Metabolic trajectories of diabetic ketoacidosis onset described by breath analysis.

Purpose: This feasibility study aimed to investigate the use of exhaled breath analysis to capture and quantify relative changes of metabolites during resolution of acute diabetic ketoacidosis under insulin and rehydration therapy. Methods: Breath analysis was conducted on 30 patients of which 5 with DKA. They inflated Nalophan bags, and their metabolic content was subsequently interrogated by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). Results: SESI-HRMS analysis showed that acetone, pyruvate, and acetoacetate, which are well known to be altered in DKA, were readily detectable in breath of participants with DKA. In addition, a total of 665 mass spectral features were found to significantly correlate with base excess and prompt metabolic trajectories toward an in-control state as they progress toward homeostasis. Conclusion: This study provides proof-of-principle for using exhaled breath analysis in a real ICU setting for DKA monitoring. This non-invasive new technology provides new insights and a more comprehensive overview of the effect of insulin and rehydration during DKA treatment.

Characterization of the Ruminal Microbiome of Water Buffaloes (Bubalus bubalis) Kept in Different Ecosystems in the Eastern Amazon.

Increasing the efficiency of rumen fermentation is one of the main ways to maximize the production of ruminants. It is therefore important to understand the ruminal microbiome, as well as environmental influences on that community. However, there are no studies that describe the ruminal microbiota in buffaloes in the Amazon. The objective of this study was to characterize the rumen microbiome of the water buffalo (Bubalus bubalis) in the eastern Amazon in the dry and rainy seasons in three grazing ecosystems: Baixo Amazonas (BA), Continente do Pará (CP), Ilha do Marajó (IM), and in a confinement system: Tomé-Açu (TA). Seventy-one crossbred male buffaloes (Murrah × Mediterranean) were used, aged between 24 and 36 months, with an average weight of 432 kg in the rainy season and 409 kg in the dry season, and fed on native or cultivated pastures. In the confinement system, the feed consisted of sorghum silage, soybean meal, wet sorghum premix, and commercial feed. Samples of the diet from each ecosystem were collected for bromatological analysis. The collections of ruminal content were carried out in slaughterhouses, with the rumen completely emptied and homogenized, the solid and liquid fractions separated, and the ruminal pH measured. DNA was extracted from the rumen samples, then sequenced using Restriction Enzyme Reduced Representation Sequencing. The taxonomic composition was largely similar between ecosystems. All 61 genera in the reference database were recognized, including members of the domains Bacteria and Archaea. The abundance of 23 bacterial genera differed significantly (p < 0.01) between the Tomé-Açu confinement and other ecosystems. Bacillus, Ruminococcus, and Bacteroides had lower abundance in samples from the Tomé-Açu system. Among the Archaea, the genus Methanomicrobium was less abundant in Tomé-Açu, while Methanosarcina was more abundant. There was a difference caused by all evaluated factors, but the diet (available or offered) was what most influenced the ruminal microbiota.

Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host.

BACKGROUND: Producing animal protein while reducing the animal's impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible. RESULTS: Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets. CONCLUSIONS: Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual's future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits.

BACKGROUND: Rumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3139 rumen samples, collected from 1200 dual purpose ewes, using restriction enzyme-reduced representation sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (residual feed intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits. RESULTS: Incorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass diet. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance. CONCLUSIONS: This paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log10 proportions of each tag normalized within cohort (i.e., the group of animals sampled at the same time) is recommended for future predictions using RE-RRS metagenome profiles.

Fear of hypoglycemia and quality of life in young people with type 1 diabetes and their parents in the era of sensor glucose monitoring.

Introduction: It is crucial to understand psychosocial outcomes in children and adolescents with type 1 diabetes (T1D) and their families to provide optimal family-centered care. Hence, the aim of this study was to explore psychosocial outcomes in young people with T1D and their parents using currently available glucose monitoring devices in a real-life clinic setting. Methods: Children and adolescents aged 2-18 years with T1D for more than 6 months and their parents were recruited into a cross-sectional study to complete the Hypoglycemia Fear Survey (HFS) and the Pediatric Quality of Life Inventory (PedsQL) Generic Score Scales, Diabetes Module and Family Impact Module. Demographics and diabetes-specific parameters were obtained from medicals records. Results: Fifty-nine children and adolescents (mean age 15.1 ± 3.0 years) and 49 parents of children (mean age of children 12.5± 3.3 years) of which 44 were child-parent dyads completed the questionnaires. Parents had a higher mean (SD) FOH total and worry subscore than children, total score was 37.9 (14.6) vs. 32.2 (11.9), p = 0.047 and worry subscore was 17.8 (10.4) vs. 12.8 (9.0), p = 0.01. Furthermore, lower parental diabetes-specific QoL score was observed in parents, 78.8 (12.2) vs. 82.7 (10.3), p=0.02. No difference in FOH and QoL between real-time continuous glucose monitoring (rtCGM) and intermittently scanned glucose monitoring (isCGM) users and users of devices with and without alerts was observed. In isCGM users (n=36 completing the child questionnaires, n=33 completing parent questionnaires), higher parental FOH and lower parental diabetes-specific QoL correlated with higher scanning frequency, r = 0.399, p = 0.021, and r = -0.464, p = 0.007 respectively. No significant correlation was documented between scanning frequency and child questionnaire scores. Conclusions: Parents are more likely to perceive higher levels of psychosocial burden related to their child's diabetes than children and adolescents with T1D, especially parents of younger children. This highlights the need for family-based education and treatment resources to support parents in diabetes management in addition to rapidly advancing diabetes technology. In isCGM users, higher parental FOH and lower parent-perceived QoL correlated with a higher scanning frequency, indicating the potential impact of glucose monitoring modality on psychosocial outcomes or vice versa.

Low-cost sample preservation methods for high-throughput processing of rumen microbiomes.

BACKGROUND: The use of rumen microbial community (RMC) profiles to predict methane emissions has driven interest in ruminal DNA preservation and extraction protocols that can be processed cheaply while also maintaining or improving DNA quality for RMC profiling. Our standard approach for preserving rumen samples, as defined in the Global Rumen Census (GRC), requires time-consuming pre-processing steps of freeze drying and grinding prior to international transportation and DNA extraction. This impedes researchers unable to access sufficient funding or infrastructure. To circumvent these pre-processing steps, we investigated three methods of preserving rumen samples for subsequent DNA extraction, based on existing lysis buffers Tris-NaCl-EDTA-SDS (TNx2) and guanidine hydrochloride (GHx2), or 100% ethanol. RESULTS: Rumen samples were collected via stomach intubation from 151 sheep at two time-points 2 weeks apart. Each sample was separated into four subsamples and preserved using the three preservation methods and the GRC method (n = 4 × 302). DNA was extracted and sequenced using Restriction Enzyme-Reduced Representation Sequencing to generate RMC profiles. Differences in DNA yield, quality and integrity, and sequencing metrics were observed across the methods (p < 0.0001). Ethanol exhibited poorer quality DNA (A260/A230 < 2) and more failed samples compared to the other methods. Samples preserved using the GRC method had smaller relative abundances in gram-negative genera Anaerovibrio, Bacteroides, Prevotella, Selenomonas, and Succiniclasticum, but larger relative abundances in the majority of 56 additional genera compared to TNx2 and GHx2. However, log10 relative abundances across all genera and time-points for TNx2 and GHx2 were on average consistent (R2 > 0.99) but slightly more variable compared to the GRC method. Relative abundances were moderately to highly correlated (0.68 ± 0.13) between methods for samples collected within a time-point, which was greater than the average correlation (0.17 ± 0.11) between time-points within a preservation method. CONCLUSIONS: The two modified lysis buffers solutions (TNx2 and GHx2) proposed in this study were shown to be viable alternatives to the GRC method for RMC profiling in sheep. Use of these preservative solutions reduces cost and improves throughput associated with processing and sequencing ruminal samples. This development could significantly advance implementation of RMC profiles as a tool for breeding ruminant livestock.

Three-variate trajectories of metabolic control, body mass index, and insulin dose: Heterogeneous response to initiation of pump therapy in youth with type 1 diabetes.

OBJECTIVE: Continuous subcutaneous insulin infusion (CSII) in youths with type 1 diabetes (T1D) is often associated with lower HbA1c, lower total daily insulin dose (TDD), and lower body mass index (BMI) compared with multiple daily injections (MDI). Individual responses to CSII are diverse. The aim was to identify unique three-variate patterns of HbA1c, BMI standard deviation score (SDS), and TDD after switching to CSII. METHODS: Five thousand one hundred and thirty-three youths (≤20 years; 48% boys; median age at pump start 12.5 years) with T1D duration ≥3 years at CSII initiation were selected from the multicenter DPV registry. We applied group-based multitrajectory modeling to identify groups of individuals following similar trajectories. Measurements were aggregated quarterly during a 3-year follow-up period. Trajectory variables were changes of HbA1c, BMI-SDS, and TDD from baseline (delta = quarterly aggregated values at each time point [i] minus the respective baseline value). RESULTS: Four groups of diverging Delta-HbA1c, Delta-BMI-SDS, and Delta-TDD patterns were identified. All showed improvements in HbA1c during the first 3 months. Group 1 (12%) was characterized by modest HbA1c increase thereafter, TDD reduction, and stable BMI-SDS. In Group 2 (39%), increasing HbA1c, decreasing BMI-SDS, and stable TDD were found. By contrast, sustainably improved HbA1c, increasing BMI-SDS, and stable TDD were observed in Group 3 (32%). Group 4 (17%) was characterized by increasing levels for HbA1c, BMI-SDS, and TDD. Between-group differences in baseline HbA1c, BMI-SDS, TDD as well as in sex ratio, age at diabetes onset and at pump start were observed. CONCLUSIONS: Definite trajectories of glycemic control, BMI, and TDD over 3 years after CSII initiation were identified in youths with T1D allowing a more personalized treatment recommendation.

Autonomic cardiac regulation during spontaneous nocturnal hypoglycemia in children with type 1 diabetes.

BACKGROUND: Hypoglycemia is the most common complication in insulin treated diabetes. Though mostly mild, it can be fatal in rare cases: It is hypothesized that hypoglycemia related QTc prolongation contributes to cardiac arrhythmia. OBJECTIVE: To evaluate influence of nocturnal hypoglycemia on QTc and heart rate variability (HRV) in children with T1D. METHODS: Children and adolescents with T1D for at least 6 months participated in an observational study using continuous glucose monitoring (CGM) and Holter electrocardiogram for five consecutive nights. Mean QTc was calculated for episodes of nocturnal hypoglycemia (<3.7 mmol/L) and compared to periods of the same duration preceding hypoglycemia. HRV (RMSSD, low and high frequency power LF and HF) was analyzed for different 15 min intervals: before hypoglycemia, onset of hypoglycemia, before/after nadir, end of hypoglycemia and after hypoglycemia. RESULTS: Mean QTc during hypoglycemia was significantly longer compared to euglycemia (412 ± 15 vs. 405 ± 18 ms, p = 0.005). HRV changed significantly: RMSSD (from 88 ± 57 to 73 ± 43 ms) and HF (from 54 ± 17 to 47 ± 17nu) decreased from before hypoglycemia to after nadir, while heart rate (from 69 ± 9 to 72 ± 12 bpm) and LF (from 44 ± 17 to 52 ± 21 nu) increased (p = 0.04). CONCLUSION: A QTc lengthening effect of nocturnal hypoglycemia in children with T1D was documented. HRV changes occurred even before detection of nocturnal hypoglycemia by CGM, which may be useful for hypoglycemia prediction.

Characteristics of Patients with Type 1 Diabetes and Additional Autoimmune Disease in the DPV Registry.

CONTEXT: Autoimmune diseases affect ~8% of the population. Type 1 diabetes mellitus (T1DM) is linked to other autoimmune diseases (AIDs), such as autoimmune thyroid disease or Addison's disease (AD), that may impact diabetes therapy and outcome. OBJECTIVE: To analyze demographic and clinical characteristics of other AIDs in T1DM from a large standardized registry, the Prospective Diabetes Follow-up Registry (DPV). METHODS: We searched the registry for T1DM with the additional diagnosis of Hashimoto's thyroiditis (HT), Graves' disease (GD), and/or AD. T1DM with other AIDs (n = 6166, 5.4%) were compared with isolated T1DM (n = 107 457). For group comparisons, we used multivariable regression models with age, sex, diabetes duration, migration background, and type of insulin regimen as basic adjustments (microvascular endpoints: additionally adjusted for glycated hemoglobin). RESULTS: Patients with additional AIDs were more often female (54.7 vs 32.0%, P < .001) and had a longer diabetes duration (7.9 [4.2-12.5] vs 6.7 [2.7-12.9] years, P < .001). After adjustment, daily insulin dosage was higher in AD and HT than in isolated T1DM (0.858 ±â€…0.032 and 0.813 ±â€…0.005 vs 0.793 ±â€…0.001 IU/kg per day). Retinopathy was less common in HT (1.5%), whereas it was more frequent in GD (3.1%) than in isolated T1DM (1.8%). In both GD and HT, microalbuminuria occurred less often (10.6% and 14.3% vs 15.5%) and neuropathy (2.1% and 1.8% vs 0.8%) was more common than in isolated T1DM. All P < .05. CONCLUSION: T1DM with additional AIDs show heterogeneous differences compared with isolated T1DM. T1DM plus AD or HT requires more insulin. Further, the rate of neuropathy is higher in HT or GD, whereas the rate of microalbuminuria is lower.

Are psychiatric disorders associated with thyroid hormone therapy in adolescents and young adults with type 1 diabetes?

BACKGROUND: To evaluate the association between thyroid autoimmunity and psychiatric disorders (depression, anxiety, eating disorder, schizophrenia or attention-deficit/hyperactivity disorder) among adolescents and young adults with type 1 diabetes (11-25 years). METHODS: We compared 9368 type 1 diabetes patients with thyroid autoimmunity (3789 of them treated with levothyroxine) with 62 438 type 1 diabetes patients without any thyroid disease from a multicentre diabetes patient follow-up registry (DPV) in terms of psychiatric disorders. Thyroid autoimmunity was defined as documented diagnosis of Hashimoto thyroiditis or positive antibodies against thyroid peroxidase or thyroglobulin. Multivariable logistic regression models were used to calculate odds ratios for the respective psychiatric disorders in type 1 diabetes patients with thyroid autoimmunity (overall and stratified by levothyroxine therapy) compared to type 1 diabetes patients without thyroid diseases (reference). RESULTS: Of the 9368 patients with thyroid autoimmunity, 62% were female with a median (Q1-Q3) age of 16.3 (14.2-17.6) years. Thyroid autoimmunity (with or without levothyroxine therapy) revealed a slight, but significant higher chance for depression (odds ratio [OR], 1.35, 95% confidence interval [CI], 1.19, 1.52), eating disorder (OR, 1.25, CI, 1.03, 1.51), attention-deficit/hyperactivity disorder (OR, 1.22, CI, 1.07, 1.39) and schizophrenia (OR, 1.63, CI, 1.04, 2.56). In individuals with prescribed levothyroxine therapy because of thyroid dysfunction significantly higher odds for depression (OR, 1.63, CI, 1.34, 1.99), anxiety (OR, 1.60, CI, 1.18, 2.18), and attention-deficit/hyperactivity disorder (OR, 1.71, CI, 1.38, 2.12) were observed compared to reference. Thyroid autoimmunity without required levothyroxine therapy revealed no differences to the reference group. CONCLUSIONS: Patients on levothyroxine had significantly higher odds for psychiatric disorders, but thyroid autoimmunity in terms of high antibody levels only did not show higher odds for any psychiatric disorder.

Copeptin Kinetics and Its Relationship to Osmolality During Rehydration for Diabetic Ketoacidosis in Children.

CONTEXT: Copeptin is a surrogate marker for arginine vasopressin (AVP) release in response to hyperosmolal stimuli such as diabetic ketoacidosis (DKA). OBJECTIVE: The objective of this work is to characterize kinetics of copeptin and osmolality, and their dynamic relationship during rehydration and insulin therapy in children with type 1 diabetes (T1D) and DKA. DESIGN AND SETTING: A prospective, observational, multicenter study was conducted. PATIENTS AND INTERVENTION: Children with T1D admitted for DKA underwent serial serum copeptin and osmolality measurements from start of rehydration at 14 time points during 72 hours. MAIN OUTCOME MEASURES: Measurements included temporal course of copeptin and osmolality (kinetics), relationship between both (dynamics), and association between-subject variability (BSV) (coefficient of variation, CV%). RESULTS: Twenty-eight children (20 newly diagnosed T1D) aged 1 to 16 years were included. Copeptin decreased from 95 pmol/L (95% CI, 55-136 pmol/L) (CV%, 158%) to 9.7 pmol/L (95% CI, 8.1-11.4 pmol/L) (CV%, 31%) with a 50% recovery time (t1/2) of 7.1 hours (range, 5.1-11.5 hours) (114%). Serum osmolality decreased from 321 mOsm/kg (range, 315-327 mOsm/kg) (4%) to 294 mOsm/kg (range, 292-296 mOsm/kg) (1%) with a t1/2 of 4.3 hours (range, 3.0-5.6 hours) (64%). Copeptin levels doubled with each osmolality increase by 15 mOsm/kg (range, 10-21 mOsm/kg) (59%), from 9.8 pmol/L (range, 7.3-12.3 pmol/L) (48%) to 280 mOsm/kg. Copeptin kinetics differed between newly diagnosed and known T1D patients (P = .001), and less between mild vs moderate-severe DKA (P = .04). CONCLUSIONS: First, this study characterized for the first time copeptin kinetics and dynamics in the high hyperosmolar range in children with DKA. Second, it revealed significant differences in copeptin kinetics between newly diagnosed and known T1D patients that may be explained by changes at the osmoreceptor and renal AVP receptor level due to longstanding osmotic diuresis and DKA.

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling.

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p<0.05) except for the correlation between PC2 and methane yield. A Sensitivity study suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, meaning the current work using 118 samples/lane and future proposed 384 samples/lane are well within that threshold. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

Identification of factors associated with virus level in tonsils of pigs experimentally infected with porcine reproductive and respiratory syndrome virus.

Porcine reproductive and respiratory syndrome (PRRS) is one of the most important global swine diseases from both an economic and animal welfare standpoint. PRRS has plagued the US swine industry for over 25 yr, and containment of PRRS virus (PRRSV) has been unsuccessful to date. The primary phase of PRRS, tracked by serum viremia, typically clears between 21 and 42 d postinfection (dpi) but tonsils are a main site of PRRSV persistence and PRRSV can be detected in tonsils in excess of 150 dpi. Measuring tonsil virus (TV) levels at late stages of infection (6 to 7 wk postinfection) can be used to assess tonsil persistence, as levels of virus in tonsil at this time likely influence how long the virus will remain in the tissue. TV levels were measured on pigs experimentally infected with either the NVSL-97-7895 (NVSL; n = 524) or KS-2006-72109 (KS06; n = 328) PRRSV type 2 isolates across five trials. The objectives of this study were to (i) estimate the heritability of TV levels at 35 or 42 dpi; (ii) identify factors the affect TV level, including serum viremia; (iii) identify genomic regions associated with TV level; and (iv) compare results for the two PRRSV isolates. TV level was lowly heritable for both isolates (NVSL: 0.05 ± 0.06; KS06: 0.11 ± 0.10). Level of TV was phenotypically associated with traits related to viral clearance from serum: pigs with low TV levels had an earlier and faster rate of maximal serum viral clearance, lower total serum viral load, and lower viremia level at 35 or 42 dpi. Although no genomic regions with major effects on TV level were identified, several showed some association (>0.1% of total genetic variance in the NVSL-infected dataset, the KS06-infected dataset, and the combined dataset). These regions contained the genes CCL1, CCL2, CCL8, HS3ST3B1, GALNT10, TCF7, C1QA/B/C, HPSE, G0S2, and CD34, which are involved in viral infiltration or replication, immune cell migration, and viral clearance from tissue. Results were similar between the two PRRSV isolates. In conclusion, selection for viral clearance traits in serum may reduce PRRSV persistence in the tonsil across PRRSV isolates. However, genetic correlations need to be estimated to determine whether this will be successful.

Harnessing longitudinal information to identify genetic variation in tolerance of pigs to Porcine Reproductive and Respiratory Syndrome virus infection.

BACKGROUND: High resistance (the ability of the host to reduce pathogen load) and tolerance (the ability to maintain high performance at a given pathogen load) are two desirable host traits for producing animals that are resilient to infections. For Porcine Reproductive and Respiratory Syndrome (PRRS), one of the most devastating swine diseases worldwide, studies have identified substantial genetic variation in resistance of pigs, but evidence for genetic variation in tolerance has so far been inconclusive. Resistance and tolerance are usually considered as static traits. In this study, we used longitudinal viremia measurements of PRRS virus infected pigs to define discrete stages of infection based on viremia profile characteristics. These were used to investigate host genetic effects on viral load (VL) and growth at different stages of infection, to quantify genetic variation in tolerance at these stages and throughout the entire 42-day observation period, and to assess whether the single nucleotide polymorphism (SNP) WUR10000125 (WUR) with known large effects on resistance confers significant differences in tolerance. RESULTS: Genetic correlations between resistance and growth changed considerably over time. Individuals that expressed high genetic resistance early in infection tended to grow slower during that time-period, but were more likely to experience lower VL and recovery in growth by the later stage. The WUR genotype was most strongly associated with VL at early- to mid-stages of infection, and with growth at mid- to late-stages of infection. Both, single-stage and repeated measurements random regression models identified significant genetic variation in tolerance. The WUR SNP was significantly associated only with the overall tolerance slope fitted through all stages of infection, with the genetically more resistant AB pigs for the WUR SNP being also more tolerant to PRRS. CONCLUSIONS: The results suggest that genetic selection for improved tolerance of pigs to PRRS is possible in principle, but may be feasible only with genomic selection, requiring intense recording schemes that involve repeated measurements to reliably estimate genetic effects. In the absence of such records, consideration of the WUR genotype in current selection schemes appears to be a promising strategy to improve simultaneously resistance and tolerance of growing pigs to PRRS.

Genetic relationships of antibody response, viremia level, and weight gain in pigs experimentally infected with porcine reproductive and respiratory syndrome virus1.

Genetic and antigenic variability between Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) isolates has encumbered vaccine development. Here, the genetic basis of PRRSV antibody response was assessed using data from experimental infection trials of commercial crossbred weaner pigs across with one of two distinct PRRSV isolates, NVSL-97-7895 (~750 pigs) and KS-2006-72109 (~450 pigs). Objectives were to estimate the genetic parameters of antibody response, measured as the sample to positive ratio (S:P) of PRRSV N-protein specific IgG in serum at 42 d post infection (dpi); assess the relationship of S:P at 42 dpi with serum viremia and growth under infection; and identify genomic regions associated with S:P at 42 dpi. Estimates of heritability of S:P at 42 dpi for NVSL and KS06 were 0.31 ± 0.09 and 0.40 ± 0.10 and appeared to be under similar genetic control (genetic correlation 0.73 ± 0.39). Estimates of genetic correlations of S:P were generally weak with viral load (NVSL: -0.20 ± 0.18; KS06: -0.69 ± 0.20), measured as area under the curve of log10 serum viremia from 0 to 21 dpi, and with weight gain (WG) from 0 to 42 dpi (NVSL: -0.38 ± 0.19; KS06: -0.08 ± 0.25). However, genetic correlations of S:P at 42 dpi with daily serum viremia and with 3-d WG revealed dynamic relationships, with S:P at 42 dpi having the strongest negative genetic correlations with daily viremia when IgG production starts (10-20 dpi), and negative genetic correlations with WG early after infection but positive later on. This suggests that animals that placed more emphasis on immune response early in infection reaped benefits of that later in infection by more effectively clearing the virus. The WUR10000125 SNP on SSC4, previously associated with response to PRRSV, did not have a significant effect on S:P at 42 dpi (P > 0.05) but genotype-specific genetic correlations of S:P with daily viremia and 3-d WG suggested that the lower WG of pigs with the unfavorable AA WUR10000125 genotype may be due to their utilization of a more energetically costly host response compared to pigs with the favorable genotype. Genome-wide association studies identified three SNPs in the Major Histocompatibility Complex associated with S:P that explained ~10 (NVSL) and 45% (KS06) of the genetic variance but were not associated with viremia or WG. In conclusion, antibody response to PRRSV infection is a possible biomarker for improved host response to PRRSV infection.

Fixed-length haplotypes can improve genomic prediction accuracy in an admixed dairy cattle population.

BACKGROUND: Fitting covariates representing the number of haplotype alleles rather than single nucleotide polymorphism (SNP) alleles may increase genomic prediction accuracy if linkage disequilibrium between quantitative trait loci and SNPs is inadequate. The objectives of this study were to evaluate the accuracy, bias and computation time of Bayesian genomic prediction methods that fit fixed-length haplotypes or SNPs. Genotypes at 37,740 SNPs that were common to Illumina BovineSNP50 and high-density panels were phased for ~58,000 New Zealand dairy cattle. Females born before 1 June 2008 were used for training, and genomic predictions for milk fat yield (n = 24,823), liveweight (n = 13,283) and somatic cell score (n = 24,864) were validated within breed (predominantly Holstein-Friesian, predominantly Jersey, or admixed KiwiCross) in later-born females. Covariates for haplotype alleles of five lengths (125, 250, 500 kb, 1 or 2 Mb) were generated and rare haplotypes were removed at four thresholds (1, 2, 5 or 10%), resulting in 20 scenarios tested. Genomic predictions fitting covariates for either SNPs or haplotypes were calculated by using BayesA, BayesB or BayesN. This is the first study to quantify the accuracy of genomic prediction using haplotypes across the whole genome in an admixed population. RESULTS: A correlation of 0.349 ± 0.016 between yield deviation and genomic breeding values was obtained for milk fat yield in Holstein-Friesians using BayesA fitting covariates. Genomic predictions were more accurate with short haplotypes than with SNPs but less accurate with longer haplotypes than with SNPs. Fitting only the most frequent haplotype alleles reduced computation time with little decrease in prediction accuracy for short haplotypes. Trends were similar for all traits and breeds and there was little difference between Bayesian methods. CONCLUSIONS: Fitting covariates for haplotype alleles rather than SNPs can increase prediction accuracy, although it decreased drastically for long (>500 kb) haplotypes. In this population, fitting 250 kb haplotypes with a 1% frequency threshold resulted in the highest genomic prediction accuracy and fitting 125 kb haplotypes with a 10% frequency threshold improved genomic prediction accuracy with comparable computation time to fitting SNPs. This increased accuracy is likely to increase genetic gain by changing the ranking of selection candidates.

Use of multi-trait and random regression models to identify genetic variation in tolerance to porcine reproductive and respiratory syndrome virus.

BACKGROUND: A host can adopt two response strategies to infection: resistance (reduce pathogen load) and tolerance (minimize impact of infection on performance). Both strategies may be under genetic control and could thus be targeted for genetic improvement. Although there is evidence that supports a genetic basis for resistance to porcine reproductive and respiratory syndrome (PRRS), it is not known whether pigs also differ genetically in tolerance. We determined to what extent pigs that have been shown to vary genetically in resistance to PRRS also exhibit genetic variation in tolerance. Multi-trait linear mixed models and random regression sire models were fitted to PRRS Host Genetics Consortium data from 1320 weaned pigs (offspring of 54 sires) that were experimentally infected with a virulent strain of PRRS virus to obtain genetic parameter estimates for resistance and tolerance. Resistance was defined as the inverse of within-host viral load (VL) from 0 to 21 (VL21) or 0 to 42 (VL42) days post-infection and tolerance as the slope of the reaction-norm of average daily gain (ADG21, ADG42) on VL21 or VL42. RESULTS: Multi-trait analysis of ADG associated with either low or high VL was not indicative of genetic variation in tolerance. Similarly, random regression models for ADG21 and ADG42 with a tolerance slope fitted for each sire did not result in a better fit to the data than a model without genetic variation in tolerance. However, the distribution of data around average VL suggested possible confounding between level and slope estimates of the regression lines. Augmenting the data with simulated growth rates of non-infected half-sibs (ADG0) helped resolve this statistical confounding and indicated that genetic variation in tolerance to PRRS may exist if genetic correlations between ADG0 and ADG21 or ADG42 are low to moderate. CONCLUSIONS: Evidence for genetic variation in tolerance of pigs to PRRS was weak when based on data from infected piglets only. However, simulations indicated that genetic variance in tolerance may exist and could be detected if comparable data on uninfected relatives were available. In conclusion, of the two defense strategies, genetics of tolerance is more difficult to elucidate than genetics of resistance.

Comparison of host genetic factors influencing pig response to infection with two North American isolates of porcine reproductive and respiratory syndrome virus.

BACKGROUND: Porcine reproductive and respiratory syndrome (PRRS) is one of the most important swine diseases in the world and genetic selection of pigs for increased resistance to PRRS is an attractive method to improve the health status of the swine herd. This study compared phenotypic and genetic responses to infection with one of two genetically distinct type 2 PRRS virus (PRRSV) isolates: NVSL-97-7895 (NVSL) and KS-2006-72109 (KS06), and evaluated whether the single nucleotide polymorphism (SNP) WUR10000125 (WUR) on chromosome 4 that was associated with viral load and weight gain under infection with NVSL also has an effect on response to infection across North American PRRSV isolates. Wood's lactation curve was fitted to repeated viremia measurements to derive five curve characteristics that were evaluated. RESULTS: Infection with NVSL was characterized by reaching a 14 ± 2 % higher peak viremia (PV) 2.5 ± 0.6 days earlier (time to peak; TP) than KS06, followed by 36 ± 1 % faster virus clearance, which occurred 3.9 ± 0.7 days sooner. Weight gain from 0 to 42 days post-infection (WG) tended to be higher under infection with KS06 than NVSL (3.7 ± 1.5 kg). Estimates of heritability were moderate for both PRRSV isolates for viral load from 0 to 21 days post-infection (VL) (NVSL: 0.31 ± 0.06; KS06: 0.51 ± 0.09) and WG (NVSL: 0.33 ± 0.06; KS06: 0.31 ± 0.09). Strong negative genetic correlations were observed between VL and WG for both NVSL (-0.74 ± 0.10) and KS06 (-0.52 ± 0.17) infected pigs. Pigs with genotype AB at the WUR SNP had a more desirable phenotype than AA pigs for all traits under infection with NVSL, but only for VL and PV with KS06; effects on other traits were smaller and not significantly different from zero (P > 0.05). Genetic correlations of host response between isolates were strong for VL, WG and PV. Accounting for WUR genotype had little impact on these correlations, suggesting that response to PRRSV infection has a substantial polygenic component that is common between these two isolates. CONCLUSIONS: These results suggest that the KS06 PRRSV isolate is less virulent than NVSL but that genetic selection for increased resistance to either of these genetically distinct isolates is expected to increase resistance to the other isolate.