Associations of fasting glucose, 2h OGTT, and HbA1c with cfPWV (m/s).

*<p>: Other covariates include heart rate, total cholesterol, triglyceride, HDL-C, and LDL-C.</p><p>cfPWV is presented as mean (standard error).</p

Clinical characteristics of the participants by HbA1c levels.

<p>Abbreviations: HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol;</p><p>OGTT, oral glucose tolerance test; bpm, beats per minute.</p><p>Data are mean ± standard deviations for the continuous variables and percentage for the categorical variables.</p><p>Linear regression model was used to test trend for continuous variables; χ² test was used for the categorical variables.</p

Geometric means of carotid-to-femoral pulse wave velocity (cfPWV, in m/s) by the presence of prediabetes status defined by IFG, IGT, and high HbA1c (5.7–6.4%).

<p>The analyses were adjusted for age, sex, BMI, MAP, heart rate and lipids (total cholesterol, triglyceride, HDL-C and LDL-C). Symbol ‘*’ represents significant difference (p<0.05) between the ‘absence’ and ‘presence’ groups of each marker.</p

Geometric means of cfPWV (in m/s) by the combinations of high HbA1c (5.7–6.4%) with IFG and IGT.

<p>Symbol ‘+’ represents the presence of the corresponding glucose exposures. The analyses were adjusted for age, sex, BMI, MAP, heart rate and lipids (total cholesterol, triglyceride, HDL-C and LDL-C). ‘*’ represents significant difference (p<0.05) comparing individuals with high HbA1c and IFG/IGT with the normal subjects (without any of these abnormalities); ‘**’ represents significant difference (p<0.05) comparing individuals with high HbA1c and IFG/IGT with those who had only high HbA1c; and ‘***’ represents significant difference (p<0.05) comparing individuals with high HbA1c and IFG/IGT with those who had only IFG or IGT.</p

The geometric means of cfPWV (in m/s) by according to HbA1c (in quintiles) by the presence/absence of high blood pressure defined by SBP ≥120 <b>mmHg and DBP ≥80</b><b>mmHg.</b>

<p> The analyses were adjusted for age, sex, BMI, heart rate and lipids.</p

Stratified associations between HbA1c and cfPWV (m/s) by sex, age and BMI.

<p>Analyses were adjusted for age, sex, BMI, total cholesterol, triglyceride, HDL-C, LDL-C, blood pressure, and heart rate but not the strata variable. cfPWV is presented as mean (standard error).</p

<b>Supplementary material for "Identification of Eukaryotic Translation Initiation Factor 4B as a Novel Candidate Gene for Congenital Hypothyroidism"</b>

Congenital hypothyroidism (CH) is the most common endocrine disorder in neonates, but its etiology is still poorly understood. To identify novel genes, we performed whole exome sequencing in 98 CH patients not harboring known CH candidate genes. Through bioinformatic analysis, eukaryotic translation initiation factor 4B (EIF4B) was identified as the most promising candidate gene. The EIF4B gene was inherited in an autosomal recessive model, and one patient with thyroid dysgenesis carried EIF4B biallelic variants (p.S430F/p.P328L). Functional analysis was performed using morpholino, a synthetic short antisense oligonucleotide that contains 25 DNA bases on a methylene morpholine backbone, in zebrafish and CRISPR‒Cas9-mediated gene knockout in mice. In zebrafish, the knockdown of eif4ba/b expression caused thyroid dysgenesis and growth retardation. Thyroid hormone levels were significantly decreased in morphants compared with controls. Thyroxine treatment in morphants partially rescued growth retardation. In mice, the homozygous conceptuses of Eif4b+/- parents did not survive. Eif4b knockout embryos showed severe growth retardation, including thyroid dysgenesis and embryonic lethality before E18.5. These experimental data supported a role for EIF4B function in the pathogenesis of the hypothyroid phenotype seen in CH patients. Our work indicated that EIF4B was identified as a novel candidate gene in CH. EIF4B is essential for animal survival, but further studies are needed to validate its role in the pathogenesis of CH.</p

Regional plot of association results in LD block containing <i>PTPN22</i> at 1p13.2 in GWAS stage.

<p>(A) The results of association for 1,277 genotyped and imputed SNPs in the 1.2-Mb region containing <i>PTPN22</i> with Graves’ disease. The color of each SNP spot reflects its r², with the top typed SNP (large red diamond) within each association locus changing from red to white. Genetic recombination rates, estimated using the 1000 Genomes pilot 1 CHB and JPT samples, are shown in cyan. Physical positions are based on NCBI build 36. (B) Linkage disequilibrium plots of the 1,277 SNPs in the 1.2-Mb region containing <i>PTPN22</i>. The r² value is estimated by the genotype data of GD cases and controls enrolled in the GWAS. We constructed the plots using Haploview software version 4.2. (C) The plots of the association of 474 genotyped and imputed SNPs with GD. These 474 SNPs are located in a ~445-kb linkage disequilibrium region containing <i>PTPN22</i> and were marked with arrows in panels A and B. </p

RFLP Analysis of Different S. suis 2 Isolates

<p> S. suis S10: a highly virulent strain from China; <i>S</i>. <i>suis</i> 9801: swine isolate from Jiangsu Province in 1998; S. suis Habb: human isolate from Jiangsu Province in 1998; S. suis ZYS3: swine isolate from Sichuan Province in 2005; S. suis ZYH13: human isolate from Sichuan Province in 2005; M: 1 kb DNA Ladder (MBI Ferments, Gdansk, Poland). </p

Phylogenetic Trees of Six Representative Isolates Based on Comparison of 16S rDNA and Five Putative Virulence-Associated-Factor Genes with Known Sequences

<p>Swine isolates from Sichuan ( S. suis ZYS3 and S. suis ZYS8) labeled in green, human isolates ( S. suis ZYH13 and S. suis ZYH14) from Sichuan labeled in red, Jiangsu isolates from 1998 ( S. suis 9801 and S. suis Habb) labeled in blue, and the standard highly virulent strain S. suis P1/7 labeled in pink. All representative strains from other streptococcus species or isolates of S. suis 2 are as indicated in the tree. </p