Identifying major depressive disorder in older adults through naturalistic driving behaviors and machine learning
(2025) npj Digital Medicine, 8 (1), art. no. 102, .
Chen, C.a , Brown, D.C.a , Al-Hammadi, N.a , Bayat, S.b c , Dickerson, A.d , Vrkljan, B.e , Blake, M.a , Zhu, Y.a , Trani, J.-F.f g h i , Lenze, E.J.j , Carr, D.B.k , Babulal, G.M.a g i
a Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
b Department of Biomedical Engineering, Schuluch School of Engineering, University of Calgary, Calgary, AB, Canada
c Department of Geomatics Engineering, Schuluch School of Engineering, University of Calgary, Calgary, AB, Canada
d Department of Occupational Therapy, East Carolina University, Greenville, NC, United States
e Occupational Therapy, School of Rehabilitation Science, McMaster University, Hamilton, ON, Canada
f Brown School, Washington University in St. Louis, St. Louis, MO, United States
g Institute of Public Health, Washington University in St. Louis, St. Louis, MO, United States
h National Conservatory of Arts and Crafts, Paris, France
i Centre for Social Development in Africa, Faculty of Humanities, University of Johannesburg, Johannesburg, South Africa
j Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
k Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Depression in older adults is often underdiagnosed and has been linked to adverse outcomes, including motor vehicle crashes. With a growing population of older drivers in the United States, innovations in screening methods are needed to identify older adults at greatest risk of decline. This study used machine learning techniques to analyze real-world naturalistic driving data to identify depression status in older adults and examined whether specific demographics and medications improved model performance. We analyzed two years of GPS data from 157 older adults, including 81 with major depressive disorder, using XGBoost and logistic regression models. The top-performing model achieved an area under the curve of 0.86 with driving features combined with total medication use. These findings suggest that naturalistic driving data holds high potential as a functional digital neurobehavioral marker for AI identifying depression in older adults on a national scale, thereby ensuring equitable access to treatment. © The Author(s) 2025.
Funding details
National Institutes of HealthNIH
National Institute on AgingNIAR01AG068183, R01AG056466, R01AG067428
National Institute on AgingNIA
Document Type: Article
Publication Stage: Final
Source: Scopus
Heterogeneous clinical phenotypes of sporadic early-onset Alzheimer’s disease: a neuropsychological data-driven approach
(2025) Alzheimer’s Research and Therapy, 17 (1), art. no. 38, .
Putcha, D.a , Katsumi, Y.a , Touroutoglou, A.a , Eloyan, A.b , Taurone, A.b , Thangarajah, M.b , Aisen, P.c , Dage, J.L.d e , Foroud, T.e , Jack, C.R., Jr.f , Kramer, J.H.g , Nudelman, K.N.H.e , Raman, R.c , Vemuri, P.f , Atri, A.h , Day, G.S.i , Duara, R.j , Graff-Radford, N.R.i , Grant, I.M.k , Honig, L.S.l , Johnson, E.C.B.m , Jones, D.T.f , Masdeu, J.C.n , Mendez, M.F.o , Musiek, E.p , Onyike, C.U.q , Riddle, M.r , Rogalski, E.s , Salloway, S.r , Sha, S.t , Turner, R.S.u , Wingo, T.S.v , Wolk, D.A.w , Womack, K.p , Carrillo, M.C.x , Rabinovici, G.D.g , Dickerson, B.C.a , Apostolova, L.G.d e y , Hammers, D.B.d , Grant, I.z , Clark, D.z , Toga, A.z , Polsinelli, A.z , Newell, K.z , Murray, M.E.z , Lagarde, J.z , La Joie, R.z , Kukull, W.A.z , Koeppe, R.z , Kirby, K.z , Hammers, D.z , Grinberg, L.T.z , Ghetti, B.z , Beckett, L.z , the LEADS Consortiumz
a Frontotemporal Disorders Unit and Massachusetts Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 149 13th St, Charlestown, Boston, MA 02129, United States
b Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, RI 02912, United States
c Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, 92093, United States
d Department of Neurology, Indiana University School of Medicine, Indianapolis, IN 46202, United States
e Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, United States
f Department of Radiology, Mayo Clinic, Rochester, MN 55902, United States
g Department of Neurology, University of CA – San Francisco, San Francisco, CA 94143, United States
h Banner Sun Health Research Institute, Sun City, AZ 85351, United States
i Department of Neurology, Mayo Clinic in Florida, Jacksonville, FL 32224, United States
j Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL 33140, United States
k Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, IL, Chicago, 60611, Bangladesh
l Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, United States
m Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, United States
n Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, TX 77030, United States
o Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, United States
p Department of Neurology, Washington University in St. Louis, St. Louis, MO 63130, United States
q Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21218, United States
r Department of Neurology, Alpert Medical School, Brown University, Providence, RI 02912, United States
s Department of Neurology, University of Chicago, Chicago, IL 60615, United States
t Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA 94305, United States
u Department of Neurology, Georgetown University, Washington, DC 20057, United States
v Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, United States
w Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
x Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, IL 60631, United States
y Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, IN 46202, United States
Abstract
Background: The clinical presentations of early-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease are distinct, with EOAD having a more aggressive disease course with greater heterogeneity. Recent publications from the Longitudinal Early-Onset Alzheimer’s Disease Study (LEADS) described EOAD as predominantly amnestic, though this phenotypic description was based solely on clinical judgment. To better understand the phenotypic range of EOAD presentation, we applied a neuropsychological data-driven method to subtype the LEADS cohort. Methods: Neuropsychological test performance from 169 amyloid-positive EOAD participants were analyzed. Education-corrected normative comparisons were made using a sample of 98 cognitively normal participants. Comparing the relative levels of impairment between each cognitive domain, we applied a cut-off of 1 SD below all other domain scores to indicate a phenotype of “predominant” impairment in a given cognitive domain. Individuals were otherwise considered to have multidomain impairment. Whole-cortex general linear modeling of cortical atrophy was applied as an MRI-based validation of these distinct clinical phenotypes. Results: We identified 6 phenotypic subtypes of EOAD: Dysexecutive Predominant (22% of sample), Amnestic Predominant (11%), Language Predominant (11%), Visuospatial Predominant (15%), Mixed Amnestic/Dysexecutive Predominant (11%), and Multidomain (30%). These phenotypes did not differ by age, sex, or years of education. The APOE ɛ4 genotype was enriched in the Amnestic Predominant group, who were also rated as least impaired. Cortical thickness analysis validated these clinical phenotypes with dissociations in atrophy patterns observed between the Dysexecutive and Amnestic Predominant groups. In contrast to the heterogeneity observed from our neuropsychological data-driven approach, diagnostic classifications for this same sample based solely on clinical judgment indicated that 82% of individuals were amnestic-predominant, 9% were non-amnestic, 4% met criteria for Posterior Cortical Atrophy, and 5% met criteria for Primary Progressive Aphasia. Conclusion: A neuropsychological data-driven method to phenotype EOAD individuals uncovered a more detailed understanding of the presenting heterogeneity in this atypical AD sample compared to clinical judgment alone. Clinicians and patients may over-report memory dysfunction at the expense of non-memory symptoms. These findings have important implications for diagnostic accuracy and treatment considerations. © The Author(s) 2025.
Author Keywords
Alzheimer’s disease; Clinical; Cognition; Early-onset; Neuropsychology; Phenotypes; Variants
Funding details
Northwestern UniversityNU
Mayo Clinic
University of Southern CaliforniaUSC
Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University
Department of Radiology, Weill Cornell Medicine
School of Medicine, Indiana UniversityIUSM
Stanford UniversitySU
National Institute of Biomedical Imaging and BioengineeringNIBIB
University of ChicagoU of C
Harvard Medical SchoolHMS
Feinberg School of MedicineFSM
David Geffen School of Medicine, University of California, Los AngelesDGSOM
Massachusetts General HospitalMGH
University of California, DavisUCD
School of Medicine, Johns Hopkins UniversitySOM, JHU
University of CaliforniaUC
University of WashingtonUW
Perelman School of Medicine, University of Pennsylvania
National Institutes of HealthNIHS10RR021110, S10RR023401, S10RR023043
National Institutes of HealthNIH
National Institute on AgingNIAU24 AG072122
National Institute on AgingNIA
Alzheimer’s AssociationAAGENETICS-19–639372, LDRFP-21–824473, LDRFP-21–818464, LDRFP-21–828356
Alzheimer’s AssociationAA
P41EB015896
Document Type: Article
Publication Stage: Final
Source: Scopus
Lifespan in rodents with MYT1L heterozygous mutation
(2025) Scientific Reports, 15 (1), art. no. 4998, .
Schreiber, A.a , Swift, R.G.b c , Wilson, L.d , Kroll, K.L.e f , Dougherty, J.D.b c f , Maloney, S.E.b f
a Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110-1093, United States
b Department of Psychiatry, Washington University School of Medicine, Campus Box 8232, 660 South Euclid Avenue, St. Louis, MO 63110-1093, United States
c Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110-1093, United States
d Division of Comparative Medicine, Washington University School of Medicine, St. Louis, MO 63110-1093, United States
e Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63110-1093, United States
f Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, MO 63110-1093, United States
Abstract
MYT1L syndrome is a newly recognized disorder characterized by intellectual disability, speech and motor delay, neuroendocrine disruptions, ADHD, and autism. In order to study this gene and its association with these phenotypes, our lab recently created a Myt1l heterozygous mutant mouse inspired by a clinically relevant mutation. This model recapitulates several of the physical and neurologic abnormalities seen in humans with MYT1L syndrome, such as weight gain, microcephaly, and behavioral disruptions. The majority of patients with this syndrome are young, and little is known about the impact of age on health and mortality in these patients. Using a Myt1l mutant mouse, we examined the impact of Myt1l mutation on body weights, lifespan, and histopathology findings of mice at the end of life. This cohort of heterozygous mice demonstrated increased body weight across the lifespan, however there was no significant difference in lifespan, apparent cause of death, or end of life histopathological findings between Myt1l heterozygous and wildtype mice. These findings suggest while Myt1l heterozygous mutation may influence overall brain development, it does not strongly impact other organ systems in the body over time. © The Author(s) 2025.
Author Keywords
Lifespan; MYT1L syndrome; Neurodevelopmental disorders; Obesity
Funding details
Intellectual and Developmental Disabilities Research CenterIDDRC
National Institute of Mental HealthNIMHR01MH124808
National Institute of Mental HealthNIMH
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHDP50HD103525
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHD
Document Type: Article
Publication Stage: Final
Source: Scopus
A synthetic chronogenetic gene circuit for programmed circadian drug delivery
(2025) Nature Communications, 16 (1), art. no. 1457, .
Pferdehirt, L.a b c d , Damato, A.R.e , Lenz, K.L.a b c , Gonzalez-Aponte, M.F.e , Palmer, D.a b c d , Meng, Q.-J.f , Herzog, E.D.e , Guilak, F.a b c d
a Department of Orthopedic Surgery, Washington University School of Medicine, St. Louis, MO, United States
b Shriners Hospitals for Children – Saint Louis, St. Louis, MO, United States
c Center of Regenerative Medicine, Washington University School of Medicine, St. Louis, MO, United States
d Department of Biomedical Engineering, Washington University, St. Louis, MO, United States
e Department of Biology, Washington University, St. Louis, MO, United States
f Wellcome Centre for Cell Matrix Research, Division of Cell Matrix Biology and Regenerative Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
Abstract
Circadian medicine, the delivery of therapeutic interventions based on an individual’s daily rhythms, has shown improved efficacy and reduced side-effects for various treatments. Rheumatoid arthritis and other inflammatory diseases are characterized by diurnal changes in cytokines, leading to inflammatory flares, with peak disease activity in the early morning. Using a combination of synthetic biology and tissue engineering, we developed circadian-based gene circuits, termed “chronogenetics”, that express a prescribed transgene downstream of the core clock gene promoter, Period2 (Per2). Gene circuits were transduced into induced pluripotent stem cells that were tissue-engineered into cartilage constructs. Our anti-inflammatory chronogenetic constructs produced therapeutic concentrations of interleukin-1 receptor antagonist in vitro. Once implanted in vivo, the constructs expressed circadian rhythms and entrained to daily light cycles, producing daily increases in biologic drug at the peak of Per2 expression. This approach represents the development of a cell-based chronogenetic therapy for various applications in circadian medicine. © The Author(s) 2025.
Funding details
Shriners Hospitals for Children
Medical Research CouncilMRC
Center of Regenerative Medicine, Washington University in St. LouisCRM, WUSTL
Memphis Research ConsortiumMRCMR/K019392/1
National Institutes of HealthNIHAR080902, AG46927, AR078949, AR073752, AR072999, AR074992, AG15768, GM131403
F31CA250161, 20875
Document Type: Article
Publication Stage: Final
Source: Scopus
Association between Sun Exposure and Risk of Relapse in Pediatric-Onset Multiple Sclerosis
(2025) Neurology: Neuroimmunology and NeuroInflammation, 12 (2), art. no. e200375, .
Chang, G.a , Sebastian, P.b , Virupakshaiah, A.c , Schoeps, V.A.c , Cherbuin, N.d , Casper, T.C.e , Gorman, M.P.f , Benson, L.A.f , Chitnis, T.g h , Rensel, M.i , Abrams, A.W.i , Lotze, T.j , Mar, S.S.k , Schreiner, T.L.l m , Wheeler, Y.S.n , Rose, J.W.o , Graves, J.p , Krupp, L.B.q , Waldman, A.T.a , Lucas, R.r , Waubant, E.c , The US Network of Pediatric Multiple Sclerosis Centerss
a Division of Child Neurology, The Children’s Hospital of Philadelphia, Philadelphia, PA, United States
b Liverpool Hospital, Sydney, Australia
c UCSF Weill Institute for Neurosciences, University of California, San Francisco, United States
d Centre for Research on Ageing Health and Wellbeing, Australian National University, Canberra, Australia
e University of Utah, School of Medicine, Salt Lake City, United States
f Boston Children’s HospitalMA, United States
g Brigham and Women’s Hospital, Boston, MA, United States
h Harvard Medical School, Boston, MA, United States
i Cleveland ClinicOH, United States
j Texas Children’s Hospital, Houston, TX, United States
k Washington University, St. Louis, MO, United States
l Children’s Hospital Colorado, Aurora, United States
m University of Colorado, Aurora, United States
n Children’s Hospital of Alabama, Birmingham, United States
o George E. Wahlen Department of Veterans Affairs Medical Center, University of Utah, Salt Lake City, United States
p University of California, San Diego, CA, United States
q NYU Grossman School of Medicine, New York, NY, United States
r National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
Abstract
Background and ObjectivesLow sun and ultraviolet radiation (UVR) exposures have been associated with increased risk of developing pediatric-onset multiple sclerosis (MS); however, their effect on disease course has not been well characterized. We primarily investigated whether there was an association between time spent in the sun in early childhood and risk of relapse in pediatric MS. We secondarily investigated the effect of sun exposure during more recent periods on risk of relapse.MethodsWe conducted a multicenter cohort study of participants with pediatric-onset MS recruited from 18 pediatric MS clinics across the United States between November 1, 2011, and July 1, 2017. Relapses were identified prospectively after study enrollment; relapses preceding study enrollment were entered retrospectively. Time spent in the sun at various periods of life was measured using a detailed environmental questionnaire, and ambient UVR exposure was determined using zip codes. Multivariable Cox regression models were used to assess the association between time spent in the sun and UVR dose at specific periods of life and the risk of relapse. Models were adjusted for demographic, clinical, and sun exposure-related characteristics.ResultsIn our cohort of 334 children with MS, 206 (62%) experienced at least one relapse from disease onset to the end of the follow-up period. After adjustment, ≥30 minutes of daily sun exposure during the first summer of life was associated with a lower risk of relapse compared with <30 minutes (adjusted hazard ratio [aHR] 0.67, CI 0.48-0.92, p = 0.01). Greater time spent in the sun during the second trimester of pregnancy was also associated with reduced risk of relapse (aHR 0.68, CI 0.48-0.97, p = 0.04). UVR dose and time spent in the sun later in life were not significantly associated with relapse risk.DiscussionIn this large cohort study of children with MS, greater early childhood and prenatal sun exposure time was associated with lower risk of relapse. Further investigation of sun exposure at other periods is needed to better characterize its impact on disease course and guide potential future interventions. © 2025 American Academy of Neurology.
Funding details
National Multiple Sclerosis SocietyNMSSHC-1509-06233
National Multiple Sclerosis SocietyNMSS
Document Type: Article
Publication Stage: Final
Source: Scopus
Psychological Support Approaches in Psychedelic Therapy: Results From a Survey of Psychedelic Practitioners
(2025) The Journal of Clinical Psychiatry, 86 (1), .
Bender, D.A.a b , Nayak, S.M.c , Siegel, J.S.a d , Hellerstein, D.J.e f , Ercal, B.C.a , Lenze, E.J.a
a Washington University School of Medicine, Saint Louis, Missouri
b Corresponding Author: David A. Bender, MD, Washington University in St. Louis School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63110 ()
c Johns Hopkins University School of Medicine, Baltimore, MD, Liberia
d Department of Psychiatry, New York University Grossman School of MedicineNY, United States
e Columbia University Vagelos College of Physicians and SurgeonsNY, United States
f New York State Psychiatric InstituteNY, United States
Abstract
Objective: To assess the viewpoints of psychedelic practitioners in research settings on approaches to psychological support for psychedelic treatments. Methods: An anonymous survey was distributed via email to contacts listed on ClinicalTrials.gov for clinical trials of psilocybin and LSD, personal contacts of authors, and through snowball sampling. The survey included Likert type, multiple choice, free response, and demographic items. Responses to survey items were coded to represent either emotive (emphasizing human and spiritual elements) or neuromodulatory (emphasizing biological drug effects) approaches to psychedelic treatment. Summative scores (“E-Scores”) were determined to quantitatively represent preferences. Data were collected from March 2023 to July 2023. Results: Forty qualified respondents completed the survey. Respondents came from varying educational backgrounds (42.5% MD/DO and 57.5% other) and practiced in at least 4 countries, 11 U.S. states, and 16 institutions. Respondents had overseen a total of 1,656 psychedelic sessions (average = 41.4). There was a substantial range of response for many items (average range = 84.2% of maximum). Exploratory factor analysis identified 4 latent factors: The Importance of Trust, The Role of Spirituality, Creating an Emotional Setting, and Conceptualizing Negative Experiences. The average respondent held a slight preference for an emotive approach. Respondents who received training at the Multidisciplinary Association for Psychedelic Studies (MAPS) or the California Institute of Integral Studies (CIIS) had significantly greater emotive preference compared to other respondents (P < .05). Conclusions: Among psychedelic researchers, there is no consensus on certain psychological support strategies for psychedelic treatments. There is an aggregate preference for an emotive approach to psychological support, which is higher among individuals receiving training at certain institutions. © Copyright 2025 Physicians Postgraduate Press, Inc.
Document Type: Article
Publication Stage: Final
Source: Scopus
Single-Gene Deletion of FGF3 in a Patient With Features of 11q13 Microdeletion Syndrome
(2025) American Journal of Medical Genetics, Part A, .
Rahi, H.a , Dickson, P.I.b c , Toler, T.L.c , Corliss, M.M.a , Cao, Y.a
a Department of Pathology & Immunology, Washington University School of Medicine, Saint Louis, MO, United States
b Department of Genetics, Washington University School of Medicine, Saint Louis, MO, United States
c Department of Pediatrics, Washington University School of Medicine, Saint Louis, MO, United States
Abstract
Chromosome 11q13 microdeletion syndrome, or otodental syndrome, involves dental, auditory, and ocular anomalies linked to deletions in the 11q13.2q13.4 region. We report a 1-year-old girl with a 43 kb deletion of the FGF3 gene on chromosome 11q13.3, exhibiting otodental dysplasia, hearing difficulty, and developmental delay. Her family history includes permanent childhood hearing loss and otodental syndrome. Chromosomal microarray analysis (CMA) and sequencing confirmed a complete heterozygous deletion of FGF3. This case suggests that FGF3 haploinsufficiency is sufficient to cause the syndrome’s key clinical features, emphasizing the need for further research and long-term follow-up. © 2025 Wiley Periodicals LLC.
Author Keywords
11q13 microdeletion; chromosomal microarray analysis; FGF3
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Sequence variants in HECTD1 result in a variable neurodevelopmental disorder
(2025) American Journal of Human Genetics, .
Zerafati-Jahromi, G.a , Oxman, E.e , Hoang, H.D.d , Charng, W.-L.a , Kotla, T.d , Yuan, W.d , Ishibashi, K.e , Sebaoui, S.f , Luedtke, K.e , Winrow, B.e , Ganetzky, R.D.g h i , Ruiz, A.j , Manso-Basúz, C.j , Spataro, N.j , Kannu, P.k , Athey, T.k , Peroutka, C.l , Barnes, C.l , Sidlow, R.m , Anadiotis, G.n , Magnussen, K.n , Valenzuela, I.o , Moles-Fernandez, A.o , Berger, S.p , Grant, C.L.p , Vilain, E.aa , Arnadottir, G.A.q , Sulem, P.q , Sulem, T.S.q , Stefansson, K.q , Massey, S.r , Ginn, N.r , Poduri, A.s v , D’Gama, A.M.u v w , Valentine, R.v , Trowbridge, S.K.s t , Murali, C.N.x , Franciskovich, R.x , Tran, Y.y , Webb, B.D.z , Keppler-Noreuil, K.M.z , Hall, A.L.z , McGivern, B.ab , Monaghan, K.G.ab , Guillen Sacoto, M.J.ab , Baldridge, D.d , Silverman, G.A.d , Dahiya, S.b , Turner, T.N.c , Schedl, T.c , Corbin, J.G.f , Pak, S.C.d , Zohn, I.E.e , Gurnett, C.A.a
a Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
b Department of Pathology, Washington University in St. Louis, St. Louis, MO, United States
c Department of Genetics, Washington University in St. Louis, St. Louis, MO, United States
d Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, United States
e Center for Genetic Medicine Research, Children’s National Hospital, Washington, DC, United States
f Center for Neuroscience Research, Children’s National Hospital, Washington, DC, United States
g Mitochondrial Medicine Frontier Program, Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
h Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
i Center for Computational Genomics Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
j Center for Genomic Medicine, Parc Taulí Hospital University, Parc Taulí Institute of Research and Innovation (I3PT-CERCA), Autonomous University of Barcelona, Sabadell, Spain
k Department of Medical Genetics, Alberta Health Services, Edmonton, AB, Canada
l Department of Pediatrics, University of Virginia, Charlottesville, VA, United States
m Department of Medical Genetics and Metabolism, Valley Children’s Hospital, Madera, CA, United States
n Department of Genetics and Metabolism, Randall Children’s Hospital at Legacy Emanuel, Portland, OR, United States
o Department of Clinical and Molecular Genetics, University Hospital Vall d’Hebron and Medicine Genetics Group, Valle Hebron Research Institute, Barcelona, Spain
p Rare Disease Institute, Children’s National Hospital, Washington, DC, United States
q deCODE Genetics/Amgen Inc., Reykjavik, Iceland
r Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
s Department of Neurology, Boston Children’s Hospital, Boston, MA, United States
t Department of Neurology, Harvard Medical School, Boston, MA, United States
u Division of Newborn Medicine, Boston Children’s Hospital, Boston, MA, United States
v Epilepsy Genetics Program, Department of Neurology, Boston Children’s Hospital, Boston, MA, United States
w Department of Pediatrics, Harvard Medical School, Boston, MA, United States
x Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
y Department of Neurology, Baylor College of Medicine, Houston, TX, United States
z Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States
aa Institute for Clinical and Translational Science, University of California, Irvine, Irvine, CA, United States
ab GeneDx, Gaithersburg, MD, United States
Abstract
Dysregulation of genes encoding the homologous to E6AP C-terminus (HECT) E3 ubiquitin ligases has been linked to cancer and structural birth defects. One member of this family, the HECT-domain-containing protein 1 (HECTD1), mediates developmental pathways, including cell signaling, gene expression, and embryogenesis. Through GeneMatcher, we identified 14 unrelated individuals with 15 different variants in HECTD1 (10 missense, 3 frameshift, 1 nonsense, and 1 splicing variant) with neurodevelopmental disorders (NDDs), including autism, attention-deficit/hyperactivity disorder, and epilepsy. Of these 15 HECTD1 variants, 10 occurred de novo, 3 had unknown inheritance, and 2 were compound heterozygous. While all individuals in this cohort displayed NDDs, no genotype-phenotype correlation was apparent. Conditional knockout of Hectd1 in the neural lineage in mice resulted in microcephaly, severe hippocampal malformations, and complete agenesis of the corpus callosum, supporting a role for Hectd1 in embryonic brain development. Functional studies of select variants in C. elegans revealed dominant effects, including either change-of-function or loss-of-function/haploinsufficient mechanisms, which may explain phenotypic heterogeneity. Significant enrichment of de novo variants in HECTD1 was also shown in an independent cohort of 53,305 published trios with NDDs or congenital heart disease. Thus, our clinical and functional data support a critical requirement of HECTD1 for human brain development. © 2025 The Authors
Author Keywords
autism; epilepsy; HECTD1; neurodevelopmental disorders; ubiquitin-proteasome system
Funding details
National Institutes of HealthNIH
Children’s Discovery InstituteCDI
National Center for Advancing Translational SciencesNCATS
University of WashingtonUWR01HD110556
University of WashingtonUW
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHDP50HD103525
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHD
R01HD098861
National Human Genome Research InstituteNHGRI1U01HG011745
National Human Genome Research InstituteNHGRI
P50HD105328
Institute of Clinical and Translational SciencesICTSUL1TR002345
Institute of Clinical and Translational SciencesICTS
Document Type: Article
Publication Stage: Article in Press
Source: Scopus