OBJECTIVETo investigate the role of lipoprotein lipase (LPL) gene on Chinese patients with hypertriglyceridemic type 2 diabetes.

METHODSThree subject groups, including hypertriglyceridemic group, normalipidemic type 2 diabetes group and healthy controls, were recruited and screened for sequence changes in LPL gene with PCR, SSCP, restriction analysis and direct DNA sequencing. LPL mass and activity in post-heparin plasma and in in vitro expression were investigated. Comparative modeling was performed via Swiss-PDB Viewer to provide the potential 2-D structures of wildtype and mutant proteins.

RESULTSFour missense mutations, Ala71Thr, Val18Ile, Gly188Glu and Glu242Lys, were identified in patients with hypertriglyceridemic type 2 diabetes, and not in both normalipidemic diabetes and the control subjects. The four missense mutations were located in the highly conserved amino acid sites, which are involved in highly conserved exon 3, 5, or 6 regions. They led to reduced LPL mass and enzyme activities in both post-heparin plasma and in vitro expression. The modeled structures displayed the differences to a great extent between the mutant and wide-type molecules.

CONCLUSIONThese results indicated that the 4 missense mutations lead to LPL deficiency and subsequent hypertriglyceridemia. The LPL deficiency predispose a progressive diabetic pathway to those affected individuals. LPL gene is one of susceptibility gene for hypertriglyceridemic type 2 diabetes.

Asian Continental Ancestry Group ; Diabetes Mellitus, Type 2 ; complications ; genetics ; Female ; Genetic Predisposition to Disease ; Humans ; Hypertriglyceridemia ; complications ; enzymology ; genetics ; Lipoprotein Lipase ; genetics ; Male ; Middle Aged ; Mutation, Missense ; Polymerase Chain Reaction ; Polymorphism, Single-Stranded Conformational

PURPOSE: Fusarium species are among prevalent airborne fungi and causative agents of human respiratory atopic disorders. We previously identified a 36.5-kDa F. proliferatum component recognized by IgE antibodies in 9 (53%) of the 17 F. proliferatum-sensitized atopic serum samples. The purpose of this study is to characterize the 36.5-kDa allergen of F. proliferatum. METHODS: Characterization of allergens and determination of IgE cross-reactivity were performed by cDNA cloning/expression and immunoblot inhibition studies. RESULTS: Based on the finding that the 36.5-kDa IgE-binding component reacted with the mouse monoclonal antibody FUM20 against fungal vacuolar serine protease allergens, the cDNA of F. proliferatum vacuolar serine protease (Fus p 9.0101) was subsequently cloned. Nine serum samples from respiratory atopic patients with IgE binding to the vacuolar serine protease allergen of Penicillium chrysogenum (Pen ch 18) also showed IgE-immunoblot reactivity to rFus p 9.0101. The purified rFus p 9.0101 can inhibit IgE and FUM20 binding to the 36.5-kDa component of F. proliferatum. Thus, a novel and important Fus p 9.0101 was identified. The rPen ch 18 can inhibit IgE binding to Fus p 9.0101. It indicates that IgE cross-reactivity between Fus p 9.0101 and Pen ch 18 also exists. Furthermore, neither rFus p 9.0101 K88A nor rPen ch 18 K89A mutants inhibited IgE binding to rFus p 9.0101. Lys88 was considered a critical core amino acid in IgE binding to r Fus p 9.0101 and a residue responsible for IgE cross-reactivity between Fus p 9.0101 and Pen ch 18 allergens. CONCLUSIONS: Results obtained from this study indicate that vacuolar serine protease may be a major allergen of F. proliferatum and an important IgE cross-reactive pan-fungal allergen, and provide important bases for clinical diagnosis of fungal allergy.
Allergens ; Animals ; Antibodies ; Clone Cells ; Diagnosis ; DNA, Complementary ; Fungi ; Fusarium* ; Humans ; Hypersensitivity ; Immunoglobulin E ; Mice ; Penicillium chrysogenum ; Serine Proteases* ; Serine*

Fusarium head blight (FHB) caused by Fusarium graminearum is a devastating disease that results in extensive yield losses to wheat and barley. A green fluorescent protein (GFP) expressing plasmid pRP22-GFP was constructed for monitoring the colonization of two biocontrol agents, Brevibacillus brevis ZJY-1 and Bacillus subtilis ZJY-116, on the spikes of barley and their effect on suppression of FHB. Survival and colonization of the Brevibacillus brevis ZJY-1 and Bacillus subtilis ZJY-116 strains on spikes of barley were observed by tracking the bacterial transformants with GFP expression. Our field study revealed that plasmid pRP22-GFP was stably maintained in the bacterial strains without selective pressure. The retrieved GFP-tagged strains showed that the bacterial population fluctuation accorded with that of the rain events. Furthermore, both biocontrol strains gave significant protection against FHB on spikes of barley in fields. The greater suppression of barley FHB disease was resulted from the treatment of barley spikes with biocontrol agents before inoculation with F. graminearum.
Bacillus ; classification ; cytology ; isolation & purification ; physiology ; Cell Survival ; physiology ; Fusarium ; isolation & purification ; pathogenicity ; physiology ; Hordeum ; microbiology ; parasitology ; Pest Control, Biological ; methods ; Plant Diseases ; microbiology ; parasitology ; Species Specificity ; Survival Analysis

OBJECTIVETo investigate the role of a potential diabetes-related mitochondrial region, which includes two previously reported mutations, 3243A-->G and 3316G-->A, in Chinese patients with adult-onset type 2 diabetes.

METHODSA total of 277 patients and 241 normal subjects were recruited for the study. Mitochondrial nt 3116 - 3353, which spans the 16S rRNA, tRNA(leu(UUR)) and the NADH dehydrogenase 1 gene, were detected using polymerase chain reaction (PCR), direct DNA sequencing, PCR-restriction fragment length polymorphism and allele-specific PCR. Variants were analyzed by two-tailed Fisher exact test. The function of the variants in 16S rRNA were predicted for minimal free energy secondary structures by RNA folding software mfold version 3.

RESULTSFour homoplasmic nucleotide substitutions were observed, 3200T-->C, 3206C-->T, 3290T-->C and 3316G-->A. Only the 3200T-->C mutation is present in the diabetic population and absent in the control population. No statistically significant associations were found between the other three variants and type 2 diabetes. The 3200T-->C and 3206C-->T nucleotide substitutions located in 16S rRNA are novel variants. The 3200T-->C caused a great alteration in the minimal free energy secondary structure model while the 3206C-->T altered normal 16S rRNA structure little.

CONCLUSIONSThe results suggest that the 3200T-->C mutation is linked to the development of type 2 diabetes, but that the other observed mutations are neutral. In contrast to the Japanese studies, the 3316G-->A does not appear to be related to type 2 diabetes.

Age of Onset ; Aged ; Alleles ; Base Sequence ; DNA Mutational Analysis ; DNA, Mitochondrial ; chemistry ; genetics ; Diabetes Mellitus, Type 2 ; genetics ; Humans ; Middle Aged ; Models, Molecular ; Nucleic Acid Conformation ; Point Mutation ; Polymerase Chain Reaction ; methods ; Polymorphism, Restriction Fragment Length ; RNA, Ribosomal, 16S ; chemistry ; genetics

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.