Polygenic Scores and Parental Predictors: An Adult Height Study Based on the United Kingdom Biobank and the Framingham Heart Study

Human height is a polygenic trait, influenced by a large number of genomic loci. In the pre-genomic era, height prediction was based largely on parental height. More recent predictions of human height have made great strides by integrating genotypic data from large biobanks with improved statistical techniques. Nevertheless, recent studies have not leveraged parental height, an added feature that we hypothesized would offer complementary predictive value. In this study, we assessed the predictive power of polygenic risk scores (PRS) combined with the traditional parental height predictors. Our study analyzed genotypic data and parental height from 1,071 trios from the United Kingdom Biobank and 444 trios from the Framingham Heart Study. We explored a series of statistical models to fully evaluate the performance of several PRS constructed together with parental information and proposed a model we call PRS++ that includes gender, parental height, and PRSs of parents and proband. Our estimate of height with an R2 of ∼0.82 is, to our knowledge, the most accurate estimate yet achieved for predicting human adult height. Without parental information, the R2 from the best PRS-driven model is ∼0.73. In summary, using adult height prediction as an example, we demonstrated that traditional predictors still play important roles and merit integration into the current trends of intensive PRS approaches.

Informing Parents about Newborn Screening: A European Comparison Study

Knowledge about newborn screening (NBS) is an important factor for parents to make an informed decision about participation. In Europe, countries inform parents differently about their NBS program, potentially including different knowledge aspects in their information. The aim of this study was to assess twenty-six European parental information products and to analyze their knowledge aspects through a content analysis. The analyzed aspects were compared to a list of eight knowledge aspects from scientific literature. The list includes aspects important for parents’ decision-making, such as the purpose of screening. The study showed that most of the eight knowledge aspects are included in NBS information products of the majority of countries. However, there were differences between countries, for example in the amount of detail and phrasing of the information. Additional relevant knowledge aspects have also been identified and are recommended to optimize information products, such as the handling of residual bloodspot samples. This study only assessed knowledge aspects in information products meant for printing, but many countries also use other communication methods, and the impact on knowledge of the delivery of the information needs further study. Preferences of parents on alternative communication methods need to be considered and evaluated on their effectiveness.

Designing Interface of Mobile Parental Information System based on Users’ Perception Using Kansei Engingeering

Users’ psychological emotion plays important role in designing an interface of software including application of information system. This research attempted to implement Kansei Engineering Type I (KEPack) as a method to analyze kinds of emotional factor related to user interface for mobile Parental Information System. This research used Kansei Words to explore users’ requirements based on psychological factors. Eighteen words were used for Kansei Words that have relationship with Parental Information System. Ten samples of mobile information system were selected as specimens considered suitable for designing interface of Parental Information System. Data questionnaires collected from thirty respondents were processed using multivariate statistical analysis such as Factor Analysis (FA) and Partial Least Square (PLS). This research found that the two important emotional factors i.e funny and informative have to be considered for designing user interface for mobile Parental Information System.

A statistical test for detecting parent-of-origin effects when parental information is missing

Genomic imprinting is an epigenetic mechanism that leads to differential contributions of maternal and paternal alleles to offspring gene expression in a parent-of-origin manner. We propose a novel test for detecting the parent-of-origin effects (POEs) in genome wide genotype data from related individuals (twins) when the parental origin cannot be inferred. The proposed method exploits a finite mixture of linear mixed models: the key idea is that in the case of POEs the population can be clustered in two different groups in which the reference allele is inherited by a different parent. A further advantage of this approach is the possibility to obtain an estimation of parental effect when the parental information is missing. We will also show that the approach is flexible enough to be applicable to the general scenario of independent data. The performance of the proposed test is evaluated through a wide simulation study. The method is finally applied to known imprinted genes of the MuTHER twin study data.