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Familial Aggregation (familial + aggregation)
Selected AbstractsFamilial Aggregation and Heritability of Electrocardiographic Intervals and Heart Rate in a Rural Chinese PopulationANNALS OF NONINVASIVE ELECTROCARDIOLOGY, Issue 2 2009Jianping Li M.D., Ph.D. Background: Estimates of the genetic influences on electrocardiographic (ECG) parameters are inconsistent in previous reports, and no such studies have been performed in China. So we estimated genetic contributions to PR and QRS intervals and the rate-adjusted QT interval (Bazett's QTc) in a Chinese rural population. Methods: A total of 2909 subjects from 847 families were enrolled in the current study. Genetic contributions to ECG parameters were estimated in two ways: correlation coefficients among family members (father-mother, parent-offspring, first sibling-other sibling) and the heritability of each of the ECG parameters. Results: Our results showed significant correlations among family members on theses parameters: the correlation coefficients for PR interval, QRS duration, QTc interval, and HR, between parent-sibling, and sibling-sibling were 0.17 and 0.13, 0.18 and 0.23, 0.22 and 0.28, 0.19 and 0.18, respectively. The heritability for PR interval, QRS duration, QTc interval, and HR were estimated as 0.34, 0.43, 0.40, and 0.34, respectively. Conclusion: Genetic factors, together with the environmental and other cofactors contribute no more than 60% to the variance of the ECG intervals, supporting the concept that multiple factors, including gene-gene and gene-environment interactions could influence ECG interval phenotypes, and genetic factors play a major role. [source] Familial clustering of cancer at human papillomavirus-associated sites according to the Swedish Family-Cancer DatabaseINTERNATIONAL JOURNAL OF CANCER, Issue 8 2008Shehnaz K. Hussain Abstract Familial aggregation of cervical cancer has been demonstrated previously, however aggregation of other human papillomavirus-associated anogenital, upper aerodigestive tract and skin cancers has not been fully characterized. The Swedish Family-Cancer Database, which contains reliable data on cancer incidence and nuclear family linkages for all residents of Sweden between 1958 and 2004, was used to calculate standardized incidence ratios (SIR) and 95% confidence intervals for offspring site-specific cancer risks according to site-specific cancer in sibling and parental probands. Offspring cancer risk was significantly increased when either a sibling or parent was affected at the same site for penile squamous cell carcinoma (SCC, SIR = 7.54), cervical adenocarcinoma (AC, SIR = 2.31), vulvar SCC (SIR = 2.27), skin SCC (SIR = 2.14), rectal AC (SIR = 1.86), in situ cervical SCC (SIR = 1.80), invasive cervical SCC (SIR = 1.77) and upper aerodigestive tract SCC (SIR = 1.57). Significant aggregation on the order of 2-fold between anogenital cancers at different sites or histologies was also observed. In situ cervical SCC risk in offspring was strongly influenced by siblings affected with oropharyngeal SCC (SIR = 3.17) and tonsillar SCC (SIR = 1.84). Familial skin SCC was largely unassociated with anogenital or upper aerodigestive tract cancer risk in offspring. These data suggest that common host factors exist among individuals affected with anogenital and upper aerodigestive tract cancers. © 2007 Wiley-Liss, Inc. [source] Familial aggregation in the night eating syndromeINTERNATIONAL JOURNAL OF EATING DISORDERS, Issue 6 2006Jennifer D. Lundgren PhD Abstract Objective: This study examined the extent to which the night eating syndrome (NES) affects first-degree relatives of NES and control probands. Method: NES participants and controls were assessed with the Night Eating Questionnaire (NEQ), the Night Eating Syndrome History and Inventory (NESHI), 10 day sleep and food records, the Eating Disorder Examination (EDE), the Structured Clinical Interview for DSM IV Axis I Disorders (SCID I), and a Family History Questionnaire (FHQ) to assess the presence of NES among first-degree relatives. A proband predictive model, using logistic regression analyses and the generalized estimating equation to control for correlation among observations within families was used to assess familial aggregation. Results: The odds of an NES proband having an affected first-degree relative were significantly greater than that of a control proband (odds ratio = 4.9, p < .001). A number of covariates were included in the model: proband body mass index (BMI) (kg/m2), proband gender, proband age, proband ethnicity, first-degree relative gender, relationship to proband (i.e., mother, father, or sibling), and the interaction between relationship to proband and proband status (night eater or control); none was statistically significant (p > .05). Conclusion: The study showed a strong aggregation of NES in families. © 2006 by Wiley Periodicals, Inc. Int J Eat Disord 2006 [source] The effect of familial aggregation on the children with primary nocturnal enuresisNEUROUROLOGY AND URODYNAMICS, Issue 5 2009Qing Wei Wang Abstract Objective To evaluate the effect of familial aggregation on the children with PNE by evaluating nocturnal urine output, bladder, and arouse function. Patients and Methods According to whether relatives of family of probands over three generations were affected by PNE, forty-five children with familial aggregation PNE (FPNE), seventy children with sporadic PNE (SPNE) and ten children with normal lower urinary tract function but waiting for operation (control group) were included. Questionnaire of arousal from sleep (AS scores), bladder diary and daytime urodynamic studies were performed in all patients. Results The incidences of severe PNE and nonmonosymptomatic PNE in FPNE group were significantly higher than those in SPNE group. The nocturnal urine output and AS scores in both PNE groups was significantly higher, maximal voided volume significantly smaller than those in control group. Moreover, the incidences of small bladder in FPNE group was 44%, significantly higher than that in SPNE group (21%), but no significantly difference was found in nocturnal polyuria and arousal AS scores between two PNE groups. There were 53% patents with daytime detrusor overactivity and 60% patents with urodynamic functional bladder outflow obstruction in FPNE group, significantly higher than those in SPNE group (19% and 37%). Maximum cystometric capacity significantly decreased from control group to FPNE group. Conclusion Familial aggregation has significant effects on the children with PNE, and FPNE are more likely to be severe symptoms and bladder dysfunction. It would be beneficial to have an urodynamic study for their diagnosis and treatment. Neurourol. Urodynam. 28:423,426, 2009. © 2008 Wiley-Liss, Inc. [source] Familial aggregation of olfactory impairment and odor identification in older adults,THE LARYNGOSCOPE, Issue 8 2010Laura A. Raynor MS Abstract Objectives/Hypothesis: The objective of this analysis was to estimate the genetic contributions to olfactory impairment. Study Design: Population based. Methods: Olfactory impairment was measured using the San Diego Odor Identification Test at the 5-year follow-up examination for the population-based Epidemiology of Hearing Loss study. Subjects were classified as impaired if they correctly identified fewer than six out of eight odorants. To reduce confounding by age, analysis was restricted to subjects who were 60 to 79 years of age. Familial aggregation was evaluated by heritability estimates, tetrachoric correlations, and odds ratios in 207 sibling pairs from 135 sibships. Results: The prevalence of olfactory impairment was 20.2% overall and was higher in men. After adjustment for sex, age, and smoking, heritability of olfactory impairment was moderate (h2 = 0.55), although not statistically significantly different from 0 (P = .09). By contrast, the adjusted heritability estimate for bubble gum, one of the individual odorants, was significant (h2 = 0.51; P = .01). Conclusions: Genetic factors might contribute to general olfactory impairment in older adults, but the strength of familial aggregation differs for individual odorants, a finding consistent with prior research. Laryngoscope, 2010 [source] Familial aggregation in amyotrophic lateral sclerosisANNALS OF NEUROLOGY, Issue 4 2010Susan Byrne MRCPI No abstract is available for this article. [source] Familial aggregation of amyotrophic lateral sclerosis,ANNALS OF NEUROLOGY, Issue 1 2009Fang Fang MD Objective To assess the relative risk for amyotrophic lateral sclerosis (ALS) in families of ALS patients. Methods We conducted a cohort study based on the Swedish Multi-Generation Register in 1961 to 2005. Among 6,671 probands (first ALS case in the family), 1,909 full siblings, 13,947 children, and 5,405 spouses were identified (exposed group). Other persons in the Multi-Generation Register, who were siblings, children, or spouses to persons without ALS, served as the reference group. Relative risks for ALS among the exposed group, compared with the reference group, were calculated from Poisson regression models. Concurrence of ALS within twins was assessed in 86,441 twin pairs registered in the Swedish Twin Register. Results Nine cases of ALS were noted among the siblings and 37 cases among the children of the probands, giving a 17-fold risk among the siblings (95% confidence interval, 8.1,30.4) and a 9-fold risk among the children (95% confidence interval, 6.2,12.0), compared with the reference group. Siblings and children had a greater excess risk if the proband was diagnosed at a younger age, and the excess risks decreased with increasing age at diagnosis of the proband (p < 0.001). Spouses had no significantly increased risk (p = 0.27). Two cases were identified among the cotwins of ALS probands, giving a relative risk of 32 (95% confidence interval, 5.2,102.6). Interpretation The siblings and children of ALS patients have an about 10-fold risk for ALS compared with the reference group. The excess risks vary with both age and kinship, indicating a major genetic role in familial ALS. Ann Neurol 2009;66:94,99 [source] Familial aggregation of postpartum mood symptoms in bipolar disorder pedigreesBIPOLAR DISORDERS, Issue 1 2008Jennifer L Payne Objectives:, We sought to determine if postpartum mood symptoms and depressive episodes exhibit familial aggregation in bipolar I pedigrees. Methods:, A total of 1,130 women were interviewed with the Diagnostic Interview for Genetic Studies as part of the National Institute of Mental Health (NIMH) Genetics Initiative Bipolar Disorder Collaborative Study and were asked whether they had ever experienced mood symptoms within four weeks postpartum. Women were also asked whether either of two major depressive episodes described in detail occurred postpartum. We examined the odds of postpartum mood symptoms in female siblings, who had previously been pregnant and had a diagnosis of bipolar I, bipolar II, or schizoaffective (bipolar type) disorders (n = 303), given one or more relatives with postpartum mood symptoms. Results:, The odds ratio for familial aggregation of postpartum mood symptoms was 2.31 (p = 0.011) in an Any Mood Symptoms analysis (n = 304) and increased to 2.71 (p = 0.005) when manic symptoms were excluded, though this was not significantly different from the Any Mood Symptoms analysis. We also examined familial aggregation of postpartum major depressive episodes; however, the number of subjects was small. Conclusions:, Limitations of the study include the retrospective interview, the fact that the data were collected for other purposes and the inability to control for such factors as medication use. Taken together with previous studies, these data provide support for the hypothesis that there may be a genetic basis for the trait of postpartum mood symptoms generally and postpartum depressive symptoms in particular in women with bipolar disorder. Genetic linkage and association studies incorporating this trait are warranted. [source] Suggestive linkage of familial primary cutaneous amyloidosis to a locus on chromosome 1q23BRITISH JOURNAL OF DERMATOLOGY, Issue 1 2005M-W. Lin Summary Background, There is a high incidence of primary cutaneous amyloidosis (PCA) in South America, South-east Asia and Taiwan. To date, the aetiology of PCA remains unknown, but it is believed to be multifactorial. Although most cases are sporadic, some patients have a family history. Familial aggregation and different susceptibility to PCA among ethnic groups suggest that genetic factors may play an important role in its pathogenesis. However, no genetic loci for familial PCA (FPCA) have been identified so far. Objectives, In order to identify the susceptibility gene of FPCA, we took a candidate gene approach and performed linkage analysis on chromosome 1q21.3,24.2, including the 1q23.2 region where the gene encoding serum amyloid P component (APCS) is located. Patients and methods, Nine FPCA families including 29 individuals affected with PCA were recruited for this linkage study. Initially, 11 highly polymorphic microsatellite markers spanning the region from 1q21.3 to 1q24.2 were genotyped and revealed a suggestive linkage region. This region was further fine-mapped with seven additional markers. We also re-sequenced the 2·5-kb genomic region of the APCS gene in 29 affected and 42 control individuals. Two-point and multipoint linkage analyses were performed using the LINKAGE program. Nonparametric linkage (NPL) analysis and reconstruction of haplotypes were performed with the GENEHUNTER program. Results, Both two-point and multipoint linkage analysis for all 11 markers generated negative or small positive total lod scores for all nine families. However, when we considered only three families, a maximum two-point total lod score of 2·09 was obtained for the marker D1S2844 at , = 0·01. A plateau of multipoint total lod score between D1S2768 and D1S2878 with a maximum of 2·48 at the marker D1S2844 was observed. A maximum NPL score of 3·11 (P = 0·008) was also obtained for the marker D1S2878. However, re-sequencing of the APCS gene identified no functional mutation. Conclusions, Both parametric and nonparametric linkage evidence suggested that a possible susceptibility locus for a subset of FPCA might exist on chromosome 1q23. This is the first report demonstrating suggestive evidence of linkage of FPCA to a locus in this candidate region. No functional sequence variations of the APCS gene were found to be associated with this disease among the study families. Our data imply the existence of at least one additional locus responsible for FPCA in these families, confirming genetic heterogeneity of this skin disorder. [source] Common genetic variants in candidate genes and risk of familial lymphoid malignanciesBRITISH JOURNAL OF HAEMATOLOGY, Issue 4 2009Xueying (Sharon) Liang Summary Familial aggregation, linkage and case,control studies support the role of germline genes in the aetiology of lymphoid malignancies. To further examine the role of genetic variation underlying susceptibility, we analysed 1536 single nucleotide polymorphisms in 152 genes involved in apoptosis, DNA repair, immune response and oxidative stress pathways among a unique sample of 165 unrelated familial cases including patients with chronic lymphocytic leukaemia (CLL), Waldenström macroglobulinaemia (WM) and Hodgkin lymphoma (HL), and 107 spouse controls. We confirmed previous studies showing a polymorphism in the IL10 promoter (rs1800890/-3575T>A) to be associated with non-Hodgkin lymphoma, as this allele was found to be associated with both CLL and WM. We also confirmed the role of IL6 variation to be associated with HL. Polymorphisms in TNFSF10 were associated with both CLL and WM. Future replication and functional studies are needed to clarify the role of these genetic variants. Finally, our data further support the close association of WM and CLL. [source] Restless legs syndrome: an update on genetics and future perspectivesCLINICAL GENETICS, Issue 4 2008I Pichler Restless legs syndrome (RLS) is a common, underdiagnosed neurological condition with an age-dependent prevalence of up to 14%. Familial aggregation has been widely shown since Ekbom's first description of the disorder in 1945. Five loci (12q, 14q, 9p, 2q, and 20p) have been described so far, although no positive association with any specific genes, either within these loci or additional candidates investigated, has been reported. Two recent genome-wide association studies have reported positive association with sequence variants in or around specific genes on chromosomes 6p, 2p and 15q. The molecular findings, together with the variable expressivity of the phenotype, suggest a substantial clinical and genetic heterogeneity of RLS. This article reviews the clinical characteristics, diagnosis and epidemiology with a focus on the genetics and pathogenesis of RLS. [source] The familial aggregation of cannabis use disordersADDICTION, Issue 4 2009Kathleen R. Merikangas ABSTRACT Aims The aim of this paper is to examine the familial aggregation of cannabis use disorders and other psychiatric conditions among first-degree relatives and spouses of probands with a cannabis use disorder. Design Controlled family study methods. Setting Out-patient psychiatric clinics and the local community (same geographic area). Participants Two hundred and sixty-two probands with a life-time history of cannabis use disorder, alcohol dependence, anxiety disorders or no history of any disorder, and their first-degree relatives and spouses. Measurements Cannabis use disorders and other DSM-III-R disorders in the relatives and spouses using the Schedule for Affective Disorders and Schizophrenia. Findings Results reveal an elevated risk of life-time history of cannabis use disorders among siblings [odds ratio (OR: 3.6), adult offspring (OR): 6.9], and spouses (OR: 4.4) of probands with cannabis use disorders. There is a latent familial factor underlying cannabis use disorders that was shared partially with alcohol abuse/dependence. Comorbid mood and anxiety disorders aggregated independently from cannabis use disorders in families. Equal elevation in the magnitude of the association among the first-degree adult relatives and spouses of probands with a cannabis use disorder suggests the probable contribution of both environmental and genetic factors. Conclusions These findings support a family-based approach to drug abuse intervention and the importance of future research concerning environmental mediators of familial transmission of drug abuse. [source] Modeling the genetic and environmental association between peer group deviance and cannabis use in male twinsADDICTION, Issue 3 2009Nathan A. Gillespie ABSTRACT Background Peer group deviance (PGD) is linked strongly to liability to drug use, including cannabis. Our aim was to model the genetic and environmental association, including direction of causation, between PGD and cannabis use (CU). Method Results were based on 1736 to 1765 adult males from the Mid-Atlantic Twin Registry with complete CU and PGD data measured retrospectively at three time-intervals between 15 and 25 years using a life-history calendar. Results At all ages, multivariate modeling showed that familial aggregation in PGD was explained by a combination of additive genetic and shared environmental effects. Moreover, the significant PGD,CU association was best explained by a CU,PGD causal model in which large portions of the additive genetic (50,78%) and shared environmental variance (25,73%) in PGD were explained by CU. Conclusions Until recently PGD was assumed to be an environmental, upstream risk factor for CU. Our data are not consistent with this hypothesis. Rather, they suggest that the liability to affiliate with deviant peers is explained more clearly by a combination of genetic and environmental factors that are indexed by CU which sits as a ,risk indicator' in the causal pathway between genetic and environmental risks and the expression of PGD. This is consistent with a process of social selection by which the genetic and environmental risks in CU largely drive the propensity to affiliate with deviant peers. [source] Genetic and phenotypic effects of phonological short-term memory and grammatical morphology in specific language impairmentGENES, BRAIN AND BEHAVIOR, Issue 4 2008M. Falcaro Deficits in phonological short-term memory and aspects of verb grammar morphology have been proposed as phenotypic markers of specific language impairment (SLI) with the suggestion that these traits are likely to be under different genetic influences. This investigation in 300 first-degree relatives of 93 probands with SLI examined familial aggregation and genetic linkage of two measures thought to index these two traits, non-word repetition and tense marking. In particular, the involvement of chromosomes 16q and 19q was examined as previous studies found these two regions to be related to SLI. Results showed a strong association between relatives' and probands' scores on non-word repetition. In contrast, no association was found for tense marking when examined as a continuous measure. However, significant familial aggregation was found when tense marking was treated as a binary measure with a cut-off point of ,1.5 SD, suggestive of the possibility that qualitative distinctions in the trait may be familial while quantitative variability may be more a consequence of non-familial factors. Linkage analyses supported previous findings of the SLI Consortium of linkage to chromosome 16q for phonological short-term memory and to chromosome 19q for expressive language. In addition, we report new findings that relate to the past tense phenotype. For the continuous measure, linkage was found on both chromosomes, but evidence was stronger on chromosome 19. For the binary measure, linkage was observed on chromosome 19 but not on chromosome 16. [source] Association and aggregation analysis using kin-cohort designs with applications to genotype and family history data from the Washington Ashkenazi StudyGENETIC EPIDEMIOLOGY, Issue 2 2001Nilanjan Chatterjee Abstract When a rare inherited mutation in a disease gene, such as BRCA1, is found through extensive study of high-risk families, it is critical to estimate not only age-specific penetrance of the disease associated with the mutation, but also the residual effect of family history once the mutation is taken into account. The kin-cohort design, a cross-sectional survey of a suitable population that collects DNA and family history data, provides an efficient alternative to cohort or case-control designs for estimating age-specific penetrance in a population not selected because of high familial risk. In this report, we develop a method for analyzing kin-cohort data that simultaneously estimate the age-specific cumulative risk of the disease among the carriers and non-carriers of the mutations and the gene-adjusted residual familial aggregation or correlation of the disease. We employ a semiparametric modeling approach, where the marginal cumulative risks corresponding to the carriers and non-carriers are treated non-parametrically and the residual familial aggregation is described parametrically by a class of bivariate failure time models known as copula models. A simple and robust two-stage method is developed for estimation. We apply the method to data from the Washington Ashkenazi Study [Struewing et al., 1997, N Engl J Med 336:1401,1408] to study the residual effect of family history on the risk of breast cancer among non-carriers and carriers of specific BRCA1/BRCA2 germline mutations. We find that positive history of a single first-degree relative significantly increases risk of the non-carriers (RR = 2.0, 95% CI = 1.6,2.6) but has little or no effect on the carriers. Genet. Epidemiol. 21:123,138, 2001. © 2001 Wiley-Liss, Inc. [source] Sex-specific familial risks of urinary bladder cancer and associated neoplasms in SwedenINTERNATIONAL JOURNAL OF CANCER, Issue 9 2009Justo Lorenzo Bermejo Abstract Male gender and a family history of cancer are established risk factors for urinary bladder neoplasms. This study used the latest update of the Swedish Family-Cancer Database, which includes 42,255 bladder cancer patients, to investigate the sex-specific incidences and types of tumors in relatives of bladder cancer patients. Men with parents or siblings affected by lung cancer did not show an increased risk of bladder neoplasms. Among women, the familial association was restricted to daughters of women with lung cancer. Brothers showed higher risks than the sons of bladder cancer patients. Men older than 54 years were at an increased risk of bladder cancer only if their fathers or siblings were diagnosed after age 65 years. The present data indicated a limited contribution of smoking to the familial clustering of bladder cancer with other neoplasms. The dependence of the relative risks on the type of familial relationship probably reflected a heterogeneous character of familial aggregation. Age-specific results suggested differential risk factors for tumors diagnosed before 50 years of age versus neoplasms detected later in life. The present data may guide the design of forthcoming gene identification studies and the interpretation of the genome-wide association studies that are about to be published. © 2008 Wiley-Liss, Inc. [source] Cancer patterns in nasopharyngeal carcinoma multiplex families in TaiwanINTERNATIONAL JOURNAL OF CANCER, Issue 7 2009Kelly J. Yu Abstract Genetic and environmental factors have been implicated in the etiology of nasopharyngeal carcinoma (NPC), a tumor known to be closely associated with Epstein-Barr virus (EBV) infection. Studies have reported familial aggregation of NPC and have suggested the possible aggregation of NPC and other cancers. We evaluated familial aggregation of cancer in 358 high-risk families with two or more NPC cases enrolled in a NPC genetics study in Taiwan. Participants were linked to the Taiwan National Cancer Registry to identify incident cancers diagnosed after study enrollment (started in 1996) and before December 31, 2005, or death. In total, 2,870 individuals from the NPC Multiplex Family Study contributed 15,151 person-years over an average of 5.3 years of follow-up. One hundred ten incident cancers were identified. Multiple-primary standardized incidence ratios (MP-SIRs) were computed to evaluate overall cancer risk associated with infectious agents and with other tumors. The overall MP-SIR was 1.3 (95% CI: 1.1,1.6), which was largely explained by an excess in NPC (MP-SIR = 15; 95% CI: 10,23). Exclusion of incident NPC diagnoses led to an overall MP-SIR of 1.0 (95% CI: 0.83,1.3). Similarly, the observed excess risk of cancers associated with infectious agents (MP-SIR = 2.0; 95% CI: 1.5,2.6) was driven by the excess in NPC; exclusion of NPC cases led to a reduced MP-SIR that did not differ from 1.0. Analysis of the largest NPC multiplex family study to date confirms the presence of coaggregation of NPC within families in Taiwan but does not provide evidence for a broader familial syndrome involving NPC and other tumors. © 2008 Wiley-Liss, Inc. [source] Familial aggregation in the night eating syndromeINTERNATIONAL JOURNAL OF EATING DISORDERS, Issue 6 2006Jennifer D. Lundgren PhD Abstract Objective: This study examined the extent to which the night eating syndrome (NES) affects first-degree relatives of NES and control probands. Method: NES participants and controls were assessed with the Night Eating Questionnaire (NEQ), the Night Eating Syndrome History and Inventory (NESHI), 10 day sleep and food records, the Eating Disorder Examination (EDE), the Structured Clinical Interview for DSM IV Axis I Disorders (SCID I), and a Family History Questionnaire (FHQ) to assess the presence of NES among first-degree relatives. A proband predictive model, using logistic regression analyses and the generalized estimating equation to control for correlation among observations within families was used to assess familial aggregation. Results: The odds of an NES proband having an affected first-degree relative were significantly greater than that of a control proband (odds ratio = 4.9, p < .001). A number of covariates were included in the model: proband body mass index (BMI) (kg/m2), proband gender, proband age, proband ethnicity, first-degree relative gender, relationship to proband (i.e., mother, father, or sibling), and the interaction between relationship to proband and proband status (night eater or control); none was statistically significant (p > .05). Conclusion: The study showed a strong aggregation of NES in families. © 2006 by Wiley Periodicals, Inc. Int J Eat Disord 2006 [source] Males with anorexia nervosa: A controlled study of eating disorders in first-degree relativesINTERNATIONAL JOURNAL OF EATING DISORDERS, Issue 3 2001Michael Strober Abstract Objective To compare lifetime rates of full and partial anorexia nervosa and bulimia nervosa in first-degree relatives of males with anorexia nervosa and in relatives of never-ill comparison subjects. Methods Rates of eating disorders were obtained for 747 relatives of 210 probands from personal structured clinical interviews and family history. Best-estimate diagnoses were determined blind to proband diagnosis and pedigree status. Results Full and partial syndromes of anorexia nervosa aggregated in female relatives of ill probands. For the full syndrome of anorexia nervosa, the crude relative risk was 20.3 among female relatives and for partial syndrome anorexia nervosa, the crude relative risk was 3.3. In contrast, bulimia nervosa was relatively uncommon among relatives of ill probands. Conclusion Although anorexia nervosa in males is exceedingly rare, there is a pattern of familial aggregation that is highly similar to that observed in recent family studies of affected females. On the basis of these findings, there is no evidence that familial-genetic factors distinguish the occurrence of anorexia nervosa in the two sexes. © 2001 by John Wiley & Sons, Inc. Int J Eat Disord 29: 263,269, 2001. [source] Subject and informant characteristics influence the reliability and validity of family history information: an analysis based on the generalized estimating equations approachINTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH, Issue 2 2000Reinhard Heun Abstract Family history information is a necessary surrogate for unavailable interview information in family studies. However, the reliability and validity of such information has rarely been assessed during the conduct of family studies. This paper presents a reanalysis of data on the reliability and validity of family history information for dementia and depression using the general estimation equations approach. All available relatives of patients and controls were interviewed and questioned about the psychiatric morbidity of other family members. Interinformant reliability of this family history information was evaluated as well as factors influencing this information. The validity of family history was investigated by comparing the informant derived diagnoses with interview-derived diagnoses. To account for possible lack of independence of family history provided by several family members on other family members, the generalized estimating equations (GEE) were used in statistical analysis. The interinformant reliability for depression (kappa = 0.13) was low. It was fair for dementia (kappa = 0.34). The informants more frequently agreed about the diagnosis of dementia when the subject was older. The sensitivity of family history was 35.2% for dementia and 31.8% for depression. The specificity of family history information was generally above 97%. The sensitivity of family history increased significantly with the severity of both disorders. The sensitivity of the family history for dementia was higher when the informant was a first-degree relative, when he was younger and when the index subject of the family suffered from dementia. The specificity of the family history was slightly reduced with higher age. The observed low sensitivity of family history information leads to underestimation of psychiatric disorders. The informants provide more useful information on more severe disorders. The sensitivity of family history was higher in families with an affected index subject than in control families, so familial aggregation of dementia might be overestimated in studies using the family history method. Copyright © 2000 Whurr Publishers Ltd. [source] Differences in age at onset and familial aggregation between clinical types of idiopathic Parkinson's diseaseMOVEMENT DISORDERS, Issue 9 2004Alexei Korchounov MD Abstract Idiopathic Parkinson's disease (PD) can be subdivided by its patterns of motor symptoms into tremor-dominant (TDT), akinetic-rigid (ART), and mixed type (MT). Our objective was to determine whether age at onset and family history are different in these three types. In total, 366 patients with PD were assigned in a standardized approach to one of the three subtypes. Age at onset and family history were obtained in all patients and all presumably affected family members were examined. Mean ages at disease onset were similar in all three groups, but distribution of age at onset was markedly different: monophasic in TDT with a peak around 60 years, biphasic in ART with two peaks, one in the middle of the sixth decade (earlier onset, ART-EO), another during the first half of the seventh decade (later onset, ART-LO), and increasing with age only in MT patients A positive family history was significantly associated only with TDT (odds ratio = 5.7) and ART-EO (odds ratio = 7.8), but not with MT or ART-LO patients. Segregation analysis suggested an autosomal recessive mode of transmission in ART-EO and an autosomal dominant mode of transmission in TDT. © 2004 Movement Disorder Society [source] The effect of familial aggregation on the children with primary nocturnal enuresisNEUROUROLOGY AND URODYNAMICS, Issue 5 2009Qing Wei Wang Abstract Objective To evaluate the effect of familial aggregation on the children with PNE by evaluating nocturnal urine output, bladder, and arouse function. Patients and Methods According to whether relatives of family of probands over three generations were affected by PNE, forty-five children with familial aggregation PNE (FPNE), seventy children with sporadic PNE (SPNE) and ten children with normal lower urinary tract function but waiting for operation (control group) were included. Questionnaire of arousal from sleep (AS scores), bladder diary and daytime urodynamic studies were performed in all patients. Results The incidences of severe PNE and nonmonosymptomatic PNE in FPNE group were significantly higher than those in SPNE group. The nocturnal urine output and AS scores in both PNE groups was significantly higher, maximal voided volume significantly smaller than those in control group. Moreover, the incidences of small bladder in FPNE group was 44%, significantly higher than that in SPNE group (21%), but no significantly difference was found in nocturnal polyuria and arousal AS scores between two PNE groups. There were 53% patents with daytime detrusor overactivity and 60% patents with urodynamic functional bladder outflow obstruction in FPNE group, significantly higher than those in SPNE group (19% and 37%). Maximum cystometric capacity significantly decreased from control group to FPNE group. Conclusion Familial aggregation has significant effects on the children with PNE, and FPNE are more likely to be severe symptoms and bladder dysfunction. It would be beneficial to have an urodynamic study for their diagnosis and treatment. Neurourol. Urodynam. 28:423,426, 2009. © 2008 Wiley-Liss, Inc. [source] Inheritance of sutural pattern at the pterion in rhesus monkey skullsTHE ANATOMICAL RECORD : ADVANCES IN INTEGRATIVE ANATOMY AND EVOLUTIONARY BIOLOGY, Issue 10 2006Qian Wang Abstract Five of the bones that characteristically comprise the cranial vault articulate on the lateral aspect of the skull at or near the cephalometric landmark referred to as the pterion. The pattern of articulation in the sutures associated with these bones varies among and within primate species and has been used as a criterion for classification in taxonomic studies, as well as in archeological and forensic studies. Within species, the sutural patterns found within the region of the pterion have remarkable consistency, which lead to the hypothesis that these patterns have a genetic basis. Sutural pattern variations were investigated at the pterion in 422 skulls from 66 rhesus monkey families with known genealogies from the long-standing colony on Cayo Santiago. Four specific types of articulation patterns were recorded. The results demonstrated that the most common suture pattern at the pterion of Cayo Santiago rhesus monkeys (86%; similar to that seen in some other anthropoid species but not humans and some apes) was characterized by an articulation between the temporal bone and parietal bone. Articulation between the sphenoid and parietal bones (type SP) accounted for 14% of the specimens and was concentrated in a dozen families. Mothers with the SP phenotype had a high incidence of offspring with SP phenotypes. Most non-SP mothers having SP offspring had siblings or family members from previous generations with the SP type. This is the first study to examine variation in sutural patterns at the pterion in pedigrees. Variation of sutural patterns shows familial aggregation, suggesting that this variation is heritable. Future work will be focused on defining the inheritance patterns of variation at the pterion, with the ultimate objective of identifying the specific genes involved and their mechanism of action. Anat Rec Part A, 288A:1042,1049, 2006. © 2006 Wiley-Liss, Inc. [source] Familial associations of intense preoccupations, an empirical factor of the restricted, repetitive behaviors and interests domain of autismTHE JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY AND ALLIED DISCIPLINES, Issue 8 2009Christopher J. Smith Background:, Clinical heterogeneity of autism likely hinders efforts to find genes associated with this complex psychiatric disorder. Some studies have produced promising results by restricting the sample according to the expression of specific familial factors or components of autism. Previous factor analyses of the restricted, repetitive behaviors and interest (RRBI) domain of autism have consistently identified a two-factor model that explains a moderate amount of variance. The identification of additional factors may explain more variance in the RRBI domain and provide an additional component of autism that may help in the identification of underlying genetic association. Methods:, We conducted factor analyses of RRBI symptoms with a sample that included verbal subjects meeting full criteria for autism aged 5 to 22 years (n = 245). Among affected sibling pairs (n = 126) we examined the familial aggregation of the identified factors. We also examined the associations of the factors with autism-related personality traits in fathers and mothers (n = 50). Results:, The previously identified two-factor model , insistence on sameness (IS) and repetitive stereotypic motor behaviors (RSMB) , was replicated in our sample. Next, a second factor analysis that included the item for verbal rituals resulted in a four-factor model , IS, ,simple' RSMB, ,complex' RSMB, and a fourth factor including symptoms associated with intense preoccupations (IP). Of these four, both IS and IP were significantly familial among affected siblings, but only IP was significantly correlated with the broader autism phenotype traits of rigidity and aloofness in fathers. Conclusions:, The results support previous evidence for the IS factor, its familiality, and the identification of IP as an additional strong candidate trait for genetic studies of autism. [source] Familial aggregation of olfactory impairment and odor identification in older adults,THE LARYNGOSCOPE, Issue 8 2010Laura A. Raynor MS Abstract Objectives/Hypothesis: The objective of this analysis was to estimate the genetic contributions to olfactory impairment. Study Design: Population based. Methods: Olfactory impairment was measured using the San Diego Odor Identification Test at the 5-year follow-up examination for the population-based Epidemiology of Hearing Loss study. Subjects were classified as impaired if they correctly identified fewer than six out of eight odorants. To reduce confounding by age, analysis was restricted to subjects who were 60 to 79 years of age. Familial aggregation was evaluated by heritability estimates, tetrachoric correlations, and odds ratios in 207 sibling pairs from 135 sibships. Results: The prevalence of olfactory impairment was 20.2% overall and was higher in men. After adjustment for sex, age, and smoking, heritability of olfactory impairment was moderate (h2 = 0.55), although not statistically significantly different from 0 (P = .09). By contrast, the adjusted heritability estimate for bubble gum, one of the individual odorants, was significant (h2 = 0.51; P = .01). Conclusions: Genetic factors might contribute to general olfactory impairment in older adults, but the strength of familial aggregation differs for individual odorants, a finding consistent with prior research. Laryngoscope, 2010 [source] European Mathematical Genetics Meeting, Heidelberg, Germany, 12th,13th April 2007ANNALS OF HUMAN GENETICS, Issue 4 2007Article first published online: 28 MAY 200 Saurabh Ghosh 11 Indian Statistical Institute, Kolkata, India High correlations between two quantitative traits may be either due to common genetic factors or common environmental factors or a combination of both. In this study, we develop statistical methods to extract the contribution of a common QTL to the total correlation between the components of a bivariate phenotype. Using data on bivariate phenotypes and marker genotypes for sib-pairs, we propose a test for linkage between a common QTL and a marker locus based on the conditional cross-sib trait correlations (trait 1 of sib 1 , trait 2 of sib 2 and conversely) given the identity-by-descent sharing at the marker locus. The null hypothesis cannot be rejected unless there exists a common QTL. We use Monte-Carlo simulations to evaluate the performance of the proposed test under different trait parameters and quantitative trait distributions. An application of the method is illustrated using data on two alcohol-related phenotypes from the Collaborative Study On The Genetics Of Alcoholism project. Rémi Kazma 1 , Catherine Bonaďti-Pellié 1 , Emmanuelle Génin 12 INSERM UMR-S535 and Université Paris Sud, Villejuif, 94817, France Keywords: Gene-environment interaction, sibling recurrence risk, exposure correlation Gene-environment interactions may play important roles in complex disease susceptibility but their detection is often difficult. Here we show how gene-environment interactions can be detected by investigating the degree of familial aggregation according to the exposure of the probands. In case of gene-environment interaction, the distribution of genotypes of affected individuals, and consequently the risk in relatives, depends on their exposure. We developed a test comparing the risks in sibs according to the proband exposure. To evaluate the properties of this new test, we derived the formulas for calculating the expected risks in sibs according to the exposure of probands for various values of exposure frequency, relative risk due to exposure alone, frequencies of latent susceptibility genotypes, genetic relative risks and interaction coefficients. We find that the ratio of risks when the proband is exposed and not exposed is a good indicator of the interaction effect. We evaluate the power of the test for various sample sizes of affected individuals. We conclude that this test is valuable for diseases with moderate familial aggregation, only when the role of the exposure has been clearly evidenced. Since a correlation for exposure among sibs might lead to a difference in risks among sibs in the different proband exposure strata, we also add an exposure correlation coefficient in the model. Interestingly, we find that when this correlation is correctly accounted for, the power of the test is not decreased and might even be significantly increased. Andrea Callegaro 1 , Hans J.C. Van Houwelingen 1 , Jeanine Houwing-Duistermaat 13 Dept. of Medical Statistics and Bioinformatics, Leiden University Medical Center, The Netherlands Keywords: Survival analysis, age at onset, score test, linkage analysis Non parametric linkage (NPL) analysis compares the identical by descent (IBD) sharing in sibling pairs to the expected IBD sharing under the hypothesis of no linkage. Often information is available on the marginal cumulative hazards (for example breast cancer incidence curves). Our aim is to extend the NPL methods by taking into account the age at onset of selected sibling pairs using these known marginal hazards. Li and Zhong (2002) proposed a (retrospective) likelihood ratio test based on an additive frailty model for genetic linkage analysis. From their model we derive a score statistic for selected samples which turns out to be a weighed NPL method. The weights depend on the marginal cumulative hazards and on the frailty parameter. A second approach is based on a simple gamma shared frailty model. Here, we simply test whether the score function of the frailty parameter depends on the excess IBD. We compare the performance of these methods using simulated data. Céline Bellenguez 1 , Carole Ober 2 , Catherine Bourgain 14 INSERM U535 and University Paris Sud, Villejuif, France 5 Department of Human Genetics, The University of Chicago, USA Keywords: Linkage analysis, linkage disequilibrium, high density SNP data Compared with microsatellite markers, high density SNP maps should be more informative for linkage analyses. However, because they are much closer, SNPs present important linkage disequilibrium (LD), which biases classical nonparametric multipoint analyses. This problem is even stronger in population isolates where LD extends over larger regions with a more stochastic pattern. We investigate the issue of linkage analysis with a 500K SNP map in a large and inbred 1840-member Hutterite pedigree, phenotyped for asthma. Using an efficient pedigree breaking strategy, we first identified linked regions with a 5cM microsatellite map, on which we focused to evaluate the SNP map. The only method that models LD in the NPL analysis is limited in both the pedigree size and the number of markers (Abecasis and Wigginton, 2005) and therefore could not be used. Instead, we studied methods that identify sets of SNPs with maximum linkage information content in our pedigree and no LD-driven bias. Both algorithms that directly remove pairs of SNPs in high LD and clustering methods were evaluated. Null simulations were performed to control that Zlr calculated with the SNP sets were not falsely inflated. Preliminary results suggest that although LD is strong in such populations, linkage information content slightly better than that of microsatellite maps can be extracted from dense SNP maps, provided that a careful marker selection is conducted. In particular, we show that the specific LD pattern requires considering LD between a wide range of marker pairs rather than only in predefined blocks. Peter Van Loo 1,2,3 , Stein Aerts 1,2 , Diether Lambrechts 4,5 , Bernard Thienpont 2 , Sunit Maity 4,5 , Bert Coessens 3 , Frederik De Smet 4,5 , Leon-Charles Tranchevent 3 , Bart De Moor 2 , Koen Devriendt 3 , Peter Marynen 1,2 , Bassem Hassan 1,2 , Peter Carmeliet 4,5 , Yves Moreau 36 Department of Molecular and Developmental Genetics, VIB, Belgium 7 Department of Human Genetics, University of Leuven, Belgium 8 Bioinformatics group, Department of Electrical Engineering, University of Leuven, Belgium 9 Department of Transgene Technology and Gene Therapy, VIB, Belgium 10 Center for Transgene Technology and Gene Therapy, University of Leuven, Belgium Keywords: Bioinformatics, gene prioritization, data fusion The identification of genes involved in health and disease remains a formidable challenge. Here, we describe a novel bioinformatics method to prioritize candidate genes underlying pathways or diseases, based on their similarity to genes known to be involved in these processes. It is freely accessible as an interactive software tool, ENDEAVOUR, at http://www.esat.kuleuven.be/endeavour. Unlike previous methods, ENDEAVOUR generates distinct prioritizations from multiple heterogeneous data sources, which are then integrated, or fused, into one global ranking using order statistics. ENDEAVOUR prioritizes candidate genes in a three-step process. First, information about a disease or pathway is gathered from a set of known "training" genes by consulting multiple data sources. Next, the candidate genes are ranked based on similarity with the training properties obtained in the first step, resulting in one prioritized list for each data source. Finally, ENDEAVOUR fuses each of these rankings into a single global ranking, providing an overall prioritization of the candidate genes. Validation of ENDEAVOUR revealed it was able to efficiently prioritize 627 genes in disease data sets and 76 genes in biological pathway sets, identify candidates of 16 mono- or polygenic diseases, and discover regulatory genes of myeloid differentiation. Furthermore, the approach identified YPEL1 as a novel gene involved in craniofacial development from a 2-Mb chromosomal region, deleted in some patients with DiGeorge-like birth defects. Finally, we are currently evaluating a pipeline combining array-CGH, ENDEAVOUR and in vivo validation in zebrafish to identify novel genes involved in congenital heart defects. Mark Broom 1 , Graeme Ruxton 2 , Rebecca Kilner 311 Mathematics Dept., University of Sussex, UK 12 Division of Environmental and Evolutionary Biology, University of Glasgow, UK 13 Department of Zoology, University of Cambridge, UK Keywords: Evolutionarily stable strategy, parasitism, asymmetric game Brood parasites chicks vary in the harm that they do to their companions in the nest. In this presentation we use game-theoretic methods to model this variation. Our model considers hosts which potentially abandon single nestlings and instead choose to re-allocate their reproductive effort to future breeding, irrespective of whether the abandoned chick is the host's young or a brood parasite's. The parasite chick must decide whether or not to kill host young by balancing the benefits from reduced competition in the nest against the risk of desertion by host parents. The model predicts that three different types of evolutionarily stable strategies can exist. (1) Hosts routinely rear depleted broods, the brood parasite always kills host young and the host never then abandons the nest. (2) When adult survival after deserting single offspring is very high, hosts always abandon broods of a single nestling and the parasite never kills host offspring, effectively holding them as hostages to prevent nest desertion. (3) Intermediate strategies, in which parasites sometimes kill their nest-mates and host parents sometimes desert nests that contain only a single chick, can also be evolutionarily stable. We provide quantitative descriptions of how the values given to ecological and behavioral parameters of the host-parasite system influence the likelihood of each strategy and compare our results with real host-brood parasite associations in nature. Martin Harrison 114 Mathematics Dept, University of Sussex, UK Keywords: Brood parasitism, games, host, parasite The interaction between hosts and parasites in bird populations has been studied extensively. Game theoretical methods have been used to model this interaction previously, but this has not been studied extensively taking into account the sequential nature of this game. We consider a model allowing the host and parasite to make a number of decisions, which depend on a number of natural factors. The host lays an egg, a parasite bird will arrive at the nest with a certain probability and then chooses to destroy a number of the host eggs and lay one of it's own. With some destruction occurring, either natural or through the actions of the parasite, the host chooses to continue, eject an egg (hoping to eject the parasite) or abandon the nest. Once the eggs have hatched the game then falls to the parasite chick versus the host. The chick chooses to destroy or eject a number of eggs. The final decision is made by the host, choosing whether to raise or abandon the chicks that are in the nest. We consider various natural parameters and probabilities which influence these decisions. We then use this model to look at real-world situations of the interactions of the Reed Warbler and two different parasites, the Common Cuckoo and the Brown-Headed Cowbird. These two parasites have different methods in the way that they parasitize the nests of their hosts. The hosts in turn have a different reaction to these parasites. Arne Jochens 1 , Amke Caliebe 2 , Uwe Roesler 1 , Michael Krawczak 215 Mathematical Seminar, University of Kiel, Germany 16 Institute of Medical Informatics and Statistics, University of Kiel, Germany Keywords: Stepwise mutation model, microsatellite, recursion equation, temporal behaviour We consider the stepwise mutation model which occurs, e.g., in microsatellite loci. Let X(t,i) denote the allelic state of individual i at time t. We compute expectation, variance and covariance of X(t,i), i=1,,,N, and provide a recursion equation for P(X(t,i)=z). Because the variance of X(t,i) goes to infinity as t grows, for the description of the temporal behaviour, we regard the scaled process X(t,i)-X(t,1). The results furnish a better understanding of the behaviour of the stepwise mutation model and may in future be used to derive tests for neutrality under this model. Paul O'Reilly 1 , Ewan Birney 2 , David Balding 117 Statistical Genetics, Department of Epidemiology and Public Health, Imperial, College London, UK 18 European Bioinformatics Institute, EMBL, Cambridge, UK Keywords: Positive selection, Recombination rate, LD, Genome-wide, Natural Selection In recent years efforts to develop population genetics methods that estimate rates of recombination and levels of natural selection in the human genome have intensified. However, since the two processes have an intimately related impact on genetic variation their inference is vulnerable to confounding. Genomic regions subject to recent selection are likely to have a relatively recent common ancestor and consequently less opportunity for historical recombinations that are detectable in contemporary populations. Here we show that selection can reduce the population-based recombination rate estimate substantially. In genome-wide studies for detecting selection we observe a tendency to highlight loci that are subject to low levels of recombination. We find that the outlier approach commonly adopted in such studies may have low power unless variable recombination is accounted for. We introduce a new genome-wide method for detecting selection that exploits the sensitivity to recent selection of methods for estimating recombination rates, while accounting for variable recombination using pedigree data. Through simulations we demonstrate the high power of the Ped/Pop approach to discriminate between neutral and adaptive evolution, particularly in the context of choosing outliers from a genome-wide distribution. Although methods have been developed showing good power to detect selection ,in action', the corresponding window of opportunity is small. In contrast, the power of the Ped/Pop method is maintained for many generations after the fixation of an advantageous variant Sarah Griffiths 1 , Frank Dudbridge 120 MRC Biostatistics Unit, Cambridge, UK Keywords: Genetic association, multimarker tag, haplotype, likelihood analysis In association studies it is generally too expensive to genotype all variants in all subjects. We can exploit linkage disequilibrium between SNPs to select a subset that captures the variation in a training data set obtained either through direct resequencing or a public resource such as the HapMap. These ,tag SNPs' are then genotyped in the whole sample. Multimarker tagging is a more aggressive adaptation of pairwise tagging that allows for combinations of two or more tag SNPs to predict an untyped SNP. Here we describe a new method for directly testing the association of an untyped SNP using a multimarker tag. Previously, other investigators have suggested testing a specific tag haplotype, or performing a weighted analysis using weights derived from the training data. However these approaches do not properly account for the imperfect correlation between the tag haplotype and the untyped SNP. Here we describe a straightforward approach to testing untyped SNPs using a missing-data likelihood analysis, including the tag markers as nuisance parameters. The training data is stacked on top of the main body of genotype data so there is information on how the tag markers predict the genotype of the untyped SNP. The uncertainty in this prediction is automatically taken into account in the likelihood analysis. This approach yields more power and also a more accurate prediction of the odds ratio of the untyped SNP. Anke Schulz 1 , Christine Fischer 2 , Jenny Chang-Claude 1 , Lars Beckmann 121 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany 22 Institute of Human Genetics, University of Heidelberg, Germany Keywords: Haplotype, haplotype sharing, entropy, Mantel statistics, marker selection We previously introduced a new method to map genes involved in complex diseases, using haplotype sharing-based Mantel statistics to correlate genetic and phenotypic similarity. Although the Mantel statistic is powerful in narrowing down candidate regions, the precise localization of a gene is hampered in genomic regions where linkage disequilibrium is so high that neighboring markers are found to be significant at similar magnitude and we are not able to discriminate between them. Here, we present a new approach to localize susceptibility genes by combining haplotype sharing-based Mantel statistics with an iterative entropy-based marker selection algorithm. For each marker at which the Mantel statistic is evaluated, the algorithm selects a subset of surrounding markers. The subset is chosen to maximize multilocus linkage disequilibrium, which is measured by the normalized entropy difference introduced by Nothnagel et al. (2002). We evaluated the algorithm with respect to type I error and power. Its ability to localize the disease variant was compared to the localization (i) without marker selection and (ii) considering haplotype block structure. Case-control samples were simulated from a set of 18 haplotypes, consisting of 15 SNPs in two haplotype blocks. The new algorithm gave correct type I error and yielded similar power to detect the disease locus compared to the alternative approaches. The neighboring markers were clearly less often significant than the causal locus, and also less often significant compared to the alternative approaches. Thus the new algorithm improved the precision of the localization of susceptibility genes. Mark M. Iles 123 Section of Epidemiology and Biostatistics, LIMM, University of Leeds, UK Keywords: tSNP, tagging, association, HapMap Tagging SNPs (tSNPs) are commonly used to capture genetic diversity cost-effectively. However, it is important that the efficacy of tSNPs is correctly estimated, otherwise coverage may be insufficient. If the pilot sample from which tSNPs are chosen is too small or the initial marker map too sparse, tSNP efficacy may be overestimated. An existing estimation method based on bootstrapping goes some way to correct for insufficient sample size and overfitting, but does not completely solve the problem. We describe a novel method, based on exclusion of haplotypes, that improves on the bootstrap approach. Using simulated data, the extent of the sample size problem is investigated and the performance of the bootstrap and the novel method are compared. We incorporate an existing method adjusting for marker density by ,SNP-dropping'. We find that insufficient sample size can cause large overestimates in tSNP efficacy, even with as many as 100 individuals, and the problem worsens as the region studied increases in size. Both the bootstrap and novel method correct much of this overestimate, with our novel method consistently outperforming the bootstrap method. We conclude that a combination of insufficient sample size and overfitting may lead to overestimation of tSNP efficacy and underpowering of studies based on tSNPs. Our novel approach corrects for much of this bias and is superior to the previous method. Sample sizes larger than previously suggested may still be required for accurate estimation of tSNP efficacy. This has obvious ramifications for the selection of tSNPs from HapMap data. Claudio Verzilli 1 , Juliet Chapman 1 , Aroon Hingorani 2 , Juan Pablo-Casas 1 , Tina Shah 2 , Liam Smeeth 1 , John Whittaker 124 Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, UK 25 Division of Medicine, University College London, UK Keywords: Meta-analysis, Genetic association studies We present a Bayesian hierarchical model for the meta-analysis of candidate gene studies with a continuous outcome. Such studies often report results from association tests for different, possibly study-specific and non-overlapping markers (typically SNPs) in the same genetic region. Meta analyses of the results at each marker in isolation are seldom appropriate as they ignore the correlation that may exist between markers due to linkage disequlibrium (LD) and cannot assess the relative importance of variants at each marker. Also such marker-wise meta analyses are restricted to only those studies that have typed the marker in question, with a potential loss of power. A better strategy is one which incorporates information about the LD between markers so that any combined estimate of the effect of each variant is corrected for the effect of other variants, as in multiple regression. Here we develop a Bayesian hierarchical linear regression that models the observed genotype group means and uses pairwise LD measurements between markers as prior information to make posterior inference on adjusted effects. The approach is applied to the meta analysis of 24 studies assessing the effect of 7 variants in the C-reactive protein (CRP) gene region on plasma CRP levels, an inflammatory biomarker shown in observational studies to be positively associated with cardiovascular disease. Cathryn M. Lewis 1 , Christopher G. Mathew 1 , Theresa M. Marteau 226 Dept. of Medical and Molecular Genetics, King's College London, UK 27 Department of Psychology, King's College London, UK Keywords: Risk, genetics, CARD15, smoking, model Recently progress has been made in identifying mutations that confer susceptibility to complex diseases, with the potential to use these mutations in determining disease risk. We developed methods to estimate disease risk based on genotype relative risks (for a gene G), exposure to an environmental factor (E), and family history (with recurrence risk ,R for a relative of type R). ,R must be partitioned into the risk due to G (which is modelled independently) and the residual risk. The risk model was then applied to Crohn's disease (CD), a severe gastrointestinal disease for which smoking increases disease risk approximately 2-fold, and mutations in CARD15 confer increased risks of 2.25 (for carriers of a single mutation) and 9.3 (for carriers of two mutations). CARD15 accounts for only a small proportion of the genetic component of CD, with a gene-specific ,S, CARD15 of 1.16, from a total sibling relative risk of ,S= 27. CD risks were estimated for high-risk individuals who are siblings of a CD case, and who also smoke. The CD risk to such individuals who carry two CARD15 mutations is approximately 0.34, and for those carrying a single CARD15 mutation the risk is 0.08, compared to a population prevalence of approximately 0.001. These results imply that complex disease genes may be valuable in estimating with greater precision than has hitherto been possible disease risks in specific, easily identified subgroups of the population with a view to prevention. Yurii Aulchenko 128 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Compression, information, bzip2, genome-wide SNP data, statistical genetics With advances in molecular technology, studies accessing millions of genetic polymorphisms in thousands of study subjects will soon become common. Such studies generate large amounts of data, whose effective storage and management is a challenge to the modern statistical genetics. Standard file compression utilities, such as Zip, Gzip and Bzip2, may be helpful to minimise the storage requirements. Less obvious is the fact that the data compression techniques may be also used in the analysis of genetic data. It is known that the efficiency of a particular compression algorithm depends on the probability structure of the data. In this work, we compared different standard and customised tools using the data from human HapMap project. Secondly, we investigate the potential uses of data compression techniques for the analysis of linkage, association and linkage disequilibrium Suzanne Leal 1 , Bingshan Li 129 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, USA Keywords: Consanguineous pedigrees, missing genotype data Missing genotype data can increase false-positive evidence for linkage when either parametric or nonparametric analysis is carried out ignoring intermarker linkage disequilibrium (LD). Previously it was demonstrated by Huang et al (2005) that no bias occurs in this situation for affected sib-pairs with unrelated parents when either both parents are genotyped or genotype data is available for two additional unaffected siblings when parental genotypes are missing. However, this is not the case for consanguineous pedigrees, where missing genotype data for any pedigree member within a consanguinity loop can increase false-positive evidence of linkage. The false-positive evidence for linkage is further increased when cryptic consanguinity is present. The amount of false-positive evidence for linkage is highly dependent on which family members are genotyped. When parental genotype data is available, the false-positive evidence for linkage is usually not as strong as when parental genotype data is unavailable. Which family members will aid in the reduction of false-positive evidence of linkage is highly dependent on which other family members are genotyped. For a pedigree with an affected proband whose first-cousin parents have been genotyped, further reduction in the false-positive evidence of linkage can be obtained by including genotype data from additional affected siblings of the proband or genotype data from the proband's sibling-grandparents. When parental genotypes are not available, false-positive evidence for linkage can be reduced by including in the analysis genotype data from either unaffected siblings of the proband or the proband's married-in-grandparents. Najaf Amin 1 , Yurii Aulchenko 130 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Genomic Control, pedigree structure, quantitative traits The Genomic Control (GC) method was originally developed to control for population stratification and cryptic relatedness in association studies. This method assumes that the effect of population substructure on the test statistics is essentially constant across the genome, and therefore unassociated markers can be used to estimate the effect of confounding onto the test statistic. The properties of GC method were extensively investigated for different stratification scenarios, and compared to alternative methods, such as the transmission-disequilibrium test. The potential of this method to correct not for occasional cryptic relations, but for regular pedigree structure, however, was not investigated before. In this work we investigate the potential of the GC method for pedigree-based association analysis of quantitative traits. The power and type one error of the method was compared to standard methods, such as the measured genotype (MG) approach and quantitative trait transmission-disequilibrium test. In human pedigrees, with trait heritability varying from 30 to 80%, the power of MG and GC approach was always higher than that of TDT. GC had correct type 1 error and its power was close to that of MG under moderate heritability (30%), but decreased with higher heritability. William Astle 1 , Chris Holmes 2 , David Balding 131 Department of Epidemiology and Public Health, Imperial College London, UK 32 Department of Statistics, University of Oxford, UK Keywords: Population structure, association studies, genetic epidemiology, statistical genetics In the analysis of population association studies, Genomic Control (Devlin & Roeder, 1999) (GC) adjusts the Armitage test statistic to correct the type I error for the effects of population substructure, but its power is often sub-optimal. Turbo Genomic Control (TGC) generalises GC to incorporate co-variation of relatedness and phenotype, retaining control over type I error while improving power. TGC is similar to the method of Yu et al. (2006), but we extend it to binary (case-control) in addition to quantitative phenotypes, we implement improved estimation of relatedness coefficients, and we derive an explicit statistic that generalizes the Armitage test statistic and is fast to compute. TGC also has similarities to EIGENSTRAT (Price et al., 2006) which is a new method based on principle components analysis. The problems of population structure(Clayton et al., 2005) and cryptic relatedness (Voight & Pritchard, 2005) are essentially the same: if patterns of shared ancestry differ between cases and controls, whether distant (coancestry) or recent (cryptic relatedness), false positives can arise and power can be diminished. With large numbers of widely-spaced genetic markers, coancestry can now be measured accurately for each pair of individuals via patterns of allele-sharing. Instead of modelling subpopulations, we work instead with a coancestry coefficient for each pair of individuals in the study. We explain the relationships between TGC, GC and EIGENSTRAT. We present simulation studies and real data analyses to illustrate the power advantage of TGC in a range of scenarios incorporating both substructure and cryptic relatedness. References Clayton, D. G.et al. (2005) Population structure, differential bias and genomic control in a large-scale case-control association study. Nature Genetics37(11) November 2005. Devlin, B. & Roeder, K. (1999) Genomic control for association studies. Biometics55(4) December 1999. Price, A. L.et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics38(8) (August 2006). Voight, B. J. & Pritchard, J. K. (2005) Confounding from cryptic relatedness in case-control association studies. Public Library of Science Genetics1(3) September 2005. Yu, J.et al. (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics38(2) February 2006. Hervé Perdry 1 , Marie-Claude Babron 1 , Françoise Clerget-Darpoux 133 INSERM U535 and Univ. Paris Sud, UMR-S 535, Villejuif, France Keywords: Modifier genes, case-parents trios, ordered transmission disequilibrium test A modifying locus is a polymorphic locus, distinct from the disease locus, which leads to differences in the disease phenotype, either by modifying the penetrance of the disease allele, or by modifying the expression of the disease. The effect of such a locus is a clinical heterogeneity that can be reflected by the values of an appropriate covariate, such as the age of onset, or the severity of the disease. We designed the Ordered Transmission Disequilibrium Test (OTDT) to test for a relation between the clinical heterogeneity, expressed by the covariate, and marker genotypes of a candidate gene. The method applies to trio families with one affected child and his parents. Each family member is genotyped at a bi-allelic marker M of a candidate gene. To each of the families is associated a covariate value; the families are ordered on the values of this covariate. As the TDT (Spielman et al. 1993), the OTDT is based on the observation of the transmission rate T of a given allele at M. The OTDT aims to find a critical value of the covariate which separates the sample of families in two subsamples in which the transmission rates are significantly different. We investigate the power of the method by simulations under various genetic models and covariate distributions. Acknowledgments H Perdry is funded by ARSEP. Pascal Croiseau 1 , Heather Cordell 2 , Emmanuelle Génin 134 INSERM U535 and University Paris Sud, UMR-S535, Villejuif, France 35 Institute of Human Genetics, Newcastle University, UK Keywords: Association, missing data, conditionnal logistic regression Missing data is an important problem in association studies. Several methods used to test for association need that individuals be genotyped at the full set of markers. Individuals with missing data need to be excluded from the analysis. This could involve an important decrease in sample size and a loss of information. If the disease susceptibility locus (DSL) is poorly typed, it is also possible that a marker in linkage disequilibrium gives a stronger association signal than the DSL. One may then falsely conclude that the marker is more likely to be the DSL. We recently developed a Multiple Imputation method to infer missing data on case-parent trios Starting from the observed data, a few number of complete data sets are generated by Markov-Chain Monte Carlo approach. These complete datasets are analysed using standard statistical package and the results are combined as described in Little & Rubin (2002). Here we report the results of simulations performed to examine, for different patterns of missing data, how often the true DSL gives the highest association score among different loci in LD. We found that multiple imputation usually correctly detect the DSL site even if the percentage of missing data is high. This is not the case for the naďve approach that consists in discarding trios with missing data. In conclusion, Multiple imputation presents the advantage of being easy to use and flexible and is therefore a promising tool in the search for DSL involved in complex diseases. Salma Kotti 1 , Heike Bickeböller 2 , Françoise Clerget-Darpoux 136 University Paris Sud, UMR-S535, Villejuif, France 37 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany Keywords: Genotype relative risk, internal controls, Family based analyses Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRRs. We will analytically derive the GRR estimators for the 1:1 and 1:3 matching and will present the results at the meeting. Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRR. We will analytically derive the GRR estimator for the 1:1 and 1:3 matching and will present the results at the meeting. Luigi Palla 1 , David Siegmund 239 Department of Mathematics,Free University Amsterdam, The Netherlands 40 Department of Statistics, Stanford University, California, USA Keywords: TDT, assortative mating, inbreeding, statistical power A substantial amount of Assortative Mating (AM) is often recorded on physical and psychological, dichotomous as well as quantitative traits that are supposed to have a multifactorial genetic component. In particular AM has the effect of increasing the genetic variance, even more than inbreeding because it acts across loci beside within loci, when the trait has a multifactorial origin. Under the assumption of a polygenic model for AM dating back to Wright (1921) and refined by Crow and Felsenstein (1968,1982), the effect of assortative mating on the power to detect genetic association in the Transmission Disequilibrium Test (TDT) is explored as parameters, such as the effective number of genes and the allelic frequency vary. The power is reflected by the non centrality parameter of the TDT and is expressed as a function of the number of trios, the relative risk of the heterozygous genotype and the allele frequency (Siegmund and Yakir, 2007). The noncentrality parameter of the relevant score statistic is updated considering the effect of AM which is expressed in terms of an ,effective' inbreeding coefficient. In particular, for dichotomous traits it is apparent that the higher the number of genes involved in the trait, the lower the loss in power due to AM. Finally an attempt is made to extend this relation to the Q-TDT (Rabinowitz, 1997), which involves considering the effect of AM also on the phenotypic variance of the trait of interest, under the assumption that AM affects only its additive genetic component. References Crow, & Felsenstein, (1968). The effect of assortative mating on the genetic composition of a population. Eugen.Quart.15, 87,97. Rabinowitz,, 1997. A Transmission Disequilibrium Test for Quantitative Trait Loci. Human Heredity47, 342,350. Siegmund, & Yakir, (2007) Statistics of gene mapping, Springer. Wright, (1921). System of mating.III. Assortative mating based on somatic resemblance. Genetics6, 144,161. Jérémie Nsengimana 1 , Ben D Brown 2 , Alistair S Hall 2 , Jenny H Barrett 141 Leeds Institute of Molecular Medicine, University of Leeds, UK 42 Leeds Institute for Genetics, Health and Therapeutics, University of Leeds, UK Keywords: Inflammatory genes, haplotype, coronary artery disease Genetic Risk of Acute Coronary Events (GRACE) is an initiative to collect cases of coronary artery disease (CAD) and their unaffected siblings in the UK and to use them to map genetic variants increasing disease risk. The aim of the present study was to test the association between CAD and 51 single nucleotide polymorphisms (SNPs) and their haplotypes from 35 inflammatory genes. Genotype data were available for 1154 persons affected before age 66 (including 48% before age 50) and their 1545 unaffected siblings (891 discordant families). Each SNP was tested for association to CAD, and haplotypes within genes or gene clusters were tested using FBAT (Rabinowitz & Laird, 2000). For the most significant results, genetic effect size was estimated using conditional logistic regression (CLR) within STATA adjusting for other risk factors. Haplotypes were assigned using HAPLORE (Zhang et al., 2005), which considers all parental mating types consistent with offspring genotypes and assigns them a probability of occurence. This probability was used in CLR to weight the haplotypes. In the single SNP analysis, several SNPs showed some evidence for association, including one SNP in the interleukin-1A gene. Analysing haplotypes in the interleukin-1 gene cluster, a common 3-SNP haplotype was found to increase the risk of CAD (P = 0.009). In an additive genetic model adjusting for covariates the odds ratio (OR) for this haplotype is 1.56 (95% CI: 1.16-2.10, p = 0.004) for early-onset CAD (before age 50). This study illustrates the utility of haplotype analysis in family-based association studies to investigate candidate genes. References Rabinowitz, D. & Laird, N. M. (2000) Hum Hered50, 211,223. Zhang, K., Sun, F. & Zhao, H. (2005) Bioinformatics21, 90,103. Andrea Foulkes 1 , Recai Yucel 1 , Xiaohong Li 143 Division of Biostatistics, University of Massachusetts, USA Keywords: Haploytpe, high-dimensional, mixed modeling The explosion of molecular level information coupled with large epidemiological studies presents an exciting opportunity to uncover the genetic underpinnings of complex diseases; however, several analytical challenges remain to be addressed. Characterizing the components to complex diseases inevitably requires consideration of synergies across multiple genetic loci and environmental and demographic factors. In addition, it is critical to capture information on allelic phase, that is whether alleles within a gene are in cis (on the same chromosome) or in trans (on different chromosomes.) In associations studies of unrelated individuals, this alignment of alleles within a chromosomal copy is generally not observed. We address the potential ambiguity in allelic phase in this high dimensional data setting using mixed effects models. Both a semi-parametric and fully likelihood-based approach to estimation are considered to account for missingness in cluster identifiers. In the first case, we apply a multiple imputation procedure coupled with a first stage expectation maximization algorithm for parameter estimation. A bootstrap approach is employed to assess sensitivity to variability induced by parameter estimation. Secondly, a fully likelihood-based approach using an expectation conditional maximization algorithm is described. Notably, these models allow for characterizing high-order gene-gene interactions while providing a flexible statistical framework to account for the confounding or mediating role of person specific covariates. The proposed method is applied to data arising from a cohort of human immunodeficiency virus type-1 (HIV-1) infected individuals at risk for therapy associated dyslipidemia. Simulation studies demonstrate reasonable power and control of family-wise type 1 error rates. Vivien Marquard 1 , Lars Beckmann 1 , Jenny Chang-Claude 144 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Genotyping errors, type I error, haplotype-based association methods It has been shown in several simulation studies that genotyping errors may have a great impact on the type I error of statistical methods used in genetic association analysis of complex diseases. Our aim was to investigate type I error rates in a case-control study, when differential and non-differential genotyping errors were introduced in realistic scenarios. We simulated case-control data sets, where individual genotypes were drawn from a haplotype distribution of 18 haplotypes with 15 markers in the APM1 gene. Genotyping errors were introduced following the unrestricted and symmetric with 0 edges error models described by Heid et al. (2006). In six scenarios, errors resulted from changes of one allele to another with predefined probabilities of 1%, 2.5% or 10%, respectively. A multiple number of errors per haplotype was possible and could vary between 0 and 15, the number of markers investigated. We examined three association methods: Mantel statistics using haplotype-sharing; a haplotype-specific score test; and Armitage trend test for single markers. The type I error rates were not influenced for any of all the three methods for a genotyping error rate of less than 1%. For higher error rates and differential errors, the type I error of the Mantel statistic was only slightly and of the Armitage trend test moderately increased. The type I error rates of the score test were highly increased. The type I error rates were correct for all three methods for non-differential errors. Further investigations will be carried out with different frequencies of differential error rates and focus on power. Arne Neumann 1 , Dörthe Malzahn 1 , Martina Müller 2 , Heike Bickeböller 145 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany 46 GSF-National Research Center for Environment and Health, Neuherberg & IBE-Institute of Epidemiology, Ludwig-Maximilians University München, Germany Keywords: Interaction, longitudinal, nonparametric Longitudinal data show the time dependent course of phenotypic traits. In this contribution, we consider longitudinal cohort studies and investigate the association between two candidate genes and a dependent quantitative longitudinal phenotype. The set-up defines a factorial design which allows us to test simultaneously for the overall gene effect of the loci as well as for possible gene-gene and gene time interaction. The latter would induce genetically based time-profile differences in the longitudinal phenotype. We adopt a non-parametric statistical test to genetic epidemiological cohort studies and investigate its performance by simulation studies. The statistical test was originally developed for longitudinal clinical studies (Brunner, Munzel, Puri, 1999 J Multivariate Anal 70:286-317). It is non-parametric in the sense that no assumptions are made about the underlying distribution of the quantitative phenotype. Longitudinal observations belonging to the same individual can be arbitrarily dependent on one another for the different time points whereas trait observations of different individuals are independent. The two loci are assumed to be statistically independent. Our simulations show that the nonparametric test is comparable with ANOVA in terms of power of detecting gene-gene and gene-time interaction in an ANOVA favourable setting. Rebecca Hein 1 , Lars Beckmann 1 , Jenny Chang-Claude 147 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Indirect association studies, interaction effects, linkage disequilibrium, marker allele frequency Association studies accounting for gene-environment interactions (GxE) may be useful for detecting genetic effects and identifying important environmental effect modifiers. Current technology facilitates very dense marker spacing in genetic association studies; however, the true disease variant(s) may not be genotyped. In this situation, an association between a gene and a phenotype may still be detectable, using genetic markers associated with the true disease variant(s) (indirect association). Zondervan and Cardon [2004] showed that the odds ratios (OR) of markers which are associated with the disease variant depend highly on the linkage disequilibrium (LD) between the variant and the markers, and whether the allele frequencies match and thereby influence the sample size needed to detect genetic association. We examined the influence of LD and allele frequencies on the sample size needed to detect GxE in indirect association studies, and provide tables for sample size estimation. For discordant allele frequencies and incomplete LD, sample sizes can be unfeasibly large. The influence of both factors is stronger for disease loci with small rather than moderate to high disease allele frequencies. A decline in D' of e.g. 5% has less impact on sample size than increasing the difference in allele frequencies by the same percentage. Assuming 80% power, large interaction effects can be detected using smaller sample sizes than those needed for the detection of main effects. The detection of interaction effects involving rare alleles may not be possible. Focussing only on marker density can be a limited strategy in indirect association studies for GxE. Cyril Dalmasso 1 , Emmanuelle Génin 2 , Catherine Bourgain 2 , Philippe Broët 148 JE 2492 , Univ. Paris-Sud, France 49 INSERM UMR-S 535 and University Paris Sud, Villejuif, France Keywords: Linkage analysis, Multiple testing, False Discovery Rate, Mixture model In the context of genome-wide linkage analyses, where a large number of statistical tests are simultaneously performed, the False Discovery Rate (FDR) that is defined as the expected proportion of false discoveries among all discoveries is nowadays widely used for taking into account the multiple testing problem. Other related criteria have been considered such as the local False Discovery Rate (lFDR) that is a variant of the FDR giving to each test its own measure of significance. The lFDR is defined as the posterior probability that a null hypothesis is true. Most of the proposed methods for estimating the lFDR or the FDR rely on distributional assumption under the null hypothesis. However, in observational studies, the empirical null distribution may be very different from the theoretical one. In this work, we propose a mixture model based approach that provides estimates of the lFDR and the FDR in the context of large-scale variance component linkage analyses. In particular, this approach allows estimating the empirical null distribution, this latter being a key quantity for any simultaneous inference procedure. The proposed method is applied on a real dataset. Arief Gusnanto 1 , Frank Dudbridge 150 MRC Biostatistics Unit, Cambridge UK Keywords: Significance, genome-wide, association, permutation, multiplicity Genome-wide association scans have introduced statistical challenges, mainly in the multiplicity of thousands of tests. The question of what constitutes a significant finding remains somewhat unresolved. Permutation testing is very time-consuming, whereas Bayesian arguments struggle to distinguish direct from indirect association. It seems attractive to summarise the multiplicity in a simple form that allows users to avoid time-consuming permutations. A standard significance level would facilitate reporting of results and reduce the need for permutation tests. This is potentially important because current scans do not have full coverage of the whole genome, and yet, the implicit multiplicity is genome-wide. We discuss some proposed summaries, with reference to the empirical null distribution of the multiple tests, approximated through a large number of random permutations. Using genome-wide data from the Wellcome Trust Case-Control Consortium, we use a sub-sampling approach with increasing density to estimate the nominal p-value to obtain family-wise significance of 5%. The results indicate that the significance level is converging to about 1e-7 as the marker spacing becomes infinitely dense. We considered the concept of an effective number of independent tests, and showed that when used in a Bonferroni correction, the number varies with the overall significance level, but is roughly constant in the region of interest. We compared several estimators of the effective number of tests, and showed that in the region of significance of interest, Patterson's eigenvalue based estimator gives approximately the right family-wise error rate. Michael Nothnagel 1 , Amke Caliebe 1 , Michael Krawczak 151 Institute of Medical Informatics and Statistics, University Clinic Schleswig-Holstein, University of Kiel, Germany Keywords: Association scans, Bayesian framework, posterior odds, genetic risk, multiplicative model Whole-genome association scans have been suggested to be a cost-efficient way to survey genetic variation and to map genetic disease factors. We used a Bayesian framework to investigate the posterior odds of a genuine association under multiplicative disease models. We demonstrate that the p value alone is not a sufficient means to evaluate the findings in association studies. We suggest that likelihood ratios should accompany p values in association reports. We argue, that, given the reported results of whole-genome scans, more associations should have been successfully replicated if the consistently made assumptions about considerable genetic risks were correct. We conclude that it is very likely that the vast majority of relative genetic risks are only of the order of 1.2 or lower. Clive Hoggart 1 , Maria De Iorio 1 , John Whittakker 2 , David Balding 152 Department of Epidemiology and Public Health, Imperial College London, UK 53 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: Genome-wide association analyses, shrinkage priors, Lasso Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants of small effect, which is a plausible scenario for many complex diseases. Moreover, many simulation studies assume a single causal variant and so more complex realities are ignored. Analysing large numbers of variants simultaneously is now becoming feasible, thanks to developments in Bayesian stochastic search methods. We pose the problem of SNP selection as variable selection in a regression model. In contrast to single SNP tests this approach simultaneously models the effect of all SNPs. SNPs are selected by a Bayesian interpretation of the lasso (Tibshirani, 1996); the maximum a posterior (MAP) estimate of the regression coefficients, which have been given independent, double exponential prior distributions. The double exponential distribution is an example of a shrinkage prior, MAP estimates with shrinkage priors can be zero, thus all SNPs with non zero regression coefficients are selected. In addition to the commonly-used double exponential (Laplace) prior, we also implement the normal exponential gamma prior distribution. We show that use of the Laplace prior improves SNP selection in comparison with single -SNP tests, and that the normal exponential gamma prior leads to a further improvement. Our method is fast and can handle very large numbers of SNPs: we demonstrate its performance using both simulated and real genome-wide data sets with 500 K SNPs, which can be analysed in 2 hours on a desktop workstation. Mickael Guedj 1,2 , Jerome Wojcik 2 , Gregory Nuel 154 Laboratoire Statistique et Génome, Université d'Evry, Evry France 55 Serono Pharmaceutical Research Institute, Plan-les-Ouates, Switzerland Keywords: Local Replication, Local Score, Association In gene-mapping, replication of initial findings has been put forwards as the approach of choice for filtering false-positives from true signals for underlying loci. In practice, such replications are however too poorly observed. Besides the statistical and technical-related factors (lack of power, multiple-testing, stratification, quality control,) inconsistent conclusions obtained from independent populations might result from real biological differences. In particular, the high degree of variation in the strength of LD among populations of different origins is a major challenge to the discovery of genes. Seeking for Local Replications (defined as the presence of a signal of association in a same genomic region among populations) instead of strict replications (same locus, same risk allele) may lead to more reliable results. Recently, a multi-markers approach based on the Local Score statistic has been proposed as a simple and efficient way to select candidate genomic regions at the first stage of genome-wide association studies. Here we propose an extension of this approach adapted to replicated association studies. Based on simulations, this method appears promising. In particular it outperforms classical simple-marker strategies to detect modest-effect genes. Additionally it constitutes, to our knowledge, a first framework dedicated to the detection of such Local Replications. Juliet Chapman 1 , Claudio Verzilli 1 , John Whittaker 156 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: FDR, Association studies, Bayesian model selection As genomewide association studies become commonplace there is debate as to how such studies might be analysed and what we might hope to gain from the data. It is clear that standard single locus approaches are limited in that they do not adjust for the effects of other loci and problematic since it is not obvious how to adjust for multiple comparisons. False discovery rates have been suggested, but it is unclear how well these will cope with highly correlated genetic data. We consider the validity of standard false discovery rates in large scale association studies. We also show that a Bayesian procedure has advantages in detecting causal loci amongst a large number of dependant SNPs and investigate properties of a Bayesian FDR. Peter Kraft 157 Harvard School of Public Health, Boston USA Keywords: Gene-environment interaction, genome-wide association scans Appropriately analyzed two-stage designs,where a subset of available subjects are genotyped on a genome-wide panel of markers at the first stage and then a much smaller subset of the most promising markers are genotyped on the remaining subjects,can have nearly as much power as a single-stage study where all subjects are genotyped on the genome-wide panel yet can be much less expensive. Typically, the "most promising" markers are selected based on evidence for a marginal association between genotypes and disease. Subsequently, the few markers found to be associated with disease at the end of the second stage are interrogated for evidence of gene-environment interaction, mainly to understand their impact on disease etiology and public health impact. However, this approach may miss variants which have a sizeable effect restricted to one exposure stratum and therefore only a modest marginal effect. We have proposed to use information on the joint effects of genes and a discrete list of environmental exposures at the initial screening stage to select promising markers for the second stage [Kraft et al Hum Hered 2007]. This approach optimizes power to detect variants that have a sizeable marginal effect and variants that have a small marginal effect but a sizeable effect in a stratum defined by an environmental exposure. As an example, I discuss a proposed genome-wide association scan for Type II diabetes susceptibility variants based in several large nested case-control studies. Beate Glaser 1 , Peter Holmans 158 Biostatistics and Bioinformatics Unit, Cardiff University, School of Medicine, Heath Park, Cardiff, UK Keywords: Combined case-control and trios analysis, Power, False-positive rate, Simulation, Association studies The statistical power of genetic association studies can be enhanced by combining the analysis of case-control with parent-offspring trio samples. Various combined analysis techniques have been recently developed; as yet, there have been no comparisons of their power. This work was performed with the aim of identifying the most powerful method among available combined techniques including test statistics developed by Kazeem and Farrall (2005), Nagelkerke and colleagues (2004) and Dudbridge (2006), as well as a simple combination of ,2-statistics from single samples. Simulation studies were performed to investigate their power under different additive, multiplicative, dominant and recessive disease models. False-positive rates were determined by studying the type I error rates under null models including models with unequal allele frequencies between the single case-control and trios samples. We identified three techniques with equivalent power and false-positive rates, which included modifications of the three main approaches: 1) the unmodified combined Odds ratio estimate by Kazeem & Farrall (2005), 2) a modified approach of the combined risk ratio estimate by Nagelkerke & colleagues (2004) and 3) a modified technique for a combined risk ratio estimate by Dudbridge (2006). Our work highlights the importance of studies investigating test performance criteria of novel methods, as they will help users to select the optimal approach within a range of available analysis techniques. David Almorza 1 , M.V. Kandus 2 , Juan Carlos Salerno 2 , Rafael Boggio 359 Facultad de Ciencias del Trabajo, University of Cádiz, Spain 60 Instituto de Genética IGEAF, Buenos Aires, Argentina 61 Universidad Nacional de La Plata, Buenos Aires, Argentina Keywords: Principal component analysis, maize, ear weight, inbred lines The objective of this work was to evaluate the relationship among different traits of the ear of maize inbred lines and to group genotypes according to its performance. Ten inbred lines developed at IGEAF (INTA Castelar) and five public inbred lines as checks were used. A field trial was carried out in Castelar, Buenos Aires (34° 36' S , 58° 39' W) using a complete randomize design with three replications. At harvest, individual weight (P.E.), diameter (D.E.), row number (N.H.) and length (L.E.) of the ear were assessed. A principal component analysis, PCA, (Infostat 2005) was used, and the variability of the data was depicted with a biplot. Principal components 1 and 2 (CP1 and CP2) explained 90% of the data variability. CP1 was correlated with P.E., L.E. and D.E., meanwhile CP2 was correlated with N.H. We found that individual weight (P.E.) was more correlated with diameter of the ear (D.E.) than with length (L.E). Five groups of inbred lines were distinguished: with high P.E. and mean N.H. (04-70, 04-73, 04-101 and MO17), with high P.E. but less N.H. (04-61 and B14), with mean P.E. and N.H. (B73, 04-123 and 04-96), with high N.H. but less P.E. (LP109, 04-8, 04-91 and 04-76) and with low P.E. and low N.H. (LP521 and 04-104). The use of PCA showed which variables had more incidence in ear weight and how is the correlation among them. Moreover, the different groups found with this analysis allow the evaluation of inbred lines by several traits simultaneously. Sven Knüppel 1 , Anja Bauerfeind 1 , Klaus Rohde 162 Department of Bioinformatics, MDC Berlin, Germany Keywords: Haplotypes, association studies, case-control, nuclear families The area of gene chip technology provides a plethora of phase-unknown SNP genotypes in order to find significant association to some genetic trait. To circumvent possibly low information content of a single SNP one groups successive SNPs and estimates haplotypes. Haplotype estimation, however, may reveal ambiguous haplotype pairs and bias the application of statistical methods. Zaykin et al. (Hum Hered, 53:79-91, 2002) proposed the construction of a design matrix to take this ambiguity into account. Here we present a set of functions written for the Statistical package R, which carries out haplotype estimation on the basis of the EM-algorithm for individuals (case-control) or nuclear families. The construction of a design matrix on basis of estimated haplotypes or haplotype pairs allows application of standard methods for association studies (linear, logistic regression), as well as statistical methods as haplotype sharing statistics and TDT-Test. Applications of these methods to genome-wide association screens will be demonstrated. Manuela Zucknick 1 , Chris Holmes 2 , Sylvia Richardson 163 Department of Epidemiology and Public Health, Imperial College London, UK 64 Department of Statistics, Oxford Center for Gene Function, University of Oxford, UK Keywords: Bayesian, variable selection, MCMC, large p, small n, structured dependence In large-scale genomic applications vast numbers of markers or genes are scanned to find a few candidates which are linked to a particular phenotype. Statistically, this is a variable selection problem in the "large p, small n" situation where many more variables than samples are available. An additional feature is the complex dependence structure which is often observed among the markers/genes due to linkage disequilibrium or their joint involvement in biological processes. Bayesian variable selection methods using indicator variables are well suited to the problem. Binary phenotypes like disease status are common and both Bayesian probit and logistic regression can be applied in this context. We argue that logistic regression models are both easier to tune and to interpret than probit models and implement the approach by Holmes & Held (2006). Because the model space is vast, MCMC methods are used as stochastic search algorithms with the aim to quickly find regions of high posterior probability. In a trade-off between fast-updating but slow-moving single-gene Metropolis-Hastings samplers and computationally expensive full Gibbs sampling, we propose to employ the dependence structure among the genes/markers to help decide which variables to update together. Also, parallel tempering methods are used to aid bold moves and help avoid getting trapped in local optima. Mixing and convergence of the resulting Markov chains are evaluated and compared to standard samplers in both a simulation study and in an application to a gene expression data set. Reference Holmes, C. C. & Held, L. (2006) Bayesian auxiliary variable models for binary and multinomial regression. Bayesian Analysis1, 145,168. Dawn Teare 165 MMGE, University of Sheffield, UK Keywords: CNP, family-based analysis, MCMC Evidence is accumulating that segmental copy number polymorphisms (CNPs) may represent a significant portion of human genetic variation. These highly polymorphic systems require handling as phenotypes rather than co-dominant markers, placing new demands on family-based analyses. We present an integrated approach to meet these challenges in the form of a graphical model, where the underlying discrete CNP phenotype is inferred from the (single or replicate) quantitative measure within the analysis, whilst assuming an allele based system segregating through the pedigree. [source] Score Statistic to Test for Genetic Correlation for Proband-Family DesignANNALS OF HUMAN GENETICS, Issue 4 2005R. El Galta Summary In genetic epidemiological studies informative families are often oversampled to increase the power of a study. For a proband-family design, where relatives of probands are sampled, we derive the score statistic to test for clustering of binary and quantitative traits within families due to genetic factors. The derived score statistic is robust to ascertainment scheme. We considered correlation due to unspecified genetic effects and/or due to sharing alleles identical by descent (IBD) at observed marker locations in a candidate region. A simulation study was carried out to study the distribution of the statistic under the null hypothesis in small data-sets. To illustrate the score statistic, data from 33 families with type 2 diabetes mellitus (DM2) were analyzed. In addition to the binary outcome DM2 we also analyzed the quantitative outcome, body mass index (BMI). For both traits familial aggregation was highly significant. For DM2, also including IBD sharing at marker D3S3681 as a cause of correlation gave an even more significant result, which suggests the presence of a trait gene linked to this marker. We conclude that for the proband-family design the score statistic is a powerful and robust tool for detecting clustering of outcomes. [source] Quantification of the familial contribution to juvenile idiopathic arthritisARTHRITIS & RHEUMATISM, Issue 8 2010Sampath Prahalad Objective We previously demonstrated that there is familial aggregation of juvenile idiopathic arthritis (JIA). Using a large JIA cohort, we sought to identify additional clusters of JIA cases and to calculate robust estimates of the relative risk (RR) of JIA in the siblings and cousins of JIA probands. We also estimated the population attributable risk (PAR) of familial factors in JIA. Methods A probabilistic record-linking analysis was performed by matching the records of 862 patients with JIA with the records of ,7 million individuals in the Utah Population Database (UPDB), a computerized genealogic database. For each patient, 5 control subjects matched for birth year and sex were selected from the UPDB. Specialized software was used to test for familial aggregation of disease, to estimate the magnitude of familial risks, and to identify families at high risk of disease. Results We identified 22 founders who had significantly more descendants with JIA than expected (5,13 descendants; P values ranged from <0.0001 to <0.008). The PAR of familial factors for JIA was ,13%. The RR of JIA in the siblings of patients was significantly increased (11.6, 95% confidence interval [95% CI] 4.9,27.5, P < 2.59 × 10,8). The RR of JIA in first cousins was also increased (5.82, 95% CI 2.5,13.8, P < 6.07 × 10,5). Conclusion We have identified the largest sets of JIA pedigrees described to date. Approximately 13% of cases of JIA can be attributed to familial factors. Siblings and first cousins of probands with JIA have an increased risk of JIA. The observed decline in the magnitude of risk between siblings and cousins suggests that JIA is influenced by shared genetic factors. [source] Shared familial aggregation of susceptibility to autoimmune diseasesARTHRITIS & RHEUMATISM, Issue 9 2009Kari Hemminki MD No abstract is available for this article. [source] Genetics of basal cell carcinomaAUSTRALASIAN JOURNAL OF DERMATOLOGY, Issue 2 2010Sally E De Zwaan ABSTRACT Basal cell carcinoma is the most common human malignancy in populations of European origin, and Australia has the highest incidence of basal cell carcinoma in the world. Great advances in the understanding of the genetics of this cancer have occurred in recent years. Mutations of the patched 1 gene (PTCH1) lead to basal cell carcinoma predisposition in Gorlin syndrome. PTCH1 is part of the hedgehog signalling pathway, and derangements within this pathway are now known to be important in the carcinogenesis of many different cancers including sporadic basal cell carcinoma. The molecular biology of the hedgehog pathway is discussed, and mouse models of basal cell carcinoma based on this pathway are explored. New developments in non-surgical treatment of basal cell carcinoma are based on this knowledge. Other genes of importance to basal cell carcinoma development include the tumour suppressor gene P53 and the melanocortin-1 receptor gene. In addition, we discuss molecules of possible importance such as the glutathione-S-transferases, DNA repair genes, cyclin-dependent kinase inhibitor 2A, Brahma and connexins. Evidence of familial aggregation of this cancer is explored and supports the possibility of genetic predisposition to this common malignancy. [source] | |||||||||||||||||||||||||||||||