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Objective: To investigate phenotypes of comorbidity before and after an epilepsy diagnosis in a national cohort of post-9/11 Service Members and Veterans and explore phenotypic associations with mortality., Methods: Among a longitudinal cohort of Service Members and Veterans receiving care in the Veterans Health Administration (VHA) from 2002 to 2018, annual diagnoses for 26 conditions associated with epilepsy were collected over 5 years, ranging from 2 years prior to 2 years after the year of first epilepsy diagnosis. Latent class analysis (LCA) was used to identify probabilistic comorbidity phenotypes with distinct health trajectories. Descriptive statistics were used to describe the characteristics of each phenotype. Fine and Gray cause-specific survival models were used to measure mortality outcomes for each phenotype up to 2021., Results: Six distinct phenotypes were identified: (1) relatively healthy, (2) post-traumatic stress disorder, (3) anxiety and depression, (4) chronic disease, (5) bipolar/substance use disorder, and (6) polytrauma. Accidents were the most common cause of death overall, followed by suicide/mental health and cancer, respectively. Each phenotype exhibited unique associations with mortality and cause of death, highlighting the differential impact of comorbidity patterns on patient outcomes., Significance: By delineating clinically meaningful epilepsy comorbidity phenotypes, this study offers a framework for clinicians to tailor interventions. Moreover, these data support systems of care that facilitate treatment of epilepsy and comorbidities within an interdisciplinary health team that allows continuity of care. Targeting treatment toward patients with epilepsy who present with specific heightened risks could help mitigate adverse outcomes and enhance overall patient care., (Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Background: The Dohne Merino sheep was introduced to Australia from South Africa in the 1990s. It was primarily used in crosses with the Merino breed sheep to improve on attributes such as reproduction and carcass composition. Since then, this breed has continued to expand in Australia but the number of genotyped and phenotyped purebred individuals remains low, calling into question the accuracy of genomic selection. The Australian Merino, on the other hand, has a substantial reference population in a separate genomic evaluation (MERINOSELECT). Combining these resources could fast track the impact of genomic selection on the smaller breed, but the efficacy of this needs to be investigated. This study was based on a dataset of 53,663 genotypes and more than 2 million phenotypes. Its main objectives were (1) to characterize the genetic structure of Merino and Dohne Merino breeds, (2) to investigate the utility of combining their evaluations in terms of quality of predictions, and (3) to compare several methods of genetic grouping. We used the 'LR-method' (Linear Regression) for these assessments., Results: We found very low Fst values (below 0.048) between the different Merino lines and Dohne breed considered in our study, indicating very low genetic differentiation. Principal component analysis revealed three distinct groups, identified as purebred Merino, purebred Dohne, and crossbred animals. Considering the whole population in the reference led to the best quality of predictions and the largest increase in accuracy (from 'LR-method') from pedigree to genomic-based evaluations: 0.18, 0.14 and 0.16 for yearling fibre diameter (YFD), yearling greasy fleece weight (YGFW) and yearling liveweight (YWT), respectively. Combined genomic evaluations showed higher accuracies than the evaluation based on the Dohne reference only (accuracies increased by 0.16, 0.06 and 0.07 for YFD, YGFW, and YWT, respectively). For the combined genomic evaluations, metafounder models were more accurate than Unknown Parent Groups models (accuracies increased by 0.04, 0.04 and 0.06 for YFD, YGFW and YWT, respectively)., Conclusions: We found promising results for the future transition of the Dohne breed from pedigree to genomic selection. A combined genomic evaluation, with the MERINOSELECT evaluation in addition to using metafounders, is expected to enhance the quality of genomic predictions for the Dohne Merino breed., (© 2024. The Author(s).)

Objective: Persistent symptoms post-mild traumatic brain injury (mTBI) includes autonomic dysregulation (AD). The composite autonomic symptoms score, (COMPASS-31), was developed to quantify AD symptom severity in the last year, which limits clinical utility. The primary aim was to determine validity of a modified-COMPASS-31 measuring symptoms in the last month compared to the original, secondarily to compare both original and modified versions to the Neurobehavioral Symptom Inventory (NSI), and tertiarily to detect change post-treatment of the modified-COMPASS-31 compared to NSI and headache intensity (HI)., Participants: Thirty-three military personnel with persistent headache post-mTBI., Main Outcome Measures: Total and domain scores for COMPASS-31 (original vs. modified) NSI and HI at baseline. Change in modified-COMPASS-31. NSI, and HI., Results: Baseline COMPASS-31 versions were comparable and highly correlated ( r  = 0.72, p  < 0.001), they were moderately correlated at best to the NSI ( r  < 0.6), which may suggest differences in measurement metrics. The mean change in modified-COMPASS-31 scores (15.4/100, effect size 0.8) was mild to moderately correlated to the change in HI ( r  = 0.39) score, but not to NSI ( r  = 0.28)., Conclusion: The modified-COMPASS-31 appears to be valid, can measure change of AD symptom severity, and is recommended as an outcome measure.

The chronic mental health consequences of mild traumatic brain injury (TBI) are a leading cause of disability. This is surprising given the expectation of significant recovery after mild TBI, which suggests that other injury-related factors may contribute to long-term adverse outcomes. The objective of this study was to determine how number of prior injuries, gender, and environment/context of injury may contribute to depressive symptoms after mild TBI among deployed United States service members and veterans (SMVs). Data from the Long-term Impact of Military-Relevant Brain Injury Consortium Prospective Longitudinal Study was used to assess TBI injury characteristics and depression scores previously measured on the Patient Health Questionnaire-9 (PHQ-9) among a sample of 1456 deployed SMVs. Clinical diagnosis of mild TBI was defined via a multi-step process centered on a structured face-to-face interview. Logistical and linear regressions stratified by gender and environment of injury were used to model depressive symptoms controlling for sociodemographic and combat deployment covariates. Relative to controls with no history of mild TBI ( n  = 280), the odds ratios (OR) for moderate/severe depression (PHQ-9 ≥ 10) were higher for SMVs with one mild TBI ( n  = 358) OR: 1.62 (95% confidence interval [CI] 1.09-2.40, p  = 0.016) and two or more mild TBIs ( n  = 818) OR: 1.84 (95% CI 1.31-2.59, p  < 0.001). Risk differences across groups were assessed in stratified linear models, which found that depression symptoms were elevated in those with a history of multiple mild TBIs compared with those who had a single mild TBI ( p  < 0.001). Combat deployment-related injuries were also associated with higher depression scores than injuries occurring in non-combat or civilian settings ( p  < 0.001). Increased rates of depression after mild TBI persisted in the absence of post-traumatic stress disorder. Both men and women SMVs separately exhibited significantly increased depressive symptom scores if they had had combat-related mild TBI. These results suggest that contextual information, gender, and prior injury history may influence long-term mental health outcomes among SMVs with mild TBI exposure.

Background: Chronic headache after traumatic brain injury (TBI) is a common, yet disabling, disorder whose diverse clinical characteristics and treatment needs remain poorly defined., Objective: To examine diagnostic coding patterns and cost among military Veterans with comorbid chronic headache and TBI., Methods: We identified 141,125 post-9/11 era Veterans who served between 2001 and 2019 with a headache disorder diagnosed after TBI. We first identified patterns of Complex Headache Combinations (CHC) and then compared the patterns of healthcare costs in 2022-dollar values in the three years following the TBI diagnosis., Results: Veterans had diverse individual headache and CHC diagnoses with uniformly high cost of care. Post-whiplash and post-TBI CHCs were common and consistently associated with higher costs after TBI than those with other types of headache and CHCs. Post-TBI migraine had the highest unadjusted mean inpatient ($27,698), outpatient ($61,417), and pharmacy ($4,231) costs, which persisted even after adjustment for confounders including demographic, military, and clinical characteristics., Conclusion: Headache diagnoses after TBI, particularly those diagnosed with post-traumatic headache, are complex, and associated with dual high cost and care burdens. More research is needed to examine whether this higher expenditure reflects more intensive treatment and better outcomes or refractory headache with worse outcomes.

Purpose: The primary aim of this study was to examine the factors associated with long-term outcomes of postconcussive disruptive dizziness in Veterans of the post-9/11 wars., Method: For this observational cohort study, the Neurobehavioral Symptom Inventory-Vestibular subscale (NSI-V) score was used as an outcome measure for dizziness in 987 post-9/11 Veterans who indicated disruptive dizziness at an initial Veterans Health Administration Comprehensive Traumatic Brain Injury Evaluation (CTBIE). An NSI-V change score was calculated as the difference in the scores obtained at the initial CTBIE and on a subsequent survey. Differences in the NSI-V change scores were examined for demographics, injury characteristics, comorbidities, and vestibular and balance function variables, and multiple linear regression analyses were used to explore associations among the variables and the NSI-V change score., Results: The majority of Veterans (61%) demonstrated a decrease in the NSI-V score, suggesting less dizziness on the survey compared with the CTBIE; 16% showed no change; and 22% had a higher score. Significant differences in the NSI-V change score were observed for traumatic brain injury (TBI) status, diagnoses of post-traumatic stress disorder (PTSD), headache and insomnia, and vestibular function. Multivariate regressions revealed significant associations between the NSI-V change score and the initial CTBIE NSI-V score, education level, race/ethnicity, TBI status, diagnoses of PTSD or hearing loss, and vestibular function., Conclusions: Postconcussive dizziness can continue for years following an injury. Factors associated with poor prognosis include TBI, diagnoses of PTSD or hearing loss, abnormal vestibular function, increased age, identification as a Black Veteran, and high school education level.

Objective: The study aimed to examine the association between post-concussive comorbidity burdens [post-traumatic stress disorder (PTSD), depression, and/or headache] and central nervous system (CNS) polypharmacy (five or more concurrent medications) with reported neurobehavioral symptoms and symptom validity screening among post-9/11 veterans with a history of mild traumatic brain injury (mTBI)., Setting: Administrative medical record data from the Department of Veterans Affairs (VA) were used in the study., Participants: Post-9/11 veterans with mTBI and at least 2 years of VA care between 2001 and 2019 who had completed the comprehensive traumatic brain injury evaluation (CTBIE) were included in the study., Design: Retrospective cross-sectional design was used in the study., Main Measures: Neurobehavioral Symptom Inventory (NSI), International Classification of Diseases, Ninth Revision, and Clinical Modification diagnosis codes were included in the study., Results: Of the 92,495 veterans with a history of TBI, 90% had diagnoses of at least one identified comorbidity (PTSD, depression, and/or headache) and 28% had evidence of CNS polypharmacy. Neurobehavioral symptom reporting and symptom validity failure was associated with comorbidity burden and polypharmacy after adjusting for sociodemographic characteristics. Veterans with concurrent diagnoses of PTSD, depression, and headache were more than six times more likely [Adjusted odds ratio = 6.55 (99% CI: 5.41, 7.92)]. to fail the embedded symptom validity measure (Validity-10) in the NSI., Conclusion: TBI-related multimorbidity and CNS polypharmacy had the strongest association with neurobehavioral symptom distress, even after accounting for injury and sociodemographic characteristics. Given the regular use of the NSI in clinical and research settings, these findings emphasize the need for comprehensive neuropsychological evaluation for individuals who screen positively for potential symptom overreporting, the importance of multidisciplinary rehabilitation to restore functioning following mTBI, and the conscientious utilization of symptom validity measures in research efforts., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Swan, Kennedy, Cooper, Amuan, Mayo, Tate, Song, Eapen, Van Cott, Lopez and Pugh.)

Objectives: To compare sub-occipital muscle pressure sub pain thresholds (PPTs) in individuals with persistent-post-traumatic-headache (PPTH) in relation to the presence or not of cranial nerve and/or autonomic symptoms reported during sustained neck rotation (SNR)., Background: Previously 81% of military service members with PPTH demonstrated symptoms with SNR up to 60 seconds. Of these, 54% reported symptoms in one (Uni-Symp) and 46% in both directions of rotation (Bi-Symp). Sub-occipital PPTs, in relation to SNR direction, were of interest., Methods: Retrospective review of records of 77 individuals, with PPTH with both SNR and PPTs. Average suboccipital and scalene PPTs were compared between Asymptomatic (n = 13), upon SNR testing, or Symptomatic (Uni-Symp, n = 32, Bi-Symp, n = 32), groups., Results: The Bi-Symp group had significantly reduced sub-occipital PPTs relative to the Asymptomatic group on both sides [p < 0.009] with no side-to-side differences in either group. The Uni-Symp group had significantly lower sub-occipital PPTs on the symptomatic SNR test direction compared to the asymptomatic side [t(31) = 3.37, p = 0.002]. There were no differences within or between groups in the scalene PPTs(p's > 0.08)., Conclusions: An upper cervical mechanical trigger of symptoms during SNR tests in some individuals with PPTH is possible. The direction of symptomatic SNR tests may indicate direction of guarded hypermobile dysfunction and direct treatment.

Objectives: To examine and categorize symptoms occurring within 60 s of vertebrobasilar-insufficiency (VBI) testing (left- and right-neck rotation) in individuals with persistent post-traumatic headache., Background: As part of routine clinical cervical screening in our patients, we found extended VBI testing often triggered additional symptoms. Therefore, we aimed to document the prevalence and precise symptoms occurring during each movement direction of this test and determine any demographic or baseline signs or symptoms associated with a positive test., Methods: A retrospective medical record review on military personnel receiving treatment for persistent post-traumatic headache was performed. Participants were grouped according to presence of non-headache related symptoms triggered during the tests. Frequency, onset, and symptom characteristics reported were categorized as potentially vascular and/or possible autonomic or cranial nerve in nature., Results: At least one symptom was reported by 81.3% of 123 patients. Of these, 54% reported symptoms in one and 46% in both directions of rotation, yielding 146 abnormal tests. Most reported symptoms were tear disruption (41%), altered ocular-motor-control (25%), and blepharospasm (16%). Enlisted individuals and those with altered baseline facial sensation were more likely to have a positive test., Conclusions: The majority reported symptoms not typical of VBI within 60 seconds of sustained neck rotation. Further study is needed to better understand the mechanisms and clinical relevance.

Objectives: To explore the prevalence of acute neck pain in high school athletes following sports-related concussion (SRC) and to examine the role of acute neck pain in modifying or amplifying concurrent concussive symptoms., Design: Retrospective observational., Setting: High school sporting events., Participants: High school athletes who suffered a sports-related concussion between the 2011 and 2019 academic years academic years from the National Athletic Treatment, Injury and Outcomes Network (NATION) Study., Interventions: Not applicable., Main Outcome Measures: Prevalence of neck pain (yes/no) along with 33 other commonly reported concussion symptoms, number of symptoms reported, mechanism of injury (contact with person/surface or object), sport type (contact/noncontact), and injury history (first time/repeated injury)., Results: One hundred thirty-eight of 401 athletes (33.9%) indicated acute neck pain following SRC. Those with neck pain reported significantly more symptoms overall (M = 13.53, SD = 6.89) relative to their non-neck pain counterparts (M = 8.46, SD = 5.68; t [191.35] = 7.11, P < 0.001). Athletes with SRC due to contact with a surface were significantly less likely to report neck pain than those reported contact with a person. Neck pain, repeated injury, and female sex were significantly associated with a greater number of concussion symptoms in the acute phase., Conclusions: Our data suggest that acute neck pain is a frequent acute symptom following SRC and signals the necessity for additional screening to seek and identify comorbid cervical pathology. Prospective studies should seek to access the benefit of cervical therapy in the early stages in SRC patients with neck pain to reduce the risk of persistent postconcussion symptoms., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: To identify disruption due to dizziness symptoms following deployment-related traumatic brain injury (TBI) and factors associated with receiving diagnoses for these symptoms., Setting: Administrative medical record data from the Department of Veterans Affairs (VA)., Participants: Post-9/11 veterans with at least 3 years of VA care who reported at least occasional disruption due to dizziness symptoms on the comprehensive TBI evaluation., Design: A cross-sectional, retrospective, observational study., Main Measures: International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes of dizziness, vestibular dysfunction, and other postconcussive conditions; neurobehavioral Symptom Inventory., Results: Increased access to or utilization of specialty care at the VA was significant predictors of dizziness and/or vestibular dysfunction diagnoses in the fully adjusted model. Veterans who identified as Black non-Hispanic and those with substance use disorder diagnoses or care were substantially less likely to receive dizziness and vestibular dysfunction diagnoses., Conclusions: Access to specialty care was the single best predictor of dizziness and vestibular dysfunction diagnoses, underscoring the importance of facilitating referrals to and utilization of specialized, comprehensive clinical facilities or experts for veterans who report disruptive dizziness following deployment-related TBI. There is a clear need for an evidence-based pathway to address disruptive symptoms of dizziness, given the substantial variation in audiovestibular tests utilized by US providers by region and clinical specialty. Further, the dearth of diagnoses among Black veterans and those in more rural areas underscores the potential for enhanced cultural competency among providers, telemedicine, and patient education to bridge existing gaps in the care of dizziness., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

A deterministic bio-economic model was developed to estimate economic weights for genetic improvement of lactation milk yield, fat yield, age at first calving, calving interval, mature weight and survival under low, medium and high production systems in the Tropics. Input parameters were obtained from dairy production systems in Kenya which has a tropical environment. The highest proportion of revenue is from the sale of milk followed by sale of heifers, cull cows and sale of male calves under all production systems. On the other hand, feed cost is the most important production cost followed by labour, marketing, reproduction and health costs, respectively. Economic values for the six traits were derived from a profit equation using revenue and production costs per cow per year. The economic values were then discounted using diffusion coefficients which account for differences between traits in the time when the improvement is expressed. Economic weights were robust to changes in input and output prices, changes in feeding strategies, and changes in milk and surplus heifer marketing strategies. Genetic standard deviations were multiplied by economic values to standardise the economic value of traits and to compare their potential for economic response. When expressed as proportion of their sum, these relative economic weights under the low, medium and high production systems for lactation milk yield were 51.36, 59.79 and 63.98%; for fat yield 4.50, 10.69 and 9.05%; for age at first calving 3.16, 2.66 and 0.55%; for calving interval 33.59, 19.88 and 20.05%; for mature weight 1.55, 1.34 and 1.19% and for survival rate 5.84, 5.64 and 5.18%, respectively. The predicted responses followed the same pattern as the relative economic weights. This shows that milk yield and calving interval were most important in all production systems but the value of response for traits differed between production systems with more emphasis on milk yield and less on calving interval in the high production systems. Moderate correlations were estimated between the breeding objective for the low, medium and high production systems. To maximise response in the overall breeding objective, different selection criteria are required for the three production systems., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objectives: Examine the association of multimorbidity and psychosocial functioning with posttraumatic stress disorder (PTSD) symptom severity reported among post-9/11 veterans., Method: This was a secondary analysis of survey data collected from a national sample of post-9/11 veterans with at least 3 years of Department of Veterans Affairs care, stratified by comorbidity trajectory and sex ( N = 1,989). Comorbidity trajectories were derived by latent class analysis to develop probabilistic combinations of physical and mental health conditions in a previous effort (Pugh et al., 2016). In this study, linear models analyzed symptom severity reported on the PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition by psychosocial factors (i.e., resilience, self-efficacy, and postdeployment social support) while controlling for sociodemographic characteristics and deployment experiences., Results: Veterans in the mental health, pain, and polytrauma clinical triad comorbidity trajectories reported more severe PTSD symptoms than the healthy comorbidity trajectory ( p < .01). All psychosocial factors were significantly associated with PTSD symptom severity, accounting for nearly 43% of variability in follow-up analyses. Confidence in self-efficacy demonstrated the strongest association among them ( p < .01)., Conclusion: Veterans experiencing multimorbidity, particularly mental health distress, reported greater PTSD symptom severity after controlling for psychosocial factors, sociodemographics, and deployment experiences. The salience of psychosocial factors in reported PTSD symptom severity underscores resilience, self-efficacy and social support as potential facilitators of functional reintegration following military service. Our analyses underscore the need to address the systemic barriers in health care access and delivery for minority patient populations in future investigations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The objective of this study was to investigate the accuracy of genomic prediction of body weight and eating quality traits in a numerically small sheep population (Dorper sheep). Prediction was based on a large multi-breed/admixed reference population and using (a) 50k or 500k single nucleotide polymorphism (SNP) genotypes, (b) imputed whole-genome sequencing data (~31 million), (c) selected SNPs from whole genome sequence data and (d) 50k SNP genotypes plus selected SNPs from whole-genome sequence data. Furthermore, the impact of using a breed-adjusted genomic relationship matrix on accuracy of genomic breeding value was assessed. The selection of genetic variants was based on an association study performed on imputed whole-genome sequence data in an independent population, which was chosen either randomly from the base population or according to higher genetic proximity to the target population. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of genomic prediction was assessed according to the correlation between genomic breeding value and corrected phenotypes divided by the square root of trait heritability. The accuracy of genomic prediction was between 0.20 and 0.30 across different traits based on common 50k SNP genotypes, which improved on average by 0.06 (absolute value) on average based on using prioritized genetic markers from whole-genome sequence data. Using prioritized genetic markers from a genetically more related GWAS population resulted in slightly higher prediction accuracy (0.02 absolute value) compared to genetic markers derived from a random GWAS population. Using high-density SNP genotypes or imputed whole-genome sequence data in GBLUP showed almost no improvement in genomic prediction accuracy however, accounting for different marker allele frequencies in reference population according to a breed-adjusted GRM resulted to on average 0.024 (absolute value) increase in accuracy of genomic prediction., (© 2021 Wiley-VCH GmbH.)

Background: Imputation to whole-genome sequence is now possible in large sheep populations. It is therefore of interest to use this data in genome-wide association studies (GWAS) to investigate putative causal variants and genes that underpin economically important traits. Merino wool is globally sought after for luxury fabrics, but some key wool quality attributes are unfavourably correlated with the characteristic skin wrinkle of Merinos. In turn, skin wrinkle is strongly linked to susceptibility to "fly strike" (Cutaneous myiasis), which is a major welfare issue. Here, we use whole-genome sequence data in a multi-trait GWAS to identify pleiotropic putative causal variants and genes associated with changes in key wool traits and skin wrinkle., Results: A stepwise conditional multi-trait GWAS (CM-GWAS) identified putative causal variants and related genes from 178 independent quantitative trait loci (QTL) of 16 wool and skin wrinkle traits, measured on up to 7218 Merino sheep with 31 million imputed whole-genome sequence (WGS) genotypes. Novel candidate gene findings included the MAT1A gene that encodes an enzyme involved in the sulphur metabolism pathway critical to production of wool proteins, and the ESRP1 gene. We also discovered a significant wrinkle variant upstream of the HAS2 gene, which in dogs is associated with the exaggerated skin folds in the Shar-Pei breed., Conclusions: The wool and skin wrinkle traits studied here appear to be highly polygenic with many putative candidate variants showing considerable pleiotropy. Our CM-GWAS identified many highly plausible candidate genes for wool traits as well as breech wrinkle and breech area wool cover.

Objective: To evaluate whether neurobehavioral symptoms differ between groups of veterans with mild traumatic brain injury (mTBI) classified by health characteristics., Participants: A total of 71 934 post-9/11 veterans with mTBI from the Chronic Effects of Neurotrauma Consortium Epidemiology warfighter cohort., Design: Cross-sectional analysis of retrospective cohort., Main Measures: Health phenotypes identified using latent class analysis of health and function over 5 years. Symptom severity measured using Neurobehavioral Symptom Inventory; domains included vestibular, somatic, cognitive, and affective., Results: Veterans classified as moderately healthy had the lowest symptom burden while the polytrauma phenotype group had the highest. After accounting for sociodemographic and injury characteristics, polytrauma phenotype veterans had about 3 times the odds of reporting severe symptoms in each domain compared with moderately healthy veterans. Those veterans who were initially moderately healthy but whose health declined over time had about twice the odds of severe symptoms as consistently healthier Veterans. The strongest associations were in the affective domain. Compared with the moderately healthy group, veterans in other phenotypes were more likely to report symptoms substantially interfered with their daily lives (odds ratio range: 1.3-2.8)., Conclusion: Symptom severity and interference varied by phenotype, including between veterans with stable and declining health. Ameliorating severe symptoms, particularly in the affective domain, could improve health trajectories following mTBI., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Genetic parameters for test-day milk yield, lactation persistency, and age at first calving (as a fertility trait) were estimated for the first 4 lactations in multiple-breed dairy cows in low-, medium-, and high-production systems in Kenya. Data included 223,285 test-day milk yield records from 11,450 cows calving from 1990 to 2015 in 148 herds. A multivariate random regression model was used to estimate variance and covariance components. The fixed effects in the model included herd, year, and test month, and age as a covariate. The lactation profile over days in milk (DIM) was fitted as a cubic smoothing spline. Random effects included herd, year, and test month interaction effects, genetic group effects, and additive genetic and permanent environmental effects modeled with a cubic Legendre polynomial function. The residual variance was heterogeneous with 11 classes. Consequently, the variance components were varied over the lactation and with the production system. The estimated heritability for milk yield was lower in the low-production system (0.04-0.48) than in the medium- (0.22-0.59) and high-production (0.21-0 60) systems. The genetic correlations estimated between different DIM within lactations decreased as the time interval increased, becoming negative between the ends of the lactations in the low- and medium-production systems. Low (0.05) to medium (0.60) genetic correlations were estimated among first lactation test-day milk yields across the 3 production systems. Genetic correlations between the first lactation test-day milk yield and age at first calving ranged from 0.27 to 0.49, 0 to 0.81, and -0.08 to 0.27 in the low-, medium-, and high-production systems, respectively. Medium to high heritabilities (0.17-0.44) were estimated for persistency, with moderate to high (0.30-0.87) genetic correlations between 305-d milk yield and persistency. This indicates that genetic improvement in persistency would lead to increased milk yield. The low to medium genetic correlations between test-day milk yield between production systems indicate that sires may be re-ranked between production systems. Therefore, we conclude that sires should be selected based on a genetic evaluation within the target production system., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Objective: To determine the validity of diagnoses indicative of early-onset dementia (EOD) obtained from an algorithm using administrative data, we examined Veterans Health Administration (VHA) electronic medical records (EMRs)., Method: A previously used method of identifying cases of dementia using administrative data was applied to a random sample of 176 cases of Post-9/11 deployed veterans under 65 years of age. Retrospective, cross-sectional examination of EMRs was conducted, using a combination of administrative data, chart abstraction, and review/consensus by board-certified neuropsychologists., Results: Approximately 73% of EOD diagnoses identified using existing algorithms were identified as false positives in the overall sample. This increased to approximately 76% among those with mental health conditions and approximately 85% among those with mild traumatic brain injury (TBI; i.e. concussion). Factors related to improved diagnostic accuracy included more severe TBI, diagnosing clinician type, presence of neuroimaging data, absence of a comorbid mental health condition diagnosis, and older age at time of diagnosis., Conclusions: A previously used algorithm for detecting dementia using VHA administrative data was not supported for use in the younger adult samples and resulted in an unacceptably high number of false positives. Based on these findings, there is concern for possible misclassification in population studies using similar algorithms to identify rates of EOD among veterans. Further, we provide suggestions to develop an enhanced algorithm for more accurate dementia surveillance among younger populations.

Objective: To describe the prevalence and impact of vestibular dysfunction and nonspecific dizziness diagnoses and explore their associations with traumatic brain injury (TBI) severity, mechanism, and postconcussive comorbidities among post-9/11 veterans., Setting: Administrative medical record data from the US Departments of Defense and Veterans Affairs (VA)., Participants: Post-9/11 veterans with at least 3 years of VA care., Design: Cross-sectional, retrospective, observational study., Main Measures: International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes for TBI, vestibular dysfunction, dizziness, and other commonly associated postconcussive conditions; Neurobehavioral Symptom Inventory., Results: Of the 570 248 post-9/11 veterans in this sample, 0.45% had a diagnosis of vestibular dysfunction and 2.57% had nonspecific dizziness. Those with either condition were more likely to have evidence of TBI (57.11% vs 28.51%) and reported more disruption from neurobehavioral symptoms. Blast and nonblast injuries were associated with greater symptom disruption, particularly in combination., Conclusions: There was a consistent, significant association between TBI and vestibular dysfunction or nonspecific dizziness, after controlling for sociodemographic factors, injury mechanism, and comorbid conditions. Given that most deployed post-9/11 veterans report blast and/or nonblast injuries, the need for prompt identification and management of these conditions and symptoms is clear.

Background: Whole-genome sequence (WGS) data could contain information on genetic variants at or in high linkage disequilibrium with causative mutations that underlie the genetic variation of polygenic traits. Thus far, genomic prediction accuracy has shown limited increase when using such information in dairy cattle studies, in which one or few breeds with limited diversity predominate. The objective of our study was to evaluate the accuracy of genomic prediction in a multi-breed Australian sheep population of relatively less related target individuals, when using information on imputed WGS genotypes., Methods: Between 9626 and 26,657 animals with phenotypes were available for nine economically important sheep production traits and all had WGS imputed genotypes. About 30% of the data were used to discover predictive single nucleotide polymorphism (SNPs) based on a genome-wide association study (GWAS) and the remaining data were used for training and validation of genomic prediction. Prediction accuracy using selected variants from imputed sequence data was compared to that using a standard array of 50k SNP genotypes, thereby comparing genomic best linear prediction (GBLUP) and Bayesian methods (BayesR/BayesRC). Accuracy of genomic prediction was evaluated in two independent populations that were each lowly related to the training set, one being purebred Merino and the other crossbred Border Leicester x Merino sheep., Results: A substantial improvement in prediction accuracy was observed when selected sequence variants were fitted alongside 50k genotypes as a separate variance component in GBLUP (2GBLUP) or in Bayesian analysis as a separate category of SNPs (BayesRC). From an average accuracy of 0.27 in both validation sets for the 50k array, the average absolute increase in accuracy across traits with 2GBLUP was 0.083 and 0.073 for purebred and crossbred animals, respectively, whereas with BayesRC it was 0.102 and 0.087. The average gain in accuracy was smaller when selected sequence variants were treated in the same category as 50k SNPs. Very little improvement over 50k prediction was observed when using all WGS variants., Conclusions: Accuracy of genomic prediction in diverse sheep populations increased substantially by using variants selected from whole-genome sequence data based on an independent multi-breed GWAS, when compared to genomic prediction using standard 50K genotypes.

Mild traumatic brain injury in the Veteran population is frequently comorbid with pain, post-traumatic stress disorder, and/or depression. However, not everyone exposed to mild traumatic brain injury experiences these comorbidities and it is unclear what factors contribute to this variability. The objective of this study was to identify comorbidity phenotypes among Post-9/11 deployed Veterans with no or mild traumatic brain injury and examine the association of comorbidity phenotypes with adverse outcomes. We found that Veterans with mild traumatic brain injury (n = 93,003) and no brain injury (n = 434,378) were mean age of 32.0 (SD 9.21) on entering Department of Veterans Health Administration care, were predominantly Caucasian non-Hispanic (64.69%), and served in the Army (61.31%). Latent class analysis revealed five phenotypes in each subcohort; Moderately Healthy and Mental Health phenotypes were common to both. The Healthy phenotype was found only in no brain injury. Unique phenotypes in mild traumatic brain injury included Moderately Healthy+Decline, Polytrauma, and Polytrauma+Improvement. There was substantial variation in adverse outcomes. The Polytrauma+Improvement phenotype had the lowest likelihood of adverse outcomes. There were no differences between Moderately Healthy+Decline and Polytrauma phenotypes. Phenotypes of comorbidity vary significantly by traumatic brain injury status including divergence in phenotypes (and outcomes) over time in the mild traumatic brain injury subcohort. Understanding risk factors for the divergence between Polytrauma vs. Polytrauma+Improvement and Moderately Healthy vs. Moderately Healthy+Decline, will improve our ability to proactively mitigate risk, better understand the early patterns of comorbidity that are associated with neurodegenerative sequelae following mild traumatic brain injury, and plan more patient-centered care., Competing Interests: The authors have declared that no competing interests exist.

Objective: This study aimed to assess the outcomes of 2 treatments for patients with dizziness after mild traumatic brain injury (mTBI) who demonstrate abnormal cervical spine proprioception (CSP)., Methods: A retrospective records review was conducted on the medical charts of patients treated for dizziness after mTBI who received either standard care (vestibular rehabilitation therapy [VRT]) or cervical spine proprioceptive retraining (CSPR) from 2009 to 2013. All patients included in the analysis were active-duty military with recurring dizziness after mTBI who had at least 1 abnormal CSP test. Patients were excluded for dizziness with a clear peripheral vestibular or central symptom origin, incomplete data, or no CSP assessment, or if both treatments were administered. Forty-eight total patients were included in the final dataset (22 VRT; 26 CSPR). Traditional VRT was compared with CSPR when abnormal CSP tests were present, regardless of the presence or absence of neck pain. A clinician review of records was used to determine improvement of dizziness based on patient reports of symptoms at discharge evaluation (ie, no symptoms for at least 2 weeks)., Results: Patients who received CSPR were 30 times more likely to report improvement in dizziness symptoms compared with those who received VRT (adjusted odds ratio: 30.12; 95% confidence interval 4.44-204.26, P < .001) when abnormal CSP tests were present. Patients with dizziness over 1 year were significantly less likely to improve., Conclusion: These results suggest that patients with dizziness after mTBI and who had abnormal CSP assessments responded better to CSPR compared with those who received VRT., (Copyright © 2019. Published by Elsevier Inc.)

Background: The use of whole-genome sequence (WGS) data for genomic prediction and association studies is highly desirable because the causal mutations should be present in the data. The sequencing of 935 sheep from a range of breeds provides the opportunity to impute sheep genotyped with single nucleotide polymorphism (SNP) arrays to WGS. This study evaluated the accuracy of imputation from SNP genotypes to WGS using this reference population of 935 sequenced sheep., Results: The accuracy of imputation from the Ovine Infinium ® HD BeadChip SNP (~ 500 k) to WGS was assessed for three target breeds: Merino, Poll Dorset and F1 Border Leicester × Merino. Imputation accuracy was highest for the Poll Dorset breed, although there were more Merino individuals in the sequenced reference population than Poll Dorset individuals. In addition, empirical imputation accuracies were higher (by up to 1.7%) when using larger multi-breed reference populations compared to using a smaller single-breed reference population. The mean accuracy of imputation across target breeds using the Minimac3 or the FImpute software was 0.94. The empirical imputation accuracy varied considerably across the genome; six chromosomes carried regions of one or more Mb with a mean imputation accuracy of < 0.7. Imputation accuracy in five variant annotation classes ranged from 0.87 (missense) up to 0.94 (intronic variants), where lower accuracy corresponded to higher proportions of rare alleles. The imputation quality statistic reported from Minimac3 (R 2 ) had a clear positive relationship with the empirical imputation accuracy. Therefore, by first discarding imputed variants with an R 2 below 0.4, the mean empirical accuracy across target breeds increased to 0.97. Although accuracy of genomic prediction was less affected by filtering on R 2 in a multi-breed population of sheep with imputed WGS, the genomic heritability clearly tended to be lower when using variants with an R 2 ≤ 0.4., Conclusions: The mean imputation accuracy was high for all target breeds and was increased by combining smaller breed sets into a multi-breed reference. We found that the Minimac3 software imputation quality statistic (R 2 ) was a useful indicator of empirical imputation accuracy, enabling removal of very poorly imputed variants before downstream analyses.

Genetic correlations between 16 meat quality and nutritional value traits and live weight at various ages, live ultrasound fat and muscle depth, carcass measures, and carcass dissection traits were estimated for Merino sheep in the Information Nucleus (IN). Genetic correlations between live weight at various ages and the carcass traits are also reported. The IN comprised 8 genetically linked flocks managed across a range of Australian sheep environments. Meat quality traits included between 1,200 and 1,300 records for progeny from over 170 sires for intramuscular fat (IMF), lean meat yield (LMY), shear force (SF5), pH, meat color, and meat nutritional value traits including iron and zinc levels and long-chain omega-3 and omega-6 polyunsaturated fatty acid levels. The genetic correlations indicated that selection of Merino sheep to either reduce fat or increase muscle using ultrasound assessments will result in little change in IMF and SF5. Myoglobin levels would tend to be reduced following selection for reduced ultrasound fat depth (0.35 ± 0.21, 0.43 ± 0.14), whereas increases in myoglobin levels would occur due to selection for increased ultrasound muscle depth (0.25 ± 0.24, 0.38 ± 0.15). Selection for increased live weight will result in favorable correlated responses in hot carcass weight (0.76 to 0.97), dressing percentage (0.13 to 0.47), and carcass muscle (0.37 to 0.95), but unfavorable responses of increases in carcass fatness (0.13 to 0.65) and possible small reductions in muscle oxidative activity (-0.13 ± 0.14 to -0.73 ± 0.33) and iron content (-0.14 ± 0.15 to -0.38 ± 0.16), and a possible deterioration of shear force from selection at later ages (0.15 ± 0.26, 0.27 ± 0.24). Negligible changes are generally expected for LMY and meat color traits following selection for increased live weight (most genetic correlations less than 0.20 in size). Selection for increased LMY would tend to result in unfavorable changes in several aspects of meat quality, including reduced IMF (-0.27 ± 0.18), meat tenderness (0.53 ± 0.26), and meat redness (-0.69 ± 0.40), as well as reduced iron levels (-0.25 ± 0.22). These genetic correlations are a first step in assisting the development of breeding values for new traits to be incorporated into genetic evaluation programs to improve meat production from Merino sheep and other dual-purpose sheep breeds., (© The Author(s) 2018. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: To examine the association between traumatic brain injury (TBI) severity; social, family, and community reintegration outcomes; and return to work status among post-9/11 veterans in Department of Veterans Affairs (VA) care., Design: Retrospective observational cohort study., Setting: Mail/online survey fielded to a national sample of veterans., Participants: Sample of post-9/11 veterans with at least 3 years of VA care stratified according to TBI severity and comorbidities who completed and returned surveys (N=2023)., Interventions: Not applicable., Main Outcome Measures: Deployment Risk and Resilience Inventory-2 family functioning and social support subscales; Military to Civilian Questionnaire; and employment status., Results: Bivariate analyses revealed that veterans with every classification of TBI severity reported significantly more difficulty on social, family, and community reintegration outcomes than those with no TBI. In the fully adjusted model, veterans with unclassified and moderate/severe TBI reported significantly more difficulty with community reintegration and were less likely to be employed relative to those with no TBI; those with unclassified TBI also reported significantly more difficulty with family functioning. Veterans with mild TBI also reported significantly more difficulty with community reintegration., Conclusions: This study provides insight into long-term outcomes associated with TBI in post-9/11 veterans and suggests that exposure to TBI has a negative effect on social and family functioning, community reintegration, and return to work even after controlling for comorbidity, deployment experiences, and sociodemographic characteristics. Additional research is required to explicate what appears to be complex interactions among TBI severity, psychosocial well-being, combat exposures, and socioeconomic resources in this population., (Published by Elsevier Inc.)

Objectives: To describe the prevalence of sensory dysfunction (i.e. auditory, visual, vestibular, chemosensory and multiple sensory problems) and explore associations with traumatic brain injury (TBI) severity and injury mechanism among deployed Post-9/11 Veterans., Methods: This retrospective cohort analysis used Departments of Defense and Veterans Affairs diagnostic codes and administrative data., Results: Among the 570,248 Veterans in this cohort, almost 23% had at least one diagnosis of sensory dysfunction. In the multinomial regression analysis, the odds of all types of sensory dysfunction were greater among those with any TBI relative to those with no TBI. The odds for auditory or multisensory problems were higher among those that indicated exposure to blast. In particular, exposure to quaternary blast injury (e.g. crush, respiratory and burn injuries) was associated with increased odds for auditory, visual, vestibular and multisensory problems., Conclusions: Sensory problems affect a substantial number of deployed Post-9/11 Veterans and are more common among those with TBI or with exposure to deployment-related blast exposure. Because sensory problems profoundly impact quality of life, their identification and enhanced education and therapy are vital tools to improve prognosis for these relatively young Veterans.

Objectives: To examine long-term outcomes of self-reported physical and mental health among Post-9/11 Veterans stratified by traumatic brain injury (TBI) severity, we hypothesized that more severe TBI would be associated with significantly poorer outcomes., Methods: A prospective longitudinal survey of physical and mental health status was conducted with a national cohort of Post-9/11 Veterans. We then used generalized linear models (GLM) to assess the unique contribution of TBI severity on long-term outcomes after controlling for socio-demographic characteristics, comorbidity phenotypes, and deployment experiences., Results: TBI of any severity was associated with significantly poorer outcomes relative to the No TBI group. However, the manifestation of these outcomes identified in our study differed meaningfully by TBI severity level., Conclusions: Veterans with any TBI exposure experience poorer long-term outcomes than those with no TBI even when covariates are considered. In particular, measures of somatization, PTSD symptom distress, and depression indicate pervasive and long-term health concerns among individuals with TBI. Additional research is required to fully explicate what appear to be complex relationships among TBI severity, physical and mental well-being, combat exposures, and socioeconomic resources in this population.

Background: Building an efficient reference population for genomic selection is an issue when the recorded population is small and phenotypes are poorly informed, which is often the case in sheep breeding programs. Using stochastic simulation, we evaluated a genomic design based on a reference population with medium-density genotypes [around 45 K single nucleotide polymorphisms (SNPs)] of dams that were imputed from very low-density genotypes (≤ 1000 SNPs)., Methods: A population under selection for a maternal trait was simulated using real genotypes. Genetic gains realized from classical selection and genomic selection designs were compared. Genomic selection scenarios that differed in reference population structure (whether or not dams were included in the reference) and genotype quality (medium-density or imputed to medium-density from very low-density) were evaluated., Results: The genomic design increased genetic gain by 26% when the reference population was based on sire medium-density genotypes and by 54% when the reference population included both sire and dam medium-density genotypes. When medium-density genotypes of male candidates and dams were replaced by imputed genotypes from very low-density SNP genotypes (1000 SNPs), the increase in gain was 22% for the sire reference population and 42% for the sire and dam reference population. The rate of increase in inbreeding was lower (from - 20 to - 34%) for the genomic design than for the classical design regardless of the genomic scenario., Conclusions: We show that very low-density genotypes of male candidates and dams combined with an imputation process result in a substantial increase in genetic gain for small sheep breeding programs.

Genetic correlations between 29 wool production and quality traits and 25 meat quality and nutritional value traits were estimated for Merino sheep from an Information Nucleus (IN). Genetic correlations among the meat quality and nutritional value traits are also reported. The IN comprised 8 flocks linked genetically and managed across a range of sheep production environments in Australia. The wool traits included over 5,000 yearling and 3,700 adult records for fleece weight, fiber diameter, staple length, staple strength, fiber diameter variation, scoured wool color, and visual scores for breech and body wrinkle. The meat quality traits were measured on samples from the and included over 1,200 records from progeny of over 170 sires for intramuscular fat (IMF), shear force of meat aged for 5 d (SF5), 24 h postmortem pH (pHLL; also measured in the , pHST), fresh and retail meat color and meat nutritional value traits such as iron and zinc levels, and long-chain omega-3 and omega-6 polyunsaturated fatty acid levels. Estimated heritabilities for IMF, SF5, pHLL, pHST, retail meat color lightness (), myoglobin, iron, zinc and across the range of long-chain fatty acids were 0.58 ± 0.11, 0.10 ± 0.09, 0.15 ± 0.07, 0.20 ± 0.10, 0.59 ± 0.15, 0.31 ± 0.09, 0.20 ± 0.09, 0.11 ± 0.09, and range of 0.00 (eicosapentaenoic, docosapentaenoic, and arachidonic acids) to 0.14 ± 0.07 (linoleic acid), respectively. The genetic correlations between the wool production and meat quality traits were low to negligible and indicate that wool breeding programs will have little or no effect on meat quality. There were moderately favorable genetic correlations between important yearling wool production traits and the omega-3 fatty acids that were reduced for corresponding adult wool production traits, but these correlations are unlikely to be important in wool/meat breeding programs because they have high SE, and the omega-3 traits have little or no genetic variance. Significant genetic correlations among the meat quality traits included IMF with SF5 (-0.76 ± 0.24), fresh meat color * (0.50 ± 0.18), and zinc (0.41 ± 0.19). Selection to increase IMF will improve meat tenderness and color which may address some of the issues with Merino meat quality. These estimated parameters allow Merino breeders to combine wool and meat objectives without compromising meat quality.

Background: The application of genomic selection to sheep breeding could lead to substantial increases in profitability of wool production due to the availability of accurate breeding values from single nucleotide polymorphism (SNP) data. Several key traits determine the value of wool and influence a sheep's susceptibility to fleece rot and fly strike. Our aim was to predict genomic estimated breeding values (GEBV) and to compare three methods of combining information across traits to map polymorphisms that affect these traits., Methods: GEBV for 5726 Merino and Merino crossbred sheep were calculated using BayesR and genomic best linear unbiased prediction (GBLUP) with real and imputed 510,174 SNPs for 22 traits (at yearling and adult ages) including wool production and quality, and breech conformation traits that are associated with susceptibility to fly strike. Accuracies of these GEBV were assessed using fivefold cross-validation. We also devised and compared three approximate multi-trait analyses to map pleiotropic quantitative trait loci (QTL): a multi-trait genome-wide association study and two multi-trait methods that use the output from BayesR analyses. One BayesR method used local GEBV for each trait, while the other used the posterior probabilities that a SNP had an effect on each trait., Results: BayesR and GBLUP resulted in similar average GEBV accuracies across traits (~0.22). BayesR accuracies were highest for wool yield and fibre diameter (>0.40) and lowest for skin quality and dag score (<0.10). Generally, accuracy was higher for traits with larger reference populations and higher heritability. In total, the three multi-trait analyses identified 206 putative QTL, of which 20 were common to the three analyses. The two BayesR multi-trait approaches mapped QTL in a more defined manner than the multi-trait GWAS. We identified genes with known effects on hair growth (i.e. FGF5, STAT3, KRT86, and ALX4) near SNPs with pleiotropic effects on wool traits., Conclusions: The mean accuracy of genomic prediction across wool traits was around 0.22. The three multi-trait analyses identified 206 putative QTL across the ovine genome. Detailed phenotypic information helped to identify likely candidate genes.

Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross-validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross-validations. The accuracies of GEBVs from random cross-validations (range 0.17-0.61) were higher than were those from sire family cross-validations (range 0.00-0.51). The GEBV accuracies of 0.41-0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy, it identified several candidate genes which are known to be associated with NLB and LSIZE. The approach provides a way to make use of all data available in genomic prediction for traits that have limited recording., (© 2017 Stichting International Foundation for Animal Genetics.)

Hearing loss is the second most common disability awarded by the U.S. Department of Veterans Affairs (VA) to former members of the U.S. uniformed services. Hearing readiness and conservation practices differ among the four largest uniformed military services (Air Force, Army, Marine Corps, and Navy). Utilizing a data set consisting of all hearing loss claims submitted to the VA from fiscal years 2003-2013, we examined characteristics of veterans submitting claims within one year of separation from military service. Our results indicate that having a hearing loss disability claim granted was significantly more likely for men, individuals over the age of 26 years at the time of the claim, individuals most recently serving in the U.S. Army, and those with at least one hearing loss diagnosis. Importantly, individuals with at least one test record in the Defense Occupational and Environmental Health Readiness System-Hearing Conservation (DOEHRS-HC) system were significantly less likely to have a hearing loss disability claim granted by the VA. Within the DOEHRS-HC cohort, those with at least one threshold shift or clinical hearing loss diagnosis while on active duty were more than two and three times more likely to have a hearing loss disability claim granted, respectively. These findings indicate that an established history of reduced hearing ability while on active duty was associated with a significantly increased likelihood of an approved hearing loss disability claim relative to VA claims without such a history. Further, our results show a persistent decreased rate of hearing loss disability awards overall. These findings support increased inclusion of personnel in DoD hearing readiness and conservation programs to reduce VA hearing loss disability awards., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Genetic correlations between 29 wool production and quality traits and 14 whole carcass measures and carcass component traits were estimated from the Information Nucleus of 8 flocks managed across a range of Australian sheep production environments and genetically linked. Wool data were from over 5,000 Merino progeny born over 5 yr, whereas carcass data were from over 1,200 wether progeny of over 176 sires, slaughtered at about 21 kg carcass weight, on average. Wool traits included yearling and adult records for wool weight, fiber diameter, fiber diameter variation, staple strength, scoured color, and visual scores for breech and body wrinkle. Whole carcass measures included HCW, dressing percentage (DP), and various measures of fat depth and eye muscle dimensions. Carcass components were obtained by dissection, and lean meat yield (LMY) was predicted. Heritability estimates for whole carcass measures ranged from 0.12 ± 0.08 to 0.35 ± 0.10 and ranged from 0.17 ± 0.10 to 0.46 ± 0.10 for carcass dissection traits, with no evidence of important genotype × environment interactions. Genetic correlations indicated that selection for increased clean wool weight will result in reduced carcass fat (-0.17 to -0.34) and DP (-0.48 ± 0.15), with little effect on carcass muscle. Selection for lower fiber diameter will reduce HCW (-0.48 ± 0.15) as well as carcass fat (0.14 to 0.27) and muscle (0.21 to 0.50). There were high genetic correlations between live animal measures of fat and muscle depth and the carcass traits (generally greater than 0.5 in size). Selection to increase HCW (and DP) will result in sheep with fewer wrinkles on the body (-0.57 ± 0.10) and barer breeches (-0.74 ± 0.12, favorable), with minor deterioration in scoured wool color (reduced brightness and increased yellowness). Selection for reduced fat will also result in sheep with fewer body wrinkles (-0.42 to -0.79). Increasing LMY in Merinos through selection would result in a large reduction in carcass fat and DP (-0.66 to -0.84), with a smaller increase in carcass muscle and some increase in wool weight and wrinkles. Although no major antagonisms are apparent between the wool and carcass traits, developing selection indexes for dual-purpose wool and meat breeding objectives will require accurate estimates of genetic parameters to ensure that unfavorable relationships are suitably considered. The findings will aid development of dual-purpose wool and meat breeding objectives.

The purpose of this study was to describe the prevalence of hearing loss and tinnitus in a cohort of Iraq and Afghanistan Veterans (IAV) with common post-deployment conditions, including traumatic brain injury (TBI), post-traumatic stress disorder (PTSD), and other typical post-concussive conditions such as headaches and vertigo/dizziness. This retrospective observational study used data from the national Veterans Health Administration (VA) data repository from fiscal years 2001-2014. Veteran data was included if there were at least three years of VA care, with one or more years of care in 2007 or after. We identified comorbidities that may be associated with post-deployment hearing loss or tinnitus including TBI, PTSD, depression, and common post-concussive symptoms using International Classification of Diseases, 9th Revision, Clinical Modification codes. A multinomial logistic regression analysis was used to examine conditions associated with hearing loss or tinnitus. Among IAV, 570,332 were included in the final analysis. Of these, 7.78% of these were diagnosed with hearing loss alone, 6.54% with tinnitus alone, and 6.24% with both hearing loss and tinnitus. Comorbid TBI, PTSD, and depression were significantly associated with increased rates of hearing loss, tinnitus, or both conditions together. Older individuals, males, and those with TBI, PTSD, or vertigo/dizziness were significantly more likely to have hearing loss, tinnitus, or both. In order to provide more holistic post-deployment support, this myriad of conditions should be carefully considered in the planning of clinical care and beyond., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Genetic correlations between 29 wool production and quality traits and live weight and ultrasound fat depth (FAT) and eye muscle depth (EMD) traits were estimated from the Information Nucleus (IN). The IN comprised 8 genetically linked flocks managed across a range of Australian sheep production environments. The data were from a maximum of 9,135 progeny born over 5 yr from 184 Merino sires and 4,614 Merino dams. The wool traits included records for yearling and adult fleece weight, fiber diameter (FD), staple length (SL), fiber diameter CV (FDCV), scoured color, and visual scores for breech and body wrinkle. We found high heritability for the major yearling wool production traits and some wool quality traits, whereas other wool quality traits, wool color, and visual traits were moderately heritable. The estimates of heritability for live weight generally increased with age as maternal effects declined. Estimates of heritability for the ultrasound traits were also higher when measured at yearling age rather than at postweaning age. The genetic correlations for fleece weight with live weights were positive (favorable) and moderate (approximately 0.5 ± 0.1), whereas those with FD were approximately 0.3 (unfavorable). The other wool traits had lower genetic correlations with the live weights. The genetic correlations for FAT and EMD with FD and SL were positive and low, with FDCV low to moderate negative, but variable with wool weight and negligible for the other wool traits. The genetic correlations for FAT and EMD with postweaning weight were positive and high (0.61 ± 0.18 to 0.75 ± 0.14) but were generally moderate with weights at other ages. Selection for increased live weight will result in a moderate correlated increase in wool weight as well as favorable reductions in breech cover and wrinkle, along with some unfavorable increases in FD and wool yellowness but little impact on other wool traits. The ultrasound meat traits, FAT and EMD, were highly positively genetically correlated (0.8), and selection to increase them would result in a small unfavorable correlated increase in FD, moderately favorable reductions in breech cover and wrinkle, but equivocal or negligible changes in other wool traits. The estimated parameters provide the basis for calculation of more accurate Australian Sheep Breeding Values and selection indexes that combine wool and meat objectives in Merino breeding programs.

Background: Genomic prediction using high-density (HD) marker genotypes is expected to lead to higher prediction accuracy, particularly for more heterogeneous multi-breed and crossbred populations such as those in sheep and beef cattle, due to providing stronger linkage disequilibrium between single nucleotide polymorphisms and quantitative trait loci controlling a trait. The objective of this study was to evaluate a possible improvement in genomic prediction accuracy of production traits in Australian sheep breeds based on HD genotypes (600k, both observed and imputed) compared to prediction based on 50k marker genotypes. In particular, we compared improvement in prediction accuracy of animals that are more distantly related to the reference population and across sheep breeds., Methods: Genomic best linear unbiased prediction (GBLUP) and a Bayesian approach (BayesR) were used as prediction methods using whole or subsets of a large multi-breed/crossbred sheep reference set. Empirical prediction accuracy was evaluated for purebred Merino, Border Leicester, Poll Dorset and White Suffolk sire breeds according to the Pearson correlation coefficient between genomic estimated breeding values and breeding values estimated based on a progeny test in a separate dataset., Results: Results showed a small absolute improvement (0.0 to 8.0% and on average 2.2% across all traits) in prediction accuracy of purebred animals from HD genotypes when prediction was based on the whole dataset. Greater improvement in prediction accuracy (1.0 to 12.0% and on average 5.2%) was observed for animals that were genetically lowly related to the reference set while it ranged from 0.0 to 5.0% for across-breed prediction. On average, no significant advantage was observed with BayesR compared to GBLUP.

Genomic selection is becoming a standard tool in livestock breeding programs, particularly for traits that are hard to measure. Accuracy of genomic selection can be improved by increasing the quantity and quality of data and potentially by improving analytical methods. Adding genotypes and phenotypes from additional breeds or crosses often improves the accuracy of genomic predictions but requires specific methodology. A model was developed to incorporate breed composition estimated from genotypes into genomic selection models. This method was applied to age at puberty data in female beef cattle (as estimated from age at first observation of a corpus luteum) from a mix of Brahman and Tropical Composite beef cattle. In this dataset, the new model incorporating breed composition did not increase the accuracy of genomic selection. However, the breeding values exhibited slightly less bias (as assessed by deviation of regression of phenotype on genomic breeding values from the expected value of 1). Adding additional Brahman animals to the Tropical Composite analysis increased the accuracy of genomic predictions and did not affect the accuracy of the Brahman predictions., (© 2015 Stichting International Foundation for Animal Genetics.)

Objectives: To identify and validate trajectories of comorbidity associated with traumatic brain injury in male and female Iraq and Afghanistan war Veterans (IAV)., Methods: Derivation and validation cohorts were compiled of IAV who entered the Department of Veterans Affairs (VA) care and received 3 years of VA care between 2002-2011. Chronic disease and comorbidities associated with deployment including TBI were identified using diagnosis codes. A latent class analysis (LCA) of longitudinal comorbidity data was used to identify trajectories of comorbidity., Results: LCA revealed five trajectories that were similar for women and men: (1) Healthy, (2) Chronic Disease, (3) Mental Health, (4) Pain and (5) Polytrauma Clinical Triad (PCT: pain, mental health and TBI). Two additional classes found in men were 6) Minor Chronic and 7) PCT with chronic disease. Among these gender-stratified trajectories, it was found that women were more likely to experience headache (Pain trajectory) and depression (Mental Health trajectory), while men were more likely to experience lower back pain (Pain trajectory) and substance use disorder (Mental Health trajectory). The probability of TBI was highest in the PCT-related trajectories, with significantly lower probabilities in other trajectories., Conclusions: It was found that TBI was most common in PCT-related trajectories, indicating that TBI is commonly comorbid with pain and mental health conditions for both men and women. The relatively young age of this cohort raises important questions regarding how disease burden, including the possibility of neurodegenerative sequelae, will accrue alongside normal age-related decline in individuals with TBI. Additional 'big data' methods and a longer observation period may allow the development of predictive models to identify individuals with TBI that are at-risk for adverse outcomes.

Background: Female reproductive technologies such as multiple ovulation and embryo transfer (MOET) and juvenile in vitro embryo production and embryo transfer (JIVET) can boost rates of genetic gain but they can also increase rates of inbreeding. Inbreeding can be managed using the principles of optimal contribution selection (OCS), which maximizes genetic gain while placing a penalty on the rate of inbreeding. We evaluated the potential benefits and synergies that exist between genomic selection (GS) and reproductive technologies under OCS for sheep and cattle breeding programs., Methods: Various breeding program scenarios were simulated stochastically including: (1) a sheep breeding program for the selection of a single trait that could be measured either early or late in life; (2) a beef breeding program with an early or late trait; and (3) a dairy breeding program with a sex limited trait. OCS was applied using a range of penalties (severe to no penalty) on co-ancestry of selection candidates, with the possibility of using multiple ovulation and embryo transfer (MOET) and/or juvenile in vitro embryo production and embryo transfer (JIVET) for females. Each breeding program was simulated with and without genomic selection., Results: All breeding programs could be penalized to result in an inbreeding rate of 1 % increase per generation. The addition of MOET to artificial insemination or natural breeding (AI/N), without the use of GS yielded an extra 25 to 60 % genetic gain. The further addition of JIVET did not yield an extra genetic gain. When GS was used, MOET and MOET + JIVET programs increased rates of genetic gain by 38 to 76 % and 51 to 81 % compared to AI/N, respectively., Conclusions: Large increases in genetic gain were found across species when female reproductive technologies combined with genomic selection were applied and inbreeding was managed, especially for breeding programs that focus on the selection of traits measured late in life or that are sex-limited. Optimal contribution selection was an effective tool to optimally allocate different combinations of reproductive technologies. Applying a range of penalties to co-ancestry of selection candidates allows a comprehensive exploration of the inbreeding vs. genetic gain space.

Recent theories posit that adult neurogenesis supports dentate gyrus pattern separation and hence is necessary for some types of discrimination learning. Using an inducible transgenic mouse model, we investigated the contribution of adult-born neurons to spatial and nonspatial touch-screen discriminations of varying levels of difficulty. Arresting neurogenesis caused a modest but statistically significant impairment in a position discrimination task. However, the effect was present only on trials after a learned discrimination was reversed, suggesting that neurogenesis supports cognitive flexibility rather than spatial discrimination per se. The deficit was present 4-10 weeks after the arrest of neurogenesis but not immediately after, consistent with previous evidence that the behavioral effects of arresting neurogenesis arise because of the depletion of adult-born neurons at least 1 month old. The arrest of neurogenesis failed to affect a nonspatial brightness discrimination task that was equal in difficulty to the spatial task. The data suggest that adult neurogenesis is not strictly necessary for spatial or perceptual discrimination learning and instead implicate adult neurogenesis in factors related to reversal learning, such as cognitive flexibility or proactive interference., (© 2014 Wiley Periodicals, Inc.)

Background: The accuracy of genomic prediction depends largely on the number of animals with phenotypes and genotypes. In some industries, such as sheep and beef cattle, data are often available from a mixture of breeds, multiple strains within a breed or from crossbred animals. The objective of this study was to compare the accuracy of genomic prediction for several economically important traits in sheep when using data from purebreds, crossbreds or a combination of those in a reference population., Methods: The reference populations were purebred Merinos, crossbreds of Border Leicester (BL), Poll Dorset (PD) or White Suffolk (WS) with Merinos and combinations of purebred and crossbred animals. Genomic breeding values (GBV) were calculated based on genomic best linear unbiased prediction (GBLUP), using a genomic relationship matrix calculated based on 48 599 Ovine SNP (single nucleotide polymorphisms) genotypes. The accuracy of GBV was assessed in a group of purebred industry sires based on the correlation coefficient between GBV and accurate estimated breeding values based on progeny records., Results: The accuracy of GBV for Merino sires increased with a larger purebred Merino reference population, but decreased when a large purebred Merino reference population was augmented with records from crossbred animals. The GBV accuracy for BL, PD and WS breeds based on crossbred data was the same or tended to decrease when more purebred Merinos were added to the crossbred reference population. The prediction accuracy for a particular breed was close to zero when the reference population did not contain any haplotypes of the target breed, except for some low accuracies that were obtained when predicting PD from WS and vice versa., Conclusions: This study demonstrates that crossbred animals can be used for genomic prediction of purebred animals using 50 k SNP marker density and GBLUP, but crossbred data provided lower accuracy than purebred data. Including data from distant breeds in a reference population had a neutral to slightly negative effect on the accuracy of genomic prediction. Accounting for differences in marker allele frequencies between breeds had only a small effect on the accuracy of genomic prediction from crossbred or combined crossbred and purebred reference populations.

Procedures are described for estimating selection index accuracies for individual animals and expected genetic change from selection for the general case where indexes of EBVs predict an aggregate breeding objective of traits that may or may not have been measured. Index accuracies for the breeding objective are shown to take an important general form, being able to be expressed as the product of the accuracy of the index function of true breeding values and the accuracy with which that function predicts the breeding objective. When the accuracies of the individual EBVs of the index are known, prediction error variances (PEVs) and covariances (PECs) for the EBVs within animal are able to be well approximated, and index accuracies and expected genetic change from selection estimated with high accuracy. The procedures are suited to routine use in estimating index accuracies in genetic evaluation, and for providing important information, without additional modelling, on the directions in which a population will move under selection., (© 2012 Animal Genetics & Breeding Unit, UNE.)

In single-step genomic evaluation using best linear unbiased prediction (ssGBLUP), genomic predictions are calculated with a relationship matrix that combines pedigree and genomic information. For missing pedigrees, unknown selection processes, or inclusion of several populations, a BLUP model can include unknown-parent groups (UPG) in the animal effect. For ssGBLUP, UPG equations also involve contributions from genomic relationships. When those contributions are ignored, UPG solutions and genetic predictions can be biased. Options to eliminate or reduce such bias are presented. First, mixed model equations can be modified to include contributions to UPG elements from genomic relationships (greater software complexity). Second, UPG can be implemented as separate effects (higher cost of computing and data processing). Third, contributions can be ignored when they are relatively small, but they may be small only after refinements to UPG definitions. Fourth, contributions may approximately cancel out when genomic and pedigree relationships are constructed for compatibility; however, different construction steps are required for unknown parents from the same or different populations. Finally, an additional polygenic effect that also includes UPG can be added to the model., (© 2013 Blackwell Verlag GmbH.)

Background: Genomic predictions can be applied early in life without impacting selection candidates. This is especially useful for meat quality traits in sheep. Carcass and novel meat quality traits were predicted in a multi-breed sheep population that included Merino, Border Leicester, Polled Dorset and White Suffolk sheep and their crosses., Methods: Prediction of breeding values by best linear unbiased prediction (BLUP) based on pedigree information was compared to prediction based on genomic BLUP (GBLUP) and a Bayesian prediction method (BayesR). Cross-validation of predictions across sire families was used to evaluate the accuracy of predictions based on the correlation of predicted and observed values and the regression of observed on predicted values was used to evaluate bias of methods. Accuracies and regression coefficients were calculated using either phenotypes or adjusted phenotypes as observed variables., Results and Conclusions: Genomic methods increased the accuracy of predicted breeding values to on average 0.2 across traits (range 0.07 to 0.31), compared to an average accuracy of 0.09 for pedigree-based BLUP. However, for some traits with smaller reference population size, there was no increase in accuracy or it was small. No clear differences in accuracy were observed between GBLUP and BayesR. The regression of phenotypes on breeding values was close to 1 for all methods, indicating little bias, except for GBLUP and adjusted phenotypes (regression = 0.78). Accuracies calculated with adjusted (for fixed effects) phenotypes were less variable than accuracies based on unadjusted phenotypes, indicating that fixed effects influence the latter. Increasing the reference population size increased accuracy, indicating that adding more records will be beneficial. For the Merino, Polled Dorset and White Suffolk breeds, accuracies were greater than for the Border Leicester breed due to the smaller sample size and limited across-breed prediction. BayesR detected only a few large marker effects but one region on chromosome 6 was associated with large effects for several traits. Cross-validation produced very similar variability of accuracy and regression coefficients for BLUP, GBLUP and BayesR, showing that this variability is not a property of genomic methods alone. Our results show that genomic selection for novel difficult-to-measure traits is a feasible strategy to achieve increased genetic gain.

Traumatic brain injury (TBI) is a major public health issue affecting 1.7 million Americans each year, of which approximately 50,000 are fatal. High-fat sucrose (HFS) diets are another public health issue which can lead to obesity, hypertension, and many other debilitating disorders. These two disorders combined can lead to more complicated issues. It has recently been shown that HFS diets can reduce levels of brain-derived neurotrophic factor (BDNF) leading to reductions in neuronal and behavioral plasticity. This reduction in BDNF is suspected of increasing the susceptibility of the brain to injury. To test the effects of a HFS diet on recovery of function post-TBI, male Sprague-Dawley rats were used in this study. Eight weeks prior to TBI, rats were placed on a special HFS diet (n=14) or a standard rodent diet (n=14). Following this eight-week period, rats were prepared with bilateral frontal cortical contusion injuries (CCI) or sham procedures. Beginning two days post-TBI, animals were tested on a battery of behavioral tests to assess somatosensory dysfunction and spatial memory in the Morris water maze, with a reference memory and a working memory task. Following testing, animals were sacrificed and their brains processed for lesion analysis. The HFS diet worsened performance on the bilateral tactile adhesive removal test in sham animals. Injured animals on the Standard diet had a greater improvement in somatosensory performance in the adhesive removal test and had better performance on the working memory task compared to animals on the HFS diet. The HFS diet also resulted in significantly greater loss of cortical tissue post-CCI than in the Standard diet group. This study may aid in determining how nutritional characteristics or habits interact with damage to the brain., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Microarray-based transcriptional profiling was used to determine the effect of progesterone in the cortical contusion (CCI) model. Gene ontology (GO) analysis then evaluated the effect of dose on relevant biological pathways. Treatment (vehicle, progesterone 10 mg/kg or 20 mg/kg given i.p.) was started 4 h post-injury and administered every 12 h post-injury for up to 72 h, with the last injection 12 hr prior to death for the 24 h and 72 h groups. In the CCI-injured vehicle group compared to non-injured animals, expression of 1,114, 4,229, and 291 distinct genes changed >1.5-fold (p<0.05) at 24 h, 72 h, and 7 days, respectively. At 24 h, the effect of low-dose progesterone on differentially expressed genes was <20% the effect of higher dose compared to vehicle. GO analysis identified a significant effect of low- and high-dose progesterone treatment compared to vehicle on DNA damage response. At 72 h, high-dose progesterone treatment compared to vehicle affected expression of almost twice as many genes as did low-dose progesterone. Both low- and high-dose progesterone resulted in expression of genes regulating inflammatory response and apoptosis. At 7 days, there was only a modest difference in high-dose progesterone compared to vehicle, with only 14 differentially expressed genes. In contrast, low-dose progesterone resulted in 551 differentially expressed genes compared to vehicle. GO analysis identified genes for the low-dose treatment involved in positive regulation of cell proliferation, innate immune response, positive regulation of anti-apoptosis, and blood vessel remodeling.