@article {769,
	title = {Delineation of a Human Mendelian Disorder of the DNA Demethylation Machinery: TET3 Deficiency.},
	journal = {Am J Hum Genet},
	volume = {106},
	year = {2020},
	month = {2020 02 06},
	pages = {234-245},
	abstract = {<p>Germline pathogenic variants in chromatin-modifying enzymes are a common cause of pediatric developmental disorders. These enzymes catalyze reactions that regulate epigenetic inheritance via histone post-translational modifications and DNA methylation. Cytosine methylation (5-methylcytosine [5mC]) of DNA is the quintessential epigenetic mark, yet no human Mendelian disorder of DNA demethylation has yet been delineated. Here, we describe in detail a Mendelian disorder caused by the disruption of DNA demethylation. TET3 is a methylcytosine dioxygenase that initiates DNA demethylation during early zygote formation, embryogenesis, and neuronal differentiation and is intolerant to haploinsufficiency in mice and humans. We identify and characterize 11 cases of human TET3 deficiency in eight families with the common phenotypic features of intellectual disability and/or global developmental delay; hypotonia; autistic traits; movement disorders; growth abnormalities; and facial dysmorphism. Mono-allelic frameshift and nonsense variants in TET3 occur throughout the coding region. Mono-allelic and bi-allelic missense variants localize to conserved residues; all but one such variant occur within the catalytic domain, and most display hypomorphic function in an assay of catalytic activity. TET3 deficiency and other Mendelian disorders of the epigenetic machinery show substantial phenotypic overlap, including features of intellectual disability and abnormal growth, underscoring shared disease mechanisms.</p>},
	keywords = {Adult, Amino Acid Sequence, Autistic Disorder, Child, Child, Preschool, Developmental Disabilities, Dioxygenases, DNA Demethylation, Embryonic Development, Female, Gene Expression Regulation, Developmental, Growth Disorders, Humans, Infant, Male, Middle Aged, Movement Disorders, Pedigree, Protein Conformation, Sequence Homology, Young Adult},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2019.12.007},
	author = {Beck, David B and Petracovici, Ana and He, Chongsheng and Moore, Hannah W and Louie, Raymond J and Ansar, Muhammad and Douzgou, Sofia and Sithambaram, Sivagamy and Cottrell, Trudie and Santos-Cortez, Regie Lyn P and Prijoles, Eloise J and Bend, Renee and Keren, Boris and Mignot, Cyril and Nougues, Marie-Christine and {\~O}unap, Katrin and Reimand, Tiia and Pajusalu, Sander and Zahid, Muhammad and Saqib, Muhammad Arif Nadeem and Buratti, Julien and Seaby, Eleanor G and McWalter, Kirsty and Telegrafi, Aida and Baldridge, Dustin and Shinawi, Marwan and Leal, Suzanne M and Schaefer, G Bradley and Stevenson, Roger E and Banka, Siddharth and Bonasio, Roberto and Fahrner, Jill A}
}
@article {722,
	title = {Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.},
	journal = {Front Genet},
	volume = {10},
	year = {2019},
	month = {2019},
	pages = {611},
	abstract = {<p>The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.</p>},
	issn = {1664-8021},
	doi = {10.3389/fgene.2019.00611},
	author = {Nellaker, Christoffer and Alkuraya, Fowzan S and Baynam, Gareth and Bernier, Raphael A and Bernier, Francois P J and Boulanger, Vanessa and Brudno, Michael and Brunner, Han G and Clayton-Smith, Jill and Cogn{\'e}, Benjamin and Dawkins, Hugh J S and deVries, Bert B A and Douzgou, Sofia and Dudding-Byth, Tracy and Eichler, Evan E and Ferlaino, Michael and Fieggen, Karen and Firth, Helen V and FitzPatrick, David R and Gration, Dylan and Groza, Tudor and Haendel, Melissa and Hallowell, Nina and Hamosh, Ada and Hehir-Kwa, Jayne and Hitz, Marc-Phillip and Hughes, Mark and Kini, Usha and Kleefstra, Tjitske and Kooy, R Frank and Krawitz, Peter and K{\"u}ry, S{\'e}bastien and Lees, Melissa and Lyon, Gholson J and Lyonnet, Stanislas and Marcadier, Julien L and Meyn, Stephen and Moslerov{\'a}, Veronika and Politei, Juan M and Poulton, Cathryn C and Raymond, F Lucy and Reijnders, Margot R F and Robinson, Peter N and Romano, Corrado and Rose, Catherine M and Sainsbury, David C G and Schofield, Lyn and Sutton, Vernon R and Turnovec, Marek and Van Dijck, Anke and Van Esch, Hilde and Wilkie, Andrew O M}
}
