Personal Goals of Older Female Twins

2009 ◽  
Vol 14 (2) ◽  
pp. 160-167 ◽  
Author(s):  
Katariina Salmela-Aro ◽  
Sanna Read ◽  
Jari-Erik Nurmi ◽  
Markku Koskenvuo ◽  
Jaakko Kaprio ◽  
...  
Keyword(s):  
Physical Exercise ◽  
Independent Living ◽  
Environmental Effect ◽  
Close Relationships ◽  
Environmental Influence ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Personal Goals ◽  
Cultural Activities ◽  
The Individual

This study examined genetic and environmental influences on older women’s personal goals by using data from the Finnish Twin Study on Aging. The interview for the personal goals was completed by 67 monozygotic (MZ) pairs and 75 dizygotic (DZ) pairs. The tetrachoric correlations for personal goals related to health and functioning, close relationships, and independent living were higher in MZ than DZ twins, indicating possible genetic influence. The pattern of tetrachoric correlations for personal goals related to cultural activities, care of others, and physical exercise indicated environmental influence. For goals concerning health and functioning, independent living, and close relationships, additive genetic effect accounted for about half of the individual variation. The rest was the result of a unique environmental effect. Goals concerning physical exercise and care of others showed moderate common environmental effect, while the rest of the variance was the result of a unique environmental effect. Personal goals concerning cultural activities showed unique environmental effects only.

scholarly journals Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

2014 ◽  
Vol 49 (5) ◽  
pp. 372-383 ◽  
Author(s):  
Maria Gabriela Campolina Diniz Peixoto ◽  
Daniel Jordan de Abreu Santos ◽  
Rusbel Raul Aspilcueta Borquis ◽  
Frank Ângelo Tomita Bruneli ◽  
João Cláudio do Carmo Panetto ◽  
...  
Keyword(s):  
Milk Production ◽  
Legendre Polynomial ◽  
Legendre Polynomials ◽  
Regression Models ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Random Regression ◽  
Additive Genetic Effect ◽  
Fifth Order

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Handedness in Twins: Joint Analysis of Data From 35 Samples

2006 ◽  
Vol 9 (1) ◽  
pp. 46-53 ◽  
Author(s):  
Sarah E. Medland ◽  
David L. Duffy ◽  
Margaret J. Wright ◽  
Gina M. Geffen ◽  
Nicholas G. Martin
Keyword(s):  
Confidence Interval ◽  
Familial Aggregation ◽  
Twin Studies ◽  
Genetic Effect ◽  
Joint Analysis ◽  
Additive Genetic Effect ◽  
Significant Heterogeneity ◽  
Environmental Model ◽  
Individual Level ◽  
The Individual

AbstractSimultaneous analysis of handedness data from 35 samples of twins (with a combined sample size of 21,127 twin pairs) found a small but significant additive genetic effect accounting for 25.47% of the variance (95% confidence interval [CI] 15.69–29.51%). No common environmental influences were detected (C = 0.00; 95% CI 0.00–7.67%), with the majority of the variance, 74.53%, explained by factors unique to the individual (95% CI 70.49–78.67%). No significant heterogeneity was observed within studies that used similar methods to assess handedness, or across studies that used different methods. At an individual level the majority of studies had insufficient power to reject a purely unique environmental model due to insufficient power to detect familial aggregation. This lack of power is seldom mentioned within studies, and has contributed to the misconception that twin studies of handedness are not informative.

scholarly journals Use of individual race results in the estimation of genetic parameters of trotting performance for Finnhorse and Standardbred trotters

1999 ◽  
Vol 8 (4-5) ◽  
pp. 353-363 ◽  
Author(s):  
T. THUNEBERG-SELONEN ◽  
J. PÖSÖ ◽  
E. MÄNTYSAARI
Keyword(s):  
Animal Model ◽  
Maximum Likelihood ◽  
Variance Components ◽  
Fixed Effects ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Performance Traits ◽  
Estimation Of Genetic Parameters

The heritability and repeatability for trotting performance traits were estimated from individual race results. Data comprised of records from 1991 to 1995 for 4808 Finnhorses and from 1993 to 1995 for 5869 Standardbred trotters. The statistical model included the additive genetic effect of an animal and two permanent environmental effects, and the fixed effects of sex, age, starting method*starting lane combination, driver and race. The first permanent environmental effect described repeatability over a horse’s career while the second one characterized repeatability within a racing year. Variance components for three trotting performance traits were estimated by the animal model and the method of restricted maximum likelihood (REML). Heritability and repeatability estimates were moderately high for time at finish (h 2 =0.23–0.28 and r=0.50–0.57), moderate for ranking within a race (h 2 =0.12 and r=0.25) and low for earnings (h 2 =0.05–0.09 and r=0.15–0.18). Time at finish seemed to be the most usable measure of trotting performance because of its wide information substance. However, time at finish does not take into account records of disqualified horses or of those which did not finish, but use of earnings, either from individual race results or preferably from annual records, is one possible way to consider records of such horses.;

scholarly journals Genetic maternal effects contributes to the risk of Tourette’s disorder

2020 ◽  
Author(s):  
Behrang Mahjani ◽  
Lambertus Klei ◽  
Christina M. Hultman ◽  
Henrik Larsson ◽  
Sven Sandin ◽  
...  
Keyword(s):  
Obsessive Compulsive Disorder ◽  
Maternal Effects ◽  
Genetic Effect ◽  
Tic Disorders ◽  
Additive Genetic Effect ◽  
Obsessive Compulsive ◽  
Compulsive Disorder ◽  
Medical Birth Register ◽  
Swedish Medical ◽  
The Individual

AbstractBackgroundRisk for Tourette’s and related tic disorders (CTD) derives from a combination of genetic and environmental factors. While multiple studies have demonstrated the importance of direct additive genetic variation for CTD, little is known about the role of cross-generational transmission of genetic risks, such as maternal effects. Here, we partition sources of variation on CTD risk into direct additive genetic effect and maternal effects.MethodsThe study population consists of 2,522,677 individuals from the Swedish Medical Birth Register, born in Sweden between January 1, 1982, to December 31, 1990, and followed for a diagnosis of CTD through December 31, 2013.ResultsWe identified 6,227 (0.25%) individuals in the birth cohort diagnosed with CTD. Using generalized linear mixed models, we estimated 4.7% (95% CrI, 4.4%-4.8%) genetic maternal effects, 0.5% (95% CrI, 0.2%-7%) environmental maternal effects, and 61% (95% CrI, 59%-63%) direct additive genetic effects. Around 1% of genetic maternal effects were due to maternal effects from the individual with comorbid obsessive-compulsive disorder.ConclusionsOur results demonstrate genetic maternal effects contributing to the risk of CTD in offspring and also highlight new sources of overlapping risk between CTD and obsessive-compulsive disorder.

scholarly journals Estimation of Genetic Parameters and Breeding Values of Milk Yield Using Test Day Model with Cubic Splines and Legendre Polynomials in Chinese Holstein Cattle

2021 ◽  
Vol 25 (02) ◽  
pp. 354-360
Author(s):  
Wan Lv
Keyword(s):  
Milk Yield ◽  
Legendre Polynomials ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Genetic Effect ◽  
Information Criterion ◽  
Additive Genetic Effect ◽  
Optimal Model ◽  
Breeding Values ◽  
Estimation Of Genetic Parameters

This study aimed to estimate the genetic parameters and breeding values of milk yield traits of Holstein cows in Shandong Province using the best model identified by a comparison between a numbers of alternative random regression test day models (RRMs). The data included 585,702 test day records of milk yield in the first lactation of 88,215 Holstein cows, covering 219 cattle farms in Shandong Province during the period from 2005 to 2016. Different models were investigated, which differed in the number of knots of Spline functions to improve the fitting of population lactation curve and in orders (2, 3, or 4) of Legendre polynomials to fit additive genetic effect and permanent environmental effect. The optimal test day model was screened out by Akaike information criterion (AIC) and Bayesian information criterion (BIC) criteria. Detailed analysis of genetic parameters and accuracy of estimation of breeding values were performed using the optimal model. In the results, the optimal model (Sp15-La4-Lp3) for analyzing the milk yield data was the one with 15 knots of Splines, 4 orders of Legendre polynomials for additive genetic effect and 3 orders of Legendre polynomials for permanent environmental effect. Using the optimal model, estimates of additive genetic variances of milk yield at different days in milk (DIM) during the whole lactation ranged from 8.54 to 15.39, the permanent environmental variance ranged from 17.65 to 31.42. Correspondingly, the heritability ranged from 0.20 to 0.30, and repeatability ranged from 0.43 to 0.54. Rank correlations between EBV of bull with different number of daughters and the bull’s parent average ranged from 0.79 to 0.94, and the correlations between EBV of bulls and the sire-maternal grandsire index ranged from 0.48 to 0.86. In conclusion, Sp15-La4-Lp3 could be the optimal model for estimation of genetic parameters and prediction of breeding values of milk in Shandong Holstein population. The amount of progeny information is critical to the conventional genetic evaluation of bulls. © 2021 Friends Science Publishers

Older Women’s Personal Goals and Exercise Activity: An 8-Year Follow-Up

2014 ◽  
Vol 22 (3) ◽  
pp. 386-392 ◽  
Author(s):  
Milla Saajanaho ◽  
Anne Viljanen ◽  
Sanna Read ◽  
Merja Rantakokko ◽  
Li-Tang Tsai ◽  
...  
Keyword(s):  
Older Adults ◽  
Older Women ◽  
Independent Living ◽  
Controlled Trial ◽  
Life Goals ◽  
Personal Goals ◽  
Cross Sectional ◽  
Cultural Activities ◽  
Exercise Activity

This study investigated the associations of personal goals with exercise activity, as well as the relationships between exercise-related and other personal goals, among older women. Both cross-sectional and longitudinal designs were used with a sample of 308 women ages 66–79 at baseline. Women who reported exercise-related personal goals were 4 times as likely to report high exercise activity at baseline than those who did not report exercise-related goals. Longitudinal results were parallel. Goals related to cultural activities, as well as to busying oneself around the home, coincided with exercise-related goals, whereas goals related to own and other people’s health and independent living lowered the odds of having exercise-related goals. Helping older adults to set realistic exercise-related goals that are compatible with their other life goals may yield an increase in their exercise activity, but this should be evaluated in a controlled trial.

Are palliative cancer patients willing and able to participate in a physical exercise program?

2005 ◽  
Vol 3 (4) ◽  
pp. 281-287 ◽  
Author(s):  
LINE M. OLDERVOLL ◽  
JON H. LOGE ◽  
HANNE PALTIEL ◽  
MAY B. ASP ◽  
UNNI VIDVEI ◽  
...  
Keyword(s):  
Palliative Care ◽  
Physical Exercise ◽  
Training Program ◽  
Cancer Patients ◽  
Physical Training ◽  
Exercise Program ◽  
Group Exercise ◽  
Medical Problems ◽  
Incurable Cancer ◽  
The Individual

Objective: The primary aim of the present article was to identify palliative care patient populations who are willing to participate in and able to complete a group exercise/physical training program designed specifically for the individual patient.Method: We conducted a prospective phase II intervention study examining the willingness and ability of palliative care cancer patients to participate in a group exercise physical training program. Patients who were diagnosed with incurable cancer and had a life expectancy of less than 1 year at two outpatient clinics were invited to participate in an exercise program in the hospitals. The groups met twice a week over a 6-week period.Results: One hundred one consecutive patients were asked for inclusion. Sixty-three patients agreed to participate. Sixteen (25%) of the 63 patients dropped out after consent was given, but before the program started due to medical problems, social reasons, or death. Thus, 47 patients started the exercise program. Thirteen patients withdrew during the program due to sudden death, medical problems, or social reasons. The most frequent reasons for withdrawal were increased pain or other symptoms. Thirty-four patients completed the exercise program.Significance of results: A high proportion of incurable cancer patients were willing to participate (63%) in a structured exercise program. The attrition rate was high, but despite being severely ill, 54% of the patients completed the exercise period. This shows that a physical exercise program tailored to the individual patient is feasible in this population.

scholarly journals A review of deep learning applications for genomic selection

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Osval Antonio Montesinos-López ◽  
Abelardo Montesinos-López ◽  
Paulino Pérez-Rodríguez ◽  
José Alberto Barrón-López ◽  
Johannes W. R. Martini ◽  
...  
Keyword(s):  
Deep Learning ◽  
Plant Breeding ◽  
Genomic Selection ◽  
Genomic Prediction ◽  
Mixed Model ◽  
Prediction Models ◽  
Genetic Effect ◽  
Training Data ◽  
Additive Genetic Effect ◽  
Main Body

Abstract Background Several conventional genomic Bayesian (or no Bayesian) prediction methods have been proposed including the standard additive genetic effect model for which the variance components are estimated with mixed model equations. In recent years, deep learning (DL) methods have been considered in the context of genomic prediction. The DL methods are nonparametric models providing flexibility to adapt to complicated associations between data and output with the ability to adapt to very complex patterns. Main body We review the applications of deep learning (DL) methods in genomic selection (GS) to obtain a meta-picture of GS performance and highlight how these tools can help solve challenging plant breeding problems. We also provide general guidance for the effective use of DL methods including the fundamentals of DL and the requirements for its appropriate use. We discuss the pros and cons of this technique compared to traditional genomic prediction approaches as well as the current trends in DL applications. Conclusions The main requirement for using DL is the quality and sufficiently large training data. Although, based on current literature GS in plant and animal breeding we did not find clear superiority of DL in terms of prediction power compared to conventional genome based prediction models. Nevertheless, there are clear evidences that DL algorithms capture nonlinear patterns more efficiently than conventional genome based. Deep learning algorithms are able to integrate data from different sources as is usually needed in GS assisted breeding and it shows the ability for improving prediction accuracy for large plant breeding data. It is important to apply DL to large training-testing data sets.

scholarly journals Genomic Breeding Values for Claw Diseases/Disorders in Czech Holstein Cows

2019 ◽  
Vol 67 (5) ◽  
pp. 1245-1251
Author(s):  
Ludmila Zavadilová ◽  
Eva Kašná ◽  
Zuzana Krupová
Keyword(s):  
Infectious Diseases ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Holstein Cows ◽  
Additive Genetic Effect ◽  
Genomic Information ◽  
White Line ◽  
Genomic Breeding ◽  
Breeding Values

Genomic breeding values (GEBV) were predicted for claw diseases/disorders in Holstein cows. The data sets included 6,498, 6,641 and 16,208 cows for the three groups of analysed disorders. The analysed traits were infectious diseases (ID), including digital and interdigital dermatitis and interdigital phlegmon, and non-infectious diseases (NID), including ulcers, white line disease, horn fissures, and double sole and overall claw disease (OCD), comprising all recorded disorders. Claw diseases/disorders were defined as 0/1 occurrence per lactation. Linear animal models were employed for prediction of conventional breeding values (BV) and genomic breeding values (GEBV), including the random additive genetic effect of animal and the permanent environmental effect of cow and fixed effects of parity, herd, year and month of calving. Both high and intermediate weights (80% and 50%, respectively) of genomic information were employed for GEBV50 and GEBV80 prediction. The estimated heritability for ID was 3.47%, whereas that for NID 4.61% and for OCD was 2.29%. Approximate genetic correlations among claw diseases/disorders traits ranged from 19% (ID x NID) to 81% (NID x OCD). The correlations between predicted BV and GEBV50 (84–99%) were higher than those between BV and GEBV80 (70–98%). Reliability of breeding values was low for each claw disease/disorder (on average, 3.7 to 14.8%) and increased with the weight of genomic information employed.

scholarly journals Estimates of (co)variance components and genetic parameters for body weights and growth efficiency traits in the New Zealand white rabbit

2017 ◽  
Vol 25 (4) ◽  
pp. 329 ◽  
Author(s):  
M. Sakthivel ◽  
D. Balasubramanyam ◽  
P. Kumarasamy ◽  
H. Gopi ◽  
A. Raja ◽  
...  
Keyword(s):  
Body Weight ◽  
New Zealand ◽  
Variance Components ◽  
Environmental Effect ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Genetic Effect ◽  
Growth Efficiency ◽  
Body Weights ◽  
Heritability Estimates

The genetic parameters of growth traits in the New Zealand White rabbits kept at Sheep Breeding and Research Station, Sandynallah, The Nilgiris, India were estimated by partitioning the variance and covariance components. The (co)variance components of body weights at weaning (W42), post-weaning (W70) and marketing (W135) age and growth efficiency traits viz., average daily gain (ADG), relative growth rate (RGR) and Kleiber ratio (KR) estimated on a daily basis at different age intervals (42 to 70 d; 70 to 135 d and 42 to 135 d) from weaning to marketing were estimated by restricted maximum likelihood, fitting 6 animal models with various combinations of direct and maternal effects. Data were collected over a period of 15 yr (1998 to 2012). A log-likelihood ratio test was used to select the most appropriate univariate model for each trait, which was subsequently used in bivariate analysis. Heritability estimates for W42, W70 and W135 were 0.42±0.07, 0.40±0.08 and 0.27±0.07, respectively. Heritability estimates of growth efficiency traits were moderate to high (0.18 to 0.42). Of the total phenotypic variation, maternal genetic effect contributed 14 to 32% for early body weight traits (W42 and W70) and ADG1. The contribution of maternal permanent environmental effect varied from 6 to 18% for W42 and for all the growth efficiency traits except for KR2. Maternal permanent environmental effect on most of the growth efficiency traits was a carryover effect of maternal care during weaning. Direct maternal genetic correlations, for the traits in which maternal genetic effect was significant, were moderate to high in magnitude and negative in direction. Maternal effect declined as the age of the animal increased. The estimates of total heritability and maternal across year repeatability for growth traits were moderate and an optimum rate of genetic progress seems possible in the herd by mass selection. The genetic and phenotypic correlations among body weights and between growth efficiency traits were also estimated. Moderate to high heritability and higher genetic correlation in body weight traits promise good scope for genetic improvement provided measures are taken to keep the inbreeding at the lowest level.

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