Expressive

rs11171739 - ERBB3

Magnitude 2.2 · 8 studies on file

Reported associations

  • Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology. - Biological psychiatry (2022) · van der Meer D, Shadrin AA, O'Connell K, Bettella F, Djurovic S, Wolfers T, Alnæs D, Agartz I, Smeland OB, Melle I, Sánchez JM, Linden DEJ, Dale AM, Westlye LT, Andreassen OA, Frei O, Kaufmann T · PubMed 35164939

    Schizophrenia is a complex polygenic disorder with subtle, distributed abnormalities in brain morphology. There are indications of shared genetic architecture between schizophrenia and brain measures despite low genetic correlations. Through the use of analytical methods that allow for mixed directions of effects, this overlap may be leveraged to improve our understanding of underlying mechanisms of schizophrenia and enrich polygenic risk prediction outcome. We ran a multivariate genome-wide analysis of 175 brain morphology measures using data from 33,735 participants of the UK Biobank and analyzed the results in a conditional false discovery rate together with schizophrenia genome-wide association study summary statistics of the Psychiatric Genomics Consortium (PGC) Wave 3. We subsequentl

  • Eight novel susceptibility loci and putative causal variants in atopic dermatitis. - The Journal of allergy and clinical immunology (2021) · Tanaka N, Koido M, Suzuki A, Otomo N, Suetsugu H, Kochi Y, Tomizuka K, Momozawa Y, Kamatani Y, Ikegawa S, Yamamoto K, Terao C · PubMed 34116867

    Atopic dermatitis (AD) is the most common allergic disease in the world. While genetic components play critical roles in its pathophysiology, a large proportion of its genetic background is still unexplored. This study sought to illuminate the genetic associations with AD using genome-wide association study (GWAS) and its downstream analyses. This study conducted a GWAS for AD comprising 2,639 cases and 115,648 controls in the Japanese population, followed by a trans-ethnic meta-analysis with UK Biobank data and downstream analyses including partitioning heritability analysis by linkage disequilibrium score regression. This study identified 17 significant susceptibility loci, among which 4 loci-AFF1, ITGB8, EHMT1, and EGR2-were novel in the Japanese GWAS. The trans-ethnic meta-analysis rev

  • A General Dimension of Genetic Sharing across Diverse Cognitive Traits Inferred from Molecular Data - Unknown journal (n.d.) · Unknown authors · PubMed 32895543

    ABSTRACT: It has been known since 1904 that, in humans, diverse cognitive traits are positively inter correlated. This forms the basis for the general factor of intelligence (g). Here, we directly test whether there is a partial genetic basis for individual differences in g using data from seven different cognitive tests (N = 11,263 to N = 331,679) and genome-wide autosomal single nucleotide polymorphisms. A genetic g factor accounts for an average of 58.4% (SE = 4.8%) of the genetic variance in the cognitive traits, with the proportion varying widely across traits (range: 9% to 95%). We distill genetic loci that are broadly relevant for many cognitive traits (g) from loci associated specifically with individual cognitive traits. These results contribute to elucidating the etiology of a lo

  • A genome-wide cross trait analysis from UK Biobank highlights the shared genetic architecture of asthma and allergic diseases - Unknown journal (n.d.) · Unknown authors · PubMed 29785011

    ABSTRACT: Clinical and epidemiological data suggest that asthma and allergic diseases are associated and may share a common genetic etiology. We analyzed genome-wide single-nucleotide polymorphism (SNP) data for asthma and allergic diseases in 33,593 cases and 76,768 controls of European ancestry from the UK Biobank. Two publicly available independent genome wide association studies (GWAS) were used for replication. We have found a strong genome-wide genetic correlation between asthma and allergic diseases (rg = 0.75, P = 6.84×10−62). Cross trait analysis identified 38 genome-wide significant loci, including 7 novel shared loci. Computational analysis showed that shared genetic loci are enriched in immune/inflammatory systems and tissues with epithelium cells. Our work identifies common

  • Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls - Unknown journal (n.d.) · Unknown authors · PubMed 17554300

    ABSTRACT: There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined ~2,000 individuals for each of 7 major diseases and a shared set of ~3,000 controls. Case-control comparisons identified 24 independent association signals at P<5×10-7: 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed asso

  • A type 1 diabetes genetic risk score discriminates between type 1 diabetes and type 2 diabetes in a Chinese population - Unknown journal (n.d.) · Unknown authors · PubMed 40569436

    ABSTRACT: Aims/hypothesis We aimed to generate a population-specific type 1 diabetes genetic risk score (GRS) and assess whether it could improve discrimination between type 1 diabetes and type 2 diabetes in a Chinese population. Methods We performed a genome-wide association analysis on 1303 individuals with type 1 diabetes and 2236 control individuals. An independent replication cohort of 501 individuals with type 1 diabetes and 853 control individuals was used to validate the top common variant associations. HLA typing data were used to identify tag SNPs for DQA1-DQB1 haplotypes. We integrated significant signals to construct a Chinese type 1 diabetes GRS (C-GRS). The accuracy of the C-GRS was tested in an independent validation cohort consisting of 262 individuals with type 1 diabetes,

  • Meta-analysis of Immunochip data of four autoimmune diseases reveals novel single-disease and cross-phenotype associations - Unknown journal (n.d.) · Unknown authors · PubMed 30572963

    ABSTRACT: Background In recent years, research has consistently proven the occurrence of genetic overlap across autoimmune diseases, which supports the existence of common pathogenic mechanisms in autoimmunity. The objective of this study was to further investigate this shared genetic component. Methods For this purpose, we performed a cross-disease meta-analysis of Immunochip data from 37,159 patients diagnosed with a seropositive autoimmune disease (11,489 celiac disease (CeD), 15,523 rheumatoid arthritis (RA), 3477 systemic sclerosis (SSc), and 6670 type 1 diabetes (T1D)) and 22,308 healthy controls of European origin using the R package ASSET. Results We identified 38 risk variants shared by at least two of the conditions analyzed, five of which represent new pleiotropic loci in autoim

  • Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 39715877

    ABSTRACT: Socioeconomic status (SES) impacts health and life-course outcomes. This genome-wide association study (GWAS) of sociologically informed occupational status measures (ISEI, SIOPS, CAMSIS) using the UK Biobank (N = 273,157) identified 106 independent single-nucleotide polymorphisms of which 8 are novel to the study of SES. Genetic correlations with educational attainment (rg = 0.96-0.97) and income (rg = 0.81-0.91) point to a common genetic factor for SES. We observed a 54-57% reduction in within-family predictions compared with population-based predictions, attributed to indirect parental effects (22-27% attenuation) and assortative mating (21-27%) following our calculations. Using polygenic scores from population predictions of 5-10% (incremental R2 =

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