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Formaldehyde and Brain Disorders: A Meta-Analysis and Bioinformatics Approach

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Abstract

While there is significant investigation and investment in brain and neurodegenerative disease research, current understanding of the etiologies of illnesses like Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and brain cancer remains limited. Environmental exposure to the pollutant formaldehyde, an emerging neurotoxin widely used in industry, is suspected to play a critical role in mediating these disorders, although findings are limited and inconsistent. Focusing on highly exposed groups, we performed a meta-analysis of human epidemiological studies of formaldehyde and neurodegenerative disease (N =  19) or brain tumors (N = 12). To assess the biological plausibility of observed associations, we then conducted a bioinformatics analysis using WikiPathways and the Comparative Toxicogenomics Database and identified candidate genes and pathways that may be related to these interactions. We reported the meta-relative risk (meta-RR) of ALS following high exposures to formaldehyde was increased by 78% (meta-RR = 1.78, 95% confidence interval, CI 1.20–2.65). Similarly, the meta-RR for brain cancer was increased by 71% (meta-RR = 1.71; 95% CI 1.07–2.73) among highly exposed individuals. Multiple sensitivity analyses did not reveal sources of heterogeneity or bias. Our bioinformatics analysis revealed that the oxidative stress genes superoxide dismutase (SOD1, SOD2) and the pro-inflammatory marker tumor necrosis factor (TNF) were identified as the top relevant genes, and the folate metabolism, vitamin B12 metabolism, and the ALS pathways were highly affected by formaldehyde and related to the most brain diseases of interest. Further inquiry revealed the two metabolic pathways are also intimately tied with the formaldehyde cycle. Overall, our bioinformatics analysis supports the link of formaldehyde exposure to ALS or brain tumor reported from our meta-analysis. This new multifactorial approach enabled us to both interrogate the robustness of the epidemiological data and identify genes and pathways that may be involved in these interactions, ultimately lending strong evidence and potential biological plausibility for the association between formaldehyde exposure and brain disease.

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Data Availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Abbreviations

5MTHF:

5-Methyltetrahydrofolate

AD:

Alzheimer’s disease

ALS:

Amyotrophic lateral sclerosis

ALS-PDC:

ALS-parkinsonism-dementia complex

BT:

Brain tumor

CNS:

Central nervous system

CNKI:

Chinese National Knowledge Infrastructure

CQVIP:

Chongqing VIP Information

CTD:

Comparative Toxicogenomics Database

CI:

Confidence interval

CST3:

Cytostatin

GSEA:

Gene set enrichment analysis

GBC/GSC:

Glioblastoma stem-like cells

IARC:

International Agency for Research on Cancer

L-BMAA:

Beta-aminomethyl-L-alanine

Meta-RR:

Meta-relative risk

MAPT:

Mictorubule associated protein tau

MS:

Multiple sclerosis

NDD:

Neurodegenerative disease

NOS:

Newcastle-Ottawa Scale

OMP:

Olfactory marker protein

OSM:

Oncostatin M

oNDD:

Other neurodegenerative disease

PD:

Parkinson’s disease

ppm:

Parts per million

PNS:

Peripheral nervous system

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

RR:

Relative risk

SOD2:

Superoxide dismutase 2

SNAP25:

Synaptosomal-associated protein 25

THF:

Tetrahydrofolate

TNF:

Tumor necrosis factor

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Acknowledgments

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.

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Authors and Affiliations

  1. Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA

    Iemaan Rana, Linda Rieswijk & Luoping Zhang

  2. Institute of Data Science, Maastricht University, Maastricht, Netherlands

    Linda Rieswijk

  3. Division of Epidemiology and Biostatistics, School of Public Health, University of California Berkeley, Berkeley, CA, USA

    Craig Steinmaus

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  1. Iemaan Rana
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  2. Linda Rieswijk
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  4. Luoping Zhang
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IR conducted the literature search, analyzed, and interpreted the meta-analysis data in collaboration with CS and LZ. LR performed the bioinformatics analysis. LZ conceived and designed the study. IR and LZ contributed to most of the discussion. All authors read and approved the final manuscript.

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Correspondence to Luoping Zhang.

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Rana, I., Rieswijk, L., Steinmaus, C. et al. Formaldehyde and Brain Disorders: A Meta-Analysis and Bioinformatics Approach. Neurotox Res 39, 924–948 (2021). https://doi.org/10.1007/s12640-020-00320-y

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