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EP-4740210-A1 - MULTIPLE-ANCESTRY POLYGENIC RISK ASSESSMENT FOR BREAST CANCER

EP4740210A1EP 4740210 A1EP4740210 A1EP 4740210A1EP-4740210-A1

Abstract

Provided herein are methods for assessing a risk of a trait in a subject, by selecting a plurality of ancestry-informative SNP markers based on objective design criteria, measuring a genotype of the subject, obtaining trait-associated SNP markers, and calculating a multiple-ancestry polygenic risk score for the risk of the trait in the subject based on the plurality of ancestry-informative SNP markers and the trait-associated SNP markers. The trait can be risk of cancer. Also provided are methods for assessing ancestry of a subject.

Inventors

  • HUGHES, Elisha
  • GUTIN, ALEXANDER
  • PRUSS, DMITRY
  • SIMMONS, TIMOTHY

Assignees

  • Myriad Genetics, Inc.

Dates

Publication Date
20260513
Application Date
20240705

Claims (20)

  1. 1. A method for assessing a risk of a trait in a subject, the method comprising: selecting a plurality of trait-associated SNP markers and a plurality of ancestry- informative SNP markers; measuring a genotype of the subject; and calculating a multiple-ancestry polygenic risk score for the risk of the trait in the subject based on the trait-associated SNP markers and the plurality of ancestry-informative SNP markers.
  2. 2. The method of claim 1, wherein the trait-associated SNPs are selected using a synthetic stepwise regression methodology that accounts for linkage disequilibrium between variants.
  3. 3. The method of claim 1, wherein the trait-associated SNPs comprise one or more of European breast cancer-associated SNPs, African breast cancer-associated SNPs, East Asian breast cancer-associated SNPs, and Amerindian breast cancer-associated SNPs.
  4. 4. The method of claim 1, further comprising calculating the multiple-ancestry polygenic risk score for the risk of the trait in the subject with additional clinical variables of the subject.
  5. 5. The method of claim 4, wherein the additional clinical variables are age, personal medical history, and family medical history of the subject.
  6. 6. The method of claim 1, wherein the trait is a risk of a disease in the subject.
  7. 7. The method of claim 6, wherein the disease is cancer.
  8. 8. The method of claim 1, wherein the plurality of ancestry-informative SNP markers are from 10 to 50,000 SNP markers.
  9. 9. The method of claim 1, wherein the plurality of ancestry-informative SNP markers are from 10 to 56 SNP markers.
  10. 10. The method of claim 1, wherein the trait-associated SNP markers are a plurality of cancer-associated SNP markers.
  11. 11. The method of claim 1, wherein the trait-associated SNP markers are a plurality of from 10 to 50,000 breast cancer-associated SNP markers.
  12. 12. The method of claim 1, wherein the trait-associated SNP markers are a plurality of from 10 to 329 breast cancer-associated SNP markers.
  13. 13. The method of claim 1, wherein the calculating a multiple-ancestry polygenic risk score for the risk of the trait in the subject is done with training clinical data of a reference group.
  14. 14. The method of claim 1, wherein the calculating a multiple-ancestry polygenic risk score for the risk of the trait in the subject is done with validating clinical data of a reference group.
  15. 15. The method of claim 1, wherein the genotype of the subject is measured by NGS.
  16. 16. The method of claim 1, wherein the plurality of ancestry-informative SNP markers determine a fractional heritage in the genotype of the subject for each of four or more different heritage populations.
  17. 17. The method of claim 1, wherein the plurality of ancestry-informative SNP markers determine a fractional heritage in the genotype of the subject for each of African, European, East Asian, and Amerindian heritage populations.
  18. 18. The method of claim 1, wherein the multiple-ancestry polygenic risk score for the risk of the trait in the subject is accurate for subjects in four or more different heritage populations, even when the heritage populations are self-reported.
  19. 19. The method of claim 1, wherein the multiple-ancestry polygenic risk score for the risk of the trait in the subject is accurate for subjects in African, European, East Asian, and Amerindian heritage populations, even when the heritage populations are self-reported.
  20. 20. The method of claim 1, wherein the multiple-ancestry polygenic risk score for the risk of the trait in the subject is calibrated for subjects in four or more different heritage populations so that the risk of the trait is not overestimated in any heritage population.

Description

MULTIPLE-ANCESTRY POLYGENIC RISK ASSESSMENT FOR BREAST CANCER CROSS REFERENCE TO RELATED APPLICATION [0001] This application claims the benefit under 35 U.S.C. § 119(e) of U.S. Provisional Application No. 63/525,534, filed July 7, 2023, the contents of which are incorporated herein by reference in their entirety. TECHNICAL FIELD [0002] This disclosure relates to the fields of genetics and medicine. More particularly, this disclosure relates to methods for assessing and predicting polygenic traits and breast cancer risks for medical use, as well as treating breast cancer. BACKGROUND [0003] It is desirable to use polygenic risk scores to assess the expectation of a clinical trait or condition in a subject such as the risk of a particular disease. Risk scores from genomic data depend on identifying polymorphic loci to be used. [0004] Conventional methods for trait expectation, such as for breast cancer risk, have identified various breast cancer associated genes. However, breast cancer genetics is highly complex, and these conventional methods have limitations that cannot overcome or address these complexities, which reduces the accuracy of risk predictions. Also, conventional methods may rely on genomic data from a single heritage. [0005] An important drawback in conventional methods for characterizing risk of a trait from genomic data is that baseline data for a trait in one particular population may not accurately predict the same trait in a different population of different heritage. Conventional methods using genomic data from a population drawn from one heritage can overestimate the risk of a particular trait in a different population. Overestimation of risk is a significant drawback, especially for disease traits. [0006] Another drawback of conventional methods for determining traits such as cancer risk include the problem that calculations using genomic data often depend on self-reported heritage information. Errors in self-reported heritage information in genomic data can prevent appropriate determination of cancer risk for a global population. [0007] A significant drawback of conventional methods for determining risk of a trait is a lack of discrimination between low risk and high risk of the trait for different populations. For example, conventional methods for breast cancer risk based on genomic data from one heritage may not be able to distinguish between low risk and high risk for a population of a different heritage. This drawback of conventional methods can confuse prevention and treatment strategies for a disease trait and jeopardize patient outcomes. [0008] Conventional methods for polygenic risk scores may rely on SNPs discovered through genome-wide association studies (GWAS). However, such SNPs are usually not causal, but may be in linkage disequilibrium (LD) with causal variants. Historically, genomewide association studies have included predominantly European populations, resulting in miscalibrated and inaccurate PRS for non-Europeans. What is need is a set of SNPs for polygenic risk estimation that will discriminate risk for all heritage groups and populations. It is also desirable to develop a method of polygenic risk estimation that does not bias calculations by population, and provides accurate results for all heritage groups and populations. [0009] What is needed is a highly calibrated and accurate method for determining polygenic risk scores for traits such as breast cancer risk to avoid overestimation. There is a need for such methods to be useful for all heritage populations, and regardless of selfreported patient data. An advantageous clinical risk algorithm can improve medical care and patient treatment. [0010] There is an urgent need for methods to assess traits such as breast cancer risk with good discrimination of risk level for all populations regardless of heritage. There is a need for methods that can be efficiently brought to the point of medical care. BRIEF SUMMARY [0011] This disclosure provides improved methods for determining polygenic traits, such as risks for breast cancer. The methods of this disclosure can be used in medicine, as well as for treating diseases for which risk is identified and/or assessed. [0012] In some aspects, methods of this disclosure may provide superior prediction of clinical risk in breast cancer patients. The methods of this disclosure can provide polygenic risk prediction for breast cancer which can be applied globally to all patients of all heritage groups. [0013] A multiple-ancestry polygenic risk score of this disclosure can be used to assess the expectation of a clinical trait or condition such as cancer. [0014] Aspects of this disclosure can characterize an individual’s risk of a trait from genomic data obtained for the trait in one or more particular heritage groups or populations, where the individual may be of a different or the same heritage group or population. Embodiments of this disclosure can provide a multiple-ancestry po