EXPERIMENTAEXPERIMENTAL L

MAN MAN

One Man’s One Man’s

Intimate JourneyIntimate Journey

Inside Himself, Inside Himself,

Cell by CellCell by Cell

David Ewing Duncan David Ewing Duncan

David Ewing Duncan, 2007

“All Life is an experiment. The more experiments you make the better.”

– Ralph Waldo Emerson

Personalized Medicine Is:

GenesEnvironmentBrainBody

Not yet ready for individuals

Uneven validation and unregulated

Expensive: my tests ~ $100,000

Health Care and bioethics communities unprepared

Observations and Caveats

GENESGENES

DED Results: Illumina 1 Million SNP Chip

Genetic Markers Tested: 1 Million

Disease and Behavior Variants Found: 169

Sample Variations, Analysis by Omicia, Inc.:

Gene | snpdb | var_id | snpdb_var_id | gp_position | ref | var| aa_ref | aa_var | allele1 | allele2 | genotype |-------------+-------+------------+------------------+-----------------+-----------+---------+--------------+------------+--------------+---------+---------+----------+-------

ABCA1 | HGMD | rs2230806 | CM030397 | chr9:106660688 | C | T | R | K | T | C | var/ref |

ABCA1 | HGMD | rs2230808 | CM042912 | chr9:106602625 | T | C | K | R | T | C | ref/var |

ABCA1 | HGMD | rs4149313 | CM990005 | chr9:106626574 | T | C | I | M | T | C | ref/var |

ABCB1 | HGMD | rs2032582 | CM033585 | chr7:86998554 | A | C | S | A | C | C | var/var |

ABO | HGMD | rs512770 | CM011264 | chr9:135123327 | A | G | S | P | A | G | ref/var |

ABO | HGMD | rs688976 | CM011263 | chr9:135126591 | A | C | F | V | A | C | ref/var |

ADH1C | HGMD | rs283413 | CM050165 | chr4:100487213 | A | C | * | G | C | C | var/var |

ADH1C | HGMD | rs698 | CM033593 | chr4:100479812 | T | C | I | V | C | C | var/var |

ADRB2 | HGMD | rs1042713 CM950016 | chr5:148186633 | G | A | G | R | A | G

AGT | HGMD | rs699 | CM920010 | chr1:228912417 | A | G | M | T | G | G | var/var |

AHSG | HGMD | rs4917 | CM052829 | chr3:187820407 | T | C | M | T | C | C | var/var |

AHSG | HGMD | rs4918 | CM052828 | chr3:187821076 | G | C | S | T | C | C | var/var |

ALOX12 | HGMD | rs1126667 | CM062424 | chr17:6843484 | A | G | Q | R | A | G | ref/var |

APOB | HGMD | rs533617 | CM980092 | chr2:21087477 | T | C | H | R | T | C | ref/var |

+ 155 MoreCourtesy of Omicia, Inc. and Illumina

Lower Back Pain:DED: 3 Variants in gene CILP

• CILP is the gene for cartilage intermediate layer protein, OMIM 603489

• DED is Homozygous for 1184C allele (395Thr allele) (OMIM allele .0001)

• DED -- Herniated Disc, 1997

Courtesy of Omicia, Inc.

Novelty-Seeking Behavior2 Variants in gene DRD3

• DRD3 is one of the genes for dopamine receptors, OMIM 126451

• Heterozygous (A1/A2) for Ser9Gly allele (OMIM allele .0001)

• Associated with significantly higher novelty-seeking behavior

• (Venter A1/A1; Watson A1/A2)

Courtesy of Omicia, Inc.

Caffeine “Rapid Metabolizer”DED: No Variants in gene CYP1A2

• CYP1A2 is one of the cytochrome P450 enzymes, related to drug metabolism

• Homozygous for the reference, meaning a “rapid” metabolizer of caffeine => no additional MI risk from coffee drinking

Courtesy of Omicia, Inc.

MYOCARDIAL INFARCTION

At risk allele David’s genotype

David’s OR PAR Het OR

Hom OR

Location

Rs10757278G

G - G 1.64 (general)

2.02 (early onset)

21% (general) 31%

early

1.26 1.64 9p21

At risk allele

HerbertDuncan(Father)

Patricia Duncan(Mother)

DanielleDuncan

(Daughter)

DonaldDuncan

(Brother)

rs10757278G

AG AG AG AG

Family Results

Courtesy of deCode Genetics

MI “Gene”: 3 Generations of Duncan’s

Father Mother A-G A-G

David Brother G-G A-G

Daughter A-G

Ancestral DNA - Y Chromosome

No 12 Marker Y-DNA Matches FoundGenetic Distance - 1

Name E-mailMr. Bobby Royce Henry (Y67) JHHenry99@…Alan C. Duncan (Y37) idlelane@…Wallace T. Duncan (Y25) WDuncan321@…

25 Marker Matches (6)Genetic Distance - 1

Name E-mailAlan C. Duncan (Y37) idlelane@…Wallace T. Duncan WDuncan321@…Daniel Earl Duncan (Y37) nyfromca@…

Courtesy of Family Tree

Genes: Issues

Population data not always relevant to individuals

SNPs are not sequencing

Shifting probabilities

Most genes unvalidated and unregulated

Potential for confusion

ENVIRONMENTENVIRONMENT

Tested: 320

Detected: 165

Cost: $15,000

My Chemical

Report Card

What’s Inside David

Total Tested: 320Detected: 165

Higher than Mean: 1550

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350

BisphenolMetalsPhalatesPFOsDioxinsPesticidesBDEsPCBsTOTALSResults

My life with chemicals…

Childhood in Kansas

“The groundwater, soil, and leachate are contaminated with volatile organic compounds (VOCs), pesticides, polychlorinated biphenyls (PCBs), polycyclic aromomatic hydrocarbons (PAHs), and heavy metals from former waste disposal activities…”

-- EPA Report on Doepke Superfund Site

Pesticides

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PesticidesDavid's Results 2.42 2.47 5.11 10.57 0.326 10.5 0.034 0.159 0.0845 12.1 3.67 16.7 1.75 256 3.58 2.26

CDC Mean <LOD <LOD <LOD <LOD <LOD <LOD <LOD <LOD <LOD 11.1 N/A 17 N/A 295 <LOD <LOD

CDC 95th % 21.8 <LOD 20.3 <LOD <LOD 43.3 <LOD <LOD <LOD 49.7 78.3 <LOD <LOD 26.5 57.1

Heptachlor-

Epoxid

alpha-E<LODosulph

Dieldrin HCB

alpha-HCH

beta-HCH

gamma-HCH ALDRIN

CL8-STYRE

NE

OXYCHLORDA

NE

c-CHLORDANE

t-NONACHLOR

c-NONACHLOR

p,p-DDE

p,p-DDT MIREX

Phthalates

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140

DED results 35 53.9

CDC Mean 17.7 15.6

CDC 95th % 95.2 122

mBuP mBzP

Dioxin-Like PCBs

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600

DED Results 0.815 523 4.15 0.992 5.08 19.2 5.12 0.761 0.387

CDC Mean LOD LOD LOD LOD LOD 22.7 LOD LOD LOD

CDC 95th % LOD LOD 32.6 LOD 44.6 108 18.2 LOD LOD

Dioxin-Like

PCBs

PCB-28

PCB-66

PCB-74

PCB-105

PCB-118

PCB-126

PCB-156

PCB-167

PCB-189

PBDEs

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DED results 249 40.5 15.6 22.4

CA Study 14.1 3.1 3.4

Sweden 2.1

TX 8

PBDE-47 (Penta)

PBDE-99 (Octa)

PBDE-153PBDE-209

(Deca)

Methyl Mercury LevelTest #1:

5 ppm

Safe Level 10 ppm or less

CoalBurned for electricityReleased into air

Settles over oceanPlankton

Little FishBigger FishHuge FishHumans

Methyl Mercury LevelTest #2:

12 ppm

Safe Level 10 ppm or less

www.ctd.mdibl.org

Genes + Chemicals + Disease

COMPARATIVE TOXICOGENOMIC DATABASE -- CTD

Gene-Environment Interaction

DED Genes that provide protection from:

Mercury: GTSP1(Broberg, et. al, Archives of Environmental Health )

DDT: ABCB1, LDLR

PBDE-47 (Flame Retardant): CYP1A

Data courtesy of Carolyn Mattingly, Mount Desert Island Laboratory, Maine

Environment: Issues

No respect vis-à-vis genetics

Most work done on animals

Budgets small (but growing)

Potentially disruptive to business and regulations

BRAINBRAIN

QuickTime™ and aH.264 decompressor

are needed to see this picture.

fMRI

EEG, TMS

Alzheimer’s Disease?

Structure Volume (cm^3) % of ICV (Normative Range) % vs. Normative Range

Hippocampus 7.07 0.42 (0.37-0.50) 27

Lateral Ventricles 32.80 1.94 (-0.59-3.04) 88

Temporal Horn of LV 2.12 0.13 (0.00-0.18) 92

Courtesy of James Brewer, UCSD

Quantifying Brain Volumes

cue stimulicue stimuli delaydelay responsresponsee

+Remember FacesRemember Faces

Ignore ScenesIgnore Scenes

1 sec1 sec 1 sec1 sec 1 sec1 sec 1 sec1 sec 8 sec8 sec 1 sec1 sec

+Remember ScenesRemember Scenes

Ignore FacesIgnore Faces

Passively ViewPassively View +

Working memory task

• Equivalent perceptual, bottom-up information.• Equivalent perceptual, bottom-up information.• Differences in activity mediated by top-down signals.• Differences in activity mediated by top-down signals.

Top-down modulation in visual processing

DED Brain

Courtesy of Adam Gazzaley, UCSF

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BOLD signal

Remember Remember ScenesScenes

IgnoreIgnoreScenesScenes

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PassivePassiveViewView

Younger (19-30 y.o.)Younger (19-30 y.o.)Younger (19-30 y.o.)Younger (19-30 y.o.) Older (60-77 y.o.) Older (60-77 y.o.) Older (60-77 y.o.) Older (60-77 y.o.)

Gazzaley, A. Gazzaley, A. et al.et al. Nature Neuroscience Nature Neuroscience (2005)(2005)

Remember Remember ScenesScenes

IgnoreIgnoreScenesScenes

PassivePassiveViewView

Remember Remember ScenesScenes

IgnoreIgnoreScenesScenes

PassivePassiveViewView

David Duncan (age= 48 y.o.)David Duncan (age= 48 y.o.)David Duncan (age= 48 y.o.)David Duncan (age= 48 y.o.)

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BOLD signal

Courtesy of Adam Gazzaley, UCSF

Face MemoryFace Memory

Response TimeResponse TimeResponse TimeResponse Time

fMRI Working Memory fMRI Working Memory PerformancePerformance

AccuracyAccuracyAccuracyAccuracy

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Scene MemoryScene Memory

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Face MemoryFace Memory Scene MemoryScene Memory

YoungerDDOlder

Electroencephalography (EEG)

Event-Related Potentials (ERPs) Spectral

EEG data: P1 amplitude

Attend FacesPassively View FacesIgnore Faces

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P9-Avg SM-FacePV_Face

RememberPassiveIgnore

RememberPassiveIgnore

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Younger Older

EEG data: P1 amplitude

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P1 amplitude

David Duncan

Other Brain Tests

Fear AnxietyImpulsivenessRiskGreedAltruismPoliticsDiseaseMore

Brain: Issues

Not relevant to individuals

Lack of data - small groups tested

Very early days

BODYBODY

(Note: The following information (the Entelos Model of the “Virtual David”) is being revised and may not be accurate

in its current form -- DED)

Test Data

questionnaire

age, gender

diabetes

blood sample

blood pressure

standard lipid panel

lipoprotein particle size distribution

inflammatory markers

glucose metabolism markers

ultrasound carotid IMT

CT scan coronary calcium score

buccal swab genetic analysis

RiskAssessment

Recommendation

Framingham Risk Score ATP3 Treatment Guidelines

scientific literature on markers and associated

risk

no recommendation

qualitative assessment; no outcomes studies

population associated risk

David

geneticmarkers

biomarkers

imaging

Heart Project: Entelos

•2 types of imaging

•Carotid IMT thickness

•Ultrasound

•Max thickness:

•Min thickness:

•Physician assessment:

•Heartscan coronary artery screen

•Low-dose CT

•Below 25th percentile for age group

MYOCARDIAL INFARCTION*

-21% of the population is homozygous for the variant-Study included 4,587 cases and 12,767 controls-Variant close to tumor suppressor genes p15 and p16

At risk alleleDavid’s

genotypeDavid’s OR PAR Het OR Hom OR Location

rs10757278 G G - G 1.64(genotype OR)

21% (general)

31% (early onset)1.26 1.64 9p21

OR is compared to non-carriers

PAR = population attributable risk

OR = odds ratio*Helgadottir et al. Science 2007

Cholesterol MetabolismCholesterol Metabolism

AtherogenesisAtherogenesisCell Population Lifecycles andCell Population Lifecycles and

Lipid ProcessingLipid Processing

AtherogenesisAtherogenesisInflammatory NetworkInflammatory Network

PlaquePlaqueStabiliStabili

tyty

QuickTime™ and aH.264 decompressor

are needed to see this picture.

Virtual Population

David’sVirtual Human Profile

Statistical mirror for ARIC population study

and deCODE Genetics analysis of rs10757278

David David relative to ARIC ARIC Virtual Population

low high range closer bound mean SD mean SD

TC mg/dl 209 231 50-90th 50th 207 39.5 210.65 41.02

TG mg/dl 98.8 109.2 10-50th 50th 144.8 94.6 153.08 89.32

LDL-C mg/dl 127.3 140.7 10-50th 50th 136 36.4 133.64 34.92

HDL-C mg/dl 61.75 68.25 95-100th 95th 43.1 12.4 42.07 11.9

IMT microns 590 650 50th 75th* 465 110 493.21 117.18

*Howard, Stroke 1993

rs10757278 ARIC fraction Virtual Population fraction

homo LR 0.25 0.25

hetero 0.5 0.5

homo HR 0.25 0.25

homo LR w/ events 0.20 0.2

hetero w/ events 0.252 0.252

homo HR w/ events 0.328 0.328

1423 Virtual Humans

53 Virtual Davids

ARIC: Atherosclerosis Risk in Communities45 to 64 year-old members from four US communities:•Forsyth County, NC•Selected Minneapolis suburbs, MN•Washington County, MD•Jackson, MS

15,792 patients in overall population (~5000 white males for David’s analysis)

Virtual David

Average weight gain*

No weight gain

Average weight gain + statin

Average weight gain + cholesterol re-uptake inhibition

Severe weight gain**

Severe weight gain + statin

*Average weight gain - 1 pound/year**Severe weight gain - 5 pounds/year

Years to Event

Cum

ula

tive P

rob

ab

ility

rs10757278 Homozygous High-Risk

Virtual David

Years to Event

Cum

ula

tive P

rob

ab

ility

rs10757278 Homozygous High-Risk

Virtual David

Years to Event

Cum

ula

tive P

rob

ab

ility

rs10757278 Homozygous Low-Risk

Virtual David

David

geneticmarkers

biomarkers

imaging

What should I do?What should I do?

Therapies

Lifestyle

Genetics Physiology Disease

What should I do?What should I do?

Body: Issues

Bioinformatics is ready

Need pipeline to collect data

Expensive (for now)

It might work: true predictive models feel like Gattaca

Conclusions / Recommendations from the Guinea-Pig

Information Overload

Urgent focus on Individuals

Education of Health Care Providers

Educate Public

Privacy Laws

Regulation -- Efficacy and Safety

The Experimental Man Project

Coming Soon:

Website:

Wiki-Style “Virtual Man”

at the Center for Life Science Policy

UC Berkeley

www.experimentalman.com

David Ewing Duncan, 2007

Still Looking for Help in:

More Genes

More Brain Scans

Microbial Study

Cell Studies

Thanks to:

Josh Adler, MD

Judy Illes

Adam Gazzaley Lab

James Brewster Lab

Eric Wasserman Lab

Martin Reese and Omicia, Inc.

Entelos, Inc.

deCode Genetics

Illumnia, Inc.

Axyss Biosystems

Family Tree

Environmental Working Group

National Geographic

Wired

John Wiley and Sons

UCSF, UC Berkeley, Stanford University, Harvard Medical School

and many, many others who have contributed their time and resources;

and special thanks to my family

Thank you…

My Website:

www.davidewingduncan.com

David Ewing Duncan, 2007