Biology subjects

Krawitz, P. M.

Publications and source records attributed to Krawitz, P. M..

4 recordsLinked to original sources

bioRxiv2020

A CRISPR-Cas9-engineered mouse model for GPI anchor deficiency mirrors human phenotype and shows hippocampal synaptic dysfunctions.

Pathogenic germline mutations in PIGV lead to glycosylphosphatidylinositol biosynthesis deficiency (GPIBD). Individuals with pathogenic biallelic mutations in genes of the glycosylphosphatidylinositol (GPI) anchor pathway exhibit cognitive impairments, motor delay, and often epilepsy. Thus far, the pathophysiology underlying the disease remains unclear, and suitable rodent models that mirror all symptoms observed in human patients have not been available. Therefore, we used CRISPR-Cas9 to introduce the most prevalent hypomorphic missense mutation in European patients, Pigv:c.1022C>A (p.A341E), at a site that is conserved in mice. Mirroring the human pathology, mutant Pigv341E mice exhibited deficits in motor coordination, cognitive impairments, and alterations in sociability and sleep patterns, as well as increased seizure susceptibility. Furthermore, immunohistochemistry revealed reduced synaptophysin immunoreactivity in Pigv341E mice, and electrophysiology recordings showed decreased hippocampal synaptic transmission that could underlie impaired memory formation. In single-cell RNA sequencing, Pigv341E-hippocampal cells exhibited changes in gene expression, most prominently in a subtype of microglia and subicular neurons. A significant reduction in Abl1 transcript levels in several cell clusters suggested a link to the signaling pathway of GPI-anchored ephrins. We also observed elevated levels of Hdc transcripts, which might affect histamine metabolism with consequences for circadian rhythm. This new mouse model will not only open the doors to further investigation into the pathophysiology of GPIBD, but will also deepen our understanding of the role of GPI-anchor-related pathways in brain development. Significance statementInherited GPI-anchor biosynthesis deficiencies (IGDs) explain many cases of syndromic intellectual disability. Although diagnostic methods are improving, the pathophysiology underlying the disease remains unclear. Furthermore, we lack rodent models suitable for characterizing cognitive and social disabilities. To address this issue, we generated the first viable mouse model for an IGD that mirrors the condition in human patients with a behavioral phenotype and susceptibility to epilepsy. Using the new model, we obtained neurological insights such as deficits in synaptic transmission that will facilitate understanding of the pathophysiology of IGDs.

neuroscience↗

bioRxiv2019

Complement- and inflammasome-mediated autoinflammation-paroxysmal nocturnal hemoglobinuria

Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired hematopoietic stem cell disorder characterized by complement-mediated hemolysis and thrombosis, and bone marrow failure. Affected cells harbor somatic mutation in X-linked PIGA gene, essential for the initial step in glycosylphosphatidylinositol (GPI) biosynthesis. Loss of GPI biosynthesis results in defective cell-surface expression of GPI-anchored complement regulators CD59 and DAF. The affected stem cells generate many abnormal blood cells after clonal expansion, which occurs under bone marrow failure. Here, we report the mechanistic basis of a disease entity, autoinflammation-paroxysmal nocturnal hemoglobinuria (AIF-PNH), caused by germline mutation plus somatic loss of PIGT on chromosome 20q. A region containing maternally imprinted genes implicated in clonal expansion in 20q-myeloproliferative syndromes was lost together with normal PIGT from paternal chromosome 20. Taking these findings together with a lack of bone marrow failure, the mechanisms of clonal expansion in AIF-PNH appear to differ from those in PNH. AIF-PNH is characterized by intravascular hemolysis and recurrent autoinflammation, such as urticaria, arthralgia, fever and aseptic meningitis. Consistent with PIGTs essential role in synthesized GPIs attachment to precursor proteins, non-protein-linked free GPIs appeared on the surface of PIGT-defective cells. PIGT-defective THP-1 cells accumulated higher levels of C3 fragments and C5b-9 complexes, and secreted more IL-1{beta} than PIGA-defective cells after activation of the complement alternative pathway. IL-1{beta} secretion was dependent upon C5b-9 complexes, accounting for the effectiveness of the anti-C5 drug eculizumab for both intravascular hemolysis and autoinflammation. These results suggest that free GPIs enhance complement activation and inflammasome-mediated IL-1{beta} secretion.

immunology↗

bioRxiv2017

Advances in computer-assisted syndrome recognition and differentiation in a set of metabolic disorders

Significant improvements in automated image analysis have been achieved over the recent years and tools are now increasingly being used in computer-assisted syndromology. However, the recognizability of the facial gestalt might depend on the syndrome and may also be confounded by severity of phenotype, size of available training sets, ethnicity, age, and sex. Therefore, benchmarking and comparing the performance of deep-learned classification processes is inherently difficult.\n\nFor a systematic analysis of these influencing factors we chose the lysosomal storage diseases Mucolipidosis as well as Mucopolysaccharidosis type I and II, that are known for their wide and overlapping phenotypic spectra. For a dysmorphic comparison we used Smith-Lemli-Opitz syndrome as a metabolic disease and Nicolaides-Baraitser syndrome as another disorder that is also characterized by coarse facies. A classifier that was trained on these five cohorts, comprising 288 patients in total, achieved a mean accuracy of 62%.\n\nThe performance of automated image analysis is not only significantly higher than randomly expected but also better than in previous approaches. In part this might be explained by our large training sets. We therefore set up a simulation pipeline that is suited to analyze the effect of different potential confounders, such as cohort size, age, sex, or ethnic background on the recognizability of phenotypes. We found that the true positive rate increases for all analyzed disorders for growing cohorts (n=[10...40]) while ethnicity and sex have no significant influence.\n\nThe dynamics of the accuracies strongly suggest that the maximum recognizability is a phenotype-specific value, that hasnt been reached yet for any of the studied disorders. This should also be a motivation to further intensify data sharing efforts, as computer-assisted syndrome classification can still be improved by enlarging the available training sets.\n\nAvailability: software for classification: https://app.face2gene.com/research,

genetics↗

bioRxiv2017

Characterization of Glycosylphosphatidylinositol Biosynthesis Defects by Clinical Features, Flow Cytometry, and Automated Image Analysis

BackgroundGlycosylphosphatidylinositol 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.\n\nMethodsWe 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.\n\nResultsWe 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.\n\nConclusionsDue 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.

genetics↗