ENHANCED RISK PROBABILITIES USING BIOMOLECULE ESTIMATIONS

• US 20120190018A1
• Filed: 10/15/2011
• Published: 07/26/2012
• Est. Priority Date: 01/25/2011
• Status: Active Grant

• Current Assignee: Roche Molecular Systems (Roche Holding AG)
• Original Assignee: Ariosa Diagnostics Incorporated (Roche Holding AG)
• Inventors: Struble, Craig, Wang, Eric, Sparks, Andrew, Oliphant, Arnold
• Granted Patent: US 8,756,020 B2
• Time in Patent Office: Days
• US Class Current: 435/6.11
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/10 Ploidy or copy number detection
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection

Abstract

The present invention provides processes for determining more accurate risk probabilities for medical conditions. The risk probabilities of the presence or absence of a medical condition are calculated using frequency data from selected biomolecules and biomolecule source contribution of at least one source in a mixed sample.

Claims

1. A computer-implemented process for producing risk probabilities for a medical condition, comprising the steps of:

determining the frequency of a first set of two or more biomolecules in a mixed sample;

determining the frequency of a second set of two or more biomolecules in a mixed sample;

determining a biomolecule source contribution from at least a first source in the mixed sample; and

calculating an initial risk probability for a medical condition by comparing the frequency of the first and second sets in view of the biomolecule source contribution of the first source.

2. The process of claim 1, wherein the mixed sample is a maternal sample.

3. The process of claim 2, wherein the maternal sample is maternal blood, maternal plasma or maternal serum.

4. The process of claim 2, wherein the maternal sample is maternal plasma.

5. The process of claim 1, wherein the sets of biomolecules are sets of nucleic acids corresponding to a genomic region in the mixed sample.

6. The process of claim 5, wherein the first set of nucleic acids corresponds to a first genomic region, the second set of nucleic acids corresponds to a second genomic region, and the frequencies are compared to determine the presence or absence of a copy number variation in the first or second genomic region.

7. The process of claim 5, wherein the first set of nucleic acids corresponds to a first chromosome, the second set of nucleic acids corresponds to a second chromosome, and the frequencies are compared to determine the presence or absence of an aneuploidy in the first or second chromosome.

8. The process of claim 7, wherein the frequencies are compared to determine the presence or absence of an aneuploidy in a maternal sample.

9. The process of claim 1, wherein the frequency of the biomolecules is quantified through sequencing.

10. The process of claim 9, wherein the biomolecules are preselected through amplification of loci prior to sequencing.

11. The process of claim 9, wherein the frequency of the biomolecules is determined through massively parallel shotgun sequencing.

12. The process of claim 1, wherein the frequency of the biomolecules is quantified using digital PCR.

13. The process of claim 1, wherein the initial risk probability is calculated using ancillary information.

14. The process of claim 13, wherein the ancillary information is maternal age.

15. The process of claim 13, wherein the ancillary information is gestational age.

16. The process of claim 13, wherein the ancillary information is results from a prior medical test or procedure.

17. A computer-implemented process for producing risk probabilities for a medical condition, comprising the steps of:

a. inputting the frequency for a first set of two or more biomolecules from a first and a second source in a mixed sample;

b. inputting the frequency for a second set of two or more biomolecules from a first and a second source in a mixed sample;

c. calculating an initial risk probability for a medical condition by comparing the first and second sets;

d. inputting the biomolecule source contribution from at least a first source in the mixed sample; and

e. adjusting the risk probability based on the biomolecule source contribution.

18. The process of claim 17, wherein the mixed sample is a maternal sample.

19. The process of claim 18, wherein the maternal sample is maternal blood, maternal plasma or maternal serum.

20. The process of claim 18, wherein the maternal sample is maternal plasma.

21. The process of claim 17, wherein the sets of biomolecules are sets of nucleic acids corresponding to a genomic region in the mixed sample.

22. The process of claim 21, wherein the first set of nucleic acids corresponds to a first genomic region, the second set of nucleic acids corresponds to a second genomic region, and the frequencies are compared to determine the presence or absence of a copy number variation in the first or second genomic region.

23. The process of claim 21, wherein the first set of nucleic acids corresponds to a first chromosome, the second set of nucleic acids corresponds to a second chromosome, and the frequencies are compared to determine the presence or absence of an aneuploidy in the first or second chromosome.

24. The process of claim 17, wherein the frequency of the biomolecules is quantified through sequencing.

25. The process of claim 24, wherein the biomolecules are preselected through amplification of loci prior to sequencing.

26. The process of claim 24, wherein the frequency of the biomolecules is determined through massively parallel shotgun sequencing.

27. The process of claim 17, wherein the frequency of the biomolecules is quantified using digital PCR.

28. The process of claim 17, wherein the initial risk probability is calculated using ancillary information.

29. The process of claim 28, wherein the ancillary information is maternal age.

30. The process of claim 28, wherein the ancillary information is gestational age.

31. The process of claim 28, wherein the ancillary information is results from a prior medical test or procedure.

32. An executable software product stored on a computer-readable medium containing program instructions for calculating a risk probability for a medical condition, the program comprising instructions for:

inputting the frequency of a first set of two or more biomolecules in a mixed sample;

inputting the frequency of a second set of two or more biomolecules in a mixed sample;

inputting the biomolecule source contribution from at least a first source in the mixed sample; and

calculating an initial risk probability for a medical condition by comparing the frequency of the first and second sets in view of the biomolecule source contribution.

33. An executable software product stored on a computer-readable medium containing program instructions for calculating a risk probability for a medical condition, the program comprising instructions for:

inputting the frequency of a first set of two or more biomolecules in a mixed sample;

inputting the frequency data for a second set of two or more biomolecules in a mixed sample;

calculating an initial risk probability for a medical condition by comparing the frequency of the first and second sets;

inputting data on the biomolecule source contribution from at least a first source in the mixed sample; and

adjusting the risk probability based on the biomolecule source contribution.

34. An executable software product stored on a computer-readable medium containing program instructions for calculating a risk probability for a medical condition, the program comprising instructions for:

a memory;

a processor coupled to the memory; and

a software component executed by the processor that is configured to;

receive a first data set comprising frequency of a first set of two or more biomolecules in a mixed sample;

receive a second data set comprising frequency of a second set of two or more biomolecules in a mixed sample;

receive a third data set comprising a biomolecule source contribution from at least a first source in the mixed sample; and

calculate a risk probability for a medical condition based on a comparison of the frequency of the first and second sets of biomolecules in view of the third data set.

35. An executable software product stored on a computer-readable medium containing program instructions for calculating a risk probability for a medical condition, the program comprising instructions for:

a memory;

a processor coupled to the memory; and

a software component executed by the processor that is configured to;

receive a first data set comprising frequency of a first set of two or more biomolecules from a first and second source in a mixed sample;

receive a second data set comprising frequency data for a second set of two or more biomolecules in a mixed sample;

calculate a risk probability for a medical condition based on a comparison of the frequency of the first and second sets of biomolecules;

receive a third data set comprising a biomolecule source contribution from one or more sources in the mixed sample; and

adjust the calculated risk probability based on the biomolecule source contribution.

36. A computer software product including a non-transitory computer-readable storage medium having fixed therein a sequence of instructions which when executed by a computer direct performance of steps of:

receiving a first data set comprising frequency data for a first set of two or more biomolecules in a mixed sample;

receiving a second data set comprising frequency data for a second set of two or more biomolecules in a mixed sample;

receiving a third data set comprising a biomolecule source contribution from one or more sources in the mixed sample; and

calculating a risk probability for a medical condition based on a comparison of the frequency of the first and second sets of biomolecules in view of the biomolecule source contribution in the mixed sample.

37. A computer software product including a non-transitory computer-readable storage medium having fixed therein a sequence of instructions which when executed by a computer direct performance of steps of:

receiving a first data set comprising frequency data for a first set of two or more biomolecules in a mixed sample;

receiving a second data set comprising frequency data for a second set of two or more biomolecules in a mixed sample;

calculating a risk probability for a medical condition based on a comparison of the frequency of the first and second sets of biomolecules;

receiving a third data set comprising a biomolecule source contribution from one or more sources in the mixed sample; and

adjusting the calculated risk probability based on the biomolecule source contribution.

38. A system, comprising:

a memory;

a processor coupled to the memory; and

a software component executed by the processor that is configured to;

receive a first data set comprising frequency data for a first set of two or more biomolecules in a mixed sample;

receive a second data set comprising frequency data for a second set of two or more biomolecules in a mixed sample;

receive a third data set comprising a biomolecule source contribution from one or more sources in the mixed sample; and

calculate a risk probability for a medical condition based on a comparison of the frequency of the first and second sets of biomolecules in view of the third data set.

39. A system, comprising:

a memory;

a processor coupled to the memory; and

a software component executed by the processor that is configured to;

receive a first data set comprising frequency data for a first set of two or more biomolecules in a mixed sample;

receive a second data set comprising frequency data for a second set of two or more biomolecules in a mixed sample;

calculate a risk probability for a medical condition based on a comparison of the frequency of the first and second sets of biomolecules.

receive a third data set comprising a biomolecule source contribution from one or more sources in the mixed sample; and

adjust the risk probability based on the biomolecule source contribution.