Diagnosis of Wilson Disease and Its Phenotypes by Using Artificial Intelligence

Abstract

WD is caused by ATP7B variants disrupting copper efflux resulting in excessive copper accumulation mainly in liver and brain. The diagnosis of WD is challenged by its variable clinical course, onset, morbidity, and ATP7B variant type. Currently it is diagnosed by a combination of clinical symptoms/signs, aberrant copper metabolism parameters (e.g., low ceruloplasmin serum levels and high urinary and hepatic copper concentrations), and genetic evidence of ATP7B mutations when available. As early diagnosis and treatment are key to favorable outcomes, it is critical to identify subjects before the onset of overtly detrimental clinical manifestations. To this end, we sought to improve WD diagnosis using artificial neural network algorithms (part of artificial intelligence) by integrating available clinical and molecular parameters. Surprisingly, WD diagnosis was based on plasma levels of glutamate, asparagine, taurine, and Fischer’s ratio. As these amino acids are linked to the urea–Krebs’ cycles, our study not only underscores the central role of hepatic mitochondria in WD pathology but also that most WD patients have underlying hepatic dysfunction. Our study provides novel evidence that artificial intelligence utilized for integrated analysis for WD may result in earlier diagnosis and mechanistically relevant treatments for patients with WD.

Artificial neural network applied to fragile X-associated tremor/ataxia syndrome stage diagnosis based on peripheral mitochondrial bioenergetics and brain imaging outcomes

“…To select a training set size, we performed a learning curve analysis 49 by utilizing carrier status, FXTAS diagnosis, stage, sex, age, five MRI findings, and 22 units of mitochondrial outcomes for each cell type (PBMC and fibroblasts). Basically, a relatively small number of samples from our data was randomly chosen to train the ANN as detailed before 50 . The trained ANN was then used to predict the pattern of a randomly sampled test set not included in the training set.…”

“…The ANN approach applied to this study followed that described before for Wilson’s disease 50 . The ANN design consisted of a three-layer network: an input layer with either 2 or 5 units for defining FXTAS Stages (Fig.…”

Demographic and histopathologic features of dogs with abnormally high concentrations of hepatic copper

“…Most studies have prioritized using noninvasive data (clinical, imaging, and/or multiomics data) instead of liver histology to develop these models 99,100 . However, future prospective studies in dogs could utilize these machine learning methods on both clinical and histopathologic datasets to develop and validate artificial neural network algorithms similar to those developed for humans 100,101,103 . Such algorithms could dramatically improve our ability to screen, predict, diagnose, phenotype, and treat CAH and other hepatic disorders.…”

“…In human medicine, machine learning methods similar to those used in this study have been used to develop diagnostic algorithms for many hepatic diseases 99,100 including nonalcoholic fatty liver disease, 101 hepatocellular carcinoma, 102 and even Wilson's disease. 103 Most studies have prioritized using noninvasive data (clinical, imaging, and/or multiomics data) instead of liver histology to develop these models. 99,100 However, future prospective studies in dogs could utilize these machine learning methods on both clinical and histopathologic datasets to develop and validate artificial neural network algorithms similar to those developed for humans.…”

Cardiac involvement in Wilson’s disease: a retrospective cohort study

“…The prevalence of this disease is 1:30 000-1:50 000 in the USA, Europe and Asia [2]. Mutations in ATPase copper transporting beta (ATP7B) gene that is located on chromosome 13 are responsible for WD development [3][4][5]. WD is characterized by a wide variety of clinical manifestations, including Kayser-Fleischer rings, liver cirrhosis, hepatocellular carcinoma, tremors, renal disorders, joint problems and endocrinopathy [6][7][8].…”