Browsing by Author "Bogdan, Ryan"

Now showing 1 - 8 of 8
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    Associations between Suicidal Thoughts and Behaviors and Genetic Liability for Cognitive Performance, Depression, and Risk-Taking in a High-Risk Sample
    (Karger, 2021) Johnson, Emma C.; Aliev, Fazil; Meyers, Jacquelyn L.; Salvatore, Jessica E.; Tillman, Rebecca; Chang, Yoonhoo; Docherty, Anna R.; Bogdan, Ryan; Acion, Laura; Chan, Grace; Chorlian, David B.; Kamarajan, Chella; Kuperman, Samuel; Pandey, Ashwini; Plawecki, Martin H.; Schuckit, Marc; Tischfield, Jay; Edenberg, Howard J.; Bucholz, Kathleen K.; Nurnberger, John I.; Porjesz, Bernice; Hesselbrock, Victor; Dick, Danielle M.; Kramer, John R.; Agrawal, Arpana; Psychiatry, School of Medicine
    Background: Suicidal thoughts and behaviors (STBs) and nonsuicidal self-injury (NSSI) behaviors are moderately heritable and may reflect an underlying predisposition to depression, impulsivity, and cognitive vulnerabilities to varying degrees. Objectives: We aimed to estimate the degrees of association between genetic liability to depression, impulsivity, and cognitive performance and STBs and NSSI in a high-risk sample. Methods: We used data on 7,482 individuals of European ancestry and 3,359 individuals of African ancestry from the Collaborative Study on the Genetics of Alcoholism to examine the links between polygenic scores (PGSs) for depression, impulsivity/risk-taking, and cognitive performance with 3 self-reported indices of STBs (suicidal ideation, persistent suicidal ideation defined as ideation occurring on at least 7 consecutive days, and suicide attempt) and with NSSI. Results: The PGS for depression was significantly associated with all 4 primary self-harm measures, explaining 0.6-2.5% of the variance. The PGS for risk-taking behaviors was also associated with all 4 self-harm behaviors in baseline models, but was no longer associated after controlling for a lifetime measure of DSM-IV alcohol dependence and abuse symptom counts. Polygenic predisposition for cognitive performance was negatively associated with suicide attempts (q = 3.8e-4) but was not significantly associated with suicidal ideation nor NSSI. We did not find any significant associations in the African ancestry subset, likely due to smaller sample sizes. Conclusions: Our results encourage the study of STB as transdiagnostic outcomes that show genetic overlap with a range of risk factors.
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    ERRATUM: Genome‐wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward‐related ventral striatum activity in African‐ and European‐Americans
    (Wiley, 2019-11) Wetherill, Leah; Lai, Dongbing; Johnson, Emma C.; Anokhin, Andrey; Bauer, Lance; Bucholz, Kathleen K.; Dick, Danielle M.; Hariri, Ahmad R.; Hesselbrock, Victor; Kamarajan, Chella; Kramer, John; Kuperman, Samuel; Meyers, Jacquelyn L.; Nurnberger, John I., Jr.; Schuckit, Marc; Scott, Denise M.; Taylor, Robert E.; Tischfield, Jay; Porjesz, Bernice; Goate, Alison M.; Edenberg, Howard J.; Foroud, Tatiana; Bogdan, Ryan; Agrawal, Arpana; Medical and Molecular Genetics, School of Medicine
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    Genome-wide association studies of alcohol dependence, DSM-IV criterion count and individual criteria
    (Wiley, 2019-06-04) Lai, Dongbing; Wetherill, Leah; Bertelsen, Sarah; Carey, Caitlin E.; Kamarajan, Chella; Kapoor, Manav; Meyers, Jacquelyn L.; Anokhin, Andrey P.; Bennett, David A.; Bucholz, Kathleen K.; Chang, Katharine K.; Jager, Philip L. De; Dick, Danielle M.; Hesselbrock, Victor; Kramer, John; Kuperman, Samuel; Nurnberger, John I.; Raj, Towfique; Schuckit, Marc; Scott, Denise M.; Taylor, Robert E.; Tischfield, Jay; Hariri, Ahmad R.; Edenberg, Howard J.; Agrawal, Arpana; Bogdan, Ryan; Porjesz, Bernice; Goate, Alison M.; Foroud, Tatiana; Medical and Molecular Genetics, School of Medicine
    Genome-wide association studies (GWAS) of alcohol dependence (AD) have reliably identified variation within alcohol metabolizing genes (e.g., ADH1B) but have inconsistently located other signals, which may be partially attributable to symptom heterogeneity underlying the disorder. We conducted GWASs of DSM-IV AD (primary analysis), DSM-IV AD criterion count (secondary analysis), and individual dependence criteria (tertiary analysis) among 7,418 (1,121 families) European American (EA) individuals from the Collaborative Study on the Genetics of Alcoholism (COGA). Trans-ancestral meta-analyses combined these results with data from 3,175 (585 families) African American (AA) individuals from COGA. In the EA GWAS, three loci were genome-wide significant: rs1229984 in ADH1B for AD criterion count (p=4.16E-11) and Desire to cut drinking (p=1.21E-11); rs188227250 (chromosome 8, Drinking more than intended, p=6.72E-09); rs1912461 (chromosome 15, Time spent drinking, p=1.77E-08). In the trans-ancestral meta-analysis, rs1229984 was associated with multiple phenotypes and two additional loci were genome-wide significant: rs61826952 (chromosome 1, DSM-IV AD, p=8.42E-11); rs7597960 (chromosome 2, Time spent drinking, p=1.22E-08). Associations with rs1229984 and rs18822750 were replicated in independent datasets. Polygenic risk scores derived from the EA GWAS of AD predicted AD in two EA datasets (p<0.01; 0.61-1.82% of variance). Identified novel variants (i.e., rs1912461, rs61826952) were associated with differential central evoked theta power (loss minus gain; p=0.0037) and reward-related ventral striatum reactivity (p=0.008), respectively. This study suggests that studying individual criteria may unveil new insights into the genetic etiology of AD liability.
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    Genome-wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward-related ventral striatum activity in African- and European-Americans
    (Wiley, 2019-05-19) Wetherill, Leah; Lai, Dongbing; Johnson, Emma C.; Anokhin, Andrey; Bauer, Lance; Bucholz, Kathleen K.; Dick, Danielle M.; Hariri, Ahmad R.; Hesselbrock, Victor; Kamarajan, Chella; Kramer, John; Kuperman, Samuel; Meyers, Jacquelyn L.; Nurnberger, John I.; Schuckit, Marc; Scott, Denise M.; Taylor, Robert E.; Tischfield, Jay; Porjesz, Bernice; Goate, Alison M.; Edenberg, Howard J.; Foroud, Tatiana; Bogdan, Ryan; Agrawal, Arpana; Medical and Molecular Genetics, School of Medicine
    Genetic influences on alcohol and drug dependence partially overlap, however specific loci underlying this overlap remain unclear. We conducted a genome-wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7,291 European-Americans (EA; 2,927 cases) and 3,132 African-Americans (AA: 1,315 cases) participating in the family-based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h2 in EA=0.60, AA=0.37). The AA GWAS identified 3 regions with genome-wide significant (GWS; p<5E-08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion-deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans-ancestral meta-analysis (EA+AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and 4 sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward-related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non-European samples with distinct patterns of substance use may lead to the identification of novel ancestry-specific genetic markers of risk.
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    A large-scale genome-wide association study meta-analysis of cannabis use disorder
    (Elsevier, 2020-12) Johnson, Emma C.; Demontis, Ditte; Thorgeirsson, Thorgeir E.; Walters, Raymond K.; Polimanti, Renato; Hatoum, Alexander S.; Sanchez-Roige, Sandra; Paul, Sarah E.; Wendt, Frank R.; Clarke, Toni-Kim; Lai, Dongbing; Reginsson, Gunnar W.; Zhou, Hang; He, June; Baranger, David A.A.; Gudbjartsson, Daniel F.; Wedow, Robbee; Adkins, Daniel E.; Adkins, Amy E.; Alexander, Jeffry; Bacanu, Silviu-Alin; Bigdeli, Tim B.; Boden, Joseph; Brown, Sandra A.; Bucholz, Kathleen K.; Bybjerg-Grauholm, Jonas; Corley, Robin P.; Degenhardt, Louisa; Dick, Danielle M.; Domingue, Benjamin W.; Fox, Louis; Goate, Alison M.; Gordon, Scott D.; Hack, Laura M.; Hancock, Dana B.; Hartz, Sarah M.; Hickie, Ian B.; Hougaard, David M.; Krauter, Kenneth; Lind, Penelope A.; McClintick, Jeanette N.; McQueen, Matthew B.; Meyers, Jacquelyn L.; Montgomery, Grant W.; Mors, Ole; Mortensen, Preben B.; Nordentoft, Merete; Pearson, John F.; Peterson, Roseann E.; Reynolds, Maureen D.; Rice, John P.; Runarsdottir, Valgerdur; Saccone, Nancy L.; Sherva, Richard; Silberg, Judy L.; Tarter, Ralph E.; Tyrfingsson, Thorarinn; Wall, Tamara L.; Webb, Bradley T.; Werge, Thomas; Wetherill, Leah; Wright, Margaret J.; Zellers, Stephanie; Adams, Mark J.; Bierut, Laura J.; Boardman, Jason D.; Copeland, William E.; Farrer, Lindsay A.; Foroud, Tatiana M.; Gillespie, Nathan A.; Grucza, Richard A.; Mullan Harris, Kathleen; Heath, Andrew C.; Hesselbrock, Victor; Hewitt, John K.; Hopfer, Christian J.; Horwood, John; Iacono, William G.; Johnson, Eric O.; Kendler, Kenneth S.; Kennedy, Martin A.; Kranzler, Henry R.; Madden, Pamela A.F.; Maes, Hermine H.; Maher, Brion S.; Martin, Nicholas G.; McGue, Matthew; McIntosh, Andrew M.; Medland, Sarah E.; Nelson, Elliot C.; Porjesz, Bernice; Riley, Brien P.; Stallings, Michael C.; Vanyukov, Michael M.; Vrieze, Scott; Davis, Lea K.; Bogdan, Ryan; Gelernter, Joel; Edenberg, Howard J.; Stefansson, Kari; Børglum, Anders D.; Agrawal, Arpana; Medical and Molecular Genetics, School of Medicine
    Background: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder. Methods: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations. Findings: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia. Interpretation: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.
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    Multi-omics cannot replace sample size in genome-wide association studies
    (Wiley, 2023) Baranger, David A. A.; Hatoum, Alexander S.; Polimanti, Renato; Gelernter, Joel; Edenberg, Howard J.; Bogdan, Ryan; Agrawal, Arpana; Biochemistry and Molecular Biology, School of Medicine
    The integration of multi-omics information (e.g., epigenetics and transcriptomics) can be useful for interpreting findings from genome-wide association studies (GWAS). It has been suggested that multi-omics could circumvent or greatly reduce the need to increase GWAS sample sizes for novel variant discovery. We tested whether incorporating multi-omics information in earlier and smaller-sized GWAS boosts true-positive discovery of genes that were later revealed by larger GWAS of the same/similar traits. We applied 10 different analytic approaches to integrating multi-omics data from 12 sources (e.g., Genotype-Tissue Expression project) to test whether earlier and smaller GWAS of 4 brain-related traits (alcohol use disorder/problematic alcohol use, major depression/depression, schizophrenia, and intracranial volume/brain volume) could detect genes that were revealed by a later and larger GWAS. Multi-omics data did not reliably identify novel genes in earlier less-powered GWAS (PPV <0.2; 80% false-positive associations). Machine learning predictions marginally increased the number of identified novel genes, correctly identifying 1-8 additional genes, but only for well-powered early GWAS of highly heritable traits (i.e., intracranial volume and schizophrenia). Although multi-omics, particularly positional mapping (i.e., fastBAT, MAGMA, and H-MAGMA), can help to prioritize genes within genome-wide significant loci (PPVs = 0.5-1.0) and translate them into information about disease biology, it does not reliably increase novel gene discovery in brain-related GWAS. To increase power for discovery of novel genes and loci, increasing sample size is required.
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    Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders
    (Springer Nature, 2023) Hatoum, Alexander S.; Colbert, Sarah M. C.; Johnson, Emma C.; Huggett, Spencer B.; Deak, Joseph D.; Pathak, Gita; Jennings, Mariela V.; Paul, Sarah E.; Karcher, Nicole R.; Hansen, Isabella; Baranger, David A. A.; Edwards, Alexis; Grotzinger, Andrew; Substance Use Disorder Working Group of the Psychiatric Genomics Consortium; Tucker-Drob, Elliot M.; Kranzler, Henry R.; Davis, Lea K.; Sanchez-Roige, Sandra; Polimanti, Renato; Gelernter, Joel; Edenberg, Howard J.; Bogdan, Ryan; Agrawal, Arpana; Medical and Molecular Genetics, School of Medicine
    Genetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci for published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder, and opioid use disorder in a sample of 1,025,550 individuals of European descent and 92,630 individuals of African descent. Nineteen independent SNPs were genome-wide significant (P < 5e-8) for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries, PDE4B was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets
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    The addiction risk factor: A unitary genetic vulnerability characterizes substance use disorders and their associations with common correlates
    (Springer Nature, 2022) Hatoum, Alexander S.; Johnson, Emma C.; Colbert, Sarah M. C.; Polimanti, Renato; Zhou, Hang; Walters, Raymond K.; Gelernter, Joel; Edenberg, Howard J.; Bogdan, Ryan; Agrawal, Arpana; Medical and Molecular Genetics, School of Medicine
    Substance use disorders commonly co-occur with one another and with other psychiatric disorders. They share common features including high impulsivity, negative affect, and lower executive function. We tested whether a common genetic factor undergirds liability to problematic alcohol use (PAU), problematic tobacco use (PTU), cannabis use disorder (CUD), and opioid use disorder (OUD) by applying genomic structural equation modeling to genome-wide association study summary statistics for individuals of European ancestry (Total N = 1,019,521; substance-specific Ns range: 82,707–435,563) while adjusting for the genetics of substance use (Ns = 184,765−632,802). We also tested whether shared liability across SUDs is associated with behavioral constructs (risk-taking, executive function, neuroticism; Ns = 328,339−427,037) and non-substance use psychopathology (psychotic, compulsive, and early neurodevelopmental disorders). Shared genetic liability to PAU, PTU, CUD, and OUD was characterized by a unidimensional addiction risk factor (termed The Addiction-Risk-Factor, independent of substance use. OUD and CUD demonstrated the largest loadings, while problematic tobacco use showed the lowest loading. The Addiction-Risk-Factor was associated with risk-taking, neuroticism, executive function, and non-substance psychopathology, but retained specific variance before and after accounting for the genetics of substance use. Thus, a common genetic factor partly explains susceptibility for alcohol, tobacco, cannabis, and opioid use disorder. The Addiction-Risk-Factor has a unique genetic architecture that is not shared with normative substance use or non-substance psychopathology, suggesting that addiction is not the linear combination of substance use and psychopathology.