A multi-incident, Old-Order Amish family with PD

BACKGROUND

PD is largely a sporadic condition of unknown etiology, but specific inherited mutations are a cause of PD.

OBJECTIVE

To describe a large, multi-incident Amish pedigree with PD.

METHODS

Case ascertainment, calculation of population prevalence, and calculation of kinship coefficients (a measure of relatedness between two individuals) for affecteds and subjects in a large kindred with PD were conducted. Sequencing of genes with known mutations sufficient to cause PD and marker-by-marker haplotype analysis in chromosomal regions flanking previously described genes with known mutations were performed.

RESULTS

The authors have examined 113 members of this pedigree and classified 67 as normal (no evidence of PD), 17 as clinically definite PD, 6 as clinically probable PD, and 23 as clinically possible PD. The mean age at onset of the clinically definite subjects was 56.7 years. The phenotype in this family is typical of idiopathic PD, including rest tremor, rigidity, bradykinesia, postural instability, and response to levodopa. In addition, dementia occurred in six of the clinically definite subjects, and many subjects experienced levodopa-related motor complications including wearing off and dopa-induced dyskinesias. In the index Amish community, a minimum prevalence of PD in the population 40 years and older of 552/100,000 was calculated. The mean kinship coefficient in the subjects with PD and those with PD by history (0.036) was higher (p = 0.007) than in a group of age-matched normal Amish control subjects (0.016), providing evidence that PD is inherited in this family. Sequence analysis did not detect any mutations in known PD genes. No single haplotype cosegregates with the disease in any of the chromosomal regions previously found to be linked to PD, and no marker in these regions exhibits increased homozygosity among definite PD cases.

CONCLUSIONS

PD in this community is more common than in the general population, and this increased prevalence may be due in part to a novel gene(s).

Defining alcohol-related phenotypes in humans. The Collaborative Study on the Genetics of Alcoholism

Alcoholism is a disease that runs in families and results at least in part from genetic risk factors. The Collaborative Study on the Genetics of Alcoholism (COGA) is a Federally funded effort to identify and characterize those genetic factors. The study involves more than 1,000 alcoholic subjects and their families, with researchers conducting comprehensive psychological, physiological, electrophysiological, and genetic analyses of the participants. These analyses have identified several traits, or phenotypes, that appear to be genetically determined, such as the presence of alcohol dependence, the level of response to alcohol, the presence of coexisting depression, or the maximum number of drinks a person consumes per occasion. Genetic analyses have identified regions on several chromosomes that are associated with these phenotypes and need to be studied further.

A bootstrapped commingling analysis of platelet monoamine oxidase activity levels corrected for cigarette smoking

Monoamine oxidase (MAO) activity levels have been suggested as a possible biological marker for alcohol dependence and abuse, as well as for schizophrenia and other psychiatric conditions. Using platelet MAO activities in the Collaborative Study on the Genetics of Alcoholism data set, we applied bootstrapping methods as a novel way to test for admixture in families. This bootstrapping involved resampling in family units and hypothesis testing of the resampled datasets for commingling in the distribution of MAO activity levels. Prior to commingling analysis, we used linear models to find covariates of greatest effect on MAO activity levels. While an alcoholism diagnosis was significant in men (n = 1151, P < 0.0001) and women (n = 1254, P = 0.0003), the effect lost significance after controlling for cigarette smoking, indicating alcoholism and smoking behavior to be highly confounded. When smoking histories were compared, former smokers had levels (mean = 7.1) closer to those who never smoked (mean = 7.0) than to current smokers (mean = 5.4). Furthermore, current daily smoking and time since smoking cessation were significantly related to MAO levels, indicating smoking probably has a direct effect on MAO levels, rather than the reverse. These results suggest that studies using MAO levels as a biological marker should consider smoking as an important covariate. Finally, admixture was found in MAO levels controlled for smoking and sex, possibly indicating a major genetic locus; this confirms previous evidence for admixture.

Hereditary vascular retinopathy, cerebroretinal vasculopathy, and hereditary endotheliopathy with retinopathy, nephropathy, and stroke map to a single locus on chromosome 3p21.1-p21.3

We performed a genomewide search for linkage in an extended Dutch family with hereditary vascular retinopathy associated with migraine and Raynaud phenomenon. Patients with vascular retinopathy are characterized by microangiopathy of the retina, accompanied by microaneurysms and telangiectatic capillaries. The genome search, using a high throughput capillary sequencer, revealed significant evidence of linkage to chromosome 3p21.1-p21.3 (maximum pairwise LOD score 5.25, with D3S1578). Testing of two additional families that had a similar phenotype, cerebroretinal vasculopathy, and hereditary endotheliopathy with retinopathy, nephropathy, and stroke, revealed linkage to the same chromosomal region (combined maximum LOD score 6.30, with D3S1588). Haplotype analysis of all three families defined a 3-cM candidate region between D3S1578 and D3S3564. Our study shows that three autosomal dominant vasculopathy syndromes with prominent cerebroretinal manifestations map to the same 3-cM interval on 3p21, suggesting a common locus.

Mapping genotype to phenotype for linkage analysis

We model functions that use genetic information as input and trait information as output to understand genetic linkage in complex diseases. Using simulated data from GAW11, we have applied categorical classification methods and neural network analysis. We use sharing at selected markers as input, and the classification of the sib pair (for example, affected-affected or affected-unaffected) as output. In addition, our methods include environmental risk factors as predictors of phenotype. Categorical and neural network methods each led to results consistent with findings from other methods such as the logistic regression method of Rice et al. [this issue]. Post-analysis comparison with the GAW11 answers showed that these methods are capable of detecting correct signals in a single replicate. One advantage of our methods is that they allow analysis of the entire genome at once, so that interactions among multiple trait-influencing loci may be detected. Furthermore, these methods can use a variety of sib pairs rather than affected pairs only.

Clustering methods applied to allele sharing data

Here we focus on using clustering methods to disentangle the interacting factors that lead to the presentation of complex diseases. Relative pairs are placed in discrete subgroups, or classes, based upon their pattern of allele sharing at a sequence of markers and on concomitant risk factors. The relationship between the locus information and the affectation status of the relative pairs within each subgroup then can be assessed. Cluster analysis (CLA) and latent class analysis (LCA) were applied to sibling allele sharing data from GAW11 simulated data, and to an existing Alzheimer's disease (AD) dataset. Both methods were able to identify markers linked to all 3 disease loci in the GAW11 data. LCA and CLA also replicated regions of chromosomes identified in an analysis of the AD data using affected-sib-pair methods. These analyses indicate that classification tools may be useful for detecting susceptibility genes for complex traits.

The lod score method

The lod score method originated in a seminal article by Newton Morton in 1955. The method is broadly concerned with issues of power and the posterior probability of linkage, ensuring that a reported linkage has a high probability of being a true linkage. In addition, the method is sequential, so that pedigrees or lod curves may be combined from published reports to pool data for analysis. This approach has been remarkably successful for 50 years in identifying disease genes for Mendelian disorders. After discussing these issues, we consider the situation for complex disorders, where the maximum lod score (MLS) statistic shares some of the advantages of the traditional lod score approach but is limited by unknown power and the lack of sharing of the primary data needed to optimally combine analytic results. We may still learn from the lod score method as we explore new methods in molecular biology and genetic analysis to utilize the complete human DNA sequence and the cataloging of all human genes.

Definition of the phenotype

Definition of the phenotype is a key issue in designing any genetic study whose goal is to detect disease genes. This chapter describes strategies to increase the power to detect susceptibility loci for complex diseases. A narrowly defined disease phenotype can offer advantages over broad definitions. Studies of clinical disease can also benefit from judicious selection of endophenotypes and related quantitative traits for analysis. The effect of diagnostic and measurement error is also discussed; power is maximized when strategies to reduce error are incorporated into a study design.

A genome screen of maximum number of drinks as an alcoholism phenotype

The Collaborative Study on the Genetics of Alcoholism (COGA) is a multicenter research program to detect and map susceptibility genes for alcohol dependence and related phenotypes. The measure M of "maximum number of drinks consumed in a 24-hour period" is closely related to alcoholism diagnosis in this dataset and provides a quantitative measure to grade nonalcoholic individuals. Twin studies have shown log(M) to have a heritability of approximately 50%. Genome screens for this trait were performed in two distinct genotyped samples (wave 1 and wave 2), and in the combined sample. MAPMAKER/SIBS was used to carry out Haseman-Elston based regression analyses. On chromosome 4, an unweighted all-pairs multipoint LOD of 2.2 was obtained between D4S2407 and D4S1628 in wave 1; in wave 2, the region flanked by D4S2404 and D4S2407 gave a LOD of 1.5. In the combined sample, the maximal LOD was 3.5 very close to D4S2407. This evidence for linkage is in the region of the alcohol dehydrogenase gene cluster on chromosome 4. These findings on chromosome 4 are consistent with a prior report from COGA in which strictly defined nonalcoholic subjects in wave 1 were analyzed. The present analysis on log(M) allows more individuals to be included and thus is potentially more powerful.

Juxtaposed regions of extensive and minimal linkage disequilibrium in human Xq25 and Xq28

Linkage disequilibrium (LD), or the non-random association of alleles, is poorly understood in the human genome. Population genetic theory suggests that LD is determined by the age of the markers, population history, recombination rate, selection and genetic drift. Despite the uncertainties in determining the relative contributions of these factors, some groups have argued that LD is a simple function of distance between markers. Disease-gene mapping studies and a simulation study gave differing predictions on the degree of LD in isolated and general populations. In view of the discrepancies between theory and experimental observations, we constructed a high-density SNP map of the Xq25-Xq28 region and analysed the male genotypes and haplotypes across this region for LD in three populations. The populations included an outbred European sample (CEPH males) and isolated population samples from Finland and Sardinia. We found two extended regions of strong LD bracketed by regions with no evidence for LD in all three samples. Haplotype analysis showed a paucity of haplotypes in regions of strong LD. Our results suggest that, in this region of the X chromosome, LD is not a monotonic function of the distance between markers, but is more a property of the particular location in the human genome.

Linkage of a gene for familial hypobetalipoproteinemia to chromosome 3p21.1-22

Familial hypobetalipoproteinemia (FHBL) is an apparently autosomal dominant disorder of lipid metabolism characterized by less than fifth percentile age- and sex-specific levels of apolipoprotein beta (apobeta) and low-density lipoprotein-cholesterol. In a minority of cases, FHBL is due to truncation-producing mutations in the apobeta gene on chromosome 2p23-24. Previously, we reported on a four-generation FHBL kindred in which we had ruled out linkage of the trait to the apobeta gene. To locate other loci containing genes for low apobeta levels in the kindred, a genomewide search was conducted. Regions on 3p21.1-22 with two-point LOD scores >1.5 were identified. Additional markers were typed in the region of these signals. Two-point LOD scores in the region of D3S2407 increased to 3.35 at O = 0. GENEHUNTER confirmed this finding with an nonparametric multipoint LOD score of 7.5 (P=.0004). Additional model-free analyses were conducted with the square root of the apobeta level as the phenotype. Results from the Loki and SOLAR programs further confirmed linkage of FHBL to 3p21.1-22. Weaker linkage to a region near D19S916 was also indicated by Loki and SOLAR. Thus, a heretofore unidentified genetic susceptibility locus for FHBL may reside on chromosome 3.

Covariates in linkage analysis

We apply a novel technique to detect significant covariates in linkage analysis using a logistic regression approach. An overall test of linkage is first performed to determine whether there is significant perturbation from the expected 50% sharing under the hypothesis of no linkage; if the overall test is significant, the importance of the individual covariate is assessed. In addition, association analyses were performed. These methods were applied to simulated data from multiple populations, and detected correct marker linkages and associations. No population heterogeneity was detected. These methods have the advantages of using all sib pairs and of providing a formal test for heterogeneity across populations.

Genome screen for platelet monoamine oxidase (MAO) activity

To identify loci involved in the control of platelet monoamine oxidase B (MAO-B) activity, a genomewide linkage screen was performed using 291 markers in 148 nuclear families containing a total of 1,008 nonindependent sib-pairs. Participants were genotyped and their platelet MAO-B activity levels were measured as part of the Collaborative Study on the Genetics of Alcoholism (COGA). Sib-pair analysis using Haseman-Elston regression was carried out with two programs. Two-point analysis on all pairs with SIBPAL indicated three markers with p-values below 0.01: D6S1018 (p = 0.0004), D2S1328 (p = 0.008), and D2S408 (p = 0.003). MAPMAKER/SIBS multipoint analyses using independent pairs(N = 409) gave maximal lod scores of 2. 0 on chromosome 6 and 1.1 and 1.4 for the two regions on chromosome 2. These results are consistent with linkage, but do not provide definitive evidence. We are currently creating a denser map in these regions and have begun genotyping a second sample in COGA.