Using linkage studies combined with whole‐exome sequencing to identify novel candidate genes for familial colorectal cancer

Abstract

Colorectal cancer (CRC) is a complex disorder for which the majority of the underlying germline predisposition factors remain still unidentified. Here, we combined whole‐exome sequencing (WES) and linkage analysis in families with multiple relatives affected by CRC to identify candidate genes harboring rare variants with potential high‐penetrance effects. Forty‐seven affected subjects from 18 extended CRC families underwent WES. Genome‐wide linkage analysis was performed under linear and exponential models. Suggestive linkage peaks were identified on chromosomes 1q22–q24.2 (maxSNP = rs2134095; LODlinear = 2.38, LODexp = 2.196), 7q31.2–q34 (maxSNP = rs6953296; LODlinear = 2.197, LODexp = 2.149) and 10q21.2–q23.1 (maxSNP = rs1904589; LODlinear = 1.445, LODexp = 2.195). These linkage signals were replicated in 10 independent sets of random markers from each of these regions. To assess the contribution of rare variants predicted to be pathogenic, we performed a family‐based segregation test with 89 rare variants predicted to be deleterious from 78 genes under the linkage intervals. This analysis showed significant segregation of rare variants with CRC in 18 genes (weighted p‐value > 0.0028). Protein network analysis and functional evaluation were used to suggest a plausible candidate gene for germline CRC predisposition. Etiologic rare variants implicated in cancer germline predisposition may be identified by combining traditional linkage with WES data. This approach can be used with already available NGS data from families with several sequenced members to further identify candidate genes involved germline predisposition to disease. This approach resulted in one candidate gene associated with increased risk of CRC but needs evidence from further studies.

Next Generation Sequencing and Bioinformatics Analysis of Family Genetic Inheritance

“…For instance, a genome wide linkage analysis involving 972 bipolar pedigrees was able to locate with significance a genomic region with variants linked with the disease (Badner et al, 2012). Linkage analysis has been used in combination with WES (e.g., in another study of familial goiter) to inform selection of candidate genes for exome sequencing (Yan et al, 2013) and to identify novel candidate genes for familial colorectal cancer (Toma et al, 2019). Combining linkage analysis with NGS based methods provides the ability to differentiate between novel variants and sequencing artifacts or analytical errors in studies involving multiple unrelated individuals, however, rare variants are expected to co-segregate within a family (Bailey-Wilson and Wilson, 2011).…”

Candidate Gene Discovery in Hereditary Colorectal Cancer and Polyposis Syndromes–Considerations for Future Studies

“…We reviewed these studies following the general setup of candidate discovery studies, which cover cohort composition, variant discovery and prioritization, and variant validation ( Table 1 , Table S1 ). Six studies based discovery on the same cohort that was enlarged over time [ 53 , 64 , 69 , 72 , 75 , 76 ].…”

“…We noted that among the 37 candidate gene discovery studies, FH-based inclusion criteria varied from study to study. Some studies used a relatively broad inclusion criterion such as “one first-degree relative or second-degree relative with CRC” while others applied more stringent criteria “the presence of at least three relatives with CRC, of which at least two in consecutive affected generations and at least one case diagnosed with CRC before the age of 60” ( Table 1 : Inclusion criteria FH) [ 42 , 43 , 48 , 50 , 53 , 56 , 59 , 64 , 69 , 70 , 72 , 75 , 76 ]. Furthermore, phenotypic characteristics strongly associated with hereditary CRC and polyposis syndromes, such as tumor types and age-of-onset strongly varied between, but also within cohorts ( Table 1 : Inclusion criteria index phenotype; Table 1 : Inclusion criteria age).…”

“…Age-based inclusion criteria were applied in twelve out of the 32 unique discovery cohorts [ 13 , 43 , 47 , 49 , 53 , 54 , 56 , 59 , 64 , 65 , 67 , 69 , 70 , 71 , 72 , 75 , 76 ]. However, this age-based inclusion criterion was heterogeneous ranging from an age at diagnosis ≤35 years [ 47 ] to diagnosis <60 years [ 43 ], to at least one relative diagnosed <60 years [ 53 , 64 , 69 , 72 , 75 , 76 ]. The observed heterogeneity within these NGS study cohorts is in contrast with the discovery studies that were performed before the NGS-era, as discovery studies before the NGS-era were directed to families with multiple affected members and a strong phenotype of hCRC and/or polyposis.…”

“…In general, we observed prioritization based on either complete screening of WES or WGS data or, more targeted, by focusing on specific genes or regions that are more likely to be involved in hereditary cancer. The main applied variant prioritization strategies included linkage ( n = 8 studies [ 41 , 43 , 52 , 55 , 61 , 66 , 73 , 75 ]), variants shared among affected relatives or absence of the variant in unaffected relatives ( n = 19 studies [ 41 , 43 , 48 , 51 , 52 , 53 , 55 , 57 , 60 , 61 , 63 , 64 , 66 , 67 , 68 , 69 , 70 , 74 , 76 ]) and gene function ( n = 14 studies [ 13 , 47 , 53 , 57 , 58 , 59 , 63 , 64 , 65 , 71 , 72 , 74 , 75 , 76 ]). Other approaches include the prioritization of recurrent variants ( n = 7 studies [ 13 , 39 , 40 , 44 , 50 , 56 , 65 ]) and prioritization based on expected recessive or dominant mode-of-inheritance ( ...…”