Zhang C, Li JL (2023) Involvement of the heat shock response (HSR) regulatory pathway in cadmium-elicited cerebral damage. Environmental science and pollution research international 30(48):106648-59. https://doi:10.1007/s11356-023-29880-0 Sarihi S, Niknam M, Mahjour S, Hosseini-Bensenjan M, Moazzen F, Soltanabadi S, Akbari H (2021) Toxic heavy metal concentrations in multiple sclerosis patients: A systematic review and meta-analysis. EXCLI journal 20:1571-84. https://doi:10.17179/excli2021-3484 Borné Y, Fagerberg B, Persson M, Östling G, Söderholm M, Hedblad B, Sallsten G, Barregard L, Engström G (2017) Cadmium, Carotid Atherosclerosis, and Incidence of Ischemic Stroke. Journal of the American Heart Association 6(12). https://doi:10.1161/jaha.117.006415 Liu H, Su L, Chen X, Wang S, Cheng Y, Lin S, Ding L, Liu J, Chen C, Unverzagt FW, Hake AM, Jin Y, Gao S (2021) Higher blood cadmium level is associated with greater cognitive decline in rural Chinese adults aged 65 or older. The Science of the total environment 756:144072. https://doi:10.1016/j.scitotenv.2020.144072 Wang X, Xiao P, Wang R, Luo C, Zhang Z, Yu S, Wu Q, Li Y, Zhang Y, Zhang H, Zhao X (2022) Relationships between urinary metals concentrations and cognitive performance among U.S. older people in NHANES 2011-2014. Frontiers in public health 10:985127. https://doi:10.3389/fpubh.2022.985127 Lu K, Liu T, Wu X, Zhong J, Ou Z, Wu W (2023) Association between serum iron, blood lead, cadmium, mercury, selenium, manganese and low cognitive performance in old adults from National Health and Nutrition Examination Survey (NHANES): a cross-sectional study. The British journal of nutrition 130(10):1743-53. https://doi:10.1017/s0007114523000740 Gustin K, Tofail F, Vahter M, Kippler M (2018) Cadmium exposure and cognitive abilities and behavior at 10 years of age: A prospective cohort study. Environment international 113:259-68. https://doi:10.1016/j.envint.2018.02.020 Min JY, Min KB (2016) Blood cadmium levels and Alzheimer's disease mortality risk in older US adults. Environmental health : a global access science source 15(1):69. https://doi:10.1186/s12940-016-0155-7 Peng Q, Bakulski KM, Nan B, Park SK (2017) Cadmium and Alzheimer's disease mortality in U.S. adults: Updated evidence with a urinary biomarker and extended follow-up time. Environmental research 157:44-51. https://doi:10.1016/j.envres.2017.05.011 Chen S, Shen R, Shen J, Lyu L, Wei T (2023) Association of blood cadmium with all-cause and cause-specific mortality in patients with hypertension. Frontiers in public health 11:1106732. https://doi:10.3389/fpubh.2023.1106732 Nordberg M, Winblad B, Basun H (2000) Cadmium concentration in blood in an elderly urban population. Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine 13(4):311-7. https://doi:10.1023/a:1009268123320 Park JH, Lee DW, Park KS, Joung H (2014) Serum trace metal levels in Alzheimer's disease and normal control groups. American journal of Alzheimer's disease and other dementias 29(1):76-83. https://doi:10.1177/1533317513506778 Li K, Li A, Mei Y, Zhao J, Zhou Q, Li Y, Yang M, Xu Q (2023) Trace elements and Alzheimer dementia in population-based studies: A bibliometric and meta-analysis. Environmental pollution (Barking, Essex : 1987 318:120782. https://doi:10.1016/j.envpol.2022.120782 Zhao Y, Ray A, Broberg K, Kippler M, Lill CM, Vineis P, Katzke VA, Rodriguez-Barranco M, Chirlaque MD, Guevara M, Gómez JH, Hansen J, Panico S, Middleton LT, Masala G, Pala V, Vinagre-Aragon A, Zibetti M, Vermeulen R, Peters S (2023) Prediagnostic Blood Metal Levels and the Risk of Parkinson's Disease: A Large European Prospective Cohort. Movement disorders : official journal of the Movement Disorder Society. https://doi:10.1002/mds.29602 Yuan A, Rao MV, Veeranna, Nixon RA (2017). Neurofilaments and Neurofilament Proteins in Health and Disease. Cold Spring Harbor perspectives in biology 9(4). https://doi:10.1101/cshperspect.a018309 Jacomy H, Zhu Q, Couillard-Després S, Beaulieu JM, Julien JP (1999) Disruption of type IV intermediate filament network in mice lacking the neurofilament medium and heavy subunits. Journal of neurochemistry 73(3):972-84. https://doi:10.1046/j.1471-4159.1999.0730972.x Park JY, Jang SY, Shin YK, Suh DJ, Park HT (2013) Calcium-dependent proteasome activation is required for axonal neurofilament degradation. Neural regeneration research 8(36):3401-9. https://doi:10.3969/j.issn.1673-5374.2013.36.005 Rao MV, Darji S, Stavrides PH, Goulbourne CN, Kumar A, Yang DS, Yoo L, Peddy J, Lee JH, Yuan A, Nixon RA (2023) Autophagy is a novel pathway for neurofilament protein degradation in vivo. Autophagy 19(4):1277-92. https://doi:10.1080/15548627.2022.2124500 Khalil M, Teunissen CE, Otto M, Piehl F, Sormani MP, Gattringer T, Barro C, Kappos L, Comabella M, Fazekas F, Petzold A, Blennow K, Zetterberg H, Kuhle J (2018) Neurofilaments as biomarkers in neurological disorders. Nature reviews Neurology14(10):577-89. https://doi:10.1038/s41582-018-0058-z Bacioglu M, Maia LF, Preische O, Schelle J, Apel A, Kaeser SA, Schweighauser M, Eninger T, Lambert M, Pilotto A, Shimshek DR, Neumann U, Kahle PJ, Staufenbiel M, Neumann M, Maetzler W, Kuhle J, Jucker M (2016) Neurofilament Light Chain in Blood and CSF as Marker of Disease Progression in Mouse Models and in Neurodegenerative Diseases. Neuron 91(1):56-66. https://doi:10.1016/j.neuron.2016.05.018 Alnemeh-Al Ali H, Griveau A, Artzner F, Dupont A, Lautram N, Jourdain MA, Eyer J (2022) Investigation on the self-assembly of the NFL-TBS.40-63 peptide and its interaction with gold nanoparticles as a delivery agent for glioblastoma. International journal of pharmaceutics: X 4:100128. https://doi:10.1016/j.ijpx.2022.100128 Chelban V, Nikram E, Perez-Soriano A, Wilke C, Foubert-Samier A, Vijiaratnam N, Guo T, Jabbari E, Olufodun S, Gonzalez M, Senkevich K, Laurens B, Péran P, Rascol O, Le Traon AP, Todd EG, Costantini AA, Alikhwan S, Tariq A, Ng BL, Muñoz E, Painous C, Compta Y, Junque C, Segura B, Zhelcheska K, Wellington H, Schöls L, Jaunmuktane Z, Kobylecki C, Church A, Hu MTM, Rowe JB, Leigh PN, Massey L, Burn DJ, Pavese N, Foltynie T, Pchelina S, Wood N, Heslegrave AJ, Zetterberg H, Bocchetta M, Rohrer JD, Marti MJ, Synofzik M, Morris HR, Meissner WG, Houlden H (2022) Neurofilament light levels predict clinical progression and death in multiple system atrophy. Brain : a journal of neurology 145(12):4398-408. https://doi:10.1093/brain/awac253 Chatterjee P, Pedrini S, Doecke JD, Thota R, Villemagne VL, Doré V, Singh AK, Wang P, Rainey-Smith S, Fowler C, Taddei K, Sohrabi HR, Molloy MP, Ames D, Maruff P, Rowe CC, Masters CL, Martins RN (2023) Plasma Aβ42/40 ratio, p-tau181, GFAP, and NfL across the Alzheimer's disease continuum: A cross-sectional and longitudinal study in the AIBL cohort. Alzheimer's & dementia : the journal of the Alzheimer's Association 19(4):1117-34. https://doi:10.1002/alz.12724 Korley FK, Goldstick J, Mastali M, Van Eyk JE, Barsan W, Meurer WJ, Sussman J, Falk H, Levine D (2019) Serum NfL (Neurofilament Light Chain) Levels and Incident Stroke in Adults With Diabetes Mellitus. Stroke 50(7):1669-75. https://doi:10.1161/strokeaha.119.024941 Lin CH, Li CH, Yang KC, Lin FJ, Wu CC, Chieh JJ, Chiu MJ (2019) Blood NfL: A biomarker for disease severity and progression in Parkinson disease. Neurology 93(11):e1104-e11. https://doi:10.1212/wnl.0000000000008088. Halloway S, Desai P, Beck T, Aggarwal N, Agarwal P, Evans D, Rajan KB, Project. CHaA (2022) Association of Neurofilament Light With the Development and Severity of Parkinson Disease. Neurology 98(22):e2185-e93. https://doi:10.1212/wnl.0000000000200338 Bar-Or A, Thanei GA, Harp C, Bernasconi C, Bonati U, Cross AH, Fischer S, Gaetano L, Hauser SL, Hendricks R, Kappos L, Kuhle J, Leppert D, Model F, Sauter A, Koendgen H, Jia X, Herman AE (2023) Blood neurofilament light levels predict non-relapsing progression following anti-CD20 therapy in relapsing and primary progressive multiple sclerosis: findings from the ocrelizumab randomised, double-blind phase 3 clinical trials. EBioMedicine 93:104662. https://doi:10.1016/j.ebiom.2023.104662 Leroux A, Di J, Smirnova E, McGuffey EJ, Cao Q, Bayatmokhtari E, Tabacu L, Zipunnikov V, Urbanek JK, Crainiceanu C (2019) Organizing and analyzing the activity data in NHANES. Statistics in biosciences 11(2):262-87. https://doi:10.1007/s12561-018-09229-9 Schubert CR, Paulsen AJ, Pinto AA, Chappell RJ, Chen Y, Ferrucci L, Hancock LM, Cruickshanks KJ, Merten N (2023) Effect of Neurotoxin Exposure on Blood Biomarkers of Neurodegeneration and Alzheimer Disease. Alzheimer disease and associated disorders https://doi:10.1097/wad.0000000000000579 Li H, Wang Z, Fu Z, Yan M, Wu N, Wu H, Yin P (2018) Associations between blood cadmium levels and cognitive function in a cross-sectional study of US adults aged 60 years or older. BMJ open 8(4):e020533. https://doi:10.1136/bmjopen-2017-020533 Sasaki N, Carpenter DO (2022) Associations between Metal Exposures and Cognitive Function in American Older Adults. International journal of environmental research and public health 19(4). https://doi:10.3390/ijerph19042327 Yang W, Vuong AM, Xie C, Dietrich KN, Karagas MR, Lanphear BP, Braun JM, Yolton K, Chen A (2020) Maternal cadmium exposure and neurobehavior in children: The HOME study. Environmental research 186:109583. https://doi:10.1016/j.envres.2020.109583 Kim Y, Ha EH, Park H, Ha M, Kim Y, Hong YC, Kim EJ, Kim BN (2013) Prenatal lead and cadmium co-exposure and infant neurodevelopment at 6 months of age: the Mothers and Children's Environmental Health (MOCEH) study. Neurotoxicology 35:15-22. https://doi:10.1016/j.neuro.2012.11.006 Afifi OK, Embaby AS (2016). Histological Study on the Protective Role of Ascorbic Acid on Cadmium Induced Cerebral Cortical Neurotoxicity in Adult Male Albino Rats. Journal of microscopy and ultrastructure 4(1):36-45. https://doi:10.1016/j.jmau.2015.10.001 Xu Y, Hong H, Lin X, Tong T, Zhang J, He H, Yang L, Mao G, Hao R, Deng P, Yu Z, Pi H, Cheng Y, Zhou Z (2023) Chronic cadmium exposure induces Parkinson-like syndrome by eliciting sphingolipid disturbance and neuroinflammation in the midbrain of C57BL/6J mice. Environmental pollution (Barking, Essex : 1987) 337:122606. https://doi:10.1016/j.envpol.2023.122606 Yıldız MO, Çelik H, Caglayan C, Genç A, Doğan T, Satıcı E (2022) Neuroprotective effects of carvacrol against cadmium-induced neurotoxicity in rats: role of oxidative stress, inflammation and apoptosis. Metabolic brain disease 37(4):1259-69. https://doi:10.1007/s11011-022-00945-2 Namgyal D, Ali S, Hussain MD, Kazi M, Ahmad A, Sarwat M (2021) Curcumin Ameliorates the Cd-Induced Anxiety-like Behavior in Mice by Regulating Oxidative Stress and Neuro-Inflammatory Proteins in the Prefrontal Cortex Region of the Brain. Antioxidants (Basel, Switzerland) 10(11). https://doi:10.3390/antiox10111710 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3841618","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265793406,"identity":"998964f1-da4b-4ec9-a4f2-f7e351f06383","order_by":0,"name":"Jing Luo","email":"","orcid":"","institution":"Jiangsu College of Nursing","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Luo","suffix":""},{"id":265793407,"identity":"d4e189ec-23f1-44a3-986d-fc3602d708d0","order_by":1,"name":"Song Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACPmYIzQ/Ehg8SKmoIa2GDapFsYGAwNnhw5hgRWhgQWswkH7YwE6GFnffwh487aiX42Zu3VSQ2sDHwt3cnEHAYX5rkzDPHJSR7jpXdSNwhwyBx5uwGAlp4zJh5247VGdzIMbuReIaNwUAil6AW489ALRIgLQWJbcxEaTGQ5m2rAWthIFaLmeTMtgMgvxRLJJw5xkPQL/z8Z4w/fGyrA4XYxo8/Kmrk+Nt78WuBgsNwFg8xykGgjliFo2AUjIJRMBIBAAN/QblIARMUAAAAAElFTkSuQmCC","orcid":"","institution":"The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Song","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2024-01-07 06:29:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3841618/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3841618/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49384502,"identity":"85e581d2-efe1-4d2f-905b-2962806f17f3","added_by":"auto","created_at":"2024-01-09 19:46:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37486,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of the study participants.\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3841618/v1/b03796d08b3b8e8397844678.png"},{"id":49386387,"identity":"795ef52b-a99d-4cd6-b10f-4988ed975013","added_by":"auto","created_at":"2024-01-09 19:54:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":14560,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of blood cadmium levels.\u003c/p\u003e","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3841618/v1/18a88a5ecacfa666698c4ce6.png"},{"id":49384500,"identity":"e53c1b41-d975-4b39-b1fb-a0c1f1f17d0c","added_by":"auto","created_at":"2024-01-09 19:46:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":63737,"visible":true,"origin":"","legend":"\u003cp\u003eRestricted cubic spline curve for the association between blood cadmium and serum neurofilament light chain levels. The solid line represents the fitting curve; the dashed line represents the confidence interval.\u003c/p\u003e","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3841618/v1/0fa1711f73d921fe808266b7.png"},{"id":51555500,"identity":"53ffd5d6-3eef-4b4d-a285-4e1ebc7cefef","added_by":"auto","created_at":"2024-02-23 15:52:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":510062,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3841618/v1/9e68db73-7d8c-4f99-bf21-6a8cb297507c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The association between cadmium exposure and axonal injury biomarker, serum neurofilament light chain levels in US adults","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCadmium is a heavy metal and widely present in food, water, air, and tobacco due to industrial and agricultural activities [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Cadmium cannot be degraded in the natural environment and has high mobility, bioaccumulation, and toxicity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Animal studies have indicated that cadmium can cross the blood-brain barrier [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and induced neuronal swelling, degeneration, and death via oxidative stress, inflammation, autophagy, and apoptosis pathways [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Some epidemiological studies have shown that long-term, even low levels of cadmium exposure are closely associated with neurological diseases, including multiple sclerosis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], ischemic stroke [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and cognitive decline [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Additionally, higher cadmium exposure is associated with increased risk of Alzheimer's disease mortality [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, several studies show there is no relationship between cadmium exposure and cognitive function [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Notably, a latest nested case-control study from a prospective European cohort suggests a negative association between blood cadmium and Parkinson's disease risk [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In view of the inconsistent evidence, more evidence is needed to explore the potential effects of cadmium on nerve cells.\u003c/p\u003e \u003cp\u003eNeurofilaments are neuron-specific type IV intermediate filament heteropolymers composed of light, medium, and heavy chains [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Neurofilaments are synthesized in the neuronal perikaryon and are integrated into the axonal cytoskeleton [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In physiological conditions, neurofilaments are primarily cleared by the proteasomes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and autophagic lysosomes [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, after neuro-axonal damage, neurofilaments are released into cerebrospinal fluid and blood in turn [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Among these neurofilaments, neurofilament light chain (NfL) can self-assemble and constitute the backbone of nerve fibers, and has a small molecular weight and high solubility, and has thus been proposed as a putative biomarker of neuro-axonal injury [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Nowadays, NfL levels has been extensively validated as a sensitive diagnostic biomarker in several neurological disorders, including multiple system atrophy, multiple sclerosis [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], Alzheimer\u0026rsquo;s disease [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], and stroke [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. NfL levels can also predict disease progression and therapeutic effects in some neurologic conditions [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. To date, seldom study investigates the association between cadmium exposure and NfL levels in the general population.\u003c/p\u003e \u003cp\u003eIn the present study, we aim to determine the potential association between blood cadmium and NfL levels in a large population-based survey of US adults. This study may provide a new idea for the early prevention and mechanism exploration of neurodegenerative diseases.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Population\u003c/h2\u003e \u003cp\u003eThe National Health and Nutritional Health Survey (NHANES) is an ongoing cross-sectional study that assesses the nutritional and health status of the general civilians in the United States every two years. To obtain a representative sample, NHANES program uses the multi-stage stratified design with oversampling of the non-Hispanic Asians, Hispanics, non-Hispanic blacks, older adults, and low-income individuals. Detailed information about the NHANES has been reported in other study [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The protocol of NHANES is approved by the Centers for Disease Control and Prevention Research Ethics Review Board and documented signed consents are obtained from all participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Blood Cadmium\u003c/h2\u003e \u003cp\u003eOne-half sample from participants aged 12 years and older are eligible. Whole blood cadmium concentrations are detected using inductively coupled plasma mass spectrometry (PerkinElmer ELAN DRC II, Norwalk, CT) after appropriate sample collection and dilution steps. Random duplicate testing is performed on 2.0% of all samples. The limit of detection (LOD) for blood cadmium is 0.1\u0026micro;g/L, which is defined as three times the standard deviation at zero analyte concentration. For data below the LOD, an imputed value is equal to the LOD/\u0026radic;2, and 137 participants have values below the LOD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Serum Neurofilament Light Chain\u003c/h2\u003e \u003cp\u003eIn the 2013\u0026ndash;2014 cycle of NHANES, serum NfL levels are detected using a highly sensitive immunoassay developed by Siemens Healthineers. Its principle is the use of acridinium ester chemiluminescence and paramagnetic particles. All the measurement steps are performed on the automated Attelica immunoassay system. The lower limit of quantification (LLOQ) and the upper limit of quantification (ULOQ) of serum NfL is 3.9pg/mL and 500pg/mL, respectively. The LLOQ is determined by replicate testing of low concentration samples (n\u0026thinsp;=\u0026thinsp;44) and defined as the coefficient of variation (CV)\u0026thinsp;\u0026le;\u0026thinsp;20%. For data below the LLOQ or above the ULOQ, an imputed value is equal to the LLOQ/\u0026radic;2 or ULOQ\u0026times;\u0026radic;2, respectively. 22 participants have values below the LLOQ. No participants have values above ULOQ.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Other variables\u003c/h2\u003e \u003cp\u003eParticipants\u0026rsquo; self-reported information includes age (years), gender (men and women), race (Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, and other races), education level (the highest grade), smoking status, alcohol drinking status, and medical history. In the present study, education level is classified as less than high school grade, high school grade, and college graduate or above grade. Smokers are defined as those who have smoked at least 100 cigarettes in life. Alcohol drinkers are defined as those who have consumed alcohol at least 12 times per year. Body mass index (BMI) is calculated as weight in kilograms divided by height in meters squared, and classified as normal (\u0026lt;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (25 to 30 kg/m\u003csup\u003e2\u003c/sup\u003e), and obesity (\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e). Diabetes is defined as someone who met one of the following items: 1) fasting plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;126 mg/dL; 2) hemoglobin A1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5%; 3) self-reported physician diagnosis of diabetes or current taking anti-diabetic drugs. Cardiovascular disease (CVD) is defined as participants who are self-reported physician diagnosis of either congestive heart failure, coronary heart disease, angina pectoris, heart attack, or stroke.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical Analysis\u003c/h2\u003e \u003cp\u003eAll analyses are performed using Stata version 15.1 (Stata Corporation, College Station, TX, USA). Given the multi-stage design of NHANES, appropriate weight and sampling unit variables are designated according to the NHANES analytic guidelines. Qualitative variables are expressed by frequency distributions. Continuous variables are expressed by medians and inter-quartile range (IQR). General characteristics and serum NfL according to blood cadmium are evaluated using the chi-square test for categorical variables and linear regression for continuous variables. Linear regression models are fitted to explore the potential relationship between blood cadmium and serum NfL levels. The selection of covariates is based on previous studies. The first model is a crude model without any adjustment. The second model adjusts for age, sex, and race. The third model further adjusts for educational level, BMI, smoking status, alcohol drinking status, diabetes, and CVD. Linear trends and interaction effects are tested using blood cadmium as continuous variable in logistic regression models. The restricted cubic spline (RCS) model is applied to explore the potential dose-effect relationship between blood cadmium and serum NfL levels. A two-tailed value of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 is considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eWe exclude participants without data on blood cadmium and serum NfL, leaving 1,040 participants with a median (IQR) age of 47 (35\u0026ndash;60) years included in the following analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe histogram shows a non-normal distribution of blood cadmium levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The median (IQR) blood cadmium levels are 0.30 (0.18\u0026ndash;0.63) \u0026micro;g/L. Compared with participants in the lowest quintile of blood cadmium levels, those in the highest quartile are more likely to be elderly, female, non-Hispanic Black, smokers, and CVD patients, to have a lower degree of education, BMI, and serum NfL levels (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eBlood cadmium levels, \u0026micro;g/L\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ1 (0.05\u0026ndash;0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ2 (0.19\u0026ndash;0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ3 (0.31\u0026ndash;0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ4 (\u0026ge;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of subjects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e281 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253 (24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e253 (24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e253 (24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197 (70.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144 (56.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (38.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e130 (51.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109 (43.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e155 (61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e123 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167 (59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114 (45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99 (39.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139 (54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e154 (60.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e133 (52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace/Ethnicity, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMexican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43 (17.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 (41.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97 (38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62 (24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79 (31.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e167 (59.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156 (61.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160 (63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106 (41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75 (29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102 (40.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75 (30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125 (44.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (34.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoker, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115 (45.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e207 (81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol drinker, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206 (76.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e166 (71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167 (74.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e174 (76.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43 (17.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVD, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum NfL (pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.8 (6.9, 14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.0 (8.0, 18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.6 (9.1, 21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.1 (8.8, 20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe find a positive association between blood cadmium and serum NfL levels (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In the crude model (model 1), compared with participants in quartile 1, blood cadmium levels in quintile 4 is positively associated with serum NfL levels (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.62, 95%CI: 1.05, 6.18, \u003cem\u003ep\u003c/em\u003e for trend\u0026thinsp;=\u0026thinsp;0.001). This association persisted after adjustment for age, sex, and race (model 2, \u003cem\u003ep\u003c/em\u003e for trend\u0026thinsp;=\u0026thinsp;0.006) and even after further adjustment for education level, BMI, smoking status, alcohol drinking status, diabetes, and CVD (model 3, \u003cem\u003ep\u003c/em\u003e for trend\u0026thinsp;=\u0026thinsp;0.014).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of blood cadmium with serum neurofilament light chain levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuartile 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuartile 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.18 (-0.54, 4.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70 (-1.51, 2.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59 (-1.24, 2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuartile 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.90 (1.14, 12.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.60 (-0.68, 9.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.93 (-0.02, 9.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuartile 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.15 (1.81, 6.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.62 (1.05, 6.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.35 (0.41, 6.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eModel 1 crude model without any adjustment; model 2 adjusted for age, gender, and race; model 3 adjusted for all covariates in model 2 plus education level, BMI, smoking status, alcohol drinking status, diabetes, and cardiovascular diseases.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe RCS analysis show a potential linearity dose-effect relationship between blood cadmium and serum NfL levels (chi2\u0026thinsp;=\u0026thinsp;2.07, \u003cem\u003ep\u003c/em\u003e for non-linearity\u0026thinsp;=\u0026thinsp;0.15). When blood cadmium exceeds 0.7\u0026micro;g/L, there is a significant positive relationship between blood cadmium and serum NfL levels; however, the strength of this correlation seems to reach a plateau beyond this concentration (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOur study shows an interaction between age and blood cadmium levels (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.013). The results of stratified analysis by age show a significant positive relationship between blood cadmium and serum NfL levels only in individuals aged 50 to 75 years old (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). No significant interactions are found between blood cadmium levels and sex (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.596), race (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.779), education levels (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.934), BMI (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.291), smoking status (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.246), alcohol drinking status (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.280), diabetes (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.978), and CVD (\u003cem\u003ep\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.811).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of blood cadmium with serum neurofilament light chain levels stratified by age\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026minus;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuartile 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuartile 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuartile 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQuartile 4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for trend\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e \u003cp\u003e-0.17 (-2.93, 2.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.36 (-2.86, 5.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.04 (-4.58, 6.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.610\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;75 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026minus;\" colname=\"c3\"\u003e \u003cp\u003e2.72 (-2.19, 7.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.04 (3.44, 16.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.00 (2.25, 15.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eWe investigate the potential association between blood cadmium and serum NfL levels in a large representative population-based survey of US individuals using the data from the 2013\u0026ndash;2014 cycle of NHANES. Our study shows a positive relationship between blood cadmium and serum NfL levels. This association still exist after adjusting potential confounding factors, including age, sex, race, education level, BMI, smoking status, alcohol drinking status, diabetes, and CVD.\u003c/p\u003e \u003cp\u003eAs far as we known, only one published study explores the correlation between blood cadmium and serum NfL levels. The Beaver Dam Offspring Study (1,516 midlife participants) show that a doubling in baseline cadmium level is associated with a 0.2% (95% CI: 0.0, 0.3) higher increase per year in NfL concentrations [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Additionally, many studies have shown that cadmium exposure is toxic to the nervous system. Studies using NHANES data show that increased blood cadmium is associated with worse cognitive function in adults aged 60 years or older [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Similarly, a study conducted in Chinese adults aged 65 or older also report that higher cadmium exposure is associated with greater cognitive decline [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, the Health Outcomes and Measures of the Environment study, which measure maternal urinary cadmium concentrations at 26 weeks of gestation and assess cognitive function of children at ages 1, 2, 3, 4, 5, and 8 years, its result show no significant association between maternal cadmium exposure and cognitive function of children [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The Mothers and Children's Environmental Health study shows that prenatal cadmium levels during either early or late pregnancy period show no relationship with neurodevelopment at 6 months of age [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The above findings suggest that the potential effects of cadmium exposure on the nervous system may be influenced by age, which is closely related to cumulative exposure of cadmium. In the present study, we find an interaction between age and blood cadmium, and the stratified analysis shows a significant positive relationship between blood cadmium and serum NfL levels is limited to individuals aged 50 to 75 years.\u003c/p\u003e \u003cp\u003eOur study indicates a linearity dose-effect relationship between blood cadmium and serum NfL levels, and the potential threshold dose of blood cadmium associated neuro-axonal injury is 0.7 \u0026micro;g/L. However, when the blood cadmium concentration continued to increase, the strength of its association with serum NfL levels do not increase. In the present study, the subjects are the general population rather than occupationally exposed people, and median blood cadmium concentrations are at a low level, thus the neurological effects of higher doses of cadmium exposure cannot be ascertained.\u003c/p\u003e \u003cp\u003eIn an animal study, transmission electron microscopy shows degenerative changes in myelinated fibers in cadmium intervention groups, with swollen axons, irregular outlines, disordered arrangement of neurofilaments, swelling of many mitochondria, and destruction of cartridges [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Although the exact molecular mechanism has not been fully elucidated, the toxic effects of cadmium on nerve cells may rely on inflammation, oxidative stress, sphingolipid disturbance [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], mitochondrial damage, interference with neurotransmitter transmission, and induction of cell autophagy and apoptosis[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Many chemicals with anti-inflammatory and antioxidant properties can protect against cadmium-induced neurotoxicity [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study has several strengths. Firstly, this study is based on a representative sample, which allows for avoidance of selection bias and extrapolation of the results to the general population. Secondly, according to the dose-effect relationship identified in this study, the potential threshold of nerve cell damage induced by cadmium exposure can be further explored. Thirdly, after adjusting for potential confounding factors, the result remains robust. Finally, subgroup analysis provides clue to identify potential high-risk individuals. Meanwhile, several limitations exist in our study. Firstly, the study is cross-sectional design and the causal relationship cannot be ascertained. Secondly, the range of blood cadmium concentrations of this study population is in the low range, thus the neurological effects of higher cadmium exposure (e.g., occupational exposure) could not be determined. Finally, blood cadmium should not be equivalent to levels in nerve cells because the affinity for cadmium varies between tissues and the effect of cadmium on nerves may be tissue-specific.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn this large representative population-based survey of US individuals, we find a positive linear association between blood cadmium and serum NfL levels, and the potential threshold dose of blood cadmium is 0.7 \u0026micro;g/L. These findings need to be further confirmed in well-designed prospective cohort and toxicological studies. This study may provide a novel idea for the primary prevention of neurodegenerative diseases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThanks to all participants who collected data and making the NHANES datasets available on the website.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.L designed the study. S.L and J.L performed the statistical analysis, drafted the manuscript, revised the manuscript, and supervised the study. Both authors contributed to the final submitted version and agree to be responsible for all the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets can be found in online repositories (https://wwwn.cdc.gov/nchs/nhanes/). This study was available from corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of\u0026nbsp;the United States National Center for Health Statistics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from the parents.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWang M, Chen Z, Song W, Hong D, Huang L, Li Y (2021) A review on Cadmium Exposure in the Population and Intervention Strategies Against Cadmium Toxicity. Bulletin of environmental contamination and toxicology 106(1):65-74. https://doi:10.1007/s00128-020-03088-1\u003c/li\u003e\n \u003cli\u003eBuha A, Đukić-Ćosić D, Ćurčić M, Bulat Z, Antonijević B, Moulis JM, Goumenou M, Wallace D (2020) Emerging Links between Cadmium Exposure and Insulin Resistance: Human, Animal, and Cell Study Data. Toxics 8(3). https://doi:10.3390/toxics8030063\u003c/li\u003e\n \u003cli\u003eZhang T, Xu Z, Wen L, Lei D, Li S, Wang J, Huang J, Wang N, Durkan C, Liao X, Wang G (2021) Cadmium-induced dysfunction of the blood-brain barrier depends on ROS-mediated inhibition of PTPase activity in zebrafish. Journal of hazardous materials 412:125198. https://doi:10.1016/j.jhazmat.2021.125198\u003c/li\u003e\n \u003cli\u003eLi CX, Talukder M, Xu YR, Zhu SY, Zhao YX, Li JL (2023) Cadmium aggravates the blood-brain barrier disruption via inhibition of the Wnt7A/\u0026beta;-catenin signaling axis. Environmental pollution (Barking, Essex : 1987 324:121400. https://10.1016/j.envpol.2023.121400\u003c/li\u003e\n \u003cli\u003eWang T, Wang Q, Song R, Zhang Y, Zhang K, Yuan Y, Bian J, Liu X, Gu J, Liu Z (2015) Autophagy Plays a Cytoprotective Role During Cadmium-Induced Oxidative Damage in Primary Neuronal Cultures. Biological trace element research 168(2):481-9. https://doi:10.1007/s12011-015-0390-8\u003c/li\u003e\n \u003cli\u003ePhuagkhaopong S, Ospondpant D, Kasemsuk T, Sibmooh N, Soodvilai S, Power C, Vivithanaporn P (2017) Cadmium-induced IL-6 and IL-8 expression and release from astrocytes are mediated by MAPK and NF-\u0026kappa;B pathways. Neurotoxicology 60:82-91. https://doi:10.1016/j.neuro.2017.03.001\u003c/li\u003e\n \u003cli\u003eWang T, Zhu Q, Cao B, Cai Y, Wen S, Bian J, Zou H, Song R, Gu J, Liu X, Liu Z, Yuan Y (2022) Ca(2+) transfer via the ER-mitochondria tethering complex in neuronal cells contribute to cadmium-induced autophagy. Cell biology and toxicology 38(3):469-85. https://doi:10.1007/s10565-021-09623-y\u003c/li\u003e\n \u003cli\u003eTalukder M, Bi SS, Lv MW, Ge J, Zhang C, Li JL (2023) Involvement of the heat shock response (HSR) regulatory pathway in cadmium-elicited cerebral damage. Environmental science and pollution research international 30(48):106648-59. https://doi:10.1007/s11356-023-29880-0\u003c/li\u003e\n \u003cli\u003eSarihi S, Niknam M, Mahjour S, Hosseini-Bensenjan M, Moazzen F, Soltanabadi S, Akbari H (2021) Toxic heavy metal concentrations in multiple sclerosis patients: A systematic review and meta-analysis. EXCLI journal 20:1571-84. https://doi:10.17179/excli2021-3484\u003c/li\u003e\n \u003cli\u003eBorn\u0026eacute; Y, Fagerberg B, Persson M, \u0026Ouml;stling G, S\u0026ouml;derholm M, Hedblad B, Sallsten G, Barregard L, Engstr\u0026ouml;m G (2017) Cadmium, Carotid Atherosclerosis, and Incidence of Ischemic Stroke. Journal of the American Heart Association 6(12). https://doi:10.1161/jaha.117.006415\u003c/li\u003e\n \u003cli\u003eLiu H, Su L, Chen X, Wang S, Cheng Y, Lin S, Ding L, Liu J, Chen C, Unverzagt FW, Hake AM, Jin Y, Gao S (2021) Higher blood cadmium level is associated with greater cognitive decline in rural Chinese adults aged 65 or older. The Science of the total environment 756:144072. https://doi:10.1016/j.scitotenv.2020.144072\u003c/li\u003e\n \u003cli\u003eWang X, Xiao P, Wang R, Luo C, Zhang Z, Yu S, Wu Q, Li Y, Zhang Y, Zhang H, Zhao X (2022) Relationships between urinary metals concentrations and cognitive performance among U.S. older people in NHANES 2011-2014. Frontiers in public health 10:985127. https://doi:10.3389/fpubh.2022.985127\u003c/li\u003e\n \u003cli\u003eLu K, Liu T, Wu X, Zhong J, Ou Z, Wu W (2023) Association between serum iron, blood lead, cadmium, mercury, selenium, manganese and low cognitive performance in old adults from National Health and Nutrition Examination Survey (NHANES): a cross-sectional study. The British journal of nutrition 130(10):1743-53. https://doi:10.1017/s0007114523000740\u003c/li\u003e\n \u003cli\u003eGustin K, Tofail F, Vahter M, Kippler M (2018) Cadmium exposure and cognitive abilities and behavior at 10 years of age: A prospective cohort study. Environment international 113:259-68. https://doi:10.1016/j.envint.2018.02.020\u003c/li\u003e\n \u003cli\u003eMin JY, Min KB (2016) Blood cadmium levels and Alzheimer\u0026apos;s disease mortality risk in older US adults. Environmental health : a global access science source 15(1):69. https://doi:10.1186/s12940-016-0155-7\u003c/li\u003e\n \u003cli\u003ePeng Q, Bakulski KM, Nan B, Park SK (2017) Cadmium and Alzheimer\u0026apos;s disease mortality in U.S. adults: Updated evidence with a urinary biomarker and extended follow-up time. Environmental research 157:44-51. https://doi:10.1016/j.envres.2017.05.011\u003c/li\u003e\n \u003cli\u003eChen S, Shen R, Shen J, Lyu L, Wei T (2023) Association of blood cadmium with all-cause and cause-specific mortality in patients with hypertension. Frontiers in public health 11:1106732. https://doi:10.3389/fpubh.2023.1106732\u003c/li\u003e\n \u003cli\u003eNordberg M, Winblad B, Basun H (2000) Cadmium concentration in blood in an elderly urban population. Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine 13(4):311-7. https://doi:10.1023/a:1009268123320\u003c/li\u003e\n \u003cli\u003ePark JH, Lee DW, Park KS, Joung H (2014) Serum trace metal levels in Alzheimer\u0026apos;s disease and normal control groups. American journal of Alzheimer\u0026apos;s disease and other dementias 29(1):76-83. https://doi:10.1177/1533317513506778\u003c/li\u003e\n \u003cli\u003eLi K, Li A, Mei Y, Zhao J, Zhou Q, Li Y, Yang M, Xu Q (2023) Trace elements and Alzheimer dementia in population-based studies: A bibliometric and meta-analysis. Environmental pollution (Barking, Essex : 1987 318:120782. https://doi:10.1016/j.envpol.2022.120782\u003c/li\u003e\n \u003cli\u003eZhao Y, Ray A, Broberg K, Kippler M, Lill CM, Vineis P, Katzke VA, Rodriguez-Barranco M, Chirlaque MD, Guevara M, G\u0026oacute;mez JH, Hansen J, Panico S, Middleton LT, Masala G, Pala V, Vinagre-Aragon A, Zibetti M, Vermeulen R, Peters S (2023) Prediagnostic Blood Metal Levels and the Risk of Parkinson\u0026apos;s Disease: A Large European Prospective Cohort. Movement disorders : official journal of the Movement Disorder Society. https://doi:10.1002/mds.29602\u003c/li\u003e\n \u003cli\u003eYuan A, Rao MV, Veeranna, Nixon RA (2017). Neurofilaments and Neurofilament Proteins in Health and Disease. Cold Spring Harbor perspectives in biology 9(4). https://doi:10.1101/cshperspect.a018309\u003c/li\u003e\n \u003cli\u003eJacomy H, Zhu Q, Couillard-Despr\u0026eacute;s S, Beaulieu JM, Julien JP (1999) Disruption of type IV intermediate filament network in mice lacking the neurofilament medium and heavy subunits. Journal of neurochemistry 73(3):972-84. https://doi:10.1046/j.1471-4159.1999.0730972.x\u003c/li\u003e\n \u003cli\u003ePark JY, Jang SY, Shin YK, Suh DJ, Park HT (2013) Calcium-dependent proteasome activation is required for axonal neurofilament degradation. Neural regeneration research 8(36):3401-9. https://doi:10.3969/j.issn.1673-5374.2013.36.005\u003c/li\u003e\n \u003cli\u003eRao MV, Darji S, Stavrides PH, Goulbourne CN, Kumar A, Yang DS, Yoo L, Peddy J, Lee JH, Yuan A, Nixon RA (2023) Autophagy is a novel pathway for neurofilament protein degradation in vivo. Autophagy 19(4):1277-92. https://doi:10.1080/15548627.2022.2124500\u003c/li\u003e\n \u003cli\u003eKhalil M, Teunissen CE, Otto M, Piehl F, Sormani MP, Gattringer T, Barro C, Kappos L, Comabella M, Fazekas F, Petzold A, Blennow K, Zetterberg H, Kuhle J (2018) Neurofilaments as biomarkers in neurological disorders. Nature reviews Neurology14(10):577-89. https://doi:10.1038/s41582-018-0058-z\u003c/li\u003e\n \u003cli\u003eBacioglu M, Maia LF, Preische O, Schelle J, Apel A, Kaeser SA, Schweighauser M, Eninger T, Lambert M, Pilotto A, Shimshek DR, Neumann U, Kahle PJ, Staufenbiel M, Neumann M, Maetzler W, Kuhle J, Jucker M (2016) Neurofilament Light Chain in Blood and CSF as Marker of Disease Progression in Mouse Models and in Neurodegenerative Diseases. Neuron 91(1):56-66. https://doi:10.1016/j.neuron.2016.05.018\u003c/li\u003e\n \u003cli\u003eAlnemeh-Al Ali H, Griveau A, Artzner F, Dupont A, Lautram N, Jourdain MA, Eyer J (2022) Investigation on the self-assembly of the NFL-TBS.40-63 peptide and its interaction with gold nanoparticles as a delivery agent for glioblastoma. International journal of pharmaceutics: X 4:100128. https://doi:10.1016/j.ijpx.2022.100128\u003c/li\u003e\n \u003cli\u003eChelban V, Nikram E, Perez-Soriano A, Wilke C, Foubert-Samier A, Vijiaratnam N, Guo T, Jabbari E, Olufodun S, Gonzalez M, Senkevich K, Laurens B, P\u0026eacute;ran P, Rascol O, Le Traon AP, Todd EG, Costantini AA, Alikhwan S, Tariq A, Ng BL, Mu\u0026ntilde;oz E, Painous C, Compta Y, Junque C, Segura B, Zhelcheska K, Wellington H, Sch\u0026ouml;ls L, Jaunmuktane Z, Kobylecki C, Church A, Hu MTM, Rowe JB, Leigh PN, Massey L, Burn DJ, Pavese N, Foltynie T, Pchelina S, Wood N, Heslegrave AJ, Zetterberg H, Bocchetta M, Rohrer JD, Marti MJ, Synofzik M, Morris HR, Meissner WG, Houlden H (2022) Neurofilament light levels predict clinical progression and death in multiple system atrophy. Brain : a journal of neurology 145(12):4398-408. https://doi:10.1093/brain/awac253\u003c/li\u003e\n \u003cli\u003eChatterjee P, Pedrini S, Doecke JD, Thota R, Villemagne VL, Dor\u0026eacute; V, Singh AK, Wang P, Rainey-Smith S, Fowler C, Taddei K, Sohrabi HR, Molloy MP, Ames D, Maruff P, Rowe CC, Masters CL, Martins RN (2023) Plasma A\u0026beta;42/40 ratio, p-tau181, GFAP, and NfL across the Alzheimer\u0026apos;s disease continuum: A cross-sectional and longitudinal study in the AIBL cohort. Alzheimer\u0026apos;s \u0026amp; dementia : the journal of the Alzheimer\u0026apos;s Association 19(4):1117-34. https://doi:10.1002/alz.12724\u003c/li\u003e\n \u003cli\u003eKorley FK, Goldstick J, Mastali M, Van Eyk JE, Barsan W, Meurer WJ, Sussman J, Falk H, Levine D (2019) Serum NfL (Neurofilament Light Chain) Levels and Incident Stroke in Adults With Diabetes Mellitus. Stroke 50(7):1669-75. https://doi:10.1161/strokeaha.119.024941\u003c/li\u003e\n \u003cli\u003eLin CH, Li CH, Yang KC, Lin FJ, Wu CC, Chieh JJ, Chiu MJ (2019) Blood NfL: A biomarker for disease severity and progression in Parkinson disease. Neurology 93(11):e1104-e11. https://doi:10.1212/wnl.0000000000008088.\u003c/li\u003e\n \u003cli\u003eHalloway S, Desai P, Beck T, Aggarwal N, Agarwal P, Evans D, Rajan KB, Project. CHaA (2022) Association of Neurofilament Light With the Development and Severity of Parkinson Disease. Neurology 98(22):e2185-e93. https://doi:10.1212/wnl.0000000000200338\u003c/li\u003e\n \u003cli\u003eBar-Or A, Thanei GA, Harp C, Bernasconi C, Bonati U, Cross AH, Fischer S, Gaetano L, Hauser SL, Hendricks R, Kappos L, Kuhle J, Leppert D, Model F, Sauter A, Koendgen H, Jia X, Herman AE (2023) Blood neurofilament light levels predict non-relapsing progression following anti-CD20 therapy in relapsing and primary progressive multiple sclerosis: findings from the ocrelizumab randomised, double-blind phase 3 clinical trials. EBioMedicine 93:104662. https://doi:10.1016/j.ebiom.2023.104662\u003c/li\u003e\n \u003cli\u003eLeroux A, Di J, Smirnova E, McGuffey EJ, Cao Q, Bayatmokhtari E, Tabacu L, Zipunnikov V, Urbanek JK, Crainiceanu C (2019) Organizing and analyzing the activity data in NHANES. Statistics in biosciences 11(2):262-87. https://doi:10.1007/s12561-018-09229-9\u003c/li\u003e\n \u003cli\u003eSchubert CR, Paulsen AJ, Pinto AA, Chappell RJ, Chen Y, Ferrucci L, Hancock LM, Cruickshanks KJ, Merten N (2023) Effect of Neurotoxin Exposure on Blood Biomarkers of Neurodegeneration and Alzheimer Disease. Alzheimer disease and associated disorders https://doi:10.1097/wad.0000000000000579\u003c/li\u003e\n \u003cli\u003eLi H, Wang Z, Fu Z, Yan M, Wu N, Wu H, Yin P (2018) Associations between blood cadmium levels and cognitive function in a cross-sectional study of US adults aged 60 years or older. BMJ open 8(4):e020533. https://doi:10.1136/bmjopen-2017-020533\u003c/li\u003e\n \u003cli\u003eSasaki N, Carpenter DO (2022) Associations between Metal Exposures and Cognitive Function in American Older Adults. International journal of environmental research and public health 19(4). https://doi:10.3390/ijerph19042327\u003c/li\u003e\n \u003cli\u003eYang W, Vuong AM, Xie C, Dietrich KN, Karagas MR, Lanphear BP, Braun JM, Yolton K, Chen A (2020) Maternal cadmium exposure and neurobehavior in children: The HOME study. Environmental research 186:109583. https://doi:10.1016/j.envres.2020.109583\u003c/li\u003e\n \u003cli\u003eKim Y, Ha EH, Park H, Ha M, Kim Y, Hong YC, Kim EJ, Kim BN (2013) Prenatal lead and cadmium co-exposure and infant neurodevelopment at 6 months of age: the Mothers and Children\u0026apos;s Environmental Health (MOCEH) study. Neurotoxicology 35:15-22. https://doi:10.1016/j.neuro.2012.11.006\u003c/li\u003e\n \u003cli\u003eAfifi OK, Embaby AS (2016). Histological Study on the Protective Role of Ascorbic Acid on Cadmium Induced Cerebral Cortical Neurotoxicity in Adult Male Albino Rats. Journal of microscopy and ultrastructure 4(1):36-45. https://doi:10.1016/j.jmau.2015.10.001\u003c/li\u003e\n \u003cli\u003eXu Y, Hong H, Lin X, Tong T, Zhang J, He H, Yang L, Mao G, Hao R, Deng P, Yu Z, Pi H, Cheng Y, Zhou Z (2023) Chronic cadmium exposure induces Parkinson-like syndrome by eliciting sphingolipid disturbance and neuroinflammation in the midbrain of C57BL/6J mice. Environmental pollution (Barking, Essex : 1987) 337:122606. https://doi:10.1016/j.envpol.2023.122606\u003c/li\u003e\n \u003cli\u003eYıldız MO, \u0026Ccedil;elik H, Caglayan C, Gen\u0026ccedil; A, Doğan T, Satıcı E (2022) Neuroprotective effects of carvacrol against cadmium-induced neurotoxicity in rats: role of oxidative stress, inflammation and apoptosis. Metabolic brain disease 37(4):1259-69. https://doi:10.1007/s11011-022-00945-2\u003c/li\u003e\n \u003cli\u003eNamgyal D, Ali S, Hussain MD, Kazi M, Ahmad A, Sarwat M (2021) Curcumin Ameliorates the Cd-Induced Anxiety-like Behavior in Mice by Regulating Oxidative Stress and Neuro-Inflammatory Proteins in the Prefrontal Cortex Region of the Brain. Antioxidants (Basel, Switzerland) 10(11). https://doi:10.3390/antiox10111710\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"cadmium, neurofilament, axonal injury, neurodegenerative diseases","lastPublishedDoi":"10.21203/rs.3.rs-3841618/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3841618/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and Aims: \u003c/strong\u003eCadmium exposure has been shown a toxic effect on the nervous system, but little is known regarding the link between cadmium exposure and axonal injury. Therefore, we aim to investigate whether there is a relationship between blood cadmium and serum neurofilament light chain (NfL) levels in the general population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods and Results: \u003c/strong\u003eIn the National Health and Nutrition Examination Survey 2013–2014, 1,040 participants with a median (IQR) age of 47 (35–60) years are enrolled. Serum NfL levels are measured using a highly sensitive immunoassay. Whole blood cadmium concentrations are detected using inductively coupled plasma mass spectrometry. Linear regression and restricted cubic spline models are used to analyze the strength and shape of the relationship between blood cadmium and serum NfL levels. In full adjusted model, blood cadmium levels are positively associated with serum NfL levels (Q4 vs Q1, \u003cem\u003eβ\u003c/em\u003e = 3.35, 95%CI: 0.41, 6.30, \u003cem\u003ep\u003c/em\u003e for trend = 0.014). A potential linear positive dose-effect relationship is found between blood cadmium and serum NfL levels (\u003cem\u003ep\u003c/em\u003e for non-linearity = 0.15), and the potential threshold dose of blood cadmium is 0.7 µg/L. The stratified analysis shows a significant positive relationship between blood cadmium and serum NfL levels is limited to middle-aged and older adults.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThe present study suggests a positive association between blood cadmium and serum NfL levels in the general US population. This study is expected to provide new ideas for the primary prevention and mechanism exploration of neurodegenerative diseases.\u003c/p\u003e","manuscriptTitle":"The association between cadmium exposure and axonal injury biomarker, serum neurofilament light chain levels in US adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-09 19:46:42","doi":"10.21203/rs.3.rs-3841618/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4a43e715-5c42-4831-a860-4b75f5313493","owner":[],"postedDate":"January 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-02-23T15:51:59+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-09 19:46:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3841618","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3841618","identity":"rs-3841618","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}