Chapter 26
Medicine and Disease
The question that this chapter tries to answer is, “what use is bioinformatics for
medicine?” Medicine is primarily concerned with the cure of ill health, and the
maintenance of good health. 1 The connexion between DNA and illness once seemed
clear. Some diseases have a clear genetic signature. Well-characterized diseases such
as sickle-cell anaemia, known to be caused by a single point mutation in the gene
coding for haemoglobin, seemed to provide solid confirmation of the “one gene,
one enzyme” hypothesis. Another example of a genetic disease: normal individuals
have about 30 repeats of the nucleotide triplet CGG, whereas patients suffering from
fragile X syndrome have hundreds or thousands.
On the other hand, many common diseases (e.g., asthma, diabetes and epilepsy)
appear to have a genetic basis but lack the simple patterns of inheritance that would
allow one to infer that they are the result of disorder in a single gene. Such polygenic
diseases are likely much more common than single-gene diseases. Furthermore,
their incidence is known to be increasing and, although this is often attributed to
environmental factors, it has been argued that it is a result of population mixing, 2
itself a corollary of globalization; the mixing tends to reintroduce susceptibility genes
exogenously, which endogenously had been selected against (it can be assumed that
the populations being mixed, having previously existed in different environments,
have different sets of susceptibilities and resistances). Note the contrast with the
benefits of mixing for diminishing the incidence of single-gene recessive diseases. 3
1 Some would also argue for a preventive role, but the primacy of the curative purpose is indisputable.
See Ramsden (2021) for more discussion.
2 Awdeh and Alper (2005), Awdeh et al. (2006).
3 The antithesis of polygenicity, pleiotropy (one gene affecting many traits), has been shown in at
least one case to stabilize coöperation (Foster et al. 2004)—cf. Sect. 4.1.1.
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J. Ramsden, Bioinformatics, Computational Biology,
https://doi.org/10.1007/978-3-030-45607-8_26
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