Genetic contribution to the comorbidity between attention-deficit/hyperactivity disorder and substance use disorders.

We characterized the genetic architecture of the attention-deficit hyperactivity disorder-substance use disorder (ADHD-SUD) relationship by investigating genetic correlation, causality, pleiotropy, and common polygenic risk. Summary statistics from genome-wide association studies (GWAS) were used to investigate ADHD (Neff = 51,568), cannabis use disorder (CanUD, Neff = 161,053), opioid use disorder (OUD, Neff = 57,120), problematic alcohol use (PAU, Neff = 502,272), and problematic tobacco use (PTU, Neff = 97,836). ADHD, CanUD, and OUD GWAS meta-analyses included cohorts with case definitions based on different diagnostic criteria. PAU GWAS combined information related to alcohol use disorder, alcohol dependence, and the items related to alcohol problematic consequences assessed by the alcohol use disorders identification test. PTU GWAS was generated a multi-trait analysis including information regarding Fagerström Test for Nicotine Dependence and cigarettes per day. Linkage disequilibrium score regression analyses indicated positive genetic correlation with CanUD, OUD, PAU, and PTU. Genomic structural equation modeling showed that these genetic correlations were related to two latent factors: one including ADHD, CanUD, and PTU and the other with OUD and PAU. The evidence of a causal effect of PAU and PTU on ADHD was stronger than the reverse in the two-sample Mendelian randomization analysis. Conversely, similar strength of evidence was found between ADHD and CanUD. CADM2 rs62250713 was a pleiotropic SNP between ADHD and all SUDs. We found seven, one, and twenty-eight pleiotropic variants between ADHD and CanUD, PAU, and PTU, respectively. Finally, OUD, CanUD, and PAU PRS were associated with increased odds of ADHD. Our findings demonstrated the contribution of multiple pleiotropic mechanisms to the comorbidity between ADHD and SUDs.

Pleiotropy and genetically inferred causality linking multisite chronic pain to substance use disorders.

Individuals suffering from chronic pain develop substance use disorders (SUDs) more often than others. Understanding the shared genetic influences underlying the comorbidity between chronic pain and SUDs will lead to a greater understanding of their biology. Genome-wide association statistics were obtained from the UK Biobank for multisite chronic pain (MCP, Neffective = 387,649) and from the Million Veteran Program and the Psychiatric Genomics Consortium meta-analyses for alcohol use disorder (AUD, Neffective = 296,974), cannabis use disorder (CanUD, Neffective = 161,053), opioid use disorder (OUD, Neffective = 57,120), and problematic tobacco use (PTU, Neffective = 270,120). SNP-based heritability was estimated for each of the traits and genetic correlation (rg) analyses were performed to assess MCP-SUD pleiotropy. Bidirectional Mendelian Randomization analyses evaluated possible causal relationships. Finally, to identify and characterize individual loci, we performed a genome-wide pleiotropy analysis and a brain-wide analysis using imaging phenotypes available from the UK Biobank. MCP was positively genetically correlated with AUD (rg = 0.26, p = 7.55 × 10-18), CanUD (rg = 0.37, p = 8.21 × 10-37), OUD (rg = 0.20, p = 1.50 × 10-3), and PTU (rg = 0.29, p = 8.53 × 10-12). Although the MR analyses supported bi-directional relationships, MCP had larger effects on AUD (pain-exposure: beta = 0.18, p = 8.21 × 10-4; pain-outcome: beta = 0.07, p = 0.018), CanUD (pain-exposure: beta = 0.58, p = 2.70 × 10-6; pain-outcome: beta = 0.05, p = 0.014) and PTU (pain-exposure: beta = 0.43, p = 4.16 × 10-8; pain-outcome: beta = 0.09, p = 3.05 × 10-6) than the reverse. The genome-wide analysis identified two SNPs pleiotropic between MCP and all SUD investigated: IHO1 rs7652746 (ppleiotropy = 2.69 × 10-8), and CADM2 rs1248857 (ppleiotropy = 1.98 × 10-5). In the brain-wide analysis, rs7652746 was associated with multiple cerebellum and amygdala imaging phenotypes. When analyzing MCP pleiotropy with each SUD separately, we found 25, 22, and 4 pleiotropic variants for AUD, CanUD, and OUD, respectively. To our knowledge, this is the first large-scale study to provide evidence of potential causal relationships and shared genetic mechanisms underlying MCP-SUD comorbidity.

Functional correlates of a novel 8-factor model of PTSD in U.S. military veterans: Results from the National Health and Resilience in Veterans Study.

Emerging evidence indicates that more nuanced models of posttraumatic stress disorder (PTSD) may better capture the condition's symptom structure. Recent theoretical and empirical work suggest that an 8-factor model of PTSD with separate internally- (e.g. flashbacks) and externally- (e.g. trauma-cue related physiological reactivity) generated intrusive symptom clusters may advance understanding of PTSD and its treatment and course. However, the model's functional and clinical significance still requires evaluation. To this end, we analyzed data from the National Health and Resilience in Veterans Study, a nationally representative sample of 3847 trauma-exposed U.S. military veterans. Multivariable regressions were performed to assess the relationship between the 8 PTSD symptom clusters, assessed using the PTSD Checklist for DSM-5, and clinical and functional measures. Results revealed that externally-generated intrusions were associated with higher odds of current depression and anxiety and worse mental, cognitive, and psychosocial functioning. Anhedonia (e.g., loss of interest in enjoyable activities) symptoms were associated with all the correlates tested, while negative affect (e.g., having strong negative feelings such as fear) symptoms were associated with all measures except depression. Avoidance symptoms were associated with lower odds of current anxiety while externalizing behavior symptoms were linked to higher odds of suicidal ideation. Anxious arousal symptoms were associated with lower odds of suicidal ideation but higher odds of PTSD-related impairment/distress, while dysphoric arousal symptoms were associated with higher odds of current depression, PTSD-related impairment/distress and worse mental and cognitive functioning. Results suggest that a more nuanced 8-factor model of PTSD symptoms may help inform understanding of the clinical and functional correlates of this multi-faceted disorder.

Evaluating a novel 8-factor dimensional model of PTSD in U.S. military veterans: Results from the National Health and Resilience in Veterans Study.

BACKGROUND: Accumulating data suggest that the structure of posttraumatic stress disorder (PTSD) symptoms may be more nuanced than proposed by prevailing nosological models. Emerging theory further suggests that an 8-factor model with separate internally- (e.g., flashbacks) and externally- (e.g., trauma cue-related emotional reactivity) generated intrusive symptoms may best represent PTSD symptoms. To date, however, scarce research has evaluated the fit of this model and whether index traumas are differentially associated with it in populations at high risk for trauma exposure, such as military veterans. METHODS: Data were analyzed from a nationally representative sample of 3847 trauma-exposed U.S. veterans who participated in the National Health and Resilience in Veterans Study. Confirmatory factor analyses were conducted to evaluate the fit of a novel 8-factor model of PTSD symptoms relative to 4-factor DSM-5 and empirically-supported 7-factor hybrid models. RESULTS: The 8-factor model fit the data significantly better than the 7-factor hybrid and 4-factor DSM-5 models. Combat exposure and harming others were more strongly associated with internally-generated intrusions, while interpersonal violence and disaster/accident showed stronger significant associations with externally-generated intrusions. LIMITATIONS: The 8-factor model requires validation in non-veteran and more diverse trauma-exposed populations, as well as with clinician-administered interviews. CONCLUSIONS: Results of this study provide support for a novel 8-factor model of PTSD symptoms that is characterized by separate internally- and externally-generated intrusions. They also suggest that certain index traumas may lead to differential expression of these symptoms.

Association Patterns of Antisocial Personality Disorder across Substance Use Disorders.

There is a high prevalence of antisocial personality disorder (ASPD) in individuals affected by substance use disorders (SUD). However, there is limited information on the specific patterns of association of ASPD with SUD severity and specific SUD diagnostic criteria. We investigated the association of alcohol, cannabis, cocaine, opioid, and tobacco use disorders (AUD, CanUD, CocUD, OUD, and TUD, respectively) in 1,660 individuals with ASPD and 6,640 controls matched by sex (24% female), age, and racial/ethnic background in a sample ascertained for addiction-related traits. Generalized linear regressions were used to test the association of ASPD with the five DSM-5 SUD diagnoses, their severity (i.e., mild, moderate, severe), and their individual diagnostic criteria. We found that ASPD is associated with the diagnosis and severity of AUD (Odds Ratio, ORs=1.89 and 1.25), CanUD (ORs=2.13 and 1.32), and TUD (ORs=1.50 and 1.21) ( ps <.003). Of the specific diagnostic criteria, the "hazardous use" criterion showed the strongest association with ASPD across the five SUDs investigated (from OR TUD =1.88 to OR CanUD =1.37). However, when criteria of different SUDs were included in the same model, ASPD was independently associated only with TUD "hazardous use" and CocUD "attempts to quit". Attempting to quit cocaine was inversely related to the presence of ASPD and remained significant (OR=0.57, 95% confidence interval = 0.36-0.89) after controlling for interactive effects with sex. The current work provides novel insights into how different SUDs, their severity, and their diagnostic criteria associate with ASPD, potentially furthering our understanding of the impact of polysubstance addiction on mental health.

Polysubstance addiction patterns among 7,989 individuals with cocaine use disorder.

To characterize polysubstance addiction (PSA) patterns of cocaine use disorder (CoUD), we performed a latent class analysis (LCA) in 7,989 participants with a lifetime DSM-5 diagnosis of CoUD. This analysis identified three PSA subgroups among CoUD participants (i.e., low, 17%; intermediate, 38%; high, 45%). While these subgroups varied by age, sex, and racial-ethnic distribution (p < 0.001), there was no difference with respect to education or income (p > 0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR = 21.96 vs. 6.39, difference-p = 8.08✕10-6), agoraphobia (OR = 4.58 vs. 2.05, difference-p = 7.04✕10-4), mixed bipolar episode (OR = 10.36 vs. 2.61, difference-p = 7.04✕10-4), posttraumatic stress disorder (OR = 11.54 vs. 5.86, difference-p = 2.67✕10-4), antidepressant medication use (OR = 13.49 vs. 8.02, difference-p = 1.42✕10-4), and sexually transmitted diseases (OR = 5.92 vs. 3.38, difference-p = 1.81✕10-5) than the low-PSA CoUD subgroup. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.

Polysubstance addiction and psychiatric, somatic comorbidities among 7,989 individuals with cocaine use disorder: a latent class analysis.

Aims: We performed a latent class analysis (LCA) in a sample ascertained for addiction phenotypes to investigate cocaine use disorder (CoUD) subgroups related to polysubstance addiction (PSA) patterns and characterized their differences with respect to psychiatric and somatic comorbidities. Design: Cross-sectional study. Setting: United States. Participants: Adult participants aged 18-76, 39% female, 47% African American, 36% European American with a lifetime DSM-5 diagnosis of CoUD (N=7,989) enrolled in the Yale-Penn cohort. The control group included 2,952 Yale-Penn participants who did not meet for alcohol, cannabis, cocaine, opioid, or tobacco use disorders. Measurements: Psychiatric disorders and related traits were assessed via the Semi-structured Assessment for Drug Dependence and Alcoholism. These features included substance use disorders (SUD), family history of substance use, sociodemographic information, traumatic events, suicidal behaviors, psychopathology, and medical history. LCA was conducted using diagnoses and diagnostic criteria of alcohol, cannabis, opioid, and tobacco use disorders. Findings: Our LCA identified three subgroups of PSA (i.e., low, 17%; intermediate, 38%; high, 45%) among 7,989 CoUD participants. While these subgroups varied by age, sex, and racial-ethnic distribution (p<0.001), there was no difference on education or income (p>0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR=21.96 vs. 6.39, difference-p=8.08×10 -6 ), agoraphobia (OR=4.58 vs. 2.05, difference-p=7.04×10 -4 ), mixed bipolar episode (OR=10.36 vs. 2.61, difference-p=7.04×10 -4 ), posttraumatic stress disorder (OR=11.54 vs. 5.86, difference-p=2.67×10 -4 ), antidepressant medication use (OR=13.49 vs. 8.02, difference-p=1.42×10 -4 ), and sexually transmitted diseases (OR=5.92 vs. 3.38, difference-p=1.81×10 -5 ) than the low-PSA CoUD subgroup. Conclusions: We found different patterns of PSA in association with psychiatric and somatic comorbidities among CoUD cases within the Yale-Penn cohort. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.