Examining time-varying dynamics of co-occurring depressed mood and anxiety
(2024) Journal of Affective Disorders, 362, pp. 24-35.
Piccirillo, M.L.a b , Frumkin, M.R.c d , Spink, K.M.a , Tonge, N.A.e , Foster, K.T.a f
a University of Washington, Department of Psychology, United States
b Rutgers Robert Wood Johnson Medical School, Department of Psychiatry, United States
c Washington University in St. Louis, Department of Psychology and Brain Sciences, United States
d Massachusetts General Hospital, Department of Psychiatry, United States
e George Mason University, Department of Psychology, United States
f University of Washington, Department of Global Health, United States
Abstract
Background: Dimensional frameworks of psychopathology call for multivariate approaches to map co-occurring disorders to index what symptoms emerge when and for whom. Ecological momentary assessment (EMA) offers a method for assessing and differentiating the dynamics of co-occurring symptoms with greater temporal granularity and naturalistic context. The present study used multivariate mixed effects location-scale modeling to characterize the time-varying dynamics of depressed mood and anxiety for women diagnosed with social anxiety disorder (SAD) and major depression (MDD). Methods: Women completed five daily EMA surveys over 30 days (150 EMA surveys/woman, T ≈ 5250 total observations) and two clinical diagnostic and retrospective self-report measures administered approximately two months apart. Results: There was evidence of same-symptom lagged effects (bs = 0.08–0.09), but not cross-symptom lagged effects (bs < 0.01) during EMA. Symptoms co-varied such that momentary spikes from one’s typical level of anxiety were associated with increases in momentary depressed mood (b = 0.19) and greater variability of depressed mood (b = 0.06). Similarly, spikes from one’s typical levels of depressed mood were associated with increases in momentary anxiety (b = 0.19). Furthermore, the presence and magnitude of effects demonstrated person-specific heterogeneity. Limitations: Our findings are constrained to the dynamics of depressed and anxious mood among cisgender women with primary SAD and current or past MDD. Conclusions: Findings from this work help to characterize how daily experiences of co-occurring mood and anxiety fluctuate and offer insight to aid the development of momentary, person-specific interventions designed to regulate symptom fluctuations. © 2024
Author Keywords
Affective dynamics; Ecological momentary assessment; Heterogeneity; HiTOP; Internalizing
Funding details
National Science FoundationNSF
National Institutes of HealthNIHF31MH115641, K99AA029459, T32AA007455, F31MH124291
National Institutes of HealthNIH
Document Type: Article
Publication Stage: Final
Source: Scopus
Multi-scale signaling and tumor evolution in high-grade gliomas
(2024) Cancer Cell, 42 (7), pp. 1217-1238.e19.
Liu, J.a b , Cao, S.a b , Imbach, K.J.c d , Gritsenko, M.A.e , Lih, T.-S.M.f , Kyle, J.E.e , Yaron-Barir, T.M.g h i , Binder, Z.A.j , Li, Y.a b , Strunilin, I.a b , Wang, Y.-T.e , Tsai, C.-F.e , Ma, W.k , Chen, L.f , Clark, N.M.l , Shinkle, A.a b , Naser Al Deen, N.a b , Caravan, W.a b , Houston, A.a b , Simin, F.A.a b , Wyczalkowski, M.A.a b , Wang, L.-B.a b , Storrs, E.a b , Chen, S.a b , Illindala, R.a m n , Li, Y.D.a m n , Jayasinghe, R.G.a b , Rykunov, D.k , Cottingham, S.L.o , Chu, R.K.p , Weitz, K.K.e , Moore, R.J.e , Sagendorf, T.e , Petyuk, V.A.e , Nestor, M.e , Bramer, L.M.e , Stratton, K.G.e , Schepmoes, A.A.e , Couvillion, S.P.e , Eder, J.e , Kim, Y.-M.e , Gao, Y.e , Fillmore, T.L.o , Zhao, R.e , Monroe, M.E.e , Southard-Smith, A.N.a b , Li, Y.E.q r , Jui-Hsien Lu, R.a b , Johnson, J.L.g , Wiznerowicz, M.s t , Hostetter, G.u , Newton, C.J.u , Ketchum, K.A.v , Thangudu, R.R.v , Barnholtz-Sloan, J.S.w , Wang, P.k , Fenyö, D.x y , An, E.z , Thiagarajan, M.aa , Robles, A.I.z , Mani, D.R.l , Smith, R.D.e , Porta-Pardo, E.c , Cantley, L.C.g ab ac , Iavarone, A.ad ae , Chen, F.a m , Mesri, M.z , Nasrallah, M.P.af , Zhang, H.f ag ah , Resnick, A.C.ai aj , Chheda, M.G.a m n , Rodland, K.D.ak , Liu, T.e , Ding, L.a b m q , Philadelphia Coalition for a Cureal , Clinical Proteomic Tumor Analysis Consortiumal
a Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, United States
b McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, United States
c Josep Carreras Leukaemia Research Institute, Badalona, Spain
d Universidad Autónoma de Barcelona, Barcelona, Bellaterra, 08193, Spain
e Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
f Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States
g Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10021, United States
h Englander Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, United States
i Columbia University Vagelos College of Physicians and Surgeons, New York, NY 10032, United States
j Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
k Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
l The Broad Institute of MIT and Harvard, Cambridge, MA 02142, United States
m Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63130, United States
n Department of Neurology, Washington University in St. Louis, St. Louis, MO 63130, United States
o Department of Pathology, Spectrum Health and Helen DeVos Children’s Hospital, Grand Rapids, MI, United States
p Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, United States
q Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, United States
r Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO 63110, United States
s International Institute for Molecular Oncology, Poznań, Poland
t Poznan University of Medical Sciences, Poznań, Poland
u Van Andel Research Institute, Grand Rapids, MI, United States
v ICF, 530 Gaither Road Suite 500, Rockville, MD 20850, United States
w Center for Biomedical Informatics and Information Technology & Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20850, United States
x Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, United States
y Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, United States
z Office of Cancer Clinical Proteomics Research, National Cancer Institute, Rockville, MD 20850, United States
aa Frederick National Laboratory for Cancer Research, Frederick, MD 21701, United States
ab Department of Cell Biology, Harvard Medical School, Boston, MA 02115, United States
ac Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, United States
ad Department of Neurological Surgery and Department of Biochemistry, University of Miami Miller School of Medicine, Miami, FL 33136, United States
ae Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, United States
af Department of Pathology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
ag Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States
ah Department of Urology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States
ai Center for Data Driven Discovery in Biomedicine, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, United States
aj Division of Neurosurgery, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, United States
ak Department of Cell, Developmental, and Cancer Biology, Oregon Health & Science University, Portland, OR 97221, United States
Abstract
Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas. © 2024 The Authors
Author Keywords
CPTAC; glioblastoma; glycoproteomics; lipidome; metabolome; proteomics; single nuclei ATAC-seq; single nuclei RNA-seq; tumor recurrence
Funding details
Merck
Pacific Northwest National LaboratoryPNNL
U.S. Department of EnergyUSDOE
Orbus Therapeutics
BattelleBMI
DE-AC05-76RL01830
LABAE20038PORT
P41-GM103311
National Institutes of HealthNIHRYC2019-026415-I, PID2019- 107043RA-I00
National Institutes of HealthNIH
National Human Genome Research InstituteNHGRIR01NS107833, R01NS117149
National Human Genome Research InstituteNHGRI
R01HG009711
Document Type: Article
Publication Stage: Final
Source: Scopus
Pathogenic variants in autism gene KATNAL2 cause hydrocephalus and disrupt neuronal connectivity by impairing ciliary microtubule dynamics
(2024) Proceedings of the National Academy of Sciences of the United States of America, 121 (27), pp. e2314702121.
DeSpenza, T., Jra b c , Singh, A.c , Allington, G.d e , Zhao, S.f , Lee, J.g , Kizlitug, E.c , Prina, M.L.g , Desmet, N.g , Dang, H.Q.g , Fields, J.h , Nelson-Williams, C.c , Zhang, J.c , Mekbib, K.Y.c g , Dennis, E.e , Mehta, N.H.e , Duy, P.Q.a , Shimelis, H.i , Walsh, L.K.i , Marlier, A.a , Deniz, E.j , Lake, E.M.R.k , Constable, R.T.k , Hoffman, E.J.a l , Lifton, R.P.m , Gulledge, A.g , Fiering, S.h , Moreno-De-Luca, A.i n , Haider, S.o , Alper, S.L.p q , Jin, S.C.f , Kahle, K.T.c e q r , Luikart, B.W.g
a Interdepartmental Neuroscience Program, Yale School of Medicine, Yale University, CT 06510, New Haven, United States
b Medical Scientist Training Program, Yale School of Medicine, Yale University, CT 06510, New Haven, United States
c Department of Neurosurgery, Yale School of Medicine, Yale University, CT 06510, New Haven, United States
d Department of Pathology, Yale School of Medicine, Yale University, CT 06510, New Haven, United States
e Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, United States
f Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, United States
g Department of Molecular and Systems Biology, Geisel School of Medicine at DartmouthHanover NH 03755, Jamaica
h Department of Microbiology and Immunology, Geisel School of Medicine at DartmouthHanover NH 03755, Jamaica
i Autism and Developmental Medicine Institute, Geisinger, PA 17821, Danville, United States
j Department of Pediatrics, Yale University School of Medicine, CT 06510, New Haven, United States
k Department of Radiology and Biomedical Imaging, Yale University School of Medicine, CT 06520-8042, New Haven, United States
l Child Study Center, Yale School of Medicine, CT 06510, New Haven, United States
m Laboratory of Human Genetics and Genomics, Rockefeller University, NY, NY 10065, United States
n Department of Radiology, Diagnostic Medicine Institute, Geisinger, PA 17821, Danville, United States
o Department of Pharmaceutical and Biological Chemistry, University College London School of Pharmacy, London, WC1N 1AX, United Kingdom
p Division of Nephrology and Center for Vascular Biology Research, Beth Israel Deaconess Medical Center, Department of Medicine, Harvard Medical School, Boston, MA 02215, United States
q Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, United Kingdom
r Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115, United States
Abstract
Enlargement of the cerebrospinal fluid (CSF)-filled brain ventricles (cerebral ventriculomegaly), the cardinal feature of congenital hydrocephalus (CH), is increasingly recognized among patients with autism spectrum disorders (ASD). KATNAL2, a member of Katanin family microtubule-severing ATPases, is a known ASD risk gene, but its roles in human brain development remain unclear. Here, we show that nonsense truncation of Katnal2 (Katnal2Δ17) in mice results in classic ciliopathy phenotypes, including impaired spermatogenesis and cerebral ventriculomegaly. In both humans and mice, KATNAL2 is highly expressed in ciliated radial glia of the fetal ventricular-subventricular zone as well as in their postnatal ependymal and neuronal progeny. The ventriculomegaly observed in Katnal2Δ17 mice is associated with disrupted primary cilia and ependymal planar cell polarity that results in impaired cilia-generated CSF flow. Further, prefrontal pyramidal neurons in ventriculomegalic Katnal2Δ17 mice exhibit decreased excitatory drive and reduced high-frequency firing. Consistent with these findings in mice, we identified rare, damaging heterozygous germline variants in KATNAL2 in five unrelated patients with neurosurgically treated CH and comorbid ASD or other neurodevelopmental disorders. Mice engineered with the orthologous ASD-associated KATNAL2 F244L missense variant recapitulated the ventriculomegaly found in human patients. Together, these data suggest KATNAL2 pathogenic variants alter intraventricular CSF homeostasis and parenchymal neuronal connectivity by disrupting microtubule dynamics in fetal radial glia and their postnatal ependymal and neuronal descendants. The results identify a molecular mechanism underlying the development of ventriculomegaly in a genetic subset of patients with ASD and may explain persistence of neurodevelopmental phenotypes in some patients with CH despite neurosurgical CSF shunting.
Author Keywords
autism; cerebrospinal fluid dynamics; ciliopathy; hydrocephalus; structural brain disorder
Document Type: Article
Publication Stage: Final
Source: Scopus
Multi-Tracer Studies of Brain Oxygen and Glucose Metabolism Using a Time-of-Flight Positron Emission Tomography – Computed Tomography Scanner
(2024) Journal of Visualized Experiments: JoVE, (208), .
Lee, J.J.a , Metcalf, N.a , Durbin, T.A.a , Byers, J.a , Casey, K.a , Jafri, H.a , Goyal, M.S.b , Vlassenko, A.G.a
a Mallinckrodt Institute of Radiology, Washington University School of Medicine
b Mallinckrodt Institute of Radiology, Washington University School of Medicine;
Abstract
The authors have developed a paradigm using positron emission tomography (PET) with multiple radiopharmaceutical tracers that combines measurements of cerebral metabolic rate of glucose (CMRGlc), cerebral metabolic rate of oxygen (CMRO2), cerebral blood flow (CBF), and cerebral blood volume (CBV), culminating in estimates of brain aerobic glycolysis (AG). These in vivo estimates of oxidative and non-oxidative glucose metabolism are pertinent to the study of the human brain in health and disease. The latest positron emission tomography-computed tomography (PET-CT) scanners provide time-of-flight (TOF) imaging and critical improvements in spatial resolution and reduction of artifacts. This has led to significantly improved imaging with lower radiotracer doses. Optimized methods for the latest PET-CT scanners involve administering a sequence of inhaled 15O-labeled carbon monoxide (CO) and oxygen (O2), intravenous 15O-labeled water (H2O), and 18F-deoxyglucose (FDG)-all within 2-h or 3-h scan sessions that yield high-resolution, quantitative measurements of CMRGlc, CMRO2, CBF, CBV, and AG. This methods paper describes practical aspects of scanning designed for quantifying brain metabolism with tracer kinetic models and arterial blood samples and provides examples of imaging measurements of human brain metabolism.
Document Type: Article
Publication Stage: Final
Source: Scopus
The impact of clinical genome sequencing in a global population with suspected rare genetic disease
(2024) American Journal of Human Genetics, .
Thorpe, E.a , Williams, T.b , Shaw, C.b c d , Chekalin, E.a , Ortega, J.a e , Robinson, K.a , Button, J.a , Jones, M.C.f g , Campo, M.D.f g , Basel, D.h , McCarrier, J.h , Keppen, L.D.i , Royer, E.j , Foster-Bonds, R.k , Duenas-Roque, M.M.l , Urraca, N.m , Bosfield, K.m , Brown, C.W.m , Lydigsen, H.m , Mroczkowski, H.J.m , Ward, J.m , Sirchia, F.n o , Giorgio, E.n p , Vaux, K.q , Salguero, H.P.r , Lumaka, A.s t , Mubungu, G.s , Makay, P.s , Ngole, M.s , Lukusa, P.T.s , Vanderver, A.u v , Muirhead, K.w , Sherbini, O.u , Lah, M.D.x , Anderson, K.x , Bazalar-Montoya, J.y , Rodriguez, R.S.y , Cornejo-Olivas, M.z aa , Milla-Neyra, K.z , Shinawi, M.ab ac , Magoulas, P.ad , Henry, D.ae , Gibson, K.af , Wiafe, S.ag , Jayakar, P.ah , Salyakina, D.ah , Masser-Frye, D.f ai , Serize, A.aj , Perez, J.E.aj , Taylor, A.ak , Shenbagam, S.ak , Abou Tayoun, A.ak al , Malhotra, A.a , Bennett, M.a , Rajan, V.a am , Avecilla, J.a , Warren, A.a , Arseneault, M.a , Kalista, T.a , Crawford, A.a , Ajay, S.S.a , Perry, D.L.a , Belmont, J.b , Taft, R.J.a
a Illumina Inc, San Diego, CA, United States
b Genetic and Genomic Services PBC, Houston, TX, United States
c Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
d Department of Statistics, Rice University, Houston, TX, United States
e C2N Diagnostics, St. Louis, MO, United States
f Rady Children’s Hospital, San Diego, CA, United States
g University of California, San Diego, San Diego, CA, United States
h Department of Pediatrics, Medical College of Wisconsin, Milwaukee, WI, United States
i Sanford USD Medical Center, Sioux Falls, SD, United States
j Sanford Children’s Specialty Clinics at Sanford Health, USD Sanford School of Medicine, Sioux Falls, SD, United States
k Rare Genomics Institute, Los Angeles, CA, United States
l Servicio de Genética, Hospital Edgardo Rebagliati Martins – EsSalud, Lima, Peru
m University of Tennessee Health Science Center, Le Bonheur Children’s Hospital, Memphis, TN, United States
n Department of Molecular Medicine, University of Pavia, Pavia, Italy
o Medical Genetics Unit, IRCCS San Matteo Foundation, Pavia, Italy
p Medical Genetics Unit, IRCCS Mondino Foundation, Pavia, Italy
q Point Loma Pediatrics, San Diego, CA, United States
r Padrino Children’s Foundation, B.C.S., Todos Santos, Mexico
s Centre de Genetique Humaine, Universite de Kinshasa, Kinshasa, Democratic Republic Congo
t Center for Human Genetics, Centre Hospitalier Universitaire, Liège, Belgium
u Division of Neurology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
v Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
w Ambry Genetics, Aliso Viejo, CA, United States
x Indiana University School of Medicine, Indianapolis, IN, United States
y Instituto Nacional de Salud del Niño-San Borja, Lima, Peru
z Neurogenetics Research Center, Instituto Nacional de Ciencias Neurologicas, Lima, Peru
aa Neurogenetics Working Group, Universidad Científica del Sur, Lima, Peru
ab Washington University, St. Louis, MO, United States
ac St. Louis Children’s Hospital, St. Louis, MO, United States
ad Texas Children’s Hospital, Houston, TX, United States
ae UCSF Benioff Children’s Hospitals, San Francisco, CA, United States
af Canterbury District Health Board, Canterbury, New Zealand
ag Rare Disease Ghana Initiative, Accra, Ghana
ah Nicklaus Children’s Health System, Miami, FL, United States
ai San Diego-Imperial Counties Developmental Services, Inc., San Diego, CA, United States
aj South Miami Hospital, South Miami, FL, United States
ak Al Jalila Genomics Center of Excellence, Al Jalila Children’s Specialty Hospital, Dubai, United Arab Emirates
al Center for Genomic Discovery, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
am Veracyte, San Diego, CA, United States
Abstract
There is mounting evidence of the value of clinical genome sequencing (cGS) in individuals with suspected rare genetic disease (RGD), but cGS performance and impact on clinical care in a diverse population drawn from both high-income countries (HICs) and low- and middle-income countries (LMICs) has not been investigated. The iHope program, a philanthropic cGS initiative, established a network of 24 clinical sites in eight countries through which it provided cGS to individuals with signs or symptoms of an RGD and constrained access to molecular testing. A total of 1,004 individuals (median age, 6.5 years; 53.5% male) with diverse ancestral backgrounds (51.8% non-majority European) were assessed from June 2016 to September 2021. The diagnostic yield of cGS was 41.4% (416/1,004), with individuals from LMIC sites 1.7 times more likely to receive a positive test result compared to HIC sites (LMIC 56.5% [195/345] vs. HIC 33.5% [221/659], OR 2.6, 95% CI 1.9–3.4, p < 0.0001). A change in diagnostic evaluation occurred in 76.9% (514/668) of individuals. Change of management, inclusive of specialty referrals, imaging and testing, therapeutic interventions, and palliative care, was reported in 41.4% (285/694) of individuals, which increased to 69.2% (480/694) when genetic counseling and avoidance of additional testing were also included. Individuals from LMIC sites were as likely as their HIC counterparts to experience a change in diagnostic evaluation (OR 6.1, 95% CI 1.1–∞, p = 0.05) and change of management (OR 0.9, 95% CI 0.5–1.3, p = 0.49). Increased access to genomic testing may support diagnostic equity and the reduction of global health care disparities. © 2024 The Authors
Author Keywords
change of management; clinical genome testing; clinical utility; diagnostic equity; genetic testing; low- and middle-income; rare disease; rare genetic disease; whole-genome sequencing
Funding details
Eli Lilly and Company
Gilead Sciences
Ministero dell’Istruzione, dell’Università e della RicercaMIUR
NextGenerationEUNGEU
R01HG012284
PE0000006, 1553 11.10.2022
U01MH115483
Universidad Científica del SurUCSUR: UCS009-DGIDI-CIENTIFICA-2023
Universidad Científica del SurUCSUR: UCS
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Neural Correlates of Novelty-Evoked Distress in 4-Month-Old Infants: A Synthetic Cohort Study
(2024) Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, .
Filippi, C.A.a , Winkler, A.M.b , Kanel, D.c d , Elison, J.T.e , Hardiman, H.c d , Sylvester, C.f , Pine, D.S.c , Fox, N.A.d
a Department of Child and Adolescent Psychiatry, New York University Grossman School of Medicine, New York, New York, United States
b Division of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas, United States
c Emotion and Development Branch, National Institute of Mental Health, Bethesda, Maryland, United States
d Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, United States
e Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, United States
f Departments of Psychiatry, Radiology, and the Taylor Family Institute for Innovative Research, Washington University, St. Louis, Missouri, United States
Abstract
Background: Observational assessments of infant temperament have provided unparalleled insight into prediction of risk for social anxiety. However, it is challenging to administer and score these assessments alongside high-quality infant neuroimaging data. In the current study, we aimed to identify infant resting-state functional connectivity associated with both parent report and observed behavioral estimates of infant novelty-evoked distress. Methods: Using data from the OIT (Origins of Infant Temperament) study, which includes deep phenotyping of infant temperament, we identified parent-report measures that were associated with observed novelty-evoked distress. These parent-report measures were then summarized into a composite score used for imaging analysis. Our infant magnetic resonance imaging sample was a synthetic cohort, harmonizing data from 2 functional magnetic resonance imaging studies of 4-month-old infants (OIT and BCP [Baby Connectome Project]; n = 101), both of which included measures of parent-reported temperament. Brain-behavior associations were evaluated using enrichment, a statistical approach that quantifies the clustering of brain-behavior associations within network pairs. Results: Results demonstrated that parent-report composites of novelty-evoked distress were significantly associated with 3 network pairs: dorsal attention–salience/ventral attention, dorsal attention–default mode, and dorsal attention–control. These network pairs demonstrated negative associations with novelty-evoked distress, indicating that less connectivity between these network pairs was associated with greater novelty-evoked distress. Additional analyses demonstrated that dorsal attention–control network connectivity was associated with observed novelty-evoked distress in the OIT sample (n = 38). Conclusions: Overall, this work is broadly consistent with existing work and implicates dorsal attention network connectivity in novelty-evoked distress. This study provides novel data on the neural basis of infant novelty-evoked distress. © 2024 Society of Biological Psychiatry
Author Keywords
Anxiety; Attention; Connectivity; Infancy; Resting-state fMRI; Temperament
Funding details
National Institute of Mental HealthNIMHR00MH125878, U01MH110274, R01MH122389, R01MH104324, R01MH131584, R21MH122976
National Institute of Mental HealthNIMH
ZIA-MH002782
Document Type: Article
Publication Stage: Article in Press
Source: Scopus