Use of biomarkers in therapy with bifidobacteria

Abstract

The present invention relates to a method of identifying a subject having an increased probability of a beneficial clinical response to administration to the subject of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium by measuring the levels of certain specific biomarkers in the subject.

Description

Technical Field

[0001] The present invention relates to a method of identifying subjects having an increased probability of having a beneficial clinical response to administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium to said subject by measuring the levels of certain specific biomarkers in the subject. Background Art

[0002] Regulation of energy balance is essential for the survival of an organism. When nutrients are freely available, they are stored to account for low energy intake during periods of scarcity. In the normal state, the brain, together with energy storage tissues, regulates energy balance by reducing energy intake when energy stores are crowded. If the energy storage system is disturbed, the brain is no longer able to maintain energy balance. This can result in an inability to maintain adequate energy intake, often manifested as frailty in the elderly population, or to excessive energy storage in adipose tissue and even obesity.

[0003] Body mass index (BMI) is a simple measure of weight for height that is commonly used to classify the weight status of adults. It is defined as a person's weight in kilograms divided by the square of their height in meters (kg / m2).

[0004] The World Health Organization (WHO) defines a BMI below 18.5 as underweight; a BMI between 18.5 and 24.99 as normal weight; a BMI greater than or equal to 25 as overweight; and a BMI greater than or equal to 30 as obese.

[0005] Overweight and obesity are defined as abnormal or excessive fat accumulation. Underweight is defined as body weight that is too low to maintain normal body functions. Both underweight and overweight may lead to disturbances in metabolic function (e.g., hormonal signaling).

[0006] Overweight and obesity were once considered a problem of high-income countries, but are now on the rise in low- and middle-income countries, particularly in urban settings. In developing countries with emerging economies (classified as low- and middle-income countries by the World Bank), the rate of increase in childhood overweight and obesity is more than 30% higher than in developed countries.

[0007] Worldwide, overweight and obesity are associated with more deaths than underweight. Most groups in the world live in countries where overweight and obesity kill more people than underweight (this includes all high-income and most middle-income countries). The underlying cause of obesity and overweight is an energy imbalance between calories consumed and calories expended.

[0008] The most common consequences of being overweight and obese are diseases such as: cardiovascular disease (mainly heart disease and stroke), which was the leading cause of death in 2012; diabetes; musculoskeletal disorders (especially osteoarthritis - a highly disabling degenerative disease of the joints); and some cancers (endometrial, breast and colon).

[0009] The risk of these diseases increases with increasing BMI.

[0010] Childhood obesity is associated with a higher likelihood of obesity, premature death and disability in adulthood. But in addition to increased future risks, obese children also experience breathing difficulties, increased risk of fractures, high blood pressure, early markers of cardiovascular disease, insulin resistance and psychological effects.

[0011] Overweight and obesity and their related diseases are largely preventable, and the food industry can play a significant role in combating obesity.

[0012] It is well known that dysfunctional energy regulation can lead to various metabolic disorders, including obesity. The connection between the gut microbiota, energy homeostasis, and the pathogenesis of metabolic disorders is now well established (Amabebe et al. 2020).

[0013] The 2015 publication by Waterson and Horvath, “Neuronal regulation of Energy Homeostasis: Beyond the Hypothalamus and feeding,” highlighted the importance of the brain in maintaining energy homeostasis and its relationship to obesity and other metabolic diseases.

[0014] Probiotics are live microorganisms that, when administered in adequate amounts, confer health benefits on the host, while prebiotics are substrates selectively utilized by host microorganisms that confer health benefits. Preliminary evidence suggests that oral administration of certain probiotics significantly affects body composition or weight management in clinical intervention studies (Stenman et al., 2016), suggesting a link between gut microbiota and human fat regulation. Studies have shown that the probiotic strain Bifidobacterium animalis ssp. lactis 420 (B420) reduces human fat accumulation (Stenman et al., 2016).

[0015] Given the potential for some probiotics and prebiotics to improve weight management in the broader population, it is important to be able to better predict which subjects within the broader population will respond better to administration of these probiotics and prebiotics.

[0016] The present invention aims to provide a solution to the problems of the prior art. Summary of the invention

[0017] In one aspect, the present invention relates to a method of identifying a subject having an increased probability of having a beneficial clinical response to the administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium, the method comprising the steps of:

[0018] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1, bile acid GLCA, bile acid LCA, bacteria Coprococcus, bacteria Ruminococcus, and / or bacteria Akkermansia, and

[0019] ii. comparing said level to a threshold value,

[0020] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0021] In another aspect, the present invention relates to a method of identifying a subject having an increased probability of having a beneficial clinical response to the administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium, the method comprising the steps of:

[0022] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, Unclassified Clostridiales-Incertae Sedis XIII and Eubacterium coprostanoligenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, Unclassified Clostridiales-Incertae Sedis XIII and Eubacterium coprostanoligenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and

[0023] ii. comparing said level to a threshold value,

[0024] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0025] In another aspect, the present invention relates to the use of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium for at least one of: managing weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing android fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome in a subject, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by:

[0026] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1, bile acid GLCA, bile acid LCA, bacteria Coprococcus, bacteria Ruminococcus, and / or bacteria Akkermansia, and

[0027] ii. comparing said level to a threshold value,

[0028] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0029] In another aspect, the present invention relates to the use of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium for at least one of: managing weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome in a subject, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by:

[0030] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and

[0031] ii. comparing said level to a threshold value,

[0032] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0033] In a further aspect, the present invention relates to a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium for use in a subject for managing body weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by:

[0034] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1, bile acid GLCA, bile acid LCA, bacteria Coprococcus, bacteria Ruminococcus, and / or bacteria Akkermansia, and

[0035] ii. comparing said level to a threshold value,

[0036] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0037] In a further aspect, the present invention relates to a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium for use in a subject for managing body weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by:

[0038] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and

[0039] ii. comparing said level to a threshold value,

[0040] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0041] In another aspect, the present invention relates to a method for managing body weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome in a subject in need thereof, the method comprising administering to the subject a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by:

[0042] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1, bile acid GLCA, bile acid LCA, bacteria Coprococcus, bacteria Ruminococcus, and / or bacteria Akkermansia, and

[0043] ii. comparing said level to a threshold value,

[0044] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0045] In another aspect, the present invention relates to a method for managing body weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome in a subject in need thereof, the method comprising administering to the subject a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by:

[0046] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and

[0047] ii. comparing said level to a threshold value,

[0048] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0049] In another aspect, the present invention relates to a method for managing body weight, such as reducing BMI, reducing blood sugar levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing male-type fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome in a subject in need thereof, the method comprising:

[0050] i. Have the subject perform more than 7,000 steps of daily personal activity or equivalent physical activity; and

[0051] ii. administering a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium to a subject who has obtained an activity under i), the subject has an increased probability of having a beneficial clinical response to the administration of said bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium.

[0052] In some embodiments, the bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium is as described herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1Human subjects BMI (kg / m2) (visit 8 minus visit 2) plotted against total hPAI1 levels in blood (pg / mL). The gray markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0054] Figure 2 Human subjects BMI (kg / m2) (visit 8 minus visit 2) plotted against the amount of glycolithocholic acid levels in the blood (GLCA, μmol / L). The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0055] Figure 3 Human subjects BMI (kg / m2) (visit 8 minus visit 2) plotted against the amount of lithocholic acid levels in the blood (LCA, μmol / L). The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0056] Figure 4 Human subject BMI (kg / m2) (visit 8 minus visit 2) plotted against the relative abundance of Coprococcus. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0057] Figure 5 Human subject BMI (kg / m2) (visit 8 minus visit 2) plotted against the relative abundance of Ruminococcus. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0058] Figure 6 Human subject BMI (kg / m2) (visit 8 minus visit 2) plotted against the relative abundance of Akkermansia. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0059] Figure 7 Trunk fat (g) obtained from DXA scans of human subjects (visit 8 minus visit 2) plotted against total hPAI1. Grey markers and linear trend line are data from B420, while black markers and linear trend line are data from the placebo group. Dashed line is threshold.

[0060] Figure 8 Trunk fat (g) obtained from DXA scans of human subjects (visit 8 minus visit 2) plotted against the amount of glycolithocholic acid. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0061] Fig. 9 Trunk fat (g) obtained from DXA scans of human subjects (visit 8 minus visit 2) plotted against the amount of lithocholic acid. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0062] Fig.10 Trunk fat (g) from DXA scans of human subjects (visit 8 minus visit 2) plotted against the relative abundance of Coprococcus spp. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0063] Fig.11 Trunk fat (g) from DXA scans of human subjects (visit 8 minus visit 2) plotted against the relative abundance of Ruminococcus spp. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0064] Fig.12 Trunk fat (g) from DXA scans of human subjects (visit 8 minus visit 2) plotted against the relative abundance of Akkermansia. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0065] Fig.13 . Plot of the amount of male-type fat (g) (visit 8 minus visit 2) in human subjects obtained by DXA scans plotted against the amount of hPAI1. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0066] Fig.14. Plot of male-type fat (g) (visit 8 minus visit 2) versus the amount of glycolithocholic acid obtained by DXA scans in human subjects. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0067] Fig.15 .Androgenetic fat (g) (visit 8 minus visit 2) in human subjects plotted against the amount of lithocholic acid obtained by DXA scans. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0068] Fig.16 . Plot of the relative abundance of Coprococcus spp. in male-type fat (g) from DXA scans of human subjects (visit 8 minus visit 2). The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0069] Fig.17 . Plot of the relative abundance of Ruminococcus spp. in male-type fat (g) from DXA scans of human subjects (visit 8 minus visit 2). The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0070] Fig.18 . Plot of male-type fat (g) obtained from DXA scans in human subjects (visit 8 minus visit 2) against the relative abundance of Akkermansia spp. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0071] Fig.19 Total fat (g) in human subjects obtained by DXA scan (visit 8 minus visit 2) plotted against the amount of hPAI1. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0072] Fig. 20 Total fat (g) (visit 8 minus visit 2) in human subjects plotted against the amount of glycolithocholic acid obtained by DXA scan. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0073] Fig.21 Total fat (g) obtained from DXA scans of human subjects (visit 8 minus visit 2) plotted against the amount of lithocholic acid. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0074] Fig. 22 Total fat (g) from DXA scans in human subjects (visit 8 minus visit 2) plotted against the relative abundance of Coprococcus spp. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0075] Fig.23 Total fat (g) from DXA scans of human subjects (visit 8 minus visit 2) plotted against the relative abundance of Ruminococcus spp. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0076] Fig.24 Total fat (g) from DXA scans in human subjects (visit 8 minus visit 2) plotted against the relative abundance of Akkermansia. The grey markers and linear trend line are data from B420, while the black markers and linear trend line are data from the placebo group. The dashed line is the threshold.

[0077] Fig.25 . Graph of DXAFMASS (v5-v2) versus relative amount Lipid_ESP PC(36:4) in serum at v2 for both B420 and placebo treatments. Prospectively, the slope is lower for B420 compared to placebo, meaning that for B420 treatment, Lipid_ESP PC(36:4) at high values ​​increases the probability of total fat loss.

[0078] Retrospectively, high values ​​of Lipid_ESP PC(36:4) with B420 treatment were associated with total fat loss in responders but not in non-responders. The dashed line is the threshold.

[0079] Fig.26. Graph of DXAFMASS (v5-v2) versus relative amount Lipid_ESP PC(32:1) in serum at v2 for both B420 and placebo treatments. Prospectively, the slope is lower for B420 compared to placebo, meaning that for B420 treatment, Lipid_ESP PC(32:1) at high values ​​increases the probability of total fat loss.

[0080] Retrospectively, high values ​​of Lipid_ESP PC(32:1) with B420 treatment were associated with total fat loss in responders but not in non-responders. The dashed line is the threshold.

[0081] Fig. 27 .Graph of DXAFMASS (v5-v2) for both B420 and placebo treatments versus the relative amount Lipid_ESP PE (38:4) in serum at v2. Prospectively, the slope for B420 is lower compared to placebo, meaning that for B420 treatment, high values ​​of Lipid_ESP PE (38:4) increase the probability of total fat loss. Retrospectively, high values ​​of Lipid_ESP PE (38:4) for B420 treatment are associated with total fat loss in responders, but not in non-responders. The dashed line is the threshold.

[0082] Fig.28 . Graph of DXAFMASS (v5-v2) versus the relative amount of Lipid_ESP SM (d40:1) in serum at v2 for both B420 and placebo treatments. Prospectively, the slope is lower for B420 compared to placebo, meaning that for B420 treatment, Lipid_ESP SM (d40:1) at high values ​​increases the probability of total fat loss.

[0083] Retrospectively, high values ​​of Lipid_ESP SM (d40:1) with B420 treatment were associated with a reduction in total fat in responders but not in non-responders. The dashed line is the threshold.

[0084] Fig.29 . Graph of DXAFMASS (v5-v2) versus the relative amount of Lipid_ESN PE(36:4) in serum at v2 for both B420 and placebo treatments. Prospectively, the slope is lower for B420 compared to placebo, meaning that for B420 treatment, Lipid_ESN PE(36:4) at high values ​​increases the probability of total fat loss.

[0085] Retrospectively, high values ​​of Lipid_ESN PE(36:4) with B420 treatment were associated with a reduction in total fat in responders but not in non-responders. The dashed line is the threshold.

[0086] Fig.30 . Graph of DXAFMASS (v5-v2) versus the relative amount of Lipid_ESN PI (40:4) in serum at v2 for both B420 and placebo treatments. Prospectively, the slope is lower for B420 compared to placebo, meaning that for B420 treatment, Lipid_ESN PI (40:4) at high values ​​increases the probability of total fat loss.

[0087] Retrospectively, high values ​​of Lipid_ESN PI(40:4) with B420 treatment were associated with total fat loss in responders but not in non-responders. The dashed line is the threshold.

[0088] Fig.31 . Graph of DXAFMASS (v5-v2) versus the relative amount of Lipid_ESN PE(40:5) in serum at v2 for both B420 and placebo treatments. Prospectively, the slope is lower for B420 compared to placebo, meaning that for B420 treatment, Lipid_ESN PE(40:5) at high values ​​increases the probability of total fat loss.

[0089] Retrospectively, high values ​​of Lipid_ESN PE(40:5) with B420 treatment were associated with a reduction in total fat in responders but not in non-responders. The dashed line is the threshold.

[0090] Fig.32 . Graph of DXAFMASS (v5-v2) versus BA (ISO-LCA) in feces at v2 for both B420 and placebo treatments. Prospectively, the slope was lower for B420 compared to placebo, meaning that for B420 treatment, BA (ISO-LCA) at high values ​​increased the probability of total fat loss.

[0091] Retrospectively, high values ​​of BA (ISO-LCA) with B420 treatment were associated with a reduction in total fat in responders but not in non-responders. The dashed line is the threshold.

[0092] Fig.33 . Graph of DXAFMASS (v5-v2) versus BA (LCA) in feces at v2 for both B420 and placebo treatments. Prospectively, the slope was lower for B420 compared to placebo, meaning that BA (LCA) at high values ​​increased the probability of total fat loss for B420 treatment.

[0093] Retrospectively, high values ​​of BA(LCA) with B420 treatment were associated with a reduction in total fat in responders but not in non-responders. The dashed line is the threshold.

[0094] Fig.34 . Plot of DXAFMASS (v5-v2) for both B420 and placebo treatments versus relative abundance taxa (Bacteria_Firmicutes_Clostridium_Clostriales_Clostriales_Undetermined XIII_Aminobiformis_Aminobiformis) in feces at v2. Prospectively, the slope was lower for B420 compared to placebo, meaning that for B420 treatment, high values ​​of (Bacteria_Firmicutes_Clostridium_Clostriales_Clostriales_Undetermined XIII_Aminobiformis_Aminobiformis) increased the probability of total fat loss.

[0095] Retrospectively, high values ​​for (Bacteria_Firmicutes_Clostridium_Clostridiumales_Clostridiumales_Undefined XIII_Aminoacidioides_Aminoacidiolyticus) treated with B420 were associated with a reduction in total fat in responders but not in non-responders. The dashed line is the threshold.

[0096] Fig.35 . Graph of GLUC (v5-v2) for both B420 and placebo treatments versus relative abundance taxa (Bacteria_Firmicutes_Clostridium_Clostriales_Clostriales_Undetermined XIII_Unclassified Clostridiales_Undetermined XIII_Unclassified Clostridiales_Undetermined XIII) in feces at v2. Prospectively, the slope for B420 was lower compared to placebo, meaning that for B420 treatment, high values ​​of (Bacteria_Firmicutes_Clostridium_Clostriales_Clostriales_Undetermined XIII_Unclassified Clostridiales_Undetermined XIII_Unclassified Clostridiales_Undetermined XIII) increased the probability of glucose reduction.

[0097] Retrospectively, high values ​​for (Bacteria_Firmicutes_Clostridium_Clostriales_Clostriales_Undetermined status XIII_Unclassified Clostridiales_Undetermined status XIII_Unclassified Clostridiales_Undetermined status XIII) treated with B420 were associated with glucose reduction in responders but not in non-responders. The dashed line is the threshold.

[0098] Fig.36 . Graph of GLUC (v5-v2) for both B420 and placebo treatments versus relative abundance taxa (Bacteria_Firmicutes_Clostridium_Clostriales_Eubacteriaceae_Eubacterium_Eubacterium coproducens) in feces at v2. Prospectively, the slope for B420 was lower compared to placebo, meaning that for B420 treatment, high values ​​of (Bacteria_Firmicutes_Clostridium_Clostriales_Eubacteriaceae_Eubacterium_Eubacterium coproducens) increased the probability of glucose reduction.

[0099] Retrospectively, high values ​​for (Bacteria_Firmicutes_Clostridium_Clostriales_Eubacteriaceae_Eubacterium_Eubacterium coproducens) treated with B420 were associated with glucose reduction in responders but not in non-responders. The dashed line is the threshold.

[0100] Fig.37 . Graph of the GLUC (v5-v2) for both B420 and placebo treatments versus the relative response (relative to total peak area) of the metabolite pimelic acid in feces at v2. Prospectively, the slope is lower for B420 compared to placebo, meaning that for B420 treatment, (pimelic acid) at high values ​​increases the probability of glucose lowering.

[0101] Retrospectively, high values ​​of (pimelate) with B420 treatment were associated with glucose reduction in responders but not in non-responders. The dashed line is the threshold.

[0102] Fig.38 . Graph of GLUC (v5-v2) for both B420 and placebo treatments versus relative response (relative to total peak area) of the metabolite azelaic acid in feces at v2. Prospectively, the slope is lower for B420 compared to placebo, meaning that (azelaic acid) at high values ​​increases the probability of glucose lowering for B420 treatment.

[0103] Retrospectively, high values ​​of B420-treated (azelaic acid) were associated with glucose reduction in responders but not in non-responders. The dashed line is the threshold.

[0104] Fig.39 . Graph of GLUC (v5-v2) for both B420 and placebo treatments versus STP (AVGSTEPS) in clinical studies at v2. Prospectively, the slope is lower for B420 compared to placebo, meaning that for B420 treatment, (AVGSTEPS) at high values ​​increases the probability of glucose lowering.

[0105] Retrospectively, high values ​​of (AVGSTEPS) for B420 treatment were associated with glucose lowering in responders but not in non-responders. The dashed line is the threshold.

[0106] Fig.40 .Graph of GLUC (v5-v2) versus BA (DCA) in serum at v2 for both B420 and placebo treatments. Prospectively, the slope is lower for B420 compared to placebo, meaning that for B420 treatment, high values ​​of BA (DCA) increase the probability of glucose reduction. Retrospectively, high values ​​of BA (DCA) for B420 treatment are associated with glucose reduction in responders, but not in non-responders. The dashed line is the threshold. DETAILED DESCRIPTION

[0107] advantage

[0108] The present inventors have unexpectedly discovered that by measuring the levels of one or more biomarkers of the genera hPAI1 total, GLCA, LCA, Coprococcus, Ruminococcus and Akkermansia in a subject at baseline, it is possible to predict whether the subject will have a beneficial clinical response to the administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more of said strains of the genus Bifidobacterium, in particular the strain Bifidobacterium animalis lactis subsp. 420 (strain B420), compared to the placebo group.

[0109] The detailed aspects of the present invention are set forth below. Some detailed aspects are discussed in part in separate sections. This is for ease of reference and is not restrictive in any way. All embodiments described below are equally applicable to all aspects of the present invention, unless the context otherwise specifically provides.

[0110] bacteria

[0111] The bacteria used in the present invention are selected from the bacteria of the genus Bifidobacterium or a mixture thereof. Preferably, the Bifidobacterium used in the present invention is a Bifidobacterium that is generally recognized as safe and preferably GRAS approved. Generally recognized as safe (GRAS) is a sign data of the U.S. Food and Drug Administration (FDA): experts believe that the chemical substance or substance added to food is safe and is therefore exempt from the usual Federal Food, Drug and Cosmetic Act (FFDCA) restrictions on food additive tolerance requirements.

[0112] In particular, the bacterial strain is Bifidobacterium animalis subsp. lactis 420 (B420).

[0113] These bacterial strains are commercially available from DuPont Nutrition Biosciences Aps, Denmark.

[0114] Bacterial strain B420 has also been deposited by DuPont Nutrition Biosciences of Denmark at the Leibniz-Institut Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (DSMZ), Inhoffenstrasse 7B, 38124 Braunschweig, Germany, under the Budapest Treaty on the International Recognition of the Deposit of Microorganisms for the Purposes of Patent Procedure, where the bacterial strain is recorded under the following accession number:

[0115] strain B420 (DGCC420); deposited on June 30, 2015 under accession number DSM32073.

[0116] In a first aspect, the present invention relates to a method of identifying a subject having an increased probability of having a beneficial clinical response to the administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium, the method comprising the steps of:

[0117] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and

[0118] ii. comparing said level to a threshold value,

[0119] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0120] In the context of the present invention, a biomarker or biological marker is a measurable indicator of certain biological states or conditions of a subject. Biomarkers are measured using blood, urine or feces, and they are often used to study and predict a subject's clinical response to the administration of drugs and to the administration of other products (e.g., probiotic strains).

[0121] The bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium can be used in any form that can exert the effects described herein. For example, the bacteria can be viable, dormant, inactivated or dead bacteria. Preferably, the bacteria are viable bacteria.

[0122] One or more bacterial strains may comprise whole bacteria or may comprise bacterial components. Examples of such components include cell wall components (e.g., peptidoglycan), bacterial nucleic acids (e.g., DNA and RNA), bacterial membrane components, and bacterial structural components (e.g., proteins, carbohydrates, lipids, and combinations of these (e.g., lipoproteins, glycolipids, and glycoproteins)).

[0123] One or more bacterial strains may also include or alternatively include bacterial metabolites. In this specification, the term "bacterial metabolites" is included in the growth, survival, continuation, transshipment or existence of bacteria during the manufacture and storage of probiotic products and during the gastrointestinal transit in mammals, as a result of bacterial metabolism, all molecules produced or modified by (probiotic) bacteria. Examples include all organic acids, inorganic acids, alkalis, proteins and peptides, enzymes and coenzymes, amino acids and nucleic acids, carbohydrates, lipids, glycoproteins, lipoproteins, glycolipids, vitamins, all biologically active compounds, metabolites containing inorganic components, and all small molecules, such as nitrous acid molecules or molecules containing sulfurous acid.

[0124] Preferably, the bacteria comprises whole bacteria, more preferably comprises whole viable bacteria.

[0125] Preferably, the Bifidobacterium or Bifidobacteria used according to the present invention is a Bifidobacterium suitable for human and / or animal consumption. Those skilled in the art will readily know specific Bifidobacterium species and / or strains from the genera described herein that are used in the food and / or agricultural industry and which are generally considered suitable for human and / or animal consumption.

[0126] In the present invention, the Bifidobacterium used may be of the same species or may comprise a mixture of species and / or strains.

[0127] Suitable bacteria are selected from the following species: Bifidobacterium lactis, Bifidobacterium bifidium, Bifidobacterium longum, Bifidobacterium animalis, Bifidobacterium breve, Bifidobacterium infantis, Bifidobacterium catenulatum, Bifidobacterium pseudocatenulatum, Bifidobacterium adolescentis, and Bifidobacterium angulatum, and any combination thereof.

[0128] Preferably, the Bifidobacterium used in the present invention belongs to the species Bifidobacterium animalis. More preferably, the Bifidobacterium used in the present invention belongs to the subspecies Bifidobacterium animalis lactis.

[0129] In a particularly preferred embodiment, the bacterium used in the present invention is Bifidobacterium animalis subsp. lactis (strain) 420 (B420).

[0130] In one embodiment, the bacterium used in the present invention is a probiotic bacterium. In this specification, the term 'probiotic bacterium' is defined as covering any non-pathogenic bacteria, which, when used in sufficient amounts, imparts health benefits to the host. These probiotic strains generally have the ability to survive when passing through the upper part of the digestive tract. They are non-pathogenic, non-toxic, and exert beneficial effects on health via the ecological interaction with the resident flora in the digestive tract and the ability to affect the immune system in a positive way via "GALT" (gut-associated lymphoid tissue) on the one hand. According to the definition of probiotics, these bacteria have the ability to live through the intestine when given in sufficient quantities, but they do not cross the intestinal barrier, and therefore their main effect is induced in the lumen and / or wall of the gastrointestinal tract. Then they form a part of the resident flora during the application period. This colonization (or temporary colonization) allows probiotic bacteria to exercise beneficial effects, such as inhibiting the potential pathogenic microorganisms present in the flora and interacting with the immune system of the intestine.

[0131] In a preferred embodiment, the bacterial strain of the genus Bifidobacterium or a mixture thereof is a probiotic strain.

[0132] In another embodiment according to the present invention, the beneficial clinical response to the bacterial strain of the genus Bifidobacterium or the mixture of two or more of the strains of the genus Bifidobacterium is at least one of the following occurring in the subject: weight management, such as reducing BMI, reducing blood sugar levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing male-type fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (especially but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome.

[0133] In certain embodiments, the beneficial clinical response to said bacterial strain of the genus Bifidobacterium or a mixture of two or more of said strains of the genus Bifidobacterium is at least one of: lowering BMI, lowering blood sugar levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass.

[0134] In a specific embodiment of the present invention, when the biomarker is selected from the group consisting of total hPAI1, bile acid selected from GLCA, LCA, Iso-LCA and DCA, the biological sample is a blood sample.

[0135] In another specific embodiment of the present invention, when the biomarker is a bacterium selected from the group consisting of Coprococcus, Ruminococcus, Akkermansia, Acidaminolyticus, Clostridiales-Undetermined XIII and Eubacterium copropenes, the biological sample is a fecal sample.

[0136] In another specific embodiment of the present invention, when the biomarker is selected from pimelic acid and azelaic acid, the biological sample is a stool sample.

[0137] In another specific embodiment of the present invention, when the biomarker is a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4), the biological sample is a blood sample.

[0138] In an embodiment according to the present invention, the measured level of total hPAI1 in a biological sample obtained from a subject exceeds 48245 pg. / ml.

[0139] In another embodiment, the measured level of GLCA in a biological sample obtained from a subject exceeds 0.0070 μmol / l.

[0140] In another embodiment, the measured level of LCA in a biological sample obtained from the subject exceeds 0.0380 μmol / l.

[0141] In another embodiment, the measured level of relative abundance of Coprococcus in a biological sample obtained from the subject exceeds 0.0426.

[0142] In another embodiment, the measured level of relative abundance of Ruminococcus in a biological sample obtained from a subject exceeds 0.0631.

[0143] In another embodiment, the measured level of relative abundance of Akkermansia in a biological sample obtained from the subject exceeds 0.0062.

[0144] In another embodiment, the measured level of relative abundance of Amino Acidophilus in the biological sample obtained from said subject exceeds 0.00043.

[0145] In another embodiment, the measured level of relative abundance of unclassified Clostridiales-undetermined status XIII in the biological sample obtained from said subject exceeds 0.00018.

[0146] In another embodiment, the measured level of relative abundance of Eubacterium coproperogenum in the biological sample obtained from said subject exceeds 0.0084.

[0147] In another embodiment, the measured level of Iso-LCA in the biological sample obtained from said subject exceeds 29 μmol / l.

[0148] In another embodiment, the measured level of DCA in the biological sample obtained from said subject exceeds 0.41 nmol / ml.

[0149] In another embodiment, the measured level of the phospholipid phosphatidylcholine (36:4) in a biological sample obtained from said subject exceeds 0.064, as described herein, which is measured in relative amount, calculated as the peak area of ​​this phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode.

[0150] In another embodiment, the measured level of the phospholipid phosphatidylcholine (32:1) in the biological sample obtained from the subject exceeds 0.0037, as described herein, which is measured in relative quantity, calculated as the peak area of ​​this phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode.

[0151] In another embodiment, the measured level of the phospholipid phosphatidylethanolamine (38:4) in a biological sample obtained from the subject exceeds 0.00074, as described herein, which is measured in relative quantity, calculated as the peak area of ​​this phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode.

[0152] In another embodiment, the measured level of the phospholipid phosphatidylethanolamine (36:4) in a biological sample obtained from said subject exceeds 0.00091, as described herein, which is measured in relative quantity, calculated as the peak area of ​​that phospholipid divided by the total peak area of ​​all identified lipids in negative ionization mode.

[0153] In another embodiment, the measured level of the phospholipid phosphatidylinositol (40:4) in a biological sample obtained from the subject exceeds 0.00019, as described herein, which is measured in relative amounts, calculated as the peak area of ​​this phospholipid divided by the total peak area of ​​all identified lipids in negative ionization mode.

[0154] In another embodiment, the measured level of pimelic acid in a biological sample obtained from said subject exceeds 0.000126, which is measured as a relative amount as described herein, calculated as the peak area of ​​the ion at 125 m / z divided by the total peak area of ​​all identified peaks.

[0155] In another embodiment, the measured level of azelaic acid in a biological sample obtained from said subject exceeds 0.000135, which is measured as a relative amount as described herein, calculated as the peak area of ​​the ion at 83 m / z divided by the total peak area of ​​all identified peaks.

[0156] In another embodiment, the subject's daily activity is greater than 7000 steps, or a corresponding amount of physical activity.

[0157] In another embodiment, the measured level of pimelic acid in the biological sample obtained from said subject exceeds 0.000126.

[0158] In another embodiment, the measured level of azelaic acid in the biological sample obtained from said subject exceeds 0.000135.

[0159] According to the present invention, different analytical techniques can be used to analyze biological samples according to the present invention. One of the techniques is liquid chromatography-mass spectrometry (LC-MS), which combines the physical separation capability of liquid chromatography (or HPLC) with the mass analysis capability of mass spectrometry (MS). Another technique is gas chromatography-mass spectrometry (GC-MS), which is an analytical method that combines the characteristics of gas chromatography and mass spectrometry to identify the different substances in the sample. Another technique is nuclear magnetic resonance (NMR). These techniques are well known to those skilled in the art.

[0160] According to a particular embodiment of the invention, if the biological sample to be analyzed is a blood sample, the levels of the biomarkers are measured by LC-MS.

[0161] According to another particular embodiment, if the biological sample to be analyzed is a stool sample, the levels of the biomarkers are measured by LC-MS.

[0162] In one embodiment, the level of at least one of these biomarkers is measured prior to administering the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium to the subject.

[0163] In certain embodiments, the subject according to the present invention is overweight or obese.

[0164] In another specific embodiment, the subject according to the present invention has a BMI of more than 25.

[0165] In certain embodiments, the total amount of hPAI1 and the bile acid GLCA of a subject according to the present invention exceed a threshold value.

[0166] dose

[0167] The bifidobacterium used according to the present invention (e.g., a strain of Bifidobacterium animalis subsp. lactis, such as Bifidobacterium animalis subsp. lactis (strain) 420 (B420)) may contain from 10 6 Up to 10 12 CFU of bacteria / g of support, and more particularly from 10 8 Up to 10 12 CFU of bacteria / g of support, preferably for lyophilized form 10 9 Up to 10 12 CFU / g.

[0168] Suitably, the bifidobacterium (e.g., a strain of Bifidobacterium animalis subsp. lactis (e.g., Bifidobacterium animalis subsp. lactis (strain) 420 (B420))) may be present in an amount of from about 10 6 to about 10 12 CFU of microorganisms / dose, preferably about 10 8 to about 10 12 The term "per dose" means that this amount of microorganism is provided to the subject per day or per intake, preferably per day. For example, if the microorganism is to be administered in a food product (e.g., in yogurt), the yogurt will preferably contain from about 10 CFU of microorganism / dose. 8 Up to 10 12Alternatively, however, such an amount of microorganisms may be divided into multiple administrations, each administration consisting of a smaller amount of the microbial load - as long as the total amount of microorganisms received by the subject at any particular time (e.g., per 24-hour period) is from about 10 6 to about 10 12 CFU of microorganisms, preferably 10 8 to about 10 12 CFU of microorganisms is sufficient.

[0169] According to the present invention, the effective amount of at least one strain of microorganisms may be at least 10 6 CFU of microorganisms / agent, preferably from about 10 6 to about 10 12 CFU of microorganisms / agent, preferably about 10 8 to about 10 12 CFU of microorganism / agent.

[0170] In one embodiment, preferably, the bifidobacterium (eg, a strain of animal Bifidobacterium lactis subsp. lactis (eg, animal Bifidobacterium lactis subsp. lactis (strain) 420 (B420)))) can be present in an amount of from about 10 6 to about 10 12 CFU of microorganisms / day, preferably about 10 8 to about 10 12 CFU of microorganisms / day. Therefore, the effective amount in this embodiment can be from about 10 6 to about 10 12 CFU of microorganisms / day, preferably about 10 8 to about 10 12 CFU of microorganisms / day.

[0171] CFU stands for “colony forming unit.” “Support” means a food product, a dietary supplement, or a pharmaceutically acceptable formulation.

[0172] Effect / Subjects / Medical Indications

[0173] The bacterial strains of the genus Bifidobacterium involved in the present invention are administered to subjects, including, for example, livestock (including cattle, horses, pigs and sheep) and humans. In some aspects of the invention, the subject is a companion animal (including a pet), such as, for example, a dog or a cat. In some aspects of the invention, the subject may suitably be a human.

[0174] One or more bacterial strains according to the present invention can have at least one of the following beneficial clinical responses in a subject: weight management, such as reducing BMI, reducing blood sugar levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing male-type fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing insulin secretion after eating, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (especially but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome.

[0175] One or more bacterial strains of the present invention can have at least one of the following beneficial clinical responses in a subject: lowering BMI, lowering blood sugar levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass.

[0176] Composition

[0177] Although one or more bacterial strains can be administered alone, in a specific embodiment of the present invention, one or more bacterial strains are used in combination with one or more fibers and / or prebiotics. In another specific embodiment, the fiber and / or prebiotic is polydextrose.

[0178] In certain embodiments, the one or more bacterial strains are in the form of a composition.

[0179] Although the composition can be administered alone according to the invention (i.e. without any support, diluent or excipient), the composition is usually and preferably administered on or in a support as part of a product, in particular as a component of a food product, dietary supplement or pharmaceutical composition or formulation. These products typically contain additional components well known to those skilled in the art.

[0180] A "combination" is understood to be a combination of two or more substances. The substance may be a chemical substance or a biological substance, such as bacteria, comprising a substance having a desired effect.

[0181] "Preparation" is understood to be a process or composition of combining different chemical and / or biological substances (including substances having a desired effect) to produce a final product. Composition and preparation can be used interchangeably.

[0182] Any product that can benefit from the composition can be used in the present invention. These include, but are not limited to, foods, especially fruit preserves and dairy products and dairy-derived products and pharmaceuticals.

[0183] When used as or for preparing a food (eg, a functional food), the composition of the present invention may be used in combination with one or more of the following substances: a nutritionally acceptable carrier, a nutritionally acceptable diluent, a nutritionally acceptable excipient, a nutritionally acceptable adjuvant, a nutritionally active ingredient.

[0184] For example, the composition of the present invention can be used as an ingredient of soft drinks, juices or beverages containing whey protein, healthy teas, cocoa drinks, milk drinks and lactic acid bacteria drinks, yogurt and drinking yogurt, cheese, ice cream, sorbet and desserts, confectionery, biscuit cakes and cake mixes, snack foods, balanced foods and beverages, fruit fillings, health glazes, chocolate bread fillings, cheesecake flavor fillings, fruit flavor cake fillings, cake and donut icings, instant baking filling creams, biscuit fillings, ready-to-eat bread fillings, low-calorie fillings, adult nutritional beverages, acidified soy / juice drinks, aseptic / distilled chocolate drinks, bar mixes, beverage powders, calcium-fortified soy / yogurt and chocolate milk, and calcium-fortified coffee drinks.

[0185] The composition can further be used as an ingredient in food products such as American cheese sauce, anti-caking agent for grated and shredded cheese, dessert plates, cream cheese, dry blend whipped fatty acid free natural cream, frozen / thawed dairy fresh cream, freeze / thaw stable spray cream, low fat and light natural cheddar cheese, low fat Swiss yogurt, aerated frozen desserts, hard case ice cream, label friendly improved economy and indulgence hard case ice cream, low fat ice cream: soft serve, barbecue sauce, cheese dip, cottage cheese dressing, dry blend Alfredo sauce, mixed cheese sauce, dry blend ketchup, and the like.

[0186] The composition of the present invention may be used as a food ingredient and / or a feed ingredient.

[0187] The term "food ingredient" or "feed ingredient" as used herein includes preparations which are or can be added to functional foods or foods as nutritional supplements.

[0188] The food ingredient may be in the form of a solution or as a solid, depending on the use and / or the mode of application and / or the mode of administration.

[0189] Food Products

[0190] In one embodiment, one or more bacterial strains according to the present invention are in the form of a food product (e.g., a food supplement, a beverage, or a milk-based powder). Here, the term "food" is used in a broad sense and encompasses food for humans as well as food for animals (i.e., feed). In a preferred aspect, the food is for human consumption. The food may be in the form of a solution or as a solid, depending on the purpose, and / or the mode of application, and / or the mode of administration.

[0191] Advantageously, when the product is a food product (comprising bacteria of the genus Bifidobacterium or a mixture thereof, and one or more prebiotics and / or fibers), it should remain effective through a normal "sell by" date or "expiration" date during which the food product is sold by a retailer. Preferably, the effective time should extend beyond such a date until the end of the normal freshness period when food spoilage becomes apparent. The required length of time and normal shelf life will vary with the food material, and one of ordinary skill in the art will recognize that shelf life times vary depending on the type of food material, the size of the food material, storage temperature, processing conditions, packaging materials, and packaging equipment.

[0192] Food supplements

[0193] One or more bacterial strains of the present invention may be a dietary supplement (also referred to herein as a food supplement) or may be added to a dietary supplement.

[0194] As used herein, the term "dietary supplement" is a product intended for ingestion that contains a "dietary ingredient" intended to add additional nutritional value to the (supplemented) diet. A "dietary ingredient" may be one or any combination of the following: a vitamin, a mineral, an herb or other botanical, an amino acid, a dietary substance, a concentrate, a metabolite, a component or an extract intended for a person to supplement their diet by increasing their total dietary intake.

[0195] Dietary supplements can come in many forms, such as tablets, capsules, soft gels, gel caps, liquids, or powders. Some dietary supplements can help ensure you get enough essential nutrients in your diet; others can help you reduce your risk of disease.

[0196] Functional Foods

[0197] One or more bacterial strains of the present invention may be a functional food or may be added to a functional food.

[0198] As used herein, the term "functional food" means a food that is not only capable of providing a nutritional effect, but is also capable of delivering additional beneficial effects to the consumer.

[0199] Thus, a functional food is a conventional food that has incorporated therein components or ingredients (such as those described herein) that impart a specific functional effect - such as a medical or physiological benefit - to the food rather than a purely nutritional effect.

[0200] While there is no legal definition of functional foods, most parties interested in this area agree that they are foods marketed as having specific health benefits beyond basic nutritional effects.

[0201] Some functional foods are nutraceuticals. Here, the term "nutraceutical" means food that not only provides nutritional effects and / or taste satisfaction, but also delivers therapeutic (or other beneficial) effects to consumers. Nutraceuticals cross the traditional dividing line between food and medicine.

[0202] Medical food

[0203] In one embodiment, one or more bacterial strains of the present invention, such as Bifidobacterium animalis subsp. lactis (strain) 420 (B420), are in the form of a medical food product.

[0204] By "medical food" is meant a food that is formulated for consumption or administration with or without a physician's supervision and is intended for use in a specific dietary management or condition for which unique nutritional requirements are established through medical evaluation based on recognized scientific principles.

[0205] drug

[0206] One or more bacterial strains of the present invention can be used as pharmaceutical preparations or compositions or for the preparation of pharmaceutical preparations or compositions. Herein, the term "medicine" is used in a broad sense and covers medicines for humans and medicines for animals (i.e., veterinary applications). In a preferred aspect, the medicine is used for human use and / or for animal husbandry.

[0207] Medicines may be used for therapeutic purposes - which may be curative or palliative or preventive in nature.

[0208] The pharmaceutically acceptable formulation or support or composition may be, for example, a formulation or support in the form of a compressed tablet, tablet, capsule, ointment, suppository or drinkable solution. Other suitable forms are provided below.

[0209] When used as a medicine or for preparing a medicine, one or more bacterial strains of the present invention may be used in combination with one or more of the following substances: a pharmaceutically acceptable carrier, a pharmaceutically acceptable diluent, a pharmaceutically acceptable excipient, a pharmaceutically acceptable adjuvant, a pharmaceutically active ingredient.

[0210] The drug may be in the form of a solution or as a solid, depending on the use and / or mode of application and / or mode of administration.

[0211] One or more bacterial strains of the present invention can be used as a pharmaceutical ingredient. Here, one or more bacterial strains can be the only active ingredient, or it can be at least one of a plurality of (ie, 2 or more) active ingredients.

[0212] According to the present invention, pharmaceutical preparations can be used in the form of solid or liquid preparations or in the form of substitutes thereof. Examples of solid preparations include, but are not limited to, tablets, capsules, dusts, granules and powders that can be wettable, spray-dried or freeze-dried. Examples of liquid preparations include, but are not limited to, aqueous, organic or aqueous-organic solutions, suspensions and emulsions.

[0213] Suitable examples of forms include one or more of the following for immediate, delayed, modified, sustained, pulsed or controlled release applications: tablets, pills, capsules, beads, solutions or suspensions which may contain flavoring or coloring agents.

[0214] For example, if the pharmaceutical formulation of the present invention is used in the form of a tablet (e.g., as a functional ingredient), the tablet may also contain one or more of the following substances: excipients such as microcrystalline cellulose, lactose, sodium citrate, calcium carbonate, calcium hydrogen phosphate, and glycine; disintegrants such as starch (preferably corn, potato, or tapioca starch), sodium glycolate starch, cross-linked sodium carboxymethyl cellulose, and certain complex silicates; granulation binders such as polyvinyl pyrrolidone, hydroxypropyl methylcellulose (HPMC), hydroxypropyl cellulose (HPC), sucrose, gelatin, and gum arabic; lubricants such as magnesium stearate, stearic acid, glyceryl behenate, and talc may be included.

[0215] Other examples of forms include creams. For some aspects, the microorganisms used in the present invention can be used, for example, in pharmaceutical and / or cosmetic creams, such as sunscreen creams and / or after-sun creams.

[0216] In one aspect, the pharmaceutical formulation according to the invention may be administered in the form of an aerosol, for example by way of a nasal spray, for example for administration to the respiratory tract.

[0217] Pharmacy

[0218] In one embodiment, the pharmaceutically acceptable formulation of the present invention is a medicament.

[0219] As used herein, the term "medicament" encompasses medicaments for both human and animal use in human and veterinary medicine. In addition, as used herein, the term "medicament" means any substance that provides treatment and / or beneficial effects. As used herein, the term "medicament" is not necessarily limited to substances that require a marketing permit, but can include substances that can be used in cosmetics, health supplements, foods (including, for example, feed and beverages), probiotic cultures, and natural remedies. In addition, as used herein, the term "medicament" encompasses products designed for incorporation into animal feed (e.g., livestock feed and / or pet food).

[0220] Prebiotics

[0221] In one embodiment, one or more bacterial strains according to the invention are used in combination with one or more fibers and / or prebiotics.

[0222] Prebiotics are a class of functional foods, defined as non-digestible food ingredients that beneficially affect the host by selectively stimulating the growth and / or activity of one or a limited number of bacteria (especially but not limited to probiotics, bifidobacteria and / or lactic acid bacteria) in the colon, and thus improve the health of the host. Typically, prebiotics are carbohydrates (e.g., oligosaccharides), but this definition does not exclude non-carbohydrates. The most common form of prebiotics is nutritionally classified as soluble fiber. To some extent, many forms of dietary fiber show a certain level of prebiotic effect.

[0223] In one embodiment, prebiotics are selectively fermented ingredients that allow for specific changes in both composition and / or activity of the gastrointestinal microflora, conferring well-being and health benefits on the host.

[0224] Suitably, prebiotics can be used according to the present invention in an amount of 0.01 to 100 g / day, preferably 0.1 to 50 g / day, more preferably 0.5 to 20 g / day. In one embodiment, prebiotics can be used according to the present invention in an amount of 1 to 10 g / day, preferably 2 to 9 g / day, more preferably 3 to 8 g / day. In another embodiment, prebiotics can be used according to the present invention in an amount of 5 to 50 g / day, preferably 10 to 25 g / day.

[0225] Examples of dietary sources of prebiotics include soy, inulin sources (such as Jerusalem artichoke, jicama, and chicory root), raw oats, unrefined wheat, unrefined barley, and yacon.

[0226] Examples of suitable prebiotics include alginates, xanthan gum, pectin, locust bean gum (LBG), inulin, guar gum, galacto-oligosaccharides (GOS), fructooligosaccharides (FOS), polydextrose (i.e. ), lactitol, lactosucrose, soy oligosaccharides, isomaltulose (Palatinose TM), isomalto-oligosaccharides, glucopyranose, xylo-oligosaccharides, manno-oligosaccharides, β-glucan, cellobiose, raffinose, gentiobiose, melibiose, xylobiose, cyclodextrin, isomaltose, trehalose, stachyose, panose, pullulan, verbascose, galactomannans and all forms of resistant starch.

[0227] A particularly preferred example of a fiber and / or prebiotic is polydextrose.

[0228] The combination of bifidobacteria according to the invention with one or more fibers and / or prebiotics exhibits a synergistic effect (i.e. an effect greater than the additive effect of the bacteria when used alone). Without wishing to be bound by theory, it is believed that this combination is able to selectively stimulate the growth and / or activity of bifidobacteria in the colon and thus improve their effects and host health.

[0229] In one embodiment, the one or more bacterial strains of the genus Bifidobacterium used in combination with the one or more fibers and / or prebiotics belong to the species Bifidobacterium animalis. More preferably, the Bifidobacterium used in combination with the one or more fibers and / or prebiotics belongs to the subspecies Bifidobacterium animalis lactis.

[0230] In a particularly preferred embodiment, the Bifidobacterium used in combination with one or more fibers and / or prebiotics is Bifidobacterium animalis subsp. lactis (strain) 420 (B420).

[0231] Another particularly preferred embodiment of the fiber and / or prebiotic is Ultra Polydextrose (LU).

[0232] Ultra polydextrose (LU) is a randomly cross-linked glucose polymer that is not digested by the host and may increase the number of bifidobacteria in continuous culture systems in the colon.

[0233] Numbered embodiments of the present invention:

[0234] 1. A method of identifying a subject having an increased probability of having a beneficial clinical response to administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium, the method comprising the steps of:

[0235] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps, or corresponding physical activity; and

[0236] ii. comparing said level to a threshold value,

[0237] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0238] 2. The method of embodiment 1, wherein the beneficial clinical response to the bacterial strain of the genus Bifidobacterium or the mixture of two or more of the strains of the genus Bifidobacterium is at least one of the following occurring in the subject: weight management, such as reducing BMI, reducing blood sugar levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing male-type fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome.

[0239] 3. The method of embodiment 2, wherein the beneficial clinical response to the bacterial strain of the genus Bifidobacterium or the mixture of two or more of the strains of the genus Bifidobacterium is at least one of the following occurring in the subject: reduction in BMI, reduction in body fat, reduction in blood glucose levels, control of weight gain, induction of weight loss, reduction in total body fat mass, reduction in mesenteric fat mass, reduction in trunk fat mass and / or reduction in androgenetic fat mass.

[0240] 4. The method of any one of the preceding embodiments, wherein when the biomarker is selected from the group consisting of total hPAI1, bile acid selected from GLCA, LCA, Iso-LCA and DCA, the biological sample is a blood sample.

[0241] 5. The method of any one of embodiments 1-4, wherein when the biomarker is a bacterium selected from the group consisting of Coprococcus, Ruminococcus, Akkermansia, Acidaminolyticus, Clostridiales-Undetermined XIII, and Eubacterium copropenes, the biological sample is a fecal sample.

[0242] 6. The method of any one of embodiments 1-5, wherein when the biomarker is selected from pimelic acid and azelaic acid, the biological sample is a stool sample.

[0243] 7. The method of any of the preceding embodiments, wherein when the biomarker is a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4), the biological sample is a blood sample.

[0244] 8. The method of any one of the preceding embodiments, wherein the bacterial strain of the genus Bifidobacterium or a mixture thereof is a probiotic strain.

[0245] 9. The method of any one of the preceding embodiments, wherein the bacterial strain of the genus Bifidobacterium or a mixture of two or more of said strains of the genus Bifidobacterium, if of the species Bifidobacterium animalis, preferably belongs to Bifidobacterium animalis subsp. lactis.

[0246] 10. The method of embodiment 9, wherein the bacterial strain of the species Bifidobacterium animalis subsp. lactis is strain B420.

[0247] 11. The method of any preceding embodiment, wherein the measured level of total hPAI1 in a biological sample obtained from the subject exceeds 48245 pg / ml.

[0248] 12. The method of any one of embodiments 1-11, wherein the measured level of GLCA in a biological sample obtained from the subject exceeds 0.0070 μmol / l.

[0249] 13. The method of any one of embodiments 1-12, wherein the measured level of LCA in a biological sample obtained from the subject exceeds 0.0380 μmol / l.

[0250] 14. The method of any one of embodiments 1-13, wherein the measured level of relative abundance of Coprococcus in the biological sample obtained from the subject exceeds 0.0426.

[0251] 15. The method of any one of embodiments 1-14, wherein the measured level of relative abundance of Ruminococcus in the biological sample obtained from the subject exceeds 0.0631.

[0252] 16. The method of any one of embodiments 1-15, wherein the measured level of relative abundance of Akkermansia in the biological sample obtained from the subject exceeds 0.0062.

[0253] 17. The method of any one of embodiments 1-16, wherein the measured level of relative abundance of Amino Acid-Solving Bacteria in the biological sample obtained from the subject exceeds 0.00043.

[0254] 18. The method of any one of embodiments 1-17, wherein the measured level of relative abundance of unclassified Clostridiales - undetermined status XIII in a biological sample obtained from the subject exceeds 0.00018.

[0255] 19. The method of any one of embodiments 1-18, wherein the measured level of relative abundance of Eubacterium copropionicum in the biological sample obtained from the subject exceeds 0.0084.

[0256] 20. The method of any one of embodiments 1-19, wherein the measured level of Iso-LCA in a biological sample (eg, feces) obtained from the subject exceeds 29 μmol / l.

[0257] 21. The method of any one of embodiments 1-20, wherein the measured level of DCA in a biological sample (eg, serum) obtained from the subject exceeds 0.41 nmol / ml.

[0258] 22. The method of any one of embodiments 1-21, wherein the measured level of the phospholipid phosphatidylcholine (36:4) in a biological sample obtained from the subject exceeds 0.064, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode.

[0259] 23. The method of any one of embodiments 1-22, wherein the measured level of the phospholipid phosphatidylcholine (32:1) in a biological sample obtained from the subject exceeds 0.0037, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode.

[0260] 24. The method of any one of embodiments 1-23, wherein the measured level of the phospholipid phosphatidylethanolamine (38:4) in a biological sample obtained from the subject exceeds 0.00074, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode.

[0261] 25. The method of any one of embodiments 1-24, wherein the measured level of the phospholipid phosphatidylethanolamine (36:4) in a biological sample obtained from the subject exceeds 0.00091, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in negative ionization mode.

[0262] 26. The method of any one of embodiments 1-25, wherein the measured level of the phospholipid phosphatidylinositol (40:4) in a biological sample obtained from the subject exceeds 0.00019, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in negative ionization mode.

[0263] 27. The method of any one of embodiments 1-26, wherein the measured level of pimelic acid in the biological sample obtained from the subject exceeds 0.000126, as described herein, measured in relative amounts, calculated as the peak area of ​​the ion at 125 m / z divided by the total peak area of ​​all identified peaks.

[0264] 28. The method of any one of embodiments 1-27, wherein the measured level of azelaic acid in the biological sample obtained from the subject exceeds 0.000135, as described herein, measured in relative quantity, calculated as the peak area of ​​the ion at 83 m / z divided by the total peak area of ​​all identified peaks.

[0265] 29. The method of any one of the preceding embodiments, wherein the measured levels are measured by LC-MS when the biological sample is a blood sample.

[0266] 30. The method of any one of the preceding embodiments, wherein the measured levels when the biological sample is a stool sample are measured by GC-MS and / or NMR.

[0267] 31. The method of any one of the preceding embodiments, wherein the level of at least one of the biomarkers is measured prior to administering the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium to the subject.

[0268] 32. The method of any one of the preceding embodiments, wherein the subject is overweight or obese.

[0269] 33. The method of any one of the preceding embodiments, wherein the subject has a BMI greater than 25.

[0270] 34. The method of any one of the preceding embodiments, wherein the subject's total hPAI1 and bile acid GLCA exceed the thresholds.

[0271] 35. The method of any preceding embodiment, wherein the bacterial strain is used in combination with one or more fibers and / or prebiotics.

[0272] 36. The method of any preceding embodiment, wherein the fiber and / or prebiotic is polydextrose.

[0273] 37. The method of any one of the preceding embodiments, wherein the bacterial strain is in the form of a composition, a food product, a dietary supplement, or a pharmaceutically acceptable formulation.

[0274] 38. The method of embodiment 37, wherein the pharmaceutically acceptable formulation is a medicament.

[0275] 39. The method of embodiment 37, wherein the food product is a medical food product.

[0276] 40. The method of any of the preceding embodiments, wherein the subject's daily activity is greater than 7000 steps, or a corresponding amount of physical activity.

[0277] 41. Use of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium for at least one of the following in a subject: managing weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by:

[0278] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and

[0279] ii. comparing said level to a threshold value,

[0280] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0281] 42. Use of the bacterial strain of the genus Bifidobacterium as described in embodiment 39 or a mixture of two or more strains thereof, as further defined in any one of embodiments 1-40.

[0282] 43. A bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium for use in a subject for managing weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by:

[0283] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and

[0284] ii. comparing said level to a threshold value,

[0285] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0286] 44. The bacterial strain of the genus Bifidobacterium for use as described in embodiment 43 or a mixture of two or more strains as further defined in any one of embodiments 1-40.

[0287] 45. A method of managing body weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome in a subject in need thereof, the method comprising administering to the subject a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by:

[0288] i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and

[0289] ii. comparing said level to a threshold value,

[0290] wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

[0291] 46. ​​The method of embodiment 45, as further defined in any one of embodiments 1-40.

[0292] 47. A method of managing body weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing male-type fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome in a subject in need thereof, the method comprising:

[0293] i. Have the subject perform more than 7,000 steps of daily personal activity or equivalent physical activity; and

[0294] ii. administering a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium to a subject who has obtained an activity under i), the subject has an increased probability of having a beneficial clinical response to the administration of said bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium.

[0295] 48. The method of embodiment 47, wherein the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium is defined in any one of embodiments 8-10.

[0296] Examples

[0297] introduction

[0298] The following example is based on a multivariate data analysis of the results from the MetSProb study (Stenman 2016). MetSProb is a randomized, double-blind, placebo-controlled clinical study conducted in Finland in an overweight and obese study population (ClinicalTrials.gov NCT01978691). The results of the study were published in two original papers in 2016 (Stenman et al. 2016) and 2019 (Hibberd et al. 2019).

[0299] The main results were reported by Stenman et al., which showed that probiotics alone or together with prebiotics controlled total body fat mass in healthy overweight or obese subjects. The second publication (Hibberd et al. (2019)) investigated the association between the gut microbiota and the observed clinical benefits after 6 months of intervention with prebiotics, probiotics and synbiotic products, showing that the intake of the probiotic strain B420 and its combination with polydextrose (PDX) caused changes in the gut microbiota and its metabolism, indicating the potential to support improvements in intestinal barrier function and obesity-related markers.

[0300] During the MetSProb study (Stenman 2016), a large number of parameters (130 in total, such as glucose, insulin, total hPAI1, bile acids, bacteria, etc.) were measured in blood and stool samples taken from subjects in the study population.

[0301] The multivariate Latent Class Analysis statistical model was applied to all measured data of all 130 parameters from subjects in the MetSProb human clinical study, surprisingly, the group supplied with B420 had only a set of six predictors for weight loss or reduced weight gain at baseline during the 6-month intervention period compared to the placebo group. In the study, weight loss was measured as body mass index (BMI), DXA trunk fat (DXA_TrFa), DXA male-type fat (DXA_AnFa), and DXA total fat (DXA_fat).

[0302] The six predictor variables were human plasminogen activator inhibitor-1 (total HPAI1), the secondary bile acids glycolithocholic acid (GLCA) and lithocholic acid (LCA) measured in the blood, and the fecal bacterial genera Coprococcus, Ruminococcus, and Akkermansia.

[0303] Statistical MANOVA analysis confirmed the findings for the six predictor variables.

[0304] Based on one or more of these six predictor variables, the subject can be classified as a responder or non-responder to the Bifidobacterium B420 intervention. The sample can be extracted as a blood or stool sample, and for the prediction, a median threshold can be used, as shown in the example below.

[0305] Participants and study design (Hibberd et al. 2019)

[0306] Double-blind, randomized, parallel, placebo-controlled clinical trials were conducted in overweight and obese adults to investigate the effects of probiotic, prebiotic, or synbiotic (probiotic + prebiotic) interventions on total body fat mass and obesity-related markers. The study population and clinical results have been described in detail previously (Stenman et al., 2016) and are summarized here.

[0307] Study participants were recruited from four clinical research centers in southern Finland between December 2013 and October 2014. Participants were overweight or obese (body mass index (BMI) 28.0-34.9) but were otherwise healthy. Exclusion criteria included a diagnosis of type 1 or 2 diabetes or cardiovascular disease, bariatric surgery, pregnant or breastfeeding women, recent use of laxatives, immunomodulatory drugs, high-dose vitamin D supplements, fiber supplements (within the previous 6 weeks), probiotics (6 weeks), antibiotics (2 months), antiobesity drugs (3 months), participation in a weight loss program (3 months), or a weight change of 3 kg in the previous 3 months. Participants were randomly assigned to one of four groups: (1) placebo, 12 g / day microcrystalline cellulose; (2) prebiotic LU, 12 g / day; and (3) the probiotic Bifidobacterium animalis subsp. lactis 420 in 12 g microcrystalline cellulose. TM (B420) 1010 cfu / day; (4) Biostime LU + B420, 1010 cfu / day of B420 in 12 g / day of LU. The study product was manufactured by DuPont Nutrition and Health (Madison, WI, USA) in sachets, and participants were instructed to mix it into a commercially available fruit shake (130 kcal) once a day while maintaining their normal diet and exercise habits. Participants attended a clinic visit for screening and baseline assessments, and subsequently attended clinic visits after 2, 4, and 6 months of study product use. Follow-up was conducted one month after the end of the intervention. Participants were monitored for study product compliance and protocol violations as previously described (Stenman et al., 2016), and the baseline characteristics of the protocol compliance group (n = 134) are summarized in Table 1. Body composition and metabolic biomarkers measured from participants included total body fat mass and lean mass measured by dual-energy X-ray absorptiometry (DXA) (total mass, masculine (waist region), feminine (hip region), trunk, legs, arms), BMI, waist and hip circumference, and the following blood markers for fasting participants: serum hsCRP, serum glucose, serum insulin, blood glycated hemoglobin, blood lipids (total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein, and triglycerides), serum cortisol, and serum liver markers (aspartate aminotransferase; alanine aminotransferase; and γ-glutamyltransferase) (Stenman et al., 2016).

[0308]

[0309] Table 1. Participant flow. Before unblinding of the study, participants were divided into the intention-to-treat (ITT) group and the per-protocol (PP) group according to their adherence to the study protocol.

[0310] Sample collection and processing (Hibberd et al. 2019).

[0311] Fecal samples were obtained from participants at the baseline visit, during the study intervention visit (2, 4, and 6 months), and one month after the end of treatment (+1 month). Samples were immediately frozen and stored at -80°C until analysis. Fecal microbiota was analyzed in all samples, and fecal metabolites and bile acids were analyzed at baseline and 6-month visits. Fasting blood samples collected at baseline and 6-month visits were used to analyze plasma bile acids.

[0312] Example 1: Statistical Analysis

[0313] This study aimed to identify baseline biomarkers associated with responder status during the intervention period in individual subjects receiving active treatment (B420) compared to placebo treatment.

[0314] experiment

[0315] The MetSProb human clinical study was a cross-sectional design in which subjects received placebo (N=36) or active (B420, N=25) treatment and multiple parameters were assessed at 2 paired time points (v2=baseline, v8=after 6 months of intervention).

[0316] The objective was to explore whether baseline (v2) biomarkers were associated with responder status during the intervention period (v8-v2) compared to placebo for strain B420.

[0317] Responder status was based on 4 weight and body composition parameters (BMI, DXA trunk fat (DXA_TrFa), DXA male-type fat (DXA_AnFa), and DXA total fat (DXA_fat)), and responders were those subjects who lost weight (i.e., v8-v2 difference < 0). Otherwise, subjects were classified as non-responders.

[0318] Plotting any weight and body composition parameter from v8-v2 against any baseline (v2) parameter for the 2 treatment populations (B420 and placebo), the pattern of the difference in slope for B420 vs. placebo will show if the parameter is a biomarker. If the difference in slope (B420 vs. placebo) is significantly different from zero at the 5% level, then the parameter is a biomarker, and if the sign of the difference is negative (positive), it means that a high (low) value of the biomarker increases the probability of being a responder.

[0319] The software used was SAS 9.4 (SAS Institute Inc., Cary, NC, USA, 2016).

[0320] Exploratory statistical analysis

[0321] A multivariate latent class analysis model was fitted to all parameters at 2 time points (v2, v8), and from this model a directional submodel was derived that fitted the 4 weight and body composition parameters (BMI, DXA_TrFa, DXA_AnFa, DXA_fat) (v8-v2) relative to all baseline (v2) parameters. This allowed statistical quantification of the difference in slope (denoted as "j1") (B420 vs. placebo).

[0322] The analysis results are shown in Table 2.

[0323]

[0324] Table 2. Summary of latent class analysis results.

[0325] The three information vectors (j1, R_j1, NR_j1) are the Z scores of the slope difference (B420 versus placebo) between responders (R_j1) and non-responders (NR_j1) in the prospective setting (unaware of responder status; j1) and the retrospective setting, respectively.

[0326] If "j1" is significant, it means that either or both of (R_j1, NR_j1) are significant.

[0327] If "j1" is significant, it means a decrease in body weight; if "R_j1" is significant, it means a decrease in body weight; if "NR_j1" is significant, it means a decrease in weight gain.

[0328] From Table 2, it can be observed that six parameters (hPAI1 total, GLCA, LCA, Coprococcus, Ruminococcus, Akkermansia) were identified as baseline biomarkers, all of which had a negative sign, meaning that high values ​​were associated with an increased probability of being a responder.

[0329] Confirmatory statistical analysis

[0330] The 6 predicted biomarkers identified in Table 2 were all confirmed as true biomarkers by simpler modeling.

[0331] The response was set to the 4 body weight and body composition measurements (BMI, DXA_TrFa, DXA_AnFa, and DXA_fat) for v8 - v2 on the original scale (applying mean centering and unit scaling). The regressor was set to an arbitrary single value among the 6 biomarkers for baseline (v2) on the original scale. The treatment identifier (B420, placebo) was set as a categorical variable.

[0332] PROC MIXED was used to fit a multivariate analysis of variance (MANOVA, type = CS) where the slopes for the 2 treatments (B420 and placebo) were different; and the mean of the slope difference (B420 - placebo) was estimated. The p - value (Pr<t) was one - sided (lower - sided).

[0333] Table 3 separately lists the SAS output (PROC MIXED) for each of these 6 biomarkers.

[0334]

[0335]

[0336] Table 3: Results of the MANOVA analysis.

[0337] The thresholds for the predictor variables can be calculated as the median (50th percentile) and the 33:66 percentile range based on the measurement data. The thresholds are depicted in Table 4.

[0338]

[0339] Table 4. Summary of exploratory and confirmatory statistical analyses. Thresholds are the median (50th percentile) and the 33:66 percentile range.

[0340] The MANOVA analysis confirmed the findings of the latent class analysis.

[0341] Example 2 - hPAI1 Total Results

[0342] Total hPAI1 is human plasminogen activator inhibitor - 1 (PAI - 1), a serine protease inhibitor (serpin) encoded by the SERPINE1 gene. Elevated PAI - 1 is a risk factor for thrombosis and atherosclerosis and also a risk factor for other diseases such as cancer.

[0343] It was found by latent class analysis model (Example 1) that total human plasminogen activator inhibitor-1 (hPAI1 total amount) in blood samples was a significant predictor of weight loss. Since both predictive Z score and responder Z score were significantly negative, this meant that high levels of hPAI1 total amount were able to predict weight loss during the 6-month intervention period using B420. The blood level threshold for predicting weight loss for subjects was in the range of [40653:53294] pg / mL, with a median of 48245 pg / mL. Figure 1 The BMI (kg / m2) of each subject in the intervention group B420 (N=25) and the placebo group (N=36) during the 6-month intervention period 2 ) (v8-v2) plotted against the total amount of hPAI1 at baseline. The median threshold is also plotted.

[0344] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Figure 1 It can be observed that during the 6-month intervention period, the placebo group had a positive increase in weight gain / BMI, while the B420 group had a negative trend line in weight loss / BMI.

[0345] Method Description

[0346] Blood clinical assays for total human plasminogen activator inhibitor-1 (hPAI1 total) were measured using an ELISA assay (pg / mL) as described in Stenman 2016 - Supplementary Information.

[0347] Statistical analysis: See Example 1.

[0348] Example 3—Bile Acid Results

[0349] It was found by latent class analysis model (Example 1) that secondary bile acids glycolithocholic acid (GLCA) and lithocholic acid (LCA) in blood samples are significant predictors of weight loss. Since both the predictive Z scores of GLCA and LCA and the responder Z scores are significantly negative, this means that high levels of one or another secondary bile acid can predict weight loss during the 6-month intervention period using B420. The blood level threshold for predicting weight loss of the subject should be in the range of [0.0033:0.0078] and [0.0301:0.0583], wherein the median values ​​of GLC and LCA are 0.0070 μmol / L and 0.0380 μmol / L, respectively. Figure 2 and Figure 3 The BMI (kg / m2) of each subject in the intervention group B420 (N=25) and the placebo group (N=36) during the 6-month intervention period 2) plotted against the bile acid concentration at baseline. The median threshold is also plotted.

[0350] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Figure 2 and Figure 3 It can be observed that during the 6-month intervention period, the placebo group had a positive trend line for weight gain / BMI, while the B420 group had a negative trend line for weight loss / BMI.

[0351] Secondary bile acids (such as LCA) are produced by bacteria in the microbiome, and secondary bile acids can be conjugated in the liver (such as GLCA).

[0352] Method Description: Plasma Bile Acid Analysis - LC-MRM-MS

[0353] Fasting blood samples collected at both baseline and 6-month visit were used for analysis of plasma bile acids. Sample preparation was performed in triplicate and samples were stored at -80°C until analysis.

[0354] A mixture of 15 stable isotope labeled bile acids was added to an Eppendorf tube and the solvent was evaporated (Table 5).

[0355]

[0356]

[0357] Table 5: Deuterium-labeled standards used for LC-MRM-MS quantification of bile acids.

[0358] For each replicate, 50 μL plasma was vortex mixed with 100 μL 1% formic acid aqueous solution, and 350 μL acetonitrile was added. The test tube was ultrasonicated for 10 min, and then kept on ice for 30 min to help protein precipitation. After centrifugation at 16000 × g for 2 min, the supernatant was loaded on activated Phenomenex Phree phospholipid removal 96-well SPE plates. The plate was centrifuged for 5 min at 500 x g, and the initial eluent was collected in a 1 mL 96-well collection plate. Each well was washed with 500 μL 70% acetonitrile aqueous solution containing 0.2% formic acid. The flow-through liquid was merged with the initial flow-through liquid and dried in a vacuum concentrator. The precipitate was redissolved in 100 μL 50% methanol aqueous solution.

[0359] An Agilent 1290 UHPLC system coupled to a Thermo Fisher TSQ Vantage via a heated electrospray ionization (HESI) source was updated in negative mode. The ACQUITY UPLC BEH C from Waters was used. 18 (2.1mm×150mm, 1.7μm, ) column for gradient elution, the mobile phase was 0.01% formic acid in water (solvent A) and 0.01% formic acid in acetonitrile (solvent B). The gradient was optimized from 25% to 40% B in 12 min, and then from 40% to 75% B in 14 min. The column was washed with 100% B for 2 min, and 25% B was used for 4 min balance between injections. The flow rate was 0.35 mL / min, and the column was maintained at 45° C. The injection volume was 10 μL.

[0360] The mass spectrometer settings of the TSQ instrument in EZ mode were: negative mode, spray voltage: 3000 V, capillary temperature: 320 °C, sheath gas: 45 psi, auxiliary gas 5, vaporizer gas temperature: 300 °C, collision pressure: 1.3 mTorr, cycle time: 0.800 s

[0361] Statistical analysis: see Example 1

[0362] Example 4 - Fecal Bacteria Coprococcus and Ruminococcus Results

[0363] It was found by latent class analysis model (Example 1) that the relative abundance of bacterial genera Coprococcus and Ruminococcus, identified by sequencing 16S rRNA in feces, was a significant predictor of reduced weight gain. Since both the predictive Z score and the non-responder Z score were significant negative values ​​and the responder Z score was negative but not significant for Coprococcus and Ruminococcus, this means that high levels of one genus or another can predict reduced weight gain during the 6-month intervention period using B420. The relative abundance threshold of feces for predicted weight gain reduction of subjects was in the range of [0.0360:0.0537] and [0.0319:0.0921], with median values ​​of Coprococcus and Ruminococcus being 0.0426 and 0.0631, respectively. Figure 4 and Figure 5 The BMI (kg / m2) of each subject in the intervention group B420 (N=25) and the placebo group (N=36) during the 6-month intervention period 2 ) (v8-v2) plotted against the relative abundance of Coprococcus and Ruminococcus, and the threshold.

[0364] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Figure 4 and Figure 5 It can be observed that during the 6-month intervention period, the placebo group had a positive trend line for weight gain / BMI, while the B420 group had a negative trend line for weight loss / BMI.

[0365] Methods Description: DNA Isolation and Microbiome Sequencing (From Hibberd 2019).

[0366] Using MagMAX TM Microbial DNA was extracted from fecal samples using the Total Nucleic Acid Isolation Kit (Applied Biosystems, Bridgewater, NJ, USA) and the OneStep-96 TM Purification was performed using the PCR Inhibitor Removal Kit (Zymo Research, Irvine, CA, USA). Microbial DNA was amplified by PCR in triplicate using primers 515F (5'-GTGCCAGCMGCCGCGGTAA) and 806R (5'-GGACTACHVGGGTWTCTAAT), which target the V4 variable region of the 16S rRNA gene. PCR amplification conditions were: initial DNA denaturation at 95°C for 3 min, followed by 30 cycles of 95°C for 45 s, 55°C for 60 s, and 72°C for 90 s; and a final extension at 72°C for 10 min. PCR products were purified, normalized, and paired-end 2 × 250 bp reads were generated using the Illumina MiSeq system (Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign).

[0367] Statistical analysis: See Example 1.

[0368] Example 5 - Fecal Bacteria Akkermansia Results

[0369] The relative abundance of the bacterial genus Akkermansia, identified by sequencing 16S rRNA in feces, was found to be a significant predictor of reduced weight gain by latent class analysis models (Example 1). Since both the predictive Z score and the non-responder Z score were significantly negative and the responder Z score was negative but not significant for Akkermansia, this means that high levels of Akkermansia are able to predict reduced weight gain during the 6-month intervention period using B420. The fecal relative abundance thresholds for predicted reduced weight gain for subjects were in the range of [0.0041:0.0118], with a median value of 0.0062 for Akkermansia. Figure 6Figure 2 depicts the BMI (kg / m2) of each subject in the intervention group B420 (N=25) and placebo (N=36) during the 6-month intervention. 2 ) (v8-v2) plotted against the relative abundance of Akkermansia and the threshold.

[0370] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Figure 6 It can be observed that during the 6-month intervention period, the placebo group showed a positive trend line for weight gain / BMI, while the B420 group also showed a positive trend line for weight gain / BMI, but to a lesser extent than placebo. The predictor genus Akkermansia at baseline predicted: lower weight gain / small change in BMI after 6 months of intervention with B420 compared to the placebo group.

[0371] Method description: See Example 4.

[0372] Example 6

[0373] Through latent class analysis model, it was found that total human plasminogen activator inhibitor-1 (hPAI1 total amount) in blood samples was a significant predictor of weight loss. Since both predictive Z score and responder Z score were significantly negative, this meant that high levels of hPAI1 total amount could predict weight loss during the 6-month intervention period using B420. The blood level threshold for predicting weight loss in subjects was in the range of [40653:53294] pg / mL, with a median of 48245 pg / mL (Table 4). Figure 7 Figure 2 is a graph of the change in trunk fat (v8-v2) obtained by DXA scans during the 6-month intervention period for each subject in the intervention group B420 (N=25) and placebo (N=36) plotted against the total hPAI1 at baseline. The median total hPAI1 threshold is also plotted.

[0374] A linear regression line is used to show the difference, from Figure 7 It can be observed that during the 6-month intervention period, the placebo group had a positive increase in body weight / trunk fat, while the B420 group had a decrease in trunk fat / trunk fat showed a negative trend line.

[0375] Methods: Trunk fat, androgenetic fat, and total fat were measured by dual-energy X-ray absorptiometry (DXA) scanning as described in Stenman 2016, and changes were measured in grams.

[0376] HPAI1 total amount determination and statistical analysis: Example 2.

[0377] Example 7

[0378] The latent class analysis model found that the secondary bile acids glycolithocholic acid (GLCA) and lithocholic acid (LCA) in blood samples were significant predictors of weight loss. Since both the predictive Z scores and responder Z scores of GLCA and LCA were significantly negative, this means that high levels of one or another secondary bile acid can predict weight loss during the 6-month intervention period using B420. The blood level threshold for predicting weight loss in subjects should be within the range of [0.0033:0.0078] and [0.0301:0.0583], with the median values ​​of GLC and LCA being 0.0070 μmol / L and 0.0380 μmol / L, respectively. Figure 8 and Fig. 9 Figure 2 shows the change in trunk fat (v8-v2) obtained by DXA scans during the 6-month intervention period for each subject in the intervention group B420 (N=25) and placebo (N=36) plotted against the bile acid concentration at baseline. The median thresholds for GLCA and LCA are also plotted.

[0379] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Figure 8 and Fig. 9 It can be observed that during the 6-month intervention period, the placebo group had an increase in trunk fat / positive trend line for trunk fat, while the B420 group had a decrease in trunk fat / negative trend line.

[0380] Method description: Bile acid determination: see Example 3. DXA scanning method: see Example 6. Statistical analysis: see Example 1.

[0381] Example 8

[0382] It was found by latent class analysis model (Example 1) that the relative abundance of bacterial genera Coprococcus and Ruminococcus, identified by sequencing 16S rRNA in feces, was a significant predictor of reduced weight gain. Since both the predictive Z score and the non-responder Z score were significantly negative and the responder Z score was negative but not significant for Coprococcus and Ruminococcus, this means that high levels of one genus or the other can predict reduced weight gain during the 6-month intervention period using strain B420. The relative abundance thresholds of feces for predicted reduced weight gain for subjects were in the range of [0.0360:0.0537] and [0.0319:0.0921], with median values ​​of Coprococcus and Ruminococcus of 0.0426 and 0.0631, respectively. Fig.10 and Fig.11Figure 3 is a graph of the change in trunk fat (v8-v2) measured by DXA scan within the 6-month intervention for each subject in the intervention group B420 (N=25) and placebo (N=36) plotted against the relative abundance of Coprococcus and Ruminococcus, as well as the threshold value.

[0383] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig.10 and Fig.11 It can be observed that during the 6-month intervention period, the placebo group had an increase in trunk fat / BMI with a positive trend line, while the B420 group had a decrease in trunk fat / negative trend line.

[0384] Method description: Fecal microbiome 16S rRNA sequencing: see Example 4. DXA scanning method: see Example 6. Statistical analysis: see Example 1.

[0385] Example 9

[0386] The relative abundance of the bacterial genus Akkermansia, identified by sequencing 16S rRNA in feces, was found to be a significant predictor of reduced weight gain by latent class analysis models (Example 1). Since both the predictive Z score and the non-responder Z score were significantly negative and the responder Z score was negative but not significant for Akkermansia, this means that high levels of Akkermansia can predict reduced weight gain during the 6-month intervention period using B420. The relative abundance thresholds of feces for predicted reduced weight gain for subjects were in the range of [0.0041:0.0118], with the median of Akkermansia = 0.0062. Fig.12 Middle is a graph plotting the change in trunk fat (v8-v2) during the 6-month intervention against the relative abundance of Akkermansia for each subject in the intervention group B420 (N=25) and placebo (N=36), as well as the median threshold.

[0387] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig.12 It can be observed that: during the 6-month intervention period, trunk fat increased / positive trendline in the placebo group, while trunk fat also increased / positive trendline in the B420 group, but to a lesser extent than placebo. Predictor genus Akkermansia at baseline predicted: lower trunk fat increase after 6-month intervention with B420 compared to placebo.

[0388] Method description: See Example 8.

[0389] Example 10

[0390] Through latent class analysis model, it was found that total human plasminogen activator inhibitor-1 (hPAI1 total amount) in blood samples was a significant predictor of weight loss. Since both predictive Z score and responder Z score were significantly negative, this meant that high levels of hPAI1 total amount could predict weight loss during the 6-month intervention period using B420. The blood level threshold for predicting weight loss in subjects was in the range of [40653:53294] pg / mL, with a median of 48245 pg / mL (Table 4). Fig.13 Figure 2 is a graph of the change in male-pattern fat (v8-v2) obtained by DXA scans during the 6-month intervention period for each subject in the intervention group B420 (N=25) and placebo (N=36) relative to the total hPAI1 at baseline. The median total hPAI1 threshold is also plotted.

[0391] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig.13 It can be observed that during the 6-month intervention period, the male-pattern fat increased in the placebo group / positive trend line, while the male-pattern fat decreased in the B420 group / negative trend line.

[0392] Method description: See Example 6.

[0393] Example 11

[0394] The latent class analysis model found that the secondary bile acids glycolithocholic acid (GLCA) and lithocholic acid (LCA) in blood samples were significant predictors of weight loss. Since both the predictive Z scores and responder Z scores of GLCA and LCA were significantly negative, this means that high levels of one or another secondary bile acid can predict weight loss during the 6-month intervention period using B420. The blood level threshold for predicting weight loss in subjects should be within the range of [0.0033:0.0078] and [0.0301:0.0583], with the median values ​​of GLC and LCA being 0.0070 μmol / L and 0.0380 μmol / L, respectively. Fig.14 and Fig.15 Figure 2 shows the change in male-type fat (v8-v2) obtained by DXA scans during the 6-month intervention period for each subject in the intervention group B420 (N=25) and placebo (N=36) plotted against the bile acid concentration at baseline. The median thresholds for GLCA and LCA are also plotted.

[0395] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig.14 and Fig.15It can be observed that during the 6-month intervention period, the male-pattern fat increased in the placebo group / positive trend line, while the male-pattern fat decreased in the B420 group / negative trend line.

[0396] Method description: See Example 7.

[0397] Example 12

[0398] It was found by latent class analysis model (Example 1) that the relative abundance of bacterial genera Coprococcus and Ruminococcus, identified by sequencing 16S rRNA in feces, was a significant predictor of reduced weight gain. Since both the predictive Z score and the non-responder Z score were significant negative values ​​and the responder Z score was negative but not significant for Coprococcus and Ruminococcus, this means that high levels of one genus or another can predict reduced weight gain during the 6-month intervention period using B420. The relative abundance threshold of feces for predicted weight gain reduction of subjects was in the range of [0.0360:0.0537] and [0.0319:0.0921], with median values ​​of Coprococcus and Ruminococcus being 0.0426 and 0.0631, respectively. Fig.16 and Fig.17 Middle is a graph plotting the change in male-type fat (v8-v2) for each subject in the intervention group B420 (N=25) and placebo (N=36) during the 6-month intervention against the relative abundance of Coprococcus and Ruminococcus, as well as the median threshold.

[0399] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig.16 and Fig.17 It can be observed that during the 6-month intervention period, male-type fat increased in the placebo group / positive trend line, while male-type fat decreased in the B420 group / negative trend line. The genus Ruminococcus was less predictive of male-type fat loss than Coprococcus.

[0400] Method description: See Example 8

[0401] Example 13

[0402] The relative abundance of the bacterial genus Akkermansia, identified by sequencing 16S rRNA in feces, was found to be a significant predictor of reduced weight gain by latent class analysis models (Example 1). Since both the predictive Z score and the non-responder Z score were significantly negative and the responder Z score was negative but not significant for Akkermansia, this means that high levels of Akkermansia can predict reduced weight gain during the 6-month intervention period using B420. The relative abundance thresholds of feces for predicted reduced weight gain for subjects were in the range of [0.0041:0.0118], with the median of Akkermansia = 0.0062. Fig.18 Middle is a plot of the change in male-type fat (v8-v2) during the 6-month intervention against the relative abundance of Akkermansia for each subject in the intervention group B420 (N=25) and placebo (N=36), as well as the median threshold.

[0403] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig.18 It can be observed that: during the 6-month intervention period, the placebo group had an increase in trunk fat / positive trendline, while the B420 group also had an increase in trunk fat / positive trendline, but to a lesser extent than the placebo. The predictor genus Akkermansia at baseline predicted: the change in male-pattern fat gain after 6 months of intervention with B420 was lower compared to the placebo group.

[0404] Method description: See Example 8

[0405] Example 14

[0406] Through latent class analysis model, it was found that total human plasminogen activator inhibitor-1 (hPAI1 total amount) in blood samples was a significant predictor of weight loss. Since both the predictive Z score and the responder Z score were significantly negative, this meant that high levels of hPAI1 total amount were able to predict weight loss during the 6-month intervention period using B420. The blood level threshold for predicting weight loss in the subject was in the range of [40653:53294] pg / mL (33:66 percentiles), with a median of 48245 pg / mL. Fig.19 Figure 2 is a graph of the change in total fat (v8-v2) obtained by DXA scans during the 6-month intervention period for each subject in the intervention group B420 (N=25) and placebo (N=36) relative to the total hPAI1 at baseline. The median total hPAI1 threshold is also plotted.

[0407] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig.19It can be observed that during the 6-month intervention period, total fat increased in the placebo group / positive trend line, while total fat decreased in the B420 group / negative trend line.

[0408] Method description: See Example 6.

[0409] Example 15

[0410] The latent class analysis model found that the secondary bile acids glycolithocholic acid (GLCA) and lithocholic acid (LCA) in blood samples were significant predictors of weight loss. Since both the predictive Z scores and responder Z scores of GLCA and LCA were significantly negative, this means that high levels of one or another secondary bile acid can predict weight loss during the 6-month intervention period using B420. The blood level threshold for predicting weight loss in subjects should be within the range of [0.0033:0.0078] and [0.0301:0.0583], with the median values ​​of GLC and LCA being 0.0070 μmol / L and 0.0380 μmol / L, respectively. Fig. 20 and Fig.21 Figure 2 is a graph of the change in total fat (v8-v2) obtained by DXA scans during the 6-month intervention period for each subject in the intervention group B420 (N=25) and placebo (N=36) plotted against the bile acid concentration at baseline. The median thresholds for GLCA and LCA are also plotted.

[0411] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig. 20 and Fig.21 It can be observed that during the 6-month intervention period, total fat increased in the placebo group / positive trend line, while total fat decreased in the B420 group / negative trend line.

[0412] Method description: See Example 7.

[0413] Example 16

[0414] It was found by latent class analysis model (Example 1) that the relative abundance of bacterial genera Coprococcus and Ruminococcus, identified by sequencing 16S rRNA in feces, was a significant predictor of reduced weight gain. Since both the predictive Z score and the non-responder Z score were significant negative values ​​and the responder Z score was negative but not significant for Coprococcus and Ruminococcus, this means that high levels of one genus or another can predict reduced weight gain during the 6-month intervention period using B420. The relative abundance threshold of feces for predicted weight gain reduction of subjects was in the range of [0.0360:0.0537] and [0.0319:0.0921], with median values ​​of Coprococcus and Ruminococcus being 0.0426 and 0.0631, respectively. Fig. 22 and Fig.23 Middle is a graph plotting the change in total fat (v8-v2) during the 6-month intervention against the relative abundance of Coprococcus and Ruminococcus for each subject in the intervention group B420 (N=25) and placebo (N=36), as well as the median threshold.

[0415] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig. 22 and Fig.23 It can be observed that during the 6-month intervention period, total fat increased in the placebo group / positive trend line, while total fat decreased in the B420 group / negative trend line.

[0416] Method description: See Example 8.

[0417] Example 17

[0418] The relative abundance of the bacterial genus Akkermansia, identified by sequencing 16S rRNA in feces, was found to be a significant predictor of reduced weight gain by latent class analysis models (Example 1). Since both the predictive Z-score and the non-responder Z-score were significantly negative and the responder Z-score was negative but not significant for Akkermansia, this means that high levels of Akkermansia were able to predict reduced weight gain during the 6-month intervention period using B420. The fecal relative abundance thresholds for predicted total fat change for subjects were in the range of [0.0041:0.0118], with the median for Akkermansia = 0.0062. Fig.24 Middle is a graph plotting the change in total fat (v8-v2) against the relative abundance of Akkermansia for each subject in the intervention group B420 (N=25) and placebo (N=36) during the 6-month intervention, as well as the median threshold.

[0419] According to the confirmatory analysis (Table 4), a linear regression line was used to show the difference, from Fig.24It can be observed that during the 6-month intervention period, the total fat in the placebo group increased, showing a positive trend line, while the total fat in the B420 group decreased, showing a negative trend line.

[0420] Method description: See Example 8.

[0421] Example 18

[0422] The SlimCap_HL post hoc study was designed to identify baseline biomarkers associated with responder status (during the intervention period) in individual subjects receiving active treatment (B420) compared to placebo treatment.

[0423] Summary of new prediction findings that differ between the MetSProb and SlimCap HL studies:

[0424]

[0425] Clinical study design

[0426] The dataset used for the responder analysis was from the SlimCap HL clinical trial. SlimCap HL is a randomized, triple-blind, placebo-controlled, multicenter, parallel-group study in overweight or obese individuals who followed a healthy lifestyle consisting of a recommended low-calorie diet (20% calorie restriction) and increased daily activity (1000 more steps per day). The clinical study consisted of five visits: a screening visit (visit 1), a baseline visit (visit 2), and visits 2, 4, and 6 months after baseline (visits 3, 4, and 5, respectively), of which only the baseline (visit 2, v2) and 6-month data were used for the responder analysis. At baseline, overweight or obese healthy individuals from France and Spain were divided into two groups, placebo and B420 TM .B420 TM The group was supplemented with Bifidobacterium animalis subsp. lactis 420 as follows: once daily orally at a target dose of 1 × 10 10 The study was conducted in 24 participants with 20 colony-forming units (CFU) of capsules containing microcrystalline cellulose (MCC), 1% magnesium stearate, and 1% silicon dioxide for 6 months (lot numbers: 1103400800 [2.07×1010 CFU per capsule], 1103714113 [1.92×1010 CFU per capsule], and 1103840294 [1.47×1010 CFU per capsule]). The placebo group was supplemented with capsules containing microcrystalline cellulose (MCC), 1% magnesium stearate, and 1% silicon dioxide, taken orally once daily for 6 months, lot numbers: 1103400790, 1103714112, and 1103840293. There were 209 participants in each group, for a total of 418 participants in the study.

[0427] The aim of this study was to demonstrate that when participants followed a healthy lifestyle intervention, B420 TM Whether it reduces total body fat mass more than placebo. This study validates a previous clinical study, MetsProb, in a larger group of people who used only probiotics and followed a healthy lifestyle program consisting of calorie restriction and increased daily activity.

[0428] The study population included overweight and obese participants, especially those with abdominal obesity, who were not receiving pharmacological treatment for metabolic syndrome or related disorders, and who were not taking medications or supplements to manage their weight or body fat. Participants were asked to follow healthy lifestyle habits during the study period.

[0429] The primary endpoint of the study was the difference in relative change in total body fat from baseline (Visit 2) to 6 months of product intake (Visit 5) between the active treatment group and the placebo group.

[0430] Secondary variables were the differences between the active treatment group and the placebo group in:

[0431] - Body fat mass in the trunk area (DXA)

[0432] -waistline

[0433] - Fat mass in male-shaped areas of the body (DXA)

[0434] -Lean body mass (DXA)

[0435] -Energy intake

[0436] - Fat mass in other body regions (arms, legs and gynecology) (DXA)

[0437] -Absolute total body fat mass (DXA)

[0438] -weight

[0439] -Body mass index (BMI)

[0440] - Hips

[0441] - Relative total body fat mass (DXA) at 2 and 4 months

[0442] -Total body fat percentage (added during SAP development)

[0443] Auxiliary variables were the differences between the active and placebo groups in:

[0444] - Food intake

[0445] -Physical activity (IPAQ, see Appendix 2)

[0446] - Daily activity (daily steps, pedometer / accelerometer)

[0447] Exploratory variables were the differences between the active treatment group and the placebo group in:

[0448] -Fasting blood sugar

[0449] -Fasting insulin

[0450] -Insulin resistance

[0451] - Glycated hemoglobin HbA1c

[0452] - Blood lipids (total cholesterol, HDL, LDL and triglycerides)

[0453] -Inflammatory markers

[0454] - Circulating Zonulin

[0455] - Markers of intestinal barrier function and endotoxemia

[0456] - Fecal microbiota

[0457] - Fecal metabolites

[0458] -Adipose tissue biomarkers

[0459] At visit 2 (baseline, v2), after reviewing 3 days of food diaries and pedometer / accelerometer records, dietary counseling was performed to guide participants to follow a healthy lifestyle intervention. A 20% calorie restriction of total energy expenditure (TEE) and an increase in daily activity (1000 more steps per day compared to baseline) were instructed. The 20% calorie restriction was determined based on TEE, which was calculated according to the FAO based on BMR at visit 1 and physical activity level (PAL) based on the IPAQ.

[0460] Body fat and lean mass were measured using dual-energy X-ray absorptiometry (DXA) at Visits 2, 3, 4, and 5. DXA measurements were performed on the day of the site visit or as close to the site visit as possible and up to 3 days after the visit. Waist circumference was measured at the midpoint between the lower edge of the last palpable rib and the top of the iliac crest. Hip circumference was measured around the widest part of the hips with the tape parallel to the floor.

[0461] Blood samples were collected at Visit 2 and Visit 5 for analysis of biomarkers. Blood glucose, HbA1c, and lipid parameters were also measured at screening (Visit 1) for inclusion / exclusion criteria purposes. In addition, circulating zonulin, a marker associated with intestinal permeability, was analyzed in all participants. To explore possible mechanisms of action, other biomarkers related to intestinal barrier function and endotoxemia (LPS, sCD14) and adipose tissue metabolism (adiponectin) were analyzed in all participants as exploratory parameters, as well as systemic inflammatory biomarkers obtained by NMR (glycosylated blood proteins, GlycA / GlycB). The levels of a wide range of metabolites in the blood as markers of inflammation and adipose tissue metabolism were analyzed using advanced analytical methods.

[0462] Fecal samples were collected from at least 50 participants per study group, and a total of 220 fecal samples were collected, 115 at V2 and 105 at V5. Fecal microbiota composition and activity were analyzed using state-of-the-art methods, including 16S sequencing, quantitative PCR, and determination of bacterial metabolites (e.g., SCFA, BCFA). In addition, fecal zonulin, a host-associated marker of gut health, was measured as an exploratory parameter.

[0463] Analytical methods - additional methods to those used in MetSProb.

[0464] LC-MS of lipids in serum.

[0465] The method is inspired by the literature reference Satomi Y. et al. 2017, Cajka T and Fiehn O 2014, and Sanjoy K. Bhattacharya 2017 .

[0466] 1.1. Chemicals and reagents

[0467] Acetonitrile (LC / MS grade), ethanol (99.5%, HPLC grade), 2-propanol (LC / MS grade), formic acid (LC / MS grade), and ammonium acetate were purchased from Thermo Fisher Scientific Inc. (Kamstrup, Denmark).

[0468] Sample preparation

[0469] Human serum (20 μL) was divided into three 1.5 mL tubes and

[0470] 180 μL of 90% ethanol (5° C.) was added, followed by mixing for 5 min at 5° C. After centrifugation at 14,000 rpm for 5 min at 20° C., 160 μL of the supernatant was used for liquid chromatography / mass spectrometry (LC / MS) analysis.

[0471] 1.3. Liquid chromatography / mass spectrometry

[0472] The LC / MS system consisted of a Vanquish UHPLC (Thermo Fisher Scientific, Sunnyvale, CA, USA) and an Orbitrap Fusion MS system (Thermo Fisher Scientific, Sunnyvale, CA, USA). LC separations were performed at 65 °C using reversed-phase columns Acquity UPLC CSH C18 (1.7 μm, 100 × 2.1 mm and Acquity UPLC CSH C18 1.7 μm VanGuard TM , Waters Corporation, Milford, Massachusetts, USA) was implemented. The mobile phase consisted of 600:400 (v / v) acetonitrile / water (mobile phase A) containing 10mM ammonium acetate and 900:100 (v / v) isopropanol / acetonitrile (mobile phase B) containing 10mM ammonium acetate. Lipid separation was performed using gradient elution by the following procedure. The flow rate was set to 0.5mL / min, and the ratio of mobile phase B was increased from 15% B to 30% B immediately at 2.4min, to 48% B at 3.0min, to 82% B at 13.2min, to 99% B at 13.8min, maintained at 99% B for 0.6min, then reduced to 15% B at 14.5 and kept constant for 3.5min. Mass spectrometry was performed under both positive ionization mode (ESP) and negative ionization mode (ESN), respectively. Electrospray ionization was performed by direct introduction of the LC eluent using a heated electrospray ionization probe (H-ESI, Thermo Fisher Scientific, San Jose, CA, USA).

[0473] The spray voltage was 2.5 kV (for negative ionization mode) or 3.5 kV (for positive ionization mode), and the evaporator temperature was 350° C. The ion transfer tube was set to 325° C. Full mass spectra (MS) were obtained by Orbitrap, ranging from m / z 170 to m / z 1700, with a mass resolution of 120000 FWHM (full width at half maximum) at m / z 400. Product ion spectra (MS / MS) were obtained by high-energy C-trap dissociation (HCD).

[0474] 1.4. Peak extraction from LC / MS raw data

[0475] The raw data of LC / MS were obtained from LipidSearch TM5.0 processing. First, perform a product search on the raw data file in LipidSearch according to the following procedure:

[0476] 1. Process the extracted ion chromatogram [EIC] and detect the peak of each lipid ion [separated peak area: SPA].

[0477] 2. Collect the MS2 spectrum contained in the EIC region.

[0478] 3. Calculate the product ion chromatogram [PIC] of each product ion peak in the MS2 spectrum, and calculate a virtual spectrum [deconvoluted MS2 spectrum: DMS] that is subordinate to the shape distribution of the SPA.

[0479] 4. List lipid ions with matching DMS and peak patterns as candidates.

[0480] After the product search, LipidSearch performs an alignment process.

[0481] Alignment is performed in the following three steps.

[0482] Retention time correction

[0483] Lipid molecule peak grouping

[0484] ·verify

[0485] The peak areas of annotated compounds were exported as CSV files along with monoisotopic m / z values ​​and retention time information and further data processing was performed using Excel and different statistical tools. The relative amounts used for thresholds and numbers were calculated as the peak area of ​​a given phospholipid divided by the total peak area of ​​all identified lipids in negative mode (ESN) or positive mode (ESP).

[0486] GC-MS analysis of metabolites in feces

[0487] The derivatization and GC-MS analysis methods were based on reference 4.

[0488] Materials and Chemicals

[0489] Anhydrous ethanol was purchased from VWR. Pyridine (>99.5%) was from Fischer Scientific, and chloroform (>99.9%), ethyl chloroformate (>98%), sodium hydroxide, sodium bicarbonate, and sodium sulfate were obtained from Sigma Aldrich.

[0490] GC-MS

[0491] The fecal aqueous extracts were derivatized with ethyl chloroformate (ECF) prior to analysis using GC-TOFMS. ECF reacts with carboxylic acids, amines, and phenols to produce esters, carbamates, and carbonates, respectively. Samples were derivatized and analyzed in duplicate, but 13 samples were analyzed in a single run due to low sample quantity. A total of 150 μL of sample was placed in a 2 mL vial with 50 μL of demineralized water, 200 μL of ethanol, 40 μL of sodium hydroxide (5 w / w%), and 40 μL of pyridine, which was done manually. The vials were then placed on a sample tray and derivatized by a dual-track multipurpose sampler (MPS, Gerstel). An internal standard (10 μg of ethoxyacetic acid) was added to all vials before derivatization and extraction of one sample at a time. Reagents (2×20 μL) were added twice with vigorous stirring (30 sec) after each addition. The derivatives were extracted by adding 400 μL of chloroform containing an internal standard (heptadecane, 155 μg / mL) and shaking vigorously for 10 s, followed by adding 400 μL of sodium bicarbonate (50 mM) and stirring vigorously. All organic extracts were transferred and dried in batches by slowly aspirating 200 μL of the bottom organic phase into a vial with an insert containing anhydrous sodium sulfate.

[0492] The derivatized samples were placed in a cooled (5°C) sample tray (98 position tray) until analysis by GC-TOFMS (Agilent 7890, LECO HT) was used for analysis. The GC was equipped with Rtx5-MS (Restek, 30m×0.25mm×0.25μm). The inlet was operated in split mode (1:20) at 280°C. The injection volume was 1μL. Helium was used as the carrier gas with a flow rate of 1mL / min. The oven temperature program was started at 50°C and increased to 320°C (maintained for 10min) at 10°C / min, with a total run time of 37min. The transmission line temperature was 250°C. The ion source temperature was 250°C, the acquisition rate was 20 Hz, and the mass range was 25 to 1000m / z.

[0493] The characteristic ions of each analyte are selected and extracted as responses, which are standardized using the responses of internal standards. Specifically, the characteristic ions of pimelic acid (ethyl derivative) and azelaic acid (ethyl derivative) are 125m / z and 83m / z, respectively. Aliquots are taken from all samples to make combined control samples. For every 15 sample injections, the combined control is derivatized and analyzed. The response of the combined control is used for drift correction of instrument performance. The relative response of pimelic acid and azelaic acid is obtained by dividing by the total peak area of ​​the specific sample.

[0494] Experiment—Design and Parameters

[0495] The basic design of the responder analysis experiment was a cross-sectional balanced control-treatment setting (status = ITT), with subjects observed longitudinally at 2 time points (v2 = baseline, v5 = 6 months after intervention), with control equal to placebo and treatment equal to B420.

[0496] The experiment was a multi-chamber trial that shared the same basic design in different versions and in which the clinical chamber served as the inner (core) array and the other chambers served as the outer (performance) array.

[0497] The 12 rooms in the experiment are summarized in Table 1 below, each room contains summary data for the number of subjects (N_Subj) and the number of parameters (N_Param). Room 1 is the clinical room, and rooms 2-12 are the different performance rooms.

[0498]

[0499]

[0500] Table 1. Chamber configurations studied.

[0501] The clinical room covers the valid ITT population of the general clinical trial, while the other rooms are different subsets of the clinical room population.

[0502] Responder status was based on 2 clinical parameters listed in Table 2 below (_RESP_ is the responder status classifier).

[0503]

[0504] Table 2. Responder status classifiers.

[0505] Therefore, 2 different responder status classifiers (DXAFMASS_5%, GLUC) were used in post hoc analyses, and both were defined by contrast during the intervention period (v5-v2).

[0506] The objective was to identify parameters / biomarkers that significantly differentiated responders to B420 from placebo and that were significantly different between responders and non-responders based on baseline (v2) values ​​for the entire ITT population.

[0507] Model

[0508] A multivariate latent class model (LCA) was fit to the data using the statistical software SAS 9.4 (SAS Institute, Cary, NC, USA, 2016) by using the clinical room as the inner (core) array and the other rooms (performance) as the outer array.

[0509] In the model, two categorical identifiers, treatment (B420, placebo) and responder status (non-responder, responder), were used in the regression specification for both the intercept and slope.

[0510] The association between the responder status classifier and potential biomarkers is summarized by a set of 3 information vectors (t, t__0, t__1), respectively for the difference in slope (B420 versus placebo) in the prospective setting (unaware of responder status) and in the retrospective setting of non-responders and responders.

[0511] Statistics are information carriers on the Z-scale, and these are interpreted by sign (direction of effect) and magnitude (the higher the absolute value, the more significant the intensity).

[0512] Significant biomarkers at the 5% level (ie, absolute Z score > 1.96) by two-sided testing are indicated by a color code (red = information carrier for positive scores, blue = information carrier for negative scores).

[0513] LCA model results

[0514] The significant biomarkers for the responder status classifier in Table 3 (DXAFMASS) and the responder status classifier in Table 4 (GLUC) are summarized below.

[0515] On the left are the biomarker signatures; in the ANOVA section are the information carriers; in the threshold section are the thresholds (medians) and P33 and P66 percentiles of the biomarkers in the B420 population.

[0516]

[0517]

[0518] Table 3. Biomarkers for responder status classifier (DXAFMASS) (Z-scores, columns t, t__0, t__1).

[0519]

[0520] Table 4. Biomarkers for responder status classifier (GLUC) (Z-scores, columns t, t__0, t__1).

[0521] For both responder status classifiers (DXAFMASS, GLUC) it was observed that biomarkers at high values ​​increased the probability of being a responder (prospectively) and this was confirmed retrospectively by significance for "t__1" and non-significance for "t__0".

[0522]

[0523]

[0524]

[0525] *) Detection in LC-MS mode: electrospray positive mode; **) Detection in LC-MS mode: electrospray negative mode.

[0526] Accurate structural assignment of phospholipids is based on high-resolution LC-MS-MS fragmentation.

[0527] References

[0528] Amabebe et al. 2020

[0529] Amabebe E, Robert FO, Agbalalah T, Orubu ESF. Microbial dysbiosis-induced obesity: role of gut microbiota in homoeostasis of energy metabolism. Br J Nutr. 2020 May 28;123(10):1127-1137. doi:10.1017 / S0007114520000380. Epub 2020 Feb 3. PMID: 32008579.

[0530] Waterson and Horvath 2015

[0531] Waterson MJ, Horvath TL. Neuronal Regulation of Energy Homeostasis: Beyond the Hypothalamus and Feeding. Cell Metab. 2015 Dec 1;22(6):962-70. doi:10.1016 / j.cmet.2015.09.026. Epub 2015 Oct 22. PMID: 26603190.

[0532] Stenman et al. 2016

[0533] Lotta K.Stenman,Markus J.Lehtinen,Nils Meland,Jeffrey E.Christensen,Nicolas Yeung,Markku T.Saarinen,Michael Courtney,Rémy Burcelin,Marja-Leena Jüri Linros, Dan Apter, Mika Scheinin, Hilde Kloster Smerud, Aila Rissanen, Sampo Lahtinen. Probiotictic With or Without Prebiotic Controls Body Fat Mass, Associated With Serum Zonulin, in Overweight and Obese Adults-Randomized Controlled Trial. Ebiomedicine (2016) 13:190-200. Doi: 10.1016 / j.ebiom.2016.10.036.

[0534] Hibberd et al. 2019

[0535] Hibberd, AA, Yde, CC, Ziegler, ML, Honore, AH, Saarinen, MT, Lahtinen, S., Stahl, B., Jensen, HM, & Stenman, LK (2019). Probiotic or synbiotic alters the gut microbiota and metabolism in a randomised controlled trial of weight management in overweight adults. Beneficial microbes, 2019;10(2):121-135. Doi:10.3920 / BM2018.0028.

[0536] Satomi Y. et al. 2017

[0537] One-step lipid extraction for plasma lipidomics analysis by liquid chromatography mass spectrometry. Satomi Y., Hirayama M., Kobayashi H. (2017) Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences, 1063, pp. 93-100.

[0538] Cajka T and Fiehn O 2014

[0539] Cajka T, Fiehn O (2014) Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry. Trac-Trend Anal Chem 61:192–206.

[0540] Sanjoy K. Bhattacharya 2017

[0541] Sanjoy K. Bhattacharya (ed.), Lipidomics: Methods and Protocols, Methods in Molecular Biology, vol. 1609, DOI 10.1007 / 978-1-4939-6996-8_14, Springer Science+Business Media LLC[ Springer Science+Business Media LLC] 2017 (Chapter 14).

[0542] Zhao L et al. 2017

[0543] Zhao L et al. (2017) High Throughput and Quantitative Measurement of Microbial Metabolome by Gas Chromatography / Mass Spectrometry Using Automated Alkyl Chloroformate Derivatization. DOI 10.1021 / acs.analchem.7b00660, Anal. Chem. 2017, 89, 10, 5565–5577.

[0544] All publications mentioned in the above description are incorporated herein by reference. Various modifications and variations of the described methods and systems of the present invention will be apparent to those skilled in the art without departing from the scope and spirit of the present invention. Although the present invention has been described in conjunction with specific preferred embodiments, it should be understood that the present invention as claimed should not be unduly limited to such specific embodiments. In fact, various modifications of the described modes for practicing the present invention that are apparent to those skilled in the art of biochemistry and biotechnology or related fields are intended to fall within the scope of the following claims.

[0545] Taxonomy:

[0546] As used herein, the term "aminoacidiolyticus" refers to a bacterial species of the following taxonomy: Bacteria; Firmicutes; Clostridium; Clostridiales; Clostridiales; Undetermined status XIII; Aminoacidiolyticus; Aminoacidiolyticus

[0547] As used herein, the term "Clostridiales-Undetermined Status XIII" refers to a bacterial species of the following taxonomy: Bacteria; Firmicutes; Clostridium; Clostridiales; Clostridiales; Undetermined Status XIII; Unclassified Clostridiales Undetermined Status XIII.

[0548] As used herein, the term "Eubacterium copropionicum" refers to a bacterial species of the following taxonomy: Bacteria; Firmicutes; Clostridium; Clostridiales; Eubacteriaceae; Eubacterium; Eubacterium.

[0549] As used herein, the term "Coprococcus" refers to the genus of anaerobic cocci, including the following species: Coprococcus catus, Coprococcus comes, and Coprococcuseutactus.

[0550] As used herein, the term "Ruminococcus" refers to a genus of bacteria in the class Clostridium, including species selected from the group consisting of Ruminococcus albus, Ruminococcus bromii, Ruminococcus callidus, Ruminococcus flavefaciens, Ruminococcus gauvreauii, Ruminococcus gnavus, Ruminococcus lactaris, Ruminococcus obeum, and Ruminococcus torques.

Claims

1. A method of identifying a subject having an increased probability of having a beneficial clinical response to administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium, the method comprising the steps of: i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acid selected from GLCA, LCA, Iso-LCA and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4) and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, Unclassified Clostridiales-Incertae Sedis XIII and Eubacteriumcoprostanoligenes; pimelic acid and azelaic acid; and / or measuring the daily activity of the subject in terms of steps, or corresponding physical activity; as well as ii. comparing said level to a threshold value, wherein when the measured level of at least one of the biomarkers is above the threshold value, the subject is identified as having the increased probability.

2. The method of claim 1, wherein the beneficial clinical response to the bacterial strain of the genus Bifidobacterium or the mixture of two or more of the strains of the genus Bifidobacterium is at least one of the following occurring in the subject: weight management, such as reducing BMI, reducing blood sugar levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing male-type fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome.

3. The method according to any one of the preceding claims, wherein the bacterial strain of the genus Bifidobacterium or the mixture of two or more of the strains of the genus Bifidobacterium, if belonging to the species Bifidobacterium animalis, preferably belongs to the species Bifidobacterium animalis subsp. Lactis, such as the bacterial strain of the species Bifidobacterium animalis subsp. Lactis, strain B420.

4. The method of any one of the preceding claims, wherein the measured level of total hPAI1 in the biological sample obtained from the subject exceeds 48245 pg / ml.

5. The method of any one of claims 1 to 4, wherein the measured level of GLCA in the biological sample obtained from the subject exceeds 0.0070 μmol / l and / or the measured level of LCA in the biological sample obtained from the subject exceeds 0.0380 μmol / l.

6. The method of any one of claims 1-5, wherein the measured level of relative abundance of Coprococcus in the biological sample obtained from the subject exceeds 0.0426 and / or the measured level of relative abundance of Ruminococcus in the biological sample obtained from the subject exceeds 0.0631 and / or the measured level of relative abundance of Akkermansia in the biological sample obtained from the subject exceeds 0.0062 and / or the measured level of relative abundance of Aminoacidiolyticus in the biological sample obtained from the subject exceeds 0.00043 and / or the measured level of relative abundance of Unclassified Clostridiales-Undetermined Status XIII in the biological sample obtained from the subject exceeds 0.00018 and / or the measured level of relative abundance of Eubacterium copropene in the biological sample obtained from the subject exceeds 0.0084.

7. The method of any one of claims 1 to 6, wherein the measured level of Iso-LCA in the biological sample such as feces obtained from the subject exceeds 29 μmol / l, and / or the measured level of DCA in the biological sample such as serum obtained from the subject exceeds 0.41 nmol / ml.

8. The method of any one of claims 1-7, wherein the measured level of the phospholipid phosphatidylcholine (36:4) in the biological sample obtained from the subject exceeds 0.064, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode, and / or the measured level of the phospholipid phosphatidylcholine (32:1) in the biological sample obtained from the subject exceeds 0.0037, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode, and / or the measured level of the phospholipid phosphatidylethanolamine (38:4) in the biological sample obtained from the subject exceeds 0.0064, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode, and / or .00074, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in positive ionization mode, and / or the measured level of the phospholipid phosphatidylethanolamine (36:4) in the biological sample obtained from the subject is greater than 0.00091, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in negative ionization mode, and / or the measured level of the phospholipid phosphatidylinositol (40:4) in the biological sample obtained from the subject is greater than 0.00019, as described herein, measured in relative amounts, calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all identified lipids in negative ionization mode.

9. The method of any one of claims 1-8, wherein the measured level of pimelic acid in the biological sample obtained from the subject exceeds 0.000126, as described herein, measured in relative amounts, calculated as the peak area of ​​the 125 m / z ion divided by the total peak area of ​​all identified peaks, and / or the measured level of azelaic acid in the biological sample obtained from the subject exceeds 0.000135, as described herein, measured in relative amounts, calculated as the peak area of ​​the 83 m / z ion divided by the total peak area of ​​all identified peaks.

10. The method of any of the preceding claims, wherein the daily activity of the subject exceeds 7000 steps, or is a corresponding physical activity.

11. Use of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium for at least one of the following in a subject: managing weight, such as reducing BMI, reducing blood sugar levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by: i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and ii. comparing said level to a threshold value, in, When the measured level of at least one of these biomarkers is above said threshold value, the subject is identified as having said increased probability.

12. Use of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains as claimed in claim 11, as further defined in any one of claims 1 to 10.

13. A bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium for use in a subject for managing body weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by: i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and ii. comparing said level to a threshold value, in, When the measured level of at least one of these biomarkers is above said threshold value, the subject is identified as having said increased probability.

14. The bacterial strain of the genus Bifidobacterium for use as claimed in claim 13 or a mixture of two or more strains as further defined in any one of claims 1 to 10.

15. A method of managing body weight, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing androgenetic fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome in a subject in need thereof, the method comprising administering to the subject a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium, wherein the subject has been identified as having an increased probability of having a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium by: i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproporogenes; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and i. measuring the level of at least one of the following biomarkers in a biological sample obtained from the subject: total hPAI1; bile acids selected from GLCA, LCA, Iso-LCA, and DCA; phospholipids selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); bacteria selected from Coprococcus, Ruminococcus, Akkermansia, Aminoacidiolyticus, Unclassified Clostridiales-Undetermined XIII, and Eubacterium coproducens; pimelic acid and azelaic acid; and / or measuring the subject's daily activity in steps; and ii. comparing said level to a threshold value, in, When the measured level of at least one of these biomarkers is above said threshold value, the subject is identified as having said increased probability.

16. The method of claim 15, as further defined in any one of claims 1-10.

17. A method of performing the following in a subject in need: managing weight, such as reducing BMI, reducing blood sugar levels, reducing body fat, controlling weight gain, inducing weight loss, reducing total body fat mass, reducing mesenteric fat mass, reducing trunk fat mass and / or reducing male-type fat mass, treating diabetes (preferably but not limited to type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing post-meal insulin secretion, reducing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome, the method comprising: i. The subject is required to perform more than 7,000 steps of daily personal activity or corresponding physical activity; as well as ii. administering a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium to said subject who has obtained said activity under i), said subject having an increased probability of having a beneficial clinical response to said administration of said bacterial strain of the genus Bifidobacterium or a mixture of two or more strains of the genus Bifidobacterium.

18. The method according to claim 17, wherein the bacterial strain of the genus Bifidobacterium or the mixture of two or more strains of the genus Bifidobacterium is as defined in claim 3.

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