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Rare CNVs in Suicide Attempt include Schizophrenia-Associated Loci and Neurodevelopmental Genes: A Pilot Genome-Wide and Family-Based Study.

PloS one | 2016

Suicidal behavior (SB) has a complex etiology involving genes and environment. One of the genetic components in SB could be copy number variations (CNVs), as CNVs are implicated in neurodevelopmental disorders. However, a recently published genome-wide and case-control study did not observe any significant role of CNVs in SB. Here we complemented these initial observations by instead using a family-based trio-sample that is robust to control biases, having severe suicide attempt (SA) in offspring as main outcome (n = 660 trios). We first tested for CNV associations on the genome-wide Illumina 1M SNP-array by using FBAT-CNV methodology, which allows for evaluating CNVs without reliance on CNV calling algorithms, analogous to a common SNP-based GWAS. We observed association of certain T-cell receptor markers, but this likely reflected inter-individual variation in somatic rearrangements rather than association with SA outcome. Next, we used the PennCNV software to call 385 putative rare (<1%) and large (>100 kb) CNVs, observed in n = 225 SA offspring. Nine SA offspring had rare CNV calls in a set of previously schizophrenia-associated loci, indicating the importance of such CNVs in certain SA subjects. Several additional, very large (>1MB) sized CNV calls in 15 other SA offspring also spanned pathogenic regions or other neural genes of interest. Overall, 45 SA had CNVs enriched for 65 medically relevant genes previously shown to be affected by CNVs, which were characterized by a neurodevelopmental biology. A neurodevelopmental implication was partly congruent with our previous SNP-based GWAS, but follow-up analysis here indicated that carriers of rare CNVs had a decreased burden of common SNP risk-alleles compared to non-carriers. In conclusion, while CNVs did not show genome-wide association by the FBAT-CNV methodology, our preliminary observations indicate rare pathogenic CNVs affecting neurodevelopmental functions in a subset of SA, who were distinct from SA having increased SNP risk-allele burden. These observations may open up new avenues in the genetic etiology of SB.

Pubmed ID: 28030616 RIS Download

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QUANTO (tool)

RRID:SCR_009084

Software program that computes sample size or power for association studies of genes, environmental factors, gene-environment interaction, or gene-gene interaction. Available study designs for a disease (binary) outcome include the unmatched case-control, matched case-control, case-sibling, case-parent, and case-only designs. Study designs for a quantitative tra it include independent individuals and case parent designs. Quanto is a 32-bit Windows application requiring Windows 95, 98, NT, 2000, ME or XP to run. The graphical user interface allows th e user to easily change the model and view the results without having to edit an input file and rerun the program for every model. The results of a session are stored to a log file. This log can be printed or saved to a file for reviewing at a later date. An option is included to create a text file of the log that can be imported into other documents. (entry from Genetic Analysis Software)

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PennCNV (tool)

RRID:SCR_002518

A free software tool for Copy Number Variation (CNV) detection from SNP genotyping arrays. Currently it can handle signal intensity data from Illumina and Affymetrix arrays. With appropriate preparation of file format, it can also handle other types of SNP arrays and oligonucleotide arrays. PennCNV implements a hidden Markov model (HMM) that integrates multiple sources of information to infer CNV calls for individual genotyped samples. It differs form segmentation-based algorithm in that it considered SNP allelic ratio distribution as well as other factors, in addition to signal intensity alone. In addition, PennCNV can optionally utilize family information to generate family-based CNV calls by several different algorithms. Furthermore, PennCNV can generate CNV calls given a specific set of candidate CNV regions, through a validation-calling algorithm.

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RRID:SCR_005223

Database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)

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RRID:SCR_005726

ToppGene Suite is a one-stop portal for gene list enrichment analysis and candidate gene prioritization based on functional annotations and protein interactions network. ToppGene Suite is a one-stop portal for (i) gene list functional enrichment, (ii) candidate gene prioritization using either functional annotations or network analysis and (iii) identification and prioritization of novel disease candidate genes in the interactome. Functional annotation-based disease candidate gene prioritization uses a fuzzy-based similarity measure to compute the similarity between any two genes based on semantic annotations. The similarity scores from individual features are combined into an overall score using statistical meta-analysis.

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BEDTools (tool)

RRID:SCR_006646

A powerful toolset for genome arithmetic allowing one to address common genomics tasks such as finding feature overlaps and computing coverage. Bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.

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