Download Dickinson D., Elvevåg B. Genes, “Cognition and Brain through a

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Courtney Marsh
BIOL303, Section 501
Dr. Ely
5 November 2010
Functional Gene Group Analysis Advantages and Findings
The study of genetics becomes more complex every day. New discoveries about genes
are facilitated by improving technology and new methods of analysis that are often affiliated
with this new technology. The scale of genotyping and genetic association studies has increased
rapidly from single-locus analysis to genome-wide association studies. Genome-wide association
studies are typically used to study common genes of large effect. This classical method of
grouping genes based on their pathways is called “vertical grouping.” Vertical grouping is less
effective when rare variants of large effect are of importance or when identifying genes of small
effect for complex traits. With genome wide association studies, a hypothesis is not needed.
They do not focus on a certain idea, so more unexpected discoveries can be made.
Collective testing of genes involved in biological pathways has emerged as an alternative
strategy for testing the combined effects of genetic variants with small effect size. These
pathways are usually defined as a set of proteins that participate in cascades of intracellular
reactions that are often triggered by extracellular ligands. Testing the combined effect of multiple
genetic variants in such pathways has been shown to be more powerful than testing single gene
effects. Functional gene group analysis is good for analyzing complex traits or common
disorders that are potentially influenced by many genes of small effect. If different variants share
a common molecular function, studying their combined effects is useful. Functional gene group
analysis can be used to identify etiological factors that underlie complex diseases for which
classic, genome-wide analysis has been unsuccessful so far. Grouping genes according to cellular
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function is known as “horizontal grouping.” This method takes a hypothesis-driven approach by
directly testing functional gene groups.
In a 2008 analysis, Torkamani, et al., recognized that, although some chronic diseases are
clearly linked to certain DNA sequences, most common diseases are influenced by rare or lowpenetrance variations (“polygenes”) and environmental factors. The polygenes are difficult to
identify, but, in order to understand the genetic basis of seven common diseases (including
Crohn’s disease, hyptertension, bipolar disorder, and diabetes), a pathway analysis approach was
used. Results from genome-wide association studies were used, though the studies, when
analyzed locus-by-locus, did not conclude a relationship between the individual loci and
pathways. By analyzing genetic similarities between the diseases and their pathways, the
researchers were able to re-categorize the diseases.
The study of cognitive ability is intriguing because its heritability is known to exist but
the genetic basis of its heritability has been unclear when testing focused in individual genes.
Posthuma, et al., 2001 determined that verbal IQ heritability is 85% while performance IQ
heritability is 69%. Genetic variance explained 46% of the variance in perceptual speed. The
study involved 344 sets of twins (688 people total), divided into two age cohorts (older and
younger). Perceptual speed was determined by the number of correct answers per second to a test
that involved identifying the longer of two parts of an image. Perceptual speed was found to be
phenotypically correlated to verbal IQ and performance IQ, based on a common genetic factor.
This common genetic factor accounted for 10% of the variance in verbal IQ and 22% of the
variance in performance IQ. These data support the claim that cognitive ability is heritable, but
also confirm that the exact level of heritability and its influences are difficult to pinpoint.
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Therefore, it is necessary to consider a variety of approaches to studying the genetic basis of
cognitive ability.
When studies of the heritability of cognitive ability involve analyzing individual genes,
results do not point to any one gene as a major influence. For example, typically, each of the
reported DNA variants associated with cognitive ability explains less than 1%-2% of the
variation (Deary et al. 2009). Therefore, it is useful to examine the effect of groups of genes
(functional gene group analysis) to investigate genetic influence on cognitive ability.
Many pathways modulate synaptic function. They have a high degree of convergence,
resulting in a common phenotypic effect. It is, therefore, conceivable that genetic variation in
some or all of these pathways leads to similar consequences in synaptic function. Understanding
the genetic and environmental factors that influence cognitive ability may help clarify the
etiological basis of individual differences in both normal and abnormal cognitive functioning
(Plomin and Kovis 2005). Some of the pathways examined in the study "Functional Gene Group
Analysis Reveals a Role of Synaptic Heterotrimeric G Proteins in Cognitive Ability" by Ruano,
et al., (2010) included cell metabolism, G protein relay (G protein subunits), GPCR signaling (G
protein coupled receptors), intracellular signal transduction (enzymes downstream of G protein
or tyrosine kinase signaling), and neurotransmitter metabolism (metabolizing enzymes).
Data was collected from 627 subjects, aged between 5-19 years. The IQ scores were
normally distributed. The possible effects of population stratification were investigated and were
found to be insignificant. Genome-wide SNP-by-SNP analysis, the traditional method of
analysis, did not detect significant associations. Collective testing of genes in synaptically
relevant biological pathways was also less successful in identifying genetic variation underlying
cognitive ability than collectively testing genes that are grouped according to function in a
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biological process. These vertical groups were the dopaminergic, glutamatergic, serotonergic,
and cannabinoid pathways.
The effect of the functional group cannot be explained by the effect of a few individual
SNPs or genes but must be ascribed to the combined effect of multiple genes in the functional
gene group. However, analysis using functional gene groups was able to find an association with
cognitive ability. SNPs associated with cognitive ability tend to cluster in genes that are known
to be expressed in synapses. The group of synaptic heterotrimeric G proteins plays a role in
explaining variation in cognitive ability. There are 33 genes in the human genome for
heterotrimeric G proteins and 27 of these are expressed in the synapse. G proteins are central
relay factors between the activation of plasma membrane receptors by extracellular ligands and
the cellular responses that these induce (Dessal et al. 2010). They provide the only pathway for
most signaling molecules in the brain. Therefore, G proteins act as a signaling bottleneck, or a
point of convergence.
In this study, G proteins were shown to be more closely associated with cognitive ability
than would be expected by chance alone, suggesting that the combined effects of genes relating
to G-proteins play an important role in the variation of cognitive ability. Association of the group
of G proteins could not be attributed to a single gene or SNP. This confirms the importance of
focusing on the gene group as the unit of analysis. Alterations in synaptic processes (relating to
G proteins) prominently affect the properties of neuronal networks in the brain and lead to
altered intelligence levels. It is interesting to note that “none of the genes in the group of
heterotrimeric G proteins have been associated with cognitive ability previously.”
It is important to note that an earlier study by Golding et al. (2001) was consistent with
the findings of Ruano et al. This study took place in the UK and used 1,568 DNA samples (from
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blood) of individuals of white European origin. An important difference is that it was not limited
to individuals with ADHD, as was the Ruano et al. 2010 study. Both studies focused on the
functional gene group rather than on individual SNPs providing a strong linkage between
cognitive ability and the functional gene group that expresses heterotrimeric G proteins, but also
indicates that the conclusions are applicable to more individuals than only those with ADHD.
The study by Ruano et al. (2010) found that the estimated effect size of the genes in the
group of heterotrimeric G proteins explained only 3.3% of the observed variation in cognitive
ability. This effect size is large when compared to the effect of single genes, but not much in
terms of the estimated heritability of cognitive ability. While the G protein group had the largest
effect on cognitive variance of any of the gene groups tested, the group of transmitter
synthesizing and metabolizing proteins had the second most significant effect in the Ruano et al.
2010 study. It is therefore suggested that further research should focus on the relationship
between cognitive ability and factors that influence synaptic signaling processes, like the
production and metabolism of transmitters.
Previous studies have indicated a role for such synaptic metabolic enzymes in cognitive
ability. For example, various catechol-O-methyltransferase (COMT) variants alter the efficiency
working memory, fluid intelligence, and control of attention (Dickinson 2009). Since,
experiments regarding metabolic enzymes like COMT, as well as experiments regarding other
biological pathways, inevitably show that environment and developmental factors also play a
role in cognitive ability. Further scientific research should also investigate the genetic response
to environmental and developmental factors.
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References
Deary I.J., Johnson W., Houlihan L.M. Genetic foundations of human intelligence. Hum. Genet.
2009;126:215–232.
Dessal, AL, Prades, R, Giralt E, and AV Smrcka. “Rational Design of a Selective Covalent
Modifier of G Protein{beta}{gamma} Subunits.” Molecular Pharmacology. 2010 Sep 29.
Dickinson D., Elvevåg B. Genes, “Cognition and Brain through a COMT Lens.” Neuroscience.
2009;164:72–87.
Golding J., Pembrey M., Jones R., ALSPAC Study Team ALSPAC—the Avon Longitudinal
Study of Parents and Children. I. Study methodology. Paediatr. Perinat. Epidemiol.
2001;15:74–87.
Plomin R., Kovas Y. Generalist genes and learning disabilities. Psychol. Bull. 2005;131:592–
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Posthuma D, de Geus EJ, and Boomsma DI. “Perceptual speed and IQ are associated through
common genetic factors.” Behavioral Genetics. 2001 Nov;31(6):593-602.
Ruano, Dina, Avecacis, Goncalo R., Glaser, Beate, Lips, Esther. Cornelisse, L. Niels, de Jong,
Arthur P.H., Evans, David, Smith, George, Timpson, Nicolas, Smit, August, Heutink,
Peter, Verhage, Matthijs, and Danielle Posthuma. "Functional Gene Group Analysis
Reveals a Role of Synaptic Heterotrimeric G Proteins in Cognitive Ability." The
American Journal of Human Genetics 86.2 (2010): 113-25.
Torkamani A, Topol EJ, Schork NJ. “Pathway analysis of seven common diseases assessed by
genome-wide association.” Genomics. 2008 Nov;92(5):265-72. Epub 2008 Sep 16.
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