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유전체 의학과 미래 의학 최형진 충북대학교 내분비내과

유전체의학과 미래의학 1 유전체의학_공개용

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유전체 의학과 미래 의학

최형진

충북대학교 내분비내과

Genomics/

Biomarker

Big Data/

Medical Informatics Smart Device/

Wearable

Genome Sequencing

Data Science

Quantified Self

Health Avatar

Mobile Health

Machine Learning

미래의학 유전체, 빅데이터, 스마트 의료

최형진

시대변화

Genomics/

Biomarker

Big Data/

Medical Informatics Smart Device/

Wearable

Genome Sequencing

Data Science

Quantified Self

Health Avatar

Mobile Health

Machine Learning

Contents

1. Introduction

2. Genetic Variation and Expression

Analyses

3. Human Genome Project and Beyond

4. Personalized Medicine in Endocrinology

① Common Disease Risk

② Rare Disease Risk

③ Pharmacogenomics

1997

발전한다?

저의 유전자

분석 결과를

반영하여 진료해주세요!! 헠?

Your

estimated

lifetime

risk

$2,000~$3,000

Personal Genome Service

$99

2013.01.29

헬스케어 3.0 시대의 변화 키워드

2011.11.23 헬스케어 3.0: '건강수명' 시대의 도래

주: 선의 굵기는 영향의 강도를 의미

2013.4.25. KBS 9시 뉴스

며칠 전 유전자 검사를 받은 40대 남성입니다.

혈액세포의 DNA 상태를 분석해 앞으로 암에 걸릴 위험이 있는지 여부를 판단할 수 있다고 합니다.

2013.4.25. KBS 9시 뉴스

2013.4.25. KBS 9시 뉴스

60년전 DNA의 구조가 밝혀진 이래 2003년 인간 유전자 지도가 완성됐고, 현재는 어떤 유전자가 어떤 질병을 일으키는지 분석도 80% 정도 끝난 상태입니다.

예를들어 13번 염색체의 BRCA2 유전자에 이상이 생기면 유방암에 걸릴 확률이 높습니다. 또 17번 염색체 유전자는 난소암, 7번 염색체 유전자는 비만을 일으킵니다.

개인별 유전체 분석을 통해 암 발병 예측

및 예방, 치료하는 ‘유전체 기반 맞춤치료’는 전 세계적으로 가장 주목받고 있는 차세대 치료 트랜드. 때문에 국내 주요 대학병원들도 관심을 보이고 각기 ‘맞춤치료’를 주요 전략으로 내세우고 있지만, 삼성서울병원처럼 구체적으로 언제부터 시작하겠다고 공언한 곳은 없다.

송 원장은 또 "미국 보스턴에 하버드의대와

MIT대가 공동으로 설립한 세계 최고 유전체

연구소인 브로드(Broad) 연구소의 최신 기법을 공동 활용하는 협약도 맺었다"고 말했다. 브로드 연구소는 암이나 당뇨병을 일으키는 원인 유전자를 찾아내어 이를 교정하는 방식의 개인 맞춤형 치료를 연구하는 기관이다.

2013.04.04

“유전체를 기반으로 한

맞춤형 항암치료를

5년 내 시작하겠다”

“5년 안에 모든 암환자

맞춤치료 실현하겠다”

2013.06.24

2011 Nature. Charting a course for genomic medicine from base pairs to bedside

Genomics and KOREA

Contents

1. Introduction

2. Genetic Variation and Expression

Analyses

3. Human Genome Project and Beyond

4. Personalized Medicine in Endocrinology

① Common Disease Risk

② Rare Disease Risk

③ Pharmacogenomics

DNA

mRNA

Protein

Metabolite

Epigenetics

Genetics Information and OMICs

Genomics

Epigenomics

Transcriptomics

Proteomics

Metabolomics

외래/입원

진료

당뇨병으로

진단된 환자

임상정보 수집 혈액 샘플 수집

외래/입원

진료 및 투약

당뇨병 합병증

및 추적관찰 정보

합병증/치료효과 관련

유전체 연관 분석

유전체 분석

검체 수집

구 분 수집 목표 수집 현황 달성도 (%) 수집 예상 달성도 (%)

당뇨병 1400 건 1365 97.50% 1462 104.4

Food Diabetes

Genetic

Predisposition

Environmental

Predisposition

Epigenetic change

Epigenetic change

Diabetic

Complications

1. Diabetes

Susceptibility 2. Diabetes

Complication

Pathogenesis

Metabolomics

2013 Metabolomics platforms for genome wide association studies—linking the genome to the metabolome

Metabolomics

Metabolomics - OGTT

2008 Metabolic profiling of the human response to a glucose challenge reveals distinct axes of insulin sensitivity

2013 Diabetes. Metabolite profiles during oral glucose challenge

Metabolomics Profiling

• Quantification of 186 metabolites

– Acylcarnitines

– Amino Acids

– Biogenic Amines

– Hexoses (sum of Hexoses)

– Phospho and Sphingolipids

• Phosphatidylcholines

• LysoPhosphatidylcholines

• Sphingomyelin

Metabolomics

Next-Generation Sequencing (NGS)

Benchtop Genome Center (90min)

454/FLX (Roche), Solexa (Illumina), SOLiD (AB)

50ng DNA (Sanger=1 ug)

Contents

1. Introduction

2. Genetic Variation and Expression

Analyses

3. Human Genome Project and Beyond

4. Personalized Medicine in Endocrinology

① Common Disease Risk

② Rare Disease Risk

③ Pharmacogenomics

1000 Genomes Samples

Population

When cell li

ne avail. (ap

prox)

DNA seque

nced from b

lood

Offspring sa

mples from

trios avail.

First set Second

set Third set Total

Utah residents (CEPH) with Northern and Western Eu

ropean ancestry (CEU) Available no yes 100 100

Toscani in Italia (TSI) Available no no 100 100

British from England and Scotland (GBR) Available no no 96 4 100

Finnish from Finland (FIN) Available no no 100 100

Iberian populations in Spain (IBS) Available no yes 30 70 100

Total European ancestry 426 74 500

Han Chinese in Beijing, China (CHB) Available no no 100 100

Japanese in Toyko, Japan (JPT) Available no no 100 100

Han Chinese South (CHS) Available most yes 100 100

Chinese Dai in Xishuangbanna (CDX) Feb-12 some no 100 100

Kinh in Ho Chi Minh City, Vietnam (KHV) Available some some 100 100

Chinese in Denver, Colorado (CHD) (pilot 3 only) Available no no 0

TOTAL East Asian ancestry 300 200 500

Yoruba in Ibadan, Nigeria (YRI) Available no yes 100 100

Luhya in Webuye, Kenya (LWK) Available no no 100 100

Gambian in Western Division, The Gambia (GWD) Aug-12 no yes 100 100

Mende in Sierra Leono (MSL) Aug-12 no yes 100 100

Esan in Nigeria (ESN) Aug-12 no yes 100 100

TOTAL West African ancestry 200 300 500

African Ancestry in Southwest US (ASW) Available no some 61 1 62

African Caribbean in Barbados (ACB) Available yes yes 79 21 100

Mexican Ancestry in Los Angeles, CA (MXL) Available no yes 70 70

Puerto Rican in Puerto Rico (PUR) Available yes yes 70 20 90

Colombian in Medellin, Colombia (CLM) Available no yes 70 19 89

Peruvian in Lima, Peru (PEL) Available yes yes 70 19 89

TOTAL Americas 271 150 79 500

Gujarati Indian in Houston, TX (GIH) Available no no 100 100

Punjabi in Lahore, Pakistan (PJL) May-Aug 20

12 yes yes 100 100

Bengali in Bangladesh (BEB) Aug-12 no yes 100 100

Sri Lankan Tamil in the UK (STU) Aug-12 yes yes 100 100

Indian Telegu in the UK (ITU) Aug-12 yes yes 100 100

TOTAL South Asian ancestry 100 400 500

TOTAL 1197 524 779 2500

Wellcome Trust: 10,000 human genomes to uncover disease-causing variants

Korean Reference Genome

Comprehensive Catalogues of

Genomic Data Variation in the human genome

Mendelian (monogenic) diseases

(N=21,862) as of 2013-06-28

Whole genome sequencing (N=1,000)

Four ethnic groups

(CEU, YRI, JPT, CHB, N=270)

GWAS catalog

Complex (multigenic) traits

(1647 publications and 10953 SNPs)

As of 2013-06-28

Disease-related variations

Functional elements in the human genome

ENCyclopedia Of DNA Elements

Contents

1. Introduction

2. Genetic Variation and Expression

Analyses

3. Human Genome Project and Beyond

4. Personalized Medicine in Endocrinology

① Common Disease Risk

② Rare Disease Risk

③ Pharmacogenomics

Genome-wide Profiling Human Genome(DNA) Study

Microarray

Proteonomics

GWAS, Candidate gene study

Familial study

Linkage study

Genomic Study

Genomic Medicine

Novel Variant(SNP) Discovery Novel Target Discovery

GENE for everyone VARIANT based individualization

Non-responder of treatment

Severe side effect

Anti-oxidant

Monoclonal antibody for osteoporosis

Genetic counseling for rare diseases

Sensitive urine test, DM subtype

Mendelian disease diagnosis

High risk of future osteoporosis

High risk of DM complications

Diagnosis

Treatment

Prevention

Common Disease Risk

Rare Disease Risk

Therapeutic Option

Novel Disease Target Personalized Medicine

Personalized Medicine

2012 European Heart Journal. Personalized medicine: hope or hype?

Contents

1. Introduction

2. Genetic Variation and Expression

Analyses

3. Human Genome Project and Beyond

4. Personalized Medicine in Endocrinology

① Common Disease Risk

② Rare Disease Risk

③ Pharmacogenomics

Common Disease Risk

1. Disease Genetic Susceptibility

2. Ethnic Difference

3. Complication Genetic Susceptibility

4. Environmental Interaction

5. Epigenetics

6. Pleiotropy

Common Disease Risk

1. Disease Genetic Susceptibility

2. Ethnic Difference

3. Complication Genetic Susceptibility

4. Environmental Interaction

5. Epigenetics

6. Pleiotropy

Influence of Genetics on Human Disease

For any condition the overall balance of g

enetic and environmental determinants ca

n be represented by a point somewhere w

ithin the triangle.

45

Single

Locus /

Mendelian

Multiple

Loci or multi-

chromosomal

Environmental

Cystic Fibrosis

Hemophilia A

Examples:

Alzheimer’s Disease

Type II Diabetes

Cardiovascular Disease

Diet

Carcinogens

Infections

Stress

Radiation

Lifestyle

Gene = F8

Gene= CFTR

F8 = Coagulation Factor VIII

CFTR = Cystic Fibrosis Conductance Transmembrane Regulator

Lung Cancer

2008 HMG Genome-based prediction of common diseases- advances and prospects

2008 HMG Genome-based prediction of common diseases- advances and prospects

Variants and Disease Susceptibility

2008 NRG Genome-wide association studies for complex traits- consensus, uncertainty and challenges

Promise of Human Genome Project

Estrada et al., Nature Genetics, 2012

+ novel targets

for bone biology

Recent largest GWAS

GEFOS consortium

Diabetes ≠ Genetic Disease?

• Familial aggregation – Genetic influences?

– Epigenetic influences • Intrauterine environment

– Shared family environment? • Socioeconomic status

• Dietary preferences

• Food availability

• Gut microbiome content

• Overestimated heritability – Phantom heritability

2012. Drong AW, Lindgren CM, McCarthy MI. Clin Pharmacol Ther. The genetic and epigenetic basis of type 2 diabetes and obesity.

2012. PNAS The mystery of missing heritability- Genetic interactions create phantom heritability

Per-allele effect of BMI-associated

loci on body weight

2012 Genetic determinants of common obesity and their value in prediction

2011 Hum Genet. Type 2 diabetes and obesity- genomics and the clinic

2014 DC Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity

SNP N …………

…………

…………

…………

∑ = 1

Max = N x 2

∑ = 2

∑ = 4

SNP 1

0

1

2

SNP 2

0+0

1+1

2+1

Genetic Predisposition Score

2008 HMG Genome-based prediction of common diseases- advances and prospects

Single variant Single variant 20 variants

2010 AJCN Cumulative effects and predictive value of common obesity-susceptibility variants identified by genome-wide association studies

◇◆ ‘parental obesity’ as a test to predict obesity

in adult life •Dark blue 1–2 yrs

•Green 3–5 yrs

•Red 6–9 yrs

•Light blue 10–14 yrs

•Grey , 15–17 yrs

Genetic Prediction of Obesity Risk

The predictive ability of

the currently

established BMI-

associated loci is poor

2012 Genetic determinants of common obesity and their value in prediction

CONCLUSIONS:

In this study, adding genetic information to a

previously validated clinic + biological score does

not seem to improve the prediction of T2DM

“At the end of the era of common variant discovery for T2D,

polygenic scores can predict T2D in whites and blacks but do

not outperform clinical models.

Further optimization of polygenic prediction may require novel

analytic methods, including less common as well as

functional variants.”

2014 DC Polygenic Type 2 Diabetes Prediction at the Limit of Common Variant Detection

2014 DC Polygenic Type 2 Diabetes Prediction at the Limit of Common Variant Detection

Predicting Complex Diseases

2013 NG Predicting the influence of common variants

“For most diseases, it should be possible to identify the individuals with the highest

genetic risk. However, if the aim is to identify individuals with just twice the mean

population risk, we cannot currently do that with SNPs”

Mean population risk

Highest genetic risk

x2

Dis

ease R

isk

Rare Variant?

Rare Variants

with Large Effect Size?

• "These results indicate that the T2D landscape is not dominated by low-frequency and rare coding variants of large effect."

• "To conclude, either private loss of function variants may not have a phenotypic impact in diabetes-related traits or functional annotations need to be improved to separate SNPs with significant associations into meaningful categories."

• "In 5,334 samples, no low-frequency or rare causal variants were identified using single marker or gene-level tests. "

Rare Variant?

2014 NG Identification of low-frequency and rare sequence variants associated with elevated or reduced risk of type 2 diabetes

Variant based approach

2014 NG Loss-of-function mutations in SLC30A8 protect against type 2 diabetes

Gene based approach

2014 NG Low copy number of the salivary amylase gene predisposes to obesity

Gene-centric CNV association study

(GCAS)

2014 NG Low copy number of the salivary amylase gene predisposes to obesity

Normal-weight controls

(BMI < 25 kg/m2)

Obese cases

(BMI ≥ 30 kg/m2)

2014 NG Low copy number of the salivary amylase gene predisposes to obesity

AMY1 copy numbers and Obesity

2014 NG Low copy number of the salivary amylase gene predisposes to obesity

Common Disease Risk

1. Disease Genetic Susceptibility

2. Ethnic Difference

3. Complication Genetic Susceptibility

4. Environmental Interaction

5. Epigenetics

6. Pleiotropy

Trans-ethnic heterogeneity

2012 Ethnic differences in genetic predisposition to hypertension

Different linkage disequilibrium

patterns

2009 PLOS one. Transferability and Fine-Mapping of Genome-Wide Associated Loci for Adult Height across Human Populations

Replicate Not Replicate

Trans-ethnic heterogeneity

East

Asia

n

So

uth

Asia

n

2013 Comparing methods for performing trans-ethnic meta-analysis of genome-wide association studies

535 SNPs (59 GWS loci) Korea

Ansung N=2729

In silico

Replication

European BMD GWAS

182 suggestive SNPs

276 SNPs (25 GWS loci)

16 suggestive SNPs

Replicated in Koreans

Replication rate: 51.6% (276/535 SNPs)

FDA Halt 23andMe

2013.11.22.

Common Disease Risk

1. Disease Genetic Susceptibility

2. Ethnic Difference

3. Complication Genetic Susceptibility

4. Environmental Interaction

5. Epigenetics

6. Pleiotropy

당뇨병 합병증 예측 유전형 연구

관찰기간 20년

합병증 발병

50%

20%

고위험 유전형 환자

저위험 유전형 환자

당뇨병

합병증

Diabetes Complication Prediction

2013 NEJM APOL1 Risk Variants, Race, and Progression of Chronic Kidney Disease

APOL1 genotype predicts kidney function decline

2014 DC Genetic Risk Score Associations With Cardiovascular Disease and Mortality in the Diabetes Heart Study

Genetic Risk and

Cardiovascular Mortality

2014 DC Genetic Risk Score Associations With Cardiovascular Disease and Mortality in the Diabetes Heart Study

2014 DRCP Transcription factor 7-like 2 (TCF7L2) gene

polymorphism rs7903146 is associated with stroke in type 2

diabetes patients with long disease duration

Common Disease Risk

1. Disease Genetic Susceptibility

2. Ethnic Difference

3. Complication Genetic Susceptibility

4. Environmental Interaction

5. Epigenetics

6. Pleiotropy

Gene-Environment Interaction

Gene Environment

Disease

Genetic Predisposition Score Sugar-Sweetened Beverages

2010 PLoS Med Physical activity attenuates the genetic predisposition to obesity in 20,000 men and women from EPIC-Norfolk prospective population study

Gene-Environment Interaction Exercise X Genetic Predisposition

High Sugar Intake

Low Sugar Intake

Genetic Predisposition Score

10 40 20 30

BMI Slope = 2.43

Slope = 1.46 Slope = ΔBMI / Δ10 alleles

2012 NEJM Sugar-Sweetened Beverages and Genetic Risk of Obesity

Soda School

No-Soda School

Obese Family Lean Family

Common Disease Risk

1. Disease Genetic Susceptibility

2. Ethnic Difference

3. Complication Genetic Susceptibility

4. Environmental Interaction

5. Epigenetics

6. Pleiotropy

당뇨병과 후성유전체 연구

Food Diabetes

Genetic

Predisposition

Environmental

Predisposition

Epigenetic change

Epigenetic change

Diabetic

Complications

1. Diabetes

Susceptibility 2. Diabetes

Complication

Pathogenesis

2012 The genetic and epigenetic basis of type 2 diabetes and obesity

Common Disease Risk

1. Disease Genetic Susceptibility

2. Ethnic Difference

3. Complication Genetic Susceptibility

4. Environmental Interaction

5. Epigenetics

6. Pleiotropy

Pleiotropy

2012 NG Meta-analysis identifies multiple loci associated with kidney function-related traits in

east Asian populations

2011 NRG The pleiotropic structure of the genotype-phenotype map- the evolvability of

complex organisms.

Contents

1. Introduction

2. Genetic Variation and Expression

Analyses

3. Human Genome Project and Beyond

4. Personalized Medicine in Endocrinology

① Common Disease Risk

② Rare Disease Risk

③ Pharmacogenomics

2012 European Heart Journal. Personalized medicine: hope or hype?

Laboratory Director

강현석

Personal genomics: His daughter's DNA (2007)

Do-it-yourself science

Mutation provides clue to daughter’s undefined syndrome

2013.6.26.

Contents

1. Introduction

2. Genetic Variation and Expression Analyses

3. Human Genome Project and Beyond

4. Personalized Medicine in Endocrinology

① Common Disease Risk

② Rare Disease Risk

③ Pharmacogenomics

• Cancer

• Non-cancer

Variable Drug Responses

2012 European Heart Journal. Personalized medicine: hope or hype?

Herceptin

Glivec

November 19, 2013

Cancer genomics

Pharmacogenomics

From 2012 MGR of Pf. Hye-Suk Han

Targeted Therapy Genetic Test Cancer

Genomics in Oncology

JCO-2013-Dienstmann-1874-84

JCO-2013-Garraway-1806-14

10 oncogenic drivers testing

2014 JAMA Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs

Personalized Medicine

Pharmacogenomics

Nutrigenomics

IRS1 SNP GA/AA

High fat/

Low carb

IRS1 SNP GG Standard

Higher

effect

Similar

effect

Large Effect Size Variant?

Disease susceptibility variant Pharmacogenetic variant

Environmental

Exposure

Drug

Exposure

Variants and Disease Susceptibility

2008 NRG Genome-wide association studies for complex traits- consensus, uncertainty and challenges

Natural selection

Pharmacogenetics

GWAS

Effect Size vs. Sample Size

genotype relative

risks (GRR)

Small effect size

Large

effect size

2007 BMC Genetics. Power analysis for genome-wide association studies Small sample size

Large sample size

November 19, 2013

November 19, 2013

2013 NEJM A Randomized Trial of

Genotype-Guided Dosing of Warfarin

2013 NEJM A

Randomized Trial of

Genotype-Guided Dosing

of Warfarin

Median

21 days

Median

29 days

Median

44 days

Median

59 days

P<0.001

P=0.003

Case/Control=39/833

SNP chip

Chr 6

Discover

Validate

2013/10/24 China

Discovery Patients (N=294)

SNP chip

Chr 3

2013/12/25

Discover

Validate

Replication Patients (N=100)

Taiwan Bipolar Consortium

Anti-thyroid drug related agranulocytosis

Hyperthyroidism Anti-thyroid drug Fatal side effect

Agranulocytosis

Hyperthyroidism: incidence 0.1~0.4 / 1000 / year (M<F)

Rare side effect: 0.3~0.6% among treated

Second exposure Relapse

HLA class II related?

2013.11.14.

141 drugs

158 labels

60 indications/contraindications Atorvastatin, Azathioprine, Carbamazepine, Carvediolol, Clopidogrel, Codein, Diazepam…..

CPIC Pharmacogenetic Tests: 최형진

No Drug

(N= 10)

Gene

(6 genes=8 bioma

rkers)

Target SNPs

(N=12)

#5

(HJC) Genotype Interpretation Clinical Interpretation

1 Clopidogrel CYP2C19

rs4244285 (G>A) GG *1/*1

(EM) Use standard dose rs4986893 (G>A) GG

rs12248560 (C>T) CC

2 Warfarin

VKORC1 rs9923231 (C>T) TT Low dose

(higher risk of bleeding) Warfarin dose=0.5~2 mg/day

CYP2C9 rs1799853 (C>T) CC

rs1057910 (A>C) AC

3 Simvastatin SLCO1B1 rs4149056 (T>C) TT Normal

4 Azathioprine (AP),

MP, or TG TPMT rs1142345 (A>G) AA Normal

5 Carbamazepine

or Phenytoin HLA-B*1502

rs2844682 (C>T) CT Normal

rs3909184 (C>G) CC

6 Abacavir HLA-B*5701 rs2395029 (T>G) TT Normal

7 Allopurinol HLA-B*5801 rs9263726 (G>A) GG Normal

Clopidogrel1): UM/EM=standard dose, IM/PM= consider alternative antiplatelet agent (eg. prasugrel/ticagrelor)

Warfarin2): high dose=5~7 mg/day, medium dose=3~4 mg/day, low dose=0.5~2 mg/day

$99

N>400,000

Point-of-care

Genotyping

HyBeacon Probes

Pharmacogenomics

• Treatment Response

– GGPS1 SNP ↔ Bisphosphonate response

Choi et. al. Yonsei Med J. 2010

Metformin Transporters

AA

AC

CC

MATE1

OCT1

GG GA AA

2011 Nature. Drugs, diabetes and cancer

2013 The Role of Pharmacogenetics in Drug Disposition and Response of Oral Glucose-Lowering Drugs

2010 Interaction between polymorphisms in the OCT1 and MATE1 transporter and metformin response

Expected Metformin response

Other drug Metformin usual dose Metformin low dose (S/E)

0% -1% -2% -1.5% -2.5% -3% +0.5%

HbA1c change

Good Response

Genotype

Poor Response

Genotype

2012 Individualized therapy for type 2 diabetes- clinical implications of pharmacogenetic data

List of SNPs Associated with Diabetes Drug Response

2012 Individualized therapy for

type 2 diabetes- clinical

implications of pharmacogenetic

data

Genotype Guided Personalized Treatment

Baseline

Genotyping

- Drug metabolism

- DM etiology

- DM complication

1 week 3 month Long term

Genotype based treatment strategy

- Drug choice

- Drug dose

- Lifestyle modification

- Complication evaluation

New

T2DM

2010 Lancet Clinical assessment incorporating a personal genome

Whole Genome

Sequencing Heliscope Genome sequencer

Pharmacogenomic variants

2010 Lancet Clinical assessment incorporating a personal genome

2010 Lancet Clinical assessment incorporating a personal genome

Common

Disease Risk

Prediction

2010 Lancet Clinical assessment incorporating a

personal genome

Common

Disease Risk

Prediction

Rare variants

2010 Lancet Clinical assessment incorporating a personal genome

2010 Lancet Clinical assessment incorporating a personal genome

A Genotype-First Approach to Defining

the Subtypes of a Complex Disease

2014.2.27.

Genome-wide Profiling Human Genome(DNA) Study

Microarray

Proteonomics

GWAS, Candidate gene study

Familial study

Linkage study

Genomic Study

Genomic Medicine

Novel Variant(SNP) Discovery Novel Target Discovery

GENE for everyone VARIANT based individualization

Non-responder of treatment

Severe side effect

Anti-oxidant

Monoclonal antibody for osteoporosis

Genetic counseling for rare diseases

Sensitive urine test, DM subtype

Mendelian disease diagnosis

High risk of future osteoporosis

High risk of DM complications

Diagnosis

Treatment

Prevention

Common Disease Risk

Rare Disease Risk

Therapeutic Option

Novel Disease Target Personalized Medicine

Genome Surgery

Future of Genomic Medicine?

Test when needed Without information Know your type

Blood

type

Geno

type

Here is my

sequence