Empty Cribs: Infertility Challenges for Orthodox Jewish Couples

This dissertation discusses an issue that is of importance to many people throughout their lifetime—infertility. One in every eight couples (12%) is incapable of carrying a pregnancy to term after one year of natural attempts. This paper further examines the prevalence of infertility among couples, bringing into focus more common variables such as gender and age. But, going beyond these, the present study will demonstrate that other variables including stressors such as social factors, interpersonal dynamics, and personal judgment affect couples in a manner which indirectly reduces their chances of conceiving a child. This research will touch on a number of such stressors, but it will focus in particular on the factors that account for infertility among Orthodox Jewish couples. Using thorough personal interviews, the present study discovered themes of protective factors and stressors that result from the traditions and laws of the Orthodox Jewish population; some of the themes were found to be unique to this population. This study emphasizes the importance of higher awareness of infertility in the Orthodox Jewish community, and discusses important clinical implications and recommendations in providing this information to the community. This dissertation is available in open access at AURA, http://aura.antioch.edu/ and OhioLINK ETD Center, https://etd.ohiolink.edu

The Twin Questions of Personalized Medicine: Who Are You and Whom Do You Most Resemble?

Personalized medicine is typically described as the use of molecular or genetic characteristics to customize therapy. This perspective at best provides an incomplete model of the patient and at worst can lead to grossly inappropriate practices. Personalization of medicine requires two characterizations: a well-grounded understanding of who the patient is and an equally robust understanding of the subpopulation that most resembles that patient in the context of the decisions at hand. These characterizations are readily represented probabilistically and can be used to drive decision-making in a rational manner that maximizes the positive outcomes for the patient

Tissue and Process Specific microRNA–mRNA Co-Expression in Mammalian Development and Malignancy

An association between enrichment and depletion of microRNA (miRNA) binding sites, 3′ UTR length, and mRNA expression has been demonstrated in various developing tissues and tissues from different mature organs; but functional, context-dependent miRNA regulations have yet to be elucidated. Towards that goal, we examined miRNA–mRNA interactions by measuring miRNA and mRNA in the same tissue during development and also in malignant conditions. We identified significant miRNA-mediated biological process categories in developing mouse cerebellum and lung using non-targeted mRNA expression as the negative control. Although miRNAs in general suppress target mRNA messages, many predicted miRNA targets demonstrate a significantly higher level of co-expression than non-target genes in developing cerebellum. This phenomenon is tissue specific since it is not observed in developing lungs. Comparison of mouse cerebellar development and medulloblastoma demonstrates a shared miRNA–mRNA co-expression program for brain-specific neurologic processes such as synaptic transmission and exocytosis, in which miRNA target expression increases with the accumulation of multiple miRNAs in developing cerebellum and decreases with the loss of these miRNAs in brain tumors. These findings demonstrate the context-dependence of miRNA–mRNA co-expression

Expression differences by continent of origin point to the immortalization process

Analysis of recently available microarray expression data sets obtained from immortalized cell lines of the individuals represented in the HapMap project have led to inconclusive comparisons across cohorts with different ancestral continent of origin (ACOO). To address this apparent inconsistency, we applied a novel approach to accentuate population-specific gene expression signatures for the CEU [homogeneous US residents with northern and western European ancestry (HapMap samples)] and YRI [homogenous Yoruba people of Ibadan, Nigeria (HapMap samples)] trios. In this report, we describe how four independent data sets point to the differential expression across ACOO of gene networks implicated in transforming the normal lymphoblast into immortalized lymphoblastoid cells. In particular, Werner syndrome helicase and related genes are differentially expressed between the YRI and CEU cohorts. We further demonstrate that these differences correlate with viral titer and that both the titer and expression differences are associated with ACOO. We use the 14 genes most differentially expressed to construct an ACOO-specific ‘immortalization network’ comprised of 40 genes, one of which show significant correlation with genomic variation (eQTL). The extent to which these measured group differences are due to differences in the immortalization procedures used for each group or reflect ACOO-specific biological differences remains to be determined. That the ACOO group differences in gene expression patterns may depend strongly on the process of transforming cells to establish immortalized lines should be considered in such comparisons

A SNP-centric database for the investigation of the human genome

BACKGROUND: Single Nucleotide Polymorphisms (SNPs) are an increasingly important tool for genetic and biomedical research. Although current genomic databases contain information on several million SNPs and are growing at a very fast rate, the true value of a SNP in this context is a function of the quality of the annotations that characterize it. Retrieving and analyzing such data for a large number of SNPs often represents a major bottleneck in the design of large-scale association studies. DESCRIPTION: SNPper is a web-based application designed to facilitate the retrieval and use of human SNPs for high-throughput research purposes. It provides a rich local database generated by combining SNP data with the Human Genome sequence and with several other data sources, and offers the user a variety of querying, visualization and data export tools. In this paper we describe the structure and organization of the SNPper database, we review the available data export and visualization options, and we describe how the architecture of SNPper and its specialized data structures support high-volume SNP analysis. CONCLUSIONS: The rich annotation database and the powerful data manipulation and presentation facilities it offers make SNPper a very useful online resource for SNP research. Its success proves the great need for integrated and interoperable resources in the field of computational biology, and shows how such systems may play a critical role in supporting the large-scale computational analysis of our genome

Extracting Physician Group Intelligence from Electronic Health Records to Support Evidence Based Medicine

Evidence-based medicine employs expert opinion and clinical data to inform clinical decision making. The objective of this study is to determine whether it is possible to complement these sources of evidence with information about physician “group intelligence” that exists in electronic health records. Specifically, we measured laboratory test “repeat intervals”, defined as the amount of time it takes for a physician to repeat a test that was previously ordered for the same patient. Our assumption is that while the result of a test is a direct measure of one marker of a patient's health, the physician's decision to order the test is based on multiple factors including past experience, available treatment options, and information about the patient that might not be coded in the electronic health record. By examining repeat intervals in aggregate over large numbers of patients, we show that it is possible to 1) determine what laboratory test results physicians consider “normal”, 2) identify subpopulations of patients that deviate from the norm, and 3) identify situations where laboratory tests are over-ordered. We used laboratory tests as just one example of how physician group intelligence can be used to support evidence based medicine in a way that is automated and continually updated