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- Zheng, Hou-Feng, et al.
(författare)
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Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture
- 2015
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 526:7571, s. 112-
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Tidskriftsartikel (refereegranskat)abstract
- The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF <= 1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants(1-8), as well as rare, population specific, coding variants(9). Here we identify novel non-coding genetic variants with large effects on BMD (n(total) = 53,236) and fracture (n(total) = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD8 (rs11692564(T), MAF51.6%, replication effect size510.20 s.d., P-meta = 2 x 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 x 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1cre/flox mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size +10.41 s.d., P-meta = 1 x 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.
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| 5. |
- Minikel, EV, et al.
(författare)
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Quantifying prion disease penetrance using large population control cohorts
- 2016
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Ingår i: Science translational medicine. - : American Association for the Advancement of Science (AAAS). - 1946-6242 .- 1946-6234. ; 8:322, s. 322ra9-
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Tidskriftsartikel (refereegranskat)abstract
- Large genomic reference data sets reveal a spectrum of pathogenicity in the prion protein gene and provide genetic validation for a therapeutic strategy in prion disease.
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| 6. |
- van Houten, C. B., et al.
(författare)
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Observational multi-centre, prospective study to characterize novel pathogen-and host-related factors in hospitalized patients with lower respiratory tract infections and/or sepsis - the "TAILORED-Treatment" study
- 2018
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Ingår i: BMC Infectious Diseases. - : Springer Science and Business Media LLC. - 1471-2334. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Background: The emergence and spread of antibiotic resistant micro-organisms is a global concern, which is largely attributable to inaccurate prescribing of antibiotics to patients presenting with non-bacterial infections. The use of 'omics' technologies for discovery of novel infection related biomarkers combined with novel treatment algorithms offers possibilities for rapidly distinguishing between bacterial and viral infections. This distinction can be particularly important for patients suffering from lower respiratory tract infections (LIT(1) and/or sepsis as they represent a significant burden to healthcare systems. Here we present the study details of the TAILORED-Treatment study, an observational, prospective, multi-centre study aiming to generate a multi-parametric model, combining host and pathogen data, for distinguishing between bacterial and viral aetiologies in children and adults with LRTI and/or sepsis. Methods: A total number of 1200 paediatric and adult patients aged 1 month and older with LRT1 and/or sepsis or a non-infectious disease are recruited from Emergency Departments and hospital wards of seven Dutch and Israeli medical centres. A panel of three experienced physicians adjudicate a reference standard diagnosis for all patients (i.e., bacterial or viral infection) using all available clinical and laboratory information, including a 28-day follow-up assessment. Nasal swabs and blood samples are collected for multi-omics investigations including host RNA and protein biomarkers, nasal microbiota profiling, host genomic profiling and bacterial proteomics. Simplified data is entered into a custom-built database in order to develop a multi-parametric model and diagnostic tools for differentiating between bacterial and viral infections. The predictions from the model will be compared with the consensus diagnosis in order to determine its accuracy. Discussion: The TAILORED-Treatment study will provide new insights into the interplay between the host and microorganisms. New host- or pathogen-related biomarkers will be used to generate a multi-parametric model for distinguishing between bacterial and viral infections. This model will be helpful to better guide antimicrobial therapy for patients with LRTI and sepsis. This study has the potential to improve patient care, reduce unnecessary antibiotic prescribing and will contribute positively to institutional, national and international healthcare economics.
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