Determining Susceptibility To A Sudden Cardiac Event
Disclosed herein is a method of do terming the likelihood of a sudden cardiac event, such as an arrythmia, in a subject. Also disclosed is a method of determining whether a subject is at risk of a sudden cardiac event arid whether the subject would benefit from a treatment such as implantation of an ICD.
1 . A method for predicting the likelihood of a sudden cardiac event (SCE) in a subject, comprising:
obtaining a first dataset associated with a sample obtained from the subject, wherein the first dataset comprises data for a single nucleotide polymorphism (SNP) marker selected from Table 15; and
analyzing the first dataset to determine the presence or absence of data for the SNP marker, wherein the presence of the SNP marker data is positively correlated or negatively correlated with the likelihood of SCE in the subject.
2 . The method of claim 1 , wherein the SNP marker is rs17024266.
3 . The method of claim 1 , wherein the first dataset comprises data for at least two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more SNP markers selected from Table 15, and further comprising analyzing the first dataset to determine the presence or absence of data for the at least two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty or more SNP markers selected from Table 15.
4 . The method of claim 3 , further comprising determining the likelihood of SCE in the subject according to the relative number of positively correlated and negatively correlated SNP marker data present in the first dataset.
5 . The method of claim 1 , father comprising determining the likelihood that the subject would benefit from implantation of an internal cardioverter defibrillator (ICD) based on the analysis.
6 . The method of claim 1 , wherein the SCE is a ventricular arrhythmia.
7 . The method of claim 1 , wherein the SNP marker comprises at least one SNP marker selected from the group consisting of: rs17024266, rs1472929, rs17093751, rs6791277, rs4665719, rs12477891, rs5943590, rs1018615, and rs10088053.
8 . The method of claim 1 , wherein the likelihood of SCE in the subject is increased in the subject compared to a control.
9 . The method of claim 8 , wherein the control is a second dataset associated with a control sample, wherein the second dataset comprises data for a control wild-type marker at a specified locus rather than the SNP marker at that locus.
10 . The method of claim 1 , wherein the likelihood of SCE in the subject is not increased in the subject compared to a control.
11 . The method of claim 1 , further comprising selecting a therapeutic regimen based on the analysis.
12 . The method of claim 1 , wherein the data is genotyping data.
13 . The method of claim 1 , wherein the method is implemented on one or more computers.
14 . The method of claim 1 , wherein the first dataset is obtained stored on a storage memory.
15 . The method of claim 1 , wherein obtaining the first dataset associated with the sample comprises obtaining the sample and processing the sample to experimentally determine the first dataset.
16 . The method of claim 1 , wherein obtaining the first dataset associated with the sample comprises receiving the first dataset directly or indirectly from a third party that has processed the sample to experimentally determine the first dataset.
17 . The method of claim 1 , wherein the data is obtained from a nucleotide-based assay.
18 . The method of claim 1 , wherein the subject is a human subject.
19 . The method of claim 1 , further comprising assessing a clinical factor in the subject; and combining the assessment with the analysis of the first dataset to predict the likelihood of SCE in the subject.
20 . The method of claim 19 , wherein the clinical factor comprises at least one clinical factor selected from the group consisting of age, gender, race, implant indication, prior pacing status, ICD presence, cardiac resynchronization therapy defibrillator (CRT-D) presence, total number of devices, device type, defibrillation thresholds performed, number of programming zones, heart failure (HF) etiology, HF onset, left ventricular ejection fraction (LVEF) at implant, New York Heart Association (NYHA) class, months from most recent myocardial infarction (MI) at implant, prior arrhythmia event in setting of MI or arthroscopic chondral osseous autograft transplantation (Cor procedure), diabetes status, Blood Urea Nitrogen (BUN), Cr, renal disease history, rhythm parameters to determine sinus v. non-sinus, heart rate, QRS duration prior to implant, left bundle branch block, systolic blood pressure, history of hypertension, smoking status, pulmonary disease, body mass index (BMI), family history of sudden cardiac death, B-type natriuretic peptide (BNP) levels, prior cardiac surgeries, medications, microvolt-level T-wave alternans (MTWA) result, and inducibility at electro-physiologic study (EPS).
21 . A method for determining the likelihood of SCE in a subject, comprising:
obtaining a sample from the subject, wherein the sample comprises a SNP marker selected from Table 15;
contacting the sample with a reagent;
generating a complex between the reagent and the SNP marker;
detecting the complex to obtain a dataset associated with the sample, wherein the dataset comprises data for the SNP marker; and
analyzing the dataset to determine the presence or absence of the SNP marker, wherein the presence of the marker is positively correlated or negatively correlated with the likelihood of SCE in the subject.
22 . A computer-implemented method for predicting the likelihood of SCE in a subject, comprising:
storing, in a storage memory, a dataset associated with a first sample obtained from the subject, wherein the dataset comprises data for a SNP marker selected from Table 15; and
analyzing, by a computer processor, the dataset to determine the presence or absence of the SNP marker, wherein the presence of the SNP marker is positively correlated or negatively correlated with the likelihood of SCE in the subject.
23 . A system for predicting the likelihood of SCE in a subject, the system comprising:
a storage memory for storing a dataset associated with a sample obtained from the subject, wherein the dataset comprises data for a SNP marker selected from Table 15; and
a processor communicatively coupled to the storage memory for analyzing the dataset to determine the presence or absence of the SNP marker, wherein the presence of the SNP marker is positively correlated or negatively correlated with the likelihood of SCE in the subject.
24 . A computer-readable storage medium storing computer-executable program code, the program code comprising:
program code for storing a dataset associated with a sample obtained from a subject, wherein the dataset comprises data for a SNP marker selected from Table 15; and
program code for analyzing the dataset to determine the presence or absence of the SNP marker, wherein the presence of the SNP marker is positively correlated or negatively correlated with the likelihood of SCE in the subject.
25 . A kit for use in predicting the likelihood of SCE in a subject, comprising:
a set of reagents comprising a plurality of reagents for determining from a sample obtained from the subject data for a SNP marker selected from Table 15; and
instructions for using the plurality of reagents to determine data from the sample.
26 . The kit of claim 25 , wherein the instructions comprise instructions for conducting a nucleotide-based assay.
27 . A kit for use in predicting the likelihood of SCE in a subject, comprising:
a set of reagents consisting essentially of a plurality of reagents for determining from a sample obtained from the subject data for a SNP marker selected from Table 15; and
instructions for using the plurality of reagents to determine data from the sample.
28 . The kit of claim 27 , wherein the instructions comprise instructions for conducting a nucleotide-based assay.