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Updated: Nov 21, 2025

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants
Published on: February 21, 2015
Somatic copy number variants in neuropsychiatric disorders
Eduardo A Maury1, Christopher A Walsh2
1Division of Genetics and Genomics, Manton Center for Orphan Disease, and Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA, USA; Bioinformatics & Integrative Genomics Program and Harvard/MIT MD-PHD Program, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Mosaic copy number variants (CNVs) are found in some body cells and may help explain neuropsychiatric disorders. Further research with sensitive methods could clarify disease mechanisms.
Area of Science:
- Genetics
- Neuroscience
- Developmental Biology
Background:
- Copy number variants (CNVs) are linked to neuropsychiatric disorders.
- Rare inherited and de novo CNVs (dnCNVs) significantly impact disease risk.
- Post-zygotic dnCNVs, present in a subset of cells, are an emerging area of study.
Purpose of the Study:
- To explore the role of post-zygotic, or mosaic, CNVs in neuropsychiatric disorders.
- To understand how mutations present in a fraction of cells contribute to disease pathology.
- To highlight the potential of sensitive methods in uncovering mechanisms of neuropsychiatric disease.
Main Methods:
- Review of recent studies on mosaic CNVs.
- Conceptual analogy to conditional mutations in animal models.
- Emphasis on the need for advanced experimental and statistical approaches.
Main Results:
- Mosaic CNVs, though contributing a modest fraction of risk (0.3-0.5%), offer insights into cell-type specific pathologies.
- The study highlights the potential of mosaic mutations to elucidate disease mechanisms.
- Current understanding of mosaic CNVs in neuropsychiatric disorders is limited but growing.
Conclusions:
- Mosaic CNVs represent a potential avenue for understanding neuropsychiatric disease mechanisms.
- Further investigation using sensitive methodologies is crucial for advancing this field.
- Understanding mosaic mutations can illuminate how genetic variations affect cellular and circuit-level functions in the brain.
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