Table 4 Logistic Regression Analysis Examining Proteins relation to Prevalent Diabetes

From: Using a Targeted Proteomics Chip to Explore Pathophysiological Pathways for Incident Diabetes– The Malmö Preventive Project

 

OR (95% CI)

p-value

OR (95% CI)

p-value

OR (95% CI)

p-value

Model 1

Model 2

Model 3

PAI

1.35 (1.22–1.50)

2.0 × 10−8

1.00 (0.89–1.13)

0.984

0.80 (0.67–0.95)

0.012

FABP4

1.61 (1.44–1.81)

3.6 × 10−16

1.16 (1.01–1.34)

0.049

1.02 (0.82–1.27)

0.847

CD163

1.58 (1.40–1.78)

8.3 × 10−14

1.35 (1.20–1.52)

3.5 × 10−7

1.17 (0.99–1.38)

0.061

Gal4

1.97 (1.76–2.22)

6.8 × 10−30

1.85 (1.63–2.10)

1.7 × 10−21

1.54 (1.29–1.84)

1.0 × 10−6

PON3

0.59 (0.53–0.66)

1.7 × 10−21

0.78 (0.45–1.35)

6.6 × 10−5

0.94 (0.79–1.12)

0.495

IGFBP2

0.60 (0.54–0.67)

4.2 × 10−20

0.77 (0.68–0.88)

1.1 × 10−4

1.04 (0.86–1.26)

0.672

CTSD

1.73 (1.55–1.92)

1.4 × 10−23

1.46 (1.30–1.65)

2.3 × 10−10

1.14 (0.96–1.35)

0.140

  1. Logistic regressions for prevalent diabetes (681 cases in the MPP) adjusted for age and sex (Model 1) and age, sex, BMI, SBP, HT, TG, HDL, physical activity and cystatin C (Model 2) and age, sex, BMI, SBP, HT, TG, HDL, physical activity, cystatin C and FPG (Model 3). PAI; Plasminogen activator inhibitor 1, FABP4; fatty acid binding protein, CD163; scavenger receptor cysteine rich type 1 protein M130, Gal-4; Galectin-4, PON 3; Paraoxonase, IGFBP-2; Insulin-like growth factor-binding protein 2, CTSD; Cathepsin D.
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