Table 1.
Multi-omics studies in Alzheimer’s disease considered in this review.
| Authors | Omics considered | Biological sample | Clinical features of study cohort | Integrative method? | Findings |
|---|---|---|---|---|---|
| Beckmann et al. (2020) | Genomics | Brain tissue | AD | No | VGF is causally related to AD and is down regulated in patients. |
| Transcriptomics | |||||
| Chung et al. (2022) | Genomics | Brain tissue | AD | No | MGMT expression and methylation associated with AD pathology and risk. |
| Transcriptomics | |||||
| Clark et al. (2021) | Proteomics | Cerebrospinal fluid | AD and MCI | Yes | Distinct multi-omics molecular signatures differentially related to AD pathology. Biomarker candidates of AD and cognitive decline. |
| Lipidomics | |||||
| Metabolomics | |||||
| Cohn et al. (2021) | Proteomics | Brain tissue | AD | No | In late AD tau and neuronal debris are resealed through extracellular vesicles. |
| Transcriptomics | |||||
| Lipidomics | |||||
| Du et al. (2021) | Genomics | Plasma | AD and MCI | No | Genomic and transcriptomic biomarkers are associated with neuroimaging features |
| Proteomics | |||||
| Fang et al. (2022) | Genomics | Brain tissue | AD | No | Identification of 103 risk genes for AD. Three drugs associated with decreased risk of AD. |
| Transcriptomics | |||||
| Proteomics | |||||
| Han et al. (2021) | Genomics | Brain tissue | AD | No | Web-based tool for visualisation of data |
| Transcriptomics | |||||
| Hu et al. (2020) | Genomics | Brain tissue | General population | Yes | Identification of 16 shared causal pathways between AD and Type 2 Diabetes |
| Transcriptomics | |||||
| Johnson et al. (2020) | Genomics | Brain tissue, Cerebrospinal fluid | General population | No | Microglial metabolism is associated with both normal ageing and AD and could serve a neuroprotective anti-inflammatory function. |
| Proteomics | |||||
| Johnson et al. (2022) | Genomics | Brain tissue | General population | No | APOEε4 and cognitive decline are not associated with the same biological pathways. |
| Transcriptomics | |||||
| Proteomics | |||||
| Lefterov et al. (2019) | Transcriptomics | Brain tissue | AD | No | Differential association of APOE genotype with transcriptomic and lipidomic profiles in AD |
| Lipidomics | |||||
| Li et al. (2020) | Genomics | Brain tissue | AD and MCI | Yes | Prediction of PET-imaging outcomes improved by multi-omics modelling |
| Transcriptomics | |||||
| Li et al. (2021) | Genomics | Brain tissue | AD and MCI | Yes | Molecular subtypes are associated with MCI to AD conversion risk |
| Transcriptomics | |||||
| Madrid et al. (2021) | Genomics | Blood | AD | No | Glypican-2 (GPC2) protein downregulated in AD cases |
| Transcriptomics | |||||
| Min et al. (2021) | Genomics | Brain tissue | AD | No | Somatic mutations unlikely to be causal for AD |
| Transcriptomics | |||||
| Nativio et al. (2020) | Transcriptomics | Brain tissue | AD | No | AD affects the epigenome. Disease pathways are affected by chromatin and transcription regulation. |
| Proteomics | |||||
| Epigenomics | |||||
| Odom et al. (2021) | Genomics | Brain tissue | AD | Yes | Most pathways involved in AD pathology are not picked up by single-omic approaches |
| Transcriptomics | |||||
| Park et al. (2022) | Genomics | Blood | AD and MCI | Yes | Identification of possible molecular drivers of AD heterogeneity or subtypes |
| Transcriptomics | |||||
| Proteomics | |||||
| Peña-Bautista et al. (2021) | Genomics | Blood | AD and MCI | No | Lipids and miRNAs involved in fatty acids mechanisms associated with disease. |
| Lipidomics | |||||
| Rosenthal et al. (2022) | Genomics | Brain tissue | AD | No | Identification of 17 gene clusters of pathways altered in AD |
| Transcriptomics | |||||
| Ruffini et al. (2020) | Genomics | Brain tissue | AD | No | AD shares many proteomic and transcriptomic pathways with other neurodegenerative diseases |
| Transcriptomics | |||||
| Proteomics | |||||
| Seyfried et al. (2017) | Genomics | Brain tissue | AD | No | Genetic risk loci for late-onset AD are preferentially enriched in microglia |
| Transcriptomics | |||||
| Proteomics | |||||
| Shigemizu et al. (2020) | Genomics | Blood | MCI | No | Effective in MCI-to-AD conversion prediction model. |
| Transcriptomics | |||||
| Song et al. (2021) | Genomics | Blood | AD | No | 30 cross-omics blood-based biomarkers associated with AD. |
| Transcriptomics | |||||
| Proteomics | |||||
| Tasaki et al. (2018) | Genomics | Brain tissue | General population | Yes | Specific set of neuronal genes to controls cognitive decline in older adults |
| Transcriptomics | |||||
| Tasaki et al. (2019) | Genomics | Brain tissue | General population | No | Cognitive and motor impairment could share an underlying genetic architecture |
| Transcriptomics | |||||
| Proteomics | |||||
| Wang M. et al. (2021) | Genomics | Brain tissue | AD | Yes | Molecular signatures and gene networks identified for four brain regions. ATP6V1A is an important driver of AD. |
| Transcriptomics | |||||
| Wingo et al. (2022) | Genomics | Brain tissue | General population | No | Many of the neurodegenerative disease causal proteins are shared with psychiatric disorders |
| Transcriptomics | |||||
| Proteomics | |||||
| Xicota et al. (2019) | Transcriptomics | Plasma | Memory clinic patients | Yes | Potential blood omics signature for prediction of amyloid positivity |
| Metabolomics | |||||
| Lipidomics | |||||
| Xie et al. (2021) | Genomics | Brain tissue | General population | Yes | Discovery of multi-omic networks associated with brain function and neuroimaging. |
| Transcriptomics | |||||
| Proteomics | |||||
| Xu et al. (2020) | Proteomics | Plasma | AD and MCI | No | Five lipid modules and 5 protein modules regulating homeostasis and innate immunity are strongly associated with AD. |
| Lipidomics | |||||
| Yu et al. (2022) | Transcriptomics | Blood, brain tissues | AD | No | Actin cytoskeleton is the most pronounced change in the cerebral cortex and serum of AD patients |
| Proteomics | |||||
| Zhou et al. (2021) | Genomics | Blood, brain tissues | AD | No | Useful tool for database browsing and network visualisation |
| Transcriptomics | |||||
| Proteomics |
AD, dementia of AD type; MCI, mild cognitive impairment.