Epigenetics replacing single gene based disease research!

Epigenetic pathology are the one of the biggest hot spots for genome scale studies of epigenetic diseases because of its ability to reveal more than the candidate gene approaches.For example, methylation changes can affect large genomic regions in colorectal cancer, and widespread methylation changes are even more striking outside of the usually examined CpG islands (i.e., in shores and gene bodies).
Stem cells, the focus for a wide range of both basic and applied research on disease, have shown promiscuous methylation differences from somatic cells on a genome-wide scale, notably including differences at non-CpG sites.  sites of differential methylation largely overlap, with strong statistical significance, across physiological states—the same sites appear, for example, in normal cells compared with cancer cells, in stem cells compared with differentiated cells and in comparisons of tissues derived from different germ layers. Thus, the language of epigenomic organization seems to be common for normal development and for disease, just as the language of anatomy is common for normal and abnormal physiology.

The influence of epigenetic control has definitely influenced how the disease based studies are being organized.Only  2% of cancer epigenetics are published genome scale studies , the rate of increase over the past five years of cancer epigenomic studies is more than double that of conventional gene-based analyses of cancer . A similar kind of trend is also picking up in other fields of noncancer human disease epigenetics, such as epigenetics of cardiovascular, immunological and neuropsychiatric disease. These differences are driven in part by the availability of new technology, of course, but also by the growing realization that variation in both DNA methylation and chromatin are widespread across the genome and may be organized into large genomic domains.
Another important factor driving such 'disease epigenomics' is the relatively limited yield to date of conventional single-nucleotide polymorphism (SNP)–based genetic analysis in explaining most common human diseases. As has been widely described in both scientific and lay publications, it was anticipated a decade ago that genetic analysis would be much more successful at attributing risk of disease to specific genetic markers. the actual 'genome anatomy' target for disease is probably much larger than scientists previously realized—perhaps involving more than half of the genome—and because understanding of the normal function of this genome anatomy requires epigenomics, it is possible that much of what appears to be negative genetic-association data could become meaningful in an epigenomic context . For example, most genome-wide association studies (GWAS) identify not genes, but nearby regions or intergenic deserts. Yet these same regions frequently harbor differentially methylated regions that discriminate tissue types or distinguish cancer from normal cells. They are also the canonical regions for lincRNAs that help establish chromatin structure and normal gene function. Furthermore, gene deserts may promote trans associations of chromosomes in epigenetic regulation. Another way in which disease-associated DNA sequence variants might affect disease risk is through their linkage to DNA sequences that regulate DNA methylation, chromatin modification or binding factors. Substantial association of SNPs with DNA methylation has already been found.
So Epigenetics  is all set to over take single gene based disease research.

A breakthrough perosnalised medicine Biomarker in Cancer !!

Results of a new study at M.D Anderson Cancer institute have found a new diagnostic test which will set up all together a new trend in personalized  medicine.They show that a specific protein can be used as a 'biomarker' to identify which patients with a rare type of non-Hodgkin lymphoma would benefit from a new class of cancer drug.
The presence or absence of the biomarker can now be used as a diagnostic test to identify which patients will benefit from this drug.It's one of the first examples of being able to personalise cancer medicine and tailor treatment for the individual patient.
Biomarkers also have implications for reducing the cost burden of introducing new cancer drugs on the NHS, as only the subset of patients that would see a benefit would receive the treatment.
'New cancer drugs would be more likely to gain approval from the National Institute for Health and Clinical Excellence where biomarkers exist to identify the appropriate patient group,' believes Professor La Thangue, as their analyses of how well the treatment works in relation to how much it costs the NHS would improve.
Cancer drug discovery and development has changed significantly with greater understanding of what goes wrong in biological processes within cancer cells. New drugs target a variety of these cellular processes, but they will often only be effective in a subset of patients according to the profile of their particular cancer.
For example, trastuzumab (Herceptin) is an effective drug against breast cancer but only among those patients with cancers that express the protein which the drug targets. Patients without that protein see no benefit from the drug.
A biomarker is something that can be measured to predict whether a particular cancer will respond to treatment with a particular drug. Simple diagnostic tests based on the level of biomarker present can then flag up patients that will respond to that drug.
Biomarkers can also be used to identify appropriate patient groups for clinical trials. This would improve the ability of the trial to determine a drug's clinical benefits and increase the likelihood that new and effective drugs make it into clinics. Currently the failure rate for new drugs in development is estimated to be 80%.
The Oxford and Texas team focussed on a new class of cancer drug called HDAC inhibitors because they stop the action of the protein histone deacetylase. SAHA (Vorinostat or Zolinza) was the first drug of this class to gain regulatory approval, and can be used in the treatment of a rare type of non-Hodgkin lymphoma known as cutaneous T-cell lymphoma, or CTCL.
The researchers used a whole-genome screen to identify those genes active in CTCL cells that govern whether the cancer cells respond to the drug SAHA or not. The screen works by silencing each gene in turn to assess its effect on how well the drug works. HR23B was found to determine the CTCL cells' sensitivity to SAHA.
The scientists now report that HR23B works as a biomarker in a clinically relevant setting. The presence of HR23B in biopsies from patients with CTCL predicted who would respond to the treatment 71.7% of the time.
With this first demonstration of a predictive biomarker for a cancer drug, the approach using a whole-genome screen can be done again and again to find biomarkers for different cancers and different drugs. The hope is that the identification of new biomarkers can become routine.
The Oxford group has a patent on the whole-genome screen for identifying biomarkers and is looking at options for commercialising a biomarker kit using HR23B as a companion diagnostic test to go with the drug SAHA.
This will surely be the path breaker in Cancer which is itself is not one disease but an array of so many disorders clubbed together under one name.

GWAS establishing links in HYPERTENSION..

High blood pressure or hypertension affects more than one in three people worldwide and is a major cause of strokes, heart attacks and heart failure .In USA alone About 74.5 million people in the United States age 20 and older have high blood pressure.  The degree with which blood pressure traits can be inherited suggests a genetic component. However, limited consistent evidence of genes associated with blood pressure have been produced.  large-scale genome-wide association studies (GWAS) have been used successfully to identify genes associated with common diseases and traits,however  studies on blood pressure or hypertension have failed to identify loci at a genome-wide significant threshold (p-value < 5 x 10^-8). The significance of GWAS data relies on several variables, including the accuracy of phenotypic measures, density of markers and size of the study population. Thus, if blood pressure variation in the general population is due to multiple genetic factors with small effects, a very large sample size is needed to identify them.

Researchers at the Johns Hopkins University School of Medicine, along with an international team of collaborators, established the Cohorts for Heart and Aging Research in Genome Epidemiology (CHARGE) Consortium to address the need for a very large sample size. The CHARGE Consortium was formed to “facilitate genome-wide association study meta-analyses and replication opportunities among multiple large and well-phenotyped longitudinal cohort studies.” In other words, they’re combining data from a number of large GWAS studies that collect data in a standardized fashion to perform a “study of studies”. The Consortium consists of almost 30,000 people of European descent whose average systolic blood pressure (meaning the blood pressure when the heart is contracting) ranged from 118 mm Hg to 143 mm Hg and average diastolic blood pressure (meaning the blood pressure when the heart relaxes between beats) ranged from 72 mm Hg to 83 mm Hg.

Using data from the CHARGE Consortium, scientists report that they have identified a number of single nucleotide polymorphisms (SNPs) for blood pressure and hypertension that just missed the significance threshold for GWAS.

he top ten CHARGE SNPs for systolic blood pressure, diastolic blood pressure and hypertension were then included in a joint meta-analysis with the Global Blood Pressure Genetics (Global BPgen) Consortium consisting of another 34,000 people of European ancestry published in the same issue of the journal Nature Genetics . Eleven CHARGE genes showed significant associations across the genome, attaining genome-wide significance (p-value < 5 x 10^-8).

Four CHARGE loci attained genome-wide significance for systolic blood pressure:

• ATPase, Ca(2+)-transporting, Plasma membrane (ATP2B1)
• Cytochrome P450, Family 17, Subfamily A, Polypeptide 1 (CYP17A1)
• Pleckstrin homology domain-containing protein, Family A, Member 7 (PLEKHA7)
• SH2B adaptor protein 3 (SH2B3)

Six CHARGE loci attained genome-wide significance for diastolic blood pressure:

• ATPase, Ca(2+)-transporting, Plasma membrane (ATP2B1)
• Calcium channel, Voltage-dependent, Beta-2 subunit (CACNB2)
• Cytoplasmic tyrosine kinase (CSK) – Unc51-like kinase 3 (ULK3)
• SH2B adaptor protein 3 (SH2B3)
• T-Box 3 (TBX3) – T-Box 5 (TBX5)
• Unc51-like kinase 4 (ULK4)

One CHARGE loci attained genome-wide significance for hypertension:

• ATPase, Ca(2+)-transporting, Plasma membrane (ATP2B1)

One gene in particular, ATP2B1 was linked to all three traits: systolic blood pressure, diastolic blood pressure and hypertension. The gene ATP2B1 encodes a plasma membrane protein that pumps calcium out of cells that line the vascular endothelium – the thin layer of cells that line the inside of blood vessels. A high concentration of intracellular calcium causes endothelial cells to contract, constricting the blood vessel and reducing flow. This is why calcium channel blockers are frequently prescribed to lower blood pressure. Thus, it’s not surprising to find a calcium-specific protein pump in the list of genes associated with blood pressure and hypertension .SH2B adaptor protein 3 (SH2B3) was associated with both systolic and diastolic blood pressure. The SH2B3 gene encodes a protein that mediates the interaction between extracellular receptors and intracellular signaling pathways. In addition, there is evidence that SH2B3 is involved in controlling adaptive immune responses. SH2B also regulates proliferation of several hematopoietic cell lineages (meaning blood cells).

New links established between DNA damage and tumour suppression!

p53   encoded by the TP53 gene is very important in multicellular organisms, where it regulates the cell cycle and, thus, functions as a tumor suppressor that is involved in preventing cancer. As such, p53 has been described as "the guardian of the genome".
However recently NCI scientists have linked p53  with TRF2, a protein that forms a complex that protects the ends of chromosomes from undergoing erosion. The ends of chromosomes are known as telomeres, and these end-pieces have been shown to influence cell longevity as well as cancer.  While activated p53 can be an indicator of DNA damage due to telomere malfunction, this study is the first to show that p53 also functions by negatively regulating the telomere-binding protein TRF2, thus suggesting the presence of a novel feedback loop. The study, lead by Curtis C. Harris, M.D., with coworkers Kaori Fujita, Ph.D., and Izumi Horikawa, M.D., of the Laboratory of Human Carcinogenesis, Center for Cancer Research.
Telomeres are capped at each end to protect them from degrading and from being recognized as damaged DNA. At the end of their lifespan, telomeres lose this protection and DNA-damage signaling pathways are triggered that activate p53. Harris and his team found that p53 controls TRF2 levels, through an intermediary component known as Siah-1. In this experiment, TRF2 was found to be repressed and Siah-1 was induced in normal human tissue cells when p53 was activated. The scientists also found that p53 affects DNA damage signaling from uncapped telomeres, as well as regulating the telomere-capping complex. This suggests that the p53-Siah-1-TRF2 pathway plays an integral part in orchestrating the DNA damage response of telomeres. Both p53 and telomeres have therapeutic significance in cancer. This discovery, therefore, provides not only a new mechanistic insight into p53- and telomere-based cancer therapeutics currently used or tested, but also the experimental basis for the development of new therapies, according to the scientists.
This can later prove to be a landmark link in cancer therapies.

New Ray of Hope for diabetics!

Type 2 diabetes comprises 90% of people with diabetes around the world, and is largely the result of excess body weight and physical inactivity.this fatal disease becoming a major epidemic for the world community which is already the burden of epidemics of aids , hypertension related disorders etc.

But a new discovery in Japan might be boon for type 2 Diabetics where a  hormone produced  and secreted by liver previously known for insulin resistance is the new focus. The discovery may be a new target for the treatment of insulin resistance and type 2 diabetes."The current study sheds light on a previously underexplored function of the liver; the liver participates in the pathogenesis of insulin resistance through hormone secretion," said Hirofumi Misu of Kanazawa University in Japan.

The researchers had discovered earlier that genes encoding secretory proteins are abundantly expressed in the livers of people with Type 2 diabetes. Now, the researchers reported the results of comprehensive gene expression analyses, revealing that the liver expresses higher levels of the gene encoding selenoprotein P (SeP) in people with type 2 diabetes who are more insulin resistant.

Further studies in mice added support to the notion that the connection between SeP and insulin resistance is causal. When the researchers gave normal mice SeP, they became insulin resistant and their blood sugar levels rose. 

A treatment that blocked the activity of SeP in the livers of diabetic and obese mice improved their sensitivity to insulin and lowered blood sugar levels.

Advent of Personalized Epigenomic Signatures!!!!

In a genome-wide scan, researchers found over 200 DNA regions with epigenetic modifications that vary between people. About half appear stable over time and form a personalized epigenetic “signature.” Four regions varied with body mass index, a finding that may pave the way toward new insights into how extra pounds affect your health.

Epigenetics is the study of factors that change the way genes are read, or expressed, without changing the DNA sequence itself. Epigenetic changes have been linked to several diseases over the past few years, raising the possibility that researchers might learn how to manipulate epigenomic factors to prevent or treat disease.
Methylation is a common epigenetic modification that affects gene expression. A research team led by Drs. Daniele Fallin and Andrew Feinberg at Johns Hopkins University previously found that methylation patterns can change as people age. For the new study, they wanted to further explore methylation patterns over time and between people. They also wanted to see whether any specific regions could be linked to disease risk. The study was supported by NIH’s National Institute of Environmental Health Sciences (NIEHS), National Institute on Aging (NIA), National Human Genome Research Institute (NHGRI) and others. The team also included scientists at NIA.
The researchers analyzed DNA from 74 people who gave samples 11 years apart in a study in Reykjavik, Iceland. Using an approach called comprehensive high-throughput array-based relative methylation (CHARM) that Feinberg helped to develop, the scientists searched for patterns of change over time among over 4 million methylation sites.
As reported in the September 15, 2010, issue of Science Translational Medicine, the scientists identified 227 regions that varied significantly between people. About half appeared to be stable over time within individuals, defining a personalized epigenomic signature.


To explore whether DNA methylation might play a role in disease risk, the researchers compared methylation patterns with body mass index, which has been linked to many health problems, including diabetes, heart disease and stroke. They found 13 regions that varied with body mass index. Of these, 4 had methylation patterns that consistently correlated with body mass index across the 11 years. These were all located in or near genes previously implicated in regulating body weight or diabetes.
“Some of the genes we found are in regions of the genome previously suspected but not confirmed for a link to body mass index and obesity,” Feinberg says. “Meanwhile, others were a surprise, such as one known to be associated with foraging behavior in hungry worms.”
Researchers have been debating the significance of DNA methylation and other epigenomic modifications. These results suggest that some DNA regions vary between people but remain essentially stable over time, while others can be altered by environmental factors and may contribute to diseases and disorders.
“What we accomplished is a small proof-of-principle study that we think is just the tip of the iceberg in using epigenetics to expand our knowledge of new markers for many common diseases and opening the door for personalized epigenetic medicine,” Feinberg says.