WO2012164525A2

WO2012164525A2 - Aging biomarkers

Info

Publication number: WO2012164525A2
Application number: PCT/IB2012/052750
Authority: WO
Inventors: Johan Auwerx; Richardus HOUTKOOPER; Sander Houten; Carmen Argmann
Original assignee: Ecole Polytechnique Federale De Lausanne (Epfl); Academisch Medisch Centrum
Priority date: 2011-06-01
Filing date: 2012-05-31
Publication date: 2012-12-06
Also published as: WO2012164525A3

Abstract

The present invention relates to novel biomarkers for aging and healthspan, methods and uses thereof, in particular, for determining the biological age of a subject and/or preventing or delaying aging process in a subject, and kits for use in said methods.

Description

AGING BIOMARKERS

Field of the Invention

Background of the Invention

Aging (and ultimately death) is an inevitable part of life and comes with all sorts of physical and mental ailments, including common metabolic, inflammatory, cardiovascular and neurodegenerative diseases, which will reduce healthspan. Examples of such diseases include Parkinson's and Alzheimer's disease, and from a cardio metabolic perspective, obesity, type 2 diabetes, and atherosclerosis.

Even though these clinical manifestations are well known, the complex biomolecular networks contributing to the aging process are only beginning to be uncovered (Houtkooper et al, 2010). Several common processes are suggested to cause or at least contribute to aging, including DNA damage, accumulation of reactive oxygen species (ROS), and general metabolic dysfunction. So far, these were mostly seen as independent events, but evidence suggests that some of these pathways are interconnected, as recently highlighted by the link between DNA damage and metabolic control (Bai et al, 2011; Sahin et al., 2011).

Regardless of the mechanism, a common feature of aging-related disease is the involvement of metabolic systems in general, and the mitochondria in particular (Houtkooper et al, 2010; Kenyon, 2010). The best-characterized metabolic pathway implicated in aging is the insulin/IGF 1 signaling pathway (Russell and Kahn, 2007). Both the C. elegans and D. melanogaster mutants of insulin receptor showed increased lifespan and the effect is mediated through the FOXOl (Forkhead box protein 01) transcription factor, the heat-shock factor HSF1 (Heat shock factor protein 1), and SKN1 transcription factor (reviewed in (Kenyon, 2010). Involvement of the insulin/IGF 1 pathway in mammalian lifespan regulation is debated but seems likely (Russell and Kahn, 2007). A second longevity pathway is centered on the mammalian target of rapamycin (mTOR), which integrates insulin signaling with sensing of other nutrients— most notably amino acids— and as such regulates protein translation and autophagy (Zoncu et al., 2011). In line with this, mTOR was shown to be involved in the aging-associated decrease in ketone body production (Sengupta et al, 2010) and inhibition of mTOR by administration of rapamycin increased mouse lifespan (Harrison et al, 2009). Opposing these nutrient excess systems are the nutrient restriction pathways, such as the sirtuin and AMP-activated protein kinase (AMPK) pathways (Haigis and Sinclair, 2010). Being activated by energy stress, for instance after prolonged fasting or exercise, they inhibit energy-demanding processes in favor of energy-production (Canto and Auwerx, 2009). Both sirtuins and AMPK have been suggested as positive regulators of longevity in lower organisms (discussed in (Houtkooper et al, 2010), but as for the insulin/IGF 1 pathway, convincing involvement in mammalian longevity needs to be confirmed. In C. elegans, AMPK was shown to directly phosphorylate the CREB-regulated transcriptional coactivator- 1, which then becomes unable to coactivate the CREB transcription factor to decrease lifespan (Mair et al, 2011), indicating an aging pathway that could be conserved in mammals. Additionally, in mouse, AMPK has been connected with SIRT1 (Canto et al, 2009) and PGC-Ια signaling (Canto et al, 2009; Canto et al, 2010) consolidating the link of this system with mitochondrial metabolism, notably mitochondrial respiration. It is still debated, however, how mitochondrial function impacts aging, as both inhibiting and stimulating mitochondrial metabolism seems to enhance lifespan (discussed in (Houtkooper et al, 2010; Kenyon, 2010)). Most likely, the physiological context and the nature of the manipulation itself may determine the aging response. This phenotype seems at least partly mediated by the mitochondrial unfolded protein response and acts in a cell-non-autonomous fashion involving a yet unidentified "mitokine" (Durieux et al, 2011).

Aging and the diseases associated with it are a heavy burden on society. The current increase in life expectancy not only impacts on our social systems, but also goes hand in hand with the emergence of common chronic diseases, including those of the nervous, immune, and cardio -metabolic systems, which often reach epidemic proportions. In this respect it is important to understand the natural aging process and to elucidate where lifestyle and/or pharmacological interventions can have an impact. In recent years, many novel therapeutic options have been suggested to prevent aging-associated disease. Although some of these pharmaceutical interventions were shown to extend lifespan, even in mammals (Harrison et al, 2009; Pearson et al, 2008), there is no good readout for improved healthspan as aging biomarkers have not been identified. Therefore, there is still a need for novel aging biomarkers which would be useful for better understanding aging process and be a very efficient tool for monitoring aging process and for treating age-related diseases.

The present invention solves this problem by identifying novel aging biomarkers and providing sets of biomarkers with a high predictive accuracy.

Summary of the Invention

The present invention is directed towards novel biomarkers for aging and healthspan, methods and uses thereof.

A first aspect of the invention provides an ex-vivo method of determining the biological age of a subject comprising at least one method selected from:

(1) an ex-vivo method comprising the steps of:

a) Obtaining a blood sample from a subject;

b) Determining the level of at least one, at least two, or at least three, metabolite(s) selected from the group consisting of:

(i) medium and long chain acylcarnitines

(ii) unsaturated fatty acids

(iii) amino acids selected from the group consisting of proline, alanine, serine, tyrosine, and methionine; and

in said blood sample;

(2) an ex-vivo method comprising the steps of:

a) Obtaining a liver sample from a subject;

Maltose, Glucose, Maltotetraose, Glycerol-3-phosphate, Phenylacetylglycine, Malate, Gamma-glutamylleucine, Xanthosine, 5-dodecenoate (C12: ln7), Reduced glutathione (GSH), Ascorbate, Inosine, Alpha-tocopherol, Lactate, Cysteine, Cysteine-glutathione disulfide, Choline, Tagatose, Hexadecanedioate, Ophthalmate, Xylonate, Palmitoyl ethanolamide, Cytidine 5'-diphosphocholine, Thiamin, Hydroxyisovaleroyl carnitine, and NAD⁺;

in said liver sample; and

(3) an ex-vivo method comprising the steps of:

a) Obtaining a muscle sample from a subject; b) Determining the level of at least one, at least two, or at least three, metabolite(s) selected from the group consisting of:

Linoleate (C18:2n6), Dihomo-linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17: ln7), Oleate (C18: ln9), Cytidine, 10- nonadecenoate (C19:ln9), 1-arachidonoyl GPI, Glycerophosphorylcholine, Fructose, 12-HETE, Linolenate (C18:3n3 or 6), Eicosenoate (C20:ln9 or 11), Uridine 5 '-monophosphate, Margarate (C17:0), Eicosapentaenoate (C20:5n3), Dihomo-linolenate, Maltose, Carnosine, Methyl palmitate (15 or 2), Docosapentaeonoate (C22:5n6), Myristate (C14:0), Caproate (C6:0), Choline, and NAD⁺;

in said muscle sample.

A second aspect of the invention relates to an ex-vivo use of at least one, at least two, or at least three, metabolite(s) selected from the group mentioned above from a biological sample of a subject for determining the biological age of said subject.

A third aspect of the invention relates to an ex-vivo method for detecting the development of an age-related disease or disorder in a subject comprising determining at least one metabolite selected from the groups mentioned above in a biological sample of a subject.

A fourth aspect of the invention relates to a method of treating, preventing, or delaying, an age-related disease or disorder in a subject, comprising administering in a subject an effective amount of an agent or composition that increases the level of C18:2co6 and/or C18:3co3 fatty acids and/or increases the level of long and medium chain acylcarnitines including C16 acylcarnitine, in the blood of said subject.

A fifth aspect of the invention resides in an agent or composition that increases the level of C18:2co6 and/or C18:3co3 fatty acids and/or increases the level of long and medium chain acylcarnitines including C16 acylcarnitine, in the blood of a subject, for use in the treatment or prevention of an age-related disease or disorder in said subject.

A sixth aspect of the invention relates to a method of screening a compound for its ability to inhibit or delay the aging process in a subject comprising any one of the methods (1), (2) or (3) mentioned above.

A seventh aspect of the invention relates to an ex-vivo method of monitoring the aging process in a subject comprising any one of the methods (1), (2) or (3) mentioned above. An eighth aspect of the invention is a kit for carrying out any of the methods and uses mentioned above.

Other features and advantages of the invention will be apparent from the following detailed description.

Description of the figures

Figure 1 shows the metabolites present in blood samples which have the highest impact on predictive accuracy for aging.

Figure 2 shows the numerical values which led to the representation on the right-side of figure 1.

Figure 3 shows the metabolites present in liver samples which have the highest impact on predictive accuracy for aging.

Figure 4 shows the numerical values which led to the representation on the right-side of figure 3.

Figure 5 shows the metabolites present in muscle samples which have the highest impact on predictive accuracy for aging.

Figure 6 shows the numerical values which led to the representation on the right-side of figure 5.

Figure 7 shows the effect of aging on global parylation, NAD⁺ content and SIRT1 activity. Global PARylation as a marker for PARP activity is assessed using a aPAR antibody (left panels) in liver samples (top) and muscle samples (bottom). NAD⁺ levels in liver samples (top) and muscle samples (bottom) are represented in the middle panels, NAD+ was measured using an enzymatic cycle reaction (Enzychrom, Bio Assays Systems). SIRT1 activity was evaluated by measuring acetylation of PGC-la (right panels). Ac-Lys represents acetylation status of lysine residues, in the case of PGC-la representative for SIRT1 activity. For each panel, the samples from young mice are represented on the left side while the samples from old mice are represented on the right side.

Detailed Description of the invention

The term "subject" as used herein refers to mammals. For example, mammals contemplated by the present invention include human, primates, domesticated animals such as cattle, sheep, pigs, horses, laboratory rodents including rat and mouse. "Biological age" refers to the physiological state of an animal, preferably a mammal, or of the tissue from said animal, relative to the physiological changes that occur throughout the animal's lifespan.

"Chronological age" refers to the age of an animal as measured by a time scale, such as months and years.

A subject can be qualified either as "young" or "old" based on his chronological age. The age value above which a subject is qualified as an "old" subject, or below which he/she/it is qualified as a "young" subject, is a relative value that depends on the life-expectancy of a population of subjects of the same animal species. As first estimate, and without being limited to this estimation, the cut-off age value could generally be about half of the life- expectancy. For instance, a mouse that is 13 weeks old is considered as a "young" mouse, whereas a mouse that is 93 weeks old is considered as an "old" mouse. In humans, a 20 year- old subject is considered as a young subject, whereas an 80 year-old is considered as an old subject.

As used herewith, the term "metabolite" refers to endogenous organic compounds of a cell, an organism, a tissue or being present in biological samples obtained from a subject as defined above. As defined herewith, metabolites are derived from intermediary metabolism and have typically a molecular weight below 1500 Dalton. Typical examples of metabolites are carbohydrates, lipids, phospholipids, sphingolipids and sphingophospho lipids, amino acids, tripeptides, cholesterol, steroid hormones and oxidized sterols. This includes any substance produced by metabolism or by a metabolic process and any substance involved in metabolism. The metabolites according to the invention are preferably those related to fatty acid metabolism, phospholipid metabolism, triglyceride metabolism, amino acid metabolism, glucose metabolism including intermediates of glycolysis and glycogen metabolism, and redox homeostasis.

As defined herewith "acylcarnitine" refers to the condensation product of a carboxylic acid and carnitine. This corresponds to the transport form for a carboxylic acid crossing the mitochondrial membrane. The term "acylcarnitines" covers short, medium, and long chain acylcarnitines. "Medium chain acylcarnitines" refers to acylcarnitines of 6-12 carbon atoms in length. "Long chain acylcarnitines" refers to acylcarnitines of 12-22 carbon atoms in length.

"Biological sample" refers to any sample that is obtained from the subject's body. Biological samples include, for instance, samples of mammal, preferably human, whole blood, erythrocytes, serum, plasma, urine, cerebrospinal fluid, tear fluid, sweat, milk as well as liver tissue sample, muscle tissue sample.

Biological sample preferably covers blood sample, liver sample and muscle sample.

"Blood sample" refers to a sample of whole blood of the subject. It also includes herewith erythrocytes, serum and plasma samples. As used herewith, blood generally refers to both erythrocytes and plasma.

"Liver sample" refers to any sample from the liver of the subject.

"Muscle sample" refers to any sample from a muscle of the subject. It includes gastrocnemius, soleus and quadriceps muscle samples, such as a needle biopsy from the vastus lateralis.

Preferably, the biological sample is blood or plasma, as it is easily obtained without the need of sacrificing the animal or being too invasive in humans.

As defined herewith, "age-related disease or disorder" refers to a disease or disorder generally observed in old subjects. It includes common metabolic, inflammatory, cardiovascular and neurodegenerative diseases. Examples of age-related diseases or disorders include Parkinson's disease, Alzheimer's disease, obesity, type 2 diabetes, atherosclerosis, reduced kidney function (renal insufficiency), reduced skeletal muscle strength (sarcopenia), chronic inflammatory diseases (arthritis, arthrosis), anemia.

As used herein, "treatment" and "treating" and the like generally mean obtaining a desired pharmacological and physiological effect. The effect may be prophylactic in terms of preventing or partially preventing a disease, symptom or condition thereof and/or may be therapeutic in terms of a partial or complete cure of a disease, condition, symptom or adverse effect attributed to the disease. The term "treatment" as used herein covers any treatment of a disease in a mammal, particularly a human, and includes: (a) preventing the disease from occurring in a subject which may be predisposed to the disease but has not yet been diagnosed as having it such as a preventive early asymptomatic intervention; (b) inhibiting the disease, i.e., arresting its development; or relieving the disease, i.e., causing regression of the disease and/or its symptoms or conditions such as improvement or remediation of damage. In particular, the methods, uses, formulations and compositions according to the invention are useful in the treatment of age-related diseases and disorders and/or in the prevention of evolution of an age-related diseases and disorders into its final stage and possibly death. When applied to an age-related disease or disorder such as, for instance, Alzheimer's or Parkinson's disease, prevention of a disease or disorder includes the prevention of the appearance or development of said disease in an individual identified as at risk of developing said disease, for instance due to past occurrence of said disease in the circle of the individual's relatives.

Also covered by the terms "prevention/treatment" of an age-related disease is the stabilization of an already diagnosed age-related disease or disorder in an individual. By "stabilization", it is meant the prevention of evolution of said disease into advanced or final stage in subject with the disease at an early stage.

The term "effective amount" as used herein refers to an amount of at least one metabolite, composition or pharmaceutical formulation thereof according to the invention, that elicits the biological or medicinal response in a tissue, system, animal or human that is being sought. In one embodiment, the effective amount is a "therapeutically effective amount" for the alleviation of the symptoms of the disease or condition being treated. In another embodiment, the effective amount is a "prophylactically effective amount" for prophylaxis of the symptoms of the disease or condition being prevented. The term also includes herein the amount of active polypeptide sufficient to reduce the progression of the disease, notably to reduce or inhibit the tumor growth or infection and thereby elicit the response being sought (i.e. an "inhibition effective amount").

The term "efficacy" of a treatment according to the invention can be measured based on changes in the course of disease in response to a use or a method according to the invention. For example, the efficacy of a treatment of an age-related disease or disorder can be measured by a reduction of the symptoms of the disease or disorder, for instance increased muscle strength, better glucose tolerance, increased cold tolerance, increased exercise capacity.

The nomenclature for some of the metabolites according to the invention is presented in Table 1 and will be used along the text of the present application.

Table 1. Nomenclature for the metabolites referred to herewith

Common name Lipid/ Glucid/ other Chemical IUPAC name

name

Linoleic acid, C18:2(n-6) (9Z,12Z)-octadeca-9,12-dienoic Linoleate acid Common name Lipid/ Glucid/ other Chemical IUPAC name

name

Gamma- lino lenic acid C18:3(n-3) (6Z,9Z,12Z)-octadeca-6,9,12- trienoic acid

Arachidonic acid C20:4(n-6) (5Z,8Z,l lZ,14Z)-icosa-5,8,l l,14- tetraenoic acid

Docosapentaenoic acid C22:5(n-6) (4Z,7Z, 10Z, 13Z, 16Z)-docosa- 4,7,10,13,16-pentaenoic acid

Vaccenic Acid C18: l(n-7) (1 lZ)-octadec-l 1-enoic acid nervonic acid C24: l(n-9) (15Z)-tetracos-15-enoic acid

Eicosapentaenoic acid C20:5(n-3) (5Z, 8Z, 11 Z, 14Z, 17Z)-icosa- 5,8,11,14,17-pentaenoic acid

5-Dodecenoic acid C12: l(n-7) (5Z)-dodec-5-enoic acid

Hexadecanedioic acid Hexadecanedioate hexadecanedioic acid

Eicosadienoic acid Dihomo-linoleate (1 lE,14E)-icosa-l 1,14-dienoic acid

(C20:2n6)

Heptadecenoic Acid 10-heptadecenoate (lOE)-heptadecanoic acid or (10Z)- (C17: ln7) heptadecanoic acid

oleic acid, C18: l(n-9) (9Z)-octadec-9-enoic acid

Oleate

Cytidine Cytidine 4-amino- 1 - [3 ,4-dihydroxy-5 - (hydroxymethyl)oxo lan-2-yl] - pyrimidin-2-one

Nonadeca- 10(Z)-enoic 10-nonadecenoate (Z)-nonadec-lO-enoic acid acid (C19: ln9)

α-Lino lenic acid or C18:3(n-3 or 6) (9Z, 12Z, 15Z)-octadeca-9, 12,15- Gamma- lino lenic acid or trienoic acid or (6Z,9Z,12Z)- Linolenate octadeca-6,9,12-trienoic acid eicosenoic acid, C20: l(n-9 or 11) Eicosenoic acid

Eicosenoate

Heptadecanoic acid Margarate (17:0) heptadecanoic acid Common name Lipid/ Glucid/ other Chemical IUPAC name

name

Eicosapentaenoic acid, C20:5 (n-3) (5Z, 8Z, 11 Z, 14Z, 17Z)-icosa- Eicosapentaenoate 5,8,11,14,17-pentaenoic acid

8,11 , 14-Eicosatrienoic Dihomo-linolenate (8E, 11 E, 14E)-icosa-8, 11 , 14-trienoic acid acid

Methyl palmitate Methyl palmitate (15 2-methyl-hexadecanoic acid or 15- or 2) methyl-hexadecanoic acid

Myristic acid, C14:0 tetradecanoic acid

Myristate

Caproic acid, C6:0 Hexanoic acid

Caproate

Palmitoylcarnitine C16 acylcarnitine (3R)-3-hexadecanoyloxy-4- trimethylazaniumylbutanoate

Lauroleoylcarnitine CI 2: 1 acylcarnitine 3-[(Z)-dodec-3-enoyl]oxy-4- trimethylazaniumylbutanoate or 3- [(Z)-dodec-5-enoyl]oxy-4- trimethylazaniumylbutanoate

Caproleoylcarnitine C10: l acylcarnitine 3-[(Z)-dec-3-enoyl]oxy-4- trimethylazaniumylbutanoate

Myristoylcarnitine C14 acylcarnitine 3-tetradecanoyloxy-4- (trimethylazaniumyl)butanoate

Caproylcarnitine C6 acylcarnitine 3-hexanoyloxy-4- trimethylazaniumylbutanoate

Maltose Maltose (2R,3S,4S,5R,6R)-2- (hydroxymethyl)-6-[(2R,3S,4R,5R)- 4,5 ,6-trihydroxy-2- (hydroxymethyl)oxan-3 - yl]oxyoxane-3,4,5-triol

Glucose Glucose (3R,4R,5S,6S)-6-

(hy droxymethy l)oxane-2 ,3,4,5- tetrol Common name Lipid/ Glucid/ other Chemical IUPAC name

name

Maltotetraose Maltotetraose 4-[5-[3,4-dihydroxy-6-

(hydroxymethyl)-5-[3,4,5- trihydroxy-6-(hydroxymethyl)oxan-

2-yl]oxy-oxan-2-yl]oxy-3 ,4- dihydroxy-6-(hydroxymethyl)oxan-

2-yl]oxy-2,3 ,5 ,6-tetrahydroxy- hexanal

Glycero 1-3 -phosphate Glycero 1-3- 1 ,2 ,3 -Propanetrio 1, 1 -(dihydrogen phosphate phosphate)

Phenylacetylglycine Phenylacetylglycine 2-(2-phenylacetyl)aminoacetic acid

Malate Malate 2-hydroxybutanedioic acid

L-gamma-glutamyl-L- Gamma- n/a

leucine glutamylleucine

Xanthosine Xanthosine Xanthine-9b-D-ribofuranoside

Reduced glutathione Reduced glutathione (2S)-2-amino-4-[[(lR)-l- (GSH) (GSH) (carboxymethylcarbamoyl)-2- sulfanyl-ethyl]carbamoyl]butanoic acid

Ascorbate (vitamin C) Ascorbate (vitamin (2S)-2-[(lR)-l,2-dihydroxyethyl]- C) 4 ,5 -dihydroxy-furan-3 -one

Inosine Inosine 9-[(2R,3R,4S,5R)-3,4-dihydroxy-5- (hydroxymethyl)oxo lan-2-yl] -3H- purin-6-one

Alpha-tocopherol Alpha-tocopherol (2R)-2,5,7,8-tetramethyl-2-

[(4R,8R)-4,8,12- trimethyltridecyl]chroman-6-ol

Lactate Lactate (2S)-2-hydroxypropanoic acid

Cysteine Cysteine (2R)-2-amino-3-sulfanyl-propanoic acid

Cysteine-glutathione Cysteine-glutathione (2S)-2-amino-4-[[(R)-[(2S)-2- disulfide disulfide amino-3 ,3-dihydroxy- propyl]sulfanylcarbothioyl

Choline Choline 2-hydroxyethyl-trimethyl- ammonium

Tagatose Tagatose (3S,4S,5R)-1,3,4,5,6- pentahydroxyhexan-2-one

Ophtalmate Ophtalmate (2S)-2-Amino-4-[[(2S)-2- aminobutanoyl] -

(carboxymethyl)carbamoyl]butanoic acid

Xylonate Xylonate (2R,3R,4R)-2,3,4,5- tetrahydroxypentanoate Common name Lipid/ Glucid/ other Chemical IUPAC name

name

Palmitoyl ethanolamide Palmitoyl N-(2-hydroxyethyl)hexadecanamide ethanolamide

Cytidine 5'- Cytidine 5'- 2-[[[5-(4-amino-2-oxo-pyrimidin- 1 - diphosphocholine diphosphocholine yl)-3 ,4-dihydroxy-oxolan-2- yljmethoxy-hydroxy- phosphoryljoxy-hydroxy- phosphoryljoxyethyl-trimethyl- azanium

Thiamin (vitamin Bl) Thiamin (vitamin 2- [3 - [(4-amino-2-methyl-p vrimidin- Bl) 5 -yl)methyl] -4-methyl- 1 -thia-3 - azoniacyclopenta-2,4-dien-5- yljethanol

Hydroxyisovaleroyl Hydroxyisovaleroyl 3 - [4-hydroxy-3 -methyl- carnitine carnitine butanoyl]oxy-4- trimethylazaniumylbutanoate

Hydroxyproline Trans-4- (2S ,4R)-4-hydroxypyrro lidine-2- hydroxyproline carboxylic acid

Pantothenic acid Pantothenate 3-[[(2R)-2,4-dihydroxy-3,3- dimethyl-butanoyl]amino]propanoic acid

1 -arachidonoylglycero- 1-arachidonoyl GPI n/a

phosphoinositol

Glycerophosphorylcho line Glycerophosphorylc 2- [ [(2R)-2 ,3-dihydroxypropoxy] - ho line hydroxy-phosphoryljoxyethyl- trimethyl-azanium

Fructose Fructose (2R,3S,4S,5R)-2,5- bis(hydroxymethyl)oxolane-2,3,4- triol

12-Hydroxyeicosatetra- 12-HETE (5E,8Z, 10Z, 14Z)- 12-hydroxyicosa- enoic acid 5,8,10,14-tetraenoic acid

Uridine 5'- Uridine 5'- 5'-Uridylic acid

monophosphate monophosphate

Carnosine Carnosine (2S)-2-(3-aminopropanoylamino)-3- (3H-imidazol-4-yl)propanoic acid Biomarkers for aging according to the invention

In a first embodiment, the invention relates to metabolites, present in a biological sample from a subject, which are useful as biomarkers for aging in said subject or tissue's subject.

The metabolites useful as biomarkers for aging according to the invention are preferably those involved in fatty acid metabolism, phospholipid metabolism, amino acid metabolism, glucose metabolism including intermediates of glycolysis and glycogen metabolism, and redox homeostasis including NAD⁺.

In a specific aspect, the metabolites useful as biomarkers for aging are selected from at least one of:

(1) A first group of metabolites present in blood sample consisting of:

(i) medium and long chain acylcarnitines

(ii) unsaturated fatty acids

(iv) β-hydroxybutyrate;

(2) A second group of metabolites present in liver sample, consisting of:

Maltose, Glucose, Maltotetraose, Glycerol-3-phosphate, Phenylacetylglycine, Malate, Gamma-glutamylleucine, Xanthosine, 5-dodecenoate (C12: ln7), Reduced glutathione (GSH), Ascorbate, Inosine, Alpha-tocopherol, Lactate, Cysteine, Cysteine-glutathione disulfide, Choline, Tagatose, Hexadecanedioate, Ophtalmate, Xylonate, Palmitoyl ethanolamide, Cytidine 5'-diphosphocholine, Thiamin, Hydroxyisovaleroyl carnitine, and NAD⁺; and

(3) A third group of metabolites present in muscle sample, consisting of:

Linoleate (C18:2n6), Dihomo-linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17: ln7), Oleate (C18: ln9), Cytidine, 10- nonadecenoate (C19:ln9), 1-arachidonoyl GPI, Glycerophosphorylcholme, Fructose, 12-HETE, Linolenate (C18:3n3 or 6), Eicosenoate (C20: ln9 or 11), Uridine 5'- monophosphate, Margarate (C17:0), Eicosapentaenoate (C20:5n3), Dihomo- linolenate, Maltose, Carnosine, Methyl palmitate (15 or 2), Docosapentaeonoate (C22:5n6), Myristate (C14:0), Caproate (C6:0), Choline, and NAD⁺.

In a preferred aspect, the metabolites present in blood sample are selected from the group consisting of: C18:2co6 fatty acid, C16 acylcarnitine, C18:3co3 fatty acid, C20:4co6 fatty acid, C12: l acylcarnitine, C22:5co6 fatty acid, CI 0:1 acylcarnitine, C18: l co7 fatty acid, Proline, C24: l co9 fatty acid, C20:5co3 fatty acid, Alanine, C14 acylcarnitine, Serine, and C6 acylcarnitine.

In a more preferred aspect, the metabolites present in blood sample are selected from the group consisting of: C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid, or more preferably from the group consisting of: C18:2co6 fatty acid and C16 acylcarnitine.

In another preferred aspect, the metabolites present in blood sample are selected from: a) the group consisting of:

C16 acylcarnitine, C12: l acylcarnitine, CI 0:1 acylcarnitine, C14 acylcarnitine, and C6 acylcarnitine;

b) the group consisting of:

C18:2co6 fatty acid, C18:3co3 fatty acid, C20:4co6 fatty acid, C22:5co6 fatty acid, C18: lco7 fatty acid, C24: l co9 fatty acid, and C20:5co3 fatty acid; and

c) the group consisting of proline, alanine and serine.

In a preferred aspect, the metabolites present in liver sample are selected from the group consisting of: Maltose, Glucose, and Maltotetraose; or more preferably is NAD⁺.

In an alternative preferred aspect, the metabolites present in muscle sample are selected from the group consisting of: Linoleate (C18:2n6), Dihomo-linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17: ln7), Oleate (C18: ln9), Cytidine, 10-nonadecenoate (C19:ln9), 1-arachidonoyl GPI; more preferably from the group consisting of: Linoleate (C18:2n6), Dihomo-linoleate (C20:2n6), and Trans-4- hydroxyproline; or more preferably from the group consisting of: linolenic fatty acid and linoleic fatty acid; or still more preferably is NAD⁺.

The metabolites useful as bio markers for aging mentioned above are useful in the methods, uses, compositions and kits according to the invention either as a single metabolite or within a set of at least two metabolites, preferably at least three metabolites, between three and ten, at least nine, at least ten metabolites or at least fifteen metabolites. Preferably, the set according to the invention comprises at most 50 metabolites, more preferably at most 25 metabolites.

The smallest possible set(s) of at least two metabolites or even a single metabolite according to the invention is the one(s) which gives a predictive accuracy for predicting aging in a sample higher than 70%, preferably higher than 80% or higher than 85%, more preferably higher than 90%, higher than 95%, higher than 99%, or reaches 100%. Predictive accuracy of a set of metabolites for predicting aging in a subject can be calculated using a learning algorithm such as Random Forest (RF) which estimates the importance of each variable to the classes. Random Forest analysis generates many classification trees using a random training set of individuals and a random small selection of metabolites. Individuals that are left out of the tree are used to estimate the classification error providing an internal cross validation. As such, the "mean decrease accuracy" indicates how much a certain metabolite contributes to separation of the two test groups, and the overall "predictive accuracy" indicates the accuracy with which a set of metabolites combined can separate the groups.

Preferably, a set of at least two metabolites mentioned above are used in the methods, uses, compositions and kits according to the invention as described in details below.

In a preferred aspect, a set of at least two metabolites present in blood sample comprises at least one medium or long chain acylcarnitine selected from the group consisting of:

C16 acylcarnitine, C12: l acylcarnitine, CI 0:1 acylcarnitine, C14 acylcarnitine, and C6 acylcarnitine.

In another preferred aspect, a set of at least two metabolites present in blood sample comprises at least one unsaturated fatty acid selected from the group consisting of:

C18:2co6 fatty acid, C18:3co3 fatty acid, C20:4co6 fatty acid, C22:5co6 fatty acid, C18: l co7 fatty acid, C24: l co9 fatty acid, and C20:5co3 fatty acid.

In an alternative preferred aspect, a set of at least two metabolites present in blood sample comprises at least one amino acid selected from the group consisting of proline, alanine and serine.

In a still preferred aspect, a set of metabolites according to the invention comprises or consists of:

a) the following 7 polyunsaturated fatty acids:

C18:2co6 fatty acid, C18:3co3 fatty acid, C20:4co6 fatty acid, C22:5co6 fatty acid, C18: l co7 fatty acid, C24: l co9 fatty acid, and C20:5co3 fatty acid; or

b/ the following 5 acylcarnitines:

C16 acylcarnitine, C12: l acylcarnitine, CI 0:1 acylcarnitine, C14 acylcarnitine, and C6 acylcarnitine; c) / the following 3 amino acids:

Proline, Alanine, and Serine; or

d) any combination of a), b) and/or c).

In a further preferred aspect, a set of at least two metabolites present in blood sample comprises: C18:2co6 fatty acid and C16 acylcarnitine.

In a still further preferred aspect, a set of at least three metabolites present in blood sample comprises: C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid.

In an alternative aspect, a set of at least two metabolites present in liver sample comprises at least one metabolite selected from: Maltose, Glucose, Maltotetraose, Glycerol- 3-phosphate, Phenylacetylglycine, Malate, Gamma-glutamylleucine, Xanthosine, 5- dodecenoate (C12: ln7), Reduced glutathione (GSH), Ascorbate, Inosine, Alpha-tocopherol, Lactate, Cysteine, Cysteine-glutathione disulfide, Choline, Tagatose, Hexadecanedioate, Ophtalmate, Xylonate, Palmitoyl ethanolamide, Cytidine 5 '-diphosphocholine, Thiamin, Hydroxyisovaleroyl carnitine, and NAD⁺.

In a preferred aspect, a set of at least two metabolites present in liver sample comprises at least one metabolite selected from: Maltose, Glucose, and Maltotetraose.

In another alternative aspect, a set of at least two metabolites present in muscle sample comprises at least one metabolite selected from: Linoleate (C18:2n6), Dihomo- linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17:ln7), Oleate (C18: ln9), Cytidine, 10-nonadecenoate (C19: ln9), 1-arachidonoyl GPI, Glycerophosphorylcholine, Fructose, 12-HETE, Linolenate (C18:3n3 or 6), Eicosenoate (C20: ln9 or 11), Uridine 5 '-monophosphate, Margarate (C17:0), Eicosapentaenoate (C20:5n3), Dihomo-linolenate, Maltose, Carnosine, Methyl palmitate (15 or 2), Docosapentaeonoate (C22:5n6), Myristate (C14:0), Caproate (C6:0), Choline, and NAD⁺.

In a preferred aspect of this alternative, a set of at least two metabolites present in muscle sample comprises at least one metabolite selected from the group consisting of: Linoleate (C18:2n6), Dihomo-linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17: ln7), Oleate (C18: ln9), Cytidine, 10-nonadecenoate (C19: ln9), and 1-arachidonoyl GPI.

In an alternative aspect, a set of at least two metabolites present in liver sample and/or in muscle sample comprises NAD⁺. In another aspect, the metabolites and sets of metabolites mentioned above are used in combination.

Methods of detection of the biomarkers according to the invention

The metabolites according to the invention present in a biological sample from a subject can be analysed using standard techniques known in the art including mass spectrometry (MS), in particular by high-throughput MS, preferably by MS-technologies with ionisation techniques such as Matrix Assisted Laser Desorption/ionisation (MALDI), Electro Spray Ionization (ESI) and Atmospheric Pressure Chemical Ionization (APCI). Other standard techniques involve ¹³C- and/or ³¹P- Nuclear Magnetic Resonance spectroscopy (NMR), optionally coupled to MS, tandem MS, Liquid Chromatography-Mass Spectrometry (LC-MS), LC-tandem MS High Performance Liquid Chromatography (HPLC), Gas Chromatography (GC-MS), and Thin Layer Chromatography (TLC), Capillary Electrophoresis (CE-MS), electrochemical analysis, refractive index spectroscopy (RI), Ultraviolet spectroscopy (UV), fluorescent analysis, radiochemical analysis, Near-InfraRed spectroscopy (Near-IR), Nuclear Magnetic Resonance spectroscopy (NMR), Light Scattering analysis (LS), and enzymatic reaction.

Methods and uses according the invention

In one embodiment, the invention relates to an ex-vivo method of determining the biological age of a subject comprising obtaining a biological sample from a subject and determining the level of at least one metabolite or of a set of at least two metabolites as described above.

The biological sample is preferably selected among a sample from blood (including erythrocytes, serum and plasma samples), a sample from liver and/or a sample from muscle of the subject.

In a specific aspect, the invention relates to an ex-vivo method of determining the biological age of a subject comprising at least one method selected from:

(1) an ex-vivo method comprising the steps of:

a) Obtaining a blood sample from a subject;

b) Determining the level of at least one metabolite or of a set of at least two or at least three metabolites selected from the group consisting of:

(i) medium and long chain acylcarnitines (ii) unsaturated fatty acids

(iv) β-hydroxybutyrate;

in said blood sample;

(2) an ex-vivo method comprising the steps of:

a) Obtaining a liver sample from a subject;

Maltose, Glucose, Maltotetraose, Glycerol-3-phosphate, Phenylacetylglycine, Malate, Gamma-glutamylleucine, Xanthosine, 5-dodecenoate (C12: ln7), Reduced glutathione (GSH), Ascorbate, Inosine, Alpha-tocopherol, Lactate, Cysteine, Cysteine-glutathione disulfide, Choline, Tagatose, Hexadecanedioate, Ophtalmate, Xylonate, Palmitoyl ethanolamide, Cytidine 5 '-diphosphocholine, Thiamin, Hydroxyisovaleroyl carnitine, and NAD⁺;

in said liver sample; and

(3) an ex-vivo method comprising the steps of:

a) Obtaining a muscle sample from a subject;

in said muscle sample.

Preferably, the method (1) described above comprises detecting at least one metabolite or a set of at least two, or at least three, metabolites selected from the group consisting of: C18:2co6 fatty acid, C16 acylcarnitine, C18:3co3 fatty acid, C20:4co6 fatty acid, C12: l acylcarnitine, C22:5co6 fatty acid, CI 0:1 acylcarnitine, C18: l co7 fatty acid, Proline, C24: l co9 fatty acid, C20:5co3 fatty acid, Alanine, C14 acylcarnitine, Serine, and C6 acylcarnitine.

In another embodiment, the invention relates to an ex-vivo use of at least one metabolite or of a set of at least two or at least three metabolites from a biological sample of a subject for determining the biological age of said subject, characterized in that said metabolite is as described above.

In a specific aspect, the invention relates to an ex-vivo use of at least one metabolite or of a set of at least two or at least three metabolites from a biological sample of a subject for determining the biological age of said subject, characterized in that:

(1) said metabolite is obtained from a blood sample of said subject and is selected from the group consisting of:

(i) medium and long chain acylcarnitines

(ii) unsaturated fatty acids

(iii) amino acids selected from the group consisting of proline, alanine, serine, tyrosine, and methionine;

(iv) β-hydroxybutyrate; and/or

(2) said metabolite is obtained from a liver sample of said subject and is selected from the group consisting of:

Maltose, Glucose, Maltotetraose, Glycero 1-3 -phosphate, Phenylacetylglycine, Malate, Gamma-glutamylleucine, Xanthosine, 5-dodecenoate (C12: ln7), Reduced glutathione (GSH), Ascorbate, Inosine, Alpha-tocopherol, Lactate, Cysteine, Cysteine-glutathione disulfide, Choline, Tagatose, Hexadecanedioate, Ophtalmate, Xylonate, Palmitoyl ethanolamide, Cytidine 5'-diphosphocholine, Thiamin, Hydroxyisovaleroyl carnitine, and NAD⁺; and/or

(3) said metabolite is obtained from a muscle sample of said subject and is selected from the group consisting of:

Linoleate (C18:2n6), Dihomo-linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17: ln7), Oleate (C18: ln9), Cytidine, 10- nonadecenoate (C19: ln9), 1 -arachidonoyl GPI, Glycerophosphorylcholine, Fructose, 12-HETE, Linolenate (C18:3n3 or 6), Eicosenoate (C20: ln9 or 11), Uridine 5'- monophosphate, Margarate (C17:0), Eicosapentaenoate (C20:5n3), Dihomo- linolenate, Maltose, Carnosine, Methyl palmitate (15 or 2), Docosapentaeonoate (C22:5n6), Myristate (C14:0), Caproate (C6:0), Choline, and NAD⁺.

In a further embodiment, the invention relates to an ex-vivo method for diagnosing or predicting an age-related disease or disorder in a subject, comprising obtaining a biological sample from a subject and determining the level of at least one metabolite or of a set of at least two metabolites as described above.

Similarly, in a further embodiment, the invention relates to an ex-vivo method for detecting the development of an age-related disease or disorder in a subject, comprising obtaining a biological sample from a subject and determining the level of at least one metabolite or of a set of at least two metabolites as described above.

In a specific aspect, the invention relates to an ex-vivo method for detecting the development of an age-related disease or disorder in a subject, comprising at least one method selected from:

(1) an ex-vivo method comprising the steps of:

a) Obtaining a blood sample from a subject;

b) Determining the level of at least one metabolite or a set of at least two or at least three metabolites selected from the group consisting of:

(i) medium and long chain acylcarnitines

(ii) unsaturated fatty acids

(iv) β-hydroxybutyrate;

in said blood sample;

(2) an ex-vivo method comprising the steps of:

a) Obtaining a liver sample from a subject; b) Determining the level of at least one metabolite or a set of at least two or at least three metabolites selected from the group consisting of:

in said liver sample; and

(3) an ex-vivo method comprising the steps of:

a) Obtaining a muscle sample from a subject;

in said muscle sample.

Another object of the invention is an ex-vivo method of monitoring the aging process subject comprising at least one method selected from:

(1) an ex-vivo method comprising the steps of:

a) Obtaining a blood sample from a subject;

(i) medium and long chain acylcarnitines

(ii) unsaturated fatty acids

in said blood sample; (2) an ex-vivo method comprising the steps of:

a) Obtaining a liver sample from a subject;

in said liver sample; and

(3) an ex-vivo method comprising the steps of:

a) Obtaining a muscle sample from a subject;

in said muscle sample.

A preferred alternative to the preceding method comprises determining the level of at least one metabolite selected from the group consisting of: C18:2co6 fatty acid, C16 acylcarnitine, C18:3co3 fatty acid, C20:4co6 fatty acid, C12:l acylcarnitine, C22:5co6 fatty acid, C10: l acylcarnitine, C18: l co7 fatty acid, Proline, C24: l co9 fatty acid, C20:5co3 fatty acid, Alanine, C14 acylcarnitine, Serine, and C6 acylcarnitine, in said blood samples.

In further embodiments, any method and use according to the invention may further comprise the step of comparing the level of metabolite determined in said sample with the level of metabolite in a reference. Preferably, the level of said metabolite in a reference is selected among:

(i) the level of said metabolite determined in a biological sample from a young subject;

(ii) the average level of said metabolite determined in a biological sample from at least two young subjects.

The level of a metabolite in a reference corresponds to the level of the metabolite that is indicative of a particular physiological state, phenotype, etc, associated with a particular biological age as well as combinations of physiological states, phenotypes, etc. Using a young subject or several young subjects as a reference allows determining a level of the metabolite that is indicative of a physiological state or phenotype characterizing a young subject or young population. Using an old subject or several old subjects as a reference allows determining a level of the metabolite that is indicative of a physiological state or phenotype characterizing an old subject.

The level of a metabolite in a reference may be an absolute or relative amount or concentration of the metabolite, a presence or absence of the metabolite, a range of amount or concentration of the metabolite, a minimum and/or maximum amount or concentration of the metabolite, a mean amount or concentration of the metabolite, and/or a median amount or concentration of the metabolite. The level of combinations of metabolites in a reference may also be ratios of absolute or relative amounts or concentrations of two or more metabolites with respect to each other or a composed value / score obtained by classification. Appropriate levels of metabolites in a reference for a particular species may be determined by measuring levels of desired metabolites in one or more appropriate subjects of that species, and such reference levels may be tailored to specific populations of subjects. Such reference levels may also be tailored to specific techniques that are used to measure levels of metabolites in the biological samples, where the levels of metabolites may differ based on the specific technique that is used.

Additional preferences of the methods and uses according to the invention comprise determining the level of at least one metabolite or of a set of at least two metabolites according to any preferred alternative as disclosed herewith.

For instance, the methods and uses of the invention may comprise determining, in a blood sample of said subject, the level of at least one metabolite selected from:

1) the group consisting of:

C16 acylcarnitine, C12: l acylcarnitine, CI 0:1 acylcarnitine, C14 acylcarnitine, and C6 acylcarnitine; 2) the group consisting of:

C18:2co6 fatty acid, C18:3co3 fatty acid, C20:4co6 fatty acid, C22:5co6 fatty acid, C18: l co7 fatty acid, C24: l co9 fatty acid, and C20:5co3 fatty acid;

3) the group consisting of: proline, alanine and serine;

4) the group consisting of:

C18:2co6 fatty acid and C16 acylcarnitine;

5) the group consisting of:

C18:2co6 fatty acid, CI 6 acylcarnitine, and C18:3co3 fatty acid; or

6) any combination of 1) to 5).

In another embodiment, the invention relates to a method of treating, preventing, or delaying, an age-related disease or disorder in a subject, comprising administering in a subject in need thereof an effective amount of an agent or composition that changes the level of at least one or a set of at least two metabolites as described above. Preferably, the agent or composition prevents aging-related changes in the profile of said metabolites (e.g. fatty acids, amino acids, acylcarnitines, glucides).

In the sense of the invention, the changes of the level of said metabolites are such that the changed levels are similar to those measured in a young subject.

In a specific aspect, the invention relates to a method of treating, preventing, or delaying, an age-related disease or disorder in a subject, comprising administering in a subject in need thereof an effective amount of an agent or composition that increases the level of C18:2co6 and/or C18:3co3 fatty acids and/or increases the level of long and medium chain acylcarnitines including C16 acylcarnitine, in the blood of said subject.

Alternatively, the method of treating, preventing or delaying an age-related disease or disorder according to the invention comprises administering in a subject in need thereof an effective amount of an agent or composition that increases the level of C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid in the blood of said subject.

In another embodiment, the invention relates to a method of inhibiting or delaying the aging process in a subject, comprising administering in a subject in need thereof an effective amount of an agent or composition that changes the level of at least one or a set of at least two metabolites as described above.

In the sense of the invention, the changes of the level of said metabolites are such that the changed levels are similar to those measured in a young subject. In a specific aspect, the invention relates to a method of inhibiting or delaying the aging process in a subject, comprising administering in a subject an effective amount of an agent or composition that increases the level of C 18:2co6 and/or C 18:3co3 fatty acids and/or increases the level of long and medium chain acylcarnitines including C16 acylcarnitine, in the blood of said subject.

Alternatively, the method of inhibiting or delaying the aging process in a subject according to the invention comprises administering in a subject in need thereof an effective amount of an agent or composition that increases the level of C18:2co6 fatty acid, C 16 acylcarnitine, and C18:3co3 fatty acid in the blood of said subject.

Another object of the invention is a method of screening a compound for its ability to inhibit or delay the aging process in a subject comprising at least one method selected from:

(1) A method comprising the steps of:

a) Providing a sample selected from (i) a blood sample from a subject, (ii) primary blood-derived cells, and (iii) cell lines based on blood-derived cells, and dividing said sample in a first group and a second group;

b) exposing the blood samples from the first group to a test compound;

c) determining the level of at least one metabolite or of a set of at least two metabolites selected from the group consisting of: C18:2co6 fatty acid, C16 acylcarnitine, C18:3co3 fatty acid, C20:4co6 fatty acid, C\2:\ acylcarnitine, C22:5co6 fatty acid, C10: l acylcarnitine, C18: l co7 fatty acid, Proline, C24: l co9 fatty acid, C20:5co3 fatty acid, Alanine, C14 acylcarnitine, Serine, and C6 acylcarnitine, in the samples from the first and second groups;

d) comparing the level of said metabolites between the first and second groups and identifying test compounds that modify the level of said metabolites in the samples from the first group such that the level of said metabolites in the samples from the first group is more similar to the level of said metabolites determined in blood samples from young subjects;

(2) A method comprising the steps of:

a) Providing a sample selected from (i) a liver sample from a subject, (ii) primary hepatocyte cells, and (iii) hepatocyte cell lines, and dividing said sample in a first group and a second group;

b) exposing the samples from the first group to a test compound; determining the level of at least one or of a set of at least two metabolites selected from the group consisting of: Maltose, Glucose, Maltotetraose, Glycerol-3-phosphate, Phenylacetylglycine, Malate, Gamma-glutamylleucine, Xanthosine, 5-dodecenoate (C12: ln7), Reduced glutathione (GSH), Ascorbate, Inosine, Alpha-tocopherol, Lactate, Cysteine, Cysteine-glutathione disulfide, Choline, Tagatose, Hexadecanedioate, Ophtalmate, Xylonate, Palmitoyl ethanolamide, Cytidine 5'- diphosphocholine, Thiamin, Hydroxyisovaleroyl carnitine, and NAD⁺, in the samples from the first and second groups;

c) comparing the level of said metabolites between the first and second groups and identifying test compounds that modify the level of said metabolites in the samples from the first group such that the level of said metabolites in the samples from the first group is more similar to the level of said metabolites determined in the liver samples from young subjects; and

(3) A method comprising the steps of:

a) Providing a sample selected from (i) a muscle sample from a subject, (ii) primary muscle cells, and (iii) muscle cell lines, and dividing said sample in a first group and a second group;

b) exposing the samples from the first group to a test compound;

determining the level of at least one metabolite or of a set of at least two metabolites selected from the group consisting of: Linoleate (C18:2n6), Dihomo-linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17: ln7), Oleate (C18: ln9), Cytidine, 10-nonadecenoate (C19: ln9), 1-arachidonoyl GPI, Glycerophosphorylcholine, Fructose, 12-HETE, Linolenate (C18:3n3 or 6), Eicosenoate (C20: ln9 or 11), Uridine 5 '-monophosphate, Margarate (C17:0), Eicosapentaenoate (C20:5n3), Dihomo-linolenate, Maltose, Carnosine, Methyl palmitate (15 or 2), Docosapentaeonoate (C22:5n6), Myristate (C14:0), Caproate (C6:0), Choline, and NAD⁺, in the samples from the first and second groups;

c) comparing the level of said metabolites between the first and second groups and identifying test compounds that modify the level of said metabolites in the samples from the first group such that the level of said metabolites in the samples from the first group is more similar to the level of said metabolites determined in the muscle samples from young subjects. A preferred alternative to the preceding method comprises determining the level of at least one metabolite selected from the group consisting of: C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid, or at least one metabolite selected from the group consisting of: C18:2co6 fatty acid and C16 acylcarnitine, in said blood samples.

According to the invention, the methods (1), (2), (3) above can be applied to mammalian cells such as lymphocytes and hematopoietic stem cells, C2C12 myotubes, primary hepatocytes, Hepal .6, or cell lines based on blood-derived cells including, for instance, lymphoblasts. The test compounds can also be tested in animal models (e.g. mice) to evaluate their effect on aging.

Test compounds include small molecules, peptidomimetics, chimaeric proteins, natural or unnatural proteins, nucleic acid derived polymers (such as DNA and R A aptamers, siRNAs, PNAs, or LNAs), fusion proteins, antibodies.

Test compounds can be selected based on structural or functional similarity to other compounds already known as, for example, increasing NAD⁺ levels or otherwise activating mitochondrial metabolism, or are taken from commercially available compound libraries. Similarly, test compounds can be selected based on structural or functional similarity to other compounds already known as changing the lipid or amino acid levels in the opposite way as affected by aging as described in the present application.

The test compound to be used in the screening method of the invention may be, for instance, NAD⁺ level modulators (PARP inhibitors, NAD⁺ precursors), mitochondrial biogenesis inducers such as resveratrol, AMPK agonists.

Agents and compositions according the invention

In another embodiment, the invention relates to an agent or composition that changes the level of at least one or a set of at least two metabolites as described above, for use in the treatment or prevention of an age-related disease or disorder in said subject.

In a specific aspect, the invention relates to an agent or composition that increases the level of C18:2co6 and/or C18:3co3 fatty acids and/or increases the level of long and medium chain acylcarnitines including C16 acylcarnitine, in the blood of a subject, for use in the treatment or prevention of an age-related disease or disorder in said subject. In an alternative aspect, the invention relates to an agent or composition that increases the level of C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid in the blood of a subject, for use in the treatment or prevention of an age-related disease or disorder in said subject.

In an alternative embodiment, the invention relates to an agent or composition that changes the level of at least one or a set of at least two metabolites as described above, for use in inhibiting or delaying the aging process in a subject.

In a specific aspect, the invention relates to an agent or composition that increases the level of C18:2co6 and/or C18:3co3 fatty acids and/or increases the level of long and medium chain acylcarnitines including C16 acylcarnitine, in the blood of a subject, for use in inhibiting or delaying the aging process in said subject.

In an alternative aspect, the invention relates to an agent or composition that increases the level of C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid in the blood of a subject, for use in inhibiting or delaying the aging process in said subject.

Therefore, the invention provides pharmaceutical compositions and methods for treating a subject, preferably a mammalian subject, and most preferably a human subject who is suffering from an age-related disease or disorder, said pharmaceutical composition comprising the agent according to the invention as described herewith.

The agent according to the invention include small molecules, peptidomimetics, chimaeric proteins, natural or unnatural proteins, nucleic acid derived polymers (such as DNA and RNA aptamers, siRNAs, PNAs, or LNAs), fusion proteins, antibodies.

Pharmaceutical compositions or formulations according to the invention may be administered as a pharmaceutical formulation which can contain an agent according to the invention in any form.

The compositions according to the invention, together with a conventionally employed adjuvant, carrier, diluent or excipient may be placed into the form of pharmaceutical compositions and unit dosages thereof, and in such form may be employed as solids, such as tablets or filled capsules, or liquids such as solutions, suspensions, emulsions, elixirs, or capsules filled with the same, all for oral use, or in the form of sterile injectable solutions for parenteral (including subcutaneous and intradermal) use by injection or continuous infusion. Injectable compositions are typically based upon injectable sterile saline or phosphate- buffered saline or other injectable carriers known in the art. Such pharmaceutical compositions and unit dosage forms thereof may comprise ingredients in conventional proportions, with or without additional active compounds or principles, and such unit dosage forms may contain any suitable effective amount of the active ingredient commensurate with the intended daily dosage range to be employed.

Examples of suitable adjuvants include MPL® (Corixa), aluminum-based minerals including aluminum compounds (generically called Alum), ASOl-4, MF59, CalciumPhosphate, Liposomes, Iscom, polyinosinic:polycytidylic acid (polylC), including its stabilized form poly-ICLC (Hiltonol), CpG oligodeoxynucleotides, Granulocyte-macrophage colony-stimulating factor (GM-CSF), lipopolysaccharide (LPS), Montanide, PLG, Flagellin, QS21, RC529, IC31, Imiquimod, Resiquimod, ISS, and Fibroblast-stimulating lipopeptide (FSL1).

Compositions of the invention may be liquid formulations including, but not limited to, aqueous or oily suspensions, solutions, emulsions, syrups, and elixirs. The compositions may also be formulated as a dry product for reconstitution with water or other suitable vehicle before use. Such liquid preparations may contain additives including, but not limited to, suspending agents, emulsifying agents, non-aqueous vehicles and preservatives. Suspending agents include, but are not limited to, sorbitol syrup, methyl cellulose, glucose/sugar syrup, gelatin, hydroxyethyl cellulose, carboxymethyl cellulose, aluminum stearate gel, and hydrogenated edible fats. Emulsifying agents include, but are not limited to, lecithin, sorbitan monooleate, and acacia. Preservatives include, but are not limited to, methyl or propyl p-hydroxybenzoate and sorbic acid. Dispersing or wetting agents include but are not limited to poly(ethylene glycol), glycerol, bovine serum albumin, Tween®, Span®.

Compositions of the invention may also be formulated as a depot preparation, which may be administered by implantation or by intramuscular injection.

Solid compositions of this invention may be in the form of tablets or lozenges formulated in a conventional manner. For example, tablets and capsules for oral administration may contain conventional excipients including, but not limited to, binding agents, fillers, lubricants, disintegrants and wetting agents. Binding agents include, but are not limited to, syrup, accacia, gelatin, sorbitol, tragacanth, mucilage of starch and polyvinylpyrrolidone. Fillers include, but are not limited to, lactose, sugar, microcrystalline cellulose, maizestarch, calcium phosphate, and sorbitol. Lubricants include, but are not limited to, magnesium stearate, stearic acid, talc, polyethylene glycol, and silica. Disintegrants include, but are not limited to, potato starch and sodium starch gly collate. Wetting agents include, but are not limited to, sodium lauryl sulfate. Tablets may be coated according to methods well known in the art.

The compounds of this invention can also be administered in sustained release forms or from sustained release drug delivery systems.

According to a particular embodiment, compositions according to the invention are for subcutaneous use.

In another particular aspect, the compositions according to the invention are adapted for delivery by repeated administration.

Further materials as well as formulation processing techniques and the like are set out in Part 5 of Remington 's Pharmaceutical Sciences, 21^st Edition, 2005, Lippincott Williams & Wilkins, which is incorporated herein by reference.

Mode of administration

Compounds, compositions, and formulations thereof according to this invention may be administered in any manner including orally, parenterally, intravenously, rectally, or combinations thereof. Parenteral administration includes, but is not limited to, intravenous, intra-arterial, intra-peritoneal, subcutaneous, intradermal and intramuscular. The compositions of this invention may also be administered in the form of an implant, which allows slow release of the compositions as well as a slow controlled i.v. infusion.

Preferentially, the compounds, compositions and formulations thereof according to the invention are administered subcutaneously.

In one embodiment of the invention, the administration of compounds and compositions of the invention requires multiple successive injections. Thus, the administration can be repeated at least two times, repeatedly or continuously. The period of administration may vary for example from at least 1 , 2, 3, or 4 weeks; 2, 3, 4, 5, 6, 8, 10, or 12 months; or 2, 3, 4, or 5 years.

Subjects

Subjects to which the methods and uses according to the invention can be applied are mammals, preferably including human, primates, laboratory rodents and the like. In one embodiment, subjects to which a method of treating, preventing, delaying or inhibiting an age-related disease or disorder according to the invention can be applied are human subjects which may be predisposed to the disease but have not yet been diagnosed as having it. The method of treatment or use according to the invention then correspond to a preventive early asymptomatic intervention. In this case, the method of treatment or use may be applied to the subject prior to the appearance or development of the age-related disease or disorder, preferably a few years before the subject reaches the age at which the age-related disease or disorder usually begins to develop in the subject's species. It is understood that this age also depends on the age-related disease or disorder.

In another embodiment, the methods and uses according to the invention are applied to human subjects who are old and/or afflicted of an age-related disease or disorder.

In another embodiment, the method of screening of compounds according to the invention are applied to laboratory rodents such as rat and mice.

Kit

Another object of the invention is a kit for carrying out any one of the methods and uses according to the invention.

In a particular embodiment, the invention relates to a kit of parts for the determination of metabolites according to the invention for determining the biological age of a subject as well as for diagnosis/prediction of age-related disease or disorder comprising, for example, apparatus, reagents and standard solutions of said metabolites.

Apparatus considered are e.g. microarrays, immunoassays (including ELISAs), tandem MS, LC-MS, LC-tandem MS. Reagents are those reagents particularly developed and designed for the detection of the metabolites according to the invention. This may include internal standards containing stable isotopes, non-labeled standards, derivatisation reagents. The kit of parts may contain further hardware, such as pipettes, solutions such as buffers, blocking solutions and the like, filters, color tables and directions for use.

In a specific aspect, the invention relates to a kit as mentioned above further comprising a reference value of the quantity of said metabolite in a biological sample of a young subject or means for establishing said reference value.

References cited herein are hereby incorporated by reference in their entirety. The present invention is not to be limited in scope by the specific embodiments described herein, which are intended as single illustrations of individual aspects of the invention, and functionally equivalent methods and components are within the scope of the invention. Indeed, various modifications of the invention, in addition to those shown and described herein will become apparent to those skilled in the art from the foregoing description and accompanying drawings. Such modifications are intended to fall within the scope of the appended claims.

The invention having been described, the following examples are presented by way of illustration, and not limitation.

Examples

The following abbreviations refer respectively to the definitions below:

aPAR: antibody directed to poly(ADP-ribose)ylated proteins

PAPvP-1 : protein involved in DNA damage and NAD metabolism

PGC-Ι : protein involved in regulation of mitochondrial metabolism

Ac-Lys: antibody directed towards acetylated lysine residues in proteins. In combination with immunoprecipitated PGC-Ια, Ac-Lys identifies acetylation status of PGC-la.

Materials and methods

Mice

C57BL/6J mice of either 13 weeks old ("young") or 93 weeks old ("old") were purchased from Janvier (St. Berthevin, France). Mice were group housed and received standard chow (#2018, containing 18% protein, 50% carbohydrate and 6.0% fat; Harlan Laboratories, Madison, WI, USA). After in vivo phenotyping, mice were sacrificed after overnight fasting, reaching the age of 24 or 103 weeks. Heparinized plasma was taken and tissues were frozen in liquid nitrogen for biochemical and molecular analyses.

In vivo phenotyping

Activity levels and activity were monitored by indirect calorimetry using the comprehensive laboratory animal monitoring system (CLAMS) (Columbus Instruments, Columbus, OH, USA) (Lagouge et al, 2006). Glucose tolerance was analyzed by measuring blood glucose and insulin following intraperitoneal injection of 2 g/kg glucose after an overnight fast (Heikkinen et al, 2007). Biochemical assays

Western blotting was performed as described before (Bai et al, 2011). Additional antibodies include Tubulin (Santa Cruz Biotechnology), p-Ser (Sigma), p-ACC (Millipore), IRS-1, ρ-ΑΜΡΚα, ΑΜΡΚα, S6K1 and p-S6Kl (Cell Signaling Technology) (Urn et al, 2004).

Plasma biochemistry and targeted metabolomics

Basic plasma clinical chemistry analyses were performed according to Eumorphia SOPs (Champy et al, 2008). Plasma acylcarnitines and amino acids were determined by tandem mass spectrometry (MSⁿ) and LC-MSⁿ respectively (Chace et al, 2003; Piraud et al, 2003). Fatty acids in erythrocytes were directly transesterified and analyzed by gas chromatography with flame ionization detection (Dacremont and Vincent, 1995). Beta- hydroxybutyric acid was measured in perchloric acid deproteinized plasma using established procedures (Bergmeyer et al, 1986)

Global metabolomics

Metabolomics of quadriceps muscle and liver of young and old mice (8 and 7 mice per group, respectively) was performed by Metabolon (Durham, NC, USA), according to published methods (Gall et al, 2010). In brief, sample preparation was conducted using a proprietary series of organic and aqueous extractions to remove the protein fraction while allowing maximum recovery of small molecules. The extracted samples were split into equal parts for analysis on the GC/MS and LC-MS/MS platforms. For LC-MS/MS, samples were split in two aliquots that were either analyzed in positive (acidic solvent) or negative (basic solvent) ionization mode. GC-MS was performed on bistrimethyl-silyl-triflouroacetamide derivatized samples in a 5% phenyl GC column.

Bioinformatics and statistics

Data in figures is presented as mean±SEM or as box-and-whisker plots indicating the sample minimum, lower quartile, median, upper quartile, and sample maximum with outliers represented as small circles. A Students T-test or Welch's T-test (liver and muscle metabolomics data) was performed for statistical comparison between young and old mice. A /?-value of 0.05 or less was considered significant. Unsupervised hierarchical clustering was performed using complete linkage and Pearson rank correlation distance on the normalized metabolites using software implemented in Genepattern (de Hoon et al, 2004; Reich et al, 2006). The z-score was calculated by subtracting the mean expression value for each metabolite from each of the values and then dividing the resulting values by the standard deviation. Color in the heat-maps reflects the relative metabolite abundance level with red being higher and blue lower than the mean metabolite abundance value. Metabolite and animal ordering is determined as in hierarchical clustering using the distance function 1 -correlation.

The web-based metabolomic data processing tool, MetaboAnalyst (Xia et al, 2009) was used for tissue metabolite data analysis. See http://www.metaboanalyst.ca for detailed methodology. Briefly, for the RF analysis, the metabolite data was log transformed (log 2) and the number of predictors to try for each node was set to the square root of the total number of variables per tissue and the number of trees to grow was set to 10.000. RF is performed using the random forest package and the resulting confusion matrix, out of bag (OOB) error and variable importance (as determined by the mean decrease in accuracy when data is permuted) are presented. For MSEA, metabolite data was mapped according to HMDB and the 'Metabolite pathway associated metabolite set' library (currently 88 entries) was chosen for the enrichment analysis, which is performed using package global test. The metabolome view displays the pathway topological analysis, a method that takes into account the pathway structure when determining which pathways are more likely to be of significance. The parameters chosen for this analysis included global test and the node centrality measure 'betweenness centrality' to estimate node importance. This measure considers the global network structure such that nodes that occur between two dense clusters will have a high betweenness centrality even if its degree centrality is not high. The node importance values calculated from centrality measures are further normalized by the sum of the importance of the pathway for comparison among different pathways. Therefore, the total/maximum importance of each pathway is 1 ; the importance measure of each metabolite node is actually the percentage with respect to the total pathway importance, and the pathway impact is the cumulative percentage from the matched metabolite nodes.

GSEA was performed on the microarray dataset of C57BL/6N gastrocnemius muscle comparing 5 and 25-month-old mice and normal or caloric restricted diet (Edwards et al, 2007) using software implemented in GenePattern and as described (Lagouge et al, 2006). For the functional enrichment visualization of the mutually overlapping gene-sets and for the comparison of the two different enrichment results in the same map, the plug-in, Enrichment map (Merico et al, 2010), was used in the open-source platform Cytoscape (Smoot et al, 2011).

Example 1: Metabolic disturbances in blood

Various changes in plasma markers were noted in old mice compared to young ones, such as increased free fatty acid and decreased triglyceride levels. To expand our characterization of blood metabolites in aging mice and to identify possible novel aging biomarkers we generated an extensive metabolomics profile in the blood of young and old mice. Over 75 analytes including profiles of erythrocyte fatty acids and plasma acylcarnitines, amino acids and ketone bodies were measured and these data were clustered in order to identify groups of metabolites that respond similarly during aging. Using this profile of metabolites, the mice were separated out according to age and several interesting metabolite clusters became apparent. One of these clusters contained long chain as well as medium chain acylcarnitines. These metabolites, which are intermediates of FAO, were decreased in the old mice. The erythrocyte fatty acid profile reflects long-term changes in fatty acid homeostasis and is routinely performed for the diagnosis of poly-unsaturated fatty acid (PUFA) deficiency. For the saturated fatty acids, C16 was slightly decreased whereas the elongated CI 8 and C20 were increased. In addition, various intermediates and products of PUFA biosynthesis such as C20:4co6 were increased, whereas the substrates C18:2co6 and C18:3co3 were decreased. Overall levels of PUFAs as well as plasmalogens, which both have been implicated in protection against ROS, were not decreased.

In addition to fat metabolism, amino acid metabolism also alters significantly during aging. It was shown before that supplementation of branched-chain amino acids (BCAAs) (DAntona et al, 2010) or alteration in methionine content in the diet (Grandison et al, 2009; Miller et al, 2005) impacts lifespan. Our characterization of the plasma amino acids associated a clear reduction in the levels of proline, alanine, serine, tyrosine and methionine with aging but not in the levels of the BCAAs valine, leucine and isoleucine. Similarly, it was previously shown that the mTOR pathway inhibits ketogenesis and that ketogenic capacity is reduced in aging (Sengupta et al, 2010). In line with decreased ketogenesis, our analysis found that β-hydroxybutyrate (BHBA) levels, which reflect total ketone body levels, tended to decrease with age. Novel biomarkers of aging

The clear differences in plasma metabolite levels between young and old mice led us to test whether these can be used to discriminate the two groups reliably, a prerequisite for biomarker development.

Selection of relevant variables for sample classification is a common task with high dimensional data sets such as metabolomics and gene expression studies where one tries to identify the smallest possible set of metabolites or genes (i.e. biomarkers) that can still achieve good predictive performance. Random Forest (RF) is one such learning algorithm that can do this by estimating the importance of each variable to the classes. RF analysis generates many classification trees using a random training set of mice and a random small selection of metabolites. Mice that are left out of the tree are used to estimate the classification error providing an internal cross validation. As such, the "mean decrease accuracy" indicates how much a certain metabolite contributes to separation of the two test groups, and the overall "predictive accuracy" indicates the accuracy with which a set of metabolites combined can separate the groups.

Example 2: Novel biomarkers for aging identified in blood

RF analysis of blood targeted metabolomics data defined a set of 10 metabolites that constitute the best predictors of aging, with a 100% predictive accuracy as follows: (Figures 1 and 2).

We found plasma free fatty acids to be increased, whereas plasma medium and long chain acylcarnitines were lower in old mice.

In particular, decreased erythrocyte C18:2co6 and decreased plasma C16-acylcarnitine were strong predictors.

Calculation of predictive accuracy of aging based on different sets of metabolites gave the following results:

1/ A set of metabolites consisting of the following 7 polyunsaturated fatty acids: C18:2co6 fatty acid, C18:3co3 fatty acid, C20:4co6 fatty acid, C22:5co6 fatty acid, C18: l co7 fatty acid, C24: l co9 fatty acid, and C20:5co3 fatty acid, comprises the metabolites responsible for the overall predictive accuracy of 100%.

21 A set of metabolites consisting of the following 5 acylcarnitines: C16 acylcarnitine, C12: l acylcarnitine, C10: l acylcarnitine, C14 acylcarnitine, and C6 acylcarnitine, comprises the metabolites responsible for the overall predictive accuracy of 89%. 3/ A set of metabolites consisting of the following 3 amino acids: Proline, Alanine, and Serine, comprises the metabolites responsible for the overall predictive accuracy of 78%.

Example 3: Novel biomarkers for aging identified in liver

We also charted metabolic changes in liver of young and old mice using global metabolomics. We detected 473 metabolites in muscle of which 94 were significantly changed between the groups (data not shown). We again performed RF analysis to classify these metabolic changes (Figures 3 and 4).

In liver, the metabolite changes could 93% accurately predict the age groups and hierarchical clustering of the top 25 metabolites confirmed the separation of the two age groups (Figure 3). Following RF analysis, which was aimed to identify relative contribution of individual metabolites from the high-dimensional metabolomics data, we performed metabolite set enrichment analysis (MSEA) (Xia and Wishart, 2010) to establish which pathways are affected. In liver, the best metabolites to predict age were in glucose metabolism, phospholipid metabolism, and redox homeostasis (data not shown). Additionally, we performed a metabolome view analysis to demonstrate whether a metabolite 'hub' node was affected, which could have more biological consequences than a 'deadend' metabolite node, confirming that mainly carbohydrate metabolism and redox balance were disturbed. With respect to redox homeostasis, for example, various metabolites were changed in old mice, notably the metabolite hub reduced glutathione.

Example 4: Novel biomarkers for aging identified in muscle

We also charted metabolic changes in quadriceps muscle of young and old mice using global metabolomics. We detected 263 metabolites in muscle of which 65 were significantly changed between the groups (data not shown). We again performed RF analysis to classify these metabolic changes (Figures 5 and 6).

In muscle, the top 25 metabolites are dominated by fatty acid metabolites (Figure 5), with the top 20 set already showing a predictive accuracy of 100% and clear group separation (Figure 5, right panel). MSEA and metabolome view confirmed involvement of fatty acid metabolism, but also highlighted a strong contribution of glucose metabolism, with metabolism of the poly-unsaturated fatty acids linolenic and linoleic acid being the best predictors of age in muscle (Figure 5). These metabolites serve as hubs in poly-unsaturated fatty acid metabolism and therefore have a high impact on predictive power. We found glucose and intermediates of glycolysis and glycogen metabolism, such as maltose and maltotetraose, as biomarkers for aging in liver as well as muscle (Figures 3 and 5). In both liver and muscle, accumulation of glycogen intermediates suggests altered glycogen metabolism in aged mice, whereas the increased lactate and reduced glycolytic intermediates suggest elevated anaerobic glycolysis. In muscle, the elevated levels of glucose, glucose-6-phosphate and maltose, also suggest changes in glucose and glycogen metabolism (Figure 5). Indeed, the increase in muscle maltose levels is consistent with increased glycogenolysis. Importantly, these metabolite data go in pair with the clinical— impaired glucose tolerance— and signaling— increased IRS-1 serine phosphorylation— data. Glucose metabolism was also identified in the microarray data from aging gastrocnemius muscle and was normalized upon caloric restriction.

Example 5: NAD⁺ as novel biomarker for aging identified in liver and muscle

The effect of aging on global parylation, NAD⁺ content and SIRT1 activity was investigated in liver samples and muscle samples from young and old mice.

As shown in Figure 7, global PARylation as a marker for PARP activity was assessed using a aPAR antibody (left panels) in liver samples (top) and muscle samples (bottom). PARylation is markedly increased in old mice, both in liver and in muscle. The increased PARP activity goes in hand with a drop in NAD⁺ levels (middle panels) in liver samples (top) and muscle samples (bottom), as measured using an enzymatic cycle reaction (Enzychrom, Bio Assays Systems). These lower NAD⁺ levels result in higher SIRT1 activity, as demonstrated by a hyperacetylation of PGC-Ια (right panels).

Example 6. Screening of compounds that inhibit or delay the aging process

The method of screening a compound for its ability to inhibit or delay the aging process in a subject, according to the invention, can be carried out following a cell-based approach. In this case, the samples in which the level of metabolites according to the invention is determined can comprise mammalian cells (e.g. C2C12 myotubes, primary hepatocytes, Hepal .6), which are grown and treated with the compound to be tested for 24-72 hours.

Test compounds are selected based on structural or functional similarity to other compounds already known as, for example, increasing NAD⁺ levels or otherwise activating mitochondrial metabolism, or are taken from commercially available compound libraries. Test compounds that, for example, elevate NAD⁺ levels and/or show a good mitochondrial activation pattern can then be used in selected mouse models, where treatment (possibly in combination with a dietary challenge) will allow physiological characterization. Typical experiments that can be used for physiological characterization include cold tolerance, exercise capacity, glucose tolerance, etc.

Similarly, test compounds can be selected based on structural or functional similarity to other compounds already known as changing the lipid or amino acid levels in the opposite way as affected by aging as described in the present application.

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Claims

1. An ex-vivo method of determining the biological age of a subject comprising at least one method selected from:

(1) an ex-vivo method comprising the steps of:

a) Obtaining a blood sample from a subject;

(i) medium and long chain acylcarnitines

(ii) unsaturated fatty acids

in said blood sample;

(2) an ex-vivo method comprising the steps of:

a) Obtaining a liver sample from a subject;

in said liver sample; and

(3) an ex-vivo method comprising the steps of:

a) Obtaining a muscle sample from a subject;

in said muscle sample.

2. An ex-vivo use of at least one metabolite or a set of at least two or at least three metabolites from a biological sample of a subject for determining the biological age of said subject, characterized in that:

(i) medium and long chain acylcarnitines

(ii) unsaturated fatty acids

(iii) amino acids selected from the group consisting of proline, alanine, serine, tyrosine, and methionine; and/or

Maltose, Glucose, Maltotetraose, Glycerol-3-phosphate, Phenylacetylglycine, Malate, Gamma-glutamylleucine, Xanthosine, 5-dodecenoate (C12: ln7), Reduced glutathione (GSH), Ascorbate, Inosine, Alpha-tocopherol, Lactate, Cysteine, Cysteine-glutathione disulfide, Choline, Tagatose, Hexadecanedioate, Ophtalmate, Xylonate, Palmitoyl ethanolamide, Cytidine 5'-diphosphocholine, Thiamin, Hydroxyisovaleroyl carnitine, and NAD⁺; and/or

Linoleate (C18:2n6), Dihomo-linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17: ln7), Oleate (C18: ln9), Cytidine, 10- nonadecenoate (C19:ln9), 1-arachidonoyl GPI, Glycerophosphorylcholine, Fructose, 12-HETE, Linolenate (C18:3n3 or 6), Eicosenoate (C20: ln9 or 11), Uridine 5'- monophosphate, Margarate (C17:0), Eicosapentaenoate (C20:5n3), Dihomo- linolenate, Maltose, Carnosine, Methyl palmitate (15 or 2), Docosapentaeonoate (C22:5n6), Myristate (C14:0), Caproate (C6:0), Choline, and NAD⁺.

3. An ex-vivo method for detecting the development of an age-related disease or disorder in a subject, comprising at least one method selected from:

(1) an ex-vivo method comprising the steps of:

a) Obtaining a blood sample from a subject;

(i) medium and long chain acylcarnitines

(ii) unsaturated fatty acids

in said blood sample;

(2) an ex-vivo method comprising the steps of:

a) Obtaining a liver sample from a subject;

in said liver sample; and

(3) an ex-vivo method comprising the steps of:

a) Obtaining a muscle sample from a subject;

in said muscle sample.

4. An ex-vivo method for monitoring the aging process in a subject, comprising at least one method selected from:

(1) an ex-vivo method comprising the steps of:

a) Obtaining a blood sample from a subject;

(i) medium and long chain acylcarnitines

(ii) unsaturated fatty acids

in said blood sample;

(2) an ex-vivo method comprising the steps of:

a) Obtaining a liver sample from a subject;

in said liver sample; and

(3) an ex-vivo method comprising the steps of:

a) Obtaining a muscle sample from a subject;

in said muscle sample.

5. The method or use according to any of the preceding claims, wherein method (1) comprises detecting at least one metabolite or a set of at least two, or at least three, metabolites selected from the group consisting of: C18:2co6 fatty acid, C16 acylcarnitine, C18:3co3 fatty acid, C20:4co6 fatty acid, C12:l acylcarnitine, C22:5co6 fatty acid, C10: l acylcarnitine, C18: l co7 fatty acid, Proline, C24:lco9 fatty acid, C20:5co3 fatty acid, Alanine, C14 acylcarnitine, Serine, and C6 acylcarnitine.

6. The method or use according to any of the preceding claims, further comprising the step of comparing the level of metabolite determined in said sample with the level of metabolite in a reference.

7. The method or use according to the preceding claim, wherein the level of said metabolite in a reference is selected among:

8. The method or use according to any of the preceding claims, wherein the subject is a human.

9. The method or use according to any of the preceding claims, comprising determining the level of at least one metabolite selected from the group consisting of:

C16 acylcarnitine, C12: l acylcarnitine, CI 0:1 acylcarnitine, C14 acylcarnitine, and C6 acylcarnitine,

in a blood sample of said subject.

10. The method or use according to any of the preceding claims, comprising determining the level of at least one metabolite selected from the group consisting of:

C18:2co6 fatty acid, C18:3co3 fatty acid, C20:4co6 fatty acid, C22:5co6 fatty acid, C18: lco7 fatty acid, C24: l co9 fatty acid, and C20:5co3 fatty acid,

in a blood sample of said subject.

11. The method or use according to any of the preceding claims, comprising determining the level of at least one metabolite selected from the group consisting of proline, alanine and serine, in a blood sample of said subject.

12. The method or use according to any of the preceding claims, comprising determining the level of at least 2 metabolites selected from the group consisting of:

C18:2co6 fatty acid and C16 acylcarnitine,

in a blood sample of said subject.

13. The method or use according to any of the preceding claims, comprising determining the level of at least 3 metabolites selected from the group consisting of:

C18:2co6 fatty acid, CI 6 acylcarnitine, and C18:3co3 fatty acid,

in a blood sample of said subject.

14. The method or use according to any of the preceding claims, wherein method (2) comprises determining the level of at least 10, at least 15, at least 20, or at least 25 metabolites from the group consisting of: Maltose, Glucose, Maltotetraose, Glycerol-3- phosphate, Phenylacetylglycine, Malate, Gamma-glutamylleucine, Xanthosine, 5- dodecenoate (C12: ln7), Reduced glutathione (GSH), Ascorbate, Inosine, Alpha- tocopherol, Lactate, Cysteine, Cysteine-glutathione disulfide, Choline, Tagatose, Hexadecanedioate, Ophtalmate, Xylonate, Palmitoyl ethanolamide, Cytidine 5'- diphosphocholine, Thiamin, Hydroxyisovaleroyl carnitine, in a liver sample of said subject.

15. The method or use according to any of the preceding claims, comprising determining the level of at least 10, at least 15, at least 20, or the 25 metabolites from the group consisting of: Linoleate (C18:2n6), Dihomo-linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17: ln7), Oleate (C18: ln9), Cytidine, 10- nonadecenoate (C19: ln9), 1-arachidonoyl GPI, Glycerophosphorylcholine, Fructose, 12- HETE, Linolenate (C18:3n3 or 6), Eicosenoate (C20: ln9 or 11), Uridine 5 '- monophosphate, Margarate (C17:0), Eicosapentaenoate (C20:5n3), Dihomo-linolenate, Maltose, Carnosine, Methyl palmitate (15 or 2), Docosapentaeonoate (C22:5n6), Myristate (C14:0), Caproate (C6:0), and Choline, in a muscle sample of said subject.

16. The method or use according to any of the preceding claims, comprising determining the level of NAD⁺ in a liver and/or muscle sample of said subject.

17. A method of treating, preventing, or delaying, an age-related disease or disorder in a subject, comprising administering in a subject in need thereof an effective amount of an agent or composition that increases the level of C18:2co6 and/or C18:3co3 fatty acids and/or increases the level of C16 acylcarnitine, in the blood of said subject.

18. The method according to the preceding claim, wherein said agent or composition increases the level of C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid in the blood of said subject.

19. An agent or composition that increases the level of C18:2co6 and/or C18:3co3 fatty acids and/or increases the level of C16 acylcarnitine, in the blood of a subject, for use in the treatment or prevention of an age-related disease or disorder in said subject.

20. An agent or composition that increases the level of C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid in the blood of a subject, for use in the treatment or prevention of an age-related disease or disorder in said subject.

21. A method of inhibiting or delaying the aging process in a subject, comprising administering in a subject an effective amount of an agent or composition that increases the level of C18:2co6 and/or C18:3co3 fatty acids and/or increases the level of CI 6 acylcarnitine, in the blood of said subject.

22. An agent or composition that increases the level of C18:2co6 and/or C18:3co3 fatty acids and/or increases the level of C16 acylcarnitine, in the blood of a subject, for use in inhibiting or delaying the aging process in said subject.

23. An agent or composition that increases the level of C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid in the blood of a subject, for use in inhibiting or delaying the aging process in said subject.

24. A method of screening a compound for its ability to inhibit or delay the aging process in a subject comprising at least one method selected from:

(1) A method comprising the steps of:

b) exposing the samples from the first group to a test compound;

c) determining the level of at least one metabolite or of a set of at least two metabolites selected from the group consisting of: C18:2co6 fatty acid, C16 acylcarnitine, C18:3co3 fatty acid, C20:4co6 fatty acid, C12: l acylcarnitine, C22:5co6 fatty acid, C10: l acylcarnitine, C18:l co7 fatty acid, Proline, C24: lco9 fatty acid, C20:5co3 fatty acid, Alanine, C14 acylcarnitine, Serine, and C6 acylcarnitine, in the samples from the first and second groups;

(2) A method comprising the steps of:

b) exposing the samples from the first group to a test compound;

c) determining the level of at least one or of a set of at least two metabolites selected from the group consisting of: Maltose, Glucose, Maltotetraose, Glycerol-3- phosphate, Phenylacetylglycine, Malate, Gamma-glutamylleucine, Xanthosine, 5- dodecenoate (C12:ln7), Reduced glutathione (GSH), Ascorbate, Inosine, Alpha- tocopherol, Lactate, Cysteine, Cysteine-glutathione disulfide, Choline, Tagatose, Hexadecanedioate, Ophtalmate, Xylonate, Palmitoyl ethanolamide, Cytidine 5 '- diphosphocholine, Thiamin, Hydroxyisovaleroyl carnitine, and NAD⁺, in the samples from the first and second groups;

d) comparing the level of said metabolites between the first and second groups and identifying test compounds that modify the level of said metabolites in the samples from the first group such that the level of said metabolites in the samples from the first group is more similar to the level of said metabolites determined in the liver samples from young subjects; and

(3) A method comprising the steps of:

b) exposing the samples from the first group to a test compound;

c) determining the level of at least one metabolite or of a set of at least two metabolites selected from the group consisting of: Linoleate (C18:2n6), Dihomo- linoleate (C20:2n6), Trans-4-hydroxyproline, Pantothenate, 10-heptadecenoate (C17: ln7), Oleate (C18:ln9), Cytidine, 10-nonadecenoate (C19: ln9), 1-arachidonoyl GPI, Glycerophosphorylcholine, Fructose, 12-HETE, Linolenate (C18:3n3 or 6), Eicosenoate (C20: ln9 or 11), Uridine 5 '-monophosphate, Margarate (C17:0), Eicosapentaenoate (C20:5n3), Dihomo-linolenate, Maltose, Carnosine, Methyl palmitate (15 or 2), Docosapentaeonoate (C22:5n6), Myristate (C14:0), Caproate (C6:0), Choline, and NAD⁺, in the samples from the first and second groups;

d) comparing the level of said metabolites between the first and second groups and identifying test compounds that modify the level of said metabolites in the samples from the first group such that the level of said metabolites in the samples from the first group is more similar to the level of said metabolites determined in the muscle samples from young subjects.

25. A method according to the preceding claim, comprising determining the level of at least one metabolite selected from the group consisting of: C18:2co6 fatty acid, C16 acylcarnitine, and C18:3co3 fatty acid, or at least one metabolite selected from the group consisting of: C18:2co6 fatty acid and C16 acylcarnitine, in said blood samples.

26. The method according to any one of claims 22 to 22, wherein the subject is a mouse or a rat.

27. Kit of parts for carrying out any method or use according to the invention.