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Altered excitatory and inhibitory neurotransmission has been implicated in autism spectrum disorder (ASD). Interventions using repetitive transcranial magnetic stimulation (rTMS) to enhance or inhibit cortical excitability are under study for various targets, though the mechanistic effects of rTMS have yet to be examined in ASD. Here, we examined whether an excitatory rTMS treatment course modulates glutamatergic (Glx) or γ-aminobutyric acid (GABA) metabolite levels in emerging adults with ASD. Twenty-eight participants with ASD and executive function impairment [23.3 ± 4.69 years; seven-female] underwent two magnetic resonance spectroscopy (MRS) scans of the left dorsolateral prefrontal cortex (DLPFC). MRS scans were acquired before and after participants with ASD were randomized to receive a 20-session course of active or sham rTMS to the DLPFC. Baseline MRS data was available for 19 typically developing controls [23.8 ± 4.47 years; six-female]. Metabolite levels for Glx and GABA+ were compared between ASD and control groups, at baseline, and metabolite level change, pre-to-post-rTMS treatment, was compared in ASD participants that underwent active vs. sham rTMS. Absolute change in Glx was greater in the active vs. sham-rTMS group [F(1,19) = 6.54, p = 0.02], though the absolute change in GABA+ did not differ between groups. We also examined how baseline metabolite levels related to pre/post-rTMS metabolite level change, in the active vs. sham groups. rTMS group moderated the relation between baseline Glx and pre-to-post-rTMS Glx change, such that baseline Glx predicted Glx change in the active-rTMS group only [b = 1.52, SE = 0.32, t(18) = 4.74, p < 0.001]; Glx levels increased when baseline levels were lower, and decreased when baseline levels were higher. Our results indicate that an interventional course of excitatory rTMS to the DLPFC may modulate local Glx levels in emerging adults with ASD, and align with prior reports of glutamatergic alterations following rTMS. Interventional studies that track glutamatergic markers may provide mechanistic insights into the therapeutic potential of rTMS in ASD.Clinical Trial Registration:Clinicaltrials.gov (ID: NCT02311751), https://clinicaltrials.gov/ct2/show/NCT02311751?term=ameis&rank=1; NCT02311751.

Executive function task (EF) deficits are hypothesized to underlie difficulties with self-regulation. However, tasks assessing EF impairments have only been weakly correlated with rating scales that index self-regulation difficulties. A community sample of children and youth aged between 8 and 20 years old were assessed longitudinally. Growth curve analyses and correlations were conducted to better understand how these two types of measures relate to one another across development, as well as the impact of age-related variance. EF was assessed using the Stroop Task and Trail Making test and behavioral ratings of self-regulation were captured using the SWAN scale. EF task performance improved steeply until age 14–15, whereas the SWAN Scale showed small age-related decreases. EF task performance was moderately correlated with age among 8–13-year-olds and to a lesser extent among 14–20-year-olds. SWAN scores were not significantly related to age in either group. Correlations were similar in an ADHD “at-risk” subgroup. EF task performance and parent ratings of attention regulation have different developmental trajectories, which may partly explain why correlations are low to modest in these samples. In particular, age-related variance is an important methodological consideration with significant implications for the assessment of self-regulation in children and youth with ADHD.

Suicidality is increased in autism spectrum disorder (ASD), yet effective interventions are lacking. Developing biologically based approaches for preventing and treating suicidality in ASD hinges on the identification of biomarkers of suicidal ideation (SI). Here, we assessed magnetic resonance spectroscopy (MRS) markers of glutamatergic neurotransmission in ASD youth and young adults. Twenty-eight ASD participants (16–33 years) underwent 1H-MRS, and metabolites were quantified using LCModel. N-acetylaspartate (NAA), glutamate (Glu), and the NAA/Glu ratio from the left dorsolateral prefrontal cortex were compared between ASD SI+ (n = 13) and ASD SI− (n = 15) participants. We found that ASD SI+ participants had a higher NAA/Glu ratio compared ASD SI- participants. The NAA/Glu ratio also predicted SI and significantly discriminated between ASD SI+/SI− participants. All analyses including NAA and Glu alone were non-significant. Here, we provide preliminary evidence for the importance of NAA/Glu in ASD with SI, with implications for biomarker discovery. Further mechanistic research into risk and interventional approaches to address SI in ASD are needed.