ISSN 00062979, Biochemistry (Moscow), 2013, Vol. 78, No. 8, pp. 933945. © Pleiades Publishing, Ltd., 2013. Published in Russian in Biokhimiya, 2013, Vol. 78, No. 8, pp. 11871200.
Coordination in Gene Expression during Atherogenesis T. A. Shchelkunova1*, I. A. Morozov2, P. M. Rubtsov2,3, L. M. Samokhodskaya4, I. A. Sobenin5, A. N. Orekhov5, and A. N. Smirnov1# 1 Biological Faculty, Lomonosov Moscow State University, Leninsky Gory 1/12, 119899 Moscow, Russia; fax: (495) 9394309; Email: schelkunova[email protected] 2 Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, ul. Vavilova 32, 119991 Moscow, Russia; fax: (499) 1351405; Email: [email protected] 3 Moscow Institute of Physics and Technology, Institutskii Pereulok 9, 141700 Dolgoprudny, Moscow Region, Russia; fax: (495) 5760813 4 Faculty of Fundamental Medicine, Lomonosov Moscow State University, Lomonosovsky pr. 31/5, 119899 Moscow, Russia; fax: (495) 9329904; Email: [email protected] 5 Institute of General Pathology and Pathophysiology, Russian Academy of Medical Sciences, ul. Baltiiskaya 8, 125315 Moscow, Russia; fax: (495) 4159594; Email: [email protected]
Received March 13, 2013 Abstract—General tendencies in the regulation of gene expression during atherogenesis were investigated using correlation analysis for 34 mRNA species of several functional groups. The contents of mRNA were measured by quantitative PCR in samples of human aortal intima containing no lesions or atherosclerotic lesions of types I (initial lesions), II (fatty streaks), and Va (fibroatheromas). The coupling between mRNA contents in lesions and the same mRNAs in intact tissue was found to descend in the course of the disease progression. The data are in accordance with the opinion that successive morpho logic types of atherosclerotic lesions correspond to steps of atherogenesis. In addition, the contents of individual mRNA species could correlate with each other within the given sample type, the extent of this coupling rising along with the dis ease progression. The exception from this rule was a collapse in coupling for several functional groups of mRNA in lesions of type I. This collapse could indicate special position of these lesions in pathogenesis. Statistically significant correlations between mRNAs found in samples of all four types comprised in total about 50% of all possible correlations. 66% of these correlations were conservative, i.e. observed in at least two sample types. By couplingstrength, the studied mRNAs could be divided into four clusters whose composition significantly varied along with the disease progression. The disease pro gression was also associated with decline in number of regulatory factors that determine coordination in expression of the analyzed genes. DOI: 10.1134/S0006297913080117 Key words: mRNA, PCR, gene expression, atherogenesis, aorta, correlation analysis
Atherosclerosis manifested as a wall thickening and luminal narrowing of large arterial vessels is one of the most frequent disorders and a cause of about 30% of deaths worldwide [1]. The development of local inflam
mation and lipid deposition (intra and extracellular) are two hallmarks of atherosclerosis, the two stimulating each other [2, 3]. Atherogenesis can be stimulated by a variety of factors including turbulence in the bloodstream in cer
Abbreviations: ABCA1 and ABCG1, ATPbinding cassette transporters A1 and G1; ACAT1, acylCoAcholesterol acyltransferase 1; ApoE, apolipoprotein E; AR, androgen receptor; Arom, aromatase; CCL18, CC motifcontaining chemokine 18; CD36, CD63, and CD68, differentiation clusters 36, 63, and 68; CEH, cholesteryl ester neutral hydrolase; EEA1, early endosome antigen 1; ERα, estrogen receptor alpha; EST, estrogen sulfotransferase; GAPDH, glyceraldehyde3phosphate dehydrogenase; GNB2L1, guanine nucleotidebinding protein, betapeptide 2like 1; ICAM1, intercellular adhesion molecule 1; Lamp 1/2, lysosomeasso ciated membrane glycoproteins 1 and 2; LDLR, low density lipoprotein receptor; LXRα and LXRβ, liver X receptors alpha and beta; p62, ubiquitinbinding protein p62; PPARα and PPARγ, peroxisome proliferatoractivated receptors alpha and gamma; Rab5a, Rasrelated small GTPase 5A; SELE, selectin E; SRA, scavenger receptor A; SRBI, scavenger receptor BI; SREBP1 and SREBP2, sterol regulatory elementbinding proteins 1 and 2; STS, steroid sulfatase; TfR1, transferrin receptor 1; TLR4, Tolllike receptor 4; TNFα, tumor necrosis factor alpha; VCAM1, vascular cell adhesion molecule 1. * To whom correspondence should be addressed. # Deceased.
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tain (prone for atherogenesis) arterial regions that affects properties and integrity of endothelium, lipid metabolism disturbances, diabetes and insulin resistance, oxidative stressprovoking factors (e.g. smoking), and infections [4]. Age and male gender are also among important risk factors [5, 6]. A number of variants of morphologic clas sification of atherosclerotic lesions including that of the American Heart Association [7, 8] have been proposed. According the later, six lesion types (IVI) are distin guished. Lesions of types I (initial lesions) and II (fatty streaks) are considered as “early lesions” present even in children. Lesions of type III are considered as intermedi ates between early and advanced lesions of types IVVI (atherosclerotic plaques: atheroma, fibroatheroma, and complicated lesions, respectively), which are found at more mature age. It is believed, although not proven experimentally, that morphologic types of lesions corre spond to stages of the disease progression. If so, one can expect the presence of succession between sequential stages not only in histological terms but also in other aspects. In the present study, correlation analysis of the contents of mRNAs for several functional groups of pro teins related to lipid turnover and its regulation in aorta fragments without lesions and with lesions of types I, II, and Va was performed with the object of revealing succes sion and evolution in organization of the system of regu lation of the expression of these genes during atherogen esis.
MATERIALS AND METHODS Artery samples. The study used aorta samples extracted during autopsies from 48 (37 male and 11 female) donors aged 17 to 57 years 46 h after accidental death. These samples included 48 fragments of aorta without lesions, 21 fragments with lesions of type I, 29 fragments with lesions of type II, and 15 fragments with lesions of type Va. When comparisons between samples with different types of lesions were performed, pairs of fragments taken from the same donors were used. Twentyone norm/lesion pairs of type I, 29 norm/lesion pairs of type II, and 15 norm/lesion pairs of type Va were analyzed. The vessels were washed with PBS and dissect ed longitudinally for biochemical and histological analy sis. For mRNA measurements, the intima from the apparently normal and the atherosclerotically damaged areas was mechanically separated, frozen in liquid nitro gen, and kept at –70°C. No lesion shoulders were taken for analysis. The ascribing of samples to certain morpho logical types of atherosclerotic damages was confirmed microscopically according to the American Heart Association classification [7, 8]. mRNA measurements. mRNA contents were meas ured using quantitative realtime polymerase chain reac tion. The details of the analysis were described earlier [9].
Briefly, RNA was isolated from frozen samples using TRIzol Reagent (Invitrogen, USA). The synthesis of cDNA was performed on total RNA using a Promega ImPromІІ Reverse Transcription System kit (Promega, USA). The synthesized cDNA was used as a template for realtime PCR on a RotorGene 3000 amplifier (Corbett Research, Australia) with a kit of reagents including the intercalating dye SYBR Green І (Syntol, Russia) as rec ommended by the manufacturer. The primers used were those described by us previously [10] as well as published primers for GNB2L1 [11]. Amplified products were sequenced using an ABI PRISM BigDye Terminator v.3.1 kit of reagents and an ABI PRISM 3100Avant automated DNA sequencer to confirm the expected sequence. The results of PCR were included only when the melting tem perature and the electrophoretic mobility of the amplified products corresponded to the expected values. The con tents of individual mRNAs were expressed as percent of glyceraldehyde3phosphate dehydrogenase (GAPDH) mRNA content used as an internal reference control. Statistics. Less than half of the data for mRNA con tents in samples corresponded to normal distribution. Therefore, correlations between values were evaluated using the Spearman rank correlation coefficient (Rs). For comparisons between mRNA contents in different sam ple types, pairs of samples taken from the same donor were used. The number of such pairs is shown in Table 1. The results were analyzed with the Statistica 8.0 program. Correlations were considered significant at p < 0.05. Correlation graph weight Gh calculated as the sum of modules of significant correlation coefficients Rs for ana lyzed mRNA pairs (Gh = Σ|Rs|) was used as the integral index for coupling between mRNA contents [12]. Cluster and factor analyses were performed on the base of Spearman correlation matrixes. For cluster analysis, options “K means” and “Sort distances and take observa tions at constant intervals” were used. To perform factor analysis, the “principal components” option was used.
RESULTS GAPDH mRNA content is often used as a house keeping gene for normalizing the results of measurements of other mRNA species. However, there is a risk of changes in expression of the gene in pathological circum stances. To validate the relevancy of GAPDH mRNA as a common reference point for aortal tissue without and with atherosclerotic lesions of different types, analysis of the expression of a second housekeeping gene, GNB2L1, in pairs of aortal fragments from several donors was per formed. The ratios of GNB2L1 mRNA contents in injures to its contents in intact aorta fragments, as nor malized by GAPDH mRNA, were close to 1.0 for lesions of type I, II, and Va (0.94 ± 0.38 (n = 6), 0.96 ± 0.24 (n = 6), and 0.88 ± 0.11 (n = 4), respectively). These data sug BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
COORDINATION IN GENE EXPRESSION DURING ATHEROGENESIS gest that the expression of the two housekeeping genes does not vary significantly during atherogenesis. Succession in mRNA expression in the course of atherogenesis. The content of individual mRNA species in samples containing atherosclerotic lesions correlated as a whole with their content in samples without lesions taken from the same donors (Table 1, lowermost line with correlation graph weight values). At that, for a number of studied mRNAs (coding for EST, ICAM1, LDLR, CEH, LXRβ, PPARα, SREBP1, SREBP2, TNFα, TLR4, and TfR), a high succession in expression along the “intact tissue – lesions of type I – lesions of type II – lesions of type Va” sequence was a characteristic feature (Table 1, right column, correlation graph weight values >3.0). These mRNAs belong to all functional groups with the exception of endosome/lysosome components. The con tent of other mRNAs (coding for STS, SELE, VCAM1, SRA, ACAT1, ApoE, SRBI, PPARγ, CCL18, CD68, EEA1, and Lamp1) in certain sample types very weakly correlated with their content in samples of other types (Table 1, right column, correlation graph weight values Gh 1.5). The division of mRNAs into groups on a basis of the extent of succession did not relate to induction, inhibition, or absence of changes in expression levels dur ing atherogenesis [13]. Thus, the group with high succes sion included EST mRNA with high induction and CEH mRNA the level, which did not change. Similarly, the group with low succession combined CCL18 mRNA with very high induction and STS mRNA the level, which declined during atherogenesis. For the total population of mRNAs, the extent of coupling between their expression levels in atherosclerotic lesion and intact intima declined progressively in accordance with morphological classifi cation of lesions along with moderate coupling between lesions III and IIVa (Table 1, lowermost line). These data suggest succession in the system of regulation of expression for the majority of the analyzed genes along the “intact tissue – lesions of type I – lesions of type II – lesions of type Va” sequence. High succession in expres sion of individual genes during progression of the disease can point to maintaining of expression control by main systemic and/or local regulators. Low succession can be associated with predominant regulators specific for each stage of the disease and, partially, with differences in cel lular composition of samples containing atherosclerotic lesions of different types. Evolution of ties between different mRNAs during atherogenesis. For the total mRNA population, progres sive rise in the extent of coupling between different mRNA species along the “intact tissue – lesions of type I – lesions of type II – lesions of type Va” sequence was a characteristic feature (Table 2). The portion of negative correlations significantly increased in lesions of type Va as compared with the tissue without lesions. The extent of coupling of individual mRNAs with other mRNA species in the course of atherogenesis could BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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change in different modes (figure). In variant (a), the mRNA (EEA1, LDLR, SELE, VCAM1, CEH) coupling did not change significantly during atherogenesis. In vari ant (b), monotonic rise in the extent of coupling for mRNA (CCL18, TfR1, ApoE, LXRβ) was observed. In variant (c), mRNAs (SRA, ACAT1, ABCG1, AR) with another dynamics of increase in coupling during athero genesis was presented. Variant (d) includes mRNAs (Lamp1, Lamp2, Rab5a, ERα) whose extent of coupling in general declined in the course of atherogenesis. Variant (e) encompasses mRNAs (PPARγ, PPARα, TLR4, p62, SREBP2) whose extent of coupling was waveshaped with “collapse” in lesions of type I. Variant (f) in total was sim ilar to the previous variant, but it did not contain a “col lapse” in lesions of type I (mRNA ABCA1, LXRα, CD63, SREBP1). In variant (g), this “collapse” was observed in lesions of type I (and II) followed by signifi cant rise in coupling in lesions of type Va (mRNA SRBI, ICAM1, TNFα). In variant (h), changes in the extent of mRNA coupling (CD68, CD36, STS, EST, Arom) had the shape of a “reverse” wave, i.e. it included a maximum in lesions of type I and minimum in lesions of type II. It should be noted that ascribing of individual mRNA to a certain group is based on formal resemblance and as such is rather arbitrary. The membership of these groups does not relate to functional grouping of encoded proteins or quantitative changes in mRNAs in the course of athero genesis. Thus, variant (e) encompasses mRNA PPARγ whose level was significantly upregulated during athero genesis and mRNA SREBP2 and TLR4 whose expression was resistant to the disease [13]. Representation and conservatism of correlations between mRNAs in aortal samples. For the total mRNA population, correlations found in the four types of aortal samples constituted in sum about half (47.6%) of all potentially possible ties between mRNAs analyzed (Table 3). Among the observed correlations, 66% were conserva tive, i.e. correlations shared for two (37%), three (20%), or all four (9%) types of aortal samples. The SRA mRNA was the absolute leader in terms of the conservatism of its ties; its correlations with other mRNA species were found in at least two types of aortal tissue. The lowest level of conservatism was a feature of p62 mRNA (only 30% of found correlations). The absolute outsider in terms of coupling was mRNA CEH (in all three ties, although all conservative). In the correlations mosaic of Table 3, some signs of the order can be seen, which is particularly evident for lines that include mRNA SRA, CD36, ACAT1, ABCA1, ABCG1, ApoE, and SRBI, i.e. factors determining lipid uptake and reverse cholesterol transfer. This suggests a dependence of expression of the studied mRNAs on some shared regulators. To reveal mRNA groups with similar regulation, cluster analysis for each of four types of aortal tissue was performed. At least two groups of key regula tors, lipids and inflammatory factors, are believed to act
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Table 1. Correlations between the contents of studied mRNAs in samples of aortal intima without lesions (“0”) and samples containing atherosclerotic lesions of morphological types I, II, and Va Group
Correlation coefficient*
mRNA 0I (n = 21)
0II (n = 29)
0Va (n = 15)
III (n = 15)
IIVa (n = 13)
Σ|Rs|
STS Arom
ns 0.91
0.42 0.53
ns 0.95
ns ns
ns ns
0.42 2.39
EST AR ERα
0.79 0.79 0.57
0.66 0.65 0.60
0.67 ns ns
0.82 0.57 0.70
0.73 0.66 0.65
3.67 2.67 2.52
Cell adhesion
Esel ICAM1 VCAM1
0.72 0.73 0.62
0.52 0.60 ns
ns 0.83 ns
ns 0.55 ns
ns 0.75 0.85
1.24 3.46 1.47
Lipid uptake/accumulation
LDLR SRA CD36 ACAT1
0.82 0.81 0.51 0.55
0.78 ns ns ns
0.67 ns ns ns
0.84 0.70 0.70 0.80
0.74 ns 0.71 ns
3.87 1.51 1.92 1.35
Cholesterol reverse transfer
ABCA1 ABCG1 CEH ApoE SRBI
0.82 0.62 0.85 0.64 0.78
0.50 0.51 0.92 ns ns
ns ns 0.86 ns ns
0.63 0.52 0.93 0.55 ns
ns ns 0.94 ns ns
1.95 1.65 4.50 1.19 0.78
Sensors/transcriptional regulators of lipid turnover
LXRα LXRβ PPARα PPARγ SREBP1 SREBP2
0.77 0.74 0.74 ns 0.52 0.79
0.72 0.75 0.50 ns 0.52 0.55
ns 0.85 0.74 −0.62 0.64 0.82
0.75 0.60 0.77 ns 0.57 0.52
ns 0.72 0.84 ns 0.83 0.72
2.24 3.76 3.59 0.62 3.08 3.40
Inflammation
TNFα CCL18 TLR4
0.81 0.55 0.73
0.62 ns 0.78
0.74 ns 0.64
ns 0.62 0.75
0.86 ns 0.90
3.03 1.17 3.8
Endosome/lysosome components
EEA1 Rab5a Lamp1 Lamp2 p62 CD63 CD68 TfR
ns ns ns 0.62 0.66 0.64 0.70 0.85
ns 0.52 ns ns 0.79 0.69 ns 0.64
ns ns ns ns ns ns ns 0.64
ns 0.56 ns 0.85 0.65 0.91 0.60 0.76
ns 0.86 ns 0.83 ns ns ns 0.75
0.0 1.94 0.0 2.30 2.10 2.24 1.30 3.64
Σ|Rs|
20.65
13.77
8.43
17.22
13.34
Sex hormones metabolism/action
All groups
* ns, absence of statistically significant correlation. Black background highlights correlations for mRNAs with high succession of expression in aor tal samples without lesion and containing atherosclerotic lesions of types I, II, and Va (Σ|Rs| > 3.0, right column); gray background highlights cor relations for mRNAs with low succession of expression in said aortal sample sequence (Σ|Rs| 1.5, right column).
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b
Gh
Gh
a
d
Gh
Gh
c
f
Gh
Gh
e
h
Gh
Gh
g
Variants of changes in extent of coupling (Gh) of individual mRNAs with other mRNA species during atherogenesis
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Table 2. Coupling between mRNAs and portion of negative correlations for total mRNA population in intact (“0”) and atherosclerotically damaged aortal tissue Lesion type
Σ|Rs| Negative correlations, %
0
I
II
Va
59.95
64.07
85.98
88.04
6.2
3.1
7.6
28.0
in vessel wall. Therefore, the number of clusters should be at least three. To choose the optimal number of clusters, two arbitrary criteria were used. The first criterion was based on the presence of shared regulatory elements LXRE in the ABCA1, ABCG1, ApoE, and LXRα genes, with existence of functional connection between respec tive proteins [3] and high conservatism of correlations between all mRNAs within this group (Table 3). Based on these suppositions, we suggested that at least three of the mRNAs should be members of a common cluster in aor tal tissue. The second criterion was based purely on the most conservative ties (in total 25) between mRNAs shown in Table 3. We believe that division into clusters should not lead to obvious divergence of members of such pairs into different clusters. Table 4 shows the results of division of total correla tions into 3, 4, and 5 clusters. One can see that the best correspondence to the applied criteria was achieved when the total correlations were divided into four clusters. Table 5 shows the distribution of individual mRNA correlations between four clusters. The clusters were enu merated according to the membership of mRNA of ABCA1 (cluster 1), SELE (cluster 2), EEA1 (cluster 3), and cluster 4 without stable representation of any mRNA. One can see that with the exception of mRNAs ABCA1/ABCG1/LXRα, SELE/VCAM1/LDLR, and EEA1/Rab5a, correlations of the majority of the mRNAs drifted from one cluster to another in the “intact tissue – lesions of types I, II, and Va” sequence. The leaders in terms of drift are mRNAs SRA, CD68, and TfR1, which drifted always together however, obviously due to high conservatism in coupling between these mRNAs (Table 3). The drift of a given mRNA from one cluster to another seems to be associated with quantitative and/or qualitative changes in ensembles of regulators of gene expression. Factor analysis was used for formal descrip tion of these changes. Table 6 shows that along the disease progression, the number of factors that determine correlations between mRNAs declines. This regularity becomes even more pronounced when individual factor loadings into correla tions of individual mRNAs are considered (Table 7). One can see that along the “intact tissue – lesions of type I –
lesions of type II – lesions of type Va” sequence the load ing of factor 3 and then that of factor 2 decreases. As a result, in fibroatheroma (lesion of type Va) the majority of correlations are determined by single factor.
DISCUSSION The changes in expression (at the levels of activity and content of protein and/or mRNA) of many factors engaged in formation of local inflammation, lipid turnover, cell adhesion, and metabolism/action of sex hormones during atherogenesis has been determined in many studies [1419]. Such investigations concern main ly advanced atherosclerotic lesions or were performed with macrophages exposed to modified (oxidized, acety lated, aggregated, etc.) low density lipoproteins, which represent surrogate model of atherogenesis. The dynam ics of such changes on the transition from one morpho logical type of lesion to the following type and particular ly at the early stages of the disease has not been fully examined. Such changes for the analyzed group of mRNAs were presented by the authors in a separate pub lication [13]. Moreover, revealing of the quantitative changes in expression of certain genes is only one side of cognition of atherogenesis pathophysiology. Protein products of different genes often act in a cell together, as functional and/or structural ensembles. The EEA1 Rab5a pair can serve as an example of such ensembles, where the components of the pair interact each other physically during formation and functioning of early endosomes [20]. Therefore, it is very important to know how expression in gene ensembles is coordinated. In a number of cases, this coordination is achieved due to presence in regulatory sequences of certain gene groups of similar elements that provide similar effects of modulato ry factors. Specifically, lipids from low density lipopro teins can serve as such factors directly or indirectly affect ing activities of transcriptional factors of LXR (sterol sen sors), PPAR (fatty acid sensors), and SREBP (mediators of cholesterol sensors SCAP and INSIG) groups [3]. By now, structural–functional organization of regulatory regions, even partially, has been revealed for only a small number of genes. And even less is known about tissue BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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* Shortened abbreviations are used.
Inflam mation
Adhe sion
Table 3. Superposition of significant correlation ties between the content of studied mRNAs in aortal intima without lesions and in lesions of types I, II, and Va. Black and gray backgrounds highlight positive and negative correlations, respectively. Symbols •, ••, and ••• mark off correlations shared for two, three, and four tissue types, respectively. Symbol # marks off correlations with sign reversal in one of tissue types COORDINATION IN GENE EXPRESSION DURING ATHEROGENESIS 939
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Table 4. Selection of optimal number of clusters of correlation ties between studied mRNAs in four aortal tissue types Lesion type 0
I
II
Va
0
I
II
Va
0
I
II
Va
3/4
3/4
Given cluster number 4
3
5
Presence of ABCA1, ABCG1, ApoE, and LXRα mRNAs in shared cluster (criterion 1) 4/4
2/4
4/4
4/4
3/4
4/4
4/4
4/4
4/4
15/16
14/16
Total
4/4
14/16
Number of highly conservative correlations which members present in shared clusters (criterion 2) Σ Total
14
17
25
24
16
80/100
specific functioning of regulatory elements in the context of different physiological and pathophysiological circum stances. Correlation analysis of gene expression allows to a certain extent to clarify the situation with evolution of the system of interactions between genes in the course of progression of diseases such as atherosclerosis. This approach is particularly suitable for human studies, when current powerful tools of analysis such as knockdown or reporter construct introduction cannot be applied. Here, we operated mainly with statistically signifi cant (p < 0.05) correlations without Bonferroni correc tion for probability of catching random correlations in repeated rounds of the analysis. The introduction of such correction for correlations between 34 mRNA species would lead to application of p value of p = 0.05/(33 × 33) ~ 0.00005. No one correlation with threshold of p = 0.05 corresponds to this hard criterion in intact tissue and lesions of types I, II, and Va. Formally correct, this approach deprives correlation analysis of any sense. On the other hand, the superposition of correlations in aortal samples without lesions and with atherosclerotic lesions shown in Table 3 demonstrates that 66% of the found cor relations are conservative. The coincidence of random correlations in two or more tissue types seems to be extremely unlikely (the probability of such coincidence is equal to the product of p values, i.e. no more than 0.05 × 0.05 = 0.0025, a significant part of correlations being characterized by p values of p < 0.01). The remaining 34% of significant (at p < 0.05) correlations are found only in one tissue type, and among them, indeed, random corre lations may be present. In interpretation of these noncon servative correlations, we issued from the assumption that random correlations are distributed within the correlation matrix in random fashion and this distribution pattern only “fogs” the picture as well, to some extent without crucial change. An analysis of succession in mRNA
21
25 78/100
16
14
17
14
13
58/100
expression calculated as in Table 1 but using both signifi cant and nonsignificant correlations can serve as an illustration of the appropriateness of the used approach. In this case, hierarchy of correlation graph weights was preserved while differences of these values appeared very small, which hampered separation of groups with high and low succession in expression during atherogenesis. According to the theory of correlation adaptometry, biological systems of different levels of organization respond to unfavorable conditions by rise in coupling between analyzed parameters [12, 21]. The data obtained here generally correspond to this theory, demonstrating rise in coupling between 34 mRNA species in the course of the disease progression along the sequence: aortal tis sue without lesions < atherosclerotic lesions of type I < atherosclerotic lesions of type II atherosclerotic lesions of type Va (Table 2). This general tendency is particularly apparent for CCL18, TfR1, ApoE, and LXRβ mRNA (figure, panel (b)). For a number of mRNAs (PPARα, PPARγ, TLR4, p62, SREBP2, SRBI, ICAM1, TNFα) that belong to different functional groups including groups of lipid sensors and inflammatory factors, a “col lapse” in coupling in lesions of type I is a feature (figure, panels (e) and (g)). From the viewpoint of the theory of correlation adaptometry, the data can point to some mechanisms active in the initial stage of atherogenesis that prevent further disease progression. When this “col lapse” is interpreted, the fact that mRNA content was measured in mixed cellular population should be taken into account. Foam cells formed from macrophages, according to histological analysis, constitutes only a small portion of the total cellular population of the intima. Even in lipofibrous plaques of aorta, hematogenous cells including monocytes/macrophages compose no more than 15% of the total cell population [22]. Therefore, one can suggest that the measured mRNA levels and their BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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Table 5. Distribution of correlations of individual mRNAs between four clusters Lesion type Group
mRNA 0
I
II
Va
Cluster No. Sex hormones metabolism/action
Cell adhesion
Lipid uptake/ accumulation
Cholesterol reverse transfer
Sensors/transcrip tional regulators of lipid turnover
Inflammation
Endosome/ lysosome components
STS
4
3
4
3
Arom
2
2
4
2
EST
4
3
4
4
AR
4
2
3
3
ERα
4
2
3
3
SELE
2
2
2
2
ICAM1
2
2
2
4
VCAM1
2
2
2
2
LDLR
2
2
2
2
SRA
2
3
1
4
CD36
2
3
1
1
ACAT1
3
3
1
4
ABCA1
1
1
1
1
ABCG1
1
1
1
1
CEH
2
4
4
2
ApoE
2
1
1
1
SRBI
4
1
1
4
LXRα
1
1
1
1
LXRβ
1
1
3
3
PPARα
1
4
3
3
PPARγ
3
3
1
1
SREBP1
1
1
1
2
SREBP2
4
4
3
2
TNFα
2
3
2
4
CCL18
2
3
1
1
TLR4
1
4
3
3
CD68
2
3
1
4
EEA1
3
3
3
3
Rab5a
3
3
3
3
Lamp1
3
3
1
3
Lamp2
3
3
1
4
p62
3
4
3
2
CD63
1
4
3
3
TfR1
2
3
1
4
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Table 6. Cumulative contribution of factors 16 loading in correlations between mRNAs in intact aorta and lesions of types I, II, and Va. The number of mRNA species (from 34) whose correlations are determined more than by 70% by cumulative contribution of factors is shown Factors Lesion type 1
1+2
1+2+3
1+2+3+4
1+2+3+4+5
1+2+3+4+5+6
0
2
9
21
28
32
33
I
7
17
27
32
33
34
II
11
21
29
33
34
Va
17
23
27
32
34
correlations reflect gene expression mainly in quantita tively dominant resident intimal cells. We speculate that lipid uptake by scattered macrophages in lesions of type I decrease the pressure of these lipids onto surrounding res ident cells. As a result, the extent of coordination in expression of genes encoding the abovementioned pro teins declines. Lesions of type I are found even in infants. It is implied though not proved that such lesions can dis appear spontaneously. Thus, the evacuation of proathero genic lipids from the subendothelial space by not numer ous macrophages can serve as one of the mechanisms keeping aorta in working condition, and formation of foam cells at the initial stage of atherogenesis can be more likely a physiological adaptation than a transition to pathology. Negative correlations represent another interesting aspect of the analysis. Such correlations can arise as a result of opposite effects of the same regulator on expres sion of two genes. Mechanisms of opposite effects are diverse and include the use of positive and negative regu latory elements by a regulator, modulation of form of activity of a regulatory protein (e.g. functioning as tran scriptional regulator or coregulator), or context dependent recruitment of coactivators and corepressors of an alternative regulatory element by transcriptional factors [23]. Under other equal circumstances, negative correlations generally point to a stratification of the pop ulation in respect of parameter pairs under study. In this connection, significantly higher level of negative correla tions in lesions of type Va as compared with norm and lesions of types I and II (Table 2) attracts attention. Lesions of type Va are considered as possible precursors of complicated lesions of type VI, calcified plaques of type Vb, and depleted of lipid core plaques of type Vc. It is not excluded that negative correlations in lesions of type Va reflect the direction of the future fibroatheroma develop ment. The ties of mRNAs for sex hormone metabolism and reception (excluding mRNA of estrogen receptor) are particularly enriched by negative correlations, which may point to involvement of sex hormones in control of
further atheroma development. Gender differences in cardiovascular risks that are dependent on sex hormones are well known [24]. The data on progressive decline during atherogenesis in number of mRNA species whose content in athero sclerotic lesions correlates with their content in normal tissue (Table 1) was generally expected. The existence of mRNAs whose levels never or almost never correlate with their contents in norm or other lesion types or, on the contrary, always or almost always correlate with their con tents in norm or other lesion types was unexpected. One can assume that in regulation of gene expression of the first type, local regulatory factors specific for given stage dominate at different stages of atherogenesis, while in the case of genes of the second type key regulators retain their importance in the course of the disease and can have either systemic or local origin. Interestingly, members of the same functional groups of mRNAs, such as PPARγ and PPARα, ACAT1, and LDLR, can be found at oppo site poles of succession. Cluster analysis of correlations between mRNA con tents showed that the studied mRNAs can be combined into several groups or clusters (in our opinion, four clus ters; Table 4) in which the coupling between individual mRNAs exceeds the coupling between mRNAs from dif ferent clusters. For the majority of mRNA species, a “drift” from one cluster to the other in the “intact tissue – lesions of type I – lesions of type II – lesions of type Va” sequence is a character feature (Table 5). This drift presumably reflects changes in predominant gene expression regulators during atherogenesis. These changes in regulators are confirmed by factor analysis (Tables 6 and 7). According to results of this analysis, in intact aorta the studied genes are subjected to a wide spectrum of regulators. In the course of atherosclerosis progression this spectrum narrows so that in lesions of type Va, the regulation becomes mainly singlefactor. This evolution in regulation is visually illustrated by exit of mRNAs ABCA1, ABCG1, and SRBI under predom inant pressure of factor 3 in intact tissue with transition BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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Table 7. Contributions of factors 13 in individual mRNAs correlations. Marked by black background contributions are >0.7 Lesion type mRNA 0
Va
II
I Contribution of factors
STS Arom
1
2
3
1
2
3
1
–0.31
–0.73
–0.34
–0.86
0.30
0.33
0.22
–0.55
–0.32
–0.84
0.26
1
2
–0.56
0.86
0.33
–0.16
–0.22
0.26
–0.11
0.61
0.26
2
3
0.26
–0.49
–0.15
0.54
3
–0.09
–0.82
–0.21
–0.83
0.07
–0.06
0.08
–0.43
–0.73
–0.75
0.37
0.29
AR
–0.80
–0.23
0.11
–0.52
0.22
0.61
0.60
0.71
0.09
0.96
0.04
–0.06
ERα
–0.76
–0.30
0.01
–0.37
0.33
0.50
0.22
0.84
–0.10
0.63
–0.29
0.33
0.69
–0.08 –0.04
EST
SELE
0.82
–0.25
0.13
–0.14
0.21
–0.90
0.08
–0.71
0.60
–0.51
ICAM1
0.44
–0.54
0.32
–0.56
0.35
–0.49
–0.31
–0.72
0.41
–0.96
0.19
VCAM1
0.07
–0.42
–0.45
–0.64
0.46
0.08
–0.42
–0.30
0.69
–0.60
0.30
0.33
LDLR
0.07
–0.19
–0.47
–0.30
0.58
–0.61
0.34
–0.69
0.40
–0.75
0.02
–0.05
SRA
0.16
–0.69
0.61
–0.82
–0.51
0.09
–0.98
0.12
0.00
–0.95
0.02
–0.16
CD36
0.51
–0.56
0.30
–0.87
–0.32
0.10
–0.85
0.11
–0.14
–0.88
–0.26
–0.14
ACAT1
–0.52
–0.34
0.17
0.29
–0.16
–0.28
–0.81
0.15
–0.18
–0.98
–0.02
0.03
ABCA1
–0.20
0.34
0.82
0.17
–0.92
0.01
–0.91
0.20
0.24
–0.83
0.06
–0.46
–0.05
–0.22
–0.34
–0.67
–0.25
0.32
0.85
0.53
–0.77
–0.22
–0.95
0.13
0.04
–0.92
CEH
0.30
0.15
–0.48
0.67
–0.18
0.26
0.19
–0.13
0.03
–0.30
ApoE
ABCG1
–0.70
–0.56
0.15
–0.84
–0.32
–0.09
–0.96
0.17
0.09
–0.96
0.20
0.06
SRBI
0.35
0.35
0.74
0.03
–0.95
–0.13
–0.92
0.30
–0.04
–0.97
–0.09
–0.15
LXRα
–0.70
0.29
0.48
0.37
–0.50
0.60
–0.56
0.70
0.18
–0.76
–0.41
–0.25
LXRβ
–0.34
0.38
0.08
0.32
–0.46
–0.39
0.43
0.80
0.32
0.89
0.29
–0.20
PPARα
–0.85
0.32
0.25
0.74
–0.35
0.22
0.28
0.94
0.05
0.90
–0.21
–0.28
PPARγ
–0.84
–0.24
0.35
–0.50
–0.46
0.64
–0.92
0.37
–0.00
–0.83
–0.52
–0.11
0.60
–0.36
–0.53
0.05
SREBP1
0.05
0.51
0.34
–0.04
–0.73
–0.54
–0.84
0.34
0.32
–0.33
SREBP2
–0.66
–0.24
–0.44
0.56
0.55
–0.04
0.48
0.67
–0.19
0.20
0.55
–0.75
0.22
–0.58
–0.38
–0.60
–0.12
–0.78
–0.41
–0.95
0.01
0.01
0.37
–0.59
–0.75
–0.13
–0.93
–0.33
0.02
–0.96
–0.18
0.06
0.83
–0.23
0.87
–0.27
0.78
–0.33
–0.34
TNFα
0.82
–0.05
TLR4
–0.96
0.16
0.02
0.21
0.10
CD68
CCL18
0.15
–0.44
0.80
–0.83
–0.43
0.18
–0.93
0.13
–0.08
–0.97
0.12
–0.00
EEA1
–0.73
–0.53
0.08
–0.97
0.06
0.13
0.25
0.91
–0.07
0.89
0.42
–0.04
Rab5a
–0.79
–0.54
–0.06
–0.91
–0.00
0.27
0.29
0.85
0.13
0.92
0.29
0.05
0.42
–0.65
0.49
–0.24
Lamp1
–0.72
–0.35
–0.05
–0.83
–0.02
0.11
–0.48
0.58
0.22
0.60
Lamp2
–0.20
–0.80
0.41
–0.96
–0.05
0.14
–0.80
0.07
–0.15
–0.79
p62
–0.73
–0.17
0.09
0.54
0.64
–0.16
0.69
0.56
0.22
0.25
0.65
–0.52
–0.62
0.72
–0.02
0.73
–0.57
0.30
–0.06
0.87
–0.20
0.34
–0.77
–0.38
0.58
–0.53
0.38
–0.71
–0.44
–0.37
–0.86
–0.30
–0.30
–0.96
–0.01
–0.01
10.97
7.48
5.41
13.88
7.40
5.17
13.44
10.79
3.04
21.02
4.61
2.53
CD63 TfR1 Eigenvalue
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under the influence of factor 2 in lesions of type I and fol lowing transition under predominant influence of factor 1 in lesions of types II and Va. We do not take the risk of hypothesizing on the nature of these regulatory factors. Possibly, regulators that act separately in intact tissue, along the disease develop ment begin act in one direction, composing thus a shared factor. Such a situation might arise, for example, follow ing functional integration of lipid and cytokine signaling. Indeed, as shown in Table 5, in lesions of types II and Va, mRNAs for oxysterol sensor LXRα, fatty acid sensor PPARγ, chemokine CCL18, and fatty acid transporter CD36 (which acts also as a signaling receptor for oxidized lipoproteins [25]) belong to a shared cluster. In intact tis sue and in lesions of type I these mRNAs belong to dif ferent clusters. Although the expression of only a small gene group that constitutes about 0.1% of all human genes was ana lyzed in the present study, this analysis allowed us to reveal several regularities that have not been described previously. The data obtained using matrixes allowing simultaneous analysis of expression of more than 20,000 genes usually need confirmation by quantitative PCR, which has been applied for only a few mRNA species of interest [15, 2629]. Thus, in the end, the representative ness of our results yields to no results of others. To the best of our knowledge, there are no publications where sequential stages of the disease were studied in parallel. An analysis of several disease stages in the same individ ual is among advantages of the present study. As a rule, changes in gene expression during atherogenesis are char acterized by the extent of induction or reduction in mRNA content by means of comparisons between advanced atherosclerotic lesion (fibroatheroma) and intact vessel tissue. For the same aim, cells of a certain type (endothelial cells, macrophages) isolated from dif ferent segments of the bloodstream or different tissues are used. Information thus obtained, of course being very important, still does not answer the question about rea sons for largescale reorganization in genome functioning in the course of the disease development. Here, we attempted to solve this question using the correlation analysis approach, which, to our best knowledge, had not been used for this aim previously. From the results obtained, the conclusion that sequential narrowing of the spectrum of gene expression regulators towards single factor dependence in lesions of type Va seems to be the most important. It should be noted, however, that the selection of mRNAs for this study was not random, so conclusion on drift towards singlefactor regulation dur ing the disease progression needs confirmation with an additional mRNA population. In the case of such confir mation, one can expect the generation of efficient thera peutics for remission of advanced forms of atherosclero sis.
This work was financially supported by the Russian Foundation for Basic Research (project 090400329a). The part of experiments was performed using facili ties of the Center of Collective Use “Genome” at the Engelhardt Institute of Molecular Biology.
REFERENCES 1. The Global Burden of Disease: 2004 Update, World Health Organization, Geneva, Switzerland, 2008. 2. Hansson, G. K., and Hermansson, A. (2011) Nat. Immunol., 12, 204212. 3. Smirnov, A. N. (2010) Biochemistry (Moscow), 75, 793 810. 4. Gebbers, J.O. (2007) Ger. Med. Sci., 5, Doc04. 5. Villablanca, A. C., Jayachandran, M., and Banka, C. (2010) Clin. Sci. (Lond.), 119, 493513. 6. PerezLopez, F. R., LarradMur, L., Kallen, A., Chedraui, P., and Taylor, H. S. (2010) Reprod. Sci., 17, 511531. 7. Stary, H. C., Chandler, A. B., Glagov, S., Guyton, J. R., Insull, W., Jr., Rosenfeld, M. E., Schaffer, S. A., Schwartz, C. J., Wagner, W. D., and Wissler, R. W. (1994) Arterioscler. Thromb., 14, 840856. 8. Stary, H. C., Chandler, A. B., Dinsmore, R. E., Fuster, V., Glagov, S., Insull, W., Jr., Rosenfeld, M. E., Schwartz, C. J., Wagner, W. D., and Wissler, R. W. (1995) Arterioscler. Thromb. Vasc. Biol., 15, 15121531. 9. Shchelkunova, T. A., Morozov, I. A., Rubtsov, P. M., Samokhodskaya, L. M., Kireev, R. A., Andrianova, I. V., Orekhov, A. N., and Smirnov, A. N. (2008) Biochemistry (Moscow), 73, 920928. 10. Shchelkunova, T. A., Albert, E. A., Morozov, I. A., Rubtsov, P. M., Samokhodskaya, L. M., Sobenin, I. A., Orekhov, A. N., and Smirnov, A. N. (2011) Biochemistry (Moscow), 76, 11781184. 11. Ishii, T., Wallace, A. M., Zhang, X., Gosselink, J., Abboud, R. T., English, J. C., Pare, P. D., and Sandford, A. J. (2006) Eur. Respir. J., 27, 300306. 12. Razzhevaikin, V. N. (2010) Zh. Obshch. Biol., 71, 7584. 13. Shchelkunova, T. A., Morozov, I. A., Rubtsov, P. M., Samokhodskaya, L. M., Andrianova, I. V., Sobenin, I. A., Orekhov, A. N., and Smirnov, A. N. (2013) Biochemistry (Moscow), 78, 463470. 14. Laguna, J. C., and Alegret, M. (2012) Pharmacogenomics, 13, 477495. 15. Hagg, D. A., Olson, F. J., Kjelldahl, J., Jernas, M., Thelle, D. S., Carlsson, L. M., Fagerberg, B., and Svensson, P. A. (2009) Atherosclerosis, 204, e1520. 16. Liu, P. Y., Christian, R. C., Ruan, M., Miller, V. M., and Fitzpatrick, L. A. (2005) J. Clin. Endocrinol. Metab., 90, 10411046. 17. Nakamura, Y., Miki, Y., Suzuki, T., Nakata, T., Darnel, A. D., Moriya, T., Tazawa, C., Saito, H., Ishibashi, T., Takahashi, S., Yamada, S., and Sasano, H. (2003) Am. J. Pathol., 163, 13291339. 18. Edfeldt, K., Swedenborg, J., Hansson, G. K., and Yan, Z. Q. (2002) Circulation, 105, 11581161. 19. Albrecht, C., Soumian, S., Amey, J. S., Sardini, A., Higgins, C. F., Davies, A. H., and Gibbs, R. G. (2004) Stroke, 35, 28012806. BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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Coordination in Gene Expression during Atherogenesis T. A. Shchelkunova1*, I. A. Morozov2, P. M. Rubtsov2,3, L. M. Samokhodskaya4, I. A. Sobenin5, A. N. Orekhov5, and A. N. Smirnov1# 1 Biological Faculty, Lomonosov Moscow State University, Leninsky Gory 1/12, 119899 Moscow, Russia; fax: (495) 9394309; Email: schelkunova[email protected] 2 Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, ul. Vavilova 32, 119991 Moscow, Russia; fax: (499) 1351405; Email: [email protected] 3 Moscow Institute of Physics and Technology, Institutskii Pereulok 9, 141700 Dolgoprudny, Moscow Region, Russia; fax: (495) 5760813 4 Faculty of Fundamental Medicine, Lomonosov Moscow State University, Lomonosovsky pr. 31/5, 119899 Moscow, Russia; fax: (495) 9329904; Email: [email protected] 5 Institute of General Pathology and Pathophysiology, Russian Academy of Medical Sciences, ul. Baltiiskaya 8, 125315 Moscow, Russia; fax: (495) 4159594; Email: [email protected]
Received March 13, 2013 Abstract—General tendencies in the regulation of gene expression during atherogenesis were investigated using correlation analysis for 34 mRNA species of several functional groups. The contents of mRNA were measured by quantitative PCR in samples of human aortal intima containing no lesions or atherosclerotic lesions of types I (initial lesions), II (fatty streaks), and Va (fibroatheromas). The coupling between mRNA contents in lesions and the same mRNAs in intact tissue was found to descend in the course of the disease progression. The data are in accordance with the opinion that successive morpho logic types of atherosclerotic lesions correspond to steps of atherogenesis. In addition, the contents of individual mRNA species could correlate with each other within the given sample type, the extent of this coupling rising along with the dis ease progression. The exception from this rule was a collapse in coupling for several functional groups of mRNA in lesions of type I. This collapse could indicate special position of these lesions in pathogenesis. Statistically significant correlations between mRNAs found in samples of all four types comprised in total about 50% of all possible correlations. 66% of these correlations were conservative, i.e. observed in at least two sample types. By couplingstrength, the studied mRNAs could be divided into four clusters whose composition significantly varied along with the disease progression. The disease pro gression was also associated with decline in number of regulatory factors that determine coordination in expression of the analyzed genes. DOI: 10.1134/S0006297913080117 Key words: mRNA, PCR, gene expression, atherogenesis, aorta, correlation analysis
Atherosclerosis manifested as a wall thickening and luminal narrowing of large arterial vessels is one of the most frequent disorders and a cause of about 30% of deaths worldwide [1]. The development of local inflam
mation and lipid deposition (intra and extracellular) are two hallmarks of atherosclerosis, the two stimulating each other [2, 3]. Atherogenesis can be stimulated by a variety of factors including turbulence in the bloodstream in cer
Abbreviations: ABCA1 and ABCG1, ATPbinding cassette transporters A1 and G1; ACAT1, acylCoAcholesterol acyltransferase 1; ApoE, apolipoprotein E; AR, androgen receptor; Arom, aromatase; CCL18, CC motifcontaining chemokine 18; CD36, CD63, and CD68, differentiation clusters 36, 63, and 68; CEH, cholesteryl ester neutral hydrolase; EEA1, early endosome antigen 1; ERα, estrogen receptor alpha; EST, estrogen sulfotransferase; GAPDH, glyceraldehyde3phosphate dehydrogenase; GNB2L1, guanine nucleotidebinding protein, betapeptide 2like 1; ICAM1, intercellular adhesion molecule 1; Lamp 1/2, lysosomeasso ciated membrane glycoproteins 1 and 2; LDLR, low density lipoprotein receptor; LXRα and LXRβ, liver X receptors alpha and beta; p62, ubiquitinbinding protein p62; PPARα and PPARγ, peroxisome proliferatoractivated receptors alpha and gamma; Rab5a, Rasrelated small GTPase 5A; SELE, selectin E; SRA, scavenger receptor A; SRBI, scavenger receptor BI; SREBP1 and SREBP2, sterol regulatory elementbinding proteins 1 and 2; STS, steroid sulfatase; TfR1, transferrin receptor 1; TLR4, Tolllike receptor 4; TNFα, tumor necrosis factor alpha; VCAM1, vascular cell adhesion molecule 1. * To whom correspondence should be addressed. # Deceased.
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tain (prone for atherogenesis) arterial regions that affects properties and integrity of endothelium, lipid metabolism disturbances, diabetes and insulin resistance, oxidative stressprovoking factors (e.g. smoking), and infections [4]. Age and male gender are also among important risk factors [5, 6]. A number of variants of morphologic clas sification of atherosclerotic lesions including that of the American Heart Association [7, 8] have been proposed. According the later, six lesion types (IVI) are distin guished. Lesions of types I (initial lesions) and II (fatty streaks) are considered as “early lesions” present even in children. Lesions of type III are considered as intermedi ates between early and advanced lesions of types IVVI (atherosclerotic plaques: atheroma, fibroatheroma, and complicated lesions, respectively), which are found at more mature age. It is believed, although not proven experimentally, that morphologic types of lesions corre spond to stages of the disease progression. If so, one can expect the presence of succession between sequential stages not only in histological terms but also in other aspects. In the present study, correlation analysis of the contents of mRNAs for several functional groups of pro teins related to lipid turnover and its regulation in aorta fragments without lesions and with lesions of types I, II, and Va was performed with the object of revealing succes sion and evolution in organization of the system of regu lation of the expression of these genes during atherogen esis.
MATERIALS AND METHODS Artery samples. The study used aorta samples extracted during autopsies from 48 (37 male and 11 female) donors aged 17 to 57 years 46 h after accidental death. These samples included 48 fragments of aorta without lesions, 21 fragments with lesions of type I, 29 fragments with lesions of type II, and 15 fragments with lesions of type Va. When comparisons between samples with different types of lesions were performed, pairs of fragments taken from the same donors were used. Twentyone norm/lesion pairs of type I, 29 norm/lesion pairs of type II, and 15 norm/lesion pairs of type Va were analyzed. The vessels were washed with PBS and dissect ed longitudinally for biochemical and histological analy sis. For mRNA measurements, the intima from the apparently normal and the atherosclerotically damaged areas was mechanically separated, frozen in liquid nitro gen, and kept at –70°C. No lesion shoulders were taken for analysis. The ascribing of samples to certain morpho logical types of atherosclerotic damages was confirmed microscopically according to the American Heart Association classification [7, 8]. mRNA measurements. mRNA contents were meas ured using quantitative realtime polymerase chain reac tion. The details of the analysis were described earlier [9].
Briefly, RNA was isolated from frozen samples using TRIzol Reagent (Invitrogen, USA). The synthesis of cDNA was performed on total RNA using a Promega ImPromІІ Reverse Transcription System kit (Promega, USA). The synthesized cDNA was used as a template for realtime PCR on a RotorGene 3000 amplifier (Corbett Research, Australia) with a kit of reagents including the intercalating dye SYBR Green І (Syntol, Russia) as rec ommended by the manufacturer. The primers used were those described by us previously [10] as well as published primers for GNB2L1 [11]. Amplified products were sequenced using an ABI PRISM BigDye Terminator v.3.1 kit of reagents and an ABI PRISM 3100Avant automated DNA sequencer to confirm the expected sequence. The results of PCR were included only when the melting tem perature and the electrophoretic mobility of the amplified products corresponded to the expected values. The con tents of individual mRNAs were expressed as percent of glyceraldehyde3phosphate dehydrogenase (GAPDH) mRNA content used as an internal reference control. Statistics. Less than half of the data for mRNA con tents in samples corresponded to normal distribution. Therefore, correlations between values were evaluated using the Spearman rank correlation coefficient (Rs). For comparisons between mRNA contents in different sam ple types, pairs of samples taken from the same donor were used. The number of such pairs is shown in Table 1. The results were analyzed with the Statistica 8.0 program. Correlations were considered significant at p < 0.05. Correlation graph weight Gh calculated as the sum of modules of significant correlation coefficients Rs for ana lyzed mRNA pairs (Gh = Σ|Rs|) was used as the integral index for coupling between mRNA contents [12]. Cluster and factor analyses were performed on the base of Spearman correlation matrixes. For cluster analysis, options “K means” and “Sort distances and take observa tions at constant intervals” were used. To perform factor analysis, the “principal components” option was used.
RESULTS GAPDH mRNA content is often used as a house keeping gene for normalizing the results of measurements of other mRNA species. However, there is a risk of changes in expression of the gene in pathological circum stances. To validate the relevancy of GAPDH mRNA as a common reference point for aortal tissue without and with atherosclerotic lesions of different types, analysis of the expression of a second housekeeping gene, GNB2L1, in pairs of aortal fragments from several donors was per formed. The ratios of GNB2L1 mRNA contents in injures to its contents in intact aorta fragments, as nor malized by GAPDH mRNA, were close to 1.0 for lesions of type I, II, and Va (0.94 ± 0.38 (n = 6), 0.96 ± 0.24 (n = 6), and 0.88 ± 0.11 (n = 4), respectively). These data sug BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
COORDINATION IN GENE EXPRESSION DURING ATHEROGENESIS gest that the expression of the two housekeeping genes does not vary significantly during atherogenesis. Succession in mRNA expression in the course of atherogenesis. The content of individual mRNA species in samples containing atherosclerotic lesions correlated as a whole with their content in samples without lesions taken from the same donors (Table 1, lowermost line with correlation graph weight values). At that, for a number of studied mRNAs (coding for EST, ICAM1, LDLR, CEH, LXRβ, PPARα, SREBP1, SREBP2, TNFα, TLR4, and TfR), a high succession in expression along the “intact tissue – lesions of type I – lesions of type II – lesions of type Va” sequence was a characteristic feature (Table 1, right column, correlation graph weight values >3.0). These mRNAs belong to all functional groups with the exception of endosome/lysosome components. The con tent of other mRNAs (coding for STS, SELE, VCAM1, SRA, ACAT1, ApoE, SRBI, PPARγ, CCL18, CD68, EEA1, and Lamp1) in certain sample types very weakly correlated with their content in samples of other types (Table 1, right column, correlation graph weight values Gh 1.5). The division of mRNAs into groups on a basis of the extent of succession did not relate to induction, inhibition, or absence of changes in expression levels dur ing atherogenesis [13]. Thus, the group with high succes sion included EST mRNA with high induction and CEH mRNA the level, which did not change. Similarly, the group with low succession combined CCL18 mRNA with very high induction and STS mRNA the level, which declined during atherogenesis. For the total population of mRNAs, the extent of coupling between their expression levels in atherosclerotic lesion and intact intima declined progressively in accordance with morphological classifi cation of lesions along with moderate coupling between lesions III and IIVa (Table 1, lowermost line). These data suggest succession in the system of regulation of expression for the majority of the analyzed genes along the “intact tissue – lesions of type I – lesions of type II – lesions of type Va” sequence. High succession in expres sion of individual genes during progression of the disease can point to maintaining of expression control by main systemic and/or local regulators. Low succession can be associated with predominant regulators specific for each stage of the disease and, partially, with differences in cel lular composition of samples containing atherosclerotic lesions of different types. Evolution of ties between different mRNAs during atherogenesis. For the total mRNA population, progres sive rise in the extent of coupling between different mRNA species along the “intact tissue – lesions of type I – lesions of type II – lesions of type Va” sequence was a characteristic feature (Table 2). The portion of negative correlations significantly increased in lesions of type Va as compared with the tissue without lesions. The extent of coupling of individual mRNAs with other mRNA species in the course of atherogenesis could BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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change in different modes (figure). In variant (a), the mRNA (EEA1, LDLR, SELE, VCAM1, CEH) coupling did not change significantly during atherogenesis. In vari ant (b), monotonic rise in the extent of coupling for mRNA (CCL18, TfR1, ApoE, LXRβ) was observed. In variant (c), mRNAs (SRA, ACAT1, ABCG1, AR) with another dynamics of increase in coupling during athero genesis was presented. Variant (d) includes mRNAs (Lamp1, Lamp2, Rab5a, ERα) whose extent of coupling in general declined in the course of atherogenesis. Variant (e) encompasses mRNAs (PPARγ, PPARα, TLR4, p62, SREBP2) whose extent of coupling was waveshaped with “collapse” in lesions of type I. Variant (f) in total was sim ilar to the previous variant, but it did not contain a “col lapse” in lesions of type I (mRNA ABCA1, LXRα, CD63, SREBP1). In variant (g), this “collapse” was observed in lesions of type I (and II) followed by signifi cant rise in coupling in lesions of type Va (mRNA SRBI, ICAM1, TNFα). In variant (h), changes in the extent of mRNA coupling (CD68, CD36, STS, EST, Arom) had the shape of a “reverse” wave, i.e. it included a maximum in lesions of type I and minimum in lesions of type II. It should be noted that ascribing of individual mRNA to a certain group is based on formal resemblance and as such is rather arbitrary. The membership of these groups does not relate to functional grouping of encoded proteins or quantitative changes in mRNAs in the course of athero genesis. Thus, variant (e) encompasses mRNA PPARγ whose level was significantly upregulated during athero genesis and mRNA SREBP2 and TLR4 whose expression was resistant to the disease [13]. Representation and conservatism of correlations between mRNAs in aortal samples. For the total mRNA population, correlations found in the four types of aortal samples constituted in sum about half (47.6%) of all potentially possible ties between mRNAs analyzed (Table 3). Among the observed correlations, 66% were conserva tive, i.e. correlations shared for two (37%), three (20%), or all four (9%) types of aortal samples. The SRA mRNA was the absolute leader in terms of the conservatism of its ties; its correlations with other mRNA species were found in at least two types of aortal tissue. The lowest level of conservatism was a feature of p62 mRNA (only 30% of found correlations). The absolute outsider in terms of coupling was mRNA CEH (in all three ties, although all conservative). In the correlations mosaic of Table 3, some signs of the order can be seen, which is particularly evident for lines that include mRNA SRA, CD36, ACAT1, ABCA1, ABCG1, ApoE, and SRBI, i.e. factors determining lipid uptake and reverse cholesterol transfer. This suggests a dependence of expression of the studied mRNAs on some shared regulators. To reveal mRNA groups with similar regulation, cluster analysis for each of four types of aortal tissue was performed. At least two groups of key regula tors, lipids and inflammatory factors, are believed to act
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Table 1. Correlations between the contents of studied mRNAs in samples of aortal intima without lesions (“0”) and samples containing atherosclerotic lesions of morphological types I, II, and Va Group
Correlation coefficient*
mRNA 0I (n = 21)
0II (n = 29)
0Va (n = 15)
III (n = 15)
IIVa (n = 13)
Σ|Rs|
STS Arom
ns 0.91
0.42 0.53
ns 0.95
ns ns
ns ns
0.42 2.39
EST AR ERα
0.79 0.79 0.57
0.66 0.65 0.60
0.67 ns ns
0.82 0.57 0.70
0.73 0.66 0.65
3.67 2.67 2.52
Cell adhesion
Esel ICAM1 VCAM1
0.72 0.73 0.62
0.52 0.60 ns
ns 0.83 ns
ns 0.55 ns
ns 0.75 0.85
1.24 3.46 1.47
Lipid uptake/accumulation
LDLR SRA CD36 ACAT1
0.82 0.81 0.51 0.55
0.78 ns ns ns
0.67 ns ns ns
0.84 0.70 0.70 0.80
0.74 ns 0.71 ns
3.87 1.51 1.92 1.35
Cholesterol reverse transfer
ABCA1 ABCG1 CEH ApoE SRBI
0.82 0.62 0.85 0.64 0.78
0.50 0.51 0.92 ns ns
ns ns 0.86 ns ns
0.63 0.52 0.93 0.55 ns
ns ns 0.94 ns ns
1.95 1.65 4.50 1.19 0.78
Sensors/transcriptional regulators of lipid turnover
LXRα LXRβ PPARα PPARγ SREBP1 SREBP2
0.77 0.74 0.74 ns 0.52 0.79
0.72 0.75 0.50 ns 0.52 0.55
ns 0.85 0.74 −0.62 0.64 0.82
0.75 0.60 0.77 ns 0.57 0.52
ns 0.72 0.84 ns 0.83 0.72
2.24 3.76 3.59 0.62 3.08 3.40
Inflammation
TNFα CCL18 TLR4
0.81 0.55 0.73
0.62 ns 0.78
0.74 ns 0.64
ns 0.62 0.75
0.86 ns 0.90
3.03 1.17 3.8
Endosome/lysosome components
EEA1 Rab5a Lamp1 Lamp2 p62 CD63 CD68 TfR
ns ns ns 0.62 0.66 0.64 0.70 0.85
ns 0.52 ns ns 0.79 0.69 ns 0.64
ns ns ns ns ns ns ns 0.64
ns 0.56 ns 0.85 0.65 0.91 0.60 0.76
ns 0.86 ns 0.83 ns ns ns 0.75
0.0 1.94 0.0 2.30 2.10 2.24 1.30 3.64
Σ|Rs|
20.65
13.77
8.43
17.22
13.34
Sex hormones metabolism/action
All groups
* ns, absence of statistically significant correlation. Black background highlights correlations for mRNAs with high succession of expression in aor tal samples without lesion and containing atherosclerotic lesions of types I, II, and Va (Σ|Rs| > 3.0, right column); gray background highlights cor relations for mRNAs with low succession of expression in said aortal sample sequence (Σ|Rs| 1.5, right column).
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b
Gh
Gh
a
d
Gh
Gh
c
f
Gh
Gh
e
h
Gh
Gh
g
Variants of changes in extent of coupling (Gh) of individual mRNAs with other mRNA species during atherogenesis
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Table 2. Coupling between mRNAs and portion of negative correlations for total mRNA population in intact (“0”) and atherosclerotically damaged aortal tissue Lesion type
Σ|Rs| Negative correlations, %
0
I
II
Va
59.95
64.07
85.98
88.04
6.2
3.1
7.6
28.0
in vessel wall. Therefore, the number of clusters should be at least three. To choose the optimal number of clusters, two arbitrary criteria were used. The first criterion was based on the presence of shared regulatory elements LXRE in the ABCA1, ABCG1, ApoE, and LXRα genes, with existence of functional connection between respec tive proteins [3] and high conservatism of correlations between all mRNAs within this group (Table 3). Based on these suppositions, we suggested that at least three of the mRNAs should be members of a common cluster in aor tal tissue. The second criterion was based purely on the most conservative ties (in total 25) between mRNAs shown in Table 3. We believe that division into clusters should not lead to obvious divergence of members of such pairs into different clusters. Table 4 shows the results of division of total correla tions into 3, 4, and 5 clusters. One can see that the best correspondence to the applied criteria was achieved when the total correlations were divided into four clusters. Table 5 shows the distribution of individual mRNA correlations between four clusters. The clusters were enu merated according to the membership of mRNA of ABCA1 (cluster 1), SELE (cluster 2), EEA1 (cluster 3), and cluster 4 without stable representation of any mRNA. One can see that with the exception of mRNAs ABCA1/ABCG1/LXRα, SELE/VCAM1/LDLR, and EEA1/Rab5a, correlations of the majority of the mRNAs drifted from one cluster to another in the “intact tissue – lesions of types I, II, and Va” sequence. The leaders in terms of drift are mRNAs SRA, CD68, and TfR1, which drifted always together however, obviously due to high conservatism in coupling between these mRNAs (Table 3). The drift of a given mRNA from one cluster to another seems to be associated with quantitative and/or qualitative changes in ensembles of regulators of gene expression. Factor analysis was used for formal descrip tion of these changes. Table 6 shows that along the disease progression, the number of factors that determine correlations between mRNAs declines. This regularity becomes even more pronounced when individual factor loadings into correla tions of individual mRNAs are considered (Table 7). One can see that along the “intact tissue – lesions of type I –
lesions of type II – lesions of type Va” sequence the load ing of factor 3 and then that of factor 2 decreases. As a result, in fibroatheroma (lesion of type Va) the majority of correlations are determined by single factor.
DISCUSSION The changes in expression (at the levels of activity and content of protein and/or mRNA) of many factors engaged in formation of local inflammation, lipid turnover, cell adhesion, and metabolism/action of sex hormones during atherogenesis has been determined in many studies [1419]. Such investigations concern main ly advanced atherosclerotic lesions or were performed with macrophages exposed to modified (oxidized, acety lated, aggregated, etc.) low density lipoproteins, which represent surrogate model of atherogenesis. The dynam ics of such changes on the transition from one morpho logical type of lesion to the following type and particular ly at the early stages of the disease has not been fully examined. Such changes for the analyzed group of mRNAs were presented by the authors in a separate pub lication [13]. Moreover, revealing of the quantitative changes in expression of certain genes is only one side of cognition of atherogenesis pathophysiology. Protein products of different genes often act in a cell together, as functional and/or structural ensembles. The EEA1 Rab5a pair can serve as an example of such ensembles, where the components of the pair interact each other physically during formation and functioning of early endosomes [20]. Therefore, it is very important to know how expression in gene ensembles is coordinated. In a number of cases, this coordination is achieved due to presence in regulatory sequences of certain gene groups of similar elements that provide similar effects of modulato ry factors. Specifically, lipids from low density lipopro teins can serve as such factors directly or indirectly affect ing activities of transcriptional factors of LXR (sterol sen sors), PPAR (fatty acid sensors), and SREBP (mediators of cholesterol sensors SCAP and INSIG) groups [3]. By now, structural–functional organization of regulatory regions, even partially, has been revealed for only a small number of genes. And even less is known about tissue BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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* Shortened abbreviations are used.
Inflam mation
Adhe sion
Table 3. Superposition of significant correlation ties between the content of studied mRNAs in aortal intima without lesions and in lesions of types I, II, and Va. Black and gray backgrounds highlight positive and negative correlations, respectively. Symbols •, ••, and ••• mark off correlations shared for two, three, and four tissue types, respectively. Symbol # marks off correlations with sign reversal in one of tissue types COORDINATION IN GENE EXPRESSION DURING ATHEROGENESIS 939
940
SHCHELKUNOVA et al.
Table 4. Selection of optimal number of clusters of correlation ties between studied mRNAs in four aortal tissue types Lesion type 0
I
II
Va
0
I
II
Va
0
I
II
Va
3/4
3/4
Given cluster number 4
3
5
Presence of ABCA1, ABCG1, ApoE, and LXRα mRNAs in shared cluster (criterion 1) 4/4
2/4
4/4
4/4
3/4
4/4
4/4
4/4
4/4
15/16
14/16
Total
4/4
14/16
Number of highly conservative correlations which members present in shared clusters (criterion 2) Σ Total
14
17
25
24
16
80/100
specific functioning of regulatory elements in the context of different physiological and pathophysiological circum stances. Correlation analysis of gene expression allows to a certain extent to clarify the situation with evolution of the system of interactions between genes in the course of progression of diseases such as atherosclerosis. This approach is particularly suitable for human studies, when current powerful tools of analysis such as knockdown or reporter construct introduction cannot be applied. Here, we operated mainly with statistically signifi cant (p < 0.05) correlations without Bonferroni correc tion for probability of catching random correlations in repeated rounds of the analysis. The introduction of such correction for correlations between 34 mRNA species would lead to application of p value of p = 0.05/(33 × 33) ~ 0.00005. No one correlation with threshold of p = 0.05 corresponds to this hard criterion in intact tissue and lesions of types I, II, and Va. Formally correct, this approach deprives correlation analysis of any sense. On the other hand, the superposition of correlations in aortal samples without lesions and with atherosclerotic lesions shown in Table 3 demonstrates that 66% of the found cor relations are conservative. The coincidence of random correlations in two or more tissue types seems to be extremely unlikely (the probability of such coincidence is equal to the product of p values, i.e. no more than 0.05 × 0.05 = 0.0025, a significant part of correlations being characterized by p values of p < 0.01). The remaining 34% of significant (at p < 0.05) correlations are found only in one tissue type, and among them, indeed, random corre lations may be present. In interpretation of these noncon servative correlations, we issued from the assumption that random correlations are distributed within the correlation matrix in random fashion and this distribution pattern only “fogs” the picture as well, to some extent without crucial change. An analysis of succession in mRNA
21
25 78/100
16
14
17
14
13
58/100
expression calculated as in Table 1 but using both signifi cant and nonsignificant correlations can serve as an illustration of the appropriateness of the used approach. In this case, hierarchy of correlation graph weights was preserved while differences of these values appeared very small, which hampered separation of groups with high and low succession in expression during atherogenesis. According to the theory of correlation adaptometry, biological systems of different levels of organization respond to unfavorable conditions by rise in coupling between analyzed parameters [12, 21]. The data obtained here generally correspond to this theory, demonstrating rise in coupling between 34 mRNA species in the course of the disease progression along the sequence: aortal tis sue without lesions < atherosclerotic lesions of type I < atherosclerotic lesions of type II atherosclerotic lesions of type Va (Table 2). This general tendency is particularly apparent for CCL18, TfR1, ApoE, and LXRβ mRNA (figure, panel (b)). For a number of mRNAs (PPARα, PPARγ, TLR4, p62, SREBP2, SRBI, ICAM1, TNFα) that belong to different functional groups including groups of lipid sensors and inflammatory factors, a “col lapse” in coupling in lesions of type I is a feature (figure, panels (e) and (g)). From the viewpoint of the theory of correlation adaptometry, the data can point to some mechanisms active in the initial stage of atherogenesis that prevent further disease progression. When this “col lapse” is interpreted, the fact that mRNA content was measured in mixed cellular population should be taken into account. Foam cells formed from macrophages, according to histological analysis, constitutes only a small portion of the total cellular population of the intima. Even in lipofibrous plaques of aorta, hematogenous cells including monocytes/macrophages compose no more than 15% of the total cell population [22]. Therefore, one can suggest that the measured mRNA levels and their BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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Table 5. Distribution of correlations of individual mRNAs between four clusters Lesion type Group
mRNA 0
I
II
Va
Cluster No. Sex hormones metabolism/action
Cell adhesion
Lipid uptake/ accumulation
Cholesterol reverse transfer
Sensors/transcrip tional regulators of lipid turnover
Inflammation
Endosome/ lysosome components
STS
4
3
4
3
Arom
2
2
4
2
EST
4
3
4
4
AR
4
2
3
3
ERα
4
2
3
3
SELE
2
2
2
2
ICAM1
2
2
2
4
VCAM1
2
2
2
2
LDLR
2
2
2
2
SRA
2
3
1
4
CD36
2
3
1
1
ACAT1
3
3
1
4
ABCA1
1
1
1
1
ABCG1
1
1
1
1
CEH
2
4
4
2
ApoE
2
1
1
1
SRBI
4
1
1
4
LXRα
1
1
1
1
LXRβ
1
1
3
3
PPARα
1
4
3
3
PPARγ
3
3
1
1
SREBP1
1
1
1
2
SREBP2
4
4
3
2
TNFα
2
3
2
4
CCL18
2
3
1
1
TLR4
1
4
3
3
CD68
2
3
1
4
EEA1
3
3
3
3
Rab5a
3
3
3
3
Lamp1
3
3
1
3
Lamp2
3
3
1
4
p62
3
4
3
2
CD63
1
4
3
3
TfR1
2
3
1
4
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Table 6. Cumulative contribution of factors 16 loading in correlations between mRNAs in intact aorta and lesions of types I, II, and Va. The number of mRNA species (from 34) whose correlations are determined more than by 70% by cumulative contribution of factors is shown Factors Lesion type 1
1+2
1+2+3
1+2+3+4
1+2+3+4+5
1+2+3+4+5+6
0
2
9
21
28
32
33
I
7
17
27
32
33
34
II
11
21
29
33
34
Va
17
23
27
32
34
correlations reflect gene expression mainly in quantita tively dominant resident intimal cells. We speculate that lipid uptake by scattered macrophages in lesions of type I decrease the pressure of these lipids onto surrounding res ident cells. As a result, the extent of coordination in expression of genes encoding the abovementioned pro teins declines. Lesions of type I are found even in infants. It is implied though not proved that such lesions can dis appear spontaneously. Thus, the evacuation of proathero genic lipids from the subendothelial space by not numer ous macrophages can serve as one of the mechanisms keeping aorta in working condition, and formation of foam cells at the initial stage of atherogenesis can be more likely a physiological adaptation than a transition to pathology. Negative correlations represent another interesting aspect of the analysis. Such correlations can arise as a result of opposite effects of the same regulator on expres sion of two genes. Mechanisms of opposite effects are diverse and include the use of positive and negative regu latory elements by a regulator, modulation of form of activity of a regulatory protein (e.g. functioning as tran scriptional regulator or coregulator), or context dependent recruitment of coactivators and corepressors of an alternative regulatory element by transcriptional factors [23]. Under other equal circumstances, negative correlations generally point to a stratification of the pop ulation in respect of parameter pairs under study. In this connection, significantly higher level of negative correla tions in lesions of type Va as compared with norm and lesions of types I and II (Table 2) attracts attention. Lesions of type Va are considered as possible precursors of complicated lesions of type VI, calcified plaques of type Vb, and depleted of lipid core plaques of type Vc. It is not excluded that negative correlations in lesions of type Va reflect the direction of the future fibroatheroma develop ment. The ties of mRNAs for sex hormone metabolism and reception (excluding mRNA of estrogen receptor) are particularly enriched by negative correlations, which may point to involvement of sex hormones in control of
further atheroma development. Gender differences in cardiovascular risks that are dependent on sex hormones are well known [24]. The data on progressive decline during atherogenesis in number of mRNA species whose content in athero sclerotic lesions correlates with their content in normal tissue (Table 1) was generally expected. The existence of mRNAs whose levels never or almost never correlate with their contents in norm or other lesion types or, on the contrary, always or almost always correlate with their con tents in norm or other lesion types was unexpected. One can assume that in regulation of gene expression of the first type, local regulatory factors specific for given stage dominate at different stages of atherogenesis, while in the case of genes of the second type key regulators retain their importance in the course of the disease and can have either systemic or local origin. Interestingly, members of the same functional groups of mRNAs, such as PPARγ and PPARα, ACAT1, and LDLR, can be found at oppo site poles of succession. Cluster analysis of correlations between mRNA con tents showed that the studied mRNAs can be combined into several groups or clusters (in our opinion, four clus ters; Table 4) in which the coupling between individual mRNAs exceeds the coupling between mRNAs from dif ferent clusters. For the majority of mRNA species, a “drift” from one cluster to the other in the “intact tissue – lesions of type I – lesions of type II – lesions of type Va” sequence is a character feature (Table 5). This drift presumably reflects changes in predominant gene expression regulators during atherogenesis. These changes in regulators are confirmed by factor analysis (Tables 6 and 7). According to results of this analysis, in intact aorta the studied genes are subjected to a wide spectrum of regulators. In the course of atherosclerosis progression this spectrum narrows so that in lesions of type Va, the regulation becomes mainly singlefactor. This evolution in regulation is visually illustrated by exit of mRNAs ABCA1, ABCG1, and SRBI under predom inant pressure of factor 3 in intact tissue with transition BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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Table 7. Contributions of factors 13 in individual mRNAs correlations. Marked by black background contributions are >0.7 Lesion type mRNA 0
Va
II
I Contribution of factors
STS Arom
1
2
3
1
2
3
1
–0.31
–0.73
–0.34
–0.86
0.30
0.33
0.22
–0.55
–0.32
–0.84
0.26
1
2
–0.56
0.86
0.33
–0.16
–0.22
0.26
–0.11
0.61
0.26
2
3
0.26
–0.49
–0.15
0.54
3
–0.09
–0.82
–0.21
–0.83
0.07
–0.06
0.08
–0.43
–0.73
–0.75
0.37
0.29
AR
–0.80
–0.23
0.11
–0.52
0.22
0.61
0.60
0.71
0.09
0.96
0.04
–0.06
ERα
–0.76
–0.30
0.01
–0.37
0.33
0.50
0.22
0.84
–0.10
0.63
–0.29
0.33
0.69
–0.08 –0.04
EST
SELE
0.82
–0.25
0.13
–0.14
0.21
–0.90
0.08
–0.71
0.60
–0.51
ICAM1
0.44
–0.54
0.32
–0.56
0.35
–0.49
–0.31
–0.72
0.41
–0.96
0.19
VCAM1
0.07
–0.42
–0.45
–0.64
0.46
0.08
–0.42
–0.30
0.69
–0.60
0.30
0.33
LDLR
0.07
–0.19
–0.47
–0.30
0.58
–0.61
0.34
–0.69
0.40
–0.75
0.02
–0.05
SRA
0.16
–0.69
0.61
–0.82
–0.51
0.09
–0.98
0.12
0.00
–0.95
0.02
–0.16
CD36
0.51
–0.56
0.30
–0.87
–0.32
0.10
–0.85
0.11
–0.14
–0.88
–0.26
–0.14
ACAT1
–0.52
–0.34
0.17
0.29
–0.16
–0.28
–0.81
0.15
–0.18
–0.98
–0.02
0.03
ABCA1
–0.20
0.34
0.82
0.17
–0.92
0.01
–0.91
0.20
0.24
–0.83
0.06
–0.46
–0.05
–0.22
–0.34
–0.67
–0.25
0.32
0.85
0.53
–0.77
–0.22
–0.95
0.13
0.04
–0.92
CEH
0.30
0.15
–0.48
0.67
–0.18
0.26
0.19
–0.13
0.03
–0.30
ApoE
ABCG1
–0.70
–0.56
0.15
–0.84
–0.32
–0.09
–0.96
0.17
0.09
–0.96
0.20
0.06
SRBI
0.35
0.35
0.74
0.03
–0.95
–0.13
–0.92
0.30
–0.04
–0.97
–0.09
–0.15
LXRα
–0.70
0.29
0.48
0.37
–0.50
0.60
–0.56
0.70
0.18
–0.76
–0.41
–0.25
LXRβ
–0.34
0.38
0.08
0.32
–0.46
–0.39
0.43
0.80
0.32
0.89
0.29
–0.20
PPARα
–0.85
0.32
0.25
0.74
–0.35
0.22
0.28
0.94
0.05
0.90
–0.21
–0.28
PPARγ
–0.84
–0.24
0.35
–0.50
–0.46
0.64
–0.92
0.37
–0.00
–0.83
–0.52
–0.11
0.60
–0.36
–0.53
0.05
SREBP1
0.05
0.51
0.34
–0.04
–0.73
–0.54
–0.84
0.34
0.32
–0.33
SREBP2
–0.66
–0.24
–0.44
0.56
0.55
–0.04
0.48
0.67
–0.19
0.20
0.55
–0.75
0.22
–0.58
–0.38
–0.60
–0.12
–0.78
–0.41
–0.95
0.01
0.01
0.37
–0.59
–0.75
–0.13
–0.93
–0.33
0.02
–0.96
–0.18
0.06
0.83
–0.23
0.87
–0.27
0.78
–0.33
–0.34
TNFα
0.82
–0.05
TLR4
–0.96
0.16
0.02
0.21
0.10
CD68
CCL18
0.15
–0.44
0.80
–0.83
–0.43
0.18
–0.93
0.13
–0.08
–0.97
0.12
–0.00
EEA1
–0.73
–0.53
0.08
–0.97
0.06
0.13
0.25
0.91
–0.07
0.89
0.42
–0.04
Rab5a
–0.79
–0.54
–0.06
–0.91
–0.00
0.27
0.29
0.85
0.13
0.92
0.29
0.05
0.42
–0.65
0.49
–0.24
Lamp1
–0.72
–0.35
–0.05
–0.83
–0.02
0.11
–0.48
0.58
0.22
0.60
Lamp2
–0.20
–0.80
0.41
–0.96
–0.05
0.14
–0.80
0.07
–0.15
–0.79
p62
–0.73
–0.17
0.09
0.54
0.64
–0.16
0.69
0.56
0.22
0.25
0.65
–0.52
–0.62
0.72
–0.02
0.73
–0.57
0.30
–0.06
0.87
–0.20
0.34
–0.77
–0.38
0.58
–0.53
0.38
–0.71
–0.44
–0.37
–0.86
–0.30
–0.30
–0.96
–0.01
–0.01
10.97
7.48
5.41
13.88
7.40
5.17
13.44
10.79
3.04
21.02
4.61
2.53
CD63 TfR1 Eigenvalue
BIOCHEMISTRY (Moscow) Vol. 78 No. 8 2013
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SHCHELKUNOVA et al.
under the influence of factor 2 in lesions of type I and fol lowing transition under predominant influence of factor 1 in lesions of types II and Va. We do not take the risk of hypothesizing on the nature of these regulatory factors. Possibly, regulators that act separately in intact tissue, along the disease develop ment begin act in one direction, composing thus a shared factor. Such a situation might arise, for example, follow ing functional integration of lipid and cytokine signaling. Indeed, as shown in Table 5, in lesions of types II and Va, mRNAs for oxysterol sensor LXRα, fatty acid sensor PPARγ, chemokine CCL18, and fatty acid transporter CD36 (which acts also as a signaling receptor for oxidized lipoproteins [25]) belong to a shared cluster. In intact tis sue and in lesions of type I these mRNAs belong to dif ferent clusters. Although the expression of only a small gene group that constitutes about 0.1% of all human genes was ana lyzed in the present study, this analysis allowed us to reveal several regularities that have not been described previously. The data obtained using matrixes allowing simultaneous analysis of expression of more than 20,000 genes usually need confirmation by quantitative PCR, which has been applied for only a few mRNA species of interest [15, 2629]. Thus, in the end, the representative ness of our results yields to no results of others. To the best of our knowledge, there are no publications where sequential stages of the disease were studied in parallel. An analysis of several disease stages in the same individ ual is among advantages of the present study. As a rule, changes in gene expression during atherogenesis are char acterized by the extent of induction or reduction in mRNA content by means of comparisons between advanced atherosclerotic lesion (fibroatheroma) and intact vessel tissue. For the same aim, cells of a certain type (endothelial cells, macrophages) isolated from dif ferent segments of the bloodstream or different tissues are used. Information thus obtained, of course being very important, still does not answer the question about rea sons for largescale reorganization in genome functioning in the course of the disease development. Here, we attempted to solve this question using the correlation analysis approach, which, to our best knowledge, had not been used for this aim previously. From the results obtained, the conclusion that sequential narrowing of the spectrum of gene expression regulators towards single factor dependence in lesions of type Va seems to be the most important. It should be noted, however, that the selection of mRNAs for this study was not random, so conclusion on drift towards singlefactor regulation dur ing the disease progression needs confirmation with an additional mRNA population. In the case of such confir mation, one can expect the generation of efficient thera peutics for remission of advanced forms of atherosclero sis.
This work was financially supported by the Russian Foundation for Basic Research (project 090400329a). The part of experiments was performed using facili ties of the Center of Collective Use “Genome” at the Engelhardt Institute of Molecular Biology.
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