Mapping of genes involved in rare recessive diseases is usually difficult because of the lack of families with more than one affected progeny. The problem may be avoided by using inbred affected individuals and the strategy of homozygosity mapping.

In practice, the use of homozygosity mapping in a genome-wide scan requires that a set of markers regularly spaced and spanning the whole genome are tested. Investigators are then faced to the problem of choosing the spacing of markers.

To help solve this problem, we give some useful clues by computing (1) the expected length of the region of identity by descent around the disease locus, (2) the distribution, given the spacing of markers, of the number of affected individuals expected not to be homozygous at the marker closest to the disease locus and, (3) the expected type-one error. We show that even if the markers are very closely spaced, it is not unlikely that some affected individuals in the sample will not be homozygous at the marker closest to the disease locus. Excluding a region by the criterion that all affected individuals in the sample are not homozygous may then dramatically increase the rate of false negatives. We thus propose to relax the criterion to declare a region candidate, based on the sample size and the spacing of markers.

For this study we consulted the Bone Marrow Donors' Registry of Lombardy (Italy) and analyzed 43937 HLA-A,B phenotypes and 13922 HLA-A,B,DR phenotypes. We estimated the HLA-A,B and HLA-A,B,DR haplotype frequencies via the maximum-likelihood method. We analyzed the genetic structure of the 11 provinces of Lombardy by means of Principal Component Analysis and Correspondence Analysis, and estimated the variety of the different haplotypes at provincial level and the percentage of unique phenotypes at village level. We found 11189 different HLA-A,B phenotypes, 661 different HLA-A,B haplotypes and more than 4000 different HLA-A,B,DR haplotypes. We identified 20 villages, in Western Lombardy, very rich in unique/rare phenotypes. Here we report a formula which allows the identification of a putative donor matched for two haplotypes with a recipient. This result may be of great importance for the genetic study of the population of Lombardy and, even more, for bone marrow transplantation programs.

Nonrandom associations between DNA polymorphisms are commonly tested by Fisher's exact test in spite of it is seriously conservative. Theoretical statistical studies have shown that the exact test with Tocher's correction does not present this problem but Tocher's correction is never used by experimentalists for detecting gametic associations. We have examined the practical consequences of using these two alternative tests for the detection of nonrandom associations in populations. A total of 1566 pairs of RFLPs of eleven gene regions and sixteen populations from previously published human and Drosophila disequilibrium data were examined. The analysis reveals remarkable differences between the two tests for detecting gametic associations. In some gene regions, the exact test with Tocher's correction detects a percentage of significant associations between RFLPS which is twice or three times higher than that detected by the exact test without correction. Therefore, the widely used exact test can be seriously underestimating disequilibrium in populations. In addition, the study shows that the standard chi-square test for independence in 2 × 2 tables detects a similar percentage of significant associations between RFLPs than Tocher's test.

Twenty-two cases with Turner syndrome features were subjected to standard cytogenetic techniques using giemsa trypsin (GTG-) banding then fluorescence in situ hybridization (FISH) using a specific whole-X chromosome painting probe, Quint-Essential Y-specific DNA probe (AMELY) for Yp11.2, alpha-satellite (DYZ3) probe and X/Y cocktail-alpha satellite probe (ONCOR) for confirmation of the initial diagnosis and comparison of the two techniques. Eight cases (36%) showed the same karyotype results by both techniques [5 cases: 45,X/46,XX, 2 cases: 45,X/46,X,i(Xq) and one case with a triple cell line 45,X/46,XX/47,XXX]. In the other 14 cases (64%) the FISH technique has identified a third cell line in 7 cases (32%), delineated the origin of the marker in 5 cases (23%) to be derivative X and clarified the deletion of the Yp11.2 region in 2 cases (9%) with the 45,X/46,XY karyotype. The application of FISH has highlighted the differences between the initial diagnosis based on the standard cytogenetic technique and the final diagnosis determined by the application of DNA probes specific for the X and Y chromosomes. FISH proved useful in detection of the low frequency cell lines which need analysis of a large number of metaphase spreads by GTG-banding, helped in identifying the nature and the origin of the unknown markers which has an important implication in the development of gonadal tumours and delineated the deletion of the Yp11.2 region in the 45,X/46,XY Turner patients.

The history of Hungary starts in the 9th century with the arrival of the Magyars in the Carpathian Basin. They spoke, like modern Hungarians, an Uralic language belonging to the Finno-Ugric language group. Their original composition probably included Iranian and Turkish people, while other populations were already present in the territory (Avars, Slavs, Germans). Some of the Hungarian ethnic groups claim to be descendants of ancient Magyars settlers (such as the Örség), others of Huns, Turks or Iranians. We collected and compared the previously published gene frequencies of eight ethnic groups and seven hypothetical ancestral populations, including Uralics, applying a model of admixture. The results, most of which confirm historical hypotheses or the oral tradition, show that only one ethnic group (Örség) highly resembles the Uralic population.

Unlike monogenic diseases for which considerable progress has been made in past years, the identification of susceptibility genes involved in multifactorial diseases still poses numerous challenges, including the development of new statistical methodologies. Recently, several authors have advocated the use of the estimating equations (EE) approach as an alternative to standard maximum likelihood methods for analysing correlated data. Since most genetic studies rely on family data, the EE found a natural field of application in genetic epidemiology. The objective of this review is to give a brief description of the EE principles, and to outline its applications in the main areas of genetic epidemiology, including familial aggregation analysis, segregation analysis, linkage analysis and association studies.

We applied a complex segregation analysis to 46 pedigrees with a total of 121 nuclear families and 660 individuals, to verify hypotheses regarding the inheritance of OFC and linkage with markers on chromosomes 6 and 2. The POINTER program for segregation analysis strongly rejected the hypothesis of no familial transmission of OFC in these families. When the hypothesis of a two-locus model was tested with COMDS, the analysis showed the presence of at least two loci and the model assuming a dominant major gene and a recessive modifier locus was statistically accepted. Given the fitted two-locus model, we tested for a possible linkage between the major OFC locus and the two markers studied. For D6S259, the estimate of the recombination fraction was θ=0.098, corresponding to a LOD score around 2.1. On the contrary, the data analysis concerning the D2S378 marker showed an estimate of the recombination fraction not significantly different from the independence hypothesis.

Every science has roots that antedate acceptance as a discipline. Neglecting these intimations, there is a consensus that population genetics became a recognised science about 1920, and that it split into two branches about 1960. One branch is concerned with historical processes, uniting genetics with anthropology and (in other species) with paleontology and taxonomy. The other branch is concerned with inheritance in contemporary populations, uniting genetics with epidemiology, medicine, psychology, and (in other species) with agriculture. Anthony Edwards (1995) identified this dichotomy as ‘differential-equation biology’ vs ‘statistical biology’. The distinction becomes fastidious when current gene frequencies are taken as indirect evidence for selection by disease in the remote past: such inference from a unique event is more characteristic of evolutionary genetics but concerns all population geneticists. From time to time interest groups are formed around twins, behaviour, demography, or quantitative traits, but they are generally recognised as aspects of genetic epidemiology. If the young science is in jeopardy, it is not by fission but by exclusion of studies that are only indirectly related to disease, which provides a focus but does not specify the contents. I will argue that every aspect of population genetics that is not primarily concerned with evolution is part of genetic epidemiology, and that the field must suffer if it is not inclusive. As with all human activity progress is punctuated, often cyclical, and therefore suggests the real and apparent movement of celestial bodies for which the language of astronomy is appropriate.

Direct identity-by-descent mapping is a technique for narrowing down the location of the gene or genes responsible for a given genetic disease to small segments of the genome. The technique involves DNA comparisons between pairs of affected individuals. The data generated are in the form of matching segments of the genome, representing regions likely to be identical-by-descent (IBD). Regions in the genome over which there are significantly more segments aligned than is expected by chance are taken as candidate regions for the disease gene or genes. Due to the complex geometric nature of the data, significance testing involves certain mathematical difficulties. We present here a new method for measuring this significance. This method introduces a novel statistic and is appropriate whether or not the relationships between the paired individuals are known. We give examples that we have calculated by implementing this method, including an application to real data.

The 1080-bp coding region of the human plasma α(1,3)fucosyltransferase gene (FUT6) was sequenced in a total of 161 individuals (322 chromosomes) drawn from three populations, involving 56 Africans (Xhosa), 52 European-Africans of South Africa, and 53 Japanese. In addition to six reported base substitutions, eleven new base substitutions and a single base insertion were found in the coding region of the FUT6. Eleven functional and four null alleles were encountered, of which 10 alleles were novel alleles identified in this study. Two null alleles have been identified previously, whereas two novel null alleles, which contained a single base (cytosine) insertion at nucleotide 499, were found in a Xhosa population. The allelic distributions of FUT6 were different among these three populations. The heterozygosity of FUT6 was 0.860, 0.699, and 0.632, in Xhosa, European-African (South Africa), and in Japanese populations, respectively. The extensive DNA sequence diversity of the FUT6 may be suitable for application as a tool in genetic studies for modern human evolution.

To dissect the genetic pathway of hypertension, we measured angiotensinogen in 685 members of 186 families recruited from a rural community in southwest Nigeria. Commingling and segregation analyses were carried out. A mixture of two and/or three distributions fits the data significantly better than a single distribution in commingling analysis, suggesting a major gene effect. Segregation analysis confirmed that a recessive major gene model for low values of angiotensinogen provides the best fit to the data and about 13% of the variance was due to the recessive gene segregation.

Between January 1992 and January 1995 a total of 24233 babies born consecutively in Corniche Hospital which is the only maternity hospital in Abu Dhabi, the capital of UAE, were surveyed for the presence of major congenital malformations. A total of 401 infants (16.6/1000) had a major defect. Of these malformations, 267 (67%) were associated with an estimated recurrence risk greater than 1%, and 95 (24%) carried an estimated recurrence risk greater than 10%. This included a total of 91 cases of single gene disorders and 4 cases of cleft lip and palate where a mother and another sibling were affected putting their estimated recurrence risk in the high category group. When antenatal diagnosis is feasible, this should be considered in 60% of mothers (a total of 242). In 59% (a total of 237) the estimated recurrence risk was >1% and the antenatal diagnosis of the disorder was possible. The importance of Genetic Counselling is revealed in our study since more than three quarters of mothers were under 36 years old, and may well plan future pregnancies.

Two sets of markers and populations were considered in this study: (a) the variability at 17 protein loci and in the sequences of the first hypervariable segment of the mitochondrial DNA (mtDNA) were compared in 10 South American Indian tribes, in a total 3016 and 241 individuals, respectively; and (b) a triple comparison was made, in relation to 17 protein, mtDNA and six hypervariable tandem repeat loci in four Brazilian Indian tribes, involving 1567, 56 and 194 persons, respectively. Both the intrapopulational diversities and the population relationships obtained in these groups with these different sets of markers showed no significant correlation. High levels of heterogeneity were observed both at the protein and hypervariable individual loci, as well between mtDNA sites. The different positions observed for the Yanomama (but not for the other nine tribes) in the trees which summarized the protein and mtDNA data suggest some degree of asymmetric interchange related to sex between them and neighbouring tribes.

Patterns of dystrophin gene deletions in DMD/BMD patients were compared in four populations: Turks (n = 146 deletions), Europeans (n = 838), North Indians (n = 89), and Indians from all over India (n = 103). Statistical tests revealed that there are differences in the proportions of small deletions. In contrast, the distribution of deletion breakpoints and the frequencies of specific deletions commonly observed in the four populations are not significantly different. The variations strongly suggest that sequence differences exist in the introns, and the differences are in agreement with genetic distances among populations. The similarities suggest that some intronic sequences have been conserved and that those will trigger recurrent deletions, since it is unlikely that gene flow would disperse the deleted chromosomes, which vanish from the gene pool in a few generations.

Studies of rare Mendelian disorders of low density lipoprotein cholesterol (LDL-C) metabolism have identified specific genetic mutations in the LDL receptor and apolipoprotein B. Although these rare mutations account for a small proportion of LDL-C variation, twin and adoption studies indicate that at least 50% of the overall LDL-C observed variation is genetically determined. In a heterogeneous sample of 3227 subjects from the NHLBI Family Heart Study collected from four US centres, we find evidence for a common major gene accounting for mild elevations (1.25 standard deviations) in LDL-C. The analysis favored a recessive model with a frequency of 0.52 for the gene influencing elevated LDL-C, phenotypic means of 113 mg/dl for the normal genotypes and 146 mg/dl for the abnormal genotype, and a significant polygenic heritability. This statistically-inferred major gene accounted for 24% of the variation in LDL-C, with polygenes accounting for another 28% of the variation. Using parameters for major gene transmission estimated in the segregation analysis, LDL-C showed no linkage to the LDL receptor gene (LDLR), nor to the apolipoprotein E gene (APOE), nor to the cholesterol 7α-hydroxylase gene (CYP7A1), indicating the major gene effect influencing mild elevation in LDL-C is not explained by any of these candidate loci.

Carriers of X-linked juvenile retinoschisis (RS) were previously suggested to give birth to an excess of boys. We determined the carrier status for the 214G > A mutation of the RS1 gene in 202 females belonging to a large RS founder pedigree. The secondary sex ratio (SSR) in the offspring of 149 carriers was 129.8 (z = 2.25), which differed significantly from that of the Finnish population (SSR 106) but not from that of 53 non-carrier females belonging to the same pedigree (SSR 116.7; z = 0.51). Since possible causes for the skewed SSR include factors affecting fertilisation, implantation and embryonic death, we searched for expression of RS1 in various placental and uterine cells and found that, in addition to the retina, RS1 is expressed in the uterus. We hypothesize that the RS1 protein has a role in implantation or embryonic survival.

We identified pepsinogen C (PGC) gene polymorphisms by means of PCR, which amplified DNA in the region within the intron between exons 7 and 8, and by 6% polyacrylamide gel electrophoresis. Six alleles were found in a Japanese population. The frequencies of these alleles in 408 unrelated Japanese individuals were 0·074, 0·026, 0·335, 0·237, 0·016 and 0·314, respectively. The serum pepsinogen II level significantly decreased in the order of the allele 6 homozygote, the allele 6 heterozygote and the other genotypes (χ2=7·850, D.F.=2, p=0·020). These findings indicated that the genetic background of serum pepsinogen should be considered when screening for stomach cancer by this procedure.

A score statistic for testing the Hardy–Weinberg law for data sampled from several populations with different allele frequencies is derived assuming a common coefficient of disequilibrium (odds ratio-type) across strata. The assumption can be examined by a chi-square goodness-of-fit test. It is unlikely such a model would be rejected in typical studies involving human populations. Under this model, a Wald-type test has substantially less power than the score test. An approximate formula for the sample size required for a specific power of the stratified score test for detecting departure from equilibrium is given.

Typically genetic studies of continuous traits such as cholesterol levels or blood pressure assume that interindividual variability follows a normal distribution. Here we develop methods to analyze positively skewed data by assuming a lognormal distribution. We develop a variance components approach for identifying such effects from a major gene, residual polygenic factors and nongenetic factors. We compare by a simulation study results from fitting this lognormal model with either applying the log transformation or not transforming the data. We found that the lognormal model provided more precise estimates and more powerful tests than a simple log transformation when analyzing lognormally distributed data. Power varied with sibship size. For the same total number of nonindependent sibpairs, larger sibships were less powerful. However, larger sibships are more economical because they require a smaller sample size to obtain a specified power. To illustrate the application of this lognormal model to real data, we studied evidence for linkage between triglycerides and the lipoprotein lipase gene.

Replication error (RER) is defined as mutation events in repetitive DNA segments. To investigate further the RER phenomenon and reveal any differences in mutation outcome between different short tandem repeat (STR) loci, we have investigated the somatic mutation rate and the size distribution of new tumour alleles in four tetranucleotide STRs in a large material of unselected colorectal adenocarcinomas. DNA was extracted from the blood and carcinomas of 217 patients. All blood/tumour pairs were analysed using the STRs HUMTHO1, HUMFES/FPS, HUMVWA31/A and HUMF13A1. Mutations are detected at all four loci. There are substantial differences in mutation rate and mutation direction (i.e. expansion versus contraction) between different STR loci. In all four STRs, the majority of events represent gain or loss of a single repeat. Almost all new tumour alleles correspond to known alleles in a population database, indicating that these are also composed of integers of the four base pair repeat. There is no statistically significant size bias in the mutating alleles as compared to the allelic distribution in the population database.