| 1. |
- Middeldorp, Christel M., et al.
(författare)
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The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects
- 2019
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Ingår i: European Journal of Epidemiology. - : Springer Science and Business Media LLC. - 0393-2990 .- 1573-7284. ; 34:3, s. 279-300
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Tidskriftsartikel (refereegranskat)abstract
- The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.
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| 2. |
- Plant, Darren, et al.
(författare)
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Investigation of potential non-HLA rheumatoid arthritis susceptibility loci in a European cohort increases the evidence for nine markers
- 2010
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 69:8, s. 1548-1553
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Tidskriftsartikel (refereegranskat)abstract
- Background Genetic factors have a substantial role in determining development of rheumatoid arthritis (RA), and are likely to account for 50-60% of disease susceptibility. Genome-wide association studies have identified non-human leucocyte antigen RA susceptibility loci which associate with RA with low-to-moderate risk. Objectives To investigate recently identified RA susceptibility markers using cohorts from six European countries, and perform a meta-analysis including previously published results. Methods 3311 DNA samples were collected from patients from six countries (UK, Germany, France, Greece, Sweden and Denmark). Genotype data or DNA samples for 3709 controls were collected from four countries (not Sweden or Denmark). Eighteen single nucleotide polymorphisms (SNPs) were genotyped using Sequenom MassArray technology. Samples with a >95% success rate and only those SNPs with a genotype success rate of >95% were included in the analysis. Scandinavian patient data were pooled and previously published Swedish control data were accessed as a comparison group. Meta-analysis was used to combine results from this study with all previously published data. Results After quality control, 3209 patients and 3692 controls were included in the study. Eight markers (ie, rs1160542 (AFF3), rs1678542 (KIF5A), rs2476601 (PTPN22), rs3087243 (CTLA4), rs4810485 (CD40), rs5029937 (6q23), rs10760130 (TRAF1/C5) and rs7574865 (STAT4)) were significantly associated with RA by meta-analysis. All 18 markers were associated with RA when previously published studies were incorporated in the analysis. Data from this study increased the significance for association with RA and nine markers. Conclusions In a large European RA cohort further evidence for the association of 18 markers with RA development has been obtained.
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| 3. |
- Schumann, Gunter, et al.
(författare)
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KLB is associated with alcohol drinking, and its gene product beta-Klotho is necessary for FGF21 regulation of alcohol preference
- 2016
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 113:50, s. 14372-14377
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Tidskriftsartikel (refereegranskat)abstract
- Excessive alcohol consumption is a major public health problem worldwide. Although drinking habits are known to be inherited, few genes have been identified that are robustly linked to alcohol drinking. We conducted a genome-wide association metaanalysis and replication study among >105,000 individuals of European ancestry and identified beta-Klotho (KLB) as a locus associated with alcohol consumption (rs11940694; P = 9.2 x 10(-12)). beta-Klotho is an obligate coreceptor for the hormone FGF21, which is secreted from the liver and implicated in macronutrient preference in humans. We show that brain-specific beta-Klotho KO mice have an increased alcohol preference and that FGF21 inhibits alcohol drinking by acting on the brain. These data suggest that a liver-brain endocrine axis may play an important role in the regulation of alcohol drinking behavior and provide a unique pharmacologic target for reducing alcohol consumption.
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| 4. |
- Zhou, Wei, et al.
(författare)
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Global Biobank Meta-analysis Initiative : Powering genetic discovery across human disease
- 2022
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Ingår i: Cell Genomics. - : Elsevier. - 2666-979X. ; 2:10
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Tidskriftsartikel (refereegranskat)abstract
- Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
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