Patent Application
20240182972
The present invention refers to the medical field. Particularly, the present invention refers to an in vitro method for screening and/or selecting genes whose methylation status indicates whether a patient suffering from obesity is responding or will respond to a treatment with a very-low-calorie ketogenic diet (VLCKD). Moreover, the present invention refers to an in vitro method for monitoring or predicting whether a patient suffering from obesity is responding or will respond to VLCKD.
Ketosis has gained interest over recent years due to its induced benefits that it imparts on several health conditions. Ketosis is associated with a delay in the onset of diseases and increased longevity. Similarly, ketosis is suggested to have an extensive range of health benefits, from increased physical endurance in athletes to delayed aging. Also, to improve conditions such as neurodegenerative disease cancer, cardiovascular disease, and obesity. Some of these studies involved high fat ketogenic diets and even though the main characteristic of ketogenic diets is the carbohydrates restriction, the specific composition in macronutrients and calories should be taken into consideration for the impact in clinical practice.
VLCKD was demonstrated to be an effective strategy in managing obesity, including weight loss and maintenance, increased preservation of muscle mass, and enhanced resting metabolic rate. Moreover, it can improve metabolic parameters in patients with obesity and type 2 diabetes. Additionally, it was demonstrated that VLCKD can reduce food craving and improve psychobiological parameters to help improve quality of life in patients with obesity. However, the molecular mechanisms underlying these benefits of ketogenic diet remain unknown.
So, there is an unmet medical need of finding a molecular method for monitoring or predicting whether a patient suffering from obesity is responding or will respond to VLCKD, particularly whether an improvement of metabolic parameters has occurred in a patient suffering from obesity after the induction of nutritional ketosis by means of a treatment with VLCKD. The present invention aims to solve this need and an evaluation regarding how VLCKD might affect the obesity methylome is herein provided. Obesity-related methylome changes have been identified in the present invention, which are mediated by the induced weight loss or ketosis by means of treatment with VLCKD. Said methylome changes are thus herein proposed as an indication of whether a patient suffering from obesity is responding or will respond to a treatment with VLCKD.
The present invention refers to a method for monitoring or predicting whether a patient suffering from obesity is responding or will respond to VLCKD, particularly for monitoring or predicting whether an improvement of metabolic parameters has occurred in a patient suffering from obesity after the induction of nutritional ketosis by means of a treatment with VLCKD.
Particularly, twenty-one patients with obesity (n=12 women, 47.9±1.02 yr, 33.0±0.2 kg/m2) after 6 months on a VLCKD and 12 normal weight volunteers (n=6 women, 50.3±6.2 yrs, 22.7±1.5 kg/m2) were studied. Data from the Infinium MethylationEPIC BeadChip methylomes of blood leukocytes were obtained at time points of ketotic phases (basal, maximum ketosis, and out of ketosis) during VLCKD (n=10) and at baseline in volunteers (n=12). Results were further validated by pyrosequencing in representative cohort of patients on a VLCKD (n=18) and correlated with gene expression.
After weight reduction by VLCKD, differences were found at 988 CpG sites (786 unique genes). The VLCKD altered methylation levels in patients with obesity had high resemblance with those from normal weight volunteers and was concomitant with a downregulation of DNA methyltransferases (DNMT)1, 3a and 3b. Most of the encoded genes were involved in metabolic processes, protein metabolism, and muscle, organ, and skeletal system development. Novel genes representing the top scoring associated events were identified, including ZNF331, FGFRL1 (VLCKD-induced weight loss) and CBFA2T3, C3orf38, JSRP1, and LRFN4 (VLCKD-induced ketosis). Interestingly, ZNF331 and FGFRL1 were validated in an independent cohort and inversely correlated with gene expression.
So, the present invention is making a clear contribution as compared to the prior art, since the molecular mechanisms underlying the potential health benefits of a ketogenic diet are still unknown. So, the present invention is showing for the first time that the methylome status indicates whether a patient suffering from obesity is responding or will respond to a treatment with a VLCKD, particularly whether an improvement of metabolic parameters has occurred in a patient suffering from obesity after the induction of nutritional ketosis by means of a treatment with VLCKD.
Consequently, the special technical feature that defines a contribution over the prior art and confers unity to the present invention is that the methylation status indicates whether a patient suffering from obesity is responding or will respond to a treatment with a VLCKD, particularly whether an improvement of metabolic parameters has occurred in a patient suffering from obesity after the induction of nutritional ketosis by means of a treatment with VLCKD.
So, the first embodiment of the present invention refers to an in vitro method for monitoring or predicting whether a patient suffering from obesity is responding or will respond to a treatment with VLCKD, which comprises determining the methylation status of at least a gene or CpG selected from Table S2, S3 or S4, wherein a statistically significant variation or deviation of level of methylation, as compared with a pre-established level of methylation, is an indication that the subject is responding or will respond to a VLCKD.
In a preferred embodiment, the present invention comprises screening and/or selecting genes whose methylation status indicates whether a patient suffering from obesity is responding or will respond to a treatment with a VLCKD, by following these steps:
In a preferred embodiment, the genes and CpG sites which are selected according to the steps a) and c) are comprised in Table 2 or Table S2 and their methylation status indicates whether a patient suffering from obesity is responding or will respond to VLCKD giving rise to both weight loss and nutritional ketosis induction, and/or the genes and CpG sites which are selected according to the steps b) and c) are comprised in Table 3 or Table S3 and their methylation status indicates whether a patient suffering from obesity is responding or will respond to VLCKD due to the induction of nutritional ketosis.
In a preferred embodiment, the present invention refers to a method for monitoring or predicting whether a patient suffering from obesity is responding or will respond to VLCKD giving rise to both weight loss and nutritional ketosis induction, which comprises determining the methylation status of at least a gene selected from Table 2 or Table S2, wherein a statistically significant variation or deviation of level of methylation, as compared with a pre-established level of methylation, is an indication that the subject is responding or will respond to a VLCKD.
In a preferred embodiment, the methylation status of the genes is determined in at least a CpG site selected from Table 2 or Table S2.
In a preferred embodiment, the present invention refers to a method for monitoring or predicting whether an improvement of metabolic parameters has occurred in a patient suffering from obesity after the induction of nutritional ketosis by means of a treatment with a VLCKD, which comprises determining the methylation status of at least a gene selected from Table 3 or Table S3 in a biological sample obtained from the patient, wherein a statistically significant variation or deviation of level of methylation, as compared with a pre-established level of methylation, is an indication that ketosis reduction has occurred.
In a preferred embodiment, the methylation status of the genes is determined in at least a CpG site selected from Table 3 or Table S3.
In a preferred embodiment, an overall hypomethylation of the genes is observed when the patient is responding or will respond to the treatment with a VLCKD.
In a preferred embodiment, the methylation status detection is conducted by means of a technique selected from the group consisting of: methylation specific PCR, bisulfite sequencing, techniques based on restriction-digestion, pyrosequencing, assay ChIP-on-chip, differential conversion, differential restriction and/or differential weight of site(s) methylated.
In a preferred embodiment, the biological sample isolated from the patient is whole blood, preferably blood leucocytes.
The second embodiment of the present invention refers to the in vitro use of the methylation status of at least a gene selected from Table S2, S3 or S4 for monitoring or predicting whether a patient suffering from obesity is responding or will respond to VLCKD.
In a preferred embodiment, the present invention refers to the in vitro use of the methylation status of at least a gene selected from Table 2 or Table S2 for monitoring or predicting whether a patient suffering from obesity is responding or will respond to VLCKD giving rise to both weight loss and nutritional ketosis induction.
In a preferred embodiment, the present invention refers to the in vitro use of the methylation status of at least a CpG site selected from Table 2 or Table S2.
In a preferred embodiment, the present invention refers to the in vitro use of the methylation status of at least a gene selected from Table 3 or Table S3 for monitoring or predicting whether an improvement of metabolic parameters has occurred in a patient suffering from obesity after the induction of nutritional ketosis by means of a treatment with a VLCKD.
In a preferred embodiment, the present invention refers to the in vitro use of the methylation status of at least a CpG site selected from Table 3 or Table S3.
On the other hand, the present invention also refers to a method for detecting hypermethylation or hypomethylation in at least a gene selected from Tables 2, S2, 3, S3 or S4 which comprises: a) obtaining DNA from the subject, b) detecting a hypermethylation or hypomethylation in CpG sites selected from Tables 2, S2, 3, S3 or S4, wherein said (b) detecting is conducted by a technique selected from the group consisting of methylation specific PCR, bisulphite sequencing, techniques based on restriction-digestion, pyrosequencing, assay ChIP-on-chip, differential conversion, differential restriction and differential weight of site(s) methylated.
The present invention also refers to a computer-implemented invention, wherein a processing unit (hardware) and a software are configured to: Receive methylation level values of any of the genes selected from Tables 2, S2, 3, S3 or S4; process the methylation level values received for finding substantial variations or deviations; and provide an output through a terminal regarding the variation or deviation of the methylation level, wherein the variation or deviation of the methylation level indicates whether a patient suffering from obesity is responding or will respond to a treatment with a VLCKD, particularly whether an improvement of metabolic parameters has occurred in a patient suffering from obesity after the induction of nutritional ketosis by means of a treatment with VLCKD.
The last embodiment of the present invention refers to a method for treating a patient suffering from obesity with VLCKD, wherein the method comprises a first step of predicting whether the patient will respond to VLCKD by determining the methylation status of a least a gene selected from Table 2, S2, 3, S3 or S4, according to the method herein described.
For the purpose of the present invention the following abbreviation list is included:
For the purpose of the present invention the following terms are defined:
The DNA and RNA for methylation and gene expression assays were isolated from blood samples of patients from a 6-month nutritional intervention study performed at the Endocrinology and Nutrition Department of the Hospital Clinico, Universitario of Valladolid; the patients were receiving treatment for obesity. In addition, samples from a group of healthy volunteers were also analyzed. The inclusion criteria were age between 18 to 65 years, body mass index (BMI)≥30 kg/m2, stable body weight over the previous 3 months, a desire to lose weight, and a history of failed dietary efforts. The main exclusion criteria were thyroid alteration, diabetes mellitus, obesity induced by other endocrine disorders or drugs, and participation in any active weight-loss program in the previous 3 months. In addition, patients with previous bariatric surgery, reported or suspected abuse of narcotics or alcohol, severe depression or any other psychiatric disease, severe hepatic insufficiency, any type of renal insufficiency or gout episodes, nephrolithiasis, neoplasia, previous instances of cardiovascular or cerebrovascular disease, uncontrolled hypertension, orthostatic hypotension, and hydroelectrolytic or electrocardiographic alterations were excluded. Females who were pregnant, breastfeeding, or intending to become pregnant and those with child-bearing potential who were not using adequate contraceptive methods were also excluded. Apart from obesity and metabolic syndrome, participants were generally healthy individuals. Under these criteria, 21 patients with obesity and 12 volunteers with normal weight were included in this study. The study protocol was in accordance with the Declaration of Helsinki and was approved by the Ethics Committee for Clinical Research of Hospital Clinico Universitario de Valladolid, Spain (C.I: 40/13, PNK-DHA2013-01). Participants provided written informed consent before any intervention related to the study. Participants received no monetary incentives.
Patients included in this study derived from a randomized clinical trial investigating the effect of docosahexaenoic acid (DHA) supplementation in a very low-calorie ketogenic diet. The clinical trial consisted in two arms: one arm where patients follow a VLCKD and other arms where patients followed a VLCKD+DHA. Nutritional intervention was based on a commercial weight-loss program (PNK method®). Briefly, the intervention included an evaluation by the specialist physician conducting the study, an assessment by an expert dietician, and exercise recommendations. This method is based on high-biological-value protein preparations obtained from cow's milk, soy, avian eggs, green peas, and cereals. Each protein preparation contained 15 g protein, 4 g carbohydrates, 3 g fat, and provided 90-100 kcal. The VLCKD+DHA arm was supplemented with 500 mg DHA. The weight-loss program has five steps and adheres to the most recent guidelines of the EFSA (2015) on total carbohydrate intake. The first three steps consist of a VLCKD (600-800 kcal/day) that is low in carbohydrates (<50 g daily from vegetables) and lipids (only 10 g of olive oil per day). The amount of high biological-value proteins ranged between 0.8 and 1.2 g per kg of ideal body weight to ensure that patients were meeting their minimum bodily requirements and to prevent the loss of lean mass. In step 1, the patients ate high-biological-value protein preparations five times a day and vegetables with low glycemic indices. In step 2, one of the protein servings was substituted with a natural protein (e.g., meat or fish) either at lunch or at dinner. In step 3, a second serving of low-fat natural protein was substituted for the second serving of biological protein preparation. Throughout these ketogenic phases, supplements of vitamins and minerals, such as K, Na, Mg, Ca, and omega-3 fatty acids, were provided in accordance with international recommendations. These three steps were maintained until the patient lost the target amount of weight, ideally 80%. Because of this, the ketogenic steps varied in time depending on the individual and the weight-loss target. The total ketosis state lasted for a maximum of 60 days. In either step 4 or 5, ketosis was ended by the physician in charge of the patient based on the amount of weight lost, and the patient began a low-calorie diet (800-1500 kcal/day). At this point, the patients underwent a progressive incorporation of different food groups and participated in a program of alimentary re-education to guarantee long-term maintenance of the weight loss. The maintenance diet consisted of an eating plan balanced for carbohydrates, protein, and fat. Depending on the individual, calories consumed ranged between 1500 and 2000 kcal/day, with the goal of maintaining the weight loss and promoting a healthy lifestyle. During this study, patients followed the steps of the method until they reached the target weight, or up to a maximum of 4 months of follow-up, although patients remained under medical supervision for the following months. Patients visited the research team every 15±2 days to evaluate adherence and potential side effects. Complete anthropometry, body composition, and biochemical assessments were performed at four of the visits, which were determined according to the evolution of each patient through the steps of ketosis and weight loss: Visit 1 (Baseline), visit 2 (Maximum Ketosis), visit 3 (Reduced Ketosis) and visit 4 (Endpoint). DNA methylation and gene expression were performed at visits 1, 2, and 4.
In all visits, patients received dietary instructions, individual supportive counsel, and encouragement to exercise on a regular basis using a formal exercise program. Additionally, a program of reinforcement telephone calls was instituted, and a phone number was provided to all participants to address any concerns.
All anthropometric measurements were performed after an overnight fast (8 to 10 hours) under resting conditions in duplicate and performed by well-trained health workers. At each visit, patients were weighed on the same calibrated scale (Seca 200 scale, Medical Resources, EPI Inc OH, USA). BMI was calculated as body weight in kg, divided by the square of body height in meters (BMI=weight (kg)/height2 (m). Waist circumference (WC) was measured using a standard flexible non-elastic metric tape placed over the midpoint between the last rib and the iliac crest, with the patient standing and exhaling.
Ketosis was determined by measuring ketone bodies, specifically β-hydroxy-butyrate (β-OHB), in capillary blood using a portable meter (GlucoMen LX Sensor, A. Menarini Diagnostics, Neuss, Germany; sensitivity <0.2 mmol/1). As with anthropometric assessments, all determinations of capillary ketonemia were made after an overnight fast of 8 to 10 hours. These measurements were performed daily by each patient during the entire VLCKD, and the corresponding values were reviewed using machine memory by the research team to control adherence. Additionally, β-OHB levels were determined at each visit by the physician in charge of the patient.
DNA from fresh-frozen (FF) blood samples was isolated using a standard phenol-chloroform/proteinase-k protocol according to the manufacturer's instructions, with slight modifications. Genomic DNA was isolated from leukocytes using the MasturPure™ DNA purification kit (Epicentre Biotechnologies, Madison, WI, USA). The isolated DNA was treated with RNase A for 1 h at 45° C. All DNA samples were quantified using the fluorometric method (Quan-iT PicoGreen DsDNA Assay, Life Technologies) and were assessed for purity using a NanoDrop (Thermo Scientific) to determine 260/280 and 260/230 ratio measurements. The integrity of the FF DNA was verified by electrophoresis in 1.3% agarose gel. DNA (500 ng) was bisulfite converted using the EZ DNA methylation kit Methylation-Gold (Zymo Research, CA, USA) according to the manufacturer's instructions, which converts non-methylated cytosine into uracil.
High-quality DNA samples (500 ng) obtained from blood leukocytes of patients included in the VLCKD+DHA arm of the clinical trial (discovery cohort; n=10 patients, 3 paired samples/patient) were selected for bisulfite conversion (Zymo Research; EZ-96 DNA Methylation™ Kit) and hybridization to Infinium MethylationEPIC BeadChip (Illumina) following the Illumina Infinium HD methylation protocol. DNA quality checks, bisulfite modification, hybridization, data normalization, statistical filtering, and value calculations were performed as previously described. Whole-genome amplification and hybridization were then performed on a BeadChip followed by single-base extension and analysis on a HiScan SQ module (Illumina) to assess cytosine methylation states. The annotation of CG islands (CGIs) used the following categorization: 1) shore, for each of the 2-kb sequences flanking a CGI; 2) shelf, for each of the 2-kb sequences next to a shore; and 3) open sea, for DNA not included in any of the previous sequences or in CGIs. The transcription start site 200 and the transcription start site 1500 indicate regions either 200 or 1500 bp from the transcription start site, respectively.
Pyrosequencing was used to assess selected markers in 18 patients (validation cohort: (n=7 derived from the discovery cohort and n=11 from an independent cohort of patients; 3 paired samples/patient). DNA samples analyzed in the validation cohort were derived from patients included in the two arms of the clinical trial and merged for the statistical analysis (VLCKD: n=10; VLCKD+DHA: n=8). The primer sequences used in this analysis were designed using Qiagen's PyroMark Assay Design 2.0 software to hybridize to CpG-free sites to ensure methylation-independent amplification. Genomic DNA was isolated from FF blood leukocytes using the MasturPure™ DNA purification kit (Epicentre Biotechnologies, Madison, WI, USA), according to the manufacturer's instructions. DNA methylation analyses were performed using bisulfite-treated DNA (Zymo Research; EZ-96 DNA Methylation™ Kit) followed by a highly quantitative analysis based on PCR-based pyrosequencing using the PyroMark Q24 System version 2.0.7 (Qiagen). Methylation level was expressed as the percentage of methylated cytosine over the sum of methylated and unmethylated cytosines. Non-CpG cytosine residues were used as built-in controls to verify bisulfite conversion. The values are expressed as the mean for all sites. We also included human non-methylated and methylated DNA set as controls in each run (Zymo Research). The inter-assay precision (% CV) was <2.5%, intra-assay (% CV) was <1.0%.
RNA from blood leukocytes (n=18 patients) was extracted using Trizol (Invitrogen) according to the manufacturer's recommendations. The RNA concentrations were measured with a Nanodrop 2000 spectrophotometer (Thermo Scientific). From total extracted RNA, 2 μg were DNase treated using a DNA-free kit as a template (Ambion) to generate first-strand cDNA synthesis using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Real-time quantitative polymerase chain reaction (qRT-PCR) was performed using TaqMan Universal PCR Master Mix, TaqMan Probes (Applied Biosystems), and the Step OnePlus Real-Time PCR System (Applied Biosystems). All experiments were performed in duplicate, and gene expression levels were normalized to the levels of housekeeping gene GAPDH. The fold change in gene expression was calculated using the 2−ΔΔCt relative quantitation method according to the manufacturer's guidelines (Applied Biosystems), and data are reported as the geometric mean (SEM). qRT-PCR experiments were performed in compliance with the MIQE (Minimum Information for Publication of Quantitative Real-Time PCR Experiments) guidelines (http://www.rdml.org/miqe).
The sample size of the current study was calculated to detect differences for methylation levels taking into account published values of epigenome-wide analysis in the field of obesity. The interventional differences were examined in two independent cohorts. Microarray-based DNA methylation analysis was performed in the discovery cohort (n=10 patients; 3 paired samples/patient), and then the identified genes were validated in an independent cohort of patients (validation cohort; n=18 patients; 3 paired samples/patient). Finally, the association between DNA methylation level of the identified CpG sites and the anthropometric or biochemical parameters was assessed in the global cohort of patients included in this study (n=28). The methylation level of each cytosine was expressed as a β value, which was calculated as the fluorescence intensity ratio of the methylated to the unmethylated version of the probe. β values ranged between 0 (unmethylated) and 1 (completely methylated) according to the combination of the Cy3 and Cy5 fluorescence intensities. Color balance adjustment and normalization were performed to normalize the samples between the two-color channels using Genome Studio Illumina software (V2010.3). Genome Studio normalizes data using different internal controls that are present on the Infinium MethylationEPIC BeadChip. This software also normalized data depending on internal background probes. β values with detected p-values>0.01 were considered to fall below the minimum intensity and threshold, and these CpGs were consequently removed from further analysis. Additionally, probes that contained single nucleotide polymorphisms (SNPs) at the 10 bp 3′ end of the interrogating probe were filtered out. To identify consistent patterns of DMCpGs due to the nutritional intervention, a linear model was fitted using a B-spline approximation. The three linear models were fitted: Model 1 was fitted by including the three points of the nutritional intervention to evaluate the general effect of VLCKD; Model 2 including baseline and maximum ketosis to evaluate the effect of ketosis and weight loss; Model 3 including methylation levels at maximum ketosis and endpoint to evaluate the effect of only weight loss, without ketosis. P values were adjusted for multiple comparisons using the false discovery rate (FDR) procedure of Benjamini and Hochberg, and results were considered statistically significant when FDR<0.10. Additionally, we applied a threshold for the significant sites based on the mean difference between visits with a minimum p value change of ±0.02. Euclidean cluster analysis of significant CpGs was performed using a heatmap function. The global methylation level was compared between the nutritional intervention visits by univariant ANOVA and a Bonferroni post-hoc analysis. All of the aforementioned statistical analyses were performed using R software (version 3.2.0). To estimate enrichment in biological processes, a hypergeometric test was performed using the GOstats package on the biological processes defined by gene ontology (GO). This analysis detected significant over-representation of GO terms in one set (i.e., list of identified genes) with respect to the entire genome. GO terms with an adjusted p-value<0.05 were considered significant. With SPSS version 21.0 software (SPSS Inc., Chicago, IL) for Windows XP (Microsoft, Redmond, WA), the genomic distribution of the differentially methylated CpGs was compared with the distribution of the CpGs from all analyzed sites on the Infinium MethylationEPIC BeadChip. P values were computed using the chi-square test to determine over- or under-representation of the CpGs. The potential association between anthropometric or biochemical parameters and DNA methylation levels (p-values) was evaluated using the Spearman coefficient test. Differences in DNA methylation levels and expression of the identified genes during the time-course of the intervention and between the nutritional intervention visits were assessed by the non-parametric tests, Kruskal Wallis and Mann-Whitney U, respectively. P≤0.05 was considered statistically significant.
Samples from a total of 21 patients who followed the nutritional intervention based on a VLCKD were compared with samples from 12 healthy volunteers with normal weight and evaluated in this study. We first evaluated the discovery cohort (n=10 participants with obesity who followed a VLCKD+DHA (n=5 women) and n=12 (6 women) volunteers with normal weight). An extended validation cohort composed of 11 patients (7 women) with obesity that followed a VLCKD+DHA or a VLCKD-DHA was also analyzed. Statistically significant differences were not observed between either cohort in age, gender, height, body weight, BMI, waist circumference, ketosis, or the response to weight loss treatment (Table 1). Differences statistically significant were only detected in body weight, BMI and waist circumference between patients with obesity and subjects with normal weight (Table 1). All patients lost weight after nutritional intervention (21.8±4.9/o), together with reductions in BMI (21.9±5.1%) and waist circumference (19.3±4.4%).
DNA methylation profiles of blood leukocytes involving approximately 850 thousand CpGs were analyzed after VLCKD intervention. This analysis revealed statistically significant differences (cut-off point Δ≥0.02; FDR≤0.10) at 988 CpG sites, from a total of 739,222 valid CpGs (Table S2). The differentially methylated CpGs were mostly characterized as changes towards CpG hypomethylation occurring after nutritional intervention, in both total DMCpGs (
Interestingly, most differentially methylated genes belonged to a network significantly enriched in protein interactions (p<0.001) according to STRING analysis (
An analysis comparing baseline (day 0) with maximum ketosis (day 30) yielded 1365 DMCpGs. With respect to all CpGs analyzed, these CpGs were found mainly in the open sea (
We used pyrosequencing, a technique that is most feasible for studies of patients in hospitals, to evaluate the DNA methylation levels of ZNF331 and FGFRL1 in an independent cohort of samples from leukocytes (validation cohort; n=18 patients who follow a VLCKD+DHA or VLCKD-DHA merged Table 1). Statistically significant differences were found in the methylation levels after nutritional intervention with respect to baseline (
aStatistically significant differences compared with control Normal weight in discovery cohort.
bStatistically significant differences compared with Baseline in both cohorts.
cStatistically significant differences compared with Maximum Ketosis in both cohorts.
| Number | Date | Country | Kind |
|---|---|---|---|
| 21382469.1 | May 2021 | EP | regional |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2022/063669 | 5/20/2022 | WO |
