Genome Medicine - Latest Articles

A whole genome association study of mother-to-child transmission of HIV in Malawi

Bonnie Joubert — 2010-03-01T00:00:00Z

Background: More than 300,000 children are newly infected with HIV each year, predominantly through mother-to-child transmission (HIV MTCT). Identification of host genetic traits associated with transmission may more clearly explain the mechanisms of HIV MTCT and further the development of a vaccine to protect infants from infection. Associations between transmission and a selection of genes or single nucleotide polymorphisms (SNP)s may give an incomplete picture of HIV MTCT etiology. Thus, this study employed a genome wide association approach to identify novel variants associated with HIV MTCT. Methods: We conducted a nested case-control study of HIV MTCT using infants of HIV(+) mothers, drawn from a cohort study of malaria and HIV in pregnancy in Blantyre, Malawi. Whole genome scans (650,000 SNPs genotyped using Illumina genotyping assays) were obtained for each infant. Logistic regression was used to evaluate the association between each SNP and HIV MTCT. Results: Genotype results were available for 100 HIV(+) infants (at birth, 6, or 12 weeks) and 126 HIV(-) infants (at birth, 6, and 12 weeks). We identified 9 SNPs within 6 genes with a p-value<5x10-5 associated with the risk of transmission, in either unadjusted or adjusted by maternal HIV viral load analyses. Carriers of the rs8069770 variant allele were associated with a lower risk of HIV MTCT (Odds Ratio=0.27, 95% Confidence Interval=0.14, 0.51), where rs8069770 is located within HS3ST3A1, a gene involved in heparan sulfate biosynthesis. Interesting associations for SNPs located within or near genes involved in pregnancy and development, innate immunological response, or HIV protein interactions were also observed. Conclusions: This study used a genome wide approach to identify novel variants associated with the risk of HIV MTCT in order to gain new insights into HIV MTCT etiology. Replication of this work using a larger sample size will help us to differentiate true positive findings.

Collaboratively charting the gene-to-phenotype network of human congenital heart defects

Roland Barriot — 2010-03-01T00:00:00Z

Background: How to efficiently integrate the daily practice of molecular biologists, geneticists, and clinicians with the emerging computational strategies from systems biology is still much of an open question.DescriptionWe built on the recent advances in Wiki-based technologies to develop a collaborative knowledge base and gene prioritization portal aimed at mapping genes and genomic regions, and untangling their relations with corresponding human phenotypes, congenital heart defects (CHDs). This portal is not only an evolving community repository of current knowledge on the genetic basis of CHDs, but also a collaborative environment for the study of candidate genes potentially implicated in CHDs - in particular by integrating recent strategies for the statistical prioritization of candidate genes. It thus serves and connects the broad community that is facing CHDs, ranging from the pediatric cardiologist and clinical geneticist to the basic investigator of cardiogenesis. Conclusions: This study describes the first specialized portal to collaboratively annotate and analyze gene-phenotype networks. Of broad interest to the biological community, we argue that such portals will play a significant role in systems biology studies of numerous complex biological processes.CHDWiki is accessible at http://www.esat.kuleuven.be/~bioiuser/chdwiki

Coping with antibiotic resistance: contributions from genomics

Gian Maria Rossolini — 2010-02-25T00:00:00Z

Antibiotic resistance is a public health issue of global dimensions with a significant impact on morbidity, mortality and healthcare-associated costs. The problem has recently been worsened by the steady increase in multiresistant strains and by the restriction of antibiotic discovery and development programs. Recent advances in the field of bacterial genomics will further current knowledge on antibiotic resistance and help to tackle the problem. Bacterial genomics and transcriptomics can inform our understanding of resistance mechanisms, and comparative genomic analysis can provide relevant information on the evolution of resistant strains and on resistance genes and cognate genetic elements. Moreover, bacterial genomics, including functional and structural genomics, is also proving to be instrumental in the identification of new targets, which is a crucial step in new antibiotic discovery programs.

Developmental origins of health and disease: Reducing the burden of chronic disease in the next generation

Peter Gluckman — 2010-02-24T00:00:00Z

Despite a wealth of underpinning experimental support, there has been considerable resistance to the concept that environmental factors acting early in life (usually in fetal life) have profound effects on vulnerability to disease later in life, often in adulthood. This has resulted in an unwillingness among public health decision makers to implement relatively simple approaches, based upon an understanding of developmental plasticity and intergenerational influences, to reducing the burden of disease particularly in low socioeconomic groups.

Pharmacogenomics and personalized medicine: lost in translation?

Jean-Sebastien Hulot — 2010-02-22T00:00:00Z

A report on the Joint Cold Spring Harbor/Wellcome Trust Conference 'Pharmacogenomics and Personalized Medicine', Hinxton, UK, 12-15 September 2009.

Non-coding RNAs: a key to future personalized molecular therapy?

Marco Galasso — 2010-02-18T00:00:00Z

Continual discoveries on non-coding RNA (ncRNA) have changed the landscape of human genetics and molecular biology. Over the past ten years it has become clear that ncRNAs are involved in many physiological cellular processes and contribute to molecular alterations in pathological conditions. Several classes of ncRNAs, such as small interfering RNAs, microRNAs, PIWI-associated RNAs, small nucleolar RNAs and transcribed ultra-conserved regions, are implicated in cancer, heart diseases, immune disorders, and neurodegenerative and metabolic diseases. ncRNAs have a fundamental role in gene regulation and, given their molecular nature, they are thus both emerging therapeutic targets and innovative intervention tools. Next-generation sequencing technologies (for example SOLiD or Genome Analyzer) are having a substantial role in the high-throughput detection of ncRNAs. Tools for non-invasive diagnostics now include monitoring body fluid concentrations of ncRNAs, and new clinical opportunities include silencing and inhibition of ncRNAs or their replacement and re-activation. Here we review recent progress on our understanding of the biological functions of human ncRNAs and their clinical potential.

Inversion variants in the human genome: role in disease and genome architecture

Lars Feuk — 2010-02-12T00:00:00Z

Significant advances have been made over the past 5 years in mapping and characterizing structural variation in the human genome. Despite this progress, our understanding of inversion variants is still very restricted. While unbalanced variants such as copy number variations can be mapped using array-based approaches, strategies for characterization of inversion variants have been limited and underdeveloped. Traditional cytogenetic approaches have long been able to identify microscopic inversion events, but discovery of submicroscopic events has remained elusive and largely ignored. With the advent of paired-end sequencing approaches, it is now possible to map inversions across the human genome. Based on the paired-end sequencing studies published to date, it is now feasible to make a first map of inversions across the human genome and to use this map to explore the characteristics and distribution of this form of variation. The current map of inversions indicates that many remain to be identified, especially in the smaller size ranges. This review provides an overview of the current knowledge about human inversions and their contribution to human phenotypes. Further characterization of inversions should be considered as an important step towards a deeper understanding of human variation and genome dynamics.

Multi-locus models of genetic risk of disease

Naomi Wray — 2010-02-02T00:00:00Z

Background: Evidence for genetic contribution to complex diseases is described by recurrence risks to relatives of diseased individuals. Genome-wide association studies allow a description of the genetics of the same diseases in terms of risk loci, their effects and allele frequencies. To reconcile the two descriptions requires a model of how risks from individual loci combine to determine an individual's overall risk. Methods: We derive predictions of risk to relatives from risks at individual loci under a number of models and compare them with published data on disease risk. Results: The model in which risks are multiplicative on the risk scale model is known to imply equality between the recurrence risk to monozygotic twins and the square of the recurrence risk to sibs, a relationship often not observed, especially for low prevalence diseases. We show that this theoretical equality is achieved by allowing impossible probabilities of disease. Other models, in which probabilities of disease are constrained to a maximum of one, generate results more consistent with empirical estimates for a range of diseases. Conclusion: The unconstrained multiplicative model, often used in theoretical studies because of its mathematical tractability, is not a realistic model. We find three models, the constrained multiplicative, Odds (or Logit) and Probit (or liability threshold) models, all fit the data on risk to relatives. Currently, in practice it would be difficult to differentiate between these models, but this may become possible if genetic variants that explain the majority of the genetic variance are identified.

Integration of microRNA changes in vivo identifies novel molecular features of muscle insulin resistance in Type 2 Diabetes

Iain Gallagher — 2010-02-01T00:00:00Z

Background: Skeletal muscle insulin resistance (IR) is considered a critical component of type II diabetes, yet to date IR has evaded characterization at the global gene expression level in humans. MicroRNAs (miRNAs) are considered fine-scale rheostats of protein-coding gene product abundance. The relative importance and mode of action of miRNAs in human complex diseases remains to be fully elucidated. We produce a global map of coding and non-coding RNAs in human muscle IR with the aim of identifying novel disease biomarkers. Methods: We profiled >47,000 mRNA sequences and >500 human miRNAs using gene-chips and 118 subjects (n = 71 patients versus n = 47 controls). A tissue-specific gene-ranking system was developed to stratify thousands of miRNA target-genes, removing false positives, yielding a weighted inhibitor score, which integrated the net impact of both up- and down-regulated miRNAs. Both informatic and protein detection validation was used to verify the predictions of in vivo changes. Results: The muscle mRNA transcriptome is invariant with respect to insulin or glucose homeostasis. In contrast, a third of miRNAs detected in muscle were altered in disease (n = 62), many changing prior to the onset of clinical diabetes. The novel ranking metric identified six canonical pathways with proven links to metabolic disease while the control data demonstrated no enrichment. The Benjamini-Hochberg adjusted Gene Ontology profile of the highest ranked targets was metabolic (P < 7.4 × 10-8), post-translational modification (P < 9.7 × 10-5) and developmental (P < 1.3 × 10-6) processes. Protein profiling of six development-related genes validated the predictions. Brain-derived neurotrophic factor protein was detectable only in muscle satellite cells and was increased in diabetes patients compared with controls, consistent with the observation that global miRNA changes were opposite from those found during myogenic differentiation. Conclusions: We provide evidence that IR in humans may be related to coordinated changes in multiple microRNAs, which act to target relevant signaling pathways. It would appear that miRNAs can produce marked changes in target protein abundance in vivo by working in a combinatorial manner. Thus, miRNA detection represents a new molecular biomarker strategy for insulin resistance, where micrograms of patient material is needed to monitor efficacy during drug or life-style interventions.

Downstream EWS/FLI1 - upstream Ewing's sarcoma

Heinrich Kovar — 2010-01-28T00:00:00Z

Ewing's sarcoma family tumors are a good example of how genome research has advanced our understanding of the molecular pathogenesis of an otherwise enigmatic disease. This group of embryonal bone tumors is characterized by the expression of a chimeric ETS-family oncogene, predominantly EWS/FLI1. There is now convincing evidence for a mesenchymal descent from an early pluripotent progenitor. EWS/FLI1 has been shown to drive proliferation of Ewing's sarcoma cells and block most of the differentiation potential except for a partial neural gene expression program. The EWS/FLI1 fusion protein acts mainly as a gene activator, directly interacting with chromatin at two kinds of binding site: distant enhancers enriched in GGAA microsatellites, and proximal promoters containing classical ETS-binding motifs and recognition motifs for other transcription factors. EWS/FLI1 also represses a large number of genes, mainly indirectly, presumably by altering microRNA expression and epigenetic mechanisms, and potentially affecting post-transcriptional gene regulation. Modulation of EWS/FLI1 expression is not only a desirable therapeutic goal, but may also occur under physiological conditions and influence the course of the disease.