PRKACA and PRKACB code for two catalytic subunits (Ca and Cb) of cAMP-dependent protein kinase (PKA), a pleiotropic holoenzyme that regulates numerous fundamental biological processes such as metabolism, development, memory, and immune response. We report seven unrelated individuals presenting with a multiple congenital malformation syndrome in whom we identified heterozygous germline or mosaic missense variants in PRKACA or PRKACB. Three affected individuals were found with the same PRKACA variant, and the other four had different PRKACB mutations. In most cases, the mutations arose de novo, and two individuals had offspring with the same condition. Nearly all affected individuals and their affected offspring shared an atrioventricular septal defect or a common atrium along with postaxial polydactyly. Additional features included skeletal abnormalities and ectodermal defects of variable severity in five individuals, cognitive deficit in two individuals, and various unusual tumors in one individual. We investigated the structural and functional consequences of the variants identified in PRKACA and PRKACB through the use of several computational and experimental approaches, and we found that they lead to PKA holoenzymes which are more sensitive to activation by cAMP than are the wild-type proteins. Furthermore, expression of PRKACA or PRKACB variants detected in the affected individuals inhibited hedgehog signaling in NIH 3T3 fibroblasts, thereby providing an underlying mechanism for the developmental defects observed in these cases. Our findings highlight the importance of both Ca and Cb subunits of PKA during human development.Protein kinase A (PKA) can be found as an inactive tetrameric holoenzyme formed by the association of two catalytic (C) subunits with a regulatory (R) subunit dimer. Activation is achieved through binding of two molecules of cyclic AMP (cAMP) to each R-subunit and subsequent unleashing of the C-subunits to engage substrates. PRKACA

The pLI score reflects the tolerance of a given gene to the loss of function on the basis of the number of protein truncating variants, that is, the frameshift, splice donor, splice acceptor, and stop‐gain variants referenced for this gene in control databases weighted by the size of the gene and the sequencing coverage. It is frequently used to prioritize candidate genes when analyzing whole exome or whole genome data. We list here the main pitfalls to consider before using this score. Concrete illustrations are given for each of these pitfalls.

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