Stigmata that are desired: Contradictions in addiction.

Many experts in the etiology, assessment, and treatment of substance use/addiction view stigma and stigmatization - negatively branding addiction and substance users - as obstacles to the solution of the substance misuse problem. Discussions on this topic impact research and policy, and result in oft-repeated calls to remove the stigma from substance use and users. The goal of the article is to analyze the stigmatization concept as applied to substance use/addiction. It is widely accepted in the literature that stigmatization negatively affects substance users because addiction stigma interferes in both seeking and receiving professional care. It is argued that the societal disapproval of substance use/addiction is inappropriate because it is a mental disorder, involving biological processes. Nonetheless, neither those processes nor negative attitudes to substance use affirm the concept of stigmatization as currently applied. This concept conflates potential mistreatment and malpractice with the prosocial justified societal disapproval of a lethally dangerous behavior. Consequently, the stigmatization concept suffers from internal contradictions, is either misleading or redundant, and may do more harm than the supposed mistreatment of substance users that stigmatization connotes. On the contrary, the justified disapproval of harmful behavior may be a factor raising individual resistance to substance use. Instead of mitigating the effects of that disapproval, it may need to be capitalized on. If it is employed explicitly, conscientiously, and professionally, its internalization may be one of the resistance mechanisms needed to achieve any progress in the still elusive prevention of substance use and addiction.

Transdiagnostic risk of mental disorders in offspring of affected parents: a meta-analysis of family high-risk and registry studies.

The offspring of parents with mental disorders are at increased risk for developing mental disorders themselves. The risk to offspring may extend transdiagnostically to disorders other than those present in the parents. The literature on this topic is vast but mixed. To inform targeted prevention and genetic counseling, we performed a comprehensive, PRISMA 2020-compliant meta-analysis. We systematically searched the literature published up to September 2022 to retrieve original family high-risk and registry studies reporting on the risk of mental disorders in offspring of parents with any type of mental disorder. We performed random-effects meta-analyses of the relative risk (risk ratio, RR) and absolute risk (lifetime, up to the age at assessment) of mental disorders, defined according to the ICD or DSM. Cumulative incidence by offspring age was determined using meta-analytic Kaplan-Meier curves. We measured heterogeneity with the I2 statistic, and risk of bias with the Quality In Prognosis Studies (QUIPS) tool. Sensitivity analyses addressed the impact of study design (family high-risk vs. registry) and specific vs. transdiagnostic risks. Transdiagnosticity was appraised with the TRANSD criteria. We identified 211 independent studies that reported data on 3,172,115 offspring of parents with psychotic, bipolar, depressive, disruptive, attention-deficit/hyperactivity, anxiety, substance use, eating, obsessive-compulsive, and borderline personality disorders, and 20,428,575 control offspring. The RR and lifetime risk of developing any mental disorder were 3.0 and 55% in offspring of parents with anxiety disorders; 2.6 and 17% in offspring of those with psychosis; 2.1 and 55% in offspring of those with bipolar disorder; 1.9 and 51% in offspring of those with depressive disorders; and 1.5 and 38% in offspring of those with substance use disorders. The offspring's RR and lifetime risk of developing the same mental disorder diagnosed in their parent were 8.4 and 32% for attention-deficit/hyperactivity disorder; 5.8 and 8% for psychosis; 5.1 and 5% for bipolar disorder; 2.8 and 9% for substance use disorders; 2.3 and 14% for depressive disorders; 2.3 and 1% for eating disorders; and 2.2 and 31% for anxiety disorders. There were 37 significant transdiagnostic associations between parental mental disorders and the RR of developing a different mental disorder in the offspring. In offspring of parents with psychosis, bipolar and depressive disorder, the risk of the same disorder onset emerged at 16, 5 and 6 years, and cumulated to 3%, 19% and 24% by age 18; and to 8%, 36% and 46% by age 28. Heterogeneity ranged from 0 to 0.98, and 96% of studies were at high risk of bias. Sensitivity analyses restricted to prospective family high-risk studies confirmed the pattern of findings with similar RR, but with greater absolute risks compared to analyses of all study types. This study demonstrates at a global, meta-analytic level that offspring of affected parents have strongly elevated RR and lifetime risk of developing any mental disorder as well as the same mental disorder diagnosed in the parent. The transdiagnostic risks suggest that offspring of parents with a range of mental disorders should be considered as candidates for targeted primary prevention.

Normalization of Prevention Principles and Practices to Reduce Substance Use Disorders Through an Integrated Dissemination and Implementation Framework.

Major research breakthroughs over the past 30 years in the field of substance use prevention have served to: (1) enhance understanding of pharmacological effects on the central and peripheral nervous systems and the health and social consequences of use of psychoactive substances, particularly for children and adolescents; (2) delineate the processes that increase vulnerability to or protect from initiation of substance use and progression to substance use disorders (SUDs) and, based on this understanding, (3) develop effective strategies and practices to prevent the initiation and escalation of substance use. The challenge we now face as a field is to "normalize" what we have learned from this research so that it is incorporated into the work of those involved in supporting, planning, and delivering prevention programming to populations around the world, is integrated into health and social service systems, and helps to shape public policies. But we wish to go further, to incorporate these effective prevention practices into everyday life and the mind-sets of the public, particularly parents and educators. This paper reviews the advances that have been made in the field of prevention and presents a framework and recommendations to achieve these objectives generated during several meetings of prevention and implementation science researchers sponsored by the International Consortium of Universities for Drug Demand Reduction (ICUDDR) that guides a roadmap to achieve "normalization."

The Concept of Resistance to Substance Use and a Research Approach: The Resist! Project.

Illicit substance use is dangerous in both acute and chronic forms, frequently resulting in lethal poisoning, addiction, and other negative consequences. Similar to research in other psychiatric conditions, whose ultimate goal is to enable effective prevention and treatment, studies in substance use are focused on factors elevating the risk for the disorder. The rapid growth of the substance use problem despite the effort invested in fighting it, however, suggests the need in changing the research approach. Instead of attempting to identify risk factors, whose neutralization is often infeasible if not impossible, it may be more promising to systematically reverse the perspective to the factors enhancing the aspect of liability to disorder that shares the same dimension but is opposite to risk, that is, resistance to substance use. Resistance factors, which enable the majority of the population to remain unaffected despite the ubiquity of psychoactive substances, may be more amenable to translation. While the resistance aspect of liability is symmetric to risk, the resistance approach requires substantial changes in sampling (high-resistance rather than high-risk) and using quantitative indices of liability. This article provides an overview and a practical approach to research in resistance to substance use/addiction, currently implemented in a NIH-funded project. The project benefits from unique opportunities afforded by the data originating from two longitudinal twin studies, the Virginia Twin Study of Adolescent and Behavioral Development and the Minnesota Twin Family Study. The methodology described is also applicable to other psychiatric disorders.

Physical inactivity during adolescence heightens risk for cannabis use disorder in adulthood.

The association between physical inactivity and substance use throughout adolescence was prospectively investigated in relation to developing cannabis use disorder (CUD). Physical inactivity and substance use in males (N = 462) and females (N = 178) were measured at 12-14, 16, 19, and 22 years of age in a repeated measures design. A structured diagnostic interview was administered to formulate current CUD diagnosis at 22 years of age. Mixture modeling path analysis evaluated the association between physical inactivity, substance use, and CUD. Males: Slope of physical inactivity increase spanning 12-22 years of age mediates the association between number of parents with substance use disorder (SUD) and rate of increase in substance use frequency (prodrome) which mediates the association between physical inactivity (hypothesized vulnerability) and CUD. Females: Number of SUD parents predicts slope of physical inactivity increase in daughters throughout adolescence which covaries with slope of increasing substance use frequency culminating in CUD. The association between parental SUD load (number of SUD affected parents) and CUD was found to not be mediated by physical inactivity. Rate of increase in physical inactivity during adolescence in males and females is a facet of the vulnerability for CUD. These results have ramifications for prevention considering that numerous cognitive, behavior, and emotion features of CUD vulnerability are attenuated by exercise. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Gateway That Never Was.

This brief communication responds to the article by Rajabi et al., recently published in Behavior Genetics. To test the hypothesis of cigarette smoking as a "gateway" for subsequent opium use and contrast it with the common liability model, Mendelian randomization analysis was applied to data obtained from an Iranian sample, using CHRNA3 rs1051730 as an instrumental variable. It is doubtful, however, if the assumptions of instrumental variable analysis hold in this case. The authors misstate both the gateway hypothesis and the common liability model. The article has many other deficiencies that diminish the veracity of its categorical conclusions that accept the causal interpretation of the "gateway hypothesis" and reject the common liability model, with which the data are fully consistent.

Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets.

BACKGROUND: In the last decade, Genome-wide Association studies (GWASs) have contributed to decoding the human genome by uncovering many genetic variations associated with various diseases. Many follow-up investigations involve joint analysis of multiple independently generated GWAS data sets. While most of the computational approaches developed for joint analysis are based on summary statistics, the joint analysis based on individual-level data with consideration of confounding factors remains to be a challenge. RESULTS: In this study, we propose a method, called Coupled Mixed Model (CMM), that enables a joint GWAS analysis on two independently collected sets of GWAS data with different phenotypes. The CMM method does not require the data sets to have the same phenotypes as it aims to infer the unknown phenotypes using a set of multivariate sparse mixed models. Moreover, CMM addresses the confounding variables due to population stratification, family structures, and cryptic relatedness, as well as those arising during data collection such as batch effects that frequently appear in joint genetic studies. We evaluate the performance of CMM using simulation experiments. In real data analysis, we illustrate the utility of CMM by an application to evaluating common genetic associations for Alzheimer's disease and substance use disorder using datasets independently collected for the two complex human disorders. Comparison of the results with those from previous experiments and analyses supports the utility of our method and provides new insights into the diseases. The software is available at https://github.com/HaohanWang/CMM .

Forecasting Opioid Use Disorder at 25 Years of Age in 16-Year-Old Adolescents.

OBJECTIVE: To evaluate the accuracy of detecting 16-year-old male (n = 465) and female (n = 162) youths who subsequently manifest opioid use disorder (OUD) at 25 years of age. We hypothesized that the combined measures of 2 components of etiology, heritable risk, and substance use, accurately detect youths who develop OUD. STUDY DESIGN: Heritable risk was measured by the transmissible liability index (TLI). Severity of the prodrome presaging OUD was quantified by the revised Drug Use Screening Inventory containing the consumption frequency index (CFI) documenting substance use events during the past month and the overall problem density (OPD) score indicating co-occurring biopsychosocial problems. Diagnosis of OUD was formulated by a clinical committee based on results of the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition in conjunction with medical and social history records. RESULTS: Bivariate analysis shows that the TLI, CFI, and OPD scores at 16 years of age predict OUD at 25 years. Multivariate modeling indicates that the TLI combined with the CFI predict OUD with 86% accuracy (sensitivity = 87%; specificity = 62%). The TLI and CFI at 16 years of age mediate the association between parental substance use disorder and OUD in offspring at 25 years of age, indicating that these measures respectively evaluate risk and prodrome. CONCLUSIONS: These results demonstrate the feasibility of identifying youths requiring intervention to prevent OUD.

Discovering weaker genetic associations guided by known associations.

BACKGROUND: The current understanding of the genetic basis of complex human diseases is that they are caused and affected by many common and rare genetic variants. A considerable number of the disease-associated variants have been identified by Genome Wide Association Studies, however, they can explain only a small proportion of heritability. One of the possible reasons for the missing heritability is that many undiscovered disease-causing variants are weakly associated with the disease. This can pose serious challenges to many statistical methods, which seems to be only capable of identifying disease-associated variants with relatively stronger coefficients. RESULTS: In order to help identify weaker variants, we propose a novel statistical method, Constrained Sparse multi-locus Linear Mixed Model (CS-LMM) that aims to uncover genetic variants of weaker associations by incorporating known associations as a prior knowledge in the model. Moreover, CS-LMM accounts for polygenic effects as well as corrects for complex relatednesses. Our simulation experiments show that CS-LMM outperforms other competing existing methods in various settings when the combinations of MAFs and coefficients reflect different scenarios in complex human diseases. CONCLUSIONS: We also apply our method to the GWAS data of alcoholism and Alzheimer's disease and exploratively discover several SNPs. Many of these discoveries are supported through literature survey. Furthermore, our association results strengthen the belief in genetic links between alcoholism and Alzheimer's disease.

Derivation and assessment of the opioid use disorder severity scale: prediction of health, psychological and social adjustment problems.

Background: Severity of substance use disorder (SUD) is typically evaluated by tabulating the number of symptoms. The resulting estimate of disorder severity is, however, biased due to intercorrelations among symptoms and their unequal salience. Objective. Employing item response theory (IRT) methodology, opioid use disorder symptoms were calibrated to derive the Opioid Use Disorder Severity Scale (OUDSS) and assess its predictive ability in men and women separately. Methods: A two-parameter IRT model was utilized to derive the OUDSS from DSM-IV symptoms recorded on the Structured Clinical Interview for DSM-IV (SCID) in 438 men and 429 women who reported at least one lifetime opioid consumption event. The predictive ability of the OUDSS was evaluated using the 10 health, psychological, and social adjustment domains of the revised Drug Use Screening Inventory (DUSI-R) assessed 2 years later. Results: The OUDSS score predicted the severity of problems in all 10 DUSI-R domains in men and women. The OUDSS also predicted the DUSI-R diagnostic cutoff score of overall problem density score in men and women (OR = 2.21 and OR = 4.83, respectively). Withdrawal was the most frequently endorsed symptom in this sample of opioid users. The other symptoms' frequencies, while somewhat lower than withdrawal's, did not differ from it substantially, indicating a similar severity threshold. Conclusions: OUDSS enables dimensional measurement of opioid use severity on an interval scale. The OUDSS and DUSI-R together can identify problem areas requiring prevention or treatment.

Genome-Wide Meta-Analyses of FTND and TTFC Phenotypes.

INTRODUCTION: FTND (FagerstrÓ§m test for nicotine dependence) and TTFC (time to smoke first cigarette in the morning) are common measures of nicotine dependence (ND). However, genome-wide meta-analysis for these phenotypes has not been reported. METHODS: Genome-wide meta-analyses for FTND (N = 19,431) and TTFC (N = 18,567) phenotypes were conducted for adult smokers of European ancestry from 14 independent cohorts. RESULTS: We found that SORBS2 on 4q35 (p = 4.05 × 10-8), BG182718 on 11q22 (p = 1.02 × 10-8), and AA333164 on 14q21 (p = 4.11 × 10-9) were associated with TTFC phenotype. We attempted replication of leading candidates with independent samples (FTND, N = 7010 and TTFC, N = 10 061), however, due to limited power of the replication samples, the replication of these new loci did not reach significance. In gene-based analyses, COPB2 was found associated with FTND phenotype, and TFCP2L1, RELN, and INO80C were associated with TTFC phenotype. In pathway and network analyses, we found that the interconnected interactions among the endocytosis, regulation of actin cytoskeleton, axon guidance, MAPK signaling, and chemokine signaling pathways were involved in ND. CONCLUSIONS: Our analyses identified several promising candidates for both FTND and TTFC phenotypes, and further verification of these candidates was necessary. Candidates supported by both FTND and TTFC (CHRNA4, THSD7B, RBFOX1, and ZNF804A) were associated with addiction to alcohol, cocaine, and heroin, and were associated with autism and schizophrenia. We also identified novel pathways involved in cigarette smoking. The pathway interactions highlighted the importance of receptor recycling and internalization in ND. IMPLICATIONS: Understanding the genetic architecture of cigarette smoking and ND is critical to develop effective prevention and treatment. Our study identified novel candidates and biological pathways involved in FTND and TTFC phenotypes, and this will facilitate further investigation of these candidates and pathways.

Analysis of substance use and its outcomes by machine learning I. Childhood evaluation of liability to substance use disorder.

BACKGROUND: Substance use disorder (SUD) exacts enormous societal costs in the United States, and it is important to detect high-risk youths for prevention. Machine learning (ML) is the method to find patterns and make prediction from data. We hypothesized that ML identifies the health, psychological, psychiatric, and contextual features to predict SUD, and the identified features predict high-risk individuals to develop SUD. METHOD: Male (N = 494) and female (N = 206) participants and their informant parents were administered a battery of questionnaires across five waves of assessment conducted at 10-12, 12-14, 16, 19, and 22 years of age. Characteristics most strongly associated with SUD were identified using the random forest (RF)algorithm from approximately 1000 variables measured at each assessment. Next, the complement of features was validated, and the best models were selected for predicting SUD using seven ML algorithms. Lastly, area under the receiver operating characteristic curve (AUROC) evaluated accuracy of detecting individuals who develop SUD+/- up to thirty years of age. RESULTS: Approximately thirty variables strongly predict SUD. The predictors shift from psychological dysregulation and poor health behavior in late childhood to non-normative socialization in mid to late adolescence. In 10-12-year-old youths, the features predict SUD+/- with 74% accuracy, increasing to 86% at 22 years of age. The RF algorithm optimally detects individuals between 10-22 years of age who develop SUD compared to other ML algorithms. CONCLUSION: These findings inform the items required for inclusion in instruments to accurately identify high risk youths and young adults requiring SUD prevention.

Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity.

BACKGROUND: This longitudinal study explored the utility of machine learning (ML) methodology in predicting the trajectory of severity of substance use from childhood to thirty years of age using a set of psychological and health characteristics. DESIGN: Boys (N = 494) and girls (N = 206) were recruited using a high-risk paradigm at 10-12 years of age and followed up at 12-14, 16, 19, 22, 25 and 30 years of age. MEASUREMENTS: At each visit, the subjects were administered a comprehensive battery to measure psychological makeup, health status, substance use and psychiatric disorder, and their overall harmfulness of substance consumption was quantified according to the multidimensional criteria (physical, dependence, and social) developed by Nutt et al. (2007). Next, high- and low- substance use severity trajectories were derived differentially associated with probability of segueing to substance use disorder (SUD). ML methodology was employed to predict trajectory membership. FINDINGS: The high-severity trajectory group had a higher probability of leading to SUD than the low-severity trajectory (89.0% vs 32.4%; odds ratio = 16.88, p < 0.0001). Thirty psychological and health status items at each of the six visits predict membership in the high- or low-severity trajectory, with 71% accuracy at 10-12 years of age, increasing to 93% at 22 years of age. CONCLUSION: These findings demonstrate the applicability of the machine learning methodology for detecting membership in a substance use trajectory with high probability of culminating in SUD, potentially informing primary and secondary prevention.

Association of cognitive function and liability to addiction with childhood herpesvirus infections: A prospective cohort study.

Liability to substance use disorder (SUD) is largely nonspecific to particular drugs and is related to behavior dysregulation, including reduced cognitive control. Recent data suggest that cognitive mechanisms may be influenced by exposure to neurotropic infections, such as human herpesviruses. In this study, serological evidence of exposure to human herpesvirus Herpes simplex virus Type 1 (HSV-1), cytomegalovirus (CMV), and Epstein-Barr virus (EBV) as well as Toxoplasma gondii was determined in childhood (age ~11 years) in 395 sons and 174 daughters of fathers with or without SUD. Its relationships with a cognitive characteristic (IQ) in childhood and with risk for SUD in adulthood were examined using correlation, regression, survival, and path analyses. Exposure to HSV-1, EBV, and T. gondii in males and females, and CMV in males, was associated with lower IQ. Independent of that relationship, EBV in females and possibly in males, and CMV and possibly HSV-1 in females were associated with elevated risk for SUD. Therefore, childhood neurotropic infections may influence cognitive development and risk for behavior disorders such as SUD. The results may point to new avenues for alleviating cognitive impairment and SUD risk.

Informing Prevention and Intervention Policy Using Genetic Studies of Resistance.

The common paradigm for conceptualizing the influence of genetic and environmental factors on a particular disease relies on the concept of risk. Consequently, the bulk of etiologic, including genetic, work focuses on "risk" factors. These factors are aggregated at the high end of the distribution of liability to disease, the latent variable underlying the distribution of probability and severity of a disorder. However, liability has a symmetric but distinct aspect to risk, resistance to disorder. Resistance factors, aggregated at the low end of the liability distribution and supporting health and recovery, appear to be more promising for effective prevention and intervention. Herein, we discuss existing work on resistance factors, highlighting those with known genetic influences. We examine the utility of incorporating resistance genetics in prevention and intervention trials and compare the statistical power of a series of ascertainment schemes to develop a general framework for examining resistance outcomes in genetically informative designs. We find that an approach that samples individuals discordant on measured liability, a low-risk design, is the most feasible design and yields power equivalent to or higher than commonly used designs for detecting resistance genetic and environmental effects.

Variants on chromosome 4q21 near PKD2 and SIBLINGs are associated with dental caries.

A recent genome-wide association study (GWAS) for dental caries nominated the chromosomal region 4q21 near ABCG2, PKD2 and the SIBLING (small integrin-binding ligand N-linked glycoprotein) gene family. In this investigation, we followed up and fine-mapped this region using a tag-SNP (single-nucleotide polymorphism) approach in 13 age- and race-stratified samples from 6 independent studies (N=4089). Participants were assessed for dental caries via intraoral examination and 49 tag-SNPs were genotyped capturing much of the variation in the 4q21 locus. Linear models were used to test for genetic association, while adjusting for sex, age and components of ancestry. SNPs in and near PKD2 showed significant evidence of association in individual samples of black adults (rs17013735, P-value=0.0009) and white adults (rs11938025; P-value=0.0005; rs2725270, P-value=0.003). Meta-analyses across black adult samples recapitulated the association with rs17013735 (P-value=0.003), which occurs at low frequency in non-African populations, possibly explaining the race specificity of the effect. In addition to race-specific associations, we also observed evidence of gene-by-fluoride exposure interaction effects in white adults for SNP rs2725233 upstream of PKD2 (P=0.002). Our results show evidence of regional replication, though no single variant clearly accounted for the original GWAS signal. Therefore, while we interpret our results as strengthening the hypothesis that chromosome 4q21 may impact dental caries, additional work is needed.

Risk and resistance perspectives in translation-oriented etiology research.

Risk for a disorder and the mechanisms that determine its elevation, risk factors, are the focus of medical research. Targeting risk factors should serve the goal of prevention and treatment intervention. Risk, however, is but one of the aspects of liability to a disorder, a latent trait that encompasses effects of all factors leading to or from the diagnostic threshold. The coequal but opposite aspect of liability is resistance to a disorder. The factors that increase resistance and thus enable prevention or recovery may differ from those that elevate risk. Accordingly, there are nontrivial differences between research perspectives that focus on risk and on resistance. This article shows how this distinction translates into goals and methods of research and practice, from the choice of potential mechanisms tested to the results sought in intervention. The resistance concept also differs from those of "resilience" and "protective factors," subsuming but not limited to them. The implications of the concept are discussed using substance use disorder as an example and substantiate the need for biomedical research and its translation to shift to the resistance perspective.