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What is the heritability of brain gyrification?

What is the heritability of brain gyrification?



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Brains of mammals with a folded neocortex do not have identical patterns of folding in the same species.

Do two genetically identical individuals of a species have the same pattern of brain gyrification (i.e., folds/wrinkles)? Or are there other causes?


Short Answer:

Genetically identical individuals do not have identical brain structure.

Longer Answer:

The easiest way to answer your question is to look at "natural" clones: monozygotic (i.e. "identical") twins.

Brain morphology is of a lot of interest in neuroscience because differences in brain morphology are often confounding factors in human brain studies (for example those using MRI/fMRI).

I'll refer to a study by White et al., 2002. They studied volumetric and surface morphology measures in monozygotic twins. They found remarkably strong correlations in total volume (r values of .98-.99 for measures like total brain volume, cerebrum volume, cerebral gray matter/white matter, and cerebellum), and still strong correlations with different lobes of the cerebral cortex (r values from .69 to .97 for frontal/parietal/temporal/occipital gray and white matter).

However, surface measures: surface area, gyral and sulcal curvature, and surface complexity were more weakly correlated (r values of 0.49 to 0.69).

Of course, because these are monozygotic twins raised together, it's hard to know how much of the similarities are due to the shared environment as well as shared genetics. However, it is clear that brains of identical twins are not identical, and in particular their brains seem to differ more on measures of cortical surface structure rather than overall brain size. The authors write:

Many different types of nongenetic influences may contribute to the plasticity of the cortical surface characteristics, such as educational experiences, physical activity or social interactions. Furthermore, probabilistic events during the complex process of neurodevelopment [e.g. connections between neurons (Muller et al., 1997)], differences in gene expression either by chance or modulated by early-immediate genes (Abraham et al., 1993; Worley et al., 1993), or variability in cell-cell interactions (Fletcher et al., 1991) may also contribute to variability between MZ twins.


References

White, T., Andreasen, N. C., & Nopoulos, P. (2002). Brain volumes and surface morphology in monozygotic twins. Cerebral cortex, 12(5), 486-493.


You say "copying" (question has now been edited)

Welcome to Biology.SE. CC (stands for Copy Cat) was the name of a cloned cat. We never say "copying", we say "cloning".

Cloning in nature (question has now been edited)

Note that cloning is not necessarily a human process. Many animals (included animals that have a brain but excluding all mammals) clone themselves. See wiki>parthenogenesis

Rephrasing your question (question has now been edited)

We can rephrase your question as

What is the heritability of brain gyrification?

If it is unclear why this rephrasing of your question would be correct, then you'll want to have a look at this post.

Answer

There seems indeed to have genetic factors affecting gyri (White et al. 2010). Typically, the Fibroblast Growth Factor (FGF)- and Sonic Hedgehog (SHH)-signaling pathways have been seem to affect gyri (Rash et al. 2013; Wang et al. 2016).


Genetics of primary cerebral gyrification: Heritability of length, depth and area of primary sulci in an extended pedigree of Papio baboons

Genetic control over morphological variability of primary sulci and gyri is of great interest in the evolutionary, developmental and clinical neurosciences. Primary structures emerge early in development and their morphology is thought to be related to neuronal differentiation, development of functional connections and cortical lateralization. We measured the proportional contributions of genetics and environment to regional variability, testing two theories regarding regional modulation of genetic influences by ontogenic and phenotypic factors. Our measures were surface area, and average length and depth of eleven primary cortical sulci from high-resolution MR images in 180 pedigreed baboons. Average heritability values for sulcal area, depth and length (h(2)(Area)=.38+/-.22 h(2)(Depth)=.42+/-.23 h(2)(Length)=.34+/-.22) indicated that regional cortical anatomy is under genetic control. The regional pattern of genetic contributions was complex and, contrary to previously proposed theories, did not depend upon sulcal depth, or upon the sequence in which structures appear during development. Our results imply that heritability of sulcal phenotypes may be regionally modulated by arcuate U-fiber systems. However, further research is necessary to unravel the complexity of genetic contributions to cortical morphology.

Copyright 2009 Elsevier Inc. All rights reserved.

Figures

Structural MRI data were processed…

Structural MRI data were processed using object-based-morphometry pipeline. Brain mages were processed with…

Top panel: eleven cortical sulci…

Top panel: eleven cortical sulci were used in this analysis (Table 1). Bottom…

Heritability for sulcal area (top,…

Heritability for sulcal area (top, Δ, solid line), sulcal length (middle, ○, dashed…

Heritability for sulcal area (Δ,…

Heritability for sulcal area (Δ, solid line), sulcal length (○, dashed line) and…


Genetics of primary cerebral gyrification: Heritability of length, depth and area of primary sulci in an extended pedigree of Papio baboons

Genetic control over morphological variability of primary sulci and gyri is of great interest in the evolutionary, developmental and clinical neurosciences. Primary structures emerge early in development and their morphology is thought to be related to neuronal differentiation, development of functional connections and cortical lateralization. We measured the proportional contributions of genetics and environment to regional variability, testing two theories regarding regional modulation of genetic influences by ontogenic and phenotypic factors. Our measures were surface area, and average length and depth of eleven primary cortical sulci from high-resolution MR images in 180 pedigreed baboons. Average heritability values for sulcal area, depth and length (h 2 Area = .38 ± .22 h 2 Depth = .42 ± .23 h 2 Length = .34 ± .22) indicated that regional cortical anatomy is under genetic control. The regional pattern of genetic contributions was complex and, contrary to previously proposed theories, did not depend upon sulcal depth, or upon the sequence in which structures appear during development. Our results imply that heritability of sulcal phenotypes may be regionally modulated by arcuate U-fiber systems. However, further research is necessary to unravel the complexity of genetic contributions to cortical morphology.


On the genetic architecture of cortical folding and brain volume in primates

Understanding the evolutionary forces that produced the human brain is a central problem in neuroscience and human biology. Comparisons across primate species show that both brain volume and gyrification (the degree of folding in the cerebral cortex) have progressively increased during primate evolution and there is a strong positive correlation between these two traits across primate species. The human brain is exceptional among primates in both total volume and gyrification, and therefore understanding the genetic mechanisms influencing variation in these traits will improve our understanding of a landmark feature of our species. Here we show that individual variation in gyrification is significantly heritable in both humans and an Old World monkey (baboons, Papio hamadryas). Furthermore, contrary to expectations based on the positive phenotypic correlation across species, the genetic correlation between cerebral volume and gyrification within both humans and baboons is estimated as negative. These results suggest that the positive relationship between cerebral volume and cortical folding across species cannot be explained by one set of selective pressures or genetic changes. Our data suggest that one set of selective pressures favored the progressive increase in brain volume documented in the primate fossil record, and that a second independent selective process, possibly related to parturition and neonatal brain size, may have favored brains with progressively greater cortical folding. Without a second separate selective pressure, natural selection favoring increased brain volume would be expected to produce less folded, more lissencephalic brains. These results provide initial evidence for the heritability of gyrification, and possibly a new perspective on the evolutionary mechanisms underlying long-term changes in the nonhuman primate and human brain.

These two authors contributed equally to this paper.

Present address: Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.


On the genetic architecture of cortical folding and brain volume in primates

Understanding the evolutionary forces that produced the human brain is a central problem in neuroscience and human biology. Comparisons across primate species show that both brain volume and gyrification (the degree of folding in the cerebral cortex) have progressively increased during primate evolution and there is a strong positive correlation between these two traits across primate species. The human brain is exceptional among primates in both total volume and gyrification, and therefore understanding the genetic mechanisms influencing variation in these traits will improve our understanding of a landmark feature of our species. Here we show that individual variation in gyrification is significantly heritable in both humans and an Old World monkey (baboons, Papio hamadryas). Furthermore, contrary to expectations based on the positive phenotypic correlation across species, the genetic correlation between cerebral volume and gyrification within both humans and baboons is estimated as negative. These results suggest that the positive relationship between cerebral volume and cortical folding across species cannot be explained by one set of selective pressures or genetic changes. Our data suggest that one set of selective pressures favored the progressive increase in brain volume documented in the primate fossil record, and that a second independent selective process, possibly related to parturition and neonatal brain size, may have favored brains with progressively greater cortical folding. Without a second separate selective pressure, natural selection favoring increased brain volume would be expected to produce less folded, more lissencephalic brains. These results provide initial evidence for the heritability of gyrification, and possibly a new perspective on the evolutionary mechanisms underlying long-term changes in the nonhuman primate and human brain.

These two authors contributed equally to this paper.

Present address: Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.


1. Introduction

The formation of cortical folding is highly reproducible within species, with minor individual variations (Rakic, 2009). Yet the purposes of cortical folding across the lifespan are still unknown. The degree of gyrification of the human brain has historically been believed to reflect a need to increase SA without disproportionately increasing head size (e.g., Armstrong et al., 1995 Reillo et al., 2011). Various theories have been posited to explain patterns of cortical folding. It may, for example, be a way of improving connectivity by reducing distance between regions (for a review of gyrification and connectivity, see Zilles et al., 2013) or the reduction of axonal length between cortical areas (Van Essen, 1997 for a review see White & Hilgetag, 2011). It also seems likely that improved connectivity provides a means of allowing for increased cognitive capacity. Primate research seems consistent with this hypothesis. For example, studies of primates have indicated that larger brains have increased folding relative to smaller brains (e.g., Rilling & Insel, 1999), and among more recently evolved primates, convolution has been found to have increased at a faster pace than has brain size (Zilles, 1989). Consequently, degree of gyrification might reflect cognitive changes most distinctive to human primates, and may modulate intelligence in humans.

Folding, and consequent surface expansion of the cerebral cortex, appears to be an important factor in influencing mammalian cognitive abilities (for a review, see Sun & Hevner, 2014). Overall, there are converging lines of evidence consistent with differential expansion being a mechanism for gyrification the idea of connectivity as the primary function of gyrification has generally not been supported (Sun & Hevner, 2014 Ronan et al.,2014 for studies modeling increased cortical thickness without gyrification, see Murre & Sturdy, 1995 and Ruppin et al, 1993). Of the small number of gyrification studies published to date, the phenotype has been studied largely in relation to neuropsychiatric disorders such as Alzheimer’s disease, autism, velocardial facial syndrome, and schizophrenia (Liu et al., 2012 Wallace et al., 2013 Schaer et al., 2013 Kates et al., 2009 Schaer et al., 2006 Palaniyappan et al., 2012 Nanda et al., 2013). Wallace et al. (2013) reported that while autism-spectrum cases did not differ from controls in SA, they exhibited significant posterior gyrification increases bilaterally. This group made the case that lack of gyrification-SA association may reflect developmentally dissociable phenotypes, and that gyrification increases could lead to certain cognitive abilities observed in people with autism-spectrum disorders. Gyrification has also been negatively associated with psychosis and 22q11 deletion syndrome (e.g., Palaniyappan et al., 2012 Nanda et al., 2013 Schaer et al., 2006), both genetic conditions notable for multiple cognitive deficits (reviews by Elvevag & Goldberg, 2000 Green et al., 2004 Eisenberg et al., 2010). An examination of Alzheimer’s disease cases found that global gyrification and sulcal width differentiated mild Alzheimer’s cases from healthy controls (Liu et al., 2012). Mild cognitive impairment has also been associated with greater than normal reductions in gyrification in late-life (Liu et al., 2013). The latter findings suggest that gyrification might be very relevant to cognitive aging.

Other research has examined the relevance of gyrification to normative aging. A study by Zilles et al. (1988) manually measured 3DGI postmortem in the brains of 61 adults ages 16– 91. This early study of a gyrification index, similar to the index derived currently using our MRI methods, manually measured degree of gyrification using multiple histological brain slices. Manual measurement of postmortem brain is very labor-intensive, and in that study it required the measurement of only every fourth slice of the brain. They found no significant relationship between 3DGI and age. Using different types of measures, Magnotta et al. (1999) observed reduced gyrification with age in the brains of 148 adults aged 18� years based on measures of sulcal and gyral curvature. Hogstrom and colleagues (2013) reported results from an MRI study of 322 adults ages 20�, and found that 3DGI decreased with age (Hogstrom et al., 2013). This study used the same index of gyrification as in the present study, one that is based on the entire cortex.

Some research suggests that genetic factors have a strong influence on sulci and gyri during neurodevelopment (Piao et al., 2004). Evaluating gyral patterns in monozygotic (MZ) twins, Lohmann et al. (1999) observed that deeper and developmentally earlier sulci of the brain are more highly correlated between twins than are the surface sulci. They concluded that more superficial sulci, developing after birth, may be more affected by environmental influences.

These two early studies are limited by the fact that they each included only about 20 twin pairs. These are considered to be very small sample sizes for twin analysis, something that may substantially increase the risk of unreliable results (Neale & Cardon, 1992 Martin et al., 1978). In addition, Lohman et al. (1999) included only MZ twins. Without including dizygotic (DZ) twins, analyses cannot fully disentangle genetic influences from those due to the common environment (Neale & Cardon, 1992). The development of semi-automated techniques has made it possible for subsequent MRI twin studies to have substantially larger sample sizes. That, in turn, has made it possible to obtain more reliable estimates of the amount of variance in gyrification that is accounted for by genetic and environmental influences.

It is important to note, in addition, that our index of gyrification is different from the gyrification that has been examined in these twin studies. They were examining gyral patterns. In the present study, we examined degree of gyrification. The difference is analogous to shape versus volume of brain structures. Gyral patterns reflect the extent to which the patterns (or exact locations) are the same. We are measuring degree of gyrification such that one can have the same amount of gyrification without the gyri and sulci being in the same location. Heritability of the former is likely to be lower than heritability of the latter it is probable that gyral patterns are less heritable than degree of gyrification.

In 515 middle-aged twins in the Vietnam Era Twin Study of Aging (VETSA Kremen et al., 2006, 2013), we previously examined the genetic covariance among total SA, mean CT, and GCA (Vuoksimaa et al., 2014). SA, rather than CT, drove the phenotypic and genetic associations between cortex and GCA. As noted, previous research suggests that gyrification is positively phenotypically associated with cognitive ability and negatively phenotypically associated with Alzheimer’s disease and mild cognitive impairment. These findings raise the possibility that gyrification could be the underlying source of our observed SA-GCA relationships. We are unaware of any genetically informative studies of degree of gyrification or of the relationship between gyrification and cognitive ability. The goals of the present study were to: 1) estimate the heritability of gyrification 2) examine the phenotypic and genetic associations between gyrification and SA, given that gyrification is related to SA and 3) test whether gyrification underlies the relationship between SA and GCA.


Potential Mechanisms for Changes in Heritability With Age

Current theories describe the creation of cortical areas as occurring through the establishment of a series of genetically controlled anchor points which serve as loci for overlapping gradients of growth factors (Grove & Fukuchi-Shimogori, 2003). Characteristics of specific cortical areas develop over time in response to the local combination of growth factors and activation. It has been argued that primary motor and sensory cortices may serve as core anchor regions whose earliest development is strongly genetically determined (Rosa & Tweedale, 2005). The pattern observed here of genetic effects predominating in these core regions early in childhood may be consistent with their relatively early development, followed by a mature state in which a high degree of plasticity reflects their roles as the direct intermediaries with the external environment.

The reason for a decrease in total variance over development, particularly that due to environmental factors, is not obvious. It may seem more logical that variance because of environmental factors should increase with age as opportunities for exposure to unique environmental events extend. For the early-developing cortical regions in which environmental variance does increase during the age range of our study, this may be the case. However, for the later developing areas, the heritable phenotype is something that itself is being created over time. As described earlier, there is an increasing body of literature regarding changes in gene expression continuing over the course of postnatal development. If genes with particularly strong effects come on line, they may potentially substantially impact the variance because of genetic factors. The interaction of genetic with environmental factors over time may also increase heritability.

One mechanism that has been suggested for this is gene𠄾nvironment correlation (rGE). rGE occurs when the same genes affect both a trait and relevant features of the environment, and also acts to increase the amount of variance ascribed to genetic factors (Kendler & Baker, 2007 Scarr & McCartney, 1983). rGE can be divided into three types. The passive form of rGE occurs when parents provide both genes and early environmental conditions for their children. The active form concerns the tendency for individuals to seek environments that reinforce genetic predispositions The third type, evocative/reactive rGE, refers to the way in which genetically driven behaviors can result in the creation of specific environmental responses (Plomin, DeFries, & Loehlin, 1977). The relative prominence of these factors is likely to change over development, and may increase as children become more independent and able to choose their own environments.

Other models of gene𠄾nvironment (Gൾ) interactions include experience-expectant and experience-dependent processes, outlined by Greenough and colleagues as mechanisms by which environmental factors affect brain development (Andersen, 2003 Greenough, Black, & Wallace, 1987). Experience-expectant refers to the integration of environmental stimuli into normal patterns of brain development, the classic example being the effects of monocular visual deprivation on the developing visual cortex as described by Hubel and Wiesel (1998). Specific times during the development of a particular neural system when certain types of environmental stimulation must occur for normal development to take place are called critical periods. Experience-dependent processes are defined in contrast as means by which unique environmental factors may affect the developing nervous system in distinctive ways. In this case the brain may have particular sensitivities to environmental factors such as a trauma at specific developmental stages, resulting in differing effects on the long-term trajectory depending on when an event occurred. The prolonged developmental course of the human brain suggests that these processes may continue to play a role in reaching the mature phenotype well after birth.

Canalization refers to the frequently observed robustness of mature phenotypes against minor genetic or environmental perturbations during development, as in the example of compensatory growth (Flatt, 2005 Schmalhausen, 1949 Tanner, 1963 Waddington, 1942). Gൾ interactions have been proposed as one path by which canalization may occur. For example, genetic determinants of plasticity in response to the environment may constrain structures to develop along a heritable trajectory from an undifferentiated beginning to a genetically determined mature state (Garlick, 2002). Repetitive patterns of activity may also sculpt plastic developing structures. An example of this was described by Zelditch, Lundrigan, and Garland (2004), who found that variance in murine skull morphometry decreased during early postnatal development. They hypothesized that high initial variance decreased as initial unorganized immature patterns of motor activity took on the predictable characteristics of adulthood. Such a process is reminiscent of those thought to underlie activity-dependent changes in the cerebral cortex.

This model would suggest that heritability values in mature individuals may be different for those whose environment was deficient in the necessary environmental features. Studies regarding the effects of deficient environmental conditions on the heritability of brain structures in adults are not to our knowledge currently available, and identifying and directly measuring relevant environmental factors is highly challenging. However, one might speculate that if an environmental feature during development was an integral component of developing a mature heritable phenotype, departure from the optimal range for family members would result in an increase in variance due to their shared environment. Some indirect evidence for this may be found in the IQ literature. As previously mentioned, IQ increases in heritability over childhood and adolescence, and shared environmental effects are typically nonsignificant (Plomin, Fulker, Corley, & DeFries, 1997). Studies of heritability of cognition have found that there is a Gൾ interaction such that shared environmental factors become more prominent relative to genetic factors as socioeconomic conditions worsen (Harden, Turkheimer, & Loehlin, 2007 Turkheimer, Haley, Waldron, D’Onofrio, & Gottesman, 2003).

Delineating how genetic and environmental factors interact during development is essential to improve our understanding of causes of psychopathology (Thapar, Harold, Rice, Langley, & O𠆝onovan, 2007). The familiar “stress-diathesis” framework arose from the recognition that individuals possess varying degrees of vulnerability or resilience to environmental stressors. Twin studies have supported the role of Gൾ interaction in several different disorders. For example, studies have found that adverse life events are more likely to result in depression in both adults and adolescent girls who are also at genetic risk (Kendler et al., 1995 Silberg, Rutter, Neale, & Eaves, 2001). Children are more likely to exhibit antisocial behavior if they have both a genetic risk and a history of adverse early experiences, compared to children with either risk factor separately (Cadoret, Cain, & Crowe, 1983).

Such findings are consistent with a growing body of work on the impact of interactions of specific genetic polymorphisms with specific environmental risk factors (Moffitt, Caspi, & Rutter, 2006). Emerging data from large-scale studies that measure genotypes, relevant environmental factors, and behavioral or health outcomes are indicating that identifying specific Gൾ interactions is possible. One of the first examples was the finding that maltreated children were more likely to develop behavioral problems if they also had a specific functional polymorphism in the gene encoding a neurotransmitter-metabolizing enzyme, monoamine oxidase A (Caspi et al., 2002). The effects of polymorphism in the promoter region for the gene encoding the serotonin receptor have also been demonstrated to contribute to Gൾ interactions (Caspi et al., 2003 Kaufman et al., 2004 Kendler, Kuhn, Vittum, Prescott, & Riley, 2005).

In the twin model described earlier, the effects of this type of interaction would be subsumed under genetic effects, and it is likely that such Gൾ interactions over time are contributing to the increase in heritability of some brain regions. Identifying which environmental conditions affect outcome for individuals with specific genetic variations will be a major advance toward the ultimate goal of knowing how to tailor interventions to facilitate healthy brain development.


Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types

We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals.

Conflict of interest statement

COMPETING FINANCIAL INTERESTS

The authors declare no competing financial interests.

Figures

Overview of the approach. For…

Overview of the approach. For each tissue in our gene expression data set,…

Results of the multiple-tissue analysis…

Results of the multiple-tissue analysis for selected traits. Results for the remaining traits…

Validation of gene expression results…

Validation of gene expression results with chromatin data. (A) Examples of validation using…

Results of the brain analysis…

Results of the brain analysis for selected traits. Numerical results for all traits…

Results of the analysis of…

Results of the analysis of ImmGen gene expression data (top) and hematopoiesis ATAC-seq…


The Biology of Bigotry

Given the result of the recent US presidential election, minority groups worldwide are understandably worried about the future. Already social media platforms are awash with reports of emboldened bigots verbally, and in some disturbing cases, physically assaulting people of color, Muslims, and members of the LGBTQI+ community (though see update).

But where does this animosity come from? A popular adage is that racists are not born but rather they are made, and while this message is ultimately a hopeful one, it ignores a substantial portion of the story: that of biology. As I discuss in the Cambridge Handbook of the Psychology of Prejudice, there are multiple lines of evidence pointing to a genetic basis for prejudicial attitudes and behavior and if we hope to reduce net prejudice, understanding this is of critical importance.

The primary source of this evidence comes from the field of behavioral genetics. This endeavor relies on the natural experiment provided by contrasting identical and non-identical twin pairs. Where identical twins share all of their parents’ segregating genes (i.e. are 100% genetically identical), non-identical twins on average share only half of these genes. Based on this knowledge, one can assume that a trait shared more strongly by identical twins than non-identical twins is influenced by genes. If, however, identical and non-identical twin pairs are equally similar then presumably the environment the twins share has had an influence on the trait [1] .

Combining this relatively simple premise with complex mathematical modeling yields researchers incredible power to dissect variation (i.e. differences between individuals) into that caused by genetic effects, the environment shared by twins (e.g. their household and religious and political up-bringing), and finally, variation caused by individual experiences, chance biological effects, and any error in measurement of the trait.

For instance, 30 years of research using the twin method has revealed that genes account for between 20 and 40% of the variation in political orientation (as I’ve covered previously). Similarly, twin studies have revealed substantial genetic effects on prejudicial attitudes.

One study from 1986 observed that identical twins were more similar in their attitudes towards white superiority, apartheid and mixed marriage than non-identical twins. Further modeling revealed that between 30 and 40% of variation in these attitudes was due to genes. Surprisingly, the shared environment of the twins, which includes shared aspects of the family household, accounted for less than 15% of variation in the same attitudes [2] .

A more recent study including attitudes to equal rights for gays and women found that a third of the variation support for these ideas was due to genetic effects [3] . From ethnocentrism (18%) [4] , negative attitudes to non-Europeans (32%) [5] , generalized prejudice (38%) [6] and in-group favoritism (i.e. preferring one’s own religious, political or ethnic group: 46%) [7] , twin data has consistently shown strong genetic effects influencing bigoted attitudes, generally with small influences of the home environment.

This seems counter-intuitive: how can genes influence acquired attitudes while shared environmental influences are small?

It’s important to understand that genes aren’t coding for specific attitudes: there is no gene for racism. What these results indicate is that genes are contributing to behavioral and psychological dispositions to regard out-group members, such as those that are ethnically or culturally different, negatively. Whether these genes are different for different types of out-groups, such as those of a different sexuality vs. those of a different religion, remains to be seen, though it seems likely that most prejudices stem from a similar mechanism, one that fosters fear and suspicion of out-group members. Despite these genetic influences, the specific attitudes (i.e. “immigrants get more than they deserve from the government”) are almost certainly derived from the environment, with genes influencing the degree to which they are endorsed. Consequently, in an environment densely populated with bigoted rhetoric (such as many experienced during the recent election campaign) individuals with a genetic predisposition to out-group hostility may find themselves more readily espousing prejudicial attitudes.

This is ultimately mixed news: unfortunately, it means that more heritable attitudes are more firmly entrenched [8] but by observing the changes in prejudice over time, it is clear that the specific types and strengths of prejudice within a society are open to change. Key to this is the understanding that heritability refers only to causes of variation, and says nothing about the average level of the trait itself. Take intelligence as an example: intelligence is highly heritable (

85%), yet since IQ testing began, psychologists have consistently observed generational increases in the average intelligence of the population, referred to as the Flynn Effect. The causes of these increases are largely unknown but could be attributed to better nutrition, more widely accessible education, or a lower burden of disease. Regardless of the cause, the heritability of intelligence has not changed for the most part, while the average IQ has continued to shift upwards.

The same is possible for prejudice. While genes may maintain some variation in how strongly prejudice is endorsed, overall prejudice within society can be reduced: a rising tide lifts all boats. Even across the few studies mentioned above, it is apparent that the focus of prejudice rapidly shifts from racism (i.e. issues of segregation) to those concerning gay rights within the space of 20 years.

However, it is incredibly important to consider these genetic effects when attempting to understand and intervene in prejudice. Multiple studies have shown that the family environment contributes relatively little to the maintenance of prejudicial attitudes over and above genes—likely racism tends to cluster within families because of shared genes. As a result, social interventions should be tailored, taking into account the fact that genetic variation may mitigate their effectiveness for certain individuals.

Humans have made great strides in overcoming the burden of prejudice but it is often a lack of understanding that keeps us from truly succeeding: We can no more assume that all individuals are equally prone to bigotry based on their environment than we can assume that one’s genes entirely determine their future. Rather, to resolve complex social issues requires a nuanced understanding of the interaction between biology and behavior, one that starts at the level of a single gene and extends to the entirety of modern culture. In the uncertain days to come it will be crucial to bear this in mind.

1. Neale, M.C. and L.C. Cardon, Methodology for genetic studies of twins and families. 1992, Kluwer, Boston: Kluwer Academic Publishers.

2. Martin, N.G., et al., Transmission of social attitudes. Proceedings of the National Academy of Sciences of the United States of America, 1986. 83(12): p. 4364-4368.

3. Alford, J., C. Funk, and J. Hibbing, Are Political Orientations Genetically Transmitted?, J. Alford, Editor. 2005. p. 153-167.

4. Orey, B.D. and H. Park, Nature, nurture, and ethnocentrism in the Minnesota Twin Study. Twin Research and Human Genetics, 2012. 15(01): p. 71-73.

5. Kandler, C., et al., The genetic and environmental roots of variance in negativity toward foreign nationals. Behavior Genetics, 2015. 45(2): p. 181-199.


Is ADHD Caused by Toxins and Pollution?

Scientific research 4 suggests that exposure to chemicals — everyday toxins found in foods, carpeting and flooring, cleaning and lawn products, and personal-care products, like toothpastes — may contribute at least somewhat to disorders such as ADHD, autism, and learning disabilities. Infants and children are especially vulnerable to chemical exposure because their biological systems are still developing. During fetal development, exposure to even minuscule amounts of toxins at critical junctures can have a lifelong impact on the child’s brain and physical health. Brain development may be impacted by these toxins. These findings come from research that is not widely respected by all members of the medical community.

In 2010, the Learning and Developmental Disabilities Initiative (LDDI) released the first-ever report identifying chemical pollution in people from the learning and developmental disability community, called “Mind, Disrupted: How Chemicals May Affect How We Think and Who We Are.” 5 It concluded that you don’t have to live next to a waste site to be exposed to brain-damaging chemicals. Examples of household chemicals include:

  • Perfluorinated compounds (PFCs) are used to prevent food and other substances from sticking to carpets, drapes, and cooking pans. Teflon and Scotchgard are examples.
  • Polybrominated diphenyl ethers (PBDEs), used as fire retardants, are found in clothing and furniture, as well as bedding.
  • Triclosan is an antibacterial agent found in soaps, toothpastes, and many other personal-care products.
  • Bisphenol A (BPA) is an epoxy resin used to line food cans and other containers. It is also used to make plastic containers, like infant bottles, and certain paper products.
  • Phthalates make rubber-based materials soft and pliable. They are found in vinyl, plastic bottles, toys, shower curtains, and raincoats. They are also used to make personal-care products, air fresheners, and shampoos.

Every participant in the Learning and Developmental Disabilities Initiative tested positive for at least 26 of the 89 chemicals studied.

A 2015 study, 6 completed by the University of Calgary, linked the chemicals used in making plastic (BPA and BPS) to hyperactivity in zebrafish, which are often used to study embryonic brain development because they share 80 percent of the genes found in humans, and have similar developmental processes. They called the results of their study, “a smoking gun” that linked negative changes in brain development to BPA and BPS exposure.

Lead exposure may also cause ADHD symptoms, according to a study published in Psychological Science in 2015. 7 The study’s researchers emphasized that lead exposure is not the only cause of ADHD symptoms rather, it’s one environmental factor that may lead to a formal ADHD diagnosis. Similarly, lead exposure doesn’t guarantee an ADHD diagnosis, but it may provide doctors with further clues about the root of a child’s symptoms.


PI3K-Yap activity drives cortical gyrification and hydrocephalus in mice

Mechanisms driving the initiation of brain folding are incompletely understood. We have previously characterized mouse models recapitulating human PIK3CA-related brain overgrowth, epilepsy, dysplastic gyrification and hydrocephalus (Roy et al., 2015). Using the same, highly regulatable brain-specific model, here we report PI3K-dependent mechanisms underlying gyrification of the normally smooth mouse cortex, and hydrocephalus. We demonstrate that a brief embryonic Pik3ca activation was sufficient to drive subtle changes in apical cell adhesion and subcellular Yap translocation, causing focal proliferation and subsequent initiation of the stereotypic 'gyrification sequence', seen in naturally gyrencephalic mammals. Treatment with verteporfin, a nuclear Yap inhibitor, restored apical surface integrity, normalized proliferation, attenuated gyrification and rescued the associated hydrocephalus, highlighting the interrelated role of regulated PI3K-Yap signaling in normal neural-ependymal development. Our data defines apical cell-adhesion as the earliest known substrate for cortical gyrification. In addition, our preclinical results support the testing of Yap-related small-molecule therapeutics for developmental hydrocephalus.

Keywords: PI3K Yap cortical gyrification critical period human biology hydrocephalus medicine mouse neuroscience.

Conflict of interest statement

AR, RM, MD, JM, TB, KA, IG, KM No competing interests declared

Figures

Figure 1.. Embryonic induction of Pik3ca H1047R…

Figure 1.. Embryonic induction of Pik3ca H1047R activating mutation causes cortical gyrification in mice.

Figure 1—figure supplement 1.. Genetic strategy for…

Figure 1—figure supplement 1.. Genetic strategy for Pik3ca H1047R mouse model and expression of GFAP-cre…

Figure 1—figure supplement 2.. Characterization of true…

Figure 1—figure supplement 2.. Characterization of true gyrification in Pik3ca H1047R mutant neocortex and hippocampus.

Figure 1—figure supplement 3.. Pik3ca H1047R mutant…

Figure 1—figure supplement 3.. Pik3ca H1047R mutant demonstrates increase in ventricular length.

Figure 2.. Altered neurogenesis in Pik3ca H1047R…

Figure 2.. Altered neurogenesis in Pik3ca H1047R mutant at embryonic and postnatal stages follows the…

Figure 2—figure supplement 1.. Pik3ca H1047R mutant…

Figure 2—figure supplement 1.. Pik3ca H1047R mutant demonstrates normal cell fate specification but disrupted neural…

Figure 3.. Non-random gyrification pattern in Pik3ca…

Figure 3.. Non-random gyrification pattern in Pik3ca H1047R mutant has a narrow embryonic critical period.

Figure 3—figure supplement 1.. Minimal induction of…

Figure 3—figure supplement 1.. Minimal induction of PI3K overactivation is sufficient to initiate cortical folding…

Figure 4.. Embryonic induction of Pik3ca H1047R…

Figure 4.. Embryonic induction of Pik3ca H1047R mutation causes early disruption of apical cell adhesion.

Figure 4—figure supplement 1.. Disruption of apical…

Figure 4—figure supplement 1.. Disruption of apical cell adhesion caused by embryonic induction of PI3K…

Figure 5.. Embryonic induction of Pik3ca H1047R…

Figure 5.. Embryonic induction of Pik3ca H1047R mutation disrupts early developing ependyma and induces increase…

Figure 5—figure supplement 1.. Six3 + cells…

Figure 5—figure supplement 1.. Six3 + cells ectopically concentrate at the mutant gyral ventricular zone.

Figure 6.. Translocation of Yap from nucleus…

Figure 6.. Translocation of Yap from nucleus to cytoplasm by verteporfin attenuates gyrification and ventriculomegaly…

Figure 6—figure supplement 1.. Verteporfin administration has…

Figure 6—figure supplement 1.. Verteporfin administration has no overt effect on control littermates.

Figure 6—figure supplement 2.. Barcode plots across…

Figure 6—figure supplement 2.. Barcode plots across groups showing gene enrichment.

Figure 6—figure supplement 3.. Pik3ca mutant gyrification…

Figure 6—figure supplement 3.. Pik3ca mutant gyrification is physiologically relevant.

Figure 7.. Reduction of nYap by verteporfin…

Figure 7.. Reduction of nYap by verteporfin re-establishes developing apical junctions and suppresses focal proliferation…

Figure 7—figure supplement 1.. Reduction of nYap…

Figure 7—figure supplement 1.. Reduction of nYap by verteporfin re-establishes cell adhesion in Pik3ca H1047R…

Figure 7—figure supplement 2.. Effect of verteporfin…

Figure 7—figure supplement 2.. Effect of verteporfin on apical junctions initiates early.


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