Epigenome-wide association study of total nicotine equivalents in multiethnic current smokers from three prospective cohorts.

The impact of tobacco exposure on health varies by race and ethnicity and is closely tied to internal nicotine dose, a marker of carcinogen uptake. DNA methylation is strongly responsive to smoking status and may mediate health effects, but study of associations with internal dose is limited. We performed a blood leukocyte epigenome-wide association study (EWAS) of urinary total nicotine equivalents (TNEs; a measure of nicotine uptake) and DNA methylation measured using the MethylationEPIC v1.0 BeadChip (EPIC) in six racial and ethnic groups across three cohort studies. In the Multiethnic Cohort Study (discovery, n = 1994), TNEs were associated with differential methylation at 408 CpG sites across >250 genomic regions (p < 9 × 10-8). The top significant sites were annotated to AHRR, F2RL3, RARA, GPR15, PRSS23, and 2q37.1, all of which had decreasing methylation with increasing TNEs. We identified 45 novel CpG sites, of which 42 were unique to the EPIC array and eight annotated to genes not previously linked with smoking-related DNA methylation. The most significant signal in a novel gene was cg03748458 in MIR383;SGCZ. Fifty-one of the 408 discovery sites were validated in the Singapore Chinese Health Study (n = 340) and the Southern Community Cohort Study (n = 394) (Bonferroni corrected p < 1.23 × 10-4). Significant heterogeneity by race and ethnicity was detected for CpG sites in MYO1G and CYTH1. Furthermore, TNEs significantly mediated the association between cigarettes per day and DNA methylation at 15 sites (average 22.5%-44.3% proportion mediated). Our multiethnic study highlights the transethnic and ethnic-specific methylation associations with internal nicotine dose, a strong predictor of smoking-related morbidities.

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.

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.

Clonal hematopoiesis and risk of prostate cancer in large samples of European ancestry men.

Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk.

Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits.

One mechanism by which genetic factors influence complex traits and diseases is altering gene expression. Direct measurement of gene expression in relevant tissues is rarely tenable; however, genetically regulated gene expression (GReX) can be estimated using prediction models derived from large multi-omic datasets. These approaches have led to the discovery of many gene-trait associations, but whether models derived from predominantly European ancestry (EA) reference panels can map novel associations in ancestrally diverse populations remains unclear. We applied PrediXcan to impute GReX in 51,520 ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) participants (35% African American, 45% Hispanic/Latino, 10% Asian, and 7% Hawaiian) across 25 key cardiometabolic traits and relevant tissues to identify 102 novel associations. We then compared associations in PAGE to those in a random subset of 50,000 White British participants from UK Biobank (UKBB50k) for height and body mass index (BMI). We identified 517 associations across 47 tissues in PAGE but not UKBB50k, demonstrating the importance of diverse samples in identifying trait-associated GReX. We observed that variants used in PrediXcan models were either more or less differentiated across continental-level populations than matched-control variants depending on the specific population reflecting sampling bias. Additionally, variants from identified genes specific to either PAGE or UKBB50k analyses were more ancestrally differentiated than those in genes detected in both analyses, underlining the value of population-specific discoveries. This suggests that while EA-derived transcriptome imputation models can identify new associations in non-EA populations, models derived from closely matched reference panels may yield further insights. Our findings call for more diversity in reference datasets of tissue-specific gene expression.

Increasing risk of hepatocellular carcinoma with successive generations in the United States among Mexican American adults: The Multiethnic Cohort.

BACKGROUND: US-born Latinos have a higher incidence of hepatocellular carcinoma (HCC) than foreign-born Latinos. Acculturation to unhealthy lifestyle behaviors and an immigrant self-selection effect may play a role. In this study, the authors examined the influence of generational status on HCC risk among Mexican American adults. METHODS: The analytic cohort included 31,377 self-reported Mexican Americans from the Multiethnic Cohort Study (MEC). Generational status was categorized as: first-generation (Mexico-born; n = 13,382), second-generation (US-born with one or two parents born in Mexico; n = 13,081), or third-generation (US-born with both parents born in the United States; n = 4914). Multivariable Cox proportional hazards regression was performed to examine the association between generational status and HCC incidence. RESULTS: In total, 213 incident HCC cases were identified during an average follow-up of 19.5 years. After adjusting for lifestyle and neighborhood-level risk factors, second-generation and third-generation Mexican Americans had a 37% (hazard ratio [HR], 1.37; 95% confidence interval [CI], 0.98-1.92) and 66% (HR, 1.66; 95% CI, 1.11-2.49) increased risk of HCC, respectively, compared with first-generation Mexican Americans (p for trend = 0.012). The increased risk associated with generational status was mainly observed in males (second-generation vs. first-generation: HR, 1.60 [95% CI, 1.05-2.44]; third-generation vs. first-generation: HR, 2.08 [95% CI, 1.29-3.37]). CONCLUSIONS: Increasing generational status of Mexican Americans is associated with a higher risk of HCC. Further studies are needed to identify factors that contribute to this increased risk.

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.

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.

Avocado and Guacamole Consumption and Colorectal Cancer Risk: The Multiethnic Cohort Study.

Dietary fiber and phytonutrients can protect against colorectal cancer, yet their consumption is low in the US. Avocados are a potential source of these beneficial nutrients. Therefore, this study aimed to examine the relationship between avocados/guacamole consumption and colorectal cancer risk in the Multiethnic Cohort Study. We assessed avocados/guacamole consumption by using a food frequency questionnaire. We classified participants into three consumer groups: <1 serving/month, 1-3 servings/month, and ≥1 serving/week with one serving defined as ½ avocado or ½ cup. Colorectal cancer cases were ascertained through the Surveillance, Epidemiology and End Results Program cancer registries. Cox proportional hazards models of colorectal cancer were used to calculate hazard ratios and 95% confidence intervals across avocados/guacamole intake groups in each sex overall and by anatomic subsite (i.e., right colon, left colon, and rectum) and race and ethnicity. Of 192,651 eligible participants, 62.8% reported consuming <1 serving/month avocados/guacamole, 26.7% reported 1-3 servings/month, and 10.5% reported ≥1 serving/week. When adjusted for relevant covariates, there was no significant association with incident colorectal cancer overall, for subsites, or within racial and ethnic subgroups (all p for trend ≥ 0.06). In this large prospective cohort study, we did not find that consumption of avocados/guacamole was associated with colorectal cancer risk.

The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians.

Epidemiological studies of obesity, Type-2 diabetes (T2D), cardiovascular diseases and several common cancers have revealed an increased risk in Native Hawaiians compared to European- or Asian-Americans living in the Hawaiian islands. However, there remains a gap in our understanding of the genetic factors that affect the health of Native Hawaiians. To fill this gap, we studied the genetic risk factors at both the chromosomal and sub-chromosomal scales using genome-wide SNP array data on ~4,000 Native Hawaiians from the Multiethnic Cohort. We estimated the genomic proportion of Native Hawaiian ancestry ("global ancestry," which we presumed to be Polynesian in origin), as well as this ancestral component along each chromosome ("local ancestry") and tested their respective association with binary and quantitative cardiometabolic traits. After attempting to adjust for non-genetic covariates evaluated through questionnaires, we found that per 10% increase in global Polynesian genetic ancestry, there is a respective 8.6%, and 11.0% increase in the odds of being diabetic (P = 1.65×10-4) and having heart failure (P = 2.18×10-4), as well as a 0.059 s.d. increase in BMI (P = 1.04×10-10). When testing the association of local Polynesian ancestry with risk of disease or biomarkers, we identified a chr6 region associated with T2D. This association was driven by an uniquely prevalent variant in Polynesian ancestry individuals. However, we could not replicate this finding in an independent Polynesian cohort from Samoa due to the small sample size of the replication cohort. In conclusion, we showed that Polynesian ancestry, which likely capture both genetic and lifestyle risk factors, is associated with an increased risk of obesity, Type-2 diabetes, and heart failure, and that larger cohorts of Polynesian ancestry individuals will be needed to replicate the putative association on chr6 with T2D.

A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: application to BRCA1 and BRCA2.

A large number of variants identified through clinical genetic testing in disease susceptibility genes, are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion), can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analyses of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC), and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity - findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared to classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and pre-formatted excel calculators for implementation of the method for rare variants in BRCA1, BRCA2 and other high-risk genes with known penetrance.

Atopic allergic conditions and prostate cancer risk and survival in the Multiethnic Cohort study.

BACKGROUND: Previous studies investigating relationship between atopic allergic conditions (AACs)-a highly reactive immune state-and prostate cancer (PCa) risk were inconclusive, and few have studied diverse racial/ethnic populations. METHODS: We analysed 74,714 men aged ≥45 years at enrollment in Multiethnic Cohort study. Using multivariable Cox regression, we estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for self-reported AAC status on PCa outcomes. RESULTS: Through 2017, 8697 incident PCa and 1170 related deaths occurred. Twenty-one percent of men reported a history of AACs. AACs were not associated with incident PCa (HR = 0.98, 95% CI: 0.93-1.03) but were significantly inversely associated with PCa mortality (HR = 0.79, 95% CI: 0.67-0.92). This inverse association was consistently observed across all racial/ethnic groups (HR range: 0.60-0.90). Among men diagnosed with PCa, AACs were inversely associated with PCa-specific death (HR = 0.75, 95% CI: 0.63-0.89). Adjusting for potential confounding effect of PSA screening did not meaningfully change the results. No significant heterogeneity was observed in the effect of AACs on PCa incidence or mortality by Dietary Inflammatory Index. CONCLUSIONS: Hyper-allergic conditions were not associated with PCa incidence but were inversely associated with PCa mortality, suggesting a potential role in reducing tumour progression. Further aetiological research is warranted to understand underlying mechanisms.

Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts.

Inadequate representation of non-European ancestry populations in genome-wide association studies (GWAS) has limited opportunities to isolate functional variants. Fine-mapping in multi-ancestry populations should improve the efficiency of prioritizing variants for functional interrogation. To evaluate this hypothesis, we leveraged ancestry architecture to perform comparative GWAS and fine-mapping of obesity-related phenotypes in European ancestry populations from the UK Biobank (UKBB) and multi-ancestry samples from the Population Architecture for Genetic Epidemiology (PAGE) consortium with comparable sample sizes. In the investigated regions with genome-wide significant associations for obesity-related traits, fine-mapping in our ancestrally diverse sample led to 95% and 99% credible sets (CS) with fewer variants than in the European ancestry sample. Lead fine-mapped variants in PAGE regions had higher average coding scores, and higher average posterior probabilities for causality compared to UKBB. Importantly, 99% CS in PAGE loci contained strong expression quantitative trait loci (eQTLs) in adipose tissues or harbored more variants in tighter linkage disequilibrium (LD) with eQTLs. Leveraging ancestrally diverse populations with heterogeneous ancestry architectures, coupled with functional annotation, increased fine-mapping efficiency and performance, and reduced the set of candidate variants for consideration for future functional studies. Significant overlap in genetic causal variants across populations suggests generalizability of genetic mechanisms underpinning obesity-related traits across populations.

Associations of minor histocompatibility antigens with outcomes following allogeneic hematopoietic cell transplantation.

The role of minor histocompatibility antigens (mHAs) in mediating graft versus leukemia and graft versus host disease (GvHD) following allogeneic hematopoietic cell transplantation (alloHCT) is recognized but not well-characterized. By implementing improved methods for mHA prediction in two large patient cohorts, this study aimed to comprehensively explore the role of mHAs in alloHCT by analyzing whether (1) the number of predicted mHAs, or (2) individual mHAs are associated with clinical outcomes. The study population consisted of 2249 donor-recipient pairs treated for acute myeloid leukemia and myelodysplastic syndrome with alloHCT. A Cox proportional hazard model showed that patients with a class I mHA count greater than the population median had an increased hazard of GvHD mortality (hazard ratio [HR] = 1.39, 95% confidence interval [CI] = 1.01, 1.77, p = .046). Competing risk analyses identified the class I mHAs DLRCKYISL (GSTP), WEHGPTSLL (CRISPLD2), and STSPTTNVL (SERPINF2) were associated with increased GVHD mortality (HR = 2.84, 95% CI = 1.52, 5.31, p = .01), decreased leukemia-free survival (LFS) (HR = 1.94, 95% CI = 1.27, 2.95, p = .044), and increased disease-related mortality (DRM) (HR = 2.32, 95% CI = 1.5, 3.6, p = .008), respectively. One class II mHA YQEIAAIPSAGRERQ (TACC2) was associated with increased risk of treatment-related mortality (TRM) (HR = 3.05, 95% CI = 1.75, 5.31, p = .02). WEHGPTSLL and STSPTTNVL were both present within HLA haplotype B*40:01-C*03:04 and showed a positive dose-response relationship with increased all-cause mortality and DRM and decreased LFS, indicating these two mHAs contribute to the risk of mortality in an additive manner. Our study reports the first large-scale investigation of the associations of predicted mHA peptides with clinical outcomes following alloHCT.

Change in the inflammatory potential of diet over 10 years and subsequent mortality: the Multiethnic Cohort Study.

Dietary inflammatory potential assessed by the Dietary Inflammatory Index (DII®) has been associated with health outcomes. However, longitudinal changes in the DII in relation to health outcomes rarely have been studied. This study aimed to examine change in the DII score over 10 years and its association with subsequent mortality in the Multiethnic Cohort. The analysis included 56 263 African American, Japanese American, Latino, Native Hawaiian and White participants who completed baseline (45-75 years) and 10-year follow-up surveys, including a FFQ. Mean energy-adjusted DII (E-DII) decreased over 10 years in men (from -0·85 to -1·61) and women (from -1·80 to -2·47), reflecting changes towards a more anti-inflammatory diet. During an average follow-up of 13·0 years, 16 363 deaths were identified. In multivariable Cox models, compared with anti-inflammatory stable individuals, risk of all-cause mortality was increased with pro-inflammatory change in men (hazard ratio (HR) = 1·13, 95 % CI 1·03, 1·23) and women (HR = 1·22, 95 % CI 1·13, 1·32). Per one-point increase in E-DII score over time, HR was 1·02 (95 % CI 1·00, 1·03) for men and 1·06 (95 % CI 1·04, 1·07) for women (P for heterogeneity < 0·001). While no heterogeneity by race and ethnicity was observed for men, the increased risk per one-point increase among women was stronger in non-Whites than in Whites (P for heterogeneity = 0·004). Our findings suggest that a change towards a more pro-inflammatory diet is associated with an increased risk of mortality both in men and women, and that the association is stronger in women, especially non-White women, than in men.

Modifying effects of race and ethnicity and APOE on the association of physical activity with risk of Alzheimer's disease and related dementias.

INTRODUCTION: We investigated whether the protective association of physical activity with risk of Alzheimer's disease and related dementias (ADRD) has genetic or behavioral variations. METHODS: In the Multiethnic Cohort, we analyzed moderate or vigorous physical activity (MVPA) reported at ages 45 to 75 among 88,047 participants in relation to 13,039 incident diagnoses of late-onset ADRD identified in Medicare claims (1999 to 2014), by five racial and ethnic groups, hours sitting, and in a subset (16%), apolipoprotein E (APOE) genotype. RESULTS: MVPA was inversely associated with ADRD (hazard ratio for ≥14 vs <2.5 hours/week: 0.83, 95% confidence interval [CI]: 0.76 to 0.90 in men; 0.88, 5% CI: 0.81 to 0.95 in women). The association was inverse in all racial and ethnic groups except Black participants (P-heterogeneity = 0.52), but stronger in individuals with lower levels of sitting duration or those who do not carry the APOE e4 risk allele. DISCUSSION: The different effects of physical activity by sitting duration and APOE genotype warrant further research.

Multi-ethnic GWAS and fine-mapping of glycaemic traits identify novel loci in the PAGE Study.

AIMS/HYPOTHESIS: Type 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study. METHODS: We conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci. RESULTS: Four novel associations were identified (p < 5 × 10-9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis. CONCLUSIONS/INTERPRETATION: Our findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations. DATA AVAILABILITY: Full summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog ( https://www.ebi.ac.uk/gwas/downloads/summary-statistics ).

Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci.

BACKGROUND: Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. METHODS: We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. RESULTS: We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. CONCLUSIONS: Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.

PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients.

BACKGROUND: Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors. METHODS: We included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models. RESULTS: The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56-0.74) versus 0.63 (95%PI 0.54-0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34-2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers. CONCLUSIONS: Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.

A transcriptome-wide association study identifies novel candidate susceptibility genes for prostate cancer risk.

A large proportion of heritability for prostate cancer risk remains unknown. Transcriptome-wide association study combined with validation comparing overall levels will help to identify candidate genes potentially playing a role in prostate cancer development. Using data from the Genotype-Tissue Expression Project, we built genetic models to predict normal prostate tissue gene expression using the statistical framework PrediXcan, a modified version of the unified test for molecular signatures and Joint-Tissue Imputation. We applied these prediction models to the genetic data of 79 194 prostate cancer cases and 61 112 controls to investigate the associations of genetically determined gene expression with prostate cancer risk. Focusing on associated genes, we compared their expression in prostate tumor vs normal prostate tissue, compared methylation of CpG sites located at these loci in prostate tumor vs normal tissue, and assessed the correlations between the differentiated genes' expression and the methylation of corresponding CpG sites, by analyzing The Cancer Genome Atlas (TCGA) data. We identified 573 genes showing an association with prostate cancer risk at a false discovery rate (FDR) ≤ 0.05, including 451 novel genes and 122 previously reported genes. Of the 573 genes, 152 showed differential expression in prostate tumor vs normal tissue samples. At loci of 57 genes, 151 CpG sites showed differential methylation in prostate tumor vs normal tissue samples. Of these, 20 CpG sites were correlated with expression of 11 corresponding genes. In this TWAS, we identified novel candidate susceptibility genes for prostate cancer risk, providing new insights into prostate cancer genetics and biology.