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AbstractIntroduction. We report a very rare case of familial breast cancer and diffuse gastric cancer, with germline pathogenic variants in both BRCA1 and CDH1 genes. To the best of our knowledge, this is the first report of such an association.Family description. The proband is a woman diagnosed with breast cancer at the age of 52 years.

She requested genetic counselling in 2012, at the age of 91 years, because of a history of breast cancer in her daughter, her sister, her niece and her paternal grandmother and was therefore concerned about her relatives. Her sister and maternal aunt also had gastric cancer. She was tested for several genes associated with hereditary breast cancer.Results. A large deletion of BRCA1 from exons 1 to 7 and two CDH1 pathogenic cis variants were identified.Conclusion.

This complex situation is challenging for genetic counselling and management of at-risk individuals.cancer. Breastcancer. Gastricclinical geneticsgenetic screening/counsellingmolecular geneticsIntroductionGLI-Kruppel family member 3 (GLI3) encodes for a zinc finger transcription factor which plays a key role in the sonic hedgehog (SHH) signalling pathway essential in both limb and craniofacial development.1 2 In hand development, SHH is expressed in the zone of polarising activity (ZPA) on the posterior side of the handplate. The ZPA expresses SHH, creating a gradient of SHH from the posterior to the anterior side of the handplate.

In the presence of SHH, full length GLI3-protein is produced (GLI3A), whereas absence of SHH causes cleavage of GLI3 into its repressor form (GLI3R).3 4 Abnormal expression of this SHH/GLI3R gradient can cause both preaxial and postaxial polydactyly.2Concordantly, pathogenic DNA variants in the GLI3 gene are known to cause multiple syndromes with craniofacial and limb involvement, such as. Acrocallosal syndrome5 (OMIM. 200990), Greig cephalopolysyndactyly syndrome6 (OMIM. 175700) and Pallister-Hall syndrome7 (OMIM.

146510). Also, in non-syndromic polydactyly, such as preaxial polydactyly-type 4 (PPD4, OMIM. 174700),8 pathogenic variants in GLI3 have been described. Out of these diseases, Pallister-Hall syndrome is the most distinct entity, defined by the presence of central polydactyly and hypothalamic hamartoma.9 The other GLI3 syndromes are defined by the presence of preaxial and/or postaxial polydactyly of the hand and feet with or without syndactyly (Greig syndrome, PPD4).

Also, various mild craniofacial features such as hypertelorism and macrocephaly can occur. Pallister-Hall syndrome is caused by truncating variants in the middle third of the GLI3 gene.10â12 The truncation of GLI3 causes an overexpression of GLI3R, which is believed to be the key difference between Pallister-Hall and the GLI3-mediated polydactyly syndromes.9 11 Although multiple attempts have been made, the clinical and genetic distinction between the GLI3-mediated polydactyly syndromes is less evident. This has for example led to the introduction of subGreig and the formulation of an Oro-facial-digital overlap syndrome.10 Other authors, suggested that we should not regard these diseases as separate entities, but as a spectrum of GLI3-mediated polydactyly syndromes.13Although phenotype/genotype correlation of the different syndromes has been cumbersome, clinical and animal studies do provide evidence that distinct regions within the gene, could be related to the individual anomalies contributing to these syndromes. First, case studies show isolated preaxial polydactyly is caused by both truncating and non-truncating variants throughout the GLI3 gene, whereas in isolated postaxial polydactyly cases truncating variants at the C-terminal side of the gene are observed.12 14 These results suggest two different groups of variants for preaxial and postaxial polydactyly.

Second, recent animal studies suggest that posterior malformations in GLI3-mediated polydactyly syndromes are likely related to a dosage effect of GLI3R rather than due to the influence of an altered GLI3A expression.15Past attempts for phenotype/genotype correlation in GLI3-mediated polydactyly syndromes have directly related the diagnosed syndrome to the observed genotype.10â12 16 Focusing on individual hand phenotypes, such as preaxial and postaxial polydactyly and syndactyly might be more reliable because it prevents misclassification due to inconsistent use of syndrome definition. Subsequently, latent class analysis (LCA) provides the possibility to relate a group of observed variables to a set of latent, or unmeasured, parameters and thereby identifying different subgroups in the obtained dataset.17 As a result, LCA allows us to group different phenotypes within the GLI3-mediated polydactyly syndromes and relate the most important predictors of the grouped phenotypes to the observed GLI3 variants.The aim of our study was to further investigate the correlation of the individual phenotypes to the genotypes observed in GLI3-mediated polydactyly syndromes, using LCA. Cases were obtained by both literature review and the inclusion of local clinical cases. Subsequently, we identified two subclasses of limb anomalies that relate to the underlying GLI3 variant.

We provide evidence for two different phenotypic and genotypic groups with predominantly preaxial and postaxial hand and feet anomalies, and we specify those cases with a higher risk for corpus callosum anomalies.MethodsLiterature reviewThe Human Gene Mutation Database (HGMD Professional 2019) was reviewed to identify known pathogenic variants in GLI3 and corresponding phenotypes.18 All references were obtained and cases were included when they were diagnosed with either Greig or subGreig syndrome or PPD4.10â12 Pallister-Hall syndrome and acrocallosal syndrome were excluded because both are regarded distinct syndromes and rather defined by the presence of the non-hand anomalies, than the presence of preaxial or postaxial polydactyly.13 19 Isolated preaxial or postaxial polydactyly were excluded for two reasons. The phenotype/genotype correlations are better understood and both anomalies can occur sporadically which could introduce falsely assumed pathogenic GLI3 variants in the analysis. Additionally, cases were excluded when case-specific phenotypic or genotypic information was not reported or if these two could not be related to each other. Families with a combined phenotypic description, not reducible to individual family members, were included as one case in the analysis.Clinical casesThe Sophia Childrenâs Hospital Database was reviewed for cases with a GLI3 variant.

Within this population, the same inclusion criteria for the phenotype were valid. Relatives of the index patients were also contacted for participation in this study, when they showed comparable hand, foot, or craniofacial malformations or when a GLI3 variant was identified. Phenotypes of the hand, foot and craniofacial anomalies of the patients treated in the Sophia Children's Hospital were collected using patient documentation. Family members were identified and if possible, clinically verified.

Alternatively, family members were contacted to verify their phenotypes. If no verification was possible, cases were excluded.PhenotypesThe phenotypes of both literature cases and local cases were extracted in a similar fashion. The most frequently reported limb and craniofacial phenotypes were dichotomised. The dichotomised hand and foot phenotypes were preaxial polydactyly, postaxial polydactyly and syndactyly.

Broad halluces or thumbs were commonly reported by authors and were dichotomised as a presentation of preaxial polydactyly. The extracted dichotomised craniofacial phenotypes were hypertelorism, macrocephaly and corpus callosum agenesis. All other phenotypes were registered, but not dichotomised.Pathogenic GLI3 variantsAll GLI3 variants were extracted and checked using Alamut Visual V.2.14. If indicated, variants were renamed according to standard Human Genome Variation Society nomenclature.20 Variants were grouped in either missense, frameshift, nonsense or splice site variants.

In the group of frameshift variants, a subgroup with possible splice site effect were identified for subgroup analysis when indicated. Similarly, nonsense variants prone for nonsense mediated decay (NMD) and nonsense variants with experimentally confirmed NMD were identified.21 Deletions of multiple exons, CNVs and translocations were excluded for analysis. A full list of included mutations is available in the online supplementary materials.Supplemental materialThe location of the variant was compared with five known structural domains of the GLI3 gene. (1) repressor domain, (2) zinc finger domain, (3) cleavage site, (4) activator domain, which we defined as a concatenation of the separately identified transactivation zones, the CBP binding domain and the mediator binding domain (MBD) and (5) the MID1 interaction region domain.1 6 22â24 The boundaries of each of the domains were based on available literature (figure 1, exact locations available in the online supplementary materials).

The boundaries used by different authors did vary, therefore a consensus was made.In this figure the posterior probability of an anterior phenotype is plotted against the location of the variant, stratified for the type of mutation that was observed. For better overview, only variants with a location effect were displayed. The full figure, including all variant types, can be found in the online supplementary figure 1. Each mutation is depicted as a dot, the size of the dot represents the number of observations for that variant.

If multiple observations were made, the mean posterior odds and IQR are plotted. For the nonsense variants, variants that were predicted to produce nonsense mediated decay, are depicted using a triangle. Again, the size indicates the number of observations." data-icon-position data-hide-link-title="0">Figure 1 In this figure the posterior probability of an anterior phenotype is plotted against the location of the variant, stratified for the type of mutation that was observed. For better overview, only variants with a location effect were displayed.

The full figure, including all variant types, can be found in the online supplementary figure 1. Each mutation is depicted as a dot, the size of the dot represents the number of observations for that variant. If multiple observations were made, the mean posterior odds and IQR are plotted. For the nonsense variants, variants that were predicted to produce nonsense mediated decay, are depicted using a triangle.

Again, the size indicates the number of observations.Supplemental materialLatent class analysisTo cluster phenotypes and relate those to the genotypes of the patients, an explorative analysis was done using LCA in R (R V.3.6.1 for Mac. Polytomous variable LCA, poLCA V.1.4.1.). We used our LCA to detect the number of phenotypic subgroups in the dataset and subsequently predict a class membership for each case in the dataset based on the posterior probabilities.In order to make a reliable prediction, only phenotypes that were sufficiently reported and/or ruled out were feasible for LCA, limiting the analysis to preaxial polydactyly, postaxial polydactyly and syndactyly of the hands and feet. Only full cases were included.

To determine the optimal number of classes, we fitted a series of models ranging from a one-class to a six-class model. The optimal number of classes was based on the conditional Akaike information criterion (cAIC), the non adjusted and the sample-size adjusted Bayesian information criterion (BIC and aBIC) and the obtained entropy.25 The explorative LCA produces both posterior probabilities per case for both classes and predicted class membership. Using the predicted class membership, the phenotypic features per class were determined in a univariate analysis (Ï2, SPSS V.25). Using the posterior probabilities on latent class (LC) membership, a scatter plot was created using the location of the variant on the x-axis and the probability of class membership on the y-axis for each of the types of variants (Tibco Spotfire V.7.14).

Using these scatter plots, variants that give similar phenotypes were clustered.Genotype/phenotype correlationBecause an LC has no clinical value, the correlation between genotypes and phenotypes was investigated using the predictor phenotypes and the clustered phenotypes. First, those phenotypes that contribute most to LC membership were identified. Second those phenotypes were directly related to the different types of variants (missense, nonsense, frameshift, splice site) and their clustered locations. Quantification of the relation was performed using a univariate analysis using a Ï2 test.

Because of our selection criteria, meaning patients at least have two phenotypes, a multivariate using a logistic regression analysis was used to detect the most significant predictors in the overall phenotype (SPSS V.25). Finally, we explored the relation of the clustered genotypes to the presence of corpus callosum agenesis, a rare malformation in GLI3-mediated polydactyly syndromes which cannot be readily diagnosed without additional imaging.ResultsWe included 251 patients from the literature and 46 local patients,10â12 16 21 26â43 in total 297 patients from 155 different families with 127 different GLI3 variants, 32 of which were large deletions, CNVs or translocations. In six local cases, the exact variant could not be retrieved by status research.The distribution of the most frequently observed phenotypes and variants are presented in table 1. Other recurring phenotypes included developmental delay (n=22), broad nasal root (n=23), frontal bossing or prominent forehead (n=16) and craniosynostosis (n=13), camptodactyly (n=8) and a broad first interdigital webspace of the foot (n=6).View this table:Table 1 Baseline phenotypes and genotypes of selected populationThe LCA model was fitted using the six defined hand/foot phenotypes.

Model fit indices for the LCA are displayed in table 2. Based on the BIC, a two-class model has the best fit for our data. The four-class model does show a gain in entropy, however with a higher BIC and loss of df. Therefore, based on the majority of performance statistics and the interpretability of the model, a two-class model was chosen.

Table 3 displays the distribution of phenotypes and genotypes over the two classes.View this table:Table 2 Model fit indices for the one-class through six-class model evaluated in our LCAView this table:Table 3 Distribution of phenotypes and genotypes in the two latent classes (LC)Table 1 depicts the baseline phenotypes and genotypes in the obtained population. Note incomplete data especially in the cranium phenotypes. In total 259 valid genotypes were present. In total, 289 cases had complete data for all hand and foot phenotypes (preaxial polydactyly, postaxial polydactyly and syndactyly) and thus were available for LCA.

Combined, for phenotype/genotype correlation 258 cases were available with complete genotypes and complete hand and foot phenotypes.Table 2 depicts the model fit indices for all models that have been fitted to our data.Table 3 depicts the distribution of phenotypes and genotypes over the two assigned LCs. Hand and foot phenotypes were used as input for the LCA, thus are all complete cases. Malformation of the cranium and genotypes do have missing cases. Note that for the LCA, full case description was required, resulting in eight cases due to incomplete phenotypes.

Out of these eight, one also had a genotype that thus needed to be excluded. Missingness of genotypic data was higher in LC2, mostly due to CNVs (table 1).In 54/60 cases, a missense variant produced a posterior phenotype. Likewise, splice site variants show the same phenotype in 23/24 cases (table 3). For both frameshift and nonsense variants, this relation is not significant (52 anterior vs 54 posterior and 26 anterior vs 42 posterior, respectively).

Therefore, only for nonsense and frameshift variants the location of the variant was plotted against the probability for LC2 membership in figure 1. A full scatterplot of all variants is available in online supplementary figure 1.Figure 1 reveals a pattern for these nonsense and frameshift variants that reveals that variants at the C-terminal of the gene predict anterior phenotypes. When relating the domains of the GLI3 protein to the observed phenotype, we observe that the majority of patients with a nonsense or frameshift variant in the repressor domain, the zinc finger domain or the cleavage site had a high probability of an LC2/anterior phenotype. This group contains all variants that are either experimentally determined to be subject to NMD (triangle marker in figure 1) or predicted to be subject to NMD (diamond marker in figure 1).

Frameshift and nonsense variants in the activator domain result in high probability for an LC1/posterior phenotype. These variants will be further referred to as truncating variants in the activator domain.The univariate relation of the individual phenotypes to these two groups of variants are estimated and presented in table 4. In our multivariate analysis, postaxial polydactyly of the foot and hand are the strongest predictors (Beta. 2.548, p<0001âand Beta.

1.47, p=0.013, respectively) for patients to have a truncating variant in the activator domain. Moreover, the effect sizes of preaxial polydactyly of the hand and feet (Beta. Â0.797, p=0123âand â1.772, p=0.001) reveals that especially postaxial polydactyly of the foot is the dominant predictor for the genetic substrate of the observed anomalies.View this table:Table 4 Univariate and multivariate analysis of the phenotype/genotype correlationTable 4 shows exploration of the individual phenotypes on the genotype, both univariate and multivariate. The multivariate analysis corrects for the presence of multiple phenotypes in the underlying population.Although the craniofacial anomalies could not be included in the LCA, the relation between the observed anomalies and the identified genetic substrates can be studied.

The prevalence of hypertelorism was equally distributed over the two groups of variants (47/135 vs 21/47 respectively, p<0.229). However for corpus callosum agenesis and macrocephaly, there was a higher prevalence in patients with a truncating variant in the activator domain (3/75 vs 11/41, p<0.001. OR. 8.8, p<0.001) and 42/123 vs 24/48, p<0.05).

Noteworthy is the fact that 11/14 cases with corpus callosum agenesis in the dataset had a truncating variant in the activator domain.DiscussionIn this report, we present new insights into the correlation between the phenotype and the genotype in patients with GLI3-mediated polydactyly syndromes. We illustrate that there are two LCs of patients, best predicted by postaxial polydactyly of the hand and foot for LC1, and the preaxial polydactyly of the hand and foot and syndactyly of the foot for LC2. Patients with postaxial phenotypes have a higher risk of having a truncating variant in the activator domain of the GLI3 gene which is also related to a higher risk of corpus callosum agenesis. These results suggest a functional difference between truncating variants on the N-terminal and the C-terminal side of the GLI3 cleavage site.Previous attempts of phenotype to genotype correlation have not yet provided the clinical confirmation of these assumed mechanisms in the pathophysiology of GLI3-mediated polydactyly syndromes.

Johnston et al have successfully determined the Pallister-Hall region in which truncating variants produce a Pallister-Hall phenotype rather than Greig syndrome.11 However, in their latest population study, subtypes of both syndromes were included to explain the full spectrum of observed malformations. In 2015, Demurger et al reported the higher incidence of corpus callosum agenesis in the Greig syndrome population with truncating mutations in the activator domain.12 Al-Qattan in his review summarises the concept of a spectrum of anomalies dependent on haplo-insufficiency (through different mechanisms) and repressor overexpression.13 However, he bases this theory mainly on reviewed experimental data. Our report is the first to provide an extensive clinical review of cases that substantiate the phenotypic difference between the two groups that could fit the suggested mechanisms. We agree with Al-Qattan et al that a variation of anomalies can be observed given any pathogenic variant in the GLI3 gene, but overall two dominant phenotypes are present.

A population with predominantly preaxial anomalies and one with postaxial anomalies. The presence of preaxial or postaxial polydactyly and syndactyly is not mutually exclusive for one of these two subclasses. Meaning that preaxial polydactyly can co-occur with postaxial polydactyly. However, truncating mutations in the activator domain produce a postaxial phenotype, as can be derived from the risk in table 4.

The higher risk of corpus callosum agenesis in this population shows that differentiating between a preaxial phenotype and a postaxial phenotype, instead of between the different GLI3-mediated polydactyly syndromes, might be more relevant regarding diagnostics for corpus callosum agenesis.We chose to use LCA as an exploratory tool only in our population for two reasons. First of all, LCA can be useful to identify subgroups, but there is no âtrueâ model or number of subgroups you can detect. The best fitting model can only be estimated based on the available measures and approximates the true subgroups that might be present. Second, LC membership assignment is a statistical procedure based on the posterior probability, with concordant errors of the estimation, rather than a clinical value that can be measured or evaluated.

Therefore, we decided to use our LCA only in an exploratory tool, and perform our statistics using the actual phenotypes that predict LC membership and the associated genotypes. Overall, this method worked well to differentiate the two subgroups present in our dataset. However, outliers were observed. A qualitative analysis of these outliers is available in the online supplementary data.The genetic substrate for the two phenotypic clusters can be discussed based on multiple experiments.

Overall, we hypothesise two genetic clusters. One that is due to haploinsufficiency and one that is due to abnormal truncation of the activator. The hypothesised cluster of variants that produce haploinsufficiency is mainly based on the experimental data that confirms NMD in two variants and the NMD prediction of other nonsense variants in Alamut. For the frameshift variants, it is also likely that the cleavage of the zinc finger domain results in functional haploinsufficiency either because of a lack of signalling domains or similarly due to NMD.

Missense variants could cause haploinsufficiency through the suggested mechanism by Krauss et al who have illustrated that missense variants in the MID1 domain hamper the functional interaction with the MID1-Î±4-PP2A complex, leading to a subcellular location of GLI3.24 The observed missense variants in our study exceed the region to which Krauss et al have limited the MID-1 interaction domain. An alternative theory is suggested by Zhou et al who have shown that missense variants in the MBD can cause deficiency in the signalling of GLI3A, functionally implicating a relative overexpression of GLI3R.22 However, GLI3R overexpression would likely produce a posterior phenotype, as determined by Hill et al in their fixed homo and hemizygous GLI3R models.15 Therefore, our hypothesis is that all included missense variants have a similar pathogenesis which is more likely in concordance with the mechanism introduced by Krauss et al. To our knowledge, no splice site variants have been functionally described in literature. However, it is noted that the 15 and last exon encompasses the entire activator domain, thus any splice site mutation is by definition located on the 5â² side of the activator.

Based on the phenotype, we would suggest that these variants fail to produce a functional protein. We hypothesise that the truncating variants of the activator domain lead to overexpression of GLI3R in SHH rich areas. In normal development, the presence of SHH prevents the processing of full length GLI34 into GLI3R, thus producing the full length activator. In patients with a truncating variant of the activator domain of GLI3, thus these variants likely have the largest effect in SHH rich areas, such as the ZPA located at the posterior side of the hand/footplate.

Moreover, the lack of posterior anomalies in the GLI3â699/- mouse model (hemizygous fixed repressor model) compared with the GLI3â699/â699 mouse model (homozygous fixed repressor model), suggesting a dosage effect of GLI3R to be responsible for posterior hand anomalies.15 These findings are supported by Lewandowski et al, who show that the majority of the target genes in GLI signalling are regulated by GLI3R rather than GLI3A.44 Together, these findings suggest a role for the location and type of variant in GLI3-mediated syndromes.Interestingly, the difference between Pallister-Hall syndrome and GLI3-mediated polydactyly syndromes has also been attributed to the GLI3R overexpression. However, the difference in phenotype observed in the cases with a truncating variant in the activator domain and Pallister-Hall syndrome suggest different functional consequences. When studying figure 1, it is noted that the included truncating variants on the 3â² side of the cleavage site seldomly affect the CBP binding region, which could provide an explanation for the observed differences. This binding region is included in the Pallister-Hall region as defined by Johnston et al and is necessary for the downstream signalling with GLI1.10 11 23 45 Interestingly, recent reports show that pathogenic variants in GLI1 can produce phenotypes concordant with Ellis von Krefeld syndrome, which includes overlapping features with Pallister-Hall syndrome.46 The four truncating variants observed in this study that do affect the CBP but did not result in a Pallister-Hall phenotype are conflicting with this theory.

Krauss et al postulate an alternative hypothesis, they state that the MID1-Î±4-PP2A complex, which is essential for GLI3A signalling, could also be the reason for overlapping features of Opitz syndrome, caused by variants in MID1, and Pallister-Hall syndrome. Further analysis is required to fully appreciate the functional differences between truncating mutations that cause Pallister-Hall syndrome and those that result in GLI3-mediated polydactyly syndromes.For the clinical evaluation of patients with GLI3-mediated polydactyly syndromes, intracranial anomalies are likely the most important to predict based on the variant. Unfortunately, the presence of corpus callosum agenesis was not routinely investigated or reported thus this feature could not be used as an indicator phenotype for LC membership. Interestingly when using only hand and foot phenotypes, we did notice a higher prevalence of corpus callosum agenesis in patients with posterior phenotypes.

The suggested relation between truncating mutations in the activator domain causing these posterior phenotypes and corpus callosum agenesis was statistically confirmed (OR. 8.8, p<0.001). Functionally this relation could be caused by the GLI3-MED12 interaction at the MBD. Pathogenic DNA variants in MED12 can cause Opitz-Kaveggia syndrome, a syndrome in which presentation includes corpus callosum agenesis, broad halluces and thumbs.47In conclusion, there are two distinct phenotypes within the GLI3-mediated polydactyly population.

Patients with more posteriorly and more anteriorly oriented hand anomalies. Furthermore, this difference is related to the observed variant in GLI3. We hypothesise that variants that cause haploinsufficiency produce anterior anomalies of the hand, whereas variants with abnormal truncation of the activator domain have more posterior anomalies. Furthermore, patients that have a variant that produces abnormal truncation of the activator domain, have a greater risk for corpus callosum agenesis.

Thus, we advocate to differentiate preaxial or postaxial oriented GLI3 phenotypes to explain the pathophysiology as well as to get a risk assessment for corpus callosum agenesis.Data availability statementData are available upon reasonable request.Ethics statementsPatient consent for publicationNot required.Ethics approvalThe research protocol was approved by the local ethics board of the Erasmus MC University Medical Center (MEC 2015-679)..

AbstractIntroduction best site brand levitra online. We report a very rare case of familial breast cancer and diffuse gastric cancer, with germline pathogenic variants in both BRCA1 and CDH1 genes. To the best of our knowledge, this is the first brand levitra online report of such an association.Family description.

The proband is a woman diagnosed with breast cancer at the age of 52 years. She requested genetic counselling in 2012, at the age of 91 years, because of a history of breast cancer in her daughter, her sister, her brand levitra online niece and her paternal grandmother and was therefore concerned about her relatives. Her sister and maternal aunt also had gastric cancer.

She was tested brand levitra online for several genes associated with hereditary breast cancer.Results. A large deletion of BRCA1 from exons 1 to 7 and two CDH1 pathogenic cis variants were identified.Conclusion. This complex brand levitra online situation is challenging for genetic counselling and management of at-risk individuals.cancer.

Breastcancer. Gastricclinical geneticsgenetic screening/counsellingmolecular geneticsIntroductionGLI-Kruppel family member 3 (GLI3) encodes for a zinc finger transcription factor which plays a key role in the sonic hedgehog (SHH) signalling pathway essential in both limb brand levitra online and craniofacial development.1 2 In hand development, SHH is expressed in the zone of polarising activity (ZPA) on the posterior side of the handplate. The ZPA expresses SHH, creating a gradient of SHH from the posterior to the anterior side of the handplate.

In the presence of SHH, full length GLI3-protein is produced (GLI3A), whereas absence of SHH causes cleavage of GLI3 into its repressor form (GLI3R).3 4 Abnormal expression of this SHH/GLI3R gradient can cause both preaxial and postaxial polydactyly.2Concordantly, pathogenic DNA variants in the GLI3 gene are known to cause multiple syndromes with craniofacial and limb involvement, such as brand levitra online. Acrocallosal syndrome5 (OMIM. 200990), Greig cephalopolysyndactyly syndrome6 (OMIM brand levitra online.

175700) and Pallister-Hall syndrome7 (OMIM. 146510). Also, in non-syndromic polydactyly, such as preaxial polydactyly-type 4 (PPD4, OMIM.

174700),8 pathogenic variants in GLI3 have been described. Out of these diseases, Pallister-Hall syndrome is the most distinct entity, defined by the presence of central polydactyly and hypothalamic hamartoma.9 The other GLI3 syndromes are defined by the presence of preaxial and/or postaxial polydactyly of the hand and feet with or without syndactyly (Greig syndrome, PPD4). Also, various mild craniofacial features such as hypertelorism and macrocephaly can occur.

Pallister-Hall syndrome is caused by truncating variants in the middle third of the GLI3 gene.10â12 The truncation of GLI3 causes an overexpression of GLI3R, which is believed to be the key difference between Pallister-Hall and the GLI3-mediated polydactyly syndromes.9 11 Although multiple attempts have been made, the clinical and genetic distinction between the GLI3-mediated polydactyly syndromes is less evident. This has for example led to the introduction of subGreig and the formulation of an Oro-facial-digital overlap syndrome.10 Other authors, suggested that we should not regard these diseases as separate entities, but as a spectrum of GLI3-mediated polydactyly syndromes.13Although phenotype/genotype correlation of the different syndromes has been cumbersome, clinical and animal studies do provide evidence that distinct regions within the gene, could be related to the individual anomalies contributing to these syndromes. First, case studies show isolated preaxial polydactyly is caused by both truncating and non-truncating variants throughout the GLI3 gene, whereas in isolated postaxial polydactyly cases truncating variants at the C-terminal side of the gene are observed.12 14 These results suggest two different groups of variants for preaxial and postaxial polydactyly.

Subsequently, we identified two subclasses of limb anomalies that relate to the underlying GLI3 variant. We provide evidence for two different phenotypic and genotypic groups with predominantly preaxial and postaxial hand and feet anomalies, and we specify those cases with a higher risk for corpus callosum anomalies.MethodsLiterature reviewThe Human Gene Mutation Database (HGMD Professional 2019) was reviewed to identify known pathogenic variants in GLI3 and corresponding phenotypes.18 All references were obtained and cases were included when they were diagnosed with either Greig or subGreig syndrome or PPD4.10â12 Pallister-Hall syndrome and acrocallosal syndrome were excluded because both are regarded distinct syndromes and rather defined by the presence of the non-hand anomalies, than the presence of preaxial or postaxial polydactyly.13 19 Isolated preaxial or postaxial polydactyly were excluded for two reasons. The phenotype/genotype correlations are better understood and both anomalies can occur sporadically which could introduce falsely assumed pathogenic GLI3 variants in the analysis.

Additionally, cases were excluded when case-specific phenotypic or genotypic information was not reported or if these two could not be related to each other. Families with a combined phenotypic description, not reducible to individual family members, were included as one case in the analysis.Clinical casesThe Sophia Childrenâs Hospital Database was reviewed for cases with a GLI3 variant. Within this population, the same inclusion criteria for the phenotype were valid.

Relatives of the index patients were also contacted for participation in this study, when they showed comparable hand, foot, or craniofacial malformations or when a GLI3 variant was identified. Phenotypes of the hand, foot and craniofacial anomalies of the patients treated in the Sophia Children's Hospital were collected using patient documentation. Family members were identified and if possible, clinically verified.

The dichotomised hand and foot phenotypes were preaxial polydactyly, postaxial polydactyly and syndactyly. Broad halluces or thumbs were commonly reported by authors and were dichotomised as a presentation of preaxial polydactyly. The extracted dichotomised craniofacial phenotypes were hypertelorism, macrocephaly and corpus callosum agenesis.

All other phenotypes were registered, but not dichotomised.Pathogenic GLI3 variantsAll GLI3 variants were extracted and checked using Alamut Visual V.2.14. If indicated, variants were renamed according to standard Human Genome Variation Society nomenclature.20 Variants were grouped in either missense, frameshift, nonsense or splice site variants. In the group of frameshift variants, a subgroup with possible splice site effect were identified for subgroup analysis when indicated.

Similarly, nonsense variants prone for nonsense mediated decay (NMD) and nonsense variants with experimentally confirmed NMD were identified.21 Deletions of multiple exons, CNVs and translocations were excluded for analysis. A full list of included mutations is available in the online supplementary materials.Supplemental materialThe location of the variant was compared with five known structural domains of the GLI3 gene. (1) repressor domain, (2) zinc finger domain, (3) cleavage site, (4) activator domain, which we defined as a concatenation of the separately identified transactivation zones, the CBP binding domain and the mediator binding domain (MBD) and (5) the MID1 interaction region domain.1 6 22â24 The boundaries of each of the domains were based on available literature (figure 1, exact locations available in the online supplementary materials).

Each mutation is depicted as a dot, the size of the dot represents the number of observations for that variant. If multiple observations were made, the mean posterior odds and IQR are plotted. For the nonsense variants, variants that were predicted to produce nonsense mediated decay, are depicted using a triangle.

Again, the size indicates the number of observations." data-icon-position data-hide-link-title="0">Figure 1 In this figure the posterior probability of an anterior phenotype is plotted against the location of the variant, stratified for the type of mutation that was observed. For better overview, only variants with a location effect were displayed. The full figure, including all variant types, can be found in the online supplementary figure 1.

Only full cases were included. To determine the optimal number of classes, we fitted a series of models ranging from a one-class to a six-class model. The optimal number of classes was based on the conditional Akaike information criterion (cAIC), the non adjusted and the sample-size adjusted Bayesian information criterion (BIC and aBIC) and the obtained entropy.25 The explorative LCA produces both posterior probabilities per case for both classes and predicted class membership.

Using the predicted class membership, the phenotypic features per class were determined in a univariate analysis (Ï2, SPSS V.25). Using the posterior probabilities on latent class (LC) membership, a scatter plot was created using the location of the variant on the x-axis and the probability of class membership on the y-axis for each of the types of variants (Tibco Spotfire V.7.14). Using these scatter plots, variants that give similar phenotypes were clustered.Genotype/phenotype correlationBecause an LC has no clinical value, the correlation between genotypes and phenotypes was investigated using the predictor phenotypes and the clustered phenotypes.

First, those phenotypes that contribute most to LC membership were identified. Second those phenotypes were directly related to the different types of variants (missense, nonsense, frameshift, splice site) and their clustered locations. Quantification of the relation was performed using a univariate analysis using a Ï2 test.

Other recurring phenotypes included developmental delay (n=22), broad nasal root (n=23), frontal bossing or prominent forehead (n=16) and craniosynostosis (n=13), camptodactyly (n=8) and a broad first interdigital webspace of the foot (n=6).View this table:Table 1 Baseline phenotypes and genotypes of selected populationThe LCA model was fitted using the six defined hand/foot phenotypes. Model fit indices for the LCA are displayed in table 2. Based on the BIC, a two-class model has the best fit for our data.

The four-class model does show a gain in entropy, however with a higher BIC and loss of df. Therefore, based on the majority of performance statistics and the interpretability of the model, a two-class model was chosen. Table 3 displays the distribution of phenotypes and genotypes over the two classes.View this table:Table 2 Model fit indices for the one-class through six-class model evaluated in our LCAView this table:Table 3 Distribution of phenotypes and genotypes in the two latent classes (LC)Table 1 depicts the baseline phenotypes and genotypes in the obtained population.

Note incomplete data especially in the cranium phenotypes. In total 259 valid genotypes were present. In total, 289 cases had complete data for all hand and foot phenotypes (preaxial polydactyly, postaxial polydactyly and syndactyly) and thus were available for LCA.

Note that for the LCA, full case description was required, resulting in eight cases due to incomplete phenotypes. Out of these eight, one also had a genotype that thus needed to be excluded. Missingness of genotypic data was higher in LC2, mostly due to CNVs (table 1).In 54/60 cases, a missense variant produced a posterior phenotype.

Likewise, splice site variants show the same phenotype in 23/24 cases (table 3). For both frameshift and nonsense variants, this relation is not significant (52 anterior vs 54 posterior and 26 anterior vs 42 posterior, respectively). Therefore, only for nonsense and frameshift variants the location of the variant was plotted against the probability for LC2 membership in figure 1.

A full scatterplot of all variants is available in online supplementary figure 1.Figure 1 reveals a pattern for these nonsense and frameshift variants that reveals that variants at the C-terminal of the gene predict anterior phenotypes. When relating the domains of the GLI3 protein to the observed phenotype, we observe that the majority of patients with a nonsense or frameshift variant in the repressor domain, the zinc finger domain or the cleavage site had a high probability of an LC2/anterior phenotype. This group contains all variants that are either experimentally determined to be subject to NMD (triangle marker in figure 1) or predicted to be subject to NMD (diamond marker in figure 1).

2.548, p<0001âand Beta. 1.47, p=0.013, respectively) for patients to have a truncating variant in the activator domain. Moreover, the effect sizes of preaxial polydactyly of the hand and feet (Beta.

Â0.797, p=0123âand â1.772, p=0.001) reveals that especially postaxial polydactyly of the foot is the dominant predictor for the genetic substrate of the observed anomalies.View this table:Table 4 Univariate and multivariate analysis of the phenotype/genotype correlationTable 4 shows exploration of the individual phenotypes on the genotype, both univariate and multivariate. The multivariate analysis corrects for the presence of multiple phenotypes in the underlying population.Although the craniofacial anomalies could not be included in the LCA, the relation between the observed anomalies and the identified genetic substrates can be studied. The prevalence of hypertelorism was equally distributed over the two groups of variants (47/135 vs 21/47 respectively, p<0.229).

However for corpus callosum agenesis and macrocephaly, there was a higher prevalence in patients with a truncating variant in the activator domain (3/75 vs 11/41, p<0.001. OR. 8.8, p<0.001) and 42/123 vs 24/48, p<0.05).

These results suggest a functional difference between truncating variants on the N-terminal and the C-terminal side of the GLI3 cleavage site.Previous attempts of phenotype to genotype correlation have not yet provided the clinical confirmation of these assumed mechanisms in the pathophysiology of GLI3-mediated polydactyly syndromes. Johnston et al have successfully determined the Pallister-Hall region in which truncating variants produce a Pallister-Hall phenotype rather than Greig syndrome.11 However, in their latest population study, subtypes of both syndromes were included to explain the full spectrum of observed malformations. In 2015, Demurger et al reported the higher incidence of corpus callosum agenesis in the Greig syndrome population with truncating mutations in the activator domain.12 Al-Qattan in his review summarises the concept of a spectrum of anomalies dependent on haplo-insufficiency (through different mechanisms) and repressor overexpression.13 However, he bases this theory mainly on reviewed experimental data.

Our report is the first to provide an extensive clinical review of cases that substantiate the phenotypic difference between the two groups that could fit the suggested mechanisms. We agree with Al-Qattan et al that a variation of anomalies can be observed given any pathogenic variant in the GLI3 gene, but overall two dominant phenotypes are present. A population with predominantly preaxial anomalies and one with postaxial anomalies.

The presence of preaxial or postaxial polydactyly and syndactyly is not mutually exclusive for one of these two subclasses. Meaning that preaxial polydactyly can co-occur with postaxial polydactyly. However, truncating mutations in the activator domain produce a postaxial phenotype, as can be derived from the risk in table 4.

Second, LC membership assignment is a statistical procedure based on the posterior probability, with concordant errors of the estimation, rather than a clinical value that can be measured or evaluated. Therefore, we decided to use our LCA only in an exploratory tool, and perform our statistics using the actual phenotypes that predict LC membership and the associated genotypes. Overall, this method worked well to differentiate the two subgroups present in our dataset.

However, outliers were observed. A qualitative analysis of these outliers is available in the online supplementary data.The genetic substrate for the two phenotypic clusters can be discussed based on multiple experiments. Overall, we hypothesise two genetic clusters.

One that is due to haploinsufficiency and one that is due to abnormal truncation of the activator. The hypothesised cluster of variants that produce haploinsufficiency is mainly based on the experimental data that confirms NMD in two variants and the NMD prediction of other nonsense variants in Alamut. For the frameshift variants, it is also likely that the cleavage of the zinc finger domain results in functional haploinsufficiency either because of a lack of signalling domains or similarly due to NMD.

However, it is noted that the 15 and last exon encompasses the entire activator domain, thus any splice site mutation is by definition located on the 5â² side of the activator. Based on the phenotype, we would suggest that these variants fail to produce a functional protein. We hypothesise that the truncating variants of the activator domain lead to overexpression of GLI3R in SHH rich areas.

In normal development, the presence of SHH prevents the processing of full length GLI34 into GLI3R, thus producing the full length activator. In patients with a truncating variant of the activator domain of GLI3, thus these variants likely have the largest effect in SHH rich areas, such as the ZPA located at the posterior side of the hand/footplate. Moreover, the lack of posterior anomalies in the GLI3â699/- mouse model (hemizygous fixed repressor model) compared with the GLI3â699/â699 mouse model (homozygous fixed repressor model), suggesting a dosage effect of GLI3R to be responsible for posterior hand anomalies.15 These findings are supported by Lewandowski et al, who show that the majority of the target genes in GLI signalling are regulated by GLI3R rather than GLI3A.44 Together, these findings suggest a role for the location and type of variant in GLI3-mediated syndromes.Interestingly, the difference between Pallister-Hall syndrome and GLI3-mediated polydactyly syndromes has also been attributed to the GLI3R overexpression.

However, the difference in phenotype observed in the cases with a truncating variant in the activator domain and Pallister-Hall syndrome suggest different functional consequences. When studying figure 1, it is noted that the included truncating variants on the 3â² side of the cleavage site seldomly affect the CBP binding region, which could provide an explanation for the observed differences. This binding region is included in the Pallister-Hall region as defined by Johnston et al and is necessary for the downstream signalling with GLI1.10 11 23 45 Interestingly, recent reports show that pathogenic variants in GLI1 can produce phenotypes concordant with Ellis von Krefeld syndrome, which includes overlapping features with Pallister-Hall syndrome.46 The four truncating variants observed in this study that do affect the CBP but did not result in a Pallister-Hall phenotype are conflicting with this theory.

Interestingly when using only hand and foot phenotypes, we did notice a higher prevalence of corpus callosum agenesis in patients with posterior phenotypes. The suggested relation between truncating mutations in the activator domain causing these posterior phenotypes and corpus callosum agenesis was statistically confirmed (OR. 8.8, p<0.001).

Functionally this relation could be caused by the GLI3-MED12 interaction at the MBD. Pathogenic DNA variants in MED12 can cause Opitz-Kaveggia syndrome, a syndrome in which presentation includes corpus callosum agenesis, broad halluces and thumbs.47In conclusion, there are two distinct phenotypes within the GLI3-mediated polydactyly population. Patients with more posteriorly and more anteriorly oriented hand anomalies.

Furthermore, this difference is related to the observed variant in GLI3. We hypothesise that variants that cause haploinsufficiency produce anterior anomalies of the hand, whereas variants with abnormal truncation of the activator domain have more posterior anomalies. Furthermore, patients that have a variant that produces abnormal truncation of the activator domain, have a greater risk for corpus callosum agenesis.

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Medicaid managed care enrollees can only leave and join another plan within the first 90 days of joining a health plan can i get levitra over the counter. After the 90 days has expired, enrollees are âlocked inâ to the plan for the rest of the year. Consumers can switch plans during the âlock inâ period only for good cause. The can i get levitra over the counter pharmacy benefit changes are not considered good cause.

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Each plan will have its own formulary and drug coverage policies like prior authorization and step therapy. Pharmacy networks can also differ from plan to plan. Prescriber Prevails applies in certain brand levitra online drug classes. Prescriber prevails applys to medically necessary precription drugs in the following classes. atypical antipsychotics, anti-depressants, anti-retrovirals, anti-rejection, seizure, epilepsy, endocrine, hemotologic and immunologic therapeutics.

Prescribers will need to demonstrate reasonable profession judgment and supply brand levitra online plans witht requested information and/or clinical documentation. Pharmacy Benefit Information Website -- http://mmcdruginformation.nysdoh.suny.edu/-- This website provides very helpful information on a plan by plan basis regarding pharmacy networks and drug formularies. The Department of Health plans to build capacity for interactive searches allowing for comparison of coverage across plans in the near future. Standardized Prior Autorization (PA) Form -- The Department of Health worked with managed care plans, provider organizations and other state agencies to develop a standard prior authorization form for the brand levitra online pharmacy benefit in Medicaid managed care. The form will be posted on the Pharmacy Information Website in July of 2013.

Mail Order Drugs -- Medicaid managed care members can obtain mail order/specialty drugs at any retail network pharmacy, as long as that retail network pharmacy agrees to a price that is comparable to the mail order/specialty pharmacy price. CAN CONSUMERS brand levitra online SWITCH PLANS IN ORDER TO GAIN ACCESS TO DRUGS?. Changing plans is often an effective strategy for consumers eligible for both Medicaid and Medicare (dual eligibles) who receive their pharmacy service through Medicare Part D, because dual eligibles are allowed to switch plans at any time. Medicaid consumers will have this option only in the limited circumstances during the first year of enrollment in managed care. Medicaid managed care enrollees can only leave and join another plan within brand levitra online the first 90 days of joining a health plan.

After the 90 days has expired, enrollees are âlocked inâ to the plan for the rest of the year. Consumers can switch plans during the âlock inâ period only for good cause. The pharmacy benefit changes brand levitra online are not considered good cause. After the first 12 months of enrollment, Medicaid managed care enrollees can switch plans at any time. STEPS CONSUMERS CAN TAKE WHEN A MANAGED CARE PLAM DENIES ACCESS TO A NECESSARY DRUG As a first step, consumers should try to work with their providers to satisfy plan requirements for prior authorization or step therapy or any other utilization control requirements.

If the plan still denies access, consumers can pursue review processes specific to managed care while at the brand levitra online same time pursuing a fair hearing. All plans are required to maintain an internal and external review process for complaints and appeals of service denials. Some plans may develop special procedures for drug denials. Information on brand levitra online these procedures should be provided in member handbooks. Beginning April 1, 2018, Medicaid managed care enrollees whose plan denies prior approval of a prescription drug, or discontinues a drug that had been approved, will receive an Initial Adverse Determination notice from the plan - See Model Denial IAD Notice and IAD Notice to Reduce, Suspend or Stop Services The enrollee must first request an internal Plan Appeal and wait for the Plan's decision.

An adverse decision is called a 'FInal Adverse Determination" or FAD. See model Denial FAD Notice and FAD Notice to Reduce, brand levitra online Suspend or Stop Services. The enroll has the right to request a fair hearing to appeal an FAD. The enrollee may only request a fair hearing BEFORE receiving the FAD if the plan fails to send the FAD in the required time limit, which is 30 calendar days in standard appeals, and 72 hours in expedited appeals. The plan may extend the time to decide both standard and expedited appeals by up to 14 days if more information is brand levitra online needed and it is in the enrollee's interest.

AID CONTINUING -- If an enrollee requests a Plan Appeal and then a fair hearing because access to a drug has been reduced or terminated, the enrollee has the right to aid continuing (continued access to the drug in question) while waiting for the Plan Appeal and then the fair hearing. The enrollee must request the Plan Appeal and then the Fair Hearing before the effective date of the IAD and FAD notices, which is a very short time - only 10 days including mailing time. See more about brand levitra online the changes in Managed Care appeals here. Even though that article is focused on Managed Long Term Care, the new appeals requirements also apply to Mainstream Medicaid managed care. Enrollees who are in the first 90 days of enrollment, or past the first 12 months of enrollment also have the option of switching plans to improve access to their medications.

Consumers who experience problems with access to prescription drugs should always file a complaint with the State Department of Healthâs Managed Care Hotline, number listed below brand levitra online. ACCESSING MEDICAID'S PHARMACY BENEFIT IN FEE FOR SERVICE MEDICAID For those Medicaid recipients who are not yet in a Medicaid Managed Care program, and who do not have Medicare Part D, the Medicaid Pharmacy program covers most of their prescription drugs and select non-prescription drugs and medical supplies for Family Health Plus enrollees. Certain drugs/drug categories require the prescribers to obtain prior authorization. These include brand name drugs that have a generic alternative under New York's mandatory generic drug program or brand levitra online prescribed drugs that are not on New York's preferred drug list. The full Medicaid formulary can be searched on the eMedNY website.

Even in fee for service Medicaid, prescribers must obtain prior authorization before prescribing non-preferred drugs unless otherwise indicated. Prior authorization is required for original prescriptions, brand levitra online not refills. A prior authorization is effective for the original dispensing and up to five refills of that prescription within the next six months. Click here for more information on NY's prior authorization process. The New York State Board of Pharmacy publishes an annual list of the brand levitra online 150 most frequently prescribed drugs, in the most common quantities.

The State Department of Health collects retail price information on these drugs from pharmacies that participate in the Medicaid program. Click here to search for a specific drug from the most frequently prescribed drug list and this site can also provide you with the locations of pharmacies that provide this drug as well as their costs. Click here to view New York State Medicaidâs Pharmacy Provider Manual. WHO YOU CAN CALL FOR HELP Community Health Advocates Hotline. 1-888-614-5400 NY State Department of Health's Managed Care Hotline.

1-800-206-8125 (Mon. - Fri. 8:30 am - 4:30 pm) NY State Department of Insurance.