Genetic studies on systemic lupus erythematosus in East Asia point to population differences in disease susceptibility

Wang, Yong Fei; Lau, Yu Lung; Yang, Wanling

doi:10.1002/ajmg.c.31696

Cited by 11 publications

(6 citation statements)

References 66 publications

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“…With fewer variables (3 vs. 6), our model had a relatively lower sensitivity of 85% (0.3 as cutoff; Figure 3, Supplementary Table 7) than the PREDICTS model but a higher specificity of 87%. Furthermore, because Asian SLE populations have different prevalence of CVD and genetic backgrounds from western populations (43,44), whether the PREDICTS model is applicable to the Chinese population remains to be confirmed. Thus, with better predictive capacity and Asian population specificity, this prediction model can serve as a useful tool in identifying atherosclerosis risk in Asian SLE patients early.…”

Section: Discussionmentioning

confidence: 99%

Establishing a Risk Prediction Model for Atherosclerosis in Systemic Lupus Erythematosus

Xing

Pang

et al. 2021

Front. Immunol.

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Background and aims: Patients with systemic lupus erythematosus (SLE) have a significantly higher incidence of atherosclerosis than the general population. Studies on atherosclerosis prediction models specific for SLE patients are very limited. This study aimed to build a risk prediction model for atherosclerosis in SLE.Methods: RNA sequencing was performed on 67 SLE patients. Subsequently, differential expression analysis was carried out on 19 pairs of age-matched SLE patients with (AT group) or without (Non-AT group) atherosclerosis using peripheral venous blood. We used logistic least absolute shrinkage and selection operator regression to select variables among differentially expressed (DE) genes and clinical features and utilized backward stepwise logistic regression to build an atherosclerosis risk prediction model with all 67 patients. The performance of the prediction model was evaluated by area under the curve (AUC), calibration curve, and decision curve analyses.Results: The 67 patients had a median age of 42.7 (Q1–Q3: 36.6–51.2) years, and 20 (29.9%) had atherosclerosis. A total of 106 DE genes were identified between the age-matched AT and Non-AT groups. Pathway analyses revealed that the AT group had upregulated atherosclerosis signaling, oxidative phosphorylation, and interleukin (IL)-17-related pathways but downregulated T cell and B cell receptor signaling. Keratin 10, age, and hyperlipidemia were selected as variables for the risk prediction model. The AUC and Hosmer–Lemeshow test p-value of the model were 0.922 and 0.666, respectively, suggesting a relatively high discrimination and calibration performance. The prediction model had a higher net benefit in the decision curve analysis than that when predicting with age or hyperlipidemia only.Conclusions: We built an atherosclerotic risk prediction model with one gene and two clinical factors. This model may greatly assist clinicians to identify SLE patients with atherosclerosis, especially asymptomatic atherosclerosis.

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Section: Discussionmentioning

confidence: 99%

Establishing a Risk Prediction Model for Atherosclerosis in Systemic Lupus Erythematosus

Xing

Pang

et al. 2021

Front. Immunol.

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“…Increased international collaboration would provide an unprecedented opportunity to study the mechanism of population differences in disease association and causation in both complex and rare disorders. Wang et al describes how scientists and clinicians have closely collaborated in genetic research of SLE at both the national and international level and constructed mega data sets with thousands of Chinese and European patients and controls (Wang, Lau, & Yang, ). This big database led to the discovery of 10 previously unreported systemic lupus erythematosus (SLE) genetic loci and the computation of a polygenic risk score for SLE, paving the path for new treatment and healthcare model for SLE.…”

Section: Going Forwardmentioning

confidence: 99%

Development of clinical genetics in Asia

Chung

Willis

Poh-San

2019

American J of Med Genetics Pt C

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This Special Issue on Clinical Genetics in Asia highlights a collection of articles showing the growth, development, and current status of clinical genetics in Asia. In this Introduction, the Guest Editors share on the themes of this issue to provide useful insights into the rapid growth of genomics and clinical genetics in this region. The contents of this Issue cover a range of topics from the history and development of clinical genetics in Asia to studies on disorders with clinical significance or phenotype differences in the Asian populations to the status of precision medicine. The goal is to provide a glimpse of how significantly the field of genetics in Asia has developed in recent years with the aspiration that this can serve as a catalyst to increase international collaboration and cooperation in combating genetic diseases. We hope that this issue shows Asia's readiness and willingness to be a part of more international conversations about genetics in future.

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“…Although most risk loci are consistently present among populations with different ancestries, some loci are exclusive to speci c populations. For example, risk alleles that are mapped to the genes PTPN22 and SH2B3-ATXN2 were identi ed as SLE risk variants only in Europeans and are apparently absent in Chinese populations [20]. Ramos et al [18], who used integrated Haplotype Score (iHS) and F ST analysis, found evidence of positive selection at the PTPN22 locus in Africans.…”

Section: Introductionmentioning

confidence: 99%

Positive Selection Affects the Expression of Systemic Lupus Erythematosus Associated Loci in Human Populations

Oberreiter¹,

Goellner²,

Morris³

et al. 2021

Preprint

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Background: Systemic lupus erythematosus (SLE) shows marked population-specific disparities in disease prevalence, including substantial variation in manifestations and complications according to genetic ancestry. Several recent studies suggest that a substantial proportion of variation of gene expression shows genetic ancestry-associated differences in gene regulation on immune responses. Positive selection may act in a population-specific manner on expression quantitative trait loci (eQTLs) and thereby contributes to the difference in the differences of SLE prevalence and manifestation in human populations. We tested the hypothesises that some of the identified SLE risk polymorphisms display pleiotropic effects or polygenicity driven by positive selection. We performed a genome-wide scan for recent positive selection by using integrated Haplotype Score (iHS) statistics in different human populations. In addition, we estimated the timing of beneficial mutations to understand what possible selective pressures drive positive selection at SLE-associated loci. Results: We identified several SLE risk loci that are population-specifically under positive selection. Almost all SNPs that are under positive selection function as cis-eQTLs in different tissue types. We determined that adaptive eQTLs affect the expression of fewer genes than non-adaptive eQTLs, suggesting a limited range of effect of an eQTL at SLE risk sites that show signatures of positive selection. Furthermore, some positively selected SNPs are located in transcription factor binding sequences. The timing of positive selection for the studied loci suggests that both environmental and recent lifestyle changes during as well as after the Neolithic Transition may have become selectively effective. We propose a novel link between positively selected eQTLs at a certain SLE risk locus in Europeans and a physiological pathway not previously considered in SLE.Conclusions: We conclude that population-specific adaptive eQTLs contribute to the observed variation in specific manifestations and complications of SLE in different ethnicities. Our results suggest also that human populations adapt more rapidly to environmental and lifestyle stimuli via modification of gene expression without having to alter the genetic code.

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Genetic studies on systemic lupus erythematosus in East Asia point to population differences in disease susceptibility

Cited by 11 publications

References 66 publications

Establishing a Risk Prediction Model for Atherosclerosis in Systemic Lupus Erythematosus

Establishing a Risk Prediction Model for Atherosclerosis in Systemic Lupus Erythematosus

Development of clinical genetics in Asia

Positive Selection Affects the Expression of Systemic Lupus Erythematosus Associated Loci in Human Populations

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