Formaldehyde and Brain Disorders: A Meta-Analysis and Bioinformatics Approach (2024)

The publisher's final edited version of this article is available at Neurotox Res

Formaldehyde Exposure is Universal and Carcinogenic

Formaldehyde is ubiquitous in the environment and our bodies. In most organisms, including humans, formaldehyde is endogenously produced through amino acid and methanol metabolism, lipid peroxidation, demethylation of DNA, RNA, and histones (EFSA 2014; Swenberg et al. 2011) and is either consumed as an intermediate in the “one-carbon pool” (Neuberger 1981) or used for the biosynthesis of purines, thymidine, and some amino acids. It is reportedly kept at a concentration of approximately 80–100 μM in the blood (Casanova et al. 1988; Heck et al. 1985) with a delicate equilibrium maintained by endogenous metabolic pathways. Commercially, formaldehyde is indispensable for many products and processes that are important to the world’s economy (Tang et al. 2009). From its use in embalming to hair relaxation to the manufacture of plastics and composite wood products, the global formaldehyde production is rapidly growing and is projected to reach 36.6 million tons in 2026 (Bhisey 2026). Thus, chronic exogenous exposure to formaldehyde, a major public health concern, is known to cause nasopharyngeal cancer and myeloid leukemia in humans (IARC 2012). However, potential links between the exposure and brain cancers and other neural disorders are less understood.

Formaldehyde Has the Potential to Damage the Brain

Exposure to formaldehyde via inhalation is known to impair memory (Bach et al. 1990; Kilburn et al. 1987) and cognitive functions (Kilburn et al. 1985; Perna et al. 2001) in humans, to cause deficits in learning and memory (Qiang et al. 2014), neuronal damage (Sarsilmaz et al. 2007), and oxidative stress in the cerebellum (Songur et al. 2008) of experimental animals, and to induce misfolded neuronal tau and related proteins (Nie et al. 2007) in vitro. These formaldehyde-associated alterations and neurotoxicity have raised questions about its role in modulating diseases of the central nervous system (CNS), such as neurodegenerative disease (NDD) and brain tumor (BT).

Although the two are distinct pathological disorders, NDD and BT are suspected to share common mechanisms of genetic and molecular abnormalities (Du and Pertsemlidis 2011), indicating that the mechanisms of these seemingly dichotomous diseases may converge in the dysregulation of gene expression and at the post-translational level. For example, increased lipid peroxidation, a biomarker of oxidative stress, was found in animal models of Alzheimer’s disease (AD) (Pratico et al. 2001) and Huntington’s disease (Perez-De La Cruz et al. 2009), and in patients with Parkinson’s disease (PD) (Dexter et al. 1989) and brain cancer (Popov et al. 2003).

Formaldehyde Inhalation and Olfactory Function

A major route of exogenous exposure to formaldehyde in humans is via inhalation, where it could come in contact with and damage the olfactory bulb, an outgrowth of the forebrain specialized for the processing of signals that give rise to the sense of smell (Shepherd and Greer 1998). Repeated formaldehyde inhalation exposure impairs olfactory function in humans (Kilburn et al. 1985; Holmstrom and Wilhelmsson 1988; Hisamitsu et al. 2011; Edling et al. 1988), which has been linked to PD (Doty et al. 1988; Tissingh et al. 2001), amyotrophic lateral sclerosis (ALS) (Viguera et al. 2018), AD (McCaffrey et al. 2000; Morgan et al. 1995), and BT (Daniels et al. 2001). Given formaldehyde’s ability to damage the olfactory system that appears to be intimately tied to both NDD and brain cancer, here, we will focus on the effect of inhalation to formaldehyde on the brain in this study.

Formaldehyde Exposure and Brain Disorders

We previously reported the growing evidence that formaldehyde exposure may contribute to the risk of brain cancer (Zhang and Rana 2018a) and NDD (Zhang and Rana 2018b). A number of epidemiological studies conducted with professional workers, such as anatomists, pathologists, embalmers, and funeral home workers, and in industrial workers have analyzed the association between formaldehyde exposure and brain cancer, although the findings remain limited and inconsistent. In 2012, the International Agency for Research on Cancer (IARC) noted that despite several studies identifying statistically significant positive associations between exposure to formaldehyde and brain cancer, the results are inconsistent (IARC 2012). To the best of our knowledge, no authoritative entities have evaluated formaldehyde’s ability to cause NDD, though some studies have been suggestive.

Investigators in China have shown an association between mean endogenous levels of formaldehyde in normal, mild cognitive impairment, and AD patients (Tong et al. 2017). Other studies have reported the genesis of AD-like neuropathology in primates treated with methanol (Yang et al. 2014), a precursor of formaldehyde. The Western Pacific ALS-parkinsonism-dementia complex (ALS-PDC) disorder (Guam, Kii Peninsula, Honshu Island, Japan, and Papua, Indonesia on the island of New Guinea) is strongly associated with exposure to cycad seed genotoxins, namely methylazoxymethanol (the aglycone of cycasin) and beta-aminomethyl-L-alanine (L-BMAA), both of which are metabolized to formaldehyde (Spencer 2019; Spencer et al. 2012). Most recently, investigators in China reported that excess formaldehyde impaired memory in patients with mutations in formaldehyde metabolism enzyme ALDH2 and in the ALDH2 deficient mice (Ai et al. 2019).

To determine whether exogenous exposure to formaldehyde is associated with increased risk of NDD or brain cancer, we conducted a meta-analysis of all studies of formaldehyde-exposed workers. We then applied a bioinformatics analysis to identify candidate genes and pathways associated with both formaldehyde exposure and NDD/BT with the aim of investigating underlying mechanisms.

Meta-analysis Objective

Given formaldehyde’s documented neurotoxicity in vivo (Sarsilmaz et al. 2007; Lu et al. 2008; Aslan et al. 2006; Tulpule and Dringen 2011) and in vitro (Nie et al. 2007; Tulpule et al. 2012; Song et al. 2010; Tang et al. 2013), we hypothesized formaldehyde plays a role in NDD and possibly brain cancer. We investigated this process by carefully reviewing the epidemiological evidence and performing a meta-analysis to examine the association between human exposure to high levels of formaldehyde and NDD and brain cancer. Meta-analysis provides a method for reviewing the current literature on a topic of interest, identifying heterogeneity in the literature and its possible sources, and evaluating major aspects of causal inference including the magnitude of the association, dose-response, and the possible presence and extent of bias and confounding.

Previously, two meta-analyses have reported mixed findings on formaldehyde exposure and brain cancer (Blair et al. 1990; Bosetti et al. 2008) and no meta-analysis has been conducted to date on formaldehyde-associated NDD. Our meta-analysis on brain tumors differs from previous reports by including a number of updated cohort studies (Beane Freeman et al. 2013; Coggon et al. 2014; Hauptmann et al. 2009; Meyers et al. 2013), multiple new analyses of heterogeneity and bias, and a focus on groups with higher formaldehyde exposure if available by employing an a priori hypothesis targeting exposure magnitude (A Priori Approach and Exposure Categories).

Searching and Identifying Relevant Human Studies

The literature search was conducted according to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA, Moher D, Liberati A, Tetzlaff J, Altman DG, Group P 2009). The screening process and results are shown in Fig. 1. We conducted a systematic electronic literature review using PubMed in July 2018, which was updated in May 2019. We performed electronic searches of online databases (PubMed, Web of Science Core Collection, Biosis Previews, Embase, Google Scholar, ToxNet, Chinese National Knowledge Infrastructure, CNKI, Wanfang Data, and Chongqing VIP Information, CQVIP) using the search terms, inclusion, and exclusion criteria outlined in Supplementary Section A1.

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Fig. 1

Study selection process for meta-analyses using PRISMA guidelines

Selection of NDD Studies

We identified 394 studies from PubMed, 32 studies from ToxNet, and 5 studies from scanning bibliographies. After 28 duplicates were removed, 403 studies were primarily screened. Of these studies, 371 were excluded because they were reviews, correspondence, animal, mechanistic or para-occupational studies, or did not include the relevant exposure or outcome of interest (Fig. 1). When the final 32 studies were identified, 13 studies were further excluded for lacking clear formaldehyde exposure data or relative risk (RR) estimates. Finally, 19 NDD studies were selected, among which there were nine (6 + 3, detailed in Exposure Assessment and Estimate) studies on ALS, six on PD, one on AD, and three on multiple sclerosis (MS).

Selection of Brain Tumor Studies

Following thorough searches from multiple resources and excluding 44 duplicates, we screened a total of 1,297 articles by title and abstract (Fig. 1). We excluded 1,252 articles that used animal or mechanistic study designs, lacked the exposure or outcome of interest, had para-occupational exposure, or were correspondence or a review, leaving 45 articles for full text review. Of these studies, 12 studies with 67,819 participants were eligible for inclusion in the meta-analysis. Table 1 also summarizes these selected brain cancer studies. Because brain cancer is a diverse cancer that may be defined differently among studies, the ICD codes from these studies have been reported in Supplementary Table 1.

There were five studies of professional workers and seven studies of industrial workers (Table 1). Two studies were case-control design (Coggon et al. 2014; Hauptmann et al. 2009), and ten were cohort studies. Six studies were conducted in the USA, one study was in Canada, two studies were in the UK, one study was in Italy, and two studies were in China.

Statistical Methods

We calculated overall summary estimates and weights of the studies using both the fixed effects inverse variance method (Greenland 1998) and the random effects method (DerSimonian and Laird 1986). Heterogeneity was evaluated using the general variance-based method (Petitti 1994). If heterogeneity was present, the random effects model was used. One benefit of the random effects model is the ability to incorporate between study variance into the summary variance estimate and confidence intervals (CI), which may help prevent artificially narrow CIs resulting from use of the fixed effects model in the presence of between-study heterogeneity (Petitti 1994). We evaluated publication bias through funnel plots, Egger’s test, and Begg’s test (Begg and Mazumdar 1994; Egger et al. 1997). All meta-analysis and statistical analysis were conducted with Stata IC 15.1 (StataCorp 2017) and Microsoft Excel 2013 (Corporation 2013).

Formaldehyde Exposure Increases Risk of NDD

Major ALS Findings

The findings of our meta-analysis of NDD are presented in Table 2. As discussed above in Exposure Assessment and Estimate, only six of nine studies of ALS had formaldehyde exposure assessments (Fang et al. 2009; Peters et al. 2017; Roberts et al. 2016; Seals et al. 2017; Weisskopf et al. 2009; Pinkerton et al. 2013). When examining the most highly exposed groups, we found a meta-relative risk (meta-RR) of 1.78 with a 95% CI of 1.20 to 2.65 (Fig. 2a). While there was somewhat high heterogeneity, we note that large majority of studies (5 of 6) have RRs that are greater than 1.0.

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Fig. 2

Forest plot of ALS meta-analysis using random effects model a and funnel plot of ALS studies b. Forest plot of brain tumor meta-analysis using random effects model c and funnel plot of brain tumor d

Table 2

Meta-analysis results of amyotrophic lateral sclerosis (ALS) and other neurodegenerative diseases (NDD)

		Fixed effects model			Random effects modela			Heterogeneity
Analysis	N	Meta-RR	CIL	CIU	Meta-RR	CIL	CIU	X2	P
Amyotrophic lateral sclerosis (ALS)
Main-highest peak exposure	6	1.37	1.21	1.56	1.78	1.20	2.65	19.08	< 0.01
Ever exposureb	6	1.25	1.17	1.33	1.17	0.93	1.47	20.59	< 0.01
Including studies with proxy exposurec	11	1.10	0.98	1.23	1.18	0.65	2.17	158.33	< 0.01
Exclude one ALS studyd
Fang et al. (2009)	5	1.36	1.20	1.55	1.73	1.14	2.60	17.96	< 0.01
Weisskopf et al. (2009)	5	1.30	1.14	1.48	1.31	1.08	1.59	4.96	0.29
Pinkerton et al. (2013)	5	1.37	1.21	1.56	1.89	1.24	2.88	18.77	< 0.01
Roberts et al. (2016)	5	1.36	1.19	1.54	1.65	1.12	2.45	16.10	< 0.01
Peters et al. (2017)	5	1.43	1.23	1.65	2.24	1.09	4.61	17.98	< 0.01
Seals et al. (2017)	5	1.52	1.22	1.90	2.21	1.05	4.66	17.75	< 0.01
Other NDD subtypes
Parkinson’s diseaseb	9	1.23	1.10	1.38	1.70	1.17	2.48	46.49	< 0.01
Multiple sclerosisb	5	0.54	0.43	0.68	0.80	0.37	1.73	35.33	< 0.01
Total NDD in EE studies
Plastics	5	4.06	2.63	6.25	3.64	1.84	7.19	7.44	0.11
Wood workersb	8	1.19	1.02	1.38	1.10	0.86	1.42	9.35	0.23
Textile workersb	12	0.73	0.65	0.83	0.77	0.44	1.34	158.22	< 0.01

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CI confidence interval, EE exposure estimated, NDD neurodegenerative disease, N number of studies, meta-RR meta-analysis relative risk

^aRandom effects model was used when X² heterogeneity statistic > degrees of freedom (number of studies minus 1)

^bNot reported in Roberts et al. 2016 and was calculated by the authors

^cIncludes additional papers where formaldehyde exposure was not clearly defined but included professions with known exposure (plastics manufacturing, woodwork, and textile work)

^dOne study excluded at a time.

The funnel plot revealed some evidence of asymmetry consistent with publication bias (Fig. 2b), although the number of studies is small and there was no evidence of bias in the in Egger’s (p = 0.204) or Begg’s tests (p = 0.188).

ALS Sensitivity Analysis

Examining “ever exposure” revealed a lower meta-RR of 1.17 (95% CI 0.93–1.47), in comparison with our a priori “high exposures” (meta-RR = 1.78, 95% CI 1.20–2.65; Table 2). Therefore, there was a 61% increase in meta-RR, suggesting the presence of an exposure-response relationship (Fig. 3a).

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Fig. 3

Meta-relative risk of ALS mortality a and brain cancer mortality b by level of formaldehyde exposure using random effects model. The relative risks are indicated by the black lines in the middle, and the 95% confidence intervals are indicated by the upper and lower vertical black lines

To determine the effects of adding the three ALS studies that assessed exposure by proxy, we included additional studies of individuals with known exposure to plastics, woodwork, and textiles (Chiò et al. 1991; Deapen and Henderson 1986; Gunnarsson et al. 1991) and found the risk of ALS was lower (meta-RR = 1.18, 95% CI 0.65–2.17; Table 2). When we excluded any one individual study included in our main analysis (meta-RR = 1.78), the meta-RRs of ALS in the sensitivity analysis fluctuated but did not change substantially (range 1.30 to 2.24).

Increased Meta-relative Risk of Brain Cancer

Next, we performed the meta-analysis and stratified sensitivity analyses on brain cancer; the results are reported in Table 3, and the forest plot is displayed in Fig. 2c. The meta-RR for all studies combined was 1.71 (95% CI 1.07–2.73). Figure 2 d shows the funnel plot for publication bias. Among all studies, there was no evidence of asymmetry consistent with obvious publication bias. Egger’s (p = 0.076) and Begg’s (p = 0.337) tests similarly did not show evidence of publication bias.

We conducted a series of sensitivity analyses below to evaluate the impact of including or excluding each individual study or other possible studies. In general, results were similar across all analyses, demonstrating the robustness of our findings.

Strengths and Limitations of Meta-Analyses

Bioinformatics Approach

To deepen our understanding of the epidemiologic association between formaldehyde exposure and brain cancer and NDDs, we used gene-association data to identify (1) formaldehyde-associated genes, (2) the genes associated with the diseases of interest (ALS, AD, PD, MS, BT), (3) overlapped common genes from formaldehyde and NDD/BT, and (4) inferred formaldehyde–gene–NDD/BT associations and their associated pathways. Lastly, (5) we overlapped the genes and pathways identified from the inferred chemical–gene/pathway–disease associations to create an integrated network of candidate genes and pathways that could have played a role in mediating the associations observed in the human epidemiological studies (Fig. 4a).

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Fig. 4

Summary of bioinformatics analysis approach. a. Definitions of numbers are explained in “Bioinformatics Approach” in the text. Close-up of the integrative network depicted in Supplementary Fig. 2, which contains the genes and pathways that were overlapping between two or more NDDs of interest b. The color of the nodes depicts the respective combinations of the different disease types. The turquoise gene SOD2 (in the middle) and the gray pathway Vitamin B₁₂ Metabolism (at the bottom), for example, are both observed to be affected in AD, ALS, brain tumor, PD, as well as in oNDD after formaldehyde exposure b

Results of Bioinformatics Approach

Genes and Pathways Involved in Formaldehyde-Induced Brain Disorders

We analyzed the results of the bioinformatics screen to determine concordance with known mechanisms of NDD/BT, including oxidative stress, abnormal protein aggregation, and inflammation, and to identify novel pathways that may be dysregulated.

Mitochondrial Dysfunction and Vitamin B₁₂ Metabolism

Mitochondrial dysfunction is another common mechanism in NDD pathology, manifesting as decreased energy production, excitotoxicity, impaired calcium buffering, and increased mitochondrial membrane permeability (Beal 1998). Deficiency in vitamin B₁₂, a pathway overlapping ALS, AD, PD, and MS is known to cause mitochondrial toxicity as a result of citric acid cycle inhibition (Toyoshima et al. 1996) and predicts worsening mobility in PD patients (Christine et al. 2018).

Low vitamin B₁₂ levels inhibit the enzyme methionine synthase that catalyzes formation of methionine from hom*ocysteine, leading to increased hom*ocysteine (Fig. 5a). Hyperhom*ocystemia can cause the dysfunction or death of cells in the nervous system by impairing DNA repair mechanisms and inducing oxidative stress (Kruman et al. 2000, 2002; Obeid and Herrmann 2006). This mechanism was demonstrated in PC12 cells as a model for neuronal secretion and differentiation (Wagner et al. 1993), where formaldehyde exposure induced oxidative stress and inhibited hydrogen sulfide production, contributing to neurotoxicity induced by hom*ocysteine (Tang et al. 2013). In human epidemiological studies, hyperhom*ocystemia has been strongly linked to development of dementia, AD (Seshadri et al. 2002), and cognitive decline in PD patients.

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Fig. 5

Intersection of folate driven one-carbon pool, formaldehyde cycle, and vitamin B₁₂ pathway a. Potential mechanisms underlying formaldehyde-induced neurodegenerative disease and brain cancer b

Formaldehyde and Olfactory Impairment

Although it is commonly postulated that most inhaled airborne formaldehyde is detoxified upon contact with the mucosal surfaces of the mouth and nose, formaldehyde encounters and could damage the olfactory bulb (Formaldehyde Inhalation and Olfactory Function). Repeated formaldehyde inhalation exposure impairs olfactory function in humans (Kilburn et al. 1985; Holmstrom and Wilhelmsson 1988; Hisamitsu et al. 2011; Edling et al. 1988) and in rats. (Zhang et al. 2014) Our recently published study shows that formaldehyde inhalation inhibits the growth of hematopoietic stem and progenitor cells in the olfactory mucosa of exposed mice in vivo and ex vivo (Zhao et al. 2020b). Exposure to formaldehyde also decreased glutamate, GABA, and nitric oxide synthase expression (Li et al. 2010) and reduced expression of synaptosomal-associated protein 25 (SNAP25) in the olfactory bulb, as well as mature and immature olfactory sensory neuron markers, olfactory marker protein (OMP), and Tuj-1 in rats (Zhang et al. 2014). Decreases in SNAP25 are predictive of neuron loss and decreased synaptogenesis (Washbourne et al. 2002).

Olfactory impairment has been linked to PD (Doty et al. 1988, 1995; Tissingh et al. 2001), ALS (Viguera et al. 2018), and AD (McCaffrey et al. 2000; Morgan et al. 1995). In particular, AD specific neuropathology has been detected in the olfactory epithelium (Yamagishi et al. 1994; Lee et al. 1993; Arnold et al. 1998), with phosphorylated tau and neurofilament proteins present in the axons and dendrites of olfactory neurons (Talamo et al. 1989; Reyes et al. 1993). AD patients also have altered olfactory evoked response potentials (Warner et al. 1986). Reduced olfactory performance has also been reported in patients with brain tumors (Daniels et al. 2001).

Interestingly, the mammalian olfactory epithelium has a unique capacity to replace olfactory receptor neurons throughout life (Graziadei and Graziadei 1979; Schwob 2002) using olfactory ensheathing cells (OECs) that wrap olfactory axons and support their continued regeneration (Su et al. 2013). When activated, these OECs have the ability to travel from the olfactory bulb in the peripheral nervous system (PNS) to primary tumor sites in the CNS and along the invasive tumor border where they can selectively target glioblastoma stem-like cells (GBC/GSC), which are thought to initiate glioblastomas (Carvalho et al. 2019).

Supplement_11.20.20_LP

We are grateful to Profs. Marc Weisskopf from Harvard University, Christopher Chang, and Martyn Smith at UC Berkeley for their helpful discussions. Special thanks to Yun Zhao for creating Supplementary Fig. 3 depicting formaldehyde-genes in the ALS pathway, and for procurement and careful translation of the Chinese papers.

Funding This project was partially supported by the UC Berkeley Superfund Research Program (SRP, P42ES004705) to LZ and CS, who are project leaders. IR and LR are SRP trainees at UC Berkeley.

Compliance with Ethical Standards

Conflict of Interest The authors declare that they have no competing interests.

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s12640-020-00320-y.

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