Meta-analysis of 32 genome-wide linkage studies of schizophrenia.

A genome scan meta-analysis (GSMA) was carried out on 32 independent genome-wide linkage scan analyses that included 3255 pedigrees with 7413 genotyped cases affected with schizophrenia (SCZ) or related disorders. The primary GSMA divided the autosomes into 120 bins, rank-ordered the bins within each study according to the most positive linkage result in each bin, summed these ranks (weighted for study size) for each bin across studies and determined the empirical probability of a given summed rank (P(SR)) by simulation. Suggestive evidence for linkage was observed in two single bins, on chromosomes 5q (142-168 Mb) and 2q (103-134 Mb). Genome-wide evidence for linkage was detected on chromosome 2q (119-152 Mb) when bin boundaries were shifted to the middle of the previous bins. The primary analysis met empirical criteria for 'aggregate' genome-wide significance, indicating that some or all of 10 bins are likely to contain loci linked to SCZ, including regions of chromosomes 1, 2q, 3q, 4q, 5q, 8p and 10q. In a secondary analysis of 22 studies of European-ancestry samples, suggestive evidence for linkage was observed on chromosome 8p (16-33 Mb). Although the newer genome-wide association methodology has greater power to detect weak associations to single common DNA sequence variants, linkage analysis can detect diverse genetic effects that segregate in families, including multiple rare variants within one locus or several weakly associated loci in the same region. Therefore, the regions supported by this meta-analysis deserve close attention in future studies.

TGFBR1*6A is not associated with prostate cancer in men of European ancestry.

The TGFBR1*6A (*6A) variant in exon 1 of the TGFBR1 gene has been postulated as a putative tumor susceptibility allele in several studies. We have performed a case-control study in 537 men with histologically verified prostate cancer and in 488 unrelated controls to investigate the association of *6A with prostate cancer. Our results revealed that the frequency of the (*)6A allele does not differ in men with prostate cancer compared to healthy controls, even in a subset of age-matched cases and controls. There is no compelling evidence for an association of the *6A variant with prostate cancer.

Polymorphisms in the prostate cancer susceptibility gene HPC2/ELAC2 in multiplex families and healthy controls.

Two polymorphisms in the newly cloned prostate cancer susceptibility gene, HPC2/ELAC2, are suspected to be associated with an increased risk of developing the disease. These missense variants result in a serine (S) to leucine (L) substitution at amino acid residue 217 and an alanine (A) to threonine (T) substitution at residue 541. We genotyped these polymorphisms in 257 multiplex prostate cancer sibships and in 355 race-matched healthy unrelated controls. A significant increase in the frequency of the T allele is seen in the prostate cancer subjects compared with controls. There is, however, little evidence for excess clustering of the T allele within the multiplex families known to be segregating this allele, and there is no evidence for linkage of prostate cancer to the HPC2/ELAC2 region of chromosome 17p11.2 in these families. The T allele shows no association with either Gleason score or age-of-onset in segregating families.

Model-free linkage analysis with covariates confirms linkage of prostate cancer to chromosomes 1 and 4.

As with many complex genetic diseases, genome scans for prostate cancer have given conflicting results, often failing to provide replication of previous findings. One factor contributing to the lack of consistency across studies is locus heterogeneity, which can weaken or even eliminate evidence for linkage that is present only in a subset of families. Currently, most analyses either fail to account for locus heterogeneity or attempt to account for it only by partitioning data sets into smaller and smaller portions. In the present study, we model locus heterogeneity among affected sib pairs with prostate cancer by including covariates in the linkage analysis that serve as surrogate measures of between-family linkage differences. The model is a modification of the Olson conditional logistic model for affected relative pairs. By including Gleason score, age at onset, male-to-male transmission, and/or number of affected first-degree family members as covariates, we detected linkage near three locations that were previously identified by linkage (1q24-25 [HPC1; LOD score 3.25, P=.00012], 1q42.2-43 [PCAP; LOD score 2.84, P=.0030], and 4q [LOD score 2.80, P=.00038]), near the androgen-receptor locus on Xq12-13 (AR; LOD score 3.06, P=.00053), and at five new locations (LOD score > 2.5). Without covariates, only a few weak-to-moderate linkage signals were found, none of which replicate findings of previous genome scans. We conclude that covariate-based linkage analysis greatly improves the likelihood that linked regions will be found by incorporation of information about heterogeneity within the sample.

A genome scan for type 2 diabetes susceptibility loci in a genetically isolated population.

A total of 896 individuals of Ashkenazi Jewish descent were ascertained in Israel from 267 multiplex families, including 472 sib-pairs affected with type 2 diabetes. A genome-wide scan with average marker spacing of 9.5 cM revealed five regions on four chromosomes (4q, 8q, 14q, and 20q) that exhibited nominal evidence for linkage (P < 0.05). The highest observed nonparametric linkage Z score was 2.41 (equivalent to a logarithm of odds score of 1.26) at marker D4S1501. A maximal signal, with a Z score of 2.05, was observed on chromosome 20 near marker D20S195, and another on 20p near marker D20S103 (Z 1.80). A single marker on chromosome 8 (D8S593) and two adjacent markers on chromosome 14 (D14S749 and D14S605) also attained evidence of linkage. To explore the hypothesis that the signals on chromosomes 4 and 20 are differentially attributable to variation in BMI or age of onset, an ordered subset analysis was conducted. This analysis revealed that only when the families were ranked by BMI (in increasing order) did a subset attain nominal significance, and only for chromosome 4. The findings reported here lend credence to the hypothesis, now supported by four studies of Caucasian populations and most recently by a combined analysis of 1,852 pedigrees, that a type 2 diabetes susceptibility locus resides on chromosome 20q. This population, because of its unique genetic attributes, may facilitate identification of this and other genes contributing to type 2 diabetes.

Linkage and association: basic concepts.

Many investigators are turning their efforts to dissecting the etiology of complex traits. The primary tools for gene discovery, localization, and functional analysis are linkage and association studies. While the conceptual underpinnings of these approaches have long been known, advances in recent decades in molecular genetics, in the development of efficient computational algorithms, and in computing power have enabled the large-scale application of these methods. Here, we review the biological basis of linkage and association among loci and the common methods used to assess these relationships with respect to observed phenotypes. We further consider the two most common approaches--genome scans and candidate gene studies--especially their respective strengths, weaknesses, and resource requirements. Finally, we highlight some of the major challenges that arise from these investigative approaches and those that are inherent in the nature of complex traits. The chapters that follow elaborate on many of these topics.

Identification of a gene frequently mutated in prostate tumors.

Although prostate cancer is the second leading cause of cancer death for men in the United States, the genetics of tumor development are poorly understood. Several expressed sequence tagged genes (ESTs) that are expressed predominantly in the prostate have recently been identified, although their role in the development and maintenance of the prostate is unknown. Here, we demonstrate that the gene identified as UNIGENE cluster Hs. 104215, which codes for a message found predominantly in the prostate, may be important in tumor development. We name this gene PCan1 for Prostate Cancer gene 1. Northern blot experiments were performed using RNA isolated from tumor-derived cell lines and human prostate to determine the expression pattern of the gene. DNA sequencing was used to identify mutations that occurred in tumor tissue. By Northern blot analysis, this gene product was not detectable in LNCaP, DU 145, or PC-3 prostate cancer cell lines, although it was readily observed in RNA isolated from total prostate and from dissected central and peripheral regions of prostate. Sequence analysis of genomic DNA from LNCaP, DU 145, or PC-3 cells demonstrated a G/A polymorphism at position 193. Analysis of matched tumor-derived DNA and blood-derived DNA samples from 11 of 13 patients who had undergone a radical prostatectomy and who were homozygous for A in blood-derived DNA demonstrated mutation of position 193 in matched tumor samples resulting in G/A polymorphism. Sixteen additional patient samples were G/A polymorphic in both blood-derived DNA and tumor-derived DNA and two samples were GG in both blood-derived and tumor-derived DNA. Our results suggest that this gene may be a hot spot for mutation in prostate cancer, especially because our radiation hybrid mapping located this gene within a region identified in linkage mapping studies of affected families with prostate cancer. Loss of heterozygosity in prostate tumors has also been reported at the location of PCan1. Further studies to determine the functional role of this candidate tumor suppressor gene are warranted.

A kinship analysis of asthma among the Hutterites.

A formal kinship analysis of asthma in a large Hutterite kindred indicates that cases are significantly more related to one another than are age matched controls. The higher kinship coefficient is shown to be due to an increased probability of the condensed identity state delta 8 which, in turn, is shown to be due to an increased probability of detailed identity state delta 10.

Exploiting linkage disequilibrium in population isolates.

A comparison of haplotype frequencies between unrelated cases and controls from population isolates identifies a strong signal for the presence/absence of the discrete phenotype in an interval on chromosome 6 bounded by markers 34 and 35. We define a dissimilarity index, D, which is sensitive to differences in allele distributions and differences in the patterns of linkage disequilibrium between cases and controls. We describe two statistical methods to utilize D: a method appropriate for a single moderately sized sample and a sequential approach appropriate for multiple small independent samples.

Replication linkage study for prostate cancer susceptibility genes.

BACKGROUND: Since the publication of the first genome screen for prostate cancer (CaP) 5 years ago, over a dozen linkage studies have appeared. Most attention has been directed to chromosome 1, where two separate regions have been identified as harboring a prostate cancer susceptibility locus: HPC1 in the 1q24-25 interval and PCaP in the 1q42.2-43 interval. Linkage analysis of chromosome 16 has also provided evidence of harboring two loci predisposing to CaP. METHODS: We report on a replication linkage study of chromosomes 1 and 16 in 45 new and 4 expanded multiplex CaP families. Multipoint Z-scores were obtained for 30 highly polymorphic short-sequence tandem repeat markers spanning chromosome 1, and 22 markers spanning chromosome 16. RESULTS: The replication sample gave no evidence for a CaP susceptibility locus in the 1q24-25 interval and equivocal evidence for such a locus at 1q42.2-43. With respect to chromosome 16, positive Z-scores were obtained over a contiguous interval covering the entire p arm and the proximal half of the q arm. CONCLUSIONS: The linkage analysis of our replication sample does not support the existence of HPC1, and the evidence for the existence of PCaP remains equivocal. Evidence of a susceptibility locus on 16p remains strong, but the evidence for a susceptibility locus on 16q is weakened.

Genomewide scan for prostate cancer-aggressiveness loci.

The aggressiveness of prostate cancer (PCa) varies widely: some tumors progress to invasive, potentially life-threatening disease, whereas others stay latent for the remainder of an individual's lifetime. The mechanisms resulting in this variability are not yet understood, but they are likely to involve both genetic and environmental influences. To investigate genetic factors, we conducted a genomewide linkage analysis of 513 brothers with PCa, using the Gleason score, which reflects tumor histology, as a quantitative measure of PCa aggressiveness. To our knowledge, this is the first time that a measure of PCa aggressiveness has been directly investigated as a quantitative trait in a genomewide scan. We employed a generalized multipoint Haseman-Elston linkage-analysis approach that regresses the mean-corrected cross product between the brothers' Gleason scores on the estimated proportion of alleles shared by brothers identical by descent at each marker location. Our results suggest that candidate regions on chromosomes 5q, 7q, and 19q give evidence for linkage to PCa-aggressiveness genes. In particular, the strongest signals detected in these regions were at the following markers (with corresponding P values): for chromosome 5q31-33, between markers D5S1480 and D5S820 (P=.0002); for chromosome 7q32, between markers D7S3061 and D7S1804 (P=.0007); and, for chromosome 19q12, at D19S433 (P=.0004). This indicates that one or more of these candidate regions may contain genes that influence the progression of PCa from latent to invasive disease. Identification of such genes would be extremely valuable for elucidation of the mechanism underlying PCa progression and for determination of treatment in men in whom this disease has been diagnosed.

A genome screen of multiplex sibships with prostate cancer.

Analysis of a genome screen of 504 brothers with prostate cancer (CaP) who were from 230 multiplex sibships identified five regions with nominally positive linkage signals, on chromosomes 2q, 12p, 15q, 16p, and 16q. The strongest signal in these data is found on chromosome 16q, between markers D16S515 and D16S3040, a region suspected to contain a tumor-suppressor gene. On the basis of findings from previous genome screens of families with CaP, three preplanned subanalyses were carried out, in the hope of increasing the subgroup homogeneity. Subgroups were formed by dividing the sibships into a group with a positive family history (FH+) that met criteria for "hereditary" CaP (n=111) versus those which did not meet the criteria (n=119) and by dividing the families into those with a mean onset age below the median (n=115) versus those with a mean onset age above the median (n=115). A separate subanalysis was carried out for families with a history of breast cancer (CaB+ [n=53]). Analyses of these subgroups revealed a number of potentially important differences in regions that were nonsignificant when all the families were analyzed together. In particular, the subgroup without a positive family history (FH-) had a signal in a region that is proximal to the putative site of the HPC1 locus on chromosome 1, whereas the late-age-at-onset group had a signal on 4q. The CaB+ subgroup revealed a strong linkage signal at 1p35.1.

Markov chain Monte Carlo linkage analysis of a complex qualitative phenotype.

We tested a new computer program, LOKI, that implements a reversible jump Markov chain Monte Carlo (MCMC) technique for segregation and linkage analysis. Our objective was to determine whether this software, designed for use with continuously distributed phenotypes, has any efficacy when applied to the discrete disease states of the simulated data from the Mordor data from GAW Problem 1. Although we were able to identify the genomic location for two of the three quantitative trait loci by repeated application of the software, the MCMC sampler experienced significant mixing problems indicating that the method, as currently formulated in LOKI, was not suitable for the discrete phenotypes in this data set.

Genetic dissection of a complex trait.

A number of genetic and statistical tools were applied to various partitions of the simulated data to identify susceptibility loci, relevant environmental factors, and their interaction(s). The distribution of genotypes at D1G24 among affected children in the first population was found to differ significantly from Hardy-Weinberg expectation. Two transmission/disequilibrium tests identified the preferential transmission of allele 1 as the source of the disequilibrium. Simple contingency table analysis revealed a positive association between exposure to environmental factor E1 and disease phenotype. Multipoint linkage analyses on various subsets of the data identified three "signal" regions (in addition to the aforementioned D1G24) localized at D1G9-10, D3G45, and D5G38. The even numbered chromosomes appeared to be devoid of susceptibility loci. Further analyses of subsamples of affected sib pairs, selected according to their disease phenotype and their exposure to E1, clarified some linkage relationships, particularly for D3G45, thereby suggesting the presence of a specific gene x environment interaction. Logistic analysis designed to clarify the relationship between disease phenotype and two risk factors (E1 exposure and the presence of allele 1 at D1G24) in the first population, revealed a significantly negative interaction which, upon learning the details of the generating model, we now attribute to the presence of heterogeneity.

Genome-wide search for schizophrenia susceptibility loci: the NIMH Genetics Initiative and Millennium Consortium.

Schizophrenia has a complex pattern of inheritance, indicative of interactions among multiple genes and environmental factors. The detection and replication of specific susceptibility loci for such complex disorders are facilitated by the availability of large samples of affected sib pairs and their nuclear families, along with standardized assessment and systematic ascertainment procedures. The NIMH Genetics Initiative on Schizophrenia, a multisite collaborative study, was established as a national resource with a centralized clinical data base and cell repository. The Millennium Schizophrenia Consortium has completed a genome-wide scan to detect susceptibility loci for schizophrenia in 244 individuals from the nuclear families of 92 independent pairs of schizophrenic sibs ascertained by the NIMH Genetics Initiative. The 459 marker loci used in the scan were spaced at 10-cM intervals on average. Individuals of African descent were higher than those of European descent in their average heterozygosity (79% vs. 76%, P < .0001) and number of alleles per marker (9.2 vs. 8.4, P < .0001). Also, the allele frequencies of 73% of the marker loci differed significantly (P < .01) between individuals of European and African ancestry. However, regardless of ethnic background, this sample was largely comprised of schizophrenics with more than a decade of psychosis associated with pervasive social and occupational impairment.

No evidence for a schizophrenia susceptibility gene in the vicinity of IL2RB on chromosome 22.

Pulver et al. [1994a] reported modest linkage evidence for a dominantly (D) inherited "schizophrenia gene" in the vicinity of IL2RB on chromosome 22q12, and Coon et al. [1994] adduced moderate evidence under a recessive (R) model. We report here a replication study to test the hypothesis that one of these two models (or a third, intermediate (I) model) adequately describes the co-segregation of schizophrenia and chromosome 22q12 markers in an independent sample of 23 multiplex families. Altogether nine transmission models were evaluated. The models differed depending on whether the 15 family members with a diagnosis of schizophrenia spectrum disorders were considered unaffected (a "narrow" (N) definition), affected (a "wide" (W) definition), or declared "unknown" (U). The entire region between D22S268 and D22S307 is excluded (i.e., lod <-2) for models RN, RW, RU, and IW. Lod scores for the remaining models are uniformly negative; albeit, equivocal with respect to the dominant hypothesis over a small region between D22S268 and IL2RB. Nonparametric analysis under both diagnostic criteria also failed to yield any evidence for a susceptibility locus in this region of chromosome 22.

Sequence variants in the pancreatic islet beta-cell inwardly rectifying K+ channel Kir6.2 (Bir) gene: identification and lack of role in Caucasian patients with NIDDM.

Signals derived from the metabolism of glucose in pancreatic beta-cells lead to insulin secretion via the closure of ATP-sensitive K+ channels (KATP). The cloning of the gene encoding the beta-cell inward rectifier Kir6.2 (Bir), a subunit of the beta-cell KATP channel, provided the opportunity to look for mutations in this gene that might contribute to the impaired insulin secretion of NIDDM. By single-strand conformational polymorphism (SSCP) analysis on 35 Northern-European Caucasian patients with NIDDM, six sequence variants were detected: Glu10gag-->Lys10aag (E1OK), Glu23gag-->Lys23aag (E23K), Leu270ctg-->Val270gtg (L270V), Ile337atc-->Val337gtc (I337V), and two silent mutations. Allelic frequencies for the missense variants were compared between the NIDDM group (n = 306) and nondiabetic control subjects (n = 175) and did not differ between the two groups. Pairwise allelic associations indicated significant linkage disequilibrium between the variants in Kir6.2 and between them and a nearby pancreatic beta-cell sulfonylurea receptor (SUR1) missense variant (S1370A), but these linkage disequilibria did not differ between the NIDDM and control groups. The results of these studies thus revealed that mutations in the coding region of Kir6.2 1) were not responsible for the previously noted association of the SUR1 variants with NIDDM (Inoue H et al., Diabetes 45:825-831, 1996) and 2) did not contribute to the impaired insulin secretion characteristic of NIDDM in Caucasian patients.

The utility of deviant sib pairs in the detection of linkage.

A tripartite sampling design was used to help deduce the genetic structure of a complex biological system. Univariate and multivariate population parameters were estimated from an age/sex stratified sample of unrelated individuals. Estimates of familial resemblance between and within continuous variables were obtained from a sample of randomly ascertained nuclear families. Finally, a sample of highly deviant concordant and discordant independent sib pairs facilitated the discovery of major genes through multipoint linkage analysis. No false positive signals were inferred. The pleiotropic effects of major genes, however, became obscured when linkage analysis was performed on adjusted quantitative variables.

Familial aspects of prostate cancer: a case control study.

PURPOSE: We evaluated the importance of positive family history, age at diagnosis and history of vasectomy in predicting the risk for prostate cancer in the brothers of prostate cancer patients. MATERIALS AND METHODS: A total of 1,084 men with newly diagnosed prostate cancer responded by interview to a family history survey, which included detailed information on the diagnosis of any cancer in the parents of the proband, diagnosis of prostate cancer in male relatives and age at onset of prostate cancer in the proband. A history of vasectomy was also obtained from the proband. The control cases consisted of 935 spouses of the probands who were administered the same questionnaire in an identical fashion. RESULTS: Prostate cancer was not significantly associated with other types of cancer in proband parents. The presence of prostate cancer in the father, grandfather or uncle of the proband significantly increased the risk of prostate cancer in proband brothers. Early age at onset in the proband was also associated with an increased risk to the proband brothers. CONCLUSIONS: Men with a family history of prostate cancer are at a significantly increased risk for prostate cancer, especially if the affected relative had early onset of cancer. Prostate cancer does not seem to be associated with a higher incidence of other cancers in family members.