Genetic and Neural Factors in Alcohol-Related Cognition
Phase: NA
Conditions: Alcohol Abuse
Sponsor: Virginia Commonwealth University

Genetic and Neural Factors in Alcohol-Related 
Cognition 
 
HM20013938 
Approved by IRB 8/24/2018  

Table 1. Overview and schedule of proposed training activities and their alignment with training goals (TG). 
Domain 
Activity Description 
Proposed Award 
Year 
Y1 Y2 Y3 Y4 Y5 
Mentored 
Training 
Meet with Dr. Dick to select/discuss directed readings, develop of 
theoretical models, and track progress (4 hours/month Y1-Y5; TG #1) 
X 
X 
X 
X 
X 
Meet with Dr. Goldman to discuss directed readings from literatures 
on clinical alcohol misuse, externalizing behaviors, and their genetic 
basis (1 hour/month Y1-Y5; TG #1).  
X 
X 
X 
X 
X 
Meet with Dr. Aliev to select/discuss directed readings and 
develop/review genetic and genomic statistical analyses (4 
hours/month Y1-Y5; TG #2) 
X 
X 
X 
X 
X 
Meet with Dr. Moeller to develop and discuss the design, progress, 
and results of the neuroimaging study (1 hour/month Y3-Y5; TG #1-2) 
 
 
X 
X 
X 
[Meet with Dr. Parrott to develop the design and implementation of 
alcohol administration (1 hour/month Y2-Y3; TG #1-2)] 
 
[X] [X] 
 
 
Lab rotation with Dr. Goldman at NIAAA’s Laboratory of 
Neurogenetics to learn advanced molecular genetics and alcohol 
misuse investigation techniques (5 days in Y1; TG #1-2) 
X 
 
 
 
 
Lab rotation with Dr. Parrott at the University of Georgia to learn 
advanced alcohol administration and aggression laboratory 
techniques (3 days in Y2; TG #1-2) 
 
X 
 
 
 
[VCU Lab visit by Dr. Parrott to evaluate the implementation of alcohol 
administration protocol (3 days in Y3; TG #1-2)] 
 
 
[X] 
 
 
Conferences Present results at annual meetings of Behavior Genetics Association 
annual meeting and Research Society on Alcoholism (Y2-Y5) 
 
X 
X 
X 
X 
Courses 
HGEN 502: Advanced Human Genetics - 3 hours/week in Y1. A 
comprehensive study of specific areas in human genetics.  
X 
 
 
 
 
HGEN 603: Mathematical and Statistical Genetics - 3 hours/week in 
Y1. Provides an introduction to the rudiments of theoretical and 
applied mathematical population genetics.  
X 
 
 
 
 
HGEN 617: Genetic Analysis of Complex Traits - 3 hours/week in Y2. 
Introduces the theory/practice of analysis of complex human traits.  
 
X 
 
 
 
HGEN 619: Quantitative Genetics - 3 hours/week in Y2. The effects of 
genes and environment on complex human traits. 
 
X 
 
 
 
[IPAS 600: The Biological Basis of Addiction -  3 hours/week in Y3.] 
 
 
[X] 
 
 
[RHAB 644: Alcohol and Human Behavior -  3 hours/week in Y3.] 
 
 
[X] 
 
 
Grant 
Writing 
Prepare (Y4-Y5) [and submit (Y5)] an R01 application. 
 
 
 
X 
X 
Responsible 
Conduct of 
Research 
Biennial human subjects research re-certification through the 
Collaborative Institutional Training Initiative (CITI) (Y1, Y3, Y5) 
X 
 
X 
 
X 
VCU- and department-wide ethics workshops and discussions with 
mentors and student scholars (Y1-Y5) 
X 
X 
X 
X 
X 
CCTR 520: Fundamentals of Research Regulation - 2 hours/week in 
Y1.  The regulations that govern translational and clinical research.  
X 
 
 
 
 
OVPR 601: Scientific Integrity - 1 hour/week in Y1. A survey of 
contemporary issues relating to responsible conduct in research.  
X 
 
 
 
 
OVPR 602: Responsible Scientific Conduct - 1 hour/week in Y2. A 
survey of issues relating to responsible conduct in research. 
 
X 
 
 
 
OVPR 603: Responsible Conduct of Research - 1 hour/week in Y2. 
This course will develop and refine skills needed to solve problems 
involving relevant topic areas of responsible scientific conduct.  
 
X 
 
 
 
Workshops 
Attend University of Washington Summer Institute in Statistical 
Genetics (3 weeks in Y1) 
X 
 
 
 
 
 
Contact PD/PI: Chester, David S
Candidate Information and Goals for Career Development                                                        
Page 78

SPECIFIC AIMS 
Aggressive behavior in the context of alcohol misuse is a substantial public health concern. Genetic 
predispositions have been identified for both aggression and alcohol misuse. However, the biological factors 
that predispose individuals towards alcohol-influenced aggression remain poorly understood. Specifically, the 
extent to which alcohol-influenced aggression is genetically-influenced is unknown. Further, it remains to be 
seen whether alcohol-influenced aggression is uniquely heritable, or is simply the by-product of genetic risk 
factors for both alcohol misuse and aggression. If alcohol-influenced aggression is found to be substantially 
genetically-influenced, the specific genetic and neural pathways through which these effects are transmitted 
must then be investigated. The goal of the research activities in this K01 proposal is to fill these gaps in our 
knowledge. 
The overall objective of the research activities in this K01 award proposal is to examine the genetic factors 
and neural mechanisms that promote alcohol-influenced aggression. The proposed research activities will 
address the following research aims and test their associated hypotheses: 
Aim 1: Examine the extent to which genetic factors influence the extent to which individuals act 
aggressively in the context of alcohol misuse. Hypothesis 1: Genome-wide complex trait analysis (GCTA) 
will reveal that alcohol-influenced aggression exhibits substantial genetic heritability. 
Aim 2: Examine whether genetic factors for alcohol-influenced aggression exist above-and-beyond 
genetic risk factors for general aggressiveness and alcohol misuse. Hypothesis 2: After statistically 
controlling for genome-wide associations with non-alcohol-influenced aggression and alcohol misuse, 
significant genetic heritability will still be observed for alcohol-influenced aggression via GCTA. 
Aim 3: Identify the specific genetic loci and polymorphisms that are most strongly linked to alcohol-
influenced aggression and create polygenic risk scores from these findings. Hypothesis 3: Genome-wide 
association study (GWAS) techniques will identify specific gene polymorphisms associated with alcohol-
influenced aggression. 
Aim 4: Identify functional and structural brain mechanisms that transmit the genetic effects on alcohol-
influenced aggression. Hypothesis 4: Polygenic risk scores for alcohol-influenced aggression will be 
associated with greater laboratory aggression, through changes in brain structure and function. 
 
This proposal capitalizes on the resources available through [NIH-funded publicly-available datasets from 
the database of Genotypes and Phenotypes (dbGaP)] and VCU’s Spit for Science (S4S) project, on which my 
primary mentor, Dr. Danielle Dick is a Principal Investigator. Drs. Goldman and Aliev (Co-Mentors) also play 
substantial roles in many of these projects. I would begin by analyzing existing data from [the dbGaP discovery 
sample], then seeking to replicate these findings with ongoing data collection for Spit for Science at my current 
institution, VCU. Finally, I would conduct a new MRI brain imaging study, using S4S participants (recruited 
based on their underlying genetic risk profiles) analyses in order to leverage my existing skillset in 
neuroimaging and laboratory aggression measurement and further accomplish the proposed research aims.   
Accomplishing these aims would advance my long-term goal to become an independent alcohol 
investigator who integrates across multiple disciplines to study the factors that influence alcohol-influenced 
aggression. These activities would set the stage for R01-level applications to investigate the environmental 
factors that influence these effects, and biologically-informed interventions that might ameliorate them.  
Contact PD/PI: Chester, David S
Specific Aims                                                                                                 
Page 79

RESEARCH STRATEGY 
A. Significance 
A1. Aggressive behavior is a substantial public health concern in the United States, with approximately 1.2 
million violent crimes occurring in 20151. Such violent crimes (e.g., aggravated assault, murder, rape) resulted 
in over 1.5 million non-fatal injuries and over 17,000 deaths in 20152. Previous estimates of these aggressive 
acts’ financial toll was approximately $177 billion3. Violent crime is occurring with greater frequency in recent 
years, rendering the investigation and treatment of aggression an urgent issue1. Alcohol is a significant factor 
in at least 40% of criminally violent acts4. These frequency rates hold across juvenile and adult populations5 
and soar to approximately 66% in the context of intimate partner violence5. One in three college 
undergraduates experienced alcohol-influenced aggression and sexual assault rates on college campuses are 
drastically magnified by alcohol misuse5,70. These statistics lead to the inevitable conclusion that alcohol-
influenced aggression is a significant threat to public health and necessitates further research into its 
underlying bases. 
A2. Alcohol is not merely correlated with greater aggression, but numerous laboratory experiments have 
shown that alcohol consumption causes increased aggression6-8. Further, there exists a dose-response curve, 
in which greater doses of alcohol cause greater corresponding levels of aggressive behavior9. Alcohol’s ability 
to increase aggression is likely due to its ability to reduce inhibitory psychological processes and increase 
negative emotions such as anger and frustration10.  
A3. Despite alcohol’s profound effect on aggression, there is substantial variability among individuals in the 
extent of the alcohol-aggression link11. Indeed, not all alcohol misuse results in aggressive acts, yet the 
reasons for the underlying variability in this phenomenon remain incompletely understood. Given that variability 
in both aggression and alcohol misuse is substantially influenced by genetic components12-13, it is likely that 
such heritable factors substantially contribute to individual differences in alcohol-influenced aggression. 
A4. To date, there has been little-to-no investigation of the genetic basis of alcohol-influenced aggression. 
A substantial body of research has developed around the genetic basis of alcohol misuse and aggression, 
treating these outcomes separately. This has produced a critical gap in the understanding of aggression, 
alcohol consumption, and their interactive effects.  
A5. Behavioral genetics should factor in the contextual nature of human behaviors. Attempts to identify the 
genetic basis of alcohol misuse and aggressive phenotypes are aided by modeling the complexity inherent in 
them14-15. For instance, one study found that a genetic risk score for aggression’s effect on intimate partner 
violence was moderated by a laboratory alcohol adminstration16. Ignoring these contextual, environmental 
factors may underlie some of the irreproducibility of genetic associations with aggressive phenotypes. This 
project will model aggressive phenotypes alongside the contextual element of alcohol misuse, and use 
polygenic risk scores to predict such alcohol-induced aggression. 
A6. Another beneficial development for genetic approaches to alcohol-influenced behaviors is the 
incorporation of neuroscientific approaches to test mechanistic hypotheses. Genetic effects on complex 
behaviors are likely mediated by changes in brain structure and function17 (see Figure 1 for conceptual model).  
 The added granularity provided by these neural mechanisms is 
critical for understanding how genetic influences impact outcome, and 
potentially for developing effective treatments for alcohol misuse. The 
proposed approach, which brings together polygenic, contextual, and 
neural mechanistic effects, is in line with the NIAAA Strategic Plan’s goal 
to identify genomic and non-genomic mechanisms of alcohol effects. 
B. Innovation 
The proposed research details a novel approach to understanding 
the biological basis of alcohol-influenced aggression. This project will 
advance the field in several ways. First, the genetic basis of alcohol misuse and aggression have been 
frequently investigated in separation, but rarely together. The proposed research will serve as the first 
systematic investigation of the genetic basis of alcohol-influenced aggression. Second, the proposed research 
will use existing data from the NIAAA-funded Collaborative Studies on Genetics of Alcoholism (COGA) 
project18 [and four other publicly-available genomic datasets] to develop novel polygenic risk scores for 
alcohol-influenced aggression. These risk scores would be a resource to the field and could be used by other 
researchers to examine this under-investigated behavioral phenotype. The proposed research will use these 
polygenic risk scores to identify at-risk individuals from another NIAAA-funded longitudinal project, Spit for 
Science19. I will collect new data from these individuals using neuroimaging techniques and laboratory alcohol 
administration and aggression tasks. Building off of these ongoing projects is an efficient use of resources 
Contact PD/PI: Chester, David S
Research Strategy                                                                                             
Page 80

given the immense expense of longitudinal genotyping projects. Further, employing a sample of alcohol-
dependent probands and a normative undergraduate sample will enhance the generalizability of the findings 
obtained in this research.  
In addition to these innovative aspects, the research and training activities associated with this proposal will 
provide novel training for in genetic, genomic, and statistical methods, and conceptual knowledge of alcohol 
misuse phenotypes. I will combine this new skillset with my existing expertise in neuroimaging and aggression 
to begin a career of investigating alcohol misuse and its ability to magnify violence. 
C. Approach 
The proposed research seeks to identify whether alcohol-influenced aggression has a substantially 
heritable genetic component (Aim I), that this heritability exists above-and-beyond genetic risk factors for 
general aggressiveness and alcohol misuse (Aim II), that specific genetic polymorphisms will be associated 
with alcohol-influenced aggression and these can be translated into polygenic risk scores (Aim III), and that 
these risk scores will exert their effects on alcohol-influenced aggression through specific alterations in brain 
function and structure (Aim IV). I will pursue these aims using [a discovery sample comprised of five NIH-
funded genomic datasets that are publicly available through the database of Genotypes and Phenotypes 
(dbGaP) and a replication sample from] the NIAAA-funded VCU Spit for Science Student Survey. 
Discovery Sample from dbGaP 
The GWAS discovery sample (N = 31,123) will be drawn from five ongoing and completed, multisite studies 
on the genetic basis of substance dependence and related behavior, available via dbGaP (Table 1). 
Table 1. List of dbGaP projects used in discovery sample (N = 31,123). 
Project 
Funding 
Source 
Sample 
Size 
Participants 
dbGaP ID 
Yale-Penn Alcohol Dependence 
GWAS (ADGWAS)73 
NIAAA/NIDA 
2,909 
Alcohol-dependent participants + 
controls 
phs000425.v1.p1 
Collaborative Studies on Genetics of 
Alcoholism (COGA)20 
NIAAA 
17,783 
Alcohol-dependent probands + genetic 
relatives, + controls 
phs000092.v1.p1  
Collaborative Genetic Study of 
Nicotine Dependence (COGEND)74 
NCI 
2,900 
Nicotine-dependent probands + genetic 
siblings, + controls 
phs000092.v1.p1  
Family Study of Cocaine Dependence 
(FSCD)75 
NIDA 
1,044 
Cocaine-dependent participants + 
controls 
phs000092.v1.p1  
Australian GWAS of Heroin 
Dependence (GWASHD)76 
NIDA 
6,487 
Heroin-dependent participants + controls  phs000277.v1.p1 
Participants. Across the discovery sample, participants exhibit substantial demographic variance (Table 2). 
The COGA sample, which is roughly generalizable to the other samples, exhibited substantial socioeconomic 
diversity (54.6% completed high school, median income: $35,000, income range: $1,000-150,000). 
Table 2. Demographics of dbGaP projects used in discovery sample. 
Genotyping and imputation. Participants provided 
blood samples to biologic repositories, on which 
whole-genome genotyping was performed. Several 
genome-wide Illumina arrays were used, including the 
Human OmniExpress 12.VI, the Omni2.5 BeadChip, 
and the Human610-Quad BeadChip.] Genotypic data 
were checked for minor allele frequency (SNPs 
excluded with frequencies < 3%), pedigree 
structure/Mendelian inconsistencies, with samples 
imputed to 1000 Genomes21 using SHAPEIT22 and 
then IMPUTE223.  
Phenotype measures. Participants completed the Semi-Structured Assessment for the Genetics of 
Alcoholism (SSAGA)24 [or variants of this instrument (e.g., Semi Structured Assessment for Drug Dependence 
and Alcoholism) that included our specific questions-of-interest]. The SSAGA includes reports of whether 
participants have previously performed physically-aggressive acts, and whether the acts were performed while 
participants had consumed alcohol or not (e.g., “have you ever physically injured anyone on purpose?”). 
Greater alcohol-influenced aggression is indicated by a greater number of yes (with alcohol) responses to such 
questions and non-alcohol-influenced aggression is indicated by a greater number of yes (no alcohol) 
responses. The SSAGA also assesses the extent to which participants have previously engaged in specific 
aspects of alcohol misuse (e.g., binge drinking)25. 
Analytic Plan  
Genome-wide complex trait analyses (GCTA). The initial analysis of the [discovery] dataset will seek to 
decompose phenotypic variance into the proportions that can be explained by genetic (h2) and 
Project 
Sex 
Age 
Range 
Age 
M(SD) 
Ethnicity/Race 
ADGWAS 
46.9% F, 
53.1% M 
18-79 
37.4 
(11.8) 
35.1% ED, 
64.9% EM 
COGA 
53.7% F, 
46.3% M 
18-97 
39.83 
(14.6) 
65.8% ED, 
26.2% EM 
COGEND 
61.8% F, 
38.2% M 
25-47 
36.5 
(5.5) 
55.4% ED, 
44.6% EM 
FSCD 
50.3% F, 
49.7% M 
18-60 
37.0 
(8.8) 
48.3% ED, 
51.7% EM 
GWASHD 
47.0% F, 
53.0% M 
18-58 
35.6 
(9.2) 
100% ED 
ED=European-Descent, EM=Ethnic-Minority 
Contact PD/PI: Chester, David S
Research Strategy                                                                                             
Page 81

environmental/measurement-error factors26. GCTA will quantify the heritability of aggressive, alcohol-misusing, 
and alcohol-aggressive phenotypes. GCTA will then be applied to determine the extent whether alcohol-
influenced aggression has distinct heritability from general aggression and alcohol misuse (Figure 2A) or 
shares substantial genetic overlap with these two related phenotypes (Figure 2B).  
These analyses will be conducted with the 
GCTA software toolkit v1.2627, using a restricted 
maximum likelihood method to compute a 
bivariate genetic relationship matrix by 
correlating the genetic similarity between each 
participant. Then, these genetic similarity 
estimates are modeled as random effects 
predictors of each phenotype: alcohol-
influenced aggression, non-alcohol-influenced 
aggression, and alcohol misuse. Fixed-effects covariates will include age, ethnicity/race, sex, and 
socioeconomic status. To prevent heritability inflation, any two participants who share a second-cousin degree 
of relatedness or more will be excluded from subsequent analyses. A heritability (h2) estimate will be calculated 
for alcohol-influenced aggression, controlling for the heritability of non-alcohol-influenced aggression and 
alcohol misuse phenotypes. A substantial heritability estimate (h2 > 0.1, p < .05) for alcohol-influenced 
aggression will serve as support for the unique genetic basis for this phenotype.  
Genome-wide association study (GWAS). After the GCTA, GWAS will be used to identify single nucleotide 
polymorphisms (SNPs) and clusters of SNPs that are significantly associated with alcohol-influenced 
aggression28-29. Due to the skewness of the alcohol-influenced aggression scores (see Figure 3), quasi-
Poisson regression analyses will be used to accommodate such a 
distribution using the Bioconductor v2.1 package30 and SNPTEST 
v2.531. Specifically, alcohol-influenced aggression scores will be 
regressed onto principal components of the available SNPs using 
an additive model, excluding non-autosomal SNPs, with 
demographics factors as covariates. Due to racial stratification, 
separate GWAS will be performed for participants of African, 
American, East Asian, European, South Asian, and Mixed Race 
descent71. Participants will be empirically assigned to these 
ancestral super-populations using the 1KGP population base and 
the Mahalanobis’ distance between each population71. I will meta-
analyze these separate sets of GWAS findings METAL v3.032, which 
will produce meta-analytic ‘% variance explained’ effect size 
estimates and p values for each SNP. [In addition to this meta-
analytic approach, I will test for gene-by-race/ethnicity moderation 
using a kernel-machine approach to estimate whether each SNP’s association with alcohol-influenced 
aggression varies across the discovery sample’s diverse racial/ethnic groups, using the Robust Joint Tests 
package77.] After correction for genetic inflation and weighting based on sample size, I will calculate polygenic 
risk scores for alcohol-influenced aggression [based on SNPs meeting increasingly stringent significance 
thresholds: .5, .4, .3, .2, .1, .05, .01, .001, .0001. The threshold that maximizes the variance explained (R2) in 
alcohol-related aggression will be used for risk score calculation33.] Using an additive approach, I will sum 
across the number of alleles that are significantly linked to the phenotype, weighted by their respective effect 
size estimates from the GWAS. For example, if the A allele (versus the corresponding G allele) of a given SNP 
is significantly associated with greater alcohol-influenced aggression, then each copy of the A allele will be 
initially coded as +1 (GG = 0, GA = 1, AA = 2). These scores will then be multiplied by the GWAS effect size 
estimate for that given SNP. This polygenic risk scores will capture aggregate genetic risk for alcohol-
influenced aggression in a manner that represents the current state of the field34. 
Feasibility  
Preliminary phenotypic analyses on the alcohol-influenced aggression scores from the COGA dataset, 
assessed among a subset of 9,273 participants, revealed a substantially-variable, albeit positively-skewed, 
distribution of alcohol-influenced aggression (Figure 3). Scores were distributed across the possible 0-10 range 
of the score, median = 1.00, M = 1.57, SD = 1.73. These initial estimates of phenotypic frequencies suggest 
that there will be sufficient proportions of participants to adequately power the analyses in this proposal.  
Power analysis. Power calculations for the GCTA heritability analysis35, which assumed an underlying 
Contact PD/PI: Chester, David S
Research Strategy                                                                                             
Page 82

heritability of һ2 = 0.2, a type I error rate of 0.05, and a variance of SNP-derived genetic relationships of 
.00002, suggested that 80% power for the proposed GCTA can be obtained with 4,430 participants. The 
[discovery] sample far exceeds this sample size at over [31,000] participants. GWAS power analyses, 
implemented via the GWAS.PC v1.0 package for R statistical software35 were also performed to determine the 
minimum effect size (in units of % variance explained) that [the discovery sample could detect with 80% power. 
Calculations were based on the planned detection of multiple, additive SNP markers, an alpha level of .05, and 
a minor allele frequency of 0.05, revealing that the proposed GWAS is able to detect effect sizes of 0.09% 
variance-explained and larger. However, this is likely an optimistic assessment as this power analysis did not 
account for the moderating effects of ethnicity/race and the genetic relatedness of participants (yet recent 
research has indicated that GWAS power is not significantly affected by underlying genetic relationships 
between participants72).]  
Potential Problems and Alternative Strategies 
The proposed GWAS on the [discovery] sample may not yield any statistically-significant SNPs that are 
associated with alcohol-influenced aggression. If this is the case, polygenic risk scores will be obtained from 
the largest GWAS projects for both aggression (the EAGLE consortium37) and alcohol misuse (Psychiatric 
Genomics Consortium38). An alcohol-influenced aggression risk score will be computed by multiplying the 
aggression and alcohol misuse polygenic risk scores with one another, to statistically simulate the interactive 
effect of these genetic dispositions. There is a current push in genomics research for sample sizes that are 
unattainable by any individual investigator (e.g., N > 50,000)15. The proposed research outlined in the 
[discovery and replication] datasets are admittedly underpowered to detect a complex phenotype such as 
alcohol-influenced aggression. However, the proposed research activities will provide invaluable training that 
will be employed in well-powered datasets throughout my career as an alcohol investigator. 
Sample II: Spit for Science - The VCU Student Survey 
The proposed research will attempt to replicate the findings from the [discovery] sample in a new sample of 
undergraduate students enrolled in VCU’s Spit for Science (S4S) project19 (Phase I). Replicating the polygenic 
factors obtained in a discovery dataset, in an independent sample, is a critical step in building cumulative 
scientific knowledge40. Among a subset of participants in the Spit for Science sample, brain imaging will be 
used to identify the neural mechanisms of polygenic risk for alcohol-influenced aggression (Phase II).  
Phase I - Replication in S4S Sample 
Participants. At the outset of each academic year, incoming first-year VCU undergraduates are invited to 
participate in the S4S project via an online survey, and they have the option to provide a saliva sample that will 
be genotyped. Compensation is $10. From 2011-2014, S4S has enrolled six consecutive cohorts (68% 
average enrollment from incoming freshman, average cohort N = ~2,50019). Of those individuals who 
completed the initial online component, 97% provided a saliva sample for genotyping. Participants in the 
sample reflect general demographics among VCU students, which are relatively diverse (40% male, 60% 
female; 51% White, 19% African American, 15% Asian, 6% Hispanic/Latino, and 9% 
other/multiracial/unknown). Increasing freshman class sizes have magnified the S4S cohort sizes in recent 
years to approximately 3,300 participants per cohort. 
Genotyping and imputation. Genotyping is performed at Rutgers University Cell and DNA Repository 
(RUCDR) using the Affymetrix BioBank array. The 653,000 gene variants included in this array contain 
296,000 common GWAS framework variants for imputation as well as 357,000 functional variants. Quality 
control uses AffyPipe analysis pipeline39 to exclude Off Target Variants, SNPs missing > 5% of genotypes, 
samples missing > 2% of genotypes, and SNPs missing > 2% of genotypes after sample filtering. Samples will 
be imputed to 1000 Genomes21 using SHAPEIT22 and then IMPUTE223. 
Phenotype measures. The same SSAGA24 questions from the [discovery samples] about alcohol-
influenced aggression will be added to the existing online survey administered to all new S4S participants at 
the onset of their participation. The S4S online survey already includes demographic assessments. These 
surveys will be administered in the fall of 2018, 2019, and 2020.  
Analytic Plan  
[S4S data will undergo the same GWAS and risk score procedures as employed in the discovery dataset.] 
Feasibility 
This first phase of Aim II builds upon the already successful and ongoing S4S project, by simply adding a 
short online survey to the existing S4S battery of questionnaires. However, undergraduates at VCU differ from 
the [diverse members of the discovery sample] in ways that may suppress the amount of alcohol-influenced 
aggression among the S4S sample (e.g., lower levels of alcohol misuse and dependence). A pilot sample of 
VCU undergraduates were asked about their aggressive behavior and whether it occurred in the context of 
Contact PD/PI: Chester, David S
Research Strategy                                                                                             
Page 83

alcohol misuse or not. Of the 166 female and male participants surveyed, 53.6% indicated that they had 
participated in a physical fight in the past 5 years (30.1% had been in more than 1 fight). Of those who had 
previously fought, 38.2% participated in this fight under the influence of alcohol. These initial estimates suggest 
that 1 out of 5 VCU undergraduates (i.e., 20.48%) have perpetrated a substantial act of physical aggression 
under the context of alcohol misuse. This prevalence rate indicates that the much larger pool of potential S4S 
participants is likely to exhibit alcohol-influenced aggression at a sufficient rate to test associations with 
polygenic risk scores.  
Power analysis. The expected S4S sample size of 10,000 students will provide 80% power to detect a 
genome-wide effect of 0.35% variance explained in alcohol-influenced aggression, or larger. [The S4S GWAS 
is likely to be under-powered, yet performing this replication GWAS will serve as a valuable training in how to 
collect genomic data and use it to replicate previous GWAS results.]  
Potential Problems and Alternative Strategies. The S4S sample GWAS may not replicate the profile of SNPs 
found in the [discovery] sample, as the S4S sample is smaller and is comprised of undergraduate students. 
However, replication is a crucial step in genomic science and this is as important training experience. 
Phase II - Investigating Neural Mechanisms in an S4S Sub-Sample 
Participants. From the 2018-2020 cohorts of the S4S sample, I will recruit [202] individuals with low (N = 
[101]) and high (N = [101]) polygenic risk scores for alcohol-influenced aggression for a brain imaging 
experiment. Participants [will be equal numbers of males and females and] are expected to reflect the 
ethnic/racial makeup of the larger S4S sample which is relatively diverse (40% male, 60% female; 51% White, 
19% African American, 15% Asian, 6% Hispanic/Latino, and 9% other/multiracial/unknown). Ages will range 
from 21-35 to ensure that only adults complete the study, that they can legally consume alcohol, and that aging 
effects do not influence our MRI data. 
Recruitment and Screening. I will recruit VCU students who enrolled in the 2018-2020 cohorts of the S4S 
study, using their existing contact information in the S4S participant database. Participants will be recruited 
based on their polygenic risk scores that were obtained from the [discovery] GWAS. The S4S GWAS will not 
be used to establish the polygenic risk scores used to recruit these participants as they draw from the same 
pool of individuals. Establishing polygenic effects on behavior requires replication in an independent sample, 
as the use of dependent samples artificially inflates association statistics41. Recruitment based on polygenic 
risk scores will proceed by contacting individuals from the lowest end of the distribution of polygenic risk scores 
(low risk group) and the highest end of the distribution of risk scores (high risk group), working from both ends 
of the distribution towards the median. Individuals who are contacted based on their risk scores will be 
screened with an online survey various conditions that would make the alcohol administration and MRI 
scanning procedures unsafe or invalid (see Protection of Human Subjects for a detailed list) and will be 
contacted to schedule an appointment if they pass these criteria42,43.  
MRI [Sessions]. [The MRI study will take the form of a two-session experiment, in which alcohol or placebo 
beverages are administered to each participant in a counterbalanced order. In Session 1,] participants will 
arrive at VCU’s Collaborative Advanced Research Imaging (CARI) facility where they will repeat the screening 
procedures and then will practice the computer tasks that they will perform in the scanner. Then, participants 
will be told that they will receive [either] a placebo [or] an alcoholic beverage, but that they will not be informed 
of the nature of each beverage 
until the end of the study (see 
Figure 4 for the MRI scan 
timeline). [By random 
assignment,] participants will 
then consume [either a placebo 
beverage of orange juice with 
4ml ethyl alcohol added to the 
rim or an alcoholic beverage 
consisting of a 1:5 ratio of 95% ethyl alcohol and orange juice43. The alcohol dose will be proportional to 
participants’ body weight and sex, due to sex differences in body fat composition and alcohol metabolism 
(females: 0.9 g/kg ethyl alcohol; males: 1.0 g/kg ethyl alcohol)43,44. This alcohol dose typically increases 
participants’ breath-alcohol-concentration to .08%, the legal driving limit in Virginia43,44.] After consuming the 
beverage, participants will then be placed in the MRI scanner and complete a validated laboratory aggression 
paradigm that allows individuals to “hurt” a fictitious opponent with an aversive noise blast, while undergoing 
echo-planar functional MRI (EPI). In this task, participants compete against an opponent to press a button 
faster, and the loser of the competition then hears an aversive noise blast. Aggression is operationalized as the 
Contact PD/PI: Chester, David S
Research Strategy                                                                                             
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volume of the noise blast (65-105 decibels) that participants select for a fictional opponent who repeatedly 
provokes them by selecting extremely loud noise blasts. After completing these scans, [participants will leave 
and return to the CARI center 7 days later for Session 2. Participants will consume either a placebo (if they 
consumed an alcoholic beverage in Session 1) or an alcoholic beverage (if they consumed an alcoholic 
beverage in Session 1), and then will be returned to the scanner to complete the aggression paradigm a 
second time against a new provocative opponent.] Participants will be told that both of their opponents are 
same-sex VCU undergraduates, when in fact, they are computer programs. 
After completing the aggression task, participants will undergo diffusion tensor imaging (DTI), which 
quantifies the integrity of white matter pathways45, and a high-resolution T1 scan, which quantifies gray matter 
density46 (see Figure 5 for a depiction of each brain imaging modality). Participants will be removed from the 
MRI scanner and allowed to relax in a nearby testing room 
until their BAC is between .02-.04%. [At the end of Session 
2, an experimenter will briefly interview each participant to 
assess their suspicion of our deception during the study, 
debriefed as to the true purposes of the study, provided with 
counseling resources in case of distress, and then paid 
$100 for their participation. Participants who guess that they 
had no actual partners or that the goal of the study was 
actually to measure aggression will be excluded from all 
data analyses] 
Analytic Plan 
A [mixed]-effects general linear model (GLM) will test 
the test the prediction that the high polygenic risk group will select louder noise blasts after alcohol 
administration, and that this effect would be absent from those with 
low polygenic risk (Figure 6). All MRI analyses will be conducted 
with FSL v.5.0)47-54. Using FSL, GLMs will compare the two 
polygenic risk groups’ estimates of white matter integrity (i.e., 
fractional anisotropy values)51,52, gray matter density53, and 
functional blood-oxygen-level-dependent (BOLD) signal47-49 across 
[two specific brain networks: the dopaminergic reward circuit, the 
prefrontal control circuit (Figure 7). Aggression is predicted by 
exaggerated activity in the brain’s reward network and by blunted 
activity in the lateral prefrontal cortex’s regulatory regions42, and 
alcohol operates in a similar manner on both of these networks78, 
rendering them likely mediators of polygenic risk.]  
BOLD estimates will be obtained from the aggression trials of 
the task. Multiple comparisons corrections will be conducted using nonparametric threshold-free cluster 
enhancement54. Mediation models will then be fit in which the effect of polygenic risk score group on 
aggression (after the alcohol administration) will be mediated by functional and structural brain estimates from 
brain regions that were significantly different between the two polygenic risk groups (Figure 8). The PROCESS 
macro for SPSS will be used to conduct nonparametric bootstrapping (using 5,000 bootstrapped resamples) to 
test the significance of each neural mechanism’s indirect effect55. 
Feasibility 
I have performed numerous functional and structural MRI experiments 
using these laboratory aggression procedures and statistical techniques56-
65. [My lab has also completed a complex MRI study using this aggression 
paradigm, which recruited 112 participants over 1 year, suggesting that 
Contact PD/PI: Chester, David S
Research Strategy                                                                                             
Page 85

the large MRI sample size in this proposal can be readily obtained at VCU.] Prior research using this laboratory 
aggression paradigm has shown that aggression on this task is reliably increased by alcohol administration66 
and can be safely and effectively administered in the MRI scanner80. Therefore, this task is well-adapted for the 
MRI environment, and for alcohol administration.  
Power analysis. FMRIPOWER v1.067 [and powerMediation79] packages were used to analyze pilot fMRI 
data from previous research on differences between groups (that are at-risk for aggression) in aggression-
related brain activity 42. Using the ventral striatum (a core node of the brain’s reward circuit68) as the region-of-
interest, [mediation modeling will have at least 80% power to detect a small indirect effect (0.09%) between 
risk groups with 198 participants, 99 per group69. Based on previous work with this aggression paradigm, 4 of 
these participants will likely be suspicious of our deception. As such, a sample size of 202 participants was 
selected (101 per group).] 
Potential Problems and Alternative Strategies 
Participants in the low and high polygenic risk groups will likely differ on other variables (e.g., physical 
health) that might serve as problematic confounds. To address this, participants from each group will be 
closely-matched on age, sex, race, and socioeconomic status. The groups will be equated in physical and 
mental health as the screening procedures exclude any individuals with diagnosed physical or mental 
pathologies. There are also risks posed by the MRI environment, alcohol administration, and aggression task 
procedures. I have extensive MRI experience, participants undergo extensive screening procedures, and 
participants are under constant supervision by CARI center staff who are certified in safe MRI and alcohol 
administration procedures. CARI center staff are prepared to effectively handle any potential medical 
emergencies. If a brain abnormality is observed, a licensed radiologist is available through the CARI facility for 
consultation. The success of this study hinges on effective participant recruitment. Multiple offshoot studies 
using S4S data have been successful (e.g., an F31-funded fMRI study in Dr. Dick’s lab that recruits S4S 
participants for based on polygenic risk scores for externalizing behaviors). Further, the recruitment pool is 
large enough to provide many potential participants who meet this study’s inclusionary criteria.  
Benchmarks for Success 
Table 3 summarizes the timeline of the major tasks for both Aim I and Aim II projects. These milestones 
provide benchmarks for success. [All manuscript submissions will target flagship journals of behavioral 
genetics and alcohol misuse (e.g., Addiction Biology, Nature Genetics).] 
 Summary and Future Directions 
The proposed research integrates 
across disciplines, methodological 
and statistical approaches to 
investigate a costly and complex 
phenomenon: alcohol-influenced 
aggression. The studies will 
estimate the extent to which 
alcohol-influenced aggression is 
genetically heritable, and whether 
this heritability is distinct from 
general forms of aggressiveness 
and alcohol misuse. These studies 
will also identify specific genome-wide polymorphisms that are linked to alcohol-influenced aggression and will 
seek to replicate these findings in an independent sample. Further, I will build upon these discoveries by 
combining neuroimaging with a laboratory alcohol administration to identify the neural pathways through which 
these genetic risk factors alter brain structure and functional responses to aggression after alcohol 
administration. These research and training activities are a logical extension from my current skillset and will 
enable him to pursue a career as an independent alcohol misuse researcher. I will use the skillset gained from 
the proposed projects to apply for an R01 to conduct a larger investigation of the environmental factors (e.g., 
childhood trauma) that interact with the genetic risk factors for alcohol-influenced aggression. The ultimate goal 
of such investigation is to construct and validate effective interventions that reduce violent behavior in the 
context of alcohol misuse. The novel training and research experiences that I will gain under this K01 award 
will provide the foundation for these future career steps. 
Table 3. Research activities by award year (Y). 
Activity 
Y1 
Y2 
Y3 
Y4 
Y5 
[Discovery] data preparation 
X 
 
 
 
 
[Discovery] data analysis 
X 
X 
 
 
 
[Discovery manuscript submission] 
 
[X] 
 
 
 
S4S genotyping data collection 
X 
X 
 
 
 
S4S genotyping data analysis 
 
 
X 
 
 
[S4S genotyping manuscript submission] 
 
 
[X] 
 
 
S4S neuroimaging data collection 
 
 
[X] 
X 
 
S4S neuroimaging data analysis 
 
 
 
 
X 
[S4S neuroimaging manuscript  submission] 
 
 
 
 
[X] 
R01 application preparation 
 
 
 
X 
X 
[R01 application submission] 
 
 
 
 
[X] 
Contact PD/PI: Chester, David S
Research Strategy                                                                                             
Page 86

TRAINING IN THE RESPONSIBLE CONDUCT OF RESEARCH 
Across the proposed award timeline, I will receive substantial training in the responsible and ethical conduct of 
research on human participants. Virginia Commonwealth University’s (VCU) Office of Research and Innovation 
offers regular education and training activities in responsible conduct of research. In year 1, I will enroll in two 
VCU courses: CCTR 520: Fundamentals of Research Regulation (2 lecture hours, 2 credits) and OVPR 601: 
Scientific Integrity (1 lecture hour, 1 credit). In year 2, I will enroll in two VCU courses: OVPR 602: Responsible 
Scientific Conduct (1 lecture hour, 1 credit) and OVPR 603: Responsible Conduct of Research (1 lecture hour, 
1 credit). In addition, regular workshops are offered by various VCU departments, centers, and institutes in 
areas such as the informed consent process, adverse and reportable events in research, vulnerable 
populations, bio-safety, data management, and conflicts of interest. I will attend these regular workshops and 
will also gain informal research ethics training in interactions with my primary and co-mentors. Further, my 
weekly laboratory meetings with doctoral students and undergraduate research assistants will regularly involve 
discussions of the responsible conduct of research. As a VCU researcher, I have completed the Basic, 
Social/Behavioral, and Biomedical courses in responsible conduct of research from the Collaborative Institution 
Training Initiative (CITI). I will keep these certifications up-to-date via biennial online courses.  
 
Contact PD/PI: Chester, David S
Training in the Responsible Conduct of Research                                                               
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