546 Diabetes Care Volume 40, April 2017 Extracellular RNAs Are Associated Ravi Shah,1 Venkatesh Murthy,2 Michael Pacold,3 Kirsty Danielson,1 With Insulin Resistance and Kahraman Tanriverdi,4 Martin G. Larson,5 Kristina Hanspers,6 Alexander Pico,6 Metabolic Phenotypes Eric Mick,4 Jared Reis,7 Sarah de Ferranti,8 Elizaveta Freinkman,3 Daniel Levy,7 9 10 Diabetes Care 2017;40:546–553 | DOI: 10.2337/dc16-1354 Udo Hoffmann, Stavroula Osganian, Saumya Das,1 and Jane E. Freedman4 OBJECTIVE Insulin resistance (IR) is a hallmark of obesity and metabolic disease. Circulating extracellular RNAs (ex-RNAs), stable RNA molecules in plasma, may play a role in 1 IR, though most studies on ex-RNAs in IR are small. We sought to characterize the Department of Medicine, Massachusetts Gen- eral Hospital, Harvard Medical School, Boston, relationship between ex-RNAs and metabolic phenotypes in a large community- MA based human cohort. 2Department of Medicine and Radiology, Univer- sity of Michigan-Ann Arbor, Ann Arbor, MI RESEARCH DESIGN AND METHODS 3Metabolomics Core, Whitehead Institute, Mas- sachusetts Institute of Technology, Boston, MA We measured circulating plasma ex-RNAs in 2,317 participants without diabetes 4 EPIDEMIOLOGY/HEALTH SERVICES RESEARCH fi University of Massachusetts at Worcester, in the Framingham Heart Study (FHS) Offspring Cohort at cycle 8 and de ned Worcester, MA associations between ex-RNAs and IR (measured by circulating insulin level). 5Biostatistics Department, Boston University We measured association between candidate ex-RNAs and markers of adiposity. School of Public Health, Boston, MA 6 Sensitivity analyses included individuals with diabetes. In a separate cohort of Gladstone Institutes, San Francisco, CA 7Division of Cardiovascular Sciences, National 90 overweight/obese youth, we measured selected ex-RNAs and metabolites. Heart, Lung, and Blood Institute, Bethesda, MD Biology of candidate microRNAs was investigated in silico. 8Preventative Cardiology, Department of Medi- cine and Cardiology, Boston Children’s Hospital, RESULTS Boston, MA 9 The mean age of FHS participants was 65.8 years (56% female), with average BMI Department of Radiology, Massachusetts Gen- 2 eral Hospital, Boston, MA 27.7 kg/m ; participants in the youth cohort had a mean age of 15.5 years (60% 10Department of Medicine, Division of General 2 female), with mean BMI 33.8 kg/m . In age-, sex-, and BMI-adjusted models across Pediatrics, Boston Children’s Hospital, Boston, 391 ex-RNAs in FHS, 18 ex-RNAs were associated with IR (of which 16 were microRNAs). MA miR-122 was associated with IR and regional adiposity in adults and IR in children Corresponding authors: Ravi Shah, rvshah@ (independent of metabolites). Pathway analysis revealed metabolic regulatory roles partners.org, and Venkatesh Murthy, vlmurthy@ med.umich.edu. for miR-122, including regulation of IR pathways (AMPK, target of rapamycin signaling, Received 23 June 2016 and accepted 7 January and mitogen-activated protein kinase). 2017. CONCLUSIONS This article contains Supplementary Data online at http://care.diabetesjournals.org/lookup/ These results provide translational evidence in support of an important role of suppl/doi:10.2337/dc16-1354/-/DC1. ex-RNAs as novel circulating factors implicated in IR. R.S., V.M., M.P., and K.D. contributed equally to this work. The content is solely the responsibility of the au- Insulin resistance (IR) is a hallmark of human obesity and associated with the risk of thors and does not necessarily represent the of- developing diabetes and cardiovascular disease. IR can exist across the spectrum of ficial views of Harvard Catalyst, Harvard BMI from lean (,25 kg/m2) to overweight/obese (.25 kg/m2). These findings in- University, and its affiliated academic health dicate that a BMI-centric definition of obesity may not capture its underlying biology care centers or the National Institutes of Health. (1). Investigation of clinical and molecular markers that define architecture of IR has © 2017 by the American Diabetes Association. intensified, focusing on adipose tissue distribution and function, metabolite pro- Readers may use this article as long as the work fi is properly cited, the use is educational and not les, gut microbial diversity, and epigenetic and genetic variation. Recently, RNA for profit, and the work is not altered. More infor- located outside of cellular structures (extracellular RNAs [ex-RNAs]), circulating RNA mation is available at http://www.diabetesjournals molecules that are stable in plasma, have emerged as potential novel mediators in .org/content/license. care.diabetesjournals.org Shah and Associates 547 IR, potentially orchestrating control over measured by ELISA (Roche e411; Roche measured using an electrochemilumines- networks of gene expression. Indeed, an- Diagnostics, Indianapolis, IN; intra-assay cence immunoassay (Roche Elecsys/ imal models suggest exquisite regulation coefficient of variation [CV] 2.0%). HOMA Cobas immunoassay analyzer; CV 1.1– of circulating ex-RNAs in the develop- of IR (HOMA-IR), a marker of IR, was cal- 4.9%). HOMA-IR was calculated as speci- ment and resolution of obesity and in culated as the product of insulin (mIU/mL) fied above. Blood for plasma specimen metabolic cross talk between various or- and glucose (mmol/L) divided by 22.5 (9). storage was collected in the fasting state gans involved in adipocyte dysfunction Insulin (pmol/L) was converted to mIU/mL in lithium heparin-containing tubes, (2), suggesting their importance as clinical by multiplying by 0.144, and glucose centrifuged immediately at 4°C, then and functional biomarkers. As such, stud- (mg/dL) was converted to mmol/L by mul- transferred into cryovials, and frozen ies in small groups of patients with obe- tiplying by 0.0555. Interleukin-6 (IL-6; at 280°C for long-term storage. sity and IR have identified candidate ELISA, R&D Systems, Minneapolis, MN; ex-RNAs associated with metabolic dys- intra-assay CV 3.7%) and soluble tumor Quantification of Plasma Extracellular function (3–6), though there is absence necrosis factor receptor II (TNFRII; ELISA; Circulating ex-RNAs of validation in large at-risk populations R&D Systems) were measured at the time Detailed methods for quantification of and against metabolic phenotypes (e.g., of FHS Offspring Exam Cycle 8. Total adi- ex-RNAs in FHS have been published by visceral and hepatic adiposity) known to ponectin from FHS Offspring Exam Cycle our group (14). In the initial study in FHS, impact cardiometabolic risk. 7 (1998–2001) was included, measured by plasma small RNA sequencing was per- In this study, we investigate plasma- ELISA(R&DSystems)asdescribed(10).For formed in 40 FHS participants to deter- circulating ex-RNA abundance in two sep- ex-RNA analysis, an aliquot of 170 mLplasma mine which ex-RNAs were abundantly arate cohorts across the life span of samples was transferred to our laboratory in and reliably expressed in human plasma human obesitydthe 8th Framingham March 2014 and stored at 280°C for analy- (14). A plasma microRNA (miRNA) was Heart Study (FHS) Offspring Cohort sis. A subset of participants underwent chosen to be included for validation in (adults) and the POOL study (obese/ abdominal computed tomographic (CT) im- the full FHS Offspring Exam Cycle 8 co- overweight youth)dto study ex-RNAs as- aging (June 2002 to April 2005) for quanti- hort if it was expressed at .10 reads sociated with IR. We further investigate fication of visceral and subcutaneous per kilobase transcript per million reads the relationship between these ex-RNAs adipose tissue volume and fat attenuation mapped by sequencing. Because of the and several clinical hallmarks of metabolic (with lower attenuation as a marker of fat novelty and limited understanding of dysfunction. We subsequently tested the quality [11]) and liver attenuation (a surro- the other (non-microRNA) ex-RNA tar- association of two top candidate ex-RNAs gate of hepatic steatosis [12]), with previ- gets, we included all expressed small discovered in FHS with IR in the POOL ously described methods (13). nucleolar RNAs (snoRNAs) and Piwi- study and defined a relationship between Written informed consent was obtained interacting RNAs (piRNAs). We subse- miR-122 and IR independent of adverse from all study participants, with Institu- quently included only those plasma metabolite profiles in youth. tional Review Board approval at Boston ex-RNAs detectable in at least 100 FHS University, Massachusetts General Hospi- participants for this analysis (as deter- RESEARCH DESIGN AND METHODS tal, and the University of Massachusetts. mined from the final analytic cohort Framingham Heart Study specified below; N =2,317).Ofthe The Framingham Heart Study (FHS) is a Study Population and Clinical 2,822 plasma samples from the FHS Off- community-based, prospective study of Assessment in POOL spring Exam Cycle 8 in FHS, 59 (2%) cardiovascular disease conducted in Fra- POOL is an ongoing, prospective research subjects were excluded because of lab- mingham, MA, with serial examinations ev- registry of overweight and obese youth oratory error (e.g., inaccurate volume ery 4–8 years and concomitant in-depth and young adults, 2–25 years old (Boston of plasma pipetted, N = 31; poor protein phenotyping of metabolic traits over mul- Children’s Hospital, Boston, MA). Subjects precipitation performance, N = 23; or tiple prior examinations. The study design were local residents who were over- potential contamination, N =5),result- has been published (7). Standard anthro- weight or obese at study entry (BMI ing in 2,763 subjects. We subsequently pometric indices were measured as reported more than or equal to age/sex-specific excluded individuals who were not fast- (8). Diabetes was defined as fasting 85th percentile on Centers for Disease ing at the time of the blood draw for at plasma glucose $126 mg/dL, hemoglobin Control and Prevention growth charts least 8 h (N = 54), individuals without A1c $6.5% (where measured), or treat- for those ,18 years of age or $25 insulin or fasting blood glucose mea- ment with either insulin or a hypoglycemic kg/m2 for those $18 years of age).