Renal Molecular Pathologist Network

Overview of the project

Prof. Loreto Gesualdo, MD FERAProject Coordinator

CHRONIC KIDNEY DISEASE

CKD affects 10% of the EU population

Silent Epidemic Disease (Social Problem) that needs early diagnosis to prevent or to reduce progression to ESKD

Replacement therapies such as dialysis or renal transplantation

High Costs on National Health System

(40,000/80,000 euro/year per patient)

PRECISION MEDICINE

To identify new biomarkers in biological fluids that precede the appearance of obvious clinical signs

To correlate the clinical phenotype with specific kidney

damage patterns

To develop silicon models capable of predicting the

evolution of the disease and identify the most appropriate

therapeutic targets

New strategies for accurate diagnosis and prognosis of kidney disease

Precision medicine is the most effective tool to get early diagnosis of common and rare kidney disease

Roadmap to precision medicine in Nephrology

A professional who can perform renal biopsy, interpret the histological patterns of renal damage and correlate them with specific biomarkers released into biological fluids

The first official course in Molecular Renal Pathology financed by the European Union

The Renal Pathologist of the Future

Renal Biopsy Histopathology Molecular Biomarkers

OBJECTIVES

To strengthen the cooperation among Universities in order toboost innovat ion and exchange of best pract ices

To train a new professional, the renalmolecular pathologist, able to evaluateclinical, histopathological and molecularsignatures of renal damage

To realize a multidisciplinary and highly specializedTraining Course in Nephrology, Telepathology andMolecu lar Medic ine Appl ied to Nephro logy

EU POLICIES

The project intercepts some of the main priorities of Europeanpolicies:

Education and Training 2020 (2009/C 119/02): ReMaP will helpimprove the quality and efficiency of the education and trainingsystem

Opening up Education [COM(2013) 654 final], the purpose of theproject is to increase the use of ICT in the education and trainingsystem

Rethinking Education [COM (2012) 669 final], the project willpromote field learning through quality placements and innovativelearning models

CONTRIBUTO DEL PROGETTO ALLE PRIORITÁ COMUNITARIE INDIVIDUATE

1. Università degli Studi di Bari (UNIBA –Italia)

2. University of Cyprus (UCY – Cipro)3. Universitaetsklinikum Aachen (UKA-

Germania)4. Academisch Medisch Centrum bij de

Universiteit van Amsterdam (AMC – Olanda)5. Instituto de Investigacion Sanitaria de la

Fundacion Jimenez Diaz (IIS-JFD – Spagna)6. Univerzita Karlova v Praze (CUNI – Rep.

Ceca)7. GRIFO Multimedia srl (GRIFO – Italia

Duration: 36 months

CONSORTIUM

• O1: Set up of the e-learning platform

• O2: Nephropathology Training Course

• O3: Telepathology Training Course

• O4: OMICS applied to Nephrology Training Course

• O5: Test and release of the Platform

ACTIVITIES

The ReMaP (LearningManagement System or LMS)e-learning platform is theonline tool that allowsstudents to access the threemodules that make up theReMaP training course. TheVirtual Classroom will provide:• Didactic Materials• Video Lessons• Community Area• Questionnaires and

Interactive Tests

SET UP OF THE E-LEARNING PLATFORM

Lead Partner: GRIFOParticipating Organizations: UNIBA, AMC, UCY, IIS-FJD, UKA

The lessons will be focused onetiopathogenesis, diagnosis andprognosis of kidney disease.

Lead Partner: UKAParticipating Organizations UNIBA,AMC, UCY, IIS-FJD

NEPHROLOGY TRAINING COURSE

19 days

INTERNSHIP

UNIBA will host 2 student of Prague UKA will host 2 students of Bari + 2 students of Aachen + 2 students of Amsterdam

CUNI will host 2 student of Nicosia + 2 student of Madrid

A number of lectures

providing theory and

practical knowledge of

Histopathology and tele-

histopathology applied to

renal diseases.

TELEPATHOLOGY TRAINING COURSE

Lead Partner: AMC (The Netherlands)

Participating Organization: UNIBA, AMC, CUNI,

FJD, GRIFO

19 days

INTERNSHIP

AMC will host 2 students of Bari + 2 students of Nicosia + 2 students of AmsterdamUNIBA will host 2 students of Madrid CUNI will host 2 students of PragueFJD will host 2 students of Aachen

The omics sciences trainingcourse will illustrate the stateof the art of this emergingdiscipline in moleculardiagnostics and will providestudents with new practicaltechnical skills

OMICS SCIENCES TRAINING COURSE

Lead Partner: UNIBAParticipating Organizations: UNIBA, UCY, UKA, IIS-JFD, GRIFO

UNIBA ospiterà 2 studenti di BariUCY ospiterà 2 studenti di Aachen + 2 studenti di Praga + 2 studenti di Nicosia

IIS-JFD ospiterà 2 studenti di Madrid + 2 studenti di Amsterdam

19 days

INTERNSHIP

Renal pathology

1. Renal Pathology discusses the role of the renalbiopsy in the care of patients with kidneydiseases.

2. Renal Biopsy provides diagnosis, guidestreatment, predicts prognosis, revealspathogenesis and validates outcome

Renal pathology

Copyright Laura Barisoni

Copyright Laura Barisoni

Copyright Laura Barisoni

The integrative -OMICS model is the frame of Systems Biology, a ground that through a bioinformatics approach aims to decode the emergent properties in phenotype

Pesce F et al. Nephrol Dial Transplant 2013

OMICS sciences for Personalized Medicine

The flow of information: from DNA to Human

What are “Omics” sciences?

ü The suffix “ome” comes from “genome” (which was formed after“chromosome”)

ü Omics implies an integration of biology with information science

ü Omics conveys a systems approach

ü Whole profile of a sub-system

ü Significant data acquisition (high-throughput)

Jiang S et al. Nat Rev Nephrol 2013

Sources of biological material in “Omics” studies of Kidney diseases

Multiscale analysis of Kidney function

He JC et al. Kidney Int 2012

GENOMICS

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isease!

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TRANSCRIPTOMICSPROTEOMICSMETABOLOMICSOMICS INTEGRATION

Genome-wide association studies (GWAS)

Single Nucleotide Polymorphism

GWAS of chronic kidney disease and kidney function

Köttgen A et al. Nat Genet. 2010 O’Seaghdha CM & Fox CS Nat Rev Nephrol. 2011

CKD

eGFR

GWAS variants for kidney disease and its risk factors

Atzler D et al. Nephrol Dial Transplant. 2014

GWAS of kidney function decline in individuals of European descent

Gorski M et al. Kidney Int. 2015

Regional association plots of the novel loci identified bygenome-wide association study (GWAS) of kidney functiondecline traits

Cdh23 and galnt11 knockdowns exacerbate nephrotoxicinjury in zebrafish embryos

GENOMICS

PROTEOMICSMETABOLOMICSOMICS INTEGRATION

!!!!!!!!!!!!!!Disease!gene)c!!

regula)on!!

Master regulators Gene networks Multi-phenotypes Disease

TRANSCRIPTOMICS

Hodgin JB and Cohen CD. Semin Nephrol 2010Bhavnani SK et al. BMC Bioinformatics. 2009

The Human Renal Transcriptome

Relationships between renal diseases (black nodes) and differentially regulated genes (white nodes) inrenal biopsies. The size of the disease nodes is proportional to the number of edges (lines) that connectthem to genes.

Tryggvason SH Kidney Int. 2013

Transcriptome profile changes during disease progression

The glomerular transcriptome was analyzed at three different time points during progression ofadriamycin-induced nephrosis in mice

GENOMICS

PROTEOMICSMETABOLOMICSOMICS INTEGRATION

TRANSCRIPTOMICS

Smith MP et al Nat Rev Nephrol 2009

Application of proteomic analysis to the study of renal diseases

Mischak H Nephrol Dial Transplant 2015

Urine proteomics as a liquid kidney biopsy: no more kidney punctures!

Urinary proteome analysis in nephrology. Proteome analysis of a urine samples (typically < 1 mL) gives information on the presence and abundance of more than 1000 peptides and proteins. They can be combined into a high-dimensional classifier (here exemplified for three biomarkers, hence three dimensions), separated into cases and controls.

Graphical depiction of the information obtained from the different approaches. Kidney biopsy can give information on microscopic structural changes in the kidney. In contrast, urine proteome analysis does not give information on morphological changes, but gives information on global protein changes in the kidney, which can be associated with the molecular changes in disease.

GENOMICS

PROTEOMICSMETABOLOMICSOMICS INTEGRATION

TRANSCRIPTOMICS

Simplified diagram showing three trade-offs (boldtype) when choosing a metabolomic technology(caps). Italics show best use of instrument. Acronymsdenote: ESI-MS (Electrospray Mass Spectrometry),NMR (Nuclear Magnetic Resonance), FT-IR (FourierTransform Infrared Spectroscopy), GC-MS and LC-MS(Gas and Liquid Chromatography coupled with MassSpectrometry).

Study design and tools in Metabolomics

Metabolomics in the study of kidney diseases

Atzler D et al. Nephrol Dial Transplant 2014

GENOMICS

PROTEOMICSMETABOLOMICSOMICS INTEGRATION

TRANSCRIPTOMICS

A Systems Biology approach

Overcoming the limitations of different approaches

Limited insights into the functional pathways and regulatory networks

underlying disease

Require collecting data from thousands of individuals (e.g., GWAS)

Reductionist “single gene” fishing expeditions

Green Ed et al. Nature 2011

“Organisms function in an integrated manner – our senses, our muscles, our metabolism and our mind work together seamlessly,

but biologists have historically studied organisms part by part and celebrated the modern ability to study them molecule by molecule, gene by gene.

“Systems Biology” is devoted to a new science, a critical science of the future that seeks to understand the integration of the pieces to form biological systems.”

David BaltimoreNobel Laureate

PresidentCalifornia Institute of Technology

Pasadena, California

Medicine will become:Predictive, Preventive, Personalized and

ParticipatoryLee Hood

Co-founder and PresidentInstitute for Systems Biology

Seattle, Washington

Hood L et al. Science 2004

“Most medical treatments have been designed for the “average patient.” As a result of this “one-size-fits-all-approach,” treatments can be very successful for some patients but not for others.

This is changing with the emergence of precision medicine, an innovative approach to disease prevention and treatment that takes into account individual differences in people’s genes, environments, and lifestyles.

Precision medicine gives clinicians tools to better understand the complex mechanisms underlying a patient’s health, disease, or condition, and to better predict which treatments will be most effective.”

The White House, Office of the Press Secretary, January 30, 2015

FACT SHEET: President Obama’s Precision Medicine Initiative

The Elements of Precision Medicine

“Precision medicine, as envisioned by UCSF, consists of seven overlapping and intersectingelements, including basic, clinical, and social/behavioral discovery, plus the enabling tools ofdigital health, 'omic technologies, and computational health sciences. These elements areintegrated by a knowledge network, creating a sort of "Google maps for health," whichinforms new research and technologies, and leads to more precise and predictive care.”

Precision medicine — describing individualsa | The six dimensions by which individualsmight be described in the precision medicineera are the ‘omic’ data (such as the genomicand metabolomic phenotypes), data fromhealth system registries (for example,electronic medical records, claims, andpharmacy registries), study-participant-generated data, the individual’s motivationsand behaviour, their microbiome, and theirexposome and social determinants. These sixfactors interact with each other, producing adynamic state.

b | The precision participant descriptorintegrates (and displays) the data from the sixdimensions and is the phenotype of theindividual. A dynamic cloud surrounds thephenotypic display to illustrate the changingnature of the phenotype as inputs (left side)vary over time.

c | The electronic health-care system of thefuture will need to curate the data and displayit in a user-friendly fashion to health-careproviders at the point of care.

Elliott M. Antman & Joseph LoscalzoNature Reviews Cardiology 13, (2016)

DIVIDING DIABETESDiabetes exemplifies the problem ofimprecise phenotypes. “There are ahundred ways to be diabetic, involvingdifferent processes in the pancreas, liver,muscle, brain and fat,” says GaryChurchill, a mouse geneticist at theJackson Laboratory in Bar Harbor, Maine.“

“Genetic studies lose statistical power bylooking at a conglomeration ofunderlying causes.”Different genes are responsible forparticular subtypes of diabetes, somixing them together obscures thereasons why people with the samegenetic mutation respond differently tothe same treatment.

Cathryn M. Delude, Nature 2015

Precision Medicine Approaches to Diabetic Kidney Disease: Tissue as an Issue

Gluck C. Curr Diab Rep. 2017

The BEAt-DKD project aims to deliver tools and knowledge that will facilitate the development of new,personalised treatments for DKD. Among other things, the project will identify and validate biologicalmarkers (biomarkers) to help researchers track whether a patient’s condition has worsened, andwhether a treatment is working for them. They will also work to identify different sub-groups ofpatients that could respond differently to certain treatments. The results will therefore pave the wayfor the development of effective personalised treatments for DKD.

Nature Medicine 22, (2016)

Copyright Laura Barisoni

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