Applications of machine learning in metabolomics: Disease modeling and classification

A Galal, M Talal, A Moustafa - Frontiers in genetics, 2022 - frontiersin.org
Metabolomics research has recently gained popularity because it enables the study of
biological traits at the biochemical level and, as a result, can directly reveal what occurs in a …

New diagnostic approaches for undiagnosed rare genetic diseases

T Hartley, G Lemire, KD Kernohan… - Annual review of …, 2020 - annualreviews.org
Accurate diagnosis is the cornerstone of medicine; it is essential for informed care and
promoting patient and family well-being. However, families with a rare genetic disease …

Metabolomics in the clinic: A review of the shared and unique features of untargeted metabolomics for clinical research and clinical testing

AD Kennedy, BM Wittmann, AM Evans… - Journal of Mass …, 2018 - Wiley Online Library
Metabolomics is the untargeted measurement of the metabolome, which is composed of the
complement of small molecules detected in a biological sample. As such, metabolomic …

Inborn errors of metabolism in the era of untargeted metabolomics and lipidomics

IT Ismail, MR Showalter, O Fiehn - Metabolites, 2019 - mdpi.com
Inborn errors of metabolism (IEMs) are a group of inherited diseases with variable
incidences. IEMs are caused by disrupting enzyme activities in specific metabolic pathways …

Integrative omics approaches to advance rare disease diagnostics

D Smirnov, N Konstantinovskiy… - Journal of Inherited …, 2023 - Wiley Online Library
Over the past decade high‐throughput DNA sequencing approaches, namely whole exome
and whole genome sequencing became a standard procedure in Mendelian disease …

Analysis of transcript-deleterious variants in Mendelian disorders: implications for RNA-based diagnostics

S Maddirevula, H Kuwahara, N Ewida, HE Shamseldin… - Genome biology, 2020 - Springer
Background At least 50% of patients with suspected Mendelian disorders remain
undiagnosed after whole-exome sequencing (WES), and the extent to which non-coding …

Clinical diagnosis of metabolic disorders using untargeted metabolomic profiling and disease-specific networks learned from profiling data

LR Thistlethwaite, X Li, LC Burrage, K Riehle… - Scientific reports, 2022 - nature.com
Untargeted metabolomics is a global molecular profiling technology that can be used to
screen for inborn errors of metabolism (IEMs). Metabolite perturbations are evaluated based …

The diagnosis of inborn errors of metabolism by an integrative “multi‐omics” approach: A perspective encompassing genomics, transcriptomics, and proteomics

SL Stenton, LS Kremer, R Kopajtich… - Journal of inherited …, 2020 - Wiley Online Library
Given the rapidly decreasing cost and increasing speed and accessibility of massively
parallel technologies, the integration of comprehensive genomic, transcriptomic, and …

Strategies to uplift novel Mendelian gene discovery for improved clinical outcomes

EG Seaby, HL Rehm, A O'Donnell-Luria - Frontiers in Genetics, 2021 - frontiersin.org
Rare genetic disorders, while individually rare, are collectively common. They represent
some of the most severe disorders affecting patients worldwide with significant morbidity and …

[HTML][HTML] Metabolomics: a challenge for detecting and monitoring inborn errors of metabolism

M Mussap, M Zaffanello, V Fanos - Annals of translational medicine, 2018 - ncbi.nlm.nih.gov
Timely newborn screening and genetic profiling are crucial in early recognition and
treatment of inborn errors of metabolism (IEMs). A proposed nosology of IEMs has inserted …