Genomic Insights for Personalized Care: Motivating At-Risk Individuals Toward Evidence-Based Health Practices.

Lung cancer and tobacco use pose significant global health challenges and require a comprehensive translational roadmap for improved prevention strategies. We propose the GREAT care paradigm ( G enomic Informed Care for Motivating High R isk Individuals E ligible for Evidence-b a sed Prevention), which employs polygenic risk scores (PRSs) to stratify disease risk and personalize interventions, such as lung cancer screening and tobacco treatment. We developed PRSs using large-scale multi-ancestry genome-wide association studies and adjusted for genetic ancestry for standardized risk stratification across diverse populations. We applied our PRSs to over 340,000 individuals of diverse ethnic background and found significant odds ratios for lung cancer and difficulty quitting smoking. These findings enable the evaluation of PRS-based interventions in ongoing trials aimed at motivating health behavior changes in high-risk patients. This pioneering approach enhances primary care with genomic insights, promising improved outcomes in cancer prevention and tobacco treatment, and is currently under assessment in clinical trials.

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.

In-vivo design feedback and perceived utility of a genetically-informed smoking risk tool among current smokers in the community.

BACKGROUND: The use of genetically-informed personalized risk information for behavioral disorders, namely smoking and smoking-related behaviors, is a promising yet understudied area. The Genetics and Smoking Risk Profile, or RiskProfile, leverages genetic and environmental information to communicate one's risk for smoking-related diseases. Although prior studies have examined attitudes toward genetic results, little research has investigated these perceptions through a lens of in-vivo testing; that is, user-centered design feedback in response to personalized genetic results being returned contemporaneously. This qualitative study engaged current smokers in usability testing of the RiskProfile within the context of concurrently receiving this personalized, genetically-informed smoking cessation intervention. METHODS: Eighty-nine participants who were current smokers responded to open-ended interview questions on perceptions of smoking-related genetic information and the content and format of the RiskProfile intervention that they had received moments before. Data were analyzed via the conventional content analysis approach in which themes were allowed to emerge throughout the analysis. RESULTS: Participants were able to reference and offer design input on specific elements of the RiskProfile. Overall, current smokers perceived the RiskProfile to have high potential utility. Constructive feedback that current smokers offered about the tool centered around suggested improvements to optimize its usability and technical content. CONCLUSIONS: The detailed and constructive feedback from participants highlights that in-vivo feedback offers a useful design approach that addresses concerns of rigor and relevance when returning genetic results. This unique method demonstrated perceived utility and constructive design feedback for the RiskProfile among current smokers and can play an important role in optimizing the design and implementation of personalized genetic risk interventions moving forward.

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.

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.

Estimating Uterine Fibroid SNP-Based Heritability in European American Women with Imaging-Confirmed Fibroids.

BACKGROUND: Heritability estimates (including twin and single nucleotide polymorphism [SNP]-based heritability studies) for fibroids have been inconsistent across prior studies ranging between 9 and 69%. These inconsistencies are due to variations in study design and included populations. A major design issue has been lack of imaging confirmation to identify controls, where asymptomatic women without imaging confirmation may be misclassified as controls leading to an attenuation of heritability estimates. To reconcile the differences in prior heritability estimates and the impact of misclassification of controls on heritability, we determined SNP-based heritability and characterized the genetic architecture of pelvic image-confirmed fibroid cases and controls. METHODS: Analyses were performed among women of European American descent using genome-wide SNP data from BioVU, a clinical database composed of DNA linked to de-identified electronic health records. We estimated the genetic variance explained by all SNPs using Genome-Wide Complex Trait Analysis on imputed data. Fibroid cases and controls were identified using a previously reported phenotyping algorithm that required pelvic imaging confirmation. RESULTS: In total, we used 1,067 image-confirmed fibroid cases and 1,042 image-confirmed fibroid controls. The SNP-based heritability estimate for fibroid risk was h2 = 0.33 ± 0.18 (p = 0.040). We investigated the relationship between heritability per chromosome and chromosome length (r2 < 1%), with chromosome 8 explaining the highest proportion of variance for fibroid risk. There was no enrichment for intergenic or genic SNPs for the fibroid SNP-based heritability. Excluding loci previously associated with fibroid risk from genome-wide association study did not attenuate fibroid heritability suggesting that loci associating with fibroid risk are yet to be discovered. CONCLUSIONS: We observed that fibroid SNP-based heritability was higher than the previous estimate using genome-wide SNP data that relied on self-reported outcomes, but within the range of prior twin pair studies. Furthermore, these data support that imprecise phenotyping can significantly affect the ability to estimate heritability using genotype data.

A Trans-Ethnic Genome-Wide Association Study of Uterine Fibroids.

Uterine fibroids affect up to 77% of women by menopause and account for up to $34 billion in healthcare costs each year. Although fibroid risk is heritable, genetic risk for fibroids is not well understood. We conducted a two-stage case-control meta-analysis of genetic variants in European and African ancestry women with and without fibroids classified by a previously published algorithm requiring pelvic imaging or confirmed diagnosis. Women from seven electronic Medical Records and Genomics (eMERGE) network sites (3,704 imaging-confirmed cases and 5,591 imaging-confirmed controls) and women of African and European ancestry from UK Biobank (UKB, 5,772 cases and 61,457 controls) were included in the discovery genome-wide association study (GWAS) meta-analysis. Variants showing evidence of association in Stage I GWAS (P < 1 × 10-5) were targeted in an independent replication sample of African and European ancestry individuals from the UKB (Stage II) (12,358 cases and 138,477 controls). Logistic regression models were fit with genetic markers imputed to a 1000 Genomes reference and adjusted for principal components for each race- and site-specific dataset, followed by fixed-effects meta-analysis. Final analysis with 21,804 cases and 205,525 controls identified 326 genome-wide significant variants in 11 loci, with three novel loci at chromosome 1q24 (sentinel-SNP rs14361789; P = 4.7 × 10-8), chromosome 16q12.1 (sentinel-SNP rs4785384; P = 1.5 × 10-9) and chromosome 20q13.1 (sentinel-SNP rs6094982; P = 2.6 × 10-8). Our statistically significant findings further support previously reported loci including SNPs near WT1, TNRC6B, SYNE1, BET1L, and CDC42/WNT4. We report evidence of ancestry-specific findings for sentinel-SNP rs10917151 in the CDC42/WNT4 locus (P = 1.76 × 10-24). Ancestry-specific effect-estimates for rs10917151 were in opposite directions (P-Het-between-groups = 0.04) for predominantly African (OR = 0.84) and predominantly European women (OR = 1.16). Genetically-predicted gene expression of several genes including LUZP1 in vagina (P = 4.6 × 10-8), OBFC1 in esophageal mucosa (P = 8.7 × 10-8), NUDT13 in multiple tissues including subcutaneous adipose tissue (P = 3.3 × 10-6), and HEATR3 in skeletal muscle tissue (P = 5.8 × 10-6) were associated with fibroids. The finding for HEATR3 was supported by SNP-based summary Mendelian randomization analysis. Our study suggests that fibroid risk variants act through regulatory mechanisms affecting gene expression and are comprised of alleles that are both ancestry-specific and shared across continental ancestries.

Transethnic and race-stratified genome-wide association study of fibroid characteristics in African American and European American women.

OBJECTIVE: To identify, through genome-wide association studies, genetic loci that associate with differences in fibroid size and number in a population of African American and European American women. DESIGN: Cross-sectional study. SETTING: Not applicable. PATIENT(S): Using BioVU, a clinical population from the Vanderbilt University Medical Center, and the Coronary Artery Risk Development in Young Adults cohort, a prospective cohort, we identified 1520 women (609 African American and 911 European American) with documented fibroid characteristics. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Outcome measurements include volume of largest fibroid, largest fibroid dimension, and number of fibroids (single vs. multiple). RESULT(S): In race-stratified analyses we achieved genome-wide significance at a variant located between MAT2B and TENM2 (rs57542984, ß = 0.13; 95% confidence interval 0.09, 0.17) for analyses of largest fibroid dimension in African Americans. The strongest signal for transethnic analyses was at a variant on 1q31.1 located between PLA2G4A and BRINP3 (rs6605005, ß = 0.24; 95% confidence interval 0.15, 0.33) for fibroid volume. Results from MetaXcan identified an association between predicted expression of the gene ER degradation enhancing alpha-mannosidase like protein 2 (EDEM2) in the thyroid and number of fibroids (Z score = -4.51). CONCLUSION(S): This study identified many novel associations between genetic loci and fibroid size and number in both race-stratified and transethnic analyses. Future studies are necessary to further validate our study findings and to better understand the mechanisms underlying these associations.

Evaluating risk factors for differences in fibroid size and number using a large electronic health record population.

OBJECTIVE: To evaluate individual characteristics of women with fibroids in relation to fibroid size and number. METHODS: This cross-sectional study involved 2302 women (black and white, age range 18-87) with image- or surgery-confirmed fibroids from the Synthetic Derivative, a database of de-identified demographic and clinical information from patient electronic health records (EHRs) from the Vanderbilt University Medical Center. We performed multivariate regression analyses on the following outcomes: volume of largest fibroid, largest dimension of all fibroids, and number of fibroids (single vs multiple). Candidate risk factors included age at diagnosis, body mass index (BMI), race, type 2 diabetes status, and number of living children (a proxy for parity). We assessed potential effect measure modification by race and both age and BMI using a likelihood ratio test. RESULTS: Black race was strongly associated with having multiple fibroids (adjusted odds ratio [aOR]: 1.83, 95% confidence interval [CI]: 1.49, 2.24) and larger fibroid volume (adjusted beta: 1.77, 95% CI: 1.38, 2.27) and greater largest dimension (adjusted beta: 1.28, 95% CI: 1.18, 1.38). Having multiple fibroids was most strongly associated with ages 43-47 (aOR = 3.37, 95% CI: 2.55, 4.46) compared with the youngest age group (ages 18-36). Having a larger number of living children was associated with having single a fibroid (aOR: 0.88, 95% CI: 0.78, 0.99). CONCLUSIONS: Our findings suggest that different underlying etiologies are involved for women developing single versus multiple fibroids and small versus large fibroids. Studies are needed of the mechanisms by which these characteristics influence fibroid formation and growth.

Admixture mapping of uterine fibroid size and number in African American women.

OBJECTIVE: To evaluate the relationship between genetic ancestry and uterine fibroid characteristics. DESIGN: Cross-sectional study. SETTING: Not applicable. PATIENT(S): A total of 609 African American participants with image- or surgery-confirmed fibroids in a biorepository at Vanderbilt University electronic health record biorepository and the Coronary Artery Risk Development in Young Adults studies were included. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Outcome measures include fibroid number (single vs. multiple), volume of largest fibroid, and largest fibroid dimension of all fibroid measurements. RESULT(S): Global ancestry meta-analyses revealed a significant inverse association between percentage of European ancestry and risk of multiple fibroids (odds ratio: 0.78; 95% confidence interval 0.66, 0.93; P=6.05 × 10-3). Local ancestry meta-analyses revealed five suggestive (P<4.80 × 10-3) admixture mapping peaks in 2q14.3-2q21.1, 3p14.2-3p14.1, 7q32.2-7q33, 10q21.1, 14q24.2-14q24.3, for number of fibroids and one suggestive admixture mapping peak (P<1.97 × 10-3) in 10q24.1-10q24.32 for volume of largest fibroid. Single variant association meta-analyses of the strongest associated region from admixture mapping of fibroid number (10q21.1) revealed a strong association at single nucleotide polymorphism variant rs12219990 (odds ratio: 0.41; 95% confidence interval 0.28, 0.60; P=3.82 × 10-6) that was significant after correction for multiple testing. CONCLUSION(S): Increasing African ancestry is associated with multiple fibroids but not with fibroid size. Local ancestry analyses identified several novel genomic regions not previously associated with fibroid number and increasing volume. Future studies are needed to explore the genetic impact that ancestry plays into the development of fibroid characteristics.

Leiomyomas in Pregnancy and Spontaneous Abortion: A Systematic Review and Meta-analysis.

OBJECTIVE: To systematically review studies reporting the risk of spontaneous abortion among pregnant women of typical reproductive potential with and without uterine leiomyomas. DATA SOURCES: We searched PubMed, EMBASE, Web of Science, and ClinicalTrials.gov for publications from January 1970 to December 2016. METHODS OF STUDY SELECTION: We excluded studies that did not use imaging to uniformly document leiomyoma status of all participants, did not have a comparison group without leiomyomas, or primarily included women seeking care for recurrent miscarriage, infertility care, or assisted reproductive technologies. TABULATION, INTEGRATION, AND RESULTS: Two authors independently reviewed eligibility, extracted data, and assigned overall quality ratings based on predetermined criteria. Of 1,469 articles identified, nine were eligible. Five enrolled general obstetric populations and four included women undergoing amniocentesis. In five studies in general obstetric populations that included 21,829 pregnancies (1,394 women with leiomyomas and 20,435 without), only one adjusted for potential confounders. This meta-analysis revealed no increase in risk of spontaneous abortion among those with leiomyomas compared with those without (11.5% compared with 8.0%; risk ratio 1.16, 95% CI 0.80-1.52). When bias from confounding was estimated for nonadjusted studies, the aggregate calculated risk ratio was 0.83 (95% CI 0.68-0.98). CONCLUSION: Leiomyoma presence was not associated with increased risk of spontaneous abortion in an analysis of more than 20,000 pregnant women. Failure of prior studies to adjust for confounders may have led to the common clinical belief that leiomyomas are a risk factor for spontaneous abortion.

An integrative genomics approach for identifying novel functional consequences of PBRM1 truncated mutations in clear cell renal cell carcinoma (ccRCC).

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. Recent large-scale next-generation sequencing analyses reveal that PBRM1 is the second most frequently mutated gene harboring many truncated mutations and has a suspected tumor suppressor role in ccRCC. However, the biological consequences of PBRM1 somatic mutations (e.g., truncated mutations) that drive tumor progression in ccRCC remain unclear. METHODS: In this study, we proposed an integrative genomics approach to explore the functional consequences of PBRM1 truncated mutations in ccRCC by incorporating somatic mutations, mRNA expression, DNA methylation, and microRNA (miRNA) expression profiles from The Cancer Genome Atlas (TCGA). We performed a systematic analysis to detect the differential molecular features in a total of 11 ccRCC samples harboring PBRM1 truncated mutations from the 33 "pan-negative" ccRCC samples. We excluded the samples that had any of the five high-confidence driver genes (VHL, BAP1, SETD2, PTEN and KDM5C) reported in ccRCC to avoid their possible influence in our results. RESULTS: We identified 613 differentially expressed genes (128 up-regulated and 485 down-regulated genes using cutoff |log2FC| > 1 and p < 0.05) in PBRM1 mutated group versus "pan-negative" group. The gene function enrichment analysis revealed that down-regulated genes were significantly enriched in extracellular matrix organization (adjusted p = 2.05 × 10(-7)), cell adhesion (adjusted p = 2.85 × 10(-7)), and ion transport (adjusted p = 9.97 × 10(-6)). Surprisingly, 26 transcriptional factors (TFs) genes including HOXB9, PAX6 and FOXC1 were found to be significantly differentially expressed (23 over expressed TFs and three lower expressed TFs) in PBRM1 mutated group compared with "pan-negative" group. In addition, we identified 1405 differentially methylated CpG sites (targeting 1308 genes, ||log2FC| > 1, p < 0.01) and 185 significantly altered microRNAs (|log2FC| > 1, p < 0.05) associated with truncated PBRM1 mutations. Our integrative analysis suggested that methylation and miRNA alterations were likely the downstream events associated with PBRM1 truncation mutations. CONCLUSIONS: In summary, this study provided some important insights into the understanding of tumorigenesis driven by PBRM1 truncated mutations in ccRCC. The approach may be applied to many driver genes in various cancers.