Amorim, C. E. G., Gao, Z., Baker, Z., Diesel, J. F., Simons, Y. B., Haque, I. S., … Przeworski, M. (2017). The population genetics of human disease: The case of recessive, lethal mutations. PLOS Genetics, 13(9), e1006915. (open access)
The news headlines promoting this paper said that it confirmed mutation selection balance theory. But it didn’t.  The authors looked at 417 mutations in 32 genes that cause recessive lethal disorders that cause death or failure of reproduction, such as cystic fibrosis. They estimated allele frequencies based on mutation and selection rates and compared those to actual rates.  Actual rates were higher, much higher, for many mutations  For .nonCpGtv mutations, rates were 30fold higher on average, for nonCpGti mutations rates were 15-fold higher on average. They note that rarer mutations that cause fatal outcomes are less likely to have been found, and the possible role of balancing selection and four other explanations.  However, over all, this  does not seem to be a robust confirmation of our ability to predict allele prevalence rates using accepted parameters and mutation selection balance theory; instead it poses questions about exactly why the predicted rates are so much higher than the actual rates.  
Author summary
What determines the frequencies of disease mutations in human populations? To begin to answer this question, we focus on one of the simplest cases: mutations that cause completely recessive, lethal Mendelian diseases. We first review theory about what to expect from mutation and selection in a population of finite size and generate predictions based on simulations using a plausible demographic scenario of recent human evolution. For a highly mutable type of mutation, transitions at CpG sites, we find that the predictions are close to the observed frequencies of recessive lethal disease mutations. For less mutable types, however, predictions substantially under-estimate the observed frequency. We discuss possible explanations for the discrepancy and point to a complication that, to our knowledge, is not widely appreciated: that there exists ascertainment bias in disease mutation discovery. Specifically, we suggest that alleles that have been identified to date are likely the ones that by chance have reached higher frequencies and are thus more likely to have been mapped. More generally, our study highlights the factors that influence the frequencies of Mendelian disease