Expressive

rs116617502 - LINC02240

Magnitude 2.0 · 6 studies on file

Reported associations

  • The genetic architecture of human cortical folding - Science advances (2026) · van der Meer D, Kaufmann T, Shadrin AA, Makowski C, Frei O, Roelfs D, Monereo-Sánchez J, Linden DEJ, Rokicki J, Alnæs D, de Leeuw C, Thompson WK, Loughnan R, Fan CC, Westlye LT, Andreassen OA, Dale AM · PubMed 34910505

    ABSTRACT: The first genome-wide study of sulcal depth shows that it is highly genetically discoverable, associated with neurodevelopment. The folding of the human cerebral cortex is a highly genetically regulated process that allows for a much larger surface area to fit into the cranial vault and optimizes functional organization. Sulcal depth is a robust yet understudied measure of localized folding, previously associated with multiple neurodevelopmental disorders. Here, we report the first genome-wide association study of sulcal depth. Through the multivariate omnibus statistical test (MOSTest) applied to vertex-wise measures from 33,748 U.K. Biobank participants (mean age, 64.3 years; 52.0% female), we identified 856 genome-wide significant loci (P < 5 × 10−8). Comparisons with corti

  • Larger cerebral cortex is genetically correlated with greater frontal area and dorsal thickness - Proceedings of the National Academy of Sciences of the United States of America (2023) · Makowski C, Wang H, Srinivasan A, Qi A, Qiu Y, van der Meer D, Frei O, Zou J, Visscher PM, Yang J, Chen CH · PubMed 36893272

    ABSTRACT: Significance Adjusting vs. retaining global measures in analysis of brain MRI data has been a long-standing question and can have important implications for genomic studies of the cortex. Adjusting for global measures ensures that results for regions of interest are not confounded by overall larger brain size. However, adjusting for globals may throw away important signal when total and regional measures are correlated. We show that retaining vs. adjusting for global brain measures in genomic studies impacts gene discovery, particularly for fronto-parietal cortex. Understanding the genetic factors that contribute to expanded association areas in the human brain, such as the prefrontal cortex, can help provide mechanistic insight into higher human cognition and its unique developm

  • Discovery of genomic loci of the human cerebral cortex using genetically informed brain atlases* - Science (New York, N.Y.) (2022) · Makowski C, van der Meer D, Dong W, Wang H, Wu Y, Zou J, Liu C, Rosenthal SB, Hagler DJ, Fan CC, Kremen WS, Andreassen OA, Jernigan TL, Dale AM, Zhang K, Visscher PM, Yang J, Chen CH · PubMed 35113692

    ABSTRACT: To determine the impact of genetic variants on the brain, we used genetically-informed brain atlases in genome-wide association studies of regional cortical surface area and thickness in 39,898 adults and 9136 children. We uncovered 440 genome-wide significant loci in the discovery cohort and 800 from a post-hoc combined meta-analysis. Loci in adulthood were largely captured in childhood, showing signatures of negative selection, and were linked to early neurodevelopment and pathways associated with neuropsychiatric risk. Opposing gradations of decreased surface area and increased thickness were associated with common inversion polymorphisms. Inferior frontal regions, encompassing Broca's area which is important for speech, were enriched for human-specific genomic elements. Thu

  • Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology - NeuroImage (2022) · Shadrin AA, Kaufmann T, van der Meer D, Palmer CE, Makowski C, Loughnan R, Jernigan TL, Seibert TM, Hagler DJ, Smeland OB, Motazedi E, Chu Y, Lin A, Cheng W, Hindley G, Thompson WK, Fan CC, Holland D, Westlye LT, Frei O, Andreassen OA, Dale AM · PubMed 34560273

    ABSTRACT: Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commo

  • An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank - Nature neuroscience (2021) · Smith SM, Douaud G, Chen W, Hanayik T, Alfaro-Almagro F, Sharp K, Elliott LT · PubMed 33875891

    ABSTRACT: UK Biobank is a major prospective epidemiological study, including multimodal brain imaging, genetics and ongoing health outcomes. Previously, we published genome-wide associations of 3,144 brain imaging-derived phenotypes, with a discovery sample of 8,428 subjects. Here we present a new open resource of GWAS summary statistics, using the 2020 data release, almost tripling the discovery sample size. We now include the X chromosome, and new classes of image derived phenotypes (subcortical volumes and tissue contrast). Previously we had found 148 replicated clusters of associations between genetic variants and imaging phenotypes; here we find 692, including 12 on the X chromosome. We describe some of the newly found associations, focussing on the X chromosome and autosomal associat

  • Understanding the genetic determinants of the brain with MOSTest - Nature communications (2020) · van der Meer D, Frei O, Kaufmann T, Shadrin AA, Devor A, Smeland OB, Thompson WK, Fan CC, Holland D, Westlye LT, Andreassen OA, Dale AM · PubMed 32665545

    ABSTRACT: Regional brain morphology has a complex genetic architecture, consisting of many common polymorphisms with small individual effects. This has proven challenging for genome-wide association studies (GWAS). Due to the distributed nature of genetic signal across brain regions, multivariate analysis of regional measures may enhance discovery of genetic variants. Current multivariate approaches to GWAS are ill-suited for complex, large-scale data of this kind. Here, we introduce the Multivariate Omnibus Statistical Test (MOSTest), with an efficient computational design enabling rapid and reliable inference, and apply it to 171 regional brain morphology measures from 26,502 UK Biobank participants. At the conventional genome-wide significance threshold of α = 5 × 10−8, MOS

Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.