behavioral, hormonal, and tissue biomarkers of …
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BEHAVIORAL, HORMONAL, AND TISSUE BIOMARKERS OF STRESS REGULATION IN YOUNG ADULT RATS AFTER DIFFERENT SCHEDULES OF EARLY LIFE STRESS:
EUSTRESS VERSUS DISTRESS
by
Emily T Stoneham A Dissertation
Submitted to the Graduate Faculty
of George Mason University in Partial Fulfillment of
The Requirements for the Degree of
Doctor of Philosophy Neuroscience
Committee: _________________________________ Dr. Ted Dumas, Dissertation Director _________________________________ Dr. Kim Blackwell, Committee Member _________________________________ Dr. Dan Cox, Committee Member _________________________________ Dr. Daniela Kaufer, Committee Member _________________________________ Dr. James Olds, Director, Krasnow Institute for
Advanced Studies _________________________________ Dr. Donna M. Fox, Associate Dean, Office of
Student Affairs & Special Programs, College of Science
_________________________________ Dr. Peggy Agouris, Dean, College of Science Date:_____________________________ Spring Semester 2014 George Mason University Fairfax, VA
Behavioral, Hormonal, and Tissue Biomarkers of Stress Regulation in Young Adult Rats after Different Schedules of Early Life Stress: Eustress versus Distress
A Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at George Mason University
by
Emily T Stoneham Master of Aeronautical Science
Embry-Riddle Aeronautical University, 2006
Director: Theodore C. Dumas, Assistant Professor Department of Neuroscience
Spring Semester 2014 George Mason University
Fairfax, VA
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This work is licensed under a creative commons
attribution-noderivs 3.0 unported license.
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DEDICATION
This is dedicated to my wonderful and supporting husband John, and our dachshunds past and present; Calvin, Gretchen, and Sable; without whom I would be lost.
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ACKNOWLEDGEMENTS
I would like to thank my parents for never giving up on me no matter what bizarre situations I find myself in. Without your support, I would never have broken free, found true love (in husband and dog form), or been able to find the confidence I so desperately needed. A special thank you goes out to Lt. Col. Steve Harmon (ret.), for whom I owe the daring rescue from hell that gave me the impetus to go back to school and find out who I really was. Thank you to Ted Dumas for keeping me motivated. I would not have found my calling if had it not been for your positive and supportive mentorship. You have pushed me out of my comfort zone and shown me the possibilities that lie in those unfamiliar places, waiting to be discovered. I would like to thank Daniela Kaufer and Aaron Friedman for the patience to help me understand difficult protocols (even when my questions were borderline ridiculous), and Dan Cox for introducing me to the kingdom of the flies. I must also thank Jim Olds, for his enlightening words when I was struggling to understand the inner workings of the academic world. I absolutely could not have completed this project without three very generous and wonderful people; Dan McHail, Sabina Samipour, and Sarah Albani. Thank you for encouraging me to be a good person as well as a good scientist. Ebube Utomi, without your wonderful animal care, this project would not have been. Thank you for your unceasing dedication to the animals. To the SMART program, thank you for giving me the opportunity to fulfill a long time dream. Without your funding, I would never have made it this far.
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TABLE OF CONTENTS
Page List of Tables .................................................................................................................... vii List of Figures .................................................................................................................. viii List of Abbreviations ......................................................................................................... ix Abstract ............................................................................................................................... x Chapter One: Introduction .................................................................................................. 1 Chapter two: Methods ......................................................................................................... 5
Subjects ........................................................................................................................... 5 Maternal Separation (MS) ............................................................................................... 6 Surgery ............................................................................................................................ 9 Vector Production ........................................................................................................... 9 Drug Description ............................................................................................................. 9 Vector and Drug Delivery ............................................................................................. 10 Morris Water Maze ....................................................................................................... 10 Vector Expression Confirmation ................................................................................... 12 Peripheral Tissue Analysis ............................................................................................ 12 Corticosterone Analysis ................................................................................................ 13
Chapter three: Results ....................................................................................................... 14 Behavioral Assessment ................................................................................................. 14
MWM Performance: Vector Effects .......................................................................... 14 MWM Performance: Stress Effects ........................................................................... 20
CORT Assay ................................................................................................................. 26 Tissue weights ............................................................................................................... 30
Body Weight .............................................................................................................. 30 Adrenal Gland Weight ............................................................................................... 31 Thymus Gland Weight ............................................................................................... 35
Chapter Four: Discussion .................................................................................................. 39
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Chapter Five: Conclusions ................................................................................................ 45 Chapter Six: Lessons learned ............................................................................................ 46
Protocol Difficulties ...................................................................................................... 46 Corticosterone Analyses ............................................................................................ 46 Personnel ................................................................................................................... 46 Infusion Troubleshooting .......................................................................................... 47 Surgery Troubleshooting ........................................................................................... 48
Addendum ......................................................................................................................... 49 For your amusement ...................................................................................................... 49
The Neuron Song ....................................................................................................... 49 Lab Rat 4 Life ............................................................................................................ 50
References ......................................................................................................................... 51 Citations for Table 1 ...................................................................................................... 58
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LIST OF TABLES
Table Page Table 1 Overview of prior maternal separation stress research .......................................... 4 Table 2 Results comparison: Prior research versus this study .......................................... 41
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LIST OF FIGURES
Figure Page Figure 1 Event Overview .................................................................................................... 8 Figure 2 MWM pool with spatial cues ............................................................................. 11 Figure 3 Escape learning by vector and MS condition ..................................................... 15 Figure 4 Quadrant dwell and distance to goal location for immediate probe by MS condition and vector .......................................................................................................... 17 Figure 5 Quadrant dwell and distance to goal location drug ratio for twenty-four hour probe by MS condition and vector .................................................................................... 19 Figure 6 Escape learning by MS condition and block ...................................................... 21 Figure 7 Quadrant Dwell for immediate probe by MS condition ..................................... 22 Figure 8 Distance to goal location for the immediate probe by MS condition ................. 23 Figure 9 Quadrant dwell for twenty-four hour probe by Drug and MS condition ........... 24 Figure 10 Distance to goal location for twenty-four hour probe drug ratio by MS condition ........................................................................................................................... 26 Figure 11 Average CORT by MS condition and vector ................................................... 27 Figure 12 Average CORT by MS condition and drug ...................................................... 28 Figure 13 CORT versus distance by MS condition and drug ........................................... 29 Figure 14 Body weight by MS condition .......................................................................... 31 Figure 15 Adrenal gland weight by MS condition and vector .......................................... 32 Figure 16 Adrenal gland weight by MS condition ............................................................ 34 Figure 17 Thymus gland weight by MS condition and vector .......................................... 36 Figure 18 Thymus weight by MS condition ..................................................................... 38
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LIST OF ABBREVIATIONS
Artificial Cerebral Spinal Fluid .................................................................................. ACSF BDNF Receptor Blocking Drug .................................................................................. K252a Brain Derived Neurotrophic Factors ........................................................................... BDNF Corticosterone ............................................................................................................. CORT Daily Stress .................................................................................................................. P2-11 Dentate Gyrus .................................................................................................................. DG Estrogen Receptor/ Glucocorticoid Receptor Chimera ............................................... ERGR Glucocorticoid .................................................................................................................. GC Glucocorticoid Receptors ................................................................................................. GR Goal-Opposite Quadrant ................................................................................................ G-O Green Fluorescent Protein .............................................................................................. GFP Hypothalamic-pituitary-adrenal axis ............................................................................ HPA In Situ Hybridization ....................................................................................................... ISH Intermittent Stress ........................................................................................................... INT Maternal Separation ......................................................................................................... MS National Institutes of Health .......................................................................................... NIH No Difference ................................................................................................................... ND Postnatal Day ...................................................................................................................... P Quadrant ..................................................................................................................... QUAD Return to Baseline .......................................................................................................... RTB Transdominant Glucocorticoid Receptor .................................................................... TdGR Unstressed (Non-Handled Control) .............................................................................. CON
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ABSTRACT
BEHAVIORAL, HORMONAL, AND TISSUE BIOMARKERS OF STRESS REGULATION IN YOUNG ADULT RATS AFTER DIFFERENT SCHEDULES OF EARLY LIFE STRESS: EUSTRESS VERSUS DISTRESS
Emily T Stoneham, Ph.D.
George Mason University, 2014
Dissertation Director: Theodore C. Dumas
Individuals experiencing stressful early life environments due to isolation, abuse, or
neglect, are predisposed not only toward physically debilitating illnesses (coronary and
metabolic diseases) but also potentially devastating neuropsychiatric disorders (post-
traumatic stress disorder, memory impairment, depression). Memory loss in adults
exposed to early life stress is primarily the result of an altered cortisol homeostasis and
most often involves hippocampal dysfunction. Interestingly, timing of early life stress
with respect to developmental stage and predictability of stressful episodes is critical in
determining the magnitude of future adult disorders. Conventional early life stress studies
in rats use one of two maternal separation paradigms. In the daily stress model, separation
occurs every day, typically during the first postnatal week. For the intermittent stress
model, separation occurs more randomly. Because different separation schedules have
been employed independently, varying reports could result from any number of
undocumented variables. Moreover, prior work has focused on outcome in middle aged
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and older rats, preventing discovery of early biomarkers for impending memory loss. As
such, we applied daily or intermittent maternal separation and, in young adulthood, we
examined behavioral and hormonal variables indicative of hippocampal integrity. We
discovered that daily maternal separation impaired spatial learning, while intermittent
maternal separation tended to improve spatial memory in young adults. This research also
showed that daily and intermittent separation paradigms produce opposing hormonal
profiles that may serve as biomarkers predictive of impending memory dysfunction at
older ages. Interestingly, elevation in stress hormone levels became dependent on brain-
derived neurotrophic factor following intermittent separation. Attempts to recuperate
recover normal spatial cognition by overexpressing glucocorticoid and estrogen related
proteins in the hippocampus proved ineffective.
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CHAPTER ONE: INTRODUCTION
Early life chronic stress has long been associated with failure to thrive. More
often than not, survivors of early life stress display neuropsychological problems,
including depression, schizophrenia, post-traumatic stress disorder, and memory
dysfunction. Perhaps all of these conditions, but especially depression and memory loss,
involve impaired function and atrophy of the hippocampus (Carrión, Haas, Garrett, Song,
& Reiss, 2010; Lindauer, Olff, van Meijel, Carlier, & Gersons, 2006; Lupien et al., 1998;
Palazidou, 2012). The hippocampus also provides negative feedback inhibition to the
hormonal stress response [hypothalamic-pituitary-adrenal (HPA) axis] and it is thought
that memory impairment in adults that were abused in childhood is at least in part a
function of dysregulation of the HPA axis and exaggerated release of cortisol. Since
lasting elevations in cortisol cause hippocampal damage, it is possible that early life
stress sets up a positive feedback loop whereby lasting elevations in cortisol during
development impair systems that regulate cortisol release later in life.
Maternal separation (MS) is the most common rodent model of early life stress in
humans (Nishi, Horii-Hayashi, Sasagawa, & Matsunaga, 2013; Teicher, Tomoda, &
Andersen, 2006). Typically, rat pups are removed from the home cage for varying
numbers of hours per day and varying numbers of days during the first three postnatal
weeks (Table 1). Results of MS become manifest later in life as reduced hippocampal
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volume along with elevated plasma corticosterone (CORT), lower levels of stress
hormone CORT (glucocorticoid) receptors and lower levels of the neuroprotective factor,
brain derived neurotrophic factor (BDNF) in the hippocampus (Chourbaji, Brandwein, &
Gass, 2010). Alterations in CORT receptors and BDNF have been shown previously to
regulate memory performance (McEwen et al., 1997; D Suri & Vaidya, 2013; I. C.
Weaver, 2009). It is believed that changes in CORT receptors and BDNF levels resulting
from MS increase susceptibility to hippocampal related impairments later in life (Heim,
Plotsky, & Nemeroff, 2004; O’Sullivan et al., 2011; Deepika Suri et al., 2013). However,
how alterations in CORT receptors and BDNF levels affect the hippocampus and
memory ability in young adulthood has not been investigated. Understanding how MS
impacts the hippocampus of young adults is important as it may reveal alterations in
cognitive ability heretofore unknown or may uncover behavioral or biological markers of
impending memory failure.
Maternal separation schedules typically used to create early life chronic stress,
vary with regard to three basic variables; age of pups at separation, number of
separations, and schedule of separation prior to weaning. Table 1 provides an outline of
the paradigms used for induction of chronic stress in the last 20 years. Although it is by
no means all-inclusive, it is indicative of the disparity in research methods across
laboratories. Most research looking into the effects of early life stress focus on a daily
stress protocol and yet refer to it as unpredictable, intermittent, or variable stress (Ladd et
al, 2005; Kikusui et al, 2006; Greisen et al 2005; Gogberashvili et al, 2008). This type of
research also points to differences in plasma corticosterone level and adrenal and thymus
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weights as biomarkers for future cognitive and behavioral impairment (Slotten et al.,
2006; Plotsky and Meaney, 1993; O’Sullivan et al., 2011; Neumann et al., 2005; Marais
et al., 2008; Lippmann et al., 2007). To understand how these different MS schedules
may be influencing the stress response, we investigated the effects of continuous and
intermittent MS schedules on learning and memory performance in a hippocampal-
dependent maze task in young adult rats and assessed CORT and BDNF signaling. We
discovered opposing effects of continuous and intermittent MS on spatial learning and
memory and regulation of plasma CORT by BDNF. Continuous MS impaired spatial
learning while intermittent MS tended to enhance spatial memory. Furthermore,
corticosterone regulation became somewhat reliant on BDNF signaling following
intermittent MS. Combined, the results show that different schedules of MS stress can
produce different behavioral and biological outcomes in young adults. The findings point
to enhanced stress susceptibility resulting from continuous MS and enhanced resilience
resulting from intermittent MS, which might serve as predictors for the presence or
absence of more severe cognitive decline in later life.
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Table 1 Overview of prior maternal separation stress research This is a representative sample of MS research performed in the last two decades. Red arrows indicate impairment, green an improvement, open arrows indicate that the overall effect is dependent on other factors. Findings in italics represent differences between tested ages (same MS), Items in bold represent differences between MS groups (same age at testing). RTB = Return to Baseline, ND = No Difference
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CHAPTER TWO: METHODS
Subjects All experiments were conducted in accordance with the guidelines specified by the
National Institutes of Health (NIH Guide for the Care and Use of Laboratory Animals)
and approved by the Institutional Animal Care and Use Committee of George Mason
University. Long-Evans hooded rats bred in-house were used for this study. Day of birth
was designated as P0. After birth, litters were culled to twelve pups, with even numbers
of male and female rats where possible. Animals were housed together with their mother
in standard laboratory rat cages (20.3cm H X 30.5cm L X 35.5cm W). Animals were
housed under standard laboratory conditions on a 12 h light/dark cycle with lights on at
7:00 AM. in a room with controlled temperature (23 ± 2 ºC). Fresh food pellets (7012
Harlan Teklad LM-485) and drinking water were available ad libitum. Dams and their
litters were randomly assigned to either a non-handled control (CON) or Maternal
Separation (MS) group. Given that lesser effects of MS on spatial learning and memory
were expected in young adults compared to prior studies using older animals, and
because male rats tend to show more robust effects of MS, only male rats were used in
this study (Kalinichev, Easterling, Plotsky, & Holtzman, 2002; Lehmann, Pryce,
Bettschen, & Feldon, 1999; Oreland et al., 2009; Slotten et al., 2006).
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Maternal Separation (MS) MS was carried out using procedures described elsewhere (Kosten and Kehoe, 2010,
Matthews and Robins, 2003). Briefly, MS dates for the intermittent (INT) litters were
chosen by utilizing Random.org to make a randomized list from days P2 to P20, and then
taking the first ten days that came up on the list. Requirements for the randomization
were that at least three of the days fall between P2-P7, and that there were no more than
three consecutive days anywhere on the schedule. If adjustments had to be made, the next
date on the randomized list was chosen to replace the aberrant day and the requirements
checked again, repeating as necessary. For the predictable daily stress, animals were
separated for ten consecutive days from P2-11.
Litter separations from the dam utilized similar procedures as described elsewhere
(Aisa B Fau - Tordera et al., 2007; Kosten & Kehoe, 2010). Briefly, on the first day of
MS the dam from a single litter was removed to a separate transfer cage, male pups were
removed to a different transfer cage, and female pups were removed to a new, clean
temporary home cage, before the dam was reunited with the female pups in the new cage.
The dam and female pups remained in the housing room, while the male pups were
brought to an adjacent room and placed in unlined, individual plexiglass isolation
chambers (15 cm L x 15 cm W x 10 cm H). For pups in the INT group, MS that occurred
after P14 required the use of clear, plexiglass cage covers to prevent escape. Pups were
warmed with an infrared heat lamp placed over the isolation chambers. The side of the
chamber closest to the lamp was maintained 32 ºC, the middle of the chamber at 30 ºC
and the farthest point at 28 ºC. To mask vivarium noise and the sounds of the other pups,
white noise was played through speakers at 75-80dB at the level of the isolation
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chambers, as verified by an iPhone digital noise meter (Decibel Meter Pro). At the end of
the 3-hour period, male pups were put back into their transfer cage and returned to the
housing room. The dam was moved to a temporary cage while male and female pups
were moved back to the permanent home cage at which time the dam was moved back to
the permanent home cage. The same temporary cage was used until MS for each litter.
The CON litters were left completely undisturbed until weaning except for routine
facility care and a single cage change by the experimenter. Male pups were singly housed
after weaning, and handled daily (weekdays) for three minutes from P22 until infusion at
P30. Three days post cannulation surgery (P34), handling was continued along with brief
head restraint and mock cannula insertions (Fig 1).
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Figure 1 Event Overview This timeline shows a schedule overview for any given litter, from birth to tissue extraction.
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Surgery Adult animals underwent stereotaxic surgery at P30 to implant indwelling cannulae
placed dorsal to the apex of the DG in both hippocampi (-3.6 mm anteroposterior and
±2.5 mm mediolateral from bregma, -3.0 mm dorsoventral from dura) (Dumas et al.,
2010). Rats were weighed prior to surgery and had their tail tattooed with a unique
identifier during the surgery. Post surgery, rats were given ketoprofen (5mg/kg)
subcutaneously two times a day for three days. Rats were allowed ten days to recover
from cannulae implant.
Vector Production The three neuroprotective vectors that were used in this study have been described
previously (Kaufer et al., 2004; Dumas et al., 2010). All three vectors were designed to
express enhanced green fluorescent protein (eGFP), the control vector expressing only
eGFP. One vector expresses a transdominant negative glucocorticoid receptor (TdGR)
and another, an estrogen receptor-glucocorticoid receptor chimera (ERGR). The TdGR
and ERGR chimeric receptor genes are under transcriptional control of viral α4 promoter
and, in these vectors, the eGFP reporter gene is driven by the α22 promoter (Kaufer et
al., 2004). Expression of eGFP is driven by the α4 promoter in the control plasmid.
Plasmids were packaged into HSV-1 amplicons and were received as a kind gift from Dr.
Ki Ann Goosens (MIT).
Drug Description A selective BDNF receptor (tyrosine receptor kinase B; TrKB) blocker (K252a)
was used to prevent BDNF binding and further downstream signaling through
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phosphorylation of the TrKB receptor. Solubilized K252a (1mM in DMSO from Sigma
Aldrich; K2015-200 µl) was diluted as needed with ACSF to a concentration of 68 ng/µl.
Vector and Drug Delivery Animals were randomly selected for infusion with GFP, ERGR, or TdGR vectors. On
P40, a microinfusion pump was used to infuse vector at a rate of 0.3 µl per minute for a
total of 2.0 µl per hemisphere. One hour prior to the 24-hour recall probe (P43), animals
were infused with either K252a or artificial cerebrospinal fluid (ACSF) at a rate of 0.3 µl
per minute for a total of 0.8 µl per hemisphere.
Morris Water Maze The Morris water maze (MWM) was used to test learning and memory. MWM
procedures were followed as described previously (Dumas et al., 2010) except that the
water was made opaque with non-toxic white paint and the escape platform was covered
with white, plastic, shelf-liner. The maze was a black circular pool (1.7 m in diameter)
filled with tap water (24-27 ºC) to a level that covers a stationary escape platform (17.5
cm diameter) by 1-2 cm. Surrounding the pool were white curtains that had black spatial
cues sewn onto them (Fig 2).
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Figure 2 MWM pool with spatial cues Platform is just visible under the tinted water. Curtains surround the pool and the cues sewn onto them consist of multiple vertical lines, alternating horizontal stripes, and geometric objects (circle, triangle, square). Equipment was located 6-8 feet from the pool, and housing cages were kept in a biohood
on an opposite wall ~ 15 feet from the pool. Training was performed in six blocks of
three trials, each with a 15-30 minute interblock interval. The goal quadrant was varied
across testing cohorts. Four starting locations, offset from the platform locations by 45º
were equally spaced around the pool. The starting location for each trial was chosen
pseudo-randomly. Just prior to training, each rat was positioned to climb onto the escape
platform three times from different directions. The first block of training trials
immediately followed climbing practice. For each training trial, the animal was allowed a
maximum of one minute to find the platform. At the end of each trial, a fifteen second
latency was imposed for the rat to spend on the platform. If the rat was unable to find the
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platform after one minute, it was gently guided to the platform where it would remain for
fifteen seconds. After the sixth training block, an immediate probe trial was performed in
which the platform was removed and the rat was allowed to explore the maze for one
minute. The platform was then replaced, and three more refresher trials were performed.
Twenty-four hours later, the rat was placed in the MWM for a second, one-minute probe
trial. For each training trial, latency to escape and mean swim speed were calculated. For
each probe trial, the amount of time spent in each quadrant and distance to platform
center were analyzed.
Vector Expression Confirmation Neuronal infection was confirmed by eGFP expression in brain sections from MWM
tested animals. Animals were anesthetized and perfused with 4% paraformaldehyde 35-
45 minutes following the 24-hour probe trial. Brains of these animals were removed and
placed into 30 % sucrose overnight and sectioned on a cryostat at 30 µm thickness.
Vector expression was identified through visualization of DG granule cells on an
epifluorescent microscope (490 nm excitation wavelength). Only a handful of eGFP-
positive cells were observed across vectors.
Peripheral Tissue Analysis Following anesthetization (Isoflurane, > 5 % vapor) and before brain extraction or
perfusion, adrenal and thymus glands were removed and placed on filter paper soaked in
artificial cerebrospinal fluid (ACSF). Adrenal glands were dissected of fat and
surrounding tissue and weighed. The thymus gland was also removed and weighed.
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Corticosterone Analysis Trunk blood was taken either at the time of decapitation or by nicking the renal
artery. Blood was immediately centrifuged at 10,000 rpm at 4 ºC for five minutes. Plasma
was then poured off into fresh Eppendorf tubes and stored at -20 until assayed with a
corticosterone ELISA kit (Enzo life sciences ADI-900-097).
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CHAPTER THREE: RESULTS
Behavioral Assessment
MWM Performance: Vector Effects Although there was minimal evidence of vector expression, analysis for vector
effects on behavior was performed. Figure 3 shows mean escape latency for each vector
group at each block of training. Mean escape latency decreased significantly across
Vector training blocks [F(4.169, 679.595) = 206.993, p < 0.001; Greenhouse-Geisser
correction for non-sphericity], but there was no main effect of vector [F(2) = 0.524, p =
0.593] or vector by condition [F(4) = 0.360, p = 0.837], indicating all groups learned to
escape the water at a similar rate and to a similar extent.
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Figure 3 Escape learning by vector and MS condition Escape latency in seconds for the average amount of time it took animals in each stress condition (CON, P2-11, INT) by vector (eGFP, ERGR, TdGR) to find the hidden platform over 6 blocks. The three trials were averaged within each block. There was no effect of vector on escape learning. Sample sizes: CON: eGFP = 15, ERGR = 24, TdGR = 25; P2-11: eGFP = 18, ERGR = 17, TdGR = 18; INT: eGFP = 17, ERGR = 25, TdGR = 13
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For the immediate probe, the mean dwell time per quadrant was calculated for each
vector group (Fig 4a). Chi Square tests for eGFP [Chi2 (3, 50) = 65.040 p < 0.001],
ERGR [Chi2 (3, 66) = 75.212 < 0.001], and TdGR animals [Chi2 (3, 55) = 77.727 p <
0.001], and the shapes of the distributions suggest all groups displayed a goal quadrant
bias. We also analyzed the distance to the platform location at each second for the first
fifteen seconds to examine platform approach behavior. A two-way repeated measures
ANOVA for distance to the escape platform revealed a main effect of sample time [F(14,
2366) = 79.925) , p < 0.001], but no effect of vector (Fig 4b). Taken together, these
results indicate that there was no impact of vector on escape or spatial learning.
17
Figure 4 Quadrant dwell and distance to goal location for immediate probe by MS condition and vector A) Bar graphs showing mean quadrant dwell time for each vector-MS combination. Vector groups are separated by column and MS condition is represented by row where the left set of quadrant dwell times represent eGFP, the middle represent ERGR, and the right, TdGR. Animals spent considerable time in the goal quadrant regardless of vector. B) The average distance animals came to the goal location for each of the first 15 seconds of the immediate probe. There was no effect of vector on this distance to goal location during the immediate probe. Sample sizes: CON: eGFP = 15, ERGR = 24, TdGR = 25; P2-11: eGFP = 18, ERGR = 17, TdGR = 18; INT: eGFP = 17, ERGR = 25, TdGR = 13
The same analyses applied to the immediate probe were also applied to the 24-hr
probe. Chi Square analyses of quadrant dwell times indicated no significance for any
vector group indicating substantial forgetting of platform location across the 24-hr
retention period. (Fig 5a).
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Distance to goal location per second for each animal receiving K252a was
normalized by the mean distance to goal location per second for all ACSF animals
(K252a /ACSF ratio). These ratios were averaged across subjects within each vector
group. Vector delivery had no statistically significant impact on the K252a/ACSF ratio
[F(6.900, 217.340) = 1.578, p = 0.144; Greenhouse-Geisser correction for non-
sphericity], and there was no main effect of vector [F(2) = 1.591, p = 0.212] (Fig 5b).
These results suggest no impact of neuroprotective vector expression on spatial memory
following massed training trials.
In summary, there was no effect of vector delivery on escape learning, spatial
learning, or spatial memory, so data were collapsed across vector for subsequent behavior
analyses.
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Figure 5 Quadrant dwell and distance to goal location drug ratio for twenty-four hour probe by MS condition and vector A) Bar graphs showing mean quadrant dwell time for each vector-MS combination. Vector groups are separated by column and MS condition is represented by row where the left set of quadrant dwell times represent eGFP, the middle represent ERGR, and the right, TdGR. B) Distance for K252a animals divided by the corresponding mean distance for ACSF. B) Distance for K252a animals divided by the corresponding mean distance for ACSF. There was no effect of vector on distance to goal location during the twenty-four hour probe. Sample sizes: CON: eGFP = 15, ERGR = 21, TdGR = 21; P2-11: eGFP = 18, ERGR = 15, TdGR = 13; INT: eGFP = 17, ERGR = 25, TdGR = 13
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MWM Performance: Stress Effects Figure 6 shows mean escape latency for each MS condition at each block of
training. Mean escape latency decreased significantly across training blocks [F(4.144,
750.128) = 228.472, p < 0.001; Greenhouse-Geisser correction for non-sphericity], and
there was a significant main effect of MS condition [F(2) = 3.681, p < 0.05]. Animals in
the P2-11 group displayed higher escape latencies across training blocks (Tukey; p <
0.005). CON and INT groups were not different, suggesting an escape learning
impairment selective to P2-11 stress.
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Figure 6 Escape learning by MS condition and block Escape latency in seconds for the average amount of time it took animals in each stress condition (CON, P2-11, INT) to find the hidden platform over 6 blocks. The three trials were averaged within each block. P2-11 animals were consistently slower to find the platform than CON or INT animals. Sample sizes: CON = 68; P2-11 = 53; INT = 63 For the immediate probe, mean dwell time per quadrant was calculated for each MS
group (Fig 7). Chi Square tests and distribution shape indicated a goal quadrant bias for
all MS groups; CON [Chi2 (3, 68) = 107.647 p < 0.001], INT [Chi2 (3, 63) = 76.710 p <
0.001], P2-11 [Chi2 (3, 53) = 49.866 p < 0.001] (Fig 8).
22
Figure 7 Quadrant Dwell for immediate probe by MS condition For each quadrant collapsed by condition, the bars show the amount of time the animals spent searching the left (L), goal (G), right (R), or opposite (O) quadrants. A separate Chi square test comparing all four quadrants was performed for each condition (CON, P2-11, INT). ***p < 0.001 Sample sizes: CON = 68; P2-11 = 53; INT = 63
We also analyzed the distance to the platform location at each second for the first fifteen
seconds of the immediate probe to examine platform approach behavior. A two-way
repeated measures ANOVA for the distance to the goal location measured at one Hz
across the first fifteen seconds revealed main effects of MS condition [F(2) = 3.370, p <
0.05] and sample time [F(3.688, 667.490) = 82.615, p < 0.001; Greenhouse-Geisser
correction] (Fig 8). Animals in the P2-11 group were consistently farther from the goal
location than the CON group [Tukey; p < 0.05].
23
Figure 8 Distance to goal location for the immediate probe by MS condition Each point marks the average distance between the nose of the animal and the goal location, for each of the first 15 seconds of the immediate probe by MS condition (CON, P2-11, INT). P2-11 animals did not orient as directly as the CON or INT animals. Sample sizes: CON = 68; P2-11 = 53; INT = 63 These results indicate that although P2-11 animals searched the goal quadrant to a similar
extent as the CON and INT animals, their approach proximity was reduced, suggesting
impaired spatial learning.
Spatial memory was assessed by performance in the twenty-four hour probe trial.
While a Chi-square analysis revealed a significant distribution for quadrant dwell times
for P2-11 animals after delivery of K252a [Chi2 P2-11 (3, 46) = 11.391, p < 0.05], there
24
was no clear goal quadrant bias. Neither CON nor INT showed a quadrant preference
[Chi2 CON (3, 62) = 2.774 p = 0.428; INT (3, 63) = 7.794, p = 0.0.050] (Fig 9).
Figure 9 Quadrant dwell for twenty-four hour probe by Drug and MS condition For each animal, the amount of time spent in each quadrant was recorded and the quadrant with the highest value scored with a ‘1’. A) Quadrant dwell for each MS condition in the ACSF drug group. B) Quadrant dwell for each MS condition in the K252a drug group. Each quadrant’s score was summed for all animals in that group, and a chi-square performed over the 4 quadrants. For the twenty-four hour probe, no group showed preference for a particular quadrant. Sample sizes: CON = 62; P2-11 = 46; INT = 63.
25
Distance to goal location per second for each animal receiving K252a was
normalized by the mean distance to goal location per second for all ACSF animals
(K252a/ACSF ratio). These ratios were averaged across subjects within each MS group.
There was no main effect of sample time [F(3.313, 248.456) = 1.341, p = 0.260;
Greenhouse-Geisser correction for non-sphericity]. However, there was a main effect of
MS condition [F(2) = 3.370, p <0.05]. K252a/ACSF ratios for INT animals were larger
than for CON animals [Tukey, p < 0.05] (Fig 10). These data indicate that goal location
approach is worsened by K252a in INT animals relative to CON animals and suggest that
spatial memory becomes reliant on BDNF after INT stress.
26
Figure 10 Distance to goal location for twenty-four hour probe drug ratio by MS condition INT animals’ drug ratio was larger than CON animals’ ratio, indicating K252a impaired their initial approach to the goal location. The bottom panel shows each drug separation within MS condition. Sample sizes: CON = 31; P2-11 = 19; INT = 29
CORT Assay Vector expression had no effect on plasma CORT levels (Fig 11), so data was
collapsed across vector condition.
27
Figure 11 Average CORT by MS condition and vector CORT levels broken down by vector show no difference between MS condition or vector. Sample sizes: CON: eGFP = 9, ERGR = 13, TdGR = 10; P2-11: eGFP = 8, ERGR = 9, TdGR = 13; INT: eGFP = 9, ERGR = 16, TdGR = 9.
CORT values were compared across MS and drug conditions. A two-way
ANOVA for CORT level revealed no main effects of MS or drug, though there was a
trend for MS by drug interaction [F(2) = 2.813, p = 0.071]. Further analyses revealed that
CORT levels in INT animals tended to be higher than P2-11 animals [Tukey; p = 0.055]
(Fig 12A) and were significantly increased when compared to combined P2-11 and CON
groups [F(1) = 5.192, p < 0.03] (Fig 12B).
28
Figure 12 Average CORT by MS condition and drug CORT levels broken apart by drug indicate near significance in the ACSF group only. A) The INT animals have a trend for increased CORT when BDNF receptors have not been blocked. This effect disappears with K252a block of the BDNF receptor. B) INT animals have increased CORT when CON and P2-11 groups are combined. This effect is limited to ACSF group only. Sample sizes: ACSF: CON = 14; P2-11 = 10; INT = 19; K252a: CON = 15; P2-11 = 11; INT = 14.
The loss of a statistical trend for an increase in CORT in INT animals in the
presence of K252a suggests that plasma CORT is regulated by BDNF signaling after INT
stress.
The relationship of CORT and behavior can be expressed by plotting each
animal’s CORT value against its average distance to goal location over fifteen seconds of
29
the twenty-four hour probe trial. Regression analyses showed a strong negative
relationship between distance and CORT for the INT animals treated with ACSF [β = -
0.58, t(16) = -2.845, p < 0.02], suggesting elevations in CORT improved spatial memory
in INT animals (Fig 13). No other regressions were significant [CON: β = 0.29, t(25) =
1.525, p = 0.140; P2 β = 0.02, t(23) = 0.11, p = 0.150; INT β = -0.27, t(28) = -1.482, p =
0.150]. The loss of a statistical relationship between CORT and maze performance during
K252a treatment for the INT groups suggests that the ability of CORT to influence maze
performance in INT animals is BDNF-dependent.
Figure 13 CORT versus distance by MS condition and drug These regression plots show the CORT plotted against the animals’ own 15 sec average distance to goal location, separated by drug delivered. For the CON animals, average distance traveled during initial goal orientation appears to increase with increased CORT regardless of drug (NS). For P2-11 animals, there is no relationship, and for INT animals, average distance traveled increases with decreased CORT (p < 0.05), in the ACSF group only, which appears to be in opposition to the K252a group. ACSF: CON = 14; P2-11 = 10; INT = 19; K252a: CON = 15; P2-11 = 11; INT = 14.
30
Tissue weights
Body Weight Body weight at time of surgery was different between MS conditions [F(2) =
13.815, p < 0.001]. P2-11 animals weighed less than both CON [Tukey; p < 0.001], and
INT animals [Tukey; p < 0.001], which were not different from each other, suggesting
less robust physical development after P2-11 stress (Fig 14).
31
Figure 14 Body weight by MS condition Animals were weighed post-cannulation surgery, and weights compared across MS condition. P2-11 animals were significantly smaller than CON or INT. INT animals were not different from CON animals. CON = 58; P2-11 = 44; INT = 55.
Adrenal Gland Weight There was no effect of vector on adrenal weight either raw [F(2) = 1.085, p =
0.341] (Fig 15A) or normalized to body weight [F(2) = 1.286, p = 0.280] (Fig 15B), so
data was collapsed across vector.
32
Figure 15 Adrenal gland weight by MS condition and vector There was no effect of vector on adrenal weight, even after normalizing to the animal’s own body weight. A) Adrenal weight by MS condition and vector, B) Normalized adrenal weight by MS condition and vector. Sample sizes: CON: eGFP = 11, ERGR = 21, TdGR = 22; P2-11: eGFP = 18, ERGR = 15, TdGR = 12; INT: eGFP = 14, ERGR = 21, TdGR = 10.
33
There was an effect of MS condition on raw adrenal gland weight [F(2) = 3.556, p
< 0.05] (Fig 16A). Adrenal glands from P2-11 animals, but not INT animals, were
smaller than those from CON animals [Tukey; p < 0.04], suggesting loss of adrenal gland
mass after P2-11 stress. However, when normalized by body weight, there was no
difference in adrenal gland weight across conditions [F(2) = 1.449, p = 0.238] (Fig 16B).
This suggests that adrenal weight differences follow body mass differences.
34
Figure 16 Adrenal gland weight by MS condition There was only an effect of MS condition on adrenal weight after normalizing to the animal’s own body weight. A) Adrenal weight by MS condition, B) Normalized adrenal weight by MS condition. CON = 58; P2-11 = 45; INT = 52.
35
Thymus Gland Weight Thymus weights were not affected by vector expression, either as raw weights
[F(2) = 0.953, p = 0.388] (Fig 17A) or when normalized to body weight [F(2) =0.454, p =
0.636] (Fig 17B), so data was collapsed across vector.
36
Figure 17 Thymus gland weight by MS condition and vector There was no effect of vector on thymus weight, even after normalizing to the animals own body weight. A) Thymus weight by MS condition and vector, B) Normalized thymus weight by MS condition and vector. Sample sizes: CON: eGFP = 9, ERGR = 21, TdGR = 22; P2-11: eGFP = 18, ERGR = 15, TdGR = 12; INT: eGFP = 14, ERGR = 21, TdGR = 10.
37
There was no effect of MS condition on raw thymus weight [F(2) = 1.431, p =
0.242] (Fig 18A), though there was an MS effect when normalized to body weight, [F(2)
= 20.654, p < 0.000] (Fig 18B). P2-11 animals had greater normalized thymus weights
than CON [Tukey; p < 0.001] and INT animals [Tukey; p < 0.001]. This may not be due
to an increase in gland size, but a delay in the normal progression of thymus involution
due to stunted growth.
38
Figure 18 Thymus weight by MS condition There was an effect of MS condition on adrenal weight, even after normalizing to the animals’ own body weight. A) Adrenal weight by MS condition, B) Normalized adrenal weight by MS condition. CON = 54; P2-11 = 45; INT = 45.
39
CHAPTER FOUR: DISCUSSION
Prior rodent studies of early life stress incorporated a continuous maternal
separation schedule and assays performed in midlife. This study aimed to differentiate the
effects of two schedules of maternal stress, continuous (daily, P2-11) stress and random
intermittent stress (INT), on learning and memory ability in young adult rats. Compared
to unstressed CON animals, INT stress had no impact on escape learning or spatial
learning in the MWM. While containing the same total number of stress episodes as the
INT stress condition, the P2-11 schedule produced an escape deficit during training and a
spatial learning impairment during the immediate probe. Escape latencies during training
were higher and spatial search strategies during immediate probing were less accurate.
Interestingly, there was a trend for enhanced memory following INT stress compared to
P2-11 and CON subjects. Drug effects on spatial memory indicate that for the INT
animals, BDNF positively regulates CORT, and the BDNF-dependent increase in CORT
improves spatial memory. There was no effect of vector on any aspect of MWM
performance. The evidence from the behavioral results indicates that P2-11 and INT
stress schedules differentially regulate young adult learning and memory with
impairments observed only after P2-11 stress.
CORT levels in INT animals were increased relative to combined P2-11 and CON
groups after ACSF treatment. However, when TrkB receptors in the hippocampus were
40
blocked before the 24-hour probe, there was no difference in plasma CORT across MS
conditions. The loss of an effect of INT stress on CORT level when K252a was applied
suggests that the elevation in plasma CORT following INT stress is reliant on BDNF
signaling. Prior research states that CORT regulates BDNF (Alboni et al., 2011; Revest et
al., 2013; Wosiski-Kuhn, Erion, Gomez-Sanchez, Gomez-Sanchez, & Stranahan, 2014).
In contrast, we have shown that BDNF may regulate CORT, a finding found in at least
one other resilience study (Taliaz et al., 2011). In INT animals, elevated CORT was
associated with reduced distance from the goal location during the 24-hour probe. This
effect was reversed when TrKB receptors were inhibited; suggesting that the BDNF-
dependent increase in plasma CORT enhanced spatial memory. There was no effect of
vector on plasma CORT.
P2-11 animals weighed less than INT or CON subjects at the time of implantation
surgery. When normalized by body weight, adrenal glands weights were no different than
in CON animals. There was no effect of MS condition on raw thymus gland weight.
When normalized by body weight, thymus glands were larger in P2-11 animals than in
INT or CON subjects, suggesting thymus enlargement after P2-11 stress. An enlarged
thymus gland following P2-11 stress might reflect a tonic increase in immune activity or
delayed development due to an overall slowing of growth. This could be explored in
future studies through measures of circulating macrophages and monocytes or antibody
levels. There were no vector effects on adrenal or thymus mass.
Table 2 shows that the effects of early life stress are schedule-dependent and
differ when viewed in young adulthood versus midlife.
41
Table 2 Results comparison: Prior research versus this study This is a summation of previous findings in ELS research that investigates MS stress effects in older (P60+) animals compared to our findings in younger adult animals (P40).
The most pronounced effects of early life stress were due to the P2-11 schedule, which
produced a spatial learning deficit, reduced body weight, and increased thymus to body
42
weight ratios. INT stress was associated with an acquired CORT response that facilitated
spatial memory and was dependent on BDNF signaling.
Prior work has focused on hippocampal atrophy (Carrion & Wong, 2012;
McEwen et al., 1997), dysregulation of the HPA axis (Daniels et al., 2009), and the
spatial memory deficit that occurs in midlife following early life stress (Choy, de Visser,
Nichols, & van den Buuse, 2008). The current work shows that memory is not disrupted
by early life stress in young adulthood, but instead escape learning rate is slower and
spatial learning is less accurate after P2-11 stress. Moreover, plasma CORT levels are not
altered by MS stress as is observed in midlife. However, the central mechanisms that
regulate CORT are affected by INT stress in that hippocampal BDNF becomes a
necessary positive regulator in young adults. Moreover, regression analyses of
relationships between CORT level and spatial memory support the idea that this BDNF-
dependent increase in CORT is beneficial for spatial memory and perhaps by promoting
resilience to stress.
Higher CORT levels and improved learning and memory were directly related to
BDNF-TrkB binding, but only in INT stressed animals. This could be a result of
enhanced BDNF actions through downstream pathways or due to a change in BDNF
release during stress. The significance of this finding may explain the often-unexpected
appearance of resilience to stress in individuals previously considered at risk for stress-
related illness due to childhood abuse or neglect, without consideration for the temporal
details of the maltreatment. The current work shows that measurement of CORT
43
responses to stressors during BDNF blockade could be a useful identifier of stress
susceptibility or resilience in humans.
Previous work utilizing MS to create models for the behavioral and cognitive
decline in adulthood due to early life stress have focused primarily on the daily,
predictable stress schedule that is similar to the P2-11 model used in this study. Thus, a
general conclusion that early life stress is related to adulthood dysfunction is claimed
with little regard for variability in schedule or total duration of MS stress. In reality, early
life stress is not as consistently experienced as in the animal model, and many studies
have noted the lack of research regarding unpredictable or variable instances of childhood
maltreatment or neglect and the effect on the adult (Callaghan, Graham, Li, &
Richardson, 2013; Goldberg et al., 2013; Masten, 2001; Pitzer & Fingerman, 2010;
Southwick & Charney, 2012; Zovkic, Meadows, Kaas, & Sweatt, 2013). In the case of
childhood exposure to highly variable timing of trauma due to loss or life-threatening
events, long term studies have not only found a resilience effect contrary to predicted
models, but a significant interaction between the persistence of the event and resilience or
chronic dysfunction outcomes (Bonanno & Papa, 2002; Robertson & Cooper, 2013;
Suarez, 2013). This might suggest that total duration, and not predictability, is the key
factor that separates P2-11 and INT stress effects. Without further study, the specific
impacts of duration and predictability cannot be fully understood as they relate to adult
resilience.
Earlier work has shown that very similar gene therapy techniques as applied in the
current study are neuroprotective against CORT manipulations in adulthood (Kaufer et
44
al., 2004). Interestingly, manipulating the stress hormone pathway through gene therapy
application neither impaired, nor improved performance in the MWM. This is somewhat
contrary to the hypothesis that supplementing for deficient receptor or protein levels
associated with early life stress should attenuate behavioral impairment and could be due
to insufficient infection/expression of the vector or MWM testing age.
Baseline CORT is highly variable amongst laboratory rats housed under the same
conditions (García & Armario, 2001). By clamping down on this natural variability,
adrenalectomy or within-animal CORT comparisons before and after MWM testing
might have revealed additional early life stress effects on reactive plasma CORT. As
well, the timing for blood collection to analyze CORT was not ideal because collection of
blood plasma was secondary to collection of brain tissue, which was optimized by
euthanasia 30-45 minutes post probe for BDNF and pTrKB expression. This may also
have impacted the CORT values. However, CORT levels and blood collection procedures
were consistent across assays.
In the future, it may be informative to further investigate the connection between
BDNF and CORT, since to date most research analyzes the effect of CORT on BDNF
and few very show that BDNF influences CORT (Taliaz et al., 2011). In particular, the
relationship between gender and stress effects might help to parse out not just this
distinction, but also explain gender differences in stress responsiveness(Oreland et al.,
2009; Slotten et al., 2006; S. a Weaver, Diorio, & Meaney, 2007). A more complete
understanding of vulnerability and resilience after ELS would in the future also include
unaltered, female subjects.
45
CHAPTER FIVE: CONCLUSIONS
This study was successful at identifying potential biomarkers for resilience and
vulnerability to cognitive impairment following ELS. Detection of biomarkers at an early
age permits early intervention, which can potentially prevent cognitive dysfunction later
in life and avert the cost of treatment. This study also provides information about risk
likelihood by identifying a set of biomarkers associated with vulnerability. These
biomarkers (hormonal, behavioral, physiological) could be non-invasively and
inexpensively evaluated through acute application of drug and ultrasound (Berghuis et
al., 2005). Additionally, the data suggest modifications to stress and hormonal tests may
improve differentiation of individuals susceptible to cognitive impairment. Equally
important, better stress resiliency tests may identify individuals that are best able to adapt
to stressful situations, which could be useful in military screening and for the young
individual who is interested in working in challenging environments.
46
CHAPTER SIX: LESSONS LEARNED
Protocol Difficulties
Corticosterone Analyses Reflecting on our protocols, it would have been much more ideal if we could have
obtained blood samples from each animal for baseline corticosterone values, but
obtaining enough blood for baseline analysis was not only extremely difficult
procedurally, but would have impacted recovery of the animal in time for testing. Though
it would have been better to normalize corticosterone levels to each animal’s own
baseline, we discovered (by testing CORT from non-infused, non-maze tested animals)
that there were no identifiable differences between tested and untested animals, other
than an overall increase in corticosterone. This is most easily explained by the time
constraint differences. The untested animals were euthanized within 10 minutes of being
selected from the housing rack. With respect to blood collection for tested animals, the
timing for blood collection was not ideal simply because it was secondary to collection of
brain tissue, which was optimized for BDNF and pTrKB expression. Previous studies
have indicated that this results in an overall lower level of corticosterone, which may
account for the overall difference between tested and untested animals.
Personnel One of the most difficult aspects of this study was finding the resources and
people to maintain proper timing of procedures. We discovered that with a cohort of
47
more than 5 animals, we had to split the cohort into a second, staggered group. The
reasons for this were the need to implant cannulae for a single cohort on the same day to
keep them on the same schedule. Where possible, we tried to account for this between
cohorts, but it meant that the split groups were not always the same age at time of testing
because we only had one MWM that was sized for rats, so training and testing days
would overlap if they were not at least 3 days apart. However, we accommodated this by
balancing the cannulation dates between the two groups so there was equal time between
surgeries, vector expression, drug infusions, and the MWM test. Additionally, it was a
challenge to maintain a one-hour interval between drug infusion and the twenty-four hour
probe test. Infusions on average were a 7-10 minute procedure from removing the cage
from the rack, infusing, replacing, and preparing drug for the next animal. Combined
with the required coordination between immediate and testing probe (twenty-four hours
after the immediate probe (or as close as possible)), as well as the time restrictions for
tissue collection after the probe, this was the one variable with the most slippage. With an
average of five animals in any given cohort and only three people involved in testing, this
became a significant challenge, though the full implication of alterations to this timing is
unknown. However, any stress related to the infusion should not have impacted the
effect of the MWM probe.
Infusion Troubleshooting We discovered that cleaning the infusion equipment with 70% ethanol after
infusions with drug, caused precipitates from the ACSF to clog the infuser. The
48
workarounds were to widen the infuser tip by cutting it at a slight angle, and repeatedly
running sterile water through it afterwards.
Surgery Troubleshooting Animals began losing their implants after a change in the type of glue used to
cement the base, even with skull screws firmly in place. It was discovered that name
brand super glue performed exponentially better than the generic/store brands.
49
ADDENDUM
For your amusement
The Neuron Song As sung to ‘The Galaxy Song’ by Eric Idle and John Du Prez When serotonin level’s down and makes you frown, And life seems post-mitotic, And people are stupid, obnoxious, or daft, And you feel you’ve become neuroooooootic, Just remember that you’re using a cortex that’s evolving Evolving at nine thousand years a trait. A SNiP for every cigarette you smoke, take a toke, A hindbrain that gives to us our strange gait. Hippocampi, you and me, and all the memories we see, Are moving at the perceived speed of time, In an inner spiral fold, that is a bit of temp-ral lobe, Of an organ that we call the seat of mind. Our cer-e-brum itself contains a hundred billion cells; It’s thirty billion neurons side to side; It bulges in the back, two-hundred thousand earth-years old, Modern cortex is one-tenth our lengthy hides. We’re thirty-thousand neurons from true enlightenment, We try ev-ry thousand or two-thousand years; And our brain itself is one of millions of billions In that amazing and confounding last frontier The human brain itself keeps on expanding and expanding, In all of the directions it can grow; As fast as it can grow, the filopod-ia you know, Twelve microns in a hour and that’s the fastest speed they go. So remember, when you may be feeling perplexed and deranged How amazingly unlikely is your brain; And pray that all junk DNA is really something cool, Or the universe will think we’re nincompoops.
50
MLE
Lab Rat 4 Life
51
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Citations for Table 1
(Aisa, Tordera, Lasheras, Del Río, & Ramírez, 2007; Cao et al., 2013; Chen et al., 2012; Daniels et al., 2009; Daskalakis et al., 2011; Diehl et al., 2012; Fóscolo, Fóscolo, Marubayashi, Reis, & Coimbra, 2008; Greisen, Altar, Bolwig, Whitehead, & Wörtwein, 2005; Kalinichev et al., 2002; Kikusui, Nakamura, Kakuma, & Mori, 2006; Ladd, Thrivikraman, Huot, & Plotsky, 2005; Lee et al., 2012; Lehmann et al., 1999; Lippmann et al., 2007; Marais et al., 2008; Matthews & Robbins, 2003; Milde, Enger, & Murison, 2004; Neumann et al., 2005; O’Sullivan et al., 2011; Oreland et al., 2009; Plotsky & Meaney, 1993; Slotten et al., 2006; Deepika Suri et al., 2013; van Oers, 1998; S. a Weaver et al., 2007)
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BIOGRAPHY
Emily T Stoneham graduated from Martin High School in Arlington, TX in 1987. She received her Bachelor of Science from the University of Arlington, Arlington, TX in 1992 with a major in Behavioral Psychology. She received her officer’s commission in the United States Air Force in 1992, and was assigned to Edwards AFB, CA from 1993-1996 as a human factors engineer. She was awarded a one-year opportunity to work at Hughes Research Laboratory, Malibu, CA as an Education With Industry participant, where she worked as a Graphical User Interface designer. In 1997, she was assigned to Brooks AFB, San Antonio, TX as a human factors engineer in the development of user interface for intelligent tutoring systems. In 1999, she was assigned at Tinker AFB, OK as a human factors engineer. She received her Masters in Aeronautical Science from Embry-Riddle Aeronautical University in 2006. In 2007 she entered the Ph.D. program in neuroscience at GMU and became a Ph.D. candidate in 2010. She was funded as a SMART scholar, receiving a four-year scholarship from ASEE through the SMART program in 2009.