One Size Does Not Fit All
Year: 2017
Type: editorial
Abstract: HomeCirculation: Cardiovascular GeneticsVol. 10, No. 5One Size Does Not Fit All Free AccessEditorialPDF/EPUBAboutView PDFSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBOne Size Does Not Fit AllGenetic Prediction of Kawasaki Disease Treatment Response in Diverse Populations Michael A. Portman, MD and Sadeep Shrestha, PhD, MHS, MS Michael A. PortmanMichael A. Portman From the Department of Pediatrics, Seattle Children's Research Institute, University of Washington (M.A.P.); and Department of Epidemiology, University of Alabama at Birmingham (S.S.). and Sadeep ShresthaSadeep Shrestha From the Department of Pediatrics, Seattle Children's Research Institute, University of Washington (M.A.P.); and Department of Epidemiology, University of Alabama at Birmingham (S.S.). Originally published12 Oct 2017https://doi.org/10.1161/CIRCGENETICS.117.001917Circulation: Cardiovascular Genetics. 2017;10:e001917Kawasaki disease (KD) is an acute systemic vasculitis afflicting children predominantly <5 years of age. The KD diagnosis depends on the presence of persistent high fever and clinical symptoms and signs of an inflammatory reaction.1 Although the acute inflammatory phase is usually self-limited, the vasculitis shows a predilection for involving the coronary arteries. Transient or even persistent coronary artery dilation can ensue and result in aneurysm formation. Thrombosis or scarring within the coronary artery wall may eventually lead to clinically important stenosis, often requiring intervention.1 Because of the variable nature of KD, accurate prediction for treatment response during the early phase is essential for successful initial clinical management and treatment.See Article by Kuo and Wong et alIn this month's issue of Circulation: Cardiovascular Genetics, Kuo et al2 developed a genetic-based risk score for predicting treatment outcome for KD. Although, the leading cause for acquired heart disease in children from developed nations, the cause for KD remains undefined. Environmental factors likely trigger the autoinflammatory response in genetically susceptible individuals. Japan and other East Asian countries show >10-fold greater KD incidence than North American and European populations.1 The higher incidence persists in East Asians living in the United States,3 suggesting that genetics are responsible, although cultural and dietary factors are also implicated for influencing differences in incidence.4 Accordingly, multiple investigators have pursued hypothesis-derived candidate genes or used genome-wide strategies to identify KD susceptibility loci.1Intravenous gamma globulin (IVIG) serves globally as the primary treatment for KD. Randomized clinical trials performed in the 1980s suggested that IVIG reduced the prevalence of persistent coronary artery lesions (CAL).5,6 Nevertheless, a more recent clinical trial performed by the National Heart, Lung, and Blood Institute–funded pediatric heart network showed a 19% CAL prevalence rate 5 weeks after treatment with IVIG and aspirin.7 Additionally, multiple studies show that resistance or refractoriness to IVIG defined as persistent or recurrent fever occurs at a rate between 10% and 25%.1 The rate depends on many factors, including the specific ethnicity and race of the population studied, as well as the parameters used to define resistance. Also, IVIG is a blood product with multiple vendors using widely different collection and processing techniques, which could alter potency.Nevertheless, the studies consistently show that refractory cohorts exhibit higher prevalence and CAL severity than do IVIG responders.1 Thus, multiple clinical trials with varying design have tested therapy adjunctive to IVIG during the acute KD presentation to reduce refractoriness and CAL. Most of these trials have been inadequately powered to detect adjunct treatment effect because of the low IVIG refractory rate in the general KD population and the complexities involved in quantifying coronary artery outcomes.7–9Multiple clinical and laboratory algorithms have been suggested for predicting which patients are at high risk for IVIG refractoriness and CAL. In Japan, investigators have used clinical and laboratory scoring systems to determine eligibility for clinical trials targeted toward high-risk KD patients.10 Those trials demonstrated that adding prednisolone to IVIG improves coronary artery outcomes in patients identified early with increased severity by those scores. However, the scoring systems have shown poor sensitivity and are considered unsuitable for use in non-Japanese populations.1 Other biomarkers have also shown limited success in predicting KD treatment outcome.The pursuit of genes involved in KD pathogenesis or those associated with susceptibility represents another approach for developing predictive biomarkers. Conceivably, these genes also define disease severity and treatment response. Despite identification of single-nucleotide polymorphisms (SNPs) or haplotypes in multiple genes, only SNPs in 2 genes, ITPKC (inositol 1,4,5 triphosphosphate 3-kinase C) and FcγR2A (FcGamma receptor 2A), consistently associate with KD across multiple different ethnic/racial populations.11,12 The KD susceptibility locus rs28493229 on ITPKC has received some attention as a predictor for IVIG treatment response.13 ITPKC inhibits a cascade which eventually enhances Ca++ mobilization and NLRP3 (nucleotide-binding domain, leucine-rich-containing family, pyrin domain-containing-3) inflammasome activation, leading to release of proinflammatory IL1β and IL-18. Compared with the GG genotype at rs28493229, the CC genotype leads to decreased ITPKC protein expression and proinflammatory cytokine release from immune cells, than occurs with either GG or GC genotype.14 However, the CC accounts for only 2.9% of a KD cohort from various ethnicities.11 The C allele only trended toward overrepresentation in KD IVIG nonresponders in multiethnic populations. Onouchi et al13 tested a 2-locus association model using rs28493229 and another KD-associated functional SNP in Caspase-3 to improve prediction for IVIG resistance over a single SNP. The combination modestly increased the odds ratio for IVIG resistance and CAL in Japanese patients with KD. The apparent cooperative effect of these 2 SNPs on IVIG nonresponse and CAL was later replicated in a Taiwanese cohort, although with similar modest odds ratios and thus, limited predictable power.15The IVIG mechanism of anti-inflammatory action provides an alternate pharmacogenetics approach to develop predictor models for treatment response in KD. As noted, the FcγR2A consistently appears as a KD-risk gene in both genome-wide association study and candidate-driven cohort- and family-based studies. Evidence also continues to accumulate in support of FcγRs as logical gene family involved in IVIG mechanism. Several effectors and regulatory immunologic functions are initiated by the binding of IVIG to classical FcγRs, which regulate FcγR clustering on the surface of cells.16 These receptors bind with high affinity to IgG, the component in IVIG that forms the connection between the humoral and cellular immune components, as well as a crucial link between innate and adaptive immunity.17 The neutrophil antigen 1 allotype in the extracellular domain 1 of FcγR3B has been identified as a major risk factor for IVIG refractoriness and persistent CAL.18 Neutrophil antigen 1 allotype selectively increases binding affinity for IgG1 and IgG3 over neutrophil antigen 2, suggesting that IVIG modulates inflammation in KD through this receptor. Further, SNPs in the inhibitory FcγR2B at −120 T/a and −386 G/c also associate with IVIG response. These polymorphisms enhance the responses to specific transcription factors, resulting in elevated FcγR2B expression on lymphocytes and monocytes. However, because of substantial race and ethnic variance in frequency, these single SNPs will not serve as ubiquitous and clinically relevant IVIG response predictors. Genetic risk score analysis using multiple functional and copy number variants of FcγR gene families showed that the prediction models were statistically significant for both KD susceptibility and IVIG response among non-Hispanic Whites but not in others.19 The differences depend largely on deviations in SNP frequency and copy number variants among racial and ethnic groups. For example, FcγR2B-120T/a allele is not polymorphic in East Asians and occurs rarely in Hispanics, therefore, contributing minimally to a predictive model in those populations. Thus, approaches using only a few SNPs or copy number variants to develop risk scores for KD face considerable challenges in establishing effective cross-population predictive power.Kuo et al2 used a novel approach by conducting a genome-wide association analysis to develop a risk score for IVIG resistance. Using the Affymetrix genome-wide human SNP array 6.0 platform in a modest-size population, they first evaluated the associations of individual SNPs. Rather than a traditional logistic regression analysis in a case–control setting, they first applied a mixed linear model algorithm in genome-wide complex trait analysis to estimate the proportion of phenotypic variance explained by genome-wide SNPs. This accounts for the polygenic effect, and then they evaluated the fixed effect of all SNPs by excluding the candidate markers (Mixed Linear Model Effect) one at a time. They then calculated a weighted genetic risk score proposed by Jager et al using the top 11 associated SNPs to provide a prediction of the IVIG responsiveness. The analyses yielded impressive odds ratios for IVIG nonresponse when comparing patients with the highest grouped weighted genetic risk score with the lowest. The receiver characteristics suggest reasonable sensitivity and specificity for predicting IVIG response in the Taiwanese population, which can possibly extend to other East Asian population.However, caution is needed with the interpretation and application of the findings from such pilot studies, as well as the applicability of the results to other populations. The results reveal genetic heterogeneity because many of these SNPs do not occur in genes indicated in other IVIG-resistance studies.13,19 This discrepancy could be because of limitations in the genome-wide association platform. In particular, given the complexity of genomic sequences with copy numbers and ≈100% sequence homology across FcGR gene families, some of these variants are not well captured in genotyping arrays and require complex methodologies.The authors also conducted an additive genetic model, and some of the previous associations with candidate genes were observed with dominant model (eg, ITPKC variant). They performed standard and thorough quality control procedures of genome-wide scan data that narrowed the number of SNPs by 30.44% to 603 698. As with any genome-wide association study, some of the quality control methods could have been influenced by the small sample size inherent in a study from an orphan disease. All the participants in the study were patients with KD; so some SNP frequencies may deviate from general Taiwanese population.The authors state that 8 SNPs reached genome-wide significance; however, these along with 3 others (total of 11) included in estimating the risk score have not been replicated and validated in other cohorts, thereby increasing the false-positive risk in their study. Additionally, marked differences exist for risk allele frequencies among populations (Table VI in the Data Supplement in the study by Kuo et al).2 For example, the most significant risk allele rs9380548 is not polymorphic in the HapMap (White) CEU and Yoruban (YRI) populations. There is also redundancy created by using highly correlated SNPs; although sensitivity analysis performed by the authors with only 7 SNPs showed similar results in this population, which suggests that the correlated SNPs did not have independent effects. The authors showed no population stratification occurred within the studied Taiwanese population; however, analyses of these SNPs in other populations may provide different weighted genetic score even if they proved significant. To illustrate, the chromosome 3 SNPs seem to correlate or exist in high linkage disequilibrium in the study population and have similar patterns in Hapmap CEU, CHB, and JPT populations; however, risk allele frequency differs substantially across populations. Further, these SNP allele frequencies differ in the YRI suggesting alternate correlation and potentially varying linkage disequilibrium across SNPs and separate haploblock regions.Considering the modest effect size yielded by individual SNP analyses, the approach used by Kuo et al shows promise for developing genetic predictive risk scores for IVIG treatment response in KD and other diseases. The SNPs used in the weighted genetic risk score should be evaluated for biological relevance to the inflammatory processes involved in KD, the IVIG mechanism of action, or both. Additionally, the SNPs should undergo analyses to determine whether they are in linkage disequilibrium with other functional variants before the weighted genetic risk score receives acceptance as a true predictor of IVIG response.In conclusion, the study highlights the major barriers faced by those attempting to advance KD treatment. Population diversity based on geography, culture, environmental exposure, and genetic drift accounts for much of the inconsistency in results from KD studies. Risk factors, outcome predictors, and even treatments which work in some populations may not have similar impact or efficacy in others. Thus, we need a more refined approach, which should take these factors into account. It is unknown whether one universal prediction model can be developed for all populations or population-specific prediction models will be required.AcknowledgmentsFunding provided in part by R21-HL-090558-01 to MAP and by the Seattle Children's KDKIDS Guild.DisclosuresNone.FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.Correspondence to Michael A. Portman, MD, Seattle Children's Research Institute, University of Washington, 1900 9th Ave, Seattle, WA 98101. E-mail [email protected]References1. McCrindle BW, Rowley AH, Newburger JW, Burns JC, Bolger AF, Gewitz M, et al; American Heart Association Rheumatic Fever, Endocarditis, and Kawasaki Disease Committee of the Council on Cardiovascular Disease in the Young; Council on Cardiovascular and Stroke Nursing; Council on Cardiovascular Surgery and Anesthesia; and Council on Epidemiology and Prevention. 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FcγR gene copy number in Kawasaki disease and intravenous immunoglobulin treatment response.Pharmacogenet Genomics. 2013; 23:455–462. doi: 10.1097/FPC.0b013e328363686e.CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Padilla L, Collins J, Idigo A, Lau Y, Portman M and Shrestha S (2021) Kawasaki Disease and Clinical Outcome Disparities Among Black Children, The Journal of Pediatrics, 10.1016/j.jpeds.2020.09.052, 229, (54-60.e2), Online publication date: 1-Feb-2021. Padilla L, Portman M and Shrestha S (2021) Reply, The Journal of Pediatrics, 10.1016/j.jpeds.2020.11.022, 230, (277-278), Online publication date: 1-Mar-2021. Portman M, Dahdah N, Slee A, Olson A, Choueiter N, Soriano B, Buddhe S and Altman C (2019) Etanercept With IVIg for Acute Kawasaki Disease: A Randomized Controlled Trial, Pediatrics, 10.1542/peds.2018-3675, 143:6, Online publication date: 1-Jun-2019. Buda P, Friedman-Gruszczyńska J and Książyk J (2021) Anti-inflammatory Treatment of Kawasaki Disease: Comparison of Current Guidelines and Perspectives, Frontiers in Medicine, 10.3389/fmed.2021.738850, 8 October 2017Vol 10, Issue 5 Advertisement Article InformationMetrics © 2017 American Heart Association, Inc.https://doi.org/10.1161/CIRCGENETICS.117.001917 Originally publishedOctober 12, 2017 Keywordsallergy and immunologymucocutaneous lymph node syndromehumansEditorialsimmune systemPDF download Advertisement SubjectsGenetic, Association StudiesInflammatory Heart Disease
Authors: Michael A. Portman, Sadeep Shrestha
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W2764108935