| 1. |
- Sliz, E., et al.
(författare)
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Evidence of a causal effect of genetic tendency to gain muscle mass on uterine leiomyomata
- 2023
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Uterine leiomyomata (UL) are the most common tumours of the female genital tract and the primary cause of surgical removal of the uterus. Genetic factors contribute to UL susceptibility. To add understanding to the heritable genetic risk factors, we conduct a genome-wide association study (GWAS) of UL in up to 426,558 European women from FinnGen and a previous UL meta-GWAS. In addition to the 50 known UL loci, we identify 22 loci that have not been associated with UL in prior studies. UL-associated loci harbour genes enriched for development, growth, and cellular senescence. Of particular interest are the smooth muscle cell differentiation and proliferation-regulating genes functioning on the myocardin-cyclin dependent kinase inhibitor 1A pathway. Our results further suggest that genetic predisposition to increased fat-free mass may be causally related to higher UL risk, underscoring the involvement of altered muscle tissue biology in UL pathophysiology. Overall, our findings add to the understanding of the genetic pathways underlying UL, which may aid in developing novel therapeutics.
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| 3. |
- Kurki, MI, et al.
(författare)
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FinnGen provides genetic insights from a well-phenotyped isolated population
- 2023
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 613:7944, s. 508-
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Tidskriftsartikel (refereegranskat)abstract
- Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10–11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.
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| 4. |
- Divaris, K., et al.
(författare)
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Phenotype Harmonization in the GLIDE2 Oral Health Genomics Consortium
- 2022
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Ingår i: Journal of Dental Research. - : Sage Publications. - 0022-0345 .- 1544-0591. ; 101:11, s. 1408-1416
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Tidskriftsartikel (refereegranskat)abstract
- Genetic risk factors play important roles in the etiology of oral, dental, and craniofacial diseases. Identifying the relevant risk loci and understanding their molecular biology could highlight new prevention and management avenues. Our current understanding of oral health genomics suggests that dental caries and periodontitis are polygenic diseases, and very large sample sizes and informative phenotypic measures are required to discover signals and adequately map associations across the human genome. In this article, we introduce the second wave of the Gene-Lifestyle Interactions and Dental Endpoints consortium (GLIDE2) and discuss relevant data analytics challenges, opportunities, and applications. In this phase, the consortium comprises a diverse, multiethnic sample of over 700,000 participants from 21 studies contributing clinical data on dental caries experience and periodontitis. We outline the methodological challenges of combining data from heterogeneous populations, as well as the data reduction problem in resolving detailed clinical examination records into tractable phenotypes, and describe a strategy that addresses this. Specifically, we propose a 3-tiered phenotyping approach aimed at leveraging both the large sample size in the consortium and the detailed clinical information available in some studies, wherein binary, severity-encompassing, and “precision,” data-driven clinical traits are employed. As an illustration of the use of data-driven traits across multiple cohorts, we present an application of dental caries experience data harmonization in 8 participating studies (N = 55,143) using previously developed permanent dentition tooth surface–level dental caries pattern traits. We demonstrate that these clinical patterns are transferable across multiple cohorts, have similar relative contributions within each study, and thus are prime targets for genetic interrogation in the expanded and diverse multiethnic sample of GLIDE2. We anticipate that results from GLIDE2 will decisively advance the knowledge base of mechanisms at play in oral, dental, and craniofacial health and disease and further catalyze international collaboration and data and resource sharing in genomics research.
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| 5. |
- Liukkonen, J, et al.
(författare)
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Immunological and Microbiological Profiling of Cumulative Risk Score for Periodontitis
- 2020
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Ingår i: Diagnostics (Basel, Switzerland). - : MDPI AG. - 2075-4418. ; 10:8
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Tidskriftsartikel (refereegranskat)abstract
- The cumulative risk score (CRS) is a mathematical salivary diagnostic model to define an individual’s risk of having periodontitis. In order to further validate this salivary biomarker, we investigated how periodontal bacteria, lipopolysaccharide (LPS), and systemic and local host immune responses relate to CRS. Subgingival plaque, saliva, and serum samples collected from 445 individuals were used in the analyses. Plaque levels of 28 microbial species, especially those of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Porphyromonas endodontalis, Prevotella intermedia, and Tannerella forsythia, and serum and salivary levels of IgA and IgG against these five species were determined. Additionally, LPS activity was measured. High CRS associated strongly with all IgA/IgG antibody and LPS levels in saliva, whereas in serum the associations were not that obvious. In the final logistic regression model, the best predictors of high CRS were saliva IgA burden against the five species (OR 7.04, 95% CI 2.25–22.0), IgG burden (3.79, 1.78–8.08), LPS (2.19, 1.38–3.47), and the sum of 17 subgingival Gram-negative species (6.19, 2.10–18.3). CRS is strongly associated with microbial biomarker species of periodontitis and salivary humoral immune responses against them.
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