Gene dosage architecture across complex traits and common diseases
Creators: name: Sayeh Kazem
name: Kumar, Kuldeep
name: Renne, Thomas
name: Huguet, Guillaume
name: Martineau  Jean-Louis
name: Saci, Zohra
name: Almasy, Laura
name: Glahn, David
name: Dumas, Guillaume
name: Sebsatien Jacquemont
Publisher: name: F1000 Research Limited
Year: 2024

description: <b>Introduction</b>: Copy Number Variants (CNVs) are genomic deletions or duplications larger than 1000 base pairs (the fundamental unit of double-stranded nucleic acids), and play a crucial role in complex traits and common diseases [1][2][3][4]. Coding CNVs offer unique molecular insights; to date, only a few studies have conducted genome-wide CNV investigations, facing challenges such as limited statistical power and focusing primarily on a subset of CNVs. In contrast, Single-Nucleotide Polymorphisms (SNPs) associated with complex traits provide indirect insight into biological functions and it is often difficult to link them to changes in gene transcription and function [5]. Knowledge Gap: CNVs architecture and its potential convergence to common-variants architecture, across traits, remains unexplored.<br>
Previous studies, including our own, have shown that measures of constraint scores (Intolerance to inactivation score or loss of function score) explain a significant proportion of the effects of coding CNVs on cognitive, and behavioral traits. It is shown that close to 50% of coding genes with low constraint score (high intolerant to inactivation), decrease cognitive ability when deleted or duplicated [6]. However, it is unclear if the biological function of genes can inform on the effects of CNVs beyond constraint metrics.<br>
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<b>Overarching Aim:</b> Our overarching aim is to comprehensively characterize the CNV architecture of complex traits. <br>
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<b>Hypothesis:</b> We hypothesize that common variants and CNVs have pleiotropic effects on the same pairs of traits with similar genetic-correlations.<br>
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<b>Dataset &amp; Analytical Design: </b>Our outcome phenotypic measures of interest cover 28 traits, including cognition, socioeconomic status, blood assays, physical and psychological health, from 500,000 UK-Biobank participants. We use CNVs &gt;50 kilobases, fully encompassing &gt;1 genes. Since the population frequency (&lt;1/10000) of most coding CNVs remains an obstacle for variant-level associations, we aggregate variants that disrupt genes involved in the same biological function for each individual. Our main steps are:<br>
     1. Defining gene-lists and aggregating CNVs within gene-lists. The gene-lists are defined<br>
                based on gene expression specificity across tissues or cell-types and top 10% genes are considered for each gene-list. We use 3 resources to define gene-lists:<br>
                - Whole Body Tissues: 60 tissues from FANTOM5, The Functional Annotation of Mammalian Genomes 5 project. <br>
                - Whole Body Single Cells: 81 cell types from Human Protein Atlas (HPA).<br>
                - Brain Single Cells: 461 brain cells from Human Brain Cell Atlas. <br>
     2. Estimating the effect sizes of CNVs on traits using burden association analysis (CNVs analysis. in aggregate), per gene-list, for deletion and duplication separately.<br>
     3.Computing burden genetic correlation between pairs of traits, using effect-sizes.<br>
     4.Comparing CNV and common variant genetic correlations<br>
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<b>Results</b>: We observed that some traits (Townsend deprivation index, pulmonary metrics, neuroticism, cognitive ability) were associated with most tissues, while others were associated with only a few gene sets. We found that brain tissues are highly pleiotropic and have in general higher proportions of intolerant genes than non-brain tissues. Furthermore, at the cellular level, neuronal and glial cells are associated with cognitive traits the most. Precisely, among non-neuronal cells, microglia, choroid plexus, and oligodendrocytes have the strongest associations with cognitive traits. For neuronal cells, both excitatory and inhibitory neurons are linked to cognitive traits.<br>
We found that CNVs and common-variant architectures are concordant (slope(B):1.53, p=2.44e-35), based on genetic-correlations, as illustrated in the figure. Stratification based on constraint scores did not impact this concordance. 82% of traits showed negative correlations between deletion and duplication effect-size profiles. <br>
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<b>Conclusion:</b> We found that the majority of traits are dosage-sensitive. There is a convergent association between CNVs and common variants which proves that they have pleiotropic effects on the same pairs of traits with similar genetic-correlations. The constraint measure influences gene lists, and that impacts on pleiotropy.<br>
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<b>References:</b><br>
[1]: Auwerx C, Lepamets M, Sadler MC, Patxot M, Stojanov M, Baud D, Mägi R; Estonian Biobank Research Team; Porcu E, Reymond A, Kutalik Z. The individual and global impact of copy-number variants on complex human traits. Am J Hum Genet. 2022 Apr 7;109(4):647-668. doi: 10.1016/j.ajhg.2022.02.010. Epub 2022 Mar 2. PMID: 35240056; PMCID: PMC9069145.<br>
[2]: Auwerx C, Jõeloo M, Sadler MC, Tesio N, Ojavee S, Clark CJ, Mägi R; Estonian Biobank Research Team; Reymond A, Kutalik Z. Rare copy-number variants as modulators of common disease susceptibility. Genome Med. 2024 Jan 8;16(1):5. doi: 10.1186/s13073-023-01265-5. PMID: 38185688; PMCID: PMC10773105.<br>
[3]: Kendall KM, Bracher-Smith M, Fitzpatrick H, Lynham A, Rees E, Escott-Price V, Owen MJ, O'Donovan MC, Walters JTR, Kirov G. Cognitive performance and functional outcomes of carriers of pathogenic copy number variants: analysis of the UK Biobank. Br J Psychiatry. 2 May;214(5):297-304. doi: 10.1192/bjp.2018.301. Epub 2 Feb 15. PMID: 30767844; PMCID: PMC6520248.<br>
[4]: Hujoel, Margaux LA, et al. "Influences of rare copy-number variation on human complex traits." Cell 185.22 (2022): 4233-4248.<br>
[5]: Tam, V., Patel, N., Turcotte, M. et al. Benefits and limitations of genome-wide association studies. Nat Rev Genet 20, 467–484 (2). https://doi.org/10.1038/s41576--0127-1<br>
[6]: Huguet, G.et al.Genome-wide analysis of gene dosage in 24,092 individuals estimates that 10,000genes modulate cognitive ability.Mol Psychiatry(2021).