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Record W1989732416 · doi:10.1194/jlr.e036954

microRNAs: small regulators with a big impact on lipid metabolism

2013· article· en· W1989732416 on OpenAlexaboutno aff
Kathryn J. Moore

Bibliographic record

VenueJournal of Lipid Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyHuman genomeRNAGeneticsENCODEGenomeComputational biologyNon-coding RNAGene

Abstract

fetched live from OpenAlex

Although the completion of the Human Genome Project in 2001 gave us a comprehensive readout of our DNA, our understanding of how to interpret this blueprint was far from complete. Over the last decade, our understanding of the complexity of the genome has been further advanced by the Encyclopedia of DNA Elements (ENCODE) project, a multi-center effort whose goal was to generate a comprehensive list of functional elements in the human genome by sequencing RNA from a diverse range of sources. Using comparative genomics, integrative bioinformatic methods, and human curation, the ENCODE investigators identified such elements as binding sites for proteins that influence gene activity, RNA species with numerous roles, and chemical modifications that serve to silence stretches of our chromosomes (1Dunham I. Kundaje A. Aldred S.F. Collins P.J. Davis C.A. Doyle F. Epstein C.B. Frietze S. Harrow J. Kaul R. et al.An integrated encyclopedia of DNA elements in the human genome.Nature. 2012; 489: 57-74Crossref PubMed Scopus (11021) Google Scholar). From this annotation, it is now estimated that over 90% of the human genome serves some biochemical purpose, prompting scientists to reassess stretches of DNA that were previously disregarded as “Junk DNA.” In particular, noncoding RNA has emerged as an important class of regulatory molecules that modulate gene expression, including those that mediate pre-, co-, and post-transcriptional regulatory processes. These include long noncoding RNA (lncRNA, <200 nucleotides), which facilitate chromatin remodeling; small nuclear RNA (snRNA ∼150 nucleotides), which mediate splicing; and cytoplasmic microRNA (miRNA, ∼22 nucleotides), which destabilize RNA and/or inhibit protein translation. miRNAs are currently the most widely studied and can simultaneously repress hundreds of genes to directly influence the output of interconnected biological networks (2Bartel D.P. MicroRNAs: target recognition and regulatory functions.Cell. 2009; 136: 215-233Abstract Full Text Full Text PDF PubMed Scopus (15852) Google Scholar). Numerous reports have now shown these small RNAs to be potent posttranscriptional regulators of gene networks controlling lipid homeostasis. In the last several years, miRNAs have been proven to be: i) regulators of plasma levels of lipoproteins (3Esau C. Davis S. Murray S.F. Yu X.X. Pandey S.K. Pear M. Watts L. Booten S.L. Graham M. McKay R. et al.miR-122 regulation of lipid metabolism revealed by in vivo antisense targeting.Cell Metab. 2006; 3: 87-98Abstract Full Text Full Text PDF PubMed Scopus (1769) Google Scholar, 4Rayner K.J. Suarez Y. Davalos A. Parathath S. Fitzgerald M.L. Tamehiro N. Fisher E.A. Moore K.J. Fernandez-Hernando C. MiR-33 contributes to the regulation of cholesterol homeostasis.Science. 2010; 328: 1570-1573Crossref PubMed Scopus (979) Google Scholar), ii) novel intercellular signaling molecules (5Zernecke A. Bidzhekov K. Noels H. Shagdarsuren E. Gan L. Denecke B. Hristov M. Koppel T. Jahantigh M.N. Lutgens E. et al.Delivery of microRNA-126 by apoptotic bodies induces CXCL12-dependent vascular protection.Sci. Signal. 2009; 2: ra81Crossref PubMed Scopus (1078) Google Scholar), iii) plasma biomarkers of physiological status (6Mitchell P.S. Parkin R.K. Kroh E.M. Fritz B.R. Wyman S.K. Pogosova-Agadjanyan E.L. Peterson A. Noteboom J. O’Briant K.C. Allen A. et al.Circulating microRNAs as stable blood-based markers for cancer detection.Proc. Natl. Acad. Sci. USA. 2008; 105: 10513-10518Crossref PubMed Scopus (6418) Google Scholar, 7Lawrie C.H. Gal S. Dunlop H.M. Pushkaran B. Liggins A.P. Pulford K. Banham A.H. Pezzella F. Boultwood J. Wainscoat J.S. et al.Detection of elevated levels of tumour-associated microRNAs in serum of patients with diffuse large B-cell lymphoma.Br. J. Haematol. 2008; 141: 672-675Crossref PubMed Scopus (1476) Google Scholar), iv) etiological factors in complex diseases (8Couzin J. MicroRNAs make big impression in disease after disease.Science. 2008; 319: 1782-1784Crossref PubMed Scopus (100) Google Scholar), and v) promising therapeutic targets (9Rayner K.J. Esau C.C. Hussain F.N. McDaniel A.L. Marshall S.M. van Gils J.M. Ray T.D. Sheedy F.J. Goedeke L. Liu X. et al.Inhibition of miR-33a/b in non-human primates raises plasma HDL and lowers VLDL triglycerides.Nature. 2011; 478: 404-407Crossref PubMed Scopus (594) Google Scholar, 10Jopling C.L. Yi M. Lancaster A.M. Lemon S.M. Sarnow P. Modulation of hepatitis C virus RNA abundance by a liver-specific MicroRNA.Science. 2005; 309: 1577-1581Crossref PubMed Scopus (2127) Google Scholar). These various roles are highlighted in this Thematic Review series in the current issue of the Journal of Lipid Research. The human genome encodes over 1,000 miRNAs, approximately one-third of which are organized in polycistronic clusters. While most miRNAs are located within intergenic regions of the genome, others are located within protein-coding genes. One such example is miR-33, which is cotranscribed with the SREBF family of genes and is a critical regulator of lipoprotein metabolism and fatty acid oxidation (11Rayner K.J. Fernandez-Hernando C. Moore K.J. MicroRNAs regulating lipid metabolism in atherogenesis.Thromb. Haemost. 2012; 107: 642-647Crossref PubMed Google Scholar). In a review of the roles of miRNAs in regulating HDL, Mireille Ouimet and Kathryn Moore of New York University School of Medicine discuss the functional relevance of miR-33 to lipid homeostasis, how this and other recently identified microRNAs regulate components of the reverse cholesterol transport pathway, and their potential as therapeutic targets for the treatment of atherosclerosis. While miR-33 was one of the first miRNAs shown to have a role in lipid biology, the number of genes in the complex network that controls lipid homeostasis identified to be under miRNA control is rapidly growing and includes those involved in sensing and effector pathways, lipoproteins, and extracellular enzymes. It thus follows that natural genetic variation in the compendium of elements that regulate miRNA expression (transcriptional control elements and premiRNAs) or miRNA activity (target sites) will contribute to interindividual variability in lipid phenotypes. This is the topic of a review by Praveen Sethupathy of the University of North Carolina, who describes the evidence for miRNA-related genetic variation as etiological factors in lipid disorders and the use of systems approaches to uncover miRNA-related genetic associations, thereby illuminating the “needles in the genetic haystack” that control lipid phenotypes. The exciting discovery that miRNAs can be exported into the extracellular space and be stably delivered to adjacent cells and/or distal tissues has unearthed new potential roles for miRNAs. Extracellular miRNAs are now recognized as a novel class of signaling molecules that mediate cell-to-cell communication, and distinct circulating miRNA signatures have been identified in health and disease. This is the topic of a review by Katey Rayner and colleagues of the University of Ottawa Heart Institute, who highlight the various routes of export of miRNAs into the extracellular space, their transport by membrane-derived vesicles (exosomes and microparticles) and lipoproteins, and how miRNAs in the circulation may give us hints of the underlying biology of certain disease states. As the tools to study miRNAs have been developed, our appreciation of the complexity of miRNA gene regulation has continued to expand. Recent advances in high-throughput small RNA sequencing technology have revealed an unexpected dynamic repertoire of miRNAs generated by a single genomic locus. In the final review of the series, Kasey Vickers and colleagues summarize the mechanisms through which multiple functionally distinct isoforms can arise from a miRNA coding sequence, the resulting plasticity of miRNA control, and the biological relevance of such isomiRs in regulating lipid metabolism. As scientists continue to unravel the miRNA networks that regulate hepatic and systemic lipid homeostasis, exciting discoveries in the field of lipid metabolism are likely to proceed at an unprecedented pace. This will no doubt be paralleled by the rapid identification of novel disease biomarkers and targets for therapeutic intervention. Preclinical studies of miR-33 inhibitors in mice and nonhuman primates have revealed the potential for miRNA inhibitors in the treatment of dyslipidemias and atherosclerosis, and further studies in humans are eagerly awaited. The recent FDA approval of Mipomersen, a first-in-class antisense oligonucleotide inhibitor that targets apolipoprotein B-100 to reduce LDL cholesterol for the treatment of homozygous familial hypercholesterolemia (12Gebhard C. Huard G. Kritikou E.A. Tardif J.C. Apolipoprotein B antisense inhibition - update on mipomersen.Curr. Pharm. Des. 2013; (Epub ahead of print)Crossref PubMed Scopus (17) Google Scholar), opens the door to other oligonucleotide-based therapies, bringing miRNA therapeutics one step closer to reality.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.326
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations18
Published2013
Admission routes1
Has abstractyes

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