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

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, R 2 = .994, adjusted R 2 = .989, F(3, 5) = 143.758, p < .001.

Supposition without appreciation for evolutionary mechanisms represents a danger to the field of evolutionary psychology. Microevolution (e.g., natural selection and genetic drift) operates in synergistic fashion with macroevolution (e.g., evolutionary history and adaptive constraints), as coordinated by developmental biology responding to an environment. In general, natural, sexual, frequency-dependent, individual, kin, group, and species selection operate on phenotypes and drive change in gene frequency across successive 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 environmental extremes, and this is evident in the evolution of the human brain.
The CYP19A1 gene codes for cytochrome P450 aromatase (P450arom) and is located on the long leg of chromosome 15, at 21.2 (S. A. Chen et al., 1988;Simpson et al., 1994;Zhang et al., 2004). P450arom is the enzyme that converts 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 484476S GOXXX10.1177/2158244013484476SAGE OpenMalone research-article2013 1 Walden University, OR, USA nine transcripts (Sebastian & Bulun, 2001) for specific tissue expression ( Figure 1). For example, the major placental transcript 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.
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(Malone, , 2012 and the evidence that neocortical 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) demonstrates a strong phylogenetic trend and (b) if its orthologous relationship correlates to previously hypothesized mechanisms for human brain evolution.
Organisms possess genotypes that permit deviations in developmental pathways in response to varying environmental conditions (Scoville & Pfrender, 2010). The most crucial aspect of the primate brain is neither size nor "executive 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 phenotypic plasticity, to accommodate multiform selective pressures without concurrent change in genetic conformation, yet liable to epigenetic and transcript-level expression regulation (Malone, 2011d(Malone, , 2012. A rapidly growing consensus indicates a system linking the neurodevelopmentally sensitive response to environmental stimuli with the genetics of neuroinflammation combines to predispose ASD pathogenesis with male bias (Angelidou et al., 2012;Becker, 2012;Hu, 2013aHu, , 2013bJames, 2008, p. 15;Malone, 2012;Rossignol & Frye, 2011), and alterations to one or more components within the system may initiate 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 endophenotype linking genes with environment is theorized (Angelidou et al., 2012;Becker, 2012;Hu, 2013aHu, , 2013bJames, 2008;Malone, 2011c). This suggests that a predisposing genetic profile could exist within an individual without developmental disorder who did not receive environmental insult during developmentally sensitive periods (Angelidou et al., 2012;Hu, 2013aHu, , 2013bJames, 2008;Malone, 2012). Likewise, this view suggests that an individual without a genetic burden could develop disorder under very great environmental stress during the same early life stage (Angelidou et al., 2012;Hu, 2013aHu, , 2013bJames, 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 epigenetic imprinting, miRNA regulation, and other forms of transcript-level expression modification that may alter developmental trajectories. Therefore, if CYP19A1 complexity trends with phylogeny and correlates strongly to previously 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 , a multiz alignment (Blanchette et al., 2004)  The above species provide a skeletal framework for the subphylum Vertebrata, thus representing a foundation for an evolutionary perspective, with special emphasis on nonhuman 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 primate, CYP19A1 should demonstrate organization nearly identical to the current human model, particularly if the gene demonstrates an evolutionary trend through the extant primate 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 lasting group size change regardless of brain development. Because, unlike Dunbar, this study is concerned with the cause of human brain evolution, NCR becomes the 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 corrected 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 dispersion. Dunbar (1992) log-transformed all data due to curvilinear relationship between group size and NCR, and performed the regression on reduced major axes as this provides greatest 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 complex 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 phylogeny, 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 alignment against the February 2009 (GRCh37/hg19) human CYP19A1 assembly. Amino acid sequence was chosen over nucleic acid because each transcriptome sequenced represents 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 relative 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 reasonably 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 approximate human conformation in primates, especially as all tissue-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 primate species to current human data was determined (Table  1). Furthermore, the Neanderthal CYP19A1 composite produced 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 conservative 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 χ 2 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 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). evolutionary trend toward increased phenotypic plasticity. Most methods yield the same slope estimates when R 2 > .9 (Mertler & Vannatta, 2010) and the linear regression was produced, R 2 = .994, adjusted R 2 = .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 without threat of multicollinearity as the variance inflation factor for all variables is below 10 and all collinearity tolerance 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 illustrates significant changes from prosimians, to monkey, and finally to great apes. It is clear that CYP19A1 has increased in size and complexity in a way that trends with phylogeny and strongly correlates 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 fundamental aspects of fine regulation in at least 13 regions of the brain and for both hemispheres (Figure 7). Histone mapping provides evidence of regulation through developmental stages by gender, and the data sets (Figure 8) appear to validate previous hypotheses (Cheung et al., 2010;Malone, 2012). Seven-nucleotide seed targets (CYP19A1: miR-539, ATTTCTCA, score: 65 and CYP19A1: 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, embryonic stem cell, human skeletal muscle myoblasts, human umbilical vein endothelial cells, human erythromyeloblastoid 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 promoters by tissue-specific DNA methylation (Figure 8) was determined and MRE-seq, MeDIP-seq, H3K4me3 ChIPseq, 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 individual brain regions, (b) by gender, (c) across all developmental 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 disorder. For some species, genetic accommodation is the phenotype upon which selection critically operates. The evolution of myriad regulatory mechanisms on primate brain development 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 ecotype'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 R 2 = .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.
notypic plasticity, as modified by gender and age of exposure, 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 expression 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 histone mapping seeks to label regions where genetic expression is active and potentially modified in some way. Transcription levels may be altered by normal cell mechanisms, 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. and complexity of the gene, a wide range of phenotypic profiles arise from histone transcription regulation, and it is satisfying 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 tissues, 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 primary 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 equivalent 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).
For many decades, the common approach to genetics was to study artificially induced and naturally occurring mutations as a means to understand normal gene expression. This author asserts that as great phenotypic plasticity is the primary character trait selected for, the search for genes linked to developmental disorder that also demonstrate phylogenetic 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 disorder to determine what may be the core genomic set responsible for human brain evolution (preliminary results provided in Table 2). Those genes demonstrating higher orthology further from primates specifically, and toward placental mammal, 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.  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* 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.