Let's consider common diseases that a healthy 30 year old can have without noticing any symptoms. E.g. it is known that many people have undiagnosed diabetes, many people have undiagnosed hypothyroidism. Also kidney function can be impaired quite a bit (e.g. due to diabetes) without that leading to symptoms. If we focus on these issues then you could choose to the following test: Glucose and HbA1c to see if the person has diabetes, TSH and T4 to detect hypothyroidism, and creatinine, urea, sodium, potassium to detect problems with the kidneys. Also, measuring HDL and LDL cholesterol can be useful as quite a few young people have too high cholesterol levels.
Now, to make the question better defined, one can ask how to choose some given number of blood tests such that some chosen health criterion, say, the survival probability after ten years is optimized. This can in principle be calculated from the known statistics. To see how to set up this calculation, consider doing just one blood test for disease X.
The patient is in this case selected from a pool of people who do not have any significant symptoms of disease X. So, if X represents diabetes, the patient is currently not complaining about excessive thirsts, feeling tired etc. If X represents kidney disease then the patient is not at the stage where the kidney function is so low that it causes symptoms. This means that the probability that the patient will be found to be suffering from X should be derived from the appropriate conditional probability that conditions on the patient not having any significant symptoms (the symptoms are mild enough for it to be compatible to having no complaints).
For any chosen X you can then calculate the health criterion (e.g. survival after ten years) in the event of a positive test compared to not doing the test. So, this depends on the known effects of early treatment, the probability for detecting X will then yield the expected improvement for this health outcome.