Understanding Rare Genetic Variation and Disease Risk: A Global Neurogenetics Initiative
- PI
- Jacquemont, Sebastien
- DAR ID
- 11106
- Initial Approval Date
- January 30, 2025
- Current DAR Status
- Active
- PI Institution
- SAINTE-JUSTINE UNIVERSITY HOSPITAL CTR
- PI Institution Country
- Canada
- PI Institution Type
- Non-Profit
Requested Datasets (16)
NG00067Alzheimer's Disease Sequencing Project Umbrella StudyNG00022ADC1 - Alzheimer's Disease Center Dataset 1NG00023ADC2 - Alzheimer's Disease Center Dataset 2NG00024ADC3 - Alzheimer's Disease Center Dataset 3NG00068ADC4 - Alzheimer's Disease Center Dataset 4NG00069ADC5 - Alzheimer's Disease Center Dataset 5NG00070ADC6 - Alzheimer's Disease Center Dataset 6NG00071ADC7 - Alzheimer's Disease Center Dataset 7NG00136ADC8 - Alzheimer's Disease Center Dataset 8NG00137ADC9 - Alzheimer's Disease Center Dataset 9NG00138ADC10 - Alzheimer's Disease Center Dataset 10NG00139ADC11 - Alzheimer's Disease Center Dataset 11
Research Use Statement
Copy number variants (CNVs) -deletions or duplications of DNA segments- are associated with greatly elevated rates of neurodevelopmental psychiatric disorders (NPDs), including Autism Spectrum Disorders (ASD). Psychosis Spectrum (PS) conditions, and ADHD. ‘Genetics first’ or ‘bottom-up’ studies, in which participants are ascertained based on genetic etiology, can potentially overcome challenges posed by the genetic, mechanistic, and phenotypic heterogeneity of behaviorally defined (idiopathic) NPDs. While efforts to date have been successful in elucidating underlying neural substrates in a handful of such CNVs, critical gaps in our knowledge remain: 1) It is unknown if the growing number of CNVs identified as associated with the same psychiatric disorders (e.g., ASD and PS) show commonalities at the macroscale brain level; 2) the guiding principles underlying relationships between CNV-related variations in brain architecture and the function of genes encompassed in these CNVs are unknown; 3)
We propose to assemble the largest neuroimaging genomic dataset to date in order to identify the neural and shared molecular underpinnings of CNVs. Our multidisciplinary team, with expertise in medical and statistical genetics, mathematical modelling, and brain imaging, will address the following aims:
Aim 1: Characterize the effect of the most well-established recurrent NPD-associated CNVs on brain structure and function.
Aim 2: Beyond recurrent CNVs: Investigate effects on brain structure and function of global CNV burden genome-wide. CNVs will be identified using the same pipeline across all datasets (combining multiple CNV callers). Multimodal neuroimaging data, including T1-weighted structural images, T1w/T2w ratio images, resting-state functional MRI, and diffusion MRI, will be processed using the same harmonized pipelines developed by ENIGMA.
We propose to assemble the largest neuroimaging genomic dataset to date in order to identify the neural and shared molecular underpinnings of CNVs. Our multidisciplinary team, with expertise in medical and statistical genetics, mathematical modelling, and brain imaging, will address the following aims:
Aim 1: Characterize the effect of the most well-established recurrent NPD-associated CNVs on brain structure and function.
Aim 2: Beyond recurrent CNVs: Investigate effects on brain structure and function of global CNV burden genome-wide. CNVs will be identified using the same pipeline across all datasets (combining multiple CNV callers). Multimodal neuroimaging data, including T1-weighted structural images, T1w/T2w ratio images, resting-state functional MRI, and diffusion MRI, will be processed using the same harmonized pipelines developed by ENIGMA.
Non-Technical Summary
Neurodevelopmental disorders (NDs) such as autism spectrum disorder (ASD) and schizophrenia (SZ) represent a major health burden, each of which occurs in 1% of
our societies. The genetic contribution to NDs is as high as 60-80%. With the routine implementation of genetic testing in neurodevelopmental clinics worldwide, rare mutations that contribute significantly to neurodevelopmental symptoms are identified in 10 to 40 % of children with NDs. However, the effects of these mutations on brain structure and function are mostly unknown. We will comprehensively chart and characterize the effects of these mutations on brain structure and function. Such progress will provide insight into the mechanisms by which mutations may lead to neurodevelopmental and psychiatric disorders.
our societies. The genetic contribution to NDs is as high as 60-80%. With the routine implementation of genetic testing in neurodevelopmental clinics worldwide, rare mutations that contribute significantly to neurodevelopmental symptoms are identified in 10 to 40 % of children with NDs. However, the effects of these mutations on brain structure and function are mostly unknown. We will comprehensively chart and characterize the effects of these mutations on brain structure and function. Such progress will provide insight into the mechanisms by which mutations may lead to neurodevelopmental and psychiatric disorders.
Reported Publications
Publications shown are those reported by investigators through NIAGADS DAR reporting and renewal processes and may not represent a complete list of publications associated with the project.
No publications have been reported for this DAR.