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Genome-wide tandem repeat expansions modify schizophrenia risk in the presence of a 22q11.2 deletion
(Springer Science and Business Media LLC, 2026-04-15)
Muyang Cheng
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Yue Yin
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Worrawat Engchuan
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Tracy Heung
;
Kathleen Angkustsiri
1
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The electroencephalography protocol for the Accelerating Medicines Partnership® Schizophrenia Program: Reliability and stability of measures
(Springer Science and Business Media LLC, 2025-06-06)
Daniel H. Mathalon
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Spero Nicholas
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Brian J. Roach
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Tashrif Billah
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Suzie Lavoie
Individuals at clinical high risk for psychosis (CHR) have variable clinical outcomes and low conversion rates, limiting development of novel and personalized treatments. Moreover, given risks of antipsychotic drugs, safer effective medications for CHR individuals are needed. The Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ) Program was launched to address this need. Based on past CHR and schizophrenia studies, AMP SCZ assessed electroencephalography (EEG)-based event-related potential (ERP), event-related oscillation (ERO), and resting EEG power spectral density (PSD) measures, including mismatch negativity (MMN), auditory and visual P300 to target (P3b) and novel (P3a) stimuli, 40-Hz auditory steady state response, and resting EEG PSD for traditional frequency bands (eyes open/closed). Here, in an interim analysis of AMP SCZ EEG measures, we assess test-retest reliability and stability over sessions (baseline, month-2 follow-up) in CHR (n = 654) and community control (CON; n = 87) participants. Reliability was calculated as Generalizability (G)-coefficients, and changes over session were assessed with paired t-tests. G-coefficients were generally good to excellent in both groups (CHR: mean = 0.72, range = 0.49–0.85; CON: mean = 0.71, range = 0.44–0.89). Measure magnitudes significantly (p < 0.001) decreased over session (MMN, auditory and visual target P3b, visual novel P3a, 40-Hz ASSR) and/or over runs within sessions (MMN, auditory/visual novel P3a and target P3b), consistent with habituation effects. Despite these small systematic habituation effects, test-retest reliabilities of the AMP SCZ EEG-based measures are sufficiently strong to support their use in CHR studies as potential predictors of clinical outcomes, markers of illness progression, and/or target engagement or secondary outcome measures in controlled clinical trials. Watch Dr Daniel H. Mathalon discuss their work and this article: <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink"
Scopus© Citations 1 3
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Cognitive assessment in the Accelerating Medicines Partnership® Schizophrenia Program: harmonization priorities and strategies in a diverse international sample
(Springer Science and Business Media LLC, 2025-03-24)
Kelly Allott
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Walid Yassin
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Luis Alameda
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Tashrif Billah
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Owen Borders
Scopus© Citations 5 7
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Source‐based morphometry reveals structural brain pattern abnormalities in 22q11.2 deletion syndrome
(2024)
Ruiyang Ge
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Christopher R. K. Ching
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Anne S. Bassett
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Leila Kushan
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Kevin M. Antshel
<jats:title>Abstract</jats:title><jats:p>22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2]; and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1‐weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source‐based morphometry (SBM) pipeline (SS‐Detect) to generate structural brain patterns (SBPs) that capture co‐varying GMV. We investigated the impact of the 22q11.2 deletion, deletion size, intelligence quotient, and psychosis on the SBPs. Seventeen GMV‐SBPs were derived, which provided spatial patterns of GMV covariance associated with a quantitative metric (i.e., loading score) for analysis. Patterns of topographically widespread differences in GMV covariance, including the cerebellum, discriminated individuals with 22q11DS from healthy controls. The spatial extents of the SBPs that revealed disparities between individuals with 22q11DS and controls were consistent with the findings of the univariate voxel‐based morphometry analysis. Larger deletion size was associated with significantly lower GMV in frontal and occipital SBPs; however, history of psychosis did not show a strong relationship with these covariance patterns. 22q11DS is associated with distinct structural abnormalities captured by topographical GMV covariance patterns that include the cerebellum. Findings indicate that structural anomalies in 22q11DS manifest in a nonrandom manner and in distinct covarying anatomical patterns, rather than a diffuse global process. These SBP abnormalities converge with previously reported cortical surface area abnormalities, suggesting disturbances of early neurodevelopment as the most likely underlying mechanism.</jats:p>
3Scopus© Citations 6
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Robust and replicable functional brain signatures of 22q11.2 deletion syndrome and associated psychosis: a deep neural network-based multi-cohort study
(2024)
Kaustubh Supekar
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Carlo de los Angeles
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Srikanth Ryali
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Leila Kushan
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Charlie Schleifer
Scopus© Citations 2 5
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Chromatin regulators in the TBX1 network confer risk for conotruncal heart defects in 22q11.2DS
(2023)
Yingjie Zhao
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Yujue Wang
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Lijie Shi
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Donna M. McDonald-McGinn
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T. Blaine Crowley
<jats:title>Abstract</jats:title><jats:p>Congenital heart disease (CHD) affecting the conotruncal region of the heart, occurs in 40–50% of patients with 22q11.2 deletion syndrome (22q11.2DS). This syndrome is a rare disorder with relative genetic homogeneity that can facilitate identification of genetic modifiers. Haploinsufficiency of <jats:italic>TBX1</jats:italic>, encoding a T-box transcription factor, is one of the main genes responsible for the etiology of the syndrome. We suggest that genetic modifiers of conotruncal defects in patients with 22q11.2DS may be in the <jats:italic>TBX1</jats:italic> gene network. To identify genetic modifiers, we analyzed rare, predicted damaging variants in whole genome sequence of 456 cases with conotruncal defects and 537 controls, with 22q11.2DS. We then performed gene set approaches and identified chromatin regulatory genes as modifiers. Chromatin genes with recurrent damaging variants include <jats:italic>EP400</jats:italic>, <jats:italic>KAT6A</jats:italic>, <jats:italic>KMT2C</jats:italic>, <jats:italic>KMT2D</jats:italic>, <jats:italic>NSD1, CHD7</jats:italic> and <jats:italic>PHF21A</jats:italic>. In total, we identified 37 chromatin regulatory genes, that may increase risk for conotruncal heart defects in 8.5% of 22q11.2DS cases. Many of these genes were identified as risk factors for sporadic CHD in the general population. These genes are co-expressed in cardiac progenitor cells with <jats:italic>TBX1</jats:italic>, suggesting that they may be in the same genetic network. The genes <jats:italic>KAT6A</jats:italic>, <jats:italic>KMT2C</jats:italic>, <jats:italic>CHD7</jats:italic> and <jats:italic>EZH2</jats:italic>, have been previously shown to genetically interact with <jats:italic>TBX1</jats:italic> in mouse models. Our findings indicate that disturbance of chromatin regulatory genes impact the <jats:italic>TBX1</jats:italic> gene network serving as genetic modifiers of 22q11.2DS and sporadic CHD, suggesting that there are some shared mechanisms involving the <jats:italic>TBX1</jats:italic> gene network in the etiology of CHD.</jats:p>
Scopus© Citations 4 3
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Genetic contributors to risk of schizophrenia in the presence of a 22q11.2 deletion
(2020)
Isabelle Cleynen
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Worrawat Engchuan
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Matthew S. Hestand
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Tracy Heung
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Aaron M. Holleman
Scopus© Citations 98 2
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Using common genetic variation to examine phenotypic expression and risk prediction in 22q11.2 deletion syndrome
(2020)
Robert W. Davies
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Ania M. Fiksinski
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Elemi J. Breetvelt
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Nigel M. Williams
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Stephen R. Hooper
8Scopus© Citations 101
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A normative chart for cognitive development in a genetically selected population
(2021)
Ania M. Fiksinski
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Carrie E. Bearden
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Anne S. Bassett
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René S. Kahn
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Janneke R. Zinkstok
15Scopus© Citations 19
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Effects of copy number variations on brain structure and risk for psychiatric illness: Large‐scale studies from the<scp>ENIGMA</scp>working groups on<scp>CNVs</scp>
(2021)
Ida E. Sønderby
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Christopher R. K. Ching
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Sophia I. Thomopoulos
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Dennis Meer
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Daqiang Sun
3Scopus© Citations 46

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