Genome-phenome analyzer and methods of using same

• US 9,524,373 B2
• Filed: 02/28/2013
• Issued: 12/20/2016
• Est. Priority Date: 03/01/2012
• Status: Active Grant

• Current Assignee: SimulConsult, Inc.
• Original Assignee: SimulConsult, Inc.
• Inventors: Segal, Michael M.
• Primary Examiner(s): Lin, Jerry
• Application Number:
  US13/781,225
• Publication Number:
  US 20130231404A1
• Time in Patent Office: 1,391 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

The present invention features methods, devices, and systems, e.g., for providing diagnostic or treatment decision support to a clinician for the diagnosis or treatment of a patient in need thereof or for diagnosing or treating a patient in need thereof.

Claims

1. A method comprising the steps of:

(a) providing a plurality of patient findings for a patient being diagnosed in a physical computing device having a representation of a set of candidate diseases,

wherein each said patient finding in said plurality is representative of clinical or laboratory information gathered about said patient, and wherein said patient findings comprise genetic sequencing information associated with said patient comprising identification of one or more genetic variants, and for each of said one or more genetic variants, a measure of zygosity for said patient, wherein for each of said one or more genetic variants, a severity score is provided in said plurality of patient findings or said computing device generates said severity score;

(b) using said computing device to generate estimated probabilities of said candidate diseases using said plurality of patient findings and said severity scores for each of said one or more genetic variants;

(c) generating the pertinence of said plurality of patient findings; and

(d) outputting a candidate disease list capable of being displayed and ranked by highest said estimated probabilities and outputting a patient finding list capable of being displayed and ranked by pertinence.

2. The method of claim 1,

wherein said computing device comprises a first set of quantities representing estimated probabilities of a plurality of patient findings in the general non-diseased population, and a second set of quantities representing estimated probabilities of a plurality of patient findings each assuming the presence of a specified candidate disease;

and

said method further comprises, in step (b), using said first set of quantities and second set of quantities to iteratively modify said initial parameters representing estimated probabilities of said candidate diseases using each of said plurality of patient findings to generate said estimated probabilities of said candidate diseases.

3. The method of claim 2, wherein said severity scores for each of said one or more genetic variants are used to modify one of said first set of quantities, said one of said first set of quantities representing an estimated probability of an abnormal gene with said genetic variant in the general non-diseased population.

4. The method of claim 3, wherein a higher severity score results in a lower said one of said first set of quantities representing an estimated probability of said abnormal gene with said genetic variant in the general non-diseased population.

5. The method of claim 3, wherein said genetic sequencing information associated with said patient comprises identification of a plurality of genetic variants each associated with the same gene, and wherein said genetic variant having the highest severity score among said genetic variants each associated with said gene is used to modify said one of said first set of quantities representing said estimated probability of said abnormal gene corresponding to said genetic variant absent information about the presence of a specified candidate disease.

6. The method of claim 1, wherein said severity score for each of said one or more genetic variants is generated by said computing device as a quantitative result from a plurality of inputs.

7. The method of claim 6, wherein said plurality of inputs comprise variant information from one or more parents, siblings, or other family members of said patient.

8. The method of claim 6, wherein said plurality of inputs comprises an input selected from the group consisting of:

zygosity in one or more other family members sequenced, frequency of said genetic variant in the general population, chromosome location, type of said genetic variant, functional score, conservation score, splice prediction score, depth of read score, read quality score, and score based on whether said genetic variant is known to cause disease.

9. The method of claim 6, wherein said plurality of inputs comprises a pathogenicity model selected from the group consisting of a loss of function pathogenicity model and a gain of function pathogenicity model.

10. The method of claim 1, wherein said patient findings comprise, for at least one of said genetic variants identified, both a monoallelic severity score and a biallelic severity score.

11. The method of claim 10, wherein said monoallelic severity score is used when the corresponding genetic variant is considered to cause a monoallelic disease, and wherein said biallelic severity score is used when the corresponding genetic variant is considered to cause a biallelic disease.

12. The method of claim 11, wherein said monoallelic severity score is reduced, relative to said biallelic severity score, when the frequency of the corresponding genetic variant exceeds a threshold percentage of the population.

13. The method of claim 1, wherein said measure of zygosity for each said genetic variant is used to categorize said genetic variant as autosomal monoallelic, autosomal biallelic, X-linked monoallelic, X-linked biallelic, Y-linked, or mitochondrial.

14. The method of claim 13, wherein said genetic sequencing information associated with said patient comprises identification of two genetic variants each associated with the same gene, said two genetic variants each having monoallelic zygosity and said gene being associated with a recessive disease, and wherein said two genetic variants are collectively categorized as possibly having compound heterozygosity.

15. The method of claim 14, wherein said two genetic variants are collectively categorized as having a combined severity score corresponding to the lesser of the severity scores of said two genetic variants.

16. The method of claim 14, wherein said genetic sequencing information associated with said patient comprises identification of more than two genetic variants each associated with the same gene, said more than two genetic variants each having monoallelic zygosity and said gene being associated with a recessive disease, and wherein said more than two genetic variants are collectively categorized as possibly having compound heterozygosity and having a combined severity score corresponding to the lesser of the highest two severity scores of said more than two genetic variants.

17. The method of claim 15, wherein said patient findings further comprise, for at least one of said genetic variants identified, information about a parent, sibling, or other family member of said patient, said information comprising a measure of zygosity of said genetic variant in said family member.

18. The method of claim 17, wherein said information about said parent, sibling, or other family member of said patient is used to eliminate at least one compound heterozygote possibility, thereby resulting in a refined determination of said combined severity score.

19. The method of claim 13, wherein said genetic sequencing information associated with said patient comprises identification of two genetic variants each associated with the same gene, said two genetic variants each having monoallelic zygosity and said gene being associated with a recessive disease, wherein genetic sequencing information further comprises chromosomal location of said genetic variants, and wherein, if said chromosomal location is the same for each of said two genetic variants, said two genetic variants are not categorized as having compound heterozygosity.

20. The method of claim 13, wherein at least one of said genetic variants is of previously unidentified phenotype, wherein said genetic sequencing information comprises chromosomal location for said genetic variant, and wherein said measure of zygosity and said chromosomal location for said genetic variant are used to categorize said genetic variant as autosomal monoallelic, autosomal biallelic, X-linked monoallelic, X-linked biallelic, Y-linked, or mitochondrial.

21. The method of claim 1, wherein said patient findings further comprise information that is not obtained from genetic sequencing of genetic material from said patient, wherein said information that is not obtained from genetic sequencing of said genetic material from said patient comprises information about a laboratory test result, clinical result, or historical information associated with said patient.

22. The method of claim 1, wherein step (d) comprises transmitting said candidate disease list over the Internet or to a display device.

23. The method of claim 22, further comprising outputting to said display device said one or more candidate diseases having highest estimated probabilities in rank order.

24. The method of claim 1, wherein said method results in the diagnosis of said patient as having one of said candidate diseases having highest said estimated probabilities.

25. The method of claim 1, wherein said method results in the identification of one or more genes as having highest pertinence.

26. The method of claim 25, wherein said identification of said one or more genes as having highest pertinence results in the identification of one or more relationships between each said gene and a corresponding known disease or new variant similar to said known disease.

27. The method of claim 25, wherein said method results in the identification of two or more genes as having highest pertinence, wherein said identification of each of said two or more genes as having highest pertinence results in the identification of relationships between each said gene and a corresponding known disease or new variant similar to said known disease, and wherein said method results in the diagnosis of said patient as having each said corresponding known disease or new variant similar to said known disease.

28. The method of claim 1, wherein said physical computing device is accessed and operated over the Internet.

29. A computer readable medium having stored thereon executable instructions for directing a physical computing device to implement a method comprising the steps of:

(a) providing a plurality of patient findings for a patient being diagnosed, in said physical computing device having a representation of a set of candidate diseases, wherein each said patient finding in said plurality is representative of clinical or laboratory information gathered about said patient, and wherein said patient findings comprise genetic sequencing information associated with said patient comprising identification of one or more genetic variants, and for each of said one or more genetic variants, a measure of zygosity for said patient;

(b) generating a severity score for each of said one or more genetic variants;

(c) generating estimated probabilities of said candidate diseases using said plurality of patient findings and said severity scores for each of said one or more genetic variants;

(d) generating the pertinence of said plurality of patient findings; and

(e) outputting a candidate disease list capable of being displayed ranked by highest said estimated probabilities and outputting a patient finding list capable of being displayed and ranked by pertinence.

30. A physical computing device having a representation of a set of candidate diseases and programmed with executable instructions for directing the device to implement a method comprising the steps of:

(a) providing a plurality of patient findings for a patient being diagnosed, wherein each said patient finding in said plurality is representative of clinical or laboratory information gathered about said patient, and wherein said patient findings comprise genetic sequencing information associated with said patient comprising identification of one or more genetic variants, and for each of said one or more genetic variants, a measure of zygosity for said patient;

(b) generating a severity score for each of said one or more genetic variants;

(c) generating estimated probabilities of said candidate diseases using said plurality of patient findings and said severity scores for each of said one or more genetic variants;

(d) generating the pertinence of said plurality of patient findings; and

(e) outputting a candidate disease list capable of being displayed ranked by highest said estimated probabilities and outputting a patient finding list capable of being displayed and ranked by pertinence.

31. A method of diagnosing a patient in need thereof, said method comprising the steps of:

(a) accessing a physical computing device comprising a representation of a set of candidate diseases, wherein;

(i) said computing device receives a plurality of patient findings for said patient being diagnosed, wherein each said patient finding in said plurality is representative of clinical or laboratory information gathered about said patient, and wherein said patient findings comprise genetic sequencing information associated with said patient comprising identification of one or more genetic variants, and for each of said one or more genetic variants, a measure of zygosity for said patient, wherein for each of said one or more genetic variants, a severity score is provided in said plurality of patient findings or said computing device generates said severity score;

(ii) said computing device generates estimated probabilities of said candidate diseases using said plurality of patient findings and said severity scores for each of said one or more genetic variants; and

(iii) said computing device generates the pertinence of said plurality of patient findings;

(b) receiving, from said physical computing device, a candidate disease list capable of being displayed ranked by highest said estimated probabilities and a patient finding list ranked by pertinence; and

(c) diagnosing said patient as having one or more of said candidate diseases having highest said estimated probabilities.

32. A method of treating a patient in need thereof, said method comprising the steps of:

(a) accessing a physical computing device comprising a representation of a set of candidate diseases, wherein;

(i) said computing device receives a plurality of patient findings for a patient being diagnosed, wherein each said patient finding in said plurality is representative of clinical or laboratory information gathered about said patient, and wherein said patient findings comprise genetic sequencing information associated with said patient comprising identification of one or more genetic variants, and for each of said one or more genetic variants, a measure of zygosity for said patient, wherein for each of said one or more genetic variants, a severity score is provided in said plurality of patient findings or said computing device generates said severity score; and

(ii) said computing device generates estimated probabilities of said candidate diseases using said plurality of patient findings and said severity scores for each of said one or more genetic variants; and

(iii) said computing device generates the pertinence of said plurality of patient findings;

(b) receiving, from said physical computing device, a candidate disease list capable of being displayed ranked by highest said estimated probabilities and a patient finding list ranked by pertinence;

(c) diagnosing said patient as having one or more of said candidate diseases having highest said estimated probabilities; and

(d) treating said patient for said one or more of said candidate diseases having highest said estimated probabilities as determined in step (c).

33. A method comprising providing, in a physical computing device, a representation of a set of candidate diseases, wherein:

(i) said computing device receives a plurality of patient findings for a patient being diagnosed, wherein each said patient finding in said plurality is representative of clinical or laboratory information gathered about said patient, and wherein said patient findings comprise genetic sequencing information associated with said patient comprising identification of one or more genetic variants, and for each of said one or more genetic variants, a measure of zygosity for said patient, wherein for each of said one or more genetic variants, a severity score is provided in said plurality of patient findings or said computing device generates said severity score;

(ii) said computing device generates estimated probabilities of said candidate diseases using said plurality of patient findings and said severity scores for each of said one or more genetic variants; and

(iii) said computing device generates the pertinence of said plurality of patient findings;

(iv) said computing device outputs a candidate disease list capable of being displayed, ranked by highest said estimated probabilities and outputs a patient finding list capable of being displayed and ranked by pertinence.

34. A method comprising the steps of:

(a) receiving, in a physical computing device, a plurality of patient findings for a patient being diagnosed, wherein said patient findings comprise genetic sequencing information associated with said patient comprising identification of one or more genetic variants associated with a gene, and for each, a measure of zygosity for said patient, wherein for each of said one or more genetic variants, a severity score is provided in said plurality of patient findings or said computing device generates said severity score;

(b) using said measure of zygosity for each said genetic variant to categorize said one or more genetic variants, in said computing device, as autosomal monoallelic, autosomal biallelic, X-linked monoallelic, X-linked biallelic, Y-linked, or mitochondrial;

(c) using said computing device to identify two or more genetic variants each associated with the same gene, said two genetic variants each having monoallelic zygosity, wherein said two or more genetic variants are collectively categorized as possibly having compound heterozygosity;

(d) using said computing device to determine a combined severity score for said gene in step (c) corresponding to the lesser of the highest two severity scores of said two or more genetic variants in step (c);

(e) repeating steps (c) and (d) for each gene having two or more associated genetic variants; and

(f) outputting a list comprising all or a subset of;

(i) each said gene having an associated genetic variant identified in step (a), and;

(ii) for each said gene having two or more genetic variants identified in step (c), said combined severity score associated with said gene determined in step (d); and

for each said gene having only one genetic variant identified in step (a), said severity score associated with said genetic variant,

wherein said list comprises genes with no previously described clinical findings, and wherein said list is capable of being displayed.