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Fasoracetam in adolescents with ADHD and glutamatergic gene network variants disrupting mGluR neurotransmitter signaling

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The glutamatergic neurotransmitter system may play an important role in attention-deficit hyperactivity disorder (ADHD). This 5-week, open-label, single-blind, placebo-controlled study reports the safety, pharmacokinetics and responsiveness of the metabotropic glutamate receptor (mGluR) activator fasoracetam (NFC-1), in 30 adolescents, age 12-17 years with ADHD, harboring mutations in mGluR network genes. Mutation status was double-blinded. A single-dose pharmacokinetic profiling from 50-800 mg was followed by a single-blind placebo at week 1 and subsequent symptom-driven dose advancement up to 400 mg BID for 4 weeks. NFC-1 treatment resulted in significant improvement. Mean Clinical Global Impressions-Improvement (CGI-I) and Severity (CGI-S) scores were, respectively, 3.79 at baseline vs. 2.33 at week 5 (P < 0.001) and 4.83 at baseline vs. 3.86 at week 5 (P < 0.001). Parental Vanderbilt scores showed significant improvement for subjects with mGluR Tier 1 variants (P < 0.035). There were no differences in the incidence of adverse events between placebo week and weeks on active drug. The trial is registered at https://clinicaltrials.gov/ct2/show/study/NCT02286817 .
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ARTICLE
Fasoracetam in adolescents with ADHD and
glutamatergic gene network variants disrupting
mGluR neurotransmitter signaling
Josephine Elia1,2,3, Grace Ungal4, Charlly Kao5, Alexander Ambrosini6, Nilsa De Jesus-Rosario3, Lene Larsen3,
Rosetta Chiavacci5, Tiancheng Wang5, Christine Kurian2, Kanani Titchen1,2, Brian Sykes1,2, Sharon Hwang1,2,
Bhumi Kumar1,2, Jacqueline Potts2, Joshua Davis1,2, Jeffrey Malatack1, Emma Slattery2, Ganesh Moorthy7,
Athena Zuppa7, Andrew Weller3, Enda Byrne5, Yun R. Li5,8, Walter K. Kraft 2& Hakon Hakonarson5,7,9
The glutamatergic neurotransmitter system may play an important role in attention-decit
hyperactivity disorder (ADHD). This 5-week, open-label, single-blind, placebo-controlled
study reports the safety, pharmacokinetics and responsiveness of the metabotropic gluta-
mate receptor (mGluR) activator fasoracetam (NFC-1), in 30 adolescents, age 1217 years
with ADHD, harboring mutations in mGluR network genes. Mutation status was double-
blinded. A single-dose pharmacokinetic proling from 50800 mg was followed by a single-
blind placebo at week 1 and subsequent symptom-driven dose advancement up to 400 mg
BID for 4 weeks. NFC-1 treatment resulted in signicant improvement. Mean Clinical Global
Impressions-Improvement (CGI-I) and Severity (CGI-S) scores were, respectively, 3.79 at
baseline vs. 2.33 at week 5 (P<0.001) and 4.83 at baseline vs. 3.86 at week 5 (P<0.001).
Parental Vanderbilt scores showed signicant improvement for subjects with mGluR Tier 1
variants (P<0.035). There were no differences in the incidence of adverse events between
placebo week and weeks on active drug. The trial is registered at https://clinicaltrials.gov/
ct2/show/study/NCT02286817.
DOI: 10.1038/s41467-017-02244-2 OPEN
1Nemours, du Pont Hospital for Children, Wilmington 19803 DE, USA. 2Department of Pediatrics Sidney Kimmel Medical College of Thomas Jefferson
University, Philadelphia 19107 PA, USA. 3Department of Psychiatry Sidney Kimmel Medical College of Thomas Jefferson University 19107 Philadelphia, USA.
4Drexel University College of Medicine, Philadelphia 19129 PA, USA. 5The Center for Applied Genomics, The Childrens Hospital of Philadelphia, Philadelphia
19104 PA, USA. 6University of Pennsylvania, Philadelphia 19104 PA, USA. 7Department of Pediatrics Perelman School of Medicine, University of
Pennsylvania, Philadelphia 19104 PA, USA. 8Department of Radiation Oncology, Helen Diller Family Cancer Center, University of California San Francisco,
San Francisco 94143 CA, USA. 9Divisions of Human Genetics and Pulmonary Medicine, The Childrens Hospital of Philadelphia, Philadelphia 19104 PA, USA.
Correspondence and requests for materials should be addressed to J.E. (email: Josephine.Elia@nemours.org)
NATURE COMMUNICATIONS | (2018) 9:4 |DOI: 10.1038/s41467-017-02244-2 |www.nature.com/naturecommunications 1
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Attention-decit hyperactivity disorder (ADHD) has a
prevalence of ~8% in children with a 2:1 ratio of males
and females affected1. Symptoms persists into adulthood
in over two thirds of cases, causing signicant life-long impair-
ments2,3. While some genetic risk factors for ADHD have been
identied, a signicant gap exists in the translation of this
knowledge to identifying therapeutics with clinical utility. Stan-
dard of care medications used to treat ADHD have been largely
unchanged for the last few decades and the most effective treat-
ments largely consist of stimulants, which are non-specic and
cause signicant off-target effects4,5.
A recent large-scale, genome-wide analysis showed that CNVs
affecting a set of nearly 300 genes in the metabotropic glutama-
tergic network (mGluR) occurred at a signicantly higher fre-
quency in children with ADHD6. CNVs in these genes were
detected in 11.3% of ADHD cases vs. 1.2% of controls6, based on
an analysis of 3500 ADHD cases and nearly 12,000 control
subjects6. Importantly, a core 79-gene subset was enriched in
patients with ADHD group by over 10-fold6,7.
The glutamatergic system has been shown to play a direct role
in several animal models of ADHD8,9. For example, deletion of
the glutamate receptor metabotropic gene, GRM5, and inhibition
of the metabotropic glutamate receptor protein mGluR5 with a
pharmacologist antagonist resulted in increased spontaneous
locomotor activity in rats8. Comparable results were obtained
when GRM79and GRM810, were knocked out in mice. In human
subjects, imaging studies have shown increased glutamatergic
signaling in fronto-striatal pathways, in many but not all ADHD
youths11, while decreased signaling has been reported in ADHD
adults11,12. Glutamate changes in children and adolescents treated
with ADHD medication also show mixed results11, suggesting that
there may be a subgroup of ADHD subjects with impaired gluta-
matergic activity. Altogether, these ndings suggest that mutations
in the mGluR system occurs in at least a subset of individuals with
ADHD, warranting further research to study glutamatergic agents
as a targeted therapeutic strategy in ADHD5,13.
NFC-1 (fasoracetam monohydrate) is a small synthetic mole-
cule and a metabotropic glutamate receptor activator, which has
previously undergone extensive Phase I-III clinical trials in
humans for vascular dementia14. Preclinical studies demonstrated
that that NFC-1 affects mGluRs1517, acetylcholine release and
uptake18 and GABAb, but not adrenoceptors, serotonergic or
dopaminergic receptors19, potentially reversing learning and
memory decits caused by dysfunction of central cholinergic
neurons in a variety of models15,16. It may have the potential to
restore normal glutamatergic activity in ADHD patients with
glutamatergic hypofunction due to mutations in mGluR network
genes. Aside from focusing on CNVs in the top 79 genes iden-
tied in the main mGluR network (Tier-1 mutations)5,we
included CNVs in all 279 previously dened mGluR network
genes (200 belonging to Tier-2) as well as an additional set of 600
genes that come from other related gene networks that interact
with the mGluR network genes (Tier-3 genes)5. Rare CNVs in
these genes were used to identify and prioritize patients who may
benet from NFC-1.
The primary goal of this study was to investigate the safety and
pharmacokinetics of the mGluR activator NFC-1 molecule in
children with ADHD. A secondary objective was to determine if
NFC-1 efcacy in alleviating ADHD symptoms in patients stra-
tied by the presence of germline mutations in glutamatergic
network genes as measured by established survey instruments and
rating scales20, including Clinical Global Impression Scales for
Improvement and Severity (CGI-I and CGI-S, respectively)21,22,
Vanderbilt Parent Scale (www.nichq.org)23 and the parental
Behavior Rating Inventory of Executive Function (BRIEF)24,25 as
well as by changes in overall activity levels by actigraphy26.
Results
We conducted an open-label, single-blind-xed placebo (week 1),
followed by a 4 week dose-escalation study in tandem to a
24-hour PK study (see Supplementary Tables 1and 2for study
ow chart and study parameters collected at each visit). Out of 30
participants enrolled, 29 completed all study time points; 1
completed all but the last time point. All 30 subjects were
included in the analysis. Demographic information on the study
subjects is provided in Table 1. NFC-1 was found to be safe and
well-tolerated. The PK prole was comparable to proles pre-
viously reported for NFC-1 in adult human subjects, based on
analysis of PK parameters C
max
,T
max
, and AUC
024h
(Table 2).
PK parameters demonstrated dose linear pharmacokinetics.
Reported adverse events (AEs) were generally mild, and non-
treatment limiting (Table 3). None of the AEs were associated
with study drug use, since no difference was observed in the
frequencies of any of the AEs reported between the placebo week
(week 1) and any of the active drug weeks (weeks 25) (Sup-
plementary Table 3).
There were three serious adverse events (SAEs) during the
study, none of which was attributed to the study drug. One
subject was hospitalized in a pediatric center for an assessment of
head injury just prior to his last appointment. He was the only
subject who did not complete the study. A second subject
experienced dizziness and brief loss of consciousness (510 s) in
the middle of the school day after medication dose had been
titrated to 100 mg that morning. On evaluation within 2 h, his
vital signs and physical exam were normal. The second dose of
study drug was held on that day and subsequently decreased to
50 mg (same as previous week). There were no recurrences of
dizziness and dose titration resumed again without recurrence of
dizziness. A third subject had an elevation of creatinine phos-
phokinase (CPK) to about ~20,000, which was attributed to
intensive and strenuous sports training; NFC-1 was discontinued
initially, and resumed upon normalization of CPK Levels, which
did not rise again while on NFC-1 and despite ongoing regular
exercise.
Primary efcacy was measured by cumulative changes in global
rating scales CGI-I, CGI-S and Vanderbilt, and Brief scores.
Overall, patients showed signicant improvements in all four
clinical measures by week 5 of the study, as compared to week 1,
during which all patients received placebo (range of P<0.05 to
P<1.2 × 109; Table 4). The strongest improvements were noted
in the CGI-I score, which fell from a mean (median) baseline
score of 3.79(4) ±0.81 (minimally improved to no change), to a
mean (median) score of 2.33(2) ±0.71 (moderately to much
improved) after receiving 400 mg BID of NFC-1 during week 5
(P<1.2 × 105) (Fig. 1).
We further examined the effects of NFC-1 on study subjects
stratied by the presence of specic mGluR variants, though this
information was double blinded during the study. A total of
Table 1 Demographic information of the study participants
Caucasian African
American
Hispanic Row
totals
Mean
age
Males (all) 11 7 2 20 14.6 yo
1213 yo 2 3 2 7
1415 yo 4 1 0 5
1617 yo 5 3 0 8
Females (all) 4 6 0 10 14.4 yo
1213 yo 1 2 0 3
1415 yo 2 1 0 3
1617 yo 1 3 0 4
Column totals 15 13 2 30 14.5 yo
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17 subjects had genomic deletions or disruptive duplications in
Tier-1 mGluR genes, while 7 were categorized as having genomic
deletions or disruptive duplications in Tier-2 mGluR genes and 6
in one of the more distantly-related mGluR network genes (Tier
3), which are potentially of less relevance to mGluR signaling.
Although CGI-I improvements were noted across all patient
groups, among subjects who dose escalated to 400 mg BID,
patients in the Tier 1 and Tier 2 groups showed superior response
(P<3.1 × 106,P<2.1 × 103, respectively). Comparatively, the
responses in Tier 3 subjects being notably less (P<0.053). Final
mean CGI-I scores decreased by more than 1.5 points for Tiers 1
and 2, while the mean decreased by 1.2 points in Tier 3 patients,
when compared to placebo week (Fig. 2).
A similar trend of improvement for the CGI-S index was
observed when comparing the net change from baseline to week 5
across all patients with mean CGI-S scores falling from a mean
(median) score of 4.86(5) ±0.57 (moderately to severely ill), to a
mean (median) score of 3.93(4) ±0.90 (mildly to moderately ill)
after receiving 400 mg BID of NFC-1 week 5 (P <1.7 × 105). No
subjects demonstrated worsening of CGI-S during the study
(Fig. 1).
Importantly, baseline CGI-S scores were not signicantly dif-
ferent when compared to CGI-S scores of patients during week 1,
during which patients receiving placebo (P=0.82) or NFC-1 at
50 mg BID (P =0.18). However, signicant improvement of CGI-
S scores were observed after patients received at least 100 mg BID
(P=0.04), 200 mg BID (P=0.04), and 400 mg BID (P<0.001) as
compared to baseline, suggesting that a minimum of 100 mg of
NFC1-1 was required to observe signicant therapeutic benet
and that the improvement observed is not likely attributable to
placebo.
In addition, as with CGI-I scores, the CGI-S score improve-
ments were stratied by genetic tier, as Tier 1 subjects had the
greatest mean reduction in CGI-S scores (Fig. 2). Mean CGI-S
scores decreased by at least 1 point in both Tier 1 and Tier
2 subjects (P<3.3 × 104and P<8.5 × 103), while only a
modest 0.3 point absolute reduction in the mean was noted in
Tier 3 (P=0.45) (Table 5).
As a whole, patients also demonstrated signicant, albeit more
moderate improvements in Vanderbilt and Brief indices between
study baseline and week 5 (P<0.01 and 0.05, respectively). While
patients from across all three tiers showed a trend to improved
Vanderbilt scores (Supplementary Fig. 4), only those in Tier
1 showed a statistically signicant reduction (P<0.035). For the
Brief index, we observed an overall trend to improvement across
all tiers, though this was not statistically signicant. We also
observed a modest, though not statistically signicant, improve-
ment in every study sub-measure (Supplementary Fig. 5).
Finally, we also examined the effect of NFC-1 on the over-
activity domain of ADHD symptoms exhibited by the study
subjects by monitoring childrens activity levels by actigraphy26.
Actigraphy monitoring was performed through the entire study
period for each patient and standard measures were assessed27,28.
There was a net reduction in moderate to high intensity and
repetitive movements (Table 6), as measured by mean Moderate
to Vigorous Physical Activity (MVPA) per hour, by week 5 of
drug use as compared to that during the week of placebo (P<
3.5 × 104). In addition, we observed improvements in several
other parameters including mean hourly energy expenditure (P<
0.01), percent of time spent in MVPA (P<5.3 × 103), and vector
magnitude average counts (P<9×10
4). As the actigraphy
measures are objective in nature, they support the notion that the
measured efcacy observed in CGI-I, CGI-S and Vanderbilt
ranting scores are unlikely to be attributed to placebo effects or
other measuring bias. Measures of the two major metabolites
yielded levels that were over 2-orders of magnitude lower than for
NFC1 parent, suggesting they were non-contributory.
Discussion
The objectives of this study were to explore the safety, pharma-
cokinetic parameters and potential efcacy of a glutamate
receptor activator NFC-1 in adolescents with ADHD and dis-
ruptive mutations in genes impacting the mGluR network. While
Table 2 Pharmacokinetic parameters
Parameter Dose
50 mg 100 mg 200 mg 400 mg 800 mg
T
max
(h) 1.5 ±0.9 1.9 ±1.1 1.3 ±0.6 1.3 ±0.6 1.9 ±1.9
C
max
(µg/ml) 1.19 ±0.39 1.72 ±0.59 5.07 ±0.83 10.77 ±2.69 20.52 ±7.21
AUC
(0)
(h × µg/ml) 6.87 ±1.35 15.68 ±4.97 30.20 ±5.70 58.11 ±12.15 136.46 ±29.22
T
1/2
(h) 4.44 ±0.65 6.99 ±4.72 4.48 ±0.65 4.11 ±0.47 4.06 ±0.47
A total of six (6) subjects were included in each study/dose group
Table 3 Treatment Emergent Adverse Events (TEAEs)
Severity Any Mild Moderate
n% total n% total n% total
Headache 19 63.3% 18 60.0% 1 3.3%
Fatigue 11 36.7% 9 30.0% 2 6.7%
Abdominal Pain
Upper
8 26.7% 7 23.3% 1 3.3%
Diarrhea 7 23.3% 7 23.3% 0 0.0%
Irritability 6 20.0% 5 16.7% 1 3.3%
Dizziness 4 13.3% 4 13.3% 0 0.0%
Pyrexia 4 13.3% 4 13.3% 0 0.0%
Anxiety 3 10.0% 2 6.7% 1 3.3%
Somnolence 3 10.0% 2 6.7% 1 3.3%
Onychophagia 3 10.0% 2 6.7% 1 3.3%
Tearfulness 3 10.0% 3 10.0% 0 0.0%
Depressed Mood 3 10.0% 3 10.0% 0 0.0%
Cough 3 10.0% 3 10.0% 0 0.0%
Oropharyngeal
Pain
3 10.0% 3 10.0% 0 0.0%
Vomiting 2 6.7% 2 6.7% 0 0.0%
Memory
Impairment
2 6.7% 2 6.7% 0 0.0%
Social Avoidant
Behavior
2 6.7% 2 6.7% 0 0.0%
Visual Impairment 2 6.7% 2 6.7% 0 0.0%
Nausea 2 6.7% 2 6.7% 0 0.0%
Confusion 2 6.7% 1 3.3% 1 3.3%
Number and percent of subjects reporting TEAEs occurring in more than 5% of the study
population. No difference was observed in the frequencies of any of the adverse events reported
between the placebo week (week 1) and any of the active drug weeks (weeks 25). Please see
Supplementary Table 3for detailed week by week break down of AEs
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the heritability for many of the common complex psychiatric or
neurodevelopmental diseases, including ADHD, are high, the
utility of specic genetic associations as disease biomarkers in
guiding the diagnosis or treatment of has been challenging. Our
study is the rst to use NFC-1 to treat adolescents with ADHD
who are carriers of mGluR risk variants, and the rst time this
compound is used in the United States. This trial demonstrates
the feasibility of an innovative, precision medicine based trial
design that leverages data from genetic testing to both identify a
compound not previously registered and to repurpose it for use in
a genetically stratied data set.
We showed that adolescents with ADHD, who are found to
have germline mutations impacting the GRM network, show
clinical improvement using global improvement and severity
scales as well as ADHD symptom scales in response to escalating
dosages of NFC-1, a non-selective glutamate receptor activator
with additional GABA
B
and cholinergic enhancing effects14.We
observed no signicant changes in CGI-S scores among any
patients between enrollment and placebo week, thus precluding
any withdrawal effects on the six subjects who had been treated
with stimulants and the one subject treated with atomoxetine
(Supplementary Table 4). This indicates that rebound effects,
reported in stimulants29, though not in atomoxetine31, were
adequately managed by the washout phase ranging from 5 days
(stimulants) to 14 days (adrenergic drugs). A statistically sig-
nicant decrease in mean CGI-S scores was observed during
weeks 35 when compared to that at baseline. All subjects showed
a decrease in symptom severity as measured by the CGI-S scores
during dose escalation. The mean CGI-S score of all subjects at
baseline was 4.83 (moderately to severely ill), decreasing to 3.86
(mildly to moderately ill) after receiving 400 mg BID of NFC-1
week 5. CGI-I scores also showed dose-dependent decrease in
symptom severity during dose escalation from 50 mg BID to 400
mg BID.
At baseline most subjects were rated as moderately to severely
impaired (mean CGI-S 4.83), indicating that their ADHD
symptoms were disruptive enough to be causing functional
impairment. After 1 week of xed placebo followed by 4 weeks of
dose escalation from 50 mg BID to 400 mg BID, over 80% of
subjects showed clinically signicant improvement in ADHD
symptoms with mean CGI-S score of 3.86, mildly to moderately
impaired. Signicant improvement was also observed in CGI-I
scores as compared to placebo therapy (Fig. 1and Table 4). The
effect was most marked in Tier-1/Tier-2 mGluR mutation posi-
tive subjects (P<0.001), generated in a double-blinded assess-
ment. Parental Vanderbilt scores also showed signicant
improvement for subjects with mGluR Tier 1 variants.
Improvement increased as dose was increased, suggesting dosages
starting at 100 mg BID (35 mg/kg per day) may be required for
clinical response. These results are likely to underestimate the
response rate since maximum dosing of 400 mg BID was achieved
in only 64, 71 and 66% of Tiers 1, 2 and 3, respectively. The level
of comorbid symptoms could also affect the ability to rate the
Vanderbilt scale during such a short therapy course. As the
baseline Vanderbilt scores were slightly lower in Tier-3 subjects,
than in Tier-1/Tier-2 subjects (Table 4), it is conceivable that the
relatively lower response rate in Tier-3 subjects may be attributed
to those differences. However, the CGI-I baseline scores were
more similar and subjects with Tier-1 and Tier-2 mutations
demonstrated more robust response in CGI-I than Tier-3 subjects
(Figs. 1and 2and Table 4). Higher baseline ADHD-RS scores
could be considered for inclusion in future studies.
The half-life (T
1/2
) of NFC-1 ranged from 4.06 to 6.99 h with
an average T
1/2
of 4.82 h across all four dose ranges. These results
are similar to those previously reported in Japanese adults32.
Other pharmacokinetic parameters (Table 2) were likewise
comparable to those previously reported32, in keeping with pre-
vious reports showing that NFC-1 is a stable compound that is
excreted for the most part unchanged through the kidneys and
that there is little, if any, enterohepatic circulation taking place.
Measures of the two major drug metabolized of NFC-1 demon-
strated levels and excretion proles that were comparable to those
previously reported32. Detectable levels of NFC-1 were observed
in the subjects plasma at each visit, that allowed us to validate
drug compliance which was in keeping with the log les of the
drug intake.
We conclude that in adolescent patients with ADHD and
mutations impacting the mGluR network genes, NFC-1 is safe
and well-tolerated. Although the analysis of study efcacy is
limited to early stage data, patients receiving NFC-1 showed
signicant clinical improvement in ADHD symptoms as clinically
assessed by global rating scales. Response occurred in a dose-
related manner, minimally requiring 100 mg BID for signicant
effect. Furthermore, as hypothesized, the degree of response
observed was associated with the presence of specic gene dis-
ruptions in mGluR network genes as the most signicant
improvement in global rating scales were observed in patients in
Tier 1/Tier 2. This study supports the continued investigation of
NFC-1 in the treatment of ADHD, but also emphasizes the value
of genetic prioritization and target therapy in ADHD treatment
regimen selection. We recognize that alternative mechanisms
explaining the therapeutic efcacy of Fasoracetam may exist. For
example, Fasoracetam also affects the cholinergic pathways and
thus may also prove to be effective in those ADHD subjects with
Table 4 Study measure scores for all subjects and stratied by genetic tier
All Tier 1 Tier 2 Tier 3
CGI-I P-value 1.2E09 3.1E06 2.1E03 5.3E02
Baseline 3.79 (4) ±0.81 3.93 (4) ±0.92 3.57 (3) ±0.78 3.66 (4) ±0.51
Final 2.33 (2) ±0.71 2.23 (2) ±0.75 2.14 (2) ±0.37 2.83 (3) ±0.75
CGI-S P-value 1.7E05 3.3E04 8.5E03 4.5E01
Baseline 4.86 (5) ±0.57 4.88 (5) ±0.60 4.71 (5) ±0.48 5 (5) ±0.63
Final 3.93 (4) ±0.90 3.82 (4) ±0.88 3.57 (3) ±0.78 4.66 (4.5) ±0.81
Vanderbilt (P) P-value 1.0E02 3.5E02 1.8E01 5.2E01
Baseline 28.7 (32.5) ±13.9 28.7 (32) ±14.5 33.8 (37) ±12.4 22.8 (26) ±13.7
Final 19.7 (17.5) ±12.2 18.5 (17) ±12.2 24.4 (23) ±12.3 17.6 (16.5) ±12.8
BRIEF (P) P-value 4.9E02 1.8E01 1.9E01 4.7E01
Baseline 68.4 (70.3) ±11.2 67.2 (70) ±11.2 73.8 (71.0) ±8.85 65.9 (71.4) ±13.5
Final 62.1 (63.1) ±13.0 61.3 (61.9) ±13.7 66.0 (63.1) ±11.7 60.0 (63.0) ±13.5
Scores are given in the format of mean (median) ±s.d. Baseline refers to week 1 (xed single-blind placebo week). Final refers to week 5 where patients received the maximal dose for that study
allocation group. P-values are calculated using a two-sided, paired Studentst-test comparing scores obtained at baseline (week 1) vs. nal week of study drug
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variants in that pathway. It is also possible that activating NMDA
receptors may compensate for dysfunctional cholinergic neuro-
transmission33. Further studies are needed to examine the
molecular and neurobiologic basis for our observations.
As this is a phase I clinical trial, the sample size is limited,
recruitment was from a single tertiary care site, and treatment
duration is limited. However, the study design consisted of a
single-blinded placebo group of 1 week duration and the study
was double-blinded as to mutation tier status which was unblin-
ded at the end of study. With the exception of patient and family
blinding as to which week patients received placebo, patients were
otherwise aware of the medication given and that there was dose
escalation taking place during the study. Nevertheless, given the
safety of NFC-1 and the promising results from this cohort, this
study supports the continued investigation of NFC-1 in the
treatment of ADHD subjects with mGluR risk variants.
Methods
Study outline. This is a single-site, single-blind, xed placebo-controlled Phase 1
clinical trial to evaluate the safety, tolerability, plasma concentration prole and
targeted efcacy of orally administered NFC-1 in adolescent (1217 years) ADHD
patients exhibiting mutations in genes within the GRM network. Primary objec-
tives were to evaluate the safety and tolerability of orally administered NFC-1 and
characterize its pharmacokinetic parameters. A secondary objective was to explore
the dose-response relationship of NFC-1 on ADHD severity and global measures
and determine effect size of specic GRM network genes on ADHD based on
responsiveness of patients to NFC-1.
Participants. From over 200 patients screened for mGluR mutations using a SNP
array, 30 patients with ADHD harboring disruptive copy number variants (CNVs)
within or nearby one or more mGluR network genes (Table 5) were recruited from
the Center of Applied Genomics (CAG) at The Childrens Hospital of Philadelphia
(CHOP). The study participants included ADHD cases who had previously par-
ticipated in a large-scale genomics study at CAG/CHOP (Genetics of Complex
Pediatric Disorders) and had authorized recontact for future studies. The study
was conducted at the Jefferson University (TJU) Clinical Research Unit for the PK
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CGI-S scores Tier 1
Week of trial
CGI-S score
12345
3.0
3.5
4.0
4.5
5.0
CGI-S scores Tier 2
Week of trial
CGI-S score
12345
4.0
4.5
5.0
5.5
6.0
CGI-S scores Tier 3
Week of trial
CGI-S score
12345
2
3
4
5
6
CGI-S scores overall
Week of trial
CGI-S score
a
b
P< 1×10 –9 ***
P< 3×10 –6 ***
P< 2×10 –3 **
P= 0.053
P<1×10–5 ***
P<3×10–4 ***
P< 9×10 –3 **
P= 0.45
c
d
f
g
h
e
Fig. 1 Week by week box-and-whisker plots showing the results for the CGI-I (ad) and CGI-S (eh) scaled inventories for all study subjects (a,e)or
stratied by genetic tiers (Tier 1 (b,f), Tier 2 (c,g), and Tier 3 (d,h)). P-values denote results of the paired Studentst-test between results from study
baseline (week 1) and nal (week 5). N=30. The edges of the box plots denote 25 and 75% tiles, while the solid black horizontal line denotes the cohort
median. Upper and lower whiskers denote the limits of the nominal range of the data inferred from the upper and lower quartiles (Methods section) and
plotted points are outliers from these ranges
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Content courtesy of Springer Nature, terms of use apply. Rights reserved
part of the study and TJU Department of Psychiatry for the dose escalation part of
the study. The study was approved by the Institutional Review Board of Thomas
Jefferson University. Informed consents were obtained from all parents and assents
from all study subjects. The study IND was approved on 7 November 2014;
institutional review board approval was obtained on 11 December 2014; FPI was
obtained on 23 January 2015, and LPO was obtained on 17 May 2015.
Inclusionary criteria. Male and female patients, ages 1217 years, of any ancestry,
diagnosed with ADHD as dened by DSM-5 and a Vanderbilt ADHD rating scale
score 16, genotyped to have disruptive CNVs in the mGluR gene networks were
eligible to participate (Supplementary Materials; Supplementary Figs. 1a and 1b).
Exclusionary criteria. Any clinically signicant illness, which, in the opinion of the
investigator, may confound the results of the study, pose additional risk to the
patient by their participation, or prevent or impede the patient from completing
the study, pregnancy, positive urine for illicit drugs (including marijuana), or
history of drug or alcohol abuse within the last 3 years.
Study drug. NFC-1 (fasoracetam monohydrate) was administered per os as a
single dose during the pharmacokinetic study and twice-daily (BID) during the
dose-escalation study. NFC-1 was delivered in size 1, dark blue capsules containing
50 mg NFC-1 or size 1, dark blue capsules containing 200 mg NFC-1. Matching
placebo capsules containing microcellulose instead of NFC-1 were provided during
the week of placebo administration. The capsules were stored at controlled room
temperature of 2025 °C (6877°F). Twelve-month stability data at room tem-
perature showed no evidence of decay of the active substance.
Dosing. All study subjects completed a 24-h PK study. This was followed by an
open-label, 5-week dose-escalation study, starting with a xed single-blind placebo
week (week 1). All ADHD medications were discontinued with a washout phase
ranging from 5 days (stimulants) to 14 days (adrenergic drugs). The 24-h PK study
included ve groups with six subjects/group, where each group was given the
following respective single doses: 50, 100, 200, 400 and 800 mg. Three patients were
initially enrolled for PK studies and shown to tolerate 50 mg of the drug well prior
to enrolling the next three subjects to complete dose group 1 of 50 mg. The next six
subjects completed 100 mg and tolerated the study drug well. The DSMB approved
the 3rd study group of 6 subjects to advance to 200 mg and the 4th set of six
subjects to 400 mg, with the last group of 6 subjects approved by the DSMB to
receive 800 mg (Supplementary Fi gs. 2and 3). All study subjects tolerated their
study medications well during the PK part of the study. The patients subsequently
received a placebo BID (week 1) followed by NFC-1 50 mg BID in week 2, 100mg
BID in week 3, 200 mg BID in week 4, and 400 mg BID in week 5. Safety data was
reviewed by the study PI, study team and the DSMB after each dose cohort before
proceeding with each dose increase. Patients were blinded as to which week (out of
the 5 total weeks) they received placebo.
Study measures. The PK measures included 11 parameters of active drug and two
major metabolites at each time point during the initial pharmacokinetic portion of
the trial. Blood samples were collected just prior to dosing and at 0.5, 1, 1.5, 2, 3, 4,
6, 8, 12, and 24 h after administration of the rst dose of NFC-1. The concentra-
tions of NFC-1 and two metabolites (LAM-79 and LAM-163) in plasma were
determined by a validated ultra-performance liquid chromatography - tandem
mass spectrometry assay with D
10
-NFC-1 as an internal standard. The following
precursor to product ion transitions were used for quantitation: m/z 197.2 84.2
(NFC-1), m/z 213.2 83.9 (LAM-79), m/z 213.2 84.0 (LAM-163), and m/z
207.2 84.2 (D
10
-NFC-1). The analytical method was selective and linear over the
concentration range of 10 to 2,500 ng/mL for all three compounds in plasma.
Precision of the NFC-1 assay, as determined by percent coefcient of variation, was
5.137.16 % (within-day) and 3.819.99% (between-day), and accuracy was within
93.5107% based on quality control samples. Precision of the LAM-79 assay was
5.819.11% (within-day) and 4.617.72% (between-day), with accuracy within
103109%. Precision of the LAM-163 assay was 4.297.90% (within-day) and
3.2810.2% (between-day), and was accuracy within 100 to 112%. PK parameters,
including C
max
,T
max
, and AUC
024h
,were estimated by the methodology of Gibaldi
and Perrier34.C
max
and T
max
were obtained by visual inspection of individual
patient plasma proles. Half-life was estimated by 0.693/k
e
, where k
e
is the slope of
the terminal elimination phase from linear regression of log-transformed con-
centration values on time. AUC(024) was estimated by the linear trapezoidal
method and AUC(0) by addition of area extrapolated to innity via the
regression described above. All calculations were performed with the R program-
ming language35.
CGI-I/CGI-S scores determined by the psychiatric evaluators, together with
parental Vanderbilt ratings, were the key measurements used to assess drug efcacy
of NFC-1. The efcacy measures performed during the dose escalation study are
detailed in Supplementary Figs. 2and 3. Parental Brief rating scales were also
included as secondary measures of NFC-1 efcacy. Wechsler Abbreviated Scale of
intelligence, together with overall assessment of the childrens neurocognitive
function and ADHD-comorbid condition severities, including anxiety, autism
spectrum disorder and mood swings, were also recorded by the psychiatric
evaluators. Actigraphy data was also collected from all subjects at each visit for the
duration of the study (Table 6).
The safety measures and logging of all adverse events (spontaneous reports and
rating scales; Pittsburgh Side Effect Scale36 and the Columbia Suicide Scale37 were
evaluated throughout the study and graded in terms of severity (mild, moderate, or
severe) and relationship to study treatment (unrelated, possibly related, or
denitely related) recorded. Serum NFC-1 levels were measured during each week
of the dose-escalation study to ensure adherence. At baseline and after each week of
treatment, each subject had a physical exam, electrocardiogram, and safety
laboratory test (complete blood count, clinical chemistry and urinalysis).
Genotyping and genetic tier stratication. After informed consents were
obtained, blood samples were obtained and deoxyribonucleic acid (DNA) was
isolated from eligible adolescents age 1217 years and genotyped using the OMNI-
2.5 M genotyping assay (Illumina, San Diego), performed in the CAP-certied
genotyping laboratory at The Childrens Hospital of Philadelphia. The OMNI-2.5
M oligonucleotide array effectively captures the target CNVs in the 79 Tier-1
mGluR genes of interest and has sufcient coverage across the additional 200 Tier-
2 and 600 Tier-3 mGluR genes, as previously reported5,6.
In brief, 250 ng of genomic DNA was used to genotype each sample according
to the manufacturers guidelines. This implies, amplication of the patient DNA
and hybridization to a reference genome. Upon washing, the samples are scanned
to capture over 2.5 M SNPs dispersed throughout the genome. Cluster plots are
generated to separate the 3 genotype states, namely homozygous allele (AA),
homozygous allele (BB) or heterozygous state (AB).
The CNV quality control measures were performed on the genotyping data
based on statistical distributions to exclude poor quality DNA samples and false
positive CNVs. The rst threshold was the percentage of attempted SNPs that were
successfully genotyped. Only samples with call rate >98.5% will be included in the
123 123
0
25
50
75
Scores
b
123 123
2
4
6
Scores
Time
Week 1
Final
**
a
CGI-I CGI-S
Genetic tier
cd
BRIEF VANDERBILT
Fig. 2 Net differences in the distribution of a CGI-I, b CGI-S, c Vanderbilt,
and d Brief global scales between week 1 (placebo; green) and the nal
(max dose; orange) week of the study shown as box plots. Patients were
stratied by genetic tier group allocation. P-values denote results of the
paired Studentst-test between results from study baseline (week 1) and
nal (week 5) for each tier. Statistically signicant comparisons are
highlighted with red asterisks. N=30. The edges of the box plots denote 25
and 75% tiles, while the solid black horizontal line denotes the cohort
median. Upper and lower whiskers denote the limits of the nominal range of
the data inferred from the upper and lower quartiles (see Methods) and
plotted points are outliers from these ranges
ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02244-2
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Content courtesy of Springer Nature, terms of use apply. Rights reserved
CNV analysis. The genome-wide intensity signal must have as little noise as
possible. Only samples with the standard deviation (SD) of normalized intensity
(Log R Ratio (LRR)) <0.25 were included. Samples of different ethnicities based on
hierarchical clustering of AIMs genotypes were separated from each other and
called separately. Wave artifacts that roughly correlate with GC content that result
from hybridization bias of low full length DNA quantity are known to interfere
with accurate inference of copy number variations. Thus, only samples where the
correlation of LRR to wave model ranges between 0.2 <X<0.4 will be accepted.
The simultaneous analysis of intensity data and genotype data in the same
experimental setting establishes a highly accurate denition for normal diploid
states and any deviation thereof. In contrast with aCGH which relies on intensity
data alone for CNV calls, the Illumina SNP array platforms provide both genotype
and intensity data for each SNP marker. The PennCNV algorithm was used to
generate CNV calls and data analysis were standardized as described previously39.
(Three different CNV states were called, including homozygous deletions (copy
number, or CN =0), hemizygous deletions (CN =1), duplications (CN =3or
more). Supplementary Table 5presents the CNV regions for the top 79 most
signicant gene loci of interest harboring CNVs (deletions or duplications)
and includes the same information for Tier-2 and Tier-3 genes.
All CNVs identied were validated visually and/or experimentally based on the
condence of the CNV call to ensure validity of the results reported (experimental
validation has been performed previously or the 79 CNV genes under study5.As
shown previously, for the 79 mGluR/GRM network genes, accuracy of the CNV
calls detected on the SNP array is over 95%. Subsequent Taqman validation raised
the accuracy of the CNV calls identied to 100%.
Statistical and network analysis. Quantitative variables were summarized using
descriptive statistics. Continuous variables were presented as N, mean and median,
standard deviation and range. Categorical variables were presented using fre-
quencies and percentage. Analyses of variance (ANOVA) were used to compare
treatment response at the respective weeks from week 1 to week 5. Where not
specied explicitly, a Studentst-test was used. Analysis was performed using SPSS
and R35,38.
Genetic stratication of mGluR genes is delineated in genetic tiers in keeping
with previous mGluR CNV association results (tier-1: 79 genes; tier-2: 200 genes;
tier-3: 600 genes; Supplementary Materials)5,6.
For Box-and-Whisker Plots, upper and lower whiskers denote the limits of the
nominal range of the data inferred from the upper and lower quartiles, representing
the smaller of the maximum score and the value of (75% tile+1.5×interquartile
range) and the larger of the minimum score and the value of (25% tile
1.5×interquartile range), respectively. Additional points are outliers beyond these
ranges. Network analysis were performed in StringDB (https://string-db.org) using
program dened parameters.
Actigraphy.Actigraphy watches: Each participant was given an Actilife watch. The
data was downloaded from the watch each week and the watches were recharged
while participants were given their weekly dose, and a clinical interview.
Data analysis: Data was loaded into the Actilife software for further analysis.
Sixty second epochs were used as the unit for analysis. The default algorithm in the
software was used to detect off-watch times, and these periods were removed from
further evaluation.
The Actilife software calculates a number of variables that measure energy
expenditure, bouts of activity, and the vigorous nature of the activity. Bouts of
activity are measured by an algorithm developed by Freedson4that has been
calibrated in children and adolescents.
Table 5 mGluR gene network variants impacting enrolled patients
Patients Chr:Start-Stop(hg19) CNV del/dupl StartSNP EndSNP GRM contributing
Tier-1 genes
Subject 1 chr7:126447564-126535600 Del Startsnp =rs4731330 Endsnp =rs12669064 GRM8
Subject 2 chr17:76573316-76595131 Dupl Startsnp =rs752811 Endsnp =rs11651207 TK1
Subject 3 chr17:43661362-43685925 Dupl Startsnp =kgp3353562 Endsnp =rs28713506 CRHR1
Subject 4 chr7:86940652-86945816 Del Startsnp =kgp11792873 Endsnp =kgp13383594 GRM3
Subject 5 chr19:49073874-49075277 Dupl Startsnp =kgp21488201 Endsnp =rs2544796 RUVBL2
Subject 6 chr7:154885237-154889184 Del Startsnp =rs1436818 Endsnp =rs1730186 DPP6
Subject 7 chr11:88308509-88588641 Del Startsnp =rs160520 Endsnp =rs7938157 GRM5
Subject 8 chr8:90836233-90858597 Del Startsnp =kgp6180974 Endsnp =kgp20067788 18p Del Syndr/RIPK2
Subject 9 chr7:125555887-125556965 Del Startsnp =kgp4046066 Endsnp =kgp3698082 GRM8
Subject 10 chr17:44166604-44347946 Dupl Startsnp =kgp3045933 Endsnp =kgp13853487 CRHR1
Subject 11 chr3:1936873-1943773 Del Startsnp =rs12637547 Endsnp =kgp5837095 CNTN4
Subject 12 chr7:153296249-153297555 Del Startsnp =rs10250553 Endsnp =kgp8411417 DPP6
Subject 13 chr22:18874965-21464479 Del Startsnp =kgp15094602 Endsnp =kgp7040282 22Qdel - RANBP1
Subject 14 chr17:43907896-43913030 Dupl Startsnp =rs16940665 Endsnp =rs16940686 CRHR1
Subject 15 chr7:125435694-125576985 Del Startsnp =kgp9704135 Endsnp =rs11767202 GRM8
Subject 16 chr14:96683973-96688669 Del Startsnp =rs945040 Endsnp =rs4905469 BDKRB2
Subject 17 chr22:19421229-20308800 Dupl Startsnp =kgp6235116 Endsnp =rs1210829 22Qdupl - RANBP1
Tier-2 genes
Subject 18 chr18:637631-717229 Del Startsnp =rs13381806 Endsnp =rs7235957 C18orf56/ENOSF1
Subject 19 chr17:44173505-44347946 Dupl Startsnp =kgp7830309 Endsnp =kgp13853487 MAPT
Subject 20 chr9:139743497-139755375 Dupl Startsnp =rs12555238 Endsnp =kgp1725313 TRAF2
Subject 21 chr6:33496513-33525680 Del Startsnp =kgp11013882 Endsnp =rs210170 GRM4
Subject 22 chr19:43513659-43594955 Del Startsnp =rs11668932 Endsnp =kgp6508883 CIC
Subject 23 chr5:140225908-140227999 Dupl Startsnp =rs7730895 Endsnp =kgp22520363 PCDHA1-A9
Subject 24 chr17:7264717-7265681 Del Startsnp =kgp3155353 Endsnp =kgp3898700 SHBG
Tier-3 genes
Subject 25 chr11:1857042-1864645 Dupl Startsnp =rs907605 Endsnp =kgp253861 SYT8/TNNI2
Subject 26 chr2:201319521-201465841 Dupl Startsnp =kgp1394853 Endsnp =rs16833843 AOX1/KCTD18/SGOL2
Subject 27 chr5:102123728-102141765 Dupl Startsnp =kgp6255090 Endsnp =kgp8236099 PAM
Subject 28 chr5:102123728-102141765 Dupl Startsnp =kgp6255090 Endsnp =kgp8236099 PAM
Subject 29 chr19:7251101-7252844 Del Startsnp =rs11671297 Endsnp =kgp10769783 INSR
Subject 30 chr2:110856809-110887808 Del Startsnp =kgp14587515 Endsnp =kgp1736195 MALL
Table 6 Results from actigraphy analysis
Measure 50
mg
100
mg
200
mg
400
mg
Model
P-value
Mean Hourly kcals 1.93 0.85 2.08 3.84 0.0099
Bouts per day (n) 0.05 0.5 0.03 0.34 0.29
Sedentary bouts (n) 0.25 0.9 0.95 0.48 0.34
Percent in MVPA 0 0 0.01 0.02 0.0053
Mean MVPA per hour 0.11 0.04 0.55 0.91 0.0035
Vector magnitude average
counts
3.95 4.95 24.31 36.63 0.0009
Actigraphy results for study patients by drug dose; moderate to vigorous physical activity
(MVPA)
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Variables examined included: average number of kCals used per hour, number
of bouts of activity per day (measured using the Freedson et al., algorithm), total
time of bouts, number of sedentary bouts, p of time in moderate to vigorous
physical activity (MVPA)40.
For each variable, a linear mixed model using was t using the lme4 package in
Rwhere each variable was treated as a xed effect, and regressed against the xed
effect of dosage, while treating subject as a random effect. The covariates of age, sex
and weight were also included as xed effects. A model with all covariates was
tted, and then a model with dosage added as a xed effect and modeled as a factor.
ANOVA using maximum likelihood was used to test for a signicant difference in
t between the two models. The analysis compares whether there are differences
overall between week 1 and the subsequent weeks.
To test if there was an interaction between dosage of the drug and the type of
CNV carried by the participant, the difference in t between models that included
dosage and genetic tier in addition to the covariates, to one that also tan
interaction term of dosage×genetic tier.
Data availability. The data sets generated during and/or analyzed during the
current study are available from the corresponding author on reasonable request.
Received: 18 January 2017 Accepted: 15 November 2017
References
1. Polanczyk, G. V., Willcutt, E. G., Salum, G. A., Kieling, C. & Rohde, L. A.
ADHD prevalence estimates across three decades: an updated systematic review
and meta-regression analysis. Int. J. Epidemiol. 43, 434442 (2014).
2. Visser, S. N. et al. Trends in the parent-report of health care provider-diagnosed
and medicated attention-decit/hyperactivity disorder: United States, 2003-
2011. J. Am. Acad. Child Adolesc. Psychiatry 53,3446.e2 (2014).
3. Barbaresi, W. J. et al. Mortality, ADHD, and psychosocial adversity in adults
with childhood ADHD: a prospective study. Pediatrics 131, 637644 (2013).
4. Adriani, W. et al. Short-term effects of adolescent methylphenidate exposure on
brain striatal gene expression and sexual/endocrine parameters in male rats.
Ann. NY Acad. Sci. 1074,5273 (2006).
5. Connolly, J. J., Glessner, J. T., Elia, J. & Hakonarson, H. ADHD &
pharmacotherapy: past, present and future: a review of the changing landscape
of drug therapy for attention decit hyperactivity disorder. Ther. Innov. Regul.
Sci. 49, 632642 (2015).
6. Elia, J. et al. Genome-wide copy number variation study associates
metabotropic glutamate receptor gene networks with attention decit
hyperactivity disorder. Nat. Genet. 44,7884 (2012).
7. Hadley, D. et al. The impact of the metabotropic glutamate receptor and other
gene family interaction networks on autism. Nat. Commun. 5, 4074 (2014).
8. Olsen, C. M., Childs, D. S., Stanwood, G. D. & Winder, D. G. Operant sensation
seeking requires metabotropic glutamate receptor 5 (mGluR5). PLoS ONE. 5,
e15085 (2010).
9. Palucha, A. et al. Activation of the mGlu7 receptor elicits antidepressant-like
effects in mice. Psychopharmacology 194, 555562 (2007).
10. Gerlai, R., Adams, B., Fitch, T., Chaney, S. & Baez, M. Performance decits of
mGluR8 knockout mice in learning tasks: the effects of null mutation and the
background genotype. Neuropharmacology 43, 235249 (2002).
11. Naaijen, J., Lythgoe, D. J., Amiri, H., Buitelaar, J. K. & Glennon, J. C. Fronto-
striatal glutamatergic compounds in compulsive and impulsive syndromes: A
review of magnetic resonance spectroscopy studies. Neurosci. Biobehav. Rev. 52,
7488 (2015).
12. Ende, G. et al. Impulsivity and Aggression in Female BPD and ADHD Patients:
Association with ACC Glutamate and GABA Concentrations.
Neuropsychopharmacology 41, 410418 (2016).
13. Yang, L. et al. Polygenic transmission and complex neuro developmental
network for attention decit hyperactivity disorder: genome-wide association
study of both common and rare variants. Am. J. Med. Genet. B Neuropsychiatr.
Genet. 162B, 419430 (2013).
14. Ogasawara, T. et al. Involvement of cholinergic and GABAergic systems in the
reversal of memory disruption by NS-105, a cognition enhancer. Pharmacol.
Biochem. Behav. 64,4152 (1999).
15. Oka, M. et al. Involvement of metabotropic glutamate receptors in Gi- and Gs-
dependent modulation of adenylate cyclase activity induced by a novel
cognition enhancer NS-105 in rat brain. Brain Res. 754, 121130 (1997).
16. Oka, M. et al. A novel cognition enhancer NS-105 modulates adenylate cyclase
activity through metabotropic glutamate receptors in primary neuronal culture.
Naunyn. Schmiede. Arch. Pharmacol. 356, 189196 (1997).
17. Hirouchi, M., Oka, M., Itoh, Y., Ukai, Y. & Kimura, K. Role of metabotropic
glutamate receptor subclasses in modulation of adenylyl cyclase activity by a
nootropic NS-105. Eur. J. Pharmacol. 387,917 (2000).
18. Ukai, Y. et al. A pyroglutamate derivative, LAM-105, improves learning and
memory in rats by enhancing the cholinergic neuronal activity. in: 17th annual
CINP Meeting Abstract 362 (1990). Oxford University Press, Kyoto, JP.
19 Oka, M., Fukui, T., Itoh, Y., Ukai, Y. & Kimura, K. NS-105 a novel nootropic
agent, reverses GABAB receptor mediated inhibition of cyclic AMP
accumulation in the rat brain. J Neurochem 65, (1995) [Suppl]; 164.
20 Wigal, S. B. & Wigal, T. L. The laboratory school protocol: its origin, use, and
new applications. J. Atten. Disord. 10,92111 (2006).
21 Goodman, D. W. Lisdexamfetamine dimesylate (vyvanse), a prodrug stimulant
for attention-decit/hyperactivity disorder. PT35, 273287 (2010).
22 Guy, W. A data processing system for psychotropic drug evaluation. Arch. Gen.
Psychiatry 23, 454 (1970).
23 Wolraich, M. L. et al. Psychometric properties of the Vanderbilt ADHD
diagnostic parent rating scale in a referred population. J. Pediatr. Psychol. 28,
559567 (2003).
24 Gioia, G. A., Isquith, P. K., Retzlaff, P. D. & Espy, K. A. Conrmatory factor
analysis of the Behavior Rating Inventory of Executive Function (BRIEF) in a
clinical sample. Child Neuropsychol. 8, 249257 (2002).
25 Gioia, G. A., Isquith, P. K., Kenworthy, L. & Barton, R. M. Proles of everyday
executive function in acquired and developmental disorders. Child
Neuropsychol. 8, 121137 (2002).
26 Wood, A. C., Rijsdijk, F., Saudino, K. J., Asherson, P. & Kuntsi, J. High
heritability for a composite index of childrens activity level measures. Behav.
Genet. 38, 266276 (2008).
27 Wood, A. C., Kuntsi, J., Asherson, P. & Saudino, K. J. Actigraph data are
reliable, with functional reliability increasing with aggregation. Behav. Res.
Methods 40, 873878 (2008).
28 Wood, A. C., Asherson, P., Rijsdijk, F. & Kuntsi, J. Is overactivity a core feature
in ADHD? Familial and receiver operating characteristic curve analysis of
mechanically assessed activity level. J. Am. Acad. Child Adolesc. Psychiatry 48,
10231030 (2009).
29 Cox, D. J. et al. Rebound effects with long-acting amphetamine or
methylphenidate stimulant medication preparations among adolescent male
drivers with attention-decit/hyperactivity disorder. J. Child Adolesc.
Psychopharmacol. 18,110 (2008).
30 Buitelaar, J. K. et al. Long-term efcacy and safety outcomes with OROS-MPH
in adults with ADHD. Int. J. Neuropsychopharmacol. 15,113 (2012).
31 Garnock-Jones, K. P. & Keating, G. M. Atomoxetine. Pediatr. Drugs 11, 203226
(2009).
32 Kumagai, Y. et al. Comparison of pharmacokinetics of NS-105, a novel agent for
cerebrovascular disease, in elderly and young subjects. Int. J. Clin. Pharmacol.
Res. 19,18 (1999).
33 Portero-Tresserra, M., Cristóbal-Narváez, P., Martí-Nicolovius, M., Guillazo-
Blanch, G. & Vale-Martínez, A. D-cycloserine in prelimbic cortex reverses
scopolamine-induced decits in olfactory memory in rats. PLoS ONE 8, e70584
(2013).
34 Gibaldi, M. & Perrier, D. Pharmacokinetics. (Marcel Decker, New York, 1982).
35 R Core Team. R: A language and environment for statistical computing. (R
Foundation for Statistical Computing, Vienna, Austria, 2015).
36 Pelham, W. E. Pharmacotherapy for children with attention-decit
hyperactivity disorder. Sch. Psych. Rev. 22, 199227 (1993).
37 Chappell, P., Feltner, D. E., Makumi, C. & Stewart, M. Initial validity and
reliability data on the Columbia-Suicide severity rating scale. Am. J. Psychiatry
169, 662663 (2012).
38 IBM SPSS Statistics for Windows. v.24 (IBM Corp., 2016).
39 Wang, K. et al. PennCNV: An integrated hidden Markov model designed for
high-resolution copy number variation detection in whole-genome SNP
genotyping data. Genome Res.17 16651674 (2007).
40 Freedson P., Pober, D. & Janz, K. F. Calibration of accelerometer output for
children. Med. Sci. Sports Exerc.37 S523S530 (2005).
Acknowledgements
We thank the patients and their families for their participation in this study. We thank
Phillip R. Harper and Rita Harper for their funding support to NeuroFix for the study
execution. We thank David H. Moskowitz and Marian Moskowitz for their voluntary
help with contractual agreements. We thank Maria B. Ivarsdottir for her voluntary
accounting work. We thank David Fitts, Liza Squires, Garry Neil and Aevi Genome
Medicine, Inc. for providing the analysis of the PK data measures for the study and for
their review of the manuscript. We thank Donna F. Stroup, PhD, MSc for her statistical
support. The study was funded by neuroFix Therapeutics Inc., a spin-off company from
the Childrens Hospital of Philadelphia. YRL is supported by the Paul and Daisy Soros
Fellowship and the NIH F30 NRSA Individual Fellowship.
Author contributions
J.E., W.K.K., and H.H. conceived the project, designed the experiments and supervised
the study. J.E., G.U., C.K., N.De.J.-R., L.L., R.C., T.W., C.K., K.T., B.S., S.H., B.K. J.P., J.D.,
J.M., E.S., G.M., A.Z., A.W. and W.K.K. performed the experiments. J.E., W.K.K., C.K.,
ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-02244-2
8NATURE COMMUNICATIONS | (2018) 9:4 |DOI: 10.1038/s41467-017-02244-2 |www.nature.com/naturecommunications
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Y.R.L. and H.H. wrote the manuscript and all authors contributed to manuscript editing
and approved the nal version of the article. All authors agree with the results and
conclusions of this article. Y.R.L., A.A., and E.B. contributed to reagents, materials or
analysis tools and helped with data analysis.
Additional information
Supplementary Information accompanies this paper at https://doi.org/10.1038/s41467-
017-02244-2.
Competing interests: H.H. is the founder of NeuroFix, served on its Advisory Board and
has stock or equity in neuroFix Therapeutics LLC, which is now owned by Aevi Genome
Medicine Inc. H.H. was not involved with the evaluation of the study participants. All of
the clinical evaluations were performed by J.E. and W.K.K. and their staff, none of whom
have any competing interests, or any afliation with neuroFix. All of the statistical analysis
was done based on a predesigned SAP by an independent statistician as work for hire
from a locked database. The remaining authors declare no competing nancial interests.
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