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Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer (NSCLC) risk, biological mechanisms of these variants remain largely unknown. By integrating a large-scale genotype data of 15 581 lung adenocarcinoma (AD) cases, 8350 squamous cell carcinoma (SqCC) cases, and 27 355 controls, as well as multiple transcriptome and epigenomic databases, we conducted histology-specific meta-analyses and functional annotations of both reported and novel susceptibility variants. We identified 3064 credible risk variants for NSCLC, which were overrepresented in enhancer-like and promoter-like histone modification peaks as well as DNase I hypersensitive sites. Transcription factor enrichment analysis revealed that USF1 was AD-specific while CREB1 was SqCC-specific. Functional annotation and gene-based analysis implicated 894 target genes, including 274 specifics for AD and 123 for SqCC, which were overrepresented in somatic driver genes (ER = 1.95, P = 0.005). Pathway enrichment analysis and Gene-Set Enrichment Analysis revealed that AD genes were primarily involved in immune-related pathways, while SqCC genes were homologous recombination deficiency related. Our results illustrate the molecular basis of both well-studied and new susceptibility loci of NSCLC, providing not only novel insights into the genetic heterogeneity between AD and SqCC but also a set of plausible gene targets for post-GWAS functional experiments.
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Humans , Adenocarcinoma of Lung/genetics , Carcinoma, Non-Small-Cell Lung/genetics , Carcinoma, Squamous Cell/genetics , Genetic Heterogeneity , Genetic Predisposition to Disease , Genome-Wide Association Study , Lung Neoplasms/genetics , Polymorphism, Single NucleotideABSTRACT
Background: Sex-disaggregated data suggest that men with coronavirus disease 2019 (COVID-19) are more likely to die than women. Whether circulating testosterone or sex hormone-binding globulin (SHBG) contributes to such sex differences remains unknown. Objective: To evaluate the associations of circulating total testosterone (TT), free testosterone (FT), and SHBG with COVID-19 mortality. Design: Prospective analysis. Setting: UK Biobank. Participants: We included 1306 COVID-19 patients (678 men and 628 women) who had serum TT and SHBG measurements and were free of cardiovascular disease or cancer at baseline (2006-2010). Main outcome measures: The death cases of COVID-19 were identified from National Health Service death records updated at 31 July 2020. Unconditional logistic regression was performed to estimate the odds ratio (OR) and 95% confidence intervals (CI) for mortality. Results: We documented 315 deaths of COVID-19 (194 men and 121 women). After adjusting for potential confounders, we did not find any statistically significant associations for TT (OR per 1-SD increase = 1.03, 95% CI: 0.85-1.25), FT (OR per 1-SD increase = 0.95, 95% CI: 0.77-1.17), or SHBG (OR per 1-SD increase = 1.09, 95% CI: 0.87-1.37) with COVID-19 mortality in men. Similar null results were observed in women (TT: OR per 1-SD increase = 1.10, 95% CI: 0.85-1.42; FT: OR per 1-SD increase = 1.10, 95% CI: 0.82-1.46; SHBG: OR per 1-SD increase = 1.16, 95% CI: 0.89-1.53). Conclusions: Our findings do not support a significant role of circulating testosterone or SHBG in COVID-19 prognosis.
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BackgroundCoronavirus disease 2019 (COVID-19) deteriorates suddenly primarily due to excessive inflammatory injury, and insulin-like growth factor-1 (IGF-1) is implicated in endocrine control of the immune system. However, the effect of IGF-1 levels on COVID-19 prognosis remains unknown. ObjectiveTo investigate the association between circulating IGF-1 concentrations and mortality risk among COVID-19 patients. DesignProspective analysis. SettingUK Biobank. Participants1425 COVID-19 patients who had pre-diagnostic serum IGF-1 measurements at baseline (2006-2010). Main outcome measuresCOVID-19 mortality (available death data updated to 22 May 2020). Unconditional logistic regression was performed to estimate the odds ratio (OR) and 95% confidence intervals (CIs) of mortality across the IGF-1 quartiles. ResultsAmong 1425 COVID-19 patients, 365 deaths occurred due to COVID-19. Compared to the lowest quartile of IGF-1 concentrations, the highest quartile was associated with a 37% lower risk of mortality (OR: 0.63, 95% CI: 0.43-0.93, P-trend=0.03). The association was stronger in women and nonsmokers (both P-interaction=0.01). ConclusionsHigher IGF-1 concentrations are associated with a lower risk of COVID-19 mortality. Further studies are required to determine whether and how targeting IGF-1 pathway might improve COVID-19 prognosis.
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Neutralizing antibody is one of the most effective interventions for acute pathogenic infection. Currently, over three million people have been identified for SARS-CoV-2 infection but SARS-CoV-2-specific vaccines and neutralizing antibodies are still lacking. SARS-CoV-2 infects host cells by interacting with angiotensin converting enzyme-2 (ACE2) via the S1 receptor-binding domain (RBD) of its surface spike glycoprotein. Therefore, blocking the interaction of SARS-CoV-2-RBD and ACE2 by antibody would cause a directly neutralizing effect against virus. In the current study, we selected the ACE2 interface of SARS-CoV-2-RBD as the targeting epitope for neutralizing antibody screening. We performed site-directed screening by phage display and finally obtained one IgG antibody (4A3) and several domain antibodies. Among them, 4A3 and three domain antibodies (4A12, 4D5, and 4A10) were identified to act as neutralizing antibodies due to their capabilities to block the interaction between SARS-CoV-2-RBD and ACE2-positive cells. The domain antibody 4A12 was predicted to have the best accessibility to all three ACE2-interfaces on the spike homotrimer. Pseudovirus and authentic SARS-CoV-2 neutralization assays showed that all four antibodies could potently protect host cells from virus infection. Overall, we isolated multiple formats of SARS-CoV-2-neutralizing antibodies via site-directed antibody screening, which could be promising candidate drugs for the prevention and treatment of COVID-19.
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BackgroundAs of March 11, 2020, the COVID-19 outbreak was declared as a pandemic. Expending our understanding of the transmission routes of the viral infection is crucial in controlling the outbreak. It is unclear whether the 2019 novel coronavirus (2019-nCoV) can directly infect the testes or male genital tract and be sexually transmitted from males. MethodsFrom January 31 to March 14, 2020, 12 patients in recovery and one patient died of COVID-19 were included in this descriptive study. The clinical characteristics, laboratory findings, chest CT scans and outcome data were recorded. To examine whether there is sexual transmission from male, we employed realtime polymerase chain reaction testing (RT-PCR) to detect 2019-nCov in semen or testicular biopsy specimen. FindingsThe age range of the 12 patients in recovery was 22-38 years. None of the patients developed severe COVID-19 pneumonia. As of March 14, 2020, ten patients discharged from the hospital while the rest 2 had developed into recovery stage. All of the 12 patients in recovery tested negative for 2019-nCoV RNA in semen samples. Another patient aged 67 died in March 10, 2020, whose tissue sample via testicular biopsy was also tested negative for viral RNA. ConclusionNo positive RT-PCR result was found in the semen or testicular biopsy specimen. The results from this study show no evidence of sexual transmission of 2019-nCov from males.
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BackgroundPrevious studies have showed clinical characteristics of patients with the 2019 novel coronavirus disease (COVID-19) and the evidence of person-to-person transmission. Limited data are available for asymptomatic infections. This study aims to present the clinical characteristics of 24 cases with asymptomatic infection screened from close contacts and to show the transmission potential of asymptomatic COVID-19 virus carriers. MethodsEpidemiological investigations were conducted among all close contacts of COVID-19 patients (or suspected patients) in Nanjing, Jiangsu Province, China, from Jan 28 to Feb 9, 2020, both in clinic and in community. Asymptomatic carriers were laboratory-confirmed positive for the COVID-19 virus by testing the nucleic acid of the pharyngeal swab samples. Their clinical records, laboratory assessments, and chest CT scans were reviewed. FindingsNone of the 24 asymptomatic cases presented any obvious symptoms before nucleic acid screening. Five cases (20.8%) developed symptoms (fever, cough, fatigue, etc.) during hospitalization. Twelve (50.0%) cases showed typical CT images of ground-glass chest and 5 (20.8%) presented stripe shadowing in the lungs. The remaining 7 (29.2%) cases showed normal CT image and had no symptoms during hospitalization. These 7 cases were younger (median age: 14.0 years; P = 0.012) than the rest. None of the 24 cases developed severe COVID-19 pneumonia or died. The median communicable period, defined as the interval from the first day of positive nucleic acid tests to the first day of continuous negative tests, was 9.5 days (up to 21 days among the 24 asymptomatic cases). Through epidemiological investigation, we observed a typical asymptomatic transmission to the cohabiting family members, which even caused severe COVID-19 pneumonia. InterpretationThe asymptomatic carriers identified from close contacts were prone to be mildly ill during hospitalization. However, the communicable period could be up to three weeks and the communicated patients could develop severe illness. These results highlighted the importance of close contact tracing and longitudinally surveillance via virus nucleic acid tests. Further isolation recommendation and continuous nucleic acid tests may also be recommended to the patients discharged.
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To date, the controlling of outbreak of corona virus disease 2019 (COVID-19) has entered into a critical period in China. Recently, work resumption and public place is planning to open outside of Hubei, suggesting an uncertain and complex development of the epidemic in the next stage. Few days ago, we conducted a study on the epidemiological and clinical characteristics of asymptomatic infections of COVID-19, and found them might be the infection source. We believe that the findings are critical for developing public health intervention strategies for controlling COVID-19 infection in the future. Screening among the high-risk population and improving the sensitivity of measurement may contribute to the detection and management of asymptomatic infection.
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Objective@#This project aimed to explore the effectiveness of estimating individual treatment effect on real data, among the heterogeneous population, with Causal Forests (CF) method, to find out the characteristics of heterogeneous population.@*Methods@#We designed and conducted four computer simulation schemes to verify the effect of estimating on individual treatment, using the CF under four different environments of the treatment effects. Real data was then analyzed for the catheterization on right heart.@*Results@#Results from the simulation process showed that the values on individual treatment effect that were estimated by causal forests were consistent with the population effect as well as in line with the expected distribution under the setting of four different effect values. Results of real data analysis showed that values of individual treatment effect among most patients appeared positive, so the use of RHC could cause an increase of the '180-day mortality rate’ in the sampled population. Patients with lower predicted probability of 2-mo survival and albumin were more likely to have a lower risk of death after using the RHC.@*Conclusion@#CF method could be effectively used to estimate the individual treatment effect and helping the individuals to make decision on the receipt of treatment.
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Objective To describe the genetic structure of populations in different areas of China,and explore the effects of different strategies to control the confounding factors of the genetic structure in cohort studies.Methods By using the genome-wide association study (GWAS) on data of 4 500 samples from 10 areas of the China Kadoorie Biobank (CKB),we performed principal components analysis to extract the fast and second principal components of the samples for the component two-dimensional diagram generation,and then compared them with the source of sample area to analyze the characteristics of genetic structure of the samples from different areas of China.Based on the CKB cohort data,a simulation data set with cluster sample characteristics such as genetic structure differences and extensive kinship was generated;and the effects of different analysis strategies including traditional analysis scheme and mixed linear model on the inflation factor (λ) were evaluated.Results There were significant genetic structure differences in different areas of China.Distribution of the principal components of the population genetic structure was basically consistent with the geographical distribution of the project area.The first principal component corresponds to the latitude of different areas,and the second principal component corresponds to the longitude of different areas.The generated simulation data showed high false positive rate (λ =1.16),even if the principal components of the genetic structure was adjusted or the area specific subgroup analysis was performed,λ could not be effectively controlled (λ ＞ 1.05);while,by using a mixed linear model adjusting for the kinship matrix,λ was effectively controlled regardless of whether the genetic structure principal component was further adjusted (λ =0.99).Conclusions There were large differences in genetic structure among populations in different areas of China.In molecular epidemiology studies,bias caused by population genetic structure needs to be carefully treated.For large cohort data with complex genetic structure and extensive kinship,it is necessary to use a mixed linear model for association analysis.
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Objective To describe the genetic structure of populations in different areas of China,and explore the effects of different strategies to control the confounding factors of the genetic structure in cohort studies.Methods By using the genome-wide association study (GWAS) on data of 4 500 samples from 10 areas of the China Kadoorie Biobank (CKB),we performed principal components analysis to extract the fast and second principal components of the samples for the component two-dimensional diagram generation,and then compared them with the source of sample area to analyze the characteristics of genetic structure of the samples from different areas of China.Based on the CKB cohort data,a simulation data set with cluster sample characteristics such as genetic structure differences and extensive kinship was generated;and the effects of different analysis strategies including traditional analysis scheme and mixed linear model on the inflation factor (λ) were evaluated.Results There were significant genetic structure differences in different areas of China.Distribution of the principal components of the population genetic structure was basically consistent with the geographical distribution of the project area.The first principal component corresponds to the latitude of different areas,and the second principal component corresponds to the longitude of different areas.The generated simulation data showed high false positive rate (λ =1.16),even if the principal components of the genetic structure was adjusted or the area specific subgroup analysis was performed,λ could not be effectively controlled (λ ＞ 1.05);while,by using a mixed linear model adjusting for the kinship matrix,λ was effectively controlled regardless of whether the genetic structure principal component was further adjusted (λ =0.99).Conclusions There were large differences in genetic structure among populations in different areas of China.In molecular epidemiology studies,bias caused by population genetic structure needs to be carefully treated.For large cohort data with complex genetic structure and extensive kinship,it is necessary to use a mixed linear model for association analysis.
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Large-scale cohort study has unique advantages in the field of etiology research for its large sample size a multi-time point data, but it also brings great difficulty in data management and quality control at the same time. Recently, China has initiated a number of large-scale population cohort studies, posing enormous challenges to the management and quality control of related cohort data. This paper summarizes the existing experience and consensus in the field of cohort study in China from the characteristics of the cohort data, aiming at the types and main forms of the four main sources of questionnaire data, clinical diagnosis and treatment data, biological sample detection data and observation outcome data, from the data storage, circulation and transmission work.The contents and methods of queue data management are comprehensively summarized. Corresponding data quality control strategies are advised in the questionnaire evaluation, data logic verification, survey object sampling and multi-database review, etc. The goal of this review is to provide guidance for the management of data and the formulation of quality control strategies in the cohort study in China.
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Objective@#To explorer factors related to spontaneous reduction in twin pregnancy following assisted reproductive technology.@*Methods@#2 848 twin pregnant women with treatment of vitro fertilization-embryo transfer (IVF-ET) or intra cytoplasmic sperm injection (ICSI) cycles were enrolled at Assisted Reproductive Centre of the First Affiliated Hospital of Nanjing Medical University, Nanjing Maternity Hospital and Shengjing Hospital of China Medical University from January 2013 to December 2016 respectively. Basic features of subjects, relevant clinical indicators, factors of assisted reproductive therapy and pregnancy outcome were collected from clinical assisted reproductive technology management system. According to the pregnancy outcome, the subjects with spontaneous reduction were classified as case group (n=686), and those with normal twin birth were classified as control group (n=2 162). The features of subjects in the two groups were compared. Non-conditional logistics regression model was used to analyze the related factors of the occurrence of spontaneous reduction.@*Results@#The age of case group and control group were (30.6±4.3) and (30.2±4.0) years old respectively. After the adjustment of male sterile factor, compared to the subjects with luteinizing hormone level on the day of human chorionic gonadotropin administration (HCG) <1.43 IU/L, OR (95%CI) of the subjects with value at 2.59-5.10 IU/L was1.62 (1.08-2.42).Compared to the subjects with number of transferred embryo as 1, OR (95%CI) of the subjects with value as 3 was 0.23 (0.07-0.74). Compared to the subjects with stage of transferred embryo as cleavage stage, OR (95%CI) of the subjects with blastula stage was 0.42 (0.27-0.67).@*Conclusion@#Luteinizing hormone level on day of HCG, number and stage of embryo transfer are related factors to spontaneous reduction in twin pregnancy following assisted reproductive technology.
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To explore the safety and efficacy for radiofrequency ablation of paroxysmal supraventricular tachycardia (PSVT) guided by Carto Univu three-dimensional mapping system. Methods: A total of 99 patients with PSVT underwent radiofrequency catheter ablation (RFCA) were assigned to a Carto Univu group (51 patients) and a two-dimensional X-ray group (48 patients) according to the mapping method. The operation time, X-ray exposure time, X-ray exposure dose, dose area product (DAP), operation success rate and complication rate were compared between the two groups. Results: The Carto Univu group and the two-dimensional X-ray group were not significant difference in the operation time, the X-ray exposure time of placing catheter, the X-ray DAP of placing catheter, the number of discharge, the discharge power, and the total discharge time (P>0.05). The mapping and ablation time, total exposure time, mapping and ablation DAP and total DAP in the Carto Univu group were significantly lower than those in the two-dimensional X-ray group (P<0.01). In the right accessory pathway cases, the mapping and ablation DAP and the total DAP in the Carto Univu group decreased compared with X-ray group (P<0.05), but it decreased more profound (P<0.01) in the left accessory pathway cases and the dual atrioventricular nodal pathways cases. Seven cases in the Carto Univu group achieved "zero X-ray", including 5 cases of the dual atrioventricular nodal pathways and 2 cases of the left accessory pathway. The immediate success rate for the two groups was 100%. After 3-12 months of follow-up, there was no recurrence in the Carto Univu group but 3 suspected recurrences in the two-dimensional X-ray group. In addition, no complications occurred in the two groups. Conclusion: Carto Univu electroanatomic mapping system can guide PSVT safely and effectively during radiofrequency ablation and reduce radiation exposure to both doctors and patients. It is especially suitable for dual atrioventricular nodal pathways, which may even achieve "zero X-ray". Perhaps Carto Univu will be the first choice for RFCA of dual atrioventricular nodal pathways.
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Humans , Catheter Ablation , Methods , Imaging, Three-Dimensional , Methods , Operative Time , Radiation Exposure , Radiography , Recurrence , Tachycardia, Supraventricular , Diagnostic Imaging , General Surgery , Treatment OutcomeABSTRACT
Objective To give specific strategies for discipline construction in the "first class"universities and colleges, through the analysis of the SCI service of 20 independent medical universities in China during 2013 to 2017. Methods Based on WoS and ESI database, this paper searches and analyzes the related data of SCI papers published by the above colleges and universities, including the quantity of output, the citation of all articles, the fund support and other bibliometrics indexes, and explores the status and problems of these SCI papers. Results All colleges and universities in this study have entered the ESI database, and the ranking of ESI is basically the same as the global ranking of US News and ARWU;the Clinical Medicine and Pharmacology&Toxicology of some colleges and universities has been in or near the global 1 per thousand of ESI, and the proportion of the quoted volume and the total volume of the document is still lower than the average level in China;the H index is directly proportional to the papers, and there is still a gap with the first-class universities in China. Most papers are funded by national fund projects, but a large number of SCI articles are not highly influential. Conclusion The results show that the global ranking of independent medical universities in China has developed rapidly in the past five years. Although there is still a gap with the international first-class universities and disciplines, but there is great potential . The level of Clinical Medicine and Pharmacology & Toxicology has reached the international first-class level. The gap between the development level of biology and biochemistry, neuroscience and behavior, and the international medical level of these field is narrowing.
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BACKGROUND AND PURPOSE: Large cohort studies on relationship between family history of stroke (FHS) and stroke risk are lacking in Asians. We aimed to systematically evaluate the association of FHS with stroke risk in a cohort study of 0.5 million Chinese adults. METHODS: Information about FHS was self-reported. The median follow-up time was 7.16 years and the end-point of follow-up was incident stroke, which was entered directly into the China Kadoorie Biobank system. Multivariate analyses were performed with Cox proportional hazards model, and interaction analyses were carried using likelihood-ratio tests. RESULTS: Compared with participants without FHS, the hazard ratio (HR) (95% confidence interval, CI) of stroke for participants with FHS was 1.50 (1.46-1.55). The HRs increased with the number of first degree relatives with stroke (HRs=1.41, 1.98 and 2.47 for 1, 2 and ≥3 relatives, respectively, P(trend) <0.001). The HRs were 1.57 (95% CI: 1.50-1.66) and 1.49 (95% CI: 1.45-1.54) for sibling history and parental history, respectively. Similar associations with offspring stroke risk were observed between paternal history (HR=1.48, 95% CI: 1.43-1.54) and maternal history (HR=1.49, 95% CI: 1.43-1.55). Moreover, significant interactions were detected between FHS and health-risk behaviors (tobacco smoking and alcohol drinking). CONCLUSIONS: FHS is an independent risk factor for stroke in Chinese. The more first degree relatives are affected by stroke, the higher are individuals’ risk of suffering from stroke. The management of the health-risk behaviors for reducing stroke should be highlighted, especially for the individuals with FHS.
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Adult , Humans , Asian People , China , Cohort Studies , Follow-Up Studies , Multivariate Analysis , Parents , Proportional Hazards Models , Risk Factors , Siblings , Smoke , Smoking , StrokeABSTRACT
Objective To investigate the association between genetic variants in microRNA biosynthesis genes and the risk of head and neck squamous cell carcinoma (HNSCC).Methods A case-control study was conducted with 576 HNSCC patients and 1 552 healthy controls matched by factors as age-(± 5 years) and sex.Eight potentially functional single nucleotide polymorphism loci in microRNA biosynthesis genes (DICER1,GEMIN3,and PIWIL1) were genotyped using the Illumina Infinium BeadChip platform.Univariate and multivariate logistic regression models were performed to assess the association between genotypes and HNSCC risk.Results The allele frequencies of rs1106042 (G＞A) in PIWIL1 were significantly different between the cases and controls (P=0.011).After controlling for factors as age,sex,smoking and alcohol intake,the A allele of rs 1106042 showed a decreased risk of HNSCC (additive model:adjusted OR=0.73,95％CI:0.57-0.93,P=0.011).Results from the stratification analysis by age,sex,smoking,alcohol intake and tumor sites showed that the effect of rs1106042 A allele on HNSCC risk was significant in older age groups (≥60),females,nonsmokers,non-alcohol drinkers,and subjects with oral cavity cancer (P＜0.05).Conclusion Potentially,functional single nucleotide polymorphism in PIWIL1 might modify the risk of HNSCC in China.
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Objective To investigate the association between genetic variants in microRNA biosynthesis genes and the risk of head and neck squamous cell carcinoma (HNSCC).Methods A case-control study was conducted with 576 HNSCC patients and 1 552 healthy controls matched by factors as age-(± 5 years) and sex.Eight potentially functional single nucleotide polymorphism loci in microRNA biosynthesis genes (DICER1,GEMIN3,and PIWIL1) were genotyped using the Illumina Infinium BeadChip platform.Univariate and multivariate logistic regression models were performed to assess the association between genotypes and HNSCC risk.Results The allele frequencies of rs1106042 (G＞A) in PIWIL1 were significantly different between the cases and controls (P=0.011).After controlling for factors as age,sex,smoking and alcohol intake,the A allele of rs 1106042 showed a decreased risk of HNSCC (additive model:adjusted OR=0.73,95％CI:0.57-0.93,P=0.011).Results from the stratification analysis by age,sex,smoking,alcohol intake and tumor sites showed that the effect of rs1106042 A allele on HNSCC risk was significant in older age groups (≥60),females,nonsmokers,non-alcohol drinkers,and subjects with oral cavity cancer (P＜0.05).Conclusion Potentially,functional single nucleotide polymorphism in PIWIL1 might modify the risk of HNSCC in China.
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<p><b>OBJECTIVE</b>To evaluate the predictive power of risk model by combining traditional epidemiological factors and genetic factors.</p><p><b>METHODS</b>Our previous GWAS data of lung cancer in Chinese were used in training set (Nanjing and Shanghai: 1473 cases vs. 1962 control) and testing set (Beijing and Wuhan: 858 cases vs. 1 115 control). All the single nucleotide polymorphisms (SNPs) associated with lung cancer risk were systematically selected and stepwise logistic regression analysis was used to select independent factors in the training set. The wGRS (weighted genetic score) was further used to calculate genetic risk score. To evaluate the contribution of the genetic factors, 3 risk models were established by using the training set, i.e. smoking model (based on smoking status) , genetic risk model (based on genetic risk score) and combined model (based on smoke and genetic risk score). The predictability of the models were evaluated by the areas under the receiver operating characteristic (ROC) curves, area under curve (AUC), net reclassification improvement (NRI) and integrated discrimination index (IDI). Besides, the results were further verified in the testing set.</p><p><b>RESULTS</b>In the training set, it was found that the AUC of the smoking, genetic risk and combined models were 0.65 (0.63-0.66), 0.60 (0.59-0.62) and 0.69 (0.67-0.71), respectively. Compared with combined model, the predictive power of other two models significantly declined, the difference was statistically significant (P<0.001). Furthermore, compared with the smoking model, the NRI of the combined model increased by 4.57% (2.23%-6.91%) and IDI increased by 3.11% (2.52%-3.69%) in the training set, the difference was statistically significant (P<0.001). Similarly, in the testing set NRI increased by 2.77%, the difference was not statistically significant (P=0.069) , and IDI increased by 3.16%, the difference was statistically significant (P<0.001).</p><p><b>CONCLUSION</b>This study showed that combining 14 genetic variants with traditional epidemiological factors could improve the predictive power of risk model for lung cancer. The model could be used in the screening of high-risk population of lung cancer in Chinese and provide evidence for the early diagnosis and treatment of lung cancer.</p>
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Humans , Area Under Curve , Asian People , Beijing , Case-Control Studies , China , Genetic Predisposition to Disease , Genetic Variation , Genome-Wide Association Study , Lung Neoplasms , Epidemiology , Genetics , Polymorphism, Single Nucleotide , ROC Curve , Risk FactorsABSTRACT
Genetic risk score (GRS) is used for evaluating the effects of genetic susceptible factors in risk prediction models.Five methods are commonly used for GRS:i.e.simple count genetic risk score (SC-GRS),odds ratio weighted genetic risk score (OR-GRS),direct logistic regression genetic risk score (DL-GRS),polygenic genetic risk score (PG-GRS) and explained variance weighted genetic risk score (EV-GRS).This paper summarizes the models,application conditions,advantages and limitations of the five methods.The complexity of prediction models increased along with the inclusion of more susceptible SNPs,some method have been developed to solve the problems,but the effects of new methods needs further evaluation.
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Genome-wide association studies (GWAS) have identified thousands of genetic loci associated with complex diseases or traits. However, the exact biological functions of these loci are largely unknown. Recent functional annotation indicates that the majority of disease/trait associated loci are concentrated in regulatory DNA of human genome. Expression quantitative trait loci (eQTL) analyses, chromosome conformation capture related methods and genome editing methods (such as CRISPR/Cas9) may facilitate the functional study of these loci. Research on noncoding RNAs and rare variants may improve the functional understanding. These efforts may promise translation of GWAS findings to clinical practices.
