Machine learning analysis of the UK Biobank reveals prognostic and diagnostic immune biomarkers for polyneuropathy and neuropathic pain in diabetes.
Diabetes Res Clin Pract
; 201: 110725, 2023 Jul.
Article
em En
| MEDLINE
| ID: mdl-37211253
ABSTRACT
AIMS:
We assessed the health data of 11,047 people with diabetes in the UK Biobank to rank 329 risk factors for diabetic polyneuropathy (DPN) and DPN with chronic neuropathic pain without a priori assumption.METHODS:
The Integrated Disease Explanation and Risk Scoring (IDEARS) platform applies machine learning algorithms to multimodal data to determine individual disease risk, and rank risk factor importance using mean SHapley Additive exPlanations (SHAP) score.RESULTS:
IDEARS models showed discriminative performances with AUC > 0.64. Lower socioeconomic status, being overweight, poor overall health, cystatin C, HbA1C, and immune activation marker, C-reactive protein (CRP), predict DPN risk. Neutrophils and monocytes were higher in males and lymphocytes lower in females with diabetes that develop DPN. Neutrophil-to-Lymphocyte Ratio (NLR) was increased and IGF-1 levels decreased in people with type 2 diabetes that later develop DPN. CRP was significantly elevated in those with DPN and chronic neuropathic pain compared to DPN without pain.CONCLUSIONS:
Lifestyle factors and blood biomarkers predict the later development of DPN and may relate to DPN pathomechanisms. Our results are consistent with DPN as a disease involving systemic inflammation. We advocate for the use of these biomarkers clinically to predict future DPN risk and improve early diagnosis.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Polineuropatias
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Diabetes Mellitus Tipo 2
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Neuropatias Diabéticas
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Neuralgia
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
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Risk_factors_studies
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Screening_studies
Limite:
Female
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Humans
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Male
País como assunto:
Europa
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article