Presentation on theme: "Genetic Approaches to Thinking, Moving and Feeling Richard B. Lipton, M.D Professor and Vice Chair, Neurology Professor of Epidemiology and Population."— Presentation transcript:
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
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
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
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
Mendelian vs. Complex Diseases and Traits 1. Mendelian (single gene) a. Autosomal dominant (Huntingtons 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
GenesEnvironment Genes + Environment Causes of Complex Cognitive, Emotional and Motor Traits
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
Can a single gene influence thinking, feeling and moving Yes for Huntingtons, 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)
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
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
Higher Concordance Rates for MZ vs. DZ Twins Shows a Significant Genetic Component TraitMZDZ Schizophrenia4614 Insulin-dependent diabetes mellitus30 6 PD < age 50* PD age 50*1111 Survival** to 90 (females) Concordance *Tanner, 1999 ** Hjelmborg et al, 2006
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
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.
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 ATAT Single Nucleotide Polymorphisms (SNPs) Millions distributed throughout genome Single base pair substitutions unique flanking DNA sequence
Association Studies Comparison of allele frequencies between unrelated affected and unaffected individuals. 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! Affected cases Unaffected controls Case – Control
Association Study Approaches Candidate gene search – functional variants (if possible) in gene with biological relevance: Genome-wide scan –Dense set of markers throughout genome: Single marker association Define common haplotypes –Assess haplotypes for association
Gene Identification in Complex Traits using Candidate Gene Approaches 1.Select candidate genes based on biology and the availability of functional SNPs or SNP haplotypes 2.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
What is the Significance of a Population Association Between a Disease and a Particular Allele (Genetic Variant)? 1)Allele is directly involved in the pathogenesis of the disease 2)The result is a false positive due to statistical error 3)The result is a false positive due to inadequate matching of cases and controls (population stratification) 4) Linkage disequilibrium
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.
Affymetrix Genotyping Technology 250 ng Genomic DNA RE Digestion Adaptor Ligation Nsp Fragmentation and Labeling PCR: One Primer Amplification Complexity Reduction Hyb & Wash AA BB AB 250,000 Genotypes
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
Barzilai et al, PLoS Biology years before
A Major Barrier to Genetic Studies in Centenarians What is the appropriate control group?
A Major Barrier to Genetic Studies in Centenarians What is the appropriate control group? Age mates of centenarians?
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
DM (%)MI (%)Stroke (%) Prevalence in population HTN (%) Offspring of Centenarians are Less Likely to Have Age-Related Diseases JAGS 2004; 52:274 P O C ** Cntnrn Offspring Control ** p<0.01
Modeling Changes in the Frequency of a Genotype as a Function of Age Age Genotypic Frequency Longevity genes Aging or killing genes Genes not contributing to life-span
Age (Year) Favorable genotype in population (%) CETP VV APOC3 CC ADIPOQ del/del Favorable Longevity-Associated Genotypes in Unrelated Year-Old Ashkenazi Individuals
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
CETP (ug/mL ) ADIPOQ VV I/V Large LDL (%) (ug/mL) -- A/- * APOC3 (mg/dL) CC C/A * * p<0.05 Longevity Genotypes are associated with HDL and LDL particle size *
CETP VV Genotype and Cognitive Function *p<0.01 CETP VV frequency (%) MMSE<25 MMSE 25 * Centenarians *p< Dementia (n=31) Non-demented (n=129) * EAS Barzilai et al, Neurology 2007
Is Size of Lipoproteins Associated with Cognitive Function? * *P<0.003 *
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.
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).
Gait VariablesDel/Del (n = 72) Ins/Ins (n = 80) Velocity, cm/sec92.2 ± ± 24.3 Cadence, steps/ min101.7 ± ± 12.1 Stride length, cm108.4 ± ± 21.2 Stance, %62.6 ± 2.9*63.8 ± 3.8 Swing, %37.4 ± 2.9*36.2 ± 3.8 Double support time, %25.0 ± 5.2*27.6 ± 8.8 Stride length variability, SD4.3 ± ± 3.3 *p<0.05 (linear regression adjusted for age & sex) 322 subjects (27% AJ, 63% women) Mean age 77.8y Adiponectin del/del genotype is associated with better balance and rhythm on gait
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
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
Genetic Research Methods: Advantages and Disadvantages Advantages Identify single genes with large effects Survey the whole genome Disadvantages Must be family-based Limited power for complex disorders Low resolution Study the Linkage More power for complex diseases Large samples for genes with small effect Association Customize choicesFind selected associations Candidate genes ( SNPs) Survey the genomeExpensive Bioinformatic challenge False positives Whole genome ( SNPs)
Pair Wise Concordance in Survival to Age 90+ Among Swedish, Danish and Finnish Twins MZ Concordant Total PairsPairs Concordance Male % Female % Total % DZ Concordant Total PairsPairs Concordance Male % Female % Total % Concordance = C/C+D Hjelmborg et al, Human Genetics, 2006
Can Plasma HDL Levels Predict Longevity? *p< vs. Others HDL (mg/dl) Females SpouseOffspringProband n=157 * n=122 n=147
These results support an association between specific genes and motor function.
< Age HDL Particle Size (nm) LDL Particle Size (nm) Control Offspring Probands < Age Lipoprotein particle size as function of age Heritability (h) of lipoprotein particle size Barzilai et al JAMA 290:2030, 2003
Are lipoprotein sizes associated with protection from age-related diseases? (in offspring of centenarians) * *P<0.003 * Barzilai et al JAMA 290:2030, 2003
Lipoprotein and their size in healthy or subjects with the Metabolic Syndrome (MS) *P<0.001 * * Barzilai et al JAMA 290:2030, 2003
* * * Average Mini-Mental Score of Tertile HDL Groups* *p<0.04 J. Gerontol 57A, M712, 2002 (HDL 37±2 mg/dl) (HDL 51±2 mg/dl) (HDL 75±2 mg/dl)
CETP (ug/mL ) ADIPOQ VV I/V Levels * (ug/mL) -- A/- * APOC3 (mg/dL) CC C/A * * p<0.05 Are Longevity Genotypes Associated with Clinically-Significant Phenotypes?
Cross Sectional HDL Levels (D ata from the Framingham study) Age HDL (mg/dl) 50
Genetic Research Methods: Advantages and Disadvantages Advantages Identify single genes with large effects Survey the whole genome Disadvantages Must be family- based Limited power for complex disorders Low resolution Study the Linkage More power for complex diseases Large samples for genes with small effect Association
Genetic Research Methods: Advantages and Disadvantages Advantages Identify single genes with large effects Survey the whole genome Disadvantages Must be family- based Limited power for complex disorders Low resolution Study the Linkage
Levels of analysis Genetics- study of single genes and their effects. Focus on the disease. Genomics-study of the functions and interactions many genes, their transcription and regulation Proteomics-Study of proteins Metabolomics-Study of small molecules (physiologic indicators) in plasma, tissues or cells including peptides, lipids, carbs, drugs