Marni Falk, Convegno Mitocon 2015
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Transcript of Marni Falk, Convegno Mitocon 2015
New perspectives in research & therapies for mitochondrial disease in the US:
Roles of networks, databases & biobanks
Marni J. Falk, M.D., FACMGAssistant Professor of Pediatrics
Division of Human GeneticsThe Children’s Hospital of Philadelphia
University of Pennsylvania Perelman School of MedicinePhiladelphia, Pennsylvania, USA
&Chair, Scientific and Medical Advisory Board
United Mitochondrial Disease Foundation (UMDF)
DISCLOSURES
Marni J. Falk, M.D. is
•Chair, Scientific and Medical Advisory Board & Member, Board of Trustees, United Mitochondrial Disease Foundation
• Organizer, Mitochondrial Disease Sequence Data Resource (MSeqDR) Consortium
• SAB Member, The Genesis Project
• Consultant, Mitobridge
OUTLINE• Mitochondrial Disease Clinical Care & Research in US
– CHOP Mito-Genetics Diagnostic Clinic experience
• Crossing the line from clinical care to human research– Establishing local and/or national biospecimen repositories– Enrolling subjects in national registries and biobanks
• North American Mitochondrial Disease Consortium (NAMDC)• Mitochondrial Disease Community Registry (MDCR)• Mitochondrial Disease Sequence Data Resource (MSeqDR)
• Translational research with mito disease biospecimens– Etiology-based studies of genetics and metabolism– Subgroup specific pathophysiology and therapies
n = 152 patients referred from 2008-2011 to CHOP Mito-Genetics Diagnostic Clinic
Ages 6 weeks to 81 years old.
CHOP Mito-Genetics Clinic: Referral Indication
Genetic diagnoses made in 28% of cases referred for suspected mito disease
Diagnostic Yield “PRE” Next Gen Sequencing:
DEFINITE MITO DISEASE
-Defined molecular etiology 14%
-Biochemical findings without evident molecular etiology* 4%
PROBABLE/POSSIBLE MITO DISEASE
-mtDNA variant of unknown significance 5%
-Normal tissue biochemistry + no clear molecular etiology 29%
-UNLIKELY PRIMARY MITO DISEASE 39%
-PROVEN OTHER GENETIC DISORDER 9%
Improved diagnostic yield from whole mtDNA genome sequencing
• Pathogenic mtDNA mutations identified in 19 patients (10 kindreds):
– tRNALEU 3243A>G heteroplasmy (3 patients)– tRNALEU 3288A>G heteroplasmy (6 patients) Hadjigeorgiop GM et al, 1999
– tRNALYS 8344A>G heteroplasmy (1 patient)– tRNASER(AGY) 12264C>T heteroplasmy (1 patient) Schrier SA et al, 2012
– tRNATRP 5537_5538insT heteroplasmy (2 patients) Santorelli FM et al,1997
– ND4 and ND6 11778G>A /14484T>C het/homo (3 patients) Brown MD et al, 2001
– ND4 11778G>A homoplasmy (1 patient)– ND5 13513G>A heteroplasmy (2 patients)
* mtDNA common mutation panel
• Potentially pathogenic mtDNA mutations (VUS) in 7 patients (5 kindreds):
– tRNATYR 5836A>G homoplasmy (2 patients)– ND2 4936C>T heteroplasmy (1 patient)– ND2 and ATP8 4960C>T /8472C>T homo/homo (2 patients) – ATP6 155A>T homoplasmy (1 patient)– COXII 7962T>C homoplasmy (1 patient)
15 other genetic diagnoses made• Primary mitochondrial disease (2 patients)
– mtDNA deletion in muscle of 1 isolated CPEO patient– POLG-related disease in 1 kindred
• Non-primary mitochondrial disease (8 patients)– Molybdenum cofactor deficiency (MOCS2)– CPT2 deficiency– WFS1-related hearing loss– Myotonia congenita– Congenital myasthenic syndrome (CHRNE)– SEPN1-related myopathy– Ullrich muscular dystrophy (COL6A1 deletion/mutation)– Gitelman syndrome
• Chromosomal copy number abnormalities (5 patients)– MEF2C deletion (SNP array)– IL1RAPL2 deletion (SNP array)– 7.91 Mb deletion on chromosome 7q31.32q32.2 (SNP array)– 3-way unbalanced translocation (Karyotype/SNP array)– Isochromosome Xp (Karyotype)
Gene-by-gene diagnostic approach in mito disease has limited success
• A dedicated Mitochondrial-Genetics Diagnostic Clinic improves the diagnosis of primary mitochondrial diseases
• Recognize “classic” but complex phenotypes
– mtDNA disorders > nDNA disorders
• Guide optimal utilization/interpretation of metabolic screening labs, genetic testing, and tissue biopsy studies
• Identify wide variety of phenotypically overlapping conditions
– Time, labor, and testing intensive• Few metabolic specialists to meet growing clinical demand
MITO DISEASE DIAGNOSTICS IN THE ERA OF NGS
• Mitochondrial disease is highly heterogeneous in causes and features
‒ Traditional single gene testing has had limited diagnostic success
‒ Newer genomics technologies enable comprehensive and efficient testing for all known genetic causes in dual genomes
‒ >200 nuclear genes
‒ All 37 mtDNA genesm
‒ Diagnose >50% of complex mitochondrial diseases in one test*
‒ Novel disease gene discovery
• We have entered a computationally sophisticated molecular diagnostic age for understanding subclasses of mitochondrial disease**:
**Calvo S, Mootha R, Ann Rev Genom Hum Genet, 2010; **McCormick E et al, 2012, Disc Med
NGS diagnostic approach comparison
• Sequence ~100+ known mito disease and related disease genes• Prior unsolved cases of infantile Leigh syndrome• 23% (13/60) diagnostic rate (Calvo S et al, Nature Genetics, 2010)
• Sequence ‘MitoExome’ of mitochondria-localized genes• Targeted capture of 1,381 nuclear genes + mtDNA genome• 291 OXPHOS patients (Calvo S et al, Sci Transl Med, 2011)• 24% (10/42) diagnostic rate for unsolved cases
• 47% extrapolated diagnostic rate to all cases
• Sequence whole nuclear exome• 38% (13/34) cases analyzed have clear genetic etiology (Baylor)
– Only analyze exome of probands, not of family members– Not include analysis of mtDNA genome
Emerging diagnostic approach for suspected mitochondrial disease
• Careful clinical evaluation/ phenotype description– History and Exam– Pedigree– Blood/urine metabolic screening laboratory studies– Tissue analyses in some
• mtDNA whole genome sequence analysis
+ mtDNA deletions, mtDNA copy number
• nDNA copy-number alterations (genome-wide SNP array)
• nDNA exome capture/Next Gen sequencing analysis
OUTLINE• Mitochondrial Disease Clinical Care & Research in US
– CHOP Mito-Genetics Diagnostic Clinic experience
• Crossing the line from clinical care to human research– Establishing local and/or national biospecimen repositories– Enrolling subjects in national registries and biobanks
• North American Mitochondrial Disease Consortium (NAMDC)• Mitochondrial Disease Community Registry (MDCR)• Mitochondrial Disease Sequence Data Resource (MSeqDR)
• Translational research with mito disease biospecimens– Etiology-based studies of genetics and metabolism– Subgroup specific pathophysiology and therapies
Challenges and benefits to PI of establishing a local biorepository
• Time-Intensive, Detail-Intensive, and Labor-Intensive– Genetic Counselor as common clinic & study coordinator– Local IRB establishment, approval, oversight/audits– Database establishment/maintenance/mining
• Excel REDCap– Local acquisition of tissue samples and establishment of cell lines and
derived materials
• High potential pay-off– High local knowledge of subject phenotypes & prior testing– Rich material for translational research at discretion of PI
• Genetic etiology, Pathophysiology, and Therapeutic modeling
>600 mito disease + control subjects enrolled since 2008 in CHOP IRB-approved
tissue research study protocolMITO DISEASE
CATEGORYLCL FCL Muscle KNOWN DIAGNOSES
Definite 21 18 5
mtDNA mutations (MELAS, MERRF, LHON, other tRNAs, CI subunits)
nDNA mutations (POLG, MPV17, RRM2B, TIMM44 , SLC25A12 )
Probable/Possible 14 17 1mtDNA variant of ? pathogenicity,
RC deficiency of ? etiology, Lactic acidemia
Other Disease 3 8 5
PDH or PC deficiency, SEPN1 mutation, MEF2C deletion,
NMNAT1 mutation
Healthy Control 14 14 10 -
Blood DNA Blood RNA Muscle DNA Muscle RNA FCL DNA FCL RNAEXTRACTED
SAMPLE #33 19 47 28 26 29
CHOP Bioinformatics efforts to improve patient-linked registry and tissue biorepository
• Sample/Data Tracking LIMS
• Manage PI Level data REDCap
• Clinical Data EPIC
• Clinical Trial Management Oncore
• Data Query + Exploration Harvest
Incorporate Phenotype Capture & Display Tools
• REDCap– Research electronic data capture tool– Free, web-based, clickable data entry– Custom design tools to capture any desired data type
• Common data elements (CDE) optimized for mitochondrial disease• Integrate with NAMDC data capture tools and fields
REDCap-based Mito Disease Data Capture
Claire Sheldon, MD, PhD, Elizabeth McCormick, MS, Jeff Miller, PhD
Central Issues in Multi-Investigator Biorepository• Trust
– Data quality: accurate and updated information entered?– Sample quality: handling and shipment protocols?– Ongoing resource funding and sustainability?
• Incentive– Why and what should local PIs contribute from own tissue repositories?– Local PI support mechanism for samples acquisition and data entry?– Ongoing, widely available source of relevant human disease subjects + tissues
• Unequal burden:benefit ratio for established vs new investigators?
• Data and sample governance/access– How will data be stored and accessed? – What are hurdles and costs to obtain samples out of repository?– Should/how will contributing PI be acknowledged in resulting publications?
• Data transparency and systems ease-of-use– What samples are in biorepository, available for study and by whom?
North American Mitochondrial Disease Consortium (NAMDC)
• Established in 2011, now 17 sites in US + Canada– NICHD/NINDS R01: PI – Dr. Michio Hirano (Columbia University, NY)
• Major goals:1.Mito Disease Patient Registry (790 enrolled by June 1)
A. Natural history studies (IND pre-requisite)B. Patient base for clinical trialsC. Detailed phenotypic information requested from physician
2.Mito Disease Specimen and DNA BiorepositoryA. Central IRB protocol biorepository at Mayo Clinic (MN)B. Any tissue type accepted
Mitochondrial Disease Community Registry
Who? Patients, caregivers & family membersConfirmed diagnosis is NOT required
Why? Need patient data collected over time in order to improve diagnoses and develop treatments
Key Considerations:Registrants fully control privacy settings
• Allow, deny or “ask me”• Who can see anonymous data• Who can analyze anonymous data• Who can contact you about
research studies and clinical trials
www.umdf.org/registry
Mitochondrial Disease Community Registry Key Points
• MDCR is sponsored by UMDF, but meant to be a community asset– UMDF pledges to steward the project and serve as guardian of collected
data
• MDCR seeks input from patients, caregivers and relatives of those affected by mitochondrial disease– Living or deceased / Any location– Confirmed diagnosis NOT required
• MDCR is meant to collect health information over time– Surveys will be presented on a regular basis– No demands or expectations- participate when you can and want
• MDCR is not meant to replace any other registry– Each registry has unique goals and capabilities
• Registrants are in full control of privacy settings– Adaptable settings about who may see and do what with your information
Philip Yeske, PhDUMDF Science and Alliance Officer
Mitochondrial Disease Community RegistryStatus & Future Directions
Present:•~1000 accounts, ~1200 health profiles, ~120K data points (questions answered)•First survey: basic demographic info, diagnostic state, opinions on state of mitochondrial research and future MDCR directions•If already registered, please sign in again and confirm first survey complete
Near Future:•Creation of FAQ based on community feedback•Selection of “Navigators”- peers willing to help peers with registry•Additional surveys presented on topics of interest
In-Planning:•Uploading and sharing of genetic data (whole exome sequencing)•Importation of Electronic Health Records•International Engagement
Philip Yeske, PhDUMDF Science and Alliance Officer
Mitochondrial Disease Sequence Data Resource (MSeqDR)
MSeqDR is an international mitochondrial disease community collaborative effort to create a unified genomic data resource that facilitates diagnosis andenables improved understanding of individual mitochondrial diseases
https://mseqdr.org is a central entry for clinicians, diagnostic labs, & researchers to enable genomic data sharing and analyses in suspected mitochondrial disease
– Flexible, updated suite of web-based and open access software tools accessible from your office/clinic desktop to securely mine all genetic & exome data in real-time
•Exploit collective information of variant allele frequencies in a large cohort of individuals with suspected mitochondrial disease (gem.app, G-browse, etcsg)•Will be linked to relevant phenotype & laboratory data•Accelerate pace and accuracy of known & novel gene discovery in mito disease
– Genomic data deposition for individual and/or community mining» Deposit aggregate-level deidentified exome or variant data to share at various
levels of comfort (BioDAS Server)» Patient-determined deposition & access to exome and phenotype data» Assist with data curtain & transfer to public resources (ClinVar, NCBI)
MSeqDR GBrowse• Visualization of variants in both nuclear & mitochondrial (mtDNA) genomes• Hosts custom tracks for mitochondrial disease community
MSeqDR LOVD• Locus specific database for all mitochondrial disease genes and all genes that
encode mitochondrial proteins• Curates gene, transcript, variant, and disease data relevant to mitochondria
MSeqDR-GEM.app• Web-based repository and tool to readily enable analysis of sequence data from
gene panels, exomes, genomes, and mtDNA genomes• Supports analysis of data from individuals, families, or cohorts
MSeqDR Tools• Centralized host and link to public and custom tools that enable users to perform
dataset and variant level analyses in both nuclear & mtDNA genomes• Provides support to phenome and ontology tools for mitochondrial disease
HBCR: Human BP Codon Resources
Mitochondrial Disease Sequence Data Resource: Major Domainshttps://mseqdr.org
Falk MJ et al, Mol Gen Metab, 2015
• MSeqDR tools technical optimization and response to community feedback
– GUID system implementation and assignment to all data types
– Phenotype data integration (existing vs new data)• Integrate NINDS Mito Disease Common Data Element Terms• HPO ontology tree-like structure
– Match degree of phenotype data shared to user access rights
– Further integration with GEM.app (GENESIS Project)
– Further integration with NIH ClinGen and NCBI (dbGAP, ClinVar)
• Ethical use and oversight– Data security protections (aggregate data, cloud computing)– Develop web portal to directly deposit deidentified phenotype data
• Translate access page into different languages– Develop data access and use oversight committee
• Clinical diagnostic labs, researchers, physicians, family support groups, etc.
MSeqDR “go-live” preparation underway
MSeqDR Live Hands-On Tutorials
MSeqDR User Analytics
Acknowledgements
FUNDINGUnited Mitochondrial Disease Foundation
NAMDC Pilot Grant Award #NAMDC7407 (NINDS/NICHD, NIH)
U01-HG006546 (NHGRI, NIH)
U41-HG006834 (NHGRI, NIH)
MEEI/HarvardXiaowu Gai, PhD
Lishuang Shen, PhD
University of MiamiStephan Zuchner, MD
Michael Gonzalez, PhD
NICHD, NIHDanuta Krotoski, PhD
Melisa Parisi, MD, PhD
UMDFChuck Mohan, CEO
Dan Wright, PresidentPhilip Yeske, PhD
Janet OwensCliff Gorski
CHOPClaire Sheldon, MD, PhD
Elizabeth McCormick, MS, CGC
MSeqDR PROTOTYPE DEVELOPMENT PARTICIPANTS:• Doug Wallace, Michio Hirano, Doug Kerr, Curt
Scharfe, Li Dong, Hakon Hakonarson, Bruce Cohen, Amy Goldstein, Richard Haas, Russell Saneto (USA)
• Marcella Attimonelli, Mannis van Oven (Italy)• Holger Prokisch (Germany)• Mark Tarnopolsky, Isabella Thiffault (Canada)• Richard Rodenburg, Jan Smeitink, IFM de Coo, Bert
Smeets, Fons Stassen (The Netherlands)• Virginia Brilhante (Finland)• Yasushi Okazaki (Japan)• Donna Maglott, Wendy Rubinstein (NCBI)• Heidi Rehm (ClinGen)• Clinical diagnostic laboratories:
• Jeana DaRe, David Ralph (Transgenomics)• Renkui Bai, Sherri Bale (GeneDx)• Richard Boles, Christine Stanley (Courtagen)
OUTLINE• Mitochondrial Disease Clinical Care & Research in US
– CHOP Mito-Genetics Diagnostic Clinic experience
• Crossing the line from clinical care to human research– Establishing local and/or national biospecimen repositories– Enrolling subjects in national registries and biobanks
• North American Mitochondrial Disease Consortium (NAMDC)• Mitochondrial Disease Community Registry (MDCR)• Mitochondrial Disease Sequence Data Resource (MSeqDR)
• Translational research with mito disease biospecimens– Etiology-based studies of genetics and metabolism– Subgroup specific pathophysiology and therapies
VALIDATION OF GENETIC ETIOLOGY AND
UNDERLYING PATHOPHYSIOLOGY
A lot of research is needed to validate novel mutations for suspected mito disease
• Traditional Sanger sequence validation– Confirm mutation presence and segregation with disease in family
• Functional analyses if novel mutation and/or disease gene– Is this clinical or research?
• What does it take to make variant “medically actionable”?
– Enzyme activity assay if known enzyme– Should other mito function(s) be assayed in tissue or cell lines?
• RC enzyme activity• Oxidant effects• Mitochondria content• mtDNA content• Mitochondrial membrane potential
– Gene rescue experiment in patient’s cells?– Transmitochondrial cybrids if novel mtDNA variant?
149,953(130,948/19,005)
20,828(20,468/360)
10,936
Synonymous
11,179(10,819/360)
Non-Synonymous
CodingTotal(SNPs/Indels)
212 genes
816(797/19)
18(17/1)
4(4/0)
Gene Candidates
Novel
Family-based whole exome sequencing: Disease diagnosis becomes a computer game
Biparental compound
heterozygous
MitoCarta
8genes
2genes
1gene
2(2/0)
Predicted pathogenic
Sequence Variants
Case 1: Young girl with Leigh syndrome, chronic lactic acidosis (3-5 mM), complex I/III deficiency. POLG heterozygote. Normal SNP array. Normal sequence of mtDNA genome and 18 individual nuclear genes. Only child, no family history of disease.
Xiaowu Gai, PhD, Eric Pierce, MD, PhD
Visualization of next generation sequencing mutationsMutation #2:
G>C transversion (p.N251K)112 of 231 reads
(maternally inherited)
Mutation #1: G>T transversion (p.P308Q)
29 of 63 total reads(paternally inherited)
Xiaowu Gai, Stephen Dingley
ControlFCL
RED: Mito Marker(anti-CcO subunit IV)
GREEN: anti-FLAG (Tagged CcO, subunit Vb)
ProbandFCL
Satish Srinivasan, PhD
Case 1: Mito morphology and protein import is defective in the patient’s skin cells
YELLOW: overlay
Human Mito Disease Subject Fibroblasts
Zhang Z et al, PLOS ONE, 2013
Cytosolic and mitochondrial translation are differentially affected in human RC disease
Zhang Z et al, PLOS ONE, 2013
Heterogeneous RC diseases,human muscle + FCLs
Public transcriptome datasets (GEO)
Zhang and Falk, IJBCB, 2014
RC dysfunction dysregulates central nodesof the nutrient-sensing signaling network to mediate downstream cellular response
DEVELOPMENT OF PERSONALIZED DISEASE
THERAPIES
WT CI CIV CI/III
Primary RC disease patient fibroblasts have variable “phosphokinase” node profiles
Mai Tsukikawa, MS
( p38/ ERK1/2)
mTORC1(Raptor/GβL)
AKT1/2PKB
TSC1/2 Rheb
•BCAA•Excess nutrientsmTORC2
(Rictor/GβL)
•Protein Synthesis•ribosome biogenesis•mRNA translation
•Cell growth•Autophagy inhibition
4E-BP1S6K1
S6IRS-1
JNKFOXO1
MAPK
Insulin
•Growth Factors
NRF1/2
ERBB
PDK-1
PPARγ
AMPKACC
PGC-1α
TFAM
SIRT1•NAD+
•↑AMP or ↓ATP•Reductive stress•Hypoxia•Metformin•AICAR
•Rapamycin
•Nicotinic Acid
•mtDNA-encoded OXPHOS subunits
•MITO Biogenesis & OXPHOS•nDNA-encoded RC subunits
•Antioxidant defense •Glutathione synthesis
•P450 metabolism•Heme Biosynthesis
P
P
P
P
GSK-3
•Glycogen Synthesis
P
P
PP
PP
•Rosiglitazone•Fibrates
•Lipid synthesis
•Lipogenesis
•Resveratrol
•Longevity•Glycolysis
•Fatty acid oxidation•Stress Response
•Pathogen Resistance
•NORMAL MITOCHONDRIAL FUNCTION
P
•Glucose
PI3-K
P
P
Directly inhibiting cytosolic translation rescues rotenone-induced cell death
in a variety of cell types
0
25
50
75
100
1 day 2 days 3 days 4 days 5 days 6 days
Control
ROT
ROT + CHX
Cell
Dea
th P
erce
nt(%
)
0
20
40
60
80
100
120
day 1 day 2 day 3 day 4 day 5 day 6
Control
ROT
ROT + CHX
ROT + ASM
ROT + ATM
Cell
Dea
thof
Per
cent
(%)
0
25
50
75
100
Control 12.5nM ROT
25nM ROT
50nM ROT
100nM ROT
Control + CHX
1.25nM ROT + CHX
25nM ROT + CHX
50nM ROT + CHX
100nM ROT + CHX
Cell
deat
h pe
rcen
t(%
)
A
C D
B
Podocytes11 mM glc
0
25
50
75
100
1 day 2 days 3 days 4 days 5 days 6 days
Control
ROT
ROT + CHX
Cell
Dea
th P
erce
nt(%
)Fibroblasts5.6 mM glc
Podocytes(48 hrs)
11 mM glc
(100 nM)
(1.8 uM)
HeLa5.6 mM glc
(125 nM)
(3.6 uM)
(1.8 uM)
(1.8 uM)
(1.8 uM)
(40 nM)
(50 nM)
Peng M et al, Human Molecular Genetics, In press
Cycloheximide maintains total cellular respiratory capacity in direct RC inhibition
0
20
40
60
80
ROUTINE LEAK ETS
CONTROL
50nM ROT
ROT + CHX
Oxy
gen
flux
per m
ass (
pmol
.s-1
.mg-
1 )
******
******
**
**
0
20
40
60
80
ROUTINE LEAK ETS
control
50nM AA
AA + CHX
Oxy
gen
flux
per m
ass (
pmol
.s-1
.mg-
1)
*****
NS
** *
NS
0
20
40
60
80
ROUTINE LEAK ETS
control
0.25uM Oligo
Oligo + CHX
Oxy
gen
flu
x p
er m
ass
(pm
ol.s-
1.m
g-1 )
***NS
***
* *
NS
CI CIII
CVPeng M et al, Human Molecular Genetics, In press
0
10,000
20,000
30,000
40,000
50,000 TMREM
ean C
ell F
luor
esce
nce
(RFU
)
Control 25 nM 50 nM 25 nM 50 nM CHXROT ROT ROT ROT
+ CHX + CHX
0.0E+00
4.0E+05
8.0E+05
1.2E+06
1.6E+06
2.0E+06
Control 50nMRotenone
ROT-0.9uMCHX
Mea
n Ce
ll Fl
uore
scen
ce(R
FU)
MitoTracker Green
# *
1.0E+061.1E+061.2E+061.3E+061.4E+061.5E+061.6E+061.7E+061.8E+061.9E+062.0E+06
F35 Q1007 Q1007-0.9uM CHX
MitoTracker Green
Mea
n Ce
ll Fl
uore
scen
ce(R
FU)
Control FBXL4 FBXL4+ CHX
* ***
50,000
60,000
70,000
80,000
90,000
100,000
110,000
Q1007 control Q1007-0.9uM chx
Mea
n Ce
ll Fl
uore
scen
ce MitoSox
*
FBXL4 FBXL4+ CHX
Peng M et al, Human Molecular Genetics, In press
H+NADH + H+NAD + 2+
H+FAD + 2+FADH
2
TC A CYCLE
Respiratory Chain Functions
III
V
Cyt C
III IVH+
H+
e- e-
H+2 + ½ O2
H O2
H+H+
H+H+
H+H+
H+
H+
H+H+H+ H+H+
CoQ
ADP + P ATP
IMM
Matrix
e-
e-
V
mTORC1S6
AMPKP
P
Mitochondrion
Lysosome
Ribosome
Ribosome
MITOPHAGY
ProteotoxicStress
CHX
RAPAProbucol
LiCl,3-MA
Probucol
[c]
[1]
[4]
[d]
[5]
[a]
[3]
[b]
[2]
Peng M et al, Human Molecular Genetics, In press
Zhang Z et al, PLOS ONE, 2013
Nicotinic acid normalizes mTORC1 & AMPK activities, NADH/NAD+ levels, and total cellular respiratory
capacity in ND4/ND6 human fibroblasts
CONCLUSIONCharacterizing and therapeutically targeting central alterations in the nutrient-sensing signaling network
may offer a personalized means to modify global sequelae downstream of OXPHOS dysfunction and
improve health outcomes in primary RC disease
New Model for Getting to Effective Therapies for Mitochondrial Diseases
In Vitro Laboratory Drug testing in Mito Disease
-Patients’ cells (Fibroblasts vs Tissue-specific)-Genetic models of RC disease
-Integrated physiologic endpoints-Toxicity studies
Disease Definition
-Phenotype + Function-Biochemical
-Organelle-Genetic etiology
-Molecular Pathway
Outcome Prioritization
-Organ system-Pathophysiology
-Function-Biomarker
Treatment Options
-Off-purpose FDA drugs-Medical Foods
-Dietary Supplements-Vitamins
-New drugs from Pharma
Standard of Care
Clinical Trials
Acknowledgements
University of PennsylvaniaRui Xiao, PhD
David L. Gasser, PhD Eiko Nakamaru-Ogiso, PhD
Joseph Baur, PhD
FUNDINGR01-HD065858 (NICHD, NIH)R03-DK082521 (NIDDK, NIH)R01-DK055852 (NIDDK, NIH)
IDDRC New Investigator Award, NICHDPhiladelphia Foundation
Tristan Mullen FundAngelina Maio Fund
Kelsey Wright FoundationJuliet’s Cure Mitochondrial Disease Research FundCenter for Mitochondrial & Epigenomic Medicine
CHOPJim (Zhe) Zhang, PhD
Marc Yudkoff, MDEric Rappaport, PhD Michael Bennett, PhDDouglas Wallace, PhD
Colleen Clarke, MS, CGC Arizona State UniversitySid Hecht, PhD
Omar Khdour, PhD
FALK LAB