Artificially induced accelerated aging to determine aging rate and / or age-related disease in a subject and associated methods

Abstract

Provided herein are methods of determining aging rate in a subject; of and identifying one or more interventions useful to reduce or prevent aging in the subject; of preventing or delaying onset of an age-related disease in the subject; and of determining a risk of developing an age-related disease in a subject and associated treatment and interventional plans.

Description

ARTIFICIALLY INDUCED ACCELERATED AGING TO DETERMINE AGING RATE AND / OR AGE-RELATED DISEASE IN A SUBJECT ANDASSOCIATED METHODSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application 63 / 552,591 filed February 12, 2024, which is incorporated herein by reference in its entirety.BACKGROUND

[0002] Aging is a universal process of physiological and molecular changes that are strongly associated with susceptibility to disease. Various studies have identified both molecular and epigenetic markers (e.g., alteration in telomere length and DNA-methylation) and clinical markers (e.g., changes in cholesterol and hemoglobin A1 c levels) associated with aging. Nonetheless, the changes described to date for assessment of biological aging are based on population trends. Moreover, aging is a heterogeneous process, making it difficult to predict how each individual will age and / or respond to therapies intended to mitigate or slow down the effects of aging.

[0003] Despite recent advances in the study of aging, the ability to provide accurate prognosis of aging is still lacking. Accordingly, there is a need for technologies that identify, prevent, and / or reduce mechanisms of aging in an individual based on specific biomarkers of aging. Further, because aging often results in age-related disease, there is also a demand for novel approaches to determine an individual’s risk of developing an age-related disease, and to identify, prevent, and / or delay onset of age-related disease.SUMMARY

[0004] The present technology relates to methods of determining aging rate in a subject and identifying one or more interventions useful to reduce or prevent aging in the subject; preventing or delaying onset of an age-related disease in a subject; and determining risk of developing an age-related disease in a subject.

[0005] In some embodiments, the present technology relates to methods of identifying one or more interventions useful to reduce or prevent aging in a subject, including: exposing a first population of cells derived from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; analyzing the population of aged cells to obtain a set of aged data; exposing a second population of cells derived from the subject to normal gravity to obtain a population of control cells; analyzing the population of control cells to obtain a set of control data; comparing the aged data and the control data to determine differences in gene activation or gene expression between the population of aged cells and the population of control cells; based on the determined differences, identifying: (i) a set of biomarkers associated with aging, and / or (ii) a cellular condition associated with aging; correlating the set of biomarkers and / or cellular condition associated with aging with one or more interventions to reduce the rate of aging in the subject; and developing an interventional plan to provide the one or more interventions to the subject to reduce the rate of aging in the subject.

[0006] In other embodiments, the present technology relates to methods of preventing or delaying onset of an age-related disease in a subject, including: exposing a first population of cells derived from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; analyzing the population of aged cells to obtain a set of aged data; exposing a second population of cells derived from the subject to normal gravity to obtain a population of control cells; analyzing the population of control cells to obtain a set of control data; comparing the aged data and the control data to determine differences in gene activation or gene expression between the population of aged cells and the population of control cells; based on the determined differences, identifying a set of biomarkers associated with age-related disease; correlating the set of biomarkers associated with age-related disease with one or more therapies to prevent or delay onset of the age-related disease in the subject; and developing a treatment plan to provide the one or more interventions to the subject to prevent or delay onset of the age-related disease.

[0007] In still other embodiments, the present technology relates to treatment plans for monitoring, delaying, or preventing onset of an age-related disease in a subject, preparedby: identifying a set of biomarkers associated with age-related disease in the subject by determining differences in gene activation or gene expression between a population of aged cells derived from the subject and a population of control cells derived from the subject, wherein the population of aged cells is obtained by exposing a first population of cells from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging in the cells, and the population of control cells is obtained by exposing a second population of cells from the subject to normal gravity; correlating the set of biomarkers associated with age-related disease with one or more therapies to prevent or delay onset of the age-related disease in the subject; and developing a treatment plan to provide one or more interventions to the subject to prevent or delay onset of the age-related disease.

[0008] In yet other embodiments, the present technology relates to methods of determining a risk of developing an age-related disease in a subject, including the steps of: (a) receiving aged data obtained from one or more analyses performed on a population of aged cells produced by exposing a first population of cells from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging; (b) receiving control data obtained from one or more analyses performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity; (c) comparing the aged data received in (a) to the control data received in (b); (d) identifying a set of biomarkers based on differences in gene activation or gene expression based on the comparing in (c) (e) correlating the biomarkers of (d) to a set of biomarkers associated with the age-related disease to determine expression of age-related biomarkers in (d); (f) (i) identifying the subject as having (A) a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold, or (B) a low risk for developing the age-related disease if the biomarkers in (d) are expressed below the high- risk threshold; and (g) developing a treatment plan for the subject based on the identification in (f).BRIEF DESCRIPTION OF THE DRAWINGS

[0009] FIG. 1 is a schematic representation of a study in accordance with one or more embodiments of the present technology.

[0010] FIG. 2A illustrates the relative expression between Ti-pG and T2 gene expression for four subjects according to the study illustrated in FIG. 1 . Expression values are UBE2D2- normalized by delta-delta-Ct method using the Ti c sample from each subject as a reference group.

[0011] FIG. 2B is a graph depicting intra-subject correlations between UBE2D2- normalized expression levels.

[0012] FIG. 3 illustrates inter-subject spearman correlation values of TI-MG expression values. Expression values are UBE2D2-normalized by delta-delta-Ct method using the Ti-Csample from each subject as a reference group.

[0013] FIG. 4 illustrates pathway expression levels for various hallmarks of aging.

[0014] FIG. 5 depicts the comparison of correlations between two groups of various hallmarks of aging. The red points show the comparison of the T1 and T2 controls, the teal points show the comparison of the simulated microgravity and the T2 controls.

[0015] FIG. 6 is a schematic representation of a cell magnetic levitation device used for simulating microgravity in accordance with the present technology.

[0016] FIG. 7A is an image of human peripheral blood mononuclear cells (PBMCs) positioned within a capillary tube of a magnetic levitation device having similar features to the device of FIG. 6 before incubation.

[0017] FIG. 7B is an image of human PBMCs in the capillary tube of FIG. 7A after incubation in the device for 24 hours.

[0018] FIG. 8 is a graph depicting the PC1 vs PC2 variance of control human PBMCs that were not magnetically levitated (C) and human PBMCs that were incubated as described in FIG. 7B (ML).

[0019] FIG. 9 is a volcano plot of differential gene expression (DGE) of human PBMCs that were incubated as described in FIG. 7B.

[0020] FIG. 10 shows a heatmap overlapping DGEs between control PBMCs that were not subjected to magnetic levitation (C) and PBMCs that were incubated as described in FIG. 7B (ML).

[0021] FIG. 11 depicts biological functions and pathways that were over-represented or under-represented in human PBMCs incubated as described in FIG. 7B as determined by gene ontology over-enrichment analysis.

[0022] FIG. 12 depicts biological functions and pathways that were identified as enriched in human PBMCs that were incubated as described in FIG. 7B as determined by gene ontology gene set enrichment analysis (GSEA).

[0023] FIG. 13A is a graph depicting the GSEA analysis of the gene ontology biological process of B-cell mediated immunity in human PBMCs as described in FIG. 7B.

[0024] FIG. 13B is a graph depicting the enrichment score of the gene ontology biological process of oxidative phosphorylation in human PBMCs as described in FIG. 7B.

[0025] FIG. 14 depicts the biological functions and pathways that were upregulated or downregulated in human PBMCs as described in FIG. 7B as determined by Ingenuity Pathways Analysis (I PA).

[0026] FIG. 15A is a graph depicting the GSEA analysis of genes that were upregulated in human PBMCs that were incubated in a magnetic levitation device for 24 hours.

[0027] FIG. 15B is a graph depicting the GSEA analysis of genes that were downregulated in human PBMCs as described in FIG. 7B.

[0028] FIG. 16 depicts transcriptomic changes that were enriched in aging hallmark pathways of human PBMCs as described in FIG. 7B.DETAILED DESCRIPTION

[0029] Described herein are methods of inducing accelerated aging in cells derived from a subject compared to non-aged cells from the subject to determine aging rate and trajectories, and identify one or more interventions useful to reduce or prevent aging in the subject; to prevent or delay onset of an age-related disease in the subject; or determine risk of developing an age-related disease in the subject, as well as associated treatment and interventional plans. In some embodiments, the present technology may be useful to evaluate a subject’s resilience to aging.

[0030] In some embodiments, the present technology includes methods of determining aging rate and / or identifying one or more interventions useful to reduce or prevent aging in a subject by inducing accelerated aging in cells derived from the subject compared to nonaged cells from the subject to identify biomarkers associated with aging and / or a cellular condition associated with aging in the aged cells. In some embodiments, the biomarkers and / or cellular condition is correlated to one or more lifestyle changes and / or dietary supplements that may be used to reduce the rate of aging in the subject, and a corresponding interventional plan is prepared. In some embodiments, the present technology may be useful to evaluate a subject’s resilience to aging. In some embodiments, accelerated aging is induced by exposing the cells derived from the subject to low gravity. The low gravity may be microgravity.

[0031] In some embodiments, the present technology includes methods of preventing or delaying onset of an age-related disease in a subject by inducing accelerated aging in cells derived from the subject compared to non-aged cells from the subject to identify biomarkers associated with the age-related disease in the aged cells. In some embodiments, the biomarkers are then correlated to one or more therapies to prevent or delay onset of the age-related disease in the subject and a corresponding treatment plan is prepared. In some embodiments, accelerated aging is induced by exposing the cells derived from the subject to low gravity. The low gravity may be microgravity. In some embodiments, the present technology provides methods of determining a risk of developing an age-related disease by inducing accelerated aging in cells derived from the subject, determining an expression of biomarkers associated with age-related disease in the aged cells, and identifying the subject’s risk of developing age-related disease.

[0032] While the present disclosure is capable of being embodied in various forms, the description below of several embodiments is made with the understanding that the present disclosure is to be considered as an exemplification of the present technology and is not intended to limit the present technology to the specific embodiments illustrated. Headings are provided for convenience only and are not to be construed to limit the present technology in any manner. Embodiments illustrated under any heading may be combined with embodiments illustrated under any other heading.Definitions

[0033] The use of numerical values in the various quantitative values specified in this application, unless expressly indicated otherwise, are stated as approximations as though the minimum and maximum values within the stated ranges were both preceded by the word “about.” It is to be understood, although not always explicitly stated, that all numerical designations are preceded by the term “about.” It is to be understood that such range format is used for convenience and brevity and should be understood flexibly to include numerical values explicitly specified as limits of a range, but also to include all individual numerical values or sub-ranges encompassed within that range as if each numerical value and subrange is explicitly specified. For example, a ratio in the range of about 1 to about 200 should be understood to include the explicitly recited limits of about 1 and about 200, but also to include individual ratios such as about 2, about 3, and about 4, and sub-ranges such as about 10 to about 50, about 20 to about 100, and so forth. It also is to be understood, although not always explicitly stated, that the reagents described herein are merely exemplary and that equivalents of such are known in the art.

[0034] The term “about,” as used herein when referring to a measurable value such as an amount or concentration and the like, is meant to encompass variations of 20%, 10%, 5%, 1%, 0.5%, or even 0.1% of the specified amount.

[0035] Also, the disclosure of ranges is intended as a continuous range, including every value between the minimum and maximum values recited, as well as any ranges that can be formed by such values. Also disclosed herein are any and all ratios (and ranges of any such ratios) that can be formed by dividing a disclosed numeric value into any other disclosed numeric value. Accordingly, the skilled person will appreciate that many such ratios, ranges, and ranges of ratios can be unambiguously derived from the numerical values presented herein and in all instances, such ratios, ranges, and ranges of ratios represent various embodiments of the present disclosure.

[0036] The term “interventions” as used herein refers to therapy used reduce or prevent aging in a subject; to prevent or delay onset of an age-related disease in the subject; or to mitigate the effects of aging or an age-related disease in a subject. Non-limiting examplesof suitable interventions include dietary supplements, nutritional supplements, nutraceuticals, pharmaceutical agents, and lifestyle changes.

[0037] As used herein a “dietary supplement” refers to any additive or supplement used to improve overall health and wellbeing in a subject. In general, dietary supplements include nutraceuticals and nutritional supplements such as, vitamins, minerals, botanicals, herbs, botanical compounds, amino acids, and live microbials, among others.

[0038] The term “nutraceutical(s)” refers to a nutrition product that is also used as a medicine. Nutraceuticals often contain modified / unmodified whole food, plant extracts alone or in combination, semipurified and purified phytochemicals, or a combination of different phytochemicals. Non-limiting examples of nutraceuticals include ubiquinone, omega-3 polyunsaturated fatty acids, chondroitin, glucosamine, s-adenosylmethionine, and levocarnitine.

[0039] Term “nutritional supplement” refers to nutritional compounds that supplement one’s diet by increasing one’s total daily intake, e.g., of protein, vitamin C, iron, etc. Nonlimiting examples of nutritional supplements include multivitamins, vitamin B12, vitamin D, iron, calcium, magnesium, echinacea, probiotics, prebiotics, collagen, resveratrol, and fiber.

[0040] As used herein, a “pharmaceutical agent” includes any drug or biological product used to diagnose, cure, treat, or prevent disease that is under the regulatory authority of the Food and Drug Administration (FDA). Exemplary pharmaceutical agents include metformin, rapamycin, and senolytics, among others.

[0041] As used herein, “microgravity” includes any environment having equal to or less than one-millionth (10-6) of the force of gravity at Earth’s surface (i.e., 1 G or normal gravity). Accordingly, microgravity includes zero gravity.Methods

[0042] In some embodiments, the present technology relates to methods of determining aging rate and / or identifying one or more interventions useful to reduce or prevent aging in a subject and associated interventional plans. In some embodiments, a method of determining aging rate and / or identifying one or more interventions useful toreduce or prevent aging in a subject comprises inducing accelerated aging in cells derived from the subject to obtain aged cells and identifying hallmarks of aging in the aged cells. In some embodiments, the present technology may be useful to evaluate a subject’s resilience to aging.

[0043] In some embodiments, the method of determining aging rate and / or identifying one or more interventions useful to reduce or prevent aging in a subject comprises exposing a first population of cells derived from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; analyzing the population of aged cells to obtain a set of aged data; exposing a second population of cells derived from the subject to normal gravity to obtain a population of control cells; analyzing the population of control cells to obtain a set of control data; comparing the aged data and the control data to determine differences in gene methylation, gene activation, or gene expression between the population of aged cells and the population of control cells; and based on the determined differences, identifying (i) a set of biomarkers associated with aging, and / or (ii) a cellular condition associated with aging. In some embodiments, the method further comprises correlating the set of biomarkers associated with aging with one or more interventions to reduce the rate of aging in the subject and developing an interventional plan to provide the one or more interventions to the subject to reduce the rate of aging in the subject. In some embodiments, the one or more interventions include one or more nutraceuticals, lifestyle changes, and / or nutritional supplements. In some embodiments, the present technology may be useful to evaluate a subject’s resilience to aging.

[0044] In other embodiments, the present technology relates to methods of preventing, and / or delaying onset of an age-related disease in a subject, and associated treatment plans. In some embodiments, a method of preventing and / or delaying onset of an age- related disease in a subject comprises inducing accelerated aging in cells derived from the subject to obtain aged cells and identifying biomarkers associated with age-related disease in the aged cells. In some embodiments, the subject already exhibits symptoms of an age- related disease. In other embodiments, the subject does not yet exhibit any symptoms of an age-relate disease.

[0045] In some embodiments, the method of preventing or delaying onset of an age- related disease in a subject comprises exposing a first population of cells derived from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; analyzing the population of aged cells to obtain a set of aged data; exposing a second population of cells derived from the subject to normal gravity to obtain a population of control cells; analyzing the population of control cells to obtain a set of control data; comparing the aged data and the control data to determine differences in gene activation or gene expression and / or differences in activation or enrichment of biological pathways or functions between the population of aged cells and the population of control cells; and based on the determined differences, identifying a set of biomarkers associated with age-related disease. In some embodiments, the method further includes, after identifying the set of biomarkers associated with age-related disease, correlating the set of biomarkers associated with age-related disease with one or more interventions to prevent or delay onset of the age-related disease in the subject and developing a treatment plan to provide the one or more interventions to the subject to prevent or delay onset of the age-related disease. In some embodiments, the one or more interventions include one or more nutraceuticals, lifestyle changes, and / or nutritional supplements.

[0046] In still other embodiments, the present technology provides methods of determining the risk of developing an age-related disease in a subject and associated treatment plans. In some embodiments, a method of determining the risk of developing an age-related disease in a subject comprises inducing accelerated aging in cells derived from the subject to obtain age cells, identifying biomarkers associated with age-related disease in the aged cells, and based on the identified biomarkers, identifying the subject as having a high risk or a low risk for developing the age-related disease.

[0047] In some embodiments, the method of determining the risk of developing an age- related disease in a subject comprises the steps of:(a) receiving aged data obtained from one or more analyses performed on a population of aged cells produced by exposing a first population of cells from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging;(b) receiving control data obtained from one or more analyses performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in gene activation or gene expression based on the comparing in (c)(e) correlating the biomarkers of (d) to a set of biomarkers associated with the age- related disease to determine expression of age-related biomarkers in (d);(f) identifying the subject as having(A) a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the age-related disease if the biomarkers in (d) are expressed below the high-risk threshold; and(g) developing a treatment plan for the subject based on the identification in (f).

[0048] Such method may be performed on a computing device. Accordingly, the present technology further provides a non-transitory medium with instructions stored thereon that, when execute by a processor of a computing device, causes the computing device to perform the steps of the method.

[0049] In some embodiments of the methods according to the present technology, while the first population of cells is being exposed to simulated microgravity, the cells are sampled and analyzed at regular time intervals to obtain time-interval aging data. The regular time intervals may be every 15 minutes, every 30 minutes, every hour, every 2 hours, every 3 hours, every 4 hours, every 5 hours, or every 6 hours. In some embodiments, the second population of cells is sampled and analyzed at the same regular time intervals to obtain time-interval control data. In such embodiments, the method includes comparing the time-interval aging data to the time-interval control data to identify one or more biomarkers associated with aging or age-related disease. The one or more biomarkers may be unique to the subject, regardless of the underlying mechanism of aging or age-related disease.

[0050] In some embodiments, the first population of cells is split into a first subpopulation of cells and second subpopulation of cells, the first and second subpopulations of cells are exposed to simulated microgravity, and then the first subpopulation of cells is returned to normal gravity while the second subpopulation of cells remains at microgravity. After the first subpopulation of cells is returned to normal gravity, time-series measurements may be taken to determine the molecular mechanisms of recovery to the induced accelerated aging. The time-series measurements may be taken every 4-18 hours after the first subpopulation of cells is returned to normal gravity. For example, to determine molecular mechanisms involved in the rejuvenation process of cells exposed to simulated microgravity, measurements may be taken at 4 hours, 8 hours, 12 hours, 24 hours, 36 hours, 48 hours, 60 hours, 72 hours, 84 hours, and 96 hours post return to normal gravity.

[0051] Once molecular mechanisms associated with recovery have been determined, the method may further include identifying one or more interventional agent that mimics the molecular mechanism of recovery by performing an in silica compound screen. Alternatively, or additionally, the method may further include identifying one or more interventional agents that prevents, reduces, or otherwise reverses aging by performing an in vitro compound screen. In some embodiments, the in silico or in vitro compound screen is performed on the second subpopulation of cells that remained at simulated microgravity. The identified interventional agents may be able to improve upon or accelerate the natural molecular mechanism of recovery in a subject.

[0052] The first and second populations of cells may comprise any type of cells from the subject. In some embodiments, the first and second populations of cells comprise populations of immune cells. In some embodiments, the populations of immune cells include peripheral blood mononuclear cells (PBMCs). In such embodiments, the PMBCs may comprise enriched subpopulations of PBMCs. When the first and second population of cells comprise enriched subpopulations of PBMCs, the PBMCs may be sorted with fluorescence- activated cellular sorting (FACS), microfluidics, density gradient centrifugation, differential centrifugation, paramagnetic beads, levitation technology or a combination of these methods. Other type of cells, in addition to PBMCs or other than PBMCs, that may beincluded in the first and second populations of cells from the subject include, but are not limited to epithelial cells, nerve cells, and muscle cells.

[0053] Methods of the present technology include exposing a first population of cells to simulated microgravity for an amount of time sufficient to include accelerated aging in the cells. Various machines known in the art may be used to simulate microgravity. For example, the first population of cells may be exposed to simulated microgravity generated by a rotating wall vessel (RWV), a random positioning machine (RMP), or a magnetic levitation device.

[0054] In some embodiments, the first population of cells is exposed to simulated microgravity for an amount of time sufficient to induce accelerated aging in the cells. The amount of time sufficient to induce accelerated aging in the first population of cells may be at least 10 hours. In some embodiments, the amount of time sufficient to induce accelerated aging in the first population of cells is about 12 hours, about 14 hours about 16 hours, about 18 hours, about 20 hours, about 22 hours, or about 24 hours. The amount of time sufficient to induce accelerated aging in the first population of cells may be at least 24 hours. In some embodiments, the amount of time sufficient to induce accelerated aging in the first population of cells is 25 hours, 30 hours, 35 hours, 40 hours, 45 hours, 50 hours, 55 hours, 60 hours, or more. In some embodiments, the amount of time is 25 hours.

[0055] When the first population of cells is exposed to simulated microgravity for an amount of time, the amount of time may be sufficient to include accelerated aging such that the population of aged cells are biologically aged 1 year, 2 years, 3 years, 4 years, 5 years, 6 years, 7 years, 8 years, 9 years, or 10 years relative to the population of control cells. In some embodiments, the population of aged cells is biologically aged by about 3 to 10 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 25 hours, then the resulting population of aged cells are biologically aged by about 3 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 35 hours, then the resulting population of aged cells are biologically aged by about 4 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 40 hours, then the resulting population of aged cells are biologically aged by about 5 years relative to the population of control cells. In someembodiments, when the first population of cells is exposed to simulated microgravity for 50 hours, then the resulting population of aged cells are biologically aged by about 6 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 60 hours, then the resulting population of aged cells are biologically aged by about 7 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 70 hours, then the resulting population of aged cells are biologically aged by about 8 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 80 hours, then the resulting population of aged cells are biologically aged by about 9 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 90 hours, then the resulting population of aged cells are biologically aged by about 10 years relative to the population of control cells.

[0056] In some embodiments, when the first population of cells is exposed to simulated microgravity for 30 to 35 hours, then the resulting population of aged cells are biologically aged by about 5 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 35 to 40 hours, then the resulting population of aged cells are biologically aged by about 6 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 40 to 45 hours, then the resulting population of aged cells are biologically aged by about 7 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 45 to 50 hours, then the resulting population of aged cells are biologically aged by about 8 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 50 to 55 hours, then the resulting population of aged cells are biologically aged by about 9 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 55 to 60 hours, then the resulting population of aged cells are biologically aged by about 10 years relative to the population of control cells.

[0057] In some embodiments, when the first population of cells is exposed to simulated microgravity for 40 to 50 hours, then the resulting population of aged cells are biologically aged by about 4 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 50 to 60 hours, then the resulting population of aged cells are biologically aged by about 5 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 60 to 70 hours, then the resulting population of aged cells are biologically aged by about 6 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 70 to 80 hours, then the resulting population of aged cells are biologically aged by about 7 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 80 to 90 hours, then the resulting population of aged cells are biologically aged by about 8 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 90 to 100 hours, then the resulting population of aged cells are biologically aged by about 90 years relative to the population of control cells. In some embodiments, when the first population of cells is exposed to simulated microgravity for 100 to 120 hours, then the resulting population of aged cells are biologically aged by about 10 years relative to the population of control cells.

[0058] In some embodiments, the population of control cells is obtained by exposing the second population of cells to normal gravity for the same amount of time that the first population of cells is exposed to simulated microgravity. In some embodiments, the second population of cells is collected from the subject concurrently with the first population of cells. In other embodiments, the second population of cells is collected from the subject during or after the first population of cells is exposed to simulated microgravity.

[0059] After the population of aged cells and the population of control cells are obtained, the methods include analyzing the populations of aged cells and control cells to obtain a set of aged data and a set of control data. Any type and / or method of cellular analysis known in the art may be used to obtain the set of aged data and the set of control data and the particular method used may depend on a number of factors such as, forexample, the age-related disease, characteristics of the subject, and feasibility of analysis. In some embodiments, the populations of aged and control cells may be analyzed using any type of “omics”. For example, the cells may be analyzed using transcriptomics to perform a transcriptome analysis, using epigenomics to perform an epigenome analysis, using metabolomics to perform a metabolome analysis, and / or using proteomics to perform a proteome analysis on the population of aged cells and the population of control cells.

[0060] In some embodiments, analyzing the population of aged cells and the population of control cells includes using transcriptomics to perform a transcriptome analysis. In some embodiments, the transcriptome analysis further comprises one or more of total RNA, enriched mRNA, enriched non-coding RNA, enriched antisense RNAs, or enriched small RNA. In other embodiments, the transcriptome analysis further comprises sequencing, quantitative polymerase chain reaction (qPCR), quantitative reverse transcriptase PCR (qRT-PCR), digital PCR (dPCR), digital droplet PCR (ddPCR), Reverse Transcription Loop-mediated Isothermal Amplification (RT-LAMP), Loop-mediated Isothermal Amplification (LAMP), serial analysis of gene expression (SAGE), cap analysis of gene expression (CAGE), gene ontology over-enrichment analysis, gene set enrichment analysis (GSEA), Ingenuity Pathway Analysis (IPA), northern blot, expression immunoassay, microarrays analysis and / or any method utilizing light intensity, fluorescent signal intensity, stable isotopes, and / or radioactive isotopes to quantify gene expression. In still other embodiments, the transcriptome analysis further comprises single-cell transcriptome analysis.

[0061] In some embodiments, analyzing the population of aged cells and the population of control cells includes using epigenomics to perform an epigenome analysis. In some embodiments, the epigenome analysis further comprises assay for transposase- accessible chromatin using sequencing (ATAC-seq), bisulfite sequencing, chromatin immunoprecipitation sequencing (CHiP-seq), Hi-C epigenome analysis, cleavage under targets and tagmentation (CUT&Tag), and / or cleavage under targets and release using nuclease (CUT&run). In other embodiments, the epigenome analysis further comprises integrated single-cell epigenome analysis.

[0062] In some embodiments, analyzing the population of aged cells and the population of control cells includes using metabolomics to perform a metabolome analysis. In some embodiments, the metabolome analysis further comprises nuclear magnetic resonance spectroscopy (NMR) and / or mass spectrometry (MS), such as, for example, Fourier transform ion cyclotron mass spectrometry (FTIC-MS).

[0063] In some embodiments, analyzing the population of aged cells and the population of control cells includes using proteomics to perform a proteome analysis. In some embodiments, the proteome analysis further comprises enzyme-linked immunosorbent assays (ELISA), western blotting, two-dimensional difference gel electrophoresis (2D-DIGE), tandem mass spectrometry, and / or mass spectrometry.

[0064] Once the set of aged data and the set of control data have been obtained, the methods include comparing the aged data and the control data to determine differences in gene activation or gene expression between the population of aged cells and the population of control cells. In some embodiments, genes identified as having differential activation or expression include one or more of:(i) CD28, CD40, CD40LG, CD80, CD86, COL1 A1 , COL1A2, COL3A1 , FN1 , IFNG, IL2, IL2RA, IL2RB, IL2RG, IL4, IL4R, IL5, IL5RA, LAMA5, LAMB1 , LAMB2, LAMC1 , LAMC2, LCK, MIR3606, MIR4758, MIR7846, THBS1 , THBS3, TNFRSF1 A, TNFRSF1 B, VTN, ZAP70;(ii) ATM, ATR, CDKN1A, CDKN2A, CHEK1 , CHEK2, CTC1 , ERCC1 , MIR21 , MME, PLA2R1 , ROMO1 , SERPINE1 , TERT, TP53, WNT16, WRN;(iii) ACTB, ACTG1 , ACTN1 , ACTN2, ACTN3, ACTN4, AFDN, ANG, ARHGEF6, CADM1 , CADM2, CADM3, CASK, CD151 , CD2AP, CD47, CDH1 , CDH10, CDH1 1 , CDH12, CDH13, CDH15, CDH17, CDH18, CDH2, CDH24, CDH3, CDH4, CDH5, CDH6, CDH7, CDH8, CDH9, CLDN1 , CLDN10, CLDN11 , CLDN12, CLDN14, CLDN15, CLDN16, CLDN17, CLDN18, CLDN19, CLDN2, CLDN20, CLDN22, CLDN23, CLDN3, CLDN4, CLDN5, CLDN6, CLDN7, CLDN8, CLDN9, COL17A1 , CRB3, CTNNA1 , CTNNB1 , CTNND1 , DST, F11 , FBLIM1 , FERMT2, FLNA, FLNC, FYB1 , FYN, GRB2, ILK, IQGAP1 , ITGA6, ITGB1 , ITGB4, JUP, KIRREL1 , KIRREL2, KIRREL3, KRT14, KRT5, LAMA3, LAMB3, LAMC2, LIMS1 , LIMS2, MAGI2, NCK1 , NCK2, NECTIN1 , NECTIN2, NECTIN3, NECTIN4,NPHS1, NPHS2, PALS1, PARD3, PARD6A, PARD6B, PARD6G, PARVA, PARVB, PATJ, PIK3CA, PIK3CB, PIK3R1, PIK3R2, PLEC, PRKCI, PTK2, PTK2B, PTPN11, PTPN6, PVR, PXN, RSU1, SDK1, SDK2, SFTPA1, SFTPA2, SFTPD, SIRPA, SIRPB1, SIRPG, SKAP2, SPTAN1 , SPTBN1 , SRC, TESK1 , TYROBP, VASP, WASL;(iv) NUPR1 , ENPP5, GPR183, CD38, NEO1 , FHL1 , PBX3, ALCAM, ALDH1 A1 , EBI3, DHRS3, PLEK, CD37, CLU, EHD3, CPNE8, PRCP, CD86, SULT1A1, EFNA1, SATB1, PLSCR1, GADD45G, TGM2, RORC, BMPR1A, GEM, CYSLTR2, RASSF4, LPL, DSG2, TRIM47, STOM, IL15, TM6SF1 , RNASE6, MMP2, ARHGAP30, SLAMF1 , NPDC1 , NDRG1 , ABAT, DENND5B, TSC22D1, ANXA6, MEF2C, CYTIP, MCM7, PERP, THBD, LAMP2, CYB561, PLAC8, LST1 , TMEM176A, LPAR6, TC2N, PROCR, FLT3, CAVIN2, MMP14, JUN, EGR1 , ID2, BCL6, S100A6, IL12RB2, MGST1 , ZFP36, CSF2RB, LSR, ECT2, MYO1 E, SERPINB8, CXCL16, PPP1R16B, LSP1, TNFSF10, CD9, PLA2G4A, DHX40, EVC, LGALS1, NDN, SELL, MLLT3, ANXA2, OXR1, GSTM1, BTG2, CTSS, ACSL4, SOCS2, MLEC, SEMA7A, PLXDC2, RFC2, EXOC6B, MCM5, GPX3, TOX, LY6E, CD63, RDH10, PLCL1, PTGER4, MAF, VMP1, RAB34, TBC1D8, DDR1, AMPD3, SYK, ANTXR2, LDHD, PDGFD, ACPP, CAMK1 D, PRNP, PHACTR1 ;(v) ADIPOR1, AGT, AHSG, APPL2, ATP2B1, BGLAP, C1QTNF12, ECHDC3, ENPP1 , ERFE, ESRRA, GKAP1 , GNAI2, GPLD1 , GPR21 , GRB10, GRB14, GRB7, GSK3A, IGF2, IL1 B, INPP5K, INS, IRS1 , KANK1 , LEP, LPL, MIR103A1 , MIR107, MIR1271 , MIR15B, MIR195, MSTN, MYO1C, NCK1, NCOA5, NR1H4, NUCKS1, OSBPL8, PID1 , PIP4K2A, PIP4K2B, PIP4K2C, PRKAA1, PRKCB, PRKCD, PRKCQ, PRKCZ, PTPN1, PTPN11, PTPN2, PTPRE, RPS6KB1, SERPINA12, SIRT1, SLC27A4, SNX5, SOCS1 , SOCS3, SORBS1 , SORL1 , SRC, TNS2, TRIM72, TSC2, USO1 , ZBTB7B;(vi) AFG3L2, AHSP, AIP, AIPL1, APCS, CALR, CALR3, CANX, CCDC115, CCT2, CCT3, CCT4, CCT5, CCT6A, CCT6B, CCT7, CCT8, CCT8L1P, CCT8L2, CDC37, CDC37L1, CHAF1A, CHAF1B, CLGN, CLPX, CLU, CRYAA, CRYAB, DNAJA1, DNAJA2, DNAJA3, DNAJA4, DNAJB1 , DNAJB11 , DNAJB13, DNAJB2, DNAJB3, DNAJB4, DNAJB5, DNAJB6, DNAJB7, DNAJB8, DNAJC4, ERLEC1, ERN1, ERN2, ERO1B, GRPEL1, GRPEL2, HEATR3, HSP90AA1, HSP90AA2P, HSP90AA4P, HSP90AA5P, HSP90AB1, HSP90AB2P, HSP90AB3P, HSP90AB4P, HSP90B1, HSP90B2P, HSPA13, HSPA14, HSPA1A, HSPA1B, HSPA1L, HSPA2, HSPA5, HSPA6, HSPA7, HSPA8, HSPA9, HSPB6,HSPD1, HSPE1, HTRA2, HY0LI1, LMAN1, MKKS, NACA, NACA2, NACA4P, NACAD, NAP1L4, NDUFAF1, NPM1, NUDC, NUDCD2, NLIDCD3, PDRG1, PET100, PFDN1, PFDN2, PFDN4, PFDN5, PFDN6, PPIA, PPIB, PTGES3, RP2, RUVBL2, SCAP, SCG5, SERPINH1, SHQ1, SIL1, SPG7, SRSF10, SRSF12, SYVN1, TAPBP, TCP1, TIMM10B, TMEM67, TOMM20, T0R1 A, TRAP1 , TTC1 , TUBB4B, UGGT1 , UGGT2, VBP1 ;(vii) ACTB, AEBP2, ARID4B, BAZ1B, BAZ2A, CBX3, CONH, CDK7, CHD3, CHD4, DDX21, DEK, DNMT1, DNMT3A, DNMT3B, DNMT3L, EED, EHMT2, EP300, ERCC2, ERCC3, ERCC6, EZH2, GATAD2A, GATAD2B, GSK3B, GTF2H1, GTF2H2, GTF2H3, GTF2H4, GTF2H5, H2AB1, H2AC14, H2AC20, H2AC4, H2AC6, H2AC7, H2AC8, H2AJ, H2AX, H2AZ1, H2AZ2, H2BC1 , H2BC10, H2BC11, H2BC12, H2BC13, H2BC14. H2BC15, H2BC17, H2BC21. H2BC3. H2BC4, H2BC5, H2BC6, H2BC7, H2BC8, H2BC9, H2BS1, H2BU1, H3-3A, H3-3B, H3C1, H3C10, H3C11, H3C12, H3C13, H3C14, H3C15, H3C2, H3C3, H3C4, H3C6, H3C7, H3C8, H4-16, H4C1, H4C11, H4C12, H4C13, H4C14, H4C15, H4C2, H4C3, H4C4, H4C5, H4C6, H4C8, H4C9, HDAC1 , HDAC2, JARID2, KAT2A, KAT2B, MBD2, MBD3, MNAT1, MTA1, MTA2, MTA3, MTF2, MYBBP1A, MYO1C, ,PHF1, PHF19, POLR1A, POLR1B, POLR1C, POLR1D, POLR1E, POLR1F, POLR1G, POLR1H, POLR2E, POLR2F, POLR2H, POLR2K, POLR2L, RBBP4, RBBP7, RRP8, SAP130, SAP18, SAP30, SAP30BP, SAP30L, SF3B1 , SIN3A, SIN3B, SIRT1 , SMARCA5, SUDS3, SUV39H1 , SUZ12, TAF1 A, TAF1 B, TAF1 C, TAF1 D, TBP, TDG, TET1 , TET2, TET3, TTF1 , UBTF, UHRF1 ;(viii) ABL1, ACD, AKT1, ATM, BLM, CCND1, CDKN1B, DKC1, E2F1, EGF, EGFR, ESR1, FOS, HDAC1, HDAC2, HNRNPC, HSP90AA1, HUS1, IFNAR2, IFNG, IL2, IRF1, JUN, MAPK1, MAPK3, MAX, MRE11, MTOR, MXD1, MYC, NBN, NCL, NFKB1, NR2F2, PARP2, PINX1, POT1, PTGES3, RAD1, RAD50, RAD9A, RBBP4, RBBP7, RPS6KB1, SAP18, SAP30, SIN3A, SIN3B, SMAD3, SMG5, SMG6, SP1, SP3, TERF1, TERF2, TERF2IP, TERT, TGFB1, TINF2, TNKS, UBE3A, WRN, WT1 , XRCC5, XRCC6, YWHAE, ZNFX1;(ix) CAMK4, CREB1, ESRRA, ABPA, GABPB1, GABPB1-IT1, HCFC1, MTERF1, MTERF3, MYEF2, NRF1, POLRMT, PPARGC1A, PPARGC1B, PPP3CA, PPRC1, SP1, TFAM, TFB1 M, and TFB2M.

[0065] In some embodiments, the methods include comparing the aged data and the control data to determine differences in activation or enrichment of biological pathways or functions between the population of aged cells and the population of control cells. In some embodiments, pathways and functions identified as being differentially represented include one or more of: CXCR chemokine receptor binding; response to chemokine; inflammatory response; defense response; immune effector process; pyruvate metabolic process; regulation of immune system process; innate immune response; leukocyte chemotaxis; myeloid leukocyte activation; regulation of response to external stimulus endocytosis; response to oxygen levels; cell activation; response to cytokine; regulation of response to stress; mitochondrial protein containing complex; MHC class II protein complex binding; antigen processing and presentation of exogenous antigen; ATP synthesis coupled electron transport; immune receptor activity; B cell mediated immunity, oxidative phosphorylation, leukocyte mediated immunity; cell activation involved immune response; lymphocyte mediated immunity; NADH regeneration; glucose catabolic process; ADP metabolic process response to endoplasmic reticulum stress; immunoregulatory interactions between a lymphoid and a non-lymphoid cell; toll-like receptor cascades; neutrophil degranulation; interleukin-10 signaling; complement system; macrophage alternative activation signaling pathway; interleukin-4 and interleukinOI 3 signaling; neuroinflammation signaling pathway; G-protein coupled receptor signaling; pathogen induced cytokine storm signaling pathway; interferon gamma signaling; gluconeogenesis I; IL-10 signaling; HIF1 a signaling; glycolysis 1 ; macrophage classical activation signaling pathway; multiple sclerosis signaling pathway; phagosome formation; TRAM1 signaling; FCy receptor-mediated phagocytosis in macrophages and monocytes; TH1 pathway; coronavirus pathogenesis pathway; CDX gastrointestinal cancer signaling pathway; aryl hydrocarbon receptor signaling; TH2 pathway; integrin signaling; pathogen induced cytokine storm signaling pathway; role of PKR in interferon induction and antiviral response; breast cancers regulation by Stathminl ; aldosterone signaling in epithelial cells; CREB signaling in neurons; PD-1 / PD-L1 cancer immunotherapy pathway; cAMP-mediated signaling; IL-8 signaling; ERK / MAPK signaling; role of hypercytokinemia / hyperchemokinemia in the pathogenesis of influenza; factors promoting cardiogenesis in vertebrates; HMGB1 signaling; adrenomedullin signalingpathway; acute phase response signaling; IL-17 signaling; colorectal cancer metastasis signaling; tumor microenvironment pathway; pulmonary fibrosis idiopathic signaling pathway; cardiac hypertrophy signaling; and hepatic fibrosis signaling pathway.

[0066] The methods then include, based on the determined differences in gene activation or gene expression or the differences in activation or enrichment of biological pathways or functions between the population of aged cells and the population of control cells, identifying (i) a set of biomarkers associated with aging or age-related disease and / or (ii) a cellular condition associated with aging or age-related disease. The set of biomarkers may be indicative of the cellular condition, or the set of biomarkers may be separate from the cellular condition. In some embodiments, the method comprises identifying a set of biomarkers associated with aging or age-related disease. The set of biomarkers may include one or more of a gene, a cluster of genes, a gene promoter, a group of gene promoters, an enhancer, a group of gene enhancers, a transcriptional activator, a group of transcriptional activators, a non-coding RNA, a group of non-coding RNAs, an antisense RNA, a group of antisense RNAs. In some embodiments, the set of biomarkers includes one or more differentially expressed or activated gene previously listed.

[0067] In some embodiments, the identified biomarkers are known biomarkers associated with age-related disease. In other embodiments, the identified biomarkers are new biomarkers associated with age-related disease. Accordingly, the method of the present technology may also identify new biomarkers associated with age-related disease.

[0068] In some embodiments, the method comprises identifying a cellular condition associated with aging or age-related disease. The cellular condition may include one or more of cellular senescence, mitochondrial dysfunction, stem cell exhaustion, altered intracellular communication, genome instability, telomere attrition, epigenetic alterations, loss of proteostasis garbaging, deregulated nutrient sensing, disabled autophagy, dysbiosis, and chronic inflammation.

[0069] The methods may further include identifying the subject as having a high risk or a low risk of developing an age-related disease or a cellular condition associated with aging or an age-related disease. In some embodiments, the subject is determined as having ahigh risk of developing an age-related disease or a cellular condition associate with aging or an age-related disease if the age-related biomarkers are expressed at or greater than a high-risk threshold. In other embodiments, the subject is determined as having a low risk of developing an age-related disease or a cellular condition associate with aging or an age- related disease if the age-related biomarkers are expressed below the high-risk threshold.

[0070] The high-risk threshold may be a maximum fold change in biomarker expression from the control population of cells to the aged population of cells that, if exceeded, is predictive of developing an age-related disease or a cellular condition associated with aging or an age-related disease. For example, if the high-risk threshold for developing the cellular condition of chronic inflammation or an age-related disease associated with chronic inflammation is 0.15, then an aged population of cells that expresses that biomarker at an expression level at least 0.15 times greater the expression level of that biomarker in the control population of cells, the subject has a high risk of developing chronic inflammation or an age-related disease associated with chronic inflammation.

[0071] In some embodiments, the cellular condition associated with aging or age- related disease includes chronic inflammation. In such embodiments, the one or more genes that exhibit differential activation or expression may include one or more of CD28, CD40, CD40LG, CD80, CD86, COL1A1 , COL1 A2, COL3A1 , FN1 , IFNG, IL2, IL2RA, IL2RB, IL2RG, IL4, IL4R, IL5, IL5RA, LAMA5, LAMB1 , LAMB2, LAMC1 , LAMC2, LCK, MIR3606, MIR4758, MIR7846, THBS1 , THBS3, TNFRSF1 A, TNFRSF1 B, VTN, and ZAP70.

[0072] When the method is a method of determining the risk of developing an age- related disease and the biomarkers in (d) and (e) comprise one or more genes associated with chronic inflammation, the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold of about 0.15. In some embodiments, the high-risk threshold is 0.21 .

[0073] In some embodiments, the cellular condition associated with aging or age- related disease includes cellular senescence. In such embodiments, the one or more genes that exhibit differential activation or expression may include one or more of ATM, ATR,CDKN1 A, CDKN2A, CHEK1 , CHEK2, CTC1 , ERCC1 , MIR21 , MME, PLA2R1 , ROMO1 , SERPINE1 , TERT, TP53, WNT16, and WRN.

[0074] When the method is a method of determining the risk of developing an age- related disease and the biomarkers in (d) and (e) comprise one or more genes associated with cellular senescence, the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold of about 0.25. In some embodiments, the high-risk threshold is 0.29.

[0075] In some embodiments, the cellular condition associated with aging or age- related disease includes altered intracellular communication. In such embodiments, the one or more genes that exhibit differential activation or expression may include one or more of ACTB, ACTG1 , ACTN1 , ACTN2, ACTN3, ACTN4, AFDN, ANG, ARHGEF6, CADM1 , CADM2, CADM3, CASK, CD151 , CD2AP, CD47, CDH1 , CDH10, CDH11 , CDH12, CDH13, CDH15, CDH17, CDH18, CDH2, CDH24, CDH3, CDH4, CDH5, CDH6, CDH7, CDH8, CDH9, CLDN1 , CLDN10, CLDN11 , CLDN12, CLDN14, CLDN15, CLDN16, CLDN17, CLDN18, CLDN19, CLDN2, CLDN20, CLDN22, CLDN23, CLDN3, CLDN4, CLDN5, CLDN6, CLDN7, CLDN8, CLDN9, COL17A1 , CRB3, CTNNA1 , CTNNB1 , CTNND1 , DST, F1 1 R, FBLIM1 , FERMT2, FLNA, FLNC, FYB1 , FYN, GRB2, ILK, IQGAP1 , ITGA6, ITGB1 , ITGB4, JUP, KIRREL1 , KIRREL2, KIRREL3, KRT14, KRT5, LAMA3, LAMB3, LAMC2, LIMS1 , LIMS2, MAGI2, NCK1 , NCK2, NECTIN1 , NECTIN2, NECTIN3, NECTIN4, NPHS1 , NPHS2, PALS1 , PARD3, PARD6A, PARD6B, PARD6G, PARVA, PARVB, PATJ, PIK3CA, PIK3CB, PIK3R1 , PIK3R2, PLEC, PRKCI, PTK2, PTK2B, PTPN1 1 , PTPN6, PVR, PXN, RSU1 , SDK1 , SDK2, SFTPA1 , SFTPA2, SFTPD, SIRPA, SIRPB1 , SIRPG, SKAP2, SPTAN1 , SPTBN1 , SRC, TESK1 , TYROBP, VASP, and WASL.

[0076] When the method is a method of determining the risk of developing an age- related disease and the biomarkers in (d) and (e) comprise one or more genes associated with altered intracellular communication, the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold of about 0.05. In some embodiments, the high-risk threshold is 0.07.

[0077] In some embodiments, the cellular condition associated with aging or age- related disease includes stem cell exhaustion. In such embodiments, the one or more genes that exhibit differential activation or expression may include one or more of NLIPR1 , ENPP5, GPR183, CD38, NEO1 , FHL1 , PBX3, ALCAM, ALDH1A1 , EBI3, DHRS3, PLEK, CD37, CLU, EHD3, CPNE8, PROP, CD86, SULT1 A1 , EFNA1 , SATB1 , PLSCR1 , GADD45G, TGM2, RORC, BMPR1A, GEM, CYSLTR2, RASSF4, LPL, DSG2, TRIM47, STOM, IL15, TM6SF1 , RNASE6, MMP2, ARHGAP30, SLAMF1 , NPDC1 , NDRG1 , ABAT, DENND5B, TSC22D1 , ANXA6, MEF2C, CYTIP, MCM7, PERP, THBD, LAMP2, CYB561 , PLAC8, LST1 , TMEM176A, LPAR6, TC2N, PROCR, FLT3, CAVIN2, MMP14, JUN, EGR1 , ID2, BCL6, S100A6, IL12RB2, MGST1 , ZFP36, CSF2RB, LSR, ECT2, MYO1 E, SERPINB8, CXCL16, PPP1 R16B, LSP1 , TNFSF10, CD9, PLA2G4A, DHX40, EVC, LGALS1 , NDN, SELL, MLLT3, ANXA2, OXR1 , GSTM1 , BTG2, CTSS, ACSL4, SOCS2, MLEC, SEMA7A, PLXDC2, RFC2, EXOC6B, MCM5, GPX3, TOX, LY6E, CD63, RDH10, PLCL1 , PTGER4, MAF, VMP1 , RAB34, TBC1 D8, DDR1 , AMPD3, SYK, ANTXR2, LDHD, PDGFD, ACPP, CAMK1 D, PRNP, and PHACTR1.

[0078] When the method is a method of determining the risk of developing an age - related disease and the biomarkers in (d) and (e) comprise one or more genes associated with stem cell exhaustion, the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold of about 0.25. In some embodiments, the high-risk threshold is 0.30.

[0079] In some embodiments, the cellular condition associated with aging or age- related disease includes deregulated nutrient sensing. In such embodiments, the one or more genes that exhibit differential activation or expression may include one or more of ADIPOR1 , AGT, AHSG, APPL2, ATP2B1 , BGLAP, C1QTNF12, ECHDC3, ENPP1 , ERFE, ESRRA, GKAP1 , GNAI2, GPLD1 , GPR21 , GRB10, GRB14, GRB7, GSK3A, IGF2, IL1 B, INPP5K, INS, IRS1 , KANK1 , LEP, LPL, MIR103A1 , MIR107, MIR1271 , MIR15B, MIR195, MSTN, MYO1 C, NCK1 , NCOA5, NR1 H4, NUCKS1 , OSBPL8, PID1 , PIP4K2A, PIP4K2B, PIP4K2C, PRKAA1 , PRKCB, PRKCD, PRKCQ, PRKCZ, PTPN1 , PTPN1 1 , PTPN2, PTPRE, RPS6KB1 , SERPINA12, SIRT1 , SLC27A4, SNX5, SOCS1 , SOCS3, SORBS1 , SORL1 , SRC, TNS2, TRIM72, TSC2, USO1 , and ZBTB7B.

[0080] When the method is a method of determining the risk of developing an age- related disease and the biomarkers in (d) and (e) comprise one or more genes associated with deregulated nutrient sensing, the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold of about -0.08. In some embodiments, the high-risk threshold is -0.85.

[0081] In some embodiments, the cellular condition associated with aging or age- related disease includes loss of proteostasis garbaging. In such embodiments, the one or more genes that exhibit differential activation or expression may include one or more of AFG3L2, AHSP, AIP, AIPL1 , APCS, CALR, CALR3, CANX, CCDC115, CCT2, CCT3, CCT4, CCT5, CCT6A, CCT6B, CCT7, CCT8, CCT8L1 P, CCT8L2, CDC37, CDC37L1 , CHAF1 A, CHAF1 B, CLGN, CLPX, CLU, CRYAA, CRYAB, DNAJA1 , DNAJA2, DNAJA3, DNAJA4, DNAJB1 , DNAJB11 , DNAJB13, DNAJB2, DNAJB3, DNAJB4, DNAJB5, DNAJB6, DNAJB7, DNAJB8, DNAJC4, ERLEC1 , ERN1 , ERN2, ERO1 B, GRPEL1 , GRPEL2, HEATR3, HSP90AA1 , HSP90AA2P, HSP90AA4P, HSP90AA5P, HSP90AB1 , HSP90AB2P, HSP90AB3P, HSP90AB4P, HSP90B1 , HSP90B2P, HSPA13, HSPA14, HSPA1 A, HSPA1 B, HSPA1 L, HSPA2, HSPA5, HSPA6, HSPA7, HSPA8, HSPA9, HSPB6, HSPD1 , HSPE1 , HTRA2, HYOU1 , LMAN1 , MKKS, NACA, NACA2, NACA4P, NACAD, NAP1 L4, NDUFAF1 , NPM1 , NUDC, NUDCD2, NUDCD3, PDRG1 , PET100, PFDN1 , PFDN2, PFDN4, PFDN5, PFDN6, PPIA, PPIB, PTGES3, RP2, RUVBL2, SCAP, SCG5, SERPINH1 , SHQ1 , SIL1 , SPG7, SRSF10, SRSF12, SYVN1 , TAPBP, TCP1 , TIMM10B, TMEM67, TOMM20, TOR1 A, TRAP1 , TTC1 , TUBB4B, UGGT1 , UGGT2, and VBP1 .

[0082] When the method is a method of determining the risk of developing an age- related disease and the biomarkers in (d) and (e) comprise one or more genes associated with loss of proteostasis garbaging, the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold of about -0.80. In some embodiments, the high-risk threshold is -0.87.

[0083] In some embodiments, the cellular condition associated with aging or age- related disease includes epigenetic alterations. In such embodiments, the one or more genes that exhibit differential activation or expression may include one or more of ACTB, AEBP2, ARID4B, BAZ1 B, BAZ2A, CBX3, CCNH, CDK7, CHD3, CHD4, DDX21 , DEK,DNMT1 , DNMT3A, DNMT3B, DNMT3L, EED, EHMT2, EP300, ERCC2, ERCC3, ERCC6, EZH2, GATAD2A, GATAD2B, GSK3B, GTF2H1 , GTF2H2, GTF2H3, GTF2H4, GTF2H5, H2AB1 , H2AC14, H2AC20, H2AC4, H2AC6, H2AC7, H2AC8, H2AJ, H2AX, H2AZ1 , H2AZ2, H2BC1 , H2BC10, H2BC11 , H2BC12, H2BC13, H2BC14. H2BC15, H2BC17, H2BC21. H2BC3. H2BC4, H2BC5, H2BC6, H2BC7, H2BC8, H2BC9, H2BS1 , H2BU1 , H3-3A, H3-3B, H3C1 , H3C10, H3C1 1 , H3C12, H3C13, H3C14, H3C15, H3C2, H3C3, H3C4, H3C6, H3C7, H3C8, H4-16, H4C1 , H4C1 1 , H4C12, H4C13, H4C14, H4C15, H4C2, H4C3, H4C4, H4C5, H4C6, H4C8, H4C9, HDAC1 , HDAC2, JARID2, KAT2A, KAT2B, MBD2, MBD3, MNAT1 , MTA1 , MTA2, MTA3, MTF2, MYBBP1A, MYO1 C, ,PHF1 , PHF19, POLR1A, POLR1 B, POLR1 C, POLR1 D, POLR1 E, POLR1 F, POLR1 G, POLR1 H, POLR2E, POLR2F, POLR2H, POLR2K, POLR2L, RBBP4, RBBP7, RRP8, SAP130, SAP18, SAP30, SAP30BP, SAP30L, SF3B1 , SIN3A, SIN3B, SIRT1 , SMARCA5, SUDS3, SUV39H1 , SUZ12, TAF1 A, TAF1 B, TAF1 C, TAF1 D, TBP, TDG, TET1 , TET2, TET3, TTF1 , UBTF, and UHRF1 .

[0084] When the method is a method of determining the risk of developing an age- related disease and the biomarkers in (d) and (e) comprise one or more genes associated with epigenetic alterations, the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold of about -0.10. In some embodiments, the high-risk threshold is -0.13.

[0085] In some embodiments, the cellular condition associated with aging or age- related disease includes telomere attrition. In such embodiments, the one or more genes that exhibit differential activation or expression may include one or more of ABL1 , ACD, AKT1 , ATM, BLM, CCND1 , CDKN1 B, DKC1 , E2F1 , EGF, EGFR, ESR1 , FOS, HDAC1 , HDAC2, HNRNPC, HSP90AA1 , HUS1 , IFNAR2, IFNG, IL2, IRF1 , JUN, MAPK1 , MAPK3, MAX, MRE1 1 , MTOR, MXD1 , MYO, NBN, NCL, NFKB1 , NR2F2, PARP2, PINX1 , POT1 , PTGES3, RAD1 , RAD50, RAD9A, RBBP4, RBBP7, RPS6KB1 , SAP18, SAP30, SIN3A, SIN3B, SMAD3, SMG5, SMG6, SP1 , SP3, TERF1 , TERF2, TERF2IP, TERT, TGFB1 , TINF2, TNKS, UBE3A, WRN, WT1 , XRCC5, XRCC6, YWHAE, and ZNFX1 .

[0086] When the method is a method of determining the risk of developing an age- related disease and the biomarkers in (d) and (e) comprise one or more genes associated with loss of telomere attrition, the subject is identified as having a high risk for developingthe age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold of about -0.05. In some embodiments, the high-risk threshold is -0.07.

[0087] In some embodiments, the cellular condition associated with aging or age- related disease includes mitochondrial dysfunction. In such embodiments, the one or more genes that exhibit differential activation or expression may include one or more of CAMK4, CREB1 , ESRRA, ABPA, GABPB1 , GABPB1 -IT1 , HCFC1 , MTERF1 , MTERF3, MYEF2, NRF1 , POLRMT, PPARGC1 A, PPARGC1 B, PPP3CA, PPRC1 , SP1 , TFAM, TFB1 M, and TFB2M.

[0088] When the method is a method of determining the risk of developing an age- related disease and the biomarkers in (d) and (e) comprise one or more genes associated with loss of mitochondrial dysfunction, the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (d) are expressed at or greater than a high-risk threshold of about -0.10. In some embodiments, the high-risk threshold is -0.14.

[0089] In some embodiments, the method determines the aging rate of the subject based on the identified biomarkers and / or cellular conditions associated with aging, n some embodiments, the method determines that the subject ages at a faster rate of aging, relative to an average rate of aging. In other embodiments, the method determines that the subject ages at an average rate of aging.

[0090] In some embodiments, the methods include correlating the set of biomarkers associated with aging or the cellular changes associated with aging one or more lifestyle changes and / or dietary supplements to reduce the rate of aging in the subject and developing interventional plan to provide the one or more interventions to the subject to reduce the rate of aging in the subject.

[0091] In some embodiments, the methods include correlating the set of biomarkers associated with age-related disease with one or more interventions to prevent or delay onset of the age-related disease in the subject and developing a treatment plan to provide the one or more intervention to the subject to prevent or delay onset of the age-related disease. The one or more interventions may include a pharmaceutical agent and / or a lifestyle change.Suitable pharmaceutical agents may be determined based on the identified biomarkers and may vary between subjects.

[0092] The one or more interventions may include one or more lifestyle changes, dietary supplements, and / or pharmaceutical agents. In some embodiments, the dietary supplements comprise one or more vitamins, minerals, botanicals, herbs, botanical compounds, amino acids, and live microbials. In some embodiments, the dietary supplements comprise one or more nutraceuticals and / or nutritional supplements, such as, for example Quercetin, Nattokinase, CoQ10, fisetin, magnesium, nicotinamide mononucleotide (NMN), N-acetyl cysteine, alpha ketoglutaric acid, omega-3 fatty acids, collagen, raspberry ketones, green tea leaf extract, vitamin D3, vitamin B12, alpha-lipoic acid, probiotics, prebiotics, echinacea, garcinia cambogia, iron, a multivitamin, and calcium citrate.

[0093] In some embodiments, the one or more lifestyle changes may be determined based on the identified biomarkers and may vary between subjects. In some embodiments, the lifestyle changes include one or more of increasing activity level, changing the method of activity (e.g., increasing the ratio of weight training to cardiovascular exercise or replacing steady-state cardiovascular exercise with high intensity interval training) increasing sleep duration, decreasing blue light exposure, increasing protein intake, decreasing sugar intake, performing heat and / or cold shock therapy, and performing mindfulness exercises, not smoking, having moderate alcohol consumption, increasing daily intake of fruits and vegetables, maintaining a healthy body mass index and waist-to-hip ratio, restricting diet, intermittent fasting, adjusted diurnal rhythm of feeding, having a balanced diet, practicing sun protection, managing stress levels, increasing hydration, maintaining social connections, increasing cognitive stimulation, practicing good hygiene and oral care, and having a positive attitude.

[0094] In some embodiments, the age-related disease comprises age-related inflammation. In some embodiments, the age-related disease comprises one or more of ischemic heart disease, Alzheimer’s disease, dementia, Parkinson’s disease, stroke, trachea cancer, bronchus cancer, lung cancer, chronic obstructive pulmonary disease(COPD), lower respiratory infections, colon cancer, rectal cancer, kidney disease, hypertensive heart disease, and diabetes mellitus.Treatment and Interventional Plans

[0095] In other embodiments, the present invention provides an interventional plan for reducing aging rate or to mitigating the effects of aging in a subject. In some embodiments, the interventional plan is prepared by: identifying a set of biomarkers associated with aging in the subject by determining differences in epigenetics, gene activation, and / or gene expression between a population of aged cells derived from the subject and a population of control cells derived from the subject, wherein the population of aged cells is obtained by exposing a first population of cells from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging in the cells, and the population of control cells is obtained by exposing a second population of cells from the subject to normal gravity; and correlating the set of biomarkers associated with aging with one or more one or more interventions to the subject to reduce the rate of aging or to mitigate the effects of aging in the subject. In some embodiments, the one or more interventions include one or more nutraceuticals, lifestyle changes, and / or nutritional supplements.

[0096] In some embodiments, the present technology provides a treatment plan for monitoring, preventing, or delaying onset of an age-related disease in a subject. In some embodiments, the treatment plan is prepared by: identifying a set of biomarkers associated with age-related disease in the subject by determining differences in gene activation or gene expression between a population of aged cells derived from the subject and a population of control cells derived from the subject, wherein the population of aged cells is obtained by exposing a first population of cells from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging in the cells, and the population of control cells is obtained by exposing a second population of cells from the subject to normal gravity; and correlating the set of biomarkers associated with age-related disease with one or more interventions to prevent or delay onset of the age-related disease in the subject.10097] In some embodiments, the treatment plan comprises a plan to provide one or more interventions, such as, for example, a dietary supplement, pharmaceutical agent, and / or a lifestyle change, to the subject to prevent or delay onset of the age-related disease.

[0098] In some embodiments, the treatment plan or the interventional plan is prepared by first identifying one or more cellular changes associated with aging or age-related disease and then identifying one or more interventional agents that induce one or more cellular changes inverse to the one or more cellular changes associated with aging or age-related disease by performing an in silico or in vitro compound screen. The interventional agents may comprise one or more pharmaceutical agents, nutraceuticals, and / or nutritional supplements.

[0099] In some embodiments, the treatment plan or interventional plan comprises a plan to provide a pharmaceutical agent to the subject. Non-limiting examples of pharmaceutical agents that may be applied to the treatment and / or interventional plan include hormetins, senolytics / senostatics, anti-inflammatory drugs, antifibrotic agents, neurotrophic factors, factors preventing the impairment of barrier function, immunomodulators, metabiotics, and prebiotics. In some embodiments, the pharmaceutical agent comprises one or more of 17-a estradiol, aspirin, epitalon, human growth hormone (HGH), metformin, NAD+ precursors, nordihydroguaiaretic acid, rapamycin, senolytic agents, sirtuin activators, telomerase activators, testosterone, thymosin beta-4, probiotics, prebiotics, metabiotics, metformin, rapamycin, and enterosorbents.

[0100] In some embodiments, the treatment plan or interventional plan comprises a plan to provide a nutraceutical to the subject. Non-limiting examples of nutraceuticals that may be applied to the treatment and / or interventional plan include acarbose, ashwagandha, B complex, B12-methylcobalamin, berberine, C vitamin, Ca-Alpha Ketoglutarat, cocoa flavanols, dehydroepiandrosterone (DHEA), E vitamin, eicosapentaenoic acid (EPA), garlic, ginger root, glucosamine sulphate, glycine, hyaluronic Acid, iodine (e.g., as potassium iodide), L-theanine, lithium, (e.g., as lithium orotate), lycopene, lysine, malate, nicotinamide riboside, pea protein, proferrin, pterostilbene, taurine, turmeric, ubiquinol, vitamin D-3, zeaxanthin, zinc, resveratrol, quercetin, nattokinase, CoQ10, fisetin, magnesium,-SO-nicotinamide mononucleotide (NMN), N-acetyl cysteine, alpha ketoglutaric acid, and omega- 3 fatty acids.

[0101] In some embodiments, the treatment plan or interventional plan comprises a plan to provide a nutritional supplement to the subject. Non-limiting examples of nutritional supplements that may be applied to the treatment and / or interventional plan include acarbose, ashwagandha, B complex, B12-methylcobalamin, berberine, C vitamin, Ca-Alpha Ketoglutarat, cocoa flavanols, dehydroepiandrosterone (DHEA), E vitamin, eicosapentaenoic acid (ERA), garlic, ginger root, glucosamine sulphate, glycine, hyaluronic Acid, iodine (e.g., as potassium iodide), L-theanine, lithium, (e.g., as lithium orotate), lycopene, lysine, malate, nicotinamide riboside, pea protein, proferrin, pterostilbene, taurine, turmeric, ubiquinol, zeaxanthin, zinc, resveratrol, collagen, raspberry ketones, green tea leaf extract, vitamin D3, vitamin B12, alpha-lipoic acid, probiotics, prebiotics, echinacea, garcinia cambogia, iron, multivitamins, and calcium citrate.

[0102] In some embodiments, the treatment plan or interventional plan comprises a plan to provide a lifestyle change to the subject. Non-limiting examples of lifestyle changes that may be applied to the treatment and / or interventional plan include increasing activity level, changing the method of activity (e.g., increasing the ratio of weight training to cardiovascular exercise or replacing steady-state cardiovascular exercise with high intensity interval training) increasing sleep duration, decreasing blue light exposure, increasing protein intake, decreasing sugar intake, performing heat and / or cold shock therapy, performing mindfulness exercises, not smoking, having moderate alcohol consumption, increasing daily intake of fruits and vegetables, maintaining a healthy body mass index and waist-to-hip ratio, restricting diet, intermittent fasting, adjusted diurnal rhythm of feeding, having a balanced diet, practicing sun protection, managing stress levels, increasing hydration, maintaining social connections, increasing cognitive stimulation, practicing good hygiene and oral care, and having a positive attitude.

[0103] The referenced patents, patent applications, and scientific literature referred to herein are hereby incorporated by reference in their entirety as if each individual publication, patent, or patent application were specifically and individually indicated to be incorporated by reference. Any conflict between any reference cited herein and the specific teachings ofthis specification shall be resolved in favor of the latter. Likewise, any conflict between an art-understood definition of a word or phrase and a definition of the word or phrase as specifically taught in this specification shall be resolved in favor of the latter.EXAMPLES

[0104] The following examples are intended to illustrate various embodiments of the present technology. As such, the specific embodiments discussed are not to be construed as limitations on the scope of the present technology. It will be apparent to one skilled in the art that various equivalents, changes, and modifications may be made without departing from the scope of present technology, and it is understood that such equivalent embodiments, are to be included herein. Further, all references cited herein are hereby incorporated by reference in their entirety, as if fully set forth herein.Example 1: Pilot Study

[0105] A study was performed on six healthy subject to test the ability of accelerated aging induced by simulated microgravity to recapitulate and predict individual variations in cellular aging mechanisms. The subject information is provided in Table 1 .Table 1. Subject Information.

[0106] FIG. 1 is a schematic representation of the study overview. As shown in FIG. 1 , the subjects had blood drawn at two time points (Ti and T2) 2-3 years apart. Each of the T1 samples was the split into two portions, one as a control, i.e., exposed to normal gravity (T1- c), and one that was exposed to simulated microgravity for 25 hours (TI-HG). After 25 hours of culturing with (T-I-HG) or without (Ti-c & T2) exposure to simulated microgravity, gene expression analysis was performed with bulk RNA-seq and qPCR.

[0107] The cells were cultured according to the following protocol: standard aseptic techniques were used for culturing the cells. Cells were thawed in a pre-warmed water bath at 37 °C and were transferred in a sterile 50-mL (milliliter) centrifugal tube containing 15 ml_ of sterile cultivation medium pre-warmed at 37 °C. The cultivation medium used was RPMI (Roswell Park Memorial Institute) 1640 medium amended with 10% (v:v) heat inactivated fetal bovine serum with additional supplements, which are listed in Table 2, below. The cryovial was washed twice with 2 ml_ pre-warmed cultivation medium. The final volume was adjusted to 45 ml_ with the addition of sterile pre-warmed medium and the cells were then centrifuged for 10 minutes at 300 x g (acceleration of gravity). Then, the supernatant was removed, and fresh sterile pre-warmed medium was added to a final volume of 45 ml_. The whole procedure was repeated twice. After the final wash, cells were resuspended in fresh sterile pre-warmed cultivation medium in a concentration of approximately 1 x106cells per mL. The cells were incubated at 37 °C in 5% CO2 atmosphere for approximately 4 hours prior of transferring to a sterile rotary vessel. Then, the vessel was placed on the rotary cell cultivation system and was incubated for 25 hours at 37 °C with 5% CO2 at 1 -20 rpm.Table 2. Cultivation Medium Supplements* HEPES is (4-(2-hydroxyethyl)-1 -piperazineethanesulfonic acid)

[0108] In the qPCR analysis, gene expression of 11 genes (ATXN1 , CCL2, CCR7, GPR68, IL1 B, IL7R, MMP9, NCAM1 , ORAI2, S100A9, and THBS1 ) from diverse pathways that were selected based on prior studies implicating changes in their gene expression in aging, age-related inflammation, and / or immune cell response to simulated microgravity were quantified. Table 2 provides the genes, associated cellular conditions, and the change in expression indicating a high-risk threshold for developing an age-related disease associated with such conditions.Table 3. Genes associated with aging

[0109] Intra-subject comparison of q-RT-PCR data from each of Subject Nos. 1 -4 revealed a strong correlation between the distribution of normalized gene expression levels from TI-MG and T2. Gene expression levels were ubiquitin conjugating enzyme E2 D2 (UBE2D2)-normalized using the delta-delta-Ct method, where Ct stands for cycle threshold. There was a stronger correlation in normalized expression values between TI-MG & T2 than between T1-MG & Ti-c or between Ti-c & T2 (FIGS. 2A and 2B), suggesting that simulated microgravity is able to induce changes in gene expression that occur during aging. Furthermore, FIG. 3 shows that gene expression levels (UBE2D2-normalized using the delta-delta-Ct method) in the T-i-pG samples were not strongly correlated between subjects, suggesting that these simulated-microgravity-induced changes are specific to, and predictive of, individual variation in aging biology.

[0110] mRNA enriched sequencing on samples from all six subjects was also performed. For each of the subjects, 4 samples: Ti-c, TI-UG, T2, and T2-UG sample. The T2-11G samples were used for quality control and batch correction but were not used in further analyses.

[0111] Reads from each sample were aligned to the human genome using standard computational methods, and then quantified as Fragments Per Kilobase Million (FPKM) and gene counts. Gene counts were used for differential expression analyses, FPKM were used for all other analyses. An additional upper quartile normalization was applied to the FPKM (FPKM-UQ), and then the values were log transformed with a pseudocount of 1 . Batch correction was performed with the ComBat algorithm from the sva R package. The pathway expression for each Hallmark of Aging were quantified by using the ssgsea algorithm on the normalized and batch corrected FPKM-UQ gene expression values from each sample.

[0112] Nine hallmarks of aging (chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, deregulated nutrient sensing, loss of proteostasis garbaging, epigenetic alterations, telomere attrition, and mitochondrial dysfunction) were quantified using pathways / gene sets from databases such as REACTOME and gene ontology, as well as from gene sets published in academic literature.

[0113] First, the expression levels of the hallmarks of aging in the T-i-c, TI-UG , and T2 groups were compared. As shown in FIG. 4, the TI-UG group was perturbed from the Ti-c group in the same direction as the T2 group was perturbed from the Ti-c group in eight of the nine of the hallmarks of aging (all except mitochondrial dysfunction). Some hallmarks, such as inflammation, were much more strongly perturbed in the TI-UG group than the T2 group, although they were perturbed in the same direction. For example, based on the difference between TI-UG and Ti c values, which was above the high-risk threshold of 0.21 , subject 5 demonstrated a risk change for inflammation. This suggests that the simulated microgravity may disproportionally impact some hallmarks of aging compared to others.

[0114] Next, for each hallmark, the correlation between Ti-c vs T2 with the correlation between TI-UG VS T2 were compared. As shown in FIG. 5, there was a stronger correlation between TI -UG vs T2 than between Ti c vs T2 for six of the nine hallmarks. This shows thatthe accelerated aging induced by simulated microgravity retains the individual biological variability that occurs during simulated microgravity.

[0115] These results show that simulated microgravity perturbs cells in the same direction as natural biological aging and increase the correlation of cellular behavior with the state of older cells. This provides strong evidence that simulated microgravity allows for an improved prediction of the next several years of an individual’s biological aging mechanism.Example 2: Magnetic Levitation of PBMCs to Investigate Effects of Microgravity

[0116] Cryopreserved PBMCs were thawed, resuspended in supplemented Roswell Park Memorial Institute (RPMI) 1640 media containing interleukin 2 (IL-2), and incubated under standard conditions (37°C, 5% CO2) for 90 minutes. Following viability assessment, PMBCs were suspended at a 2 million / mL concentration in cell culture media with 70 mM paramagnetic solution. Then, 30 pL of PBMC sample was loaded into glass capillaries and inserted into a magnetic levitation device including (i) two permanent magnets (50-mm length, 2-mm width, and 5-mm height) with the same poles facing each other, (ii) a channel (1 -mm x 1 -mm cross-section, 50-mm length and 0.2-mm wall thickness) between the two magnets, (iii) tilted side mirrors to measure the levitation height of cells inside the channel using a microscope, and (iv) polymethyl methacrylate (PMMA) pieces to hold components (i)-(iii) together (FIG. 6). The levitation device containing the PBMCs was then incubated under standard culture conditions. Multiple capillaries were incubated for 24 hours to ensure sufficient cell numbers for downstream analysis (n=5). FIGS. 7A and 7B are images of pre- and post-incubation PBMCs in the magnetic levitation device. Pre-incubation imaging showed PBMCs dispersed throughout the capillary tube (FIG. 7A); whereas post-incubation imaging revealed PBMC clustering patterns (FIG. 7B),

[0117] After incubation, the PBMCs were recovered using media and pressurized air, assessed for viability, and processed for total RNA sequencing using Qiagen mRNeasy isolation followed by Nanodrop quantification and Novogene sequencing services.

[0118] As shown in FIG. 8, human PBMCs that were incubated in a magnetic levitation device for 24 hours (magnetically levitated PBMCs) showed a PC1 variance greater than 5,whereas control human PBMCs, which were not incubated at normal gravity for 24 hours (control PBMCs) had a PC1 variance below -5.

[0119] A differential gene expression (DGE) analysis was performed on the magnetically levitated PBMCs and the control PBMCs (total genes = 14230, DE cutoff: padj <0.05 and FC > 1 1.51 ; FIGS. 9 and 10). As depicted in FIG. 9, after magnetic levitation, human PBMCs exhibited downregulation of 557 genes and upregulation of 329 genes. FIG. 10 shows a heatmap overlapping DGEs between control PBMCs and magnetically levitated PBMCs. Specifically, genes with a z-score of less than 0, i.e., 0 to -2, in magnetically levitated PBMCs, had a z-score of greater than 0, i.e., 0 to 2, in control PBMCs; and genes with a z-score of greater than 0, i.e., 0 to 2, in magnetically levitated PBMCs, had a z-score of less than 0, i.e., 0 to -2, in control PBMCs.

[0120] Further, a gene ontology over-enrichment analysis and gene set enrichment analysis of biological pathways and molecular functions associated with aging, as provided in aging related databases including GTEx_Aging_Signatures_2021 ; Aging_ Perterbations_from_GEO_down; and Aging_Perterbations_from_GEO_up were performed on the magnetically levitated PBMCs (FIGS. 1 1 and 12). As shown in FIG. 1 1 , several processes were over-represented in magnetically levitated PBMCs, with inflammatory response, defense response, immune effector process, regulation of immune system process, and innate immune response pathways all having an adjusted p-value (-logio(p- value)) of greater than 6, demonstrating statistically significant over-expression, as determined by over-enrichment analysis. Additionally, FIG. 12 shows that several pathways were enriched in magnetically levitated PBMCs, as determined by GSEA. FIGS. 13A and 13B show the GSEA enrichment analysis of the gene ontology biological processes of B- cell mediated immunity (FIG. 13A) and oxidative phosphorylation (FIG. 13B) in magnetically levitated PBMCs.

[0121] Further, an Ingenuity Pathway Analysis of ingenuity canonical pathways was performed on magnetically levitated PBMCs, which demonstrated that several canonical pathways associated with aging were upregulated in magnetically levitated PBMCs (FIG. 14A). Activation z-scores of the various pathways in magnetically levitated PBMCs (ML PBMCs) and PBMCs subjected to microgravity (pG PBMCs) are provided in FIG. 14B. Z-scores greater than 0 indicate predicted activation of the corresponding pathway and z- scores less than 0 indicate repression of the corresponding pathway. Accordingly, as shown in FIG. 14B, the majority of pathways that were repressed in PBMCs subjected to microgravity were also suppressed in magnetically levitated PBMCs.

[0122] Additionally, GSEA analyses of 96 upregulated core genes (FIG. 15A) and of 1 14 downregulated core genes (FIG. 15B) in PBMCs exposed to simulated microgravity were performed.

[0123] Finally, FIG. 16 shows the overall levitation-induced transcriptomic changes enriched in aging hallmark pathways, as determined by all of the above analyses. As shown, magnetic levitation resulted in notable transcriptomic changes in certain hallmarks of aging, e.g., cellular senescence, altered intercellular communication, and loss of proteostasis grabaging, but not in others, e.g., telomere attrition, stem cell exhaustion, genomic instability, and epigenetic alterations. Moreover, although the data summarized in FIG. 16 shows that a hallmark was altered, it does not specify the directionality of the alteration.

[0124] Various embodiments of the present technology are set forth herein below in paragraphs

[0125] -

[0204] :

[0125] Embodiment 1 . A method of determining a risk of a subject developing an age- related disease associated with one or more cellular conditions selected from the group consisting of chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomere attrition, in the subject, the method comprising the steps of:(a) receiving aged data obtained from bulk RNA-sequencing and qPCR performed on a population of aged cells produced by exposing a first population of cells from the subject to simulated microgravity for 25 hours;(b) receiving control data obtained from bulk RNA-sequencing and qPCR performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in gene activation or gene expression based on the comparing in (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with one or more of chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomere attrition;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having:(A) a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the age-related disease if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).

[0126] Embodiment 2. A method of determining a risk of a subject developing an age- related disease, the method comprising the steps of:(a) receiving aged data obtained from bulk RNA-sequencing and qPCR performed on a population of aged cells produced by exposing a first population of cells from the subject to simulated microgravity for 25 hours;(b) receiving control data obtained from bulk RNA-sequencing and qPCR performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in gene activation or gene expression based on the comparing in (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomere attrition;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having:(A) a high risk for developing the age-related disease associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomere attrition if the biomarkers in (g) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the age-related disease associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomere attrition if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).

[0127] Embodiment 3. The method of embodiment 1 or 2, wherein the high-risk threshold is 0.21 , and wherein the biomarkers in (g) comprise one or more genes associated with chronic inflammation and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high- risk threshold.

[0128] Embodiment 4. The method of embodiment 1 or 2, wherein the high-risk threshold is 0.29, and wherein the biomarkers in (g) comprise one or more genes associated with cellular senescence and the subject is identified as having a high risk for developingthe age-related disease if the biomarkers in (g) are expressed at or greater than the high- risk threshold.

[0129] Embodiment 5. The method of embodiment 1 or 2, wherein the high-risk threshold is 0.07, and wherein the biomarkers in (g) comprise one or more genes associated with altered intracellular communication and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0130] Embodiment 6. The method of embodiment 1 or 2, wherein the high-risk threshold is 0.30, and wherein the biomarkers in (g) comprise one or more genes associated with stem cell exhaustion and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high- risk threshold.

[0131] Embodiment 7. The method of embodiment 1 or 2, wherein the high-risk threshold is -0.87, and wherein the biomarkers in (g) comprise one or more genes associated with loss of proteostasis garbaging and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0132] Embodiment 8. The method of embodiment 1 or 2, wherein the high-risk threshold is -0.13, and wherein the biomarkers in (g) comprise one or more genes associated with epigenetic alterations and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk.

[0133] Embodiment 9. The method of embodiment 1 or 2, wherein the high-risk threshold is -0.07, and wherein the biomarkers in (g) comprise one or more genes associated with telomere attrition and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0134] Embodiment 10. A method of determining a risk of a subject developing a cellular condition associated with aging selected from chronic inflammation, cellularsenescence, altered intracellular communication, and loss of proteostasis garbaging in a subject, the method comprising:(a) receiving aged data obtained from one or more analytical techniques selected from differential gene expression (DGE) analysis, gene ontology over-expression analysis, gene set expression analysis (GSEA), and ingenuity pathway analysis (IPA) performed on a population of aged cells produced by exposing a first population of cells from the subject to magnetic levitation for 24 hours;(b) receiving control data obtained from one or more analytical technique selected from DGE, gene ontology over-enrichment analysis, GSEA, and IPA performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in activation or enrichment of one or more biological pathways or functions (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, and loss of proteostasis garbaging;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having:(A) a high risk for developing the cellular condition associated with aging if the biomarkers in (g) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the cellular condition associated with aging if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).

[0135] Embodiment 11. A method of determining a risk of a subject developing a cellular condition associated with aging, the method comprising:(a) receiving aged data obtained from one or more analytical techniques selected from differential gene expression (DGE) analysis, gene ontology over-expression analysis, gene set expression analysis (GSEA), and ingenuity pathway analysis (IPA) performed on a population of aged cells produced by exposing a first population of cells from the subject to magnetic levitation for 24 hours;(b) receiving control data obtained from one or more analytical technique selected from DGE, gene ontology over-enrichment analysis, GSEA, and IPA performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in activation or enrichment of one or more biological pathways or functions (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, and loss of proteostasis garbaging;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having:(A) a high risk for developing the cellular condition associated with aging selected from chronic inflammation, cellular senescence, altered intracellular communication, and loss of proteostasis garbaging if the biomarkers in (g) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the cellular condition associated with aging selected from chronic inflammation, cellular senescence, altered intracellularcommunication, and loss of proteostasis garbaging if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).

[0136] Embodiment 12. A method of identifying one or more interventions useful to reduce or prevent aging in a subject, comprising: exposing a first population of cells derived from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; analyzing the population of aged cells to obtain a set of aged data; exposing a second population of cells derived from the subject to normal gravity to obtain a population of control cells; analyzing the population of control cells to obtain a set of control data; comparing the aged data and the control data to determine differences in gene activation or gene expression between the population of aged cells and the population of control cells; based on the determined differences, identifying:(i) a set of biomarkers associated with aging, and / or(ii) a cellular condition associated with aging; correlating the set of biomarkers and / or cellular condition associated with aging with one or more interventions to reduce the rate of aging in the subject; and developing an interventional plan to provide the one or more interventions to the subject to reduce the rate of aging in the subject.

[0137] Embodiment 13. The method of embodiment 12, further comprising determining, based on the identified biomarkers and / or cellular conditions associated with aging, that the subject ages at a faster rate of aging, relative to an average rate of aging.

[0138] Embodiment 14. The method of embodiment 12, further comprising determining, based on the identified biomarkers and / or cellular conditions associated with aging, that the subject ages at an average rate of aging.

[0139] Embodiment 15. A method of preventing or delaying onset of an age-related disease in a subject, comprising: exposing a first population of cells derived from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; analyzing the population of aged cells to obtain a set of aged data; exposing a second population of cells derived from the subject to normal gravity to obtain a population of control cells; analyzing the population of control cells to obtain a set of control data; comparing the aged data and the control data to determine differences in gene activation or gene expression and / or differences in activation or enrichment of biological pathways or functions between the population of aged cells and the population of control cells; based on the determined differences, identifying a set of biomarkers associated with age-related disease; correlating the set of biomarkers associated with age-related disease with one or more therapies to prevent or delay onset of the age-related disease in the subject; and developing a treatment plan to provide the one or more interventions to the subject to prevent or delay onset of the age-related disease.

[0140] Embodiment 16. The method of any one of embodiments 12-15, further comprising: analyzing the first population of cells at regular time intervals while exposing the cells to simulated microgravity to obtain time-interval aging data;analyzing the second population of cells at the regular time intervals while exposing the cells to normal gravity to obtain time-interval control data; and comparing the time-interval aging data to the time-interval control data to identify one or more biomarkers of age-related disease.

[0141] Embodiment 17. The method of embodiment 16, wherein analyzing the first and second population of cells at the regular time interval comprises analyzing the cells hourly.

[0142] Embodiment 18. The method of any one of embodiments 12-15, further comprising: splitting the first population of cells into a first subpopulation of cell and a second subpopulation of cells; exposing the first and second subpopulation of cells to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; returning the first subpopulation of cells to normal gravity while the second subpopulation of cells stays at simulated microgravity; and taking time-series measurements of the first subpopulation of cells at normal gravity to determine molecular mechanisms of recovery to the induced accelerated aging.

[0143] Embodiment 19. The method of embodiment 18, wherein analyzing the first subpopulation of cells at normal gravity comprises taking time-series measurements of the cells to identify biomarkers associated with age-related disease.

[0144] Embodiment 20. The method of embodiment 19, wherein the time-series measurements comprise taking measurements of the cells at about 24 hours, 36 hours, 48 hours, 72 hours, and 96 hours after returning the cells to normal gravity.

[0145] Embodiment 21. The method of any one of embodiments 18-20, further comprising: identifying one or more interventional agents that mimic the molecular mechanism of recovery by performing an in silico compound screen; and reincluding the one or more interventional agents in the treatment plan or the interventional plan prepared for the subject.

[0146] Embodiment 22. The treatment plan of embodiment 21 , wherein the interventional agent further comprises one or more pharmaceutical agents, nutraceuticals, or nutritional supplements.

[0147] Embodiment 23. The method of any one of embodiments 12-22, wherein analyzing the population of aged cells and the population of control cells further comprises using transcriptomics to perform a transcriptome analysis, using epigenomics to perform an epigenome analysis, using metabolomics to perform a metabolome analysis, or using proteomics to perform a proteome analysis on the population of aged cells and the population of control cells.

[0148] Embodiment 24. The method of embodiment 23, wherein the transcriptome analysis further comprises analyzing one or more of total RNA, enriched mRNA, enriched non-coding RNA, or enriched small RNA.

[0149] Embodiment 25. The method of embodiment 23 or embodiment 24, wherein the transcriptome analysis further comprises sequencing, quantitative polymerase chain reaction (qPCR), quantitative reverse transcriptase PCR (qRT-PCR), digital PCR (dPCR), digital droplet PCR (ddPCR), Reverse Transcription Loop-mediated Isothermal Amplification (RT-LAMP), Loop-mediated Isothermal Amplification (LAMP), serial analysis of gene expression (SAGE), cap analysis of gene expression (CAGE), northern blot, expression immunoassay, microarrays analysis and / or any method utilizing light intensity, fluorescent signal intensity, stable isotopes, and / or radioactive isotopes to quantify gene expression.

[0150] Embodiment 26. The method of any one of embodiments 23-25, wherein the transcriptome analysis further comprises single-cell transcriptome analysis.

[0151] Embodiment 27. The method of any one of embodiments 23-26, wherein the epigenome analysis further comprises assay for transposase-accessible chromatin using sequencing (ATAC-seq), bisulfite sequencing, chromatin immunoprecipitation sequencing (CHiP-seq), Hi-C epigenome analysis, cleavage under targets and tagmentation (CUT&Tag), and / or cleavage under targets and release using nuclease (CUT&run).-M-

[0152] Embodiment 28. The method of any one of embodiments 23-27, wherein the epigenome analysis further comprises integrated single-cell epigenome analysis.

[0153] Embodiment 29. The method of any one of embodiments 23-28, wherein the metabolome analysis further comprises nuclear magnetic resonance spectroscopy (NMR) and / or mass spectrometry (MS).

[0154] Embodiment 30. The method of embodiment 29, wherein the mass spectrometry comprises Fourier transform ion cyclotron mass spectrometry (FTIC-MS).

[0155] Embodiment 31. The method of any one of embodiments 23-30, wherein the proteome analysis further comprises enzyme-linked immunosorbent assays (ELISA), western blotting, two-dimensional difference gel electrophoresis (2D-DIGE), tandem mass spectrometry, and / or mass spectrometry.

[0156] Embodiment 32. The method of any one of embodiments 12-31 , wherein the first population of cells and the second population of cells each comprise a population of immune cells.

[0157] Embodiment 33. The method of embodiment 32, wherein the populations of immune cells further comprise peripheral blood mononuclear cells (PBMCs).

[0158] Embodiment 34. The method of embodiment 33, wherein the PBMCs further comprise enriched subpopulations of PBMCs.

[0159] Embodiment 35. The method of any one of embodiments 32-34, wherein the PBMCs or subpopulations of PBMCs, are sorted with fluorescence-activated cellular sorting (FACS), microfluidics, density gradient centrifugation, differential centrifugation, paramagnetic beads, levitation technology or a combination of these methods.

[0160] Embodiment 36. The method of any one of embodiments 15 to 30, wherein the age-related disease comprises age-related inflammation.

[0161] Embodiment 37. The method of any one of embodiment 15 to 31 , wherein the age-related disease is selected from ischemic heart disease, Alzheimer’s disease, dementia, Parkinson’s disease, stroke, trachea cancer, bronchus cancer, lung cancer,chronic obstructive pulmonary disease (COPD), lower respiratory infections, colon cancer, rectal cancer, kidney disease, hypertensive heart disease, and diabetes mellitus.

[0162] Embodiment 38. The method of any one of embodiments 15 to 32, wherein the amount of time sufficient to induce accelerated aging in the first population of cells is at least about 24 hours.

[0163] Embodiment 39. The method of embodiment 38, wherein the amount of time is 25 hours.

[0164] Embodiment 40. The method of embodiment 38, wherein the population of aged cells comprises cells that are biologically aged by about 3 years to about 10 years relative to the population of control cells.

[0165] Embodiment 41. The method of any one of embodiments 15 to 35, wherein comparing the aged data and the control data to determine differences in gene activation or gene expression between the population of aged cells and the population of control cells comprises identifying differential activation or expression in one or more genes selected from the group consisting of:(i) CD28, CD40, CD40LG, CD80, CD86, COL1 A1 , COL1A2, COL3A1 , FN1 , IFNG, IL2, IL2RA, IL2RB, IL2RG, IL4, IL4R, IL5, IL5RA, LAMA5, LAMB1 , LAMB2, LAMC1 , LAMC2, LCK, MIR3606, MIR4758, MIR7846, THBS1 , THBS3, TNFRSF1 A, TNFRSF1 B, VTN, ZAP70;(ii) ATM, ATR, CDKN1A, CDKN2A, CHEK1 , CHEK2, CTC1 , ERCC1 , MIR21 , MME, PLA2R1 , ROMO1 , SERPINE1 , TERT, TP53, WNT16, WRN;(iii) ACTB, ACTG1 , ACTN1 , ACTN2, ACTN3, ACTN4, AFDN, ANG, ARHGEF6, CADM1 , CADM2, CADM3, CASK, CD151 , CD2AP, CD47, CDH1 , CDH10, CDH1 1 , CDH12, CDH13, CDH15, CDH17, CDH18, CDH2, CDH24, CDH3, CDH4, CDH5, CDH6, CDH7, CDH8, CDH9, CLDN1 , CLDN10, CLDN11 , CLDN12, CLDN14, CLDN15, CLDN16, CLDN17, CLDN18, CLDN19, CLDN2, CLDN20, CLDN22, CLDN23, CLDN3, CLDN4, CLDN5, CLDN6, CLDN7, CLDN8, CLDN9, COL17A1 , CRB3, CTNNA1 , CTNNB1 , CTNND1 , DST, F11 R, FBLIM1 , FERMT2, FLNA, FLNC, FYB1 , FYN, GRB2, ILK, IQGAP1 , ITGA6,ITGB1, ITGB4, JUP, KIRREL1, KIRREL2, KIRREL3, KRT14, KRT5, LAMA3, LAMB3, LAMC2, LIMS1, LIMS2, MAGI2, NCK1, NCK2, NECTIN1, NECTIN2, NECTIN3, NECTIN4, NPHS1, NPHS2, PALS1, PARD3, PARD6A, PARD6B, PARD6G, PARVA, PARVB, PATJ, PIK3CA, PIK3CB, PIK3R1, PIK3R2, PLEC, PRKCI, PTK2, PTK2B, PTPN11, PTPN6, PVR, PXN, RSU1, SDK1, SDK2, SFTPA1, SFTPA2, SFTPD, SIRPA, SIRPB1, SIRPG, SKAP2, SPTAN1 , SPTBN1 , SRC, TESK1 , TYROBP, VASP, WASL;(iv) NUPR1 , ENPP5, GPR183, CD38, NEO1 , FHL1 , PBX3, ALCAM, ALDH1 A1 , EBI3, DHRS3, PLEK, CD37, CLU, EHD3, CPNE8, PRCP, CD86, SULT1A1, EFNA1, SATB1, PLSCR1, GADD45G, TGM2, RORC, BMPR1A, GEM, CYSLTR2, RASSF4, LPL, DSG2, TRIM47, STOM, IL15, TM6SF1 , RNASE6, MMP2, ARHGAP30, SLAMF1 , NPDC1 , NDRG1 , ABAT, DENND5B, TSC22D1, ANXA6, MEF2C, CYTIP, MCM7, PERP, THBD, LAMP2, CYB561, PLAC8, LST1, TMEM176A, LPAR6, TC2N, PROCR, FLT3, CAVIN2, MMP14, JUN, EGR1 , ID2, BCL6, S100A6, IL12RB2, MGST1 , ZFP36, CSF2RB, LSR, ECT2, MYO1 E, SERPINB8, CXCL16, PPP1 16B, LSP1, TNFSF10, CD9, PLA2G4A, DHX40, EVC, LGALS1, NDN, SELL, MLLT3, ANXA2, OXR1 , GSTM1, BTG2, CTSS, ACSL4, SOCS2, MLEC, SEMA7A, PLXDC2, RFC2, EXOC6B, MCM5, GPX3, TOX, LY6E, CD63, RDH10, PLCL1, PTGER4, MAF, VMP1, RAB34, TBC1D8, DDR1, AMPD3, SYK, ANTXR2, LDHD, PDGFD, ACPP, CAMK1 D, PRNP, PHACTR1 ;(v) ADIPOR1, AGT, AHSG, APPL2, ATP2B1, BGLAP, C1QTNF12, ECHDC3, ENPP1 , ERFE, ESRRA, GKAP1 , GNAI2, GPLD1 , GPR21 , GRB10, GRB14, GRB7, GSK3A, IGF2, IL1 B, INPP5K, INS, IRS1 , KANK1 , LEP, LPL, MIR103A1 , MIR107, MIR1271 , MIR15B, MIR195, MSTN, MYO1C, NCK1, NCOA5, NR1H4, NUCKS1, OSBPL8, PID1 , PIP4K2A, PIP4K2B, PIP4K2C, PRKAA1, PRKCB, PRKCD, PRKCQ, PRKCZ, PTPN1, PTPN11, PTPN2, PTPRE, RPS6KB1, SERPINA12, SIRT1, SLC27A4, SNX5, SOCS1 , SOCS3, SORBS1 , SORL1 , SRC, TNS2, TRIM72, TSC2, USO1 , ZBTB7B;(vi) AFG3L2, AHSP, AIP, AIPL1, APCS, CALR, CALR3, CANX, CCDC115, CCT2, CCT3, CCT4, CCT5, CCT6A, CCT6B, CCT7, CCT8, CCT8L1P, CCT8L2, CDC37, CDC37L1, CHAF1A, CHAF1B, CLGN, CLPX, CLU, CRYAA, CRYAB, DNAJA1, DNAJA2, DNAJA3, DNAJA4, DNAJB1 , DNAJB11 , DNAJB13, DNAJB2, DNAJB3, DNAJB4, DNAJB5, DNAJB6, DNAJB7, DNAJB8, DNAJC4, ERLEC1, ERN1, ERN2, ERO1 B, GRPEL1,GRPEL2, HEATR3, HSP90AA1, HSP90AA2P, HSP90AA4P, HSP90AA5P, HSP90AB1, HSP90AB2P, HSP90AB3P, HSP90AB4P, HSP90B1, HSP90B2P, HSPA13, HSPA14, HSPA1A, HSPA1B, HSPA1L, HSPA2, HSPA5, HSPA6, HSPA7, HSPA8, HSPA9, HSPB6, HSPD1, HSPE1, HTRA2, HY0U1, LMAN1, MKKS, NACA, NACA2, NACA4P, NACAD, NAP1L4, NDUFAF1, NPM1, NUDC, NUDCD2, NUDCD3, PDRG1, PET100, PFDN1, PFDN2, PFDN4, PFDN5, PFDN6, PPIA, PPIB, PTGES3, RP2, RUVBL2, SOAP, SCG5, SERPINH1, SHQ1, SIL1, SPG7, SRSF10, SRSF12, SYVN1, TAPBP, TCP1, TIMM10B, TMEM67, TOMM20, TOR1 A, TRAP1 , TTC1 , TUBB4B, UGGT1 , UGGT2, VBP1 ;(vii) ACTB, AEBP2, ARID4B, BAZ1B, BAZ2A, CBX3, CCNH, CDK7, CHD3, CHD4, DDX21, DEK, DNMT1, DNMT3A, DNMT3B, DNMT3L, EED, EHMT2, EP300, ERCC2, ERCC3, ERCC6, EZH2, GATAD2A, GATAD2B, GSK3B, GTF2H1, GTF2H2, GTF2H3, GTF2H4, GTF2H5, H2AB1, H2AC14, H2AC20, H2AC4, H2AC6, H2AC7, H2AC8, H2AJ, H2AX, H2AZ1, H2AZ2, H2BC1 , H2BC10, H2BC11, H2BC12, H2BC13, H2BC14. H2BC15, H2BC17, H2BC21. H2BC3. H2BC4, H2BC5, H2BC6, H2BC7, H2BC8, H2BC9, H2BS1, H2BU1, H3-3A, H3-3B, H3C1, H3C10, H3C11, H3C12, H3C13, H3C14, H3C15, H3C2, H3C3, H3C4, H3C6, H3C7, H3C8, H4-16, H4C1, H4C11, H4C12, H4C13, H4C14, H4C15, H4C2, H4C3, H4C4, H4C5, H4C6, H4C8, H4C9, HDAC1 , HDAC2, JARID2, KAT2A, KAT2B, MBD2, MBD3, MNAT1, MTA1, MTA2, MTA3, MTF2, MYBBP1A, MYO1C, ,PHF1, PHF19, POLR1A, POLR1B, POLR1C, POLR1D, POLR1E, POLR1F, POLR1G, POLR1H, POLR2E, POLR2F, POLR2H, POLR2K, POLR2L, RBBP4, RBBP7, RRP8, SAP130, SAP18, SAP30, SAP30BP, SAP30L, SF3B1 , SIN3A, SIN3B, SIRT1 , SMARCA5, SUDS3, SUV39H1 , SUZ12, TAF1 A, TAF1 B, TAF1 C, TAF1 D, TBP, TDG, TET1 , TET2, TET3, TTF1 , UBTF, UHRF1 ;(viii) ABL1, ACD, AKT1, ATM, BLM, CCND1, CDKN1B, DKC1, E2F1, EGF, EGFR, ESR1, FOS, HDAC1, HDAC2, HNRNPC, HSP90AA1, HUS1, IFNAR2, IFNG, IL2, IRF1, JUN, MAPK1, MAPK3, MAX, MRE11, MTOR, MXD1, MYO, NBN, NCL, NFKB1, NR2F2, PARP2, PINX1, POT1, PTGES3, RAD1, RAD50, RAD9A, RBBP4, RBBP7, RPS6KB1, SAP18, SAP30, SIN3A, SIN3B, SMAD3, SMG5, SMG6, SP1, SP3, TERF1, TERF2, TERF2IP, TERT, TGFB1, TINF2, TNKS, UBE3A, WRN, WT1, XRCC5, XRCC6, YWHAE, ZNFX1;(ix) CAMK4, CREB1, ESRRA, ABPA, GABPB1, GABPB1-IT1, HCFC1, MTERF1, MTERF3, MYEF2, NRF1, POLRMT, PPARGC1A, PPARGC1B, PPP3CA, PPRC1, SP1, TFAM, TFB1 M, and TFB2M.

[0166] Embodiment 42. The method of any one of embodiments 12-41, wherein the cellular condition associated with aging comprises chronic inflammation; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from CD28, CD40, CD40LG, CD80, CD86, COL1A1, COL1A2, COL3A1, FN1, IFNG, IL2, IL2RA, IL2RB, IL2RG, IL4, IL4R, IL5, IL5RA, LAMA5, LAMB1, LAMB2, LAMC1, LAMC2, LCK, MIR3606, MIR4758, MIR7846, THBS1, THBS3, TNFRSF1 A, TNFRSF1 B, VTN, and ZAP70.

[0167] Embodiment 43. The method of any one of embodiments 12-41, wherein the cellular condition associated with aging comprises cellular senescence; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from ATM, ATR, CDKN1A, CDKN2A, CHEK1, CHEK2, CTC1, ERCC1, MIR21, MME, PLA2R1, ROMO1, SERPINE1, TERT, TP53, WNT16, and WRN.

[0168] Embodiment 44. The method of any one of embodiments 12-41, wherein the cellular condition associated with aging comprises altered intracellular communication; and the set of biomarker associated with aging or age-related disease comprises differential activation or expression in one or more genes selected from ACTB, ACTG1, ACTN1, ACTN2, ACTN3, ACTN4, AFDN, ANG, ARHGEF6, CADM1, CADM2, CADM3, CASK, CD151, CD2AP, CD47, CDH1, CDH10, CDH11, CDH12, CDH13, CDH15, CDH17, CDH18, CDH2, CDH24, CDH3, CDH4, CDH5, CDH6, CDH7, CDH8, CDH9, CLDN1, CLDN10, CLDN11, CLDN12, CLDN14, CLDN15, CLDN16, CLDN17, CLDN18, CLDN19, CLDN2, CLDN20, CLDN22, CLDN23, CLDN3, CLDN4, CLDN5, CLDN6, CLDN7, CLDN8, CLDN9, COL17A1, CRB3, CTNNA1, CTNNB1, CTNND1, DST, F11R, FBLIM1, FERMT2, FLNA, FLNC, FYB1 , FYN, GRB2, ILK, IQGAP1 , ITGA6, ITGB1 , ITGB4, JUP, KIRREL1 , KIRREL2, KIRREL3, KRT14, KRT5, LAMA3, LAMB3, LAMC2, LIMS1, LIMS2, MAGI2, NCK1, NCK2, NECTIN1, NECTIN2, NECTIN3, NECTIN4, NPHS1, NPHS2, PALS1, PARD3, PARD6A, PARD6B, PARD6G, PARVA, PARVB, PATJ, PIK3CA, PIK3CB, PIK3R1, PIK3R2, PLEC,PRKCI, PTK2, PTK2B, PTPN11 , PTPN6, PVR, PXN, RSU1 , SDK1 , SDK2, SFTPA1 , SFTPA2, SFTPD, SIRPA, SIRPB1 , SIRPG, SKAP2, SPTAN1 , SPTBN1 , SRC, TESK1 , TYROBP, VASP, and WASL.

[0169] Embodiment 45. The method of any one of embodiments 12-41 , wherein the cellular condition associated with aging comprises stem cell exhaustion; and the set of biomarkers associated with aging or age-related disease comprises differential activation or expression in one or more genes selected from NLIPR1 , ENPP5, GPR183, CD38, NEO1 , FHL1 , PBX3, ALCAM, ALDH1 A1 , EBI3, DHRS3, PLEK, CD37, CLU, EHD3, CPNE8, PRCP, CD86, SULT1 A1 , EFNA1 , SATB1 , PLSCR1 , GADD45G, TGM2, RORC, BMPR1 A, GEM, CYSLTR2, RASSF4, LPL, DSG2, TRIM47, STOM, IL15, TM6SF1 , RNASE6, MMP2, ARHGAP30, SLAMF1 , NPDC1 , NDRG1 , ABAT, DENND5B, TSC22D1 , ANXA6, MEF2C, CYTIP, MCM7, PERP, THBD, LAMP2, CYB561 , PLAC8, LST1 , TMEM176A, LPAR6, TC2N, PROCR, FLT3, CAVIN2, MMP14, JUN, EGR1 , ID2, BCL6, S100A6, IL12RB2, MGST1 , ZFP36, CSF2RB, LSR, ECT2, MYO1 E, SERPINB8, CXCL16, PPP1 R16B, LSP1 , TNFSF10, CD9, PLA2G4A, DHX40, EVO, LGALS1 , NDN, SELL, MLLT3, ANXA2, OXR1 , GSTM1 , BTG2, CTSS, ACSL4, SOCS2, MLEC, SEMA7A, PLXDC2, RFC2, EXOC6B, MCM5, GPX3, TOX, LY6E, CD63, RDH10, PLCL1 , PTGER4, MAF, VMP1 , RAB34, TBC1 D8, DDR1 , AMPD3, SYK, ANTXR2, LDHD, PDGFD, ACPP, CAMK1 D, PRNP, and PHACTR1 .

[0170] Embodiment 46. The method of any one of embodiments 12-41 , wherein the cellular condition associated with aging comprises deregulated nutrient sensing; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from ADIPOR1 , AGT, AHSG, APPL2, ATP2B1 , BGLAP, C1 QTNF12, ECHDC3, ENPP1 , ERFE, ESRRA, GKAP1 , GNAI2, GPLD1 , GPR21 , GRB10, GRB14, GRB7, GSK3A, IGF2, IL1 B, INPP5K, INS, IRS1 , KANK1 , LEP, LPL, MIR103A1 , MIR107, MIR1271 , MIR15B, MIR195, MSTN, MYO1 C, NCK1 , NCOA5, NR1 H4, NUCKS1 , OSBPL8, PID1 , PIP4K2A, PIP4K2B, PIP4K2C, PRKAA1 , PRKCB, PRKCD, PRKCQ, PRKCZ, PTPN1 , PTPN1 1 , PTPN2, PTPRE, RPS6KB1 , SERPINA12, SIRT1 , SLC27A4, SNX5, SOCS1 , SOCS3, SORBS1 , SORL1 , SRC, TNS2, TRIM72, TSC2, USO1 , and ZBTB7B.

[0171] Embodiment 47. The method of any one of embodiments 12-41, wherein the cellular condition associated with aging comprises loss of proteostasis garbaging; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from AFG3L2, AHSP, AIP, AIPL1, APCS, CALR, CALR3, CANX, CCDC115, CCT2, CCT3, CCT4, CCT5, CCT6A, CCT6B, CCT7, CCT8, CCT8L1P, CCT8L2, CDC37, ODC37L1, CHAF1A, CHAF1B, CLGN, CLPX, CLU, CRYAA, CRYAB, DNAJA1, DNAJA2, DNAJA3, DNAJA4, DNAJB1, DNAJB11, DNAJB13, DNAJB2, DNAJB3, DNAJB4, DNAJB5, DNAJB6, DNAJB7, DNAJB8, DNAJC4, ERLEC1, ERN1, ERN2, ERO1B, GRPEL1 , GRPEL2, HEATR3, HSP90AA1, HSP90AA2P, HSP90AA4P, HSP90AA5P, HSP90AB1, HSP90AB2P, HSP90AB3P, HSP90AB4P, HSP90B1, HSP90B2P, HSPA13, HSPA14, HSPA1A, HSPA1B, HSPA1L, HSPA2, HSPA5, HSPA6, HSPA7, HSPA8, HSPA9, HSPB6, HSPD1, HSPE1, HTRA2, HYOU1, LMAN1, MKKS, NACA, NACA2, NACA4P, NACAD, NAP1L4, NDUFAF1, NPM1, NUDC, NUDCD2, NUDCD3, PDRG1, PET100, PFDN1, PFDN2, PFDN4, PFDN5, PFDN6, PPIA, PPIB, PTGES3, RP2, RUVBL2, SCAP, SCG5, SERPINH1, SHQ1, SIL1, SPG7, SRSF10, SRSF12, SYVN1, TAPBP, TCP1 , TIMM10B, TMEM67, TOMM20, TOR1A, TRAP1, TTC1, TUBB4B, UGGT1, UGGT2, and VBP1.

[0172] Embodiment 48. The method of any one of embodiments 12-41, wherein the cellular condition associated with aging comprises epigenetic alterations; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from ACTB, AEBP2, ARID4B, BAZ1B, BAZ2A, CBX3, CCNH, CDK7, CHD3, CHD4, DDX21 , DEK, DNMT1 , DNMT3A, DNMT3B, DNMT3L, EED, EHMT2, EP300, ERCC2, ERCC3, ERCC6, EZH2, GATAD2A, GATAD2B, GSK3B, GTF2H1, GTF2H2, GTF2H3, GTF2H4, GTF2H5, H2AB1, H2AC14, H2AC20, H2AC4, H2AC6, H2AC7, H2AC8, H2AJ, H2AX, H2AZ1, H2AZ2, H2BC1 , H2BC10, H2BC11, H2BC12, H2BC13, H2BC14. H2BC15, H2BC17, H2BC21. H2BC3. H2BC4, H2BC5, H2BC6, H2BC7, H2BC8, H2BC9, H2BS1, H2BU1, H3-3A, H3-3B, H3C1, H3C10, H3C11 , H3C12, H3C13, H3C14, H3C15, H3C2, H3C3, H3C4, H3C6, H3C7, H3C8, H4-16, H4C1, H4C11, H4C12, H4C13, H4C14, H4C15, H4C2, H4C3, H4C4, H4C5, H4C6, H4C8, H4C9, HDAC1, HDAC2, JARID2, KAT2A, KAT2B, MBD2, MBD3, MNAT1, MTA1, MTA2, MTA3,MTF2, MYBBP1A, MY01 C, ,PHF1 , PHF19, P0LR1 A, P0LR1 B, P0LR1 C, P0LR1 D, P0LR1 E, P0LR1 F, P0LR1 G, P0LR1 H, P0LR2E, P0LR2F, P0LR2H, P0LR2K, P0LR2L, RBBP4, RBBP7, RRP8, SAP130, SAP18, SAP30, SAP30BP, SAP30L, SF3B1 , SIN3A, SIN3B, SIRT1 , SMARCA5, SUDS3, SUV39H1 , SUZ12, TAF1 A, TAF1 B, TAF1 C, TAF1 D, TBP, TDG, TET1 , TET2, TET3, TTF1 , UBTF, and UHRF1 .

[0173] Embodiment 49. The method of any one of embodiments 12-41 , wherein the cellular condition associated with aging comprises telomere attrition; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from ABL1 , ACD, AKT1 , ATM, BLM, CCND1 , CDKN1 B, DKC1 , E2F1 , EGF, EGFR, ESR1 , FOS, HDAC1 , HDAC2, HNRNPC, HSP90AA1 , HUS1 , IFNAR2, IFNG, IL2, IRF1 , JUN, MAPK1 , MAPK3, MAX, MRE11 , MTOR, MXD1 , MYO, NBN, NCL, NFKB1 , NR2F2, PARP2, PINX1 , POT1 , PTGES3, RAD1 , RAD50, RAD9A, RBBP4, RBBP7, RPS6KB1 , SAP18, SAP30, SIN3A, SIN3B, SMAD3, SMG5, SMG6, SP1 , SP3, TERF1 , TERF2, TERF2IP, TERT, TGFB1 , TINF2, TNKS, UBE3A, WRN, WT1 , XRCC5, XRCC6, YWHAE, and ZNFX1 .

[0174] Embodiment 50. The method of any one of embodiments 12-41 , wherein the cellular condition associated with aging comprises mitochondrial dysfunction; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from CAMK4, CREB1 , ESRRA, ABPA, GABPB1 , GABPB1 -IT1 , HCFC1 , MTERF1 , MTERF3, MYEF2, NRF1 , POLRMT, PPARGC1 A, PPARGC1 B, PPP3CA, PPRC1 , SP1 , TFAM, TFB1 M, and TFB2M.

[0175] Embodiment 51 . The method of any one of embodiments 12 to 50, wherein the one or more interventions further comprises one or more pharmaceutical agents, dietary supplements, and / or lifestyle changes.

[0176] Embodiment 52. The method of embodiment 51 , wherein the one or more dietary supplements comprise one or more nutraceuticals or nutritional supplements.

[0177] Embodiment 53. The method of embodiment 52, wherein the one or more nutraceuticals and / or nutritional supplements comprise one or more of acarbose, ashwagandha, B complex, B12-methylcobalamin, berberine, C vitamin, Ca-AlphaKetoglutarat, cocoa flavanols, dehydroepiandrosterone (DHEA), E vitamin, eicosapentaenoic acid (EPA), garlic, ginger root, glucosamine sulphate, glycine, hyaluronic Acid, iodine (e.g., as potassium iodide), L-theanine, lithium, (e.g., as lithium orotate), lycopene, lysine, malate, nicotinamide riboside, pea protein, proferrin, pterostilbene, taurine, turmeric, ubiquinol, zeaxanthin, zinc, resveratrol, quercetin, nattokinase, CoQ10, fisetin, magnesium, nicotinamide mononucleotide (NMN), N-acetyl cysteine, alpha ketoglutaric acid, omega-3 fatty acids, collagen, raspberry ketones, green tea leaf extract, vitamin D3, vitamin B12, alpha-lipoic acid, probiotics, prebiotics, echinacea, garcinia cambogia, iron, multivitamins, and calcium citrate.

[0178] Embodiment 54. The method of embodiment 52 or embodiment 41 , wherein the one or more nutraceuticals and / or nutritional supplements comprise one or more of quercetin, nattokinase, CoQ10, fisetin, magnesium, nicotinamide mononucleotide (NMN), N-acetyl cysteine, and alpha ketoglutaric acid.

[0179] Embodiment 55. The method of any one of embodiments 12-54 and 26, wherein the one or more lifestyle changes comprise one or more of increasing activity level, changing the method of activity, increasing sleep duration, decreasing blue light exposure, increasing protein intake, decreasing sugar intake, performing heat and / or cold shock therapy, performing mindfulness exercises, not smoking, having moderate alcohol consumption, increasing daily intake of fruits and vegetables, maintaining a healthy body mass index and waist-to-hip ratio, restricting diet, intermittent fasting, adjusted diurnal rhythm of feeding, having a balanced diet, practicing sun protection, managing stress levels, increasing hydration, maintaining social connections, increasing cognitive stimulation, practicing good hygiene and oral care, and having a positive attitude.

[0180] Embodiment 56. A treatment plan for monitoring, delaying, or preventing onset of an age-related disease in a subject, prepared by:

[0181] identifying a set of biomarkers associated with age-related disease in the subject by determining differences in gene activation or gene expression between a population of aged cells derived from the subject and a population of control cells derived from the subject, wherein the population of aged cells is obtained by exposing a firstpopulation of cells from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging in the cells, and the population of control cells is obtained by exposing a second population of cells from the subject to normal gravity;

[0182] correlating the set of biomarkers associated with age-related disease with one or more therapies to prevent or delay onset of the age-related disease in the subject; and

[0183] developing a treatment plan to provide one or more interventions to the subject to prevent or delay onset of the age-related disease.

[0184] Embodiment 57. The treatment plan of embodiment 56, wherein the one or more interventions further comprise one or more pharmaceutical agents, nutraceuticals, nutritional supplements, and / or lifestyle changes.

[0185] Embodiment 58. A method of determining a risk of developing an age-related disease in a subject, the method comprising the steps of:(a) receiving aged data obtained from one or more analyses performed on a population of aged cells produced by exposing a first population of cells from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging;(b) receiving control data obtained from one or more analyses performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in gene activation or gene expression based on the comparing in (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with the age-related disease;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having(A) a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the age-related disease if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).

[0186] Embodiment 59. The method of embodiment 58, wherein the high-risk threshold is equal to or greater than 0.15, and wherein the biomarkers in (g) comprise one or more genes associated with chronic inflammation and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0187] Embodiment 60. The method of embodiment 59, wherein the high-risk threshold is 0.21.

[0188] Embodiment 61 . The method of embodiment 58, wherein the high-risk threshold is equal to or greater than 0.25, and wherein the biomarkers in (g) comprise one or more genes associated with cellular senescence and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0189] Embodiment 62. The method of embodiment 61 , wherein the high-risk threshold is 0.29.

[0190] Embodiment 63. The method of embodiment 58, wherein the high-risk threshold is equal to or greater than 0.05, and wherein the biomarkers in (g) comprise one or more genes associated with altered intracellular communication and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0191] Embodiment 64. The method of embodiment 63, wherein the high-risk threshold is 0.07.

[0192] Embodiment 65. The method of embodiment 58, wherein the high-risk threshold is equal to or greater than 0.25, and wherein the biomarkers in (g) comprise one or moregenes associated with stem cell exhaustion and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0193] Embodiment 66. The method of embodiment 65, wherein the high-risk threshold is 0.30.

[0194] Embodiment 67. The method of embodiment 58, wherein the high-risk threshold is equal to or greater than -0.80, and wherein the biomarkers in (g) comprise one or more genes associated with deregulated nutrient sensing and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0195] Embodiment 68. The method of embodiment 67, wherein the high-risk threshold is -0.85.

[0196] Embodiment 69. The method of embodiment 58, wherein the high-risk threshold is equal to or greater than -0.80, and wherein the biomarkers in (g) comprise one or more genes associated with loss of proteostasis garbaging and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0197] Embodiment 70. The method of embodiment 69, wherein the high-risk threshold is -0.87.

[0198] Embodiment 71 . The method of embodiment 58, wherein the high-risk threshold is equal to or greater than -0.10, and wherein the biomarkers in (g) comprise one or more genes associated with epigenetic alterations and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0199] Embodiment 72. The method of embodiment 71 , wherein the high-risk threshold is -0.13.

[0200] Embodiment 73. The method of embodiment 58, wherein the high-risk threshold is equal to or greater than -0.05, and wherein the biomarkers in (g) comprise one or moregenes associated with telomere attrition and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0201] Embodiment 74. The method of embodiment 73, wherein the high-risk threshold is -0.07.

[0202] Embodiment 75. The method of embodiment 58, wherein the high-risk threshold is equal to or greater than -0.10, and wherein the biomarkers in (g) comprise one or more genes associated with mitochondrial dysfunction and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

[0203] Embodiment 76. The method of embodiment 75, wherein the high-risk threshold is -0.14.

[0204] Embodiment 77. A non-transitory medium with instructions stored thereon that, when executed by a processor of a computing device, causes the computing device to perform steps for the methods of any one of embodiments 1 to 60.

Claims

CLAIMSI / We claim:1 . A method of determining a risk of a subject developing an age-related disease associated with one or more cellular conditions selected from the group consisting of chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomere attrition, in the subject, the method comprising the steps of:(a) receiving aged data obtained from bulk RNA-sequencing and qPCR performed on a population of aged cells produced by exposing a first population of cells from the subject to simulated microgravity for 25 hours;(b) receiving control data obtained from bulk RNA-sequencing and qPCR performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in gene activation or gene expression based on the comparing in (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with one or more of chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomere attrition;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having:(A) a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the age-related disease if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).

2. A method of determining a risk of a subject developing an age-related disease, the method comprising the steps of:(a) receiving aged data obtained from bulk RNA-sequencing and qPCR performed on a population of aged cells produced by exposing a first population of cells from the subject to simulated microgravity for 25 hours;(b) receiving control data obtained from bulk RNA-sequencing and qPCR performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in gene activation or gene expression based on the comparing in (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomere attrition;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having:(A) a high risk for developing the age-related disease associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomere attrition if the biomarkers in (g) are expressed at or greater than a high- risk threshold, or(B) a low risk for developing the age-related disease associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, stem cell exhaustion, loss of proteostasis garbaging, epigenetic alterations, and telomereattrition if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).

3. The method of claim 1 or 2, wherein the high-risk threshold is 0.21 , and wherein the biomarkers in (g) comprise one or more genes associated with chronic inflammation and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

4. The method of claim 1 or 2, wherein the high-risk threshold is 0.29, and wherein the biomarkers in (g) comprise one or more genes associated with cellular senescence and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

5. The method of claim 1 or 2, wherein the high-risk threshold is 0.07, and wherein the biomarkers in (g) comprise one or more genes associated with altered intracellular communication and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high- risk threshold.

6. The method of claim 1 or 2, wherein the high-risk threshold is 0.30, and wherein the biomarkers in (g) comprise one or more genes associated with stem cell exhaustion and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

7. The method of claim 1 or 2, wherein the high-risk threshold is -0.87, and wherein the biomarkers in (g) comprise one or more genes associated with loss of proteostasis garbaging and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

8. The method of claim 1 or 2, wherein the high-risk threshold is -0.13, and wherein the biomarkers in (g) comprise one or more genes associated with epigenetic alterations and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk.

9. The method of claim 1 or 2, wherein the high-risk threshold is -0.07, and wherein the biomarkers in (g) comprise one or more genes associated with telomere attrition and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

10. A method of determining a risk of a subject developing a cellular condition associated with aging selected from chronic inflammation, cellular senescence, altered intracellular communication, and loss of proteostasis garbaging in a subject, the method comprising:(a) receiving aged data obtained from one or more analytical techniques selected from differential gene expression (DGE) analysis, gene ontology overexpression analysis, gene set expression analysis (GSEA), and ingenuity pathway analysis (I PA) performed on a population of aged cells produced by exposing a first population of cells from the subject to magnetic levitation for 24 hours;(b) receiving control data obtained from one or more analytical technique selected from DGE, gene ontology over-enrichment analysis, GSEA, and IPA performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in activation or enrichment of one or more biological pathways or functions (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, and loss of proteostasis garbaging;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having:(A) a high risk for developing the cellular condition associated with aging if the biomarkers in (g) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the cellular condition associated with aging if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).1 1. A method of determining a risk of a subject developing a cellular condition associated with aging, the method comprising:(a) receiving aged data obtained from one or more analytical techniques selected from differential gene expression (DGE) analysis, gene ontology overexpression analysis, gene set expression analysis (GSEA), and ingenuity pathway analysis (I PA) performed on a population of aged cells produced by exposing a first population of cells from the subject to magnetic levitation for 24 hours;(b) receiving control data obtained from one or more analytical technique selected from DGE, gene ontology over-enrichment analysis, GSEA, and IPA performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in activation or enrichment of one or more biological pathways or functions (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with one or more cellular conditions selected from chronic inflammation, cellular senescence, altered intracellular communication, and loss of proteostasis garbaging;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having:(A) a high risk for developing the cellular condition associated with aging selected from chronic inflammation, cellular senescence, altered intracellular communication, and loss of proteostasis garbaging if the biomarkers in (g) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the cellular condition associated with aging selected from chronic inflammation, cellular senescence, altered intracellular communication, and loss of proteostasis garbaging if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).

12. A method of identifying one or more interventions useful to reduce or prevent aging in a subject, comprising: exposing a first population of cells derived from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; analyzing the population of aged cells to obtain a set of aged data; exposing a second population of cells derived from the subject to normal gravity to obtain a population of control cells; analyzing the population of control cells to obtain a set of control data; comparing the aged data and the control data to determine differences in gene activation or gene expression between the population of aged cells and the population of control cells; based on the determined differences, identifying:(i) a set of biomarkers associated with aging, and / or(ii) a cellular condition associated with aging;correlating the set of biomarkers and / or cellular condition associated with aging with one or more interventions to reduce the rate of aging in the subject; and developing an interventional plan to provide the one or more interventions to the subject to reduce the rate of aging in the subject.

13. The method of claim 12, further comprising determining, based on the identified biomarkers and / or cellular conditions associated with aging, that the subject ages at a faster rate of aging, relative to an average rate of aging.

14. The method of claim 12, further comprising determining, based on the identified biomarkers and / or cellular conditions associated with aging, that the subject ages at an average rate of aging.

15. A method of preventing or delaying onset of an age-related disease in a subject, comprising: exposing a first population of cells derived from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; analyzing the population of aged cells to obtain a set of aged data; exposing a second population of cells derived from the subject to normal gravity to obtain a population of control cells; analyzing the population of control cells to obtain a set of control data; comparing the aged data and the control data to determine differences in gene activation or gene expression and / or differences in activation or enrichment of biological pathways or functions between the population of aged cells and the population of control cells; based on the determined differences, identifying a set of biomarkers associated with age-related disease; correlating the set of biomarkers associated with age-related disease with one or more therapies to prevent or delay onset of the age-related disease in the subject; anddeveloping a treatment plan to provide the one or more interventions to the subject to prevent or delay onset of the age-related disease.

16. The method of any one of claims 12-15, further comprising: analyzing the first population of cells at regular time intervals while exposing the cells to simulated microgravity to obtain time-interval aging data; analyzing the second population of cells at the regular time intervals while exposing the cells to normal gravity to obtain time-interval control data; and comparing the time-interval aging data to the time-interval control data to identify one or more biomarkers of age-related disease.

17. The method of claim 16, wherein analyzing the first and second population of cells at the regular time interval comprises analyzing the cells hourly.

18. The method of any one of claims 12-15, further comprising: splitting the first population of cells into a first subpopulation of cell and a second subpopulation of cells; exposing the first and second subpopulation of cells to simulated microgravity for an amount of time sufficient to induce accelerated aging thereby producing a population of aged cells; returning the first subpopulation of cells to normal gravity while the second subpopulation of cells stays at simulated microgravity; and taking time-series measurements of the first subpopulation of cells at normal gravity to determine molecular mechanisms of recovery to the induced accelerated aging.

19. The method of claim 18, wherein analyzing the first subpopulation of cells at normal gravity comprises taking time-series measurements of the cells to identify biomarkers associated with age-related disease.

20. The method of claim 19, wherein the time-series measurements comprise taking measurements of the cells at about 24 hours, 36 hours, 48 hours, 72 hours, and 96 hours after returning the cells to normal gravity.21 . The method of any one of claims 18-20, further comprising: identifying one or more interventional agents that mimic the molecular mechanism of recovery by performing an in silica compound screen; and including the one or more interventional agents in the treatment plan or the interventional plan prepared for the subject.

22. The treatment plan of claim 21 , wherein the interventional agent further comprises one or more pharmaceutical agents, nutraceuticals, or nutritional supplements.

23. The method of any one of claims 12-22, wherein analyzing the population of aged cells and the population of control cells further comprises using transcriptomics to perform a transcriptome analysis, using epigenomics to perform an epigenome analysis, using metabolomics to perform a metabolome analysis, or using proteomics to perform a proteome analysis on the population of aged cells and the population of control cells.

24. The method of claim 23, wherein the transcriptome analysis further comprises analyzing one or more of total RNA, enriched mRNA, enriched non-coding RNA, or enriched small RNA.

25. The method of claim 23 or claim 24, wherein the transcriptome analysis further comprises sequencing, quantitative polymerase chain reaction (qPCR), quantitative reverse transcriptase PCR (qRT-PCR), digital PCR (dPCR), digital droplet PCR (ddPCR), Reverse Transcription Loop-mediated Isothermal Amplification (RT-LAMP), Loop-mediated Isothermal Amplification (LAMP), serial analysis of gene expression (SAGE), cap analysis of gene expression (CAGE), northern blot, expression immunoassay, microarrays analysisand / or any method utilizing light intensity, fluorescent signal intensity, stable isotopes, and / or radioactive isotopes to quantify gene expression.

26. The method of any one of claims 23-25, wherein the transcriptome analysis further comprises single-cell transcriptome analysis.

27. The method of any one of claims 23-26, wherein the epigenome analysis further comprises assay for transposase-accessible chromatin using sequencing (ATAC- seq), bisulfite sequencing, chromatin immunoprecipitation sequencing (CHiP-seq), Hi-C epigenome analysis, cleavage under targets and tagmentation (CUT&Tag), and / or cleavage under targets and release using nuclease (CUT&run).

28. The method of any one of claims 23-27, wherein the epigenome analysis further comprises integrated single-cell epigenome analysis.

29. The method of any one of claims 23-28, wherein the metabolome analysis further comprises nuclear magnetic resonance spectroscopy (NMR) and / or mass spectrometry (MS).

30. The method of claim 29, wherein the mass spectrometry comprises Fourier transform ion cyclotron mass spectrometry (FTIC-MS).31 . The method of any one of claims 23-30, wherein the proteome analysis further comprises enzyme-linked immunosorbent assays (ELISA), western blotting, two- dimensional difference gel electrophoresis (2D-DIGE), tandem mass spectrometry, and / or mass spectrometry.

32. The method of any one of claims 12-31 , wherein the first population of cells and the second population of cells each comprise a population of immune cells.

33. The method of claim 32, wherein the populations of immune cells further comprise peripheral blood mononuclear cells (PBMCs).

34. The method of claim 33, wherein the PBMCs further comprise enriched subpopulations of PBMCs.

35. The method of any one of claims 32-34, wherein the PBMCs or subpopulations of PBMCs, are sorted with fluorescence-activated cellular sorting (FACS), microfluidics, density gradient centrifugation, differential centrifugation, paramagnetic beads, levitation technology or a combination of these methods.

36. The method of any one of claims 15 to 30, wherein the age-related disease comprises age-related inflammation.

37. The method of any one of claim 15 to 31 , wherein the age-related disease is selected from ischemic heart disease, Alzheimer’s disease, dementia, Parkinson’s disease, stroke, trachea cancer, bronchus cancer, lung cancer, chronic obstructive pulmonary disease (COPD), lower respiratory infections, colon cancer, rectal cancer, kidney disease, hypertensive heart disease, and diabetes mellitus.

38. The method of any one of claims 15 to 32, wherein the amount of time sufficient to induce accelerated aging in the first population of cells is at least about 24 hours.

39. The method of claim 38, wherein the amount of time is 25 hours.

40. The method of claim 38, wherein the population of aged cells comprises cells that are biologically aged by about 3 years to about 10 years relative to the population of control cells.41 . The method of any one of claims 15 to 35, wherein comparing the aged data and the control data to determine differences in gene activation or gene expression between the population of aged cells and the population of control cells comprises identifying differential activation or expression in one or more genes selected from the group consisting of:(i) CD28, CD40, CD40LG, CD80, CD86, COL1 A1 , COL1A2, COL3A1 , FN1 , IFNG, IL2, IL2RA, IL2RB, IL2RG, IL4, IL4R, IL5, IL5RA, LAMA5, LAMB1 , LAMB2, LAMC1 , LAMC2, LCK, MIR3606, MIR4758, MIR7846, THBS1 , THBS3, TNFRSF1A, TNFRSF1 B, VTN, ZAP70;(ii) ATM, ATR, CDKN1A, CDKN2A, CHEK1 , CHEK2, CTC1 , ERCC1 , MIR21 , MME, PLA2R1 , R0M01 , SERPINE1 , TERT, TP53, WNT16, WRN;(iii) ACTB, ACTG1 , ACTN1 , ACTN2, ACTN3, ACTN4, AFDN, ANG, ARHGEF6, CADM1 , CADM2, CADM3, CASK, CD151 , CD2AP, CD47, CDH1 , CDH10, CDH1 1 , CDH12, CDH13, CDH15, CDH17, CDH18, CDH2, CDH24, CDH3, CDH4, CDH5, CDH6, CDH7, CDH8, CDH9, CLDN1 , CLDN10, CLDN11 , CLDN12, CLDN14, CLDN15, CLDN16, CLDN17, CLDN18, CLDN19, CLDN2, CLDN20, CLDN22, CLDN23, CLDN3, CLDN4, CLDN5, CLDN6, CLDN7, CLDN8, CLDN9, COL17A1 , CRB3, CTNNA1 , CTNNB1 , CTNND1 , DST, F11 R, FBLIM1 , FERMT2, FLNA, FLNC, FYB1 , FYN, GRB2, ILK, IQGAP1 , ITGA6, ITGB1 , ITGB4, JUP, KIRREL1 , KIRREL2, KIRREL3, KRT14, KRT5, LAMA3, LAMB3, LAMC2, LIMS1 , LIMS2, MAGI2, NCK1 , NCK2, NECTIN1 , NECTIN2, NECTIN3, NECTIN4, NPHS1 , NPHS2, PALS1 , PARD3, PARD6A, PARD6B, PARD6G, PARVA, PARVB, PATJ, PIK3CA, PIK3CB, PIK3R1 , PIK3R2, PLEC, PRKCI, PTK2, PTK2B, PTPN11 , PTPN6, PVR, PXN, RSU1 , SDK1 , SDK2, SFTPA1 , SFTPA2, SFTPD, SIRPA, SIRPB1 , SIRPG, SKAP2, SPTAN1 , SPTBN1 , SRC, TESK1 , TYROBP, VASP, WASL;(iv) NUPR1 , ENPP5, GPR183, CD38, NEO1 , FHL1 , PBX3, ALCAM, ALDH1 A1 , EBI3, DHRS3, PLEK, CD37, CLU, EHD3, CPNE8, PRCP, CD86, SULT1A1 , EFNA1 , SATB1 , PLSCR1 , GADD45G, TGM2, RORC, BMPR1A, GEM, CYSLTR2, RASSF4, LPL, DSG2, TRIM47, STOM, IL15, TM6SF1 , RNASE6, MMP2, ARHGAP30, SLAMF1 , NPDC1 , NDRG1 , ABAT, DENND5B, TSC22D1 , ANXA6, MEF2C, CYTIP, MCM7, PERP, THBD, LAMP2, CYB561 , PLAC8, LST1 , TMEM176A, LPAR6, TC2N, PROCR, FLT3, CAVIN2, MMP14, JUN, EGR1 , ID2, BCL6, S100A6, IL12RB2, MGST1 , ZFP36, CSF2RB, LSR, ECT2, MYO1 E,SERPINB8, CXCL16, PPP1R16B, LSP1, TNFSF10, CD9, PLA2G4A, DHX40, EVC, LGALS1, NDN, SELL, MLLT3, ANXA2, 0XR1, GSTM1, BTG2, CTSS, ACSL4, S0CS2, MLEC, SEMA7A, PLXDC2, RFC2, EX0C6B, MCM5, GPX3, TOX, LY6E, CD63, RDH10, PLCL1, PTGER4, MAF, VMP1, RAB34, TBC1D8, DDR1, AMPD3, SYK, ANTXR2, LDHD, PDGFD, ACPP, CAMK1 D, PRNP, PHACTR1 ;(v) ADIPOR1, AGT, AHSG, APPL2, ATP2B1, BGLAP, C1QTNF12, ECHDC3, ENPP1 , ERFE, ESRRA, GKAP1 , GNAI2, GPLD1 , GPR21 , GRB10, GRB14, GRB7, GSK3A, IGF2, IL1 B, INPP5K, INS, IRS1 , KANK1 , LEP, LPL, MIR103A1 , MIR107, MIR1271 , MIR15B, MIR195, MSTN, MYO1C, NCK1, NCOA5, NR1H4, NUCKS1, OSBPL8, PID1, PIP4K2A, PIP4K2B, PIP4K2C, PRKAA1, PRKCB, PRKCD, PRKCQ, PRKCZ, PTPN1, PTPN11, PTPN2, PTPRE, RPS6KB1, SERPINA12, SIRT1, SLC27A4, SNX5, SOCS1 , SOCS3, SORBS1 , SORL1 , SRC, TNS2, TRIM72, TSC2, USO1 , ZBTB7B;(vi) AFG3L2, AHSP, AIP, AIPL1, APCS, CALR, CALR3, CANX, CCDC115, CCT2, CCT3, CCT4, CCT5, CCT6A, CCT6B, CCT7, CCT8, CCT8L1P, CCT8L2, CDC37, CDC37L1, CHAF1A, CHAF1B, CLGN, CLPX, CLU, CRYAA, CRYAB, DNAJA1, DNAJA2, DNAJA3, DNAJA4, DNAJB1 , DNAJB11 , DNAJB13, DNAJB2, DNAJB3, DNAJB4, DNAJB5, DNAJB6, DNAJB7, DNAJB8, DNAJC4, ERLEC1, ERN1, ERN2, ERO1B, GRPEL1, GRPEL2, HEATR3, HSP90AA1, HSP90AA2P, HSP90AA4P, HSP90AA5P, HSP90AB1, HSP90AB2P, HSP90AB3P, HSP90AB4P, HSP90B1, HSP90B2P, HSPA13, HSPA14, HSPA1A, HSPA1B, HSPA1L, HSPA2, HSPA5, HSPA6, HSPA7, HSPA8, HSPA9, HSPB6, HSPD1, HSPE1, HTRA2, HYOU1, LMAN1, MKKS, NACA, NACA2, NACA4P, NACAD, NAP1L4, NDUFAF1, NPM1, NUDC, NUDCD2, NUDCD3, PDRG1, PET100, PFDN1, PFDN2, PFDN4, PFDN5, PFDN6, PPIA, PPIB, PTGES3, RP2, RUVBL2, SCAP, SCG5, SERPINH1, SHQ1, SIL1, SPG7, SRSF10, SRSF12, SYVN1, TAPBP, TCP1, TIMM10B, TMEM67, TOMM20, TOR1 A, TRAP1 , TTC1 , TUBB4B, UGGT1 , UGGT2, VBP1 ;(vii) ACTB, AEBP2, ARID4B, BAZ1B, BAZ2A, CBX3, CCNH, CDK7, CHD3, CHD4, DDX21, DEK, DNMT1, DNMT3A, DNMT3B, DNMT3L, EED, EHMT2, EP300, ERCC2, ERCC3, ERCC6, EZH2, GATAD2A, GATAD2B, GSK3B, GTF2H1, GTF2H2, GTF2H3, GTF2H4, GTF2H5, H2AB1, H2AC14, H2AC20, H2AC4, H2AC6, H2AC7, H2AC8, H2AJ, H2AX, H2AZ1, H2AZ2, H2BC1 , H2BC10, H2BC11, H2BC12, H2BC13, H2BC14. H2BC15, H2BC17, H2BC21. H2BC3. H2BC4, H2BC5, H2BC6, H2BC7, H2BC8, H2BC9, H2BS1,H2BLI1, H3-3A, H3-3B, H3C1, H3C10, H3C11, H3C12, H3C13, H3C14, H3C15, H3C2, H3C3, H3C4, H3C6, H3C7, H3C8, H4-16, H4C1, H4C11, H4C12, H4C13, H4C14, H4C15, H4C2, H4C3, H4C4, H4C5, H4C6, H4C8, H4C9, HDAC1 , HDAC2, JARID2, KAT2A, KAT2B, MBD2, MBD3, MNAT1, MTA1, MTA2, MTA3, MTF2, MYBBP1A, MY01C, ,PHF1, PHF19, P0LR1A, P0LR1B, P0LR1C, P0LR1D, P0LR1E, P0LR1F, P0LR1G, P0LR1H, P0LR2E, P0LR2F, P0LR2H, P0LR2K, P0LR2L, RBBP4, RBBP7, RRP8, SAP130, SAP18, SAP30, SAP30BP, SAP30L, SF3B1 , SIN3A, SIN3B, SIRT1 , SMARCA5, SUDS3, SUV39H1 , SUZ12, TAF1 A, TAF1 B, TAF1 C, TAF1 D, TBP, TDG, TET1 , TET2, TET3, TTF1 , UBTF, UHRF1 ;(viii) ABL1, ACD, AKT1, ATM, BLM, CCND1, CDKN1B, DKC1, E2F1, EGF, EGFR, ESR1, FOS, HDAC1, HDAC2, HNRNPC, HSP90AA1, HUS1, IFNAR2, IFNG, IL2, IRF1, JUN, MAPK1, MAPK3, MAX, MRE11, MTOR, MXD1, MYC, NBN, NCL, NFKB1, NR2F2, PARP2, PINX1, POT1, PTGES3, RAD1, RAD50, RAD9A, RBBP4, RBBP7, RPS6KB1, SAP18, SAP30, SIN3A, SIN3B, SMAD3, SMG5, SMG6, SP1, SP3, TERF1, TERF2, TERF2IP, TERT, TGFB1, TINF2, TNKS, UBE3A, WRN, WT1 , XRCC5, XRCC6, YWHAE, ZNFX1;(ix) CAMK4, CREB1, ESRRA, ABPA, GABPB1, GABPB1-IT1, HCFC1, MTERF1, MTERF3, MYEF2, NRF1, POLRMT, PPARGC1A, PPARGC1B, PPP3CA, PPRC1, SP1, TFAM, TFB1 M, and TFB2M.

42. The method of any one of claims 12-41, wherein the cellular condition associated with aging comprises chronic inflammation; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from CD28, CD40, CD40LG, CD80, CD86, COL1A1, COL1A2, COL3A1, FN1, IFNG, IL2, IL2RA, IL2RB, IL2RG, IL4, IL4R, IL5, IL5RA, LAMA5, LAMB1, LAMB2, LAMC1, LAMC2, LOK, MIR3606, MIR4758, MIR7846, THBS1, THBS3, TNFRSF1A, TNFRSF1B, VTN, and ZAP70.

43. The method of any one of claims 12-41, wherein the cellular condition associated with aging comprises cellular senescence; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one ormore genes selected from ATM, ATR, CDKN1 A, CDKN2A, CHEK1 , CHEK2, CTC1 , ERCC1 , MIR21 , MME, PLA2R1 , ROMO1 , SERPINE1 , TERT, TP53, WNT16, and WRN.

44. The method of any one of claims 12-41 , wherein the cellular condition associated with aging comprises altered intracellular communication; and the set of biomarker associated with aging or age-related disease comprises differential activation or expression in one or more genes selected from ACTB, ACTG1 , ACTN1 , ACTN2, ACTN3, ACTN4, AFDN, ANG, ARHGEF6, CADM1 , CADM2, CADM3, CASK, CD151 , CD2AP, CD47, CDH1 , CDH10, CDH1 1 , CDH12, CDH13, CDH15, CDH17, CDH18, CDH2, CDH24, CDH3, CDH4, CDH5, CDH6, CDH7, CDH8, CDH9, CLDN1 , CLDN10, CLDN1 1 , CLDN12, CLDN14, CLDN15, CLDN16, CLDN17, CLDN18, CLDN19, CLDN2, CLDN20, CLDN22, CLDN23, CLDN3, CLDN4, CLDN5, CLDN6, CLDN7, CLDN8, CLDN9, COL17A1 , CRB3, CTNNA1 , CTNNB1 , CTNND1 , DST, F11 R, FBLIM1 , FERMT2, FLNA, FLNC, FYB1 , FYN, GRB2, ILK, IQGAP1 , ITGA6, ITGB1 , ITGB4, JUP, KIRREL1 , KIRREL2, KIRREL3, KRT14, KRT5, LAMA3, LAMB3, LAMC2, LIMS1 , LIMS2, MAGI2, NCK1 , NCK2, NECTIN1 , NECTIN2, NECTIN3, NECTIN4, NPHS1 , NPHS2, PALS1 , PARD3, PARD6A, PARD6B, PARD6G, PARVA, PARVB, PATJ, PIK3CA, PIK3CB, PIK3R1 , PIK3R2, PLEC, PRKCI, PTK2, PTK2B, PTPN11 , PTPN6, PVR, PXN, RSU1 , SDK1 , SDK2, SFTPA1 , SFTPA2, SFTPD, SIRPA, SIRPB1 , SIRPG, SKAP2, SPTAN1 , SPTBN1 , SRC, TESK1 , TYROBP, VASP, and WASL.

45. The method of any one of claims 12-41 , wherein the cellular condition associated with aging comprises stem cell exhaustion; and the set of biomarkers associated with aging or age-related disease comprises differential activation or expression in one or more genes selected from NUPR1 , ENPP5, GPR183, CD38, NEO1 , FHL1 , PBX3, ALCAM, ALDH1A1 , EBI3, DHRS3, PLEK, CD37, CLU, EHD3, CPNE8, PRCP, CD86, SULT1A1 , EFNA1 , SATB1 , PLSCR1 , GADD45G, TGM2, RORC, BMPR1 A, GEM, CYSLTR2, RASSF4, LPL, DSG2, TRIM47, STOM, IL15, TM6SF1 , RNASE6, MMP2, ARHGAP30, SLAMF1 , NPDC1 , NDRG1 , ABAT, DENND5B, TSC22D1 , ANXA6, MEF2C, CYTIP, MCM7, PERP, THBD, LAMP2, CYB561 , PLAC8, LST1 , TMEM176A, LPAR6, TC2N, PROCR, FLT3,CAVIN2, MMP14, JUN, EGR1, ID2, BCL6, S100A6, IL12RB2, MGST1, ZFP36, CSF2RB, LSR, ECT2, MY01 E, SERPINB8, CXCL16, PPP1 R16B, LSP1 , TNFSF10, CD9, PLA2G4A, DHX40, EVC, LGALS1, NDN, SELL, MLLT3, ANXA2, OXR1, GSTM1, BTG2, OTSS, ACSL4, SOCS2, MLEC, SEMA7A, PLXDC2, RFC2, EXOC6B, MCM5, GPX3, TOX, LY6E, CD63, RDH10, PLCL1, PTGER4, MAF, VMP1, RAB34, TBC1 D8, DDR1, AMPD3, SYK, ANTXR2, LDHD, PDGFD, ACPP, CAMK1 D, PRNP, and PHACTR1.

46. The method of any one of claims 12-41, wherein the cellular condition associated with aging comprises deregulated nutrient sensing; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from ADIPOR1, AGT, AHSG, APPL2, ATP2B1, BGLAP, C1QTNF12, ECHDC3, ENPP1, ERFE, ESRRA, GKAP1, GNAI2, GPLD1 , GPR21 , GRB10, GRB14, GRB7, GSK3A, IGF2, IL1B, INPP5K, INS, IRS1, KANK1, LEP, LPL, MIR103A1, MIR107, MIR1271, MIR15B, MIR195, MSTN, MYO1C, NCK1, NCOA5, NR1H4, NUCKS1, OSBPL8, PID1, PIP4K2A, PIP4K2B, PIP4K2C, PRKAA1, PRKCB, PRKCD, PRKCQ, PRKCZ, PTPN1, PTPN11, PTPN2, PTPRE, RPS6KB1, SERPINA12, SIRT1, SLC27A4, SNX5, SOCS1, SOCS3, SORBS1, SORL1, SRC, TNS2, TRIM72, TSC2, USO1, and ZBTB7B.

47. The method of any one of claims 12-41, wherein the cellular condition associated with aging comprises loss of proteostasis garbaging; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from AFG3L2, AHSP, AIP, AIPL1, APCS, CALR, CALR3, CANX, CCDC115, CCT2, CCT3, CCT4, CCT5, CCT6A, CCT6B, CCT7, CCT8, CCT8L1 P, CCT8L2, CDC37, CDC37L1, CHAF1A, CHAF1B, CLGN, CLPX, CLU, CRYAA, CRYAB, DNAJA1, DNAJA2, DNAJA3, DNAJA4, DNAJB1 , DNAJB11 , DNAJB13, DNAJB2, DNAJB3, DNAJB4, DNAJB5, DNAJB6, DNAJB7, DNAJB8, DNAJC4, ERLEC1, ERN1, ERN2, ERO1B, GRPEL1, GRPEL2, HEATR3, HSP90AA1, HSP90AA2P, HSP90AA4P, HSP90AA5P, HSP90AB1, HSP90AB2P, HSP90AB3P, HSP90AB4P, HSP90B1, HSP90B2P, HSPA13, HSPA14, HSPA1A, HSPA1B, HSPA1L, HSPA2, HSPA5, HSPA6,HSPA7, HSPA8, HSPA9, HSPB6, HSPD1, HSPE1, HTRA2, HY0U1, LMAN1, MKKS, NACA, NACA2, NACA4P, NACAD, NAP1L4, NDUFAF1, NPM1, NUDC, NUDCD2, NLIDCD3, PDRG1, PET100, PFDN1, PFDN2, PFDN4, PFDN5, PFDN6, PPIA, PPIB, PTGES3, RP2, RLIVBL2, SOAP, SCG5, SERPINH1, SHQ1, SIL1, SPG7, SRSF10, SRSF12, SYVN1, TAPBP, TCP1 , TIMM10B, TMEM67, TOMM20, TOR1A, TRAP1, TTC1, TUBB4B, UGGT1, UGGT2, and VBP1.

48. The method of any one of claims 12-41, wherein the cellular condition associated with aging comprises epigenetic alterations; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from ACTB, AEBP2, ARID4B, BAZ1 B, BAZ2A, CBX3, CCNH, CDK7, CHD3, CHD4, DDX21, DEK, DNMT1 , DNMT3A, DNMT3B, DNMT3L, EED, EHMT2, EP300, ERCC2, ERCC3, ERCC6, EZH2, GATAD2A, GATAD2B, GSK3B, GTF2H1, GTF2H2, GTF2H3, GTF2H4, GTF2H5, H2AB1, H2AC14, H2AC20, H2AC4, H2AC6, H2AC7, H2AC8, H2AJ, H2AX, H2AZ1, H2AZ2, H2BC1, H2BC10, H2BC11, H2BC12, H2BC13, H2BC14. H2BC15, H2BC17, H2BC21. H2BC3. H2BC4, H2BC5, H2BC6, H2BC7, H2BC8, H2BC9, H2BS1, H2BU1, H3-3A, H3-3B, H3C1, H3C10, H3C11, H3O12, H3C13, H3C14, H3C15, H3C2, H3C3, H3C4, H3C6, H3C7, H3C8, H4-16, H4C1, H4C11, H4C12, H4C13, H4C14, H4C15, H4C2, H4C3, H4C4, H4C5, H4C6, H4C8, H4C9, HDAC1, HDAC2, JARID2, KAT2A, KAT2B, MBD2, MBD3, MNAT1 , MTA1, MTA2, MTA3, MTF2, MYBBP1A, MYO1C, ,PHF1, PHF19, POLR1A, POLR1B, POLR1C, POLR1D, POLR1E, POLR1F, POLR1G, POLR1H, POLR2E, POLR2F, POLR2H, POLR2K, POLR2L, RBBP4, RBBP7, RRP8, SAP130, SAP18, SAP30, SAP30BP, SAP30L, SF3B1, SIN3A, SIN3B, SIRT1, SMARCA5, SUDS3, SUV39H1 , SUZ12, TAF1 A, TAF1 B, TAF1 C, TAF1 D, TBP, TDG, TET1 , TET2, TET3, TTF1 , UBTF, and UHRF1.

49. The method of any one of claims 12-41, wherein the cellular condition associated with aging comprises telomere attrition; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from ABL1 , ACD, AKT1 , ATM, BLM, CCND1 , CDKN1 B, DKC1 , E2F1 ,EGF, EGFR, ESR1 , FOS, HDAC1 , HDAC2, HNRNPC, HSP90AA1 , HUS1 , IFNAR2, IFNG, IL2, IRF1 , JUN, MAPK1 , MAPK3, MAX, MRE11 , MTOR, MXD1 , MYC, NBN, NCL, NFKB1 , NR2F2, PARP2, PINX1 , POT1 , PTGES3, RAD1 , RAD50, RAD9A, RBBP4, RBBP7, RPS6KB1 , SAP18, SAP30, SIN3A, SIN3B, SMAD3, SMG5, SMG6, SP1 , SP3, TERF1 , TERF2, TERF2IP, TERT, TGFB1 , TINF2, TNKS, UBE3A, WRN, WT1 , XRCC5, XRCC6, YWHAE, and ZNFX1 .

50. The method of any one of claims 12-41 , wherein the cellular condition associated with aging comprises mitochondrial dysfunction; and the set of biomarkers associated with aging or age-related disease comprise differential activation or expression in one or more genes selected from CAMK4, CREB1 , ESRRA, ABPA, GABPB1 , GABPB1 - IT1 , HCFC1 , MTERF1 , MTERF3, MYEF2, NRF1 , POLRMT, PPARGC1A, PPARGC1 B, PPP3CA, PPRC1 , SP1 , TFAM, TFB1 M, and TFB2M.

51. The method of any one of claims 12 to 50, wherein the one or more interventions further comprises one or more pharmaceutical agents, dietary supplements, and / or lifestyle changes.

52. The method of claim 51 , wherein the one or more dietary supplements comprise one or more nutraceuticals or nutritional supplements.

53. The method of claim 52, wherein the one or more nutraceuticals and / or nutritional supplements comprise one or more of acarbose, ashwagandha, B complex, B12- methylcobalamin, berberine, C vitamin, Ca-Alpha Ketoglutarat, cocoa flavanols, dehydroepiandrosterone (DHEA), E vitamin, eicosapentaenoic acid (EPA), garlic, ginger root, glucosamine sulphate, glycine, hyaluronic Acid, iodine (e.g., as potassium iodide), L- theanine, lithium, (e.g., as lithium orotate), lycopene, lysine, malate, nicotinamide riboside, pea protein, proferrin, pterostilbene, taurine, turmeric, ubiquinol, zeaxanthin, zinc, resveratrol, quercetin, nattokinase, CoQ10, fisetin, magnesium, nicotinamide mononucleotide (NMN), N-acetyl cysteine, alpha ketoglutaric acid, omega-3 fatty acids,collagen, raspberry ketones, green tea leaf extract, vitamin D3, vitamin B12, alpha-lipoic acid, probiotics, prebiotics, echinacea, garcinia cambogia, iron, multivitamins, and calcium citrate.

54. The method of claim 52 or claim 41 , wherein the one or more nutraceuticals and / or nutritional supplements comprise one or more of quercetin, nattokinase, CoQ10, fisetin, magnesium, nicotinamide mononucleotide (NMN), N-acetyl cysteine, and alpha ketoglutaric acid.

55. The method of any one of claims 12-54 and 26, wherein the one or more lifestyle changes comprise one or more of increasing activity level, changing the method of activity, increasing sleep duration, decreasing blue light exposure, increasing protein intake, decreasing sugar intake, performing heat and / or cold shock therapy, performing mindfulness exercises, not smoking, having moderate alcohol consumption, increasing daily intake of fruits and vegetables, maintaining a healthy body mass index and waist-to-hip ratio, restricting diet, intermittent fasting, adjusted diurnal rhythm of feeding, having a balanced diet, practicing sun protection, managing stress levels, increasing hydration, maintaining social connections, increasing cognitive stimulation, practicing good hygiene and oral care, and having a positive attitude.

56. A treatment plan for monitoring, delaying, or preventing onset of an age- related disease in a subject, prepared by: identifying a set of biomarkers associated with age-related disease in the subject by determining differences in gene activation or gene expression between a population of aged cells derived from the subject and a population of control cells derived from the subject, wherein the population of aged cells is obtained by exposing a first population of cells from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging in the cells, and the population of control cells is obtained by exposing a second population of cells from the subject to normal gravity;correlating the set of biomarkers associated with age-related disease with one or more therapies to prevent or delay onset of the age-related disease in the subject; and developing a treatment plan to provide one or more interventions to the subject to prevent or delay onset of the age-related disease.

57. The treatment plan of claim 56, wherein the one or more interventions further comprise one or more pharmaceutical agents, nutraceuticals, nutritional supplements, and / or lifestyle changes.

58. A method of determining a risk of developing an age-related disease in a subject, the method comprising the steps of:(a) receiving aged data obtained from one or more analyses performed on a population of aged cells produced by exposing a first population of cells from the subject to simulated microgravity for an amount of time sufficient to induce accelerated aging;(b) receiving control data obtained from one or more analyses performed on a population of control cells produced by exposing a second population of cells from the subject to normal gravity;(c) comparing the aged data received in (a) to the control data received in (b);(d) identifying a set of biomarkers based on differences in gene activation or gene expression based on the comparing in (c);(e) correlating the biomarkers of (d) to a set of biomarkers known to be associated with the age-related disease;(f) based on the correlating in (e), determining a presence of one or more age-related biomarkers expressed by the population of aged cells;(g) quantifying an expression level of the one or more age-related biomarkers in (f);(h) identifying the subject as having(A) a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than a high-risk threshold, or(B) a low risk for developing the age-related disease if the biomarkers in (g) are expressed below the high-risk threshold; and(i) developing a treatment plan for the subject based on the identification in (h).

59. The method of claim 58, wherein the high-risk threshold is equal to or greater than 0.15, and wherein the biomarkers in (g) comprise one or more genes associated with chronic inflammation and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

60. The method of claim 59, wherein the high-risk threshold is 0.21 .61 . The method of claim 58, wherein the high-risk threshold is equal to or greater than 0.25, and wherein the biomarkers in (g) comprise one or more genes associated with cellular senescence and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

62. The method of claim 61 , wherein the high-risk threshold is 0.29.

63. The method of claim 58, wherein the high-risk threshold is equal to or greater than 0.05, and wherein the biomarkers in (g) comprise one or more genes associated with altered intracellular communication and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

64. The method of claim 63, wherein the high-risk threshold is 0.07.

65. The method of claim 58, wherein the high-risk threshold is equal to or greater than 0.25, and wherein the biomarkers in (g) comprise one or more genes associated withstem cell exhaustion and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

66. The method of claim 65, wherein the high-risk threshold is 0.30.

67. The method of claim 58, wherein the high-risk threshold is equal to or greater than -0.80, and wherein the biomarkers in (g) comprise one or more genes associated with deregulated nutrient sensing and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high- risk threshold.

68. The method of claim 67, wherein the high-risk threshold is -0.85.

69. The method of claim 58, wherein the high-risk threshold is equal to or greater than -0.80, and wherein the biomarkers in (g) comprise one or more genes associated with loss of proteostasis garbaging and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

70. The method of claim 69, wherein the high-risk threshold is -0.87.71 . The method of claim 58, wherein the high-risk threshold is equal to or greater than -0.10, and wherein the biomarkers in (g) comprise one or more genes associated with epigenetic alterations and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

72. The method of claim 71 , wherein the high-risk threshold is -0.13.

73. The method of claim 58, wherein the high-risk threshold is equal to or greater than -0.05, and wherein the biomarkers in (g) comprise one or more genes associated with telomere attrition and the subject is identified as having a high risk for developing the age- related disease if the biomarkers in (g) are expressed at or greater than the high-risk threshold.

74. The method of claim 73, wherein the high-risk threshold is -0.07.

75. The method of claim 58, wherein the high-risk threshold is equal to or greater than -0.10, and wherein the biomarkers in (g) comprise one or more genes associated with mitochondrial dysfunction and the subject is identified as having a high risk for developing the age-related disease if the biomarkers in (g) are expressed at or greater than the high- risk threshold.

76. The method of claim 75, wherein the high-risk threshold is -0.14.

77. A non-transitory medium with instructions stored thereon that, when executed by a processor of a computing device, causes the computing device to perform steps for the methods of any one of claims 1 to 60.

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