WO2000013028A1

WO2000013028A1 - Method for identifying shared antigenic epitopes

Info

Publication number: WO2000013028A1
Application number: PCT/US1999/019835
Authority: WO
Inventors: Georg J. Gradl; Alain L. M. Segers; Halil Can Tezcan
Original assignee: Sangstat Medical Corporation
Priority date: 1998-08-31
Filing date: 1999-08-30
Publication date: 2000-03-09
Also published as: AU5698599A

Abstract

The invention provides a method, and a system implementing the method, for determining a set of antigenic epitopes against which a biological sample is reactive. The method includes the steps of mixing the biological sample with a plurality of antigen preparations each comprising a known mixture of antigens; determining, for each of the antigen preparations, a positive or negative reactivity with the biological sample; and identifying epitopes shared by those antigen preparations determined to have a positive reactivity as reactive epitopes.

Description

METHOD FOR IDENTIFYING SHARED ANTIGENIC EPITOPES

FIELD OF THE INVENTION

The present invention relates generally to a system and method for identifying epitopes against which a biological sample will react as a result of antibodies or similar binding components contained in the sample. The invention may be used, for example, to evaluate the histocompatibility between transplant donor tissue and transplant candidates by identifying antigens against which the immune system of a transplant candidate will form antibodies or alloreactive T-cells.

BACKGROUND OF THE INVENTION

Human leucocyte antigens (HLA antigens) are cell surface glycoproteins that determine the outcome of tissue allografts. The high polymorphism of the HLA system presents a major obstacle for clinical transplantation. This is due to the incompatibility of a recipient for the HLA antigens of a donor allograft that leads to an immune response against the graft and which, in turn, can ultimately result in graft destruction or rejection.

HLA antigens refer to the genes associated with the major histocompatibility complex (MHC) locus. HLA antigens include two classes, Class I and Class II. Class I molecules (including HLA-A, B, and C) generally consist of a highly polymorphic alpha chain associated with an invariant beta chain and are expressed on virtually all nucleated cells. Class II molecules (including HLA-DR, DQ, and DP) generally consist of a polymorphic alpha and a polymorphic beta chain and are expressed on antigen-presenting cells. Because HLA antigens have the capacity to bind and present antigenic peptides to T-lymphocytes, they play a central role in the immune response.

Production of antibodies or alloreactive T-cells against HLA antigens by an immune system may be stimulated by pregnancy, transfusion, and transplantation. Analyzing the presence of antibodies or similar binding components in a transplant candidate against HLA antigens of donor tissue (donor specific crossmatch) or against a high percentage of HLA alleles and epitopes (PRA testing) allows one to predict or assess the risk of graft rejection. Accordingly, various methods have been developed to identify the antibodies produced by the immune system of a transplant candidate and to analyze their reactions with HLA antigens. Examples of such methods are described in references such as U. S. Patent No. 5,223,397, U.S. Patent No. 5,270,169, and U.S. Patent No. 5,288,648, which are commonly assigned to the assignee of this application.

For example, panel reactive antibody (PRA) testing involves incubating a biological sample (such as blood, serum, or plasma) from a transplant candidate with lymphocytes representing known HLA specificities. After adding complement and staining dyes, cell lysis is detected and the results are expressed as a percent of panel cells that show lysis. In general, a candidate's PRA percentage reflects the likelihood that the candidate's immune system will produce antibodies against donor tissue, with higher percentages corresponding to an increased likelihood of rejection. PRA testing, however, has numerous disadvantages. For example, because PRA testing is nonspecific for HLA, one is not able to identify the precise set of antigens against which a candidate's immune system will produce antibodies. The HLA antigens are among the most polymorphic genes known - for example, over 80 different alleles have been found in the human population at the HLA-A locus alone, and over 180 different alleles have been found in the human population at the HLA-B locus. The large number of HLA alleles is one of the reasons that has made it impracticable, too time-consuming, and/or too computationally intensive to use existing methods to identify the specific alleles against which a transplant candidate's immune system will produce antibodies. Accordingly, there remains a need for a computer-implemented system and method for efficiently and accurately analyzing a biological sample to determine a set of alleles from a polymorphic gene family against which the sample will react without the attendant disadvantages of conventional methods. SUMMARY OF THE INVENTION

In general, in one aspect, the invention features a computer-implemented method for determining a set of antigenic epitopes against which a biological sample is reactive. The method includes the steps of mixing the biological sample with a plurality of antigen preparations each comprising a known mixture of antigens; determining, for each of the antigen preparations, a positive or negative reactivity with the biological sample; and identifying epitopes shared by those antigen preparations determined to have a positive reactivity as reactive epitopes.

The method may include one or more of the following features. The method further includes the step of determining a set of antigens containing at least one identified reactive epitope.

The step of identifying epitopes shared by those antigen preparations determined to have a positive reactivity as reactive epitopes includes the steps of identifying a set of antigens present in the antigen preparations determined to have a positive reactivity with the biological sample; determining a set of amino acid sequences corresponding to the determined set of antigens; and analyzing data pairs describing an amino acid and its position in an amino acid sequence for the set of amino acid sequences to determine a set of reactive data pairs, wherein each reactive data pair is a reactive epitope determined to be reactive with the biological sample.

Analysis of the data pairs may analyze the data pairs in groups, each data pair group describing a sequence of two or more amino acids and the respective positions in an amino acid sequence.

Analysis of the data pairs may further include the steps of determining the antigen preparations including one or more antigen having that data pair; correlating each antigen preparation with the positive or negative reactivity with the biological sample; and determining a correlation indicator between the presence of that data pair and a positive reactivity with the biological sample.

The correlation indicator may be a value determined by using, for example, an algorithm based on Fisher's test. In another aspect, the invention features a memory device storing computer readable instructions for aiding a computer to receive data for reactions resulting from mixing a biological sample with a plurality of antigen preparations, each comprising a known mixture of antigens, and to implement a method such as that described above for determining a set of antigenic epitopes against which the biological sample is reactive.

In another aspect, the invention features a system including a test system for determining data for reactions resulting from mixing a biological sample with a plurality of antigen preparations each comprising a known mixture of antigens, and a computer system to implement a method such as that described above for determining a set of antigenic epitopes against which the biological sample is reactive.

Additional objects and attendant advantages of the present invention will be set forth, in part, in the description that follows, or may be learned from practicing or using the present invention. The objects and advantages may be realized and attained by means of the instrumentalities and combinations particularly pointed out in the appended claims. It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not to be viewed as being restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in, and constitute a part of, the specification, illustrate embodiments of the present invention and, together with the description, serve to explain the principles of the present invention. Like elements are denoted by like reference numerals.

Fig. 1 is a block diagram illustrating a system for identifying HLA antigens against which HLA antibodies from a biological sample will react;

Fig. 2 is a chart showing an example of cell phenotypes used in an ELISA test; and Figs. 3 and 4 are flow charts illustrating computer-implemented methods for identifying HLA antigens against which HLA antibodies from a biological sample will react.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

All cited patents, patent applications and literatures are incorporated herein by reference in their entirety. In the case of inconsistencies, the present disclosure, including definitions, will prevail.

The present invention analyzes a biological sample to determine HLA antigens against which the sample includes antibodies or other similar binding components. The invention may be implemented in special purpose hardware, software applications running on general purpose hardware, or a combination of both. For example, the invention may be implemented as part of a special purpose system designed for analyzing biological samples, or as software applications for analyzing biological samples for use in a general purpose computer system.

Figure 1 is a block diagram that illustrates a general purpose computer system 100 in which an embodiment of the invention may be implemented. The computer system 100 includes a bus 102 or other communication mechanism for communicating information, and a processor 104 coupled to the bus 102 for processing information. The computer system 100 also includes a main memory 106, such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 102 for storing information and instructions to be executed by the processor 104. The main memory 106 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by the processor 104. The computer system 100 further includes a read only memory (ROM) 108 or other static storage device coupled to the bus 102 for storing static information and instructions for the processor 104. A storage device 110, such as a magnetic disk or optical disk, is provided and coupled to the bus 102 for storing information and instructions.

The computer system 100 may be coupled via bus 102 to a monitor 112 for displaying information to a computer user. An input device 14, such as a keyboard including alphanumeric and other keys, is coupled to the bus 102 for communicating information and command selections to the processor 104. Other input devices may also be provided. For example, a cursor control 116, such as a mouse, a trackball, or cursor direction keys may be coupled to the bus 102 for communicating direction information and command selections to the processor 104 and for controlling cursor movement on the display 112.

The term "computer-readable medium" as used herein refers to any medium that participates in providing instructions to processor 104 for execution. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks, such as the storage device 110. Volatile media includes dynamic memory, such as the main memory 106. Transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise the bus 102. Transmission media can also take the form of acoustic or light waves, such as those generated during radio-wave and infra-red data communications.

Common forms of computer-readable media include, without limitation, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM, any other optical medium, punchcards, papertape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read.

Various forms of computer readable media may be involved in carrying or storing one or more sequences of one or more instructions to the processor 104 for execution. For example, the instructions may initially be carried on a magnetic disk of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to the computer system 100 can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. An infrared detector can receive the data carried in the infra-red signal and appropriate circuitry can place the data on the bus 102. The bus 102 carries the data to the main memory 106, from which the processor 104 retrieves and executes the instructions. The instructions received by the main memory 106 may optionally be stored on the storage device 110 either before or after execution by the processor 104.

The computer system 100 also includes a communication interface 118 coupled to the bus 102. The invention is related to the use of computer system 100 for analyzing HLA antibodies in biological samples. In a preferred embodiment, test results from the so-called Enzyme-Linked Immunosorbent Assay (ELISA) are used. Accordingly, an ELISA system 122 provides the ELISA test data to the computer system 100 over a link 120 to the communication interface 118. The link 120 between the communication interface 118 may be a direct link or a network link, such as a link over a LAN or the Internet. In such an implementation, communication interface 118 sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.

In one embodiment, the invention analyzes ELISA test results, which can be provided by ELISA kits such as PRA-STAT®, available from SangStat Medical Corporation of Menlo Park, California. PRA-STAT® is a solid phase enzyme immunoassay in which ELISA microplate wells include: (1 ) 3 wells for positive and negative reference testing; (2) 1 well with no sHLA antigens; and (3) 44 wells, each with different sHLA antigen preparations. The antigen preparations are derived from individually phenotyped cell lines, each preparation representing a different combination of 79 HLA allele specificities as shown in the table of Figure 2. The wells are incubated with a biological sample, typically from a transplant candidate, to allow antibodies in the biological sample to react with the HLA antigens and bind to the HLA antigen coated strips. After incubation, the wells are emptied and washed to eliminate unbound material.

Peroxidase-conjugated goat anti-antibody is then added to the microplate wells to react with the bound HLA antibodies from the biological sample. The wells are then rinsed to eliminate unbound conjugate. Next, a chromogenic substrate is added to each well, causing a reaction that produces color development, the intensity of which is proportional to the amount of conjugate bound to the well. An acidic solution is added to stop color development and the absorbance in the wells is measured between 490 and 500 nm using an ELISA microplate reader, which generates optical density (OD) data for each well.

Referring to Figure 3, as shown in step 310, the present invention receives and analyzes the OD data determined by the ELISA system. As shown in Figure 1 , in one embodiment, the invention is implemented as software running on the computer system 100, which receives the OD data from the ELISA system 122 over link 120, . Alternatively, in other embodiments, the data may be manually entered in the computer system 100.

Based on the OD data, the invention determines a positive or negative reactivity for each of the wells based on the reaction between the biological sample with the antigen mixture of each well. For a given well, a positive reactivity indicates that the biological sample contains antibodies of at least one specificity that will react with an HLA antigen present in the antigen mixture of the well, whereas a negative reactivity indicates that the biological sample contains no antibodies that will react with any of the antigens present in the antigen mixture of the well.

"Positive" and "negative" reactivity may be defined differently for different applications, and various methods may be used to determine whether a given well reacts positively or negatively. This embodiment determines an OD value for each well, based on the difference between the optical density measured for that well and that measured for the no-antigen well. The determination of positive and negative reactivity is made by comparing the OD value for each well with a threshold value, calculated as 0.35 x (mean OD value of the positive references). Wells having OD values greater or equal to the threshold value are determined to have positive reactivity, while those having OD values less than the threshold value are determined to have negative reactivity.

Next, as shown by step 320 of Figure 3, the invention identifies a set of amino acid sequences comprised of possible sequences for each antigen present in the set of wells determined in step 310 as having positive reactivity. The antigens are readily determined because the antigen mixtures present in each well are known (for example, the wells of the PRA-STAT® ELISA kit contain the mixtures as indicated in Figure 2). However, a single serological antigen specificity may be associated with one or more alleles, with each allele having a slightly different amino acid sequence. The alleles corresponding to each antigen can be determined by using, for example, a look-up table. In a preferred embodiment, the look-up table is based on information collected by the World Health Organization (WHO), which contains all known alleles (and their amino acid sequences) for all known antigens. In this embodiment, each allele is identified by a sequence of 200 amino acids corresponding to the variable region of the A- B- C- DP- DQ- and DR- gene regions of the HLA molecules. It should be appreciated, however, that the number of amino acids may be varied, as needed, depending on the specific application. A given antigen may be present in the antigen mixtures of more than one well having positive reactivity, and duplicate amino acid sequences may be eliminated from the set determined in step 320.

A positive reaction between an antigen and an antibody is caused by the reaction between one or more epitopes within the antigen and the antibody. This invention next evaluates each of the identified amino acid sequences to identify the specific epitopes in those sequences that are likely to be a cause of the positive reaction with antibodies present in the biological sample. This step, represented by step 330 of Figure 3, is explained in greater detail with reference to Figure 4.

As shown in step 410 of Figure 4, this analysis begins with the set of amino acid sequences determined in step 320 of Figure 3. Recalling that each of these sequences was initially identified as corresponding to antigens contained in an antigen preparation determined to have positive reactivity with the biological sample, each of the sequences may contain one or more epitope that is reactive with antibodies included in the biological sample. The process shown in Figure 4 identifies these reactive epitopes .

Figure 4 uses the variable X to represent the number of sequences identified in step 320 of Figure 3. The invention analyzes the sequences in units of data pairs, represented herein as [p, a_x] - where p is a position in an amino acid sequence and a_x is the specific amino acid found at position p in sequence x of the X sequences -- to determine whether a given data pair is likely to be reactive with antibodies present in the biological sample. As shown in step 420, p is initialized at p=1 , indicating that the analysis begins with the first position in the amino acid sequences.

Next, as represented by step 430, a statistical "P-value" is determined for data pairs representing the specific amino acid a_x occurring at the sequence position p for each of the X identified sequences. The P-value for a given data pair [p,a_x] is calculated based on known data for each of the wells indicating whether the antigen preparation for that well included one or more antigens having the amino acid a_x at position p, and the positive or negative reactivity of that well with the biological sample as determined in step 310 of Figure 3. The P-value for a data pair represents the statistical probability that the actual positive and negative reactivity results obtained could have resulted randomly and gives an indication of whether an antigen would react positively with the biological sample because it includes the given data pair.

The P-value calculation for a given data pair correspond to the following parameters:

• TP (True Positives): the number of wells that include at least one antigen having the data pair being analyzed, that were identified in step 310 of Figure 3 as having positive reactivity with the biological sample;

• FP (False Positives): the number of wells that do not include any antigen having the data pair being analyzed, but were identified in step 310 of Figure 3 as having positive reactivity with the biological sample;

• TN (True Negatives): the number of wells that do not include any antigen having the data pair being analyzed, that were identified in step 310 of Figure 3 as having negative reactivity with the biological sample; and

• FN (False Negatives): the number of wells that do include at least one antigen having the data pair being analyzed, but were identified in step 310 of Figure 3 as having negative reactivity with the biological sample.

During the analysis in step 430, some data pairs will be eliminated as not being part of a reactive epitope. Specifically, this embodiment begins by calculating a correlation value R for each data pair [p, a_x] based on Kendall's Gamma Correlation test:

(TP*TN) -(FP* FN)

K — - j(TP + FP\TP +FN)(TN+FPXTN+FN)

The P-value will range between -1 and 1 , with values closer to -1 indicating a higher likelihood that that there is no correlation between the data pair and the reactivity results (indicating that the data pair is not responsible for causing positive reactivity with the biological sample), and values closer to 1 indicating a higher likelihood that there is correlation between the data pair and the reactivity results (indicating that the data pair does cause positive reactivity with the biological sample). In this embodiment, a data pair is determined not to be the cause of the positive reactivity if its R-value is less than zero, in which case analysis for that data pair is terminated.

If the R-value is greater than or equal to zero, the data pair is further analyzed using Fisher's exact test to determine the P-value, which is explained below. Whereas Kendall's Gamma Correlation test is relatively straight-forward and simple to calculate, Fisher's exact test is a computationally expensive algorithm to calculate. Thus, by using Kendall's test to reduce the number of data pairs upon which Fisher's test is calculated. The practical significance is that the invention reduces the computational load of the analysis, thereby achieving surprisingly efficient and accurate results.

For the data pairs [p, a_x] having a non-negative P-value, Fisher's test is used to determine a P-value as follows:

(TP + FP) \*(TP + EN) ! TN + FN) *(TN + FP) ! TP\ *TN\ *FP\ *EN! TP + TN + FP + FN) !

The P-value for a given data pair, like the R-value, provides an indication of the likelihood that the presence of the data pair in an antigen preparation is a cause of the positive reactivity results determined in step 310 of Figure 3. It should be noted that the P-value is always positive, with values closer to zero indicating a higher likelihood of correlation.

However, as can be seen by the formula above, the P-value requires factorials to be calculated, which exponentially become computationally expensive to calculate as the factorial increases.

As is known in the industry, full calculation of Fisher's test for a large number of samples is cumbersome and in the past, has simply been impracticable. To avoid this problem, the invention assumes that

a→∞

Accordingly, if the numerator is sufficiently greater than the denominator, the invention determines that the data pair being analyzed has a high P-value, indicating that the data pair is unlikely to be a cause of the positive reactivity detected with the biological sample. The specific values for the ratio are set such that it sufficiently limits the output, and may vary for different applications. In a preferred embodiment, the values are determined empirically by analyzing a representative data set. Specifically, if calculation of the numerator would cause an overflow error (so that a valid value could not be determined) and the denominator would not cause an overflow error (so that a valid value could be determined), then it is determined that the P-value is sufficiently high to indicate that the data pair is unlikely to be a cause of the detected positive reactivity. As a result, analysis of this data pair is accordingly terminated. Similarly, if the numerator is positive and the denominator is determined to be less than a predetermined threshold, which may be adjusted as appropriate for specific applications, then it is determined that the P-value is sufficiently high to indicate that the data pair is unlikely to be a cause of the positive reactivity detected with the biological sample, and analysis of the data pair is terminated.

Referring again to Figure 4, step 430 is repeated to determine the P-values for each of the data pairs [p,a_x] at position p for each of the X sequences. Keeping in mind that the goal of the process described in Figure 4 is to identify those data pairs that will react positively with antibodies in the biological sample, some of the data pairs can be eliminated in step 430 as a result of the Kendall and Fisher tests.

When all of the data pairs for the position p are evaluated, the invention determines whether there are remaining sequence positions to be evaluated, as indicated by step 440 in Figure 4. In this case, the sequences have 200 positions. Thus, if p is less than 200, at least one position remains to be evaluated. Accordingly, p is incremented, as shown by step 445, and the process returns to evaluate the data pairs for the newly advanced position p.

If p is equal to 200 in step 440, all of the positions in the sequences have been evaluated and, as indicated by step 450 in Figure 4, the invention then identifies a set of reactive data pairs - i.e., those data pairs that will positively react with antibodies in the biological sample.

In this embodiment, this is accomplished by comparing each P-value for the data pairs not eliminated in step 430 to a predetermined threshold value, wherein P- values falling below the threshold value are determined to indicate that the data pairs corresponding to those P-values will positively react with at least one antibody in the biological sample. The threshold value used may be varied depending on specific applications - in this embodiment, the threshold value is set at 5 - all data pairs having P-values of 5 or less are therefore determined to be reactive data pairs, meaning that any antigen including that data pair will react positively with at least one antibody in the biological sample.

At this point, the process of Figure 4 is completed, and the next step, represented by step 340 in Figure 3, determines the set of alleles that contain one or more reactive data pair. For example, if it is determined that the amino acid E in position 62 will react positively with the biological sample, step 340 will identify all known antigens that have the amino acid E in the position 62. This can be accomplished by using any periodically updated database including information about all known alleles and all known amino acid sequences that correspond to those alleles. Examples include, without limitation, those databases that contain information gathered from the World Health Organization (WHO) and other scientific literature.

Although illustrative embodiments of the invention have been described in detail herein with reference to the accompanying drawings, those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention specifically described herein. Such equivalents are intended to be encompassed in the scope of the following claims without departing from the scope and spirit of the invention as defined by the appended claims. For example, it will be appreciated that test results from other suitable bioassays, including flow cytometry, other in vitro immunoassays, etc., may be used without departing from the principals of the present invention. If an ELISA test is used, varieties other than the PRA-STAT® test kit available from SangStat Medical Corporation may be used. Further, the invention identifies or detects epitopes or antigens against which a biological sample will react. Such epitopes or antigens may be included in HLA genes or other polymorphic gene families. In addition, the invention may be used to identify or detect alloreactive T- cells that will be formed by the immune system against epitopes or antigens. Finally, although the embodiment described above preferably analyzes amino acid sequences by single positions, the invention may be used to analyze the sequences by groups of amino acids in sequential positions, such as duplets, triplets etc.

Claims

WHAT IS CLAIMED IS:

1. A computer-implemented method for determining a set of antigenic epitopes against which a biological sample is reactive, comprising: mixing the biological sample with a plurality of antigen preparations each comprising a known mixture of antigens; determining, for each of the antigen preparations, a positive or negative reactivity with the biological sample; and identifying epitopes shared by those antigen preparations determined to have a positive reactivity as reactive epitopes.

2. The method of claim 1 , further comprising determining a set of antigens containing at least one identified reactive epitope.

3. The method of claim 1 , wherein the step of identifying epitopes shared by those antigen preparations determined to have a positive reactivity as reactive epitopes further comprises: identifying a set of antigens present in the antigen preparations determined to have a positive reactivity with the biological sample; determining a set of amino acid sequences corresponding to the determined set of antigens; and analyzing data pairs describing an amino acid and its position in an amino acid sequence for the set of amino acid sequences to determine a set of reactive data pairs, wherein each reactive data pair is a reactive epitope determined to be reactive with the biological sample.

4. The method of claim 3, wherein the step of analyzing data pairs analyzes the data pairs in groups, each data pair group describing a sequence of two or more amino acids and the respective positions in an amino acid sequence for the set of amino acid sequences to determine a set of reactive data pair groups, wherein each reactive data pair group corresponds to a reactive epitope determined to be reactive with the biological sample.

5. The method of claim 3, wherein the step of analyzing the data pairs further comprises, for each data pair: determining the antigen preparations including one or more antigen having that data pair; correlating each antigen preparation with the positive or negative reactivity with the biological sample; and determining a correlation indicator between the presence of that data pair and a positive reactivity with the biological sample.

6. The method of claim 5, wherein the correlation indicator is a value determined by using an algorithm based on Fisher's test.

7. A memory device storing computer readable instructions for aiding a computer to determine a set of antigenic epitopes against which a biological sample is reactive, comprising: instructions for receiving data for reactions resulting from mixing the biological sample with a plurality of antigen preparations each comprising a known mixture of antigens; instructions for determining, for each of the antigen preparations, a positive or negative reactivity with the biological sample; and instructions for identifying epitopes shared by those antigen preparations determined to have a positive reactivity as reactive epitopes.

8. The memory device of claim 7, further comprising instructions for determining a set of antigens containing at least one identified reactive epitope.

9. The memory device of claim 7, wherein the instructions for identifying epitopes further comprises: instructions for identifying a set of antigens present in the antigen preparations determined to have a positive reactivity with the biological sample; instructions for determining a set of amino acid sequences corresponding to the determined set of antigens; and instructions for analyzing data pairs describing an amino acid and its position in an amino acid sequence for the set of amino acid sequences to determine a set of reactive data pairs, wherein each reactive data pair is a reactive epitope determined to be reactive with the biological sample.

10. The method of claim 9, wherein the instructions for analyzing data pairs analyzes the data pairs in groups, each data pair group describing a sequence of two or more amino acids and the respective positions in an amino acid sequence for the set of amino acid sequences to determine a set of reactive data pair groups, wherein each reactive data pair group corresponds to a reactive epitope determined to be reactive with the biological sample.

11. The method of claim 9, wherein the instructions for analyzing the data pairs further comprises, for each data pair: instructions for determining the antigen preparations including one or more antigen having that data pair; instructions for correlating each antigen preparation with the positive or negative reactivity with the biological sample; and instructions for determining a correlation indicator between the presence of that data pair and a positive reactivity with the biological sample.

12. The method of claim 11 , wherein the correlation indicator is a value determined by using an algorithm based on Fisher's test.

13. A system for determine a set of antigenic epitopes against which a biological sample is reactive, comprising: a test system for determining data for reactions resulting from mixing the biological sample with a plurality of antigen preparations each comprising a known mixture of antigens; and a computer system for: receiving the data from the test system; determining, for each of the antigen preparations, a positive or negative reactivity with the biological sample; and identifying epitopes shared by those antigen preparations determined to have a positive reactivity as reactive epitopes.

14. The system of claim 13, wherein the test system is an ELISA system.

15. The system of claim 13, wherein the computer system further determines a set of antigens containing at least one identified reactive epitope.

16. The system of claim 13, wherein the computer system identifies epitopes by: identifying a set of antigens present in the antigen preparations determined to have a positive reactivity with the biological sample; determining a set of amino acid sequences corresponding to the determined set of antigens; and analyzing data pairs describing an amino acid and its position in an amino acid sequence for the set of amino acid sequences to determine a set of reactive data pairs, wherein each reactive data pair is a reactive epitope determined to be reactive with the biological sample.

17. The system of claim 13, wherein the computer system analyzes the data pairs by, for each data pair: determining the antigen preparations including one or more antigen having that data pair; correlating each antigen preparation with the positive or negative reactivity with the biological sample; and determining a correlation indicator between the presence of that data pair and a positive reactivity with the biological sample.

18. The method of claim 17, wherein the correlation indicator is a value determined by using an algorithm based on Fisher's test.