Browsing by Author "Emanuel, Beverly"
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Item A normative chart for cognitive development in a genetically selected population(2021) Fiksinski, Ania; Bearden, Carrie; Bassett, Anne; Kahn, René; Zinkstok, Janneke; Hooper, Stephen R; Tempelaar, Wanda; McDonald, Donna; Swillen, Ann; Emanuel, Beverly; Morrow, Bernice; Gur, Raquel; Chow, Eva; Van den Bree, Marianne; Vermeesch, Joris; Warren, Stephen; Owen, Michael; Van Amelsvoort, Therese; Eliez, Stephan; Gothelf, Doron; Arango, Celso; Kates, Wendy; Simon, Tony; Murphy, Kieran; Repetto, Gabriela; Heine, Damian; Vicari, Stefano; Cubells, Joseph; Armando, Marco; Philip, Nicole; Campbell, Linda; García, Sixto; Schneider, Maude; Shashi, Vandana; 22q11DS International Consortium on Brain and Behavior; Vorstman, Jacob; Breetvelt, ElemiCertain pathogenic genetic variants impact neurodevelopment and cause deviations from typical cognitive trajectories. Understanding variant-specific cognitive trajectories is clinically important for informed monitoring and identifying patients at risk for comorbid conditions. Here, we demonstrate a variant-specific normative chart for cognitive development for individuals with 22q11.2 deletion syndrome (22q11DS). We used IQ data from 1365 individuals with 22q11DS to construct variant-specific normative charts for cognitive development (Full Scale, Verbal, and Performance IQ). This allowed us to calculate Z-scores for each IQ datapoint. Then, we calculated the change between first and last available IQ assessments (delta Z-IQ-scores) for each individual with longitudinal IQ data (n = 708). We subsequently investigated whether using the variant-specific IQ-Z-scores would decrease required sample size to detect an effect with schizophrenia risk, as compared to standard IQ-scores. The mean Z-IQ-scores for FSIQ, VIQ, and PIQ were close to 0, indicating that participants had IQ-scores as predicted by the normative chart. The mean delta-Z-IQ-scores were equally close to 0, demonstrating a good fit of the normative chart and indicating that, as a group, individuals with 22q11DS show a decline in IQ-scores as they grow into adulthood. Using variant-specific IQ-Z-scores resulted in 30% decrease of required sample size, as compared to the standard IQ-based approach, to detect the association between IQ-decline and schizophrenia (p < 0.01). Our findings suggest that using variant-specific normative IQ data significantly reduces required sample size in a research context, and may facilitate a more clinically informative interpretation of IQ data. This approach allows identification of individuals that deviate from their expected, variant-specific, trajectory. This group may be at increased risk for comorbid conditions, such as schizophrenia in the case of 22q11DS.Item Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs(2022) Sønderby, Ida; Ching, Christopher; Thomopoulos, Sophia; Van der Meer, Dennis; Sun, Daqiang; Villalon, Julio; Agartz, Ingrid; Amunts, Katrin; Arango, Celso; Armstrong, Nicola; Ayesa, Rosa; Bakker, Geor; Bassett, Anne; Boomsma, Dorret; Bülow, Robin; Butcher, Nancy; Calhoun, Vince; Caspers, Svenja; Chow, Eva; Cichon, Sven; Ciufolini, Simone; Craig, Michael; Crespo, Benedicto; Cunningham, Adam; Dale, Ander; Dazzan, Paola; De Zubicaray, Greig; Djurovic, Srdjan; Doherty, Joanne; Donohoe, Gary; Draganski, Bogdan; Durdle, Courtney; Ehrlich, Stefan; Emanuel, Beverly; Espeseth, Thomas; Fisher, Simon; Ge, Tian; Glahn, David; Grabe, Hans; Gur, RaquelThe Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.Item Genome-Wide Association Study to Find Modifiers for Tetralogy of Fallot in the 22q11.2 Deletion Syndrome Identifies Variants in the GPR98 Locus on 5q14.3(Lippincott Williams & Wilkins, 2017) Guo, Tingwei; Repetto, Gabriela; McDonald, Donna; Chung, Jonathan; Nomaru, Hiroko; Campbell, Christopher; Blonska, Anna; Bassett, Anne; Chow, Eva; Mlynarski, Elisabeth; Swillen, Ann; Vermeesch, Joris; Devriendt, Koen; Gothelf, Doron; Carmel, Miri; Michaelovsky, Elena; Schneider, Maude; Eliez, Stephan; Antonarakis, Stylianos; Coleman, Karlene; Tomita, Aoy; Mitchell, Michael; Digilio, Cristina; Dallapiccola, Bruno; Marino, Bruno; Philip, Nicole; Busa, Tiffany; Kushan, Leila; Bearden, Carrie; Piotrowicz, Małgorzata; Hawuła, Wanda; Roberts, Amy; Tassone, Flora; Simon, Tony; van Duin, Esther; van Amelsvoort, Thérèse; Kates, Wendy; Zackai, Elaine; Johnston, Richard; Cutler, David; Agopian, A; Goldmuntz, Elizabeth; Mitchell, Laura; Wang, Tao; Emanuel, Beverly; Morrow, Bernice; the International 22q11.2 Consortium/Brain and Behavior ConsortiumBACKGROUND: The 22q11.2 deletion syndrome (22q11.2DS; DiGeorge syndrome/velocardiofacial syndrome) occurs in 1 of 4000 live births, and 60% to 70% of affected individuals have congenital heart disease, ranging from mild to severe. In our cohort of 1472 subjects with 22q11.2DS, a total of 62% (n=906) have congenital heart disease and 36% (n=326) of these have tetralogy of Fallot (TOF), comprising the largest subset of severe congenital heart disease in the cohort. METHODS AND RESULTS: To identify common genetic variants associated with TOF in individuals with 22q11.2DS, we performed a genome-wide association study using Affymetrix 6.0 array and imputed genotype data. In our cohort, TOF was significantly associated with a genotyped single-nucleotide polymorphism (rs12519770, P=2.98×10-8) in an intron of the adhesion GPR98 (G-protein-coupled receptor V1) gene on chromosome 5q14.3. There was also suggestive evidence of association between TOF and several additional single-nucleotide polymorphisms in this region. Some genome-wide significant loci in introns or noncoding regions could affect regulation of genes nearby or at a distance. On the basis of this possibility, we examined existing Hi-C chromatin conformation data to identify genes that might be under shared transcriptional regulation within the region on 5q14.3. There are 6 genes in a topologically associated domain of chromatin with GPR98, including MEF2C (Myocyte-specific enhancer factor 2C). MEF2C is the only gene that is known to affect heart development in mammals and might be of interest with respect to 22q11.2DS. CONCLUSIONS: In conclusion, common variants may contribute to TOF in 22q11.2DS and may function in cardiac outflow tract development.Item Rare Genome-Wide Copy Number Variation and Expression of Schizophrenia in 22q11.2 Deletion Syndrome(American Psychiatric Association, 2017) Bassett, Anne; Lowther, Chelsea; Merico, Daniele; Costain, Gregory; Chow, Eva; van Amelsvoort, Therese; McDonald-McGinn, Donna; Gur, Raquel; Swillen, Ann; Van den Bree, Marianne; Murphy, Kieran; Gothelf, Doron; Bearden, Carrie; Eliez, Stephan; Kates, Wendy; Philip, Nicole; Sashi, Vandana; Campbell, Linda; Vorstman, Jacob; Cubells, Joseph; Repetto, Gabriela; Simon, Tony; Boot, Erik; Heung, Tracy; Evers, Rens; Vingerhoets, Claudia; van Duin, Esther; Zackai, Elaine; Vergaelen, Elfi; Devriendt, Koen; Vermeesch, Joris; Owen, Michael; Murphy, Clodagh; Michaelovosky, Elena; Kushan, Leila; Schneider, Maude; Fremont, Wanda; Busa, Tiffany; Hooper, Stephen; McCabe, Kathryn; Duijff, Sasja; Isaev, Karin; Pellecchia, Giovanna; Wei, John; Gazzellone, Matthew; Scherer, Stephen; Emanuel, Beverly; Guo, Tingwei; Morrow, Bernice; Marshall, Christian; International 22q11.2DS Brain and Behavior ConsortiumOBJECTIVE: Chromosome 22q11.2 deletion syndrome (22q11.2DS) is associated with a more than 20-fold increased risk for developing schizophrenia. The aim of this study was to identify additional genetic factors (i.e., "second hits") that may contribute to schizophrenia expression. METHOD: Through an international consortium, the authors obtained DNA samples from 329 psychiatrically phenotyped subjects with 22q11.2DS. Using a high-resolution microarray platform and established methods to assess copy number variation (CNV), the authors compared the genome-wide burden of rare autosomal CNV, outside of the 22q11.2 deletion region, between two groups: a schizophrenia group and those with no psychotic disorder at age ≥25 years. The authors assessed whether genes overlapped by rare CNVs were overrepresented in functional pathways relevant to schizophrenia. RESULTS: Rare CNVs overlapping one or more protein-coding genes revealed significant between-group differences. For rare exonic duplications, six of 19 gene sets tested were enriched in the schizophrenia group; genes associated with abnormal nervous system phenotypes remained significant in a stepwise logistic regression model and showed significant interactions with 22q11.2 deletion region genes in a connectivity analysis. For rare exonic deletions, the schizophrenia group had, on average, more genes overlapped. The additional rare CNVs implicated known (e.g., GRM7, 15q13.3, 16p12.2) and novel schizophrenia risk genes and loci. CONCLUSIONS: The results suggest that additional rare CNVs overlapping genes outside of the 22q11.2 deletion region contribute to schizophrenia risk in 22q11.2DS, supporting a multigenic hypothesis for schizophrenia. The findings have implications for understanding expression of psychotic illness and herald the importance of whole-genome sequencing to appreciate the overall genomic architecture of schizophrenia.Publication Source-based morphometry reveals structural brain pattern abnormalities in 22q11.2 deletion syndrome(2024) Repetto, Gabriela; Ge, Ruiyang; Ching, Christopher; Bassett, Anne; Kushan, Leila; Antshe, Kevin; Van Amelsvoort, Therese; Bakker, Geor; Butcher, Nancy; Campbell, Linda; Chow, Eva; Craig, Michael; Crossley, Nicolas; Cunningham, Adam; Daly, Eileen; Doherty, Joanne; Durdle, Courtney; Emanuel, Beverly; Fiksinski, Ania; Forsyth, Jennifer; Fremont, Wanda; Goodrich-Hunsaker, Naomi; Gudbrandsen, Maria; Gur, Raquel; Jalbrzikowski, Maria; Kates, Wendy; Lin, Amy; Linden, David; McCabe, Kathryn; McDonald, Donna; Moss, Hayley; Murphy, Declan; Murphy, Kieran; Owen, Michael; Villalon, Julio; Roalf, David; Ruparel, Kosha; Schmitt, J. Eric; Schuite, Sanne; Angkustsiri, Kathleen22q11.2 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.