Mutations in phospholipase C epsilon 1 are not sufficient to cause diffuse mesangial sclerosis.

Diffuse mesangial sclerosis occurs as an isolated abnormality or as a part of a syndrome. Recently, mutations in phospholipase C epsilon 1 (PLCE1) were found to cause a nonsyndromic, autosomal recessive form of this disease. Here we describe three children from one consanguineous kindred of Pakistani origin with diffuse mesangial sclerosis who presented with congenital or infantile nephrotic syndrome. Homozygous mutations in PLCE1 (also known as KIAA1516, PLCE, or NPHS3) were identified following genome-wide mapping of single-nucleotide polymorphisms. All affected children were homozygous for a four-basepair deletion in exon 3, which created a premature translational stop codon. Analysis of the asymptomatic father of two of the children revealed that he was also homozygous for the same mutation. We conclude this nonpenetrance may be due to compensatory mutations at a second locus and that mutation within PLCE1 is not always sufficient to cause diffuse mesangial sclerosis.

A comparison of methods to detect recombination hotspots.

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 approximately 68,000 and approximately 112,000 hotspots in the genome with mean widths less than 4 kb.

Into the post-HapMap era.

The HapMap Project has shifted genetic epidemiology of complex inheritance away from linkage into association mapping of genes affecting disease and response to therapy. Starting with a physical map produced by the Human Genome Project and recent investigation of structural polymorphisms in HapMap samples, population-specific linkage disequilibrium (LD) maps that accurately reflect the fine structure of blocks and steps have been created for use in association mapping, and by interpolation to increase the resolution of linkage maps. All this evidence can be integrated by meta-analysis if expressed as an estimated location and its standard error, a property apparently unique to composite likelihood, recently freed from autocorrelation by permutation of affection status. Methods that do not estimate a standard error are easier to apply, but may be misleading if a causal marker has not been typed. The month of June 2007 saw advances in genome-wide association scans (GWAS) for several diseases. Many questions remain to be answered if genetic epidemiology is to continue the significant contribution to medicine that its definition promises and its history illustrates.

A history of association mapping.

The current exciting developments in association mapping are founded on theory, which has been developed since the beginning of the last century. I hereby review these developments in their historical context.

Effects of single SNPs, haplotypes, and whole-genome LD maps on accuracy of association mapping.

We describe an association mapping approach that utilizes linkage disequilibrium (LD) maps in LD units (LDU). This method uses composite likelihood to combine information from all single marker tests, and applies a model with a parameter for the location of the causal polymorphism. Previous analyses of the poor drug metabolizer phenotype provided evidence of the substantial utility of LDU maps for disease gene association mapping. Using LDU locations for the 27 single nucleotide polymorphisms (SNPs) flanking the CYP2D6 gene on chromosome 22, the most common functional polymorphism within the gene was located at 15 kb from its true location. Here, we examine the performance of this mapping approach by exploiting the high-density LDU map constructed from the HapMap data. Expressing the locations of the 27 SNPs in LDU from the HapMap LDU map, analysis yielded an estimated location that is only 0.3 kb away from the CYP2D6 gene. This supports the use of the high marker density HapMap-derived LDU map for association mapping even though it is derived from a much smaller number of individuals compared to the CYP2D6 sample. We also examine the performance of 2-SNP haplotypes. Using the same modelling procedures and composite likelihood as for single SNPs, the haplotype data provided much poorer localization compared to single SNP analysis. Haplotypes generate more autocorrelation through multiple inclusions of the same SNPs, which could inflate significance in association studies. The results of the present study demonstrate the great potential of the genome HapMap LDU maps for high-resolution mapping of complex phenotypes.

Mapping a gene for rheumatoid arthritis on chromosome 18q21.

Although single chi-square analysis of the North American Rheumatoid Arthritis Consortium (NARAC) data identifies many single-nucleotide polymorphisms (SNPs) with p-values less than 0.05, none remain significant after Bonferroni correction. In contrast, CHROMSCAN evades heavy Bonferroni correction and auto-correlation between SNPs by using composite likelihood to model association across all markers in a region and permutation to assess significance. Analysis by CHROMSCAN identifies a 36-kb interval that includes the most significant SNP (msSNP) observed in a 10-Mb target suggested by linkage. Unexpectedly, stratification by gender and age of onset shows that association evidence comes almost entirely from females with age of onset less than 40. Combining evidence from a meta-analysis of linkage studies and three subsets of the NARAC data provides significant evidence for a determinant of rheumatoid arthritis in a 36-kb interval and illustrates the principle that estimates of location and its information are more powerful than estimates of p-values alone.

Fifty years of genetic epidemiology, with special reference to Japan.

Genetic epidemiology deals with etiology, distribution, and control of disease in groups of relatives and with inherited causes of disease in populations. It took its first steps before its recognition as a discipline, and did not reach its present scope until the Human Genome Project succeeded. The intimate relationship between genetics and epidemiology was discussed by Neel and Schull (1954), just a year after Watson and Crick reported the DNA double helix, and 2 years before human cytogenetics and the Japan Society of Human Genetics were founded. It is convenient to divide the next half-century into three phases. The first of these (1956-1979) was before DNA polymorphisms were typed, and so the focus was on segregation and linkage of major genes, cytogenetics, population studies, and biochemical genetics. The next phase (1980-2001) progressively identified DNA polymorphisms and their application to complex inheritance. The last phase began with a reliable sequence of the human genome (2002), followed by exploration of genomic diversity. Linkage continues to be useful to study recombination and to map major genes, but association mapping gives much greater resolution and enables studies of complex inheritance. The generation now entering human genetics will have collaborative opportunities undreamed of a few years ago, without the independence that led to great advances during the past half-century.

Extended tracts of homozygosity in outbred human populations.

Long tracts of consecutive homozygous single nucleotide polymorphisms (SNPs) can arise in the genome through a number of mechanisms. These include inbreeding in which an individual inherits chromosomal segments that are identical by descent from each parent. However, recombination and other processes break up chromosomal segments over generations. The longest tracts are therefore to be expected in populations with an appreciable degree of inbreeding. We examined the length, number and distribution of long tracts of homozygosity in the apparently outbred HapMap populations. We observed 1393 tracts exceeding 1 Mb in length among the 209 unrelated HapMap individuals. The longest was an uninterrupted run of 3922 homozygous SNPs spanning 17.9 Mb in a Japanese individual. We find that homozygous tracts are significantly more common in regions with high linkage disequilibrium and low recombination, and the location of tracts is similar across all populations. The Yoruba sample has the fewest long tracts per individual, consistent with a larger number of generations (and hence amount of recombination) since the founding of that population. Our results suggest that multiple-megabase-scale ancestral haplotypes persist in outbred human populations in broad genomic regions which have lower than average recombination rates. We observed three outlying individuals who have exceptionally long and numerous homozygous tracts that are not associated with recombination suppressed areas of the genome. We consider that this reflects a high level of relatedness in their ancestry which is too recent to have been influenced by the local recombination intensity. Possible alternative mechanisms and the implications of long homozygous tracts in the genome are discussed.

Linkage disequilibrium maps and association mapping.

The causal chain between a gene and its effect on disease susceptibility cannot be understood until the effect has been localized in the DNA sequence. Recently, polymorphisms incorporated in the HapMap Project have made linkage disequilibrium (LD) the most powerful tool for localization. The genetics of LD, the maps and databases that it provides, and their use for association mapping, as well as alternative methods for gene localization, are briefly described.

Impact of population structure, effective bottleneck time, and allele frequency on linkage disequilibrium maps.

Genetic maps in linkage disequilibrium (LD) units play the same role for association mapping as maps in centimorgans provide at much lower resolution for linkage mapping. Association mapping of genes determining disease susceptibility and other phenotypes is based on the theory of LD, here applied to relations with three phenomena. To test the theory, markers at high density along a 10-Mb continuous segment of chromosome 20q were studied in African-American, Asian, and Caucasian samples. Population structure, whether created by pooling samples from divergent populations or by the mating pattern in a mixed population, is accurately bioassayed from genotype frequencies. The effective bottleneck time for Eurasians is substantially less than for migration out of Africa, reflecting later bottlenecks. The classical dependence of allele frequency on mutation age does not hold for the generally shorter time span of inbreeding and LD. Limitation of the classical theory to mutation age justifies the assumption of constant time in a LD map, except for alleles that were rare at the effective bottleneck time or have arisen since. This assumption is derived from the Malecot model and verified in all samples. Tested measures of relative efficiency, support intervals, and localization error determine the operating characteristics of LD maps that are applicable to every sexually reproducing species, with implications for association mapping, high-resolution linkage maps, evolutionary inference, and identification of recombinogenic sequences.

Does haplotype diversity predict power for association mapping of disease susceptibility?

Many recent studies have established that haplotype diversity in a small region may not be greatly diminished when the number of markers is reduced to a smaller set of "haplotype-tagging" single-nucleotide polymorphisms (SNPs) that identify the most common haplotypes. These studies are motivated by the assumption that retention of haplotype diversity assures retention of power for mapping disease susceptibility by allelic association. Using two bodies of real data, three proposed measures of diversity, and regression-based methods for association mapping, we found no scenario for which this assumption was tenable. We compared the chi-square for composite likelihood and the maximum chi-square for single SNPs in diplotypes, excluding the marker designated as causal. All haplotype-tagging methods conserve haplotype diversity by selecting common SNPs. When the causal marker has a range of allele frequencies as in real data, chi-square decreases faster than under random selection as the haplotype-tagging set diminishes. Selecting SNPs by maximizing haplotype diversity is inefficient when their frequency is much different from the unknown frequency of the causal variant. Loss of power is minimized when the difference between minor allele frequencies of the causal SNP and a closely associated marker SNP is small, which is unlikely in ignorance of the frequency of the causal SNP unless dense markers are used. Therefore retention of haplotype diversity in simulations that do not mirror genomic allele frequencies has no relevance to power for association mapping. TagSNPs that are assigned to bins instead of haplotype blocks also lose power compared with random SNPs. This evidence favours a multi-stage design in which both models and density change adaptively.

Positional cloning by linkage disequilibrium.

Recently, metric linkage disequilibrium (LD) maps that assign an LD unit (LDU) location for each marker have been developed (Maniatis et al. 2002). Here we present a multiple pairwise method for positional cloning by LD within a composite likelihood framework and investigate the operating characteristics of maps in physical units (kb) and LDU for two bodies of data (Daly et al. 2001; Jeffreys et al. 2001) on which current ideas of blocks are based. False-negative indications of a disease locus (type II error) were examined by selecting one single-nucleotide polymorphism (SNP) at a time as causal and taking its allelic count (0, 1, or 2, for the three genotypes) as a pseudophenotype, Y. By use of regression and correlation, association between every pseudophenotype and the allelic count of each SNP locus (X) was based on an adaptation of the Malecot model, which includes a parameter for location of the putative gene. By expressing locations in kb or LDU, greater power for localization was observed when the LDU map was fitted. The efficiency of the kb map, relative to the LDU map, to describe LD varied from a maximum of 0.87 to a minimum of 0.36, with a mean of 0.62. False-positive indications of a disease locus (type I error) were examined by simulating an unlinked causal SNP and the allele count was used as a pseudophenotype. The type I error was in good agreement with Wald's likelihood theorem for both metrics and all models that were tested. Unlike tests that select only the most significant marker, haplotype, or haploset, these methods are robust to large numbers of markers in a candidate region. Contrary to predictions from tagging SNPs that retain haplotype diversity, the sample with smaller size but greater SNP density gave less error. The locations of causal SNPs were estimated with the same precision in blocks and steps, suggesting that block definition may be less useful than anticipated for mapping a causal SNP. These results provide a guide to efficient positional cloning by SNPs and a benchmark against which the power of positional cloning by haplotype-based alternatives may be measured.

Genetic epidemiology, genetic maps and positional cloning.

Genetic epidemiology developed in the middle of the last century, focused on inherited causes of disease but with methods and results applicable to other traits and even forensics. Early success with linkage led to the localization of genes contributing to disease, and ultimately to the Human Genome Project. The discovery of millions of DNA markers has encouraged more efficient positional cloning by linkage disequilibrium (LD), using LD maps and haplotypes in ways that are rapidly evolving. This has led to large international programmes, some promising and others alarming, with laws about DNA patenting and ethical guidelines for responsible research still struggling to be born.

Linkage disequilibrium in human populations.

Whereas the human linkage map appears on limited evidence to be constant over populations, maps of linkage disequilibrium (LD) vary among populations that differ in gene history. The greatest difference is between populations of sub-Saharan origin and populations remotely derived from Africa after a major bottleneck that reduced their heterozygosity and altered their Malecot parameters, increasing the intercept M that reflects association in founders and decreasing the exponential decline epsilon. Variation among populations within this ethnic dichotomy is much smaller. These observations validate use of a cosmopolitan LD map based on a sizeable sample representing a large population reliably typed for markers at high density. Then an LD map for a region or isolate within an ethnic group may be created by fitting the sample LD to the cosmopolitan map, estimating Malecot parameters simultaneously. The cosmopolitan map scaled by epsilon recovers 95% of the information that a local map at the same density gives and therefore more than the information in a low-resolution local map. Relative to a Eurasian cosmopolitan map the scaling factors are estimated to be 0.82 for isolates of European descent, 1.53 for Yorubans, and 1.74 for African Americans. These observations are consistent with a common bottleneck (perhaps but not necessarily speciation) approximately 173,500 years ago, if the bottleneck associated with migration out of Africa was 100,000 years ago. Eurasian populations (especially isolates with numerous cases) are efficient for genome scans, and populations of recent African origin (such as African Americans) are efficient for identification of causal polymorphisms within a candidate sequence.

Recollections of James Neel.

In his long and influential career Neel contributed to almost all aspects of genetic epidemiology from mutation to ethical and philosophical issues. His research spanned North America, Japan, Africa, and Latin America in a fascinating equipoise among clinical, biochemical, epidemiological, and molecular studies that have stimulated hundreds of researchers who enjoyed the controversies he generated as much as the insights he provided. Without exception, we treasure recollections of a high-principled and warm-hearted colleague whose field studies were a model for their generation.

Properties of linkage disequilibrium (LD) maps.

A linkage disequilibrium map is expressed in linkage disequilibrium (LD) units (LDU) discriminating blocks of conserved LD that have additive distances and locations monotonic with physical (kb) and genetic (cM) maps. There is remarkable agreement between LDU steps and sites of meiotic recombination in the one body of data informative for crossing over, and good agreement with another method that defines blocks without assigning an LD location to each marker. The map may be constructed from haplotypes or diplotypes, and efficiency estimated from the empirical variance of LD is substantially greater for the rho metric based on evolutionary theory than for the absolute correlation r, and for the LD map compared with its physical counterpart. The empirical variance is nearly three times as great for the worst alternative (r and kb map) as for the most efficient approach (rho and LD map). According to the empirical variances, blocks are best defined by zero distance between included markers. Because block size is algorithm-dependent and highly variable, the number of markers required for positional cloning is minimized by uniform spacing on the LD map, which is estimated to have approximately equal 1 LDU per locus, but with much variation among regions. No alternative representation of linkage disequilibrium (some of which are loosely called maps) has these properties, suggesting that LD maps are optimal for positional cloning of genes determining disease susceptibility.

Toward positional cloning with SNPs.

Efficient methods are available for positional cloning of major genes by linkage and linkage disequilibrium (LD). The application of these methods to complex diseases is more demanding, but advances in sequencing the human genome, SNP discovery, high-throughput genotyping techniques, LD maps, and haplotype annotation are revolutionizing positional cloning of oligogenes for common multifactorial disease.