Designing a RCT and Network Meta-analysis

A review of literature with possible meta-analysis of available data is often recommended before a randomized clinical trial (RCT) can be proposed. This article goes a step further and suggests using network meta-analysis for planning and designing a RCT. Authors emphasize that a trial design based on updating the evidence from a network meta-analysis of relevant previous trials may require a considerably smaller sample size to reach the same conclusion compared with a trial designed and analyzed in isolation.

Weak vs. Strong Social Ties

The relative contribution of the number of strong social ties versus the number of weak social ties to the health status was explored in this study. Authors examined social network characteristics as predictors of mortality in the Finnish Public Sector Study (n = 7,617) and the Health and Social Support Study (n = 20,816). At baseline, social network characteristics were surveyed. During a mean follow-up period of 16 years, participants with a small social network (≤10 members) were more likely to die than those with a large social network (≥21 members) (adjusted hazard ratio (HR) = 1.23, 95% confidence interval (CI): 1.04, 1.46). Mortality risk was increased among participants with both a small number of strong ties (≤2 members) and a small number of weak ties (≤5 members) (HR = 1.55, 95% CI: 1.26, 1.79) and among participants with both a large number of strong ties and a small number of weak ties (HR = 1.28, 95% CI: 1.08, 1.52), but not among those with a small number of strong ties and a large number of weak ties (HR = 1.04, 95% CI: 0.87, 1.25). Authors conclude that the number of weak ties may be an important component of social networks for mortality risk.

Diagnostics After Multilevel Regression in Stata

Here are few diagnostics that can be run in Stata after running a multilevel model

1. Assess normality of residuals

predict resid_std, rstandard
qnorm resid_std

2. Examine relationship between predicted and residual values

predict resid, res
predict fit, fit

3. Examine variance-covariance matrix

estat recovariance
estat recovariance, correlation

4. Determine Cook’s D and DFBETAs using MLT module

net install mlt.pkg    /* Installs MLT package*/
mltcooksd              /* reports Cook’s D of the whole model */
mltcooksd, fixed       /* reports Cook’s D of the Fixed part */
mltcooksd, random      /* reports Cook’s D of the Random part */
mltcooksd, approx      /* Uses approximation and returns results faster */

A very easy and simple video explaining Bayes Theorem

Must watch TED talk

Talks about how artificial intelligence algorithms are able to affect our opinions. We all are vulnerable, yes we ALL are.

Case against propensity scores

Here is an interesting video (couple of years old but still relevant)

CLABSI Trends and Parenteral Nutrition

Healthcare-associated infections (HAIs) harmful for patients and costly for the health system. Central line associated bloodstream infections (CLABSI) are the most costly of HAIs (between 45K to 55K per CLABSI), increase length of stay by several days, and increase mortality by 15% to 40%. Although the rate of CLABSI has been decreasing since the institution of several preventive practices, the rates remain pretty high.

Patients who receive parenteral nutrition have more than 4-times higher risk of CLABSI than those who who do not receive parenteral nutrition. However the data on the risk of CLABSI risk since the institution of penalties for CLABSI by CMS (Centers for Medicare & Medicaid Services) was not available, that was until the publication of study by Fonseca et al. They used data from all adult patient discharges between January 1, 2009, and December 31, 2014, from 2 affiliated hospitals in a large health system in New York City. They conducted univariate and multivariate analyses to examine the relationship and temporal trends between parenteral nutrition and CLABSIs.

Of the 38,674 patients with central lines, 3517 developed CLABSIs. Of these 3517 patients, 767 patients were prescribed parenteral nutrition. Patients who were prescribed parenteral nutrition were 2.65 times more likely to have CLABSI than patients without parenteral nutrition. What this study shows is that there has been a decrease in the risk of CLABSI among patients who receive parenteral nutrition, although the risk remains much higher. Obviously, this study advocates for additional research to identifies strategies to decrease the risk of CLABSI in patients who receive parenteral nutrition.

Burnout

Burnout among healthcare workers, particularly physicians, has gained increasing attention recently. The societal expectation is that physicians will be selfless and put their patient’s needs first. Often physicians are expected to work long hours and do whatever it takes to help their patient and to go the extra mile; in other words give one's all. Burnout is further exacerbated by the changes in national health system and healthcare organizations; such changes are resulting in work environments that are high in demands and low in resources.

However, what is burnout is open to interpretation. Experts still debate about the dimensions of burnout. The most common burnout measurement tool, Maslach Burnout Inventory (MBI) assumes three dimensions of burnout; emotional exhaustion (EE), depersonalization (DP), and personal accomplishment (PA). MBI has been criticized for its various aspects. For example, it measures three dimensions of burnout (EE, DP, PA) but recommends against merging those three dimensions to reach to the measurement of burnout itself. Thus, MBI is measuring three concepts but unable to define a single concept of burnout. Another criticism is that burnout is an amalgam of an individual state (EE), an undesirable coping strategy (DP), and result of the EE state (lack of PA). However, the biggest criticism of MBI is that it is not available in public domain.

The dimensions of burnout are open for discussion. While MBI, as noted above, considers that burnout has three dimensions, others consider burnout to have two or even one dimension; it is possible that burnout may have more than 3 dimensions. For example, Oldenburg Burnout Inventory considers only two dimensions of burnout out while Copenhagen Burnout Inventory (CBI) considers only one dimension of burnout.

Obviously, the disagreements about the definition and dimensions of burnout limit the study of effective interventions and have lead some to suggest that burnout perhaps does not exist as a separate entity on its own.

CHADS-VASc Score predicts stroke and death in congestive heart failure patients

The CHA₂DS₂-VASc score (congestive heart failure, hypertension, age ≥75 years [doubled], diabetes, stroke/transient ischemic attack/thromboembolism [doubled], vascular disease [prior myocardial infarction, peripheral artery disease, or aortic plaque], age 65-75 years, sex category [female]) is used clinically for stroke risk stratification in atrial fibrillation (AF). However, whether it can predict these outcomes in patients with heart failure remained unknown.

Melgaard et al, examined the nationwide prospective cohort study using Danish registries, including 42,987 patients (21.9% with concomitant AF) not receiving anticoagulation who were diagnosed as having incident HF during 2000-2012.

In patients without AF, the risks of ischemic stroke, thromboembolism, and death were 3.1% (n = 977), 9.9% (n = 3187), and 21.8% (n = 6956), respectively.  The risks were greater with increasing CHA₂DS₂-VASc scores. Interestingly, the absolute risk of thromboembolic complications was higher among patients without AF compared with patients with concomitant AF at high CHA₂DS₂-VASc scores. However, predictive accuracy was modest, and the clinical utility of the CHA₂DS₂-VASc score in patients with HF remains to be determined.

Treatment of Abdominal Aortic Aneurysm

What is a better treatment option for patients with abdominal aortic aneurysms (AA)? Currently, there are two main options; endovascular repair (below left) or open surgical repair (below right).

Chang and his colleagues analyzed the longitudinally linked California Office of Statewide Health Planning and Development inpatient database from 2001 to 2009 with a median follow-up of 3.3 years. They studied 23,670 patients, with 52% receiving endovascular repair. Endovascular repair was associated with improved 30-day outcomes (all-cause mortality, readmission, surgical site infection, pneumonia, and sepsis), as well as significantly improved survival until 3 years postoperatively. After 3 years, mortality was higher for patients who underwent an endovascular repair. No significant difference in long-term mortality was observed for the entire cohort on adjusted analysis (hazard ratio, 0.99; 95% CI, 0.94-1.04; P = .64). Endovascular repair was found to be associated with a significantly higher rate of re-interventions and AAA late ruptures.

Some Stuff from ESC

 

Warfarin Discontinuation Increases Stroke Risk

Non-steroidal Mineralcorticoid Receptor Antagonist Could Cut Mortality

One study says:
- Stimulation of either the right or left vagus nerve appeared to improve cardiac function in patients with heart failure
And other one says:
- Stimulating the vagus nerve didn't improve cardiac function in heart failure patients
Go figure!

Antidote for Dabigatran

Until recently, warfarin (also known as Coumadin), a vitamin K antagonist (VKA), had been the only available oral anticoagulant. The use of warfarin has been always complicated by many issues including its narrow therapeutic index and multiple drug and diet interactions affected its safety, compliance, and efficacy. Patients needed regular and close monitoring of the its anticoagulant effect (how thin is blood?). Despite regular monitoring, patients suffered bleeding complications when blood was too thin (supra-therapeutic range) or blood was thin within the desired range but other patient factors (such as trauma/injury) resulted in bleeding.

A very common use of warfarin is for anticoagulation in patients who suffer from atrial fibrillation. With increasing age, the risk of atrial fibrillation increases and atrial fibrillation is common older individuals. Patients with atrial fibrillation can develop a clot in the left atrium of the heart and this clot can dislodge and go to other parts of the body. If this dislodged clot goes to arteries that supply blood to the brain, it usually results in large stroke. The risk of stroke with atrial fibrillation varies from person to person but can be calculated using a CHADS2 score and may vary from 1.8% per year to 18% per year without anticoagulation.

The above noted problems with warfarin prompted the development of new oral anticoagulants that target key coagulation proteins. Within past few years, FDA has approved several new oral anticoagulants that don’t require regular monitoring with blood tests and have very few drug interactions. However, one limitation with these new anticoagulants is lack of an antidote that can quickly reverse the effect of these drugs in cases of emergency, such as when a patient is bleeding. On the other hand, vitamin K can be used to reverse the effect of warfarin. Several pharmaceutical companies and other research groups are trying to develop agents that can effectively reverse the effects of these new anticoagulants.

Pollack and colleagues have published in this issue of the New England Journal of Medicine a trial of such an antidote of dabigatran, an oral thrombin inhibitor that is approved for the prevention of stroke in patients with non-valvular atrial fibrillation and for the prevention and treatment of venous thromboembolism. Investigators used idarucizumab, a monoclonal antibody fragment that binds dabigatran with an affinity that is 350 times as high as that of dabigatran’s affinity with thrombin (a coagulant protein through which dabigatran acts). In blood, idarucizumab binds free and thrombin-bound dabigatran and neutralizes its activity. In this prospective cohort study, investigators examined the safety of 5 g of intravenous idarucizumab and its inhibitory effect on dabigatran in patients who had serious bleeding (group A) or who required an urgent procedure (group B). Investigators determined the maximum percentage reversal of the anticoagulant effect of dabigatran within 4 hours after the administration of idarucizumab (primary endpoint).

Of the 90 patients who received idarucizumab (51 patients in group A and 39 in group B), idarucizumab normalized the blood coagulation in 88 to 98% of the patients often within minutes. Concentrations of unbound dabigatran was below 20 ng per milliliter at 24 hours in 79% of the patients. Among 35 patients in group A who could be assessed, bleeding was controlled at a median of 11.4 hours. Among 36 patients in group B who underwent a procedure, normal intraoperative hemostasis was reported in 33, and mildly or moderately abnormal hemostasis was reported in 2 patients and 1 patient, respectively. One thrombotic event occurred within 72 hours after idarucizumab administration in a patient in whom anticoagulants had not been reinitiated.

As noted above idarucizumab is specific for dabigatran and is unlikely to be effective with other new oral antocagulants. However, various reversal agents and/or strategies, nonspecific to dabigatran, are available to physicians, including prothrombin complex concentrates, activated prothrombin complex concentrates, or recombinant factor VIIa.

Southern Dietary Pattern and Heart Disease

We are what we eat – and the diseases we get are the often (at least partly) a result of dietary choices we make.

A study published in the American Heart Association’s journal, Circulation, finds that people who have Southern dietary pattern – characterized by added fats, fried food, eggs, organ and processed meats, and sugar-sweetened beverages – are at a higher risk of heart attacks and sudden cardiac death. Investigators analyzed data from 17,418 participants in Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a national, population-based, longitudinal study of white and black adults aged ≥45 years, enrolled from 2003-2007. They found 56% higher risk of heart attacks and sudden cardiac death among individuals who eat ‘Southern’ food than those who rarely eat such food.

So next time when you are thinking about what to eat, chose something healthy!

Updated Guidelines - Diabetics and Cardiovascular Disease

American Heart Association and American Diabetes Association has recently published an update to the guidelines for the prevention of cardiovascular disease in adults with type 2 diabetes mellitus. There are certain interesting aspects to it.

1. Use of Hemoglobin A_1C for the diagnosis of diabetes mellitus
 Pre-diabetes = A_1C between 5.7% and 6.4%
Diabetes Mellitus = A_1C >/= 6.5%

2. Lifestyle Management of Diabetes
Physical Activity
Nutrition
Weight Reduction (through physical activity, nutrition, weight-loss drugs, and/or bariatric surgery)

3. Cardiovascular risk reduction
Control of blood glucose (A_1C <7%)
Control of blood pressure (< 140/90)
Control of Cholesterol (statins)
Aspirin for moderate 10-year CVD risk (5-10%)

4. Screening for cardiovascular diseases in asymptomatic patients
Paucity of data suggesting any specific benefits of invasive interventions over medical therapy alone makes any CAD screening in the asymptomatic patient with diabetes mellitus highly controversial.

Statins After Stroke: What is the effect on mortality and morbidity?

Statins (cholesterol lowering drugs such as Lipitor or Crestor and others) have been shown to reduce major cardiovascular events after stroke and are considered the standard of therapy in patients with stroke. Most patients with new stroke are prescribed one of the statins when discharged from hospital. However, whether the beneficial effects of statins seen in strict clinical trials settings are also present in non-clinical trial settings remains to be seen. In other words, while it is established that statins have efficacy (work in clinical trials) it remains to be seen whether statin have effectiveness (work in usual delivery of healthcare).

The distinction between efficacy and effectiveness is an important one. A clinical trial has inclusion (and exclusion) criteria which limit enrollment to only a certain group of individuals. Patients who volunteer for clinical trials are also known to be more compliant and receptive to medical advice. Furthermore, patients in clinical trial are closely followed (and observed) and, therefore, perhaps get better care. Thus, results seen in a clinical trial setting may not hold true in the usual healthcare delivery environment where all sort of patients get drugs (or interventions), compliance may be an issue, and patients are not as closely followed. This necessitates effectiveness studies, which are not commonly performed, although thought to be quite important. Perhaps the biggest reason is that such studies are not required for a drug approval by FDA and perhaps drug companies fear that effectiveness studies may show that a particular drug (or intervention) is not as effective as shown in the clinical trial (or not effective at all).

It is then no surprise that effectiveness studies for statins in stroke (one of the commonly prescribed drug class) have not been done, that is until now. O’Brien et al report in this issue of circulation such an effectiveness study. Investigators linked data from Get With The Guidelines (GWTG)-Stroke register with the Medicare data and followed patients 2-year post-discharge for major cardiovascular events, time spent at home (out of hospital or nursing home), all cause mortality, readmissions to hospitals, and hemorrhagic stroke. Investigators report that from 2007–2011, 77,468 patients who were not taking statins at the time of admission were hospitalized with ischemic stroke. Of these 77K patients, 71% were discharged on some form of statin therapy; 31% on high-intensity statin therapy.

What they found was that the rates were lower for major adverse cardiovascular events (9% lower), mortality (16% lower), and readmission (7% lower) within two years of hospital discharge were lower for patients who were taking statins as compared with those not taking a statin. On average, patients also spent 28 more days at home. Of note, these results were adjusted for risk factors. There were no differences in rates of hemorrhagic stroke, ischemic stroke, or cardiovascular readmission by statin therapy.

Now contrast this data with the results from clinical trials of statins that showed a 20% reduction in major adverse cardiovascular events, 16% reduction in risk of ischemic stroke, and as high as 32% reduced risk of mortality. Obviously, as expected, the benefits are much larger in a clinical trial setting. This example, among others, highlights the need for effectiveness trials. Of note, this trial was funded through PCORI (a tax-payer funded program) and not by a drug company.

Life Expectancy After Myocardial Infarction

This study examines sex and race differences in long-term survival after AMI using life expectancy and YPLL to account for differences in population-based life expectancy. Investigators used the Cooperative Cardiovascular Project, a prospective cohort study of Medicare beneficiaries hospitalized for AMI between 1994 and 1995 (N = 146,743).

Investigators found that the life expectancy estimates after myocardial infarction were similar for men and women of the same race but lower for black patients than white patients.

Below is a figure from the manuscript summarizing the findings

3D Printing in Medicine

Very interesting!

With 3D printing physicians can make exact replica of a particular patient’s left atrial appendage to obtain a better fit during the appendage closure procedure. Left atrial appendage is the most common site of thrombus (or clot) formation in patients with atrial fibrillation. These clots can dislodge and go into circulation, blocking blood flow, and causing damage to the affected organs. The biggest concern (and the biggest risk) is of strokes.

Lung Function Trajectories Leading to COPD

It is commonly believed that the decline in lung function may be greater in people with already poor lung function than those with normal lung function. Now a study with a relatively large sample size shows that the decline in lung function varies among people and perhaps doesn’t depend on the baseline lung function.

Peter Lange and colleagues used three independent cohorts (Framingham, Copenhagen Heart, Lovelace Smokers) and showed that low FEV₁ in early adulthood is important in the genesis of COPD and that accelerated decline in FEV₁ is not an obligate feature of COPD.

Changing Microbiology of Community Acquired Pneumonia

Since the start of pneumococcal conjugate vaccine use for routine childhood immunization, the overall rate of invasive disease and pneumonia among adults has decreased, likely due to herd immunity. We also now have have more sensitive laboratory tests to detect pathogens responsible for pneumonia in adults. This requires an updated assessment of the incidence of pneumonia and causative pathogens.

Seema Jain and her colleagues have recently explored this question in a prospective, multicenter, population-based, active surveillance study, the Centers for Disease Control and Prevention (CDC) Etiology of Pneumonia in the Community (EPIC) study, and published results in the NEJM.

The study enrolled adults 18 years of age or older were enrolled at three hospitals in Chicago (John H. Stroger, Jr., Hospital of Cook County, Northwestern Memorial Hospital, and Rush University Medical Center) and at two in Nashville (University of Tennessee Health Science Center–Saint Thomas Health and Vanderbilt University Medical Center) from January 1, 2010, to June 30, 2012.

There were 2320 cases of pneumonia confirmed with radiographs. Quite interestingly, and in contrast to what would one expect to see, pneumonia were distributed about evenly between younger (18-49) middle (50-64) and older (>64) age groups, roughly one third in each category. Most (78%) had some underlying condition predisposing to pneumonia. Surprisingly, less than half were vaccinated with influenza or pneumococcal vaccine. Only in 38% of patients, a pathogen was detected despite using an extensive battery of laboratory diagnostics. Pathogens detected were as follows: one or more viruses in 530 (23%), bacteria in 247 (11%), bacterial and viral pathogens in 59 (3%), and a fungal or mycobacterial pathogen in 17 (1%). The most common pathogens were human rhinovirus (in 9% of patients), influenza virus (in 6%), and pneumococcus (in 5%).

At a population level, the annual incidence of pneumonia was 24.8 cases (95% confidence interval, 23.5 to 26.1) per 10,000 adults, with the highest rates among adults 65 to 79 years of age (63.0 cases per 10,000 adults) and those 80 years of age or older (164.3 cases per 10,000 adults).

The results overall reaffirm the common observation that pneumonia incidence is highest in the elderly population. Results further show that despite current diagnostic tests, no pathogen was detected in the majority of patients. The overall pathogens for pneumonia are changing with respiratory viruses being detected more frequently than bacteria.

Left Atrial Appendage Occlusion Device

Oral anticoagulants such as warfarin, factor Xa inhibitors, and direct thrombin inhibitors are the current standard of care in high-risk patients with atrial fibrillation to reduce the risk of stroke in patients with risk factors, albeit at the expense of an increase in bleed. However, the benefit of oral anticoagulation needs to be weighed against an increased risk of bleeding.

Left atrial appendage occlusion devices have the potential to change the therapy for stroke prevention in atrial fibrillation patients. ACC/HRS/SCAI have just published an overview of the literature on this topic. The overview reviews several questions related to the use of these occlusion devices. The overview starts with literature review of currently available devices (WATCHMAN, Amplatzer Cardiac Plug, LARIAT, and others) and then delves into the question of the need and requirements for care team and facilities needed for the use of such devices. This is followed by training requirement for the operator, standardization of protocols, and selection of patients for occlusion device placement. The overview is an interesting read and is available here.

Individualized Care Plans for High Utilizers of Hospital Services

There are always a small number of patients frequently visit Emergency Department (ED) and are frequently admitted to the hospital. The underlying reasons are sometimes medical conditions and sometimes are complex psychological and social issues. Formulating a care plan that is individualized for a patient with appropriate support from healthcare professionals may help to decrease utilization of healthcare services and resources by such patients.

A study published in this month’s Journal of Hospital Medicine examined the same question. Investigators formed a multidisciplinary team that developed individualized care plans integrated into electronic medical record (EMR) that summarized patient histories, utilization patterns, and management strategies. They enrolled twenty-four medically and psychosocially complex patients with the highest rates of inpatient admissions and ED visits from August 1, 2012 to August 31, 2013.

Investigators found that hospital admissions decreased by 56% (P < 0.001) and 50.5% (P = 0.003), 6 and 12 months after care-plan implementation. Thirty-day readmissions decreased by 66% (P < 0.001) and 51.5% (P = 0.002), 6 and 12 months after care-plan implementation. ED visits, ED costs, and inpatient LOS did not significantly change. Inpatient variable direct costs were reduced by 47.7% (P = 0.001) and 35.8% (P = 0.052), 6 and 12 months after care-plan implementation.

At least this one study found that individualized care plans developed by a multidisciplinary team and integrated with the existing healthcare workforce and EMR reduce hospital admissions, 30-day readmissions, and hospital costs for complex, high-utilizing patients.

Plotting Histograms in R

Histogram is probably one of the first things that we plot to look at a continuous variable. In R you can draw a histogram using its built-in ‘hist’ command. Other packages, such as ggplot2 has much more developed functions to plot histograms although one does need to learn how to use functions within those packages.

First, lets simulate data (generate fake data)
DAT = rnorm(1000, 100, 10)
Above line will generate 1000 draws from a normal distribution with a mean of 100 and standard deviation of 10

Now lets take a look at first few rows we generated
head(DAT)

Lets look at the summary of the data
summary(DAT)

Note: You may get different data every time as we have not set a seed but that is not important at this time.

Now draw first histogram
hist(DAT)

Add color to the histogram
hist(DAT, col="blue")

Now lets take control on the number of histogram bars
hist(DAT, col="blue", breaks=25)

Change Y-axis from frequency (which is default) to density
hist(DAT, col="blue", breaks=25, probability=TRUE)

Add labels to the histogram
hist(DAT, col="blue", breaks=25, probability=TRUE,
     main="My Pretty Histogram",    ### For title of the figure
     xlab="My Fake Data")           ### For x-axis label

Add a dark green-color  kernel density curve to the plot
lines(density(DAT), col="darkgreen", lwd=2) 

Add a red-color normal density curve to the plot
curve(dnorm(x, mean(DAT), sd(DAT)), add=TRUE, col="red", lwd=2) 

Below is similar to what you should expect to get:

Identifying and Developing a Research Question

Below are some of the resources that may be helpful in learning how to develop a research question

1. Coming up with a research question [Kinmond 2012]

2. Developing great research questions [Lipowski 2008]

3. When is a research question not a research question? [Mayo 2013]

Installing Packages in R

R has thousands of packages that extend its use to almost every arena of research. It is highly likely that you will not need most of these packages but it is also likely that you will need several of them (perhaps from 5 to 20) depending on what you plan to do. Most of these packages are available on the the CRAN website.

http://www.cran.r-project.org/web/packages/available_packages_by_name.html

Bioconductor is another source of R packages for bioinformatics-related research packages can be downloaded from its website.

http://www.bioconductor.org/packages/release/bioc/

To use a package, there are two steps:

First Step: Download and Install a Package – you can download a package to a local directory and install it from there using drop down menu OR you can directly install it from the CRAN repository. Depending on the R GUI user interface that you use, the exact steps may be slightly different. Often, first you have to specify which mirror you want to use; chose a mirror that is geographically closer to you for faster downloads. Then you can chose a package from the package list.

I use RStudio GUI. In Rstudio, click on the tab labeled ‘Packages’. If this tab is not visible, press Ctrl+7 and the tab will become visible (usually in the right lower quadrant of the window). From there you can chose install, then type in the name of package (if multiple packages, enter package names separated by space or a comma). Make sure that ‘install dependencies’ box is checked. Make sure that the correct repository and installation location are selected. Then click Install. You can also chose to use installation command directly from the console; the command below will install ggplot2 package:

install.packages("ggplot2")

Note that you need to install packages only once

Second Step: Loading a Package – Installing a package makes it available for later use but packages are not automatically uploaded during a session. Once you have installed a package, you will need to load that package when you need it during a session. To load a package use the function ‘library()’. the following command will load the package ggplot2.

library(ggplot2)

Some may like to use ‘require()’ function instead of ‘library()’. However, see this post for the differences between the two and why one should prefer ‘library()’ over ‘require()’

Personally, I try to load all needed packages at the beginning of a script. However, this strategy may not work if there is an overlap in the names of functions between two packages and you may see a warning “The following objects were masked from ‘package:xyz’:”. 

Some other useful commands to know

.libpaths() # – will give you location of library for packages
library() # – will show you all installed packages
search() # – will show you currently loaded packages

Some Thoughts About Clinical Research

Clinical research requires a wide range of skills. These skill include the ability to work with a wide range of people, to lead teams with people from wide and vastly different backgrounds, to design appropriate studies, to ask right questions, to understand research methods specific to the study question, to develop in-depth content expertise in the area of research focus, to get funding for research projects, to present study results at national meetings, to write manuscripts for publication in peer-review journals, and so on and so forth.

A fundamental skill for a researcher is the ability to knit together the conceptual framework for a study (theory) with appropriate measurement, with the result either supporting or opposing the conceptual framework. The theory should be based on the most current state of knowledge, the data collected should have the ability to test the theory, the statistical models should reflect both the conceptual structure hypothesized to have given rise to the data and the nature of collected data, and the inferences should be based on the data and the tested statistical models. This process is not linear, rather it is a loop in which theoretical aspects inform the collection of data and results of the data analyses help in refining the theory, which generates more testable hypothesis, additional data collection, and so on.

Most research is probabilistic, as opposed to deterministic. In other words, the results we obtain are not always certain; we have to include uncertainty in our analyses and expect some uncertainty in our results and inferences. Thus, we have to accept that our results are unlikely to be laws governing the system we plan to study and more likely to be an approximation of what we expect to find in the real world, with some uncertainty. There are many reasons and sources of this uncertainty some of which can be addressed while others may still be there despite our best attempts.

A researcher should determine whether the interest of research is to build inferences at population level or at the level of individuals unit (often a patient in clinical research). The study design, data collection and analysis, and the inferences may be quite different depending on what is the object of our interest. While we study individuals, our results usually address inferences at population level. In general, it is much easier to predict about the response at a population level, that is on an average, individuals with higher body mass index (say >30) will have higher blood glucose than (say) 126mg/dL. However, it is much difficult to predict with certainty how likely a particular individual with a BMI>30 is to have higher blood glucose level than 126 mg/dL. For a predictor to work well at an individual level, among other things effect size needs to be quite large.

Another important concept is that of causality. While we often have a conceptual model in our mind that A is caused by B, it may be quite difficult to prove except perhaps in a clinical trial setting. There are several factors that can increase the likelihood that the direction of cause and effect in our conceptual model is correct, such as temporality and biological plausibility.  However, often there remains a possibility that B is in fact caused by A or that some other unknown (or unmeasured) factor, C, may be responsible for both A and B. Hence, we often claim an association or correlation between A and B and not causality.

Starting to work with R

There may be some who have just started working with R after someone convinced them that R is the way to go. For those souls, it may be difficult to get started quickly. Below are some of the steps to use to start working with R

Step 1: Go to the CRAN webpage and download the version of R that is appropriate for your operating system - http://cran.r-project.org/

Step 2: Install R

Step 3: Download a GUI for R – While R comes with a GUI, other GUIs are much better. My favorite is RStudio, To download RStudio, go to RStudio website and download the version that is appropriate for your operating system - http://www.rstudio.com/products/rstudio/download/

Step 4: Install RStudio (or a GUI of your choice).

Step 5: Start using RStudio (or GUI of your choice)

That’s it – Good luck!

Fractional Flow Reserve–Guided PCI for Stable CAD

The utility of PCI in stable CAD is unclear. Fractional flow reserve (FFR) may be used to stratify patients between those who will benefit from PCI from those who will not.

A randomized clinical trial published in NEJM examined this question. Patients with FFR<0.8 were randomized to PCI or medical therapy. Although the primary endpoint included a soft endpoint (revascularization) there was significant decrease in the primary endpoint among patients who underwent PCI (8.1 vs 19.5%). Further, the hard endpoints (death or nonfatal myocardial infarction) were also reduced significantly in FFR patients (4.6% vs 8.0%). Quite interestingly, the individuals with FFR greater than 0.8 met primary endpoint as often as those with FFR<0.8 and PCI (8.1 vs. 9.0%) although this was not a direct comparison group.

Interesting results! ……… Perhaps practice changing?

Thunder and Spark–Cluster computing made easy (a little)

Here it is

Epiviz–an interactive visual tool for genomics data

Epiviz is an interactive visualization tool for functional genomics data. It supports genome navigation like other genome browsers, but allows multiple visualizations of data within genomic regions using scatterplots, heatmaps and other user-supplied visualizations.

Cant Imagine this can happen

Even in this day and age when almost everything is available on internet how can this happen? Perhaps no one who was hiring or promoting this dude knew how to use internet. Someone can lie about his/her qualifications (such as getting a PhD) and no one checks before hiring for assistant or associate professor? Shouldn’t folks at NUS, WVU and VCU be ashamed of their gross negligence?

Maximizing Public Data Sources for Sequencing and GWAS Studies

An interesting presentation

CONFIRM-HF - Replete Iron in Heart Failure Patients?

Findings from the CONFIRM-HF (Ferric CarboxymaltOse evaluatioN on perFormance in patients with IRon deficiency in coMbination with chronic Heart Failure) trial, point to a simple and safe solution for heart failure patients with iron deficiency who can experience significant and sustainable improvements in functional capacity and quality of life as well as reduced risk of hospital admission for worsening heart failure by iron supplementation.

CONFIRM-HF is a double-blind, placebo-controlled trial, which enrolled 304 stable, symptomatic heart failure patients from 41 sites across nine European countries. All patients had iron deficiency, defined as a serum ferritin level < 100 ng/mL, or between 100 and 300 ng/mL with transferrin saturation < 20%. Subjects were randomized to receive either intravenous iron (n=152), given as ferric carboxymaltose solution (FCM), or a normal saline placebo (n=152), for 52 weeks. Completion of the six-minute walk test (6MWT) was required at baseline, and the primary endpoint of the study was improvement in this test at week 24.

Compared to placebo-treated subjects, those treated with FCM completed 33 extra meters in the 6MWT at week 24 (p=0.002), 42 extra meters at week 36, and 36 extra meters at week 52 (both p<0.001) and the improvement was seen in all subgroups. Despite the reduction in hospitalizations among FCM-treated patients, the number of deaths was similar in both groups, suggesting a one-year follow-up may not be long enough to detect differences in mortality.
Adverse events were mild, and occurred at a similar rate in both groups.

A New Drug For Heart Failure

ACE inhibitors are standard of therapy in patients with heart failure as clinical trials have shown mortality benefit with these drugs. A trial published in NEJM compared a new drug LCZ696 with enalapril (an ACE Inhibitor) and found this new drug to far better.

This trial randomly assigned 8442 patients with class II, III, or IV heart failure and an ejection fraction of 40% or less to receive either LCZ696 (at a dose of 200 mg twice daily) or enalapril (at a dose of 10 mg twice daily), in addition to recommended therapy.

The trial was stopped early (after a median follow-up of 27 months) because there was clear evidence of benefit of LCZ696 over enalapril. The primary outcome (a composite of death from cardiovascular causes or hospitalization for heart failure) had occurred in 914 patients (21.8%) in the LCZ696 group and 1117 patients (26.5%) in the enalapril group (hazard ratio in the LCZ696 group, 0.80; 95% confidence interval [CI], 0.73 to 0.87; P<0.001). A total of 711 patients (17.0%) receiving LCZ696 and 835 patients (19.8%) receiving enalapril died (hazard ratio for death from any cause, 0.84; 95% CI, 0.76 to 0.93; P<0.001); of these patients, 558 (13.3%) and 693 (16.5%), respectively, died from cardiovascular causes (hazard ratio, 0.80; 95% CI, 0.71 to 0.89; P<0.001). As compared with enalapril, LCZ696 also reduced the risk of hospitalization for heart failure by 21% (P<0.001) and decreased the symptoms and physical limitations of heart failure (P=0.001).

The incidence and type of adverse effects were different between the two drugs; the LCZ696 group had higher proportions of patients with hypotension and nonserious angioedema while enalapril group have higher proportions with renal impairment, hyperkalemia, and cough.

LCZ696 is an investigational combination drug consisting of two antihypertensives (blood pressure lowering drugs), valsartan and AHU-377, in a 1:1 mixture. It is being developed by Novartis. The combination is often described as a dual-acting angiotensin receptor-neprilysin inhibitor although the two effects are achieved by two different molecules. AHU-377 is a prodrug that is activated to LBQ657 by de-ethylation via esterases.LBQ657 inhibits the enzyme neprilysin, which is responsible for the degradation of atrial and brain natriuretic peptide, two blood pressure lowering peptides that work mainly by reducing blood volume.

On the financial side, projections on peak sales from the company's own bullish $2 billion to $5 billion. The highest estimate is by Deutsche's awestruck of $10 billion while the lowest is by EvaluatePharma which pegged nearer-term 2020 sales at a much more modest $1.3 billion.

Colchicine - Postpericardiotomy Syndrome - Postop AFib

Not surprisingly, increased morbidity and perhaps increased mortality, is associated with postpericardiotomy syndrome as well as post-operative development of atrial fibrillation and pericardial and pleural effusions. Colchicine may prevent these complications and COPPS-2 trial looked at this possibility.

This trial was reported in JAMA and also presented at ESC

The results were as below:

PRIMARY ENDPOINT: “The primary end point of postpericardiotomy syndrome occurred in 35 patients (19.4%) assigned to colchicine and in 53 (29.4%) assigned to placebo (absolute difference, 10.0%; 95% CI, 1.1%-18.7%; number needed to treat = 10).

SECONDARY ENDPOINT: “There were no significant differences between the colchicine and placebo groups for the secondary end points of postoperative AF (colchicine, 61 patients [33.9%]; placebo, 75 patients [41.7%]; absolute difference, 7.8%; 95% CI, −2.2% to 17.6%) or postoperative pericardial/pleural effusion (colchicine, 103 patients [57.2%]; placebo, 106 patients [58.9%]; absolute difference, 1.7%; 95% CI, −8.5% to 11.7%), although there was a reduction in postoperative AF in the prespecified on-treatment analysis (placebo, 61/148 patients [41.2%]; colchicine, 38/141 patients [27.0%]; absolute difference, 14.2%; 95% CI, 3.3%-24.7%).

ADVERSE EVENTS: “Adverse events occurred in 21 patients (11.7%) in the placebo group vs 36 (20.0%) in the colchicine group (absolute difference, 8.3%; 95% CI; 0.76%-15.9%; number needed to harm = 12), but discontinuation rates were similar”.

Platelet Glycoprotein IIIa and Aspirin Resistance

Aspirin is the mainstay of treatment for the prevention of cardiovascular disease. It acts by irreversibly inhibiting COX1 enzymes and hence blocking arachidonic acid-thromboxane pathway. Due to lack of a nucleus, platelets cannot generate new COX1 and hence COX1 is inhibited for the lifetime of platelets (8 days). Aspirin treatment results in marked decrease in the excretion of urinary metabolites of thromboxane; the residual excretion is thought to be of endothelial origin where presence of nucleus results in formation of new COX1.

Despite adequate aspirin therapy, a significant number of individuals continue to have higher platelet reactivity and incomplete inhibition of platelet function. Such individuals are also at increased risk of future cardiovascular events. However, the underlying mechanisms that result in higher residual platelet reactivity after aspirin treatment are unclear and are being extensively explored by several researchers.

To identify mechanism of aspirin resistance, this study examined the differences in proteome of 2 aspirin resistant and 4 aspirin sensitive individuals and found that the levels of glycoprotein IIIa were higher in aspirin resistant individuals than in those without aspirin resistance.

Due to small sample size, it is difficult to rule-out the possibility of a type I error, however, considering the role of glycoprotein IIIa in platelet biology, it is conceivable that protein may play a role in aspirin resistant although exact mechanism remains unknown.

Benefits of Aspirin Use in the General Population

Aspirin is perhaps the most commonly used drug world-wide for various ailments. Its prophylactic use in secondary prevention of cardiovascular diseases is well-established, however its use for cardiovascular disease prophylaxis in primary prevention has not been as clear. In particular, some recent meta-analysis has raised concern that aspirin use may not be beneficial for primary prevention of cardiovascular diseases. In support of a role of aspirin use in general population, a systematic review recently concluded:

“For average-risk individuals aged 50–65 years taking aspirin for 10 years, there would be a relative reduction of between 7% (women) and 9% (men) in the number of cancer, myocardial infarction or stroke events over a 15-year period and an overall 4% relative reduction in all deaths over a 20-year period”

In other words, aspirin use is beneficial for both cardiovascular and cancer standpoint, its takes three years to see a beneficial effect, and effect lasts long after aspirin use has been discontinued.

Platelet Diameters in Inherited Thrombocytopenia

An interesting article providing a systematic evidence for what is well-known but not reported in a systematic manner.

“To improve knowledge in this field, we evaluated platelet size on blood films obtained from 376 patients with all 19 forms of IT identified so far and found that these conditions differ not only in mean platelet diameter, but also in platelet diameter distribution width and the percentage of platelets with increased or reduced diameters………….. We also measured platelet diameters in 87 patients with immune thrombocytopenia and identified cutoff values for mean platelet diameter and the percentage of platelets with increased or reduced size….”

iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections

Identifying master regulators of biological processes and mapping their downstream gene networks are key challenges in systems biology. iRegulon is a software that implements a genome-wide ranking-and-recovery approach to detect enriched transcription factor motifs and their optimal sets of direct targets. The software can be obtained from this website

 

Circleator: Flexible Circular Visualization of Genome-Associated Data

Came through this interesting package which builds graphs similar to Circos but just a little easier

“Circleator is a Perl application that generates circular figures of genome-associated data. It leverages BioPerl to support standard annotation and sequence file formats and produces publication-quality SVG output. It is designed to be both flexible and easy to use. It includes a library of circular track types and predefined configuration files for common use-cases, including: 1. visualizing gene annotation and DNA sequence data from a GenBank flat file,
2. displaying patterns of gene conservation in related microbial strains,
3. showing SNPs and indels relative to a reference genome and gene set, and
4. viewing RNA-Seq plots.”

Greater Collagen-Induced Platelet Aggregation Following Cyclooxygenase 1 Inhibition Predicts Incident Acute Coronary Syndromes

Platelets have several pathways that initiate aggregation such as thrombin-, collagen-, thromboxane-, and ADP-mediated pathways. Individuals vary widely in their ability to have platelet aggregation through each of these pathways. Furthermore, this variability is not correlated. In other words, an individual may have low aggregation though one pathway but may have high aggregation through another pathway. This phenomenon may be more important when we try to measure platelet aggregation the laboratory to assess whether there is increased risk of in vivo platelet aggregation (and hence cardiovascular events).

Collagen is one of the first agonists that initiates platelet aggregation at the site of vessel wall injury. Therefore, examining an association of collagen-mediated platelet aggregation with subsequent cardiovascular events makes sense. Moreover, if we can decrease variability in platelet aggregation by blocking one or another pathway, we may be better able to assess activation through collagen pathway.

Aspirin is commonly used for prevention of cardiovascular disease and works by inhibiting thromboxane-pathway an dis very effective in completely inhibiting activity through this pathway. Thus aspirin can be used to inhibit variability through one pathway and effect of collagen can be studied with fewer interactions. We followed the same logic in this paper where we examined platelet aggregation after 2-week aspirin therapy in healthy individuals. Most of these individuals did not use aspirin after the 2-week study period. During follow-up increased collagen-mediated platelet aggregation was significantly associated with acute coronary syndrome.

“After COX1 pathway inhibition, collagen-induced aggregation was significantly greater in participants with ACS compared with those without (29.0 vs. 23.6 ohms, p < 0.001). In Cox proportional hazards models, this association remained significant after adjusting for traditional cardiovascular risk factors (HR = 1.10, 95%CI = 1.06-1.15; p < 0.001).”

The Science Publishing Complex – <1% publish 42% of all papers

There are not as many successful scientists as we think there are – most are just trying (or leaving).

“Using the entire Scopus database, we estimated that there are 15,153,100 publishing scientists (distinct author identifiers) in the period 1996–2011. However, only 150,608 (<1%) of them have published something in each and every year in this 16-year period (uninterrupted, continuous presence [UCP] in the literature). This small core of scientists with UCP are far more cited than others, and they account for 41.7% of all papers in the same period and 87.1% of all papers with >1000 citations in the same period.”

The End of HDL-raising Therapies?

Patients with cardiovascular disease are at increased risk of subsequent events than individuals without a history of cardiovascular disease despite optimal medical management. Various strategies has been proposed to decrease this increased risk among them increasing HDL.

The HPS2-THRIVE trial examined this question by randomly assigning almost 26,000 individuals with established vascular disease to either placebo or Naicin+laropiprant; a combination that should raise HDL cholesterol. Participants were followed for a median period of 3.9 years. Individuals randomized to the treatment arm had lower LDL (about 10 mg/dL) and higher HDL (about 6 mg.dL) than those who were randomized to placebo. During follow-up, there was no difference in the incidence of major cardiovascular events between the two groups13.2% vs. 13.7%; p = 0.29). On the other hand, individuals randomized to the treatment arm had increased incidence of adverse events such as poor diabetes control or increased incidence of new diagnosis of diabetes.

For now, this trial, puts to rest the use of niacin for decreasing the risk of cardiovascular disease. However, it also raises important questions about the interest in the development of pharmacological therapies directed towards raising HDL-cholesterol. It further questions our current understanding of the role of HDL in the pathogenesis of cardiovascular diseases.

Some interesting articles

Sticky Platelet Syndrome: History and Future Perspectives
in Seminars in thrombosis and hemostasis

The relationship between platelet to lymphocyte ratio and the clinical outcomes in ST elevation myocardial infarction
in Blood coagulation & fibrinolysis

Detection of platelet microRNA expression in patients with diabetes mellitus with or without ischemic stroke
in Journal of Diabetes Complications

Aspirin may modify tumor microenvironment via antiplatelet effect
in Medical Hypothesis

Some interesting articles

 

Optimizing current treatment of gout
in Nature Reviews Rheumatology

 

Anti-diabetic activity of insulin-degrading enzyme inhibitors mediated by multiple hormones
in Nature

 

Health eHeart: A Framingham Study for the Social Media Era?
An interesting concept

High-Platelet Reactivity and Stroke

Nevio Taglieri, and his colleagues from the University of Bologna (Bologna, Italy), conducted a meta-analysis of 14 studies (collectively enrolling 11,959 patients) to evaluate the risk of stroke in patients who had platelet testing while undergoing percutaneous coronary intervention (PCI). Among the studies included in the meta-analysis, prevalence of high platelet reactivity was 30% ±15% (range, 6% to 67%). As expected, prevalence of platelet hyperactivity was higher in studies using VerifyNow than in those using light-transmission aggregometery (LTA) (42% ±13% vs 22% ±10%; P = 0.006). Overall, the annual stroke rate was 0.9%. After pooled analysis, the risk of stroke was higher in patients with high platelet reactivity than in those without (1.2% vs 0.7%; RR 1.84; 95% CI 1.21-2.80).

The study provides interesting insights: first, it confirms the role of platelet aggregation in the athero-thrombo-embolic phenomena. Secondly, it suggests that there is a group of people who, despite having complete (near complete) blockage of P2Y12 receptors, may have higher activity through other platelet aggregation pathways and may benefit from a different drug. Of note, most patients in this meta-analysis were already on clopidogrel and aspirin, two of the several platelet aggregation pathways.

Multilevel Modeling and obtaining P-values

Something quick and to the point

A Gentle Introduction to Learning R

 

A gentle introduction to learning R – good resource for a beginner

Triple Anti-platelet Therapy

Role of platelets in acute coronary syndromes (ACS) is well established. Anti-platelet agents are standard of care for the prevention of ACS. However, due to the high risk of bleeding, anti-platelet agents except aspirin are not indicated for the prevention of ACS in primary prevention population as the risk of an ACS event is low. However, individuals with established CAD are at an increased risk of subsequent events and aspirin is indicated for such patients. In addition, those who has had a stent placed, usually get dual anti-platelet therapy (aspirin + either clopidogrel, prasugrel, or ticagrelor). One would imagine that in a very high-risk population, inhibition of an additional pathway may provide additional benefit. However, the TRACER trial, found that addition of vorapaxar, an oral protease-activated-receptor 1 (PAR 1) antagonist that inhibits thrombin-induced platelet activation, had no additional benefit in patient with acute coronary syndrome. In stead, addition of vorapaxar to the standard dual anti-platelet regiment was associated with increase risk of major bleeding. This study, suggested that perhaps too much of platelet inhibition may not be beneficial for ACS prevention but increases risk of bleeding.

More recently, a meta-analysis found that adding cilostazol, another anti-platelet agent that acts by inhibiting phosphodiestrase, to standard dual anti-platelet therapy was associated with 36% reduction in major adverse cardiac events (MACE; odds ratio (OR) = 0.64; 95% confidence interval (CI) = 0.51-0.81, P < .01), a 40% reduction (OR = 0.60, 95% CI = 0.44-0.80; P < .01) in target vessel revascularization (TVR), a 44% reduction (OR = 0.56, 95% CI = 0.34-0.91; P = .02) in target lesion revascularization (TLR) and a 47%/44% reduction in in-segment/in-stent restenosis (P < .01) and lower in-segment/in-stent late loss (P < .01). The effect sizes are large showing that the addition of cilostazol is very effective in reducing events. Cilostazol also inhibits smooth muscle contraction resulting in peripheral arterial dilatation. It is possible that the beneficial effect may be due to a combination of these two effects.

Thrombocytopenia in vWD type 2B

Von Willebrand factor (vWF) is a chaperone protein for coagulation factor VIII and is essential for the recruitment of platelets to the growing thrombus under conditions of high shear stress usually present in the arterial system. Deficiency (quantitative or qualitative) of vWF is associated with bleeding tendency, clinically known as von Willebrand disease (vWD).   Type 2 vWD is due to functional defect in vWF and type 2B is associated with gain-of-function mutations in the exon 28 of vWF gene resulting in an increase in the affinity of VWF for platelets. The region encoded by exon 28 binds to the platelet vWF receptor, glycoprotein Iba (GpIba). Patient with type 2B vWD present with bleeding and moderate to severe thrombocytopenia as well as a decreased in the high molecular weight vWF multimers. Thrombocytopenia is associated with the presence of giant platelets and spontaneous platelet aggregates. The molecular mechanism underlying the thrombocytopenia are unclear.

GpIba is present on the surface of megakaryocytes as well on platelets. Thus it is possible that interaction of mutated vWF from patients with type 2B vWD with megakaryocytes results in decreased platelet formation and release of giant platelets. In fact, Nurden et al showed that this may be the case. They showed that culture of megakaryocytes from controls performed with or without purified vWF had a positive influence on platelet production with specific inhibition by an antibody blocking vWF binding to GpIba . Megakaryocytes cultured with vWF from patients with type 2B vWD showed disorganized demarcation membrane system and abnormal granule distribution when examined under electron microscopy. The platelets produced from such megakaryocytes had abnormalities similar to those found in patients with vWD type 2B. This impaired megakaryocytopoiesis could not only explain the occurrence of giant platelets, but also contribute to a lower platelet count in VWD type 2B patients.

In addition to defects in platelet production, there may also be defects in platelet utilization, that is increased uptake of platelets (with attached vWF) by the monocyte-macrophage system of the body. Casari et al showed that this is also the case in a series of experiments reported here. They found that vWD type 2B platelets have a shorter circulatory half-life than wild-type (wt) platelets, which could contribute to the lower platelet counts in vWD type 2B mice. Further analysis revealed that VWF type 2B is present at the surface of platelets of thrombocytopenic
vWD type 2B mice, and that these vWF/platelet complexes were taken up efficiently by macrophages in liver and spleen. Thus, they provide direct evidence that part of the thrombocytopenia in vWD type 2B can be explained by an increased clearance of VWF/platelet
complexes.

Flow Cytometry Analysis in R

Here are some really nice lectures on this topic.

Explanation of different options for normalizations in Cufflinks

This is the best explanation that I have seen so far on the different normalization schema available in Cufflinks and how it affects calculation for FPKM. I am copying it directly from the thread which can be seen here

“With cufflinks you can have three different normalizations: fragments mapped to genome (in millions), fragments mapped to transcriptome (in millions: --compatable-hits-norm) or upper quartile (-N). Regardless of the normalization the same number of reads is quantified at each gene. I've looked into it myself. If you run cufflinks using all three of those normalizations then look at each of the separate isoforms.fpkm_tracking files you can confirm it. Check for the coverage and FPKM columns. You should see different FPKMs but identical coverages across the three quantifications. Furthermore if you divide the FPKMs by each other you should see that at each gene there's a constant ratio between the FPKMs.

If you calculate FPKMs yourself you can see why the numbers shift around. To be honest the "FPKM" designation is misleading when you're using any normalization other than "mapped reads in millions". Right? Fragments per kilobase per million mapped reads is what you're used to.
So say we have a gene that's 2500 bases long. We've got 121 fragments that mapped to it and we've got 34.7 million fragments mapped to the genome. We can get the FPKM like so..

FPKM = 121/(34.7*2.5) = 1.394813

Say only 27.4 million fragments mapped to the transcriptome. So if you used --compatible-hits-norm then the calculation looks like this:

FPKM = 121/(27.4*2.5) = 1.766423

Those aren't that different from one another. Now if you use upper quartile we're talking about the upper quartile value of fragments mapped to genes in the sample. That number might be something like 12,000. Divide this value by 1e6 to put it into "millions" like you do with mapped fragments it becomes 0.012. So now the calculation looks like this:

FPKM = 121/(0.012*2.5) = 4033.333

So maybe it makes sense to scale the upper quartile normalization value by 1000 so that the "FPKM" comes out as 4.033 instead of 4033. That's reasonable. But it really shouldn't be called an FPKM because if you think about it it's like someone telling you there are 14 cars outside and you assume they mean 14...but they actually told you 14 in base 16 which would be 20 in base 10 (or maybe like expecting a measurement to be in cm but you're given the measurement in inches with a cm designation). It's not fragments per kilobase per million mapped reads, it's fragments per kilobase per upper quartile of read counts @ genes. So FPKPUQRCG. That name sucks.

The point of these different normalizations is only applicable to when you're comparing samples to each other. So if you're goal is to see if gene X is expressed higher in Sample A verses B then regardless of the normalization used (as long as you use the same one on both samples) you'll find your answer. The upper quartile normalization has been showing to be more robust so maybe it's better to use it for comparing samples to one another. Also, obviously, for the expression levels to make sense to other people we all need to be using the same normalization. We should probably all be using upper quartile normalization but that puts the numbers on a different scale than we used to seeing.”

Extracting phenotype type by genotype using GenABEL

GenABEL is an excellent R package for GWAS studies. It uses special data structure to efficiently store data. The data structure is quite useful and results in remarkable time saving when running GWAS, it does have some limitations. For example, often in GWAS studies one need to know phenotype distribution across genotype of some variant but I couldn’t find a straightforward way of looking at phenotype distribution across genotypes (there may be a better way of doing it but I couldn’t find it)

To get phenotypic information across genotypes I used the following approach (assuming that data is in an object called ‘data’

1. Abstract phenotypic information
pheno<- phdata(data)
The returned object is a dataframe and can be confirmed with class(pheno) command

2. Abstract SNP data
snps <- as.character(data[, c("SNP1", "SNP2", "SNP3")])
You can change as.character in the line above with as.numeric if you want to get genotype information in 0,1,2 format.
The returned object is a matrix with row numbers as subject ID. Thus we need to do two things with this matrix. First we have to convert it into a dataframe and then we have to convert rownames into a column of id

3. Convert matrix 'snps' into a dataframe with row names as an additional column
snps.df<-data.frame(as.numeric(rownames(snps)),snps)
colnames(snps.df)[1]="id"                          ### Change the column name to 'id'
snp.data <- merge(pheno, snps.df, by="id")  

Now you have a dataframe with phenotype data and SNPs genotype data

Downloading and Merging NHANES datasets in R

The National Health and Nutrition Examination Survey (NHANES) is a program of studies designed to assess the health and nutritional status of adults and children in the United States. The survey is unique in that it combines interviews and physical examinations. The data files for more recent surveys are given in SAS Export format. To read these files in to R, one needs to use functions in the foreign package. If you don’t have this package, you may need to install it first. In the first step, we download these files and then in the second step we import these files to R.

# load foreign package (Converts data files into R)
require(foreign)    

# Set your working directory
setwd( "<YOUR WORKING DIRECTORY>")

### Download demographics file of NHANES 2005-2006 dataset
download.file(
ftp://ftp.cdc.gov/pub/Health_Statistics/nchs/nhanes/2005-2006/DEMO_D.XPT,
"Demo0506.xpt", mode='wb')

###Read downloaded file
Demo56<-read.xport("Demo0506.xpt")

### Download Blood pressure file of NHANES 2005-2006 dataset
download.file(
ftp://ftp.cdc.gov/pub/Health_Statistics/nchs/nhanes/2005-2006/BPX_D.XPT,
"BP0506.xpt", mode='wb')

### Read downloaded file
BP56<-read.xport("BP0506.xpt")

### Merge the two files
N_05_06 <- merge(Demo56, BP56, all=T)

You can download several files and then merge them together to get your dataset.

Updating R – in Windows 7

R is a great statistical software with tremendous flexibility. However, there is not a very straightforward (point and clinic) way of updating it. R Users have developed several different methods of updating R with its packages, including one described on CRAN.

I came across this one post, it is about updating R on Mac; tried it on Windows 7 with minor changes and it worked fine.

So here is what I did:
First, in the older version I wrote following commands
tmp <- installed.packages()
installedpkgs <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
save(installedpkgs, file="installed_old.rda")

Then I downloaded and installed newer version of the R. In the newer version of R I wrote following commands:
source(http://bioconductor.org/biocLite.R)
biocLite()
load("installed_old.rda")
tmp <- installed.packages()
installedpkgs.new <- as.vector(tmp[is.na(tmp[,"Priority"]), 1])
missing <- setdiff(installedpkgs, installedpkgs.new)
for (i in 1:length(missing)) biocLite(missing[i])

All packages were automatically installed to the newer version. Then, I went to Windows Control Panel and uninstalled the older version of R.

That’s it!

Some R Code Using SAScii

For example, I want use Adult Demographic File from NHANES III. To import it using SAScii

library(SAScii)
SAScode <- "ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/nhanes/nhanes3/1A/adult.sas"
ftpdata <-"ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/nhanes/nhanes3/1A/adult.dat"
data <- read.SAScii(ftpdata, SAScode, beginline=5)

Because the line with INPUT in the SAS code file begins at line 5, I gave the option begineline=5. Of course, it assumes that you have downloaded and installed the package ‘SAScii’. Now you can save this file in any desirable format or use it for further downstream analysis. It does take quite sometime, longer than what it would take using SAS, but it does produce desired output.

An Interesting R Package–SAScii

For several surveys, such as NHANES III, data for many files is available in ASCII format with SAS code. However, those of us, who want to use that data in R, it is little cumbersome to use first SAS, import data into it, then transfer data into a format that can be imported into R. I came across of this relatively new package, SAScii, that uses the ASCII format and then SAS code to directly import data into R. Quite nice.

REDUCE Trial – My Thoughts

This week, REDUCE trial was published in JAMA “Short-term vs Conventional Glucocorticoid Therapy in Acute Exacerbations of Chronic Obstructive Pulmonary Disease; The REDUCE Randomized Clinical Trial” JAMA. 2013;():1-9. doi:10.1001/jama.2013.5023.

REDUCE (Reduction in the Use of Corticosteroids in Exacerbated COPD), was a randomized, non-inferiority multicenter trial in 5 Swiss teaching hospitals that enrolled 314 patients (between March 2006 through February 2011) who had presented to the emergency department with acute COPD exacerbation and were past or present smokers (≥20 pack-years) without a history of asthma. Participants were treated with 40 mg of prednisone daily for either 5 or 14 days in a placebo-controlled, double-blind fashion. The predefined non-inferiority criterion was an absolute increase in exacerbations of at most 15% or a 6 months follow-up. The trial found that 5-day treatment with systemic glucocorticoids was non-inferior to 14-day treatment with regard to re-exacerbation within 6 months of follow-up but significantly reduced glucocorticoid exposure.

The trial results are interesting for those of us who actually practice medicine and see COPD patients on a regular basis with exacerbations. There are three settings in which the results of this trial can potentially impact practice. In office practice, there are definitely some patients who would do just fine with 5 days course of prednisone and these are patients who get prescribed Medrol dose pack. On the other hand, there are patients who need longer courses of steroids and for such patients it is important to give them longer courses of steroids (up to 14 days and sometimes even longer) to keep them out of hospital. Interestingly, based on only the severity of the patient’s symptoms and signs alone, it is impossible to predict who will need longer treatment. It is only history of the patients that tells what will work. The practice in Emergency Department is unlikely to be much different than in an office setting except that there may be patients with more severe exacerbation. There too, history is the only helpful thing. However, once patients are admitted to the hospital, it is likely that these are those subsets of patients who didn’t respond as quickly to steroids in ED and thus needed admission with persistent severe symptoms. For such patients, it remains a possibility that a larger number (if not all) of them will need longer therapy.

Thus, in my view, if a patient is new to me and presents with COPD exacerbation and I don’t have historical information on this patient, I will feel comfortable in giving this patient a 5-day course of steroids. Otherwise, if I have some additional information telling me that shorter course will not be helpful, I should go for longer course.

VPREB3 and Platelets

VPREB3 protein is the human homolog of the mouse VpreB3 (8HS20) protein, and is specifically expressed in cell lines representative of all stages of B-cell differentiation. It is also related to VPREB1 and other members of the immunoglobulin supergene family. This protein associates with membrane mu heavy chains early in the course of pre-B cell receptor biosynthesis. The precise function of the protein is not known, but it may contribute to mu chain transport in pre-B cells.

This protein doesn’t appear to be detectable in platelet proteome studies but its transcript is present in platelets (detected by both RNA-seq and microarray studies). Its role in platelet biology remains unclear. Even interesting is that the RNA-seq experiment found a much lower expression level than the microarray experiment (0.15 RPKM vs. 27250 MFI). Perhaps the level of gene expression is quite variable from person to person.

CD23 and Platelets

CD (Fc Epsilon Receptor II), has been shown to be present in platelets and may play a role in platelet aggregation. However, none of the publically available platelet proteome databases (Martens et al. Proteomics 2006; Burkhart et al, Blood 2012; Vaudel et al, Journal of Proteome Research 2012) have found this specific protein in platelets. When looking at transcriptome, CD23 RNA doesn’t appear to be present in megakaryocyte (using microarray). However, platelet RNA-seq analysis have found low levels of transcript in platelets (RPKM = 0.37).

While it is easy to speculate why there is such a discrepancy, it is possible that CD23 is induced in people with some allergy exposure and in individuals who are otherwise healthy (as were people in the studies that failed to find CD23), this transcript and its product may not be detectable.

It will be worthwhile to look at individuals with allergic responses (or parasitic infections) and examine whether they have higher expression of CD23 gene and protein. Comparing platelet aggregation in individuals with allergies and those without may also be illuminating.

Here comes STREAM ……

The results of STREAM were presented at ACC meeting and study was published online in NEJM – “Fibrinolysis or Primary PCI in ST-Segment Elevation Myocardial Infarction”. In nutshell the results can be summarized as pre-hospital fibrinolysis with bolus tenecteplase in conjunction with timely coronary angiography was similar to primary PCI in patients with early STEMI who could not undergo primary PCI within 1 hour after the first medical contact. Patients who failed fibrinolysis underwent emergent PCI (36.3% of the fibrinolysis group). Cardiogenic shock and congestive heart failure occurred more often in the primary PCI group and intracranial hemorrhage and ischemic strokes were more frequent in the fibrinolysis group. The study findings are likely to be reassuring for some parts of the world while may change treatment strategies at other places.

Some Useful Shell Commands for Cluster

bkill
especially bkill 0 as it will kill all jobs submitted by the user

bjobs

bhosts

Farnesyl Pyrophosphate and ADP-mediated Platelet Aggregation

Read this article recently and it seems interesting. Farnesyl pyrophosphate (FPP) can itself activate platelets and can induce platelet aggregation. However, this study concludes that FPP can act as endogenous antithrombotic factor by acting as insurmountable antagonist of ADP-mediated platelet aggregation. FPP is an intermediate in the cholesterol biosynthetic pathway. FPP also serves as a donor in post-translational isoprenylation of proteins. The steady-state plasma level was reported to be 6.6 ng/ml,  but  even  the  mild  physiological alteration caused by eating a meal has been demonstrated to increase the plasma concentration 200 fold. FPP is a natural antagonist of the LPA₂  (lysophosphatidic acid type 2) and LPA₃  receptors, and an agonist at the LPA₄  and LPA₅ receptors. While these receptors are present in platelets, FPP doesn’t appear to act through these receptors. Hogberg et al realized that the structure of ADP and FPP is similar as are their receptors. Thus, through a series of experiments they should that FPP inhibits platelet aggregation by blocking ADP receptors.

Platelet Function and Subsequent MACE in ACS patients

An interesting substudy of TRILOGY ACS was published in JAMA recently in which a group of patients with ACS underwent evaluation of platelet function after prasugrel or clopidogrel. All patients were also on aspirin. Thus, platelet function studies were performed after treatment with aspirin + prasugrel and aspirin + clopidgorel. TRILOGY ACS trial was a randomized, double-blind, active-comparator trial comparing prasugrel with clopidogrel in patients with unstable angina or non–ST-segment elevation myocardial infarction (UA/NSTEMI) who were managed medically without planned revascularization.Platelet function was assessed in a subset of enrolled patients using VerifyNow kits. VerifyNow P2Y₁₂ is a whole-blood, turbidimetric-based assay that measures platelet agglutination to fibrinogen-coated polystyrene beads after platelet activation with adenosine diphosphate. The results are expressed in PRU (P2Y₁₂ reaction units). There was no significant association between platelet reactivity and occurrence of ischemic outcomes during a 30 month follow-up period.

The results of this study are important; it is a large study, enrolling a high-risk population and followed for a relatively longer period of time. While trials of antiplatelet agents have established, beyond doubt, that platelet play an important (if not essential) role in the pathogenesis of ACS and perhaps also in the development and progression of atherosclerosis, studies have generally failed to find an association of platelet function with future events. Probably the most likely explanation is that we have, so far, been unable to identify a platelet function test that ACTUALLY measures platelet function in a way which is important clinically. We can predict bleeding but not aggregability. We do need to explore existing platelet function tests for association with future events that have not yet been examined and we also need to develop newer tests that are more closer in measuring what happens inside the vessel.

Today’s Interesting Links - September 10th, 2012

 

Genetic polymorphisms of CYP2C19 influences the response to clopidogrel in ischemic heart disease patients in the South Indian Tamilian population.

Regulated granule trafficking in platelets and neurons: A common molecular machinery

Idiopathic Sudden Sensorineural Hearing Loss: Classic Cardiovascular and New Genetic Risk Factors

Panobinostat (LBH589)-induced acetylation of tubulin impairs megakaryocyte maturation and platelet formation.

Itga2b regulation at the onset of definitive hematopoiesis and commitment to differentiation

Effects of clopidogrel added to aspirin in patients with recent lacunar stroke