Methods for predicting the health state of a subject from fibroblasts

Abstract

In the present study, the Inventors propose that characterizing fibroblasts derived from individuals of very different ages, regarding their Structure, Inflammation, and Metabolism (SIM) signatures, and assessing their stress response to challenges mimicking life stresses, would enhance their understanding of the aging process and frailty syndrome and intrinsic capacity. To address these inquiries, they used fibroblasts obtained from skin biopsies of 133 male and female volunteers from the INSPIRE human translational cohort (INSPIRE-T cohort) 21, spanning ages 20 to 96 years, and encompassing various frailty statuses (robust, pre-frail, frail). Through this thorough characterization, they pinpointed markers specifically associated with aging, intrinsic capacity or indicators of frailty syndrome. The present invention relates to an in vitro method for predicting intrinsic capacity decline and / or frailty in a subject comprising the step of determining the level of extracellular periostin in a sample comprising fibroblasts obtained from said subject.

Description

[0001] METHODS FOR PREDICTING THE HEALTH STATE OF A SUBJECT FROM FIBROBLASTS

[0002] FIELD OF THE INVENTION:

[0003] The present invention is in the field of medicine and relates in particular to ageing.

[0004] BACKGROUND OF THE INVENTION:

[0005] Aging, often characterized by declining function over time, is a physiological process and the primary risk factor for age-related diseases, impacting health and survival h The World Health Organization (WHO) identifies five key domains to track health during aging, which can reveal frailty as a sign of unhealthy aging and precursor of dependency2. Intrinsic capacity (IC), a function-centered construct, which is defined as the composite of all physical and mental capacities of an individual and now recognized as measurable and predictive, refers to individual attributes contributing to healthy aging3>4. These clinical advances have been paralleled by notable progress in comprehending the intricate and dynamic cell changes underlying biological aging. Several aging molecular hallmarks have been recognized as pivotal drivers of the aging process5. The emerging field of geroscience proposed that aging biology is the main driver of chronic disease susceptibility and that targeting it will slow the appearance and progression of age-related diseases and disabilities6. Recently, we introduced a novel gerophysiological approach, merging the WHO healthy aging model with geroscience, to explore how the complex physiological alterations of aging impact individual intrinsic capacity7. Our approach also delves into the Structure / Inflammation / Metabolism network, which plays a pivotal role in determining the progression of age-related bodily functions. Fibroblasts are crucial for the architecture and function of all human tissues. They possess similar abilities to mesenchymal stromal cells (MSCs)8. Their multipotency and capacity to produce and regulate extracellular matrix (ECM) components largely influence tissue architecture, ensuring optimal function. Through paracrine signaling, fibroblasts can interact with surrounding cells including immune cells, modulating inflammation and immunity. Additionally, they play a role in regulating tissue metabolism and metabolite secretion. Consequently, fibroblasts serve as a valuable model for investigating the three intersecting elements of structure, inflammation, and metabolism. Skin behaves as a crucial physical barrier separating internal organs from the external environment, enduring constant exposure to external threats. Among its constituents, skin fibroblasts play a pivotal role as the primary component of the dermal layer. Beyond their foundational contribution to skin architecture, dermal fibroblasts actively engage in metabolic regulation, immune and inflammatory responses, wound healing, and intercellular communication within both the skin ecosystem and the extrinsic skin compartment9 10 11 12. Their relatively low proliferation rate leads to the accumulation of age-related damage13. Moreover, their accessibility via superficial skin biopsies renders them invaluable for investigating human aging, given their distinctive attributes and potential to uncover age and functional decline-related biomarkers. Numerous multi-omics studies have documented proteomic, epigenetic and transcriptomic alterations in human skin fibroblasts with age14 15 16. Notably, RNAseq profiles have allowed the prediction of chronological age17, and differences in cellular phenotype between fibroblasts from young and old individuals have been delineated. The biophysical and biomolecular characteristics of human skin fibroblasts have enabled the quantification of cellular aging18. Additionally, studies on non-human models have revealed a correlation between the stress resistance of isolated skin fibroblasts and life expectancy across species19. However, despite all these studies, most of these studies does not cover all ages of life, enrolled a small number of donors, with only a few subjecting cells to challenges. It is important to note that while certain blood biomarkers are linked to frailty syndrome in older individuals20, there is a need for one or a set of biomarkers that can predict the risk of frailty in younger individuals. This would allow for the implementation of suitable preventive or intervention strategies to reduce the likelihood or severity of frailty. Currently, no studies have been conducted to determine whether biomarkers of aging biomarkers are associated with Intrinsic Capacity at all ages. Establishing a close correlation between biomarkers and Intrinsic Capacity could enhance understanding of the underlying mechanisms of Intrinsic decline and provide targets for risk identification and early interventions.

[0006] SUMMARY OF THE INVENTION:

[0007] The present invention is defined by the claims. In particular, the present invention relates to an in vitro method for predicting intrinsic capacity decline and / or frailty in a subject comprising the step of determining the level of extracellular periostin in a sample comprising fibroblasts obtained from said subject.

[0008] DETAILED DESCRIPTION OF THE INVENTION:

[0009] A subject’s intrinsic capacity to cope with life’s stresses and challenges can affect his resilience and vulnerability to frailty during ageing. In summary, a lower intrinsic capacity can make a subject less able to cope with difficulties, thus increasing the risk of frailty during ageing. In the present study, the Inventors propose that characterizing fibroblasts derived from individuals of very different ages, regarding their Structure, Inflammation, and Metabolism (SIM) signatures, and assessing their stress response to challenges mimicking life stresses, would enhance their understanding of the aging process and frailty syndrome and intrinsic capacity. To address these inquiries, they used fibroblasts obtained from skin biopsies of 133 male and female volunteers from the INSPIRE human translational cohort (INSPIRE-T cohort)21, spanning ages 20 to 96 years, and encompassing various frailty statuses (robust, pre-frail, frail). Through this thorough characterization, they pinpointed markers specifically associated with aging, intrinsic capacity or indicators of frailty syndrome.

[0010] As used herein, the term “subject” refers to any mammals, such as a rodent, a feline, a canine, a horse or a primate. In a preferred embodiment, the subject is a human. In some embodiments, the subject is an adult aged between 20 and 39. In some embodiments, the subject is an adult aged between 80 and 100. In some embodiments, the subject is a baby (from birth to 2 years old), a child (from 2 years old to 10-12 years old), an adolescent (from 10-12 years old to approximately 18 years old), an adult (from 18 years old to 70 years old) or an elderly (from 70 years old).

[0011] As used herein, the term “sample” refers to any biological material (i.e. a material produced by or derived from an organism) used for the purpose of evaluation in vitro. In some embodiments, the sample is a tissue sample. In some embodiments, the sample is a synthetic (e.g. organoids, spheroids, tumoroids, oncospheroids, tissue reconstitution, tissue-like, engineered tissues, 3D models, 3D bioprints, organ-on-chip) or natural tissue sample (e.g. biopsy, tissue removed from the surface of the body of a subject, explants). In some embodiments, the synthetic tissue comprises, consists essentially in or consists in fibroblasts and mesenchymal stroma / stem cells. In some embodiments, the sample is a skin sample. In some embodiments, the sample is a synthetic skin sample, a skin biopsy or a skin explant. In some embodiments, the sample comprises, consists essentially in or consists in fibroblasts. In some embodiments, the sample comprises, consists essentially in or consists in fibroblasts obtained from a subject. In some embodiments, the fibroblasts are dermal fibroblasts. In some embodiments, the sample comprises, consists essentially in or consists in a population of fibroblasts obtained from the in vitro culture of fibroblasts, preferentially obtained from a subject. In some embodiments, the sample comprises, consists essentially in or consists in a population of fibroblasts obtained by collecting biological material from an organism, preferentially a subject; isolating fibroblasts from said biological material; and cultivating said isolated fibroblasts in a culture medium to obtain a population of fibroblasts. In some embodiments, the sample comprises, consists essentially in or consists in fibroblasts and mesenchymal stroma / stem cells.

[0012] As used herein, the term “predetermined reference value” refers to a threshold value or a cutoff value. A "threshold value", “reference value” or "cut-off value" can be determined experimentally, empirically, or theoretically. A threshold value can also be arbitrarily selected based upon the existing experimental and / or clinical conditions, as would be recognized by a person of ordinary skilled in the art. For example, retrospective measurement of the level of the marker of the invention in properly banked historical patient samples may be used in establishing the predetermined corresponding reference value. In some embodiments, the predetermined corresponding reference value is the median measured in the population of the patients for the marker of in the invention. In some embodiments, the threshold value has to be determined in order to obtain the optimal sensitivity and specificity according to the function of the test and the benefit / risk balance (clinical consequences of false positive and false negative). Typically, the optimal sensitivity and specificity (and so the threshold value) can be determined using a Receiver Operating Characteristic (ROC) curve based on experimental data. For example, after determining the level of the marker of the invention in a group of reference, one can use algorithmic analysis for the statistic treatment of the levels determined in samples to be tested, and thus obtain a classification standard having significance for sample classification. The full name of ROC curve is receiver operator characteristic curve, which is also known as receiver operation characteristic curve. It is mainly used for clinical biochemical diagnostic tests. ROC curve is a comprehensive indicator that reflects the continuous variables of true positive rate (sensitivity) and false positive rate (1-specificity). It reveals the relationship between sensitivity and specificity with the image composition method. A series of different cut-off values (thresholds or critical values, boundary values between normal and abnormal results of diagnostic test) are set as continuous variables to calculate a series of sensitivity and specificity values. Then sensitivity is used as the vertical coordinate and specificity is used as the horizontal coordinate to draw a curve. The higher the area under the curve (AUC), the higher the accuracy of diagnosis. On the ROC curve, the point closest to the far upper left of the coordinate diagram is a critical point having both high sensitivity and high specificity values. The AUC value of the ROC curve is between 1.0 and 0.5. When AUC>0.5, the diagnostic result gets better and better as AUC approaches 1. When AUC is between 0.5 and 0.7, the accuracy is low. When AUC is between 0.7 and 0.9, the accuracy is moderate. When AUC is higher than 0.9, the accuracy is quite high. This algorithmic method is preferably done with a computer. Existing software or systems in the art may be used for the drawing of the ROC curve, such as: MedCalc 9.2.0.1 medical statistical software, SPSS 9.0, ROCPOWER.SAS, DESIGNROC.FOR, MULTIREADER POWER. SAS, CREATE-ROC.SAS, GB STAT VIO.O (Dynamic Microsystems, Inc. Silver Spring, Md., USA), etc.

[0013] In some embodiments, the level of extracellular periostin or any marker according to the invention (e.g. fibroblast biomarker) is determined by immunohistochemistry (IHC). Immunohistochemistry typically includes the following steps i) fixing said tissue sample with formalin, ii) embedding said tissue sample in paraffin, iii) cutting said tissue sample into sections for staining, iv) incubating said sections with the binding partner specific for the marker, v) rinsing said sections, vi) incubating said section with a biotinylated secondary antibody and vii) revealing the antigen-antibody complex with avidin-biotin-peroxidase complex. Accordingly, the tissue sample is firstly incubated with the binding partners. After washing, the labeled antibodies that are bound to marker of interest are revealed by the appropriate technique, depending of the kind of label is borne by the labeled antibody, e.g. radioactive, fluorescent or enzyme label. Multiple labelling can be performed simultaneously. Alternatively, the method of the present invention may use a secondary antibody coupled to an amplification system (to intensify staining signal) and enzymatic molecules. Such coupled secondary antibodies are commercially available, e.g. from Dako, EnVision system. Counterstaining may be used, e.g. H&E, DAPI, Hoechst. Other staining methods may be accomplished using any suitable method or system as would be apparent to one of skill in the art, including automated, semi-automated or manual systems. For example, one or more labels can be attached to the antibody, thereby permitting detection of the target protein (i.e the marker). Exemplary labels include radioactive isotopes, fluorophores, ligands, chemiluminescent agents, enzymes, and combinations thereof. In some embodiments, the label is a quantum dot. Non-limiting examples of labels that can be conjugated to primary and / or secondary affinity ligands include fluorescent dyes or metals (e.g. fluorescein, rhodamine, phycoerythrin, fluorescamine), chromophoric dyes (e.g. rhodopsin), chemiluminescent compounds (e.g. luminal, imidazole) and bioluminescent proteins (e.g. luciferin, luciferase), haptens (e.g. biotin). A variety of other useful fluorescers and chromophores are described in Stryer L (1968) Science 162:526-533 and Brand L and Gohlke J R (1972) Annu. Rev. Biochem. 41 :843-868. Affinity ligands can also be labeled with enzymes (e.g. horseradish peroxidase, alkaline phosphatase, beta-lactamase), radioisotopes (e.g. 3H, 14C, 32P, 35S or 1251) and particles (e.g. gold). The different types of labels can be conjugated to an affinity ligand using various chemistries, e.g. the amine reaction or the thiol reaction. However, other reactive groups than amines and thiols can be used, e.g. aldehydes, carboxylic acids and glutamine. Various enzymatic staining methods are known in the art for detecting a protein of interest. For example, enzymatic interactions can be visualized using different enzymes such as peroxidase, alkaline phosphatase, or different chromogens such as DAB, AEC or Fast Red. In other examples, the antibody can be conjugated to peptides or proteins that can be detected via a labeled binding partner or antibody. In an indirect IHC assay, a secondary antibody or second binding partner is necessary to detect the binding of the first binding partner, as it is not labeled. The resulting stained specimens are each imaged using a system for viewing the detectable signal and acquiring an image, such as a digital image of the staining. Methods for image acquisition are well known to one of skill in the art. For example, once the sample has been stained, any optical or non-optical imaging device can be used to detect the stain or biomarker label, such as, for example, upright or inverted optical microscopes, scanning confocal microscopes, cameras, scanning or tunneling electron microscopes, canning probe microscopes and imaging infrared detectors. In some examples, the image can be captured digitally. The obtained images can then be used for quantitatively or semi-quantitatively determining the amount of the marker in the sample. Various automated sample processing, scanning and analysis systems suitable for use with immunohistochemistry are available in the art. Such systems can include automated staining and microscopic scanning, computerized image analysis, serial section comparison (to control for variation in the orientation and size of a sample), digital report generation, and archiving and tracking of samples (such as slides on which tissue sections are placed). Cellular imaging systems are commercially available that combine conventional light microscopes with digital image processing systems to perform quantitative analysis on cells and tissues, including immunostained samples. See, e.g., the CAS-200 system (Becton, Dickinson & Co.). In particular, detection can be made manually or by image processing techniques involving computer processors and software. Using such software, for example, the images can be configured, calibrated, standardized and / or validated based on factors including, for example, stain quality or stain intensity, using procedures known to one of skill in the art (see e.g., published U.S. Patent Publication No. US20100136549). The image can be quantitatively or semi-quantitatively analyzed and scored based on staining intensity of the sample. Quantitative or semi-quantitative histochemistry refers to method of scanning and scoring samples that have undergone histochemistry, to identify and quantitate the presence of the specified biomarker (i.e. the marker). Quantitative or semi-quantitative methods can employ imaging software to detect staining densities or amount of staining or methods of detecting staining by the human eye, where a trained operator ranks results numerically. For example, images can be quantitatively analyzed using a pixel count algorithms (e.g., Aperio Spectrum Software, Automated Quantitative Analysis platform (AQUA® platform), and other standard methods that measure or quantitate or semi -quantitate the degree of staining; see e.g., U.S. Pat. No. 8,023,714; U.S. Pat. No. 7,257,268; U.S. Pat. No. 7,219,016; U.S. Pat. No. 7,646,905; published U.S. Patent Publication No. US20100136549 and 20110111435; Camp et al. (2002) Nature Medicine, 8: 1323-1327; Bacus et al. (1997) Analyt Quant Cytol Histol, 19:316-328). A ratio of strong positive stain (such as brown stain) to the sum of total stained area can be calculated and scored. The amount of the detected biomarker (i.e. the marker) is quantified and given as a percentage of positive pixels and / or a score. For example, the amount can be quantified as a percentage of positive pixels. In some examples, the amount is quantified as the percentage of area stained, e.g., the percentage of positive pixels. For example, a sample can have at least or about at least or about 0, 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25%, 26%, 27%, 28%, 29%, 30%, 31%, 32%, 33%, 34%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95% or more positive pixels as compared to the total staining area. In some embodiments, a score is given to the sample that is a numerical representation of the intensity or amount of the histochemical staining of the sample, and represents the amount of target biomarker (e.g., the marker) present in the sample. Optical density or percentage area values can be given a scaled score, for example on an integer scale. Thus, in some embodiments, the method of the present invention comprises the steps consisting in i) providing one or more immuno-stained slices of tissue section obtained by an automated slide-staining system by using a binding partner capable of selectively interacting with the marker (e.g. an antibody as above descried), ii) proceeding to digitalisation of the slides of step a. by high resolution scan capture, iii) detecting the slice of tissue section on the digital picture iv) providing a size reference grid with uniformly distributed units having a same surface, said grid being adapted to the size of the tissue section to be analyzed, and v) detecting, quantifying and measuring intensity of stained cells in each unit whereby the number or the density of cells stained of each unit is assessed.

[0014] In some embodiments, the level of extracellular periostin or any marker according to the invention is determined by single-cell proteomic. In some embodiments, the level of extracellular periostin or any marker according to the invention is determined by mass spectrometry. Mass spectrometry (MS) is an analytical technique used to measure a mass-to-charge ratio of ions in pure samples as well as complex mixtures. Results are depicted in a spectrum. The spectra are used to determine the elemental or isotopic signature of a sample, the masses of particles and of molecules, and to elucidate the chemical identity or structure of molecules and other chemical compounds. In a typical MS procedure, the sample may be solid, liquid, or gaseous. The sample is ionized, for example by bombarding it with a beam of electrons. Some of the sample's molecules break up into positively charged fragments or simply become positively charged without fragmenting. These ions (fragments) are then separated according to their mass-to-charge ratio, for example by accelerating them and subjecting them to an electric or magnetic field. The ions are detected by a mechanism capable of detecting charged particles, such as an electron multiplier. Results are displayed as spectra of the signal intensity of detected ions as a function of the mass-to-charge ratio. The atoms or molecules in the sample can be identified by correlating known masses to the identified masses or through a characteristic fragmentation pattern. In some embodiments, the level of at least one metabolite is determined by high resolution mass spectrometry (HRMS). In some embodiments, the level of at least one metabolite is determined by high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS). In some embodiments, the level of at least one metabolite is determined by supercritical fluid chromatography coupled with high-resolution mass spectrometry (SFC-HRMS). Supercritical fluid chromatography is typically used for the analysis and purification of low to moderate molecular weight. It is a normal phase chromatography that uses a supercritical fluid (e.g. carbon dioxide) as the mobile phase.

[0015] In some embodiments, the level of extracellular periostin or any marker according to the invention is determined by Nuclear Magnetic Resonance (NMR). NMR is a physical phenomenon wherein nuclei is in a strong constant magnetic field and is perturbated by a weak oscillating magnetic field. The nuclei respond by producing an electromagnetic signal with a frequency characteristic of the magnetic field at the nucleus. This process occurs when the oscillation frequency matches the intrinsic frequency of the nuclei which depends on the strength of the static magnetic field, the chemical environment, and the magnetic properties of the isotope involved. The most commonly used nuclei areJH and13C but19F,31P or33S can be studied by high field NMR spectroscopy as well. Methods for predicting intrinsic capacity decline in a subject

[0016] In a first aspect, the present invention relates to an in vitro method for predicting intrinsic capacity decline in a subject comprising the step of determining the level of extracellular periostin in a sample comprising fibroblasts obtained from said subject. The method can encompass the preliminary steps of : i) isolating fibroblasts from said sample ii) cultivating said isolated fibroblasts in a culture medium

[0017] As used herein, the term “intrinsic capacity” or “IC” is a function-centered construct, which is defined as the composite of all physical and mental capacities of an individual and refers to individual attributes contributing to healthy aging. The term “intrinsic capacity” can be interchanged with the terms “functional reserve”, “functional capacity”, “reserve capacity”, “reserve potential”, “resilience capacity”, “adaptability” or “adaptive reserve”. The World Health Organization identify five key domains: mobility (e.g. balance, speed), cognition (e.g. memory, intelligence, problem solving), vitality (e.g. handgrip strength, nutritional status), psycho-social (e.g. depression, low energy) and neuro-sensorial (e.g. hearing, vision). Examplary methods to measure intrinsic capacity are described in Yetian Liang et al. (Yetian L. et al., Measurements of Intrinsic Capacity in Older Adults: A Scoping Review and Quality Assessment, Journal of the American Medical Directors Association, Volume 24, Issue 3, 2023, Pages 267-276. e2, ISSN 1525-8610).

[0018] As used herein, the term “intrinsic capacity decline” refers to a predictor of adverse health outcomes able to identify individuals at higher risk of functional decline. Intrinsic capacity decline can be as example associated with cognitive decline, limited mobility, malnutrition, visual impairment, hearing loss, depressive symptoms. The trajectories of intrinsic capacity decline are specific to each subject and can be reversed or slowed down by appropriate management. An exemplary method to monitor intrinsic capacity is depicted in Lu, W.-H. et al., 2023 (Lu, W.-H. et al, Reference centiles for intrinsic capacity throughout adulthood and their association with clinical outcomes: a cross sectional analysis from the INSPIRE-T cohort. Nat. Aging (2023)). As used herein, the term “periostin” refers to a protein encoded by POSTN gene (Entrez : 10631; Ensembl: ENSG00000133110). An exemplary amino acid is depicted in SEQ ID NO: Periostin OS=Homo sapiens OX=9606

[0019] MI PFLPMFSLLLLLIVNPINANNHYDKILAHSRIRGRDQGPNVCALQQILGTKKKYFSTC

[0020] KNWYKKSICGQKTTVLYECCPGYMRMEGMKGCPAVLPIDHVYGTLGIVGATTTQRYSDAS

[0021] KLREEIEGKGSFTYFAPSNEAWDNLDSDIRRGLESNVNVELLNALHSHMINKRMLTKDLK

[0022] NGMI I PSMYNNLGLFINHYPNGWTVNCARI IHGNQIATNGWHVIDRVLTQIGTSIQDF

[0023] IEAEDDLSSFRAAAITSDILEALGRDGHFTLFAPTNEAFEKLPRGVLERIMGDKVASEAL

[0024] MKYHILNTLQCSESIMGGAVFETLEGNTIEIGCDGDSITVNGIKMVNKKDIVTNNGVIHL

[0025] IDQVLI PDSAKQVIELAGKQQTTFTDLVAQLGLASALRPDGEYTLLAPVNNAFSDDTLSM

[0026] DQRLLKLILQNHILKVKVGLNELYNGQILETIGGKQLRVFVYRTAVCIENSCMEKGSKQG

[0027] RNGAIHI FREI IKPAEKSLHEKLKQDKRFSTFLSLLEAADLKELLTQPGDWTLFVPTNDA

[0028] FKGMTSEEKEILIRDKNALQNI ILYHLTPGVFIGKGFEPGVTNILKTTQGSKI FLKEVND

[0029] TLLVNELKSKESDIMTTNGVIHWDKLLYPADTPVGNDQLLEILNKLIKYIQIKFVRGST

[0030] FKEI PVTVYTTKI ITKWEPKIKVIEGSLQPI IKTEGPTLTKVKIEGEPEFRLIKEGETI

[0031] TEVIHGEPI IKKYTKI IDGVPVEITEKETREERI ITGPEIKYTRI STGGGETEETLKKLL

[0032] QEEVTKVTKFIEGGDGHLFEDEEIKRLLQGDTPVRKLQANKKVQGSRRRLREGRSQ

[0033] In some embodiments, the present invention relates to an in vitro method for predicting intrinsic capacity decline in a subject comprising the steps of: i) determining the level of extracellular periostin in a sample comprising fibroblasts obtained from said subject; ii) comparing the level determined at step i) with a predetermined reference value and iii) concluding that the subject is at risk of suffering from intrinsic capacity decline when the level of extracellular periostin determined at step i) is lower than the predetermined reference value.

[0034] To monitor the intrinsic capacity (increase or decline) of a subject, the method according to the invention can encompass the comparison of extracellular periostin level in samples collected on the subject at different times (e.g. two different times or more). In some embodiments, the present invention relates to an in vitro method for predicting intrinsic capacity decline in a subject comprising the steps of: i) determining the level of extracellular periostin in a first sample comprising fibroblasts obtained from said subject; ii) comparing the level determined at step i) with the level determined in a second sample comprising fibroblasts obtained from said subject at a different time (i.e. second sample collection several minutes, days, weeks, months, years after the first one); and iii) concluding that the subject is at risk of suffering from intrinsic capacity decline when the level of extracellular periostin obtained at step ii) is lower as compared to the level determined at step i).

[0035] Methods for predicting frailty in a subject

[0036] In a second aspect, the present invention relates to an in vitro method for predicting frailty in a subject comprising the step of determining the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration in a sample comprising fibroblasts obtained from said subject. The method can encompass the preliminary steps of : i) isolating fibroblasts from said sample ii) cultivating said isolated fibroblasts in a culture medium

[0037] As used herein, the term “frailty” refers to a clinically recognizable state in which the ability of a subject to cope with everyday or acute stressors is compromised by an increased vulnerability brought by age-associated declines in physiological reserve and function across multiple organ systems. Frailty confers as example high risk for falls, disability, hospitalization, and mortality. An exemplary method to measure frailty is described in L.P Fried et al., 2001 (Fried, L P et al. “Frailty in older adults: evidence for a phenotype.” The journals of gerontology. Series A, Biological sciences and medical sciences vol. 56,3 (2001): M146-56).

[0038] As used herein, the term “basal mitochondrial respiration” refers to a process of energy conversion of substrates into ATP. As example, basal mitochondrial respiration can be determined by monitoring OCR (i.e. the rate at which cells consume oxygen) in the absence of any inhibitors.

[0039] As used herein, the term “maximal mitochondrial respiration” refers to the highest rate at which mitochondria consume oxygen under conditions in which the electron transport chain is fully uncoupled from ATP synthesis.

[0040] As used herein, the term “percentage of CFU-f’ or “Colony-Forming Unit-Fibroblast” refers to the proportion of cells within a given population that are capable of adhering to a culture surface and forming fibroblast-like colonies under defined culture conditions. In some embodiments, the present invention relates to an in vitro method for predicting frailty in a subject comprising the step of: i) determining the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration in a sample comprising fibroblasts obtained from said subject; ii) comparing the level determined at step i) with a predetermined reference value and iii) concluding that the subject is at risk of suffering from frailty when the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration determined at step i) is lower than the predetermined reference value.

[0041] In some embodiments, the present invention relates to an in vitro method for predicting frailty in a subject comprising the step of: i) determining the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration in a first sample comprising fibroblasts obtained from said subject; ii) comparing the level determined at step i) with the level determined in a second sample comprising fibroblasts obtained from said subject at a different time (i.e. second sample collection several minutes, days, weeks, months, years after the first one); and iii) concluding that the subject is at risk of suffering from frailty when the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration obtained at step ii) is lower as compared to the level determined at step i).

[0042] Methods for monitoring ageing of a synthetic tissue comprising fibroblasts

[0043] In a third aspect, the present invention relates to an in vitro method for monitoring ageing of a synthetic tissue comprising fibroblasts comprising the step of determining the level of extracellular periostin. In some embodiments, the synthetic tissue comprises, consists essentially in or consists in fibroblasts and mesenchymal stroma / stem cells. The present methods can also be used to screen anti-ageing and / or senolytic compounds. According to this embodiment, the methods can comprise a step of administering to the synthetic tissue a compound. An increasing level of extracellular periostin as compared to a predetermined reference value would be indicative of a functional anti-ageing and / or senolytic compound. The methods can encompass the preliminary steps of : i) isolating fibroblasts from said synthetic tissue ii) cultivating said isolated fibroblasts in a culture medium

[0044] In some embodiments, the present invention relates to an in vitro method for monitoring ageing of a synthetic tissue comprising fibroblasts, the method comprising the steps of : i) determining the level of extracellular periostin in a sample obtained from the synthetic tissue; ii) comparing the level determined at step i) with a predetermined reference value and iii) concluding that the synthetic tissue is ageing when the level of extracellular periostin determined at step i) is lower than the predetermined reference value.

[0045] In some embodiments, the present invention relates to an in vitro method for monitoring ageing of a synthetic tissue comprising fibroblasts, the method comprising the steps of : i) determining the level of extracellular periostin in a first sample obtained from the synthetic tissue; ii) determining the level of extracellular periostin in a second sample obtained from the synthetic tissue at a different time (i.e. second sample collection several minutes, days, weeks, months, years after the first one); iii) comparing the level determined at step i) with the level determined at step ii); and iv) concluding that the synthetic tissue is ageing when the level of extracellular periostin obtained at step ii) is lower as compared to the level determined at step i).

[0046] In some embodiments, the synthetic tissue is a skin synthetic tissue. Thus, the present invention also relates to an in vitro method for monitoring ageing of a skin synthetic tissue comprising fibroblasts, the method comprising the step of determining the level of extracellular periostin. In some embodiments, the skin synthetic tissue is an organoid, a spheroid, a tumoroid, an oncospheroid, a skin tissue reconstitution, a skin-like model, an engineered skin tissue, a 3D model, a bio printed skin, a skin-on-chip or a skin tissue-like. In some embodiments, the fibroblasts are isolated and cultured as described in the material and methods section. In some embodiments, the culture medium is an a-MEM medium (Life technologies) supplemented with 1% ASP, 1% L-glutamine and 5% FBS, at 37 °C in a humidified incubator with 20% 02 and 5% CO2, or equivalent.

[0047] In some embodiments, the in vitro method for monitoring ageing of said synthetic tissue comprises the step of determining the level of extracellular periostin and at least one selected from the group comprising extracellular IL-6, ECAR, cell doubling time, OCR-uncoupled respiration, yH2AX, GLUT-1 mRNA, SOD1 mRNA, GPxl mRNA, TIMP1 mRNA and / or hexokinase 2 mRNA.

[0048] In some embodiments, the in vitro method for monitoring ageing of said synthetic tissue comprises the step of determining the level of extracellular periostin and at least one selected from the group comprising extracellular IL-6, ECAR, cell doubling time, OCR-uncoupled respiration, yH2AX, GLUT-1 mRNA, SOD1 mRNA, GPxl mRNA, TIMP1 mRNA, hexokinase 2 mRNA, extracellular IL-ip, cell size and / or P-galactosidase.

[0049] In some embodiments, the in vitro method for monitoring ageing of said synthetic tissue comprises the step of determining the level of extracellular periostin and at least one selected from the group comprising extracellular IL-6, ECAR, cell doubling time, OCR-uncoupled respiration, yH2AX, GLUT-1 mRNA, SOD1 mRNA, GPxl mRNA, TIMP1 mRNA, extracellular IL-ip and / or cell size.

[0050] In some embodiments, the in vitro method for monitoring ageing of said synthetic tissue comprises the step of determining the level of extracellular periostin and at least one selected from the group comprising extracellular IL-6, ECAR, cell doubling time, OCR-uncoupled respiration, yH2AX, GLUT-1 mRNA, SOD1 mRNA, GPxl mRNA, TIMP1 mRNA, hexokinase 2 mRNA, extracellular IL-6 in LPS-challenging medium, extracellular IL-ip in LPS-challenging medium, extracellular IFN- P in poly:IC- challenging medium, cell size in doxorubicin-challenging medium and / or P-galactosidase in doxorubicin-challenging medium.

[0051] Methods of treating

[0052] In some embodiments, the methods of the present invention comprise a further step of administering the subject with a treatment or practising a non-drug treatment in order to reverse or slow-down intrinsic capacity decline and / or frailty. Thus, the present invention also relates to a method of treating intrinsic capacity decline and / or frailty in a subject in need thereof, the method comprising administering the subject with a treatment or practising a non-drug treatment against intrinsic capacity decline and / or frailty. Typically, treatments are well-known and includes drug administration or non-drug treatment (e.g. functional rehabilitation, orthophonic or mortician therapy, behavioural therapy, cognitive stimulation, memory stimulation, sport, diets).

[0053] As used herein, the terms “treating”, “treatment” or “therapy” refer to both prophylactic or preventive treatment as well as curative or disease modifying treatment, including treatment of subject at risk of contracting the disorder or suspected to have contracted the disorder as well as subject who are ill or have been diagnosed as suffering from a disease or medical condition, and includes suppression of clinical relapse. The term encompasses both drug administration and non-drug treatment. The treatment may be administered to a subject having a medical disorder or who ultimately may acquire the disorder, in order to prevent, cure, delay the onset of, reduce the severity of, or ameliorate one or more symptoms of a disorder or recurring disorder, or in order to prolong the survival of a subject beyond that expected in the absence of such treatment. By "therapeutic regimen" is meant the pattern of treatment of an illness, e.g., the pattern of dosing used during therapy. A therapeutic regimen may include an induction regimen and a maintenance regimen. The phrase "induction regimen" or "induction period" refers to a therapeutic regimen (or the portion of a therapeutic regimen) that is used for the initial treatment of a disease. The general goal of an induction regimen is to provide a high level of drug to a subject during the initial period of a treatment regimen. An induction regimen may employ (in part or in whole) a "loading regimen", which may include administering a greater dose of the drug than a physician would employ during a maintenance regimen, administering a drug more frequently than a physician would administer the drug during a maintenance regimen, or both. The phrase "maintenance regimen" or "maintenance period" refers to a therapeutic regimen (or the portion of a therapeutic regimen) that is used for the maintenance of a subject during treatment of an illness, e.g., to keep the subject in remission for long periods of time (months or years). A maintenance regimen may employ continuous therapy (e.g., administering a drug at regular intervals, e.g., weekly, monthly, yearly, etc.) or intermittent therapy (e.g., interrupted treatment, intermittent treatment, treatment at relapse, or treatment upon achievement of a particular predetermined criteria [e.g., disease manifestation, etc.]). As used herein the terms "administering" or "administration" refer to the act of injecting or otherwise physically delivering a substance as it exists outside the body (e.g., treatment against intrinsic capacity decline and / or frailty) into the subject, such as by mucosal, intradermal, intravenous, subcutaneous, intramuscular delivery and / or any other method of physical delivery described herein or known in the art. When a disease, or a symptom thereof, is being treated, administration of the substance typically occurs after the onset of the disease or symptoms thereof. When a disease or symptoms thereof, are being prevented, administration of the substance typically occurs before the onset of the disease or symptoms thereof.

[0054] The invention will be further illustrated by the following figures and examples. However, these examples and figures should not be interpreted in any way as limiting the scope of the present invention.

[0055] FIGURES:

[0056] Figure 1. Cellular characteristics of human skin fibroblasts that are significantly correlated with age. Linear regression with marginal distribution represents cell parameters as a function of age. Correlation between age with cell doubling time (days) (A), number of yH2AX foci per cell (B) and extracellular IL-6 concentration (pg / ml / 105cells) (C) are shown. Association of cell size (a.u.) (D) and senescence associated-P-galactosidase (gMFI) (E) with age after doxorubicin challenge are shown. The black line represents the regression line and the dashed line show the 95% confidence of the fit. Histograms depict the marginal distribution of the respective variable, r and p-value represent the Pearson correlation coefficient, and the associated p-value for each measured parameter with age. A p-value < 0.05 was considered significant (A-E).

[0057] Figure 2. Overview of the study design focused on dermal fibroblasts for the INSPIRE-T sub-cohort comprising 133 donors aged 20 from 96 years old. Cell characteristics were examined on skin fibroblasts according to the three transverse and common elements at the organism scale (stroma / structure, inflammation and metabolism). The outcome measured results per experiments are listed.

[0058] Figure 3. The age affects the regulation of pivotal molecular mediators implicated in the organization of structure / stroma, inflammation and metabolism within skin fibroblasts. Linear regression with marginal distribution represents cell parameters from stroma / structure (A-C), inflammation (D-F) and metabolism (G-L) as a function of age. Correlation between age with COL1A1 (A) and TIMP1 mRNA expression (2'ACt) (B) and extracellular periostin logarithmic concentration (pg / ml / 105cells) (C) are shown. Association with age of extracellular IL-6 (D) and IL1-P (E) concentration (pg / ml / 105cells) after LPS stimulation (Ipg / ml), and extracellular IFN-P concentration (pg / ml / 105cells) after Poly I:C stimulation (lOOpg / ml) (F) are shown. Correlation between age with uncoupled respiration over basal mitochondrial respiration (%) (G), ECAR measure (mpH / min / 2.104cells) (H), GLUT-1 and Hexokinase 2 mRNA expression (2'ACt) (I- J), mRNA expression (2'ACt) of SOD1 (K) and GPX1 (L) are shown. The black line represents the regression line and the dashed line show the 95% confidence of the fit. Histograms depict the marginal distribution of the respective variable, r and p-value represent the Pearson correlation coefficient, and the associated p-value for each measured parameter with age. A p-value < 0.05 was considered significant (A-L).

[0059] Figure 4. Age-related fibroblast markers cluster young and old individuals. Unsupervised multivariate analyses by principal component analysis (PCA) (B) and correlation circle (C) from the PCA applied on 16 variables (A), Extracellular periostin, Extracellular IL- 6, TIMP1 mRNA, extracellular 11-6 (LPS), Extracellular IL-lb (LPS), Extracellular IFN-lb (Poly EC), SOD1 mRNA, GPX1 mRNA, Uncoupled respiration, ECAR, GLUT-1 mRNA, Hexokinase 2 mRNA, yH2AX per cell, cell doubling time, cell size (doxorubicin), b- galactosidase (doxorubicin). PCA (E) and correlation circle (F) from the PCA applied on 12 variables (D), Extracellular periostin, Extracellular IL-6, TIMP1 mRNA, Extracellular IL-lb (LPS), SOD1 mRNA, GPX1 mRNA, Uncoupled respiration, ECAR, GLUT-1 mRNA, yH2AX per cell, cell doubling time, cell size (doxorubicin).

[0060] Figure 5. Association of Mahalanobis distance with age. Scatterplot of Mahalanobis distance versus age for n=108 donors with complete data on 31 cellular markers representing stroma / structure (% CFU-F, Extracellular periostin, cell migration basal / residual chemoattractant), inflammation (Extracellular IL1-P basal / LPS residual, Extracellular IL-6 basal / LPS residual, Extracellular IL-10 basal / LPS residual, Extracellular TGF-P basal / LPS residual, Extracellular IFN-P basal / Poly EC residual), metabolism (% differentiated adipocytes, Intensity of adipose differentiation, OCR-basal respiration, OCR-uncoupled respiration and Basal ECAR) and senescence (cell size basal / doxorubicin residual, beta galactosidase basal / doxorubicin residual, number of yH2AX spots per cell basal / doxorubicin residual, number of pl6 spots per cell basal / doxorubicin residual, nucleus area basal / doxorubicin residual, cell granularity basal / doxorubicin residual). The black line represents the regression line and the dashed lines show the 95% confidence of the fit. Histograms depict the marginal distribution of the respective variable, r and p-value represent the Pearson correlation coefficient, and the associated p-value for each measured parameter with age. A p-value < 0.05 was considered significant.

[0061] Figure 6. Multivariate analysis of senescence, structure, inflammation and metabolism markers with aging and health outcomes. Biplot of the first two principal components resulting from a PCA applied to (A) 12 senescence markers: cell size basal / doxorubicin residual, beta galactosidase basal / doxorubicin residual, number of yH2AX spots per cell basal / doxorubicin residual, number of pl6 spots per cell basal / doxorubicin residual, nucleus area basal / doxorubicin residual and cell granularity basal / doxorubicin residual, (B) 4 structures markers: Cell migration, Cell migration chemoattractant residual, % CFU-F and Extracellular periostin. Vectors represent the loadings of each biomarker on principal component 1 (x-axis) and principal component 2 (y-axis), (C) 10 inflammatory markers: Extracellular IL1-P basal / LPS residual, Extracellular IL-6 basal / LPS residual, Extracellular IL-10 basal / LPS residual, Extracellular TGF-P basal / LPS residual and Extracellular IFN-P basal / Poly I:C residual, and (D) 5 metabolism markers: % differentiated adipocytes, Intensity of adipose differentiation, OCR-basal respiration, OCR-uncoupled respiration and Basal ECAR and. (E) Association of the principal components with age, intrinsic capacity and frailty status, r and p-value represent the Pearson correlation coefficient, and the associated p-value for principal components with age. Linear regressions were performed to examine the association between principal components and IC score with adjustment for age, age2 and sex. Logistic regressions were performed to examine the association between principal components and pre-frailty / frailty with adjustment for age, age2 and sex.

[0062] Figure 7. Metabolism and structure human skin fibroblast biomarkers revealed functional decline. Violin plots show the distribution of basal mitochondrial respiration (pmol / min / 2.104cells) (A) and extracellular periostin logarithmic concentration (pg / ml / 105cells) (B) in robust and pre-frail / frail population. The horizontal line represents the median. Logistic regressions were performed to examine the association between cell parameters and pre-frailty / frailty. Cell parameters p values “padj” are based on logistic regression with adjustment for age and sex (A-B). Linear regression with marginal distribution represents Intrinsic Capacity score (IC) as a function of extracellular periostin logarithmic concentration (pg / ml / 105cells) and extracellular periostin p value “padj” is based on linear regression with adjustment for age and sex. The black line represents the regression line and the dashed line show the 95% confidence of the fit. Histograms depict the marginal distribution of the respective variable (C). Violin plot shows the distribution of extracellular periostin logarithmic concentration (pg / ml / 105cells) by IC centile group. The horizontal line represents the median. Association between IC centile groups (age and sex specific) and extracellular periostin secretion is determined using student's t-test (D). A p-value < 0.05 was considered significant (A-D).

[0063] Figure 8. Metabolism and structure human skin fibroblast markers reveal functional decline regardless of chronological age. Violin plots show the distribution of basal and maximal mitochondrial respiration (pmol / min / 2.104cells) (A) (B), CD36 mRNA expression (C), % CFU-f (D) and extracellular Periostin concentration (pg / ml / 105cells) (E) in robust and pre-frail / frail population. The horizontal line represents the median. Logistic regressions were performed to examine the association between cell parameters and pre- frailty / frailty status. Cell parameters p values “padj” are based on logistic regression with adjustment for age and sex (A-E). Linear regression with marginal distribution represents Intrinsic Capacity score (IC) as a function of extracellular Periostin concentration (pg / ml / 105cells) and extracellular Periostin p value “padj” is based on linear regression with adjustment for age and sex. The black line represents the regression line and the dashed line show the 95% confidence of the fit. Histograms depict the marginal distribution of the respective variable (F). Violin plot shows the distribution of extracellular Periostin concentration (pg / ml / 105cells) by IC centile group. The horizontal line represents the median. Association between IC centile groups (age and sex specific) and extracellular Periostin secretion is determined using student's one-way ANOVA test (G). A p-value < 0.05 was considered significant (A-G).

[0064] EXAMPLE 1 :

[0065] Material and Methods

[0066] Statement of ethics. Ethical and regulatory factors are taken into account within the INSPIRE-T cohort study. This study adheres to the principles outlined in the Declaration of Helsinki, which serves as the ethical framework for clinical research involving human subjects. Compliance with these principles is mandatory for all individuals involved in human research. The protocol for the INSPIRE-T cohort study was reviewed and approved by the French Ethical Committee based in Rennes (CPP Ouest V) in October 2019. Additionally, this research is registered on the clinical trials registry website http: / / clinicaltrials.gov (ID NCT04224038).

[0067] Skin biopsies. Skin biopsies were obtained from 133 volunteers from the INSPIRE human translational cohort (INSPIRE-T cohort)22. Individuals were recruited according to their chronological age (20 to 100 years old), sex and frailty status (robust, pre-frail, frail) (data not shown). Frailty status was assessed with following criteria: unintentional weight loss, selfreported exhaustion, weakness (grip strength), slow walking speed, and low physical activity. Individuals with no characteristics were considered robust, whereas those with one or two characteristics were considered prefrail and those with three or more than three characteristics were considered frail2. The 2 frail individuals in this cohort were assigned to the pre-frail group for statistical studies. Intrinsic capacity score was measured as the mean score of the five domains (cognition, locomotion, psychology, vitality and sensory (vision and hearing)23.

[0068] Human skin fibroblasts - Cell culture. Fibroblasts were obtained from skin biopsies cultivated in a-MEM medium (Life technologies) supplemented with 1% ASP and 20% FBS. Cells were detached by incubating at 37 °C for 5 min with 0.1% trypsin and 0.02% EDTA, numerated using an automated cell counter (Beckman Coulter) Vi-CELL XR and seeded at constant cell density (2000cells / cm2) until passage 3. Cells were maintained in a-MEM medium (Life technologies) supplemented with 1% ASP, 1% L-glutamine and 5% FBS, at 37 °C in a humidified incubator with 20% 02 and 5% CO2. Medium was changed every 2-3 days. All experiments were performed at passage 4.

[0069] Gene Expression Analysis. Total RNA was isolated using ReliaPrep™ RNA Cell Miniprep System (Promega) according to manufacturer recommendations. Total mRNA was reverse-transcribed into cDNA using high-capacity cDNA reverse transcription kit (Life technologies). RT-qPCR was performed on a Fluidigm BioMarkHD instrument (Fluidigm Corporation, USA) as previously described24cDNA pre-amplification step. 1.25 pL of cDNA were preamplified using the Preamp Master Mix kit (Fluidigm, cat.no. PN 100-5580) according to the manufacturer’s instructions: 1 pL of Preamp Master Mix was combined with 0,5 pL of Pooled Delta Gene assay mix (500nM) and 1.25 pL of cDNA in a 5 pL total volume reaction. Thermal cycling conditions were: 95 °C for 2 min followed by 15 cycles of 95 °C for 15 s, 60°C for 2 min.

[0070] Clean up reaction with Exonuclease I. After each preamplification reaction, samples were cleaned-up with exonuclease I (New England Biolabs cat.no PN-M0293S) treatment according to the manufacturer’s instructions. 2 pL of diluted Exo I at 4U / pL added to each 5- pL preamplification reaction. Thermal cycle the Exo I reaction using the following conditions: 37°C for 30 min, 80°C for 15 min. Then, samples were diluted 1 :20 by adding 93 pL nuclease- free water for a 100 pL total volume.

[0071] Real time qPCR using BiomarkTM HD system. PCR was performed following Gene Expression with the 192.24 IFC Using Delta Gene Assays protocol (PN 100-7222 Cl), using a 10X assays mix and a pre-sample mix prepared separately. The lOx assays mix was prepared by mixing 0,2 pL of 100 pM each Delta Gene™ primers (forward and reverse combined), 2 pL 2X Assay Loading Reagent (Fluidigm PN 100-7611) and 1,8 pL of IX DNA suspension buffer to a final volume of 4 pL (per reaction). The pre-sample mix was prepared by mixing 2 pL of 2X SsoFast EvaGreen Supermix with low ROX™ (Bio-Rad PN 172-5211), 0.2 pL 192.24 Delta Gene Sample Reagent (Fluidigm PN 100-6653) and 1.8 pL pre-amplified and Exo I treated cDNA to a final volume of 4 pL. Then, 3 pL of lOx assays mix and of pre-sample mix are transferred into the 192.24 IFC, loaded into the BiomarkTM IFC controller RX and transferred to the BiomarkTM HD apparatus. Thermal cycling conditions were as follows: 50°C for 120 s, 95°C for 600 s followed by 40 cycles of 95°C for 15 s, 60°C for 60 s.

[0072] Gene expression determination. The ACt was obtained by normalizing mean expression values of each gene to the geometric mean of the reference genes, ribosomal protein lateral stalk subunit P0 (RPLP0) and peptidylprolyl isomerase A (PPIA). Gene expression was calculated by the 2-ACT method or in fold increase of 2-ACT to control cells. These experiments were conducted on fibroblasts from 65 individuals from INSPIRE-Tcohort.

[0073] Senescence induction with doxorubicin. Treated cells were seeded at 1 x 104cells / cm2 in 24 well plates for immunofluorescence staining and in 6 well plates for C12FDG staining, and were incubated for 24h with 250nM doxorubicin. Then, cells were carefully washed with PBS before being cultured in standard medium. Control cells were seeded at 1 x 103 cells / cm2 to maintain their proliferation for long term culture. Medium was changed every 2-3 days for 10 days after treatment. 3 replicates were plated for each condition and donor. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0074] SA-p- al activity measurement by C12-FDG staining. 10 days after doxorubicinin treatment, cells were treated with 100 nM Bafilomycin 1 (Invivogen tlrl-bafal) for 2 hours then incubated with 20 pM 5-Dodecanoylaminofluorescein Di-P-D-Galactopyranoside substrate (C12FDG, Abeam ab273642) in the dark for 1 hour at 37 °C. Cells were then washed with PBS and nuclei were stained with DAPI. C12FDG uptake was quantified by flow cytometry using a MACSQuant (Milteny)ion FITC channel. Mean fluorescent intensity (MFI) were evaluated using Kaluza software.

[0075] Immunofluorescence. 10 days after doxorubicin treatment, cells were fixed using 4% paraformaldehyde (PF A) at RT for 20 min. Next, cells were permeabilized and blocked using solution (0.2% Triton X-100, 2% NHS) at RT for 20 min. Then, cells were labelled with mouse anti-human phospho-histone H2AX (Serl39) antibody (1 : 1000, Merk Millipore) for y-H2AX DNA damages foci and with rabbit anti-human pl6 antibody (1 :270, Abeam) overnight at 4°C. After washing, their respective secondary antibodies were incubated at RT for 2h: donkey antimouse A1488 secondary antibody (1 :400, ThermoFisher) and donkey anti-rabbit A1555 secondary antibody (1 :200, ThermoFisher). Finally, after repeated washing, nuclei were stained with DAPI at RT for 20min. Images were taken with the high content imaging system Operetta (Perkin Elmer). y-H2AX foci number per cell, pl 6 nuclear spots number per cell and nuclear area were calculated Harmony software (Perkin Elmer).

[0076] Population Doubling Assay. During fibroblasts amplification, cells were seeded at 2000cells / cm2in T-175 cell culture flasks. At 90% of cell confluence, fibroblasts were harvested and numerated. Doubling times were calculated using the following formula: DT = ln2* t / (In Cl -In CO), where t is the culture duration, Cl is the number of cells at the end of the culture and CO is the number of seeded cells. Doubling times of fibroblasts at passage 2 were studied. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE- T cohort.

[0077] Colony Forming Unit (CFU) Assay. Fibroblasts were plated in 96 well plates by creating of a range of cells with serial half-dilutions where each point of the range is seeded in 12 replicates. The medium was changed every 2-3 days. The cultures were kept at 37 °C with 5% CCh and at day 11 of growth, plates were fixed and stained with DAPI (1 : 10000, Sigma). Images were acquired using Operetta High Content Analysis system (Revvity) with lOx NA 0.4, 15 field of view were captured per well. Harmony analysis software (Revvity) was used to obtain automatically Colony-formation assay involved using Poisson distribution statistics by determining the number of wells with no clonogenic growth at day 11. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-Tcohort.

[0078] Cell migration assay. Fibroblasts migration was performed using the IncuCyte® S3 Live-Cell Analysis System (v20192.3.7219.27517-1, 2019B Rev2 GUI, Essenbioscience). Cells were seeded at 1500 cells / well density in a-MEM medium (Life technologies) supplemented with 1% ASP and 0.1% FBS in a 96-well plate (top). 200 pl of a-MEM medium (Life technologies) supplemented with 1% ASP and 10% FBS were added in wells of the reservoir plate (bottom). 3 replicates were plated for each condition and donor. Fibroblast migration across the membrane surface through the pores was automatically quantified for 24 h. The total count of fibroblast per well (bottom) normalized to the initial count (top) was calculated without (spontaneous migration) and with chemoattractant (cell migration under chemoattractant) via the Incucyte S3 software (Essenbioscience). These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0079] Myofibroblastic differentiation. Cells were seeded at 1.5 x io4cells / well in 24 well plates and were cultured in standard conditions for 96 h (time to reach cell confluence). Myofibroblastic differentiation was induced with 2 ng / ml TGF-pi (Miltenyi) for 10 days. Medium was changed every 2-3 days. RT-qPCR was performed for the smooth muscle actin (a-SMA), caldesmon (CALD1), calponin (CNN1), collagen type la (COL1A1) matrix metalloproteinase 1 (MMP1), tissue inhibitor of metalloproteinase 1 (TIMP1) and periostin (POSTN) gene expression. Untreated cells were analysed when cells reached confluency. 3 replicates were plated for each condition and donor. These experiments were conducted on fibroblasts from 65 individuals from INSPIRE-T cohort.

[0080] Adipogenic differentiation. Cells were seeded at 1.25 x io4cells / well in 24 well plates and were cultured in standard conditions for 96 h (time to reach cell confluence). Adipogenic differentiation was induced with 1 pM dexamethasone, 60 pM indomethacine, 500 pM IBMX) (Sigma Aldrich) for 14 days. Medium was changed every 2-3 days. Control cells were seeded in standard medium at 1 x 103 cells / cm2 to maintain their proliferation for long term culture. 3 replicates were plated for each condition and donor. Fibroblasts were fixed, nuclei were marked with DAPI (1 : 10000, Sigma) and lipids droplets were marked with Bodipy 493 / 503 (1 :500). Images were acquired using Operetta High Content Analysis system (Revvity) with 20x Air / 0.45 NA, 99 field of view were captured per well. DAPI and Bodipy were excited with the 360-400nm and 460-490nm excitation filters respectively. Nuclei and cells were segmented with “Find nuclei” and “Find cytoplasm” building blocks. Bodipy+ / total cells were quantified using the Harmony Analysis Software (Revvity). These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0081] LPS and Poly IC stimulation. Dermal fibroblasts (control and treated conditions) were seeded at 5 * 104cells / cm2in 24 well plates and treated by LPS (1 pg / ml) or Poly IC (lOOpg / ml) for 1 hour. Untreated fibroblasts were used as control condition. Then, cells were carefully washed 4 times with PBS before being maintain in standard medium for 48h. 3 replicates were plated for each condition and donor. Conditioned cell culture supernatants were collected and used for cytokine and chemokine profiling by ELLA method. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0082] Simple Plex™ assays on Ella™. Supernatants were stored at -80°C. IL-6, IL- 10, IL1- P and TGF-P concentrations were measured after LPS stimulation and the IFN-P concentration was measured after Poly IC stimulation. All of these cytokines have been quantified in control supernatants. Periostin concentration was also measured in control supernatant. Proteins were quantified by disposable microfluidic single and multianalyte SimplePlex cartridge using the fully automated immunoassay platform, Ella (ProteinSimple / Bio-techne, San Jose, CA). The supernatant samples were thawed on ice and diluted in sample diluent (SD 13) if necessary and loaded into cartridges with relevant high and low control concentrates. Five panels were used: IL-10 and IL1-P as pure (Panel 1); TGF-P as pure (Panel 2); IFN-P at a dilution of 1 :2 (Panel 3), IL-6 at a dilution of 1 :4 (Panel 4) and Periostin at a dilution of 1 :2 (Panel 5). Each protein channel contains 3 analyte-specific glass nanoreactors, which allows for each supernatant sample to be run in triplicates for target protein samples. Cartridges include a built-in lotspecific standard curve for defined supernatant protein. All steps in the procedure were run automatically by the instrument with no user activity. The obtained data were displayed as pg / mL and automatically calculated by the internal instrument software. Results were normalized to cell number measured during supernatant collection. Metabolic flux analysis. Seahorse XFe96 cell culture microplates were coated overnight with poly-D-lysine (0.1 mg / ml). The following day, the wells were thoroughly washed with PBS and allowed to dry for 1 hour. Fibroblasts were seeded at 20,000 cells per well in complete a-MEM medium (Life technologies) and incubated overnight at 37 °C in 5% CO2. 6 replicates were plated for each donor. Sensor cartridges were hydrated overnight in Seahorse XF calibrant at 37 °C without CO2 supplementation. On the day of the assay, fibroblasts were carefully washed with PBS, placed in XF DMEM supplemented with glucose (10 mM), glutamine (2 mM) and pyruvate (1 mM) then incubated for 1 hour at 37 °C without CO2 supplementation. After Seahorse XFe96 Analyzer calibration, the Oxygen Consumption Rate (OCR) was measured at the basal level then after the sequential injection of oligomycin (2.5 pM), FCCP (6 pM) and rotenone (2.5 pM) + antimycin A (2.5 pM). 3 cycles were performed at each step, consisting of 3 min of mix followed by 3 min of measurement. At the end of the experiment, the nuclei were stained with DAPI and the number of nuclei per well was determined using the Operetta High Content Imaging System (Perkin Elmer) and used to normalize the raw OCR data. This protocol provides information on basal respiration (basal OCR), uncoupled respiration (as a percentage of basal respiration), maximal respiration (maximal OCR) and extracellular acidification rate (basal ECAR). Cell density, plate coating as well as oligomycin and FCCP concentrations were determined by a dedicated pilot experiment. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0083] Statistical Analysis. Statistical analysis was performed using both Python and Jupyther notebook, and GraphPad Prism version 10 for Windows (GraphPad Software, USA). The python package pandas was used for data manipulation. Packages matplotlib and seaborn were used for plotting graphs, statsmodels module was used for statistics. The significance of the correlation between cell parameters with age was measured by the linear regression analyses. Pearson's correlation coefficients (r) were calculated to indicate the strength of the relationship between variables. Spearman rank’s correlations were used to evaluate association between some cell parameters with age. Logistic regressions were performed to examine the association between cell parameters and pre-frailty / frailty, with adjustment for age and sex. Linear regressions were performed to examine the association between cell parameters and Intrinsic Capacity (IC) score, with adjustment for age and sex. Association between IC centile and cell parameters were determined using student's t-test. A p < 0.05 was considered significant. Pearson's correlation coefficients were calculated to indicate the strength of the relationship between two cell parameters and are shown on matrix correlations. A p-value < 0.05 was considered significant (*p-value < 0.05, **p-value < 0.01, ***p -value< 0.001, and ****p - value< 0.0001), and those >0.05 were considered nonsignificant (ns). The package skleam decomposition module was used respectively for dimensionality reduction analysis. Using GraphPad Prism, Mann-Whitney test for two-independent samples was used to estimate the difference between two groups. Levene's test was used to assess homogeneity of variance between between two groups. A p-value < 0.05 was considered significant. Mahalanobis distance, a measure of dysregulation25, was calculated in R v4.3.1 using observations with complete data on 31 biomarkers (all except gene expression markers). For variables with both a basal level and a post-challenge level, the basal level and the residuals of a linear regression of the post-challenge level on the basal level were included. The Mahalanobis distance for each individual was log transformed and standardized by dividing by the sample standard deviation. For the principal components analysis of the metabolism biomarkers, we used the FactoMineR package26in R to calculate the principal components and the factoextra package27to produce the biplot. For both the principal components analysis and the Mahalanobis distance, biomarkers with right-skewed distributions were log-transformed and all biomarkers were scaled to have a mean of 0 and a standard deviation of 1 prior to analysis.

[0084] Results

[0085] Clinical characteristics of individual donors in the skin fibroblasts sub-cohort.

[0086] Primary human fibroblasts were obtained from skin biopsies collected from 133 individual donors spanning ages 20 to 96 years in the INSPIRE-T cohort22. The characteristics of the study population are summarized in Table 1. The mean (standard deviation [SD]) age was 60.5 (19.7) years. Males had a higher body mass index (BMI) and IC score than females.

[0087] Human skin fibroblasts retain aging signature in vitro. Our goal was to validate that human skin fibroblasts maintained characteristics of aging when cultured in vitro. To do so, we investigated various markers classically associated with cellular aging28. As expected29, the investigation of the fibroblast doubling time revealed a positive Pearson correlation (r=0.4 pvalue=3.10'6) between doubling time and age, suggesting that the growth of skin fibroblasts was decreased with aging (Figure 1A). Positive Pearson correlations were also observed between age and DNA damage marker, such as the number of y-H2AX foci per nucleus (r=0.36 p value=3.10'5) (Figure IB), as well as the inflammatory marker Extracellular IL-6 (r=0.21 pvalue=0.016) (Figure IC). Of note, the number of y-H2AX foci per cell and IL-6 production were significantly linearly correlated (r=0.46 pvalue=1.10'7) (data not shown). As these markers have been described as part of the markers of cellular senescence, we explored other known markers of cellular senescence such as morphological characteristics like nuclear area, cell size and cell granularity, as well expression of pl6 for cell cycle arrest and Senescence- Associated P-Galactosidase (SA-P-Gal) activity. None of these markers exhibited significant increase with age (data not shown) and Spearman correlation showed non-linear increase of nuclear pl6 expression with age (r=0.18 pvalue=0.043) (data not shown). Next, we evaluated fibroblasts stress response to challenges simulating life stresses. We used doxorubicin, a chemotherapy drug and potent DNA-damaging agent, as an inducer of senescence, aiming to determine putative age-dependent differences in the responses of the donors. Doxorubicin challenge induced significant increase with age of senescent markers such SA-P-Gal activity with age (Pearson correlation: r=0.21 pvalue=0.017) (Figure ID) as well as in cell size (Pearson correlation: r=0.22 pvalue=0.011) (Figure IE). Furthermore, there was a significant linear correlation between cell size and SA-P-Gal activity (r=0.3 pvalue=0.001) (data not shown).. However, none other known markers of cellular senescence, such as phosphorylated histone H2AX (y-H2AX) foci (data not shown), the number of pl6 nuclear spots per cell (data not shown), morphological characteristics like nuclear area (data not shown), and cell granularity (data not shown) exhibited a significant increase with age. Taken together, our findings indicated that fibroblasts from the INSPIRE-T sub-cohort exhibited molecular markers associated with donor chronological age, including cell doubling time and certain markers of senescence such as DNA damage and the pro-inflammatory cytokine IL-6.

[0088] Study design to reveal Structure, Inflammation and Metabolism (SIM) derived markers. In parallel of hallmarks of aging, we proposed that a fine exploration of the three interrelated system, i.e. SIM, should reveal putative markers related not only to aging but also to healthy aging. Firstly, we conducted an extensive experimental exploration involving all fibroblasts in the sub-cohort that we exposed to significant stresses, aiming to explore SIM derived molecular markers (Figure 2).

[0089] Aging impacts the regulation of key molecular actors involved in skin structure organization. Because the key structural role of fibroblasts is related to their ability both to secrete and to remodel the extracellular matrix and their ability to differentiate towards myofibroblasts, we investigated both components. Our findings indicated that there was no significant change in COL1A1 and MMP1 expressions with age (Figure 3A,data not shown) whereas TIMP1 expression exhibited a significant increase (Pearson correlation: r=0.56, p- value=1.10'6) (Figure 3B). The secretion of periostin, well-known for its ability to regulate ECM organization, specifically in facilitating proper collagen assembly and preserving homeostasis30 31, displayed a significant negative correlation between extracellular periostin levels and age, as determined by Pearson correlation analysis (r=-0.27, p-value=0.0026) (Figure 3C). Finally, we evaluated the myofibroblast potency of fibroblasts following stimulation with TGF-beta. This was achieved by quantifying the expression of the mRNA of ACTA2, CNN1, and CALD1, known to be expressed during myofibroblast differentiation. The results reveal no significant association between these mRNAs induction and age (data not shown).

[0090] Aging exacerbated cytokine production by human skin fibroblasts in response to inflammation stimuli. Fibroblasts are recognized for their role in modulating immune system components by secreting signalling factors such as cytokines and growth factors32. With advancing age, there is a tendency for increased production of pro-inflammatory cytokines, contributing to the development of chronic, low-grade inflammation known as Inflammaging33and non-immune cells like fibroblasts have been implicated in this phenomenon through the release of active molecules34Our study revealed a significant age-related increase in extracellular levels of pro-inflammatory cytokine such as IL-6 under basal conditions (Pearson correlation: r=0.21, p-value=0.016) (Figure 1C), while extracellular IL-ip remained unchanged with age (data not shown). Interestingly, extracellular basal levels of IL-10, TGF- P, and IFN-P were consistently undetectable in the supernatants of the majority of donor fibroblasts, regardless of age, under basal conditions (data not shown). To explore age-related differences among donors, we investigated how aging influences the inflammatory response of fibroblasts to cellular stressors such as bacterial and viral infections. To simulate these inflammatory challenges, cells were exposed to either the bacterial ligand LPS or the viral PRR ligand poly (I:C), a synthetic analog of viral dsRNA. Following LPS stimulation, we observed significant positive Pearson correlations between extracellular pro-inflammatory IL-6 (Figure 3D) and IL-ip (Figure 3E) levels and age (r=0.39, p-value=5.10'6and r=0.19, p-value=0.028, respectively). Moreover, after LPS stimulation, extracellular IL-6 and IL-ip exhibited a significant linear correlation (r=0.35, p-value=8.10'5) (data not shown). However, we found no age-dependent differences in extracellular IL-10 and TGF-P levels (data not shown). Finally, our results indicated that Poly (I: C) stimulation significantly enhanced the secretion of antiviral IFN-P in skin fibroblasts, and this increase was positively correlated with age (Pearson correlation: r=0.23, p-value=0.0092) (Figure 3F).

[0091] Aging impaired metabolic abilities of primary fibroblasts. Cell fate and behavior are strongly dependent on energy metabolism flexibility with numerous studies highlighting the importance of energy and redox metabolism in determining cell future and physiological function35 9 36. We first investigated mitochondrial metabolic activity by determining oxygen consumption rate (OCR). At the basal level, there was no significant variation of fibroblast OCR with age (data not shown). However, we observed a positive Pearson correlation between age and uncoupled respiration or proton leak (r=0.2 pvalue=0.022) (Figure 3G) associated with no difference with age of other OCR parameter such as maximal respiration (data not shown) and expression of genes regulating mitochondrial metabolism (NRF1, SDHA, COX4il, MT- ND1 and PDK1) (data not shown). In parallel to OCR, the flux analyser allowed for measurement of extracellular acidification rate (ECAR). This modification of the mitochondrial respiration was linked to an increase of basal glycolysis-related ECAR with chronological age (Pearson correlation: r=0.19 pvalue=0.033) (Figure 3H). Expression of genes related to glucose metabolism including the glucose transporter GLUT1 and the hexokinase-2 (HK2) which phosphorylates glucose during the first and irreversible step of glycolysis was also significantly increased with age (Pearson correlation: r=0.26 pvalue=0.037 and r=0.37 pvalue=0.0023 respectively) (Figure 31, 3J). We noticed that GLUT1 gene expression was significantly linearly correlated with HK2 gene expression (r=0.34 pvalue=0.009) and with basal glycolysis- related ECAR (r=0.74 pvalue=3.10'n) (data not shown). In addition, basal glycolysis-related ECAR was also linearly correlated with uncoupled respiration (r=0.5 pvalue=9.10'9) (data not shown). Then, we focused on gene expression of different enzymes involved in the anti- oxidative response. Pearson correlations showed very significant increase in SOD1 expression (r=0.56 pvalue=l .10'6) and a significant increase in GPxl (r=0.4 pvalue=0.001) expression with age (Figure 3K, 3L) whereas we observed no age dependent differences in NRF1, SIRT1, NRF2 and SOD2 expression (data not shown). Our findings also revealed significant Pearson correlations between the expression of the SOD1 gene and the expression of the GPxl gene (r=0.49, p-value=0.0001), the uncoupled respiration (r=0.37, p-value=0.005), and glycolysis- related ECAR (r=0.41, p-value=0.002) (data not shown). Additionally, significant correlations were observed between the expression of the SOD1, GLUT1 and HK2 gene (r=0.39, p- value=0.003; r=0.41, p-value=0.001 respectively) (data not shown). Among their intrinsic abilities, fibroblasts can behave as adipocyte progenitors to store electrons as triglycerides32. We challenged their ability to differentiate into adipocytes and observed a negative Spearman correlation showing non-linear decrease of the % of differentiated cells with age (r=-0.32 pvalue=0.0008) (data not shown). Altogether these results revealed that mitochondrial respiration would be less efficient with chronological age, associated with increase in glycolytic metabolism and the up-regulation of the expression of genes involved in antioxidant defense systems. Aging was also associated with a limited ability to store lipids.

[0092] Age-related fibroblasts markers cluster young and old individuals. Our aforementioned results have allowed us to determine 16 parameters altered with age, related to structure, inflammation and metabolism. To investigate the relationships among the 16 variables significantly altered with age (Figure 4A), a Principal Component Analysis (PCA) was performed using all fibroblasts from individuals (n=57) for whom the dataset was complete (Figure 4B, 4C). The PCA effectively distinguished fibroblasts from young (20-39 years) and older donors (80-100 years) represented by the pink and the blue circle respectively (Figure 4B) Two principal components (PC) explained 45.1% of the total variance (PC1=32.4%, PC2=12.7%). Furthermore, a minimum signature of 12 variables (Figure 4D) was sufficient to yield a clear demarcation between young and aged individuals, with PCI and 2 capturing 38.4% and 16.2% of the variance respectively (Figure 4E-F). The correlation circle obtained (Figure 4E) indicated that extracellular periostin was positioned relatively close to the axis of PC2, suggesting a significant contribution of extracellular periostin to the differentiation between age groups.

[0093] Association of Mahalanobis distance with age. Multiparametric analysis using a set of cellular markers has become a promising approach for elucidating the complex mechanisms of aging (Cohen A, 2013). Mahalanobis distance is a statistical measure that takes into account the correlations between variables, thus providing a more precise evaluation of multivariate variations compared to classical methods. For this study, we opted for the largest set of cellular markers feasible across the maximum donor pool. Thus, our analysis was based on 31 cellular markers from 108 donors. Using this subset, we investigated the association between Mahalanobis distance and individuals age (Figure 5). Our results indicate that the set of 31 SIM and senescence related markers revealed a Mahalanobis distance significantly associated with age (r=0.32, p=0.001). These findings underscore the intricate relationship between cellular markers spanning various biological domains and the aging process, as evidenced by the significant association between Mahalanobis distance and age. Multivariate analysis of structure, inflammation, metabolism and senescence markers with aging and health outcomes. To explore how different biological domains are associated with age, intrinsic capacity (IC), and frailty status, PCA were performed on an extensive array of markers representing senescence (Figure 6A), structure (Figure 6B), inflammation (Figure 6C), and metabolism (Figure 6D). Figure 6E presents correlation coefficients and p-values for PCI and PC2 across domains of senescence, structure, inflammation, and metabolism, with respect to age, pre-frailty / frailty, and intrinsic capacity (IC). Regarding senescence, both PCI and PC2 showed significant associations with age (r = 0.26, p = 0.003 and r = 0.21, p = 0.014, respectively). However, neither PCI nor PC2 is significantly associated with IC or frailty status. Regarding structure, neither PCI nor PC2 showed significant correlations with age. However, PC2 exhibited a significant correlation with IC (p = 0.03). Additionally, both PCI and PC2 showed significant associations with pre- frailty / frailty status (p = 0.03 and p = 0.004, respectively). In the context of inflammation, PC2 showed a significant positive association with age (r = 0.32, p = 0.003), whereas PCI did not show any significant associations with age, IC, or frailty status. In the context of metabolism domain, PCI showed a positive correlation with age (r = 0.32, p = 0.0003) and a significant association with IC (p = 0.02), with a regression coefficient of 0.95. PC2 was not significantly associated with IC in this domain, and neither PCI nor PC2 showed a significant association with frailty status. Overall, this multivariate analysis allows for a comprehensive exploration of the underlying biological mechanisms contributing to age-related changes and IC and frailty status.

[0094] Association between extracellular periostin and energy metabolism with frailty and only extracellular periostin with IC of skin fibroblasts from donors in the INSPIRE- T cohort. After conducting the multivariate analysis of SIM and senescence markers in relation to aging and health outcomes, our attention turned to the individual examination of variables. Logistic regressions were conducted for each of the cellular markers between fibroblast characteristics and both pre-frailty / frailty status and intrinsic capacity (IC) within the study population (data not shown). Among all variables, the senescence and inflammation markers indicated no significant correlation with frailty status or IC, while basal mitochondrial respiration and extracellular periostin (pvalue =0.001) were significantly decreased in fibroblasts from pre-frail donors compared to the robust group, independently of age and sex (Figure 7A, 7B). Next, we investigated whether IC - a measure reflecting an individual's combined physical and mental abilities - was associated with age-related markers in our study23. Our findings indicated that only extracellular periostin was significantly associated with IC score, as revealed by linear regression analysis, independent of age and sex (extracellular periostin pvalue =0.012) (Figure 7C). Furthermore, by using age- and sex-specific cut-offs for intrinsic capacity, referenced against centile curves, that stratified participants from the INSPIRE-T cohort into percentile categories ranging from <10th to >90th 23, we observed a positive association between centile categories and extracellular periostin levels (Figure 7D). The concentration of extracellular periostin was notably lower in individuals classified within the [0,25] percentile range for lower IC, compared to those falling within the [26,75] and [76,90] (p-value=0.039, p-value=0.019 respectively) categories. These findings collectively underscore the specific and robust link between extracellular periostin, intrinsic capacity, prefrailty and comorbidities independent of age and sex.

[0095] EXAMPLE 2 :

[0096] Material and Methods

[0097] Statement of ethics. Ethical and regulatory factors are considered within the INSPIRE- T cohort study. This study adheres to the principles outlined in the Declaration of Helsinki, which serves as the ethical framework for clinical research involving human subjects. Compliance with these principles is mandatory for all individuals involved in human research. The protocol for the INSPIRE-T cohort study was reviewed and approved by the French Ethical Committee based in Rennes (CPP Ouest V) in October 2019 and registered on the clinical trials registry website http: / / clinicaltrials.gov (ID NCT04224038). All participants signed and informed consent enabling data to be used for research purposes.

[0098] Clinical characteristics of individual donors in the skin fibroblasts cohort of 133 donors. Primary human fibroblasts were obtained from skin biopsies collected from 133 individual donors spanning ages 20 to 96 years in the INSPIRE-T cohort22. The INSPIRE-T cohort is a population study of 1000 individuals from Toulouse and surrounding areas (France), including participants aged 20 years and older, with varying levels of functional capacity (from robustness to frailty, and even dependency), followed over 10 years. The characteristics of the 133 selected donors are summarized in Table 1. The mean (standard deviation [SD]) age was 60.5 (19.7) years. Males had a higher body mass index (BMI) and IC score than females.

[0099] Skin biopsies. Skin biopsies from non-sun-exposed areas were obtained from 133 volunteers from the INSPIRE human translational cohort (INSPIRE-T cohort)22. Individuals were recruited according to their chronological age (20 to 96 years old), sex and frailty status (robust, pre-frail, frail) (data not shown). Frailty status was assessed with following criteria: unintentional weight loss, self-reported exhaustion, weakness (grip strength), slow walking speed, and low physical activity. Individuals with none, one or two and three or more characteristic were classified as robust, prefrail, and frail, respectively2. Only two individuals in this cohort were frail; both were grouped with the pre-frail group for statistical reasons. Intrinsic capacity score was measured as the mean score of the five domains (cognition, locomotion, psychology, vitality and sensory (vision and hearing)23(data not shown). Lu WH et al. identified several key variables for assessing the IC score: Cognition was measured using the 30-item Mini -Mental State Examination (MMSE), with scores ranging from 0 to 30 (higher scores indicate better cognition); Locomotion was evaluated through the Short Physical Performance Battery (SPPB), which includes walking, chair stands, and balance tests, summarized on a scale from 0 to 12 (higher scores are better); Psychological well-being was assessed using the nine-item Patient Health Questionnaire for depression (PHQ-9), where scores range from 0 to 27 (higher scores indicate greater depression severity); Vitality was determined by measuring grip strength in the dominant hand using a hydraulic dynamometer (Jamar; measured in kg); Vision was assessed with visual acuity using the WHO simple eye chart, which scores from 0 to 3 (higher scores reflect better vision); and Hearing was evaluated through the whisper test, scored from 0 to 2 (with higher scores indicating better hearing).

[0100] Human skin fibroblasts - Cell culture. Fibroblasts were obtained from 4 mm3skin biopsies, cultured in a-MEM medium (Life technologies) supplemented with 0.25 units / ml Amphotericin, 100 mg / ml Streptomycin, 100 units / ml Penicillin (ASP) and 20% Fetal Bovine Serum (FBS). Cells were detached by incubating at 37 °C for 5 min with trypsin / EDTA solution (Life technologies), numerated using an automated cell counter (Beckman Coulter) Vi-CELL XR and seeded at constant cell density (2000 cells / cm2) until passage 3. Cells were maintained in a-MEM medium (Life technologies) supplemented with 1% ASP, 1% L-glutamine and 5% FBS, at 37°C in a humidified incubator with 20% 02 and 5% CO2. Medium was changed every 2-3 days. All experiments were performed at passage 4.

[0101] Cell biology assays. Described in Figure 2

[0102] Gene Expression Analysis. Total RNA was isolated using ReliaPrep™ RNA Cell Miniprep System (Promega) according to manufacturer recommendations. Total mRNA was reverse-transcribed into cDNA using high-capacity cDNA reverse transcription kit (Life technologies). RT-qPCR was performed on a Fluidigm BioMarkHD instrument (Fluidigm Corporation, USA) as previously described24. cDNA pre-amplification step. 1.25 pL of cDNA were preamplified using the Preamp Master Mix kit (Fluidigm, cat.no. PN 100-5580) according to the manufacturer’s instructions: 1 pL of Preamp Master Mix was combined with 0,5 pL of Pooled Delta Gene assay mix (500nM) and 1.25 pL of cDNA in a 5 pL total volume reaction. Thermal cycling conditions were: 95°C for 2 min followed by 15 cycles of 95°C for 15 s, 60°C for 2 min.

[0103] Clean up reaction with Exonuclease I: After each preamplification reaction, samples were cleaned-up with exonuclease I (New England Biolabs cat.no PN-M0293S) treatment according to the manufacturer’s instructions. 2 pL of diluted Exo I at 4U / pL added to each 5- pL preamplification reaction. Thermal cycle the Exo I reaction using the following conditions: 37°C for 30 min, 80°C for 15 min. Then, samples were diluted 1 :20 by adding 93 pL nuclease- free water for a 100 pL total volume.

[0104] Real time qPCR using BiomarkTM HD system. PCR was performed following Gene Expression with the 192.24 IFC Using Delta Gene Assays protocol (PN 100-7222 Cl), using a 10X assays mix and a pre-sample mix prepared separately. The lOx assays mix was prepared by mixing 0,2 pL of 100 pM each Delta Gene™ primers (forward and reverse combined), 2 pL 2X Assay Loading Reagent (Fluidigm PN 100-7611) and 1,8 pL of IX DNA suspension buffer to a final volume of 4 pL (per reaction).

[0105] The pre-sample mix was prepared by mixing 2 pL of 2X SsoFast EvaGreen Supermix with low ROX™ (Bio-Rad PN 172-5211), 0.2 pL 192.24 Delta Gene Sample Reagent (Fluidigm PN 100-6653) and 1.8 pL pre-amplified and Exo I treated cDNA to a final volume of 4 pL. Then, 3 pL of lOx assays mix and of pre-sample mix are transferred into the 192.24 IFC, loaded into the BiomarkTM IFC controller RX and transferred to the BiomarkTM HD apparatus. Thermal cycling conditions were as follows: 50°C for 120 s, 95°C for 600 s followed by 40 cycles of 95 °C for 15 s, 60°C for 60 s.

[0106] Gene expression determination. The ACt was obtained by normalizing mean expression values of each gene to the geometric mean of the reference genes, ribosomal protein lateral stalk subunit P0 (RPLPO) and peptidylprolyl isomerase A (PPIA). Gene expression was calculated by the 2-ACT method or in fold increase of 2-ACT to control cells. These experiments were conducted on fibroblasts from 65 individuals from INSPIRE-T cohort. 3 technical replicates for each condition and donor.

[0107] Senescence induction with doxorubicin. Treated cells were seeded at 1 x 104cells / cm2in 24 well plates for immunofluorescence staining and in 6 well plates for C12FDG staining, and were incubated for 24h with 250nM doxorubicin. Then, cells were carefully washed with PBS before being cultured in standard medium. Control cells were seeded at 1 x 103cells / cm2to maintain their proliferation for long term culture. Medium was changed every 2-3 days for 10 days after treatment. 3 technical replicates were plated for each condition and donor. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0108] SA-p- al activity measurement by C12-FDG staining. 10 days after doxorubicin treatment, cells were treated with 100 nM Bafilomycin 1 (Invivogen tlrl-bafal) for 2 hours then incubated with 20 pM 5-Dodecanoylaminofluorescein Di-P-D-Galactopyranoside substrate (C12FDG, Abeam ab273642) in the dark for 1 hour at 37 °C. Cells were then washed with PBS and nuclei were stained with DAPI. C12FDG uptake was quantified by flow cytometry using a MACSQuant (Miltenyi) on FITC channel. Mean fluorescent intensity (MFI) were evaluated using Kaluza software. 3 technical replicates for each condition and donor.

[0109] Immunofluorescence. 10 days after doxorubicin treatment, cells were fixed using 4% paraformaldehyde (PF A) at RT for 20 min. Next, cells were permeabilized and blocked using solution (0.2% Triton X-100, 2% NHS) at RT for 20 min. Then, cells were labelled with mouse anti-human phospho-histone H2AX (Serl39) antibody (1 : 1000, Merk Millipore) for y-H2AX DNA damages foci and with rabbit anti-human pl6 antibody (1 :270, Abeam) overnight at 4°C. After washing, their respective secondary antibodies were incubated at RT for 2h: donkey antimouse A1488 secondary antibody (1 :400, ThermoFisher) and donkey anti-rabbit A1555 secondary antibody (1 :200, ThermoFisher). Finally, after repeated washing, nuclei were stained with DAPI at RT for 20min. Images were taken with the high content imaging system Operetta (Perkin Elmer). y-H2AX foci number per cell, pl 6 nuclear spots number per cell and nuclear area were calculated Harmony software (Perkin Elmer). 3 technical replicates for each condition and donor. Population Doubling Assay. During fibroblasts amplification, cells were seeded at 2000cells / cm2in T-175 cell culture flasks. At 90% of cell confluence, fibroblasts were harvested and numerated. Doubling times were calculated using the following formula: DT = ln2* t / (In Cl -In CO), where t is the culture duration, Cl is the number of cells at the end of the culture and CO is the number of seeded cells. Doubling times of fibroblasts at passage 2 were studied. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE- T cohort.

[0110] Colony Forming Unit (CFU) Assay. Fibroblasts were plated in 96 well plates by creating of a range of cells with serial half-dilutions where each point of the range is seeded in 12 technical replicates. The medium was changed every 2-3 days. The cultures were kept at 37 °C with 5% CO2 and at day 11 of growth, plates were fixed and stained with DAPI (1 : 10000, Sigma). Images were acquired using Operetta High Content Analysis system (Revvity) with lOx NA 0.4, 15 field of view were captured per well. Harmony analysis software (Revvity) was used to obtain automatically Colony-formation assay involved using Poisson distribution statistics by determining the number of wells with no clonogenic growth at day 11. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-Tcohort.

[0111] Cell migration assay. Fibroblasts migration was performed using the IncuCyte® S3 Live-Cell Analysis System (v20192.3.7219.27517-1, 2019B Rev2 GUI, Essenbioscience). Cells were seeded at 1500 cells / well density in a-MEM medium (Life technologies) supplemented with 1% ASP and 0.1% FBS in a 96-well plate (top). 200 pl of a-MEM medium (Life technologies) supplemented with 1% ASP and 10% FBS were added in wells of the reservoir plate (bottom). 3 technical replicates were plated for each condition and donor. Fibroblast migration across the membrane surface through the pores was automatically quantified for 24 h. The total count of fibroblast per well (bottom) normalized to the initial count (top) was calculated without (spontaneous migration) and with chemoattractant (cell migration under chemoattractant) via the Incucyte S3 software (Essenbioscience). These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0112] Myofibroblastic differentiation. Cells were seeded at 1.5 x 104cells / well in 24 well plates and were cultured in standard conditions for 96 h (time to reach cell confluence). Myofibroblastic differentiation was induced with 2 ng / ml TGF-pi (Miltenyi) for 10 days. Medium was changed every 2-3 days. RT-qPCR was performed for the smooth muscle actin (a-SMA), caldesmon CALD1 calponin (CNN1), collagen type la (COL1A1) matrix metalloproteinase 1 (MMP1), tissue inhibitor of metalloproteinase 1 (TIMP1') and Periostin gene expression. Untreated cells were analyzed when cells reached confluency. 3 technical replicates were plated for each condition and donor. These experiments were conducted on fibroblasts from 65 individuals from INSPIRE-T cohort.

[0113] Adipogenic differentiation. Cells were seeded at 1.25 x io4cells / well in 24 well plates and were cultured in standard conditions for 96 h (time to reach cell confluence). Adipogenic differentiation was induced with 1 pM dexamethasone, 60 pM indomethacine, 500 pM IB MX) (Sigma Aldrich) for 14 days. Medium was changed every 2-3 days. Control cells were seeded in standard medium at 1 x 103 cells / cm2 to maintain their proliferation for long term culture. 3 technical replicates were plated for each condition and donor. Fibroblasts were fixed, nuclei were marked with DAPI (1 : 10000, Sigma) and lipids droplets were marked with Bodipy 493 / 503 (1 :500). Images were acquired using Operetta High Content Analysis system (Revvity) with 20x Air / 0.45 NA, 99 field of view were captured per well. DAPI and Bodipy were excited with the 360-400nm and 460-490nm excitation filters respectively. Nuclei and cells were segmented with “Find nuclei” and “Find cytoplasm” building blocks. Bodipy+ / total cells were quantified using the Harmony Analysis Software (Revvity). These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0114] LPS and Poly IC stimulation. Dermal fibroblasts (control and treated conditions) were seeded at 5 x io4cells / cm2in 24 well plates and treated by LPS (1 pg / ml) or Poly IC (lOOpg / ml) for 1 hour. Untreated fibroblasts were used as control condition. Then, cells were carefully washed 4 times with PBS before being maintain in standard medium for 48h. 3 technical replicates were plated for each condition and donor. Conditioned cell culture supernatants were collected and used for cytokine and chemokine profiling by ELLA method. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0115] Simple Plex™ assays on Ella™. Supernatants were stored at -80°C. IL-6, IL- 10, IL1- P and TGF-P concentrations were measured after LPS stimulation and the IFN-P concentration was measured after Poly IC stimulation. All of these cytokines have been quantified in control supernatants. Periostin concentration was also measured in control supernatant. Proteins were quantified by disposable microfluidic single and multianalyte SimplePlex cartridge using the fully automated immunoassay platform, Ella (ProteinSimple / Bio-techne, San Jose, CA). The supernatant samples were thawed on ice and diluted in sample diluent (SD 13) if necessary and loaded into cartridges with relevant high and low control concentrates. Five panels were used: IL-10 and IL1-P as pure; TGF-P as pure; IFN-P at a dilution of 1 :2, IL-6 at a dilution of 1 :4 and Periostin at a dilution of 1 :2. Each protein channel contains 3 analyte-specific glass nanoreactors, which allows for each supernatant sample to be run in triplicates for target protein samples (3 technical replicates). Cartridges include a built-in lot-specific standard curve for defined supernatant protein. All steps in the procedure were run automatically by the instrument with no user activity. The obtained data were displayed as pg / mL and automatically calculated by the internal instrument software. Results were normalized to cell number measured during supernatant collection.

[0116] Metabolic flux analysis. Seahorse XFe96 cell culture microplates were coated overnight with poly-D-lysine (0.1 mg / ml). The following day, the wells were thoroughly washed with PBS and allowed to dry for 1 hour. Fibroblasts were seeded at 20,000 cells per well in complete a-MEM medium (Life technologies) and incubated overnight at 37 °C in 5% CO2. 6 technical replicates were plated for each donor. Sensor cartridges were hydrated overnight in Seahorse XF calibrant at 37 °C without CO2 supplementation. On the day of the assay, fibroblasts were carefully washed with PBS, placed in XF DMEM supplemented with glucose (10 mM), glutamine (2 mM) and pyruvate (1 mM) then incubated for 1 hour at 37 °C without CO2 supplementation. After Seahorse XFe96 Analyzer calibration, the Oxygen Consumption Rate (OCR) was measured at the basal level then after the sequential injection of oligomycin (2.5 pM), FCCP (6 pM) and rotenone (2.5 pM) + antimycin A (2.5 pM). 3 cycles were performed at each step, consisting of 3 min of mix followed by 3 min of measurement. At the end of the experiment, the nuclei were stained with DAPI and the number of nuclei per well was determined using the Operetta High Content Imaging System (Perkin Elmer) and used to normalize the raw OCR data. This protocol provides information on basal respiration (basal OCR), uncoupled respiration (as a percentage of basal respiration), maximal respiration (maximal OCR) and extracellular acidification rate (basal ECAR). Cell density, plate coating as well as oligomycin and FCCP concentrations were determined by a dedicated pilot experiment. These experiments were conducted on fibroblasts from 133 individuals from INSPIRE-T cohort.

[0117] Statistical Analysis. Statistical analysis was performed using both Python and Jupyter notebook, and GraphPad Prism version 10 for Windows (GraphPad Software, USA). The python package pandas was used for data manipulation. Packages matplotlib and seaborn were used for plotting graphs, statsmodels module was used for statistics. Associations between ef each cell parameter with chronological age were assessed using linear regression with the cell parameter as the outcome. Pearson correlation coefficients were also calculated. Associations with intrinsic capacity (IC) were evaluated using linear regression with IC as the outcome; these models were adjusted for age and sex. Associations with frailty status were evaluated using logistic regression with frail / pre-frail versus non-frail as the outcome, adjusting for age and sex. Association between IC centile and cell parameters were determined using one-way ANOVA test.

[0118] Depending on their distribution and characteristics, variables were transformed using either a natural logarithm (In), a shifted logarithm (ln(x + 1)) to account for zero values, or a reciprocal transformation (1 / x), to satisfy the assumptions of homoscedasticity and normality of residuals, as assessed by the Breusch-Pagan test and residual plots, before performing linear regression analyses. For associations with age and frailty status, all variables were log- transformed, except for extracellular IL-ip, IL-ip (LPS), IL-10, IL-10 (LPS), TGF-P, TGF-P (LPS), INF-P and INF-P (Poly I :C), which were transformed using a shifted logarithm [ln(x + 1)]. For associations with IC, all variables were log-transformed, except for P-galactosidase, CNN1 and MMP1 mRNA fold increase (TGF-P), and extracellular IFN-P and TGF-P (raw values); extracellular IL-ip, IL-ip (LPS), IL-10, IL-10 (LPS), TGF-P (LPS) and IFN-P (Poly I:C), which were transformed using a shifted logarithm [ln(x + 1)]; and % differentiated adipocytes, intensity of adipose differentiation, OCR-Basal and maximal respiration, which were transformed using a reciprocal transformation (1 / x).

[0119] While no formal adjustment for multiple comparisons was used, we carefully considered the risk of false positives in the analysis and presentation. From an ensemble of results, the null expectation is 5% false positives at alpha = 0.05. We would not interpret results as meaningful unless the number of positives far exceeds this. By presenting both positive and negative findings and considering them as an ensemble, we avoid the risk of cherry picking a few false positive results. Some positive results may nonetheless be false positives, but it is impossible to distinguish precisely which ones, and we ensure that our broad conclusions do not hinge on the result of any single test. The package sklearn decomposition module was used respectively for dimensionality reduction analysis. Using GraphPad Prism, Mann-Whitney test for two-independent samples was used to estimate the difference between two groups.

[0120] Mahalanobis distance, a measure of homeostatic dysregulation25, calculates how unusual a biomarker profile is relative to a population average. It is given by the equation: where v is a vector of biological parameter values for a given individual at a given time, p is the vector of mean values for those same parameters, and S is the correlation matrix among those parameters. Both x and S are calculated from a reference population - often the entire study population - and it is with respect to the multivariate mean of this population that distance is measured. It has previously been widely applied epidemiologically and in various species using standard clinical blood biomarkers383940. High DM indicates high deviation from the mean and is broadly associated with worse health outcomes and adverse profiles on determinants of health38 39 4041 42 43 44; it has also been shown to mediate relationships between determinants of health and health outcomes45 46. This is, to our knowledge, the first application to cell culture variables. DM was calculated in R v4.3.1 using observations with complete data on 31 features (all except gene expression markers). Features with right-skewed distributions were log- transformed and all features were scaled to have a mean of 0 and a standard deviation of 1 prior to analysis. For variables with both a basal level and a post-challenge level, the basal level and the residuals of a linear regression of the post-challenge level on the basal level were included. The Mahalanobis distance for each individual was log transformed and standardized by dividing by the sample standard deviation.

[0121] Results

[0122] Logistic regressions were conducted for each of the cellular markers between fibroblast characteristics and pre-frailty / frailty status within the study population (data not shown). Among all variables, the senescence and inflammation markers indicated no significant correlation with frailty status, while basal and maximal mitochondrial respiration, CD36 mRNA expression, percentage of CFU-f and extracellular Periostin were significantly decreased in fibroblasts from pre-frail / frail donors compared to the robust group, independently of age and sex (Figure 8 A, B, C, D, E). Next, we investigated whether IC - a measure reflecting an individual's combined physical and mental abilities - was associated with age-related markers in our study23(data not shown). Only extracellular Periostin was significantly associated with IC score, independently of age and sex as revealed by linear regression analysis, (Figure 8F). Furthermore, by using age- and sex-specific cut-offs for IC, referenced against centile curves, that stratified participants from the INSPIRE-T cohort into percentile categories ranging from <10th to >90th 23, we observed a positive association between centile categories and extracellular Periostin levels (Figure 8G). The concentration of extracellular Periostin was significantly lower in individuals with low IC, classified within the [0,25] percentile range, compared to those in the [76,90] percentile categories. In summary, our findings reveal that extracellular Periostin and basal mitochondrial respiration are key markers associated with frailty and intrinsic capacity (IC), independent of chronological age and sex. Extracellular Periostin, in particular, emerges as a robust indicator of functional health, correlating strongly with IC scores and centile categories.

[0123] TABLES

[0124] Table 1. General characteristics of human skin fibroblasts used in this study from participants of the INSPIRE Human Translational Research Cohort. Categorical variables were summarized by numbers (percentages) and tested using Fisher’s exact test, while continuous variables were presented as mean (standard deviation) and tested using the Mann- Whitney U test. Education data were missing for one participant (total sample size, n = 132). BMI, body mass index; IC, intrinsic capacity. REFERENCES:

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Claims

CLAIMS:

1. An in vitro method for predicting intrinsic capacity decline in a subject comprising the step of determining the level of extracellular periostin in a sample comprising fibroblasts obtained from said subject.

2. The in vitro method for predicting intrinsic capacity decline according to claim 1, comprising the steps of: i) determining the level of extracellular periostin in a sample comprising fibroblasts obtained from said subject; ii) comparing the level determined at step i) with a predetermined reference value and iii) concluding that the subject is at risk of suffering from intrinsic capacity decline when the level of extracellular periostin determined at step i) is lower than the predetermined reference value.

3. The in vitro method for predicting intrinsic capacity decline according to claim 1, comprising the steps of: i) determining the level of extracellular periostin in a first sample comprising fibroblasts obtained from said subject; ii) comparing the level determined at step i) with the level determined in a second sample comprising fibroblasts obtained from said subject; and iii) concluding that the subject is at risk of suffering from intrinsic capacity decline when the level of extracellular periostin obtained at step ii) is lower as compared to the level determined at step i).

4. An in vitro method for predicting frailty in a subject comprising the step of determining the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration in a sample comprising fibroblasts obtained from said subject.

5. The in vitro method for predicting frailty according to claim 4, comprising the steps of:i) determining the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration in a sample comprising fibroblasts obtained from said subject; ii) comparing the level determined at step i) with a predetermined reference value and iii) concluding that the subject is at risk of suffering from frailty when the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration determined at step i) is lower than the predetermined reference value.

6. The in vitro method for predicting frailty according to claim 4, comprising the steps of: i) determining the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration in a first sample comprising fibroblasts obtained from said subject; ii) comparing the level determined at step i) with the level determined in a second sample comprising fibroblasts obtained from said subject; and iii) concluding that the subject is at risk of suffering from frailty when the level of extracellular periostin, CD36 mRNA, percentage of CFU-f, maximal mitochondrial respiration and / or basal mitochondrial respiration obtained at step ii) is lower as compared to the level determined at step i).

7. The in vitro method according to any of claims 1 to 6, wherein the sample is a skin sample.

8. An in vitro method for monitoring ageing of a synthetic tissue comprising fibroblasts comprising the step of determining the level of extracellular periostin.

9. The in vitro method for monitoring ageing of a synthetic tissue according to claim 8, the method comprising the steps of : i) determining the level of extracellular periostin in a sample obtained from said synthetic tissue; ii) comparing the level determined at step i) with a predetermined reference value and iii) concluding that the synthetic tissue is ageing when the level of extracellular periostin determined at step i) is lower than the predetermined reference value.

10. The in vitro method for monitoring ageing of a synthetic tissue according to claim 8, the method comprising the steps of : i) determining the level of extracellular periostin in a sample obtained from said synthetic tissue; ii) determining the level of extracellular periostin in a second sample obtained from said synthetic tissue; iii) comparing the level determined at step i) with the level determined at step ii); and iv) concluding that the synthetic tissue is ageing when the level of extracellular periostin obtained at step ii) is lower as compared to the level determined at step i).

11. The in vitro method for monitoring ageing of a synthetic tissue according to any of claims 8 to 10, comprising the steps of determining the level of extracellular periostin and at least one selected from the group comprising extracellular IL-6, ECAR, cell doubling time, OCR-uncoupled respiration, yH2AX, GLUT-1 mRNA, SOD1 mRNA, GPxl mRNA, TEMPI mRNA, hexokinase 2 mRNA, extracellular IL-6 in LPS- challenging medium, extracellular IL-ip in LPS-challenging medium, extracellular IFN- P in poly:IC-challenging medium, cell size in doxorubicin-challenging medium and / or P-galactosidase in doxorubicin-challenging medium.

12. The in vitro method according to any of claims 8 to 11, wherein the synthetic tissue is a skin synthetic tissue.

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