Diagnostic Assessments

All participants underwent diagnostic assessments including the Structured Clinical Interview for DSM-IV Axis-I disorders (SCID-I (First et al, 1997)) and the Borderline Section of the International Personality Disorder Examination (IPDE (Loranger, 1999)). In addition, the Standard Progressive Matrices Test (Raven et al, 2003) and a German vocabulary intelligence test (Mehrfach-Wortschatz-Intelligenz-Test, Version B (Lehrl, 2005) were completed by all participants to estimate their intelligence. Inclusion criteria for the BPD group were at least five DSM-IV criteria for BPD (APA, 2000). For exclusion of ADHD diagnosis in BPD patients, three different measurements were applied: (1) the short version of the Wender Utah Rating Scale (WURS-k (Retz-Junginger et al, 2003)) to assess childhood ADHD symptoms; (2) the Connor Adult ADHD Rating Scale (Conners et al, 2002) was used, based on the DSM-IV criteria for ADHD (APA, 2000); (3) the Wender-Reimherr Adult Attention Deficit Disorder Scale (Rösler et al, 2008), which is a clinical interview conceptualized for adult ADHD. For the ADHD group, the same measurements were applied and BPD diagnosis was excluded via the IPDE. Substance use was assessed with the SCID-I (First et al, 1997). Furthermore, a urine drug screening was performed on the day of the MR investigation. No physical examinations were performed on the participants in the study. Medical and neurological conditions were gathered before participation in a detailed medical anamnesis. Serious physical and neurological diseases were exclusion criteria in this study. First-degree relatives of patients and controls were not necessarily free of psychiatric disorders.

Further clinical variables were assessed by self-reported measures concerning borderline symptom severity (Borderline Symptom List-23, BSL-23 (Bohus et al, 2007)), childhood trauma history (Childhood Trauma Questionnaire, CTQ, (Bernstein et al, 2003)), trait dissociation (Dissociative Experience Scale, DES (Bernstein and Putnam, 1986)), the State-Trait Anxiety Inventory, STAI (Spielberger et al, 1983), and depression (Bernstein and Putnam, 1986)) Beck Depression Inventory II (Beck et al, 1995).

All measurements and interviews were conducted by well-trained clinical psychologists and psychiatrists. Exclusion criteria for all participants were psychotropic medication within 2 weeks prior to the study, significant somatic disorders, pregnancy, and mental deficiency or developmental disorders. Patients were not generally free of medication. Some patients gradually reduced intake of their psychotropic medication (in consultation with their attending physician) and stopped intake 2 weeks before the study took place. Other patients were recruited while consulting a physician to start medication and were investigated before they started with pharmacotherapy. Lifetime history of any co-occurring psychiatric disorder was an exclusion criterion for HC. BPD and ADHD patients were not included if they had a lifetime history of bipolar affective disorder, psychotic disorder, current suicidal crisis, or substance abuse within the last 2 months.

Assessment of Impulsivity and Aggression

For impulsivity and aggression, the following self-rating scales were applied: the Barratt Impulsiveness Scale (BIS-11) (Preuss et al, 2008), the State-Trait Anger Expression Inventory (STAXI) (Schwenkmezger and Hodapp, 1991), and the Brown Goodwin Lifetime History of Aggression (BGLHA) (Brown et al, 1979). The BIS-11 consists of 30 items, which are answered on a four-point Likert scale (1=‘rarely/never’ to 4=‘always’) and can be divided into the subscales Motor Impulsiveness, Non-Planning Impulsiveness, and Attentional Impulsiveness. The BGLHA assesses different types of aggressive and antisocial behavior (ie, instances of fighting, temper tantrums, antisocial behavior involving the police), where each item is rated on a scale from 0–4, indicating the frequency of these events ranging from ‘never’ to ‘more than four times’. The trait version of the STAXI consists of 10 items assessing the disposition to experience anger. All items are rated on a four-point Likert scale ranging from 1 (almost never) to 4 (almost always). The BGLHA is a measurement of past overt aggressive behavior in contrast to the STAXI, which measures the tendency to feel anger (which may or may not provoke aggressive behavior). As anxiety and anger are both high arousal, negatively valenced emotions, a strong relationship can be expected.

MR Spectroscopy

In vivo, single voxel 1H MRS was performed at a 3.0 T whole-body MR scanner with a 32 channel receive-only head coil (Siemens Magnetom TIM Trio). Two MRS voxels were acquired and both were placed on the ACC based on an isotropic 1 mm³ MPRAGE data set with reconstructed coronal and transverse planes aligned with the shape of the corpus callosum (see Figure 1). With a MEGA-PRESS sequence for GABA editing, a 40 × 30 × 20 mm³ voxel was acquired (TE=68 ms, TR=3 s, NEX=96on, 96 off) (Figure 1). The editing pulse (Gauss shape, 20.36 ms length, bandwidth (FWHM): 44 Hz) in the MEGA-PRESS sequence was switched between 1.9 and 1.5 ppm (second editing frequency 1.5 ppm) alternating every excitation. This editing scheme diminishes contamination by nearby MM resonances (Aufhaus et al, 2013; Henry et al, 2001: Aufhaus, 2013 #13421)

The glutamate signal was analyzed from a smaller and thus more exactly localized voxel of 15 × 30 × 12 mm³ acquired with a PRESS sequence in the ACC (TE=80 ms, TR=3 s, NEX=96 (Schubert et al, 2004)) owing to the higher concentration and thus better Signal to Noise Ratio for glutamate compared with GABA.

For quantification of the (in vivo) spectra, the GABA signals were analyzed using the jMRUI-software (Stefan et al, 2009). The MEGA-PRESS sequence includes an editing pulse mirrored at 1.7 ppm (1.9 ppm and 1.5 ppm). This editing scheme does not only suppress the MM signals but additionally results in a different spectral pattern for GABA compared with the pulse schemes without macromolecule suppression. The jMRUI procedure included zerofilling to 2048 points, slight apodization (4 Hz, Lorentzian shape), and HLSVD filtering of the residual water peak. Three peaks with Lorentzian shape were used to fit GABA.

For the other metabolites, LCModel (Provencher, 1993) was used with a simulated basis data set (based on Gamma routines) containing the following metabolites: alanine, aspartate, creatine and phosphocreatine (tCr), GABA, glucose, glutamine, glutamate, glycerol-phosphoryl-choline, phosphoryl-choline, myo-Inositol, lactate, N-acetylaspartate, N-acetylaspartylglutamate, scyllo-Inositol, and taurine. In addition, signals of macromolecules and lipids were directly simulated by LCModel. Glutamate was evaluated as a ratio to total creatine (Glu/tCr). In the edited GABA spectra, the tCr signal is edited out. As we have previously established a quantitation method for GABA (Aufhaus et al, 2013) based on phantom measurements including correction for the voxel’s tissue compartmentation (Weber-Fahr et al, 2002), quantitative values for GABA levels are reported. All spectra were of good quality and spectral fits had Cramer rao Lower Bounds below 20 for glutamate and GABA (no subject was excluded).

Impulsivity and Aggression

Both patient groups displayed elevated self-reported trait impulsivity (BIS total), anger (STAXI), aggression (BGLHA), depression scores (BDI), childhood trauma history (CTQ), and trait dissociation (DES) compared with HCs. As compared with BPD patients, ADHD patients reported higher impulsivity in all BIS-11 facets (non-planning, motor, and attentional impulsivity). No significant differences between patient groups were found in anger (STAXI) and aggression (BGLHA) scores (Table 1).

The aggression scores BGLHA and STAXI for the whole group (controlling for BPD and ADHD) are highly correlated (r=0.67; P<0.001), but only STAXI is significantly correlated with the anxiety score STAI. The impulsivity score BIS-11 total also yields a significant correlation with the STAI score (r=0.25; P<0.03), and shows a trend but no significant correlations with neither BGLHA (r=0.17; P=0.13) nor STAXI (r=0.21; P=0.06). The BDI depression score yields significant correlations with STAXI and STAI (r>0.35, P<0.003) but not with BIS-11 and BGLHA (r<0.12, P>0.3).

MR Spectroscopy

Neither GABA nor Glu/tCr was associated with either age (r<−0.17; P>0.14) or the voxel’s gray matter content expressed as the gray matter/brain matter (GM/BM) ratio (r<0.07; P>0.5), whereas the GM/BM ratio significantly decreased with age (r=−0.31; P=0.006). Thus, age and GM/BM were not used as covariates for the further group comparisons and correlations for GABA and Glu/tCr. In a general linear model, a significant group difference among HC, BPD, and ADHD was observed for GABA. Tukey’s post hoc test yielded that ADHD patients exhibit significantly lower GABA levels than controls (Table 1). The Glu/tCr ratio was not significantly different between groups (Table 1).

GABA, Glutamate, and Impulsivity

A significant positive partial correlation was observed between the BIS-11 total score and Glu/tCr, controlling for diagnosis with two binary variables. As expected, a significant negative partial correlation between BIS-11 total score and GABA (Table 3 & Figures 2a–d) was found. Although the inclusion of the anxiety and aggression scores as potential confounders in the partial correlation with Glu/tCr did not affect the significance, the negative correlation with GABA was reduced to a trend level (Table 3).

GABA, Glutamate, and Aggression

A significant negative partial correlation controlling for diagnosis with two binary variables between the BGLHA aggression score and GABA, but no positive correlation with Glu/tCr was found. Neither controlling for impulsivity, nor BDI nor STAI scores in a partial correlation explained the negative correlation of BGLHA with GABA significant (Table 3).

Explorative Analysis of the BSL Score and CAARS Scores in Relation to GABA and Glutamate Levels

The BSL score assessed in our study is significantly correlated with the aggression score (r=0.29, P=0.009) but not the BIS-11 impulsivity score (P=0.25). Accordingly, we observe a significant negative correlation of the BSL score with GABA (r=−0.25, P=0.03). The CAARS total scores assessed in our study are highly correlated with both the BIS-11 total scores (r=0.59, P<0.001) and the aggression scores BGLHA and STAXI (r>0.35, P<0.001). It further yields significant, equally directed correlations with Glu/tCr (r=0.40, P<0.001) and GABA (r=−0.27, P=0.02) as observed for the impulsivity and aggressions scores. Neither Glu/tCr (r=0.19, P=0.09) nor GABA (r=−0.19, P=0.10) yielded a significant association with the subscore hyperactivity. The partial correlations with the hyperactivity score used as a control variable still yielded significant results for impulsivity and Glu/tCr (r=−0.28, P=0.01) as well as for aggression and GABA (r=−0.23, P=0.05).

The study was supported by a grant from the German Research Foundation (DFG) to GE and CS (EN 361/12-1 SCHM 1526/13-1). MB is a consultant for AOK insurance company; he receives grants by the German Research Foundation (DFG), The Ministry of Research, Germany (BMBF), CS revceives grants from the DFG and BMBF, ES is an advisor for Medice, Eli Lilly, Shire and gives lectures for Eli Lilly, Medice.