Differential Gene Expression: Ischemic vs. Nonischemic

1. Differential Gene Expression: Ischemic vs. Nonischemic Jing Hu Dongmei Li Shuyan Wan Richard Yamada Jeong-Me Yoon Zailong Wang (Mentor)

Introduction and summary of previous work (Richard)

Exploratory Analysis of Data (Jeong-Mi)

Statistical Methods (Shuyan)

Selected Gene Analysis (Jing)

Conclusions and Further Work (Dongmei)

Ischemic Lack of Blood and Oxygen

Cardio Refers to the Heart

Myopathy Muscle Related Disease

ischemic cardiomyopathy is a medical term that doctors use to describe patients who havecongestive heart failurethat is a result ofcoronary artery disease . (coronary arteries are blocked)

Risk Factors: genetics, smoking, high fat diet, obesity, and prior heart problems

Incidence: 1 in 100, typically male, starting with middle age

Symptoms include: chest pain, shortness of breath, irregular/rapid pulse, and sensation of feeling the heart beat

Treatment Regimens: ACE inhibitors, beta blockers, angioplasty (to improve blood flow to the damaged or weakened heart muscle), and heart transplant (severe cases)

What kinds of changes occur in cardiac transcription profiles brought about by heart failure?

2 ways to go about attacking the question: Molecular Biology (hypothesis based) vs High Thru-put techniques (i.e. microarrays followed by confirmation of gene expression with qPCR)

Gene expression analysis of ischemic and nonischemic cardiomyopathy: shared and distinct gene in the development of heart failure

M. Kittleson, K. Minhas, R. Irizarry, S. Ye, G. Edness, E. Breton, J. Conte, G. Tamselli, J. Garcia, and J. Hare. Physiol. Genomics, 21:299-307, 2005

31 cardiomyopathy vs. 6 normal patients (clinical characteristics were reasonably similar within groups)

Tissue taken from cardio-myopathy patients at the time of LVAD or cardiac transplantation

Identified differentially expressed genes in 2 comparisons: NICM (hypertrophic, valvular, alcholic) vs NF hearts and ICM vs NF using significance analysis of microarrays

Identified genes with FDR < 5% and absolute fold change greater than 2.0

No hypothesis, but the microarray experiment was used to generate hypothesis

Types of genes differentially expressed (41 total): cell growth maintenance(9), signal transduction(7), metabolism(3), cell adhesion/cell communication(2), binding(2), and catalytic activity(2), nucleus(3), other (13)

Predominance of fatty acid metabolic genes genesis of NICM might be metabolic in nature

Predominance of abnormalities in catalytic activity with ICM (serine proteinase inhibitors)

TNFRSF11B (member of TNF receptor subfamily) is significantly downregulated in ICM

Collected myocardial samples from patients undergoing cardiac transplantation whose failure arises from ischemic cardiomyopathy and from "normal" organ donors whose hearts cannot be used for transplants

The transcriptional profile of the mRNA in these samples was measured with gene array technology.

Changes in transcriptional profiles can be correlated with the physiologic profile of heart-failure hearts acquired at the time of transplantation.

Because of the results of Kittleson et al, we can generate a simple working hypothesis:

Our differentially expressed genes, using our methods of statistical analysis of the data, should roughly be the same as what Kittleson et al obtained in their paper .

Goal: identify genes whose expression levels are

differentially expressed between Ischemic and

Normal.

Affymetrix Data with Two Population:

54,675 genes are expressed

for32 Ischemic samples

14 Normal samples

How do we compare?

Pre-processing:

Only obtain the expression measurementof the data (ie., put it into exprSet) using thedefault of justRMA method:

bgcorrect.method = rma

normalized.method = quantiles

summary.method = liwong

Histogram of Ischemic/Normal :

The distribution is skewed right.

The rangeis between 4 to 14.

Both histograms have similar shapes.

Boxplot of Ischemic/Normal:

There are many outliers from the upper values.

The intensity of Ischemic is higher than Normal.

Histogram of MAD (Median Absolute Deviation)

&Cut-off Method by MAD :

Apply MAD > 0.1.

We can filter out 675 genes from a total of 54675 genes.

Quantile-Quantile plot:

A visual aid for identifying genes with unusual test

statistics.

It shows the large deviation at the right tail.

t-Testfor:

Mean difference between Ischemic and Normal

H 0:H 1 :

We are testing 54675 genes simultaneously and adjust for multiple testing when assessing the statistical significance of the observed associations to control the false positive rate.

Motivation:

To identify as many differentially expressed genes as possible, while incurring a relatively low proportion of false positives.

H 0 : No differential gene expression (between Ischemic and normal group)

Large multiplicity problem: more than fifty thousand hypotheses are tested simultaneously.

How can we control the false positive rate genomewide? FDR or pFDR.

FDR: = E(F/S)

In case S=0, defined to be: E(F/S|S>0)P(S>0) or define F/S=0 if S=0.

Alternatively, definepFDR =E(F/S|S>0). When m is large, P(S>=0) is approx. 1 and FDR is approx. equal to pFDR.

FDR is a measure of the overall accuracy of a set of significant features.

Select desired limitqon E(FDR)

Reject

Order the p-values

For an individual hypothesis,

Multiple testing of such data will produce correlated test statistics !

RNA source

normalization process

pooled variability estimation

Between genes :

Between measurement errors of expression levels :

Positive Dependency

(Benjamini & Yekutieli, 2001 and Yekutieli, 2002).

The linear step-up procedure controls the FDR for positive dependent test statistics.

This condition is satisfied by :

- positively correlated one-sided normal and t test statistics.

- absolute values of normal and t test statistics, when all null hypotheses are true.

adjustedp -values for the Benjamini & Hochberg (1995) step-up FDR controlling procedure (independent and positive regression dependent test statistics).

adjustedp -values for the Benjamini & Yekutieli (2001) step-up FDR controlling procedure (general dependency structures).

rawpBHBY

017577 17577 17577

1e-04 384003796035207

2e-04 39239 38833 35935

3e-04 39717 39334 36373

4e-04 40053 39690 36714

5e-04 40321 39972 36966

6e-04 40565 40174 37166

7e-04 40786 40389 37370

8e-04 40948 40569 37513

9e-04 41096 40739 37661

0.0141226 40885 37781

Further select genes based on the fold change between two conditions (Ischemic vs. Normal)

The fold change for each gene is calculated as the average expression over all Ischemic samples divided by the average expression over all normal samples.

There are 1495 genes with Log2(fold change) > 1, and 26 genes with Log2(fold change) < -1

There are only 43 genes with Log2(fold change) > 2, and 3 genes with Log2(fold change) < -2

We choose the first option

Among the 54,675 mRNA transcripts present on the Affymetrix microarray platform, 675 housekeeping genes were filtered out.

By selecting the adjusted P-value less than 0.0001, only 35,207 genes are left for the analysis of fold change.

After fold change selection, only 1521 genes are leftfor further selection.

Finally, 74 up-regulated genes and 26 down-regulated genes are selected from the microarray analysis for further biological verification and study.

Of the 100 genes, there are 53 genes that have known biological functions. The functions of the other 47 genes are unknown.

Based on the biological process of the genes, the 100 genes can be classified in several categories.

Among the 100 genes that are differentially expressed between ischemic and normal, the majority fell into cell adhesion, cell growth and maintenance, signal transduction, muscle contraction and development, immune response andregulation of transcription.

Most of the genes are up-regulated in above process except one or two genes in the process of cell growth and maintenance and cell adhesion.

Few genes belong to metabolism, inflammatory response, acute phase response and oncogenesis.

Serine proteinase inhibitors has an anti-ischemic protective effect and has been previously observed in pigs subject to experimentally induced myocardial ischemia (Khan 2004): Aprotinin reduces reperfusion injury after regional ischemia and cardioplegic arrest. Protease inhibition may represent a molecular strategy to prevent postoperative myocardial injury after surgical revascularization with cardiopulmonary bypass.

It was hypothesized to ben an important gene in Kittlesons paper (Physiol. Genomics, 2004).

The gene differentiation analysis find out the genes that either up-regulated or down-regulated in ischemic patients, which can correlated with clinical parameters in heart failure patients and supported ongoing efforts to incorporate expression profiling-based biomarkers in determining prognosis and response to therapy in heart failure.

Although only one common gene is found in the analysis, it is consistent considering the sample size difference, the tissue difference and the statistical analysis method difference.

However, most of the genes identified from the analysis fell in the same categories of the biological functions.

Because circumstances causing a donor heart to be ineligible for cardiac transplantation, such as infection or prolonged hypotension, can also affect gene expression, a normal functional unused donor heart is not the same as a normal heart.

First, the gene expression profile of these 100 genes need to be verified by the Northern Blot or Real-Time RT-PCR (qPCR).

After verification, some high fold change unknown function genes can be chosen to study their functions for biologists.

MBI (Prof. Friedman and staff)

Professors Shili Lin and Joseph Verducci

Dr. Zailong Wang

Dr. Nusrat Rabbee

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Differential Gene Expression: Ischemic vs. Nonischemic