Clinical mastitis in cows treated with sometribove (recombinant bovine somatotropin) and its relationship to milk yield.

Effect of sometribove (methionyl bovine somatotropin) on mastitis in 15 full lactation trials (914 cows) in Europe and the US and 70 short-term studies (2697 cows) in eight countries was investigated. In full lactation studies, sometribove (500 mg/2 wk) was given for 252 d, commencing 60 d postpartum. Although herds varied considerably, incidence of clinical mastitis within a herd was similar for cows receiving control and sometribove treatments. Relative risk analyses indicated no treatment effect, and percentage of mastitis during treatment was similar for control and sometribove groups. A positive linear relationship existed between peak milk yield and mastitis incidence (percentage of cows contracting mastitis or cases per 100 cow days); sometribove treatment did not alter this relationship. Increases in mastitis related to milk yield increase from sometribove or related to genetic selection were similar. When expressed per unit of milk, mastitis incidence declined slightly as milk yield increased; this relationship was not altered by sometribove. No effect on clinical mastitis was observed in 70 commercial herds utilizing sometribove for 84 d. However, effects were significant for stage of lactation and milk yield. Overall, studies represented a wide range of research and commercial situations demonstrating that sometribove had no effect on incidence of clinical mastitis during the lactation of treatment. Furthermore, sometribove did not alter typical relationships between milk yield or herd factors and incidence of clinical mastitis

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders