Elevated risk of venous but not arterial thrombosis in Waldenström macroglobulinemia/lymphoplasmacytic lymphoma.

BACKGROUND: Many malignancies, including multiple myeloma and its precursor, monoclonal gammopathy of unknown significant, are associated with an elevated risk of thromboembolism. There is limited information on the risk of thrombosis in patients with Waldenström macroglobulinemia (WM) and lymphoplasmacytic lymphoma (LPL). OBJECTIVES: To assess the risk of venous and arterial thrombosis in WM/LPL patients in a large population-based cohort study in Sweden. PATIENTS/METHODS: A total of 2190 patients with WM/LPL and 8086 matched controls were identified through Swedish registers between 1987 and 2005. Information on occurrence of venous and arterial thrombosis after the diagnosis of WM/LPL was obtained through the centralized Swedish Patient Register, with follow-up to 2006. Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Patients with WM/LPL had a significantly increased risk of venous thrombosis and the highest risk was observed during the first year following diagnosis (HR = 4.0, 95% CI 2.5-6.4). The risk was significantly elevated 5 (HR = 2.3, 95% CI 1.7-3.0) and 10 years after diagnosis (HR = 2.0, 95% CI 1.6-2.5). There was no increased risk of arterial thrombosis during any period of follow-up time (10-year HR = 1.0, 95% CI 0.9-1.1). CONCLUSIONS: Venous thrombosis is a significant cause of morbidity in patients with WM/LPL. The potential role of thromboprophylaxis in WM/LPL, especially during the first year after diagnosis and in patients treated with thrombogenic agents, needs to be assessed to further improve outcome in WM/LPL patients.

Immunophenotypic and gene expression analysis of monoclonal B-cell lymphocytosis shows biologic characteristics associated with good prognosis CLL.

Monoclonal B-cell lymphocytosis (MBL) is a hematologic condition wherein small B-cell clones can be detected in the blood of asymptomatic individuals. Most MBL have an immunophenotype similar to chronic lymphocytic leukemia (CLL), and 'CLL-like' MBL is a precursor to CLL. We used flow cytometry to identify MBL from unaffected members of CLL kindreds. We identified 101 MBL cases from 622 study subjects; of these, 82 individuals with MBL were further characterized. In all, 91 unique MBL clones were detected: 73 CLL-like MBL (CD5(+)CD20(dim)sIg(dim)), 11 atypical MBL (CD5(+)CD20(+)sIg(+)) and 7 CD5(neg) MBL (CD5(neg)CD20(+)sIg(neg)). Extended immunophenotypic characterization of these MBL subtypes was performed, and significant differences in cell surface expression of CD23, CD49d, CD79b and FMC-7 were observed among the groups. Markers of risk in CLL such as CD38, ZAP70 and CD49d were infrequently expressed in CLL-like MBL, but were expressed in the majority of atypical MBL. Interphase cytogenetics was performed in 35 MBL cases, and del 13q14 was most common (22/30 CLL-like MBL cases). Gene expression analysis using oligonucleotide arrays was performed on seven CLL-like MBL, and showed activation of B-cell receptor associated pathways. Our findings underscore the diversity of MBL subtypes and further clarify the relationship between MBL and other lymphoproliferative disorders.

Methods for testing familial aggregation of diseases in population-based samples: application to Hodgkin lymphoma in Swedish registry data.

We use data on lymphoma in families of Hodgkin lymphoma (HL) cases from the Swedish Family Cancer Database (Hemminki et al. 2001) to illustrate survival methods for detecting familial aggregation in first degree relatives of case probands compared to first degree relatives of control probands, from registries that permit sampling of all cases. Because more than one case may occur in a given family, the first degree relatives of case probands are not necessarily independent, and we present procedures that allow for such dependence. A bootstrap procedure also accommodates matching of case and control probands by resampling the matching clusters, defined as the combined set of all first degree relatives of the matched case and control probands. Regarding families as independent sampling units leads to inferences based on "sandwich variance estimators" and accounts for dependencies from having more than one proband in a family, but not for matching. We compare these methods in analysis of familial aggregation of HL and also present simulations to compare survival analyses with analyses of binary outcome data.

Clinical characteristics of familial B-CLL in the National Cancer Institute Familial Registry.

In an ongoing study, families with two or more living cases of B-CLL in first-degree relatives have been recruited through physician and self-referral. Since 1967, 28 kindreds with 73 cases of B-CLL have been enrolled within the National Cancer Institute (NCI) Familial B-CLL Registry. Medical, clinical, and demographic information have been obtained from private physicians, patient interview, hospital records, and death certificates. We used SEER Registry data to compare characteristics of sporadic B-CLL to familial B-CLL. The mean age at diagnosis was approximately 10 years younger among familial cases (57.9 +/- 12.1) than that observed in sporadic cases (70.1 +/- 11.9). A higher percentage of second primary tumors among familial CLL cases compared to reports in sporadic was also observed (16% vs. 8.8%). However, the transformation rate to non-Hodgkin's lymphoma does not appear to be different from that reported for sporadic cases. In conclusion, we observed some differences between familial and sporadic cases; whether any of these characteristics affect survival time or severity of disease is unknown. The study of families with multiple B-CLL cases will aid in delineating the genes and environmental factors that may play a role in the development of both forms of B-CLL.

Use of weighted p-values in regional inference procedures.

Our previous studies have demonstrated that the power to detect linkage was improved by calculating a moving average of consecutive p-values in a small region as compared with testing all single p-values. The goal of this study was to test whether the power can be improved further with an alternative method whereby the middle p-values in the sequence were given more weight than the others. We also wanted to compare the moving average tests with multipoint linkage tests. The simulated extended pedigree data from the general population was analyzed to identify two major genes (MG1 and MG5) underlying two quantitative traits (Q1 and Q5). We used the variance components method implemented in the GENEHUNTER program to test for linkage of 14-marker regions each on chromosome 19 and chromosome 1 to the adjusted quantitative traits Q1 and Q5, respectively, in all 50 replicates. As before, we found that the moving average test was more powerful than a test based on single p-values. In some cases, the weighting procedure increased the power further and was similar to that of multipoint analysis, but this was not consistently found. In addition, all methods had low power and it is not possible to make a general conclusion that some weighting schemes are better than others.

Gene x environment interaction from case-control and case-case approaches.

Using the Genetic Analysis Workshop 12 data, we applied case-control and case-case approaches to study the effects of a major gene and its interaction with sex on the disease liability. Although no joint additive effect was simulated, the case-case approach detected a small but significant multiplicative interaction effect, which could not be explained by the effect of random error. Given that analyses of "real" data will not be made with the knowledge of the true effects a priori, this study showed that the measure of gene x environment interaction is critical and the definition of interaction should be explicit.

Suggestive evidence of a locus on chromosome 10p using the NIMH genetics initiative bipolar affective disorder pedigrees.

As part of a four-center NIMH Genetics Initiative on Bipolar Disorder, a genome screen using 365 markers was performed on 540 DNAs from 97 families, enriched for affected relative pairs. This is the largest uniformly ascertained and assessed linkage sample for this disease, and includes 232 subjects diagnosed with bipolar I (BPI), 32 with schizo-affective, bipolar type (SABP), 72 with bipolar II (BPII), and 88 with unipolar recurrent depression (UPR). A hierarchical set of definitions of affected status was examined. Under Model I, affected individuals were those with a diagnosis of BPI or SABP, Model II included as affected those fitting Model I plus BPII, and Model III included those fitting Model II plus UPR. This data set was previously analyzed using primarily affected sib pair methods. We report the results of nonparametric linkage analyses of the extended pedigree structure using the program Genehunter Plus. The strongest finding was a lod score of 2.5 obtained on chromosome 10 near the marker D10S1423 with diagnosis as defined under Model II. This region has been previously implicated in genome-wide studies of schizophrenia and bipolar disorder. Other chromosomal regions with lod scores over 1.50 for at least one Model Included chromosomes 8 (Model III), 16 (Model III), and 20 (Model I). Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:18-23, 2000

Variant genotypes of the low-affinity Fcgamma receptors in two control populations and a review of low-affinity Fcgamma receptor polymorphisms in control and disease populations.

Fcgamma-receptors (FcgammaR) provide a critical link between humoral and cellular immunity. The genes of the low-affinity receptors for IgG and their isoforms, namely, FcgammaRIIa, FcgammaRIIb, FcgammaRIIIa, FcgammaRIIIb, and SH-FcgammaRIIIb, are located in close proximity on chromosome 1q22. Variant alleles may differ in biologic activity and a number of studies have reported the frequencies of variant FcgammaR alleles in both disease and control populations. No large study has evaluated the possibility of a nonrandom distribution of variant genotypes. We analyzed 395 normal individuals (172 African Americans [AA] and 223 Caucasians [CA]) at the following loci: FcgammaRIIa, FcgammaRIIIa, and FcgammaRIIIb, including the SH-FcgammaRIIIb. The genotypic distributions of FcgammaRIIa, FcgammaRIIIa, and FcgammaRIIIb conform to the Hardy-Weinberg law in each group. There was no strong evidence that combinations of 2-locus genotypes of the 3 loci deviated from random distributions in these healthy control populations. The distribution of SH-FcgammaRIIIb is underrepresented in CA compared with AA (P < .0001) controls. A previously reported variant FcgammaRIIb was not detected in 70 normal individuals, indicating that this allele, if it exists, is very rare (<1%). In conclusion, we present data that should serve as the foundation for the interpretation of association studies involving multiple variant alleles of the low-affinity FcgammaR.

Assessment of estimation procedures for risk and onset hazard with dependent data.

Analysis of the role of candidate genes as risk factors for age-dependent hereditary conditions often ignores the importance of dependence among sibships or other family clusters for age of onset. We examined the performance of several methods of survival analysis with dependent data using Collaborative Study on the Genetics of Alcoholism families as submitted for GAW11. Additionally, an arbitrary truncation of cluster size was performed to explore the potential impact of heterogeneity of family size on the resulting inferences concerning the role of candidate genes. Our results showed substantial differences in attribution of risk to candidate genes according to whether the method utilized allowed for dependence in onset age and according to whether the sample was truncated or arbitrarily stratified. Further work needs to be done to clarify the importance of properly accounting for dependent data in age-dependent phenotypes and in integrating these methods into widely used genetic analysis computer programs.

Comparison of two linkage inference procedures for genes related to the P300 component of the event related potential.

Our goal was to detect genes contributing to the P300 component of the event related potential (ERP). We found that all of the ERP traits were highly correlated. Most of them distinguished alcoholics from nonalcoholics. To have one summary variable for the ERP traits, we calculated the first principal component (PRIN1). After adjusting for age and sex, we screened for linkage of PRIN1 to all of the markers using the two-point Haseman-Elston sib-pair test. We compared results obtained from computing a moving average of two-point p-values ("regional" inference) in an approximately 10 cM region with those obtained from single, two-point tests. Different "suggestive" and "significant" linkage regions were found using the two methods. Based on the regional method, areas on chromosomes 2 and 5 should be followed up in future studies.

Meta-analysis of linkage studies.

Lander and Kruglyak [1995] gave guidelines for interpreting linkage results based on estimating how often a particular threshold for significance would be exceeded by chance in a single genome scan. What is unknown is how often two or more genome scans would exceed a particular threshold within the same region. We develop theoretical estimates of these values and compare these with the empirical estimates derived from the GAW11 data. For single-point analysis, the theoretical estimates predict the empirical estimates. For multipoint analysis, the theoretical values overestimate what is observed. For both single point and multipoint, modest p-values within a single genome scan may give highly significant results when replicated in the same region in other scans.

Regional inference with averaged P values increases the power to detect linkage.

Controversy exists with respect to the choice of an appropriate critical value when testing for linkage in a genomic screen. A number of critical values have been proposed for single-locus and multi-locus linkage analyses. In this study, criteria based on multiple single-locus analyses (i.e., regional test criteria) are evaluated using simulation methods for three different map densities. Tests based on single loci, multiple consecutive single loci, and moving averages of consecutive single loci are considered. Appropriate critical values are determined based on results from simulations under the null hypothesis of no linkage. The power of each "regional test " was compared to the power of a single-locus test. Results suggest that the best power was found when averaging P values over an interval size of 9-15 cM, and that testing the average of P values from two consecutive loci is superior to testing each single locus separately. The increase in power ranged from 7- 29% over the simulations considered.

Follow-up study on a susceptibility locus for schizophrenia on chromosome 6q.

Evidence for suggestive linkage to schizophrenia with chromosome 6q markers was previously reported from a two-stage approach. Using nonparametric affected sib pairs (ASP) methods, nominal p-values of 0.00018 and 0.00095 were obtained in the screening (81 ASPs; 63 independent) and the replication (109 ASPs; 87 independent) data sets, respectively. Here, we report a follow-up study of this 50cM 6q region using 12 microsatellite markers to test for linkage to schizophrenia. We increased the replication sample size by adding an independent sample of 43 multiplex pedigrees (66 ASPs; 54 independent). Pairwise and multipoint nonparametric linkage analyses conducted in this third data set showed evidence consistent with excess sharing in this 6q region, though the statistical level is weaker (p=0.013). When combining both replication data sets (total of 141 independent ASPs), an overall nominal p-value=0.000014 (LOD=3. 82) was obtained. The sibling recurrence risk (lambdas) attributed to this putative 6q susceptibility locus is estimated to be 1.92. The linkage region could not be narrowed down since LOD score values greater than three were observed within a 13cM region. The length of this region was only slightly reduced (12cM) when using the total sample of independent ASPs (204) obtained from all three data sets. This suggests that very large sample sizes may be needed to narrow down this region by ASP linkage methods. Study of the etiological candidate genes in this region is ongoing.

A high-density genome scan detects evidence for a bipolar-disorder susceptibility locus on 13q32 and other potential loci on 1q32 and 18p11.2.

Bipolar disorder is a severe mental illness characterized by mood swings of elation and depression. Family, twin, and adoption studies suggest a complex genetic etiology that may involve multiple susceptibility genes and an environmental component. To identify chromosomal loci contributing to vulnerability, we have conducted a genome-wide scan on approximately 396 individuals from 22 multiplex pedigrees by using 607 microsatellite markers. Multipoint nonparametric analysis detected the strongest evidence for linkage at 13q32 with a maximal logarithm of odds (lod) score of 3.5 (P = 0. 000028) under a phenotype model that included bipolar I, bipolar II with major depression, schizoaffective disorder, and recurrent unipolar disorder. Suggestive linkage was found on 1q31-q32 (lod = 2. 67; P = 0.00022) and 18p11.2 (lod = 2.32; P = 0.00054). Recent reports have linked schizophrenia to 13q32 and 18p11.2. Our genome scan identified other interesting regions, 7q31 (lod = 2.08; P = 0. 00099) and 22q11-q13 (lod = 2.1; P = 0.00094), and also confirmed reported linkages on 4p16, 12q23-q24, and 21q22. By comprehensive screening of the entire genome, we detected unreported loci for bipolar disorder, found support for proposed linkages, and gained evidence for the overlap of susceptibility regions for bipolar disorder and schizophrenia.

Optimal ascertainment strategies to detect linkage to common disease alleles.

Traditionally, extended pedigrees with many affected individuals have been studied for the purpose of detection of linkage. For traits caused by a rare susceptibility allele, this is a productive strategy. However, this sampling strategy may not work well for traits determined by multiple loci in which one or more have common susceptibility alleles. We simulated three single-additive-locus models of inheritance and two-locus models with additive or multiplicative interactions, all with rare or common susceptibility alleles. A trait locus was linked, with no recombination, to a marker locus with four equally frequent alleles. Family structure varied, but the total number of affected individuals was held constant. Two generations of individuals were genotyped. We used three nonparametric affected-sib-pair programs and two nonparametric pedigree-analysis programs to perform linkage analysis. For single-locus, additive, and multiplicative models, we found that, when the susceptibility allele was rare, (frequency .0025), extended pedigrees with first or second cousins had the most power for detection of linkage. However, when the susceptibility allele was common in the single-locus, additive, and multiplicative two-locus models (frequency .25), extended pedigrees were no more powerful than nuclear families. There was also a decrease in power when the pedigrees had a greater number of affected individuals, more so for the single-locus and multiplicative models than for the additive model. We conclude that for single-locus, additive, and multiplicative models of qualitative traits with common alleles, there is no benefit to the collection of extended pedigrees, and there may be a loss of power in the collection of pedigrees with many affected individuals.

Closing in on genes for manic-depressive illness and schizophrenia.

Advances in the human genetic map, and in genetic analysis of linkage and association in complex inheritance traits, have led to genetic progress in the major psychoses. For chromosome 6 in schizophrenia, and chromosomes 18 and 21 in manic-depressive illness, there are reports of linkage in several independent data sets. These are small effect genes, best detected with affected-relative-pair linkage methods. Association with candidate genes is an alternative strategy to uncovering susceptibility genes for these illnesses, but convincing associations remain to be demonstrated. New clinical and laboratory investigation methods are being developed. Testing every gene in the human genome for association with illness has recently been proposed (Risch and Merikangas 1996). This would require further progress in characterizing the genome and in automated large-scale genotyping. The best type of pedigree sampling for common disease studies, whether for linkage or association, is not yet established. An endophenotype hybrid strategy can combine genetic linkage, association, and pathophysiologic studies. As clinical molecular investigation methods advance, identification of disease susceptibility mutations and delineation of their pathophysiological roles may be expected.

True and false positive peaks in genomewide scans: applications of length-biased sampling to linkage mapping.

Disease-susceptibility loci are now being mapped via genomewide scans in which a linkage statistic is computed at each of a large number of markers. Such disease-susceptibility loci may be identified via a peak in the test statistic when the latter is plotted against the genetic map. In this paper we establish, by appealing to renewal theory, that true positive peaks are expected to be longer than false positive peaks. These results are verified by a realistic simulation of a genomewide linkage study based on the affected-sib-pair design. Since longer peaks are more likely to contain a gene of interest than are shorter peaks, these differences may aid in linkage mapping, justifying assignment of lower priority to shorter peaks. However, since these differences are generally small, statistics based on both peak length and height may not be much more powerful than those based on height alone. The results presented here also provide a theoretical framework for methods that use the length of shared haplotypes in populations to map disease genes.