Functional characterization of enhancer activity during a long terminal repeat's evolution.

Many transposable elements (TEs) contain transcription factor binding sites and are implicated as potential regulatory elements. However, TEs are rarely functionally tested for regulatory activity, which in turn limits our understanding of how TE regulatory activity has evolved. We systematically tested the human LTR18A subfamily for regulatory activity using massively parallel reporter assay (MPRA) and found AP-1- and CEBP-related binding motifs as drivers of enhancer activity. Functional analysis of evolutionarily reconstructed ancestral sequences revealed that LTR18A elements have generally lost regulatory activity over time through sequence changes, with the largest effects occurring owing to mutations in the AP-1 and CEBP motifs. We observed that the two motifs are conserved at higher rates than expected based on neutral evolution. Finally, we identified LTR18A elements as potential enhancers in the human genome, primarily in epithelial cells. Together, our results provide a model for the origin, evolution, and co-option of TE-derived regulatory elements.

Dissecting the genetic overlap of smoking behaviors, lung cancer, and chronic obstructive pulmonary disease: A focus on nicotinic receptors and nicotine metabolizing enzyme.

Smoking is a major contributor to lung cancer and chronic obstructive pulmonary disease (COPD). Two of the strongest genetic associations of smoking-related phenotypes are the chromosomal regions 15q25.1, encompassing the nicotinic acetylcholine receptor subunit genes CHRNA5-CHRNA3-CHRNB4, and 19q13.2, encompassing the nicotine metabolizing gene CYP2A6. In this study, we examined genetic relations between cigarettes smoked per day, smoking cessation, lung cancer, and COPD. Data consisted of genome-wide association study summary results. Genetic correlations were estimated using linkage disequilibrium score regression software. For each pair of outcomes, z-score-z-score (ZZ) plots were generated. Overall, heavier smoking and decreased smoking cessation showed positive genetic associations with increased lung cancer and COPD risk. The chromosomal region 19q13.2, however, showed a different correlational pattern. For example, the effect allele-C of the sentinel SNP (rs56113850) within CYP2A6 was associated with an increased risk of heavier smoking (z-score = 19.2; p = 1.10 × 10-81 ), lung cancer (z-score = 8.91; p = 5.02 × 10-19 ), and COPD (z-score = 4.04; p = 5.40 × 10-5 ). Surprisingly, this allele-C (rs56113850) was associated with increased smoking cessation (z-score = -8.17; p = 2.52 × 10-26 ). This inverse relationship highlights the need for additional investigation to determine how CYP2A6 variation could increase smoking cessation while also increasing the risk of lung cancer and COPD likely through increased cigarettes smoked per day.

Studying the Utility of Using Genetics to Predict Smoking-Related Outcomes in a Population-Based Study and a Selected Cohort.

INTRODUCTION: The purpose of this study is to examine the predictive utility of polygenic risk scores (PRSs) for smoking behaviors. AIMS AND METHODS: Using summary statistics from the Sequencing Consortium of Alcohol and Nicotine use consortium, we generated PRSs of ever smoking, age of smoking initiation, cigarettes smoked per day, and smoking cessation for participants in the population-based Atherosclerosis Risk in Communities (ARIC) study (N = 8638), and the Collaborative Genetic Study of Nicotine Dependence (COGEND) (N = 1935). The outcomes were ever smoking, age of smoking initiation, heaviness of smoking, and smoking cessation. RESULTS: In the European ancestry cohorts, each PRS was significantly associated with the corresponding smoking behavior outcome. In the ARIC cohort, the PRS z-score for ever smoking predicted smoking (odds ratio [OR]: 1.37; 95% confidence interval [CI]: 1.31, 1.43); the PRS z-score for age of smoking initiation was associated with age of smoking initiation (OR: 0.87; 95% CI: 0.82, 0.92); the PRS z-score for cigarettes per day was associated with heavier smoking (OR: 1.17; 95% CI: 1.11, 1.25); and the PRS z-score for smoking cessation predicted successful cessation (OR: 1.24; 95% CI: 1.17, 1.32). In the African ancestry cohort, the PRSs did not predict smoking behaviors. CONCLUSIONS: Smoking-related PRSs were associated with smoking-related behaviors in European ancestry populations. This improvement in prediction is greatest in the lowest and highest genetic risk categories. The lack of prediction in African ancestry populations highlights the urgent need to increase diversity in research so that scientific advances can be applied to populations other than those of European ancestry. IMPLICATIONS: This study shows that including both genetic ancestry and PRSs in a single model increases the ability to predict smoking behaviors compared with the model including only demographic characteristics. This finding is observed for every smoking-related outcome. Even though adding genetics is more predictive, the demographics alone confer substantial and meaningful predictive power. However, with increasing work in PRSs, the predictive ability will continue to improve.

Review and Consensus on Pharmacogenomic Testing in Psychiatry.

The implementation of pharmacogenomic (PGx) testing in psychiatry remains modest, in part due to divergent perceptions of the quality and completeness of the evidence base and diverse perspectives on the clinical utility of PGx testing among psychiatrists and other healthcare providers. Recognizing the current lack of consensus within the field, the International Society of Psychiatric Genetics assembled a group of experts to conduct a narrative synthesis of the PGx literature, prescribing guidelines, and product labels related to psychotropic medications as well as the key considerations and limitations related to the use of PGx testing in psychiatry. The group concluded that to inform medication selection and dosing of several commonly-used antidepressant and antipsychotic medications, current published evidence, prescribing guidelines, and product labels support the use of PGx testing for 2 cytochrome P450 genes (CYP2D6, CYP2C19). In addition, the evidence supports testing for human leukocyte antigen genes when using the mood stabilizers carbamazepine (HLA-A and HLA-B), oxcarbazepine (HLA-B), and phenytoin (CYP2C9, HLA-B). For valproate, screening for variants in certain genes (POLG, OTC, CSP1) is recommended when a mitochondrial disorder or a urea cycle disorder is suspected. Although barriers to implementing PGx testing remain to be fully resolved, the current trajectory of discovery and innovation in the field suggests these barriers will be overcome and testing will become an important tool in psychiatry.

Variants in the CHRNA5-CHRNA3-CHRNB4 Region of Chromosome 15 Predict Gastrointestinal Adverse Events in the Transdisciplinary Tobacco Use Research Center Smoking Cessation Trial.

INTRODUCTION: Reducing adverse events from pharmacologic treatment is an important goal of precision medicine and identifying genetic predictors of adverse events is a step toward this goal. In 2012, King et al. reported associations between genetic variants and adverse events in a placebo-controlled smoking cessation trial of varenicline and bupropion. Strong associations were found between gastrointestinal adverse events and 11 variants in the CHRNA5-CHRNA3-CHRNB4 region of chromosome 15, a region repeatedly associated with smoking-related phenotypes. Our goal was to replicate, in an independent sample, the impact of variants in the CHRNA5-CHRNA3-CHRNB4 region on gastrointestinal adverse events and to extend the analyses to adherence and smoking cessation. METHODS: The University of Wisconsin Transdisciplinary Tobacco Use Research Center (TTURC) conducted a multiarmed, placebo-controlled smoking cessation trial of bupropion and nicotine replacement therapy that included 985 genotyped European-ancestry participants. We evaluated relationships between our key variables using logistic regression. RESULTS: Gastrointestinal adverse events were experienced by 31.6% TTURC participants. Each of the CHRNA5-CHRNA3-CHRNB4 associations from the King et al. study was found in TTURC, with the same direction of effect. Neither these variants nor the gastrointestinal adverse events themselves were associated with adherence to medication or successful smoking cessation. CONCLUSIONS: Variants in the CHRNA5-CHRNA3-CHRNB4 region of chromosome 15 are associated with gastrointestinal adverse events in smoking cessation. Additional independent variants in this region strengthen the association. The consistency between the results of these two independent studies supports the conclusion that these findings reflect biological response to the use of smoking cessation medication. IMPLICATIONS: The fact that our findings from the TTURC smoking cessation trial support the independent findings of King et al. suggest that associations of variants in the CHRNA5-CHRNA3-CHRNB4 region of chromosome 15 with gastrointestinal adverse events while taking medications for smoking cessation reflect biology. However, although adherence to medication was a strong predictor of successful smoking cessation in TTURC, neither adverse events nor the genetic variants associated with them predicted either adherence or successful cessation in this study. Thus, although we should strive to minimize adverse events during treatment, we should not expect that to increase successful smoking cessation substantially.

E-cigarette Usage Is Associated With Increased Past-12-Month Quit Attempts and Successful Smoking Cessation in Two US Population-Based Surveys.

INTRODUCTION: We examined past-12-month quit attempts and smoking cessation from 2006 to 2016 while accounting for demographic shifts in the US population. In addition, we sought to understand whether the current use of electronic cigarettes was associated with a change in past-12-month quit attempts and successful smoking cessation at the population level. METHODS: We analyzed data from 25- to 44-year-olds from the National Health Interview Survey (NHIS) from 2006 to 2016 (N = 26,354) and the Tobacco Use Supplement to the Current Population Survey (TUS-CPS) in 2006-2007, 2010-2011, and 2014-2015 (N = 33,627). Data on e-cigarette use were available in the 2014-2016 NHIS and 2014-2015 TUS-CPS surveys. RESULTS: Past-12-month quit attempts and smoking cessation increased in recent years compared with 2006. Current e-cigarette use was associated with higher quit attempts (adjusted odds ratio [aOR] = 2.29, 95% confidence interval [CI] = 1.87 to 2.81, p < .001) and greater smoking cessation (aOR = 1.64, 95% CI = 1.21 to 2.21, p = .001) in the NHIS. Multivariable logistic regression of the TUS-CPS data showed that current e-cigarette use was similarly significantly associated with increased past-12-month quit attempts and smoking cessation. Significant interactions were found for smoking frequency (everyday and some-day smoking) and current e-cigarette use for both outcomes (p < .0001) with the strongest positive effects seen in everyday smokers. CONCLUSIONS: Compared with 2006, past-12-month quit attempts and smoking cessation increased among adults aged 25-44 in recent years. Current e-cigarette use was associated with increased past-12-month quit attempts and successful smoking cessation among established smokers. These findings are relevant to future tobacco policy decisions. IMPLICATIONS: E-cigarettes were introduced into the US market over the past decade. During this period, past-12-month quit attempts and smoking cessation have increased among US adults aged 25-44. These trends are inconsistent with the hypothesis that e-cigarette use is delaying quit attempts and leading to decreased smoking cessation. In contrast, current e-cigarette use was associated with significantly higher past-12-month quit attempts and past-12-month cessation. These findings suggest that e-cigarette use contributes to a reduction in combustible cigarette use among established smokers.

The Value of Biosamples in Smoking Cessation Trials: A Review of Genetic, Metabolomic, and Epigenetic Findings.

Introduction: Human genetic research has succeeded in definitively identifying multiple genetic variants associated with risk for nicotine dependence and heavy smoking. To build on these advances, and to aid in reducing the prevalence of smoking and its consequent health harms, the next frontier is to identify genetic predictors of successful smoking cessation and also of the efficacy of smoking cessation treatments ("pharmacogenomics"). More broadly, additional biomarkers that can be quantified from biosamples also promise to aid "Precision Medicine" and the personalization of treatment, both pharmacological and behavioral. Aims and Methods: To motivate ongoing and future efforts, here we review several compelling genetic and biomarker findings related to smoking cessation and treatment. Results: These Key results involve genetic variants in the nicotinic receptor subunit gene CHRNA5, variants in the nicotine metabolism gene CYP2A6, and the nicotine metabolite ratio. We also summarize reports of epigenetic changes related to smoking behavior. Conclusions: The results to date demonstrate the value and utility of data generated from biosamples in clinical treatment trial settings. This article cross-references a companion paper in this issue that provides practical guidance on how to incorporate biosample collection into a planned clinical trial and discusses avenues for harmonizing data and fostering consortium-based, collaborative research on the pharmacogenomics of smoking cessation. Implications: Evidence is emerging that certain genotypes and biomarkers are associated with smoking cessation success and efficacy of smoking cessation treatments. We review key findings that open potential avenues for personalizing smoking cessation treatment according to an individual's genetic or metabolic profile. These results provide important incentive for smoking cessation researchers to collect biosamples and perform genotyping in research studies and clinical trials.

Leveraging Genomic Data in Smoking Cessation Trials in the Era of Precision Medicine: Why and How.

Implications: This article outlines a framework for the consistent integration of biological data/samples into smoking cessation pharmacotherapy trials, aligned with the objectives of the recently unveiled Precision Medicine Initiative. Our goal is to encourage and provide support for treatment researchers to consider biosample collection and genotyping their existing samples as well as integrating genetic analyses into their study design in order to realize precision medicine in treatment of nicotine dependence.

Genome-Wide Association Study of Heavy Smoking and Daily/Nondaily Smoking in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

Introduction: Genetic variants associated with nicotine dependence have previously been identified, primarily in European-ancestry populations. No genome-wide association studies (GWAS) have been reported for smoking behaviors in Hispanics/Latinos in the United States and Latin America, who are of mixed ancestry with European, African, and American Indigenous components. Methods: We examined genetic associations with smoking behaviors in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (N = 12 741 with smoking data, 5119 ever-smokers), using ~2.3 million genotyped variants imputed to the 1000 Genomes Project phase 3. Mixed logistic regression models accounted for population structure, sampling, relatedness, sex, and age. Results: The known region of CHRNA5, which encodes the α5 cholinergic nicotinic receptor subunit, was associated with heavy smoking at genome-wide significance (p ≤ 5 × 10-8) in a comparison of 1929 ever-smokers reporting cigarettes per day (CPD) > 10 versus 3156 reporting CPD ≤ 10. The functional variant rs16969968 in CHRNA5 had a p value of 2.20 × 10-7 and odds ratio (OR) of 1.32 for the minor allele (A); its minor allele frequency was 0.22 overall and similar across Hispanic/Latino background groups (Central American = 0.17; South American = 0.19; Mexican = 0.18; Puerto Rican = 0.22; Cuban = 0.29; Dominican = 0.19). CHRNA4 on chromosome 20 attained p < 10-4, supporting prior findings in non-Hispanics. For nondaily smoking, which is prevalent in Hispanic/Latino smokers, compared to daily smoking, loci on chromosomes 2 and 4 achieved genome-wide significance; replication attempts were limited by small Hispanic/Latino sample sizes. Conclusions: Associations of nicotinic receptor gene variants with smoking, first reported in non-Hispanic European-ancestry populations, generalized to Hispanics/Latinos despite different patterns of smoking behavior. Implications: We conducted the first large-scale genome-wide association study (GWAS) of smoking behavior in a US Hispanic/Latino cohort, and the first GWAS of daily/nondaily smoking in any population. Results show that the region of the nicotinic receptor subunit gene CHRNA5, which in non-Hispanic European-ancestry smokers has been associated with heavy smoking as well as cessation and treatment efficacy, is also significantly associated with heavy smoking in this Hispanic/Latino cohort. The results are an important addition to understanding the impact of genetic variants in understudied Hispanic/Latino smokers.

CYP2A6 metabolism in the development of smoking behaviors in young adults.

Cytochrome P450 2A6 (CYP2A6) encodes the enzyme responsible for the majority of nicotine metabolism. Previous studies support that slow metabolizers smoke fewer cigarettes once nicotine dependent but provide conflicting results on the role of CYP2A6 in the development of dependence. By focusing on the critical period of young adulthood, this study examines the relationship of CYP2A6 variation and smoking milestones. A total of 1209 European American young adults enrolled in the Collaborative Study on the Genetics of Alcoholism were genotyped for CYP2A6 variants to calculate a previously well-validated metric that estimates nicotine metabolism. This metric was not associated with the transition from never smoking to smoking initiation nor with the transition from initiation to daily smoking (P > 0.4). But among young adults who had become daily smokers (n = 506), decreased metabolism was associated with increased risk of nicotine dependence (P = 0.03) (defined as Fagerström Test for Nicotine Dependence score ≥4). This finding was replicated in the Collaborative Genetic Study of Nicotine Dependence with 335 young adult daily smokers (P = 0.02). Secondary meta-analysis indicated that slow metabolizers had a 53 percent increased odds (OR = 1.53, 95 percent CI 1.11-2.11, P = 0.009) of developing nicotine dependence compared with normal metabolizers. Furthermore, secondary analyses examining four-level response of time to first cigarette after waking (>60, 31-60, 6-30, ≤5 minutes) demonstrated a robust effect of the metabolism metric in Collaborative Study on the Genetics of Alcoholism (P = 0.03) and Collaborative Genetic Study of Nicotine Dependence (P = 0.004), illustrating the important role of this measure of dependence. These findings highlight the complex role of CYP2A6 variation across different developmental stages of smoking behaviors.

A multiancestry study identifies novel genetic associations with CHRNA5 methylation in human brain and risk of nicotine dependence.

Nicotine dependence is influenced by chromosome 15q25.1 single nucleotide polymorphisms (SNPs), including the missense SNP rs16969968 that alters function of the α5 nicotinic acetylcholine receptor (CHRNA5) and noncoding SNPs that regulate CHRNA5 mRNA expression. We tested for cis-methylation quantitative trait loci (cis-meQTLs) using SNP genotypes and DNA methylation levels measured across the IREB2-HYKK-PSMA4-CHRNA5-CHRNA3-CHRNB4 genes on chromosome 15q25.1 in the BrainCloud and Brain QTL cohorts [total N = 175 European-Americans and 65 African-Americans (AAs)]. We identified eight SNPs that were significantly associated with CHRNA5 methylation in prefrontal cortex: P ranging from 6.0 × 10(-10) to 5.6 × 10(-5). These SNP-methylation associations were also significant in frontal cortex, temporal cortex and pons: P ranging from 4.8 × 10(-12) to 3.4 × 10(-3). Of the eight cis-meQTL SNPs, only the intronic CHRNB4 SNP rs11636753 was associated with CHRNA5 methylation independently of the known SNP effects in prefrontal cortex, and it was the most significantly associated SNP with nicotine dependence across five independent cohorts (total N = 7858 European ancestry and 3238 AA participants): P = 6.7 × 10(-4), odds ratio (OR) [95% confidence interval (CI)] = 1.11 (1.05-1.18). The rs11636753 major allele (G) was associated with lower CHRNA5 DNA methylation, lower CHRNA5 mRNA expression and increased nicotine dependence risk. Haplotype analyses showed that rs11636753-G and the functional rs16969968-A alleles together increased risk of nicotine dependence more than each variant alone: P = 3.1 × 10(-12), OR (95% CI) = 1.32 (1.22-1.43). Our findings identify a novel regulatory SNP association with nicotine dependence and connect, for the first time, previously observed differences in CHRNA5 mRNA expression and nicotine dependence risk to underlying DNA methylation differences.

KAT2B polymorphism identified for drug abuse in African Americans with regulatory links to drug abuse pathways in human prefrontal cortex.

Drug abuse is a common and heritable set of disorders, but the underlying genetic factors are largely unknown. We conducted genome-wide association studies of drug abuse using 7 million imputed single nucleotide polymorphisms (SNPs) and insertions/deletions in African Americans (AAs; n = 3742) and European Americans (EAs; n = 6845). Cases were drawn from the Urban Health Study of street-recruited people, who injected drugs and reported abusing opioids, cocaine, marijuana, stimulants and/or other drugs 10 or more times in the past 30 days, and were compared with population controls. Independent replication testing was conducted in 755 AAs and 1131 EAs from the Genetic Association Information Network. An intronic SNP (rs9829896) in the K(lysine) acetyltransferase 2B (KAT2B) gene was significantly associated with drug abuse in AAs (P = 4.63 × 10-8 ) and independently replicated in AAs (P = 0.0019). The rs9829896-C allele (frequency = 12%) had odds ratios of 0.68 and 0.53 across the AA cohorts: meta-analysis P = 3.93 × 10-10 . Rs9829896-C was not associated with drug abuse across the EA cohorts: frequency = 36% and meta-analysis P = 0.12. Using dorsolateral prefrontal cortex data from the BrainCloud cohort, we found that rs9829896-C was associated with reduced KAT2B expression in AAs (n = 113, P = 0.050) but not EAs (n = 110, P = 0.39). KAT2B encodes a transcriptional regulator in the cyclic adenosine monophosphate and dopamine signaling pathways, and rs9829896-C was associated with expression of genes in these pathways: reduced CREBBP expression (P = 0.011) and increased OPRM1 expression (P = 0.016), both in AAs only. Our study identified the KAT2B SNP rs9829896 as having novel and biologically plausible associations with drug abuse and gene expression in AAs but not EAs, suggesting ancestry-specific effects.

Return of individual genetic results in a high-risk sample: enthusiasm and positive behavioral change.

PURPOSE: The goal of this study was to examine participant responses to disclosure of genetic results in a minority population at high risk for depression and anxiety. METHODS: Eighty-two subjects in a genetic study of nicotine dependence were offered personalized genetic results. All were nicotine-dependent and 64% self-identified as African American. Pathway Genomics was used to evaluate genetic risks for five complex diseases. Participants returned 4-8 weeks after enrollment for in-person genetic counseling interviews and evaluation of baseline measures. A telephone follow-up was performed 4-8 weeks later to assess responses to results. RESULTS: Fifty of the 82 subjects (61%) were interested in receiving genetic results. These participants had multiple risk factors, including high baseline measures of depression (66%) and anxiety (32%), as well as low rates of employment (46%), adequate health literacy (46%), and health insurance (45%). Pathway Genomics reported "increased risk" for at least one disease in 77% of subjects. Ninety-five percent of participants reported that they appreciated the genetic results, and receiving these results was not associated with changes in symptoms of depression or anxiety. Furthermore, after return of genetic results, smoking cessation attempts increased (P = 0.003). CONCLUSION: Even in an underserved population at high risk for adverse psychological reactions, subjects responded positively to personalized genetic results.

Interpreting joint SNP analysis results: when are two distinct signals really two distinct signals?

In genetic association studies, much effort has focused on moving beyond the initial single-nucleotide polymorphism (SNP)-by-SNP analysis. One approach is to reanalyze a chromosomal region where an association has been detected, jointly analyzing the SNP thought to best represent that association with each additional SNP in the region. Such joint analyses may help identify additional, statistically independent association signals. However, it is possible for a single genetic effect to produce joint SNP results that would typically be interpreted as two distinct effects (e.g., both SNPs are significant in the joint model). We present a general approach that can (1) identify conditions under which a single variant could produce a given joint SNP result, and (2) use these conditions to identify variants from a list of known SNPs (e.g., 1000 Genomes) as candidates that could produce the observed signal. We apply this method to our previously reported joint result for smoking involving rs16969968 and rs588765 in CHRNA5. We demonstrate that it is theoretically possible for a joint SNP result suggestive of two independent signals to be produced by a single causal variant. Furthermore, this variant need not be highly correlated with the two tested SNPs or have a large odds ratio. Our method aids in interpretation of joint SNP results by identifying new candidate variants for biological causation that would be missed by traditional approaches. Also, it can connect association findings that may seem disparate due to lack of high correlations among the associated SNPs.

Distinct loci in the CHRNA5/CHRNA3/CHRNB4 gene cluster are associated with onset of regular smoking.

Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotype.

Environmental and genetic risk factors associated with total knee arthroplasty following cruciate ligament surgery.

Aims: The purpose of this study is to determine an individual's age-specific prevalence of total knee arthroplasty (TKA) after cruciate ligament surgery, and to identify clinical and genetic risk factors associated with undergoing TKA. Methods: This study was a retrospective case-control study using the UK Biobank to identify individuals reporting a history of cruciate ligament surgery. Data from verbal history and procedural codes recorded through the NHS were used to identify instances of TKA. Patient clinical and genetic data were used to identify risk factors for progression from cruciate ligament surgery to TKA. Individuals without a history of cruciate ligament reconstruction were used for comparison. Results: A total of 2,576 individuals with a history of cruciate ligament surgery were identified, with 290 (11.25%) undergoing TKA. In patients with prior cruciate ligament surgery, prevalence of TKA was 0.75% at age 45 years, 9.10% at age 65 years, and 20.43% at age 80 years. Patients with prior cruciate ligament surgery were 4.6 times more likely to have undergone TKA by age 55 years than individuals without prior cruciate ligament surgery. In the cruciate ligament surgery cohort, BMI > 30 kg/m2 (odds ratio (OR) 4.01 (95% confidence interval (CI) 2.74 to 5.87)), a job that always involved heavy manual or physical labour (OR 2.72 (95% CI 1.57 to 4.71)), or a job that always involved walking and standing (OR 2.58 (95% CI 1.58 to 4.20)) were associated with greater TKA odds. No single-nucleotide polymorphism (SNP) was associated with risk of TKA following cruciate ligament surgery. Conclusion: Patients with a history of prior cruciate ligament surgery have substantially higher risk of TKA and undergo arthroplasty at a relatively younger age than individuals without a history of prior cruciate ligament surgery. Physically demanding work and obesity were associated with higher odds of TKA after cruciate ligament surgery, but no SNP was associated with risk of TKA.

Factors associated with genetic markers for rotator cuff disease in patients with atraumatic rotator cuff tears.

For atraumatic rotator cuff tears, genetics contributes to symptomatic tear risk and may influence rotator cuff healing after surgical repair. But little is known about how genetic factors influence rotator cuff tear patient characteristics at presentation. We collected saliva samples for genotyping from atraumatic rotator cuff tear patients. We examined nine single nucleotide polymorphisms (SNPs) associated with cuff tears in prior literature. We estimated associations of SNP dosage with (1) age at tear diagnosis, (2) bilateral atraumatic tear prevalence, and (3) tear size. Linear regression was used to estimate associations with diagnosis age adjusted for sex and principal components. Logistic regression and ordinal logistic regression were used to estimate associations with bilateral tear prevalence and tear size category, respectively, adjusting for age, sex, and principal components. Of 344 eligible patients, 336 provided sufficient samples for genotyping. Median age at tear diagnosis was 61, 22% (N = 74) had bilateral atraumatic tears, and 9% (N = 29) had massive tears. SNP rs13107325 in the SLC39A8 gene and rs11850957 in the STXBP6 gene were associated with younger diagnosis age even after accounting for multiple comparisons (rs13107325: -4 years, 95% CI = -6.5, -1.4; rs11850957: -2.7 years, 95% CI = -4.3, -1.1). No other significant associations were observed with diagnosis age, tear size, or bilateral tear prevalence. SLC39A8 encodes a Mn transporter. STXBP6 may play a role in inflammatory responses by altering phagocytosis and antigen presentation of monocytes and macrophages. Further research is needed to determine if genetic markers can be used alongside patient characteristics to aid in identifying optimal surgical repair candidates.

Smoking and genetic risk variation across populations of European, Asian, and African American ancestry--a meta-analysis of chromosome 15q25.

Recent meta-analyses of European ancestry subjects show strong evidence for association between smoking quantity and multiple genetic variants on chromosome 15q25. This meta-analysis extends the examination of association between distinct genes in the CHRNA5-CHRNA3-CHRNB4 region and smoking quantity to Asian and African American populations to confirm and refine specific reported associations. Association results for a dichotomized cigarettes smoked per day phenotype in 27 datasets (European ancestry (N = 14,786), Asian (N = 6,889), and African American (N = 10,912) for a total of 32,587 smokers) were meta-analyzed by population and results were compared across all three populations. We demonstrate association between smoking quantity and markers in the chromosome 15q25 region across all three populations, and narrow the region of association. Of the variants tested, only rs16969968 is associated with smoking (P < 0.01) in each of these three populations (odds ratio [OR] = 1.33, 95% CI = 1.25-1.42, P = 1.1 × 10(-17) in meta-analysis across all population samples). Additional variants displayed a consistent signal in both European ancestry and Asian datasets, but not in African Americans. The observed consistent association of rs16969968 with heavy smoking across multiple populations, combined with its known biological significance, suggests rs16969968 is most likely a functional variant that alters risk for heavy smoking. We interpret additional association results that differ across populations as providing evidence for additional functional variants, but we are unable to further localize the source of this association. Using the cross-population study paradigm provides valuable insights to narrow regions of interest and inform future biological experiments.

Imputation across genotyping arrays for genome-wide association studies: assessment of bias and a correction strategy.

A great promise of publicly sharing genome-wide association data is the potential to create composite sets of controls. However, studies often use different genotyping arrays, and imputation to a common set of SNPs has shown substantial bias: a problem which has no broadly applicable solution. Based on the idea that using differing genotyped SNP sets as inputs creates differential imputation errors and thus bias in the composite set of controls, we examined the degree to which each of the following occurs: (1) imputation based on the union of genotyped SNPs (i.e., SNPs available on one or more arrays) results in bias, as evidenced by spurious associations (type 1 error) between imputed genotypes and arbitrarily assigned case/control status; (2) imputation based on the intersection of genotyped SNPs (i.e., SNPs available on all arrays) does not evidence such bias; and (3) imputation quality varies by the size of the intersection of genotyped SNP sets. Imputations were conducted in European Americans and African Americans with reference to HapMap phase II and III data. Imputation based on the union of genotyped SNPs across the Illumina 1M and 550v3 arrays showed spurious associations for 0.2 % of SNPs: ~2,000 false positives per million SNPs imputed. Biases remained problematic for very similar arrays (550v1 vs. 550v3) and were substantial for dissimilar arrays (Illumina 1M vs. Affymetrix 6.0). In all instances, imputing based on the intersection of genotyped SNPs (as few as 30 % of the total SNPs genotyped) eliminated such bias while still achieving good imputation quality.

Protocol for a collaborative meta-analysis of 5-HTTLPR, stress, and depression.

BACKGROUND: Debate is ongoing about what role, if any, variation in the serotonin transporter linked polymorphic region (5-HTTLPR) plays in depression. Some studies report an interaction between 5-HTTLPR variation and stressful life events affecting the risk for depression, others report a main effect of 5-HTTLPR variation on depression, while others find no evidence for either a main or interaction effect. Meta-analyses of multiple studies have also reached differing conclusions. METHODS/DESIGN: To improve understanding of the combined roles of 5-HTTLPR variation and stress in the development of depression, we are conducting a meta-analysis of multiple independent datasets. This coordinated approach utilizes new analyses performed with centrally-developed, standardized scripts. This publication documents the protocol for this collaborative, consortium-based meta-analysis of 5-HTTLPR variation, stress, and depression. STUDY ELIGIBILITY CRITERIA: Our goal is to invite all datasets, published or unpublished, with 5-HTTLPR genotype and assessments of stress and depression for at least 300 subjects. This inclusive approach is to minimize potential impact from publication bias. DATA SOURCES: This project currently includes investigators from 35 independent groups, providing data on at least N = 33,761 participants.The analytic plan was determined prior to starting data analysis. Analyses of individual study datasets will be performed by the investigators who collected the data using centrally-developed standardized analysis scripts to ensure a consistent analytical approach across sites. The consortium as a group will review and interpret the meta-analysis results. DISCUSSION: Variation in 5-HTTLPR is hypothesized to moderate the response to stress on depression. To test specific hypotheses about the role of 5-HTTLPR variation on depression, we will perform coordinated meta-analyses of de novo results obtained from all available data, using variables and analyses determined a priori. Primary analyses, based on the original 2003 report by Caspi and colleagues of a GxE interaction will be supplemented by secondary analyses to help interpret and clarify issues ranging from the mechanism of effect to heterogeneity among the contributing studies. Publication of this protocol serves to protect this project from biased reporting and to improve the ability of readers to interpret the results of this specific meta-analysis upon its completion.