| 61. |
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| 62. |
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| 63. |
- Han, Buhm, et al.
(författare)
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A method to decipher pleiotropy by detecting underlying heterogeneity driven by hidden subgroups applied to autoimmune and neuropsychiatric diseases
- 2016
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 48:7, s. 803-
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Tidskriftsartikel (refereegranskat)abstract
- There is growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing among all individuals (whole-group pleiotropy) or a subset of individuals in a genetically heterogeneous cohort (subgroup heterogeneity). Here we describe the use of a well-powered statistic, BUHMBOX, to distinguish between those two situations using genotype data. We observed a shared genetic basis for 11 autoimmune diseases and type 1 diabetes (T1D; P < 1 x 10(-4)) and for 11 autoimmune diseases and rheumatoid arthritis (RA; P < 1 x 10(-3)). This sharing was not explained by subgroup heterogeneity (corrected P-BUHMBOX > 0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (P < 1 x 10(-9)) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (P-BUHMBOX = 0.008; 2,406 seronegative RA cases). We also observed a shared genetic basis for major depressive disorder (MDD) and schizophrenia (P < 1 x 10(-4)) that was not explained by subgroup heterogeneity (P-BUHMBOX = 0.28; 9,238 MDD cases).
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| 64. |
- Ishigaki, Kazuyoshi, et al.
(författare)
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Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis
- 2022
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Ingår i: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 54:11, s. 1640-1651
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Tidskriftsartikel (refereegranskat)abstract
- Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10−8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.
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| 65. |
- Karlson, EW, et al.
(författare)
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Cumulative association of 22 genetic variants with seropositive rheumatoid arthritis risk
- 2010
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Ingår i: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 69:6, s. 1077-1085
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Tidskriftsartikel (refereegranskat)abstract
- Recent discoveries of risk alleles have made it possible to define genetic risk profiles for patients with rheumatoid arthritis (RA). This study examined whether a cumulative score based on 22 validated genetic risk alleles for seropositive RA would identify high-risk, asymptomatic individuals who might benefit from preventive interventions.MethodsEight human leucocyte antigen (HLA) alleles and 14 single-nucleotide polymorphisms representing 13 validated RA risk loci were genotyped among 289 white seropositive cases and 481 controls from the US Nurses' Health Studies (NHS) and 629 white cyclic-citrullinated peptide antibody-positive cases and 623 controls from the Swedish Epidemiologic Investigation of Rheumatoid Arthritis (EIRA). A weighted genetic risk score (GRS) was created, in which the weight for each risk allele is the log of the published odds ratio (OR). Logistic regression was used to study associations with incident RA. Area under the curve (AUC) statistics were compared from a clinical-only model and clinical plus genetic model in each cohort.ResultsPatients with GRS >1.25 SD of the mean had a significantly higher OR of seropositive RA in both NHS (OR=2.9, 95%CI 1.8 to 4.6) and EIRA (OR 3.4, 95% CI 2.3 to 5.0) referent to the population average. In NHS, the AUC for a clinical model was 0.57 and for a clinical plus genetic model was 0.66, and in EIRA was 0.63 and 0.75, respectively.ConclusionThe combination of 22 risk alleles into a weighted GRS significantly stratifies individuals for RA risk beyond clinical risk factors alone. Given the low incidence of RA, the clinical utility of a weighted GRS is limited in the general population.
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| 66. |
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| 67. |
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| 68. |
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| 69. |
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| 70. |
- Lenz, Tobias L., et al.
(författare)
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Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases
- 2015
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Ingår i: Nature Genetics. - : Macmillan Publishers Ltd.. - 1061-4036 .- 1546-1718. ; 47:9, s. 1085-1090
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Tidskriftsartikel (refereegranskat)abstract
- Human leukocyte antigen (HLA) genes confer substantial risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen-binding repertoires between a heterozygote's two expressed HLA variants might result in additional non-additive risk effects. We tested the non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (n(cases) = 5,337), type 1 diabetes (T1D; n(cases) = 5,567), psoriasis vulgaris (n(cases) = 3,089), idiopathic achalasia (n(cases) = 727) and celiac disease (ncases = 11,115). In four of the five diseases, we observed highly significant, non-additive dominance effects (rheumatoid arthritis, P = 2.5 x 10(-12); T1D, P = 2.4 x 10(-10); psoriasis, P = 5.9 x 10(-6); celiac disease, P = 1.2 x 10(-87)). In three of these diseases, the non-additive dominance effects were explained by interactions between specific classical HLA alleles (rheumatoid arthritis, P = 1.8 x 10(-3); T1D, P = 8.6 x 10(-27); celiac disease, P = 6.0 x 10(-100)). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (rheumatoid arthritis, 1.4%; T1D, 4.0%; celiac disease, 4.1%) beyond a simple additive model.
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