Dordt College

The popularization of biobanks provides an unprecedented amount of genetic and phenotypic information that can be used to research the relationship between genetics and human health. Despite the opportunities these datasets provide, they also pose many problems associated with computational time and costs, data size and transfer, and privacy and security. The publishing of summary statistics from these biobanks, and the use of them in a variety of downstream statistical analyses, alleviates many of these logistical problems. However, major questions remain about how to use summary statistics in all but the simplest downstream applications. Here, we present a novel approach to utilize basic summary statistics (estimates from single marker regressions on single phenotypes) to evaluate more complex phenotypes using multivariate methods. In particular, we present a covariate-adjusted method for conducting principal component analysis (PCA) utilizing only biobank summary statistics. We validate exact formulas for this method, as well as provide a framework of estimation when specific summary statistics are not available, through simulation. We apply our method to a real data set of fatty acid and genomic data.

Chronic pain can pose a serious challenge in everyday life for many individuals globally, especially in developing countries, but studies explicitly exploring risk factors of chronic pain beyond demographic characteristics using survey data have been scarce. To address this problem, this study analyzed World Health Organization data on chronic pain in Ukraine to explore demographic, psychological, and treatment perception-related risk factors to chronic pain. We replicated previous reports of older age, female sex, married status, inadequate financial resources, and comorbidity of other physical conditions as significant demographic risk factors for chronic pain diagnosis but not necessarily for severe pain. We also found evidence for psychological risk factors and treatment perceptions as significant predictors for chronic pain diagnosis and its severity. These results provide a first step in examining beyond demographic risk factors for chronic pain diagnosis and severity and, instead, assessing potential psychological risk factors.

A novel metagenomics method was produced for taxonomic analysis of a community of soil bacteria via quantitative polymerase chain reaction (qPCR). Taxonomies were confirmed via phylum-specific primers targeting various regions of the 16S DNA gene. Through this method, the effects of common herbicides on soil bacterial communities were determined. This method was verified by direct comparison to shotgun sequencing of the same DNA library used for qPCR. Taxonomic analysis of a similar accuracy as metagenomic shotgun sequencing was achieved. The novel method improves the ability to taxonomically analyze soil bacterial communities without specialized equipment for DNA sequencing.

The current generation of young teachers entering the profession is often presumed to have an easy comfort with and seemingly innate understanding of technology. Prensky (2001) has gone so far as to name them “digital natives” and has claimed that members of the millennial generation “think and process information fundamentally differently from their predecessors” (p. 1). However, recent studies in several English-speaking western nations call the millennial generation's innately skillful use of technology into question, and some studies of millennial teachers indicate that they are, in fact, no better at integrating technology into their teaching than their colleagues from other generations. Rogers' (2003) diffusion of innovations theory provides an alternative to the digital native/digital immigrant approach for explaining teachers' technology integration habits. Based on this approach, suggestions for teacher educators are recommended for training millennial teachers to integrate technology and pedagogy.

Context.A new class of exoplanets has emerged: the ultra hot Jupiters, the hottest close-in gas giants. The majority of them have weaker-than-expected spectral features in the 1.1−1.7μm bandpass probed by HST/WFC3 but stronger spectral features at longer wavelengths probed bySpitzer. This led previous authors to puzzling conclusions about the thermal structures and chemical abundances of these planets.Aims.We investigate how thermal dissociation, ionization, H−opacity, and clouds shape the thermal structures and spectral properties of ultra hot Jupiters.Methods.We use the SPARC/MITgcm to model the atmospheres of four ultra hot Jupiters and discuss more thoroughly the case of WASP-121b. We expand our findings to the whole population of ultra hot Jupiters through analytical quantification of the thermal dissociation and its influence on the strength of spectral features.Results.We predict that most molecules are thermally dissociated and alkalies are ionized in the dayside photospheres of ultra hot Jupiters. This includes H2O, TiO, VO, and H2but not CO, which has a stronger molecular bond. The vertical molecular gradient created by the dissociation significantly weakens the spectral features from H2Owhile the 4.5μm CO feature remains unchanged. The water band in the HST/WFC3 bandpass is further weakened by the continuous opacity of the H−ions. Molecules are expected to recombine before reaching the limb, leading to order of magnitude variations of the chemical composition and cloud coverage between the limb and the dayside.Conclusions.Molecular dissociation provides a qualitative understanding of the lack of strong spectral features of water in the 1−2μm bandpass observed in most ultra hot Jupiters. Quantitatively, our model does not provide a satisfactory match to the WASP-121b emission spectrum. Together with WASP-33b and Kepler-33Ab, they seem the outliers among the population of ultra hot Jupiters, in need of a more thorough understanding.

Recent analyses have suggested a strong heritable component to circulating fatty acid (FA) levels; however, only a limited number of genes have been identified which associate with FA levels. In order to expand upon a previous genome wide association study done on participants in the Framingham Heart Study Offspring Cohort and FA levels, we used data from 2,400 of these individuals for whom red blood cell FA profiles, dietary information and genotypes are available, and then conducted a genome-wide evaluation of potential genetic variants associated with 22 FAs and 15 FA ratios, after adjusting for relevant dietary covariates. Our analysis found nine previously identified loci associated with FA levels (FADS, ELOVL2, PCOLCE2, LPCAT3, AGPAT4, NTAN1/PDXDC1, PKD2L1, HBS1L/MYB and RAB3GAP1/MCM6), while identifying four novel loci. The latter include an association between variants in CALN1 (Chromosome 7) and eicosapentaenoic acid (EPA), DHRS4L2 (Chromosome 14) and a FA ratio measuring delta-9-desaturase activity, as well as two loci associated with less well understood proteins. Thus, the inclusion of dietary covariates had a modest impact, helping to uncover four additional loci. While genome-wide association studies continue to uncover additional genes associated with circulating FA levels, much of the heritable risk is yet to be explained, suggesting the potential role of rare genetic variation, epistasis and gene-environment interactions on FA levels as well. Further studies are needed to continue to understand the complex genetic picture of FA metabolism and synthesis.

Reviewed Title: Katz, Victor J. and Karen Hunger Parshall. Taming the Unknown: A History of Algebra from Antiquity to the Early Twentieth Century. Princeton, NJ: Princeton University Press, 2014. 485 pages. ISBN 9780691149059