SummaryThe present study performed a segregation analysis of a cohort of first-degree relatives (FDR) of glioma patients. The families with two or more gliomas were also expanded to determine if any more gliomas could be detected, and if any other types of cancers were associated. These glioma-prone families (n = 24/432) were extended to include first-, second-and third-degree relatives (n = 807) and a cohort was assembled, the standardized incidence risk for other types of cancer calculated and the pedigrees investigated for a possible mode of inheritance. A segregation analysis of the 2141 FDR in 297 families, performed using the Pointer software, did not clearly reject a multifactorial model Ï 2 (3) = 6.13, P < 0.2. However, when letting all parameters be free, the recessive model provided the best fit. In the extended families, no increased risk of other types of cancer was found. This population-based study proposes that familial glioma occurs in about 5% of all glioma cases and that 1% have a possible autosomal dominant inheritance. This first segregation analysis performed in familial glioma must be cautiously interpreted, but an autosomal recessive gene provided the best fit, which could possibly explain 2% of all glioma cases. and pathology records. The complex segregation analysis was performed with the POINTER software (Morton et al, 1983). Since Pointer cannot accept pedigrees, the 297 families were divided into 504 nuclear families, one subset of nuclear families including siblings and parents of the proband and one subset of nuclear families including spouse and children of the proband. It was thus a mixture of complete and incomplete selection, since ascertainment through both parents and children was used. Data for the 257 wives or husbands could not be collected from the questionnaire and were coded as unaffected and having the same age as the proband. The segregation analysis was performed under the mixed model, which assumes the familial aggregation to be due to a major gene, a multifactorial component and a random environmental component, each acting independently. The estimated parameters are: H = multifactorial heritability; q = the estimated gene frequency of the major locus in the population; t = displacement between the homozygous means in standard deviations; d = degree of dominance, where d = 0 corresponds to an autosomal recessive gene and d = 1 corresponds to an autosomal dominant gene. Each person was assigned to one of nine liability classes since the risk of being affected varies with age ( Table 1). The risk of being affected was defined by Iselius et al (1991), as indicated by the formula:R j is the risk of being affected (morbid risk), I j is the cumulative incidence to the midpoint of the jth age interval and M j-i is the disease-specific mortality to the end of the preceding age interval. The incidence and mortality rates for glioma in each class (Ij) were calculated from the Regional Cancer Registry for Northern Sweden during the years 1958-1994. The age of each case was set...