Yes / Purpose: To investigate whether a genetic risk score (GRS) improved performance of predicting refractive error compared to knowing a child’s number of myopic parents (NMP) alone. Methods: This was a retrospective analysis of data from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort study. Refractive error was assessed longitudinally between age 7–15 using non-cycloplegic autorefraction. Genetic variants (n=149) associated with refractive error from a Consortium for Refractive Error And Myopia (CREAM) genome-wide association study were used to calculate a GRS for each child. Using refractive error at ages 7 and 15 years as the outcome variable, coefficient of determination (R2) values were calculated via linear regression models for the predictors: NMP, GRS and a combined model. Results: Number of myopic parents was weakly predictive of refractive error in children aged 7 years, R2=3.0% (95% CI 1.8–4.1%,p<0.0001) and aged 15 years, R2=4.8% (3.1–6.5%,p<0.0001). The GRS was also weakly predictive;age 7 years, R2=1.1% (0.4–1.9%,p<0.0001) and 15 years R2=2.6% (1.3–3.9%,p<0.0001). Combining the 2 variables gave larger R2 values at age 7, R2=3.7%(2.5–5.0%,p<0.0001) and 15, R2=7.0% (5.0–9.0%,p<0.0001). The combined model improved performance at both ages (both p<0.0001). Conclusion: A GRS improved the ability to detect children at risk of myopia independently of knowing the NMP. We speculate this may be because NMP captures information concerning environmental risk factors for myopia. Nevertheless, further gains are required to make such predictive tests worthwhile in the clinical environment. / The UK Medical Research Council and Wellcome. Grant Number: 102215/2/13/2 The University of Bristol provide core support for ALSPAC PDF. Grant Number: 459KB The College of Optometrists NIHR Senior Research Fellowship. Grant Number: SRF‐2015‐08‐005 23andMe

Yes / Background: Myopia has been shown to have a complex mode of inheritance, being influenced by both genetic and environmental factors. Here, an introduction into myopia genetics is given, with the shortcomings of current genetic prediction for myopia discussed, including the proportionally limited research on genetic prediction in people of non-European ancestry. A previously developed genetic risk score derived from European participants was evaluated in participants of non-European ancestry. Methods: Participants from UK Biobank who self-reported their ethnicity as “Asian”, “Chinese”, or “Black” and who had refractive error and genetic data available were included in the analysis. Ancestral homogeneity was confirmed using principal component analysis, resulting in samples of 3500 Asian, 444 Chinese, and 3132 Black participants. A published refractive error GWAS meta-analysis of 711,984 participants of European ancestry was used to create a weighted genetic risk score model which was then applied to participants from each ethnic group. Accuracy of genetic prediction of refractive error was estimated as the proportion of variance explained (PVE). Receiver operating characteristic (ROC) curves were developed to estimate myopia prediction performance at three thresholds: any myopia (equal to or more than 0.75D), moderate myopia (between -3.00D and -4.99D) and high myopia (equal to or more than -5.00D). Odds ratios for myopia were calculated for the participants in the top 10th or 5th percentile of genetic risk score distribution, comparing them to the remainder of the population. Results: The PVE value for refractive error was 6.4%, 6.2%, and 1.5% for those with Asian, Chinese and Black ethnicity, respectively (compared to 11.2% in Europeans). Odds ratios for any myopia and moderate myopia development for those within the top 10th and 5th percentile of genetic risk were significant in all ethnic groups P<0.05). However, the genetic risk score was not able to reliably identify those at risk of high myopia, other than for participants of Chinese ethnicity (P<0.05). Conclusion: Prediction of refractive error in Asian, Chinese and Black participants was ~57%, 55% and 13% as accurate in comparison to prediction in European participants. Further research in diverse ethnic populations is needed to improve prediction accuracy. / This research has been conducted using the UK Biobank Resource (applications #17351). UK Biobank was established by the Wellcome Trust; the UK Medical Research Council; the Department for Health (London, UK); Scottish Government (Edinburgh, UK); and the Northwest Regional Development Agency (Warrington, UK). It also received funding from the Welsh Assembly Government (Cardiff, UK); the British Heart Foundation; and Diabetes UK. Collection of eye and vision data was supported by The Department for Health through an award made by the NIHR to the Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust, and UCL Institute of Ophthalmology, London, United Kingdom (grant no. BRC2_009). Additional support was provided by The Special Trustees of Moorfields Eye Hospital, London, United Kingdom (grant no. ST 12 09). Many parts of this project were performed during the time that author Neema Ghorbani Mojarrad was supported by the College of Optometrists with a Postgraduate Scholarship.

Thesis (MScAgric)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Mastitis is the most prevalent and costly production disease of dairy cattle; hence mastitis incidence is a distinctly important trait in dairy cattle. The primary objective of the study was to determine the economic value, and develop a model for genetic prediction of clinical mastitis in South African Holstein cattle. These procedures are a prerequisite to including this trait in the breeding objective. The cost of clinical mastitis per incident was calculated as the sum of revenue loss due to discarded milk during the infection period and the associated treatment costs. Economic value (ZAR/incident) was calculated as the change in profit (increase in costs) resulting from a simulated marginal increase in mastitis incidence in an average herd. Average economic losses due to clinical mastitis were estimated at ZAR919.96/cow/year and the average incidence was 0.9cases/cow/year. The economic value of clinical mastitis was ‐ZAR1079.51/incident. A model for predicting estimated breeding values (EBVs) for clinical mastitis using somatic cell score (SCS), fore teat length (FTL), udder depth (UD) and rear udder height (RUH) was developed, using genetic (co)variances among these traits. Since EBVs for SCS, FTL, UD and RUH are routinely estimated under the national genetic evaluation programme, EBVs for clinical mastitis can be predicted from the model developed in the current study. Thus, the results of the study provide the basis for including clinical mastitis in the breeding objective for South African Holstein cattle. / AFRIKAANSE OPSOMMING: Mastitis is die mees algemeenste en duursteproduksie siekte wat voorkom by melkbeeste, daarom is die voorkoms van mastitis 'n belangrike eienskap in melkbeeste. Die primêre doel van die studie was om die ekonomiese waarde te bepaal, asook die ontwikkeling van 'n model vir genetiese voorspelling van kliniese mastitis in Suid‐Afrikaanse Holstein beeste. Hierdie prosedures is 'n voorvereiste vir insluiting van hierdie eienskap as ‘n teeldoelwit in seleksie programme. Die koste van kliniese mastitis per voorval is bereken as die som van die inkomste verlies weens melk weggegooi tydens die infeksie periode en die gepaardgaande koste vir die behandeling. Ekonomiese waarde (ZAR / voorval) is bereken as die verandering in wins (toename in koste) wat voortspruit uit 'n gesimuleerde marginale toename in mastitis voorkoms in 'n gemiddelde kudde. Gemiddelde ekonomiese verliese as gevolg van kliniese mastitis was beraam op ZAR919.96/koei/jaar en die gemiddelde voorkoms was 0.9gevalle/koei/jaar. Die ekonomiese waarde van kliniese mastitis was ‐ ZAR1079.51/geval. 'n Model vir die voorspelling van beraamde teelwaardes (EBV’s) vir kliniese mastitis is ontwikkel deur gebruik te maak van die ko‐variansies tussen die onderskeie eienskappe: somatiese sel telling (SST), voorspeen lengte (VSL), uier diepte (UD) en agter uier hoogte (AUH). Aangesien teelwaardes vir SST, VSL, UD en AUH gereeld beraam word onder die Nasionale genetiese evaluasie program, kan teelwaardes vir kliniese mastitis voorspel word vanuit die model wat ontwikkel is in die huidige studie. Dus verskaf die resultate van hierdie studie ‘n basis vir die insluiting van kliniese mastitis as ‘n teeldoelwit in seleksie programme van die Suid‐Afrikaanse Holstein beeste.

Yes / Appeals have been made for eye care professionals to start prescribing anti-myopia therapies as part of their routine management of myopic children. 1–3 These calls are fuelled by two key considerations. Firstly, that interventions to slow myopia progression have shown success in randomized controlled trials (RCTs) 4–7, and secondly, appreciation that the risk of sight-threatening complications rises dose-dependently with the level of myopia. 8,9 Notwithstanding existing gaps in knowledge regarding the efficacy of current treatments (see below), these considerations argue that myopia control interventions should be widely adopted, and that they should be instigated at an early age – especially in children most at risk – in order to reduce the final level of myopia. Therefore in managing a child with myopia, an eye care professional would have to decide not only which therapy to recommend, but at what age to start treatment. In this review we discuss the future role of genetic prediction in helping clinicians treat myopia. / NIHR Senior Research Fellowship. Grant Number: SRF‐2015‐08‐005