Cluster effect for SNP-SNP interaction pairs for predicting complex traits.

Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP-SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP-SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP-SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a hub SNP with a significant main effect and a large minor allele frequency (MAF) tended to have a higher false-positive rate. In addition, peripheral null SNPs in a cluster with a small MAF tended to enhance false positivity. We also demonstrated that using the modified significance criterion based on the 3 p-value rules and the bootstrap approach (3pRule + bootstrap) can reduce false positivity and maintain high true positivity. In addition, our results also showed that a pair without a significant main effect tends to have weak or no interaction. This study identified the cluster effect and suggested using the 3pRule + bootstrap approach to enhance SNP-SNP interaction detection accuracy.

Early Prostate Cancer Deaths Among Men With Higher vs Lower Genetic Risk.

Importance: Prostate cancer, a leading cause of cancer death among men, urgently requires new prevention strategies, which may involve targeting men with an underlying genetic susceptibility. Objective: To explore differences in risk of early prostate cancer death among men with higher vs lower genetic risk to inform prevention efforts. Design, Setting, and Participants: This cohort study used a combined analysis of genotyped men without prostate cancer at inclusion and with lifestyle data in 2 prospective cohort studies in Sweden and the US, the Malmö Diet and Cancer Study (MDCS) and the Health Professionals Follow-Up Study (HPFS), followed up from 1991 to 2019. Data were analyzed between April 2023 and April 2024. Exposures: Men were categorized according to modifiable lifestyle behaviors and genetic risk. A polygenic risk score above the median or a family history of cancer defined men at higher genetic risk (67% of the study population); the remaining men were categorized as being at lower genetic risk. Main Outcomes and Measures: Prostate cancer death analyzed using time-to-event analysis estimating hazard ratios (HR), absolute risks, and preventable deaths by age. Results: Among the 19 607 men included for analysis, the median (IQR) age at inclusion was 59.0 (53.0-64.7) years (MDCS) and 65.1 (58.0-71.8) years (HPFS). During follow-up, 107 early (by age 75 years) and 337 late (after age 75 years) prostate cancer deaths were observed. Compared with men at lower genetic risk, men at higher genetic risk had increased rates of both early (HR, 3.26; 95% CI, 1.82-5.84) and late (HR, 2.26; 95% CI, 1.70-3.01) prostate cancer death, and higher lifetime risks of prostate cancer death (3.1% vs 1.3% [MDCS] and 2.3% vs 0.6% [HPFS]). Men at higher genetic risk accounted for 94 of 107 early prostate cancer deaths (88%), of which 36% (95% CI, 12%-60%) were estimated to be preventable through adherence to behaviors associated with a healthy lifestyle (not smoking, healthy weight, high physical activity, and a healthy diet). Conclusions and Relevance: In this 20-year follow-up study, men with a genetic predisposition accounted for the vast majority of early prostate cancer deaths, of which one-third were estimated to be preventable. This suggests that men at increased genetic risk should be targeted in prostate cancer prevention strategies.

Case-Case Genome-Wide Analyses Identify Subtype-Informative Variants That Confer Risk for Breast Cancer.

Breast cancer includes several subtypes with distinct characteristic biological, pathologic, and clinical features. Elucidating subtype-specific genetic etiology could provide insights into the heterogeneity of breast cancer to facilitate the development of improved prevention and treatment approaches. In this study, we conducted pairwise case-case comparisons among five breast cancer subtypes by applying a case-case genome-wide association study (CC-GWAS) approach to summary statistics data of the Breast Cancer Association Consortium. The approach identified 13 statistically significant loci and eight suggestive loci, the majority of which were identified from comparisons between triple-negative breast cancer (TNBC) and luminal A breast cancer. Associations of lead variants in 12 loci remained statistically significant after accounting for previously reported breast cancer susceptibility variants, among which, two were genome-wide significant. Fine mapping implicated putative functional/causal variants and risk genes at several loci, e.g., 3q26.31/TNFSF10, 8q22.3/NACAP1/GRHL2, and 8q23.3/LINC00536/TRPS1, for TNBC as compared with luminal cancer. Functional investigation further identified rs16867605 at 8q22.3 as a SNP that modulates the enhancer activity of GRHL2. Subtype-informative polygenic risk scores (PRS) were derived, and patients with a high subtype-informative PRS had an up to two-fold increased risk of being diagnosed with TNBC instead of luminal cancers. The CC-GWAS PRS remained statistically significant after adjusting for TNBC PRS derived from traditional case-control GWAS in The Cancer Genome Atlas and the African Ancestry Breast Cancer Genetic Consortium. The CC-GWAS PRS was also associated with overall survival and disease-specific survival among patients with breast cancer. Overall, these findings have advanced our understanding of the genetic etiology of breast cancer subtypes, particularly for TNBC. Significance: The discovery of subtype-informative genetic risk variants for breast cancer advances our understanding of the etiologic heterogeneity of breast cancer, which could accelerate the identification of targets and personalized strategies for prevention and treatment.

Transcriptome-wide association analysis identifies candidate susceptibility genes for prostate-specific antigen levels in men without prostate cancer.

Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide association study (GWAS) summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10 × 10-6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61 × 10-6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses identified 155 statistically significantly (p < 0.05/22,249 = 2.25 × 10-6) genes. Out of 173 unique PSA-associated genes across analyses, we replicated 151 (87.3%) in a TWAS of 209,318 PCa-free individuals from the Million Veteran Program. Based on conditional analyses, we found 20 genes (11 single tissue, nine cross-tissue) that were associated with PSA levels in the discovery TWAS that were not attributable to a lead variant from a GWAS. Ten of these 20 genes replicated, and two of the replicated genes had colocalization probability of >0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine-mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels.

Hierarchical joint analysis of marginal summary statistics-Part II: High-dimensional instrumental analysis of omics data.

Instrumental variable (IV) analysis has been widely applied in epidemiology to infer causal relationships using observational data. Genetic variants can also be viewed as valid IVs in Mendelian randomization and transcriptome-wide association studies. However, most multivariate IV approaches cannot scale to high-throughput experimental data. Here, we leverage the flexibility of our previous work, a hierarchical model that jointly analyzes marginal summary statistics (hJAM), to a scalable framework (SHA-JAM) that can be applied to a large number of intermediates and a large number of correlated genetic variants-situations often encountered in modern experiments leveraging omic technologies. SHA-JAM aims to estimate the conditional effect for high-dimensional risk factors on an outcome by incorporating estimates from association analyses of single-nucleotide polymorphism (SNP)-intermediate or SNP-gene expression as prior information in a hierarchical model. Results from extensive simulation studies demonstrate that SHA-JAM yields a higher area under the receiver operating characteristics curve (AUC), a lower mean-squared error of the estimates, and a much faster computation speed, compared to an existing approach for similar analyses. In two applied examples for prostate cancer, we investigated metabolite and transcriptome associations, respectively, using summary statistics from a GWAS for prostate cancer with more than 140,000 men and high dimensional publicly available summary data for metabolites and transcriptomes.

Genome-wide analysis to assess if heavy alcohol consumption modifies the association between SNPs and pancreatic cancer risk.

BACKGROUND: Pancreatic cancer is a leading cause of cancer-related death globally. Risk factors for pancreatic cancer include common genetic variants and potentially heavy alcohol consumption. We assessed if genetic variants modify the association between heavy alcohol consumption and pancreatic cancer risk. METHODS: We conducted a genome-wide interaction analysis of single nucleotide polymorphisms (SNP) by heavy alcohol consumption (more than 3 drinks per day) for pancreatic cancer in European ancestry populations from genome-wide association studies (GWAS). Our analysis included 3,707 cases and 4,167 controls from case-control studies and 1,098 cases and 1,162 controls from cohort studies. Fixed effect meta-analyses were conducted. RESULTS: A potential novel region of association on 10p11.22, lead SNP rs7898449 (Pinteraction = 5.1 x 10-8 in the meta-analysis, Pinteraction = 2.1x10-9 in the case-control studies, Pinteraction = 0.91 cohort studies) was identified. A SNP correlated with this lead SNP is an eQTL for the NRP1 gene. Of the 17 genomic regions with genome-wide significant evidence of association with pancreatic cancer in prior studies, we observed suggestive evidence that heavy alcohol consumption modified the association for one SNP near LINC00673, rs11655237 on 17q25.1 (Pinteraction = 0.004). CONCLUSIONS: We identified a novel genomic region that may be associated with pancreatic cancer risk in conjunction with heavy alcohol consumption located near an eQTL for the NRP1, a protein that plays an important role in the development and progression of pancreatic cancer Impact: This work can provide insight into the etiology of pancreatic cancer particularly in heavy drinkers.

Diet Quality and Risk of Bladder Cancer in the Multiethnic Cohort Study.

This study analyzed the overall quality of the diet using predefined indices, including the Healthy Eating Index-2015 (HEI-2015), the Alternative Healthy Eating Index-2010 (AHEI-2010), the alternate Mediterranean Diet (aMED) score, the Dietary Approaches to Stop Hypertension (DASH) score, and the Dietary Inflammatory Index (DII®), to explore their association with the risk of bladder cancer in the Multiethnic Cohort Study. Data were taken from 186,979 African American, Japanese American, Latino, Native Hawaiian, and non-Hispanic White participants aged 45-75 years, with 1152 incident cases of invasive bladder cancer during a mean follow-up period of 19.2 ± 6.6 years. Cox models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) with comprehensive adjustment for smoking. Comparing the highest vs. lowest diet quality score quintile, HRs (95% CIs) in men was 1.08 (0.86-1.36) for HEI-2015, 1.05 (0.84-1.30) for AHEI-2010, 1.01 (0.80-1.27) for aMED, 1.13 (0.90-1.41) for DASH, and 0.96 (0.76-1.21) for DII®, whereas the corresponding HRs for women were 0.75 (0.53-1.07), 0.64 (0.45-0.92), 0.60 (0.40-0.88), 0.66 (0.46-0.95), and 0.63 (0.43-0.90) with all p values for trend <0.05. The inverse association found in women did not vary by smoking status or race and ethnicity. Our findings suggest that adopting high-quality diets may reduce the risk of invasive bladder cancer among women in a multiethnic population.

Alcohol intake and endogenous sex hormones in women: Meta-analysis of cohort studies and Mendelian randomization.

BACKGROUND: The mechanisms underlying alcohol-induced breast carcinogenesis are not fully understood but may involve hormonal changes. METHODS: Cross-sectional associations were investigated between self-reported alcohol intake and serum or plasma concentrations of estradiol, estrone, progesterone (in premenopausal women only), testosterone, androstenedione, dehydroepiandrosterone sulfate, and sex hormone binding globulin (SHBG) in 45 431 premenopausal and 173 476 postmenopausal women. Multivariable linear regression was performed separately for UK Biobank, European Prospective Investigation into Cancer and Nutrition, and Endogenous Hormones and Breast Cancer Collaborative Group, and meta-analyzed the results. For testosterone and SHBG, we also conducted Mendelian randomization and colocalization using the ADH1B (alcohol dehydrogenase 1B) variant (rs1229984). RESULTS: Alcohol intake was positively, though weakly, associated with all hormones (except progesterone in premenopausal women), with increments in concentrations per 10 g/day increment in alcohol intake ranging from 1.7% for luteal estradiol to 6.6% for postmenopausal dehydroepiandrosterone sulfate. There was an inverse association of alcohol with SHBG in postmenopausal women but a small positive association in premenopausal women. Two-sample randomization identified positive associations of alcohol intake with total testosterone (difference per 10 g/day increment: 4.1%; 95% CI, 0.6-7.6) and free testosterone (7.8%; 4.1-11.5), and an inverse association with SHBG (-8.1%; -11.3% to -4.9%). Colocalization suggested a shared causal locus at ADH1B between alcohol intake and higher free testosterone and lower SHBG (posterior probability for H4, 0.81 and 0.97, respectively). CONCLUSIONS: Alcohol intake was associated with small increases in sex hormone concentrations, including bioavailable fractions, which may contribute to its effect on breast cancer risk.

Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction.

We performed genome-wide association studies of breast cancer including 18,034 cases and 22,104 controls of African ancestry. Genetic variants at 12 loci were associated with breast cancer risk (P < 5 × 10-8), including associations of a low-frequency missense variant rs61751053 in ARHGEF38 with overall breast cancer (odds ratio (OR) = 1.48) and a common variant rs76664032 at chromosome 2q14.2 with triple-negative breast cancer (TNBC) (OR = 1.30). Approximately 15.4% of cases with TNBC carried six risk alleles in three genome-wide association study-identified TNBC risk variants, with an OR of 4.21 (95% confidence interval = 2.66-7.03) compared with those carrying fewer than two risk alleles. A polygenic risk score (PRS) showed an area under the receiver operating characteristic curve of 0.60 for the prediction of breast cancer risk, which outperformed PRS derived using data from females of European ancestry. Our study markedly increases the population diversity in genetic studies for breast cancer and demonstrates the utility of PRS for risk prediction in females of African ancestry.

Intake of Sugar and Food Sources of Sugar and Colorectal Cancer Risk in the Multiethnic Cohort Study.

BACKGROUND: The influence of sugar intake on the risk of colorectal cancer (CRC) remains controversial, and there is a need to investigate the heterogeneity of effects among racial and ethnic groups. OBJECTIVES: To examine the association of intake of simple sugars and their food sources with CRC risk according to race/ethnicity in a multiethnic cohort study. METHODS: We analyzed data from 192,651 participants who participated in the Multiethnic Cohort Study comprising African American, Japanese American, Latino, Native Hawaiian, and White older adults living in Hawaii and California with an average follow-up of 19 y. Intakes of total and specific types of sugars and sugary foods were estimated from a quantitative food frequency questionnaire completed by the participants in 1993-1996. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for CRC risk according to quintiles (Q) of sugar and food intakes using Cox models adjusted for potential confounders. RESULTS: As of December 2017, 4403 incident CRC cases were identified. Among all participants, multivariable-adjusted CRC HRs for Q2, Q3, Q4, and Q5 compared with Q1 for total sugars were 1.03 (95% CI: 0.94, 1.13), 1.05 (95% CI: 0.96, 1.16), 1.12 (95% CI: 1.01, 1.24), and 1.13 (95% CI: 1.01, 1.27), respectively. A similar positive association was observed for total fructose, glucose, fructose, and maltose but not for added sugars and sugary foods. The increased risk appeared to be limited to colon cancer and to be strongest among younger participants (i.e., 45-54 y at baseline); an association with CRC was observed for sugar-sweetened beverages in the latter group. Among racial and ethnic groups, increased risk of CRC was most apparent in Latinos. CONCLUSIONS: In this diverse cohort, intakes of total sugar, total fructose, glucose, fructose, and maltose were associated with an increased risk of CRC, and the association was strongest for colon cancer, younger participants, and Latinos.

Reproductive Factors and Thyroid Cancer Risk: The Multiethnic Cohort Study.

Background: Women are three times more likely to be diagnosed with thyroid cancer than men, with incidence rates per 100,000 in the United States of 20.2 for women and 7.4 for men. Several reproductive and hormonal factors have been proposed as possible contributors to thyroid cancer risk, including age at menarche, parity, age at menopause, oral contraceptive use, surgical menopause, and menopausal hormone therapy. Our study aimed to investigate potential reproductive/hormonal factors in a multiethnic population. Methods: Risk factors for thyroid cancer were evaluated among female participants (n = 118,344) of the Multiethnic Cohort Study. The cohort was linked to Surveillance, Epidemiology, and End Results cancer incidence and statewide death certificate files in Hawaii and California, with 373 incident papillary thyroid cancer cases identified. Exposures investigated include age at menarche, parity, first pregnancy outcome, birth control use, and menopausal status and type. Multivariable Cox proportional hazards models were used to obtain relative risk (RR) of papillary thyroid cancer and their 95% confidence intervals (CI). Covariates included age, race and ethnicity, reproductive history, body size, smoking, and alcohol consumption. Results: We observed a statistically significant increased risk of papillary thyroid cancer for oophorectomy (adjusted RR 1.58, 95% CI: 1.26, 1.99), hysterectomy (adjusted RR 1.65, 95% CI: 1.33, 2.04), and surgical menopause (adjusted RR 1.55, 95% CI: 1.22, 1.97), and decreased risk for first live birth at ≤20 years of age versus nulliparity (adjusted RR 0.66, 95% CI: 0.46, 0.93). These associations did not vary by race and ethnicity (p het > 0.44). Conclusion: The reproductive risk factors for papillary thyroid cancer reported in the literature were largely confirmed in all racial and ethnic groups in our multiethnic population, which validates uniform obstetric and gynecological practice.

Plant-based dietary patterns and mortality from all causes, cardiovascular disease, and cancer: The Multiethnic Cohort Study.

BACKGROUND & AIMS: Plant-based dietary patterns have been associated with lower risk of cardiovascular disease (CVD), some cancers, and related mortality in U.S. POPULATIONS: However, the quality of plant foods has rarely been considered in the association between plant-based diets and mortality, especially in a population with various racial and ethnic backgrounds. We investigated whether the adherence to plant-based dietary patterns and the healthiness of plant foods are associated with mortality from all causes, CVD, and cancer and evaluated how the association varies by race and ethnicity. METHODS: A total of 144,729 African American, Japanese American, Latino, Native Hawaiian, and White men and women who participated in the Multiethnic Cohort Study (1993-2019) were included. Cox models were used to estimate HR and 95% CI of mortality from all causes, CVD, and cancer across quintiles of three plant-based diet scores: overall plant-based diet index (PDI), healthful plant-based diet index (hPDI), and unhealthful plant-based diet index (uPDI). RESULTS: Over an average 21 years of follow-up, we identified 65,087 deaths, including 18,663 from CVD and 16,171 from cancer. Comparing the highest versus lowest quintiles, greater scores of PDI and hPDI were associated with a lower risk of all-cause mortality in both men (HR = 0.85, 95% CI: 0.82-0.89 for PDI; HR = 0.88, 95% CI: 0.85-0.91 for hPDI; both P for trend <0.0001) and women (HR = 0.89, 95% CI: 0.86-0.93 for PDI; HR = 0.86, 95% CI: 0.83-0.89 for hPDI; both P for trend <0.0001). An increased risk of all-cause mortality with uPDI was observed only in women (HR = 1.11, 95% CI: 1.07-1.15, P for trend <0.0001; P for heterogeneity by sex = 0.019). A similar trend was shown for CVD mortality with a significant increase in risk with uPDI for both men and women. PDI was associated with a lower risk of cancer mortality in men (HR = 0.86, 95% CI: 0.80-0.92, P for trend <0.0001), while neither hPDI nor uPDI was associated in either sex. Compared with the other racial and ethnic groups within each sex, the association of uPDI with all-cause mortality was stronger in White men (P for heterogeneity by race and ethnicity = 0.009) and weaker in Latino women (P for heterogeneity = 0.002). CONCLUSION: A healthy plant-based dietary pattern emphasizing the quality of plant foods was associated with a lower risk of all-cause and CVD mortality in both men and women, although the magnitude of the associations varied across racial and ethnic groups.

Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes.

African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3' UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.

MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups.

Polygenic risk scores (PRSs) are now showing promising predictive performance on a wide variety of complex traits and diseases, but there exists a substantial performance gap across populations. We propose MUSSEL, a method for ancestry-specific polygenic prediction that borrows information in summary statistics from genome-wide association studies (GWASs) across multiple ancestry groups via Bayesian hierarchical modeling and ensemble learning. In our simulation studies and data analyses across four distinct studies, totaling 5.7 million participants with a substantial ancestral diversity, MUSSEL shows promising performance compared to alternatives. For example, MUSSEL has an average gain in prediction R2 across 11 continuous traits of 40.2% and 49.3% compared to PRS-CSx and CT-SLEB, respectively, in the African ancestry population. The best-performing method, however, varies by GWAS sample size, target ancestry, trait architecture, and linkage disequilibrium reference samples; thus, ultimately a combination of methods may be needed to generate the most robust PRSs across diverse populations.

Dietary Fiber Intake and Risk of Advanced and Aggressive Forms of Prostate Cancer: A Pooled Analysis of 15 Prospective Cohort Studies.

BACKGROUND: Evidence of an association between dietary fiber intake and risk of advanced and aggressive forms of prostate cancer (PC) and PC mortality is limited. OBJECTIVE: The aim of this study was to examine associations between intakes of dietary fiber overall and by food source and risk of advanced and aggressive forms of PC. DESIGN: The study design was a pooled analysis of the primary data from 15 cohorts in 3 continents. Baseline dietary fiber intake was assessed using a validated food frequency questionnaire or diet history in each study. PARTICIPANTS/SETTING: There were 842 149 men followed for up to 9 to 22 years between 1985 and 2009 across studies. MAIN OUTCOME MEASURES: The primary outcome measures were advanced (stage T4, N1, or M1 or PC mortality), advanced restricted (excluded men with missing stage and those with localized PC who died of PC), and high-grade PC (Gleason score ≥8 or poorly differentiated/undifferentiated) and PC mortality. STATISTICAL ANALYSIS PERFORMED: Study-specific multivariable hazard ratios (MVHR) were calculated using Cox proportional hazards regression and pooled using random effects models. RESULTS: Intake of dietary fiber overall, from fruits, and from vegetables was not associated with risk of advanced (n = 4863), advanced restricted (n = 2978), or high-grade PC (n = 9673) or PC mortality (n = 3097). Dietary fiber intake from grains was inversely associated with advanced PC (comparing the highest vs lowest quintile, MVHR 0.84; 95% CI 0.76-0.93), advanced restricted PC (MVHR 0.85; 95% CI 0.74-0.97), and PC mortality (MVHR 0.78; 95% CI 0.68-0.89); statistically significant trends were noted for each of these associations (P ≤ .03), and a null association was observed for high-grade PC for the same comparison (MVHR 1.00; 95% CI 0.93-1.07). The comparable results were 1.06 (95% CI 1.01-1.10; P value, test for trend = .002) for localized PC (n = 35,199) and 1.05 (95% CI 0.99-1.11; P value, test for trend = .04) for low/intermediate grade PC (n = 34 366). CONCLUSIONS: Weak nonsignificant associations were observed between total dietary fiber intake and risk of advanced forms of PC, high-grade PC, and PC mortality. High dietary fiber intake from grains was associated with a modestly lower risk of advanced forms of PC and PC mortality.

Disentangling the relationships of body mass index and circulating sex hormone concentrations in mammographic density using Mendelian randomization.

PURPOSE: Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR). METHODS: We applied two-sample MR approaches to assess the association between genetically predicted circulating concentrations of sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG)], BMI, and mammographic density phenotypes (dense and non-dense area). We created instrumental variables from large European ancestry-based genome-wide association studies and applied estimates to mammographic density phenotypes in up to 14,000 women of European ancestry. We performed analyses overall and by menopausal status. RESULTS: Genetically predicted BMI was positively associated with non-dense area (IVW: ß = 1.79; 95% CI = 1.58, 2.00; p = 9.57 × 10-63) and inversely associated with dense area (IVW: ß = - 0.37; 95% CI = - 0.51,- 0.23; p = 4.7 × 10-7). We observed weak evidence for an association of circulating sex hormone concentrations with mammographic density phenotypes, specifically inverse associations between genetically predicted testosterone concentration and dense area (ß = - 0.22; 95% CI = - 0.38, - 0.053; p = 0.009) and between genetically predicted estradiol concentration and non-dense area (ß = - 3.32; 95% CI = - 5.83, - 0.82; p = 0.009), although results were not consistent across a range of MR approaches. CONCLUSION: Our findings support a positive causal association between BMI and mammographic non-dense area and an inverse association between BMI and dense area. Evidence was weaker and inconsistent for a causal effect of circulating sex hormone concentrations on mammographic density phenotypes. Based on our findings, associations between circulating sex hormone concentrations and mammographic density phenotypes are weak at best.

Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction.

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.

Combining magnetic resonance imaging with a multi-ancestry polygenic risk score to improve identification of clinically significant prostate cancer.

Multi-parametric magnetic resonance imaging (mpMRI) has emerged as an important tool for identifying clinically significant prostate cancer. We examined if the addition of a 400-variant multi-ancestry polygenic risk score (PRS) to mpMRI has the potential to improve identification. Based on data from 24 617 men from the Mass General Brigham Biobank, we identified 1243 men who underwent mpMRI. Men in the top PRS quartile were more likely to have clinically significant prostate cancer (47.1% vs 28.6% in the bottom PRS quartile, adjusted relative proportion 1.72 [95% CI = 1.35 to 2.19]). Both among men with a positive and a negative mpMRI, men in the top PRS quartile had the highest frequency of clinically significant cancer. In a constructed scenario for selecting men to undergo biopsy, use of the PRS lowered the frequency of missed clinically significant cancers from 9.1% to 5.9%. Our study provides initial support for using the PRS to improve identification of potentially lethal prostate cancer.

Thyroid Cancer Survival in the Multiethnic Cohort Study.

OBJECTIVE: The US 5-year survival rate after thyroid cancer (TC) diagnosis is over 95%. Our aim was to investigate survival differences by sex and race and ethnicity in a multiethnic US population. DESIGN: In the Multiethnic Cohort (MEC) study, a total of 605 incident TC cases were identified by linkage to HI and CA statewide cancer registries. Cox models were performed to compare the risk of all-cause mortality among TC cases by sex and race and ethnicity, with adjustment for age, first course of treatment, baseline body mass index, smoking status, alcohol intake, and neighborhood socioeconomic status. Survival among cases was also compared to matched MEC controls with no thyroid cancer. RESULTS: After a mean follow-up of 10.1 years, 250 deaths occurred among TC cases, including 63 deaths attributed to thyroid cancer. The median survival was 14.7 years, and the 5-year age-adjusted overall survival was 84.4% for female cases and 68.7% for male cases (p < 0.0001, HR 2.28 (95% CI: 1.72, 3.01)). Age-adjusted survival was lower among African American, Native Hawaiian, and Filipino cases, compared to Japanese American cases, with Whites and Latinos being intermediate. Men and Filipinos were found to have excess mortality due to thyroid cancer compared to controls (adjusted HR 1.39, 95% CI: 1.11, 1.74; HR 1.62, 95% CI: 1.04, 2.53, respectively). CONCLUSIONS: Sex and racial and ethnic disparities in survival among TC cases were similar to those found in the general population. However, cases with TC had an excess risk of death among males and for Filipinos.

Identification of Genes with Rare Loss of Function Variants Associated with Aggressive Prostate Cancer and Survival.

BACKGROUND: Prostate cancer (PrCa) is a substantial cause of mortality among men globally. Rare germline mutations in BRCA2 have been validated robustly as increasing risk of aggressive forms with a poorer prognosis; however, evidence remains less definitive for other genes. OBJECTIVE: To detect genes associated with PrCa aggressiveness, through a pooled analysis of rare variant sequencing data from six previously reported studies in the UK Genetic Prostate Cancer Study (UKGPCS). DESIGN, SETTING, AND PARTICIPANTS: We accumulated a cohort of 6805 PrCa cases, in which a set of ten candidate genes had been sequenced in all samples. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We examined the association between rare putative loss of function (pLOF) variants in each gene and aggressive classification (defined as any of death from PrCa, metastatic disease, stage T4, or both stage T3 and Gleason score ≥8). Secondary analyses examined staging phenotypes individually. Cox proportional hazards modelling and Kaplan-Meier survival analyses were used to further examine the relationship between mutation status and survival. RESULTS AND LIMITATIONS: We observed associations between PrCa aggressiveness and pLOF mutations in ATM, BRCA2, MSH2, and NBN (odds ratio = 2.67-18.9). These four genes and MLH1 were additionally associated with one or more secondary analysis phenotype. Carriers of germline mutations in these genes experienced shorter PrCa-specific survival (hazard ratio = 2.15, 95% confidence interval 1.79-2.59, p = 4 × 10-16) than noncarriers. CONCLUSIONS: This study provides further support that rare pLOF variants in specific genes are likely to increase aggressive PrCa risk and may help define the panel of informative genes for screening and treatment considerations. PATIENT SUMMARY: By combining data from several previous studies, we have been able to enhance knowledge regarding genes in which inherited mutations would be expected to increase the risk of more aggressive PrCa. This may, in the future, aid in the identification of men at an elevated risk of dying from PrCa.