Pedigree Disequilibrium Test Research Articles

Morphological and biochemical features of obesity are associated with mineralization genes’ polymorphisms

Ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) was recently extensively studied as a candidate gene for obesity phenotypes. As the human homologue of the mouse progressive ankylosis (ANKH) and alkaline phosphatase (ALPL) are known functional partners of ENPP1 in bone mineralization, we hypothesized that these genes may also be jointly involved in determining obesity features. To examine the effects of the three genes, possible gene-sex and gene-gene interactions on variability of four obesity phenotypes: the body mass index (BMI), the waist-hip ratio (WHR), the epidermal growth factor receptor (EGFR), and leptin. In all, 962 healthy individuals from 230 families were genotyped for 45 single nucleotide polymorphisms (SNPs). The association analysis was performed using two family based association tests (family based association test and pedigree disequilibrium test). The combined P-values of the two tests were estimated by Monte-Carlo simulations. Relative magnitude of the genetic and familial effects, gene-sex and gene-gene interactions were assessed using variance component models. Associations were observed between ENPP1 polymorphisms and BMI (P=0.0037) and leptin (P=0.0068). ALPL markers were associated with WHR (P=0.0026) and EGFR (P=0.0001). The ANKH gene was associated with all four studied obesity-related traits (P<0.0184), and its effects were modulated by sex. Gene-gene interactions were not detected. The observed pattern of association signals indicates that ANKH may have a generalized effect on adipose tissue physiology, whereas ENPP1 and ALPL affect distinct obesity features. The joint analysis of related genes and integration of the results obtained by different methods used in this research should benefit other studies of similar design.

Association and expression study of synapsin III and schizophrenia

The synapsin III gene, SYN3, which belongs to the family of synaptic vesicle-associated proteins, has been implicated in the modulation of neurotransmitter release and in synaptogenesis, suggesting a potential role in several neuropsychiatric diseases. The human SYN3 gene is located on chromosome 22q12-13, a candidate region implicated in previous linkage studies of schizophrenia. However, association studies of SYN3 and schizophrenia have produced inconsistent results. In this study, four SYN3 SNPs (rs133945 (−631 C > G), rs133946 (−196 G > A), rs9862 and rs1056484) were tested in three sets of totally 3759 samples that comprise 655 affected subjects and 626 controls in the Irish Case-Control Study of Schizophrenia (ICCSS), 1350 samples incorporating 273 pedigrees in the Irish Study of High Density Schizophrenia Families (ISHDSF), and 564 unrelated schizophrenia patients and 564 healthy individuals in a Chinese case-control sample. The expression levels of SYN3 in schizophrenic patients and unaffected controls were compared using postmortem brain cDNAs provided by the Stanley Medical Research Institute (SMRI). There was no significant association in either the Irish or Chinese case-control samples, nor in the combined samples. Consistent with this finding, we did not find any significant difference in allele or haplotype frequencies when we used the pedigree disequilibrium test to analyze the Irish family sample. In the expression studies, no significant difference ( p = 0.507) was observed between patients and controls. Both the association studies and expression studies didn’t support a major role for SYN3 in the susceptibility of schizophrenia in Irish and Chinese populations.

A cross‐validation procedure for general pedigrees and matched odds ratio fitness metric implemented for the multifactor dimensionality reduction pedigree disequilibrium test

As genetic epidemiology looks beyond mapping single disease susceptibility loci, interest in detecting epistatic interactions between genes has grown. The dimensionality and comparisons required to search the epistatic space and the inference for a significant result pose challenges for testing epistatic disease models. The multifactor dimensionality reduction-pedigree disequilibrium test (MDR-PDT) was developed to test for multilocus models in pedigree data. In the present study we rigorously tested MDR-PDT with new cross-validation (CV) (both 5- and 10-fold) and omnibus model selection algorithms by simulating a range of heritabilities, odds ratios, minor allele frequencies, sample sizes, and numbers of interacting loci. Power was evaluated using 100, 500, and 1,000 families, with minor allele frequencies 0.2 and 0.4 and broad-sense heritabilities of 0.005, 0.01, 0.03, 0.05, and 0.1 for 2- and 3-locus purely epistatic penetrance models. We also compared the prediction error (PE) measure of effect with a predicted matched odds ratio (MOR) for final model selection and testing. We report that the CV procedure is valid with the permutation test, MDR-PDT performs similarly with 5- and 10-fold CV, and that the MOR is more powerful than PE as the fitness metric for MDR-PDT.

Polymorphisms in the neural nicotinic acetylcholine receptor α4 subunit (CHRNA4) are associated with ADHD in a genetic isolate

The neural nicotinic acetylcholine receptor α4 subunit (CHRNA4), at 20q13.2-q13.3, is an important candidate gene for conferring susceptibility to attention deficit/hyperactivity disorder (ADHD). Several studies have already looked for association/linkage between ADHD and CHRNA4 in different populations. We used the Pedigree Disequilibrium Test to search for evidence of association between ADHD and six SNP marker loci in families from the isolated Paisa population. We found that the T allele of SNP rs6090384 exhibits a deficit of transmission in unaffected individuals (OR = 5.43, IC 1.54-19.13) (global P value = 0.014). We also found significant association and linkage to extended haplotypes rs2273502-rs6090384 (combination of variants C-T, respectively) (P = 0.02) and rs6090384-rs6090387 (P = 0.04) (combination of variants T-G, respectively). SNP rs6090384, variant T, has also been reported to be associated with inattention in a previous study. This makes ours the ninth study to examine the association of CHRNA4 with ADHD and the seventh one to find evidence for association in a population with a different ethnicity.

COL1A1andCOL2A1Genes and Myopia Susceptibility: Evidence of Association and Suggestive Linkage to theCOL2A1Locus

Collagen involvement in myopia development via scleral remodeling is well-known. Recently, COL1A1 and COL2A1 gene polymorphisms were reported to be associated with high-grade and common myopia, respectively. This study was conducted to investigate whether these collagen genes are associated and/or genetically linked with myopia in large Caucasian family datasets. High-grade myopia was defined as <or=-5.00 D. Two independent datasets comprising 146 (Duke) and 130 (Cardiff) families with high-grade myopia participated in the association study. Allelic discrimination assays were performed on tagging SNPs for COL1A1 and COL2A1. The pedigree disequilibrium test (PDT) and the association test in the presence of linkage (APL) were used for association analyses. Linkage analyses for COL2A1 locus markers were performed with the Fastlink and Merlin programs in conjunction with data obtained from our collaborative whole-genome linkage study (254 families). Significant association was identified between five SNPs (rs1034762, rs1635529, rs1793933, rs3803183, and rs17122571) of the COL2A1 locus and high-grade myopia (P < 0.045, minimum (min) P = 0.008) and with myopia status set at <or=-0.50 or -0.75 D (min P = 0.004) in the Duke dataset. The SNP rs1635529 also showed significant association in the Cardiff dataset (<or=-5.00 D, min P = 0.004; <or=-0.50 D, min P = 0.007). Linkage analyses showed suggestive linkage to the COL2A1 locus on 12q. No association was found between COL1A1 SNPs and any degree of myopia. The COL2A1 gene was associated with high-grade myopia in two independent Caucasian family datasets. COL1A1 gene polymorphisms were not associated with myopia in our dataset, indicating possible heterogeneity across different ethnicities.

Analysis of maternal–offspring HLA compatibility, parent‐of‐origin and non‐inherited maternal effects for the classical HLA loci in type 1 diabetes

Type 1 diabetes (T1D) is a complex trait for which variation in the classical human leucocyte antigen (HLA) loci within the Major Histocompatibility Complex (MHC) significantly influences disease risk. To date, HLA class II DR-DQ genes confer the strongest known genetic effect in T1D. HLA loci may also influence T1D through additional inherited or non-inherited effects. Evidence for the role of increased maternal-offspring HLA compatibility, and both parent-of-origin (POO) and non-inherited maternal HLA (NIMA) effects in autoimmune disease has been previously established. The current study tested hypotheses that classical HLA loci influence T1D through these mechanisms, in addition to genetic transmission of particular risk alleles. The Type 1 Diabetes Genetics Consortium (T1DGC) cohort was of European descent and consisted of 2271 affected sib-pair families (total n = 11 023 individuals). Class I genes HLA-A, Cw and B, and class II genes HLA-DRB1, DQA1, DQB1, DPA1 and DPB1 were studied. The pedigree disequilibrium test was used to examine transmission of HLA alleles to individuals with T1D. Conditional logistic regression was used to model compatibility relationships between mother-offspring and father-offspring for all HLA loci. POO and NIMA effects were investigated by comparing frequencies of maternal and paternal transmitted and non-transmitted HLA alleles for each locus. Analyses were also stratified by gender of T1D-affected offspring. Strong associations were observed for all classical HLA loci except for DPA1, as expected. Compatibility differences between mother-offspring and father-offspring were not observed for any HLA loci. Furthermore, POO and NIMA HLA effects influencing T1D were not present. Maternal-offspring HLA compatibility, POO and NIMA effects for eight classical HLA loci were investigated. Results suggest that these HLA-related effects are unlikely to play a major role in the development of T1D.

Polymorphisms near SOCS3 are associated with obesity and glucose homeostasis traits in Hispanic Americans from the Insulin Resistance Atherosclerosis Family Study

The SOCS3 gene product participates in the feedback inhibition of a range of cytokine signals. Most notably, SOCS3 inhibits the functioning of leptin and downstream steps in insulin signaling after being expressed by terminal transcription factors, such as STAT3 and c-fos. The SOCS3 gene is located in the chromosome region 17q24-17q25, previously linked to body mass index (BMI), visceral adipose tissue (VAT), and waist circumference (WAIST) in Hispanic families in the Insulin Resistance Atherosclerosis Family Study (IRASFS). A high density map of 1,536 single nucleotide polymorphisms (SNPs) was constructed to cover a portion of the 17q linkage interval in 1,425 Hispanic subjects from 90 extended families in IRASFS. Analysis of this dense SNP map data revealed evidence of association of rs9914220 (located 10 kb 5' of the SOCS3 gene) with BMI, VAT, and WAIST (P-value ranging from 0.003 to 0.017). Using a tagging SNP approach, rs9914220 and 22 additional SOCS3 SNPs were genotyped for genetic association analysis with measures of adiposity and glucose homeostasis. The adiposity phenotypes utilized in association analyses included BMI, WAIST, waist to hip ratio (WHR), subcutaneous adipose tissue, VAT, and visceral to subcutaneous ratio (VSR). Linkage disequilibrium calculations revealed three haplotype blocks near SOCS3. Haplotype Block 3 (5' of SOCS3) contained SNPs consistently associated with BMI, WAIST, WHR, and VAT (P-values ranging from 2.00 x 10(-4) to 0.036). Haplotype Block 1 contained single-SNPs that were associated with most adiposity traits except for VSR (P-values ranging from 0.002 to 0.047). When trait associated SNPs were included in linkage analyses as covariates, a reduction of VAT LOD score from 1.26 to 0.76 above the SOCS3 locus (110 cM) was observed. Multi-SNP haplotype testing using the quantitative pedigree disequilibrium test was broadly consistent with the single-SNP associations. In conclusion, these results support a role for SOCS3 genetic variants in human obesity.

AMBIENCE: A Novel Approach and Efficient Algorithm for Identifying Informative Genetic and Environmental Associations With Complex Phenotypes

We developed a computationally efficient algorithm AMBIENCE, for identifying the informative variables involved in gene-gene (GGI) and gene-environment interactions (GEI) that are associated with disease phenotypes. The AMBIENCE algorithm uses a novel information theoretic metric called phenotype-associated information (PAI) to search for combinations of genetic variants and environmental variables associated with the disease phenotype. The PAI-based AMBIENCE algorithm effectively and efficiently detected GEI in simulated data sets of varying size and complexity, including the 10K simulated rheumatoid arthritis data set from Genetic Analysis Workshop 15. The method was also successfully used to detect GGI in a Crohn's disease data set. The performance of the AMBIENCE algorithm was compared to the multifactor dimensionality reduction (MDR), generalized MDR (GMDR), and pedigree disequilibrium test (PDT) methods. Furthermore, we assessed the computational speed of AMBIENCE for detecting GGI and GEI for data sets varying in size from 100 to 10(5) variables. Our results demonstrate that the AMBIENCE information theoretic algorithm is useful for analyzing a diverse range of epidemiologic data sets containing evidence for GGI and GEI.

Interaction between interleukin 3 and dystrobrevin-binding protein 1 in schizophrenia

Schizophrenia is a common psychotic mental disorder that is believed to result from the effects of multiple genetic and environmental factors. In this study, we explored gene–gene interactions and main effects in both case–control (657 cases and 411 controls) and family-based (273 families, 1350 subjects) datasets of English or Irish ancestry. Fifty three markers in 8 genes were genotyped in the family sample and 44 markers in 7 genes were genotyped in the case–control sample. The Multifactor Dimensionality Reduction Pedigree Disequilibrium Test (MDR-PDT) was used to examine epistasis in the family dataset and a 3-locus model was identified (permuted p = 0.003). The 3-locus model involved the IL3 (rs2069803), RGS4 (rs2661319), and DTNBP1 (rs2619539) genes. We used MDR to analyze the case–control dataset containing the same markers typed in the RGS4, IL3 and DTNBP1 genes and found evidence of a joint effect between IL3 (rs31400) and DTNBP1 (rs760761) (cross-validation consistency 4/5, balanced prediction accuracy = 56.84%, p = 0.019). While this is not a direct replication, the results obtained from both the family and case–control samples collectively suggest that IL3 and DTNBP1 are likely to interact and jointly contribute to increase risk for schizophrenia. We also observed a significant main effect in DTNBP1, which survived correction for multiple comparisons, and numerous nominally significant effects in several genes.

Nitric oxide synthase genes and their interactions with environmental factors in Parkinson’s disease

Nitric oxide synthase (NOS) genes (NOS1, NOS2A, and NOS3) may create excess nitric oxide that contributes to neurodegeneration in Parkinson's disease (PD). NOS genes might also interact with one another or with environmental factors in PD. Coding and tagging single nucleotide polymorphisms (SNPs) (27 NOS1, 18 NOS2A, and five NOS3 SNPs) were genotyped in families with PD (1,065 cases and 1,180 relative and other controls) and were tested for allelic associations with PD using the association in the presence of linkage test and the pedigree disequilibrium test (PDT), allelic associations with age-at-onset (AAO) using the quantitative transmission disequilibrium test, and interactions using the multifactor dimensionality reduction-PDT. Gene-environment interactions involving cigarette smoking, caffeine, nonsteroidal anti-inflammatory drugs, and pesticides were examined using generalized estimating equations in participants with environmental data available. Significant associations with PD were detected for the NOS1 SNPs rs3782218, rs11068447, rs7295972, rs2293052, rs12829185, rs1047735, rs3741475, and rs2682826 (range of p = 0.00083-0.046) and the NOS2A SNPs rs2072324, rs944725, rs12944039, rs2248814, rs2297516, rs1060826, and rs2255929 (range of p = 0.0000040-0.047) in earlier-onset families with sporadic PD, and some SNPs were also associated with earlier AAO. There was no compelling statistical evidence for gene-gene interactions. However, of the significantly associated SNPs, interactions were found between pesticides and the NOS1 SNPs rs12829185, rs1047735, and rs2682826 (range of p = 0.012-0.034) and between smoking and the NOS2A SNPs rs2248814 (p = 0.021) and rs1060826 (p = 0.013). These data implicate NOS1 and NOS2A as genetic risk factors for PD and demonstrate that their interactions with established environmental factors may modulate the environmental effects.

Association of polymorphisms in cyclooxygenase (COX)-2 with coronary and carotid calcium in the Diabetes Heart Study

Background Cardiovascular disease is the leading cause of death among Americans. Inflammation is a hallmark of the development of atherosclerosis and is mediated by prostaglandins, catalyzed by cyclooxygenase (COX)-2. We sought to determine if variants in the COX-2 gene were associated with subclinical measures of cardiovascular disease in a primarily type 2 diabetic population. Methods Eight polymorphisms in COX-2 were genotyped and vascular calcified plaque measured in the coronary, carotid, and aortic arterial beds in 977 Caucasian siblings (83% with T2DM) from 369 Diabetes Heart Study families. Tests for single nucleotide polymorphism (SNP) and haplotypic association were performed using SOLAR and quantitative pedigree disequilibrium test (QPDT), respectively (results adjusted for age, gender, diabetes affection status, smoking, and use of lipid altering medications). Results All eight SNPs genotyped were found to be in strong pair-wise linkage disequilibrium ( D′ = 1.0). Three SNPs (rs689466, rs2066826 and rs20417) are associated with either coronary or carotid calcified plaque. Subjects carrying the G allele of rs689466 ( n = 31) or the A allele of rs2066826 ( n = 16) had significantly lower coronary calcified plaque ( P = 0.02 and 0.04, respectively). Subjects homozygous for the C allele of rs20417 ( n = 22) or the A allele of rs2066826 ( n = 16) had increased carotid calcified plaque ( P = 0.011, P = 0.014). In addition, multiple two-SNP and three-SNP haplotypes were associated with CorCP with P-values ranging from P = 0.002 to P = 0.035. Conclusions Polymorphisms in COX-2 were associated with significant changes in coronary and carotid calcified plaque. Diabetic individuals with these variants may be at higher risk for developing cardiovascular disease.

A human type 1 diabetes susceptibility locus maps to chromosome 21q22.3.

OBJECTIVE— The Type 1 Diabetes Genetics Consortium (T1DGC) has assembled and genotyped a large collection of multiplex families for the purpose of mapping genomic regions linked to type 1 diabetes. In the current study, we tested for evidence of loci associated with type 1 diabetes utilizing genome-wide linkage scan data and family-based association methods.RESEARCH DESIGN AND METHODS— A total of 2,496 multiplex families with type 1 diabetes were genotyped with a panel of 6,090 single nucleotide polymorphisms (SNPs). Evidence of association to disease was evaluated by the pedigree disequilibrium test. Significant results were followed up by genotyping and analyses in two independent sets of samples: 2,214 parent-affected child trio families and a panel of 7,721 case and 9,679 control subjects.RESULTS— Three of the SNPs most strongly associated with type 1 diabetes localized to previously identified type 1 diabetes risk loci: INS, IFIH1, and KIAA0350. A fourth strongly associated SNP, rs876498 (P = 1.0 × 10−4), occurred in the sixth intron of the UBASH3A locus at chromosome 21q22.3. Support for this disease association was obtained in two additional independent sample sets: families with type 1 diabetes (odds ratio [OR] 1.06 [95% CI 1.00–1.11]; P = 0.023) and case and control subjects (1.14 [1.09–1.19]; P = 7.5 × 10−8).CONCLUSIONS— The T1DGC 6K SNP scan and follow-up studies reported here confirm previously reported type 1 diabetes associations at INS, IFIH1, and KIAA0350 and identify an additional disease association on chromosome 21q22.3 in the UBASH3A locus (OR 1.10 [95% CI 1.07–1.13]; P = 4.4 × 10−12). This gene and its flanking regions are now validated targets for further resequencing, genotyping, and functional studies in type 1 diabetes.

Detection of Catalase as a major protein target of the lipid peroxidation product 4-HNE and the lack of its genetic association as a risk factor in SLE

BackgroundSystemic lupus erythematosus (SLE) is a multifactorial disorder characterized by the presence of autoantibodies. We and others have implicated free radical mediated peroxidative damage in the pathogenesis of SLE. Since harmful free radical products are formed during this oxidative process, including 4-hydroxy 2-nonenol (4-HNE) and malondialdehyde (MDA), we hypothesized that specific HNE-protein adducts would be present in SLE red blood cell (RBC) membranes. Catalase is located on chromosome 11p13 where linkage analysis has revealed a marker in the same region of the genome among families with thrombocytopenia, a clinical manifestation associated with severe lupus in SLE affected pedigrees. Moreover, SLE afflicts African-Americans three times more frequently than their European-American counterparts. Hence we investigated the effects of a genetic polymorphism of catalase on risk and severity of SLE in 48 pedigrees with African American ancestry.MethodsTryptic digestion followed by matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) analysis was used to identify the protein modified by HNE, following Coomassie staining to visualize the bands on the acrylamide gels. Genotyping analysis for the C → T, -262 bp polymorphism in the promoter region of catalase was performed by PCR-RFLP and direct PCR-sequencing. We used a "pedigree disequilibrium test" for the family based association analysis, implemented in the PDT program to analyze the genotyping results.ResultsWe found two proteins to be HNE-modified, migrating around 80 and 50 kD respectively. Tryptic digestion followed by matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) analysis of the Coomassie stained 80 kD band revealed that the target of HNE modification was catalase, a protein shown to associate with RBC membrane proteins. All the test statistics carried out on the genotyping analysis for the C → T, -262 bp polymorphism in the promoter region of catalase were non-significant (p > 0.05) in our data, which suggested that this SNP is not associated with SLE.ConclusionOur results indicate that catalase is one of the proteins modified due to oxidative stress. However, catalase may not be a susceptibility gene for SLE. Nonetheless, catalase is oxidatively modified among SLE patients. This suggests a possible role between oxidative modification of catalase and its affects on enzymatic activity in SLE. An oxidatively modified catalase could be one of the reasons for lower enzymatic activity among SLE subjects, which in turn could favor the accumulation of deleterious hydrogen peroxide. Furthermore, HNE-products are potential neoantigens and could be involved in the pathogenesis of SLE. Decrease in catalase activity could affect the oxidant-antioxidant balance. Chronic disturbance of this balance in patients with SLE may work favorably for the premature onset of atherogenesis with severe vascular effect.

Analysis of C1q polymorphisms suggests association with systemic lupus erythematosus, serum C1q and CH50 levels and disease severity

Background:Several findings link systemic lupus erythematosus (SLE) with C1q, the first molecule of the classical complement pathway. Polymorphisms of the C1qA gene are associated with low serum C1q levels in...

Common variants near MC4R are associated with fat mass, weight and risk of obesity

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.

Variation in the miRNA-433 Binding Site of FGF20 Confers Risk for Parkinson Disease by Overexpression of α-Synuclein

Parkinson disease (PD) is a common neurodegenerative disorder caused by environmental and genetic factors. We have previously shown linkage of PD to chromosome 8p. Subsequently, fibroblast growth factor 20 (FGF20) at 8p21.3-22 was identified as a risk factor in several association studies. To identify the risk-conferring polymorphism in FGF20, we performed genetic and functional analysis of single-nucleotide polymorphisms within the gene. In a sample of 729 nuclear families with 1089 affected and 1165 unaffected individuals, the strongest evidence of association came from rs12720208 in the 3' untranslated region of FGF20. We show in several functional assays that the risk allele for rs12720208 disrupts a binding site for microRNA-433, increasing translation of FGF20 in vitro and in vivo. In a cell-based system and in PD brains, this increase in translation of FGF20 is correlated with increased alpha-synuclein expression, which has previously been shown to cause PD through both overexpression and point mutations. We suggest a novel mechanism of action for PD risk in which the modulation of the susceptibility gene's translation by common variations interfere with the regulation mechanisms of microRNA. We propose this is likely to be a common mechanism of genetic modulation of individual susceptibility to complex disease.

The Future Is Now – Will the Real Disease Gene Please Stand Up?

The transmission/disequilibrium test (TDT) [Spielman et al.: Am J Hum Genet 1993;52:506–516] has been postulated as the future of gene mapping for complex diseases, provided one is able to genotype a dense enough map of markers across the genome. Risch and Merikangas [Science 1996;273:1516–1517] suggested a million-marker screen in affected sibpair (ASP) families, demonstrating that the TDT is a more powerful test of linkage than traditional linkage tests based on allele-sharing when there is also association between marker and disease alleles. While the future of genotyping has arrived, successes in family-based association studies have been modest. This is often attributed to excessive false positives in candidate gene studies. This problem is only exacerbated by the increasing numbers of whole genome association (WGA) screens. When applied in ASPs, the TDT statistic, which assumes transmissions to siblings are independent, is not expected to have a constant variance in the presence of variable linkage. This results in generally more extreme statistics, hence will further aggravate the problem of having a large number of positive results to sort through. So an important question is how many positive TDT results will show up on a chromosome containing a disease gene due only to linkage, and will they obfuscate the true disease gene location. To answer this question we combined theory and computer simulations. These studies show that in ASPs the normal version of the TDT statistic has a mean of 0 and a variance of 1 in unlinked regions, but has a variance larger than 1 in linked regions. In contrast, the pedigree disequilibrium test (PDT) statistic adjusts for correlation between siblings due to linkage and maintains a constant variance of 1 at unassociated markers irrespective of linkage. The TDT statistic is generally larger than the PDT statistic across linked regions. This is true for unassociated as well as associated markers. To compare the two tests we ranked both statistics at the disease locus, or an associated marker, among statistics at all other markers. The TDT did better job than PDT placing the score of the associated marker near the top. Though, strictly speaking, the TDT in ASPs should be interpreted as a test of linkage and not a test of association, there is a good chance that if a marker stands out, the marker is associated as well as linked. In conclusion, our results suggest that TDT is an effective screening tool for WGA studies, especially in multiplex families.

Multifactor Dimensionality Reduction–Phenomics: A Novel Method to Capture Genetic Heterogeneity with Use of Phenotypic Variables

Complex human diseases do not have a clear inheritance pattern, and it is expected that risk involves multiple genes with modest effects acting independently or interacting. Major challenges for the identification of genetic effects are genetic heterogeneity and difficulty in analyzing high-order interactions. To address these challenges, we present MDR-Phenomics, a novel approach based on the multifactor dimensionality reduction (MDR) method, to detect genetic effects in pedigree data by integration of phenotypic covariates (PCs) that may reflect genetic heterogeneity. The P value of the test is calculated using a permutation test adjusted for multiple tests. To validate MDR-Phenomics, we compared it with two MDR-based methods: (1) traditional MDR pedigree disequilibrium test (PDT) without consideration of PCs (MDR-PDT) and (2) stratified phenotype (SP) analysis based on PCs, with use of MDR-PDT with a Bonferroni adjustment (SP-MDR). Using computer simulations, we examined the statistical power and type I error of the different approaches under several genetic models and sampling scenarios. We conclude that MDR-Phenomics is more powerful than MDR-PDT and SP-MDR when there is genetic heterogeneity, and the statistical power is affected by sample size and the number of PC levels. We further compared MDR-Phenomics with conditional logistic regression (CLR) for testing interactions across single or multiple loci with consideration of PC. The results show that CLR with PC has only slightly smaller power than does MDR-Phenomics for single-locus analysis but has considerably smaller power for multiple loci. Finally, by applying MDR-Phenomics to autism, a complex disease in which multiple genes are believed to confer risk, we attempted to identify multiple gene effects in two candidate genes of interest--the serotonin transporter gene (SLC6A4) and the integrin beta 3 gene (ITGB3) on chromosome 17. Analyzing four markers in SLC6A4 and four markers in ITGB3 in 117 white family triads with autism and using sex of the proband as a PC, we found significant interaction between two markers--rs1042173 in SLC6A4 and rs3809865 in ITGB3.

Information-Theoretic Metrics for Visualizing Gene-Environment Interactions

The purpose of our work was to develop heuristics for visualizing and interpreting gene-environment interactions (GEIs) and to assess the dependence of candidate visualization metrics on biological and study-design factors. Two information-theoretic metrics, the k-way interaction information (KWII) and the total correlation information (TCI), were investigated. The effectiveness of the KWII and TCI to detect GEIs in a diverse range of simulated data sets and a Crohn disease data set was assessed. The sensitivity of the KWII and TCI spectra to biological and study-design variables was determined. Head-to-head comparisons with the relevance-chain, multifactor dimensionality reduction, and the pedigree disequilibrium test (PDT) methods were obtained. The KWII and TCI spectra, which are graphical summaries of the KWII and TCI for each subset of environmental and genotype variables, were found to detect each known GEI in the simulated data sets. The patterns in the KWII and TCI spectra were informative for factors such as case-control misassignment, locus heterogeneity, allele frequencies, and linkage disequilibrium. The KWII and TCI spectra were found to have excellent sensitivity for identifying the key disease-associated genetic variations in the Crohn disease data set. In head-to-head comparisons with the relevance-chain, multifactor dimensionality reduction, and PDT methods, the results from visual interpretation of the KWII and TCI spectra performed satisfactorily. The KWII and TCI are promising metrics for visualizing GEIs. They are capable of detecting interactions among numerous single-nucleotide polymorphisms and environmental variables for a diverse range of GEI models.

A multi-marker test based on family data in genome-wide association study.

BackgroundComplex diseases are believed to be the results of many genes and environmental factors. Hence, multi-marker methods that can use the information of markers from different genes are appropriate for mapping complex disease genes. There already have been several multi-marker methods proposed for case-control studies. In this article, we propose a multi-marker test called a Multi-marker Pedigree Disequilibrium Test (MPDT) to analyze family data from genome-wide association studies. If the parental phenotypes are available, we also propose a two-stage test in which a genomic screening test is used to select SNPs, and then the MPDT is used to test the association of the selected SNPs.ResultsWe use simulation studies to evaluate the performance of the MPDT and the two-stage approach. The results show that the MPDT constantly outperforms the single marker transmission/disequilibrium test (TDT) [1]. Comparing the power of the two-stage approach with that of the one-stage approach, which approach is more powerful depends on the value of the prevalence; when the prevalence is no less than 10%, the two-stage approach may be more powerful than the one-stage approach. Otherwise, the one-stage approach is more powerful.ConclusionThe proposed MPDT, is more powerful than the single marker TDT. When the parental phenotypes are available and the prevalence is no less than 10%, the proposed two-stage approach is more powerful than the one-stage approach.