Background Chronic pain is a public health burden, and opioids remain among the strongest analgesics available. While outpatient prescribing of opioids in the US has declined in the past decade, and most opioid use disorder (OUD) cases now stem from non-prescribed opioids (e.g., fentanyl), the risk of developing opioid dependence remains a concern. Methods To assess the prevalence of co-occurring chronic pain and OUD diagnoses in the All of Us Research Program (AoU) and the role of genetic liability and social determinants of health, we performed cross-sectional analyses on AoU Release 8 data. Findings Of participants with co-occurring chronic pain and OUD diagnoses, the chronic pain diagnosis preceded OUD in 57% of cases, while 43% of cases received an OUD diagnosis at the same time or before the chronic pain diagnosis. Participants whose chronic pain diagnosis came first were less likely to have a PTSD diagnosis and were less likely to report using prescription opioids for non-prescribed purposes, but had a greater number of opioid prescriptions recorded. Relative to a diagnosis of chronic pain alone, co-occurring chronic pain and OUD diagnoses were associated with fewer years of education, lower income, greater likelihood of other psychiatric diagnoses, and higher polygenic scores for chronic pain and OUD. Greater likelihood of an anxiety diagnosis, higher polygenic liability for chronic pain, and lower polygenic liability for OUD were associated with co-occurring diagnoses of chronic pain and OUD compared to only a diagnosis of OUD. Interpretation Our results suggest that socioeconomic hardship and co-occurring mental health conditions are correlates of risk for co-occurring chronic pain and OUD; these areas should be prioritised in future research to improve prevention and treatment outcomes. Funding R03DA059747 (ECJ); Department of Anesthesiology Training Grant R90NR021799 (PNRV, BG, ECJ); K01AA030083 (ASH)

Chronic pain (CP) is common and debilitating, affecting 12-40% of people worldwide. In this study, we conducted a genome-wide association study (GWAS) of CP in the All of Us Research Program across six genetic ancestries (Ntotal = 313 931, Ncase = 64 894, Ncontrol = 249 037). In the cross-ancestral meta-analysis, one locus on chromosome 3 reached genome-wide (GW) significance (α = 5E-08; lead SNP: rs3849410, p = 2.64E-08,). This same lead SNP, rs3849410, also reached GW significance in the European subsample (p = 7.45E-10) and in European females (p = 4.25E-08). Two additional loci, with lead SNPs rs7652179 and rs4760489, reached GW significance (p = 8.57E-09, and 3.07E-08, respectively) in European ancestry. Sex-stratified analyses revealed one locus on chromosome 11 (lead SNP: rs77607049) in males (p = 1.13E-08); in females, two other loci on chromosomes 11 (lead SNP: rs368001205) and 12 were also identified (lead SNP: rs80043169; p = 1.58E-08, 9.14E-09, respectively; p < 2.5E-08). CP was genetically correlated with psychiatric, physical, and immune traits, including anxiety (rg = 0.72, p = 2.00E-46), generalized addiction risk (rg = 0.38, p = 2.08E-17), higher C-reactive protein levels (rg = 0.36, p = 6.38E-22) and greater body mass index (rg = 0.43, p = 8.03E-47). This study represents one of the largest cross-ancestral investigations of the genetics of CP to date and demonstrates shared genetic effects between CP and multiple health conditions. PERSPECTIVE: This article presents multi-ancestral cross-sex and sex-stratified GWAS of chronic pain (CP). One significant cross-ancestral locus and 3 sex-specific loci were identified; a previously published locus for multisite CP met traditional genome-wide significance in the current European ancestry GWAS. This study identifies 4 novel genetic loci associated with CP.

Objective: Though caffeine use during pregnancy is common, its longitudinal associations with child behavioral and physical health outcomes remain poorly understood. Here, we estimated associations between prenatal caffeine exposure, body mass index (BMI), and behavior as children enter adolescence. Method: Longitudinal data and caregiver-reported prenatal caffeine exposure were obtained from the ongoing Adolescent Brain and Cognitive Development (ABCD)(SM) Study, which recruited 11,875 children aged 9-11 years at baseline from 21 sites across the United States starting June 1, 2016. Prenatal caffeine exposure was analyzed as a 4-level categorical variable, and further group contrasts were used to characterize "any exposure" and "daily exposure" groups. Outcomes included psychopathology characteristics in children, sleep problems, and BMI. Potentially confounding covariates included familial (e.g., income, familial psychopathology), pregnancy (e.g., prenatal substance exposure), and child (e.g., caffeine use) variables. Results: Among 10,873 children (5686 boys [52.3 %]; mean [SD] age, 9.9 [0.6] years) with nonmissing prenatal caffeine exposure data, 6560 (60 %) were exposed to caffeine prenatally. Relative to no exposure, daily caffeine exposure was associated with higher child BMI (beta = 0.08; FDR-corrected p = 0.02), but was not associated with child behavior following correction for multiple testing. Those exposed to two or more cups of caffeine daily (n = 1028) had greater sleep problems than those with lower/no exposure (beta > 0.92; FDR-corrected p < 0.04). Conclusion: Daily prenatal caffeine exposure is associated with heightened childhood BMI, and when used multiple times a day greater sleep problems even after accounting for potential confounds. Whether this relationship is a consequence of prenatal caffeine exposure or its correlated factors remains unknown.

INTRODUCTION:Pregnant individuals who smoke face increased health risks because smoking harms both the mother and their developing offspring. AIMS AND METHODS:Using 307 417 Europeans from the UK Biobank, we examined whether exposure to maternal smoking during pregnancy (MSP) interacts with genetic risk to predict offspring birth weight (BW) and smoking behaviors. We investigated interactions between MSP and genetic risk at multiple levels: single variant, gene level, and polygenic score. We examined self-reported BW, smoking initiation status (SI), age of smoking initiation, cigarettes per day, and smoking cessation status. RESULTS:One locus tagged by single-nucleotide polymorphism rs72689499 on chromosome 14 reached significance for interaction with MSP on the multiplicative (log10) scale for BW (p = 5.13 × 10-9). In gene-level testing, three genes on chromosome 1 and one gene on chromosome 14 reached significance for interaction with MSP on both the additive and multiplicative scale for BW. These genes include PTCH2, EIF2B3, PLK3, and TSHR. Single-nucleotide polymorphism and gene-level results were insignificant for all offspring smoking behaviors. We also detected an interaction between polygenic risk for smoking and MSP on SI on both the additive (p = 4.4 × 10-5) and multiplicative (p = 1.0 × 10-5) scale. We found evidence of gene-environment correlation in the polygenic risk analysis using a post hoc t test which showed that MSP-exposed offspring had a higher SI polygenic risk scores than those unexposed to MSP (p = 5.9 × 10-623). CONCLUSIONS:Our results support the main effect of MSP on BW and show a genetic interaction between MSP and genetic factors influencing BW. IMPLICATIONS:We detected interactions between maternal smoking and genetic factors to influence birth weight; these interactions were detectable at both the single-nucleotide polymorphism and gene levels. Many of the genes detected to interact with maternal smoking to influence birth weight have other reported associations with height or smoking-related traits. For smoking initiation, we detected a negative interaction between maternal smoking and polygenic risk, as well as evidence of gene-environment correlation.

Although substance use is associated with a shortened lifespan, impeded health and accelerated biological ageing, the factors contributing to the associations between substance use and ageing are poorly understood. We used summary statistics from genome-wide association studies (GWAS) to investigate whether substance involvement (N from 28K to 2M)-including alcohol, tobacco, cannabis and opioid use and use disorders-is genetically correlated with various ageing metrics (N from 162K to 2.7M) and whether these correlations reflect shared genetic etiologies or putative causal relationships. Using Linkage Disequilibrium Score Regression (LDSC), we found widespread evidence of genetic correlations between substance use/use disorders and indices of physical, cognitive and biological ageing. We then employed a series of Mendelian randomization-based approaches, finding significant causal effects of genetic predispositions to both tobacco use disorder and quantity of tobacco smoked on various markers of ageing. Causal effects of problematic alcohol use and cannabis use disorder were also found, though findings were mixed. Evidence of reverse causality (i.e., ageing causing substance use), meanwhile, was scant. Collectively, these results demonstrate strong triangulation across approaches and highlight the importance of integrating genetic insights into public health strategies for reducing the burden of SUDs across the lifespan.

BACKGROUND:Genetic research on nicotine dependence has utilized multiple assessments that are in weak agreement. METHODS:We conducted a genome-wide association study (GWAS) of nicotine dependence defined using the Diagnostic and Statistical Manual of Mental Disorders (DSM-NicDep) in 61,861 individuals (47,884 of European ancestry [EUR], 10,231 of African ancestry, and 3,746 of East Asian ancestry) and compared the results to other nicotine-related phenotypes. RESULTS:We replicated the well-known association at the CHRNA5 locus (lead single-nucleotide polymorphism [SNP]: rs147144681, p = 1.27E-11 in EUR; lead SNP = rs2036527, p = 6.49e-13 in cross-ancestry analysis). DSM-NicDep showed strong positive genetic correlations with cannabis use disorder, opioid use disorder, problematic alcohol use, lung cancer, material deprivation, and several psychiatric disorders, and negative correlations with respiratory function and educational attainment. A polygenic score of DSM-NicDep predicted DSM-5 tobacco use disorder criterion count and all 11 individual diagnostic criteria in the independent National Epidemiologic Survey on Alcohol and Related Conditions-III sample. In genomic structural equation models, DSM-NicDep loaded more strongly on a previously identified factor of general addiction liability than a "problematic tobacco use" factor (a combination of cigarettes per day and nicotine dependence defined by the Fagerström Test for Nicotine Dependence). Finally, DSM-NicDep showed a strong genetic correlation with a GWAS of tobacco use disorder as defined in electronic health records (EHRs). CONCLUSIONS:Our results suggest that combining the wide availability of diagnostic EHR data with nuanced criterion-level analyses of DSM tobacco use disorder may produce new insights into the genetics of this disorder.

Chronic pain (CP) is a debilitating condition that impacts an individual's physical and mental health. CP is common, affecting around 12-40% of individuals across the world. In this study, we conducted a genome-wide association study (GWAS) of lifetime incidence of CP in the All of Us Research Program, across six different ancestries in the United States (total Ncase = 137 043, total Ncontrol = 154 038). We found one genome-wide significant locus in the cross-ancestry meta-analysis on chromosome 5 (lead SNP: rs1196962975, p = 4.53E-08). Additionally, one locus on chromosome 11 (lead SNP: rs5795684) reached genome-wide significance in the admixed genetic ancestry sample (p = 1.13E-08). Cross-ancestry genetic correlations ranged from 0.40 - 0.78. CP was genetically correlated with a range of psychiatric, physical health, and immune traits, including anxiety (rg = 0.69, p = 1.82E-69), generalized addiction risk (rg = 0.39, p = 1.98E-18), and increased serum C-reactive protein levels (rg = 0.35, p = 5.28E-22). This study represents the largest cross-ancestral investigation of the genetics of lifetime incidence of chronic pain to date and demonstrates shared genetic effects between chronic pain and psychiatric disorders and other physical health conditions.

Substance use shortens lifespan, impedes health, and accelerates the biological aging process. We found widespread genetic correlations between alcohol, tobacco, cannabis, and opioid use and use disorders with indices of aging across the lifespan. There was evidence of tobacco and alcohol use and use disorders causally impacting physical, cognitive, and biological aging, with the effects of alcohol being more dependent on quantity of consumption; evidence of reverse causality was scant.

Positive correlations between mates can increase trait variation and prevalence, as well as bias estimates from genetically informed study designs. While past studies of similarity between human mating partners have largely found evidence of positive correlations, to our knowledge, no formal meta-analysis has examined human partner correlations across multiple categories of traits. Thus, we conducted systematic reviews and random-effects meta-analyses of human male-female partner correlations across 22 traits commonly studied by psychologists, economists, sociologists, anthropologists, epidemiologists and geneticists. Using ScienceDirect, PubMed and Google Scholar, we incorporated 480 partner correlations from 199 peer-reviewed studies of co-parents, engaged pairs, married pairs and/or cohabitating pairs that were published on or before 16 August 2022. We also calculated 133 trait correlations using up to 79,074 male-female couples in the UK Biobank (UKB). Estimates of the 22 mean meta-analysed correlations ranged from rmeta = 0.08 (adjusted 95% CI = 0.03, 0.13) for extraversion to rmeta = 0.58 (adjusted 95% CI = 0.50, 0.64) for political values, with funnel plots showing little evidence of publication bias across traits. The 133 UKB correlations ranged from rUKB = -0.18 (adjusted 95% CI = -0.20, -0.16) for chronotype (being a 'morning' or 'evening' person) to rUKB = 0.87 (adjusted 95% CI = 0.86, 0.87) for birth year. Across analyses, political and religious attitudes, educational attainment and some substance use traits showed the highest correlations, while psychological (that is, psychiatric/personality) and anthropometric traits generally yielded lower but positive correlations. We observed high levels of between-sample heterogeneity for most meta-analysed traits, probably because of both systematic differences between samples and true differences in partner correlations across populations. Meta-analyses of 22 traits and analyses of 133 traits from UK Biobank find widespread evidence of mate similarity, particularly for social attitudes, education and substance use traits.

Positive correlations between human mating partners are consistently observed across traits. Such correlations can increase phenotypic variation and, to the extent that they reflect genetic similarity in co-parents, can also increase prevalence for rare phenotypes and bias estimates in genetic designs. We conducted the largest set of meta-analyses on human partner correlations to date, incorporating 480 partner correlations across 22 traits. We also calculated 133 trait correlations between up to 79,074 male-female couples in the UK Biobank (UKB). Estimates of the mean meta-analyzed correlations ranged from r meta =.08 for extraversion to r meta = .58 for political values. UKB correlations ranged from r UKB =-.18 for chronotype to r UKB =.87 for birth year. Overall, attitudes, education, and substance use traits mostly showed the highest correlations, while psychological and biological traits generally yielded lower but still positive correlations. We observed high between-study heterogeneity for most meta-analyzed traits, likely because of both systematic differences between samples and true differences in partner correlations across populations.

Parents share half of their genes with their children, but they also share background social factors and actively help shape their child's environment - making it difficult to disentangle genetic and environmental causes of parent-offspring similarity. While adoption and extended twin family designs have been extremely useful for distinguishing genetic and nongenetic parental influences, these designs entail stringent assumptions about phenotypic similarity between relatives and require samples that are difficult to collect and therefore are typically small and not publicly shared. Here, we describe these traditional designs, as well as modern approaches that use large, publicly available genome-wide data sets to estimate parental effects. We focus in particular on an approach we recently developed, structural equation modeling (SEM)-polygenic score (PGS), that instantiates the logic of modern PGS-based methods within the flexible SEM framework used in traditional designs. Genetically informative designs such as SEM-PGS rely on different and, in some cases, less rigid assumptions than traditional approaches; thus, they allow researchers to capitalize on new data sources and answer questions that could not previously be investigated. We believe that SEM-PGS and similar approaches can lead to improved insight into how nature and nurture combine to create the incredible diversity underlying human behavior.

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

Elevated neuroticism may confer vulnerability to the depressogenic effects of stressful life events (SLEs). However, the mechanisms underlying this susceptibility remain poorly understood. Accumulating evidence suggests that stress-related disruptions in neural reward processing might undergird links between stress and depression. Using data from the Saint Louis Personality and Aging Network (SPAN) study and Duke Neurogenetics Study (DNS), we examined whether neuroticism moderates links between stressful life events (SLE) and depression as well as SLEs and ventral striatum (VS) response to reward. In the longitudinal SPAN sample (n = 971 older adults), SLEs prospectively predicted future depressive symptoms, especially among those reporting elevated neuroticism, even after accounting for prior depressive symptoms and previous SLE exposure (NxSLE interaction: p = .016, ΔR² = 0.003). Cross-sectional analyses of the DNS, a young adult college sample with neuroimaging data, replicated this interaction (n = 1,343: NxSLE interaction: p = .019, ΔR² = 0.003) and provided evidence that neuroticism moderates the association between SLEs and reward-related VS response (n = 1,195, NxSLE: p = .017, ΔR² = 0.0048). Blunted left VS response to reward was associated with a lifetime depression diagnosis, r = -0.07, p = .02, but not current depressive symptoms, r = -0.003, p = .93. These data suggest that neuroticism may promote vulnerability to stress-related depression and that sensitivity to stress-related reductions in VS response may be a potential neural mechanism underlying vulnerability to clinically significant depression. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Offspring resemble their parents for both genetic and environmental reasons. Understanding the relative magnitude of these alternatives has long been a core interest in behavioral genetics research, but traditional designs, which compare phenotypic covariances to make inferences about unmeasured genetic and environmental factors, have struggled to disentangle them. Recently, Kong et al. (2018) showed that by correlating offspring phenotypic values with the measured polygenic score of parents' nontransmitted alleles, one can estimate the effect of "genetic nurture"-a type of passive gene-environment covariation that arises when heritable parental traits directly influence offspring traits. Here, we instantiate this basic idea in a set of causal models that provide novel insights into the estimation of parental influences on offspring. Most importantly, we show how jointly modeling the parental polygenic scores and the offspring phenotypes can provide an unbiased estimate of the variation attributable to the environmental influence of parents on offspring, even when the polygenic score accounts for a small fraction of trait heritability. This model can be further extended to (a) account for the influence of different types of assortative mating, (b) estimate the total variation due to additive genetic effects and their covariance with the familial environment (i.e., the full genetic nurture effect), and (c) model situations where a parental trait influences a different offspring trait. By utilizing structural equation modeling techniques developed for extended twin family designs, our approach provides a general framework for modeling polygenic scores in family studies and allows for various model extensions that can be used to answer old questions about familial influences in new ways.

When people are rejected by others, they typically feel an immediate sense of pain-referred to as social pain. Social pain is hypothesized to be the alarm response of a "quick and crude" ostracism detection system, a system that is highly sensitive to even minimal signs of exclusion. Physiological reactivity has been found to accompany this social pain, but it is unclear whether the physiological mechanism underlying the ostracism detection system is also "quick and crude." To test whether physiological reactivity to exclusion is "quick and crude," the present study investigated whether pupil dilation (an index of physiological reactivity) differs when detecting exclusion from human entities versus nonhuman entities and when experiencing versus witnessing exclusion using a Cyberball paradigm. Experiment 1 showed that pupil size decreased less when viewing players who were exclusive than those who were inclusive, regardless of whether the players were human (i.e., undergraduate students) or nonhuman (i.e., computerized) entities. The same pupil reactivity pattern was observed in Experiment 2 after participants watched interactions in which another person was included or excluded by human or nonhuman entities. In Experiment 3, participating in real-life interactions with human players did not cause pupil reactivity to be greater to human players compared to nonhuman players, but pupil size again decreased less when viewing exclusive players compared to inclusive players. Across all three experiments, pupil size decreased less when viewing players who were exclusive than inclusive regardless of the social identity of the players. These findings support the idea of a highly sensitive, "quick and crude" physiological mechanism that underlies the ostracism detection system.