Author
Lindsey A. Criswell
Other affiliations: University of California, Berkeley, University of California, Los Angeles, Mayo Clinic ...read more
Bio: Lindsey A. Criswell is an academic researcher from University of California, San Francisco. The author has contributed to research in topics: Lupus erythematosus & Population. The author has an hindex of 88, co-authored 312 publications receiving 33651 citations. Previous affiliations of Lindsey A. Criswell include University of California, Berkeley & University of California, Los Angeles.
Papers published on a yearly basis
Papers
More filters
Harvard University1, Broad Institute2, Monash University3, Kyoto University4, Genentech5, Vanderbilt University6, New York University7, NewYork–Presbyterian Hospital8, Second Military Medical University9, University of Queensland10, University of Toronto11, University of Groningen12, University of Tartu13, Beijing Jiaotong University14, Icahn School of Medicine at Mount Sinai15, Radboud University Nijmegen16, Medisch Spectrum Twente17, Leiden University18, University of Paris19, French Institute of Health and Medical Research20, University of Alabama at Birmingham21, University of Amsterdam22, GlaxoSmithKline23, University of Cambridge24, Hanyang University25, Spanish National Research Council26, Complutense University of Madrid27, Umeå University28, Boston University29, Council on Education for Public Health30, McGill University31, National Health Service32, University of Manchester33, University of Pittsburgh34, University of California, San Francisco35, Karolinska Institutet36, North Shore-LIJ Health System37, University of Chicago38, University of Tokyo39
TL;DR: A genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries provides empirical evidence that the genetics of RA can provide important information for drug discovery, and sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis.
Abstract: A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.
1,910 citations
1,514 citations
TL;DR: It is shown that the risk allele of a missense SNP in PTPN22 disrupts the P1 proline-rich motif that is important for interaction with Csk, potentially altering these proteins' normal function as negative regulators of T-cell activation.
Abstract: Rheumatoid arthritis (RA) is the most common systemic autoimmune disease, affecting ∼1% of the adult population worldwide, with an estimated heritability of 60%. To identify genes involved in RA susceptibility, we investigated the association between putative functional single-nucleotide polymorphisms (SNPs) and RA among white individuals by use of a case-control study design; a second sample was tested for replication. Here we report the association of RA susceptibility with the minor allele of a missense SNP in PTPN22 (discovery-study allelic P =6.6×10 −4 ; replication-study allelic P =5.6×10 −8 ), which encodes a hematopoietic-specific protein tyrosine phosphatase also known as "Lyp." We show that the risk allele, which is present in ∼17% of white individuals from the general population and in ∼28% of white individuals with RA, disrupts the P1 proline-rich motif that is important for interaction with Csk, potentially altering these proteins' normal function as negative regulators of T-cell activation. The minor allele of this SNP recently was implicated in type 1 diabetes, suggesting that the variant phosphatase may increase overall reactivity of the immune system and may heighten an individual carrier's risk for autoimmune disease.
1,501 citations
Brigham and Women's Hospital1, Harvard University2, Massachusetts Institute of Technology3, National Institutes of Health4, University of Toronto5, University of Manchester6, Celera Corporation7, Leiden University8, Karolinska Institutet9, University of Texas at Austin10, Radboud University Nijmegen Medical Centre11, University of California, San Francisco12, VU University Amsterdam13, University of Leeds14, University of Oxford15, University of Aberdeen16, The Feinstein Institute for Medical Research17, Karolinska University Hospital18, University of Groningen19, University of California, Davis20, King's College21, University of Amsterdam22, University of Sheffield23, Hoffmann-La Roche24, University Health Network25, North Shore-LIJ Health System26, Broad Institute27
TL;DR: Seven new rheumatoid arthritis risk alleles were identified at genome-wide significance (P < 5 × 10−8) in an analysis of all 41,282 samples, and an additional 11 SNPs replicated at P < 0.05, suggesting that most represent genuine rhearatoid arthritisrisk alleles.
Abstract: To identify new genetic risk factors for rheumatoid arthritis, we conducted a genome-wide association study meta-analysis of 5,539 autoantibody-positive individuals with rheumatoid arthritis (cases) and 20,169 controls of European descent, followed by replication in an independent set of 6,768 rheumatoid arthritis cases and 8,806 controls. Of 34 SNPs selected for replication, 7 new rheumatoid arthritis risk alleles were identified at genome-wide significance (P < 5 x 10(-8)) in an analysis of all 41,282 samples. The associated SNPs are near genes of known immune function, including IL6ST, SPRED2, RBPJ, CCR6, IRF5 and PXK. We also refined associations at two established rheumatoid arthritis risk loci (IL2RA and CCL21) and confirmed the association at AFF3. These new associations bring the total number of confirmed rheumatoid arthritis risk loci to 31 among individuals of European ancestry. An additional 11 SNPs replicated at P < 0.05, many of which are validated autoimmune risk alleles, suggesting that most represent genuine rheumatoid arthritis risk alleles.
1,277 citations
University of Oklahoma1, Oklahoma Medical Research Foundation2, Veterans Health Administration3, Uppsala University4, University of California, San Francisco5, University of Southern California6, University of Alabama at Birmingham7, University of Minnesota8, University of California, Los Angeles9, Hammersmith Hospital10, Wake Forest University11, Broad Institute12, North Shore-LIJ Health System13, Genentech14, University of California, Riverside15, Université de Montréal16, Medical University of South Carolina17, University of California, Davis18, University of Texas Southwestern Medical Center19
TL;DR: The results show that numerous genes, some with known immune-related functions, predispose to SLE, and evidence of association with replication is found at FCGR2A, PTPN22 and STAT4, regions previously associated with SLE and other autoimmune diseases.
Abstract: Systemic lupus erythematosus (SLE) is a common systemic autoimmune disease with complex etiology but strong clustering in families (lambda(S) = approximately 30). We performed a genome-wide association scan using 317,501 SNPs in 720 women of European ancestry with SLE and in 2,337 controls, and we genotyped consistently associated SNPs in two additional independent sample sets totaling 1,846 affected women and 1,825 controls. Aside from the expected strong association between SLE and the HLA region on chromosome 6p21 and the previously confirmed non-HLA locus IRF5 on chromosome 7q32, we found evidence of association with replication (1.1 x 10(-7) or =9 other loci (P < 2 x 10(-7)). Our results show that numerous genes, some with known immune-related functions, predispose to SLE.
1,253 citations
Cited by
More filters
28 Jul 2005
TL;DR: PfPMP1）与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。
18,940 citations
[...]
TL;DR: The role of vitamin D in skeletal and nonskeletal health is considered and strategies for the prevention and treatment ofitamin D deficiency are suggested.
Abstract: Once foods in the United States were fortified with vitamin D, rickets appeared to have been conquered, and many considered major health problems from vitamin D deficiency resolved. But vitamin D deficiency is common. This review considers the role of vitamin D in skeletal and nonskeletal health and suggests strategies for the prevention and treatment of vitamin D deficiency.
11,849 citations
Journal Article•
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
9,847 citations
TL;DR: This study has demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in theBritish population is generally modest.
Abstract: There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.
9,244 citations
National Institutes of Health1, University of Chicago2, Duke University3, Harvard University4, University of Oxford5, GlaxoSmithKline6, Johns Hopkins University7, Yale University8, deCODE genetics9, Princeton University10, Howard Hughes Medical Institute11, Washington University in St. Louis12, University of California, Berkeley13, Stanford University14, University of Michigan15, Cornell University16, University of Washington17, University of Queensland18, Vanderbilt University19, North Carolina State University20, QIMR Berghofer Medical Research Institute21
TL;DR: This paper examined potential sources of missing heritability and proposed research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
Abstract: Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
7,797 citations