Objective:
Familial cerebral cavernous malformation (CCM) is an autosomal dominant disease caused by mutations in
CCM1
,
CCM2
or
CCM3
, and characterized by multiple brain lesions that can lead to intracerebral hemorrhage (ICH), seizures, and neurological deficits. Carriers of the same mutation can manifest variable symptoms and severity of disease, suggesting the influence of modifiers. As the three CCM proteins form a trimeric complex
in vitro
and interact with many other proteins, we hypothesized that variants in
CCM1-2-3
and in other genes encoding proteins involved in CCM signaling modify disease severity, as manifested by ICH and greater total or large lesion counts.
Methods:
We analyzed 188 Hispanic CCM1 patients harboring the common Hispanic mutation (CHM,
CCM1
Q455X). ICH and lesion counts at enrollment were obtained by clinical assessment and MRI. Samples were genotyped on the Affymetrix Axiom Genome-Wide LAT1 Human Array. We analyzed 504 variants (MAF≥1%) within +/- 5kb of 42 genes for association with ICH, total and large (≥5 mm in diameter) lesion counts, adjusting for age, gender and family structure.
Results:
At baseline, 30.3% of CCM1-CHM patients had a history of ICH. Mean total lesion count was 60.1 ± 115.0 (range 0 to 713). Mean large lesion count was 4.9 ± 8.7 (range 0 to 104). Two
NTRK1
variants (rs41267423 and rs1800879) as well as
SLMAP
rs7621574 and
PCDHGA1
rs17097189 were significantly associated with ICH (
P
≤0.014). Suggestive associations with ICH (
P
≤0.05) were observed for additional 15 variants in 11 genes.
RAP1GAP
rs2625408 was associated with both total and large lesion counts (
P
≤0.004) and additional 4 variants in 4 genes were associated with one of these phenotypes. No single variant was associated with both ICH and total or large lesion count; however, different variants in
RAP1GAP
and
KDR
genes were associated with all three phenotypes tested.
Conclusions:
Variants in genes involved in CCM signaling may contribute to variability in CCM1 disease severity. Genotypes that replicate in other cohorts might be useful as predictors in clinical management.