The role of copy number variants in suicide attempt and suicidal ideation

• Grant number: 24/11033-1
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate (Direct)
• Start date: January 15, 2025
• End date: January 14, 2026
• Field of knowledge: Biological Sciences - Genetics - Human and Medical Genetics
• Principal Investigator: Marcos Leite Santoro
• Grantee: Lucas Toshio Ito
• Supervisor: Niamh Mullins
• Host Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil
• Institution abroad: Icahn School of Medicine at Mount Sinai, United States
• Associated to the scholarship: 22/15880-5 - Impact of genetic variants on structural neuroimaging: a longitudinal approach in psychiatric disorders, BP.DD

Abstract

Suicide is a global public health concern that claims nearly 700,000 lives each year, and mental disorders stand out as a significant risk factor in this context. Suicide attempts (SA) and suicidal ideation (SI) also confer an increasing risk of death by suicide, thus, understanding their etiology can play a pivotal role in advancing suicide prevention efforts. The heritability of suicidal thoughts and behaviors is firmly established (~30-50%), and the most recent genome-wide association study for SA found 12 genome-wide significant loci. However, there is an urgent need to explore rare and large effect variants, such as the copy number variants (CNVs), which are large duplications or deletions of more than 1 kilobase. Considering that they can affect multiple genes and have been associated with many mental disorders, investigating CNVs can provide a crucial path for understanding the etiology SA and SI, however, most CNV studies are still limited by their small sample size. This work aims to identify CNVs associated with SA and SI, using the largest sample size available until now. Data will be analyzed from Psychiatric Genetics Consortium (PGC) datasets that contain CNV data and SA and/or SI phenotypes which comprise more than 30,000 individuals. CNVs were called by the CNV Working Group from PGC according to their platform array chip and filtered by quality control. Association analysis will be carried out in R, testing the association of deletion or duplication counts with SA and SI using logistic regression analysis, adjusted for population structure and CNV quality metrics. The CNV burden will be measured according to the size in base pairs, the number of CNVs overlapping genes, and the number of CNVs overlapping breakpoints, and then compared between cases and controls. New CNVs identified in this work will be compared with CNVs associated with other major psychiatric disorders. Given the scarcity of large-scale studies in this domain and the significant potential impact of CNVs on suicide, it is crucial to prioritize research efforts in investigating this issue. This will allow a more comprehensive understanding of the genetic foundations of suicide, which is essential for effective suicide prevention strategies.