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. 2016 Jun 11;32(12):i101–i110. doi: 10.1093/bioinformatics/btw282

Table 1.

Temporal directionality and connectivity significance of selected disease pairs unique to each race cohort

Pop. Disease 1 Disease 2 P-val β
EA Thyroid cancer Postsurgical hypothyroidism <6.4E−324 5.25
EA Lymphosarcoma Aplastic anemia <6.4E−324 3.42
EA Ulcerative colitis Intestinal obstruction <6.4E−324 3.27
EA Toxic diffuse goiter Postsurgical hypothyroidism 1.3E−153 3.11
EA Familial hypercholesterolemia Acute cystitis <6.4E−324 3.09
AA Diabetes mellitus, type 2 Diabetic cataract 2.1E−16 5.73
AA Hyperthyroidism Toxic diffuse goiter <6.4E−324 5.10
AA Chronic ulcer of skin Osteomyelitis 1.4E−235 4.96
AA Hypertension IgA glomerulonephritis 6.4E−75 4.09
AA HIV disease Esophageal candidiasis <6.4E−324 3.87
HL Diabetes mellitus, type 1 Clostridium difficile colitis 3.3E−73 2.51
HL Benign essential hypertension Phobic disorder 5.1E−28 2.25
HL Coronary artery disease ARDS 1.7E−61 1.89
HL Generalized anxiety disorder Anemia 3.1E−64 1.72
HL Major depressive disorder Decubitus ulcer 2.1E−42 1.67

For each population, we determined which temporally related disease pairs had Bonferroni-corrected significant connectivity (P < 1.42 × 10−06). We present particular disease pairs of interest from among the top-25 associations for each population, ranked by effect size. Effect size, or β, can be interpreted as the odds ratio of disease 2 occurring given disease 1, holding age and sex constant.