Over the last decade biomedical research has seen tremendous advancements in the field of genetics that enables unlimited access to >60 vertebrate genomes—including the human and mouse genomes, two of the most widely studied species in biomedical research. These advancements are largely due to rapid development of high throughput sequencing technologies such as next-generation sequencing (NGS) technologies that allow for more affordable and efficient sequencing compared to traditional Sanger technology. The availability of the entire human genome sequence has accelerated our efforts to gain insight into the genetics underlying human disease. Such efforts include Genome-Wide Association Studies (GWAS) — a widely used approach that examines the association between common genetic variants and specific human disease traits. GWAS has led to the successful identification of a large number of SNPs that are linked with chronic diseases ranging from Crohn’s disease, systemic lupus erythermatosus (SLE), type I diabetes (T1D), and many other common western world diseases(reviewed by Visscher et al.1). On the other hand, genetic deficiencies that cause severe disease—such as primary immunodeficiency diseases associated with a poor survival— represent mostly rare mutations within the human population2. Such patients can be found in pediatric clinics and more often than not, the genetic deficiencies underlying disease remain elusive. The availability of NGS, however, offers exciting new opportunities in that it enables the identification of all genome-wide variants in individual patients for limited costs. Nonetheless, both approaches are faced with a significant challenge to identify the causal variants. First of all, most GWAS identify loci that contain more than one SNP but more importantly, SNP maps are incomplete and require in depth probing of the identified genetic region (reviewed by Visscher et al.1). Thus the approach is generally not limited to a single SNP, but rather uncovers multiple gene candidates for a single locus and researchers are often left with the critical question to identify variant causality. This is further complicated by the fact that GWAS is often used for the analysis of complex polygenic traits where gene variants need to exist in combination with one other to assert an effect. In the case of monogenic traits underlying severe disease phenotypes, linkage analysis is rarely an option, whereas whole genome sequencing likely results in the identification of numerous “unique” variants. The biological consequences of such variants would again need to be confirmed and candidate gene selections are guided by
Providing insight into the functional genome is not just limited to understanding gene or protein function, but also includes gene regulation and complex interactions with other genes within the context of cellular or organismal function. The mammalian genome is believed to consist of ~22,000 annotated genes—most of which have been poorly described. In addition, there is almost an unlimited number of phenotypes to be probed, making this an even more daunting task. Nonetheless, experimental models, including fruit fly and mouse models, have been extremely valuable in revealing unique insight into gene function. Typically, forward and reverse genetic approaches have been applied in parallel to uncover gene function. Reverse genetics begins with the creation of a genetic change and ends with the identification of a phenotype. This approach is hypothesis-based and assumes a specific gene function up front. On the other hand, forward (or classical) genetics proceeds from phenotype to the identification of a causal genetic change (SNP or mutation). This approach has led to important discoveries in the field of immunology most notably the identification of TLR4 as the sole LPS receptor3— a discovery recently awarded with the Nobel Prize. Until a few years ago, identification of such genetic variants required positional cloning. This was once considered an arcane art, requiring significant effort, time and financial resources. However, the current availability of the genome sequence for most inbred mouse strains has eliminated the need for contig construction and trivialized the identification of informative markers for high-resolution mapping and/or the identification of existing variants within an associated chromosomal region. Moreover, low cost high-throughput DNA sequencing has accelerated the process of finding unique mutations either introduced spontaneously or by following treatment with mutagens. The current limitation for forward genetics is rather the restricted number of strong monogenic phenotypes, something also referred to as the “phenotype gap”4. To overcome this limitation, germline mutagenesis— in which random mutations are introduced in spermatogonial stem cells— has proven to be an effective approach to expand the number of phenotypes.
2. N-ethyl-N-nitrosourea mutagenesis
In mice, a widely used mutagen to create and expand the number of phenotypes is the alkylating agent N-ethyl-N-nitrosourea (ENU). ENU is a powerful mutagen that according to our latest estimates can introduce more than 3 base-pair changes per million base-pairs of genomic DNA5. ENU introduces point mutations in spermatogonial stem cells, predominantly affecting A/T base pairs (44% A/T→T/A transversions and 38% A/T→G/C transitions), whereas at the protein level, ENU primarily results in missense mutations (64% missense, 26% splicing errors and 10% nonsense mutations)6. With three bp changes per million bps and a total length of ~2,717 Mb for the mouse genome, one can calculate that each G1 male carries ~8,000 bp changes genome-wide. With the coding region being 1.3% of total genomic sequence and 76% of random bp changes creating a coding change, it follows that each G1 mouse carries about 80 coding changes genome-wide, according to our latest estimates. These exist in a heterozygous form and do not necessarily cause a phenotype. In our experience, the majority of ENU-induced mutations, behave as recessive traits or are codominant at best. The approach entails a weekly injection of ~90mg/kg ENU for 3 weeks that is followed by a brief period of sterility for up to 12 weeks. After the recovery period, each G0 male is bred to untreated, wild type C57BL/6 female mice to generate G1 offspring. These G1 animals are then either used for phenotypic screens or can be used to produce G2 mice, which in turn are backcrossed to the G1 male to generate G3 offspring. While screening the G1 population for phenotypes is limited to the identification of dominant mutations, screening of G3 mice allows for the discovery of recessive mutations. Although the total number of base-pair changes in G3 mice will be reduced—each mouse will carry ~11 coding changes in homozygous form—this has proven to be the more powerful approach to capture mice with phenotypes of interest and more importantly allows for the retrieval of lethal phenotypes.
The rate-limiting step in ENU mutagenesis has long been the identification of causative mutations. Until recently, identified mutant lines were outcrossed to genetically different inbred strains and often the analyses of hundreds if not thousands of meiosis were needed to obtain a small enough critical region that could be sequenced. However, the availability of NGS has significantly facilitated the process of variant identification. Currently, targeted exon-enrichment—i.e. targeting exonic sequence within a critical region using sequence capture probes—, whole-exome and whole-genome sequencing are all proven strategies to effectively uncover mutations. The coverage of (targeted) genomic DNA is often exceptional, particularly for the exon-enrichment approach, where generally high quality sequence (minimal depth >10) for more than >98 % of the targeted region can be obtained5. Nonetheless, causality of the identified mutations remains a critical aspect of this approach and low resolution mapping (generally < 30 meioses) and/or genetic confirmation are still integral parts of the ENU mutagenesis approach. In addition, the availability of NGS also provides further opportunities for the phenotypic probing of ENU germline mutants. Often, phenotypes identified in ENU germline mice are lost or significantly influenced by modifier loci located on outcross strains carrying a high degree of genetic variation. For example, identification of genes required for optimal NK cell function has been difficult because of the large variation in NK cell ligands/receptors existing on different mouse backgrounds (Hoebe, unpublished results). By being able to analyze and sequence large genomic regions, fine mapping is superfluous and the exploration of subtle phenotypes can be traced following an outcross to strains with minimal genetic variation between the outcross and parent ENU strain. Ultimately, the genetic diversity should be just enough to allow low-resolution linkage analysis—a prime example being the genetic diversity between C57BL/6J and C57BL/10J strains.
3. Unraveling lymphocyte immune function using ENU mutagenesis
As referred to above, a critical aspect of ENU mutagenesis is the (biological) field of interest to be probed. ENU mutagenesis has been used to define the genetic footprint of a wide variety of phenotypes, including visible, behavioral, developmental and immunological phenotypes7. Nonetheless, its success is depending on: 1) the use of reliable screening assays with limited biological variation, 2) targeting large genomic footprints, and 3) probing a biological phenotype that is poorly defined. Our laboratory has used ENU mutagenesis to identify genes with non-redundant function in lymphocyte development, priming or effector function. Among the biological screens we apply is an
4. Gimap5 and loss of immunological tolerance driving auto-immune diseases
Using N-ethyl-N-nitrosourea (ENU) germline mutagenesis, our laboratory previously identified Gimap5-deficient mice—designated
Gimap5 is part of the family of Gimap genes which are predominantly expressed in lymphocytes and regulate lymphocyte survival during development and homeostasis 13. Gimap proteins contain a GTP-binding AIG1 homology domain, first identified in disease-resistance genes in higher plants9,10. More recent crystallographic studies showed that the Gimap proteins resemble a nucleotide coordination and dimerization mode previously observed for dynamin GTPase—a component essential for the scission and fusion of cellular vesicular compartments such as endosomes at the cell surface or the Golgi apparatus in the cytosol14. Members of the Gimap family appear to be localized to different subcellular compartments with Gimap5 reported to localize in lysosomes based on studies in human, mouse and rat lymphocytes15. Overall, the function of these proteins and their role in disease development remain poorly defined.
Genetic aberrancies in Gimap5 have been strongly linked to reduced lymphocyte survival and homeostasis, but importantly have also been associated with autoimmune diseases. In humans, polyadenylation polymorphisms in GIMAP5—causing relative modest changes in GIMAP5 RNA expression—were associated with increased concentrations of IA2 auto-antibodies in type 1 diabetes (T1D) patients and an increased risk of systemic lupus erythematosus (SLE)16,17. Studies using biobreeding (BB) rats— carrying a mutation (
Given the important role of regulatory T cells in immune-mediated sequelae induced by CD4+ T cells undergoing LIP, our laboratory assessed whether the colitis was driven by abnormalities in regulatory T cell development or function. Although relatively normal numbers of Foxp3+ Treg cells are found in 3-week-old mice, a loss of Treg cell numbers is observed by 6 weeks of age particularly in the MLNs34. In addition, regulatory T cells in
Interestingly, the T cell phenotypes in
5. Mutations in hematopietic protein 1; an immunodeficiency resulting in loss of a broad range of immunological functions
Genetic aberrancies causing severe combined immunodeficiency (SCID) are generally rare and associated with a high morbidity and/or mortality. They often present significant challenges in terms of treatment due to the wide variety of immune cells that can be affected. Therefore, besides defining the genetic footprint underlying SCID, a critical challenge lies in obtaining a thorough understanding of the degree of the immunodeficiency presented by specific mutations in genes, including defining the types of immune cells affected and functional aberrancies observed. Our laboratory previously identified a germline mutant, designated
To identify the causative mutation in
Hem1 is part of the Wiskott-Aldrich syndrome protein family Verprolin-homologous protein (WAVE) protein complex in hematopoietic cells regulating cell mobility and intracellular processes requiring rearrangement of the cytoskeleton following immuno-receptor activation, including B and T cell, chemokine and innate immune receptors such as Toll-like receptors. Specifically, receptor triggering causes activation of Rho family of Guanosine triphosphatases (GTPases) such as CDC42, RhoA and Rac ultimately resulting in the activation of downstream adaptor complexes involved in the regulating of actin (de)polymerization. For hematopoietic cells, the adaptor complexes Wiskott-Aldrich syndrome protein (WASP) and WAVE are particularly important for the control of actin polymerization45-48. The hematopoietic cell-specific WAVE complex consists of a pentameric subunit complex including, Sra-1 (Specifically Rac-associated protein-1), Hem1, Abi (Abelson interactor 1 or 2), WAVE, and HSPC300 (Hematopoietic stem/progenitor cell protein 300)49. Under non-stimulated conditions, the WAVE complex is inactive, but following immunoreceptor activation, GTP-bound Rac binds the pentameric complex presumably through Sra149. In addition, this complex requires binding of phophatidylinositol (3,4,5) triphosphate (PIP3) interaction and phosphorylation by kinases50, including Abl kinase and Mitogen-activated protein kinases51. Ultimately, this results in a conformational change revealing the WAVE-specific VCA (Verprolin-homology, Cofillin-homology, and acidic) region and allow interaction with the actin-regulatory complex (Arp2/3), ultimately converting monomeric actin (G-actin) into filamentous actin (F-actin). Interestingly, the absence of individual subunit components often causes the degradation of all components of the WAVE complex resulting in aberrant actin polymerization. The consequences of deregulated actin polymerization in hematopoietic cells are wide-ranging and affect broad immunological functions, including but not limited to: 1) leukocyte migration/chemotaxis, 2) loss of immune synapse formation affecting T and B cell receptor signaling (thereby affecting T cell function and development), 3) leukocyte adhesion, and 4) DC-specific phagocytosis and their ability to cross present/prime T cells. As such, mutations in the specific subunit components of the WAVE complex resulting in abnormal gene expression/function cause severe combined immunodeficiencies that stretch beyond lymphocyte populations also affecting granulocyte function and are predicted to correlate with high mortality/morbidity.
6. Implications for human PID
Assessing the immune system using ENU mutagenesis in mice has previously led to important breakthrough discoveries in understanding the genetics in human patients with PID. A prime example is the identification of the
With regard to the
Finally, perhaps due to its indispensable role in a wide variety of immune pathways, mutations in human HEM1 leading to dysregulated actin polymerization, have thus far not been reported. Nonetheless, over- or under-expression of HEM1 is associated with disease prognosis in leukemia54. Specifically, HEM1 overexpression in B-cell chronic lymphocytic leukemia (CLL) is associated with a poor outcome, whereas down-regulation of HEM1 expression in CLL cells rendered tumor cells more susceptible to fludarabine-mediated killing54. These findings may indicate the critical role for HEM1 in invasion and/or metastasis of tumor cells from hematopoietic origin.
7. Concluding remarks
A major challenge in the field of genomics is to obtain a comprehensive understanding of the functions of all annotated mammalian genes. Whereas identification and analysis of genome wide SNPs and/or unique nucleotide changes are drastically improved following the development of next generation sequencing technologies, understanding the consequences of such genetic variants remains a major challenge in virtually all biomedical fields. ENU mutagenesis provides one approach that is both powerful and unbiased, uncovering gene function by introducing the sort of genetic abnormalities that can be observed in human patients (e.g. primary immuno-deficiencies). Ultimately, utilization of both forward and reverse genetic approaches will be instrumental in closing the existing phenotype gap and will help us understand the association between identified genetic variants, the implications for protein and biological function, and human disease.
This research was funded by grants from the NIH, including NIH/NIAID RO1 Grant 00426912 and PHS Grant P30 DK078392 (Integrative Morphology Core of the Cincinnati Digestive Disease Research Core Center)
Five years of GWAS discovery. Am J Hum Genet Visscher P. M. MA Brown Mc Carthy. M. I. Yang J. 2012 90 7 24
Primary immunodeficiencies of protective immunity to primary infections. Clin Immunol Bousfiha A. Picard C. Boisson-Dupuis S. Zhang S. Y. Bustamante J. Puel A. et al. 2010 135 204 9
- 3. Poltorak A, He X, Smirnova I, Liu MY, Van Huffel C, Du X, et al. Defective LPS signaling in C3H/HeJ and C57BL/10ScCr mice: mutations in Tlr4 gene. Science 1998; 282:2085-8.
Combining mutagenesis and genomics in the mouse--closing the phenotype gap. Trends Genet Brown S. D. Peters J. 1996 12 433 5
- 5. Sheridan R, Lampe K, Shanmukhappa SK, Putnam P, Keddache M, Divanovic S, et al. Lampe1: an ENU-germline mutation causing spontaneous hepatosteatosis identified through targeted exon-enrichment and next-generation sequencing. PLoS One 2011; 6:e21979.
- 6. Justice MJ, Noveroske JK, Weber JS, Zheng B, Bradley A. Mouse ENU mutagenesis. HumMolGenet 1999; 8:1955-63.
Precis on forward genetics in mice. NatImmunol Beutler B. Du X. Xia Y. 2007 8 659 64
NK-cell-mediated killing of target cells triggers robust antigen-specific T-cell-mediated and humoral responses. Blood Krebs P. MJ Barnes Lampe. K. Whitley K. Bahjat K. S. Beutler B. et al. N. 2009 113 6593 602
Chronic polyarthritis caused by mammalian DNA that escapes from degradation in macrophages. Nature Kawane K. Ohtani M. Miwa K. Kizawa T. Kanbara Y. Yoshioka Y. et al. 2006 443 998 1002
Toll-like receptor-independent gene induction program activated by mammalian DNA escaped from apoptotic DNA degradation. JExpMed Okabe Y. Kawane K. Akira S. Taniguchi T. Nagata S. 2005 202 1333 9
- 11. Tsukumo S, Yasutomo K. DNaseI in pathogenesis of systemic lupus erythematosus. ClinImmunol 2004; 113:14-8.
- 12. Barnes MJ, Aksoylar H, Krebs P, Bourdeau T, Arnold CN, Xia Y, et al. Loss of T cell and B cell quiescence precedes the onset of microbial flora-dependent wasting disease and intestinal inflammation in Gimap5-deficient mice. J Immunol 2010; 184:3743-54.
- 13. Nitta T, Nasreen M, Seike T, Goji A, Ohigashi I, Miyazaki T, et al. IAN family critically regulates survival and development of T lymphocytes. PLoSBiol 2006; 4:e103.
Structural basis of oligomerization in septin-like GTPase of immunity-associated protein 2 (GIMAP2). Proc Natl Acad Sci U S A Schwefel D. Frohlich C. Eichhorst J. Wiesner B. Behlke J. Aravind L. et al. 2010 107 20299 304
- 15. Wong V, Saunders A, Hutchings A, Pascall J, Carter C, Bright N, et al. The auto-immunity-related GIMAP5 GTPase is a lysosome-associated protein. self/Nonself 2010; 1:9.
- 16. Hellquist A, Zucchelli M, Kivinen K, Saarialho-Kere U, Koskenmies S, Widen E, et al. The human GIMAP5 gene has a common polyadenylation polymorphism increasing risk to systemic lupus erythematosus. J Med Genet 2007; 44:314-21.
- 17. Shin JH, Janer M, McNeney B, Blay S, Deutsch K, Sanjeevi CB, et al. IA-2 autoantibodies in incident type I diabetes patients are associated with a polyadenylation signal polymorphism in GIMAP5. Genes Immun 2007; 8:503-12.
- 18. Hornum L, Romer J, Markholst H. The diabetes-prone BB rat carries a frameshift mutation in Ian4, a positional candidate of Iddm1. Diabetes 2002; 51:1972-9.
Genetic dissection of autoimmune type I diabetes in the BB rat. NatGenet Jacob H. J. Pettersson A. Wilson D. Mao Y. Lernmark A. Lander E. S. 1992 2 56 60
Lymphopenia in the BB rat model of type 1 diabetes is due to a mutation in a novel immune-associated nucleotide (Ian)-related gene. Genome Res Macmurray A. J. Moralejo D. H. Kwitek A. E. Rutledge E. A. Van Yserloo B. Gohlke P. et al. 2002 12 1029 39
- 21. Ramanathan S, Poussier P. BB rat lyp mutation and Type 1 diabetes. ImmunolRev 2001; 184:161-71.
- 22. van den Brandt J, Fischer HJ, Walter L, Hunig T, Kloting I, Reichardt HM. Type 1 diabetes in BioBreeding rats is critically linked to an imbalance between Th17 and regulatory T cells and an altered TCR repertoire. J Immunol 2010; 185:2285-94.
Eosinophilic bowel disease controlled by the BB rat-derived lymphopenia/Gimap5 gene. Gastroenterology Cousins L. Graham M. Tooze R. Carter C. Miller J. R. Powrie F. M. et al. 2006 131 1475 85
- 24. Podolsky DK. Inflammatory bowel disease. N Engl J Med 2002; 347:417-29.
Xavier RJ, Podolsky DK.Unravelling the pathogenesis of inflammatory bowel disease. Nature 2007 448 427 34
- 26. Lees CW, Barrett JC, Parkes M, Satsangi J. New IBD genetics: common pathways with other diseases. Gut 2011.
Mackay IR.Clustering and commonalities among autoimmune diseases. J Autoimmun 2009 33 170 7
- 28. Khoruts A, Fraser JM. A causal link between lymphopenia and autoimmunity. Immunol Lett 2005; 98:23-31.
Homeostatic expansion of T cells during immune insufficiency generates autoimmunity. Cell King C. Ilic A. Koelsch K. Sarvetnick N. 2004 117 265 77
- 30. Krupica T, Jr., Fry TJ, Mackall CL. Autoimmunity during lymphopenia: a two-hit model. Clin Immunol 2006; 120:121-8.
Analysis of intestinal lymphocytes in mouse colitis mediated by transfer of CD4+, CD45RBhigh T cells to SCID recipients. J Immunol Aranda R. Sydora B. C. Mc Allister P. L. Binder S. W. Yang H. Y. Targan S. R. et al. 1997 158 3464 73
Regulatory interactions between CD45RBhigh and CD45RBlow CD4+ T cells are important for the balance between protective and pathogenic cell-mediated immunity. J Exp Med Powrie F. Correa-Oliveira R. Mauze S. Coffman R. L. 1994 179 589 600
Phenotypically distinct subsets of CD4+ T cells induce or protect from chronic intestinal inflammation in C. B-17 scid mice. Int Immunol Powrie F. Leach M. W. Mauze S. Caddle L. B. Coffman R. L. 1993 5 1461 71
Loss of Immunological Tolerance in Gimap5-Deficient Mice Is Associated with Loss of Foxo in CD4+ T Cells. J Immunol Aksoylar H. I. Lampe K. MJ Barnes Plas. D. R. Hoebe K. 2012 188 146 54
Cloning and characterization of three human forkhead genes that comprise an FKHR-like gene subfamily. Genomics MJ Anderson Viars. C. S. Czekay S. Cavenee W. K. Arden K. C. 1998 47 187 99
Biggs WH, 3rd, Cavenee WK, Arden KC.Identification and characterization of members of the FKHR (FOX O) subclass of winged-helix transcription factors in the mouse. Mamm Genome 2001 12 416 25
Abnormal angiogenesis in Foxo1 (Fkhr)-deficient mice. J Biol Chem Furuyama T. Kitayama K. Shimoda Y. Ogawa M. Sone K. Yoshida-Araki K. et al. 2004 279 34741 9
- 38. Kerdiles YM, Beisner DR, Tinoco R, Dejean AS, Castrillon DH, DePinho RA, et al. Foxo1 links homing and survival of naive T cells by regulating L-selectin, CCR7 and interleukin 7 receptor. NatImmunol 2009; 10:176-84.
An essential role of the Forkhead-box transcription factor Foxo1 in control of T cell homeostasis and tolerance. Immunity Ouyang W. Beckett O. Flavell R. A. Li M. O. 2009 30 358 71
- 40. Tothova Z, Gilliland DG. FoxO transcription factors and stem cell homeostasis: insights from the hematopoietic system. Cell Stem Cell 2007; 1:140-52.
Foxo transcription factors control regulatory T cell development and function. Immunity Kerdiles Y. M. Stone E. L. Beisner D. L. MA Mc Gargill Ch’en. I. L. Stockmann C. et al. 2010 33 890 904
Foxo proteins cooperatively control the differentiation of Foxp3+ regulatory T cells. Nat Immunol Ouyang W. Beckett O. Ma Paik Q. De Pinho J. H. Li R. A. M. O. 2010 11 618 27
- 43. Gomis RR, Alarcon C, He W, Wang Q, Seoane J, Lash A, et al. A FoxO-Smad synexpression group in human keratinocytes. Proc Natl Acad Sci U S A 2006; 103:12747-52.
Integration of Smad and forkhead pathways in the control of neuroepithelial and glioblastoma cell proliferation. Cell Seoane J. Le Shen H. V. Anderson L. Massague S. A. J. 2004 117 211 23
- 45. Park H, Chan MM, Iritani BM. Hem-1: putting the "WAVE" into actin polymerization during an immune response. FEBS Lett 2010; 584:4923-32.
- 46. Park H, Staehling-Hampton K, Appleby MW, Brunkow ME, Habib T, Zhang Y, et al. A point mutation in the murine Hem1 gene reveals an essential role for Hematopoietic protein 1 in lymphopoiesis and innate immunity. J Exp Med 2008; 205:2899-913.
Thrasher AJ, Burns SO. WASP: a key immunological multitasker.Nat Rev Immunol 2010 10 182 92
Dominant negative mutation of the hematopoietic-specific Rho GTPase, Rac2, is associated with a human phagocyte immunodeficiency. Blood Williams D. A. Tao W. Yang F. Kim C. Gu Y. Mansfield P. et al. 2000 96 1646 54
Purification and architecture of the ubiquitous Wave complex. Proc Natl Acad Sci U S A Gautreau A. Ho H. Y. Li J. Steen H. Gygi S. P. Kirschner M. W. 2004 101 4379 83
Lebensohn AM, Kirschner MW.Activation of the WAVE complex by coincident signals controls actin assembly. Mol Cell 2009 36 512 24
Danson CM, Pocha SM, Bloomberg GB, Cory GO. Phosphorylation of WAVE2 by MAP kinases regulates persistent cell migration and polarity.J Cell Sci 2007 120 4144 54
Herpes simplex virus encephalitis in human UNC-93B deficiency. Science Casrouge A. Zhang S. Y. Eidenschenk C. Jouanguy E. Puel A. Yang K. et al. 2006 314 308 12
Lim MK, Sheen DH, Kim SA, Won SK, Lee SS, Chae SC, et al. IAN5 polymorphisms are associated with systemic lupus erythematosus.Lupus 2009 18 1045 52
Joshi AD, Hegde GV, Dickinson JD, Mittal AK, Lynch JC, Eudy JD, et al. ATM, CTLA4, MNDA, and HEM1 in high versus low CD38 expressing B-cell chronic lymphocytic leukemia.Clin Cancer Res 2007 13 5295 304