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Genomics & Medicine Personal Genomics The Lancet 2010, 375: 1525-1535. Doug Brutlag Professor Emeritus of Biochemistry & Medicine Stanford University School of Medicine. Low Heritability of Common SNPs.

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genomics medicine http biochem158 stanford edu
Genomics & Medicine

Personal Genomics

The Lancet 2010, 375: 1525-1535.

Doug Brutlag

Professor Emeritus of Biochemistry & Medicine

Stanford University School of Medicine

low heritability of common snps
Low Heritability of Common SNPs

Odds Ratio

  • Rare High Penetrance Variants Carry High Risk
  • Common SNPs Carry Low Risk
  • Multiple Variants May Increase Risk Synergistically
  • Common SNPs Associated with Genes Containing High Risk Alleles
  • Common SNPs Associations can Suggest Regions to Sequence in Cohorts or Trios or Subpopulations

Manolio et al. Nature 461, 747-753 (2009)

disease genes are often enriched in subpopulations
Disease Genes are Often Enriched in Subpopulations
  • Subpopulations are often enriched for disease alleles
  • Subpopulations can cause synthetic SNP associations
  • Focusing on a subpopulations will eliminate synthetic SNP associations
  • Focusing on subpopulations eliminates need for population stratification adjustments
  • Egypt is a haplotype heaven!
    • Highest frequency of genetic (SNP) variations
    • High numbers of genetic subpopulations due to multiple migrations and invasions
    • Greeks, Romans, Turks, Persians etc.
summary of genome wide association studies
Summary ofGenome-Wide Association Studies
  • Genome-wide association studies make no assumptions about disease mechanism or cause
  • Genome-wide association studies usually discover only genetic correlations, not causal mutations
  • Genome-wide associations suggest:
    • Genes and regions one must analyze by re-sequencing for causal alleles
    • Subpopulations that may be enriched for causal or preventive alleles
    • Genes and gene products for functional and structural studies
    • Genes to examine for regulatory studies
  • Genome-wide association studies coupled with proper biological and structural studies can lead to:
    • Unexpected causes for disease
    • Novel mechanisms for disease (missense mutations, regulatory changes, alternative splicing, copy number variation etc.)
    • Multiple genes and multiple pathways involved in disease
    • Novel diagnostics and prognosis
    • Novel treatments
genetic loci associated with hypertriglyceridemia http www ncbi nlm nih gov pubmed 20657596
Genetic Loci Associated with Hypertriglyceridemia
Novel Rare Variants in GWAS Genes for Hypertriglyceridemia
rare variant accumulation in hypertriglyceridemia http www ncbi nlm nih gov pubmed 20657596
Rare Variant Accumulation in Hypertriglyceridemia
so what can we learn from personal genomics
So What Can We Learn fromPersonal Genomics?
  • Disease risk for common diseases
    • Genetic predisposition towards a disease (relative risk or odds ratio)
    • Genetic versus environmental contributions to disease (penetrance)
    • How to alter your environment and behavior to avoid the disease
  • Disease Carrier status
    • Premarital genetic counseling
    • Preimplantation genetic diagnosis
    • Neonatal diagnosis
      • Amniocentesis
      • Chorion villus sampling (CVS)
      • Fetal cells in pregnant mothers blood
  • Familial traits, diseases and relationships
    • Known family diseases (breast cancers, colorectal cancer, lysosome storage diseases, etc.)
    • Paternity (10% of people do not know their true biological father)
    • Maternity (about 1% of people do not know their true biological mother)
    • Inbreeding and incest lead to increased homozygosity and recessive diseases
    • Orphans can find family relations
  • Pharmacogenomics and Pharmacogenetics: Drug susceptibility
    • Efficacy of common drugs
    • Adverse reactions to common drugs
  • Ancestry
    • One can follow maternal line using mitochondrial DNA SNPs
    • Males can follow paternal line using Y chromosome SNPs
    • Shared haplotypes with recent relatives (up to 5th cousins)
choice of gwas studies
Choice of GWAS Studies
  • Common traits of broad interest
    • Prevalence of > 1%
    • Report Mendelian traits when possible
    • Focus on drug responses
  • Avoid false discoveries
    • Large case-control studies > 750 cases
    • Highly significant expectation values (<0.01 errors)
    • Published in reputable journals
    • Studies that have been replicated
  • May impute highly linked missing SNPs
  • Calculate likelihood and odds ratio using customers ethnicity as detected
  • Distinguish preliminary studies (non-replicated or smaller sample sizes) from established research.
informed for 23andme customers http informeddna com index php 23andme schedule appointment 23 html
INFORMED for 23andMe Customers
dnadirect clinical genetic testing
DNAdirect: Clinical Genetic Testing

dnadirect clinical genetic testing48
DNAdirect: Clinical Genetic Testing

personal genomics references
Personal Genomics References
  • Clinical Assessment Incorporating a Personal Genome. Ashley, E. et al. (2010)

Lancet 375, 1525-1535.

  • Emerging genomic applications in coronary artery disease. Damani SB,

Topal EJ, JACC Cardiovasc. Intervention (2011). 4:473-482.

  • Clinical applicability of sequence variations in genes related to drug

metabolism. Stojiljkovic M, Patrinos GP, Pavlovic S. (2011) Curr Drug Metab.


  • Clinical pharmacogenetics and potential application in personalized medicine.

Zhou et al., (2008) Curr Drug Metab. 9(8):738-84.

  • Genes, mutations, and human inherited disease at the dawn of the age of

personalized genomics. Cooper et al (2010) Hum Mutat. 31(6):631-55.

  • Web-based, participant-driven studies yield novel genetic associations for

common traits. Eriksson et al. (2010) PLoS Genetics 6, e1000993.