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Population Genetics in Kidney Health and Disease

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Population Genetics in Kidney Health and Disease PopulationPopulation GeneticsGenetics inin KidneyKidney HealthHealth andand DiseaseDisease Presentation Outline Introduction Some principles of Population Genetics Illustrative Example: ¾ African Heritage Populations ‐ Mapping Common Genetic Variants Take Home Messages –Call for Collaborations Acknowledgments Population Genetics: Society and Ethics • Genetic and non-genetic evidence indicates that humans are part of one extended family • Human sanctity and value is independent of population affiliation or genetics • Where we are going to is more important than where we came from Common Ancestors Unique Ancestors Individual 1 Individual 2 Population Genetics in Kidney Health and Disease ¾A “population” in human genetics can be designated as a group of people who share common ancestry patterns at a “genome wide” or “genetic locus” level ¾“Population genetic architecture” can be measured using DNA diversity markers DNA Diversity Markers Arise from “slips” in DNA Replication Classification of DNA Diversity Markers Biological Type SNPs,STRs,CNVs,other Genomic Location Uniparental (non‐recombining): useful in tracing genealogies and sex biased demographic history Biparental (autosomal): useful in assessing "relatedness", in tracing evolutionary history of genomic regions, and in trait/disease phenotype mapping Demographic History Choice and combination depends on scientific, historical, genealogical, clinical or forensic question of interest DNA Markers SNP=Single Nucleotide Polymorphism DNA Markers STR=Simple Tandem Repeat (microsatellite) one of many kinds of DNA markers original: Mississippi copy error 1: Missississippi copy error 2: Mississississippi TWIGS Repeat Event Markers: STR Timespans < 1000 years Twigs on a given Branch define a Combinations of markers define “Haplotypes” LINEAGE BRANCHES Unique Event Markers: SNP Timespans >10K years Combinations of markers define “Haplogroups” “For man is but the tree of the field” Deuteronomy 20:19 UniparentalPopulation (Y- ChromosomeSpecific Blocks and of “Linkage mtDNA) Disequilibrium” Markers are more usefulSize inand tracing Structure genealogies Reflect Population than are BiparentalArchitecture region and are markers more Useful in Disease Gene Mapping Biparental and undergo recombination Reconstructing Ancestry ¾Individuals who share the same set of markers for a given DNA region share a common ancestry at that genomic region 9DNA region Y chromsome: shared paternal ancestry 9DNA region mtDNA: shared maternal ancestry 9Disease related region of interest: shared Identity by Descent (IBD) 9Extended length haplotypes in panmictic and diverse populatoions (e.g. Africa) signifies evolutionary selection DNA Diversity Markers Classification of DNA Diversity Markers Biological Type SNPs,STRs,CNVs,other Genomic Location Uniparental (non‐recombining): useful in tracing genealogies and sex biased demographic history Biparental (autosomal): useful in assessing "relatedness", in tracing evolutionary history of genomic regions, and in trait/disease phenotype mapping Demographic History Choice and combination depends on scientific, historical, genealogical, clinical or forensic question of interest t tttctccatttgtcgtgacacctttgttgacaccttcatttctgcattctcc aattctatttcactggtctatgg cagagaacacaaaatatggccagtggcctaaatccagcctactacctttttg tttttttttgtaacattttacta g t a t acatagccattcccatgtgtttccatga c tgtctgggctgcttttgcactctaatggcagagttaagaaattgtagc cagagaccacaatgcctcaaatatttactctacagccctttataaaaacagtgtgccaactcctgatttatgaa cttatcattatgtcaataccatactgtctttattactgtagttttataagtcatgacatcagataatgtaaatc SNPs: 3 million differencesg between individuals ctccaactttgtttttaatcaaaagtgttttggccatcctagatatactttgtattgccacataaatttgaagag c a tcagcctgtcagtgtctacaaaatagcatgctaggattttgatagggattgtgtagaatctatagattaattag t aggagaatgactatcttgacaatactgg 95% of thesectgcccctctgtattcgtggggga differences havettggttccacaacaacacccaccc no ccccactcggcaacccctgaaaccccca •Smaller percentagesacatcccccagcttttttcccctg encode phenotypicctaccaaaatccatggatgctca agtccatataaaatgccatactatttgdifferencesphenotypiccatataacctctgcaatcctcccc effects tatagtttagatcatctctagat tacttataatactaataaaatctaaatt gctatgtaaatagttgctatactgtgttgagggttttttgttttgttt t •An evenc smaller percentage causeg or c c ttgttttatttgtttgtttgtttgtattttaagagatggtgtcttgctttga ttgcccaggctggagtgcagtgg tgagatcatagcttactgcagcctcaapredispose to diseaseactcctggactcaaacagtcctcc or variable drug cacctcagcctcccaaagtgctgresponse ggatacaggtgtgacccactgtgccca•Population frequencygttattattttttatttgtattat may be “neutral’tttactgttgtattatttttaat or tattttttctgaatattttccatctataffectedInfluenced by “selection”agttggttgaatcatggatgtgga just by demographyacaggcaaatatggagggctaac tgtattgcatcttccagttcatgagtag tgcagtctctctgtttatttaaagttttagtttttctcaaccatgttt g a c a tacttttcagtatacaagactttgacgttttttgttaaatgtatttgtaagtattttattatttgtgatgttat ttaaaaagaaattgttgactgggcacagtggctcacgcctgtaatcccagcactttgggaggctgaggcgggca t g gatcacgaggtcaggagatcaagaccac tcctggctaacatggtaaaacccca gtctctactaaaaatagaaaaaa attagccaggcgtggtggcgagtgcctgtagtcccagctactcgggaggctg gaggcaggagaatggtgtgaacc g Useful to infer human originsc and tgggaggcggagcttgcagtgagctgagatcgtgccactgcattccagcctg gcgtgacagagcgagactctgtc a c aaaaaaataaataaaatttaaaaaaagmigrations andaagaagaaattattttcttaattt also in gene mappingcattttcaggttttttatttatt g t tctactatatggatacatgattgatttttgtatattgatcatgtatcctgcaaactagctaacatagtttattaa c tttctctttttttgtggattttaaaggattttctacatagataaataaacacacataaacagttttacttcttt g cttttcaacctagactggatgcattttttgtttttgtttgtttgtttgctttttaacttgctgcagtgactagaa gaatgtattgaagaatatattgttgaag caaaagcagtgagagtggacatccctgctttccccctgattttagggg a c ggaatgttttcagtctttcactatttaatatgattttagctataggtttatcctagatccctgttatcatgttg aggaaattcccttctatttctagtttgttgagattttttaattcatgtgattgcgctatctggctttgctctca Demographic factors affect the entire genome: founder , bottleneck, expansion, migration, admixture Selection: differential effect on specific genomic regions Evolutionary Medicine Adapted from Lluis Quintana-Murci McClellan and King Cell 2010 Common variants which passed evolutionary filter may Very many private rare variants which contribute to now be relevant to common disease due to increased common disease and have not passed evolutionary filter life expectancy (or change in adaptive forces: diet, drugs, other) Whole Exome Sequencing: Implications for Rare Variant Mapping Can High Risk Common Variants be Mapped? Population Genetics in Kidney Health and Disease Jewish Heritage Druze Heritage African Heritage •12 million Africans principally from three regions of West and South Africa were forcibly translocated to the Americas in ~ 400 years of slave trade (~ 1.5 M did not survive the voyage) •Subsequent admixture with Europeans to current genome wide African American population average of ~83% African Identify “ancestry” of chromosomal regions using DNA markers whose allele frequencies differ markedly between parent populations Admixture Generates Blocks of Linkage Disequilibrium (LD) greatly facilitating population-based gene mapping LinkageLinkage disequilibriumdisequilibrium Linkage Disequilibrium (LD) is the nonrandom association (at the population level) of two alleles on the same chromosome: AB? In equilibrium: PAB = PA * PB In disequilibrium: PAB > PA * PB LinkageLinkage DisequilibriumDisequilibrium (LD)(LD) IfIf alleleallele AA isis foundfound inin significantsignificant LDLD withwith thethe causativecausative alleleallele (B),(B), wewe shouldshould detectdetect associationassociation ofof alleleallele AA toto thethe examinedexamined phenotypephenotype AB In “conventional” genome wide association (GWAS), only loci A in sufficient physical proximity to causative locus B to mitigate recombination will be associated with the health or disease phenotype of interest Recombination Breaks Down LD recombination C AG 10 generations C AG 100 generations T AG C AG Admixture restores LD Mapping by Admixture Linkage Disequilibrium (MALD) Cases: admixed population with differential disease risk Controls: subjects or other chromosomal regions Adapted from Smith and O’Brien 2005 In the case of a parent populationFeasibility specific depends common on: variant which confers common disease risk– the genomic regions containing that• Populationvariant should disparity be significantly in disease enrich frequencyed in markers which “paint” the ancestry of the region in “cases”•Common compared variant to “controls” (in the at or risk compared population) to genomic regions which do not contribute (most of genome)•Admixture LD End Stage Kidney Disease (ESKD) ¾ESKD is the final common pathway of chronic kidney disease (CKD) and is fatal without renal replacement therapy by dialysis or transplantation (much of the developing world where kidney disease is increasing) ¾~550 North Americans (out of 40M with CKD) and ~5,000 Israelis 4.19 1.95 1 3.62 1.86 1 %AF <1 31.2 (24.3) 83.4 (16.3) 24 High Rates of Kidney Disease among HIV Positive African Americans Highleyman 2007 The most striking discrepancy is a > 10 fold greater risk for Kidney Disease (HIVAN) in HIV infected African Americans compared to HIV infected European Americans •Population disparities not readily attributable to socio-economic or environmental factors •Familial clustering of CKD and ESKD of varying etiologies in African Americans (Freedman 1999) OVERARCHING GENETIC RISK VARIANT (Freedman 1999) Non-diabetic ESKD in African Americans: Admixture scan Smith panel (Kao et al.) Smith panel (Kopp et al.) Tian + EMI panel (Shlush et al.) Bercovici et al. 2008 26 OR statistic for each SNP Admixture peak:
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