Validation and application of health utilities index in Chinese subjects with down syndrome

Objectives: The objectives of the study were (1) to validate the Chinese version of Health Utilities Index (HUI-Ch); (2) to examine the Health-related Quality of Life (HRQoL) of Chinese subjects with Down syndrome (DS); and (3) to study the impact of chronic health conditions on HRQoL of Chinese with DS. Methods: The multiple choice questionnaire for scoring Health Utilities Index Mark 2 (HUI2) and Health Utilities Index Mark 3 (HUI3) was translated and validated. In addition to the HRQoL scores from HUI2 and HUI3, proxy-data on socio-demographics, and 10 common chronic health conditions for people with DS were collected and analyzed. Data analysis involves multiple imputation and multiple regression analysis to predict variations in HRQoL in relation to different factors. Lastly, a gradient interval was constructed on the number of chronic health conditions in relation to HRQoL. Results: HUI-Ch was validated according to standard guidelines. People with DS were found to have a lower HRQoL as compared to the general population, with the majority categorized as moderate or severe on the scale. Behavioral and hearing problems on HUI2, and hearing problems on HUI3 were found to be statistically significant predictors of a lower HRQoL score. A significant gradient relationship existed showing when the number of health problems increased, the HRQoL scores decreased. Conclusions: HUI-Ch is a valid instrument to assess HRQoL. It can have broad application in Chinese subjects with DS including the study of the impact of different chronic health conditions on their quality of life. The quantifiable nature of HUI-Ch will facilitate longitudinal study on the well-being of subjects with DS and evaluation of effectiveness of intervention programs in the near future

Discovery and Annotation of Functional Chromatin Signatures in the Human Genome

Transcriptional regulation in human cells is a complex process involving a multitude of regulatory elements encoded by the genome. Recent studies have shown that distinct chromatin signatures mark a variety of functional genomic elements and that subtle variations of these signatures mark elements with different functions. To identify novel chromatin signatures in the human genome, we apply a de novo pattern-finding algorithm to genome-wide maps of histone modifications. We recover previously known chromatin signatures associated with promoters and enhancers. We also observe several chromatin signatures with strong enrichment of H3K36me3 marking exons. Closer examination reveals that H3K36me3 is found on well-positioned nucleosomes at exon 5′ ends, and that this modification is a global mark of exon expression that also correlates with alternative splicing. Additionally, we observe strong enrichment of H2BK5me1 and H4K20me1 at highly expressed exons near the 5′ end, in contrast to the opposite distribution of H3K36me3-marked exons. Finally, we also recover frequently occurring chromatin signatures displaying enrichment of repressive histone modifications. These signatures mark distinct repeat sequences and are associated with distinct modes of gene repression. Together, these results highlight the rich information embedded in the human epigenome and underscore its value in studying gene regulation

Efficiently identifying genome-wide changes with next-generation sequencing data

We propose a new and effective statistical framework for identifying genome-wide differential changes in epigenetic marks with ChIP-seq data or gene expression with mRNA-seq data, and we develop a new software tool EpiCenter that can efficiently perform data analysis. The key features of our framework are: (i) providing multiple normalization methods to achieve appropriate normalization under different scenarios, (ii) using a sequence of three statistical tests to eliminate background regions and to account for different sources of variation and (iii) allowing adjustment for multiple testing to control false discovery rate (FDR) or family-wise type I error. Our software EpiCenter can perform multiple analytic tasks including: (i) identifying genome-wide epigenetic changes or differentially expressed genes, (ii) finding transcription factor binding sites and (iii) converting multiple-sample sequencing data into a single read-count data matrix. By simulation, we show that our framework achieves a low FDR consistently over a broad range of read coverage and biological variation. Through two real examples, we demonstrate the effectiveness of our framework and the usages of our tool. In particular, we show that our novel and robust ‘parsimony’ normalization method is superior to the widely-used ‘tagRatio’ method. Our software EpiCenter is freely available to the public

ChromaSig: A Probabilistic Approach to Finding Common Chromatin Signatures in the Human Genome

Computational methods to identify functional genomic elements using genetic information have been very successful in determining gene structure and in identifying a handful of cis-regulatory elements. But the vast majority of regulatory elements have yet to be discovered, and it has become increasingly apparent that their discovery will not come from using genetic information alone. Recently, high-throughput technologies have enabled the creation of information-rich epigenetic maps, most notably for histone modifications. However, tools that search for functional elements using this epigenetic information have been lacking. Here, we describe an unsupervised learning method called ChromaSig to find, in an unbiased fashion, commonly occurring chromatin signatures in both tiling microarray and sequencing data. Applying this algorithm to nine chromatin marks across a 1% sampling of the human genome in HeLa cells, we recover eight clusters of distinct chromatin signatures, five of which correspond to known patterns associated with transcriptional promoters and enhancers. Interestingly, we observe that the distinct chromatin signatures found at enhancers mark distinct functional classes of enhancers in terms of transcription factor and coactivator binding. In addition, we identify three clusters of novel chromatin signatures that contain evolutionarily conserved sequences and potential cis-regulatory elements. Applying ChromaSig to a panel of 21 chromatin marks mapped genomewide by ChIP-Seq reveals 16 classes of genomic elements marked by distinct chromatin signatures. Interestingly, four classes containing enrichment for repressive histone modifications appear to be locally heterochromatic sites and are enriched in quickly evolving regions of the genome. The utility of this approach in uncovering novel, functionally significant genomic elements will aid future efforts of genome annotation via chromatin modifications

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning

Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which has been hampered by our inability to monitor serotonin release and transport with high spatial and temporal resolution. We developed and applied a binding-pocket redesign strategy, guided by machine learning, to create a high-performance, soluble, fluorescent serotonin sensor (iSeroSnFR), enabling optical detection of millisecond-scale serotonin transients. We demonstrate that iSeroSnFR can be used to detect serotonin release in freely behaving mice during fear conditioning, social interaction, and sleep/wake transitions. We also developed a robust assay of serotonin transporter function and modulation by drugs. We expect that both machine-learning-guided binding-pocket redesign and iSeroSnFR will have broad utility for the development of other sensors and in vitro and in vivo serotonin detection, respectively

Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome.

Eukaryotic gene transcription is accompanied by acetylation and methylation of nucleosomes near promoters, but the locations and roles of histone modifications elsewhere in the genome remain unclear. We determined the chromatin modification states in high resolution along 30 Mb of the human genome and found that active promoters are marked by trimethylation of Lys4 of histone H3 (H3K4), whereas enhancers are marked by monomethylation, but not trimethylation, of H3K4. We developed computational algorithms using these distinct chromatin signatures to identify new regulatory elements, predicting over 200 promoters and 400 enhancers within the 30-Mb region. This approach accurately predicted the location and function of independently identified regulatory elements with high sensitivity and specificity and uncovered a novel functional enhancer for the carnitine transporter SLC22A5 (OCTN2). Our results give insight into the connections between chromatin modifications and transcriptional regulatory activity and provide a new tool for the functional annotation of the human genome. Activation of eukaryotic gene transcription involves the coordination of a multitude of transcription factors and cofactors on regulatory DNA sequences such as promoters and enhancers and on the chromatin structure containing these elements 1-3 . Promoters are located at the 5¢ ends of genes immediately surrounding the transcriptional start site (TSS) and serve as the point of assembly of the transcriptional machinery and initiation of transcription 4 . Enhancers contribute to the activation of their target genes from positions upstream, downstream or within a target or neighboring gene Recent investigations using chromatin immunoprecipitation (ChIP) and microarray (ChIP-chip) experiments have described the chromatin architecture of transcriptional promoters in yeast, fly and mammalian systems 9 . In a manner largely conserved across species, active promoters are marked by acetylation of various residues of histones H3 and H4 and methylation of H3K4, particularly trimethylation of this residue. Nucleosome depletion is also a general characteristic of active promoters in yeast and flies, although this feature remains to be thoroughly examined in mammalian systems. Although some studies suggest that distal regulatory elements like enhancers may be marked by similar histone modification patterns 10-13 , the distinguishing chromatin features of promoters and enhancers have yet to be determined, hindering our understanding of a predictive histone code for different classes of regulatory elements. Here, we present high-resolution maps of multiple histone modifications and transcriptional regulators in 30 Mb of the human genome, demonstrating that active promoters and enhancers are associated with distinct chromatin signatures that can be used to predict these regulatory elements in the human genome. RESULTS Chromatin architecture and transcription factor localization We performed ChIP-chip analysis 14 to determine the chromatin architecture along 44 human loci selected by the ENCODE consortium as common targets for genomic analysis 15 , totaling 30 Mb

Histone Modifications at Human Enhancers Reflect Global Cell-Type-Specific Gene Expression

The human body is composed of diverse cell types with distinct functions. Although it is known that lineage specification depends on cell-specific gene expression, which in turn is driven by promoters, enhancers, insulators and other cis-regulatory DNA sequences for each gene1, 2, 3, the relative roles of these regulatory elements in this process are not clear. We have previously developed a chromatin-immunoprecipitation-based microarray method (ChIP-chip) to locate promoters, enhancers and insulators in the human genome4, 5, 6. Here we use the same approach to identify these elements in multiple cell types and investigate their roles in cell-type-specific gene expression. We observed that the chromatin state at promoters and CTCF-binding at insulators is largely invariant across diverse cell types. In contrast, enhancers are marked with highly cell-type-specific histone modification patterns, strongly correlate to cell-type-specific gene expression programs on a global scale, and are functionally active in a cell-type-specific manner. Our results define over 55,000 potential transcriptional enhancers in the human genome, significantly expanding the current catalogue of human enhancers and highlighting the role of these elements in cell-type-specific gene expression

Development and implementation of guidelines for the management of depression: a systematic review

Objective: To evaluate the development and implementation of clinical practice guidelines for the management of depression globally. Methods: We conducted a systematic review of existing guidelines for the management of depression in adults with major depressive or bipolar disorder. For each identified guideline, we assessed compliance with measures of guideline development quality (such as transparency in guideline development processes and funding, multidisciplinary author group composition, systematic review of comparative efficacy research) and implementation (such as quality indicators). We compared guidelines from low- and middle-income countries with those from high-income countries. Findings: We identified 82 national and 13 international clinical practice guidelines from 83 countries in 27 languages. Guideline development processes and funding sources were explicitly specified in a smaller proportion of guidelines from low- and middle-income countries (8/29; 28%) relative to high-income countries (35/58; 60%). Fewer guidelines (2/29; 7%) from low- and middle-income countries, relative to high-income countries (22/58; 38%), were authored by a multidisciplinary development group. A systematic review of comparative effectiveness was conducted in 31% (9/29) of low- and middle-income country guidelines versus 71% (41/58) of high-income country guidelines. Only 10% (3/29) of low- and middle-income country and 19% (11/58) of high-income country guidelines described plans to assess quality indicators or recommendation adherence. Conclusion: Globally, guideline implementation is inadequately planned, reported and measured. Narrowing disparities in the development and implementation of guidelines in low- and middle-income countries is a priority. Future guidelines should present strategies to implement recommendations and measure feasibility, cost-effectiveness and impact on health outcomes