Med. Sci. 2020, 8, x doi: FOR PEER REVIEW www.mdpi.comjournal medsci [607823]

Med. Sci. 2020, 8, x; doi: FOR PEER REVIEW www.mdpi.com/journal/ medsci
Type of the Paper (Article, Review, Communication, etc.) 1
Cumulative Effects of Low -level Lead E xposure and 2
Chronic Physiological Stress on Hepatic 3
Dysfunction – A Preliminary Study 4
Emmanuel Obeng -Gyasi 1,* 5
1 Department of Built Environment, North Carolina Agricultural and Technical State University; 6
Greensboro, NC 27411, USA; 7
* Correspondence: [anonimizat]; Tel.: +1 -336-285-3132 8
Received: date; Accepted: date; Published: da te 9
Abstract: Chronic physiological stress and hepatic injury were explored in this cross -sectional study 10
using data from the National Health and Nutrition Examination Survey (NHANES) 2007 -2010. Lead 11
exposure was measured using Blood Lead Levels (BLL), whic h were divided into quartiles of 12
exposure based on the distribution within the database. Allostatic load (AL), a variable 13
representing chronic physiological stress, was operationalized using ten clinical markers. The 14
geometric mean values for markers of l iver injury of interest (a) Aspartate Aminotransferase (AST), 15
b) Alanine Aminotransferase (ALT), (c) Alkaline Phosphatase (ALP, and (d) Gamma glutamyl – 16
transferase (GGT) were explored in quartiles of lead exposure. Associations between AL and AST, 17
ALT, ALP, and GGT among those exposed to lead were analyzed using linear regression models. 18
In examining lead exposure in increasing quartiles, the geometric mean of the liver injury markers 19
showed significant elevations as lead exposure levels increased. Simple linear regression revealed 20
AL was positively associated with several markers of hepatic injury in all degrees of lead exposure. 21
This study demonstrates the potential dangers of social and environmental exposures on liver 22
health. 23
Keywords: Allostatic Load ; Liver Lead ; Lead-Exposure; Chronic Stress; Psychosocial Stress 24
25
1. Introduction 26
Lead exposure may come about due to exposure from lead-contaminated paint, water , jewelry, 27
candy, soil , and dust [1, 2]. The accumulation of lead in the body begins in the womb [3], builds 28
up in the bone over time, and in duces pathology in numerous organ systems within the body [4-9]. 29
This process can alter the life course of exposed individuals by downwardly altering their education 30
outcomes, income, and behavior [10, 11]. 31
No level of lead exposure is safe, and even very low levels of exposure may significantly harm 32
the health of individuals [12]. Little is known about the cumulative effects of low levels of lead 33
exposure on the liver and even less about t he cumulative role of lead exposure and the exposure to 34
chronic physiologi cal stress on the liver. 35
The liver is the largest organ in the human body and has three vital functions (a) detoxification 36
–where it recovers and eliminates many toxins and toxicants, (b) synthesis – where it metabolizes 37
critical macromolecules such as carbohydrates, fats, and proteins, and produces bile and critical 38
coagulation factors, and (c) storage – where the liver stores essential vitamins such as (A, D, E, and K) 39
and glycogen which is critical for the energy needs of the body. 40
Studies examining the hepatotoxicity of lead have found that lead exposure modifies cholesterol 41
and xenobiotic metabolism, and can be involved in pathological mechanisms bringing about hepatic 42
hyperplasia [13]. 43

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Liver injury can be evaluated by examining clinical markers of liver damage such as Alanine 44
aminotransferase (ALT), Aspartate aminotransferase (AST), Alkaline phosphatase (ALP), and 45
Gamma-glutamyl transferase (GGT). Serum activity of these markers is often a ref lection of the 46
physiological state of the liver, and their activity in the blood often indicates the severity of ce llular 47
damage [14, 15]. Lead exposure has been shown to alter these makers [16, 17]. 48
Stress can result from a mixture of biological and behavioral reactions [18] that result in 49
activation of the hypothalamic -pituitary -adrenocortical (HPA) axis and stimulation of the 50
sympathetic nervous system (SNS) with increased levels of epinephrine, cortisol, and pro – 51
inflammatory cytokines [19], all of which could induce liver dysfunctions [20]. Additionally, stress 52
help to promote unhealthy behaviors such as alcohol intake, smoking, and poor diet, which are also 53
associated with adverse liver pathologies. 54
Allostatic load (AL) can serve as a marker of chronic systemic physiological stress in that it 55
collects markers from various physiological s ystems within multiple organ systems: This helps to 56
understand the biological burden that stress has on the human body [21-24]. 57
This study seeks to explore the role of chronic physiological stress and low -level lead exposure 58
on hepatic function. 59
2. Materials and Methods 60
2.1. Hypothesis 61
This study hypothesizes that increasing levels of low -level lead exposure and chronic 62
physiological stress promotes liver injury. The objectives of this study was therefore to examine th e 63
effects of AL on AST, ALT,ALP, and GGT in adults exposed to various degrees of lead. 64
2.2. Research Design 65
This cross -sectional study was based on analysis of data from the National Health and Nutrition 66
Examination Survey (NHANES). The relationship between chronic physiological stress (AL), and 67
markers of liver injury ALT, AST, ALP, and GGT among individuals exposed to differe ntial lead 68
levels as defined by blood lead levels (BLL) were explored using NHANES 2007 -2010. NHANES data 69
is a stratified, multistage probability sample of the civilian non -institutionalized individuals within 70
the United States. 71
2.2.1. Operationalizing All ostatic Load 72
Based on prior studies [25, 26], AL was operationalized via a cumulative index of dysfunction 73
across multiple physiological systems such as the cardiovascular system (SBP, DBP, triglycerides, 74
HDL cholesterol, total cholesterol), the inflammatory system (CRP -for systemic inflammation), and 75
finally the metabolic system (Albumin, BMI, hemoglobin A1C, and Creatinine Clearance). These 76
markers were divided into quartiles of lead exposure based on their distribution within the database 77
with high -risk for each biomarker considered the top quarter i n the distribution for all markers apart 78
from the markers for albumin, creatinine clearance, and for HDL cholesterol, for which the lowest 79
quarter of the distribution was the highest risk [8, 27-32]. Each participant within the data was 80
assigned a value of 0 if in the lo w-risk category with a value of 1 for those in the high -risk category 81
to ultimately calculate a total AL value out of 10. 82
2.2.2. NHANES Data Collection Procedures 83
Demographic information was collected during an in -home interview using a standardized 84
questionna ire with clinical and anthropometric data collected at the mobile examination center 85
(MEC). Blood was drawn from particpants antecubital vein with Inductively Coupled Plasma Mass 86
Spectrometry (ICP -MS) used to analyze it for BLL. Urine was analyzed for urin ary creatinine and 87
albumin at the University of Minnesota. A solid -phase fluorescent immunoassay was used to 88
measure Urine albumin was measured using a Sequoia -Turner Digital fluorometer (sequoia -Turner 89

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Corp., Mountain View, CA, USA). Creatinine was analyz ed using the Jaffe rate reaction with a 90
Beckman Synchron CX3 clinical analyzer (Beckman Coulter, Fullerton, CA, USA). Hemoglobin A1C 91
was analyzed via a Tosoh A1C 2.2 plus Glycohemoglobin Analyzer or a Tosoh G7 Automated 92
HPLC Analyzer (Tosoh Medics, Inc, San Francisco, CA, USA). CRP was analyzed via latex – 93
enhanced nephelometry on a Behring Nephelometer Analyzer System (Behring Diagnostics, Inc, San 94
Jose, CA, USA). 95
Fasting total serum cholesterol and triglycerides were analyzed enzymatically via a 96
Roche/Hi tachi Modular P Chemistry Analyzer (Roche Diagnostics Corp, Indianapolis, IN, USA). 97
HDL cholesterol was measured via a adaptation of the customary multistep precipitation reaction. 98
Biochemistry biomarkers of interest were measured using a Beckman Synchron LX20 and 99
Beckman Coulter UniCel ® DxC800 (Beckman Coulter, Fullerton, CA, USA). 100
Stata SE/16.0 (StataCorp, College Station, TX, USA) was used for data analysis, as this enabled 101
for the adjustment needed to account for the complex design. 102
2.3. Data Analysis 103
The data in this cross -sectional study were analyzed for various degrees of lead exposure based 104
on the distribution of BLL within the database. The study examined the role of stress , as measured 105
by AL, on markers of liver injury among individuals differe ntially exposed to low lead levels. 106
The geometric mean values of the markers and variables of interest were firstly explored at 107
various quartiles (Q1,Q2, Q3, and Q4) of lead exposure based on the distribution of BLLs in the 108
database. Q1 was defined as tho se with BLL less than or equal to 0.8 μg/dL and had N=3739 people. 109
Q2 was defined as those with BLL of 0.8 -1.21 μg/dL and consisted of N=3765 people. Q3 included of 110
those with BLL of 1.21-2.92 μg/dL and consisted of N=3754 people, with Q4 consisting of v alues 1.92 111
μg/dL and above and consisting of N=3761 people. 112
Simple linear regression was performed to examine associations between AL and the markers 113
of interest (AST, ALT, ALP, and GGT) among those exposed to different quartiles of lead. The data 114
was adjusted for age, sex, alcohol consumption, and smoking, as these variables have been shown to 115
alter liver function [33-35]. Each exposure-outcome combination was examined in individual model s. 116
In this study, AL was the dependent variable, with the clinical markers of interest (AST, ALT, 117
ALP, and GGT) being the independent variables. Stata SE 16.0 used for the data analysis which 118
factored in the complex design of the database to ensure the ana lysis was representative [18] of the 119
US general adult population. The Shapiro -Wilk revealed the necessity of natural log -transformation 120
of variables of interest due to the lack of a normal distribution. P -values less than or equal to 0.05 121
were considered signifi cant. 122
3. Results 123
3.1. Study Variables Among Individuals Exposed to Quartiles of Lead Exposure. 124
The geometric mean value s of individuals exposed to lead levels within the four quartiles were 125
analyzed for all critical variables in this study. Results indicated that for most values as lead levels 126
increased, so did the markers of interest. The results can be found in Table 1 below. 127
Table 1. The geometric mean values of Variables of Interest within Quartiles of Lead Exposure . 128
Variable Quartile 1 Quartile 2 Quartile 3 Quartile 4 p-Value
BLL(SE) 0.584
(0.003) 0.992
(0.003) 1.52 (0.006) 3.23 (0.054) p<0.0001 for all
Age(SE) 27.1 (0.337) 35.6 (0.335) 43.5 (0.545) 50.6 (0.599) p<0.0001 for all
Gender Male: 33.9
Female:
66.1 Male: 46.8
Female:
53.2 Male: 55.3
Female:
44.7 Male: 62.4
Female:
37.5 p<0.0001 for all
BMI 25.9 (0.159) 25.3 (0.204) 26.0 (0.218) 25.9 (0.184) p>0.05 for all
Allostatic Load 1.93 (0.058) 2.29 (0.040) 2.59 (0.038) 2.76 (0.046) p<0.01 for all

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AST 24.5 (0.343) 25.5 (0.203) 26.3 (0.250) 27.2 (0.358) p<0.05 for all
ALT 22.9 (0.381) 25.7 (0.407) 26.0 (0.325) 26.2 (0.444) p<0.0001 for Q1 to
Q2,Q3,and Q4
GGT 20.4
(0.555) 25.2 (0.669) 28.5 (0.537) 33.4 0.829) p<0.001 for all
Alkaline
Phosphatase 76.9 (1.35) 76.2 (0.775) 73.1 (0.695) 74.7 (0.695) p<0.05 for Q3 to Q2 and Q1
3.2. Association of AL with markers of interest in low lead -exposed participants 129
The relationship between AL and the ma rkers among t hose exposed to quartiles of lead levels 130
was explored using linear regres sion models. Results indicated that even after adjusting for critical 131
confounding factors, chronic physiological stress significantly altered the liver function among lea d- 132
exposed individuals. The results are found in Table 2. 133
Table 2. Simple linear regres sion—Relationship of AL with hepatic -markers in Quartiles of lead 134
exposure. 135
Variable Quartile 1
Coef.lnAL
Adjusted
(SE)* p-
Value Quartile 2
Coef.lnAL
Adjusted
(SE)* p-
Value Quartile 3
Coef.lnAL
Adjusted
(SE)* p-
Value Quartile 4
Coef.lnAL
Adjusted
(SE)* p-Value
AST 0.178 (0.100) 0.087 0.121 (0.074) 0.111 0.173 (0.051) 0.002 -0.087
(0.044) 0.056
ALT 0.195 (0.073) 0.012 0.165 (0.063) 0.014 0.236 (0.037) 0.0001 -0.007
(0.035) 0.847
GGT 0.149 (0.056) 0.012 0.151 (0.035) 0.0001 0.166 (0.035) 0.0001 0.049 (0.028) 0.094
Alkaline
Phosphatase 0.301 (0.102) 0.006 0.167(0.069) 0.021 0.236 (0.057) 0.0001 0.137 (0.061) 0.033
*adjusted for age, sex, smoking and alcohol consumption 136
4. Discussion 137
4.1. Stress and Liver Health among those Differentially Exposed to Lead 138
Exposure to distress can come from several sources such as occupation, family life, emotional 139
problems, and can alter the health of various populations [36-38]. When combined with the exposure 140
to lead via water, air, soil, dust, and food [39-41], the damage to the health of populations may suffer 141
a combined or synergistic effect [16, 26, 42 -45]. 142
Allostasis is the process through which individuals maintain physiological balance by altering 143
parameters within the body and matching them to environmental demands [46]. Allsostais, which 144
seeks to adapt to the demands of the environment [47], is similar to homeostasis but is different in 145
that homeostasis defines health as a state in which all physiological parameters must operate within 146
non-changing setpoints (i.e blood pressure of 120/80 mmHg), with those that cannot be brought down 147
to those values requiring pharmaceutical intervention. With allostasis, individuals can appropriatel y 148
respond t o challenges but , if the challenges are continu ous do not turn off, then the body, rather than 149
going to a lower set point, adapts at the higher set point. When the setpoint changes, it is called 150
allostatic load. The ‘wear and tear’ on the body in the adaptation to the new setpoint is critical to 151
understanding the long term health effects [48]. 152
This study sought to examine the effects of chro nic stress, as measured by AL, on markers of 153
liver injury among those differentially exposed to lead in the US general adult population. Critical 154
findings within this study indicate that chronic stress, when combined with low -level lead exposure, 155

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alters liver markers toward pathology. This study builds on work, which highlights the dangers of 156
low-level lead expo sure [49] on human health. It also most critically highlights the risks of chronic 157
unrelenting stress when combined with environmental exposures such as lead and speaks to the dual 158
burden of environmental and social exposures on health. 159
The association between AL and AST and ALT were paradoxically significant for the lowest 160
quartiles but were not significant for the highest one. This may potentially be due to several factors 161
such as length of exposure for the lower quartiles as compared to the highest one but this is not clear . 162
4.2. Limitations 163
Due to the cross -sectional nature of the stud y, the exposure and outcome were measured at one 164
point in time and did not allow for examining temporality. It should be noted that the half -life of lead 165
in blood is roughly 35 days, and it serves as a reflection of acute external exposure to lead. Bone 166
lead levels in concert with blood lead levels would have painted a more holistic picture of lea d 167
exposure levels. Another limitation is in the variables available. Due to the lack of availability for 168
variables relating to social support and other measures of resilience they were not adjusted for in this 169
study but may offer critical insight into exp osure risk. 170
5. Conclusions 171
Low-level lead exposure in combination with chronic physiological stress alters hepatic function 172
with increasing levels of lead exposure resulting in worse outcomes. To improve the health of 173
populations, a holistic approach is needed to both decrease their exposure to toxicants and promote 174
behaviors and environments, which reduce or prevent chronic stress. 175
Author Contributions: : Conceptualization, E.O .-G.,; methodology, E.O .-G.; software, E.O .-G.; validation, E.O .- 176
G.,; formal analysis, E.O .-G.; investigation, E.O .-G.; resources, E.O .-G.; data curation, E.O .-G.; writing—original 177
draft preparation, E.O .-G.; writing —review and editing, E.O .-G.; visualization, E.O .-G.; supervision, E.O .-G.; 178
project administration, E.O .-G.; funding acquisition, E.O .-G. 179
Funding: This resear ch received no external funding 180
Conflicts of Interest: The author declares no conflict of interest. 181
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