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A new biophysical metric for interrogating the information content in human genome sequence variation: Proof of concept.

ABSTRACT: The 21st century emergence of genomic medicine is shifting the paradigm in biomedical science from the population phenotype to the individual genotype. In characterizing the biology of disease and health disparities in population genetics, human populations are often defined by the most common alleles in the group. This definition poses difficulties when categorizing individuals in the population who do not have the most common allele(s). Various epidemiological studies have shown an association between common genomic variation, such as single nucleotide polymorphisms (SNPs), and common diseases. We hypothesize that information encoded in the structure of SNP haploblock variation in the human leukocyte antigen-disease related (HLA-DR) region of the genome illumines molecular pathways and cellular mechanisms involved in the regulation of host adaptation to the environment. In this paper we describe the development and application of the normalized information content (NIC) as a novel metric based on SNP haploblock variation. The NIC facilitates translation of biochemical DNA sequence variation into a biophysical quantity derived from Boltzmann's canonical ensemble in statistical physics and used widely in information theory. Our normalization of this information metric allows for comparisons of unlike, or even unrelated, regions of the genome. We report here NIC values calculated for HLA-DR SNP haploblocks constructed by Haploview, a product of the International Haplotype Map Project. These haploblocks were scanned for potential regulatory elements using ConSite and miRBase, publicly available bioinformatics tools. We found that all of the haploblocks with statistically low NIC values contained putative transcription factor binding sites and microRNA motifs, suggesting correlation with genomic regulation. Thus, we were able to relate a mathematical measure of information content in HLA-DR SNP haploblocks to biologically relevant functional knowledge embedded in the structure of DNA sequence variation. We submit that NIC may be useful in analyzing the regulation of molecular pathways involved in host adaptation to environmental pathogens and in decoding the functional significance of common variation in the human genome.

SUBMITTER: Lindesay J

PROVIDER: S-EPMC3902476 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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A new biophysical metric for interrogating the information content in human genome sequence variation: Proof of concept.

Lindesay James J Mason Tshela E TE Ricks-Santi Luisel L Hercules William W Kurian Philip P Dunston Georgia M GM

Journal of computational biology and bioinformatics research 20120201 2

The 21<sup>st</sup> century emergence of genomic medicine is shifting the paradigm in biomedical science from the population phenotype to the individual genotype. In characterizing the biology of disease and health disparities in population genetics, human populations are often defined by the most common alleles in the group. This definition poses difficulties when categorizing individuals in the population who do not have the most common allele(s). Various epidemiological studies have shown an ...[more]

PMID: 24478921

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Project description:BackgroundCombinations of foods that provide suitable levels of nutrients and energy are required for optimum health. Currently, however, it is difficult to define numerically what are 'suitable levels'.ObjectiveTo develop new metrics based on energy considerations-the Nutrient Balance Concept (NBC)-for assessing overall nutrition quality when combining foods and meals.MethodThe NBC was developed using the USDA Food Composition Database (Release 27) and illustrated with their MyPlate 7-day sample menus for a 2000 calorie food pattern. The NBC concept is centered on three specific metrics for a given food, meal or diet-a Qualifying Index (QI), a Disqualifying Index (DI) and a Nutrient Balance (NB). The QI and DI were determined, respectively, from the content of 27 essential nutrients and 6 nutrients associated with negative health outcomes. The third metric, the Nutrient Balance (NB), was derived from the Qualifying Index (QI) and provided key information on the relative content of qualifying nutrients in the food. Because the Qualifying and Disqualifying Indices (QI and DI) were standardized to energy content, both become constants for a given food/meal/diet and a particular consumer age group, making it possible to develop algorithms for predicting nutrition quality when combining different foods.ResultsCombining different foods into composite meals and daily diets led to improved nutrition quality as seen by QI values closer to unity (indicating nutrient density was better equilibrated with energy density), DI values below 1.0 (denoting an acceptable level of consumption of disqualifying nutrients) and increased NB values (signifying complementarity of foods and better provision of qualifying nutrients).ConclusionThe Nutrient Balance Concept (NBC) represents a new approach to nutrient profiling and the first step in the progression from the nutrient evaluation of individual foods to that of multiple foods in the context of meals and total diets.

Project description:Identifying the complete set of functional elements within the human genome would be a windfall for multiple areas of biological research including medicine, molecular biology, and evolution. Complete knowledge of function would aid in the prioritization of loci when searching for the genetic bases of disease or adaptive phenotypes. Because mutations that disrupt function are disfavored by natural selection, purifying selection leaves a detectable signature within functional elements; accordingly, this signal has been exploited for over a decade through the use of genomic comparisons of distantly related species. While this is so, the functional complement of the genome changes extensively across time and between lineages; therefore, evidence of the current action of purifying selection in humans is essential. Because the removal of deleterious mutations by natural selection also reduces within-species genetic diversity within functional loci, dense population genetic data have the potential to reveal genomic elements that are currently functional. Here, we assess the potential of this approach by examining an ultradeep sample of human mitochondrial genomes (n = 16,411). We show that the high density of polymorphism in this data set precisely delineates regions experiencing purifying selection. Furthermore, we show that the number of segregating alleles at a site is strongly correlated with its divergence across species after accounting for known mutational biases in human mitochondrial DNA (ρ = 0.51; P < 2.2 × 10(-16)). These two measures track one another at a remarkably fine scale across many loci-a correlation that is purely the result of natural selection. Our results demonstrate that genetic variation has the potential to reveal with surprising precision which regions in the genome are currently performing important functions and likely to have deleterious fitness effects when mutated. As more complete human genomes are sequenced, similar power to reveal purifying selection may be achievable in the human nuclear genome.

Project description:BackgroundPrevious work has indicated that post-traumatic stress disorder (PTSD) symptoms, measured by the Clinician-Administered PTSD Scale (CAPS) within 60 days of trauma exposure, can reliably produce likelihood estimates of chronic PTSD among trauma survivors admitted to acute care centers. Administering the CAPS is burdensome, requires skilled professionals, and relies on symptoms that are not fully expressed upon acute care admission. Predicting chronic PTSD from peritraumatic responses, which are obtainable upon acute care admission, has yielded conflicting results, hence the rationale for a stepwise screening-and-prediction practice. This work explores the ability of peritraumatic responses to produce risk likelihood estimates of early CAPS-based PTSD symptoms indicative of chronic PTSD risk. It specifically evaluates the Peritraumatic Dissociative Experiences Questionnaire (PDEQ) as a risk-likelihood estimator.MethodsWe used individual participant data (IPD) from five acute care studies that used both the PDEQ and the CAPS (n = 647). Logistic regression calculated the probability of having CAPS scores ≥ 40 between 30 and 60 days after trauma exposure across the range of initial PDEQ scores, and evaluated the added contribution of age, sex, trauma type, and prior trauma exposure. Brier scores, area under the receiver-operating characteristic curve (AUC), and the mean slope of the calibration line evaluated the accuracy and precision of the predicted probabilities.ResultsTwenty percent of the sample had CAPS ≥ 40. PDEQ severity significantly predicted having CAPS ≥ 40 symptoms (p < 0.001). Incremental PDEQ scores produced a reliable estimator of CAPS ≥ 40 likelihood. An individual risk estimation tool incorporating PDEQ and other significant risk indicators is provided.ConclusionPeritraumatic reactions, measured here by the PDEQ, can reliably quantify the likelihood of acute PTSD symptoms predictive of chronic PTSD and requiring clinical attention. Using them as a screener in a stepwise chronic PTSD prediction strategy may reduce the burden of later CAPS-based assessments. Other peritraumatic metrics may perform similarly and their use requires similar validation.Trial registrationJerusalem Trauma Outreach and Prevention Study (J-TOPS): NCT00146900.

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A new biophysical metric for interrogating the information content in human genome sequence variation: Proof of concept.

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A new biophysical metric for interrogating the information content in human genome sequence variation: Proof of concept.

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