Aims/hypothesis: Obesity increases the risk of developing major diseases such as diabetes and cardiovascular disease. Adipose tissue, particularly adipocytes, may play a major role in the development of obesity and its comorbidities. The aim of this study was to characterise, in adipocytes from obese people, the most differentially expressed genes that might be relevant to the development of obesity. Methods: We carried out microarray gene profiling of isolated abdominal subcutaneous adipocytes from 20 non-obese (BMI 25±3 kg/m 2 ) and 19 obese (BMI 55± 8 kg/m 2 ) non-diabetic Pima Indians using Affymetrix HG-U95 GeneChip arrays. After data analyses, we measured the transcript levels of selected genes based on their biological functions and chromosomal positions using quantitative real-time PCR. Results: The most differentially expressed genes in adipocytes of obese individuals consisted of 433 upregulated and 244 downregulated genes. Of these, 410 genes could be classified into 20 functional Gene Ontology categories. The analyses indicated that the inflammation/ immune response category was over-represented, and that most inflammation-related genes were upregulated in adipocytes of obese subjects. Quantitative real-time PCR confirmed the transcriptional upregulation of representative inflammation-related genes (CCL2 and CCL3) encoding the chemokines monocyte chemoattractant protein-1 and macrophage inflammatory protein 1α. The differential expression levels of eight positional candidate genes, including inflammation-related THY1 and C1QTNF5, were also confirmed. These genes are located on chromosome 11q22-q24, a region with linkage to obesity in the Pima Indians. Conclusions/interpretation: This study provides evidence supporting the active role of mature adipocytes in obesityrelated inflammation. It also provides potential candidate genes for susceptibility to obesity.

Metabolic effects of cortisol may be critically modulated by glucocorticoid metabolism in tissues. Specifically, active cortisol is regenerated from inactive cortisone by the enzyme 11 beta-hydroxysteroid dehydrogenase type 1 (11-HSD1) in adipose and liver. We examined activity and mRNA levels of 11-HSD1 and tissue cortisol and cortisone levels in sc adipose tissue biopsies from 12 Caucasian (7 males and 5 females) and 19 Pima Indian (10 males and 9 females) nondiabetic subjects aged 28 +/- 7.6 yr (mean +/- SD; range, 18-45). Adipose 11-HSD1 activity and mRNA levels were highly correlated (r = 0.51, P = 0.003). Adipose 11-HSD1 activity was positively related to measures of total (body mass index, percentage body fat) and central (waist circumference) adiposity (P < 0.05 for all) and fasting glucose (r = 0.43, P = 0.02), insulin (r = 0.60, P = 0.0005), and insulin resistance by the homeostasis model (r = 0.70, P < 0.0001) but did not differ between sexes or ethnic groups. Intra-adipose cortisol was positively associated with fasting insulin (r = 0.37, P = 0.04) but was not significantly correlated with 11-HSD1 mRNA or activity or with other metabolic variables. In this cross-sectional study, higher adipose 11-HSD1 activity is associated with features of the metabolic syndrome. Our data support the hypothesis that increased regeneration of cortisol in adipose tissue influences metabolic sequelae of human obesity.

Aims/hypothesis: The specific contributions made by the various cell types in adipose tissue to obesity, particularly obesity-related inflammation, need to be clarified. The aim of this study was to elucidate the potential role of adipocyte precursor cells (preadipocytes/stromal vascular cells [SVC]

Aims/hypothesis. The enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) modulates tissuespecific glucocorticoid concentrations by generating active cortisol. We have shown that adipose tissue 11β-HSD1 mRNA levels were associated with adiposity and insulinaemia. Here we conducted further expression and genetic association studies in Pima Indians. Methods. The 11β-HSD1 mRNA concentrations were measured in abdominal subcutaneous adipocytes (n=61) and skeletal muscle tissues (n=64). Single nucleotide polymorphisms in the HSD11B1 gene were genotyped in a larger group of full-blooded Pima Indians. Results. Two representative SNPs (SNP1, n=706; SNP5, n=839) were associated with Type 2 diabetes mellitus (p=0.01), although neither SNP was associated with obesity. Among subjects with normal glucose tolerance, SNP1 (n=127) and SNP5 (n=159) were associated with insulin-mediated glucose uptake rates (p=0.03 and p=0.04), and SNP1 was further associated with fasting, 30-min, and 2-h plasma insulin concentrations (p=0.002, p=0.002 and p=0.03). Adipocyte 11β-HSD1 mRNA concentrations were correlated positively with adiposity and insulinaemia, and were additionally negatively correlated with insulin-mediated glucose uptake rates; nevertheless, the adipocyte 11β-HSD1 expression did not correlate with genotypes of the donors. The muscle 11β-HSD1 mRNA concentrations did not correlate with any anthropometric or metabolic variables. Conclusions/interpretation. We confirmed that adipocyte 11β-HSD1 mRNA concentrations were associated with adiposity, and showed that genetic variations in the HSD11B1 gene were associated with Type 2 diabetes mellitus, plasma insulin concentrations and insulin action, independent of obesity. The variable adipose expression might not be a primary consequence of these HSD11B1 SNPs. Therefore, it is possible that the HSD11B1 gene is under tissue-specific regulation, and has tissue-specific consequences.

The aim of this study was to determine whether amyloid precursor protein (APP) is expressed in human adipose tissue, dysregulated in obesity, and related to insulin resistance and inflammation. APP expression was examined by microarray expression profiling of subcutaneous abdominal adipocytes (SAC) and cultured preadipocytes from obese and nonobese subjects. Quantitative real-time PCR (QPCR) was performed to confirm differences in APP expression in SAC and to compare APP expression levels in adipose tissue, adipocytes, and stromal vascular cells (SVCs) from subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) specimens. Adipose tissue samples were also examined by western blot and immunofluorescence confocal microscopy. Microarray studies demonstrated that APP mRNA expression levels were higher in SAC (~2.5-fold) and preadipocytes (~1.4) from obese subjects. Real-time PCR confirmed increased APP expression in SAC in a separate group of obese compared with nonobese subjects (P = 0.02). APP expression correlated to in vivo indices of insulin resistance independently of BMI and with the expression of proinflammatory genes, such as monocyte chemoattractant protein-1 (MCP-1) (R = 0.62, P = 0.004), macrophage inflammatory protein-1α (MIP-1α) (R = 0.60, P = 0.005), and interleukin-6 (IL-6) (R = 0.71, P = 0.0005). Full-length APP protein was detected in adipocytes by western blotting and APP and its cleavage peptides, Aβ40 and Aβ42, were observed in SAT and VAT by immunofluorescence confocal microscopy. In summary, APP is highly expressed in adipose tissue, upregulated in obesity, and expression levels correlate with insulin resistance and adipocyte cytokine expression levels. These data suggest a possible role for APP and/or Aβ in the development of obesity-related insulin resistance and adipose tissue inflammation.

Expansion of adipose tissue mass results from increased number and size of adipocyte cells. We hypothesized that subcutaneous abdominal preadipocytes in obese individuals might have an intrinsically higher propensity to differentiate into adipocytes. Thus we investigated the relationship between obesity and the level of in vitro preadipocyte differentiation in Pima Indians. Subcutaneous abdominal stromal vascular fractions containing preadipocytes were cultured from 58 nondiabetic subjects [31 M/27 F, 30 Ϯ 6 yr, body fat 34 Ϯ 8% by dual-energy X-ray absorptiometry (means Ϯ SD)]. The average percentage of preadipocyte differentiation (PDIFF; cell count by microscopy) was 11 Ϯ 11% (range 0.2-51%). PDIFF correlated negatively with percent body fat (r ϭ Ϫ0.35, P ϭ 0.006) and waist circumference (r ϭ Ϫ0.45, P ϭ 0.0004). Multiple regression analysis indicated that waist circumference (P ϭ 0.01), sex (P ϭ 0.01), and percent body fat (P ϭ 0.05) were significant determinants of PDIFF. Molecular characterization of predifferentiated cultured cells was performed by real-time PCR measurements of glucocorticoid receptor-␣ (GR␣), insulin-like growth factor I receptor (IGF-IR), peroxisome proliferator-activated receptor-␥ (PPAR␥), enhancer-binding protein GATA-3, CCAAT/ enhancer-binding protein-␣ undifferentiated protein (CUP/AP-2␣), and endothelial cell-specific marker 2 (ECSM2). The mRNA concentrations of GR␣ correlated with PDIFF (r ϭ 0.29, P ϭ 0.03), but the others did not (IGF-IR, r ϭ 0.003, P ϭ 1.0; PPAR␥, r ϭ Ϫ0.1, P ϭ 0.5; GATA-3, r ϭ 0.02, P ϭ 0.9; CUP/AP-2␣, r ϭ Ϫ0.2, P ϭ 0.1; ECSM2, r ϭ 0.04, P ϭ 0.7). Contrary to our hypothesis, the results may indicate a blunted in vitro differentiation potential of preadipocytes in centrally obese individuals. The lower differentiation potential of preadipocytes in the obese subjects might be due, at least partly, to decreased glucocorticoid receptor expression.

Objectives We investigated the impact of anemia based on admission hemoglobin (Hb) level as a prognostic risk factor for severe outcomes in hospitalized patients with coronavirus disease 2019 (COVID-19). Methods A single-center, retrospective cohort study was conducted from a random sample of 733 adult patients (age ≥ 18 years) obtained from a total of 4356 laboratory confirmed SARS-CoV-2 cases who presented to the Emergency Department of Montefiore Medical Center between March–June 2020. The primary outcome was a composite endpoint of in-hospital severe outcomes of COVID-19. A secondary outcome was in-hospital all-cause mortality. Results Among the 733 patients included in our final analysis, 438 patients (59.8%) presented with anemia. 105 patients (14.3%) had mild, and 333 patients (45.5%) had moderate-severe anemia. Overall, 437 patients (59.6%) had a composite endpoint of severe outcomes. On-admission anemia was an independent risk factor for all-cause mortality, (Odds Ratio 1.52, 95% CI [1.01–2.30], p = 0.046) but not for composite severe outcomes. However, moderate-severe anemia (Hb < 11 g/dL) on admission was independently associated with both severe outcomes (OR1.53, 95% CI [1.05–2.23], p = 0.028) and mortality (OR 1.67, 95% CI [1.09–2.56], p = 0.019) during hospitalization. Conclusion Anemia on admission was independently associated with increased odds of all-cause mortality in patients hospitalized with COVID-19. Furthermore, moderate-severe anemia (Hb <11 g/dL) was an independent risk factor for severe COVID-19 outcomes. Moving forward, COVID-19 patient management and risk stratification may benefit from addressing anemia on admission.

Background: The type 2 deiodinase gene (DIO2) encodes a deiodinase that converts the thyroid prohormone, thyroxine, to the biologically active triiodothyronine. Thyroid hormones regulate energy balance and may also influence glucose metabolism. Therefore, we hypothesized that variations in DIO2 could contribute to obesity or type 2 diabetes mellitus (T2DM) in Pima Indians. Methods: Sequencing of the DIO2 gene in DNA from 83 Pima Indians identified 12 single-nucleotide polymorphisms (SNPs). Several of these SNPs were in perfect genotypic concordance among the 83 samples that were sequenced, and all 12 could be divided into five linkage disequilibrium groups. One representative SNP from each group (Thr92Ala, rs225011, rs225015, rs6574549, and a rare 5¢ flanking SNP) was selected for further genotyping for association analyses. In this study, the five selected variants in DIO2, as described above, were genotyped in three groups of Pima Indians: (i) a case (n = 150)/control (n = 150) group for early-onset T2DM (onset age < 25 years); (ii) a case (n = 362)/control (n = 127) group for obesity; (iii) a large (n = 1,311, cases n = 810/ controls n = 501) family-based group, of which 256 nondiabetic subjects had undergone detailed metabolic phenotyping. Results: The Thr92Ala variant common in Pima Indians, rs225011, and rs225015 were modestly associated with early-onset T2DM ( p = 0.01-0.04) in the case-control study, but were not associated with obesity in the obesity case-control study, nor associated with T2DM (at any age) or body-mass index (BMI; as a quantitative trait) in the family-based analysis. Thr92Ala, rs225011, rs225015, and rs6574549 were also nominally associated with hepatic glucose output ( p = 0.02). rs6574549 was associated with fasting insulin ( p = 0.02), insulin action ( p = 0.04), and energy expenditure ( p = 0.02). None of these nominal associations remained statistically significant after corrections for multiple testing. Conclusions: We propose that variation in DIO2 may have a subtle role in altering metabolic processes that lead to early-onset T2DM, but this gene does not have a large impact on T2DM at older ages, nor does DIO2 influence BMI in the Pima Indian population.