Large-scale Linkage Disequilibrium Mapping of Rheumatoid Arthritis-associated Genes in Japan ～ Results and Perspectives ～ February 4, 2006 Workshop on Immunology, Cancer and Aging 2006 Kyoto University Kyoto Japan Ryo Yamada Unit of Human Disease Genomics, CGM, Kyoto University, Kyoto Japan Lab. For Rheumatic Diseases, SRC, RIKEN, Yokohama, Japan

Biology Study to understand complex system A network of protein–protein interactions in yeast by Benno Schwikowski, Peter Uetz3 & Stanley Nature Biotechnology 18 : (2000)

What is a “Genetic Study” ? Inheritance –Relation between phenotype and inherited materials from parents to children Inheritance can be traced in pedigrees or can be estimated in the history of populations Interventional genetics Population genetics

Genetic studies –Controlled genetic interventions (Transgenics) Controlled, but impossible in humans. Controlled, but almost impossible to create transgenics of many genes in a strain. –Uncontrolled genetic interventions (Human population) Uncontrolled, but human samples are available. Uncontrolled, but many variations in many genes are combined.

Classification of assays into three from genetic approach standpoint 1.Non-genetic in vitro assays 2.Genetic assays with controlled interventions 3.Genetic evaluation with uncontrolled interventions “History”

Relation between Non-genetic Approach and Genetic Approach Molecular approach followed by genetic validation Genetic Approach followed by molecular validation Either way has a long way to go to understand this complexity.

Molecular Approach and Genetic Validation 1.Molecular Approach –in vitro analyses of a molecule and its interaction with surrounding molecules. 2.Genetic Validations –Controlled genetic interventions Transgenic animals –Targeted interventions of the coding gene counterpart in model animals (Tg,KO) and identification of correlation between the interventions and phenotypes. –Uncontrolled genetic interventions Mating history of human beings –Identification of native genetic variations in human population that mimic the targeted genetic interventions in models.

Genetic Approach and Molecular Validation 1.Genetic Approach –Dissection of combined effects of multiple variations in many genes on phenotypes in human. 2.Molecular Validation –Molecular assays to reveal causative links between genetic variations and phenotype manifestation. 3.Genetic Validation with Controlled Interventions –Transgenic animals are also used for validation of findings from genetic studies in human.

Genomic Approach 100 million (?) polymorphisms In 25,000 coding genes x 6 billion individuals A network of protein–protein interactions in yeast by Benno Schwikowski, Peter Uetz3 & Stanley Nature Biotechnology 18 : (2000) Too complicated interactions among genes. Where to start? First of all how to simplify in order to deal with?

First of all how to simplify in order to deal with? DNA-variations and their Effects on Transcripts, Peptides, Molecules … Phenotypes

Central Dogma & DNA Variations ＤＮ Ａ mRNA Peptide Transcription Translation Transcription initiation point Transcription termination point Splicing and mRNA maturation Translation initiation point Codon triplets Translation termination point Variations Post-translational peptide modifications Molecules

Multiple Branchings Sequence (qualitative) variations, quantitative variations, Chrono-spatial variations ＤＮＡ ｍＲＮＡ１ ｍＲＮＡ２ Ｐｅｐｔｉｄｅ１ Ｐｅｐｔｉｄｅ２ Ｐｅｐｔｉｄｅ３ Ｍｏｌｅｃｕｌｅ３ Ｍｏｌｅｃｕｌｅ２Ｍｏｌｅｃｕｌｅ１ Ｍｏｌｅｃｕｌｅ４ Transcript variations Peptide variations Molecular variations Gene-molecule network

ＤＮＡ ｍＲＮＡ１ ｍＲＮＡ２ Ｐｅｐｔｉｄｅ１ Ｐｅｐｔｉｄｅ２ Ｐｅｐｔｉｄｅ３ Ｍｏｌｅｃｕｌｅ３ Ｍｏｌｅｃｕｌｅ２Ｍｏｌｅｃｕｌｅ１ Ｍｏｌｅｃｕｌｅ４ Phenotype1 Phenotype2 Phenotype3 Phenotype4 Complex relation between gene- molecular network and phenotypes

ＤＮＡ ｍＲＮＡ１ ｍＲＮＡ２ Ｐｅｐｔｉｄｅ１ Ｐｅｐｔｉｄｅ２ Ｐｅｐｔｉｄｅ３ Ｍｏｌｅｃｕｌｅ３ Ｍｏｌｅｃｕｌｅ２ Ｍｏｌｅｃｕｌｅ１ Ｍｏｌｅｃｕｌｅ４ Phenotype1 Phenotype2 Phenotype3 Phenotype4 Genetic variations and network

Susceptible Non-susceptible Association study of Complex Traits with DNA-markers DNA RNA Peptides

Extreme example of simplification of genetic study Monogenic determination ～ Recessive trait ～ ＤＮＡ ｍＲＮＡ１ Ｐｅｐｔｉｄｅ１ Ｍｏｌｅｃｕｌｅ１ Disease mutation and mal-functional molecule Disease phenotype Non-disease phenotype Bijection (One-to-one) between DNA/mRNA/Protein variation and phenotype variation

Monogenic Trait Complex Trait Missense Silent Non-coding Depth of transmission of allele-specific molecular difference depends on type of polymorphism Missense mutation and significant change of molecular function Difference between rare diseases and common diseases

Susceptible Non-susceptible Association study of Complex Traits with DNA-markers DNA RNA Peptides How to simplify ?

Susceptible Non-susceptible Simplification of design DNA-mRNA-Protein relation is not straight, but comparison between DNA variations and phenotype variations bypassing mRNA/proteins simplifies the analysis structure.

DNA-analyses Data is Simple and Fixed throughout the Life. No quantitative, chronological or spatial variation is present for DNA polymorphisms. Birt Time course RNA, proteins and others DNA Time course Triggering Event Disease Manifest ations Diag nosi s Clinical F/U No observation In pre-clinical phase RNA, proteins and others DNA-specific simplification

Simplified –Quantitative, chronological and spatial variations are excluded. –The simplification potentially expands the capacity to incorporate different variations into DNA- phenotype analysis. Genetics-specific items could be included into the analysis because of the room created by simplification of study DNA

Another big world of heritable items (genes) Non-coding RNA x 23,000 in mammals Genetics-specific players Functional RNA-genes

Coding-gene World and Variations Coding DNA Coding mRNA Non-coding-gene World and Variations DNA Functional RNA Effects on transcription Effects on translation ?? Effects on phenotypes??

Large-scale LD mapping and Identification of RA-Susceptible PADI4 Polymorphisms and Follow-up Replication Studies ～ Coding-gene based approach ～

Genetics and Genetic Analysis of Rheumatoid Arthritis Twin and family studies –Relative risk to monozygotic twin ( λ MZ ) 12~62 –Relative risk to siblings (λ sib ) 2~17 –HLA locus explains 1/3-1/2 of total genetic components. –There are multiple non- HLA genes. Multiple linkage studies Many candidate- approach studies

Two Ways of Whole Genome LD Mapping Coding Gene-based Approach Map-based Approach Gene A Gene B Gene A Gene B Gene D Gene C Gene D

SNP distribution of RIKEN study

SNPs Samples Replication-based analysis SNPs Samples Stage 1 Stage 2 One-Stage Design Joint analysis SNPs Samples Stage 1 Stage 2 Two-Stage Design Michael Boehnke : Design Considerations in Large Scale Genetic Association Studies Design Considerations in Large Scale Genetic Association Studies HapMap Tutorials 836 vs. 658 two-stage joint screening

12,890 / 21,153 genes 12,890 （ 60.9% ） genes were evaluated with block/SNPs No. SNPs per gene and density of SNPs 5.0±6.4 /gene 0.2±0.3 /kb No. coding genes in autosomal chromosomes ： 21,153 Covered with SNPs not in block Covered with block Not covered 4,509 8,381 8,263 12,890 Gene k 20k 40k 30k 50k RIEN project started 27,283Genes

Major findings from SNP-based studies Japanese, Korean : RA-specific Caucasians : SLE RA and other autoimmunities Japanese : RA Caucasian : IBD Japanese : RA and other autoimmunities

MΦ Anti-oxydant transporter

PADI4 Missense SNPs Stability of transcript SLC22A4 Intronic SNPs Transcriptional regulation FCRL3 Transcriptional regulation PTPN22 Missense SNP Molecular function? RR ～ ２ Promoter SNP RR ～ ２

Multiple Genes and Multiple Diseases

PADI4 and anti-CCP antibody and RA PADI4 : Enzyme to produce citrullinated peptides anti-CCP antibody : RA-specific autoantibody to recognize citrulline- containing epitopes

Hypothetical mechanism of RA-susceptible variant

Rheumatoid Arthritis and PADI4 Citrulline and a-CCP Antibody Antiperinuclear Anti-keratin Anti-Sa Very many and heterogeneous autoantibodies are detectable in RA sera. Sensitivity and specificity vary. Some of RA-autoantibodies are extremely specific but their relatively low sensitivity limited their clinical utility. Their epitope target turned out to be common and citrulline residue in the molecules. Anti-CCP antibody has established as a reliable clinical marker of RA and they could predict development of RA several years before clinical onset. Citrulline is a non-coding native amino-acid and they are in proteins only after enzymatic conversion from arginine by PADI.

Anti-citrullinated peptide anyibody ~Most reliable autoantibody for RA

ＰＡＤＩ４ Ca 2+ -dependent post-translational modification Loss of ionic NH2+ of Arg residue Effects on intra- and inter- molecular interactions C=NH 2 + NH 2 CH 2 HCNH 3 + COO - NH C=O NH 2 CH 2 HCNH 3 + COO - NH ArginineCitrulline PADIs

この部分だけ！ PADI4 Citrullination Antigenicity Increased reactivity to citrullinated epitopes in T cells from human RA- prone HLA-transgenic mouse

K Arita M Sato et al. Nat Str & Mol Biol 2004 Tightly regulated reactions ＰＡＤＩ４ Ca 2+ -dependent post-translational modification

PADI-activation: Intracellularly under strict regulation of Ca 2+ concentration Extracellular leakage of enzymes

Association Plots in the PADI Cluster -log 10 (P) ＝５ PADI4

Enzyme substrate Missenes SNPs, but no allelic difference in enzyme activity.

RA-susceptible variant transcript is more stable.

Hypothetical mechanism of RA-susceptible variant

Replication studies on PADI4 padi_92 or padi_94 Asian Caucasian 3 “Positive” reports & 3 “Negative” reports

Caucasians Japanese PDCD1 MIF1CTLA4SLC22A4/A5 PTPN22TNFRSF1PADI4 Susceptible allele

Uncontrollable genetic interventions Only once. But multiple occasions on multiple regions and ethnic groups. Each population offers different information on genotype-phenotype relation. Ethnic / regional variations make genetic studies further complicated but offers more information to struggle with.

Ethnic variations

Japanese Caucasian 0W0 1M0 0W0 1M0 0M1 1M1 Assumption of common responsible variant Segregation

Perspectives Genetic determinants of prognosis and clinical responsiveness Coding genes and non-coding genes Ethnic diversity and genetic factors Combination of multiple genetic factors with or without environment factors

SNP Research Center, RIKEN, Yokohama, Japan –Lab. for Rheumatic Diseases Kazuhiko Yamamoto Akari Suzuki Yuta Kochi Mikako Mori Kyoko Kobayashi Miyako Yamanaka Emi Kanno Keiko Myouzen –Akihiro Sekine –Tatsuhiko Tsunoda –Yusuke Nakamura Clinical Institutes of Collaboration –University of Tokyo Hospitals Tetsuji Sawada –National Sagamihara Hospital Shigeto Tohma Toshihiro Matsui Center for Genomic Medicine, Kyoto University, Kyoto, Japan –Fumihiko Matsuda –Shohei Chida –Alexandre Vasilescu –Hitomi Hiratani –Sachiko Toyoda –Justine Yovo-Vasilescu –Chanavee Ratanajaraya –Miki Kokubo –Kenei Ohigashi –Victor Renault –Masao Yamaguchi –Katsura Hirosawa