TREATMENT OF DISEASE VIA TRANSCRIPTION FACTOR MODULATION
20210188928 · 2021-06-24
Inventors
- John Barker Harley (Cincinnati, OH, US)
- Leah Kottyan (Cincinnati, OH, US)
- Matthew Weirauch (Cincinnati, OH, US)
Cpc classification
C12Q2600/106
CHEMISTRY; METALLURGY
C07K16/2896
CHEMISTRY; METALLURGY
A61K31/00
HUMAN NECESSITIES
C12Q1/6806
CHEMISTRY; METALLURGY
C12Q1/6883
CHEMISTRY; METALLURGY
International classification
C07K16/28
CHEMISTRY; METALLURGY
C12Q1/6806
CHEMISTRY; METALLURGY
Abstract
Disclosed herein are methods of treatment of various disease states in which an individual in need thereof if administered one or more therapeutic agents capable of modulating one or more transcription factors. Also disclosed are methods by which an individual may be treated for one or more disease states, in which loci in which transcription factors bind are detected.
Claims
1. A method of treating a disease with a therapeutic agent, in an individual in need thereof.
2. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 1, wherein said therapeutic agent is selected from an agent listed in column C of Table 1, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor ESR1.
3. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 2, wherein said therapeutic agent is selected from an agent listed in column C of Table 2, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor ESR2.
4. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 3, wherein said therapeutic agent is selected from an agent listed in column C of Table 3, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor AR.
5. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 4, wherein said therapeutic agent is selected from an agent listed in column C of Table 4, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor PGR.
6. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 5, wherein said therapeutic agent is selected from an agent listed in column C of Table 5, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor HDAC2.
7. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 6, wherein said therapeutic agent is selected from an agent listed in column C of Table 6, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor NR3C1.
8. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 7, wherein said therapeutic agent is selected from an agent listed in column C of Table 7, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor VDR.
9. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 8, wherein said therapeutic agent is selected from an agent listed in column C of Table 8, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor RXRA.
10. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 9, wherein said therapeutic agent is selected from an agent listed in column C of Table 9, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor RARG.
11. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 10, wherein said therapeutic agent is selected from an agent listed in column C of Table 10, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor NFκB1.
12. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 11, wherein said therapeutic agent is selected from an agent listed in column C of Table 11, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor CHD1.
13. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 12, wherein said therapeutic agent is selected from an agent listed in column C of Table 12, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor NOTCH1.
14. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 13, wherein said therapeutic agent is selected from an agent listed in column C of Table 13, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor STAT5B.
15. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 14, wherein said therapeutic agent is selected from an agent listed in column C of Table 14, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor HDAC1.
16. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 15, wherein said therapeutic agent is selected from an agent listed in column C of Table 15, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor CDK9.
17. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 16, wherein said therapeutic agent is selected from an agent listed in column C of Table 16, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor HDAC6.
18. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 17, wherein said therapeutic agent is selected from an agent listed in column C of Table 17, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor JUN.
19. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 18, wherein said therapeutic agent is selected from an agent listed in column C of Table 18, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor HDAC8.
20. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 19, wherein said therapeutic agent is selected from an agent listed in column C of Table 19, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor EP300.
21. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 20, wherein said therapeutic agent is selected from an agent listed in column C of Table 20, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor MYC.
22. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 21, wherein said therapeutic agent is selected from an agent listed in column C of Table 21, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor BRD4.
23. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 22, wherein said therapeutic agent is selected from an agent listed in column C of Table 22, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor NFATC1.
24. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 23, wherein said therapeutic agent is selected from an agent listed in column C of Table 23, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor RUNX1.
25. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 24, wherein said therapeutic agent is selected from an agent listed in column C of Table 24, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor TCF7L2.
26. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 25, wherein said therapeutic agent is selected from an agent listed in column C of Table 25, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor PHF8.
27. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 26, wherein said therapeutic agent is selected from an agent listed in column C of Table 26, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor HNF4A.
28. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 27, wherein said therapeutic agent is selected from an agent listed in column C of Table 27, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor MED1.
29. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 28, wherein said therapeutic agent is selected from an agent listed in column C of Table 28, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor NFκB2.
30. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 29, wherein said therapeutic agent is selected from an agent listed in column C of Table 29, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor CREBBP.
31. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 30, wherein said therapeutic agent is selected from an agent listed in column C of Table 30, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor STAT3.
32. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 31, wherein said therapeutic agent is selected from an agent listed in column C of Table 31, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor SMARCA4.
33. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 32, wherein said therapeutic agent is selected from an agent listed in column C of Table 32, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor BRD2.
34. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 33, wherein said therapeutic agent is selected from an agent listed in column C of Table 33, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor STAT4.
35. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 34, wherein said therapeutic agent is selected from an agent listed in column C of Table 34 and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor KDM5B.
36. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 35, wherein said therapeutic agent is selected from an agent listed in column C of Table 35, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor BRD3.
37. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 36, wherein said therapeutic agent is selected from an agent listed in column C of Table 36, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor EZH2.
38. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 37, wherein said therapeutic agent is selected from an agent listed in column C of Table 37, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor ATF1.
39. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 38, wherein said therapeutic agent is selected from an agent listed in column C of Table 38, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor CREB1.
40. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 39, wherein said therapeutic agent is selected from an agent listed in column C of Table 39, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor TP53.
41. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 40, wherein said therapeutic agent is selected from an agent listed in column C of Table 40, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor HNF4G.
42. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 41, wherein said therapeutic agent is selected from an agent listed in column C of Table 41, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor NR2C2.
43. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 42, wherein said therapeutic agent is selected from an agent listed in column C of Table 42, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor SIRT6.
44. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 43, wherein said therapeutic agent is selected from an agent listed in column C of Table 43 and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor BRCA1.
45. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 44, wherein said therapeutic agent is selected from an agent listed in column C of Table 44, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor NR1H2.
46. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 45, wherein said therapeutic agent is selected from an agent listed in column C of Table 45, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor KAT5.
47. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 46, wherein said therapeutic agent is selected from an agent listed in column C of Table 46 and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor CTNNB1.
48. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 47, wherein said therapeutic agent is selected from an agent listed in column C of Table 47, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor KDMSA.
49. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 48, wherein said therapeutic agent is selected from an agent listed in column C of Table 48, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor PPARG.
50. The method of claim 1, wherein said disease is selected from one or more diseases or conditions listed in column B of Table 49, wherein said therapeutic agent is selected from an agent listed in column C of Table 49, and wherein said therapeutic agent is administered in an amount effective to modulate the transcription factor ZEB1.
51. A method of treating a disease comprising the step of identifying one or more, or two or more, or three or more, or four or more, or five or more, or six or more, or seven or more, or eight or more, or nine or more, or ten or more, or 11 or more, or 12 or more, or 13 or more, or 14 or more, or 15 or more, or 16 or more, or 17 or more, or 18 or more, or 19 or more, or 20 or more, or 21 or more, or 22 or more, or 23 or more, or 24 or more, or 25 or more, or 26 or more, or 27 or more, or 28 or more, or 29 or more, or 30 or more, or 31 or more, or 32 or more, or 33 or more, or 34 or more, or 35 or more, or 36 or more, or 37 or more, or 38 or more, or 39 or more, or 40 or more, or more than 40 loci associated with said disease in an individual suspected of having or having said disease, and treating said individual with a compound that modulates a TF associated with said one or more loci.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0005] The application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.
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DETAILED DESCRIPTION
[0024] The following description of certain examples of the technology should not be used to limit its scope. Other examples, features, aspects, embodiments, and advantages of the technology will become apparent to those skilled in the art from the following description, which is by way of illustration, one of the best modes contemplated for carrying out the technology. As will be realized, the technology described herein is capable of other different and obvious aspects, all without departing from the technology. Accordingly, the drawings and descriptions should be regarded as illustrative in nature and not restrictive.
[0025] It is further understood that any one or more of the teachings, expressions, embodiments, examples, etc. described herein may be combined with any one or more of the other teachings, expressions, embodiments, examples, etc. that are described herein. The following-described teachings, expressions, embodiments, examples, etc. should therefore not be viewed in isolation relative to each other. Various suitable ways in which the teachings herein may be combined will be readily apparent to those of ordinary skill in the art in view of the teachings herein. Such modifications and variations are intended to be included within the scope of the claims.
[0026] The terms and expressions used herein have the ordinary meaning as is accorded to such terms and expressions with respect to their corresponding respective areas of inquiry and study except where specific meanings have otherwise been set forth herein.
[0027] As used herein and in the appended claims, the singular forms “a,” “and,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a method” includes a plurality of such methods and reference to “a dose” includes reference to one or more doses and equivalents thereof known to those skilled in the art, and so forth.
[0028] The term “about” or “approximately” means within an acceptable error range for the particular value as determined by one of ordinary skill in the art, which will depend in part on how the value is measured or determined, e.g., the limitations of the measurement system. For example, “about” can mean within 1 or more than 1 standard deviation, per the practice in the art. Alternatively, “about” can mean a range of up to 20%, or up to 10%, or up to 5%, or up to 1% of a given value. Alternatively, particularly with respect to biological systems or processes, the term can mean within an order of magnitude, preferably within 5-fold, and more preferably within 2-fold, of a value. Where particular values are described in the application and claims, unless otherwise stated the term “about” meaning within an acceptable error range for the particular value should be assumed.
[0029] The terms “individual,” “host,” “subject,” and “patient” are used interchangeably to refer to an animal that is the object of treatment, observation and/or experiment. Generally, the term refers to a human patient, but the methods and compositions may be equally applicable to non-human subjects such as other mammals. In some embodiments, the terms refer to humans. In further embodiments, the terms may refer to children.
[0030] The term “therapeutically effective amount,” as used herein, refers to any amount of a compound which, as compared to a corresponding subject who has not received such amount, results in improved treatment, healing, prevention, or amelioration of a disease, disorder, or side effect, or a decrease in the rate of advancement of a disease or disorder. The term also includes within its scope amounts effective to enhance normal physiological function.
[0031] The terms “treat,” “treating” or “treatment,” as used herein, refers to any treatment of a disease or condition associated with a disease or physiological parameter that is dysregulated (such as blood pressure dysregulation), particularly in a human, and includes a) preventing the disease from occurring in a subject that may be predisposed to the disease and or condition but has not yet been diagnosed as having it; b) inhibiting the disease or condition, and c) relieving the disease and/or condition. “Treatment” can also encompass delivery of an agent or administration of a therapy in order to provide for a pharmacological effect, even in the absence of a disease or condition. The term “treatment” is used in some aspects to refer to administration of a compound disclosed herein to mitigate a disease or disorder in a host, for example a mammal, more specifically a human. The term “treatment” can include preventing a disorder from occurring in a host, particularly when the host is predisposed to acquiring the disease, but has not yet been diagnosed, inhibiting the disorder; and/or alleviating or reversing the disorder. Insofar as the methods describe “preventing” a disease or disorder, it is understood that the term “prevent” does not require that the disease state be completely thwarted. Rather, the term “preventing” refers to the ability of the skilled artisan to identify a population that is susceptible to disorders, such that administration of the compounds disclosed herein can occur prior to onset of a disease. The term does not mean that the disease state must be completely avoided.
[0032] The term “pharmaceutically acceptable,” as used herein, refers to a material, such as a carrier or diluent, which does not abrogate the biological activity or properties of the compounds described herein. Such materials are administered to an individual without causing undesirable biological effects or interacting in a deleterious manner with any of the components of the composition in which it is contained.
[0033] The term “pharmaceutically acceptable salt,” as used herein, refers to a formulation of a compound that does not cause significant irritation to an organism to which it is administered and does not abrogate the biological activity and properties of the compounds described herein.
[0034] The terms “composition” or “pharmaceutical composition,” as used herein, refers to a mixture of at least one compound, such as the compounds provided herein, with at least one and optionally more than one other pharmaceutically acceptable chemical components, such as carriers, stabilizers, diluents, dispersing agents, suspending agents, thickening agents, and/or excipients.
[0035] The term “carrier” applied to pharmaceutical compositions of the disclosure refers to a diluent, excipient, or vehicle with which an active compound (e.g., dextromethorphan) is administered. Such pharmaceutical carriers can be sterile liquids, such as water, saline solutions, aqueous dextrose solutions, aqueous glycerol solutions, and oils, including those of petroleum, animal, vegetable, or synthetic origin, such as peanut oil, soybean oil, mineral oil, sesame oil and the like. Suitable pharmaceutical carriers are described in “Remington's Pharmaceutical Sciences” by E. W. Martin, 18th Edition.
[0036] The term “modulated” or “modulation” or “regulated” or “regulation” can refer to both up regulation, activation, or stimulation, for example, by agonizing or potentiating, and down regulation, inhibition or suppression, for example by antagonizing, decreasing or inhibiting, unless otherwise specified or clear from the context of a specific usage.
[0037] Explaining the genetics of many diseases is challenging because most associations localize to regulatory regions. Applicant has tested the hypothesis that transcription factors (TFs) are associated with multiple loci of individual complex genetic disorders with a novel computational method for discovering disease-driving mechanisms.
TABLE-US-00001 TABLE 1 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: ESR1 Breast cancer 1-[4-(OCTAHYDRO-PYRIDO[1,2- Breast_cancer_early_onset A]PYRAZIN-2-YL)-PHEN . . . Central_corneal_thickness 1-[4-(OCTAHYDRO-PYRIDO[1,2- Coronary_heart_disease A]PYRAZIN-2-YL)-PHENYL]-2-PHENYL- Inflammatory_bowel_disease 1,2,3,4-TETRAHYDRO-ISOQUINOLIN-6- Interstitial_lung_disease OL Juvenile_idiopathic_arthritis 17-METHYL-17-ALPHA- Lipoprotein- DIHYDROEQUILENIN associated_phospholipase_A2_ 2-PHENYL-1-[4-(2-PIPERIDIN-1-YL- activity_and_mass ETHOXY)-PHENYL] . . . Prostate_cancer 2-PHENYL-1-[4-(2-PIPERIDIN-1-YL- Renal_cell_carcinoma ETHOXY)-PHENYL]-1,2,3,4- TETRAHYDRO-ISOQUINOLIN-6-OL (2R,3R,4S)-3-(4-HYDROXYPHENYL)-4- METHYL-2-[4-(2 . . . (2R,3R,4S)-3-(4-HYDROXYPHENYL)-4- METHYL-2-[4-(2-PYRROLIDIN-1- YLETHOXY)PHENYL]CHROMAN-6-OL (3AS,4R,9BR)-2,2-DIFLUORO-4-(4- HYDROXYPHENYL)-1 . . . (3AS,4R,9BR)-2,2-DIFLUORO-4-(4- HYDROXYPHENYL)-1,2,3,3A,4,9B- HEXAHYDROCYCLOPENTA[C]CHROME N-8-OL (3AS,4R,9BR)-4-(4-HYDROXYPHENYL)- 1,2,3,3A,4,9B- . . . (3AS,4R,9BR)-4-(4-HYDROXYPHENYL)- 1,2,3,3A,4,9B- HEXAHYDROCYCLOPENTA[C]CHROME N-9-OL (3AS,4R,9BR)-4-(4-HYDROXYPHENYL)- 6-(METHOXYMETH . . . (3AS,4R,9BR)-4-(4-HYDROXYPHENYL)- 6-(METHOXYMETHYL)-1,2,3,3A,4,9B- HEXAHYDROCYCLOPENTA[C]CHROME N-8-OL 3-CHLORO-2-(4-HYDROXYPHENYL)-2H- INDAZOL-5-OL 3-ETHYL-2-(4-HYDROXYPHENYL)-2H- INDAZOL-5-OL 4-[(1S,2R,5S)-4,4,8-TRIMETHYL-3- OXABICYCLO[3.3 . . . . 4-[(1S,2R,5S)-4,4,8-TRIMETHYL-3- OXABICYCLO[3.3.1]NON-7-EN-2- YL]PHENOL 4-[(1S,2S,5S)-5-(HYDROXYMETHYL)- 6,8,9-TRIMETHYL . . . 4-[(1S,2S,5S)-5-(HYDROXYMETHYL)- 6,8,9-TRIMETHYL-3- OXABICYCLO[3.3.1]NON-7-EN-2- YL]PHENOL 4-[(1S,2S,5S)-5-(HYDROXYMETHYL)-8- METHYL-3-OXAB . . . 4-[(1S,2S,5S)-5-(HYDROXYMETHYL)-8- METHYL-3-OXABICYCLO[3.3.1]NON-7- EN-2-YL]PHENOL 4-[(1S,2S,5S,9R)-5-(HYDROXYMETHYL)- 8,9-DIMETHYL . . . 4-[(1S,2S,5S,9R)-5-(HYDROXYMETHYL)- 8,9-DIMETHYL-3- OXABICYCLO[3.3.1]NON-7-EN-2- YL]PHENOL 4-(6-HYDROXY-1H-INDAZOL-3- YL)BENZENE-1,3-DIOL [5-HYDROXY-2-(4-HYDROXYPHENYL)- 1-BENZOFURAN-7-Y . . . [5-HYDROXY-2-(4-HYDROXYPHENYL)- 1-BENZOFURAN-7-YL]ACETONITRILE (9ALPHA,13BETA,17BETA)-2-[(1Z)-BUT- 1-EN-1-YL]ES . . . (9ALPHA,13BETA,17BETA)-2-[(1Z)-BUT- 1-EN-1-YL]ESTRA-1,3,5(10)-TRIENE-3,17- DIOL (9BETA,11ALPHA,13ALPHA,14BETA,17A LPHA)-11-(METH . . . (9BETA,11ALPHA,13ALPHA,14BETA,17A LPHA)-11-(METHOXYMETHYL)ESTRA- 1(10),2,4-TRIENE-3,17-DIOL AFIMOXIFENE ALLYLESTRENOL ANASTROZOLE ARZOXIFENE BAZEDOXIFENE CHLOROTRIANISENE CLOMIFENE CLOMIPHENE CLOMIPHENE CITRATE COMPOUND 19 COMPOUND 4-D CONJUGATED ESTROGENS DANAZOL DEHYDROEPIANDROSTERONE DESOGESTREL DIENESTROL DIENOGEST DIETHYL (1R,2S,3R,4S)-5,6-BIS(4- HYDROXYPHENYL)- . . . DIETHYL (1R,2S,3R,4S)-5,6-BIS(4- HYDROXYPHENYL)-7- OXABICYCLO[2.2.1]HEPT-5-ENE-2,3- DICARBOXYLATE DIETHYLSTILBESTROL DIMETHYL (1R,4S)-5,6-BIS(4- HYDROXYPHENYL)-7-OXA . . . DIMETHYL (1R,4S)-5,6-BIS(4- HYDROXYPHENYL)-7- OXABICYCLO[2.2.1]HEPTA-2,5-DIENE- 2,3-DICARBOXYLATE ENDOXIFEN ESTRADIOL ESTRADIOL CYPIONATE ESTRADIOL VALERATE ESTRAMUSTINE ESTRIOL ESTRONE ESTROPIPATE ETHINYL ESTRADIOL ETHYNODIOL ETHYNODIOL DIACETATE ETONOGESTREL EXEMESTANE FISPEMIFENE FLUOXYMESTERONE FULVESTRANT GENISTEIN HEXESTROL IODINE LASOFOXIFENE LEFLUNOMIDE LETROZOLE LEVONORGESTREL MEGESTROL MELATONIN MESTRANOL METHYL-PIPERIDINO-PYRAZOLE MITOTANE NALOXONE NORELGESTROMIN NORGESTIMATE NORGESTREL OSPEMIFENE PROGESTERONE QUINESTROL RALOXIFEN RALOXIFENE RALOXIFENE CORE TAMOXIFEN TAMOXIFEN CITRATE TOREMIFENE TRILOSTANE
TABLE-US-00002 TABLE 2 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: ESR2 Parkinson_disease 1-CHLORO-6-(4-HYDROXYPHENYL)-2-NAPHTHOL Type_l_diabetes 2-(4-HYDROXY-PHENYL)BENZOFURAN-5-OL 2-(5-HYDROXY-NAPHTHALEN-1-YL)-1,3- BENZOOXAZOL-6-OL 3-(3-FLUORO-4-HYDROXYPHENYL)-7-HYDROXY-1- NAPHTH . . . 3-(3-FLUORO-4-HYDROXYPHENYL)-7-HYDROXY-1- NAPHTHONITRILE 3-(6-HYDROXY-NAPHTHALEN-2-YL)- BENZO[D]ISOOXAZOL . . . 3-(6-HYDROXY-NAPHTHALEN-2-YL)- BENZO[D]ISOOXAZOL-6-OL (3AS,4R,9BR)-2,2-DIFLUORO-4-(4- HYDROXYPHENYL)-1 . . . (3AS,4R,9BR)-2,2-DIFLUORO-4-(4- HYDROXYPHENYL)-1,2,3,3A,4,9B- HEXAHYDROCYCLOPENTA[C]CHROMEN-8-OL (3AS,4R,9BR)-2,2-DIFLUORO-4-(4- HYDROXYPHENYL)-6 . . . (3AS,4R,9BR)-2,2-DIFLUORO-4-(4- HYDROXYPHENYL)-6-(METHOXYMETHYL)- 1,2,3,3A,4,9B- HEXAHYDROCYCLOPENTA[C]CHROMEN-8-OL (3AS,4R,9BR)-4-(4-HYDROXYPHENYL)-6- (METHOXYMETH . . . (3AS,4R,9BR)-4-(4-HYDROXYPHENYL)-6- (METHOXYMETHYL)-1,2,3,3A,4,9B- HEXAHYDROCYCLOPENTA[C]CHROMEN-8-OL 3-BROMO-6-HYDROXY-2-(4-HYDROXYPHENYL)- 1H-INDEN- . . . 3-BROMO-6-HYDROXY-2-(4-HYDROXYPHENYL)- 1H-INDEN-1-ONE 4-(4-HYDROXYPHENYL)-1-NAPHTHALDEHYDE OXIME 571-20-0 5-HYDROXY-2-(4-HYDROXYPHENYL)-1- BENZOFURAN-7-CA . . . 5-HYDROXY-2-(4-HYDROXYPHENYL)-1- BENZOFURAN-7-CARBONITRILE [5-HYDROXY-2-(4-HYDROXYPHENYL)-1- BENZOFURAN-7-Y . . . [5-HYDROXY-2-(4-HYDROXYPHENYL)-1- BENZOFURAN-7-YL]ACETONITRILE AFIMOXIFENE BAZEDOXIFENE BISPHENOL A CHLOROTRIANISENE DEHYDROEPIANDROSIERONE DIETHYLSTILBESTROL ESTRADIOL ESTRAMUSTINE ESTRAMUSTINE PHOSPHATE SODIUM ESTRIOL ESTRONE ESTROPIPATE ETHINYL ESTRADIOL EXEMESTANE FISPEMIFENE FULVESTRANT GENISTEIN HPTE LASOFOXIFENE N-BUTYL-11-[(7R,8R,9S,13S,14S,17S)-3,17- DIHYDRO . . . N-BUTYL-11-[(7R,8R,9S,13S,14S,17S)-3,17- DIHYDROXY-13-METHYL-7,8,9,11,12,13,14,15,16,17- DECAHYDRO-6H-CYCLOPENTA[A]PHENANTHREN- 7-YL]-N-METHYLUNDECANAMIDE OSPEMIFENE PHTPP PRINABEREL RALOXIFEN RALOXIFENE RALOXIFENE HYDROCHLORIDE TAMOXIFEN TOREMIFENE TRILOSTANE
TABLE-US-00003 TABLE 3 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: AR Interstitial_lung_disease (2S)-N-(4-CYANO-3-IODOPHENYL)-3-(4- Mean_platelet_volume CYANOPHENOXY . . . Prostate_cancer (2S)-N-(4-CYANO-3-IODOPHENYL)-3-(4- CYANOPHENOXY)-2-HYDROXY-2- METHYLPROPANAMIDE 4-{[(1R,2S)-1,2-DIHYDROXY-2-METHYL-3- (4-NITROPH . . . 4-{[(1R,2S)-1,2-DIHYDROXY-2-METHYL-3- (4-NITROPHENOXY)PROPYL]AMINO}-2- (TRIFLUOROMETHYL)BENZONITRILE 4-[(7R,7AS)-7-HYDROXY-1,3- DIOXOTETRAHYDRO-1H-PY . . . 4-[(7R,7AS)-7-HYDROXY-1,3- DIOXOTETRAHYDRO-1H-PYRROLO[1,2- C]IMIDAZOL-2(3H)-YL]-1- NAPHTHONITRILE (5S,8R,9S,10S,13R,14S,17S)-13-{2-[(3,5- DIFLUORO . . . (5S,8R,9S,10S,13R,14S,17S)-13-{2-[(3,5- DIFLUOROBENZYL)OXY]ETHYL}-17- HYDROXY-10- METHYLHEXADECAHYDRO-3H- CYCLOPENTA[A]PHENANTHREN-3-ONE ABIRATERONE ANDARINE ARN-509 ASC-J9 BICALUTAMIDE BISPHENOL A CALUSTERONE CYPROTERONE CYPROTERONE ACETATE DANAZOL DROMOSTANOLONE DROSPIRENONE DROSTANOLONE ENOBOSARM ENZALUTAMIDE EPALRESTAT ETHYLESTRENOL FIDARESTAT FLUDROCORTISONE FLUFENAMIC ACID FLUOXYMESTERONE FLUTAMIDE GALETERONE GLPG0492 HYDROXYFLUTAMIDE KETOCONAZOLE LEVONORGESTREL LGD-2941 METHYLTESTOS1ERONE METHYLTRIENOLONE MIBOLERONE MIFEPRISTONE NANDROLONE NANDROLONE DECANOATE NANDROLONE PHENPROPIONATE NILUTAMIDE OXANDROLONE OXYMETHOLONE PRASTERONE SORBINIL SPIRONOLACTONE STANOZOLOL TESTOSTERONE TESTOSTERONE CYPIONATE TESTOSTERONE ENANTHATE TESTOSTERONE PROPIONATE TESTOSTERONE UNDECANOATE ZENARESTAT
TABLE-US-00004 TABLE 4 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: PGR Breast _cancer ALLYLESTRENOL Migraine ANASTROZOLE Polycystic_ovary_ ASOPRISNIL syndrome DANAZOL DESOGESTREL DIENOGEST DROSPIRENONE DYDROGESTERONE ETHYNODIOL ETHYNODIOL DIACETATE ETONOGESTREL FLUTICASONE PROPIONATE GESTODENE HYDROXYPROGESTERONE CAPROATE LETROZOLE LEVONORGESTREL MEDROXYPROGESTERONE MEDROXYPROGESTERONE ACETATE MEGESTROL MEGESTROL ACETATE METHYLTRIENOLONE MIFEPRISTONE NORELGESTROMIN NORETHINDRONE NORETHINDRONE ACETATE NORETHYNODREL NORGESTIMATE NORGESTREL ONAPRISTONE PROGESTERONE PROMEGESTONE SPIRONOLACTONE TAMOXIFEN TANAPROGET TELAPRISTONE ULIPRISTAL ULIPRISTAL ACETATE ZK112993
TABLE-US-00005 TABLE 5 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: HDAC2 Blood_metabolite_levels 4SC-202 Cholesterol_total AMINOPHYLLINE Chronic_kidney_disease APICIDIN Height BELINOSTAT Mean_corpuscular_hemoglobin BUTYRIC ACID Mean_corpuscular_volume CHIDAMIDE Mean_platelet_volume CHR-3996 Multiple_sclerosis CUDC-101 Phospholipid_levels_plasma DACINOSTAT QRS_duration ENTINOSTAT Red_blood_cell_traits GIVINOSTAT Testicular_germ_cell_tumor LOVASTATIN Type_2_diabetes MOCETINOSTAT Urate_levels OXTRIPHYLLINE PANOBINOSTAT PCI-24781 PIVANEX PRACINOSTAT RESMINOSTAT ROMIDEPSIN SCRIPTAID THEOPHYLLINE TRICHOSTATIN A VALPROIC ACID VORINOSTAT
TABLE-US-00006 TABLE 6 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: NR3Cl Bladder_cancer ALCLOMETASONE Height ALCLOMETASONE Inflammatory_bowel_disease DIPROPIONATE Intracranial_aneurysm AMCINONIDE Phospholipid_levels_plasma BECLOMETHASONE Prostate_cancer BECLOMETHASONE Vitiligo DIPROPIONATE BETAMETHASONE BETAMETHASONE ACETATE BETAMETHASONE DIPROPIONATE BETAMETHASONE SODIUM PHOSPHATE BETAMETHASONE VALERATE BUDESONIDE CICLESONIDE CLOBETASOL CLOBETASOL PROPIONATE CLOCORTOLONE CLOCORTOLONE PIVALATE CORTISONE ACETATE DESONIDE DESOXIMETASONE DEXAMETHASONE DEXAMETHASONE ACETATE DEXAMETHASONE SODIUM PHOSPHATE DIFLORASONE DIFLORASONE DIACETATE DIFLUPREDNATE FLUDROCORTISONE FLUMETHASONE PIVALATE FLUNISOLIDE FLUOCINOLONE ACETONIDE FLUOCINONIDE FLUOROMETHOLONE FLUOROMETHOLONE ACETATE FLUOXYMESTERONE FLUPREDNISOLONE FLURANDRENOLIDE FLUTICASONE FLUTICASONE FUROATE FLUTICASONE PROPIONATE HALCINONIDE HALOBETASOL PROPIONATE HYDROCORTAMATE HYDROCORTISONE HYDROCORTISONE ACETATE HYDROCORTISONE BUTYRATE HYDROCORTISONE CYPIONATE HYDROCORTISONE SODIUM PHOSPHATE HYDROCORTISONE SODIUM SUCCINATE HYDROCORTISONE VALERATE LOTEPREDNOL LOTEPREDNOL ETABONATE MEDRYSONE MEGESTROL ACETATE MEPREDNISONE METHYLPREDNISOLONE METHYLPREDNISOLONE ACETATE MIFEPRISTONE MOMETASONE MOMETASONE FUROATE ONAPRISTONE PARAMETHASONE PARAMETHASONE ACETATE PREDNICARBATE PREDNISOLONE PREDNISOLONE ACETATE PREDNISOLONE SODIUM PHOSPHATE PREDNISOLONE TEBUTATE PREDNISONE RIMEXOLONE SPIRONOLACTONE TRIAMCINOLONE TRIAMCINOLONE ACETONIDE TRIAMCINOLONE DIACETATE TRIAMCINOLONE HEXACETONIDE ZK112993
TABLE-US-00007 TABLE 7 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: VDR Ankylosing_spondylitis 1,25-DIHYDROXYVITAMIN D3 Basal_cell_carcinoma 1,3-CYCLOHEXANEDIOL,4- Breast_cancer METHYLENE-5-[(2E)-[(1S,3 . . . Celiac_disease 1,3-CYCLOHEXANEDIOL,4- Cholesterol_total METHYLENE-5-[(2E)- Chronic_lymphocytic_leukemia [(1S,3AS,7AS)-OCTAHYDRO-1-(5- Crohns_disease HYDROXY-5-METHYL-1,3- Fibrinogen HEXADIYNYL)-7A-METHYL-4H- Height INDEN-4- IgG_glycosylation YLIDENE]ETHYLIDENE]-, Inflammatory_bowel_disease (1R,3S,5Z) Juvenile_idiopathic_arthritis 19356-17-3 Mean_corpuscular_hemoglobin 5-{2-[1-(1-METHYL-PROPYL)-7A- Mean_platelet_volume METHYL-OCTAHYDRO-I . . . Multiple_sclerosis 5-{2-[1-(1-METHYL-PROPYL)-7A- Primary_biliary_cirrhosis METHYL-OCTAHYDRO-INDEN-4- Rheumatoid_arthritis YLIDENE]-ETHYLIDENE}-2- Systemic_lupus_erythematosus METHYLENE-CYCLOHEXANE- Type_1_diabetes 1,3-DIOL Ulcerative_colitis ALFACALCIDOL Vitiligo BONEFOS CALCIFEDIOL CALCIPOTRIENE CALCIPOTRIOL CALCITRIOL CALCIUM CHOLECALCIFEROL DIHYDROTACHYSTEROL DOXERCALCIFEROL ELOCALCITOL ERGOCALCIFEROL INECALCITOL LEXACALCITOL LITHOCHOLIC ACID PARICALCITOL SEOCALCITOL TACALCITOL
TABLE-US-00008 TABLE 8 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: RXRA Blood_metabolite_levels ACITRETIN Blood_metabolite_ratios ADAPALENE Cholesterol_total ALITRETINOIN Chronic_kidney_disease BEXAROTENE Fasting_glucose- ETODOLAC related_traits_interaction_with_BMI ETRETINATE Height METHOPRENE Inflammatory_bowel_disease ACID LDL_cholesterol R-ETODOLAC Mean_platelet_volume Metabolic_syndrome Metabolite_levels Triglycerides Urate_levels
TABLE-US-00009 TABLE 9 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: RARG Blood_metabolite_levels ACITRETIN Blood_metabolite_ratios ADAPALENE Height AHPN Inflammatory_bowel_disease ALITRETINOIN Juvenile_idiopathic_arthritis CD564 Multiple_sclerosis DODECYL-ALPHA-D- Red_blood_cell_traits MALTOSIDE Serum_albumin_level ETRETINATE FENRETINIDE MM 11253 TAZAROTENE TTNPB
TABLE-US-00010 TABLE 10 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: NFKB1 Acute_lymphoblastic_leukemia_B- BARDOXOLONE cell_precursor BORTEZOMIB Ankylosing_spondylitis THALIDOMIDE Atopic_dermatitis TRIFLUSAL Body_mass_index Celiac_disease Chronic_lymphocytic_leukemia Height IgG_glycosylation Inflammatory_bowel_disease Juvenile_idiopathic_arthritis Kawasaki_disease Mean_corpuscular_hemoglobin Mean_corpuscular_volume Multiple_sclerosis Primary_biliary_cirrhosis Rheumatoid_arthritis Systemic_lupus_erythematosus Type_1_diabetes Ulcerative_colitis Vitiligo
TABLE-US-00011 TABLE 11 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: CHD1 Crohns_disease EPIRUBICIN HDL_cholesterol Height Inflammatory_bowel_disease Lipid_metabolism_phenotypes Mean_corpuscular_volume Menopause_age_at_onset Multiple_sclerosis Red_blood_cell_traits Rheumatoid_arthritis Schizophrenia Systemic_lupus_erythematosus Systemic_sclerosis Telomere_length Triglycerides Type_1_diabetes Ulcerative_colitis Vitiligo
TABLE-US-00012 TABLE 12 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: Ankylosing_spondylitis RO4929097 NOTCH1 Cholesterol_total Crohns_disease Graves_disease Height Inflammatory_bowel_disease Lipid_metabolism_phenotypes Mean_corpuscular_hemoglobin Multiple_sclerosis Red_blood_cell_traits Rheumatoid_arthritis Schizophrenia Systemic_lupus_erythematosus
TABLE-US-00013 TABLE 13 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: STAT5B Celiac_disease DASATINIB Chronic_lymphocytic_leukemia Graves_disease Inflammatory_bowel_disease LDL_cholesterol Multiple_sclerosis Rheumatoid_arthritis Self-reported_allergy Systemic_lupus_erythematosus Type_1_diabetes Ulcerative_colitis
TABLE-US-00014 TABLE 14 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: HDACl Blood_metabolite_levels 4SC-202 Blood_metabolite_ratios APICIDIN Cholesterol_total BELINOSTAT Glycated_hemoglobin_levels BUTYRIC ACID Height CBHA Inflammatory_bowel_disease CHEMBL152543 Mean_corpuscular_hemoglobin CHEMBL191091 Mean_corpuscular_volume CHEMBL491491 Metabolite_levels CHIDAMIDE Red_blood_cell_traits CHLAMYDOCIN Systemic_lupus_erythematosus CHR-3996 CUDC-101 DACINOSTAT DEPUDECIN ENTINOSTAT GIVINOSTAT MOCETINOSTAT NEXTURASTAT A OXAMFLATIN PANOBINOSTAT PCI-24781 PIVANEX PRACINOSTAT PYROXAMIDE RESMINOSTAT RG2833 ROMIDEPSIN SB-639 SCRIPTAID SK-7041 TRICHOSTATIN A VALPROIC ACID VORINOSTAT
TABLE-US-00015 TABLE 15 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: CDK9 Atopic_dermatitis DINACICLIB Complement_C3_and_C4_levels FLAVOPIRIDOL Height P276-00 Mean_platelet_volume RGB-286638 Menopause_age_at_onset Systemic_lupus_erythematosus
TABLE-US-00016 TABLE 16 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: HDAC6 Ankylosing_spondylitis ACY-1215 Chronic_lymphocytic_leukemia BELINOSTAT Crohns_disease BUFEXAMAC Mean_corpuscular_volume CUDC-101 Multiple_sclerosis DACINOSTAT QT_interval GIVINOSTAT NEXTURASTAT A PANOBINOSTAT PCI-24781 PRACINOSTAT RESMINOSTAT ROMIDEPSIN SCRIPTAID TRICHOSTATIN A TUBACIN VORINOSTAT
TABLE-US-00017 TABLE 17 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: JUN Blood_metabolite_levels IRBESARTAN Mean_corpuscular_volume T-5224 Red_blood_cell_traits VINBLASTINE Ulcerative_colitis
TABLE-US-00018 TABLE 18 Column A Transcription Column B Column C Factor Disease State Treatment Agent TF: HDAC8 Parkinson_disease 4-DIMETHYLAMINO-N-(6- Red_blood_cell_traits HYDROXYCARBAMOYETHYL)BENZA . . . Systemic_lupus_erythematosus 4-DIMETHYLAMINO-N-(6- HYDROXYCARBAMOYETHYL)BENZAMIDE- N-HYDROXY-7-(4-DIMETHYLAMINO- BENZOYL)AMINOHEPTANAMIDE 4SC-202 5-(4-METHYL-BENZOYLAMINO)- BIPHENYL-3,4′-DICARBO . . . 5-(4-METHYL-BENZOYLAMINO)- BIPHENYL-3,4′-DICARBOXYLIC ACID 3-DIMETHYLAMIDE-4′- HYDROXYAMIDE APICIDIN BELINOSTAT BUTYRIC ACID CHR-3996 CUDC-101 DACINOSTAT ENTINOSTAT GIVINOSTAT N-HYDROXY-4-(METHYL{[5-(2- PYRIDINYL)-2-THIENYL] . . . N-HYDROXY-4-(METHYL{[5-(2- PYRIDINYL)-2- THIENYL]SULFONYL}AMINO)BENZAMIDE PANOBINOSTAT PCI-24781 PIVANEX PRACINOSTAT RESMINOSTAT ROMIDEPSIN SCRIPTAID TRICHOSTATIN A VALPROIC ACID VORINOSTAT
TABLE-US-00019 TABLE 19 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: EP300 Alzheimer_disease ANACARDIC Alzheimer_disease_late_onset ACID Ankylosing_spondylitis CURCUMIN Atopic_dermatitis GARCINOL Basal_cell_carcinoma LYS-COA Blood_metabolite_levels PLUMBAGIN Celiac_disease Central_corneal_thickness Cholesterol_total Chronic_lymphocytic_leukemia Crohns_disease Endometriosis Fasting_glucose- related_traits_interaction_with_BMI Fibrinogen Glycemic_traits HDL_cholesterol Heart_rate Height IgG_glycosylation Inflammatory_bowel_disease LDL_cholesterol Lipid_metabolism_phenotypes Lipoprotein- associated_phospholipase_A2_ac- tivity_and_mass Mean_corpuscular_hemoglobin Mean_corpuscular_volume Mean_platelet_volume Metabolic_syndrome Migraine Multiple_sclerosis Pancreatic_cancer Platelet_counts Primary_biliary_cirrhosis Primary_tooth_develop- ment_time_to_first_tooth_eruption Pulmonary_function Pulmonary_function_interaction QRS_duration Red_blood_cell_traits Renal_cell_carcinoma Renal_function-related_traits_BUN Rheumatoid_arthritis Self-reported_allergy Systemic_lupus_erythematosus Triglycerides Type_1_diabetes Ulcerative_colitis Urate_levels Vitiligo
TABLE-US-00020 TABLE 20 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: MYC Ankylosing_spondylitis ALISERTIB Bladder_cancer DINACICLIB Blood_metabolite_levels Blood_metabolite_ratios Body_mass_index Cholesterol_total Chronic_lymphocytic_leukemia Crohns_disease Esophageal_cancer_squamous_cell Fibrinogen Glycated_hemoglobin_levels Glycemic_traits_pregnancy HDL_cholesterol Heart_rate Height IgG_glycosylation Inflammatory_bowel_disease Interstitial_lung_disease Juvenile_idiopathic_arthritis Lipid_metabolism_phenotypes Lipoprotein- associated_phospholipase_A2_acti- vity_and_mass Lung_cancer Mean_corpuscular_hemoglobin Mean_corpuscular_hemoglobin_con- centration Mean_corpuscular_volume Mean_platelet_volume Menopause_age_at_onset Metabolic_syndrome Metabolite_levels Migraine Multiple_sclerosis Pancreatic_cancer Phospholipid_levels_plasma Platelet_counts QRS_duration Red_blood_cell_traits Renal_cell_carcinoma Renal_function-related_traits_BUN Resting_heart_rate Rheumatoid_arthritis Schizophrenia Systemic_lupus_erythematosus Testicular_germ_cell_tumor Triglycerides Ulcerative_colitis Vitiligo
TABLE-US-00021 TABLE 21 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: BRD4 Acute_lymphoblastic_leukemia B- CPI-203 cell_precursor GW841819X Ankylosing_spondylitis I-BET151 Bipolar_disorder MS417 Body_mass_index MS436 Celiac_disease PFI-1 Cholesterol_total XD14 Chronic_lymphocytic_leukemia Crohns_disease End-stage_coagulation Esophageal_cancer_squamous_cell Fasting_glucose- related_traits_interaction_with_BMI Fibrinogen Glycated_hemoglobin_levels HDL_cholesterol Height IgG_glycosylation Inflammatory_bowel_disease Interstitial_lung_disease Juvenile_idiopathic_arthritis Kawasaki_disease Mean_corpuscular_hemoglobin Mean_corpuscular_volume Mean_platelet_volume Menopause_age_at_onset Metabolic_syndrome Multiple_sclerosis Parkinson_disease Phospholipid_levels_plasma Platelet_counts Red_blood_cell_traits Rheumatoid_arthritis Systemic_lupus_erythematosus Testicular_germ_cell_tumor Triglycerides Type_1_diabetes Ulcerative_colitis
TABLE-US-00022 TABLE 22 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: Asthma_and_hay_fever PSEUDO- NFATCl Atopic_dermatitis EPHEDRINE Basal_cell_carcinoma Behcets_disease Celiac_disease Chronic_lymphocytic_leukemia Crohns_disease IgG_glycosylation Inflammatory_bowel_disease Juvenile_idiopathic_arthritis Mean_corpuscular_hemoglobin Mean_platelet_volume Multiple_sclerosis Platelet_counts Primary_biliary_cirrhosis Prostate_cancer Red_blood_cell_traits Rheumatoid_arthritis Systemic_lupus_erythematosus Systemic_sclerosis Type_1_diabetes Ulcerative_colitis
TABLE-US-00023 TABLE 23 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: RUNX1 Acute_lymphoblastic_leukemia_B- METHACHOLINE cell_precursor CHLORIDE Alzheimer_disease Alzheimer_disease_late_onset Ankylosing_spondylitis Central_corneal_thickness Coronary_heart_disease Crohns_disease Fibrinogen HDL_cholesterol Height Inflammatory_bowel_disease Juvenile_idiopathic_arthritis Mean_corpuscular_hemoglobin Mean_platelet_volume Multiple_sclerosis Platelet_counts Red_blood_cell_traits Rheumatoid_arthritis Systemic_lupus_erythematosus Takayasu_arteritis Ulcerative_colitis
TABLE-US-00024 TABLE 24 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: TCF7L2 Basal_cell_carcinoma REPAGLINIDE Breast_cancer Chronic_lymphocytic_leukemia Fasting_glucose- related_traits_interaction_with_BMI Fibrinogen Height Hodgkin_lymphoma Inflammatory_bowel_disease Lipoprotein- associated_phospholipase_A2_ac- tivity_and_mass Mean_corpuscular_hemoglobin Mean_corpuscular_volume Ovarian_cancer Primary_biliary_cirrhosis Primary_tooth_develop- ment_time_to_first_tooth_eruption Red_blood_cell_traits Schizophrenia Serum_albumin_level Systemic_lupus_erythematosus
TABLE-US-00025 TABLE 25 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: PHF8 Blood_metabolite_levels DAMINOZIDE Esophageal_cancer_squamous_cell Fasting_glucose- related_traits_interaction_with_BMI Glycated_hemoglobin_levels HDL_cholesterol Heart_rate Height Inflammatory_bowel_disease Interstitial_lung_disease Mean_corpuscular_hemoglobin Mean_platelet_volume Menopause_age_at_onset Multiple_sclerosis Phospholipid_levels_plasma Red_blood_cell_traits Schizophrenia Systemic_lupus_erythematosus Telomere_length
TABLE-US-00026 TABLE 26 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: HNF4A Blood_metabolite_levels LINOLEIC ACID Blood_metabolite_ratios Breast_cancer C-reactive_protein Cholesterol_total Colorectal_cancer HDL_cholesterol Inflammatory_bowel_disease LDL_cholesterol Lipid_metabolism_phenotypes Metabolic_syndrome Metabolite_levels Multiple_sclerosis Primary_biliary_cirrhosis Sphingolipid_levels Triglycerides Urate_levels
TABLE-US-00027 TABLE 27 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: MED1 ANCA-associated_vasculitis 5-{2-[1-(1-METHYL- Blood_metabolite_levels PROPYL)-7A-METHYL- Blood_metabolite_ratios OCTAHYDRO-I . . . Celiac_disease 5-{2-[1-(1-METHYL- Crohns_disease PROPYL)-7A-METHYL- Educational_attainment OCTAHYDRO-INDEN-4- Graves_disease YLIDENE]- Height ETHYLIDENE}- IgG_glycosylation 2-METHYLENE- Inflammatory_bowel_disease CYCLOHEXANE- Kawasaki_disease 1,3-DIOL Prostate_cancer Rheumatoid_arthritis Systemic_lupus_erythe- matosus Takayasu_arteritis Type_1_diabetes Vitiligo
TABLE-US-00028 TABLE 28 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: NFKB2 Celiac_disease TRIPTOSAR Height Inflammatory_bowel_disease Mean_corpuscular_hemoglobin Multiple_sclerosis Primary_biliary_cirrhosis Rheumatoid_arthritis Systemic_lupus_erythematosus Type_1_diabetes Ulcerative_colitis Urinary_metabolites_H- NMR_features Vitiligo
TABLE-US-00029 TABLE 29 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: Acute_lymphoblastic_leukemia_B- 9-ACETYL-2,3,4,9- CREBBP cell_precursor TETRAHYDRO- Celiac_disease 1H-CARBAZOL-1- Crohns_disease ONE ISCHEMIN Inflammatory_bowel_disease Mean_corpuscular_hemoglobin Mean_corpuscular_volume Multiple_sclerosis Red_blood_cell_traits Rheumatoid_arthritis Systemic_lupus_erythematosus Type_1_diabetes
TABLE-US-00030 TABLE 30 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: STAT3 Chronic_lymphocytic_leukemia ATIPRIMOD Crohns_disease DCL000217 Graves_disease Inflammatory_bowel_disease Juvenile_idiopathic_arthritis Lipoprotein- associated_phospholipase_A2_ac- tivity_and_mass Multiple_sclerosis Pancreatic_cancer Systemic_lupus_erythematosus Vitiligo
TABLE-US-00031 TABLE 31 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: Alzheimer_disease CISPLATINUM SMARCA4 Blood_pressure VINORELBINE Crohns_disease Glycated_hemoglobin_levels Inflammatory_bowel_disease Mean_corpuscular_hemoglobin Mean_corpuscular_volume Red_blood_cell_traits Systemic_lupus_erythematosus
TABLE-US-00032 TABLE 32 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: BRD2 Body_mass_index ET BROMODOMAIN Breast_cancer INHIBITOR Cholesterol_total GW841819X Crohns_disease I-BET151 Height ME BROMODOMAIN Inflammatory_bowel_disease INHIBITOR XD14 Mean_corpuscular_hemoglobin Red_blood_cell_traits Serum_albumin_level
TABLE-US-00033 TABLE 33 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: STAT4 Celiac_disease LISOFYLLINE Crohns_disease HDL_cholesterol Height Inflammatory_bowel_disease Juvenile_idiopathic_arthritis Multiple_sclerosis Ulcerative_colitis
TABLE-US-00034 TABLE 34 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: KDM5B Glycated_hemoglobin_levels PBIT Height Inflammatory_bowel_disease Lipid_metabolism_phenotypes Lipoprotein- associated_phospholipase_A2_ac- tivity_and_mass Mean_corpuscular_hemoglobin Multiple_sclerosis Systemic_lupus_erythematosus
TABLE-US-00035 TABLE 35 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: BRD3 Esophageal_cancer_squamous_cell GW841819X Height I-BET151 Juvenile_idiopathic_arthritis XD14 Mean_platelet_volume Multiple_sclerosis Rheumatoid_arthritis Schizophrenia
TABLE-US-00036 TABLE 36 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: EZH2 Bone_mineral_density EI1 C-reactive_protein EPZ-6438 Fasting_glucose- GSK126 related_traits_interaction_with_BMI Inflammatory_bowel_disease Ovarian_cancer Prostate_cancer
TABLE-US-00037 TABLE 37 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: ATF1 Ankylosing_spondylitis PSEUDOEPHEDRINE Colorectal_cancer Mean_corpuscular_hemoglobin Mean_corpuscular_volume Red_blood_cell_traits Systemic_lupus_erythematosus
TABLE-US-00038 TABLE 38 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: CREB1 Chronic_lymphocytic_leukemia NALOXONE Glycated_hemoglobin_levels Height Mean_platelet_volume Prostate_cancer Schizophrenia
TABLE-US-00039 TABLE 39 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: TP53 Glycated_hemo- 1-(9-ETHYL-9H- globin_levels CARBAZOL-3-YL)-N- Mean_platelet_volume METHYL- Multiple_sclerosis METHANAMINE Rheumatoid_arthritis DOXORUBICIN Testicular_germ_cell_tumor
TABLE-US-00040 TABLE 40 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: HNF4G Blood_metabolite_levels PALMITIC ACID Blood_metabolite_ratios Metabolic_syndrome Urate_levels
TABLE-US-00041 TABLE 41 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: NR2C2 Cholesterol_total RETINOL Glycated_hemoglobin_levels Mean_platelet_volume
TABLE-US-00042 TABLE 42 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: SIRT6 Mean_corpuscular_hemoglobin PANOBINOSTAT Mean_corpuscular_volume Red_blood_cell_traits
TABLE-US-00043 TABLE 43 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: BRCA1 Chronic_lymphocytic_leukemia BMN673 Systemic_lupus_erythematosus CARBOPLATIN OLAPARIB PLATINUM RUCAPARIB TAXANE VELIPARIB VINORELBINE
TABLE-US-00044 TABLE 44 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: NR1H2 Alzheimer_disease 1,1,1,3,3,3-HEXAFLUORO-2-{4- Glycated_hemo- [(2,2,2-TRIFLUOROET . . . globin_levels 1,1,1,3,3,3-HEXAFLUORO-2-{4- [(2,2,2-TRIFLUORO- ETHYL)AMINO]PHENYL}PRO- PAN-2-OL 22R-HYDROXYCHOLESTEROL 27-HYDROXYCHOLESTEROL GW3965 T0901317
TABLE-US-00045 TABLE 45 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: KAT5 Height COENZYME A Schizophrenia S-ACETYL-CYSTEINE
TABLE-US-00046 TABLE 46 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: CTNNB1 Schizophrenia UREA
TABLE-US-00047 TABLE 47 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: KDM5A Type_1_diabetes PBIT
TABLE-US-00048 TABLE 48 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: PPARG C-reactive_protein (2S)-2-(4-CHLOROPHENOXY)-3- Fibrinogen PHENYLPROPANOIC ACID Rheumatoid_ar- (2S)-3-(1-{[2- thritis (2-CHLOROPHENYL)-5- METHYL-1,3-OXAZOL-4- YL]METHYL}- 1H-INDOL-5-YL)-2- ETHOXYPROPANOIC ACID 3-FLUORO-N-[1-(4- FLUOROPHENYL)-3-(2- THIENYL)-1H-PYRAZOL-5- YL]BENZENESULFONAMIDE (4S,5E,7Z,10Z,13Z,16Z,19Z)-4- HYDROXYDOCOSA- 5,7,10,13,16,19- HEXAENOIC ACID (5R,6E,8Z,11Z,14Z,17Z)-5- HYDROXYICOSA-6,8,11,14,17- PENTAENOIC ACID (8E,10S,12Z)-10-HYDROXY-6- OXOOCTADECA-8,12-DIENOIC ACID (8R,9Z,12Z)-8-HYDROXY-6- OXOOCTADECA-9,12-DIENOIC ACID AD-5061 ALEGLITAZAR BALSALAZIDE BALSALAZIDE DISODIUM BARDOXOLONE BEZAFIBRATE CIGLITAZONE DB07509 DICLOFENAC FARGLITAZAR FMOC-L-LEUCINE GENISTEIN GLIPIZIDE GW0072 GW1929 GW7845 GW9662 IBUPROFEN INDOMETHACIN L-764406 L-796449 LINOLEIC ACID LY-465608 LY-510929 METAGLIDASEN MITIGLINIDE MURAGLITAZAR NATEGLINIDE NAVEGLITAZAR NETOGLITAZONE NTZDPA OLANZAPINE OLSALAZINE SODIUM PAT5A PIOGLITAZONE PIOGLITAZONE HYDROCHLORIDE RAGAGLITAZAR REGLITAZAR REPAGLINIDE ROSIGLITAZONE ROSIGLITAZONE MALEATE ROSIGLITAZONE & SIMVASTATIN RS5444 SB-219993 SB-219994 SULFASALAZINE T131 TELMISARTAN TREPROSTINIL TROGLITAZONE ZOLEDRONIC ACID
TABLE-US-00049 TABLE 49 Column A Transcription Column B Column C Factor Disease/Condition Treatment Agent TF: ZEB1 Mean_corpuscular_hemoglobin CYTARABINE Mean_corpuscular_volume DOXORUBICIN Systemic_lupus_erythematosus GEMCITABINE SALINOMYCIN
[0038] Dosage
[0039] As will be apparent to those skilled in the art, dosages outside of these disclosed ranges may be administered in some cases. Further, it is noted that the ordinary skilled clinician or treating physician will know how and when to interrupt, adjust, or terminate therapy in consideration of individual patient response.
[0040] In one aspect, the dosage of an agent disclosed herein, based on weight of the active compound, administered to an individual in need thereof may be about 0.25 mg/kg, 0.5 mg/kg, 0.1 mg/kg, 1 mg/kg, 2 mg/kg, 3 mg/kg, 4 mg/kg, 5 mg/kg, 6 mg/kg, or more of a subject's body weight. In another embodiment, the dosage may be a unit dose of about 0.1 mg to 200 mg, 0.1 mg to 100 mg, 0.1 mg to 50 mg, 0.1 mg to 25 mg, 0.1 mg to 20 mg, 0.1 mg to 15 mg, 0.1 mg to 10 mg, 0.1 mg to 7.5 mg, 0.1 mg to 5 mg, 0.1 to 2.5 mg, 0.25 mg to 20 mg, 0.25 to 15 mg, 0.25 to 12 mg, 0.25 to 10 mg, 0.25 mg to 7.5 mg, 0.25 mg to 5 mg, 0.5 mg to 2.5 mg, 1 mg to 20 mg, 1 mg to 15 mg, 1 mg to 12 mg, 1 mg to 10 mg, 1 mg to 7.5 mg, 1 mg to 5 mg, or 1 mg to 2.5 mg.
[0041] In one aspect, an agent disclosed herein may be present in an amount of from about 0.5% to about 95%, or from about 1% to about 90%, or from about 2% to about 85%, or from about 3% to about 80%, or from about 4%, about 75%, or from about 5% to about 70%, or from about 6%, about 65%, or from about 7% to about 60%, or from about 8% to about 55%, or from about 9% to about 50%, or from about 10% to about 40%, by weight of the composition.
[0042] The compositions may be administered in oral dosage forms such as tablets, capsules (each of which includes sustained release or timed release formulations), pills, powders, granules, elixirs, tinctures, suspensions, syrups, and emulsions. They may also be administered in intravenous (bolus or infusion), intraperitoneal, subcutaneous, or intramuscular forms all utilizing dosage forms well known to those of ordinary skill in the pharmaceutical arts. The compositions may be administered by intranasal route via topical use of suitable intranasal vehicles, or via a transdermal route, for example using conventional transdermal skin patches. A dosage protocol for administration using a transdermal delivery system may be continuous rather than intermittent throughout the dosage regimen.
[0043] A dosage regimen will vary depending upon known factors such as the pharmacodynamic characteristics of the agents and their mode and route of administration; the species, age, sex, health, medical condition, and weight of the patient, the nature and extent of the symptoms, the kind of concurrent treatment, the frequency of treatment, the route of administration, the renal and hepatic function of the patient, and the desired effect. The effective amount of a drug required to prevent, counter, or arrest progression of a symptom or effect of a disease can be readily determined by an ordinarily skilled physician
[0044] Compositions may include suitable dosage forms for oral, parenteral (including subcutaneous, intramuscular, intradermal and intravenous), transdermal, sublingual, bronchial or nasal administration. Thus, if a solid carrier is used, the preparation may be tableted, placed in a hard gelatin capsule in powder or pellet form, or in the form of a troche or lozenge. The solid carrier may contain conventional excipients such as binding agents, fillers, tableting lubricants, disintegrants, wetting agents and the like. The tablet may, if desired, be film coated by conventional techniques. Oral preparations include push-fit capsules made of gelatin, as well as soft, scaled capsules made of gelatin and a coating, such as glycerol or sorbitol. Push-fit capsules can contain active ingredients mixed with a filler or binders, such as lactose or starches, lubricants, such as talc or magnesium stearate, and, optionally, stabilizers. In soft capsules, the active compounds may be dissolved or suspended in suitable liquids, such as fatty oils, liquid, or liquid polyethylene glycol with or without stabilizers. If a liquid carrier is employed, the preparation may be in the form of a syrup, emulsion, soft gelatin capsule, sterile vehicle for injection, an aqueous or non-aqueous liquid suspension, or may be a dry product for reconstitution with water or other suitable vehicle before use. Liquid preparations may contain conventional additives such as suspending agents, emulsifying agents, wetting agents, non-aqueous vehicle (including edible oils), preservatives, as well as flavoring and/or coloring agents. For parenteral administration, a vehicle normally will comprise sterile water, at least in large part, although saline solutions, glucose solutions and like may be utilized. Injectable suspensions also may be used, in which case conventional suspending agents may be employed.
[0045] Conventional preservatives, buffering agents and the like also may be added to the parenteral dosage forms. For topical or nasal administration, penetrants or permeation agents that are appropriate to the particular barrier to be permeated are used in the formulation. Such penetrants are generally known in the art. The pharmaceutical compositions are prepared by conventional techniques appropriate to the desired preparation containing appropriate amounts of the active ingredient, that is, one or more of the disclosed active agents or a pharmaceutically acceptable salt thereof according to the invention.
[0046] The dosage of an agent disclosed herein used to achieve a therapeutic effect will depend not only on such factors as the age, weight and sex of the patient and mode of administration, but also on the degree of inhibition desired and the potency of an agent disclosed herein for the particular disorder or disease concerned. It is also contemplated that the treatment and dosage of an agent disclosed herein may be administered in unit dosage form and that the unit dosage form would be adjusted accordingly by one skilled in the art to reflect the relative level of activity. The decision as to the particular dosage to be employed (and the number of times to be administered per day) is within the discretion of the physician, and may be varied by titration of the dosage to the particular circumstances of this invention to produce the desired therapeutic effect.
[0047] In one aspect, a method of treating a disease is disclosed, in which the method may comprise the step of identifying one or more, or two or more, or three or more, or four or more, or five or more, or six or more, or seven or more, or eight or more, or nine or more, or ten or more, or 11 or more, or 12 or more, or 13 or more, or 14 or more, or 15 or more, or 16 or more, or 17 or more, or 18 or more, or 19 or more, or 20 or more, or 21 or more, or 22 or more, or 23 or more, or 24 or more, or 25 or more, or 26 or more, or 27 or more, or 28 or more, or 29 or more, or 30 or more, or 31 or more, or 32 or more, or 33 or more, or 34 or more, or 35 or more, or 36 or more, or 37 or more, or 38 or more, or 39 or more, or 40 or more, or more than 40 loci associated with a disease state as listed herein. The individual may have, or be suspected of having the disease. The method may further comprise the step of treating the individual with a compound that modulates the TF associated with the one or more loci.
Examples
[0048] Application to a matrix of 213 phenotypes and 1,544 TF binding datasets identifies 2,264 significant associations for hundreds of TFs in 94 phenotypes, including prostate and breast cancers. Strikingly, nearly half of the systemic lupus erythematosus risk loci are occupied by the Epstein-Barr virus EBNA2 protein and 24 human TFs, revealing an important gene-environment interaction. Similar EBNA2-anchored associations also exist in multiple sclerosis, rheumatoid arthritis, inflammatory bowel disease, type 1 diabetes, juvenile idiopathic arthritis, and celiac disease. Instances of allele-dependent DNA binding and downstream effects on gene expression at plausibly causal autoimmune variants support a genetic mechanism of pathogenesis centered on EBNA2. Applicant's results nominate mechanisms operating across disease risk loci, suggesting new paradigms of disease origins.
[0049] The mechanisms generating genetic associations have proven difficult to elucidate for most diseases. Gene-environment interactions may explain the etiology of many autoimmune diseases.sup.1-3. In particular, Epstein-Barr virus (EBV) infection has been implicated in the autoimmune mechanisms and epidemiology of systemic lupus erythematosus (SLE).sup.4-7, increasing SLE risk by as much as 50-fold in children.sup.4. SLE patients also have elevated EBV loads in blood and early lytic viral gene expression.sup.6. Despite connections between EBV and multiple autoimmune diseases, the underlying molecular mechanisms remain unknown.sup.8,9.
[0050] Genome wide association studies (GWASs) have identified >50 convincing European ancestry SLE loci (
[0051] Intersection of Disease Risk Loci with TF-DNA Binding Interactions
[0052] To identify TFs that bind a significant number of risk loci for a given disease, Applicant developed the RELI (Regulatory Element Locus Intersection) algorithm. RELI systematically estimates the significance of the intersection of the genomic coordinates of plausibly causal genetic variants and DNA sequences immunoprecipitated (through ChIP-seq) by a particular TF. Observed intersection counts are compared to a null distribution composed of variant sets chosen to match the disease loci in terms of allele frequency and linkage disequilibrium (LD) block structure (
[0053] Applicant first gauged the ability of RELI to capture known or suspected connections between TFs and diseases. The androgen receptor (AR) plays a well-established role in prostate cancer.sup.17, and RELI analysis revealed that AR binding sites in VCaP cells significantly intersect prostate cancer-associated loci (17 of 52 loci, Relative Risk (RR)=3.7, corrected P-value (Pc)<10.sup.−6, Table 1). Similarly, binding sites for GATA3 in MCF7 cells significantly intersect breast cancer variants.sup.18 (Pc<10.sup.−10, Table 1). Consistent with EBV contributing to multiple sclerosis (MS).sup.19-21 and results from a recent study.sup.22, RELI reveals that the EBV-encoded EBNA2 protein occupies 44 of the 109 MS loci in Mutu B cells (Pc<10.sup.−29, Table 1). Prostate and breast cancer loci do not significantly intersect EBNA2 peaks, nor do the loci of certain inflammatory diseases such as systemic sclerosis (Table 1). Collectively, these observations illustrate that predictions made by RELI are specific and consistent with previously established disease mechanisms.
TABLE-US-00050 TABLE Intersection of TF ChIP-seq datasets with multiple genetic loci of diseases and phenotypes. Phenotype Cell line TF Number Fraction RR P.sub.c & P* Prostate Ca VCaP + Dht_18 hr AR 17 0.33 3.70 2.60E−07 Breast Ca MCF7 + Estradiol GATA3 22 0.36 3.87 7.45E−11 MS Mutu EBNA2 44 0.40 4.66 6.34E−30 SSc Mutu EBNA2 2 0.10 — NS SSc IB4 EBNA2 1 0.05 — NS SSc GM12878 EBNA2 0 0.00 — NS SLE Mutu EBNA2 26 0.49 5.96 1.09E−25 SLE IB4 EBNA2 10 0.19 7.46 1.09E−11 SLE GM12878 EBNA2 10 0.19 8.57 1.94E−13 SLE IB4 EBNA-LP 4 0.08 — NS SLE Mutu EBNA3C 5 0.09 — NS SLE Raji EBNA1 0 0.00 — NS SLE Akata Zta 0 0.00 — NS SLE* Mutu* EBNA2* 25* 0.63* 2.85* 1.81E−11* SLE* IB4* EBNA2* 10* 0.25* 3.61* 2.44E−06* SLE* GM12878* EBNA2* 10* 0.25* 4.97* 1.22E−09* Detailed results are presented in Supplementary Data 3. ‘*’: RELI null model limited to EBV-infected B cell line open chromatin regions (see text). RR = ‘relative risk’. Pc = RELI Bonferroni corrected P-value. NS = Pc > 10E.sup.−6. All disease ancestries are European. Ca = cancer. MS = multiple sclerosis. SSc = systemic sclerosis. SLE = systemic lupus erythematosus.
[0054] Applicant assembled 53 European ancestry SLE loci (P<5×10.sup.−8) with risk allele frequencies >1%, constituting 1,359 plausibly causal SLE variants. To explore the possible environmental contribution from EBV, Applicant evaluated the ChIP-seq data from EBV-infected B cells for the EBV gene products EBNA1, EBNA2 (three datasets), EBNA3C, EBNA-LP, and Zta (Supplementary Data 2). EBNA2 occupies loci that significantly intersect SLE risk loci in all three available ChIP-seq datasets (Table 1). For example, 26 of 53 European SLE GWAS loci contain DNA immunoprecipitated by EBNA2 in the Mutu B cell line, an almost 6-fold enrichment (Pc<10.sup.−24). No association was detected for the other EBV-encoded proteins. To examine the possibility that these results might simply be explained by enrichment of SLE loci in B cell open chromatin regions, Applicant restricted the RELI null model to variants located in DNase hypersensitive regions in EBV-infected B cells. With this higher stringency null model, all of the EBNA2 associations remained significant. Thus, the associations Applicant detect between SLE risk loci and EBNA2 cannot simply be explained by the previously established strong co-localization between SLE risk loci and B cell regulatory regions in the genome.sup.23.
[0055] Applicant next applied RELI to a large collection of human TF ChIP-seq datasets (1,544 experiments evaluating 344 TFs and 221 cell lines). In total, 132 ChIP-seq datasets involving 60 unique TFs strongly intersect SLE loci (10-53<Pc<10−6). 109 (83%) of the experiments were performed in EBV-infected B cell lines, with impressive fidelity between datasets. Nearly identical results were obtained using a null model that also takes the distance to the nearest gene transcription start site into account (
[0056] If EBV is involved in SLE pathogenesis, then the absence of EBV, and hence EBNA2, should diminish the observed associations with SLE risk loci. For eight TFs, ChIP-seq datasets are available in both EBNA2-expressing (EBV-infected) and EBV negative B cell lines.
[0057] Notably, the four TFs with the strongest RELI P-values in EBV-infected B cells (BATF, IRF4, PAX5, and SPI1) have weaker P-values in EBV negative B cells (
[0058] EBNA2-Occupied Genomic Sites Intersect Autoimmune-Associated Loci
[0059] Applicant applied RELI to 213 diseases and phenotypes obtained from the NHGRI GWAS catalog.sup.29 and other sources, revealing nine phenotypes displaying strong EBNA2 association in addition to SLE and MS: rheumatoid arthritis (RA), inflammatory bowel disease (IBD), type 1 diabetes (T1D), juvenile idiopathic arthritis (JIA), celiac disease (CelD), chronic lymphocytic leukemia (CLL), Kawasaki disease (1(D), ulcerative colitis (UC), and immunoglobulin glycosylation (IgG) (
[0060] Consistent with the SLE results (
[0061] In order to identify additional EBNA2 co-factor candidates, Applicant isolated EBNA2 disorder-associated variants located within EBNA2 ChIP-seq peaks and evaluated them using RELI This analysis confirms the importance of RBPJ, followed by members of the basal transcriptional machinery (TBP and p300), and NFκB subunits (which are involved in EBNA2-mediated gene activation.sup.34) (
[0062] The particular TFs tend to be shared across the EBNA2 disorders, but the loci they occupy are less frequently shared. No EBNA2-bound locus is associated with all seven EBNA2 disorders; most loci are unique to only one disorder (
[0063] If changes in gene regulation explain these results, then expression trait quantitative loci (eQTLs), ChIP-seq peaks for Pol-II, and histone marks associated with active gene regulatory regions should be relatively concentrated at the risk loci occupied by EBNA2. These predictions are indeed true for each of the seven EBNA2 disorders (
[0064] EBNA2 Participates in Allele-Dependent Formation of Transcription Complexes at Disease Risk Loci
[0065] The observed associations (
[0066] Applicant applied MARIO to 271 ChIP-seq datasets performed in the five genotyped cell lines, altogether assessing 98 different molecules. Since EBNA2 binds DNA through co-factors, Applicant first asked if the variants displaying EBNA2 allele-dependent binding might also coincide with similarly altered binding of other TFs. This analysis revealed strong concordance of allele-dependent binding events both within and across cell types. For example, Applicant identified 68 heterozygous common variants located within allele-dependent EBNA2 GM12878 ChIP-seq peaks. EBF1, whose binding is globally influenced by EBNA2.sup.36, has a coincident ChIP-seq peak favoring the same allele at 39 (57%) of these loci, as opposed to only 8 (11%) on the opposite allele (P<10.sup.−4, binomial test,
TABLE-US-00051 TABLE 2 Allele-dependent binding of EBNA2 to autoimmune-associated genetic variants. Reads Reads Str. Gene(s) rs ID ARS (Str.) (Weak) Base Disease(s) Tag SNP and r.sup.2 with allelic SNP CD37* rs5828386 0.69 55 18 G MS MS: rs8107548, r.sup.2 = 0.940 CD37* rs1465697.sup.# 0.57 57 29 C MS MS: rs8107548, r.sup.2 = 0.959 HLA-DQA1 rs9271693.sup.# 0.66 27 3 C IBD, UC IBD: rs477515, r.sup.2 = 0.824 UC: rs9268853, r.sup.2 = 0.885 HLA-DQA1 rs9271588.sup.# 0.50 22 11 C SjS.sup.72 SjS: same HLA-DQB1{circumflex over ( )}{circumflex over ( )} rs3129763 0.52 11 0 A CLL, SSc CLL: rs674313, r.sup.2 = 0.854 SSc: same IKZF2* rs996032.sup.# 0.65 27 6 A SLE (AS) SLE: rs3768792, r.sup.2 = 0.888 CCR1 rs68181568 0.64 21 0 C CelD CelD: rs13098911, r.sup.2 = 0.919 RERE{circumflex over ( )} rs2401138 0.63 48 20 C V V: rs4908760, r.sup.2 = 0.827 TMBIM1* rs2382818.sup.# 0.61 31 12 A IBD IBD: rs2382817, r.sup.2 = 1.0 CLEC16A{circumflex over ( )}{circumflex over ( )} rs7198004 0.59 16 0 G SLE SLE: rs12599402, r.sup.2 = 0.963 CLEC16A rs998592 0.50 10 0 C SLE SLE: rs12599402, r.sup.2 = 0.927 CD44{circumflex over ( )}{circumflex over ( )} rs3794102.sup.# 0.58 30 13 G V V: rs10768122, r.sup.2 = 1.0 BLK{circumflex over ( )} rs2736335 0.53 19 8 A KD, KD KD: rs2254546, r.sup.2 = 1.0 (AS), SLE, SLE: rs7812879, r.sup.2 = 0.929 SLE (AS), SLE (multi) PRKCQ rs947474 0.52 11 0 A T1D, RA.sup.73 TID: same RA: same TNIP1* rs2233287 0.52 17 7 G Ssc Ssc: same RHOH{circumflex over ( )}{circumflex over ( )} rs13136820 0.52 141 86 T GD GD: rs6832151; r.sup.2 = 0.939 DQ658414 rs73318382 0.50 10 0 A SLE, SLE SLE: rs57095329; r.sup.2 = 1.0 (MIR3142, (AS), SLE MIR164A)* (multi) RMI2{circumflex over ( )} rs34437200 0.49 10 2 A CelD, IBD, CelD: rs12928822; r.sup.2 = 0.841 JIA, MS IBD: rs529866; r.sup.2 = 0.948 JIA: rs66718203; r.sup.2 = 0.841 MS: rs6498184; r.sup.2 = 0.965 ZFP36L1 rs194749.sup.# 0.47 11 4 C IBD, T1D IBD: same TID: rs1465788; r.sup.2 = 0.814 HLA-DQB1{circumflex over ( )}{circumflex over ( )} rs532098.sup.# 0.41 24 15 G SLE SLE = same HLA-DRB1, rs674313 0.41 24 15 G CLL, SSc CLL: same HLA-DRB5 SSc: rs3129763; r.sup.2 = 0.863 PPIF{circumflex over ( )}{circumflex over ( )} rs1250567 0.41 8 3 T MS MS: rs1782645; r.sup.2 = 0.8475 TAGAP* rs1738074 0.40 47 32 T CelD, MS.sup.74 CelD: same MS: same Examples of EBNA2 ChIP-seq-derived allele-dependent binding to heterozygous autoimmune-associated variants. All allelic results are from Mutu cells, except for the RMI2 locus, which uses EBNA2 GM12878 ChIP-seq data. Each variant was assigned to a gene using the following procedure. If the variant is located within the promoter (+/−5kb) of a gene expressed in EBV infected B cells (median RPKM of 2 or more based on GTEx55 data, assign to that gene (indicated with ‘*’). Otherwise, if the variant is located within a Hi-C chromatin looping region in GM12878 EBV infected B cells.sup.75, assign it to the closest interacting gene that is expressed in EBV infected B cells (indicated with ‘{circumflex over ( )}{circumflex over ( )}’). Otherwise, if the variant is located within a Hi-C chromatin looping region in primary B cells.sup.76, assign it to the closest interacting gene that is expressed in EBV infected B cells (indicated with ‘{circumflex over ( )}’). Otherwise, assign the variant to the nearest gene that is expressed in EBV infected B cells. Variants marked with a ‘.sup.#’ are eQTLs for the indicated gene in at least one EBV infected B cell dataset.sup.55,77-84. “ARS”: Allelic Reproducibility Score” (see Supplementary Methods). “Reads (Strong (Str.))” and “Reads (Weak)” indicate the number of ChIP-seq reads mapping to the strong and weak allele, respectively. “Str Base” is the base with more reads. r.sup.2 values derived from European ancestry frequencies are provided. All r.sup.2 values are greater than 0.80 when matching for ancestry. All disease associations are taken from the original disease lists, with the exception of three additional associations - citations are provided for these. Disease abbreviations: MS, multiple sclerosis; IBD, inflammatory bowel disease; UC, ulcerative colitis; SLE, systemic lupus erythematosus; CLL, chronic lymphocytic lymphoma; SSc, systemic sclerosis; SjS, Sjögren's syndrome; CelD, celiac disease; V, vitiligo; KD, Kawasaki's disease; T1D, Type 1 Diabetes; GD, Graves disease; JIA, juvenile idiopathic arthritis. GWAS results for diseases are in the European ancestry (EU), except as indicated (East Asian (AS)).
[0067] To detect potential downstream effects of allelic EBNA2 binding, Applicant measured genome-wide gene expression levels by RNA-seq in Ramos, an EBV negative B cell line that can support an EBV infection. Applicant confirmed the expected presence or absence of EBNA2 by sequencing and western blot (
[0068] Applicant next searched for autoimmune-associated variants that might impact EBNA2 binding, resulting in allelic expression of a nearby gene. This analysis was dependent on the small subset of genetic variants satisfying four necessary criteria: the variant must be (1) plausibly causal for an autoimmune disorder; (2) immunoprecipitated by EBNA2; (3) heterozygous in the cell line assayed; and (4) proximal to a plausible target mRNA that contains a heterozygous variant in Ramos cells (to detect allelic expression). For example, the 23 EBNA2 variants listed satisfy the first three criteria, but only five satisfy the fourth criterion of being within 50 kb of a potential target gene containing a heterozygous variant in the Ramos cell line.
[0069] Despite these limitations, Applicant's approach identified autoimmune-associated variants displaying allelic EBNA2 binding and allelic expression of a nearby gene. For example, rs3794102, a variant strongly associated with vitiligo (P<10.sup.−9), has significantly skewed allelic binding of eight proteins—EBNA2, its suspected co-factor EBF136, and chromatin accessibility all favor the non-reference ‘G’ vitiligo risk allele (
[0070] Autoimmune-Associated Genetic Mechanisms in EBV-Infected B Cells
[0071] Applicant next used RELI to rank cell types by their relative importance to each of the EBNA2 disorders, based on the intersection between disease-associated variants and likely regulatory regions in that cell type. This procedure revealed a clear enrichment for EBV-infected B cells in SLE. For example, of the 175 H3K27ac ChIP-seq datasets available, the highest ranked 30 datasets are all from EBV-infected B-cell lines (
[0072] RELI identifies relationships between particular TFs and many diseases
[0073] Extension of RELI analysis to GWAS data for 213 phenotypes produced 2,264 significant (Pc<10.sup.−6) TF-disease connections. In addition to the EBNA2-related associations, clustering of these results reveals a large grouping of hematopoietic phenotypes and well-established blood cell regulators such as GATA1 and TAL1 (
[0074] Discussion
[0075] Efforts to understand the gene-environment interaction of SLE loci with EBV have revealed that EBNA2 and its associated human TFs occupy a significant fraction of autoimmune risk loci. Further analyses suggest that multiple causal autoimmune variants may act through allele-dependent binding of these proteins, resulting in downstream alterations in gene expression. In this scenario, the relevant TFs and gene expression changes must occur in the cell type that alters disease risk. Collectively, Applicant's data identify the EBV-infected B cell as a possible site for gene action in multiple autoimmune diseases, with the caveat that existing data are biased, having been predominantly collected in this cell type. Notably, four of the top 20 TFs that co-occupy EBNA2 disorder loci with EBNA2 are targeted by at least one available drug (MED1, EP300, NFKB1, and NFKB2).sup.45, and a recent study shows that the C-terminal domain of the BS69/ZMYND11 protein can bind to and inhibit EBNA2.sup.46. These results offer promise for the development of future therapies for manipulating the action of these proteins in individuals harboring risk alleles at EBNA2-bound loci.
[0076] The disclosed results nominate particular TFs and cell types for 94 phenotypes, providing mechanisms possibly explaining the molecular and cellular origins of disease risk for experimental verification and exploration.
[0077] Methods Summary
[0078] Applicant compiled and curated a set of 99,733 variants associated with or in strong linkage disequilibrium with 213 phenotypes (based upon direct genotyping and/or standard variant imputation). Applicant collected a set of 2,511 functional genomics datasets (ChIP-seq for specific proteins, ChIP-seq for histone marks, DNase-seq, and eQTLs) from a variety of sources. Applicant developed a novel algorithm, RELI (Regulatory Element Locus Intersection), to estimate the significance of the intersection between the variants associated with a given phenotype and a given functional genomics dataset. To identify allelic binding of proteins within ChIP-seq datasets, Applicant genotyped five EBV-infected B cell lines, and developed a novel pipeline called MARIO (Measurement of Allelic Ratios Informatics Operator) to detect allelic read count imbalance at heterozygotes in the assayed cell line. To identify gene expression patterns dependent upon both genotype and EBV, Applicant performed RNA-seq in Ramos B cell lines with or without EBV infection. Details are provided in the Supplementary Methods.
[0079] Collection and Processing of Datasets
[0080] Applicant compiled a large collection of genetic and functional genomic datasets from a variety of sources. Phenotype-associated genetic variants were largely obtained from the NHGRI GWAS catalog.sup.29. This catalog does not contain candidate gene studies, including those from the widely-used ImmunoChip platform.sup.47. For SLE, MS, SSc, RA, and JIA, peer-reviewed literature was thus curated to maximize the number and accuracy of loci. Only associations exceeding genome-wide significance (P<5×10.sup.−8) were considered. Datasets were separated and annotated by ancestry, except where noted. Phenotypes were filtered to only include those with five or more associated loci separated by at least 500 kb, following Farh et al..sup.30. Loci containing multiple variants were restricted to the single most strongly associated variant, and subsequently expanded to incorporate variants in strong linkage disequilibrium (LD) (r2>0.8) with this variant using Plink.sup.48. The resulting variants in each locus are referred to as plausibly causal.
[0081] Functional genomics data, including ChIP-seq and DNase-seq, were obtained from a variety of sources, including ENCODE.sup.49 (downloaded on 4/14), Roadmap epigenomics.sup.50 (6/15), Cistrome.sup.51 (12/15), PAZAR.sup.52 (4/14), ReMap-ChIP.sup.53 (8/15), and Gene Expression Omnibus.sup.54. ChIP-seq datasets containing less than 500 peaks were removed. The genomic coordinates of the peaks for each dataset were stored as .bed files. eQTLs were obtained from GTExPortal.sup.55 (1/16), the Pritchard lab eQTL database (http://eqtl.uchicago.edu/) (4/14), and the Harvard eQTL database (https://www.hsph.harvard.edu/liming-liang/software/eqtl/) (4/14). TF binding motif models in the form of position frequency matrices were obtained from Cis-BP (build 1.02).sup.56.
[0082] Regulatory Element Locus Intersection (RELI) Algorithm
[0083] Applicant created the RELI algorithm to search for potential shared regulatory mechanisms acting across phenotype-associated loci. In brief, RELI takes a set of variants as input, expands the set using LD blocks, and calculates the statistical intersection of the resulting loci with every dataset in a compendium (e.g., ChIP-seq datasets) (
[0084] RELI was designed to be flexible in terms of the null models it employs. The default null model, as described above, uses all common variants in the genome. Applicant also considered a higher-stringency null model by only considering common variants located within DNase-seq peaks in any of the 22 available EBV-infected B cell line datasets. This null model thus controls for the known association of SLE-associated variants with regulatory regions in B
[0085] Applicant identified the optimal clusters depicted as red boxes in
[0086] Cell Line Genotyping and Imputation
[0087] Without genotyping data, it is not possible to distinguish between perfect allelic imbalance at a heterozygous variant (e.g., 10 reads on one allele and 0 on the other) and homozygosity. Applicant therefore genotyped five EBV-infected B cell lines that had previously been used for ChIP-seq experiments. Genotyping was performed as previously described.sup.59 on Illumina OMNI-5 genotyping arrays using Infinium2 chemistry. Genotypes were called using the Gentrain2 algorithm within Illumina Genome Studio. Quality control on the variants from autosomal chromosomes was performed as previously described.sup.59. Quality control data cleaning was performed in the context of a larger batch of non-disease controls to allow for the assessment of data quality. Briefly, all cell lines had call rates >99%, only common variants (minor allele frequency >0.01) were included, and all variants were previously shown to be in Hardy-Weinberg equilibrium in control populations at P>0.000159. To detect associated variants that were not directly genotyped on the OMNI-5, Applicant performed genome-wide imputation using overlapping 150 kb sections of the genome with IMPUTE2.sup.60 and used a composite imputation reference panel of pre-phased integrated haplotypes from the 1,000 Genomes Project sequence data freeze from June 2014. Imputed genotypes were required to meet or exceed a probability threshold of 0.9, an information measure of >0.5, and the same quality-control criteria threshold described above for the genotyped markers.
[0088] Detection of Allele-Dependent Sequencing Reads Using MARIO
[0089] Applicant developed the MARIO (Measurement of Allelic Ratio Informatics Operator) pipeline to identify allele-dependent behavior at heterozygous variants in functional genomics datasets such as ChIP-seq. In brief, the pipeline downloads a set of reads, aligns them to the genome, calls peaks using MACS2.sup.44 (parameters: -nomodel -extsize 147 -g hs -q 0.01), identifies allele-dependent behavior at heterozygotes within peaks (described below), and annotates the results (
[0090] To estimate the significance of the degree of allelic imbalance of a given ChIP-seq, ATAC-seq, or DNase-seq dataset at a given heterozygote, Applicant developed a value called the ARS (Allelic Reproducibility Score). The ARS is based on a combination of two predictive variables for a given heterozygous variant of a given dataset—the total number of reads available at the variant and the imbalance between the number of reads for each allele. Other variables were tested and deemed uninformative (see below). The ARS value also accounts for the number of available experimental replicates, and the degree to which they agree. ARS values were calibrated using seven TFs with ChIP-seq datasets available in four replicate experiments in GM12878 or K562 cell lines: SPI1 (set 1), SPI1 (set 2), NRSF, REST, RNF2, YY1 and ZBTB33. The presence of multiple replicates monitoring binding of the same TF in the same cell type enables the estimation of the degree to which allelic behavior is reproducible, given the values of the predictive variables.
[0091] ARS values were defined and calculated using the following procedure:
[0092] 1) Determine the number of reads mapping to each allele of each heterozygous variant in each replicate. The pipeline was applied to each experimental replicate and counted the number of reads that overlap each heterozygous variant, corresponding to the two alternative alleles. All duplicate reads were removed using the “MarkDuplicates” tool from the PICARD software package (https://broadinstitute.github.io/picard/). Before mapping reads using Bowtie2.sup.61 (parameters -N 1 -np 0 -n-ceil 10 -no-unal), Applicant masked all common variants in the GrCh37 (hg19) reference genome to N. This step removed bias generated by reads carrying non-reference alleles. Applicant designated the allele with the greater number of reads the strong allele, and the other the weak allele (
[0093] 2) Identify predictive variables of reproducible allele-dependent behavior across replicates. Applicant identified variables that are predictive of reproducible allelic behavior across multiple ChIP-seq replicates within a dataset. Applicant collected a set of seven datasets, {D}, with each dataset comprised of four experimental replicates, {R} (
[0094] Applicant evaluated the performance of each of these variables using a true-positive set of reproducible variants. This set was created by identifying all variants that share the same strong allele across all four replicates (
[0095] 3) Determine a function mapping the values of the predictive variables to a single ARS value. Applicant next created a function for mapping the values of predictive variables for any heterozygous variant to a single ARS value estimating the degree of reproducible allelic behavior. Applicant developed a scheme that accounts for the fact that any given dataset might contain any number of experimental replicates, with agreement between a larger number of replicates being a desirable trait. Within each of the seven datasets in the set {D}, all possible combinations of one, two, or three replicates is considered. Without loss of generality, the procedure for the case of two replicates is described, which considers the subsets {R1,R2}, {R1,R3}, {R1,R4}, etc. The set {H} of reproducible variants is first identified (as described above) for each subset. The WS_ratio is transformed into ranges, {(0 -0.1), (0 -0.2), (0 -0.3), . . . (0 -1)}, and for each range, the fraction of variants that are contained in the reproducible variant set as a function of num_reads is calculated (
[0096] where w is the WS_ratio, r is num_reads, and Aw and Bw are the fitting parameters. The resulting functions yield ARS values for any given heterozygous variant in any dataset, as a function of the number of experimental replicates, the WS_ratio, and num_reads. As a final step, when multiple replicates are available, an ARS value is only reported for a variant if the strong allele is consistent in the majority of cases, to account for the possibility of a failed experiment. A direct interpretation of the ARS values can be seen in the relationship between ARS values and the WS_ratio (
[0097] The corresponding NCBI experiment run identifiers for the seven ChIP-seq datasets with four available replicates are: NRSF (SRR1176035, SRR1176037, SRR1176039, SRR1176050), REST (SRR400395, SRR400396, SRR400397, SRR400398), RNF2 (SRR400400, SRR400401, SRR400402, SRR400403), SPI1 (set 1) (SRR1176055, SRR1176056, SRR1176057, SRR1176058), SPI1 (set 2) (SRR351880, SRR351881, SRR578180, SRR578181), YY1 (SRR351719, SRR351720, SRR578174, SRR578175), ZBTB33 (SRR1176059, SRR1176060, SRR1176061, SRR1176062).
[0098] EBV Infection of Ramos Cells.
[0099] All cells were confirmed to be free of mycoplasma infection using PlasmaTest (InvivoGen, San Diego, Calif.) prior to use in experiments. Wild-type EBV was prepared from supernatants of B95-8 cells cultured in RPMI medium 1640 supplemented with 10% FBS for two weeks. Briefly, the cells were pelleted and the virus suspension was filtered through 0.45 μM Millipore filters. The concentrated virus stocks were aliquoted and stored at −80° C.
[0100] Applicant infected ˜2×10.sup.6 Ramos Cells (ATCC CRL-1596) in the presence of growth medium containing 2 μg/ml of phytohemagglutinin (PHA) for 4 hours. The infected cells were washed, cultured in growth media, and observed daily for multinuclear giant cell formation and morphological changes characteristic of EBV-infected B cells. After 10 passages, the infection was confirmed by measuring the expression of viral EBNA2 protein levels (
[0101] RNA-Seq
[0102] RNA was isolated from Ramos cell lines with and without EBV infection using the mirVANA Isolation Kit (Ambion). RNA sequencing targeting 150 million mappable 125 basepair reads from paired-end, poly-A enriched libraries was performed at the CCHMC DNA Sequencing and Genotyping Core Facility at CCHMC.
[0103] Sequencing reads were aligned to the GrCh37 (hg19) build of the human genome using TopHat.sup.62 and Bowtie2.sup.61 with Ensembl.sup.63 RNA transcript annotations as a guide. In parallel, these data were aligned to the EBV genome (NCBI). As expected, 0 reads mapped in the EBV negative dataset, whereas 7,349 reads mapped in the EBV-infected dataset. 82.8% of the sequence reads aligned specifically to the human transcriptome, with a 2.6% increase in the aligned reads in the EBV negative samples. No abnormal quality control (QC) flags were identified following QC analysis with the software FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). For allelic analysis, sequencing reads were aligned to the GrCh37 (hg19) build of the human genome using Hisat2.sup.64. Differential expression analysis was performed using Cufflinks.sup.65.
[0104] As additional QC, Applicant further compared the results to a study examining host gene expression changes to EBV infection in primary B cells.sup.28. Of the 80 genes whose expression is significantly altered by the presence of EBV in Applicant's study, 18 of them are also significantly differentially expressed in this dataset. Further, among the 80 differentially expressed genes detected, many of them represent classic host genes whose expression is modulated by EBV. Some gene expression is increased by the virus, while the expression of other genes is decreased. In all of these cases, the data agree with the established paradigm. Genes whose expression is activated by EBV include CD44.sup.66, TNFAIP2.sup.67, MX1.sup.68, and IFI44.sup.69; genes with lower expression include VAV3.sup.70 and CD99.sup.71.
[0105] Allelic qPCR
[0106] gDNA and RNA were extracted from Ramos cells with and without B95.8 EBV infection using the DNeasy Blood & Tissue Kit (Qiagen) and mirVana miRNA Isolation Kit (Invitrogen), respectively. RNA was treated with DNase using the TURBO DNA-free Kit (Ambion) and converted to cDNA using the High-Capacity RNA-to-cDNA Kit (Applied Biosystems). qPCR was performed with a single set of Taqman genotyping primers (Applied Biosystems) to rs8193 using the ABI 7500 PCR system. Fold change of expression was calculated with 2-ΔΔCT values, where cDNA was normalized to gDNA.
[0107] Data Availability
[0108] RNA-seq data are available in the Gene Expression Omnibus (GEO) database under accession number GSE93709. Full datasets and results, including disease variants (with alleles) and all RELI and MARIO output, are provided in the Supplementary Material.
[0109] Code Availability
[0110] The final RELI and MARIO source code, with documentation, will be made freely available under the GNU General Public License on the Weirauch Lab Bitbucket page: https://bitbucket.org/account/user/weirauchlab/projects/ci
REFERENCES
[0111] 1 Fujinami, R. S., von Herrath, M. G., Christen, U. & Whitton, J. L. Molecular mimicry, bystander activation, or viral persistence: infections and autoimmune disease. Clin Microbiol Rev 19, 80-94, doi:10.1128/CMR.19.1.80-94.2006 (2006). [0112] 2 Ercolini, A. M. & Miller, S. D. The role of infections in autoimmune disease. Clinical and experimental immunology 155, 1-15, doi:10.1111/j.1365-2249.2008.03834.x (2009). [0113] 3 Sener, A. G. & Afsar, I. Infection and autoimmune disease. Rheumatol Int 32, 3331-3338, doi:10.1007/s00296-012-2451-z (2012). [0114] 4 James, J. A. et al. An increased prevalence of Epstein-Barr virus infection in young patients suggests a possible etiology for systemic lupus erythematosus. J Clin Invest 100, 3019-3026, doi:10.1172/JC1119856 (1997). [0115] 5 Hanlon, P., Avenell, A., Aucott, L. & Vickers, M. A. Systematic review and meta-analysis of the sero-epidemiological association between Epstein-Barr virus and systemic lupus erythematosus. Arthritis research & therapy 16, R3, doi:10.1186/ar4429 (2014). [0116] 6 McClain, M. T. et al. Early events in lupus humoral autoimmunity suggest initiation through molecular mimicry. Nat Med 11, 85-89, doi:10.1038/nm1167 (2005). [0117] 7 Harley, J. B. & James, J. A. Epstein-Barr virus infection induces lupus autoimmunity. Bulletin of the NYU hospital for joint diseases 64, 45-50 (2006). [0118] 8 Ascherio, A. & Munger, K. L. EBV and Autoimmunity. Curr Top Microbiol Immunol 390, 365-385, doi:10.1007/978-3-319-22822-8_15 (2015). [0119] 9 Draborg, A. H., Duus, K. & Houen, G. Epstein-Barr virus in systemic autoimmune diseases. Clinical & developmental immunology 2013, 535738, doi:10.1155/2013/535738 (2013). [0120] 10 Vaughn, S. E., Kottyan, L. C., Munroe, M. E. & Harley, J. B. Genetic susceptibility to lupus: the biological basis of genetic risk found in B cell signaling pathways. Journal of leukocyte biology 92, 577-591, doi:10.1189/j1b.0212095 (2012). [0121] 11 Alarcon-Riquelme, M. E. et al. Genome-Wide Association Study in an Amerindian Ancestry Population Reveals Novel Systemic Lupus Erythematosus Risk Loci and the Role of European Admixture. Arthritis Rheumatol 68, 932-943, doi:10.1002/art.39504 (2016). [0122] 12 Bentham, J. et al. Genetic association analyses implicate aberrant regulation of innate and adaptive immunity genes in the pathogenesis of systemic lupus erythematosus. Nat Genet 47, 1457-1464, doi:10.1038/ng.3434 (2015). [0123] 13 Sun, C. et al. High-density genotyping of immune-related loci identifies new SLE risk variants in individuals with Asian ancestry. Nat Genet 48, 323-330, doi:10.1038/ng.3496 (2016). [0124] 14 Maurano, M. T. et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190-1195, doi:10.1126/science.1222794 (2012). [0125] 15 Hindorff, L. A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci USA 106, 9362-9367, doi:10.1073/pnas.0903103106 (2009). [0126] 16 Fang, H., Knezevic, B., Burnham, K. L. & Knight, J. C. XGR software for enhanced interpretation of genomic summary data, illustrated by application to immunological traits. Genome Med 8, 129, doi:10.1186/s13073-016-0384-y (2016). [0127] 17 Schweizer, M. T. & Yu, E. Y. Persistent androgen receptor addiction in castration-resistant prostate cancer. J Hematol Oncol 8, 128, doi:10.1186/s13045-015-0225-2 (2015). [0128] 18 Asch-Kendrick, R. & Cimino-Mathews, A. The role of GATA3 in breast carcinomas: a review. Hum Pathol 48, 37-47, doi:10.1016/j.humpath.2015.09.035 (2016). [0129] 19 Almohmeed, Y. H., Avenell, A., Aucott, L. & Vickers, M. A. Systematic review and meta-analysis of the sero-epidemiological association between Epstein Barr virus and multiple sclerosis. PLoS One 8, e61110, doi:10.1371/journal.pone.0061110 (2013). [0130] 20 Pender, M. P. & Burrows, S. R. Epstein-Barr virus and multiple sclerosis: potential opportunities for immunotherapy. Clinical & translational immunology 3, e27, doi:10.1038/cti.2014.25 (2014). [0131] 21 Marquez, A. C. & Horwitz, M. S. The Role of Latently Infected B Cells in CNS Autoimmunity. Front Immunol 6, 544, doi:10.3389/fimmu.2015.00544 (2015). [0132] 22 Ricigliano, V. A. et al. EBNA2 binds to genomic intervals associated with multiple sclerosis and overlaps with vitamin D receptor occupancy. PloS one 10, e0119605, doi:10.1371/journal.pone.0119605 (2015). [0133] 23 Hu, X. et al. Integrating autoimmune risk loci with gene-expression data identifies specific pathogenic immune cell subsets. American journal of human genetics 89, 496-506, doi:10.1016/j.ajhg.2011.09.002 (2011). [0134] 24 Trynka, G. et al. Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci. American journal of human genetics 97, 139-152, doi:10.1016/j.ajhg.2015.05.016 (2015). [0135] 25 Zhou, H. et al. Epstein-Barr virus oncoprotein super-enhancers control B cell growth. Cell host & microbe 17, 205-216, doi:10.1016/j.chom.2014.12.013 (2015). [0136] 26 Gewurz, B. E. et al. Canonical NF-kappaB activation is essential for Epstein-Barr virus latent membrane protein 1 TES2/CTAR2 gene regulation. J Virol 85, 6764-6773, doi:10.1128/JVI.00422-11 (2011). [0137] 27 Ersing, I., Bernhardt, K. & Gewurz, B. E. NF-kappaB and IRF7 pathway activation by Epstein-Barr virus Latent Membrane Protein 1. Viruses 5, 1587-1606, doi:10.3390/v5061587 (2013). [0138] 28 Price, A. M. et al. Analysis of Epstein-Barr virus-regulated host gene expression changes through primary B-cell outgrowth reveals delayed kinetics of latent membrane protein 1-mediated NF-kappaB activation. J Virol 86, 11096-11106, doi:10.1128/JVI.01069-12 (2012). [0139] 29 Welter, D. et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res 42, D1001-1006, doi:10.1093/nar/gkt1229 (2014). [0140] 30 Farh, K. K. et al. Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature 518, 337-343, doi:10.1038/nature13835 (2015). [0141] 31 Zimber-Strobl, U. et al. Epstein-Barr virus nuclear antigen 2 exerts its transactivating function through interaction with recombination signal binding protein RBP-J kappa, the homologue of Drosophila Suppressor of Hairless. EMBO J 13, 4973-4982 (1994). [0142] 32 Grossman, S. R., Johannsen, E., Tong, X., Yalamanchili, R. & Kieff, E. The Epstein-Barr virus nuclear antigen 2 transactivator is directed to response elements by the J kappa recombination signal binding protein. Proc Natl Acad Sci USA 91, 7568-7572 (1994). [0143] 33 Henkel, T., Ling, P. D., Hayward, S. D. & Peterson, M. G. Mediation of Epstein-Barr virus EBNA2 transactivation by recombination signal-binding protein J kappa. Science 265, 92-95 (1994). [0144] 34 Scala, G. et al. Epstein-Barr virus nuclear antigen 2 transactivates the long terminal repeat of human immunodeficiency virus type 1. J Virol 67, 2853-2861 (1993). [0145] 35 Wang, J. H. et al. Aiolos regulates B cell activation and maturation to effector state. Immunity 9, 543-553 (1998). [0146] 36 Lu, F. et al. EBNA2 Drives Formation of New Chromosome Binding Sites and Target Genes for B-Cell Master Regulatory Transcription Factors RBP-jkappa and EBF1. PLoS Pathog 12, e1005339, doi:10.1371/journal.ppat.1005339 (2016). [0147] 37 Bailey, S. D., Virtanen, C., Haibe-Kains, B. & Lupien, M. ABC: a tool to identify SNVs causing allele-specific transcription factor binding from ChIP-Seq experiments. Bioinformatics 31, 3057-3059, doi:10.1093/bioinformatics/btv321 (2015). [0148] 38 Buchkovich, M. L. et al. Removing reference mapping biases using limited or no genotype data identifies allelic differences in protein binding at disease-associated loci. BMC medical genomics 8, 43, doi:10.1186/s12920-015-0117-x (2015). [0149] 39 Kumasaka, N., Knights, A. J. & Gaffney, D. J. Fine-mapping cellular QTLs with RASQUAL and ATAC-seq. Nat Genet 48, 206-213, doi:10.1038/ng.3467 (2016). [0150] 40 Shi, W., Fornes, O., Mathelier, A. & Wasserman, W. W. Evaluating the impact of single nucleotide variants on transcription factor binding. Nucleic Acids Res 44, 10106-10116, doi:10.1093/nar/gkw691 (2016). [0151] 41 Ma, B., Huang, J. & Liang, L. RTeQTL: Real-Time Online Engine for Expression Quantitative Trait Loci Analyses. Database: the journal of biological databases and curation 2014, doi:10.1093/database/bau066 (2014). [0152] 42 Kryworuckho, M., Diaz-Mitoma, F. & Kumar, A. CD44 isoforms containing exons V6 and V7 are differentially expressed on mitogenically stimulated normal and Epstein-Barr virus-transformed human B cells. Immunology 86, 41-48 (1995). [0153] 43 Gonnella, R. et al. PKC theta and p38 MAPK activate the EBV lytic cycle through autophagy induction. Biochim Biophys Acta 1853, 1586-1595, doi:10.1016/j.bbamcr.2015.03.011 (2015). [0154] 44 Ernst, J. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43-49, doi:10.1038/nature09906 (2011). [0155] 45 Griffith, M. et al. DGIdb: mining the druggable genome. Nature methods 10, 1209-1210, doi:10.1038/nmeth.2689 (2013). [0156] 46 Harter, M. R. et al. BS69/ZMYND11 C-Terminal Domains Bind and Inhibit EBNA2. PLoS Pathog 12, e1005414, doi:10.1371/journal.ppat.1005414 (2016). [0157] 47 Trynka, G. et al. Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease. Nat Genet 43, 1193-1201, doi:10.1038/ng.998 (2011). [0158] 48 Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. American journal of human genetics 81, 559-575, doi:10.1086/519795 (2007). [0159] 49 Consortium, E. P. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57-74, doi:10.1038/nature11247 (2012). [0160] 50 Roadmap Epigenomics, C. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317-330, doi:10.1038/nature14248 (2015). [0161] 51 Liu, T. et al. Cistrome: an integrative platform for transcriptional regulation studies. Genome Biol 12, R83, doi:10.1186/gb-2011-12-8-r83 (2011). [0162] 52 Portales-Casamar, E. et al. The PAZAR database of gene regulatory information coupled to the ORCA toolkit for the study of regulatory sequences. Nucleic Acids Res 37, D54-60, doi:10.1093/nar/gkn783 (2009). [0163] 53 Griffon, A. et al. Integrative analysis of public ChIP-seq experiments reveals a complex multi-cell regulatory landscape. Nucleic Acids Res 43, e27, doi:10.1093/nar/gku1280 (2015). [0164] 54 Barrett, T. et al. NCBI GEO: archive for functional genomics data sets-update. Nucleic Acids Res 41, D991-995, doi:10.1093/nar/gks1193 (2013). [0165] 55 Consortium, G. T. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648-660, doi:10.1126/science.1262110 (2015). [0166] 56 Weirauch, M. T. et al. Determination and inference of eukaryotic transcription factor sequence specificity. Cell 158, 1431-1443, doi:10.1016/j.cell.2014.08.009 (2014). [0167] 57 Genomes Project, C. et al. A global reference for human genetic variation. Nature 526, 68-74, doi:10.1038/nature15393 (2015). [0168] 58 Smigielski, E. M., Sirotkin, K., Ward, M. & Sherry, S. T. dbSNP: a database of single nucleotide polymorphisms. Nucleic Acids Res 28, 352-355 (2000). [0169] 59 Kottyan, L. C. et al. Genome-wide association analysis of eosinophilic esophagitis provides insight into the tissue specificity of this allergic disease. Nat Genet 46, 895-900, doi:10.1038/ng.3033 (2014). [0170] 60 Verma, S. S. et al. Imputation and quality control steps for combining multiple genome-wide datasets. Frontiers in genetics 5, 370, doi:10.3389/fgene.2014.00370 (2014). [0171] 61 Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nature methods 9, 357-359, doi:10.1038/nmeth.1923 (2012). [0172] 62 Trapnell, C., Pachter, L. & Salzberg, S. L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105-1111, doi:10.1093/bioinformatics/btp120 (2009). [0173] 63 Flicek, P. et al. Ensembl 2013. Nucleic Acids Res 41, D48-55, doi:10.1093/nar/gks1236 (2013). [0174] 64 Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nature methods 12, 357-360, doi:10.1038/nmeth.3317 (2015). [0175] 65 Trapnell, C. et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28, 511-515, doi:10.1038/nbt.1621 (2010). [0176] 66 Birkenbach, M., Josefsen, K., Yalamanchili, R., Lenoir, G. & Kieff, E. Epstein-Barr virus-induced genes: first lymphocyte-specific G protein-coupled peptide receptors. J Virol 67, 2209-2220 (1993). [0177] 67 Chen, C. C. et al. NF-kappaB-mediated transcriptional upregulation of TNFAIP2 by the Epstein-Barr virus oncoprotein, LMP1, promotes cell motility in nasopharyngeal carcinoma. Oncogene 33, 3648-3659, doi:10.1038/onc.2013.345 (2014). [0178] 68 Craig, F. E. et al. Gene expression profiling of Epstein-Barr virus-positive and -negative monomorphic B-cell posttransplant lymphoproliferative disorders. Diagn Mol Pathol 16, 158-168, doi:10.1097/PDM.0b013e31804f54a9 (2007). [0179] 69 Smith, N. et al. Induction of interferon-stimulated genes on the IL-4 response axis by Epstein-Barr virus infected human b cells; relevance to cellular transformation. PLoS One 8, e64868, doi: 10.1371/journal.pone.0064868 (2013). [0180] 70 Portis, T., Dyck, P. & Longnecker, R. Epstein-Barr Virus (EBV) LMP2A induces alterations in gene transcription similar to those observed in Reed-Sternberg cells of Hodgkin lymphoma. Blood 102, 4166-4178, doi:10.1182/blood-2003-04-1018 (2003). [0181] 71 Lee, I. S., Shin, Y. K., Chung, D. H. & Park, S. H. LMP1-induced downregulation of CD99 molecules in Hodgkin and Reed-Sternberg cells. Leuk Lymphoma 42, 587-594, doi:10.3109/10428190109099318 (2001). [0182] 72 Li, Y. et al. A genome-wide association study in Han Chinese identifies a susceptibility locus for primary Sjogren's syndrome at 7q11.23. Nat Genet 45, 1361-1365, doi:10.1038/ng.2779 (2013). [0183] 73 Okada, Y. et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 376-381, doi:10.1038/nature12873 (2014). [0184] 74 International Multiple Sclerosis Genetics, C. et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature 476, 214-219, doi:10.1038/nature10251 (2011). [0185] 75 Mifsud, B. et al. Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C. Nat Genet 47, 598-606, doi:10.1038/ng.3286 (2015). [0186] 76 Javierre, B. M. et al. Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters. Cell 167, 1369-1384 e1319, doi:10.1016/j.cell.2016.09.037 (2016). [0187] 77 Liang, L. et al. A cross-platform analysis of 14,177 expression quantitative trait loci derived from lymphoblastoid cell lines. Genome Res 23, 716-726, doi:10.1101/gr.142521.112 (2013). [0188] 78 Stranger, B. E. et al. Population genomics of human gene expression. Nat Genet 39, 1217-1224, doi:10.1038/ng2142 (2007). [0189] 79 Veyrieras, J. B. et al. High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLoS Genet 4, e1000214, doi:10.1371/journal.pgen.1000214 (2008). [0190] 80 Pickrell, J. K. et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464, 768-772, doi:10.1038/nature08872 (2010). [0191] 81 Montgomery, S. B. et al. Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 464, 773-777, doi:10.1038/nature08903 (2010). [0192] 82 Mangravite, L. M. et al. A statin-dependent QTL for GATM expression is associated with statin-induced myopathy. Nature 502, 377-380, doi:10.1038/nature12508 (2013). [0193] 83 Dimas, A. S. et al. Common regulatory variation impacts gene expression in a cell type-dependent manner. Science 325, 1246-1250, doi:10.1126/science.1174148 (2009). [0194] 84 Gaffney, D. J. et al. Dissecting the regulatory architecture of gene expression QTLs. Genome Biol 13, R7, doi:10.1186/gb-2012-13-1-r7 (2012).
[0195] All percentages and ratios are calculated by weight unless otherwise indicated.
[0196] All percentages and ratios are calculated based on the total composition unless otherwise indicated.
[0197] It should be understood that every maximum numerical limitation given throughout this specification includes every lower numerical limitation, as if such lower numerical limitations were expressly written herein. Every minimum numerical limitation given throughout this specification will include every higher numerical limitation, as if such higher numerical limitations were expressly written herein. Every numerical range given throughout this specification will include every narrower numerical range that falls within such broader numerical range, as if such narrower numerical ranges were all expressly written herein.
[0198] The dimensions and values disclosed herein are not to be understood as being strictly limited to the exact numerical values recited. Instead, unless otherwise specified, each such dimension is intended to mean both the recited value and a functionally equivalent range surrounding that value. For example, a dimension disclosed as “20 mm” is intended to mean “about 20 mm.”
[0199] Every document cited herein, including any cross referenced or related patent or application, is hereby incorporated herein by reference in its entirety unless expressly excluded or otherwise limited. The citation of any document is not an admission that it is prior art with respect to any invention disclosed or claimed herein or that it alone, or in any combination with any other reference or references, teaches, suggests or discloses any such invention. Further, to the extent that any meaning or definition of a term in this document conflicts with any meaning or definition of the same term in a document incorporated by reference, the meaning or definition assigned to that term in this document shall govern.
[0200] While particular embodiments of the present invention have been illustrated and described, it would be obvious to those skilled in the art that various other changes and modifications can be made without departing from the spirit and scope of the invention. It is therefore intended to cover in the appended claims all such changes and modifications that are within the scope of this invention.