Manganese Exposure and Neurologic Outcomes in Adult Populations

INTRODUCTION

Manganese (Mn) plays a critical role in many physiologic processes, including protein and energy metabolism, cellular protection from damaging free radicals, bone mineralization, immune function, reproduction, digestion, and metabolic regulation.¹ Although vital in trace amounts, Mn overexposure has been associated with neurodegeneration and neurotoxicity.² Chronic exposure to increased levels of Mn in occupational settings has resulted in a condition called manganism. Manganism is characterized by extrapyramidal symptoms, including bradykinesia, dystonia, gait instabilities, and speech impairments.³ In 1837, Dr John Couper first reported neurologic features associated with Mn exposure when several employees of a Mn processing facility presented with extrapyramidal symptoms. During the twentieth century, research remained focused on occupational exposure to Mn with workplace studies in industries such as welding, mining, and the manufacturing of Mn-containing products. In recent decades, research has become more focused on investigating the impact of chronic low-level exposure to Mn within the general population to understand the subsequent cognitive and neuromotor effects. In 1999, Mergler and colleagues² were among the first to investigate the impact of low-level environmental exposure to Mn within a community setting. Subtle neurologic impairments were observed in relation to blood Mn levels. Current research builds on this concept by substantiating that lower-level environmental exposures are associated with subclinical neurologic effects.⁴

Abundant exposure to Mn occurs through diet,⁵ with factors such as age, gender, and nutritional status affecting absorption rates, which range from 1% to 5%.⁶ Although Mn is naturally present throughout the environment, anthropogenic sources such as industrial air pollution, agricultural fungicides, and gasoline additives contribute to the burden of excess environmental Mn. The inhalation of Mn is concerning because of greater absorption rates, especially within the brain.⁵ Homeostatic regulation is efficient at stabilizing levels of ingested Mn; however, airborne Mn may bypass these mechanisms and directly enter the brain by crossing the blood-brain barrier through membrane transporter proteins, transferrin and transferrin receptors,⁷ or via the olfactory nerve.⁸

Depending on the route of exposure, Mn absorption occurs via the gastrointestinal tract or lung with subsequent distribution throughout the body.⁹ The highest levels of Mn are reported in various organs, including the liver, bone, kidneys, pancreas, adrenal gland, and the pituitary gland within the brain.¹⁰ Typical levels of Mn in blood range from 4 to 15 μg/L.⁵ Circulating Mn is typically bound to hemoglobin; thus, the main compartment for Mn is the erythrocytes.¹¹ The liver plays the primary role in the biological regulation of Mn by conjugating excess Mn to bile for excretion through the intestine.⁹ As indicated by the neurologic impairments associated with Mn exposure, the brain is very vulnerable to Mn toxicity. Mn accumulates in the brain with an affinity toward the basal ganglia structures.¹² With a half-life estimated to be around 150 days, Mn has a slow clearance rate from the brain.^13,14 In addition, it is thought that the high energy requirement and longevity of neurons contributes to enhanced neurologic susceptibility to Mn.⁹

This article examines the recent literature investigating the neurologic impact of Mn exposure on adult populations. This article synthesizes study findings to create a better understanding of the current state of research and to provide suggestions for future research directions.

METHODS

This systematic review investigates the effect of Mn exposure on adult neurocognitive and neuromotor function. In 2016, a systematic review assessing Mn exposure and cognition across the lifespan was published.⁴ Thus, to incorporate the findings from current research into the discussion regarding adult Mn exposure and neurocognition, the authors searched for studies that were published between January 2016 and November 2019 investigating Mn exposure and neurocognition. We identified studies that met our criteria though PubMed and Medline using the following search terms: (manganese) AND (neurocognition OR cognition OR neuro) AND (adults) AND (occupation OR occupational OR environment OR environ*) (“2016/01/01”[Date – Publication]: “2019/11/01”[Date – Publication]). Previously, a review was published to assess the literature regarding Mn exposure and neuromotor outcomes.¹⁵ Therefore, we searched for studies that evaluated Mn exposure among adults and were published between November 2007 and November 2019. Studies that met our criteria were obtained using both PubMed and Medline and the following search terms: (manganese) AND (neurofunctional OR neuromotor OR motor OR neurobehavioral) AND (adults) AND (welders OR occupational OR occupational OR environ*) (“2007/07/ 01”[Date – Publication]: “2019/11/01”[Date – Publication]).

DISCUSSION

Exposure Biomarkers

There is a substantial amount of research characterizing Mn exposure through environmental matrices such as water,^16–18 soil,^16,18,19 and air.^16,20–36 Although these markers indicate levels of external exposure, they are not able to specify individual dose concentrations. In epidemiologic studies, personalized biomarkers of exposure strengthen study findings by capturing internal dose measurements and minimizing reporting bias. However, there is no concurrence on which biomarker of Mn exposure is ideal. Table 1 provides an overview of several different biomarkers commonly used in the studies included in this article.

Table 1.

Biomarkers of manganese exposure

Acute Exposures			Cumulative Exposures
Blood	Urine	Saliva	Hair	Nails	Bone
Most widely used biomarker of Mn exposure38	Poor correlation between Mn exposure and Mn levels in urine39	Although levels are present at concentrations similar to blood, saliva is an alternative noninvasive biomarker for Mn exposure39	Quantifies longer-term cumulative exposures transpiring over several months40	Fingernails and toenails are noninvasive measures that represent aggregate exposures spanning from several months to approximately 1 y37	Approximately 40% of Mn is stored in bone45
Mn in blood has a short half-life of hours10	Past studies have not made significant observations using urine as a Mn biomarker38	Saliva Mn levels seem to linearly increase with exposure39	Exogenous contamination is a significant concern40	Mn concentrations quantified in nails have been associated with levels of Mn in the striatum and midbrain regions41,42 of the brain	Estimated half-life of Mn in bone is 8 y10
Optimal for acute exposures37 such as occupational settings	The future use of urine as a marker of Mn exposure is not recommended30	Use of saliva as a Mn biomarker is questionable10,38,39	Used as a noninvasive biomarker in many studies40		Bone Mn concentrations have been correlated with Mn levels in the brain, specifically the striatum, hippocampus, and choroid plexus43

Blood Mn/iron ratio (MIR) was used as the biomarker for exposure in a study conducted in Guizhou, China.²⁷ The decline in fine motor movement was worsened by Mn exposure, and plasma MIR was inversely associated with fine motor skills. Viana and colleagues⁴⁴ in 2014 incorporated saliva measurements in a study of residents in Brazil living near a ferromanganese refinery to assess Mn exposure; however, no significant correlations were detected with saliva. Urine has been used as a Mn biomarker in many studies^{16,18,19,28,29}; however, the future use of urine as a biomarker is not recommended. Toenails, fingernails, and hair are more frequently collected and analyzed for Mn content.^21,44–47 A Brazilian community study also collected scalp hair, axillary hair, and fingernail specimens, all of which were positively correlated with neuromotor function. Bone, a novel biomarker of Mn exposure, is an appealing biomarker of exposure because of the long-term storage of Mn. Rolle-McFarland and colleagues⁴⁵ in 2019 described associations between bone Mn levels and cognitive deficits, which may stem from underlying hippocampal and striatal impairments. Wells and colleagues⁴⁸ in 2018 found similar associations between increased hand bone Mn concentrations and reduced manual dexterity in an occupational cohort.

Many factors influence personal exposure levels, including ingestion or inhalation rates, age,⁴ gender,⁴⁹ iron (Fe) status,⁵⁰ and nutritional status.⁶ Although exposure may remain constant, variability in individual accumulation of Mn has also been noted. Mutations in Mn transporter and Fe metabolism genes are associated with variations in Mn accumulation,^51–54 thus predisposing an individual to Mn excess or depletion. An Italian study discovered that there was a higher prevalence of Parkinson disease (PD) in the areas surrounding a ferroalloy smelter.¹⁹ Polymorphisms in ATP13A2 (PARK9), a PD-related gene, had a significant impact on the observed effects among the older participants.

Occupational Findings

With known increased exposure levels, the earliest adverse effects related to Mn exposure were first noted in occupational settings. Since the initial observations, regulatory measures have been established to govern exposure; however, a strong consensus on the proper exposure limits is lacking.⁵⁵ Table 2 provides an overview of the occupational studies included in this review. A recent study of welders assessed Mn exposure through reported work history⁵⁶ and accumulated exposure to welding fumes.⁵⁷ Lower cognitive scores were associated with welding fume exposure. In China, a questionnaire was administered to welders to assess potential Mn exposure through queries such as duration of work and type of workplace.³⁵ Similarly, increased Mn exposure through welding histories was associated with negative health outcomes.

Table 2.

Epidemiologic studies investigating occupational exposure to manganese

Author	Location	Study Design	Participants Age at Motor Assessment	Source of Mn Exposure	Biomarker/Environmental Measures	Covariates	Outcome Measure	Results
Bouchard et al,58 2007	Canada	Prospective cohort	Exposed n = 69 Referents n = 68 Mean age 58.1 y	Mn ferroalloy plant	Dust (mg Mn/m3 years) n = 69	Age, education, alcohol, and smoking	Motor Scale of the Luria-Nebraska, finger tapping, Dynamometer, 9-hole Hand Steadiness Test	Exposed had poorer scores compared with referents both in the initial and follow-up examinations for the Luria-Nebraska test. Increasing levels of CEI were significantly associated with poorer scores on the Luria Motor Scale and the Hand Steadiness Test
Shin et al, 200726	Korea	Cross-sectional study	350 workers Age not specified	Manufacturing factories	Air (mg/m3) n = 121 Blood (μg/dL) n = 121 Duration of work (years) n = 121 CEV n = 121 PI n = 111	Age, alanine aminotransferase, and educational level	WHO-NCTB and computerized finger tapping	The proportion of workers with increased signals increased with all the Mn exposure variables. The PI was significantly associated with a correct score of pursuit aiming II tests and finger tapping of the dominant hand
Cowan et al,27 2009	Guizhou, China	Cross sectional study	Smelters n = 26 18–56 y	Ferroalloy plant	Air (mg/m3) Blood MIR n = 136 Plasma MIR n = 143 Mn concentration in erythrocytes n = 144	Age, years of education, sex, income, and years of employment	Groove-type steadiness tester, 9-hole tests, and Purdue Pegboard Coordination Test	Plasma MIR was significantly correlated with pegboard scores. Age-related decline in fine-movement coordination was observed among all study participants regardless of Mn exposure
Chang et al,24 2009	Korea	Cross-sectional study	Welders n = 43 Controls n = 29 40–57 y	Steel block factory	Air (mg/m3) Blood (μg/dL) n = 72 PI n = 73	Age, educational level, alcohol consumption, and smoking	Grooved pegboard, finger-tapping test, CATSYS, hand pronation/supination test	Grooved-pegboard and finger-tapping tests showed significant differences between the 2 groups. Blood Mn levels were shown to be significantly associated with grooved pegboard (dominant hand)
Chang et al,32 2010	Korea	Cross-sectional study	Welders n = 42 Controls n = 26 40–57 y	Steel block factory	Air (mg/m3) n = 73 Blood (μg/dL) n = 73 Pallidal index n = 73	Age, educational level, alcohol consumption, and smoking	Grooved pegboard, finger-tapping test, CATSYS, hand pronation/supination test	Hand pronation/supination and finger-tapping tests were significantly lower among the welders than among the controls
Bowler et al,60 2011	California	Prospective cohort	Welders n = 26 32–65 y	Mn-containing welding fumes	Blood (μg/L) n = 24	Age, ethnicity, duration of welding, type of welding, blood Pb, and smoking	UPDRS3 and the CATSYS Tremor system	Rigidity, dominant postural hand tremor, and body sway increased significantly at follow-up
Sen et al,88 2011	United States	Cross-sectional study	Welders n = 7 Controls n = 7 Mean age 48 y	Not specified	CEI (Mg Mn/m3) n=7	Age	Grooved pegboard; MRI	The welders scored worse than the controls on the grooved-pegboard test for both dominant and nondominant hand
Laohaudomchok et al,30 2011	United States	Cross-sectional study	Welders n = 46 Mean age 37.4 y	Welding school	Air (μg/m3) n = 46	Age, race, education, income, dietary Mn, and BMI	Neuroskill device and finger tapping	Mn exposure over a work shift was significantly associated with worse stability of handwriting
Kim et al,33 2011	Korea	Cross-sectional study	Welders n = 30 Controls n = 19 40–58 y	Factory	Air (μg/m3) n = 100 Blood (μg/L) n = 191	Age, educational level, smoking status, and alcohol consumption status	Finger-tapping tests and the grooved-pegboard test	Fractional anisotropy and radial diffusivity were significantly associated with grooved-pegboard (dominant and nondominant hand) and finger-tapping (dominant and nondominant hand) test outcomes
Racette et al,56 2012	United States	Prospective cohort	389 welders 40–58 y	Factories and shipyards	CEI (Mg Mn/m3) n = 886	Age at baseline, sex, race, tobacco smoking, alcohol consumption, and occupational pesticide exposure	UPDRS3	Exposure was most strongly associated with progression of upper limb bradykinesia, upper and lower limb rigidity
Wastensson et al,61 2012	Sweden	Cross-sectional study	Welders n = 17 Referents n = 21 Mean age 69 y	Shipyard	CEI (mA/m2) n = 17	Age and smoking habits	The Kløve-Matthews static steadiness test, CATSYS, finger-tapping test, grooved-pegboard test, eurythmokinesimeter, diadochokinesimeter, and Jamar dynamometer	Former welders performed less well than referents in the grooved-pegboard test, and poorer performance was associated with CEI
Chang et al,75 2013	Korea	Cross-sectional study	Welders n = 40 Controls n = 26 40–58 y	Steel block factory	Air (mg/m3) Blood (μg/dL) n = 66	Age, educational level, alcohol consumption, and smoking	MRI, Grooved-pegboard, and finger-tapping test	Significant brain volume reductions were found in welders compared with controls, and these volume reductions are associated with motor deficits
Ellingsen et al,28 2014	Russia	Cross-sectional study	Welders n = 137 Referents n = 137 19–70 y	Shipyard	Air (μg/m3) n = 130 Blood (μg/L) n = 123 Urine (μg/g) n = 126	Age, tobacco smoking, the concentration of carbohydrate-deficient transferrin in serum, self-reported mild head injury, shift work, duration of education, coffee consumption	Finger-tapping, foot-tapping, grooved-pegboard, dynamometer, CATSYS 2000, Kløve-Matthews Static Steadiness and Hand Pronation-Supination tests	Welders had poorer performance on motor tests compared with nonwelder referents
Park et al,59 2014	Quebec, Canada	Cross-sectional study	Referents n = 67 Alloy workers n = 68 Mean age 43.9 y	Silico-Mn and ferro-Mn production plant	CE (mg/m3) n = 68	Age and educational level	Luria-Nebraska Neuropsychological Battery–Motor Scale and Finger Tapping	The duration of Mn exposure and Mn as small respirable particulates is strongly associated with the Luria-Nebraska Motor Scale
Long et al,29 2014	Guangxi, China	Cross-sectional study	Smelters n = 9 Controls n = 23 Mean age 39.3 y	Mn-iron alloy factory	Air (mg/m3) n=9 Blood (mg/L) n = 32 Urine (μg/L) n = 32	Age	Purdue pegboard motor testing	Increase in GABA level was significantly associated with the duration of exposure and significant inverse associations between GABA levels and all Purdue Pegboard Test scores in the smelter workers
Baker et al,71 2015	Washington	Prospective cohort	Welders n = 56 Mean age 28 y	Welding	Air (μg/m3) n = 56 TI-weighted indices n = 17	Smoking status, alcohol drinker, prior self-reported loss of consciousness, self-reported respirator use, and age at baseline	Grooved pegboard (Lafayette Instrument Evaluation, West Lafayette, IN), UPDRS3	There were no associations between cumulative exposure and UPDRS3 score or grooved-pegboard time
Lewis et al,69 2016	Pennsylvania	Cross-sectional study	Welders n = 20 Controls n = 13 Mean age 47.1 y	Not specified	hW (hours) n = 20 yW (years) n = 20	Age, education level, BMI, and respirator use	Maximal voluntary contraction tasks, single-finger ramp tasks, quick force pulse production tasks., UPDRS, and the grooved-pegboard test	There also were no significant differences between welders and controls on the grooved-pegboard test
Seo et al,73 2016	Korea	Cross-sectional study	Welders n = 53 Controls n = 44 40+ y	Factories for mild steel blocks and shipbuilding	Air (mg/m3) n = 53 Blood (μg/dL) n = 97	Age, education level, tobacco use, alcohol consumption, use of medication, medical history, subjective symptoms, job type (type of welding and duration), work history	fMRI, Wisconsin Card-sorting Task, Word-Color Test, Computerized Neuropsychological Test	Blood Mn level was significantly higher in welders than in controls. Reaction time for given tasks were not significantly different between groups even though welders took longer. Based on fMRI images, no specific regions had significant activity in welders while WCST was being completed
Al-Lozi et al,57 2017	United States	Cross-sectional study	Welders n = 82 Nonwelders n = 13 23–66 y	Welding	Exposure welding metrics (duration, intensity and total exposure)	Work history, cumulative Mn exposure, age, sex, race, ethnicity, medical history, history of head injury, previous exposures, alcohol/tobacco use	Assess cognitive control in response inhibition, working memory, fluency, verbal fluency, letter-number sequencing, Two Black Letter Task, Go-N-Go, Simon Task, Cognitive Control Summary was scored for those completing all 5 tasks, WAIS3- verbal/matrix reasoning	Poorer performance in cognitive control tasks in relation to welding fume exposure. Welders had lower IQ and cognitive control scores
Zhang et al,35 2017	Qingdao City, China	Cross-sectional study	n = 505 19–54 y	Welding	Work history	Smoking habits, years of work, education level, age	Questionnaires assessing symptoms	Correlation between the highest level of symptom reports with highest level of air Mn measurements. Those with >15 y of welding reported high levels of tremor and motor disabilities
Bowler et al,23 2018	United States	Cross-sectional study	Welders n = 26 Controls n = 17 ≥18 y	Welding for semitruck manufacture	Air (mg/m3) n = 43 MRI n = 43	Age, education, ethnicity, alcohol consumption, smoking habits	Rey-O Copy Trial, Trials B Test, Trails A, Digit Symbol Coding, WAIS3, WHO-AVLT, verbal fluency	Welders scored lower than controls in verbal fluency, Parallel Lines Test, and Digit Symbol Coding. Welders had shorter T1 relaxation times
Lee et al,36 2018	Pennsylvania	Cross-sectional study	Welders n = 43 Controls n = 32 Age not stated	Welding	Blood (ng/mL) n = 75	Recent hours welding, lifetime exposure, cumulative exposure inhaled over lifetime	Grooved-pegboard test, UPDRS3, single-finger/multifinger pressing task, MRI	Results of Phonemic Fluency Test suggest that processes associated with phonemic fluency are among some of the earliest changes in welders with low Mn exposure
Ma et al,31 2018	United States	Cross-sectional study	Welders n = 39 Controls n = 22 Mean age 40 y	Mn fumes	Air (mg/m3) n = 39	Age	UPDRS3	High exposure to Mn showed a significant increase of thalamic GABA levels, as well as significantly worse performance in general motor function
Wells et al,48 2018	United States	Cross-sectional study	Workers n = 7 Comparison n = 12 18–62 y	Trailer manufacturer	Bone Mn (μg/g) n = 19	Age and occupation	Purdue Pegboard Test	High MnBn was significantly associated with lower manual dexterity based on the Purdue pegboard assembly task
Criswell et al,65 2019	Midwest United States	Cross-sectional study	Mn-exposed welders n = 27 Other Mn-exposed workers n = 12 Nonexposed n = 29 22–69 y	Welding worksites	CEI n = 68 PI n = 68	Sex; age; imaging scan date; current consumption of cigarettes, caffeine or alcohol	UPDRS3	Cumulative Mn exposure is associated with increased PI. PI was associated with clinical parkinsonism
Palzes et al,46 2019	Zarcero County, Costa Rica	Cross-sectional study	Organic farmers n = 26 Conventional farmers n = 22 18+ y	Farmers from organic and conventional farms	Hair (μg/g) n = 33 Toenails (μg/g) n = 40	Sociodemographic characteristics, work history, medical history, computer literacy, age	Letter retrieving/working memory task, fNIR	Brain activity decreased with every 2-fold increase in nail and hair Mn concentration
Rolle-McFarland et al,45 2019	Zunyi, China	Cross-sectional study	Ferroalloy smelters n = 30 Manufacturing workers n = 30 ≥18 y	Equipment manufacturing and installation company (control) and ferroalloy smelting facility	Bone (μg/g) n = 60 Fingernail (μg/g) n = 55 Blood (μg/L) n = 60	Age, education, drinking status, smoking status	Animal naming, fruit naming, WHO/UCLA Verbal Learning Test (AVLT), UPenn Smell Identification Test	MnBn and MnFn are associated with decreased performance in cognitive function but not smell MnB had no association with cognitive function

Abbreviations: AVLT, auditory verbal learning test; BMI, body mass index; CEI, Cumulative Exposure Index; CEV, cumulative exposure variable; CATSYS, Coordination Ability Test System; GABA, gamma-aminobutyric acid; Ferro-Mn, ferromanganese; fMRI, functional MRI; fNIR, functional near infrared; IQ, intelligence quotient; hW, hours spent welding in the 90 day period preceding MRI; MnBn, Bone Mn; MnB, Blood Mn; MnFn, Fingernail Mn; NCTB, Neurobehavioral Core Test Battery; PI, pallidal index; UCLA, University of California, Los Angeles; UPDRS, Unified Parkinson Disease Rating Scale; UPenn, University of Pennsylvania; WAIS, Wechsler Adult Intelligence Scale; WHO, World Health Organization; yW, cumulative lifetime years welding.

Data from Refs.^{23,24,26–32,34–36,45,46,48,56,57,59–61,65,71,73–75,88,91}

In a cohort study, welders compared with nonwelder referents had poorer performance on motor tests; however, there were no statistically significant associations indicating poorer test performance related to Mn exposure.²⁸ Similarly, Mn exposure assessed from personal monitoring was significantly associated with worse stability of handwriting among welders.³⁰ When measuring Mn dust at a ferromanganese alloy plant, initial and follow-up examinations on exposed workers showed a significant association between poorer motor performance and exposure.⁵⁸ In a cohort of welders, Mn cumulative exposure was strongly associated with the progression of limb bradykinesia and limb rigidity.²² In another study, the duration of Mn exposure and Mn small respirable particulates were strongly associated with motor function.⁵⁹

To assess the permanency of Mn-associated health outcomes among acutely exposed welders, a follow-up neuromotor examination was done 3.5 years after cessation of confined-space welding.⁶⁰ Symptoms including extrapyramidal, olfactory, and mood disturbances did not improve over time and may even have deteriorated, whereas cognitive function seemed to improve for the retired welders. To investigate even longer-term cessation of exposure to Mn, a study recruited welders who had been retired for an average of 18 years.⁶¹ Results were similar among retired welders and referents.⁶¹

Community Findings

The studies of community exposure to Mn are described in Table 3. A study among people living near a ferromanganese refinery in Ohio and a demographically similar community examined the effects of long-term, low-level environmental Mn exposure on neuromotor function.³³ No association was found between blood Mn levels and Unified Parkinson’s Disease Rating Scale (UPDRS) data or postural sway; however, adjusted models showed significant differences between the exposed and the referents, with heightened impairments observed among the exposed. Similar results were seen using the same study population, where blood Mn and cumulative exposure index did not predict any motor outcomes.⁶² Another study conducted in the same region showed a significant association of airborne Mn with several neuromotor outcomes.²⁵ Increased tremor and motor symptoms, executive dysfunction, and tremor-dominant and non–tremor-dominant symptom clusters were identified in chronically exposed residents.²⁰

Table 3.

Epidemiologic studies investigating community-level manganese exposures

Author	Location	Study Design	Participants; Age at Motor Assessment	Source of Mn Exposure	Biomarker/Environmental Measures	Covariates	Outcome Measure	Results
Kim et al,33 2011	Ohio	Cross-sectional study	Exposed n = 100 Reference n = 90 30–75 y	Ferro-Mn and silico-Mn smelter	Air (μg/m3) n = 100 Blood (μg/L) n = 190	Age, sex, ethnicity, smoking status, drinking status, educational level, household income, insurance status, serum ferritin, ALT, and GGT; BMI; medication history, blood lead, cadmium, and mercury	UPDRS and CATSYS 2000	UPDRS motor and postural sway scores were significantly higher in the exposed group than in the comparison group. No significant difference between the exposed and comparison groups was evident as to MnB
Bowler et al,62 2012	Ohio	Cross-sectional study	Exposed n = 100 Reference n = 91 30–75 y	Ferro-Mn smelter	CEI air (μg/m3) n = 100 Blood (μg/L) n = 190	Age, sex, education, diabetes, mental health medication, and health insurance status	Finger tapping, grooved pegboard, dynamometer, and UPDRS	MnB did not predict any motor outcomes either in the exposed or in the comparison group
Rentschler et al,19 2012	Italy	Cross-sectional study	255 adults 63–80 y	Ferroalloy smelters	Soil (ppm) Blood (μg/L) Urine (mg/L)	Age and gender	Luria-Nebraska Motor Battery, stylus and balance plate	For both adolescents and elderly, negative correlations between Mn in soil and motor coordination were shown
Lucchini et al,16 2014	Brescia, Italy	Cross-sectional study	Exposed n = 153 Reference n = 102 65–75 y	Ferroalloy plant	Air (ng/m3) n = 254 soil (ppm) n = 255 Blood (μg/L) n = 238 Urine (μg/L) n = 239	Age, gender, alcohol, smoke, and distance from the nearest ferro-Mn plant	Luria-Nebraska Neuropsychological Battery	Air Mn was negatively associated with the motor coordination tests of the Luria-Nebraska Neuropsychological Battery
Viana et al,44 2014	Bahia, Brazil	Cross-sectional study	89 adults 15–55 y	Ferro-Mn refinery	Scalp hair (μg/g) n = 81 Fingernail (μg/g) n = 73 Axillary hair (μg/g) n = 18 Saliva (μg/g) n = 82	Age, gender, years of schooling, locale of residence, time in years of residence in the communities, drinking habits, and family income	Grooved-pegboard Test	MnH, MnFN, and MnAxH levels were positively correlated with motor function for the dominant hand
Bowler et al,25 2016	Ohio	Cross-sectional study	186 adults 30–75 y	Ferro-Mn smelter	Air (μg/m3) n = 186	Sex, employment status, household income	Finger tapping, hand dynamometer, grooved pegboard, and the CATSYS tremor system	Tremor and motor function were associated with higher exposure to airborne Mn
Cabral Pinto et al,18 2018	Estarreja, Portugal	Cross-sectional study	N = 103 residents 55+ y	Industrial activity	Urine Water Soil	Years of residency, medical history, health status, work history, education, water used in irrigation and drinking, use of homegrown foods, daily habits	MMSE, MoCA, CDR Scale	Association between mild dementia and moderate dementia with high contents of Cr, Mn, Cd, and Se. Stream water was associated with dementia and high levels of Cr, Mn, Cd and Se in urine
Kornblith et al,20 2018	Ohio	Cross-sectional study	N = 182 30–75 y	Ferro-Mn smelter	Air (μg/m3) n = 182	Age, gender, employment, race, and years of residence	CATSYS, UPDRS	Increased tremor and motor symptoms and executive dysfunction were observed, and TD and NTD symptom clusters were identified

Abbreviations: ALT, alanine transaminase; CDR, Clinical Dementia Rating; GGT, gamma-glutamyl transferase; MMSE, Mini-Mental State Examination; MnAxH, Auxiliary Hair Mn; MoCA, Montreal Cognitive Assessment; NTD, non-tremor dominant; TD, tremor dominant.

Older populations are vulnerable to environmental exposures for multiple reasons. First, older adults have the opportunity for chronic exposure, particularly if they reside in a community with a Mn point source. Second, older generations were likely exposed to contaminants at greater levels than are present today because of changes in regulations and advances in control technology. Third, aging is a key risk factor for neurologic decline and the development of neurodegenerative disorders. Studying older populations provides an insight into the potential health issues that may burden future generations if exposure patterns are not altered. An Italian study recruited older adults living near a ferroalloy plant to represent people with lifelong exposure to environmental Mn.¹⁶ The researchers observed a negative correlation between airborne Mn and coordination, with women showing greater motor dysfunction than men. Using the same cohort, Rentschler and colleagues,¹⁹ in 2012 described a negative association between soil Mn and motor coordination, again with women showing greater motor dysfunction.¹⁹

Although personal biomarkers are generally preferred, some studies justify applying environmental measures to indicate Mn exposure. In a study of environmentally exposed adults,^20,63 Mn exposure was estimated based on the US Environmental Protection Agency’s AERMOD (atmospheric dispersion modeling) dispersion models. Researchers aimed to determine whether subtypes of Mn neurotoxicity were similar to those observed in PD.²⁰ Among those exposed to low levels of Mn, subtle cognitive impairment was observed; however, there was no indication of motor dysfunction. Findings indicate that PD and Mn-induced motor disorders have distinct pathophysiology patterns.

Neuroimaging

MRI is useful as a biomarker of exposure because of its ability to show Mn accumulation in the brain. Because of its paramagnetic properties, Mn is a longitudinal relaxation time (T1) contrast agent, which means that, when water is excited with radiofrequency pulses within the MRI scanner, the manner in which the signal decays is influenced by accumulated Mn. For T1-weighted images, regions of the brain with Mn accumulation show higher signal than other regions. One method to assess Mn accumulation is with the pallidal index (PI). This metric takes the ratio of signal intensity in 2 anatomic locations of a T1-weighted image, usually the globus pallidus and frontal white matter. PI seems to be higher in exposed groups versus controls⁶⁴ and shows a dose-response relationship with blood Mn and recent air-exposure Mn,^26,64 as well as workers’ cumulative Mn exposure.⁶⁵ Shin and Aschner⁶⁶ found a significant relationship between PI and motor dysfunction, as measured by pursuit aiming tests and finger tapping, respectively.

Another method for assessing Mn accumulation in the brain is by directly measuring T1. Because Mn accumulation leads to shorter T1 values, the inverse of the T1, R1 (R1 = 1/T1), is commonly used. Researchers have found that the relationship between Mn exposure and Mn accumulation in the brain is not straightforward. For 1 cohort of welders, R1 increased after 300 hours of work in the past 90 days, suggestive of a Mn exposure threshold below which there are no significant increases in R1.^36,67 In another cohort of welders, R1 increased significantly only for those exposed to air exposure greater than 0.1 mg/m³.⁶⁸ In addition, R1 was sensitive to changes in Mn exposure and changed proportionately with fluctuating levels of Mn exposure.⁶⁹ However, changes in R1 in relation to short-term Mn exposure are influenced by the person’s lifetime cumulative exposure,⁷⁰ suggesting that lifetime exposure may have a longer-lasting effect on Mn retention in the brain. Some studies associated T1 with impaired cognitive performance. Shorter T1 was related to lower performance on verbal fluency, verbal learning, memory, and preservation tests.²³ Verbal dysfunction, which is not commonly tested, may be an early symptom of Mn exposure. In addition, T1 changes have been detected when there is low Mn exposure and before neurologic changes are clinically evident.⁷¹

MRI technology can also be used to measure neurochemicals in vivo with magnetic resonance spectroscopy (MRS). MRS can measure many chemicals in the millimolar range, including gamma-aminobutyric acid (GABA), the major inhibitory neurotransmitter in the central nervous system. Because of its high abundance in the basal ganglia, GABA has been targeted as a potential biomarker for motor dysfunction with Mn exposure. Consequently, thalamic GABA levels have been found to be higher in workers in smelters^29,72 and welders,^31,70 where it also correlated with Mn exposure as measured at 12-month and -month intervals. In a study of welders by Ma and colleagues³¹ (2018), highly exposed welders had higher thalamic GABA levels as well as higher UPDRS3 scores compared with less exposed welders and controls. Although thalamic GABA also correlated with R1 in the substantia nigra and frontal cortex, thalamic GABA did not correlate with UPDRS3 scores. Thalamic GABA changes proportionately with increasing or decreasing Mn exposure in the workplace; however, UPDRS3 scores seem to remain static.⁷⁰

To measure cognitive processes during tasks, functional MRI (fMRI) is a useful biomarker of effect. fMRI is based on the principle that the brain uses more energy in regions of the brain that are used during particular tasks, which results in measurable increased blood flow (seen as blood oxygen level–dependent contrast) in regions of increased cognitive use. To test the effect of Mn on memory, Chang and colleagues³² (2010) used a commonly used paradigm, the N-back task, where participants are asked to remember pertinent items from N trials previously presented. Chang and colleagues³² used a 2-back task and found welders have increased brain activity in working memory networks compared with controls. Using the Wisconsin Card-sorting Task (WCST), Seo and colleagues⁷³ (2016) found that welders had lower activation compared with controls in the areas of the brain related to executive function, such as the prefrontal cortex, under conditions of higher cognitive demand. However, although air Mn exposure was measured in both of these studies, there was large variability within each cohort and air Mn exposure was not taken into account in any of the reported analyses.

In addition, brain structure can be assessed using diffusion tensor imaging (DTI) and voxel-based morphometry (VBM). DTI measures the integrity of white matter by determining how free water can diffuse within a given location. The greater water diffusion is restricted within fibers, the higher its fractional anisotropy (FA), and vice versa. Higher FA corresponds with increased fiber organization. In general, FA has been found to be lower in the corpus collosum,³⁴ frontal white matter,³⁴ and basal ganglia^36,74 in welders. Specifically, lower FA was found in the basal ganglia of welders with 30 years or more of experience welding,³⁶ suggesting that long-term exposure to Mn might have a degradational effect on neuronal integrity beyond normal aging. Lower FA was also related to fine motor dysfunction, as measured by synergy indices.⁷⁴

Using VBM, Chang and colleagues⁷⁵ (2013) found decreased brain volume in the globus pallidus and cerebellar regions in welders, which correlated with cognitive performance and grooved-pegboard performance. However, this is the only study to have been performed with significant results in morphometry, which is confounded because of the difficulty in segmenting the basal ganglia because of high signal intensity caused by Mn exposure.

Manganese and Neurodegenerative Diseases

Evidence suggests that, because of accumulation in the brain, neurotoxic metals may play a role in neurodegenerative diseases.⁷⁶ Exposure to toxic levels of Mn results in manganism, a neurodegenerative condition, and is implicated in the etiopathogenesis of several prevalent neurodegenerative diseases, including PD and Alzheimer disease (AD).⁷⁷ Because of numerous links between Mn and PD-like symptoms, Mn exposure may be involved with PD development; however, inconsistent results have been reported.⁷⁸ A meta-analysis was conducted in 2018 and results suggest that increased Mn concentrations may be a potential risk factor for PD.⁷⁹ Multiple assessments may be used to observe the prevalence of parkinsonian symptoms, such as the UPDRS, pegboard tasks, and various motor tasks.^22,36,56 Lee and colleagues³⁶ observed significantly lower stability in welders compared with controls; however, UPDRS scores were similar. There was an association between cumulative Mn exposure and UPDRS scores in a cohort of US welders.²² Findings suggest that there are associations between neurodegenerative patterns in Mn toxicity and parkinsonian features along with further potential associations with movement disorder symptoms.²⁰ Mn seems to accelerate the transmission of misfolded alpha-synuclein, a protein that, when misfolded, clumps and becomes toxic to neurons and has thus been linked to PD.⁸⁰ However, contrary to PD, Mn-induced movement disorders likely result from the reduced ability to release dopamine.^78,81,82

Because of the age distribution among workers, many occupationally based studies do not include senior participants. However, when investigating cognitive decline, older adults may be among the most vulnerable populations to consider when studying the neurotoxic impacts of Mn exposure. More than 35 million people worldwide have dementia and the incidence rate is expected to increase over the next few decades.⁸³ Dementia is a condition that encompasses significant impairments in memory, thinking abilities, social skills, and behavior.⁸³ AD, the most common form of dementia, has suggestive causal links with preceding Mn exposure. Pinto and colleagues¹⁸ examined a group of older participants living in close proximity to Estarreja Chemical Complex (ECC), a source of environmental contamination in Portugal. The investigators described an association between mild and moderate dementia and high concentrations of several metals, including Mn. Previous research has proposed that Mn may be a contributing factor in the pathogenesis of AD by disrupting amyloid-β (Aβ) peptide degradation.⁸⁴ In a sample of Portuguese residents, Pinto and colleagues¹⁸ observed associations between high concentrations of Mn measured in water and moderate levels of dementia. In mouse models, the intraperitoneal injection of a Mn chelator was effective at reducing Mn levels within the brain, decreasing Aβ peptides, and restoring cognitive function,⁸⁴ thereby providing a potential avenue to explore with regard to human intervention. However, opposing observations have been made as well. A meta-analysis conducted by Du and colleagues⁸⁵ described low serum Mn levels among people with mild cognitive impairment and AD. Further investigation into the potential relationship between Mn and AD is of great public health and socioeconomic interest.

Summary

Overall, the research included in this review contributes novel and valuable information to the existing literature and provides directions for future research. Innovative biomarkers, including those from advanced neuroimaging, were incorporated into many studies to assess both Mn exposure and neurologic outcomes. Studies examining the effects of occupational exposures to Mn continue to show adverse neurologic outcomes. With participants from communities located near Mn point sources, usually industrial facilities, studies in these populations show variability in the observed effects, which reflects the complexities of Mn exposure measurement, individual absorption, and impairment assessment. Unique populations, specifically those incorporating older adults, were used to study the impact of lifelong Mn exposure and provide insight into what the future may hold for younger exposed populations.

Limitations

The literature is saturated with studies investigating occupational Mn exposure, and, as a result, studies involving women are lacking. Although gender influences the development and progression of AD⁸⁶ and PD,⁸⁷ hormonal uniqueness is hypothesized to affect the pharmacokinetics of Mn as well.⁴⁹ Therefore, gender-based selection bias limits the ability to generalize from many studies. Regarding occupational research, there is possible bias from the healthy worker effect because sicker workers may no longer be actively employed.⁵⁸ Inaccurate work history and the lack of a reliable biomarker may contribute to recall bias and exposure misclassification among participants.^{22,24,26,30,32,33} In addition, sample size constraints pose a challenge to many epidemiologic studies.^{27,30,44–46,60,73,74,88} It is known that coexposures may influence the neurotoxicity of Mn; therefore, possible confounding may be present because of failure to consider concomitant exposures such as tobacco smoke⁸⁹ and lead.⁹⁰ In addition, because of the cross-sectional nature of many of the reviewed studies, temporality is not feasible to definitively establish and future studies would benefit from using a longitudinal design.

KEY POINTS.

• Chronic increased manganese (Mn) exposure is associated with cognitive and motor impairments in both occupational and community settings.

• Numerous biomarkers are used to ascertain Mn exposure.

• Neuroimaging is an innovate tool used as both a biomarker of Mn exposure and a biomarker of effect.

• Older adults are a novel population that can provide insight into the impacts of chronic Mn exposure and the role of Mn in the development and progression of neurodegenerative diseases.

Future Directions.

• Elucidating the optimal biomarker of Mn exposure

• Leveraging novel methods, such as neuroimaging, to directly measure Mn exposure and characterize effects

• Considering individual variability with regard to both Mn accumulation and neurotoxicity

• Understanding the role of Mn in neurodegenerative diseases and ultimately developing intervention methods

CLINICS CARE POINTS.

• Environmental exposures should be considered when assessing neurodevelopmental deficits and neurodegenerative diseases.

• Those with increased susceptibility to Mn accumulation (ie. individuals with liver diseases, patients receiving parenteral nutrition) should be carefully monitored for Mn associated effects.

• Efforts to mitigate elevated environmental Mn exposure, especially in vulnerable populations, should be taken.