genome-wide association studies and clinical applications
DESCRIPTION
National Human Genome Research Institute. Genome-Wide Association Studies and Clinical Applications. U.S. Department of Health and Human Services National Institutes of Health National Human Genome Research Institute. National Institutes of Health. - PowerPoint PPT PresentationTRANSCRIPT
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Genome-Wide Association Studies and Clinical
ApplicationsNational Human
Genome Research Institute
National Institutes of
Health
U.S. Department of Health and
Human Services
U.S. Department of Health and Human Services
National Institutes of HealthNational Human Genome Research
InstituteTeri A. Manolio, M.D., Ph.D.Director, Office of Population GenomicsSenior Advisor to the Director, NHGRI,
for Population GenomicsMarch 8, 2011
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What do GWA Studies Have To Do with Direct to Consumer Testing?• Among first studies identifying several
easily measured variants associated with risk of common, complex diseases– Common, not Mendelian– Followed long barren period– This actually works!
• Results more rigorously validated than some prior genetic findings
• Findings more rapidly incorporated into multi-gene or genome-wide panels
• Accelerating pace of discovery
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www.genome.gov/gwastudies/NHGRI GWA Catalogwww.genome.gov/GWAStudies
904 Associations at p < 5 x 10-8
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Hunter DJ and Kraft P, N Engl J Med 2007; 357:436-39.
“There have been few, if any, similar bursts of discovery in the history of medical research…”
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What is a Genome-Wide Association Study?
• Method for interrogating all 10 million common (MAF > 5%) variable points in human genome
• Variation inherited in groups, or blocks, so not all 10 million points have to be tested
• Blocks are shorter (so need to test more points) the less closely people are related
• Allows studies in unrelated persons, assuming 5,000 – 10,000 base pair lengths in common (500,000 – 1,000,000 markers @ $450)
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DNA on Chromosome 7GAAATAATTAATGTTTTCCTTCCTTCTCCTATTTTGTCCTTTACTTCAATTTATTTATTTATTATTAATATTATTATTTTTTGAGACGGAGTTTC/ACTCTTGTTGCCAACCTGGAGTGCAGTGGCGTGATCTCAGCTCACTGCACACTCCGCTTTCCTGGTTTCAAGCGATTCTCCTGCCTCAGCCTCCTGAGTAGCTGGGACTACAGTCACACACCACCACGCCCGGCTAATTTTTGTATTTTTAGTAGAGTTGGGGTTTCACCATGTTGGCCAGACTGGTCTCGAACTCCTGACCTTGTGATCCGCCAGCCTCTGCCTCCCAAAGAGCTGGGATTACAGGCGTGAGCCACCGCGCTCGGCCCTTTGCATCAATTTCTACAGCTTGTTTTCTTTGCCTGGACTTTACAAGTCTTACCTTGTTCTGCC/TTCAGATATTTGTGTGGTCTCATTCTGGTGTGCCAGTAGCTAAAAATCCATGATTTGCTCTCATCCCACTCCTGTTGTTCATCTCCTCTTATCTGGGGTCACA/CTATCTCTTCGTGATTGCATTCTGATCCCCAGTACTTAGCATGTGCGTAACAACTCTGCCTCTGCTTTCCCAGGCTGTTGATGGGGTGCTGTTCATGCCTCAGAAAAATGCATTGTAAGTTAAATTATTAAAGATTTTAAATATAGGAAAAAAGTAAGCAAACATAAGGAACAAAAAGGAAAGAACATGTATTCTAATCCATTATTTATTATACAATTAAGAAATTTGGAAACTTTAGATTACACTGCTTTTAGAGATGGAGATGTAGTAAGTCTTTTACTCTTTACAAAATACATGTGTTAGCAATTTTGGGAAGAATAGTAACTCACCCGAACAGTG/TAATGTGAATATGTCACTTACTAGAGGAAAGAAGGCACTTGAAAAACATCTCTAAACCGTATAAAAACAATTACATCATAATGATGAAAACCCAAGGAATTTTTTTAGAAAACATTACCAGGGCTAATAACAAAGTAGAGCCACATGTCATTTATCTTCCCTTTGTGTCTGTGTGAGAATTCTAGAGTTATATTTGTACATAGCATGGAAAAATGAGAGGCTAGTTTATCAACTAGTTCATTTTTAAAAGTCTAACACATCCTAGGTATAGGTGAACTGTCCTCCTGCCAATGTATTGCACATTTGTGCCCAGATCCAGCATAGGGTATGTTTGCCATTTACAAACGTTTATGTCTTAAGAGAGGAAATATGAAGAGCAAAACAGTGCATGCTGGAGAGAGAAAGCTGATACAAATATAAAT/GAAACAATAATTGGAAAAATTGAGAAACTACTCATTTTCTAAATTACTCATGTATTTTCCTAGAATTTAAGTCTTTTAATTTTTGATAAATCCCAATGTGAGACAAGATAAGTATTAGTGATGGTATGAGTAATTAATATCTGTTATATAATATTCATTTTCATAGTGGAAGAAATAAAATAAAGGTTGTGATGATTGTTGATTATTTTTTCTAGAGGGGTTGTCAGGGAAAGAAATTGCTTTTT
SNPs 1 / 300 bases
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Linkage Disequilibrium Plot of NINJ2 Region Associated with Total
and Ischemic Stroke
Ikram MA et al., N Engl J Med 2009; 360:1718-28.
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Christensen and Murray, N Engl J Med 2007; 356:1094-97.
Mapping the Relationships Among SNPs
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Boston Provi-dence
New York
Phila-delphi
aBalti-more
Providence 59New York 210 152Philadelphia 320 237 86
Baltimore 430 325 173 87Washington 450 358 206 120 34
Distances Among East Coast Cities
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Boston Provi-dence
New York
Phila-delphi
aBalti-more
Providence 59New York 210 152Philadelphia 320 237 86
Baltimore 430 325 173 87Washington 450 358 206 120 34
Distances Among East Coast Cities
< 100
101-200
201-300
301-400
> 400
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Boston Provi-dence
New York
Phila-delphi
aBalti-more
Providence 59New York 210 152Philadelphia 320 237 86
Baltimore 430 325 173 87Washington 450 358 206 120 34
Distances Among East Coast Cities
< 100
101-200
201-300
301-400
> 400
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Distances Among East Coast Cities
Boston Provi-
dence NewYork Phila-
delphia Balti-more Wash-
ington
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Distances Among East Coast Cities
Boston
Provi-
dence
New York
Phila-delph
iaBalti-more
Wash-
ington
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Christensen and Murray, N Engl J Med 2007; 356:1094-97.
Mapping the Relationships Among SNPs
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One Tag SNP May Serve as Proxy for Many
CAGATCGCTGGATGAATCGCATCTGTAAGCATCGGATTGCTGCATGGATCGCATCTGTAAGCAC
CAGATCGCTGGATGAATCGCATCTGTAAGCATCAGATCGCTGGATGAATCCCATCAGTACGCAT
CGGATTGCTGCATGGATCCCATCAGTACGCATCGGATTGCTGCATGGATCCCATCAGTACGCAC
SNP2↓
SNP3↓
SNP4↓
SNP5↓
SNP6↓
SNP1↓
Block 1 Block 2
SNP7↓
SNP8↓
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One Tag SNP May Serve as Proxy for Many
CAGATCGCTGGATGAATCGCATCTGTAAGCATCGGATTGCTGCATGGATCGCATCTGTAAGCAC
CAGATCGCTGGATGAATCGCATCTGTAAGCATCAGATCGCTGGATGAATCCCATCAGTACGCAT
CGGATTGCTGCATGGATCCCATCAGTACGCATCGGATTGCTGCATGGATCCCATCAGTACGCAC%
SNP2↓
SNP3↓
SNP4↓
SNP5↓
SNP6↓
SNP1↓
Block 1 Block 2
SNP7↓
SNP8↓
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One Tag SNP May Serve as Proxy for Many
CAGATCGCTGGATGAATCGCATCTGTAAGCATCGGATTGCTGCATGGATCGCATCTGTAAGCAC
CAGATCGCTGGATGAATCGCATCTGTAAGCATCAGATCGCTGGATGAATCCCATCAGTACGCAT
CGGATTGCTGCATGGATCCCATCAGTACGCATCGGATTGCTGCATGGATCCCATCAGTACGCAC%
SNP3↓
SNP5↓
SNP6↓
Block 1 Block 2
SNP7↓
SNP8↓
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One Tag SNP May Serve as Proxy for Many
CAGATCGCTGGATGAATCGCATCTGTAAGCATCGGATTGCTGCATGGATCGCATCTGTAAGCAC
CAGATCGCTGGATGAATCGCATCTGTAAGCATCAGATCGCTGGATGAATCCCATCAGTACGCAT
CGGATTGCTGCATGGATCCCATCAGTACGCATCGGATTGCTGCATGGATCCCATCAGTACGCAC%
SNP3↓
SNP6↓
Block 1 Block 2
SNP8↓
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One Tag SNP May Serve as Proxy for Many
GTT 35%CTC 30%GTT 10%GAT 8%CAT 7%CAC 6%
other haplotypes 4%
Block 1 Block 2 FrequencySingleton
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www.hapmap.org
Nature 2005; 437:1299-320.Nature 2007; 449:851-61.
Nature 2010; 467:52-8.Nature 2010; 467:1061-73.
www.1000genomes.org
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A HapMap for More Efficient Association Studies: Goals
• Use just the density of SNPs needed to find associations between SNPs and diseases
• Do not miss chromosomal regions with disease association
• Produce a tool to assist in finding genes affecting health and disease
• Use more SNPs for complete genome coverage of populations of recent African ancestry populations due to shorter LD
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Progress in Genotyping Technology
1 10 102 103 104 105 106
No. of SNPs
Cost
per
gen
otyp
e (C
ents
, USD
)10
1
102
ABITaqMan
ABISNPlex
IlluminaGolden Gate
IlluminaInfinium/Sentrix Affymetr
ix100K/500K
Perlegen
Affymetrix
MegAllele
2001 2005
Affymetrix
10K
Courtesy S. Chanock, NCI
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0
300
600
900
1200
1500
1800
Jul-05 Oct-05 Jan-06 Apr-06 Jul-06 Oct-06
Affymetrix 500K
Illumina 317K
Illumina 550K Illumina
650Y
Continued Progress in Genotyping Technology
Courtesy S. Gabriel, Broad InstituteJuly 2005 Oct 2006
Cost
per
per
son
(USD
)
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Association of Alleles and Genotypes of rs1333049 with Myocardial
InfarctionC
N (%)G
N (%)2
(1df) P-value
Cases 2,132 (55.4)
1,716 (44.6) 55.1 1.2 x 10-
13Controls
2,783 (47.4)
3,089 (52.6)
Allelic Odds Ratio = 1.38
Samani N et al, N Engl J Med 2007; 357:443-53.
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Association of Alleles and Genotypes of rs1333049 with Myocardial
Infarction C
N (%)G
N (%)2
(1df) P-value
Cases 2,132 (55.4)
1,716 (44.6) 55.1 1.2 x 10-
13Controls
2,783 (47.4)
3,089 (52.6)
Allelic Odds Ratio = 1.38CC
N (%)CG
N (%)GG
N (%)2
(2df) P-value
Cases 586 (30.5)
960 (49.9) 378 (19.6)
59.7 1.1 x 10-14Control
s676
(23.0)1,431 (48.7) 829 (28.2)
Heterozygote Odds Ratio = 1.47Homozygote Odds Ratio = 1.90
Samani N et al, N Engl J Med 2007; 357:443-53.
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Klein et al, Science 2005; 308:385-389.
P Values of GWA Scan for Age-Related Macular Degeneration
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GWA Scan of LV Internal Dimensions
Vasan RS et al., JAMA 2009; 302:168-78.
SLC35F1, C6orf204, PLN
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Regional Plot for rs89107 Associated with LV Internal
Dimensions
Vasan RS et al., JAMA 2009; 302:168-78.
red r2 > 0.8orange r2 0.5-0.8yellow r2 0.2-0.5white r2 < 0.2
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Regional Plot for rs10852932 Associated with Aortic Root
Diameter
Vasan RS et al., JAMA 2009; 302:168-78.
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Unique Aspects of GWA Studies• Permit examination of inherited genetic
variability at unprecedented level of resolution
• Permit "agnostic" genome-wide evaluation • Once genome measured, can be related to
any trait• Most robust associations in GWA studies have
not been with genes previously suspected of association with the disease
• Some associations in regions not even known to harbor genes “The chief strength of the new approach also contains its
chief problem: with more than 500,000 comparisons per study, the potential for false positive results is unprecedented.”
Hunter DJ and Kraft P, N Engl J Med 2007; 357:436-39.
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Larson, G. The Complete Far Side. 2003.
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May 1999
J. Hirschhorn and D. Altshuler J Clin Endo Metab 2002
Am J Hum Genet July 2004
Am J Hum Genet July 2004PLoS Biol Sept 2005
Nat Genet July 2006
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Chanock S, Manolio T, et al., Nature 2007; 447:655-60.
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Traits with Published GWA Studies (n = 199, 3/4/11)• Macular Degen.
• Glaucoma• Myopia• Optic Disc Size• Corneal Thickness• Corneal
Dystrophy• Retinal Vessel
Size• Lung Cancer• SCLC Treatment
Rsp.• Prostate Cancer• Breast Cancer• Aromatase Inh.
Rsp.• Mammographic
Dens.• Colorectal Cancer• Bladder Cancer• Neuroblastoma• Melanoma• Basal Cell Cancer• TP53 Cancer
Pred’n• Ac/Ch Lymph.
Leuk.• Asparaginase
Hypersen.• Follicular
Lymphoma• Thyroid Cancer• Myeloprolif. Syn.• Testic. Germ Cell
Ca.• Glioma• Ovarian Cancer• Pancreatic Cancer• Esophageal
Cancer• Nasopharyngeal
Ca• Hepatocellular Ca• Renal Cell Ca• Bleomycin Sens.• MTX
Pharmacokin.• Cleft Palate• Periodontitis• Tooth
Development• Quinine Taste
Sens.• Eosinophilic
Esoph.• Infl. Bowel
Disease
• CSF Protein Levels• Tauopathies • Alzheimer’s Disease• Var. Creutzfeldt-
Jakob• Cognitive Ability• Dyslexia• Memory• Brain Imaging• Brain 5-HTT in psych.• Brain
Cytoarchitecture• Amygdala Activation• Partial Epillepsy• EEG Traits• Hearing, Otosclerosis• Restless Legs Synd.• Essential Tremor • Nicotine Depend.• Alcohol Dependence • Methamphet. Dep.• Heroin Addiction• Coffee Consumption• Pain• Panic Disorder • Conduct Disorder• Neuroticism• Hoarding• Schizophrenia• Schiz. Treatment
Rsp.• Bipolar Disorder• BPD Lithium Rsp.• Depression Trt Rsp.• Suicide Att./Ideation• Extrapyramidal Eff.• Family Chaos• Narcolepsy• ADHD• ADHD Treatment
Rsp.• Personality Traits• Carbamazepine Rsp.• Rheum. Arthritis
• Celiac Disease• Hirschsprung Dis.• Ileal Carcinoid• Biliiubin Levels• Gallstones• 1º Sclerosing
Cholang.• Biliary Atresia• Non-Alc Hepatosteat• Cirrhosis• Drug-Induced Liver Inj• Acetamin. Hepatotox.• Hepatitis C • Hepatitis C Response• Chronic Hepatitis B • ECG Intervals• Coronary Disease• Coronary Spasm• Heart Failure• Atrial Fibrill’n/Flutter• Ventricular
Fibrillation • Resting Heart Rate• Stroke• Intracranial Aneurysm • Carotid Athero. AIDS• Kawasaki Disease• Moyamoya Disease• Hypertension• Anti-Hypertens. Rsp.• Aortic Aneur./PAD • Lipids/Lipoproteins• Warfarin Dosing• Ximelegatran
Adv.Rsp.• Clopidogrel Pltlet.Rsp.• Parkinson Disease• Amyotrophic
Lat.Scler.• Multiple Sclerosis• MS Interferon-β Rsp. • Prog. Supra. Palsy• Neuromyelitis Optica
• RA Anti-TNF Rsp.• Syst. Lupus Eryth.• Juv. Idiop. Arthritis• Ankylosing Spond.• Systemic Sclerosis• Behçet’s Disease• Dupuytren’s Cont.• Osteoarthritis• Osteoporosis• Idiopathic Scoliosis• Paget’s Dis. Bone • Psoriasis • Sarcoidosis• Pulmonary Fibrosis• COPD/Lung Funct.• CF Severity• Asthma• Chr. Rhinosinusitis• Atopy• Stevens-Johnson Syn.• HIV Setpoint/Prog.• HIV Mother/Child • HIV Replication• CD4:CD8 Ratio• Ribavirin Adv. Rsp.• Severe Malaria• Leprosy• Tuberculosis• Meningococcal Dis.• Type 1 Diabetes • Type 2 Diabetes• Diabetic Nephrop. • Metformin Treat.
Rsp.• End-St. Renal Dis.• Kidney Stones• Obesity, BMI, Waist• IR, MetabolicTraits• Adipokine Levels• Anorexia nervosa• Exercise Behavior
• Fetal Growth• Height• Digit Length Ratio• Thyroid Function• Menarche• Menopause/Ov.
Failure• Polycystic Ovary
Syn• Endometriosis• Alopecia• Male Infertility• Erectile
Dysfunction• Hypospadias• High Altitude
Adapt.• Fetal Hemoglobin• Iron Status• Hem/Thromb
Levels• C-Reactive Protein• Adhesion
Molecules• Eosinophil
Numbers• Total IgE Levels• Urate Levels, Gout• Protein Levels• N-Glycan Levels• PSA Levels• Folate Path.
Vitamins• β-Carotene Levels• Vitamin D Levels• Phosphorus Levels• Sphyngolipid
Levels• Recombination
Rate• Telomere Length• Longevity• Radiation
Response• Self-Rated Health• Constitut. Med.
Type• Hair
Color/Morphol.• Pigmentation• Vitiligo• Keloid• Recessive
Diseases
NeuroblastomaGliomaOvarian CancerPrimary Sclerosing CholangitisAmyotrophic Lateral SclerosisProgressive Supranuclear PalsyIdiopathic Pulmonary FibrosisHeightAlopeciaHair ColorUrate LevelsClopidogrel Platelet ResponseStevens-Johnson Syndrome
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NHGRI Catalog of GWA Studies: http://www.genome.gov/gwastudies/
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0 10 20 30 40 50 60
TFBSConservedIntergenic
5' (2kb)miRTS3' UTR5' UTRIntronic
Synonymous
Functional Classification of 465 Trait -Associated SNP (TAS)
Blocks (r2 > 0.9)
TAS Block Random Block
0 10 20 30 40 50 60 Percent Hindorff L et al, PNAS 2009; 106:9362-67.
Non-
Synonymous
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0 10 20 30 40 50 60
TFBSConservedIntergenic
5' (2kb)miRTS3' UTR5' UTRIntronic
Synonymous
Functional Classification of 465 TAS Blocks and Random LD
Blocks
TAS Block Random Block
0 10 20 30 40 50 60 Percent Hindorff L et al, PNAS 2009; 106:9362-67.
Non-
Synonymous *
**
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Odds Ratios of Discrete Associations
0
20
40
60
80
100
120
1.2 1.4 1.6 1.8 2.0 2.2 2.4 3.04.05.06.0 9.013.020.030.0
Odds Ratio (upper inclusive bound)
Num
ber o
f Ass
ocia
tions
3 4 5 6 9 13 20 30
// //
Median = 1.28
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• Over 80% of GWA-identified SNPs and LD SNPs (r2 > 0.9) are intronic or intergenic
• Very few GWA studies have been narrowed to true functional (presumed causal) variants
• Selection bias in genotyped SNPs for excess of missense, common, and European variants
• Most associated odds ratios are < 1.5• Some traits have dozens or even hundred(s) of
associated loci• GWA-defined SNPs explain very little heritability
Discoveries to Date
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Familial Resemblance?
http://en.wikipedia.org/wiki/Image:Kennedy_bros.jpg#file
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Proportion of Familial Risk Explained by GWA Studies to Date
Condition Number of Loci
Percent (%)
ExplainedMeasure
AMD 5 50 Sibling Recurrence Risk
Crohn’s Disease 71 23 Liability
SLE 6 15 Sibling Recurrence Risk
T2DM 40 10 Sibling Recurrence Risk
Height 180 10 Phenotypic Variance
Lipid Levels 95 10 - 12 Phenotypic Variance
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Maher, B. Nature 2008; 456:18-21.
“When scientists opened up the human genome, they expected to find the genetic components of
common traits and diseases. But they were nowhere to be seen...”
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Jakobsdottir J et al, PLoS Genet 2009; e1000337.
Area Under ROC Curve for Predicting AMD
• AUC with 3 variants = 0.79• To correctly classify 74% of cases would
misclassify 31% of controls• At 80% sensitivity, would misclassify > 40%
controls
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What are the limitations of genetic markers in risk assessment for
disease?• Most markers are not deterministic– many
people without the markers will develop disease, and many people with the markers will not
• Most of the genetic risk remains unexplained
• Little or no evidence to date that interventions based on genotype improve outcome
• Genetic markers may provide additional risk information for more aggressive risk management in carriers, but again little evidence
• And yet…
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http://www.avimedi.net/en/stevens-johnson-syndrome-photos.html#photos
Stevens-Johnson Syndrome
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http://www.avimedi.net/en/stevens-johnson-syndrome-photos.html#photos
Stevens-Johnson Syndrome
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Pharmacogenomics J online, 11Jan2011
CAUTION: This patient carries the HLA-B*1502 allele, a known risk factor for carbamazepine-induced SJS in Han Chinese individuals…
Stevens- Johnson Syndrome, HLA-B*1502, and Carbamazepine
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MC Escher, at http://web.ncf.ca/ek867
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Clinical Questions that GWA-Defined Associations May Help
Answer• Can newly-discovered loci teach us
about physiology or classification of disease?
• Can GWA-defined loci be used to develop specific, targeted treatments?
• Can GWA loci help direct treatment selection, dosing, or monitoring for adverse effects?
• Can GWA loci be used to predict disease or indicate more intensive screening?
• Can GWA loci identify those in whom more intensive environmental modification is appropriate?
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Predicting Disease Risk in the Genomic Era
• Pretty much the same as it was before• May be useful in initiating counseling
about non-genetic risk factors• Possibly useful for screening for very high
risk of many conditions at once• Identifying genetic variants influencing
response to drugs may be more immediately useful
• Clinical decision tools currently under development
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Genomic Jargon Break• Mendelian (single gene) vs complex
(many genetic variants and environment)
• SNPs named by rs (reference sequence) numbers, in dbSNP, different “builds”
• Location referred to by chromosomal region “18q12.3”
• Rare vs. common variation• Common: minor allele frequency >
5% • Rare: typically MAF < 1%