Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 May 1;75(5):447-457.
doi: 10.1001/jamapsychiatry.2018.0039.

Measuring and Estimating the Effect Sizes of Copy Number Variants on General Intelligence in Community-Based Samples

Free PMC article

Measuring and Estimating the Effect Sizes of Copy Number Variants on General Intelligence in Community-Based Samples

Guillaume Huguet et al. JAMA Psychiatry. .
Free PMC article


Importance;: Copy number variants (CNVs) classified as pathogenic are identified in 10% to 15% of patients referred for neurodevelopmental disorders. However, their effect sizes on cognitive traits measured as a continuum remain mostly unknown because most of them are too rare to be studied individually using association studies.

Objective: To measure and estimate the effect sizes of recurrent and nonrecurrent CNVs on IQ.

Design, setting, and participants: This study identified all CNVs that were 50 kilobases (kb) or larger in 2 general population cohorts (the IMAGEN project and the Saguenay Youth Study) with measures of IQ. Linear regressions, including functional annotations of genes included in CNVs, were used to identify features to explain their association with IQ. Validation was performed using intraclass correlation that compared IQ estimated by the model with empirical data.

Main outcomes and measures: Performance IQ (PIQ), verbal IQ (VIQ), and frequency of de novo CNV events.

Results: The study included 2090 European adolescents from the IMAGEN study and 1983 children and parents from the Saguenay Youth Study. Of these, genotyping was performed on 1804 individuals from IMAGEN and 977 adolescents, 445 mothers, and 448 fathers (484 families) from the Saguenay Youth Study. We observed 4928 autosomal CNVs larger than 50 kb across both cohorts. For rare deletions, size, number of genes, and exons affect IQ, and each deleted gene is associated with a mean (SE) decrease in PIQ of 0.67 (0.19) points (P = 6 × 10-4); this is not so for rare duplications and frequent CNVs. Among 10 functional annotations, haploinsufficiency scores best explain the association of any deletions with PIQ with a mean (SE) decrease of 2.74 (0.68) points per unit of the probability of being loss-of-function intolerant (P = 8 × 10-5). Results are consistent across cohorts and unaffected by sensitivity analyses removing pathogenic CNVs. There is a 0.75 concordance (95% CI, 0.39-0.91) between the effect size on IQ estimated by our model and IQ loss calculated in previous studies of 15 recurrent CNVs. There is a close association between effect size on IQ and the frequency at which deletions occur de novo (odds ratio, 0.86; 95% CI, 0.84-0.87; P = 2.7 × 10-88). There is a 0.76 concordance (95% CI, 0.41-0.91) between de novo frequency estimated by the model and calculated using data from the DECIPHER database.

Conclusions and relevance: Models trained on nonpathogenic deletions in the general population reliably estimate the effect size of pathogenic deletions and suggest omnigenic associations of haploinsufficiency with IQ. This represents a new framework to study variants too rare to perform individual association studies and can help estimate the cognitive effect of undocumented deletions in the neurodevelopmental clinic.

Conflict of interest statement

Conflict of Interest Disclosures: None reported.


Figure 1.
Figure 1.. Venn Diagram and Flowchart for Quality Control of Arrays and Copy Number Variants (CNVs)
A, Venn diagram representing different steps of microarray selection by quality control and verification of genetic information. The blue circle represents an array without good quality control. The green circle represents individuals having discordance between pedigree information and array (sex and relationship). The red circle represents duplicated microarrays. B, Flowchart representing the steps of CNVs selection after that microarray with good quality was selected. kb indicates kilobase; seg dup, segmental duplication; and SYS, Saguenay Youth Study.
Figure 2.
Figure 2.. Predicted Loss of Performance IQ (PIQ) for Recurrent Copy Number Variants (CNVs) and Nonrecurrent CNVs Observed in the Clinic
A, Distribution of the loss of PIQ per gene estimated by the model 4 for all RefSeq genes (N = 17 102). The black solid vertical line is the median, the dashed black vertical line is the mean, and the dashed orange vertical line is the mean individual effect of genes included in rare deletions (model 2). Of note, 36% of genes have an associated estimated loss of PIQ less than −0.67, 33% (n = 5597) are predicted to affect IQ greater than or equal to 1 point, 23% (n = 3949) by greater than or equal to 2 points, and 6% (n = 968) have maximum effect size. B, Concordance between loss of PIQ estimated by model 4 (y-axis) and loss of PIQ measured by previously published studies (x-axis) for 15 recurrent CNVs. Each point corresponds to a known recurrent CNV: (1) 17p12_(HNPP), (2) 16p12.1, (3) 15q11.2, (4) 16p13.11, (5) 1q21.1 TAR, (6) 17q12, (7) 16p11.2 Distal (SH2B1), (8) 1q21.1 Distal (Class I), (9) 15q13.3 (BP4-BP5), (10) 16p11.2 proximal (BP4-BP5), (11) 22q11.2, (12) 7q11.23 (William-Beuren), (13) 3q29 (DLG1), (14) 8p23.1, and (15) 17p11.2 (Smith-Magenis). The diagonal dashed line represents exact concordance. When loss of IQ was not directly measured in a previous study, we derived the loss of IQ from the published OR measuring the enrichment of a CNV in the neurodevelopmental clinic (open circles). Of note, the PIQ loss estimated by the model is 4.4 points for the 17q21.31 deletion, including KANSL1 a causal gene for intellectual disabilities. This is discordant with the estimated decrease of 36.3 points based on empirical data from the literature. Including this CNV, the concordance is 0.62 (95% CI, 0.20-0.85). C, Coverage of genes by the Center Hospitalier Universitaire Sainte-Justine (CHU-SJ) cohort according to significance level of CNVs. The y-axis represents the number of unique genes observed in the cohort, and the x-axis represents the number of individuals seen in the cohort. Coverage was obtained using 1000 iterations (bootstrap procedure on the order of individuals’ inclusion). D, Density of loss of PIQ estimated by the model 4 for genes included in CNVs from CHU-SJ for the different clinical significance category of CNVs. Solid lines correspond to medians, and the dashed lines correspond to means. ICC3,1 indicates intraclass correlation coefficient (1, 3); VUS, variant of unknown significance.
Figure 3.
Figure 3.. Association Between De Novo and IQ Loss
A, Probability of de novo estimated by model 5 (y-axis) according to the loss of performance IQ (PIQ) estimated by model 4 (x-axis) for the 897 deletions from the Center Hospitalier Universitaire Sainte-Justine cohort and 1264 deletions from the Simon simplex collection cohort for which inheritance status is available (the orange lines are all copy number variants [CNVs], and the gray lines are nonrecurrent CNVs). The de novo frequency increased even for modest associations with IQ (eg, −5 points of PIQ is associated with a de novo frequency of 7.8%). B, Concordance between de novo frequency observed in DECIPHER (x-axis) and the probability of being de novo estimated by model 5 (y-axis) for 15 recurrent CNVs. Each point corresponds to a known recurrent CNV: (1) 17p12_(HNPP), (2) 16p12.1, (3) 15q11.2, (4) 16p13.11, (5) 1q21.1 TAR, (6) 17q12, (7) 16p11.2 Distal (SH2B1), (8) 1q21.1 Distal (Class I), (9) 15q13.3 (BP4-BP5), (10) 16p11.2 proximal (BP4-BP5), (11) 22q11.2, (12) 7q11.23 (William-Beuren), (13) 3q29 (DLG1), (14) 8p23.1, and (15) 17p11.2 (Smith-Magenis). The first bisector represents the perfect concordance. ICC3,1 indicates intraclass correlation coefficient (1, 3).

Similar articles

See all similar articles

Cited by 6 articles

  • Insufficient Evidence for "Autism-Specific" Genes.
    Myers SM, Challman TD, Bernier R, Bourgeron T, Chung WK, Constantino JN, Eichler EE, Jacquemont S, Miller DT, Mitchell KJ, Zoghbi HY, Martin CL, Ledbetter DH. Myers SM, et al. Am J Hum Genet. 2020 May 7;106(5):587-595. doi: 10.1016/j.ajhg.2020.04.004. Epub 2020 Apr 30. Am J Hum Genet. 2020. PMID: 32359473
  • Critical exon indexing improves clinical interpretation of copy number variants in neurodevelopmental disorders.
    Wassman ER, Ho KS, Bertrand D, Davis KW, Martin MM, Page S, Peiffer A, Prasad A, Serrano MA, Twede H, Vanzo R, Scherer SW, Uddin M, Hensel CH. Wassman ER, et al. Neurol Genet. 2019 Dec 6;5(6):e378. doi: 10.1212/NXG.0000000000000378. eCollection 2019 Dec. Neurol Genet. 2019. PMID: 32042908 Free PMC article.
  • Cognitive Genomics: Recent Advances and Current Challenges.
    Fitzgerald J, Morris DW, Donohoe G. Fitzgerald J, et al. Curr Psychiatry Rep. 2020 Jan 10;22(1):2. doi: 10.1007/s11920-019-1125-x. Curr Psychiatry Rep. 2020. PMID: 31925558 Review.
  • Association of Copy Number Variation of the 15q11.2 BP1-BP2 Region With Cortical and Subcortical Morphology and Cognition.
    Writing Committee for the ENIGMA-CNV Working Group, van der Meer D, Sønderby IE, Kaufmann T, Walters GB, Abdellaoui A, Ames D, Amunts K, Andersson M, Armstrong NJ, Bernard M, Blackburn NB, Blangero J, Boomsma DI, Brodaty H, Brouwer RM, Bülow R, Cahn W, Calhoun VD, Caspers S, Cavalleri GL, Ching CRK, Cichon S, Ciufolini S, Corvin A, Crespo-Facorro B, Curran JE, Dalvie S, Dazzan P, de Geus EJC, de Zubicaray GI, de Zwarte SMC, Delanty N, den Braber A, Desrivieres S, Di Forti M, Doherty JL, Donohoe G, Ehrlich S, Eising E, Espeseth T, Fisher SE, Fladby T, Frei O, Frouin V, Fukunaga M, Gareau T, Glahn DC, Grabe HJ, Groenewold NA, Gústafsson Ó, Haavik J, Haberg AK, Hashimoto R, Hehir-Kwa JY, Hibar DP, Hillegers MHJ, Hoffmann P, Holleran L, Hottenga JJ, Hulshoff Pol HE, Ikeda M, Jacquemont S, Jahanshad N, Jockwitz C, Johansson S, Jönsson EG, Kikuchi M, Knowles EEM, Kwok JB, Le Hellard S, Linden DEJ, Liu J, Lundervold A, Lundervold AJ, Martin NG, Mather KA, Mathias SR, McMahon KL, McRae AF, Medland SE, Moberget T, Moreau C, Morris DW, Mühleisen TW, Murray RM, Nordvik JE, Nyberg L, Olde Loohuis LM, Ophoff RA, Owen MJ, Paus T, Pausova Z, Peralta JM, Pike B, Prieto C, Quinlan EB, Reinbold CS, Reis Marques T, Rucker JJH, Sachdev PS, Sando SB, Schofield PR, Schork AJ, Schumann G, Shin J, Shumskaya E, Silva AI, Sisodiya SM, Steen VM, Stein DJ, Strike LT, Tamnes CK, Teumer A, Thalamuthu A, Tordesillas-Gutiérrez D, Uhlmann A, Úlfarsson MÖ, van 't Ent D, van den Bree MBM, Vassos E, Wen W, Wittfeld K, Wright MJ, Zayats T, Dale AM, Djurovic S, Agartz I, Westlye LT, Stefánsson H, Stefánsson K, Thompson PM, Andreassen OA. Writing Committee for the ENIGMA-CNV Working Group, et al. JAMA Psychiatry. 2019 Oct 30;77(4):1-11. doi: 10.1001/jamapsychiatry.2019.3779. Online ahead of print. JAMA Psychiatry. 2019. PMID: 31665216
  • Estimating the effect size of the 15Q11.2 BP1-BP2 deletion and its contribution to neurodevelopmental symptoms: recommendations for practice.
    Jønch AE, Douard E, Moreau C, Van Dijck A, Passeggeri M, Kooy F, Puechberty J, Campbell C, Sanlaville D, Lefroy H, Richetin S, Pain A, Geneviève D, Kini U, Le Caignec C, Lespinasse J, Skytte AB, Isidor B, Zweier C, Caberg JH, Delrue MA, Møller RS, Bojesen A, Hjalgrim H, Brasch-Andersen C, Lemyre E, Ousager LB, Jacquemont S; 15q11.2 Working Group. Jønch AE, et al. J Med Genet. 2019 Oct;56(10):701-710. doi: 10.1136/jmedgenet-2018-105879. Epub 2019 Aug 26. J Med Genet. 2019. PMID: 31451536 Free PMC article.
See all "Cited by" articles

Publication types