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One in eight women will develop breast cancer in their lifetime, and tamoxifen is used to suppress breast cancer recurrence, but nearly 50% of patients are not effectively treated with this drug. Given that tamoxifen is orally administered and, thus, reaches the intestine, this variable patient response to the drug is likely related to the gut microbiota composed of trillions of bacteria, which are remarkably different among individuals. This study aims to understand the impact of the gut microbiome on tamoxifen absorption, metabolism, and recycling. The significance of our research is in defining the role that gut microbes play in tamoxifen pharmacokinetics, thus paving the way for more tailored and effective therapeutic interventions in the prevention of breast cancer recurrence.

Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by ‘brute force’ surveys of all genes within RNA-sequencing measures across tissues within a population. Expanding on this intuition, we reasoned that parallel strategies could be used to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of gene variation between individuals. Thus, comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling. Here, we surveyed gene-gene correlation structure across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or high-fat/high-sucrose (HFHS) diet. Variation of genes such as FGF21, ADIPOQ, GCG, and IL6 showed enrichments which recapitulate experimental observations. Further, similar analyses were applied to explore both within-tissue signaling mechanisms (liver PCSK9 ) and genes encoding enzymes producing metabolites (adipose PNPLA2 ), where inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference of tissue-specific variation in relationships with metabolic traits. We refer to this resource as g ene-derived correlations across tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code ( gdcat.org ). This resource enables querying of any gene in any tissue to find correlated patterns of genes, cell types, pathways, and network architectures across metabolic organs.

This study evaluated the supplementation of a precision biotic (PB) on the enterohepatic health markers and growth performance of broiler chickens undergoing an enteric challenge. In the first study, three treatments were used: Unchallenged Control (UC); Challenged Control (CC; dietary challenge and 10× dose of coccidia vaccine); and a challenged group supplemented with PB (1.3 kg/ton). In the second study, three treatments were used: control diet, diet supplemented with Avilamycin (10 ppm), and a diet supplemented with PB (0.9 kg/ton). All the birds were exposed to natural challenge composed by dietary formulation and reused litter from a coccidiosis positive flock. In Trial 1, PB decreased ileal histological damage, increased villi length, and the expression of SLC5A8 in ileal tissue versus CC; it reduced ileal expression of IL-1β compared to both UC and CC treatments. PB increased the expression of cell cycling gene markers CCNA2 and CDK2 in the ileum compared to CC. In Trial 2, PB improved the growth performance, intestinal lesion scores and intestinal morphology of broiler chickens. These results indicate that birds supplemented with PB are more resilient to enteric challenges, probably by its action in modulating microbiome metabolic pathways related to nitrogen metabolism and protein utilization.

High-fructose corn syrup (HFCS) consumption is a risk factor for obesity and metabolic syndrome, yet the underlying mechanisms are incompletely understood. Catabolism of dietary fructose primarily occurs in the small intestine and liver, with fructose breakdown in the liver being pathological, while small intestinal fructose clearance protects the liver. Here, we unexpectedly found that inhibition of fructose catabolism specifically in the small intestine mitigates fructose-induced obesity and insulin resistance. Mechanistically, blocking intestinal fructose catabolism reduces dietary fat absorption, which is associated with a decrease in the surface area of the ileal lacteals and alterations in gut microbiome. Fecal transplantation experiments revealed that such a microbiome stimulates the intestine-resident macrophages, promoting lacteal growth and boosting dietary fat absorption. Given the preclinical and clinical studies reporting the effect of fructose catabolism suppression on mitigating diet-induced obesity, our data suggest that such effects are partly mediated by intestinal lacteal remodeling.

Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by ‘brute force’ surveys of all genes within RNA-sequencing measures across tissues within a population. Expanding on this intuition, we reasoned that parallel strategies could be used to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of gene variation between individuals. Thus, comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling. Here, we surveyed gene-gene correlation structure across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or high-fat/high-sucrose (HFHS) diet. Variation of genes such as FGF21, ADIPOQ, GCG, and IL6 showed enrichments which recapitulate experimental observations. Further, similar analyses were applied to explore both within-tissue signaling mechanisms (liver PCSK9 ) and genes encoding enzymes producing metabolites (adipose PNPLA2 ), where inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference of tissue-specific variation in relationships with metabolic traits. We refer to this resource as g ene-derived correlations across tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code ( gdcat.org ). This resource enables querying of any gene in any tissue to find correlated patterns of genes, cell types, pathways, and network architectures across metabolic organs.

Abstract Disclosure: C. Viesi: None. Type 2 Diabetes (T2D) affects over 530 million people around the globe. Insulin resistance, encompassing tissues such as muscle, adipose, and liver, is the initial step hallmarked by hyperinsulinemia. Coupled with β-cell failure, these coordinated responses progress to T2D, becoming irreversible and medically challenging. Despite the well-established requirement for communication between pancreas and peripheral tissues in T2D progression, this area remains almost entirely unexplored. Here, we performed a human population genetic screening across 310 individuals to search for new endocrine regulators of pancreas function. Specifically, global gene expression from 18 peripheral tissues was analyzed to identify potential endocrine regulators of insulin secretion. This analysis prioritized liver-specific Haptoglobin-related protein (HPR) as genetically-enriched with islet insulin responses. Mouse models using AAV technology and acute protein administration of HPR showed that this newly secreted protein is sufficient to prevent diet-induced insulin resistance through enhanced beta-cell respiration. When mice were administered soluble HPR, then pancreatic tissue subjected to global RNA-sequencing, enhanced respiration pathways were observed. Next, we generated hepatocyte-specific overexpression models using AAV, which were sufficient to rescue whole-body glucose disposal profiles and weight gain in diet-induced insulin-resistant mice. Altogether, these findings highlight HPR as a novel soluble protein which signals from liver to pancreatic islets. Presentation: 6/3/2024

Disclosure: L.M. Velez: None. C. Johnson: None. I. Yoon: None. K. Aberra: None. R. Feng: None. I. Tamburini: None. N. Ujagar: None. M. Nelson: None. A. Senior: None. D. Ashbrook: None. R. Williams: None. D. Nicholas: None. M. Seldin: None. Polycystic ovary syndrome (PCOS) is one of the most common female endocrinopathies, and is frequently associated with major metabolic abnormalities such as insulin resistance, cardiovascular disease, and obesity. Despite the prevalence of PCOS, the genetic architecture and subsequent interactions with metabolic and reproductive variables remain relatively unexplored. Here, our aim was to define genetic interactions which mediate susceptibility to PCOS using a panel of genetically diverse strains of female mice. Leveraging accessibility in mice and defined environmental variables, we aimed to interrogate major metabolic traits, to gain mechanistic insights into the pathophysiologic outcomes associated with PCOS. Specifically, our PCOS model involved a subcutaneous (sc) implantation of an aromatase inhibitor (Letrozole)-containing pellet (or matched controls) for 6 weeks, thus promoting increased levels of circulating androgen levels. In sum, 23 strains of female mice under normal or PCOS conditions (n = 180) were subjected to in vivo echocardiographic analysis of heart function, glucose tolerance tests (GTT), body weight and composition, estrous cycle determination, and terminal assessment of testosterone (T) levels in serum. Globally, T levels, ejection fraction (EF), fat mass (FM), and AUC from GTT were increased in PCOS vs CTRLs; however, genetics remained a strong determinant: we observed substantial variation in physiologic responses to PCOS depending on the genetic background. For example, comparing PCOS vs CTRLs, some strains showed high vs low T levels and consequent insulin resistance (i.e. strains BXD124, BXD60, 129X1/SvJ, A/J, DBA/2J), increased FM (i.e.,BXD124, 129X1/SvJ, BXD48a, C3H/Hej) or increased EF (i.e., DBA/2J, NOD, BXD79), while other genetic backgrounds showed changes in insulin resistance (AUC) (i.e.,BXD75, BXD73, AKR/J), FM (i.e.,BXD73, BXD77, BXD125) or EF (i.e.,BXD77, BXD73b) without changes in T, or high vs low T with no change in insulin resistance (i.e.,BXD125, C57BL/6J), FM (i.e., A/J, BALBc/j, DBA/2J) or EF (i.e.,129, BXD124, BXD60). As part of this ongoing project we intend to categorize degrees of metabolic and reproductive abnormalities of the PCOS models and relate to human PCOS phenotypes, and, along with integration with –omics analysis of diverse key tissues, survey the genetics of inter-tissue signaling as a result of PCOS.In summary, we present a framework to study genetic differences in the context of PCOS and here we showed that the effect of a PCOS-model on key reproductive and metabolic traits is heavily modulated by the genetic background, thus highlighting future directions for the assessment of gene by PCOS interactions. Presentation: Thursday, June 15, 2023

Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Beginning with the discovery of insulin over a century ago, characterization of molecules responsible for signal between tissues has required careful and elegant experimentation where these observations have been integral to deciphering physiology and disease. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. For example, physiologic dissection of the actions of soluble proteins such as proprotein convertase subtilisin/kexin type 9 (PCSK9) and glucagon-like peptide 1 (GLP1) have yielded among the most promising therapeutics to treat cardiovascular disease and obesity, respectively1–4. A major obstacle in the characterization of such soluble factors is that defining their tissues and pathways of action requires extensive experimental testing in cells and animal models. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by “brute-force” surveys of all genes within RNA-sequencing measures across tissues within a population5–9. Expanding on this intuition, we reasoned that parallel strategies could be used to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of gene variation between individuals. Thus, comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling. Here, we surveyed gene-gene correlation structure across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or HFHS diet. Variation of genes such as FGF21, ADIPOQ, GCG and IL6 showed enrichments which recapitulate experimental observations. Further, similar analyses were applied to explore both within-tissue signaling mechanisms (liver PCSK9) as well as genes encoding enzymes producing metabolites (adipose PNPLA2), where inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference of tissue-specific variation in relationships with metabolic traits. We refer to this resource as Gene-Derived Correlations Across Tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables querying of any gene in any tissue to find correlated patterns of genes, cell types, pathways and network architectures across metabolic organs.

Abstract Disclosure: M. Zhou: None. I. Tamburini: None. C. Van: None. J. Molendijk: None. L.M. Velez: None. C. Nguyen: None. R. Yeo: None. C. Filho: None. A.L. Hevener: None. J. Justice: None. L.M. Sparks: None. E.E. Kershaw: None. D. Nicholas: None. M. Seldin: None. Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. A major obstacle in the characterization of such soluble factors is that defining their tissues and pathways of action requires extensive experimental testing in cells and animal models. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by “brute-force” surveys of all genes within RNA-sequencing measures across tissues within a population. Expanding on this intuition, we reasoned those parallel strategies could be leveraged to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of genetic gene variation between individuals. Thus, genetics comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling by adopting a gene-centric approach. Here, we surveyed gene-gene genetic correlation structure for ∼6.1x10^12 gene pairs across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or HFHS diet. where the variation of genes such as FGF21, ADIPOQ, GCG, and IL6 showed enrichments that recapitulate experimental observations. Further, similar analyses were applied to explore both local within-tissue signaling mechanisms (liver PCSK9) as well as genes encoding enzymes producing metabolites (adipose PNPLA2), where genetic inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference in tissue-specific variation in relationships with metabolic traits. Finally, we utilized this resource to suggest new functions for metabolic coordination between organs. For example, we prioritized key proteins for putative signaling between skeletal muscle and hippocampus, and further suggest colon as a central coordinator for systemic circadian clocks. We refer to this resource as Genetically-Derived Correlations Across Tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables the querying of any gene in any tissue to find genetic coregulation correlated patterns of genes, cell types, pathways, and network architectures across metabolic organs. Presentation: 6/1/2024

Abstract Disclosure: M. Zhou: None. I. Tamburini: None. C. Van: None. J. Molendijk: None. L.M. Velez: None. C. Nguyen: None. R. Yeo: None. C. Filho: None. A.L. Hevener: None. J. Justice: None. L.M. Sparks: None. E.E. Kershaw: None. D. Nicholas: None. M. Seldin: None. Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. A major obstacle in the characterization of such soluble factors is that defining their tissues and pathways of action requires extensive experimental testing in cells and animal models. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by “brute-force” surveys of all genes within RNA-sequencing measures across tissues within a population. Expanding on this intuition, we reasoned those parallel strategies could be leveraged to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of genetic gene variation between individuals. Thus, genetics comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling by adopting a gene-centric approach. Here, we surveyed gene-gene genetic correlation structure for ∼6.1x10^12 gene pairs across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or HFHS diet. where the variation of genes such as FGF21, ADIPOQ, GCG, and IL6 showed enrichments that recapitulate experimental observations. Further, similar analyses were applied to explore both local within-tissue signaling mechanisms (liver PCSK9) as well as genes encoding enzymes producing metabolites (adipose PNPLA2), where genetic inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference in tissue-specific variation in relationships with metabolic traits. Finally, we utilized this resource to suggest new functions for metabolic coordination between organs. For example, we prioritized key proteins for putative signaling between skeletal muscle and hippocampus, and further suggest colon as a central coordinator for systemic circadian clocks. We refer to this resource as Genetically-Derived Correlations Across Tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables the querying of any gene in any tissue to find genetic coregulation correlated patterns of genes, cell types, pathways, and network architectures across metabolic organs. Presentation: 6/1/2024