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Posts Tagged ‘Genome Research’


Larry H Bernstein, MD, FCAP, Reviewer and Curator

https://pharmaceuticalintelligence.com/2013-12-08/larryhbern/Developments-in-the-Genomics-and-Proteomics-of-Type-2-Diabetes-Mellitus-and-Treatment-Targets

Researchers Solve a Mystery about Type 2 Diabetes Drug

AB SCIEX TripleTOF® and QTRAP® technologies support breakthrough medical study.
Published: Friday, November 22, 2013
Researchers from St. Vincent’s Institute of Medical Research in Melbourne, Australia, in collaboration with researchers at McMaster University in Canada, are reportedly the first to discover how the type 2 diabetes drug metformin actually works, providing a molecular understanding that could lead to the development of more effective therapies. Mass spectrometry technologies from AB SCIEX played a critical role in the analysis that led to this breakthrough finding.  The research is published in this month’s issue of the journal Nature Medicine.
Doctors have known for decades that metformin helps treat type 2 diabetes.  However, questions had lingered for more than 50 years whether this drug, which is available as a generic drug,
  • worked to lower blood glucose in patients by directly working on the glucose.
People with type 2 diabetes have high blood sugar levels and have trouble converting sugar in their blood into energy because of low levels of insulin. For treating this condition, metformin is considered the most widely prescribed anti-diabetic drug in the world.
Until now, no one had been able to explain adequately how this drug lowers blood sugar. According to this new study, the drug works by reducing harmful fat in the liver. People who take metformin reportedly often have a fatty liver, which is frequently caused by obesity.
“Fat is likely a key trigger for pre-diabetes in humans,” said Professor Bruce Kemp, PhD, the Head of Protein Chemistry and Metabolism at St. Vincent’s Institute of Medical Research.  “Our study indicates that
  • metformin doesn’t directly reduce sugar metabolism, as previously suspected, but instead
  •  reduces fat in the liver, which in turn allows insulin to work effectively.”
The breakthrough in pinning down how the drug functions began with the researchers making
  • genetic mutations to the genes of two enzymes, ACC1 and ACC2,
in mice, so they could no longer be controlled.  What happened next surprised the researchers:
  • the mice didn’t get fat as expected,
but Associate Professor Gregory Steinberg, PhD at McMaster University noticed that
  • the mice had fatty livers and a pre-diabetic condition.
Then the researchers put the mice on
  • a high fat diet and they became fat, while metformin
  • did not lower the blood sugar levels of the mutant mice.
The findings are expected to help researchers better directly target the condition, which affects over 100 million people around the world, according to published reports. It is also believed that with the mystery of metformin solved, the application of the drug could go beyond just diabetes and potentially be used to treat other medical conditions.
“AB SCIEX mass spectrometry solutions help researchers explore big questions and conduct breakthrough studies, such as this remarkable type 2 diabetes study,” said Rainer Blair, President of AB SCIEX.   “In order to understand disease at the molecular level, researchers need the sensitive detection and reproducible quantitation provided by AB SCIEX tools. We enable the research community to solve biological mysteries and rethink the possibilities to transform health.
For the research conducted by the Australian and Canadian researchers, the analysis at the molecular level was optimized on AB SCIEX instrumentation, including the AB SCIEX TripleTOF® 5600 and the AB SCIEX QTRAP® 5500 system.
The TripleTOF system, with its high-speed, high-quality MS/MS capabilities,
  • was used for the discovery of key proteins and phosphopeptides.
The QTRAP system, with its high sensitivity MRM (multiple reaction monitoring) capabilities,
  • was used for quantitation of metabolites, including nucleotides and malonyl-CoA. 

Bardoxolone Methyl in Type 2 Diabetes and Stage 4 Chronic Kidney Disease

D de Zeeuw, T Akizawa, P Audhya, GL Bakris, M Chin, ….,and GM Chertow, for the BEACON Trial Investigators
Type 2 diabetes mellitus is the most important cause of progressive chronic kidney disease in the developed and developing worlds. Various therapeutic approaches to slow progression, including
  • restriction of dietary protein,
  • glycemic control, and
  • control of hypertension,
have yielded mixed results.1-3 Several randomized clinical trials have shown that
  • inhibitors of the renin–angiotensin–aldosterone system significantly reduce the risk of progression,4-6 although
  • the residual risk remains high.7
None of the new agents tested during the past decade have proved effective in late-stage clinical trials.8-12
Oxidative stress and impaired antioxidant capacity intensify 
  • with the progression of chronic kidney disease.13
In animals with chronic kidney disease,
  • oxidative stress and inflammation
  • are associated with impaired activity of the nuclear 1 factor (erythroid-derived 2)–related factor 2 (Nrf2) transcription factor.
The synthetic triterpenoid bardoxolone methyl and its analogues are the most potent known activators of the Nrf2 pathway. Studies involving humans,14 including persons with type 2 diabetes mellitus and stage 3b or 4 chronic kidney disease, have shown that
  • bardoxolone methyl can reduce the serum creatinine concentration for up to 52 weeks.15
We designed the Bardoxolone Methyl Evaluation in Patients with Chronic Kidney Disease and Type 2 Diabetes Mellitus: the Occurrence of Renal Events (BEACON) trial to test the hypothesis that
  • treatment with bardoxolone methyl reduces the risk of end-stage renal disease (ESRD) or death from cardiovascular causes
among patients with type 2 diabetes mellitus and stage 4 chronic kidney disease.

Methods

Study Design and Oversight

The BEACON trial was a phase 3, randomized, double-blind, parallel-group, international, multicenter trial of
  • once-daily administration of bardoxolone methyl (at a dose of 20 mg in an amorphous spray-dried dispersion formulation), as compared with placebo.
Participants were receiving background conventional therapy that included 
  • inhibitors of the renin–angiotensin–aldosterone system,
  • insulin or other hypoglycemic agents, and, when appropriate,
  • other cardiovascular medications.
The trial design and the characteristics of the trial participants at baseline have been described previously.16,17
Reata Pharmaceuticals sponsored the trial. The trial was jointly designed by employees of the sponsor and the academic investigators who were members of the steering committee. The steering committee, which was led by the academic investigators and included members who were employees of the sponsor, supervised the trial design and operation. An independent data and safety monitoring committee reviewed interim safety data every 90 days or on an ad hoc basis on request. The sponsor collected the trial data and transferred them to independent statisticians at Statistics Collaborative. The sponsor also contracted a second independent statistical group (Axio Research) to support the independent data and safety monitoring committee. The trial protocol was approved by the institutional review board at each participating study site. The protocol and amendments are available with the full text of this article at NEJM.org. The steering committee takes full responsibility for the integrity of the data and the interpretation of the trial results and for the fidelity of the study to the protocol. The first and last authors wrote the first draft of the manuscript. All the members of the steering committee made the decision to submit the manuscript for publication.

Study Population

Briefly, we included adults with 
  • type 2 diabetes mellitus and
  • an estimated glomerular filtration rate (GFR) of 15 to <30 ml per minute per 1.73 m2 BSA.
  1. Persons with poor glycemic control,
  2. uncontrolled hypertension, or
  3. a recent cardiovascular event (≤12 weeks before randomization) or
  4. New York Heart Association class III or IV heart failure were excluded.
Additional inclusion and exclusion criteria are listed in Table S1 in the Supplementary Appendix, available at NEJM.org. All the patients provided written informed consent.

Randomization and Intervention

 Randomization was stratified according to study site with the use of variable-sized blocks. The steering committee, sponsor, investigators, and trial participants were unaware of the group assignments. After randomization,
  • patients received either bardoxolone methyl or placebo.
The prescription of all other medications was at the discretion of treating physicians, who were encouraged to adhere to published clinical-practice guidelines. Patients underwent event ascertainment and laboratory testing according to the study schema shown in Figure S1 in the Supplementary Appendix. Ambulatory blood-pressure monitoring was performed in a substudy that included 174 patients (8%).
The statistical analysis plan defined the study period as the number of days from randomization to a common study-termination date. In the case of patients who were still receiving the study drug on the termination date, data on vital events were collected for an additional 30 days.
Outcomes
 The primary composite outcome was ESRD or death from cardiovascular causes. We defined ESRD as
  • the need for maintenance dialysis for 12 weeks or more or kidney transplantation.
If a patient died before undergoing dialysis for 12 weeks, the independent events-adjudication committee adjudicated whether the need for dialysis represented ESRD or acute renal failure. Patients who declined dialysis and who subsequently died were categorized as having had ESRD. All ESRD events were adjudicated. Death from cardiovascular causes was defined as death due to either cardiovascular or unknown causes.
The trial had three prespecified secondary outcomes —
  1. first, the change in estimated GFR as calculated with the use of the four-variable Modification of Diet in Renal Disease study equation, with serum creatinine levels calibrated to an isotope-dilution standard for mass spectrometry;
  2. second, hospitalization for heart failure or death due to heart failure; and
  3. third, a composite outcome of nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, or death from cardiovascular causes.

The events-adjudication committee, whose members were unaware of the study assignments, evaluated whether

  • ESRD events,
  • cardiovascular events,
  • neurologic events, and
  • deaths
met the prespecified criteria for primary and secondary outcomes (described in detail in the Supplementary Appendix).
Statistical Analysis
We calculated that we needed to enroll 2000 patients on the basis of the following assumptions:

  • a two-sided type I error rate of 5%, an event rate of 24% for the primary composite outcome in the placebo group during the first 2 years of the study,
  • a hazard ratio of 0.68 (bardoxolone methyl vs. placebo) for the primary composite outcome,
  • discontinuation of the study drug by 13.5% of the patients in the bardoxolone methyl group each year, and
  • a 2.5% annual loss to follow-up in each group.

Under these assumptions, if 300 patients had a primary composite outcome, the statistical power would be 85%.

We collected and analyzed all outcome data in accordance with the intention-to-treat principle. We calculated Kaplan–Meier product-limit estimates of
  • the cumulative incidence of the primary composite outcome.
We computed hazard ratios and 95% confidence intervals with the use of Cox proportional-hazards regression models with adjustment for

  • the baseline estimated GFR and urinary albumin-to-creatinine ratio.

We performed analogous analyses for secondary time-to-event outcomes. Given the abundance of early adverse events, we also report discrete cumulative incidences at 4 weeks and 52 weeks.

For longitudinal analyses of estimated GFR, we performed mixed-effects regression analyses using

  1. study group,
  2. time,
  3. the interaction of study group with time,
  4. estimated GFR at baseline,
  5. the interaction of baseline estimated GFR with time, and
  6. urinary albumin-to-creatinine ratio as covariates, and
  7. we compared the means between the bardoxolone methyl group and the placebo group.
We adopted similar approaches when examining the effects of treatment on other continuous measures assessed at multiple visits. Since the between-group difference in the primary composite outcome was not significant,
secondary and other outcomes with P values of less than 0.05 were considered to be nominally significant.
Statistical analyses were performed with the use of SAS software, version 9.3 (SAS Institute). Additional details of the statistical analysis are provided in the Supplementary Appendix.

Results

Patients

From June 2011 through September 2012, a total of 2185 patients underwent randomization, including 1545 (71%) in the United States, 334 (15%) in the European Union, 133 (6%) in Australia, 87 (4%) in Canada, 46 (2%) in Israel, and 40 (2%) in Mexico. Figure S2 in the Supplementary Appendix shows the disposition of the study participants.
As shown in Table 1Table 1Baseline Characteristics of the Patients in the Intention-to-Treat Population., the patients were diverse with respect to age, sex, race or ethnic group, and region of origin;
  • diabetic retinopathy and neuropathy were common conditions among the patients,
  • as was overt cardiovascular disease.
See Table S2 in the Supplementary Appendix for a more detailed description of the characteristics of the patients at baseline; Figure S3 in the Supplementary Appendix shows the distribution of baseline estimated GFR and urinary albumin-to-creatinine ratio.
Drug Exposure
The median duration of exposure to the study drug was 7 months (interquartile range, 3 to 11) among patients randomly assigned to bardoxolone methyl and
  • 8 months (interquartile range, 5 to 11) among those randomly assigned to placebo.
Figure S4 in the Supplementary Appendix shows the time to discontinuation of the study drug. Table S3 in the Supplementary Appendix shows the reasons that patients discontinued the study drug and the reasons that patients discontinued the study.
  • The median duration of follow-up was 9 months in both groups.

Outcomes

Primary Composite Outcome
A total of 69 of 1088 patients (6%) randomly assigned to bardoxolone methyl and 69 of 1097 (6%) randomly assigned to placebo had a primary composite outcome (hazard ratio in the bardoxolone methyl group vs. the placebo group, 0.98; 95% confidence interval [CI], 0.70 to 1.37; P=0.92) (Figure 1AFigure 1Kaplan–Meier Plots of the Time to the First Event of the Primary Outcome and Its Components.).
  • Death from cardiovascular causes occurred in 27 patients randomly assigned to bardoxolone methyl and in 19 randomly assigned to placebo (hazard ratio, 1.44; 95% CI, 0.80 to 2.59; P=0.23) (Figure 1B).
  • ESRD developed in 43 patients randomly assigned to bardoxolone methyl and in 51 randomly assigned to placebo (hazard ratio, 0.82; 95% CI, 0.55 to 1.24; P=0.35) (Figure 1C).

One patient in each group died from cardiovascular causes after the development of ESRD. The mean (±SD) estimated GFR

  • before the development of ESRD was 18.1±8.3 ml per minute per 1.73 m^2 in the bardoxolone methyl group and
  • 14.9±4.0 ml per minute per 1.73 m2 in the placebo group.
Secondary Outcomes
During the study period, 96 patients in the bardoxolone methyl group had heart-failure events (93 patients with at least one hospitalization due to heart failure and 3 patients who died from heart failure without hospitalization),
  • as compared with 55 in the placebo group (55 patients with at least one hospitalization due to heart failure and
  • no patients who died from heart failure without hospitalization) (hazard ratio, 1.83; 95% CI, 1.32 to 2.55; P<0.001) (Figure 2AFigure 2Kaplan–Meier Plots of the Time to the First Event of the Discrete Secondary Outcomes.).
A total of 139 patients in the bardoxolone methyl group, as compared with 86 in the placebo group, had
  • a composite outcome event of nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, or death from cardiovascular causes (hazard ratio, 1.71; 95% CI, 1.31 to 2.24; P<0.001) (Figure 2B).
Incidences of Composite Outcomes and Rates of Death from Any Cause
The cumulative incidences of the primary composite outcome and of the two secondary composite outcomes at 4 weeks and at 52 weeks are shown in Table S4 in the Supplementary Appendix. The rates of death from any cause are shown in Figure S5 in the Supplementary Appendix. From the time of randomization to the end of follow-up, 75 patients died: 44 patients in the bardoxolone methyl group and 31 in the placebo group (hazard ratio, 1.47; 95% CI, 0.93 to 2.32; P=0.10). The causes of death are listed in Table S5 in the Supplementary Appendix.

Estimated GFR

Patients randomly assigned to placebo had a significant mean decline in the estimated GFR from the baseline value (−0.9 ml per minute per 1.73 m2; 95% CI, −1.2 to −0.5), whereas those randomly assigned to bardoxolone methyl had a significant mean increase from the baseline value (5.5 ml per minute per 1.73 m2; 95% CI, 5.2 to 5.9). The difference between the two groups was 6.4 ml per minute per 1.73 m2 (95% CI, 5.9 to 6.9; P<0.001) (Figure 3AFigure 3Estimated Glomerular Filtration Rate (GFR), Body Weight, and Urinary Albumin-to-Creatinine Ratio.).
Physiological Variables
Physiological variables are shown in Table S6 in the Supplementary Appendix. The mean body weight remained stable in the placebo group
  • but declined steadily and substantially in the bardoxolone methyl group (Figure 3B).
There was a significantly smaller decrease from baseline in mean systolic blood pressure in the bardoxolone methyl group than in the placebo group (between-group difference, 1.5 mm Hg [95% CI, 0.5 to 2.5]), and
  • the mean diastolic blood pressure increased from baseline in the bardoxolone methyl group whereas it decreased in the placebo group (between-group difference, 2.1 mm Hg [95% CI, 1.6 to 2.6]).
Blood-pressure results from the substudy in which ambulatory blood-pressure monitoring was performed were similar in direction but were more pronounced (between-group difference of 7.9 mm Hg [95% CI, 3.8 to 12.0] in systolic blood pressure and 3.2 mm Hg [95% CI, 1.3 to 5.2] in diastolic blood pressure).
  • Heart rate also increased significantly in the bardoxolone methyl group, as compared with the placebo group (between-group difference, 3.8 beats per minute; 95% CI, 3.2 to 4.4).
Other Laboratory Variables
Data on laboratory variables are shown in Table S7 in the Supplementary Appendix.
  • The urinary albumin-to-creatinine ratio increased significantly in the bardoxolone methyl group, as compared with the placebo group (Figure 3C).
  • Serum magnesium, albumin, hemoglobin, and glycated hemoglobin levels decreased significantly in the bardoxolone methyl group, as compared with the placebo group.
  • The level of B-type natriuretic peptide increased significantly by week 24 in the bardoxolone methyl group, as compared with the placebo group.
Adverse Events
The rates of serious adverse events are summarized in Table 2Table 2Most Commonly Reported Serious Adverse Events in the Intention-to-Treat Population. Serious adverse events occurred more frequently in the bardoxolone methyl group than in the placebo group (717 events in 363 patients vs. 557 events in 295 patients). There were 11 neoplastic events in the bardoxolone methyl group and 10 in placebo group. The most commonly reported adverse events are summarized in Table S8 in the Supplementary Appendix.

Discussion

The current trial was designed to determine whether bardoxolone methyl, an activator of the cytoprotective Nrf2 pathway, would reduce the risk of ESRD
  • among patients with type 2 diabetes mellitus and stage 4 chronic kidney disease
  • who were receiving guideline-based conventional therapy.
The trial was terminated early because of safety concerns, driven primarily by an increase in cardiovascular events in the bardoxolone methyl group. Bardoxolone methyl did not lower the risk of ESRD or of death from cardiovascular causes, although too few events occurred during the trial to reliably determine the true effect of the drug on the primary composite outcome.
Given the truncated duration of the trial and the number of adjudicated events (46% of the events planned), and assuming no change in any of the original assumptions, we estimated the conditional power of the trial to be less than 40%. Although patients treated with bardoxolone methyl had a significant increase in the estimated GFR, as compared with those who received placebo,
  • there was a significantly higher incidence of heart failure and of the composite outcome of nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, or death from cardiovascular causes in the bardoxolone methyl group.
  • There were numerically more deaths from any cause among patients treated with bardoxolone methyl than among those in the placebo group.
Bardoxolone methyl is among the first orally available antioxidant Nrf2 activators. A small previous study showed that bardoxolone methyl
  • reduced inflammation and oxidative stress13 and
  • induced a decline in the serum creatinine level.
In the 52-Week Bardoxolone Methyl Treatment: Renal Function in CKD/Type 2 Diabetes (BEAM) trial,15 227 patients with type 2 diabetes mellitus and an estimated GFR of 20 to 45 ml per minute per 1.73 m2
  • had a significant increase in the estimated GFR (mean change, 8.2 to 11.4 ml per minute per 1.73 m2, depending on the dose group)
  • that was sustained over the entire trial period.
Muscle spasms and hypomagnesemia were the most common adverse events;
  • there was no increase in the rate of heart failure or other cardiovascular events.
The current trial was designed to determine whether the change in estimated GFR that we anticipated on the basis of the results of the BEAM trial would translate into a slower progression toward ESRD. Although in the current trial ESRD developed in fewer patients in the bardoxolone methyl group than in the placebo group, the early termination of the trial precludes conclusion of the effect on ESRD events.
The mechanism linking bardoxolone methyl to heart failure is unknown. Since an excess in heart-failure events was unanticipated, echocardiography was not performed routinely before randomization. Although weight declined significantly in the bardoxolone methyl group, we were unable to determine whether there was loss of body fat, intracellular (skeletal muscle) water, or extracellular (interstitial) water.
The fall in serum albumin and hemoglobin levels may reflect hemodilution caused by fluid retention.
Bardoxolone methyl also increased blood pressure.
An increase in preload due to volume expansion and an increase in afterload (as reflected by increased blood pressure),
  • coupled with an increase in heart rate,
  • constitute a potentially potent combination of factors that are likely to precipitate heart failure in an at-risk population.
The rise in the level of B-type natriuretic peptide with bardoxolone methyl
  • is consistent with an increase in left ventricular wall stress owing to one or more of these mediators or to unrecognized factors such as
  • impaired diastolic filling of the left ventricle.
After recognizing the initial increase in heart-failure events, the independent data and safety monitoring committee tried to identify
  • clinical characteristics that were associated with patients who were at elevated risk for heart failure
  • after the initiation of bardoxolone methyl therapy (with the possibility of modifying eligibility criteria or otherwise altering the trial),
but the committee was unable to do so. Other, noncardiovascular adverse events were also observed more frequently among patients exposed to bardoxolone methyl than among those who received placebo. Whether the effects of Nrf2 activation, or one or more counterregulatory responses, rendered this particular population vulnerable, is unknown. Zoja et al.18 found an increase in albuminuria and blood pressure along with weight loss in Zucker diabetic fatty rats treated with an analogue of bardoxolone methyl; these effects were not observed in other studies in Zucker diabetic fatty rats or other rodent models or in 1-year toxicologic studies in monkeys.19-21
Why were these adverse effects identified in the current trial and not in the BEAM trial?
  1. First, the number of patient-months of drug exposure in the current trial was roughly 10 times that in the BEAM trial.
  2. Second, the population in the present trial had more severe chronic kidney disease than did the population in the BEAM trial.
Observational studies have shown significantly higher rates of death and cardiovascular events, including heart failure,
  • among patients with stage 4 chronic kidney disease than among patients with stage 3 chronic kidney disease.22
Finally, our trial used an amorphous spray-dried dispersion formulation of bardoxolone methyl at a fixed dose rather than at an adjusted dose. We chose the 20-mg dose and the specific formulation used in the BEACON trial
  1. on the basis of four phase 2 studies of chronic kidney disease (three studies used the crystalline formulation, and one used the amorphous formulation),
  2. a crossover pharmacokinetics study involving humans that used both formulations, and
  3. several studies in animals that used both formulations (Meyer C: personal communication),
to provide an activity and safety profile that was similar to that observed with 75 mg of the crystalline formulation, which was one of the dose levels tested in the BEAM trial.
In conclusion, among patients with type 2 diabetes mellitus and stage 4 chronic kidney disease, bardoxolone methyl did not reduce the risk of the primary composite outcome of ESRD or death from cardiovascular causes. Significantly increased risks of heart failure and of the composite cardiovascular outcome (nonfatal myocardial infarction, nonfatal stroke, hospitalization for heart failure, or death from cardiovascular causes) prompted termination of the trial.
Alto, CA 93034, or at gchertow@stanford.edu.
Investigators in the Bardoxolone Methyl Evaluation in Patients with Chronic Kidney Disease and Type 2 Diabetes Mellitus: the Occurrence of Renal Events (BEACON) trial are listed in the Supplementary Appendix, available at NEJM.org.
Table 1. Baseline Characteristics of the Patients in the Intention-to-Treat Population.

Fig 1. Kaplan–Meier Plots of the Time to the First Event of the Primary Outcome and Its Components.

nejmoa1303154_f1   Kaplan–Meier Plot of Cumulative Probabilities of the Primary and Secondary End Points and Death.

Fig 2. Kaplan–Meier Plots of the Time to the First Event of the Discrete Secondary Outcomes

nejmoa1303154_f2  Kaplan–Meier Plot of Cumulative Probabilities of Acute Kidney Injury and Hyperkalemia
Fig 3.  Estimated Glomerular Filtration Rate (GFR), Body Weight, and Urinary Albumin-to-Creatinine Ratio
Table 2  Most Commonly Reported Serious Adverse Events in the Intention-to-Treat Population

References

    1  Klahr S, Levey AS, Beck GJ, et al. The effects of dietary protein restriction and blood-pressure control on the progression of chronic renal disease. N Engl J Med 1994;330:877-884
    2  The ADVANCE Collaborative Group. Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes. N Engl J Med 2008;358:2560-2572
    3  Parving HH, Andersen AR, Smidt UM, Svendsen PA. Early aggressive antihypertensive treatment reduces rate of decline in kidney function in diabetic nephropathy. Lancet 1983;1:1175-1179
    4  Brenner BM, Cooper ME, de Zeeuw D, et al. Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med 2001;345:861-869
    5 Lewis EJ, Hunsicker LG, Clarke WR, et al. Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl J Med 2001;345:851-860
   6  Parving HH, Lehnert H, Brochner-Mortensen J, Gomis R, Andersen S, Arner P. The effect of irbesartan on the development of diabetic nephropathy in patients with type 2 diabetes. N Engl J Med 2001;345:870-878
    7  Heerspink HJ, de Zeeuw D. The kidney in type 2 diabetes therapy. Rev Diabet Stud 2011;8:392-402
    8  Pfeffer MA, Burdmann EA, Chen CY, et al. A trial of darbepoetin alfa in type 2 diabetes and chronic kidney disease. N Engl J Med 2009;361:2019-2032
    9   Parving HH, Brenner BM, McMurray JJ, et al. Cardiorenal end points in a trial of aliskiren for type 2 diabetes. N Engl J Med 2012;367:2204-2213
    10   Packham DK, Wolfe R, Reutens AT, et al. Sulodexide fails to demonstrate renoprotection in overt type 2 diabetic nephropathy. J Am Soc Nephrol 2012;23:123-130
Combined Angiotensin Inhibition for the Treatment of Diabetic Nephropathy
Linda F. Fried, M.D., M.P.H., Nicholas Emanuele, M.D., Jane H. Zhang, Ph.D., Mary Brophy, M.D., Todd A. Conner, Pharm.D., William Duckworth, M.D., David J. Leehey, M.D., Peter A. McCullough, M.D., M.P.H., Theresa O’Connor, Ph.D., Paul M. Palevsky, M.D., Robert F. Reilly, M.D., Stephen L. Seliger, M.D., Stuart R. Warren, J.D., Pharm.D., Suzanne Watnick, M.D., Peter Peduzzi, Ph.D., and Peter Guarino, M.P.H., Ph.D. for the VA NEPHRON-D Investigators
N Engl J Med 2013; 369:1892-1903November 14, 2013DOI: 10.1056/NEJMoa1303154
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Background
Combination therapy with angiotensin-converting–enzyme (ACE) inhibitors and angiotensin-receptor blockers (ARBs) decreases proteinuria; however, its safety and effect on the progression of kidney disease are uncertain.
Methods
We provided losartan (at a dose of 100 mg per day) to patients with type 2 diabetes, a urinary albumin-to-creatinine ratio (with albumin measured in milligrams and creatinine measured in grams) of at least 300, and an estimated glomerular filtration rate (GFR) of 30.0 to 89.9 ml per minute per 1.73 m2 of body-surface area and then randomly assigned them to receive lisinopril (at a dose of 10 to 40 mg per day) or placebo. The primary end point was the first occurrence of a change in the estimated GFR (a decline of ≥30 ml per minute per 1.73 m2 if the initial estimated GFR was ≥60 ml per minute per 1.73 m2 or a decline of ≥50% if the initial estimated GFR was <60 ml per minute per 1.73 m2), end-stage renal disease (ESRD), or death. The secondary renal end point was the first occurrence of a decline in the estimated GFR or ESRD. Safety outcomes included mortality, hyperkalemia, and acute kidney injury.
Results
The study was stopped early owing to safety concerns. Among 1448 randomly assigned patients with a median follow-up of 2.2 years, there were 152 primary end-point events in the monotherapy group and 132 in the combination-therapy group (hazard ratio with combination therapy, 0.88; 95% confidence interval [CI], 0.70 to 1.12; P=0.30). A trend toward a benefit from combination therapy with respect to the secondary end point (hazard ratio, 0.78; 95% CI, 0.58 to 1.05; P=0.10) decreased with time (P=0.02 for nonproportionality). There was no benefit with respect to mortality (hazard ratio for death, 1.04; 95% CI, 0.73 to 1.49; P=0.75) or cardiovascular events. Combination therapy increased the risk of hyperkalemia (6.3 events per 100 person-years, vs. 2.6 events per 100 person-years with monotherapy; P<0.001) and acute kidney injury (12.2 vs. 6.7 events per 100 person-years, P<0.001).
Conclusions
Combination therapy with an ACE inhibitor and an ARB was associated with an increased risk of adverse events among patients with diabetic nephropathy. (Funded by the Cooperative Studies Program of the Department of Veterans Affairs Office of Research and Development; VA NEPHRON-D ClinicalTrials.gov number, NCT00555217.)
A complete list of investigators in the Veterans Affairs Nephropathy in Diabetes (VA NEPHRON-D) study is provided in the Supplementary Appendix, available at NEJM.org.
Figure 1  Kaplan–Meier Plot of Cumulative Probabilities of the Primary and Secondary End Points and Death.
Figure 2 Kaplan–Meier Plot of Cumulative Probabilities of Acute Kidney Injury and Hyperkalemia

The End of Dual Therapy with Renin–Angiotensin–Aldosterone System Blockade?

Nov 14, 2013       de Zeeuw D.  (Editorial)
 N Engl J Med 2013; 369:1960-1962
Treatment aimed at multiple risk factors and specific markers such as glucose level, blood pressure, body weight, cholesterol levels, and albuminuria has been the main focus to slow cardiovascular and renal risk among patients with diabetes. Among the agents used, those that interrupt the renin–angiotensin–aldosterone system (RAAS) have shown protection that extends beyond decreasing blood pressure. In part, these additional effects may be explained by a decrease in albuminuria.1 Therefore, angiotensin-converting–enzyme (ACE) inhibitors and angiotensin II–receptor blockers (ARBs) have become first-choice drugs in patients with diabetes. Despite some success, the residual cardiovascular and renal risk among patients with diabetes remains

Diabetes: Mouse Studies Point to Kinase as Treatment Target

Published: Nov 24, 2013
By Kristina Fiore, Staff Writer, MedPage Today

Targeting a pathway that plays a major role in both hepatic glucose production and insulin sensitivity may eventually help treat type 2 diabetes, researchers reported.
In a series of experiments in mice, researchers found that inhibition of the kinase CaMKII — or even some of its downstream components — lowered blood glucose and insulin levels, Ira Tabas, MD, PhD, of Columbia University Medical Center in New York City, and colleagues reported online in Cell Metabolism.
The pathway is activated by glucagon signaling in the liver, and appears to have roles in both insulin resistance as well as hepatic glucose production in the liver.
In an earlier study, Tabas and colleagues showed that inhibiting the CaMKII pathway lowered hepatic glucose production by suppressing p38-mediated FoxO1 nuclear localization.
In the current study, they found CaMKII inhibition suppresses levels of the pseudo-kinase TRB3 to improve Akt-phosphorylation, thereby improving insulin sensitivity.
Thus this single pathway targets “two cardinal features of type 2 diabetes — hyperglycemia and defective insulin signaling,” the researchers wrote.
“When we realized we had one common pathway that was responsible for these two disparate processes that, in essence, comprises all of type 2 diabetes, we though it would be an ideal target for new drug therapy,” Tabas told MedPage Today.
Tabas and colleagues conducted several experiments to evaluate the CaMKII pathway.
In one experiment in obese mice, they found that

  • no matter how CaMKII was knocked out, it led to lower blood glucose levels and lower fasting plasma insulin levels in response to a glucose challenge.

The improvements also occurred

  • when they knocked out downstream processes, including p38 and MAPK-activating protein kinase 2 (MK2).

“Thus liver p38 and MK2, like CaMKII, play an important role in the development of hyperglycemia and hyperinsulinemia in obese mice,” they wrote.
In further analyses, the researchers discovered

  • deleting or inhibiting any of these three elements ultimately improved insulin-induced Akt-phosphorylation in obese mice —
  • an important part of improving insulin sensitivity.

And unlike the effects on hepatic glucose production, these changes didn’t occur through effects on FoxO1.
Instead, inhibiting the CaMKII pathway suppressed levels of the pseudo-kinase TRB3, which likely occurred because of suppression of ATF4

  • all of which led to an increase in Akt-phosphorylation and insulin sensitivity.

Indeed, when mice were made to overexpress TRB3, the improvement in phosphorylation disappeared, “indicating that

  • the suppression of TRB3 by CaMKII deficiency is causally important in the improvement in insulin signaling,” they wrote.

As a result, there “appear to be two separate CaMKII pathways,

  • one involved in CaMKII-p38-FoxO1 dependent hepatic glucose production, and
  • the other involved in defective insulin-induced p-Akt,” they wrote.

The findings suggest the possibility of a drug that can target both hyperglycemia and insulin resistance in type 2 diabetes, they said.

Association Between a Genetic Variant Related to Glutamic Acid Metabolism and Coronary Heart Disease in Individuals With Type 2 Diabetes

Lu Qi; Qibin Qi; S Prudente; C Mendonca; F Andreozzi; et al.
JAMA. 2013;310(8):821-828.     http://dx.doi.org/10.1001/jama.2013.276305.

Importance

Diabetes is associated with an elevated risk of coronary heart disease (CHD). Previous studies have suggested that the genetic factors predisposing to excess cardiovascular risk may be different in diabetic and nondiabetic individuals.

Objective

To identify genetic determinants of CHD that are specific to patients with diabetes.

Design, Setting, and Participants

We studied 5 independent sets of CHD cases and CHD-negative controls from the Nurses’ Health Study (enrolled in 1976 and followed up through 2008), Health Professionals Follow-up Study (enrolled in 1986 and followed up through 2008), Joslin Heart Study (enrolled in 2001-2008), Gargano Heart Study (enrolled in 2001-2008), and Catanzaro Study (enrolled in 2004-2010). Included were a total of 1517 CHD cases and 2671 CHD-negative controls, all with type 2 diabetes. Results in diabetic patients were compared with those in 737 nondiabetic CHD cases and 1637 nondiabetic CHD-negative controls from the Nurses’ Health Study and Health Professionals Follow-up Study cohorts. Exposures included 2 543 016 common genetic variants occurring throughout the genome.

Main Outcomes and Measures

Coronary heart disease—defined as fatal or nonfatal myocardial infarction, coronary artery bypass grafting, percutaneous transluminal coronary angioplasty, or angiographic evidence of significant stenosis of the coronary arteries.

Results

A variant on chromosome 1q25 (rs10911021) was consistently associated with CHD risk among diabetic participants,

  • with risk allele frequencies of 0.733 in cases vs 0.679 in controls (odds ratio, 1.36 [95% CI, 1.22-1.51]; P = 2 × 10−8).

No association between this variant and CHD was detected among nondiabetic participants, with risk allele frequencies of 0.697 in cases vs 0.696 in controls (odds ratio, 0.99 [95% CI, 0.87-1.13]; P = .89),

  • consistent with a significant gene × diabetes interaction on CHD risk (P = 2 × 10−4).

Compared with protective allele homozygotes, rs10911021 risk allele

  • homozygotes were characterized by a 32% decrease in the expression of the neighboring glutamate-ammonia ligase (GLUL) gene in human endothelial cells (P = .0048).
  • A decreased ratio between plasma levels of γ-glutamyl cycle intermediates pyroglutamic and glutamic acid was also shown in risk allele homozygotes (P = .029).

Conclusion and Relevance

A single-nucleotide polymorphism (rs10911021) was identified that was significantly associated with CHD among persons with diabetes but not in those without diabetes and was functionally related to glutamic acid metabolism, suggesting a mechanistic link.

Adipocyte Heme Oxygenase-1 Induction Attenuates Metabolic Syndrome In Both Male And Female Obese Mice

Angela Burgess1,2, Ming Li2, Luca Vanella1, Dong Hyun Kim1, Rita Rezzani4, et al.

1Department of Physiology and Pharmacology, University of Toledo, Toledo, OH 43614
2Department of Pharmacology, New York Medical College, Valhalla, NY 10595
3Department of Medicine, New York Medical College, Valhalla, NY 10595
4Department of Biomedical Sciences and Biotechnology, University of Brescia, Brescia, Italy
5Department of Pediatrics and Center for Applied Genomics, Charles University, Prague, Czech Republic
6The Rockefeller University, New York, New York 10065

Hypertension. 2010 December ; 56(6): 1124–1130.    http://dx.doi.org/10.1161/HYPERTENSIONAHA.110.151423

Abstract

Increases in visceral fat are associated with
  • increased inflammation,
  • dyslipidemia,
  • insulin resistance,
  • glucose intolerance and
  • vascular dysfunction.
We examined the effect of the potent heme oxygenase (HO)-1 inducer, cobalt protoporphyrin (CoPP), on regulation of adiposity and glucose levels in both female and male obese mice. Both lean and obese mice were administered CoPP intraperitoneally, (3mg/kg/once a week) for 6 weeks. Serum levels of
  1. adiponectin,
  2. TNFα,
  3. IL-1β and
  4. IL-6, and
  5. HO-1,
  6. PPARγ,
  7. pAKT, and
  8. pMPK protein expression
were measured in adipocytes and vascular tissue . While female obese mice continued to gain weight at a rate similar to controls, induction of HO-1 slowed the rate of weight gain in male obese mice. HO-1 induction led to lowered blood pressure
levels in obese males and females mice similar to that of lean male and female mice.
HO-1 induction also produced a significant decrease in the plasma levels of IL-6, TNF-α, IL-1β and fasting glucose of obese females compared to untreated female obese mice. HO-1 induction
  • increased the number and
  • decreased the size of adipocytes of obese animals.
HO-1 induction increased adiponectin, pAKT, pAMPK, and PPARγ levels in adipocyte of obese animals. Induction of HO-1, in adipocytes was associated with
  • an increase in adiponectin and
  • a reduction in inflammatory cytokines.
These findings offer the possibility of treating not only hypertension, but also other detrimental metabolic consequences of obesity
  • including insulin resistance and dyslipidemia in obese populations
  • by induction of HO-1 in adipocytes.
Introduction
Moderate to severe obesity is associated with increased risk for cardiovascular complications and insulin resistance in humans1, 2 and animals3, 4. Cardiovascular risk is specifically associated with increased intra-abdominal fat. Women in their reproductive years have a higher BMI than males, which largely reflects increased overall subcutaneous adipose tissue or “gynoid” obesity, this is not associated with increased cardiovascular risk5. However, due to increases in visceral fat with aging, after the age of 60 the fat distribution in females more closely resembles that in males6. Increased androgen levels also often occur after the menopausal transition. These changes in visceral fat content and androgen levels correlate with both central obesity and insulin resistance and are an important determinant of cardiovascular risk7.
Heme oxygenase (HO) catalyzes the breakdown of heme, a potentially harmful pro-oxidant, into its products biliverdin and carbon monoxide, with a concomitant release of iron (reviewed in8). While HO-2 is expressed constitutively, HO-1 is inducible in response to oxidative stress and its induction has been reported to normalize vascular and renal function9–11. Further, induction of HO-1 slows weight gain, decreases levels of TNF-α and IL-6 and increases serum levels of adiponectin in obese rats and obese diabetic mice4, 9, 12.
The association observed between HO-1 and adiponectin has led to the proposal of the existence of a cytoprotective HO-1/adiponectin axis4, 13. Previously, L’Abbate et al,14 have shown that induction of HO-1 is associated with a parallel increase in the serum levels of adiponectin, which has well-documented
  1. insulin-sensitizing,
  2. antiapoptotic,
  3. antioxidative and
  4. anti-inflammatory properties.
Adiponectin is an abundant protein secreted from adipocytes. Once secreted, it mediates its actions by binding to a set of receptors, such as
  • adipoR1 and adipoR2, and also
  • through induction of AMPK signaling pathways15, 16.
In addition, increases in adiponectin play a protective role against TNF mediated endothelial activation17.
In this study, we evaluated the effect of CoPP, a potent inducer of HO-1,
  • on visceral and subcutaneous fat distribution in both female and male obese mice.
We show for the first time a resistance to weight reduction upon administration of CoPP in female obese mice but
  • a significant decrease in inflammatory cytokines.
Despite continued obesity,
  1. CoPP normalized blood pressure levels,
  2. decreased circulating cytokines, and
  3. increased insulin sensitivity in obese females.
CoPP treatment of obese mice
  • increased the number and
  • reduced the size of adipocytes.
CoPP treatment of both male and female obese mice reversed the reduction in adiponectin levels seen in obesity. This study suggests that in spite of continued obesity,
  • HO-1 induction in female obese mice serves a protective role against obesity associated metabolic consequences via expansion of healthy smaller insulin-sensitive adipocytes.

Results

Effect of induction of HO-1 on body weight, appearance, and fat content of female and male obese mice. Previously, we have shown CoPP treatment results in the prevention of weight gain in several male models of obesity including obese and db/db mice and Zucker fat rats4, 12. We extended our studies to examine the effect of CoPP on weight gain in female obese mice. CoPP-treatment prevented weight gain in male obese mice when compared to age-matched male controls (Figure S1). The revention of body weight gain was accompanied by a
reduction in visceral fat in male obese mice. However, female obese mice administered CoPP did not lose weight but continued to gain weight at the same rate as untreated female obese mice (Figure S1). This was in spite of food intake being comparable between the two
groups. CoPP administration decreased subcutaneous fat content in both obese males and females (p<0.05; p<0.05, respectively). CoPP produced a decrease (p<0.05) in visceral fat in male but not in female obese mice when compared to untreated obese mice (Figure S1D).
We examined adipocyte size by haematoxilin-eosin staining in both lean, obese and CoPP treated obese female mice (Figure 1A, upper panel). CoPP treatment resulted in a decrease in adipocyte size (p<0.05) compared to untreated obese animals (Figure 1A, lower left panel). We then examined the number of adipocytes in lean, obese and CoPP-treated obese female mice. The number of adipocytes (mean±SE) in lean, obese and CoPP-treated obese animals was 40.83±3.50, 18.33±1.80 and 32.00±1.67 respectively indicating that CoPP treatment of obese mice increased the number of adipocytes to levels similar to those in lean animals (Figure 1A, lower right panel). Similar results were seen in male animals.
The induction of HO-1 was associated with a reduction in blood pressure (BP). Systolic blood pressure in obese female mice was 142 ± 6.5 mm Hg compared to obese-CoPP treated, 109 ± 8.1 mm Hg, p<0.05. The value in obese female mice treated with CoPP is similar to the blood pressure seen in lean female mice (110 ± 9.6 mm Hg). The systolic blood pressure in obese male mice was 144± 4.5 mm Hg compared to obese-CoPP treated, 104 ± 3.6 mm Hg, p<0.05.
We further examined whether CoPP affects HO-1 expression in adipocyte using immunohistochemistry and western blot analysis. Immunostaining showed increased levels of HO-1 (green staining), located on the surface of adipocytes, after CoPP treatment (p<0.05), compared with female obese mice, Figure 1B. As seen in Figure 1C, HO-1 and

HO-2 levels in adipocyte isolated from lean, untreated female obese mice or female obese mice treated with CoPP. Densitometry analysis showed that HO-1 was increased
significantly in female obese mice treated with CoPP, compared to non-treated female obese mice, p<0.05, which is in agreement with immunohistochemistry results. This pattern of HO expression in obesity occurs in other tissues, including aortas, kidneys and hearts of male obese mice4, 13.
Effect of CoPP on HO-1 expression and HO activity in female and male obese mice
HO-1 protein levels were increased by CoPP treatments in liver and renal tissues similar to that seen in adipocytes. Western blot analysis showed significant differences  (p<0.05) in the ratio of HO-1 to actin in renal of male and female obese and lean mice (Figure S 2A). Obesity decreasd HO-1 levels in both sexes when compared to age matched lean animals.
In addition, HO-1 levels were significantly (p<0.05) lower in obese females compared to obese males (Figure S 2A). This reflects a less active HO system in both male and female
obese animals compared to age matched lean controls. Next, we compared the effect of CoPP on male and female HO-1 gene expression in adipocytes. CoPP increased HO-1
expression in both male and female obese animals compared to untreated obese animals (Figure S 2B, p<0.001 and p<0.001, respectively). Similar results of HO-1 expression were seen in liver tissues (Result not shown).
Effect of CoPP on cytokine levels in female and male obese mice
CoPP administration resulted in a significnt increase in the levels of plasma adiponectin in both female (p<0.001) and male obese (p<0.001) mice (Figure 2A). Untreated female obese animals exhibited a significant (p<0.05) increase in plasma IL-6 levels when compared to age-matched male obese mice (Figure 2B). CoPP decreased plasma IL-6 levels in both female and male obese mice (p<0.05A )p<0.01, respectively) when compared to untreated obese miec. Similar results were observed with plasma TNF-α and IL-1β levels (Figure 2C and 2D). These results indicate that though female obese mice exhibited elevated serum levels of inflammatory cytokines compared to male obese mice, CoPP acts with equal efficacy in both female and male obese animals in reducing inflammation while simultaneously increasing serum adiponectin levels (Figure 2). 

Effect of CoPP on blood glucose and LDL levels in female and male obese mice 

Fasting glucose levels were determined after the development of insulin resistance. CoPP produced a decrease in glucose levels in both fasting female (p<0.05) and male (p<0.001) obese mice when compared to untreated obese control animals (Figure 3A). CoPP reduced LDL levels in both male (p<0.01) and female (p<0.05) obese mice when compared to untreated obese controls (Figure 3B). Treatment with SnMP, increased LDL levels. In separate experiments two weeks apart, glucose levels and insulin sensitivity were determined after development of insulin resistance (Fig. 4A and B). Blood glucose levels in female obese mice were elevated (p<0.01) 30 min after glucose administration and remained elevated. In CoPP-treated female obese mice produced a decrease in glucose but not in the vehicle-treated female obese mice (p<0.01).

Effect of Obesity on Protein Expression Levels of pAKT, pAMPK, and PPARγ levels in female and male obese mice

Western blot analysis of adipocytes harvested from fat tissues,showed significant  differences in basal protein expression levels of pAKT and pAMPK in untreated female obese mice compared to untreated obese male mice. pAMPK levels were higher in obese females compared to obese males (Figure 5A, p< 0.05). This was also the case for pAKT protein levels, where increased levels of pAKT were seen in obese females compared to obese males (Figure 5B, p<0.05). CoPP treatment increased pAMPK and pAKT levels in bothe obese females and obese males. In addition, CoPP administration increased PPARγ levels, in both male (p<0.001) and female (p<0.05) obese mice (Figures 5C).

Discussion

In the current study, we show for the first time that induction of HO-1 regulates adiposity in both male and female animals via an increase in adipocyte HO-1 protein levels. A second novel finding is that induction of HO-1 was associated not only with a decrease in adipocyte cell size but with an increase in adipocyte cell number. Further, induction of HO-1 affects visceral and subcutaneous fat distribution and metabolic function in male obese mice differently than in female obese mice. Despite continued obesity, upregulation of HO-1 induced major improvements in the metabolic profile of female obese mice exhibiting symptoms of Type 2 diabetes including: high plasma levels of proinflammatory cytokines, hyperglycemia, dyslipidemia, and low adiponectin levels. CoPP treatment resulted in increased serum adiponectin levels and decreased blood pressure. Adiponectin is exclusively secreted from adipose tissue, and its expression is higher in subcutaneous rather than invisceral adipose tissue. Increased adiponectin levels reduce adipocyte size and increase adipocyte number12, resulting in smaller, more insulin sensitive adipocytes. Adiponectin has recently attracted much attention because it has insulin-sensitizing properties that enhance fatty acid oxidation, liver insulin action, and glucose uptake and positively affect serum trglyceride levels18–21. Levels of circulating adiponectin are inversely correlated with plasma levels of oxidized LDL in patients with Type 2 diabetes and coronary artery disease, which suggests that low adiponectin levels are associated with an increased oxidative state in the arterial wall22. Thus, increases in adiponectin mediated by upregulation of HO-1 may account for improved insulin sensitivity and reduced levels of LDL and inflammatory cytokines (TNF-α, IL-1β, and IL-6 levels) in both male and female mice.

 Females continued to gain weight in spite of the metabolic improvements. One plausible explanation for this anomaly is the direct effects of HO-1 on adiponectin mediating clonal expansion of pre-adipocytes. This supports the concept that expansion of adipogenesis leads to an increased number of adipocytes of smaller cell size; smaller adipocytes are considered to be healthy, insulin sensitive adipocyte cells that are capable of producing adiponectin23. This hypothesis is supported by the increase in the number of smaller adipocytes seen in
CoPP-treated female obese animals without affecting weight gain when compared to female obese animals. Similar results for the presence were seen in males indicating that this effect is not sex specific.
Upregulation of HO-1 was also associated with increased levels of adipocyte pAKT, and pAMPK and PPARγ levels. Previous studies have indicated that insulin resistance and  impaired PI3K/pAKT signaling can lead to the of endothelial dysfunction24. In the current study, increased HO-1 expression was associated with increases in both AKT and AMPK phosphorylation; these actions may protect renal arterioles from insulin mediated endothelial damage. By this mechanism, increased levels of HO-1 limit oxidative stress and facilitate activation of an adiponectin-pAMPK-pAKT pathway and increased insulin sensitivity. Induction of adiponectin and activation of the pAMPK-AKT pathway has been shown to provide vascular protection25, 26. A reduction in AMPK and AKT levels may also explain why inhibition of HO activity in CoPP-treated obese mice  increased inflammatory cytokine levels while decreasing adiponectin. The action of CoPP in increasing pAKT, pAMPK and PPARγ is associated with improved glucose tolerance and decreased insulin resistant.
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Copy Number Variants (CNV) Alleles to be Detected by a Complete Recessive Carrier Screening Diagnostics

Reporter: Aviva Lev-Ari, PhD, RN

 

Using array comparative genomic hybridization data for 21,470 individuals, Baylor College of Medicine‘s James Lupski and colleagues considered the frequency with which deletions or other disruptive copy number variants appear in genes known for roles in recessive disease. As they report in Genome Research, the investigators unearthed more than 3,200 instances in which deletions affected one allele of a recessive disease gene, affecting 419 different recessive disease genes in all. The CNVs — which render individuals potential carriers of recessive disease — tended to occur in long genes and genes falling far from those contributing to dominant disease risk, study authors note. Based on their findings, they argue that “a complete recessive carrier screening method or diagnostic test should detect CNV alleles.”

Deletions of recessive disease genes: CNV contribution to carrier states and disease-causing alleles

Abstract

Over 1,200 recessive disease genes have been described in humans. The prevalence, allelic architecture, and per-genome load of pathogenic alleles in these genes remain to be fully elucidated, as does the contribution of DNA copy-number variants (CNVs) to carrier status and recessive disease. We mined CNV data from 21,470 individuals obtained by array comparative genomic hybridization in a clinical diagnostic setting to identify deletions encompassing or disrupting recessive disease genes. We identified 3,212 heterozygous potential carrier deletions affecting 419 unique recessive disease genes. Deletion frequency of these genes ranged from one occurrence to 1.5%. When compared with recessive disease genes never deleted in our cohort, the 419 recessive disease genes affected by at least one carrier deletion were longer and were located farther from known dominant disease genes, suggesting that the formation and/or prevalence of carrier CNVs may be affected by both local and adjacent genomic features and by selection. Some subjects had multiple carrier CNVs (307 subjects) and/or carrier deletions encompassing more than one recessive disease gene (206 deletions). Heterozygous deletions spanning multiple recessive disease genes may confer carrier status for multiple single-gene disorders, for complex syndromes resulting from the combination of two or more recessive conditions, or may potentially cause clinical phenotypes due to a multiply heterozygous state. In addition to carrier mutations, we identified homozygous and hemizygous deletions potentially causative for recessive disease. We provide further evidence that CNVs contribute to the allelic architecture of both carrier and recessive disease-causing mutations. Thus, a complete recessive carrier screening method or diagnostic test should detect CNV alleles.

  • Received February 7, 2013.
  • Accepted May 6, 2013.

© 2013, Published by Cold Spring Harbor Laboratory Press

 

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What is the Future for Genomics in Clinical Medicine?


What is the Future for Genomics in Clinical Medicine?

Author and Curator: Larry H Bernstein, MD, FCAP

 

Introduction

This is the last in a series of articles looking at the past and future of the genome revolution.  It is a revolution indeed that has had a beginning with the first phase discovery leading to the Watson-Crick model, the second phase leading to the completion of the Human Genome Project, a third phase in elaboration of ENCODE.  But we are entering a fourth phase, not so designated, except that it leads to designing a path to the patient clinical experience.
What is most remarkable on this journey, which has little to show in treatment results at this time, is that the boundary between metabolism and genomics is breaking down.  The reality is that we are a magnificent “magical” experience in evolutionary time, functioning in a bioenvironment, put rogether like a truly complex machine, and with interacting parts.  What are those parts – organelles, a genetic message that may be constrained and it may be modified based on chemical structure, feedback, crosstalk, and signaling pathways.  This brings in diet as a source of essential nutrients, exercise as a method for delay of structural loss (not in excess), stress oxidation, repair mechanisms, and an entirely unexpected impact of this knowledge on pharmacotherapy.  I illustrate this with some very new observations.

Gutenberg Redone

The first is a recent talk on how genomic medicine has constructed a novel version of the “printing press”, that led us out of the dark ages.

Topol_splash_image

In our series The Creative Destruction of Medicine, I’m trying to get into critical aspects of how we can Schumpeter or reboot the future of healthcare by leveraging the big innovations that are occurring in the digital world, including digital medicine.

We have this big thing about evidence-based medicine and, of course, the sanctimonious randomized, placebo-controlled clinical trial. Well, that’s great if one can do that, but often we’re talking about needing thousands, if not tens of thousands, of patients for these types of clinical trials. And things are changing so fast with respect to medicine and, for example, genomically guided interventions that it’s going to become increasingly difficult to justify these very large clinical trials.

For example, there was a drug trial for melanoma and the mutation of BRAF, which is the gene that is found in about 60% of people with malignant melanoma. When that trial was done, there was a placebo control, and there was a big ethical charge asking whether it is justifiable to have a body count. This was a matched drug for the biology underpinning metastatic melanoma, which is essentially a fatal condition within 1 year, and researchers were giving some individuals a placebo.

The next observation is a progression of what he have already learned. The genome has a role is cellular regulation that we could not have dreamed of 25 years ago, or less. The role is far more than just the translation of a message from DNA to RNA to construction of proteins, lipoproteins, cellular and organelle structures, and more than a regulation of glycosidic and glycolytic pathways, and under the influence of endocrine and apocrine interactions. Despite what we have learned, the strength of inter-molecular interactions, strong and weak chemical bonds, essential for 3-D folding, we know little about the importance of trace metals that have key roles in catalysis and because of their orbital structures, are essential for organic-inorganic interplay. This will not be coming soon because we know almost nothing about the intracellular, interstitial, and intrvesicular distributions and how they affect the metabolic – truly metabolic events.

I shall however, use some new information that gives real cause for joy.

Reprogramming Alters Cells’ Fate

Kathy Liszewski
Gordon Conference  Report: June 21, 2012;32(11)
New and emerging strategies were showcased at Gordon Conference’s recent “Reprogramming Cell Fate” meeting. For example, cutting-edge studies described how only a handful of key transcription factors were needed to entirely reprogram cells.
M. Azim Surani, Ph.D., Marshall-Walton professor at the Gurdon Institute, University of Cambridge, U.K., is examining cellular reprogramming in a mouse model. Epiblast stem cells are derived from the early-stage embryonic stage after implantation of blastocysts, about six days into development, and retain the potential to undergo reversion to embryonic stem cells (ESCs) or to PGCs.”  They report two critical steps both of which are needed for exploring epigenetic reprogramming.  “Although there are two X chromosomes in females, the inactivation of one is necessary for cell differentiation. Only after epigenetic reprogramming of the X chromosome can pluripotency be acquired. Pluripotent stem cells can generate any fetal or adult cell type but are not capable of developing into a complete organism.”
The second read-out is the activation of Oct4, a key transcription factor involved in ESC development. The expression of Oct4 in epiSCs requires its proximal enhancer.  Dr. Surani said that their cell-based system demonstrates how a systematic analysis can be performed to analyze how other key genes contribute to the many-faceted events involved in reprogramming the germline.
Reprogramming Expressway
A number of other recent studies have shown the importance of Oct4 for self-renewal of undifferentiated ESCs. It is sufficient to induce pluripotency in neural tissues and somatic cells, among others. The expression of Oct4 must be tightly regulated to control cellular differentiation. But, Oct4 is much more than a simple regulator of pluripotency, according to Hans R. Schöler, Ph.D., professor in the department of cell and developmental biology at the Max Planck Institute for Molecular Biomedicine.
Oct4 has a critical role in committing pluripotent cells into the somatic cellular pathway. When embryonic stem cells overexpress Oct4, they undergo rapid differentiation and then lose their ability for pluripotency. Other studies have shown that Oct4 expression in somatic cells reprograms them for transformation into a particular germ cell layer and also gives rise to induced pluripotent stem cells (iPSCs) under specific culture conditions.
Oct4 is the gatekeeper into and out of the reprogramming expressway. By modifying experimental conditions, Oct4 plus additional factors can induce formation of iPSCs, epiblast stem cells, neural cells, or cardiac cells. Dr. Schöler suggests that Oct4 a potentially key factor not only for inducing iPSCs but also for transdifferention.  “Therapeutic applications might eventually focus less on pluripotency and more on multipotency, especially if one can dedifferentiate cells within the same lineage. Although fibroblasts are from a different germ layer, we recently showed that adding a cocktail of transcription factors induces mouse fibroblasts to directly acquire a neural stem cell identity.
Stem cell diagram illustrates a human fetus st...

Stem cell diagram illustrates a human fetus stem cell and possible uses on the circulatory, nervous, and immune systems. (Photo credit: Wikipedia)

English: Embryonic Stem Cells. (A) shows hESCs...

English: Embryonic Stem Cells. (A) shows hESCs. (B) shows neurons derived from hESCs. (Photo credit: Wikipedia)

Transforming growth factor beta (TGF-β) is a s...

Transforming growth factor beta (TGF-β) is a secreted protein that controls proliferation, cellular differentiation, and other functions in most cells. http://en.wikipedia.org/wiki/TGFbeta (Photo credit: Wikipedia)

Pioneer Transcription Factors

Pioneer transcription factors take the lead in facilitating cellular reprogramming and responses to environmental cues. Multicellular organisms consist of functionally distinct cellular types produced by differential activation of gene expression. They seek out and bind specific regulatory sequences in DNA. Even though DNA is coated with and condensed into a thick fiber of chromatin. The pioneer factor, discovered by Prof. KS Zaret at UPenn SOM in 1996, he says, endows the competence for gene activity, being among the first transcription factors to engage and pry open the target sites in chromatin.
FoxA factors, expressed in the foregut endoderm of the mouse,are necessary for induction of the liver program. They found that nearly one-third of the DNA sites bound by FoxA in the adult liver occur near silent genes

A Nontranscriptional Role for HIF-1α as a Direct Inhibitor of DNA Replication

ME Hubbi, K Shitiz, DM Gilkes, S Rey,….GL Semenza. Johns Hopkins University SOM
Sci. Signal 2013; 6(262) 10pgs. [DOI: 10.1126/scisignal.2003417]   http:dx.doi.org/10.1126/scisignal.2003417

http://SciSignal.com/A Nontranscriptional Role for HIF-1α as a Direct Inhibitor of DNA Replication/

Many of the cellular responses to reduced O2 availability are mediated through the transcriptional activity of hypoxia-inducible factor 1 (HIF-1). We report a role for the isolated HIF-1α subunit as an inhibitor of DNA replication, and this role was independent of HIF-1β and transcriptional regulation. In response to hypoxia, HIF-1α bound to Cdc6, a protein that is essential for loading of the mini-chromosome maintenance (MCM) complex (which has DNA helicase activity) onto DNA, and promoted the interaction between Cdc6 and the MCM complex. The binding of HIF-1α to the complex decreased phosphorylation and activation of the MCM complex by the kinase Cdc7. As a result, HIF-1α inhibited firing of replication origins, decreased DNA replication, and induced cell cycle arrest in various cell types. To whom correspondence should be addressed. E-mail: gsemenza@jhmi.edu
Citation: M. E. Hubbi, Kshitiz, D. M. Gilkes, S. Rey, C. C. Wong, W. Luo, D.-H. Kim, C. V. Dang, A. Levchenko, G. L. Semenza, A Nontranscriptional Role for HIF-1α as a Direct Inhibitor of DNA Replication. Sci. Signal. 6, ra10 (2013).

Identification of a Candidate Therapeutic Autophagy-inducing Peptide

Nature 2013;494(7436).    http://nature.com/Identification_of_a_candidate_therapeutic_autophagy-inducing_peptide/   http://www.ncbi.nlm.nih.gov/pubmed/23364696
http://www.readcube.com/articles/10.1038/nature11866

Beth Levine and colleagues have constructed a cell-permeable peptide derived from part of an autophagy protein called beclin 1. This peptide is a potent inducer of autophagy in mammalian cells and in vivo in mice and was effective in the clearance of several viruses including chikungunya virus, West Nile virus and HIV-1.

Could this small autophagy-inducing peptide may be effective in the prevention and treatment of human diseases?

PR-Set7 Is a Nucleosome-Specific Methyltransferase that Modifies Lysine 20 of

Histone H4 and Is Associated with Silent Chromatin

K Nishioka, JC Rice, K Sarma, H Erdjument-Bromage, …, D Reinberg.   Molecular Cell, Vol. 9, 1201–1213, June, 2002, Copyright 2002 by Cell Press   http://www.cell.com/molecular-cell/abstract/S1097-2765(02)00548-8

http://www.sciencedirect.com/science/article/pii/S1097276502005488           http://www.ncbi.nlm.nih.gov/pubmed/12086618
http://www.cienciavida.cl/publications/b46e8d324fa4aefa771c4d6ece4d2e27_PR-Set7_Is_a_Nucleosome-Specific.pdf

We have purified a human histone H4 lysine 20methyl-transferase and cloned the encoding gene, PR/SET07. A mutation in Drosophila pr-set7 is lethal: second in-star larval death coincides with the loss of H4 lysine 20 methylation, indicating a fundamental role for PR-Set7 in development. Transcriptionally competent regions lack H4 lysine 20 methylation, but the modification coincided with condensed chromosomal regions polytene chromosomes, including chromocenter euchromatic arms. The Drosophila male X chromosome, which is hyperacetylated at H4 lysine 16, has significantly decreased levels of lysine 20 methylation compared to that of females. In vitro, methylation of lysine 20 and acetylation of lysine 16 on the H4 tail are competitive. Taken together, these results support the hypothesis that methylation of H4 lysine 20 maintains silent chromatin, in part, by precluding neighboring acetylation on the H4 tail.

Next-Generation Sequencing vs. Microarrays

Shawn C. Baker, Ph.D., CSO of BlueSEQ
GEN Feb 2013
With recent advancements and a radical decline in sequencing costs, the popularity of next generation sequencing (NGS) has skyrocketed. As costs become less prohibitive and methods become simpler and more widespread, researchers are choosing NGS over microarrays for more of their genomic applications. The immense number of journal articles citing NGS technologies it looks like NGS is no longer just for the early adopters. Once thought of as cost prohibitive and technically out of reach, NGS has become a mainstream option for many laboratories, allowing researchers to generate more complete and scientifically accurate data than previously possible with microarrays.

Gene Expression

Researchers have been eager to use NGS for gene expression experiments for a detailed look at the transcriptome. Arrays suffer from fundamental ‘design bias’ —they only return results from those regions for which probes have been designed. The various RNA-Seq methods cover all aspects of the transcriptome without any a priori knowledge of it, allowing for the analysis of such things as novel transcripts, splice junctions and noncoding RNAs. Despite NGS advancements, expression arrays are still cheaper and easier when processing large numbers of samples (e.g., hundreds to thousands).
Methylation
While NGS unquestionably provides a more complete picture of the methylome, whole genome methods are still quite expensive. To reduce costs and increase throughput, some researchers are using targeted methods, which only look at a portion of the methylome. Because details of exactly how methylation impacts the genome and transcriptome are still being investigated, many researchers find a combination of NGS for discovery and microarrays for rapid profiling.

Diagnostics

They are interested in ease of use, consistent results, and regulatory approval, which microarrays offer. With NGS, there’s always the possibility of revealing something new and unexpected. Clinicians aren’t prepared for the extra information NGS offers. But the power and potential cost savings of NGS-based diagnostics is alluring, leading to their cautious adoption for certain tests such as non-invasive prenatal testing.
Cytogenetics
Perhaps the application that has made the least progress in transitioning to NGS is cytogenetics. Researchers and clinicians, who are used to using older technologies such as karyotyping, are just now starting to embrace microarrays. NGS has the potential to offer even higher resolution and a more comprehensive view of the genome, but it currently comes at a substantially higher price due to the greater sequencing depth. While dropping prices and maturing technology are causing NGS to make headway in becoming the technology of choice for a wide range of applications, the transition away from microarrays is a long and varied one. Different applications have different requirements, so researchers need to carefully weigh their options when making the choice to switch to a new technology or platform. Regardless of which technology they choose, genomic researchers have never had more options.

Sequencing Hones In on Targets

Greg Crowther, Ph.D.

GEN Feb 2013

Cliff Han, PhD, team leader at the Joint Genome Institute in the Los Alamo National Lab, was one of a number of scientists who made presentations regarding target enrichment at the “Sequencing, Finishing, and Analysis in the Future” (SFAF) conference in Santa Fe, which was co-sponsored by the Los Alamos National Laboratory and DOE Joint Genome Institute. One of the main challenges is that of target enrichment: the selective sequencing of genomic or transcriptomic regions. The polymerase chain reaction (PCR) can be considered the original target-enrichment technique and continues to be useful in contexts such as genome finishing. “One target set is the unique gaps—the gaps in the unique sequence regions. Another is to enrich the repetitive sequences…ribosomal RNA regions, which together are about 5 kb or 6 kb.” The unique-sequence gaps targeted for PCR with 40-nucleotide primers complementary to sequences adjacent to the gaps, did not yield the several-hundred-fold enrichment expected based on previously published work. “We got a maximum of 70-fold enrichment and generally in the dozens of fold of enrichment,” noted Dr. Han.

“We enrich the genome, put the enriched fragments onto the Pacific Biosciences sequencer, and sequence the repeats,” continued Dr. Han. “In many parts of the sequence there will be a unique sequence anchored at one or both ends of it, and that will help us to link these scaffolds together.” This work, while promising, will remain unpublished for now, as the Joint Genome Institute has shifted its resources to other projects.
At the SFAF conference Dr. Jones focused on going beyond basic target enrichment and described new tools for more efficient NGS research. “Hybridization methods are flexible and have multiple stop-start sites, and you can capture very large sizes, but they require library prep,” said Jennifer Carter Jones, Ph.D., a genomics field applications scientist at Agilent. “With PCR-based methods, you have to design PCR primers and you’re doing multiplexed PCR, so it’s limited in the size that you can target. But the workflow is quick because there’s no library preparation; you’re just doing PCR.” She discussed Agilent’s recently acquired HaloPlex technology, a hybrid system that includes both a hybridization step and a PCR step. Because no library preparation is required, sequencing results can be obtained in about six hours, making it suitable for clinical uses. However, the hybridization step allows capture of targets of up to 5 megabases—longer than purely PCR-based methods can deliver. The Agilent talk also provided details on the applications of SureSelect, the company’s hybridization technology, to Methyl-Seq and RNA-Seq research. With this technology, 120-mer baits hybridize to targets, then are pulled down with streptavidin-coated magnetic beads.
These are selections from the SFAF conference, which is expected to be a boost to work on the microbiome, and lead to infectious disease therapeutic approaches.

Summary

We have finished a breathtaking ride through the genomic universe in several sessions.  This has been a thorough review of genomic structure and function in cellular regulation.  The items that have been discussed and can be studied in detail include:

  1.  the classical model of the DNA structure
  2. the role of ubiquitinylation in managing cellular function and in autophagy, mitophagy, macrophagy, and protein degradation
  3. the nature of the tight folding of the chromatin in the nucleus
  4. intramolecular bonds and short distance hydrophobic and hydrophilic interactions
  5. trace metals in molecular structure
  6. nuclear to membrane interactions
  7. the importance of the Human Genome Project followed by Encode
  8. the Fractal nature of chromosome structure
  9. the oligomeric formation of short sequences and single nucletide polymorphisms (SNPs)and the potential to identify drug targets
  10. Enzymatic components of gene regulation (ligase, kinases, phosphatases)
  11. Methods of computational analysis in genomics
  12. Methods of sequencing that have become more accurate and are dropping in cost
  13. Chromatin remodeling
  14. Triplex and quadruplex models not possible to construct at the time of Watson-Crick
  15. sequencing errors
  16. propagation of errors
  17. oxidative stress and its expected and unintended effects
  18. origins of cardiovascular disease
  19. starvation and effect on protein loss
  20. ribosomal damage and repair
  21. mitochondrial damage and repair
  22. miscoding and mutational changes
  23. personalized medicine
  24. Genomics to the clinics
  25. Pharmacotherapy horizons
  26. driver mutations
  27. induced pluripotential embryonic stem cell (iPSCs)
  28. The association of key targets with disease
  29. The real possibility of moving genomic information to the bedside
  30. Requirements for the next generation of electronic health record to enable item 29

Other Related articles on this Open Access Online Scientific Journal, include the following:

https://pharmaceuticalintelligence.com/2013/01/14/oogonial-stem-cells-purified-a-view-towards-the-future-of-reproductive-biology/   SSaha

https://pharmaceuticalintelligence.com/2012/10/22/blood-vessel-generating-stem-cells-discovered/ RSaxena

https://pharmaceuticalintelligence.com/2012/08/22/a-possible-light-by-stem-cell-therapy-in-painful-dark-of-osteoarthritis-kartogenin-a-small-molecule-differentiates-stem-cells-to-chondrocyte-healthy-cartilage-cells/   ASarkar and RSaxena

https://pharmaceuticalintelligence.com/2012/08/07/human-embryonic-pluripotent-stem-cells-and-healing-post-myocardial-infarction/    LHB

https://pharmaceuticalintelligence.com/2013/02/03/genome-wide-detection-of-single-nucleotide-and-copy-number-variation-of-a-single-human-cell/  SJWilliams

https://pharmaceuticalintelligence.com/2013/01/09/gene-therapy-into-healthy-heart-muscle-reprogramming-scar-tissue-in-damaged-hearts/ ALev-Ari

https://pharmaceuticalintelligence.com/2013/01/03/differentiation-therapy-epigenetics-tackles-solid-tumors/  SJWilliams

https://pharmaceuticalintelligence.com/2012/12/09/naotech-therapy-for-breast-cancer/  TBarliya

Read Full Post »


Reporter: Aviva Lev-Ari, PhD, RN

Set of Papers Outline ENCODE Findings as Consortium Looks Ahead to Future Studies

NEW YORK (GenomeWeb News) – An international collaboration involving more than 400 researchers working to characterize gene regulatory networks in the human genome is publishing dozens of new studies this week.

In papers appearing in NatureScienceGenome ResearchGenome BiologyJournal of Biological Chemistry, and elsewhere, members of the Encyclopedia of DNA Elements, or ENCODE, consortium describe approaches used to define some four million regulatory regions in the genome, among other things. All told, the team explained, ENCODE efforts have made it possible assign biological functions to around 80 percent of genome sequences — filling in large gaps left by studies that focused on protein-coding sequences alone.

“We found that a much bigger part of the genome — a surprising amount, in fact — is involved in controlling when and where proteins are produced, than in simply manufacturing the building blocks,” ENCODE’s lead analysis coordinator Ewan Birney, associate director of the European Molecular Biology Laboratory European Bioinformatics Institute, said in a statement.

“This concept of ‘junk DNA,’ which has been sort of perpetuated for the past 20 years or so is really not accurate,” ENCODE researcher Rick Myers, director of the HudsonAlpha Institute for Biotechnology, said during a telephone briefing with reporters today. “Most of the genome — more than 80 percent of the base pairs in the genome — has some biological activity, some biological function.”

Researchers participating in a complementary effort within the larger ENCODE project, known as GENCODE, more completely characterize the coding portions of the genome. “As part of the ENCODE project, we both tidied up the protein-coding genes and we also found many non-coding RNA genes as well,” Birney said during today’s telebriefing.

Based on the success of ENCODE so far, the project is expected to be extended by another four years or so. The amount of new funding from the National Human Genome Research Institute for that follow-up work is expected to be as high as $123 million.

“Later this month, NHGRI will be announcing a new round of funding that will take the ENCODE project into its next phase,” NHGRI Director Eric Green said during the call.

Studies done in the decade or so since the human genome was deciphered have highlighted how little of the genome is actually comprised of gene sequences. With the realization that only around 2 percent of the genome is dedicated to protein-coding functions came a spate of speculation about the role of the other 98 percent of genome.

While this portion of the genome was suspected of harboring regulatory sequences, the extent of that regulation and its impact on coding sequences in human tissues over time was not known.

“When the Human Genome Project ended in 2003, we quickly realized that we understood the meaning of only a very small percent of the human genome’s letters,” Green explained. “We did know the genetic code for determining the order of amino acids and proteins, but we understood precious little about the signals that turned genes on or off — or that controlled the amount of proteins produced in different tissues.”

To begin studying such control networks systematically, the international ENCODE consortium kicked off the main phase of its analyses in 2007, following an earlier pilot study.

NHGRI has provided $123 million for the project over the past five years. Another $30 million went to support the development of ENCODE-related technologies since the ENCODE pilot started in 2003, while $40.6 million from NHGRI went towards the pilot itself.

During the study’s main phase, investigators from nearly three-dozen labs around the world took multi-pronged approaches to assess transcription factor binding patterns, histone modification patterns, chromatin structure signatures and other features of the genome that interact with one another to control gene expression over time and across different tissues in the body.

To accomplish the roughly 1,600 experiments done to test some 180 cell types for ENCODE, teams turned to methods such as chromatin immunoprecipitation coupled with sequencing to define the genome-wide binding patterns for more than 100 different transcription factors, for example, while other strategies were used to profile DNA methylation patterns, chromatin features, and so forth.

“It’s really a detailed hierarchy, where proteins bind and epigenetic marks — like DNA methylation and other marks — precisely cooperate and regulate how the genes are going to get turned on [or off] and the amount of this,” Myers said. “These complex networks are one of the big components of the contributions of the 30 papers that are being published today.”

For example, a University of Washington-led team reporting in Science online todaydefined millions of regulatory regions, including some that are operational during normal development, by taking advantage of an enzyme known as DNase I, which chops off DNA specifically at open chromatin sites in the genome. That group found that more than three-quarters of disease-associated variants identified in genome-wide association studies fall in parts of the genome that overlap with regulatory sites.

“We now know that the majority of these changes that are associated with common diseases and traits that don’t fall within genes actually occur within the gene-controlling switches,” University of Washington genome sciences researcher John Stamatoyannopoulos, senior author on that study, said during today’s telebriefing. “This phenomenon is not confined to a particular type of disease. It seems to be present across the board for a very wide variety of different diseases and traits.”

Results from such analyses also hint that some outwardly unrelated conditions might be traced back to similar regulatory processes. And, researchers say, by bringing together information on active regulatory regions with disease-risk variants, it may be possible to define new functionally important tissues for certain conditions.

“By creating these extensive blueprints of the control circuitry, we’re now exposing previously hidden connections between different kinds of diseases that may explain common clinical features,” Stamatoyannopoulos said.

“This has also allowed us to see that the GWAS studies that have been performed contain far more information than was previously believed,” he added, “because hundreds of additional DNA changes that were not thought to be important also appear to affect these gene-controlling switches.”

The new data are also expected to help in understanding genetic disease and interpreting information from personal genomes, according to Michael Snyder, an ENCODE investigator and director of Stanford University’s Center of Genomics and Personalized Medicine.

“We believe the ENCODE project will have a profound impact on personal genomes and, ultimately on personalized medicine,” Snyder told reporters. “We can now better see what personal variants do, in terms of causing phenotypic differences, drug responses, and disease risk.”

Many of the studies stemming from ENCODE can be viewed through a Nature,Genome Research, and Genome Biology-conceived website that links ENCODE papers that share themes or “threads” that are related to one another.

Along with the newly published papers, the ENCODE team is making data available to other members of the research community through the project’s website. Data from studies can also be accessed through an ENCODE browser housed at the University of California at Santa Cruz or via NCBI or EBI sites.

“For basic researchers, the ENCODE data represents a powerful resource for understanding fundamental questions about how life is encoded in our genome,” NHGRI’s Green said. “For more clinically-oriented researchers, the ENCODE data provide key information about which genome sequences are functionally important.”

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    August 10, 2012 / GenomeWeb Daily News
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    Source:

    NEWS & VIEWS

    52 | NATURE | VOL 489 | 6 SEPTEMBER 2012

    FORUM: Genomics

    ENCODE explained

    The Encyclopedia of DNA Elements (ENCODE) project dishes up a hearty banquet of data that illuminate the roles of the functional elements of the human genome. Here, five scientists describe the project and discuss how the data are influencing research directions across many fields. See Articles p.57, p.75, p.83, p.91, p.101 & Letter p.109

    Serving up a genome feast

    JOSEPH R. ECKER

    Starting with a list of simple ingredients and blending them in the precise amounts needed to prepare a gourmet meal is a challenging task. In many respects, this task is analogous to the goal of the ENCODE project1, the recent progress of which is described in this issue2–7. The project aims to fully describe the list of common ingredients (functional elements) that make up the human genome (Fig. 1). When mixed in the right proportions, these ingredients constitute the information needed to build all the types of cells, body organs and, ultimately, an entire person from a single genome.

    The ENCODE pilot project8 focused on just 1% of the genome — a mere appetizer — and its results hinted that the list of human genes was incomplete. Although there was scepticism about the feasibility of scaling up the project to the entire genome and to many hundreds of cell types, recent advances in low-cost, rapid DNA-sequencing technology radically changed that view9. Now the ENCODE consortium presents a menu of 1,640 genome-wide data sets prepared from 147 cell types, providing a six-course serving of papers in Nature, along with many companion publications in other journals.

    One of the more remarkable findings described in the consortium’s ‘entrée’ paper (page 57)2 is that 80% of the genome contains elements linked to biochemical functions, dispatching the widely held view that the human genome is mostly ‘junk DNA’. The authors report that the space between genes is filled with enhancers (regulatory DNA elements), promoters (the sites at which DNA’s transcription into RNA is initiated) and numerous previously overlooked regions that encode RNA transcripts that are not translated into proteins but might have regulatory roles. Of note, these results show that many DNA variants previously correlated with certain diseases lie within or very near non-coding functional DNA elements, providing new leads for linking genetic variation and disease.

    The five companion articles3–7 dish up diverse sets of genome-wide data regarding the mapping of transcribed regions, DNA binding of regulatory proteins (transcription factors) and the structure and modifications of chromatin (the association of DNA and proteins that makes up chromosomes), among other delicacies.

    Djebali and colleagues3 (page 101) describe ultra-deep sequencing of RNAs prepared from many different cell lines and from specific compartments within the cells. They conclude that about 75% of the genome is transcribed at some point in some cells, and that genes are highly interlaced with overlapping transcripts that are synthesized from both DNA strands. These findings force a rethink of the definition of a gene and of the minimum unit of heredity.

    Moving on to the second and third courses, Thurman et al.4 and Neph et al.5 (pages 75 and 83) have prepared two tasty chromatin-related treats. Both studies are based on the DNase I hypersensitivity assay, which detects genomic regions at which enzyme access to, and subsequent cleavage of, DNA is unobstructed by chromatin proteins. The authors identified cell-specific patterns of DNase I hypersensitive sites that show remarkable concordance with experimentally determined and computationally predicted binding sites of transcription factors. Moreover, they have doubled the number of known recognition sequences for DNA-binding proteins in the human genome, and have revealed a 50-base-pair ‘footprint’ that is present in thousands of promoters5.

    The next course, provided by Gerstein and colleagues6 (page 91) examines the principles behind the wiring of transcription-factor networks. In addition to assigning relatively simple functions to genome elements (such as ‘protein X binds to DNA element Y’), this study attempts to clarify the hierarchies of transcription factors and how the intertwined networks arise.

    Beyond the linear organization of genes and transcripts on chromosomes lies a more complex (and still poorly understood) network of chromosome loops and twists through which promoters and more distal elements, such as enhancers, can communicate their regulatory information to each other. In the final course of the ENCODE genome feast, Sanyal and colleagues7 (page 109) map more than 1,000 of these long-range signals in each cell type. Their findings begin to overturn the long-held (and probably oversimplified) prediction that the regulation of a gene is dominated by its proximity to the closest regulatory elements.

    One of the major future challenges for ENCODE (and similarly ambitious projects) will be to capture the dynamic aspects of gene regulation. Most assays provide a single snapshot of cellular regulatory events, whereas a time series capturing how such processes change is preferable. Additionally, the examination of large batches of cells — as required for the current assays — may present too simplified a view of the underlying regulatory complexity, because individual cells in a batch (despite being genetically identical) can sometimes behave in different ways. The development of new technologies aimed at the simultaneous capture of multiple data types, along with their regulatory dynamics in single cells, would help to tackle these issues.

    A further challenge is identifying how the genomic ingredients are combined to assemble the gene networks and biochemical pathways that carry out complex functions, such as cell-to-cell communication, which enable organs and tissues to develop. An even greater challenge will be to use the rapidly growing body

    “These findings force a rethink of the definition of a gene and of the minimum unit of heredity.”ENCODEEncyclopedia of DNA Elementsnature.com/encode

    © 2012 Macmillan Publishers Limited. All rights reserved

    RESEARCH

    NEWS & VIEWS

    6 SEPTEMBER 2012 | VOL 489 | NATURE | 53

    of data from genome-sequencing projects to understand the range of human phenotypes (traits), from normal developmental processes, such as ageing, to disorders such as Alzheimer’s disease10.

    Achieving these ambitious goals may require a parallel investment of functional studies using simpler organisms — for example, of the type that might be found scampering around the floor, snatching up crumbs in the chefs’ kitchen. All in all, however, the ENCODE project has served up an all-you-can-eat feast of genomic data that we will be digesting for some time. Bon appétit!

    Joseph R. Ecker is at the Howard Hughes Medical Institute and the Salk Institute for Biological Studies, La Jolla, California 92037, USA.

    e-mail: ecker@salk.eduNucleosomeHistoneChromatinmodicationsLong-rangechromatin interactionsFunctionalgenomicelementsDNase IhypersensitivesitesDNA methylationChromosomeDNALong-rangeregulatoryelementsProtein-codingand non-codingtranscriptsPromoterarchitectureTranscriptionfactorTranscriptionmachineryTranscription-factorbinding sitesTranscribed region

    Figure 1 | Beyond the sequence. The ENCODE project2–7 provides information on the human genome far beyond that contained within the DNA sequence — it describes the functional genomic elements that orchestrate the development and function of a human. The project contains data about the degree of DNA methylation and chemical modifications to histones that can influence the rate of transcription of DNA into RNA molecules (histones are the proteins around which DNA is wound to form chromatin). ENCODE also examines long-range chromatin interactions, such as looping, that alter the relative proximities of different chromosomal regions in three dimensions and also affect transcription. Furthermore, the project describes the binding activity of transcription-factor proteins and the architecture (location and sequence) of gene-regulatory DNA elements, which include the promoter region upstream of the point at which transcription of an RNA molecule begins, and more distant (long-range) regulatory elements. Another section of the project was devoted to testing the accessibility of the genome to the DNA-cleavage protein DNase I. These accessible regions, called DNase I hypersensitive sites, are thought to indicate specific sequences at which the binding of transcription factors and transcription-machinery proteins has caused nucleosome displacement. In addition, ENCODE catalogues the sequences and quantities of RNA transcripts, from both non-coding and protein-coding regions.

    Expression control

    WENDY A. BICKMORE

    Once the human genome had been sequenced, it became apparent that an encyclopaedic knowledge of chromatin organization would be needed if we were to understand how gene expression is regulated. The ENCODE project goes a long way to achieving this goal and highlights the pivotal role of transcription factors in sculpting the chromatin landscape.

    Although some of the analyses largely confirm conclusions from previous smaller-scale studies, this treasure trove of genome-wide data provides fresh insight into regulatory pathways and identifies prodigious numbers of regulatory elements. This is particularly so for Thurman and colleagues’ data4 regarding DNase I hypersensitive sites (DHSs) and for Gerstein and colleagues’ results6 concerning DNA binding of transcription factors. DHSs are genomic regions that are accessible to enzymatic cleavage as a result of the displacement of nucleosomes (the basic units of chromatin) by DNA-binding proteins (Fig. 1). They are the hallmark of cell-type-specific enhancers, which are often located far away from promoters.

    The ENCODE papers expose the profusion of DHSs — more than 200,000 per cell type, far outstripping the number of promoters — and their variability between cell types. Through the simultaneous presence in the same cell type of a DHS and a nearby active promoter, the researchers paired half a million enhancers with their probable target genes. But this leaves

    © 2012 Macmillan Publishers Limited. All rights reserved

    RESEARCH

    NEWS & VIEWS

    more than 2 million putative enhancers without known targets, revealing the enormous expanse of the regulatory genome landscape that is yet to be explored. Chromosome-conformation-capture methods that detect long-range physical associations between distant DNA regions are attempting to bridge this gap. Indeed, Sanyal and colleagues7 applied these techniques to survey such associations across 1% of the genome.

    The ENCODE data start to paint a picture of the logic and architecture of transcriptional networks, in which DNA binding of a few high-affinity transcription factors displaces nucleosomes and creates a DHS, which in turn facilitates the binding of further, lower-affinity factors. The results also support the idea that transcription-factor binding can block DNA methylation (a chemical modification of DNA that affects gene expression), rather than the other way around — which is highly relevant to the interpretation of disease-associated sites of altered DNA methylation11.

    The exquisite cell-type specificity of regulatory elements revealed by the ENCODE studies emphasizes the importance of having appropriate biological material on which to test hypotheses. The researchers have focused their efforts on a set of well-established cell lines, with selected assays extended to some freshly isolated cells. Challenges for the future include following the dynamic changes in the regulatory landscape during specific developmental pathways, and understanding chromatin structure in tissues containing heterogeneous cell populations.

    Wendy A. Bickmore is in the Medical Research Council Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK.

    e-mail: wendy.bickmore@igmm.ed.ac.uk 

    “The results imply that sequencing studies focusing on protein-coding sequences risk missing crucial parts of the genome.”

    11 Years Ago

    The draft human genome

    OUR GENOME UNVEILED

    Unless the human genome contains a lot of genes that are opaque to our computers, it is clear that we do not gain our undoubted complexity over worms and plants by using many more genes. Understanding what does give us our complexity — our enormous behavioural repertoire, ability to produce conscious action, remarkable physical coordination (shared with other vertebrates), precisely tuned alterations in response to external variations of the environment, learning, memory … need I go on? — remains a challenge for the future.

    David Baltimore

    From Nature 15 February 2001

    GENOME SPEAK

    With the draft in hand, researchers have a new tool for studying the regulatory regions and networks of genes. Comparisons with other genomes should reveal common regulatory elements, and the environments of genes shared with other species may offer insight into function and regulation beyond the level of individual genes. The draft is also a starting point for studies of the three-dimensional packing of the genome into a cell’s nucleus. Such packing is likely to influence gene regulation … The human genome lies before us, ready for interpretation.

    Peer Bork and Richard Copley

    From Nature 15 February 2001

    Non-codingbut functional

    INÊS BARROSO

    The vast majority of the human genome does not code for proteins and, until now, did not seem to contain defined gene-regulatory elements. Why evolution would maintain large amounts of ‘useless’ DNA had remained a mystery, and seemed wasteful. It turns out, however, that there are good reasons to keep this DNA. Results from the ENCODE project2–8 show that most of these stretches of DNA harbour regions that bind proteins and RNA molecules, bringing these into positions from which they cooperate with each other to regulate the function and level of expression of protein-coding genes. In addition, it seems that widespread transcription from non-coding DNA potentially acts as a reservoir for the creation of new functional molecules, such as regulatory RNAs.

    What are the implications of these results for genetic studies of complex human traits and disease? Genome-wide association studies (GWAS), which link variations in DNA sequence with specific traits and diseases, have in recent years become the workhorse of the field, and have identified thousands of DNA variants associated with hundreds of complex traits (such as height) and diseases (such as diabetes). But association is not causality, and identifying those variants that are causally linked to a given disease or trait, and understanding how they exert such influence, has been difficult. Furthermore, most of these associated variants lie in non-coding regions, so their functional effects have remained undefined.

    The ENCODE project provides a detailed map of additional functional non-coding units in the human genome, including some that have cell-type-specific activity. In fact, the catalogue contains many more functional non-coding regions than genes. These data show that results of GWAS are typically enriched for variants that lie within such non-coding functional units, sometimes in a cell-type-specific manner that is consistent with certain traits, suggesting that many of these regions could be causally linked to disease. Thus, the project demonstrates that non-coding regions must be considered when interpreting GWAS results, and it provides a strong motivation for reinterpreting previous GWAS findings. Furthermore, these results imply that sequencing studies focusing on protein-coding sequences (the ‘exome’) risk missing crucial parts of the genome and the ability to identify true causal variants.

    However, although the ENCODE catalogues represent a remarkable tour de force, they contain only an initial exploration of the depths of our genome, because many more cell types must yet be investigated. Some of the remaining challenges for scientists searching for causal disease variants lie in: accessing data derived from cell types and tissues relevant to the disease under study; understanding how these functional units affect genes that may be distantly located7; and the ability to generalize such results to the entire organism.

    Inês Barroso is at the Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK, and at the University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Cambridge, UK.e-mail: ib1@sanger.ac.uk5 4 | N AT U R E | VO L 4 8 9 | 6 S E P T E M B E R 2 0 1 2

    © 2012 Macmillan Publishers Limited. All rights reserved

    Evolution and the code

    JONATHAN K. PRITCHARD & YOAV GILAD

    One of the great challenges in evolutionary biology is to understand how differences in DNA sequence between species determine differences in their phenotypes. Evolutionary change may occur both through changes in protein-coding sequences and through sequence changes that alter gene regulation.

    There is growing recognition of the importance of this regulatory evolution, on the basis of numerous specific examples as well as on theoretical grounds. It has been argued that potentially adaptive changes to protein-coding sequences may often be prevented by natural selection because, even if they are beneficial in one cell type or tissue, they may be detrimental elsewhere in the organism. By contrast, because gene-regulatory sequences are frequently associated with temporally and spatially specific gene-expression patterns, changes in these regions may modify the function of only certain cell types at specific times, making it more likely that they will confer an evolutionary advantage12.

    However, until now there has been little information about which genomic regions have regulatory activity. The ENCODE project has provided a first draft of a ‘parts list’ of these regulatory elements, in a wide range of cell types, and moves us considerably closer to one of the key goals of genomics: understanding the functional roles (if any) of every position in the human genome.

    Nonetheless, it will take a great deal of work to identify the critical sequence changes in the newly identified regulatory elements that drive functional differences between humans and other species. There are some precedents for identifying key regulatory differences (see, for example, ref. 13), but ENCODE’s improved identification of regulatory elements should greatly accelerate progress in this area. The data may also allow researchers to begin to identify sequence alterations occurring simultaneously in multiple genomic regions, which, when added together, drive phenotypic change — a process called polygenic adaptation14.

    However, despite the progress brought by the ENCODE consortium and other research groups, it remains difficult to discern with confidence which variants in putative regulatory regions will drive functional changes, and what these changes will be. We also still have an incomplete understanding of how regulatory sequences are linked to target genes. Furthermore, the ENCODE project focused mainly on the control of transcription, but many aspects of post-transcriptional regulation, which may also drive evolutionary changes, are yet to be fully explored.

    Nonetheless, these are exciting times for studies of the evolution of gene regulation. With such new resources in hand, we can expect to see many more descriptions of adaptive regulatory evolution, and how this has contributed to human evolution.

    Jonathan K. Pritchard and Yoav Gilad are in the Department of Human Genetics, University of Chicago, Chicago 60637 Illinois, USA. J.K.P. is also at the Howard Hughes Medical Institute, University of Chicago.

    e-mails: pritch@uchicago.edu; gilad@uchicago.edu 

    From catalogue to function

    ERAN SEGAL

    Projects that produce unprecedented amounts of data, such as the human genome project15 or the ENCODE project, present new computational and data-analysis challenges and have been a major force driving the development of computational methods in genomics. The human genome project produced one bit of information per DNA base pair, and led to advances in algorithms for sequence matching and alignment. By contrast, in its 1,640 genome-wide data sets, ENCODE provides a profile of the accessibility, methylation, transcriptional status, chromatin structure and bound molecules for every base pair. Processing the project’s raw data to obtain this functional information has been an immense effort.

    For each of the molecular-profiling methods used, the ENCODE researchers devised novel processing algorithms designed to remove outliers and protocol-specific biases, and to ensure the reliability of the derived functional information. These processing pipelines and quality-control measures have been adapted by the research community as the standard for the analysis of such data. The high quality of the functional information they produce is evident from the exquisite detail and accuracy achieved, such as the ability to observe the crystallographic topography of protein–DNA interfaces in DNase I footprints5, and the observation of more than one-million-fold variation in dynamic range in the concentrations of different RNA transcripts3.

    But beyond these individual methods for data processing, the profound biological insights of ENCODE undoubtedly come from computational approaches that integrated multiple data types. For example, by combining data on DNA methylation, DNA accessibility and transcription-factor expression. Thurman et al.4 provide fascinating insight into the causal role of DNA methylation in gene silencing. They find that transcription-factor binding sites are, on average, less frequently methylated in cell types that express those transcription factors, suggesting that binding-site methylation often results from a passive mechanism that methylates sites not bound by transcription factors.

    Despite the extensive functional information provided by ENCODE, we are still far from the ultimate goal of understanding the function of the genome in every cell of every person, and across time within the same person. Even if the throughput rate of the ENCODE profiling methods increases dramatically, it is clear that brute-force measurement of this vast space is not feasible. Rather, we must move on from descriptive and correlative computational analyses, and work towards deriving quantitative models that integrate the relevant protein, RNA and chromatin components. We must then describe how these components interact with each other, how they bind the genome and how these binding events regulate transcription.

    If successful, such models will be able to predict the genome’s function at times and in settings that have not been directly measured. By allowing us to determine which assumptions regarding the physical interactions of the system lead to models that better explain measured patterns, the ENCODE data provide an invaluable opportunity to address this next immense computational challenge. ■

    Eran Segal is in the Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.

    e-mail: eran.segal@weizmann.ac.il

    1. The ENCODE Project Consortium Science 306, 636–640 (2004).

    2. The ENCODE Project Consortium Nature 489, 57–74 (2012).

    3. Djebali, S. et al. Nature 489, 101–108 (2012).

    4. Thurman, R. E. et al. Nature 489, 75–82 (2012).

    5. Neph, S. et al. Nature 489, 83–90 (2012).

    6. Gerstein, M. B. et al. Nature 489, 91–100 (2012).

    7. Sanyal, A., Lajoie, B., Jain, G. & Dekker, J. Nature 489, 109–113 (2012).

    8. Birney, E. et al. Nature 447, 799–816 (2007).

    9. Mardis, E. R. Nature 470, 198–203 (2011).

    10. Gonzaga-Jauregui, C., Lupski, J. R. & Gibbs, R. A. Annu. Rev. Med. 63, 35–61 (2012).

    11. Sproul, D. et al. Proc. Natl Acad. Sci. USA 108, 4364–4369 (2011).

    12. Carroll, S. B. Cell 134, 25–36 (2008).

    13. Prabhakar, S. et al. Science 321, 1346–1350 (2008).

    14. Pritchard, J. K., Pickrell, J. K. & Coop, G. Curr. Biol. 20, R208–R215 (2010).

    15. Lander, E. S. et al. Nature 409, 860–921 (2001).

    “The high quality of the functional information produced is evident from the exquisite detail and accuracy achieved.” 

    6 S E P T E M B E R 2 0 1 2 | VO L 4 8 9 | N AT U R E | 5 5 NEWS & VIEWS RESEARCH © 2012 Macmillan Publishers Limited. All rights reserved

    http://www.sciencemag.org SCIENCE VOL 337 7 SEPTEMBER 2012 1159

    NEWS&ANALYSIS

    When researchers fi rst sequenced the human

    genome, they were astonished by how few

    traditional genes encoding proteins were

    scattered along those 3 billion DNA bases.

    Instead of the expected 100,000 or more

    genes, the initial analyses found about 35,000

    and that number has since been whittled down

    to about 21,000. In between were megabases

    of “junk,” or so it seemed.

    This week, 30 research papers, including

    six in Nature and additional papers published

    by Science, sound the death knell for

    the idea that our DNA is mostly littered with

    useless bases. A decadelong project, the

    Encyclopedia of DNA Elements (ENCODE),

    has found that 80% of the human genome

    serves some purpose, biochemically speaking.

    “I don’t think anyone would have anticipated

    even close to the amount of sequence

    that ENCODE has uncovered that looks like

    it has functional importance,” says John A.

    Stamatoyannopoulos, an ENCODE re searcher

    at the University of Washington, Seattle.

    Beyond defi ning proteins, the DNA bases

    highlighted by ENCODE specify landing

    spots for proteins that infl uence gene activity,

    strands of RNA with myriad roles, or

    simply places where chemical modifi cations

    serve to silence stretches of our chromosomes.

    These results are going “to change

    the way a lot of [genomics] concepts are

    written about and presented in textbooks,”

    Stamatoyannopoulos predicts.

    The insights provided by ENCODE into

    how our DNA works are already clarifying

    genetic risk factors for a variety of diseases

    and offering a better understanding of gene

    regulation and function. “It’s a treasure trove

    of information,” says Manolis Kellis, a computational

    biologist at Massachusetts Institute

    of Technology (MIT) in Cambridge who analyzed

    data from the project.

    The ENCODE effort has revealed that

    a gene’s regulation is far more complex

    than previously thought, being infl uenced

    by multiple stretches of regulatory DNA

    located both near and far from the gene

    itself and by strands of RNA not translated

    into proteins, so-called noncoding RNA.

    “What we found is how beautifully complex

    the biology really is,” says Jason Lieb,

    an ENCODE researcher at the University of

    North Carolina, Chapel Hill.

    Throughout the 1990s, various researchers

    called the idea of junk DNA into question.

    With the human genome in hand, the

    National Human Genome Research Institute

    (NHGRI) in Bethesda, Maryland, decided it

    wanted to fi nd out once and for all how much

    of the genome was a wasteland with no functional

    purpose. In 2003, it funded a pilot

    ENCODE, in which 35 research teams analyzed

    44 regions of the genome—30 million

    bases in all, about 1% of the total genome. In

    2007, the pilot project’s results revealed that

    much of this DNA sequence was active in

    some way. The work called into serious question

    our gene-centric view of the genome,

    fi nding extensive RNA-generating activity

    beyond traditional gene boundaries (Science,

    15 June 2007, p. 1556). But the question

    remained whether the rest of the genome was

    like this 1%. “We want to know what all the

    bases are doing,” says Yale University bioinformatician

    Mark Gerstein.

    Teams at 32 institutions worldwide have

    now carried out scores of tests, generating

    1640 data sets. While the pilot phase tests

    depended on computer chip–like devices

    called microarrays to analyze DNA samples,

    the expanded phase benefi ted from the arrival

    of new sequencing technology, which made it

    cost-effective to directly read the DNA bases.

    Taken together, the tests present “a greater

    idea of what the landscape of the genome

    looks like,” says NHGRI’s Elise Feingold.

    Because the parts of the genome used

    could differ among various kinds of cells,

    ENCODE needed to look at DNA function

    in multiple types of cells and tissues. At

    fi rst the goal was to study intensively three

    types of cells. They included GM12878, the

    immature white blood cell line used in the

    1000 Genomes Project, a large-scale effort to

    catalog genetic variation across humans; a leukemia

    cell line called K562; and an approved

    human embryonic stem cell line, H1-hESC.

    As ENCODE was ramping up, new

    sequencing technology brought the cost of

    sequencing down enough to make it feasible

    to test extensively even more cell types.

    ENCODE added a liver cancer cell line,

    HepG2; the laboratory workhorse cancer cell

    line, HeLa S3; and human umbilical cord tissue

    to the mix. Another 140 cell types were

    studied to a much lesser degree.

    In these cells, ENCODE researchers

    closely examined which DNA bases are transcribed

    into RNA and then whether those

    strands of RNA are subsequently translated

    into proteins, verifying predicted proteincoding

    genes and more precisely locating

    each gene’s beginning, end, and coding

    regions. The latest protein-coding gene count

    is 20,687, with hints of about 50 more, the

    consortium reports in Nature. Those genes

    account for about 3% of the human genome,

    less if one counts only their coding regions.

    Another 11,224 DNA stretches are classifi ed

    as pseudogenes, “dead” genes now known to

    be active in some cell types or individuals.

    ENCODE Project Writes Eulogy

    For Junk DNA

    GENOMICS

    Hypersensitive

    sites

    CH3CO

    CH3

    Long-range regulatory elements

    (enhancers, repressors/

    silencers, insulators)

    cis-regulatory elements

    (promoters, transcription

    factor binding sites)

    Gene Transcript

    RNA

    polymerase

    CH3CO (Epigenetic modifications)

    ChIP-seq

    Computational

    predictions and

    RT-PCR

    RNA-seq

    DNase-seq

    FAIRE-seq

    5C

    Zooming in. A diagram of DNA in ever-greater detail shows how ENCODE’s various tests (gray boxes) translate

    DNA’s features into functional elements along a chromosome.

    CREDIT: ADAPTED FROM THE ENCODE PROJECT CONSORTIUM, PLOS BIOLOGY 9, 4 (APRIL 2011)

    Published by AAAS

    Downloaded from http://www.sciencemag.org on September 10, 2012

    http://www.sciencemag.org SCIENCE VOL 337 7 SEPTEMBER 2012 1161

    NEWS&ANALYSIS

    ENCODE drives home, however, that

    there are many “genes” out there in which

    DNA codes for RNA, not a protein, as the end

    product. The big surprise of the pilot project

    was that 93% of the bases studied were transcribed

    into RNA; in the full genome, 76%

    is transcribed. ENCODE defi ned 8800 small

    RNA molecules and 9600 long noncoding

    RNA molecules, each of which is at least 200

    bases long. Thomas Gingeras of Cold Spring

    Harbor Laboratory in New York has found

    that various ones home in on different cell

    compartments, as if they have fi xed addresses

    where they operate. Some go to the nucleus,

    some to the nucleolus, and some to the cytoplasm,

    for example. “So there’s quite a lot

    of sophistication in how RNA works,” says

    Ewan Birney of the European Bioinformatics

    Institute in Hinxton, U.K., one of the key leaders

    of ENCODE (see p. 1162).

    As a result of ENCODE, Gingeras and

    others argue that the fundamental unit of

    the genome and the basic unit of heredity

    should be the transcript—the piece of

    RNA decoded from DNA—and not the

    gene. “The project has played an important

    role in changing our concept of the gene,”

    Stamatoyannopoulos says.

    Another way to test for functionality of

    DNA is to evaluate whether specific base

    sequences are conserved between species, or

    among individuals in a species. Previous studies

    have shown that 5% of the human genome

    is conserved across mammals, even though

    ENCODE studies implied that much more

    of the genome is functional. So MIT’s Lucas

    Ward and Kellis compared functional regions

    newly identifi ed by ENCODE among multiple

    humans, sampling from the

    1000 Genomes Project. Some

    DNA sequences not conserved

    between humans and other

    mammals were nonetheless

    very much preserved across

    multiple people, indicating

    that an additional 4% of the

    genome is newly under selection

    in the human lineage, they

    report in a paper published

    online by Science (http://scim.

    ag/WardKellis). Two such regions were near

    genes for nerve growth and the development

    of cone cells in the eye, which underlie distinguishing

    traits in humans. On the fl ip side,

    they also found that some supposedly conserved

    regions of the human genome, as highlighted

    by the comparison with 29 mammals,

    actually varied among humans, suggesting

    these regions were no longer functional.

    Beyond transcription, DNA’s bases function

    in gene regulation through their interactions

    with transcription factors and other

    proteins. ENCODE carried out several tests

    to map where those proteins bind along the

    genome (Science, 25 May 2007, p. 1120). Two,

    DNase-seq and FAIRE-seq, gave an overview

    of the genome, identifying where the protein-

    DNA complex chromatin unwinds and a protein

    can hook up with the DNA, and were

    applied to multiple cell types. ENCODE’s

    DNase-seq found 2.89 million such sites

    in 125 cell types. Stamatoyannopoulos and

    his colleagues describe their more extensive

    DNase-seq studies in Science (p. 1190): His

    team examined 349 types of cells, including

    233 60- to 160-day-old fetal tissue samples.

    Each type of cell had about 200,000 accessible

    locations, and there seemed to be at least

    3.9 million regions where transcription factors

    can bind in the genome. Across all cell

    types, about 42% of the genome can be accessible,

    he and his colleagues report. In many

    cases, the assays were able to pinpoint the specifi

    c bases involved in binding.

    Last year, Stamatoyannopoulos showed

    that these newly discovered functional regions

    sometimes overlap with specifi c DNA bases

    linked to higher or lower risks of various diseases,

    suggesting that the regulation of genes

    might be at the heart of these risk variations

    (Science, 27 May 2011, p. 1031). The work

    demonstrated how researchers could use

    ENCODE data to come up with new hypotheses

    about the link between genetics and a

    particular disorder. (The ENCODE analysis

    found that 12% of these bases, or SNPs,

    colocate with transcription factor binding

    sites and 34% are in open chromatin defi ned

    by the DNase-seq tests.) Now, in their new

    work published in Science,

    Stamatoyannopoulos’s lab has

    linked those regulatory regions

    to their specifi c target genes,

    homing in on the risk-enhancing

    ones. In addition, the group

    fi nds it can predict the cell type

    involved in a given disease.

    For example, the analysis fi ngered

    two types of T cells as

    pathogenic in Crohn’s disease,

    both of which are involved in

    this inflammatory bowel disorder. “We are

    informing disease studies in a way that would

    be very hard to do otherwise,” Birney says.

    Another test, called ChIP-seq, uses an

    antibody to home in on a particular DNAbinding

    protein and helps pinpoint the locations

    along the genome where that protein

    works. To date, ENCODE has examined

    about 100 of the 1500 or so transcription

    factors and about 20 other DNA binding

    proteins, including those involved in modifying

    the chromatin-associated proteins

    called histones. The binding sites found

    through ChIP-seq coincided with the sites

    mapped through FAIRE-seq and DNAseseq.

    Overall, 8% of the genome falls within

    a transcription factor binding site, a percentage

    that is expected to double once more

    transcription factors have been tested.

    Yale’s Gerstein used these results to fi gure

    out all the interactions among the transcription

    factors studied and came up with a network

    view of how these regulatory proteins

    work. These transcription factors formed a

    three-layer hierarchy, with the ones at the top

    having the broadest effects and the ones in

    the middle working together to coregulate a

    common target gene, he and his colleagues

    report in Nature.

    Using a technique called 5C, other

    researchers looked for places where DNA

    from distant regions of a chromosome, or

    even different chromosomes, interacted. It

    found that an average of 3.9 distal stretches

    of DNA linked up with the beginning of each

    gene. “Regulation is a 3D puzzle that has to

    be put together,” Gingeras says. “That’s what

    ENCODE is putting out on the table.”

    To date, NHGRI has put $288 million

    toward ENCODE, including the pilot project,

    technology development, and ENCODE

    efforts for the mouse, nematode, and fruit fl y.

    All together, more than 400 papers have been

    published by ENCODE researchers. Another

    110 or more studies have used ENCODE data,

    says NHGRI molecular biologist Michael

    Pazin. Molecular biologist Mathieu Lupien of

    the University of Toronto in Canada authored

    one of those papers, a study looking at epigenetics

    and cancer. “ENCODE data were

    fundamental” to the work, he says. “The cost

    is defi nitely worth every single dollar.”

    –ELIZABETH PENNISI

    ENCODE By the Numbers

    147 cell types studied

    80% functional portion of human genome

    20,687 protein-coding genes

    18,400 RNA genes

    1640 data sets

    30 papers published this week

    442 researchers

    $288 million funding for pilot,

    technology, model organism, and current project

    “ We are informing

    disease studies in a

    way that would be

    very hard to do

    otherwise.”

    —EWAN BIRNEY,

    EUROPEAN BIOINFORMATICS

    INSTITUTE

    Published by AAAS

    Downloaded from http://www.sciencemag.org on September 10, 2012

    http://www.nature.com/encode/

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