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The performance of some weakly parametric linkage tests in common use was compared on 200 replicates of oligogenic inheritance from Genetic Analysis Workshop 10. Each random sample for the quantitative trait was dichotomized at different thresholds and also selected through 2 affected sibs, generating 8 combinations of sample and variable. The variance component program SOLAR performed best with a continuous trait, even in selected samples, when the population mean was used. The sib-pair program SIBPAL2 was best in most other cases when the phenotype product, population mean, and empirical estimates of pair correlations were used. The BETA program that introduced phenotype products was slightly more powerful than maximum likelihood scores under the null hypothesis and approached but did not exceed SIBPAL2 under its optimal conditions. Type I errors generally exceeded expectations from a χ2 test, but were conservative with respect to bounds on lods. All methods can be improved by use of the population mean, empirical correlations, logistic representation for affection status, and correct lods for samples that favour the null hypothesis. It remains uncertain whether all information can be extracted by weakly parametric methods and whether correction for ascertainment bias demands a strongly parametric model. Performance on a standard set of simulated data is indispensable for recognising optimal methods.

Recently a graphical study of linkage disequilibrium around the CAPN3 locus failed to refine the 1.3-Mb interval suggested by haplotype sharing. On the contrary, the Malecot model as implemented in the ALLASS program maps CAPN3 within 3 kb of its true location (23 kb from the locus midpoint), overcoming identified problems with small samples, interrelated sibships, and short duration.

Sib pair tests for linkage to a quantitative trait or affection status are examined by simulation. A sibship of size s contributes only s-1 independent sib pairs but all s(s-1)/2 pairs are needed for an efficient test. Redundancy increases with sibship size. Using simulated data on the null hypothesis of no linkage, we have considered equal and unequal weights. Unequal weights lose power as measured by the equivalent number of observations, and goodness of fit to the theoretical distribution is degraded. The Fisher z(r) test with equally weighted pairs is more reliable than any t(r) test based on conjectured degrees of freedom, but significance levels must be established by simulation if the number of pairs is small or redundancy is large. An approach to parametric analysis through nuisance parameters is discussed.

Segregation analysis provides a genetic model of disease based upon morbid risks in age-specific classes, from which the model derives genotype-specific morbid risks. In the absence of disease-specific mortality each morbid risk is a cumulative incidence (age-specific penetrance). If disease-specific mortality reduces the number of affected in the older classes, the morbid risk is less than the corresponding penetrance. When counselling individuals with a family history of disease, their genetic risk is a function of penetrances, which can be calculated from morbid risks. We have applied this method to breast, ovarian and colorectal cancer.

Objective: A number of linkage disequilibrium (LD)-based methods have been developed to describe recombination and infer hotspots. We determine the correspondence between LDMAP and LDhat, and between LDMAP and LDhot by comparison with linkage maps and hotspots that have been verified by sperm typing. Methods: Regression and variance analyses were used to compare LDMAP and LDhat with linkage maps. The location and intensity of hotspots inferred by LDMAP and LDhot were compared with fifteen verified hotspots. Results: Despite different methodologies and assumptions, LDMAP, LDhat, and linkage maps are highly concordant. Closer inspection shows that LDMAP corresponds more closely with linkage maps across the genome and on sixteen chromosomes compared with LDhat. LDhot identified fourteen and ten of the verified hotspots using high and low density maps. In comparison, LDMAP identified all fifteen hotspots at high and low density. However, some significant discrepancies between sperm and LD-based recombination rates remain. Conclusions: Combining information from linkage and LDMAP to construct sex-specific high resolution linkage maps suggests that some of these discrepancies may be due to female recombination while others may relate to the age of hotspots. LDMAP based estimates between ∼68,000 and ∼112,000 hotspots in the genome with mean widths less than 4 kb.

The central problem of complex inheritance is to combine evidence from data that typically differ in markers, phenotypes, ascertainment, and other factors, without sacrificing the reliability that lods have given to linkage mapping for major loci. Here we evaluate 5 possible solutions on 200 replicates simulated in Genetic Analysis Workshop 10. Two methods differ from less efficient ones by distinguishing the tails of a normal distribution. Maximum likelihood scores (currently implemented only for the BETA model) and the approach of Self and Liang perform about as well as pooling samples, which is not feasible with heterogeneous data. With moderately heterogeneous data the Self and Liang method appears to be more efficient than maximum likelihood scores. Although improvements are being made in sample design and statistical analysis, the problem of combining linkage evidence from multiple data sets appears to have been solved. Allelic association presents different problems not yet addressed.

Genetic epidemiology faces six critical issues: its scope, genetic mapping, complex inheritance, population structure, nonmendelian genetics, and the internationalization of genetics. To solve these problems the scope must be broadened to include normal variation, although much of descriptive genetics will be lost to related sciences. Genetic mapping continues to play an essential role for positional cloning and chromosome architecture, which sequencing cannot replace. A large part of current effort is devoted to complex inheritance, requiring development of methods to pool multiple studies. The effect of population structure on forensic DNA identification appears to have been solved, but its effect for complex inheritance and genetic loads remains to be clarified. Populational analysis of non-Mendelian genetics has been largely neglected. The infrastructure of genetics must be internationalized if legal and ethical principles are to be supported and genetic epidemiology is to realise its potential.

The genetic basis for colorectal cancer was investigated by complex segregation analysis of a published series of 305 pedigrees ascertained through a large population database. Two hundred and five of the pedigrees were ascertained through patients diagnosed with colorectal cancer before age 55, and 100 from patients diagnosed with colorectal cancer between the ages of 55 and 74. The analysis was carried out using the program POINTER. Using the joint-likelihood approach, the familial aggregation of colorectal cancer was compatible with the inheritance of a dominant gene. The gene frequency of the putative abnormal allele was 0.002 with a lifetime penetrance of 85%. However, under conditional likelihood, this mode of inheritance for a major gene was not favoured. The possible aetiologies of this paradoxical finding are discussed.

Complex genetic models and segregation analysis were applied to family data obtained in a hyperendemic goiter area in Brazil. The single locus and Falconer’s models did not fit the data. Edward’s mode

A mathematical theory is derived for the distribution of heteromorphisms in trisomics and polyploids. Applied to the sparse literature, it appears that most trisomy 21 is due to first division maternal nondisjunction, although there are case reports of second division nondisjunction, both paternal and maternal. Most triploids appear to be due to dispermy or failure of the first meiotic division in the oocyte. The need for larger systematic samples is stressed. This maximum likelihood analysis gives great resolution to epidemiological studies, permitting discrimination of etiological factors acting on fathers and mothers, at different meiotic stages, and on dispermy.

Complex segregation analysis was applied to a sample of 12,293 nuclear families each with at least 1 diabetic patient. The families were divided into two groups depending on the proband's treatment: insulin-dependent (IDG) and insulin-independent (IIG). Heterogeneity analysis has revealed a highly significant difference in the IIG group when families were divided into different mating types. The higher recurrence risk was found in the group with affected mothers. Also evidence for a major recessive gene was found in the IGG group, while it was not possible to distinguish between the hypothesis for absence of a major locus and absence of polygenic inheritance in the IDG group. Risks to develop the disease were calculated for a few typical situations.