Aldehyde exposure induces axonal damage through inflammatory response

doi:10.21203/rs.3.rs-4712842/v1

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Aldehyde exposure induces axonal damage through inflammatory response

https://doi.org/10.21203/rs.3.rs-4712842/v1

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The potential neurological effects of low-concentration aldehydes in the human body remain largely unexplored. To address this, we conducted a study involving 331 participants from the National Health and Nutrition Examination Survey (NHANES) 2013–2014. Utilizing logistic regression model, bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) regression models, we examined the combined impact of serum aldehydes on the overall risk of axonal damage. Through bioinformatics and mediation analyses, we unraveled the mechanisms underlying aldehyde-induced axonal damage. In our logistic regression model, we found associations between isopentanaldehyde and hexanaldehyde with neurofilament light chain (NfL) levels (fourth vs. first quartile). BKMR analysis demonstrated a significant overall effect of aldehydes on NfL levels when all chemicals were at or above the 55th percentile, compared to the 50th percentile. Additionally, WQS regression analysis revealed a positive association between the WQS index and NfL concentrations(OR = 2.46, 95%CI: 1.27–4.73). In terms of pathways and hub genes, inflammatory response and TNF emerged as the top-ranking enrichment pathway and hub gene. Notably, mediation analysis indicated that WBC, MONO, and NEUT played significant roles in mediating the relationships between isopentanaldehyde and NfL concentrations. Collectively, the current evidence suggests that aldehyde exposure may elevate the risk of axonal damage through inflammatory response.

Biological sciences/Computational biology and bioinformatics

Earth and environmental sciences/Environmental sciences

Health sciences/Neurology

Aldehyde

axonal damage

neurofilament light chain

inflammatory response

BKMR

WQS

Axonal damage is a prominent characteristic of various neurological disorders such as multiple sclerosis, traumatic brain injury, and Alzheimer's disease^1–5. Axons are long, slender projections of nerve cells that transmit electrical impulses to other cells in the nervous system.The severity and location of the damage determine the range of symptoms, which includes cognitive impairment, motor and sensory deficits, and paralysis. The underlying mechanisms of axonal damage are complex and involve a range of factors, such as inflammation, oxidative stress, and mitochondrial dysfunction^6–8. Toxic exposures can lead to axonal damage and contribute to the development of neurological disorders. For instance, exposure to lead, mercury, or arsenic can lead to axonal degeneration, resulting in cognitive and motor deficits^9–12. Similarly, exposure to solvents, such as toluene or styrene, has been linked to axonal damage and peripheral neuropathy^13–14. Therefore, identifying and reducing exposure to toxic substances is essential for preventing axonal damage in various neurological disorders.

Aldehydes are a class of organic compounds that contain a -CHO group.Reactive aldehyde exposure can originate from external sources, such as industrial power plants, vehicle emissions, alcoholic drinks, tobacco products like cigarettes and e-cigarettes, flavors, cosmetics, and paint lacquers^15–16.The burning of tobacco products is a significant contributor to aldehyde exposure. Propanaldehyde, heptanaldehyde, and hexanaldehyde are some of the saturated aldehydes present in tobacco smoke¹⁷.Aside from external sources, aldehydes can also be produced internally through lipid peroxidation, metabolic ascorbic acid or carbohydrate autooxidation, as well as metabolic activation via amine oxidase, cytochrome P-450, or myeloperoxidase¹⁸. Exposure to aldehydes can be detrimental to human health and has been associated with various adverse effects, such as cardiopulmonary function¹⁹ and allergic reactions²⁰.Formaldehyde has been proven to induce cognitive impairment and neurodegenerative disorders²¹. Despite this, only limited research has been conducted on the correlation between aldehydes and axonal damage,especially on the population.

Neurofilament light chain (NfL) is a protein that is primarily expressed in the axons of neurons²². When axonal damage occurs, NfL is released into the cerebrospinal fluid (CSF) and can also be detected in blood samples²². As a result, NfL has emerged as a promising biomarker for the diagnosis and monitoring of axonal damage in various neurological disorders, including multiple sclerosis, Alzheimer's disease, and traumatic brain injury^23–25.In this study, the serum NfL was chosen as a metric to evaluate axonal damage.

The aim of this study was to investigate the individual and combined relationship between serum aldehydes and axonal damage risk in 331 subjects using three statistical models. This research focused not only on the correlation between aldehydes and axonal damage risk, but also on exploring the mechanism via bioinformatics analysis and mediation analysis.

2.1. Study population

The National Health and Nutrition Examination Survey (NHANES) is a cross-sectional, nationwide study that has been conducted nationwide since the 1960s to evaluate the health and nutrition status of both children and adults in the United States.The NHANES collects data from representative samples of Americans through interviews, examinations, and laboratory tests designed with multilevel probability sampling. We obtained data from the year in which aldehyde test data were included. In total, 10,175 participants were in the NHANES from 2013 to 2014. After excluding participants without serum NfL data, the sample size decreased to 2085. Further exclusions of participants without serum aldehyde data resulted in a final sample size of 331. Details regarding the data integration process are available in Supplementary Figure S1.

2.2. Measurement of serum NfL

Siemens Healthineers has developed a highly sensitive NfL immunoassay that utilizes acridinium ester (AE) chemiluminescence and paramagnetic particles, and can be run on an existing, high-throughput, automated platform (Attelica). The assay involves incubating the sample with AE-labeled antibodies, which bind to the NfL antigen, followed by the addition of capture antibody-coated paramagnetic particles (PMP) to form antigen-AE-labeled antibody-PMP complexes. The unbound AE-labeled antibodies are then removed, and chemiluminescence is initiated by the addition of acid and base, with light emission being measured. All these steps are carried out using the fully automated Attelica immunoassay system.The assay has a lower limit of quantification (LLOQ) of 3.9 pg/mL and an upper limit of quantification (ULOQ) of 500 pg/mL. If the analytic results for an analyte fall below the LLOQ, an imputed fill value equal to the LLOQ divided by the square root of two is entered in the analyte results field. Conversely, if the analytic results for an analyte exceed the ULOQ, an imputed fill value equal to the ULOQ multiplied by the square root of two is entered in the analyte results field.

2.3. Assessment of aldehyde exposure

An automated analytical method using SPME GC and HRMS with isotope-dilution techniques was utilized to detect aldehyde levels in serum samples from a group of NHANES participants aged 12 years and older in 2013–2014. In total, 12 aldehydes were detected, but only 6 (benzaldehyde, isopentanaldehyde, propanaldehyde, butyraldehyde, hexanaldehyde, and heptanaldehyde) were included in the analysis due to being detectable in more than 75% of participants²⁶. The procedure used to detect these aldehydes has been previously published²⁷.

2.4. Outcomes and covariation assessment

Based on previous research²⁸, NfL concentrations were divided into two categories: low (≤ 25.5 pg/mL) and high (> 25.5 pg/mL), where the high group indicated severe axonal damage. Covariates including age, sex, and ethnicity, which might affect the association between aldehyde concentration and NfL concentrations, were obtained through interviews and medical examinations. Since the sample size of the high NfL group was only 40, only three covariates were considered. A complete blood count, including white blood cell count(WBC), lymphocytes(LYMPH), monocytes(MONO), and neutrophils(NEUT), was conducted using a Beckman Coulter DXH 800 instrument with the Beckman Coulter method.

2.5. Statistical analysis

To ensure accurate representation of the civilian population of the United States, the survey procedure was adjusted for the complex survey design and included sample weights for this random subsample. The use of sampling weights was recommended by the National Center for Health Statistics (NCHS) to account for the complex NHANES survey design. Wilcoxon rank sum test and Chi-square tests were employed to compare continuous variables and categorical variables, respectively. Since continuous variables exhibited a non-normal distribution, they were presented as median and interquartile range (IQR), whereas categorical variables were presented as frequency and percentage. The association between serum aldehydes and NfL concentrations was analyzed using survey-weighted multiple logistic regression analysis, with two separate models constructed for each aldehyde. Model 1 was unadjusted, while Model 2 was adjusted for demographic factors (age, sex, and race). The serum aldehydes concentrations were categorized into four quartiles (Q1, Q2, Q3, and Q4) as categorical variables. Additionally, the Bayesian kernel machine regression (BKMR) model (R package “bkmr”) and weighted quantile sum (WQS) regression model (R package “gWQS”)were utilized to explore the association between mixed aldehydes and NfL concentrations, as described in detail previously²⁹.The serum aldehydes concentrations were ln-transformed in the BKMR and WQS model analysis. All statistical analyses were conducted using R software (version 3.9.0). P<0.05 was considered statistically significant.

2.6. Functional enrichment analysis and hub gene identification

To investigate the mechanism underlying aldehyde-induced axonal damage, we identified 410 axonal damage-related genes in the GeneCard database(https://www.genecards.org) and 3876 genes regulated by aldehydes (including hexanaldehyde, butyraldehyde, and benzaldehyde, which were found in the CTD databasE(http://ctdbase.org), while the remaining aldehydes were not). Among these, 99 genes were shared. We then performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses using the Metascape website³⁰. To predict potential interactions among the 99 genes, we utilized the Search Tool for the Retrieval of Interacting Genes database (Version 11.5, http://string-db.org), with a combined score of > 0.9 being considered significant. For visualization purposes, Cytoscape 3.9.0 was used. Additionally, we utilized the cytoHubba application³¹ to explore the hub genes within the obtained protein-protein interaction network.To visualize the results of aldehyde-related diseases in the CTD database, air bubble diagrams were used.

2.7. Mediation analyses

From the initial sample size of 331 individuals, one participant was excluded due to the absence of complete blood count data, resulting in a final cohort of 330 participants in the mediation analyses.A mediation model (R package “mediation”) was employed to estimate the potential mediating effects of inflammation parameters including WBC,LYMPH,MONO and NEUT on the relationship between hexanaldehyde, isopentanaldehyde and NfL concentrations. The quasi-Bayesian Monte Carlo method with 1000 simulations based on normal approximation was used for mediation analyses. The direct effect (DE) referred to the impact of hexanaldehyde and isopentanaldehyde exposure on NfL concentrations without a mediator, while the indirect effect (IE) referred to the impact of hexanaldehyde and isopentanaldehyde exposure on NfL concentrations through the mediator. The proportion of mediation was calculated by dividing the indirect effect by the total effect (TE).

3.1. Population characteristics

Table 1 presented an overview of the general characteristics of the study population. The analysis included a total of 331 participants, with 40 individuals exhibiting high NfL levels. Comparing the low NfL and high NfL groups, no significant differences were found in terms of gender or ethnicity. However, there was a significant difference in age between these two groups. Furthermore, the serum concentration of hexanaldehyde was notably higher in participants with high NfL levels compared to those in the low NfL group. The Spearman correlation analysis revealed a partially dense correlation pattern among certain aldehydes within the 331 subjects, as shown in Supplementary Figure S2. The Spearman correlation coefficients ranged from −0.06 to 0.54, indicating various degrees of correlation. Notably, a strong correlation was observed between exposure to butyraldehyde and propanaldehyde (ρ = 0.54), as well as between isopentanaldehyde and propanaldehyde (ρ = 0.54), as depicted in the heatmap.

Table 1 Characteristics of the overall target population according to NfL concentrations.

	Overall (n=331)	Low NfL (n=291)	High NfL (n=40)	p
Age	43.00 (33.00, 56.00)	42.00 (32.00, 55.00)	58.00 (40.14, 67.76)	0.002
Sex(%)				0.417
Male	159 (51.6)	137(50.4)	22(63.3)
Female	172(48.4)	154(49.6)	18(36.7)
Ethnicity(%)				0.789
White	130(60.3)	116(60.6)	14(57.3)
Asian	40 (5.2)	35(5.1)	5 (6.3)
Black	46(9.6)	40(9.7)	6(9.0)
Mexican	69 (15.0)	58(14.5)	11(19.6)
Other	46(9.9)	42(10.1)	4(7.8)
Benzaldehyde	1.28 (0.82, 1.76)	1.28 (0.80, 1.77)	1.32 (0.90, 1.69)	0.877
Butyraldehyde	0.54 (0.39, 0.70)	0.53 (0.39, 0.69)	0.60 (0.43, 0.78)	0.161
Heptanaldehyde	0.49 (0.43, 0.58)	0.49 (0.43, 0.58)	0.51 (0.44, 0.55)	0.647
Hexanaldehyde	2.10 (1.71, 2.62)	2.08 (1.70, 2.53)	2.59 (2.00, 2.87)	0.002
Isopentanaldehyde	0.43 (0.30, 0.68)	0.43 (0.29, 0.67)	0.49 (0.32, 1.15)	0.14
Propanaldehyde	1.93 (1.44, 2.48)	1.90 (1.40, 2.44)	2.30 (1.75, 2.80)	0.064

Notes: Data are expressed as median (interquartile range), or n (percentage),n was unweighted sample size, percentage was weighted.

Wilcoxon rank sum test and Chi-square tests were used for comparisons among groups. Sampling design complexity is taken into account in all analyses.

Statistical significance (p<0.05).

Abbreviations: NfL ,serum neurofilament light chain.

3.2. Multivariable logistic regression model to assess the association between aldehydes and NfL concentrations

Multivariable logistic regression was utilized to evaluate the impact of individual aldehydes on NfL concentrations. Hexanaldehyde and isopentanaldehyde displayed significant associations with NfL concentrations in the top two quartiles in the unadjusted model. After adjusting for all covariates, hexanaldehyde and isopentanaldehyde continued to display significant associations with NfL concentrations in the upper two quartiles. The other aldehydes did not show any significant association with NfL concentrations (Table 2).

Table 2

Multivariable associations of selected aldehydes with NfL concentrations in US population 2013–2014.
	Q1	Q2	Q3	Q4	p for trend
Benzaldehyde
Model 1	Reference	1.22(0.32,4.69)	2.17(0.58,8.14)	0.75(0.18,3.19)	0.805
Model 2	Reference	1.39(0.24,7.94)	2.45(0.35,17.15)	0.85(0.13,5.80)	0.987
Butyraldehyde
Model 1	Reference	0.38(0.05,2.60)	1.03(0.15,6.89)	2.41(0.57,10.12)	0.229
Model 2	Reference	0.30(0.02,4.19)	1.07(0.09,13.27)	2.00(0.37,10.89)	0.164
Heptanaldehyde
Model 1	Reference	0.73(0.34,1.55)	1.68(0.45,6.19)	0.97(0.25,3.82)	0.774
Model 2	Reference	0.64(0.22,1.80)	1.50(0.34,6.64)	1.15(0.31,4.24)	0.569
Hexanaldehyde
Model 1	Reference	2.93(0.46,18.60)	3.60(1.12,11.57)	7.54(2.96,19.21)	< 0.001
Model 2	Reference	2.98(0.28,32.20)	3.45(0.81,14.80)	8.31(3.09,22.34)	< 0.001
Isopentanaldehyde
Model 1	Reference	4.41(1.48,13.14)	2.35(0.51,10.79)	4.15(1.66,10.35)	0.109
Model 2	Reference	3.47(1.01,11.95)	1.88(0.39,9.13)	5.04(1.63,15.64)	0.061
Propanaldehyde
Model 1	Reference	3.42(0.73,16.05)	4.27(0.89,20.38)	3.44(0.94,12.65)	0.080
Model 2	Reference	3.12(0.49,19.71)	4.65(0.68,31.52)	3.53(0.75,16.60)	0.060
Model 1: unadjusted
Model 2: adjusted for sex, age, ethnicity
Notes: Data were expressed as median (interquartile range).Sampling design complexity was taken into account in all analyses.
Statistical significance (p < 0.05).
Abbreviations: NfL ,serum neurofilament light chain;Q, quartile.

3.3. BKMR model to assess the association between aldehydes and NfL concentrations

The ln-transformed concentration of each aldehyde was considered as a continuous variable in our study. We applied the BKMR model to examine the combined impact of aldehyde exposures on binary outcomes. Figure 1.a illustrated the overall association between aldehyde mixtures and NfL concentrations.When the percentile of all aldehyde mixtures reached 55% or higher, it demonstrated a notable elevation in NfL concentrations, thereby underscoring a positive correlation between mixed aldehydes and NfL levels. Figure 1.b revealed that isopentanaldehyde and hexanaldehyde exhibited an increase in NfL concentrations when other aldehydes were maintained at median values. The posterior inclusion probabilities (PIP) derived from the BKMR model revealed that isopentanaldehyde had a PIP of 0.855, and hexanaldehyde had a PIP of 0.600,suggesting that isopentanaldehyde and hexanaldehyde made the most substantial contributions to the mixed exposure model (Supplementary Table S1). To further investigate the potential relationship between serum aldehydes, we generated bivariate cross-sections of the exposure-response function. Supplementary Figure S3 confirms that there was no evidence of interaction between any two types of aldehydes based on parallel exposure-response relationships. Consequently, We proceeded to assess the individual effect of each aldehyde by estimating univariate summaries of the change in NfL concentrations associated with a shift from the 25th percentile to the 75th percentile for a single aldehyde, while keeping all other aldehydes fixed at specific thresholds (25th, 50th, or 75th percentile). Our analysis revealed a significant positive effect for isopentanaldehyde and hexanaldehyde (Supplementary Figure S4).

3.4. WQS regression model to assess the association between aldehydes and NfL concentrations

The WQS index was statistically associated with NfL concentrations in the positive direction (OR = 2.46, 95%CI: 1.27–4.73) ,while no statistically significant association was observed in the negative direction (OR = 1.05, 95%CI: 0.70–2.04). Detailed findings from the adjusted models can be found in Table 3. Figure 2 presents the estimated weights of aldehydes for each WQS index. In the positive model, the top three aldehydes with the highest weights were butyraldehyde, isopentanaldehyde, and hexanaldehyde (weighted 0.47, 0.29, and 0.19, respectively). It is worth noting that butyraldehyde differed from the BKMR results, whereas isopentanaldehyde and hexanaldehyde were consistent with the BKMR findings..

Table 3

Association between WQS regression index and NfL concentrations in US population 2013–2014.
Variables	OR	95% CI of OR	p
Positive	2.46	1.27,4.73	0.008
Negative	1.05	0.70 ,2.04	0.514
Notes:Analysis was adjusted for sex, age, ethnicity.OR estimates represent the odds ratios of NfL concentrations when the WQS index was increased by one quartile.
Statistical significance (p < 0.05).
Abbreviations: NfL ,serum neurofilament light chain.OR: odds ratio; CI: confidence interval;

3.5. The results of functional enrichment analysis and the identification of hub genes in aldehyde-induced axonal damage

Figure 3.a illustrated an overlap between genes associated with aldehydes and those linked to axonal damage, comprising a total of 99 genes.The top five enrichment results were inflammatory response,cell activation,regulation of cell-cell adhesion,positive regulation of cell death,regulation of mononuclear cell migration and regulation of neuron death(Figure 3.b &c) . Moreover, Figure 3.d showed the top ten hub genes in aldehyde-induced axonal damage, including TNF, IL6, CCL2, CXCL10, CCL3, CCL5, CXCL8, CXCL1, IL13, and FOS.A considerable number of aldehyde-related diseases documented in the CTD database were found to be associated with axonal damage (Supplementary Figure S5, Figure S6, and Figure S7)

3.6. Mediation analyses results

Furthermore, we conducted mediation analyses to investigate whether inflammation parameters, including WBC, LYMPH, MONO, and NEUT, played a mediating role in the associations between isopentanaldehyde, hexanaldehyde, and NfL concentrations. The result indicated that WBC, MONO, and NEUT had significant mediation effects on the relationships between isopentanaldehyde and NfL concentrations, accounting for 20.12%, 16.79%, and 4.23% of the total effect, respectively (all P<0.05). However, no significant mediation effects were observed for WBC, LYMPH, MONO, and NEUT in the relationships between hexanaldehyde and NfL concentrations (all P>0.05). For more detailed information, please refer to Figure 4 and Supplementary Figure S8.

In this study, We conducted a comprehensive analysis using various statistical approaches to investigate the impact of six different aldehydes on axonal damage in the general population of the United States.The results revealed significant associations between hexanaldehyde and isopentanaldehyde with NfL concentrations, as indicated by multivariable logistic regression. Additionally, the BKMR model demonstrated a significant overall mixed exposure effect on NfL concentrations. Furthermore, the univariate exposure-response analysis showed a positive correlation between hexanaldehyde, isopentanaldehyde, and NfL concentrations. The WQS model identified the specific roles of butyraldehyde, isopentanaldehyde and hexanaldehyde in the development of axonal damage. To gain insights into the underlying mechanisms, we extensively utilized multiple databases and discovered that inflammatory response played a crucial role in this process, with TNF being identified as the top-ranked hub gene. Finally, mediation analysis confirmed the involvement of inflammation parameters in mediating the process of aldehyde-induced axonal damage. This study emphasized the significance of evaluating the collective effects of chemicals on health outcomes using diverse statistical methods and provides systematic evidence for the crucial role of inflammatory response in aldehyde-induced axonal damage.

The characteristics of the study population indicated a significant age difference between the low NfL and high NfL groups, while no difference was observed in terms of gender. These findings aligned with previous research, which consistently demonstrated that sex did not affect NfL levels in healthy populations³² and NfL levels naturally increased with age in individuals without underlying health conditions^33-35.

The traditional approach of using multiple logistic regression models has been commonly employed to investigate the health impacts of chemicals^36-37. However, this method falls short in accounting for mixed environmental exposure and the intricate nonlinear interactions involved^38-39. In recent years, the WQS and BKMR models have emerged as alternatives and have been extensively applied to explore the influence of chemical mixtures on human health^40-43. However,these two models possess its own strengths and weaknesses. The WQS regression model considers the overall burden of chemical exposures by employing weights derived through bootstrap sampling, which better reflects the complexities of real-life exposures. Nevertheless, a drawback of the WQS model is its inability to simultaneously assess the joint effects of chemicals with diverse directional effects⁴⁴. In contrast, the BKMR analysis enables the capture of exposure-response relationships while holding other chemicals at fixed levels, allowing for the detection of interactions between pairs of chemicals. However, the BKMR model's use of a kernel algorithm poses a limitation in terms of extrapolating exposure-response functions when estimating the effects of co-exposure patterns with both high and low chemical levels. Despite the differences arising from the characteristics of these three statistical models, their results consistently indicate a correlation between isopentanaldehyde, hexanaldehyde and NfL concentration, highlighting the significant role played by these two aldehydes in the development of axonal damage.

Currently, numerous studies have demonstrated the detrimental effects of aldehydes on the nervous system, with a particular focus on formaldehyde-induced damage and the exploration of its underlying mechanisms. Formaldehyde (FA) has been found to decrease the total counts of pyramidal neurons in the CA regions of the hippocampus when inhaled⁴⁵. Research on FA-exposed rats has also observed various associated symptoms, including lethargy, reduced motor activity, and loss of appetite^46-47. Another study revealed that FA induces ferroptosis in hippocampal neuronal cells by upregulating the Warburg effect⁴⁸. Furthermore, investigations using transgenic zebrafish lines demonstrated that glutaraldehyde reduces the width of the brain and spinal cord, as well as the myelination of Schwann cells and oligodendrocytes⁴⁹. However, it is worth noting that most of these studies have been conducted on animal models, with limited research available on humans. Since the mode and dosage of aldehyde exposure greatly differ between humans and animal experiments, and human exposure is usually low-level and chronic, distinct from the high-level and short-term exposure in animal studies, it is crucial to analyze human samples to explore the effects of aldehyde exposure on axonal damage. Additionally, while many studies have investigated the effects of individual aldehydes on neurotoxicity, there is a scarcity of research on the combined influence of multiple aldehydes. Given that real-life aldehyde exposure typically involves exposure to multiple aldehydes simultaneously, it is more realistic to utilize statistical models like WQS and BKMR to assess the overall impact of multiple aldehydes on axonal injury. The findings of both WQS and BKMR models in this study provide compelling evidence that multiple aldehydes contribute to an overall increase in blood NfL concentration, indicating the occurrence of axonal injury. These results further strengthened the conclusion that aldehyde exposure could induce neurotoxicity in humans.

Through comprehensive analysis of data from multiple databases and mediation analyses results of isopentanaldehyde , it was revealed that inflammatory response played a crucial role in the development of axonal damage caused by aldehyde exposure. Numerous studies have provided evidence of aldehydes triggering inflammatory responses. For instance, research has shown that aldehydes present in office dust can intensify the inflammatory effects on the upper airways⁵⁰. Formaldehyde, specifically, has been found to significantly increase tissue MDA levels and serum cytokine levels⁵¹. Moreover, formaldehyde could induce lung inflammation through a mechanism involving oxidant and antioxidant enzymes in lung tissue⁵². These studies collectively illustrated the ability of aldehydes to induce inflammatory responses in the body.Neurodegenerative diseases are widely recognized for the presence of localized brain cell inflammation and the infiltration of leukocytes from the peripheral blood⁵³. When activated, microglia release various inflammatory soluble factors, including superoxide, nitric oxide, TNF-α, and others⁵⁴. Microglial cells can also be activated by environmental factors such as rotenone (a pesticide), diesel exhaust particles or direct neuronal injury⁵⁵. It is important to note that transient elevation of inflammatory processes is a natural occurrence and does not result in neuronal cell death⁵⁶. However, persistent stimulation may lead to the prolonged production of cytokines, which can cause injury and death of neuronal cells. TNF has been identified as the highest-ranked hub gene, and there was substantial evidence linking formalin exposure to TNF-α upregulation^57-58. Additionally, elevated systemic levels of TNF-α have been associated with accelerated cognitive decline in participants with Alzheimer's disease⁵⁹, further indicating the significant role of TNF in the development of axonal damage.In contrast to isopentanaldehyde, inflammatory parameters did not play a mediating role in the relationships between hexanaldehyde and NfL concentrations ,which could be explained that hexanaldehyde could not exert a potent enough influence to trigger an inflammatory response in the body.

This study owned several strengths. Firstly, while the toxicity of aldehydes was well-known, the potential health impacts of low-concentration aldehydes in the human body have not been extensively investigated. This research sheded light on this previously unexplored area by demonstrating, through population data, that aldehyde exposure could lead to axonal damage via an inflammatory response. This finding provided valuable insights into the health effects of aldehyde exposure in humans.Secondly, this study was conformity with the principles of "Replacement, Reduction, and Refinement" of animal studies. By utilizing population data instead of relying solely on animal studies, we were able to reduce the need for animal experimentation and minimize potential harm to animals. This approach aligned with ethical considerations and advanced the field of toxicology research.

This study has several limitations that should be considered. Firstly, the design of this study was cross-sectional, which prevents us from establishing a causal relationship between serum aldehydes and axonal damage. Secondly, the small sample size in this study limited the number of covariates that could be included, potentially introducing bias. Lastly, incomplete analysis occurred due to missing data in the CTD database.

Ethics approval and consent to participate

The protocols of NHANES were approved by the institutional review board of the National Center for Health Statistics, CDC. Written informed consent was obtained from each participant before participation in this study.

Authors’ contributions

Lanling Lin participated in concept design, interpretation, drafting, critical revision and approval of the article.

Data availability

Data that support the findings of this study have been deposited in the National Health and Nutrition Examination Survey (NHANES) database (2013-2014). (https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?BeginYear=2013)

Statement

We confirm that all methods employed in the study adhere strictly to the guidelines set forth by the National Health and Nutrition Examination Survey (NHANES).

Acknowledgements

We thank the NHANES participants, staff and investigators. We sincerely acknowledge the National Center for Health Statistics that put people’s lives first.

Conflicts of Interest: There is no conflicts of interest.

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Aldehyde exposure induces axonal damage through inflammatory response

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Abstract

Figures

1. Introduction

2. Materials and methods

2.1. Study population

2.2. Measurement of serum NfL

2.3. Assessment of aldehyde exposure

2.4. Outcomes and covariation assessment

2.5. Statistical analysis

2.6. Functional enrichment analysis and hub gene identification

2.7. Mediation analyses

3. Results

3.1. Population characteristics

4. Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1