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. 2018 Jan 9;10(1):3.
doi: 10.1186/s13073-017-0510-5.

Characterization of glycosylphosphatidylinositol biosynthesis defects by clinical features, flow cytometry, and automated image analysis

Alexej Knaus  1   2   3   4 , Jean Tori Pantel  1 , Manuela Pendziwiat  5 , Nurulhuda Hajjir  1 , Max Zhao  1 , Tzung-Chien Hsieh  1   4 , Max Schubach  1   6 , Yaron Gurovich  7 , Nicole Fleischer  7 , Marten Jäger  1   6 , Sebastian Köhler  1 , Hiltrud Muhle  5 , Christian Korff  8 , Rikke S Møller  9   10 , Allan Bayat  11 , Patrick Calvas  12 , Nicolas Chassaing  12 , Hannah Warren  13 , Steven Skinner  13 , Raymond Louie  13 , Christina Evers  14 , Marc Bohn  15 , Hans-Jürgen Christen  16 , Myrthe van den Born  17 , Ewa Obersztyn  18 , Agnieszka Charzewska  18 , Milda Endziniene  19 , Fanny Kortüm  20 , Natasha Brown  21   22 , Peter N Robinson  23 , Helenius J Schelhaas  24 , Yvonne Weber  25 , Ingo Helbig  4   26 , Stefan Mundlos  1   2 , Denise Horn  27 , Peter M Krawitz  28   29   30
Affiliations

Characterization of glycosylphosphatidylinositol biosynthesis defects by clinical features, flow cytometry, and automated image analysis

Alexej Knaus et al. Genome Med. .

Abstract

Background: Glycosylphosphatidylinositol biosynthesis defects (GPIBDs) cause a group of phenotypically overlapping recessive syndromes with intellectual disability, for which pathogenic mutations have been described in 16 genes of the corresponding molecular pathway. An elevated serum activity of alkaline phosphatase (AP), a GPI-linked enzyme, has been used to assign GPIBDs to the phenotypic series of hyperphosphatasia with mental retardation syndrome (HPMRS) and to distinguish them from another subset of GPIBDs, termed multiple congenital anomalies hypotonia seizures syndrome (MCAHS). However, the increasing number of individuals with a GPIBD shows that hyperphosphatasia is a variable feature that is not ideal for a clinical classification.

Methods: We studied the discriminatory power of multiple GPI-linked substrates that were assessed by flow cytometry in blood cells and fibroblasts of 39 and 14 individuals with a GPIBD, respectively. On the phenotypic level, we evaluated the frequency of occurrence of clinical symptoms and analyzed the performance of computer-assisted image analysis of the facial gestalt in 91 individuals.

Results: We found that certain malformations such as Morbus Hirschsprung and diaphragmatic defects are more likely to be associated with particular gene defects (PIGV, PGAP3, PIGN). However, especially at the severe end of the clinical spectrum of HPMRS, there is a high phenotypic overlap with MCAHS. Elevation of AP has also been documented in some of the individuals with MCAHS, namely those with PIGA mutations. Although the impairment of GPI-linked substrates is supposed to play the key role in the pathophysiology of GPIBDs, we could not observe gene-specific profiles for flow cytometric markers or a correlation between their cell surface levels and the severity of the phenotype. In contrast, it was facial recognition software that achieved the highest accuracy in predicting the disease-causing gene in a GPIBD.

Conclusions: Due to the overlapping clinical spectrum of both HPMRS and MCAHS in the majority of affected individuals, the elevation of AP and the reduced surface levels of GPI-linked markers in both groups, a common classification as GPIBDs is recommended. The effectiveness of computer-assisted gestalt analysis for the correct gene inference in a GPIBD and probably beyond is remarkable and illustrates how the information contained in human faces is pivotal in the delineation of genetic entities.

Keywords: Anchor biosynthesis defects; Automated image analysis; GPI; Gene; Prediction.

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Conflict of interest statement

Consent for publication

Written informed consent was obtained before enrolment from the responsible persons (parents) on behalf of all study participants to publish their photographs as well as their clinical data for scientific purposes.

Competing interests

PMK is a member of the scientific advisory board of FDNA, the company providing the Face2Gene platform. YG and NF are employees of FNDA. The remaining authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Flow cytometric profiling for GPIBDs. Cell surface levels of FLAER and tissue-specific GPI-anchored proteins were assessed on fibroblasts (a) as well as on granulocytes (b) of individuals affected by GPIBDs. The relative expression was grouped for GPIBDs of the same phenotypic series, MCAHS (PIGA, PIGN, PIGT) and HPMRS (PGAP3, PIGV, PIGO, PIGW), but showed no significant differences (significance was tested with Wilcoxon-Mann-Whitney test; the p value was corrected for sample size (Bonferoni))
Fig. 2
Fig. 2
Automated image analysis for five of the most prevalent GPIBDs. A model for the classification of the gene–phenotypes was repeatedly trained and cross-validated on patient subsets that were randomly down-sampled to the same cohort size of n = 10. A mean accuracy of 0.44 was achieved, which is significantly better than random (0.20). For explanatory purposes, the rows of the confusion matrix start with instances of previously published or newly identified individuals with GPIBDs. If the predicted gene matches the molecularly confirmed diagnosis, such a test case would contribute to the true positive rate, shown on the diagonal. Actual affected individual photographs were used to generate an averaged and de-identified composite photo and are shown at the top of the columns. The performance of computer-assisted image classification is significantly better than expected under the null model of perfect heterogeneity and indicates a gene-specific phenotypic substructure for the molecular pathway disease. Higher false positive error rates occur between genes of the same phenotypic series, HPMRS and MCAHS, as indicated by the dendrogram
See this image and copyright information in PMC

References

    1. Kinoshita T, Fujita M, Maeda Y. Biosynthesis, remodelling and functions of mammalian GPI-anchored proteins: recent progress. J Biochem. 2008;144(3):287–94. doi: 10.1093/jb/mvn090. - DOI - PubMed
    1. Murakami Y, Kanzawa N, Saito K, Krawitz PM, Mundlos S, Robinson PN, Karadimitris A, Maeda Y, Kinoshita T. Mechanism for release of alkaline phosphatase caused by glycosylphosphatidylinositol deficiency in patients with hyperphosphatasia-mental retardation syndrome. J Biol Chem. 2012;287(9):6318-6325. - PMC - PubMed
    1. Chiyonobu T, Inoue N, Morimoto M, Kinoshita T, Murakami Y. Glycosylphosphatidylinositol (GPI) anchor deficiency caused by mutations in PIGW is associated with West syndrome and hyperphosphatasia with mental retardation syndrome. J Med Genet. 2014;51(3):203–7. doi: 10.1136/jmedgenet-2013-102156. - DOI - PubMed
    1. Hansen L, Tawamie H, Murakami Y, Mang Y, ur Rehman S, Buchert R, Schaffer S, Muhammad S, Bak M, Nothen MM, et al. Hypomorphic mutations in PGAP2, encoding a GPI-anchor-remodeling protein, cause autosomal-recessive intellectual disability. Am J Hum Genet. 2013;92(4):575–83. doi: 10.1016/j.ajhg.2013.03.008. - DOI - PMC - PubMed
    1. Howard MF, Murakami Y, Pagnamenta AT, Daumer-Haas C, Fischer B, Hecht J, Keays DA, Knight SJ, Kolsch U, Kruger U, et al. Mutations in PGAP3 impair GPI-anchor maturation, causing a subtype of hyperphosphatasia with mental retardation. Am J Hum Genet. 2014;94(2):278-287. - PMC - PubMed

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