BioMed Central Blog
Global lipid profiling provides clues to schizophrenia pathogenesis
Recent research published in Genome Medicine presents a comprehensive, global view of lipid abnormalities associated with schizophrenia, providing new pathophysiological insights into the disorder.
Following on from their earlier work published in Genome Medicine, which reported metabolites that differentiate schizophrenia from related disorders, Matej Orešič and colleagues from the VTT Technical Research Centre of Finland used metabolomics (a high-throughput method for detecting small metabolites) to determine the lipid profile of people with schizophrenia. In psychiatric research, several theories have been proposed to explain how brain function may be altered by changes in lipid composition, and this study sought to understand which specific pathways are affected in schizophrenia.
The group analyzed the lipid content of serum samples taken from monozygotic twins that are discordant for schizophrenia i.e. only one twin in each pair is affected. The advantage of this unique study design is that discordant twins are an ideal population for investigating the contribution of genetic factors to disease etiology. Age and gender matched healthy twin pairs were included as controls, and neurocognitive and magnetic resonance image data were available for selected twins.
Compared with healthy controls, individuals with schizophrenia had higher triglyceride levels and showed signs of insulin resistance, in line with earlier reports. However, the patients’ unaffected co-twins were also found to be insulin resistant, providing new evidence that this could be an inherited trait associated with predisposition to schizophrenia. Affected twins also had lower levels of phospholipid derivatives called lysophosphatidylcholines (lysoPCs). This change, which was not observed in healthy co-twins or controls, correlated with decreased cognitive speed. Because lysoPCs are involved in blood-brain barrier transport of polyunsaturated fatty acids, the authors conclude that a drop in their levels may be responsible for changes in neurotransmission and weaker cognitive performance. They also propose that lysoPC deficiency could make schizophrenia patients more susceptible to infections. These findings pave the way for further research into the role of lysoPCs in schizophrenia.
The mechanistic insights reported by Orešič and colleagues may be useful for the discovery of new drug targets for schizophrenia. In addition, the work demonstrates how a discordant twin study design can successfully uncouple genetic and environmental factors, allowing disease-specific inherited traits to be accurately defined.
Posted by Paraminder Dhillon at 13:49 Comments (0)
The December issue of Genome Medicine highlights the growing potential of genomics research for the development of personalized medicine, particularly for improving the effectiveness of anticancer therapeutics.
In a Research article, Matthias Schwab and colleagues demonstrate for the first time that decreased expression of an organic cation transporter SLC22A1 in hepatocellular carcinoma (liver cancer) correlates with increased methylation of the encoding gene. Their findings suggest that aberrant DNA methylation could be used for early detection of the disease, and that demethylating agents could be used for treatment. 
Continuing the theme of cancer therapy, Ram Ganapathi and Ronald Bukowski discuss recent progress in predicting response or toxicity following sunitinib treatment in patients with renal cell cancer, and make suggestions for improving future trials.
In a report on the 2011 Wellcome Trust Pharmacogenomics and Personalized Medicine meeting, Mia Wadelius and Ana Alfirevic highlight other examples of pharmacogenomics research and its increasing presence in the clinic. This report has already been highly accessed, emphasizing the growing interest in this area.
The importance of post-genomic technologies is described in a Research Highlight from Frank Kooy and colleagues, which focuses on a novel metabolomics approach to understanding Fragile X syndrome. Our upcoming special issue on “Disease Metabolomics” will expand on this theme and provide insights from experts in this field. 
The issue wraps up with two Reviews on vastly different areas of research. The first, from Leonard Zon and colleagues, discusses recent advances in hematopoiesis research that are facilitated by the zebrafish model.
Finally, Melanie Myers addresses the important issue of direct-to-consumer (DTC) genetic testing and advertising in terms of the impact on health care providers.
Genome Medicine wishes you a happy new year and looks forward to bringing you the best in genomic medicine in 2012. Look out for our upcoming Editorial to read our Section Editors’ views on how the field had changed over the past year.
Posted by Paraminder Dhillon at 15:17 Comments (0)
DNA methylation of drug transporter gene might explain chemoresistance in liver cancer
Hepatocellular carcinoma is the third highest cause of cancer-related
death world-wide. Although several treatments are available – and many more are
undergoing clinical trials – drug resistance is a problem in some cases.
In the latest issue of Genome Medicine, Matthias Schwab and colleagues show for the first time that there is a link between the level of expression of the chemotherapy drug transporter SLC22A and DNA methylation. This finding might explain reduced drug responses in liver cancer and provide a new approach for treating patients.
The team looked at the methylation patterns in the 5' end of
three genes encoding organic cation transporters (SLC22A1, SLC22A2 and SLC22A3)
in liver samples taken from people with hepatocellular carcinoma and compared
them with normal livers. A
state-of-the-art mass spectrometry approach was used to examine DNA
methylation.
They found that decreased expression of SLC22A1 in hepatocellular carcinoma correlated with increased methylation of the SLC22A1 gene, and suggests that SLC22A1 is epigenetically regulated.
The good news is that epigenetic modifications are reversible and so pretreatment with a chemical to reduce methylation might result in improved chemotherapy.
Posted by Maria Hodges at 13:53 Comments (0)
November highlights from Genome Medicine: miRNA as a biomarker, RNA-seq, diabetes and more
November’s
issue of Genome Medicine reflects the
excitement in the field about the potential for RNA to act as a biomarker for
disease and to help researchers unravel the underlying disease mechanism.
MicroRNAs, which
are short RNAs of around 22 nucleotides, are attracting a lot of interest for
detecting and predicting the outcome of a disease. In a Research Highlight,
Florian Kuchenbauer and colleagues reflect on the recent finding that microRNAs
are expressed at different levels in blood in different diseases, which could
lead to blood-based diagnosis of disease. This issue also features a Research
Article by Rotem Ben-Hamo and Sol Efroni, which indicates a role for
microRNA hsa-miR-9, along with the p38 network, in predicting the prognosis of patients with the brain cancer
glioblastoma multiforme (see blog to find out more).
The other Research Highlight this month examines a new assay, termed CaptureSeq, that enriches low-level RNA transcripts for high-throughput RNA sequencing (RNA-Seq).
Recently, Genome Medicine has highlighted the increasing clinical impact of pharmacogenomic research, and in a Review Article by Jose Florez and Chunmei Huang the authors look at insights emerging from the pharmacogenetic and pharmacogenomic studies of type 2 diabetes.
Stuart Orkin, Guest Editor of our Focus on Stem Cells, and Jonghwan Kim have provided a Review on embryonic stem cell-specific
signatures in cancer.
Meeting
reports in the journal are proving to be popular, and this month is no
exception. Have a look at the Report of the Wellcome Trust meeting on Epigenomics of common disease and the Cold Spring Harbor Laboratory Report on Personal Genomes.
If you missed last month’s issue, you can look at it here. Elad Ziv and colleagues’ Research Article attracted a lot of interest, as the first report that doctors do change prescriptions for patients with breast cancer when they receive genotyping information. David Gurwitz and Jeantine Lunshof discuss this study and the implications for personalized medicine in an associated Research Highlight.
Other highly accessed articles from last month include Alan Wright’s Report on the Wellcome Trust conference on the Genomics of Common Diseases, Huck-Hui Ng’s review article on transcriptomic analysis of stem cells, and Wyeth Wasserman’s Review of the methods and software for predicting functional variation within the cis-regulatory sequences.
Posted by Maria Hodges at 16:57 Comments (0)
A transcription network at the core of brain cancer
Research published this week in Genome Medicine provides new insights
into the molecular pathways underlying brain cancer (glioblastoma multiforme). Sol
Efroni and Rotem Ben-Hamo from Bar IIan University in Israel analyzed gene
expression and clinical data for a large number of patients, with the aim of
identifying prognostic biomarkers and new therapeutic targets.
Glioblastoma multiforme is a common, aggressive form of brain cancer associated with extremely low survival rates. The disease is usually fatal even following therapy, highlighting the need for early diagnosis and the development of more effective drug regimes. In this study, Efroni and Ben-Hamo applied a series of computational algorithms to five independent microarray datasets to identify gene expression networks that correlate with poor prognosis. As part of their analysis, data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) database and The National Cancer Institute’s Pathway Interaction Database (PID) were merged, representing a uniquely powerful “systems biology” approach to biomarker discovery.
This integrated approach revealed that the expression of one pathway, the p38/MAPK transcription network, significantly affiliates with poor survival. This network was shown to be regulated by a microRNA, hsa-miR-9, implicating another important biomarker for the disease. Interestingly, analysis of DrugBank data showed that patients who had received drugs targeting the p38/MAPK pathway displayed higher survival rates compared with patients who had been treated with other drugs. These results suggest that the p38/MAPK network is critical in glioblastoma multiforme progression and should form the focus of future clinical studies of the disease.
Posted by Paraminder Dhillon at 10:01 Comments (0)
Genome Medicine workshop at 7th Annual Meeting of Asian Epigenome Alliance
The Editors
of Genome Medicine are delighted to announce a Workshop on the
Epigenetics/Epigenomics of Disease to be held as part of the 7th Annual
Meeting of the Asian Epigenome Alliance/3rd Shanghai International
Conference of Epigenetics and Disease.
The meeting will take place in Shanghai on 19-22 April 2012. During this three-day conference, 48 leading scientists from around the world will highlight the exceptional advances in the field.
This meeting has been organized by Genome Medicine’s editorial board member Jingde Zhu of Shanghai Cancer Institute/Renji Hospital and Lin He from Shanghai Fudan University, in conjunction with Rebecca Furlong, the Editor of Genome Medicine.
The workshop with Genome Medicine will have three sessions:
Genome Medicine day
Cancer epigenetics
and epigenomics
Epigenomics and autoimmune disease and asthma
Epigenomics and in the metabolic and psychiatric disorders
Speakers for the workshop include Esteban Ballestar, Jingde Zhu and Bin-Tean Teh.
The sessions for the other two days include:
Chemistry and biology of the epigenetic signals and key players
Epigenetic(-omic) perspectives of the complex biological systems
High order chromatin structures in the complex biological system
Towards the epigenome reference maps: New conceptual and technological
breakthrough
Non-coding RNAs in development and disease
The Asian Epigenome Alliance was launched in 2003 to promote epigenetic and epigenomic research in the region.
For more information, go to the website:http://www.bioon.com/z/shanghaiepigeneticssymposium201204/index.html.
Posted by Maria Hodges at 16:38 Comments (0)
Genome Medicine announces 'Disease metabolomics' special issue
Next year Genome Medicine will publish a special issue focusing on disease metabolomics. This issue will highlight the rapid advances that have been made in the
prediction, detection, understanding and monitoring of human disease by
small-metabolite profiling. The issue will be guest edited by Tim Veenstra (NCI Frederick).
The publication of these articles will be coordinated with a series of commissioned reviews and opinions written by leaders in the field including:
Mika Ala-Korpela (University of Oulu, Finland)
Jeremy Nicholson (Imperial College London, UK)
Julian Griffin (Cambridge
University, UK)
Jerzy Adamski (Helmholtz Zentrum München, Germany)
Oliver
Fiehn (University of California Davis, USA).
The editors of Genome Medicine are now accepting submissions of research, method, database and software manuscripts for this special issue. We encourage the submission of manuscripts employing small-molecule metabolite profiling in the study of human health and disease, as well as technological and software developments in this field. We welcome studies that combine metabolomic approaches with other strategies.
The deadline for submission is 31st December 2011 and if you would like to submit your manuscript for consideration, please visit our submission page for further instructions.
Update: The deadline for submissions has been extended by popular demand to Friday 13th January, 2012.
For more information please email editorial@genomemedicine.com.
Posted by Maria Hodges at 15:39 Comments (0)
Data sharing: lessons from the Wellcome Trust Sanger Institute
Sharing of scientific data has many benefits. It boosts research, speeds
up translation and helps ensure that good practice is maintained. The teams that
generate the data are rewarded too: studies show that sharing data increases
citation rates.
The Wellcome Trust Sanger Institute in the UK, a key player in the Human Genome Project, has often led the way in this area, and in the latest issue of Genome Medicine, Tim Hubbard and Stephanie Dyke from the Wellcome Trust Sanger Institute explain how they developed and implemented the Institute’s policy.
The Human Genome Project was groundbreaking in many ways, one of which was the decision, known as the “Bermuda Agreement” or “Bermuda Principles”, to release data as soon as possible and well ahead of publication. Over the years, early data sharing became established as an import aspect of genomic research.
The success
of the Human Genome Project led to the launch of many new initiatives and
studies based on genomic science and different types of data. In addition, more and
more human data were used and this had implications for confidentiality. A consensus was reached around 2006-2007 that
the way forward was to share data in a managed way that limited access to the
data for approved purposes. In recognition of this, the Wellcome Trust Sanger
Institute began consulting on its own data-sharing policy.
Tim Hubbard and colleagues approached the task by breaking it into three steps: guidance, facilitation and oversight. The aim of the guidance part was to understand the types of data being generated, the quality required to be useful to colleagues and the timelines involved. During the facilitation stage, the barriers to sharing - technical (such as the time required to get the data in the correct format) and concerning credit for the work – were addressed.
The final
step required was oversight; a way of monitoring data sharing was needed and a
governance body, the data-sharing working group, was established.
As the field of genomic medicine moves on, probably with the integration of electronic health records with genetic data, policies for data sharing will evolve and need to be updated. The three steps followed by the Wellcome Trust Sanger Institute are likely to provide a framework for other institutes implementing their own policy.
Posted by Maria Hodges at 13:43 Comments (0)
Tracking down cancers of unknown primary origin
In some cases of cancer, the major challenge is to identify
the site at which the cancer initially arose. A cancer of unknown primary
origin (CUP) refers to a disorder in which the location of the primary tumor
remains a mystery, even after routine diagnostic tests and biopsy. Not knowing
the primary source of a cancer can setback the development of an effective
treatment plan for the patient and reduce their overall chance of survival.
This week in Genome Medicine, Olli
Kallioniemi and colleagues at the University of Helsinki present an improved
method for pinpointing the tissue origin of a primary tumor, using gene expression data. Their method could
improve the accuracy of diagnosis and pave the way for tailored anti-cancer
therapy in CUP patients.
A number of methods for predicting the site of tumor origin have been described, and most of these compare the gene expression profile of the CUP sample with a “reference set” of tumor-specific hallmarks. These conventional approaches rely on an a priori defined set of genes, limiting the adaptability of the method to emerging information about specific cancers. The method described by Kallioniemi and colleagues, wAGEP (weighted Alignment of Gene Expression Profiles) can be adapted to any reference dataset, allowing it to be continually optimized as new tumor expression data becomes available. As well as being flexible, wAGEP proved to be highly accurate in classifying tumor samples according to tissue origin.
Another key advantage of wAGEP is that it can be used to investigate a CUP case on a gene-by-gene level, so provides information about the individual genes involved in initiating the cancer and also driving its spread to different tissue types (metastasis). Every cancer is unique and its evolution can be multifaceted, but by defining some of the systematic changes involved, novel molecular predictors could be revealed.
The method described is accurate, scalable and enables gene-by-gene analysis of cancers of unknown primary origin. Application of wAGEP in a clinical setting could allow the rapid diagnosis of unclassified cancers and implementation of personalized treatment regimes.
Posted by Paraminder Dhillon at 16:23 Comments (0)
An answer to the problem of non-communicable diseases?
Every year non-communicable diseases (such as cancer, heart disease and
diabetes) kill 36 million people worldwide, a quarter of whom die
before the age of 60. This week’s high-level United Nations meeting tackled this issue. In
anticipation of this meeting, many prominent scientists came together to write
a statement, published in Genome
Medicine, about the role of systems medicine in the prevention and
treatment of non-communicable diseases.
Systems medicine can be thought of as a
patient-centered holistic approach that combines medical information with wider
knowledge about health and disease such as the effects of human genetics,
environment and behavior. The team proposed a grand vision based around
the four ‘p’s - predictive, preventative, personalized and participatory - medicine.
Information and communication technologies are a vital element of this proposal, but so too are primary healthcare providers, who are able to look at a patient as a whole person. This is important because diseases appear to be somehow linked; that is, people with a non-communicable disease tend to suffer from two or more of them.
In response, Wylie Burke, also writing in Genome Medicine, acknowledged the potential of this approach but
emphasized that progress will not be made without tackling social issues such
as poverty, bad housing and restricted access to education and
employment.
In all probability both approaches are likely to go hand in hand. Systems medicine will help untangle the complex relationships between lifestyle and disease, and will pinpoint opportunities for prevention. But without a drive towards better public health, the number of deaths from non-communicable diseases will continue to increase.
Posted by Maria Hodges at 16:57 Comments (0)
Hepatitis C treatment gets personal: predicting drug response
Around 3% of the world’s population is infected with hepatitis C virus (HCV), which affects the liver. The current standard-of-care therapy is not effective in the majority of genotype 1 viral cases and more serious, chronic diseases of the liver can result. Recently published in Genome Medicine, David Booth and colleagues from the Universities of Sydney and Melbourne use a powerful sequencing approach to identify DNA variants that can predict failure to respond to hepatitis C therapy. Their findings could help to optimize treatment options for many hepatitis C patients.
The recommended treatment for HCV infection is a 48-week course of pegylated interferon alpha and ribavirin, which clears the infection in less than 50% of genotype 1 cases. Over the past few years, researchers have performed genome-wide association studies (GWAS) to identify genetic factors underlying the lack of viral clearance in most patients. These analyses revealed that single nucleotide changes, or polymorphisms, in the IL28B gene region can predict non-response to treatment. In their latest study, David Booth and colleagues used a high-throughput “massively parallel sequencing” approach to identify new, highly sensitive genetic predictors of drug response. DNA samples from responders or non-responders were pooled, so that many patients could be screened simultaneously and cost-effectively for common mutations. Compared with previous results, the genetic variants identified through this analysis were shown to predict failure to respond with high sensitivity and specificity.
By predicting which patients are unlikely to respond to the standard treatment, clinicians would be able to make an informed choice about which patients should be offered newly emerging therapies. These results therefore hold great promise for the clinical management of hepatitis C.
Posted by Paraminder Dhillon at 14:49 Comments (0)
Predicting genetic risk for disease
A lot has been written about the potential for
genomic information to revolutionize medicine. Much of the excitement centers
around the idea that if we know an individual’s genome we can use this
information to predict risk of a particular disease and then give specific
treatment. In a research article published
in the latest issue of Genome Medicine,
Cecile Janssens, Muin Khoury and colleagues improve current models of
genetic risk, taking us one step nearer to this aim.
Genetic risk prediction is a very active area of research, boosted by the number of genetic variants associated with common diseases that have been recently discovered through genome-wide association studies. Previous studies looked at how single mutations affect risk, but increasingly scientists and clinicians are finding that multiple mutations contribute to disease and so risk prediction needs to take into account multiple parameters.
The authors explore how several parameters of risk prediction, especially sensitivity and positive predictive value (PPV) vary under different models. They find that sensitivity and PPV are jointly maximized when the proportion of individuals identified at high risk by the test equals the population disease frequency. Otherwise, either the sensitivity is high or the PPV is high, but not both.
These results will help to advance strategies for predicting disease risk based on genetic data, as we move towards an era of personalized healthcare.
Posted by Maria Hodges at 17:38 Comments (0)
Linking diet and hormone exposure to breast cancer risk
One-and-a-half million people worldwide were diagnosed with breast cancer last
year. In the UK, it is the most common form of cancer. Many studies have tried
to find the regions of the
genome that are associated with breast cancer risk, yet so far only a small
proportion of inherited cancers can be explained. A report
in the latest issue of Genome Medicine
identifies two genomic regions linked to breast cancer risk.
Ross Prentice and colleagues from the Fred Hutchinson Cancer Research Center, Seattle, combined environmental information (such as diet and history of hormone treatment) with genotype information for breast cancer, both obtained from the Women’s Health Initiative (WHI) clinical trial. They found that, by taking both types of information into account, the significance of certain mutations (single nucleotide polymorphisms) for postmenopausal breast cancer risk changed.
The team identified two genomic regions associated with risk of breast cancer: the fibroblast growth factor receptor two (FGFR2) and the mitochondrial ribosomal protein S30 (MRPS30) regions. These findings are likely to lead to further investigations of regions close to the MRPS30 and FGFR2 genes to understand the link between the effects of hormonal and dietary exposures and postmenopausal breast cancer risk. This approach of combining environmental and genotype information will aid the search for regions linked to increased risk of other diseases.
Posted by Maria Hodges at 15:59 Comments (0)
Optimizing patient participation in genetic research
Genetic and medical research projects often rely on the
donation of blood or tissue samples from human subjects. Optimum recruitment of
willing participants is thereby a key consideration in research. In a
recent study published in Genome Medicine,
David Lanfear and colleagues show that the site of enrollment can influence rates of patient participation in genetic research. This finding
could inform future recruitment strategies and improve research quality.
As genetic research becomes more commonplace, a growing concern is the relatively low numbers of patient participants compared with non-genetic studies, which could increase the potential for selection biases. Lanfear et al. examined a host of socio-demographic and clinical variables, in addition to site of recruitment, to determine which factors are associated with low or high rates of patient participation. Data were collected from 24 US-based hospitals as part of the TRIUMPH study, a prospective registry of heart attack patients. This analysis revealed wide variability in the rates of consent across the different institutes. Strikingly, the site of recruitment was found to be more important in predicting consent than factors such as patient age, gender and level of education. Lanfear and colleagues conclude that differences in how hospital personnel interact with patients and present information can impact their willingness to participate.
The implications of this study are further discussed by Gert Helgesson, in a Research Highlight published in the same issue of Genome Medicine. Helgesson touches upon the potential for improving participation rates with better training and standardization of enrollment processes, but also emphasizes that ethical issues should be taken into consideration when striving for recruitment success.
Posted by Paraminder Dhillon at 16:50 Comments (0)
Genetic defects linked to Alzheimer’s disease
Alzheimer’s disease is the
most common cause of dementia in the developed world. Recent progress has
resulted in a flurry of papers identifying new genes linked to this disease
and Genome Medicine is pleased to
have published one of these key papers.
Despite continued investigation, the causes of Alzheimer’s disease are not yet fully understood but they are thought to be a mixture of genetic and environmental factors. Several studies have used genome-wide association studies (GWAS) to search the entire human genome for genes that are mutated in Alzheimer’s sufferers in the hope of finding a way to treat or slow down the disease.
A team of researchers across Spain and USA, sponsored by non-profit Fundations Alzheimur and Fundació ACE, performed their own GWAS study using patients with Alzheimer’s disease, and non-affected controls, from Spain and then combined their results with four public GWAS data sets. Researcher Dr Agustín Ruiz commented, “Combining these data sets allowed us to look more accurately at small genetic defects. Using this technique we were able to confirm the presence of mutations (SNP) known to be associated with Alzheimer’s disease, including those within the MS4A cluster, and we also found a novel site.”
“Several of the 16 genes within the MS4A cluster are implicated in the activities of the immune system and are probably involved in allergies and autoimmune disease. MS4A2 in particular has been linked to aspirin-intolerant asthma. Our research provides new evidence for a role of the immune system in the progression of Alzheimer’s disease,” continued Dr Ruiz.
Posted by Maria Hodges at 17:38 Comments (1)