- Research article
- Open Access
- Published: 30 November 2022
- Meng-Yuan Shang1,2 na1,
- Yong Wu3 na1,
- Chu-Yi Zhang4,
- Hao-Xiang Qi4,
- Qing Zhang1,2,
- Jin-Hua Huo4,
- Lu Wang4,
- Chuang Wang1,2 &
- …
- Ming Li4
BMC Medicine volume 20, Article number: 464 (2022) Cite this article
Abstract
Background
Bipolar upset (BD) is simply a highly heritable psychiatric unwellness exhibiting important correlation with intelligence.
Methods
To analyse the shared familial signatures betwixt BD and intelligence, we utilized the summary statistic from genome-wide relation studies (GWAS) to behaviour the bivariate causal substance exemplary (MiXeR) and conjunctional mendacious find complaint (conjFDR) analyses. Subsequent look quantitative trait loci (eQTL) mapping successful quality encephalon and enrichment analyses were besides performed.
Results
Analysis with MiXeR suggested that astir 10.3K variants could power intelligence, among which 7.6K variants were correlated with the hazard of BD (Dice: 0.80), and 47% of these variants predicted BD hazard and quality successful accordant allelic directions. The conjFDR investigation identified 37 chiseled genomic loci that were jointly associated with BD and quality with a conjFDR < 0.01, and 16 loci (43%) had the aforesaid directions of allelic effects successful some phenotypes. Brain eQTL analyses recovered that genes affected by the “concordant loci” were chiseled from those modulated by the “discordant loci”. Enrichment analyses suggested that genes related to the “concordant loci” were importantly enriched successful pathways/phenotypes related with synapses and slumber quality, whereas genes associated with the “discordant loci” were enriched successful pathways related to compartment adhesion, calcium ion binding, and abnormal affectional phenotypes.
Conclusions
We confirmed the polygenic overlap with mixed directions of allelic effects betwixt BD and quality and identified aggregate genomic loci and hazard genes. This survey provides hints for the mesoscopic phenotypes of BD and applicable biologic mechanisms, promoting the cognition of the familial and phenotypic heterogeneity of BD. The indispensable worth of leveraging quality successful BD investigations is besides highlighted.
Background
Bipolar upset (BD) is simply a highly heritable psychiatric upset characterized by temper swings betwixt mania/hypomania and slump [1, 2]. Early duplicate studies person indicated important publication of a familial constituent successful the etiology of BD [3,4,5], and familial analyses including genome-wide relation studies (GWASs) person reported aggregate genomic loci showing grounds of associations with hazard of BD [6, 7]. To date, BD hazard loci person been recovered to incorporate genes encoding ion channels, neurotransmitter transporters, and synaptic proteins [8], yet the mesoscopic phenotypes linking these pathways and BD stay mostly obscure. Accumulating grounds person shown that steadfast individuals oregon siblings carrying BD familial hazard alleles exhibited alterations successful peculiar intermediate phenotypes (e.g., amygdala enactment and cognitive function) [9,10,11,12], and studies of these intermediate phenotypes are hence believed to supply clues for the biologic underpinnings of BD.
To date, increasing grounds has shown a putative correlation betwixt hazard of BD and intelligence, for example, erstwhile studies recovered that children with precocious quality quotient (IQ) scores had a higher accidental of being diagnosed with BD successful adulthood [13,14,15]. Further studies recovered that individuals with either highly precocious oregon debased schoolhouse grades were much apt to beryllium diagnosed with BD aboriginal successful beingness compared to their peers with mean show [16], suggesting that the correlation betwixt BD and IQ is not linear. In addition, a large-scale prospective epidemiological survey of much than 1 cardinal Swedish men recovered a “reversed–J” shaped relation betwixt quality and hospitalization for BD (the mean follow-up play was 22.6 years, and the patients had nary psychiatric comorbidities) [17]. Specifically, they recovered that the hazard of hospitalization with immoderate signifier of BD decreased arsenic the quality increased; successful the meantime, subjects with either the lowest IQ scores oregon the highest IQ scores (especially those who performed amended successful verbal oregon method tests) had greater hazard of hospitalization with axenic BD [17].
These findings suggested important associations betwixt BD and quality with analyzable correlation patterns. Since some BD hazard and quality are proven to beryllium heritable, it is plausible to hypothesize that determination is simply a shared familial ground betwixt BD and intelligence. Although erstwhile familial correlation estimates utilizing the Linkage Disequilibrium Score Regression (LDSC) method based connected GWAS results yielded non-significant results betwixt BD and quality [8], it should beryllium noticed that the LDSC method tin lone seizure important correlations erstwhile aggregate variants showed accordant allelic effect directions (the aforesaid oregon the opposite, but not mixed) successful some phenotypes. Since variants associated with some BD and quality whitethorn person mixed directions of allelic effects betwixt phenotypes, the putative shared familial instauration betwixt them is inactive warranted. Indeed, mixed directions of allelic effects betwixt phenotypes with overlapped familial ground are commonly seen [18,19,20], and Frei et al. described a caller statistical method, MiXeR, for precisely estimating the wide shared polygenic architecture careless of allelic effect directions [21]. In addition, the conjunctional mendacious find complaint (conjFDR) analyses, which are built connected an empirical Bayesian statistical model and leverages the combined powerfulness of some GWASs, are believed to summation the accidental of discovering caller hazard loci based connected GWAS summary statistic [22,23,24,25,26,27].
Using these approaches, erstwhile studies person demonstrated extended familial overlap betwixt BD and quality with mixed directions of allelic effects [25, 28], which seems successful enactment with the epidemiological observations. In the contiguous study, we repeated the MiXeR and conjFDR analyses utilizing summary statistic from the latest GWASs of BD and intelligence, identifying some known and caller hazard genes showing concordant oregon discordant effects betwixt the 2 traits. Follow-up functional annotations and gene-set enrichment analyses recovered chiseled molecular pathways and quality phenotypes associated with “concordant loci” and “discordant loci,” respectively. These results identified familial mechanisms explaining the phenotypic heterogeneity crossed the bipolar spectrum disorders and provides hints for the mesoscopic phenotypes of BD by leveraging intelligence.
Methods
GWAS samples
GWAS summary datasets of BD (n = 41,917 cases and 371,549 controls) [8] and quality (n = 269,867 individuals) [29] were retrieved from published studies. As described successful the archetypal study, the BD GWAS illustration included 41,917 cases from 57 cohorts collected successful Europe, North America, and Australia, and 371,549 controls from European countries [8]. The quality GWAS information included 14 datasets from Europe and North America, and a communal latent g origin underlying aggregate dimensions of cognitive functioning was calculated and applied to operationalize the cohorts with quality measured utilizing chiseled approaches [29]. The accusation astir the effect allele, effect size (beta oregon likelihood ratio), modular error, and P worth were obtained from the GWAS studies.
Statistical analyses
The genome-wide familial correlation (rg) of BD with quality was calculated utilizing LDSC [30]. MiXeR (version v1.3) was utilized to conception a bivariate causal substance exemplary to estimation the full fig of shared and trait-specific causal variants betwixt BD and quality based connected GWAS summary statistic [21, 31]. MiXeR results are presented arsenic a Venn diagram of the shared and unsocial polygenic components crossed BD and intelligence, and the dice coefficient people (polygenic overlap measurement successful the 0~100% scale) were besides computed [18].
The conditional quantile-quantile (Q-Q) plots were generated to supply a ocular signifier of enrichment successful azygous nucleotide polymorphism (SNP) associations betwixt BD and intelligence. As described successful the erstwhile survey [32], the Q-Q plots computed the empirical cumulative distributions of P values successful the superior phenotype for each SNPs and for subsets of SNPs (e.g., P ≤ 0.1, P ≤ 0.01, P ≤ 0.001, respectively) successful the secondary phenotype. Increased grade of leftward deflection, from the expected null enactment arsenic the relation value increases successful a phenotype, suggests enrichment of associations of the different phenotype [32].
We adjacent conducted the conjFDR analyses to qualify the genomic loci and SNPs jointly associated with some BD and intelligence. As described successful the erstwhile studies [32, 33], this method re-adjusted the GWAS summary statistic successful the superior phenotype (e.g., BD) by leveraging pleiotropic enrichment with the GWAS summary statistic successful the secondary phenotype (e.g., intelligence). The conditional FDR (condFDR) estimates were calculated for each variant successful the superior phenotype utilizing the stratified empirical cumulative organisation function. This process was past performed again with the superior and secondary phenotypes switched, and conjFDR was defined arsenic the maximum of the 2 condFDR values [32, 33]. During the conjFDR analyses, each P values successful the archetypal GWAS datasets were corrected for genomic inflation, since the empirical null distributions of SNP associations successful GWASs mightiness beryllium affected by colonisation stratification [32]. Random pruning of SNPs was performed passim the 500 iterations successful some the conditional Q-Q plots and conjFDR analyses to minimize ostentation resulted from linkage disequilibrium (LD) dependency, and 1 randomly-returned typical SNP for each LD-independent artifact was retained aft each pruning iteration (cluster of SNPs with r2 > 0.1). As recommended successful the erstwhile survey [18], we remained lone 1 awesome successful the highly extended large histocompatibility analyzable (MHC) portion (hg19, chr6:26M-34M) to minimize the impacts of analyzable LD patterns successful this genomic area. SNPs with a conjFDR < 0.01 were considered statistically significant.
Functional annotations of the genomic hazard loci
To place genes associated with the hazard loci, we conducted look quantitative trait loci (eQTL) analyses of each the important SNPs successful each autarkic genomic portion (conjFDR < 0.01 and astatine r2 < 0.2), to place genes associated with the hazard loci successful aggregate datasets. We utilized datasets of postmortem postnatal quality encephalon tissues (dorsolateral prefrontal cortex (DLPFC) oregon hippocampus) specified arsenic psychENCODE (n = 1387 for DLPFC) [34], BrainMeta (n = 2865 for cortex) [35], BrainSeq (n = 477 for hippocampus) [36] and Genotype-Tissue Expression (GTEx; n = 175 for DLPFC and n = 165 for hippocampus) [37], datasets of prenatal cortex tissues from O’Brien et al. (n = 120) [38] and Walker et al. (n = 201) [39] studies, arsenic good arsenic single-cell eQTLs resources (including mature midbrain dopaminergic neurons (from 175 donors) and serotonergic-like neurons (from 161 donors) differentiated from quality induced pluripotent stem cells (iPSC) lines [40]; and excitatory neurons and inhibitory neurons from 196 individuals by azygous nuclei RNA-sequencing [41]). Detailed accusation astir the illustration characteristics, look quantification, and normalization, arsenic good arsenic statistical investigation successful each eQTL dataset, tin beryllium recovered successful the archetypal publications. The psychENCODE and BrainSeq datasets lone provided SNP associations passing genome-wide level of statistical value (false find complaint (FDR) < 0.05 successful psychENCODE and FDR < 0.01 successful BrainSeq), we hence straight retrieved the important eQTL associations. For the different eQTL datasets, we empirically considered the genes with eQTL P < 0.001 to beryllium significant. We did not execute eQTL investigation successful the MHC portion (hg19, chr6:26M-34M) fixed its analyzable LD patterns and imaginable mapping problems utilizing short-reads sequencing.
Enrichment analyses of the hazard genes
For the hazard genes identified by eQTL analyses, we conducted enrichment analyses of Gene Ontology (GO), Reactome pathway [42], UniProt keywords [43], and Monarch Human Phenotype Ontology (HPO) [44] utilizing the STRING dataset (version 11.5) [45].
Results
Polygenic overlap betwixt BD and intelligence
The polygenic overlap (i.e., shared causal variants) betwixt BD and quality was assessed utilizing MiXeR based connected GWAS summary statistics. The bivariate MiXeR investigation revealed that astir 8.6K (standard deviation (SD) = 0.2K) variants influenced BD, and astir 10.3K (SD = 0.3K) variants influenced intelligence. Intriguingly, 7.6K (SD = 0.5K) variants influenced some BD and intelligence, and the wide measurement of polygenic overlap betwixt BD and quality was 80.3% (standard mistake (SE) = 4.9%) connected a 0–100% standard (quantified arsenic the Dice coefficient) (Fig. 1A).
We past generated conditional quantile-quantile (Q-Q) plots conditioning BD connected quality and vice versa, to further picture the pleiotropic enrichment of SNP associations betwixt BD and intelligence. The evident leftward deflection of the curves for some BD-given quality and intelligence-given BD suggested beardown enrichment of the important variants for 1 trait successful the other. Notably, SNPs with higher value for the conditional trait exhibited greater leftward deflection successful some plots, confirming the important polygenic overlap betwixt BD and quality (Fig. 1B).
Shared familial loci betwixt BD and intelligence
Both MiXeR and the Q-Q plots indicated important polygenic overlap betwixt BD and intelligence, but nary important familial correlation was observed betwixt them (LDSC rg = −0.066, P = 0.062, Fig. 1A). Since LDSC analyses lone reported important familial correlations with the premise that determination were galore SNPs showing associations with some phenotypes successful concordant absorption of allelic effects, we suspected that the shared variants betwixt BD and quality had mixed directions of allelic effects. Indeed, MiXeR investigation showed that the “concordant variants” took up lone 47% (SE = 0.4%) of the shared familial components (7.6K variants) betwixt BD and intelligence.
We hence applied the familial pleiotropy-informed conjFDR method [33], which identifies loci associated with some BD and quality careless of the allelic effect directionality with boosted statistical power. We identified 37 chiseled genomic loci (r2 < 0.2) that were jointly associated with BD and quality with a conjFDR < 0.01 (Fig. 2 and Table 1), including 24 autarkic loci that were not identified successful the archetypal BD GWAS [8]. Further computation of the z-scores of these loci revealed that 16 SNPs exhibited the aforesaid directions of effect betwixt BD and quality (i.e., 1 allele predicted a higher hazard of BD and greater intelligence), portion 21 SNPs had the other directions (Fig. 2 and Table 1). This uncovering is accordant with a erstwhile survey describing loci jointly associated with BD and quality [25], albeit that survey reported less associated hazard loci.
We past performed a elaborate genomic mapping investigation of the 37 shared loci betwixt BD and intelligence. The locus with the strongest concordant effect connected some the hazard of BD and quality was successful MIR2113 connected chromosome 6 (rs1487445, conjFDR = 7.78×10−11), and the T-allele of rs1487445 predicted some accrued hazard of BD (odds ratio (OR) = 1.077, P = 1.48×10−15) and higher IQ scores (beta = 0.031, P = 3.27×10−29) (Fig. 3A). The variant with the strongest other effects connected BD and quality is successful the chromosome 3p21.1 portion (rs12487445, conjFDR = 1.54×10−6), and the A-allele of rs12487445 predicted accrued hazard of BD (OR = 1.062, P = 2.44×10−10) but little IQ scores (beta = −0.018, P = 3.31×10−11) (Fig. 3B). The locus showing the 2nd strongest other effects was successful the highly extended MHC portion (rs3749971, conjFDR = 3.27×10−5), and the G-allele of rs3749971 predicted accrued hazard of BD (OR = 1.106, P = 8.91×10−10) portion little IQ scores (beta = −0.030, P = 3.06×10−9) (Fig. S1). Another locus with the other directions of allelic effects betwixt BD and quality was successful the cistron ADCY2 (rs17826816, conjFDR = 1.04×10−4), and its G-allele was linked to higher hazard of BD (OR = 1.065, P = 1.32×10−8) but little IQ scores (beta = −0.018, P = 1.68×10−8) (Fig. S2).
Since BD and schizophrenia grounds beardown familial correlations [46], and schizophrenia besides has important polygenic overlap with quality [25], determination is the anticipation that the identified BD hazard loci done leveraging quality are not exclusively associated with BD. We verified this by examining the aforementioned 37 BD hazard SNPs successful the largest schizophrenia GWAS successful Europeans (74,776 cases and 101,023 controls) [47], we recovered that 15 of these loci were besides associated with schizophrenia successful the aforesaid allelic directions (Table 1). Notably, 13 of the 21 SNPs showing other directions of effect betwixt BD and quality besides exhibited important associations with schizophrenia; by contrast, lone 2 of the 16 SNPs showing the aforesaid directions of effect betwixt BD and quality were associated with schizophrenia. Therefore, though some BD and schizophrenia person polygenic overlap with intelligence, the imaginable familial mechanisms regulating quality successful these 2 disorders are apt divergent.
Risk genes and functional annotations successful the important genomic loci
Since bulk of the hazard SNPs for BD are successful the noncoding genomic regions, functional annotations of them are urgently needed. Accumulating grounds suggests that noncoding SNPs impact cistron transcription and splicing apt successful a compartment type- and developmental stage-specific mode [7, 48]. We frankincense examined the regulatory effects of the BD hazard SNPs utilizing datasets containing quality eQTL results successful postnatal DLPFC and hippocampal tissues, prenatal cortex tissues, arsenic good arsenic antithetic types of encephalon cells. In summary, 25 of the 37 hazard loci had eQTL associations successful astatine slightest 1 dataset (Table 1); 9 of the 16 hazard loci showing concordant effects connected BD and quality contained eQTL-associated hazard genes, portion 16 of the 21 loci showing other effects connected BD and quality contained eQTL associated hazard genes. There were nary overlapped eQTL hazard genes betwixt the “concordant loci” and “discordant loci”.
Specifically, 37 protein-coding genes were importantly affected by SNPs successful the loci showing concordant effects connected BD and quality (Table S1). Although GO investigation of these genes did not uncover immoderate important enrichment, Reactome pathway investigation recovered that their proteins were importantly enriched successful the pathways of “Activation of AMPK downstream of NMDARs,” “Microtubule-dependent trafficking of connexons from Golgi to the plasma membrane,” “RHO GTPases activate IQGAPs,” “Selective autophagy,” “Transmission crossed Chemical Synapses,” and “Membrane Trafficking” (Fig. 4A and Table S2). UniProt keywords investigation suggested that these proteins were importantly enriched successful the presumption of “GTP-binding” and “Fatty acerb biosynthesis” (Fig. 4A and Table S2). Monarch HPO investigation recovered that these genes were enriched successful the presumption “Intelligence,” “Cognition,” and “Self reported acquisition attainment.” Intriguingly, we recovered that these genes besides showed important enrichment successful the word “Sleep measurement” (Fig. 4A and Table S2).
We identified 135 protein-coding genes affected by SNPs successful the genomic loci showing other effects connected BD and quality (Table S3). GO investigation of these genes revealed important enrichment successful the presumption “Cell adhesion” and “Calcium ion binding”, whereas Reactome pathway investigation did not place immoderate importantly enriched pathways (Fig. 4B and Table S4). Similarly, UniProt keywords investigation recovered important enrichment of these proteins successful the presumption “Cell adhesion” and “Calcium” (Fig. 4B and Table S4). Monarch HPO investigation recovered that these genes were enriched successful the presumption “Intelligence” and “Cognition.” It should beryllium noticed that these genes were besides importantly enriched successful “Anxiety,” “Emotional grounds measurement,” and “Worry measurement” (Fig. 4B and Table S4).
Discussion
A erstwhile survey by Gale et al. [17] recovered elevated hazard of processing BD successful subjects with either little oregon higher IQ scores, and extended familial overlap betwixt BD and quality with mixed directions of allelic effects was demonstrated [25, 28]. In the contiguous study, we person identified aggregate genomic loci and hazard genes correlated with some BD and intelligence, with either the aforesaid oregon other directions of allelic effects. These results supply imaginable explanations for the higher prevalence of BD successful subjects with either debased oregon precocious intelligence, and item the etiological heterogeneity of BD.
By leveraging pleiotropic enrichment betwixt BD and quality utilizing the conjFDR method, we herein identified 37 loci jointly associated with BD and quality (16 loci showed the aforesaid allelic effect directions, and 21 loci showed other directions) based connected large-scale GWAS summary statistics, and 24 loci were not identified successful the archetypal BD GWAS [8]. We noticed that 1 of the astir important loci, which showed the aforesaid directions of allelic effects betwixt BD and intelligence, was successful MIR2113 connected chromosome 6 (rs1487445, conjFDR = 7.78×10−11). Notably, a caller survey recovered that a variant rs77910749, which is successful implicit LD with rs1487445 (r2 = 1.00 successful Europeans) and resides wrong a highly conserved putative enhancer LC1 successful the upstream portion of POU3F2 [49], could change LC1 enhancer enactment and POU3F2 look during neurodevelopment successful embryonic rodent encephalon and quality iPSC-derived cerebral organoids. Intriguingly, rs77910749 knock-in mice exhibited behavioral defects successful sensory gating [49], which is an amygdala-dependent endophenotype commonly seen successful BD patients [50].
Despite that little quality and higher quality are some linked to accrued hazard of BD, we speculate that the molecular mechanisms underlying the 2 conditions are distinct. Indeed, functional annotations revealed that nary overlap of the genes affected by the “concordant loci” and those affected by the “discordant loci.” Further analyses recovered that genes related to the “concordant loci” were importantly enriched successful synapses related pathways, whereas genes related to the “discordant loci” were importantly enriched successful the biologic processes of “Cell adhesion” and “Calcium ion binding.” More intriguingly, though some sets of genes showed important enrichment successful the presumption “Intelligence” and “Cognition,” the “concordant genes” besides showed enrichment successful “Sleep measurement,” whereas the “discordant genes” were alternatively enriched successful “Anxiety,” “Emotional grounds measurement,” and “Worry measurement.” These results suggested that the “concordant genes” were apt related to the dysrhythmia successful BD, portion “discordant genes” were perchance progressive successful the abnormal affectional behaviors. Therefore, further investigations into genes shared by quality and BD, either with the aforesaid oregon other directions of allelic effects, volition apt widen our cognition of this upset and biologic mechanisms of the quality brain.
Nonetheless, we acknowledged the imaginable regulation that the shared loci betwixt BD and quality tin not afloat explicate their nonlinear relationships successful epidemiological observations, arsenic different factors (e.g., household and societal environment, humanistic culture, and education) whitethorn besides impact these traits. In addition, our analyses were based connected samples from European ancestry, contempt the results being intriguing, validations successful different taste populations are indispensable successful the future.
Conclusions
We observed important polygenic overlap betwixt BD and quality and identified aggregate loci associated with BD and quality with mixed directions of allelic effects. Enrichment analyses suggested antithetic biologic processes related to the “concordant genes” and the "discordant genes", providing hints for the mesoscopic phenotypes of BD and applicable biologic mechanisms. An appealing hypothesis, that whether BD patients with little quality grounds much terrible affectional disturbance, portion BD patients with higher quality person much predominant dysrhythmia, is of large involvement for further objective validations.
Availability of information and materials
Abbreviations
Bipolar disorder
condFDR:Conditional mendacious find rate
conjFDR:Conjunctional mendacious find rate
DLPFC:Dorsolateral prefrontal cortex
eQTL:Expression quantitative trait loci
FDR:False find rate
GO:Gene Ontology
GWAS:Genome-wide relation studies
GTEx:Genotype-Tissue Expression
HPO:Human Phenotype Ontology
IQ:Intelligence quotient
iPSC:Induced pluripotent stem cells
LD:Linkage disequilibrium
LDSC:Linkage Disequilibrium Score Regression
MHC:Major histocompatibility complex
OR:Odds ratio
Q-Q:Quantile-quantile
SD:Standard deviation
SE:Standard error
SNP:Single nucleotide polymorphism
References
McIntyre RS, Berk M, Brietzke E, Goldstein BI, Lopez-Jaramillo C, Kessing LV, et al. Bipolar disorders. Lancet. 2020;396(10265):1841–56.
Carvalho AF, Firth J, Vieta E. Bipolar disorder. N Engl J Med. 2020;383(1):58–66.
Kieseppa T, Partonen T, Haukka J, Kaprio J, Lonnqvist J. High concordance of bipolar I upset successful a nationwide illustration of twins. Am J Psychiatry. 2004;161(10):1814–21.
McGuffin P, Rijsdijk F, Andrew M, Sham P, Katz R, Cardno A. The heritability of bipolar affective upset and the familial narration to unipolar depression. Arch Gen Psychiatry. 2003;60(5):497–502.
Bertelsen A, Harvald B, Hauge M. A Danish duplicate survey of manic-depressive disorders. Br J Psychiatry. 1977;130:330–51.
Gordovez FJA, McMahon FJ. The genetics of bipolar disorder. Mol Psychiatry. 2020;25(3):544–59.
Zhang C, Xiao X, Li T, Li M. Translational genomics and beyond successful bipolar disorder. Mol Psychiatry. 2021;26(1):186–202.
Mullins N, Forstner AJ, O'Connell KS, Coombes B, Coleman JRI, Qiao Z, et al. Genome-wide relation survey of much than 40,000 bipolar upset cases provides caller insights into the underlying biology. Nat Genet. 2021;53(6):817–29.
Li M, Li T, Xiao X, Chen J, Hu Z, Fang Y. Phenotypes, mechanisms and therapeutics: insights from bipolar upset GWAS findings. Mol Psychiatry. 2022;27(7):2927–39.
Glahn DC, Almasy L, Barguil M, Hare E, Peralta JM, Kent JW Jr, et al. Neurocognitive endophenotypes for bipolar upset identified successful multiplex multigenerational families. Arch Gen Psychiatry. 2010;67(2):168–77.
Erk S, Meyer-Lindenberg A, Schmierer P, Mohnke S, Grimm O, Garbusow M, et al. Hippocampal and frontolimbic relation arsenic intermediate phenotype for psychosis: grounds from steadfast relatives and a communal hazard variant successful CACNA1C. Biol Psychiatry. 2014;76(6):466–75.
Hill SK, Reilly JL, Keefe RS, Gold JM, Bishop JR, Gershon ES, et al. Neuropsychological impairments successful schizophrenia and psychotic bipolar disorder: findings from the Bipolar-Schizophrenia Network connected Intermediate Phenotypes (B-SNIP) study. Am J Psychiatry. 2013;170(11):1275–84.
Koenen KC, Moffitt TE, Roberts AL, Martin LT, Kubzansky L, Harrington H, et al. Childhood IQ and big intelligence disorders: a trial of the cognitive reserve hypothesis. Am J Psychiatry. 2009;166(1):50–7.
Smith DJ, Anderson J, Zammit S, Meyer TD, Pell JP, Mackay D. Childhood IQ and hazard of bipolar upset successful adulthood: prospective commencement cohort study. BJPsych Open. 2015;1(1):74–80.
Karpinski RI, Kinase Kolb AM, Tetreault NA, Borowski TB. High intelligence: a hazard origin for intelligence and physiological overexcitabilities. Intelligence. 2018;66:8–23.
MacCabe JH, Lambe MP, Cnattingius S, Sham PC, David AS, Reichenberg A, et al. Excellent schoolhouse show astatine property 16 and hazard of big bipolar disorder: nationalist cohort study. Br J Psychiatry. 2010;196(2):109–15.
Gale CR, Batty GD, McIntosh AM, Porteous DJ, Deary IJ, Rasmussen F. Is bipolar upset much communal successful highly intelligent people? A cohort survey of a cardinal men. Mol Psychiatry. 2013;18(2):190–4.
Bahrami S, Shadrin A, Frei O, O'Connell KS, Bettella F, Krull F, et al. Genetic loci shared betwixt large slump and quality with mixed directions of effect. Nat Hum Behav. 2021;5(6):795–801.
Bahrami S, Hindley G, Winsvold BS, O'Connell KS, Frei O, Shadrin A, et al. Dissecting the shared familial ground of migraine and intelligence disorders utilizing caller statistical tools. Brain. 2021;145(1):142–53.
Rodevand L, Bahrami S, Frei O, Chu Y, Shadrin A, O'Connell KS, et al. Extensive bidirectional familial overlap betwixt bipolar upset and cardiovascular illness phenotypes. Transl Psychiatry. 2021;11(1):407.
Frei O, Holland D, Smeland OB, Shadrin AA, Fan CC, Maeland S, et al. Bivariate causal substance exemplary quantifies polygenic overlap betwixt analyzable traits beyond familial correlation. Nat Commun. 2019;10(1):2417.
Cheng W, Frei O, van der Meer D, Wang Y, O'Connell KS, Chu Y, et al. Genetic relation betwixt schizophrenia and cortical encephalon aboveground country and thickness. JAMA Psychiatry. 2021;78(9):1020–30.
Bahrami S, Steen NE, Shadrin A, O'Connell K, Frei O, Bettella F, et al. Shared familial loci betwixt assemblage wide scale and large psychiatric disorders: A genome-wide relation study. JAMA Psychiatry. 2020;77(5):503–12.
Pisanu C, Congiu D, Severino G, Ardau R, Chillotti C, Del Zompo M, et al. Investigation of familial loci shared betwixt bipolar upset and risk-taking propensity: imaginable implications for pharmacological interventions. Neuropsychopharmacology. 2021;46(9):1680–92.
Smeland OB, Bahrami S, Frei O, Shadrin A, O'Connell K, Savage J, et al. Genome-wide investigation reveals extended familial overlap betwixt schizophrenia, bipolar disorder, and intelligence. Mol Psychiatry. 2020;25(4):844–53.
Cheng W, van der Meer D, Parker N, Hindley G, O'Connell KS, Wang Y, et al. Shared familial architecture betwixt schizophrenia and subcortical encephalon volumes implicates aboriginal neurodevelopmental processes and encephalon improvement successful childhood. Mol Psychiatry. 2022. https://doi.org/10.1038/s41380-41022-01751-z.
Icick R, Shadrin A, Holen B, Karadag N, Lin A, Hindley G, et al. Genetic overlap betwixt temper instability and alcohol-related phenotypes suggests shared biologic underpinnings. Neuropsychopharmacology. 2022;47(11):1883–91.
Hindley G, Frei O, Shadrin AA, Cheng W, O'Connell KS, Icick R, et al. Charting the scenery of familial overlap betwixt intelligence disorders and related traits beyond familial correlation. Am J Psychiatry. 2022;179(11):833–43.
Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, de Leeuw CA, et al. Genome-wide relation meta-analysis successful 269,867 individuals identifies caller familial and functional links to intelligence. Nat Genet. 2018;50(7):912–9.
Bulik-Sullivan B, Finucane HK, Anttila V, Gusev A, Day FR, Loh PR, et al. Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control C, Duncan L et al: An atlas of familial correlations crossed quality diseases and traits. Nat Genet. 2015;47(11):1236–41.
Holland D, Frei O, Desikan R, Fan CC, Shadrin AA, Smeland OB, et al. Beyond SNP heritability: Polygenicity and discoverability of phenotypes estimated with a univariate Gaussian substance model. PLoS Genet. 2020;16(5):e1008612.
Andreassen OA, Djurovic S, Thompson WK, Schork AJ, Kendler KS, O'Donovan MC, et al. Improved detection of communal variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease hazard factors. Am J Hum Genet. 2013;92(2):197–209.
Andreassen OA, Thompson WK, Schork AJ, Ripke S, Mattingsdal M, Kelsoe JR, et al. Improved detection of communal variants associated with schizophrenia and bipolar upset utilizing pleiotropy-informed conditional mendacious find rate. PLoS Genet. 2013;9(4):e1003455.
Wang D, Liu S, Warrell J, Won H, Shi X, Navarro FCP, et al. Comprehensive functional genomic assets and integrative exemplary for the quality brain. Science. 2018;362(6420):eaat8464.
Qi T, Wu Y, Fang H, Zhang F, Liu S, Zeng J, et al. Genetic power of RNA splicing and its chiseled relation successful analyzable trait variation. Nat Genet. 2022;54(9):1355–63.
Collado-Torres L, Burke EE, Peterson A, Shin J, Straub RE, Rajpurohit A, et al. Regional heterogeneity successful cistron expression, regulation, and coherence successful the frontal cortex and hippocampus crossed improvement and schizophrenia. Neuron. 2019;103(2):203–16.
GTEx Consortium. Laboratory Data Analysis, Coordinating Center -Analysis Working Group, Statistical Methods groups-Analysis Working Group, Enhancing GTEx groups, NIH Common Fund, Nih/Nci, Nih/Nhgri, Nih/Nimh, Nih/Nida et al: Genetic effects connected cistron look crossed quality tissues. Nature. 2017;550(7675):204–13.
O'Brien HE, Hannon E, Hill MJ, Toste CC, Robertson MJ, Morgan JE, et al. Expression quantitative trait loci successful the processing quality encephalon and their enrichment successful neuropsychiatric disorders. Genome Biol. 2018;19(1):194.
Walker RL, Ramaswami G, Hartl C, Mancuso N, Gandal MJ, de la Torre-Ubieta L, et al. Genetic power of look and splicing successful processing quality encephalon informs illness mechanisms. Cell. 2019;179(3):750–771 e722.
Jerber J, Seaton DD, Cuomo ASE, Kumasaka N, Haldane J, Steer J, et al. Population-scale single-cell RNA-seq profiling crossed dopaminergic neuron differentiation. Nat Genet. 2021;53(3):304–12.
Bryois J, Calini D, Macnair W, Foo L, Urich E, Ortmann W, et al. Cell-type-specific cis-eQTLs successful 8 quality encephalon compartment types place caller hazard genes for psychiatric and neurological disorders. Nat Neurosci. 2022;25(8):1104–12.
Gillespie M, Jassal B, Stephan R, Milacic M, Rothfels K, Senff-Ribeiro A, et al. The reactome pathway knowledgebase 2022. Nucleic Acids Res. 2022;50(D1):D687–d692.
UniProt C. UniProt: the cosmopolitan macromolecule knowledgebase successful 2021. Nucleic Acids Res. 2021;49(D1):D480–9.
Kohler S, Gargano M, Matentzoglu N, Carmody LC, Lewis-Smith D, Vasilevsky NA, et al. The Human Phenotype Ontology successful 2021. Nucleic Acids Res. 2021;49(D1):D1207–17.
Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, et al. The STRING database successful 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021;49(D1):D605–12.
Bipolar Disorder Schizophrenia Working Group of the Psychiatric Genomics Consortium. Genomic dissection of bipolar upset and schizophrenia, including 28 subphenotypes. Cell. 2018;173(7):1705–1715 e1716.
Trubetskoy V, Pardinas AF, Qi T, Panagiotaropoulou G, Awasthi S, Bigdeli TB, et al. Mapping genomic loci implicates genes and synaptic biology successful schizophrenia. Nature. 2022;604(7906):502–8.
Edwards SL, Beesley J, French JD, Dunning AM. Beyond GWASs: illuminating the acheronian roadworthy from relation to function. Am J Hum Genet. 2013;93(5):779–97.
Shen SQ, Kim-Han JS, Cheng L, Xu D, Gokcumen O, Hughes AE, et al. A campaigner causal variant underlying some higher quality and accrued hazard of bipolar disorder. bioRxiv. 2019:580258.
Perry W, Minassian A, Feifel D, Braff DL. Sensorimotor gating deficits successful bipolar upset patients with acute psychotic mania. Biol Psychiatry. 2001;50(6):418–24.
Acknowledgements
Dataset(s) from the survey “Genetic power of look and splicing successful processing quality encephalon informs illness mechanisms” utilized for the analyses described successful this manuscript were generated successful the Geschwind laboratory and supported by NIH grants to D.H.G (5R37 MH060233, 5R01 MH094714, 1R01 MH110927) and to J.L.S (R00MH102357). Dataset(s) were obtained from dbGaP recovered astatine http://www.ncbi.nlm.nih.gov/gap done dbGaP survey accession fig phs001900.
Funding
This enactment was supported by grants from Natural Science Funds for Distinguished Young Scholar of Zhejiang (LR20H090001 to C.W.), National Natural Science Foundation of China (82225016 to M.L., 82171527 to C.W.), Municipal Key R&D Program of Ningbo (2022Z127 to C.W.), Yunnan Fundamental Research Projects (202101AT070283 and 202101AT070359 to L.W.), Spring City Plan: the High-level Talent Promotion and Training Project of Kunming (2022SCP001), and Open Research Fund (AMHD-2021-1 and AMHD-2022-1).
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All the GWAS information utilized successful this survey were publically disposable and nary archetypal information was collected, and nary ethical committee support was required for this study.
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The authors state that they person nary competing interests.
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Cite this article
Shang, MY., Wu, Y., Zhang, CY. et al. Bidirectional familial overlap betwixt bipolar upset and intelligence. BMC Med 20, 464 (2022). https://doi.org/10.1186/s12916-022-02668-8
Received: 26 August 2022
Accepted: 17 November 2022
Published: 30 November 2022
DOI: https://doi.org/10.1186/s12916-022-02668-8
Keywords
- Bipolar disorder
- Intelligence
- Genome-wide relation study
- Polygenic overlap
- Shared loci