Representative principal coordinate analysis (PCoA) plots for different patterns of sex dependencies in disease-associated molecular abundance changes (using simulated data; the patterns are idealized for illustrative purposes, whereas in real data sets mixtures of different patterns as well as stronger influences of noise and biases would be expected). Top left: Sex-specific change (here only male patients); top right: Sex-dimorphic change (i.e. divergent changes between female and male patients); lower left: Sexmodulated changes (i.e. deviations of the patient from control data in both sexes, but with significantly stronger deviations in one sex than in the other); bottom right: Sex-neutral changes (i.e. the deviation of patient data from control data is similar for both sexes; see also the corresponding box plot examples in Fig. 3). The intentional simplicity of these PCoA emphasizes the conceptual nature of these patterns, facilitating understanding of fundamental principles in sex-based analyses of complex diseases.