WO2018146482A1 - Nouveau procédé de calcul d'âge - Google Patents

Nouveau procédé de calcul d'âge Download PDF

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Publication number
WO2018146482A1
WO2018146482A1 PCT/GB2018/050362 GB2018050362W WO2018146482A1 WO 2018146482 A1 WO2018146482 A1 WO 2018146482A1 GB 2018050362 W GB2018050362 W GB 2018050362W WO 2018146482 A1 WO2018146482 A1 WO 2018146482A1
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cpg sites
age
homolog
methylation
sites listed
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PCT/GB2018/050362
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English (en)
Inventor
Thomas STUBBS
Marc Jan BONDER
Oliver STEGLE
Wolf Reik
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Babraham Institute
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Priority claimed from GBGB1702163.5A external-priority patent/GB201702163D0/en
Priority claimed from GBGB1704463.7A external-priority patent/GB201704463D0/en
Application filed by Babraham Institute filed Critical Babraham Institute
Publication of WO2018146482A1 publication Critical patent/WO2018146482A1/fr

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material

Definitions

  • the invention relates to a novel method for calculating the age of a biological sample obtained from a subject, in particular a mouse.
  • the invention also relates to ageing biomarkers, a kit comprising biosensors capable of detecting said biomarkers, a method of assessing the effect of a biological intervention upon the age of a subject and a method of screening for an anti- ageing agent.
  • Ageing describes the progressive decline in cellular, tissue and organismal function during life, which ultimately drives age-related diseases and limits lifespan [1]. From a biological perspective, ageing is associated with numerous changes at the cellular and molecular level [2], including epigenetic changes, that is modifications of DNA or chromatin that do not change the primary nucleotide sequence. At present it is not clear which epigenetic changes are causative or correlative, but these mechanisms are of particular interest due to their reversibility, suggesting that rejuvenation might be possible at least in principle [3,4].
  • WO 2015/048665 describes a method for determining the age of a biological sample comprising measuring a methylation level of a set of methylation markers in genomic DNA of the biological sample.
  • a method of calculating the age of a biological sample obtained from a mouse which comprises the steps of:
  • step (c) comparing the methylation profile identified in step (b) with a methylation profile obtained for a control data set by analysis of the methylation values of a plurality of samples of differing ages.
  • a method of calculating the age of a biological sample obtained from a subject which comprises the steps of:
  • step (c) comparing the methylation profile identified in step (b) with a methylation profile obtained for a control data set by analysis of the methylation values of a plurality of samples of differing ages.
  • biomarkers comprising CpG sites within any of the murine CpG sites listed in Table 3 or 4 or a homolog thereof as an ageing biomarker.
  • a kit comprising one or more biosensors capable of detecting the methylation status of CpG sites within any of the murine CpG sites listed in Table 3 or 4 or a homolog thereof.
  • a method of assessing the effect of a biological intervention upon the age of a subject which comprises the following steps:
  • step (c) repeating the method of step (a) on a subsequent biological sample obtained from said subject to identify whether said biological intervention has had an effect upon the age of said subject.
  • step (c) repeating the method of step (a) to identify whether a reduction in age has been calculated.
  • an anti-ageing agent identified by the method of screening defined herein.
  • a method of treating a subject suffering from a premature ageing disorder which comprises administering to said subject an anti-ageing agent as defined herein.
  • A Overview of the Babraham dataset. Tissues (liver, lung, heart and cortex) were isolated from mice at 4 distinct time points (newborn, 14 weeks, 27 weeks and 41 weeks). DNA was isolated from these tissues and reduced-representation bisulfite (RRBS) libraries made.
  • B Heatmap of the top 500 tissue independent age-associated correlations. Highlighted are ages and tissues, CG sites were clustered by Euclidean distance.
  • C Single CG sites within the genome are correlated with age. Shown is an example site: chr2:37758496, with a pearson correlation with age of 0.75. Tissues are highlighted by colour. Jitter is for aesthetic purposes only.
  • H Tissue-specific correlations with age.
  • An example is provided of a tissue-specific correlation with age in cortex, liver, lung and heart. Correlations for these CG sites are provided for all tissues combined and for the tissue in question. Jitter is for aesthetic purposes only.
  • Figure 2 Prediction of chronological age from a mouse epigenetic clock
  • (A) Flow-chart to illustrate the steps taken in defining the model and testing it.
  • Datasets are displayed as segments of a circle. They are coloured to correspond with later figures, namely: Reizel in brown (R), Cannon in green (C), Babraham in purple (B), Zhang in pink (Z) and Schillebeeckx in light green (S).
  • the two independent datasets are displayed as segments in a separate circle to those datasets utilised for the training phase.
  • the flow of methylation data is shown as colour-coded lines.
  • Training occurs at the node (screen) with the caption: "model maker”.
  • the chosen CG sites and their corresponding weighting are passed on to the prediction tool itself (node with the caption: "epigenetic age predictor”. Test data enters this prediction tool and age predictions are outputted, as displayed by the pocket watches exiting this node.
  • the clock sites within the heatmap are clustered on Euclidean distance and the samples are ordered principally by age but followed by tissue, dataset and sex.
  • (D) Mean absolute error (MAE) of the model as depicted per age group, young (defined as below 20 weeks of age) and old (defined as 20 weeks of age or older) in the test data and training data.
  • the training data is shown in the background in grey.
  • (A) Flow-chart to illustrate the steps taken in defining the model and testing it.
  • Datasets are displayed as segments of a circle. They are coloured to correspond with later figures, namely: Reizel in brown (R), Cannon in green (C), Babraham in purple (B), Zhang in pink (Z) and Schillebeeckx in light green (S).
  • the two independent datasets are displayed as segments in a separate circle to those datasets utilised for the training phase.
  • the flow of methylation data is shown as colour-coded lines.
  • Training occurs at the node (screen) with the caption: "glmnet”.
  • the chosen CG sites and their corresponding weighting are passed on to the prediction tool itself (node with the caption: "epigenetic age predictor”. Test data enters this prediction tool and age predictions are outputted, as displayed by the pocket watches exiting this node.
  • a method of calculating the age of a biological sample obtained from a mouse which comprises the steps of:
  • step (b) identifying a methylation profile for said sample which comprises measuring the methylation status of CpG sites within any of the CpG sites listed in Table 3 or 4; and (c) comparing the methylation profile identified in step (b) with a methylation profile obtained for a control data set by analysis of the methylation values of a plurality of samples of differing ages.
  • the inventors have generated high-resolution methylomes from the experimentally tractable mouse across a wide range of tissues and ages.
  • the inventors have found that discrete DNA methylation changes correlate with chronological age and are associated with biological functions. Based on these findings, the inventors generated a highly accurate multi-tissue age predictor for the mouse, characterized its properties, and demonstrated that it can be applied to inform other studies by applying it to various publicly available datasets, including key biological interventions.
  • an age calculation method for a mouse subject provides great utility as a screening model.
  • the average lifespan of a mouse is approx. 2-4 years compared with approx. 80 years for a human. Therefore, an accurate mouse age calculation method is difficult to provide because the accuracy values correspond to much higher values when normalised to a value equivalent to a human. For example, an accuracy value of ⁇ 6 months in a mouse is equivalent to ⁇ 20 years in a human which provides a significant hurdle when attempting to ascertain the impact of biological intervention upon a mouse.
  • the age calculation method of the invention using the CpG sites listed in Table 3 provides an accuracy value of 4.09 weeks (see Study 1 and Figure 2E) which is equivalent to just 3.6 years in a human.
  • mice age calculation method of the invention provides a highly sensitive, accurate and reproducible ageing model. Such a model finds great utility in identifying agents and moieties which have either a positive or negative effect upon ageing. It will be appreciated that the age of the test individual is calculated based on the age of the biological sample being analysed.
  • CpG refers to regions of DNA where a cytosine nucleotide is followed by a guanine nucleotide in the linear sequence of bases along a 5' to 3' direction.
  • CpG is shorthand for 5'-C-phosphate-G-3', i.e., cytosine and guanine separated by a single phosphate group.
  • step (b) comprises measuring the methylation status of any of the CpG sites listed in Table 3.
  • the ageing model defined herein made use of all 644 CpG sites listed in Table 3 it will be appreciated that a smaller subset of the sites may be used to provide an equally effective ageing model.
  • step (b) comprises measuring the methylation status of at least 5, 10, 25, 50, 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3.
  • step (b) comprises measuring the methylation status of at least 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3. In a yet further embodiment, step (b) comprises measuring the methylation status of all of the 644 CpG sites listed in Table 3.
  • step (b) comprises measuring the methylation status of any of the CpG sites listed in Table 4.
  • step (b) comprises measuring the methylation status of at least 5, 10, 25, 50, 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4.
  • step (b) comprises measuring the methylation status of at least 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4.
  • step (b) comprises measuring the methylation status of all of the 329 CpG sites listed in Table 4.
  • the age calculation method of the invention may also find utility in other organisms which have homologs of the CpG sites listed in Tables 3 and 4.
  • a method of calculating the age of a biological sample obtained from a subject which comprises the steps of:
  • step (c) comparing the methylation profile identified in step (b) with a methylation profile obtained for a control data set by analysis of the methylation values of a plurality of samples of differing ages.
  • step (b) comprises measuring the methylation status of any of the CpG sites listed in Table 3 or a homolog thereof.
  • step (b) comprises measuring the methylation status of at least 5, 10, 25, 50, 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3 or a homolog thereof.
  • step (b) comprises measuring the methylation status of at least 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3 or a homolog thereof. In a yet further embodiment, step (b) comprises measuring the methylation status of all of the 644 CpG sites listed in Table 3 or a homolog thereof.
  • step (b) comprises measuring the methylation status of any of the CpG sites listed in Table 4 or a homolog thereof.
  • step (b) comprises measuring the methylation status of at least 5, 10, 25, 50, 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4.
  • step (b) comprises measuring the methylation status of at least 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4.
  • step (b) comprises measuring the methylation status of all of the 329 CpG sites listed in Table 4.
  • measuring the methylation status of CpG sites in step (b) of the first and second aspects of the invention may be conducted in accordance with general methodology known to the person skilled in the art.
  • such measurement can be conducted in accordance with the methods described herein in the Materials and Methods section.
  • methodology is also described in WO
  • the measurement of methylation comprises treatment of genomic DNA from the biological sample with bisuflite to convert unmethylated cytosines of CpG
  • the measuring step (b) comprises measurement of the mean methylation level of each CG site calculated using the Bismark methodology [35], such as by using Bismark coverage files, as described herein.
  • the comparing step (c) may be conducted in accordance with general statistical comparison methodology known to the person skilled in the art. In particular, it is noted that such comparing can be conducted in accordance with the methods described herein in the Materials and Methods section.
  • the comparing step (c) comprises use of a linear regression model or an elastic-net generalized linear model as implemented in the GLMNET package [32].
  • the comparing step (c) comprises use of an elastic-net generalized linear model as implemented in the GLMNET package [32].
  • control data set referred to in step (c) is also known as preparation of a training data set (as opposed to the test data set from a test subject).
  • a control data set or training data set is typically conducted by analysing the methylation values of the CpG sites defined herein on a plurality of samples of differing ages.
  • Such a training data set may be prepared in accordance with general methodology known to the person skilled in the art, in particular using the methodology described herein in the
  • the biological sample is selected from whole blood, blood serum, plasma, cerebrospinal fluid (CSF), urine, saliva, or other bodily fluid (stool, tear fluid, synovial fluid, sputum), breath, e.g. as condensed breath, or an extract or purification there from, or dilution thereof.
  • Biological samples also include tissue homogenates, tissue sections and biopsy specimens from a live subject, or taken post-mortem. The samples can be prepared, for example where appropriate diluted or concentrated, and stored in the usual manner. It will be understood that the methods of the invention may be performed in vitro.
  • the biological sample is whole blood, blood serum, plasma or saliva, such as blood serum or saliva, in particular blood serum.
  • biomarkers comprising CpG sites within any of the murine CpG sites listed in Table 3 or a homolog thereof as an ageing biomarker.
  • the one or more biomarkers comprise any of the CpG sites listed in Table 3 or a homolog thereof.
  • the one or more biomarkers comprise at least 5, 10, 25, 50, 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3 or a homolog thereof. In a further embodiment, the one or more biomarkers comprise at least 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3 or a homolog thereof. In a yet further embodiment, the one or more biomarkers comprise all of the 644 CpG sites listed in Table 3 or a homolog thereof.
  • biomarkers comprising CpG sites within any of the murine CpG sites listed in Table 4 or a homolog thereof as an ageing biomarker.
  • the one or more biomarkers comprise any of the CpG sites listed in Table 4 or a homolog thereof.
  • the one or more biomarkers comprise at least 5, 10, 25, 50, 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4 or a homolog thereof. In a further embodiment, the one or more biomarkers comprise at least 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4 or a homolog thereof. In a yet further embodiment, the one or more biomarkers comprise all of the 329 CpG sites listed in Table 4 or a homolog thereof.
  • biomarker means a distinctive biological or biologically derived indicator of a process, event, or condition. Biomarkers can be used in methods of diagnosis, e.g. clinical screening, and prognosis assessment and in monitoring the results of therapy, identifying patients most likely to respond to a particular therapeutic treatment, drug screening and development. Biomarkers and uses thereof are valuable for identification of new drug treatments and for discovery of new targets for drug treatment.
  • kits comprising one or more biosensors capable of detecting the methylation status of CpG sites within any of the murine CpG sites listed in Table 3 or 4 or a homolog thereof.
  • the kit comprises one or more biosensors capable of detecting the methylation status of any of the CpG sites listed in Table 3 or a homolog thereof.
  • the kit comprises one or more biosensors capable of detecting the methylation status of at least 5, 10, 25, 50, 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3 or a homolog thereof.
  • the kit comprises one or more biosensors capable of detecting the methylation status of at least 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3 or a homolog thereof.
  • the kit comprises one or more biosensors capable of detecting all of the 644 CpG sites listed in Table 3 or a homolog thereof.
  • the kit comprises one or more biosensors capable of detecting the methylation status of any of the CpG sites listed in Table 4 or a homolog thereof.
  • the kit comprises one or more biosensors capable of detecting the methylation status of at least 5, 10, 25, 50, 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4 or a homolog thereof. In a yet further embodiment, the kit comprises one or more biosensors capable of detecting the methylation status of at least 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4 or a homolog thereof. In a yet further embodiment, the kit comprises one or more biosensors capable of detecting all of the 329 CpG sites listed in Table 4 or a homolog thereof.
  • the kit additionally comprises one or more components selected from the group: a ligand specific for the biomarker, one or more controls, one or more reagents and one or more consumables; optionally together with instructions for use of the kit in accordance with any of the methods defined herein.
  • biosensor means anything capable of detecting the presence of the biomarker. Examples of biosensors are described herein. Biosensors according to the invention may comprise a ligand or ligands capable of specific binding to the biomarker. Such biosensors are useful in detecting and/or measuring a biomarker of the invention.
  • the biomarker may be detected and/or measured using enrichment methods, mass readout or base calling methods.
  • the enrichment method is selected from:
  • Antibody-based enbrichment methods such as pulling down of methyl-cytosine in a specific context
  • Size selection-based enrichment methods such as upon digestion with specific or non-specific restriction enzymes
  • the mass readout method is selected from mass spectrometry based approaches for detection of methylation levels for specific CG sites by their mass
  • the base calling method is selected from lllumina sequencing based approaches for detection of methylation levels using DNA libraries that have undergone some form of DNA modification, such as bisulfite treatment (converting cytosine to uracil - read as Thymine, while leaving methylated cytosine unaltered). This can be achieved in a number of different methods:
  • ⁇ Amplicon sequencing - Specific primers are designed such that the methylation state at a given site can be determined.
  • Additional base calling approaches could be used for the detection of cytosine modifications, such as pore methods where the base modification is detected by voltage differences across a channel occupied by a given base combination (Oxford Nanopore) such pores are not limited to biological pores (e.g. protein pores vs grapheme pores). Approaches based on stalling of polymerases during polymerisation could be used, such as those utilised by Pacific Bioscience for the detection of methyl-adenine.
  • the biomarker may be directly detected, e.g. by SELDI or MALDI-TOF.
  • the biomarker may be detected directly or indirectly via interaction with a ligand or ligands such as an antibody or a biomarker-binding fragment thereof, or other peptide, or ligand, e.g. aptamer, or oligonucleotide, capable of specifically binding the biomarker.
  • the ligand may possess a detectable label, such as a luminescent, fluorescent or radioactive label, and/or an affinity tag.
  • detecting and/or measuring can be performed by one or more method(s) selected from the group consisting of: SELDI (-TOF), MALDI (-TOF), a 1-D gel-based analysis, a 2-D gel-based analysis, mass spectroscopy (MS) such as selected reaction monitoring (SRM), reverse phase (RP) LC, size permeation (gel filtration), ion exchange, affinity, HPLC, UPLC and other LC or LC MS-based techniques.
  • SRM selected reaction monitoring
  • RP reverse phase
  • LC MS techniques include ICAT® (Applied Biosystems, CA, USA), or iTRAQ® (Applied Biosystems, CA, USA).
  • Liquid chromatography e.g. high pressure liquid chromatography (HPLC) or low pressure liquid chromatography (LPLC)
  • thin-layer chromatography e.g. high pressure liquid chromatography (HPLC) or low pressure liquid chromatography (LPLC)
  • NMR nuclear magnetic resonance
  • the detecting and/or measuring is performed using mass spectroscopy (MS). In a further embodiment, the detecting and/or measuring is performed using selected reaction monitoring (SRM).
  • SRM is a method used in tandem mass spectrometry in which an ion of a particular mass is selected in the first stage of a tandem mass spectrometer and an ion product of a fragmentation reaction of the precursor ion is selected in the second mass spectrometer stage for detection.
  • Specific analyte panels can be developed for SRM matching the analytes on the biomarker panel. The analyte panels can quantitatively measure the protein analytes with high precision. This methodology has the advantage of allowing raw blood to be used instead of blood serum which minimizes the number intermediate processing steps.
  • Methods according to the invention may comprise analysing a sample of blood serum by SELDI-TOF or MALDI-TOF to detect the presence of the biomarker.
  • Detecting and/or measuring the biomarkers may be performed using an immunological method, involving an antibody, or a fragment thereof capable of specific binding to the biomarker.
  • Suitable immunological methods include sandwich immunoassays, such as sandwich ELISA, in which the detection of the biomarkers is performed using two antibodies which recognize different epitopes on a biomarker; radioimmunoassays (RIA), direct, indirect or competitive enzyme linked immunosorbent assays (ELISA), enzyme immunoassays (EIA), Fluorescence immunoassays (FIA), western blotting, immunoprecipitation and any particle- based immunoassay (e.g. using gold, silver, or latex particles, magnetic particles, or Q-dots).
  • Immunological methods may be performed, for example, in microtitre plate or strip format.
  • Immunological methods in accordance with the invention may be based, for example, on any of the following methods.
  • biomarker In immunonephelometry, the interaction of an antibody and target antigen on the biomarker results in the formation of immune complexes that are too small to precipitate. However, these complexes will scatter incident light and this can be measured using a nephelometer.
  • the antigen, i.e. biomarker, concentration can be determined within minutes of the reaction.
  • Radioimmunoassay (RIA) methods employ radioactive isotopes such as I 125 to label either the antigen or antibody.
  • the isotope used emits gamma rays, which are usually measured following removal of unbound (free) radiolabel.
  • the major advantages of RIA compared with other immunoassays, are higher sensitivity, easy signal detection, and well-established, rapid assays.
  • the major disadvantages are the health and safety risks posed by the use of radiation and the time and expense associated with maintaining a licensed radiation safety and disposal program. For this reason, RIA has been largely replaced in routine clinical laboratory practice by enzyme immunoassays.
  • EIA Enzyme immunoassays were developed as an alternative to radioimmunoassays (RIA). These methods use an enzyme to label either the antibody or target antigen. The sensitivity of EIA approaches that of RIA, without the danger posed by radioactive isotopes.
  • One of the most widely used EIA methods for detection is the enzyme-linked immunosorbent assay (ELISA). ELISA methods may use two antibodies one of which is specific for the target antigen and the other of which is coupled to an enzyme, addition of the substrate for the enzyme results in production of a chemiluminescent or fluorescent signal.
  • Fluorescent immunoassay refers to immunoassays which utilize a fluorescent label or an enzyme label which acts on the substrate to form a fluorescent product. Fluorescent measurements are inherently more sensitive than colorimetric (spectrophotometric) measurements. Therefore, FIA methods have greater analytical sensitivity than EIA methods, which employ absorbance (optical density) measurement.
  • Chemiluminescent immunoassays utilize a chemiluminescent label, which produces light when excited by chemical energy; the emissions are measured using a light detector.
  • Immunological methods according to the invention can thus be performed using well-known methods. Any direct (e.g., using a sensor chip) or indirect procedure may be used in the detection of the biomarker of the invention.
  • the Biotin-Avidin or Biotin-Streptavidin systems are generic labelling systems that can be adapted for use in immunological methods of the invention.
  • One binding partner hapten, antigen, ligand, aptamer, antibody, enzyme etc
  • biotin hapten, antigen, ligand, aptamer, antibody, enzyme etc
  • biotin hapten, antigen, ligand, aptamer, antibody, enzyme etc
  • avidin or streptavidin surface, e.g. well, bead, sensor etc
  • a biotinylated ligand e.g. antibody or aptamer
  • a biomarker of the invention may be immobilised on an avidin or streptavidin surface, the immobilised ligand may then be exposed to a sample containing or suspected of containing the biomarker in order to detect and/or quantify a biomarker of the invention. Detection and/or quantification of the immobilised antigen may then be performed by an immunological method as described herein.
  • antibody as used herein includes, but is not limited to: polyclonal, monoclonal, bispecific, humanised or chimeric antibodies, single chain antibodies, Fab fragments and F(ab')2 fragments, fragments produced by a Fab expression library, anti-idiotypic (anti-Id) antibodies and epitope-binding fragments of any of the above.
  • antibody as used herein also refers to immunoglobulin molecules and immunologically-active portions of immunoglobulin molecules, i.e., molecules that contain an antigen binding site that specifically binds an antigen.
  • the immunoglobulin molecules of the invention can be of any class (e.g., IgG, IgE, IgM, IgD and IgA) or subclass of immunoglobulin molecule.
  • biosensors can be developed, accordingly, in methods and uses of the invention, detecting and quantifying can be performed using a biosensor, microanalytical system, microengineered system, microseparation system, immunochromatography system or other suitable analytical devices.
  • the biosensor may incorporate an immunological method for detection of the biomarker, electrical, thermal, magnetic, optical (e.g. hologram) or acoustic technologies. Using such biosensors, it is possible to detect the target biomarker at the anticipated concentrations found in biological samples.
  • the biomarker of the invention can be detected using a biosensor incorporating technologies based on "smart” holograms, or high frequency acoustic systems, such systems are particularly amenable to "bar code” or array configurations.
  • a holographic image is stored in a thin polymer film that is sensitised to react specifically with the biomarker.
  • the biomarker reacts with the polymer leading to an alteration in the image displayed by the hologram.
  • the test result read-out can be a change in the optical brightness, image, colour and/or position of the image.
  • a sensor hologram can be read by eye, thus removing the need for detection equipment.
  • a simple colour sensor can be used to read the signal when quantitative measurements are required. Opacity or colour of the sample does not interfere with operation of the sensor.
  • the format of the sensor allows multiplexing for simultaneous detection of several substances.
  • biosensors for detection of the biomarker of the invention combine biomolecular recognition with appropriate means to convert detection of the presence, or quantitation, of the biomarker in the sample into a signal.
  • Biosensors can be adapted for "alternate site” diagnostic testing, e.g. in the ward, outpatients' department, surgery, home, field and workplace.
  • Biosensors to detect the biomarker of the invention include acoustic, plasmon resonance, holographic and microengineered sensors. Imprinted recognition elements, thin film transistor technology, magnetic acoustic resonator devices and other novel acousto-electrical systems may be employed in biosensors for detection of the biomarker of the invention.
  • kits as defined herein in any of the methods defined herein.
  • a method of assessing the effect of a biological intervention upon the age of a subject which comprises the following steps:
  • step (c) repeating the method of step (a) on a subsequent biological sample obtained from said subject to identify whether said biological intervention has had an effect upon the age of said subject.
  • the subject is selected from a mammal (i.e. a human) or a mouse. In a further embodiment, the subject is selected from a mouse.
  • the biological intervention is selected from one or more of: therapy, administration of a test substance, genetic manipulation such as overexpression of a gene or knock-out of a gene, dietary manipulation, metabolic manipulation, surgical manipulation (e.g. castration), social manipulation, behavioural manipulation, environmental
  • step (c) comprises assessing whether there is an increase or reduction in the age of the biological sample.
  • step (c) may be repeated on one or more occasions to assess the effect of the biological intervention upon age over a given time period.
  • the assessment would require comparison of the ageing effect compared to the actual time period which had elapsed since the initial sample was taken.
  • the time elapsed between taking samples from a subject undergoing assessment may be 3 days, 5 days, a week, two weeks, a month, 2 months, 3 months, 6 or 12 months.
  • Samples may be taken prior to and/or during and/or following a particular intervention (i.e. therapy or genetic manipulation). Samples can be taken at intervals over the remaining life, or a part thereof, of a subject.
  • anti-ageing refers to any agent, such as an inhibitor (i.e. competitive, non-competitive or un-competitive inhibitor) or antagonist (i.e. competitive, noncompetitive or un-competitive antagonist) capable of slowing or retarding the natural ageing process.
  • an anti-ageing agent identified by the method of screening defined herein.
  • a method of treating a subject suffering from a premature ageing disorder which comprises administering to said subject an anti-ageing agent as defined herein.
  • a premature ageing disorder refers to any disorder which is particularly prevalent in the elderly but when suffered by more youthful individuals can bring about premature ageing.
  • the premature ageing disorder is selected from: progeric disorders such as Hutchinson-Gilford progeria syndrome (HGPS), Werner syndrome, Bloom syndrome, Rothmund-Thomson syndrome, Cockayne syndrome or Xeroderma pigmentosum; disorders characterised by cognitive impairment, such as Alzheimer's disease or dementia; Parkinson's disease or cancer.
  • progeric disorders such as Hutchinson-Gilford progeria syndrome (HGPS), Werner syndrome, Bloom syndrome, Rothmund-Thomson syndrome, Cockayne syndrome or Xeroderma pigmentosum
  • disorders characterised by cognitive impairment such as Alzheimer's disease or dementia
  • Parkinson's disease or cancer According to a further aspect of the invention there is provided a computer-readable medium which comprises the training data set comprising the CpG sites within any of the murine CpG sites listed in Table 3 or 4 or a homolog thereof.
  • the computer-readable medium comprises a training data set comprising any of the CpG sites listed in Table 3 or a homolog thereof.
  • the computer-readable medium comprises the training data set comprising at least 5, 10, 25, 50, 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3 or a homolog thereof. In a yet further embodiment, the computer-readable medium comprises the training data set comprising at least 100, 150, 200, 250, 300, 350, 400, 450, 550, 600 or all of the 644 CpG sites listed in Table 3 or a homolog thereof. In a yet further embodiment, the computer-readable medium comprises the training data set comprising all of the 644 CpG sites listed in Table 3 or a homolog thereof.
  • the computer-readable medium comprises a training data set comprising any of the CpG sites listed in Table 4 or a homolog thereof.
  • the computer-readable medium comprises the training data set comprising at least 5, 10, 25, 50, 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4 or a homolog thereof. In a yet further embodiment, the computer-readable medium comprises the training data set comprising at least 100, 150, 200, 250, 300 or all of the 329 CpG sites listed in Table 4 or a homolog thereof. In a yet further embodiment, the computer- readable medium comprises the training data set comprising all of the 329 CpG sites listed in Table 4 or a homolog thereof. The following studies illustrate the invention.
  • RRBS libraries were prepared from isolated DNA following published protocols [34]. Briefly, RRBS libraries were prepared by Mspl digestion of 100-500ng genomic DNA, followed by end-repair and T-tailing using Klenow Exo- (Fermentas). Adapter ligation was performed overnight (homemade adapters) using T4 DNA Ligase (NEB), followed by a cleanup step using AMPure XP beads (Agencourt, 0.9x). Subsequently, libraries were bisulfite treated according to the manufactures instructions (Sigma Imprint Kit; 2 step protocol) and purified using an automated liquid handling robotic system (Agilent Bravo).
  • the libraries were amplified using KAPA HiFi Uracil HotStart DNA Polymerase (KAPA Biosystems), indexing the samples with individual primers. All amplified libraries were purified (AMPure XP beads, 0.8x) and assessed for quality and quantity using High-Sensitivity DNA chips on the Agilent Bioanalyzer. High-throughput sequencing of all libraries was carried out with a 75 bp paired- end protocol on a HiSeq 2000 instrument (lllumina).
  • the mapped sequences were deduplicated by chromosomal position as well as the UMI sequences of both Read 1 and Read 2 (no mismatches tolerated) using the tool UmiBam (https://Qithub.com/FeiixKrueger/Umi-Grinder; vO.0.1 ; options: -bam ⁇ dual_umi).
  • UmiBam https://Qithub.com/FeiixKrueger/Umi-Grinder; vO.0.1 ; options: -bam ⁇ dual_umi.
  • Neighbouring genes were defined for single CG sites that were within 2kb of a gene. GO terms were defined using the gprofiler online software [37]. A background gene list was determined for each of the GO analyses. This list consisted of the neighbouring genes (max distance of 2kb) for all sites considered in that analysis. Tissue independent GO terms were filtered for terms that contained at least 1500 genes and the top 5 GO terms visualised. Tissue dependent GO terms were filtered for at least 150 In addition, GO terms for the tissue-specific correlations were filtered for at least 100 overlapping genes and the top 10 selected. Predicting age in mice
  • the Reizel study consists of 173 samples originating from four different tissues: Liver, Muscle, Cerebellum and Spleen and data was collected at six time points ranging from 1 to 31 weeks.
  • gender and tissue specificity of demethylation during ageing has been studied.
  • a perturbation based on castration and restoring testosterone levels after castration has been performed.
  • the perturbations were not taken into the training, these were left for the test-set. Further information can be found in Table 1. After QC there were 143 samples left.
  • the Zhang study consists of 4 samples all originating from liver at the age between 6 and 8 weeks. In the original study methylation differences between different strains of mice, and the difference between mouse and zebrafish DNA-methylation levels are assessed. In our study these samples were used as a validation to see how the predictor works for an unobserved time-point. The age of these mice has been set to 7 weeks in our study. Further information can be found in Table 1. After QC there were 4 samples left. Schillebeeckx ⁇ 311
  • the Schillebeeckx study consists of 23 samples all originating from the liver, the adrenal gland and from endometrial cancer at the age of 4 to 6 weeks.
  • a laser capture microdissection RRBS method is introduced.
  • the 1 1 liver samples after QC there were 5 samples left.
  • these samples were used as a validation to see how the predictor works for an unobserved time-point.
  • the age of these mice has been set to 5 weeks in our study. Further information can be found in Table 1.
  • the predictor we used the elastic-net generalized linear model as implemented in the GLMNET package [32]. To optimize the alpha, defining the elastic net mixing parameter (1 for lasso to 0 for ridge) and to optimize the lambda, the regularization parameter, we used a double-loop cross-validation set-up. This setup is described in Ronde et al. [38]. We have trained the model to predict the log transformed mouse age (in weeks); 3 weeks were added before the log transforming the ages, to be able to predict samples pre-birth. For the training set we selected 129 healthy samples from the Babraham, Reizel and
  • x is the summed beta score per sample.
  • liver, lung, heart, and brain (cortex) samples from newborn to 41 week-old mice ( Figure 1A).
  • Figure 1A To reduce genetic variability and hormonal variations, we restricted our cohort to male C57BL/6-BABR mice and sampled 3-5 animals per time point. In total we collected 62 samples (Table 1) and extracted genomic DNA for methylation analysis from them.
  • RRBS Reduced Representation Bisulphite Sequencing
  • DNA methylation levels at a discrete set of CpGs are predictive of age
  • this error rate is equivalent to that reported for the human DNA methylation clock (3.6 years median absolute error) [6], assuming an average lifespan of 85 years.
  • the performance of our mouse age-predictor varied between young and old mice. In young animals ( ⁇ 20 weeks) the model-predictions were remarkably accurate, with a mean absolute error of 2.66 weeks in the test samples. In mice aged 20 weeks or older, the mean absolute error was 10.07 weeks (Figure 6D). It is expected that future datasets generated by the community will help to further improve the accuracy of the mouse clock.
  • PCA principal component analysis
  • DNA methylation age is altered in ovariectomised females and by maternal diet
  • mice epigenetic clock which estimates age based on the methylation state at 644 discrete CG sites throughout the mouse genome.
  • the accuracy of our novel epigenetic clock is very high, performing comparably to the human epigenetic clock and also allowed us to assess (epigenetic) age in unrelated methylation datasets.
  • the epigenetic clock and the new comprehensive set of methylomes are available to the ageing research community and will enable mechanistic and intervention studies in the experimentally tractable mouse model system.
  • mouse methylation clock is affected by biological
  • Levine ME Lu AT, Bennett DA, Horvath S. Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer's disease related cognitive functioning. Aging (Albany NY). 2015;7:1 198-211.
  • Huntington's disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels.
  • RRBS libraries were prepared from isolated DNA following published protocols [36]. Briefly, RRBS libraries were prepared by Mspl digestion of 100 - 500 ng genomic DNA, followed by end-repair and T-tailing using Klenow Exo- (Fermentas). Adapter ligation was performed overnight (homemade adapters) using T4 DNA Ligase (NEB), followed by a cleanup step using AMPure XP beads (Agencourt, 0.9x). Subsequently, libraries were bisulfite treated according to the manufactures instructions (Sigma Imprint Kit; 2 step protocol) and purified using an automated liquid handling robotic system (Agilent Bravo).
  • the libraries were amplified using KAPA HiFi Uracil HotStart DNA Polymerase (KAPA Biosystems), indexing the samples with individual primers. All amplified libraries were purified (AMPure XP beads, 0.8x) and assessed for quality and quantity using High-Sensitivity DNA chips on the Agilent Bioanalyzer. High-throughput sequencing of all libraries was carried out with a 75 bp paired- end protocol on a HiSeq 2000 instrument (lllumina).
  • CpG density is predictive of the methylation age relations
  • CpG density was used as a linear predictor using multiple thresholds to predict if a methylation age relation would be significant or not using the AUC function for the pROC library [39].
  • Neighbouring genes were defined for single CG sites that were within 4 kb of a gene. GO terms were defined using the gprofiler online software [40]. For the GO enrichment analysis a background gene list was made consisting of the neighbouring genes (max distance of 4 kb) for all sites considered in that analysis. Significant GO terms were ordered by p-value, and the top 6 GO terms are shown.
  • the Reizel study consists of 173 samples originating from four different tissues: Liver, Muscle, Cerebellum and Spleen and data was collected at six time points ranging from 1 to 31 weeks.
  • gender and tissue specificity of demethylation during ageing has been studied.
  • a perturbation based on castration and restoring testosterone levels after castration has been performed.
  • the perturbations were not taken into the training, these were left for the test-set. After QC there were 143 samples left. Cannon et al. ⁇ 291
  • the Zhang study consists of 4 samples all originating from liver at the age between 6 and 8 weeks. In the original study methylation differences between different strains of mice, and the difference between mouse and zebrafish DNA-methylation levels are assessed. In our study these samples were used as a validation to see how the predictor works for an unobserved time-point. The age of these mice has been set to 7 weeks in our study. After QC there were 4 samples left. Schillebeeckx ⁇ 321
  • the Schillebeeckx study consists of 23 samples all originating from the liver, the adrenal gland and from endometrial cancer.
  • the mice were ovariectomized at the age of 3 to 4 weeks, samples were collected after an additional 3 months.
  • a laser capture microdissection RRBS method was introduced.
  • the liver samples which were generated using normal RRBS, and after QC 3 samples were left.
  • these samples were used as a validation to see how the predictor works for an unobserved time-point.
  • the age of these mice has been set to 16 weeks in our study. Age prediction
  • the predictor we used the elastic-net generalized linear model as implemented in the GLMNET package [33]. To optimize the alpha, defining the elastic net mixing parameter (1 for lasso to 0 for ridge) and to optimize the lambda, the regularization parameter, we used a double-loop cross-validation set-up. This setup is described in Ronde et al. [41]. We have trained the model to predict the log transformed mouse age (in weeks); 3 weeks were added before the log transforming the ages, to be able to predict samples pre-birth.
  • liver, lung, heart, and brain (cortex) samples from newborn to 41 week-old mice ( Figure 9A).
  • Figure 9A To reduce genetic variability and hormonal variations, we restricted our cohort to male C57BL/6-BABR mice and sampled 3-5 animals per time point. In total we collected 62 samples and extracted genomic DNA for methylation analysis from them.
  • RRBS Reduced Representation Bisulphite Sequencing
  • DNA methylation levels at a discrete set of CpGs are predictive of age
  • PCA principal component analysis
  • DNA methylation age is altered in ovariectomised females and by diet
  • mice epigenetic clock which estimates age based on the methylation state at 329 discrete CG sites (see Table 4) throughout the mouse genome.
  • the accuracy of our novel epigenetic clock is very high, performing comparably to the human epigenetic clock and also allowed us to assess (epigenetic) age in unrelated methylation datasets.
  • the 329 sites (see Table 4) of our mouse epigenetic clock perform significantly better in predicting age in mouse samples than the sites in the mouse genome corresponding to the human Horvath clock sites.
  • the epigenetic clock and the new comprehensive set of methylomes are available to the ageing research community and will enable mechanistic and intervention studies in the experimentally tractable mouse model system.
  • mouse methylation clock is affected by biological
  • Levine ME Hosgood HD, Chen B, Absher D, Assimes T, Horvath S. DNA methylation age of blood predicts future onset of lung cancer in the women's health initiative. Aging. 2015;7:690-700.
  • Levine ME Lu AT
  • Bennett DA Horvath S. Epigenetic age of the pre-frontal cortex is associated with neuritic plaques, amyloid load, and Alzheimer's disease related cognitive functioning. Aging. 2015;7: 1198-21 1.
  • Huntington's disease accelerates epigenetic aging of human brain and disrupts DNA methylation levels.

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Abstract

L'invention concerne un nouveau procédé de calcul de l'âge d'un échantillon biologique prélevé chez un sujet, en particulier une souris. L'invention concerne également des biomarqueurs de vieillissement, un kit comprenant des biocapteurs capables de détecter lesdits biomarqueurs, un procédé d'évaluation de l'effet d'une intervention biologique sur l'âge d'un sujet et un procédé de criblage d'un agent antivieillissement.
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Cited By (6)

* Cited by examiner, † Cited by third party
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WO2019046725A1 (fr) * 2017-08-31 2019-03-07 The Regent Of The University Of California Profilage de méthylome chez des animaux et utilisations de celui-ci
WO2020037222A1 (fr) * 2018-08-17 2020-02-20 President And Fellows Of Harvard College Procédés de mesure de l'âge de méthylation ribosomique
WO2020254405A1 (fr) 2019-06-17 2020-12-24 Vib Vzw Prédiction de l'âge à l'aide de signatures de méthylation de l'adn
WO2021148601A1 (fr) * 2020-01-24 2021-07-29 Evonik Operations Gmbh Horloge épigénétique pour galliformes
WO2021148593A1 (fr) * 2020-01-24 2021-07-29 Evonik Operations Gmbh Procédé d'établissement d'une horloge épigénétique pour une espèce aviaire
US11999995B2 (en) 2018-08-31 2024-06-04 The Regents Of The University Of California Methylome profiling in animals and uses thereof

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WO2014075083A1 (fr) * 2012-11-09 2014-05-15 The Regents Of The University Of California Procédés de pronostic de l'âge et agents d'identification qui induisent ou inhibent le vieillissement prématuré

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019046725A1 (fr) * 2017-08-31 2019-03-07 The Regent Of The University Of California Profilage de méthylome chez des animaux et utilisations de celui-ci
WO2020037222A1 (fr) * 2018-08-17 2020-02-20 President And Fellows Of Harvard College Procédés de mesure de l'âge de méthylation ribosomique
US11999995B2 (en) 2018-08-31 2024-06-04 The Regents Of The University Of California Methylome profiling in animals and uses thereof
WO2020254405A1 (fr) 2019-06-17 2020-12-24 Vib Vzw Prédiction de l'âge à l'aide de signatures de méthylation de l'adn
WO2021148601A1 (fr) * 2020-01-24 2021-07-29 Evonik Operations Gmbh Horloge épigénétique pour galliformes
WO2021148593A1 (fr) * 2020-01-24 2021-07-29 Evonik Operations Gmbh Procédé d'établissement d'une horloge épigénétique pour une espèce aviaire

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