Racial disparities in infant mortality: what has birth weight got to do with it and how large is it?

<p>Abstract</p> <p>Background</p> <p>It has been hypothesized that birth weight is not on the causal pathway to infant mortality, at least among "normal" births (i.e. those located in the central part of the birth weight distribution), and that US racial disparities (African American versus European American) may be underestimated. Here these hypotheses are tested by examining the role of birth weight on racial disparities in infant mortality.</p> <p>Methods</p> <p>A two-component Covariate Density Defined mixture of logistic regressions model is used to decompose racial disparities, 1) into disparities due to "normal" versus "compromised" components of the birth cohort, and 2) further decompose these components into indirect effects, which are associated with birth weight, versus direct effects, which are independent of birth weight.</p> <p>Results</p> <p>The results indicate that a direct effect is responsible for the racial disparity in mortality among "normal" births. No indirect effect of birth weight is observed despite significant disparities in birth weight. Among "compromised" births, an indirect effect is responsible for the disparity, which is consistent with disparities in birth weight. However, there is also a direct effect among "compromised" births that reduces the racial disparity in mortality. This direct effect is responsible for the "pediatric paradox" and maybe due to differential fetal loss. Model-based adjustment for this effect indicates that racial disparities corrected for fetal loss could be as high as 3 or 4 fold. This estimate is higher than the observed racial disparities in infant mortality (2.1 for both sexes).</p> <p>Conclusions</p> <p>The results support the hypothesis that birth weight is not on the causal pathway to infant mortality among "normal" births, although birth weight could play a role among "compromised" births. The overall size of the US racial disparities in infant mortality maybe considerably underestimated in the observed data possibly due to racial disparities in fetal loss.</p

The SpikerBox: A Low Cost, Open-Source BioAmplifier for Increasing Public Participation in Neuroscience Inquiry

Although people are generally interested in how the brain functions, neuroscience education for the public is hampered by a lack of low cost and engaging teaching materials. To address this, we developed an open-source tool, the SpikerBox, which is appropriate for use in middle/high school educational programs and by amateurs. This device can be used in easy experiments in which students insert sewing pins into the leg of a cockroach, or other invertebrate, to amplify and listen to the electrical activity of neurons. With the cockroach leg preparation, students can hear and see (using a smartphone oscilloscope app we have developed) the dramatic changes in activity caused by touching the mechanosensitive barbs. Students can also experiment with other manipulations such as temperature, drugs, and microstimulation that affect the neural activity. We include teaching guides and other resources in the supplemental materials. These hands-on lessons with the SpikerBox have proven to be effective in teaching basic neuroscience

A Multi-Parameter, High-Content, High-Throughput Screening Platform to Identify Natural Compounds that Modulate Insulin and Pdx1 Expression

Diabetes is a devastating disease that is ultimately caused by the malfunction or loss of insulin-producing pancreatic beta-cells. Drugs capable of inducing the development of new beta-cells or improving the function or survival of existing beta-cells could conceivably cure this disease. We report a novel high-throughput screening platform that exploits multi-parameter high-content analysis to determine the effect of compounds on beta-cell survival, as well as the promoter activity of two key beta-cell genes, insulin and pdx1. Dispersed human pancreatic islets and MIN6 beta-cells were infected with a dual reporter lentivirus containing both eGFP driven by the insulin promoter and mRFP driven by the pdx1 promoter. B-score statistical transformation was used to correct systemic row and column biases. Using this approach and 5 replicate screens, we identified 7 extracts that reproducibly changed insulin and/or pdx1 promoter activity from a library of 1319 marine invertebrate extracts. The ability of compounds purified from these extracts to significantly modulate insulin mRNA levels was confirmed with real-time PCR. Insulin secretion was analyzed by RIA. Follow-up studies focused on two lead compounds, one that stimulates insulin gene expression and one that inhibits insulin gene expression. Thus, we demonstrate that multi-parameter, high-content screening can identify novel regulators of beta-cell gene expression, such as bivittoside D. This work represents an important step towards the development of drugs to increase insulin expression in diabetes and during in vitro differentiation of beta-cell replacements

Quantifying the extent to which index event biases influence large genetic association studies

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.As genetic association studies increase in size to 100,000s of individuals, subtle biases may influence conclusions. One possible bias is "index event bias" (IEB) that appears due to the stratification by, or enrichment for, disease status when testing associations between genetic variants and a disease-associated trait. We aimed to test the extent to which IEB influences some known trait associations in a range of study designs and provide a statistical framework for assessing future associations. Analysing data from 113,203 non-diabetic UK Biobank participants, we observed three (near TCF7L2, CDKN2AB and CDKAL1) overestimated (BMI-decreasing) and one (near MTNR1B) underestimated (BMI-increasing) associations among 11 type 2 diabetes risk alleles (at P  500,000 if the prevalence of those diseases differs by > 10% from the background population. In conclusion, IEB may result in false positive or negative genetic associations in very large studies stratified or strongly enriched for/against disease cases.H.Y., A.R.W. and T.M.F. are supported by the European Research Council grant: 323195; SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC. S.E.J. is funded by the Medical Research Council (grant: MR/M005070/1). M.A.T., M.N.W. and A.M. are supported by the Wellcome Trust Institutional Strategic Support Award (WT097835MF). R.M.F. is a Sir Henry Dale Fellow (Wellcome Trust and Royal Society grant: 104150/Z/14/Z). R.B. is funded by the Wellcome Trust and Royal Society grant: 104150/Z/14/Z. J.T. is funded by a Diabetes Research and Wellness Foundation Fellowship. Z.K. received financial support from the Leenaards Foundation, the Swiss Institute of Bioinformatics and the Swiss National Science Foundation (31003A-143914) and SystemsX.ch (39). The work of M.P.B was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award no. T32HL007779. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. E.R.P. holds a WT New investigator award 102820/Z/13/Z

Chapter 11: Challenges in and Principles for Conducting Systematic Reviews of Genetic Tests used as Predictive Indicators

In this paper, we discuss common challenges in and principles for conducting systematic reviews of genetic tests. The types of genetic tests discussed are those used to 1). determine risk or susceptibility in asymptomatic individuals; 2). reveal prognostic information to guide clinical management in those with a condition; or 3). predict response to treatments or environmental factors. This paper is not intended to provide comprehensive guidance on evaluating all genetic tests. Rather, it focuses on issues that have been of particular concern to analysts and stakeholders and on areas that are of particular relevance for the evaluation of studies of genetic tests. The key points include:The general principles that apply in evaluating genetic tests are similar to those for other prognostic or predictive tests, but there are differences in how the principles need to be applied or the degree to which certain issues are relevant.A clear definition of the clinical scenario and an analytic framework is important when evaluating any test, including genetic tests.Organizing frameworks and analytic frameworks are useful constructs for approaching the evaluation of genetic tests.In constructing an analytic framework for evaluating a genetic test, analysts should consider preanalytic, analytic, and postanalytic factors; such factors are useful when assessing analytic validity.Predictive genetic tests are generally characterized by a delayed time between testing and clinically important events.Finding published information on the analytic validity of some genetic tests may be difficult. Web sites (FDA or diagnostic companies) and gray literature may be important sources.In situations where clinical factors associated with risk are well characterized, comparative effectiveness reviews should assess the added value of using genetic testing along with known factors compared with using the known factors alone.For genome-wide association studies, reviewers should determine whether the association has been validated in multiple studies to minimize both potential confounding and publication bias. In addition, reviewers should note whether appropriate adjustments for multiple comparisons were used

Comparative genomics reveals functional transcriptional control sequences in the Prop1 gene

Mutations in PROP1 are a common genetic cause of multiple pituitary hormone deficiency (MPHD). We used a comparative genomics approach to predict the transcriptional regulatory domains of Prop1 and tested them in cell culture and mice. A BAC transgene containing Prop1 completely rescues the Prop1 mutant phenotype, demonstrating that the regulatory elements necessary for proper PROP1 transcription are contained within the BAC. We generated DNA sequences from the PROP1 genes in lemur, pig, and five different primate species. Comparison of these with available human and mouse PROP1 sequences identified three putative regulatory sequences that are highly conserved. These are located in the PROP1 promoter proximal region, within the first intron of PROP1, and downstream of PROP1. Each of the conserved elements elicited orientation-specific enhancer activity in the context of the Drosophila alcohol dehydrogenase minimal promoter in both heterologous and pituitary-derived cells lines. The intronic element is sufficient to confer dorsal expansion of the pituitary expression domain of a transgene, suggesting that this element is important for the normal spatial expression of endogenous Prop1 during pituitary development. This study illustrates the usefulness of a comparative genomics approach in the identification of regulatory elements that may be the site of mutations responsible for some cases of MPHD

Rare coding variants in ten genes confer substantial risk for schizophrenia

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, PPeer reviewe

Telomere length and bipolar disorder

Variation in telomere length is heritable and is currently considered a promising biomarker of susceptibility for neuropsychiatric disorders, particularly because of its association with memory function and hippocampal morphology. Here, we investigate telomere length in connection to familial risk and disease expression in bipolar disorder (BD). We used quantitative polymerase chain reactions and a telomere-sequence to single-copy-gene-sequence ratio method to determine telomere length in genomic DNA extracted from buccal smears from 63 patients with BD, 74 first-degree relatives (49 relatives had no lifetime psychopathology and 25 had a non-BD mood disorder) and 80 unrelated healthy individuals. Participants also underwent magnetic resonance imaging to determine hippocampal volumes and cognitive assessment to evaluate episodic memory using the verbal paired associates test. Telomere length was shorter in psychiatrically-well relatives (p=0.007) compared to unrelated healthy participants. Telomere length was also shorter in relatives (regardless of psychiatric status; p<0.01) and patients with BD not on lithium (p=0.02) compared to lithium-treated patients with BD. In the entire sample, telomere length was positively associated with left and right hippocampal volume and with delayed recall. This study provides evidence that shortened telomere length is associated with familial risk for BD. Lithium may have neuroprotective properties that require further investigation using prospective designs

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.Peer reviewe