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Swan, M. Multigenic Condition Risk Assessment in Direct-to-Consumer Genomic Services. Genet. Med. 2010, May;12(5):279-88.
Swan, M. Translational antiaging research. Rejuvenation Res. 2010, Feb;13(1):115-7.
Swan, M. Engineering Life into Technology: the Application of Complexity Theory to a Potential Phase Transition of Intelligence. Symmetry 2010, 2, 150:183.
Swan, M. Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int. J. Environ. Res. Public Health 2009, 2, 492-525.
1Conditions, genes, variants, underlying research references, and methodology white paper(s) available on public website
Which service to buy?
*Physician prescription required
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Consumer genomics: interpretation variance
Source: www.DIYgenomics.org and Swan, M. Multigenic Condition Risk Assessment in Direct-to-Consumer Genomic Services. Genet. Med. 2010, May;12(5):279-88. Private data upload: Marat Nepomnyashy
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Open-source mobile apps (5,000+ downloads)
Health condition, drug response, athletic performance
23andMe data upload
Android
iPhone
Android development: Michael Kolb, Lawrence S. Wong, Laura Klemme, Melanie SwaniPhone development: Ted Odet, Greg Smith, Laura Klemme, Melanie Swan
“genomics”4,000+ downloads
“genomics”1,000+ downloads
T T T
T T T
T C C
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Citizen science health landscape
Source: Extended from Swan, M. Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int. J. Environ. Res. Public Health 2009, 2, 492-525.
Health collaboration communities
Health social networks
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Lifecycle of a health condition
Pre-clinical (80%) Clinical (20%)
Preventive medicineLong-tail medicine
Self-trackingWellness profiling
Health community collaborationApplied healthspan engineering
Traditional medicineDisease treatmentMedical expertise
EmergencyExceptions
Time
# conditionsbecoming
clinical
Goal: decrease in clinical conditions over time
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Genome hacking philosophy
Goal: preventive medicine Realize preventive medicine by establishing baseline markers
of wellness and pre-clinical interventions
Generalized hypothesis One or more polymorphisms may result in out-of-bounds
baseline levels of phenotypic markers. These levels may be improved through personalized intervention.
Source: http://diygenomics.pbworks.com/MTHFR
Genotype Phenotype Intervention Outcome+ + =
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Vitamin B deficiency / MTHFR mutation
Do common mutations in the MTHFR gene prevent vitamin B from working correctly?
Test whether 2 variations in the MTHFR gene keep vitamin B9 (folic acid) from being metabolized into its active form (folate) rs1801133/C677T rs1801131/A1298C
Without this form of vitamin B, homocysteine may accumulate (risk of cardiovascular disease, etc.)
50% or more of the population may have some form of MTHFR polymorphism
Source: http://diygenomics.pbworks.com/MTHFR
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Homocysteine metabolism pathway
Source: Swan, M., Hathaway, K., Hogg, C., McCauley, R., Vollrath, A. Citizen science genomics as a model for crowdsourced preventive medicine research. J Participat Med. 2010 Dec 23; 2:e20.
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Vitamin B / MTHFR study protocol
1. Genotype
MTHFR gene SNPs:
rs1801133 (A/G)
rs1801131 (A/G)
2. Phenotype
Blood tests:
B-12 and
Homocysteine
3. Intervention
(2 week periods)
1. B-complex
2. L-methylfolate
3. B-complex + L-methylfolate
Investigate genotype-phenotype linkage and apply interventions to improve phenotypic outcomes
Protocol confirmed with two separate experts in the field
Source: http://diygenomics.pbworks.com/MTHFR
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Vitamin B / MTHFR pilot study results
Drug store vitamin (Centrum) reduced homocysteine levels for 6/7 participants
Blood Test #
2. Homocysteine levels
DIYgenomics MTHFR Vitamin B deficiency study1
1. Genotype profiles
Baseline LMF
Source: Swan, M., Hathaway, K., Hogg, C., McCauley, R., Vollrath, A. Citizen science genomics as a model for crowdsourced preventive medicine research. J Participat Med. 2010 Dec 23; 2:e20.
1Results are not statistically significant and are intended as a pilot demonstration of citizen science genomic studies
Baseline+ LMF
Centrum
Homocysteine umol/l
Centrum
LMF = L-methylfolate
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Personal health collaboration studies
More information: www.DIYgenomics.org www.DIYgenomics.org/DIYgenomics_poster.ppt
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Agenda
Citizen science progress to date
Scaling citizen science
Grand vision next steps
Image credit: http://www.gettyimages.com
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Scaling citizen science
Engaging participants and building trust Innovating the Institutional Review Board Accessing blood tests 2.0 Developing a philosophy of epistemology of citizen
science
Image credit: http://slobodkina.com
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Engaging personal health collaborators
Participation must be fun and easy
Relevant value proposition to target market
Nomenclature framing: enhancement, optimization
Crowdsourcing the value chain: data, questions, financing, analysis
Source: Swan, M. Review of cancer risk prediction in direct-to-consumer genomic services. (poster) Canary Foundation Early Detection Symposium, May 25-27, 2010, Stanford University, Stanford CA.
Image credit: http://www.xianet.net
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Wellness profiling: immune system
Immune system genomic wellness profiling Immune response: T-cell activation
CTLA4, CD226, CD86, IL3
Source: DIYgenomics
Alleles 23andMe alleles
Gene RSID Poss Unf Fav Poss Fav Ex p-value OR Case Ctrl Citation CTLA4 rs231775 A/G A G AG G AA 0.007 0.642 172 145 Duan 2010 CTLA4 rs5742909 C/T C T CT T CC 0.098 0.67 172 145 Duan 2010 CTLA4 rs733618 C/T C T CT T TT 0.041 4.62 269 395 DallaCosta 2010 CD226 rs763361 C/T T C CT C CC 0.000 1.22 1,990 1,642 Dieudé 2010 CD86 rs1129055 A/G G A AG A GG 0.006 0.51 269 395 DallaCosta 2010 IL3 rs181781 A/G A G AG G GG 0.041 0.55 60 270 Lee 2010 IL3 rs2073506 A/G A G CT C CC 0.009 0.32 60 270 Lee 2010 IL3 rs40401 C/T T C CT C CC 0.014 2.18 60 270 Lee 2010
Aging studies need not be longitudinal, current improvements to known biomarkers of aging can be measured Image credit: http://www.gettyimages.com
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Circles of preventive medicine
Individual
2. Preventive CareHealth Social NetworksCitizen Science Studies
Health Advisors
3. Traditional health care system and physicians
1. Automated digital health monitoring
Source: Extended from Swan, M. Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int. J. Environ. Res. Public Health 2009, 2, 492-525.
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Health self-management
Source: Extended from Swan, M. Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int. J. Environ. Res. Public Health 2009, 2, 492-525, Figure 1.