Q-GLO RESEARCH

Province of Ontario Neurodevelopmental Disorders (POND) Network

Neurodevelopmental disorders arise from disturbances in the growth and development of the brain and the nervous systems. There are more than 300,000 children and youth in Ontario with neurodevelopmental disorders. There are few effective medications and they are only partially effective and have significant adverse effects, particularly in children. Thus, there is a clear and urgent need for new and better-targeted therapies that include behavioural and psychosocial interventions. To address these gaps, the POND Network has brought together a multidisciplinary team of scientists, clinicians, engineers, and community stakeholders who share the goal of improving the long-term outcomes for children with neurodevelopmental disorders.

Identification of genetic variants

The broad phenotypic spectrum of ASD is seen in the variability of presentation and severity among individuals and reflects the complexity of the underlying genetic etiology which ranges from monogenic syndromes to an accumulation of many low-risk alleles. While over 100 ASD susceptibility genes have already been described, studies estimate that there are over 1000 autism susceptibility genes indicating that capturing the complete genetic architecture underlying ASD will require sequencing many more individuals with ASD.

To identify novel ASD susceptibility genes, Q-GLO studies sporadic cases of ASD (no family history of ASD) to look for de novo mutations in the proband, and complex cases of ASD (have family history of ASD) for inherited and shared variants between family members. To identify these variants, Q-GLO employs several sequencing strategies including targeted gene panels, whole exome, and whole genome sequencing

Microbiome dysbiosis

The healthy human gut contains a network of millions of bacteria that help to digest food, fight infection and promote human health. Stress, changes in diet, antibiotic use, and other environmental conditions can disrupt the bacterial network, which in turns contributes to a wide range of illnesses. Our research aims to describe the microbiome (bacteria and bacterial genes) in individuals diagnosed with a neurodevelopment disorder (ASD and ADHD) or mood disorder (depression and anxiety) compared with their neurotypical, cohabiting siblings. Since bacterial composition can be relatively easily manipulated, personalized treatment of gut-bacteria-related psychiatric disorders shows tremendous potential for improving human health and reducing the economic burden of mental health disorders on the health care system.

“The ARBA” Study

We are currently investigating a study drug called arbaclofen to improve social functioning in children and teens with Autism. This study is comparing arbaclofen against placebo for improving social & global function and communication.

Q-GLO PUBLICATIONS

2019

Callaghan, D. B., Rogic, S., Tan, P. P. C., Calli, K., Qiao, Y., Baldwin, R., Jacobson, M., Belmadani, M., Holmes, N., Yu, C., Li, Y., Li, Y., Kurtzke, F. E., Kuzeljevic, B., Yu, A. Y., Hudson, M., Mcaughton, A. J. M., Xu, Y., Dionne-Laporte, A., Girard, S., Liang, P., Separovic, E. R., Liu, X., Rouleau, G., Pavlidis, P., & Lewis, M. E. S. (2019). Whole genome sequencing and variant discovery in the ASPIRE autism spectrum disorder cohort. Clin. Genet, 96(3), 199-206. doi:https://doi.org/10.1111/cge.13556

Cook, E., Izukawa, T., Young, S., Rosen, G., Jamali, M., Zhang, L., Johnson, D., Bain, E., Hilland, J., Ferrone, C., Buckstein, J., Francis, J., Momtaz, B., McNaughton, A., Liu, X., Snetsinger, B., Buckstein, R., & Rauh, M. (2019). Comorbid and inflammatory characteristics of genetic subtypes of clonal hematopoiesis. Blood Advances, 3, 2482-2486. doi:https://doi.org/10.1182/bloodadvances.2018024729

Feldman, M. A., Azzano, A., Ward, R. A., Hudson, M., Sjaarda, C. P., & Liu, X. (2019). Relationship of family history conditions and early signs of autism spectrum disorder in low and high-risk infants. Research in Autism Spectrum Disorders, 65, 25-33. doi:https://doi.org/10.1016/j.rasd.2019.05.002

McDonnell, C., DeLucia, E., Hayden, E., Anagnostou, E., Nicolson, R., Kelley, E., Georgiades, S., Liu, X., & Stevenson, R. (2019). An Exploratory Analysis of Predictors of Youth Suicide-Related Behaviors in Autism Spectrum Disorder: Implications for Prevention Science. Journal of Autism and Developmental Disorders. doi:https://doi.org/10.1007/s10803-019-04320-6

Sjaarda, C. P., Sabbagh, M., Wood, S., Ward-King, J., McNaughton, A. J. M., Hudson, M. L., Tao, M., Ayub, M., & Liu, X. (2019). Homozygosity for the 10-repeat dopamine transporter (DAT1) allele is associated with reduced EEG response in males with ASD. Research in Autism Spectrum Disorders, 60, 25-35. doi:https://doi.org/10.1016/j.rasd.2018.12.003

Sjaarda, C. P., Wood, S., McNaughton, A. J. M., Taylor, S., Hudson, M. L., Liu, X., Guerin, A., & Ayub, M. (2019). Exome sequencing identifies de novo splicing variant in XRCC6 in sporadic case of autism. J Hum Genet. doi:https://doi.org/10.1038/s10038-019-0707-0

Zarrei, M., Burton, C., Engchuan, W., Young, E., Higginbotham, E., Macdonald, J., Trost, B., Chan, A., Walker, S., Lamoureux, S., Heung, T., Mojarad, B., Kellam, B., Paton, T., Faheem, M., Miron, K., Lu, C., Wang, T., Samler, K., & Scherer, S. (2019). A large data resource of genomic copy number variation across neurodevelopmental disorders. npj Genomic Medicine, 4. doi:https://doi.org/10.1038/s41525-019-0098-3

Zhao, Y., Tyrishkin, K., Sjaarda, C., Khanal, P., Stafford, J., Rauh, M., Liu, X., Babak, T., & Yang, X. (2019). A one-step tRNA-CRISPR system for genome-wide genetic interaction mapping in mammalian cells. Scientific Reports. https://doi.org/10.1038/s41598-019-51090-3

2018

Normandeau, C. P., Ventura-Silva, A. P., Hawken, E. R., Angelis, S., Sjaarda, C., Liu, X., Pego, J. M., & Dumont, E. C. (2018). A Key Role for Neurotensin in Chronic-Stress-Induced Anxiety-Like Behavior in Rats. Neuropsychopharmacology, 43(2), 285-293. doi:https://doi.org/10.1038/npp.2017.134

2017

Cohen, I., Liu, X., Hudson, M., Gillis, J., Cavalari, R., Romanczyk, R., Karmel, B., & Gardner, J. (2017). Level 2 Screening With the PDD Behavior Inventory: Subgroup Profiles and Implications for Differential Diagnosis. Canadian Journal of School Psychology, 32, 299-315. doi: https://doi.org/10.1177/0829573517721127

Li, W., Zhang, L., Luo, X., Liu, B., Liu, Z., Lin, F., Liu, Z., Xie, Y., Hudson, M., Rathod, S., Husain, N., Liu, X., Ayub, M., & Naeem, F. (2017). A qualitative study to explore views of patients’ , carers’ and mental health professionals’ to inform cultural adaptation of CBT for psychosis (CBTp) in China. BMC Psychiatry, 17. doi: https://doi.org/10.1186/s12888-017-1290-6

Sjaarda, C. P., Hecht, P., McNaughton, A. J. M., Zhou, A., Hudson, M. L., Will, M. J., Smith, G., Ayub, M., Liang, P., Chen, N., Beversdorf, D., & Liu, X. (2017). Interplay between maternal Slc6a4 mutation and prenatal stress: a possible mechanism for autistic behavior development. Sci. Rep, 7(1), 8735. doi: https://doi.org/10.1038/s41598-017-07405-3

Tan, Y. Q., Tu, C., Meng, L., Yuan, S., Sjaarda, C., Luo, A., Du, J., Li, W., Gong, F., Zhong, C., Deng, H. X., Lu, G., Liang, P., & Lin, G. (2017). Loss-of-function mutations in TDRD7 lead to a rare novel syndrome combining congenital cataract and nonobstructive azoospermia in humans. Genet. Med. doi:https://doi.org/10.1038/gim.2017.130

Xi, Y., Arbabi, A., McNaughton, A., Hamilton, A., Hull, D., Perras, H., Chiu, T., Morrison, S., Goldsmith, C., Creede, E., Anger, G., Honeywell, C., Cloutier, M., Macchio, N., Kiss, C., Liu, X., Crocker, S., Davies, G., Brudno, M., & Armour, C. (2017). Noninvasive Prenatal Detection of Trisomy 21 by Targeted Semiconductor Sequencing: A Technical Feasibility Study. Fetal diagnosis and therapy, 42. doi: https://doi.org/10.1159/000460248

Yuen, R. K. C., Merico, D., Bookman, M., Howe, L., Thiruvahindrapuram, B., Patel, R. V., Whitney, J., Deflaux, N., Bingham, J., Wang, Z., Pellecchia, G., Buchanan, J. A., Walker, S., Marshall, C. R., Uddin, M., Zarrei, M., Deneault, E., D’Abate, L., Chan, A. J., Koyanagi, S., Paton, T., Pereira, S. L., Hoang, N., Engchuan, W., Higginbotham, E. J., Ho, K., Lamoureux, S., Li, W., MacDonald, J. R., Nalpathamkalam, T., Sung, W. W., Tsoi, F. J., Wei, J., Xu, L., Tasse, A. M., Kirby, E., Van, E. W., Twigger, S., Roberts, W., Drmic, I., Jilderda, S., Modi, B. M., Kellam, B., Szego, M., Cytrynbaum, C., Weksberg, R., Zwaigenbaum, L., Woodbury-Smith, M., Brian, J., Senman, L., Iaboni, A., Doyle-Thomas, K., Thompson, A., Chrysler, C., Leef, J., Savion-Lemieux, T., Smith, I. M., Liu, X., Nicolson, R., Seifer, V., Fedele, A., Cook, E. H., Dager, S., Estes, A., Gallagher, L., Malow, B. A., Parr, J. R., Spence, S. J., Vorstman, J., Frey, B. J., Robinson, J. T., Strug, L. J., Fernandez, B. A., Elsabbagh, M., Carter, M. T., Hallmayer, J., Knoppers, B. M., Anagnostou, E., Szatmari, P., Ring, R. H., Glazer, D., Pletcher, M. T., & Scherer, S. W. (2017). Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder. Nat. Neurosci, 20(4), 602-611. doi: https://doi.org/10.1038/nn.4524

2016

Cohen, I., Liu, X., Hudson, M., Gillis, J., Cavalari, R., Romanczyk, R., Karmel, B., & Gardner, J. (2016). Using the PDD Behavior Inventory as a Level 2 Screener: A Classification and Regression Trees Analysis. Journal of Autism and Developmental Disorders, 46, 3006-3022. doi: https://doi.org/10.1007/s10803-016-2843-0

Hecht, P., Hudson, M., Connors, S., Tilley, M., Liu, X., & Beversdorf, D. (2016). Maternal serotonin transporter genotype affects risk for ASD with exposure to prenatal stress. Autism research : official journal of the International Society for Autism Research, 9. doi: https://doi.org/10.1002/aur.1629

Tan, P., Rogic, S., Zoubarev, A., McDonald, C., Lui, F., Charathsandran, G., Jacobson, M., Belmadani, M., Leong, J., Van Rossum, T., Portales-Casamar, E., Qiao, Y., Calli, K., Liu, X., Hudson, M., Rajcan-Separovic, E., Lewis, M. E. S., & Pavlidis, P. (2016). Interactive Exploration, Analysis and Visualization of Complex Phenome-Genome Datasets with ASPIREdb. Human mutation, 37. doi: https://doi.org/10.1002/humu.23011

Wang, C., Hudson, M., Liu, X., Ward, R., & Feldman, M. (2016). Parent Prediction of Autism Spectrum Disorder in Infants at Risk: A Follow-up Study. Journal of Child and Family Studies. doi: https://doi.org/10.1007/s10826-016-0508-4

2015

Feldman, M., Hendry, A., Ward, R., Hudson, M., & Liu, X. (2015). Behavioral Development and Sociodemographics of Infants and Young Children at Higher and Lower Risk for Autism Spectrum Disorders. Journal of Autism and Developmental Disorders, 45, 1167-1175. doi: https://doi.org/10.1007/s10803-014-2277-5

Heidari, A., Tongsook, C., Najafipour, R., Musante, L., Vasli, N., Garshasbi, M., Hu, H., Mittal, K., McNaughton, A., Sritharan, K., Hudson, M., Stehr, H., Talebi, S., Moradi, M., Darvish, H., Rafiq, A., Mozhdehipanah, H., Rashidinejad, A., Samiei, S., & Vincent, J. (2015). Mutations in the Histamine N-Methyltransferase gene, HNMT, are Associated with Non-Syndromic Autosomal Recessive Intellectual Disability. Human Molecular Genetics, 24. doi: https://doi.org/10.1093/hmg/ddv286

Liu, Y., Li, J., Liu, X., Liu, X., Khawar, W., Zhang, X., Wang, F., Chen, X., & Sun, Z. (2015). Quantitative Risk Stratification of Oral Leukoplakia with Exfoliative Cytology. PLOS ONE, 10, e0126760. doi: https://doi.org/10.1371/journal.pone.0126760

Shi, L.-J., Jianjun, o., Gong, J.-B., Wang, S.-H., Zhou, Y., Zhu, F.-R., Liu, X., Zhao, J., & Luo, X.-R. (2015). Broad autism phenotype features of Chinese parents with autistic children and their associations with severity of social impairment in probands. BMC Psychiatry, 15, 168. doi: https://doi.org/10.1186/s12888-015-0568-9

Wallace, J., Hall, G., Yin, Z., & Liu, X. (2015). Determination of Algae and Macrophyte Species Distribution in Three Wastewater Stabilization Ponds Using Metagenomics Analysis. Water, 7, 3225-3242. doi: https://doi.org/10.3390/w7073225

 

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