The underlying aetiology of several neurodegenerative illnesses is still poorly understood. Study of clinical symptoms is currently the primary method used for differential diagnosis of most neurodegenerative disorders. Cerebrospinal fluid biomarkers emerged in the last 20 years as reliable tools for the diagnosis of neurodegenerative disease, particularly Alzheimer’s disease. Structural neuroimaging methods like computed tomography and magnetic resonance imaging have also been largely explored and used to help diagnosis. However, thanks to their higher sensitivity, positron emission tomography and single-photon emission computed tomography are increasingly used. Genetic markers linked to well-known neurodegenerative diseases have already been identified, albeit their specificity is still debatable.
The goal of most recent diagnostic studies is to develop clearly recognizable, sensitive, focused, and reasonably priced metabolite biomarkers from easily accessible matrices such as saliva, urine or blood to provide early diagnosis and to discriminate between the many types of neurological diseases. Omics approaches, such as proteomics, metabolomics and lipidomics are other cutting-edge methods for the identification of novel biomarkers as well as novel dysfunctional pathways suitable for therapeutic targeting. Moreover, computational methods, and particularly machine learning techniques, are becoming highly helpful in all fields, including illness monitoring process as well as the diagnosis of neurodegenerative diseases.
The creation of novel multi-omics tools to effectively explore disease processes and find early signs indicative of illness onset is required due to the absence of efficient biomarkers and disease preventative therapy.
This Research Topic discusses the critical need for innovative omics approaches to provide the groundwork for diagnostic tools for neurodegenerative disorders that go beyond the state-of-the-art.
We welcome submissions covering the following areas:
• Integrated OMICS in neurodegenerative diseases
• Molecular changes associated with neurodegenerative diseases
• Predictive metabolite biomarkers associated with neurodegenerative diseases
• Identification of novel metabolite biomarkers for the early diagnosis
• Emerging fields and technologies that can be used to diagnose diseases include metagenomics, structural and molecular biology, biophysics, biochemistry, and artificial intelligence
• Novel statistical/modelling approaches for omics data integration, interpretation and detection of neurodegenerative disease
The underlying aetiology of several neurodegenerative illnesses is still poorly understood. Study of clinical symptoms is currently the primary method used for differential diagnosis of most neurodegenerative disorders. Cerebrospinal fluid biomarkers emerged in the last 20 years as reliable tools for the diagnosis of neurodegenerative disease, particularly Alzheimer’s disease. Structural neuroimaging methods like computed tomography and magnetic resonance imaging have also been largely explored and used to help diagnosis. However, thanks to their higher sensitivity, positron emission tomography and single-photon emission computed tomography are increasingly used. Genetic markers linked to well-known neurodegenerative diseases have already been identified, albeit their specificity is still debatable.
The goal of most recent diagnostic studies is to develop clearly recognizable, sensitive, focused, and reasonably priced metabolite biomarkers from easily accessible matrices such as saliva, urine or blood to provide early diagnosis and to discriminate between the many types of neurological diseases. Omics approaches, such as proteomics, metabolomics and lipidomics are other cutting-edge methods for the identification of novel biomarkers as well as novel dysfunctional pathways suitable for therapeutic targeting. Moreover, computational methods, and particularly machine learning techniques, are becoming highly helpful in all fields, including illness monitoring process as well as the diagnosis of neurodegenerative diseases.
The creation of novel multi-omics tools to effectively explore disease processes and find early signs indicative of illness onset is required due to the absence of efficient biomarkers and disease preventative therapy.
This Research Topic discusses the critical need for innovative omics approaches to provide the groundwork for diagnostic tools for neurodegenerative disorders that go beyond the state-of-the-art.
We welcome submissions covering the following areas:
• Integrated OMICS in neurodegenerative diseases
• Molecular changes associated with neurodegenerative diseases
• Predictive metabolite biomarkers associated with neurodegenerative diseases
• Identification of novel metabolite biomarkers for the early diagnosis
• Emerging fields and technologies that can be used to diagnose diseases include metagenomics, structural and molecular biology, biophysics, biochemistry, and artificial intelligence
• Novel statistical/modelling approaches for omics data integration, interpretation and detection of neurodegenerative disease
