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Discovery and Functional Impact of Common and Rare Variants in RA

Discovery and Functional Impact of Common and Rare Variants in RA
RA 常见和罕见变异的发现及其功能影响
批准号:
8576206
负责人:
Soumya Raychaudhuri
金额:
$37.49万
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-08-02 至 2018-07-31

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英文摘要
DESCRIPTION (provided by applicant): Genome-wide association studies (GWAS) and related approaches have identified >60 rheumatoid arthritis (RA) risk loci. Despite this, many alleles remain to be discovered to account for heritability estimates observed in families. We have published data that most common RA risk alleles are shared across diverse ethnic groups. In Aim 1, we will exploit this observation to discover new RA risk alleles - we will conduct a multi- ethnic GWAS of ~20,000 RA cases and 60,000 matched controls (Asian and European ancestry). We will also compare and contrast genetic findings across two ethnic groups, and develop new analytical methods. We have data (manuscript in press) that RA risk genes identified from GWAS harbor rare alleles that contribute to risk of RA. Together with data from other diseases, this leads to the hypothesis that causal genes at RA risk loci discovered by GWAS will contain independent, protein-coding mutations (most of which will be rare in the general population). In Aim 2, we will test this hypothesis by sequencing all genes (~650 in total) identified by GWAS in 1,300 RA case and 1,300 non-RA controls of European ancestry. We will also sequence ~2,000 RA case-control samples of Asian ancestry in order to compare and contrast genetic findings across two ethnic groups. We will perform genetic burden tests to determine which genes harbor more rare risk alleles in cases compared to controls than would be expected by chance. However, finding causal variants and genes is only the first step in translating genetic discoveries to improved patient care, and drug discovery in particular. We hypothesize that genes with an allelic series (i.e., multiple alleles that influence disease risk) re excellent drug targets, especially genes that carry loss-of-function (LOF) alleles that protect from disease. We have unpublished data on one RA risk locus that demonstrates our ability to progress from a GWAS to a high-throughput screen (HTS) of ~2,000 small molecules. In Aim 3 we will extend this approach to new RA risk genes: for at least one gene, we will understand the functional consequences of new RA risk alleles using cutting-edge molecular techniques (e.g., TALENs, RNAi), and use this information to conduct an HTS. Together, these three Aims will (1) discover new RA risk loci using GWAS in Europeans and Asians, (2) discover rare RA risk alleles at causal genes from GWAS loci (also in Europeans and Asians), and (3) translate genetic discoveries into new biology and an HTS of small molecule compounds. IMPACT: We will build upon our past accomplishments to perform the most comprehensive genetic study of RA to date (from common to rare alleles). We will develop innovative methods for integrating GWAS and sequence data, as well as innovative methods to use human genetics to guide drug discovery. Our team has all of the experience and resources to accomplish these Aims.
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Integrative analysis of high dimensional tissue molecular data to define key biological systems in autoimmune diseases (SBC)
  • 批准号:
    10450354
  • 项目类别:
  • 资助金额:
    $30.0万
  • 财政年份:
    2022
  • 负责人:
    Soumya Raychaudhuri
  • 依托单位:
Integrative analysis of high dimensional tissue molecular data to define key biological systems in autoimmune diseases (SBC)
  • 批准号:
    10687728
  • 项目类别:
  • 资助金额:
    $28.29万
  • 财政年份:
    2022
  • 负责人:
    Soumya Raychaudhuri
  • 依托单位:
Integrative analysis of high dimensional tissue molecular data to define key biological systems in autoimmune diseases (SBC)
  • 批准号:
    10594505
  • 项目类别:
  • 资助金额:
    $60.0万
  • 财政年份:
    2022
  • 负责人:
    Soumya Raychaudhuri
  • 依托单位:
Computational systems immunology core
  • 批准号:
    10598096
  • 项目类别:
  • 资助金额:
    $55.95万
  • 财政年份:
    2021
  • 负责人:
    Soumya Raychaudhuri
  • 依托单位:
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