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Non-Hodgkin Lymphoma
Published in Tariq I. Mughal, Precision Haematological Cancer Medicine, 2018
Waldenström’s macroglobulinemia (WM) has a key driver mutation, MYD88L265P, in >95% of the patients; other important mutations are CXCR4 (40%), ARID1A (17%) and CD79B (15%). Copy number alterations (CNAs) resulting in gene losses occur in PRDM2 (93%), BTG1 (87%), HIVEP2 (77%), MLKN1 (77%), PLEKHG1 (70%), LYN (60%), ARID1B (50%) and FOXP1 (37%). The most common cytogenetic deletions are in chromosome 6q, which mostly overlaps with the CNAs, and comprise of losses in PLEKHG1, HIVEP2, ARID1B and BCLAF1. Mutations in MYD88, which is associated with Toll-like receptor (TLR) and interleukin-1 receptor signalling, mediating IRAK1 and IRAK4, is involved in the NFĸB signalling by direct interaction with BTK.
Emerging roles of noncoding RNAs in T cell differentiation and functions in autoimmune diseases
Published in International Reviews of Immunology, 2019
Systemic lupus erythematosus (SLE) is a systemic autoimmune disorder characterized by the production of autoantibodies against dsDNA and other nuclear antigens. Autoantibodies activate complement system leading to tissue destruction. Whole transcriptome analysis has identified the involvement of lncRNAs in SLE, as both upregulation and downregulation of some lncRNAs were found to be associated with SLE. For example, lncRNAs FNDC1, linc0949, linc0597 were found to be downregulated while lncRNAs, TAGP, HIVEP2, SOD2, WTAP and ACAT2 were found to be upregulated in SLE [40]. The mechanism of this differential expression of lncRNAs in SLE is yet to be defined. Nonetheless, combination of up and downregulated lncRNAs could potentially be used as biomarker for SLE. Another study using GWAS has identified the genetic association of GAS5 (growth arrest-specific lncRNA) with the locus 1q25 of SLE. The role of GAS5 lncRNA was further tested in mouse model where it was found to increase the susceptibility to SLE due to its immunosuppressive effect on glucocorticoids. Furthermore, the suppression of GAS5 found to inhibit cell cycle and apoptosis thereby promoting an enhanced antigen exposure and autoantibodies in SLE [41].
Co-occurring medical conditions among individuals with ASD-associated disruptive mutations
Published in Children's Health Care, 2020
Evangeline C. Kurtz-Nelson, Jennifer S. Beighley, Caitlin M. Hudac, Jennifer Gerdts, Arianne S. Wallace, Kendra Hoekzema, Evan E. Eichler, Raphael A. Bernier
Participants in this study included 301 individuals with disruptive mutations to ASD-risk genes (ages 7 months to 38 years, mean age = 8 years, 50.5% female). Individuals in both TIGER and SVIP were recruited based on previous identification of a disruptive mutation to a high-confidence ASD-risk gene through clinical or research genetic testing. Participants were included in the current study if review of genetic findings confirmed the presence of a pathogenic or likely pathogenic mutation in a known ASD-associated gene (Feliciano et al., 2018; Nakashima et al., 2019; Stessman et al., 2017) and medical history information was available from five or more individuals with a disruptive mutation in a specific gene. Gene, variant, and inheritance information for participants are listed in the Supplemental Appendix. Seven gene groups (ADNP, DYRK1A, GRIN2B, MED13L, SCN2A, SETBP1, STXBP1) included participants from both TIGER and SVIP, eight groups (ASXL3, CHAMP1, CSNK2A1, HIVEP2, HNRNPH2, PACS1, PPP2R5D, SYNGAP1) included participants from SVIP only, and three groups (ARID1B, CHD8, FOXP1) included participants from TIGER only. In total, 32 individuals (10.6%) participated in TIGER and SVIP as confirmed by matching genetic and phenotypic information, 195 (64.8%) participated in SVIP only, and 74 individuals (24.6%) participated in TIGER only. Groups did not significantly differ across study (TIGER, SVIP, or both) in adaptive behavior skills (as measured by the Vineland-II Adaptive Behavior Composite (Sparrow, Balla, & Cicchetti, 2005; F(2, p. 289) = 0.71, p = .50), ASD symptom severity (as measured by the total T-score of the Social Responsiveness Scale, Second Edition (Constantino & Gruber, 2012; (F(2, p. 177) = 0.84, p = .43), and sex (F(2, 298) = 1.24, p = .29). However, study participants in the TIGER group were significantly older than those in the SVIP group, F(2, 298) = 4.68, p = .01. Cognitive assessment scores were not available for SVIP-only participants, so cognitive skills could not be compared across studies.