Combined Analysis of Micro RNA and Proteomic Profiles and Interactions in Pat...
01-Brianna_Chan
1. Quantitative Histology of Macrophages in
Lung Parenchyma of COPD Patients with
Alpha-1-Antitrypsin Deficiency
Brianna Chan
Summer Student
Hogg Lab
Summer Student Research Day
12th
August, 2014
3. Proteases from Neutrophils and
Macrophages cause Emphysema
Matrix metalloproteinase
(MMPs)
Macrophages
Emphysema
Smoking
Neutrophil Elastase
Neutrophils
• P599
Sept 2013
Similar adaptive immune response in COPD
patients with and without α1 antitrypsin
deficiency
S. Baraldo, M. Saetta, et. al.
• Macrophage and neutrophil counts in patients
with severe COPD, both with AND without
AATD, are similar
4. Hypothesis
• There is no difference in cellular infiltrate
associated with emphysematous destruction
in COPD with and without AATD
Aim
• To extract lung tissue sections for IHC for
point counting
• To determine volume fractions of
macrophages in COPD lungs with and without
AATD, compared to controls
5. Demographic Data of Subjects
Group Age Sex Genotype
Smoking Index
(pack-years)
Number of
Cores
Number of tissue
sample sections
(1 per core)
Control
42 M MM 15
47
129
65 F MM NA
64 M MM 15
53 M MM 0
77 M MM 0
AATD
55 M ZZ 6
37
39 F ZZ 18
51 M ZZ 25
55 M ZZ 9
48 M ZZ 25
COPD
77 F MM 45
45
59 F MM 40
58 F MM 30
55 M MM 80
53 F MM 24
*AATD (Alpha-1-Antitrypsin Deficiency)
7. Point counting
• Positive cells (macrophages)
• Positive cells in air space cells
• Negative cells (all other alveolar tissue)
129 sections x 8 sub-images each
=1032 sub-images counted
=77,022 Clicks!
8. VvofMacropahges
inlungparenchyma(%)
Control AATD COPD
0
10
20
30
40
50 p-value = 0.027
Kruskal-Wallis Test
Volume Fraction of Macrophages per Case
Volume Fraction= Number of total positive cells (from alveolar tissue and in air spaces)
Total number of all cells (Positive cells + Negative cells)
n=5 n=5 n=5
9. • No difference in Vv of macrophages in diseased lungs
• Control lungs appear to have an average Vv even higher than
the diseased lungs
• Macrophage may play a different role in controls versus
diseased lungs
Increased macrophage levels ≠ Increased amount of MMP
proteases secreted
• Macrophages are important in the development of
emphysema in COPD
Conclusion
10. Future Directions
• Pair current results with micro-CT scan for mean
linear intercept (Lm) and lung heights
• Investigate other cell types see whether the
phenomenon was also found in other cells
• Gene expression and microbiome analyses
• Correlate occurrences of inflammatory cells to
discover the pathogenesis of inflammation in COPD
lungs with AATD
11. Acknowledgements
•Dr. James Hogg
•Dr. Dragoş Vasilescu
•Dr. Daisuke Kinose
•Dr. Mark Elliott
•Jaimmie Que
•Fanny Chu
•Dean English
•Dr. Stephan van Eeden
•Dr. Tillie Hackett
•Dr. Hyung-Kyung Koo
•Marc Sze
•Malik Carroll
• Dr. Joel Cooper
• Dr. Marc Decramer
• Dr. Bart Vanaudenaerde
• Dr. Geert Verleden
• Dr. Stijn Verleden
13. Average Volume Fraction per Lung Group
Volume Fraction= Number of total positive cells (from alveolar tissue and in air spaces)
Total number of all cells (Positive cells + Negative cells)
14. Image Extraction
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Editor's Notes
My name is Brianna Chan, I am an undergraduate student working in Dr. Hogg’s lab this summer and I would like to talk about my project on quantitative histology of macrophages in lung alveolar walls of COPD patients with AATD.
From many previous presentations, we have already heard much about COPD and its symptoms and risk factors, so I will not go into detail for that in my presentation, but specifically for our study, I would like to emphasize that the underlying mechanism of inflammation in COPD is important because of our focus on inflammatory cells.
Alpha-1 Antitrypsin Deficiency (or AATD) is a rare genetic disorder caused by several misense mutations in a gene that predisposes subjects to COPD. People with this disorder have a deficiency of Alpha-1 antitrypsin, which is an important lung protease inhibitor produced by the liver (hepatocytes) for neutrophil elastase. Under normal secreting conditions, the function of neutrophil elastase is to kill bacteria that invades the lungs. However, its other function is also to break down elastic fibres (elastin and collagen) in the alveolar wall as part of the normal tissue regeneration process. AATD patients lack this enzyme that leads to excessive and uninhibited destruction of elastic fibres causing a gradual loss of elasticity in the lungs leading to emphysema due to an imbalance between proteases and its inhibitor that causes more digestion of extracellular matrix molecules. This is the classical theory of emphysema known as the protease-antiprotease imbalance hypothesis.
Although early attention was focused on neutrophil elastase, since then, many other proteases have been implicated that have similar capacity to degrade elastin.
We chose to investigate macrophages in this study because they are the other innate immune cell that also have proteinases that perform similar functions as neutrophil elastase. These are known as MMPs. They are enzymes that degrade extracellular matrix molecules by inactivating cytokines and cleaving cell surface receptors. Similar to neutrophil elastase mechanism, smoking induces macrophages to activate MMPs which degrades alveolar lung tissue causing emphysema.
The reason for our interest in these inflammatory cells is due to a recent study conducted by an Italian group who presented at the European Respiratory Society Conference last fall with their poster titled “Similar adaptive immune response in COPD patients with and without α1 antitrypsin deficiency” From their findings, it is reported that innate inflammatory cell counts in patients with severe COPD, both with AND without AATD, are actually similar.
Therefore, this leads to our hypothesis that there is no difference in inflammatory cell counts associated with destruction of lung tissue by emphysema in COPD with and without AATD.
To investigate our hypothesis, we use Systematic Uniform Random Sampling (SURS) to extract tissue sections from lungs for IHC staining to determine volume fractions of macrophages in COPD and AATD lungs by point counting.
We have 3 groups of lung samples, separated into donor controls, AATD and COPD (without AATD). Each group includes 5 lungs (known as cases).
We can notice a trend that AATD patients in general were slightly younger than COPD patients, and their smoking index were less than COPD.
We perform genotyping of the alpha-1 antitrypsin gene, with the ZZ allele responsible for the deficiency, whereas both control and COPD groups have the wild type MM homozygous allele.
Here are the number of cores per group, to make a total of 129 cores from which 1 section is taken per core.
After we obtain a shipment of lungs from our collaborators, the lungs are first inflated by air, frozen in liquid nitrogen, and then weighed.
The whole lung is first taken for an MDCT scan to find the whole lung volume and lung density.
Then, the lung is sliced into slabs of around 2 cm thick.
Next, by random sampling, a cluster of 4 cores are taken from a slab of lung. Here is an image of me coring under supervision.
Each core is used for a different purpose to collect specific information for our larger study.
For histology, 1 core would be taken for embedding and infiltration by fixative (OCT), and cut by a cryostat for frozen thin sections of 4 um thick and placed on a glass slide. These secitons would then undergo immunohistochemical staining. In this study specifically for macrophages, we used CD68+ antibody solution for detection and identification of macrophages.
This is an image of me doing titration to obtain the optimal dilution for staining, with the new auto-staining machine behind me.
Here is an example of a section that was obtained after imaging. From each of these sections we overlay squares in which 8 of these sub-images are extracted by systematic uniform random sampling for point counting to obtain the volume fraction of macrophages in order to investigate the extent of inflammation.
Due to the interest of time I will not go into detail about the image extraction technique, but if any of you are interested I can explain further during the Q&A session.
Here is an example of a sub-image that is used for point counting.
Now comes the bulk part of my involvement in the study, which is point counting.
We overlay a grid on top of the image (323 point grid), then count the crosses that fall on tissue.
Here is a close up.
Specifically, positive cells are macrophages stained red that fall on tissue.
Positive cells in air spaces are macrophages that are detached from the tissue (but are nonetheless still our target cell).
Negative cells are all the remaining cells that fall on alveolar tissue that are stained purple.
As you can see the image seems to have a lot of red staining, so this specific image would probably generate quite a large volume fraction of macrophages.
To give you an idea of how much work was done, we had 129 sections from which 8 images were taken from each section, generating a total of 1032 sub-images which equal to 77,022 clicks. This process took e approximately one and a half months to finish.
Here comes the most exciting part of the research, the results!
This is the volume fraction graph of macrophages per case in each lung group, on the x-axis from left to right the controls, AATD and COPD, with each group having 5 lungs. The volume fraction of macrophages on the y-axis is expressed as a percentage using the formula for volume fraction as shown.
We ran a Kruskal-Wallis test for one-way analysis of variance, since we have more than two independent samples, this method did not assume normal distribution of the residuals.
Our measurements do not show a difference between the Vv of macrophages found in either disease group (COPD or AATD), and the variability between cases were low. However, as the P-value <0.05, the difference is statistically significant for an increase in Vv of macrophages in donor control lungs, and have larger variability between cases, which is contrary to our previous studies where controls typically had lower Vv than diseased lungs.
Results of the current study indicate that there is no significant difference in Vv of macrophages in diseased lungs, however interestingly, control lungs appear to have an average Vv even higher than the diseased lungs, especially in 2 lungs which we suspect may be correlated to 15-pack year smoking that pulled up the average mean Vv, or this may have been due to a variety of reasons that are currently unconfirmed at this time due to the observational nature of this project. It may have been a technical issue such as using a new staining system that is more sensitive, or something more fundamentally biological. The controls were donor lungs from brain dead patients that were unsuitable for transplantation, which may have something to do with the inflammatory condition once it is extracted from the body.
We deduce that macrophages may play a different role in controls versus diseased lungs; and in relation to our rationale for studying macrophages, perhaps increased macrophage levels may not mean increased amount of MMP proteases secreted due to the higher Vv in controls phenomenon observed.
Nevertheless, we still believe that macrophages are important inflammatory cells in the development of emphysema in COPD, as supported by the large Vv of macrohpages in diseased lungs, but we just don’t know the mechanism and to what extent it is held true.
(Some reasons include technical factors such as difference in staining as we now have a new staining machine that seems to have a higher sensitivity for stains than the old machine, perhaps we should have diluted the antibody solution more; our new sampling method using SURS that was not used in previous studies; or demographics of the patient population of the control sample lungs just happened to have more macrophage counts compared to regular alveolar tissue. Shrinkage of tissue tends to occur in control lungs during inflation process causing larger amount of macrophages to show up on images.)
As our study data showed some unexpected results compared to previous studies, we still have much work to do. Our immediate next steps would be to pair results of the current study with micro-CT data on the same core cluster taken for histology for the mean linear intercept to find average distance between lung alveolar walls, and lung heights, which is the position of the core section in the region of lung. We are also in the process of investigating other inflammatory cell types such as neutrophils, CD4 and CD8 cells, in fact several of our lab members are currently collecting data for neutrophils and B cells. We want to do this firstly to see whether the phenomenon of higher Vv in controls was observed versus diseased lungs, which may give us an idea of why this trend is happening and what went wrong (if it had something to do with the study protocol). We may also carry out gene expression and microbiome analyses on AATD lungs later on.
All these information would also help correlate the occurrences of inflammatory cells using information such as lung density, volume and region of disease to discover the pathogenesis of inflammation in COPD lungs with AATD, which may predict clinical outcomes for the treatment of COPD in the very long run.
I would like to thank Dr. Hogg for the opportunity to partake in such interesting pulmonary research, supervisors/mentors Dragos and Daisuke for introducing me to the project, preparing me with necessary skills to carry out this research and overseeing the project in general, and all the others for their lab expertise and giving me advice during the lab meetings.
Also I would like to acknowledge our collaborators in the USA and in Belgium who provided us with the invaluable lungs. Without them, we cannot carry out this research.
Thank you for listening and please feel free to ask any questions and I will try my best to answer them.
Points represent cores
Different colours represent different cases
We can see that the diseased cases on average have smaller variation between cores compared to controls.
There are several outliers that may have contributed to the increased Vv in groups.
This is the volume fraction graph of macrophages, with the volume fraction as the y-axis and the 3 groups of lungs as the x-axis.
The formula for volume fraction is as shown.
Describe SURS in image extraction
Draw large square covering most of the core
Use excel program Dragos provided to generate smaller squares by random sampling
Exclude all airways and blood vessels, or if no tissue falls on square, margins, take only parenchyma
Count total number of included squares and number then in an S shaped fashion for the remaining squares
Divide number by 8 since our aim is to obtain 8 sub-images
Round down to get nearest integer (~2.3=2)
Take random number from random number generator online (e.g. Got 1), take next 7 images to get a total of 8 images to count per core (1,3,5,7,9,11,13,17)
This is a close up of an extracted image.
Stereology
3D interpretation of 2D cross sections of materials or tissues
SURS is a design-based sampling principle typically used in modern stereology in biomedical research. We take our sample of plane sections by following a randomized sampling design, in our study by choosing a random position at which to start cutting the lung slabs to generate cores, or to extract images from a core section (from random number generator). Extrapolation from the sample to the 3-D material is valid because of the randomness of the sampling design
SURS provide unbiased and quantitative data representative of entire unit sampled, making it possible to estimate total quantities by extrapolation without actually having to process entire unit (impossible, time consuming, expensive)
The popular science fact that the human lungs have a surface area (of gas exchange surface) equivalent to a tennis court (75 m2), was obtained by stereological methods
