Lorenzi et al., 2018 - Google Patents
Susceptibility of brain atrophy to TRIB3 in Alzheimer's disease, evidence from functional prioritization in imaging geneticsLorenzi et al., 2018
View HTML- Document ID
- 8501417033444942317
- Author
- Lorenzi M
- Altmann A
- Gutman B
- Wray S
- Arber C
- Hibar D
- Jahanshad N
- Schott J
- Alexander D
- Thompson P
- Ourselin S
- Alzheimer’s Disease Neuroimaging Initiative
- Publication year
- Publication venue
- Proceedings of the National Academy of Sciences
External Links
Snippet
The joint modeling of brain imaging information and genetic data is a promising research avenue to highlight the functional role of genes in determining the pathophysiological mechanisms of Alzheimer's disease (AD). However, since genome-wide association (GWA) …
- 206010001897 Alzheimer's disease 0 title abstract description 74
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/32—Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
- G06F19/322—Management of patient personal data, e.g. patient records, conversion of records or privacy aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
- G06F19/34—Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
- G06F19/345—Medical expert systems, neural networks or other automated diagnosis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/22—Health care, e.g. hospitals; Social work
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/28—Neurological disorders
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES OR MICRO-ORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or micro-organisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Hybridisation probes
- C12Q1/6883—Hybridisation probes for diseases caused by alterations of genetic material
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Lorenzi et al. | Susceptibility of brain atrophy to TRIB3 in Alzheimer’s disease, evidence from functional prioritization in imaging genetics | |
Helbig et al. | A recurrent missense variant in AP2M1 impairs clathrin-mediated endocytosis and causes developmental and epileptic encephalopathy | |
Zhao et al. | Common genetic variation influencing human white matter microstructure | |
Zeggini et al. | Translational genomics and precision medicine: Moving from the lab to the clinic | |
Eijsbouts et al. | Genome-wide analysis of 53,400 people with irritable bowel syndrome highlights shared genetic pathways with mood and anxiety disorders | |
Purves et al. | A major role for common genetic variation in anxiety disorders | |
Bovijn et al. | Evaluating the cardiovascular safety of sclerostin inhibition using evidence from meta-analysis of clinical trials and human genetics | |
Zhang et al. | Bayesian model reveals latent atrophy factors with dissociable cognitive trajectories in Alzheimer’s disease | |
Agosta et al. | Apolipoprotein E ε4 is associated with disease-specific effects on brain atrophy in Alzheimer's disease and frontotemporal dementia | |
Synofzik et al. | SYNE1 ataxia is a common recessive ataxia with major non-cerebellar features: a large multi-centre study | |
Iniesta et al. | Antidepressant drug-specific prediction of depression treatment outcomes from genetic and clinical variables | |
Alves et al. | Progression of motor impairment and disability in Parkinson disease: a population-based study | |
Lord et al. | Mendelian randomization identifies blood metabolites previously linked to midlife cognition as causal candidates in Alzheimer’s disease | |
Honea et al. | Characterizing the role of brain derived neurotrophic factor genetic variation in Alzheimer’s disease neurodegeneration | |
Geissler et al. | A lifetime of attention-deficit/hyperactivity disorder: diagnostic challenges, treatment and neurobiological mechanisms | |
Zhao et al. | Elevated dementia risk, cognitive decline, and hippocampal atrophy in multisite chronic pain | |
Tang et al. | APOE affects the volume and shape of the amygdala and the hippocampus in mild cognitive impairment and Alzheimer’s disease: age matters | |
Lim et al. | Risk of Alzheimer's disease and related dementia by sex and race/ethnicity: The Multiethnic Cohort Study | |
Du et al. | The genetic determinants of language network dysconnectivity in drug-naïve early stage schizophrenia | |
Ruzicka et al. | Single-cell multi-cohort dissection of the schizophrenia transcriptome | |
La Cognata et al. | Omics data and their integrative analysis to support stratified medicine in neurodegenerative diseases | |
Hansson et al. | The genetic regulation of protein expression in cerebrospinal fluid | |
Ezzati et al. | Machine learning predictive models can improve efficacy of clinical trials for Alzheimer’s disease | |
Zheutlin et al. | Multivariate pattern analysis of genotype–phenotype relationships in schizophrenia | |
Wang et al. | Impacts of CD33 genetic variations on the atrophy rates of hippocampus and parahippocampal gyrus in normal aging and mild cognitive impairment |