Model 1: Age ~ Cell types
                            OLS Regression Results                            
==============================================================================
Dep. Variable:                    age   R-squared:                       0.066
Model:                            OLS   Adj. R-squared:                  0.051
Method:                 Least Squares   F-statistic:                     4.511
Date:                Mon, 27 Jul 2026   Prob (F-statistic):           0.000197
Time:                        13:31:27   Log-Likelihood:                -1654.6
No. Observations:                 389   AIC:                             3323.
Df Residuals:                     382   BIC:                             3351.
Df Model:                           6                                         
Covariance Type:            nonrobust                                         
==============================================================================
                 coef    std err          t      P>|t|      [0.025      0.975]
------------------------------------------------------------------------------
const       -250.9514    302.275     -0.830      0.407    -845.282     343.379
B            146.0844    305.300      0.478      0.633    -454.194     746.363
NK           237.4345    305.290      0.778      0.437    -362.825     837.694
CD4T         301.6834    302.911      0.996      0.320    -293.898     897.265
CD8T         255.9574    303.347      0.844      0.399    -340.482     852.397
Mono         454.6654    304.981      1.491      0.137    -144.987    1054.318
Neutro       297.3502    302.075      0.984      0.326    -296.587     891.287
Eosino     -1944.1266   2114.267     -0.920      0.358   -6101.185    2212.932
==============================================================================
Omnibus:                       24.571   Durbin-Watson:                   1.955
Prob(Omnibus):                  0.000   Jarque-Bera (JB):               20.812
Skew:                           0.487   Prob(JB):                     3.03e-05
Kurtosis:                       2.420   Cond. No.                     5.96e+15
==============================================================================

Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The smallest eigenvalue is 1.71e-29. This might indicate that there are
strong multicollinearity problems or that the design matrix is singular.

Model 2: Age ~ Predicted + Cell types
                            OLS Regression Results                            
==============================================================================
Dep. Variable:                    age   R-squared:                       0.529
Model:                            OLS   Adj. R-squared:                  0.520
Method:                 Least Squares   F-statistic:                     61.01
Date:                Mon, 27 Jul 2026   Prob (F-statistic):           1.99e-58
Time:                        13:31:27   Log-Likelihood:                -1521.7
No. Observations:                 389   AIC:                             3059.
Df Residuals:                     381   BIC:                             3091.
Df Model:                           7                                         
Covariance Type:            nonrobust                                         
==============================================================================
                 coef    std err          t      P>|t|      [0.025      0.975]
------------------------------------------------------------------------------
const        -81.9090    215.246     -0.381      0.704    -505.127     341.309
predicted      0.5628      0.029     19.329      0.000       0.506       0.620
B             77.8498    217.249      0.358      0.720    -349.307     505.007
NK            40.5239    217.452      0.186      0.852    -387.032     468.080
CD4T         101.8267    215.768      0.472      0.637    -322.419     526.072
CD8T          49.1227    216.096      0.227      0.820    -375.768     474.013
Mono         160.7246    217.526      0.739      0.460    -266.977     588.426
Neutro        93.2758    215.185      0.433      0.665    -329.822     516.374
Eosino      -605.2327   1505.890     -0.402      0.688   -3566.129    2355.664
==============================================================================
Omnibus:                        7.954   Durbin-Watson:                   2.055
Prob(Omnibus):                  0.019   Jarque-Bera (JB):                8.000
Skew:                           0.351   Prob(JB):                       0.0183
Kurtosis:                       3.045   Cond. No.                     3.11e+17
==============================================================================

Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The smallest eigenvalue is 1.69e-29. This might indicate that there are
strong multicollinearity problems or that the design matrix is singular.