Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

A global perspective on the influence of environmental exposures on the nervous system


Economic transitions in the era of globalization warrant a fresh look at the neurological risks associated with environmental change. These are driven by industrial expansion, transfer and mobility of goods, climate change and population growth. In these contexts, risk of infectious and non-infectious diseases are shared across geographical boundaries. In low- and middle-income countries, the risk of environmentally mediated brain disease is augmented several fold by lack of infrastructure, poor health and safety regulations, and limited measures for environmental protection. Neurological disorders may occur as a result of direct exposure to chemical and/or non-chemical stressors, including but not limited to, ultrafine particulate matters. Individual susceptibilities to exposure-related diseases are modified by genetic, epigenetic and metagenomic factors. The existence of several uniquely exposed populations, including those in the areas surrounding the Niger Delta or north western Amazon oil operations; those working in poorly regulated environments, such as artisanal mining industries; or those, mostly in sub-Saharan Africa, relying on cassava as a staple food, offers invaluable opportunities to advance the current understanding of brain responses to environmental challenges. Increased awareness of the brain disorders that are prevalent in low- and middle-income countries and investments in capacity for further environmental health-related research are positive steps towards improving human health.

This article has not been written or reviewed by Nature editors. Nature accepts no responsibility for the accuracy of the information provided.


Reports from the World Health Organization (WHO) indicate that the global burden of disease is determined by patterns of disease and disability in low- and middle-income countries (LMICs), which, predictably, have their own environmental signatures ( However, the effect of such signatures on both brain health and region or global disability-adjusted life years (DALYs) remains unknown and needs to be added to the agenda of global environmental health research. As for high-income countries, environmental health research programmes in LMICs must primarily focus on elucidating the entire range and source of exposures to define the human 'exposome' (the measure of all the exposures of an individual in their lifetime and how these exposures relate to health) relevant to brain health in LMICs. The research agenda should also include mechanistic and translational research, as well as capacity building to foster a new generation of environmental health scientists.


In this Review, we focus on environmental risk factors for brain diseases and conditions in LMICs ( An iterative search of the literature was conducted using PubMed to retrieve information related to environmental determinants and mechanisms of brain disease in LMICs. Additional opinion was obtained from interviews with leading environmental scientists and neuroscientists, as well as programme officers at the US National Institutes of Health and US National Institute of Environmental Health Sciences (NIEHS), and Fogarty International Center. This Review integrates the goals and approaches to environmental health research as per the NIEHS 2012–2017 strategic plan (

Environmental exposure and brain health

LMICs are home to around 80–85% of the world's population1. Of these 5.8 billion people2, 1 billion remain in extreme poverty, living below the US$1.25 per day poverty line3. Around 3 billion people do not have piped drinking water in their home and 173 million people rely on the direct use of surface water. Without proper sanitation, about one billion continue to defecate in gutters, in the open bush or in open water bodies4. Wildfires and deforestation are commonplace and drought and floods, possibly due to climate change, degrade the existing farming systems and create food insecurity5,6,7. Armed conflicts and population displacements impose a toll on human life8. Industrial expansion coexists with an unprecedented rise in artisanal mining and unprotected labour9. In some instances, normal urbanization operations, such as road construction and quarantines (for example during Ebola outbreaks in the Democratic Republic of the Congo) have created conditions that exacerbated the risk of environmental exposure and brain disease10. Flawed regulations compounded by a lack of infrastructure set the stage for environmental degradation and pollution to pose serious threats — of a chemical or non-chemical nature — to human health. The degradation of local ecosystems leads to the creation of 'microenvironments' that have a high risk of harmful exposures, often resulting in unique challenges and increased risk of human disease (Fig. 1).

Figure 1: Environmental (chemical and non-chemical) threats to brain health in low- and middle-income countries.

Multiple sources of exposure (air, water and food) coexist, and malnutrition and vector-borne diseases, notably infections, compound the risk of brain disease. Co-exposures not shown include heat, psychological stress and a poor physical environment, such as crowding.

High-risk populations and microenvironments

Risk of exposure-related brain disease is determined by age, gender and microenvironments created by natural disasters in which economic, social and cultural determinants of health often have important roles. One example of a profit-mediated environmental risk is that caused by the oil industry through accidental spills or mismanagement of oil operations. For instance, crude oil operations have polluted large areas of rainforests, including streams and rivers in Ecuador, Peru and Colombia11. The population of Nigeria has faced similar challenges owing to reoccurring oil spills as a result of ageing, ill-maintained or sabotaged pipelines in the Niger Delta. The impact of such man-made and preventable natural disasters on human health has yet to be determined. Effects on human health will depend on the type and composition of the spilled oils, which often contain a mixture of polycyclic hydrocarbons that are known to be toxic to the nervous system11. Oil spills arise owing to reasons, such as a lack of vigilance, neglect of necessary health and safety checks, or sometimes even promotion of commercial interests at the expense of communities. Symptoms of acute exposure to raw oil include consistent episodes of headache, nausea, dizziness and fatigue. Chronic effects include psychological disorders, endocrine abnormalities and genotoxic effects12.

Microenvironments in which the population has a higher susceptibility to exposure-related diseases have also been created by extreme poverty and natural disasters, including drought and flooding that can degrade soils, plants and farming operations. The burden of conventional neurodevelopmental stressors (for example, lead) on children is exacerbated by unique environmental challenges, including malnutrition and enteric infections13,14,15,16 and, possibly, a diet of neurotoxicant-containing plants such as cassava (Manihot esculenta; also known as tapioca), the grass pea Lathyrus sativus or the seeds from the cycad plants, which are all known to be associated with a high burden of neurodisabilities at a population level17,18,19,20,21,22. Populations with unique exposures and risks include those living in the tropical cassava belt of Angola, the Central African Republic, Cameroon, Congo, Tanzania, Uganda, Nigeria and Mozambique23,24,25,26,27,28,29,30; those reliant on L. sativus as a staple food in Ethiopia, Eritrea, India and Bangladesh20,31,32,33; and the people of the Pacific island Guam or the Japanese Kii Peninsula where the rates of environmentally linked syndromes such as amyotrophic lateral sclerosis-parkinsonism-dementia complex (ALS/PDC) have been declining for reasons that have yet to be uncovered34,35.

The impact of early childhood diseases that lead to a vicious cycle of enteric infections and malnutrition has been underestimated and neglected, especially in areas that lack acceptable levels of hygiene and sanitation and that have reduced accessibility to vaccines and antimicrobials. This has caused clinically silent, chronic-illness-related effects, which jeopardize the child's full cognitive development13,15. This vicious cycle establishes what is called environmental enteropathy, a mostly subclinical condition (even without diarrhoea) caused by various degrees of intestinal barrier dysfunction, luminal-to-blood intestinal bacterial translocation, low-grade local and systemic inflammation, and disrupted innate intestinal immune responses that may affect growth36 and cognition37 and possibly lead to neurodegeneration as well as liver, and metabolic diseases later in life38,39.

Adolescents in LMICs experience a higher burden of exposures (in contrast with those in high-income countries), primarily because of the childhood labour crisis. Although there are regulations and international agreements restricting child labour, often there are exceptions for certain industries, notably the growing agricultural industry, one of the most hazardous industries worldwide40,41. In this context, adolescent workers are at risk of exposure to agrochemicals such as pesticides42,43. Other work-related threats include exposure to organic solvents in work that involves painting and manufacture, to toxic metals and fine particulate matters in artisanal mining, and to heat and ambient air pollution while working long hours and outside41. Exposure to industrial solvents such as n-hexane, for example, may occur because of poor safety regulations or recreational glue sniffing. This may result in headache, acute encephalopathy or sensorimotor neuropathies that are reversible on cessation44.

Adults in LMICs may be at a particularly high risk of environmental exposure and related brain diseases compared with those in high-income countries. In general, they experience a higher burden of disease owing to a lifetime of cumulative exposures and co-morbidities that are highly prevalent in LMICs. The latter include malaria, nutritional deficiencies and neurotropic infections such as those caused by human T-cell lymphotropic viruses (HTLV). For example, it was reported that endemic foci of HTLV-I-associated myelopathy coexist with outbreaks of konzo (a spastic paraparesis linked to the toxicity of cassava cyanogens) in some regions of the Congo45,46. In these areas, women of childbearing age are particularly susceptible to the toxicity of cassava cyanogens for reasons that have not been elucidated, although they may be linked to hormonal influences and poor nutrition47.

Pathways to brain disease

Exposure-related brain damage may result from chemical and/or non-chemical stressors. Damage to the nervous system often leads to a range of bilateral and symmetrical motor and/or sensory symptoms. Behavioural problems, cognition deficits and psychiatric illness may also occur. Non-chemical stressors include, but are not limited to, psychological stress, heat, noise, fine and ultrafine particulate matter (FUPM), and waterborne, airborne or foodborne pathogens that may occur under the conceptual framework shown in Fig. 1. Chemicals with neurotoxic potential that people are commonly exposed to are listed in Tables 1,2,3. Mixed exposure, for example chemical-covered FUPM from industrial emissions; co-exposure to chemical and non-chemical stressors; and repeated and multiple exposure can occur, creating a complex human environmental exposome.

Table 1 Heavy metals and exposure-related outcomes
Table 2 Organic compounds and exposure-related outcomes
Table 3 Complex exposures and neurological outcomes

Brain damage linked to chemical exposure may result from chemicals interfering with neurotransmission through molecular mimicry or reacting with crucial biomolecules and causing incorrect function (for example, protein or DNA adduction and/or crosslinking). For both chemical and non-chemical exposures, the mechanisms of brain damage may include injury to the vascular system (for example, fine particulate matter induced vascular pathology), systemic dyshomeostasis (for example, cadmium-induced kidney disease) and hormonal imbalance (for example, through endocrine disruption; Table 1).

The susceptibility to exposure-related disease is, however, determined by mechanisms of functional genetics, epigenetics and metagenomics at the interface between risk factors and neurological outcomes (Fig. 2).

Figure 2: Environmental framework and pathways to environmentally induced neurological disease in low- and middle-income countries.

Susceptibility to neurological disease is determined at the interface between a particular exposure, epigenetic and metagenetic make up, and the presence of co-morbidities.

It is increasingly acknowledged that genetic and epigenetic factors, including the effect of maternal stress on brain function, influence the effect of environmental exposure48,49. For example, the E4 allele of the APOE gene that is reportedly associated with higher risk of late-onset Alzheimer's disease, although not in people from sub-Saharan Africa and with a mild association among Hispanic people, is associated with protection against early childhood diarrhoea and its related cognitive impairment50,51,52. One example of gene–environment interactions is the relationship between air pollution components and the gene encoding the MET receptor tyrosine kinase. Several studies have implicated MET as an autism risk gene53,54,55. Stratification of the risk conferred by a functional promoter variant in this gene (rs1858830) and by local traffic-related air pollution (regional particulate matter less than 10 micrometres in diameter and nitrogen dioxide exposure) revealed significant multiplicative interaction between the risk genotype and the air pollution exposure56.

Our knowledge of the pathways that lead to late onset of exposure-related neurological disease is still sparse57,58. Many studies suggest that the genetic and environmental causes of late onset diseases act in parallel and share common molecular mechanisms59. A number of studies have supported the concept that early-life exposure to pollutants reprograms global gene expression in old age through epigenetic mechanisms60,61,62,63. Variation in exposure response, even among individuals exposed to the same environment could be due not only to early-life exposures, but also to differences in genetic make up64,65,66. The extent and nature of exposures and related brain diseases in LMICs provide opportunities to explore and overcome the long reach that childhood exposure has into adulthood, as well as provide us with new advances in environmental health sciences67.

Exposure-related neurological deficits in LMICs range from peripheral neuropathies to a large number of acute, subacute or chronic central nervous system diseases. Deficits may occur prenatally, or during childhood or adolescence, and may be carried through to old age. Clinical implications include, but are not limited to, neural tube defects, learning disabilities, behavioural problems, psychiatric disorders, cognitive decline and the occurrence of distinct entities such as neurolathyrism, tropical ataxic neuropathy, ALS/PDC and konzo20,30,35,68,69 (Fig. 3).

Figure 3: Neurocognition deficits in konzo, a disease linked to eating cyanogenic cassava.

a, Spasticity in a 14-year old boy severely affected by konzo. b, Deficits in mental processing are evident from the results of a neuropsychological test.

The human microbiome may be of particular interest to the mechanistic understanding of exposure-related diseases in LMICs because it may influence the burden of heavy metals70, the metabolism of foodborne neurotoxicants such as cassava cyanogens18, and the outcome of enteric diseases in early life, including the child's neurodevelopmental potential71,72,73

Research and capacity building

Recent advances in environmental health sciences have elucidated the myriad risk factors and mechanisms of brain damage that are associated with environmental exposures. The existence of uniquely exposed populations in LMICs offers invaluable opportunities to advance our current understanding of brain responses to environmental threats. In some instances, well-characterized neurotoxicants may be used as chemical probes to dissect the pathophysiology of the nervous system. However, challenges at the population level still remain, including setting exposure limits and developing metrics and methodologies to assess the long-term impact of environmental exposures on disease burden in LMICs and, therefore, globally. Climate change and mining of rare elements, which may include radioactive materials, present unpredictable risks, and should be added to the environmental health research agenda. The toll of such exposures on the global burden of disease may be efficiently addressed only through competent partnerships and alliances established on a global scale and focused on key areas and priorities (Box 1). Although there is evidence that some of these are already in place, more research and research capacity is needed to continue this agenda to improve human health, globally.

One Health–Global Health dimensions

Environmental degradation and contamination, changes in climate and ecosystems, and vector-born pathogens or neurotoxicants are the primary environmental threats to human life and intellectual performance. Humans, plants and animals adapt to environmental challenges, but some may overcome their adaptive capabilities and create imminent risks for all17,74. Strategies to promote human health will therefore require a serious commitment to trans-disciplinary work, plant and animal health and building capacity on a global scale75.


  1. 1

    Sumner, A. Global Poverty and the New Bottom Billion: What if Three-Quarters of the World's Poor Live in Middle-Income Countries? 1–43 (IDS, 2010).

    Google Scholar 

  2. 2

    World Bank. Data. Low and Middle Income Countries (World Bank, 2015).

  3. 3

    World Bank. Global Monitoring Report 2014/2015: Ending Poverty and Sharing Prosperity (World Bank, 2015).

  4. 4

    Lang, V. & Lingnau, H. Defining and measuring poverty and inequality post-2015. J. Int. Develop. 27, 399–414 (2015).

    Google Scholar 

  5. 5

    Haile, M. Weather patterns, food security and humanitarian response in sub-Saharan Africa. Phil. Trans. R. Soc. Lond. B 360, 2169–2182 (2005).

    Google Scholar 

  6. 6

    Bjorklund, G. Workshop 4 (synthesis): securing food production under climate variability — exploring the options. Water Sci. Technol 49, 147–149 (2004).

    CAS  Google Scholar 

  7. 7

    Kim, K. H., Kabir, E. & Ara Jahan, S. A review of the consequences of global climate change on human health. J. Environ. Sci. Health C. Environ. Carcinog. Ecotoxicol. Rev. 32, 299–318 (2014).

    Google Scholar 

  8. 8

    Rieder, M. & Choonara, I. Armed conflict and child health. Arch. Dis. Child. 97, 59–62 (2012).

    Google Scholar 

  9. 9

    Seccatore, J. et al. An estimation of the artisanal small-scale production of gold in the world. Sci. Total Environ. 496, 662–667 (2014).

    ADS  CAS  Google Scholar 

  10. 10

    Banea, M., Tylleskar, T. & Rosling, H. Konzo and ebola in Bandundu region of Zaire. Lancet 349, 621 (1997).

    CAS  Google Scholar 

  11. 11

    Jernelov, A. The threats from oil spills: now, then, and in the future. Ambio 39, 353–366 (2010).

    PubMed  PubMed Central  Google Scholar 

  12. 12

    Levy, B. S. & Nassetta, W. J. The adverse health effects of oil spills: a review of the literature and a framework for medically evaluating exposed individuals. Int. J. Occup. Environ. Health 17, 161–167 (2011).

    CAS  Google Scholar 

  13. 13

    Guerrant, R. L. et al. The impoverished gut — a triple burden of diarrhoea, stunting and chronic disease. Nature Rev. Gastroenterol Hepatol. 10, 220–229 (2013).

    Google Scholar 

  14. 14

    Guerrant, R. L. et al. Magnitude and impact of diarrheal diseases. Arch. Med. Res. 33, 351–355 (2002).

    Google Scholar 

  15. 15

    Guerrant, R. L. et al. Malnutrition as an enteric infectious disease with long-term effects on child development. Nutr. Rev. 66, 487–505 (2008).

    PubMed  PubMed Central  Google Scholar 

  16. 16

    Petri, W. A. Jr. et al. Enteric infections, diarrhea, and their impact on function and development. J. Clin. Invest. 118, 1277–1290 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17

    Wang, W. et al. Cassava genome from a wild ancestor to cultivated varieties. Nature Commun. 5, 5110 (2014).

    ADS  CAS  Google Scholar 

  18. 18

    Tshala-Katumbay, D. et al. Cassava food toxins, konzo disease, and neurodegeneration in sub-Sahara Africans. Neurology 80, 949–951 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19

    Sarmento, A. et al. Valorization of traditional foods: nutritional and bioactive properties of Cicer arietinum L. and Lathyrus sativus L. pulses. J. Sci. Food Agric. 95, 179–185 (2015).

    CAS  Google Scholar 

  20. 20

    Spencer, P. S. & Schaumburg, H. H. Lathyrism: a neurotoxic disease. Neurobehav. Toxicol. Teratol. 5, 625–629 (1983).

    CAS  Google Scholar 

  21. 21

    Marler, T. E. & Lindstrom, A. J. Free sugar profile in cycads. Front. Plant. Sci. 5, 526 (2014).

    PubMed  PubMed Central  Google Scholar 

  22. 22

    Kisby, G. E. & Spencer, P. S. Is neurodegenerative disease a long-latency response to early-life genotoxin exposure? Int. J. Environ. Res. Public Health 8, 3889–3921 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23

    Banea, J. P. et al. Effectiveness of wetting method for control of konzo and reduction of cyanide poisoning by removal of cyanogens from cassava flour. Food Nutr. Bull. 35, 28–32 (2014).

    Google Scholar 

  24. 24

    Tylleskar, T. et al. Konzo in the Central African Republic. Neurology 44, 959–961 (1994).

    CAS  Google Scholar 

  25. 25

    Ciglenecki, I. et al. Konzo outbreak among refugees from Central African Republic in Eastern region, Cameroon. Food Chem. Toxicol. 49, 579–582 (2011).

    CAS  Google Scholar 

  26. 26

    Nzwalo, H. & Cliff, J. Konzo: from poverty, cassava, and cyanogen intake to toxico-nutritional neurological disease. PLoS Negl. Trop. Dis. 5, e1051 (2011).

    PubMed  PubMed Central  Google Scholar 

  27. 27

    Mlingi, N. L. et al. Recurrence of konzo in southern Tanzania: rehabilitation and prevention using the wetting method. Food Chem. Toxicol. 49, 673–677 (2011).

    CAS  Google Scholar 

  28. 28

    Cliff, J. et al. Konzo associated with war in Mozambique. Trop. Med. Int. Health 2, 1068–1074 (1997).

    CAS  Google Scholar 

  29. 29

    Okitundu Luwa, E. A. D. et al. Persistence of konzo epidemics in Kahemba, Democratic Republic of Congo: phenomenological and socio-economic aspects. Pan. Afr. Med. J. 18, 213 (2014).

    Google Scholar 

  30. 30

    Oluwole, O. S. et al. Persistence of tropical ataxic neuropathy in a Nigerian community. J. Neurol. Neurosurg. Psych. 69, 96–101 (2000).

    CAS  Google Scholar 

  31. 31

    Tekle-Haimanot, R. et al. Clinical and electroencephalographic characteristics of epilepsy in rural Ethiopia: a community-based study. Epilepsy Res. 7, 230–239 (1990).

    CAS  Google Scholar 

  32. 32

    Ludolph, A. C. et al. Studies on the aetiology and pathogenesis of motor neuron diseases. 1. Lathyrism: clinical findings in established cases. Brain 110, 149–165 (1987).

    Google Scholar 

  33. 33

    Ngudi, D. D. et al. Research on motor neuron diseases konzo and neurolathyrism: trends from 1990 to 2010. PLoS Negl. Trop. Dis. 6, e1759 (2012).

    PubMed  PubMed Central  Google Scholar 

  34. 34

    Lee, S. E. Guam dementia syndrome revisited in 2011. Curr. Opin. Neurol. 24, 517–524 (2011).

    Google Scholar 

  35. 35

    Kaji, R. et al. ALS-parkinsonism-dementia complex of Kii and other related diseases in Japan. Parkinsonism Relat. Disord. 18 (Suppl 1), S190–S191 (2012).

    Google Scholar 

  36. 36

    Prendergast, A. J. et al. Stunting is characterized by chronic inflammation in Zimbabwean infants. PLoS ONE 9, e86928 (2014).

    ADS  PubMed  PubMed Central  Google Scholar 

  37. 37

    Patrick, P. D. et al. Limitations in verbal fluency following heavy burdens of early childhood diarrhea in Brazilian shantytown children. Child Neuropsychol. 11, 233–244 (2005).

    Google Scholar 

  38. 38

    Korpe, P. S. & Petri, W. A. Jr. Environmental enteropathy: critical implications of a poorly understood condition. Trends Mol. Med. 18, 328–336 (2012).

    PubMed  PubMed Central  Google Scholar 

  39. 39

    Petri, W. A., Naylor, C. & Haque, R. Environmental enteropathy and malnutrition: do we know enough to intervene? BMC Med. 12, 187 (2014).

    PubMed  PubMed Central  Google Scholar 

  40. 40

    Tilman, D. & Clark, M. Global diets link environmental sustainability and human health. Nature 515, 518–522 (2014).

    ADS  CAS  PubMed  Google Scholar 

  41. 41

    Ferguson, K. T. et al. The physical environment and child development: an international review. Int. J. Psychol. 48, 437–468 (2013).

    PubMed  PubMed Central  Google Scholar 

  42. 42

    Crane, A. L. et al. Longitudinal assessment of chlorpyrifos exposure and effect biomarkers in adolescent Egyptian agricultural workers. J. Expo. Sci. Environ. Epidemiol. 23, 356–362 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43

    Rohlman, D. S. et al. Characterizing exposures and neurobehavioral performance in Egyptian adolescent pesticide applicators. Metab. Brain Dis. 29, 845–855 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44

    Spencer, P. S. et al. The enlarging view of hexacarbon neurotoxicity. Crit. Rev. Toxicol. 7, 279–356 (1980).

    CAS  Google Scholar 

  45. 45

    Tylleskar, T. et al. Konzo, an epidemic spastic paraparesis in Africa, is not associated with antibodies to HTLV-I, HIV, or HIV gag-encoded proteins. J. Acquir. Immune Defic. Syndr. Hum. Retrovirol. 12, 317–318 (1996).

    CAS  Google Scholar 

  46. 46

    Jeannel, D. et al. The risk of tropical spastic paraparesis differs according to ethnic group among HTLV-I carriers in Inongo, Zaire. J. Acquir. Immune Defic. Syndr. 6, 840–844 (1993).

    CAS  Google Scholar 

  47. 47

    Tylleskar, T. et al. Dietary determinants of a non-progressive spastic paraparesis (Konzo): a case-referent study in a high incidence area of Zaire. Int. J. Epidemiol. 24, 949–956 (1995).

    CAS  Google Scholar 

  48. 48

    Vidal, A. C. et al. Maternal stress, preterm birth, and DNA methylation at imprint regulatory sequences in humans. Genet. Epigenet. 6, 37–44 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49

    Bale, T. L. Lifetime stress experience: transgenerational epigenetics and germ cell programming. Dialogues Clin. Neurosci. 16, 297–305 (2014).

    PubMed  PubMed Central  Google Scholar 

  50. 50

    Maestre, G. et al. Apolipoprotein E and Alzheimer's disease: ethnic variation in genotypic risks. Ann. Neurol. 37, 254–259 (1995).

    CAS  Google Scholar 

  51. 51

    Oria, R. B. et al. ApoE polymorphisms and diarrheal outcomes in Brazilian shanty town children. Braz. J. Med. Biol. Res. 43, 249–256 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52

    Oria, R. B. et al. APOE4 protects the cognitive development in children with heavy diarrhea burdens in Northeast Brazil. Pediatr. Res. 57, 310–316 (2005).

    Google Scholar 

  53. 53

    Jackson, P. B. et al. Further evidence that the rs1858830 C variant in the promoter region of the MET gene is associated with autistic disorder. Autism Res. 2, 232–236 (2009).

    Google Scholar 

  54. 54

    Sousa, I. et al. MET and autism susceptibility: family and case-control studies. Eur. J. Hum. Genet. 17, 749–758 (2009).

    CAS  Google Scholar 

  55. 55

    Peng, Y. et al. MET receptor tyrosine kinase as an autism genetic risk factor. Int. Rev. Neurobiol. 113, 135–165 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. 56

    Volk, H. E. et al. Autism spectrum disorder: interaction of air pollution with the MET receptor tyrosine kinase gene. Epidemiology 25, 44–47 (2014).

    PubMed  PubMed Central  Google Scholar 

  57. 57

    Charleta, L. et al. Neurodegenerative diseases and exposure to environmental metals Mn, Pb, and Hg. Coord. Chem. Rev. 256, 2147–2163 (2012).

    Google Scholar 

  58. 58

    Oteiza, P. I., Mackenzie, G. G. & Verstraeten, S. V. Metals in neurodegeneration: involvement of oxidants and oxidant-sensitive transcription factors. Mol. Aspects Med. 25, 103–115 (2004).

    CAS  Google Scholar 

  59. 59

    Ali, S. F., Binienda, Z. K. & Imam, S. Z. Molecular aspects of dopaminergic neurodegeneration: gene-environment interaction in parkin dysfunction. Int. J. Environ. Res. Public Health 8, 4702–4713 (2011).

    CAS  Google Scholar 

  60. 60

    Dosunmu, R., Alashwal, H. & Zawia, N. H. Genome-wide expression and methylation profiling in the aged rodent brain due to early-life Pb exposure and its relevance to aging. Mech. Ageing Dev. 133, 435–443 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61

    Bihaqi, S. W. et al. Infantile postnatal exposure to lead (Pb) enhances tau expression in the cerebral cortex of aged mice: relevance to AD. Neurotoxicology 44, 114–120 (2014).

    CAS  Google Scholar 

  62. 62

    Wang, G. et al. Early life origins of metabolic syndrome: the role of environmental toxicants. Curr. Environ. Health Rep. 1, 78–89 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63

    Collotta, M., Bertazzi, P. A. & Bollati, V. Epigenetics and pesticides. Toxicology 307, 35–41 (2013).

    CAS  Google Scholar 

  64. 64

    Singh, S. et al. Influence of CYP2C9, GSTM1, GSTT1 and NAT2 genetic polymorphisms on DNA damage in workers occupationally exposed to organophosphate pesticides. Mutat. Res. 741, 101–108 (2012).

    CAS  Google Scholar 

  65. 65

    Morahan, J. M. et al. Genetic susceptibility to environmental toxicants in ALS. Am. J. Med. Genet. B Neuropsychiatr. Genet. 144B, 885–890 (2007).

    CAS  Google Scholar 

  66. 66

    Goodrich, J. M. & Basu, N. Variants of glutathione s-transferase pi 1 exhibit differential enzymatic activity and inhibition by heavy metals. Toxicol. In Vitro 26, 630–635 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67

    Currie, E. & Vogl, T. Early-life health and adult circumstance in developing countries. Ann. Rev. Econom. 5, 1–36 (2013).

    Google Scholar 

  68. 68

    Tshala-Katumbay, D. et al. Analysis of motor pathway involvement in konzo using transcranial electrical and magnetic stimulation. Muscle Nerve 25, 230–235 (2002).

    Google Scholar 

  69. 69

    Boivin, M. J. et al. Neuropsychological effects of konzo: a neuromotor disease associated with poorly processed cassava. Pediatrics 131, e1231–e1239 (2013).

    PubMed  PubMed Central  Google Scholar 

  70. 70

    Breton, J. et al. Gut microbiota limits heavy metals burden caused by chronic oral exposure. Toxicol. Lett. 222, 132–138 (2013).

    CAS  Google Scholar 

  71. 71

    Alonso, C. et al. Intestinal barrier function and the brain-gut axis. Adv. Exp. Med. Biol. 817, 73–113 (2014).

    CAS  Google Scholar 

  72. 72

    Sommer, F. & Backhed, F. The gut microbiota — masters of host development and physiology. Nature Rev. Microbiol. 11, 227–238 (2013).

    CAS  Google Scholar 

  73. 73

    Arrieta, M. C. et al. The intestinal microbiome in early life: health and disease. Front. Immunol. 5, 427 (2014).

    PubMed  PubMed Central  Google Scholar 

  74. 74

    Gleadow, R. M. et al. Growth and nutritive value of cassava (Manihot esculenta Cranz.) are reduced when grown in elevated CO. Plant Biol. 11 (Suppl 1), 76–82 (2009).

    CAS  Google Scholar 

  75. 75

    Erisman, J. W. et al. Put people at the centre of global risk management. Nature 519, 151–153 (2015).

    ADS  CAS  Google Scholar 

  76. 76

    Nean, A. & Guillarte, T. Mechanisms of heavy metal neurotoxicity: lead and manganese. Toxicol. Res. 2, 99–114 (2013).

    Google Scholar 

  77. 77

    Mason, L. H., Harp, J. P. & Han, D. Y. Pb neurotoxicity: neuropsychological effects of lead toxicity. Biomed. Res. Int. 2014, 840547 (2014).

    PubMed  PubMed Central  Google Scholar 

  78. 78

    Sanders, T. et al. Neurotoxic effects and biomarkers of lead exposure: a review. Rev. Environ. Health 24, 15–45 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. 79

    Farina, M., Rocha, J. B. & Aschner, M. Mechanisms of methylmercury-induced neurotoxicity: evidence from experimental studies. Life Sci. 89, 555–563 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. 80

    Ercal, N., Gurer-Orhan, H. & Aykin-Burns, N. Toxic metals and oxidative stress part I: mechanisms involved in metal-induced oxidative damage. Curr. Top. Med. Chem. 1, 529–539 (2001).

    CAS  Google Scholar 

  81. 81

    Florea, A. M. & Busselberg, D. Occurrence, use and potential toxic effects of metals and metal compounds. Biometals 19, 419–427 (2006).

    CAS  Google Scholar 

  82. 82

    Valko, M., Morris, H. & Cronin, M. T. Metals, toxicity and oxidative stress. Curr. Med. Chem. 12, 1161–1208 (2005).

    CAS  Google Scholar 

  83. 83

    Catalani, S. et al. Neurotoxicity of cobalt. Hum. Exp. Toxicol. 31, 421–437 (2012).

    CAS  Google Scholar 

  84. 84

    Kumar, V. & Gill, K. D. Aluminium neurotoxicity: neurobehavioural and oxidative aspects. Arch. Toxicol. 83, 965–978 (2009).

    CAS  Google Scholar 

  85. 85

    Harley, K. G. et al. Prenatal and early childhood bisphenol A concentrations and behavior in school-aged children. Environ. Res. 126, 43–50 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. 86

    Yolton, K. et al. Prenatal exposure to bisphenol A and phthalates and infant neurobehavior. Neurotoxicol. Teratol. 33, 558–566 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. 87

    Engel, S. M. et al. Prenatal phthalate exposure is associated with childhood behavior and executive functioning. Environ. Health Perspect. 118, 565–571 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. 88

    Miodovnik, A. et al. Endocrine disruptors and childhood social impairment. Neurotoxicology 32, 261–267 (2011).

    CAS  Google Scholar 

  89. 89

    Jamal, G. A. et al. A clinical neurological, neurophysiological, and neuropsychological study of sheep farmers and dippers exposed to organophosphate pesticides. Occup. Environ. Med. 59, 434–441 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90

    Blanc-Lapierre, A. et al. Cognitive disorders and occupational exposure to organophosphates: results from the PHYTONER study. Am. J. Epidemiol. 177, 1086–1096 (2013).

    Google Scholar 

  91. 91

    Fonnum, F. & Mariussen, E. Mechanisms involved in the neurotoxic effects of environmental toxicants such as polychlorinated biphenyls and brominated flame retardants. J. Neurochem. 111, 1327–1347 (2009).

    CAS  Google Scholar 

  92. 92

    Costa, L. G. et al. A mechanistic view of polybrominated diphenyl esters developmental neurotoxicity. Toxicol. Lett. 15, 282–294 (2014).

    Google Scholar 

  93. 93

    Linares, V., Belles, M. & Domingo, J. L. Human exposure to PBDE and critical evaluation of health hazards. Arch. Toxicol. 89, 335–356 (2015).

    CAS  Google Scholar 

  94. 94

    Viaene, M. Overview of the neurotoxicants effects in solvent-exposed workers. Arch. Public Health 60, 217–232 (2002).

    Google Scholar 

  95. 95

    Tshala-Katumbay, D. et al. New insights into mechanisms of gamma-diketone-induced axonopathy. Neurochem. Res. 34, 1919–1923 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  96. 96

    Kassa, R. M. et al. On the biomarkers and mechanisms of konzo, a distinct upper motor neuron disease associated with food (cassava) cyanogenic exposure. Food Chem. Toxicol. 49, 571–578 (2011).

    CAS  Google Scholar 

  97. 97

    Spencer, P. S. Food toxins, ampa receptors, and motor neuron diseases. Drug Metab. Rev. 31, 561–587 (1999).

    CAS  Google Scholar 

  98. 98

    Makila-Mabe, B.G. et al. Serum 8,12-iso-iPF2alpha-VI isoprostane marker of oxidative damage and cognition deficits in children with konzo. PLoS ONE 9, e107191 (2014).

    ADS  PubMed  PubMed Central  Google Scholar 

  99. 99

    Kang, Y. et al. Arsenic in Chinese coals: distribution, modes of occurrence, and environmental effects. Sci. Total Environ. 412413, 1–13 (2011).

    ADS  Google Scholar 

  100. 100

    Liu, J. et al. Chronic arsenic poisoning from burning high-arsenic-containing coal in Guizhou, China. Environ. Health Perspect. 110, 119–122 (2002).

    PubMed  PubMed Central  Google Scholar 

  101. 101

    Block, M. L. et al. Nanometer size diesel exhaust particles are selectively toxic to dopaminergic neurons: the role of microglia, phagocytosis, and NADPH oxidase. FASEB J. 18, 1618–1620 (2004).

    CAS  Google Scholar 

  102. 102

    Kilburn, K. H. Effects of diesel exhaust on neurobehavioral and pulmonary functions. Arch. Environ. Health 55, 11–17 (2000).

    CAS  Google Scholar 

  103. 103

    Costa, L. G. et al. Neurotoxicants are in the air: convergence of human, animal, and in vitro studies on the effects of air pollution on the brain. Biomed. Res. Int. 2014, 736385 (2014).

    PubMed  PubMed Central  Google Scholar 

Download references


All the authors are thankful to NIEHS and Fogarty International Centre for research grant support and the scientific expertise of their respective programme officers A. Kirshner and K. Michels and staff members. The intellectual contribution of R. Kalaria of Newcastle University, UK, is very much appreciated.

Author information



Corresponding author

Correspondence to Desire Tshala-Katumbay.

Ethics declarations

Competing interests

The authors declare no competing financial interests. Financial support for publication has been provided by the Fogarty International Center.

Rights and permissions

This work is licensed under the Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Tshala-Katumbay, D., Mwanza, JC., Rohlman, D. et al. A global perspective on the influence of environmental exposures on the nervous system. Nature 527, S187–S192 (2015).

Download citation

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links