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 n of blood tests (say n = 10) such that the survival probability after, say, ten years is optimized. This can be calculated from the known statistics.  You can calculate the conditional probability that a blood test for some disease X yields a positive result given that the person hasn't got any symptoms yet. If the patient has disease X and doesn't yet have any symptoms then that yields some survival probability after ten years depending on whether the patient receives treatment or not.


After a blood test for some disease X, we have:

P(surviving after ten years) =  P(X|looks healthy)*P(surviving after ten years with diagnosed X without symptoms from start|X) +  P(not X|looks healthy)*P(surviving after ten years|not X)

And then you choose X so that this is maximized.