1697-P: Functional Impact of Type 1 Diabetes Risk Variants Identified in African- and European-Ancestry Populations

OBJECTIVEGenetic risk scores (GRSs) for type 1 diabetes (T1D) may assist T1D classification and prediction but are often developed from European populations. To improve health outcomes, it is important to understand the performance and utility of GRSs in diverse ancestry populations.RESEARCH DESIGN AND METHODSWe assessed performance of three previously published T1D GRSs in differentiating people with and without Type 1 diabetes in African (with/without T1D=194/235), European (n=1109/125), and Hispanic (266/170) ancestry populations in the USA, and from Cameroon and Uganda (n=144/5001). The assessed GRSs were developed from European ancestry populations (GRS1, GRS2) and from an African ancestry population (AAGRS).RESULTSThe discriminative power, as measured by the area under the receiver operating characteristic curve (AUC), for GRS2 and AAGRS were equivalent on the African ancestry populations, and both outperformed the GRS1: the AUCs produced by the GRS2, AAGRS and GRS1 on Uganda/Cameroon data were 0.882 (0.845-0.914), 0.874 (0.838-0.907) and 0.816 (0.772-0.857) respectively. GRS2 outperformed the AAGRS and GRS1 on Hispanic and European populations. The GRS2 distributions varied by population, with lower average scores for African populations. If the same GRS2 risk thresholds of 11.5 were set for European and African populations, the sensitivities were 0.91 and 0.53, respectively.CONCLUSIONSThe GRS2 produced similar or improved discriminative power across the populations but the AAGRS matched performance on African ancestry participants with fewer single nucleotide polymorphisms. Varying GRS2 risk thresholds may be required for different populations due to the divergent distributions.

CYP19A1 facilitates the bioconversion of estrogens from androgens. CYP19A1 intron single nucleotide polymorphisms (SNPs) may alter mRNA splicing, resulting in altered CYP19A1 activity, and potentially influencing disease susceptibility. Genetic studies of CYP19A1 SNPs have been well documented in populations of European ancestry; however, studies in populations of African ancestry are limited. In the present study, ten ‘candidate’ intronic SNPs in CYP19A1 from 125 African Americans (AA) and 277 European Americans (EA) were genotyped and their frequencies compared. Allele frequencies were also compared with HapMap and ASW 1000 Genomes populations. We observed significant differences in the minor allele frequencies between AA and EA in six of the ten SNPs including rs10459592 (p<0.0001), rs12908960 (p<0.0001), rs1902584 (p = 0.016), rs2470144 (p<0.0001), rs1961177 (p<0.0001), and rs6493497 (p = 0.003). While there were no significant differences in allele frequencies between EA and CEU in the HapMap population, a 1.2- to 19-fold difference in allele frequency for rs10459592 (p = 0.004), rs12908960 (p = 0.0006), rs1902584 (p<0.0001), rs2470144 (p = 0.0006), rs1961177 (p<0.0001), and rs6493497 (p = 0.0092) was observed between AA and the Yoruba (YRI) population. Linkage disequilibrium (LD) blocks and haplotype clusters that is unique to the EA population but not AA was also observed. In summary, we demonstrate that differences in the allele frequencies of CYP19A1 intron SNPs are not consistent between populations of African and European ancestry. Thus, investigations into whether CYP19A1 intron SNPs contribute to variations in cancer incidence, outcomes and pharmacological response seen in populations of different ancestry may prove beneficial.

Introduction: Screening for type 1 diabetes (T1D) genetic risk in early life can prevent life threatening complications such as diabetic ketoacidosis and allow cost-effective recruitment into intervention and immunotherapy trials. Celiac disease (CD) frequently presents as a comorbidity in those with T1D and shares a strong genetic basis with T1D. Single nucleotide polymorphism (SNP) based genetic risk scores (GRS) for both T1D and CD have shown to be very predictive of future disease but are difficult to generate and typically require SNP array genotyping. We aimed to develop a combined GRS screening panel that could be genotyped from a single dried blood spot at birth. Methods: We developed assays for proxy SNPs of common HLA-DQ haplotypes reported in previous GRS and additional loci from the most recent available genome-wide association studies (GWAS) . We used backwards stepwise regression to identify a subset of variants able to be genotyped with DNA eluted from 800 6mm dried blood spots. We developed and validated neural network models to quantify genetic risk of both T1D and CD using T1DGC and UK Celiac case-control SNP array data, validated in UK Biobank. Assays were developed with LGC Genomics and validated on 675 Seattle area samples. Results: The complete panel consisted of 71 validated SNP assays, including 11 backup variants for key loci. We generated neural nework models which demonstrate equivalent or greater predictive power (AUC: T1D=0.914, CD=0.893) to previously published GRS yet require much less expertise to apply. We have developed an algorithm for preparation of raw genotyping data and subsequent generation of GRS requiring little expertise to apply. Conclusion: A 71 SNP blood-spot screening panel is highly effective at screening genetic risk associated with T1D and CD at birth. Using a neural network model the panel enables widely available, easy to generate and inexpensive population screening of genetic risk for T1D and CD. Disclosure S. A. Sharp: None. J. M. Locke: None. Y. Xu: None. D. P. Fraser: None. L. A. Ferrat: None. M. N. Weedon: None. M. Inouye: None. R. A. Oram: Consultant; Janssen Research &amp; Development, LLC, Research Support; Randox R &amp; D. W. Hagopian: Research Support; Janssen Research &amp; Development, LLC. Funding Diabetes UK (16/0005529) JDRF (3-SRA-2019-827-S-B)

> It is not in the stars to hold our destiny but in ourselves > > —William Shakespeare The widespread availability and lower costs of genotyping and sequencing have resulted in the performance of a large number of genotype–phenotype association studies in cardiovascular medicine. The stringent requirements for correction for multiple testing and replication have particularly favored genotype–phenotype studies examining the association between genetic variation and quantitative traits that allows for greater statistical power. Multiple genome-wide association studies and a subsequent meta-analysis have identified >180 common and rare genetic variants associated with lipid traits.1,2 However, the effect size of these individual genetic variants is small, explaining only a small fraction of phenotypic variation prompting investigators to use genetic risk scores (GRS) that represent an aggregate of genetic risk to demonstrate clinical utility. Single-nucleotide polymorphisms (SNPs) and GRS have been used to predict cardiovascular disease such as coronary artery disease (CAD) and hypertension, surrogate markers of disease such as coronary calcium, cardiovascular outcomes such as myocardial infarction, and intermediate traits such as blood pressure and lipids.3 Article, see p 495 The Global Lipids Genetics Consortium has performed the largest genetic association study of lipid levels in 188 577 individuals from a total of 60 studies.1,2 There were 157 genetic loci that were identified, 95 were described previously and 62 were novel. The lipid level variance explained by the novel loci in this study ranged from 1.6% for high-density lipoprotein cholesterol (HDL-C) levels to 2.6% for total cholesterol levels. The total lipid variance explained by the previously described loci was 10% to 12%. The population studied was predominantly of European ancestry, and subjects on lipid-lowering therapy were excluded. The association of these genetic loci with lipid levels and a change in lipid levels with intervention in a prediabetic population …

Genetic vulnerability to diabetes and obesity: Does education offset the risk?

A Meta-Analysis of Genome-Wide Association Studies of Multiple Myeloma in Persons of African Ancestry [African-American Multiple Myeloma Study (AAMMS)] Identifies Suggestive Risk Variants

Genetic discovery and risk characterization in type 2 diabetes across diverse populations.

The prevalence of type 2 diabetes (T2D) and obesity has recently increased dramatically. These common diseases are likely to arise from the interaction of multiple genetic, socio-demographic and environmental risk factors. While previous research has found genetic risk and education to be strong predictors of these diseases, few studies to date have examined their joint effects. This study investigates whether education modifies the association between genetic background and risk for type 2 diabetes (T2D) and obesity. Using data from non-Hispanic Whites in the Health and Retirement Study (HRS, n ¼ 8398), we tested whether education modifies genetic risk for obesity and T2D, offsetting genetic effects; whether this effect is larger for individuals who have high risk for other (unobserved) reasons, i.e., at higher quantiles of HbA1c and BMI; and whether effects differ by gender. We measured T2D risk using Hemoglobin A1c (HbA1c) level, and obesity risk using body-mass index (BMI). We constructed separate genetic risk scores (GRS) for obesity and diabetes respectively based on the most current available information on the single nucleotide polymorphism (SNPs) confirmed as genome-wide significant predictors for BMI (29 SNPs) and diabetes risk (39 SNPs). Linear regression models with years of schooling indicate that the effect of genetic risk on HbA1c is smaller among people with more years of schooling and larger among those with less than a high school (HS) degree compared to HS degree-holders.

Most genome-wide association studies (GWAS) have been carried out in European ancestry populations; no risk variants for breast cancer have been identified solely from African ancestry GWAS data. Few GWAS hits have replicated in African ancestry populations. In a nested case-control study of breast cancer in the Black Women's Health Study (1,199 cases/1,948 controls), we evaluated index single-nucleotide polymorphisms (SNP) in 21 loci from GWAS of European or Asian ancestry populations, overall, in subtypes defined by estrogen receptor (ER) and progesterone receptor (PR) status (ER+/PR+, n = 336; ER-/PR-, n = 229), and in triple-negative breast cancer (TNBC, N = 81). To evaluate the contribution of genetic factors to population differences in breast cancer subtype, we also examined global percent African ancestry. Index SNPs in five loci were replicated, including three associated with ER-/PR- breast cancer (TERT rs10069690 in 5p15.33, rs704010 in 10q22.3, and rs8170 in 19p13.11): per allele ORs were 1.29 [95% confidence interval (CI) 1.04-1.59], P = 0.02, 1.52 (95% CI 1.12-2.08), P = 0.01, and 1.30 (95% CI 1.01-1.68), P = 0.04, respectively. Stronger associations were observed for TNBC. Furthermore, cases in the highest quintile of percent African ancestry were three times more likely to have TNBC than ER+/PR+ cancer. These findings provide the first confirmation of the TNBC SNP rs8170 in an African ancestry population, and independent confirmation of the TERT ER- SNP. Furthermore, the risk of developing ER- breast cancer, particularly TNBC, increased with increasing proportion of global African ancestry. The findings illustrate the importance of genetic factors in the disproportionately high occurrence of TNBC in African American women.

We conducted a cross-sectional study of Malay participants aged 40-80 years (n = 2,932) to examine the associations between polymorphisms at newly identified, lipid-associated loci with blood lipid levels and prevalent cardiovascular disease (CVD) in a Malay population in Asia. A polymorphism adjacent to the TRIB1 locus (rs17321515) was associated with elevated total cholesterol and LDL-cholesterol (LDL-C) after adjustment for age and sex (both P values <0.007) and with increased risk of coronary heart disease and CVD [odds ratio (OR) 1.23, 95% confidence interval (95% CI) 1.03-1.46; and OR 1.2, 95% CI 1.02-1.42, respectively] under an additive model of inheritance. In addition, using recessive models of inheritance, polymorphisms on chromosome 19 adjacent to the CILP2 and PBX4 loci (rs16996148) and on chromosome 1 at the GALNT2 locus (rs4846914) were associated with elevated HDL-C (P = 0.005) and lower LDL-C (P = 0.048), respectively. Although novel, the former is consistent with the association between this polymorphism and lower blood triglycerides observed in the initial studies conducted in populations of European ancestry. Neither showed statistically significant association with CVD. These observations should form the basis of further investigation to identify the causative polymorphisms at this locus, and also to understand the mechanistic roles that this protein may play in lipoprotein metabolism in Asians and other populations.

Genetic Risk Prediction for CKD: A Journey of a Thousand Miles

Background: Polygenic risk scores (PRS) integrate risk information from breast cancer associated SNPs (single nucleotide polymorphism). The risk scores have mostly been developed in populations of European ancestry, and have been shown to improve risk prediction over standard breast cancer risk models in these populations. The ability of the PRS to personalize screening is currently being studied. We included PRS as a component of breast cancer risk assessment in the WISDOM Study, a trial of personalized vs. annual breast cancer screening. In order to account for race/ethnicity in PRS risk assessment, we developed a race/ethnicity calibrated and inclusive PRS risk score that we incorporated here into the Gail model to determine impact on risk stratification. Methods: We constructed two different PRS for each race/ethnicity: For Caucasian populations, we constructed two PRS based on SNPs discovered in European-ancestry populations. One PRS was based on 167 SNPs (PRS-167) and the other based on 313 SNPs (PRS-313) from the Breast Cancer Association Consortium studies as previously published. For each of the Asian-, Hispanic- and African-ancestry populations we added additional ancestry specific SNPs to the PRS-167 or the PRS-313, that were literature curated or our own identified race/ethnicity SNPs that we validated to provide independent risk prediction for their ancestry group: Asian added 10 or 4 additional SNPs, Hispanic 2 SNPs, and African 8 and 12 SNPs, respectively to each model. We tested this approach using datasets from several case-control studies of multiple racial/ethnic populations and compared discrimination of the models using area under the receiver operating characteristic curve (AUROC). Furthermore, we applied our multi-racial/ethnic PRS-313 in a sample of ~3000 multi-racial/ethnic women from the Athena Breast Screening Registry, case-control sampled by Gail score to be at elevated (Gail &amp;gt;1.67) or average (Gail≤1.67) risk, to evaluate the impact of our multi-ethnic adjustment on risk stratification. Results: A multi-race/ethnicity adjusted PRS-313 and PRS-167 plus ethnicity specific SNPs has moderate-high discriminatory power with AUROCs of 0.65 and 0.64, respectively. The specificity of our PRS-167 in the different race/ethnicity ancestries performs relatively well in Asian (AUROC 0.59) and Hispanic (AUROC 0.63) populations, but less so in African-ancestry (AUROC 0.56). Incorporating multi-race/ethnicity PRS into Gail model selected women, resulted in 20% of average-risk women transitioning to risk above 1.67%, and conversely, 38% of elevated risk patients were reclassified to average risk. Conclusion: We constructed a PRS risk score that can be applied to multi-ethnic populations and found moderate-high discrimination. Additional work is needed for the African-ancestry population. The addition of a multi-race/ethnicity SNP model to risk classification based on the Gail model significantly changes risk stratification and clinical care recommendations due to down- or up-reclassification of women at average versus elevated risk. Citation Format: Sarah Theiner, Donglei Hu, Scott Huntsman, Yiwey Shieh, Laura Fejerman, Irene Acerbi, Sarah D Sawyer, Paige Kendall, Wei Zheng, Dezheng Huo, Olufunmilayo I Olopade, Christopher Haiman, Karla Kerlikowske, Steven Cummings, Ester John, Gabriela Torres-Mejia, Lawrence H Kushi, Denise Wolf, Jeffery A Tice, David A Pearce, Laura Esserman, Athena Breast Health Network Investigators and Advocate Partners, Laura J van ‘t Veer, Elad Ziv. A breast cancer multi-racial/ethnic polygenic risk score for improved personalized breast cancer screening [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-10-05.

Polygenic Risk Scores for Follow Up After Colonoscopy and Polypectomy: Another Tool for Risk Stratification and Planning Surveillance?

Based on US national cancer registry data, age differences at breast cancer diagnosis have been reported between African-American women and European-American women. Such differences between populations of African and European ancestry have not been studied in other countries at a nationwide level. Here, we report and compare descriptive nationwide epidemiological indicators of invasive breast cancer for the populations of European ancestry living in the US and in mainland France and for women of African ancestry living in the US and in the French West Indies (Martinique and Guadeloupe). Based on the available data, we determined age frequency distributions, world age-standardized incidence, and the distribution of expected cases of breast cancer in a standard population of women by age. The age frequency distributions revealed that women of African ancestry were younger at diagnosis than women of European ancestry. By contrast, compared with the US regardless of ancestry and mainland France, the standardized incidences appeared lower, and the largest numbers of expected cases younger, in the French West Indies. The populations with African ancestry were not homogeneous in terms of epidemiologic indicators of age-related breast cancer. These descriptive findings suggest that populations of African ancestry cannot be considered uniform when determining whether it would be appropriate to decrease the age of entry into screening programs for breast cancer.

IntroductionThe Rose hypothesis predicts that since genetic variation is greater within than between populations, genetic risk factors will be associated with individuals’ risk of disease but not population disparities, and...