Firma epigenetica della T21 - Dipartimento di Medicina...

Firma epigenetica della T21

Maria Giulia BacaliniIRCCS Istituto delle Scienze Neurologiche di Bologna

Sindrome di Down: dalla diagnosi alla terapia - III Convegno

Napoli, 18-19 ottobre 2019

Epigenetics

Epigenetics is the study of mechanisms that control gene expression in a potentially

heritable way (mitosis and in some cases meiosis).Anna Portela & Manel Esteller, 2010

DNA methylation was the first epigenetic modification discovered

Epigenetics

Genome regulation:

• Genomic stability

• Gene expression

Epigenetics is the study of mechanisms that control gene expression in a potentially

heritable way (mitosis and in some cases meiosis).Anna Portela & Manel Esteller, 2010

DNA methylation was the first epigenetic modification discovered

Epigenetics

DNA methylation is established during development…

… but it is also:

• affected by the genetic background

• lifelong remodelled byseveral environmental cues

DNA methylation in Down Syndrome

Altered DNA Methylation in Leukocytes with Trisomy 21

Krist i Kerkel1, Nicole Schupf2,3, Kota Hatta4, Deborah Pang2, Martha Salas1, Alexander Kratz5, Mark

Minden6, Vundaval li Murty1,5, Warren B. Zigman3, Richard P. Mayeux2,7, Edmund C. Jenkins3, Ali

Torkamani8, Nicholas J. Schork 8, Wayne Silverman9,10, B. Anne Croy4, Benjamin Tycko1,2,5*

1 Institute for Cancer Genetics, Columbia University Medical Center, New York, New York, United States of America, 2 Taub Institute for Research on Alzheimer’s disease

and the Aging Brain, Columbia University Medical Center, New York, New York, United States of America, 3 Departments of Human Genetics, Epidemiology, and

Psychiatry, Institute for Basic Research on Developmental Disabilities, New York, New York, United States of America, 4 Departments of Anatomy and Cell Biology and

Microbiology and Immunology, Queen’s University, Kingston, Canada, 5 Department of Pathology, Columbia University Medical Center, New York, New York, United

States of America, 6 Department of Medical Oncology and Hematology and Department of Medical Biophysics, University of Toronto and Princess Margaret Hospital,

Toronto, Canada, 7 Department of Neurology, Columbia University Medical Center, New York, New York, United States of America, 8 Scripps Translational Science

Institute, La Jolla, California, United States of America, 9 Department of Behavioral Psychology, Kennedy Krieger Institute, Baltimore, Maryland, United States of America,

10 Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America

Abst ract

The primary abnormality in Down syndrome (DS), trisomy 21, is well known; but how this chromosomal gain produces thecomplex DS phenotype, including immune system defects, is not well understood. We profiled DNA methylation in totalperipheral blood leukocytes (PBL) and T-lymphocytes from adults with DS and normal controls and found gene-specificabnormalities of CpG methylation in DS, with many of the differentially methylated genes having known or predicted rolesin lymphocyte development and function. Validation of the microarray data by bisulfite sequencing and methylation-sensitive Pyrosequencing (MS-Pyroseq) confirmed strong differences in methylation (p, 0.0001) for each of 8 genes tested:TMEM131, TCF7, CD3Z/CD247, SH3BP2, EIF4E, PLD6, SUMO3, and CPT1B, in DS versus control PBL. In addition, we validateddifferential methylation of NOD2/CARD15 by bisulfite sequencing in DSversus control T-cells. The differentially methylatedgenes were found on various autosomes, with no enrichment on chromosome 21. Differences in methylation weregenerally stable in a given individual, remained significant after adjusting for age, and were not due to altered cell counts.Some but not all of the differentially methylated genes showed different mean mRNA expression in DSversus control PBL;and the altered expression of 5 of these genes, TMEM131, TCF7, CD3Z, NOD2, and NPDC1, was recapitulated by exposingnormal lymphocytes to the demethylating drug 5-aza-29deoxycytidine (5aza-dC) plus mitogens. We conclude that alteredgene-specific DNA methylation is a recurrent and functionally relevant downstream response to trisomy 21 in human cells.

Citat ion: Kerkel K, Schupf N, Hatta K, Pang D, Salas M, et al. (2010) Altered DNA Methylation in Leukocytes with Trisomy 21. PLoS Genet 6(11): e1001212.doi:10.1371/journal.pgen.1001212

Editor: Dirk Schubeler, Friedrich Miescher Institute for Biomedical Research, Switzerland

Received September 24, 2009; Accepted October 19, 2010; Published November 18, 2010

Copyright: ß 2010 Kerkel et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was supported by NIH grant P01HD035897 to BT, ECJ, NS, WBZ, and WS; by NIH grant PO1AG07232 to RPM and NS; by NIH grant AG014763to NS; and by NIH grant U54 RR0252204-01, which provides partial funding to AT and NJS. The funders had no role in study design, data collection and analysis,decision to publish, or preparation of the manuscript.

Compet ing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

Int roduct ion

It isnow 5 decadessince Down syndrome(DS) wasfirst shown to

result from trisomy 21 [1,2], and some progress has been made

toward understanding thegenesthat contributeto thecomplex array

of DS phenotypes– mostly by studying the effectsof the trisomy on

transcriptional profiles in humans and mice and by creating

transgenic and trans-chromosomal mouse models [3,4]. We are still

far from understanding the mechanisms that underlie the complex

spectrum of phenotypesin DS. Survival in DScan range from death

inuteroto lateadulthood; cardiac defectsarepresent in about 40% of

cases, while cognitive disability is invariably present but can range

from mild tosevere. Additionally, therearemultipleblood cell-related

phenotypesincluding leukemoid reactionsand childhood leukemias,

macrocytosiswith or without anemia, amarkedly increased incidence

of autoimmune disorders, and increased susceptibility to recurrent

bacterial and viral infections [5–10].

All of these abnormalities must ultimately reflect the down-

stream responsesof human cellsand tissues to the chromosome 21

aneuploidy. In theory, one mechanism by which cells might

respond to changes in gene dosage is altered DNA methylation.Gain of methylation at cytosines in CpG dinucleotides in

promoter-associated CpG islands (CGI’s) can enforce dosagecompensation in X-inactivation, and methylation in other typesof

CG-rich sequences including intragenic sequences and insulatorelements can affect expression and hence functional gene dosage

at imprinted loci. With these simple ideasin mind weset out to askwhether gains or losses of genomic DNA methylation might occur

as a downstream consequence of trisomy 21 in blood cells fromadults with DS. Studies profiling mRNA expression in cells and

tissues with trisomy 21 have shown that while many genes onchromosome 21 are over-expressed, subsets of genes on otherchromosomes also show consistently altered expression in this

background due to gene-gene interactions (for example [11–15]).So in testing for epigenetic changesdownstream of trisomy 21 it is

important to examine the whole genome. Here we show that asmall group of genes, distributed across various chromosomes and

not over-represented on chromosome 21, are consistently altered

PLoS Genetics | www.plosgenetics.org 1 November 2010 | Volume 6 | Issue 11 | e1001212

Full Terms & Conditions of access and use can be found at

https://www.tandfonline.com/action/journalInformation?journalCode=kepi20

Epigenet ics

ISSN: 1559-2294 (Pr int ) 1559-2308 (Online) Journal homepage: ht tps:/ /www.tandfonline.com/ loi/kepi20

Epigenet ic dysregulat ion in the developing Downsyndrome cortex

Nady El Hajj, Marcus Dit t r ich, Julia Böck, Theo F. J. Kraus, Indrajit Nanda,Tobias Mü ller , Lar issa Seidmann, Tim Tralau, Danuta Galetzka, EberhardSchneider & Thomas Haaf

To cite this art icle: Nady El Hajj, Marcus Dittrich, Julia Böck, Theo F. J. Kraus, Indrajit Nanda,

Tobias Müller, Larissa Seidmann, Tim Tralau, Danuta Galetzka, Eberhard Schneider & Thomas

Haaf (2016) Epigenetic dysregulation in the developing Down syndrome cortex, Epigenetics, 11:8,

563-578, DOI: 10.1080/15592294.2016.1192736

To link to this ar t icle: https:/ /doi.org/10.1080/15592294.2016.1192736

© 2016 The Author(s). Published withlicense by Taylor & Francis Group, LLC©Nady El Hajj, Marcus Dittrich, Julia Böck,Theo F. J. Kraus, Indrajit Nanda, TobiasMüller, Larissa Seidmann, Tim Tralau,Danuta Galetzka, Eberhard Schneider, andThomas Haaf

View supplementary material

Accepted author version posted online: 31May 2016.Published online: 01 Jul 2016.

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Our model

Whole blood from

29 DS persons (DSP)

29 unaffected siblings of DSP

29 mothers of DSP

DSP

DSS DSMAge

The Infinium HumanMethylation450

BeadChip allows researchers to interrogate

> 485,000 methylation sites per sample at

single-nucleotide resolution.

Large DNA methylation remodelling in DS

We identified 4648 differentially methylated region between DSP and DSS blood


Identification of an epigenetic signature of Down Syndrome To provide an unambiguous epigenetic signature of DS,

from the list of 4648 Class A BOPs altered in DSP we

selected a short list of DMRs whose DNA methylation

status was remarkably different compared to healthy

sibs. To this aim, we considered only the BOPs

containing at least 2 adjacent CpG sites for which the

DNA methylation difference between DSP and DSS

was higher than 0.15, as previously suggested [32]. Of

the 4648 BOPs selected above, 68 met these more

stringent criteria (Supplementary Table 2). Fig. 3A

reports the DNA methylation profile for some of the

selected BOPs. Hierarchical clustering analysis showed

that the methylation status of the 68 loci clearly

separated DSP from DSS and DSM, while it did not

distinguish DSS from DSM (Fig. 3B). 73% of the

probes included in this epigenetic signature were

hypermethylated in DSP respect to DSS.

To investigate if our selection of CpG probes universally

characterizes DS, independently from genetic or

environmental factors, we took advantage of our family-

based cohort and we calculated for each DSP-DSS pair

the difference between the methylation levels of the most

significant CpG probe in each of the 68 BOPs.

Hierarchical clustering of the difference values did not

clearly distinguish any family from the others, indicating

that the identified signature is not significantly affected

by genetic or environmental factors (Fig. 3C).

The number of loci included in the epigenetic signature

of DS was too small to perform ontology enrichment

analyses, however from a careful screening of the list

four main functions emerged: 1) haematopoiesis

(RUNX1, DLL1, EBF4 and PRMD16); 2) morphogenesis

and development (HOXA2, HOXA4, HOXA5, HOXA6,

HHIP, NCAM1); 3) neuronal development (NAV1, EBF4,

PRDM8, NCAM1, GABBR1); 4) regulation of chromatin

structure (PRMD8, KDM2B, TET1).

Table 1. KEGG pathways and gene ontology analysis for Down Syndrome associated DMRs. The table reports the significantly enriched KEGG pathways and gene ontologies, as resulting from the analysis with Fisher’s exact test and GOrilla platform (see Materials and methods section).

Description q-value

Kegg Pathway

Ribosome 0.013

Allograft rejection 0.013

Graft-versus-host disease 0.013

Cell adhesion molecules (CAMs) 0.013

Autoimmune thyroid disease 0.013

PI3K-Akt signaling pathway 0.013

Basal cell carcinoma 0.013

HTLV-I infection 0.034

Type I diabetes mellitus 0.040

Gene Ontology Process

System process (GO:0003008 ) 0.027

Anatomical structure morphogenesis (GO:0009653 ) 0.032

Regulation of signal transduction (GO:0009966 ) 0.027

Multicellular organismal process (GO:0032501 ) 0.000

Single-organism process (GO:0044699 ) 0.015

Single-multicellular organism process (GO:0044707 ) 0.000

Positive regulation of biological process (GO:0048518 ) 0.027

Embryonic organ morphogenesis (GO:0048562 ) 0.006

Regulation of response to stimulus (GO:0048583 ) 0.035

Embryonic skeletal system morphogenesis (GO:0048704 ) 0.018

Anatomical structure development (GO:0048856 ) 0.017

Regulation of body fluid levels (GO:0050878 ) 0.038

www.impactaging.com 86 AGING, February 2015, Vol. 7 No.2

We identified 4648 regions differentially methylated between DSP and DSS blood


Identification of an epigenetic signature of Down Syndrome To provide an unambiguous epigenetic signature of DS,

from the list of 4648 Class A BOPs altered in DSP we

selected a short list of DMRs whose DNA methylation

status was remarkably different compared to healthy

sibs. To this aim, we considered only the BOPs

containing at least 2 adjacent CpG sites for which the

DNA methylation difference between DSP and DSS

was higher than 0.15, as previously suggested [32]. Of

the 4648 BOPs selected above, 68 met these more

stringent criteria (Supplementary Table 2). Fig. 3A

reports the DNA methylation profile for some of the

selected BOPs. Hierarchical clustering analysis showed

that the methylation status of the 68 loci clearly

separated DSP from DSS and DSM, while it did not

distinguish DSS from DSM (Fig. 3B). 73% of the

probes included in this epigenetic signature were

hypermethylated in DSP respect to DSS.

To investigate if our selection of CpG probes universally

characterizes DS, independently from genetic or

environmental factors, we took advantage of our family-

based cohort and we calculated for each DSP-DSS pair

the difference between the methylation levels of the most

significant CpG probe in each of the 68 BOPs.

Hierarchical clustering of the difference values did not

clearly distinguish any family from the others, indicating

that the identified signature is not significantly affected

by genetic or environmental factors (Fig. 3C).

The number of loci included in the epigenetic signature

of DS was too small to perform ontology enrichment

analyses, however from a careful screening of the list

four main functions emerged: 1) haematopoiesis

(RUNX1, DLL1, EBF4 and PRMD16); 2) morphogenesis

and development (HOXA2, HOXA4, HOXA5, HOXA6,

HHIP, NCAM1); 3) neuronal development (NAV1, EBF4,

PRDM8, NCAM1, GABBR1); 4) regulation of chromatin

structure (PRMD8, KDM2B, TET1).

Table 1. KEGG pathways and gene ontology analysis for Down Syndrome associated DMRs. The table reports the significantly enriched KEGG pathways and gene ontologies, as resulting from the analysis with Fisher’s exact test and GOrilla platform (see Materials and methods section).

Description q-value

Kegg Pathway

Ribosome 0.013

Allograft rejection 0.013

Graft-versus-host disease 0.013

Cell adhesion molecules (CAMs) 0.013

Autoimmune thyroid disease 0.013

PI3K-Akt signaling pathway 0.013

Basal cell carcinoma 0.013

HTLV-I infection 0.034

Type I diabetes mellitus 0.040

Gene Ontology Process

System process (GO:0003008 ) 0.027

Anatomical structure morphogenesis (GO:0009653 ) 0.032

Regulation of signal transduction (GO:0009966 ) 0.027

Multicellular organismal process (GO:0032501 ) 0.000

Single-organism process (GO:0044699 ) 0.015

Single-multicellular organism process (GO:0044707 ) 0.000

Positive regulation of biological process (GO:0048518 ) 0.027

Embryonic organ morphogenesis (GO:0048562 ) 0.006

Regulation of response to stimulus (GO:0048583 ) 0.035

Embryonic skeletal system morphogenesis (GO:0048704 ) 0.018

Anatomical structure development (GO:0048856 ) 0.017

Regulation of body fluid levels (GO:0050878 ) 0.038


We identified 4648 differentially methylated region between DSP and DSS blood

An epigenetic signature of DS

We further selected a short list of 68 DMRs whose DNA methylation status was

remarkably different between DSP and DSS

An epigenetic signature of DS

This signature is common to all the DSP-DSS pairs

Finally, we validated 3 of the DMRs included in the

epigenetic signature of DS (RUNX1 island, KDM2B N-

Shore and NCAM1 island) using an alternative method,

the Sequenom’s EpiTYPER assay. Besides the 29 DSP

and 29 DSS used for genome wide DNA methylation

analysis, the validation cohort included additional 49

DSP and 33 age- and sex- matched unrelated controls.

EpiTYPER analysis confirmed that the CpG sites

included in the 450k BeadChip were differentially

methylated between DSP and controls and showed that

the DMRs extended also to the adjacent CpG sites. In

particular, in RUNX1 and KDM2B amplicons all the

CpG sites resulted significantly hypermethylated in

DSP respect to controls (Fig. 4A and Fig. 4B;

Student’s t-test). On the contrary, only 7/11 of the

CpGs assessed in NCAM1 island were significantly

different between DSP and controls (Fig. 4C). As DS

can be characterized by total or partial trisomy, we

checked whether this could affect the methylation of

these DMRs. No significant difference between free

trisomy and translocation or mosaicism was found

(data not shown).

Figure 3. Epigenetic signature of Down Syndrome. (A) DNA methylation profiles of 6 of the 68 BOPs included in theepigenetic signature of DS. (B) The heatmap reports DNA methylation values for the 68 BOPs included in the epigenetic signature ofDS (CpG probes in rows, samples in columns and color‐coded). Dendrograms depicts hierarchical clustering of probes and samples.(C) For the 68 BOPs included in the epigenetic signature of DS, the heatmap reports DNA methylation differences between eachDSP and his/her DSS (CpG probes in rows, samples in columns). Dendrograms depicts hierarchical clustering of probes and samples(DSP‐DSS pairs). Both in (B) and in (C) the methylation value of the most significant CpG probe within each BOP was considered.


DNA methyaltion differences

between DSP-DSS pairs

Atypical aging in Down syndrome

Mean surivival in DS:

1933: 9 years

Today: 60 years

Expected to further increase in the future

• Premature/accelerated aging in DS (Martin 1978) is atypical and segmental:

• Integumentary system

• Endocrine system

• Sensory system

• Musculoskeletal system

• Immunological system

• Neurological system

• Persons with DS suffer a premature/accelerated decline of cognitive

functions and develop Alzheimer's disease with high frequency

The epigenetic clock

• Built from 8000 samples from 82 Illumina DNA

methylation array datasets

• 353 CpGs

• DNA methylation age (DNAmAge)

• High correlation between DNAmAge and

chronological age on a large data set (cor = 0.97,

error = 2.9 years)

• Its measurement of chronological age in controls is

extremely accurate

• It applies to most sorted cell types and complex

tissues

A multi-tissue predictor of age, including the methylation levels of 353 CpG sites,

that allows to estimate the DNA methylation age of most tissues and cell types

The epigenetic clock

Condition Source

Alzheimer disease Prefrontal cortex

Amyloid load and neuropathology Prefrontal cortex

Body mass index Liver

C-reactive protein Blood

Cancer Blood

Centenarians and centenarians' offspring Blood

Cognitive performance Blood and brain

Down syndrome Blood and brain

Frailty Blood

Glucose Blood

Hungtinton disease Blood and brain

Insuline levels Blood

Menopause Blood

Mortality (all-cause) Blood

Obesity Liver

Osteoarthritis Cartilage

Parkinson disease Blood

Sex Blood

Triglycerides Blood

Werner syndrome Blood

Persons with DS have higher values of

DNAmAge than controls (+ 6.6 years in

mean)

Premature/accelerated epigenetic aging in DS

+ 4.6 years

Persons with DS have higher values of

DNAmAge than controls (+ 6.6 years in

mean)

Premature/accelerated epigenetic aging in DS

+ 3.9 years + 11.5 years + 4.6 years + 2.8 years

Conclusions -1

• Esiste una firma epigenetica della Sindrome di

Down; le regioni differentemente metilate sono

distribuite in tutto il genoma

• I profili epigenetici ricapitolano il fenotipo di

invecchiamento prematuro/accelerato

Heterogeneity in DS

F1000Research

Open Peer Review

F1000 Faculty Reviews are commissioned

from members of the prestigious F1000

. In order to make these reviews asFaculty

comprehensive and accessible as possible,

peer review takes place before publication; the

referees are listed below, but their reports are

not formally published.

, Johns HopkinsRoger H. Reeves

University USA

, University of EdinburghJennifer Wishart

UK

Discuss this article

2

1

REVIEW

The importance of understanding individual differences in Down

syndrome [version 1; referees: 2 approved]

Annette Karmiloff-Smith , Tamara Al-Janabi , Hana D'Souza , Jurgen Groet ,

Esha Massand , Kin Mok , Carla Startin , Elizabeth Fisher , John Hardy ,

Dean Nizetic , Victor Tybulewicz , Andre Strydom2,3

Centre for Brain & Cognitive Development, Birkbeck University of London, London, WC1E 7HX, UK

The London Down Syndrome Consortium (LonDownS), University College London, London, UK

Division of Psychiatry, University College London, London, W1T 7NF, UK

The Blizard Institute, Barts & The London School of Medicine, Queen Mary University of London, London, E1 2AT, UK

Department of Molecular Neuroscience, University College London Institute of Neurology, London, WC1N 3BG, UK

Division of Life Science, Hong Kong University of Science and Technology, Hong Kong SAR, China

Department of Neurodegenerative Disease, Institute of Neurology, London, WC1N 3BG, UK

Lee Kong Chian School of Medicine, Nanyang Technological University, Biopolis, 138673, Singapore

Francis Crick Institute, London, NW7 1AA, UK

Department of Medicine, Imperial College London, London, W12 0NN, UK

Abstract

In this article, we first present a summary of the general assumptions about

Down syndrome (DS) still to be found in the literature. We go on to show how

new research has modified these assumptions, pointing to a wide range of

individual differences at every level of description. We argue that, in the context

of significant increases in DS life expectancy, a focus on individual differences

in trisomy 21 at all levels—genetic, cellular, neural, cognitive, behavioral, and

environmental—constitutes one of the best approaches for understanding

genotype/phenotype relations in DS and for exploring risk and protective

factors for Alzheimer’s disease in this high-risk population.

1,2 2,3 1,2 2,4

1,2 2,5,6 2,3 2,7 2,5

2,4,8 2,9,10 2,3

1

2

3

4

5

6

7

8

9

10

Referee Status:

Invited Referees

version 1

published

23 Mar 2016

23 Mar 2016, (F1000 Faculty Rev):389 (doi: First published: 5

)10.12688/f1000research.7506.1

23 Mar 2016, (F1000 Faculty Rev):389 (doi: Latest published: 5

)10.12688/f1000research.7506.1

v1

Page 1 of 10

F1000Research 2016, 5(F1000 Faculty Rev):389 Last updated: 25 DEC 2016

Heterogeneity in DS

F1000Research

Open Peer Review

F1000 Faculty Reviews are commissioned

from members of the prestigious F1000

. In order to make these reviews asFaculty

comprehensive and accessible as possible,

peer review takes place before publication; the

referees are listed below, but their reports are

not formally published.

, Johns HopkinsRoger H. Reeves

University USA

, University of EdinburghJennifer Wishart

UK

Discuss this article

2

1

REVIEW

The importance of understanding individual differences in Down

syndrome [version 1; referees: 2 approved]

Annette Karmiloff-Smith , Tamara Al-Janabi , Hana D'Souza , Jurgen Groet ,

Esha Massand , Kin Mok , Carla Startin , Elizabeth Fisher , John Hardy ,

Dean Nizetic , Victor Tybulewicz , Andre Strydom2,3

Centre for Brain & Cognitive Development, Birkbeck University of London, London, WC1E 7HX, UK

The London Down Syndrome Consortium (LonDownS), University College London, London, UK

Division of Psychiatry, University College London, London, W1T 7NF, UK

The Blizard Institute, Barts & The London School of Medicine, Queen Mary University of London, London, E1 2AT, UK

Department of Molecular Neuroscience, University College London Institute of Neurology, London, WC1N 3BG, UK

Division of Life Science, Hong Kong University of Science and Technology, Hong Kong SAR, China

Department of Neurodegenerative Disease, Institute of Neurology, London, WC1N 3BG, UK

Lee Kong Chian School of Medicine, Nanyang Technological University, Biopolis, 138673, Singapore

Francis Crick Institute, London, NW7 1AA, UK

Department of Medicine, Imperial College London, London, W12 0NN, UK

Abstract

In this article, we first present a summary of the general assumptions about

Down syndrome (DS) still to be found in the literature. We go on to show how

new research has modified these assumptions, pointing to a wide range of

individual differences at every level of description. We argue that, in the context

of significant increases in DS life expectancy, a focus on individual differences

in trisomy 21 at all levels—genetic, cellular, neural, cognitive, behavioral, and

environmental—constitutes one of the best approaches for understanding

genotype/phenotype relations in DS and for exploring risk and protective

factors for Alzheimer’s disease in this high-risk population.

1,2 2,3 1,2 2,4

1,2 2,5,6 2,3 2,7 2,5

2,4,8 2,9,10 2,3

1

2

3

4

5

6

7

8

9

10

Referee Status:

Invited Referees

version 1

published

23 Mar 2016

23 Mar 2016, (F1000 Faculty Rev):389 (doi: First published: 5

)10.12688/f1000research.7506.1

23 Mar 2016, (F1000 Faculty Rev):389 (doi: Latest published: 5

)10.12688/f1000research.7506.1

v1

Page 1 of 10

F1000Research 2016, 5(F1000 Faculty Rev):389 Last updated: 25 DEC 2016

• Subgroups?

• Increased variability?

Heterogeneity in DS - Subgroups


For example, are there epigenetic

differences between DS patients with

and without Alzheimer’s disease?


Prefrontal cortex

A meta-analysis of existing datasets suggests the existence of epigenetic differences between DS patients with and without Alzheimer’s disease

Heterogeneity in DS – Increase in variability

Collaboration with

Prof. Mikhail Ivanchenko,

Head of Applied Maths,

Lobachevsky University

Igor Yusipov

Alena KalyakulinaMikhail KrivonosovOlga Vershinina

Heterogeneity in DS – Increase in variability

Increased variability in DS...

… which is even more evident

when we consider those CpG

sites that show an increase in

variability during physiological

aging





e he

Grazie per l'attenzione!

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