Characterizing Developmental and Behavioral Profiles in Developmental Synaptopathies to Inform Clinical Trial Endpoints
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| Title: | Characterizing Developmental and Behavioral Profiles in Developmental Synaptopathies to Inform Clinical Trial Endpoints |
|---|---|
| Language: | English |
| Authors: | Latha Valluripalli Soorya, Camille W. Brune, Cristan A. Farmer, Edith V. Ocampo, Natalie I. Berger, Deborah A. Pearson, Robyn M. Busch, Patricia Klaas, Paige Siper, Kristn Currans, Amanda C. Gulsrud, Jennifer M. Phillips, Rajna Filip-Dhima, Sarah E. O’Kelley, Thomas W. Frazier, Tess Levy, Allison L. Wainer, Joseph D. Buxbaum, Craig M. Powell, Jonathan A. Bernstein, Simon K. Warfield, Darcy A. Krueger, E. Martina Bebin, Hope Northrup, Shafali S. Jeste, Alexander Kolevzon, Elizabeth Berry-Kravis, Mustafa Sahin, Siddharth Srivastava, Audrey Thurm |
| Source: | American Journal on Intellectual and Developmental Disabilities. 2025 130(5):414-437. |
| Availability: | American Association on Intellectual and Developmental Disabilities. P.O. Box 1897, Lawrence, KS 66044-1897. Tel: 785-843-1235; Fax: 785-843-1274; e-mail: AJMR@allenpress.com; Web site: https://meridian.allenpress.com/aaidd |
| Peer Reviewed: | Y |
| Page Count: | 24 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Intellectual Disability, Genetic Disorders, Neurological Impairments, Measurement Techniques, Children, Adolescents, Young Adults, Severity (of Disability), Measures (Individuals), Behavior, Individual Development, Cognitive Processes |
| DOI: | 10.1352/1944-7558-130.5.414 |
| ISSN: | 1944-7515 1944-7558 |
| Abstract: | The Developmental Synaptopathies Consortium is a multisite natural history network studying rare, neurogenetic syndromes associated with synaptic dysfunction and developmental delays. One aim of the Consortium is clinical trial readiness, including identifying clinical concepts and validating their measurement. We evaluated the scope and limitations of conventional cognitive and behavioral measurement strategies in 2-21-year-olds with Phelan-McDermid syndrome (PMS; N = 98), Tuberous Sclerosis Complex (TSC; N = 98), and PTEN Hamartoma Tumor syndrome (PHTS; N = 69). On average, intellectual disability (ID) severity was severe-to-profound in PMS, mild-to-moderate for TSC, and borderline (or absent) in PHTS. Severity of ID invalidated the use of many assessments, including standardized autism diagnostic measures. These results will inform trial planning for these and other similarly medically complex neurodevelopmental conditions. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1482498 |
| Database: | ERIC |
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| FullText | Links: – Type: pdflink Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwE-Vf9Awz5Jl4Xe6csGBfmjAAAA4TCB3gYJKoZIhvcNAQcGoIHQMIHNAgEAMIHHBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDFyqyy_CIuVaTIqf0wIBEICBmck8naGOYOCuUICaf4EEM5YOOM1FGsduYHO3CgnV33drdk2iV8nKyc6Fm8xJV1z0HFAQQXTria3x7pem_ItBm1u3h-PG_5lPVAkXvZj9j8oUGueO8UANoXrnKVciMuoFq0lpQE3eYjzsRIAfoGLGUrk_hAuT2xHG0jbMpEXtj667Tlakx-nmeyKttpmPXaeyoRfSUs_B1qd-Gg== Text: Availability: 1 Value: <anid>AN0187547689;[8z1j]01sep.25;2025Aug29.02:09;v2.2.500</anid> <title id="AN0187547689-1">Characterizing Developmental and Behavioral Profiles in Developmental Synaptopathies to Inform Clinical Trial Endpoints </title> <p>The Developmental Synaptopathies Consortium is a multisite natural history network studying rare, neurogenetic syndromes associated with synaptic dysfunction and developmental delays. One aim of the Consortium is clinical trial readiness, including identifying clinical concepts and validating their measurement. We evaluated the scope and limitations of conventional cognitive and behavioral measurement strategies in 2–21-year-olds with Phelan-McDermid syndrome (PMS; N = 98), Tuberous Sclerosis Complex (TSC; N = 98), and PTEN Hamartoma Tumor syndrome (PHTS; N = 69). On average, intellectual disability (ID) severity was severe-to-profound in PMS, mild-to-moderate for TSC, and borderline (or absent) in PHTS. Severity of ID invalidated the use of many assessments, including standardized autism diagnostic measures. These results will inform trial planning for these and other similarly medically complex neurodevelopmental conditions.</p> <p>Keywords: autism spectrum disorder; tuberous sclerosis complex; PTEN Hamartoma Tumor syndrome; Phelan McDermid syndrome; intellectual disability; neuropsychological assessment; neurodevelopmental disorders; clinical trial readiness</p> <p>Advances in genomics have pointed to considerable overlap in genetic risk factors for neurodevelopmental disorders such as intellectual disability (ID) and autism spectrum disorder (ASD; [<reflink idref="bib96" id="ref1">96</reflink>]). These advances present a promising opportunity to interrogate shared molecular and disease mechanisms informing medical, physiological, psychiatric, cognitive, and behavioral outcomes, which may reveal common treatment pathways for related conditions.</p> <p>The Developmental Synaptopathies Consortium (DSC) was formed and funded by the Rare Disease Clinical Research Network (RDCRN) in 2014 to advance this genetics-first approach to treatment development. The DSC studied three genetic syndromes associated with genes governing early synaptogenesis ([<reflink idref="bib27" id="ref2">27</reflink>]) and with disruptions or dysregulation of the mTOR pathway ([<reflink idref="bib93" id="ref3">93</reflink>]; [<reflink idref="bib115" id="ref4">115</reflink>]): (<reflink idref="bib1" id="ref5">1</reflink>) Phelan-McDermid syndrome (PMS), (<reflink idref="bib2" id="ref6">2</reflink>) Tuberous Sclerosis Complex (TSC), and (<reflink idref="bib3" id="ref7">3</reflink>) PTEN Hamartoma Tumor Syndrome (PHTS). Mutations in <emph>SHANK3</emph> impact pathways (e.g., mTOR signaling) common to multiple monogenic forms of ID and ASD, including tuberous sclerosis (TSC) and PTEN-related disorders (PRD; [<reflink idref="bib21" id="ref8">21</reflink>]; [<reflink idref="bib94" id="ref9">94</reflink>]), possibly by affecting signals from the glutamate receptors ([<reflink idref="bib82" id="ref10">82</reflink>]).</p> <hd id="AN0187547689-2">Phelan McDermid Syndrome</hd> <p>People with PMS are missing one copy (i.e., are haploinsufficient) of <emph>SHANK3</emph>, due to either a pathogenic <emph>SHANK3</emph> sequence variant or a deletion of 22q13 that includes <emph>SHANK3</emph> ([<reflink idref="bib6" id="ref11">6</reflink>]; [<reflink idref="bib114" id="ref12">114</reflink>]). <emph>SHANK3</emph> is a critical scaffolding protein responsible for promoting the growth and maturation of dendritic spines ([<reflink idref="bib88" id="ref13">88</reflink>]; [<reflink idref="bib95" id="ref14">95</reflink>]; [<reflink idref="bib97" id="ref15">97</reflink>]). Prevalence rates of PMS are not well established, with estimates ranging between 1 in 20,000 and 1 in 50,000 in the general population ([<reflink idref="bib7" id="ref16">7</reflink>]; [<reflink idref="bib88" id="ref17">88</reflink>]). Physical features may include non-specific facial dysmorphology, joint hypermobility, and dysplastic fingernails and toenails, but are largely variable except for early presence of hypotonia ([<reflink idref="bib99" id="ref18">99</reflink>]). Gastrointestinal issues are prevalent, and about a third of people with PMS have seizures at some time in life ([<reflink idref="bib72" id="ref19">72</reflink>]). PMS is often associated with pervasive delays in all areas of development, especially in early communication and motor skills ([<reflink idref="bib26" id="ref20">26</reflink>]; [<reflink idref="bib40" id="ref21">40</reflink>]; [<reflink idref="bib62" id="ref22">62</reflink>]; [<reflink idref="bib63" id="ref23">63</reflink>]; [<reflink idref="bib99" id="ref24">99</reflink>]; [<reflink idref="bib100" id="ref25">100</reflink>]).</p> <p>Moderate-to-profound ID is common among people with PMS ([<reflink idref="bib105" id="ref26">105</reflink>]), with estimates around 77% ([<reflink idref="bib98" id="ref27">98</reflink>]; [<reflink idref="bib100" id="ref28">100</reflink>]). Some studies have reported decreasing cognitive ability with age, but more recent work calls into question whether this is attributable to a true loss of skills, slower-than-expected acquisition of skills, and/or floor effects of measures ([<reflink idref="bib101" id="ref29">101</reflink>]; [<reflink idref="bib105" id="ref30">105</reflink>]). Estimates of ASD prevalence range from 50% to 80% ([<reflink idref="bib84" id="ref31">84</reflink>]; [<reflink idref="bib116" id="ref32">116</reflink>]), though these estimates may be confounded by the high rate of moderate-to-profound ID ([<reflink idref="bib101" id="ref33">101</reflink>]).</p> <p>Regression of previously acquired skills (e.g., communication, motor) in PMS may occur through adulthood ([<reflink idref="bib26" id="ref34">26</reflink>]; [<reflink idref="bib62" id="ref35">62</reflink>]). Rates of regression vary, but loss of at least one developmental skill is reported in over a third of people with PMS ([<reflink idref="bib26" id="ref36">26</reflink>]; [<reflink idref="bib100" id="ref37">100</reflink>]; [<reflink idref="bib37" id="ref38">37</reflink>]). Adolescent and adult neuropsychiatric regression has also been observed among people with PMS, with an onset often emerging between 15 and 20 years of age ([<reflink idref="bib62" id="ref39">62</reflink>]; [<reflink idref="bib63" id="ref40">63</reflink>]). Several consensus guidelines and recommendations for the management of PMS have been published ([<reflink idref="bib105" id="ref41">105</reflink>]; [<reflink idref="bib110" id="ref42">110</reflink>]; [<reflink idref="bib111" id="ref43">111</reflink>]).</p> <hd id="AN0187547689-3">Tuberous Sclerosis Complex</hd> <p>TSC is an autosomal dominant disorder caused by pathogenic sequence variants in the <emph>TSC1</emph> or <emph>TSC2</emph> genes located on chromosomes 9q34 and 16p13.3, respectively ([<reflink idref="bib18" id="ref44">18</reflink>]). <emph>TSC1</emph> and <emph>TSC2</emph> play a critical role in cell growth and division; mutations in these genes result in a multi-system disorder characterized by noncancerous tumors in the brain, heart, kidneys, lungs, and skin ([<reflink idref="bib20" id="ref45">20</reflink>]). The prevalence of TSC is estimated at 1 in 6,000 to 1 in 10,000 ([<reflink idref="bib85" id="ref46">85</reflink>]). TSC is typically identified due to the presence of seizures, which occur in 80% to 90% of people ([<reflink idref="bib65" id="ref47">65</reflink>]; [<reflink idref="bib69" id="ref48">69</reflink>]), or kidney and heart hamartomas, though both skin lesions (e.g., shagreen patches) and macrocephaly are also commonly observed in infants with TSC ([<reflink idref="bib69" id="ref49">69</reflink>]). TSC is associated with several clusters of symptoms characterized as autism-like, dysregulated behavior, eat/sleep problems, mood/anxiety symptoms, neuropsychological issues, overactivity/impulsivity, and scholastic difficulties ([<reflink idref="bib23" id="ref50">23</reflink>]).</p> <p>Prevalence estimates for ID in TSC range from 44% to 64% ([<reflink idref="bib51" id="ref51">51</reflink>]; [<reflink idref="bib58" id="ref52">58</reflink>]; [<reflink idref="bib59" id="ref53">59</reflink>]), and at least one early epidemiological study indicated that the IQ distribution had a strong left skew, with 31% of the sample falling into the profound range ([<reflink idref="bib59" id="ref54">59</reflink>]). However, studies with later-born cohorts have documented more normal distributions of IQ despite more severe seizure activity, suggesting an important role for the early detection and treatment of epileptic spasms in reducing disability associated with TSC ([<reflink idref="bib109" id="ref55">109</reflink>]). One meta-analysis documented the rate of ASD diagnosis, with estimates ranging from 20% to 69%, and found increased prevalence of autism associated with seizure onset before age 2 ([<reflink idref="bib103" id="ref56">103</reflink>]). Updated recommendations for TSC include early detection of tumors in the brain, routine skin exams, baseline EEG assessment, monitoring for neurological, psychiatric, and behavioral symptoms to initiate early intervention ([<reflink idref="bib83" id="ref57">83</reflink>]); medication for early seizure management ([<reflink idref="bib22" id="ref58">22</reflink>]; [<reflink idref="bib83" id="ref59">83</reflink>]; [<reflink idref="bib117" id="ref60">117</reflink>]); and annual screening for TSC-Associated Neuropsychiatric Disorders (TAND; [<reflink idref="bib23" id="ref61">23</reflink>]).</p> <hd id="AN0187547689-4">PTEN Hamartoma Tumor Syndrome</hd> <p>PHTS is caused by pathogenic sequence variants in <emph>PTEN</emph>, a ubiquitous tumor suppressor gene located on chromosome 10 ([<reflink idref="bib56" id="ref62">56</reflink>]). <emph>PTEN</emph> codes for a protein that helps regulate a range of cellular functions, including cell growth and division, apoptosis, and cell migration ([<reflink idref="bib77" id="ref63">77</reflink>]; [<reflink idref="bib76" id="ref64">76</reflink>]). The prevalence of PHTS is estimated at approximately 1 in 200,000 to 1 in 250,000 ([<reflink idref="bib56" id="ref65">56</reflink>]). PHTS is typically identified due to the macrocephaly that occurs in nearly all people with this condition ([<reflink idref="bib81" id="ref66">81</reflink>]). Medical complications from PHTS include an increased risk for benign hamartomas, as well as certain cancers, including thyroid, colon, and breast cancer, with specific, lifespan-screening recommendations ([<reflink idref="bib25" id="ref67">25</reflink>]). The neuropsychological profile of PHTS is heterogeneous. ID prevalence estimates range from 4% to 32% in the mild-to-moderate range ([<reflink idref="bib10" id="ref68">10</reflink>]; [<reflink idref="bib52" id="ref69">52</reflink>]), and neuropsychological deficits in attention, working memory, and executive functioning are commonly reported in PHTS ([<reflink idref="bib13" id="ref70">13</reflink>]; [<reflink idref="bib46" id="ref71">46</reflink>]; [<reflink idref="bib112" id="ref72">112</reflink>]). A large minority (between 8% and 25%) of children with PHTS are diagnosed with ASD ([<reflink idref="bib13" id="ref73">13</reflink>]; [<reflink idref="bib14" id="ref74">14</reflink>]; [<reflink idref="bib19" id="ref75">19</reflink>]; [<reflink idref="bib112" id="ref76">112</reflink>]), with a symptom profile characterized by more sensory issues and less severe social communication symptoms than idiopathic ASD ([<reflink idref="bib12" id="ref77">12</reflink>]).</p> <hd id="AN0187547689-5">The Developmental Synaptopathies Consortium</hd> <p>A primary goal of the DSC was clinical trial readiness, for which natural history research is an essential initial step ([<reflink idref="bib42" id="ref78">42</reflink>]). Natural history studies are used to define the patient population and identify clinically meaningful concepts of interest, i.e., aspects of the condition that affect how a patient feels, functions, or survives ([<reflink idref="bib43" id="ref79">43</reflink>]). Natural history studies are also used to identify, refine, or develop clinical outcome assessments and biomarkers that correlate with those concepts of interest. Finally, natural history studies may even provide external control data for rare, complex conditions where controlled treatment trials are infeasible.</p> <p>The goal of the current analysis is to inform the identification of clinically meaningful concepts and approaches to feasible and valid measurement of cognitive and behavioral phenotypes associated with these developmental synaptopathies. To accomplish this, we describe the results from baseline neurodevelopmental phenotyping performed in these natural history studies, with a focus on the feasibility and validity of assessments and their resulting data. This report is complementary to other work describing the individual disease phenotypes themselves ([<reflink idref="bib12" id="ref80">12</reflink>], [<reflink idref="bib11" id="ref81">11</reflink>]; [<reflink idref="bib35" id="ref82">35</reflink>]; [<reflink idref="bib71" id="ref83">71</reflink>]; [<reflink idref="bib70" id="ref84">70</reflink>]).</p> <hd id="AN0187547689-6">Methods</hd> <p></p> <hd id="AN0187547689-7">Participants</hd> <p>Participants were recruited from six U.S. sites for Phelan-McDermid syndrome ([<reflink idref="bib71" id="ref85">71</reflink>]), five sites for TSC ([<reflink idref="bib35" id="ref86">35</reflink>]), and four sites for PHTS ([<reflink idref="bib12" id="ref87">12</reflink>]). The inclusion criteria for all studies were English-speaking people with confirmed pathogenic findings of (<reflink idref="bib1" id="ref88">1</reflink>) PMS: pathogenic/likely pathogenic <emph>SHANK3</emph> sequence variant or deletion of 22q13 that affects the <emph>SHANK3</emph> gene, (<reflink idref="bib2" id="ref89">2</reflink>) TSC: <emph>TSC1</emph> or <emph>TSC2</emph> pathogenic/likely pathogenic variants, or (<reflink idref="bib3" id="ref90">3</reflink>) PHTS: pathogenic/likely pathogenic variants in <emph>PTEN</emph> or deletions of <emph>PTEN</emph>. Participants were ages 3–21 years, except for two participants with TSC who were 24 and 35 months old. Parents/guardians provided consent, and when appropriate, participants provided assent. The protocols were approved by a central institutional review board.</p> <hd id="AN0187547689-8">Study Procedures</hd> <p>Each protocol enacted a systematic neurodevelopmental assessment framework designed for investigating rare genetic conditions associated with ID ([<reflink idref="bib101" id="ref91">101</reflink>]). This framework employs multiple methods (observer-rated outcomes, clinician-rated outcomes, and direct assessment) and multiple assessments (i.e., different measures of the same concept) to yield estimates of functioning across the full range of phenotypic expression observed in these heterogeneous populations. Based on the extant literature, the investigators' clinical experience with the conditions, and input from parent advocacy group members who served on the steering committees, clinical outcome assessments for the following concept domains were selected: intellectual functioning (including processing speed and working memory), visual-motor integration and executive functioning, language, adaptive functioning, challenging behavior, and ASD symptoms. Supplementary materials detailing the assessment framework and the original list of measures may be found online at a link provided at the end of this paper.</p> <p>Results presented herein are data collected at the first (baseline) of three annual visits in this prospective, natural history study. Psychological and behavioral evaluations were conducted at each site by licensed clinicians or psychometrists (technicians supervised by a licensed psychologist). Annual network-wide consensus coding meetings were held to review reliability and measurement challenges. Participants typically completed in-person assessments over 1–2 days while parents/caregivers completed questionnaires and interviews.</p> <hd id="AN0187547689-9">Measures</hd> <p>The measures comprising the systematic neurodevelopmental assessment framework are described below by domain. The selection of appropriate clinical outcome assessments and endpoints (i.e., the scores used from those assessments) required the consideration of several factors, including: (<reflink idref="bib1" id="ref92">1</reflink>) the standardization age range (see supplementary materials), (<reflink idref="bib2" id="ref93">2</reflink>) the impact of planned modifications to standardized procedures on scoring and interpretation, and (<reflink idref="bib3" id="ref94">3</reflink>) the minimum developmental levels required to evaluate each developmental domain (e.g., social communication skills in children with developmental levels &gt; 12 months; [<reflink idref="bib101" id="ref95">101</reflink>]).</p> <hd id="AN0187547689-10">Intellectual Functioning, Language, and Adaptive Behavior</hd> <p></p> <hd id="AN0187547689-11">Intellectual Functioning.</hd> <p>Direct assessments of intellectual functioning were selected from the following hierarchy based on clinical judgment of the participant's chronological age, language level, and estimated developmental level:</p> <p></p> <ulist> <item> Stanford–Binet, Fifth Edition ([<reflink idref="bib91" id="ref96">91</reflink>]). The Stanford–Binet is a traditional IQ test appropriate for people aged 2–85+ years. The Stanford–Binet offers Full Scale IQ (FSIQ), Nonverbal IQ (NVIQ), and Verbal IQ (VIQ) standard scores which range from 40 to 160 (population mean ± SD = 100 ± 15).</item> <p></p> <item> Differential Ability Scales, Second edition (DAS-II; [<reflink idref="bib33" id="ref97">33</reflink>]). The DAS-II content is transitionary between developmental and traditional IQ tests, depending on the form (Early Years or School Age). The DAS-II is normed for ages 2 years, 6 months to 17 years, 11 months. The score used for FSIQ on the DAS-II was General Conceptual Ability Core Cluster; NVIQ and VIQ were the Nonverbal and Verbal Composite Core Clusters, respectively. These standard scores range from 45–165 for FSIQ and 50–150 for NVIQ and VIQ (population mean ± SD = 100 ± 15).</item> <p></p> <item> Mullen Scales of Early Learning (MSEL; [<reflink idref="bib79" id="ref98">79</reflink>]). The MSEL is a developmental test normed for children from birth to 5 years, 8 months, and was used to provide estimates of cognitive functioning when the other measures were not feasible. To facilitate comparability with FSIQ, NVIQ, and VIQ from the other tests, developmental quotients (DQ; also known as ratio IQs) were calculated using the average age equivalents for the Fine Motor and Visual Reception (nonverbal; NVDQ) or Expressive Language and Receptive Language (verbal; VDQ) subscales (FSDQ = average of NVDQ and VDQ). DQs have no population distribution and a natural floor of 0, with a ceiling of infinity (see Farmer, Thurm et al., 2025).</item> </ulist> <p>For some participants with significant ID, it was not possible to achieve a basal score on the age-appropriate test, in which case the next-lower test in the hierarchy was administered. This resulted in some out-of-age-range testing with the MSEL. This commonly used approach has been shown to yield scores that correlate with but exhibit varying levels of mean difference with IQ scores ([<reflink idref="bib8" id="ref99">8</reflink>]; [<reflink idref="bib38" id="ref100">38</reflink>]). For all cognitive scores, higher values indicate better relative performance. For descriptive purposes, scores are also categorized by the commonly used ID designations ([<reflink idref="bib4" id="ref101">4</reflink>]): No ID (standard score ≥ 70), Mild (50–69), Moderate (35–49), Severe/Profound (below 35/under 20).</p> <hd id="AN0187547689-12">Language.</hd> <p>Direct assessments of receptive and expressive language skills were administered to participants with developmental and learning readiness skills (e.g., attending to and discriminating 2D stimuli). The Peabody Picture Vocabulary Test<emph>,</emph> Fourth Edition (PPVT-4; [<reflink idref="bib30" id="ref102">30</reflink>]) and Expressive Vocabulary Test, Second Edition (EVT-2; [<reflink idref="bib113" id="ref103">113</reflink>]) were used to directly assess receptive and expressive vocabulary, respectively. These tests are normed for ages 2 years, 6 months to 90+ years, and each provides a standard score ranging 20–160 (population distribution: 100 ± 15). Higher scores indicate better relative performance.</p> <hd id="AN0187547689-13">Adaptive Behavior.</hd> <p>The Vineland Adaptive Behavior Scales, Second Edition (Vineland-II; [<reflink idref="bib102" id="ref104">102</reflink>]), was used to evaluate adaptive behavior. For consistency with previous studies, the parent/caregiver survey form was used in TSC and PHTS, and the semi-structured clinician-led interview form was used for PMS. Both forms provide domain-level standard scores that range from 20–160 (population distribution: 100 ± 15) and subdomain scaled scores ranging from 1–23 (population distribution: 15 ± 3). Higher scores indicate better relative adaptive functioning. Due to the prominence of motor delays in the PMS phenotype ([<reflink idref="bib44" id="ref105">44</reflink>]), the Motor Skills domain was administered for PMS participants regardless of participant age (normative data are available only through age 6 years, 11 months and older adults). As a result, Motor Skills age equivalents, but not standard scores, were available for these individuals.</p> <hd id="AN0187547689-14">Behavioral Measures</hd> <p></p> <hd id="AN0187547689-15">Challenging Behaviors.</hd> <p>The validity of clinical outcome assessments for challenging behaviors is compromised for people with intellectual and developmental disabilities (IDD) because diagnostic criteria are primarily defined in the context of typical development. For instance, behavior such as running in inappropriate situations may reflect alternative (maladaptive) communication patterns in younger and/or cognitively impaired populations but may be captured as overactivity by standardized challenging behavior measures. With this limitation in mind, we selected two widely used caregiver-report measures of challenging behaviors: the Aberrant Behavior Checklist–Community Version (ABC-C; [<reflink idref="bib2" id="ref106">2</reflink>]) and the Child Behavior Checklist/Adult Behavior Checklist (CBCL/ABCL; [<reflink idref="bib1" id="ref107">1</reflink>]).</p> <p>The ABC-C was originally developed for people with IDD in residential settings, having since been revised for community settings, with psychometric evaluations in a variety of samples with all levels of ID and other developmental disabilities, such as ASD ([<reflink idref="bib3" id="ref108">3</reflink>]). The ABC-C yields sum total scores on five subscales: Irritability, Social Withdrawal, Stereotypic Behavior, Hyperactivity/Noncompliance, and Inappropriate Speech. The subscale sum scores are typically used for research purposes, though some comparison data are provided by the test developer for the calculation of norm-referenced scores. In this study, we used the ABC community samples ([<reflink idref="bib78" id="ref109">78</reflink>]), which included some participants with mild ID to guide interpretation of the clinical significance of ABC subscale scores.</p> <p>The CBCL/ABCL is a screening tool for emotional and behavioral problems, with forms standardized for ages 1.5 years through adulthood. Sex-based normative data for each age-based form are provided, based on general population development samples. The CBCL yields T-scores with a range of 50–100 (population distribution: 50 ± 10). Higher scores indicate more symptoms relative to age peers. The CBCL/ABCL was standardized in typically developing populations with studies pointing to concerns with reliability and validity in those with moderate, severe, and profound ID ([<reflink idref="bib64" id="ref110">64</reflink>]) and distinct patterns observed in children with ASD and NVIQ in the ID range ([<reflink idref="bib89" id="ref111">89</reflink>]). Despite these concerns about the validity of the instrument, we included the CBCL to enable comparisons with extant literature, particularly in PHTS and TSC ([<reflink idref="bib24" id="ref112">24</reflink>]; [<reflink idref="bib28" id="ref113">28</reflink>]; [<reflink idref="bib34" id="ref114">34</reflink>]; [<reflink idref="bib87" id="ref115">87</reflink>]). However, to improve the assumption of measurement invariance across the development sample and the current studies, thereby reducing the potential to over-or under-estimate behavioral challenges in children with severe to profound ID, we considered CBCL administrations to be valid for analysis only when the child had an NVIQ ≥70.</p> <hd id="AN0187547689-16">ASD.</hd> <p>ASD phenomenology was measured using multiple methods, including caregiver reports, developmental history, and clinician-administered assessments. Within the PMS and TSC studies, participants received all clinician- and caregiver-rated instruments described below. In the PHTS study—for which groups were categorized by ASD status for an associated clinical trial (NCT#02991807)—clinician-administered instruments were completed after a <emph>Diagnostic and Statistical Manual of Mental Disorders</emph> (5th ed.; DSM-5; [<reflink idref="bib5" id="ref116">5</reflink>]) checklist interview and were administered only to the subset of participants who either presented with suspected autism or had a prior ASD diagnosis ([<reflink idref="bib12" id="ref117">12</reflink>]).</p> <p>The Social Responsiveness Scale (SRS-2; [<reflink idref="bib17" id="ref118">17</reflink>]) is a caregiver-reported ASD screening instrument that is frequently used in neurodevelopmental research ([<reflink idref="bib11" id="ref119">11</reflink>]). There are three forms (preschool, school age, adult) that are administered based on chronological age. While T-scores are available for several subscales on the SRS-2, it was not validated in people with ID and/or significant expressive language delays ([<reflink idref="bib17" id="ref120">17</reflink>]; [<reflink idref="bib57" id="ref121">57</reflink>]) and research has demonstrated reduced validity in ID ([<reflink idref="bib53" id="ref122">53</reflink>]), including one study in PMS ([<reflink idref="bib49" id="ref123">49</reflink>]) and another in fragile X syndrome ([<reflink idref="bib60" id="ref124">60</reflink>]). To address these limitations, this study utilizes a 16-item short form that retains only items that exhibited measurement invariance across sex, age, expressive language, adaptive behavior, and NVIQ ([<reflink idref="bib75" id="ref125">75</reflink>]; [<reflink idref="bib106" id="ref126">106</reflink>]). While a limitation of the short form is a lack of clinical cut-off scores, we felt that the ability to use the short form score as an index of severity made it the preferable metric. Additionally, previous work demonstrated the validity of this approach for the PMS study ([<reflink idref="bib49" id="ref127">49</reflink>]). Raw sum scores on the short form range from 0 to 48, where higher scores indicate more symptoms.</p> <p>The Repetitive Behavior Scale–Revised (RBS-R) is a caregiver-report questionnaire developed for individuals with ID with and without ASD to characterize repetitive behaviors in IDDs (including ASD; [<reflink idref="bib9" id="ref128">9</reflink>]). The RBS-R was originally developed with six subscales: Ritualistic Behavior, Sameness Behavior, Self-Injurious Behavior, Stereotyped Behavior, Compulsive Behavior, and Restricted Behavior; current standards, used here, condense the Ritualistic Behavior and Sameness Behavior subscales into one (Rituals/Sameness; [<reflink idref="bib67" id="ref129">67</reflink>]). Higher raw sum scores indicate more severe problems.</p> <p>The Autism Diagnostic Observation Schedule (2<sups>nd</sups> ed.; ADOS-2) is a clinician-administered assessment of symptoms related to an ASD diagnosis. The appropriate ADOS-2 module is selected based on the participant's age and language level. The Autism Diagnostic Interview, Revised (ADI-R) is a clinician-rated, semi-structured interview about past and current symptoms related to an ASD diagnosis. Both the ADOS-2 and ADI-R yield sum scores in several domains, which are converted to cutoffs reflecting the likelihood of an ASD diagnosis. The ADOS-2 and ADI-R were both administered by research-reliable clinicians, who underwent periodic reliability checks during the study. The DSM-5 checklist was completed by licensed clinicians (e.g., neurologist, psychiatrist, psychologist) indicating their judgment of the presence or absence of each of the ASD diagnostic criteria, based on all available information. Together, these tools comprise the gold-standard research assessment for ASD.</p> <p>Of note, the development samples for the ADOS-2 and ADI-R were largely without severe-to-profound ID, and both the test developers ([<reflink idref="bib73" id="ref130">73</reflink>]; [<reflink idref="bib92" id="ref131">92</reflink>]) and other researchers ([<reflink idref="bib90" id="ref132">90</reflink>]; [<reflink idref="bib108" id="ref133">108</reflink>]) have noted that the specificity of the instruments can be much worse for individuals with low mental age. For example, the ADI-R and ADOS-2 are standardized for participants with NVIQ scores ≥70, but improved specificity is found for mental age ≥2 years ([<reflink idref="bib61" id="ref134">61</reflink>]; [<reflink idref="bib74" id="ref135">74</reflink>]). The ADOS-2 has an additional criterion for independent walking. We followed manual-based recommendations, requiring a minimum 18-month nonverbal mental age for both the ADI-R and ADOS-2 (i.e., Modules 1–4) and independent walking for the ADOS-2 for valid administration.</p> <hd id="AN0187547689-17">ASD Classification.</hd> <p>After reviewing all available data, the clinician assigned a consensus diagnosis of ASD or non-ASD and endorsed a degree of certainty on a scale of 1–5, where higher scores reflected greater clinical certainty. As noted above, in PHTS, administration of clinician-administered scales, i.e., the ADOS-2 and ADI-R, varied ([<reflink idref="bib12" id="ref136">12</reflink>]). As such, consensus diagnoses for the full PHTS sample reflect different data sources.</p> <hd id="AN0187547689-18">Analytic Approach</hd> <p>Evaluation of the summary statistics within and across cohorts were used to accomplish the goals of this descriptive study. As comparison across groups was meant to inform the development of harmonized assessment strategies for phenotypically similar groups, rather than to test hypothesized differences across groups, statistical comparison was not performed. Visual inspection of the data determined whether mean and standard deviation (for normal distributions) or median and interquartile range (IQR; for non-normal distributions) were used. The supplementary materials detail the administration rates for each measure based on the standardization criteria outlined in the Measures section, but the summary statistics reflect only the valid administrations. Missingness was both informative (e.g., the participant did not meet the eligibility criteria for a given test or could not achieve the minimum score possible on the test) and non-informative (e.g., related to logistical or administration errors). However, it was not possible to distinguish these cases in the database, and so all missing data were treated equally.</p> <hd id="AN0187547689-19">Results</hd> <p></p> <hd id="AN0187547689-20">Demographic and Clinical Characteristics</hd> <p>More than half of each group was male, and all groups were predominately White and non-Hispanic (Table 1). The mean (± SD) age of participants at enrollment across conditions was approximately 8 years (PMS: 8.41 ± 4.59; TSC: 8.37 ± 4.59; PHTS: 8.88 ± 4.82). Seizures and sleep disturbances were among the most commonly reported medical conditions, and ASD and ADHD were the most commonly reported psychiatric diagnoses across all three conditions (Table 1).</p> <p>Table 1 Participant Demographic and Clinical Characteristics</p> <p>PHOTO (COLOR)</p> <hd id="AN0187547689-21">Intellectual Functioning, Language, and Adaptive Functioning</hd> <p></p> <hd id="AN0187547689-22">Intellectual Functioning</hd> <p>For all three conditions, the cognitive profile was relatively even across VIQ and NVIQ (Table 2). Most participants in the PMS sample were in the severe/profound range of ID, the majority of the TSC sample fell into the mild-to-moderate ID range, and the majority of the PHTS sample was in the borderline-to-average range of intellectual functioning (Figure 1C). However, visual inspection of the score distribution yielded important information about the impact of the combination of scores from multiple tests. There was a clear effect of test floor, resulting in distributional peaks at the floors of the Stanford–Binet and DAS-II, while the MSEL DQ scores have a relatively normal distribution (Figure 1A).</p> <p>PHOTO (COLOR): Figure 1 Intellectual Functioning and Adaptive Functioning in DSC-1 Cohort Note. (A) Nonverbal IQ/DQ (developmental quotient) and (B) Vineland-II Adaptive Behavior Composite (ABC) standard score distributions. (C) Nonverbal IQ/DQ (NVIQ) categorized according to ICD 10.</p> <p>Table 2 Quartiles and Range of Intellectual Functioning, Language, and Adaptive Functioning by Synaptopathies</p> <p>PHOTO (COLOR)</p> <hd id="AN0187547689-23">Adaptive Functioning</hd> <p>Vineland-II caregiver interview (PMS) and caregiver survey (TSC/PHTS) standard scores indicated a degree of impairment similar to the cognitive scores, though the lower floor for the MSEL DQs versus standard scores allowed for a larger cognitive/adaptive behavior discrepancy in the PMS sample (Table 2, Figure 1B). Within condition, the profiles were even, with similar scores across domains. However, all conditions exhibited a great deal of variability, with scores spanning the full range of impairment.</p> <hd id="AN0187547689-24">Language</hd> <p>Only one-third of the PMS participants were able to complete the PPVT-4 and EVT-2, compared to about two-thirds of the TSC sample and the majority of the PHTS sample (Table 2). Within all three conditions, the scores among those able to take the test were variable, ranging from extremely low to above average. For each condition, typical performance was similar for PPVT-4 and EVT-2, though the subsamples with valid data differed slightly.</p> <hd id="AN0187547689-25">Challenging Behavior</hd> <p>Across conditions, clinical elevations in ABC scores were observed for over 40% of each cohort on the Stereotypy and Lethargy subdomains (Table 3). Clinical elevations in Irritability, a common treatment target in syndromic IDDs, was lowest in the PHTS cohort (32%) and highest in TSC (58%). Another common treatment target, Hyperactivity, was reported at higher rates in PMS (63%), followed by TSC (53%) and PHTS (30%).</p> <p>Table 3 Challenging Behavior Measures by Synaptopathies</p> <p>PHOTO (COLOR)</p> <p>The validity of the CBCL was limited by the rate of ID: fewer than 10 participants in the PMS sample, less than one-third of the TSC sample, and only about half of the PHTS received valid CBCL administrations. Limiting evaluation to the TSC and PHTS subsamples without ID, a high rate of clinically elevated Internalizing Symptoms scores was observed for both cohorts (TSC, 52%; PHTS, 41%). Externalizing Symptoms scores were clinically elevated for 41% of the TSC sample but only 12% of the PHTS sample.</p> <hd id="AN0187547689-26">ASD Symptoms and Diagnosis</hd> <p>Scores on the RBS-R reflected low rates of repetitive behaviors and restricted interests in PMS, TSC, and PHTS evaluated for ASD. The SRS short-form scores are shown in Table 4, alongside T-scores for participants with NVIQ ≥70.</p> <p>Table 4 Social-Communication, Repetitive Behavior, and ASD Symptoms by Synaptopathies</p> <p>PHOTO (COLOR)</p> <p>Table 5 summarizes the results of the ASD diagnostic evaluation. In the PMS and TSC studies, all participants were systematically assessed for ASD. A consensus diagnosis of ASD was common in both cohorts (PMS, 59%; TSC, 44%); the rate of parent-reported historical diagnosis was higher for PMS (69%) but similar for TSC (47%). The validity of the ADI-R and ADOS-2 were limited by the rate of profound ID in the PMS and TSC cohorts. Among those with valid assessments, the tools had good sensitivity (ADI-R: PMS, 88%; TSC, 83%; ADOS-2: PMS, 96%; TSC, 94%). While the specificity of both tools was good in the TSC cohort (ADI-R, 88%; ADOS-2, 91%), it was poor for PMS (ADI-R, 41%; ADOS-2, 65%).</p> <p>Table 5 ASD Classification by Measure and Condition</p> <p>PHOTO (COLOR)</p> <p>The rate of consensus ASD diagnosis in PHTS was 62%. PHTS participants received comprehensive ASD evaluations based on clinical suspicion or history of diagnosis (87% of those assessed had a historical diagnosis); among these individuals, the sensitivity of the ADI-R and ADOS-2 was excellent (90%). However, the selective autism screening procedures for PHTS described in the Methods section limit interpretation of these psychometric data.</p> <hd id="AN0187547689-27">Discussion</hd> <p>The DSC is a network of large, multisite, natural history studies of the rare genetic conditions TSC, PMS, and PHTS. A primary goal of the DSC was clinical trial readiness, enabling nimble response to ongoing technological developments that may yield life-changing interventions for these conditions. A major aspect of clinical trial readiness is having identified the concepts of interest, or the aspects of the phenotype which affect how a person feels, functions, or survives, as well as having a good understanding of how best to assess those concepts. However, this is particularly challenging for natural history studies of rare genetic conditions, where the populations are small and heterogeneous, and the developmental nature of relevant concepts means that their manifestation necessarily changes across development. In the current manuscript, we addressed these needs by identifying areas of clinical interest and describing the scope and limitations of conventional measurement strategies for these concepts in neurologically and medically complex genetic syndromes. The results of this project will inform trial planning for these conditions, as well as other rare genetic conditions affecting neurodevelopment that share similar phenotypic features.</p> <hd id="AN0187547689-28">Adaptive Functioning</hd> <p>Consistent with extant literature, ID was most common for participants in the PMS study and least common in the PHTS study. However, the full range of impairment was observed within all three conditions. Deficits in adaptive behavior, or the ability to perform the skills necessary to achieve an age-appropriate level of independence, are a core component of the ID diagnosis. Adaptive behavior is of clear clinical relevance, as it reflects the cumulative and global effects on functioning of the disease. As is common for genetic conditions affecting neurodevelopment, developmental delay, motor impairment, and communication impairments are among the top concerns for all three conditions in the DSC (e.g., [<reflink idref="bib45" id="ref137">45</reflink>]; [<reflink idref="bib50" id="ref138">50</reflink>]; [<reflink idref="bib55" id="ref139">55</reflink>]; [<reflink idref="bib68" id="ref140">68</reflink>]). These domains are all assessed by measures of adaptive behavior. In the DSC, adaptive behavior was assessed with the Vineland-II. Because there are no IQ or mental age restrictions on use of the Vineland-II, it was feasible for all participants in all three cohorts. Thus, adaptive behavior emerged as a key clinical concept and candidate for future use in clinical trials. However, we note several issues for further consideration.</p> <p>The DSC employed both the caregiver survey and the semi-structured interview form of the Vineland-II. While differences in administration (respondent and basal/ceiling rules) preclude their interchangeable use, there are several factors to consider in selecting the most appropriate form for a new study. First, clinician time may be reduced when using the survey form, though the manual ([<reflink idref="bib102" id="ref141">102</reflink>]) notes that a clinician should review the responses with the caregiver (p. 44). For populations where more severe disability is common, however, the manual cautions that "... parents often report enjoying the semi-structured interview and find it comforting to be able to describe what their child does [as in the semi-structured interview] rather than what he or she doesn't do [as in the survey]" (p. 11).</p> <p>Second, Vineland-II adaptive behavior scores may yield higher-than-expected standard scores compared to cognitive scores, especially for younger participants ([<reflink idref="bib47" id="ref142">47</reflink>]). The role of age in the interpretation of the adaptive behavior concept is important to consider. Younger individuals are expected to do fewer things independently, and impairment is likely to become more apparent as a person ages. Indeed, Vineland-II scores tend to decline over age in samples with ID (e.g., [<reflink idref="bib107" id="ref143">107</reflink>])—a phenomenon observed in the PMS sample (see [<reflink idref="bib104" id="ref144">104</reflink>]). This has been partially addressed by additional items at lower levels of ability in the Vineland-3, leading to systematically lower scores on that instrument ([<reflink idref="bib36" id="ref145">36</reflink>]), but the issue is fundamental to the concept and therefore remains. Additionally, the use of DQs for some participants with severe cognitive impairment exacerbated the issue, since DQs do not have a floor (see PMS scores in Table 2).</p> <p>Cognitive ability, the other concept core to the ID diagnosis, is also strongly aligned with parent/caregiver concerns and is de facto the concept used to estimate ID in clinical research. The heterogeneity in cognitive ability observed in the DSC creates considerable challenges for clinical trial design. The first major issue is the selection of a single clinical outcome assessment. Following a hierarchical testing method for severe-to-profound IDD populations described by [<reflink idref="bib101" id="ref146">101</reflink>], we planned to use traditional IQ testing where possible, substituting developmental testing where necessary. The advantage of this approach is that it allows for an estimate of cognitive functioning for the entirety of the sample, whereas using only traditional IQ tests would have resulted in a high rate of missing data; for the PMS sample, 40% required out-of-age-range testing and would have had missing data if only the Stanford–Binet were used. While the rates were much lower for TSC (6%) and PHTS (2%), we note that any systematic missingness is unacceptable for clinical endpoints.</p> <p>However, the results of this study highlighted a few limitations of this hierarchical approach. In order to combine estimates across tests, norm-referenced scores (or approximations thereof) were used. But even when participants could achieve basal on a traditional IQ test, we observed significant floor effects for all three conditions (see Figure 1A). While floor effects may be tolerable in a diagnostic context where the goal is to identify impairment, floor effects in a clinical trial context obscure variability and reduce responsiveness to change ([<reflink idref="bib39" id="ref147">39</reflink>]). For the participants who could not receive standard scores, we used DQs, which are considered analogous. However, the use of DQ is compromised by significant concerns about validity, especially for older and minimally verbal people ([<reflink idref="bib86" id="ref148">86</reflink>]). Other approaches, including Z-scores, could also be considered if norm-referenced scores are required (Farmer, advance online publication).</p> <p>Communication is another clinically meaningful concept ([<reflink idref="bib55" id="ref149">55</reflink>]). The Vineland measures caregiver-reported functioning in receptive, expressive, and written communication, and, as described above, it was the only measure applicable across the full range of age and ability in this study. However, we also explored the feasibility of direct assessment using receptive and expressive vocabulary tests (i.e., EVT-2, PPVT-4) and found these tests were appropriate only for samples with less severe ID. Thus, potential cross-syndrome treatment or phenotyping efforts focused on direct language assessment may require ability-based inclusion criteria, and interpretation must be tempered by consideration of systematic missingness related to severe phenotypes in a particular domain (i.e., ID).</p> <hd id="AN0187547689-29">ASD Symptoms and Diagnosis</hd> <p>Consensus ASD diagnosis was common in all three cohorts (PMS, 59%; TSC, 44%; PHTS, 62%), marking it as a potential concept of interest. For PMS and TSC, where recruitment was unrelated to ASD status, a significant methodological strength was the systematic approach to the ASD diagnostic process. The diagnosis of ASD can be challenging in the context of ID, because many of the deficits required of an ASD diagnosis occur to some extent in all individuals with ID ([<reflink idref="bib108" id="ref150">108</reflink>]). Here, we ensured that our direct assessment (ADOS-2) and observer/clinician rated assessment (ADI-R) were analyzed only in people meeting developmental and physical/sensory requirements of the measures. Importantly, this meant that these gold-standard assessments were not appropriate for half of the PMS sample and up to 30% of the TSC sample, limiting their utility in future clinical trials. Conditioned upon a nonverbal mental age of at least 18 months, the sensitivity of the ADOS-2 and ADI-R was good in both cohorts, but their specificity was poor for PMS—likely due to ID severity.</p> <p>ASD diagnosis is less likely than a dimensional assessment of symptom severity to be part of a clinical trial endpoint. The DSC studies contained two such measures, the SRS-2 and the RBS-R. Both assessments are commonly used observer-reported assessments of ASD symptoms, but an important difference is their applicability for individuals with ID. The RBS-R was developed generally for IDD (versus ASD specifically), and the validity of the instrument was therefore unaffected by the rate of ID in the samples. Scores on the RBS-R were relatively low across conditions relative to standardization groups ([<reflink idref="bib67" id="ref151">67</reflink>]), indicating that the severity of behavior is not abnormal compared to general IDD and that RRB is not a unique clinical feature of the conditions, though it may still be meaningful. However, if repetitive behaviors present as clinically important concerns to families/caregivers, the low scores observed here indicate that the RBS-R may not exhibit sufficient responsiveness in a clinical trial context.</p> <p>The SRS, on the other hand, was not developed for use in people with ID. We addressed the variety of empirical evidence pointing to the lack of validity of the SRS when employed for people with ID, problem behavior, and/or limited language ([<reflink idref="bib49" id="ref152">49</reflink>]; [<reflink idref="bib53" id="ref153">53</reflink>]) by using the 16-item short form ([<reflink idref="bib106" id="ref154">106</reflink>]). The advantage of this approach is confidence that scores are more reflective of social communication behaviors than the participants' age, language level, cognitive ability, or challenging behaviors. A limitation of the short form is that no normative data exist, making it difficult to contextualize the scores. However, the mean scores in each condition indicate sufficient variability to detect a potential treatment effect, suggesting that the SRS short form may be a good candidate outcome measurement of social communication symptoms in predominately ID samples.</p> <hd id="AN0187547689-30">Challenging Behaviors</hd> <p>Challenging behaviors can have a significant impact on quality of life and are rated by parents/caregivers as being an important area of concern ([<reflink idref="bib55" id="ref155">55</reflink>]), but differences from typically developing individuals in the function or cause of topographically similar behaviors complicates their assessment. Because people with ID were not included in the development of commonly used psychiatric screeners like the CBCL, domain-level scores are difficult to interpret, and normative data are likely not relevant. In the current study, we addressed this by using CBCL data only from participants with NVIQ scores ≥70. As a result, however, the CBCL was not considered valid for most PMS and TSC participants and half of PHTS participants, making it a poor choice for outcome measurement in future clinical trials.</p> <p>Recognizing the limitations of the CBCL and being aware that measures validated in samples of people with IDD—such as the Developmental Behaviour Checklist ([<reflink idref="bib31" id="ref156">31</reflink>]) and the ABC—exist, we also employed the ABC. This scale is widely used in clinical trials, especially the Irritability subscale. Across all three conditions, mean scores were elevated in comparison to age- and sex-based normative data from special education settings but similar to scores from conditions with similar levels of ID severity (J. Miller, personal communication, November 1, 2024). For some subscales, such as Stereotypy or Inappropriate Speech, the numerically small mean scores suggest that responsivity might be limited in a clinical trial context, so if these are concepts of interest, the ABC may not be a good choice for outcome assessment.</p> <hd id="AN0187547689-31">Limitations and Future Directions</hd> <p>While there were considerable obstacles encountered in the outlined neurobehavioral approach, the careful, systematic cognitive and behavioral phenotyping protocol was crucial to identifying limitations and guiding future directions in the selection of cognitive and behavioral measurements for subsequent studies. The detailed descriptive analysis here points to the importance of adapting protocols to account for heterogeneity within syndromic IDDs, as well as within and across clinically meaningful concepts: cognition, communication, and behavioral challenges. Additionally, while psychometric data are a starting point for measurement selection in phenotyping and outcome protocols, they may require additional scrutiny when applied to special populations ([<reflink idref="bib40" id="ref157">40</reflink>]; [<reflink idref="bib48" id="ref158">48</reflink>]). We also note an important limitation in the representativeness of the cohorts in DSC-1, which were predominantly White and non-Hispanic. This limitation is likely due to challenges with equity and accessibility in genetic testing and research recruitment generally ([<reflink idref="bib15" id="ref159">15</reflink>]), as well as study processes which were limited to English-speaking participants. Further, we are unable to analyze how specific medical comorbidities (e.g., epilepsy), significant life changes, the onset of new psychiatric problems, or significant regression of skills affect developmental trajectories, given that the sample included a wide age range of youth and the analysis covers only the first time point.</p> <p>We identified several commonly used measures that may be appropriate for use in future clinical trials across disease and ability levels (e.g., Vineland), but found significant limitations in commonly used instruments (e.g., CBCL), which may render them invalid for trials including samples with ID. While it would be helpful to the field if natural history studies—such as this one—could offer recommendations about which measures should or should not be used in clinical trials across varying severity levels of ID, many other factors must also be considered. These include trial- or condition-specific elements such as participant age, study timeframe, the need for sensitivity to change, and other features unique to the condition.</p> <p>It is important to note that the current descriptive analysis is based exclusively on cross-sectional data, so we did not address sensitivity to change. For example, instead of the standard scores described here, theory ([<reflink idref="bib32" id="ref160">32</reflink>]; [<reflink idref="bib39" id="ref161">39</reflink>]) and quantitative data ([<reflink idref="bib41" id="ref162">41</reflink>], [<reflink idref="bib40" id="ref163">40</reflink>]; [<reflink idref="bib66" id="ref164">66</reflink>]) support the use of person ability scores for clinical trial endpoints (e.g., Stanford–Binet Change Sensitive Scores, DAS Ability Scores, or growth scales values for the EVT, PPVT, and Vineland) for developmental domains like cognitive and communication. This is because ability scores are not subject to normative floor effects, are measured at the interval level, and are more responsive to change than normative scores. Crucially, however, the use of person ability scores is not compatible with a hierarchical approach to testing, because they cannot be compared across tests. These considerations led to our recommendation to prioritize adaptive functioning as a clinical trial endpoint, capitalizing on it as a well-established clinical outcome assessment that contain ability scores (i.e., Vineland-3) and minimal floor effects across age and ability levels.</p> <p>While we identified several areas where clinically significant symptoms were observed, we note that our assessment of clinical significance was based on relative profiles from standardized datasets (e.g., in comparison to the general population or people with IDD). Patient and caregiver input on the meaningfulness of the measured concepts, the assessments, and what constitutes meaningful change in those assessments is an important and ongoing research area for genetic conditions associated with neurodevelopmental disorders ([<reflink idref="bib16" id="ref165">16</reflink>]; [<reflink idref="bib29" id="ref166">29</reflink>]; [<reflink idref="bib50" id="ref167">50</reflink>]; [<reflink idref="bib54" id="ref168">54</reflink>]). The development of patient-reported outcome measures ([<reflink idref="bib80" id="ref169">80</reflink>]) may be used in tandem with standardized measures. Many of the symptoms observed to occur at high rates in these samples are known to be associated with poorer ratings of family quality of life, and so measures of the effects of these symptoms on the family quality of life require exploration.</p> <p>In summary, the current report highlights foundational details on the application of commonly used cognitive/behavioral tools in studies of PMS, TSC, and PTEN and stresses important measurement, clinical, consumer, and contextual considerations to evaluate for clinical trial readiness.</p> <p> <emph>Portions of this project were presented at the 2024 Gatlinburg Conference on Intellectual and Developmental Disabilities and the 2024 International Association for the Scientific Study of Intellectual and Developmental Disabilities. The Developmental Synaptopathies Consortium (U54NS092090) is part of the National Center for Advancing Translational Sciences (NCATS) Rare Diseases Clinical Research Network (RDCRN) and is supported by the RDCRN Data Management and Coordinating Center (DMCC) (U2CTR002818). The RDCRN is an initiative of the Office of Rare Diseases Research (ORDR), NCATS, funded through a collaboration between NCATS and the National Institute of Neurological Disorders and Stroke (NINDS), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), and the National Institute of Mental Health (NIMH) of the National Institutes of Health. The NIMH Intramural Research Program (1ZICMH002961) also supported it. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health (NIH).</emph> </p> <p> <emph>We are sincerely indebted to the generosity of the families and patients in PMS, PTEN, and TSC clinics across the United States who contributed their time and effort to these studies. We also thank the Phelan-McDermid Syndrome Foundation, the PTEN Hamartoma Tumor Syndrome Foundation, the PTEN Research Foundation, and the TSC Alliance for their continued support.</emph> </p> <p>Supplementary materials detailing the assessment framework and the original list of measures may be found online at https://doi.org/10.31234/osf.io/gqvr8_v1.</p> <ref id="AN0187547689-32"> <title> References </title> <blist> <bibl id="bib1" idref="ref5" type="bt">1</bibl> <bibtext> Achenbach, T. M. (1999). The Child Behavior Checklist and related instruments. In Maruish M. E. (Ed.), The use of psychological testing for treatment planning and outcomes assessment (2nd ed., pp. 429–466). Lawrence Erlbaum Associates Publishers.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref6" type="bt">2</bibl> <bibtext> Aman, M. G., &amp; Singh, N. N. (1994). The Aberrant Behavior Checklist–Community Version. Slosson Education Publications, Inc.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref7" type="bt">3</bibl> <bibtext> Aman, M. G., &amp; Singh, N. N. (2017). Aberrant Behavior Checklist manual (2nd ed.). Slosson Educational Publications.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref101" type="bt">4</bibl> <bibtext> American Medical Association. (2018). ICD-10-PCS 2019: The complete official codebook.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref116" type="bt">5</bibl> <bibtext> American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596</bibtext> </blist> <blist> <bibl id="bib6" idref="ref11" type="bt">6</bibl> <bibtext> Anderlid, B. M., Schoumans, J., Annerén, G., Tapia-Paez, I., Dumanski, J., Blennow, E., &amp; Nordenskjöld, M. (2002). FISH-mapping of a 100-kb terminal 22q13 deletion. Human Genetics, 110(5), 439–443. https://doi.org/10.1007/s00439-002-0713-7</bibtext> </blist> <blist> <bibl id="bib7" idref="ref16" type="bt">7</bibl> <bibtext> Betancur, C., &amp; Buxbaum, J. D. (2013). SHANK3 haploinsufficiency: A "common" but underdiagnosed highly penetrant monogenic cause of autism spectrum disorders. Molecular Autism, 4(1). https://doi.org/10.1186/2040-2392-4-17</bibtext> </blist> <blist> <bibl id="bib8" idref="ref99" type="bt">8</bibl> <bibtext> Bishop, S. L., Guthrie, W., Coffing, M., &amp; Lord, C. (2011). Convergent validity of the Mullen Scales of Early Learning and the Differential Ability Scales in children with autism spectrum disorders. American Journal on Intellectual and Developmental Disabilities, 116(5), 331–343. https://doi.org/10.1352/1944-7558-116.5.331</bibtext> </blist> <blist> <bibl id="bib9" idref="ref128" type="bt">9</bibl> <bibtext> Bodfish, J. W., Symons, F. J., Parker, D. E., &amp; Lewis, M. H. (2000). Varieties of repetitive behavior in autism: Comparisons to mental retardation. Journal of Autism and Developmental Disorders, 30(3), 237–243. https://doi.org/10.1023/A:1005596502855</bibtext> </blist> <blist> <bibtext> Busch, R. M., Chapin, J. S., Mester, J., Ferguson, L., Haut, J. S., Frazier, T. W., &amp; Eng, C. (2013). Cognitive characteristics of PTEN hamartoma tumor syndromes. Genetics in Medicine, 15(7), 548–553. https://doi.org/10.1038/gim.2013.1</bibtext> </blist> <blist> <bibtext> Busch, R. M., Frazier, T. W., Sonneborn, C., Hogue, O., Klaas, P., Srivastava, S., Hardan, A. Y., Martinez-Agosto, J. A., Sahin, M., &amp; Eng, C. (2023). Longitudinal neurobehavioral profiles in children and young adults with PTEN hamartoma tumor syndrome and reliable methods for assessing neurobehavioral change. Journal of Neurodevelopmental Disorders, 15(1). https://doi.org/10.1186/s11689-022-09468-4</bibtext> </blist> <blist> <bibtext> Busch, R. M., Srivastava, S., Hogue, O., Frazier, T. W., Klaas, P., Hardan, A., Martinez-Agosto, J. A., Sahin, M., Eng, C., &amp; Consortium, D. S. (2019). Neurobehavioral phenotype of autism spectrum disorder associated with germline heterozygous mutations in PTEN. Translational Psychiatry, 9(1), 251–253. https://doi.org/10.1038/s41398-019-0588-1</bibtext> </blist> <blist> <bibtext> Butler, M. G., Dazouki, M. J., Zhou, X. P., Talebizadeh, Z., Brown, M., Takahashi, T. N., Miles, J. H., Wang, C. H., Stratton, R., Pilarski, R., &amp; Eng, C. (2005). Subset of individuals with autism spectrum disorders and extreme macrocephaly associated with germline PTEN tumour suppressor gene mutations. Journal of Medical Genetics, 42(4), 318–321. https://doi.org/10.1136/jmg.2004.024646</bibtext> </blist> <blist> <bibtext> Ciaccio, C., Saletti, V., D'Arrigo, S., Esposito, S., Alfei, E., Moroni, I., Tonduti, D., Chiapparini, L., Pantaleoni, C., &amp; Milani, D. (2019). Clinical spectrum of PTEN mutation in pediatric patients. A bicenter experience. European Journal of Medical Genetics, 62(12), 103596. https://doi.org/10.1016/j.ejmg.2018.12.001</bibtext> </blist> <blist> <bibtext> Cole, J. J., Williams, J. P., Sellitto, A. D., Baratta, L. R., Huecker, J. B., Baldridge, D., Kannampallil, T., Gurnett, C. A., &amp; Balls-Berry, J. E. (2025). Association of social determinants of health with genetic test request and completion rates in children with neurologic disorders. Neurology, 104(5), e210275. https://doi.org/10.1212/WNL.0000000000210275</bibtext> </blist> <blist> <bibtext> Connor-Ahmad, S., Tjeertes, J., Chladek, M., Newton, L., Symonds, T., Clinch, S., Vincenzi, B., &amp; McDougall, F. (2023). Developing Angelman syndrome-specific clinician-reported and caregiver-reported measures to support holistic, patient-centered drug development. Orphanet Journal of Rare Diseases, 18(1), 156. https://doi.org/10.1186/s13023-023-02729-y</bibtext> </blist> <blist> <bibtext> Constantino, J., &amp; Gruber, C. (2005). The Social Responsiveness Scale. Western Psychological Services.</bibtext> </blist> <blist> <bibtext> Crino, P. B., Nathanson, K. L., &amp; Henske, E. P. (2006). Medical progress: The tuberous sclerosis complex. The New England Journal of Medicine, 355(13), 1345–1356. https://doi.org/10.1056/NEJMra055323</bibtext> </blist> <blist> <bibtext> Cummings, K., Watkins, A., Jones, C., Dias, R., &amp; Welham, A. (2022). Behavioural and psychological features of PTEN mutations: a systematic review of the literature and meta-analysis of the prevalence of autism spectrum disorder characteristics. Journal of Neurodevelopmental Disorders, 14(1). https://doi.org/10.1186/s11689-021-09406-w</bibtext> </blist> <blist> <bibtext> Curatolo, P., Bombardieri, R., &amp; Jozwiak, S. (2008). Tuberous sclerosis. The Lancet, 372(9639), 657–668. https://doi.org/10.1016/S0140-6736(08)61279-9</bibtext> </blist> <blist> <bibtext> Darnell, J. C., Van Driesche, S. J., Zhang, C., Hung, K. Y. S., Mele, A., Fraser, C. E., Stone, E. F., Chen, C., Fak, J. J., Chi, S. W., Licatalosi, D. D., Richter, J. D., &amp; Darnell, R. B. (2011). FMRP stalls ribosomal translocation on mRNAs linked to synaptic function and autism. Cell, 146(2), 247–261. https://doi.org/10.1016/j.cell.2011.06.013</bibtext> </blist> <blist> <bibtext> de Saint Martin, A., Napuri, S., &amp; Nguyen, S. (2022). Tuberous sclerosis complex and epilepsy in infancy: Prevention and early diagnosis. Archives de Pediatrie, 29(5), 5S8–5S13. https://doi.org/10.1016/S0929-693X(22)00284-6</bibtext> </blist> <blist> <bibtext> de Vries, P. J., Heunis, T. M., Vanclooster, S., Chambers, N., Bissell, S., Byars, A. W., Flinn, J., Gipson, T. T., van Eeghen, A. M., Waltereit, R., Capal, J. K., Cukier, S., Davis, P. E., Smith, C., Kingswood, J. C., Schoeters, E., Srivastava, S., Takei, M., Gardner-Lubbe, S., ... Jansen, A. C. (2023). International consensus recommendations for the identification and treatment of tuberous sclerosis complex-associated neuropsychiatric disorders (TAND). Journal of Neurodevelopmental Disorders, 15(1). https://doi.org/10.1186/s11689-023-09500-1</bibtext> </blist> <blist> <bibtext> Dekker, M. C., Koot, H. M., Van Der Ende, J., &amp; Verhulst, F. C. (2002). Emotional and behavioral problems in children and adolescents with and without intellectual disability. Journal of Child Psychology and Psychiatry and Allied Disciplines, 43(8), 1087–1098. https://doi.org/10.1111/1469-7610.00235</bibtext> </blist> <blist> <bibtext> Dhawan, A., Baitamouni, S., Liu, D., Yehia, L., Anthony, K., McCarther, A., Tischkowitz, M., MacFarland, S. P., Ngeow, J., Hoogerbrugge, N., &amp; Eng, C. (2025). Cancer and overgrowth manifestations of PTEN hamartoma tumour syndrome: Management recommendations from the International PHTS Consensus Guidelines Working Group. Clinical Cancer Research, 31(9), 1754–1765. https://doi.org/10.1158/1078-0432.CCR-24-3819</bibtext> </blist> <blist> <bibtext> Dille, Y., Lagae, L., Swillen, A., &amp; Buggenhout, G. Van. (2022). Neurodevelopmental profile and stages of regression in Phelan–McDermid syndrome. Developmental Medicine and Child Neurology, 65(7), 917–925. https://doi.org/10.1111/dmcn.15482</bibtext> </blist> <blist> <bibtext> Dölen, G., &amp; Sahin, M. (2016). Editorial: Essential pathways and circuits of autism pathogenesis. Frontiers in Neuroscience, 10, Article 182. https://doi.org/10.3389/fnins.2016.00182</bibtext> </blist> <blist> <bibtext> Dovgan, K., Mazurek, M. O., &amp; Hansen, J. (2019). Measurement invariance of the child behavior checklist in children with autism spectrum disorder with and without intellectual disability: Follow-up study. Research in Autism Spectrum Disorders, 58, 19–29. https://doi.org/10.1016/j.rasd.2018.11.009</bibtext> </blist> <blist> <bibtext> Downs, J., Ludwig, N. N., Wojnaroski, M., Keeley, J., Schust Myers, L., Chapman, C. A. T., Hecker, J. E., Conecker, G., &amp; Berg, A. T. (2024). What does better look like in individuals with severe neurodevelopmental impairments? A qualitative descriptive study on SCN2A-related developmental and epileptic encephalopathy. Quality of Life Research, 33(2), 519–528. https://doi.org/10.1007/s11136-023-03543-6</bibtext> </blist> <blist> <bibtext> Dunn, L. M., &amp; Dunn, D. M. (2007). Peabody Picture Vocabulary Test–Fourth Edition (PPVT-4). Pearson.</bibtext> </blist> <blist> <bibtext> Einfeld, S., &amp; Tonge, B. (2002). Manual for the Developmental Behaviour Checklist: Primary Carer Version (DBC-P) and Teacher Version (DBC-T) (2nd ed.). Monash University Centre for Developmental Psychiatry and Psychology.</bibtext> </blist> <blist> <bibtext> Eisengart, J. B., Daniel, M. H., Adams, H. R., Williams, P., Kuca, B., &amp; Shapiro, E. (2022). Increasing precision in the measurement of change in pediatric neurodegenerative disease. In Molecular Genetics and Metabolism, 137(1–2), 201–209. https://doi.org/10.1016/j.ymgme.2022.09.001</bibtext> </blist> <blist> <bibtext> Elliott, C. D. (2007). Differential Ability Scales (2nd Ed.). The Psychological Corporation.</bibtext> </blist> <blist> <bibtext> Esbensen, A. J., Hoffman, E. K., Shaffer, R., Chen, E., Patel, L., &amp; Jacola, L. (2018). Reliability of parent report measures of behaviour in children with Down syndrome. Journal of Intellectual Disability Research, 62(9), 785–797. https://doi.org/10.1111/jir.12533</bibtext> </blist> <blist> <bibtext> Farach, L. S., Pearson, D. A., Woodhouse, J. P., Schraw, J. M., Sahin, M., Krueger, D. A., Wu, J. Y., Bebin, E. M., Lupo, P. J., Au, K. S., Northrup, H., Sahin, M., Krueger, D., Bebin, M., Wu, J. Y., Northrup, H., Warfield, S., Peters, J., Scherrer, B., ... Murray, D. S. (2019). Tuberous sclerosis complex genotypes and developmental phenotype. Pediatric Neurology, 96, 58–63. https://doi.org/10.1016/j.pediatrneurol.2019.03.003</bibtext> </blist> <blist> <bibtext> Farmer, C., Adedipe, D., Bal, V. H., Chlebowski, C., &amp; Thurm, A. (2020). Concordance of the Vineland Adaptive Behavior Scales, second and third editions. Journal of Intellectual Disability Research, 64(1), 18–26. https://doi.org/10.1111/jir.12691</bibtext> </blist> <blist> <bibtext> Farmer, C., Giserman-Kiss, I., Mohanty, E., Soorya, L., Sahin, M., Kolevzon, A., Buxbaum, J., Berry-Kravis, E., Powell, C., Bernstein, J., &amp; Thurm, A. (2025). Retrospective reports of skill attainment and loss in Phelan-McDermid Syndrome. American Journal on Intellectual and Developmental Disabilities. Advance online publication. https://<ulink href="http://www.aaidd.org/publications/journals/articles-accepted-for-publication">www.aaidd.org/publications/journals/articles-accepted-for-publication</ulink></bibtext> </blist> <blist> <bibtext> Farmer, C., Golden, C., &amp; Thurm, A. (2016). Concurrent validity of the Differential Ability Scales, Second Edition with the Mullen Scales of Early Learning in young children with and without neurodevelopmental disorders. Child Neuropsychology, 22(5), 556–569. https://doi.org/10.1080/09297049.2015.1020775</bibtext> </blist> <blist> <bibtext> Farmer, C., Kaat, A. J., Berry-Kravis, E., &amp; Thurm, A. (2022). Psychometric perspectives on developmental outcome and endpoint selection in treatment trials for genetic conditions associated with neurodevelopmental disorder. International Review of Research in Developmental Disabilities, 62, 1–39. https://doi.org/10.1016/bs.irrdd.2022.05.001</bibtext> </blist> <blist> <bibtext> Farmer, C., Thurm, A., Das, T., Bebin, E. M., Bernstein, J., Berry-Kravis, E., Buxbaum, J. D. &amp; et al. (2024). Which score for what? Operationalizing standardized cognitive test performance for the assessment of change. American Journal on Intellectual and Developmental Disabilities. Advance online publication. https://<ulink href="http://www.aaidd.org/publications/journals/articles-accepted-for-publication">www.aaidd.org/publications/journals/articles-accepted-for-publication</ulink></bibtext> </blist> <blist> <bibtext> Farmer, C., Thurm, A., Troy, J. D., &amp; Kaat, A. J. (2023). Comparing ability and norm-referenced scores as clinical trial outcomes for neurodevelopmental disabilities: a simulation study. Journal of Neurodevelopmental Disorders, 15(1), Article 4. https://doi.org/10.1186/S11689-022-09474-6</bibtext> </blist> <blist> <bibtext> Food and Drug Administration. (2019, March). Rare diseases: Natural history studies for drug development. U.S. Department of Health and Human Services. https://<ulink href="http://www.fda.gov/regulatory-information/search-fda-guidance-documents/rare-diseases-natural-history-studies-drug-development">www.fda.gov/regulatory-information/search-fda-guidance-documents/rare-diseases-natural-history-studies-drug-development</ulink></bibtext> </blist> <blist> <bibtext> Food and Drug Administration. (2022, June). Patient-focused drug development: Selecting, developing, or modifying fit-for-purpose clinical outcome assessments. U.S. Department of Health and Human Services. https://<ulink href="http://www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-focused-drug-development-selecting-developing-or-modifying-fit-purpose-clinical-outcome">www.fda.gov/regulatory-information/search-fda-guidance-documents/patient-focused-drug-development-selecting-developing-or-modifying-fit-purpose-clinical-outcome</ulink></bibtext> </blist> <blist> <bibtext> Frank, Y. (2021). The neurological manifestations of Phelan-McDermid syndrome. Pediatric Neurology, 122, 59–64https://doi.org/10.1016/j.pediatrneurol.2021.06.002</bibtext> </blist> <blist> <bibtext> Frazier, T. W., Busch, R. M., Klaas, P., Lachlan, K., Jeste, S., Kolevzon, A., Loth, E., Harris, J., Speer, L., Pepper, T., Anthony, K., Graglia, J. M., Delagrammatikas, C., Bedrosian-Sermone, S., Beekhuyzen, J., Smith-Hicks, C., Sahin, M., Eng, C., Hardan, A. Y., &amp; Uljarević, M. (2023). Development of informant-report neurobehavioral survey scales for PTEN hamartoma tumor syndrome and related neurodevelopmental genetic syndromes. American Journal of Medical Genetics, Part A, 191(7), 1741–1757. https://doi.org/10.1002/ajmg.a.63195</bibtext> </blist> <blist> <bibtext> Frazier, T. W., Embacher, R., Tilot, A. K., Koenig, K., Mester, J., &amp; Eng, C. (2015). Molecular and phenotypic abnormalities in individuals with germline heterozygous PTEN mutations and autism. Molecular Psychiatry, 20(9), 1132–1138. https://doi.org/10.1038/mp.2014.125</bibtext> </blist> <blist> <bibtext> Furnier, S. M., Gangnon, R., Daniels, J. L., Ellis Weismer, S., Nadler, C., Pazol, K., Reyes, N. M., Rosenberg, S., Rubenstein, E., Wiggins, L. D., Yeargin-Allsopp, M., &amp; Durkin, M. S. (2024). Racial and ethnic disparities in the co-occurrence of intellectual disability and autism: Impact of incorporating measures of adaptive functioning. Autism Research, 17(3), 650–667. https://doi.org/10.1002/aur.3107</bibtext> </blist> <blist> <bibtext> Gell, M., Eickhoff, S. B., Omidvarnia, A., Küppers, V., Patil, K. R., Satterthwaite, T. D., Müller, V. I., &amp; Langner, R. (2024). How measurement noise limits the accuracy of brain-behaviour predictions. Nature Communications, 15(1), 10678. https://doi.org/10.1038/s41467-024-54022-6</bibtext> </blist> <blist> <bibtext> Gergoudis, K., Weinberg, A., Templin, J., Farmer, C., Durkin, A., Weissman, J., Siper, P., Foss-Feig, J., del Pilar Trelles, M., Bernstein, J. A., Buxbaum, J. D., Berry-Kravis, E., Powell, C. M., Sahin, M., Soorya, L., Thurm, A., &amp; Kolevzon, A. (2020). Psychometric study of the Social Responsiveness Scale in Phelan–McDermid syndrome. Autism Research, 13(8), 1383–1396. https://doi.org/10.1002/aur.2299</bibtext> </blist> <blist> <bibtext> Gizzo, L., Bliss, G., Palaty, C., &amp; Kolevzon, A. (2024). Caregiver perspectives on patient-focused drug development for Phelan-McDermid syndrome. Orphanet Journal of Rare Diseases, 19(1), Article 134. https://doi.org/10.1186/s13023-024-03141-w</bibtext> </blist> <blist> <bibtext> Goh, S., Kwiatkowski, D. J., Dorer, D. J., &amp; Thiele, E. A. (2005). Infantile spasms and intellectual outcomes in children with tuberous sclerosis complex. Neurology, 65(2), 235–238. https://doi.org/10.1212/01.wnl.0000168908.78118.99</bibtext> </blist> <blist> <bibtext> Hansen-Kiss, E., Beinkampen, S., Adler, B., Frazier, T., Prior, T., Erdman, S., Eng, C., &amp; Herman, G. (2017). A retrospective chart review of the features of PTEN hamartoma tumour syndrome in children. Journal of Medical Genetics, 54(7), 471–478. https://doi.org/10.1136/jmedgenet-2016-104484</bibtext> </blist> <blist> <bibtext> Havdahl, K. A., Hus Bal, V., Huerta, M., Pickles, A., Øyen, A. S., Stoltenberg, C., Lord, C., &amp; Bishop, S. L. (2016). Multidimensional influences on autism symptom measures: Implications for use in etiological research. Journal of the American Academy of Child and Adolescent Psychiatry, 55(12), 1054–1063. https://doi.org/10.1016/j.jaac.2016.09.490</bibtext> </blist> <blist> <bibtext> Hecker, J., Conecker, G., Chapman, C., Hommer, R., Ludwig, N. N., Sevinc, G., Te, S., Wojnaroski, M., Downs, J., &amp; Berg, A. T. (2024). Patient-advocate-led global coalition adapting fit-for-purpose outcomes measures to assure meaningful inclusion of DEEs in clinical trials. Therapeutic Advances in Rare Disease, 18, Article 26330040241249762. https://doi.org/10.1177/26330040241249762</bibtext> </blist> <blist> <bibtext> Ho, C. N., Rushing, G., Valentine, J. E., Rosbeck, K. L., &amp; Roberds, S. L. (2017). The voice of the patient: A report from the Tuberous Sclerosis Alliance's externally-led patient-focused drug development meeting. Tuberous Sclerosis Alliance. https://<ulink href="http://www.tscalliance.org/wp-content/uploads/2018/01/Voice-of-the-Patient-Tuberous-Sclerosis-Alliance.pdf">www.tscalliance.org/wp-content/uploads/2018/01/Voice-of-the-Patient-Tuberous-Sclerosis-Alliance.pdf</ulink></bibtext> </blist> <blist> <bibtext> Hobert, J. A., &amp; Eng, C. (2009). PTEN hamartoma tumor syndrome: An overview. Genetics in Medicine 11(10), 687–694. https://doi.org/10.1097/GIM.0b013e3181ac9aea</bibtext> </blist> <blist> <bibtext> Hus, V., Bishop, S., Gotham, K., Huerta, M., &amp; Lord, C. (2013). Factors influencing scores on the Social Responsiveness Scale. Journal of Child Psychology and Psychiatry and Allied Disciplines, 54(2), 216–224. https://doi.org/10.1111/j.1469-7610.2012.02589.x</bibtext> </blist> <blist> <bibtext> Jansen, F. E., Braams, O., Vincken, K. L., Algra, A., Anbeek, P., Jennekens-Schinkel, A., Halley, D., Zonnenberg, B. A., Van Den Ouweland, A., Van Huffelen, A. C., Van Nieuwenhuizen, O., &amp; Nellist, M. (2008). Overlapping neurologic and cognitive phenotypes in patients with TSC1 or TSC2 mutations. Neurology, 70(12), 908–915. https://doi.org/10.1212/01.wnl.0000280578.99900.96</bibtext> </blist> <blist> <bibtext> Joinson, C., O'Callaghan, F. J., Osborne, J. P., Martyn, C., Harris, T., &amp; Bolton, P. F. (2003). Learning disability and epilepsy in an epidemiological sample of individuals with tuberous sclerosis complex. Psychological Medicine, 33(2), 335–344. https://doi.org/10.1017/S0033291702007092</bibtext> </blist> <blist> <bibtext> Kidd, S. A., Berry-Kravis, E., Choo, T. H., Chen, C., Esler, A., Hoffmann, A., Andrews, H. F., &amp; Kaufmann, W. E. (2020). Improving the diagnosis of autism spectrum disorder in Fragile X Syndrome by adapting the Social Communication Questionnaire and the Social Responsiveness Scale-2. Journal of Autism and Developmental Disorders, 50(9), 3276–3295. https://doi.org/10.1007/s10803-019-04148-0</bibtext> </blist> <blist> <bibtext> Kim, S. H., Thurm, A., Shumway, S., &amp; Lord, C. (2013). Multisite study of new autism diagnostic interview-revised (ADI-R) algorithms for toddlers and young preschoolers. Journal of Autism and Developmental Disorders, 43(7), 1527–1538. https://doi.org/10.1007/s10803-012-1696-4</bibtext> </blist> <blist> <bibtext> Kohlenberg, T. M., Trelles, M. P., McLarney, B., Betancur, C., Thurm, A., &amp; Kolevzon, A. (2020). Psychiatric illness and regression in individuals with Phelan-McDermid syndrome. Journal of Neurodevelopmental Disorders, 12(1), Article 7. https://doi.org/10.1186/s11689-020-9309-6</bibtext> </blist> <blist> <bibtext> Kolevzon, A., Delaby, E., Berry-Kravis, E., Buxbaum, J. D., &amp; Betancur, C. (2019). Neuropsychiatric decompensation in adolescents and adults with Phelan-McDermid syndrome: A systematic review of the literature. Molecular Autism, 10(1), Article 50. https://doi.org/10.1186/s13229-019-0291-3</bibtext> </blist> <blist> <bibtext> Koskentausta, T., Iivanainen, M., &amp; Almqvist, F. (2004). CBCL in the assessment of psychopathology in Finnish children with intellectual disability. Research in Developmental Disabilities, 25(4), 341–354. https://doi.org/10.1016/j.ridd.2003.12.001</bibtext> </blist> <blist> <bibtext> Krueger, D. A., Northrup, H., Krueger, D. A., Roberds, S., Smith, K., Sampson, J., Korf, B., Kwiatkowski, D. J., Mowat, D., Nellist, M., Povey, S., de Vries, P., Byars, A., Dunn, D., Ess, K., Hook, D., Jansen, A., King, B., Sahin, M., ... Frost, M. D. (2013). Tuberous sclerosis complex surveillance and management: Recommendations of the 2012 international tuberous sclerosis complex consensus conference. Pediatric Neurology, 49(4), 255–265. https://doi.org/10.1016/j.pediatrneurol.2013.08.002</bibtext> </blist> <blist> <bibtext> Kwok, E., Feiner, H., Grauzer, J., Kaat, A., &amp; Roberts, M. Y. (2022). Measuring change during intervention using norm-referenced, standardized measures: A comparison of raw scores, standard scores, age equivalents, and growth scale values from the Preschool Language Scales–Fifth Edition. Journal of Speech, Language, and Hearing Research, 65(11), 4268–4279. https://doi.org/10.1044/2022_JSLHR-22-00122</bibtext> </blist> <blist> <bibtext> Lam, K. S. L., &amp; Aman, M. G. (2007). The repetitive behavior scale-revised: Independent validation in individuals with autism spectrum disorders. Journal of Autism and Developmental Disorders, 37(5), 855–866. https://doi.org/10.1007/s10803-006-0213-z</bibtext> </blist> <blist> <bibtext> Landlust, A. M., Koza, S. A., Carbin, M., Walinga, M., Robert, S., Cooke, J., Vyshka, K., van Balkom, I. D. C., &amp; van Ravenswaaij-Arts, C. (2023). Parental perspectives on Phelan-McDermid syndrome: Results of a worldwide survey. European Journal of Medical Genetics, 66(7), 104771. https://doi.org/10.1016/j.ejmg.2023.104771</bibtext> </blist> <blist> <bibtext> Levine, A., Davis, P., Zhang, B., Peters, J., Filip-Dhima, R., Warfield, S. K., Prohl, A., Capal, J., Krueger, D., Bebin, E. M., Northrup, H., Wu, J. Y., &amp; Sahin, M. (2023). Epilepsy severity is associated with head circumference and growth rate in infants with Tuberous Sclerosis Complex. Pediatric Neurology, 144, 26–32. https://doi.org/10.1016/j.pediatrneurol.2023.03.015</bibtext> </blist> <blist> <bibtext> Levy, T., Farmer, C., Srivastava, S., Johnson, K., Trayvick, J., Brune, C., Massa, A., Silver, H., Siper, P. M., Zweifach, J., Halpern, D., Foss-Feig, J. H., Bernstein, J. A., Berry-Kravis, E., Powell, C. M., Sahin, M., Soorya, L. V., Thurm, A., Buxbaum, J. D., &amp; Kolevzon, A. (2024). Genetic subtypes of Phelan-McDermid syndrome exhibit similar rates of change despite differences in level of impairment in developmental constructs. American Journal on Intellectual and Developmental Disabilities. Advance online publication. https://<ulink href="http://www.aaidd.org/publications/journals/articles-accepted-for-publication">www.aaidd.org/publications/journals/articles-accepted-for-publication</ulink></bibtext> </blist> <blist> <bibtext> Levy, T., Foss-Feig, J. H., Betancur, C., Siper, P. M., Trelles-Thorne, M. D. P., Halpern, D., Frank, Y., Lozano, R., Layton, C., Britvan, B., Bernstein, J. A., Buxbaum, J. D., Berry-Kravis, E., Powell, C. M., Srivastava, S., Sahin, M., Soorya, L., Thurm, A., &amp; Kolevzon, A. (2022). Strong evidence for genotype-phenotype correlations in Phelan-McDermid syndrome: Results from the Developmental Synaptopathies Consortium. Human Molecular Genetics, 31(4), 625–637. https://academic.oup.com/hmg/article/31/4/625/6374812</bibtext> </blist> <blist> <bibtext> Levy, T., Gluckman, J., Siper, P. M., Halpern, D., Zweifach, J., Filip-Dhima, R., Holder, J., Trelles, M. P., Johnson, K., Bernstein, J. A., Berry-Kravis, E., Powell, C. M., Soorya, L. V., Thurm, A., Buxbaum, J. D., Sahin, M., Kolevzon, A., &amp; Srivastava, S. (2024). Clinical, genetic, and cognitive correlates of seizure occurrences in Phelan-McDermid syndrome. Journal of Neurodevelopmental Disorders, 16(1), 25–12.</bibtext> </blist> <blist> <bibtext> Lord, C., Rutter, M., DiLavore, P. C., Risi, S., Gotham, K., &amp; Bishop, S. L. (2012). Autism Diagnostic Observation Schedule, Second Edition (ADOS-2). Western Psychological Services.</bibtext> </blist> <blist> <bibtext> Lord, C., Storoschuk, S., Rutter, M., &amp; Pickles, A. (1993). Using the ADI‐R to diagnose autism in preschool children. Infant Mental Health Journal, 14(3), 234–252. https://doi.org/10.1002/1097-0355(199323)14:3234::AID-IMHJ22801403083.0.CO;2-F</bibtext> </blist> <blist> <bibtext> Lyall, K., Hosseini, M., Ladd-Acosta, C., Ning, X., Catellier, D., Constantino, J. N., Croen, L. A., Kaat, A. J., Botteron, K., Bush, N. R., Dager, S. R., Duarte, C. S., Fallin, M. D., Hazlett, H., Hertz-Picciotto, I., Joseph, R. M., Karagas, M. R., Korrick, S., Landa, R., ...Echo Program Collaborators. (2021). Distributional properties and criterion validity of a shortened version of the Social Responsiveness Scale: Results from the ECHO Program and implications for social communication research. Journal of Autism and Developmental Disorders, 51(7), 2241–2253. https://doi.org/10.1007/s10803-020-04667-1</bibtext> </blist> <blist> <bibtext> Maehama, T., &amp; Dixon, J. E. (1999). PTEN: A tumour suppressor that functions as a phospholipid phosphatase. Trends in Cell Biology, 9(4), 125–128. https://doi.org/10.1016/S0962-8924(99)01519-6</bibtext> </blist> <blist> <bibtext> Maehama, T., Taylor, G. S., &amp; Dixon, J. E. (2001). PTEN and myotubularin: Novel phosphoinositide phosphatases. Annual Review of Biochemistry, 70, 247–279. https://doi.org/10.1146/annurev.biochem.70.1.247</bibtext> </blist> <blist> <bibtext> Marshburn, E. C., &amp; Aman, M. G. (1992). Factor validity and norms for the aberrant behavior checklist in a community sample of children with mental retardation. Journal of Autism and Developmental Disorders, 22(3), 357–373. https://doi.org/10.1007/BF01048240</bibtext> </blist> <blist> <bibtext> Mullen, E. M. (1995). Mullen Scales of Early Learning (AGS ed.). American Guidance Service Inc.</bibtext> </blist> <blist> <bibtext> Müller, A. R., Luijten, M. A. J., Haverman, L., de Ranitz-Greven, W. L., Janssens, P., Rietman, A. B., ten Hoopen, L. W., de Graaff, L. C. G., de Wit, M. C., Jansen, A. C., Gipson, T., Capal, J. K., de Vries, P. J., &amp; van Eeghen, A. M. (2023). Understanding the impact of tuberous sclerosis complex: development and validation of the TSC-PROM. BMC Medicine, 21(1), Article 298. https://doi.org/10.1186/s12916-023-03012-4</bibtext> </blist> <blist> <bibtext> National Organization of Rare Disorders. (2023, November 7). PTEN Hamartoma Tumor Syndrome. https://rarediseases.org/rare-diseases/pten-hamartoma-tumor-syndrome</bibtext> </blist> <blist> <bibtext> Nisar, S., Bhat, A. A., Masoodi, T., Hashem, S., Akhtar, S., Ali, T. A., Amjad, S., Chawla, S., Bagga, P., Frenneaux, M. P., Reddy, R., Fakhro, K., &amp; Haris, M. (2022). Genetics of glutamate and its receptors in autism spectrum disorder. In Molecular Psychiatry, 27(5), 2380–2392. https://doi.org/10.1038/s41380-022-01506-w</bibtext> </blist> <blist> <bibtext> Northrup, H., Aronow, M. E., Bebin, E. M., Bissler, J., Darling, T. N., de Vries, P. J., Frost, M. D., Fuchs, Z., Gosnell, E. S., Gupta, N., Jansen, A. C., Jóźwiak, S., Kingswood, J. C., Knilans, T. K., McCormack, F. X., Pounders, A., Roberds, S. L., Rodriguez-Buritica, D. F., Roth, J., ... Young, L. (2021). Updated international Tuberous Sclerosis Complex diagnostic criteria and surveillance and management recommendations. Pediatric Neurology, 123,50–58. https://doi.org/10.1016/j.pediatrneurol.2021.07.011</bibtext> </blist> <blist> <bibtext> Oberman, L. M., Boccuto, L., Cascio, L., Sarasua, S., &amp; Kaufmann, W. E. (2015). Autism spectrum disorder in Phelan-McDermid syndrome: Initial characterization and genotype-phenotype correlations. Orphanet Journal of Rare Diseases, 10(1), Article 105. https://doi.org/10.1186/s13023-015-0323-9</bibtext> </blist> <blist> <bibtext> O'Callaghan, F. J. K., Shiell, A. W., Osborne, J. P., &amp; Martyn, C. N. (1998). Prevalence of tuberous sclerosis estimated by capture-recapture analysis. Lancet, 351(9114), 1490. https://doi.org/10.1016/S0140-6736(05)78872-3</bibtext> </blist> <blist> <bibtext> Ostrolenk, A., &amp; Courchesne, V. (2023). Examining the validity of the use of ratio IQs in psychological assessments. Acta Psychologica, 240, Article 104054. https://doi.org/10.1016/j.actpsy.2023.104054</bibtext> </blist> <blist> <bibtext> Pandolfi, V., Magyar, C. I., &amp; Dill, C. A. (2009). Confirmatory factor analysis of the Child Behavior Checklist 1.5-5 in a sample of children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 39(7), 987–995. https://doi.org/10.1007/s10803-009-0716-5</bibtext> </blist> <blist> <bibtext> Phelan, K., &amp; McDermid, H. E. (2012). The 22q13.3 deletion syndrome (Phelan-McDermid syndrome). Molecular Syndromology, 2(3–5), 186–201. https://doi.org/10.1159/000334260</bibtext> </blist> <blist> <bibtext> Piergies, A. M. H., Hirota, T., Monden, R., &amp; Zheng, S. (2022). Subgrouping school-aged children on the autism spectrum based on co-occurring psychiatric symptoms. Research in Autism Spectrum Disorders, 95, Article 101983. https://doi.org/10.1016/j.rasd.2022.101983</bibtext> </blist> <blist> <bibtext> Risi, S., Lord, C., Gotham, K., Corsello, C., Chrysler, C., Szatmari, P., Cook, E. H., Leventhal, B. L., &amp; Pickles, A. (2006). Combining information from multiple sources in the diagnosis of autism spectrum disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 45(9), 1094–1103. https://doi.org/10.1097/01.chi.0000227880.42780.0e</bibtext> </blist> <blist> <bibtext> Roid, G. H., &amp; Pomplun, M. (2012). The Stanford–Binet Intelligence Scales (5th Edition). Riverside Publishing.</bibtext> </blist> <blist> <bibtext> Rutter, M., Le Couteur, A., &amp; Lord, C. (2003). ADI-R Autism Diagnostic Interview Revised. Western Psychological Services.</bibtext> </blist> <blist> <bibtext> Sahin, M., &amp; Sur, M. (2015). Genes, circuits, and precision therapies for autism and related neurodevelopmental disorders. Science, 350(6263), aab3897. https://doi.org/10.1126/science.aab3897</bibtext> </blist> <blist> <bibtext> Sakai, Y., Shaw, C. A., Dawson, B. C., Dugas, D. V., Al-Mohtaseb, Z., Hill, D. E., &amp; Zoghbi, H. Y. (2011). Protein interactome reveals converging molecular pathways among autism disorders. Science Translational Medicine, 3(86), 86ra49-86ra49. https://doi.org/10.1126/scitranslmed.3002166</bibtext> </blist> <blist> <bibtext> Sala, C., Piëch, V., Wilson, N. R., Passafaro, M., Liu, G., &amp; Sheng, M. (2001). Regulation of dendritic spine morphology and synaptic function by Shank and Homer. Neuron, 31(1), 115–130. https://doi.org/10.1016/S0896-6273(01)00339-7</bibtext> </blist> <blist> <bibtext> Sanders, S. J., Sahin, M., Hostyk, J., Thurm, A., Jacquemont, S., Avillach, P., Douard, E., Martin, C. L., Modi, M. E., Moreno-De-Luca, A., Raznahan, A., Anticevic, A., Dolmetsch, R., Feng, G., Geschwind, D. H., Glahn, D. C., Goldstein, D. B., Ledbetter, D. H., Mulle, J. G., ... Bearden, C. E. (2019). A framework for the investigation of rare genetic disorders in neuropsychiatry. Nature Medicine, 25(10), 1477–1487. https://doi.org/10.1038/s41591-019-0581-5</bibtext> </blist> <blist> <bibtext> Sarasua, S. M., Dwivedi, A., Boccuto, L., Rollins, J. D., Chen, C. F., Rogers, R. C., Phelan, K., Dupont, B. R., &amp; Collins, J. S. (2011). Association between deletion size and important phenotypes expands the genomic region of interest in Phelan-McDermid syndrome (22q13 deletion syndrome). Journal of Medical Genetics, 48(11), 761–766. https://doi.org/10.1136/jmedgenet-2011-100225</bibtext> </blist> <blist> <bibtext> Scalisi, F. C., Callea, M., Martinelli, D., Willoughby, C. E., Tadich, A. C., Castillo, M. A., Lacruz-Rengel, M. A., Medina, M., Grimaldi, P., Bertini, E., &amp; Nevado, J. (2022). Clinical and genetic aspects of Phelan–McDermid syndrome: An interdisciplinary approach to management. Genes, 13(3), Article 504. https://doi.org/10.3390/genes13030504</bibtext> </blist> <blist> <bibtext> Schön, M., Lapunzina, P., Nevado, J., Mattina, T., Gunnarsson, C., Hadzsiev, K., Verpelli, C., Bourgeron, T., Jesse, S., van Ravenswaaij-Arts, C. M. A., &amp; Hennekam, R. C. (2023). Definition and clinical variability of SHANK3-related Phelan-McDermid syndrome. European Journal of Medical Genetics, 66(7), Article 104754. https://doi.org/10.1016/j.ejmg.2023.104754</bibtext> </blist> <blist> <bibtext> Soorya, L., Kolevzon, A., Zweifach, J., Lim, T., Dobry, Y., Schwartz, L., Frank, Y., Wang, A. T., Cai, G., Parkhomenko, E., Halpern, D., Grodberg, D., Angarita, B., Willner, J. P., Yang, A., Canitano, R., Chaplin, W., Betancur, C., &amp; Buxbaum, J. D. (2013). Prospective investigation of autism and genotype-phenotype correlations in 22q13 deletion syndrome and SHANK3 deficiency. Molecular Autism, 4(1), Article 18. https://doi.org/10.1186/2040-2392-4-18</bibtext> </blist> <blist> <bibtext> Soorya, L., Leon, J., Trelles, M. P., &amp; Thurm, A. (2018). Framework for assessing individuals with rare genetic disorders associated with profound intellectual and multiple disabilities (PIMD): the example of Phelan McDermid Syndrome. Clinical Neuropsychologist, 32(7), 1226–1255. https://doi.org/10.1080/13854046.2017.1413211</bibtext> </blist> <blist> <bibtext> Sparrow, S. S., Balla, D. A., Cicchetti, D. V., &amp; Doll, E. A. (2005). Vineland-II: Vineland Adaptive Behavior Scales: Survey Forms Manual (2nd ed.). AGS Publishing.</bibtext> </blist> <blist> <bibtext> Specchio, N., Pietrafusa, N., Trivisano, M., Moavero, R., De Palma, L., Ferretti, A., Vigevano, F., &amp; Curatolo, P. (2020). Autism and epilepsy in patients with tuberous sclerosis complex. Frontiers in Neurology, 11, Article 639. https://doi.org/10.3389/fneur.2020.00639</bibtext> </blist> <blist> <bibtext> Srivastava, S., Johnson, K., Farmer, C., Levy, T., Thurm, A., Soorya, L., Filip-Dhima, R., Quinlan, A., Bernstein, J. A., Berry-Kravis, E., Powell, C. M., Buxbaum, J. D., Sahin, M., &amp; Kolevzon, A. (2024). Longitudinal trajectory of adaptive skills in Phelan-McDermid Syndrome. American Journal on Intellectual and Developmental Disabilities. Advance online publication. https://<ulink href="http://www.aaidd.org/publications/journals/articles-accepted-for-publication">www.aaidd.org/publications/journals/articles-accepted-for-publication</ulink></bibtext> </blist> <blist> <bibtext> Srivastava, S., Sahin, M., Buxbaum, J. D., Berry-Kravis, E., Soorya, L. V., Thurm, A., Bernstein, J. A., Asante-Otoo, A., Bennett, W. E., Betancur, C., Brickhouse, T. H., Passos Bueno, M. R., Chopra, M., Christensen, C. K., Cully, J. L., Dies, K., Friedman, K., Gummere, B., Holder, J. L., ... Kolevzon, A. (2023). Updated consensus guidelines on the management of Phelan–McDermid syndrome. American Journal of Medical Genetics, Part A, 91(8), 2015–2044. https://doi.org/10.1002/ajmg.a.63312</bibtext> </blist> <blist> <bibtext> Sturm, A., Kuhfeld, M., Kasari, C., &amp; McCracken, J. T. (2017). Development and validation of an item response theory-based Social Responsiveness Scale short form. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 58(9), 1053–1061. https://doi.org/10.1111/jcpp.12731</bibtext> </blist> <blist> <bibtext> Sullivan, J., Wirrell, E., Knupp, K. G., Chen, D., Zafar, M., Flamini, R., Stutely, J., Brathwaite, C., Ventola, P., Avendaño, J., Parkerson, K. A., Wyant, N., &amp; Ticho, B. (2022). Interim results of adaptive functioning and neurodevelopment in BUTTERFLY—An observational study of children and adolescents with Dravet syndrome. Epilepsy and Behavior, 137, Article 108955. https://doi.org/10.1016/j.yebeh.2022.108955</bibtext> </blist> <blist> <bibtext> Thurm, A., Farmer, C., Salzman, E., Lord, C., &amp; Bishop, S. (2019). State of the field: Differentiating intellectual disability from autism spectrum disorder. Frontiers in Psychiatry, 10, Article 526. https://doi.org/10.3389/fpsyt.2019.00526</bibtext> </blist> <blist> <bibtext> Tye, C., Thomas, L. E., Sampson, J. R., Lewis, J., O'Callaghan, F., Yates, J. R. W., &amp; Bolton, P. F. (2018). Secular changes in severity of intellectual disability in tuberous sclerosis complex: A reflection of improved identification and treatment of epileptic spasms? Epilepsia Open, 3(2), 276–280. https://doi.org/10.1002/epi4.12111</bibtext> </blist> <blist> <bibtext> van Eeghen, A. M., Stemkens, D., Fernández-Fructuoso, J. R., Maruani, A., Hadzsiev, K., Gaasterland, C. M. W., Klein Haneveld, M. J., Vyshka, K., Hugon, A., van Eeghen, A. M., Alhambra, N., Anderlid, B.-M., Andres, S., Aten, E., Guedes, R. B., Bonaglia, M. C., Bourgeron, T., Burdeus-Olavarrieta, M., Carbin, M. J., ... van Balkom, I. D. C. (2023). Consensus recommendations on organization of care for individuals with Phelan-McDermid syndrome. European Journal of Medical Genetics, 66(7), 104747. https://doi.org/10.1016/j.ejmg.2023.104747</bibtext> </blist> <blist> <bibtext> van Ravenswaaij-Arts, C. M. A., van Balkom, I. D. C., Jesse, S., &amp; Bonaglia, M. C. (2023). Editorial: Towards a European consensus guideline for Phelan-McDermid syndrome. European Journal of Medical Genetics, 66(5), Article 104736. https://doi.org/10.1016/j.ejmg.2023.104736</bibtext> </blist> <blist> <bibtext> Varga, E. A., Pastore, M., Prior, T., Herman, G. E., &amp; McBride, K. L. (2009). The prevalence of PTEN mutations in a clinical pediatric cohort with autism spectrum disorders, developmental delay, and macrocephaly. Genetics in Medicine, 11(2), 111–117. https://doi.org/10.1097/GIM.0b013e31818fd762</bibtext> </blist> <blist> <bibtext> Williams, K. T. (2007). Expressive vocabulary test-second edition. NCS Pearson.</bibtext> </blist> <blist> <bibtext> Wilson, H. L., Wong, A. C. C., Shaw, S. R., Tse, W. Y., Stapleton, G. A., Phelan, M. C., Hu, S., Marshall, J., &amp; McDermid, H. E. (2003). Molecular characterisation of the 22q13 deletion syndrome supports the role of haploinsufficiency of SHANK3/PROSAP2 in the major neurological symptoms. Journal of Medical Genetics, 40(8), 575–584. https://doi.org/10.1136/jmg.40.8.575</bibtext> </blist> <blist> <bibtext> Winden, K. D., Ebrahimi-Fakhari, D., &amp; Sahin, M. (2018). Abnormal mTOR activation in autism. Annual Review of Neuroscience, 41, 1–23. https://doi.org/10.1146/annurev-neuro-080317-061747</bibtext> </blist> <blist> <bibtext> Xu, N., Lv, H., Yang, T., Du, X., Sun, Y., Xiao, B., Fan, Y., Luo, X., Zhan, Y., Wang, L., Li, F., &amp; Yu, Y. (2020). A 29 Mainland Chinese cohort of patients with Phelan–McDermid syndrome: genotype–phenotype correlations and the role of SHANK3 haploinsufficiency in the important phenotypes. Orphanet Journal of Rare Diseases, 15(1), Article 335. https://doi.org/10.1186/s13023-020-01592-5</bibtext> </blist> <blist> <bibtext> Yum, M. S., Lee, E. H., &amp; Ko, T. S. (2013). Vigabatrin and mental retardation in tuberous sclerosis: Infantile spasms versus focal seizures. Journal of Child Neurology, 28(3), 308–313. https://doi.org/10.1177/0883073812446485</bibtext> </blist> </ref> <aug> <p>By Latha Valluripalli Soorya; Camille W. Brune; Cristan A. Farmer; Edith V. Ocampo; Natalie I. Berger; Deborah A. Pearson; Robyn M. Busch; Patricia Klaas; Paige Siper; Kristn Currans; Amanda C. Gulsrud; Jennifer M. Phillips; Rajna Filip-Dhima; Sarah E. O'Kelley; Thomas W. Frazier; Tess Levy; Allison L. Wainer; Joseph D. Buxbaum; Craig M. Powell; Jonathan A. Bernstein; Simon K. Warfield; Darcy A. Krueger; E. Martina Bebin; Hope Northrup; Shafali S. Jeste; Alexander Kolevzon; Elizabeth Berry-Kravis; Mustafa Sahin; Siddharth Srivastava and Audrey Thurm</p> <p>Reported by Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib96" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib27" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib93" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib115" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib21" firstref="ref8"></nolink> <nolink nlid="nl6" bibid="bib94" firstref="ref9"></nolink> <nolink nlid="nl7" bibid="bib82" firstref="ref10"></nolink> <nolink nlid="nl8" bibid="bib114" firstref="ref12"></nolink> <nolink nlid="nl9" bibid="bib88" firstref="ref13"></nolink> <nolink nlid="nl10" bibid="bib95" firstref="ref14"></nolink> <nolink nlid="nl11" bibid="bib97" firstref="ref15"></nolink> <nolink nlid="nl12" bibid="bib99" firstref="ref18"></nolink> <nolink nlid="nl13" bibid="bib72" firstref="ref19"></nolink> <nolink nlid="nl14" bibid="bib26" firstref="ref20"></nolink> <nolink nlid="nl15" bibid="bib40" firstref="ref21"></nolink> <nolink nlid="nl16" bibid="bib62" firstref="ref22"></nolink> <nolink nlid="nl17" bibid="bib63" firstref="ref23"></nolink> <nolink nlid="nl18" bibid="bib100" firstref="ref25"></nolink> <nolink nlid="nl19" bibid="bib105" firstref="ref26"></nolink> <nolink nlid="nl20" bibid="bib98" firstref="ref27"></nolink> <nolink nlid="nl21" bibid="bib101" firstref="ref29"></nolink> <nolink nlid="nl22" bibid="bib84" firstref="ref31"></nolink> <nolink nlid="nl23" bibid="bib116" firstref="ref32"></nolink> <nolink nlid="nl24" bibid="bib37" firstref="ref38"></nolink> <nolink nlid="nl25" bibid="bib110" firstref="ref42"></nolink> <nolink nlid="nl26" bibid="bib111" firstref="ref43"></nolink> <nolink nlid="nl27" bibid="bib18" firstref="ref44"></nolink> <nolink nlid="nl28" bibid="bib20" firstref="ref45"></nolink> <nolink nlid="nl29" bibid="bib85" firstref="ref46"></nolink> <nolink nlid="nl30" bibid="bib65" firstref="ref47"></nolink> <nolink nlid="nl31" bibid="bib69" firstref="ref48"></nolink> <nolink nlid="nl32" bibid="bib23" firstref="ref50"></nolink> <nolink nlid="nl33" bibid="bib51" firstref="ref51"></nolink> <nolink nlid="nl34" bibid="bib58" firstref="ref52"></nolink> <nolink nlid="nl35" bibid="bib59" firstref="ref53"></nolink> <nolink nlid="nl36" bibid="bib109" firstref="ref55"></nolink> <nolink nlid="nl37" bibid="bib103" firstref="ref56"></nolink> <nolink nlid="nl38" bibid="bib83" firstref="ref57"></nolink> <nolink nlid="nl39" bibid="bib22" firstref="ref58"></nolink> <nolink nlid="nl40" bibid="bib117" firstref="ref60"></nolink> <nolink nlid="nl41" bibid="bib56" firstref="ref62"></nolink> <nolink nlid="nl42" bibid="bib77" firstref="ref63"></nolink> <nolink nlid="nl43" bibid="bib76" 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| Header | DbId: eric DbLabel: ERIC An: EJ1482498 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Characterizing Developmental and Behavioral Profiles in Developmental Synaptopathies to Inform Clinical Trial Endpoints – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Latha+Valluripalli+Soorya%22">Latha Valluripalli Soorya</searchLink><br /><searchLink fieldCode="AR" term="%22Camille+W%2E+Brune%22">Camille W. Brune</searchLink><br /><searchLink fieldCode="AR" term="%22Cristan+A%2E+Farmer%22">Cristan A. Farmer</searchLink><br /><searchLink fieldCode="AR" term="%22Edith+V%2E+Ocampo%22">Edith V. Ocampo</searchLink><br /><searchLink fieldCode="AR" term="%22Natalie+I%2E+Berger%22">Natalie I. Berger</searchLink><br /><searchLink fieldCode="AR" term="%22Deborah+A%2E+Pearson%22">Deborah A. Pearson</searchLink><br /><searchLink fieldCode="AR" term="%22Robyn+M%2E+Busch%22">Robyn M. Busch</searchLink><br /><searchLink fieldCode="AR" term="%22Patricia+Klaas%22">Patricia Klaas</searchLink><br /><searchLink fieldCode="AR" term="%22Paige+Siper%22">Paige Siper</searchLink><br /><searchLink fieldCode="AR" term="%22Kristn+Currans%22">Kristn Currans</searchLink><br /><searchLink fieldCode="AR" term="%22Amanda+C%2E+Gulsrud%22">Amanda C. Gulsrud</searchLink><br /><searchLink fieldCode="AR" term="%22Jennifer+M%2E+Phillips%22">Jennifer M. Phillips</searchLink><br /><searchLink fieldCode="AR" term="%22Rajna+Filip-Dhima%22">Rajna Filip-Dhima</searchLink><br /><searchLink fieldCode="AR" term="%22Sarah+E%2E+O%27Kelley%22">Sarah E. O’Kelley</searchLink><br /><searchLink fieldCode="AR" term="%22Thomas+W%2E+Frazier%22">Thomas W. Frazier</searchLink><br /><searchLink fieldCode="AR" term="%22Tess+Levy%22">Tess Levy</searchLink><br /><searchLink fieldCode="AR" term="%22Allison+L%2E+Wainer%22">Allison L. Wainer</searchLink><br /><searchLink fieldCode="AR" term="%22Joseph+D%2E+Buxbaum%22">Joseph D. Buxbaum</searchLink><br /><searchLink fieldCode="AR" term="%22Craig+M%2E+Powell%22">Craig M. Powell</searchLink><br /><searchLink fieldCode="AR" term="%22Jonathan+A%2E+Bernstein%22">Jonathan A. Bernstein</searchLink><br /><searchLink fieldCode="AR" term="%22Simon+K%2E+Warfield%22">Simon K. Warfield</searchLink><br /><searchLink fieldCode="AR" term="%22Darcy+A%2E+Krueger%22">Darcy A. Krueger</searchLink><br /><searchLink fieldCode="AR" term="%22E%2E+Martina+Bebin%22">E. Martina Bebin</searchLink><br /><searchLink fieldCode="AR" term="%22Hope+Northrup%22">Hope Northrup</searchLink><br /><searchLink fieldCode="AR" term="%22Shafali+S%2E+Jeste%22">Shafali S. Jeste</searchLink><br /><searchLink fieldCode="AR" term="%22Alexander+Kolevzon%22">Alexander Kolevzon</searchLink><br /><searchLink fieldCode="AR" term="%22Elizabeth+Berry-Kravis%22">Elizabeth Berry-Kravis</searchLink><br /><searchLink fieldCode="AR" term="%22Mustafa+Sahin%22">Mustafa Sahin</searchLink><br /><searchLink fieldCode="AR" term="%22Siddharth+Srivastava%22">Siddharth Srivastava</searchLink><br /><searchLink fieldCode="AR" term="%22Audrey+Thurm%22">Audrey Thurm</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22American+Journal+on+Intellectual+and+Developmental+Disabilities%22"><i>American Journal on Intellectual and Developmental Disabilities</i></searchLink>. 2025 130(5):414-437. – Name: Avail Label: Availability Group: Avail Data: American Association on Intellectual and Developmental Disabilities. P.O. Box 1897, Lawrence, KS 66044-1897. Tel: 785-843-1235; Fax: 785-843-1274; e-mail: AJMR@allenpress.com; Web site: https://meridian.allenpress.com/aaidd – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 24 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Intellectual+Disability%22">Intellectual Disability</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+Disorders%22">Genetic Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Neurological+Impairments%22">Neurological Impairments</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement+Techniques%22">Measurement Techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Children%22">Children</searchLink><br /><searchLink fieldCode="DE" term="%22Adolescents%22">Adolescents</searchLink><br /><searchLink fieldCode="DE" term="%22Young+Adults%22">Young Adults</searchLink><br /><searchLink fieldCode="DE" term="%22Severity+%28of+Disability%29%22">Severity (of Disability)</searchLink><br /><searchLink fieldCode="DE" term="%22Measures+%28Individuals%29%22">Measures (Individuals)</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior%22">Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Individual+Development%22">Individual Development</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1352/1944-7558-130.5.414 – Name: ISSN Label: ISSN Group: ISSN Data: 1944-7515<br />1944-7558 – Name: Abstract Label: Abstract Group: Ab Data: The Developmental Synaptopathies Consortium is a multisite natural history network studying rare, neurogenetic syndromes associated with synaptic dysfunction and developmental delays. One aim of the Consortium is clinical trial readiness, including identifying clinical concepts and validating their measurement. We evaluated the scope and limitations of conventional cognitive and behavioral measurement strategies in 2-21-year-olds with Phelan-McDermid syndrome (PMS; N = 98), Tuberous Sclerosis Complex (TSC; N = 98), and PTEN Hamartoma Tumor syndrome (PHTS; N = 69). On average, intellectual disability (ID) severity was severe-to-profound in PMS, mild-to-moderate for TSC, and borderline (or absent) in PHTS. Severity of ID invalidated the use of many assessments, including standardized autism diagnostic measures. These results will inform trial planning for these and other similarly medically complex neurodevelopmental conditions. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2025 – Name: AN Label: Accession Number Group: ID Data: EJ1482498 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1482498 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1352/1944-7558-130.5.414 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 414 Subjects: – SubjectFull: Intellectual Disability Type: general – SubjectFull: Genetic Disorders Type: general – SubjectFull: Neurological Impairments Type: general – SubjectFull: Measurement Techniques Type: general – SubjectFull: Children Type: general – SubjectFull: Adolescents Type: general – SubjectFull: Young Adults Type: general – SubjectFull: Severity (of Disability) Type: general – SubjectFull: Measures (Individuals) Type: general – SubjectFull: Behavior Type: general – SubjectFull: Individual Development Type: general – SubjectFull: Cognitive Processes Type: general Titles: – TitleFull: Characterizing Developmental and Behavioral Profiles in Developmental Synaptopathies to Inform Clinical Trial Endpoints Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Latha Valluripalli Soorya – PersonEntity: Name: NameFull: Camille W. Brune – PersonEntity: Name: NameFull: Cristan A. Farmer – PersonEntity: Name: NameFull: Edith V. Ocampo – PersonEntity: Name: NameFull: Natalie I. Berger – PersonEntity: Name: NameFull: Deborah A. Pearson – PersonEntity: Name: NameFull: Robyn M. Busch – PersonEntity: Name: NameFull: Patricia Klaas – PersonEntity: Name: NameFull: Paige Siper – PersonEntity: Name: NameFull: Kristn Currans – PersonEntity: Name: NameFull: Amanda C. Gulsrud – PersonEntity: Name: NameFull: Jennifer M. Phillips – PersonEntity: Name: NameFull: Rajna Filip-Dhima – PersonEntity: Name: NameFull: Sarah E. O’Kelley – PersonEntity: Name: NameFull: Thomas W. Frazier – PersonEntity: Name: NameFull: Tess Levy – PersonEntity: Name: NameFull: Allison L. Wainer – PersonEntity: Name: NameFull: Joseph D. Buxbaum – PersonEntity: Name: NameFull: Craig M. Powell – PersonEntity: Name: NameFull: Jonathan A. Bernstein – PersonEntity: Name: NameFull: Simon K. Warfield – PersonEntity: Name: NameFull: Darcy A. Krueger – PersonEntity: Name: NameFull: E. Martina Bebin – PersonEntity: Name: NameFull: Hope Northrup – PersonEntity: Name: NameFull: Shafali S. Jeste – PersonEntity: Name: NameFull: Alexander Kolevzon – PersonEntity: Name: NameFull: Elizabeth Berry-Kravis – PersonEntity: Name: NameFull: Mustafa Sahin – PersonEntity: Name: NameFull: Siddharth Srivastava – PersonEntity: Name: NameFull: Audrey Thurm IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 1944-7515 – Type: issn-electronic Value: 1944-7558 Numbering: – Type: volume Value: 130 – Type: issue Value: 5 Titles: – TitleFull: American Journal on Intellectual and Developmental Disabilities Type: main |
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