Characterizing the Genetic Influences of Prescription Opioid Misuse and the Coheritability with Depression and Anxiety Restricted; Files Only
Martin, Kathleen (Summer 2024)
Abstract
Prescription opioids are a widely used and effective treatment for acute and chronic pain, but repeated use can lead to dependence and misuse. The complications of prescription opioid misuse (POM) can be severe, including overdose, but efforts to reduce POM are limited by our understanding of the associated risk factors. To date, genetic examinations of POM have been limited, with even fewer studies addressing the effects of rare variants and coheritability with other mental health disorders, including depression and anxiety, which are highly comorbid with POM. By analyzing genetic risk factors, we can further our understanding of the biology of POM and inform strategies for prevention.
In the first study, we examined the single nucleotide polymorphism heritability of POM, including the effects of both rare and common variants. We found that POM is polygenic (SNP- heritability= 0.19[0.12]), and that rare variants accounted for most of its SNP-heritability (SNP-heritability = 0.18[0.12]). In the Genome-Wide Association Study of common variant associations, no variants reached genome-wide significance. However, in our rare variant analysis of POM, we detected one novel gene association, USP30.
In the second study we examined the shared vulnerability between depression, anxiety, and POM. The coheritability between POM, depression, and anxiety was limited, based on results from the bivariate Genomic Restricted Maximum Likelihood analyses. POM was positively correlated with a polygenic score (PGS) of depression (r = .02, p = .02); but after accounting for covariates, this association no longer reached statistical significance (OR = 1.23 [0.66, 1.12], p = .12). POM was not associated with a PGS of anxiety. We conclude that POM is highly polygenic with modest SNP-heritability, however POM does not appear to be coheritable with depression or anxiety, possibly due to poor coverage of the genome by the exome array used in the sample and limited power to detect modest genetic correlations.
The present study adds to the very limited body of literature on the genetic effects of POM, and sheds light into its shared genetic vulnerability with depression and anxiety.
Table of Contents
CHAPTER 1: Introduction 1
Genetics of Opioid Use Behaviors 3
Shared Biology of Opioids, Depression, and Anxiety 7
Shared Genomics of Opioids, Depression, and Anxiety 9
Summary 11
Hypotheses and Research Questions 11
TABLES 13
Table 1. NSDUH, 2007 Sample Demographics 13
Table 2. NSDUH, 2012 Sample Demographics 14
Table 3. NSDUH, 2013 Sample Demographics 15
Table 4. NSDUH, 2016 Sample Demographics 16
Table 5. NSDUH, 2017 Sample Demographics 17
Table 6. NSDUH, 2019 Sample Demographics 18
Table 7. NESARC-III, 2012-2013 Sample Demographics 19
CHAPTER 2: Evidence for the Role of Rare and Common Genetic Variants in Prescription Opioid Misuse 20
INTRODUCTION 20
METHODS 22
Sample and Recruitment 22
Measures 23
Genotyping and Quality Control Procedures 23
Imputation Procedures 24
Determination of Genetic Ancestry through Principal Component Analysis 24
Pre-Imputation Quality Control 25
Post-Imputation Quality Control 26
Data Analysis 27
SNP-Based Heritability Estimates 27
Genome-Wide Association Study 28
Genome-Wide Association Results Annotation 29
Genome-Wide Association Replication 30
Sequence Kernel Association Test-Optimal Unified Test of Rare Variants 30
Rare Variant Results Annotation 31
RESULTS 32
GWAS of Common Variants, SNP Heritability, and Replication 32
SKAT-O of Rare Variants 33
Rare Variant Annotation 33
DISCUSSION 34
TABLES 40
Table 8. Demographics for individuals of European Ancestry, by Prescription Opioid Misuse diagnosis 40
Table 9. Top 10 Results from MAGMA 41
Table 10. Top 10 Results from H-MAGMA 42
Table 11. Results of SKAT-O gene-based association test for POM 43
Table 12. Annotation of gene-based association of POM 44
FIGURES 45
Figure 1. Allele frequency distributions of genotyped data 45
Figure 2. PCA analysis of entire NESARC-III sample 46
Figure 3. 47
a. Scree plot of PCA analysis for individuals of European Ancestry 47
b. Plot of R2 explained by each PC 48
Figure 4. Genomic quality control procedures for the GWAS and SKAT-O analyses 49
Figure 5. LDMS-I Heritability estimates by MAF x LD bin 50
Figure 6. Manhattan plot and QQ plot of POM GWAS 51
CHAPTER 3: Examining the Shared Genetic Liability of Prescription Opioid Misuse, Depression, and Anxiety 52
INTRODUCTION 52
METHODS 54
Samples and Quality Control 54
The National Epidemiological Survey on Alcohol and Related Conditions-III (NESARC-III) 54
Depression and Anxiety Discovery GWASs 55
Measures 56
Data Analysis 57
Bivariate GREML 57
Polygenic Score Analysis 58
RESULTS 59
SNP- Heritability and Bivariate GREML 59
Polygenic Risk Scores 59
DISCUSSION 60
TABLES 65
Table 13. Depression and Anxiety Meta-GWAS Samples for PGS Generation 65
Table 14. Demographics for Individuals of European Ancestry, separated by history of POM 66
Table 15. Associations between Anxiety, Depression, and POM with PGSs 67
FIGURES 68
Figure 7. Zero-order correlations between covariates, POM, anxiety, depression, anxiety PGS, and depression PGS 68
CHAPTER 4: Discussion 69
Summary of Findings 69
Broader Applications 70
Limitations 72
Conclusions 73
References 75
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