Fig 1.
The analysed databases and applied methodologies. Solid lines show the route of the data whereas dotted lines represent expert validation.
Fig 2.
A matrix, tree and network view of comorbid relations.
Sparsity and correspondence of pairwise associative measure of comorbidity and co=morbidity posteriors of the Bayesian direct multimorbidity maps (BDMM) using three subsets (clusters) of disorders, namely metabolic syndromes (red), diseases of the nervous system (blue) and mental and behavioural disorders (green), reported in the UK Biobank dataset. Top figure a. shows the p-values of the comorbidity associations by χ2 test in purple as pairwise statistical associations, while the posterior probabilities of co=morbidities derived from the BDMM are in gold below the gray diagonal. Middle figure b. as intermediate step towards structural dependencies represents the hierarchical clustering of diseases based on the pairwise associations (χ2 p-values as distances are used by the Ward method to compute a hierarchical clustering) resulting three main clusters, which follows the expected disease groups. Bottom figure c. represents the disease networks, where the gold edges show the sparse co=morbidities in BDMM while the purple dashed lines show indirect links defined by pairwise methods. We used the following abbreviations for the disease names: ANXIETY: anxiety/panic attacks, CTS: carpal tunnel syndrome, CFS: chronic fatigue syndrome, DIAB EYE: diabetic eye disease, HEADACHES NM: headaches (not migraine), HEAD INJ: head injury, HIGH CHOL: high cholesterol, BD: mania/bipolar disorder/manic depression, MS: multiple sclerosis, NERVOUS BREAK: nervous breakdown, ONP: other neurological problem, PD: Parkinson’s disease, PN: peripheral neuropathy, POLIO: polio/poliomyelitis, PN DEP: post-natal depression, TGN: trigeminal neuralgia.
Fig 3.
Sparsity of Bayesian direct morbidity maps of multimorbidities over the diseasome.
Figure A shows the network of disorders based on χ2 independence tests whereas figure B represents the sparser BDMM of the same disorders. The node color denotes the different high level ICD-10 categories of the different disorders. The node size is proportional to the prevalence of the diseases. The two gray nodes with multiple connections are sex and age.
Fig 4.
The top 5000 connections based on different measures.
The BDMM edge posteriors (purple) together with the transformed connection values (odds ratios: red, risk ratios: blue and χ2 p-values: green). Dashed lines show the cut-off thresholds for the different measures. The given values show the original OR, RR and χ2 p-values.
Fig 5.
The scatterplot of BDMM posteriors together with transformed Bonferroni-corrected χ2 p-values.
The different colors show the connections which are significant by both methods (red), significant only based on parametric association (green) and not significant (blue). For the BDMM we used a threshold of 0.95 whereas for the χ2 test a 0.05 threshold after Bonferroni-correction was applied. The density plots are scaled to 1 separately.
Fig 6.
The BDMM structural association and the transformed χ2 p-values.
Disease-disease connections shown with less than the 0.95 BDMM edge posterior. Green dots represents the connections significant by the χ2 independence test (p-value<0.05 after Bonferroni correction), whereas blue dots denotes the remaining connections.
Fig 7.
Subnetworks of pairwise and systems-based relations from both epidemiological and molecular levels.
Solid lines show the systems-based relations: separation scores with negative values in red and BDMM Pr> 0.05 in green (for exact values see Table S3 in S1 Appendix. Note, that all of them except two relations have posteriors above 0.999). Dashed lines represent the pairwise associative metrics: relative risk with 95% confidence interval excluding 1 in dark blue (for details see S2 Dataset) and genetic overlap with hypergeometric distribution p-value below 0.05 in light blue.
Fig 8.
The Bayesian direct morbidity map around depression containing the neighbors of depression at maximum distance of two.
The thickness of lines denote the strength of the link for being a member of the network above the cut-off threshold of posterior probability Pr = 0.05. Sex and age are not shown in the figure as these nodes would bring along many nodes which are related to depression only through these. Colors indicate higher level ICD-10 categories.
Fig 9.
BDMM of depression and metabolic disorders and hypertension. a: demonstrates co=morbidities with onset time prior to depression, while b. showing the BDMM computed on the full data regardless of onset time.