FIELD OF THE INVENTION:

The present invention is in the field of medicine.

BACKGROUND OF THE INVENTION:

Exercise improves metabolic health and prevents the complications of obesity and type 2 diabetes (1, 2). This is partly due to the release of secreted factors by skeletal muscle, i.e. myokines, which can virtually target all organs remotely (3). Over the last decade, hundreds of proteins secreted by skeletal muscle have been identified as reviewed in details elsewhere (4- 7). However, very few myokines have been shown to target white adipose tissue particularly in humans. In a previous clinical study, we observed a remarkably enhanced in situ and systemic lipolytic response in lean healthy endurance-trained subjects performing a high intensity exercise the day after an exhaustive glycogen-depleting exercise compared to rest (8). This greater lipolytic response could not be explained by significant changes in classically known lipolytic stimuli such as increased catecholamines, atrial natriuretic peptide, growth hormone, cortisol, interleukin 6 or a decrease in circulating insulin during exercise. We therefore hypothesized that skeletal muscle contraction in the context of acute high intensity exercise and chronic moderate exercise may produce a cellular stress signal capable to increase adipose tissue lipolysis to sustain fuel availability and delay muscle glycogen depletion.

Recently, Growth and Differentiation Factor 15 (GDF15) emerged as a biomarker of cellular stress that can be produced by a number of organs such as lung, kidney and liver (9- 11). GDF15, also known as macrophage inhibitory cytokine-1 (MIC-1), is a stress-induced cytokine and an ancient member of the transforming growth factor beta superfamily. High levels of circulating GDF15 have been found in various diseases states such as cancer, heart failure and mitochondrial diseases (12, 13). Very recent studies demonstrate a major role of GDF15 in appetite suppression through non canonical brain neuronal networks in the brainstem such as the area postrema and the nucleus tractus solitaries (14-17). Injection of recombinant GDF15 protein in mice fed a high fat diet (HFD) induces robust weight loss (16). Similarly GDF 15-overexpressing mice are resistant to HFD-induced obesity and metabolic disturbances (18). These effects appear largely mediated by food intake suppression through the GDF 15 cognate receptor GFRAL, GDNF receptor alpha-like, which heterodimerizes with a co-receptor called RET (15, 17). RET encodes a tyrosine kinase receptor for members of the glial cell line- WO 2021/018899 PCT/EP2020/071287 derived neurotrophic factor (GDNF) family (15). In mice, GFRAL expression appears strictly confined to the area postrema and the nucleus of the tractus solitary. It is suggested that GDF15 behaves as a metabolic stress signal in response to nutritional stress to trigger conditioned taste aversion (11).

The inventors herein describe GDF15 as a novel exerkine of a peripheral crosstalk between skeletal muscle and adipose tissue. They show that conditioned media from exercised human myotubes activate lipolysis in human adipocytes in vitro. Through proteomic screening of the conditioned media, they next identified GDF15 as a novel exercise-regulated myokine that is rapidly released upon muscle contraction. Neutralization of GDF15 in conditioned media abolishes lipolysis while treatment of adipose tissue explants with recombinant GDF15 promotes lipolysis. Collectively, they herein provide the first evidence that GDF15 is produced by skeletal muscle upon contraction and that it is able to promote lipolysis in human adipose

SUMMARY OF THE INVENTION:

As defined by the claims, the present invention relates to use of GDF15 as a marker for exercise management.

DETAILED DESCRIPTION OF THE INVENTION:

The inventors hypothesized that skeletal muscle contraction produces a cellular stress signal triggering adipose tissue lipolysis to sustain fuel availability during exercise. The present study aimed at identifying novel exercise-regulated myokines, aka exerkines, able to promote lipolysis. Human primary myotubes from lean healthy volunteers were submitted to electrical pulse stimulation (EPS) to mimic either acute intense or chronic moderate exercise. Conditioned media (CM) experiments with human adipocytes were performed. Conditioned media and human plasma samples were analyzed using unbiased proteomic and/or ELISA. Real-time qPCR was performed in cultured myotubes and muscle biopsy samples. CM from both acute intense and chronic moderate exercise increased basal lipolysis in human adipocytes (1.3 to 8 fold, p<0.001). Growth and Differentiation Factor 15 (GDF15) gene expression and secretion increased rapidly upon skeletal muscle contraction. GDF15 protein was up-regulated in CM from both acute and chronic exercise-stimulated myotubes. The inventors further show that physiological concentrations of recombinant GDF15 protein increase lipolysis in human adipose tissue, while blocking GDF15 with a neutralizing antibody abrogates EPS CM- mediated lipolysis. The inventors herein provide the first evidence that GDF15 is a novel WO 2021/018899 PCT/EP2020/071287 exerkine produced by skeletal muscle contraction and able to target human adipose tissue to promote lipolysis.

Thus the first object of the present invention relates to a method for selecting an appropriate exercise regimen for inducing lipolysis in a subject comprising determining the level of GDF15 in a sample obtained from the subject and classifying the subject into an exercise category selected from the group consisting of normal (moderate) exercise; and vigorous (intensive) exercise.

A further object of the present invention relates to a method of determining whether a subject achieves a response to an exercise regimen for inducing lipolysis comprising determining the level of GFD15 in a sample obtained from the subject wherein said level indicates whether the subject achieves or does not achieve a response to the exercise regimen.

As used herein, the term“lipolysis” has its general meaning in the art and refers to the hydrolysis of lipids. More specifically, the term is used to encompass the hydrolysis of intracellular triglycerides and the release of free fatty acids and glycerol from cells. Lipolysis usually takes place intracellularly in cells containing a lipid droplet. Lipolysis can be measured by various ways to those skilled in the art, such as the assessment of free fatty acids release and of glycerol release, by bioluminescence, etc.

As used herein, the term“GDF15” has its general meaning in the art and refers to the growth differentiation factor 15. An exemplary amino acid sequence for GDF15 is represented by the amino acid sequence as set forth in SEQ ID NO: 1.

SEQ ID NO: l>sp I Q99988 I GDF15 HUMAN Growth/differentiation factor 15 OS=Homo sapiens OX=9606 GN=GDF15 PE=1 SV=3

MPGQELRTVNGSQMLLVLLVLSWLPHGGALSLAEASRASFPGPSELHSEDSRFRELRKRY

EDLLTRLRANQSWEDSNTDLVPAPAVRILTPEVRLGSGGHLHLRISRAALPEGLPEA SRL

HRALFRLSPTASRSWDVTRPLRRQLSLARPQAPALHLRLSPPPSQSDQLLAESSSAR PQL

ELHLRPQAARGRRRARARNGDHCPLGPGRCCRLHTVRASLEDLGWADWVLSPREVQV TMC

IGACPSQFRAANMHAQIKTSLHRLKPDTVPAPCCVPASYNPMVLIQKTDTGVSLQTY DDL

LAKDCHCI

In some embodiments, the subject suffers from obesity. The term "obesity" refers to a condition characterized by an excess of body fat. The operational definition of obesity is based on the Body Mass Index (BMI), which is calculated as body weight per height in meter squared (kg/m ² ). Obesity refers to a condition whereby an otherwise healthy subject has a BMI greater than or equal to 30 kg/m ² , or a condition whereby a subject with at least one co-morbidity has a BMI greater than or equal to 27 kg/m ² . An "obese subject" is an otherwise healthy subject with a BMI greater than or equal to 30 kg/m ² or a subject with at least one co-morbidity with a BMI greater than or equal 27 kg/m ² . A "subject at risk of obesity" is an otherwise healthy subject WO 2021/018899 PCT/EP2020/071287 with a BMI of 25 kg/m ² to less than 30 kg/m ² or a subject with at least one co-morbidity with a BMI of 25 kg/m ² to less than 27 kg/m ² . The increased risks associated with obesity may occur at a lower BMI in people of Asian descent. In Asian and Asian-Pacific countries, including Japan, "obesity" refers to a condition whereby a subject has a BMI greater than or equal to 25 kg/m ² . An "obese subject" in these countries refers to a subject with at least one obesity-induced or obesity-related co-morbidity that requires weight reduction or that would be improved by weight reduction, with a BMI greater than or equal to 25 kg/m ² . In these countries, a "subject at risk of obesity" is a person with a BMI of greater than 23 kg/m2 to less than 25 kg/m ² .

In some embodiments, the subject suffers from insulin resistance. As used herein, the term“insulin resistance” has its common meaning in the art. Insulin resistance is a physiological condition where the natural hormone insulin becomes less effective at lowering blood sugars. The resulting increase in blood glucose may raise levels outside the normal range and cause adverse health effects such as metabolic syndrome, dyslipidemia and subsequently type 2 diabetes mellitus. The method of the present invention is thus particularly suitable for the treatment of type 2 diabetes. As used herein, the term "type 2 diabetes" or“non-insulin dependent diabetes mellitus (NIDDM)” has its general meaning in the art. Type 2 diabetes often occurs when levels of insulin are normal or even elevated and appears to result from the inability of tissues to respond appropriately to insulin. Most of the type 2 diabetics are obese.

In some embodiments, the subject is an elderly subject. As used herein, the term "elderly subject" refers to an adult patient sixty-five years of age or older.

In some embodiments, the sample is a blood sample. As used herein the term“blood sample” means a whole blood, serum, or plasma sample obtained from the patient.

Methods for determining the level of GDF15 in the sample are well known in the art and typically involves an immunoassay. In some embodiments, an ELISA (enzyme-linked immunosorbent assay) method is used, wherein the wells of a microtiter plate are coated with a set of antibodies which recognize GDF15. The sample is then added to the coated wells. After a period of incubation sufficient to allow the formation of antibody-antigen complexes, the plate(s) can be washed to remove unbound moieties and a detectably labelled secondary binding molecule is added. The secondary binding molecule is allowed to react with any captured sample marker protein, the plate washed and the presence of the secondary binding molecule detected using methods well known in the art.

In some embodiments, the level of GDF15 is compared to a predetermined reference value. Typically, the predetermined reference value is a threshold value or a cut-off value. Typically, a "threshold value" or "cut-off value" can be determined experimentally, empirically, WO 2021/018899 PCT/EP2020/071287 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 expression levels in properly banked historical patient samples may be used in establishing the predetermined reference value. 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 quantifying the expression level in a group of reference, one can use algorithmic analysis for the statistic treatment of the determined levels 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. S AS, DESIGNROC.FOR, MULTIREADER POWER S AS, CREATE- ROC.SAS, GB STAT VIO.O (Dynamic Microsystems, Inc. Silver Spring, Md., USA), etc.

In some embodiments, the predetermined reference value was established in a population of patients who did not achieve a response to a particular exercise regimen. Accordingly when the level of GDF15 is higher than the predetermined reference value, it is concluded that the patient respond to the exercise regimen. On contrary, when the level of WO 2021/018899 PCT/EP2020/071287

GDF15 is lower than the predetermined reference value, then is it concluded that the patient does not achieve a response to the exercise regimen.

Exercise categories are generally classified on the basis of how responsive a subject is to exercise given the level of GDF15. For example, a subject may be responsive to light exercise, moderate exercise, heavy exercise, or very heavy exercise.

According to the present invention, light exercise generally refers to a subject that exercises (engages in an active workout or sports) 1-3 days per week. Moderate exercise generally refers to a subject that exercises (engages in an active workout or sports) 3-5 days per week. Heavy exercise generally refers to a subject that exercises (engages in an active workout or sports) 6-7 days per week. Very heavy exercise generally refers to a subject that exercises (engages in an active workout or sports) on average of more than once a day (e.g., two times per day). More accurately, exercise may be expressed in terms of a percentage over BMR. For example, the multipliers of the Harris-Benedict or Katch-McArdle formulas may be used as a basis to define an exercise. Accordingly, light exercise refers to a recommended exercise designed to increase a subject's TDEE to about 125% of BMR (i.e., about a 25% increase) to less than about 140% (e.g., about 128%, 130%, 133%, 135%, 137.5%, etc) of BMR. Moderate exercise refers to a recommended exercise designed to increase a subject's TDEE to about 140% of BMR to less than about 160% (e.g., about 142%, 145%, 150%, 155%, 158%, etc) of BMR. Heavy exercise refers to a recommended exercise designed to increase a subject's TDEE to about 160% of BMR to less than about 180% (e.g., about 162%, 165%, 170%, 172.5%, 175%, 178%, etc) of BMR. Very heavy or extreme exercise refers to a recommended exercise designed to increase a subject's TDEE to about 180% of BMR to more than about 210% (e.g., about 182%, 185%, 190%, 195%, 200%, etc) of BMR. Alternatively, according to some embodiments, a "normal exercise" routine comprises: 2.5 hours (150 minutes) of moderate- intensity activity per week (Moderate-intensity activities are defined as 3.0 to 5.9 METs), a "light exercise" routine comprises: less than 2.5 hours of moderate-intensity activity per week, and a "vigorous exercise" routine comprises: greater than 13 METs per week of vigorous intensity activities (Vigorous intensity activities are defined as 6 METs or greater). 1 MET is equal to 1 calorie/kg body mass/hour. The total kcal expended by a subject = MET value of activity x body weight in kg x time in hours.

Subjects with a level of GDF15 indicative that he is responsive to exercise are able to effectively induce lipolysis in response to exercise (i.e. physical activity). They tend to respond to exercise with the perspective of weight loss and are more likely to maintain weight loss. Subjects fall into this category if they are responsive to exercise. WO 2021/018899 PCT/EP2020/071287

In some embodiments, the method of the present invention further comprises a step consisting of calculating a score, representing an estimation of the subject’s response to the exercise regimen. Typically, the score is based on the level of GDF15 and may typically include another factor. Typically, other risk factors may include additional features such as age, gender, obesity, diabetes mellitus, smoking, LDLc levels, and body mass index, blood pressure, heart rate, hydration level, oxygen saturation... Based the above input features obtained from the subject, an operator can calculate a numerical function of the above list of inputs by applying an algorithm. For instance this numerical function may return a number, i.e. score (R), for instance between zero and one, where zero is the lowest possible risk indication and one is the highest. This numerical output may also be compared to a threshold (T) value between zero and one. If the risk score exceeds the threshold T, it is meant than the subject achieves as response to the exercise regimen and if the risk score is under the threshold T, it is meant than the subject does not achieve a response to the exercise regimen.

In some embodiments, the methods of the invention thus comprises the use of an algorithm. In some embodiments, the algorithm is a classification algorithm typically selected from Multivariate Regression Analysis, Linear Discriminant Analysis (LDA), Topological Data Analysis (TDA), Neural Networks, Support Vector Machine (SVM) algorithm and Random Forests algorithm (RF). As used herein, the term "classification algorithm" has its general meaning in the art and refers to classification and regression tree methods and multivariate classification well known in the art such as described in US 8, 126,690; WO2008/156617. As used herein, the term“support vector machine (SVM)” is a universal learning machine useful for pattern recognition, whose decision surface is parameterized by a set of support vectors and a set of corresponding weights, refers to a method of not separately processing, but simultaneously processing a plurality of variables. Thus, the support vector machine is useful as a statistical tool for classification. The support vector machine non-linearly maps its n- dimensional input space into a high dimensional feature space, and presents an optimal interface (optimal parting plane) between features. The support vector machine comprises two phases: a training phase and a testing phase. In the training phase, support vectors are produced, while estimation is performed according to a specific rule in the testing phase. In general, SVMs provide a model for use in classifying each of n subjects to two or more disease categories based on one k-dimensional vector (called a k-tuple) of biomarker measurements per subject. An SVM first transforms the k-tuples using a kernel function into a space of equal or higher dimension. The kernel function projects the data into a space where the categories can be better separated using hyperplanes than would be possible in the original data space. To determine the WO 2021/018899 PCT/EP2020/071287 hyperplanes with which to discriminate between categories, a set of support vectors, which lie closest to the boundary between the disease categories, may be chosen. A hyperplane is then selected by known SVM techniques such that the distance between the support vectors and the hyperplane is maximal within the bounds of a cost function that penalizes incorrect predictions. This hyperplane is the one which optimally separates the data in terms of prediction (Vapnik, 1998 Statistical Learning Theory. New York: Wiley). Any new observation is then classified as belonging to any one of the categories of interest, based where the observation lies in relation to the hyperplane. When more than two categories are considered, the process is carried out pairwise for all of the categories and those results combined to create a rule to discriminate between all the categories. As used herein, the term "Random Forests algorithm" or "RF" has its general meaning in the art and refers to classification algorithm such as described in US 8, 126,690; WO2008/156617. Random Forest is a decision-tree-based classifier that is constructed using an algorithm originally developed by Leo Breiman (Breiman L, "Random forests," Machine Learning 2001, 45:5-32). The classifier uses a large number of individual decision trees and decides the class by choosing the mode of the classes as determined by the subject trees. The subject trees are constructed using the following algorithm: (1) Assume that the number of cases in the training set is N, and that the number of variables in the classifier is M; (2) Select the number of input variables that will be used to determine the decision at a node of the tree; this number, m should be much less than M; (3) Choose a training set by choosing N samples from the training set with replacement; (4) For each node of the tree randomly select m of the M variables on which to base the decision at that node; (5) Calculate the best split based on these m variables in the training set. In some embodiments, the score is generated by a computer program.

In some embodiments, the method of the present invention thus comprises a) determining the level of GDF15 in the sample obtained from the subject; b) implementing an algorithm on data comprising the level of GDF15 so as to obtain an algorithm output; c) determining the probability that the subject achieves a response to the exercise regimen.

In some embodiments, the level of GDF15 and optionally the implementation of the score as herein disclosed may be performed by a system comprising at least one biosensor for determining the level of GDF15.

In some embodiments, the level of GDF15 is dynamically determined by at least one biosensor that is included in a measuring device. As used herein, the term“biosensor” has its general meaning in the art and refers to a sensor which converts an interaction between a target and a recognition molecule into a signal such as an electric signal, so as to measure or detect a WO 2021/018899 PCT/EP2020/071287 target. The conventional biosensor is comprised of a receptor site for recognizing a chemical substance (e.g. GDF15) as a detection target and a transducer site for converting a physical change or chemical change generated at the site into an electric signal. In a living body, there exist substances having an affinity with each other, such as enzyme/substrate, enzyme/coenzyme, antigen/antibody, aptamer/ligand, or hormone/receptor. The biosensor operates on the principle that a substance having an affinity with a receiving molecule (e.g. GDF15), as described above, is immobilized on a substrate to be used as a molecule-recognizing substance, so that the corresponding substance can be selectively measured. The term “recognition molecules” as used herein refers to a molecule that is capable of specifically recognize and bind to a biomarker. Examples of recognition molecule-target pairs include receptor-ligand, antigen-antibody, enzyme-substrate, sugar-lectin. In addition, biomimetic molecules such as a synthetic receptor that can recognize a biomarker. Synthetic receptors are discussed in more details in U.S. Pat. Nos. 7,067,326, and 6,797,522 which are incorporated herein by reference in its entirety. Aptamer may also be used as a recognition molecule. According to the mechanism of biomarker detection, there are five types of transducers that may be used in biosensors of the present invention: optical (colorimetric, fluorescent, luminescent, and interferometric) transducers, mass-based (piezoelectric and acoustic wave) transducers, magnetic field based transducers, electrochemical (amperometric, potentiometric and conductometric) transducers, and calorimetric transducers.

In some embodiments, the measuring device is in frequent contact with a sample from the subject. In some embodiments, the system of the present invention comprises an apparatus attached to a human body, such as an armband, wristband, waistband, a headband, a patch, socks, boots, shoes, glasses, a hairband, a headset, an earplug, a watch, a necklace, and a finger- ring. The measuring device is located in the apparatus and is configured for contact with a sample such as blood and/or sweat on the skin of the subject for measuring the level of GDF15.

In some embodiments, the system may comprise additional measuring devices for measuring another parameter of interest. Typically the system comprises additional devices suitable for measuring a physiological phenotype. The physiological phenotype may include physiological parameters such as body temperature, pulse rate, blood pressure, respiratory rate, hydration status, electromuscular activity and the like.

In some embodiments, the system includes one or more processors and a non-transitory memory including instructions that, when executed by the one or more processors, causes the one or more processors to perform a set of steps. In some embodiments, the system comprises an application that will implement the score as described herein. WO 2021/018899 PCT/EP2020/071287

In some embodiments, the system includes an input/output module, an analysis module and a report generation module. The input/output module is configured to receive dynamically the level of GDF15 optionally in combinations with additional parameters optionally through the associated communication device. The analysis module is configured to analyze the different parameters. The report generation module is configured to generate the profile the subject (e.g. response or no response to the exercise regimen) on an analysis of the different parameters including the level of GDF15. In some embodiments, the system includes a determination module to determine optimal performance. In some embodiments, the system includes a sharing module to share one or more pre-formatted messages with one or more stakeholders based on comparison of the generated profile and real time performance of the subject. In some embodiments, the system include providing recommendations to the subject for delivering an optimal performance. In some embodiments, the system include enabling transmission of one more recommendation messages by one or more stake holders based on determined optimal performance and comparison of generated profile and real time performance of the subject.

In some embodiments, the system comprises a communication device. Examples of communication devices include but may not be limited to mobile phones, tablets, desktop computers and the like. Various mediums can be used for connectivity including internet, intranet, Bluetooth, Wi-Fi and the like. In addition, the communication device is associated with the application. In some embodiments the communication device is connected with a server. The measurements of one or more parameters measured by the measuring devices may be indeed transmitted wirelessly to a handheld device comprising a microprocessor. The handheld device may be a smartphone, a tablet device, a cell phone, a mobile internet device, a netbook, a notebook, a personal digital assistant, an internet phone, a holographic device, a holographic phone, a cable internet device, a satellite internet device, an internet television, a DSL internet device and a remote control.

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.

FIGURES:

Figure 1. Acute intense and chronic moderate exercise model validation in human myotubes WO 2021/018899 PCT/EP2020/071287

(A-D) Acute intense exercise model, EPS3h: (A) total glycogen content, (B) lactate secretion, (C) glucose oxidation rate, and (D) palmitate oxidation rate in five days cultured human myotubes submitted to 3h EPS to mimic an acute high intensity exercise in vitro. Data are expressed as mean ± SEM (n=8). *p < 0.05, **p < 0.01, ***p < 0.001 compared to control by two-tailed unpaired Student t-test.

(E-H) Chronic moderate exercise model, EPS24h: (E) total glycogen content, (F) basal glycogen synthesis rate, (G) glucose oxidation rate, and (H) palmitate oxidation rate in five days cultured human myotubes submitted to 24h EPS to mimic moderate chronic exercise training in vitro. Data are expressed as mean ± SEM (n=8). *p < 0.05 compared to control by two-tailed unpaired Student t-test.

(I-K) Conditioned media experiments between human myotubes and human adipocytes: (I) experimental design, (J) conditioned media of EPS3h-stimulated myotubes, and (K) conditioned media of EPS24h-stimulated myotubes were applied on differentiated hMADS adipocytes for 24h to measure glycerol output, a surrogate of lipolysis. Data are expressed as mean ± SEM (n= 16-20). ***p < 0.01 compared to control by two-tailed unpaired Student t-test.

Figure 2. Identification of GDF15 as a novel exercise-regulated myokine

(A-C) Proteomic screen of conditioned media from EPS3h-stimulated myotubes: (A) Volcano plot of the unbiased proteomic screen reveal GDF15 as a significantly up-regulated protein in conditioned media, (B) quantification of GDF15 protein in media from the protein screen, (C) quantification of GDF15 protein secretion by ELISA in five days cultured human myotubes submitted to 3h EPS to mimic an acute intense exercise in vitro. Data are expressed as mean ± SEM (n=16). *p < 0.05, **p < 0.01 compared to control by two-tailed paired Student t-test.

(D-F) Proteomic screen of conditioned media from EPS24h-stimulated myotubes: (D) Volcano plot of the unbiased proteomic screen reveal GDF15 as a significantly up-regulated protein in conditioned media, (E) quantification of GDF15 protein in media from the protein screen, (F) quantification of GDF15 protein secretion by ELISA in five days cultured human myotubes submitted to 24h EPS to mimic a moderate chronic exercise training in vitro. Data are expressed as mean ± SEM (n=16). *p < 0.05 compared to control by two-tailed paired Student t-test.

(G) Time-course of GDF15 protein secretion in acutely EPS-stimulated myotubes. Data are expressed as mean ± SEM (n=6). **p < 0.01 compared to control by two-way ANOVA followed by a Bonferroni post-hoc test. WO 2021/018899 PCT/EP2020/071287

Figure 3. GDF15 gene expression changes in contracting skeletal muscle

(A) Time-course of GDF15 mRNA level in acutely EPS-stimulated myotubes. Data are expressed as mean ± SEM (n=6). **p < 0.01, ***p < 0.001 compared to control by two-way ANOVA followed by a Bonferroni post-hoc test.

(B) GDF15 mRNA level in EPS3h-stimulated myotubes and (C) in EPS24h-stimulated myotubes. Data are expressed as mean ± SEM (n=12). **p < 0.01 compared to control by two- tailed unpaired Student t-test.

(D-F) GDF15 mRNA level changes in response to exercise-mimetics: five days cultured human myotubes were treated for 3h with (D) Forskolin 10 mM, (E) Ionomycin 4 mM, (F) and the PPAR.6 agonist GW0742 100 nM. Data are expressed as mean ± SEM (n=6). **p < 0.01, ***p < 0.001 compared to control by two-tailed unpaired Student t-test.

(G) GDF 15 mRNA level changes in muscle vastus lateralis biopsy samples taken before and immediately after a lh acute exercise bout in lean healthy volunteers (Human study 1). Data are expressed as mean ± SEM (n=18). ***p < 0.001 compared to control by two-tailed paired Student t-test.

Figure 4. Changes in plasma GDF15 levels with exercise, obesity and lifestyle intervention

(A-C) Human study 2: plasma GDF 15 changes in lean healthy volunteers in response to (A) endurance exercise lh at 60% V02max, (B) sprint interval exercise 7 repetitions at 130% of maximal workload, (C) delta change from rest to exercise during endurance versus sprint interval exercise. Data are expressed as mean ± SEM (n=8-15). **p < 0.01 compared to control by two-tailed paired Student t-test.

(D-F) Human study 3 : plasma GDF 15 changes in obese middle-aged (D) and elderly (E) subjects at baseline and in response to a 8-week lifestyle intervention-induced weight loss program. Data are expressed as mean ± SEM (n=8). **p < 0.01, ***p < 0.001 compared to control by two-tailed paired Student t-test. (F) Plasma GDF 15 changes in response to lifestyle- induced weight loss in obese individuals (all subjects). Data are expressed as mean ± SEM (n=16). *p < 0.05 compared to control by two-tailed paired Student t-test.

(G) Plasma GDF 15 levels in lean healthy (study 2) versus middle-aged obese (study 3).

(H) Plasma GDF 15 levels in middle-aged obese versus elderly obese (study 3).

Figure 5. GDF15 promotes lipolysis in human adipose tissue

(A-B) Relative gene expression of GFRAL (A) and relative gene expression of RET (B) in human whole abdominal subcutaneous adipose tissue, isolated adipocytes and stroma WO 2021/018899 PCT/EP2020/071287 vascular fraction (SVF) preparations from the same samples (Human study 4), and in whole human skeletal muscle tissue. Data are expressed as mean ± SEM (n=5).

(C-D) Lipolytic response measured by glycerol release (C) and non-esterified fatty acid release (D) in human abdominal subcutaneous adipose tissue explants in basal condition and in response to 1 and 100 ng/ml of recombinant human GDF15, 10 mM forskolin (FK) and 1 mM isoprenaline (ISO). Data are expressed as mean ± SEM (n=18, 3 replicates of 6 independent donors). *p < 0.05, **p < 0.01 compared by unpaired Student t-test.

(E-F) Lipolytic response measured by glycerol release (E) and non-esterified fatty acid release (F) in human abdominal subcutaneous adipose tissue explants in basal condition and in response to 100 ng/ml of recombinant human GDF15. Data are expressed as mean ± SEM (n=6 independent donors). *p < 0.05 compared by unpaired Student t-test.

(G) Conditioned media of EPS24h-stimulated myotubes were applied on differentiated hMADS adipocytes for 24h to measure glycerol output, a surrogate of lipolysis, in absence or presence of a GDF15 neutralizing antibody. Data are expressed as mean ± SEM (n=5). *p < 0.05 compared to control by one-way ANOVA

(H) Integrative model of the skeletal muscle-adipose tissue crosstalk orchestrated by GDF15. Upon muscle contraction, GDF15 is released, reach its target receptors GFRAL/RET on adipose tissue to activate lipolysis which releases non esterified fatty acid further serving as fuels to supply muscle contraction.

EXAMPLE:

Methods

Human Study 1

Young (18-30 yrs) recreationally active (VCkpeak 40-50 ml kg ¹ min ¹ ) males recruited to partake in this study. The protocol was approved by the Ethics Committee of Dublin City University and all participants gave written informed. VCkpeak was determined on a cycle ergometer starting at 70 watts and increasing in 30-watt increments every 3 minutes until exhaustion. At least 7 days later participants completed a 60 min bout of exercise on an electrically braked cycle ergometer at 55% peak power output. A skeletal muscle biopsy of the vastus lateralis was performed pre and immediately post the exercise bout. Muscle samples were immediately frozen in liquid nitrogen before being stored at -80 °C.

Human study 2 WO 2021/018899 PCT/EP2020/071287

This was a cross-sectional study comparing an acute bout of moderate continuous exercise with a high intensity interval bout of exercise in young active men (VChpeak 50-65 ml kg ¹ min ¹ ). The protocol was approved by the Dublin City University Ethics Committee and all subjects gave written informed consent. Participants were instructed to refrain from exercise and to replicate food intake the day before each trial. In the morning, following an overnight fast, participants lay on a bed for 1-hr after arriving at the lab. A blood sample was taken and they then exercised (i) on a bicycle ergometer at 60% VChpeak for 1-hr or (ii) by performing 7 high intensity bouts of exercise at 130% peak power output. Each bout lasted 30-sec followed by 4.5-min recovery. A blood sample was taken at the end of each exercise trial. The intensity for both trials was determined using the results of an incremental exercise test to exhaustion.

Human Study 3

Middle-aged and elderly obese male subjects were enrolled in the MONA (Metabolism, Obesity, Nutrition and Age) clinical trial NCT02161926. The protocol was approved by the Ethics Committee of Toulouse University Hospitals, and all subjects gave written informed consent. They participated in an 8-week lifestyle intervention including a moderate calorie restriction of 20% below their daily energy requirement aerobic combined to two sessions of resistance exercise per week. The participants were asked to refrain from vigorous physical activity 48 hours before presenting to the clinical investigation center, and they ate a weight- maintaining diet consisting of 35% fat, 15% protein, and 50% carbohydrates 2 days before the experiment. Maximal oxygen uptake (V02max) was investigated on a bicycle ergometer by indirect calorimetry at baseline. Anthropometric and blood parameters were assessed at rest and during a 45 min acute exercise bout performed at 50% V02max, at baseline and 48-72h after the end of the lifestyle intervention. Blood was collected on EDTA and immediately processed for plasma storage at -80°C.

Human Study 4

The samples investigated in this paper were collected from 2006 to 2007 during the DiOGenes study, a pan-European randomized trial, which was approved by the ethics committees of each of the 8 European centers participating to the program (NCT00390637). The DiOGenes project investigated the effects of diets with different content of protein and glycemic index on weight-loss maintenance and metabolic and cardiovascular risk factors after an 8-week very low calorie diet (VLCD) phase, in obese/overweight individuals. Written WO 2021/018899 PCT/EP2020/071287 informed consent was obtained from each patient according to the local ethics committee of the participating countries as previously described (47).

Healthy overweight (body mass index (BMI) > 27 kg/m2) individuals, aged <65 years were eligible for the study. Exclusion criteria were BMI >45 kg/m2, liver or kidney diseases, cardiovascular diseases, diabetes mellitus type 1, special diets/eating disorders, systemic infections/chronic diseases, cancer within the last 10 years, weight change >3 kg within the previous 3 months, and other clinical disorders or use of prescription medication that might interfere with the outcome of the study.

A detailed description of inclusion and exclusion criteria has been published previously (47). A detailed description of the DiOGenes intervention trial and main outcomes can be found in the core publication (48). Briefly, among 1209 individuals screened, 932 entered a baseline clinical investigation day including anthropometric measures (height, weight, waist circumference, body composition), blood pressure measurements, fasting blood sampling, and subcutaneous adipose tissue biopsies were performed (at baseline and at the end of each phase). All procedures were standardized between the 8 study centers across Europe. Only baseline and VLCD biological samples and clinical data were used in the present investigation. Paired adipose tissue RNA samples were available at baseline and at the end of the VLCD for 359 individuals.

GDF15 protein level determination

GDF15 protein levels in cultured CM and plasma samples were determined by ELISA (R&D Systems, Minneapolis, USA).

Skeletal muscle cell primary culture

Satellite cells from rectus abdominis of healthy male subjects (age 34.3 ± 2.5 years, BMI 26.0 ± 1.4 kg/m2, fasting glucose 5.0 ± 0.2 mM) were kindly provided by Prof. Arild C. Rustan (Oslo University, Norway). Satellite cells were isolated by trypsin digestion, preplated on an uncoated petri dish for 1 h to remove fibroblasts, and subsequently transferred to T-25 collagen-coated flasks in Dulbecco’s Modified Eagle’s Medium (DMEM) low glucose (1 g/L) supplemented with 16% FBS and various factors (human epidermal growth factor, BSA, dexamethasone, gentamycin, fungizone, fetuin) as previously described (49). Cells from several donors were pooled and grown at 37 °C in a humidified atmosphere of 5% C02. Differentiation of myoblasts (i.e. activated satellite cells) into myotubes was initiated at ~ 80-90% confluence, by switching to a-Minimum Essential Medium with 2% penicillin-streptomycin, 2% FBS, and WO 2021/018899 PCT/EP2020/071287 fetuin (0.5 mg/ml). The medium was changed every other day and cells were grown up to 5 days.

Electrical Pulse Stimulation

Skeletal muscle cells were fully differentiated for 4 days, and EPS was then applied using a C-Pace EP multichannel culture pacer (IonOptix, Dublin, Ireland) for 3h (acute intense exercise model) with a protocol consisting of 24 ms pulses at 10 V, with a frequency of 0,5 Hz, or for 24h (chronic moderate exercise model) with a protocol consisting of 2 ms pulses at 10 V, with a frequency of 0, 1 Hz. After completion of EPS, conditioned media (CM) were collected for proteomic screening and CM experiments with hMADS adipocytes. The EPS protocol did not induce any visible cell detachment, and assessment of the cytotoxic effect of EPS based on the release of adenylate kinase in culture media using a colorimetric cytotoxicity assay (ToxiLightTM Non-Destructive Cytotoxicity BioAssay Kit, Lonza, USA) showed that adenylate kinase activity was not significantly changed in medium from stimulated compared to unstimulated myotubes.

Culture of human multipotent adipose-derived stem cells

hMADS cells were cultured and maintained in proliferation medium (DMEM low glucose lg/1, 10% FBS, 2 mM L-glutamine, 10 mM HEPES buffer, 50 units/ml of penicillin, 50 mg/ml of streptomycin, supplemented with 2.5 ng/ml of human fibroblast growth factor 2 (FGF2)) as previously described (50). The cells were inoculated in 6-well plates at a density of 44’ 000 cells/ml and kept at 37°C in 5% C02. Six days post-seeding, FGF2 was removed from proliferation medium. On the next day (day 0), the cells were incubated in differentiation medium (DM; serum-free proliferation medium/Ham’s F-12 medium containing 10 pg/ml of transferrin, 10 nM of insulin, 0.2 nM triiodothyronine, 100 mM 3- isobutyl-1- methylxanthine, 1 mM dexamethasone and 100 nM rosiglitazone). At day 3, dexamethasone and 3 -isobutyl-1 -methylxanthine were omitted from DM and at day 10 rosiglitazone was also omitted. Lipolysis experiments with EPS CM and the GDF15 neutralizing antibody were carried out at day 14. Human FGF2, insulin, triiodothyronine, transferrin, 3 -isobutyl- 1 -methylxanthine, and dexamethasone were from Sigma; L-glutamine, penicillin, and streptomycin from Invitrogen; Hepes, Dulbecco’s modified Eagle medium low glucose, and Ham’s F-12 medium from Lonza; and rosiglitazone from Alexis Biochemicals.

Determination of glucose metabolism WO 2021/018899 PCT/EP2020/071287

Total glycogen content was determined spectrophotometrically after complete hydrolysis into glucose by the a-amiloglucosidase as previously described (51). For glycogen synthesis experiments, myotubes were pre-incubated with a glucose- and serum-free medium for 90 min, then exposed to DMEM supplemented with D[U- ¹⁴ C] glucose (1 pCi/ml; PerkinElmer, Boston, MA) for 3 hours. Following incubation, glucose oxidation was determined by counting of ¹⁴ C02 released into the culture medium. The cells were then solubilized in KOH 30% and glycogen synthesis was determined as previously described (52).

Determination of palmitate oxidation

Myotubes were preincubated for 3 hours with [l- ¹⁴ C]palmitate (1 pCi/mL; PerkinElmer) and nonlabeled (cold) palmitate (100 mM final concentration). Palmitate was coupled to a fatty acid (FA)-free BSA in a molar ratio of 5: 1. After incubation, ¹⁴ C02 and ¹⁴ C- acid soluble metabolite were measured as previously described (53). All assays were performed in duplicate, and data were normalized to cell protein content.

Mass spectrometry-based quantitative analysis of myotube secretome

Methods are detailed in Supplementary Methods. After protein extraction from culture media (N=4 per group), one sample pool, comprising equal amounts of all protein extracts, was generated for quality assessment of LC-MS/MS. Individual samples and the sample pool were electrophoresed using SDS-polyacrylamide gel electrophoresis (SDS-PAGE) gels. Five protein bands (2mm each) per lane were excised from the gels, and proteins were in-gel reduced and alkylated using an automatic pipetting device (MassPrep, Waters), then digested at 37°C overnight with trypsin (Promega, Madison, WI, USA). A set of reference peptides [Indexed Retention Time (iRT) Kit; Biognosys, Schlieren, Switzerland] was added to the resulting peptides to allow the stability of instrument performances to be measured for QC purposes.

Samples were analyzed on a nano-ultraperformance LC system (nanoAcquity; Waters, Milford, MA, USA) coupled to a quadrupole-Orbitrap hybrid mass spectrometer (Q-Exactive plus; ThermoFisher Scientific). Mass spectrometry data were processed using MaxQuant software (v.1.5.8.3; Max Planck Institute of Biochemistry, Martinsried, Germany) (54). Peak lists were created using default parameters and searched using the Andromeda search engine (revert mode) implemented in MaxQuant against a protein database created using the MSDA software suite (55). The database contained human protein sequences (Swiss-Prot; https://www.uniprot.org/taxonomy/; Taxonomy ID: 9606; 20,195 entries), which were downloaded in October 2017. Sequences of common contaminants like keratins and trypsin WO 2021/018899 PCT/EP2020/071287

(247 entries) were added to the database (contaminants. fasta included in MaxQuant). A false discovery rate of 1% for both peptide spectrum matches (minimum length of 7 amino acids) and proteins was accepted during identification. Regarding quantification, data normalization and protein abundance estimation was performed using the label-free quantification (LFQ; (54)) option offered in MaxQuant. Proteins identified with only one unique peptide were not considered for quantification. Only proteins with at least three of four valid values per group as well as the ones absent (i.e., 0 valid values) in samples from a given group were kept for further analysis. The MS proteomics data have been deposited to the ProteomeXchange Consortium via the Pride partner repository with the dataset identifier PXD014126.

QC-related measurements showed that HPLC performance remained good and stable throughout the whole experiment, with a median coefficient of variation of 0.5% concerning retention times of all iRT peptides when considering all injections. The reproducibility of quantitative data was also satisfactory because we recorded low median coefficients of variation for MaxQuant-derived LFQ values of all quantified proteins within each of the four experimental groups (31%) and in the sample pool of all samples injected repeatedly during the course of MS-based analyses (21%).

Real-time qPCR

Total RNA from cultured myotubes or vastus lateralis muscle was isolated using Qiagen RNeasy mini kit according to manufacturer’s instructions (Qiagen GmbH, Hilden, Germany). The quantity of RNA was determined on a Nanodrop ND-1000 (Thermo Scientific, Rockford, IL, USA). Reverse-transcriptase PCR was performed on a Techne PCR System TC-412 using the Multiscribe Reverse Transcriptase method (Applied Biosystems, Foster City, CA). Real time quantitative PCR (qPCR) was performed to determine cDNA content. All primers were bought from Applied Biosystems and were: 18S (Taqman assay ID: Hs99999901_sl), GDF15 (Hs00171132_ml), GFRAL (Hs01087628_ml) and A£r(Hs01120030_ml). The amplification reaction was performed in duplicate on 20ng of cDNA in 96-well reaction plates on a StepOnePlusTMsystem (Applied Biosystems). All expression data were normalized by the 2(ACt) method using 18S or PUM1 as internal controls for cell type or whole adipose tissue data, respectively.

Statistics

All statistical analyses were performed using GraphPad Prism 7.0 for Windows (GraphPad Software Inc., San Diego, CA). Normal distribution and homogeneity of variance WO 2021/018899 PCT/EP2020/071287 of the data were tested using Shapiro-Wilk and F tests, respectively. Two-tailed Student’s unpaired and paired t-tests were performed to determine differences between treatments. Two- way ANOVA and Bonferroni’s post hoc tests were used when appropriate. All values in figures and tables are presented as mean ± SEM. Statistical significance was set at p<0.05.

Results

Conditioned media from exercised myotubes trigger lipolysis in adipocytes

The physiological and metabolic adaptations of skeletal muscle to exercise are well known (1). Using electrical pulse stimulation (EPS) of human myotubes to induce forced contraction, we modeled two exercise paradigms: an acute high intensity exercise model (EPS3h) and a chronic moderate exercise training model (EPS24h). EPS activates canonical exercise signaling pathways such as p38 mitogen-activated protein kinases (p38 MAPK) and Ca2+/calmodulin-dependent protein kinase II (CaMKII) up to 48h (data not shown). As expected, EPS3h which mimics an acute high intensity exercise induced a pronounced glycogen depletion (Figure 1A) and concomitant increase in lactate production (Figure IB). Consistent with this type of exercise, no major change in glucose oxidation rate was observed (Figure 1C) while lipid oxidation rate was reduced by 35% (Figure ID). EPS3h also induced gene expression of classically known myokines such as interleukin 6 (IL6), IL15 and fibroblast growth factor 21 (data not shown).

We further validated that EPS24h, which mimics chronic moderate exercise training, did not significantly reduced glycogen content (Figure IE) while increasing basal glycogen storage capacity (~1.5 fold, p<0.05) (Figure IF) glucose oxidation rate (~2 fold, p<0.05) (Figure IGF and lipid oxidation rate (~3 fold, p<0.05) (Figure 1H). EPS24h increased IL6 mRNA level (~3 fold, p<0.01), slightly induced myostatin, and decreased Fibronectin Type III Domain Containing 5 (FNDC5) and Brain Derived Neurotrophic Factor (BDNF) mRNA levels (data not shown). To test our hypothesis that skeletal muscle contraction produces a cellular stress signal that trigger lipolysis to sustain fuel availability during exercise, we next incubated human multipotent adipose-derived stem (hMADS) adipocytes with conditioned media (CM) of EPS-stimulated myotubes (Figure II). Interestingly, CM from EPS 3 h- stimulated myotubes induced a modest increase of basal lipolysis reflected by glycerol production (~1.3 fold, p<0.001) in the absence of any lipolytic stimuli (Figure 1J). In the same line, CM from EPS24h-stimulated myotubes induced a more robust basal lipolysis (~3 fold, p<0.001) (Figure WO 2021/018899 PCT/EP2020/071287

IK). Similarly, CM from EPS24h induced a significant increase of NEFA release (1.7 fold, p<0.05) (data not shown).

In summary, exercise-mediated skeletal muscle contraction produces secreted factors able to activate lipolysis in adipocytes in vitro.

GDF15 is a novel exerkine rapidly induced by skeletal muscle contraction

To identify potential secreted proteins produced by skeletal muscle contraction, we performed a proteomic screen of CM from EPS-stimulated and non-stimulated myotubes (Figure 2A & D). We identified 1356 differential proteins in EPS CM versus respective control. Among the significantly up-regulated proteins, GDF15 caught our attention (Figure 2A). as recent studies described GDF15 as a novel metabolic hormone (14-17). GDF15 protein levels were increased by about 2.5 fold in EPS3h CM (Figure 2B). We confirmed this finding by ELISA, GDF15 increased from 21.7±2.1 pg/ml to 29.6±3.4 pg/ml in EPS3h CM (p<0.01) (Figure 20. Importantly, we also identified GDF15 as a significantly up-regulated protein in EPS24h CM (3 fold, p<0.05) (Figure 2D-F) The concentration of GDF15 in EPS24h CM ranged from 19.4 to 110.9 pg/ml and was nearly 2-fold increased (41.2±4.0 vs 21.7±2.1 pg/ml) compared to EPS3h CM. Time-course of EPS in human primary myotubes showed that GDF15 is significantly up-regulated within lh (Figure 2G). Overall, we here identify GDF15 as a novel exercise-regulated myokine.

GDF15 gene expression is responsive to skeletal muscle contraction and exercise mimetics

Since GDF15 is a stress-responsive hormone, we tested whether acute EPS can modulate GDF15 mRNA levels. We observed a rapid up-regulation of GDF15 mRNA levels within 30min exposure to EPS (Figure 3A). A second peak of mRNA levels was observed at 3h EPS. In agreement with protein secretion data, we observed a significant up-regulation of GDF15 mRNA levels for EPS3h-stimulated myotubes (1.7 fold, p<0.01) (Figure 3B). We similarly observed an up-regulation of GDF15 mRNA levels in EPS24h-stimulated myotubes (Figure 30. Since exercise activates a complex integrative response including neuroendocrine changes beyond muscle contraction, we assessed the influence of exercise-mimetics on GDF15 mRNA levels. Forskolin which increases intracellular levels of the second messenger cAMP, did not change GDF15 gene expression (Figure 3D) while interestingly both ionomycin which facilitates calcium release (Figure 3E) and the peroxisome proliferator-activated receptor b agonist GW0742 (Figure 3F) increased GDF15 mRNA levels (1.5-2 fold, p<0.01). We next WO 2021/018899 PCT/EP2020/071287 investigated GDF15 mRNA levels in muscle biopsy samples from lean healthy individuals in response to lh of acute exercise at 55% peak power output on a bicycle ergometer (Human study 1). We found that GDF15 mRNA levels increase up to 18-fold in skeletal muscle in response to exercise (Figure 3G).

GDF15 plasma levels in response to exercise, obesity and lifestyle

Since our in vitro work revealed GDF15 as a novel exerkine, we measured GDF15 in plasma of lean healthy individuals randomly assigned in a crossover design to either lh of endurance exercise performed at 60% of V02peak or sprint interval exercise consisting of 7 repetitions of 30s at 130% of maximal aerobic power (Human study 2) (Figure 4A-C). In line with a recent report (19), we observed that both type of exercise, endurance (Figure 4A) and sprint interval (Figure 4B). augment plasma GDF15 circulating levels. Interestingly, the exercise response (exercise minus rest) tended to be lower (p=0.07) for the sprint interval exercise which produces overall a lower energy expenditure and energetic stress (Figure 40.

We further show that acute endurance exercise (45 min at 50% V02max) raises plasma GDF15 levels in both middle-aged and elderly obese subjects (Human study 3) (Figure 4D & E). Plasma GDF15 levels were measured at rest and immediately after exercise at baseline and in response to an 8-weeks lifestyle intervention program combining moderate calorie restriction and aerobic and resistance exercise. Obese subjects lost in average 5.1±0.5 kg (data not shown). Exercise-induced increase of plasma GDF15 was observed in both groups at baseline and post-lifestyle (Figure 4D & E). When combining all subjects, we observed a slight but significant increase of plasma GDF15 levels in response to lifestyle-induced weight loss (Figure 4F). This increase of plasma GDF15 tended to be positively correlated with lifestyle- induced weight loss in elderly obese subjects (r=0.66; p=0.07). Lean healthy and middle-aged obese subjects had plasma GDF15 levels within the same range (Figure 4G). while BMI- matched elderly obese had higher circulating levels of GDF15 compared to middle-aged obese individuals (Figure 4H). Consistent with this finding, we observed a significant positive correlation between resting plasma GDF15 levels and age in Human study 3 (r=0.512, p=0.043). Interestingly, no sex-difference in resting plasma GDF15 levels were found in Human study 4 (men: 475±56 vs women: 472±46 pg/ml).

Collectively, we here show that plasma GDF15 responds to various modalities of exercise in lean and obese individuals, and increases with aging.

GDF15 targets human adipose tissue to promote lipolysis WO 2021/018899 PCT/EP2020/071287

We noted a positive correlation between plasma glycerol and GDF15 level in all obese subjects investigated at rest and during exercise (Human study 3) (data not shown). We further observed a nearly significant positive relationship (r=0.35, p=0.067) between changes in plasma GDF15 levels and changes in BMI in obese individuals in response to very low calorie diet- induced weight loss (Human study 4) (data not shown). We therefore hypothesized that GDF15 was able to target white adipose tissue to induce lipolysis and weight loss. We first examined GDF15 receptors GFRAL and RET mRNA levels in human abdominal adipose tissue biopsy samples (Human study 4). We found a significant expression of the GDF15 cognate receptor GFRAL in whole adipose tissue fraction as well as in isolated adipocytes (Figure 5A). Interestingly, GFRAL expression was virtually null in whole human muscle tissue. The co receptor RET followed a similar pattern of expression as GFRAL in adipose tissue except for whole skeletal muscle tissue where its expression was comparable to whole adipose tissue (Figure 5B). As both GFRAL and RET were expressed to comparable levels in adipocytes and adipose stroma vascular cells, we further examined both GDF15 receptor expression in sorted stromal cells. We observed that both GFRAL (data not shown) and RET (data not shown) were predominantly expressed in preadipocytes, again confirming a metabolic role of GDF15 in adipocytes. Neither GFRAL (data not shown) nor RET (data not shown) adipose gene expression were influenced by obesity grade. However they were both associated with a number of biological and clinical variables such as plasma triglycerides, HOMA-IR and Matsuda index, while adipose RET mRNA levels were inversely related to BMI (Table 1).

We then investigated the effect of recombinant human GDF15 (rhGDF15) protein on lipolysis in human abdominal adipose tissue explants. rhGDF15 significantly increased lipolysis at the physiological concentration of 1 ng/ml, reflected by both glycerol (Figure 5C) and NEFA release (Figure 5D) This lipolytic response was in a comparable range as those observed for forskolin and the non selective b-adrenergic agonist isoprenaline which increased lipolysis to about 2-3 fold. A higher supra-physiological concentration of rhGDF15 at 100 ng/ml did not further raised basal lipolysis (-11%, p<0.05) in adipose explants from 6 independent donors (Figures 5E and 5F). Even more remarkable, we demonstrate that blocking GDF15 with a neutralizing IgG antibody of hGDF15 completely abrogates the lipolytic response of EPS24h CM (Figure 5G). thus indicating that GDF15 likely triggers most, if not all, the EPS24h CM lipolytic effect in hMADS adipocytes. To validate this finding, we verified that incubating a non-specific IgG antibody in control wells did not affect basal lipolysis (data not shown). We finally wondered whether this lipolytic effect of GDF15 was a human specificity. We measured both GFRAL and GDF15 gene expression in whole brain, WO 2021/018899 PCT/EP2020/071287 perigonadic white adipose tissue and skeletal muscle of adult female mice. Although GDF15 was expressed in all three organs (data not shown), GFRAL was only detectable in brain (data not shown), thus confirming recent findings (16).

Altogether, our data provide the first evidence that GDF15 can target human adipose tissue to trigger lipolysis.

Discussion:

Investigators have been searching for a link between muscle contraction and metabolic changes in other organs such as the liver and the adipose tissue for a few decades. The targets of an‘exercise factor’ have been humoral proteins released from skeletal muscle during contraction that mediate the adaptations of chronic exercise training (4, 20). This has opened a novel paradigm that skeletal muscle is an endocrine organ producing and releasing hormones, i.e. myokines, which exerts endocrine effects on remote organs (4, 21). We here provide compelling evidence that GDF15 behaves as a novel exerkine involved in a crosstalk between skeletal muscle and adipose tissue (Figure 5H). We show that the cellular stress mediated by skeletal muscle contraction can be translated into a systemic response through GDF15-mediated lipolysis in white adipocytes.

As we hypothesized that skeletal muscle contraction can release a cellular stress signal able to induce lipolysis, we developed an experimental model of exercise in cultured human myotubes. Human primary culture of skeletal muscle cells has been widely used by several investigators (22-26) and provides a powerful tool for mechanistic studies of skeletal muscle and to study muscle autonomous adaptations in the absence of the systemic milieu (27). EPS of human myotubes can be used to induce forced contraction and mimic exercise in vitro (28). Although some studies have used EPS to assess individual variability in biological response to exercise in vitro (29, 30) and to identify novel secreted factors by skeletal muscle contraction (31-33), very few have investigated how closely EPS recapitulates the metabolic consequences of exercise. We here developed two exercise models: one acute high intensity exercise that recapitulates the expected physiological responses with strong glycogen depletion and high lactate production (34), and one chronic moderate exercise which more closely mimics the biological adaptations of endurance exercise training with increased basal glycogen storage along with an up-regulation of substrate oxidation rates (35).

To identify potential muscle contraction-derived lipolytic factors, we analyzed CM from our two exercise models with human adipocytes. Remarkably, CM from both exercise models increased basal lipolysis. This effect was quite modest for the acute intense exercise model but WO 2021/018899 PCT/EP2020/071287 more pronounced for the chronic moderate exercise model. Thus a muscle contraction-derived factor contained in CM has the potential to promote lipolysis. Among the currently known myokines, only IL6 has been previously suggested to induce lipolysis in humans (36). Later the same authors proposed that muscle-derived IL6 does not promote fat mobilization from subcutaneous adipose tissue, at least at moderate exercise intensity (37), but rather selectively stimulates fat metabolism in human skeletal muscle (38). This observation was corroborated by in vitro work in adipose tissue explants showing that IL6 inhibits lipoprotein lipase activity (39). Altogether most evidence so far indicates that IL6 does not acutely stimulate lipolysis in human adipose tissue. In order to unravel novel putative lipolytic myokines, we performed a proteomic screen of EPS CM and identified GDF15 as a significantly up-regulated protein in our two in vitro exercise models. GDF15 mRNA levels rose within 30min in response to muscle contraction, followed by an elevated secretion by lh. GDF15 gene expression was also induced by pharmacological exercise-mimetics such as ionomycin and the PPARJ3 agonist GW0742, but remained insensitive to activation of cAMP-signaling by forskolin. This indicates that other molecular pathways related to exercise are involved in GDF15 regulation beyond muscle contraction. As GDF15 is a stress-responsive factor, components of the integrated stress response pathway including the protein kinase R (PKR)-like endoplasmic reticulum kinase (PERK), the eukaryotic translation initiation factor 2-alpha (EIF2a), the activating transcription factor 4 (ATF4) and the CCAAT-enhancer-binding protein homologous protein (CHOP) may be involved (11). A few studies have already suggested that this integrated stress response pathway is activated by exercise (40, 41). Thus several molecular pathways may be involved in the regulation of GDF15 expression/secretion in skeletal muscle.

We consolidated our in vitro findings showing that GDF15 mRNA levels rise from 2- to 20-fold in skeletal muscle of lean healthy subjects in response to acute aerobic exercise. This local rise of GDF15 in skeletal muscle was paralleled by an increase of circulating GDF15 levels during endurance and sprint interval exercise in lean healthy volunteers. Although circulating GDF15 can originate from other tissue sources, it is tempting to speculate, based on our data, that contracting skeletal muscle contributes to increase circulating GDF15 levels during exercise. This is in contrast with a recent study suggesting that the rise of circulating GDF15 during exhaustive exercise appears independent of skeletal muscle (19). Alternatively, muscle-derived GDF15 could play a paracrine role within skeletal muscle to target intramuscular adipose tissue. Obesity did not alter exercise-induced circulating GDF15, but interestingly, lifestyle-induced weight loss in middle-aged and elderly obese individuals significantly increased baseline circulating GDF15 levels. The rise of plasma GDF15 levels WO 2021/018899 PCT/EP2020/071287 was positively related to weight loss in response to the lifestyle program in elderly obese people, again highlighting a link between GDF15 and adipose tissue loss. Emmerson et al. observed that human subcutaneous adipose tissue is a significant site of expression of the GDF 15 receptor GFRAL (16). We therefore went on to hypothesize that GDF15 could target adipose tissue to promote lipolysis.

GDF 15 is a cellular stress-responsive hormone that has recently gained much interest as anti-obesity therapy (42, 43). Recent studies indicate that GDF 15 binds to a heterodimeric receptor complex composed of GFRAL and RET which expression is restricted to the brainstem in mice (14-17). We here provide evidence that GFRAL and RET are significantly expressed in human adipocyte. A comparable expression is also found in the stroma vascular fraction of adipose tissue, and further cell-type specific analyses revealed that both GFRAL and RET are predominantly expressed in preadipocytes compared to macrophages and lymphocytes. In contrast, GFRAL expression is skeletal muscle tissue is virtually null thus excluding a potential autocrine role of GDF15. Our data are consistent with the Genotype-Tissue Expression (GTEx) public database indicating that GFRAL is predominantly expressed in human subcutaneous adipose tissue. Of interest, GFRAL and RET gene expression in subcutaneous abdominal adipose tissue is not influenced by adiposity and obesity grade. Adipose GFRAL and RET gene expression correlated positively with plasma triglycerides, HOMA-IR and Matsuda index. This is consistent with the recent observation that GDF 15 behaves as a nutritional stress signal induced by long-term high fat feeding and metabolic disturbances in mice (9-11). In line with an effect of GDF 15 on adipose tissue, adipose RET gene expression was inversely related to BMI. Consistently, we here show that a physiological concentration of recombinant human GDF 15 induces lipolysis in a comparable range as forskolin in human subcutaneous abdominal adipose tissue explants. In our clinical studies and other studies, circulating GDF 15 typically ranged between 0.3 and 1 ng/ml (43, 44). Higher supra-physiological concentrations up to 100 ng/ml, as observed in cancer cachexia (44), did not further increase lipolysis. Most importantly, neutralization of GDF 15 in EPS24h CM with a monoclonal antibody completely abrogated lipolysis, implying that GDF 15 triggers most if not all the lipolytic response in CM from EPS- stimulated human myotubes. The higher lipolytic response observed in EPS24h CM could be explained by the nearly 2-fold greater concentration of GDF 15 accumulated in the medium over 24h. Adipocyte lipolysis is a major physiological process of fuel supply in conditions of increased energy needs such as exercise (45, 46). Our work identifies GDF 15 as a novel homeostatic hormone of the crosstalk between contracting skeletal muscles and adipose tissue in humans. WO 2021/018899 PCT/EP2020/071287

In summary, GDF15 is a novel‘exercise factor’ involved in a homeostatic regulation loop between contracting skeletal muscles and adipose tissue. Our data suggest that GDF15 is rapidly produced upon skeletal muscle contraction and exercise mimetics. Unlike in mice, GFRAL/RET expression is not highly specific to the caudal brain and displays a significant expression in human adipose tissue. As GDF15 has emerged as an interesting anti-obesity therapy through its central effects on appetite suppression, potential peripheral effects should not be neglected. Hence, future studies of the effects of GDF15 in humans are highly needed.

Table 1. Relationship between biological and anthropometric variables and subcutaneous abdominal adipose tissue GFRAL and RET mRNA levels

Biological variable Gene Symbol r -value n

Triglycerides

GFRAL 0.126 0.022 329 RET 0.178 0.001 326

Total cholesterol

GFRAL 0.056 0.308 332 RET 0.114 0.034 329

Glucose

GFRAL 0.112 0.046 316 RET 0.085 0.135 313

HOMA-IR

GFRAL 0.137 0.017 306 RET 0.157 0.006 303

Matsuda index

GFRAL -0.127 0.027 305

RET -0.166 0.004 302

BMI

GFRAL 0.028 0.693 330

RET -0.121 0.029 327

Waist circumference

GFRAL 0.106 0.053 329

RET 0.041 0.460 326 WO 2021/018899 PCT/EP2020/071287

These data were obtained from Human study 4. BMI, body mass index; HOMA-IR, homeostatic model assessment of insulin resistance; r: Pearson correlation coefficients. The Matsuda index was calculated as 10 000/square root of [(fasting glucose ^c fasting insulin) ^c (mean glucose x mean insulin during OGTT)].

REFERENCES:

Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

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