The role of linkage studies for common diseases

Ancestral haplotype reconstruction in endogamous populations using identity-by-descent

In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs.

We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to North America from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 12 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct—we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families.

When analyzing complex heritable traits, genomic data from many generations of an extended family increases the amount of information available for statistical inference. However, typically only genomic data from the recent generations of a pedigree are available, as ancestral individuals are deceased. In this work we present an algorithm, called thread, for reconstructing the genomes of ancestral individuals, given a complex pedigree and genomic data from the recent generations. Previous approaches have not been able to accommodate large datasets (both in terms of sites and individuals), made simplifying assumptions about pedigree structure, or did not tie reconstructed sequences back to specific individuals. We apply thread to a complex Old Order Amish pedigree of 1338 individuals, 394 with genotype data.

Animal breeding in the (post-) genomic era

One of the benefits of the genomics revolution for animal production will be knowledge of genes that can be used to select more profitable livestock. Although it is possible to use genetic markers linked to genes of economic importance, tests for the genes themselves will be much more successful. Consequently finding genes of economic importance to livestock will be a major research aim for the future. Most traits of economic importance are quantitative traits affected by many genes. Mutations at many genes (e.g. 500) and at many positions within a gene (e.g. 1000 coding and non-coding bases) can affect a typical quantitative trait. The effect of these mutations on phenotype is usually small (e.g. 0·1 standard deviation) but occasionally large. Many mutations are lost from the population through genetic drift and selection, so that polymorphisms exist at only a subset of the relevant genes (e.g. 100 genes). Finding these genes, that have relatively small effects, is more difficult than finding genes for a classical Mendellian trait but, as the genomic tools become more powerful, it is becoming feasible and some successes have already occurred. The standard approach is to map a quantitative trait loci (QTL) to a chromosome region using linkage and linkage disequilibrium. Then test polymorphisms in positional candidate genes for an effect on the trait. Tools such as genomic sequence, EST collections and comparative maps make this approach feasible. Candidate genes can be selected based on functional data such as gene expression obtained from microarrays. At present the gain in rate of genetic improvement from use of DNA-based tests for QTL is small, because selection without them is already quite accurate, not enough QTL have been identified and genotyping is too expensive. However, in the future, with many QTL identified and inexpensive genotyping combined with decreased generation intervals, large gains are possible.

GENLIB: an R package for the analysis of genealogical data

BACKGROUND

Founder populations have an important role in the study of genetic diseases. Access to detailed genealogical records is often one of their advantages. These genealogical data provide unique information for researchers in evolutionary and population genetics, demography and genetic epidemiology. However, analyzing large genealogical datasets requires specialized methods and software. The GENLIB software was developed to study the large genealogies of the French Canadian population of Quebec, Canada. These genealogies are accessible through the BALSAC database, which contains over 3 million records covering the whole province of Quebec over four centuries. Using this resource, extended pedigrees of up to 17 generations can be constructed from a sample of present-day individuals.

RESULTS

We have extended and implemented GENLIB as a package in the R environment for statistical computing and graphics, thus allowing optimal flexibility for users. The GENLIB package includes basic functions to manage genealogical data allowing, for example, extraction of a part of a genealogy or selection of specific individuals. There are also many functions providing information to describe the size and complexity of genealogies as well as functions to compute standard measures such as kinship, inbreeding and genetic contribution. GENLIB also includes functions for gene-dropping simulations. The goal of this paper is to present the full functionalities of GENLIB. We used a sample of 140 individuals from the province of Quebec (Canada) to demonstrate GENLIB's functions. Ascending genealogies for these individuals were reconstructed using BALSAC, yielding a large pedigree of 41,523 individuals. Using GENLIB's functions, we provide a detailed description of these genealogical data in terms of completeness, genetic contribution of founders, relatedness, inbreeding and the overall complexity of the genealogical tree. We also present gene-dropping simulations based on the whole genealogy to investigate identical-by-descent sharing of alleles and chromosomal segments of different lengths and estimate probabilities of identical-by-descent sharing.

CONCLUSIONS

The R package GENLIB provides a user friendly and flexible environment to analyze extensive genealogical data, allowing an efficient and easy integration of different types of data, analytical methods and additional developments and making this tool ideal for genealogical analysis.

ALDH2 is associated to alcohol dependence and is the major genetic determinant of "daily maximum drinks" in a GWAS study of an isolated rural Chinese sample

Alcohol dependence (AD) is a moderately heritable phenotype with a small number of known risk genes mapped via linkage or candidate gene studies. We considered 313 males from among 595 members of documented, extended pedigrees in which AD segregates collected in Northern Hunan Province, China. A joint analysis of both males and females could not be performed as the difference in alcohol consumption variance was too large. Genome-wide association analyses were performed for approximately 300,000 single nucleotide polymorphisms (SNPs). Significant associations found in the ALDH2 region for AD (minimum P = 4.73 × 10(-8)) and two AD-related phenotypes: flushing response (minimum P = 4.75 × 10(-26)) and maximum drinks in a 24-hr period (minimum P = 1.54 × 10(-16)). Association of previous candidate SNP, rs10774610 in CCDC63, was confirmed but resulted from linkage disequilibrium with ALDH2. ALDH2 is strongly associated with flushing response, AD, and maximum drinks in males, with nonsynonymous SNP rs671 explaining 29.2%, 7.9%, and 22.9% of phenotypic variation, respectively, in this sample. When rs671 was considered as a candidate SNP in females, it explained 23.6% of the variation in flushing response, but alcohol consumption rates were too low among females-despite familial enrichment for AD-for an adequate test of association for either AD or maximum drinks. These results support a mediating effect of aldehyde dehydrogenase deficiency on alcohol consumption in males and a secondary, culturally mediated limitation on alcohol consumption by females that should be appropriately modeled in future studies of alcohol consumption in populations where this may be a factor.

Increased power of mixed models facilitates association mapping of 10 loci for metabolic traits in an isolated population

The potential benefits of using population isolates in genetic mapping, such as reduced genetic, phenotypic and environmental heterogeneity, are offset by the challenges posed by the large amounts of direct and cryptic relatedness in these populations confounding basic assumptions of independence. We have evaluated four representative specialized methods for association testing in the presence of relatedness; (i) within-family (ii) within- and between-family and (iii) mixed-models methods, using simulated traits for 2906 subjects with known genome-wide genotype data from an extremely isolated population, the Island of Kosrae, Federated States of Micronesia. We report that mixed models optimally extract association information from such samples, demonstrating 88% power to rank the true variant as among the top 10 genome-wide with 56% achieving genome-wide significance, a >80% improvement over the other methods, and demonstrate that population isolates have similar power to non-isolate populations for observing variants of known effects. We then used the mixed-model method to reanalyze data for 17 published phenotypes relating to metabolic traits and electrocardiographic measures, along with another 8 previously unreported. We replicate nine genome-wide significant associations with known loci of plasma cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, thyroid stimulating hormone, homocysteine, C-reactive protein and uric acid, with only one detected in the previous analysis of the same traits. Further, we leveraged shared identity-by-descent genetic segments in the region of the uric acid locus to fine-map the signal, refining the known locus by a factor of 4. Finally, we report a novel associations for height (rs17629022, P< 2.1 × 10⁻⁸).

National population-based biobanks for genetic research

Clinical practice guidelines derived from genetic research using population-based biobanks could dramatically change the nature of personal and public health medicine. Centralized population-based biobanks have been established or proposed in at least nine countries to date, and many lessons have been learned from these landmark developments. Scientific and governmental leaders in the United States are currently contemplating pending federal legislation regarding the establishment of centralized and networked biobanks. Public health practitioners and clinical care providers may be called on to serve pronounced planning roles at the state level. Possible responsibilities include: formulating legislation, gathering public comment, reviewing research proposals, and developing procedures for informed consent, participant withdrawal, and confidentiality protection. State health agencies may also need to create and/or administer banking facilities. Proper planning may ensure that individual rights are protected while research benefits are maximized.

From DNA to RNA to disease and back: the 'central dogma' of regulatory disease variation

Much of the focus of human disease genetics is directed towards identifying nucleotide variants that contribute to disease phenotypes. This is a complex problem, often involving contributions from multiple loci and their interactions, as well as effects due to environmental factors. Although some diseases with a genetic basis are caused by nucleotide changes that alter an amino acid sequence, in other cases, disease risk is associated with altered gene regulation. This paper focuses on how studies of gene expression variation might complement disease studies and provide crucial links between genotype and phenotype.

Complex trait mapping in isolated populations: Are specific statistical methods required?

In this paper, we review the statistical methods that can be used in isolated populations to map genes involved in complex diseases. Our intention is to highlight the fact that if the features of population isolates may help in the identification of susceptibility factors for complex traits, the choice and design of methods for statistical analysis in these populations deserve particular care. We show that methods designed for outbred samples are generally not appropriate for isolated populations and could lead to false conclusions.

Association study using combination analysis of SNP and STRP markers: CD14 promoter polymorphism and IgE level in Taiwanese asthma children

Chromosome 5, especially the 5q31-33 region, may contain one or more loci to control total serum IgE as well as asthma and bronchial hyperresponsiveness. To investigate the regions related with IgE level in chromosome 5, we performed a case-control association study on 105 high-IgE-level and 85 normal-IgE-level asthmatic children using 43 microsatellite markers that span the whole chromosome 5 with 5 cM intervals. One of microsatellite marker, D5S2011, had significantly different allele frequency between the two asthmatic groups. E allele (143 bp) of the D5S2011 marker was more frequent in high-IgE asthmatics. CD14 is the candidate gene of atopy and asthma and is distant from D5S2011 by about 1 Mb. We analyzed the SNP genotypes in the CD14 gene region alone and in combination with microsatellite marker D5S2011. The CD14/-2984 polymorphism but not the CD14/-159 is associated with IgE level in Taiwanese asthmatic children. The CD14/-159 allele was observed only to be associated with IgE level when -159T was part of a haplotype containing a D5S2011 E allele. The combination analysis using SNP and STRP markers provided a novel method for increasing detection power in candidate gene association studies.

Linkage disequilibrium mapping in the Newfoundland population: a re-evaluation of the refinement of the Bardet?Biedl syndrome 1 critical interval

Genetically isolated populations, such as Newfoundland, have contributed greatly to the identification of disease-causing genes. A linkage disequilibrium (LD) study involving six Newfoundland families predicted a critical interval for Bardet-Biedl syndrome 1 (BBS1) (Young et al. in Am J Hum Genet 65:1680-1687, 1999), but the subsequent identification of BBS1 revealed that it lies outside this region. This suggested that either there is another gene responsible for BBS in these families or the Newfoundland population may not be ideal for LD studies. We screened these six Newfoundland families for mutations in BBS1 and found that affected individuals in five of them were homozygous for the same M390R mutation. There was no evidence for any BBS1 mutation in the affected individual in the sixth family. Therefore, one of the criteria for LD mapping was not met; namely, there should be a single disease-causing allele in the population. Haplotype analysis of unaffected individuals from south-west Newfoundland and English BBS1 patients homozygous for M390R, revealed that a second criterion for LD mapping was violated. The M390R mutation occurred in a common haplotype and both of these chromosomes, the ancestral wild-type and disease-causing haplotypes, were introduced to Newfoundland and spread by a founder effect. Moreover, it was found that disease-associated alleles occurred at relatively high frequencies in normal haplotypes and this probably accounted for the incorrect prediction in the previous LD study. Knowing the amount of genetic variation and its distribution in the Newfoundland population would be useful to maximize its potential for mapping hereditary disorders.

The genetics of autism

Autism is a complex, behaviorally defined, static disorder of the immature brain that is of great concern to the practicing pediatrician because of an astonishing 556% reported increase in pediatric prevalence between 1991 and 1997, to a prevalence higher than that of spina bifida, cancer, or Down syndrome. This jump is probably attributable to heightened awareness and changing diagnostic criteria rather than to new environmental influences. Autism is not a disease but a syndrome with multiple nongenetic and genetic causes. By autism (the autistic spectrum disorders [ASDs]), we mean the wide spectrum of developmental disorders characterized by impairments in 3 behavioral domains: 1) social interaction; 2) language, communication, and imaginative play; and 3) range of interests and activities. Autism corresponds in this article to pervasive developmental disorder (PDD) of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition and International Classification of Diseases, Tenth Revision. Except for Rett syndrome--attributable in most affected individuals to mutations of the methyl-CpG-binding protein 2 (MeCP2) gene--the other PDD subtypes (autistic disorder, Asperger disorder, disintegrative disorder, and PDD Not Otherwise Specified [PDD-NOS]) are not linked to any particular genetic or nongenetic cause. Review of 2 major textbooks on autism and of papers published between 1961 and 2003 yields convincing evidence for multiple interacting genetic factors as the main causative determinants of autism. Epidemiologic studies indicate that environmental factors such as toxic exposures, teratogens, perinatal insults, and prenatal infections such as rubella and cytomegalovirus account for few cases. These studies fail to confirm that immunizations with the measles-mumps-rubella vaccine are responsible for the surge in autism. Epilepsy, the medical condition most highly associated with autism, has equally complex genetic/nongenetic (but mostly unknown) causes. Autism is frequent in tuberous sclerosis complex and fragile X syndrome, but these 2 disorders account for but a small minority of cases. Currently, diagnosable medical conditions, cytogenetic abnormalities, and single-gene defects (eg, tuberous sclerosis complex, fragile X syndrome, and other rare diseases) together account for <10% of cases. There is convincing evidence that "idiopathic" autism is a heritable disorder. Epidemiologic studies report an ASD prevalence of approximately 3 to 6/1000, with a male to female ratio of 3:1. This skewed ratio remains unexplained: despite the contribution of a few well characterized X-linked disorders, male-to-male transmission in a number of families rules out X-linkage as the prevailing mode of inheritance. The recurrence rate in siblings of affected children is approximately 2% to 8%, much higher than the prevalence rate in the general population but much lower than in single-gene diseases. Twin studies reported 60% concordance for classic autism in monozygotic (MZ) twins versus 0 in dizygotic (DZ) twins, the higher MZ concordance attesting to genetic inheritance as the predominant causative agent. Reevaluation for a broader autistic phenotype that included communication and social disorders increased concordance remarkably from 60% to 92% in MZ twins and from 0% to 10% in DZ pairs. This suggests that interactions between multiple genes cause "idiopathic" autism but that epigenetic factors and exposure to environmental modifiers may contribute to variable expression of autism-related traits. The identity and number of genes involved remain unknown. The wide phenotypic variability of the ASDs likely reflects the interaction of multiple genes within an individual's genome and the existence of distinct genes and gene combinations among those affected. There are 3 main approaches to identifying genetic loci, chromosomal regions likely to contain relevant genes: 1) whole genome screens, searching for linkage of autism to shared genetic markers in populations of multiplex families (families with >1 affected family member; 2) cytogenetic studies that may guide molecular studies by pointing to relevant inherited or de novo chromosomal abnormalities in affected individuals and their families; and 3) evaluation of candidate genes known to affect brain development in these significantly linked regions or, alternatively, linkage of candidate genes selected a priori because of their presumptive contribution to the pathogenesis of autism. Data from whole-genome screens in multiplex families suggest interactions of at least 10 genes in the causation of autism. Thus far, a putative speech and language region at 7q31-q33 seems most strongly linked to autism, with linkages to multiple other loci under investigation. Cytogenetic abnormalities at the 15q11-q13 locus are fairly frequent in people with autism, and a "chromosome 15 phenotype" was described in individuals with chromosome 15 duplications. Among other candidate genes are the FOXP2, RAY1/ST7, IMMP2L, and RELN genes at 7q22-q33 and the GABA(A) receptor subunit and UBE3A genes on chromosome 15q11-q13. Variant alleles of the serotonin transporter gene (5-HTT) on 17q11-q12 are more frequent in individuals with autism than in nonautistic populations. In addition, animal models and linkage data from genome screens implicate the oxytocin receptor at 3p25-p26. Most pediatricians will have 1 or more children with this disorder in their practices. They must diagnose ASD expeditiously because early intervention increases its effectiveness. Children with dysmorphic features, congenital anomalies, mental retardation, or family members with developmental disorders are those most likely to benefit from extensive medical testing and genetic consultation. The yield of testing is much less in high-functioning children with a normal appearance and IQ and moderate social and language impairments. Genetic counseling justifies testing, but until autism genes are identified and their functions are understood, prenatal diagnosis will exist only for the rare cases ascribable to single-gene defects or overt chromosomal abnormalities. Parents who wish to have more children must be told of their increased statistical risk. It is crucial for pediatricians to try to involve families with multiple affected members in formal research projects, as family studies are key to unraveling the causes and pathogenesis of autism. Parents need to understand that they and their affected children are the only available sources for identifying and studying the elusive genes responsible for autism. Future clinically useful insights and potential medications depend on identifying these genes and elucidating the influences of their products on brain development and physiology.

Linkage of osteoporosis to chromosome 20p12 and association to BMP2

Osteoporotic fractures are a major cause of morbidity and mortality in ageing populations. Osteoporosis, defined as low bone mineral density (BMD) and associated fractures, have significant genetic components that are largely unknown. Linkage analysis in a large number of extended osteoporosis families in Iceland, using a phenotype that combines osteoporotic fractures and BMD measurements, showed linkage to Chromosome 20p12.3 (multipoint allele-sharing LOD, 5.10; p value, 6.3 x 10(-7)), results that are statistically significant after adjusting for the number of phenotypes tested and the genome-wide search. A follow-up association analysis using closely spaced polymorphic markers was performed. Three variants in the bone morphogenetic protein 2 (BMP2) gene, a missense polymorphism and two anonymous single nucleotide polymorphism haplotypes, were determined to be associated with osteoporosis in the Icelandic patients. The association is seen with many definitions of an osteoporotic phenotype, including osteoporotic fractures as well as low BMD, both before and after menopause. A replication study with a Danish cohort of postmenopausal women was conducted to confirm the contribution of the three identified variants. In conclusion, we find that a region on the short arm of Chromosome 20 contains a gene or genes that appear to be a major risk factor for osteoporosis and osteoporotic fractures, and our evidence supports the view that BMP2 is at least one of these genes.

Genomic approaches to understanding obstructive sleep apnea

Obstructive sleep apnea (OSA) is an increasingly recognized, common chronic disease in the developed nations and is a complex disease that has high social and economic costs. OSA and its associated 'intermediate' phenotypes-craniofacial structure, body fat distribution and metabolism, and neurological control of the upper airway muscles and of sleep and circadian rhythm-are under a substantial degree of genetic control. Investigating the genetic aetiology of OSA offers a means of better understanding its pathogenesis, with the goal of improving preventive strategies, diagnostic tools and therapies. Molecular studies of OSA itself are in their infancy, but considerable effort and expense has already been expended in attempts to detect genetic loci contributing to OSA-associated intermediate phenotypes, such as obesity. However, many of the fundamental questions relating to the genetic epidemiology of OSA and associated factors remain unanswered. This chapter reviews the current state of knowledge of the genetics of OSA, with a focus on genomic approaches to understanding sleep disorders.

deCODE genetics, Inc

deCODE genetics, Inc. has compiled the world's most comprehensive collection of population data on genealogy, genotypes and phenotypes. This combination of resources provides an effective system for identifying key genes linked to common diseases and to the regulation of drug response. deCODE has successfully mapped genes in over 25 common complex diseases and isolated genes in eight of these. The methodology used to map these genes is based upon the company's genealogical database of the Icelandic population, which enables deCODE scientists to efficiently conduct population- and genome-wide linkage studies to identify key genetic factors involved in phenotypes ranging from diseases to drug response. In its growing pharmacogenomics program, deCODE has combined this linkage approach with high-throughput expression profiling to develop accurate tests that can predict individual responsiveness to virtually any drug of interest. deCODE is applying its unrivaled discovery capabilities to bring to market new drugs, DNA-based diagnostic products and pharmacogenomic tests. The company believes that such tests will play a crucial role in delivering personalized medicine - contributing to the development of more effective means of diagnosing and treating disease by matching each patient with the most suitable drug.

A major susceptibility gene for asthma maps to chromosome 14q24

Asthma is a complex genetic disorder with a heterogeneous phenotype, largely attributed to the interactions among many genes and between these genes and the environment. Numerous loci and candidate genes have been reported to show linkage and association to asthma and atopy. Although some studies reporting these observations are compelling, no gene has been mapped that confers a sufficiently high risk of asthma to meet the stringent criteria for genomewide significance. Using 175 extended Icelandic families that included 596 patients with asthma, we performed a genomewide scan with 976 microsatellite markers. The families were identified by cross-matching a list of patients with asthma from the Department of Allergy/Pulmonary Medicine of the National University Hospital of Iceland with a genealogy database of the entire Icelandic nation. We detected linkage of asthma to chromosome 14q24, with an allele-sharing LOD score of 2.66. After we increased the marker density within the locus to an average of one microsatellite every 0.2 cM, the LOD score rose to 4.00. We designate this locus "asthma locus one" (AS1). Taken together, these results provide evidence of a novel susceptibility gene for asthma on chromosome 14q24.