Shrinking cost of your genome

Million-fold in 6 years

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What does $0 to the consumer mean?

2001 Wikipedia1998 Search, Maps, Translation ..

Web 2.0, Crowd-sourcing

But these new technologies (cell phone, fax, PC) are only as good as their communities.

The Personal Genome: Do I want to know? 

1. Expensive2. Discriminative3. Worthless

Genetic Information Nondiscrimination Act of 2008

(GINA)

Employment & health insurance

Destigmatization vs enhanced hiding(addressing causes vs symptoms)

•Ethnicity•Sexuality GLBT •Cancer•Facebook.com•PatientsLikeMe.com

- HIV-AIDS- Neurodegenerative Disorders - Psychiatric Meds

DNA Explorer, $80 (Ages 10 and up)

Genographic $99

DIY Bio

23andme $399

Newborns are tested for up to 40 traits (e.g. PKU)

1526 Highly Predictable & actionable gene tests (not SNP chips)

As with security/insurance purchases, we are all at risk, even though we don’t expect to see direct payback.

The Personal Genome: Do I want to know, if there will be no medical action?

• 50% to 75% get good news and for the rest:

• Planning – family, geography

• Research activism

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Individually rare collectively common: Breast cancer

deCODEme: “does not include the high-risk but rare BRCA1 and BRCA2 breast cancer risk variants”. Navigenics: “Mutations in BRCA1 or BRCA2 are less common in the population and are only present in approximately 5 – 10% of families with breast and ovarian cancer.”23andme: “Hundreds of cancer-associated BRCA1 and BRCA2 mutations have been documented, but three specific BRCA mutations are worthy of note because they are responsible for a substantial fraction of hereditary breast cancers and ovarian cancers among women with Ashkenazi Jewish ancestry”.

1M vs 3G

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Valuable Personal Genome Sequences

1464 genes are highly predictive & medically actionable (inherited & cancer) at ~$2K per gene. **Very few of these are on DTC SNP chips.** Why?PKU, Tay Sachs, Cystic Fibrosis, BRCA1/2, etc.

Pharmacogenomic drug/allele combinations:Herceptin, Iressa, ..

Also: Ancestry, Forensics, Social Networking, Education, Research

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snp.med.harvard.edu

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Anonymity vs Open-access?

Trends in laws to make data public (not just at elite institutions): e.g. H.R. 2764, SEC. 218. 26-Dec-07 open-access publishing for all NIH-funded research.

(12) Identify individual case/control status from pooled SNP data Homer et al PLoS Genetics 2008 as this became known, NCBI pulled dbGAP data

(11) Re-identification after “de-identification” using public data. Group Insurance list of birth date, gender, zip code sufficient to re-identify medical records of Governor Weld & family via voter-registration records (1998)

Self identification trend (10) Unapproved self-identification. e.g. Celera IRB. (Kennedy Science. 2002) (9) Obtaining data about oneself via FOIA or sympathetic researchers. (8) DNA data CODIS data in the public domain. even if acquitted

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Anonymity vs Open-access?

Accessing “Secure data”(7) Laptop loss. 26 million Veterans' medical records, SSN & disabilities stolen Jun 2006. (6) Hacking. A hacker gained access to confidential medical info at the U.

Washington Medical Center -- 4000 files (names, conditions, etc, 2000)(5) Combination of surnames from genotype with geographical info An

anonymous sperm donor traced on the internet 2005 by his 15 year old son who used his own Y chromosome data.

(4) Identification by phenotype. If CT or MR imaging data is part of a study, one could reconstruct a person’s appearance . Even blood chemistry can be identifying in some cases.

(3) Inferring phenotype from genotype Markers for eye, skin, and hair color, height, weight, geographical features, dysmorphologies, etc. are known & the list is growing.

(2) “Abandoned DNA bearing samples (e.g. hair, dandruff, hand-prints, etc.) (1) Government subpoena. False positive IDs and/or family coercion

index

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Who can contribute to cures & prevention?

Huntington's Nancy Wexler (psychologist)

Adrenoleukodystrophy

Odone (World Bank)

Parkinson’sBrin family

Hugh Rienhoff, (MD)MyDaughtersDNA.org

ALS Jamie Heywood (engineer)PatientsLikeMe.com

Motivating, donating, raising consciousness

LRRK2 G2019S

HFE Aull(engineer)

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Genesenvironmentstraits, cells1) First & only open access data 2) Avoid over-promising on de-identification 3) 100% on Exam to assure informed consent (*Educate pre-consent rather than post-discovery*)4) Low cost whole genome sequences5) Multiple-traits: images, stem cells, etc.6) IRB approval for 100,000 diverse volunteers 15,000 since May 2009

0431

1070

1660

1677

1687

1833

1846

1731

1730 

1781 501(c)(3)

Generic Health Advice

•Exercise

•Drink your milk

•Eat your beans

• & your grains

• & your iron

•Get more rest

UNLESS …

•Exercise HCM

•Drink your milk MCM6

•Eat your beans G6PD

• & your grains HLA-DQ2

• & your iron HFE

•Get more rest HLA-DR2

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Diagnostics Systems Biology Challenge

TRAITS(Phenome)

Genome6 Gbp

3M Alleles

NOT going from ONLY Genome Sequence to Prediction

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PersonalGenomes.orgInherited, Somatic, Environmental Genomics

VDJ-ome

TRAITS(Phenome)

Personal stem-cellsepigenome (RNA,mC)

PERSONAL GENOME

6 Gbp3M alleles

One in a life-time genome + yearly ( to daily) tests

Public Health Bio-weathermap.org : Allergens, Microbes, Viruses

Microbiome~5 new non-synonymousAlleles per generation

Even far from hospitals & farms

GautamDantas

MortenSommer

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Even far from hospitals & farmsare multi-drug resistant microbes

Researchers Find Bacteria That Devour Antibiotics

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Microbiome vs VDJ-ome

Microbe tests: Detect Drug resistance spectrumEarlier warning (e.g. meningitis)

Immune tests: Focus on response to exposureLonger times to detect exposure (e.g. HIV, TB)

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Microbiomes: What limits diagnostics

-Standard of practice: skip diagnostics; guess at pathogen & antibiotics-If diagnostic is used typically a fingerprint rather than cauastive sequences.-Ideally targeted sequencing of pathogenicity and resistance – and broad community updating mechanism.- Assay 25 microliters or 6 liters?

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Vaccination VDJ-ome

HMS/MIT: Francois Vigneault, Uri Laserson, Erez Lieberman-Aiden, George ChurchRoche: Michael Egholm, Birgitte Simen

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Time Series Vaccine ExperimentTracking human dynamic response to vaccination to 11 strains:

Hepatitis A+B, Flu A/Brisbane/59/2007 (H1N1)-like, 10/2007 (H3N2)-like, B/Florida/4/2006-like virus

Polio, Yellow fever

Meningococcus

Typhoid, Tetanus

Diptheria, Pertussis

Collect samples at

-14d, 0d,

+1d, +3d,

+7d, +14d,

+21d, +28d

V and J usage – CDR3 size distribution

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SR1+SR2+TR1

IMGT/LIGM

FV

Self Organizing Map (SOM) clustering

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27

Isotypes

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Query: FXQ8H8O01DXEUI rank=0514859 x=1493.0 y=2520.0 length=408 Target: I55621 | anti-hepatitis B virus (HBV) surface antigen (HBsAg) (human) Model: affine:local:dna2dna Raw score: 1740 Query range: 8 -> 398 Target range: 27 -> 423 9 : CGCGTTGCTCTTTTAAGAGGTGTCCAGTGTCAGGTGCAGCTGGTGGAGTCTGGGGGAGGCGTGG : 72 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| 28 : CTCGTTGCTCTTTTAAGAGGTGTCCAGTGTCAGGTGCAGCTGGTGGAGTCTGGGGGAGGCGTGG : 91 73 : TCCAGCCTGGGAGGTCCCTGAGACTCTCCTGTGCAGCCTCTGGATTCACCTTCAGTAGCTATGG : 136 |||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ||||| 92 : TCCAGCCTGGGAGGTCCCTGAGACTCTCCTGTGCAGCCTCTGGATTCACCTTCAGTAGGTATGG : 155 137 : CATGCACTGGGTCCGCCAGGCTCCAGGCAAGGGGCTGGAGTGGGTGGCAGTTATATCATATGAT : 200 ||||||||||||||||||||||||||||||||||||||||||||||||||| |||||||||||| 156 : CATGCACTGGGTCCGCCAGGCTCCAGGCAAGGGGCTGGAGTGGGTGGCAGTGATATCATATGAT : 219 201 : GGAAGTAATAAATACTATGCAGACTCCGTGAAGGGCCGATTCACCATCTCCAGAGACAATTCCA : 264 ||||||||||||| ||||||||||||||||||||||||||||||||||||||||||||||||| 220 : GGAAGTAATAAATGGTATGCAGACTCCGTGAAGGGCCGATTCACCATCTCCAGAGACAATTCCA : 283 265 : AGAACACGCTGTATCTGCAAATGAACAGCCTGAGAGCTGAGGACACGGCTGTGTATTACTGTGC : 328 ||||||| |||| |||||||||| ||||||||||||||| |||||||| ||| ||||||||||| 284 : AGAACACTCTGTTTCTGCAAATGCACAGCCTGAGAGCTGCGGACACGGGTGTATATTACTGTGC : 347 329 : GAGAGA---ACTT-ACTATGGTTCGGGGAGTTCCTG--ACTACTGGGGCCAGGGAACCCTGGTC : 386 || ||| |||| ||| ||||||| |||| || | ||||||||| |||||||||||||||| 348 : GAAAGATCAACTTTACTTTGGTTCGCAGAGTCCCGGGCACTACTGGGTCCAGGGAACCCTGGTC : 411 387 : ACCGTCTCCTCA : 398 |||||||||||| 412 : ACCGTCTCCTCA : 423

aln_summary: FXQ8H8O01DXEUI 408 8 398 + I55621 423 27 423 + 1740 390 372 95.38

UL

2929

21-Jan-2010 Emphasis on Protein/cell function, Integration & Interpretation

-Personal Genome issues: cost, unfriendly databases, consent, multiple genes + environmental factors -Personal stem cells 3 uses: Diagnostic/inheritance, therapeutic cells, test pharmaceuticals -Microbiomes: What limits diagnostics -VDJ-omes: How to generalize immune diagnostics

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PGP skin to stem cells to ...

Lee J, Park IH, Gao Y, Li JB, Li Z, Daley G, Zhang K, Church GM (2009) A Robust Approach to Identifying Tissue-specific Gene Expression Regulatory Variants Using Personalized Human Induced Pluripotent Stem Cells. PLoS Genetics Nov 2009

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PGP iPSC allele specific

expression

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iPSC-derived hepatic proteins & activity

Generation of Functional Human Hepatic Endodermfrom Human Induced Pluripotent Stem CellsGareth et al Hepatology. 2010 Jan;51:329-35.

The Personal Genome: Do I want to know? 

1. Expensive: “If you think education is expensive .. try ignorance”

2. Discriminative: Destigmatize, pass laws, educate

3. Worthless: If we share, .. priceless

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Four open-source resources

snp.med.harvard.edu (Genes + Environment = Trait prediction)

Polonator.org