Search

Abstract Background Handgrip strength (HGS) has been widely studied in clinical and epidemiological settings, but the relationship between HGS and pulmonary function is still controversial. This study analysed pulmonary function and HGS stratified by sex and age in a healthy Chinese Han population, as well as the associations between HGS and pulmonary function parameters. Methods HGS was measured by a Jamar dynamometer and pulmonary function was tested using a portable spirometer. Frequencies and variables are presented as percentages and means ± standard deviations, respectively. Chi-square tests were used for comparisons of categorical variables, and Student’s t-tests or Mann–Whitney U-tests were used for continuous variables. Pearson’s correlation coefficients were used to analyse the normally distributed variables, and Spearman correlation coefficients were used to analyse the non-normally distributed variables. Multivariate linear regression models were employed to explore the relationships between HGS and parameters of pulmonary function. The statistical significance was set at p

Background/Aims: In this study, we aim to investigate the association between renal function and arterial stiffness in a Chinese Han population, and further to discuss the effects of smoking on renal function. Methods: We collected the data of the brachium-ankle pulse wave velocity (baPWV), blood pressure, blood chemistry and smoking status. Then, the multiple linear regression was done to explore the relationship between estimated glomerular filtration (eGFR) and baPWV. Further, the parameters were compared among the four groups divided according to the quartiles of baPWV. Finally, the baPWV, eGFR and albuminuria values were compared between smokers and non-smokers. Results: baPWV is associated with eGFR in the correlation analysis and univariate linear regression model. After adjustment, the pulse pressure (PP) instead of baPWV showed a significant association with eGFR. Nevertheless, the eGFR values differed among the four baPWV groups; the baPWV values were significantly higher in the subjects at the CKD (eGFR

Background: Hypouricemia is caused by various diseases and disorders, such as hepatic failure, Fanconi renotubular syndrome, nutritional deficiencies and genetic defects. Genetic defects of the molybdoflavoprotein enzymes induce hypouricemia and xanthinuria. Here, we identified a patient whose plasma and urine uric acid levels were both extremely low and aimed to identify the pathogenic gene and verify its mechanism. Methods: Using next-generation sequencing (NGS), we detected a mutation in the human molybdenum cofactor sulfurase (MCSU) gene that may cause hypouricemia. We cultured L02 cells, knocked down MCSU with RNAi, and then detected the uric acid and MCSU concentrations, xanthine oxidase (XOD) and xanthine dehydrogenase (XDH) activity levels, and xanthine/hypoxanthine concentrations in cell lysates and culture supernatants. Results: The NGS results showed that the patient had a mutation in the human MCSU gene. The in vitro study showed that RNAi of MCSU caused the uric acid, human MCSU concentrations, the XOD and XDH activity levels among cellular proteins and culture supernatants to be extremely low relative to those of the control. However, the xanthine/hypoxanthine concentrations were much higher than those of the control. Conclusions: We strongly confirmed the pathogenicity of the human MCSU gene.

Background. MicroRNAs (miRNAs) have been found in virtually all body fluids and used successfully as biomarkers for various diseases. Evidence indicates that miRNAs have important roles in IgA nephropathy (IgAN), a major cause of renal failure. In this study, we looked for differentially expressed miRNAs in IgAN and further evaluated the correlations between candidate miRNAs and the severity of IgAN.Methods. Microarray and RT-qRCR (real-time quantitative polymerase chain reaction) were sequentially used to screen and further verify miRNA expression profiles in urinary sediments of IgAN patients in two independent cohorts. The screening cohort consisted of 32 urine samples from 18 patients with IgAN, 4 patients with MN (membranous nephropathy), 4 patients with MCD (minimal changes disease) and 6 healthy subjects; the validation cohort consisted of 102 IgAN patients, 41 MN patients, 27 MCD patients and 34 healthy subjects. The renal pathological lesions of patients with IgAN were evaluated according to Lee’s grading system and Oxford classification.Results. At the screening phase, significance analysis of microarrays analysis showed that no miRNA was differentially expressed in the IgAN group compared to all control groups. But IgAN grade I–II and III subgroups (according to Lee’s grading system) shared dysregulation of two miRNAs (miR-3613-3p and miR-4668-5p). At the validation phase, RT-qPCR results showed that urinary level of miR-3613-3p was significantly lower in IgAN than that in MN, MCD and healthy controls (0.47, 0.44 and 0.24 folds, respectively, all P < 0.01 by Mann–Whitney U test); urinary level of miR-4668-5p was also significantly lower in IgAN than that in healthy controls (0.49 fold, P < 0.01). Significant correlations were found between urinary levels of miR-3613-3p with 24-hour urinary protein excretion (Spearman r = 0.50, P = 0.034), eGFR (estimated glomerular filtration rate) (r = − 0.48, P = 0.043) and Lee’s grades (r = 0.57, P = 0.014). Similarly, miR-4668-5p was significantly correlated with eGFR (r = − 0.50, P = 0.034) and Lee’s grades (r = 0.57, P = 0.013). For segmental glomerulosclerosis according to Oxford classification, patients scored as S0 had significantly lower levels of urinary miR-3613-3p and miR-4668-5p than those scored as S1 (0.41 and 0.43 folds, respectively, all P < 0.05).Conclusions. The expression profile of miRNAs was significantly altered in urinary sediments from patients with IgAN. Urinary expression of miR-3613-3p was down-regulated in patients with IgAN. Moreover, urinary levels of both miR-3613-3p and miR-4668-5p were correlated with disease severity. Further studies are needed to explore the roles of miR-3613-3p and miR-4668-5p in the pathogenesis and progression of IgA nephropathy.

Abstract Background Productive life (PL) of a cow is the time the cow remains in the milking herd from first calving to exit from the herd due to culling or death and is an important economic trait in U.S. Holstein cattle. The large samples of Holstein genomic evaluation data that have become available recently provided unprecedented statistical power to identify genetic factors affecting PL in Holstein cows using the approach of genome-wide association study (GWAS). Methods The GWAS analysis used 1,103,641 Holstein cows with phenotypic observations on PL and genotypes of 75,282 single nucleotide polymorphism (SNP) markers. The statistical tests and estimation of SNP additive and dominance effects used the approximate generalized least squares method implemented by the EPISNPmpi computer program. Results The GWAS detected 5390 significant additive effects of PL distributed over all 29 autosomes and the X–Y nonrecombining region of the X chromosome (Chr31). Two chromosome regions had the most significant and largest cluster of additive effects, the SLC4A4-GC-NPFFR2 (SGN) region of Chr06 with pleiotropic effects for PL, fertility, somatic cell score and milk yield; and the 32–52 Mb region of Chr10 with peak effects for PL in or near RASGRP1 with many important immunity functions. The dominance tests detected 38 significant dominance effects including 12 dominance effects with sharply negative homozygous recessive genotypes on Chr18, Chr05, Chr23 and Chr24. Conclusions The GWAS results showed that highly significant genetic effects for PL were in chromosome regions known to have highly significant effects for fertility and health and a chromosome region with multiple genes with reproductive and immunity functions. SNPs with rare but sharply negative homozygous recessive genotypes for PL existed and should be used for eliminating heifers carrying those homozygous recessive genotypes.

The 4-valent (4 v) and 9-valent (9 v) human papillomavirus (HPV) vaccines are approved in China for females aged 9–45 years. However, the real-world impact of 4vHPV or 9vHPV vaccination for the prevention of high-grade cervical disease in Chinese women is lacking. Two post-marketing surveillance studies will be conducted to measure the occurrence of high-grade cervical lesions in Chinese women who had received ≥1 dose of the 4vHPV (aged 20–45 years) or 9vHPV (aged 16–26 years) vaccine in Ningbo, China. Vaccination data will be extracted from the Ningbo Regional Health Information Platform (NRHIP) from the date of the first 4vHPV (January 9, 2018) or the first 9vHPV (January 25, 2019) vaccination to March 31, 2021. The primary 4vHPV and 9vHPV vaccinated cohorts will include women vaccinated per protocol. The 4vHPV/9vHPV vaccinated test-negative (cervical HPV negative; ThinPrep cytology test negative) and corresponding matched unvaccinated HPV test-negative sub-cohorts will also be assessed. Outcomes will be the occurrence of new-onset cervical intraepithelial neoplasia grade 2/3, adenocarcinoma in situ, and invasive cervical cancer. This study aims to demonstrate that such a methodological approach is feasible and can be used to assess the impact of HPV vaccination in other regions across China.

Background The 9-valent human papillomavirus (9vHPV) vaccine was introduced in China in 2018. This study was conducted to monitor the occurrence of new-onset autoimmune diseases (AIs) in Chinese women vaccinated with the 9vHPV vaccine and adverse pregnancy outcomes in infants born to mothers with inadvertent pregnancy exposure. Research design and methods Women who received the first dose of the 9vHPV vaccine at age 16–26 years in Ningbo between January 2019 and March 2021 were monitored in the Ningbo Regional Health Information Platform. New-onset cases of seven pre-specified AIs diagnosed within six months after vaccination were collected. Cases of stillbirth and 23 major congenital anomalies diagnosed within three months of birth in target infants were collected. Results A total of 102,670 doses of the 9vHPV vaccine were administered to 41,609 women who had received no other HPV vaccine. New-onset AIs were diagnosed in 36 women, comprising 21 Hashimoto’s, 11 Graves’, and 4 uveitis disease cases. Among 50 women with maternal vaccination exposure, no stillbirths were observed. One case of microtia was observed. Conclusions In this first post-marketing surveillance of the 9vHPV vaccine in China, no safety signals were identified when putting the results in context to published data.

Abstract Background Non-alcoholic fatty liver disease (NAFLD) is the most prevalent cause of chronic hepatic disease and results in non-alcoholic steatohepatitis (NASH), which progresses to fibrosis and cirrhosis. Although the Leptin deficient rodent models are widely used in study of metabolic syndrome and obesity, they fail to develop liver injuries as in patients. Methods Due to the high similarity with humans, we generated Leptin-deficient (Leptin −/− ) pigs to investigate the mechanisms and clinical trials of obesity and NAFLD caused by Leptin. Results The Leptin −/− pigs showed increased body fat and significant insulin resistance at the age of 12 months. Moreover, Leptin −/− pig developed fatty liver, non-alcoholic steatohepatitis and hepatic fibrosis with age. Absence of Leptin in pig reduced the phosphorylation of JAK2-STAT3 and AMPK. The inactivation of JAK2-STAT3 and AMPK enhanced fatty acid β-oxidation and leaded to mitochondrial autophagy respectively, and both contributed to increased oxidative stress in liver cells. In contrast with Leptin −/− pig, although Leptin deletion in rat liver inhibited JAK2-STAT3 phosphorylation, the activation of AMPK pathway might prevent liver injury. Therefore, β-oxidation, mitochondrial autophagy and hepatic fibrosis did not occurred in Leptin −/− rat livers. Conclusions The Leptin-deficient pigs presents an ideal model to illustrate the full spectrum of human NAFLD. The activity of AMPK signaling pathway suggests a potential target to develop new strategy for the diagnosis and treatment of NAFLD.

Substantial proteolysis occurs and free amino acids can be degraded to biogenic amines by decarboxylation during stylo (Stylosanthes guianensis) ensiling. High biogenic amine concentrations in silage are harmful to the health of ruminant animals. The purposes of this work were to (1) analyze the biogenic amines and amino acids concentrations, bacterial composition, and fermentation profile of spontaneously fermented stylo silage, (2) explore the effect of formic acid or sugar additive on these silage parameters, and (3) further reveal the correlations between silage amines and fermentation parameters, amino acids, and bacteria. Freshly chopped stylo was treated with distilled water (control), formic acid (4 mL/kg), and sugar (20 g/kg) and fermented for 28 days. The results indicated that putrescine (321 mg/kg dry matter), cadaverine (384 mg/kg dry matter), and tyramine (127 mg/kg dry matter) rapidly increased in concentration and become predominant in the control silage after 28 days of fermentation. Applying formic acid and sugar at ensiling, especially the acidifier, significantly decreased putrescine, cadaverine, tyramine, and total biogenic amine concentrations compared with the control treatment (p < 0.0001). Clostridium pabulibutyricum, Weissella cibaria and W. paramesenteroides were the predominant bacteria in the control silage, and the application of both additives remarkably lowered their relative abundance in comparison with the control treatment (p < 0.001). Correlation analysis showed that putrescine, cadaverine, and tyramine were positively related to pH, butyric acid, non-protein nitrogen, and ammonia nitrogen (p < 0.01). These amines also had significant correlations with C. pabulibutyricum, W. cibaria and W. paramesenteroides (p < 0.001). Putrescine, cadaverine, and tyramine were the main biogenic amines and C. pabulibutyricum was the predominant undesirable bacterium in naturally fermented stylo silage. C. pabulibutyricum, W. cibaria and W. paramesenteroides were positively related to putrescine, cadaverine, and tyramine formation. The application of formic acid or sugar significantly reduced the undesirable bacterial population and improved the fermentation and hygienic quality of the stylo silage. These findings lay the foundation for further elucidating the microbial mechanism underlying the main biogenic amine formation during fermentation of stylo silage.

Sheep and goat may become carriers of some zoonotic diseases. They are important livestock and experimental model animals for human beings. The fast and accurate identification of genetic materials originating from sheep and goat can prevent and inhibit the spread of some zoonotic diseases, monitor market product quality, and maintain the stability of animal husbandry and food industries. This study proposed a methodology for identifying sheep and goat common specific sites from a genome-wide perspective. A total of 150 specific sites were selected from three data sources, including the coding sequences of single copy genes from nine species (sheep, goat, cow, pig, dog, horse, human, mouse, and chicken), the dbSNPs for these species, and human 100-way alignment data. These 150 sites exhibited low intraspecific heterogeneity in the resequencing data of 1450 samples from five species (sheep, goat, cow, pig, and chicken) and high interspecific divergence in the human 100-way alignment data after quality control. The results were proven to be reliable at the data level. Using the process proposed in this study, specific sites of other species can be screened, and genome-level species identification can be performed using the screened sites.

A genome-wide association study of resistance to retained placenta (RETP) using 632,212 Holstein cows and 74,747 SNPs identified 200 additive effects with p-values < 10−8 on thirteen chromosomes but no dominance effect was statistically significant. The regions of 87.61–88.74 Mb of Chr09 about 1.13 Mb in size had the most significant effect in LOC112448080 and other highly significant effects in CCDC170 and ESR1, and in or near RMND1 and AKAP12. Four non-ESR1 genes in this region were reported to be involved in ESR1 fusions in humans. Chr23 had the largest number of significant effects that peaked in SLC17A1, which was involved in urate metabolism and transport that could contribute to kidney disease. The PKHD1 gene contained seven significant effects and was downstream of another six significant effects. The ACOT13 gene also had a highly significant effect. Both PKHD1 and ACOT13 were associated with kidney disease. Another highly significant effect was upstream of BOLA-DQA2. The KITLG gene of Chr05 that acts in utero in germ cell and neural cell development, and hematopoiesis was upstream of a highly significant effect, contained a significant effect, and was between another two significant effects. The results of this study provided a new understanding of genetic factors underlying RETP in U.S. Holstein cows.

A genome-wide association study (GWAS) of fat percentage (FPC) using 1,231,898 first lactation cows and 75,198 SNPs confirmed a previous result that a Chr14 region about 9.38 Mb in size (0.14–9.52 Mb) had significant inter-chromosome additive × additive (A×A) effects with all chromosomes and revealed many new such effects. This study divides this 9.38 Mb region into two sub-regions, Chr14a at 0.14–0.88 Mb (0.74 Mb in size) with 78% and Chr14b at 2.21–9.52 Mb (7.31 Mb in size) with 22% of the 2761 significant A×A effects. These two sub-regions were separated by a 1.3 Mb gap at 0.9–2.2 Mb without significant inter-chromosome A×A effects. The PPP1R16A-FOXH1-CYHR1-TONSL (PFCT) region of Chr14a (29 Kb in size) with four SNPs had the largest number of inter-chromosome A×A effects (1141 pairs) with all chromosomes, including the most significant inter-chromosome A×A effects. The SLC4A4-GC-NPFFR2 (SGN) region of Chr06, known to have highly significant additive effects for some production, fertility and health traits, specifically interacted with the PFCT region and a Chr14a region with CPSF1, ADCK5, SLC52A2, DGAT1, SMPD5 and PARP10 (CASDSP) known to have highly significant additive effects for milk production traits. The most significant effects were between an SNP in SGN and four SNPs in PFCT. The CASDSP region mostly interacted with the SGN region. In the Chr14b region, the 2.28–2.42 Mb region (138.46 Kb in size) lacking coding genes had the largest cluster of A×A effects, interacting with seventeen chromosomes. The results from this study provide high-confidence evidence towards the understanding of the genetic mechanism of FPC in Holstein cows.

The accuracy of predicting seven human phenotypes of 3657–7564 individuals using global epistasis effects was evaluated and compared to the accuracy of haplotype genomic prediction using 380,705 SNPs and 10-fold cross-validation studies. The seven human phenotypes were the normality transformed high density lipoproteins (HDL), low density lipoproteins (LDL), total cholesterol (TC), triglycerides (TG), weight (WT), and the original phenotypic observations of height (HTo) and body mass index (BMIo). Fourth-order epistasis effects virtually had no contribution to the phenotypic variances, and third-order epistasis effects did not affect the prediction accuracy. Without haplotype effects in the prediction model, pairwise epistasis effects improved the prediction accuracy over the SNP models for six traits, with accuracy increases of 2.41%, 3.85%, 0.70%, 0.97%, 0.62% and 0.93% for HDL, LDL, TC, HTo, WT and BMIo respectively. However, none of the epistasis models had higher prediction accuracy than the haplotype models we previously reported. The epistasis model for TG decreased the prediction accuracy by 2.35% relative to the accuracy of the SNP model. The integrated models with epistasis and haplotype effects had slightly higher prediction accuracy than the haplotype models for two traits, HDL and BMIo. These two traits were the only traits where additive × dominance effects increased the prediction accuracy. These results indicated that haplotype effects containing local high-order epistasis effects had a tendency to be more important than global pairwise epistasis effects for the seven human phenotypes, and that the genetic mechanism of HDL and BMIo was more complex than that of the other traits.

Abstract Background Genomic selection using single nucleotide polymorphism (SNP) markers has been widely used for genetic improvement of livestock, but most current methods of genomic selection are based on SNP models. In this study, we investigated the prediction accuracies of haplotype models based on fixed chromosome distances and gene boundaries compared to those of SNP models for genomic prediction of phenotypic values. We also examined the reasons for the successes and failures of haplotype genomic prediction. Methods We analyzed a swine population of 3195 Duroc boars with records on eight traits: body judging score (BJS), teat number (TN), age (AGW), loin muscle area (LMA), loin muscle depth (LMD) and back fat thickness (BF) at 100 kg live weight, and average daily gain (ADG) and feed conversion rate (FCR) from 30 to100 kg live weight. Ten-fold validation was used to evaluate the prediction accuracy of each SNP model and each multi-allelic haplotype model based on 488,124 autosomal SNPs from low-coverage sequencing. Haplotype blocks were defined using fixed chromosome distances or gene boundaries. Results Compared to the best SNP model, the accuracy of predicting phenotypic values using a haplotype model was greater by 7.4% for BJS, 7.1% for AGW, 6.6% for ADG, 4.9% for FCR, 2.7% for LMA, 1.9% for LMD, 1.4% for BF, and 0.3% for TN. The use of gene-based haplotype blocks resulted in the best prediction accuracy for LMA, LMD, and TN. Compared to estimates of SNP additive heritability, estimates of haplotype epistasis heritability were strongly correlated with the increase in prediction accuracy by haplotype models. The increase in prediction accuracy was largest for BJS, AGW, ADG, and FCR, which also had the largest estimates of haplotype epistasis heritability, 24.4% for BJS, 14.3% for AGW, 14.5% for ADG, and 17.7% for FCR. SNP and haplotype heritability profiles across the genome identified several genes with large genetic contributions to phenotypes: NUDT3 for LMA, LMD and BF, VRTN for TN, COL5A2 for BJS, BSND for ADG, and CARTPT for FCR. Conclusions Haplotype prediction models improved the accuracy for genomic prediction of phenotypes in Duroc pigs. For some traits, the best prediction accuracy was obtained with haplotypes defined using gene regions, which provides evidence that functional genomic information can improve the accuracy of haplotype genomic prediction for certain traits.

The impact of genomic epistasis effects on the accuracy of predicting the phenotypic values of residual feed intake (RFI) in U.S. Holstein cows was evaluated using 6215 Holstein cows and 78,964 SNPs. Two SNP models and seven epistasis models were initially evaluated. Heritability estimates and the accuracy of predicting the RFI phenotypic values from 10-fold cross-validation studies identified the model with SNP additive effects and additive × additive (A×A) epistasis effects (A + A×A model) to be the best prediction model. Under the A + A×A model, additive heritability was 0.141, and A×A heritability was 0.263 that consisted of 0.260 inter-chromosome A×A heritability and 0.003 intra-chromosome A×A heritability, showing that inter-chromosome A×A effects were responsible for the accuracy increases due to A×A. Under the SNP additive model (A-only model), the additive heritability was 0.171. In the 10 validation populations, the average accuracy for predicting the RFI phenotypic values was 0.246 (with range 0.197–0.333) under A + A×A model and was 0.231 (with range of 0.188–0.319) under the A-only model. The average increase in the accuracy of predicting the RFI phenotypic values by the A + A×A model over the A-only model was 6.49% (with range of 3.02–14.29%). Results in this study showed A×A epistasis effects had a positive impact on the accuracy of predicting the RFI phenotypic values when combined with additive effects in the prediction model.

The rapid growth in genomic selection data provides unprecedented opportunities to discover and utilize complex genetic effects for improving phenotypes, but the methodology is lacking. Epistasis effects are interaction effects, and haplotype effects may contain local high-order epistasis effects. Multifactorial methods with SNP, haplotype, and epistasis effects up to the third-order are developed to investigate the contributions of global low-order and local high-order epistasis effects to the phenotypic variance and the accuracy of genomic prediction of quantitative traits. These methods include genomic best linear unbiased prediction (GBLUP) with associated reliability for individuals with and without phenotypic observations, including a computationally efficient GBLUP method for large validation populations, and genomic restricted maximum estimation (GREML) of the variance and associated heritability using a combination of EM-REML and AI-REML iterative algorithms. These methods were developed for two models, Model-I with 10 effect types and Model-II with 13 effect types, including intra- and inter-chromosome pairwise epistasis effects that replace the pairwise epistasis effects of Model-I. GREML heritability estimate and GBLUP effect estimate for each effect of an effect type are derived, except for third-order epistasis effects. The multifactorial models evaluate each effect type based on the phenotypic values adjusted for the remaining effect types and can use more effect types than separate models of SNP, haplotype, and epistasis effects, providing a methodology capability to evaluate the contributions of complex genetic effects to the phenotypic variance and prediction accuracy and to discover and utilize complex genetic effects for improving the phenotypes of quantitative traits.

A genome-wide association study (GWAS) of the daughter pregnancy rate (DPR), cow conception rate (CCR), and heifer conception rate (HCR) using 1,001,374–1,194,736 first-lactation Holstein cows and 75,140–75,295 SNPs identified 7567, 3798, and 726 additive effects, as well as 22, 27, and 25 dominance effects for DPR, CCR, and HCR, respectively, with log10(1/p) > 8. Most of these effects were new effects, and some new effects were in or near genes known to affect reproduction including GNRHR, SHBG, and ESR1, and a gene cluster of pregnancy-associated glycoproteins. The confirmed effects included those in or near the SLC4A4-GC-NPFFR2 and AFF1 regions of Chr06 and the KALRN region of Chr01. Eleven SNPs in the CEBPG-PEPD-CHST8 region of Chr18, the AFF1-KLHL8 region of Chr06, and the CCDC14-KALRN region of Chr01 with sharply negative allelic effects and dominance values for the recessive homozygous genotypes were recommended for heifer culling. Two SNPs in and near the AGMO region of Chr04 that were sharply negative for HCR and age at first calving, but slightly positive for the yield traits could also be considered for heifer culling. The results from this study provided new evidence and understanding about the genetic variants and genome regions affecting the three fertility traits in U.S. Holstein cows.

Aim: This study aims to investigate the association between the use of dipeptidyl peptidase-4 inhibitors (DPP-4i), glucagon-like peptide-1 receptor agonists (GLP-1 RAs), or sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and the risk of fracture among patients with type 2 diabetes mellitus.Methods: Medline, Embase, Cochrane Library, and Clinical-Trials.gov databases were searched for randomized controlled trials (RCTs). Network meta-analysis was performed for total fracture and a series of secondary outcomes.Results: A total of 177 RCTs (n = 165,081) involving the risk of fracture were identified (a median follow-up of 26 weeks). DPP-4i, GLP-1 RAs, and SGLT-2i did not increase total fracture risk compared with insulin (odds ratio: 0.86, 95% confidence interval: 0.39–1.90; 1.05, 0.54–2.04; 0.88, and 0.39–1.97, respectively), metformin (1.41, 0.48–4.19; 1.72, 0.55–5.38; 1.44, 0.48–4.30), sulfonylureas (0.77, 0.50–1.20; 0.94, 0.55–1.62; 0.79, 0.48–1.31), thiazolidinediones (0.82, 0.27–2.44; 1.00, 0.32–3.10; 0.83, 0.27–2.57), α-glucosidase inhibitor (4.92, 0.23–103.83; 5.99, 0.28–130.37; 5.01, 0.23–107.48), and placebo (1.04, 0.84–1.29; 1.27, 0.88–1.83; 1.06, 0.81–1.39).Conclusions: The use of DPP-4i, GLP-1 RAs, or SGLT-2i is unlikely to increase the risk of fracture among type 2 diabetes mellitus patients.

A genome-wide association study (GWAS) of age at first calving (AFC) using 813,114 first lactation Holstein cows and 75,524 SNPs identified 2063 additive effects and 29 dominance effects with p-values < 10−8. Three chromosomes had highly significant additive effects in the regions of 7.86–8.12 Mb of Chr15, 27.07–27.48 Mb and 31.25–32.11 Mb of Chr19, and 26.92–32.60 Mb of Chr23. Two of the genes in those regions were reproductive hormone genes with known biological functions that should be relevant to AFC, the sex hormone binding globulin (SHBG) gene, and the progesterone receptor (PGR) gene. The most significant dominance effects were near or in EIF4B and AAAS of Chr05 and AFF1 and KLHL8 of Chr06. All dominance effects were positive overdominance effects where the heterozygous genotype had an advantage, and the homozygous recessive genotype of each SNP had a very negative dominance value. Results from this study provided new evidence and understanding about the genetic variants and genome regions affecting AFC in U.S. Holstein cows.

Background and Aims. The effects of cortisol on cardiovascular diseases (CVD) and CVD risk are unknown, especially in patients with type 2 diabetes mellitus (T2DM). Furthermore, it is unclear whether 25 (OH)D can alter the associations of cortisol with CVD and CVD risk factors. Thus, the present study was to investigate the associations of serum cortisol with CVD and CVD risk factors and whether 25 (OH)D altered these associations among patients with T2DM. Materials and methods. A total of 762 patients diagnosed with T2DM were recruited. The levels of serum cortisol and 25 (OH)D were measured with a liquid chromatography-tandem mass spectrometry. Logistic regression and linear regression were used to assess the association of cortisol with CVD and multiple cardiovascular risk factors. Modification analyses were performed to identify whether 25 (OH)D altered the above associations. Results. A 1 SD increase in cortisol was associated with a higher prevalence of stroke (odds ratio (OR): 1.25, 95% confidence interval (CI): 1.05, 1.50). Elevated cortisol was associated with related cardiovascular risk factors, including deceased ß cell function, high-density lipoprotein-cholesterol (HDL-C), and fasting insulin, as well as increased triglycerides (TG), low-density lipoprotein-cholesterol (LDL-C), fasting plasma glucose (FPG), and glycated hemoglobin (HbA1c). In addition, modification analyses suggested that the associations of cortisol with ß cell function, fasting insulin, FPG, and HbA1c were modified by 25 (OH)D. Conclusions. Serum cortisol was associated with the prevalence of stroke and cardiovascular risk factors, and the associations of cortisol with cardiovascular risk factors were moderated by 25 (OH)D, suggesting that T2DM patients with exposure to lower 25 (OH)D levels and higher cortisol levels were more susceptible to have higher cardiovascular risk factors.

Genomic prediction using multi-allelic haplotype models improved the prediction accuracy for all seven human phenotypes, the normality transformed high density lipoproteins, low density lipoproteins, total cholesterol, triglycerides, weight, and the original height and body mass index without normality transformation. Eight SNP sets with 40,941-380,705 SNPs were evaluated. The increase in prediction accuracy due to haplotypes was 1.86-8.12%. Haplotypes using fixed chromosome distances had the best prediction accuracy for four phenotypes, fixed number of SNPs for two phenotypes, and gene-based haplotypes for high density lipoproteins and height (tied for best). Haplotypes of coding genes were more accurate than haplotypes of all autosome genes that included both coding and noncoding genes for triglycerides and weight, and nearly the same as haplotypes of all autosome genes for the other phenotypes. Haplotypes of noncoding genes (mostly lncRNAs) only improved the prediction accuracy over the SNP models for high density lipoproteins, total cholesterol, and height. ChIP-seq haplotypes had better prediction accuracy than gene-based haplotypes for total cholesterol, body mass index and low density lipoproteins. The accuracy of ChIP-seq haplotypes was most striking for low density lipoproteins, where all four haplotype models with ChIP-seq haplotypes had similarly high prediction accuracy over the best prediction model with gene-based haplotypes. Haplotype epistasis was shown to be the reason for the increased accuracy due to haplotypes. Low density lipoproteins had the largest haplotype epistasis heritability that explained 14.70% of the phenotypic variance and was 31.27% of the SNP additive heritability, and the largest increase in prediction accuracy relative to the best SNP model (8.12%). Relative to the SNP additive heritability of the same regions, noncoding genes had the highest haplotype epistasis heritability, followed by coding genes and ChIP-seq for the seven phenotypes. SNP and haplotype heritability profiles showed that the integration of SNP and haplotype additive values compensated the weakness of haplotypes in estimating SNP heritabilities for four phenotypes, whereas models with haplotype additive values fully accounted for SNP additive values for three phenotypes. These results showed that haplotype analysis can be a method to utilize functional and structural genomic information to improve the accuracy of genomic prediction.

Haplotype prediction models open many possibilities to improve the accuracy of genomic selection but require more data processing and computing time than single-SNP prediction models. To facilitate haplotype analysis for genomic prediction and estimation using structural and functional genomic information, we developed a computing pipeline to implement haplotype analysis with capabilities for preparation of input data for haplotype analysis, genomic prediction and estimation using GVCHAP, and analysis of GVCHAP results. Data preparation includes utility programs for haplotype imputing; defining haplotype blocks by a fixed number of SNPs, a fixed distance in base pairs per block, or user defined block lengths based on structural or functional genomic information or a mixture of both types of information; and defining haplotype genotypes within each haplotype block. GVCHAP is the main program for genomic prediction and estimation, calculates GREML (genomic restricted maximum likelihood) estimates of variance components and heritabilities, and calculates GBLUP (genomic best linear unbiased prediction) for additive and dominance values of single SNPs as well as additive values of haplotypes with reliability estimates for training and validation populations. A two-step strategy and a method of multi-node processing are implemented to remove the computing bottleneck due to the creation of genomic relationship matrices for large samples. The analysis of GVCHAP results includes calculation of observed prediction accuracies from validation studies and preparation of input files for graphical visualization of heritability estimates of haplotype blocks as well as estimates of SNP effects and heritabilities. The entire pipeline provides an efficient and versatile computing tool for identifying the most accurate haplotype model among many candidate haplotype models utilizing structural and functional genomic information for genomic selection.

Using small sets of ancestry informative markers (AIMs) constitutes a cost-effective method to accurately estimate the ancestry proportions of individuals. This study aimed to generate a small and effective number of AIMs from ∼60 K single nucleotide polymorphism (SNP) data of porcine and estimate three ancestry proportions [East China pig (ECHP), South China pig (SCHP), and European commercial pig (EUCP)] from Asian breeds and European domestic breeds. A total of 186 samples of 10 pure breeds were divided into three groups: ECHP, SCHP, and EUCP. Using these samples and a one-vs.-rest SVM classifier, we found that using only seven AIMs could completely separate the three groups. Subsequently, we utilized supervised ADMIXTURE to calculate ancestry proportions and found that the 129 AIMs performed well on ancestry estimates when pseudo admixed individuals were used. Furthermore, another 969 samples of 61 populations were applied to evaluate the performance of the 129 AIMs. We also observed that the 129 AIMs were highly correlated with estimates using ∼60 K SNP data for three ancestry components: ECHP (Pearson correlation coefficient (r) = 0.94), SCHP (r = 0.94), and EUCP (r = 0.99). Our results provided an example of using a small number of pig AIMs for classifications and estimating ancestry proportions with high accuracy and in a cost-effective manner.

Heavy chain only antibodies (HCAbs) represent a rare type of antibody that is devoid of light chains and the CH1 domain that have been reported in cartilaginous fish and camelids. By analyzing transcript data and genome sequences, we conducted a comprehensive analysis of Bactrian camel immunoglobulin heavy chain genes. Based on the transcript data, one μ gene, five γ genes, one α gene and one ε gene were found. Additionally, the variable region of HCAbs (VHH) and the conventional antibodies (VH) sequences associated with the γ3, γ1a/b and μ genes were amplified. Based on these genome sequences, seven DH, six JH, μ, γ2a, γ2c, α, and ε genes and a portion of a γ3 gene were observed. Different Kozak sequences within different VH families were found in our analysis, and the variability index differed between the VHH3 and VH3 families. Phylogenetic analysis of the constant regions of the camelid immunoglobulin genes indicates that these genes appeared before the evolutionary divergence of Bactrian camels and dromedaries.