DETAILED ACTION
Applicant’s response, filed 02/06/2026, has been fully considered. Rejections and/or objections not reiterated from previous Office Actions are hereby withdrawn. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Request for Continued Examination
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 02/06/2026 has been entered.
Claim Status
Claims 1-27, 29, 32-29, 73, 75-81, and 92-96 are pending.
Claims 92-93 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a non-elected species, as set forth in the Non-Final Office Action dated 10/28/2024.
Claim 94-96 are newly added.
Claims 3-4, 8, 38, 30-31, 40-72, 74, and 79-91 are canceled.
Claims 1-2, 5-7, 9-27, 29, 32-39, 73, 75-78, 94-96 are rejected.
Priority
Applicant's claim for the benefit of a prior-filed application, PCT/EP2019/077252, filed October 8, 2019, is acknowledged.
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d) to App. No. EPO18199156.3, filed October 8, 2018. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Accordingly, each of claims 1-39, 73, and 75-81 are afforded the effective filing date of October 8, 2018.
Drawings
The Drawings submitted April 8, 2021 are accepted.
Claim Rejections- 35 USC § 112
The outstanding rejections to claims 8, 32, and 79 are withdrawn in view of the amendments and claim cancellations submitted herein.
Claim Rejections - 35 USC § 112
35 U.S.C. 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claim 7 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 7: “The method of claim 3” lacks antecedent basis. Claim 3 has been cancelled Suggest amending claim 7 to depend from claim 1 to overcome the rejections.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
The rejection of claims 1-2, 5-7, 9-27, 29, 32-39, 73, 75-78 are maintained from the previous Office Action. The rejection of claims 94-96 are newly stated necessitated by claim amendments.
For the following rejections, underlined text indicates newly recited portions necessitated by claim amendment.
A. Claims 1-2, 5-7, 9-27, 29, 32-39, 75-78, and 94-96 are rejected under 35 U.S.C. 101 because the claimed invention is directed to one or more judicial exceptions without significantly more. Any newly recited portions are necessitated by claim amendment.
MPEP 2106 organizes judicial exception analysis into Steps 1, 2A (Prongs One and Two) and 2B as follows below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
Framework with which to Evaluate Subject Matter Eligibility:
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter;
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea;
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Framework Analysis as Pertains to the Instant Claims:
Step 1
With respect to Step 1: yes, the claims are directed to methods, i.e., a process, machine, or manufacture within the above 101 categories [Step 1: YES; See MPEP § 2106.03]
Step 2A, Prong One
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. The MPEP at 2106.04(a)(2) further explains that abstract ideas are defined as:
mathematical concepts (mathematical formulas or equations, mathematical relationships and mathematical calculations);
certain methods of organizing human activity (fundamental economic practices or principles, managing personal behavior or relationships or interactions between people); and/or
mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information).
With respect to the instant claims, under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mental processes (in particular procedures for observing, analyzing and organizing information) and mathematical concepts (in particular mathematical relationships and formulas) are as follows:
Independent claim 1:
evaluating on the training data set with a regression method comprising a Least Absolute Shrinkage and Selection Operator (LASSO), thereby determining a reduced training data set,
applying a stepwise regression to the reduced training data set, wherein independent variables of the LASSO are the DNA methylation levels of the genomic DNA sequences and wherein a dependent variable is the chronological age, wherein the age indicator comprises (i) a subset of the set of genomic DNA sequences as an ensemble and (ii) at least one coefficient per genomic DNA sequence contained in the ensemble, and wherein the reduced training data set comprises at least some data of the training data set and does not include the DNA methylation levels of genomic DNA sequences which are eliminated by the LASSO.
Independent claim 2:
evaluating on the training data set with a regression method comprising a Least Absolute Shrinkage and Selection Operator (LASSO), thereby determining a reduced training data set,
applying a stepwise regression to the reduced training data set to determine an age indicator, wherein independent variables of the LASSO are the DNA methylation levels of the genomic DNA sequences and wherein a dependent variable is the chronological age, wherein the age indicator comprises (i) a subset of the set of genomic DNA sequences as an ensemble and (ii) at least one coefficient per genomic DNA sequence contained in the ensemble, and wherein the reduced training data set comprises at least some data of the training data set and does not include the DNA methylation levels of genomic DNA sequences which are eliminated by the LASSO,
receiving the DNA methylation levels of the individual for whom the age is to be determined of at least 80% or 100% of the genomic DNA sequences comprised in the age indicator,
determining the age of the individual based on its DNA methylation levels and the age indicator, wherein the determined age can be different from the chronological age of the individual.
Dependent claim 11:
iteratively updating the age indicator, wherein iteratively updating the age indicator comprises adding the data of at least one further individual to the training data in each iteration, thereby iteratively expanding the training data set.
Dependent claim 21:
determining the quality of the age indicator by statistical evaluation and/or evaluation of the domain boundaries, wherein the statistical evaluation comprises
determining the age of the individuals comprised in the test data set
correlating the determined age and the chronological age of said individual(s)
determining at least one statistical parameter describing this correlation
judging if the statistical parameter(s) indicate(s) an acceptable quality of the age indicator or not or wherein the statistical parameter comprise a coefficient of determination (R2), wherein a R2 of greater than 0.90 or greater than 0.98 and/or at most 1 year, indicates an acceptable quality, and wherein evaluation of the domain boundaries comprises
determining the domain boundaries of the age indicator, wherein the domain boundaries are the minimum and maximum DNA methylation levels of each genomic DNA sequence comprised in the age indicator and wherein said minimum and maximum DNA methylation levels are found in the training data set which has been used for determining the age indicator
determining if the test data set exceeds the domain boundaries, wherein not exceeding the domain boundaries indicates an acceptable quality.
Dependent claim 27:
wherein the set of genomic DNA sequences comprised in the training data set is preselected from genomic DNA sequences whereof the methylation level is associable with chronological age.
Dependent claims 5-7, 9-10, 12-18, 20, 23-26, 29, 32-34, 76-78, and 94-96 recite further steps that limit the judicial exceptions in independent claims 1 and 2 and, as such, also are directed to those abstract ideas. For example, claim 5 further limits the ensemble in claim 1, claim 6 further limits the ensemble of claim 1, claim 7 further limits stepwise regression of claim 3, , claim 9 further limits the regression method of claim 1, claim 10 further limits the LASSO of claim 1, claim 12 further limits the one updating round of claim 11, claim 13 further limits the genomic DNA sequences of claim 11, claim 14 further limits the one updating round of claim 11, claim 15 further limits updating round of claim 11, claim 16 further limits the training data set of claim 11, claim 17 further limits the reduced training set of claim 16, claim 18 further limits the updating round of claim 1, claim 19 further limits the updating round of claim 1, claim 20 further limits the addition/removal of the data of claim 11, claim 23 further limits the age indicator of claim 21, claim 24 further limits the age of the individual of claim 11, claim 25 further limits the age of the individual of claim 2, claim 26 further limits the age indicator of claim 1, claim 29 further limits the genomic DNA sequences of claim 1, claim 32 further limits the age indicator of claim 1, claim 33 further limits the age indicator of claim 1, claim 34 further limits the genomic DNA sequences of claim 1, claim 75 further limits the training data set of claim 1, claim 76 further limits factor of claim 75, claim 77 further limits training data set of claim 75, claim 78 further limits the factor of claim 75, claim 94 further limits the preselected set of DNA sequences of claim 27, claim 95 further limits the set of genomic DNA sequences of claim 1, and claim 96 further limits the set of genomic sequences of claim 2.
The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation (BRI) and determined to each cover performance either in the mind and/or by mathematical operation because the method only requires a user to manually determine an age indicator or age of an individual. Without further detail as to the methodology involved in “determining”, “removed”, “determining”, “judging”, “updated”, “determined”, “pre-selected”, “selected”, “selecting”, and “amended” under the BRI, one may simply, for example, use pen and paper to determining the age of the individual, the data of at least one individual is removed from the training data set and/or the reduced training data set, determining the quality of the age indicator, determining the age of the individuals, determining at least one statistical parameter, judging if the statistical parameter(s) indicate(s) an acceptable quality, determining the domain boundaries, determining if the test data set exceeds the domain boundaries, the age indicator is updated, determined based on its DNA methylation levels, determined with the age indicator, preselected from genomic DNA sequences, selected from drug consumption, environmental pollutants, shift work and stress, determining at least one life-style factor, selecting from the set an ensemble of genomic DNA, judging whether or not a re-selection of genomic DNA sequences of the ensemble is necessary, preselecting from genomic DNA sequences, selecting from the preselected set an ensemble of genomic DNA, calculating an age of the individual, calculating a statistical measure, judging whether or not the quality according to the statistical measure is acceptable or not, amending a plurality of individuals, the age indicator is iteratively updated comprising adding the data of at least one further individual to the training data in each iteration, thereby iteratively expanding the training data set, and determining that a re-selection of genomic DNA sequences is necessary.
Some of these steps and those recited in the dependent claims require mathematical techniques, such as applying on the training data set a regression method comprising a Least Absolute Shrinkage and Selection Operator (LASSO), applying on the training data set a regression method comprising a Least Absolute Shrinkage and Selection Operator (LASSO), thereby determining the age indicator and a reduced training data set, wherein the independent variables are the methylation levels of the genomic DNA sequences and wherein the dependent variable is the age, applying a stepwise regression subsequently to the LASSO, applying the LASSO on the expanded training data set, thereby determining an updated age indicator and/or an updated reduced training data set, correlating the determined age and the chronological age, and calculating an age of the individual (p. 2, par. 6, p. 11, par. 2, p. 41, par. 4, and p. 48, par. 3).
Therefore, claims 1-2, 5-7, 9-27, 29, 32-39, 75-78, and 94-96recite an abstract idea. [Step 2A, Prong 1: YES; See MPEP § 2106.04].
Step 2A, Prong Two
Because the claims do recite judicial exceptions, direction under Step 2A, Prong Two, provides that the claims must be examined further to determine whether they integrate the judicial exceptions into a practical application (MPEP 2106.04(d)). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the judicial exceptions are integrated into a practical application (MPEP 2106.04(d).I.; MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the judicial exceptions, the claim is said to fail to integrate the judicial exceptions into a practical application (MPEP 2106.04(d).III).
Additional elements, Step 2A, Prong Two
With respect to the instant recitations, the claims recite the following additional elements:
Independent claim 1:
receiving a training data set of a plurality of individuals, the training data set comprising for each individual (i) the DNA methylation levels of a set of genomic DNA sequences for the individual, , and(ii) the chronological age of the individual,
Independent claim 2:
receiving a training data set of a plurality of individuals comprising for each individual(i) the DNA methylation levels of a set of genomic DNA sequences for the individual, , and (ii) the chronological age of the individual,
receiving the DNA methylation levels of the individual for whom the age is to be determined of at least 80% or 100% of the genomic DNA sequences comprised in the age indicator
Dependent claim 21:
receiving a test data set of a plurality of individuals who have not contributed data to the training data set comprising for each said individual of the plurality of individuals who have not contributed data to the training data set (i) the DNA methylation levels of the set of genomic DNA sequences comprised in the age indicator and (ii) the chronological age
Dependent claim 36:
measuring the DNA methylation levels of the genomic DNA sequences in the sample.
Dependent claims 22, and 35-39 recite steps that further limit the recited additional elements in the claims. For example, claim 22 further limits the training data set and/or the test dataset of claim 1, and claim 35-39 further limits the sample of claims 34.
Considerations under Step 2A, Prong Two
With respect to Step 2A, Prong Two, the additional elements of the claims do not integrate the judicial exceptions into a practical application for the following reasons. Those steps directed to data gathering, such as “receiving” and “measuring” such as perform functions of collecting the data needed to carry out the judicial exceptions. Data gathering and outputting do not impose any meaningful limitation on the judicial exceptions, or on how the judicial exceptions are performed. Data gathering and outputting steps are not sufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)).
Thus, none of the claims recite additional elements which would integrate a judicial exception into a practical application, and the claims are directed to one or more judicial exceptions [Step 2A, Prong 2: NO; See MPEP § 2106.04(d)].
Step 2B (MPEP 2106.05.A i-vi)
According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
With respect to the instant claims, the courts have found that receiving and outputting data are well-understood, routine, and conventional functions of a computer when claimed in a merely generic manner or as insignificant extra-solution activity (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network), Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015), and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, as discussed in MPEP 2106.05(d)(II)(i)).
As such, the claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (MPEP2106.05(d)). The data gathering steps as recited in the instant claims constitute a general link to a technological environment which is insufficient to constitute an inventive concept which would render the claims significantly more than the judicial exception (MPEP2106.05(g)&(h)).
Regarding claim 36, the limitation of “DNA methylation levels of the genomic DNA sequences of an individual are measured in a sample of biological material of said individual comprising said genomic DNA sequences” is well-understood, routine, and conventional in the art. There are multiple technologies for measuring the methylation levels of DNA such as COBRA – combined bisulfite restriction analysis, DHPLC – denaturing high-performance liquid chromatography, DMH – differential methylation hybridization, HPCE – high-performance capillary electrophoresis, HPLC – high-performance liquid chromatography, MCA-RDA – methylated CpG island amplification representational difference analysis, MS-AP-PCR – methylation-sensitive arbitrarily primed PCR, MS-DGGE – methylation-specific denaturing gradient gel electrophoresis, MS-DHPLC – methylation-specific denaturing high-performance liquid chromatography, MS-MCA – methylation-specific melting curve analysis, Ms-SnuPE – methylation-sensitive single nucleotide primer extension, MS-SSCA – methylation-specific single-strand conformation analysis, MSO – methylation-specific microarray, MSRE – methylation-sensitive restriction endonuclease, MSRF – methylation-sensitive restriction fingerprinting, PCR – polymerase chain reaction, RLGS – restriction landmark genomic scanning, SAM – S-adenosylmethionine, and TLC – thin-layer chromatography as disclosed by Dahl et al. (Dahl, Christina, and Per Guldberg. "DNA methylation analysis techniques." Biogerontology 4 (2003), newly cited).
Taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself [Step 2B: NO; See MPEP § 2106.05].
B. Claim 73 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because they recite transitory signals.
Claim 73 recites “a data carrier comprising the age indicator obtained by the method of claim 2”. The claimed invention is further directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because it recites a program product on computer storage media. Therefore, the claims read on carrier waves and include transitory propagating signals. (In re Nuijten, Federal Circuit, 2006). It is noted that the recitation of a "non-transitory computer-readable medium" would overcome the rejection with respect to this issue under 101. In the interest of compact prosecution, claim 73 is being examined herein with respect to whether the claim is directed to a judicial exception without significantly more.
Response to Applicant Arguments
Applicant disagrees that the "additional elements of the claims do not integrate the judicial exception into a practical application" since, allegedly, "[t]hose steps ... perform functions of collecting the data needed to carry out the judicial exceptions and the "claims simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception [p. 12, par. 1].
It respectfully found not persuasive. It is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. Furthermore, it is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements or by the additional element(s) in combination with the recited judicial exception. See MPEP 2106.05(a). The additional elements found in the claims are mere data gathering elements which do not integrate into a practical application.
Applicant submits it was not well-understood, routine, or conventional to perform subject matter recited by claim 1, such as performing the recited LASSO operation (and, in particular, the combination of LASSO and stepwise regression) to identify ensembles of genomic DNA sequences relating the age of an individual to the methylation of the genomic DNA within those ensembles.
It is respectfully found not persuasive. The steps of LASSO and stepwise are mathematical concepts and would not be evaluated at Step 2B for conventionality.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-2, 5-6, 9, 21-23, 25, 27, 29, 32-39, and 73 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Vilain et al (US 2014/0228231 A1, published 08/14/2014, cited on IDS dated 01/04/2024).
Claim 1 is directed to a method for determining an age indicator, the method comprising (a) receiving a training data set of a plurality of individuals, the training data set comprising for each individual
Vilain discloses invention provides methods and materials that use observation of DNA characteristics to obtain information relating to the age of individuals [abstract]. Vilain further discloses one can collect a reference data set (e.g. of 100 individuals of varying ages) using specific technology platform(s) and tissue(s) and then design a specific multivariate linear model is fit to this reference data set to estimate the coefficients (e.g. using least squares regression) [0054].
(i) the DNA methylation levels of a set of genomic DNA sequences and for the individual,
Vilain discloses correlating the pattern of cytosine methylation observed with a predicted age of the individual [claim 11] which reads on DNA methylation levels.
(ii) the chronological age of the individual, and
Vilain discloses comparing the predicted age of the individual with the actual chronological age of the individual, wherein the comparison comprises a diagnostic procedure for an age associated pathology [claim 12].
(b) evaluating the training data set with a regression method comprising a Least Absolute Shrinkage and Selection Operator (LASSO), determining a reduced training data set and applying a stepwise regression to the reduced training set, wherein independent variables of the LASSO are the DNA methylation levels of the genomic DNA sequences and wherein a dependent variable is the chronological age, wherein the age indicator comprises
Vilain discloses to test whether additional data points on the microarray could improve the accuracy of the model, we performed lasso penalized regression to screen for the top predictors of age [0072]. Vilain further discloses one can collect a reference data set (e.g. of 100 individuals of varying ages) using specific technology platform(s) and tissue(s) and then design a specific multivariate linear model is fit to this reference data set to estimate the coefficients (e.g. using least squares regression [0054].
(i) a subset of the set of genomic DNA sequences as an ensemble and
(ii) at least one coefficient per genomic DNA sequence contained in the ensemble, and wherein the reduced training data set comprises at least some data of the training data set and does not include the DNA methylation levels of genomic DNA sequences which are eliminated by the LASSO.
Vilain discloses quantifying the methylation status of 27,578 CpG loci in 34 identical twin saliva samples from 21 to 55 years of age using Illumina HumanMethylation27 microarray, covering over 14,000 genes with single nucleotide resolution [0063]. Vilain further discloses the resulting restricted dataset contained 16,155 probes, and all further analyses were performed on this filtered dataset [0063]. Vilain also discloses to test whether additional data points on the microarray could improve the accuracy of the model, we performed lasso penalized regression to Screen for the top predictors of age [0072].
Claim 2 is directed to a method for determining an age indicator, the method comprising (a) receiving a training data set of a plurality of individuals, the training data set comprising for each individual
Vilain discloses invention provides methods and materials that use observation of DNA characteristics to obtain information relating to the age of individuals [abstract]. Vilain further discloses one can collect a reference data set (e.g. of 100 individuals of varying ages) using specific technology platform(s) and tissue(s) and then design a specific multivariate linear model is fit to this reference data set to estimate the coefficients (e.g. using least squares regression) [0054].
(i) the DNA methylation levels of a set of genomic DNA sequences and for the individual,
Vilain discloses correlating the pattern of cytosine methylation observed with a predicted age of the individual [claim 11] which reads on DNA methylation levels.
(ii) the chronological age of the individual, and
Vilain discloses comparing the predicted age of the individual with the actual chronological age of the individual, wherein the comparison comprises a diagnostic procedure for an age associated pathology [claim 12].
(b) evaluating the training data set with a regression method comprising a Least Absolute Shrinkage and Selection Operator (LASSO), determining a reduced training data set and applying a stepwise regression to the reduced training set, wherein independent variables of the LASSO are the DNA methylation levels of the genomic DNA sequences and wherein a dependent variable is the chronological age, wherein the age indicator comprises
Vilain discloses to test whether additional data points on the microarray could improve the accuracy of the model, we performed lasso penalized regression to screen for the top predictors of age [0072]. Vilain further discloses one can collect a reference data set (e.g. of 100 individuals of varying ages) using specific technology platform(s) and tissue(s) and then design a specific multivariate linear model is fit to this reference data set to estimate the coefficients (e.g. using least squares regression [0054].
(i) a subset of the set of genomic DNA sequences as an ensemble and
(ii) at least one coefficient per genomic DNA sequence contained in the ensemble, and wherein the reduced training data set comprises at least some data of the training data set and does not include the DNA methylation levels of genomic DNA sequences which are eliminated by the LASSO.
Vilain discloses quantifying the methylation status of 27,578 CpG loci in 34 identical twin saliva samples from 21 to 55 years of age using Illumina HumanMethylation27 microarray, covering over 14,000 genes with single nucleotide resolution [0063]. Vilain further discloses the resulting restricted dataset contained 16,155 probes, and all further analyses were performed on this filtered dataset [0063]. Vilain also discloses to test whether additional data points on the microarray could improve the accuracy of the model, we performed lasso penalized regression to Screen for the top predictors of age [0072].
(c) receiving the DNA methylation levels of the individual for whom the age is to be determined of at least 80% or 100% of the genomic DNA sequences comprised in the age indicator, and
Vilain discloses method of obtaining information useful to determine an age of an individual, the method comprising the steps of (a) obtaining a biological sample derived from an individual comprising genomic DNA from white blood cells or epithelial cells; so that information useful to determine the age of the individual is obtained [claim 1].
(d) determining the age of the individual based on its DNA methylation levels and the age indicator, wherein the determined age can be different from the chronological age of the individual.
Vilain discloses comparing the predicted age of the individual with the actual chronological age of the individual, wherein the comparison comprises a diagnostic procedure for an age associated pathology [claim 12].
Claim 5 is directed to the method of claim 1, wherein the ensemble of the age indicator is smaller than the set of genomic DNA sequences.
Vilain discloses quantifying the methylation status of 27,578 CpG loci in 34 identical twin saliva samples from 21 to 55 years of age using Illumina HumanMethylation27 microarray, covering over 14,000 genes with single nucleotide resolution [0063]. Vilain further discloses the resulting restricted dataset contained 16,155 probes, and all further analyses were performed on this filtered dataset [0063].
Claim 6 is directed to the method of claim 1, wherein the ensemble of the age indicator is smaller than the set of genomic DNA sequences of the reduced training data set.
Vilain discloses quantifying the methylation status of 27,578 CpG loci in 34 identical twin saliva samples from 21 to 55 years of age using Illumina HumanMethylation27 microarray, covering over 14,000 genes with single nucleotide resolution [0063]. Vilain further discloses the resulting restricted dataset contained 16,155 probes, and all further analyses were performed on this filtered dataset [0063]. Vilain further discloses one can collect a reference data set (e.g. of 100 individuals of varying ages) using specific technology platform(s) and tissue(s) and then design a specific multivariate linear model is fit to this reference data set to estimate the coefficients (e.g. using least squares regression [0054].
Claim 9 is directed to the method of claim 1, wherein the regression method does not comprise a Ridge regression (L2 regularization) or, the regression method comprises an L2 regularization and the L2 regularization parameter/lambda parameter is 0.
Vilain discloses to test whether additional data points on the microarray could improve the accuracy of the model, we performed lasso penalized regression to screen for the top predictors of age [0072].
Claim 21 is directed to the method of claim 1, further comprising determining the quality of the age indicator, wherein the determination of said quality comprises the steps of (a) receiving a test data set of a plurality of individuals who have not contributed data to the training data set comprising= for each said individual of the plurality of individuals who have not contributed data to the training data set
Vilain discloses invention provides methods and materials that use observation of DNA characteristics to obtain information relating to the age of individuals [abstract]. Vilain further discloses one can collect a reference data set (e.g. of 100 individuals of varying ages) using specific technology platform(s) and tissue(s) and then design a specific multivariate linear model is fit to this reference data set to estimate the coefficients (e.g. using least squares regression) [0054].
(i) the DNA methylation levels of a set of genomic DNA sequences and for the individual,
Vilain discloses correlating the pattern of cytosine methylation observed with a predicted age of the individual [claim 11] which reads on DNA methylation levels.
(ii) the chronological age of the individual, and
Vilain discloses comparing the predicted age of the individual with the actual chronological age of the individual, wherein the comparison comprises a diagnostic procedure for an age associated pathology [claim 12].
(b) determining the quality of the age indicator by statistical evaluation and/or evaluation of domain boundaries,
Vilain discloses a leave-one-out analysis forms an accurate epigenetic predictor of age [0071]. Vilain further discloses to provide an unbiased estimate of predictive accuracy for age, we used a leave-one-out analysis where the multivariate regression model was fit on all but one subject and its prediction was related to the truly observed age of the left-out subject [0071] which reads on the quality of the age indicator by statistical evaluation. Vilain also discloses illustrative age prediction analyses models were also designed and tested, for example using a leave-one out analysis, where one subject from the model is systematically removed and the model is used to predict the subjects age [0042].
wherein the statistical evaluation comprises (i) determining the age of the individuals comprised in the test data set,
Vilain discloses illustrative age prediction analyses models were also designed and tested, for example using a leave-one out analysis, where one subject from the model is systematically removed and the model is used to predict the subjects age [0042].
(ii) correlating the determined age and the chronological age of said individual(s) and determining at least one statistical parameter describing this correlation, and
Vilain disclosed the predicted values are highly correlated with the observed age in males (r–0.83, p=3.3x10', n=47), females (r–0.75, p=2.4x10, n=19), and in the combined sample (r=0.83, p=2.2x10', n=66) [0071].
(iii) judging if the statistical parameter(s) indicate(s) an acceptable quality of the age indicator or not or wherein the statistical parameter comprise a coefficient of determination (R2), wherein a R2 of greater than 0.90 or greater than 0.98 and/or a MAE at most 1 year, indicates an acceptable quality, and wherein evaluation of the domain boundaries comprises
Vilain discloses validation of correlated probes in additional samples by using a multivariate linear regression model using Edaradd, Edaradd squared and NPTX2 showed that these two markers explain 76% (or R=0.76) of the variance in age of males and 70% in females [0070]. Although the instant claims recite a R2 of greater than 0.90 or greater than 0.98, it is obvious that one skilled in the art would use optimization and depends on the data input and the desired result. Vilain further discloses our ability to predict an individual’s age to an average accuracy of 5.2 years could be used by forensic scientists to estimate a person's age based on a biological sample alone, once the model has been tested in various biological tissues [0076]. Although the instant claims recite a accuracy of at most a year, it is obvious that one skilled in the art would use optimization and depends on the data input and the desired result.
(iv) determining the domain boundaries of the age indicator, wherein the domain boundaries are the minimum and maximum DNA methylation levels of each genomic DNA sequence comprised in the age indicator and wherein said minimum and maximum DNA methylation levels are found in the training data set which has been used for determining the age indicator, and
Vilain discloses quantifying the methylation levels by assigning a site that is completely methylated on both alleles in all cells has a beta value equal to 1; a completely unmethylated site equals 0, and all subsequent analyses were performed on this beta value (p.8, par. 0063) which reads on at least one coefficient per DNA sequence. Vilain further discloses for computational reasons, the data is filtered by requiring a mean methylation value between 0.05 and 0.95, and variance greater than 0, (p. 8, par. 0063) which reads on a minimum and maximum for the domain boundaries.
(v) determining if the test data set exceeds the domain boundaries, wherein not exceeding the domain boundaries indicates an acceptable quality.
Vilain further discloses for computational reasons, the data is filtered by requiring a mean methylation value between 0.05 and 0.95, and variance greater than 0, (p. 8, par. 0063) which reads on a minimum and maximum for the domain boundaries or acceptable quality.
Claim 22 is directed to the method of claim 1, wherein the training data set comprises at least 10 individuals.
Vilain further discloses one can collect a reference data set (e.g. of 100 individuals of varying ages) using specific technology platform(s) and tissue(s) and then design a specific multivariate linear model is fit to this reference data set to estimate the coefficients (e.g. using least squares regression [0054].
Claim 23 is directed to the method of claim 21, wherein the age indicator is updated when its quality does not satisfy at least one criterion.
Vilain discloses calculating the beta value, which expresses the fraction of methylated cytosines in that location defining, a site that is completely methylated on both alleles in all cells has a beta value equal to 1; a completely unmethylated site equals 0 (p. 8, par. 0063). Vilain further discloses for computational reasons, the data is filtered by requiring a mean methylation value between 0.05 and 0.95, and methylation level greater than 0, (p. 8, par. 0063) which reads on a minimum and maximum methylation level or acceptable quality.
Claim 25 is directed to the method of claim 2, wherein the age of the individual is only determined with the age indicator when he/she has not contributed data to the training data set which is used for generating said age indicator.
Vilain discloses a leave-one-out analysis forms an accurate epigenetic predictor of age [0071]. Vilain further discloses to provide an unbiased estimate of predictive accuracy for age, we used a leave-one-out analysis where the multivariate regression model was fit on all but one subject and its prediction was related to the truly observed age of the left-out subject [0071] which reads on the quality of the age indicator by statistical evaluation. Vilain also discloses illustrative age prediction analyses models were also designed and tested, for example using a leave-one out analysis, where one subject from the model is systematically removed and the model is used to predict the subjects age [0042].
Claim 27 is directed to the method of claim 1, wherein the set of genomic DNA sequences comprised in the training data set is preselected from genomic DNA sequences whereof the methylation level is associable with chronological age.
Vilain discloses a method of obtaining information useful to determine an age of an individual by observing the methylation status of one or more specific GC loci [0044].
Claim 29 is directed to the method of claim 1, wherein the genomic DNA sequences comprised in the training data set are not overlapping with each other and/or only occur once per allele.
However, Vilain discloses obtaining methylation data for specific CG loci that is selected from 87 unique CG locus (p. 5. par. 046) which reads on an allele only occurring once in the training data.
Claim 32 is directed to the method of claim 1, wherein the age indicator comprises at least 30 or at least 50 or at least 60 or at least 80 genomic DNA sequences.
Vilain discloses in this high density, genome-wide screening of CpG methylation of twins, we identified 88 CpG sites near 80 genes for which the percent methylation in saliva is significantly correlated with age [0073].
Claim 33 is directed to the method of claim 1, wherein the age indicator comprises less than 300 or less than 150 or less than 110 or less than 100 or less than 90 genomic DNA sequences.
Vilain discloses in Some embodiments of the invention, cytosine methylation is observed in at least two genomic DNA sequences [0011]. As Vilain discloses a range of at least 2 sequences, it is considered that this range encompasses the instantly claimed range of less than 300.
Claim 34 is directed to the method of claim 1, wherein the DNA methylation levels of the genomic DNA sequences of an individual in the plurality of individuals were measured in a sample of biological material of said individual comprising said genomic DNA sequences.
Vilain discloses the invention comprise the steps of obtaining a biological sample derived from an individual comprising genomic DNA from white blood cells or epithelial cells; and then observing a pattern of cytosine methylation occurring on at least one genomic DNA sequence [0011].
Claim 35 is directed to the method of claim 34, wherein the sample comprises buccal cells.
However, Vilain discloses collecting saliva using Oragene DNA collection kits (p. 8, par. 0059) which reads on a sample of biological matter. Vilain further discloses the majority (up to 74%) of the DNA in saliva collected with this method comes from white blood cells, with the remainder being buccal epithelial cells (p. 8, par. 0059).
Claim 36 is directed to the method of claim 2, further comprising a step of obtaining a sample, wherein the sample is obtained non-invasively from the individual and a step of measuring the DNA methylation levels of the genomic DNA sequences in the sample.
However, Vilain discloses collecting saliva using Oragene DNA collection kits (p. 8, par. 0059) which reads on obtaining a sample non-invasively. Vilain further discloses buccal swabs but not mouthwash samples can be used to obtain pretransplant DNA fingerprints from recipients of allogeneic bone marrow transplants (p. 8, par. 0059) which reads on a noninvasive method for obtaining a sample.
Claim 37 is directed to the method of claim 34, wherein the DNA methylation levels were measured by methylation sequencing, bisulfate sequencing, a PCR method, high resolution melting analysis (HRM), methylation-sensitive single-nucleotide primer extension (MS-SnuPE), methylation-sensitive single-strand conformation analysis, methyl-sensitive cut counting (MSCC), base-specific cleavage/MALDI-TOF, combined bisulfate restriction analysis (COBRA), methylated DNA immunoprecipitation (MeDIP), micro array-based methods, bead array-based methods, pyrosequencing and/or direct sequencing without bisulfate treatment (nanopore technology).
Vilain discloses in this study we quantified the methylation status of 27,578 CpG loci covering more than 14,000 genes at single nucleotide resolution in saliva samples of 34 pairs of identical twins, between 21 and 55 years of age, using Illumina HumanMethylation27 microarrays [0063].
Claim 38 is directed to the method of claim 34, wherein the DNA methylation levels of genomic DNA sequences of an individual are measured by base-specific cleavage/MALDI-TOF and/or a PCR method or wherein the PCR method is methylation specific PCR.
However, Vilain discloses methylation was assayed using MassArray (p. 8, par. 0061) which includes a MALDI-TOF mass spectrometer as evidenced by Sequenom P. 2, par. 1).
Claim 39 is directed to the method of claim 34, wherein the DNA methylation levels of the genomic DNA sequences were determined in a sample of biological material comprising said genomic DNA sequences of the individual.
Vilain discloses in this study we quantified the methylation status of 27,578 CpG loci covering more than 14,000 genes at single nucleotide resolution in saliva samples of 34 pairs of identical twins, between 21 and 55 years of age, using Illumina HumanMethylation27 microarrays [0063].
Claim 73 is directed to a data carrier comprising the age indicator obtained by the method of claim 2.
Vilain discloses the invention, the genomic DNA is hybridized to a complimentary sequence (e.g. a synthetic polynucleotide sequence) that is coupled to a matrix (e.g. one disposed within a microarray) [0056] which read on a data carrier.
Claim Rejections - 35 USC § 103
The outstanding 103 rejection has been withdrawn in view of the amendments within. The prior art of Wang does not teach the limitations of applying stepwise regression to the reduced training data set.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
For the following rejections, instantly claimed elements which are considered to be equivalent to the prior art teachings are described in bold for all claims, and underlined text indicates newly recited portions necessitated by claim amendment.
A. Claim(s) 7, 11-12, 14-20, and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vilain et al. as applied to claims 1 and 2 as above, and in further view of Motyer et al. (Motyer, Allan J., et al. "LASSO model selection with post-processing for a genome-wide association study data set." BMC proceedings. Vol. 5. No. Suppl 9. London: BioMed Central, 2011,newly cited).
Claim 7 recites the method of claim [1], wherein the stepwise regression is a bidirectional elimination, wherein statistically insignificant independent variables are removed, wherein the significance level is 0.05.
Vilain discloses all subsequent analyses were performed on this value and for computational reasons, data were filtered by requiring mean methylation values between 0.05 and 0.95 and variance greater than 0 [0063]but is silent on stepwise regression.
However, Motyer discloses LASSO model selection with post-processing for a genome-wide association study data set [title]. Motyer further discloses in the first stage we carried out the LASSO procedure using the glmnet package [p. 1, col. 2,m par. 3]. Motyer also discloses the second stage involves performing a stepwise selection with the SNPs selected in the first stage and was performed with both the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) [p. 2, col. 1, par. 1]. Motyer further discloses this selection was carried out using the step function in R with the full model, including all SNPs from the first stage and the three non-SNP covariates used as the initial model in the stepwise search and covariates allowed to be both deleted from and subsequently added back into the model (i.e., the direction argument of the step function was set to “both”) [p. 2, col. 1, par. 1].
Claim 11 is directed to the method of any of claim 1 , further comprising iteratively updating the age indicator, wherein iteratively updating the age indicator comprises updated comprising adding the data of at least one further individual to the training data in each iteration, thereby iteratively expanding the training data set.
Vilain is silent on stepwise regression.
However, Motyer discloses LASSO model selection with post-processing for a genome-wide association study data set [title]. Motyer further discloses in the first stage we carried out the LASSO procedure using the glmnet package [p. 1, col. 2,m par. 3]. Motyer also discloses the second stage involves performing a stepwise selection with the SNPs selected in the first stage and was performed with both the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) [p. 2, col. 1, par. 1]. Motyer further discloses this selection was carried out using the step function in R with the full model, including all SNPs from the first stage and the three non-SNP covariates used as the initial model in the stepwise search and covariates allowed to be both deleted from and subsequently added back into the model (i.e., the direction argument of the step function was set to “both”) [p. 2, col. 1, par. 1], which reads on adding at least one further individual to the training data and iteratively updating the training dataset.
Claim 12 is directed to the method of claim 11, wherein in one updating round the added data of each further individual comprise the individual's DNA methylation levels of (i) at least 5% or 50% or 100% of the set of genomic DNA sequences comprised in the initial or any of the expanded training data sets, and/or (ii) the genomic DNA sequences contained in the reduced training data set.
Vilain is silent on updating round.
However, Motyer discloses taking 100 resamples and used the same l parameter as for the original data for each resample and calculating the resample model inclusion proportion (RMIP) for each SNP [p. 2, col. 1, par. 2] which reads on updating round the added data of each further individual comprise the individual's DNA methylation levels of (i) at least 5% or 50% or 100% of the set of genomic DNA sequences comprised in the initial or any of the expanded training data sets.
Claim 14 is directed to the method of claim 11, wherein in one updating rounds the set of genomic DNA sequences whereof the methylation levels are added is identical to the ensemble for each of the further individual(s).
Vilain is silent on updating round.
However, Motyer discloses taking 100 resamples and used the same l parameter as for the original data for each resample and calculating the resample model inclusion proportion (RMIP) for each SNP [p. 2, col. 1, par. 2] which reads on the set of genomic DNA sequences whereof the methylation levels are added is identical to the ensemble for each of the further individual(s).
Claim 15 is directed to the method of claim 11, wherein one updating round comprises applying the LASSO on the expanded training data set, thereby determining an updated age indicator and/or an updated reduced training data set.
Vilain is silent on updating round.
However, Motyer discloses taking 100 resamples and used the same l parameter as for the original data for each resample and calculating the resample model inclusion proportion (RMIP) for each SNP [p. 2, col. 1, par. 2] which reads on determining an updated age indicator and/or an updated reduced training data set.
Claim 16 is directed to the method of claim 11, wherein the training data set to which the data of the at least one further individual are added is the reduced training data set, which can be the initial or any of the updated reduced training data sets.
Vilain is silent on stepwise regression.
However, Motyer discloses this selection was carried out using the step function in R with the full model, including all SNPs from the first stage and the three non-SNP covariates used as the initial model in the stepwise search and covariates allowed to be both deleted from and subsequently added back into the model (i.e., the direction argument of the step function was set to “both”) [p. 2, col. 1, par. 1], which reads on individual are added is the reduced training data set, which can be the initial or any of the updated reduced training data sets.
Claim 17 is directed to the method of claim 16, wherein the reduced training data set is the previous reduced training data set in the iteration.
Vilain is silent on stepwise regression.
However, Motyer discloses this selection was carried out using the step function in R with the full model, including all SNPs from the first stage and the three non-SNP covariates used as the initial model in the stepwise search and covariates allowed to be both deleted from and subsequently added back into the model (i.e., the direction argument of the step function was set to “both”) [p. 2, col. 1, par. 1], which reads on the reduced training data set is the previous reduced training data set in the iteration.
Claim 18 is directed to the method of claim 11, wherein one updating round comprises applying a stepwise regression on the reduced training data set thereby determining an updated age indicator.
Vilain is silent on stepwise regression.
However, Motyer discloses LASSO model selection with post-processing for a genome-wide association study data set [title]. Motyer further discloses in the first stage we carried out the LASSO procedure using the glmnet package [p. 1, col. 2,m par. 3]. Motyer also discloses the second stage involves performing a stepwise selection with the SNPs selected in the first stage and was performed with both the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) [p. 2, col. 1, par. 1]. Motyer further discloses this selection was carried out using the step function in R with the full model, including all SNPs from the first stage and the three non-SNP covariates used as the initial model in the stepwise search and covariates allowed to be both deleted from and subsequently added back into the model (i.e., the direction argument of the step function was set to “both”) [p. 2, col. 1, par. 1].
Claim 19 is directed to the method of claim 11, wherein in one updating round, the data of at least one individual is removed from the training data set and/or the reduced training data set.
Vilain discloses a leave-one-out analysis forms an accurate epigenetic predictor of age [0071]. Vilain further discloses to provide an unbiased estimate of predictive accuracy for age, we used a leave-one-out analysis where the multivariate regression model was fit on all but one subject and its prediction was related to the truly observed age of the left-out subject [0071] which reads on the quality of the age indicator by statistical evaluation. Vilain also discloses illustrative age prediction analyses models were also designed and tested, for example using a leave-one out analysis, where one subject from the model is systematically removed and the model is used to predict the subjects age [0042].
Claim 20 is directed to the method of claim 19, wherein the addition and/or removal of the data of an individual depends on at least one characteristic of the individual, wherein the characteristic is the ethnos, the sex, the chronological age, the domicile, the birth place, at least one disease and/or at least one life style factor, wherein the life style factor is selected from drug consumption, exposure to an environmental pollutant, shift work or stress.
Vilain is silent on individual depends on at least one characteristic of the individual.
However, Motyer discloses the tuning parameter l was determined using a 10-fold cross-validation (CV) along with the non-SNP covariates (Sex, Age, and Smoke) were included as unpenalized terms [p. 1, col. 2, par. 3].
Claim 24 is directed to the method of claim 11, wherein an age of the one further individual is determined based on its DNA methylation levels and the updated age indicator.
Vilain is silent on stepwise regression.
However, Motyer discloses LASSO model selection with post-processing for a genome-wide association study data set [title]. Motyer further discloses in the first stage we carried out the LASSO procedure using the glmnet package [p. 1, col. 2,m par. 3]. Motyer also discloses the second stage involves performing a stepwise selection with the SNPs selected in the first stage and was performed with both the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) [p. 2, col. 1, par. 1]. Motyer further discloses this selection was carried out using the step function in R with the full model, including all SNPs from the first stage and the three non-SNP covariates used as the initial model in the stepwise search and covariates allowed to be both deleted from and subsequently added back into the model (i.e., the direction argument of the step function was set to “both”) [p. 2, col. 1, par. 1].
In regards to claim(s) 7, 11-12, 14-20, and 24 , it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, Vilain with Motyer as they both are directed to using LASSO model selection with for a genome-wide association study. Prior art of Vilain discloses the training data set was comprised of paired methylation, transcription and clinical data, which included the age of the individual where Motyer discloses using LASSO model selection with post-processing for a genome-wide association study. Thus, it would have been obvious to one of ordinary skill in the art to combine the LASSO of Vilain with the LASSO/Stepwise combination of Motyer, finding that one of ordinary skill in the art could have substituted one known element for another, and the results of the substitution would have been predictable.
B. Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Vilain as applied to claims 1-2 as above, and in further view of Zeng et al. (Zeng, Wang, Peter, and Breheny Package “biglasso” version 1.3-6, (05/04/2017), previously cited, henceforth biglasso).
Claim 10 is directed to the method of claim 1, wherein the LASSO has an L1 regularization parameter/alpha parameter of 1.
Vilain discloses the use of Lasso, but is silent on the regularization parameter being 1.
However, the biglasso documentation discloses alpha being the elastic-net mixing parameter that controls the relative contribution from the lasso (p.6, par. 4). The penalty is defined as alpha=1 for the lasso penalty (p. 6, par. 4).
Regarding claim 10, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, Vilain with Zeng as they disclose the use of the Lasso method. The prior art of Vilain had explicitly suggested the Lasso method described for regression analysis. Zeng discloses the software package instructions for using the known application biglasso in R. Thus, it would have been obvious to one of ordinary skill in the art to replace the Lasso method with another Lasso method known for penalized regression for big data, because one of ordinary skill in the art would have been able to carry out such a substitution, and the results were reasonably predictable.
C. Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Vilain in view of Motyer as applied to claim 11 as above, and in further view of Zhang et al. (WO 2018/009696 Al, published 01/11/2018, newly cited).
Claim 13 is directed to the method of claim 11, wherein all genomic DNA sequences (independent variables) which are not present for all individuals who contribute data to the expanded training data set are removed from the expanded training data set.
Vilain is silent on stepwise regression. Motyer discloses LASSO model selection with post-processing for a genome-wide association study data set [title]. Vilain and Motyer are silent on all genomic DNA sequences (independent variables) which are not present for all individuals who contribute data to the expanded training data set are removed from the expanded training data set.
However, Zhang discloses multinomial classification, least absolute shrinkage and selection operator (LASSO) was used under multinomial distribution [0211]. Zhang further discloses for LASSO and elastic net, the tuning parameters (λ for LASSO and λ, α for elastic net) were determined according to the expected generalization error estimated from IO-fold cross-validation and information-based criteria AIC/BIC [0225]. Zhang also discloses the data were further modified by removal of 1) negative and 0 survival time; or 2) missing value in any of the four clinical and demographic covariates; to generate 365 colon cancer samples with 53 events (the event of interest was defined as death) for subsequent diagnostic analysis [0217].
Regarding claim 13, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, Vilain with Zhang as they disclose the use of the Lasso method for genome-wide association study. The prior art of Vilain had explicitly suggested the Lasso method described for regression analysis. Zhang discloses filtering the genomic data to remove data with missing values. Thus, it would have been obvious to one of ordinary skill in the art to combine the Lasso method of Vilain with another Lasso filtering method of Zhang to provide finite sample error control and improve stability of variable selection as disclosed by Zhang [0224], because one of ordinary skill in the art would have been able to carry out such a substitution, and the results were reasonably predictable.
D. Claim 26 is rejected under 35 U.S.C. 103 as being unpatentable over Vilain as applied to claim 1 as above, and in further view of Tibshirani et al. (Tibshirani, Robert. "Regression shrinkage and selection via the lasso." Journal of the Royal Statistical Society Series B: Statistical Methodology 58.1 (1996), previously cited).
Claim 26 is directed to the method of claim 1, wherein the age indicator is not further updated when the number of individuals comprised in the data has reached a predetermined value and/or a predetermined time has elapsed since a previous update.
The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent is not met. If the claimed invention may be practiced without either the first or second condition happening, then neither step A or B is required by the broadest reasonable interpretation of the claim (MPEP 211.04).
In interest of compact prosecution Vilain is silent on a predetermined value.
However, Tibshirani discloses the lasso method for variable selection in the cox model (title). Tibshirani further discloses the procedure of repeating steps until the estimate of that parameter value does not change (p. 2, par. 6) which reads on a predetermined value.
In regards to claim 26, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, Vilain with Tibshirani as they disclose the use of Lasso regression. The motivation would have been to improve accuracy of a regression model by using a predetermined value as disclosed by Tibshirani (summary).
E. Claims 75-77 are rejected under 35 U.S.C. 103 as being unpatentable over Vilain as applied to claims 1 and 2 as above, and in further view of Brenner et al. (US PGPub 2020/0056234A1, 2020, previously cited).
Claim 75 is directed to the method of claim 1, wherein the training data set or reduced training data set further comprise at least one factor relating to a life-style or risk pattern of each individual in the plurality of individuals.
Wang is silent on lifestyle or risk pattern.
However, Brenner discloses the validation phase, in which the associations with mortality were further analyzed by multiple Cox regression adjusted for age, sex, batch effects, leukocyte composition, smoking status (never, former, and current smoker), body mass index (BMI, kg/m2), physical activity (inactive, low, medium/ high), alcohol consumption (g per day), systolic blood pressure (mmHg), total cholesterol level (mg/dL), and prevalence of hypertension, CVD, diabetes, and cancer (p.8, par. 0085) which reads on a life-style and risk pattern.
Claim 76 is directed to the method of claim 75, wherein the factor is selected from drug consumption, environmental pollutants, shift work and stress.
Vilain is silent on lifestyle or risk pattern.
However, Brenner discloses the validation phase, in which the associations with mortality were further analyzed by multiple Cox regression adjusted for alcohol consumption (p.8, par. 0085) which reads on a life-style factor of drug consumption.
Claim 77 is directed to the method of claim 75, wherein the training data set and/or the reduced training data set is restricted to sequences whereof the DNA methylation level and/or the activity/level of encoded proteins is associated with at least one of the life-style factors.
Vilain is silent on the DNA methylation level and/or the activity/level of an encoded proteins is associated with at least one of the life-style factors
However, Brenner discloses a validation panel reduces the training set with lifestyle factors (p. 2, Fig. 1). Brenner further discloses risk factors related to methylation associated with fatal endpoints, sociodemographic characteristics, lifestyle factors, and prevalent diseases at baseline were assessed in relation to the methylation levels of the identified CpGs using mixed linear regression models in the validation panel, with batch as random effect, methylation ~-value as the dependent variable, and independent variables including age, sex, smoking status (never, former, and current smoker), BMI (underweight/normal weight, overweight, and obesity), physical activity (inactive, low, medium/high), alcohol consumption (g per day), and prevalent hypertension, diabetes, CVD, and cancer, again controlling for leukocyte composition (p. 8, par. 0086) which reads on sequences whereof the DNA methylation level associated with at least one of the life-style factors.
Regarding claims 75-77, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, Vilain and Brenner as they disclose predictions with DNA methylation. The motivation would have been to include relating to a life-style or risk patterns of Brenner with the age indicator of Vilain for improved DNA markers as disclosed by Brenner (p. 1, par. 0004), a finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
F. Claim 78 is rejected under 35 U.S.C. 103 as being unpatentable over Vilain in view of Brenner as cited above for claim 75, further in view of Lind et al. (Lind, P. Monica, Samira Salihovic, and Lars Lind. "High plasma organochlorine pesticide levels are related to increased biological age as calculated by DNA methylation analysis." Environment international 113 (2018), previously cited).
Claim 78 is directed to the method of claim 75, further comprising a step of determining at least one life-style factor which is associated with the difference between the determined and the chronological age of said individual.
Vilain is silent on one life-style factor which is associated with the difference between the determined and the chronological age of said individual.
However, Brenner discloses lifestyle risk factors(p.8, par. 0085). Vilain and Brenner are silent on using lifestyle factor associated with a difference between chronological age and predicted age.
However, Lind discloses high organochlorine pesticide levels are related to increased biological age as calculated by DNA methylation analysis (title). Lind further discloses lifestyle variable of alcohol intake and the difference between the chronological age and predicted age (p. 111, Table 1).
In regards to claim 78, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, Vilain and Brenner with Lind as they disclose DNA methylation analysis. The motivation would have been to combine the lifestyle risk factors of Brenner to the model of Vilain to improve the determining a DNA methylation status as disclosed by Lind (p. 112, col. 2, par. 3), a finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
G. Claims 94-96 is rejected under 35 U.S.C. 103 as being unpatentable over Vilain in view of Brenner as cited above for claim 27, further in view of Lo et al. (US20100112590 A1, published, newly cited).
Claim 94 is directed to the method of claim 27, wherein the preselected set comprises at least 400000 or at least 800000 genomic DNA sequences.
Vilain is silent on preselected set comprises at least 400000 or at least 800000 genomic DNA sequences.
However, Lo discloses the number of sequences in the subsets was varied from 60,000 to 540,000 sequences [0179].
Claim 95 is directed to the method of claim 1, wherein the set of genomic DNA sequences comprises at least 850,000 genomic DNA sequences.
Vilain is silent on the set of genomic DNA sequences comprises at least 850,000 genomic DNA sequences.
However, Lo discloses subsets of sequences were randomly chosen from these 1,990,000 tags and the percentage of sequences aligned to chromosome 21 was calculated within each subset.
Claim 96 is directed to the method of claim 2, wherein the set of genomic DNA sequences comprises at least 850,000 genomic DNA sequences.
Vilain is silent on the set of genomic DNA sequences comprises at least 850,000 genomic DNA sequences.
However, Lo discloses subsets of sequences were randomly chosen from these 1,990,000 tags and the percentage of sequences aligned to chromosome 21 was calculated within each subset.
In regards to claims 94-96, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, Vilain and Brenner with Lo as they disclose determining whether a fetal chromosomal aneuploidy exists from a biological sample obtained from a pregnant female. The motivation would have been to combine the parameters of Lo to the model of Vilain to improve the determining a DNA methylation status by nucleic acid molecules of the biological sample as they are sequenced such that a fraction of the genome is sequenced as disclosed by Lo [Abstract], a finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Conclusion
No claims are allowed.
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/D.M.B./ Examiner, Art Unit 1685
/Soren Harward/Primary Examiner, TC 1600