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Am J Hum Genet. 2019 Apr 4;104(4):749-757. doi: 10.1016/j.ajhg.2019.02.021. Epub 2019 Mar 21.

The Discovery of a LEMD2-Associated Nuclear Envelopathy with Early Progeroid Appearance Suggests Advanced Applications for AI-Driven Facial Phenotyping.

Author information

1
Faculty of Medicine, University of Cologne, Cologne, 50931, Germany; Institute of Human Genetics, University Hospital Cologne, Cologne, 50931, Germany.
2
Section of Clinical Genetics, Department of Medical Genetics, Oslo University Hospital, Oslo, 0424, Norway.
3
Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tuebingen, 72076, Germany.
4
Gregor Mendel Institute, Vienna, 1030, Austria.
5
Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Bonn, 53127, Germany.
6
Private contributor, Tel Aviv, 6523217, Israel.
7
Department of Medical Genetics, Telemark Hospital Trust, Skien, 3710, Norway.
8
Department of Paediatric Neurology and Developmental Medicine, University Children's Hospital Tuebingen, Tuebingen, 72076, Germany.
9
Department of Medical Genetics, Haukeland University Hospital, Bergen, 5021, Norway; Department of Clinical Science, University of Bergen, Bergen, 5021, Norway.
10
Department of Maxillofacial Radiology, Faculty of Dentistry, University of Oslo, Oslo, 0440, Norway; National Resource Centre for Oral Health in Rare Medical Conditions, Lovisenberg Diakonale Hospital, Oslo, 0440, Norway.
11
University of Cologne, Cologne Center for Genomics, Cologne, 50931, Germany.
12
Department of Clinical Science, University of Bergen, Bergen, 5021, Norway.
13
Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, 6525 GA, the Netherlands.
14
Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, 20246, Germany.
15
Rare Disease Unit, Pediatric Clinic, Medical and Surgical Science Department, S.Orsola-Malpighi Hospital, University of Bologna, Bologna, 40138, Italy.
16
Faculty of Medicine, University of Cologne, Cologne, 50931, Germany; Institute of Human Genetics, University Hospital Cologne, Cologne, 50931, Germany. Electronic address: christian.netzer@uk-koeln.de.

Abstract

Over a relatively short period of time, the clinical geneticist's "toolbox" has been expanded by machine-learning algorithms for image analysis, which can be applied to the task of syndrome identification on the basis of facial photographs, but these technologies harbor potential beyond the recognition of established phenotypes. Here, we comprehensively characterized two individuals with a hitherto unknown genetic disorder caused by the same de novo mutation in LEMD2 (c.1436C>T;p.Ser479Phe), the gene which encodes the nuclear envelope protein LEM domain-containing protein 2 (LEMD2). Despite different ages and ethnic backgrounds, both individuals share a progeria-like facial phenotype and a distinct combination of physical and neurologic anomalies, such as growth retardation; hypoplastic jaws crowded with multiple supernumerary, yet unerupted, teeth; and cerebellar intention tremor. Immunofluorescence analyses of patient fibroblasts revealed mutation-induced disturbance of nuclear architecture, recapitulating previously published data in LEMD2-deficient cell lines, and additional experiments suggested mislocalization of mutant LEMD2 protein within the nuclear lamina. Computational analysis of facial features with two different deep neural networks showed phenotypic proximity to other nuclear envelopathies. One of the algorithms, when trained to recognize syndromic similarity (rather than specific syndromes) in an unsupervised approach, clustered both individuals closely together, providing hypothesis-free hints for a common genetic etiology. We show that a recurrent de novo mutation in LEMD2 causes a nuclear envelopathy whose prognosis in adolescence is relatively good in comparison to that of classical Hutchinson-Gilford progeria syndrome, and we suggest that the application of artificial intelligence to the analysis of patient images can facilitate the discovery of new genetic disorders.

KEYWORDS:

LEM domain-containing protein 2”; “deep neuronal network” and “intra-syndromal similarity; “next-generation phenotyping”; “nuclear envelopathy”; “progeria-like”

PMID:
30905398
PMCID:
PMC6451726
[Available on 2019-10-04]
DOI:
10.1016/j.ajhg.2019.02.021

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