Use of biomarkers in Bifidobacterium therapy

Abstract

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

Description

[Technical Field]

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

[0002] The regulation of energy balance is crucial for the survival of an organism. When nutrients are freely available, they are stored to allow for low energy intake in times of shortage. Under normal conditions, the brain, together with energy storage tissues, regulates energy balance by reducing energy intake when energy stores become overcrowded. When the energy storage mechanism is disrupted, the brain is no longer able to maintain energy balance. This can lead to an inability to maintain adequate energy intake, often seen as wilting in the elderly population, or to excessive energy storage in adipose tissue and even obesity.

[0003] Body mass index (BMI) is a simple index of weight relative to height and is commonly used to classify weight status in 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 of less than 18.5 as underweight; a BMI of 18.5 to 24.99 as normal weight; a BMI of 25 or more as overweight; and a BMI of 30 or more as obese.

[0005] Overweight and obesity are defined as abnormal or excessive fat accumulation. Underweight is defined as being too little body weight to maintain normal biological functions. Both underweight and overweight can lead to disturbances in metabolic functions, such as hormone signaling.

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

[0007] Overweight and obesity are more associated with mortality worldwide than underweight. Most of the world's population lives in countries where overweight and obesity cause more deaths 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 overweight and obesity are cardiovascular disease (mainly heart disease and stroke), which were the leading cause of death in 2012; diabetes; musculoskeletal disorders (especially osteoarthritis, a degenerative disease that causes severe joint damage); and some cancers (endometrial, breast, and colon cancer).

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

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

[0011] Overweight and obesity and their associated diseases are largely preventable, and the food industry can play a key role in the fight against obesity.

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

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

[0014] Probiotics are live microorganisms that confer health benefits to the host when administered in adequate amounts, whereas prebiotics are substrates selectively utilized by host microorganisms to confer health benefits. Preliminary evidence has shown that oral administration of certain probiotics in clinical intervention studies has significant effects on body composition or weight management (Stenman et al., 2016), suggesting a link between the gut microbiota and body fat regulation in humans. The probiotic strain Bifidobacterium animalis ssp. lactis (B420) has been shown to reduce body fat accumulation in humans (Stenman et al., 2016).

[0015] Given the potential for some probiotics and prebiotics to improve weight management within broader populations, it is important to be able to better predict which subjects within that broad population will respond better to the administration of such probiotics and prebiotics. Summary of the Invention [Problem to be solved by the invention]

[0016] The present invention seeks to provide a solution to the problems of the prior art. [Means for solving the problem]

[0017] In one aspect, the present invention provides a method for identifying a subject exhibiting an increased probability of exhibiting a beneficial clinical response to administration of a bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, 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 GLCA, bile acid LCA, the bacterium Coprococcus, the bacterium Ruminococcus, and / or the bacterium Akkermansia; and ii. comparing said level to a threshold value Including, wherein a subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is greater than said threshold.

[0018] In another aspect, the present invention provides a method for identifying a subject exhibiting an increased probability of exhibiting a beneficial clinical response to administration of a bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, comprising the steps of: i. the presence of the following biomarkers in a biological sample obtained from said subject: total hPAI1; a bile acid selected from GLCA, LCA, Iso-LCA, and DCA; a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); a species selected from the genera Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, unclassified Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes. coprostanoligenes); pimelic acid and azelaic acid; and / or measuring the subject's level of at least one of daily activity by step count or corresponding physical activity; and ii. comparing said level to a threshold value Including, wherein a subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is greater than said threshold.

[0019] In another aspect, the present invention provides a method for the treatment of obesity, the prevention and / or treatment of obesity-related conditions, including but not limited to, lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing fasting insulin secretion, improving glucose tolerance, treating obesity, tissue inflammation (particularly, but not limited to, 2. Use of a bacterial strain of Bifidobacterium or a mixture of two or more strains thereof for at least one of reducing inflammation (including but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and managing the weight of a subject, including treating metabolic syndrome, wherein the subject has been identified as exhibiting an increased probability of exhibiting a beneficial clinical response to administration of the bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, which 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, the bacterium Coprococcus, the bacterium Ruminococcus, and / or the bacterium Akkermansia; and ii. comparing said level to a threshold value It was identified by The subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is higher than said threshold.

[0020] In another aspect, the present invention provides a method for the treatment of obesity, the prevention and / or treatment of obesity-related conditions, including but not limited to, lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing fasting insulin secretion, improving glucose tolerance, treating obesity, tissue inflammation (particularly, but not limited to, 2. Use of a bacterial strain of Bifidobacterium or a mixture of two or more strains thereof for at least one of reducing inflammation (including but not limited to muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and managing the weight of a subject, including treating metabolic syndrome, wherein the subject has been identified as exhibiting an increased probability of exhibiting a beneficial clinical response to administration of the bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, which i. the presence of the following biomarkers in a biological sample obtained from said subject: total hPAI1; a bile acid selected from GLCA, LCA, Iso-LCA, and DCA; a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); a species selected from the genera Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, unclassified Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes. coprostanoligenes); pimelic acid and azelaic acid; and / or measuring the subject's level of at least one of daily activity or corresponding physical activity by step count; and ii. comparing said level to a threshold value It was identified by The subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is higher than said threshold.

[0021] In further aspects, the present invention provides a method for the treatment of obesity, including lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly 1. A bacterial strain of Bifidobacterium or a mixture of two or more strains thereof for use in managing the weight of a subject, including but not limited to reducing inflammation in muscle tissue, liver tissue, and / or adipose tissue), treating hepatitis, treating myositis, treating cardiovascular disease, and treating metabolic syndrome, wherein the subject has been identified as exhibiting an increased probability of exhibiting a beneficial clinical response to administration of the bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, 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, the bacterium Coprococcus, the bacterium Ruminococcus, and / or the bacterium Akkermansia; and ii. comparing said level to a threshold value It was identified by The present invention relates to a bacterial strain of the genus Bifidobacterium, or a mixture of two or more strains thereof, in which a subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is higher than said threshold.

[0022] In further aspects, the present invention provides a method for the treatment of obesity, including lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing fasting insulin secretion, improving glucose tolerance, treating obesity, reducing tissue inflammation (particularly 1. A bacterial strain of Bifidobacterium or a mixture of two or more strains thereof for use in managing the weight of a subject, including but not limited to reducing inflammation in muscle tissue, liver tissue, and / or adipose tissue), treating hepatitis, treating myositis, treating cardiovascular disease, and treating metabolic syndrome, wherein the subject has been identified as exhibiting an increased probability of exhibiting a beneficial clinical response to administration of the bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, i. the presence of the following biomarkers in a biological sample obtained from said subject: total hPAI1; a bile acid selected from GLCA, LCA, Iso-LCA, and DCA; a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); a species selected from the genera Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, unclassified Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes. coprostanoligenes); pimelic acid and azelaic acid; and / or measuring the subject's level of at least one of daily activity or corresponding physical activity by step count; and ii. comparing said level to a threshold value It was identified by The present invention relates to a bacterial strain of the genus Bifidobacterium, or a mixture of two or more strains thereof, in which a subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is higher than said threshold.

[0023] In another aspect, the present invention provides a method for the treatment of obesity, the prevention and / or treatment of obesity-related conditions, including but not limited to, lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing fasting insulin secretion, improving glucose tolerance, treating obesity, tissue inflammation (particularly, but not limited to, 1. A method for managing the weight of a subject in need thereof, such as reducing inflammation (muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease, and treating metabolic syndrome, said method comprising administering to said subject a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof, wherein said subject has been identified as exhibiting an increased likelihood of exhibiting a beneficial clinical response to the administration of said bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof, which is 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, the bacterium Coprococcus, the bacterium Ruminococcus, and / or the bacterium Akkermansia; and ii. comparing said level to a threshold value It was identified by wherein a subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is greater than said threshold.

[0024] In another aspect, the present invention provides a method for the treatment of obesity, the prevention and / or treatment of obesity-related conditions, including but not limited to, lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing fasting insulin secretion, improving glucose tolerance, treating obesity, tissue inflammation (particularly, but not limited to, 1. A method for managing the weight of a subject in need thereof, such as reducing inflammation (muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease, and treating metabolic syndrome, said method comprising administering to said subject a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof, wherein said subject has been identified as exhibiting an increased likelihood of exhibiting a beneficial clinical response to the administration of said bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof, which is i. the presence of the following biomarkers in a biological sample obtained from said subject: total hPAI1; a bile acid selected from GLCA, LCA, Iso-LCA, and DCA; a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); a species selected from the genera Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, unclassified Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes. coprostanoligenes); pimelic acid and azelaic acid; and / or measuring the subject's level of at least one of daily activity or corresponding physical activity by step count; and ii. comparing said level to a threshold value It was identified by wherein a subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is greater than said threshold.

[0025] In another aspect, the present invention provides a method for managing the weight of a subject in need thereof, such as lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing 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, said method comprising: i. Prescribing the subject a personal daily activity of more than 7,000 steps per day or corresponding physical activity; and ii.i) to a subject who has performed the activity according to (ii) above, wherein the subject exhibits an increased probability of exhibiting a beneficial clinical response to the administration of said bacterial strain of Bifidobacterium or a mixture of two or more strains thereof.

[0026] In some specific embodiments, the bacterial strain of Bifidobacterium or a mixture of two or more strains thereof is as described herein. [Brief explanation of the drawings]

[0027] [Figure 1] Human subject BMI (kg / m²) plotted against blood total hPAI1 levels (pg / mL) Visit 8 - Visit 2. The gray markers and trend line are data from the B420 group, and the black is data from the placebo group. The dotted line is the threshold. [Figure 2]Human subject BMI (kg / m²) plotted against blood glycolithocholic acid (GLCA, μmol / L) levels from Visit 8 to Visit 2. The gray markers and trend line represent data from the B420 group, while the black represents data from the placebo group. The dotted line represents the threshold. [Figure 3] Human subject BMI (kg / m²) plotted against blood lithocholic acid (LCA, μmol / L) levels from Visit 8 to Visit 2. The gray markers and trend line represent data from the B420 group, while the black represents data from the placebo group. The dotted line represents the threshold. [Figure 4] Human subject BMI (kg / m2) plotted against relative abundance of Coprococcus from Visit 8 to Visit 2. The gray markers and trend line are data from B420 and black is data from the placebo group. The dotted line is the threshold. [Figure 5] Human subject BMI (kg / m²) plotted against relative abundance of Ruminococcus from Visit 8 to Visit 2. The gray markers and trend line are data from B420 and black is data from the placebo group. The dotted line is the threshold. [Figure 6] Human subject BMI (kg / m²) plotted against relative abundance of Akkermansia from Visit 8 to Visit 2. The gray markers and trend line are data from B420, and the black is data from the placebo group. The dotted line is the threshold. [Figure 7] Human subject trunk fat (g) from DXA scan plotted against total hPAI1 Visit 8 - Visit 2. Grey markers and trend line are data from B420, black is data from placebo group. Dotted line is threshold. [Figure 8] Human subject trunk fat (g) from DXA scans plotted against glycolithocholic acid amount, Visits 8-2. The gray markers and trend line are data from B420, and the black is data from the placebo group. The dotted line is the threshold. [Figure 9] Human subject trunk fat (g) from DXA scans plotted against lithocholic acid levels, Visits 8-2. The gray markers and trend line are data from the B420 group, and the black is data from the placebo group. The dotted line is the threshold. [Figure 10] Human subject trunk fat (g) from DXA scans plotted against relative abundance of Coprococcus Visit 8-Visit 2. Grey markers and trend lines are data from B420, black is data from placebo group. Dotted line is threshold. [Figure 11] Human subject trunk fat (g) from DXA scans plotted against relative abundance of Ruminococcus, Visits 8-2. The gray markers and trend line are data from B420, and the black is data from the placebo group. The dotted line is the threshold. [Figure 12] Human subject trunk fat (g) from DXA scans plotted against relative abundance of Akkermansia, Visits 8-2. The gray markers and trend line are data from B420, and the black is data from the placebo group. The dotted line is the threshold. [Figure 13] Human subject android fat (g) from DXA scans plotted against the amount of total hPAI1 Visit 8-Visit 2. The gray markers and trend line are data from B420, and the black is data from the placebo group. The dotted line is the threshold. [Figure 14] Human subject android fat (g) from DXA scans plotted against the amount of glycolithocholic acid Visit 8-Visit 2. The gray markers and trend line are data from the B420 group, and the black is data from the placebo group. The dotted line is the threshold. [Figure 15]Human subject android fat (g) from DXA scans plotted against the amount of lithocholic acid, Visit 8 - Visit 2. The gray markers and trend line are data from the B420 group, and the black is data from the placebo group. The dotted line is the threshold. [Figure 16] Human subject android fat (g) from DXA scans plotted against relative abundance of Coprococcus, Visit 8-Visit 2. The gray markers and trend line are data from B420, and the black is data from the placebo group. The dotted line is the threshold. [Figure 17] Human subject android fat (g) from DXA scans plotted against the relative abundance of Ruminococcus from Visit 8 to Visit 2. The gray markers and trend line are data from B420 and black is data from the placebo group. The dotted line is the threshold. [Figure 18] Human subject android fat (g) from DXA scans plotted against relative abundance of Akkermansia spp. Visits 8-2. The gray markers and trend line are data from B420, and black is data from the placebo group. The dotted line is the threshold. [Figure 19] Human subject total fat (g) from DXA scan plotted against total hPAI1 amount Visit 8-Visit 2. Grey markers and trend line are data from B420, black is data from placebo group. Dotted line is threshold. [Figure 20] Human subject total fat (g) from DXA scan plotted against amount of glycolithocholic acid Visit 8 - Visit 2. The gray markers and trend line are data from B420 and black is data from the placebo group. The dotted line is the threshold. [Figure 21] Human subject total fat (g) from DXA scan plotted against lithocholic acid amount Visit 8 - Visit 2. The gray markers and trend line are data from B420 and black is data from the placebo group. The dotted line is the threshold. [Figure 22] Total fat (g) from DXA scans of human subjects plotted against the relative abundance of Coprococcus Visits 8-2. The gray markers and trend line are data from B420 and black is data from the placebo group. The dotted line is the threshold. [Figure 23] Human subject total fat (g) from DXA scan plotted against relative abundance of Ruminococcus Visit 8 - Visit 2. Grey markers and trend line are data from B420, black is data from placebo group. Dotted line is threshold. [Figure 24] Total fat (g) from DXA scans of human subjects plotted against relative abundance of Akkermansia Visits 8-2. The gray markers and trend line are data from B420, and the black is data from the placebo group. The dotted line is the threshold. [Figure 25] Plot of DXAFMASS (v5-v2) against the relative amount of lipid_ESP PC(36:4) in serum in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher values ​​of lipid_ESP PC(36:4) increased the probability of total fat loss for B420 treatment. In the retrospective study, higher values ​​of lipid_ESP PC(36:4) for B420 treatment were associated with total fat loss in responders but not in non-responders. The dotted line indicates the threshold. [Figure 26]Plot of DXAFMASS (v5-v2) versus the relative amount of lipid_ESP PC(32:1) in serum in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher values ​​of lipid_ESP PC(32:1) increased the probability of total fat loss for B420 treatment. In the retrospective study, higher values ​​of lipid_ESP PC(32:1) for B420 treatment were associated with total fat loss in responders but not in non-responders. The dotted line indicates the threshold. [Figure 27] Plot of DXAFMASS (v5-v2) against the relative amount of lipid_ESP PE(38:4) in serum in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher values ​​of lipid_ESP PE(38:4) increased the probability of total fat loss for B420 treatment. In the retrospective study, higher values ​​of lipid_ESP PE(38:4) for B420 treatment were associated with total fat loss in responders but not in non-responders. The dotted line indicates the threshold. [Figure 28] Plot of DXAFMASS (v5-v2) against the relative amount of lipid_ESP SM(d40:1) in serum in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher values ​​of lipid_ESP SM(d40:1) increased the probability of total fat loss for B420 treatment. In the retrospective study, higher values ​​of lipid_ESP SM(d40:1) for B420 treatment were associated with total fat loss in responders but not in non-responders. The dotted line indicates the threshold. [Figure 29]Plot of DXAFMASS (v5-v2) against the relative amount of lipid_ESN PE(36:4) in serum in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher values ​​of lipid_ESN PE(36:4) increased the probability of total fat loss for B420 treatment. In the retrospective study, higher values ​​of lipid_ESN PE(36:4) for B420 treatment were associated with total fat loss in responders but not in non-responders. The dotted line indicates the threshold. [Figure 30] Plot of DXAFMASS (v5-v2) against the relative amount of lipid_ESN PI(40:4) in serum in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher values ​​of lipid_ESN PI(40:4) increased the probability of total fat loss for B420 treatment. In the retrospective study, higher values ​​of lipid_ESN PI(40:4) for B420 treatment were associated with total fat loss in responders but not in non-responders. The dotted line indicates the threshold. [Figure 31] Plot of DXAFMASS (v5-v2) against the relative amount of lipid_ESN PE(40:5) in serum in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher values ​​of lipid_ESN PE(40:5) increased the probability of total fat loss for B420 treatment. In the retrospective study, higher values ​​of lipid_ESN PE(40:5) for B420 treatment were associated with total fat loss in responders but not in non-responders. The dotted line indicates the threshold. [Figure 32]Plot of DXAFMASS (v5-v2) against fecal BA (ISO-LCA) in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that larger values ​​of BA (ISO-LCA) increased the probability of total fat reduction for B420 treatment. In the retrospective study, larger values ​​of BA (ISO-LCA) for B420 treatment were associated with total fat reduction in responders but not in non-responders. The dotted line indicates the threshold. [Figure 33] Plot of DXAFMASS (v5-v2) against fecal BA(LCA) in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher values ​​of BA(LCA) increased the probability of total fat reduction for B420 treatment. In the retrospective study, higher values ​​of BA(LCA) for B420 treatment were associated with total fat reduction in responders but not in non-responders. The dotted line indicates the threshold. [Figure 34]DXAFMASS (v5-v2) plot for relative abundance taxa (Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiales_Incertae Sedis XIII_Aminipila_Aminipila butyrica) in feces in v2 for both B420 and placebo treatments. In prospective studies, B420 had a smaller slope compared to placebo, meaning a higher value for (Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiales_Incertae Sedis XIII_Aminipila_Aminipila butyrica) increased the probability of total fat reduction for B420 treatment. In a retrospective study, higher values ​​of (Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiales_Incertae Sedis XIII_Aminipila_Aminipila butyrica) for B420 treatment were associated with lower total fat in responders but not in non-responders. The dotted line indicates the threshold. [Figure 35]Plot of GLUC(v5-v2) against relative abundance taxa in feces in v2 for both B420 and placebo treatments (Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiales_Incertae Sedis XIII_Unclassified Clostridiales_Incertae Sedis XIII_Unclassified Clostridiales_Incertae Sedis XIII). In prospective studies, B420 had a smaller slope compared to placebo, meaning a higher value of (Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiales_Incertae Sedis XIII_Unclassified Clostridiales_Incertae Sedis XIII_Unclassified Clostridiales_Incertae Sedis XIII) increased the probability of glucose reduction for B420 treatment. In a retrospective study, higher values ​​of (Bacteria_Firmicutes_Clostridia_Clostridiales_Clostridiales_Incertae Sedis XIII_Unclassified Clostridiales_Incertae Sedis XIII_Unclassified Clostridiales_Incertae Sedis XIII) for B420 treatment were associated with lower glucose in responders but not in non-responders. The dotted line indicates the threshold. [Figure 36]Plot of GLUC(v5-v2) for relative abundance taxa (Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Eubacterium_Eubacterium coprostanoligenes) in feces in v2 for both B420 and placebo treatments. In a prospective study, B420 had a smaller slope compared to placebo, meaning a higher value of (Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Eubacterium_Eubacterium coprostanoligenes) increased the probability of glucose reduction for B420 treatment. In a retrospective study, higher values ​​of (Bacteria_Firmicutes_Clostridia_Clostridiales_Eubacteriaceae_Eubacterium_Eubacterium coprostanoligenes) for B420 treatment were associated with glucose lowering in responders but not in non-responders. The dotted line indicates the threshold. [Figure 37]Plot of GLUC (v5-v2) versus the relative response (relative to total peak area) of the fecal metabolite pimelic acid in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher values ​​of pimelic acid increased the probability of glucose reduction for B420 treatment. In the retrospective study, higher values ​​of pimelic acid for B420 treatment were associated with glucose lowering in responders but not in non-responders. The dotted line indicates the threshold. [Figure 38] Plot of GLUC (v5-v2) versus the relative response (relative to total peak area) of the fecal metabolite azelaic acid in v2 for both B420 and placebo treatments. In the prospective study, B420 had a shallower slope compared to placebo, meaning that higher values ​​of azelaic acid increased the probability of glucose reduction for B420 treatment. In the retrospective study, higher values ​​of azelaic acid for B420 treatment were associated with glucose lowering in responders but not in non-responders. The dotted line indicates the threshold. [Figure 39] Plot of GLUC (v5-v2) against STP (AVGSTEPS) in v2 clinical trials for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that larger values ​​of (AVGSTEPS) increased the probability of glucose reduction for B420 treatment. In the retrospective study, larger values ​​of (AVGSTEPS) for B420 treatment were associated with glucose reduction in responders but not in non-responders. The dotted line indicates the threshold. [Figure 40]Plot of GLUC (v5-v2) against serum BA (DCA) in v2 for both B420 and placebo treatments. In the prospective study, B420 had a smaller slope compared to placebo, meaning that higher BA (DCA) values ​​increased the probability of glucose reduction for B420 treatment. In the retrospective study, higher BA (DCA) values ​​for B420 treatment were associated with glucose reduction in responders but not in non-responders. The dotted line indicates the threshold. DETAILED DESCRIPTION OF THE INVENTION

[0028] advantage Surprisingly, the inventors have found that measuring the levels of one or more of the biomarkers total hPAI1, GLCA, LCA, Coprococcus, Ruminococcus and Akkermansia in a subject at baseline can predict whether said subject will exhibit a beneficial clinical response to administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more such strains, in particular Bifidobacterium animalis subsp. lactis 420 (strain B420), compared to a placebo group.

[0029] Detailed aspects of the present invention are presented below. In part, some of the detailed aspects are discussed in separate sections. This is for ease of reference and is in no way intended to be limiting. All embodiments described below are equally applicable to all aspects of the present invention unless the context specifically dictates otherwise.

[0030] bacteria The bacteria used in the present invention are selected from bacteria of the genus Bifidobacterium or mixtures thereof. Preferably, the Bifidobacterium to be used in the present invention is a Bifidobacterium that has been generally recognized as safe, preferably GRAS certified. Generally recognized as safe (GRAS) is a U.S. Food and Drug Administration (FDA) designation that a chemical or substance added to food is considered safe by experts and is therefore exempt from the normal Federal Food, Drug, and Cosmetic Act (FFDCA) food additive tolerance requirements.

[0031] In particular, the bacterial strain is Bifidobacterium animalis ssp. lactis 420 (B420).

[0032] The bacterial strain is commercially available from DuPont Nutrition Biosciences Aps, Denmark.

[0033] The bacterial strain B420 has also been deposited by DuPont Nutrition Biosciences Aps, Denmark, in accordance with the Budapest Treaty on the international recognition of the deposit of microorganisms for the purposes of patent procedure with the Leibniz-Institut German Collection of Microbial Cell Cultures (Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (DSMZ)), Inhoffenstrasse 7B, 38124 Braunschweig, Germany, where it is recorded under the following accession number: strain B420 (DGCC420); deposited on June 30, 2015 under accession number DSM32073.

[0034] In a first aspect, the present invention provides a method for identifying a subject that exhibits an increased probability of exhibiting a beneficial clinical response to administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof, comprising: i. the presence of the following biomarkers in a biological sample obtained from said subject: total hPAI1; a bile acid selected from GLCA, LCA, Iso-LCA, and DCA; a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); a species selected from the genera Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, unclassified Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes. coprostanoligenes); pimelic acid and azelaic acid; and / or measuring the subject's level of at least one of daily activity by step count or corresponding physical activity; and ii. comparing said level to a threshold value Including, wherein a subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is greater than said threshold.

[0035] In the context of the present invention, a biomarker, or biological marker, is a measurable indicator of some biological state or condition in a subject. Biomarkers are measured using blood, urine, or feces, and are often used to study and predict a subject's clinical response to the administration of drugs, as well as other products, such as probiotic strains.

[0036] The Bifidobacterium strain or a mixture of two or more strains thereof may be used in any form capable of exerting the effects described herein. For example, the bacteria may be live, dormant, inactivated, or killed. Preferably, the bacteria are live.

[0037] The one or more bacterial strains may comprise whole bacteria or may comprise bacterial components, such as bacterial cell wall components such as peptidoglycan, bacterial nucleic acids such as DNA and RNA, bacterial membrane components, and bacterial structural components such as proteins, carbohydrates, lipids, and combinations thereof, e.g., lipoproteins, glycolipids, and glycoproteins.

[0038] The one or more bacterial strains may also, or instead, contain bacterial metabolites. As used herein, the term "bacterial metabolites" includes all molecules produced or modified by (probiotic) bacteria as a result of bacterial metabolism during the growth, survival, persistence, passage, or presence of the bacteria during the manufacture and storage of the probiotic product and during gastrointestinal transit in mammals. Examples include all organic acids, inorganic acids, bases, 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 molecules containing nitrite or sulfite.

[0039] Preferably, the bacteria include whole bacteria, more preferably all viable bacteria.

[0040] Preferably, the Bifidobacterium or bifidobacteria used in the present invention are suitable for human and / or animal consumption. Those skilled in the art will readily recognize specific species and / or strains of bifidobacteria from within the genera described herein that are used in the food and / or agricultural industry and are generally considered suitable for human and / or animal consumption.

[0041] In the present invention, the bifidobacteria used may be of the same species or may comprise a mixture of species and / or strains.

[0042] Suitable bacteria are those of the species Bifidobacterium lactis, Bifidobacterium bifidum, Bifidobacterium longum, Bifidobacterium animalis, Bifidobacterium breve, Bifidobacterium infantis, Bifidobacterium catenulatum, Bifidobacterium pseudocatenulatum, Bifidobacterium adressentis, Bifidobacterium spp. adolescentis, and Bifidobacterium angulatum, and any combination thereof.

[0043] Preferably, the Bifidobacterium used in the present invention is the species Bifidobacterium animalis. More preferably, the Bifidobacterium used in the present invention is Bifidobacterium animalis ssp. lactis.

[0044] In a particularly preferred embodiment, the bacterium used in the present invention is Bifidobacterium animalis ssp. lactis strain 420 (B420).

[0045] In one embodiment, the bacteria used in the present invention are probiotic bacteria. The term "probiotic bacteria" is defined herein to encompass any non-pathogenic bacteria that confer a health benefit to the host when administered as a live bacterium in adequate amounts. Such probiotic strains generally have the ability to survive passage through the upper gastrointestinal tract. They are non-pathogenic and non-toxic, and exert their beneficial effects on health through ecological interactions with the normal flora of the gastrointestinal tract, on the one hand, and through their ability to positively influence the immune system via the "GALT" (gut-associated lymphoid tissue), on the other. According to the definition of probiotics, such bacteria, when given in sufficient numbers, have the ability to travel through the intestine as live bacteria, but do not cross the intestinal barrier, thus their primary effect is induced in the lumen and / or wall of the gastrointestinal tract. Subsequently, during the administration period, these bacteria form part of the normal flora. This colonization (or transient colonization) allows the probiotic bacteria to exert beneficial effects, such as suppressing potentially pathogenic microorganisms present in the microflora and interacting with the intestinal immune system.

[0046] In a preferred embodiment, the bacterial strain of the genus Bifidobacterium or a mixture thereof is a probiotic bacterial strain.

[0047] In another embodiment of the present invention, the beneficial clinical response to the bacterial strain of Bifidobacterium or a mixture of two or more of said strains thereof is at least one of weight management, such as reducing BMI of the subject, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing 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.

[0048] In particular embodiments, the beneficial clinical response to said bacterial strain of Bifidobacterium or a mixture of two or more of said strains thereof is at least one of lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal fat mass and / or reducing android fat mass.

[0049] In a particular embodiment of the present invention, when the biomarker is selected from the group consisting of total hPAI1, bile acids selected from GLCA, LCA, Iso-LCA, and DCA, the biological sample is a blood sample.

[0050] In another detailed embodiment of the invention, when the biomarker is a bacterium selected from the group consisting of Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes, the biological sample is a fecal sample.

[0051] In another particular embodiment of the invention, when the biomarkers are selected from pimelic acid and azelaic acid, the biological sample is a fecal sample.

[0052] In another particular embodiment of the 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.

[0053] In certain embodiments of the present invention, the measured level of total hPAI1 in a biological sample obtained from the subject is greater than 48245 pg. / ml.

[0054] In another embodiment, the measured level of GLCA in a biological sample obtained from the subject is greater than 0.0070 μmol / l.

[0055] In another embodiment, the measured level of LCA in a biological sample obtained from the subject is greater than 0.0380 μmol / l.

[0056] In another embodiment, the measured level of relative abundance of Coprococcus in a biological sample obtained from the subject is greater than 0.0426.

[0057] In another embodiment, the measured level of relative abundance of Ruminococcus in a biological sample obtained from the subject is greater than 0.0631.

[0058] In another embodiment, the measured level of relative abundance of Akkermansia in a biological sample obtained from the subject is greater than 0.0062.

[0059] In another embodiment, the measured level of relative abundance of Aminipila butyrica in a biological sample obtained from said subject is greater than 0.00043.

[0060] In another embodiment, the measured level of relative abundance unclassified Clostridiales-Incertae Sedis XIII in a biological sample obtained from said subject is greater than 0.00018.

[0061] In another embodiment, the measured level of relative abundance of Eubacterium coprostanoligenes in a biological sample obtained from the subject is greater than 0.0084.

[0062] In another embodiment, the measured level of Iso-LCA in a biological sample obtained from the subject is greater than 29 μmol / l.

[0063] In another embodiment, the measured level of DCA in a biological sample obtained from the subject is greater than 0.41 nmol / ml.

[0064] In another embodiment, the measured level of the phospholipid phosphatidylcholine (36:4) in a biological sample obtained from said subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in positive ionization mode, is greater than 0.064.

[0065] In another embodiment, the measured level of the phospholipid phosphatidylcholine (32:1) in a biological sample obtained from said subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in positive ionization mode, is greater than 0.0037.

[0066] In another embodiment, the measured level of phospholipid phosphatidylethanolamine (38:4) in a biological sample obtained from said subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in positive ionization mode, is greater than 0.00074.

[0067] In another embodiment, the measured level of phospholipid phosphatidylethanolamine (36:4) in a biological sample obtained from said subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in negative ionization mode, is greater than 0.00091.

[0068] In another embodiment, the measured level of the phospholipid phosphatidylinositol (40:4) in a biological sample obtained from said subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in negative ionization mode, is greater than 0.00019.

[0069] In another embodiment, the measured level of pimelic acid in a biological sample obtained from said subject, measured as a relative amount calculated as the peak area of ​​ion 125 m / z divided by the total peak area of ​​all peaks identified as described herein, is greater than 0.000126.

[0070] In another embodiment, the measured level of azelaic acid in a biological sample obtained from the subject, measured as a relative amount calculated as the peak area of ​​ion 83 m / z divided by the total peak area of ​​all peaks identified as described herein, is greater than 0.000135.

[0071] In another embodiment, the subject's daily activity in steps is greater than 7000 steps or a corresponding physical activity.

[0072] In another embodiment, the measured level of pimelic acid in a biological sample obtained from the subject is greater than 0.000126.

[0073] In another embodiment, the measured level of azelaic acid in a biological sample obtained from the subject is greater than 0.000135.

[0074] According to the present invention, various analytical techniques can be used to analyze the biological samples of the present invention. One such technique is liquid chromatography-mass spectrometry (LC-MS), which combines the physical separation capabilities of liquid chromatography (or HPLC) with the mass analysis capabilities 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 various substances in a sample. A further technique is nuclear magnetic resonance (NMR). All of these techniques are well known to those skilled in the art.

[0075] According to a particular embodiment of the invention, when the biological sample to be analyzed is a blood sample, the levels of the biomarkers are measured by LC-MS.

[0076] According to another particular embodiment, when the biological sample to be analyzed is a fecal sample, the levels of the biomarkers are measured by LC-MS.

[0077] In one embodiment, the measurement of the level of at least one of the biomarkers is performed before administering the bacterial strain of Bifidobacterium or a mixture of two or more strains thereof to the subject.

[0078] In particular embodiments, the subject according to the present invention is overweight or obese.

[0079] In another particular embodiment, a subject according to the present invention has a BMI of over 25.

[0080] In particular embodiments, a subject according to the invention has total hPAI1 and bile acid GLCA above a threshold value.

[0081] Dosage The Bifidobacterium species used in the present invention, such as strains of Bifidobacterium animalis ssp. lactis, e.g., Bifidobacterium animalis ssp. lactis strain 420 (B420), are generally 10 6 ~10 12 CFU of bacteria / g of support, more specifically 10 8 ~10 12 CFU of bacteria / g of support, preferably 10 for lyophilized form 9 ~10 12 It may contain CFU / g.

[0082] Preferably, the Bifidobacterium is a strain of Bifidobacterium animalis ssp. lactis, such as Bifidobacterium animalis ssp. lactis (strain 420) (B420), in a concentration of about 10 6 ~about 10 12 CFU of microorganisms / dose, preferably about 10 8 ~about 1012 The microorganism may be administered in a dosage of 10 CFU of microorganism / dose. The term "per dose" means that the amount of microorganism is provided to the subject either per day or per intake, preferably per day. For example, if the microorganism is to be administered in a food, such as yogurt, then the yogurt is preferably about 10 8 ~10 12 However, or alternatively, the amount of microorganisms a subject receives at any particular time, e.g., the overall amount of microorganisms a subject receives per 24-hour period, may be about 10 6 ~about 10 12 CFU of microorganisms, preferably 10 8 ~about 10 12 As long as the microorganisms are CFUs, they may be divided into multiple doses, each containing a smaller microorganism load.

[0083] In the present invention, an effective amount of at least one strain of microorganism is at least 10 6 CFU of microorganisms / dose, preferably about 10 6 ~about 10 12 CFU of microorganisms / dose, preferably about 10 8 ~about 10 12 CFU of microorganism / dose.

[0084] In one embodiment, the Bifidobacterium spp., preferably a strain of Bifidobacterium animalis ssp. lactis, e.g., Bifidobacterium animalis ssp. lactis (strain 420) (B420), is present in a concentration of about 10 6 ~about 10 12 CFU of microorganisms / day, preferably about 10 8 ~about 10 12 CFU of microorganisms / day. Thus, an effective amount in this embodiment is about 10 6 ~about 10 12 CFU of microorganisms / day, preferably about 108 ~about 10 12 CFU of microorganisms / day.

[0085] CFU is an abbreviation for “colony forming unit.” “Substrate” means a food, dietary supplement, or pharmaceutically acceptable formulation.

[0086] Effects / target / medical indications Bifidobacterium bacterial strains to which the present invention relates are administered to subjects, including, for example, livestock (including cattle, horses, pigs, and sheep), and humans. In some embodiments of the present invention, the subject is a companion animal (including a pet), such as a dog or cat. In some embodiments of the present invention, the subject may suitably be a human.

[0087] The one or more bacterial strains of the present invention may exhibit a beneficial clinical response in a subject for at least one of weight management, such as lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing 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.

[0088] The bacterial strain or strains to which the present invention relates may exhibit a beneficial clinical response in a subject of at least one of lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal fat mass, and / or reducing android fat mass.

[0089] composition While one or more bacterial strains can be administered alone, in particular embodiments of the invention, one or more bacterial strains are used in combination with one or more fibers and / or prebiotics, hi another particular embodiment, the fiber and / or prebiotic is polydextrose.

[0090] In particular embodiments, the one or more bacterial strains are in the form of a composition.

[0091] While it is possible for the compositions of the present invention to be administered alone (i.e., without any support, diluent, or excipient), they are typically, and preferably, administered on or in a support as part of a product, particularly as a component of an edible product, a dietary supplement, or a pharmaceutical composition or formulation, which products typically contain additional ingredients well known to those skilled in the art.

[0092] A "composition" is understood to be a combination of two or more substances, which may be chemical or biological, such as bacteria, including substances that exhibit a desired effect.

[0093] By "formulation" is understood a method or composition that combines different chemical and / or biological substances, including substances that exhibit a desired effect, to produce a final product. Composition and formulation may be used interchangeably.

[0094] The present invention may be used in any product that can benefit from the composition, including but not limited to food products, particularly fruit jams and dairy and dairy-derived products, and pharmaceutical products.

[0095] When used as or in the preparation of a food product, such as a functional food product, the compositions of the present invention may be used in combination with one or more of a nutritionally acceptable carrier, a nutritionally acceptable diluent, a nutritionally acceptable excipient, a nutritionally acceptable supplement, or a nutritionally active ingredient.

[0096] For example, the composition of the present invention can be used as an ingredient in soft drinks, fruit juice or whey protein drinks, health teas, cocoa drinks, milk drinks and lactic acid bacteria drinks, yogurt and drinking yogurt, cheese, ice cream, frozen desserts and desserts, confectionery, biscuits, cakes and cake mixes, snack foods, nutritionally balanced foods and drinks, fruit fillings, cake glazes, chocolate bread fillings, cheesecake-flavored fillings, fruit-flavored cake fillings, cake and donut icings, instant bread filling creams, cookie fillings, prepared bread fillings, low-calorie fillings, nutritional drinks for adults, acidic soy / juice drinks, aseptically filled / retort chocolate drinks, energy bars, powdered drinks, calcium-fortified soy milk / plain milk and chocolate milk, calcium-fortified coffee drinks.

[0097] The composition can also be used as an ingredient in edible products such as American cheese sauce, anti-caking agents for grated and shredded cheese, chip dips, cream cheese, non-fat sour cream dry blend whipped topping, freeze / thaw dairy whipped cream, freeze / thaw stable whipped topping, low-fat and low-calorie natural cheddar cheese, low-fat Swiss-style yogurt, aerated frozen desserts, hard-pack ice cream, affordable and generously portioned hard-pack ice cream with clear ingredient labeling, low-fat ice cream: soft serve, barbecue sauce, cheese dipping sauce, cottage cheese dressing, Alfredo sauce mix, mixed cheese sauce, tomato sauce mix, and the like.

[0098] The composition of the present invention may be used as a food ingredient and / or a feed ingredient.

[0099] As used herein, the term "food ingredient" or "feed ingredient" includes preparations that are or can be added as nutritional supplements to functional foods or foodstuffs.

[0100] The food ingredient may be in the form of a solution or as a solid, depending on the application and / or the method of use and / or the mode of administration.

[0101] edible products In one embodiment, the one or more bacterial strains of the present invention are in the form of an edible product, such as a food supplement, a drink, or milk powder. As used herein, the term "food" is used broadly to include human food as well as animal food (i.e., feed). In a preferred embodiment, the food is for human consumption.

[0102] The food may be in the form of a solution or as a solid, depending on the application and / or the method of use and / or the mode of administration.

[0103] Advantageously, if the product is an edible product comprising Bifidobacterium bacteria or a mixture thereof and one or more prebiotics and / or fiber, it should remain valid until the normal "sell by" or "use by" date offered by retailers at which the edible product is safe. Preferably, the shelf life should extend beyond such date to the end of the normal freshness period at which food spoilage becomes apparent. The desired length and normal shelf life will vary from food product to food product, and those skilled in the art will recognize that shelf life will vary depending on the type of food product, the size of the food product, storage temperature, processing conditions, packaging materials and packaging equipment.

[0104] Supplementary Foods One or more bacterial strains of the present invention may be - or may be added to - a dietary supplement, also referred to herein as a food supplement.

[0105] As used herein, the term "dietary supplement" refers to a product intended to be eaten that contains a "dietary ingredient" that is intended to add additional nutritional value to the diet (complement the diet). A "dietary ingredient" can be one or any combination of the following substances: vitamins, minerals, herbs or other botanical materials, amino acids, dietary substances that people use to supplement their diet by increasing their total dietary intake, concentrates, metabolites, constituents, or extracts.

[0106] Dietary supplements can be found in many forms, such as tablets, capsules, softgels, gelcaps, liquids, or powders. Some dietary supplements can help ensure adequate dietary intake of essential nutrients; others can help reduce the risk of disease.

[0107] functional food One or more bacterial strains of the present invention may be - or may be added to - a functional food.

[0108] As used herein, the term "functional food" means a food product that not only has the ability to provide a nutritional benefit, but also has the ability to provide additional beneficial effects to the consumer.

[0109] Thus, functional foods are ordinary foods that have incorporated therein components or ingredients (such as those described herein) that confer a special functional, e.g. medical or physiological, benefit on the food apart from a purely nutritional effect.

[0110] Although there is no legal definition of functional foods, most stakeholders in the field agree that they are foods marketed as having specific health benefits beyond basic nutritional benefits.

[0111] Some functional foods are nutraceuticals. As used herein, the term "nutraceuticals" refers to foods that not only provide nutritional benefits and / or taste satisfaction, but also have the ability to provide therapeutic (or other beneficial) effects to the consumer. Nutraceuticals transcend the traditional boundaries separating foods and medicines.

[0112] Medical Food In one embodiment, one or more bacterial strains of the present invention, such as Bifidobacterium animalis ssp. lactis strain 420 (B420), are in the form of a medical food product.

[0113] "Medical food" means a food formulated to be consumed or administered with or without medical supervision and intended for special dietary management or conditions whose unique nutritional requirements are established by medical evaluation based on generally accepted scientific principles.

[0114] Pharmaceuticals One or more bacterial strains of the present invention may be used as—or in the preparation of—a pharmaceutical formulation or composition. As used herein, the term "pharmaceutical" is used broadly—and includes human pharmaceuticals as well as animal pharmaceuticals (i.e., veterinary applications). In preferred embodiments, the pharmaceutical is for human use and / or for animal husbandry.

[0115] Medicinal products are intended for therapeutic purposes - they may be of a curative or symptomatic or prophylactic nature.

[0116] The pharmaceutically acceptable formulation or support or composition may be, for example, a formulation or support in the form of a compressed tablet, a tablet, a capsule, an ointment, a suppository or a drinking solution. Other suitable forms are provided below.

[0117] When used as - or in the preparation of - a pharmaceutical, one or more bacterial strains of the present invention may be used in combination with one or more of a pharmaceutically acceptable carrier, a pharmaceutically acceptable diluent, a pharmaceutically acceptable excipient, a pharmaceutically acceptable adjuvant, a pharmaceutically active ingredient.

[0118] The pharmaceutical product may be in the form of a solution or as a solid, depending on the intended use and / or the method of use and / or the mode of administration.

[0119] The bacterial strain(s) of the present invention may be used as a pharmaceutical ingredient, where the bacterial strain(s) may be the sole active ingredient, or it may be at least one of several (i.e., two or more) active ingredients.

[0120] Pharmaceutical formulations according to the present invention may be used in the form of solid or liquid preparations or alternative forms. Examples of solid preparations include, but are not limited to, tablets, capsules, powders, granules, and dusts, which may 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.

[0121] Suitable examples of forms include one or more of a tablet, pill, capsule, ovule, solution or suspension, which may contain flavoring or coloring agents, for immediate release, delayed release, modified release, sustained release, pulsed release or controlled release applications.

[0122] By way of example, when the pharmaceutical formulation of the present invention is used in the form of a tablet, such as when used as a functional ingredient, the tablet may also contain one or more of the following: 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 starch glycolate, croscarmellose sodium, and certain complex silicates; granulation binders such as polyvinylpyrrolidone, hydroxypropylmethylcellulose (HPMC), hydroxypropylcellulose (HPC), sucrose, gelatin, and acacia; and lubricants such as magnesium stearate, stearic acid, glyceryl behenate, and talc.

[0123] Further examples of forms include creams. In some embodiments, the microorganisms used in the present invention may be used in pharmaceutical and / or cosmetic creams, such as sunscreen and / or after-sun creams.

[0124] In one embodiment, the pharmaceutical formulations of the present invention may be administered as an aerosol, eg, as an intranasal spray, eg, for administration to the respiratory tract.

[0125] Treatment drugs In one embodiment, the pharmaceutically acceptable formulation of the present invention is a therapeutic agent.

[0126] The term "therapeutic agent," as used herein, encompasses therapeutic agents used in both human and veterinary medicine for both humans and animals. Additionally, the term "therapeutic agent," as used herein, refers to any substance that provides a therapeutic and / or beneficial effect. The term "therapeutic agent," as used herein, is not necessarily limited to substances that require marketing approval, but may include substances that may be used in cosmetics, nutraceuticals, foods (including, e.g., feed and beverages), probiotic cultures, and natural remedies. Additionally, the term "therapeutic agent," as used herein, encompasses products designed to be incorporated into animal feed, e.g., livestock feed and / or pet food.

[0127] Prebiotics In one embodiment, one or more bacterial strains according to the present invention are used in combination with one or more fibers and / or prebiotics.

[0128] Prebiotics are a category of functional foods defined as non-digestible food ingredients that affect the host by selectively stimulating the growth and / or activity of one or a limited number of bacteria (particularly, but not limited to, probiotics, bifidobacteria, and / or lactic acid bacteria) in the colon, thereby improving the health of the host. Typically, prebiotics are carbohydrates (such as oligosaccharides), although this definition does not exclude non-carbohydrates. The most common forms of prebiotics are nutritionally classified as soluble fiber. Many forms of dietary fiber, to some extent, exhibit some level of prebiotic effect.

[0129] In one embodiment, prebiotics are selectively fermented ingredients that allow for specific changes in both composition and / or activity of the gastrointestinal microbiota that confer benefits to the well-being and health of the host.

[0130] Suitably, prebiotics may be used in accordance with the present invention in amounts 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 may be used in accordance with the present invention in amounts of 1 to 10 g / day, preferably 2 to 9 g / day, more preferably 3 to 8 g / day. In another embodiment, prebiotics may be used in accordance with the present invention in amounts of 5 to 50 g / day, preferably 10 to 25 g / day.

[0131] Examples of dietary sources of prebiotics include soybeans, inulin sources (such as Jerusalem artichoke, jicama, and chicory root), raw oats, raw wheat, raw barley, and yacon.

[0132] Examples of suitable prebiotics include alginate, xanthan, pectin, locust bean gum (LBG), inulin, guar gum, galactooligosaccharides (GOS), fructooligosaccharides (FOS), polydextrose (i.e., Litesse®), lactitol, lactosucrose, soybean oligosaccharides, isomaltulose (Palatinose™), isomaltooligosaccharides, glucooligosaccharides, xylooligosaccharides, mannooligosaccharides, beta-glucans, cellobiose, raffinose, gentiobiose, melibiose, xylobiose, cyclodextrins, isomaltose, trehalose, stachyose, panose, pullulan, verbascose, galactomannans, and all forms of resistant starch.

[0133] A particularly preferred example of a fiber and / or prebiotic is polydextrose.

[0134] The Bifidobacterium and one or more fibers and / or prebiotics of the present invention exhibit synergistic effects (i.e., greater than the additive effects of the bacteria when used separately). Without wishing to be bound by theory, it is believed that such combinations have the ability to selectively stimulate the growth and / or activity of Bifidobacteria in the colon, thereby improving their efficacy and host health.

[0135] In one embodiment, the one or more bacterial strains of Bifidobacterium used in combination with the one or more fibers and / or prebiotics are of the species Bifidobacterium animalis. More preferably, the Bifidobacterium used in combination with the one or more fibers and / or prebiotics is Bifidobacterium animalis ssp. lactis.

[0136] In a particularly preferred embodiment, the Bifidobacterium used in combination with one or more fibers and / or prebiotics is Bifidobacterium animalis ssp. lactis strain 420 (B420).

[0137] Another particularly preferred embodiment of fiber and / or prebiotic is Litesse® Ultra polydextrose (LU).

[0138] Litesse® Ultra polydextrose (LU) is a randomly cross-linked glucose polymer that remains undigested by the host and can increase the number of bifidobacteria in colonic continuous culture systems.

[0139] Numbered embodiments of the invention: 1. A method for identifying a subject who exhibits an increased probability of exhibiting a beneficial clinical response to administration of a bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, comprising: i. the presence of the following biomarkers in a biological sample obtained from said subject: total hPAI1; a bile acid selected from GLCA, LCA, Iso-LCA, and DCA; a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); a species selected from the genera Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, unclassified Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes. coprostanoligenes); pimelic acid and azelaic acid; and / or measuring the subject's level of at least one of daily activity by step count or corresponding physical activity; and ii. comparing said level to a threshold value Including, The subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is greater than said threshold.

[0140] 2. The method of embodiment 1, wherein the beneficial clinical response to the bacterial strain of Bifidobacterium or the mixture of two or more of the strains thereof is at least one of weight management, such as reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal fat mass and / or reducing android fat mass in the subject, treating diabetes (preferably, but not limited to, type 2 diabetes), treating impaired glucose tolerance, normalizing insulin sensitivity, increasing fed insulin secretion, decreasing 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.

[0141] 3. The method of embodiment 2, wherein the beneficial clinical response to the bacterial strain of Bifidobacterium or a mixture of two or more of said strains thereof is at least one of lowering the subject's BMI, reducing body fat, lowering blood glucose levels, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal fat mass, and / or reducing android fat mass.

[0142] 4. The method of any one of embodiments 1 to 3, wherein the biological sample is a blood sample when the biomarker is selected from the group consisting of total hPAI1, bile acids selected from GLCA, LCA, Iso-LCA, and DCA.

[0143] 5. The method of any one of embodiments 1 to 4, wherein the biological sample is a fecal sample when the biomarker is a bacterium selected from the group consisting of Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes.

[0144] 6. The method of any one of embodiments 1 to 5, wherein when the biomarker is selected from pimelic acid and azelaic acid, the biological sample is a fecal sample.

[0145] 7. The method of any one of embodiments 1 to 6, wherein the biological sample is a blood sample when the biomarker is a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4).

[0146] 8. The method according to any one of the preceding embodiments, wherein the bacterial strain of Bifidobacterium or a mixture thereof is a probiotic bacterial strain.

[0147] 9. The method according to any one of embodiments 1 to 8, wherein the bacterial strain of the genus Bifidobacterium or a mixture of two or more of said strains thereof is of the species Bifidobacterium animalis, preferably of the species Bifidobacterium animalis subsp. lactis.

[0148] 10. The method of embodiment 9, wherein the bacterial strain of the species Bifidobacterium animalis subsp. Lactis is strain B420.

[0149] 11. The method of any one of embodiments 1 to 10, wherein the measured level of total hPAI1 in a biological sample obtained from said subject is greater than 48245 pg / ml.

[0150] 12. The method of any one of embodiments 1 to 11, wherein the measured level of GLCA in a biological sample obtained from said subject is greater than 0.0070 μmol / l.

[0151] 13. The method of any one of embodiments 1 to 12, wherein the measured level of LCA in a biological sample obtained from said subject is greater than 0.0380 μmol / l.

[0152] 14. The method of any one of embodiments 1-13, wherein the measured level of relative abundance of Coprococcus in a biological sample obtained from the subject is greater than 0.0426.

[0153] 15. The method of any one of embodiments 1 to 14, wherein the measured level of relative abundance of Ruminococcus in a biological sample obtained from said subject is greater than 0.0631.

[0154] 16. The method of any one of embodiments 1-15, wherein the measured level of relative abundance of Akkermansia in a biological sample obtained from said subject is greater than 0.0062.

[0155] 17. The method of any one of embodiments 1 to 16, wherein the measured level of relative abundance of Aminipila butyrica in a biological sample obtained from the subject is greater than 0.00043.

[0156] 18. The method of any one of embodiments 1 to 17, wherein the measured level of relative abundance of unclassified Clostridiales-Incertae Sedis XIII in a biological sample obtained from the subject is greater than 0.00018.

[0157] 19. The method of any one of embodiments 1 to 18, wherein the measured level of relative abundance of Eubacterium coprostanoligenes in a biological sample obtained from the subject is greater than 0.0084.

[0158] 20. The method of any one of embodiments 1 to 19, wherein the measured level of Iso-LCA in a biological sample, such as stool, obtained from the subject is greater than 29 μmol / l.

[0159] 21. The method of any one of embodiments 1 to 20, wherein the measured level of DCA in a biological sample, such as serum, obtained from the subject is greater than 0.41 nmol / ml.

[0160] 22. The method of any one of embodiments 1 to 21, wherein the measured level of the phospholipid phosphatidylcholine (36:4) in a biological sample obtained from the subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in positive ionization mode, is greater than 0.064.

[0161] 23. The method of any one of embodiments 1 to 22, wherein the measured level of the phospholipid phosphatidylcholine (32:1) in a biological sample obtained from the subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in positive ionization mode, is greater than 0.0037.

[0162] 24. The method of any one of embodiments 1 to 23, wherein the measured level of phospholipid phosphatidylethanolamine (38:4) in a biological sample obtained from the subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in positive ionization mode, is greater than 0.00074.

[0163] 25. The method of any one of embodiments 1 to 24, wherein the measured level of phospholipid phosphatidylethanolamine (36:4) in a biological sample obtained from the subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in negative ionization mode, is greater than 0.00091.

[0164] 26. The method of any one of embodiments 1 to 25, wherein the measured level of the phospholipid phosphatidylinositol (40:4) in a biological sample obtained from the subject, measured as a relative amount calculated as the peak area of ​​the phospholipid divided by the total peak area of ​​all lipids identified as described herein in negative ionization mode, is greater than 0.00019.

[0165] 27. The method of any one of embodiments 1 to 26, wherein the measured level of pimelic acid in a biological sample obtained from said subject, measured as a relative amount calculated as the peak area of ​​ion 125 m / z divided by the total peak area of ​​all peaks identified as described herein, is greater than 0.000126.

[0166] 28. The method of any one of embodiments 1 to 27, wherein the measured level of azelaic acid in a biological sample obtained from the subject, measured as a relative amount calculated as the peak area of ​​ion 83 m / z divided by the total peak area of ​​all peaks identified as described herein, is greater than 0.000135.

[0167] 29. The method of any one of embodiments 1-28, wherein the measured level when the biological sample is a blood sample is measured by LC-MS.

[0168] 30. The method of any one of embodiments 1-29, wherein the measured level when the biological sample is a fecal sample is measured by GC-MS and / or NMR.

[0169] 31. The method according to any one of embodiments 1 to 30, wherein measuring the level of at least one of the biomarkers is performed before administering to the subject a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof.

[0170] 32. The method of any one of embodiments 1-31, wherein the subject is overweight or obese.

[0171] 33. The method of any one of embodiments 1-32, wherein the subject has a BMI greater than 25.

[0172] 34. The method of any one of embodiments 1-33, wherein the subject has total hPAI1 and bile acid GLCA above the threshold.

[0173] 35. The method according to any one of embodiments 1 to 34, wherein the bacterial strain is used in combination with one or more fibers and / or prebiotics.

[0174] 36. The method of any one of embodiments 1-35, wherein the fiber and / or prebiotic is polydextrose.

[0175] 37. The method of any one of embodiments 1 to 36, wherein the bacterial strain is in the form of a composition, a food product, a dietary supplement or a pharmaceutically acceptable formulation.

[0176] 38. The method of embodiment 37, wherein the pharmaceutically acceptable formulation is a therapeutic agent.

[0177] 39. The method of embodiment 37, wherein the edible product is a medical food product.

[0178] 40. The method according to any one of embodiments 1 to 39, wherein the subject's daily activity in steps is greater than 7000 steps or a corresponding physical activity.

[0179] 41. Reducing a subject's BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing fasting insulin secretion, improving glucose tolerance, treating obesity, tissue inflammation (particularly, but not limited to, 2. Use of a bacterial strain of Bifidobacterium or a mixture of two or more strains thereof for at least one of reducing inflammation (muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation), treating hepatitis, treating myositis, treating cardiovascular disease and managing weight, including treating metabolic syndrome, wherein the subject has been identified as exhibiting an increased probability of exhibiting a beneficial clinical response to administration of the bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, which i. the presence of the following biomarkers in a biological sample obtained from said subject: total hPAI1; a bile acid selected from GLCA, LCA, Iso-LCA, and DCA; a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); a species selected from the genera Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, unclassified Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes. coprostanoligenes); pimelic acid and azelaic acid; and / or measuring the level of at least one of the subject's daily activity by step count; and ii. comparing said level to a threshold value It was identified by The use wherein a subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is higher than said threshold.

[0180] 42. Use of a bacterial strain or a mixture of two or more strains of the genus Bifidobacterium according to embodiment 39 as further defined in any one of embodiments 1 to 40.

[0181] 43. Reducing a subject's BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing fasting insulin secretion, improving glucose tolerance, treating obesity, tissue inflammation (particularly, but not limited to, 2. A bacterial strain of Bifidobacterium or a mixture of two or more strains thereof for use in managing weight, including but not limited to reducing inflammation in muscle tissue, liver tissue, and / or adipose tissue), treating hepatitis, treating myositis, treating cardiovascular disease, and treating metabolic syndrome, wherein the subject has been identified as exhibiting an increased probability of exhibiting a beneficial clinical response to administration of the bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, which i. the presence of the following biomarkers in a biological sample obtained from said subject: total hPAI1; a bile acid selected from GLCA, LCA, Iso-LCA, and DCA; a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); a species selected from the genera Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, unclassified Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes. coprostanoligenes); pimelic acid and azelaic acid; and / or measuring the level of at least one of the subject's daily activity by step count; and ii. comparing said level to a threshold value It was identified by A bacterial strain of the genus Bifidobacterium, or a mixture of two or more strains thereof, wherein a subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is higher than said threshold.

[0182] 44. A bacterial strain or a mixture of two or more strains of the genus Bifidobacterium for use according to embodiment 43 as further defined in any one of embodiments 1 to 40.

[0183] 45. Reducing BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing fasting insulin secretion, improving glucose tolerance, treating obesity, tissue inflammation (particularly, but not limited to, muscle tissue inflammation, 1. A method for managing the weight of a subject in need thereof, such as reducing liver tissue inflammation and / or adipose tissue inflammation, treating hepatitis, treating myositis, treating cardiovascular disease, and treating metabolic syndrome, the method comprising administering to the subject a bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, wherein the subject has been identified as exhibiting an increased likelihood of exhibiting a beneficial clinical response to the administration of the bacterial strain of Bifidobacterium or a mixture of two or more strains thereof, which is i. the presence of the following biomarkers in a biological sample obtained from said subject: total hPAI1; a bile acid selected from GLCA, LCA, Iso-LCA, and DCA; a phospholipid selected from phosphatidylcholine (36:4), phosphatidylcholine (32:1), phosphatidylethanolamine (38:4), phosphatidylethanolamine (36:4), and phosphatidylinositol (40:4); a species selected from the genera Coprococcus, Ruminococcus, Akkermansia, Aminipila butyrica, unclassified Clostridiales - Incertae Sedis XIII, and Eubacterium coprostanoligenes. coprostanoligenes); pimelic acid and azelaic acid; and / or measuring the level of at least one of the subject's daily activity by step count; and ii. comparing said level to a threshold value It was identified by The subject is identified as exhibiting said increased probability when the measured level of at least one of the biomarkers is greater than said threshold.

[0184] 46. ​​The method of embodiment 45 as further defined in any one of embodiments 1 to 40.

[0185] 47. A method for managing the weight of a subject in need thereof, including lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing body fat mass, reducing mesenteric fat mass, reducing truncal 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 fed insulin secretion, decreasing 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, i. Prescribing the subject a personal daily activity of more than 7,000 steps per day or corresponding physical activity; and ii. A method comprising administering a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof to a subject who has performed the activity according to i), wherein the subject exhibits an increased probability of exhibiting a beneficial clinical response to the administration of said bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof.

[0186] 48. The method according to embodiment 47, wherein the bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof is defined in any one of embodiments 8 to 10. [Example]

[0187] Introduction The following example is based on a multivariate data analysis of the results of the MetSProb study (Stenman 2016). MetSProb was a randomized, double-blind, placebo-controlled clinical trial (ClinicalTrials.gov NCT01978691) conducted in Finland on an overweight and obese study population. These results were published in two original articles in 2016 (Stenman et al. 2016) and 2019 (Hibberd et al. 2019).

[0188] Stenman et al. reported initial results showing that probiotics, alone or in combination with prebiotics, control body fat mass in healthy overweight or obese subjects. A second published paper by Hibberd et al. (2019) investigated the association between gut microbiota and observed clinical benefits after a 6-month intervention with prebiotic, probiotic, and synbiotic products. They found that the probiotic strain B420 and its combination with polydextrose (PDX) altered gut microbiota and its metabolism, potentially supporting improvements in gut barrier function and obesity-related markers.

[0189] The MetSProb study (Stenman 2016) measured a large number of parameters (130 in total, including glucose, insulin, total hPAI1, bile acids, bacteria, etc.) in blood and fecal samples collected from subjects in the study population.

[0190] Applying multivariate latent class analysis statistical models to all measured data for all 130 parameters from subjects in the MetSProb human clinical trial, it was surprising to find that only a set of six baseline variables was predictive of weight loss or reduced weight gain in the B420-supplemented group compared with the placebo group over the 6-month intervention. Weight loss, in this study, was measured as body mass index (BMI), DXA truncal fat (DXA_TrFa), DXA android fat (DXA_AnFa), and DXA total fat (DXA_fat).

[0191] 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 blood and in the fecal bacteria Coprococcus, Ruminococcus, and Akkermansia.

[0192] Statistical MANOVA analysis confirmed the findings of these six predictor variables.

[0193] Subjects can be classified as responders or non-responders to a Bifidobacterium B420 intervention based on one or more of six predictor variables. Samples can be collected as blood or fecal samples, and predictions can use median thresholds, as shown in the example below.

[0194] Participants and study design (Hibberd et al. 2019) We conducted a double-blind, randomized, parallel-group, placebo-controlled clinical trial in overweight and obese adults to investigate the effects of a probiotic, prebiotic, or synbiotic (probiotic plus prebiotic) intervention on body fat mass and obesity-related markers. The study population and clinical outcomes have been described in detail previously (Stenman et al., 2016) and are summarized here.

[0195] 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 otherwise healthy. Exclusion criteria included a diagnosis of type 1 or type 2 diabetes or cardiovascular disease, bariatric surgery, pregnant or breastfeeding women, recent use of laxatives, immunomodulatory medications, high-dose vitamin D supplements, fiber supplements (within the past 6 weeks), probiotics (6 weeks), antibiotics (2 months), anti-obesity medications (3 months), participation in a weight-loss program (3 months), or a weight change of 3 kg in the past 3 months. Participants were randomized to four groups: (1) placebo, 12 g / day of microcrystalline cellulose; (2) prebiotic LU, 12 g / day; (3) probiotic Bifidobacterium animalis subsp. lactis 420™ (B420), 10 cfu / day in 12 g of microcrystalline cellulose; or (4) synbiotic LU + B420, 10 cfu / day in 12 g of LU. The test product was manufactured in sachets by DuPont Nutrition and Health (Madison, WI, USA), and participants were instructed to mix it into a commercially available fruit smoothie (130 kcal) once daily while continuing their usual diet and exercise habits. Participants attended clinic visits for screening and baseline assessments, followed by 2, 4, and 6 months after study drug use. A follow-up visit occurred 1 month after intervention completion. Participants were monitored for study drug compliance and protocol violations as previously described (Stenman et al., 2016), and baseline characteristics of the protocol-compliant population (n=134) are summarized in Table 1.Body composition and metabolic biomarkers measured from participants included fat mass and lean mass (total, android (waist region), gynoid (hip region), trunk, legs, and arms) measured by dual-energy X-ray absorptiometry (DXA), BMI, waist and hip circumference, and blood markers serum hsCRP, serum glucose, serum insulin, blood glycosylated hemoglobin, serum lipids (total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein, and triglycerides), serum cortisol, and serum liver markers (aspartate aminotransferase; alanine aminotransferase; and gamma-glutamyltransferase) in fasting participants (Stenman et al., 2016). [ka]

[0196] Sampling and processing (Hibberd et al. 2019). Fecal samples were obtained from participants at the baseline visit, between study intervention visits (months 2, 4, and 6), and one month after the end of treatment (month +1). Samples were immediately frozen and stored at -80°C until analysis. All samples were analyzed for fecal microbiota, and fecal metabolites and bile acids were analyzed from the baseline and six-month visits. Fasting blood samples collected at baseline and the six-month visit were used for plasma bile acid analysis.

[0197] Example 1: Statistical Analysis This study aims to identify baseline biomarkers associated with responder status during the intervention period in individual subjects receiving active treatment (B420) compared with placebo treatment.

[0198] experiment The MetSProb human clinical trial is a cross-sectional design in which subjects receive either placebo (N=36) or active drug (B420, N=25) treatment and multiple parameters are assessed at two paired time points (v2=baseline, v8=6 months post-intervention).

[0199] The objective is to explore whether baseline (v2) biomarkers are associated with responder status during the intervention period (v8-v2) for strain B420 vs. placebo.

[0200] Responder status was based on four weight and body composition parameters (Body Mass Index (BMI), DXA Trunk Fat (DXA_TrFa), DXA Androgen Fat (DXA_AnFa), and DXA Total Fat (DXA_fat)). Responders were subjects who experienced weight loss (i.e., v8-v2 difference less than 0). Otherwise, subjects were classified as non-responders.

[0201] When any v8-v2 weight and body composition parameter is plotted against any baseline (v2) parameter for the two treatment populations (B420 and placebo), the pattern of the difference in slope for B420 vs. placebo will indicate whether it is a biomarker. If the difference in slope (B420 vs. placebo) is significantly different from 0 at the 5% level, it is a biomarker; 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.

[0202] The software used is SAS 9.4 (SAS Institute Inc., Cary, NC, USA. 2016).

[0203] Exploratory statistical analysis A multivariate latent class analysis model was fitted to all parameters at the two time points (v2, v8), and from this model, a directed submodel was derived that fitted the four weight and body composition parameters (BMI, DXA_TrFa, DXA_AnFa, DXA_fat) (v8-v2) to all baseline (v2) parameters, allowing statistical quantification of the difference in slope (B420 vs. placebo) (referred to as "j1").

[0204] The results of this analysis are summarized in Table 2.

[0205] [Table 1]

[0206] The three information carriers (j1, R_j1, NR_j1) are the Z scores of the slope difference (B420 vs. placebo) for the prospective setup (responder status remains unknown; j1) and the retrospective setup for responders (R_j1) and non-responders (NR_j1), respectively.

[0207] If "j1" is significant, it means that either one (R_j1, NR_j1) or both are significant.

[0208] If "j1" is significant, it means a reduction in weight; if "R_j1" is significant, it means a weight loss; if "NR_j1" is significant, it means a reduction in weight gain.

[0209] From Table 2, it can be observed that six parameters (total hPAI1, GLCA, LCA, Coprococcus, Ruminococcus, Akkermansia) are identified as baseline biomarkers, all with negative signs meaning that higher values ​​are associated with an increased probability of being a responder.

[0210] Confirmatory statistical analysis The six predictor biomarkers identified in Table 2 are all confirmed as bona fide biomarkers through simpler modeling.

[0211] Let the response be the four body weight and body composition measures (BMI, DXA_TrFa, DXA_AnFa, DXA_fat) for v8 - v2 at raw scale (applying mean centering and unit scaling). Let the regressor be any single one of the six biomarkers for baseline (v2) at raw scale. Let the treatment identifier (B420, placebo) be the class variable.

[0212] Apply MANOVA (Multivariate Analysis of Variance; type = CS) using PROC MIXED with different slopes for the two treatments (B420 and placebo) to estimate the mean value of the difference in slopes (B420 - placebo). The p - value (Pr<t) is one - sided (lower - sided).

[0213] Table 3 is the SAS output (PROC MIXED) for each of the six biomarkers individually.

[0214]

Table 2

[0215] The threshold of the predictor can be calculated from the measured data as the median (50th percentile) and the 33:66 percentile range. Table 4 shows the thresholds.

[0216]

Table 3

[0217] The findings of the latent class analysis are confirmed by the MANOVA analysis.

[0218] Example 2 - Total hPAI1 Results Total hPAI1 is human plasminogen activator inhibitor - 1 (PAI - 1), a serine protease inhibitor (serpin) encoded by the SERPINE1 gene. An increase in PAI - 1 is a risk factor for thrombosis and atherosclerosis, but also for other diseases such as cancer.

[0219] Total human plasminogen activator inhibitor-1 (total hPAI1) in blood samples was found to be a significant predictor of weight loss by latent class analysis model (Example 1). Both the predictive Z-score and the responder Z-score were significant and negative, indicating that high total hPAI1 levels were predictive of weight loss during the 6-month intervention with B420. The blood concentration threshold for predictive weight loss in subjects was in the range [40653:53294] pg / mL, with a median of 48245 pg / mL. Figure 1 shows BMI (kg / m2) over the 6-month intervention plotted against total hPAI1 at baseline for each subject in the intervention group B420 (N=25) and the placebo group (N=36). 2 ) change (v8-v2). The median threshold is plotted in the same way.

[0220] From the confirmatory analysis (Table 4), when the linear regression line is used to illustrate the differences, it can be observed from Figure 1 that the placebo group gained weight / positive increase in BMI at 6 months of intervention, while the B420 group lost weight / negative trend line in BMI.

[0221] Show me how Blood clinical determination of total human plasminogen activator inhibitor-1 (total hPAI1) is measured using an ELISA assay (pg / mL) as described in Stenman 2016 - Supplementary Information.

[0222] Statistical analysis: See Example 1.

[0223] Example 3 - Bile Acid Results The secondary bile acids glycolithocholic acid (GLCA) and lithocholic acid (LCA) in blood samples were found to be significant predictors of weight loss using a latent class analysis model (Example 1). Both the predictive Z-score and the responder Z-score were significant and negative for both GLCA and LCA, indicating that high levels of either secondary bile acid were predictive of weight loss during the 6-month B420 intervention. The blood concentration thresholds for predictive weight loss for subjects should be in the ranges [0.0033:0.0078] and [0.0301:0.0583] for GLCA and LCA, respectively, with medians of 0.0070 μmol / L and 0.0380 μmol / L. Figures 2 and 3 show the BMI (kg / m) over the 6-month intervention plotted against baseline bile acid concentrations for each subject in the B420 intervention group (N=25) and placebo group (N=36). 2 ) change (v8-v2). The median threshold is plotted in the same way.

[0224] From the confirmatory analysis (Table 4), when the linear regression lines are used to illustrate the differences, it can be observed from Figures 2 and 3 that the placebo group gained weight / BMI had a positive trend line, while the B420 group lost weight / BMI had a negative trend line at 6 months of intervention.

[0225] Secondary bile acids (e.g., LCA) are produced by bacteria in the microbiome, and these secondary bile acids can undergo conjugation in the liver (e.g., GLCA).

[0226] Method Description: Plasma Bile Acid Analysis - LC-MRM-MS Plasma bile acid analysis was performed using fasting blood samples collected at both baseline and 6-month visits. Sample preparation was performed in triplicate and samples were stored at -80°C until analysis.

[0227] A mixture of 15 stable isotope-labeled bile acids was added to an Eppendorf tube and the solvent was evaporated (Table 5).

[0228] [Table 4]

[0229] For each replicate, 50 μL of plasma was vortexed with 100 μL of 1% formic acid and 350 μL of acetonitrile was added. The tubes were sonicated for 10 minutes and then placed on ice for 30 minutes to aid protein precipitation. After centrifugation at 16,000 × g for 2 minutes, the supernatant was loaded onto an activated Phenomenex Phree phospholipid removal 96-well SPE plate. The plate was centrifuged at 500 × g for 5 minutes, and the initial eluate was collected in a 1 mL 96-well collection plate. Each well was washed with 500 μL of 0.2% formic acid in 70% acetonitrile. The flow-through was pooled with the initial flow-through and dried in a vacuum concentrator. The precipitate was reconstituted in 100 μL of 50% methanol in water.

[0230] An Agilent 1290 UHPLC system was coupled to a Thermo TSQ Vantage via a modified heated electrospray ionization (HESI) source in negative mode. Waters ACQUITY UPLC BEH C 18 A (2.1 mm × 150 mm, 1.7 μm, 100 Å) column was used with gradient elution using 0.01% formic acid in water (solvent A) and 0.01% formic acid in acetonitrile (solvent B) as the mobile phase. The gradient was optimized from 25% to 40% B in 12 min, followed by 40% to 75% B in 14 min. Between injections, the column was washed with 100% B for 2 min and equilibrated at 25% B for 4 min. The flow rate was 0.35 mL / min, and the column was maintained at 45°C. The injection volume was 10 μL.

[0231] Mass spectrometry settings for the TSQ instrument in EZ mode were negative mode, spray voltage: 3000 V, capillary temperature: 320 °C, sheath gas: 45 psi, AUX gas 5, vaporizer gas temperature: 300 °C, collision pressure: 1.3 mTorr, and cycle time: 0.800 s.

[0232] Statistical analysis: See Example 1

[0233] Example 4 - Results for the fecal bacteria Coprococcus and Ruminococcus The relative abundance of the bacteria Coprococcus and Ruminococcus, identified by sequencing 16S rRNA from feces, was found to be a significant predictor of reduced weight gain using latent class analysis models (Example 1). The predictive Z-score and non-responder Z-score for both Coprococcus and Ruminococcus were both significantly negative, and the responder Z-score was negative but not significant, indicating that high levels of either genera predicted reduced weight gain during the 6-month B420 intervention. The fecal relative abundance thresholds for reduction in subject prospective weight gain ranged from [0.0360:0.0537] and [0.0319:0.0921] for Coprococcus and Ruminococcus, respectively, with medians of 0.0426 and 0.0631. Figures 4 and 5 show BMI (kg / m) over the 6-month intervention plotted against the relative abundance of Coprococcus and Ruminococcus for each subject in the intervention group B420 (N=25) and placebo group (N=36). 2 ) change (v8-v2) and threshold.

[0234] From the confirmatory analysis (Table 4), when the linear regression lines are used to illustrate the differences, it can be observed from Figures 4 and 5 that the placebo group gained weight / BMI had a positive trend line, while the B420 group lost weight / BMI had a negative trend line at 6 months of intervention.

[0235] Methods description: DNA isolation and microbiota sequencing (from Hibberd 2019). Microbial DNA was extracted from fecal samples using the MagMAX™ Total Nucleic Acid Isolation Kit (Applied Biosystems, Bridgewater, NJ, USA) and purified using the OneStep-96™ PCR Inhibitor Removal Kit (Zymo Research, Irvine, California, USA). Microbial DNA was amplified by triplicate PCR with primers 515F (5'-GTGCCAGCMGCCGCGGTAA) and 806R (5'-GGACTACHVGGGTWTCTAAT) targeting the V4 variable region of the 16S rRNA gene. PCR amplification conditions included an initial DNA denaturation at 95°C for 3 minutes, followed by 30 cycles of 95°C for 45 seconds, 55°C for 60 seconds, and 72°C for 90 seconds; and a final extension at 72°C for 10 minutes. PCR products were purified, normalized, and paired-end 2 × 250 bp reads were generated on an Illumina MiSeq system (Roy J. Carver Biotechnology Center, University of Illinois Urbana-Champaign).

[0236] Statistical analysis: See Example 1.

[0237] Example 5 - Results for fecal bacteria Akkermansia The relative abundance of the bacterium Akkermansia, identified by sequencing 16S rRNA from feces, was found to be a significant predictor of reduced weight gain using a latent class analysis model (Example 1). The predictive Z-score and non-responder Z-score for Akkermansia were both negative and significant, while the responder Z-score was negative but not significant, indicating that high levels of Akkermansia predicted reduced weight gain during a 6-month B420 intervention. For Akkermansia, the fecal relative abundance threshold for reduced subject weight gain ranged from [0.0041 to 0.0118], with a median of 0.0062. Figure 6 shows the BMI (kg / m) over the 6-month intervention plotted against the relative abundance of Akkermansia for each subject in the intervention group B420 (N=25) and the placebo group (N=36). 2 ) change (v8-v2) and threshold are shown.

[0238] From the confirmatory analysis (Table 4), when the linear regression lines are used to illustrate the differences, it can be observed from Figure 6 that the placebo group gained weight / BMI has a positive trend line at 6 months of intervention, while the B420 group also gained weight / BMI has a positive trend line, but to a lesser extent than placebo. The predictor Akkermansia predicts a smaller weight gain / smaller change in BMI at baseline for the 6 months of intervention with B420 compared to the placebo group.

[0239] Method description: See Example 4.

[0240] Example 6 Total human plasminogen activator inhibitor-1 (total hPAI1) in blood samples was found to be a significant predictor of weight loss using latent class analysis models. Significant negative predictive and responder Z-scores indicate that high total hPAI1 levels predict weight loss during the 6-month B420 intervention. The blood concentration thresholds for predictive weight loss for subjects ranged from [40653:53294] pg / mL, with a median of 48245 pg / mL (Table 4). Figure 7 shows the change in trunk fat (v8-v2) by DXA scan over the 6-month intervention plotted against baseline total hPAI1 for each subject in the B420 intervention group (N=25) and the placebo group (N=36). The median total hPAI1 threshold is also plotted.

[0241] Using a linear regression line to illustrate the differences, it can be observed from Figure 7 that at 6 months of intervention the placebo group gained weight / positive increase in trunk fat, while the B420 group lost trunk fat / negative trunk fat trend line.

[0242] Method Description: Trunk fat, android fat, and total fat will be measured by dual energy X-ray absorptiometry (DXA) scan as described in Stenman 2016 - change will be measured in grams.

[0243] Determination and statistical analysis of total HPAI1: Example 2.

[0244] Example 7 The secondary bile acids glycolithocholic acid (GLCA) and lithocholic acid (LCA) in blood samples were found to be significant predictors of weight loss using latent class analysis models. Both the predictive and responder Z-scores were significant and negative for both GLCA and LCA, indicating that high levels of either secondary bile acid predicted weight loss during 6 months of B420 treatment. The blood concentration thresholds for subjective predictive weight loss should be in the ranges [0.0033:0.0078] and [0.0301:0.0583] for GLCA and LCA, respectively, with medians of 0.0070 μmol / L and 0.0380 μmol / L. Figures 8 and 9 show the change in trunk fat by DXA scan (v8-v2) over the 6-month intervention plotted against baseline bile acid concentrations for each subject in the intervention group B420 (N=25) and the placebo group (N=36). Median thresholds for GLCA and LCA are also plotted.

[0245] From the confirmatory analysis (Table 4), when the linear regression lines are used to illustrate the differences, it can be observed from Figures 8 and 9 that at 6 months of intervention the placebo group had an increase in trunk fat / positive trunk fat trend line, while the B420 group had a decrease in trunk fat / negative trunk fat trend line.

[0246] Description of methods: Bile acid determination: See Example 3. DXA scan method: See Example 6. Statistical analysis: See Example 1.

[0247] Example 8 The relative abundance of the bacteria Coprococcus and Ruminococcus, identified by sequencing 16S rRNA from feces, was found to be a significant predictor of reduced weight gain using latent class analysis models (Example 1). For both Coprococcus and Ruminococcus, the predictive Z-score and non-responder Z-score were both significantly negative, and the responder Z-score was negative but not significant, indicating that high levels of either genera predicted reduced weight gain during the 6-month intervention with strain B420. The fecal relative abundance thresholds for reduction in subject prospective weight gain ranged from [0.0360:0.0537] and [0.0319:0.0921] for Coprococcus and Ruminococcus, respectively, with medians of 0.0426 and 0.0631. Figures 10 and 11 show the change in trunk fat (v8-v2) measured by DXA scan over the 6-month intervention plotted against the relative abundance of Coprococcus and Ruminococcus for each subject in the intervention group B420 (N=25) and placebo group (N=36), as well as the thresholds.

[0248] From the confirmatory analysis (Table 4), when the linear regression lines are used to illustrate the differences, it can be observed from Figures 10 and 11 that at 6 months of intervention the placebo group had an increase in trunk fat / positive trend line for BMI, while the B420 group had a decrease in trunk fat / negative trend line.

[0249] Methods description: Fecal microbiome 16S rRNA sequencing: See Example 4. DXA scan methods: See Example 6. Statistical analysis: See Example 1.

[0250] Example 9 The relative abundance of the bacterium Akkermansia, identified by sequencing 16S rRNA from feces, was found to be a significant predictor of reduced weight gain using a latent class analysis model (Example 1). The predictive Z-score and non-responder Z-score for Akkermansia were both negative and significant, while the responder Z-score was negative but not significant, indicating that high levels of Akkermansia predicted reduced weight gain during a 6-month B420 intervention. The fecal relative abundance threshold for reduced subject weight gain was in the range [0.0041:0.0118] for Akkermansia, with a median of 0.0062. In Figure 12, the change in trunk fat (v8-v2) over the 6-month intervention plotted against the relative abundance of Akkermansia for each subject in the intervention group B420 (N=25) and the placebo group (N=36) and the median threshold.

[0251] From the confirmatory analysis (Table 4), when the linear regression lines are used to illustrate the differences, it can be observed from Figure 12 that at 6 months of intervention the placebo group has increased truncal fat / positive trend line, while the B420 group also has increased truncal fat / positive trend line, but to a lesser extent than placebo. The predictor Akkermansia predicts a smaller increase in truncal fat at baseline for the 6-month intervention with B420 compared to the placebo group.

[0252] Method description: See Example 8.

[0253] Example 10 Total human plasminogen activator inhibitor-1 (total hPAI1) in blood samples was found to be a significant predictor of weight loss using latent class analysis. Both the predictive and responder Z-scores were significant and negative, indicating that high total hPAI1 levels predicted weight loss during the 6-month B420 intervention. The blood concentration thresholds for predictive weight loss for subjects ranged from [40653:53294] pg / mL, with a median of 48245 pg / mL (Table 4). Figure 13 shows the change in android fat (v8-v2) by DXA scan over the 6-month intervention plotted against baseline total hPAI1 for each subject in the B420 intervention group (N=25) and placebo group (N=36). The median total hPAI1 threshold is also plotted.

[0254] From the confirmatory analysis (Table 4), when the linear regression line is used to illustrate the differences, it can be observed from Figure 13 that at 6 months of intervention, the placebo group had an increase in android fat / positive trend line, while the B420 group had a decrease in android fat / negative trend line.

[0255] Method description: See Example 6.

[0256] Example 11 The secondary bile acids glycolithocholic acid (GLCA) and lithocholic acid (LCA) in blood samples were found to be significant predictors of weight loss using latent class analysis models. Both the predictive and responder Z-scores were significant and negative for both GLCA and LCA, indicating that high levels of either secondary bile acid predicted weight loss during 6 months of B420 treatment. The blood concentration thresholds for subjective predictive weight loss should be in the ranges [0.0033:0.0078] and [0.0301:0.0583] for GLCA and LCA, respectively, with medians of 0.0070 μmol / L and 0.0380 μmol / L. 14 and 15 show the change in android fat (v8-v2) by DXA scan over the 6-month intervention plotted against baseline bile acid concentrations for each subject in the intervention group B420 (N=25) and the placebo group (N=36). Median threshold values ​​for GLCA and LCA are also plotted.

[0257] From the confirmatory analysis (Table 4), when the linear regression line is used to illustrate the differences, it can be observed from Figures 14 and 15 that at 6 months of intervention, the placebo group had an increase in android fat / positive trend line, while the B420 group had a decrease in android fat / negative trend line.

[0258] Method description: See Example 7.

[0259] Example 12 The relative abundance of the bacteria Coprococcus and Ruminococcus, identified by sequencing 16S rRNA from feces, was found to be a significant predictor of reduced weight gain using latent class analysis models (Example 1). For both Coprococcus and Ruminococcus, the predictive Z-score and non-responder Z-score were both significantly negative, and the responder Z-score was negative but not significant, indicating that high levels of either genera predicted reduced weight gain during the 6-month B420 intervention. The fecal relative abundance thresholds for reduction in subject predicted weight gain ranged from [0.0360:0.0537] and [0.0319:0.0921] for Coprococcus and Ruminococcus, respectively, with medians of 0.0426 and 0.0631. Figures 16 and 17 show the change in android fat (v8-v2) over the 6-month intervention plotted against the relative abundance of Coprococcus and Ruminococcus for each subject in the intervention group B420 (N=25) and placebo group (N=36), as well as the median thresholds.

[0260] From the confirmatory analysis (Table 4), when the linear regression line is used to illustrate the difference, it can be observed from Figures 16 and 17 that at 6 months of intervention, the placebo group increased android fat / positive trend line, while the B420 group decreased android fat / negative trend line. The predictive effect of Ruminococcus on reducing android fat is less significant compared to Coprococcus.

[0261] Method description: See Example 8

[0262] Example 13 The relative abundance of the bacterium Akkermansia, identified by sequencing 16S rRNA from feces, was found to be a significant predictor of reduced weight gain using a latent class analysis model (Example 1). The predictive Z-score and non-responder Z-score for Akkermansia were both negative and significant, while the responder Z-score was negative but not significant, indicating that high levels of Akkermansia predicted reduced weight gain during a 6-month B420 intervention. The fecal relative abundance threshold for reduced subject weight gain was in the range [0.0041:0.0118] for Akkermansia, with a median of 0.0062. Figure 18 shows the change in android fat (v8-v2) over the 6-month intervention plotted against the relative abundance of Akkermansia for each subject in the intervention group B420 (N=25) and the placebo group (N=36) as well as the median threshold.

[0263] From the confirmatory analysis (Table 4), when the linear regression lines are used to illustrate the differences, it can be observed from Figure 18 that at 6 months of intervention the placebo group has increased truncal fat / positive trend line, while the B420 group also has increased truncal fat / positive trend line, but to a lesser extent than placebo. The predictor Akkermansia predicts a smaller change in android fat gain for the 6 months of intervention with B420 compared to the placebo group at baseline.

[0264] Method description: See Example 8

[0265] Example 14 Total human plasminogen activator inhibitor-1 (total hPAI1) in blood samples was found to be a significant predictor of weight loss using latent class analysis models. Both the predictive and responder Z-scores were significant and negative, indicating that high total hPAI1 levels predicted weight loss during the 6-month B420 intervention. The blood concentration threshold for predictive weight loss for subjects was in the range [40653:53294] pg / mL (33; 66th percentile), with a median of 48245 pg / mL. Figure 19 shows the change in total fat (v8-v2) by DXA scan over the 6-month intervention plotted against baseline total hPAI1 for each subject in the B420 intervention group (N=25) and the placebo group (N=36). The median total hPAI1 threshold is also plotted.

[0266] From the confirmatory analysis (Table 4), when the differences are illustrated using linear regression lines, it can be observed from Figure 19 that at 6 months of intervention the placebo group increased total fat / positive trend line, while the B420 group decreased total fat / negative trend line.

[0267] Method description: See Example 6.

[0268] Example 15 The secondary bile acids glycolithocholic acid (GLCA) and lithocholic acid (LCA) in blood samples were found to be significant predictors of weight loss using latent class analysis models. Both the predictive and responder Z-scores were significant and negative for both GLCA and LCA, indicating that high levels of either secondary bile acid predicted weight loss during 6 months of B420 treatment. The blood concentration thresholds for subjective predictive weight loss should be in the ranges [0.0033:0.0078] and [0.0301:0.0583] for GLCA and LCA, respectively, with medians of 0.0070 μmol / L and 0.0380 μmol / L. 20 and 21 show the change in total fat by DXA scan (v8-v2) over the 6-month intervention plotted against baseline bile acid concentrations for each subject in the intervention group B420 (N=25) and the placebo group (N=36). Median threshold values ​​for GLCA and LCA are also plotted.

[0269] From the confirmatory analysis (Table 4), when the differences are illustrated using linear regression lines, it can be observed from Figures 20 and 21 that the placebo group increased total fat / positive trend line while the B420 group decreased total fat / negative trend line at 6 months of intervention.

[0270] Method description: See Example 7.

[0271] Example 16 The relative abundance of the bacteria Coprococcus and Ruminococcus, identified by sequencing 16S rRNA from feces, was found to be a significant predictor of reduced weight gain using latent class analysis models (Example 1). For both Coprococcus and Ruminococcus, the predictive Z-score and non-responder Z-score were both significantly negative, and the responder Z-score was negative but not significant, indicating that high levels of either genera predicted reduced weight gain during the 6-month B420 intervention. The fecal relative abundance thresholds for reduction in subject prospective weight gain ranged from [0.0360:0.0537] and [0.0319:0.0921] for Coprococcus and Ruminococcus, respectively, with medians of 0.0426 and 0.0631. Figures 22 and 23 show the change in total fat (v8-v2) over the 6-month intervention plotted against the relative abundance of Coprococcus and Ruminococcus for each subject in the intervention group B420 (N=25) and placebo group (N=36), as well as the median thresholds.

[0272] From the confirmatory analysis (Table 4), when the differences are illustrated using linear regression lines, it can be observed from Figures 22 and 23 that at 6 months of intervention the placebo group increased total fat / positive trend line, while the B420 group decreased total fat / negative trend line.

[0273] Method description: See Example 8.

[0274] Example 17 The relative abundance of the bacterium Akkermansia, identified by sequencing 16S rRNA from feces, was found to be a significant predictor of reduced weight gain using a latent class analysis model (Example 1). The predictive Z-score and non-responder Z-score for Akkermansia were both negative and significant, while the responder Z-score was negative but not significant, indicating that high levels of Akkermansia predicted reduced weight gain during 6 months of B420 treatment. The fecal relative abundance threshold for predictive total fat change for subjects was in the range [0.0041:0.0118], with a median of 0.0062 for Akkermansia. In Figure 24 is the change in total fat (v8-v2) over the 6-month intervention plotted against the relative abundance of Akkermansia for each subject in the intervention group B420 (N=25) and the placebo group (N=36) and the median threshold.

[0275] From the confirmatory analysis (Table 4), when the differences are illustrated using linear regression lines, it can be observed from Figure 24 that at 6 months of intervention, the placebo group had an increase in total fat and exhibited a positive trend line, while the B420 group had a decrease in total fat and exhibited a negative trend line.

[0276] Method description: See Example 8.

[0277] Example 18 The SlimCap_HL post-hoc study aims to identify baseline biomarkers associated with responder status (during the intervention period) in individual subjects receiving active treatment (B420) compared to placebo treatment.

[0278] Summary of various novel prospective findings between the MetSProb and SlimCap HL studies: [ka]

[0279] Clinical Study Design The dataset for the responder analysis was from the SlimCap HL clinical trial. SlimCap HL was a randomized, triple-blind, placebo-controlled, multicenter, parallel-group study of overweight or obese individuals following a healthy lifestyle consisting of a recommended reduced-calorie diet (20% calorie restriction) and increased daily activity (1000 more steps per day). The clinical trial consisted of five visits: a screening visit (visit 1), a baseline visit (visit 2), and visits 2, 4, and 6 months after the baseline visit (visits 3, 4, and 5, respectively). Only baseline (visit 2, v2) and 6-month data were used for the responder analysis. At baseline, healthy overweight or obese individuals from France and Spain were divided into two groups: placebo and B420™. The B420™ group received 1 x 10 10 A target dose of 420 colony-forming units (CFU) of Bifidobacterium animalis ssp. lactis was supplemented orally once daily for 6 months in capsules containing microcrystalline cellulose (MCC), 1% magnesium stearate, and 1% silicon dioxide (batch numbers: 1103400800 [2.07 × 1010 CFU / capsule], 1103714113 [1.92 × 1010 CFU / capsule], and 1103840294 [1.47 × 1010 CFU / capsule]). The placebo group was supplemented with a capsule containing microcrystalline cellulose (MCC), 1% magnesium stearate, and 1% silicon dioxide (batch numbers: 1103400790, 1103714112, and 1103840293) taken orally once daily for six months. There were 209 participants in each group, for a total of 418 in the study.

[0280] The purpose of this study is to demonstrate whether B420™ can reduce total body fat mass more than placebo when followed by a healthy lifestyle intervention. This study is a confirmatory study of a previous clinical study, MetProb, in a larger population with probiotics alone and a healthy lifestyle program consisting of calorie restriction and increased daily activity.

[0281] The study population included overweight and obese participants, particularly those with abdominal obesity, who were not receiving pharmacological treatment for metabolic syndrome or related disorders and were not taking medications or supplements to manage their weight or body fat. Participants were expected to follow a healthy lifestyle for the duration of the study.

[0282] The primary endpoint of the study was the difference in relative change in total body fat mass between the active and placebo groups from baseline (visit 2) to 6 months of product intake (visit 5).

[0283] Secondary variables were the difference between the active and placebo groups, - Body fat mass in the trunk region of the body (DXA) -Waist circumference - Body fat mass in android regions of the body (DXA) -Lean body mass (DXA) -Energy intake - Fat mass in other areas of the body (arms, legs and gynoid) (DXA) -Absolute total body fat mass (DXA) -body weight -Body Mass Index (BMI) -Gluteal circumference -Relative total body fat mass (DXA) at 2 and 4 months -Percentage total body fat (added when creating SAP) The difference was.

[0284] The auxiliary variables were the difference between the active and placebo groups, -Food intake - Physical Activity (IPAQ, see Appendix 2) -Daily activity (daily steps, pedometer / accelerometer) The difference was.

[0285] Exploratory variables were the difference between the active and placebo groups, -Fasting blood sugar -Fasting insulin -insulin resistance -glycated hemoglobin (HbA1c) -Blood lipids (total cholesterol, HDL, LDL, triglycerides) -Inflammatory markers -Circulating zonulin -Markers of intestinal barrier function and endotoxemia -Fecal microbiota -Fecal metabolites -Adipose tissue biomarkers The difference was.

[0286] At Visit 2 (baseline, v2), after reviewing 3-day food diaries and pedometer / accelerometer records, participants received dietary counseling and were instructed to follow a healthy lifestyle intervention. They were instructed to restrict their calorie intake by 20% of their total energy expenditure (TEE) and to increase their daily activity (walking 1,000 more steps per day compared to baseline). The 20% calorie restriction was calculated at Visit 1 from TEE based on BMR according to the FAO and physical activity level (PAL) based on the IPAQ.

[0287] 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 same day as the visit or as close to it as possible and up to 3 days after the visit. Waist circumference was measured at the midpoint between the last palpable lower rib and the top of the iliac crest. Hip circumference was measured around the thickest part of the hip, with the tape measure parallel to the floor.

[0288] Blood samples for biomarker analysis were collected at Visits 2 and 5. Blood glucose, HbA1c, and lipid parameters were also measured at screening (Visit 1) for inclusion / exclusion criteria. In addition, circulating zonulin, a marker related to intestinal permeability, was analyzed in all participants. To explore possible mechanisms of action, other biomarkers related to intestinal barrier function and endotoxemia (LPS, sCD14), adipose tissue metabolism (adiponectin), and systemic inflammatory biomarkers (glycosylated blood proteins, GlycA / GlycB) were analyzed as exploratory parameters in all participants by NMR. Advanced analytical methods were used to analyze a wide range of blood metabolite levels that serve as markers of inflammation and adipose tissue metabolism.

[0289] Fecal samples were collected from at least 50 participants per study group. Overall, 220 fecal samples were collected: 115 in V2 and 105 in 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., SCFAs, BCFAs). Additionally, fecal zonulin, a host-associated marker of gut health, was measured as an exploratory parameter.

[0290] Analytical methods - additional methods in addition to those used in MetSProb. LC-MS lipids in serum. The method is inspired by references Satomi Y. et al. 2017, Cajka T and Fiehn O 2014, and Sanjoy K. Bhattacharya 2017.

[0291] 1.1. Chemicals and Reagents 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).

[0292] 1.2.Sample Preparation Human serum (20 μL) was aliquoted into triplicate 1.5 mL tubes, and 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.

[0293] 1.3. Liquid Chromatography / Mass Spectrometry The liquid chromatography / mass spectrometry system consisted of a Vanquish UHPLC (Thermo Fisher Scientific Inc., Sunnyvale, CA, USA) and an Orbitrap Fusion MS system (Thermo Fisher Scientific Inc., Sunnyvale, CA, USA). Liquid chromatographic separation was performed using a reversed-phase column, Acquity UPLC CSH C18 (1.7 μm, 100 × 2.1 mm and Acquity UPLC CSH C18 1.7 μm VanGuard™, Waters Co., Milford, MA, USA), at 65 °C. The mobile phase consisted of 600:400 (v / v) acetonitrile / water containing 10 mM ammonium acetate (mobile phase A) and 900:100 (v / v) isopropanol / acetonitrile containing 10 mM ammonium acetate (mobile phase B). Lipids were separated using a gradient elution method according to the following program: The flow rate was set at 0.5 mL / min, and the proportion of mobile phase B was increased to 30% B at 2.4 min, 48% B at 3.0 min, 82% B at 13.2 min, and 99% B at 13.8 min, maintained at 99% B for 0.6 min, then decreased to 15% B at 14.5 min and held constant for 3.5 min. Mass spectrometry analysis was performed separately in both positive (ESP) and negative (ESN) ionization modes. The eluent from the liquid chromatography was directly introduced into the electrospray ionization system using a heated electrospray ionization probe (H-ESI, Thermo Fisher Scientific Inc., San Jose, CA, USA) with a spray voltage of 2.5 kV for negative ionization mode or 3.5 kV for positive ionization mode and a vaporizer temperature of 350 °C. The ion transfer tube was set at 325 °C. Full mass spectra (MS) were acquired by an Orbitrap in the range of m / z 170 to m / z 1700 with a mass resolution of 120,000 FWHM (full width at half maximum) at m / z 400. Product ion spectra (MS / MS) were obtained by high-energy C-trap dissociation (HCD).

[0294] 1.4.Peak extraction from LC / MS raw data The raw data from LC / MS was processed by LipidSearch™ 5.0 Thermo Fisher Scientific. First, a product search of the raw data files was performed in LipidSearch using the following procedure: 1. Process the extracted ion chromatogram [EIC] and detect peaks [separated peak area: SPA] for each lipid ion. 2. Collect MS2 spectra contained in the EIC region. 3. Calculate the product ion chromatogram [PIC] of the product ion peak in each MS2 spectrum, and calculate the virtual spectrum [MS2 spectrum after deconvolution: DMS] distributed from the shape belonging to SPA. 4. Lipid ions with matching DMS and peak patterns are listed as candidates.

[0295] After the product search, an alignment procedure is performed by LipidSearch.

[0296] The alignment is carried out in three steps: ·Retention time correction Lipid molecular peak grouping ·verification

[0297] The peak areas of the annotated compounds were exported as CSV files along with the monoisotopic m / z values ​​and retention time information, and further data processing was performed using Excel and different statistical tools. The thresholds and relative amounts used in the figures were calculated as the peak area for a given phospholipid divided by the total peak area of ​​all lipids identified in either the negative (ESN) or positive (ESP) modes.

[0298] GC-MS analysis of metabolites in feces Derivatization and GC-MS analysis methods were based on reference 4.

[0299] Materials and Chemicals Absolute ethanol was purchased from VWR, pyridine (>99.5%) was from Fisher Scientific, and chloroform (>99.9%), ethyl chloroformate (>98%), sodium hydroxide, sodium bicarbonate, and sodium sulfate were obtained from Sigma Aldrich.

[0300] GC-MS Aqueous fecal extracts were derivatized with ethyl chloroformate (ECF) and then analyzed by GC-TOFMS. ECF reacts with carboxylic acids, amines, and phenols to produce esters, carbamates, and carbonates, respectively. Samples were derivatized and analyzed in duplicate, except for 13 samples, which were analyzed as singlets due to small sample volumes. A total of 150 μL of sample was manually placed in a 2 mL vial with 50 μL demineralized water, 200 μL ethanol, 40 μL sodium hydroxide (5 w / w%), and 40 μL pyridine. The vials were then placed in a sample tray, and derivatization was performed using a dual-rail multipurpose sampler (MPS, Gerstel). After adding an internal standard (10 μg ethoxyacetic acid) to all vials, each vial was derivatized, and one sample was extracted at a time. The reagent (2 × 20 μL) was added twice, with vigorous shaking (30 s) between each addition. The derivatives were extracted by adding 400 μL chloroform containing the internal standard (heptadecane, 155 μg / mL) and shaking vigorously for 10 seconds, followed by the addition of 400 μL sodium bicarbonate (50 mM) and vigorous stirring. The entire organic extract was transferred batchwise to a vial with an insert containing anhydrous sodium sulfate by slowly siphoning off 200 μL of the bottom organic phase and drying.

[0301] Derivatized samples were placed on a sample tray (98-position tray) and kept cooled (5 °C) until analysis by GC-TOFMS (Agilent 7890, LECO Pegasus® HT). The GC was equipped with an Rtx5-MS (Restek, 30 m × 0.25 mm × 0.25 μm). The inlet was operated in split mode (1:20) at 280 °C. The injection volume was 1 μL. Helium was used as the carrier gas at 1 mL / min. The oven temperature program started at 50 °C and increased at 10 °C / min to 320 °C (held for 10 min), resulting in a total run time of 37 min. The transfer line was at 250 °C. The ion source temperature was 250 °C, the acquisition rate was 20 Hz, and the mass range was 25–1000 m / z.

[0302] A characteristic ion for each analyte was selected and extracted as a response, which was normalized by the response of the internal standard. Specifically, the characteristic ions for pimelic acid (ethyl derivative) and azelaic acid (ethyl derivative) were 125 m / z and 83 m / z, respectively. A pooled control sample was prepared by taking an aliquot from every sample. The pooled control was derivatized and analyzed after every 15 sample injections. The response of the pooled control was used to correct for drift in instrument performance. The relative responses of pimelic acid and azelaic acid were obtained by dividing by the total peak area of ​​the specific sample.

[0303] Experimental design and parameters The basic design of the responder analysis experiment was a balanced cross-sectional control-treatment setup (condition = ITT) with longitudinal observation of subjects at two time points (v2 = baseline, v5 = 6 months post-intervention), with control equal to placebo and treatment equal to B420.

[0304] This experiment is a multi-compartment study in which different versions share the same basic design, with the clinical compartment being the inner (core) array and the other compartments being the outer (symptomatic) array.

[0305] Table 1 below provides an overview of the 12 compartments in this experiment, along with summary data on the number of subjects (N_Subj) and the number of parameters (N_Param) within each compartment. Compartment #1 is the clinical compartment, and compartments #2-12 are the different symptomatic compartments.

[0306] [Table 5]

[0307] The clinical compartment encompasses the valid ITT population of the general clinical trial, and the other compartments are different subsets of the clinical compartment population.

[0308] Responder status is based on two clinical parameters as outlined in Table 2 below (_RESP_ is the classifier for responder status).

[0309] [Table 6]

[0310] Thus, two different responder status classifiers (DXAFMASS_5%, GLUC) were used throughout the post-hoc analyses, all defined by the contrast during the intervention period (v5-v2).

[0311] The objective is to identify parameters / biomarkers that significantly distinguish between B420 and placebo for responders and that are significantly different compared to non-responders based on baseline (v2) values ​​for the entire ITT population.

[0312] Model A multivariate latent class model (LCA) was fitted to the data using the statistical software SAS 9.4 (SAS Institute Inc., Cary, NC, USA, 2016) using the clinical compartment as the inner (core) array and the other compartments (symptom manifestations) as the outer array.

[0313] This model uses two classification identifiers, treatment (B420, placebo) and responder status (non-responder, responder), in a regression setup for both the intercept and slope.

[0314] The association between the responder status classifier and potential biomarkers is summarized by a set of three informative carriers (t, t__0, t__1), which are the difference in slope (B420 vs. placebo) for the prospective setup (responder status remains unknown) and the retrospective setup for non-responders and responders, respectively.

[0315] Statistics are Z-scale information carriers and are interpreted by their sign (the direction of the effect) and size (strength, such that larger absolute values ​​are more significant).

[0316] Biomarkers significant at the 5% level by two-sided testing (ie absolute Z-score >1.96) are indicated by color coding (red = positive score for the informative carrier, blue = negative score for the informative carrier).

[0317] LCA model results Below, significant biomarkers are summarized for the responder status classifier (DXAFMASS) in Table 3 and for the responder status classifier (GLUC) in Table 4.

[0318] On the left are the biomarker characteristics; the ANOVA column is the informative column; the threshold column is the threshold of the biomarker (median) and the P33 and P66 percentiles for the B420 population.

[0319] [Table 7]

[0320] [Table 8]

[0321] For both responder status classifiers (DXAFMASS, GLUC), it was observed (in the prospective study) that higher biomarker values ​​increased the probability of being a responder, which was confirmed in the retrospective study by a significant "t__1" and a non-significant "t__0".

[0322] [Table 9]

[0323] [Table 10]

[0324] [Table 11]

[0325] Accurate structural assignment of phospholipids was based on high-resolution LC-MS-MS fragmentation.

[0326] References Amabebe et al. 2020 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. Waterson and Horvath 2015 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. Stenman et al.2016 Lotta K.Stenman,Markus J.Lehtinen,Nils Meland,Jeffrey E.Christensen,Nicolas Yeung,Markku T.Saarinen,Michael Courtney,Remy Burcelin,Marja-Leena Laehdeaho,Jueri 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. Hibberd et al.2019 Hibberd,A.A.,Yde,C.C.,Ziegler,M.L.,Honore,A.H.,Saarinen,M.T.,Lahtinen,S.,Stahl,B.,Jensen,H.M.,and Stenman,L.K.(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. Satomi Y.et al.2017 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. Cajka T and Fiehn O 2014 Cajka T,Fiehn O (2014) Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry.Trac-Trend Anal Chem 61:192-206. Sanjoy K.Bhattacharya 2017 Sanjoy K. Bhattacharya (ed.), Lipidomics: Methods and Protocols, Methods in Molecular Biology, vol. 1609, DOI 10.1007 / 978-1-4939-6996-8_14, (Copyright) Springer Science+Business Media LLC 2017 (Chapter 14). Zhao L, et al 2017 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

[0327] All publications mentioned in the above specification are herein incorporated by reference. Various modifications and variations of the described methods and systems of the invention will be apparent to those skilled in the art without departing from the scope and spirit of the invention. Although the invention has been described in connection with specific preferred embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention that are obvious to those skilled in the art of biochemistry and biotechnology or related fields are intended to be within the scope of the following claims.

[0328] Taxonomy: As used herein, the term "Aminipila butyrica" ​​refers to a bacterial species of the following taxonomy: Bacteria; Phylum Firmicutes; Class Clostridia; Order Clostridiales; Order Clostridiales; Incertae Sedis XIII; Genus Aminipila; Aminipila butyrica

[0329] As used herein, the term "Clostridiales - Incertae Sedis XIII" refers to bacterial species of the following taxonomy: Bacteria; Firmicutes; Clostridia; Clostridiales; Clostridiales; Incertae Sedis XIII; Unclassified Clostridiales Incertae Sedis XIII.

[0330] As used herein, the term "Eubacterium coprostanoligenes" refers to a bacterial species of the following taxonomy: Bacteria; Firmicutes; Clostridia; Clostridiales; Eubacteriaceae; Eubacterium; Eubacterium.

[0331] As used herein, the term "Coprococcus" refers to a genus of anaerobic cocci that includes the species Coprococcus catus, Coprococcus comests, and Coprococcus eutactus.

[0332] As used herein, the term "Ruminococcus" refers to a genus of bacteria in the class Clostridia that includes species selected from Ruminococcus albus, Ruminococcus bromii, Ruminococcus callidus, Ruminococcus flavefaciens, Ruminococcus gauvreauii, Ruminococcus gnavus, Ruminococcus lactaris, Ruminococcus obeum, and Ruminococcus torques.

Claims

1. A method for identifying subjects who exhibit an increased probability of showing a beneficial clinical response to the administration of a bacterial strain of the genus Bifidobacterium or a mixture of two or more such strains, i. The following biomarkers in biological samples obtained from the aforementioned subjects: 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); genera Coprococcus, Ruminococcus, Akkermansia, Aminipira butyrica, unclassified Clostridiales - unknown (Incertae) A bacterium selected from Sedis) XIII and Eubacterium coprostanoligenes; pimelic acid and azelaic acid; and / or a step of measuring at least one level of the subject's daily activity or corresponding physical activity by step count; and ii. A step of comparing the aforementioned level with a threshold. Includes, A method in which, when the measurement level of at least one of the biomarkers is higher than the threshold, the subject is identified as exhibiting an increase in the probability.

2. The method according to claim 1, wherein the beneficial clinical response to the bacterial strain of the genus Bifidobacterium or a mixture of two or more such strains is at least one of weight management, such as reducing the subject's BMI, reducing blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing 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 insulin secretion during feeding, decreasing insulin secretion during fasting, improving glucose tolerance, treating obesity, reducing tissue inflammation (in particular, 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 claim 1, wherein the bacterial strain of the genus Bifidobacterium or a mixture of two or more such strains is the species Bifidobacterium animalis, preferably strain B420, which is a bacterial strain of the subspecies Bifidobacterium animalis subsp. Lactis.

4. The method according to claim 1, wherein the measurement level of total hPAI1 in the biological sample obtained from the subject exceeds 48,245 pg / ml.

5. The method according to claim 1, wherein the GLCA measurement level in the biological sample obtained from the subject is greater than 0.0070 μmol / l, and / or the LCA measurement level in the biological sample obtained from the subject is greater than 0.0380 μmol / l.

6. The measurement level of the relative abundance of the genus Coprococcus in the biological sample obtained from the subject is above 0.0426, and / or the measurement level of the relative abundance of the genus Ruminococcus in the biological sample obtained from the subject is above 0.0631, and / or the measurement level of the relative abundance of the genus Akkermansia in the biological sample obtained from the subject is above 0.0062, and / or the measurement level of the relative abundance of Aminipira butyrica in the biological sample obtained from the subject is above 0.00043, and / or the measurement level of unclassified Clostridiales - Unknown (Incertae) in the biological sample obtained from the subject The method according to claim 1, wherein the measurement level of the relative abundance of Sedis) XIII is greater than 0.00018, and / or the measurement level of the relative abundance of Eubacterium coprostanoligenes in the biological sample obtained from the subject is greater than 0.0084.

7. The method according to claim 1, wherein the measurement level of Iso-LCA in the biological sample, such as feces, obtained from the subject is greater than 29 μmol / l, and / or the measurement level of DCA in the biological sample, such as serum, obtained from the subject is greater than 0.41 nmol / ml.

8. The measurement level of the phospholipid phosphatidylcholine (36:4) in the biological sample obtained from the subject, measured as a relative amount calculated by dividing the peak area of ​​the phospholipid by the total peak area of ​​all lipids identified in the positive ionization mode as described herein, is greater than 0.064, and / or the measurement level of the phospholipid phosphatidylcholine (32:1) in the biological sample obtained from the subject, measured as a relative amount calculated by dividing the peak area of ​​the phospholipid by the total peak area of ​​all lipids identified in the positive ionization mode as described herein, is greater than 0.0037, and / or the measurement level of the subject, measured as a relative amount calculated by dividing the peak area of ​​the phospholipid by the total peak area of ​​all lipids identified in the positive ionization mode as described herein, is greater than 0.0037, and / or the subject The method according to claim 1, wherein the measurement level of the phospholipid phosphatidylethanolamine (38:4) in the biological sample obtained from is greater than 0.00074, and / or the measurement level of the phospholipid phosphatidylethanolamine (36:4) in the biological sample obtained from the subject, measured as a relative amount calculated by dividing the peak area of ​​the phospholipid by the total peak area of ​​all lipids identified in the negative ionization mode as described herein, is greater than 0.00091, and / or the measurement level of the phospholipid phosphatidylinositol (40:4) in the biological sample obtained from the subject, measured as a relative amount calculated by dividing the peak area of ​​the phospholipid by the total peak area of ​​all lipids identified in the negative ionization mode as described herein, is greater than 0.00019.

9. The method according to claim 1, wherein the measured level of pimelic acid in the biological sample obtained from the subject, measured as a relative amount calculated by dividing the peak area of ​​ion 125 m / z by the total peak area of ​​all identified peaks as described herein, is greater than 0.000126, and / or the measured level of azelaic acid in the biological sample obtained from the subject, measured as a relative amount calculated by dividing the peak area of ​​ion 83 m / z by the total peak area of ​​all identified peaks as described herein, is greater than 0.000135.

10. The method according to claim 1, wherein the daily lifestyle activity of the subject, as measured by the number of steps, exceeds 7,000 steps, or is a corresponding physical activity.

11. To lower the target BMI, lower blood glucose levels, reduce body fat, control weight gain, induce weight loss, reduce body fat mass, reduce mesenteric fat mass, reduce trunk fat mass and / or reduce android fat mass, treat diabetes (preferably but not limited to type 2 diabetes), treat impaired glucose tolerance, normalize insulin sensitivity, increase insulin secretion during meals, decrease insulin secretion during fasting, improve glucose tolerance, treat obesity, and reduce tissue inflammation (especially but not limited to...). However, the use of a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof for at least one of the following purposes: reducing muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation; treating hepatitis; treating myositis; treating cardiovascular disease and treating metabolic syndrome; and managing weight, wherein the subject has been identified as exhibiting an increased probability of exhibiting a beneficial clinical response to the administration of the bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof, and it is, i. The following biomarkers in biological samples obtained from the aforementioned subjects: 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); genera Coprococcus, Ruminococcus, Akkermansia, Aminipira butyrica, unclassified Clostridiales - unknown (Incertae) A bacterium selected from Sedis) XIII and Eubacterium coprostanoligenes; pimelic acid and azelaic acid; and / or a step of measuring at least one level of the subject's daily activity by step count; and ii. A step of comparing the aforementioned level with a threshold. Identified by, The subject is identified as exhibiting an increase in the probability when the measurement level of at least one of the biomarkers is higher than the threshold.

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

13. To lower the target BMI, lower blood glucose levels, reduce body fat, control weight gain, induce weight loss, reduce body fat mass, reduce mesenteric fat mass, reduce trunk fat mass and / or reduce android fat mass, treat diabetes (preferably but not limited to type 2 diabetes), treat impaired glucose tolerance, normalize insulin sensitivity, increase insulin secretion during feeding, decrease insulin secretion during fasting, improve glucose tolerance, treat obesity, tissue inflammation (especially, limited to While not necessarily the case, a bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof for use in weight management, such as reducing muscle tissue inflammation, liver tissue inflammation and / or adipose tissue inflammation, treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome, has been identified as showing an increased probability of exhibiting a beneficial clinical response to administration of the said bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof, and this is because, i. The following biomarkers in biological samples obtained from the aforementioned subjects: 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); genera Coprococcus, Ruminococcus, Akkermansia, Aminipira butyrica, unclassified Clostridiales - unknown (Incertae) A bacterium selected from Sedis) XIII and Eubacterium coprostanoligenes; pimelic acid and azelaic acid; and / or a step of measuring at least one level of the subject's daily activity by step count; and ii. A step of comparing the aforementioned level with a threshold. Identified by, A bacterial strain of the genus Bifidobacterium or a mixture of two or more strains thereof, which is identified as exhibiting an increase in the probability when the measurement level of at least one of the biomarkers is higher than the threshold.

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

15. Lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing 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 insulin secretion during feeding, decreasing insulin secretion during fasting, improving glucose tolerance, treating obesity, tissue inflammation (in particular, but not limited to muscle tissue inflammation, hepatic tissue inflammation) A method for managing the weight of a subject who requires weight management, such as reducing tissue inflammation and / or adipose tissue inflammation, treating hepatitis, treating myositis, treating cardiovascular disease and treating metabolic syndrome, wherein the method comprises administering to the subject a bacterial strain of the genus Bifidobacterium or a mixture of two or more such strains, and the subject has been identified as exhibiting an increased probability of exhibiting a beneficial clinical response to the administration of the Bifidobacterium bacterial strain or a mixture of two or more such strains, i. The following biomarkers in biological samples obtained from the aforementioned subjects: 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); genera Coprococcus, Ruminococcus, Akkermansia, Aminipira butyrica, unclassified Clostridiales - unknown (Incertae) A bacterium selected from Sedis) XIII and Eubacterium coprostanoligenes; pimelic acid and azelaic acid; and / or a step of measuring at least one level of the subject's daily activity by step count; and ii. A step of comparing the aforementioned level with a threshold. Identified by, A method in which, when the measurement level of at least one of the biomarkers is higher than the threshold, the subject is identified as exhibiting an increase in the probability.

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

17. A method for managing the weight of a person who needs to manage their weight, including lowering BMI, lowering blood glucose levels, reducing body fat, controlling weight gain, inducing weight loss, reducing 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 insulin secretion during meals, decreasing insulin secretion during fasting, 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, wherein the method is i. Prescribing personal lifestyle activities exceeding 7,000 steps per day, or corresponding physical activities, to the subject; and ii. A method comprising administering to a subject that has achieved the activity described in i) above, wherein the subject exhibits an increased probability of exhibiting a beneficial clinical response to the administration of the Bifidobacterium bacterial strain or mixture of two or more strains thereof.

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

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