Phenotypic Plasticity, CYP19A1 Pleiotropy, and Maladaptive Selection in Developmental Disorders

http://sgo.sagepub.com/
SAGE Open
http://sgo.sagepub.com/content/3/2/2158244013484476
The online version of this article can be found at:
DOI: 10.1177/2158244013484476
2013 3:SAGE Open
J. Patrick Malone
Phenotypic Plasticity, CYP19A1 Pleiotropy, and Maladaptive Selection in Developmental Disorders
Published by:
http://www.sagepublications.com
can be found at:SAGE OpenAdditional services and information for
http://sgo.sagepub.com/cgi/alertsEmail Alerts:
http://sgo.sagepub.com/subscriptionsSubscriptions:
http://www.sagepub.com/journalsReprints.navReprints:
SAGE Open are in each case credited as the source of the article.
permission from the Author or SAGE, you may further copy, distribute, transmit, and adapt the article, with the condition that the Author and
© 2013 the Author(s). This article has been published under the terms of the Creative Commons Attribution License. Without requesting
by guest on May 12, 2013sgo.sagepub.comDownloaded from

SAGE Open
April-June 2013: 1–19
© The Author(s) 2013
DOI: 10.1177/2158244013484476
sgo.sagepub.com
Supposition without appreciation for evolutionary mecha-
nisms represents a danger to the field of evolutionary psy-
chology. Microevolution (e.g., natural selection and genetic
drift) operates in synergistic fashion with macroevolution
(e.g., evolutionary history and adaptive constraints), as coor-
dinated by developmental biology responding to an environ-
ment. In general, natural, sexual, frequency-dependent,
individual, kin, group, and species selection operate on phe-
notypes and drive change in gene frequency across succes-
sive generations. Mutation, the founder effect, the bottleneck
effect, drift, and Mendel’s fair coin represent opportunities
for variation. Random variation creating synonymous base
substitutions, pseudogenes, and neutral amino acids may
have no evolutionary effect. Evolution can be very fast when
selection is directed and strong in a large population with
great diversity, but rapid modifications usually incur costs
that destabilize changes. The price of change may induce
maladaptation, or even dysfunction in response to environ-
mental extremes, and this is evident in the evolution of the
human brain.
Evolution fashioned a balance between the energetics
(Aiello & Wheeler, 1995; Clutton-Brock & Harvey, 1980;
Foley, Lee, Widdowson, Knight, & Jonxis, 1991; Herculano-
Houzel, 2011; Snodgrass, Leonard, & Robertson, 2009) of
high cell number for information storage and retrieval (e.g.,
elephants), complexity for sense data processing and calcula-
tion (e.g., sonar-dependent bats), or both as in cetaceans and
primates (Herculano-Houzel & Kaas, 2011; Snodgrass et al.,
2009). The crucial element in human brain evolution is plas-
ticity, which is not merely cell growth and neurite organiza-
tion but also malleable interconnectivity and targeted cell
removal. Warm social contact and environmental enrichment
early in life tend to support neuron development and connec-
tion retention (Diamond, 1991; Harlow & Harlow, 1965;
Smith, Greenberg, Seltzer, & Hong, 2008); negative stress
tends to destabilize growth and enhance apoptosis (Belsky &
de Haan, 2011; De Bellis & Kuchibhatla, 2006; Hallmayer et
al., 2011; Harlow, 1974; Malone, 2011c, 2011d; Slavich,
Way, Eisenberger, & Taylor, 2011). These factors demon-
strate gender bias and thus provide triangulation in the search
for a genetic mechanism that unites developmental disorder
with evolution (Malone, 2012).
The CYP19A1 gene codes for cytochrome P450 aroma-
tase (P450arom) and is located on the long leg of chromo-
some 15, at 21.2 (S. A. Chen et al., 1988; Simpson et al.,
1994; Zhang et al., 2004). P450arom is the enzyme that con-
verts testosterone into the most pervasive and biologically
active steroid, neuroprotective estradiol (E2). The region on
CYP19A1 that codes for P450arom must splice onto one of
484476SGOXXX10.1177/2158244013484476SAGE OpenMalone
research-article2013
1
Walden University, OR, USA
Corresponding Author:
J. Patrick Malone, College of Behavioral Sciences, Department of
Psychology, Walden University, 5083 Falcon Dr., Klamath Falls, OR
97601-9155, USA.
Email: Jeffrey.Malone@WaldenU.edu
Phenotypic Plasticity, CYP19A1
Pleiotropy, and Maladaptive Selection in
Developmental Disorders
J. Patrick Malone1
Abstract
The contribution of evolutionary psychology to the study of development and psychopathology depends on adherence to
the principles of evolutionary biology. The human brain evolved because selection favored neither size nor complexity but
instead the phenotypic plasticity supporting cognitive flexibility. Cell proliferation, migration, elongation, synaptogenesis,
synaptic pruning, apoptosis, and myelination occur at varying rates during asynchronous phases of development throughout
the brain. Developmentally sensitive periods result from phenotypic plasticity and are vital for adaptation to the environment.
The biological systems surrounding the CYP19A1 gene provide mechanisms for neuroprotection and targeted neuronal
debridement in response to environmental stress, uniting selection with developmental biology. Updates to Dunbar’s original
hypothesis with current primatological data, inclusion of total brain mass, and the introduction of CYP19A1 orthology from
nine primate species yields a linear regression, R2
= .994, adjusted R2
= .989, F(3, 5) = 143.758, p < .001.
Keywords
autistogenesis, CYP19A1, plasticity, evolution, disorder

2 SAGE Open
nine transcripts (Sebastian & Bulun, 2001) for specific tissue
expression (Figure 1). For example, the major placental tran-
script contributes to increased circulating E2 in pregnant
women by 2 to 3 orders of magnitude (Abramovich & Rowe,
1973). However, uniting large transcripts prior to translation
permits many opportunities for transcript-level regulation
and dysfunction, especially at the common splice site.
Circulating serum estradiol demonstrates wide ranging
effects throughout the body and directly regulates the
inflammatory response in all tissues (Bastarache et al.,
2012; Bechlioulis et al., 2012; Chakrabarti & Davidge,
2013; Douin-Echinard et al., 2011; Sophonsritsuk et al.,
2013; Zierau, Zenclussen, & Jensen, 2012) and is linked to
autoimmunity in males (Becker, 2012). The inflammatory
cascade is a system of feed-forward and feedback loops, and
metabolites of these processes directly regulate gene expres-
sion in cells that reside within entirely different tissues, such
as the gastrointestinal (GI) tract (Ahlquist et al., 1982;
Grossman, Brazier, & Lechago, 1981; Strober & Fuss, 2011;
Whittle, 1981). This is a bidirectional phenomenon and
many proinflammatory compounds used by the GI as chem-
ical messengers trigger schizophrenic individuals and exac-
erbate challenges with autism spectrum disorders (ASDs)
and multiple sclerosis (S. M. Collins, Surette, & Bercik,
2012; Coury et al., 2012; Frye, Melnyk, & MacFabe, 2013;
Maenner et al., 2012; Severance et al., 2012).
Sex hormone production peaks in the third trimester and
then diminishes before birth, followed by a massive prepu-
bertal surge (Figure 2) weeks later (Fitch & Denenberg, 1998;
Forest, Sizonenko, Cathiard, & Bertrand, 1974; Main,
Schmidt, & Skakkebæk, 2000). Potentially neurotoxic levels
of testosterone are converted by P450arom into E2 which
stimulates neurogenesis, neurite outgrowth, elongation, syn-
aptogenesis, and regeneration, and mitigates apoptosis,
necrosis, and physiological debridement (Arai, Sekine, &
Murakami, 1996; Beyer, 1999; Fukudome et al., 2003;
Garcia-Segura, 2008; Hao et al., 2006; Ma et al., 1993;
Prange-Kiel & Rune, 2006; Quesada, Lee, & Micevych,
2009; Rasmussen, Torres-Aleman, MacLusky, Naftolin, &
Robbins, 1990; Zhang et al., 2004), including connections to
olivary cells otherwise deficient in autistics with male bias
(Malone, 2011a, 2012). Studies indicate E2 regulates neuro-
genesis and apoptosis throughout the cortex (Arai et al., 1996;
Fukudome et al., 2003; Raimundo et al., 2012; Real, Meo-
Evoli, Espada, & Tauler, 2011) differentially by region and is
context-specific through α- and β-estrogen receptor subtypes
on cortical cells, during different periods of development
(Kritzer, 2006; Ma et al., 1993; Rasmussen et al., 1990).
Converting normal levels of testosterone into E2 enhances
verbal and spatial performance (Cherrier et al., 2007; Spritzer
et al., 2011), promotes the development of Purkinje cell
axons within the ventromedial nucleus (VMN) of the hypo-
thalamus with male bias (Keller, Panteri, & Biamonte, 2010),
and regulates cell size, number, and activity in the fusiform
gyrus (Bölte et al., 2006; Hall, Szechtman, & Nahmias,
2003; van Kooten et al., 2008). E2 enhances long-term
potentiation (Mukai et al., 2007; Woolley, 2007), object rec-
ognition and spatial memory (Luine, Jacome, & Maclusky,
2003) with male bias, modulates working memory (Sinopoli,
Floresco, & Galea, 2006), and promotes antioxidant metabo-
lism that inhibits neuroinflammatory processes with female
bias (Sen, Khanna, & Roy, 2006). It is interesting to note that
a recent study (Sharawy, Hassan, Rashed, Shawky, & Rateb,
2012) also demonstrates that E2 levels differentially regulate
the hypothalamic-pituitary-adrenal (HPA) axis response
under stress.
E2 also regulates docosahexaenoic acid (DHA) synthesis,
which is significantly produced in females only (Burdge,
Figure 1 The highly complex CYP19A1 gene contains nine major tissue specific transcripts separate from the aromatase coding. RNA for
tissue and the enzyme must link prior to translation, thus the common splice site represents a region for regulation and failure. CYP19A1
is unusually large, with increased probability for mutation, maladaptive methylation, histone modification, dysregulation from compromised
feedback messengers, and the influence of more than a dozen major alleles identified thus far. The transcript region for Bone (~ 20kb),
Breast Cancer / Adipose and Ovary (~0.5), and Breast Cancer & Endometriosis (~0.2) are combined due to their comparatively small size
and adjoining positions in the sequence. The illustration is thus not to scale and is adapted from The Systems Theory of Autistogenesis:
Putting the Pieces Together (p. 5), by J. P. Malone, 2012, Los Angeles, CA, Sage Publications. Copyright 2012. Adapted with permission.

Malone 3
Jones, & Wootton, 2002; Giltay, Gooren, Toorians, Katan, &
Zock, 2004), to provision the unborn and nursing infant
while protecting maternal prosociality. Placental uptake is
highest during the final trimester which also represents the
greatest phase of neurogenesis, neurite formation, and arbo-
rization (Green & Yavin, 1998). E2 also regulates glutama-
tergic neurotransmission and so provides protection against
excitotoxicity (Blaylock & Strunecka, 2009; Choudhury,
Lahiri, & Rajamma, 2012; Spampinato, Merlo, Nicoletti, &
Sortino, 2012) and glutathione-mediated redox/antioxidant
capacity (Rose et al., 2012). DHA is essential for neuron
growth, elongation, arborization, neurite outgrowth, synaptic
pruning, and provides protection against apoptosis and
necrosis (P. Green & Yavin, 1998; Hashimoto et al., 2005;
Horrocks & Yeo, 1999; Ikemoto, Kobayashi, Watanabe, &
Okuyama, 1997; Kan, Melamed, Offen, & Green, 2007;
Kawakita, Hashimoto, & Shido, 2006; Okada et al., 1996)
DHA, in a physiologically correct ratio (Hashimoto et al.,
2002; Hashimoto et al., 2005; Rapoport, Ramadan, &
Basselin, 2011; Rapoport, Rao, & Igarashi, 2007) with ara-
chidonic acid (AA), enhances synaptic transmission and
long-term potentiation (Itokazu, Ikegaya, Nishikawa, &
Matsuki, 2000; Poling, Vicini, Rogawski, & Salem, 1996;
Vreugdenhil et al., 1996; Young, Gean, Chiou, & Shen, 2000;
Young, Gean, Wu, Lin, & Shen, 1998). DHA reduces apop-
tosis by promoting phosphatidylserine (PS) production, up-
regulating antiapoptotic genes, and inhibiting proapoptotic
metabolites (Horrocks & Farooqui, 2004; Kim, Akbar, &
Figure 2. The pre and post natal, prepubescent, and pubescent sex hormone surges occur just prior to the onset of developmentally
sensitive periods. Developed from “Sex differences in adolescent depression: Do sex hormones determine vulnerability?” by E. F. G.
Nanick, P. J. Lucassen & J. Bakker, 2011, The Journal of Neurobiology, 23(55), 1-10. Copyright, 2011 by Blackwell Publishing Ltd; “Cortical
development, plasticity and reorganization in children with cochlear implants,” by A. Sharma, A. A., Nash & M. Dorman, 2009, The Journal
of Communication Disorders, 42(4), 272-279. Copyright, 2009 by Elsiver; “Early Years Study final report: Reversing the real brain drain,”
by J. F. Mustard & M. N. McCain, 2000, Toronto, Canada: Ontario Children’s Secretariat; “Effects of stress throughout the lifespan on the
brain, behaviour and cognition,” by S. J.Lupien, B. S. McEwen, M. R. Gunnar & C. Heim, 2009, Nature Reviews Neuroscience, 10, 434-445.
Copyright, 2009 by Nature Publishing Group; “Protecting brains, not simply stimulating minds,” by J. P. Shonkoff, 2011, Science, 333(6045),
982-983. Copyright, 2011 by American Association for the Advancement of Science.

4 SAGE Open
Kim, 2001; Kim, Akbar, Lau, & Edsall, 2000; Lukiw et al.,
2005; McNamara, 2010; Morris et al., 2003). Dysregulation
of the omega-3/omega-6 fatty acid balance within the brain
promotes increased neuroinflammatory degeneration (Rao,
Kim, et al., 2011; Rao, Rapoport, & Kim, 2011). This proin-
flammatory reaction, including oxidative stress, results in
apoptosis, cell debris, and poorly functioning yet intact cells
removed by brain macrophages and microglia (Malone,
2011b, 2011c; Paolicelli et al., 2011), and so this broad
sequence of events is both directly and indirectly regulated
by CYP19A1 expression (Malone, 2012).
McCarthy (2008) indicated differing aspects of the devel-
oping brain are immune to E2’s fast and potent influence at
various stages, thought to prevent aberrant neuronal develop-
ment (Malone, 2012). This explains why estradiol may lose
efficacy or even enhance risk of neurodegenerative processes
following stroke in women older than 65 (Azcoitia, Arevalo,
De Nicola, & Garcia-Segura, 2011). However, in preterm
infants fed high-dose DHA (1% total fatty acids) infant milk
formulademonstratedimprovedBayleyMentalDevelopment
(MDI) scores at 18 months corrected age in females only
(Makrides et al., 2009). Because oxytocin receptor (OXTR)
sites are also regulated by E2 (Nissenson, Flouret, & Hechter,
1978), social and emotional attachments (Ainsworth, 1969;
Ainsworth, Blehar, Waters, & Wall, 1978; Bard, 2012; Bard
& Gardner, 1996; Bowlby, 1969, 1988; Bretherton, 1992;
Harlow & Harlow, 1965; Maestripieri, 2003; Russell &
Ainsworth, 1981; van Ijzendoorn, Bard, Bakermans-
Kranenburg, & Ivan, 2008) are strongly influenced by E2 (F.
S. Chen & Johnson, 2012; Krueger et al., 2012), as are the
dynamics of male aggression (Love et al., 2012; Trainor, Lin,
Finy, Rowland, & Nelson, 2007). Therefore, CYP19A1
expression broadly influences the sensitive periods of gen-
der-specific emotional and social behavior, and the brain
plasticity supporting primate cognition responsive to a
dynamic environment (Malone, 2011d, 2012).
Since Dunbar (1992), many have suggested the process of
hominid brain evolution accelerated by selection favoring a
neurology that facilitates behaviors such as (a) imitation, (b)
social mediation, (c) Machiavellian strategizing, and (d) the
interpersonal relationships of coalition formation (Byrne &
Corp, 2004; Call & Tomasello, 1998; Schillaci, 2008; Wilson,
Kahlenberg, Wells, & Wrangham, 2011; Wrangham, 1993).
Numerous studies have explored the issue of brain develop-
ment through evolution but disappoint, in part by failing to
account for the differences in study samples due to develop-
mental stage (for a review, see Healy & Rowe, 2007). The
critical aspect to human brain evolution is phenotypic plas-
ticity; primate brains experience tremendous cell prolifera-
tion postpartum, selective synaptic pruning in response to an
infinitely variable environment, “hard-wiring” due to
myelination (Figure 2), and CYP19A1 is principal to each of
these processes.
The aim of the current study is twofold. The first purpose
was to explore the evolution of CYP19A1 as evidence
indicates developmental derailment is not an exclusively
human condition (Bastian, Sponberg, Suomi, & Higley,
2003; Brent, Lee, & Eichberg, 1989; Brüne, Brüne-Cohrs,
McGrew, & Preuschoft, 2006; Capitanio, Mendoza, Mason,
& Maninger, 2005; Clay, 2012; Conti et al., 2012; Davenport,
1979; Davenport & Menzel, 1963; Davenport & Rogers,
1970; Davenport, Rogers, & Rumbaugh, 1973; Ferdowsian
et al., 2011; Goodall, 1986; Harlow & Harlow, 1965; Hook et
al., 2002; Kalcher-Sommersguter, Preuschoft, Crailsheim, &
Franz, 2011; Kempes, Gulickx, van Daalen, Louwerse, &
Sterck, 2008; Malone, 2011d; Nash, Fritz, Alford, & Brent,
1999; Ridley & Baker, 1982). The cognitive flexibility that
allows for invention and manipulation of tools, whether
material or social, rests at the core of primate brain evolution
hypotheses (Barton, 1996; Byrne & Corp, 2004; Call &
Tomasello, 1998; Dunbar, 1992, 1998, 2010; Dunbar &
Shultz, 2007; Joffe & Dunbar, 1997; Jolly, 1966; Kudo &
Dunbar, 2001; McGrew, 1992; Pawlowski, Lowen, &
Dunbar, 1998). Because the human brain does not mature
unilaterally during ontogeny, nor has it done so through phy-
logeny, there may be genetic mechanisms that link selection
to developmental neurobiology.
While it is true that brain size and complexity correlate to
physiological and ecological factors (Allman, McLaughlin,
& Hakeem, 1993; Armstrong, 1985; Clutton-Brock &
Harvey, 1980; Dunbar & Shultz, 2007; Harvey & Krebs,
1990; Walker, Burger, Wagner, & Von Rueden, 2006), the
author suggests that genetic mechanisms supporting the
social brain hypothesis would correlate less as taxonomy
goes phylogenetically afield. Such a mechanism must also
account for the gender-biased differences in developmental
pathology (Malone, 2011d, 2012) and the evidence that neo-
cortical volume positively correlates to group size in females
but not to males (Lindenfors, 2005). Therefore, this study
first seeks to determine if the CYP19A1 gene (a) demon-
strates a strong phylogenetic trend and (b) if its orthologous
relationship correlates to previously hypothesized mecha-
nisms for human brain evolution.
Organisms possess genotypes that permit deviations in
developmental pathways in response to varying environ-
mental conditions (Scoville & Pfrender, 2010). The most
crucial aspect of the primate brain is neither size nor “exec-
utive brain” volume (Reader & Laland, 2002, p. 4436).
Because learning is directly tied to synaptic malleability
(Blumenfeld-Katzir, Pasternak, Dagan, & Assaf, 2011),
selection has focused on regulation of brain remodeling
through development. The systems theory of autistogenesis
suggests human brain evolution resulted in maximal pheno-
typic plasticity, to accommodate multiform selective pres-
sures without concurrent change in genetic conformation,
yet liable to epigenetic and transcript-level expression reg-
ulation (Malone, 2011d, 2012).
A rapidly growing consensus indicates a system linking
the neurodevelopmentally sensitive response to environmen-
tal stimuli with the genetics of neuroinflammation combines

Malone 5
to predispose ASD pathogenesis with male bias (Angelidou
et al., 2012; Becker, 2012; Hu, 2013a, 2013b; James, 2008,
p. 15; Malone, 2012; Rossignol & Frye, 2011), and altera-
tions to one or more components within the system may initi-
ate neurodegenerative feedback. Though both genes and
environment seem necessary, neither appears independently
sufficient for ASD pathogenesis in the preponderance of
cases (James, 2008; Malone, 2012), a metabolic endopheno-
type linking genes with environment is theorized (Angelidou
et al., 2012; Becker, 2012; Hu, 2013a, 2013b; James, 2008;
Malone, 2011c). This suggests that a predisposing genetic
profile could exist within an individual without developmen-
tal disorder who did not receive environmental insult during
developmentally sensitive periods (Angelidou et al., 2012;
Hu, 2013a, 2013b; James, 2008; Malone, 2012). Likewise,
this view suggests that an individual without a genetic bur-
den could develop disorder under very great environmental
stress during the same early life stage (Angelidou et al.,
2012; Hu, 2013a, 2013b; James, 2008; Malone, 2012).
Malone (2011c) first hypothesized that CYP19A1 plays a
principal role in brain plasticity and developmental disorder
due to more than a dozen known alleles, opportunities for
single-nucleotide polymorphism influence, possible epigen-
etic imprinting, miRNA regulation, and other forms of tran-
script-level expression modification that may alter
developmental trajectories. Therefore, if CYP19A1 com-
plexity trends with phylogeny and correlates strongly to pre-
viously hypothesized drivers of human brain evolution, the
second aim of this study is to answer whether the gene can
provide genetic accommodation specific to (a) brain region,
(b) by gender, (c) across developmental stages, and (d) with
broad expression variability.
Method
To calculate orthologies (Kent et al., 2002), a multiz align-
ment (Blanchette et al., 2004) of CYP19A1 from the February
2009 (GRCh37/hg19) human assembly of the Genscan,
Ensembl, RefSeq, and UCSC gene database was produced
using: chimpanzee (P. troglodytes, October 2010; CGSC
2.1.3/panTro3); western lowland gorilla (G. gorilla gorilla,
May 2011; Sanger Institute gorGor3.1/gorGor3); Sumatran
orangutan (P. pygmaeus abelii, July 2007; WUGSC 2.0.2/
ponAbe2); northern white-cheeked gibbon (N. leucogenys,
January 2010; GGSC Nleu1.0/nomLeu1); rhesus macaque
(M. mulatta, January 2006; MGSC Merged 1.0/rheMac2);
common marmoset (C. jacchus, March 2009; WUGSC 3.2/
calJac3); dolphin (T. truncates, February 2008; Broad
Institute turTru1); microbat (little brown bat; M. lucifugus,
July 2010; Broad Institute Myoluc2.0/myoLuc2); megabat
(large flying fox, P. vampyrus, July 2008; Broad Institute
pteVam1); African elephant (L. africana, July 2009; Broad/
loxArf3), American opossum (M. domestica, October 2006;
Broad/monDom5); platypus (O. anatinus, March 2007;
WUGSC 5.0/ornAna1); chicken (G. gallus, May 2006;
WUGSC 2.1/galGal3); anole lizard (A. carolinensis, May
2010 (Broad AnoCar2.0/anoCar2); African clawed frog (X.
tropicalis, November 2009 (JGI 4.2/xenTro3); stickleback
fish (G. aculeatus, February 2006; Broad/gasAcu1); lamprey
eel (P. marinus, March 2007; WUGSC 3.0/petMar1).
The above species provide a skeletal framework for the
subphylum Vertebrata, thus representing a foundation for an
evolutionary perspective, with special emphasis on nonhu-
man primates. A simple alignment of Neanderthal CYP19A1
is determined to assess this unique gene in another species of
Homo as a limited form of test for internal validation. A
Neanderthal CYP19A1 composite is produced from 6
ANFO-mapped fossil samples (Feld1, Mez1, Sid1253,
Vi33.16, Vi33.25, Vi33.26) aligned against the human
genome (Briggs et al., 2009; R. E. Green et al., 2010) using
the UCSC Genome Browser (Blanchette et al., 2004;
Karolchik et al., 2003; Kent, 2002; Kent et al., 2002; Stenzel,
2009). Because modern Homo sapiens share a more recent
common ancestor with Neanderthal than any nonhuman pri-
mate, CYP19A1 should demonstrate organization nearly
identical to the current human model, particularly if the gene
demonstrates an evolutionary trend through the extant pri-
mate lineage.
Dunbar’s (1992) original model (Figure 3) presented
neocortex ratio (NCR) as an independent variable and group
size as the dependent variable, stating that “the interest lies
in the consequences of brain size” (p. 9). This perspective
neglects environmental circumstances that may induce last-
ing group size change regardless of brain development.
Because, unlike Dunbar, this study is concerned with the
cause of human brain evolution, NCR becomes the
Figure 3. Dunbar’s original assessment of the impact of a large
neocortical ratio to social group size and complexity. The formula
for the fit line is provided Y = 0.8497X0.6442
. The figure is adapted
with permission and the primate groups are indicated following the
original schema: () nocturnal prosimians; (º) diurnal prosimians;
(•) polygamous anthropoids; (†) monogamous anthropoids; (∆)
hominoids on a logarithmic scale for each axis. Adapted from
Neocortex Size as a Constraint on Group Size in Primates (p. 478),
by R. I. M. Dunbar, 1992, Kidlington, Oxford, UK, Elsevier Limited.
Copyright 1992. Adapted with permission.

6 SAGE Open
dependent variable and group size is one of the independent
variables for the purpose of the model. This study considers
that while growing through neurologically sensitive stages
within an ever-dynamic social milieu (Rodseth, Wrangham,
Harrigan, & Smuts, 1991; Sutcliffe, Dunbar, Binder, &
Arrow, 2012), situated within an environment of limited
resources, selection (Wilson et al., 2011; Wrangham, 1993)
operated on individual variability to propel primate brain
evolution. Therefore, due to its contribution to plasticity,
environmentally triggered patterns of neuronal remodeling,
and modulation of gender typical social behavior, CYP19A1
is a factor.
What has become known as “Dunbar’s equation” is cor-
rected with current information regarding orangutan
(Rodman, 1993; Singleton & van Schaik, 2002; te Boekhorst,
Schürmann, & Sugardjito, 1990; Utami, Goossens, Bruford,
de Ruiter, & van Hooff, 2002) and gorilla (Yamagiwa,
Kahekwa, & Basabose, 2003) range and social group disper-
sion. Dunbar (1992) log-transformed all data due to curvilin-
ear relationship between group size and NCR, and performed
the regression on reduced major axes as this provides great-
est estimate of relation when errors are unknown, though this
creates an added false visual sense of linearity (Figure 3).
Those species previously described by Dunbar as existing in
a group size of 1 are here considered as living in a social
group of 2+ as courtship and mating is assumed to be a com-
plex social interaction (Schillaci, 2008) within local if not
overlapping environments.
The ratio of neocortex volume to whole brain volume is
the dependent variable as it accounts for executive function,
though it is easy to imagine a small primate evolving a NCR
greater than human, yet still in possession of a brain no larger
than a walnut. To fashion a more complete model, brain mass
(Deaner, Isler, Burkart, & van Schaik, 2007; Dunbar &
Shultz, 2007) is included so that neuronal density that varies
within and between brain regions (C. E. Collins, Airey,
Young, Leitch, & Kaas, 2010) and the scaling factor (Clark,
Mitra, & Wang, 2001, Herculano-Houzel, 2009; Herculano-
Houzel & Kaas, 2011) become a feature of the model. The
female body cavity delimits the general size of the fetus, and
the size of the female pelvis restricts the size of the neonatal
brain, so brain volume enables some accounting for general
body size and encephalization quotient in primates (Deacon,
1997; Jerison, 1973).
Following species-specific data correction, SPSS v 18
was used to perform a regression with NCR as the dependent
variable. Square root transformed group size and brain mass
data (TGR and TBM, respectively) with CYP19A1 genetic
orthology are independent variables. Unlike Dunbar (1992),
the axes remain intact to prevent added visual impression of
linearity. Because visual interpretation of graphic analysis
suggested a phylogenetic trend through vertebrate phylog-
eny, with particular development in primates, a CDS FASTA
alignment (Karolchik et al., 2003) output was produced from
nine primate species to derive the amino acid sequence align-
ment against the February 2009 (GRCh37/hg19) human
CYP19A1 assembly. Amino acid sequence was chosen over
nucleic acid because each transcriptome sequenced repre-
sents an imaginary construct representing each species with
no easy accounting for substitutions to synonymous codons.
The BLAST-like alignment tool (BLAT; Kent, 2002) is used
to determine orthology.
If it is established that CYP19A1 complexity does trend
with phylogeny and that it correlates strongly to previously
hypothesized drivers of human brain evolution, then the
UCSC Genome Browser (Kent, 2002) is used to align the
Ensembl, Genscan, RefSeq, and UCSC Gene human genome
databases against data from exon microarray expression in
the fetal brain (Johnson et al., 2009), histone mapping
through brain development by gender (Cheung et al., 2010),
TargetScan miRNA regulatory sites (Friedman, Farh, Burge,
& Bartel, 2009; Grimson et al., 2007; Lewis, Burge, &
Bartel, 2005), RNA transcription levels (ENCODE Project
Consortium et al., 2011), brain DNA methylation (Maunakea
et al., 2010; Morin et al., 2008; Robertson et al., 2007), and
the presence of simple nucleotide polymorphisms (SNPs;
Sherry et al., 2001). Assessment of CYP19A1 expression
and regulation from the above data provides evidence rela-
tive to genetic accommodation specific to (a) brain region,
(b) by gender, (c) across developmental stages, and (d) with
broad genetic variability.
Results
Phylogenetically, CYP19A1 does not fully organize until
placental vertebrates (Figure 4) and appears to play a reason-
ably comparable role whether bat, elephant, or dolphin, until
the rise of Platyrrhini (New World monkeys) and Catarrhini
(Old World monkeys and apes). Visual examination of the
multiz alignment suggests that CYP19A1 begins to approxi-
mate human conformation in primates, especially as all tis-
sue-specific exons (Sebastian & Bulun, 2001) appear to align
with gaps and start/stop sequences, but visual representation
is deceptive as the130k nucleotide sequence is graphically
compressed. Individual CYP19A1 orthology for the nine pri-
mate species to current human data was determined (Table
1). Furthermore, the Neanderthal CYP19A1 composite pro-
duced by aligning the Feld1 Mez1 Sid1253 Vi33.16 Vi33.25
Vi33.26 sequences (Briggs et al., 2009; R. E. Green et al.,
2010) against the human genome through the UCSC Genome
Browser (Blanchette et al., 2004; Karolchik et al., 2003;
Kent, 2002; Kent et al., 2002; Stenzel, 2009) demonstrates
similarity to the current human model.
The square root procedure is considered the most conser-
vative transformation to use for curvilinear relationships
(Mertler & Vannatta, 2010) and was applied to group size
(TGR) and brain mass (TBM) but was not necessary for
NCR or CYP19A1 orthology. The Mahalanobis distance
procedure was used and the χ2
critical value = 18.467, df = 4
indicates no outliers. A regression was produced using NCR
as the dependent variable. The independent variables include
TGR, TBM, and CYP19A1 orthology as an estimate for

Malone 7
Figure 4. Alignment of CYP19A1 with 21 vertebrate species to the human genome. The dashed lines indicate regions identified as
transcripts that allow for tissue specific expression: 1. Placenta major, 2. Placenta minor 2, 3. Skin & Adipose tissues, 4. Fetal tissues, 5. Brain,
6. Placenta minor 1, 7. Ovary and Breast Cancer, Endometriosis, and Bone, 8. Aromatase enzyme. CYP19A1 organization does not follow a
trend in elephant, microbat (the vision dependent megabat is provided for contrast), dolphin, or the prosimians, but expands and unifies in
monkeys and finally appears on the same chromosome in apes. Upward signals from the selective sweep scan indicate those sections with
greater Neanderthal specificity, while downward signals are suggestive of positive selection in early humans (Green et al., 2010).
Table 1. CYP19A1 Orthology for Nine Key Primate Species With the Current Human Genome Sequence.
Common name Species % orthologous NCR Group no.
Chimpanzee P. troglodytes .9981 3.22 53.5
Western lowland gorilla G. gorilla gorilla .9962 2.65 17.0
Sumatran orangutan P. pygmaeus abelii .9886 2.47 5.0
Hamadryas baboon P. hamadryas .9791 2.76 51.2
Rhesus macaque monkey M. mulatta .9733 2.60 39.6
Common marmoset C. jacchus .9339 1.52 8.5
Philippine tarsier T. syrichta .8582 1.09 2.0
Gray mouse lemur M. murinus .8668 1.23 9.5
Northern greater galago O. garnettii .8820 0.94 2.0
evolutionary trend toward increased phenotypic plasticity.
Most methods yield the same slope estimates when R2
> .9
(Mertler & Vannatta, 2010) and the linear regression was
produced, R2
= .994, adjusted R2
= .989, F(3, 5) = 143.758,
p < .001, two-tailed (Figure 5) using SPSS v 18. This model
accounts for 99% of variance in primate brain evolution

8 SAGE Open
without threat of multicollinearity as the variance inflation
factor for all variables is below 10 and all collinearity toler-
ance statistics are above 0.1 (Mertler & Vannatta, 2010;
O’Brien, 2007). A reaction surface (Wu et al., 2007; Yap,
Yao, Das, Li, & Wu, 2011) of TGR, TBM, and NCR on
CYP19A1 is produced using MS Excel®
(Figure 6) that illus-
trates significant changes from prosimians, to monkey, and
finally to great apes.
It is clear that CYP19A1 has increased in size and com-
plexity in a way that trends with phylogeny and strongly cor-
relates to previous models describing human brain evolution.
Data from exon microarray expression (Johnson et al., 2009)
demonstrate that within the fetal brain, regions otherwise
considered key for tissue-specific transcription become fun-
damental aspects of fine regulation in at least 13 regions of
the brain and for both hemispheres (Figure 7). Histone map-
ping provides evidence of regulation through developmental
stages by gender, and the data sets (Figure 8) appear to vali-
date previous hypotheses (Cheung et al., 2010; Malone,
2012). Seven-nucleotide seed targets (CYP19A1: miR-539,
ATTTCTCA,score:65andCYP19A1:let-7/98,CTACCTCA,
score: 98) were detected (Figure 8) within all known miRNA
families conserved across mammals from multiz alignments
(Friedman et al., 2009; Lewis et al., 2005) and assigned scores
based on context (Grimson et al., 2007).
RNA transcription levels (ENCODE Project Consortium
et al., 2011) from seven cell lines (lymphoblastoid, embry-
onic stem cell, human skeletal muscle myoblasts, human
umbilical vein endothelial cells, human erythromyeloblas-
toid leukemia cells, normal human epidermal keratinocytes,
and normal human lung fibroblasts) suggest greater degrees
of regulation than previously specified (Figure 8) by
Sebastian and Bulun (2001). Regulation of alternative pro-
moters by tissue-specific DNA methylation (Figure 8) was
determined and MRE-seq, MeDIP-seq, H3K4me3 ChIP-
seq, RNA-seq and RNA-seq (SMART) libraries were
sequenced (Maunakea et al., 2010; Morin et al., 2008;
Robertson et al., 2007) using data available through National
Center for Biotechnology Information (Accession Number
SRP002318).
Single nucleotide polymorphisms, small insertions, and
deletions with at least 0.01 minor allele frequencies were
determined in an attempt to isolate common variants in the
general population (Sherry et al., 2001) relative to UCSC and
Genscan gene databases. Taken together, the above data sets
appear to validate another study (C. E. Collins et al., 2010),
and provides strong evidence that CYP19A1 demonstrates
the capacity for genetic accommodation (a) specific to indi-
vidual brain regions, (b) by gender, (c) across all develop-
mental stages, and with (d) broad variability previously
hypothesized (Malone, 2012).
Discussion
Evolutionary biology must inform evolutionary psychology
if it is to contribute to the study of development and its disor-
der. For some species, genetic accommodation is the pheno-
type upon which selection critically operates. The evolution
of myriad regulatory mechanisms on primate brain develop-
ment permits wide ranging synaptic reorganization in
response to as many ecotypes. Thus, epigenetic tuning of
infant genotype expression, and a plastic response to stimuli
during stages of developmental sensitivity, may result in a
broad spectrum of phenotypes from the same genotype. The
richness or paucity of environmental stimuli defines an eco-
type’s character; stimulus type, duration, and intensity
describe its potential for influence; yet the individual’s phe-
Figure 5. The SPSS v.18 normal P-P plot of regression
standardized residuals. Neocortex ratio is the dependent variable,
with CYP19A1 orthology, group size, and total brain mass as
independent variables. The expected cumulative probability
represents the model R2
= .994, and the X-axis illustrates the
cumulative probability observed in nature for each species.
Figure 6 The reaction surface for group size (TGR), total brain
mass (TBM), or neocortex ratio (NCR) suggests little overall
impact on CYP19A1 in prosimians but it is substantial in the great
apes. This reaction surface illustrates some of the phenotypic
variation generated when genetically diverse individuals of the
same or related species encounter and adapt to variform ecotypes.

Malone 9
notypic plasticity, as modified by gender and age of expo-
sure, will modify the consequences.
Unfortunately, great phenotypic plasticity is expensive
because it requires multiple overlapping systems operating
in concert. The only gene capable of so broadly influencing
the human brain’s malleable periods of cognitive, emotional,
and social sensitivity with gender bias in health and disorder
is CYP19A1. This work presents a new framework to
approach many forms of developmental disorder and offers
new hope to those suffering many pervasive forms.
Furthermore, by assessing tissue- and site-specific expres-
sion regulation through techniques such as histone mapping,
identification of allelic differences, miRNA characterization,
and accurate accounting of meaningful polymorphisms (see
Anthoni et al., 2012) true biological assay and molecular
routes to treatment appear well within reach. Detailing each
site-specific regulatory phase for CYP19A1 may reveal a
large pool of data to illuminate the genesis of developmental,
mood, and personality disorders in every stage of life.
Histones may be thought of as molecular spools around
which tightly wound DNA is wrapped to pack the almost
2-m strand into a single cell. When an aspect of the genome
is actively used, it must unwind from the histone, and so his-
tone mapping seeks to label regions where genetic expres-
sion is active and potentially modified in some way.
Transcription levels may be altered by normal cell mecha-
nisms, and by chemicals from elsewhere in the body, such as
certain nutrients or toxins. Depending upon the importance
Figure 7. Exon expression by brain region. Consolidated, and then expanded for visualization, the exon microarray expression data
from 13 brain regions of late mid-fetal human brains are grouped by regional mean as log-ratios. CYP19A1 regulation occurs throughout
fetal and neonatal development, influences learning through its impact on brain plasticity, and is linked to developmental disorders due to
its direct and indirect regulation of neuroprotective mechanisms and the neuroinflammatory response.

10 SAGE Open
and complexity of the gene, a wide range of phenotypic pro-
files arise from histone transcription regulation, and it is sat-
isfying to find that histone mapping of CYP19A1 appears to
validate several previous studies (Kritzer, 2006; Luine et al.,
2003; Ma et al., 1993; McCarthy, 2008; Rasmussen et al.,
1990). Because many of the techniques described in this
work can be performed with formaldehyde-preserved tis-
sues, it is now feasible to track the evolution of site-specific
regulatory mechanisms with fine detail across all brain
regions and throughout the entire chordate phylum.
The miRNA data presented (Figure 8) suggest that pri-
mary expression regulation of P450arom gene in placenta
occurs at the level of transcription and the tissue-specific
region is conserved throughout the mammalian class
(Helgen, 2011). It is perhaps important to note that the
same tissue-specific transcript carries the weight of
Neanderthal-specific deviation (Figure 4). It is reasonable
to suggest Neanderthal experienced no difference in
expression, due to synonymous substitutions and equiva-
lent amino acid variations, but this could represent
maternal reproductive adaption in response to dietary DHA
availability. Human CYP19A1 transcription levels are
highest in regions dedicated to reproductive tissues and the
brain (Figure 8), and these areas show positive selection in
early humans (Figure 4).
Increased gyral white matter in the human prefrontal cor-
tex (PFC) suggests selection in primates for risk assessment,
emotional restraint, attention maintenance, meta-awareness,
working memory, imitative learning, goal-directed behavior,
communication (including use of gaze), and decision making
(Barth, Reaux, & Povinelli, 2005; Beran & Evans, 2006;
Boesch, 1993, 1996; Casey, Galvan, & Hare, 2005; Casey,
Tottenham, Liston, & Durston, 2005; Caviness, Kennedy,
Richelme, Rademacher, & Filipek, 1996; Courchesne et al.,
2000; Evans & Beran, 2007a, 2007b; Giedd et al., 1999;
Jurado & Rosselli, 2007; Lenroot & Giedd, 2006; Miller,
2000; Miller & Cohen, 2001; Müller, Radtke & Wissing,
2002; Suddendorf & Whiten, 2001; Voytek & Knight, 2010;
Xi et al., 2011). Though ascribing a “reason” for some trait to
evolve is often problematic, these data seem to correlate with
Figure 8. Fine regulation of CYP19A1 by gender, across lifetime developmental stages, as detected by histone mapping, miRNA regulation,
transcription level, cytosine-guanine (CG) methylation, and known simple nucleotide polymorphisms (SNPs). This degree of regulation
is necessary because CYP19A1 transforms testosterone into neuroprotective estradiol and coordinates the conversion of omega-3 fatty
acids into DHA while competitively inhibiting proinflammatory AA. Axonal elongation, myelination, neurite outgrowth, arborization,
synaptogenesis, generation of neuroprotectin D1, inhibition of apoptosis, and targeted physiological debridement are thus modulated by
CYP19A1 with extreme regulation.

Malone 11
(a) increased DHA production in mammary tissues (Caspi et
al., 2007; Lammi-Keefe, Rozowski, Parodi, Sobrevia, &
Foncea, 2008), (b) increased DHA uptake by the placenta
(Campbell, Gordon, & Dutta-Roy, 1996; Dutta-Roy, 2000),
(c) both of which are required for proportionally thicker
cortical white matter in the growing human brain (Allman
et al., 1993; Allman, Hakeem, & Watson, 2002; Smaers,
Schleicher, Zilles, & Vinicius, 2010).
For many decades, the common approach to genetics was
to study artificially induced and naturally occurring muta-
tions as a means to understand normal gene expression. This
author asserts that as great phenotypic plasticity is the pri-
mary character trait selected for, the search for genes linked
to developmental disorder that also demonstrate phyloge-
netic trends in orthology will reveal those genes most critical
to human brain evolution. This author is currently assessing
genes known linked to human brain development and disor-
der to determine what may be the core genomic set respon-
sible for human brain evolution (preliminary results provided
in Table 2). Those genes demonstrating higher orthology fur-
ther from primates specifically, and toward placental mam-
mal, marsupial, monotreme, reptile, and so on provide
estimation for when in evolution those genes became most
selectively advantageous. It is important to point out that the
FOXP2 and HOX genes did not display strong positive
orthologous correlation, suggesting that while these genes
were important to the evolution of a central nervous system,
they did not play a central role in human brain evolution
specifically.
Authors’ Note
Raw data for the exon microarray expression may be obtained
through the NCBI Gene Expression Omnibus http://www.ncbi.nlm.
nih.gov/geo. All in silico hybridizations, histone mapping, DNA
methylation assessment, and assessment of CYP19A1 SNPs were
processed using the UCSC Genome Browser on Human February
2009 (GRCh37/hg19) Assembly, the UCSC, Ensembl, Genscan,
and RefSeq databases, and ENCODE data.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research and/or
authorship of this article.
Table 2. Preliminary Results Using the Orthology Correlation Technique on 158 Genes.
Demonstrates positive correlation Little to no positive correlation
ADH5, ADORA1, ADORA1, ADORA2A, ACHE, APBB1, ASCL1, BMP4, BMP4,
AF361886, ALK, APBB1, APOE, APP, CACNA1G*, CDH9*, CDH10*,
ARTN, BCL2, BDNF, BDNF, BMP2, NTNAP2*, EN2*, FADS2, FOXP2*,
BMP8B, CDK5RAP2, CHRM2, CREB1, GABRA4*, GABRB3*, GSTP1*,
CTH, CXCL1, CYP19A1, DCX, DISC1, HOXA1*, HOXB1*, MAFG, MAFK,
DISC2, DLG4, DLL1, DNAJC3, DRD2, MAPK3*, MDK, MDK, MECP2*, MET*,
DRD2, DVL3, E2F1, E2F8, EFNB1, NDN, NEUROG1, NLGN3*, NRXN1*,
EGF, EIF2AK3, EIF2S1, EP300, ERBB2, OLIG2, OXTR*, POU4F1, POU4F1,
ESR1, FADD, FADS1, FADS3, FADS6, PRKCB1*, PRL*, PRLR*, RELN*,
FGF2, FLNA, GDNF, GLO2, GLRX, ROBO1, SERT*, SHANK3*,
GLRX3, GPI, GRIN1, HAGH, HDAC4, SLC25A12*, SLC6A4*, SOX2, SOX8,
HDAC4, HES1, HEY1, HEY2, HEYL, IL3, TPH1, TPH2, TRVP2, TRVP4, UBE3A*
KEAP1, LONRF1, LONRF2, LONRF3,
MAP2, MEF2C, MET, MLL, NDN, NDP,
NEUROD1, NEUROG2, NF1, NFE2L2,
Nf-kB, NOG, NOTCH1, NOTCH2,
NR2E3, NRCAM, NRG1, NRP1, NRP2,
NTF3, NTN1, ODZ1, OLIG2,
PAFAH1B1, PARD3, PAX3, PAX5,
PAX6 PSMB5, PTN, RAC1, RTN4,
S100A6, S100B, S74017, SHH, SLIT2,
SOD1, STAT3, TFB1M, TFB2M, TGFB1,
TH, TNR, TRPV1, TRPV3, TRPV5,
TRPV6, VEGFA
Note: More than two dozen genes listed above were previously considered linked to developmental disorders, including autism, and are labeled with an
asterisk (*). It is important to understand that pathology purely due to genetics is considered a disease and not a disorder, and while each of those listed
may induce a disease with behavioral characters strikingly similar to those diagnostic of autism spectrum disorders, they seldom explain any aspect of the
gender bias, the influence of environmental stimuli, and never both together.

12 SAGE Open
References
Abramovich, D., & Rowe, P. (1973). Foetal plasma testosterone
levels at mid-pregnancy and at term: Relationship to foetal
sex. Journal of Endocrinology, 56, 621-622. doi:10.1677/
joe.0.0560621
Ahlquist, D. A., Duenes, J. A., Madson, T. H., Romero, J. C.,
Dozois, R., & Malagelada, J. R. (1982). Prostaglandin gen-
eration from gastroduodenal mucosa: Regional and species
differences. Prostaglandins, 24, 115-125. doi:10.1016/0090-
6980(82)90183-6
Aiello, L. C., & Wheeler, P. (1995). The expensive tissue hypoth-
esis: The brain and the digestive system in human and primate
evolution. Current Anthropology, 36, 199-221.
Ainsworth, M. D. S. (1969). Object relations, dependency, and
attachment: A theoretical review of the infant-mother relation-
ship. Child Development, 40, 969-1025. Retrieved from http://
psychology.psy.sunysb.edu/ewaters/552/PDF_Files/Attach-
depend.PDF
Ainsworth, M. D. S., Blehar, M. C., Waters, E., & Wall, S. (1978).
Patterns of attachment: A psychological study of the strange
situation. Hillsdale, NJ: Erlbaum.
Allman, J. M., Hakeem, A., & Watson, K. (2002). Two phyloge-
netic specializations in the human brain. Neuroscientist, 8,
335-346.
Allman, J. M., McLaughlin, T., & Hakeem, A. (1993). Brain struc-
tures and life-span in primate species. Proceedings of the
National Academy of Sciences of the United States of America,
90, 3559-3563. doi:10.1073/pnas.90.8.3559
Angelidou, A., Asadi, S., Alysandratos, K. D., Karagkouni, A.,
Kourembanas, S., & Theoharides, T. C. (2012). Perinatal stress,
brain inflammation and risk of autism—Review and proposal.
BMC Pediatrics, 12(1), 89. doi:10.1186/1471-2431-12-89.
Anthoni, H., Sucheston, L. E., Lewis, B. A., Tapia-Paez, I., Fan,
X., Zucchelli, M., & . . .Kere, J. (2012). The aromatase gene
CYP19A1: Several genetic and functional lines of evidence
supporting a role in reading, speech, and language. Behavioral
Genetics, 42, 509-527. doi:10.1007/s10519-012-9532-3
Arai, Y., Sekine, Y., & Murakami, S. (1996). Estrogen and apop-
tosis in the developing sexually dimorphic preoptic area in
female area in female rats. Neuroscience Research, 25, 403-
407. doi:10.1016/0168-0102(96)01070-X
Armstrong, E. (1985). Relative brain size in monkeys and prosimi-
ans. American Journal of Physical Anthropology, 66, 263-273.
doi:10.1002/ajpa.1330660303
Azcoitia, I., Arevalo, M. A., De Nicola, A. F., & Garcia-Segura,
L. M. (2011). Neuroprotective actions of estradiol revis-
ited. Trends in Endocrinology & Metabolism, 22, 467-473.
doi:10.1016/j.tem.2011.08.002
Bard, K. A. (2012). Emotional engagement: How chimpanzees
minds develop. In F. De Waal & P. Ferrari (Eds.), The primate
mind: Built to connect with other minds (pp. 1-28). Cambridge,
MA: Harvard University Press. Retrieved from http://port.aca-
demia.edu/KimBard/Papers/326394/Emotional_engagement_
How_chimpanzee_minds_develop
Bard, K. A., & Gardner, K. H. (1996). Influences on development
in infant chimpanzees: Enculturation, temperament, and cog-
nition. In A. E. Russon, K. A. Bard, & S. T. Parker (Eds.),
Reaching into thought: The minds of the great apes (pp. 235-
256). Cambridge, UK: Cambridge University Press.
Barth, J., Reaux, J. E., & Povinelli, D. J. (2005). Chimpanzees’(Pan
troglodytes) use of gaze cues in object-choice tasks: Different
methods yield different results. Animal Cognition, 8, 84-92.
doi:10.1007/s10071-004-0235-x
Barton, R. A. (1996). Neocortex size and behavioural ecology in pri-
mates. Proceedings of the Royal Society of London, Biological
Sciences, 263, 173-177. doi:10.1098/rspb.1996.0028
Bastarache, J. A., Diamond, J. M., Kawut, S. M., Lederer, D. J.,
Ware, L. B., & Christie, J. D. (2012). Postoperative estradiol
levels associate with development of primary graft dysfunction
in lung transplantation patients. Gender Medicine, 9, 154-165.
doi:10.1016/j.genm.2012.01.009
Bastian, M. L., Sponberg, A. C., Suomi, S. J., & Higley, J. D.
(2003). Long-term effects of infant rearing condition on the
acquisition of dominance rank in juvenile and adult rhesus
macaques (Macaca mulatta). Developmental Psychobiology,
42, 44-51. doi:10.1002/dev.10091
Bechlioulis, A., Naka, K. K., Kalantaridou, S. N., Kaponis, A.,
Papanikolaou, O., Vezyraki, P., & . . . Michalis, L. K. (2012).
Increased vascular inflammation in early menopausal women
is associated with hot flush severity. Journal of Clinical
Endocrinology & Metabolism, 97, E760-E764. doi:10.1210/
jc.2011-3151
Becker, K. G. (2012). Male gender bias in autism and pediatric auto-
immunity. Autism Research, 5, 77-83. doi:10.1002/aur.1227
Belsky, J., & de Haan, M. (2011). Annual research review:
Parenting and children’s brain development: The end of the
beginning. Journal of Child Psychology and Psychiatry, 52,
409-428. doi:10.1111/j.1469-7610.2010.02281.x
Beran, M. J., & Evans, T. A. (2006). Maintenance of delay of grati-
fication by four chimpanzees (Pan troglodytes): The effects
of delayed reward visibility, experimenter presence, and
extended delay intervals. Behavioural Processes, 73, 315-324.
doi:10.1016/j.beproc.2006.07.005
Beyer, C. (1999). Estrogen and the developing mammalian brain.
Anatomy and Embryology, 199, 379-390. doi:10.1007/
s004290050236
Blanchette, M., Kent, W. J., Riemer, C., Elnitski, L., Smit, A. F.,
Roskin, K. M., & . . . Miller, W. (2004). Aligning multiple
genomic sequences with the threaded blockset aligner. Genome
Research, 14, 708-715. doi:10.1101/gr.1933104
Blaylock, R. L., & Strunecka, A. (2009). Immune-glutamatergic
dysfunction as a central mechanism of the autism spec-
trum disorders. Current Medicinal Chemistry, 16, 157-170.
doi:10.2174/092986709787002745
Blumenfeld-Katzir, T., Pasternak, O., Dagan, M., & Assaf, Y.
(2011). Diffusion MRI of structural brain plasticity induced by
a learning and memory task. PLoS ONE, 6, 1-9. doi:10.1371/
journal.pone.0020678
Boesch, C. (1993). Towards a new image of culture in wild
chimpanzees? Behavioral and Brain Sciences, 16, 514-515.
doi:10.1017/S0140525X00031277
Boesch, C. (1996). Three approaches for assessing chimpanzee
culture. In A. E. Russon, K. A. Bard, & S. T. Paker (Eds.),
Reaching into thought: The minds of the great apes (pp. 404-
429). Cambridge, UK: Cambridge University Press.
Bölte, S., Hubl, D., Feineis-Matthews, S., Pruvulovic, D., Dierks,
T., & Poustka, F. (2006). Facial affect recognition training
in autism: Can we animate the fusiform gyrus? Behavioral
Neuroscience, 120, 211-216. doi:10.1037/0735-7044.120.1.21

Malone 13
Bowlby, J. (1969). Attachment and loss: Vol. 1. Attachment. New
York, NY: Basic Books.
Bowlby, J. (1988). A secure base: Clinical applications of attach-
ment theory. London, England: Routledge.
Brent, L., Lee, D. R., & Eichberg, J. W. (1989). The effects of
single caging on chimpanzee behavior. Laboratory Animal
Science, 39, 345-346.
Bretherton, I. (1992). The origins of attachment theory: John
Bowlby and Mary Ainsworth. Developmental Psychology, 28,
759-775.
Briggs, A. W., Good, J. M., Green, R. E., Krause, J., Maricic, T.,
Stenzel, U., & . . . Pääbo, S. (2009). Targeted retrieval and
analysis of five Neandertal mtDNA genomes. Science, 325,
318-321. doi:10.1126/science.1174462
Brüne, M., Brüne-Cohrs, U., McGrew, W. C., & Preuschoft, S.
(2006). Psychopathology in great apes: Concepts, treatment
options and possible homologies to human psychiatric disor-
ders. Neuroscience & Biobehavioral Reviews, 30, 1246-1259.
doi:10.1016/j.neubiorev.2006.09.002
Burdge, G. C., Jones, A. E., & Wootton, S. A. (2002).
Eicosapentaenoic and docosapentaenoic acids are the principal
products of α-linolenic acid metabolism in young men. British
Journal of Nutrition, 88, 355-363. doi:10.1079/BJN2002662
Byrne, R. W., & Corp, N. (2004). Neocortex size predicts decep-
tion rate in primates. Proceedings of the Royal Society of
London, Biological Sciences, 271, 1693-1699. doi:10.1098/
rspb.2004.2780
Call, J., & Tomasello, M. (1998). Distinguishing intentional acts
from accidental actions in orangutans (Pongo pygmaeus),
chimpanzees (Pan troglodytes), and human children (Homo
sapiens). Journal of Comparative Psychology, 112, 192-206.
doi:10.1037/0735-7036.112.2.192
Campbell, F. M., Gordon, M. J., & Dutta-Roy, A. K. (1996).
Preferential uptake of long chain polyunsaturated fatty acids by
isolated human placental membranes. Molecular and Cellular
Biochemistry, 155, 77-83. doi:10.1007/BF00714336
Capitanio, J. P., Mendoza, S. P., Mason, W. A., & Maninger, N.
(2005). Rearing environment and hypothalamic-pituitary-
adrenal regulation in young rhesus monkeys (Macaca mulatta).
Developmental Psychobiology, 46, 318-330. doi:10.1002/
dev.20067
Casey, B. J., Galvan, A., & Hare, T. A. (2005). Changes in cere-
bral functional organization during cognitive development.
Current Opinion in Neurobiology, 15, 239-244. doi:10.1016/j.
conb.2005.03.012
Casey, B. J., Tottenham, N., Liston, C., & Durston, S. (2005).
Imaging the developing brain: What have we learned about
cognitive development? Trends in Cognitive Sciences, 9, 104-
110. doi:10.1093/cercor/bhh129
Caspi, A., Williams, B., Kim-Cohen, J., Craig, I. W., Milne, B.
J., Poulton, R., & . . . Moffitt, T. E. (2007). Moderation of
breastfeeding effects on the IQ by genetic variation in fatty
acid metabolism. Proceedings of the National Academy of
Sciences of the United States of America, 104, 18860-18865.
doi:10.1073/pnas.0704292104
Caviness, V. S., Kennedy, D. N., Richelme, C., Rademacher, J. F.
P.A., & Filipek, P. A. (1996). The human brain age 7-11 years:
A volumetric analysis based on magnetic resonance images.
Cerebral Cortex, 6, 726-736. doi:10.1093/cercor/6.5.726
Chakrabarti, S., & Davidge, S. T. (2013). Estradiol modulates
tumor necrosis factor-induced endothelial inflammation:
Role of tumor necrosis factor receptor 2. Journal of Vascular
Research, 50, 21-34. doi:10.1159/000342736
Chen, F. S., & Johnson, S. C. (2012). An oxytoxin receptor gene
predicts attachment anxiety in females and autism-spectrum
traits in males. Social Psychological and Personality Science,
3, 93-99. doi:10.1177/1948550611410325
Chen, S. A., Besman, M. J., Sparkes, R. S., Zollman, S., Klisak, I.,
Mohandas, T., & . . .Shively, J. E. (1988). Human aromatase:
CDNA cloning, Southern blot analysis, and assignment of the
gene to chromosome 15. DNA, 7, 27-38.
Cherrier, M., Matusmoto, A., Amory, J., Johnson, M., Craft, S.,
Peskind, E. R., & Raskind, M. A. (2007). Characterization
of verbal and spatial memory changes from moderate to sup-
raphysiological increases in testosterone in healthy older
men. Psychoneuroendocrinology, 32, 72-79. doi:10.1016/j.
psyneuen.2006.10.008
Cheung, I., Shulha, H. P., Jiang, Y., Matevossian, A., Wang, J.,
Weng, Z., & Akbarian, S. (2010). Developmental regulation
and individual differences of neuronal H3K4me3 epigenomes
in the prefrontal cortex. Proceedings of the National Academy
of Sciences of the United States of America, 107, 8824-8829.
doi:10.1073/pnas.1001702107
Choudhury, P. R., Lahiri, S., & Rajamma, U. (2012). Glutamate
mediated signaling in the pathophysiology of autism spectrum
disorders. Pharmacology, Biochemistry and Behavior, 100,
841-849. doi:10.1016/j.pbb.2011.06.023
Clark, D. A., Mitra, P. P., & Wang, S. S.-H. (2001). Scalable
architecture in mammalian brains. Nature, 411, 189-193.
doi:10.1038/35075564
Clay, A. W. (2012). Attachment and early rearing: Longitudinal
effects in chimpanzees (Pan troglodytes) (Unpublished doc-
toral dissertation). Retrieved from http://smartech.gatech.edu/
handle/1853/43625
Clutton-Brock, T. H., & Harvey, P. H. (1980). Primates,
brains and ecology. Journal of Zoology, 190, 309-323.
doi:10.1111/j.1469-7998.1980.tb01430.x
Collins, C. E., Airey, D. C., Young, N. A., Leitch, D. B., & Kaas,
J. H. (2010). Neuron densities vary across and within corti-
cal areas in primates. Proceedings of the National Academy of
Sciences of the United States of America, 107, 15927-15932.
doi:10.1073/pnas, 1010356107
Collins, S. M., Surette, M., & Bercik, P. (2012). The interplay
between the intestinal microbiota and the brain. Nature Reviews
Microbiology, 10, 735-742. doi:10.1038/nrmicro2876
Conti, G., Hansman, C., Heckman, J. J., Novak, M. F., Ruggiero,
A., & Suomi, S. J. (2012). Primate evidence on the late health
effects of early-life adversity. Proceedings of the National
Academy of Sciences of the United States of America, 109,
8866-8871. doi:10.1073/pnas.1205340109
Courchesne, E., Chisum, H. J., Townsend, J., Cowles, A.,
Covington, J., Egaas, B., & . . . Press, G. A. (2000). Normal
brain development and aging: Quantitative analysis at in vivo
MR imaging in healthy volunteers1. Radiology, 216, 672-682.
Retrieved from http://radiology.rsna.org/content/216/3/672.
full.pdf+html
Coury, D. L., Ashwood, P., Fasano, A., Fuchs, G., Geraghty, M.,
Kaul, A., . . . Jones, N. E. (2012). Gastrointestinal conditions in

14 SAGE Open
children with autism spectrum disorder: Developing a research
agenda. Pediatrics, 130(Suppl. 2), S160-S168. doi:10.1542/
peds.2012-0900N
Davenport, R. K. (1979). Some behavioral disturbances of great
apes in captivity. In D. A. Hamburg & E. R. McCown (Eds.),
The great apes (pp. 341-357). Menlo Park, CA: Benjamin
Cummings.
Davenport, R. K., & Menzel, E. W. (1963). Stereotyped behavior
of the infant chimpanzee. Archives of General Psychiatry, 8,
99-104.
Davenport, R. K., & Rogers, C. M. (1970). Differential rearing of
the chimpanzee: A project survey. In G. H. Bourne (Ed.), The
chimpanzee (Vol. 3, pp. 337-360). Baltimore, MD: University
Park Press.
Davenport, R. K., Rogers, C. M., & Rumbaugh, D. M. (1973).
Long-term cognitive deficits in chimpanzees associated with
early impoverished rearing. Developmental Psychology, 9,
343-347. doi:10.1037/h0034877
Deacon, T. W. (1997). The symbolic species: The co-evolution of
language and the brain. New York, NY: W. W. Norton.
Deaner, R. O., Isler, K., Burkart, J., & van Schaik, C. (2007). Overall
brain size, and not encephalization quotient, best predicts cog-
nitive ability across non-human primates. Brain, Behavior and
Evolution, 70, 115-124. doi:10.1159/000102973
De Bellis, M. D., & Kuchibhatla, M. (2006). Cerebellar volumes
in pediatric maltreatment-related posttraumatic stress disor-
der. Biological Psychiatry, 60, 697-703. doi:10.1016/j.bio-
psych.2006.04.035
Diamond, M. C. (1991). Environmental influences on the young
brain. In K. R. Gibson & A. C. Peterson (Eds.), Brain matura-
tion and cognitive development (pp. 107-124). New York, NY:
Aldine De Gruyter.
Douin-Echinard, V., Calippe, B., Billon-Galès, A., Fontaine, C.,
Lenfant, F., Trémollières, F., . . . Gourdy, P. (2011). Estradiol
administration controls eosinophilia through estrogen receptor-α
activation during acute peritoneal inflammation. Journal of
Leukocyte Biology, 90, 145-154. doi:10.1189/jlb.0210073
Dunbar, R. I. M. (1992). Neocortex size as a constraint on group-
size in primates. Journal of Human Evolution, 22, 469-493.
doi:10.1016/0047-2484(92)90081-J
Dunbar, R. I. M. (1998). The social brain hypothesis. Evolutionary
Anthropology, 6, 178-190. doi:10.1002/(SICI)1520-6505
Dunbar, R. I. M. (2010). Brain and behavior in primate evolution. In
P. M. Kappeler & J. B. Silk (Eds.), Mind the gap: Tracing the
origins of human universals (pp. 319-502). London, England:
Springer.
Dunbar, R. I. M., & Shultz, S. (2007). Understanding primate brain
evolution. Philosophical Transactions of the Royal Society,
Biological Sciences, 362, 649-658. doi:10.1098/rstb.2006.2001
Dutta-Roy, A. K. (2000). Transport mechanisms for long-chain
polyunsaturated fatty acids in the human placenta. American
Journal of Clinical Nutrition, 71, 315s-322s. Retrieved from
http://ajcn.nutrition.org/content/71/1/315s.full
ENCODE Project Consortium, Myers, R. M., Stamatoyannopoulos,
J., Snyder, M., Dunham, I., Hardison, R. C., & . . . Searle, S.
(2011). A user’s guide to the encyclopedia of DNA elements
(ENCODE). PLoS Biology, 9, e1001046. doi:10.1371/journal.
pbio.1001046
Evans, T. A., & Beran, M. J. (2007a). Chimpanzees use self-
distraction to cope with impulsivity. Biology Letters, 3, 599-
602. doi:10.1098/rsbl.2007.0399
Evans, T. A., & Beran, M. J. (2007b). Delay of gratification and
delay maintenance by rhesus macaques (Macaca mulatta).
Journal of General Psychology, 134, 199-216. doi:10.3200/
GENP.134.2.199-216
Ferdowsian, H. R., Durham, D. L., Kimwele, C., Kranendonk, G.,
Otali, E., Akugizibwe, T., . . .Johnson, C. M. (2011). Signs of
mood and anxiety disorders in chimpanzees. PLoS One, 6, 1-
11. doi:10.1371/journal.pone.0019855
Fitch,R.H.,&Denenberg,V.H.(1998).Aroleforovarianhormones
in sexual differentiation of the brain. Behavioral and Brain
Sciences, 21, 311-352. doi:10.1017/S0140525X98001216
Foley, R. A., Lee, P. C., Widdowson, E. M., Knight, C. D., &
Jonxis, J. H. P. (1991). Ecology and energetics of encephaliza-
tion in hominid evolution. Philosophical Transactions of the
Royal Society, Biological Sciences, 334, 223-232. doi:10.1098/
rstb.1991.0111
Forest, M. G., Sizonenko, P. C., Cathiard, A. M., & Bertrand, J.
(1974). Hypophyso-gonadal function in humans during the first
year of life. I. Evidence for testicular activity in early infancy.
Journal of Clinical Investigation, 53, 819-828. doi:10.1172/
JCI107621
Friedman, R. C., Farh, K. K., Burge, C. B., & Bartel, D. P. (2009).
Most mammalian mRNAs are conserved targets of microRNAs.
Genome Research, 19, 92-105. doi:10.1101/gr.082701.108
Frye, R. E., Melnyk, S., & MacFabe, D. F. (2013). Unique acyl-
carnitine profiles are potential biomarkers for acquired mito-
chondrial disease in autism spectrum disorder. Translational
Psychiatry, 3, e220. doi:10.1038/tp.2012.143
Fukudome, Y., Tabata, T., Miyoshi, T., Haruki, S., Araishi, K.,
Sawada, S., & Kano, M. (2003). Insulin-like growth factor-
I as a promoting factor for cerebellar Purkinje cell develop-
ment. European Journal of Neuroscience, 17, 2006-2016.
doi:10.1046/j.1460-9568.2003.02640.x
Garcia-Segura, L. M. (2008). Aromatase in the brain: Not just for
reproduction anymore. Journal of Neuroendocrinology, 20,
705-712. doi:10.1111/j.1365-2826.2008.01713.x
Giedd, J. N., Blumenthal, J., Jeffries, N. O., Castellanos, F. X., Liu,
H., Zijdenbos, A., & . . . Rapoport, J. L. (1999). Brain develop-
ment during childhood and adolescence: A longitudinal MRI
study. Nature Neuroscience, 2, 861-863. doi:10.1038/13158
Giltay, E. J., Gooren, L. J. G., Toorians, A. W. F.T., Katan, M. B.,
& Zock, P. L. (2004). Docosahexanoic acid concentrations are
higher in women than in men because of estrogenic effects.
American Journal of Clinical Nutrition, 80, 1167-1174.
Retrieved from http://www.ajcn.org/cgi/reprint/80/5/1167
Goodall, J. (1986). The chimpanzees of Gombe: Patterns of behav-
ior. Cambridge, MA: Belknap Press.
Green, P., & Yavin, E. (1998). Mechanisms of arachidonic acid and
Docosahexanoic acid accretion in the fetal brain. Journal of
Neuroscience Research, 52, 129-136. doi:10.1002/(SICI)1097-
4547(19980415)52:2<129::AID-JNR1>3.0.CO;2-C7
Green, R. E., Krause, J., Briggs, A. W., Maricic, T., Stenzel, U.,
Kircher, M., & . . . Mullikin, J. C. (2010). A draft sequence of
the Neandertal genome. Science, 328, 710-722. doi:10.1126/
science.1188021

Malone 15
Grimson, A., Farh, K. K., Johnston, W. K., Garrett-Engele, P., Lim,
L. P., & Bartel, D. P. (2007). MicroRNA targeting specific-
ity in mammals: Determinants beyond seed pairing. Molecular
Cell, 27, 91-105. doi:10.1016/j.molcel.2007.06.017
Grossman, M. I., Brazier, M. A. B., & Lechago, J. (Eds.). (1981).
Cellular basis of chemical messengers in the digestive system
(Vol. 23). Waltham, MA: Academic Press.
Hall, G. B. C., Szechtman, H., & Nahmias, C. (2003). Enhanced
salience and emotion recognition in autism: A PET study.
American Journal of Psychiatry, 160, 1439-1441. Retrieved
from http://ajp.psychiatryonline.org/cgi/reprint/160/8/1439
Hallmayer, J., Cleveland, S., Torres, A., Phillips, J., Cohen, B.,
Torigoe, T., & . . . Risch, N. (2011). Genetic heritability and
shared environmental factors among twin pairs with autism.
Archives of General Psychiatry, 68, 1095-1102. doi:10.1001/
archgenpsychiatry.2011.76
Hao, J., Rapp, P. R., Leffler, A. E., Leffler, S. R., Janssen, W. G.,
Lou, W., & . . . Morrison, J. H. (2006). Estrogen alters spine
number and morphology in prefrontal cortex of aged female
rhesus monkeys. Journal of Neuroscience, 26, 2571-2578.
doi:10.1523/JNEUROSCI.3440-05.2006
Harlow, H. (1974). Induction and alleviation of depressive states in
monkeys. In N. F. White (Ed.), Ethology and psychiatry (pp.
197-204). Toronto, Ontario, Canada: University of Toronto
Press.
Harlow, H., & Harlow, M. K. (1965). Effects of various mother-
infant relationships on rhesus monkey behaviors. In B. M. Foss
(Ed.), Determinants of infant behavior (Vol. 4, pp. 15-36).
London, England: Methuen.
Harvey, P. H., & Krebs, J. R. (1990). Comparing brains. Science,
249, 140-146. doi:10.1126/science.2196673
Hashimoto, M. O., Hossain, S., Shimada, T., Sugioka, K., Yamasaki,
H., Fujii, Y., & . . . Shido, O. (2002). Docosahexaenoic acid
provides protection from impairment of learning ability in
Alzheimer’s disease model rats. Journal of Neurochemistry,
81, 1084-1091. doi:10.1046/j.1471-4159.2002.00905.x
Hashimoto, M. O., Tanabe, Y., Fujii, Y., Kikuta, T., Shibata, H., &
Shido, O. (2005). Chronic administration of docosahexaenoic
acid ameliorates the impairment of spatial cognition learning
ability in amyloid ß–infused rats. Journal of Nutrition, 135,
549-555. Retrieved from http://jn.nutrition.org/cgi/content/
full/135/3/549
Healy, S., & Rowe, C. (2007). A critique of comparative studies
of brain size. Proceedings of the Royal Society of London,
BiologicalSciences,274,453-464.doi:10.1098/rspb.2006.3748
Helgen, K. M. (2011). The mammalian family tree. Science, 334,
458-459. doi:10.1126/science.1214544
Herculano-Houzel, S. (2009). The human brain in numbers:
A linearly scaled-up primate brain. Frontiers in Human
Neuroscience, 3, 1-11. doi:10.3389/neuro.09.031.2009
Herculano-Houzel, S. (2011). Scaling of brain metabolism with
a fixed energy budget per neuron: Implications for neuro-
nal activity, plasticity and evolution. PLoS ONE, 6, 1-9.
doi:10.1371/journal.pone.0017514
Herculano-Houzel, S., & Kaas, J. H. (2011). Gorilla and orang-
utan brains conform to the primate cellular scaling rules:
Implications for human evolution. Brain, Behavior and
Evolution, 77, 33-44. doi:10.1159/000322729
Hook, M. A., Lambeth, S. P., Perlman, J. E., Stavisky, R.,
Bloomsmith, M. A., & Schapiro, S. J. (2002). Inter-group
variation in abnormal behavior in chimpanzees (Pan trog-
lodytes) and rhesus macaques (Macaca mulatta). Applied
Animal Behaviour Science, 76, 165-176. doi:10.1016/S0168-
1591(02)00005-9
Horrocks, L. A., & Farooqui, A. A. (2004). Docosahexanoic acid in
the diet: Its importance in maintenance and restoration of neural
membrane function. Prostaglandins, Leukotrienes & Essential
Fatty Acids, 70, 361-372. doi:10.1016/j.plefa.2003.12.011
Horrocks, L. A., & Yeo, Y. K. (1999). Health benefits of docosa-
hexaenoic acid (DHA). Pharmacological Research, 40, 211-
225. doi:10.1006/phrs.1999.0495
Hu, V. W. (2013a). The expanding genomic landscape of autism:
Discovering the “forest” beyond the “trees.” Future Neurology,
8, 29-42. doi:10.2217/fnl.12.83
Hu, V. W. (2013b). From genes to environment: Using integra-
tive genomics to build a “systems-level” understanding of
autism spectrum disorders. Child Development, 84, 89-103.
doi:10.1111/j.1467-8624.2012.01759.x
Ikemoto, A., Kobayashi, T., Watanabe, S., & Okuyama, H. (1997).
Membrane fatty acid modifications of PC12 cells by arachi-
donate or docosahexaenoate affect neurite outgrowth by not
norepinephrine release. Neurochemical Research, 22, 671-678.
doi:10.1023/A:1027393724676
Itokazu, N., Ikegaya, Y., Nishikawa, M., & Matsuki, N. (2000).
Bidirectional actions of docosahexaenoic acid on hippocam-
pal neurotransmissions in vivo. Brain Research, 862, 211-216.
doi:10.1016/S0006-8993(00)02129-6
James, S. J. (2008). Oxidative stress and the metabolic pathology
of autism. In A. W. Zimmerman (Ed.), Autism: Current theo-
ries and evidence (pp. 245-268). Totowa, NJ: Humana Press.
doi:10.1007/978-1-60327-489-0_11
Jerison, H. J. (1973). Evolution of the brain and intelligence. New
York, NY: Academic Press.
Joffe, T. H., & Dunbar, R. I. M. (1997). Visual and socio-cognitive
information processing in primate evolution. Proceedings of
the Royal Society of London, Biological Sciences, 264, 1303-
1307. doi:10.1098/rspb.1997.0180
Johnson, M. B., Imamura, Y. K., Mason, C. E., Krsnik, Z., Coppola,
G., Bogdanović, B., & . . . Šestan, N. (2009). Functional
and evolutionary insights into human brain development
through global transcriptome analysis. Neuron, 62, 494-509.
doi:10.1016/j.neuron.2009.03.027
Jolly, A. (1966). Lemur social behavior and primate intelligence.
Science, 153, 501-506. doi:10.1126/science.153.3735.501
Jurado, M. B., & Rosselli, M. (2007). The elusive nature of
executive functions: A review of our current understanding.
Neuropsychology Review, 17, 213-233. doi:10.1007/s11065-
007-9040-z
Kalcher-Sommersguter, E., Preuschoft, S., Crailsheim, K., & Franz,
C. (2011). Social competence of adult chimpanzees (Pan trog-
lodytes) with severe deprivation history: I. An individual
approach. Developmental psychology, 47, 77-90. doi:10.1037/
a0020783
Kan, I., Melamed, E., Offen, D., & Green, P. (2007).
Docosahexaenoic acid and arachidonic acid are fundamen-
tal supplements for the induction of neuronal differentiation.
Journal of Lipid Research, 48, 513-517. doi:10.1194/jlr.
C600022-JLR200
Karolchik, D., Hinrichs, A. S., Furey, T. S., Roskin, K. M., Sugnet,
C. W., Haussler, D., & Kent, W. J. (2003). The UCSC Table

16 SAGE Open
Browser data retrieval tool. Nucleic Acids Research, 32(Suppl.
1), D493-D496. doi:10.1093/nar/gkh103
Kawakita, E., Hashimoto, M., & Shido, O. (2006). Docosahexaenoic
acid promotes neurogenesis in vitro and in vivo. Neuroscience,
139, 991-997. doi:10.1016/j.neuroscience.2006.01.021
Keller, F., Panteri, R., & Biamonte, F. (2010). Interaction between
genetic vulnerability and neurosteriods in Purkinje cells as a
possible neurological mechanism in autism spectrum disor-
ders. In A. W. Zimmerman (Ed.), Autism: Current theories and
evidence (pp. 209-231). Totowa, NJ: Humana Press.
Kempes, M. M., Gulickx, M. M. C., van Daalen, H. J. C., Louwerse,
A. L., & Sterck, E. H. M. (2008). Social competence is reduced
in socially deprived rhesus monkeys (Macaca mulatta). Journal
of Comparative Psychology, 122, 62-67. doi:10.1037/0735-
7036.122.1.62
Kent, W. J. (2002). BLAT—The BLAST-like alignment tool.
Genome Research, 12, 656-664. doi:10.1101/gr.229202
Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle,
T. H., Zahler, A. M., & Haussler, D. (2002). The human
genome browser at UCSC. Genome Research, 12, 996-1006.
doi:10.1101/gr.229102
Kim, H. Y., Akbar, M., & Kim, K. (2001). Inhibition of neuronal
apoptosis by polyunsaturated fatty acids. Journal of Molecular
Neuroscience, 16, 223-227. doi:10.1385/JMN:16:2-3:223
Kim, H. Y., Akbar, M., Lau, A., & Edsall, L. (2000). Inhibition
of neuronal apoptosis by docosahexaenoic acid (22:6n-3).
Role of phosphatidylserine in antiapoptotic effect. Journal
of Biological Chemistry, 275, 35215-35223. doi:10.1074/jbc.
M00444
Kritzer, M. F. (2006). Regional, laminar and cellular distribution of
immunoreactivity for ΕΡβ in the cerebral cortex of hormonally
intact, postnatally developing male and female rats. Cerebral
Cortex, 16, 1181-1192. doi:10.1093/cercor/bhj059
Krueger, F., Parasuraman, R., Iyengar, V., Thornburg, M., Weel, J.,
Lin, M., . . . Lipsky, R. H. (2012). Oxytocin receptor genetic
variation promotes human trust behavior. Frontiers in Human
Neuroscience, 6, 1-9. doi:10.3389/fnhum.2012.00004
Kudo, H., & Dunbar, R. I. M. (2001). Neocortex size and social
network size in primates. Animal Behavior, 62, 711-722.
doi:10.1006/anbe.2001.1808
Lammi-Keefe, C. J., Rozowski, J., Parodi, C. G., Sobrevia, L., &
Foncea, R. (2008). Docosahexaenoic acid (DHA) supplemen-
tation benefits pregnancy complicated with gestational diabe-
tes mellitus (GDM). FASEB Journal, 22, 702-731.
Lenroot, R. K., & Giedd, J. N. (2006). Brain development in chil-
dren and adolescents: Insights from anatomical magnetic reso-
nance imaging. Neuroscience & Biobehavioral Reviews, 30,
718-729. doi:10.1016/j.neubiorev.2006.06.001
Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005). Conserved seed
pairing, often flanked by adenosines, indicates that thousands
of human genes are microRNA targets. Cell, 120, 15-20.
doi:10.1016/j.cell.2004.12.035
Lindenfors, P. (2005). Neocortex evolution in primates: The “social
brain” is for females. Biology Letters, 1, 407-410. doi:10.1098/
rsbl.2005.0362
Love, T. M., Enoch, M.-A., Hodgkinson, C. A., Pecina, M., Mickey,
B., Koeppe, R. A., . . . Zubieta, J.-K. (2012). Oxytocin gene
polymorphisms influence human dopaminergic function in a
sex-dependent manner. Biological Psychiatry, 72, 198-206.
doi:10.1016/j.biopsych.2012.01.033
Luine, V. N., Jacome, L. F., Maclusky, N. J. (2003). Rapid
enhancement of visual and place memory by estrogens in rats.
Endocrinology, 144, 2836-2844. doi:10.1210/en.2003-0004
Lukiw, W. J., Cui, J.-G., Marcheselli, V. L., Bodker, M., Botkjaer,
A., Gotlinger, K., & . . . Bazan, N. G. (2005). A role for
docosahexaenoic acid-derived neuroprotectin D1 in neural
cell survival and Alzheimer’s disease. Journal of Clinical
Investigation, 115, 2774-2783. doi:10.1172/JCI25420
Lupien, S. J., McEwen, B. S., Gunnar, M. R., & Heim, C. (2009).
Effects of stress throughout the lifespan on the brain, behaviour
and cognition. Nature Reviews Neuroscience, 10, 434-445.
Ma, Z. Q., Spreafico, E., Polio, G., Santagati, S., Conti, E., Cattaneo,
E., & Maggi, A. (1993). Activated estrogen receptor mediates
growth arrest and differentiation of a neuroblastoma cell line.
Proceedings of the National Academy of Sciences of the United
States of America, 90, 3740-3744. doi:10.1073/pnas.90.8.3740
Maenner, M. J., Arneson, C. L., Levy, S. E., Kirby, R. S., Nicholas,
J. S., & Durkin, M. S. (2012). Brief report: Association between
behavioral features and gastrointestinal problems among
children with autism spectrum disorder. Journal of Autism
and Developmental Disorders, 42, 1520-1525. doi:10.1007/
s10803-011-1379-6
Maestripieri, D. (2003). Attachment. In D. Maestripieri (Ed.),
Primate psychology (pp. 108-143). Cambridge, MA: Harvard
University Press.
Main, K. M., Schmidt, I. M., & Skakkebæk, N. E. (2000). A Possible
role for reproductive hormones in newborn boys: Progressive
hypogonadism without the postnatal testosterone peak. Journal
of Endocrinology & Metabolism, 85, 4905-4907. doi:10.1210/
jc.85.12.4905
Makrides, M., Gibson, R. A., McPhee, A. J., Collins, C. T., Davis, P.
G., Doyle, L. W., & . . . Ryan, P. (2009). Neurodevelopmental
outcomes of preterm infants fed high-dose docosahexaenoic
acid. Journal of the American Medical Association, 301, 175-
182. doi:10.1001/jama.2008.945
Malone, J. P. (2011a, August). Autistogenesis: A systems theory
with evolutionary perspective. Poster presented at the American
Psychological Association 119th Annual Convention,
Washington, DC.
Malone, J. P. (2011b, July). Autistogenesis: A systems theory with
evolutionary perspective. Poster presented at the Autism Society,
41st National Conference, Orlando, FL. Retrieved from http://
asa.confex.com/asa/2011/webprogram/Paper1750.html
Malone, J. P. (2011c, April). The systems theory of autistogene-
sis and its evolutionary implications. Poster presented at the
Western Psychological Association 91st Annual Convention,
Los Angeles, CA. Retrieved from http://www.westernpsych.
org/pdf/WPA%202011%203rd%20Proof.pdf
Malone, J. P. (2011d, July). Video documentation of an autistic
chimpanzee and her neurobiologically developmentally appro-
priate treatment. Poster presented at the Autism Society, 41st
National Conference, Orlando, FL. Retrieved from http://asa.
confex.com/asa/2011/webprogram/Paper1791.html [video
available at http://www.youtube.com/watch?v=qZ-Pq6slH3Q]
Malone, J. P. (2012). The systems theory of autistogen-
esis: Putting the pieces together. SAGE Open, 2, 1-8.
doi:10.1177/2158244012444281
Maunakea, A. K., Nagarajan, R. P., Bilenky, M., Ballinger, T.
J., D’Souza, C., Fouse, S. D., . . . Costello, J. F. (2010).
Conserved role of intragenic DNA methylation in regulating

Malone 17
alternative promoters. Nature, 466, 253-257. doi:10.1038/
nature09165
McCarthy, M. M. (2008). Estradiol and the developing brain.
Physiological Reviews, 88, 91-124. doi:10.1152/phys-
rev.00010.2007
McGrew, W. C. (1992). Chimpanzee material culture: Implications
for human evolution. Cambridge, UK: Cambridge University
Press.
McNamara, R. K. (2010). DHA deficiency and prefrontal cortex
neuropathology in recurrent affective disorders. Journal of
Nutrition, 140, 864-868. doi:10.3945/jn.109.113233
Mertler, C. A., & Vannatta, R. A. (2010). Advanced and multi-
variate statistical methods (4th ed.). Glendale, CA: Pyrczak
Publishing.
Miller, E. K. (2000). The prefrontal cortex and cognitive control.
Nature Reviews Neuroscience, 1, 59-66. doi:10.1038/35036228
Miller, E. K., & Cohen, J. D. (2001). An integrative theory of pre-
frontal cortex function. Annual Review of Neuroscience, 24,
167-202. doi:10.1146/annurev.neuro.24.1.167
Morin, R. D., Bainbridge, M., Fejes, A., Hirst, M., Krzywinski, M.,
Pugh, T. J., & . . . Marra, M. A. (2008). Profiling the HeLa
S3 transcriptome using randomly primed cDNA and massively
parallel short-read sequencing. Biotechniques, 45, 81-94.
doi:10.2144/000112900
Morris, M. C., Evans, D. A., Bienias, J. L., Tangney, C. C., Bennett,
D. A., Wilson, R. S., & . . . Schneider, J. (2003). Consumption
of fish and n-3 fatty acids and risk of incident Alzheimer dis-
ease. Archives of Neurology, 60, 940-946. doi:10.1001/arch-
neur.60.7.940
Mukai, H., Tsurugizawa, T., Murakami, G., Kominami, S., Ishii,
H., Ogiue-Ikeda, M., & . . . Kawato, S. (2007). Rapid mod-
ulation of long-term depression and spinogenesis via syn-
aptic estrogen receptors in hippocampal principal neurons.
Journal of Neurochemistry, 100, 950-967. doi:10.1111/j.1471-
4159.2006.04264.x
Müller, R. H., Radtke, M., & Wissing, S. A. (2002). Nanostructured
lipid matrices for improved microencapsulation of drugs.
International Journal of Pharmaceutics, 242, 121-128.
doi:10.1016/S0378-5173(02)00180-1
Mustard, J. F., & McCain, M. N. (2000). Early years study final
report: Reversing the real brain drain. Toronto, Canada:
Ontario Children’s Secretariat.
Nanick, E. F. G., Lucassen, P. J., & Bakker, J. (2011). Sex differ-
ences in adolescent depression: Do sex hormones determine
vulnerability? Journal of Neurobiology, 23(55), 1-10.
Nash, L. T., Fritz, J., Alford, P. A., & Brent, L. (1999). Variables
influencing the origins of diverse abnormal behaviors in a large
sample of captive chimpanzees (Pan troglodytes). American
journal of Primatology, 48, 15-29. doi:10.1002/(SICI)1098-
2345(1999)48:1<15::AID-AJP2>3.3.CO;2-I
Nissenson, R., Flouret, G., & Hechter, O. (1978). Opposing effects
of Estradiol and progesterone on oxytocin receptors in rabbit
uterus. Proceedings of the National Academy of Sciences of
the United States of America, 75, 2044-2048. doi:10.1073/
pnas.75.4.2044
O’Brien, R. M. (2007). A caution regarding rules of thumb for
variance inflation factors. Quality & Quantity, 41, 673-690.
doi:10.1007/s11135-006-9018-6
Okada, M., Amamoto, T., Tomonaga, M., Kawachi, A., Yazawa, K.,
Mine, K., & Fujiwara, M. (1996). The chronic administration
of Docosahexaenoic acid reduces the spatial cognitive deficit
following transient forebrain ischemia in rats. Neuroscience,
71, 17-25. doi:10.1016/0306-4522(95)00427-0
Paolicelli, R. C., Bolasco, G., Pagani, F., Maggi, L., Scianni, M.,
Panzanelli, R., & . . . Gross, C. T. (2011). Synaptic pruning by
microglia is necessary for normal brain development. Science,
333, 1456-1458. doi:10.1126/science.1202529
Pawlowski, B., Lowen, C. B., & Dunbar, R. I. M. (1998).
Neocortex size, social skills and mating success in primates.
Behaviour, 135, 357-368. Retrieved from http://www.jstor.org/
stable/4535532
Poling, J. S., Vicini, S., Rogawski, M. A., & Salem, N., Jr. (1996).
Docosahexanoic acid block of neuronal voltage-gated K+ chan-
nels:Subunitselectiveantagonismbyzinc.Neuropharmacology,
35, 969-982. doi:10.1016/0028-3908(96)00127-x
Prange-Kiel, J., & Rune, G. M. (2006). Direct and indirect effects
of estrogen on rat hippocampus. Neuroscience, 138, 765-772.
doi:10.1016/j.neuroscience.2005.05.061
Quesada, A., Lee, B. Y., & Micevych, P. E. (2009). PI3 kinase/
Akt activation mediates estrogen and IGF-1 nigral DA
neuronal neuroprotection against a unilateral rat model of
Parkinson’s disease. Developmental Neurobiology, 65, 632-
644. doi:10.1002/dneu.20609
Raimundo, N., Song, L., Shutt, T. E., McKay, S. E., Cotney, J.,
Guan, M. X., & . . . Shadel, G. S. (2012). Mitochondrial stress
engages E2F1 apoptotic signaling to cause deafness. Cell, 148,
716-726. doi:10.1016/j.cell.2011.12.027
Rao, J. S., Kim, H.-W., Kellom, M., Greenstein, D., Chen, M.,
Kraft, A. D., . . . Basselin, M. (2011). Increased neuroinflam-
matory and arachidonic acid cascade markers, and reduced
synaptic proteins, in brain of HIV-1 transgenic rats. Journal
of Neuroinflammation, 8, 1-13. doi:10.1186/1742-2094-8-101
Rao, J. S., Rapoport, S. I., & Kim, H.-W. (2011). Altered neuroin-
flammatory, arachidonic acid cascade and synaptic biomark-
ers in post-mortem Alzheimer’s disease brain. Translational
Psychiatry, 1, 1-9. doi:10.1038/tp.2011.27
Rapoport, S. I., Ramadan, E., & Basselin, M. (2011). Docosahexae-
noic acid (DHA) incorporation into the brain from plasma, as
an in vivo biomarker of brain DHA metabolism and neuro-
transmission. Prostaglandins Other Lipid Mediators, 96, 109-
113. doi:10.1016/j.prostaglandins.2011.06.003
Rapoport, S. I., Rao, J. S., & Igarashi, M. (2007). Brain metabolism of
nutritionallyessentialpolyunsaturatedfattyacidsdependsonboth
the diet and the liver. Prostaglandins, Leukotriens & Essential
Fatty Acids, 77, 251-261. doi:10.1016/j.plefa.2007.10.023
Rasmussen, J. E., Torres-Aleman, I., MacLusky, N. J., Naftolin, F.,
& Robbins, R. J. (1990). The effects of estradiol on the growth
patterns of estrogen receptor-positive hypothalamic cell lines.
Endocrinology, 126, 235-240. doi:10.1210/endo-126-1-235
Reader, S. M., & Laland, K. N. (2002). Social intelligence, innova-
tion and enhanced brain size in primates. Proceedings of the
National Academy of Sciences of the United States of America,
99, 4436-4441. doi:10.1073/pnas.062041299
Real, S., Meo-Evoli, N., Espada, L., & Tauler, A. (2011). E2F1
regulates cellular growth by mTORC1 signaling. PloS One, 6,
1-12. doi:10.1371/journal.pone.0016163

18 SAGE Open
Ridley, R. M., & Baker, H. F. (1982). Stereotypy in monkeys and
humans. Psychological Medicine, 12, 61-72. doi:10.1017/
S0033291700043294
Robertson, G., Hirst, M., Bainbridge, M., Bilenky, M., Zhao, Y.,
Zeng, T., & . . . Jones, S. (2007). Genome-wide profiles of
STAT1 DNA association using chromatin immunoprecipita-
tion and massively parallel sequencing. Nature Methods, 4,
651-657. doi:10.1038/nmeth1068
Rodman, P. S. (1993). Diversity and consistency in ecology and
behavior. In R. Tilson, K. Traylor-Holzer, & U. Seal (Eds.),
Orangutan population and habitat viability analysis workshop:
Briefing book (pp. 31-51). Oxford, UK: Oxford University
Press.
Rodseth, L., Wrangham, R., W., Harrigan, A. M., & Smuts,
B. B. (1991). The human community as a primate soci-
ety [and comments]. Current Anthropology, 32, 221-254.
doi:10.1086/203952
Rose, S., Melnyk, S., Pavliv, O., Bai, S., Nick, T. G., Frye, R.
E., & James, S. J. (2012). Evidence of oxidative damage and
inflammation associated with low glutathione redox status in
the autism brain. Translational Psychiatry, 2, 1-8. doi:10.1038/
tp.2012.61
Rossignol, D. A., & Frye, R. E. (2011). A review of research trends
in physiological abnormalities in autism spectrum disorders:
Immune dysregulation, inflammation, oxidative stress, mito-
chondrial dysfunction and environmental toxicant exposures.
Molecular Psychiatry, 17, 389-401. doi:10.1038/mp.2011.165
Russell, T., & Ainsworth, M. D. S. (1981). Maternal affection-
ate behavior and infant-mother attachment patterns. Child
Development, 52, 1341-1343.
Schillaci, M. (2008). Primate mating systems and the evolu-
tion of neocortex size. Journal of Mammalogy, 89, 58-63.
doi:10.1644/06-MAMM-A-417.1
Scoville, A., & Pfrender, M. (2010). Phenotypic plasticity facilitates
recurrent rapid adaptation to introduced predators. Proceedings
of the National Academy of Sciences of the United States of
America, 107, 4260-4263. doi:10.1073/pnas.0912748107
Sebastian, S., & Bulun, S. E. (2001). A highly complex organiza-
tion of the regulatory region of the human CYP19 (Aromatase)
gene revealed by the human genome project. Journal of Clinical
Endocrinology & Metabolism, 86, 4600-4602. doi:10.1210/
jc.86.10.4600
Sen, C. K., Khanna, S., & Roy, S. (2006). Tocotrienols: Vitamin E
beyondtocopherols.LifeScience,78,2088-2098.doi:10.1016/j.
lfs.2005.12.001
Severance, E. G., Alaedini, A., Yang, S., Halling, M., Gressitt, K.
L., Stallings, C. R., & . . . Yolken, R. H. (2012). Gastrointestinal
inflammation and associated immune activation in schizo-
phrenia. Schizophrenia Research, 138, 48-53. doi:10.1016/j.
schres.2012.02.025
Sharawy, N., Hassan, M., Rashed, L., Shawky, W., & Rateb, M.
(2012). Evaluation of the effects of estradiol on the hypothal-
amo-pitutary adrenal axis response during systemic and local
inflammation. Modern Research in Inflammation, 1, 1-10.
doi:10.4236/mri.2012.11001
Sharma, A., Nash, A. A., & Dorman, M. (2009). Cortical develop-
ment, plasticity and reorganization in children with cochlear
implants. Journal of Communication Disorders, 42, 272-279.
Sherry, S. T., Ward, M. H., Kholodov, M., Baker, J., Phan, L.,
Smigielski, E. M., & Sirotkin, K. (2001). dbSNP: The NCBI
database of genetic variation. Nucleic Acids Research, 29, 308-
311. doi:10.1093/nar/29.1.308
Shonkoff, J. P.(2011). Protecting brains, not simply stimulating
minds. Science, 333, 982-983.
Simpson, E. R., Mahendroo, M. S., Means, G. D., Kilgore, M. W.,
Hinshelwood, M. M., Graham-Lorence, S., & . . . Bulun, S. E.
(1994). Aromatase cytochrome P450, the enzyme responsible
for estrogen biosynthesis. Endocrine Reviews, 15, 342-355.
doi:10.1210/erdv-15-3-342
Singleton, I., & van Schaik, C. P. (2002). The social organisation
of a population of Sumatran orang-utans. Folia Primatologica,
73, 1-20. doi:10.1159/000060415
Sinopoli, K. J., Floresco, S. B., & Galea, L. A. (2006). Systemic
and local administration of estradiol into the prefrontal
cortex or hippocampus differentially alters working mem-
ory. Neurobiology Learning and Memory, 86, 293-304.
doi:10.1016/j.nlm.2006.04.003
Slavich, G. M., Way, B. M., Eisenberger, N. I., & Taylor, S. E.
(2011, April-May). Neural sensitivity to social rejection is
associated with inflammatory responses to social stress. Poster
session presented at the Western Psychological Association,
91st annual convention, Los Angeles, CA.
Smaers, J. B., Schleicher, A., Zilles, K., & Vinicius, L. (2010).
Frontal white matter volume is associated with brain enlarge-
ment and higher structural connectivity in anthropoid primates.
PloS One, 5, e9123.
Smith, L. E., Greenberg, J. S., Seltzer, M. M., & Hong, J. (2008).
Symptoms and behavior problems of adolescents and adults
with autism: Effects of mother-child relationship quality,
warmth, and praise. American Journal of Mental Retardation,
113, 387-402. doi:10.1352/2008.113:387-402
Snodgrass, J. J., Leonard, W. R., & Robertson, M. L. (2009). The
energetics of encephalization in early hominids. In J. J. Hublin
& M. P. Richards (Eds.), The evolution of hominin diets:
Integrating approaches to the study of palaeolithic subsistence
(pp. 15-29). New York, NY: Springer.
Sophonsritsuk, A., Appt, S. E., Clarkson, T. B., Shively, C. A.,
Espeland, M. A., & Register, T. C. (2013). Differential effects
of estradiol on carotid artery inflammation when administered
early versus late after surgical menopause. Menopause, 20(5),
1. doi:10.1097/gme.0b013e31827461e0
Spampinato, S. F., Merlo, S., Nicoletti, F., & Sortino, M. A. (2012).
A main role for metabotropic glutamate receptor 1 in the
neuroprotective effect of estrogen. Molecular and Cellular
Pharmacology, 4, 61-67.
Spritzer, M. D., Daviau, E. D., Coneeny, M. K., Engleman, S. M.,
Prince, W. T., & Rodriguez-Wisdom, K. N. (2011). Effects
of testosterone on spatial learning and memory in adult male
rats. Hormones and Behavior, 59, 484-496. doi:10.1016/j.
yhbeh.2011.01.009
Stenzel, U. (2009). Rapid and accurate semi-global alignment of
diverged sequencing reads. Poster presented at the German
Conference on Bioinformatics 2009. Retrieved from https://
bioinf.eva.mpg.de/anfo/poster_a4.pdf [ANFO software used
for Neanderthal alignment is available for download https://
bioinf.eva.mpg.de/anfo/anfo-0.97.tar.gz]

Malone 19
Strober, W., & Fuss, I. J. (2011). Proinflammatory cytokines in the
pathogenesisofinflammatoryboweldiseases.Gastroenterology,
140, 1756-1767. doi:10.1053/j.gastro.2011.02.016
Suddendorf, T., & Whiten, A. (2001). Mental evolution and devel-
opment: Evidence for secondary representation in children,
great apes, and other animals. Psychological Bulletin, 127,
629-650. doi:10.1037/0033-2909.127.5.629
Sutcliffe, A., Dunbar, R., Binder, J., & Arrow, H. (2012).
Relationships and the social brain: Integrating psychological
and evolutionary perspectives. British Journal of Psychology,
103, 149-168. doi:10.1111/j.2044-8295.2011.02061.x
te Boekhorst, I. J. A., Schürmann, C. L., & Sugardjito, J. (1990).
Residential status and seasonal movements of wild orang-utans
in the Gunung Leuser Reserve (Sumatera, Indonesia). Animal
Behaviour, 39, 1098-1109. doi:10.1016/S0003-3472(05)80782-1
Trainor, B. C., Lin, S., Finy, M. S., Rowland, M. R., & Nelson,
R. J. (2007). Photoperiod reverses the effects of estrogens
on male aggression via genomic and nongenomic pathways.
Proceedings of the National Academy of Sciences of the United
States of America, 104, 9840-9845. 10.1073/pnas.0701819104
Utami, S. S., Goossens, B., Bruford, M. W., de Ruiter, J. R., & van
Hooff, J. A. R.A. M. (2002). Male bimaturism and reproduc-
tive success in Sumatran orang-utans. Behavioral Ecolology,
13, 643-652. doi:10.1093/beheco/13.5.643
van Ijzendoorn, M. H., Bard, K. A., Bakermans-Kranenburg, M. J.,
& Ivan, K. (2008). Enhancement of attachment and cognitive
development of young nursery-reared chimpanzees in respon-
sive versus standard care. Developmental Psychobiology, 51,
173-185. doi:10.1002/dev.20356
van Kooten, I. A. J., Palmen, S. J. M. C., von Cappeln, P.,
Steinbusch, H. W. M., Korr, H., Heinsen, H., . . . Schmitz, C.
(2008). Neurons in the fusiform gyrus are fewer and smaller in
autism. Brain, 131, 987-999. doi:10.1093/brain/awn033
Voytek, B., & Knight, R. T. (2010). Prefrontal cortex and basal
ganglia contributions to visual working memory. Proceedings
America, 107, 18167-18172. doi:10.1073/pnas.1007277107
Vreugdenhil, M., Bruehl, C., Voskuyl, R. A., Kang, J. X., Leaf, A.,
& Wadman, W. J. (1996). Polyunsaturated fatty acids modu-
late sodium and calcium currents in CA1 neurons. Proceedings
America, 93, 12559-12563. doi:10.1073/pnas.93.22.12559
Walker, R., Burger, O., Wagner, J., & Von Rueden, C. R. (2006).
Evolution of brain size and juvenile periods in humans.
Journal of Human Evolution, 51, 480-489. doi:10.1016/j.
jhevol.2006.06.002
Whittle, J. (1981). Arachidonic acid metabolites and the gastro-
intestinal toxicity of anti-inflammatory agents. Prostaglandins,
21(Suppl. 1), 113-118. doi:10.1016/0090-6980(81)90126-X
Wilson, M. L., Kahlenberg, S. M., Wells, M., & Wrangham, R. W.
(2011). Ecological and social factors affect the occurrence and
outcomes of intergroups encounters in chimpanzees. Animal
Behaviour, 83, 277-291. doi:10.1016/j.anbehav.2011.11.004
Woolley, C. S. (2007). Acute effects of estrogen on neuronal physi-
ology. Annual Review of Pharmacology and Toxicology, 47,
657-680. doi:10.1146/annurev.pharmtox.47.120505.105219
Wrangham, R. W. (1993). Demonic males: Apes and the origins of
human violence. New York, NY: Mariner Books.
Wu, J., Zeng, Y., Huang, J., How, W., Zhu, J., & Wu, R. (2007).
Functional mapping for reaction norms to multiple environ-
mental signals. Genetical Research, 89, 27-38. doi:10.1017/
S0016672307008622
Xi, D., Li, Y. C., Snyder, M. A., Gao, R. Y., Adelman, A. E.,
Zhang, W., & Gao, W. J. (2011). Group II metabotropic gluta-
mate receptor agonist ameliorates MK801-induced dysfunction
of NMDA receptors via the Akt/GSK-3β pathway in adult rat
prefrontal cortex. Neuropsychopharmacology, 36, 1260-1274.
doi:10.1038/npp.2011.12
Yamagiwa, J., Kahekwa, J., & Basabose, A. K. (2003). Intra-specific
variation in social organization of gorillas: Implications for
their social evolution. Primates, 44, 359-369. doi:10.1007/
s10329-003-0049-5
Yap, J. S., Yao, L., Das, K., Li, J., & Wu, R. (2011). Functional
mapping of reaction norms to multiple environmental signals
through nonparametric covariance estimation. BMC Plant
Biology, 11, 1-13. doi:10.1186/1471-2229-11-23
Young, C., Gean, P.-W., Chiou, L.-C., & Shen, Y.-Z. (2000).
Docosahexanoic acid inhibits synaptic transmission and epi-
leptiform activity in the rat hippocampus. Synapse, 37, 90-94.
doi:10.1002/1098-2396(200008)37::2<90:AID-SYN2>3.0.CO;2-Z
Young, C., Gean, P.-W., Wu, S.-P., Lin, C.-H., & Shen, Y.-Z.
(1998). Cancellation of low frequency stimulation-induced
long-term depression by docosahexaenoic acid in the rat hip-
pocampus. Neuroscience Letters, 247, 198-200. doi:10.1016/
S0304-3940(98)00272-9
Zhang, L., Nair, A., Krady, K., Corpe, C., Bonnear, R. H., Simpson,
I., & Vannucci, S. J. (2004). Estrogen stimulates microglia and
brain recovery from hypoxia-ischemia in normoglycemic but
not diabetic female mice. Journal of Clinical Investigations,
113, 85-95. doi:10.1172/JCI18336
Zierau, O., Zenclussen, A. C., & Jensen, F. (2012). Role of
female sex hormones, estradiol and progesterone, in mast
cell behavior. Frontiers in Immunology, 3, 1-4. doi:10.3389/
fimmu.2012.00169
Author Biography
J. Patrick Malone explores the rise of developmental disorder
from an evolutionary perspective. Through neurogenetics, neuro-
physiology, and comparative developmental psychopathology, he
seeks to answer whether human brain evolution required selection
for predisposition to disorder.

Phenotypic Plasticity, CYP19A1 Pleiotropy, and Maladaptive Selection in Developmental Disorders

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (20)

Similaire à Phenotypic Plasticity, CYP19A1 Pleiotropy, and Maladaptive Selection in Developmental Disorders

Similaire à Phenotypic Plasticity, CYP19A1 Pleiotropy, and Maladaptive Selection in Developmental Disorders (20)

Dernier

Dernier (20)

Phenotypic Plasticity, CYP19A1 Pleiotropy, and Maladaptive Selection in Developmental Disorders