Single nucleotide polymorphisms (SNPs), which are the most common form of DNA variations, have great potential as a medical diagnostic tool. However, compared to the number of SNPs involved, the available training dat...Single nucleotide polymorphisms (SNPs), which are the most common form of DNA variations, have great potential as a medical diagnostic tool. However, compared to the number of SNPs involved, the available training data sets generally have a fairly small sample size, which is a main challenge to traditional data analysis methods. This paper proposed an improved univariate marginal distribution algorithm (UMDA) named multi-population UMDA (MPUMDA) for disease association study. In order to illustrate the effectiveness of our algorithm, we compared it with some current known methods, and the results showed that our method is potentially interesting as an alter-native tool in disease association study.展开更多
AIM: To investigate the association of three polymorphisms in the receptor for advanced glycation end product (RAGE) gene with Crohn’s disease (CD) risk in a Chinese population.
Many human diseases involve multiple genes in complex interactions.Large Genome-Wide Association Studies (GWASs) have been considered to hold promise for unraveling such interactions.However,statistic tests for high-o...Many human diseases involve multiple genes in complex interactions.Large Genome-Wide Association Studies (GWASs) have been considered to hold promise for unraveling such interactions.However,statistic tests for high-order epistatic interactions (≥2 Single Nucleotide Polymorphisms (SNPs)) raise enormous computational and analytical challenges.It is well known that the block-wise structure exists in the human genome due to Linkage Disequilibrium (LD) between adjacent SNPs.In this paper,we propose a novel Bayesian method,named BAM,for simultaneously partitioning SNPs into LD-blocks and detecting genome-wide multi-locus epistatic interactions that are associated with multiple diseases.Experimental results on the simulated datasets demonstrate that BAM is powerful and efficient.We also applied BAM on two GWAS datasets from WTCCC,i.e.,Rheumatoid Arthritis and Type 1 Diabetes,and accurately recovered the LD-block structure.Therefore,we believe that BAM is suitable and efficient for the full-scale analysis of multi-disease-related interactions in GWASs.展开更多
AIM： To compare the diagnostic capability of multidetector computed tomography （MDCT） and magnetic resonance imaging （MRI） for the detection of hepatocellular carcinoma （HCC） tumour nodules and their effect on ...AIM： To compare the diagnostic capability of multidetector computed tomography （MDCT） and magnetic resonance imaging （MRI） for the detection of hepatocellular carcinoma （HCC） tumour nodules and their effect on patient management. METHODS： A total of 28 patients （25 male, 3 female, mean age 67 ± 10.8 years） with biopsy-proven HCC were investigated with 64-row MDCT （slice 3 mm native, arterial and portal-venous phase, 120 mL Iomeprol, 4 mL/s, delay by bolus trigger） and MRI （Tlfs fl2d TE/ TR 2.72/129 ms, T2tse TE/TR 102/4000 ms, 5-phase dynamic contrast-enhanced Tlfs fl3d TE/TR 1.56/4.6, Gadolinium-DTPA, slice 4 mm）. Consensus reading of both modalities was used as reference. Tumour nodules were analyzed with respect to number, size, and location. RESULTS： In total, 162 tumour nodules were detected by consensus reading. MRI detected significantly more tumour nodules （159 vs 123, P 〈 0.001） compared to MDCT, with the best sensitivity for early arterial phase MRI. False-negative CT findings included nodules ≤ 5 mm （n = 5）, ≤ 10 mm （n = 17）, ≤ 15 mm （n= 12）,≤20mm（n=4）,andlnodule〉20mm.MRI missed 2 nodules ≤ 10 mm and 1 nodule ≤ 15 mm. On MRI, nodule diameters were greater than on CT （29.2 ≤25.1 mm, range 5-140 mm vs 24.1 ± 22.7 mm, range 4-129 mm, P 〈 0.005）. In 2 patients, MDCT showed only unilobar tumour spread, whereas MRI revealed additional nodules in the contralateral lobe. Detection of these nodules could have changed the therapeutic strategy. CONCLUSION： Contrast-enhanced MRI is superior to 64-row MDCT for the detection of HCC nodules. Patients should be allocated to interventional or operative treatment according to a dedicated MRI-protocol.展开更多
Chronic kidney disease （CKD） is a major public health problem that affects about 10% of the general population. Current approaches to characterize the category and progression of CKD are normally based on renal hist...Chronic kidney disease （CKD） is a major public health problem that affects about 10% of the general population. Current approaches to characterize the category and progression of CKD are normally based on renal histopathological results and clinical parameters. However, this information is not sufficient to predict CKD progression risk reliably or to guide preventive interventions. Nowadays, the appearance of systems biology has brought forward the concepts of ＂-omics＂ technologies, including genomics, transcriptomics, proteomics, and metabolomics. Systems biology, together with molecular analysis approaches such as microarray analysis, genome-wide association studies （GWAS）, and serial analysis of gene expression （SAGE）, has provided the framework for a comprehensive analysis of renal disease and serves as a starting point for generating novel molecular diagnostic tools for use in nephrology. In particular, analysis of urinary mRNA and protein levels is rapidly evolving as a non-invasive approach for CKD monitoring. All these systems biological molecular approaches are required for application of the concept of ＂personalized medicine＂ to progressive CKD, which will result in tailoring therapy for each patient, in contrast to the ＂one-size-fits-all＂ therapies currently in use.展开更多
The 2023 practice guidance on primary sclerosing cholangitis(PSC)and cholangiocarcinoma(CCA)of the American Association for the Study of Liver Diseases(AASLD)came as a needful update to the previous 2010 guidelines on...The 2023 practice guidance on primary sclerosing cholangitis(PSC)and cholangiocarcinoma(CCA)of the American Association for the Study of Liver Diseases(AASLD)came as a needful update to the previous 2010 guidelines on PSC,with a first-time inclusion of dedicated guidance on the diagnosis and management of CCA(1,2).This data-supported approach developed by consensus of an expert panel,provides guidance statements based on analytical review of the relevant literature.展开更多
文摘Single nucleotide polymorphisms (SNPs), which are the most common form of DNA variations, have great potential as a medical diagnostic tool. However, compared to the number of SNPs involved, the available training data sets generally have a fairly small sample size, which is a main challenge to traditional data analysis methods. This paper proposed an improved univariate marginal distribution algorithm (UMDA) named multi-population UMDA (MPUMDA) for disease association study. In order to illustrate the effectiveness of our algorithm, we compared it with some current known methods, and the results showed that our method is potentially interesting as an alter-native tool in disease association study.
文摘AIM: To investigate the association of three polymorphisms in the receptor for advanced glycation end product (RAGE) gene with Crohn’s disease (CD) risk in a Chinese population.
文摘Many human diseases involve multiple genes in complex interactions.Large Genome-Wide Association Studies (GWASs) have been considered to hold promise for unraveling such interactions.However,statistic tests for high-order epistatic interactions (≥2 Single Nucleotide Polymorphisms (SNPs)) raise enormous computational and analytical challenges.It is well known that the block-wise structure exists in the human genome due to Linkage Disequilibrium (LD) between adjacent SNPs.In this paper,we propose a novel Bayesian method,named BAM,for simultaneously partitioning SNPs into LD-blocks and detecting genome-wide multi-locus epistatic interactions that are associated with multiple diseases.Experimental results on the simulated datasets demonstrate that BAM is powerful and efficient.We also applied BAM on two GWAS datasets from WTCCC,i.e.,Rheumatoid Arthritis and Type 1 Diabetes,and accurately recovered the LD-block structure.Therefore,we believe that BAM is suitable and efficient for the full-scale analysis of multi-disease-related interactions in GWASs.
文摘AIM： To compare the diagnostic capability of multidetector computed tomography （MDCT） and magnetic resonance imaging （MRI） for the detection of hepatocellular carcinoma （HCC） tumour nodules and their effect on patient management. METHODS： A total of 28 patients （25 male, 3 female, mean age 67 ± 10.8 years） with biopsy-proven HCC were investigated with 64-row MDCT （slice 3 mm native, arterial and portal-venous phase, 120 mL Iomeprol, 4 mL/s, delay by bolus trigger） and MRI （Tlfs fl2d TE/ TR 2.72/129 ms, T2tse TE/TR 102/4000 ms, 5-phase dynamic contrast-enhanced Tlfs fl3d TE/TR 1.56/4.6, Gadolinium-DTPA, slice 4 mm）. Consensus reading of both modalities was used as reference. Tumour nodules were analyzed with respect to number, size, and location. RESULTS： In total, 162 tumour nodules were detected by consensus reading. MRI detected significantly more tumour nodules （159 vs 123, P 〈 0.001） compared to MDCT, with the best sensitivity for early arterial phase MRI. False-negative CT findings included nodules ≤ 5 mm （n = 5）, ≤ 10 mm （n = 17）, ≤ 15 mm （n= 12）,≤20mm（n=4）,andlnodule〉20mm.MRI missed 2 nodules ≤ 10 mm and 1 nodule ≤ 15 mm. On MRI, nodule diameters were greater than on CT （29.2 ≤25.1 mm, range 5-140 mm vs 24.1 ± 22.7 mm, range 4-129 mm, P 〈 0.005）. In 2 patients, MDCT showed only unilobar tumour spread, whereas MRI revealed additional nodules in the contralateral lobe. Detection of these nodules could have changed the therapeutic strategy. CONCLUSION： Contrast-enhanced MRI is superior to 64-row MDCT for the detection of HCC nodules. Patients should be allocated to interventional or operative treatment according to a dedicated MRI-protocol.
文摘Chronic kidney disease （CKD） is a major public health problem that affects about 10% of the general population. Current approaches to characterize the category and progression of CKD are normally based on renal histopathological results and clinical parameters. However, this information is not sufficient to predict CKD progression risk reliably or to guide preventive interventions. Nowadays, the appearance of systems biology has brought forward the concepts of ＂-omics＂ technologies, including genomics, transcriptomics, proteomics, and metabolomics. Systems biology, together with molecular analysis approaches such as microarray analysis, genome-wide association studies （GWAS）, and serial analysis of gene expression （SAGE）, has provided the framework for a comprehensive analysis of renal disease and serves as a starting point for generating novel molecular diagnostic tools for use in nephrology. In particular, analysis of urinary mRNA and protein levels is rapidly evolving as a non-invasive approach for CKD monitoring. All these systems biological molecular approaches are required for application of the concept of ＂personalized medicine＂ to progressive CKD, which will result in tailoring therapy for each patient, in contrast to the ＂one-size-fits-all＂ therapies currently in use.
文摘The 2023 practice guidance on primary sclerosing cholangitis(PSC)and cholangiocarcinoma(CCA)of the American Association for the Study of Liver Diseases(AASLD)came as a needful update to the previous 2010 guidelines on PSC,with a first-time inclusion of dedicated guidance on the diagnosis and management of CCA(1,2).This data-supported approach developed by consensus of an expert panel,provides guidance statements based on analytical review of the relevant literature.
