Table 1.
Overview of the main results for the experiments using the Rotterdam Study, UK Biobank, and Swedish Schizophrenia Exome Sequencing study data.
| Dataset (type) | Trait | Subjects & phenotype | AUC gene test (val) | Top three predictive genes | AUC pathway test (val) | Top predictive pathway | |||
| Class I | Class II | Global level | Middle level | Local level | |||||
| Rotterdam Study (genotype array) | Eye color | 4041 Blue | 2250 Other | 0.75 (0.74) | HERC2, OCA2, LAMC1 | 0.50 (0.52) | Organismal Systems (78.4%) | Digestive system (72.6%), | Pancreatic secretion (59.1%) |
| UK Biobank (exome) | Hair color | 1734 Red | 1727 Other | 0.93 (0.94) | MC1R*, SHOC2, DCTN3 | 0.77 (0.77) | Genetic Information Processing (87.4%) | Replication and repair (83.4%) | Fanconi anemia pathway (79.7%) |
| 3762 Black | 3753 Other | 0.80 (0.82) | OCA2, RPL23AP8, MC1R* | 0.76 (0.78) | Organismal Systems (46.9%) | Endocrine system (18.6%) | Axon guidance (5.0%) | ||
| 4501 Blond | 4518 Other | 0.66 (0.65) | OCA2, TC2N, SLC45A2 | 0.58 (0.57) | Organismal Systems (70.2%) | Endocrine system (30.1%), | Adrenergic signaling in cardiomyocytes (4.1%) | ||
| Bipolar disorder | 343 Cases | 347 Controls | 0.60 (0.56) | LINC00266-1, CSMD1, TCERG1L | 0.47 (0.55) | Organismal Systems (76.9%) | Endocrine system (46.5%) | Melanogenesis (32.9%) | |
| Atrial fibrillation | 192 Cases | 194 Controls | 0.56 (0.59) | **BRINP1, SORBS3, ELM0D3 | 0.57 (0.63) | Organismal Systems (39.6%) | Signal transduction (11.2%) | Cytokine−cytokine receptor interaction (4.4%) | |
| Coronary Artery Disease | 1563 Cases | 1600 Controls | 0.56 (0.58) | **STARD7-AS1, VWC2L, NSD2 | 0.54 (0.56) | Environmental Information Processing (29.5%), | Signal transduction (27.7%) | PI3K-Akt signaling pathway (4.6%) | |
| Dementia | 139 Cases | 142 Controls | 0.60 (0.65) | RPL23AP87, CTNNA3, LINC01003 | 0.55 (0.58) | Human Diseases (39.8%) | Signal transduction (22.2%) | Pathways in cancer (5.6%) | |
| Male balding pattern | 3454 Balding pattern 1 | 3454 Balding pattern 4 | 0.56 (0.57) | NGEF, NKRD18B, SYNJ2 | 0.54 (0.55) | Organismal Systems (34.6%) | Nervous system (9.7%) | Metabolic pathways (8.7%) | |
| Asthma | 4229 Cases | 4214 Controls | 0.55 (0.57) | HLA-DQB1, HCG9, LINC00266-1 | 0.51 (0.54) | Genetic Information Processing (52.3%) | Folding, sorting and degradation (41.5%) | Ubiquitin mediated proteolysis (22.0%) | |
| Diabetes | 2557 Cases | 2555 Controls | 0.54 (0.57) | **DNAH10, SNAR-I, PSMD13 | 0.54 (0.54) | Environmental Information Processing (43.5%), | Signal transduction (40.5%), | Ras signaling pathway (7.9%) | |
| Breast cancer | 1070 Cases | 1082 Controls | 0.51 (0.56) | RPL23AP87, LINC00266-1, HPSE | 0.51 (0.56) | Human Diseases (57.1%) | Infectious diseases: Viral (16.6%) | Pathways in cancer (6.5%) | |
| Sweden (exome) | Schizophrenia | 4969 Cases | 6245 Controls | 0.74 (0.73) | ZNF773, PCNT, DYSF | 0.68 (0.67) | Human Diseases (30.8%) | Infectious diseases: Viral (27.3%) | Human papillomavirus infection (11.7%) |
The performance in AUC for the network with gene-annotations is bold if the network outperformed or matched LASSO regression. Manhattan plots for the genes can be found in Supplementary Notes 3−5. *MC1R was not annotated but was identified by linkage disequilibrium. **Many genes contributed to the prediction without clear separation between genes (see Supplementary Note 4).