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The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world(1). Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, includingPIEZO1on varicose veins,COL6A1on corneal resistance,MEPEon bone density, andIQGAP2andGMPRon blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenicBRCA1andBRCA2variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community. <br /> Exome sequences from the first 49,960 participants in the UK Biobank highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.
Sensors composed of a porous silicon monolayer covered with a film of nanostructured gold layer, which provide two optical signal transduction methods, are fabricated and thoroughly characterized concerning their sensing performance. For this purpose, silicon substrates were electrochemically etched in order to obtain porous silicon monolayers, which were subsequently immersed in gold salt solution facilitating the formation of a porous gold nanoparticle layer on top of the porous silicon. The deposition process was monitored by reflectance spectroscopy, and the appearance of a dip in the interference pattern of the porous silicon layer was observed. This dip can be assigned to the absorption of light by the deposited gold nanostructures leading to localized surface plasmon resonance. The bulk sensitivity of these sensors was determined by recording reflectance spectra in media having different refractive indices and compared to sensors exclusively based on porous silicon or gold nanostructures. A thorough analysis of resulting shifts of the different optical signals in the reflectance spectra on the wavelength scale indicated that the optical response of the porous silicon sensor is not influenced by the presence of a gold nanostructure on top. Moreover, the adsorption of thiol-terminated polystyrene to the sensor surface was solely detected by changes in the position of the dip in the reflectance spectrum, which is assigned to localized surface plasmon resonance in the gold nanostructures. The interference pattern resulting from the porous silicon layer is not shifted to longer wavelengths by the adsorption indicating the independence of the optical response of the two nanostructures, namely porous silicon and nanostructured gold layer, to refractive index changes and pointing to the successful realization of two sensors in one spot.
Surface-enhanced Raman scattering (SERS) is an effective and widely used technique to study chemical reactions induced or catalyzed by plasmonic substrates, since the experimental setup allows us to trigger and track the reaction simultaneously and identify the products. However, on substrates with plasmonic hotspots, the total signal mainly originates from these nanoscopic volumes with high reactivity and the information about the overall consumption remains obscure in SERS measurements. This has important implications; for example, the apparent reaction order in SERS measurements does not correlate with the real reaction order, whereas the apparent reaction rates are proportional to the real reaction rates as demonstrated by finite-difference time-domain (FDTD) simulations. We determined the electric field enhancement distribution of a gold nanoparticle (AuNP) monolayer and calculated the SERS intensities in light-driven reactions in an adsorbed self-assembled molecular monolayer on the AuNP surface. Accordingly, even if a high conversion is observed in SERS due to the high reactivity in the hotspots, most of the adsorbed molecules on the AuNP surface remain unreacted. The theoretical findings are compared with the hot-electron-induced dehalogenation of 4-bromothiophenol, indicating a time dependency of the hot-carrier concentration in plasmon-mediated reactions. To fit the kinetics of plasmon-mediated reactions in plasmonic hotspots, fractal-like kinetics are well suited to account for the inhomogeneity of reactive sites on the substrates, whereas also modified standard kinetics model allows equally well fits. The outcomes of this study are on the one hand essential to derive a mechanistic understanding of reactions on plasmonic substrates by SERS measurements and on the other hand to drive plasmonic reactions with high local precision and facilitate the engineering of chemistry on a nanoscale.
transferGWAS
(2022)
Motivation:
Medical images can provide rich information about diseases and their biology. However, investigating their association with genetic variation requires non-standard methods. We propose transferGWAS, a novel approach to perform genome-wide association studies directly on full medical images. First, we learn semantically meaningful representations of the images based on a transfer learning task, during which a deep neural network is trained on independent but similar data. Then, we perform genetic association tests with these representations.
Results:
We validate the type I error rates and power of transferGWAS in simulation studies of synthetic images. Then we apply transferGWAS in a genome-wide association study of retinal fundus images from the UK Biobank. This first-of-a-kind GWAS of full imaging data yielded 60 genomic regions associated with retinal fundus images, of which 7 are novel candidate loci for eye-related traits and diseases.
Purpose
Due to the increasing application of genome analysis and interpretation in medical disciplines, professionals require adequate education. Here, we present the implementation of personal genotyping as an educational tool in two genomics courses targeting Digital Health students at the Hasso Plattner Institute (HPI) and medical students at the Technical University of Munich (TUM).
Methods
We compared and evaluated the courses and the students ' perceptions on the course setup using questionnaires.
Results
During the course, students changed their attitudes towards genotyping (HPI: 79% [15 of 19], TUM: 47% [25 of 53]). Predominantly, students became more critical of personal genotyping (HPI: 73% [11 of 15], TUM: 72% [18 of 25]) and most students stated that genetic analyses should not be allowed without genetic counseling (HPI: 79% [15 of 19], TUM: 70% [37 of 53]). Students found the personal genotyping component useful (HPI: 89% [17 of 19], TUM: 92% [49 of 53]) and recommended its inclusion in future courses (HPI: 95% [18 of 19], TUM: 98% [52 of 53]).
Conclusion
Students perceived the personal genotyping component as valuable in the described genomics courses. The implementation described here can serve as an example for future courses in Europe.