Joint modeling of linkage and association: identifying SNPs responsible for a linkage signal

Joint Linkage and Association Analysis Using GENEHUNTER-MODSCORE with an Application to Familial Pancreatic Cancer

INTRODUCTION

Joint linkage and association (JLA) analysis combines two disease gene mapping strategies: linkage information contained in families and association information contained in populations. Such a JLA analysis can increase mapping power, especially when the evidence for both linkage and association is low to moderate. Similarly, an association analysis based on haplotypes instead of single markers can increase mapping power when the association pattern is complex.

METHODS

In this paper, we present an extension to the GENEHUNTER-MODSCORE software package that enables a JLA analysis based on haplotypes and uses information from arbitrary pedigree types and unrelated individuals. Our new JLA method is an extension of the MOD score approach for linkage analysis, which allows the estimation of trait-model and linkage disequilibrium (LD) parameters, i.e., penetrance, disease-allele frequency, and haplotype frequencies. LD is modeled between alleles at a single diallelic disease locus and up to three diallelic test markers. Linkage information is contributed by additional multi-allelic flanking markers. We investigated the statistical properties of our JLA implementation using extensive simulations, and we compared our approach to another commonly used single-marker JLA test. To demonstrate the applicability of our new method in practice, we analyzed pedigree data from the German National Case Collection for Familial Pancreatic Cancer (FaPaCa).

RESULTS

Based on the simulated data, we demonstrated the validity of our JLA-MOD score analysis implementation and identified scenarios in which haplotype-based tests outperformed the single-marker test. The estimated trait-model and LD parameters were in good accordance with the simulated values. Our method outperformed another commonly used JLA single-marker test when the LD pattern was complex. The exploratory analysis of the FaPaCa families led to the identification of a promising genetic region on chromosome 22q13.33, which can serve as a starting point for future mutation analysis and molecular research in pancreatic cancer.

CONCLUSION

Our newly proposed JLA-MOD score method proves to be a valuable gene mapping and characterization tool, especially when either linkage or association information alone provide insufficient power to identify the disease-causing genetic variants.

Population genetics of marmosets in Asian primate research centers and loci associated with epileptic risk revealed by whole-genome sequencing

The common marmoset ( Callithrix jacchus) has emerged as a valuable nonhuman primate model in biomedical research with the recent release of high-quality reference genome assemblies. Epileptic marmosets have been independently reported in two Asian primate research centers. Nevertheless, the population genetics within these primate centers and the specific genetic variants associated with epilepsy in marmosets have not yet been elucidated. Here, we characterized the genetic relationships and risk variants for epilepsy in 41 samples from two epileptic marmoset pedigrees using whole-genome sequencing. We identified 14 558 184 single nucleotide polymorphisms (SNPs) from the 41 samples and found higher chimerism levels in blood samples than in fingernail samples. Genetic analysis showed fourth-degree of relatedness among marmosets at the primate centers. In addition, SNP and copy number variation (CNV) analyses suggested that the WW domain-containing oxidoreductase ( WWOX) and Tyrosine-protein phosphatase nonreceptor type 21 ( PTPN21) genes may be associated with epilepsy in marmosets. Notably, KCTD18-like gene deletion was more common in epileptic marmosets than control marmosets. This study provides valuable population genomic resources for marmosets in two Asian primate centers. Genetic analyses identified a reasonable breeding strategy for genetic diversity maintenance in the two centers, while the case-control study revealed potential risk genes/variants associated with epilepsy in marmosets.

Novel genetic variant associated with globoid cell leukodystrophy in a family of mixed breed dogs

BACKGROUND

Globoid cell leukodystrophy (GCL) is a fatal autosomal recessive disease caused by variants in the galactosylceramidase (GALC) gene. Two dog breed-specific variants are reported.

OBJECTIVES

Characterize the putatively causative GALC variant for GCL in a family of dogs and determine population allele frequency.

ANIMALS

Four related mixed-breed puppies with signs of neurologic disease were evaluated. Subsequently, 33 related dogs were tested for genetic markers for parentage and the identified GALC variant. Additional GALC genotyping was performed on 278 banked samples from various breeds.

METHODS

The 4 affected puppies had neurological exams and necropsies. DNA was isolated from blood samples. Variants in GALC were identified via Sanger sequencing. Parentage testing was performed using short tandem repeat markers. Prevalence of the GALC variant of interest was investigated in other breeds.

RESULTS

GCL was confirmed histopathologically. A novel missense variant in GALC (NC_006590.4:g.58893972G>A) was homozygous in all affected animals (n = 4). A recessive mode of inheritance was confirmed by parentage testing as was variant linkage with the phenotype (LOD = 3.36). Among the related dogs (n = 33), 3 dogs were homozygous and 7 heterozygous. The variant allele was not detected in screening 278 dogs from 5 breeds. The novel variant is either unique to this family or has an extremely low allele frequency in the general population.

CONCLUSIONS AND CLINICAL IMPORTANCE

A novel GALC variant was identified that likely explains GCL in this cohort. The identification of multiple causal variants for GCL in dogs is consistent with findings in humans.

Standing genetic variation affects phenotypic heterogeneity in an SCN5A-mutation founder population with excess sudden cardiac death

BACKGROUND

The Worm Study, ascertained from a multigeneration pedigree segregating a single amino acid deletion in SCN5A (c.4850_4852delTCT, p.(Phe1617del), rs749697698), is characterized by substantial phenotypic heterogeneity and overlap of sudden cardiac death, long-QT syndrome, cardiac conduction disease, Brugada syndrome, and isorhythmic atrioventricular dissociation. Linkage analysis for a synthetic trait derived from these phenotypes identified a single peak (logarithm of the odds [LOD] = 4.52) at the SCN5A/SCN10A/SCN11A locus on chromosome 3.

OBJECTIVE

This study explored the role of additional genetic variation in the chromosome 3 locus as a source of phenotypic heterogeneity in the Worm Study population.

METHODS

Genotypes underlying the linkage peak (n = 70) were characterized using microarrays. Haplotypes were determined using family-aware phasing and a population-specific reference panel. Variants with minor allele frequencies >0.10 were tested for association with cardiac conduction disease and isorhythmic dissociation using LAMP and logistic regression.

RESULTS

Only 1 haplotype carried the p.Phe1617del/rs749697698 deletion, suggesting relatively recent development (∼18 generations); this haplotype contained 5 other missense variants spanning SCN5A/SCN10A/SCN11A. Noncarrier haplotypes (n = 74) ranged in frequency from 0.5% to 5%. Although no variants were associated with cardiac conduction disease, a homozygous missense variant in SCN10A was associated with isorhythmic dissociation after correction for multiple comparisons (odds ratio 11.23; 95% confidence interval 2.76-23.39; P = 1.2 × 10^-4). This variant (rs12632942) was previously associated with PR interval.

CONCLUSION

Our data suggest that other variants, alongside a pathogenic mutation, are associated with phenotypic heterogeneity. Single-mutation screening may be insufficient to predict electrical heart disease in patients and family members. In the Worm Study population, segregating a pathogenic SCN5A mutation, compound variation in the SCN5A/SCN10A/SCN11A locus determines arrhythmic outcome.

Race-Dependent Association of Single-Nucleotide Polymorphisms in TrkB Receptor in People Living with HIV and Depression

Human immunodeficiency virus (HIV)-associated cognitive disorders (HAND) is characterized by impaired motor and intellectual functions, as well as mood disorders. Brain-derived neurotrophic factor and its receptor TrkB (or NTRK2) mediate the efficacy of antidepressant drugs. Genomic studies of BDNF/TrkB have implicated common single-nucleotide polymorphisms in the pathology of depression. In the current study, we investigated whether single-nucleotide polymorphisms (SNPs) (rs1212171, rs1439050, rs1187352, rs1778933, rs1443445, rs3780645, rs2378672, and rs11140800) in the NTRK2 has a functional impact on depression in HIV-positive subjects. We have utilized the Central Nervous System (CNS) HIV Antiretroviral Therapy Effects Research (CHARTER) cohort. Our methods explored the univariate associations of these SNPs with clinical (current and lifetime) diagnosis of depression via chi-square. The distribution of alleles was significantly different for African-Americans and Caucasians (non-Hispanic) for several SNPs, so our regression analyses included both "statistical controls" for race group and models for each group separately. Finally, we applied a method of simultaneous analysis of associations, estimating the mutually shared information across a system of variables, separately by race group. Our results indicate that there is no significant association between clinical diagnosis of major depression and these SNPs for either race group in any analysis. However, we identified that the SNP associations varied by race group and sex.

PATRIOT: A Pipeline for Tracing Identity-by-Descent for Chromosome Segments to Improve Genomic Prediction in Self-Pollinating Crop Species

The lowering genotyping cost is ushering in a wider interest and adoption of genomic prediction and selection in plant breeding programs worldwide. However, improper conflation of historical and recent linkage disequilibrium between markers and genes restricts high accuracy of genomic prediction (GP). Multiple ancestors may share a common haplotype surrounding a gene, without sharing the same allele of that gene. This prevents parsing out genetic effects associated with the underlying allele of that gene among the set of ancestral haplotypes. We present "Parental Allele Tracing, Recombination Identification, and Optimal predicTion" (i.e., PATRIOT) approach that utilizes marker data to allow for a rapid identification of lines carrying specific alleles, increases the accuracy of genomic relatedness and diversity estimates, and improves genomic prediction. Leveraging identity-by-descent relationships, PATRIOT showed an improvement in GP accuracy by 16.6% relative to the traditional rrBLUP method. This approach will help to increase the rate of genetic gain and allow available information to be more effectively utilized within breeding programs.

The conserved ASTN2/BRINP1 locus at 9q33.1-33.2 is associated with major psychiatric disorders in a large pedigree from Southern Spain

We investigated the genetic causes of major mental disorders (MMDs) including schizophrenia, bipolar disorder I, major depressive disorder and attention deficit hyperactive disorder, in a large family pedigree from Alpujarras, South of Spain, a region with high prevalence of psychotic disorders. We applied a systematic genomic approach based on karyotyping (n = 4), genotyping by genome-wide SNP array (n = 34) and whole-genome sequencing (n = 12). We performed genome-wide linkage analysis, family-based association analysis and polygenic risk score estimates. Significant linkage was obtained at chromosome 9 (9q33.1–33.2, LOD score = 4.11), a suggestive region that contains five candidate genes ASTN2, BRINP1, C5, TLR4 and TRIM32, previously associated with MMDs. Comprehensive analysis associated the MMD phenotype with genes of the immune system with dual brain functions. Moreover, the psychotic phenotype was enriched for genes involved in synapsis. These results should be considered once studying the genetics of psychiatric disorders in other families, especially the ones from the same region, since founder effects may be related to the high prevalence.

A linkage and exome study of multiplex families with bipolar disorder implicates rare coding variants of ANK3 and additional rare alleles at 10q11-q21

BACKGROUND

Bipolar disorder is a highly heritable psychiatric condition for which specific genetic factors remain largely unknown. In the present study, we used combined whole-exome sequencing and linkage analysis to identify risk loci and dissect the contribution of common and rare variants in families with a high density of illness.

METHODS

Overall, 117 participants from 15 Australian extended families with bipolar disorder (72 with affective disorder, including 50 with bipolar disorder type I or II, 13 with schizoaffective disorder-manic type and 9 with recurrent unipolar disorder) underwent whole-exome sequencing. We performed genome-wide linkage analysis using MERLIN and conditional linkage analysis using LAMP. We assessed the contribution of potentially functional rare variants using a genebased segregation test.

RESULTS

We identified a significant linkage peak on chromosome 10q11-q21 (maximal single nucleotide polymorphism = rs10761725; exponential logarithm of the odds [LODexp] = 3.03; empirical p = 0.046). The linkage interval spanned 36 protein-coding genes, including a gene associated with bipolar disorder, ankyrin 3 (ANK3). Conditional linkage analysis showed that common ANK3 risk variants previously identified in genome-wide association studies - or variants in linkage disequilibrium with those variants - did not explain the linkage signal (rs10994397 LOD = 0.63; rs9804190 LOD = 0.04). A family-based segregation test with 34 rare variants from 14 genes under the linkage interval suggested rare variant contributions of 3 brain-expressed genes: NRBF2 (p = 0.005), PCDH15 (p = 0.002) and ANK3 (p = 0.014).

LIMITATIONS

We did not examine non-coding variants, but they may explain the remaining linkage signal.

CONCLUSION

Combining family-based linkage analysis with next-generation sequencing data is effective for identifying putative disease genes and specific risk variants in complex disorders. We identified rare missense variants in ANK3, PCDH15 and NRBF2 that could confer disease risk, providing valuable targets for functional characterization.

Genetics of Smoking Behaviors in American Indians

BACKGROUND

The smoking behavior of American Indians (AI) differs from that of non-Hispanic whites (NHW). Typically light smokers, cessation interventions in AIs are generally less effective. To develop more effective cessation programs for AIs, clinicians, researchers, and public health workers need a better understanding of the genetic factors involved in their smoking behavior. Our aim was to assess whether SNPs associated with smoking behavior in NHWs are also associated with smoking in AIs.

METHODS

We collected questionnaire data on smoking behaviors and analyzed blood and saliva samples from two Tribal populations with dramatically different cultures and smoking prevalence, one in the Northern Plains (n = 323) and the other in the Southwest (n = 176). A total of 384 SNPs were genotyped using an Illumina custom GoldenGate platform. Samples were also assessed for cotinine and 3-hydroxycotinine as markers of nicotine intake and nicotine metabolite ratio.

RESULTS

Among 499 participants, we identified, in the Northern Plains sample only, a variant of the gamma-aminobutyric acid receptor subunit alpha-2 (GABRA2) (rs2119767) on chromosome 4p that was associated with many of the intake biomarkers of smoking we examined, suggesting a role for this gene in modifying smoking behavior in this population. We also identified three SNPs, in the Southwest sample only, as significant correlates of only cigarettes per day: rs4274224, rs4245147 (both dopamine receptor D2 gene), and rs1386493 (tryptophan hydroxylase 2 gene).

CONCLUSIONS

The contribution of many genes known to underlie smoking behaviors in NHWs may differ in AIs.

IMPACT

Once validated, these variants could be useful in developing more effective cessation strategies.

Combining CDKN1A gene expression and genome-wide SNPs in a twin cohort to gain insight into the heritability of individual radiosensitivity

Individual variability in response to radiation exposure is recognised and has often been reported as important in treatment planning. Despite many efforts to identify biomarkers allowing the identification of radiation sensitive patients, it is not yet possible to distinguish them with certainty before the beginning of the radiotherapy treatment. A comprehensive analysis of genome-wide single-nucleotide polymorphisms (SNPs) and a transcriptional response to ionising radiation exposure in twins have the potential to identify such an individual. In the present work, we investigated SNP profile and CDKN1A gene expression in blood T lymphocytes from 130 healthy Caucasians with a complex level of individual kinship (unrelated, mono- or dizygotic twins). It was found that genetic variation accounts for 66% (95% CI 37-82%) of CDKN1A transcriptional response to radiation exposure. We developed a novel integrative multi-kinship strategy allowing investigating the role of genome-wide polymorphisms in transcriptomic radiation response, and it revealed that rs205543 (ETV6 gene), rs2287505 and rs1263612 (KLF7 gene) are significantly associated with CDKN1A expression level. The functional analysis revealed that rs6974232 (RPA3 gene), involved in mismatch repair (p value = 9.68e-04) as well as in RNA repair (p value = 1.4e-03) might have an important role in that process. Two missense polymorphisms with possible deleterious effect in humans were identified: rs1133833 (AKIP1 gene) and rs17362588 (CCDC141 gene). In summary, the data presented here support the validity of this novel integrative data analysis strategy to provide insights into the identification of SNPs potentially influencing radiation sensitivity. Further investigations in radiation response research at the genomic level should be therefore continued to confirm these findings.

Fine-mapping scan of bipolar disorder susceptibility loci in Latino pedigrees

We previously identified bipolar disorder (BD) susceptibility loci on 8q24, 14q32, and 2q12-14 in a genome-wide nonparametric linkage screen in a Latino cohort. We now perform a fine mapping analysis using a dense map of additional SNPs to identify BD susceptibility genes within these regions. One thousand nine hundred and thirty-eight individuals with Latino ancestry (880 individuals with BD Type I or Schizoaffective, Bipolar Type) from 416 Latino pedigrees from the United States, Mexico, Costa Rica, and Guatemala were genotyped with 3,074 SNPs to provide dense coverage of the 8q24 (11.5 cM), 14q32 (7.5 cM), and 2q12-14 (6.5 cM) chromosomal loci. Single-marker association tests in the presence of linkage were performed using the LAMP software. The top linkage peak (rs7834818; LOD = 5.08, p = 3.30E - 5) and associated single marker (rs2280915, p = 2.70E - 12) were located within FBXO32 on 8q24. On chromosome 2, the top linkage peak (rs6750326; LOD = 5.06, p = 3.50E - 5) and associated single marker (rs11887088, p = 2.90E - 6) were located in intragenic regions near ACTR3 and DPP10. None of the additional markers in the region around chromosome 14q32 met significance levels for linkage or association. We identified six SNPs on 2q12-q14 and one SNP in FBXO32 on 8q24 that were significantly associated with BD in this Latino cohort.

Adjusting for Familial Relatedness in the Analysis of GWAS Data

Relatedness within a sample can be of ancient (population stratification) or recent (familial structure) origin, and can either be known (pedigree data) or unknown (cryptic relatedness). All of these forms of familial relatedness have the potential to confound the results of genome-wide association studies. This chapter reviews the major methods available to researchers to adjust for the biases introduced by relatedness and maximize power to detect associations. The advantages and disadvantages of different methods are presented with reference to elements of study design, population characteristics, and computational requirements.

Variants in TTC25 affect autistic trait in patients with autism spectrum disorder and general population

Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder with a complex genetic architecture. To identify genetic variants underlying ASD, we performed single-variant and gene-based genome-wide association studies using a dense genotyping array containing over 2.3 million single-nucleotide variants in a discovery sample of 160 families with at least one child affected with non-syndromic ASD using a binary (ASD yes/no) phenotype and a quantitative autistic trait. Replication of the top findings was performed in Psychiatric Genomics Consortium and Erasmus Rucphen Family (ERF) cohort study. Significant association of quantitative autistic trait was observed with the TTC25 gene at 17q21.2 (effect size=10.2, P-value=3.4 × 10^-7) in the gene-based analysis. The gene also showed nominally significant association in the cohort-based ERF study (effect=1.75, P-value=0.05). Meta-analysis of discovery and replication improved the association signal (P-value_meta=1.5 × 10^-8). No genome-wide significant signal was observed in the single-variant analysis of either the binary ASD phenotype or the quantitative autistic trait. Our study has identified a novel gene TTC25 to be associated with quantitative autistic trait in patients with ASD. The replication of association in a cohort-based study and the effect estimate suggest that variants in TTC25 may also be relevant for broader ASD phenotype in the general population. TTC25 is overexpressed in frontal cortex and testis and is known to be involved in cilium movement and thus an interesting candidate gene for autistic trait.

Palatability, digestibility, and metabolizable energy of dietary glycerol in adult cats

Glycerol is a humectant, which reduces water activity when added to the diet. This property seems to offer dietary benefits, specifically in high-moisture diets for cats, where some humectants cannot be used. According to the U.S. Food and Drug Administration, glycerol is generally recognized as sustenance safe (GRAS). It is suggested that cats are able to metabolize glycerol and use it as an energy source without compromising health. Three experiments were conducted to evaluate the following characteristics of glycerol in the diet for cats: 1) a preference test, 2) digestibility, ME, and fecal and urinary characteristics, and 3) postprandial plasma glycemia. Twelve healthy adult female cats were randomly distributed among 4 treatments consisting of a basal diet (4,090 kcal ME/kg DM, 32% CP, 11% fat, 2.3% crude fiber, and 7.0% ash) and 3 diets with varying percentages of glycerol, made by replacing the basal diet with 2.5, 5.0, and 10.0% purified glycerol (99.5%). The inclusion of glycerol proportionally reduced ( < 0.05) water activity in the diets. The preference test was conducted by observing the contrast between the basal diet and the 5.0% and 10% glycerol diets. Cats did not show a preference for any diet in particular ( > 0.05). The digestibility assays showed that increasing dietary glycerol levels did not affect food intake or the apparent total tract digestibility of macronutrients and energy ( > 0.05). The inclusion of glycerol in the diets did not alter the stool moisture, fecal score, or urine volume. However, glycerol was detected in urine when it was incorporated into the diet at 10%. Glycemia increased up to 900 min following the first meal after the fasting period with no difference between treatments, even when the means were adjusted for food intake. The blood glucose area under the curve also showed no significant difference between treatments ( > 0.05). Cats accepted glycerol under the conditions of the study, and its nutritional value was determined as it has been done for other species. The ME of glycerol for adult cats was estimated to be 3,185 kcal/kg DM. Supplementing the diets of the cats with 10% glycerol may exceed their capacity to metabolize glycerol, possibly leading to urinary excretions.

Comprehensive candidate gene analysis for symptomatic or asymptomatic outcomes of Leishmania infantum infection in Brazil

Genetic risk factors contribute to asymptomatic versus symptomatic visceral leishmaniasis (VL) outcomes following infection with Leishmania infantum. We therefore carried out a family-based (n = 918 post-quality control fully genotyped and phenotyped individuals) candidate gene study for symptomatic VL or asymptomatic delayed-type hypersensitivity (DTH) skin test phenotypes in highly endemic neighborhoods of northeast Brazil. A total of 248 SNPs were genotyped in 42 genes selected as candidates on the basis of prior genetic, immunological, and transcriptional profiling studies. The most significant association with the VL phenotype was with SNP rs6785358 (P = 5.7e-04; p_corrected = 0.026) 3.8 kb upstream of TGFBR2, the gene encoding the type 2 receptor for transforming growth factor beta (TGFβ). A second inhibitory member of the TGBβ superfamily signaling pathway, SMAD7, was associated with the DTH phenotype (SNP rs7238442: P = 0.001; p_corrected = 0.051). The most significant association for the DTH phenotype was with SNP rs10800309 (P = -8.4e-06; p_corrected = 3.9e-04) situated 3.1 kb upstream of FCGR2A, the gene encoding the low-affinity IIa receptor for the Fc fragment of IgG. Overall, our results imply a role for IgG-mediated inflammation in determining DTH associated with asymptomatic infection and contribute to growing evidence that the TGFβ pathway is important in the immunopathogenesis of VL.

Relationship between cytokine expression patterns and clinical outcomes: two population-based birth cohorts

BACKGROUND

Models that incorporate patterns of multiple cytokine responses to allergens, rather than individual cytokine production, may better predict sensitization and asthma.

OBJECTIVE

To characterize the patterns of peripheral blood mononuclear cells' (PBMCs) cytokine responses to house dust mite (HDM) allergens among children from two population-based birth cohorts using machine learning techniques.

METHODS

PBMCs collected at 8 years of age from the UK Manchester Asthma and Allergy Study (n = 268) and at 14 years of age from the Australian Raine Study (n = 1374) were cultured with HDM extract (10 μg/ml). Cytokine expression (IL-13, IL-5, IFN-γ, and IL10) was measured in the supernatant. Cytokine patterns were identified using a Gaussian mixture model clustering, and classification stability was assessed by bootstrapping.

RESULTS

A six-class model indicated complex latent structure of cytokine expression. Based on the characteristics of each class, we designated them as follows: 'Nonresponders' (n = 905, 55%); 'IL-10 responders' (n = 49, 3%); 'IFN-γ and IL-13 medium responders' (n = 56, 3.4%); 'IL-13 medium responders' (n = 351, 21.4%); 'IL-5 and IL-13 medium responders' (n = 77, 4.7%); and 'IL-13 and IL-5 high responders' (n = 204, 12.4%). 'IL-13 and IL-5 high responders' were at much higher risk of HDM sensitization and asthma compared to all other classes, with 88% of children assigned to this class being sensitized and 28.5% having asthma.

CONCLUSION

Using model-based clustering, we identified several distinct patterns of cytokine response to HDM and observed interplay between cytokine expression level, cytokine patterns (especially IL-13 and IL-5), and clinical outcomes. 'IL-13 and IL-5 high responders' class was strongly associated with HDM sensitization. However, among HDM-sensitized children, one-third showed no PBMC response to HDM, and the majority of HDM-sensitized children did not have asthma or wheeze. Our findings suggest that positive HDM 'allergy tests' and asthma are associated with a broad range of immunophenotypes, which may have important implications for the use of cytokine-targeted treatment approaches.

Fine mapping under linkage peaks for symptomatic or asymptomatic outcomes of Leishmania infantum infection in Brazil

Infection with the protozoan Leishmania infantum can lead to asymptomatic infection and protective immunity, or to the progressive and potentially fatal disease visceral leishmaniasis (VL). Published studies show host genetic background determines in part whether infected individuals will develop a symptomatic or asymptomatic outcome. The purpose of the current study was to fine map chromosome regions previously linked with risk for symptomatic (chromosome 9) or asymptomatic (chromosomes 15 and 19) manifestations of L. infantum infection. We conducted a family-based genetic study of VL and asymptomatic infection (detected by a DTH skin test) with a final post quality control sample of 961 individuals with full genotype and phenotype information from highly endemic neighborhoods of northeast Brazil. A total of 5485 SNPs under the linkage peaks on chromosomes 9, 15 and 19 were genotyped. No strong SNP associations were observed for the DTH phenotype. The most significant associations with the VL phenotype were with SNP rs1470217 (p=5.9e-05; pcorrected=0.057) on chromosome 9, and with SNP rs8107014 (p=1.4e-05; pcorrected=0.013) on chromosome 19. SNP rs1470217 is situated in a 180kb intergenic region between TMEM215 (Transmembrane protein 215) and APTX (Aprataxin). SNP rs8107014 lies in the intron between exons 26 and 27 of a 34 exon transcript (ENST00000204005) of LTBP4, (Latent transforming growth factor-beta-binding protein 4a). The latter supports growing evidence that the transforming growth factor-beta pathway is important in the immunopathogenesis of VL.

Genotype-Based Score Test for Association Testing in Families

The multiplex-case and control design in which multiple cases are sampled from the same family is considered. In such studies phenotype information of the un-genotyped relatives might be available. We intend to use additional family information when performing genetic association tests. A score test is revisited to provide a flexible framework to accommodate various genetic models and to improve power of the association test by adding available family information. The proposed test accounts for correlations induced by multiple cases from the same pedigree, directly deals with X-linked SNPs in mixed-sex-related samples, and incorporates additional phenotypic information such as the number of (un-genotyped) siblings and parents with similar symptoms by assigning the weights to (genotyped) multiplex cases. In addition, the score test directly incorporates posterior probabilities of imputed genotypes, which leads to an efficiency measure that reflects imputation uncertainty on the test conducted. The proposed test is applied to real applications for illustration. Its efficiency is demonstrated via simulations.

Combined linkage and family-based association analysis improves candidate gene detection in Genetic Analysis Workshop 18 simulation data

Because the genotype-phenotype correlation information is investigated differently by linkage and association analyses, various efforts have been made to model linkage and association jointly. However, joint modeling methods are usually computationally intensive; hence they cannot currently accommodate large pedigrees with dense markers. This article proposes a simple method to combine the linkage and association evidence with the aim of improving the detection power of disease susceptibility genes. Our detection power comparisons show that the combined linkage-association p values can improve remarkably the causal gene detection power in Genetic Analysis Workshop 18 simulation data.

Cntnap4 differentially contributes to GABAergic and dopaminergic synaptic transmission

Although considerable evidence suggests that the chemical synapse is a lynchpin underlying affective disorders, how molecular insults differentially affect specific synaptic connections remains poorly understood. For instance, Neurexin 1a and 2 (NRXN1 and NRXN2) and CNTNAP2 (also known as CASPR2), all members of the neurexin superfamily of transmembrane molecules, have been implicated in neuropsychiatric disorders. However, their loss leads to deficits that have been best characterized with regard to their effect on excitatory cells. Notably, other disease-associated genes such as BDNF and ERBB4 implicate specific interneuron synapses in psychiatric disorders. Consistent with this, cortical interneuron dysfunction has been linked to epilepsy, schizophrenia and autism. Using a microarray screen that focused upon synapse-associated molecules, we identified Cntnap4 (contactin associated protein-like 4, also known as Caspr4) as highly enriched in developing murine interneurons. In this study we show that Cntnap4 is localized presynaptically and its loss leads to a reduction in the output of cortical parvalbumin (PV)-positive GABAergic (γ-aminobutyric acid producing) basket cells. Paradoxically, the loss of Cntnap4 augments midbrain dopaminergic release in the nucleus accumbens. In Cntnap4 mutant mice, synaptic defects in these disease-relevant neuronal populations are mirrored by sensory-motor gating and grooming endophenotypes; these symptoms could be pharmacologically reversed, providing promise for therapeutic intervention in psychiatric disorders.

A genome-wide linkage scan of bipolar disorder in Latino families identifies susceptibility loci at 8q24 and 14q32

A genome-wide nonparametric linkage screen was performed to localize Bipolar Disorder (BP) susceptibility loci in a sample of 3757 individuals of Latino ancestry. The sample included 963 individuals with BP phenotype (704 relative pairs) from 686 families recruited from the US, Mexico, Costa Rica, and Guatemala. Non-parametric analyses were performed over a 5 cM grid with an average genetic coverage of 0.67 cM. Multipoint analyses were conducted across the genome using non-parametric Kong & Cox LOD scores along with Sall statistics for all relative pairs. Suggestive and significant genome-wide thresholds were calculated based on 1000 simulations. Single-marker association tests in the presence of linkage were performed assuming a multiplicative model with a population prevalence of 2%. We identified two genome-wide significant susceptibly loci for BP at 8q24 and 14q32, and a third suggestive locus at 2q13-q14. Within these three linkage regions, the top associated single marker (rs1847694, P = 2.40 × 10(-5)) is located 195 Kb upstream of DPP10 in Chromosome 2. DPP10 is prominently expressed in brain neuronal populations, where it has been shown to bind and regulate Kv4-mediated A-type potassium channels. Taken together, these results provide additional evidence that 8q24, 14q32, and 2q13-q14 are susceptibly loci for BP and these regions may be involved in the pathogenesis of BP in the Latino population.

Complex pedigrees in the sequencing era: to track transmissions or decorrelate?

Next-generation sequencing (NGS) studies are becoming commonplace, and the NGS field is continuing to develop rapidly. Analytic methods aimed at testing for the various roles that genetic susceptibility plays in disease are also rapidly being developed and optimized. Studies that incorporate large, complex pedigrees are of particular importance because they provide detailed information about inheritance patterns and can be analyzed in a variety of complementary ways. The nine contributions from our Genetic Analysis Workshop 18 working group on family-based tests of association for rare variants using simulated data examined analytic methods for testing genetic association using whole-genome sequencing data from 20 large pedigrees with 200 phenotype simulation replicates. What distinguishes the approaches explored is how the complexities of analyzing familial genetic data were handled. Here, we explore the methods that either harness inheritance patterns and transmission information or attempt to adjust for the correlation between family members in order to utilize computationally and conceptually simpler statistical testing procedures. Although directly comparing these two classes of approaches across contributions is difficult, we note that the two classes balance robustness to population stratification and computational complexity (the transmission-based approaches) with simplicity and increased power, assuming no population stratification or proper adjustment for it (decorrelation approaches).

Fine mapping on chromosome 13q32-34 and brain expression analysis implicates MYO16 in schizophrenia

We previously reported linkage of schizophrenia and schizoaffective disorder to 13q32-34 in the European descent Afrikaner population from South Africa. The nature of genetic variation underlying linkage peaks in psychiatric disorders remains largely unknown and both rare and common variants may be contributing. Here, we examine the contribution of common variants located under the 13q32-34 linkage region. We used densely spaced SNPs to fine map the linkage peak region using both a discovery sample of 415 families and a meta-analysis incorporating two additional replication family samples. In a second phase of the study, we use one family-based data set with 237 families and independent case-control data sets for fine mapping of the common variant association signal using HapMap SNPs. We report a significant association with a genetic variant (rs9583277) within the gene encoding for the myosin heavy-chain Myr 8 (MYO16), which has been implicated in neuronal phosphoinositide 3-kinase signaling. Follow-up analysis of HapMap variation within MYO16 in a second set of Afrikaner families and additional case-control data sets of European descent highlighted a region across introns 2-6 as the most likely region to harbor common MYO16 risk variants. Expression analysis revealed a significant increase in the level of MYO16 expression in the brains of schizophrenia patients. Our results suggest that common variation within MYO16 may contribute to the genetic liability to schizophrenia.

Low-frequency intermediate penetrance variants in the ROCK1 gene predispose to Tetralogy of Fallot

BACKGROUND

Epidemiological studies indicate a substantial excess familial recurrence of non-syndromic Tetralogy of Fallot (TOF), implicating genetic factors that remain largely unknown. The Rho induced kinase 1 gene (ROCK1) is a key component of the planar cell polarity signalling pathway, which plays an important role in normal cardiac development. The aim of this study was to investigate the role of genetic variation in ROCK1 on the risk of TOF.

RESULTS

ROCK1 was sequenced in a discovery cohort of 93 non-syndromic TOF probands to identify rare variants. TagSNPs were selected to capture commoner variation in ROCK1. Novel variants and TagSNPs were genotyped in a discovery cohort of 458 TOF cases and 1331 healthy controls, and positive findings were replicated in a further 209 TOF cases and 1290 healthy controls. Association between genotypes and TOF was assessed using LAMP.A rare SNP (c.807C > T; rs56085230) discovered by sequencing was associated with TOF risk (p = 0.006) in the discovery cohort. The variant was also significantly associated with the risk of TOF in the replication cohort (p = 0.018). In the combined cohorts the odds ratio for TOF was 2.61 (95% CI 1.58-4.30); p < 0.0001. The minor allele frequency of rs56085230 in the cases was 0.02, and in the controls it was 0.007. The variant accounted for 1% of the population attributable risk (PAR) of TOF. We also found significant association with TOF for an uncommon TagSNP in ROCK1, rs288979 (OR 1.64 [95% CI 1.15-2.30]; p = 1.5x10⁻⁵). The minor allele frequency of rs288979 in the controls was 0.043, and the variant accounted for 11% of the PAR of TOF. These association signals were independent of each other, providing additional internal validation of our result.

CONCLUSIONS

Low frequency intermediate penetrance (LFIP) variants in the ROCK1 gene predispose to the risk of TOF.

A novel method, the Variant Impact On Linkage Effect Test (VIOLET), leads to improved identification of causal variants in linkage regions

The Human Genome Project was expected to individualize medicine by rapidly advancing knowledge of common complex disease through discovery of disease-causing genetic variants. However, this has proved challenging. Although linkage analysis has identified replicated chromosomal regions, subsequent detection of causal variants for complex traits has been limited. One explanation for this difficulty is that utilization of association to follow up linkage is problematic given that linkage and association are not required to co-occur. Indeed, co-occurrence is likely to occur only in special circumstances, such as Mendelian inheritance, but cannot be universally expected. To overcome this problem, we propose a novel method, the Variant Impact On Linkage Effect Test (VIOLET), which differs from other quantitative methods in that it is designed to follow up linkage by identifying variants that influence the variance explained by a quantitative trait locus. VIOLET's performance was compared with measured genotype and combined linkage association in two data sets with quantitative traits. Using simulated data, VIOLET had high power to detect the causal variant and reduced false positives compared with standard methods. Using real data, VIOLET identified a single variant, which explained 24% of linkage; this variant exhibited only nominal association (P=0.04) using measured genotype and was not identified by combined linkage association. These results demonstrate that VIOLET is highly specific while retaining low false-negative results. In summary, VIOLET overcomes a barrier to gene discovery and thus may be broadly applicable to identify underlying genetic etiology for traits exhibiting linkage.

Detection and impact of rare regulatory variants in human disease

Advances in genome sequencing are providing unprecedented resolution of rare and private variants. However, methods which assess the effect of these variants have relied predominantly on information within coding sequences. Assessing their impact in non-coding sequences remains a significant contemporary challenge. In this review, we highlight the role of regulatory variation as causative agents and modifiers of monogenic disorders. We further discuss how advances in functional genomics are now providing new opportunity to assess the impact of rare non-coding variants and their role in disease.

Genome-wide linkage analysis for human longevity: Genetics of Healthy Aging Study

Clear evidence exists for heritability of human longevity, and much interest is focused on identifying genes associated with longer lives. To identify such longevity alleles, we performed the largest genome-wide linkage scan thus far reported. Linkage analyses included 2118 nonagenarian Caucasian sibling pairs that have been enrolled in 15 study centers of 11 European countries as part of the Genetics of Healthy Aging (GEHA) project. In the joint linkage analyses, we observed four regions that show linkage with longevity; chromosome 14q11.2 (LOD = 3.47), chromosome 17q12-q22 (LOD = 2.95), chromosome 19p13.3-p13.11 (LOD = 3.76), and chromosome 19q13.11-q13.32 (LOD = 3.57). To fine map these regions linked to longevity, we performed association analysis using GWAS data in a subgroup of 1228 unrelated nonagenarian and 1907 geographically matched controls. Using a fixed-effect meta-analysis approach, rs4420638 at the TOMM40/APOE/APOC1 gene locus showed significant association with longevity (P-value = 9.6 × 10(-8) ). By combined modeling of linkage and association, we showed that association of longevity with APOEε4 and APOEε2 alleles explain the linkage at 19q13.11-q13.32 with P-value = 0.02 and P-value = 1.0 × 10(-5) , respectively. In the largest linkage scan thus far performed for human familial longevity, we confirm that the APOE locus is a longevity gene and that additional longevity loci may be identified at 14q11.2, 17q12-q22, and 19p13.3-p13.11. As the latter linkage results are not explained by common variants, we suggest that rare variants play an important role in human familial longevity.

Evidence for association of bipolar disorder to haplotypes in the 22q12.3 region near the genes stargazin, IFT27 and parvalbumin

We have previously reported genome-wide significant linkage of bipolar disorder to a region on 22q12.3 near the marker D22S278. Towards identifying the susceptibility gene, we have conducted a fine-mapping association study of the region in two independent family samples, an independent case-control sample and a genome-wide association dataset. Two hundred SNPs were first examined in a 5 Mb region surrounding the D22S278 marker in a sample of 169 families and analyzed using PLINK. The peak of association was a haplotype near the genes stargazin (CACNG2), intraflagellar transport protein homolog 27 (IFT27) and parvalbumin (PVALB; P = 4.69 × 10(-4)). This peak overlapped a significant haplotype in a family based association study of a second independent sample of 294 families (P = 1.42 × 10(-5)). Analysis of the combined family sample yielded statistically significant evidence of association to a rare three SNP haplotype in the gene IFT27 (P = 8.89 × 10(-6)). Twelve SNPs comprising these haplotypes were genotyped in an independent sample of 574 bipolar I cases and 550 controls. Statistically significant association was found for a haplotype window that overlapped the region from the first two family samples (P = 3.43 × 10(-4)). However, analyses of the two family samples using the program LAMP, found no evidence for association in this region, but did yield significant evidence for association to a haplotype 3' of CACNG2 (P = 1.76 × 10(-6)). Furthermore, no evidence for association was found in a large genome-wide association dataset. The replication of association to overlapping haplotypes in three independent datasets suggests the presence of a bipolar disorder susceptibility gene in this region.

HTR1A a novel type 1 diabetes susceptibility gene on chromosome 5p13-q13

Background

We have previously performed a genome-wide linkage study in Scandinavian Type 1 diabetes (T1D) families. In the Swedish families, we detected suggestive linkage (LOD≤2.2) to the chromosome 5p13-q13 region. The aim of our study was to investigate the linked region in search for possible T1D susceptibility genes.

Methodology/Principal Findings

Microsatellites were genotyped in the Scandinavian families to fine-map the previously linked region. Further, SNPs were genotyped in Swedish and Danish families as well as Swedish sporadic cases. In the Swedish families we detected genome-wide significant linkage to the 5-hydroxytryptamine receptor 1A (HTR1A) gene (LOD 3.98, p<9.8×10⁻⁶). Markers tagging two separate genes; the ring finger protein 180 (RNF180) and HTR1A showed association to T1D in the Swedish and Danish families (p<0.002, p<0.001 respectively). The association was not confirmed in sporadic cases. Conditional analysis indicates that the primary association was to HTR1A. Quantitative PCR show that transcripts of both HTR1A and RNF180 are present in human islets of Langerhans. Moreover, immunohistochemical analysis confirmed the presence of the 5-HTR1A protein in isolated human islets of Langerhans as well as in sections of human pancreas.

Conclusions

We have identified and confirmed the association of both HTR1A and RFN180, two genes in high linkage disequilibrium (LD) to T1D in two separate family materials. As both HTR1A and RFN180 were expressed at the mRNA level and HTR1A as protein in human islets of Langerhans, we suggest that HTR1A may affect T1D susceptibility by modulating the initial autoimmune attack or either islet regeneration, insulin release, or both.

On the validity of the likelihood ratio test and consistency of resulting parameter estimates in joint linkage and linkage disequilibrium analysis under improperly specified parametric models

It has been shown that parametric analysis of linkage disequilibrium conditional on linkage using an overly deterministic model can be optimal for family-based association analysis. However, if one applies this strategy carelessly, there is a risk of false inference. We analyse properties of such likelihood ratio tests when the assumed disease mode of inheritance is inaccurate. Under some conditions, problems result if one is not careful to consider what null hypothesis is being tested. We show that: (a) tests for which the null hypothesis assumes the absence of both linkage and association are independent of the true mode of inheritance; (b) likelihood ratio tests assuming either linkage or association under the null hypothesis may depend on the true mode of inheritance, leading to inconsistent parameter estimates, in particular under extremely deterministic models; (c) this problem cannot be eliminated by increasing sample size or adding population controls--as sample size increases, the chance of false positive inference goes to 100%; (d) this issue can lead to systematic false positive inference of association in regions of linkage. This is important because highly deterministic models are often used intentionally in model-based analyses because they can have more power than the true model, and are implicit in many model-free analysis methods.

Significant linkage at chromosome 19q for otitis media with effusion and/or recurrent otitis media (COME/ROM)

Background

In previous analyses, we identified a region of chromosome 19 as harboring a susceptibility locus for chronic otitis media with effusion and/or recurrent otitis media (COME/ROM). Our aim was to further localize the linkage signal and ultimately identify the causative variant or variants. We followed up our previous linkage scan with dense SNP genotyping across in a 5 Mb region. A total of 607 individuals from 139 families, including 159 affected sib pairs and 62 second-degree affected relative pairs, were genotyped at 1,091 SNPs. We carried out a nonparametric linkage analysis, modeling marker-to-marker linkage disequilibrium.

Results

The maximum log of the odds (LOD) score increased to 3.75 (P = 1.6 × 10^-5) at position 63.4 Mb, with a LOD-1 support interval between 61.6 Mb and 63.8 Mb, providing significant evidence of linkage between this region and COME/ROM. The support interval contains over 90 known genes, including several genes involved in the inflammasome protein complex, a key regulator of the innate immune response to harmful exogenous or endogenous stimuli. Parametric linkage analysis suggests that for a sib of an affected individual, the recurrence risk of COME/ROM due to this linkage region is twice the recurrence risk in the population. We examined potential associations between the SNPs genotyped in this region and COME/ROM, however none provided evidence for association.

Conclusion

This study has refined the 19q region of linkage with COME/ROM, and association results suggest that the linkage signal may be due to rare variants.

On the statistical properties of family-based association tests in datasets containing both pedigrees and unrelated case-control samples

A common approach to genetic mapping of loci for complex diseases is to perform a genome-wide association study (GWAS) by analyzing a vast number of SNP markers in cohorts of unrelated cases and controls. A direct motivation for the case-control design is that unrelated, affected individuals can be easier to collect than large families with multiple affected persons in the Western world. Despite its higher potential power, investigators have not actively pursued family ascertainment in part because of a dearth of methods for analyzing such correlated data on a large scale. We examine the statistical properties of several commonly used family-based association tests, as to their performance using real-life mixtures of families and singletons taken from our own migraine and schizophrenia studies, as well as population-based data for a complex trait simulated with the evolutionary phenogenetic simulator, ForSim. In virtually every situation, the full likelihood-based methods in the PSEUDOMARKER program outperformed those implemented in FBAT, GENEHUNTER TDT, PLINK (family-based options), HRR/HHRR, QTDT, TRANSMIT, UNPHASED, MENDEL, and LAMP. We further show that GWAS is much more powerful when family samples are used rather than unrelateds, on a genotype-by-genotype basis.

PSEUDOMARKER: a powerful program for joint linkage and/or linkage disequilibrium analysis on mixtures of singletons and related individuals

A decade ago, there was widespread enthusiasm for the prospects of genome-wide association studies to identify common variants related to common chronic diseases using samples of unrelated individuals from populations. Although technological advancements allow us to query more than a million SNPs across the genome at low cost, a disappointingly small fraction of the genetic portion of common disease etiology has been uncovered. This has led to the hypothesis that less frequent variants might be involved, stimulating a renaissance of the traditional approach of seeking genes using multiplex families from less diverse populations. However, by using the modern genotyping and sequencing technology, we can now look not just at linkage, but jointly at linkage and linkage disequilibrium (LD) in such samples. Software methods that can look simultaneously at linkage and LD in a powerful and robust manner have been lacking. Most algorithms cannot jointly analyze datasets involving families of varying structures in a statistically or computationally efficient manner. We have implemented previously proposed statistical algorithms in a user-friendly software package, PSEUDOMARKER. This paper is an announcement of this software package. We describe the motivation behind the approach, the statistical methods, and software, and we briefly demonstrate PSEUDOMARKER's advantages over other packages by example.

Genome-wide linkage analysis to identify genetic modifiers of ALK mutation penetrance in familial neuroblastoma

BACKGROUND

Neuroblastoma (NB) is an important childhood cancer with a strong genetic component related to disease susceptibility. Approximately 1% of NB cases have a positive family history. Following a genome-wide linkage analysis and sequencing of candidate genes in the critical region, we identified ALK as the major familial NB gene. Dominant mutations in ALK are found in more than 50% of familial NB cases. However, in the families used for the linkage study, only about 50% of carriers of ALK mutations are affected by NB.

METHODS

To test whether genetic variation may explain the reduced penetrance of the disease phenotype, we analyzed genome-wide genotype data in ALK mutation-positive families using a model-based linkage approach with different liability classes for carriers and non-carriers of ALK mutations.

RESULTS

The region with the highest LOD score was located at chromosome 2p23-p24 and included the ALK locus under models of dominant and recessive inheritance.

CONCLUSIONS

This finding suggests that variants in the non-mutated ALK gene or another gene linked to it may affect penetrance of the ALK mutations and risk of developing NB in familial cases.

Assessing the contribution family data can make to case-control studies of rare variants

When pathogenic variants are rare then even among cases the proportion of subjects possessing a variant might be low, meaning that very large samples might be required to conclusively demonstrate evidence of an effect. Relatives of subjects within a case-control sample might provide useful additional information. The method of model-free linkage analysis implemented in MFLINK was adapted to incorporate linkage disequilibrium (LD) parameters in order to test for an effect of a putative pathogenic variant in complete LD with a disease locus. The effect of adding in to the analysis relatives of cases and controls found to carry the variant was investigated. When affected siblings or cousins of cases possessing the variant were incorporated they had a large effect on the results obtained. The evidence for involvement increased or reduced as expected, depending on whether or not the relatives themselves were found to possess the variant. The size of the effect was large relative to that expected from just increasing the size of a standard case-control sample. Affected relatives offer a valuable resource to assist the interpretation of case-control studies of rare variants. The method is capable of including other relative types and can deal with complex pedigrees.

Family-based designs for genome-wide association studies

Association mapping has successfully identified common SNPs associated with many diseases. However, the inability of this class of variation to account for most of the supposed heritability has led to a renewed interest in methods - primarily linkage analysis - to detect rare variants. Family designs allow for control of population stratification, investigations of questions such as parent-of-origin effects and other applications that are imperfectly or not readily addressed in case-control association studies. This article guides readers through the interface between linkage and association analysis, reviews the new methodologies and provides useful guidelines for applications. Just as effective SNP-genotyping tools helped to realize the potential of association studies, next-generation sequencing tools will benefit genetic studies by improving the power of family-based approaches.

A common MUC5B promoter polymorphism and pulmonary fibrosis

BACKGROUND

The mutations that have been implicated in pulmonary fibrosis account for only a small proportion of the population risk.

METHODS

Using a genomewide linkage scan, we detected linkage between idiopathic interstitial pneumonia and a 3.4-Mb region of chromosome 11p15 in 82 families. We then evaluated genetic variation in this region in gel-forming mucin genes expressed in the lung among 83 subjects with familial interstitial pneumonia, 492 subjects with idiopathic pulmonary fibrosis, and 322 controls. MUC5B expression was assessed in lung tissue.

RESULTS

Linkage and fine mapping were used to identify a region of interest on the p-terminus of chromosome 11 that included gel-forming mucin genes. The minor-allele of the single-nucleotide polymorphism (SNP) rs35705950, located 3 kb upstream of the MUC5B transcription start site, was present at a frequency of 34% among subjects with familial interstitial pneumonia, 38% among subjects with idiopathic pulmonary fibrosis, and 9% among controls (allelic association with familial interstitial pneumonia, P=1.2×10(-15); allelic association with idiopathic pulmonary fibrosis, P=2.5×10(-37)). The odds ratios for disease among subjects who were heterozygous and those who were homozygous for the minor allele of this SNP were 6.8 (95% confidence interval [CI], 3.9 to 12.0) and 20.8 (95% CI, 3.8 to 113.7), respectively, for familial interstitial pneumonia and 9.0 (95% CI, 6.2 to 13.1) and 21.8 (95% CI, 5.1 to 93.5), respectively, for idiopathic pulmonary fibrosis. MUC5B expression in the lung was 14.1 times as high in subjects who had idiopathic pulmonary fibrosis as in those who did not (P<0.001). The variant allele of rs35705950 was associated with up-regulation in MUC5B expression in the lung in unaffected subjects (expression was 37.4 times as high as in unaffected subjects homozygous for the wild-type allele, P<0.001). MUC5B protein was expressed in lesions of idiopathic pulmonary fibrosis.

CONCLUSIONS

A common polymorphism in the promoter of MUC5B is associated with familial interstitial pneumonia and idiopathic pulmonary fibrosis. Our findings suggest that dysregulated MUC5B expression in the lung may be involved in the pathogenesis of pulmonary fibrosis. (Funded by the National Heart, Lung, and Blood Institute and others.).

Effective sample size: Quick estimation of the effect of related samples in genetic case-control association analyses

Affected relatives are essential for pedigree linkage analysis, however, they cause a violation of the independent sample assumption in case-control association studies. To avoid the correlation between samples, a common practice is to take only one affected sample per pedigree in association analysis. Although several methods exist in handling correlated samples, they are still not widely used in part because these are not easily implemented, or because they are not widely known. We advocate the effective sample size method as a simple and accessible approach for case-control association analysis with correlated samples. This method modifies the chi-square test statistic, p-value, and 95% confidence interval of the odds-ratio by replacing the apparent number of allele or genotype counts with the effective ones in the standard formula, without the need for specialized computer programs. We present a simple formula for calculating effective sample size for many types of relative pairs and relative sets. For allele frequency estimation, the effective sample size method captures the variance inflation exactly. For genotype frequency, simulations showed that effective sample size provides a satisfactory approximation. A gene which is previously identified as a type 1 diabetes susceptibility locus, the interferon-induced helicase gene (IFIH1), is shown to be significantly associated with rheumatoid arthritis when the effective sample size method is applied. This significant association is not established if only one affected sib per pedigree were used in the association analysis. Relationship between the effective sample size method and other methods - the generalized estimation equation, variance of eigenvalues for correlation matrices, and genomic controls - are discussed.

Family-based association analysis to finemap bipolar linkage peak on chromosome 8q24 using 2,500 genotyped SNPs and 15,000 imputed SNPs

OBJECTIVE

  Multiple linkage and association studies have suggested chromosome 8q24 as a promising candidate region for bipolar disorder (BP). We performed a detailed association analysis assessing the contribution of common genetic variation in this region to the risk of BP.

METHODS

  We analyzed 2,756 single nucleotide polymorphism (SNP) markers in the chromosome 8q24 region of 3,512 individuals from 737 families. In addition, we extended genotype imputation methods to family-based data and imputed 22,725 HapMap SNPs in the same region on 8q24. We applied a family-based method to test 15,552 high-quality genotyped or imputed SNPs for association with BP.

RESULTS

  Our association analysis identified the most significant marker (p=4.80 × 10(-5) ), near the gene encoding potassium voltage-gated channel KQT-like protein (KCNQ3). Other marginally significant markers were located near adenylate cyclase 8 (ADCY8) and ST3 beta-galactoside alpha-2,3-sialyltransferase 1 (ST3GAL1).

CONCLUSIONS

  We developed an approach to apply MACH imputation to family-based data, which can increase the power to detect association signals. Our association results showed suggestive evidence of association of BP with loci near KCNQ3, ADCY8, and ST3GAL1. Consistent with genes identified by genome-wide association studies for BP, our results suggest the involvement of ion channelopathy in BP pathogenesis. However, common variants are insufficient to explain linkage findings in 8q24; other genetic variation should be explored.

Forward-time simulation of realistic samples for genome-wide association studies

Background

Forward-time simulations have unique advantages in power and flexibility for the simulation of genetic samples of complex human diseases because they can closely mimic the evolution of human populations carrying these diseases. However, a number of methodological and computational constraints have prevented the power of this simulation method from being fully explored in existing forward-time simulation methods.

Results

Using a general-purpose forward-time population genetics simulation environment, we developed a forward-time simulation method that can be used to simulate realistic samples for genome-wide association studies. We examined the properties of this simulation method by comparing simulated samples with real data and demonstrated its wide applicability using four examples, including a simulation of case-control samples with a disease caused by multiple interacting genetic and environmental factors, a simulation of trio families affected by a disease-predisposing allele that had been subjected to either slow or rapid selective sweep, and a simulation of a structured population resulting from recent population admixture.

Conclusions

Our algorithm simulates populations that closely resemble the complex structure of the human genome, while allows the introduction of signals of natural selection. Because of its flexibility to generate different types of samples with arbitrary disease or quantitative trait models, this simulation method can simulate realistic samples to evaluate the performance of a wide variety of statistical gene mapping methods for genome-wide association studies.

Family-based association analysis of 42 hereditary prostate cancer families identifies the Apolipoprotein L3 region on chromosome 22q12 as a risk locus

Multiple genome-wide scans for hereditary prostate cancer (HPC) have identified susceptibility loci on nearly every chromosome. However, few results have been replicated with statistical significance. One exception is chromosome 22q, for which five independent linkage studies yielded strong evidence for a susceptibility locus in HPC families. Previously, we refined this region to a 2.53 Mb interval, using recombination mapping in 42 linked pedigrees. We now refine this locus to a 15 kb interval, spanning Apolipoprotein L3 (APOL3), using family-based association analyses of 150 total prostate cancer (PC) cases from two independent family collections with 506 unrelated population controls. Analysis of the two independent sets of PC cases highlighted single nucleotide polymorphisms (SNPs) within the APOL3 locus showing the strongest associations with HPC risk, with the most robust results observed when all 150 cases were combined. Analysis of 15 tagSNPs across the 5' end of the locus identified six SNPs with P-values < or =2 × 10(-4). The two independent sets of HPC cases highlight the same 15 kb interval at the 5' end of the APOL3 gene and provide strong evidence that SNPs within this 15 kb interval, or in strong linkage disequilibrium with it, contribute to HPC risk. Further analyses of this locus in an independent population-based, case-control study revealed an association between an SNP within the APOL3 locus and PC risk, which was not confirmed in the Cancer Genetic Markers of Susceptibility data set. This study further characterizes the 22q locus in HPC risk and suggests that the role of this region in sporadic PC warrants additional studies.

Genome-wide association studies: a powerful tool for neurogenomics

As their power and utility increase, genome-wide association (GWA) studies are poised to become an important element of the neurosurgeon's toolkit for diagnosing and treating disease. In this paper, the authors review recent findings and discuss issues associated with gathering and analyzing GWA data for the study of neurological diseases and disorders, including those of neurosurgical importance. Their goal is to provide neurosurgeons and other clinicians with a better understanding of the practical and theoretical issues associated with this line of research. A modern GWA study involves testing hundreds of thousands of genetic markers across an entire genome, often in thousands of individuals, for any significant association with a particular disease. The number of markers assayed in a study presents several practical and theoretical issues that must be considered when planning the study. Genome-wide association studies show great promise in our understanding of the genes underlying common neurological diseases and disorders, as well as in leading to a new generation of genetic tests for clinicians.

Testing for genetic association in the presence of linkage and gene-covariate interactions

In order to study family-based association in the presence of linkage, we extend a generalized linear mixed model proposed for genetic linkage analysis (Lebrec and van Houwelingen (2007), Human Heredity 64, 5-15) by adding a genotypic effect to the mean. The corresponding score test is a weighted family-based association tests statistic, where the weight depends on the linkage effect and on other genetic and shared environmental effects. For testing of genetic association in the presence of gene-covariate interaction, we propose a linear regression method where the family-specific score statistic is regressed on family-specific covariates. Both statistics are straightforward to compute. Simulation results show that adjusting the weight for the within-family variance structure may be a powerful approach in the presence of environmental effects. The test statistic for genetic association in the presence of gene-covariate interaction improved the power for detecting association. For illustration, we analyze the rheumatoid arthritis data from GAW15. Adjusting for smoking and anti-cyclic citrullinated peptide increased the significance of the association with the DR locus.

Evaluation of approaches to identify associated SNPs that explain the linkage evidence in nuclear families with affected siblings

Linkage analysis is often followed by association mapping to localize disease variants. In this paper, we evaluate approaches to determine how much of the observed linkage evidence, namely the identity-by-descent (IBD) sharing at the linkage peak, is explained by associated SNPs. We study several methods: Homozygote Sharing Tests (HST), Genotype Identity-by-Descent Sharing Test (GIST), and a permutation approach. We also propose a new approach, HSTMLB, combining HST and the Maximum Likelihood Binomial (MLB) linkage statistic. These methods can identify SNPs partially explaining the linkage peak, but only HST and HSTMLB can identify SNPs that do not fully explain the linkage evidence and be applied to multiple-SNPs. We contrast these methods with the association tests implemented in the software LAMP. In our simulations, GIST is more powerful at finding SNPs that partially explain the linkage peak, while HST and HSTMLB are equally powerful at identifying SNPs that do not fully explain the linkage peak. When applied to the North American Rheumatoid Arthritis Consortium data, HST and HSTMLB identify marker pairs that may fully explain the linkage peak on chromosome 6. In conclusion, HST and HSTMLB provide simple and flexible tools to identify SNPs that explain the IBD sharing at the linkage peak.

Bayesian EM algorithm for scoring polymorphic deletions from SNP data and application to a common CNV on 8q24

Copy number variations (CNVs) in the human genome provide exciting candidates for functional polymorphisms. Hence, we now assess association between CNV carrier status and diseases status by evaluating the signal intensity of SNP genotyping assays. Here, we present a novel statistical method designed to perform such inference and apply this method to a known CNV in a bipolar disorder linkage region. Using Bayesian computations we calculate the posterior probability for carrier status of a CNV in each individual of a sample by jointly analyzing genotype information and hybridization intensity. We model the signal intensity as a mixture of normal distributions, allowing for locus-specific and allele-specific distributions. Using an expectation maximization algorithm we estimate the parameters of these distributions and use these estimates for inferring carrier status of each individual and for the boundaries of the CNV. We applied the method to a sample of 3,512 individuals to a previously described common deletion on 8q24, a region consistently showing linkage to bipolar disorder, and unambiguously inferred 172 heterozygous and 1 homozygous deletion carrier. We observed no significant association between bipolar disorder and carrier status. We carefully assessed the validity of the inferred carrier status and observed no indication of errors. Furthermore, the algorithm precisely identifies the boundaries of the CNV. Finally, we assessed the power of this algorithm to detect shorter CNVs by sub-sampling from the SNPs covered by this deletion, demonstrating that our EM algorithm produces precise estimates of carrier status.

A polygenic model for integration of linkage and pathway information

We introduce an approximate model for linkage curves which accommodates the polygenic structure of complex diseases and accounts for the simultaneous action of closely located genes. The model is extended so that information on biological pathways can be integrated. Using data on rheumatoid arthritis, we describe some of the many applications which the model allows: it can be used to test for residual linkage in the presence of already established loci, to derive a global test for linkage, to test for the relevance of a gene list in terms of linkage and to help in candidate gene prioritization by integration of gene-pathway annotation data.