The crucial element of the one-step approach that leads to unbiased point estimates is the inclusion of the appropriate probabilistic measurement model so that the estimation takes into account the unreliability of the measurement. The probabilistic modelling allows for the fact that twins with identical response patterns may have different scores on the latent trait, and also, that twins with non-identical response patterns may have exactly the same score on the latent trait. Discriminatory power of the items and the number of items are both crucial to the heritability estimated based on sum scores: the fewer the items and the worse the discrimination of the items (i.e., the smaller the variance of the latent trait in the one-parameter model; the smaller the factor loadings in the two-parameter model), the more biased the estimation will be when the analysis is performed on sum scores. High quality scales with a large number of items (say, more than 50) with high discriminatory power that are scattered across the entire scale can indeed be analysed with sum scores, but any other scale should be analysed using the IRT framework if one is interested in an unbiased heritability estimate with trustworthy confidence intervals.
