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Genome-wide association studies (GWASs) have identified numerous lung cancer risk-associated loci. However, decoding molecular mechanisms of these associations is challenging since most of these genetic variants are non-protein-coding with unknown function. Here, we implemented massively parallel reporter assays (MPRAs) to simultaneously measure the allelic transcriptional activity of risk-associated variants. We tested 2,245 variants at 42 loci from 3 recent GWASs in East Asian and European populations in the context of two major lung cancer histological types and exposure to benzo(a)pyrene. This MPRA approach identified one or more variants (median 11 variants) with significant effects on transcriptional activity at 88% of GWAS loci. Multimodal integration of lung-specific epigenomic data demonstrated that 63% of the loci harbored multiple potentially functional variants in linkage disequilibrium. While 22% of the significant variants showed allelic effects in both A549 (adenocarcinoma) and H520 (squamous cell carcinoma) cell lines, a subset of the functional variants displayed a significant cell-type interaction. Transcription factor analyses nominated potential regulators of the functional variants, including those with cell-type-specific expression and those predicted to bind multiple potentially functional variants across the GWAS loci. Linking functional variants to target genes based on four complementary approaches identified candidate susceptibility genes, including those affecting lung cancer cell growth. CRISPR interference of the top functional variant at 20q13.33 validated variant-to-gene connections, including RTEL1, SOX18, and ARFRP1. Our data provide a comprehensive functional analysis of lung cancer GWAS loci and help elucidate the molecular basis of heterogeneity and polygenicity underlying lung cancer susceptibility., Competing Interests: Declaration of interests The authors declare no competing interests., (Published by Elsevier Inc.)

Cancer biomarker research has become a data-intensive discipline requiring innovative approaches for data analysis that can combine traditional and data-driven methods. Significant leveraging can be done transferring methodologies and capabilities across scientific disciplines, such as planetary science and astronomy, each of which are grappling with and developing similar solutions for the analysis of massive scientific data., (Published by Elsevier Inc.)

Genome-wide association studies have successfully identified a subset of common variants associated with lung cancer risk. However, these variants explain only a fraction of lung cancer heritability. It has been proposed that low-frequency or rare variants might have strong effects and contribute to the missing heritability. To assess the role of low-frequency or rare variants in lung cancer development, we analyzed exome chips representing 1,348 lung cancer subjects and 1,998 control subjects during the discovery stage and subsequently evaluated promising associations in an additional 4,699 affected subjects and 4,915 control subjects during the replication stages. Single-variant and gene-based analyses were carried out for coding variants with a minor allele frequency less than 0.05. We identified three low-frequency missense variants in BAT2 (rs9469031, c.1544C>T [p.Pro515Leu]; odds ratio [OR] = 0.55, p = 1.28 × 10(-10)), FKBPL (rs200847762, c.410C>T [p.Pro137Leu]; OR = 0.25, p = 9.79 × 10(-12)), and BPIFB1 (rs6141383, c.850G>A [p.Val284Met]; OR = 1.72, p = 1.79 × 10(-7)); these variants were associated with lung cancer risk. rs9469031 in BAT2 and rs6141383 in BPIFB1 were also associated with the age of onset of lung cancer (p = 0.001 and 0.006, respectively). BAT2 and FKBPL at 6p21.33 and BPIFB1 at 20q11.21 were differentially expressed in lung tumors and paired normal tissues. Gene-based analysis revealed that FKBPL, in which two independent variants were identified, might account for the association with lung cancer risk at 6p21.33. Our results highlight the important role low-frequency variants play in lung cancer susceptibility and indicate that candidate genes at 6p21.33 and 20q11.21 are potentially biologically relevant to lung carcinogenesis., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

PARK2, a gene associated with Parkinson disease, is a tumor suppressor in human malignancies. Here, we show that c.823C>T (p.Arg275Trp), a germline mutation in PARK2, is present in a family with eight cases of lung cancer. The resulting amino acid change, p.Arg275Trp, is located in the highly conserved RING finger 1 domain of PARK2, which encodes an E3 ubiquitin ligase. Upon further analysis, the c.823C>T mutation was detected in three additional families affected by lung cancer. The effect size for PARK2 c.823C>T (odds ratio = 5.24) in white individuals was larger than those reported for variants from lung cancer genome-wide association studies. These data implicate this PARK2 germline mutation as a genetic susceptibility factor for lung cancer. Our results provide a rationale for further investigations of this specific mutation and gene for evaluation of the possibility of developing targeted therapies against lung cancer in individuals with PARK2 variants by compensating for the loss-of-function effect caused by the associated variation., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

The production of pigment by melanocytes tans the skin and protects against skin cancers. UV-exposed keratinocytes secrete α-MSH, which then activates melanin formation in melanocytes by inducing the microphthalmia-associated transcription factor (MITF). We show that PPAR-γ coactivator (PGC)-1α and PGC-1β are critical components of this melanogenic system in melanocytes. α-MSH signaling strongly induces PGC-1α expression and stabilizes both PGC-1α and PGC-1β proteins. The PGC-1s in turn activate the MITF promoter, and their expression correlates strongly with that of MITF in human melanoma cell lines and biopsy specimens. Inhibition of PGC-1α and PGC-1β blocks the α-MSH-mediated induction of MITF and melanogenic genes. Conversely, overexpression of PGC-1α induces pigment formation in cell culture and transgenic animals. Finally, polymorphism studies reveal expression quantitative trait loci in the PGC-1β gene that correlate with tanning ability and protection from melanoma in humans. These data identify PGC-1 coactivators as regulators of human tanning., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Three genetic loci for lung cancer risk have been identified by genome-wide association studies (GWAS), but inherited susceptibility to specific histologic types of lung cancer is not well established. We conducted a GWAS of lung cancer and its major histologic types, genotyping 515,922 single-nucleotide polymorphisms (SNPs) in 5739 lung cancer cases and 5848 controls from one population-based case-control study and three cohort studies. Results were combined with summary data from ten additional studies, for a total of 13,300 cases and 19,666 controls of European descent. Four studies also provided histology data for replication, resulting in 3333 adenocarcinomas (AD), 2589 squamous cell carcinomas (SQ), and 1418 small cell carcinomas (SC). In analyses by histology, rs2736100 (TERT), on chromosome 5p15.33, was associated with risk of adenocarcinoma (odds ratio [OR]=1.23, 95% confidence interval [CI]=1.13-1.33, p=3.02x10(-7)), but not with other histologic types (OR=1.01, p=0.84 and OR=1.00, p=0.93 for SQ and SC, respectively). This finding was confirmed in each replication study and overall meta-analysis (OR=1.24, 95% CI=1.17-1.31, p=3.74x10(-14) for AD; OR=0.99, p=0.69 and OR=0.97, p=0.48 for SQ and SC, respectively). Other previously reported association signals on 15q25 and 6p21 were also refined, but no additional loci reached genome-wide significance. In conclusion, a lung cancer GWAS identified a distinct hereditary contribution to adenocarcinoma.

Currently, single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) of >5% are preferentially used in case-control association studies of common human diseases. Recent technological developments enable inexpensive and accurate genotyping of a large number of SNPs in thousands of cases and controls, which can provide adequate statistical power to analyze SNPs with MAF <5%. Our purpose was to determine whether evaluating rare SNPs in case-control association studies could help identify causal SNPs for common diseases. We suggest that slightly deleterious SNPs (sdSNPs) subjected to weak purifying selection are major players in genetic control of susceptibility to common diseases. We compared the distribution of MAFs of synonymous SNPs with that of nonsynonymous SNPs (1) predicted to be benign, (2) predicted to be possibly damaging, and (3) predicted to be probably damaging by PolyPhen. Our sources of data were the International HapMap Project, ENCODE, and the SeattleSNPs project. We found that the MAF distribution of possibly and probably damaging SNPs was shifted toward rare SNPs compared with the MAF distribution of benign and synonymous SNPs that are not likely to be functional. We also found an inverse relationship between MAF and the proportion of nsSNPs predicted to be protein disturbing. On the basis of this relationship, we estimated the joint probability that a SNP is functional and would be detected as significant in a case-control study. Our analysis suggests that including rare SNPs in genotyping platforms will advance identification of causal SNPs in case-control association studies, particularly as sample sizes increase.

The candidate-gene approach in association studies of polygenic diseases has often yielded conflicting results. In this hospital-based case-control study with 696 white patients newly diagnosed with bladder cancer and 629 unaffected white controls, we applied a multigenic approach to examine the associations with bladder cancer risk of a comprehensive panel of 44 selected polymorphisms in two pathways, DNA repair and cell-cycle control, and to evaluate higher-order gene-gene interactions, using classification and regression tree (CART) analysis. Individually, only XPD Asp312Asn, RAG1 Lys820Arg, and a p53 intronic SNP exhibited statistically significant main effects. However, we found a significant gene-dosage effect for increasing numbers of potential high-risk alleles in DNA-repair and cell-cycle pathways separately and combined. For the nucleotide-excision repair pathway, compared with the referent group (fewer than four adverse alleles), individuals with four (odds ratio [OR] = 1.52, 95% CI 1.05-2.20), five to six (OR = 1.81, 95% CI 1.31-2.50), and seven or more adverse alleles (OR = 2.50, 95% CI 1.69-3.70) had increasingly elevated risks of bladder cancer (P for trend <.001). Each additional adverse allele was associated with a 1.21-fold increase in risk (95% CI 1.12-1.29). For the combined analysis of DNA-repair and cell-cycle SNPs, compared with the referent group (<13 adverse alleles), the ORs for individuals with 13-15, 16-17, and >or=18 adverse alleles were 1.22 (95% CI 0.84-1.76), 1.57 (95% CI 1.05-2.35), and 1.77 (95% CI 1.19-2.63), respectively (P for trend = .002). Each additional high-risk allele was associated with a 1.07-fold significant increase in risk. In addition, we found that smoking had a significant multiplicative interaction with SNPs in the combined DNA-repair and cell-cycle-control pathways (P<.01). All genetic effects were evident only in "ever smokers" (persons who had smoked >or=100 cigarettes) and not in "never smokers." A cross-validation statistical method developed in this study confirmed the above observations. CART analysis revealed potential higher-order gene-gene and gene-smoking interactions and categorized a few higher-risk subgroups for bladder cancer. Moreover, subgroups identified with higher cancer risk also exhibited higher levels of induced genetic damage than did subgroups with lower risk. There was a significant trend of higher numbers of bleomycin- and benzo[a]pyrene diol-epoxide (BPDE)-induced chromatid breaks (by mutagen-sensitivity assay) and DNA damage (by comet assay) for individuals in higher-risk subgroups among cases of bladder cancer in smokers. The P for the trend was .0348 for bleomycin-induced chromosome breaks, .0036 for BPDE-induced chromosome breaks, and .0397 for BPDE-induced DNA damage, indicating that these higher-order gene-gene and gene-smoking interactions included SNPs that modulated repair and resulted in diminished DNA-repair capacity. Thus, genotype/phenotype analyses support findings from CART analyses. This is the first comprehensive study to use a multigenic analysis for bladder cancer, and the data suggest that individuals with a higher number of genetic variations in DNA-repair and cell-cycle-control genes are at an increased risk for bladder cancer, confirming the importance of taking a multigenic pathway-based approach to risk assessment.

The minor allele of the R620W missense single-nucleotide polymorphism (SNP) (rs2476601) in the hematopoietic-specific protein tyrosine phosphatase gene, PTPN22, has been associated with multiple autoimmune diseases, including rheumatoid arthritis (RA). These genetic data, combined with biochemical evidence that this SNP affects PTPN22 function, suggest that this phosphatase is a key regulator of autoimmunity. To determine whether other genetic variants in PTPN22 contribute to the development of RA, we sequenced the coding regions of this gene in 48 white North American patients with RA and identified 15 previously unreported SNPs, including 2 coding SNPs in the catalytic domain. We then genotyped 37 SNPs in or near PTPN22 in 475 patients with RA and 475 individually matched controls (sample set 1) and selected a subset of markers for replication in an additional 661 patients with RA and 1,322 individually matched controls (sample set 2). Analyses of these results predict 10 common (frequency >1%) PTPN22 haplotypes in white North Americans. The sole haplotype found to carry the previously identified W620 risk allele was strongly associated with disease in both sample sets, whereas another haplotype, identical at all other SNPs but carrying the R620 allele, showed no association. R620W, however, does not fully explain the association between PTPN22 and RA, since significant differences between cases and controls persisted in both sample sets after the haplotype data were stratified by R620W. Additional analyses identified two SNPs on a single common haplotype that are associated with RA independent of R620W, suggesting that R620W and at least one additional variant in the PTPN22 gene region influence RA susceptibility.

To detect potentially imprinted, obesity-related genetic loci, we performed genomewide parent-of-origin linkage analyses under an allele-sharing model for discrete traits and under a family regression model for obesity-related quantitative traits, using a European American sample of 1,297 individuals from 260 families, with 391 microsatellite markers. We also used two smaller, independent samples for replication (a sample of 370 German individuals from 89 families and a sample of 277 African American individuals from 52 families). For discrete-trait analysis, we found evidence for a maternal effect in chromosome region 10p12 across the three samples, with LOD scores of 5.69 (single-point) and 4.52 (multipoint) for the pooled sample. For quantitative-trait analysis, we found the strongest evidence for a maternal effect (single-point LOD of 2.85; multipoint LOD of 4.01 for body mass index [BMI] and 3.69 for waist circumference) in region 12q24 and for a paternal effect (single-point LOD of 4.79; multipoint LOD of 3.72 for BMI) in region 13q32, in the European American sample. The results suggest that parent-of-origin effects, perhaps including genomic imprinting, may play a role in human obesity.

Most multipoint linkage programs assume linkage equilibrium among the markers being studied. The assumption is appropriate for the study of sparsely spaced markers with intermarker distances exceeding a few centimorgans, because linkage equilibrium is expected over these intervals for almost all populations. However, with recent advancements in high-throughput genotyping technology, much denser markers are available, and linkage disequilibrium (LD) may exist among the markers. Applying linkage analyses that assume linkage equilibrium to dense markers may lead to bias. Here, we demonstrated that, when some or all of the parental genotypes are missing, assuming linkage equilibrium among tightly linked markers where strong LD exists can cause apparent oversharing of multipoint identity by descent (IBD) between sib pairs and false-positive evidence for multipoint model-free linkage analysis of affected sib pair data. LD can also mimic linkage between a disease locus and multiple tightly linked markers, thus causing false-positive evidence of linkage using parametric models, particularly when heterogeneity LOD score approaches are applied. Bias can be eliminated by inclusion of parental genotype data and can be reduced when additional unaffected siblings are included in the analysis.

Lung cancer is a major cause of death in the United States and other countries. The risk of lung cancer is greatly increased by cigarette smoking and by certain occupational exposures, but familial factors also clearly play a major role. To identify susceptibility genes for familial lung cancer, we conducted a genomewide linkage analysis of 52 extended pedigrees ascertained through probands with lung cancer who had several first-degree relatives with the same disease. Multipoint linkage analysis, under a simple autosomal dominant model, of all 52 families with three or more individuals affected by lung, throat, or laryngeal cancer, yielded a maximum heterogeneity LOD score (HLOD) of 2.79 at 155 cM on chromosome 6q (marker D6S2436). A subset of 38 pedigrees with four or more affected individuals yielded a multipoint HLOD of 3.47 at 155 cM. Analysis of a further subset of 23 multigenerational pedigrees with five or more affected individuals yielded a multipoint HLOD score of 4.26 at the same position. The 14 families with only three affected relatives yielded negative LOD scores in this region. A predivided samples test for heterogeneity comparing the LOD scores from the 23 multigenerational families with those from the remaining families was significant (P=.007). The 1-HLOD multipoint support interval from the multigenerational families extends from C6S1848 at 146 cM to 164 cM near D6S1035, overlapping a genomic region that is deleted in sporadic lung cancers as well as numerous other cancer types. Parametric linkage and variance-components analysis that incorporated effects of age and personal smoking also supported linkage in this region, but with somewhat diminished support. These results localize a major susceptibility locus influencing lung cancer risk to 6q23-25.

Rheumatoid arthritis (RA) is the most common systemic autoimmune disease, affecting approximately 1% of the adult population worldwide, with an estimated heritability of 60%. To identify genes involved in RA susceptibility, we investigated the association between putative functional single-nucleotide polymorphisms (SNPs) and RA among white individuals by use of a case-control study design; a second sample was tested for replication. Here we report the association of RA susceptibility with the minor allele of a missense SNP in PTPN22 (discovery-study allelic P=6.6 x 10(-4); replication-study allelic P=5.6 x 10(-8)), which encodes a hematopoietic-specific protein tyrosine phosphatase also known as "Lyp." We show that the risk allele, which is present in approximately 17% of white individuals from the general population and in approximately 28% of white individuals with RA, disrupts the P1 proline-rich motif that is important for interaction with Csk, potentially altering these proteins' normal function as negative regulators of T-cell activation. The minor allele of this SNP recently was implicated in type 1 diabetes, suggesting that the variant phosphatase may increase overall reactivity of the immune system and may heighten an individual carrier's risk for autoimmune disease.

There is a critical need to understand why missense mutations are deleterious. The deleterious effects of missense mutations are commonly attributed to their impact on primary amino acid sequence and protein structure. However, several recent studies have shown that some missense mutations are deleterious because they disturb cis-acting splicing elements-so-called "exonic splicing enhancers" (ESEs). It is not clear whether the ESE-related deleterious effects of missense mutations are common. We have evaluated colocalization of pathogenic missense mutations (found in affected individuals) with high-score ESE motifs in the human mismatch-repair genes hMSH2 and hMLH1. We found that pathogenic missense mutations in the hMSH2 and hMLH1 genes are located in ESE sites significantly more frequently than expected. Pathogenic missense mutations also tended to decrease ESE scores, thus leading to a higher propensity for splicing defects. In contrast, nonpathogenic missense mutations (polymorphisms found in unaffected individuals) and nonsense mutations are distributed randomly in relation to ESE sites. Comparison of the observed and expected frequencies of missense mutations in ESE sites shows that pathogenic effects of >/=20% of mutations in hMSH2 result from disruption of ESE sites and disturbed splicing. Similarly, pathogenic effects of >/=16% of missense mutations in the hMLH1 gene are ESE related. The colocalization of pathogenic missense mutations with ESE sites strongly suggests that their pathogenic effects are splicing related.

Genomic imprinting is a mechanism in which only one of the two copies of a gene is expressed. Some genes that affect development and behavior in mammals are known to be imprinted. Deregulation of imprinted genes has been found in a number of human diseases. Incorporating imprinting information into linkage analysis results in a more powerful test for linkage. Here, we propose an efficient method to test for linkage and imprinting of quantitative traits in extended pedigrees. We compared the results obtained by using the extended-pedigree-analysis approach proposed in this study with other existing approaches. We found that the proposed method is more powerful and uses extended-pedigree information most efficiently.

To characterize cancer risk in heterozygous p53 mutation carriers, we analyzed cancer incidence in 56 germline p53 mutation carriers and 3,201 noncarriers from 107 kindreds ascertained through patients with childhood soft-tissue sarcoma who were treated at the University of Texas M. D. Anderson Cancer Center. We systematically followed members in these kindreds for cancer incidence for >20 years and evaluated their p53 gene status. We found seven kindreds with germline p53 mutations that include both missense and truncation mutation types. Kaplan-Meier analysis showed similar cancer risks between 21 missense and 35 truncation p53 mutation carriers (log-rank chi(2)=0.04; P=.84). We found a significantly higher cancer risk in female carriers than in male carriers (log-rank chi(2)=12.1; P<.001), a difference not explained by an excess of sex-specific cancer. The calculated standardized incidence ratio (SIR) showed that mutation carriers had a risk for all types of cancer that was much higher than that for the general population (SIR = 41.1; 95% confidence interval [CI] 29.9-55.0) whereas noncarriers had a risk for all types of cancer that was similar to that in the general population (SIR = 0.9; 95% CI 0.8-1.0). The calculated SIRs showed a >100-fold higher risk of sarcoma, female breast cancer, and hematologic malignancies for the p53 mutation carriers and agreed with the findings of an earlier segregation analysis based on the same cohort. These results quantitatively illustrated the spectrum of cancer risk in germline p53 mutation carriers and will provide valuable reference for the evaluation and treatment of patients with cancer.

Rheumatoid arthritis (RA) is an inflammatory disease with a complex genetic component. An association between RA and the human leukocyte antigen (HLA) complex has long been observed in many different populations, and most studies have focused on a direct role for the HLA-DRB1 "shared epitope" in disease susceptibility. We have performed an extensive haplotype analysis, using 54 markers distributed across the entire HLA complex, in a set of 469 multicase families with RA. The results show that, in addition to associations with the DRB1 alleles, at least two additional genetic effects are present within the major histocompatibility complex. One of these lies within a 497-kb region in the central portion of the HLA complex, an interval that excludes DRB1. This genetic risk factor is present on a segment of a highly conserved ancestral A1-B8-DRB1*03 (8.1) haplotype. Additional risk genes may also be present in the HLA class I region in a subset of DRB1*0404 haplotypes. These data emphasize the importance of defining haplotypes when trying to understand the HLA associations with disease, and they clearly demonstrate that such associations with RA are complex and cannot be completely explained by the DRB1 locus.

Juvenile polyposis (JP) is an autosomal dominant syndrome in which affected patients develop upper- and/or lower-gastrointestinal (GI) polyps. A subset of families with JP have germline mutations in the SMAD4 (MADH4) gene and are at increased risk of GI cancers. To date, six families with JP have been described as having the same SMAD4 deletion (1244-1247delAGAC). The objective of the present study is to determine whether this deletion is a common ancestral mutation or a mutational hotspot. DNA from members of four families with JP, from Iowa, Mississippi, Texas, and Finland, that had this 4-bp deletion was used to genotype 15 simple tandem repeat polymorphism (STRP) markers flanking the SMAD4 gene, including 2 new STRPs within 6.3 and 70.9 kb of the deletion. Haplotypes cosegregating with JP in each family were constructed, and the distances of the closest markers were determined from the draft sequence of the human genome. No common haplotype was observed in these four families with JP. A 14-bp region containing the deletion had four direct repeats and one inverted repeat. Because no common ancestor was suggested by haplotype analysis and the sequence flanking the deletion contains repeats frequently associated with microdeletions, this common SMAD4 deletion in JP most likely represents a mutational hotspot.

Some genes that affect development and behavior in mammals are known to be imprinted; and > or = 1% of all mammalian genes are imprinted. Hence, incorporating an imprinting parameter into linkage analysis may increase the power to detect linkage for these traits. Here we propose theoretical justifications for a recently developed model for testing of linkage, in the presence of genetic imprinting, between a quantitative-trait locus and a polymorphic marker; this is achieved in the variance-components framework. We also incorporate sex-specific recombination fractions into this model. We discuss the effects that imprinting and nonimprinting have on the power of the usual variance-components method and on the variance-components method that incorporates an imprinting parameter. We provide noncentrality parameters that can be used to determine the sample size necessary to attain a specified power for a given significance level, which is useful in the planning of a linkage study. Optimal strategies for a genome scan of potentially imprinted traits are discussed.

An attractive feature of variance-components methods (including the Haseman-Elston tests) for the detection of quantitative-trait loci (QTL) is that these methods provide estimates of the QTL effect. However, estimates that are obtained by commonly used methods can be biased for several reasons. Perhaps the largest source of bias is the selection process. Generally, QTL effects are reported only at locations where statistically significant results are obtained. This conditional reporting can lead to a marked upward bias. In this article, we demonstrate this bias and show that its magnitude can be large. We then present a simple method-of-moments (MOM)-based procedure to obtain more-accurate estimates, and we demonstrate its validity via Monte Carlo simulation. Finally, limitations of the MOM approach are noted, and we discuss some alternative procedures that may also reduce bias.

In this report, we present a simple and powerful way to incorporate individual-specific liability classes into linkage analysis. The proposed method is applicable to both quantitative and qualitative traits. In linkage studies, we may have information about different covariates. Incorporation of these covariates along with the estimates of residual familial effects, age-at-onset effects, and susceptibility in the definition of liability classes can increase the power to detect genetic linkage. In this study, we show how one can form individual-specific liability classes and use these classes in standard linkage-analysis programs, such as the widely used LINKAGE package, to perform more powerful genetic linkage analysis. Our simulation study shows that this approach yields higher LOD scores and more-accurate estimates of the recombination fraction in the families showing linkage. The proposed method is also applied to kindreds collected, at the M. D. Anderson Cancer Center, through probands with childhood soft-tissue sarcoma. Confirmed germ-line mutations in the p53 tumor-suppressor gene have been identified in these families. Application of our method to these families yielded significantly higher LOD scores and more-accurate recombination fractions than did analysis that did not account for individual-specific covariate information.

Rheumatoid arthritis (RA) is an autoimmune/inflammatory disorder with a complex genetic component. We report the first major genomewide screen of multiplex families with RA gathered in the United States. The North American Rheumatoid Arthritis Consortium, using well-defined clinical criteria, has collected 257 families containing 301 affected sibling pairs with RA. A genome screen for allele sharing was performed, using 379 microsatellite markers. A nonparametric analysis using SIBPAL confirmed linkage of the HLA locus to RA (P < .00005), with lambdaHLA = 1.79. However, the analysis also revealed a number of non-HLA loci on chromosomes 1 (D1S235), 4 (D4S1647), 12 (D12S373), 16 (D16S403), and 17 (D17S1301), with evidence for linkage at a significance level of P<.005. Analysis of X-linked markers using the MLOD method from ASPEX also suggests linkage to the telomeric marker DXS6807. Stratifying the families into white or seropositive subgroups revealed some additional markers that showed improvement in significance over the full data set. Several of the regions that showed evidence for nominal significance (P < .05) in our data set had previously been implicated in RA (D16S516 and D17S1301) or in other diseases of an autoimmune nature, including systemic lupus erythematosus (D1S235), inflammatory bowel disease (D4S1647, D5S1462, and D16S516), multiple sclerosis (D12S1052), and ankylosing spondylitis (D16S516). Therefore, genes in the HLA complex play a major role in RA susceptibility, but several other regions also contribute significantly to overall genetic risk.

We discuss pooling methods of mutation detection for identifying rare mutations. We provide mathematical formulae for obtaining the optimal pool size as a function of the mutation frequency in the study population and the specificity of the test. The optimal pool size depends strongly on the specificity of the test. With a test that has 99% specificity, pooling can reduce the number of tests that need to be performed by 80%, whereas, with a test with 95% specificity, pooling reduces the number of samples that must be tested by only 50%. We used the software PHRED to call mutations after sequencing of pooled samples with known STK11 mutations. We found that, when the area under the curve for the less prominent peak was used to call mutations, we were able to pool pairs of samples and correctly identify mutations. Pooling of three samples did not lead to an adequately specific test for the basic automated allele-calling procedures that we used. We discuss methods by which the specificity may be improved to permit pooling of three or more samples when testing for mutations by sequencing.

Detection of linkage to genes for quantitative traits remains a challenging task. Recently, variance components (VC) techniques have emerged as among the more powerful of available methods. As often implemented, such techniques require assumptions about the phenotypic distribution. Usually, multivariate normality is assumed. However, several factors may lead to markedly nonnormal phenotypic data, including (a) the presence of a major gene (not necessarily linked to the markers under study), (b) some types of gene x environment interaction, (c) use of a dichotomous phenotype (i.e., affected vs. unaffected), (d) nonnormality of the population within-genotype (residual) distribution, and (e) selective (extreme) sampling. Using simulation, we have investigated, for sib-pair studies, the robustness of the likelihood-ratio test for a VC quantitative-trait locus-detection procedure to violations of normality that are due to these factors. Results showed (a) that some types of nonnormality, such as leptokurtosis, produced type I error rates in excess of the nominal, or alpha, levels whereas others did not; and (b) that the degree of type I error-rate inflation appears to be directly related to the residual sibling correlation. Potential solutions to this problem are discussed. Investigators contemplating use of this VC procedure are encouraged to provide evidence that their trait data are normally distributed, to employ a procedure that allows for nonnormal data, or to consider implementation of permutation tests.

Autosomal dominant periodic fever syndromes are characterized by unexplained episodes of fever and severe localized inflammation. In seven affected families, we found six different missense mutations of the 55 kDa tumor necrosis factor receptor (TNFR1), five of which disrupt conserved extracellular disulfide bonds. Soluble plasma TNFR1 levels in patients were approximately half normal. Leukocytes bearing a C52F mutation showed increased membrane TNFR1 and reduced receptor cleavage following stimulation. We propose that the autoinflammatory phenotype results from impaired downregulation of membrane TNFR1 and diminished shedding of potentially antagonistic soluble receptor. TNFR1-associated periodic syndromes (TRAPS) establish an important class of mutations in TNF receptors. Detailed analysis of one such mutation suggests impaired cytokine receptor clearance as a novel mechanism of disease.

Linkage disequilibrium has been used to help in the identification of genes predisposing to certain qualitative diseases. Although several linkage-disequilibrium tests have been developed for localization of genes influencing quantitative traits, these tests have not been thoroughly compared with one another. In this report we compare, under a variety of conditions, several different linkage-disequilibrium tests for identification of loci affecting quantitative traits. These tests use either single individuals or parent-child trios. When we compared tests with equal samples, we found that the truncated measured allele (TMA) test was the most powerful. The trait allele frequencies, the stringency of sample ascertainment, the number of marker alleles, and the linked genetic variance affected the power, but the presence of polygenes did not. When there were more than two trait alleles at a locus in the population, power to detect disequilibrium was greatly diminished. The presence of unlinked disequilibrium (D'*) increased the false-positive error rates of disequilibrium tests involving single individuals but did not affect the error rates of tests using family trios. The increase in error rates was affected by the stringency of selection, the trait allele frequency, and the linked genetic variance but not by polygenic factors. In an equilibrium population, the TMA test is most powerful, but, when adjusted for the presence of admixture, Allison test 3 becomes the most powerful whenever D'*>.15.

Autosomal dominant periodic fevers are characterized by intermittent febrile attacks of unknown etiology and by recurrent abdominal pains. The biochemical and molecular bases of all autosomal dominant periodic fevers are unknown, and only familial Hibernian fever (FHF) has been described as a distinct clinical entity. FHF has been reported in three families-the original Irish-Scottish family and two Irish families with similar clinical features. We have undertaken a genomewide search in these families and report significant multipoint LOD scores between the disease and markers on chromosome 12p13. Cumulative multipoint linkage analyses indicate that an FHF gene is likely to be located in an 8-cM interval between D12S77 and D12S356, with a maximum LOD score (Z max) of 3.79. The two-point Z max was 3.11, for D12S77. There was no evidence of genetic heterogeneity in these three families; it is proposed that these markers should be tested in other families, of different background, that have autosomal dominant periodic fever, as a prelude to identification of the FHF-susceptibility gene.

We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

The major histocompatibility complex class III tumor necrosis factor-lymphotoxin (TNF-LT) region (6p21.3) was investigated as a possible susceptibility locus for rheumatoid arthritis (RA). Inheritance of five TNF microsatellite markers was determined in 50 multiplex families. Overall, 47 different haplotypes were observed. One of these, the TNF a6, b5, c1, d3, e3 (H1) haplotype, was present in 35.3% of affected, but in only 20.5% of unaffected, individuals (P < .005). This haplotype accounted for 21.5% of the parental haplotypes transmitted to affected offspring and only 7.3% not transmitted to affected offspring (P = .0003). The TNF a6 and TNF c1 alleles were individually associated with RA (P = .0005 and .0008, respectively), as were the HLA-DRB1 "shared epitope" (SE) (P = .0001) and HLA-DRB1*0401 (P = .0018). Both univariate and bivariate conditional logistic regression analysis showed significant effects of TNF c1 and SE in increasing risk to RA (P < .001). Stratification by the presence of SE indicated an independent effect of the TNFc1 allele (P = .0003) and the HLA A1, B8, DR3 extended haplotype (always TNFa2, b3, c1, d1, e3) (P = .0027) in SE heterozygotes, while the H1 haplotype was associated with RA in SE homozygotes (P = .0018). The TNF-LT region appears to influence susceptibility to RA, distinct from HLA-DR.

To assess evidence for genetic linkage from pedigrees, I developed a limited variance-components approach. In this method, variability among trait observations from individuals within pedigrees is expressed in terms of fixed effects from covariates and effects due to an unobservable trait-affecting major locus, random polygenic effects, and residual nongenetic variance. The effect attributable to a locus linked to a marker is a function of the additive and dominance components of variance of the locus, the recombination fraction, and the proportion of genes identical by descent at the marker locus for each pair of sibs. For unlinked loci, the polygenic variance component depends only on the relationship between the relative pair. Parameters can be estimated by either maximum-likelihood methods or quasi-likelihood methods. The forms of quasi-likelihood estimators are provided. Hypothesis tests derived from the maximum-likelihood approach are constructed by appeal to asymptotic theory. A simulation study showed that the size of likelihood-ratio tests was appropriate but that the monogenic component of variance was generally underestimated by the likelihood approach.

Methods for detecting genetic linkage are more powerful when they fully use all of the data collected from pedigrees. We first discuss a method for obtaining the probability that a pedigree member has a given genotype, conditional on the phenotypes of his relatives. We then develop a rapid method to obtain the conditional probabilities of identity-by-descent sharing of marker alleles for all related pairs of individuals from extended pedigrees. The method assumes that the individuals are noninbred and that the relationship between genotype and phenotype is known for the marker locus studied. The probabilities of identity-by-descent sharing among relative pairs, conditional on marker phenotype information, can then be used in any of the model free tests for linkage between a trait locus and a marker locus.

The robust or model-free method for detecting linkage developed by Haseman and Elston for data from sib pairs is extended to incorporate observations of multiple traits on each individual. A method is proposed that estimates the linear function that results in the strongest correlation between the squared pair differences in the trait measurements and identity by descent at a marker locus. The method is illustrated by the study of apolipoprotein and cholesterol levels in individuals from a large family that had many members diagnosed with coronary heart disease.