Isolated or nonsyndromic cleft lip with or without cleft palate (CL/P) is a common birth defect with a complex etiology. A 10-cM genome scan of 388 extended multiplex families with CL/P from seven diverse populations (2,551 genotyped individuals) revealed CL/P genes in six chromosomal regions, including a novel region at 9q21 (heterogeneity LOD score [HLOD]=6.6). In addition, meta-analyses with the addition of results from 186 more families (six populations; 1,033 genotyped individuals) showed genomewide significance for 10 more regions, including another novel region at 2q32-35 (P=.0004). These are the first genomewide significant linkage results ever reported for CL/P, and they represent an unprecedented demonstration of the power of linkage analysis to detect multiple genes simultaneously for a complex disorder.

A dozen genes/regions have been confirmed as genetic risk factors for oral clefts in human association and linkage studies, and animal models argue even more genes may be involved. Genomic sequencing studies should identify specific causal variants and may reveal additional genes as influencing risk to oral clefts, which have a complex and heterogeneous etiology. We conducted a whole exome sequencing (WES) study to search for potentially causal variants using affected relatives drawn from multiplex cleft families. Two or three affected second, third, and higher degree relatives from 55 multiplex families were sequenced. We examined rare single nucleotide variants (SNVs) shared by affected relatives in 348 recognized candidate genes. Exact probabilities that affected relatives would share these rare variants were calculated, given pedigree structures, and corrected for the number of variants tested. Five novel and potentially damaging SNVs shared by affected distant relatives were found and confirmed by Sanger sequencing. One damaging SNV in CDH1, shared by three affected second cousins from a single family, attained statistical significance (P = 0.02 after correcting for multiple tests). Family-based designs such as the one used in this WES study offer important advantages for identifying genes likely to be causing complex and heterogeneous disorders.

Supplementary data are available at Bioinformatics online.