Age-related changes in adipose tissue impact chronic medical diseases and mobility disability but mechanism remains poorly understood. The goal of this study is to define methods for phenotyping unique characteristics of adipose tissue from older adults. Older adults enrolled in Study of Muscle, Mobility and Aging selected for the adipose tissue ancillary (SOMMA-AT; N=210, 52.38% women, 76.12±4.37 years) were assessed for regional adiposity by whole-body magnetic resonance (AMRA) and underwent a needle-aspiration biopsy of abdominal subcutaneous adipose tissue (ASAT). ASAT biopsies were flash frozen, fixed, or processed for downstream applications and deposited at the biorepository. Biopsy yields, qualitative features, adipocyte sizes, and concentration of adipokines secreted in ASAT explant conditioned media were measured. Inter-measure Spearman correlations were determined. Regional, but not total, adiposity differed by sex: women had greater ASAT mass (8.20±2.73kg, p<0.001) and biopsy yield (3.44±1.81g, p<0.001) than men (ASAT=5.95±2.30kg, biopsy=2.30±1.40g). ASAT mass correlated with leptin (r=0.54, p<0.001) and not resistin (p=0.248) and adiponectin (p=0.353). Adipocyte area correlated with ASAT mass (r=0.34, p<0.001), BMI (r=0.33, p<0.001), adiponectin (r=-0.22, p=0.005) and leptin (r=0.18, p=0.024) but not with resistin (p=0.490). In addition to the detailed ASAT biopsy processing in this report, we found that adipocyte area correlated with ASAT mass, and both measures related to some key adipokines in the explant conditioned media. These results, methods, and biological repositories underscore the potential of this unique cohort to impact the understanding of aging adipose biology on disease, disability, and other aging tissues.
Abstract Disclosure: L.M. Velez: None. C. Johnson: None. I. Tamburrini: None. M. Zhou: None. C. Viesi: None. N. Ujagar: None. D. Ashbrook: None. M. Nelson: None. A. Senior: None. D. James: None. R. Williams: None. D. Nicholas: None. M. Seldin: None. Polycystic ovary syndrome (PCOS) is the most common endocrinopathy in women, with a prevalence of ∼4-20% in women of reproductive age. The diagnosis of the syndrome generally occurs when the patient consults for fertility issues and is only based on a reproductive criterion, which includes (1) hyperandrogenism, (2) oligo-anovulation, and (3) polycystic ovary morphology. However, the overlap of PCOS with cardiometabolic diseases is significant. To put in numbers; up to 75% of PCOS women present some degree of insulin insensitivity, 38-88% present obesity or overweight, 20-50% develop type 2 diabetes by age 40, and PCOS women are at increased risk of cardiovascular disease. Despite these facts, shared reproductive/metabolic mechanisms are largely underexplored. Moreover, studies addressing the genetic architecture of PCOS are missing. Here, we induced a PCOS-like condition in 25 recombinant and classical inbred female strains and matched placebo controls over 6 weeks. Comprehensive in vivo and terminal reproductive/metabolic analyses were performed, as well as ovary and adipose RNA-Seq. These strains varied in PCOS response in a number of key metabolic and reproductive traits, including circulating hormone levels, glucose metabolism, and cardiac function. We applied a linear mixed-effects model to estimate heritability, and genetic (h2), PCOS, and gene-by-PCOS interactions. High h2 was observed for lean and fat mass, glucose, and AUC, whereas PCOS effects were high for the BW change, testosterone, and AUC. Substantial gene-by-PCOS interactions were found for reproductive hormones. Undirected network construction and centrality estimates showed that the reproductive hormones LH and LH/FSH ratio were the strongest central traits connecting metabolic phenotypes. We also showed select strains represent subtypes of human PCOS-metabolism interaction with varied susceptibilities to disease in a PCOS setting. Ovarian RNA-seq analysis of PCOS DEGs showed strong enrichments with human disease settings such as hyperandrogenism, inflammation, and pregnancy hypertension. Similar analyses in GWAT RNA-seq showed enrichments in weight gain, liposarcoma, inflammation, and reproductive diseases were at the top, with adipose genes connecting these diseases and potentially involved with PCOS. In conclusion, we established a PCOS model to study relevant mechanisms intersecting reproduction with metabolism in the context of genetic variation. Presentation: 6/2/2024
Adipose tissue accumulation around non-adipose tissues is associated with obesity and metabolic disease. One relatively unstudied depot is peripancreatic adipose tissue (PAT) that accumulates in obesity and insulin resistance and may impact beta cell function. Pancreatic lipid accumulation and PAT content are negatively related to metabolic outcomes in humans, but these studies are limited by the inability to pursue mechanisms.
Lipoproteins are particles that transport fats (lipids) through the bloodstream. They differ in size and density based on the amount of lipids and proteins they carry. They are broadly broken down into several categories: Chylomicrons, which are the largest and least dense lipoproteins transport dietary triglycerides and cholesterol from the intestines to the liver and other tissues. Very-low-density lipoproteins (VLDL) are larger particles that carry triglycerides synthesized in the liver to tissues. As triglycerides are removed, VLDL particles become smaller and denser. Intermediate-density lipoproteins (IDL) are formed from the breakdown of VLDL as triglycerides are removed. Low-density lipoproteins (LDL) are smaller and denser than VLDL and IDL. They mainly transport cholesterol to tissues, earning them the label "bad cholesterol" when levels are high as they can contribute to plaque buildup in arteries. High-density lipoproteins (HDL), the smallest and densest lipoproteins, collect excess cholesterol from tissues and transport it back to the liver for disposal or recycling, earning them the title "good cholesterol." The size and density differences relate to their function in lipid transport. Larger particles like chylomicrons and VLDL primarily carry triglycerides, while smaller and denser particles like LDL and HDL primarily carry cholesterol, although the contents can shift based on conditions such as diet and/or genetics. High levels of certain lipoproteins, particularly LDL, can increase the risk of cardiovascular disease as they contribute to plaque formation in arteries, while higher levels of HDL are associated with a reduced risk due to their role in cholesterol clearance. Genetic analyses such as association mapping has been central in relating the complex nature of circulating lipoproteins to metabolic diseases. For example, genome-wide associations in large-scale patient cohorts have prioritized key enzymes and pathways linking plasma lipids to clinical phenotypes1–3. These associations have led to the prioritization of actionable treatment strategies in cardiovascular diseases, such as prioritization of Patatin-like phospholipase domain-containing protein 3 (PNPLA3) in a spectrum of liver diseases related to its role in lipid metbaolism4,5. In addition, post-hoc analyses of large-scale lipoprotein GWAS studies have guided causality inference for disease mechanisms. For example, mendelian randomization analyses following generation of these cohorts have prioritized a causal role for LDLs in driving cardiovascular disease (CVD)6. While large clinical cohort studies have reaffirmed epidemiologic correlations between various lipoprotein abundances and cardiometabolic outcomes, defining the nature of their synthesis, secretion, transport, and metabolism remain a significant challenge. Mouse models have been critical in guiding our understanding of lipid homeostasis and complex diseases, given their ease of genetic manipulation, decades of experimentation built on fixed genotypic backgrounds exposed to diverse environmental conditions, as well as accessible nature to many researchers7. The use of genetic reference panels has enabled bridging a wealth of physiologic studies in mouse models with natural genetic diversity8. In a recent study in the Journal of Lipid Research, Price and colleagues generated a new resource to explore interactions between lipoprotein size and genetic variation9. Initially, they examined lipid particle size in normal chow and western diets of both sexes of all 8 parental strains which comprise the diversity outbred population. These measurements allowed the authors to estimate the genetic contribution (or heritability) to variation in particle sizes, which was ∼60% under normal chow conditions but reduced in the cohort fed a western diet. Following the intuition that genetic background is a significant contributor to regulation of lipoprotein size, and expanded the study to assay 16-plasma lipoprotein particles in over 500 Diversity Outbred10 (DO) mice on a western diet. The large sample size enabled the authors to apply association mapping and identify 21 quantitative trait loci (QTLs), where 18 gene orthologues corresponded to conserved human lipid associations. The effects of several notable QTLs could be traced back to parental strains which contributed more allelic variations to these outcomes, such as 129 genotypes driving a hotspot on chromosome 1 and CAST on chromosome 9. To provide mechanistic validation for this new resource, the authors selected a locus association to multiple lipid species, where N-acyl sphingosine amidohydrolase 2 (Asah2), a ceramide-catabolizing neutral ceramidase11 resided. They observed that Asah2 is a master regulator of circulating lipids in that levels of HDL, midzone, large LDL, IDL, and small VLDL were significantly altered in the plasma of mice comparing knockout (KO) to litter-match controls. The effects of Asah2 mutation also showed a clear sex-specific pattern, in that the KO showed a stronger effect in females compares to males. Clearly, in vivo, manipulation of candidate genes from association mapping outcomes similar to Asah2 will be instrumental in deducing causal pathways in lipid metabolism and disease. To suggest conserved mechanisms of human cardiometabolic traits linked to lipoprotein sizes, the authors conclude by aggregating syntenic region associations in mice to human genome-wide associations to relevant outcomes such as glycemic traits and cardiovascular diseases. Beyond extending our knowledge of actionable mechanisms driving systemic lipid regulation, this new resource presents additional appeal in that the data builds on a wealth of comprehensive phenotypic and molecular characterizations performed on the same DO mice. Similar to other mouse genetic reference panels such as the C57BL6/J x DBA/2J (BXD)8,12 and Hybrid Mouse Diversity Panel (HMDP)13, tight environmental control and a wide range of measures enables researchers to integrate across data scales to dissect complex physiologic traits. Thus, genetically-driven pathways identified through associations to lipid sizes could be further characterized in an unbiased fashion by integrating observations with previous QTLs and correlations listed in Table 1. One such example would be to intersect loci which co-map to both lipoprotein size and islet functional parameters14 to inform potential conserved mechanisms of lipid and glycemic homeostasis. As more data such as RNA-sequencing, metabolite quantifications, or proteomics are layered on top of these data, a deeper understanding of genetically-varied mechanisms regulating and responding to lipoprotein size will be achievable. Future applications of additional informatics-based methods such as network modeling and/or machine learning to characterize physiologic outcomes within these integrated datasets will also enable a deeper understanding of lipid homeostasis and relationships to disease.Table 1Summary of DO screens using matched cohort to current studyStudyNumber of DO miceSummaryReference (PMID)Price et al.,500Lipoprotein size quantification37944753Price at al,.384Liver multiple phospholipids phosphatidylcholine (PC) and phosphatidylethanolamine (PE)37523383Zhang et al.,264Microbial abundances, intestinal lipids and host traits36759753Keller et al.,483Ex vivo pancreatic islet phenotypic screening paired with host metabolic traits31343992Linke et al.,385Plasma and liver mass-spec lipidomic quantification32958938 Open table in a new tab
Abstract Disclosure: Carlos Viesi, Ph.D.[1], Ian Tamburini, BS[1], Hosung Bae, Ph.D[1]., Erwin Ilegems, Ph.D.[2], Leandro Velez, Ph.D. [1], Mingqi Zhou, BS[1], Christy Nguyen, Ph.D.[1], Casey Johnson, Ph.D.[1], Cholsoon Jang, Ph.D[1]., Erika Nishimura[2] and Marcus Seldin, Ph.D.[1]. [1]Department of Biological Chemistry, Center for Epigenetics and Metabolism, University of California, Irvine, CA, USA, [2]Departments of Diabetes Protein Engineering, Diabetes Biology & Pharmacology, Medicinal Chemistry, Protein Engineering, Novo Nordisk A/S, Novo Nordisk Park, DK-2760 Måløv, Denmark. 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
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
