Title: IgG sera levels against a subset of periodontopathogens and severity of

disease in aggressive periodontitis patients: a cross-sectional study of selected

pocket sites.

Running Title: IgG levels in aggressive periodontitis

Keywords: aggressive periodontitis, antibodies, qPCR, A.

actinomycetemcomitans, P. gingivalis, T. forsythia.

Authors:

Luciana Saraiva, DDS, MSc, PhD1

Estela S Rebeis, undergraduate student¹

Eder de S Martins, DDS¹

Ricardo T Sekiguchi, DDS, MSc, PhD1

Ellen S Ando-Suguimoto DDS, MSc, PhD2

Carlos Eduardo S Mafra, DDS, MSc¹

Marinella Holzhausen, DDS, MSc, PhD1

Giuseppe A Romito, DDS, MSc, PhD, Chairman1

Marcia P A Mayer, DDS, MSc, PhD2

1 Department of Periodontology, Dental School, University of São Paulo, São Paulo,

SP, Brazil

2 Department of Microbiology, Institute of Biomedical Sciences, University of São

Paulo, São Paulo, SP, Brazil

Corresponding author:

Luciana Saraiva

Universidade de São Paulo – Faculdade de Odontologia

Departamento de Estomatologia - Periodontia

Av. Professor Lineu Prestes, 2227.

Cidade Universitária – São Paulo – SP - Brazil

CEP: 05508-000

Phone: + 55 11 3091-7833

Fax: +55 11 3091-7833

E-mail: lusaraiva@usp.br

Conflict of Interest and Source of Funding Statement

The authors declare that they have no conflict of interests. This study was supported by

Research Grant # 2010/16162-1 from São Paulo Research Foundation – FAPESP,

Brazil.

Abstract

Aims: To evaluate the association among serum immunoglobulin G (IgG) responses to

Aggregatibacter actinomycetemcomitans (Aa) serotypes a, b and c, Porphyromonas

gingivalis (Pg) Tannerella forsythia (Tf) and clinical parameters in Aggressive

Periodontitis (AP) subjects. Associations between periodontal pathogens and clinical

and immunological parameters were also evaluated.

Methods: 38 subjects diagnosed with generalized AP (GAP) and localized AP (LAP)

were included. Ten healthy controls were also evaluated. Clinical parameters were

assessed and percentages of subgingival levels of Aa, Pg and Tf, (beyond bacterial

load), were determined by quantitative real-time polymerase chain reaction. Serum IgG

antibody levels against Aa, Pg and Tf were evaluated by enzyme-linked

immunosorbent assay.

Results: Percentages of Aa, Pg and Tf were significantly higher in AP than in controls.

The response to Aa serotype c was higher in LAP subjects than in controls. There were

no differences in microbial composition or antibodies responses between GAP and

LAP, except for IgG response to Tf. Pg levels were correlated with PD, BoP and CAL in

GAP but not in LAP subjects. Tf levels correlated to PD and CAL in GAP subjects. In

GAP, the infection levels of Aa and Pg correlated with the corresponding IgG levels to

Aa serotype c and Pg.

Conclusion: Given the evidences that IgG response in AP patients correlated with

bacterial infection level in GAP, but not in LAP, and that LAP patients lack a response

to Tf, despite harboring this species, our data suggests a difference in host immune

defense between these two forms of aggressive periodontitis.

Clinical Relevance:

Scientific Rationale: Localized and Generalized Aggressive Periodontitis are

recognized clinical entities in Periodontology. However, except for clinical parameters,

there are no other data differing these two forms of disease. Principal Findings:

Despite similar periodontopathogens levels and percentages in GAP and LAP, IgG

response to T. forsythia is more prevalent in GAP than in LAP. Practical Implications:

Thus, IgG response to T. forsythia could show utility as a prognostic tool for AP,

pending further longitudinal studies.

Introduction 1

Elevated serum antibodies against periodontopathogens were reported in 2

chronic periodontitis (CP), aggressive periodontitis (AP) and refractory periodontitis 3

(Colombo et al. 1988; Kudo et al. 2012). Antibody titers in combination with other 4

factors have been used as markers of periodontal destruction in humans and can 5

contribute to the classification of periodontal disease in adults over 40 years of age 6

(Dye et al. 2009; Vlachojannis et al. 2010). 7

However, the data on the antibodies response in young patients with severe 8

bone loss are still conflicting. Bacteria infection level is the strongest determinant of 9

systemic antibody responses to periodontal pathogens (Pussinen et al. 2011). On the 10

other hand, the consensus report of the 1999 International Workshop for the 11

Classification of Periodontal Diseases and Conditions concluded that increased 12

antibody serum levels against periodontal pathogens were associated with the 13

localized (LAP) but not with the generalized (GAP) form of AP. This conclusion was 14

based on studies evaluating the immune response against A. actinomycetemcomitans 15

(Aa) in the so called juvenile periodontitis patients (Califano et al. 1997; Tinoco et al. 16

1997). However other microorganisms such as Porphyromonas gingivalis (Pg) and 17

Tannerella forsythia (Tf) strongly related to CP (Socransky & Haffajee 2002) are also 18

associated with AP (Faveri et al. 2008; Casarin et al. 2010; Tomita et al. 2013). A 19

recent report questioned this postulate, since no differences in antibodies titers against 20

11 bacterial species were found between LAP and GAP patients (Hwang et al. 2014), 21

in spite of their differences in subgingival biofilm composition and total bacterial load. 22

Furthermore, most studies evaluated immune response to Aa whole cells of a 23

single (Wang et al. 2005) and/or a mix of two serotypes (Vlachojannis et al. 2010; 24

Hwang et al. 2014), and there are very few data on immune response to each serotype 25

separately (Ando et al. 2010). Aa serotype b is associated with AP (Cortelli et al. 2012), 26

serotype c with CP (Roman-Torres et al. 2010) and serotype a with health (Asikainen 27

et al. 1995). 28

The role of serum antibody levels to periodontopathogens in periodontitis is still 29

controversial. Not only the microbiota and the total bacterial load may differ between 30

LAP and GAP, but the immune response to the same challenge may differ according to 31

yet unknown genotypic traits, such as polymorphism in genes encoding host immune 32

factors (Finoti et al. 2013). Thus, this study aimed to evaluate the association between 33

IgG response to different Aa serotypes, Pg and Tf and clinical parameters in AP, and to 34

correlate the data of serum response with the bacterial load. 35

36

Material and Methods 37

Participants 38

The study was approved by Ethics Committee of the School of Dentistry, 39

University of São Paulo (FOUSP). Subjects were selected out of 323 patients referred 40

to periodontal treatment at FOUSP. Ten periodontally healthy subjects were selected 41

among dental students. 42

AP was diagnosed according to the clinical criteria established by the 1999 43

International Workshop for the Classification of Periodontal Diseases and Conditions 44

(Armitage 1999). The inclusion criteria for the periodontally healthy subjects were: no 45

sites with probing depth (PD) and clinical attachment level (CAL) measurements > 3 46

mm, and < 10% of sites exhibiting bleeding on probing (BoP), no extensive caries 47

lesions or restorations and at least 28 permanent teeth. 48

Exclusion criteria for all groups included pregnant or nursing women, smokers 49

and patients with systemic diseases or using medications that could affect the 50

periodontium. 51

52

Periodontal examination 53

Periapical radiographs were taken and bone loss was calculated. BoP (0/1), PD 54

and CAL were measured at six sites per tooth in all teeth (excluding third molars) at 55

baseline, using a periodontal probe (Hu-Friedy®, Chicago, IL, USA). A single trained 56

examiner (LS) made all measurements. 57

Measurement reproducibility was calculated by intra-class correlation coefficient 58

(ICC) for the following variables: distance from the cement-enamel junction to the 59

gingival margin and PD, in two separate examinations, in 10 subjects with CP. 60

Agreement between replicate measurements was ICC > 0.85. 61

62

Microbial analyses 63

After removal of supragingival dental plaque, subgingival biofilm was collected 64

from the deepest pocket in each quadrant with a sterile paper point (Tanariman Ind. 65

Ltda®, AM, Brazil) which was subsequently transferred to tubes containing 100 µl of 66

sterile TE buffer (10mM Tris-HCl, 1mM EDTA, pH 7.6) and stored at -80ºC. 67

DNA was extracted using Qiamp DNA Mini kit® (Qiagen, Hilden, Germany) 68

according to the manufacturer’s instructions. After extraction, DNA concentration and 69

purity was evaluated in a spectrophotometer (ND-100 Spectrophotometer®, Nanodrop 70

Technologies Inc., DE, USA). 71

The quantification of Aa, Pg and Tf was performed by quantitative qPCR, using 72

specific primers (Rudney et al. 2003, Ramseier et al. 2009, Shelburne et al. 2000). 73

Total bacterial load was determined with 16SrRNA universal primers (Shelburne et al. 74

2000). Standard curves were made using 16SrRNA genes for each species cloned in 75

PCR 2.1 TOPO TA® vector (Invitrogen, CA, USA) diluted 107 to 101 copies. 76

Amplification efficiency ranged from 90 to 110 %. qPCR was performed using the 77

StepOnePLus™ (Applied Biosystems®, NY, USA) with Power Sybr Green PCR Master 78

Mix® (Life Technologies Co., NY, USA) and 2 µl of template DNA. DNA samples and 79

standard dilutions were run in triplicate. Amplification profiles were as follows: 80

95ºC/15´´, 65ºC/1´, 81ºC/10´´, 40 cycles for Aa; 95ºC/15´´, 60ºC/1´, 81ºC/10´´, 40 81

cycles for Pg; 95ºC/15´´, 60ºC/1´, 74ºC/10´´, 40 cycles for Tf and 95ºC/15´´, 60ºC/1´, 82

40 cycles, for quantification of total bacteria. Levels of each species were expressed 83

as the number of copies of 16S rRNA genes. An average bacterial load, for each 84

microorganism, was calculated to each subject by averaging the microbial values from 85

the four sampled sites. Infection level was considered as the mean count of each 86

bacterium obtained from the four deepest sites, multiplied by the number of affected 87

sites with PD ≥ 6 mm. The percentage of each species was calculated in relation to the 88

number of copies of 16S rRNA, obtained using universal primers for each site for each 89

patient. 90

Furthermore, the infection level (IL) of each organism was calculated for each 91

subject as follows: IL= mean levels of the pathogen at the four deepest sites x no sites 92

with PD ≥ 6 mm 93

94

Serum IgG analyses 95

Peripheral blood samples were collected by venipuncture using vacuum tubes 96

(BD vacutainer®, Becton, Dickson and Company, SP, Brazil). Blood samples were 97

centrifuged at 3,000g for 1 minute and the sera were stored in aliquots at -20ºC. 98

An enzyme-linked immunosorbent assay (ELISA) was used to determinate the 99

total IgG levels against Aa serotypes a, b and c, Pg and Tf. Formalin-fixed whole 100

bacterial cells of reference strains Aa ATCC 29523, JP2 and SA 1151 (serotypes a, b 101

and c respectively), Pg W83 and Tf ATCC 43037 were used as antigens in separate 102

assays. Ninety-six-well plates (Corning-Costar, Lowell, MA, USA) were coated with 200 103

µl/well of Aa [Optical Density (O.D)580nm = 0.3], Tf (O.D.580nm = 0.4) or Pg (O.D.600nm = 104

0.2) in sodium carbonate buffer (pH 9.6). After washing and blocking with 5% milk 105

(Molico®, Nestlé Brazil Ltda., SP, Brazil) in PBS, diluted sera samples [(1:10,000, 106

1:20,000 and 1:40,000 for Aa and Pg) and 1:500, 1:1,000 and 1:10,000 to Tf] were 107

added in triplicate. 108

Sheep anti-human IgG® (Sigma-Aldrich, MO, USA) was used as secondary 109

antibody. The end-point conversion of the enzyme substrate was measured at 490nm 110

in a microplate reader (Bio-Rad, CA, USA). A negative control (no serum sample) and 111

ten control sera (healthy participants) were included in each plate. 112

The O.D. values were normalized among plates based on data obtained for the 113

controls. The cut-off levels for reactivity to antigens were calculated based on 114

Desphande´s formula [normalized O.D. - (control mean + 2 standard deviations of 115

control)] (Desphande 1996). For Aa the formula was: normalized O.D. – (control mean 116

+ 7 SD control) in order to avoid false positives due to common antigens among 117

different serotypes (Ando et al. 2010). 118

119

Statistical Analysis 120

Kruskal-Wallis Test was used to detect differences between healthy, LAP and 121

GAP groups regarding age, PD, CAL and BoP and to find differences in IgG subclass 122

antibody levels between positive and negative subjects. Dunn´s Multiple Comparisons 123

Test was used to evaluate all pairwise comparisons. The same tests were used to 124

determinate differences in bacteria percentages among GAP, LAP and CG and to 125

determinate differences regarding age. 126

Spearman´s test was used to analyze correlations between subgingival levels of 127

Aa, Pg and Tf and species-specific IgG levels and between IgG levels and clinical 128

variables. Differences in bacteria levels in deep pockets between GAP and LAP were 129

calculated by Mann-Whitney Test. 130

Chi-square Test was used to find differences regarding ethnicity and gender 131

among the groups. Significance was established at 5% (p<0.05). All tests were 132

performed using statistical software (GraphPad Prisma®, GraphPad Software, LaJolla, 133

CA, USA). 134

135

Results 136

Thirty-eight AP patients (aged 29.24 ± 6.4 years old) were included, 10 with 137

LAP and 28 with GAP. As a control group (CG) 10 periodontally healthy subjects (21.6 138

± 1.57 years old) were examined. There was no association regarding ethnicity and 139

gender. GAP subjects were significantly older than healthy subjects (table 1). GAP 140

individuals presented significantly higher mean PD, CAL and BoP than CG while LAP 141

showed higher mean PD and BoP than CG (figure 1). 142

143

Bacterial Levels 144

Subgingival levels of Aa, Pg, Tf and total bacteria were evaluated by qPCR, and 145

the percentage of the number of copies of the microorganisms in relation to the total 146

average bacteria count in GAP, LAP and CG are shown in figure 2. 147

AP subjects harbored Aa, Pg and Tf, except for one GAP subject who 148

presented no detectable levels of Aa. Neither the bacteria levels in deep pockets nor 149

their percentages were significantly different between GAP and LAP. 150

In the CG, Aa was detected in 8 of 10 subjects, Pg was detected in 9 of 10 151

subjects and Tf was detected in all 10 control subjects. The percentage of Aa, Pg and 152

Tf were significantly higher in AP when compared to CG (figure 2). 153

Pg levels were correlated to PD (r = 0.509, p< 0.05*), BoP (r =0.512, p< 0.05*) 154

and CAL (r = 0.382, p<0.05*) in GAP subjects, but not in LAP. Furthermore, Tf levels 155

were correlated to PD (r = 0.451, p< 0.05*) and CAL (r = 0.469, p< 0.05*) in GAP. 156

157

Antibodies 158

Positive IgG levels to each pathogen were considered when the patient’s level 159

was above the cut-off level determined with sera from healthy controls at 1:10,000 160

dilutions to Aa and Pg and 1:500 to Tf. Data obtained from different dilutions were 161

reported since the sera titers to Tf were lower than for Aa or Pg (in Tf a positive reading 162

was only observed at the 1:500 dilution, whereas for Pg and Aa, the positive readings 163

above blank was observed at a much higher sera dilution). 164

The normalized O.D. values observed after ELISA as well as the number of 165

subjects responding with serum IgG to each of the studied microorganism are shown in 166

figure 3. Reactivity to Aa serotype a was rarely found in AP patients, and significantly 167

higher values were observed for CG when compared to AP. On the other hand, most 168

LAP and GAP subjects showed IgG levels to Aa serotypes b and c above the control 169

subjects, with a significant difference between LAP and CG (p<0.05) for Aa serotype c. 170

Except for a higher number of subjects responding to Tf in GAP group, IgG 171

levels to Tf were significantly higher in GAP than in LAP (p<0.05), there were no 172

statistical differences in the prevalence of subjects with positive antibodies titers to the 173

other bacteria when GAP and LAP were compared. Furthermore, there was no 174

correlation between IgG levels against any of organisms and clinical parameters. 175

The infection level was calculated for each subject taking into account the 176

bacterial levels at the deepest periodontal sites and the number of sites with PD ≥ 6 177

mm. The distribution of the AP subjects according to infection level to Aa serotype c, Pg 178

and Tf is shown in figure 4. In GAP, infection level of Pg correlated well to the 179

corresponding IgG levels to Pg (r= 0.5650, p < 0.05), but there was no correlation 180

between infection level and responses to Tf or Aa. On the other hand, infection level of 181

any of the studied organisms was not correlated to the corresponding IgG levels in 182

LAP. Furthermore, most subjects of the LAP group did not present IgG titers positive for 183

Tf, although they harbored the bacterium. The CG showed low percentages of the 184

microorganisms and no serum response to them (except for few subjects positive to Aa 185

serotype a). 186

Raw data are presented in Table 2. 187

188

Discussion 189

Antibody responses to pathogens are determined by several factors, such as 190

bacterial load (Pussinen et al. 2011), smoking (Mooney et al. 2001), ethnical 191

background (Craig et al. 2002), gender (Ebersole et al. 2008), age (Papapanou et al. 192

2000) and oxidative stress (Singer et al. 2009), although the relative contribution of 193

each factor is unknown. 194

The three-studied species were detected in subgingival samples of AP patients. 195

Aa is strongly associated with AP in certain populations, especially of African descent 196

(Ennibi et al. 2012). Fine et al. (2007) and Hwang et al. (2014) reported that Aa might 197

be highly prevalent among white Hispanics when compared to other Caucasians. In our 198

study we have also demonstrated a high prevalence of Aa in Brazilian subjects. 199

We have found no differences in microbial levels between GAP and LAP, 200

although only deep pockets were evaluated. Faveri et al. (2009) reported that Aa was 201

in significantly higher proportions in shallow and intermediate sites of LAP in 202

comparison with GAP. Methodological differences may also have accounted for the 203

different results obtained, as in the present study we have used qPCR, a very sensitive 204

method, and our samples were collected by using paper points instead of curettes 205

(Belibasakis et al., 2014). 206

Tf and Pg were highly prevalent in healthy controls, but their levels and 207

percentages were significantly lower in controls compared to AP (figure 2). On the 208

other hand, none of studied organisms comprised more than 1% (mean of 4 sites) of 209

total bacteria in each subject, and the highest value per site was less than 2% 210

observed for Aa in one GAP subject. Conversely, earlier data using checkerboard 211

DNA-DNA hybridization (Faveri et al., 2009) found higher proportions of these 212

periodontopathogens. However, it should be clear that, in these studies, the total 213

bacterial counts result from the analysis of about 40 species, which do not represent 214

the real total bacteria counts in subgingival sites. Furthermore, our data are in 215

agreement with other studies using qPCR (Abiko et al., 2010), and with those 216

evaluating the microbial diversity of subgingival sites using 16S pyrosequencing 217

(Bizzarro et al. 2013). 218

Serum IgG values against Aa and Pg were correlated with corresponding 219

quantities in saliva and with the severity of the disease in CP (Liljestrand et al. 2014). 220

We showed that in GAP subjects, Pg and Tf levels, and Pg and Aa infection levels 221

were correlated with clinical parameters but not with serum IgG. It should be mentioned 222

that the microbial analyses was performed at a single moment, and may not reflect the 223

microbial challenges that the subjects were submitted during disease progression. On 224

the other hand, neither variable correlated with disease severity in LAP. Thus, the 225

absence of differences in the amount and percentage of periodontopathogens in deep 226

periodontal pockets between LAP and GAP may indicate that the microbial challenge in 227

GAP would be more pronounced than in LAP. 228

Although serum response to Pg and Aa did not differ between LAP and GAP, 229

titers to Tf were found in more than one third of GAP patients while in controls and LAP 230

they were undetectable. Differently a recent report (Hwang et al., 2014) had not shown 231

any difference in antibodies titers between LAP and GAP. However, in this study the 232

age of the subjects (37.4 years versus 30.54), disease severity, and methods analysis 233

were different from ours. 234

Early studies have shown that subjects with AP exhibit remarkably increased 235

serum IgG antibody titers to Aa (Ebersole et al., 1983) and that antibody response to 236

Aa may be protective (Gunsolley et al. 1987; Ranney et al. 1982). Our data confirmed a 237

high response to Aa in the AP patients, and indicated that responses to serotypes b 238

and c were associated with AP, independently on the extension of destruction. 239

Serotype b is commonly associated with AP in most populations (Ennibi et al. 2012; 240

Höglund et al. 2013). Other studies reported a high prevalence of response to serotype 241

c in periodontitis patients in Europe (Jentsch et al. 2012), Asia (Bandhaya et al. 2012), 242

North (Chen et al. 2010) and Latin America (Ando et al. 2010; Cortelli et al. 2012). 243

While some studies have implicated Aa in the etiology of AP, mainly LAP 244

(Haraszthy et al. 2000; Mullally et al. 2000), others have not found a positive 245

association (Takeuchi et al. 2003, Gajardo et al. 2005). Pg and Tf are part of the red 246

complex of CP (Socransky et al. 1998), but have also been associated with AP (Tomita 247

et al. 2013; Feng et al. 2014). Our results have shown that Pg was present in all AP 248

patients and bacterial levels correlated with disease severity in GAP but not in LAP 249

subjects. Pg possesses several putative virulence factors and is considered a central 250

organism in the remodeling of the microbiota to a dysbiotic state in periodontitis 251

(Hajishengallis & Lamont 2012). An afimbriated Pg strain (W83) was used as an 252

antigen in the present study, due to variability of the main fimbriae, which could mask 253

response to other fimA types in ELISA (Yoshimura et al. 1987, De Nardin et al. 1991). 254

Pg is frequently detected in AP patients from different geographical locations 255

(Takeuchi et al. 2003; Faveri et al. 2008; Feng et al. 2014). Likewise, IgG antibody 256

response to Pg antigens has been considered beneficial for the control of Pg -mediated 257

periodontitis (Chen et al. 1991; Gibson & Genco 2001; Rajapakse et al. 2002). 258

Tf was detected in all subjects, but surprisingly the antibody response to Tf was 259

more prevalent in GAP than in LAP. Furthermore, clinical parameters of disease 260

severity were correlated to response to Tf in GAP. Little is known about the role of Tf 261

and its components on induction of periodontitis; partly due to its strict requirements for 262

culturing. Some putative virulence factors were identified in Tf such as PrtH (Saito et al. 263

1997), BspA (Sharma et al. 1998), and karilysin (Jusko et al. 2012). 264

The infection level and antibodies responses to Pg in GAP patients were 265

correlated in the present study confirming the influence of the bacterial level on IgG 266

response (Pussinen et al., 2011). However, the lack of correlation for Tf in both groups, 267

and for the three pathogens in LAP, may indicate that these organisms may escape 268

from host immune surveillance at certain circumstances. The antibodies titers for Tf 269

were low in both LAP and GAP subjects, despite high subgingival Tf levels. Previous 270

studies on the virulence potential of Tf had shown that the S –layer of the wall in this 271

species has modulatory properties (Settem et al. 2013), possibly indicating that a high 272

bacterial load, or colonization of multiple sites, is needed to induce an antibody 273

response. Pg has also some strategies to evade host defenses such as capsule 274

production (Vernal et al. 2009) and gingipain (Haruyama et al. 2009). Aa also 275

possesses production of cytolethal distending toxin with immune modulatory properties 276

(Fernandes et al. 2008; Shenker et al. 1999) and leukotoxins (Lally et al. 1994). Thus, 277

in LAP, it seems that yet unknown factors may hamper the IgG immune response to 278

pathogens, especially Tf. 279

The finding that both LAP and GAP patients exhibit high antibodies response to 280

periodontopathogens does not necessarily indicate that these antibodies confer any 281

protection to tissue destruction. Indeed, some reports showed that the so-called 282

prozone-like effect in which the administration of large amounts of specific antibody 283

had the paradoxical effect of being less protective than smaller amounts of antibodies, 284

as shown for S. pneumoniae (Goodner et al. 1935; Ramisse et al. 1996) and also for 285

Cryptococcus neoformans (Taborda et al. 2003). Moreover, long-term protective 286

immunity is dependent on the nature of the pathogen and the type of disease (Ahmed 287

& Gray, 1996). 288

Our data indicated that antibodies responses to Pg and Aa does not differ 289

between LAP and GAP. Furthermore, both AP groups presented a high response 290

against Aa serotypes b and c, but not to a. On the other hand, responses to Tf were 291

more frequently found in GAP than in LAP, although the levels and proportions of this 292

species in deep pockets did not differ between the two groups. 293

Pg, Tf and Aa were detected in the subgingival biofilm from all AP patients 294

independently of their IgG levels, therefore showing that the humoral immune response 295

was probably inefficient in removing these bacteria. It is important to emphasize that 296

whole bacterial cells were used and, therefore a greater serum IgG response was 297

expected to all their periodontopathogens components (Takahashi et al. 2001; Sugi et 298

al. 2011). One could suggest that host defense evasion mechanisms may also explain 299

this fact (Vincents et al. 2011). 300

A moderate correlation between periodontopathogens (except for Aa) and 301

clinical parameters was observed in GAP and not in LAP. 302

Future studies should focus on other periodontal pathogens, as well as the 303

immune response to this complex microbiota in AP. Furthermore the relationship of 304

these findings to initiation and progression of AP cannot be determined due to the 305

cross-sectional nature of this study and longitudinal studies should evaluate the role of 306

antibodies in AP disease progression or remission. 307

308

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The Journal of Federation of American Societies for Experimental Biology 25, 3741-614 3750. 615 616 Vlachojannis, C., Dye, B. A., Herrera-Abreu, M., Pikdöken, L., Lerche-Sehm, J., Pretzl, 617 B., Celenti, R., Papapanou, P. N. (2010) Determinants of serum IgG responses to 618 periodontal bacteria in a nationally representative sample of US adults. Journal of 619 Clinical Periodontology 37, 685-696. 620 621 Wang, D., Kawashima, Y., Nagasawa, T., Takeuchi, Y., Kojima, T., Umeda, M., Oda, 622 S., Ishikawa, I. (2005) Elevated serum IgG titer and avidity to Actinobacillus 623 actinomycetemcomitans serotype c in Japanese periodontitis patients. Oral 624 Microbiology and Immunology 20, 172-179. 625 626 Yoshimura, F., Sugano, T., Kawanami, M., Kato, H., Suzuki, T. (1987) Detection of 627 specific antibodies against fimbriae and membrane proteins from the oral anaerobe 628 Bacteroides gingivalis in patients with periodontal diseases. Microbiology and 629 Immunology 31, 935-941. 630 631 632 633 Acknowledgements: the authors thank João Paulo Ribeiro for collecting blood from 634

patients. 635

636

Table and figure legends: 637

Figure 1: Mean, SD, maximum and minimal values for PD (probing depth), CAL 638

(Clinical attachment level) and BoP (bleeding on probing) in GAP, LAP and healthy 639

groups. *** = p < 0.0001 (Kruskal-Wallis Test with Dunn´s multiple comparisons) 640

641

Figure 2: % (mean and SD) of the number of copies of the 16SrRNA gene of 642

A.actinomycetemcomitans (Aa), P. gingivalis (Pg) and T. forsythia in relation to the 643

total bacteria count in GAP, LAP and healthy groups. * Kruskal-Wallis Test and Dunn's 644

Multiple Comparison Test significant differences (p < 0.05). 645

646

Figure 3: Mean, SD, maximum and minimal O.D. values obtained in ELISA against 647

A.actinomycetemcomitans (Aa) serotypes a, b and c (1:10,000 dilution), P. gingivalis 648

(Pg) (1:10,000 dilution) and T. forsythia (Tf) (1:500 dilution) for GAP, LAP and healthy 649

groups. The number of individuals showing the response to each of the antigens in 650

each category is shown in parenthesis.* Kruskal-Wallis Test and Dunn's Multiple 651

Comparison Test significant differences (p < 0.05). 652

653

Figure 4: Distribution of subjects according to infection level of each studied 654

microorganism and IgG serum level against Aa serotype c (A), Pg (B) and Tf (C) in 655

GAP and LAP groups. 656

Table 1: Age (mean + SD) and other demographic data, percentage of sites (mean + 657

SD) with bleeding and different PD and mean CAL for healthy individuals and GAP and 658

LAP patients. 659

660

Table 2: raw data for each subject of GAP, LAP and healthy groups (microbiological 661

and IgG levels for each microorganism studied). 662