Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWASs) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N = 52) and nonsmokers (N = 171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and correcting for multiple testing using a two-stage procedure. We found >2 million significant meQTL variants (padj < 0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects, and five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTL variants for 958 unique eGenes (padj < 0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTN1 and ITIH4 colocalized across all data types (GWAS, meQTL, and eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Partitioning the Genomic Components of Behavioral Disinhibition and Substance Use (Disorder) Using Genomic Structural Equation Modeling

Externalizing behaviors encompass manifestations of risk-taking, self-regulation, aggression, sensation-/reward-seeking, and impulsivity. Externalizing research often includes substance use (SUB), substance use disorder (SUD), and other (non-SUB/SUD) "behavioral disinhibition" (BD) traits. Genome-wide and twin research have pointed to overlapping genetic architecture within and across SUB, SUD, and BD. We created single-factor measurement models-each describing SUB, SUD, or BD traits-based on mutually exclusive sets of European ancestry genome-wide association study (GWAS) statistics exploring externalizing variables. We then assessed the partitioning of genetic covariance among the three facets using correlated factors models and Cholesky decomposition. Even when the residuals for indicators relating to the same substance were correlated across the SUB and SUD factors, the two factors yielded a large correlation (rg = 0.803). BD correlated strongly with the SUD (rg = 0.774) and SUB (rg = 0.778) factors. In our initial decompositions, 33% of total BD variance remained after partialing out SUD and SUB. The majority of covariance between BD and SUB and between BD and SUD was shared across all factors, and, within these models, only a small fraction of the total variation in BD operated via an independent pathway with SUD or SUB outside of the other factor. When only nicotine/tobacco, cannabis, and alcohol were included for the SUB/SUD factors, their correlation increased to rg = 0.861; in corresponding decompositions, BD-specific variance decreased to 27%. Further research can better elucidate the properties of BD-specific variation by exploring its genetic/molecular correlates.

Single nucleotide variants in lung cancer

Germline genetic variants, including single-nucleotide variants (SNVs) and copy number variants (CNVs), account for interpatient heterogeneity. In the past several decades, genome-wide association studies (GWAS) have identified multiple lung cancer-associated SNVs in Caucasian and Chinese populations. These variants either reside within coding regions and change the structure and function of cancer-related proteins or reside within non-coding regions and alter the expression level of cancer-related proteins. The variants can be used not only for cancer risk assessment and prevention but also for the development of new therapies. In this review, we discuss the lung cancer-associated SNVs identified to date, their contributions to lung tumorigenesis and prognosis, and their potential use in predicting prognosis and implementing therapeutic strategies.

The genetic landscape of substance use disorders

Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.

Deep sequencing of candidate genes identified 14 variants associated with smoking abstinence in an ethnically diverse sample

Despite the large public health toll of smoking, genetic studies of smoking cessation have been limited with few discoveries of risk or protective loci. We investigated common and rare variant associations with success in quitting smoking using a cohort from 8 randomized controlled trials involving 2231 participants and a total of 10,020 common and 24,147 rare variants. We identified 14 novel markers including 6 mapping to genes previously related to psychiatric and substance use disorders, 4 of which were protective (CYP2B6 (rs1175607105), HTR3B (rs1413172952; rs1204720503), rs80210037 on chr15), and 2 of which were associated with reduced cessation (PARP15 (rs2173763), SCL18A2 (rs363222)). The others mapped to areas associated with cancer including FOXP1 (rs1288980) and ZEB1 (rs7349). Network analysis identified significant canonical pathways for the serotonin receptor signaling pathway, nicotine and bupropion metabolism, and several related to tumor suppression. Two novel markers (rs6749438; rs6718083) on chr2 are flanked by genes associated with regulation of bodyweight. The identification of novel loci in this study can provide new targets of pharmacotherapy and inform efforts to develop personalized treatments based on genetic profiles.

Partitioning the Genomic Components of Behavioral Disinhibition and Substance Use (Disorder) Using Genomic Structural Equation Modeling

Externalizing behaviors encompass manifestations of risk-taking, self-regulation, aggression, sensation-/reward-seeking, and impulsivity. Externalizing research often includes substance use (SU), substance use disorder (SUD), and other (non-SU/SUD) "behavioral disinhibition" (BD) traits. Genome-wide and twin research have pointed to overlapping genetic architecture within and across SUB, SUD, and BD. We created single-factor measurement models-each describing SUB, SUD, or BD traits--based on mutually exclusive sets of European ancestry genome-wide association study (GWAS) statistics exploring externalizing variables. We then applied trivariate Cholesky decomposition to these factors in order to identify BD-specific genomic variation and assess the partitioning of BD's genetic covariance with each of the other facets. Even when the residuals for indicators relating to the same substance were correlated across the SUB and SUD factors, the two factors yielded a large zero-order correlation (rg=.803). BD correlated strongly with the SUD (rg=.774) and SUB factors (rg=.778). In our initial decompositions, 33% of total BD variance remained after removing variance associated with SUD and SUB. The majority of covariance between BD and SU and between BD and SUD was shared across all factors. When only nicotine/tobacco, cannabis, and alcohol were included for the SUB/SUD factors, their zero-order correlation increased to rg=.861; in corresponding decompositions, BD-specific variance decreased to 27%. In summary, BD, SU, and SUD were highly genetically correlated at the latent factor level, and a significant minority of genomic BD variation was not shared with SU and/or SUD. Further research can better elucidate the properties of BD-specific variation by exploring its genetic/molecular correlates.

Epigenetic mechanisms of nicotine dependence

Smoking continues to be a leading cause of preventable disease and death worldwide. Nicotine dependence generates a lifelong propensity towards cravings and relapse, presenting an ongoing challenge for the development of treatments. Accumulating evidence supports a role for epigenetics in the development and maintenance of addiction to many drugs of abuse, however, the involvement of epigenetics in nicotine dependence is less clear. Here we review evidence that nicotine interacts with epigenetic mechanisms to enable the maintenance of nicotine-seeking across time. Research across species suggests that nicotine increases permissive histone acetylation, decreases repressive histone methylation, and modulates levels of DNA methylation and noncoding RNA expression throughout the brain. These changes are linked to the promoter regions of genes critical for learning and memory, reward processing and addiction. Pharmacological manipulation of enzymes that catalyze core epigenetic modifications regulate nicotine reward and associative learning, demonstrating a functional role of epigenetic modifications in nicotine dependence. These findings are consistent with nicotine promoting an overall permissive chromatin state at genes important for learning, memory and reward. By exploring these links through next-generation sequencing technologies, epigenetics provides a promising avenue for future interventions to treat nicotine dependence.

Influence of Admixture on Phenotypes

Individuals of European descent have historically been the focus of genetic studies and possess relatively homogenous genomes. As a result, analytical methods have been developed and optimized with such genomes in mind. African-descent and Latino individuals generally possess genomes of greater architectural complexity due to mosaic genomic ancestry, which can extensively and intricately impact phenotypic expression. As such, genetic analyses of admixed individuals require that genetic admixture be quantified to accurately model the impact of genetic variation on phenotypic expression. In this overview, we explore how fundamental genetic concepts such as linkage disequilibrium and differential allele frequency interact with genetic admixture to uniquely influence phenotypes in admixed individuals. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Association of nicotine dependence and gut microbiota: a bidirectional two-sample Mendelian randomization study

Background

Nicotine dependence is a key factor influencing the diversity of gut microbiota, and targeting gut microbiota may become a new approach for the prevention and treatment of nicotine dependence. However, the causal relationship between the two is still unclear. This study aims to investigate the causal relationship between nicotine dependence and gut microbiota.

Methods

A two-sample bidirectional Mendelian randomization (MR) study was conducted using the largest existing gut microbiota and nicotine dependence genome-wide association studies (GWAS). Causal relationships between genetically predicted nicotine dependence and gut microbiota abundance were examined using inverse variance weighted, MR-Egger, weighted median, simple mode, weighted mode, and MR-PRESSO approaches. Cochrane's Q test, MR-Egger intercept test, and leave-one-out analysis were performed as sensitivity analyses to assess the robustness of the results. Multivariable Mendelian randomization analysis was also conducted to eliminate the interference of smoking-related phenotypes. Reverse Mendelian randomization analysis was then performed to determine the causal relationship between genetically predicted gut microbiota abundance and nicotine dependence.

Results

Genetically predicted nicotine dependence had a causal effect on Christensenellaceae (β: -0.52, 95% CI: -0.934-0.106, P = 0.014). The Eubacterium xylanophilum group (OR: 1.106, 95% CI: 1.004-1.218), Lachnoclostridium (OR: 1.118, 95% CI: 1.001-1.249) and Holdemania (OR: 1.08, 95% CI: 1.001-1.167) were risk factors for nicotine dependence. Peptostreptococcaceae (OR: 0.905, 95% CI: 0.837-0.977), Desulfovibrio (OR: 0.014, 95% CI: 0.819-0.977), Dorea (OR: 0.841, 95% CI. 0.731-0.968), Faecalibacterium (OR: 0.831, 95% CI: 0.735-0.939) and Sutterella (OR: 0.838, 95% CI: 0.739-0.951) were protective factor for nicotine dependence. The sensitivity analysis showed consistent results.

Conclusion

The Mendelian randomization study confirmed the causal link between genetically predicted risk of nicotine dependence and genetically predicted abundance of gut microbiota. Gut microbiota may serve as a biomarker and offer insights for addressing nicotine dependence.

Lack of racial and ethnic diversity in lung cancer cell lines contributes to lung cancer health disparities

Lung cancer is the leading cause of cancer death in the United States and worldwide, and a major source of cancer health disparities. Lung cancer cell lines provide key in vitro models for molecular studies of lung cancer development and progression, and for pre-clinical drug testing. To ensure health equity, it is imperative that cell lines representing different lung cancer histological types, carrying different cancer driver genes, and representing different genders, races, and ethnicities should be available. This is particularly relevant for cell lines from Black men, who experience the highest lung cancer mortality in the United States. Here, we undertook a review of the available lung cancer cell lines and their racial and ethnic origin. We noted a marked imbalance in the availability of cell lines from different races and ethnicities. Cell lines from Black patients were strongly underrepresented, and we identified no cell lines from Hispanic/Latin(x) (H/L), American Indian/American Native (AI/AN), or Native Hawaiian or other Pacific Islander (NHOPI) patients. The majority of cell lines were derived from White and Asian patients. Also missing are cell lines representing the cells-of-origin of the major lung cancer histological types, which can be used to model lung cancer development and to study the effects of environmental exposures on lung tissues. To our knowledge, the few available immortalized alveolar epithelial cell lines are all derived from White subjects, and the race and ethnicity of a handful of cell lines derived from bronchial epithelial cells are unknown. The lack of an appropriately diverse collection of lung cancer cell lines and lung cancer cell-of-origin lines severely limits racially and ethnically inclusive lung cancer research. It impedes the ability to develop inclusive models, screen comprehensively for effective compounds, pre-clinically test new drugs, and optimize precision medicine. It thereby hinders the development of therapies that can increase the survival of minority and underserved patients. The noted lack of cell lines from underrepresented groups should constitute a call to action to establish additional cell lines and ensure adequate representation of all population groups in this critical pre-clinical research resource.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWAS) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N=52) and nonsmokers (N=171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and using a two-stage multiple testing approach with eigenMT and Bonferroni corrections. We found >2 million significant meQTL variants (padj<0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects; five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTLs for 958 unique eGenes (padj<0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTIN1 and ITIH4 colocalized across all data types (GWAS + meQTL + eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Effects of smoking on genome-wide DNA methylation profiles: A study of discordant and concordant monozygotic twin pairs

Background

Smoking-associated DNA methylation levels identified through epigenome-wide association studies (EWASs) are generally ascribed to smoking-reactive mechanisms, but the contribution of a shared genetic predisposition to smoking and DNA methylation levels is typically not accounted for.

Methods

We exploited a strong within-family design, that is, the discordant monozygotic twin design, to study reactiveness of DNA methylation in blood cells to smoking and reversibility of methylation patterns upon quitting smoking. Illumina HumanMethylation450 BeadChip data were available for 769 monozygotic twin pairs (mean age = 36 years, range = 18-78, 70% female), including pairs discordant or concordant for current or former smoking.

Results

In pairs discordant for current smoking, 13 differentially methylated CpGs were found between current smoking twins and their genetically identical co-twin who never smoked. Top sites include multiple CpGs in CACNA1D and GNG12, which encode subunits of a calcium voltage-gated channel and G protein, respectively. These proteins interact with the nicotinic acetylcholine receptor, suggesting that methylation levels at these CpGs might be reactive to nicotine exposure. All 13 CpGs have been previously associated with smoking in unrelated individuals and data from monozygotic pairs discordant for former smoking indicated that methylation patterns are to a large extent reversible upon smoking cessation. We further showed that differences in smoking level exposure for monozygotic twins who are both current smokers but differ in the number of cigarettes they smoke are reflected in their DNA methylation profiles.

Conclusions

In conclusion, by analysing data from monozygotic twins, we robustly demonstrate that DNA methylation level in human blood cells is reactive to cigarette smoking.

Funding

We acknowledge funding from the National Institute on Drug Abuse grant DA049867, the Netherlands Organization for Scientific Research (NWO): Biobanking and Biomolecular Research Infrastructure (BBMRI-NL, NWO 184.033.111) and the BBRMI-NL-financed BIOS Consortium (NWO 184.021.007), NWO Large Scale infrastructures X-Omics (184.034.019), Genotype/phenotype database for behaviour genetic and genetic epidemiological studies (ZonMw Middelgroot 911-09-032); Netherlands Twin Registry Repository: researching the interplay between genome and environment (NWO-Groot 480-15-001/674); the Avera Institute, Sioux Falls (USA), and the National Institutes of Health (NIH R01 HD042157-01A1, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995); epigenetic data were generated at the Human Genomics Facility (HuGe-F) at ErasmusMC Rotterdam. Cotinine assaying was sponsored by the Neuroscience Campus Amsterdam. DIB acknowledges the Royal Netherlands Academy of Science Professor Award (PAH/6635).

Testing Association of Previously Implicated Gene Sets and Gene-Networks in Nicotine Exposed Mouse Models with Human Smoking Phenotypes

INTRODUCTION

Smoking behaviors are partly heritable, yet the genetic and environmental mechanisms underlying smoking phenotypes are not fully understood. Developmental nicotine exposure (DNE) is a significant risk factor for smoking and leads to gene expression changes in mouse models; however, it is unknown whether the same genes whose expression is impacted by DNE are also those underlying smoking genetic liability. We examined whether genes whose expression in D1-type striatal medium spiny neurons due to DNE in the mouse are also associated with human smoking behaviors.

METHODS

Specifically, we assessed whether human orthologs of mouse-identified genes, either individually or as a set, were genetically associated with five human smoking traits using MAGMA and S-LDSC while implementing a novel expression-based gene-SNP annotation methodology.

RESULTS

We found no strong evidence that these genes sets were more strongly associated with smoking behaviors than the rest of the genome, but ten of these individual genes were significantly associated with three of the five human smoking traits examined (p < 2.5e-6). Three of these genes have not been reported previously and were discovered only when implementing the expression-based annotation.

CONCLUSIONS

These results suggest the genes whose expression is impacted by DNE in mice are largely distinct from those contributing to smoking genetic liability in humans. However, examining a single mouse neuronal cell type may be too fine a resolution for comparison, suggesting that experimental manipulation of nicotine consumption, reward, or withdrawal in mice may better capture genes related to the complex genetics of human tobacco use.

IMPLICATIONS

Genes whose expression is impacted by DNE in mouse D1-type striatal medium spiny neurons were not found to be, as a whole, more strongly associated with human smoking behaviors than the rest of the genome, though ten individual mouse-identified genes were associated with human smoking traits. This suggests little overlap between the genetic mechanisms impacted by DNE and those influencing heritable liability to smoking phenotypes in humans. Further research is warranted to characterize how developmental nicotine exposure paradigms in mice can be translated to understand nicotine use in humans and their heritable effects on smoking.

Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders

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.

Global burden of cancers attributable to tobacco smoking, 1990-2019: an ecological study

Aim and background

Identifying risk factors for cancer initiation and progression is the cornerstone of the preventive approach to cancer management and control (EPMA J. 4(1):6, 2013). Tobacco smoking is a well-recognized risk factor for initiation and spread of several cancers. The predictive, preventive, and personalized medicine (PPPM) approach to cancer management and control focuses on smoking cessation as an essential cancer prevention strategy. Towards this end, this study examines the temporal patterns of cancer burden due to tobacco smoking in the last three decades at global, regional, and national levels.

Data and methods

The data pertaining to the burden of 16 cancers attributable to tobacco smoking at global, regional, and national levels were procured from the Global Burden of Disease 2019 Study. Two main indicators, deaths and disability-adjusted life years (DALYs), were used to describe the burden of cancers attributable to tobacco smoking. The socio-economic development of countries was measured using the socio-demographic index (SDI).

Results

Globally, deaths due to neoplasms caused by tobacco smoking increased from 1.5 million in 1990 to 2.5 million in 2019, whereas the age-standardized mortality rate (ASMR) decreased from 39.8/100,000 to 30.6/100,000 and the age-standardized DALY rate (ASDALR) decreased from 948.9/100,000 to 677.3/100,000 between 1990 and 2019. Males accounted for approximately 80% of global deaths and DALYs in 2019. Populous regions of Asia and a few regions of Europe account for the largest absolute burden, whereas countries in Europe and America have the highest age-standardized rates of cancers due to tobacco smoking. In 8 out of 21 regions, there were more than 100,000 deaths due to cancers attributable to tobacco smoking led by East Asia, followed by Western Europe in 2019. The regions of Sub-Saharan Africa (except southern region) had one of the lowest absolute counts of deaths, DALYs, and age-standardized rates. In 2019, tracheal, bronchus, and lung (TBL), esophageal, stomach, colorectal, and pancreatic cancer were the top 5 neoplasms attributable to tobacco smoking, with different burdens in regions as per their development status. The ASMR and ASDALR of neoplasms due to tobacco smoking were positively correlated with SDI, with pairwise correlation coefficient of 0.55 and 0.52, respectively.

Conclusion

As a preventive tool, tobacco smoking cessation has the biggest potential among all risk factors for preventing millions of cancer deaths every year. Cancer burden due to tobacco smoking is found to be higher in males and is positively associated with socio-economic development of countries. As tobacco smoking begins mostly at younger ages and the epidemic is unfolding in several parts of the world, more accelerated efforts are required towards tobacco cessation and preventing youth from entering this addiction. The PPPM approach to medicine suggests that not only personalized and precision medicine must be provided to cancer patients afflicted by tobacco smoking but personalized and targeted preventive solutions must be provided to prevent initiation and progression of smoking.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00308-y.

Genetic insights into smoking behaviours in 10,558 men of African ancestry from continental Africa and the UK

Smoking is a leading risk factor for many of the top ten causes of death worldwide. Of the 1.3 billion smokers globally, 80% live in low- and middle-income countries, where the number of deaths due to tobacco use is expected to double in the next decade according to the World Health Organization. Genetic studies have helped to identify biological pathways for smoking behaviours, but have mostly focussed on individuals of European ancestry or living in either North America or Europe. We performed a genome-wide association study of two smoking behaviour traits in 10,558 men of African ancestry living in five African countries and the UK. Eight independent variants were associated with either smoking initiation or cessation at P-value < 5 × 10-6, four being monomorphic or rare in European populations. Gene prioritisation strategy highlighted five genes, including SEMA6D, previously described as associated with several smoking behaviour traits. These results confirm the importance of analysing underrepresented populations in genetic epidemiology, and the urgent need for larger genomic studies to boost discovery power to better understand smoking behaviours, as well as many other traits.

SNP rs9387478 at ROS1-DCBLD1 Locus is Significantly Associated with Lung Cancer Risk and Poor Survival in Indian Population

OBJECTIVE

Receptor tyrosine kinases (RTK) are relevant therapeutic targets in the treatment of lung cancer. Germline susceptibility variants that influence these RTKs may provide new insights into their regulation.  rs9387478 is located in the genomic interval between two RTK-genes ROS1/DCBLD1, of which ROS1 alterations are implicated in lung carcinogenesis and treatment response while the latter remains poorly understood.

MATERIALS AND METHODS

Venous blood was drawn from 100 control and 231 case subjects. Genotype was scored by restriction fragment length polymorphism (RFLP), PCR amplification followed by HindIII digestion. Logistic regression was applied to compare the association between variables. Survival curve was plotted to draw a correlation between the genotype and overall survival. Also, eQTL and chromatin state changes were analyzed and correlated with the survival of patients using available datasets.

RESULTS

In our population smoking correlated significantly with lung cancer [OR= 2.607] with the presence of the minor allele 'A' enhancing the nicotine dependence [CA (OR=3.23)]. Individuals with homozygous risk allele 'A' had a higher chance of developing lung cancer [OR=2.65] than individuals with CA/CC implying a recessive model of association. Patients with CC/CA genotype had better overall survival than patients with AA genotype [161 days/142 days vs 54 days, p=0.005]. The homozygous risk allele was significantly associated with increased DCBLD1 and ROS1 expression in lung cancer, with enriched active histone marks due to the polymorphism. Interestingly, increased DCBLD1 expression was associated with poor outcomes in lung cancer.

CONCLUSION

Overall, our study provides strong evidence that rs9387478 is significantly associated with both nicotine dependence and lung cancer in our North Indian cohort. The association of the SNP with prognostic genes, DCBLD1 and ROS1 make rs9387478 a promising prognostic marker in the North Indian population. The results obtained are significant, however, the study needs to be performed in a larger sample size.

The addiction risk factor: A unitary genetic vulnerability characterizes substance use disorders and their associations with common correlates

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.

Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies

BACKGROUND AND AIMS

Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome-wide findings is lacking for substance use. Here, we combined all the genome-wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs.

METHODS

Systemic literature search for genome-wide association (GWAS) and RNA-seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case-control or case/cohort samples. RNA-seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10^-6 ) in GWAS and reported as significant in RNA-seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database.

RESULTS

Total SUBD-related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA-seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of 'modulation of chemical synaptic transmission', 'regulation of trans-synaptic signaling', two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of 'dopaminergic synapse', 'cocaine addiction'] were identified (significantly higher than random, P < 1 × 10^-5 ). The top shared KEGG pathways (Benjamini-Hochberg-corrected P-value < 0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were 'Epstein-Barr virus infection', 'protein processing in endoplasmic reticulum' and 'neuroactive ligand-receptor interaction', respectively. We also identified substance-specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD.

CONCLUSIONS

This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome-wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.

Epigenetic Basis of Psychiatric Disorders: A Narrative Review

BACKGROUND

Psychiatric disorders are complex, multifactorial illnesses with a demonstrated biological component in their etiopathogenesis. Epigenetic modifications, through the modulation of DNA methylation, histone modifications and RNA interference, tune tissue-specific gene expression patterns and play a relevant role in the etiology of psychiatric illnesses.

OBJECTIVE

This review aims to discuss the epigenetic mechanisms involved in psychiatric disorders, their modulation by environmental factors and their interactions with genetic variants, in order to provide a comprehensive picture of their mutual crosstalk.

METHODS

In accordance with the PRISMA guidelines, systematic searches of Medline, EMBASE, PsycINFO, Web of Science, Scopus, and the Cochrane Library were conducted.

RESULTS

Exposure to environmental factors, such as poor socio-economic status, obstetric complications, migration, and early life stressors, may lead to stable changes in gene expression and neural circuit function, playing a role in the risk of psychiatric diseases. The most replicated genes involved by studies using different techniques are discussed. Increasing evidence indicates that these sustained abnormalities are maintained by epigenetic modifications in specific brain regions and they interact with genetic variants in determining the risk of psychiatric disorders.

CONCLUSION

An increasing amount of evidence suggests that epigenetics plays a pivotal role in the etiopathogenesis of psychiatric disorders. New therapeutic approaches may work by reversing detrimental epigenetic changes that occurred during the lifespan.

Genetic Modifiers of Oral Nicotine Consumption in Chrna5 Null Mutant Mice

The gene CHRNA5 is strongly associated with the level of nicotine consumption in humans and manipulation of the expression or function of Chrna5 similarly alters nicotine consumption in rodents. In both humans and rodents, reduced or complete loss of function of Chrna5 leads to increased nicotine consumption. However, the mechanism through which decreased function of Chrna5 increases nicotine intake is not well-understood. Toward a better understanding of how loss of function of Chrna5 increases nicotine consumption, we have initiated efforts to identify genetic modifiers of Chrna5 deletion-dependent oral nicotine consumption in mice. For this, we introgressed the Chrna5 knockout (KO) mutation onto a panel of C57BL/6J-Chr#A/J/NAJ chromosome substitution strains (CSS) and measured oral nicotine consumption in 18 CSS and C57BL/6 (B6) mice homozygous for the Chrna5 KO allele as well as their Chrna5 wild type littermates. As expected, nicotine consumption was significantly increased in Chrna5 KO mice relative to Chrna5 wildtype mice on a B6 background. Among the CSS homozygous for the Chrna5 KO allele, several exhibited altered nicotine consumption relative to B6 Chrna5 KO mice. Sex-independent modifiers were detected in CSS possessing A/J chromosomes 5 and 11 and a male-specific modifier was found on chromosome 15. In all cases nicotine consumption was reduced in the CSS Chrna5 KO mice relative to B6 Chrna5 KO mice and consumption in the CSS KO mice was indistinguishable from their wild type littermates. Nicotine consumption was also reduced in both Chrna5 KO and wildtype CSS mice possessing A/J chromosome 1 and increased in both KO and wild type chromosome 17 CSS relative to KO and wild type B6 mice. These results demonstrate the presence of several genetic modifiers of nicotine consumption in Chrna5 KO mice as well as identify loci that may affect nicotine consumption independent of Chrna5 genotype. Identification of the genes that underlie the altered nicotine consumption may provide novel insight into the mechanism through which Chrna5 deletion increases nicotine consumption and, more generally, a better appreciation of the neurobiology of nicotine intake.

The effect of nicotine dependence on the risk of developing post-traumatic stress disorder: Results from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC)

BACKGROUND

It is evident that an association between smoking and post-traumatic stress disorder (PTSD) exists, but research is lacking in establishing the directionality of the relationship.

METHODS

We used longitudinal data from wave I (2001-2002) and II (2004-2005) of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Individuals with nicotine dependence (ND) were matched to individuals without ND using propensity score matching to estimate the risk of developing PTSD after trauma. We also matched smokers (with or without ND) to lifetime non-smokers to estimate their risk of developing PTSD after trauma. Lastly, we conducted a mediation analysis on the effect of ND severity on PTSD symptoms.

RESULTS

Individuals with ND (n = 1,514) were more likely to develop PTSD (OR: 1.59; 95%CI: 1.09-2.32; p = 0.017) compared to individuals without ND (n = 6,047). Smokers (regardless of ND status) (n = 2,335) compared to non-smokers (n = 5,226) had no significant effect on risk of PTSD (p = 0.26). Withdrawal was found to be a mediator of the effect of ND severity on PTSD symptoms.

CONCLUSION

ND, but not smoking status, increases a smoker's risk of developing PTSD. This provides information that could aid in preventive strategies for individuals with ND who are exposed to trauma.

IMPLICATIONS

This study provides evidence in a national representative sample of adults in the U.S. that nicotine dependence may increase one's risk of developing PTSD after exposure to trauma. It also shows the directionality of the association between smoking and PTSD. Lastly, it demonstrates that withdrawal may be the link to the association between nicotine dependence and PTSD. We hope that with these findings, preventative strategies are put in place for smokers who are dependent and are exposed to trauma, such that they do not develop PTSD.

Genetics of substance use disorders in the era of big data

Substance use disorders (SUDs) are conditions in which the use of legal or illegal substances, such as nicotine, alcohol or opioids, results in clinical and functional impairment. SUDs and, more generally, substance use are genetically complex traits that are enormously costly on an individual and societal basis. The past few years have seen remarkable progress in our understanding of the genetics, and therefore the biology, of substance use and abuse. Various studies - including of well-defined phenotypes in deeply phenotyped samples, as well as broadly defined phenotypes in meta-analysis and biobank samples - have revealed multiple risk loci for these common traits. A key emerging insight from this work establishes a biological and genetic distinction between quantity and/or frequency measures of substance use (which may involve low levels of use without dependence), versus symptoms related to physical dependence.

Little Evidence of Modified Genetic Effect of rs16969968 on Heavy Smoking Based on Age of Onset of Smoking

INTRODUCTION

Tobacco smoking is the leading cause of preventable death globally. Smoking quantity, measured in cigarettes per day, is influenced both by the age of onset of regular smoking (AOS) and by genetic factors, including a strong effect of the nonsynonymous single-nucleotide polymorphism rs16969968. A previous study by Hartz et al. reported an interaction between these two factors, whereby rs16969968 risk allele carriers who started smoking earlier showed increased risk for heavy smoking compared with those who started later. This finding has yet to be replicated in a large, independent sample.

METHODS

We performed a preregistered, direct replication attempt of the rs16969968 × AOS interaction on smoking quantity in 128 383 unrelated individuals from the UK Biobank, meta-analyzed across ancestry groups. We fit statistical association models mirroring the original publication as well as formal interaction tests on multiple phenotypic and analytical scales.

RESULTS

We replicated the main effects of rs16969968 and AOS on cigarettes per day but failed to replicate the interaction using previous methods. Nominal significance of the rs16969968 × AOS interaction term depended strongly on the scale of analysis and the particular phenotype, as did associations stratified by early/late AOS. No interaction tests passed genome-wide correction (α = 5e-8), and all estimated interaction effect sizes were much smaller in magnitude than previous estimates.

CONCLUSIONS

We failed to replicate the strong rs16969968 × AOS interaction effect previously reported. If such gene-moderator interactions influence complex traits, they likely depend on scale of measurement, and current biobanks lack the power to detect significant genome-wide associations given the minute effect sizes expected.

IMPLICATIONS

We failed to replicate the strong rs16969968 × AOS interaction effect on smoking quantity previously reported. If such gene-moderator interactions influence complex traits, current biobanks lack the power to detect significant genome-wide associations given the minute effect sizes expected. Furthermore, many potential interaction effects are likely to depend on the scale of measurement employed.

Investigating genetic correlation and causality between nicotine dependence and ADHD in a broader psychiatric context

People with attention-deficit/hyperactivity disorder (ADHD) or other psychiatric disorders show high rates of nicotine dependence (ND). This comorbidity might be (partly) explained by shared genetic factors. Genetic correlations between ND and ADHD (or other psychiatric disorders) have not yet been estimated. A significant genetic correlation might indicate genetic overlap, but could also reflect a causal relationship. In the present study we investigated the genetic correlation (with LD score regression analyses) between ND and ADHD, as well as between ND and other major psychiatric conditions (major depressive disorder, schizophrenia, anxiety, bipolar disorder, autism spectrum, anorexia nervosa, and antisocial behavior) based on the summary statistics of large Genome Wide Association studies. We explored the causal nature of the relationship between ND and ADHD using two-sample Mendelian randomization. We found a high genetic correlation between ND and ADHD (r_g  = .53, p = 1.85 × 10^-13 ), and to a lesser extent also between ND-major depressive disorder (r_g  = .42, p = 3.6 × 10^-11 ) and ND-schizophrenia (r_g  = .18, p = 1.1 × 10^-3 ). We did not find evidence for a causal relationship from liability for ADHD to ND (which could be due to a lack of power). The strong genetic correlations might reflect different phenotypic manifestations of (partly) shared underlying genetic vulnerabilities. Combined with the lack of evidence for a causal relationship from liability for ADHD to ND, these findings stress the importance to further investigate the underlying genetic vulnerability explaining co-morbidity in psychiatric disorders.

Genetics of substance use disorders: a review

Substance use disorders (SUDs) are prevalent and result in an array of negative consequences. They are influenced by genetic factors (h2 = ~50%). Recent years have brought substantial progress in our understanding of the genetic etiology of SUDs and related traits. The present review covers the current state of the field for SUD genetics, including the epidemiology and genetic epidemiology of SUDs, findings from the first-generation of SUD genome-wide association studies (GWAS), cautions about translating GWAS findings to clinical settings, and suggested prioritizations for the next wave of SUD genetics efforts. Recent advances in SUD genetics have been facilitated by the assembly of large GWAS samples, and the development of state-of-the-art methods modeling the aggregate effect of genome-wide variation. These advances have confirmed that SUDs are highly polygenic with many variants across the genome conferring risk, the vast majority of which are of small effect. Downstream analyses have enabled finer resolution of the genetic architecture of SUDs and revealed insights into their genetic relationship with other psychiatric disorders. Recent efforts have also prioritized a closer examination of GWAS findings that have suggested non-uniform genetic influences across measures of substance use (e.g. consumption) and problematic use (e.g. SUD). Additional highlights from recent SUD GWAS include the robust confirmation of loci in alcohol metabolizing genes (e.g. ADH1B and ALDH2) affecting alcohol-related traits, and loci within the CHRNA5-CHRNA3-CHRNB4 gene cluster influencing nicotine-related traits. Similar successes are expected for cannabis, opioid, and cocaine use disorders as sample sizes approach those assembled for alcohol and nicotine.

Genetic architecture of four smoking behaviors using partitioned SNP heritability

BACKGROUND AND AIMS

Although genome-wide association studies have identified many loci that influence smoking behaviors, much of the genetic variance remains unexplained. We characterized the genetic architecture of four smoking behaviors using single nucleotide polymorphism (SNP) heritability (h²_SNP ). This is an estimate of narrow-sense heritability specifically estimating the proportion of phenotypic variation due to causal variants (CVs) tagged by SNPs.

DESIGN

Partitioned h²_SNP analysis of smoking behavior traits.

SETTING

UK Biobank.

PARTICIPANTS

UK Biobank participants of European ancestry. The number of participants varied depending on the trait, from 54 792 to 323 068.

MEASUREMENTS

Smoking initiation, age of initiation, cigarettes per day (CPD; count, log-transformed, binned and dichotomized into heavy versus light) and smoking cessation with imputed genome-wide SNPs.

FINDINGS

We estimated that, in aggregate, approximately 18% of the phenotypic variance in smoking initiation was captured by imputed SNPs [h²_SNP = 0.18, standard error (SE) = 0.01] and 12% [SE = 0.02] for smoking cessation, both of which were more than twice the previously reported estimates. Estimated age of initiation (h²_SNP  = 0.05, SE = 0.01) and binned CPD (h²_SNP  = 0.1, SE = 0.01) were substantially below published twin-based h² of 50%. CPD encoding influenced estimates, with dichotomized CPD h²_SNP  = 0.28. There was no evidence of dominance genetic variance for any trait.

CONCLUSION

A biobank study of smoking behavior traits suggested that the phenotypic variance explained by SNPs of smoking initiation, age of initiation, cigarettes per day and smoking cessation is modest overall.

Genome-wide gene-smoking interaction study identified novel susceptibility loci for non-small cell lung cancer in Chinese populations

Gene-smoking interactions play important roles in the development of non-small cell lung cancer (NSCLC). To identify single nucleotide polymorphisms (SNPs) that modify the association of smoking behavior with NSCLC risk, we conducted a genome-wide gene-smoking interaction study in Chinese populations. The genome-wide interaction analysis between SNPs and smoking status (ever- versus never-smokers) was carried out using genome-wide association studies (GWAS) of NSCLC, which included 13,327 cases and 13,328 controls. Stratified analysis by histological subtypes was also conducted. We used a genome-wide significance threshold of 5×10 -8 for identifying significant gene-smoking interactions and 1×10 -6 for identifying suggestive results. Functional annotation was performed to identify potential functional SNPs and target genes. We identified three novel loci with significant or suggestive gene-smoking interaction. For NSCLC, the interaction between rs2746087 (20q11.23) and smoking status reached genome-wide significance threshold (OR = 0.63, 95%CI: 0.54-0.74, P = 3.31×10 -8), and the interaction between rs11912498 (22q12.1) and smoking status reached suggestive significance threshold (OR = 0.72, 95%CI: 0.63-0.82, P = 8.10×10 -7). Stratified analysis by histological subtypes identified suggestive interactions between rs459724 (5q11.2) and smoking status (OR = 0.61, 95%CI: 0.51-0.73, P = 7.55×10 -8) in the risk of lung squamous cell carcinoma. Functional annotation indicated that both classic and novel biological processes, including nicotine addiction and airway clearance, may modulate the susceptibility to NSCLC. These novel loci provide new insights into the biological mechanisms underlying NSCLC risk. Independent replication in large-scale studies is needed and experimental studies are warranted to functionally validate these associations.

Multi-polygenic Analysis of Nicotine Dependence in Individuals of European Ancestry

INTRODUCTION

Heritability estimates of nicotine dependence (ND) range from 40-70%, but discovery GWAS of ND are underpowered and have limited predictive utility. In this work, we leverage genetically correlated traits and diseases to increase the accuracy of polygenic risk prediction.

METHODS

We employed a multi-trait model using summary statistic-based best linear unbiased predictors (SBLUP) of genetic correlates of DSM-IV diagnosis of ND in 6,394 individuals of European Ancestry (prevalence = 45.3%, %female = 46.8%, µage = 40.08 [s.d. = 10.43]) and 3,061 individuals from a nationally-representative sample with Fagerström Test for Nicotine Dependence symptom count (FTND; 51.32% female, mean age = 28.9 [s.d. = 1.70]). Polygenic predictors were derived from GWASs known to be phenotypically and genetically correlated with ND (i.e., Cigarettes per Day (CPD), the Alcohol Use Disorders Identification Test (AUDIT-Consumption and AUDIT-Problems), Neuroticism, Depression, Schizophrenia, Educational Attainment, Body Mass Index (BMI), and Self-Perceived Risk-Taking); including Height as a negative control. Analyses controlled for age, gender, study site, and the first 10 ancestral principal components.

RESULTS

The multi-trait model accounted for 3.6% of the total trait variance in DSM-IV ND. Educational Attainment (β=-0.125; 95% confidence interval (CI): [-0.149,-0.101]), CPD (0.071 [0.047,0.095]), and Self-Perceived Risk-Taking (0.051 [0.026,0.075]) were the most robust predictors. PGS effects on FTND were limited.

CONCLUSIONS

Risk for ND is not only polygenic, but also pleiotropic. Polygenic effects on ND that are accessible by these traits are limited in size and act additively to explain risk.

Clarifying the Genetic Influences on Nicotine Dependence and Quantity of Use in Cigarette Smokers

Nicotine dependence and smoking quantity are both robustly associated with the CHRNA5-A3-B4 gene cluster in the 15q25 region, and SNP rs16969968 in particular. The purpose of this paper is to use structural equation modeling techniques (SEM) to disentangle the complex pattern of relationships between rs16969968, nicotine quantity (as measured by the number of cigarettes an individual smokes per day; CPD) and nicotine dependence (as measured by the Fagerström Test for Nicotine Dependence; FTND). CPD is an indicator, but also a potential cause, of FTND, complicating the interpretation of associations between these constructs and requires a more detailed investigation than standard GWAS or general linear regression models can provide. FTND items and genotypes were collected in four samples, with a combined sample size of 5,373 respondents. A mega-analysis was conducted using a multiple group SEM approach to test competing hypotheses regarding the relationships between the SNP rs16969968, FTND and CPD. In the best fitting model, the FTND items loaded onto two correlated factors. The first, labeled "maintenance," assesses the motivation to maintain constant levels of nicotine through out the day. The second was labeled "urgency" as its items concern the urgency to restore nicotine levels after abstinence. We focus our attention on the "maintenance" factor, of which CPD was an indicator. The best fitting model included a negative feedback loop between the Maintenance factor and CPD. Accordingly, the motivation to maintain higher levels of nicotine increased the quantity of nicotine consumed, which subsequently decreases the maintenance motivation. The fact that the Maintenance-CPD feedback model fits the data best implies that there are at least two biological pathways that lead from rs16969968 to smoking behaviors. The model is consistent with a supply and demand system, which allows individuals to achieve a homeostatic equilibrium for their nicotine concentration.

An integrative systems-based analysis of substance use: eQTL-informed gene-based tests, gene networks, and biological mechanisms

Genome-wide association studies have identified multiple genetic risk factors underlying susceptibility to substance use, however, the functional genes and biological mechanisms remain poorly understood. The discovery and characterization of risk genes can be facilitated by the integration of genome-wide association data and gene expression data across biologically relevant tissues and/or cell types to identify genes whose expression is altered by DNA sequence variation (expression quantitative trait loci; eQTLs). The integration of gene expression data can be extended to the study of genetic co-expression, under the biologically valid assumption that genes form co-expression networks to influence the manifestation of a disease or trait. Here, we integrate genome-wide association data with gene expression data from 13 brain tissues to identify candidate risk genes for 8 substance use phenotypes. We then test for the enrichment of candidate risk genes within tissue-specific gene co-expression networks to identify modules (or groups) of functionally related genes whose dysregulation is associated with variation in substance use. We identified eight gene modules in brain that were enriched with gene-based association signals for substance use phenotypes. For example, a single module of 40 co-expressed genes was enriched with gene-based associations for drinks per week and biological pathways involved in GABA synthesis, release, reuptake and degradation. Our study demonstrates the utility of eQTL and gene co-expression analysis to uncover novel biological mechanisms for substance use traits.

Alcohol and cigarette smoking consumption as genetic proxies for alcohol misuse and nicotine dependence

PURPOSE

To investigate the role of consumption phenotypes as genetic proxies for alcohol misuse and nicotine dependence.

METHODS

We leveraged GWAS data from well-powered studies of consumption, alcohol misuse, and nicotine dependence phenotypes measured in individuals of European ancestry from the UK Biobank (UKB) and other population-based cohorts (largest total N = 263,954), and performed genetic correlations within a medical-center cohort, BioVU (N = 66,915). For alcohol, we used quantitative measures of consumption and misuse via AUDIT from UKB. For smoking, we used cigarettes per day from UKB and non-UKB cohorts comprising the GSCAN consortium, and nicotine dependence via ICD codes from UKB and Fagerström Test for Nicotine Dependence from non-UKB cohorts.

RESULTS

In a large phenome-wide association study, we show that smoking consumption and dependence phenotypes show similar strongly negatively associations with a plethora of diseases, whereas alcohol consumption shows patterns of genetic association that diverge from those of alcohol misuse.

CONCLUSIONS

Our study suggests that cigarette smoking consumption, which can be easily measured in the general population, may be good a genetic proxy for nicotine dependence, whereas alcohol consumption is not a direct genetic proxy of alcohol misuse.

Revision of the Wisconsin Smoking Withdrawal Scale: Development of brief and long forms

The assessment of tobacco withdrawal is important for both research and clinical purposes. This study describes the psychometric development of a revised version of the 28-item Wisconsin Smoking Withdrawal Scale (WSWS; Welsch et al., Experimental and Clinical Psychopharmacology, 1999, 7, p. 354). Because the different contexts of use sometimes permit only brief assessment, this revision has produced both a brief and longer form using an updated pool of candidate items. For the revised Wisconsin Smoking Withdrawal Scale 2 (WSWS2), a candidate pool of 37 items was developed to measure nine putative withdrawal constructs. The stem and wording of items were revised as was the response scale. Data for psychometric analyses were derived from three smoking cessation randomized clinical trials conducted at the University of Wisconsin Center for Tobacco Research and Intervention. Dimensionality, internal consistency, and item characteristic analyses of the candidate items were conducted in a derivation sample to ascertain the factor structure and to identify items that could be used in the WSWS2 scales. Confirmatory factor analyses (CFAs) of reduced item sets and factor structure were conducted in two validation samples along with reliability and validity analyses. Derivation and validation sample analyses yielded a longer version of the WSWS2 (WSWS2-L) with 19 items and six subscales (Craving, Negative Affect, Hunger, Sleep, Restlessness, and Concentration) and a brief 6-item version (WSWS2-B). In validation sample analyses, both the WSWS2-L and the WSWS2-B demonstrated good reliability and validity as well as good fit in CFAs. The WSWS2-L and WSWS2-B possess improved construct coverage, fewer items, and other enhancements relative to the WSWS. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Genomic relationships across psychiatric disorders including substance use disorders

BACKGROUND

A recent study investigated the genetic associations and latent genetic structure among eight psychiatric disorders using findings from genome-wide association studies (GWASs). No data from substance use disorders were included, while these represent an important category of mental disorders and could influence the latent genetic structure. We extended the original paper by recreating the genetic relationship matrix, graph, and latent genetic factor structure, including additional data from substance use disorders.

METHODS

We used GWAS summary statistics of 11 psychiatric disorders, including alcohol dependence, nicotine dependence, and cannabis use disorder. We estimated genetic correlations between all traits in Linkage Disequilibrium-Score Regression. A graph was created to illustrate the network of genetic correlations. We then used the genetic relationships to model a latent genetic factor structure.

RESULTS

Alcohol and nicotine dependence showed significant genetic correlations with several other psychiatric disorders, including ADHD, schizophrenia, and major depression. Cannabis use disorder was only significantly associated with ADHD. The addition of substance use disorders resulted in some changes in the latent structure of the factor model when compared to the original model including eight disorders. All substance use disorders contributed mostly to Factor 3, a heterogeneous factor with also loadings from ADHD, major depression, Autism Spectrum Disorders, and Tourette Syndrome.

CONCLUSIONS

Alcohol and nicotine dependence show widespread genetic correlations with other psychiatric disorders. Including substance use disorders in the factor analysis results in some changes in the underlying genetic factor structure. Given the instability of such models, identified structures should be interpreted with caution.

RNA splicing and aggregate gene expression differences in lung squamous cell carcinoma between patients of West African and European ancestry

OBJECTIVES

Despite disparities in lung cancer incidence and mortality, the molecular landscape of lung cancer in patients of African ancestry remains underexplored, and race-related differences in RNA splicing remain unexplored.

MATERIALS AND METHODS

We identified differentially spliced genes (DSGs) and differentially expressed genes (DEGs) in biobanked lung squamous cell carcinoma (LUSC) between patients of West African and European ancestry, using ancestral genotyping and Affymetrix Clariom D array. DSGs and DEGs were validated independently using the National Cancer Institute Genomic Data Commons. Associated biological processes, overlapping canonical pathways, enriched gene sets, and cancer relevance were identified using Gene Ontology Consortium, Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, and CancerMine, respectively. Association with LUSC survival was conducted using The Cancer Genome Atlas.

RESULTS

4,829 DSGs and 267 DEGs were identified, including novel targets in NSCLC as well as genes identified previously to have relevance to NSCLC. RNA splicing events within 3 DSGs as well as 1 DEG were validated in the independent cohort. 853 DSGs and 29 DEGs have been implicated as potential drivers, oncogenes and/or tumor suppressor genes. Biological processes enriched among DSGs and DEGs included metabolic process, biological regulation, and multicellular organismal process and, among DSGs, ion transport. Overlapping canonical pathways among DSGs included neuronal signaling pathways and, among DEGs, cell metabolism involving biosynthesis. Gene sets enriched among DSGs included KRAS Signaling, UV Response, E2 F Targets, Glycolysis, and Coagulation. 355 RNA splicing events within DSGs and 18 DEGs show potential association with LUSC patient survival.

CONCLUSION

These DSGs and DEGs, which show potential biological and clinical relevance, could have the ability to drive novel biomarker and therapeutic development to mitigate LUSC disparities.

Preadult polytoxicomania-strong environmental underpinnings and first genetic hints

Considering the immense societal and personal costs and suffering associated with multiple drug use or "polytoxicomania", better understanding of environmental and genetic causes is crucial. While previous studies focused on single risk factors and selected drugs, effects of early-accumulated environmental risks on polytoxicomania were never addressed. Similarly, evidence of genetic susceptibility to particular drugs is abundant, while genetic predisposition to polytoxicomania is unexplored. We exploited the GRAS data collection, comprising information on N~2000 deep-phenotyped schizophrenia patients, to investigate effects of early-life environmental risk accumulation on polytoxicomania and additionally provide first genetic insight. Preadult accumulation of environmental risks (physical or sexual abuse, urbanicity, migration, cannabis, alcohol) was strongly associated with lifetime polytoxicomania (p  = 1.5 × 10^-45; OR = 31.4), preadult polytoxicomania with OR = 226.6 (p = 1.0 × 10^-33) and adult polytoxicomania with OR = 17.5 (p = 3.4 × 10^-24). Parallel accessibility of genetic data from GRAS patients and N~2100 controls for genome-wide association (GWAS) and phenotype-based genetic association studies (PGAS) permitted the creation of a novel multiple GWAS-PGAS approach. This approach yielded 41 intuitively interesting SNPs, potentially conferring liability to preadult polytoxicomania, which await replication upon availability of suitable deep-phenotyped cohorts anywhere world-wide. Concisely, juvenile environmental risk accumulation, including cannabis and alcohol as starter/gateway drugs, strongly predicts polytoxicomania during adolescence and adulthood. This pivotal message should launch more effective sociopolitical measures to prevent this deleterious psychiatric condition.

A large-scale genome-wide association study meta-analysis of cannabis use disorder

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.

FUNDING

National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits

Cigarette smoking is the leading cause of preventable morbidity and mortality. Genetic variation contributes to initiation, regular smoking, nicotine dependence, and cessation. We present a Fagerström Test for Nicotine Dependence (FTND)-based genome-wide association study in 58,000 European or African ancestry smokers. We observe five genome-wide significant loci, including previously unreported loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416), and extend loci reported for other smoking traits to nicotine dependence. Using the heaviness of smoking index from UK Biobank (N = 33,791), rs2714700 is consistently associated; rs1862416 is not associated, likely reflecting nicotine dependence features not captured by the heaviness of smoking index. Both variants influence nearby gene expression (rs2714700/MAGI2-AS3 in hippocampus; rs1862416/TENM2 in lung), and expression of genes spanning nicotine dependence-associated variants is enriched in cerebellum. Nicotine dependence (SNP-based heritability = 8.6%) is genetically correlated with 18 other smoking traits (rg = 0.40-1.09) and co-morbidities. Our results highlight nicotine dependence-specific loci, emphasizing the FTND as a composite phenotype that expands genetic knowledge of smoking.

Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals

Here we report a large genome-wide association study (GWAS) for longitudinal smoking phenotypes in 286,118 individuals from the Million Veteran Program (MVP) where we identified 18 loci for smoking trajectory of current versus never in European Americans, one locus in African Americans, and one in Hispanic Americans. Functional annotations prioritized several dozen genes where significant loci co-localized with either expression quantitative trait loci or chromatin interactions. The smoking trajectories were genetically correlated with 209 complex traits, for 33 of which smoking was either a causal or a consequential factor. We also performed European-ancestry meta-analyses for smoking status in the MVP and GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN) (N_total = 842,717) and identified 99 loci for smoking initiation and 13 loci for smoking cessation. Overall, this large GWAS of longitudinal smoking phenotype in multiple populations, combined with a meta-GWAS for smoking status, adds new insights into the genetic vulnerability for smoking behavior.

Genome-wide association studies (GWASs) for cigarette smoking have identified several hundred loci that account for a small proportion of the overall genetic risk. Here, the authors report a large GWAS for smoking trajectories and meta-analysis for smoking status, finding multiple plausible loci.

An update on the role of common genetic variation underlying substance use disorders

PURPOSE OF THE REVIEW

Sample size increases have resulted in novel and replicable loci for substance use disorders (SUDs). We summarize some of the latest insights into SUD genetics and discuss some next steps in addiction genetics.

RECENT FINDINGS

Genome-wide association studies have substantiated the role of previously known variants (e.g., rs1229984 in ADH1B for alcohol) and identified several novel loci for alcohol, tobacco, cannabis, opioid and cocaine use disorders. SUDs are genetically correlated with psychiatric outcomes, while liability to substance use is inconsistently associated with these outcomes and more closely associated with lifestyle factors. Specific variant associations appear to differ somewhat across populations, although similar genes and systems are implicated.

SUMMARY

The next decade of human genetic studies of addiction should focus on expanding to non-European populations, consider pleiotropy across SUD and with other psychiatric disorders, and leverage human and cross-species functional data to elucidate the biological mechanisms underlying SUDs.

Heterogeneity and Polygenicity in Psychiatric Disorders: A Genome-Wide Perspective

Genome-wide association studies (GWAS) have been performed for many psychiatric disorders and revealed a complex polygenic architecture linking mental and physical health phenotypes. Psychiatric diagnoses are often heterogeneous, and several layers of trait heterogeneity may contribute to detection of genetic risks per disorder or across multiple disorders. In this review, we discuss these heterogeneities and their consequences on the discovery of risk loci using large-scale genetic data. We primarily highlight the ways in which sex and diagnostic complexity contribute to risk locus discovery in schizophrenia, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, posttraumatic stress disorder, major depressive disorder, obsessive-compulsive disorder, Tourette’s syndrome and chronic tic disorder, anxiety disorders, suicidality, feeding and eating disorders, and substance use disorders. Genetic data also have facilitated discovery of clinically relevant subphenotypes also described here. Collectively, GWAS of psychiatric disorders revealed that the understanding of heterogeneity, polygenicity, and pleiotropy is critical to translate genetic findings into treatment strategies.

The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico

Pharmacogenetic analysis has generated translational data that could be applied to guide treatments according to individual genetic variations. However, pharmacogenetic counseling in some mestizo (admixed) populations may require tailoring to different patterns of admixture. The identification and clustering of individuals with related admixture patterns in such populations could help to refine the practice of pharmacogenetic counseling. This study identifies related groups in a highly admixed population-based sample from Mexico, and analyzes the differential distribution of actionable pharmacogenetic variants. A subsample of 1728 individuals from the Mexican Genomic Database for Addiction Research (MxGDAR/Encodat) was analyzed. Genotyping was performed with the commercial PsychArray BeadChip, genome-wide ancestry was estimated using EIGENSOFT, and model-based clustering was applied to defined admixture groups. Actionable pharmacogenetic variants were identified with a query to the Pharmacogenomics Knowledge Base (PharmGKB) database, and functional prediction using the Variant Effect Predictor (VEP). Allele frequencies were compared with chi-square tests and differentiation was estimated by F_ST. Seven admixture groups were identified in Mexico. Some, like Group 1, Group 4, and Group 5, were found exclusively in certain geographic areas. More than 90% of the individuals, in some groups (Group 1, Group 4 and Group 5) were found in the Central-East and Southeast region of the country. MTRR p.I49M, ABCG2 p.Q141K, CHRNA5 p.D398N, SLCO2B1 rs2851069 show a low degree of differentiation between admixture groups. ANKK1 p.G318R and p.H90R, had the lowest allele frequency of Group 1. The reduction in these alleles reduces the risk of toxicity from anticancer and antihypercholesterolemic drugs. Our analysis identified different admixture patterns and described how they could be used to refine the practice of pharmacogenetic counseling for this admixed population.

The effect of genetic variations in the choline acetyltransferase gene (ChAT) on waterpipe tobacco smoking dependence

INTRODUCTION

Waterpipe tobacco smoking (WS) is a popular form of tobacco use, globally. While the impact of genetic variations on smoking behavior has been well-investigated, few studies have examined this issue with regard to WS. In the current study, associations between choline acetyltransferase gene (ChAT) rs1917810 and rs7094248 polymorphisms and WS dependence were examined.

METHODS

Genotyping of rs1917810 and rs7094248 in 266 Jordanian waterpipe smokers was performed using RFLP-PCR. Dependence on WS was measured using the LWDS-10J scale.

RESULTS

The frequency of rs1917810 G allele was 38.5% and that of the rs7094248 G allele was 40.8%. The rs1917810 was significantly associated with the WS dependence level (p<0.05). Carriers of the AA genotype of rs1917810 were more dependent on WS than those with GG genotype (p<0.05). However, no association between rs7094248 single-nucleotide polymorphism (SNP) and dependence on WS was observed (p>0.05).

CONCLUSIONS

The rs1917810 in the ChAT gene might be associated with dependence on WS.

Association of CHRNA5 Gene Variants with Crack Cocaine Addiction

Genome-wide studies provide increasing evidence of association of genetic variants with different behaviors. However, there is a growing need for replication and subsequent characterization of specific findings. In this sense, the CHRNA5 gene has been associated with nicotine (with genome-wide significance), alcohol and cocaine addictions. So far, this gene has not been evaluated in smoked (crack) cocaine. We aimed to analyze the influence of CHRNA5 variants in crack addiction susceptibility and severity. The sample includes 300 crack-addicted patients and 769 non-addicted individuals. The CHRNA5 SNPs evaluated were rs588765, rs16969968, and rs514743. Homozygosity for rs16969968 and rs588765 major alleles was nominally associated with a risk to crack addiction (GG, P = 0.032; CC, P = 0.036, respectively). Haplotype analyses reveal significant associations (rs588765|rs16969968|rs514743 p_{global-corrected} = 7.66 × 10^-5) and suggest a substantial role for rs16969968. These findings corroborate previous reports in cocaine addiction-in line with the expected effects of cocaine in the cholinergic system-and in the opposite direction of significant GWAS findings for nicotine addiction susceptibility. These results are strengthened by the first report of an association of rs588765 with crack addiction and by the haplotype findings. In summary, our study highlights the relevance of the α5 subunit on crack cocaine addiction, replicating previous results relating CHRNA5 with the genetics and pathophysiology of addiction of different drugs.

An association study between methamphetamine use disorder with psychosis and polymorphisms in MiRNA

BACKGROUND

Methamphetamine (MA) is an addictive psychostimulant substance that mainly leads to schizophrenia-like psychotic symptoms. The expression of miRNAs in brain plays an important role in neurological disorders and may affect by genetic variant(s) in the target site (MiRSNPs). In this study, we investigated whether polymorphisms in miRNAs are associated with MA disorder with psychosis.

METHODS

We carried out a case-control association study in 400 MA users with psychotic characters and 448 controls. Six MiRSNPs with predicted functional relevance miRNAs (miR-181b, miR-181a, miR-15b, miR-let-7e and miRlet-7d) were selected for genotyping. Allele and genotype frequencies were compared between MA users and healthy individuals. The expression of five miRNAs were measured by quantitative real-time RT-PCR in 55 cases and 57 controls. We also explored an expression Quantitative Trait Loci (eQTL) analysis based on the miRNAs expression and SNP genotype.

RESULTS

The SNP rs10760371 within miR-181a was nominally associated with MA disorder (P = 0.046). For rs1099308, rs10760371 and rs10993081 in strong linkage disequilibrium (LD), no significant association had been detected from haplotype analysis. Discrepancy had been found between MA users and healthy individuals (P < 0.01) in terms of the expression of miR-181a, miR-15b, miR-let-7e and miR-let-7d. and no noticeable difference had been found from the eQTL analysis.

CONCLUSION

Our findings suggest that rs10760371 within miR-181a may relate to the development of MA dependence with psychosis. The miRNAs expression is unlikely to be regulated by the SNPs within it.

Genome-Wide Association Study of Smoking Behavior Traits in a Chinese Han Population

Tobacco use is one of the leading causes of preventable disease worldwide. Genetic studies have elucidated numerous smoking-associated risk loci in American and European populations. However, genetic determinants for cigarette smoking in Chinese populations are under investigated. In this study, a whole-genome sequencing (WGS)-based genome-wide association study (GWAS) was performed in a Chinese Han population comprising 620 smokers and 564 nonsmokers. Thirteen single-nucleotide polymorphisms (SNPs) of the raftlin lipid linker 1 (RFTN1) gene achieved genome-wide significance levels (P < 5 x 10^-8) for smoking initiation. The rs139753473 from RFTN1 and six other suggestively significant loci from CUB and sushi multiple domains 1 (CSMD1) gene were also associated with cigarettes per day (CPD) in an independent Chinese sample consisting of 1,329 subjects (805 smokers and 524 nonsmokers). When treating males separately, associations between smoking initiation and PCAT5/ANKRD30A, two genes involved in cancer development, were identified and replicated. Within RFTN1, two haplotypes (i.e., C-A-C-G and A-G-T-C) formed by rs796812630-rs796584733-rs796349027-rs879511366 and three haplotypes (i.e., T-T-C-C-C, T-T-A-T-T, and C-A-A-T-T) formed by rs879401109-rs879453873-rs75180423-rs541378415-rs796757175 were strongly associated with smoking initiation. In addition, we also revealed two haplotypes (i.e., C-A-G-G and T-C-T-T derived from rs4875371-rs4875372-rs17070935-rs11991366) in the CSMD1 gene showing a significant association with smoking initiation. Further bioinformatics functional assessment suggested that RFTN1 may participate in smoking behavior through modulating immune responses or interactions with the glucocorticoid receptor alpha and the androgen receptor. Together, our results may help understand the mechanisms underlying smoking behavior in the Chinese Han population.

Prevalence of Some Genetic Risk Factors for Nicotine Dependence in Ukraine

Tobacco smoking is known to be a strong risk factor for developing many diseases. The development and severity of smoking dependence results from interaction of environmental and lifestyle factors, psycho-emotional predispositions, and also from genetic susceptibility. In present study, we investigated polymorphic variants in genes contributed to nicotine dependence, as well as to increased impulsivity, known to be an important risk factor for substance use disorders, in Ukraine population. The genotype frequencies at CYP2A6, DNMT3B, DRD2, HTR2A, COMT, BDNF, GABRA2, CHRNA5, and DAT1 polymorphisms were determined in 171 Ukraine residents, and these data were compared with data for several other European populations and main ethnic groups. It has been found that genotype frequencies for all studied loci are in Hardy-Weinberg equilibrium in the Ukrainian population and correspond to the respective frequencies in European populations. These findings suggest a similar impact of these loci on nicotine dependence in Ukraine. Further studies with larger sample sizes are, however, needed to draw firm conclusions about the effect size of these polymorphisms.

The Older Finnish Twin Cohort - 45 Years of Follow-up

The older Finnish Twin Cohort (FTC) was established in 1974. The baseline survey was in 1975, with two follow-up health surveys in 1981 and 1990. The fourth wave of assessments was done in three parts, with a questionnaire study of twins born during 1945-1957 in 2011-2012, while older twins were interviewed and screened for dementia in two time periods, between 1999 and 2007 for twins born before 1938 and between 2013 and 2017 for twins born in 1938-1944. The content of these wave 4 assessments is described and some initial results are described. In addition, we have invited twin-pairs, based on response to the cohortwide surveys, to participate in detailed in-person studies; these are described briefly together with key results. We also review other projects based on the older FTC and provide information on the biobanking of biosamples and related phenotypes.