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The Roles of COMT val158met Status and Aviation Expertise in Flight Simulator Performance and Cognitive Ability

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The polymorphic variation in the val158met position of the catechol-O-methyltransferase (COMT) gene is associated with differences in executive performance, processing speed, and attention. The purpose of this study is: (1) replicate previous COMT val158met findings on cognitive performance; (2) determine whether COMT val158met effects extend to a real-world task, aircraft navigation performance in a flight simulator; and (3) determine if aviation expertise moderates any effect of COMT val158met status on flight simulator performance. One hundred seventy two pilots aged 41-69 years, who varied in level of aviation training and experience, completed flight simulator, cognitive, and genetic assessments. Results indicate that although no COMT effect was found for an overall measure of flight performance, a positive effect of the met allele was detected for two aspects of cognitive ability: executive functioning and working memory performance. Pilots with the met/met genotype benefited more from increased levels of expertise than other participants on a traffic avoidance measure, which is a component of flight simulator performance. These preliminary results indicate that COMT val158met polymorphic variation can affect a real-world task.
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The Roles of COMT val158met Status and Aviation Expertise in
Flight Simulator Performance and Cognitive Ability
Q. Kennedy,
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine,
Stanford, CA 94305-5550, USA
Stanford/VA Aging Clinical Research Center, VA Palo Alto Health Care System (151Y), 3801
Miranda Avenue, Palo Alto, CA 94304-1207, USA
J. L. Taylor,
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine,
Stanford, CA 94305-5550, USA
Department of Veterans Affairs, MIRECC, Palo Alto, CA, USA
A. Noda,
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine,
Stanford, CA 94305-5550, USA
M. Adamson,
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine,
Stanford, CA 94305-5550, USA
Department of Veterans Affairs, MIRECC, Palo Alto, CA, USA
G. M. Murphy Jr,
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine,
Stanford, CA 94305-5550, USA
J. M. Zeitzer, and
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine,
Stanford, CA 94305-5550, USA
Department of Veterans Affairs, MIRECC, Palo Alto, CA, USA
J. A. Yesavage
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine,
Stanford, CA 94305-5550, USA
Department of Veterans Affairs, MIRECC, Palo Alto, CA, USA
Q. Kennedy: quinnk@stanford.edu
Abstract
The polymorphic variation in the val158met position of the catechol-O-methyltransferase (COMT)
gene is associated with differences in executive performance, processing speed, and attention. The
purpose of this study is: (1) replicate previous COMT val158met findings on cognitive
performance; (2) determine whether COMT val158met effects extend to a real-world task, aircraft
navigation performance in a flight simulator; and (3) determine if aviation expertise moderates any
© Springer Science+Business Media, LLC (outside the USA) 2010
Correspondence to: Q. Kennedy, quinnk@stanford.edu.
NIH Public Access
Author Manuscript
Behav Genet. Author manuscript; available in PMC 2011 September 1.
Published in final edited form as:
Behav Genet
. 2011 September ; 41(5): 700–708. doi:10.1007/s10519-010-9436-z.
NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript
effect of COMT val158met status on flight simulator performance. One hundred seventy two
pilots aged 41–69 years, who varied in level of aviation training and experience, completed flight
simulator, cognitive, and genetic assessments. Results indicate that although no COMT effect was
found for an overall measure of flight performance, a positive effect of the met allele was detected
for two aspects of cognitive ability: executive functioning and working memory performance.
Pilots with the met/met genotype benefited more from increased levels of expertise than other
participants on a traffic avoidance measure, which is a component of flight simulator performance.
These preliminary results indicate that COMT val158met polymorphic variation can affect a real-
world task.
Keywords
COMT; Flight simulator performance; Cognitive performance; Aviation expertise; Age
Introduction
Catechol-O-methyltransferase (COMT) metabolizes synaptic dopamine, thereby limiting the
length of time dopamine is available to activate its downstream receptors, and is particularly
important in regulating dopamine signaling in the prefrontal cortex. Dopamine signaling in
the prefrontal cortex is a critical modulator of working memory and executive function.
There is a functional polymorphism in COMT involving a single amino acid substitution of
methionine for valine (at position 108 in soluble COMT and at position 158 in membrane
bound-COMT). The met variant results in a four-fold reduction in the COMT enzyme
activity, leading to an increase in dopamine activity in the prefrontal cortex (Egan et al.
2001). This val/met polymorphism consistently has been shown to influence frontal lobe
executive performance, as measured by the Wisconsin Card Sorting Task, and other
measures of processing speed and attention (Backman et al. 2006). In particular, increased
number of met alleles have been associated with better performance on executive function
(Backman et al. 2006; Barnett et al. 2007; Bruder et al. 2005; Egan et al. 2001; Holtzer et al.
2008; Joober et al. 2002; Malhotra et al. 2002; Nagel et al. 2008), working memory (Bruder
et al. 2005; Egan et al. 2001; Goldberg and Weinberger 2004; Goldberg et al. 2003; Nagel et
al. 2008), processing speed and attention (Bilder et al. 2002; Raz et al. 2009; Starr et al.
2007), episodic recall memory (de Frias et al. 2005; Raz et al. 2009), semantic memory (de
Frias et al. 2005), visuospatial ability (Backman et al. 2006; de Frias et al. 2005), and
reaction time (Stefanis et al. 2005). These results emerge across a wide range of the adult
lifespan (de Frias et al. 2004, 2005; Dijkstra and Kaup 2005; Erickson et al. 2008; Nagel et
al. 2008; Raz et al. 2009). Taken together, the studies to date suggest that expression of
methionine at position 158 in COMT may confer an advantage to “effortful” processes, i.e.,
those under deliberate executive control.
The above results are based on computer-based or paper and pencil neuropsychological
tests. Do these results extend to real-world tasks? To date, only one study has attempted to
address this question. The relationship between COMT val158met status and gait
performance, a task associated with attention and executive control processes, was studied in
a sample of older adults. Among men, met/met carriers had significantly faster gait velocity
(Holtzer et al. 2008). In the current study, we examine another real-world task, aircraft
navigation in a flight simulator. Aircraft navigation places heavy demands on several
cognitive abilities, notably executive function, processing speed, and working memory
(Taylor et al. 2005). Thus, flight simulator performance provides an ideal way to determine
whether COMT val158met status affects performance on a real world task.
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Research also suggests that environmental factors may interact with the effects of COMT
val158met status. In a sample of Plains American Indians, a COMT by education interaction
was found on performance on the Information, Block Design, Similarities, and Digit Span
subtests of Wechsler Adult Intelligence Scale-Revised (WAIS-R), tests that tap attention,
crystallized knowledge, long-term and working memory, processing speed, and verbal
comprehension (Enoch et al. 2009). Participants with at least one met allele benefited the
most from additional years of education. For example, block design performance among val/
val carriers improved very modestly with increased years of education. However, among
those with at least one met allele, block design performance improved dramatically with
additional years of education. Those met carriers with the least years of education performed
the worst (i.e. lower than val/val carriers), whereas met carriers with the most years of
education outperformed val carriers. Previous work indicates that a COMT val158met effect
on cognitive performance increases as attentional demands increase (Blasi et al. 2005).
Enoch et al. speculate that among those with few years of education, the cognitive tests
required high levels of attentional demand, and consequently these participants were more
influenced by COMT val158met status. Thus, as years of education increase, and
presumably, training in performing paper and pencil type cognitive tasks increases,
attentional demands of these tasks decrease. This reduction of attentional demand with
additional years of education appears to be of greater benefit for met carriers.
We also sought to determine if there were environmental factors that may interact with
COMT val158met status on flight simulator performance. One likely environmental factor is
expertise, defined as the acquisition of specialized knowledge and perceptual motor skills
through years of ‘deliberate practice’ (Ericsson et al. 1993). In aviation, Federal Aviation
Administration (FAA) ratings provide a measure of flight expertise consistent with this
definition, as higher ratings require additional hours of formal flight training and to advance
skills beyond the basic level of a private pilot license. Thus, whereas education can be used
as a measure of general cognitive training, FAA ratings provide measures of specialized
skills training. Increased levels of flight expertise are consistently associated with better
flight performance and decreased attentional demands of aircraft navigation (Bellenkes et al.
1997; Schriver et al. 2008). Attentional demands are greatest at the most basic levels of
flight expertise (and the least amount of required deliberate practice) (Bellenkes et al. 1997;
Schriver et al. 2008). Thus, like the results from the Enoch et al. (2009) study, it may be that
COMT val158met status interacts with flight expertise, such that COMT influence on flight
performance is greater among pilots with the lowest level of flight experience. Buttressing
this idea is that interactions between flight expertise and age, apolipoprotein-ε4 status, and
brain size on flight simulator performance have been found (Adamson et al. 2010; Kennedy
et al. 2010; Taylor et al. in press; Taylor et al. 2007). These factors are associated with many
of the same cognitive abilities as COMT, such as executive function (Greenwood 2007;
Wolk and Dickerson 2010), working memory (Parasuraman et al. 2002), processing speed
(Salthouse 1996; Schaie 1989; Sullivan et al. 2010), and episodic recall memory
(Greenwood 2007; Luszcz et al. 1997; Raz et al. 2005).
We assessed flight simulator performance among a group of aviators varying in FAA ratings
and COMT val158met status to investigate a possible genetic by environment interaction on
a real-world task. Our goal in this study was to first attempt to replicate previous findings
regarding COMT and neuropsychological measures among a group of participants with
specialized training and second, to extend these findings to a real-world application.
Specifically, we investigated whether a genetic by environment interaction is found between
COMT val158met status and flight expertise on flight simulator performance among a
sample of 172 general aviators. We made two predictions:
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1. Increased number of met alleles will be associated with better performance on
neuropsychological and flight simulator performance tasks.
2. A COMT by expertise interaction will be found such that those with met/met will
benefit from increased expertise on flight performance measures more so than those
with val/val.
Methods
Research participants
This paper reports findings on 172 pilots who had a known COMT val158met genotype and
who were part of the ongoing longitudinal Stanford/VA Aviation Study approved by the
Stanford University Institutional Review Board. Enrollment criteria were age between 40
and 69 years, current FAA medical certificate (Class III or higher) which entails an
assessment of pilots’ vision, hearing, and physical and mental health, and current flying
activity between 300 and 15,000 h of total flight time. All participants gave written informed
consent to participate in the study, with the right to withdraw at any time. At entry, each
participant was classified into one of three levels of aviation expertise depending on which
FAA pilot proficiency ratings had been attained by study entry: (1) least expertise: VFR
(rated for flying under visual flight rules only); (2) moderate expertise: IFR (also rated for
instrument flight); and (3) most expertise: CFII and/or ATP (certified flight instructor of IFR
students or rated for flying air-transport planes). As reported in Taylor et al. (2007), all of
the VFR pilots were recreational pilots, although a small minority were employed in
aviation-related jobs such as aircraft sales or mechanics. Within the IFR group, the majority
were recreational pilots, whereas approximately one-tenth were certified flight instructors,
aviation analysts, or aviators during military service. Approximately one-half of the CFII/
ATP participants were either air-transport pilots, CFIIs, or their job duties included aircraft
piloting. Of the 249 participants who completed a test day by January 2008, 172 pilots had a
known COMT val158met genotype. Table 1 lists demographic and flight experience
characteristics of the sample.
Equipment
Pilots “flew” in a Frasca 141 flight simulator (Urbana, IL). Motion, vibration, and sound
elements were not incorporated into this simulator protocol. The simulator was linked to a
computer specialized for graphics (Dell Precision Workstation and custom C++ OpenGL
Linux software) that generated a “through-the-window” visual environment and
continuously collected data concerning the aircraft’s position and communication
frequencies. The simulator is located in a quiet, darkened room kept at a comfortable
temperature with the cockpit independently lit from the projector display. The display is
projected on a screen 15’ in front of the pilot. The simulation occurred during normal
working hours from 0900 to 1600 at the pilot’s preference. Previous work in our lab
indicates that the flight simulator has validity as it distinguishes performance between
novice and expert aviators, and between younger and older aviators (Taylor et al. 2007;
Taylor et al. 2005).
Measures
Flight simulator performance—The scoring system of the flight simulator-computer
system produces 23 variables that measure deviations from ideal positions or assigned
values (e.g., altitude in feet, heading in degrees, airspeed in knots), or reaction time in
seconds (Yesavage et al. 1999). Because these individual variables have different units of
measurement, the raw scores for each variable were converted to z-scores, using the baseline
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visit mean and SD of 141 participants enrolled during 1996–2001 (scores on the morning
and afternoon flights were averaged).
The z-scores on the individual measures were aggregated on the basis of previous principal
component analyses into four component measures (Yesavage et al. 1999; Yesavage et al.
2002): (1) accuracy of executing the air traffic control (ATC) communications regarding the
heading, altitude, radio frequency, and transponder code; (2) traffic avoidance; (3) scanning
cockpit instruments to detect engine emergencies; (4) executing a visual approach to
landing. A flight summary score, the average of the above four component measures, was
used as the primary performance measure. Thus, one global and four component measures
of flight performance were assessed.
Neuropsychological battery—Three aspects of cognitive ability were assessed:
executive function, speed of processing, and working memory.
Executive function—The Discovery subtest of the Shifting Attention Test (Cogscreen-
AE, (Kay 1995)) was used to measure cognitive flexibility, (ability to shift to a new rule),
and the ability to maintain the set. As in the Wisconsin Card Sorting Test, participants use
trial and error to discover which of multiple stimulus dimensions (such as object color) is
currently relevant and then use that dimension as the sorting rule until feedback indicates it
is no longer relevant (see Taylor et al. 2005) for additional information). Three types of
performance were measured: (1) number of completed rule sets, (2) number of failures to
maintain set, and (3) the percentage of correct responses. These three performance measures
were standardized and averaged into a composite measure of executive function.
Speed of processing—Speed of processing was measured by a composite variable
comprised of Pattern Comparison and Digit Copying (Salthouse 1992). In the Pattern
Comparison task, participants make same-different decisions about pairs of patterns made of
connected line segments. In the Digit Copying task, participants copy digits as rapidly as
possible. For each task, participants complete two 30-s trials, and the number of correct
responses was scored. Scores from the four trials were standardized and then averaged
together to create a composite measure of processing speed (see Taylor et al. 2005).
Working memory—Working memory was assessed by a composite of two subtests of the
Dual Task in Cogscreen-AE (Kay 1995), Dual Task Previous Number Alone Accuracy and
Dual Task Previous Number Dual Accuracy. In Dual Task Previous Number Alone
Accuracy, the subject attempts to recall the previous number shown while simultaneously
encoding the current number for the next stimulus presentation. In Dual Task Previous
Number Dual Accuracy, participants have the additional task of actively tracking the cursor
on the computer screen. Scores from each subtest were standardized, then averaged together
to create a composite measure of working memory.
Genotyping—DNA was extracted either from samples of frozen whole blood (see
(Murphy et al. 1997) for description of this method) or from saliva samples collected using
Oragene DNA kits (DNA Genotek, Ontario Canada; DNA extracted according to
manufacturer’s instructions). DNA was genotyped using the Human 610-Quad BeadChip
(Illumina, San Diego CA) on an Illumina Beadstation using the manufacturer-provided
procedures. The COMT val158met polymorphism can be directly detected using this chip.
Call rates greater than 99% were achieved on all subjects at this polymorphic site. All staff
who collected performance measures were blind to the genotypes.
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Procedures
Participants had one 45 min practice flight in the simulator to experience the simulator’s
flight and landing characteristics. Additionally, participants completed five 75 min practice
flights to gain familiarity with the flight scenario used throughout the study. Participants
typically completed two practice flights a day during a one to 3-week period, after which
they had a 3-week break before returning for the test day. During the test day, the participant
flew a 75-min flight in the morning and a 75-min flight in the afternoon. Each flight was
followed by a 40- to 60-min battery of cognitive tests, including CogScreen-AE (Kay 1995),
a computer-administered battery of 13 tests designed to assess perceptual and cognitive
abilities relevant to aircraft piloting. The entire test day lasted approximately 6 h, including a
30- to 50-min lunch break. Each flight began with the air-traffic controller’s (ATC) takeoff
clearance. The first ATC message was presented 3 min later, after participants had lifted off
the runway and climbed to 1200 ft (365.76 m). During the flight, pilots heard 16 ATC
messages, presented at the rate of one message every 3 min, directing the pilot to fly a new
heading, a new altitude, dial in a new radio frequency, and in 50% of the legs, dial in a new
transponder code. Participants were instructed to read back the ATC messages and execute
them in order and according to FAA standards. To further increase workload, pilots were
confronted with randomly presented emergency situations: engine malfunctions (carburetor
icing, drop of engine oil pressure) (8 of 16 legs), and/or suddenly approaching air traffic (10
of 16 legs). Pilots were to report engine malfunctions immediately and to avoid air traffic by
veering quickly yet safely in the direction diagonal to the path of the oncoming plane. Pilots
flew in severe turbulence throughout the flight, and also encountered a 15-knot crosswind
during approach and landing. Multiple versions of this flight scenario were presented to
reduce learning of specific maneuvers and ATC messages.
Statistical analyses
For all analyses, the predictor variables were COMT val158met status, expertise, and COMT
val158met genotype by expertise interaction. COMT genotype and expertise were coded as
ordinal variables (met/met = 1; met/val = 0; val/val = 1; VFR = 1, IFR/CFI = 0, CFII/ATP
= 1). The COMT val158met genotype by expertise interaction was calculated by multiplying
the coded level of COMT status to the coded level of expertise for each subject. Previous
work indicates that age is significantly associated with all measures of flight performance
(Taylor et al. 2007; Taylor et al. 2005). Therefore, we included a measure of age (centered at
median age of 57.0 years) to the model to assess the effects of COMT val158met status and
expertise, after controlling for the effects of age. Because of extreme data points, defined as
z-scores beyond two standard deviations of the mean, all dependent variables were ranked
such that the worst score was ranked “1’, the second worst score, “2,” and so on; these
ranked scores were used in the model.1 PROC GLM in SAS (SAS Institute, Cary, NC) was
utilized.
Results
Demographics
Table 1 lists demographic and flight experience information by COMT val158met allele
status. No significant differences were found between COMT groups for any demographic or
flight experience variable. The distribution of COMT val158met genotypes is consistent with
our predominantly Caucasian population (National Center for Biotechnology Information
2010).
1A similar pattern of results was found when the GLM was conducted with unranked dependent variables and when stepwise
regression was conducted with ranked variables.
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Cognitive performance
As expected, significant negative age effects were seen for all three cognitive measures (all
p’s < 0.02). After controlling for the effects of age, a significant advantage was detected in
executive function such that each additional met allele improved pilots’ performance (p =
0.017, Effect Size (ES) = 0.19) and working memory (p = 0.04, ES = 0.16). No significant
COMT val158met effects were found for speed of processing. We also note that increased
levels of expertise were associated with significantly better performance on working
memory (p = 0.006, ES = 0.21).
Flight performance
As expected from previous research, significant age and expertise effects were seen in
almost all flight performance measures (all age p’s < 0.002; all expertise (except for
emergencies) p’s < 0.05).
There was a nonsignificant trend for COMT val158met status to predict flight summary
performance (p = 0.10, ES = 0.12). After taking into account the effect of age, a significant
COMT val158met status by expertise interaction was found for traffic avoidance (p = 0.026,
ES = 0.17). As shown in Fig. 1, pilots homozygous for 158met benefited from increased
expertise on this task, whereas the other groups did not. There was a nonsignificant trend on
emergencies (p = 0.057, ES = 0.15), in which for each additional 158met allele, pilots’
emergency performance improved. No other significant COMT val158met effects were
found for the flight performance. Table 2 provides results of each flight performance and
cognitive variable by COMT val158met status by expertise level group score.
Discussion
Consistent with other studies, a significant advantage was detected in the cognitive ability
measures of executive function and working memory, after controlling for the effects of age,
for carriers of the met allele (Nagel et al. 2008; de Frias et al. 2005). These results extend
previous work in that this sample is comprised of very high functioning middle-aged and
older adults who have specialized training.
No significant main effects of COMT val158met status on flight simulator performance were
detected. We did, however, find some support for one environmental influence, flight
expertise, on COMT val158met status. Aviators with the COMT met158met genotype
benefited from increased levels of expertise on a traffic avoidance task, whereas the other
groups did not. Other researchers have suggested that people carrying the met allele will
perform better at sustained attention tasks, whereas those carrying the val allele will perform
better on more cognitively flexible tasks (Colzato et al. 2010; de Frias et al. 2010; Dickinson
and Elvevag 2009; Houlihan et al. 2009). Our results provide some support for this idea on a
real world task. Traffic avoidance requires flexibly allocating attention between scanning
cockpit instruments and looking out the window. The results suggest that without highly
specialized training, met/met carriers perform worse on real-world tasks requiring cognitive
flexibility than val/val carriers. We conjecture that the accrual of specialized training enables
those with met/met to overcome a possible tendency to fixate their attention on one task
when the overall task, such as flying, requires flexible distribution of attention to multiple
flight tasks. Future studies that incorporate eye-tracking could help determine if less
experienced, met/met pilots are more likely than the other pilots to fixate their attention on
only a subset of the relevant navigation information.
Main effects of COMT genotype status on flight simulator performance may have been
elusive because they are more likely to occur at the neurological rather than behavioral level
(de Frias et al. 2010; Dennis et al.; Dickinson and Elvevag 2009; Mier et al. 2009; Tan et al.
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2007). That is, COMT influences level of dopaminergenic activity which in turn, impacts
performance on tasks requiring sustained or flexible cognitive ability (Robbins and Arnsten
2009). There are essentially two types of dopaminergic activations. The met allele is
associated with relatively high levels of tonic dopaminergic activation, which has a
consistent and slow firing pattern and is positively associated with sustained cognitive tasks.
In contrast, the val allele is characterized by phasic dopaminergic activation, which occurs in
strong bursts and is useful for updating pertinent novel information (de Frias et al. 2010). In
a study with a sample quite similar to ours (all men, ranging in age from 50 to 65 years) (de
Frias et al. 2010), no behavioral differences were found by COMT val158met status.
However, COMT differences emerged at the level of brain activation required to do both
sustained and cognitively flexible tasks. Specifically, met carriers had greater transient
activation in the medial temporal lobe during a task which required updating of working
memory. This result indicates the met carriers were less neurologically efficient than their
val counterparts on a task requiring cognitive flexibility. The reverse pattern was found for
val carriers, who had greater sustained activation in the prefrontal cortex (PFC) during a task
in which they had to hold information in working memory. Among a sample of healthy
young adults, met carriers were less efficient at task switching than val/val carriers (Colzato
et al. 2010). Similarly, Dennis et al. (2010) found no COMT val158met differences on 19
behavioral measures in a large sample of healthy adults aged 18–84, but did find that val
carriers had greater PFC activation during a memory encoding and retrieval task. These
studies suggest a complex relationship between COMT val158met status, neurological
activity, and behavior. It may be that factors such as age and experience help determine the
circumstances in which COMT val158met differences emerge at the behavioral level.
Alternatively, our sample size may have been too small to detect COMT val158met effects
due to narrow ranges of education and specialized training (Barnett et al. 2007). For
example, there were trends for COMT val158met to predict overall flight performance and
emergency performance that may have become significant with a larger sample. With a
sample size of 172, we had the power to detect effect sizes of 0.16 or greater. We were able
to replicate previous research showing COMT val158met effects on measures of executive
function and working memory.
The main implication of the results is that on real world tasks requiring cognitive flexibility,
met carriers may need additional training than val carriers before reaching optimal levels of
performance. In the Enoch et al. (2009) study, a COMT × education effect was found on a
broad array of cognitive abilities in a group living in a socioeconomically disadvantaged
environment. Among our highly educated and specially trained participants, a genetic ×
environment interaction only occurred for a task requiring cognitive flexibility. This
difference points to a need to more thoroughly address how demographic/environmental
characteristics of the sample may influence the genetic effects on cognitive tasks.
Additionally, the COMT × expertise effect on aviation traffic avoidance has direct
implications for driving. Driving is another complex activity that requires both sustained
(steering and speed control in no or little traffic) and flexible (merging into traffic, lane
changes, reacting to other drivers) cognition. Future research could investigate whether new
drivers who are met carriers are at greater risk of traffic incidents and accidents due to
problems with the cognitively flexible aspects of driving. If so, they may benefit from
deliberate practice on these aspects of driving.
In summary, even in a sample with high levels of education and specialized training, an
advantage on neuropsychological assessments of executive function and working memory
were observed for those with the COMT met allele. Although main effects of COMT
val158met status on flight simulator performance were not detected, a COMT by expertise
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interaction on traffic avoidance suggests that met/met carriers benefit from increased
experience on real world tasks requiring cognitive flexibility. Results indicate that
examining genetic effects in real world tasks, such as aircraft navigation, can contribute to
our understanding of the interplay between genes, environment, and cognition.
Acknowledgments
We thank the study’s paid research assistants, including Katy Castile, Daniel Heraldez, and Gordon Reade of
Stanford University, for recruiting and testing participants, and Beatriz Hernandez for statistical assistance. We also
thank the aviator study participants for their donation of time and for being inspirational role models of intellectual
exploration. This research is supported in part by the Department of Veterans Affairs, Veterans Health
Administration, Office of Research and Development, the Sierra Pacific Mental Illness, Research, Education, and
Clinical Center, the Department of Veterans Affairs War-Related Illness and Injury Study Center, and by Grant
Number R37 AG 12713 from the National Institute on Aging. The content is solely the responsibility of the authors
and does not necessarily represent the official views of the National Institute on Aging or the National Institutes of
Health.
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Fig. 1.
Met/met pilots benefit from increased expertise on a traffic avoidance measure
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Table 1
Participants’ demographic and flight experience characteristics by COMT val158met status
met/met
n = 41 met/val
n = 83 val/val
n = 48
Age, mean (SD), years 57.0 (6.8) 57.0 (6.9) 56.5 (6.1)
(range, years) (41–69) (43–68) (43–69)
Education, mean (SD), years 17.4 (1.8) 16.8 (1.9) 16.8 (1.8)
Women, n (%) 5 (12.2) 14 (16.9) 7 (14.6)
White, non-Hispanic, % 98 96 92
Aviation expertise rating, %: VFR/IFR/CFII-ATP 17/54/29 27/55/18 29/48/23
Log hours, mean (SD) 2565 (2826) 2080 (2095) 2571 (3192)
Log hours in past month, mean (SD) 10.0 (13.2) 7.9 (9.9) 10.7 (13.2)
Medical Class I, II, or III, % 14/32/54 8/34/58 2/42/56
Medical waivers,% 2.5 8.4 6.3
Cholesterol-lowering medications, % 14.6 13.3 20.8
Anti-hypertensive medications, % 14.6 19.3 18.8
Self-rated health “excellent/good/fair,” % 63/34/3 55/45/0 63/37/0
Family history of dementia, %: “yes/no/not sure” 12/88/0 18/74/8 19/79/2
Note: Sample size for medical waivers is 161 and for self reported health rating, 171
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Table 2
Means (SD) (z-scores) of flight and cognitive variables by COMT val158met status by expertise level
met/met met/val val/val
VFR
(n = 7) IFR
(n = 22) CFII/ATP
(n = 12) VFR
(n = 22) IFR
(n = 46) CFII/ATP
(n = 15) VFR
(n = 14) IFR
(n = 23) CFII/ATP
(n = 11)
Flight variables
Summary score −0.27 (0.50) 0.30 (0.56) 0.35 (0.43) −0.10 (0.55) 0.03 (0.49) 0.41 (0.38) −0.05 (0.58) −0.04 (0.43) 0.27 (0.48)
Communications −0.48 (0.51) 0.35 (0.75) 0.37 (0.66) −0.18 (0.77) −0.13 (0.64) 0.41 (0.80) −0.12 (0.87) −0.13 (0.61) 0.50 (0.57)
Avoidance −0.51 (0.91) 0.36 (0.53) 0.64 (0.62) 0.13 (0.57) 0.15 (0.65) 0.63 (0.51) 0.24 (0.75) 0.05 (0.46) 0.27 (0.60)
Emergency −0.15 (1.37) 0.33 (0.88) 0.21 (0.67) −0.31(1.23) 0.13 (0.78) 0.35 (0.59) −0.23 (0.96) −0.07(0.85) 0.12 (1.01)
Approach 0.05 (0.31) 0.18 (0.58) 0.20 (0.56) −0.02 (0.48) −0.02 (0.71) 0.24 (0.52) −0.10 (0.68) −0.02 (0.65) 0.19 (0.59)
Cognitive variables
Executive function 0.48 (0.60) 0.33 (0.78) −0.12 (1.08) 0.22 (0.71) −0.11 (0.96) 0.42 (0.66) −0.23 (1.03) −0.31 (0.92) 0.22 (0.46)
Processing speed −0.39 (0.82) 0.36 (0.95) −0.20 (0.86) 0 13 (0.68) −0.12 (0.95) 0.02 (1.03) 0.40(0.72) −0.38 (0.63) −0.21 (0.84)
Working memory −0.30 (1.45) 0.21 (0.69) 0.61 (0.45) −0.17 (0.79) −0.06 (0.98) 0.23 (0.70) −0.01 (0.88) −0.18 (0.81) 0.21 (0.77)
Note: 159 participants completed the executive function measure and 170 completed the working memory measure. No significant differences in age were found in relation to the main effect of COMT
val158met status or COMT × Expertise interaction. Thus, values are mean z-scores of each group and are not adjusted for age
Behav Genet. Author manuscript; available in PMC 2011 September 1.
... Planned disruptions fit with recent suggestions that adversity-related experiences provide valuable opportunities for growth and learning in talent development and elite sports (Collins & MacNamara, 2012;Pierce et al., 2016;Sarkar & Fletcher, 2017a) and are strongly related to traditional systematic desensitization (Wolpe, 1958), stress inoculation training (Meichenbaum, 1985), or stress exposure training (Driskell & Johnston, 1998). Similar approaches have already been demonstrated to be effective in reducing anxiety and improving performance under pressure in sports (e.g., Mace & Carroll, 1986, 1989, Oudejans & Pijpers, 2009, as well as a number of other performance domains such as music (Williamon, Aufegger, & Eiholzer, 2014), aviation (Kennedy et al., 2011), military (Zach, Raviv, & Inbar, 2007), or police response (Nieuwenhuys & Oudejans, 2011). In relation to resilience, the use of planned disruptions fits within the challenge model of resilience (Fergus & Zimmerman, 2005;Seery, 2011). ...
... As such, Met variations might be related to decreased resilience under pressure (Feder et al., 2009). Interestingly, recent evidence in aviation suggests that individuals with the Met variation can learn to counteract this reactivity and increase their performance -even outperforming people with the Val variation -on pressurised tasks through regular training on similar stressful tasks (Kennedy et al., 2011). Such findings seem to provide support for the use of planned disruptions. ...
... Individuals with the Met allele have relatively lower COMT activity and accordingly higher dopamine levels in the synapse than individuals with the Val allele (Chen et al., 2004;Lotta et al., 1995). Many studies have confirmed the important roles of this polymorphism in working memory and its underlying brain basis (Aguilera et al., 2008;Bellander et al., 2015;Bruder et al., 2005;Farrell, Tunbridge, Braeutigam, & Harrison, 2012;Jin et al., 2016;Kennedy et al., 2011;Wang et al., 2013). ...
... The association of the COMT Val158/108Met polymorphism has been found to vary by population. Although most studies in the Caucasian adults linked the Met allele with better working memory performance (Aguilera et al., 2008;Bellander et al., 2015;Bruder et al., 2005;Farrell et al., 2012;Kennedy et al., 2011), previous studies in healthy Han Chinese samples have reported the association in the opposite direction (Jin et al., 2016;Wang et al., 2013). Second, findings on the association between the COMT Val158/108Met polymorphism and prefrontal activation during working memory are not as consistent as findings on the association between the same polymorphism and working memory performance. ...
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... Indeed, preliminary findings support that the heritability of expert performance may actually increase rather than decrease with deliberate practice, contrary to predictions of deliberate practice theory (Hambrick & Tucker-Drob, 2015). More generally, this also highlights the po- tential importance of more complex interplay between genes and environment-that is, gene-environment interactions (Kennedy et al., 2011;Schellenberg, 2015) and various forms of gene- environment covariation (Scarr, 1996), for expertise. ...
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We summarize key findings from the literature on neuroanatomical and functional correlates of expertise, concluding that expertise is related to macroanatomical properties of domain-relevant brain regions and ultrastructural properties of both the gray and the white matter. The consequence of these neural adaptations is a capacity for vastly more efficient performance of domain-specific tasks. In functional terms, this depends on multiple mechanisms that are situated at different levels of neural processing. These mechanisms include automation and alterations in functional connectivity, as well as specializations within memory systems and sensorimotor systems that optimize the processing of information which is relevant for the particular domain of expertise. Finally, we discuss the neural mechanisms of expertise from the perspective of new models that emphasize a multifactorial perspective and take into account both genetic and environmental influences on expertise and its acquisition.
... Other genetic factors affect expertise indirectly by influencing deliberate practice and its covariates. This highlights the potential importance of both gene-environment interactions (Kennedy et al., 2011;Schellenberg, 2015) and various forms of gene-environment covariation (Scarr, 1996) for expertise. ...
... Indeed, preliminary findings support that the heritability of expert performance may actually increase rather than decrease with deliberate practice, contrary to predictions of deliberate practice theory (Hambrick & Tucker-Drob, 2015). More generally, this also highlights the potential importance of more complex interplay between genes and environment-that is, gene-environment interactions (Kennedy et al., 2011;Schellenberg, 2015) and various forms of geneenvironment covariation (Scarr, 1996), for expertise. ...
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Scientific interest in expertise-superior performance within a specific domain-has a long history in psychology. Although there is a broad consensus that a long period of practice is essential for expertise, a long-standing controversy in the field concerns the importance of other variables such as cognitive abilities and genetic factors. According to the influential deliberate practice theory, expert performance is essentially limited by a single variable: the amount of deliberate practice an individual has accumulated. Here, we provide a review of the literature on deliberate practice, expert performance, and its neural correlates. A particular emphasis is on recent studies indicating that expertise is related to numerous traits other than practice as well as genetic factors. We argue that deliberate practice theory is unable to account for major recent findings relating to expertise and expert performance, and propose an alternative multifactorial gene-environment interaction model of expertise, which provides an adequate explanation for the available empirical data and may serve as a useful framework for future empirical and theoretical work on expert performance. (PsycINFO Database Record
... Because of its crucial role in the prefrontal circuits, it has been hypothesized that these COMT polymorphism variants directly affect specific cognitive functions in humans. For example, studies suggest that individuals with the met allele present enhanced mental flexibility and capacity to shift [10,11,12] and working memory [13,14,15]. On the other hand, val/val homozygous allele was associated with better performance in a decision making task influenced by emotional processing [16]. ...
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Background Prefrontal dopamine is catabolized by the catechol-O-methyltransferase (COMT) enzyme. Current evidence suggests that the val/met single nucleotide polymorphism in the COMT gene can predict the efficiency of executive cognition in humans. Individuals carrying the val allele perform more poorly because less synaptic dopamine is available. Methodology/Principal Findings We investigated the influence of the COMT polymorphism on motor performance in a task that requires different executive functions. We administered a manual aiming motor task that was performed under four different conditions of execution by 111 healthy participants. Participants were grouped according to genotype (met/met, met/val, val/val), and the motor performance among groups was compared. Overall, the results indicate that met/met carriers presented lower levels of peak velocity during the movement trajectory than the val carriers, but met/met carriers displayed higher accuracy than the val carriers. Conclusions/Significance This study found a significant association between the COMT polymorphism and manual aiming control. Few studies have investigated the genetics of motor control, and these findings indicate that individual differences in motor control require further investigation using genetic studies.
... Further twogroup (Val homozygotes vs. Met carriers) analysis showed that participants with the Val allele (high activity of COMT function) in our Chinese sample performed better on the two-back WM task than the Met allele carriers. These results are in clear contrast with previous reports based on Caucasian samples (Aguilera et al. 2008;Bruder et al. 2005;Farrell et al. 2012;Kennedy et al. 2011), but are consistent with previous studies of Asian samples using tasks related to WM (Cheon et al. 2008;Ma et al. 2007;Qian et al. 2009;Tai & Wu 2002;Wu et al. 2001;Yeh et al. 2009;Zhang et al. 2007). Similarly, our finding that the Val allele rather than the Met allele was associated with larger hippocampi also contradicted the finding from studies of Caucasians (Cerasa et al. 2008;Honea et al. 2009). ...
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