Characterization of a preclinical PET insert in a 7 tesla MRI scanner: beyond NEMA testing

[EN] This study evaluates the performance of the Bruker positron emission tomograph (PET) insert combined with a BioSpec 70/30 USR magnetic resonance imaging (MRI) scanner using the manufacturer acceptance protocol and the NEMA NU 4-2008 for small animal PET. The PET insert is made of 3 rings of 8 monolithic LYSO crystals (50 x 50 x 10 mm(3)) coupled to silicon photomultipliers (SiPM) arrays, conferring an axial and transaxial FOV of 15 cm and 8 cm. The MRI performance was evaluated with and without the insert for the following radiofrequency noise, magnetic field homogeneity and image quality. For the PET performance, we extended the NEMA protocol featuring system sensitivity, count rates, spatial resolution and image quality to homogeneity and accuracy for quantification using several MRI sequences (RARE, FLASH, EPI and UTE). The PET insert does not show any adverse effect on the MRI performances. The MR field homogeneity is well preserved (Diameter Spherical Volume, for 20 mm of 1.98 +/- 4.78 without and -0.96 +/- 5.16 Hz with the PET insert). The PET insert has no major effect on the radiofrequency field. The signal-to-noise ratio measurements also do not show major differences. Image ghosting is well within the manufacturer specifications (<2.5%) and no RF noise is visible. Maximum sensitivity of the PET insert is 11.0% at the center of the FOV even with simultaneous acquisition of EPI and RARE. PET MLEM resolution is 0.87 mm (FWHM) at 5 mm off-center of the FOV and 0.97 mm at 25 mm radial offset. The peaks for true/noise equivalent count rates are 410/240 and 628/486 kcps for the rat and mouse phantoms, and are reached at 30.34/22.85 and 27.94/22.58 MBq. PET image quality is minimally altered by the different MRI sequences. The Bruker PET insert shows no adverse effect on the MRI performance and demonstrated a high sensitivity, sub-millimeter resolution and good image quality even during simultaneous MRI acquisition.We acknowledge the KU Leuven core facility, Molecular Small Animal Imaging Center (MoSAIC), for their support with obtaining scientific data presented in this paper. This work was supported by Stichting tegen Kanker (2015-145, Christophe M. Deroose) and Hercules foundation (AKUL/13/029, Uwe Himmelreich) for the purchase of the PET and MRI equipment respectively. The work was supported by the following funding organizations: European Commission for the PANA project (H2020-NMP-2015-two-stage, grant 686009) and the European ERA-NET project 'CryptoView' (3rd call of the FP7 program Infect-ERA).Gsell, W.; Molinos, C.; Correcher, C.; Belderbos, S.; Wouters, J.; Junge, S.; Heidenreich, M.... (2020). Characterization of a preclinical PET insert in a 7 tesla MRI scanner: beyond NEMA testing. Physics in Medicine and Biology. 65(24):1-16. https://doi.org/10.1088/1361-6560/aba08cS1166524Balezeau, F., Eliat, P.-A., Cayamo, A. B., & Saint-Jalmes, H. (2011). Mapping of low flip angles in magnetic resonance. Physics in Medicine and Biology, 56(20), 6635-6647. doi:10.1088/0031-9155/56/20/008Benlloch, J. M., González, A. J., Pani, R., Preziosi, E., Jackson, C., Murphy, J., … Schwaiger, M. (2018). The MINDVIEW project: First results. European Psychiatry, 50, 21-27. doi:10.1016/j.eurpsy.2018.01.002Cal-Gonzalez, J., Rausch, I., Shiyam Sundar, L. K., Lassen, M. L., Muzik, O., Moser, E., … Beyer, T. (2018). Hybrid Imaging: Instrumentation and Data Processing. Frontiers in Physics, 6. doi:10.3389/fphy.2018.00047Clark, D. P., & Badea, C. T. (2014). Micro-CT of rodents: State-of-the-art and future perspectives. Physica Medica, 30(6), 619-634. doi:10.1016/j.ejmp.2014.05.011Drzezga, A., Souvatzoglou, M., Eiber, M., Beer, A. J., Fürst, S., Martinez-Möller, A., … Schwaiger, M. (2012). First Clinical Experience with Integrated Whole-Body PET/MR: Comparison to PET/CT in Patients with Oncologic Diagnoses. Journal of Nuclear Medicine, 53(6), 845-855. doi:10.2967/jnumed.111.098608Gonzalez, A. J., Aguilar, A., Conde, P., Hernandez, L., Moliner, L., Vidal, L. F., … Benlloch, J. M. (2016). A PET Design Based on SiPM and Monolithic LYSO Crystals: Performance Evaluation. IEEE Transactions on Nuclear Science, 63(5), 2471-2477. doi:10.1109/tns.2016.2522179Gonzalez, A. J., Pincay, E. J., Canizares, G., Lamprou, E., Sanchez, S., Catret, J. V., … Correcher, C. (2019). Initial Results of the MINDView PET Insert Inside the 3T mMR. IEEE Transactions on Radiation and Plasma Medical Sciences, 3(3), 343-351. doi:10.1109/trpms.2018.2866899Grant, A. M., Lee, B. J., Chang, C.-M., & Levin, C. S. (2017). Simultaneous PET/MR imaging with a radio frequency-penetrable PET insert. Medical Physics, 44(1), 112-120. doi:10.1002/mp.12031Habte, F., Ren, G., Doyle, T. C., Liu, H., Cheng, Z., & Paik, D. S. (2013). Impact of a Multiple Mice Holder on Quantitation of High-Throughput MicroPET Imaging With and Without Ct Attenuation Correction. Molecular Imaging and Biology, 15(5), 569-575. doi:10.1007/s11307-012-0602-yHammer, B. E., Christensen, N. L., & Heil, B. G. (1994). Use of a magnetic field to increase the spatial resolution of positron emission tomography. Medical Physics, 21(12), 1917-1920. doi:10.1118/1.597178Jadvar, H., & Colletti, P. M. (2014). Competitive advantage of PET/MRI. European Journal of Radiology, 83(1), 84-94. doi:10.1016/j.ejrad.2013.05.028Judenhofer, M. S., Catana, C., Swann, B. K., Siegel, S. B., Jung, W.-I., Nutt, R. E., … Pichler, B. J. (2007). PET/MR Images Acquired with a Compact MR-compatible PET Detector in a 7-T Magnet. Radiology, 244(3), 807-814. doi:10.1148/radiol.2443061756Kinahan, P. E., Townsend, D. W., Beyer, T., & Sashin, D. (1998). Attenuation correction for a combined 3D PET/CT scanner. Medical Physics, 25(10), 2046-2053. doi:10.1118/1.598392Ko, G. B., Yoon, H. S., Kim, K. Y., Lee, M. S., Yang, B. Y., Jeong, J. M., … Lee, J. S. (2016). Simultaneous Multiparametric PET/MRI with Silicon Photomultiplier PET and Ultra-High-Field MRI for Small-Animal Imaging. Journal of Nuclear Medicine, 57(8), 1309-1315. doi:10.2967/jnumed.115.170019Lee, B. J., Grant, A. M., Chang, C.-M., Watkins, R. D., Glover, G. H., & Levin, C. S. (2018). MR Performance in the Presence of a Radio Frequency-Penetrable Positron Emission Tomography (PET) Insert for Simultaneous PET/MRI. IEEE Transactions on Medical Imaging, 37(9), 2060-2069. doi:10.1109/tmi.2018.2815620Loening, A. M., & Gambhir, S. S. (2003). AMIDE: A Free Software Tool for Multimodality Medical Image Analysis. Molecular Imaging, 2(3), 131-137. doi:10.1162/153535003322556877Mannheim, J. G., Schmid, A. M., Schwenck, J., Katiyar, P., Herfert, K., Pichler, B. J., & Disselhorst, J. A. (2018). PET/MRI Hybrid Systems. Seminars in Nuclear Medicine, 48(4), 332-347. doi:10.1053/j.semnuclmed.2018.02.011Maramraju, S. H., Smith, S. D., Junnarkar, S. S., Schulz, D., Stoll, S., Ravindranath, B., … Schlyer, D. J. (2011). Small animal simultaneous PET/MRI: initial experiences in a 9.4 T microMRI. Physics in Medicine and Biology, 56(8), 2459-2480. doi:10.1088/0031-9155/56/8/009Molinos, C., Sasser, T., Salmon, P., Gsell, W., Viertl, D., Massey, J. C., … Heidenreich, M. (2019). Low-Dose Imaging in a New Preclinical Total-Body PET/CT Scanner. Frontiers in Medicine, 6. doi:10.3389/fmed.2019.00088Nagy, K., Tóth, M., Major, P., Patay, G., Egri, G., Häggkvist, J., … Gulyás, B. (2013). Performance Evaluation of the Small-Animal nanoScan PET/MRI System. Journal of Nuclear Medicine, 54(10), 1825-1832. doi:10.2967/jnumed.112.119065Nanni, C., & Torigian, D. A. (2008). Applications of Small Animal Imaging with PET, PET/CT, and PET/MR Imaging. PET Clinics, 3(3), 243-250. doi:10.1016/j.cpet.2009.01.002Omidvari, N., Cabello, J., Topping, G., Schneider, F. R., Paul, S., Schwaiger, M., & Ziegler, S. I. (2017). PET performance evaluation of MADPET4: a small animal PET insert for a 7 T MRI scanner. Physics in Medicine & Biology, 62(22), 8671-8692. doi:10.1088/1361-6560/aa910dOmidvari, N., Topping, G., Cabello, J., Paul, S., Schwaiger, M., & Ziegler, S. I. (2018). MR-compatibility assessment of MADPET4: a study of interferences between an SiPM-based PET insert and a 7 T MRI system. Physics in Medicine & Biology, 63(9), 095002. doi:10.1088/1361-6560/aab9d1Raylman, R. R., Majewski, S., Lemieux, S. K., Velan, S. S., Kross, B., Popov, V., … Marano, G. D. (2006). Simultaneous MRI and PET imaging of a rat brain. Physics in Medicine and Biology, 51(24), 6371-6379. doi:10.1088/0031-9155/51/24/006Roncali, E., & Cherry, S. R. (2011). Application of Silicon Photomultipliers to Positron Emission Tomography. Annals of Biomedical Engineering, 39(4), 1358-1377. doi:10.1007/s10439-011-0266-9Schug, D., Lerche, C., Weissler, B., Gebhardt, P., Goldschmidt, B., Wehner, J., … Schulz, V. (2016). Initial PET performance evaluation of a preclinical insert for PET/MRI with digital SiPM technology. Physics in Medicine and Biology, 61(7), 2851-2878. doi:10.1088/0031-9155/61/7/2851Shao, Y., Cherry, S. R., Farahani, K., Meadors, K., Siegel, S., Silverman, R. W., & Marsden, P. K. (1997). Simultaneous PET and MR imaging. Physics in Medicine and Biology, 42(10), 1965-1970. doi:10.1088/0031-9155/42/10/010Steinert, H. C., & von Schulthess, G. K. (2002). Initial clinical experience using a new integrated in-line PET/CT system. The British Journal of Radiology, 75(suppl_9), S36-S38. doi:10.1259/bjr.75.suppl_9.750036Stortz, G., Thiessen, J. D., Bishop, D., Khan, M. S., Kozlowski, P., Retière, F., … Sossi, V. (2017). Performance of a PET Insert for High-Resolution Small-Animal PET/MRI at 7 Tesla. Journal of Nuclear Medicine, 59(3), 536-542. doi:10.2967/jnumed.116.187666Townsend, D. W. (2008). Combined Positron Emission Tomography–Computed Tomography: The Historical Perspective. Seminars in Ultrasound, CT and MRI, 29(4), 232-235. doi:10.1053/j.sult.2008.05.006Vandenberghe, S., & Marsden, P. K. (2015). PET-MRI: a review of challenges and solutions in the development of integrated multimodality imaging. Physics in Medicine and Biology, 60(4), R115-R154. doi:10.1088/0031-9155/60/4/r115Vaquero, J. J., & Kinahan, P. (2015). Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems. Annual Review of Biomedical Engineering, 17(1), 385-414. doi:10.1146/annurev-bioeng-071114-040723Von Schulthess, G. K., & Schlemmer, H.-P. W. (2008). A look ahead: PET/MR versus PET/CT. European Journal of Nuclear Medicine and Molecular Imaging, 36(S1), 3-9. doi:10.1007/s00259-008-0940-9Wehner, J., Weissler, B., Dueppenbecker, P. M., Gebhardt, P., Goldschmidt, B., Schug, D., … Schulz, V. (2015). MR-compatibility assessment of the first preclinical PET-MRI insert equipped with digital silicon photomultipliers. Physics in Medicine and Biology, 60(6), 2231-2255. doi:10.1088/0031-9155/60/6/2231Wehrl, H. F., Judenhofer, M. S., Thielscher, A., Martirosian, P., Schick, F., & Pichler, B. J. (2010). Assessment of MR compatibility of a PET insert developed for simultaneous multiparametric PET/MR imaging on an animal system operating at 7 T. Magnetic Resonance in Medicine, 65(1), 269-279. doi:10.1002/mrm.22591Yamamoto, S., Imaizumi, M., Kanai, Y., Tatsumi, M., Aoki, M., Sugiyama, E., … Hatazawa, J. (2010). Design and performance from an integrated PET/MRI system for small animals. Annals of Nuclear Medicine, 24(2), 89-98. doi:10.1007/s12149-009-0333-6Yamamoto, S., Watabe, T., Watabe, H., Aoki, M., Sugiyama, E., Imaizumi, M., … Hatazawa, J. (2011). Simultaneous imaging using Si-PM-based PET and MRI for development of an integrated PET/MRI system. Physics in Medicine and Biology, 57(2), N1-N13. doi:10.1088/0031-9155/57/2/n1Zaidi, H., Montandon, M.-L., & Alavi, A. (2008). The Clinical Role of Fusion Imaging Using PET, CT, and MR Imaging. PET Clinics, 3(3), 275-291. doi:10.1016/j.cpet.2009.03.00

Phylogenetic relationships and evolutionary history of the southern hemisphere genus Leptinella Cass. (Compositae, Anthemideae)

The genus Leptinella Cass. (Compositae, Anthemideae) is widely distributed in the southern hemisphere (Australia, Chatham Islands, New Guinea, New Zealand, South America, sub-Antarctic Islands). Leptinella comprises 42 taxa and consists of small perennial and predominantly procumbent herbs. The genus is characterised by a remarkable variety in sex expression: there are populations with monoecious, paradioecious, and dioecious plants. Additionally, Leptinella forms an impressive polyploid complex with chromosome numbers ranging from tetraploid to a chromosome set of 2n = 24x. In the present thesis, different molecular methods are used to reconstruct the phylogenies of the genus Leptinella and related genera. The obtained molecular phylogenies are then used to a) investigate the intergeneric and infrageneric relationships of Leptinella, b) elucidate the origin, the biogeography and the divergence time of the genus, and c) reconstruct the evolution of polyploidy and sex expression in Leptinella. Chapter 2 deals with the intergeneric relationships of Leptinella. One region from the nuclear (ITS) and the chloroplast genome (ndhF) were chosen for amplification and sequencing to reconstruct the molecular phylogeny of the southern hemisphere members of the tribe Anthemideae. The analyses show that the subtribes sensu Bremer and Humphries (1993) are polyphyletic. As a consequence of the non-monophyletic nature of these subtribes, an alternative generic grouping of the southern hemisphere Anthemideae is discussed (Osmitopsis, Cotula-group, Athanasia-grade, Pentzia-clade). The study shows that the genus Leptinella is a member of the basal Cotula-group which also contains seven southern African genera, the South American genus Soliva, and the widespread southern hemisphere genus Cotula. Chapter 3 and 4 deal with the infrageneric phylogeny of the genus Leptinella. For this purpose two different methods were used: DNA sequencing and AFLP fingerprinting. Both methods are suitable for the determination of taxon groups within Leptinella, but failed to resolve the relationships of single taxa. The extensive hybridization and polyploidization in combination with low genetic variation due the young age of Leptinella may be the main points to explain the observed patterns. In chapter 3, three different markers from the nuclear (ITS) and from the chloroplast genome (psbA-trnH, trnC-petN) were sequenced for Leptinella and other members of the Cotula-group. The analyses show that Leptinella is not monophyletic and the genus is nested within Cotula. However, Leptinella and Cotula alpina form a moderate support monophyletic clade in the combined dataset. In the cpDNA and nrDNA dataset this group is not monophyletic. The division of Leptinella into three subgenera according to Lloyd (1972c) is only partly supported by the molecular data. The genus Leptinella is split in two well supported groups: The filicula-group contains taxa from New Guinea and one taxon from Australia. The remaining taxa of Leptinella from New Zealand, South America, the Chatham Islands, the sub-Antarctic islands, and three further taxa from Australia belong to the Leptinella main clade. The latter group is divided into six further groups (dioica-, longipes-, minor-, plumosa-, pectinata-, pyrethrifolia-group). Within these groups most taxa are not monophyletic. The study shows that Leptinella has radiated in the Miocene to Pleistocene. The estimated divergence time for Leptinella is much younger as the supposed break-up of the Gondwana continent. Therefore, the current distribution of Leptinella could be explained only by long distance dispersal events. In chapter 4, AFLP fingerprinting was used to study the phylogeny of the Leptinella main group. The AFLP analysis resulted in three main groups (taxon group A-C) and several subgroups. These groups are partly congruent with the results of the sequencing analysis presented in chapter 3. The results indicate different evolutionary histories of group A and C. Taxon group C is characterised by extensive hybridization and polyploidization, whereas both processes are less frequent in taxon group A. Furthermore, new ploidy level estimations for Leptinella are provided this chapter. Chapter 5 focuses on the evolution of dimorphic sex expression and polyploidy in Leptinella. For this purpose, sex expression and ploidy levels are mapped on the phylogenetic tree of chapter 3. The study shows that monoecy is the ancestral sex expression in Leptinella and dimorphic sex expression (dioecy, paradioecy) has evolved independently at least four times from monoecy. Additionally, a weak correlation was found between dimorphic sex expression and polyploidy. However, neither of two diametrical hypotheses about the correlation of dioecy and polyploidy by Westergaard (1958; break down of dimorphic sex expression through polyploidization) and Miller and Venable (2000; polyploidy as a trigger of the evolution of dioecy) was able to explain the observed patterns in Leptinella

A new subtribal classification of the tribe Anthemideae (Compositae)

A new subtribal classification of the Compositae-Anthemideae is presented based on phylogenetic reconstructions for sequence information of the internal transcribed spacer (ITS) region of the nuclear ribosomal DNA (nrDNA) for 103 of the 111 accepted genera of the tribe. Results of the present analyses are compared with results from phylogenetic analyses based on cpDNA ndhF sequence variation and discussed in conjunction with morphological, anatomical, cytological, embryological and phytochemical evidence. As a result, 14 subtribes are circumscribed and described in detail, with information provided concerning the generic members and the geographical distribution of these entities. Four subtribes (i.e. Osmitopsidinae, Phymasperminae, Pentziinae and Leucanthemopsidinae) are described as new to science, for a further subtribe a new name (Glebionidinae, replacing the illegitimate Chrysantheminae) is validated

Characterization of preclinical PET insert for 7T: beyond NEMA testing.

status: publishe

Spectrum of DDC variants causing aromatic l-amino acid decarboxylase (AADC) deficiency and pathogenicity interpretation using ACMG-AMP/ACGS recommendations

Pathogenic variants in dopa decarboxylase (DDC), the gene encoding the aromatic l-amino acid decarboxylase (AADC) enzyme, lead to a severe deficiency of neurotransmitters, resulting in neurological, neuromuscular, and behavioral manifestations clinically characterized by developmental delays, oculogyric crises, dystonia, and severe neurologic dysfunction in infancy. Historically, therapy has been aimed at compensating for neurotransmitter abnormalities, but response to pharmacologic therapy varies, and in most cases, the therapy shows little or no benefit. A novel human DDC gene therapy was recently approved in the European Union that targets the underlying genetic cause of the disorder, providing a new treatment option for patients with AADC deficiency. However, the applicability of human DDC gene therapy depends on the ability of laboratories and clinicians to interpret the results of genetic testing accurately enough to diagnose the patient. An accurate interpretation of genetic variants depends in turn on expert-guided curation of locus-specific databases. The purpose of this research was to identify previously uncharacterized DDC variants that are of pathologic significance in AADC deficiency as well as characterize and curate variants of unknown significance (VUSs) to further advance the diagnostic accuracy of genetic testing for this condition. DDC variants were identified using existing databases and the literature. The pathogenicity of the variants was classified using modified American College of Medical Genetics and Genomics/Association for Molecular Pathology/Association for Clinical Genomic Science (ACMG-AMP/ACGS) criteria. To improve the current variant interpretation recommendations, in silico variant interpretation tools were combined with structural 3D modeling of protein variants and applied comparative analysis to predict the impact of the variant on protein function. A total of 422 variants were identified (http://biopku.org/home/pnddb.asp). Variants were identified on nearly all introns and exons of the DDC gene, as well as the 3' and 5' untranslated regions. The largest percentage of the identified variants (48%) were classified as missense variants. The molecular effects of these missense variants were then predicted, and the pathogenicity of each was classified using a number of variant effect predictors. Using ACMG-AMP/ACGS criteria, 7% of variants were classified as pathogenic, 32% as likely pathogenic, 58% as VUSs of varying subclassifications, 1% as likely benign, and 1% as benign. For 101 out of 108 reported genotypes, at least one allele was classified as pathogenic or likely pathogenic. In silico variant pathogenicity interpretation tools, combined with structural 3D modeling of variant proteins and applied comparative analysis, have improved the current DDC variant interpretation recommendations, particularly of VUSs

Spectrum of DDC variants causing aromatic l-amino acid decarboxylase (AADC) deficiency and pathogenicity interpretation using ACMG-AMP/ACGS recommendations

Pathogenic variants in dopa decarboxylase (DDC), the gene encoding the aromatic l-amino acid decarboxylase (AADC) enzyme, lead to a severe deficiency of neurotransmitters, resulting in neurological, neuromuscular, and behavioral manifestations clinically characterized by developmental delays, oculogyric crises, dystonia, and severe neurologic dysfunction in infancy. Historically, therapy has been aimed at compensating for neurotransmitter abnormalities, but response to pharmacologic therapy varies, and in most cases, the therapy shows little or no benefit. A novel human DDC gene therapy was recently approved in the European Union that targets the underlying genetic cause of the disorder, providing a new treatment option for patients with AADC deficiency. However, the applicability of human DDC gene therapy depends on the ability of laboratories and clinicians to interpret the results of genetic testing accurately enough to diagnose the patient. An accurate interpretation of genetic variants depends in turn on expert-guided curation of locus-specific databases. The purpose of this research was to identify previously uncharacterized DDC variants that are of pathologic significance in AADC deficiency as well as characterize and curate variants of unknown significance (VUSs) to further advance the diagnostic accuracy of genetic testing for this condition. DDC variants were identified using existing databases and the literature. The pathogenicity of the variants was classified using modified American College of Medical Genetics and Genomics/Association for Molecular Pathology/Association for Clinical Genomic Science (ACMG-AMP/ACGS) criteria. To improve the current variant interpretation recommendations, in silico variant interpretation tools were combined with structural 3D modeling of protein variants and applied comparative analysis to predict the impact of the variant on protein function. A total of 422 variants were identified (http://biopku.org/home/pnddb.asp). Variants were identified on nearly all introns and exons of the DDC gene, as well as the 3' and 5' untranslated regions. The largest percentage of the identified variants (48%) were classified as missense variants. The molecular effects of these missense variants were then predicted, and the pathogenicity of each was classified using a number of variant effect predictors. Using ACMG-AMP/ACGS criteria, 7% of variants were classified as pathogenic, 32% as likely pathogenic, 58% as VUSs of varying subclassifications, 1% as likely benign, and 1% as benign. For 101 out of 108 reported genotypes, at least one allele was classified as pathogenic or likely pathogenic. In silico variant pathogenicity interpretation tools, combined with structural 3D modeling of variant proteins and applied comparative analysis, have improved the current DDC variant interpretation recommendations, particularly of VUSs

Allelic phenotype values: a model for genotype-based phenotype prediction in phenylketonuria

PURPOSE The nature of phenylalanine hydroxylase (PAH) variants determines residual enzyme activity, which modifies the clinical phenotype in phenylketonuria (PKU). We exploited the statistical power of a large genotype database to determine the relationship between genotype and phenotype in PKU. METHODS A total of 9336 PKU patients with 2589 different genotypes, carrying 588 variants, were investigated using an allelic phenotype value (APV) algorithm. RESULTS We identified 251 0-variants encoding inactive PAH, and assigned APVs (0 = classic PKU; 5 = mild PKU; 10 = mild hyperphenylalaninaemia) to 88 variants in PAH-functional hemizygous patients. The genotypic phenotype values (GPVs) were set equal to the higher-APV allele, which was assumed to be dominant over the lower-APV allele and to determine the metabolic phenotype. GPVs for 8872 patients resulted in cut-off ranges of 0.0-2.7 for classic PKU, 2.8-6.6 for mild PKU and 6.7-10.0 for mild hyperphenylalaninaemia. Genotype-based phenotype prediction was 99.2% for classic PKU, 46.2% for mild PKU and 89.5% for mild hyperphenylalaninaemia. The relationships between known pretreatment blood phenylalanine levels and GPVs (n = 4217), as well as tetrahydrobiopterin responsiveness and GPVs (n = 3488), were significant (both P < 0.001). CONCLUSIONS APV and GPV are powerful tools to investigate genotype-phenotype associations, and can be used for genetic counselling of PKU families

Significance of utilizing in silico structural analysis and phenotypic data to characterize phenylalanine hydroxylase variants: A PAH landscape

11 páginas, 5 figuras, 1 tabla.Phenylketonuria (PKU) is a genetic disorder caused by variations in the phenylalanine hydroxylase (PAH) gene. Among the 3369 reported PAH variants, 33.7% are missense alterations. Unfortunately, 30% of these missense variants are classified as variants of unknown significance (VUS), posing challenges for genetic risk assessment. In our study, we focused on analyzing 836 missense PAH variants following the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines specified by ClinGen PAH Variant Curation Expert Panel (VCEP) criteria. We utilized and compared variant annotator tools like Franklin and Varsome, conducted 3D structural analysis of PAH, and examined active and regulatory site hotspots. In addition, we assessed potential splicing effect of apparent missense variants. By evaluating phenotype data from 22962 PKU patients, our aim was to reassess the pathogenicity of missense variants. Our comprehensive approach successfully reclassified 309 VUSs out of 836 missense variants as likely pathogenic or pathogenic (37%), upgraded 370 likely pathogenic variants to pathogenic, and reclassified one previously considered likely benign variant as likely pathogenic. Phenotypic information was available for 636 missense variants, with 441 undergoing 3D structural analysis and active site hotspot identification for 180 variants. After our analysis, only 6% of missense variants were classified as VUSs, and three of them (c.23A>C/p.Asn8Thr, c.59_60delinsCC/p.Gln20Pro, and c.278A >T/p.Asn93Ile) may be influenced by abnormal splicing. Moreover, a pathogenic variant (c.168G>T/p.Glu56Asp) was identified to have a risk exceeding 98% for modifications of the consensus splice site, with high scores indicating a donor loss of 0.94. The integration of ACMG/AMP guidelines with in silico structural analysis and phenotypic data significantly reduced the number of missense VUSs, providing a strong basis for genetic counseling and emphasizing the importance of metabolic phenotype information in variant curation. This study also sheds light on the current landscape of PAH variants.This work was supported in part by the Nenad Blau Endowment Fund of the MCF, Marin County, CA, USA, by grant PID2021–128468NB-I00 f inanced by MCIN/AEI/10.13039/501100011033 and by a grant from Fundaci´ on Ram´ on Areces Ciencias de la Vida (XX National Call) to Santiago Ram´ on-Maiques, by the Deutsche Forschungsgemeinschaft FOR2509 and TH1461/7–2 to Nastassja Himmelreich, by the Instituto de Salud Carlos (ISCIII), European Regional Development Fund [PI22/ 00699] to Bel´ en Per´ ez, and La Fundaci´ o la Marat´ o de TV3 (Project 202012-31-32-33) and the Neuro-SysMed Center (The Research Council of Norway, Project No. 288164) to Aurora Martinez.Peer reviewe

MRI-based retrospective gating for PET reconstruction in rats: implementation and proof of principle study

status: publishe

MRI-based retrospective gating for PET reconstruction in rats: implementation and proof of principle study

status: publishe