rs12128707 - NEGR1
Magnitude 2.2 · 8 studies on file
Reported associations
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A General Cognitive Ability Factor for the UK Biobank. - Behavior genetics (2023) · Williams CM, Labouret G, Wolfram T, Peyre H, Ramus F · PubMed 36378351
UK Biobank participants do not have a high-quality measure of intelligence or polygenic scores (PGSs) of intelligence to simultaneously examine the genetic and neural underpinnings of intelligence. We created a standardized measure of general intelligence (g factor) relative to the UK population and estimated its quality. After running a GWAS of g on UK Biobank participants with a g factor of good quality and without neuroimaging data (N = 187,288), we derived a g PGS for UK Biobank participants with neuroimaging data. For individuals with at least one cognitive test, the g factor from eight cognitive tests (N = 501,650) explained 29% of the variance in cognitive test performance. The PGS for British individuals with neuroimaging data (N = 27,174) explained 7.6% of the varia
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Genetic Relationships between Attention-Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, and Intelligence. - Neuropsychobiology (2022) · Rao S, Baranova A, Yao Y, Wang J, Zhang F · PubMed 35764056
Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) commonly co-occur; both traits exert an influence on intelligence scores. Genetic relationships between these three traits are far from being clear. The summary results of genome-wide association studies of ADHD (20,183 cases and 35,191 controls), ASD (18,381 cases and 27,969 controls), and intelligence (269,867 participants) were used for the analyses. Local genetic correlation analysis and polygenic overlap analysis were used to explore the shared genetic components between ADHD, ASD, and intelligence. Mendelian randomization (MR) analysis was used to examine the causal associations between ADHD, ASD, and intelligence. A cross-trait meta-analysis was performed to identify pleiotropic genetic variants acros
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Uncovering the multivariate genetic architecture of frailty with genomic structural equation modeling - Unknown journal (n.d.) · Unknown authors · PubMed 40759756
ABSTRACT: Frailty is a multifaceted clinical state associated with accelerated aging and adverse health outcomes. Informed etiological models of frailty hold promise for producing widespread health improvements across the aging population. Frailty is currently measured using aggregate scores, which obscure etiological pathways that are only relevant to subcomponents of frailty. Here we perform a multivariate genome-wide association study of the latent genetic architecture between 30 frailty deficits, which identifies 408 genomic risk loci. Our model includes a general factor of genetic overlap across all deficits, plus six new factors indexing a shared genetic signal across specific groups of deficits. We demonstrate the added clinical and etiological value of the six factors, including pr
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Combining cross-sectional and longitudinal genomic approaches to identify determinants of cognitive and physical decline - Unknown journal (n.d.) · Unknown authors · PubMed 40374629
ABSTRACT: Large-scale genomic studies focusing on the genetic contribution to human aging have mostly relied on cross-sectional data. With the release of longitudinally curated aging phenotypes by the UK Biobank (UKBB), it is now possible to study aging over time at genome-wide scale. In this work, we evaluated the suitability of competing models of change in realistic simulation settings, performed genome-wide association scans on simulation-validated measures of age-related deweekcline, and followed up with LD-score regression and Mendelian Randomization (MR) analyses. Focusing on global cognitive and physical function, we observed marked differences between baseline function (θ) and accelerated decline (Δ). Both outcomes showed distinct heritability levels (e.g., 31.38% versus 3.15%
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Gene discovery and polygenic prediction from a 1.1-million-person GWAS of educational attainment - Unknown journal (n.d.) · Unknown authors · PubMed 30038396
ABSTRACT: We conduct a large-scale genetic association analysis of educational attainment in a sample of ~1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of ~0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of
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Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence - Unknown journal (n.d.) · Unknown authors · PubMed 29942086
[INTRO] Intelligence is highly heritable and a major determinant of human health and well-being. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence, but much about its genetic underpinnings remains to be discovered. Here, we present the largest genetic association study of intelligence to date (N=269,867), identifying 205 associated genomic loci (190 novel) and 1,016 genes (939 novel) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny
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Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction - Unknown journal (n.d.) · Unknown authors · PubMed 38839884
ABSTRACT: Restless legs syndrome (RLS) affects up to 10% of older adults. Their healthcare is impeded by delayed diagnosis and insufficient treatment. To advance disease prediction and find new entry points for therapy, we performed meta-analyses of genome-wide association studies in 116,647 individuals with RLS (cases) and 1,546,466 controls of European ancestry. The pooled analysis increased the number of risk loci eightfold to 164, including three on chromosome X. Sex-specific meta-analyses revealed largely overlapping genetic predispositions of the sexes (rg = 0.96). Locus annotation prioritized druggable genes such as glutamate receptors 1 and 4, and Mendelian randomization indicated RLS as a causal risk factor for diabetes. Machine learning approaches combining genetic and nongen
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Investigating the genetic architecture of non-cognitive skills using GWAS-by-subtraction - Unknown journal (n.d.) · Unknown authors · PubMed 33414549
ABSTRACT: Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used Genomic Structural Equation Modeling and prior genome-wide association studies (GWAS) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability.We identified 157 genome-wide significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Non-cognitive genetics were enriched in the same brain tissues and cell types as cognitive performance but showed different associations with gray-matter brain volumes. Non-cognitive genetics were further distinguished by associations with
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