Joseph D. Terwilliger

A haplotype-based 'haplotype relative risk' approach to detecting allelic associations

A novel variation of the Haplotype Relative Risk (HRR) of Rubinstein et al. [Hum Immunol 1981;3:384] is proposed, in order to glean increased information about linkage disequilibrium or allelic associations by analyzing haplotype-based data rather than genotypic data. It is shown that statistical tests based on our design give much higher power than those based on the original HRR approach. Several additional nonparametric tests based on the same data are analyzed, and power is computed for each of them. Further, parametric likelihood methods are applied to testing linkage equilibrium, and estimating delta, the coefficient of linkage disequilibrium, from the same data.

How many diseases does it take to map a gene with SNPs

“They all talked at once, their voices insistent and contradictory and impatient, making of unreality a possibility, then a probability, then an incontrovertible fact, as people will when their desires become words.” —W. Faulkner, The Sound and the Fury, 1929

Large Upward Bias in Estimation of Locus-Specific Effects from Genomewide Scans

The primary goal of a genomewide scan is to estimate the genomic locations of genes influencing a trait of interest. It is sometimes said that a secondary goal is to estimate the phenotypic effects of each identified locus. Here, it is shown that these two objectives cannot be met reliably by use of a single data set of a currently realistic size. Simulation and analytical results, based on variance-components linkage analysis as an example, demonstrate that estimates of locus-specific effect size at genomewide LOD score peaks tend to be grossly inflated and can even be virtually independent of the true effect size, even for studies on large samples when the true effect size is small. However, the bias diminishes asymptotically. The explanation for the bias is that the LOD score is a function of the locus-specific effect-size estimate, such that there is a high correlation between the observed statistical significance and the effect-size estimate. When the LOD score is maximized over the many pointwise tests being conducted throughout the genome, the locus-specific effect-size estimate is therefore effectively maximized as well. We argue that attempts at bias correction give unsatisfactory results, and that pointwise estimation in an independent data set may be the only way of obtaining reliable estimates of locus-specific effect-and then only if one does not condition on statistical significance being obtained. We further show that the same factors causing this bias are responsible for frequent failures to replicate initial claims of linkage or association for complex traits, even when the initial localization is, in fact, correct. The findings of this study have wide-ranging implications, as they apply to all statistical methods of gene localization. It is hoped that, by keeping this bias in mind, we will more realistically interpret and extrapolate from the results of genomewide scans.

LINKAGE DISEQUILIBRIUM MAPPING OF COMPLEX DISEASE : FANTASY OR REALITY?

In the past year, data about the level and nature of linkage disequilibrium between alleles of tightly linked SNPs have started to become available. Furthermore, increasing evidence of allelic heterogeneity at the loci predisposing to complex disease has been observed, which has lead to initial attempts to develop methods of linkage disequilibrium detection allowing for this difficulty. It has also become more obvious that we will need to think carefully about the types of populations we need to analyze in an attempt to identify these elusive genes, and it is becoming clear that we need to carefully re-evaluate the prognosis of the current paradigm with regard to its robustness to the types of problems that are likely to exist.

Genomewide Scan of Multiple Sclerosis in Finnish Multiplex Families

Multiple sclerosis (MS) is a neurological, demyelinating disorder with a putative autoimmune etiology. It is thought to be a multifactorial disease with a complex mode of inheritance. Here we report the results of a two-stage genomewide scan for loci predisposing to MS. The first stage of the screen, with a low-resolution map, was performed in a selection of 16 pedigrees collected from an isolated Finnish population. Multipoint, non-parametric linkage analysis of the 328 markers did not reveal statistically significant results. However, 10 slightly interesting regions (P = .1-.15) emerged, including our previous findings of the HLA complex on 6p21 and a putative locus on 5p14-p12. Eight of these novel regions were further analyzed by use of denser marker maps, in the second stage of the scan. For the chromosomal regions 4cen, 11tel, and 17q, the statistical significance increased, but not conclusively; for 2q32 and 10q21, the statistical significance did not change. Accordingly, genotyping of the high-density markers in these regions was performed, and the data were analyzed by use of two-point, parametric linkage analysis using the complete pedigree information of the 21 Finnish multiplex families. We detected suggestive evidence for a predisposing locus on chromosomal region 17q22-q24. Several markers on 17q22-q24 yielded positive LOD scores, with the maximum LOD score (Zmax) occurring with D17S807 (Zmax = 2.8, theta = .04; dominant model). Interestingly, a suggestive linkage between MS and the markers on 17q22-q24 was also revealed by a recent genomewide scan in MS families from the United Kingdom.

A Genomewide Screen for Schizophrenia Genes in an Isolated Finnish Subpopulation, Suggesting Multiple Susceptibility Loci

Schizophrenia is a severe mental disorder affecting approximately 1% of the worlds population. Here, we report the results from a three-stage genomewide screen performed in a study sample from an internal isolate of Finland. An effort was made to identify genes predisposing for schizophrenia that are potentially enriched in this isolate, which has an exceptionally high lifetime risk for this trait. Ancestors of the local families with schizophrenia were traced back to the foundation of the population in the 17th century. This genealogical information was used as the basis for the study strategy, which involved screening for alleles shared among affected individuals originating from common ancestors. We found four chromosomal regions with markers revealing pairwise LOD scores>1.0: 1q32.2-q41 (Z(max)=3.82, dominant affecteds-only model), 4q31 (Z(max)=2. 74, dominant 90%-penetrance model), 9q21 (Z(max)=1.95, dominant 90%-penetrance model), and Xp11.4-p11.3 (Z(max)=2.01, recessive 90%-penetrance model). This finding suggests that there are several putative loci predisposing to schizophrenia, even in this isolate.

A Genomewide Screen of 345 Families for Autism-Susceptibility Loci

We previously reported a genomewide scan to identify autism-susceptibility loci in 110 multiplex families, showing suggestive evidence (P <.01) for linkage to autism-spectrum disorders (ASD) on chromosomes 5, 8, 16, 19, and X and showing nominal evidence (P <.05) on several additional chromosomes (2, 3, 4, 10, 11, 12, 15, 18, and 20). In this follow-up analysis we have increased the sample size threefold, while holding the study design constant, so that we now report 345 multiplex families, each with at least two siblings affected with autism or ASD phenotype. Along with 235 new multiplex families, 73 new microsatellite markers were also added in 10 regions, thereby increasing the marker density at these strategic locations from 10 cM to approximately 2 cM and bringing the total number of markers to 408 over the entire genome. Multipoint maximum LOD scores (MLS) obtained from affected-sib-pair analysis of all 345 families yielded suggestive evidence for linkage on chromosomes 17, 5, 11, 4, and 8 (listed in order by MLS) (P <.01). The most significant findings were an MLS of 2.83 (P =.00029) on chromosome 17q, near the serotonin transporter (5-hydroxytryptamine transporter [5-HTT]), and an MLS of 2.54 (P =.00059) on 5p. The present follow-up genome scan, which used a consistent research design across studies and examined the largest ASD sample collection reported to date, gave either equivalent or marginally increased evidence for linkage at several chromosomal regions implicated in our previous scan but eliminated evidence for linkage at other regions.

Gene Mapping in the 20th and 21st Centuries: Statistical Methods, Data Analysis, and Experimental Design

Abstract In the 20th century geneticists began to unravel some of the simpler aspects of the etiology of inherited diseases in humans. The theory of linkage analysis was developed and applied long before the advent of molecular biology, but only the technological advances of the second half of the 20th century made large-scale gene mapping with a dense genome-spanning set of markers a reality. More recently, the primary topic of interest has shifted from simple Mendelian diseases, for which genotypes of some gene are the cause of disease, to more complex diseases, for which genotypes of some set of genes together with environmental factors merely alter the probability that an individual gets the disease, although individual factors are typically insufficient to cause the disease outright. To this end, a great deal of dogma has evolved about the best way to skin this cat, although to date success has been minimal with any approach. We postulate that the main reason for this is a lack of attention to experimental design. Once the data have been ascertained, the most powerful statistical methods will not be able to salvage an inappropriately designed study (Andersen 1990). Each phenotype and/or population mandates its own individually tailored study design to maximize the chances of successful gene mapping. We suggest that careful consideration of the available data from real genotype-phenotype correlation studies (as opposed to oversimplified theoretically tractable models), and the practical feasibility of different ascertainment schemes dictate how one should proceed. In this review we review the theory and practice of gene mapping at the close of the 20th century, showing that most methods of linkage and linkage disequilibrium analysis are similar in a fundamental sense, with the differences being related more to study design and ascertainment than to technical details of the underlying statistical analysis. To this end, we propose a new focus in the field of statistical genetics that more explicitly highlights the primacy of study design as the means to increase power for gene mapping.

Candidate Endophenotypes for Genetic Studies of Suicidal Behavior

Twin, adoption, and family studies have established the heritability of suicide attempts and suicide. Identifying specific suicide diathesis-related genes has proven more difficult. As with psychiatric disorders in general, methodological difficulties include complexity of the phenotype for suicidal behavior and distinguishing suicide diathesis-related genes from genes associated with mood disorders and other suicide-associated psychiatric illness. Adopting an endophenotype approach involving identification of genes associated with heritable intermediate phenotypes, including biological and/or behavioral markers more proximal to genes, is an approach being used for other psychiatric disorders. Therefore, a workshop convened by the American Foundation for Suicide Prevention, the Department of Psychiatry at Columbia University, and the National Institute of Mental Health sought to identify potential target endophenotypes for genetic studies of suicidal behavior. The most promising endophenotypes were trait aggression/impulsivity, early-onset major depression, neurocognitive function, and cortisol social stress response. Other candidate endophenotypes requiring further investigation include serotonergic neurotransmission, second messenger systems, and borderline personality disorder traits.

Two Loci on Chromosomes 2 and X for Premature Coronary Heart Disease Identified in Early- and Late-Settlement Populations of Finland

Coronary heart disease (CHD) is a complex disorder constituting a major health problem in Western societies. To assess the genetic background of CHD, we performed a genomewide linkage scan in two study samples from the genetically isolated population of Finland. An initial study sample consisted of family material from the northeastern part of Finland, settled by a small number of founders approximately 300 years ago. A second study sample originated from the southwestern region of Finland, settled approximately 2,000 years ago. Families were ascertained through probands exhibiting premature CHD, defined as >50% stenosis of at least two coronary arteries at a young age, as verified by coronary angiography. Both study samples and the pooled data set provided evidence for linkage in two chromosomal regions. A region on chromosome 2q21.1-22 yielded two-point LOD scores of 3.2, 1.9, and 3.7, in the affected sib-pair (ASP) analyses of the northeastern, southwestern, and pooled study samples. The corresponding multipoint maximum-likelihood scores (MLSs) for these three study samples were 2.4, 1.3, and 3.0. In addition, a region on chromosome Xq23-26 resulted in two-point LOD scores of 1.9, 3.5, and 2.9 and in multipoint MLSs of 3.4, 3.1, and 2.5, respectively. In conclusion, this study identifies two loci likely to contribute to premature CHD: one on chromosome 2q21.1-22 and another on chromosome Xq23-26.