Genome-wide association analyses reveal copy number variant regions associated with reproduction and disease traits in Canadian Holstein cattle.

This study aimed to evaluate the impact of copy number variants (CNV) on 13 reproduction and 12 disease traits in Holstein cattle. Intensity signal files containing log R ratio and B allele frequency information from 13,730 Holstein animals genotyped with a 95K SNP panel, and 8,467 Holstein animals genotyped with a 50K SNP panel were used to identify the CNVs. Subsequently, the identified CNVs were validated using whole-genome sequence data from 126 animals, resulting in 870 high-confidence copy number variant regions (CNVR) on 12,131 animals. Out of these, 54 CNVR had frequencies higher than or equal to 1% in the population and were used in the genome-wide association analysis (one CNVR at a time, including the G matrix). Results revealed that 4 CNVR were significantly associated with at least one of the traits analyzed in this study. Specifically, 2 CNVR were associated with 3 reproduction traits (i.e., calf survival, first service to conception, and nonreturn rate), and 2 CNVR were associated with 2 disease traits (i.e., metritis and retained placenta). These CNVR harbored genes implicated in immune response, cellular signaling, and neuronal development, supporting their potential involvement in these traits. Further investigations to unravel the mechanistic and functional implications of these CNVR on the mentioned traits are warranted.

Genetic analysis of pathogen-specific intramammary infections in dairy cows.

Mastitis is one of the most common diseases in dairy cattle, causing severe economic losses to dairy farmers. Mastitis usually occurs due to intramammary infection (IMI) caused by a variety of pathogenic bacteria. Although good progress has been made in understanding genetics of pathogen-specific clinical mastitis, studies involving genetic analysis of pathogen-specific IMI are scarce. The overall objective of this study was, therefore, to assess genetic variation of overall and pathogen-specific IMI in nonclinical primiparous and multiparous cows using bacterial culture. Data and milk samples were collected over a 2-yr interval as part of the Canadian Bovine Mastitis Research Network. The final data set contained records of 46,900 quarter milk samples from 3,382 clinically healthy primiparous and multiparous Holstein cows from 84 dairy herds. For the genetic analysis, we considered the following 7 traits: overall IMI, non-aureus staphylococci (NAS) IMI, contagious pathogen IMI, environmental pathogen IMI, major pathogen IMI, minor pathogen IMI and somatic cell score (SCS). Data were analyzed at the quarter level using a threshold-probit model via Gibbs sampling in BLUPF90. Prevalence of IMI traits at the quarter level in multiparous cow from 0 to 400 DIM ranged from 6.8 to 45.5%. Posterior mean of quarter heritability estimates (on the underlying scale, posterior SD in brackets) of overall IMI and pathogen-specific IMI traits ranged from 0.017 to 0.073 (±0.009 to 0.030). Weak to strong genetic correlations [ranging from 0.18 to 0.97 (±0.01 to 0.29)] among pathogen-specific IMI traits and with overall IMI indicated that not all of these traits were genetically similar. Weak to moderate Spearman rank correlations between estimated breeding values for overall IMI and pathogen-specific IMI traits (from 0.31 to 0.87) indicated possible substantial reranking of sires. The percentage of daughters with IMI caused by various pathogen groups ranged from 13 to 80% and from 38 to 94% for the best (10% decile) and worst sires (90% decile) according to their IMI trait-specific estimated breeding values, respectively. Pathogen-specific IMI traits and overall IMI had weak to moderate positive genetic correlations [ranging from 0.11 to 0.81 (±0.11 to 0.22)] with SCS. Therefore, selection for lower SCS will improve resistance to IMI. However, based on the observed weak to moderate rank correlations (0.04 to 0.47) between pathogen-specific IMI traits and SCS, selection for lower SCC will not improve resistance to IMI from every pathogen-specific IMI group in the same manner. Therefore, despite low heritability estimates, there was sizeable genetic variation for pathogen-specific IMI traits, indicating that long-term direct genetic selection for pathogen-specific IMI can improve pathogen-specific IMI resistance.

Genome-wide association study between copy number variants and hoof health traits in Holstein dairy cattle.

Genome-wide association studies based on SNP have been completed for multiple traits in dairy cattle; however, copy number variants (CNV) could add genomic information that has yet to be harnessed. The objectives of this study were to identify CNV in genotyped Holstein animals and assess their association with hoof health traits using deregressed estimated breeding values as pseudophenotypes. A total of 23,256 CNV comprising 1,645 genomic regions were identified in 5,845 animals. Fourteen genomic regions harboring structural variations, including 9 deletions and 5 duplications, were associated with at least 1 of the studied hoof health traits. This group of traits included digital dermatitis, interdigital dermatitis, heel horn erosion, sole ulcer, white line lesion, sole hemorrhage, and interdigital hyperplasia; no regions were associated with toe ulcer. Twenty candidate genes overlapped with the regions associated with these traits including SCART1, NRXN2, KIF26A, GPHN, and OR7A17. In this study, an effect on infectious hoof lesions could be attributed to the PRAME (Preferentially Expressed Antigen in Melanoma) gene. Almost all genes detected in association with noninfectious hoof lesions could be linked to known metabolic disorders. The knowledge obtained considering information of associated CNV to the traits of interest in this study could improve the accuracy of estimated breeding values. This may further increase the genetic gain for these traits in the Canadian Holstein population, thus reducing the involuntary animal losses due to lameness.

Estimation of genetic parameters for mid-infrared-predicted lactoferrin and milk fat globule size in Holstein cattle.

Lactoferrin (LF) and milk fat globule (MFG) are 2 biologically active components of milk with great economical and nutritional value in the dairy industry. The objectives of this study were to estimate (1) the heritability of mid-infrared (MIR)-predicted LF and MFG size (MFGS) and (2) the genetic correlations between predicted LF and MFGS with milk, fat, and protein yields, fat and protein percentages, and somatic cell score in first-parity Canadian Holstein cattle. A total of 109,029 test-day records from 22,432 cows and 1,572 farms for MIR-predicted LF and 109,212 test-day records from 22,424 cows and 1,559 farms for MIR-predicted MFGS were used in the analyses. Four separate 5-trait random regression test-day models were used. The models included days in milk, herd test date, and a polynomial regression on DIM nested in age-season of calving classes as fixed effects, random polynomial regressions on DIM nested in herd-year of calving, animal additive genetic and permanent environment classes, and a residual effect. Regression curves were modeled using orthogonal Legendre polynomials of order 4 for the fixed age-season of calving effect and of order 5 for the random effects. Moderate overall heritability estimates of 0.34 and 0.46 were estimated for the MIR-predicted LF and MIR-predicted MFGS, respectively. These heritability estimates were similar to the ones estimated for the direct measure of MFGS in a previous study. The genetic correlations between predicted MFGS and fat percentage (0.53) and between predicted LF and protein percentage (0.41) were both moderate and positive. Predicted LF and somatic cell score showed a weaker correlation (0.06) compared with other studies. The moderate genetic correlation between MIR-predicted MFGS and fat percentage and between MIR-predicted LF and protein percentage suggests that MIR predictions of MFGS and LF are not simply a function of the amount of fat and protein percentage, respectively, in the milk (i.e., the prediction equations are not simply predicting fat or protein percentages). Thus, these MIR-predicted values may provide additional information for selecting for fine milk components in Holstein cattle.

Genetic analysis of subclinical mastitis in early lactation of heifers using both linear and threshold models.

Subclinical mastitis (SCM) causes economic losses for dairy producers by reducing milk production and leading to higher incidence of clinical mastitis and premature culling. The prevalence of SCM in first-lactation heifers is highest during early lactation. The objective of this study was to estimate genetic parameters for SCM in early lactation in first-parity Holsteins. Somatic cell count test-day records were collected monthly in 91 Canadian herds participating in the National Cohort of Dairy Farms of the Canadian Bovine Mastitis Research Network. Only the first test-day record available between 5 and 30 d in milk was considered for analysis. The final data set contained 8,518 records from first lactation Holstein heifers. Six alternative traits were defined as indicators of SCM, using various cutoff values of SCC, ranging from 150,000 to 400,000 cells/mL. Both linear and threshold animal models were used. Overall prevalence of SCM using the 6 traits ranged from 13 to 24%. Heritability estimates (standard error) from linear and threshold models ranged from 0.037 to 0.057 (0.015 to 0.018) and from 0.040 to 0.051 (0.017 to 0.020), respectively. We found strong genetic correlations (standard error) among alternative SCC traits, ranging from 0.90 to 0.99 (0.013 to 0.069), indicating that these 6 traits were genetically similar. Despite low heritability, based on estimated breeding values (EBV) predicted from both models, we noted exploitable genetic variation among sires. Higher EBV of SCM resistance corresponded to sires with a higher percentage of daughters without SCM. Based on a linear model (all 6 traits), percentage of daughters with SCM ranged from 5 to 13% and from 19 to 33% for the top 10% and worst 10% of 69 sires with minimum 20 daughters in at least 5 herds, respectively. Spearman's rank correlations among EBV of sires predicted from linear (from 0.75 to 0.95) and threshold (from 0.74 to 0.95) models were moderate to high, respectively. Very high rank correlations (0.98 to 0.99) between EBV predicted for the same trait from linear and threshold model indicated that reranking of sires based on model used was minimal. In conclusion, despite low heritability, we found utilizable genetic variation in early lactation of heifers. Hence, genetic selection to improve genetic resistance to SCM in early lactation of heifers was deemed possible.

A 100-Year Review: Identification and genetic selection of economically important traits in dairy cattle.

Over the past 100 yr, the range of traits considered for genetic selection in dairy cattle populations has progressed to meet the demands of both industry and society. At the turn of the 20th century, dairy farmers were interested in increasing milk production; however, a systematic strategy for selection was not available. Organized milk performance recording took shape, followed quickly by conformation scoring. Methodological advances in both genetic theory and statistics around the middle of the century, together with technological innovations in computing, paved the way for powerful multitrait analyses. As more sophisticated analytical techniques for traits were developed and incorporated into selection programs, production began to increase rapidly, and the wheels of genetic progress began to turn. By the end of the century, the focus of selection had moved away from being purely production oriented toward a more balanced breeding goal. This shift occurred partly due to increasing health and fertility issues and partly due to societal pressure and welfare concerns. Traits encompassing longevity, fertility, calving, health, and workability have now been integrated into selection indices. Current research focuses on fitness, health, welfare, milk quality, and environmental sustainability, underlying the concentrated emphasis on a more comprehensive breeding goal. In the future, on-farm sensors, data loggers, precision measurement techniques, and other technological aids will provide even more data for use in selection, and the difficulty will lie not in measuring phenotypes but rather in choosing which traits to select for.

Socio-demographic and clinical characteristics of SARS-CoV-2-positive psychiatric in-patients: A case-control study in the psychiatric wards of a Great Metropolitan Hospital in Milan.

During the first Covid-19 outbreak, the Niguarda Hospital of Milan featured two Psychiatry wards, one for SARS-CoV-2 positive patient and one for patients requiring hospitalization and negative for SARS-CoV-2. The two groups of patients were compared and were similar in distribution of psychiatric diagnosis, duration of illness and previous hospitalizations. SARS-CoV-2 positive participants had a lower severity of symptoms both at admission and discharge, a lower frequency of psychotic symptoms and substance intoxication at admission. These findings suggest that patients admitted to the COVID ward were hospitalized not only for their mental health condition but also because of the infection.

Use of Milk Infrared Spectral Data as Environmental Covariates in Genomic Prediction Models for Production Traits in Canadian Holstein.

The purpose of this study was to provide a procedure for the inclusion of milk spectral information into genomic prediction models. Spectral data were considered a set of covariates, in addition to genomic covariates. Milk yield and somatic cell score were used as traits to investigate. A cross-validation was employed, making a distinction for predicting new individuals' performance under known environments, known individuals' performance under new environments, and new individuals' performance under new environments. We found an advantage of including spectral data as environmental covariates when the genomic predictions had to be extrapolated to new environments. This was valid for both observed and, even more, unobserved families (genotypes). Overall, prediction accuracy was larger for milk yield than somatic cell score. Fourier-transformed infrared spectral data can be used as a source of information for the calculation of the 'environmental coordinates' of a given farm in a given time, extrapolating predictions to new environments. This procedure could serve as an example of integration of genomic and phenomic data. This could help using spectral data for traits that present poor predictability at the phenotypic level, such as disease incidence and behavior traits. The strength of the model is the ability to couple genomic with high-throughput phenomic information.

Exploratory factor analysis of obsessive-compulsive patients and association with 5-HTTLPR polymorphism.

The determination of a genetic basis for obsessive-compulsive disorder (OCD) depends on how phenotypic boundaries are defined. Although a hypothesis for serotonin dysfunction in OCD has been advanced, no genes specifically responsible for serotonin regulation have as yet been definitively related to the etiology of OCD. The phenotypic variability of OCD could be at the basis of the failure of molecular biology investigations to find any genes involved in the liability to the disorder. Obsessive and compulsive contents can aggregate in OCD patients differently; multifactorial description may therefore be able to account for OCD phenotypic variance. Using principal component analysis, we derived five factors from 13 main contents of the Yale-Brown Obsessive-Compulsive Scale (YBOCS), and considered them as quantitative phenotypes to evaluate their possible association with an insertion/deletion polymorphism in the promoter region of the serotonin transporter gene (5-HTTLPR). A trend toward positive association between the fifth factor, including counting and repeating rituals, and 5-HTTLPR was found. However, only considering the subgroup of patients with tic codiagnosis, we found a significantly higher score for the fifth factor for patients with L/L genotype with respect to L/S and S/S genotypes.

Rationale and design of an independent randomised controlled trial evaluating the effectiveness of aripiprazole or haloperidol in combination with clozapine for treatment-resistant schizophrenia.

BACKGROUND: One third to two thirds of people with schizophrenia have persistent psychotic symptoms despite clozapine treatment. Under real-world circumstances, the need to provide effective therapeutic interventions to patients who do not have an optimal response to clozapine has been cited as the most common reason for simultaneously prescribing a second antipsychotic drug in combination treatment strategies. In a clinical area where the pressing need of providing therapeutic answers has progressively increased the occurrence of antipsychotic polypharmacy, despite the lack of robust evidence of its efficacy, we sought to implement a pre-planned protocol where two alternative therapeutic answers are systematically provided and evaluated within the context of a pragmatic, multicentre, independent randomised study. METHODS/DESIGN: The principal clinical question to be answered by the present project is the relative efficacy and tolerability of combination treatment with clozapine plus aripiprazole compared with combination treatment with clozapine plus haloperidol in patients with an incomplete response to treatment with clozapine over an appropriate period of time. This project is a prospective, multicentre, randomized, parallel-group, superiority trial that follow patients over a period of 12 months. Withdrawal from allocated treatment within 3 months is the primary outcome. DISCUSSION: The implementation of the protocol presented here shows that it is possible to create a network of community psychiatric services that accept the idea of using their everyday clinical practice to produce randomised knowledge. The employed pragmatic attitude allowed to randomly allocate more than 100 individuals, which means that this study is the largest antipsychotic combination trial conducted so far in Western countries. We expect that the current project, by generating evidence on whether it is clinically useful to combine clozapine with aripiprazole rather than with haloperidol, provides physicians with a solid evidence base to be directly applied in the routine care of patients with schizophrenia.

Listening to patients' needs to improve their subjective quality of life.

BACKGROUND: Subjective quality of life has gained a crucial role as a global measure of outcome in mental health care. This study aimed to investigate the impact of meeting needs for care, as assessed by both patients and mental health professionals, to improve the subjective quality of life in a sample of patients receiving community-based psychiatric care. METHOD: The study was conducted using a 4-year prospective longitudinal design. A cohort of patients from the South-Verona Community-based Mental Health Service (CMHS) was assessed at baseline and follow-up using, among other social and clinical measures, the Camberwell Assessment of Need (both staff and patient versions) and the Lancashire Quality of Life Profile. Predictors of changes of subjective quality of life were explored using block-stratified multiple regression procedures. RESULTS: Improvement in patients' clinical conditions as well as the reduction in patient-rated unmet needs in the social domain predicted an increase in subjective quality of life over 4 years; changes in staff-rated needs did not show any association with changes in subjective quality of life. CONCLUSIONS: Meeting self-perceived social needs, beyond symptoms reduction, seems to be of particular importance for ensuring a better quality of life for people with mental disorders. If the main goal of mental health care is to improve the quality of life of users, a policy of actively addressing patient-rated needs should be implemented.

Changes and predictors of change in objective and subjective quality of life: multiwave follow-up study in community psychiatric practice.

BACKGROUND: There is little knowledge of the predictors of objective and subjective quality of life. AIMS: To describe changes at 2 and 6 years in objective and subjective quality of life in 261 individuals attending a community mental health service and to identify predictors of change in each life domain. METHOD: Prospective study of demographic, diagnostic and service utilisation characteristics, psychopathology, functioning, disability, self-esteem, affect balance and service satisfaction. RESULTS: Female gender, unmarried status, older age, less education and greater disability predicted a worsening of objective quality of life over time, but explain a small amount of variance. The variance in subjective quality of life was higher (>40%). Greater clinician-rated anxiety and depressive symptoms had a negative effect on satisfaction with health and general well-being. Psychological status, self-esteem and satisfaction with service were the most important predictors in almost all subjective domains; these variables should be important targets for treatment. CONCLUSIONS: This study is the first to provide information to enable clinicians to make prognostic judgements about quality of life and plan effective therapeutic strategies to improve quality of life.