Anti-Basal Ganglia Antibodies and Streptococcal Infection in ADHD

Abstract

Objective: Group A Streptococcus has been associated with ADHD, tic disorders (TD), and obsessive–compulsive disorder (OCD) through anti-basal ganglia antibodies (ABGA). Method: We investigated the association between ABGA and streptococcal exposure with behavioral, motor, and cognitive measures in 38 children with ADHD not comorbid to OCD or TD (nc-ADHD) and in 38 healthy children. An additional group of 15 children with TD and/or OCD was examined. Results: ABGA titers were present in 3% of nc-ADHD patients and controls but in 27% of TD and/or OCD patients. Evidence of streptococcal exposure was similar between ADHD patients and controls living in the same urban area. Behavioral, motor, and cognitive measures were not associated with anti-streptococcal antibodies. Conclusion: ABGA do not distinguish nc-ADHD from controls. The differences in the frequency of streptococcal exposure in previous studies are determined by the dynamic nature of the infection rather than the behavioral phenotype of ADHD.

Keywords

anti-neuronal antibodies PANDAS post-streptococcal neuropsychiatric disorder obsessive–compulsive disorder tic disorder

Introduction

A variety of psychiatric and movement disorders are thought to be precipitated by streptococcal infections (Dale et al., 2004; Kiessling, Marcotte, & Culpepper, 1993; Swedo et al., 1989). The paradigmatic post-streptococcal entity is Sydenham’s chorea (SC), which frequently associates tic disorder (TD), obsessive–compulsive disorder (OCD), and ADHD that can precede the onset of chorea (Mercadante et al., 2000; Swedo et al., 1989). This finding led many to believe that the acute onset of neuropsychiatric symptoms, in the absence of chorea, might represent a forme frustre of SC in children with pharyngeal group A streptococcal (GAS) infections (i.e., Streptococcus pyogenes; Swedo, 1994). Consequently, PANDAS (Pediatric Autoimmune Neuropsychiatric Disorder Associated With Streptococcal infection) was described. In PANDAS patients, chorea was absent and TD and OCD were associated frequently with ADHD symptoms, choreiform movements, emotional lability, anxiety, and depression (Swedo et al., 1998).

ADHD is a condition mainly explained by a genetic predisposition, but environmental factors are also contributing. A dysfunction in fronto-striatal circuits, which control motor, cognitive, and emotional skills, is recognized in ADHD, as in TD or Tourette’s syndrome (TS; Biederman & Faraone, 2005; Millichap, 2008). One possible mechanism of basal ganglia dysfunction could be the production of autoantibodies against basal ganglia (anti-basal ganglia antibodies [ABGA]) through a molecular mimicking mechanism after GAS infection; Kiessling et al., 1993; Swedo, 1994). In fact, ABGA have been found in patients with SC (Church et al., 2002), PANDAS, or TS (Hallett, Harling-Berg, Knopf, Stopa, & Kiessling, 2000; Pavone et al., 2004), although others obtained negative findings (Morer et al., 2008; Singer, Hong, Yoon, & Williams, 2005). The occurrence of GAS infections and ABGA has been explored in patients with ADHD comorbid or not to TD or OCD, with differing results (Kiessling et al., 1993; Kiessling, Marcotte, & Culpepper, 1994; Peterson et al., 2000; Sanchez-Carpintero, Aguilera-Albesa, Crespo, Villoslada, & Narbona, 2009; Toto et al., 2012).

The purpose of this case-control study was to investigate the frequency of GAS infection and the presence of ABGA in nc-ADHD pediatric patients compared with a group of matched healthy children, and correlate the findings with behavioral, emotional, fine motor speed, and cognitive measures in both groups.

Method

A total of 91 children participated in the study. The matched samples consisted of 38 children with a primary diagnosis of ADHD, recruited consecutively from our outpatient pediatric neurology clinic without knowledge of previous GAS infection, and 38 healthy control children, matched by age and gender to the children with ADHD, recruited from their well-child care visits. Both groups were also matched by season of sample collection to limit the influence of outbursts of GAS infections (Shulman et al., 2004). An additional group of 15 pediatric patients with TD, OCD, and/or TS were recruited. Two models of informed consent were designed. Children gave assent to participate in the study after reading an adapted text with study information. Parents gave written consent after reading the standard model. The ethics committee of the Hospital approved the study.

Ascertainment of nc-ADHD Diagnosis

Patients were diagnosed with ADHD following Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR; American Psychiatric Association [APA], 2000) criteria and were classified according to the three subtypes of ADHD. A clinical evaluation of the child was required for diagnosis. Data regarding frequency and intensity of ADHD core symptoms were obtained from parents through the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; APA, 1994) Rating Scale questionnaire (DuPaul, Power, Anastopoulos, & Reid, 1998). Information from teachers was obtained in both groups through a short version of the Conners’ teacher rating scale (Escalas para la evaluación del trastorno por déficit de atención e hiperactividad [EDAH]) validated for the Spanish population (Farré & Narbona, 2003). These behavioral measures were recorded at the time of diagnosis and also at the time of study entry. Patients were excluded if they presented with OCD or TD, any neurological illness or psychiatric disorder not related to ADHD, or full-scale intelligence quotient (IQ) < 85 as measured by the Wechsler Intelligence Scale for Children–Revisited (WISC-R; 3rd ed.; Wechsler Intelligence Scale for Children–Revised; Spanish version, 1997). DSM-IV-TR diagnostic criteria were applied to exclude TD and OCD. Control participants were excluded if they fulfilled diagnostic criteria for ADHD, had family history of ADHD, IQ < 85, or any neurological or psychiatric disorder. Data on risk factors for developing ADHD were recorded including family history of ADHD, prenatal and perinatal adverse events or exposure to tobacco during pregnancy (Biederman & Faraone, 2005; Millichap, 2008). Symptoms of anxiety and depression were explored using Spanish standardized self-questionnaires: Multi-Anxiety Symptoms Scale (MASC) for anxiety symptoms (March, Parker, Sullivan, Stallings, & Conners, 1997) and Child Depression Inventory (CDI; Kovacs, 1992).

Cognitive and Fine Motor Speed Measures

A comprehensive battery of cognitive variables was included in the evaluation of ADHD patients and matched controls, to provide additional neuropsychological parameters to describe the differences between groups. We were also searching for a cognitive marker that could be associated with evidence of GAS infection and ABGA positivity. Standardized tests used for cognitive measures included selective attention (Differences Perception Test [DPT], Sky Search Attention Score of Test of Everyday Attention for Children [TEA-Ch]; Crespo-Eguílaz, Narbona, Peralta, & Repáraz, 2006; Manly, Robertson, Anderson, & Nimmo-Smith, 1999), sustained attention (DPT and Conners’ Continuous Performance Test [CPT]; Conners, 1995), impulsiveness control (DPT and CPT), interference control (Stroop; Golden, 2001), and planning (mazes; Wechsler, 1997). Fine motor speed was evaluated using Pediatric Assessment of Neurological Soft Signs (PANESS) that is expressed in seconds to perform 20 consecutive movements (Denckla, 1985). We also included values of WISC-R test subscales in the statistical analysis between groups. Methylphenidate treatment was stopped 3 days before the evaluation.

Definition of Streptococcal Infection

Throat swabs and blood samples were collected at the time of the study entry. The presence of GAS in the throat was demonstrated by blood-agar culture and bacitracin susceptibility test. A positive culture might represent a carrier status, so evidence of colonization/infection by GAS was ascertained if the culture was positive plus at least one titer elevations: anti-streptolysin O (ASO) or anti-deoxyribonuclease B (anti-DNAseB). Upper limit of normal (ULN) value was used to declare an antibody titer elevated, as it is useful in a case-control study with single-point-in-time measures, when acute and convalescent sera are not available. The ULN was defined as that titer exceeded by 20% of our healthy controls (Shet & Kaplan, 2002). Their ULN20 values were 320 IU/mL for ASO and 400 IU/mL for anti-DNAseB. They were established using standardized Dade Behring nephelometry for ASO and hemolysin inhibition for anti-DNAseB. In the absence of GAS in the throat, two titer elevations were required as evidence of recent infection. The combination of two antibodies is reported as highly sensitive and specific for identifying post-GAS disease. Data on the history of past infections or recent antibiotic treatment were collected in both groups to control other factors that can influence GAS immune response besides age and season of the year (Shet & Kaplan, 2002).

Anti-Basal Ganglia Autoantibodies

We used the semi-quantitative enzyme-linked immunosorbent assay (ELISA) to measure ABGA titers in serum samples, following the protocol by Church et al (2002). The sensitivity of ABGA ELISA was 95% in acute SC patients and 56% in chronic SC patients. The specificity was 93%, similar to that found with indirect immunofluorescence or Western immunoblotting (Church et al., 2002). Our Brain Bank provided human samples of caudate, putamen, and globus pallidus from participants without any evidence of neurological disease. The titers of ABGA in serum were considered positive if ELISA absorbance value was more than two standard deviations (SDs) above the mean of healthy controls. All samples were analyzed at the same time.

Participants With TD and/or OCD

An additional group of pediatric patients with TD, OCD, and/or TS, diagnosed with DSM-IV-TR criteria, was recruited. We measured evidence of GAS infection and titers of ABGA as described above, to support the same ABGA methodology used in the matched groups. This group of participants was not matched by age, gender, or season of recruitment with the other two groups.

Data Analysis

Descriptive statistics were explored for study variables. Group differences were examined with χ² test, Student’s t test, Wilcoxon’s test, or Mann–Whitney U test when needed. Clinical variables and antibody titers were correlated with Spearman test. SPSS 20.0 version was used for the analysis of data. A p value <.05 was considered statistically significant. Odds ratio (OR) was calculated with χ² test.

Results

The participants’ demographics are presented in Table 1. Fifteen out of 38 patients, already diagnosed as having ADHD at the time of study entry, were under methylphenidate treatment (40%), and it was stopped 3 days before the cognitive evaluation. The other 23 patients received standard therapy for ADHD after their inclusion in the study. A history of past infections and recent antibiotic treatment in both groups is shown in Table 2. The behavioral, emotional, motor, and cognitive features in ADHD patients and matched controls are provided in Table 3. Both groups differed in IQ but were all within the normal range.

Table 1.

Participant Demographics by Group.

	ADHD (n = 38)	Control participants (n = 38)
	n (%)	n (%)
Age^a	10.02 ± 2.12 years (6.4-14.0)	9.92 ± 2.11 years (6.5-13.9)
Gender (male:female)	9:1	9:1
Season of sample collection (n), Winter/Spring/Summer/Fall	9/14/10/5	9/14/10/5
Time of study entry after ADHD diagnosis
At diagnosis	23 (61)	0
During first year	7 (18)	0
Between 1-8 years	8 (21)	0
Subtypes of ADHD
Inattentive	17 (45)	0
Combined	20 (52)	0
Hyperactive	1 (3)	0
Familial history for ADHD	23 (61)	0
Psychosocial deprivation	2 (5)	0
Prematurity	1 (3)	0
Intrauterine growth retardation	2 (5)	0
Smoking during pregnancy^b	11 (29)	6 (16)
Comorbidity
Learning disorder	14 (37)	0
Anxiety	3 (8)	0
Oppositional-defiance disorder	2 (5)	0
Depression	1 (3)	0
Eating disorder	1 (3)	0
TD or OCD	0	0

p = .300, Student’s t test. Values are expressed in mean ± SD (range). TD = tic disorders; OCD = obsessive–compulsive disorder.

p = .169, χ² test.

Table 2.

Demographics, Throat Swab Culture, and Antibodies Titer Assessments by Group.

	ADHD (n = 38)	Controls (n = 38)	p ^a
	n (%)	n (%)	p ^a
Any recent infection	7 (18)	4 (10)	.516
Recent antibiotic treatment	3 (8)	3 (8)	1.000
History of GAS infections	7 (18)	4 (10)	.516
Positive swab throat culture for GAS	8 (21)	1 (3)	.039
Elevated ASO	23 (60)	19 (50)	.356
Elevated anti-DNAseB	23 (60)	19 (50)	.356
No titer elevations	10 (26)	11 (29)	.798
One titer elevations	10 (26)	16 (42)	.147
Two titer elevations	18 (47)	11 (29)	.098
Recent GAS infection^b	21 (55)	12 (32)	.037
ASO (IU/mL)^c	279 (119-325)	240 (112-294)	.421
Anti-DNAse B (IU/mL)^c	497 (300-600)	376 (200-400)	.117
ABGA positivity	1 (3)	1 (3)	1.000
ABGA (absorbance)^c	0.095 (0.063-0.10)	0.080 (0.056-0.094)	.635

Note. GAS = group A Streptococcus; ASO = anti-streptolysin O; anti-DNAseB = anti-deoxyribonuclease B; ABGA = anti-basal ganglia antibodies.

A p value <.05 was considered significant, χ² test.

Recent GAS infection was defined by two titer elevations or positive swab throat culture plus at least one titer elevations.

Antibody titers are expressed in median (interquartilic range). A p value was obtained by Wilcoxon’s test.

Table 3.

Behavioral, Emotional, Fine Motor Speed, and Cognitive Variables Results by Group.

	ADHD				Controls				ADHD vs. controls
	Total	GAS+	GAS−	GAS+ vs. GAS−	Total	GAS+	GAS−	GAS+ vs. GAS−	ADHD vs. controls
Participants enrolled (n)	38	21	17	p ^a	38	12	26	p ^a	p ^b
Behavioral
DSM-IV-RS inattention score	15 (11)	15 (13)	15 (12)	.339	1 (2)	2 (1)	1 (2)	.155	<.001
DSM-IV-RS hyperactivity/impulsivity score	6 (13)	7 (14)	6 (15)	.624	1 (4)	1 (3)	1 (4)	.631	<.001
EDAH inattention score	8 (6)	9 (6)	8 (6)	.908	1 (3)	2 (3)	0 (2)	.087	<.001
EDAH hyperactivity score	6 (7)	7 (5)	5 (8)	.488	1 (4)	2 (4)	1 (4)	.485	<.001
EDAH conduct disorder score	7 (8)	9 (8)	4 (11)	.343	1 (2)	1 (3)	1 (2)	.218	<.001
Emotional
Harm avoidance (MASC)	12 (8)	9 (9)	14 (9)	.120	8 (11)	7 (13)	7 (12)	.270	.009
Social anxiety (MASC)	10 (6)	10 (9)	11 (6)	.732	4 (9)	3 (11)	4 (7)	.254	.012
Separation anxiety (MASC)	9 (7)	9 (8)	9 (8)	.656	4 (4)	4 (6)	3 (5)	.196	.001
Physical symptoms (MASC)	9 (7)	7 (7)	9 (9)	.128	3 (4)	2 (3)	3 (4)	.467	<.001
Dysphoria (CDI)	50 (8)	50 (13)	50 (8)	.350	58 (5)	58 (3)	58 (2)	.509	<.001
Self-esteem (CDI)	49 (9)	48 (15)	49 (10)	.151	62 (10)	61 (12)	64 (11)	.409	<.001
Fine motor speed
Dominant hand tap (PANESS)	4.98 (1.39)	5.13 (1.17)	4.87 (2.05)	.538	4.38 (1.29)	4.16 (1.4)	4.59 (1.52)	.195	.007
Dominant foot tap (PANESS)	6.78 (2.86)	6.67 (2.9)	6.78 (2.85)	.799	5.85 (1.96)	5.60 (1.57)	6.06 (1.8)	.283	.001
WISC-R scales^c
Full-scale IQ	105 ± 10 (41)	104 ± 10 (36)	105 ± 9 (40)	.538	117 ± 15 (53)	122 ± 9 (32)	114 ± 16 (53)	.073	.001
Verbal-scale IQ	104 ± 11 (43)	103 ± 12 (43)	106 ± 10 (37)	.447	118 ± 16 (63)	122 ± 11 (44)	115 ± 18 (63)	.196	.001
Performance-scale IQ	104 ± 11 (43)	106 ± 12 (43)	103 ± 9 (36)	.600	111 ± 11 (41)	116 ± 7 (25)	109 ± 12 (41)	.038	.020
Spatial ability (block design)	10 ± 3 (10)	10 ± 3 (10)	10 ± 3 (10)	.521	12 ± 3 (11)	12 ± 2 (6)	12 ± 3 (11)	.569	.002
Comprehension	10 ± 3 (11)	10 ± 3 (11)	10 ± 3 (10)	.949	13 ± 4 (16)	13 ± 3 (10)	12 ± 4 (16)	.502	.001
Visuo-motor speed (coding)	9 ± 3 (12)	9 ± 3 (9)	9 ± 3 (13)	.521	11 ± 3 (11)	12 ± 3 (11)	11 ± 2 (9)	.687	.001
Arithmetic	10 (2)	10 (3)	11 (2)	.158	13 (4)	13 (2)	13 (4)	.359	.002
Planning (mazes)	50 (13)	50 (10)	50 (10)	.603	60 (13)	62 (5)	55 (15)	.038	<.001
Attention/impulsiveness tests
Selective attention (TEA-Ch)^c	37 ± 12 (55)	38 ± 10 (35)	37 ± 14 (55)	.841	46 ± 11 (45)	45 ± 14 (45)	46 ± 9 (30)	.700	.017
Sustained attention (DPT)	51 (16)	50 (10)	54 (14)	.940	57 (10)	60 (7)	55 (15)	.129	.005
Sustained attention (CPT)^c	41 ± 11 (40)	38 ± 9 (28)	44 ± 12 (40)	.072	47 ± 10 (41)	49 ± 10 (30)	47 ± 10 (39)	.068	.008
Impulsiveness control (DPT)	50 (14)	46 (16)	51 (8)	.599	57 (5)	57 (2)	56 (7)	.035	<.001
Interference control (stroop)^c	47 ± 5 (25)	47 ± 6 (25)	43 ± 5 (15)	.356	53 ± 8 (36)	54 ± 9 (26)	53 ± 7 (32)	.860	<.001

Note. Values are expressed in median (interquartilic range). Data are presented in age/gender-corrected T-scores for CDI and attention/impulsiveness tests (M = 50; SD = 10), WISC-R scales (M = 100; SD = 15), and WISC-R subscales (M = 10; SD = 2). MASC and PANESS data are presented in direct scores. GAS+/− = evidence of GAS infection positive/negative; GAS = group A streptococcal; DSM-IV-RS = Diagnostic and Statistical Manual of Mental Disorders (4th ed.) Rating Scale; EDAH = Conner’s rating scale, Spanish version; MASC = Multi-Anxiety Symptoms Scale; CDI = Child Depression Inventory; PANESS = Pediatric Assessment of Neurological Soft Signs; WISC-R = Wechsler International Scale for Children–Revisited; IQ = intelligence quotient; TEA-Ch = Test of Everyday Attention for Children; DPT = Differences Perception Test; CPT = Conners’ Continuous Performance Test.

A p value <.05 was considered significant, Mann–Whitney U test.

A p value <.05 was considered significant, Wilcoxon’s test.

Values are expressed in mean ± SD (range). A p value <.05 was considered significant, Student’s t test.

In this study, there were significantly more positive throat cultures for GAS in the ADHD patients than in the controls (OR = 9.86, 95% confidence interval [CI] = [1.16, 83.35], χ² test), despite all of them being asymptomatic at the time of sample collection (Table 2). Evidence of recent GAS infection was also more common in children with ADHD than in controls (OR = 2.67, 95% CI = [1.04, 6.82]), but if only two titer elevations were considered, no statistical significance was reached (OR = 2.2, 95% CI = [0.85, 5.69]). We further analyzed why the presence of GAS was more frequently found in the throat of patients compared with controls. We searched for other environmental conditions that could act as risk factors for exposure to GAS, including crowding and geographic location (Shet & Kaplan, 2002; Shulman et al., 2004). We found that all healthy controls were living in the same medium-class urban area, but patients with nc-ADHD did not, as our hospital is a national referral center. Eighteen out of 38 patients with nc-ADHD came from different regions. Of these, 6 (33%) had positive throat cultures compared with none of their matched controls (p = .020, OR = 1.42, 95% CI = [1.07, 1.90]). Of the 20 nc-ADHD patients who were living in the same urban area as controls, 2 (10%) had positive throat cultures compared with 1 control (5%). Therefore, for individuals living in the same urban area, no differences between groups could be ascertained.

ABGA levels were not significantly increased in ADHD participants compared with controls (OR = 0.94, 95% CI = [0.57, 15.71]). Only one child with ADHD and one control had positive ABGA titers (Table 2). Of these two children with positive ABGA, only the control participant had evidence of recent GAS infection. We found no significant association of behavioral and cognitive variables with evidence of GAS infection, throat swab culture, or the presence of antibodies (Table 3). We also did not find any correlation of these tested variables with ASO, anti-DNAseB, or ABGA titers (data not shown).

The non-matched group of patients with TD, OCD, or TS included 15 children: 2 patients with chronic TD, 8 with acute recurrent tics, 3 with TS, and 2 with OCD alone. Mean age was 7.5 years ± 3 SD, range (2.5-13.9), mostly males (4:1). ADHD was present in 3 participants (20%). We found that 11 of 15 (73%) patients in this group had elevations of ASO titers, and 5 of 15 (33%) had elevations of both ASO and anti-DNAseB. GAS was present in the throat swab culture in 2 of 15 (13%) in association with at least one titer elevations. The presence of ABGA was detected in four participants (27%) with a mean absorbance value of 0.107 ± 0.045 SD (0.058-0.189). All patients with positive ABGA in this group had also evidence of recent GAS infection. They were suffering from acute recurrent motor tics in two cases, chronic TD in one case and OCD alone in one case. None with positive ABGA had ADHD comorbidity.

Discussion

This case-control study does not support the hypothesis of autoimmunity against basal ganglia in nc-ADHD patients. The frequency of positive ABGA in children with nc-ADHD did not differ from that in healthy controls independent of recent GAS infection. Our results are reinforced by the design of the study, which included behavioral standardized measures following DSM-IV diagnostic criteria for ADHD and also cognitive, emotional, and fine motor speed variables that clearly separated both matched groups of participants. We also correlated ABGA absorbance values with clinical scores in nc-ADHD patients looking for any relationship not detected by the cut-off values of ABGA established with the control sample, but there were no significant correlations. Nonetheless, our results regarding ABGA are supported by one single measuring method, so positive findings with other methodology cannot be ruled out. The frequency of ABGA in our nc-ADHD patients (3%) was similar to that found in control samples of other studies (0%-5%), with the same semi-quantitative ELISA method (Church et al., 2002; Dale et al., 2004; Pavone et al., 2004; Sanchez-Carpintero et al., 2009; Toto et al., 2012). Conversely, we were able to detect ABGA positivity in patients with acute onset of tics or OCD (27%), comparable with other studies (Pavone et al., 2004). These patients with positive ABGA had also some evidence of recent GAS infection, including improvement of symptoms following penicillin treatment in one patient. These findings support the reliability of our technique.

Contrary to us, some authors have found positive ABGA together with high titers of anti-streptococcal antibodies in nc-ADHD participants. Kiessling et al. reported 37% of ABGA positivity in 19 nc-ADHD patients compared with 63% in 19 ADHD comorbid with TD, OCD, or TS patients, with the method of immunofluorescence (Kiessling et al., 1994). None of the nc-ADHD had both ASO and anti-DNAseB titer elevations compared with 22% of comorbid ADHD cases. The different rate of ABGA positivity of Kiessling et al. study and ours could be explained because of the different methodology used to measure ABGA.

More recently, Toto et al. (2012) studied the presence of ABGA in 20 nc-ADHD patients. They found 30% of ABGA positivity in nc-ADHD participants compared with 5% of controls, with the method by Church et al. (2002). Of these patients with positive ABGA, 50% also had high titers of ASO compared with 15% of controls, but they did not study anti-DNAseB titers. In our matched groups, two anti-streptococcal titer elevations were not significantly different between ADHD patients and controls. In other studies, ABGA is usually associated to GAS infection (Church et al., 2002; Dale et al., 2004; Kiessling et al., 1993, 1994; Pavone et al., 2004). The different ABGA positivity of Toto et al. study compared with our findings could be explained by the fact that their ADHD group had more frequent ASO elevations. This could indicate that the group with ADHD had more streptococcal infections. However, given the fact that the groups were not matched by season of sample collection, it is not possible to know whether streptococcal infections—and therefore ABGA positivity—were related to ADHD, or to the presence of an outburst of GAS infections. We did not find more evidence of GAS infections in our ADHD group by detecting elevations of two different antibodies, and checking the presence of GAS in the throat. However, the dynamic nature of GAS has to be taken into consideration in the design, especially when samples are collected at a single point in time. In this regard, we had one limitation because our institution is a referral national center and we did not control geographical variation of GAS outbursts. To overcome this limitation, we compared 20 patients and 20 controls recruited from the same urban area in the same season. Still we did not find more evidence of GAS infections. In addition, past history did not suggest that unspecific or documented GAS infections were more frequent in ADHD patients than in controls.

In our nc-ADHD group, frequencies of inherited and acquired risk factors were in line with previous studies (Biederman & Faraone, 2005; Millichap, 2008). ADHD is defined as a chronic condition, with a complex gene–environment interaction implied in the etiopathogenesis. Estimated heritability rates are about 60% to 75% but several risk pathways may contribute to a similar phenotype (Langley et al., 2009). Apart from inherited and non-inherited genetic factors, the most reliable contributors described in ADHD include low birth weight, prematurity, and severe early social adversity, each one present in some participants of our sample. Most of them are risk factors that may interfere with early development of neural networks involved in ADHD (Cortese et al., 2013).

ADHD seems to be the common end of diverse risk pathways, as it is represented in our non-selected sample. The theory of complex gene–environmental interactions in neurodevelopmental disorders, such as TS or TOC, is supported in some cases by the evidence of the role of autoimmunity as an environmental contributing factor (Madhusudan & Cavanna, 2013; Pearlman, Vora, Marquis, Najjar, & Dudley, 2014). However, autoimmunity related to GAS does not seem to play a role in nc-ADHD, when our results are taken into account. Inconsistent results have been obtained also in other neurodevelopmental disorders, where the use of different methodologies appears to yield results in contrast to neuroimmunological findings (Martino et al., 2008). This should encourage the search for more sophisticated etiopathogenetic models, which can capture the complexity of the clinical presentations of neurodevelopmental disorders (Cavanna et al., 2009).

The ADHD phenotype currently accepted in international classifications is in most cases different from that described in PANDAS, in which clinical deterioration typically occurs overnight and rapid improvement is observed after antibiotic treatment (Murphy, Storch, Lewin, Edge, & Goodman, 2012). Moreover, ADHD according to DSM-IV diagnosis is also different from what has been described in autoantibody-associated central nervous system disorders, in which onset is acute or subacute, and is followed by a slower evolution with a remission of the symptoms over weeks after treatment (Titulaer et al., 2013).

Searching for ABGA and evidence of GAS infection in ADHD has found conflicting results (Kiessling et al., 1993, 1994; Peterson et al., 2000; Sanchez-Carpintero et al., 2009; Toto et al., 2012), and our case-control study, with a detailed methodology to differentiate patients and healthy controls, has contributed with negative findings. Some evidence of a temporal relationship was reported in a study of 693 schoolchildren, in which data on GAS infection and ADHD behavioral measures were collected monthly over 8 months. Children with recurrent positive throat cultures presented higher scores of ADHD symptoms (Murphy et al., 2007). The authors concluded that GAS was associated with an increased risk of ADHD. Conversely, a higher frequency of GAS in the throat of ADHD patients could be interpreted as an epiphenomenon. It is conceivable that children with hyperactivity and impulsivity are more prone to close physical contact with their peers and, consequently, more susceptible to GAS infections. We sought an association between behavioral, emotional, and cognitive measure scores, and antibodies titers and throat swab culture results, but no significant association was found, despite the fact that our nc-ADHD patients, as expected, had worse scores than matched healthy controls.

In conclusion, our case-control study does not support the hypothesis that nc-ADHD is associated with post-streptococcal autoimmune phenomena through autoantibodies directed against basal ganglia, although other methodologies could ascertain different autoimmune processes in some children with ADHD. These results contribute to clinical assessment and practice of managing ADHD, focusing the disorder as a neurodevelopmental condition. In ADHD, an interaction of genetic and acquired factors is probably the cause in most cases. Environmental triggers in ADHD are intriguing but unknown, although additional controlled studies might shed light on this matter paving the way toward preventive measures and targeted therapies.

Footnotes

Acknowledgements

We thank Begoña Fernández, PhD, for laboratory technical support; Berta Ibáñez, PhD, and Olivia Busto, MD, for statistical analysis; and Luis Seijo, MD, for English proofread and critical review of this manuscript.

Authors’ Note

All human studies have been approved by the appropriate ethics committee and have therefore been performed in accordance with the ethical standards. All persons gave their informed consent prior to their inclusion in the study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Fondo de Investigación Sanitaria (FIS), Instituto Carlos III, Ministry of Health, Spain (PI041987); the Research Plan of the University of Navarra (PIUNA 13138301); and Spanish Paediatric Neurology Society (SENEP) grant.

Author Biographies

Sergio Aguilera-Albesa, MD, PhD, is a Pediatric Neurologist in Navarra Health Service, Spain. He earned his PhD at University of Navarra with the present study. His research interests are on detection and intervention of cognitive and behavioral problems in children with neurodevelopmental disorders, autoimmune diseases, and neurodegenerative disorders affecting basal ganglia and cerebellum.

Nerea Crespo-Eguílaz, PhD, is an Educational Psychologist and Associate Professor in the University of Navarra, Spain. Her research focus is on detection of cognitive and behavioral problems in children with developmental coordination disorder and ADHD.

José Luis Del Pozo, MD, PhD, is an expert on Infectious Diseases and Associate Professor in the University of Navarra, Spain. He completed his Clinical Research Fellow in Mayo Clinic, Rochester, Minnesota, USA.

Pablo Villoslada, MD, PhD, is Director of the multiple sclerosis pathogenesis and therapeutics Group, IDIBAPS, Spain. He is also member of the Scientific Advisory Board of the International Society of Neuroimmunology.

Rocío Sánchez-Carpintero, MD, PhD, is a senior Pediatric Neurologist and Associate Professor in the University of Navarra, Spain. She completed her Clinical Research Fellow in Great Ormond Street Hospital, London, UK. Her research focus is on cognitive abilities in children with epilepsy and Dravet syndrome.

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