# US 2021/0280269 A1 · Assay for Hemoglobin A (HBA) Detection and Genotyping

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- Number: US 2021/0280269 A1
- Document ID: US20210280269A1
- Status: Published application
- Kind: A1
- Application number: 17/193,629
- Filed: 2021-03-05
- Published: 2021-09-09
- Earliest claimed: 2020-03-06
- Assignees: Laboratory Corporation of America Holdings
- Applicants: Laboratory Corporation of America Holdings
- Inventors: Andrew Walker; Matt Robinson
- Web page: https://patentgrep.com/patent/US20210280269A1

## CPC

- G16B 20/10: Ploidy or copy number detection
- G16B 20/20: Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
- C12Q 1/6883: for diseases caused by alterations of genetic material
- G01N 27/44782: {of a plurality of samples}
- G16B 40/00: ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
- C12Q 2600/156: Polymorphic or mutational markers
- Y02A 50/30: Against vector-borne diseases, e.g. mosquito-borne, fly-borne, tick-borne or waterborne diseases whose impact is exacerbated by climate change
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- C12Q: MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS (immunoassay G01N33/53); COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)
- Y02A: TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE

## Abstract

The present disclosure relates to a Hemoglobin A (HBA) assay and a HBA genotyping decision tree matrix for implementation into clinical testing. Particularly, aspects are directed to obtaining raw data from the HBA assay performed on a plurality of samples, calculating a first set of probe ratios for each sample based on the raw data, identifying a number of reference samples to be combined as a synthetic reference sample based on the first set of probe ratios, calculating a second set of probe ratios for each sample of the plurality of samples based on the raw data and the synthetic reference sample, and determining, by the decision tree matrix, a HBA genotype for each sample based on the second set of probe ratios for each sample and copy number calling thresholds for sample probe/reference probe ratios associated with each probe of the plurality of probes.

## Claims

### Claim 1

A method comprising:
obtaining raw data from a Hemoglobin A (HBA) assay performed on a plurality of samples, wherein the HBA assay is performed using a plurality of probes capable of detection of copy number losses or gains in a α-globin gene cluster region of each sample of the plurality of samples, and the raw data comprises HBA copy number data for the plurality of probes resolved by capillary electrophoresis for each sample of the plurality of samples;
selecting a reference sample from the plurality of samples;
calculating a first set of probe ratios for each sample of the plurality of samples based on the raw data from the HBA assay and the reference sample;
identifying a predetermined number of reference samples to be combined as a synthetic reference sample for the plurality of samples based on the first set of probe ratios;
generating the synthetic reference sample based on the predetermined number of reference samples;
calculating a second set of probe ratios for each sample of the plurality of samples based on the raw data from the HBA assay and the synthetic reference sample;
iteratively inputting the second set of probe ratios for each sample into a decision tree matrix;
determining, by the decision tree matrix, a HBA genotype for each sample based on the second set of probe ratios for each sample and copy number calling thresholds for sample probe/reference probe ratios associated with each probe of the plurality of probes; and
providing the HBA genotype for each sample.

### Claim 2 (depends on 1)

The method of claim 1, wherein the calculating the first set of probe ratios comprises: (i) comparing control probe peak heights, or signals, in each sample of the plurality of samples to corresponding control probe peak heights, or signals, in the reference sample, (ii) calculating variability in signals between the control probe peak heights, or signals, in each sample and the corresponding control probe peak heights, or signals, in the reference sample as a control probe standard deviation, (iii) determining a sample of the plurality samples fails when any variability metrics are greater than a predetermined threshold, (iv) determining a sample of the plurality of samples does not fail when none of the variability metrics are greater than the predetermined threshold, and (v) for each sample that does not fail, comparing test probe peak heights, or signals, in the sample to corresponding test probe peak heights in the reference sample, and calculating a probe ratio between the test probe peak heights, or signals, in the sample and the corresponding test probe peak heights, or signals, in the reference sample.

### Claim 3 (depends on 2)

The method of claim 2, wherein the calculating the second set of probe ratios comprises: (i) comparing the control probe peak heights, or signals, in each sample of the plurality of samples to corresponding control probe peak heights, or signals, in the synthetic reference sample, (ii) calculating variability in signals between the control probe peak heights, or signals, in each sample and the corresponding control probe peak heights, or signals in the synthetic reference sample as a control probe standard deviation, (iii) determining a sample of the plurality samples fails when any variability metrics are greater than the predetermined threshold, (iv) determining a sample of the plurality of samples does not fail when none of the variability metrics are greater than the predetermined threshold, and (v) for each sample that does not fail, comparing test probe peak heights, or signals, in the sample to corresponding test probe peak heights in the synthetic reference sample, and calculating a probe ratio between the test probe peak heights, or signals, in the sample and the corresponding test probe peak heights, or signals, in the synthetic reference sample.

### Claim 4 (depends on 3)

The method of claim 3, wherein the determining the HBA genotype for each sample comprises: (i) determining aberrant probe ratio patterns for each sample based on the second set of probe ratios for each sample and the copy number calling thresholds for the sample probe/reference probe ratios associated with each probe of the plurality of probes, and (ii) identify the HBA genotype for each sample based on the aberrant probe ratio patterns.

### Claim 5 (depends on 4)

The method of claim 4, wherein the determining the aberrant probe ratio patterns and the identifying the HBA genotype for each sample comprises:
classifying each sample as normal, having a copy number variation (CNV), or as polymorphic based on the aberrant probe ratio patterns; and
sub classifying any sample classified as having the CNV as a large targeted deletion, duplication or ‘other’ based on the aberrant probe ratio patterns.

### Claim 6 (depends on 5)

The method of claim 5, wherein the determining the aberrant probe ratio patterns and the identifying the HBA genotype for each sample further comprises:
sub classifying any sample classified as having the large targeted deletion as a large heterozygous deletion or a homozygous deletion;
sub classifying any sample classified as the large heterozygous deletion or the homozygous deletion for one or more of the following deletions: SEA, FIL/THAI, MED or α20.5 based on the aberrant probe ratio patterns; and
sub classifying any sample classified as having the large heterozygous deletion for one or more of the following: α3.7 deletions, α4.2 deletions and/or α3.7 duplications based on the aberrant probe ratio patterns.

### Claim 7 (depends on 5)

The method of claim 5, wherein the determining the aberrant probe ratio patterns and the identifying the HBA genotype for each sample further comprises:
sub classifying any sample classified as ‘other’ as having α3.7 deletions, α4.2 deletions, and/or α3.7 duplications based on the aberrant probe ratio patterns.

### Claim 8 (depends on 1)

The method of claim 1, further comprising triggering performance of a confirmatory test on each sample of the plurality of samples that has the HBA genotype that is not normal or does not require manual review.

### Claim 9

A system comprising:
one or more data processors; and
a non-transitory computer readable storage medium containing instructions which, when executed on the one or more data processors, cause the one or more data processors to perform actions including:
obtaining raw data from a Hemoglobin A (HBA) assay performed on a plurality of samples, wherein the HBA assay is performed using a plurality of probes capable of detection of copy number losses or gains in a α-globin gene cluster region of each sample of the plurality of samples, and the raw data comprises HBA copy number data for the plurality of probes resolved by capillary electrophoresis for each sample of the plurality of samples;
selecting a reference sample from the plurality of samples;
calculating a first set of probe ratios for each sample of the plurality of samples based on the raw data from the HBA assay and the reference sample;
identifying a predetermined number of reference samples to be combined as a synthetic reference sample for the plurality of samples based on the first set of probe ratios;
generating the synthetic reference sample based on the predetermined number of reference samples;
calculating a second set of probe ratios for each sample of the plurality of samples based on the raw data from the HBA assay and the synthetic reference sample;
iteratively inputting the second set of probe ratios for each sample into a decision tree matrix;
determining, by the decision tree matrix, a HBA genotype for each sample based on the second set of probe ratios for each sample and copy number calling thresholds for sample probe/reference probe ratios associated with each probe of the plurality of probes; and
providing the HBA genotype for each sample.

### Claim 10 (depends on 9)

The system of claim 9, wherein the calculating the first set of probe ratios comprises: (i) comparing control probe peak heights, or signals, in each sample of the plurality of samples to corresponding control probe peak heights, or signals, in the reference sample, (ii) calculating variability in signals between the control probe peak heights, or signals, in each sample and the corresponding control probe peak heights, or signals, in the reference sample as a control probe standard deviation, (iii) determining a sample of the plurality samples fails when any variability metrics are greater than a predetermined threshold, (iv) determining a sample of the plurality of samples does not fail when none of the variability metrics are greater than the predetermined threshold, and (v) for each sample that does not fail, comparing test probe peak heights, or signals, in the sample to corresponding test probe peak heights in the reference sample, and calculating a probe ratio between the test probe peak heights, or signals, in the sample and the corresponding test probe peak heights, or signals, in the reference sample.

### Claim 11 (depends on 10)

The system of claim 10, wherein the calculating the second set of probe ratios comprises: (i) comparing the control probe peak heights, or signals, in each sample of the plurality of samples to corresponding control probe peak heights, or signals, in the synthetic reference sample, (ii) calculating variability in signals between the control probe peak heights, or signals, in each sample and the corresponding control probe peak heights, or signals in the synthetic reference sample as a control probe standard deviation, (iii) determining a sample of the plurality samples fails when any variability metrics are greater than the predetermined threshold, (iv) determining a sample of the plurality of samples does not fail when none of the variability metrics are greater than the predetermined threshold, and (v) for each sample that does not fail, comparing test probe peak heights, or signals, in the sample to corresponding test probe peak heights in the synthetic reference sample, and calculating a probe ratio between the test probe peak heights, or signals, in the sample and the corresponding test probe peak heights, or signals, in the synthetic reference sample.

### Claim 12 (depends on 11)

The system of claim 11, wherein the determining the HBA genotype for each sample comprises: (i) determining aberrant probe ratio patterns for each sample based on the second set of probe ratios for each sample and the copy number calling thresholds for the sample probe/reference probe ratios associated with each probe of the plurality of probes, and (ii) identify the HBA genotype for each sample based on the aberrant probe ratio patterns.

### Claim 13 (depends on 12)

The system of claim 12, wherein the determining the aberrant probe ratio patterns and the identifying the HBA genotype for each sample comprises:
classifying each sample as normal, having a copy number variation (CNV), or as polymorphic based on the aberrant probe ratio patterns; and
sub classifying any sample classified as having the CNV as a large targeted deletion, duplication or ‘other’ based on the aberrant probe ratio patterns.

### Claim 14 (depends on 12)

The system of claim 12, wherein the determining the aberrant probe ratio patterns and the identifying the HBA genotype for each sample further comprises:
sub classifying any sample classified as having the large targeted deletion as a large heterozygous deletion or a homozygous deletion;
sub classifying any sample classified as the large heterozygous deletion or the homozygous deletion for one or more of the following deletions: SEA, FIL/THAI, MED or α20.5 based on the aberrant probe ratio patterns; and
sub classifying any sample classified as having the large heterozygous deletion for one or more of the following deletions: α3.7 and α4.2 deletions based on the aberrant probe ratio patterns.

### Claim 15 (depends on 9)

The system of claim 9, wherein the actions further include triggering performance of a confirmatory test on each sample of the plurality of samples that has the HBA genotype that is not normal or does not require manual review.

### Claim 16

A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform actions including:
obtaining raw data from a Hemoglobin A (HBA) assay performed on a plurality of samples, wherein the HBA assay is performed using a plurality of probes capable of detection of copy number losses or gains in a α-globin gene cluster region of each sample of the plurality of samples, and the raw data comprises HBA copy number data for the plurality of probes resolved by capillary electrophoresis for each sample of the plurality of samples;
selecting a reference sample from the plurality of samples;
calculating a first set of probe ratios for each sample of the plurality of samples based on the raw data from the HBA assay and the reference sample;
identifying a predetermined number of reference samples to be combined as a synthetic reference sample for the plurality of samples based on the first set of probe ratios;
generating the synthetic reference sample based on the predetermined number of reference samples;
calculating a second set of probe ratios for each sample of the plurality of samples based on the raw data from the HBA assay and the synthetic reference sample;
iteratively inputting the second set of probe ratios for each sample into a decision tree matrix;
determining, by the decision tree matrix, a HBA genotype for each sample based on the second set of probe ratios for each sample and copy number calling thresholds for sample probe/reference probe ratios associated with each probe of the plurality of probes; and
providing the HBA genotype for each sample.

### Claim 17 (depends on 16)

The computer-program product of claim 16, wherein the calculating the first set of probe ratios comprises: (i) comparing control probe peak heights, or signals, in each sample of the plurality of samples to corresponding control probe peak heights, or signals, in the reference sample, (ii) calculating variability in signals between the control probe peak heights, or signals, in each sample and the corresponding control probe peak heights, or signals, in the reference sample as a control probe standard deviation, (iii) determining a sample of the plurality samples fails when any variability metrics are greater than a predetermined threshold, (iv) determining a sample of the plurality of samples does not fail when none of the variability metrics are greater than the predetermined threshold, and (v) for each sample that does not fail, comparing test probe peak heights, or signals, in the sample to corresponding test probe peak heights in the reference sample, and calculating a probe ratio between the test probe peak heights, or signals, in the sample and the corresponding test probe peak heights, or signals, in the reference sample.

### Claim 18 (depends on 17)

The computer-program product of claim 17, wherein the calculating the second set of probe ratios comprises: (i) comparing the control probe peak heights, or signals, in each sample of the plurality of samples to corresponding control probe peak heights, or signals, in the synthetic reference sample, (ii) calculating variability in signals between the control probe peak heights, or signals, in each sample and the corresponding control probe peak heights, or signals in the synthetic reference sample as a control probe standard deviation, (iii) determining a sample of the plurality samples fails when any variability metrics are greater than the predetermined threshold, (iv) determining a sample of the plurality of samples does not fail when none of the variability metrics are greater than the predetermined threshold, and (v) for each sample that does not fail, comparing test probe peak heights, or signals, in the sample to corresponding test probe peak heights in the synthetic reference sample, and calculating a probe ratio between the test probe peak heights, or signals, in the sample and the corresponding test probe peak heights, or signals, in the synthetic reference sample.

### Claim 19 (depends on 18)

The computer-program product of claim 18, wherein the actions further include determining a risk score for a subject associated with the sample based on the AGG genotype generated for the first allele, the second allele, or both the first allele and the second allele, and wherein the risk score identifies a risk of the subject developing late-onset neurodegenerative disease fragile X-associated tremor/ataxia syndrome (FXTAS) or fragile X-associated primary ovarian insufficiency (FXPOI) or transmitting a full mutation allele to their offspring or any combination thereof.

### Claim 20 (depends on 18)

The computer-program product of claim 18, wherein the determining the HBA genotype for each sample comprises: (i) determining aberrant probe ratio patterns for each sample based on the second set of probe ratios for each sample and the copy number calling thresholds for the sample probe/reference probe ratios associated with each probe of the plurality of probes, and (ii) identify the HBA genotype for each sample based on the aberrant probe ratio patterns.

### Claim 21 (depends on 16)

The computer-program product of claim 16, wherein the actions further include triggering performance of a confirmatory test on each sample of the plurality of samples that has the HBA genotype that is not normal or does not require manual review.