Genome mining of biosynthetic pathways with no identifiable core enzymes can lead to discovery of the so-called unknown (biosynthetic route)-unknown (molecular structure) natural products. Here we focused on a conserved fungal biosynthetic pathway that lacks a canonical core enzyme and used heterologous expression to identify the associated natural product, a highly modified cyclo-arginine-tyrosine dipeptide. Biochemical characterization of the pathway led to identification of a new arginine-containing cyclodipeptide synthase (RCDPS), which was previously annotated as a hypothetical protein and has no sequence homology to non-ribosomal peptide synthetase or bacterial cyclodipeptide synthase. RCDPS homologs are widely encoded in fungal genomes; other members of this family can synthesize diverse cyclo-arginine-Xaa dipeptides, and characterization of a cyclo-arginine-tryptophan RCDPS showed that the enzyme is aminoacyl-tRNA dependent. Further characterization of the biosynthetic pathway led to discovery of new compounds whose structures would not have been predicted without knowledge of RCDPS function.

BACKGROUND: Laboratory studies have indicated that a cholesterol metabolite and selective estrogen receptor modulator, 27-hydroxycholesterol (27HC), may be important in breast cancer etiology and explain associations between obesity and postmenopausal breast cancer risk. Epidemiologic evidence for 27HC in breast cancer risk is limited, particularly in multiethnic populations. METHODS: In a nested case-control study of 1470 breast cancer cases and 1470 matched controls within the Multiethnic Cohort Study, we examined associations of pre-diagnostic circulating 27HC with breast cancer risk among African American, Japanese American, Native Hawaiian, Latino, and non-Latino White postmenopausal females. We used multivariable logistic regression adjusted for age, education, parity, body mass index, and smoking status. Stratified analyses were conducted across racial and ethnic groups, hormone receptor (HR) status, and use of lipid-lowering drugs. We assessed interactions of 27HC with steroid hormones. RESULTS: 27HC levels were inversely related to breast cancer risk (odds ratio [OR] 0.80; 95% confidence interval [CI] 0.58, 1.12), but the association was not statistically significant in the full model. Directions of associations differed by racial and ethnic group. Results suggested an inverse association with HR-negative breast cancer (OR 0.46; 95% CI 0.20, 1.06). 27HC interacted with testosterone, but not estrone, on risk of breast cancer; 27HC was only inversely associated with risk among those with the highest levels of testosterone (OR 0.46; 95% CI 0.24, 0.86). CONCLUSION: This is the first US study to examine circulating 27HC and breast cancer risk and reports a weak inverse association that varies across racial and ethnic groups and testosterone level.

Background

A relatively high proportion of Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females with lung cancer have never smoked. We used an integrative data approach to assemble a large-scale cohort to study lung cancer risk among AANHPIs by smoking status with attention to representation of specific AANHPI ethnic groups.

Methods

We leveraged electronic health records (EHRs) from two healthcare systems-Sutter Health in northern California and Kaiser Permanente Hawai'i-that have high representation of AANHPI populations. We linked EHR data on lung cancer risk factors (i.e., smoking, lung diseases, infections, reproductive factors, and body size) to data on incident lung cancer diagnoses from statewide population-based cancer registries of California and Hawai'i for the period between 2000 and 2013. Geocoded address data were linked to data on neighborhood contextual factors and regional air pollutants.

Results

The dataset comprises over 2.2 million adult females and males of any race/ethnicity. Over 250,000 are AANHPI females (19.6% of the female study population). Smoking status is available for over 95% of individuals. The dataset includes 7,274 lung cancer cases, including 613 cases among AANHPI females. Prevalence of never-smoking status varied greatly among AANHPI females with incident lung cancer, from 85.7% among Asian Indian to 14.4% among Native Hawaiian females.

Conclusion

We have developed a large, multilevel dataset particularly well-suited to conduct prospective studies of lung cancer risk among AANHPI females who never smoked.

Impact

The integrative data approach is an effective way to conduct cancer research assessing multilevel factors on cancer outcomes among small populations.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry^1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific^4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations^11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions¹³-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry^1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific^4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations^11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions¹³-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

Background

A recent genome-wide association study identified single-nucleotide polymorphism (SNP) 2q35-rs13387042 as a marker of susceptibility to estrogen receptor (ER)-positive breast cancer. We attempted to confirm this association using the Breast Cancer Association Consortium.

Methods

2q35-rs13387042 SNP was genotyped for 31 510 women with invasive breast cancer, 1101 women with ductal carcinoma in situ, and 35 969 female control subjects from 25 studies. Odds ratios (ORs) were estimated by logistic regression, adjusted for study. Heterogeneity in odds ratios by each of age, ethnicity, and study was assessed by fitting interaction terms. Heterogeneity by each of invasiveness, family history, bilaterality, and hormone receptor status was assessed by subclassifying case patients and applying polytomous logistic regression. All statistical tests were two-sided.

Results

We found strong evidence of association between rs13387042 and breast cancer in white women of European origin (per-allele OR = 1.12, 95% confidence interval [CI] = 1.09 to 1.15; P(trend) = 1.0 x 10(-19)). The odds ratio was lower than that previously reported (P = .02) and did not vary by age or ethnicity (all P > or = .2). However, it was higher when the analysis was restricted to case patients who were selected for a strong family history (P = .02). An association was observed for both ER-positive (OR = 1.14, 95% CI = 1.10 to 1.17; P = 10(-15)) and ER-negative disease (OR = 1.10, 95% CI = 1.04 to 1.15; P = .0003) and both progesterone receptor (PR)-positive (OR = 1.15, 95% CI = 1.11 to 1.19; P = 5 x 10(-14)) and PR-negative disease (OR = 1.10, 95% CI = 1.06 to 1.15; P = .00002).

Conclusion

The rs13387042 is associated with both ER-positive and ER-negative breast cancer in European women.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury^1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries⁵. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P_interaction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

Background

Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.

Methods

Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.

Results

GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.

Conclusion

Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.