MicroRNAs in kidney development and pathophysiology
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Presentation given at the 2017 Society of Toxicology meeting in Baltimore
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MicroRNAs in kidney development and pathophysiology
- 1. Introduction to microRNAs with emphasis on kidney development and pathophysiology Christos Argyropoulos MD, MSc,PhD Assistant Professor of Medicine Division of Nephrology University of New Mexico School of Medicine Department of Internal Medicine
- 2. Conflict of Interest Disclosure • Nothing to disclose
- 3. Overview • The need for better markers in renal disease • MicroRNA (miRNA) biogenesis and regulation • miRNAs in the kidney • miRNAs in renal fibrosis and the Transforming Growth Factor pathway • miRNAs as rational, translational biomarkers in renal diseases
- 4. THE NEED OF BETTER MARKERS IN RENAL DISEASE
- 5. Bad things happen to good people when their kidneys fail • 65 y/o male admitted for an elective surgical procedure • SCr on admission 1.0 mg/dl (“wnl”) • Uncomplicated surgical procedure with “minimal hypotension” (30 mins from 145/88 to 125/60) • Received a parenteral non-steroidal analgesic and proton pump inhibitor • Day 1 SCr 1.8 mg/dl, Day 3 SCr 4.5 mg/dl (anuric), Continuous Dialysis initiated for volume overload on Day 5 • Patient died in the ICU while on dialysis from sepsis on Day 27
- 6. Acute Kidney Injury (AKI): the fast facts • Complicates 5-7% of hospitalizations (300K/yr) • Incidence is increasing over time • Etiology: – Prerenal (25-60%) – Renal (35-70%): 80-90% are ischemic/toxic – Post-renal: <5% (but 20% in community AKI) • Treating AKI is expensive: – US (2005): $10B • Costs of postsurgical AKI(2014): $42600 v.s $27600 – UK (2014): £1.02 (1% of NHS budget)
- 7. AKI: the grim facts • x 5.5-6.5 acute mortality risk • x 1.36-1.59 long term mortality risk • 20-75% will need acute dialytic support • 10-50% of dialysis dependent-survivors will develop ESRD (3% of all incident cases) Nat. Rev. Nephrol. 10, 193–207, 2014 Hospital Mortality Long Term Survival
- 8. • 8-10% of the population suffer from diabetes • 20-30% of patients with diabetes will develop evidence of diabetic chronic kidney disease (DKD/CKD) • DKD progresses in stages of increasing proteinuria • 50% of patients with overt nephropathy will develop End Stage Renal Disease (ESRD) within 10 years • The end result: Diabetic nephropathy is the leading cause of ESRD, requiring dialysis or kidney transplantation accounting for 40% of cases Facts, figures and the natural history of cardiometabolic, renal disease in diabetes
- 9. • DKD is lethal (>50% of these deaths are cardiac) • DKD is costly: – 40-50% of the $44B Medicare expenditures for CKD – 40-50% of the $50B total healthcare costs for ESRD • Current therapies reduce risk by 30% • Many of the things we tried to stabilize renal function AND improve cardiovascular disease failed miserably in trials • A paradigm change in our understanding of DKD is warranted • This improvement likely spread to other areas given biology of cardiovascular disease (“extreme phenotype”) There is a significant unmet need for therapies that stabilize progression and reduce death rates in patients with diabetic kidney disease 1Afkarian et al J Am Soc Nephrol. 2013 Feb;24(2):302-8 US1 population No Diabetes Diabetes No CKD 7.7% 11.5% CKD 17.2 31.1% 0 10 20 30 40 50 60 405060708090100 Dialysis Mortality Time (months) %Surviving GN DM
- 10. The FDA perspective about the need for better renal biomarkers • “DKD is currently diagnosed by the presence of albuminuria and/or changes in serum creatinine indicating decline in estimated glomerular filtration rate ( eGFR)” • “However, risk assessment based on these and other available clinical parameters is insufficient, particularly in patients with early stages of disease. The proposed panel is intended to be used to enrich clinical trials of early stage diabetic kidney disease with patients who are more likely to progress. “ https://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/UCM508790.pdf
- 11. MIRNA BIOGENESIS AND REGULATION
- 12. miRNAs • Short (21-23nt) non-coding RNAs • First miRNA (lin-4) identified in 1993 as a regulator of larval development in C. elegans • Second miRNA (let-7) isolated in 2000 • In 2014 (latest release of miRbase) : 28645 miRNAs in animals, plants and some viruses (~1900 in humans) • Function as negative, post-transcriptional, regulators of gene expression
- 13. miRNA Generation Nat. Rev. Drug. Discov. 13, 622-638,2014
- 14. miRNA function Nat. Rev. Drug. Discov. 13, 622-638,2014
- 15. Control In Biological Systems Is Many-To-Many, Cooperative And Patterned Feala JD, et al. PLoS ONE 7(1): e29374. (2012) Riba A et al PLoS Comput Biol 10(2): e1003490. (2014) Bracken CP et al Nature Reviews Genetics 17, 719–732 (2016) Bipartite Control Network Topologies miRNA – Transcription Factor circuits Feed Forward Loop: master control layout in many natural and artificial control systems
- 16. Statistics Of Biological Regulatory Networks Feala JD, et al. PLoS ONE 7(1): e29374. (2012)
- 17. Practical implications • miRNAs function as master controllers in FFLs – biology is intrinsically NOT model free • miRNA profiling reveals the “plant” dynamics of complex biological processes – Emerging data suggest that sequence variation may underline (dys-)regulation • miRNA associations are by definition causal to some aspects of a particular phenotype – “a priori plausible” biomarkers – direct therapeutic implications • Examination of the “plant” (targets) may have implications for microRNA research – Context for the interpretation of microRNA changes – “Stronger” biomarker signatures
- 18. MIRNAS AND THE KIDNEY
- 19. Nephrons, Channels and miRNAs Kidney International (2012) 81, 617–627
- 20. Global interference with intrarenal miRNA production is associated with experimental renal disease Zhdanova et al Kidney Int. 2011 Oct;80(7):719-30
- 21. Selective Deletion of Dicer from the PT protects against ischemic AKI JASN 2010 21(5): 756-761
- 22. Select examples of miRNA involvement in renal physiology Loop of Henle Distal Nephron Int. J. Mol. Sci. 2013, 14, 13078-13092
- 23. miRNA regulation of the TGF-beta pathway in tissue fibrosis Meng et al Nature Reviews Nephrology 12, 325–338 (2016)
- 24. miRNA from human urine are measured reproducibly and exhibit regulatory activity Argyropoulos et al J. Clin. Med. 2015, 4(7), 1498-1517; doi:10.3390/jcm4071498 Gracia et al Scientific Reports 7 (2017) doi:10.1038/srep40601
- 25. Many (?Most) Renal And “Extrarenal” miRNAs are handled by the kidneys Gidlöf O et al Cardiology 2011;118:217–26. Thompson JD, et al. Nucleic Acid Ther 2012;22:255–64. Water FM van de et al Drug Metab Dispos 2006;34:1393–7. Hanss et al PNAS, pp. 1921–1926, 1998 Extremely fast kinetics and electrophysiological experiments consistent with the notion of a nucleic channel in the PT
- 26. MIRNAS AS RATIONAL, TRANSLATIONAL BIOMARKERS IN RENAL DISEASES
- 27. Why bother with miRNAs? • Ubiquity-conservation • Breadth & width of regulation (>60% of genes) • Context-specificity (“meta-controller”) • Master Controllers in Feed Forward Loops These arguments are not disease area specific (e.g. apply equal well to cancer or even psychiatric disease) • miRNAs appear relevant in renal physiology and pathophysiology • “Nice-to-have” biomarker features
- 29. Candidate miRNA biomarkers Gomez et al American Journal of Physiology - Renal Physiology 310(10, F931-F944 Fan et al. Human Genomics (2016) 10:29 DOI 10.1186/s40246-016-0085-z
- 30. Circulating miR-210 predicts survival in clinical AKI CJASN 6: 1540–1546, 2011
- 31. MiRNA signature that predicts future development of early DKD Argyropoulos et al J. Clin. Med. 2015, 4(7), 1498-1517; doi:10.3390/jcm4071498 Feature Expression Level Expression Level And Target Analysis Intercept 2.725 3.313 hsa-miR-105-3p -0.125 -0.196 hsa-miR-122-3p 0.022 hsa-miR-124-3p 0.003 hsa-miR-126-3p 0.045 hsa-miR-1972 -0.003 -0.054 hsa-miR-28-5p -0.316 -0.682 hsa-miR-30b-5p -0.008 hsa-miR-363-3p -0.141 -0.009 hsa-miR-424-5p -0.069 hsa-miR-486-5p 0.083 0.212 hsa-miR-495 -0.045 -0.028 hsa-miR-548o-3p -0.055 hsa-miR-122-5p X Women¶ 0.007 hsa-miR-192-5p X Women¶ 0.033 0.03 hsa-miR-200c-3p X Women¶ 0.07 hsa-miR-548o-3p X Women¶ -0.296 -0.498 hsa-miR-720 X Women¶ 0.059 0.018 Mis-classification Rate 11.1% 7.4% Independently validated in hypertensive patient cohorts (AUC 0.679)
- 32. MicroRNAs in renal diseases: a meta-analysis of public tissue and urine datasets Argyropoulos et al. ASN 2015 Dataset Platform Source Normal Abnormal GSE53771 Microarray (μA) Renal Bx (Bx) 28 8 (Transplant, TxP AKI) GSE30282 μA Bx 10 30 (TxP Cell Rejection). 11 (TxP AB Rejection), 14 (DGF) GSE28283 μA Bx: Cortex 3 5 (Hypertension, HTN) GSE28344 μA Bx: Medulla 3 5 (HTN) GSE48318 qPCR Urine exosomes 2 2 (Microalbuminuria, MA) doi: 10.1371/journa l.pone.0054662 qPCR Whole urine 10 17 (MA within 2 years) The median (IQR) AUC for individual miRNAs was 0.64(0.54-0.69). miRNAs targeting KRG (“Kidney Related Genes”) performed better than unselected miRNAs In cross validated, elastic net regression, we identified a short signature of 19 miRNAs with an AUC of 0.96
- 33. Goals of a miRNA translational research program in renal disease • Use carefully designed case-control, before- after, randomized controlled trials, and n-of- 1 trials for the following goals: 1. Personalized medicine applications (diagnosis/prognosis/precision medicine) 2. Biomarker discovery (e.g. to aid trials) 3. Novel Therapeutics Caveat: many miRNAs may be non-specifically associated with renal function or damage (expensive creatinine/albuminuria)
- 34. Animal Models Clinical Associations Clinical Interventions A microRNA driven discovery process Biomarker Discovery Mechanistic Insights Therapeutics Clinical Science, Bioinformatics, Systems Biology Driven “Reverse Translation” Translational Science Evidence Based Medicine Basic Science
- 35. Summary • miRNAs are important regulators of many biological processes • They are particularly relevant for renal diseases (acute and chronic) • miRNA based: – diagnostics are promising markers of clinical outcomes in acute and chronic kidney diseases – (mi)RNA based/inspired therapies may meet the significant unmet needs in nephrology • Informatics challenges have to be addressed to facilitate the “reverse-translation” /“translation” discovery cycles for novel diagnostics and therapeutics
- 36. ?
- 37. BACKUP
- 38. Principles of miRNA – mRNA interaction Nature Reviews Genetics 9, 102-114,2008
- 39. How do we control things? Predictably simple (open loop) Error Correcting (feeback) Model based (feed forward)
- 40. Feed forward control • Control element responds to a change in the environment in a predefined manner • Based on prediction of plant (“what is being controlled”) behavior (requires model) • Can react before error actually occurs (stabilizing the system) • Benefits: reduced hysteresis, increased accuracy, cost- efficiency, lower “wear-tear”
- 41. miR-21 is a two sided sword Anti-apoptotic in early AKI (PDCD-4/BCL-2) Protective role in the context of ischemic precondition (PDCD-4) Pro-inflammatory in late AKI (MyD88/IRAK1) Pro-fibrotic if excessively upregulated Protein Cell 2013, 4(11): 813–819 Kidney Int. 2012 Dec;82(11):1149-51
- 42. Of mice and men Bartram et al BMC Nephrology 2015 16:55 Kohl et al Nephrol Dial Transplant. 2016 Aug;31(8):1280-3 “Our results indicate that mutations affecting mature microRNAs in individuals with CAKUT are rare and thus most likely not a common cause of CAKUT in humans” NGS of 96 stem-loop regions of 73 renal developmental miRNA genes in 1248 individuals with non- syndromic CAKUT from 980 families
- 44. Monitoring the process by observing the controller MA v.s. NA Overt vs Normal Pathway P-value Fraction P-value Fraction Signal Transduction Signaling by SCF-KIT 0.006 18/76 0.001 41/76 Signaling by Insulin receptor 0.009 23/109 <0.001 65/109 Signaling by NGF 0.016 38/212 <0.001 119/212 Signaling by Rho GTPases 0.024 24/125 <0.001 71/125 Signaling by ERBB4 0.027 16/76 <0.001 45/76 Signaling by ERBB2 0.035 19/97 <0.001 59/97 Signaling by PDGF 0.040 22/118 <0.001 67/118 Signaling by VEGF 0.041 4/11 Signaling by EGFR 0.044 20/106 <0.001 64/106 Dowstream signaling of activated FGFR 0.038 19/98 <0.001 61/98 Signaling by BMP 0.001 16/23 Signaling by TGFβ 0.004 11/15 DAG and IP3 signaling 0.010 20/31 PIP3 activates AKT signaling 0.020 15/26 RAF/MAP kinase cascade 0.031 7/10 Signaling by Notch 0.036 13/23 Interaction of integrin α5β3 with fibrillin 0.044 2/3 Interaction of integrin α5β3 with von Willbrand factor 0.044 2/3 Integrin cell surface interactions 0.024 40/85 Cell-Cell Communication 0.009 57/122 Cell Cycle G0 and early G1 0.040 12/21 Argyropoulos et al PLoS One. 2013;8(1):e54662
- 45. microRNA biology & therapeutic applications http://www.nature.com/nature/journal/v469/n7330/fig_tab/nature09783_F1.html http://www.nature.com/nature/journal/v469/n7330/full/nature09783.html
- 46. microRNAs as Minimally Invasive Biomarkers : a metrological argument Advantages of microRNAs Circulating microRNAs •More stable in circulation than mRNAs •High expression level and low complexity compared to mRNA •Tissue specific expression •Availability of analytical platforms Keep getting cheaper over time •Sequence conservation Allows translation of clinical associations to animal models Allows translation of animal models to clinical applications Cortez et al Nat Rev Clin Oncol. Jun 7, 2011; 8(8): 467–477.
- 47. Why bother with miRNAs in AKI? Cardiovascular System • Angiogenesis • Vascular inflammation • Atherosclerosis • LVH • Vascular tone • Endothelial dysfunction • Hypoxia • Endothelin • Prostaglandins Kidney • Tubuloglomerular feedback • Loss of renal filtration • Cellular metabolism • Cell death/apoptosis • Water homestasis • Osmoregulation • Calcium sensing • Sodium, potassium, acid base handling • Renin-Angiotensin production • Renal development • Renal senescence • EMT • Collagen production Inflamma tion • Leukocyte adhesion • Neutrophil infiltration • CD4+/Tregs • Macrophages • Dendritic cells • Cytokine networks • Native immunity (TLR) • Complement system • Reactive O2 production
- 48. Why bother with microRNAs in DKD? Cardiovascular system • Angiogenesis • Vascular inflammation • Atherosclerosis • LVH • Vascular tone • Endothelial dysfunction Kidney • Water homestasis • Osmoregulation • Calcium sensing • Sodium, potassium, acid base handling • Renin production • Renal development • Renal senescence • EMT • Collagen production Diabetes • Insulin synthesis and secretion • Peripheral tissue sensitivity • Hepatic glucose production • Inflammatory gene expression
Editor's Notes
- Class GFR UO Risk ↑ SCr × 1.5 or ↓ GFR >25% <0.5 mL/kg/h × 6 h Injury ↑ SCr × 2 or ↓ GFR >50% <0.5 mL/kg/h × 12 h Failure ↑ SCr × 3 or ↓ GFR >75% or <0.3 mL/kg/h × 24 h or anuria × 12 h if baseline SCr ≥353.6 μmol/L(≥4 mg/dL) ↑ SCr >44.2 μmol/L(>0.5 mg/dL) Loss of kidney function Complete loss of kidney function >4 weeks End-stage kidney disease Complete loss of kidney function >3 months
- Comment that among those with ESRD one may find an approximate equal proportion of patients with T1D and T2D, even though T2D is more frequent that T1D. The reason for this discrepancy is that overt nephropathy develops less frequently in patients T2D, many of whom will die from macrovascular complications before their kidney disease progresses Ref for this slide: Diabetes Care January 2004 vol. 27 no. suppl 1 s79-s83 http://care.diabetesjournals.org/content/27/suppl_1/s79.full
- To put things in context: five year survival stage for - All cancers: 68% Breast cancer: 72% (stage III), 22% (stage IV) Colon Cancer: 53% (IIIC), 11% (IV) Prostate Cancer: 28% (distant)
- Canonical and non-canonical miRNA biogenesis pathways. In the canonical pathway, microRNAs (miRNAs) are typically transcribed by RNA polymerase II to produce primary miRNA (pri-miRNA) hairpins, which are then processed by the Drosha–DGCR8 (DiGeorge syndrome critical region 8) complex to generate precursor miRNAs (pre-miRNAs). These molecules are transported by exportin 5 into the cytoplasm, where they are further processed by Dicer–TRBP (TAR RNA-binding protein 2) and loaded into Argonaute 2 (AGO2)‑containing RNA-induced silencing complexes (RISCs) to suppress downstream target gene expression. miRNAs are also produced though non-canonical pathways, such as spliceosome-dependent mechanisms, as shown here. The miRNA biogenesis pathway is a tightly regulated process. For example, Drosha is dependent on phosphorylation by glycogen synthase kinase 3β (GSK3β) for proper nuclear localization168; Drosha regulates DGCR8 expression by suppressing DGCR8 mRNA20; DGCR8 stabilizes Drosha protein20; AGO2 is hydroxylated by C-P4H169 and phosphorylated by MAPK-activated protein kinase 2 (MAPKAPK2)170, which stabilizes the protein and regulates its localization to processing bodies (P‑bodies); and TRBP is stabilized by extracellular signal-regulated kinase 1 (ERK1) or ERK2 phosphorylation25. miRNAs themselves are regulated by a number of modifications, including uridylation (Ud)171.
- Figure 2 | miRNA function: three potential mechanisms of miRNA-mediated post-transcriptional gene silencing. a | Repression of translation initiation. MicroRNA (miRNA)-mediated silencing complexes (miRISCs) inhibit the initiation of translation by affecting eukaryotic translation initiation factor 4F (eIF4F) cap recognition, 40S small ribosomal subunit recruitment and/or by inhibiting the incorporation of the 60S subunit and the formation of the 80S ribosomal complex. Some of the target mRNAs bound by the miRISC are transported into processing bodies (P‑bodies) for storage and may re‑enter the translation phase when induced by exogenous signals such as stress. b | Post-initiation translational repression. miRISCs may inhibit the elongation of ribosomes, causing them to drop off the mRNAs and/or facilitate the degradation of newly synthesized peptides. c | Destabilization of target mRNAs. Binding of miRISCs to target mRNAs may recruit RNA decapping and/or deadenylating enzymes that lead to mRNA destabilization. P‑bodies are the key cellular organelles for the degradation and storage of targeted mRNAs. AGO2, Argonaute 2; DCP1, mRNA-decapping enzyme 1; PABP, poly(A)-binding protein.
- FFL = Feed Forward Loop (=cerebellar circuits) Common Statistical Properties in many gene regulatory pathways
- Nephron with relevant channels and microRNAs (miRNAs). Structure of nephron and the number of miRNAs predicted to be involved in kidney function and homeostasis are shown. The numerical values in brackets represent the total numbers of miRNAs predicted in each nephron segment by bioinformatic analysis on five databases (miRwalk, miRanda, miRDB, RNA22, TargetScan/TargetScanS). ACE, angiotensin; AGT, angiotensinogen; ANG, angiotensin-converting enzyme; AQP, aquaporin; REN, renin genes.
- “Understanding biology by reverse engineering the control”
- 500 ul of urine processed with miRNeasy and profiled with the Exiqon
- MicroRNAs (miRNAs) interact with their mRNA targets by base pairing. In plants, most miRNAs base pair to mRNAs with nearly perfect complementarity and induce mRNA degradation by an RNAi-like mechanism — the mRNA is cleaved endonucleolytically in the middle of the miRNA–mRNA duplex. By contrast, with few exceptions, metazoan miRNAs base pair with their targets imperfectly, following a set of rules that have been identified by experimental and bioinformatics analyses. One rule for miRNA–target base paring is perfect and contiguous base pairing of miRNA nucleotides 2 to 8, representing the 'seed' region (shown in dark red and green), which nucleates the miRNA–mRNA association. GU pairs or mismatches and bulges in the seed region greatly affect repression. However, an A residue across position 1 of the miRNA, and an A or U across position 9 (shown in yellow), improve the site efficiency, although they do not need to base pair with miRNA nucleotides. Another rule is that bulges or mismatches must be present in the central region of the miRNA–mRNA duplex, precluding the Argonaute (AGO)-mediated endonucleolytic cleavage of mRNA. The third rule is that there must be reasonable complementarity to the miRNA 3' half to stabilize the interaction. Mismatches and bulges are generally tolerated in this region, although good base pairing, particularly to residues 13–16 of the miRNA (shown in orange), becomes important when matching in the seed region is suboptimal. Other factors that can improve site efficacy include an AU-rich neighbourhood and, for long 3' UTRs, a position that is not too far away from the poly(A) tail or the termination codon; these factors can make the 3' UTR regions less structured and hence more accessible to miRNP recognition. Indeed, accessibility of binding sites might have an important effect on miRNA-mediated repression. Some experimentally characterized sites deviate significantly from these rules and can, for example, even require a bulged nucleotide in the seed region pairing. In addition, combinations of sites can require a specific configuration (for example, separation by a stretch of nucleotides of specific sequence and length) for efficient repression. Usually, miRNA-binding sites in metazoan mRNAs lie in the 3' UTR and are present in multiple copies. Importantly, multiple sites for the same or different miRNAs are generally required for effective repression. When they are present close to each other (10–40 nucleotides apart) they tend to act cooperatively, that is, their effect exceeds that expected from the independent contributions of two single sites.
- On one hand, in the initial stage of AKI, miR-21 up-regulation switches on a defense mechanism against the stimulation of apoptosis recognized by TLRs, which down-regulates PDCD4 by directly targeting the 3′UTR, as well as up-regulates survival factor Bcl-2, which acts as a strong anti-apoptotic factor to inhibit cell death. Meanwhile, inhibition of PDCD4 leads to a decrease in NF-κB induced apoptosis. However, on the other hand, in the end stage of AKI, over-expression of miR-21 targeting MyD88 and IRAK1 results in the continuous activation of certain TLRs to amplify cascades of phosphorylation and ubiquitination events to trigger NF-κB to produce proinfl ammatory cytokines. Moreover, excessive up-regulation of miR-21 positively correlates with TIMP1, ColIV, and FN, while negatively correlating with MMP-9, which exacerbates tissue fi brosis by intensifying cell death and tissue injury. Make the comment that severity of the injury-> more miR-21->anti-apoptotic early, but if unchecked leads to inflammation and fibrosis. Could also explain some epidemiological observations regarding the shallow dose response relationship between severity of AKI and renal outcomes. In AKI on CKD, where miR-21 is already activated and in control of the TGF-beta pathway of fibrosis, the extra “dose” of miR-21 may be responsible for the worsening renal function relative to patients w/o CKD. miR-21 has also been shown to underline the protective effect of ischemic preconditioning on the subsequent development of AKI
- Analysis of enriched terms in REACTOME (Table) suggest that the predicted miRNA targets map to a distinct pathways involving growth factor signaling, apoptosis, immunity, substrate metabolism, transmembrane transport and certain non-kidney related terms. Furthermore, the identified pathways overlapped considerably between the comparisons of patients with overt nephropathy and normals , and follow-up v.s. baseline samples from MA patients. In the comparisons within baseline and follow-up MA samples we found only a few (<80) targets mapping to annotated REACTOME pathways, thus precluding a meaningful assessment with this structured vocabulary.
- These are the major factors that initate and cause the pathologic processes that lead to AKI. It is also their interplay that likely underlines the “remote effects” of AKI i.e. the increased mortality, even years after the initiating events. Based on these observations a developing view is that kidney injury sets in motion a complex systemic inflammatory response that is the basis for organ cross talk and it is likely that liberated pro-inflammatory cytokines