Genetic Approaches to Thinking, Moving and Feeling

1. Genetic Approaches to Thinking, Moving and Feeling Richard B. Lipton, M.D Professor and Vice Chair, Neurology Professor of Epidemiology and Population Health Albert Einstein College of Medicine

2. Why consider genetic approaches? • Genetic factors play a crucial role in disease that affect thinking, feeling and moving • Genetic factors are relevant to potential shared mechanisms: vascular disease, inflammation, recovery from injury • Method for parsing the heterogeneity • Environmental risk factors interact • Identify molecular targets and treatments with pleiotropic effects

3. The best of times • Human Genome Project -Identify the 30,000 genes in the human genome -Sequenced 3 billion base pairs(2003) -<2% of the genome codes for protein -3 million loci with single base pair differences • HapMap Project -Systematic genotyping of 3 million SNPs • Available of high throughput technologies

4. The genome, the transcriptome and the proteome • The genome is static • The transcriptome is dynamic and tissue and cell specific. SNPs in a coding region may alter protein structure; SNPs in a promoter region may alter mRNA levels. Non-coding RNA can activate arrays of related genes. • The proteome reflects post-transcriptional processes including RNA spicing, post-translational modification

5. Mendelian vs. Complex Diseases and Traits 1. Mendelian (single gene) a. Autosomal dominant (Huntington’s disease) b. Autosomal recessive (Cystic fibrosis) c. X-linked 2. Complex diseases and traits are multifactorial a. Oligogenic or polygenic susceptibility genes (No one gene is necessary or sufficient) b. Locus heterogeneity (different genes can cause same trait) c. Pleiotropic effects d. Environmental factors contribute

6. Causes of Complex Cognitive, Emotional and Motor Traits Genes + Environment Genes Environment

7. Defining the phenotypes • Define the phenotype of interest -Diseases-heterogeneity is the rule -Single domain phenotypes: declarative memory, depression, walking speed -Multiple domain phenotypes: executive function and walking speed -Covariance shared by traits -Use biological markers or endophenotypes • Once genes are identified contrast carriers and non-carriers to refine the phenotypes • Challenge: pleiotropy and polygenicity

8. Can a single gene influence thinking, feeling and moving • Yes for Huntington’s, TDP-43 • Relevant genes might influence transmitters, ion channels, recovery from insults, plasticity, dendritic complexity, etc. • A gene may influence an area of the brain that has distal secondary affects • A gene may influence several areas of the brain each of which influences a distinct cognitive, emotional or motor process • A gene may influence several brain regions or processes each of which affects more than one domain (Kovas and Plomin, Trends in Cog Sci, 2006)

9. Approach to Complex Diseases Assess the influence of genetic factors (heritability) -Family studies -Twin studies Identify specific genetic factors -Linkage analysis -Allele sharing methods -Case-control studies

10. Determining the Genetic Component Familial aggregation -Measure family relative risk. -Suggests but does not prove genetic mechanism -Look for aggregation of one domain (thinking) in relatives of probands selected for another domain (moving) Twin studies -If concordance rate for MZ twins > DZ twins some genetic influence -Look for aggregation of one domain in MZ and DZ twins with issues in another domain Heritability: the proportion of the variance in a disease or trait accounted for by genetic factors

11. Higher Concordance Rates for MZ vs. DZ Twins Shows a Significant Genetic Component Concordance Trait MZ DZ Schizophrenia 46 14 Insulin-dependent diabetes mellitus 30 6 PD < age 50* 100 17 PD ≥ age 50* 11 11 Survival** to 90 (females) 16.8 9.0 *Tanner, 1999 ** Hjelmborg et al, 2006

12. Identification of Genetic Factors in Complex Diseases • Linkage analysis: Identify extended families • where disease or an endophenotype appears • Mendelian (usually early-onset) • Allele sharing methods, genome wide screening in • affected sibling pairs (Identity by descent) • Association studies in human populations

13. Identification of Genetic Factors in Complex Diseases: Linkage Analysis Identify large families where the trait appears Mendelian (Are there high density families with relevant phenotypes?) Look for genes or DNA segments which segregate with the disease or trait. Genes and DNA segments close to each other on a chromosome tend to be inherited together. Look for coinheritance of polymorphic markers and disease.

14. Common Useful Genetic Markers • Simple Sequence Repeats Tens of thousands in genome Typically di-, tri- or tetra- nucleotide repeats (GT)n unique flanking DNA sequence • Single Nucleotide Polymorphisms(SNPs) • Millions distributed throughout genome • Single base pair substitutions A T unique flanking DNA sequence

15. Association Studies Comparison of allele frequencies between unrelated affected and unaffected individuals. Case – Control Unaffected controls Affected cases Disease-marker association exists when alleles at the marker locus occur with different relative frequencies in affected and unaffected individuals. Most important: Use unaffected individuals from the same population!

16. Association Study Approaches • Genome-wide scan • Dense set of markers throughout genome: • Candidate gene search • functional variants (if possible) in gene with biological relevance: • Single marker association • Define common haplotypes • Assess haplotypes for association

17. Gene Identification in Complex Traits using Candidate Gene Approaches • Select candidate genes based on biology and the availability of functional SNPs or SNP haplotypes • Select candidates for thinking, feeling and moving from the genes -Expressed in brain -Related to a specific domain -Identified based on biology (brain recovery-ApOE, inflammation-CRP, vascular risk genes-lipid related, intracellular signal transduction genes, longevity, energy metabolism) 3. Options limited by current hypotheses

18. What is the Significance of a Population Association Between a Disease and a Particular Allele (Genetic Variant)? • Allele is directly involved in the pathogenesis of the disease • The result is a false positive due to statistical error • The result is a false positive due to inadequate matching of cases and controls (population stratification) • 4) Linkage disequilibrium

19. Whole Genome Association (WGA): • In WGA, high density chip arrays containing hundreds of thousands of SNPs are used to screen the entire genome on a single array. • Using cases and controls, WGA association results in the generation of thousands of genotypes. Identify SNPs and SNP haplotypes associated with disease. • Then need to determine the disease causing SNPs among these, either coding sequence changes or possible promoter/enhancer etc variations.

20. Nsp Nsp Nsp PCR: One Primer Amplification Complexity Reduction AA BB AB Affymetrix Genotyping Technology 250 ng Genomic DNA RE Digestion Adaptor Ligation 250,000 Genotypes Fragmentation and Labeling Hyb & Wash

21. Genetic approaches to thinking, feeling and moving: Centenarian studies Only ~1/10,000 individuals is 100 years old Exceptional longevity occurs with greater frequency in the siblings and offspring of Centenarians Longevity genes may contribute to successful cognitive, motor and emotional aging LonGenity PPG PI: Nir Barzilai focus on Ashkenazi Jews as a founder population

22. 90 years before 104 98 92 95 Barzilai et al, PLoS Biology 2006

23. A Major Barrier to Genetic Studies in Centenarians What is the appropriate control group?

24. A Major Barrier to Genetic Studies in Centenarians What is the appropriate control group? • Age mates of centenarians?

25. A Major Barrier to Genetic Studies in Centenarians What is the appropriate control group? • Age mates of centenarians? • Alternative • Study centenarians their offspring and ages mates of their offspring • Hypothesis: Longevity gene frequency Centenarian > Offspring > Controls

26. Cntnrn Offspring of Centenarians are Less Likely to Have Age-Related Diseases 40 P 35 ** Offspring O Control C 30 25 Prevalence in population 20 15 ** p<0.01 10 ** ** 5 ** 0 HTN (%) DM (%) MI (%) Stroke (%) JAGS 2004; 52:274

27. Longevity genes Aging or “killing” genes Genes not contributing to life-span Modeling Changes in the Frequency of a Genotype as a Function of Age 0.7 0.6 0.5 0.4 Genotypic Frequency 0.3 0.2 0.1 0 60 65 70 75 80 85 90 95 100 Age

28. Favorable Longevity-Associated Genotypes in Unrelated 65-108 Year-Old Ashkenazi Individuals 35 ADIPOQ del/del 30 APOC3 CC 25 CETP VV Favorable genotype in population (%) 20 15 10 5 0 65 75 85 95 105 Age (Year)

29. Of the three longevity genes identified to date All are associated with large lipoprotein particle size The favorable form of CETP is associated with high HDL levels and large lipoprotein particle sizes and with successful cognitive aging The favorable form of adiponectin is associated with succesful motor aging

30. 80 70 * 60 50 40 * 30 20 10 0 “Longevity Genotypes” are associated with HDL and LDL particle size * Large LDL (%) -- A/- CC C/A VV I/V *p<0.05 APOC3 CETP ADIPOQ (mg/dL) (ug/mL) (ug/mL)

31. Centenarians EAS *p<0.01 *p<0.049 * * 40 20 15 30 CETP VV frequency (%) 20 10 5 10 MMSE<25 MMSE ≥ 25 0 0 Dementia (n=31) Non-demented (n=129) CETP VV Genotype and Cognitive Function Barzilai et al, Neurology 2007

32. Is Size of Lipoproteins Associated with Cognitive Function? * * *P<0.003

33. ADIPOQ: A Longevity Genotype with a Successful Motor Aging Phenotype • The ADIPOQ del/del genotype is associated with longevity and a reduced risk of insulin resistance. • The less favorable forms of ADIPOQ genotype has links with insulin resistance and metabolic syndrome, pathways which may influence motor function. • Verghese et al. therefore examined the relationship between ADIPOQ del/del and gait performance in 322 subjects (mean age 78, 27% AJ, 63% women) who received quantitative gait measures.

34. Relationship between genotype and measures of gait • In linear regression analysis, adjusted for age and sex, the favorable form of the ADIPOQ gene (del/del) was associated with better performance on stance, swing, and double support phases. • These variables generally reflect balance and rhythm (Verghese et al. JNNP,2007).

35. 322 subjects (27% AJ, 63% women) Mean age 77.8y Adiponectin del/del genotype is associated with better balance and rhythm on gait

36. Summary • Define the phenotypes of interest with care considering the spatiotemporal expression • Consider family aggregation and twin studies to look at distribution within families of domains of interest. • Consider searching for genes that account for the covariance among traits

37. Summary • Bank DNA (and other tissue?) • Consider candidate gene and WGAS in cross sectional and longitudinal studies (LonGenity focuses on AJs, EAS on the Bronx population) • Begin studies in midlife or early adult life to reduce influence of phenocopies • Use genes to refine phenotypes

38. Many thanks

39. Advantages Identify single genes with large effects Survey the whole genome Disadvantages Must be family-based Limited power for complex disorders Low resolution Genetic Research Methods: Advantages and Disadvantages Study the Linkage • More power for complex diseases • Large samples for genes with small effect Association • Customize choices • Find selected associations Candidate genes (100-1000 SNPs) • Survey the genome • Expensive • Bioinformatic challenge • False positives Whole genome (105-106 SNPs)

40. Pair Wise Concordance in Survival to Age 90+ Among Swedish, Danish and Finnish Twins MZ Concordant Total PairsPairsConcordance Male 90+ 30 394 7.6% Female 90+ 93 554 16.8% Total 90+ 123 948 12.9% DZ Concordant Total PairsPairsConcordance Male 90+ 28 646 4% Female 90+ 103 1096 9% Total 90+ 131 1724 7.5% Concordance = C/C+D Hjelmborg et al, Human Genetics, 2006

41. Proband Offspring Spouse * n=157 n=147 Can Plasma HDL Levels Predict Longevity? Females 80 70 60 HDL (mg/dl) 50 40 0 *p<0.0001 vs. Others n=122

42. These results support an association between specific genes and motor function.

44. Lipoprotein particle size as function of age Control Offspring Probands 21.6 21.4 21.2 21.0 20.8 20.6 Heritability (h) of lipoprotein particle size 0.4-0.7 9.8 9.6 9.4 LDL Particle Size (nm) HDL Particle Size (nm) 9.2 9.0 8.8 8.6 20.4 60 65 70 75 80 85 90 95 100< 60 65 70 75 80 85 90 95 100< Age Age Barzilai et al JAMA 290:2030, 2003

45. * * *P<0.003 Barzilai et al JAMA 290:2030, 2003 Are lipoprotein sizes associated with protection from age-related diseases?(in offspring of centenarians)

46. * * Lipoprotein and their size in healthy or subjects withthe Metabolic Syndrome (MS) *P<0.001 Barzilai et al JAMA 290:2030, 2003

47. Average Mini-Mental Score of Tertile HDL Groups* (HDL 75±2 mg/dl) * (HDL 51±2 mg/dl) * (HDL 37±2 mg/dl) * *p<0.04 J. Gerontol 57A, M712, 2002

48. 16 14 12 * 10 8 * 6 4 2 * 0 -- A/- CC C/A APOC3 (mg/dL) (ug/mL) Are “Longevity Genotypes” Associated with Clinically-Significant Phenotypes? *p<0.05 Levels VV I/V CETP ADIPOQ (ug/mL)

49. Cross Sectional HDL Levels (Data from the Framingham study) HDL (mg/dl) 50 50 Age

50. Advantages Identify single genes with large effects Survey the whole genome Disadvantages Must be family-based Limited power for complex disorders Low resolution Genetic Research Methods: Advantages and Disadvantages Study the Linkage • More power for complex diseases • Large samples for genes with small effect Association