Identification of Compound Heterozygous Variants in LRP4 Demonstrates That a Pathogenic Variant outside the Third ß-Propeller Domain Can Cause Sclerosteosis.

Sclerosteosis is a high bone mass disorder, caused by pathogenic variants in the genes encoding sclerostin or LRP4. Both proteins form a complex that strongly inhibits canonical WNT signaling activity, a pathway of major importance in bone formation. So far, all reported disease-causing variants are located in the third ß-propeller domain of LRP4, which is essential for the interaction with sclerostin. Here, we report the identification of two compound heterozygous variants, a known p.Arg1170Gln and a novel p.Arg632His variant, in a patient with a sclerosteosis phenotype. Interestingly, the novel variant is located in the first ß-propeller domain, which is known to be indispensable for the interaction with agrin. However, using luciferase reporter assays, we demonstrated that both the p.Arg1170Gln and the p.Arg632His variant in LRP4 reduced the inhibitory capacity of sclerostin on canonical WNT signaling activity. In conclusion, this study is the first to demonstrate that a pathogenic variant in the first ß-propeller domain of LRP4 can contribute to the development of sclerosteosis, which broadens the mutational spectrum of the disorder.

A Thyroid Genetic Classifier Correctly Predicts Benign Nodules with Indeterminate Cytology: Two Independent, Multicenter, Prospective Validation Trials.

Background: Although most thyroid nodules with indeterminate cytology are benign, in most of the world, surgery remains as the most frequent diagnostic approach. We have previously reported a 10-gene thyroid genetic classifier, which accurately predicts benign thyroid nodules. The assay is a prototype diagnostic kit suitable for reference laboratory testing and could potentially avoid unnecessary diagnostic surgery in patients with indeterminate thyroid cytology. Methods: Classifier performance was tested in two independent, ethnically diverse, prospective multicenter trials (TGCT-1/Chile and TGCT-2/USA). A total of 4061 fine-needle aspirations were collected from 15 institutions, of which 897 (22%) were called indeterminate. The clinical site was blind to the classifier score and the clinical laboratory blind to the pathology report. A matched surgical pathology and valid classifier score was available for 270 samples. Results: Cohorts showed significant differences, including (i) clinical site patient source (academic, 43% and 97% for TGCT-1 and -2, respectively); (ii) ethnic diversity, with a greater proportion of the Hispanic population (40% vs. 3%) for TGCT-1 and a greater proportion of African American (11% vs. 0%) and Asian (10% vs. 1%) populations for TGCT-2; and (iii) tumor size (mean of 1.7 and 2.5 cm for TGCT-1 and -2, respectively). Overall, there were no differences in the histopathological profile between cohorts. Forty-one of 155 and 45 of 115 nodules were malignant (cancer prevalence of 26% and 39% for TGCT-1 and -2, respectively). The classifier predicted 37 of 41 and 41 of 45 malignant nodules, yielding a sensitivity of 90% [95% confidence interval; CI 77-97] and 91% [95% CI 79-98] for TGCT-1 and -2, respectively. One hundred one of 114 and 61 of 70 nodules were correctly predicted as benign, yielding a specificity of 89% [95% CI 82-94] and 87% [95% CI 77-94], respectively. The negative predictive values for TGCT-1 and TGCT-2 were 96% and 94%, respectively, whereas the positive predictive values were 74% and 82%, respectively. The overall accuracy for both cohorts was 89%. Conclusions: Clinical validation of the classifier demonstrates equivalent performance in two independent and ethnically diverse cohorts, accurately predicting benign thyroid nodules that can undergo surveillance as an alternative to diagnostic surgery.

A 10-Gene Classifier for Indeterminate Thyroid Nodules: Development and Multicenter Accuracy Study.

BACKGROUND: In most of the world, diagnostic surgery remains the most frequent approach for indeterminate thyroid cytology. Although several molecular tests are available for testing in centralized commercial laboratories in the United States, there are no available kits for local laboratory testing. The aim of this study was to develop a prototype in vitro diagnostic (IVD) gene classifier for the further characterization of nodules with an indeterminate thyroid cytology. METHODS: In a first stage, the expression of 18 genes was determined by quantitative polymerase chain reaction (qPCR) in a broad histopathological spectrum of 114 fresh-tissue biopsies. Expression data were used to train several classifiers by supervised machine learning approaches. Classifiers were tested in an independent set of 139 samples. In a second stage, the best classifier was chosen as a model to develop a multiplexed-qPCR IVD prototype assay, which was tested in a prospective multicenter cohort of fine-needle aspiration biopsies. RESULTS: In tissue biopsies, the best classifier, using only 10 genes, reached an optimal and consistent performance in the ninefold cross-validated testing set (sensitivity 93% and specificity 81%). In the multicenter cohort of fine-needle aspiration biopsy samples, the 10-gene signature, built into a multiplexed-qPCR IVD prototype, showed an area under the curve of 0.97, a positive predictive value of 78%, and a negative predictive value of 98%. By Bayes' theorem, the IVD prototype is expected to achieve a positive predictive value of 64-82% and a negative predictive value of 97-99% in patients with a cancer prevalence range of 20-40%. CONCLUSIONS: A new multiplexed-qPCR IVD prototype is reported that accurately classifies thyroid nodules and may provide a future solution suitable for local reference laboratory testing.