BACKGROUND AND PURPOSE: There is increasing interest in extracellular RNAs (ex-RNAs), with numerous reports of associations between selected microRNAs (miRNAs) and a variety of cardiovascular disease phenotypes. Previous studies of ex-RNAs in relation to risk for cardiovascular disease have investigated small numbers of patients and assayed only candidate miRNAs. No human studies have investigated links between novel ex-RNAs and stroke. METHODS: We conducted unbiased next-generation sequencing using plasma from 40 participants of the FHS (Framingham Heart Study; Offspring Cohort Exam 8) followed by high-throughput polymerase chain reaction of 471 ex-RNAs. The reverse transcription quantitative polymerase chain reaction included 331 of the most abundant miRNAs, 43 small nucleolar RNAs, and 97 piwi-interacting RNAs in 2763 additional FHS participants and explored the relations of ex-RNAs and prevalent (n=63) and incident (n=51) stroke and coronary heart disease (prevalent=286, incident=69). RESULTS: After adjustment for multiple cardiovascular disease risk factors, 7 ex-RNAs were associated with stroke prevalence or incidence; there were no ex-RNA associated with prevalent or incident coronary heart disease. Statistically significant ex-RNA associations with stroke were specific, with no overlap between prevalent and incident events. CONCLUSIONS: This is the largest study of ex-RNAs in relation to stroke using an unbiased approach in an observational cohort and the first large study to examine human small noncoding RNAs beyond miRNAs. These results demonstrate that when studied in a large observational cohort, extracellular miRNAs are associated with stroke risk.

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 IR, though most studies on ex-RNAs in IR are small. We sought to characterize the relationship between ex-RNAs and metabolic phenotypes in a large community-based human cohort. RESEARCH DESIGN AND METHODS: We measured circulating plasma ex-RNAs in 2,317 participants without diabetes in the Framingham Heart Study (FHS) Offspring Cohort at cycle 8 and defined associations between ex-RNAs and IR (measured by circulating insulin level). We measured association between candidate ex-RNAs and markers of adiposity. Sensitivity analyses included individuals with diabetes. In a separate cohort of 90 overweight/obese youth, we measured selected ex-RNAs and metabolites. Biology of candidate microRNAs was investigated in silico. RESULTS: The mean age of FHS participants was 65.8 years (56% female), with average BMI 27.7 kg/m2; participants in the youth cohort had a mean age of 15.5 years (60% female), with mean BMI 33.8 kg/m2. In age-, sex-, and BMI-adjusted models across 391 ex-RNAs in FHS, 18 ex-RNAs were associated with IR (of which 16 were microRNAs). miR-122 was associated with IR and regional adiposity in adults and IR in children (independent of metabolites). Pathway analysis revealed metabolic regulatory roles for miR-122, including regulation of IR pathways (AMPK, target of rapamycin signaling, and mitogen-activated protein kinase). CONCLUSIONS: These results provide translational evidence in support of an important role of ex-RNAs as novel circulating factors implicated in IR.

BACKGROUND: Cardiometabolic (CM) risk factors are heritable and cluster in individuals. We hypothesized that CM risk factors are associated with multiple shared and unique mRNA and microRNA (miRNA) signatures. We examined associations of mRNA and miRNA levels with 6 CM traits: body mass index, HDL-cholesterol and triglycerides, fasting glucose, and systolic and diastolic blood pressures through cross-sectional analysis of 2812 Framingham Heart Study who had whole blood collection for RNA isolation for mRNA and miRNA expression studies and who consented to genetic research. We excluded participants taking medication for hypertension, dyslipidemia, or diabetes. We measured mRNA (n = 17,318; using the Affymetrix GeneChip Human Exon 1.0 ST Array) and miRNA (n = 315; using qRT-PCR) expression in whole blood. We used linear regression for mRNA analyses and a combination of linear and logistic regression for miRNA analyses. We conducted miRNA-mRNA coexpression and gene ontology enrichment analyses to explore relations between pleiotropic miRNAs, mRNA expression, and CM trait clustering. RESULTS: We identified hundreds of significant associations between mRNAs, miRNAs, and individual CM traits. Four mRNAs (FAM13A, CSF2RB, HIST1H2AC, WNK1) were associated with all 6 CM traits (FDR < 0.001) and four miRNAs (miR-197-3p, miR-328, miR-505-5p, miR-145-5p) were associated with four CM traits (FDR < 0.05). Twelve mRNAs, including WNK1, that were coexpressed with the four most pleiotropic miRNAs, were also miRNA targets. mRNAs coexpressed with pleiotropic miRNAs were enriched for RNA metabolism (miR-505-5p), ubiquitin-dependent protein catabolism (miR-197-3p, miR-328) and chromatin assembly (miR-328). CONCLUSIONS: We identified mRNA and miRNA signatures of individual CM traits and their clustering. Implicated transcripts may play causal roles in CM risk or be downstream consequences of CM risk factors on the transcriptome. Studies are needed to establish whether or not pleiotropic circulating transcripts illuminate causal pathways for CM risk.

MicroRNA (miRNA) expression has rapidly grown into one of the largest fields for disease characterization and development of clinical biomarkers. Consensus is lacking in regards to the optimal sample source or if different circulating sources are concordant. Here, using miRNA measurements from contemporaneously obtained whole blood- and plasma-derived RNA from 2391 individuals, we demonstrate that plasma and blood miRNA levels are divergent and may reflect different biological processes and disease associations.