Construction And Validation Of Predictive Nomogram For Leprosy Among Leprosy Close Contacts In China

Background:Leprosy is a chronic infectious disease caused by It invades the skin,mucous membrane and peripheral nerve tissue,leading to deformity and disability.In recent years,about 200,000 new cases of leprosy have been discovered globally each year,suggesting that Mycobacterium leprae is still spreading worldwide.Untreated patients with multi-bacterial leprosy are the main source of infection.In endemic areas,less than 5%of the people exposed to Mycobacterium leprae eventually develop into clinical patients.This suggests that there is a tendency to be infected and eventually develop into clinical leprosy.The type of the patient and the bacterial density index determine the possibility of transmission of Mycobacterium leprae,while long-term close contact with the patient,genetic background,immune status and living environment are the risk factors for infection.The incidence among leper contacts is 5 to 8 times that of the general population.Contact tracing and chemoprophylaxis are the main prevention and control measures to realize early detection and diagnosis of leprosy,leading to control the spread of leprosy by reducing the incidence and the malformation rate.Genome-wide association study(GWAS)identified that single nucleotide polymorphisms(SNPs)at CCDC122,C13orf31,NOD2,TNFSF15,RIPK2 gene locus associated with the onset of leprosy.These genes encode proteins involved in the immune response,and the genetic mutation leads to a change in the signaling pathways,which eventually leads to leprosy occurrence.Chapter 1:The construction of risk prediction model for leprosy contacts;Chapter 2:Validation of risk prediction model for leprosy contacts.Objective:1.This study investigated the association of 17 SNPs based on previously published GWAS studies with susceptibility to leprosy.2.Further stratified analysis was conducted to investigate the association between the SNPs and different leprosy polar forms and immune states from southwestern China,including Yunnan,Guizhou,Sichuan and Hunan provinces.3.We aimed to establish a predictive model using these genetic factors along with epidemiological factors to predict leprosy risk of leprosy household contacts(HHCs).Methods:1.Based on the previously published GWAS studies and one study combined whole-exome sequencing and targeted next-generation sequencing within the GWAS loci,we selected 17 SNPs wherein a genome-wide significant association(P<5x10-8)between the SNPs and leprosy.The SNPs were accurately genotyped using multiple polymerase chain reaction and next generation sequencing with Illumina HiSeq X-10 platform.Cases and controls were compared according to allele with the Pearson ?2 test or Fisher test using PLINK v 1.07,including 1344 leprosy patients,1908 relatives and 824 genetically unrelated contact individuals.We also analyze the differences distributions of alleles between different leprosy clinical phenotypes.Meanwhile,we invested the associations between leprosy and clinical phenotypes with SNPs based on a logistic regression model adjusted for age,ethnicity and gender.2.Weighted genetic risk score(wGRS)encompassing genome wide association studies(GWAS)variants and five non-genetic factors were examined in a case-control design associated with leprosy risk including 589 cases and 647 controls from leprosy HHCs.We constructed a risk prediction nomogram and evaluated its performance by the concordance index and calibration curve.The results were validated using bootstrap resampling with 1000 resamples and a prospective design including 1100 HHCs of leprosy patients.Results:1.After adjusting covariate factors,rs780668 and rs3764147 polymorphisms influenced susceptibilities to genetically related or unrelated leprosy contact individuals;2.rs 142179458 was associated with onset early cases;3.rs73058713 A allele increased the risk of reversal reaction,rs3764147 G allele had higher risk to present lepromatous leprosy and erythema nodosum leprosum while rs3764147 A allele increased the risk of reversal reaction.4.The C-index for the risk model was 0.792(95%confidence interval[CI]0.768-0.817),and was confirmed to be 0.780 through bootstrapping validation.The calibration curve for the probability of leprosy showed good agreement between the prediction of the nomogram and actual observation.HHCs were then divided into the low-risk group(nomogram score? 81)and the high-risk group(nomogram score>81).In prospective analysis,12 of 1100 participants had leprosy during 63 months' follow-up.We generated the nomogram for leprosy in the validation cohort(C-index 0.773[95%CI 0.658-0.888],sensitivity75.0%,specificity 66.8%).Conclusion:1.Our results demonstrated that genetic variants in the LACC1,HIF1A,SLC29A3 and CDH18 genes were positively correlated with the risk of leprosy and leprosy clinical phenotypes,providing new research directions for the immunogenetics of leprosy.2.The nomogram achieved an effective prediction of leprosy in HHCs.Using the model,the risk of an individual contact developing leprosy can be determined,which can lead to a rational preventive choice for tracing higher-risk leprosy contacts.