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Biochemical algorithm to identify individuals with ALPL variants among subjects with persistent hypophosphatasaemia

BACKGROUND: Hypophosphatasia (HPP) is a rare and underdiagnosed condition characterized by deficient bone and teeth mineralization. The aim of this study was first, to evaluate the diagnostic utility of employing alkaline phosphatase (ALP) threshold levels to identify adults with variants in ALPL am...

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Autores principales: Tornero, C., Navarro-Compán, V., Buño, A., Heath, K. E., Díaz-Almirón, M., Balsa, A., Tenorio, J. A., Quer, J., Aguado, P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896389/
https://www.ncbi.nlm.nih.gov/pubmed/35241128
http://dx.doi.org/10.1186/s13023-022-02253-5
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author Tornero, C.
Navarro-Compán, V.
Buño, A.
Heath, K. E.
Díaz-Almirón, M.
Balsa, A.
Tenorio, J. A.
Quer, J.
Aguado, P.
author_facet Tornero, C.
Navarro-Compán, V.
Buño, A.
Heath, K. E.
Díaz-Almirón, M.
Balsa, A.
Tenorio, J. A.
Quer, J.
Aguado, P.
author_sort Tornero, C.
collection PubMed
description BACKGROUND: Hypophosphatasia (HPP) is a rare and underdiagnosed condition characterized by deficient bone and teeth mineralization. The aim of this study was first, to evaluate the diagnostic utility of employing alkaline phosphatase (ALP) threshold levels to identify adults with variants in ALPL among individuals with persistently low ALP levels and second, to determine the value of also including its substrates (serum pyridoxal-5′-phosphate—PLP—and urinary phosphoetanolamine-PEA) for this purpose in order to create a biochemical algorithm that could facilitate the diagnostic work-up of HPP. RESULTS: The study population comprised 77 subjects with persistent hypophosphatasaemia. They were divided into two groups according to the presence (+GT) or absence (−GT) of pathogenic ALPL variants: 40 +GT and 37 −GT. Diagnostic utility measures were calculated for different ALP thresholds and Receiver Operating Characteristic (ROC) curves were employed to determine PLP and PEA optimal cut-off levels to predict the presence of variants. The optimal threshold for ALP was 25 IU/L; for PLP, 180 nmol/L and for PEA, 30 µmol/g creatinine. Biochemical predictive models were assessed using binary logistic regression analysis and bootstrapping machine learning technique and results were then validated. For ALP < 25 UI/L (model 1), the area under curve (AUC) and the 95% confidence intervals (CI) was 0.68 (95% CI 0.63–0.72) and it improved to 0.87 (95% CI 0.8–0.9), when PEA or PLP threshold levels were added (models 2 and 3), reaching 0.94 (0.91–0.97) when both substrates were included (model 4). The internal validation showed that the addition of serum PLP threshold levels to the model just including ALP improved significantly sensitivity (S) and negative predictive value (NPV) − 100%, respectively- with an accuracy (AC) of 93% in comparison to the inclusion of urinary PEA (S: 71%; NPV 75% and AC: 79%) and similar diagnostic utility measures as those observed in model 3 were detected when both substrates were added. CONCLUSIONS: In this study, we propose a biochemical predictive model based on the threshold levels of the main biochemical markers of HPP (ALP < 25 IU/L and PLP > 180 nmol/L) that when combined, seem to be very useful to identify individuals with ALPL variants. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-022-02253-5.
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spelling pubmed-88963892022-03-14 Biochemical algorithm to identify individuals with ALPL variants among subjects with persistent hypophosphatasaemia Tornero, C. Navarro-Compán, V. Buño, A. Heath, K. E. Díaz-Almirón, M. Balsa, A. Tenorio, J. A. Quer, J. Aguado, P. Orphanet J Rare Dis Research BACKGROUND: Hypophosphatasia (HPP) is a rare and underdiagnosed condition characterized by deficient bone and teeth mineralization. The aim of this study was first, to evaluate the diagnostic utility of employing alkaline phosphatase (ALP) threshold levels to identify adults with variants in ALPL among individuals with persistently low ALP levels and second, to determine the value of also including its substrates (serum pyridoxal-5′-phosphate—PLP—and urinary phosphoetanolamine-PEA) for this purpose in order to create a biochemical algorithm that could facilitate the diagnostic work-up of HPP. RESULTS: The study population comprised 77 subjects with persistent hypophosphatasaemia. They were divided into two groups according to the presence (+GT) or absence (−GT) of pathogenic ALPL variants: 40 +GT and 37 −GT. Diagnostic utility measures were calculated for different ALP thresholds and Receiver Operating Characteristic (ROC) curves were employed to determine PLP and PEA optimal cut-off levels to predict the presence of variants. The optimal threshold for ALP was 25 IU/L; for PLP, 180 nmol/L and for PEA, 30 µmol/g creatinine. Biochemical predictive models were assessed using binary logistic regression analysis and bootstrapping machine learning technique and results were then validated. For ALP < 25 UI/L (model 1), the area under curve (AUC) and the 95% confidence intervals (CI) was 0.68 (95% CI 0.63–0.72) and it improved to 0.87 (95% CI 0.8–0.9), when PEA or PLP threshold levels were added (models 2 and 3), reaching 0.94 (0.91–0.97) when both substrates were included (model 4). The internal validation showed that the addition of serum PLP threshold levels to the model just including ALP improved significantly sensitivity (S) and negative predictive value (NPV) − 100%, respectively- with an accuracy (AC) of 93% in comparison to the inclusion of urinary PEA (S: 71%; NPV 75% and AC: 79%) and similar diagnostic utility measures as those observed in model 3 were detected when both substrates were added. CONCLUSIONS: In this study, we propose a biochemical predictive model based on the threshold levels of the main biochemical markers of HPP (ALP < 25 IU/L and PLP > 180 nmol/L) that when combined, seem to be very useful to identify individuals with ALPL variants. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-022-02253-5. BioMed Central 2022-03-03 /pmc/articles/PMC8896389/ /pubmed/35241128 http://dx.doi.org/10.1186/s13023-022-02253-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Tornero, C.
Navarro-Compán, V.
Buño, A.
Heath, K. E.
Díaz-Almirón, M.
Balsa, A.
Tenorio, J. A.
Quer, J.
Aguado, P.
Biochemical algorithm to identify individuals with ALPL variants among subjects with persistent hypophosphatasaemia
title Biochemical algorithm to identify individuals with ALPL variants among subjects with persistent hypophosphatasaemia
title_full Biochemical algorithm to identify individuals with ALPL variants among subjects with persistent hypophosphatasaemia
title_fullStr Biochemical algorithm to identify individuals with ALPL variants among subjects with persistent hypophosphatasaemia
title_full_unstemmed Biochemical algorithm to identify individuals with ALPL variants among subjects with persistent hypophosphatasaemia
title_short Biochemical algorithm to identify individuals with ALPL variants among subjects with persistent hypophosphatasaemia
title_sort biochemical algorithm to identify individuals with alpl variants among subjects with persistent hypophosphatasaemia
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896389/
https://www.ncbi.nlm.nih.gov/pubmed/35241128
http://dx.doi.org/10.1186/s13023-022-02253-5
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