Localization of a Prostate Cancer Predisposition Gene to an 880-kb Region on Chromosome 22q12.3 in Utah High-Risk Pedigrees

Identification of Germline Genetic Variants that Increase Prostate Cancer Risk and Influence Development of Aggressive Disease

Prostate cancer (PrCa) is a heterogeneous disease, which presents in individual patients across a diverse phenotypic spectrum ranging from indolent to fatal forms. No robust biomarkers are currently available to enable routine screening for PrCa or to distinguish clinically significant forms, therefore late stage identification of advanced disease and overdiagnosis plus overtreatment of insignificant disease both remain areas of concern in healthcare provision. PrCa has a substantial heritable component, and technological advances since the completion of the Human Genome Project have facilitated improved identification of inherited genetic factors influencing susceptibility to development of the disease within families and populations. These genetic markers hold promise to enable improved understanding of the biological mechanisms underpinning PrCa development, facilitate genetically informed PrCa screening programmes and guide appropriate treatment provision. However, insight remains largely lacking regarding many aspects of their manifestation; especially in relation to genes associated with aggressive phenotypes, risk factors in non-European populations and appropriate approaches to enable accurate stratification of higher and lower risk individuals. This review discusses the methodology used in the elucidation of genetic loci, genes and individual causal variants responsible for modulating PrCa susceptibility; the current state of understanding of the allelic spectrum contributing to PrCa risk; and prospective future translational applications of these discoveries in the developing eras of genomics and personalised medicine.

Circulating Tumor Cells as a Predictor of Treatment Response in Clinically Localized Prostate Cancer

PURPOSE

Using nonenrichment-based, potentially more sensitive Epic Sciences circulating tumor cell (CTC) platform, we sought to detect and characterize CTCs in untreated, high-risk localized prostate cancer and to evaluate their clinical implication.

METHODS

Between 2012 and 2015, blood samples were prospectively collected from patients with National Comprehensive Cancer Network high-risk localized prostate cancer undergoing either radiotherapy (XRT) plus androgen deprivation therapy or radical prostatectomy (RP) with curative intent. Samples were analyzed with the Epic Sciences platform with 4^J,6-diamidino-2-phenylindole, CD45, cytokeratin (CK), and androgen receptor (AR) N-terminal staining. CTC counts were correlated with biochemical recurrence (BCR).

RESULTS

A diversity of CTC subtypes, including CK-positive, CK-negative, AR-positive, and CTC clusters, were observed in 73.3% (33 of 45) of patients with evaluable data. The median follow-up was 14.2 months (range, 0.5 to 43.7 months). BCR occurred more frequently in the RP group than XRT (15 of 26 v one of 19), with most patients in the XRT group continuing to receive androgen deprivation therapy. A higher proportion of metastatic events were observed in the RP group (five of 26 v one of 19). In the RP group, BCR and development of metastases were associated with a higher total number of CTCs, AR-positive CTCs, and CTC phenotypic heterogeneity. One patient who developed BCR and metastases quickly after RP had diverse phenotypical CTC subtypes, and single-cell genomic analyses of all detectable CTCs confirmed common prostate cancer copy number alterations and PTEN loss.

CONCLUSION

CTCs can be identified in most patients with high-risk localized prostate cancer before definitive therapy using the Epic Sciences platform. If confirmed in a larger cohort with longer follow-up, phenotypic and genomic characterization of CTCs pretherapy may provide an additional means of risk stratifying patients with newly diagnosed high-risk disease and potentially help identify patients who could require multimodal therapy.

The complexity of prostate cancer: genomic alterations and heterogeneity

Although prostate cancer is the most common malignancy to affect men in the Western world, the molecular mechanisms underlying its development and progression remain poorly understood. Like all cancers, prostate cancer is a genetic disease that is characterized by multiple genomic alterations, including point mutations, microsatellite variations, and chromosomal alterations such as translocations, insertions, duplications, and deletions. In prostate cancer, but not other carcinomas, these chromosome alterations result in a high frequency of gene fusion events. The development and application of novel high-resolution technologies has significantly accelerated the detection of genomic alterations, revealing the complex nature and heterogeneity of the disease. The clinical heterogeneity of prostate cancer can be partly explained by this underlying genetic heterogeneity, which has been observed between patients from different geographical and ethnic populations, different individuals within these populations, different tumour foci within the same patient, and different cells within the same tumour focus. The highly heterogeneous nature of prostate cancer provides a real challenge for clinical disease management and a detailed understanding of the genetic alterations in all cells, including small subpopulations, would be highly advantageous.

Molecular Updates in Prostate Cancer

A wide array of molecular markers and genomic signatures, reviewed in this article, may soon be used as adjuncts to currently established screening strategies, prognostic parameters, and early detection markers. Markers of genetic susceptibility to PCA, recurrent epigenetic and genetic alterations, including ETS gene fusions, PTEN alterations, and urine-based early detection marker PCA3, are discussed. Impact of recent genome-wide assessment on our understanding of key pathways of PCA development and progression and their potential clinical implications are highlighted.

Characterization of germline copy number variation in high-risk African American families with prostate cancer

BACKGROUND

Prostate cancer is a complex multi-allelic disease and the most common malignancy in men. The incidence of prostate cancer in African American men is more than twice as high as that of any other race. Despite the high prevalence of prostate cancer amongst African American men, this population has been under represented in genetic studies of prostate cancer. Although genomic copy number variations (CNVs) have been detected in prostate tumors, this is the first study describing germline CNVs in African American hereditary prostate cancer families.

METHODS

Ten high-risk African American families with three or more affected individuals and with an early age of onset were recruited. From these families, 37 individuals, including 23 affected males, and 14 unaffected males, were selected for CNV analysis. Array comparative genomic hybridization was used to characterize germline CNVs unique to African American men with hereditary prostate cancer.

RESULTS

Through common aberration analysis in affected family members; novel CNVs were identified at chromosomes 1p36.13 and 16q23.3. Differential analysis comparing affected and unaffected family members identified 9.4 kb duplication on chromosome 14q32.33 which segregate with prostate cancer patients in these high-risk families.

CONCLUSIONS

The duplication at 14q32.33 encompasses IGHG3 gene which has been shown to have both significant gains in copy number as well as overexpression in prostate tumors in African Americans. These CNVs may represent a component of genetic predisposition which contributes to the high prevalence and mortality of prostate cancer in African American men.

Shared genomic segment analysis: the power to find rare disease variants

Shared genomic segment (SGS) analysis uses dense single nucleotide polymorphism genotyping in high-risk (HR) pedigrees to identify regions of sharing between cases. Here, we illustrate the power of SGS to identify dominant rare risk variants. Using simulated pedigrees, we consider 12 disease models based on disease prevalence, minor allele frequency and penetrance to represent disease loci that explain 0.2-99.8% of total disease risk. Pedigrees were required to contain ≥ 15 meioses between all cases and to be HR based on significant excess of disease (P < 0.001 or P < 0.00001). Across these scenarios, the power for a single pedigree ranged widely. Nonetheless, fewer than 10 pedigrees were sufficient for excellent power in the majority of models. Power increased with the risk attributable to the disease locus, penetrance and the excess of disease in the pedigree. Sharing allowing for one sporadic case was uniformly more powerful than sharing using all cases. Furthermore, an SGS analysis using a large attenuated familial adenomatous polyposis pedigree identified a 1.96 Mb region containing the known causal APC gene with genome-wide significance. SGS is a powerful method for detecting rare variants and a valuable complement to genome-wide association studies and linkage analysis.

The genetics of cancer risk

One hundred years ago, decades before the discovery of the structure of DNA, debate raged regarding how human traits were passed from one generation to the next. Phenotypes, including risk of disease, had long been recognized as having a familial component. Yet it was difficult to reconcile genetic segregation as described by Mendel with observations exhaustively documented by Karl Pearson and others regarding the normal distribution of human characteristics. In 1918, R. A. Fisher published his landmark article, "The Correlation Between Relatives on the Supposition of Mendelian Inheritance," bridging this divide and demonstrating that multiple alleles, all individually obeying Mendel's laws, account for the phenotypic variation observed in nature.Since that time, geneticists have sought to identify the link between genotype and phenotype. Trait-associated alleles vary in their frequency and degree of penetrance. Some minor alleles may approach a frequency of 50% in the human population, whereas others are present within only a few individuals. The spectrum for penetrance is similarly wide. These characteristics jointly determine the segregation pattern of a given trait, which, in turn, determine the method used to map the trait. Until recently, identification of rare, highly penetrant alleles was most practical. Revolutionary studies in genomics reported over the past decade have made interrogation of most of the spectrum of genetic variation feasible.The following article reviews recent discoveries in the genetic basis of inherited cancer risk and how these discoveries inform cancer biology and patient management. Although this article focuses on prostate cancer, the principles are generic for any cancer and, indeed, for any trait.

Suggestive evidence of linkage identified at chromosomes 12q24 and 2p16 in African American prostate cancer families from Louisiana

BACKGROUND

In the United States, incidence of prostate cancer in African American men is more than twice than that of any other race. Thus far, numerous disease susceptibility loci have been identified for this cancer but definite locus-specific information is not yet established due to the tremendous amount of genetic and disease heterogeneity; additionally, despite high prevalence of prostate cancer amongst African American men, this population has been under represented in genetic studies of prostate cancer.

METHODS

In order to identify the susceptible locus (loci) for prostate cancer in African Americans, we have performed linkage analyses on members of 15 large high-risk families. Specifically, these families were recruited from Louisiana and represent a uniquely admixed African American population exclusive to Southern Louisiana. In addition to geographical constraints, these families were clinically homogeneous creating a well-characterized collection of large pedigrees. The families were genotyped with Illumina Infinium II SNP HumanLinkage-12 panel and extensive demographic and clinical information was documented from the hospital pathological reports and family interviews.

RESULTS

We identified two novel regions, 12q24 and 2p16, with suggestive evidence of linkage under the dominant model of inheritance.

CONCLUSIONS

This is the first time that chromosome 12q24 (HLOD = 2.21) and 2p16 (HLOD = 1.97) has been shown to be associated with prostate cancer in high-risk African American families. These results provide insight to prostate cancer in an exceptional, well-characterized African American population, and illustrate the significance of utilizing large unique, but homogenous pedigrees.

Genetics of prostate cancer risk

For decades, physicians and researchers have recognized that family history is a significant risk factor for prostate cancer. The identification of the genes responsible for inherited risk, however, proved difficult. With the sequencing of the human genome and the completion of the initial phases of the International HapMap Project, the tools are available to scan the entire genome and find genetic markers for disease. Since 2006, more than 30 inherited variants strongly associated with prostate cancer have been reported. As the inherited component of the disease is revealed, efforts are ongoing to translate genetic findings into the clinic.

Family-based association analysis of 42 hereditary prostate cancer families identifies the Apolipoprotein L3 region on chromosome 22q12 as a risk locus

Multiple genome-wide scans for hereditary prostate cancer (HPC) have identified susceptibility loci on nearly every chromosome. However, few results have been replicated with statistical significance. One exception is chromosome 22q, for which five independent linkage studies yielded strong evidence for a susceptibility locus in HPC families. Previously, we refined this region to a 2.53 Mb interval, using recombination mapping in 42 linked pedigrees. We now refine this locus to a 15 kb interval, spanning Apolipoprotein L3 (APOL3), using family-based association analyses of 150 total prostate cancer (PC) cases from two independent family collections with 506 unrelated population controls. Analysis of the two independent sets of PC cases highlighted single nucleotide polymorphisms (SNPs) within the APOL3 locus showing the strongest associations with HPC risk, with the most robust results observed when all 150 cases were combined. Analysis of 15 tagSNPs across the 5' end of the locus identified six SNPs with P-values < or =2 × 10(-4). The two independent sets of HPC cases highlight the same 15 kb interval at the 5' end of the APOL3 gene and provide strong evidence that SNPs within this 15 kb interval, or in strong linkage disequilibrium with it, contribute to HPC risk. Further analyses of this locus in an independent population-based, case-control study revealed an association between an SNP within the APOL3 locus and PC risk, which was not confirmed in the Cancer Genetic Markers of Susceptibility data set. This study further characterizes the 22q locus in HPC risk and suggests that the role of this region in sporadic PC warrants additional studies.

Genome-wide linkage analysis of 1,233 prostate cancer pedigrees from the International Consortium for Prostate Cancer Genetics using novel sumLINK and sumLOD analyses

BACKGROUND

Prostate cancer (PC) is generally believed to have a strong inherited component, but the search for susceptibility genes has been hindered by the effects of genetic heterogeneity. The recently developed sumLINK and sumLOD statistics are powerful tools for linkage analysis in the presence of heterogeneity.

METHODS

We performed a secondary analysis of 1,233 PC pedigrees from the International Consortium for Prostate Cancer Genetics (ICPCG) using two novel statistics, the sumLINK and sumLOD. For both statistics, dominant and recessive genetic models were considered. False discovery rate (FDR) analysis was conducted to assess the effects of multiple testing.

RESULTS

Our analysis identified significant linkage evidence at chromosome 22q12, confirming previous findings by the initial conventional analyses of the same ICPCG data. Twelve other regions were identified with genome-wide suggestive evidence for linkage. Seven regions (1q23, 5q11, 5q35, 6p21, 8q12, 11q13, 20p11-q11) are near loci previously identified in the initial ICPCG pooled data analysis or the subset of aggressive PC pedigrees. Three other regions (1p12, 8p23, 19q13) confirm loci reported by others, and two (2p24, 6q27) are novel susceptibility loci. FDR testing indicates that over 70% of these results are likely true positive findings. Statistical recombinant mapping narrowed regions to an average of 9 cM.

CONCLUSIONS

Our results represent genomic regions with the greatest consistency of positive linkage evidence across a very large collection of high-risk PC pedigrees using new statistical tests that deal powerfully with heterogeneity. These regions are excellent candidates for further study to identify PC predisposition genes.

The sumLINK statistic for genetic linkage analysis in the presence of heterogeneity

We present the "sumLINK" statistic--the sum of multipoint LOD scores for the subset of pedigrees with nominally significant linkage evidence at a given locus--as an alternative to common methods to identify susceptibility loci in the presence of heterogeneity. We also suggest the "sumLOD" statistic (the sum of positive multipoint LOD scores) as a companion to the sumLINK. sumLINK analysis identifies genetic regions of extreme consistency across pedigrees without regard to negative evidence from unlinked or uninformative pedigrees. Significance is determined by an innovative permutation procedure based on genome shuffling that randomizes linkage information across pedigrees. This procedure for generating the empirical null distribution may be useful for other linkage-based statistics as well. Using 500 genome-wide analyses of simulated null data, we show that the genome shuffling procedure results in the correct type 1 error rates for both the sumLINK and sumLOD. The power of the statistics was tested using 100 sets of simulated genome-wide data from the alternative hypothesis from GAW13. Finally, we illustrate the statistics in an analysis of 190 aggressive prostate cancer pedigrees from the International Consortium for Prostate Cancer Genetics, where we identified a new susceptibility locus. We propose that the sumLINK and sumLOD are ideal for collaborative projects and meta-analyses, as they do not require any sharing of identifiable data between contributing institutions. Further, loci identified with the sumLINK have good potential for gene localization via statistical recombinant mapping, as, by definition, several linked pedigrees contribute to each peak.

Identification of seven new prostate cancer susceptibility loci through a genome-wide association study

Prostate cancer (PrCa) is the most frequently diagnosed cancer in males in developed countries. To identify common PrCa susceptibility alleles, we previously conducted a genome-wide association study in which 541,129 SNPs were genotyped in 1,854 PrCa cases with clinically detected disease and in 1,894 controls. We have now extended the study to evaluate promising associations in a second stage in which we genotyped 43,671 SNPs in 3,650 PrCa cases and 3,940 controls and in a third stage involving an additional 16,229 cases and 14,821 controls from 21 studies. In addition to replicating previous associations, we identified seven new prostate cancer susceptibility loci on chromosomes 2, 4, 8, 11 and 22 (with P = 1.6 x 10(-8) to P = 2.7 x 10(-33)).

Genetic variants and prostate cancer risk: candidate replication and exploration of viral restriction genes

The genetic variants underlying the strong heritable component of prostate cancer remain largely unknown. Genome-wide association studies of prostate cancer have yielded several variants that have significantly replicated across studies, predominantly in cases unselected for family history of prostate cancer. Additional candidate gene variants have also been proposed, many evaluated within familial prostate cancer study populations. Such variants hold great potential value for risk stratification, particularly for early-onset or aggressive prostate cancer, given the comorbidities associated with current therapies. Here, we investigate a Caucasian study population of 523 independent familial prostate cancer cases and 523 age-matched controls without a personal or family history of prostate cancer. We replicate identified associations at genome-wide association study loci 8q24, 11q13, and 2p15 (P = 2.9 x 10(-4) to P = 4.7 x 10(-5)), showing study population power. We also find evidence to support reported associations at candidate genes RNASEL, EZH2, and NKX3-1 (P = 0.031 to P = 0.0085). We further explore a set of candidate genes related to RNASEL and to its role in retroviral restriction, identifying nominal associations at XPR1 and RBM9. The effects at 8q24 seem more pronounced for those diagnosed at an early age, whereas at 2p15 and RNASEL the effects were more pronounced at a later age. However, these trends did not reach statistical significance. The effects at 2p15 were statistically significantly more pronounced for those diagnosed with aggressive disease.

Discovery of functional miRNA-mRNA regulatory modules with computational methods

The identification of miRNAs and their target mRNAs and the construction of their regulatory networks may give new insights into biological procedures. This study proposes a computational method to discover the functional miRNA-mRNA regulatory modules (FMRMs), that is, groups of miRNAs and their target mRNAs that are believed to participate cooperatively in post-transcriptional gene regulation under specific conditions. The proposed method identifies negatively regulated patterns of miRNAs and mRNAs which associate with cancer and normal conditions, respectively, in a prostate cancer data set. GO and the literature also suggest that they may relate with prostate cancer. It can potentially identify the biologically relevant chains of 'miRNA-->target gene --> condition'.

The role of the BRCA2 gene in susceptibility to prostate cancer revisited

Prostate cancer is a genetically complex disease with multiple predisposing factors affecting presentation, progression, and outcome. Epidemiologic studies have long shown an aggregation of breast and prostate cancer in some families. More recently, studies have reported an apparent excess of prostate cancer cases among BRCA2 mutation-carrying families. Additionally, population-based screens of early-onset prostate cancer patients have suggested that the prevalence of deleterious BRCA2 mutations in this group is 1% to 2%, imparting a significantly increased risk of the disease compared with noncarrier cases. However, studies of high-risk prostate cancer families suggest that BRCA2 plays at most a minimal role in these individuals, highlighting the potential genetic heterogeneity of the disease. In this commentary, we review the current literature and hypotheses surrounding the relationship between BRCA2 mutations and susceptibility to prostate cancer and speculate on the potential for involvement of additional genes.

Fine mapping of familial prostate cancer families narrows the interval for a susceptibility locus on chromosome 22q12.3 to 1.36 Mb

Genetic studies suggest that hereditary prostate cancer is a genetically heterogeneous disease with multiple contributing loci. Studies of high-risk prostate cancer families selected for aggressive disease, analysis of large multigenerational families, and a meta-analysis from the International Consortium for Prostate Cancer Genetics (ICPCG), all highlight chromosome 22q12.3 as a susceptibility locus with strong statistical significance. Recently, two publications have narrowed the 22q12.3 locus to a 2.18 Mb interval using 54 high-risk families from the ICPCG collaboration, as defined by three recombination events on either side of the locus. In this paper, we present the results from fine mapping studies at 22q12.3 using both haplotype and recombination data from 42 high-risk families contributed from the Mayo Clinic and the Prostate Cancer Genetic Research Study (PROGRESS) mapping studies. No clear consensus interval is present when all families are used. However, in the subset of 14 families with >/=5 affected men per family, a 2.53-Mb shared consensus segment that overlaps with the previously published interval is identified. Combining these results with data from the earlier ICPCG study reduces the three-recombination interval at 22q12.3 to approximately 1.36 Mb.

A genome-wide association study of breast and prostate cancer in the NHLBI's Framingham Heart Study

BACKGROUND

Breast and prostate cancer are two commonly diagnosed cancers in the United States. Prior work suggests that cancer causing genes and cancer susceptibility genes can be identified.

METHODS

We conducted a genome-wide association study (Affymetrix 100K SNP GeneChip) of cancer in the community-based Framingham Heart Study. We report on 2 cancer traits--prostate cancer and breast cancer--in up to 1335 participants from 330 families (54% women, mean entry age 33 years). Multivariable-adjusted residuals, computed using Cox proportional hazards models, were tested for association with qualifying SNPs (70, 987 autosomal SNPs with genotypic call rate > or =80%, minor allele frequency > or =10%, Hardy-Weinberg test p > or = 0.001) using generalized estimating equations (GEE) models and family based association tests (FBAT).

RESULTS

There were 58 women with breast cancer and 59 men with prostate cancer. No SNP associations attained genome-wide significance. The top SNP associations in GEE models for each trait were as follows: breast cancer, rs2075555, p = 8.0 x 10(-8) in COL1A1; and prostate cancer, rs9311171, p = 1.75 x 10(-6) in CTDSPL. In analysis of selected candidate cancer susceptibility genes, two MSR1 SNPs (rs9325782, GEE p = 0.008 and rs2410373, FBAT p = 0.021) were associated with prostate cancer and three ERBB4 SNPs (rs905883 GEE p = 0.0002, rs7564590 GEE p = 0.003, rs7558615 GEE p = 0.0078) were associated with breast cancer. The previously reported risk SNP for prostate cancer, rs1447295, was not included on the 100K chip. Results of cancer phenotype-genotype associations for all autosomal SNPs are web posted at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.

CONCLUSION

Although no association attained genome-wide significance, several interesting associations emerged for breast and prostate cancer. These findings can serve as a resource for replication in other populations to identify novel biologic pathways contributing to cancer susceptibility.

Statistical recombinant mapping in extended high-risk Utah pedigrees narrows the 8q24 prostate cancer locus to 2.0 Mb

BACKGROUND

Chromosome 8q24 is a region of compelling interest for prostate cancer (PRCA). Linkage, association, and admixture analysis initially indicated the region. Subsequently, several variants at 8q24 have been found to independently associate with PRCA. One compelling hypothesis is allelic heterogeneity, whereby multiple variants affect the regulation of the same gene. In addition to potential allelic heterogeneity, 8q24 exhibits strong linkage disequilibrium over vast distances and is prone to chromosomal aberrations.

METHODS

Allelic heterogeneity and complex chromosomal structure are factors that hinder progress towards gene identification using association. Linkage techniques, however, are robust to allelic heterogeneity and therefore can contribute important localization information. We have used a linkage-based localization technique to perform recombinant mapping in eight high-risk Utah pedigrees.

RESULTS

Using pedigree-based recombinant mapping we identify a 5.7 Mb region at 8q24.21-22, between markers D8S1774 and D8S557. Considering our region with the localization previously presented, we can delimit the 8q24 PRCA locus to a 2.0 Mb consensus interval from 127.5 to 129.5 Mb.

CONCLUSION

We have used a linkage-based, recombinant mapping technique in extended high-risk Utah pedigrees to successfully narrow the 8q24 PRCA locus. The region we present halves the 95% credible interval previously described using admixture analysis and contains only three annotated genes: FAM84B, MYC, and TMEM75. It should be noted that LD stretches far beyond the interval we describe, and hence this region adds important information about where to focus future efforts to isolate the causal variants and underlying gene, whether by linkage or association techniques.

Compelling evidence for a prostate cancer gene at 22q12.3 by the International Consortium for Prostate Cancer Genetics

Previously, an analysis of 14 extended, high-risk Utah pedigrees localized in the chromosome 22q linkage region to 3.2 Mb at 22q12.3-13.1 (flanked on each side by three recombinants) contained 31 annotated genes. In this large, multi-centered, collaborative study, we performed statistical recombinant mapping in 54 pedigrees selected to be informative for recombinant mapping from nine member groups of the International Consortium for Prostate Cancer Genetics (ICPCG). These 54 pedigrees included the 14 extended pedigrees from Utah and 40 pedigrees from eight other ICPCG member groups. The additional 40 pedigrees were selected from a total pool of 1213 such that each pedigree was required to contain both at least four prostate cancer (PRCA) cases and exhibit evidence for linkage to the chromosome 22q region. The recombinant events in these 40 independent pedigrees confirmed the previously proposed region. Further, when all 54 pedigrees were considered, the three-recombinant consensus region was narrowed down by more than a megabase to 2.2 Mb at chromosome 22q12.3 flanked by D22S281 and D22S683. This narrower region eliminated 20 annotated genes from that previously proposed, leaving only 11 genes. This region at 22q12.3 is the most consistently identified and smallest linkage region for PRCA. This collaborative study by the ICPCG illustrates the value of consortium efforts and the continued utility of linkage analysis using informative pedigrees to localize genes for complex diseases.

Family based studies and genetic epidemiology: theory and practice

Family based studies have underpinned many successes in uncovering the causes of monogenic and oligogenic diseases. Now research is focussing on the identification and characterisation of genes underlying common diseases and it is widely accepted that these studies will require large population based samples. Population based family study designs have the potential to facilitate the analysis of the effects of both genes and environment. These types of studies integrate the population based approaches of classic epidemiology and the methods enabling the analysis of correlations between relatives sharing both genes and environment. The extent to which such studies are feasible will depend upon population- and disease-specific factors. To review this topic, a symposium was held to present and discuss the costs, requirements and advantages of population based family study designs. This article summarises the features of the meeting held at The University of Sheffield, August 2006.