Family-based association tests for genomewide association scans

With millions of single-nucleotide polymorphisms (SNPs) identified and characterized, genomewide association studies have begun to identify susceptibility genes for complex traits and diseases. These studies involve the characterization and analysis of very-high-resolution SNP genotype data for hundreds or thousands of individuals. We describe a computationally efficient approach to testing association between SNPs and quantitative phenotypes, which can be applied to whole-genome association scans. In addition to observed genotypes, our approach allows estimation of missing genotypes, resulting in substantial increases in power when genotyping resources are limited. We estimate missing genotypes probabilistically using the Lander-Green or Elston-Stewart algorithms and combine high-resolution SNP genotypes for a subset of individuals in each pedigree with sparser marker data for the remaining individuals. We show that power is increased whenever phenotype information for ungenotyped individuals is included in analyses and that high-density genotyping of just three carefully selected individuals in a nuclear family can recover >90% of the information available if every individual were genotyped, for a fraction of the cost and experimental effort. To aid in study design, we evaluate the power of strategies that genotype different subsets of individuals in each pedigree and make recommendations about which individuals should be genotyped at a high density. To illustrate our method, we performed genomewide association analysis for 27 gene-expression phenotypes in 3-generation families (Centre d'Etude du Polymorphisme Humain pedigrees), in which genotypes for ~860,000 SNPs in 90 grandparents and parents are complemented by genotypes for ~6,700 SNPs in a total of 168 individuals. In addition to increasing the evidence of association at 15 previously identified cis-acting associated alleles, our genotype-inference algorithm allowed us to identify associated alleles at 4 cis-acting loci that were missed when analysis was restricted to individuals with the high-density SNP data. Our genotype-inference algorithm and the proposed association tests are implemented in software that is available for free.     

Family-based association mapping in crop species

Identification of allelic variants associated with complex traits provides molecular genetic information associated with variability upon which both artificial and natural selections are based. Family-based association mapping (FBAM) takes advantage of linkage disequilibrium among segregating progeny within crosses and among parents to provide greater power than association mapping and greater resolution than linkage mapping. Herein, we discuss the potential adaption of human family-based association tests and quantitative transmission disequilibrium tests for use in crop species. The rapid technological advancement of next generation sequencing will enable sequencing of all parents in a planned crossing design, with subsequent imputation of genotypes for all segregating progeny. These technical advancements are easily adapted to mating designs routinely used by plant breeders. Thus, FBAM has the potential to be widely adopted for discovering alleles, common and rare, underlying complex traits in crop species.     

Distinct roles of synapsin I and synapsin II during neuronal development.

The synapsins are a family of neuron-specific proteins, associated with the cytoplasmic surface of synaptic vesicles, which have been shown to regulate neurotransmitter release in mature synapses and to accelerate development of the nervous system. Using neuronal cultures from mice lacking synapsin I, synapsin II, or both synapsins I and II, we have now found that synapsin I and synapsin II play distinct roles in neuronal development. Deletion of synapsin II, but not synapsin I, greatly retarded axon formation. Conversely, deletion of synapsin I, but not synapsin II, greatly retarded synapse formation. Remarkably, the deletion of both synapsins led to partial restoration of the wild phenotype. The results suggest that the synapsins play separate but coordinated developmental roles.     

Family-based association studies for next-generation sequencing

An individual's disease risk is determined by the compounded action of both common variants, inherited from remote ancestors, that segregated within the population and rare variants, inherited from recent ancestors, that segregated mainly within pedigrees. Next-generation sequencing (NGS) technologies generate high-dimensional data that allow a nearly complete evaluation of genetic variation. Despite their promise, NGS technologies also suffer from remarkable limitations: high error rates, enrichment of rare variants, and a large proportion of missing values, as well as the fact that most current analytical methods are designed for population-based association studies. To meet the analytical challenges raised by NGS, we propose a general framework for sequence-based association studies that can use various types of family and unrelated-individual data sampled from any population structure and a universal procedure that can transform any population-based association test statistic for use in family-based association tests. We develop family-based functional principal-component analysis (FPCA) with or without smoothing, a generalized T(2), combined multivariate and collapsing (CMC) method, and single-marker association test statistics. Through intensive simulations, we demonstrate that the family-based smoothed FPCA (SFPCA) has the correct type I error rates and much more power to detect association of (1) common variants, (2) rare variants, (3) both common and rare variants, and (4) variants with opposite directions of effect from other population-based or family-based association analysis methods. The proposed statistics are applied to two data sets with pedigree structures. The results show that the smoothed FPCA has a much smaller p value than other statistics.     

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.     

Family-based association analysis with tightly linked markers

Refining genomic regions which have been identified by linkage analysis to contain a disease susceptibility locus has proven to be a challenging task. Detecting association between the disease and a genetic marker can significantly narrow down the candidate region. Since an adequate sample of families is already available from the genome scan, family-based association tests may be used to search for association. The use of haplotypes consisting of tightly linked markers can be more powerful for detecting association than the use of individual markers. An extension of the transmission/disequilibrium test to allow the simultaneous analysis of more than one marker locus is complicated by ambiguity of phase in some families of the sample. The present paper shows that a recently proposed method for the analysis of nuclear families with a single affected child can be viewed as a special application of a more general principle. This observation justifies several modifications, potentially increasing the power, as well as an extension of the method to allow the analysis of general nuclear families. Finally, the problem of missing parental genotypes is discussed.     

Family-based association analysis of theMAPT gene in Parkinson

The MAPT gene has been shown to be associated with several neurodegenerative disorders, including forms of parkinsonism and Parkinson disease (PD), but the results reveal population differences. We investigated the association of 10 single-nucleotide polymorphisms (SNPs) in the region ofMAPT on chromosome 17q21 with PD and age at onset, by using 443 discordant sib pairs in PD from a public dataset (Mayo-Perlegen LEAPS Collaboration). Association with PD was assessed by the FBAT using generalized estimating equations (FBAT-GEE), while the association with age at onset as a quantitative trait was evaluated using the FBAT-logrank statistic. Five SNPs were significantly associated with PD (P < 0.05) in an additive model, and 9 SNPs were associated with PD (P < 0.05) in dominant and recessive models. Interestingly, 8 PD-associated SNPs were also associated with age at onset of PD (P < 0.05) in dominant and recessive models. The SNP most significantly associated with PD and age at onset was rs17649641 (P = 0.015 and 0.021, respectively). Two-SNP haplotypes inferred from rs17563965 and rs17649641 also showed association with PD (P = 0.018) and age at onset (P = 0.026). These results provide further support for the role of MAPT in development of PD.     

Family-based genome-wide association study of frontal theta oscillations identifies potassium channel gene KCNJ6

Event-related oscillations (EROs) represent highly heritable neuroelectric correlates of cognitive processes that manifest deficits in alcoholics and in offspring at high risk to develop alcoholism. Theta ERO to targets in the visual oddball task has been shown to be an endophenotype for alcoholism. A family-based genome-wide association study was performed for the frontal theta ERO phenotype using 634 583 autosomal single nucleotide polymorphisms (SNPs) genotyped in 1560 family members from 117 families densely affected by alcohol use disorders, recruited in the Collaborative Study on the Genetics of Alcoholism. Genome-wide significant association was found with several SNPs on chromosome 21 in KCNJ6 (a potassium inward rectifier channel; KIR3.2/GIRK2), with the most significant SNP at P = 4.7 × 10(-10)). The same SNPs were also associated with EROs from central and parietal electrodes, but with less significance, suggesting that the association is frontally focused. One imputed synonymous SNP in exon four, highly correlated with our top three SNPs, was significantly associated with the frontal theta ERO phenotype. These results suggest KCNJ6 or its product GIRK2 account for some of the variations in frontal theta band oscillations. GIRK2 receptor activation contributes to slow inhibitory postsynaptic potentials that modulate neuronal excitability, and therefore influence neuronal networks.     

Family-based association tests using genotype data with uncertainty

Family-based association studies have been widely used to identify association between diseases and genetic markers. It is known that genotyping uncertainty is inherent in both directly genotyped or sequenced DNA variations and imputed data in silico. The uncertainty can lead to genotyping errors and missingness and can negatively impact the power and Type I error rates of family-based association studies even if the uncertainty is independent of disease status. Compared with studies using unrelated subjects, there are very few methods that address the issue of genotyping uncertainty for family-based designs. The limited attempts have mostly been made to correct the bias caused by genotyping errors. Without properly addressing the issue, the conventional testing strategy, i.e. family-based association tests using called genotypes, can yield invalid statistical inferences. Here, we propose a new test to address the challenges in analyzing case-parents data by using calls with high accuracy and modeling genotype-specific call rates. Our simulations show that compared with the conventional strategy and an alternative test, our new test has an improved performance in the presence of substantial uncertainty and has a similar performance when the uncertainty level is low. We also demonstrate the advantages of our new method by applying it to imputed markers from a genome-wide case-parents association study.     

Family-based tests of association in the presence of linkage

Linkage analysis may not provide the necessary resolution for identification of the genes underlying phenotypic variation. This is especially true for gene-mapping studies that focus on complex diseases that do not exhibit Mendelian inheritance patterns. One positional genomic strategy involves application of association methodology to areas of identified linkage. Detection of association in the presence of linkage localizes the gene(s) of interest to more-refined regions in the genome than is possible through linkage analysis alone. This strategy introduces a statistical complexity when family-based association tests are used: the marker genotypes among siblings are correlated in linked regions. Ignoring this correlation will compromise the size of the statistical hypothesis test, thus clouding the interpretation of test results. We present a method for computing the expectation of a wide range of association test statistics under the null hypothesis that there is linkage but no association. To standardize the test statistic, an empirical variance-covariance estimator that is robust to the sibling marker-genotype correlation is used. This method is widely applicable: any type of phenotypic measure or family configuration can be used. For example, we analyze a deletion in the A2M gene at the 5' splice site of "exon II" of the bait region in Alzheimer disease (AD) discordant sibships. Since the A2M gene lies in a chromosomal region (chromosome 12p) that consistently has been linked to AD, association tests should be conducted under the null hypothesis that there is linkage but no association.     

Genome-wide association study of schizophrenia in Japanese population

Schizophrenia is a devastating neuropsychiatric disorder with genetically complex traits. Genetic variants should explain a considerable portion of the risk for schizophrenia, and genome-wide association study (GWAS) is a potentially powerful tool for identifying the risk variants that underlie the disease. Here, we report the results of a three-stage analysis of three independent cohorts consisting of a total of 2,535 samples from Japanese and Chinese populations for searching schizophrenia susceptibility genes using a GWAS approach. Firstly, we examined 115,770 single nucleotide polymorphisms (SNPs) in 120 patient-parents trio samples from Japanese schizophrenia pedigrees. In stage II, we evaluated 1,632 SNPs (1,159 SNPs of p<0.01 and 473 SNPs of p<0.05 that located in previously reported linkage regions). The second sample consisted of 1,012 case-control samples of Japanese origin. The most significant p value was obtained for the SNP in the ELAVL2 [(embryonic lethal, abnormal vision, Drosophila)-like 2] gene located on 9p21.3 (p = 0.00087). In stage III, we scrutinized the ELAVL2 gene by genotyping gene-centric tagSNPs in the third sample set of 293 family samples (1,163 individuals) of Chinese descent and the SNP in the gene showed a nominal association with schizophrenia in Chinese population (p = 0.026). The current data in Asian population would be helpful for deciphering ethnic diversity of schizophrenia etiology.     

Pathway analysis of a genome-wide association study in schizophrenia

Objective

The aim of this study was to identify the candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms that contribute to schizophrenia susceptibility and to generate a SNP to gene to pathway hypothesis using an analytical pathway-based approach.

Methods

We used schizophrenia GWAS data of the genotypes of 660,259 SNPs in 1378 controls and 1351 cases of European descent after quality control filtering. ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis was applied to the schizophrenia GWAS dataset. The first stage involved the pre-selection of candidate SNPs by linkage disequilibrium analysis and the functional SNP annotation of the most significant SNPs found. The second stage involved the annotation of biological mechanisms for the pre-selected candidate SNPs using improved-gene set enrichment analysis.

Results

ICSNPathway analysis identified fifteen candidate SNPs, ten candidate pathways, and nine hypothetical biological mechanisms. The most strongly associated potential pathways were as follows. First, rs1644731 and rs1644730 to RDH8 to estrogen biosynthetic process (p < 0.001, FDR < 0.001). The genes involved in this pathway are RDH8 and HSD3B1 (p < 0.05). All-trans-retinol dehydrogenase (RDH8) is a visual cycle enzyme that reduces all-trans-retinal to all-trans-retinol in the presence of NADPH. The chemical reactions and pathways involved result in the formation of estrogens, which are C18 steroid hormones that can stimulate the development of female sexual characteristics. Second, rs1146031 to ACVR1 to mesoderm formation and activin binding (p < 0.001, FDR = 0.032, 0.034). Two of 15 candidate genes are known genes associated with schizophrenia: KCNQ2 and APOL2. One of the 10 candidate pathways, estrogen biosynthetic process, is known to be associated with schizophrenia (p < 0.001, FDR < 0.001). However, 13 of candidate genes (RDH8, ACVR1, PSMD9, KCNAB1, SLC17A3, ARCN1, COG7, STAB2, LRPAP1, STAB1, CXCL16, COL4A4, EXOSC3) and 9 of candidate pathways were novel.

Conclusion

By applying ICSNPathway analysis to schizophrenia GWAS data, we identified candidate SNPs, genes like KCNQ2 and APOL2 and pathways involving the estrogen biosynthetic process may contribute to schizophrenia susceptibility. Further analyses are needed to validate the results of this analysis.     

Family-based association study of matrix metalloproteinase-3 and -9 haplotypes with susceptibility to ischemic white matter injury

Susceptibility to ischemic damage to the subcortical white matter of the brain has a strong genetic basis. Dysregulation of matrix metalloproteinases (MMPs) contributes to loss of cerebrovascular integrity and white matter injury. We investigated whether sequence variation in the genes encoding MMP3 and MMP9 is associated with variation in leukoaraiosis volume, determined by magnetic resonance imaging, in non-Hispanic whites and African-Americans using family-based association tests. Seven hundred and fifty-six white and 671 African-American individuals from sibships ascertained through two or more siblings with hypertension were genotyped for 7 and 8 haplotype-tagging polymorphisms in the MMP3 and MMP9 genes, respectively. MMP3 sequence variation was significantly associated with variation in leukoaraiosis volume in Whites. Two common haplotypes with opposing relationships to leukoaraiosis volume were identified. MMP9 sequence variation was also significantly associated with variation in leukoaraiosis volume in both African-Americans and Whites. Different haplotypes contributed to these associations in the two racial groups. These findings add to the growing body of evidence from animal models and human clinical studies suggesting a role of MMPs in ischemic white matter injury. They provide the basis for further investigation of the role of these genes in susceptibility and/or progression to clinical disease.     

Association study between monoamine oxidase A (MAOA) gene polymorphisms and schizophrenia: lack of association with schizophrenia and possible association with affective disturbances of schizophrenia

Monoamine oxidase A (MAOA) catalyzes monoamine neurotransmitters including dopamine, 5-hydroxytryptamine (5-HT, serotonin), and norepinephrine. MAOA also plays a key role in emotional regulation. The aim of this study was to investigate the associations between the exonic single nucleotide polymorphisms (SNPs) of the MAOA gene located on the X chromosome and schizophrenia. We also analyzed the relationships between these SNPs and the common clinical symptoms of schizophrenia such as persecutory delusion, auditory hallucinations, affective disturbances, and poor concentration. Two hundred seventy five Korean schizophrenia patients and 289 control subjects were recruited. Three SNPs [rs6323 (Arg294Arg), rs1137070 (Asp470Asp), and rs3027407 (3′-untranslated region)] of the MAOA gene were selected and genotyped by direct sequencing. The common clinical symptoms of schizophrenia according to the Operation Criteria Checklist were analyzed. Three examined SNPs showed no associations with male and female schizophrenia, respectively (p > 0.05). In the analysis of the common clinical symptoms of schizophrenia patients, three examined SNPs were associated with affective disturbances, especially restricted affect and blunted affect in male schizophrenia, respectively (restricted affect, p = 0.002, OR = 2.71, 95 % CI 1.45–5.00; blunted affect, p = 0.009, OR 2.25, 95 % CI 1.22–4.12). The SNPs were not associated with other clinical symptoms of schizophrenia (persecutory delusion, auditory hallucinations, and poor concentration). These results suggest that exonic SNPs (rs6323, rs1137070, and rs3027407) of the MAOA gene may be contributed to affective disturbances of Korean males schizophrenia, especially restricted affect and blunted affect.     

Genome-wide association study of treatment refractory schizophrenia in Han Chinese

We report the first genome-wide association study of a joint analysis using 795 Han Chinese individuals with treatment-refractory schizophrenia (TRS) and 806 controls. Three loci showed suggestive significant association with TRS were identified. These loci include: rs10218843 (P = 3.04 × 10(-7)) and rs11265461 (P = 1.94 × 10(-7)) are adjacent to signaling lymphocytic activation molecule family member 1 (SLAMF1); rs4699030 (P = 1.94 × 10(-6)) and rs230529 (P = 1.74 × 10(-7)) are located in the gene nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 (NFKB1); and rs13049286 (P = 3.05 × 10(-5)) and rs3827219 (P = 1.66 × 10(-5)) fall in receptor-interacting serine/threonine-protein kinase 4 (RIPK4). One isolated single nucleotide polymorphism (SNP), rs739617 (P = 3.87 × 10(-5)) was also identified to be associated with TRS. The -94delATTG allele (rs28362691) located in the promoter region of NFKB1 was identified by resequencing and was found to associate with TRS (P = 4.85 × 10(-6)). The promoter assay demonstrated that the -94delATTG allele had a significant lower promoter activity than the -94insATTG allele in the SH-SY5Y cells. This study suggests that rs28362691 in NFKB1 might be involved in the development of TRS.     

基于核心家系的EGR3基因与精神分裂症的关联研究

研究表明位于染色体8p21.3区域的EGR3(Early growth response 3)是精神分裂症(Schizophrenia)的重要易感基因, 然而, 仍有两个病例-对照研究未能验证上述发现。为了研究EGR3基因在我国患者中是否与疾病关联, 文章在中国汉族的核心家系中选择EGR3基因座位上的5个SNPs位点(rs1996147、rs1877670、rs3750192、rs35201266和rs7009708)进行基因分型和传递不平衡检验(Transmission disequilibrium test, TDT)。结果表明遗传标记rs1996147和rs3750192分别显示出显著的传递不平衡(c²>4.40, P<0.05)。在连锁不平衡分析中, 由2个(rs3750192和rs35201266)、3个(rs1877670、rs3750192和rs7009708)以及4个(rs1996147、rs1877670、rs3750192和rs7009708)SNPs位点构建的单倍型均显示与精神分裂症显著性关联(c²>7.10, 整体P<0.05)。总之, EGR3基因与中国汉族人群精神分裂症遗传易感性相关, 后续关于EGR3基因进一步的功能研究将会更好的帮助我们了解该基因在疾病病理学机制中的作用。     

基于核心家系的EGR3基因与精神分裂症的关联研究

研究表明位于染色体8p21.3区域的EGR3(Early growth response 3)是精神分裂症(Schizophrenia)的重要易感基因,然而,仍有两个病例-对照研究未能验证上述发现。为了研究EGR3基因在我国患者中是否与疾病关联,文章在中国汉族的核心家系中选择EGR3基因座位上的5个SNPs位点(rs1996147、rs1877670、rs3750192、rs35201266和rs7009708)进行基因分型和传递不平衡检验(Transmission disequilibrium test,TDT)。结果表明遗传标记rs1996147和rs3750192分别显示出显著的传递不平衡(2>4.40,P<0.05)。在连锁不平衡分析中,由2个(rs3750192和rs35201266)、3个(rs1877670、rs3750192和rs7009708)以及4个(rs1996147、rs1877670、rs3750192和rs7009708)SNPs位点构建的单倍型均显示与精神分裂症显著性关联(2>7.10,整体P<0.05)。总之,EGR3基因与中国汉族人群精神分裂症遗传易感性相关,后续关于EGR3基因进一步的功能研究将会更好的帮助我们了解该基因在疾病病理学机制中的作用。     

Brain-derived neurotrophic factor and risk of schizophrenia: an association study and meta-analysis

Brain-derived neurotrophic factor (BDNF) is the most widely distributed neurotrophin in the central nervous system (CNS), and performs many biological functions such as neural survival, differentiation, and plasticity. Previous studies have suggested that variants in the BDNF gene increase the risk of schizophrenia. In this study, we genotyped one (GT)n dinucleotide repeat and three SNPs (rs6265, rs2030324, and rs2883187) in a Chinese sample (617 cases and 672 controls). In addition, we performed an updated meta-analysis based on 16 population-based case-control studies examining association between rs6265 and schizophrenia. In single-locus analysis, no significant association was found between BDNF polymorphisms and schizophrenia in our subjects. The meta-analysis based on Asian and Caucasian subjects did not give positive result that rs6265 is associated with schizophrenia. However, haplotype analysis found a common four-locus haplotype is protective against schizophrenia (Case 3.1% vs Control 7%, p=0.0011). Our data provides evidence that BDNF is a susceptibility gene for schizophrenia in Chinese subjects.     

Family-based tests of association and linkage that use unaffected sibs, covariates, and interactions

We extend the methodology for family-based tests of association and linkage to allow for both variation in the phenotypes of subjects and incorporation of covariates into general-score tests of association. We use standard association models for a phenotype and any number of predictors. We then construct a score statistic, using likelihoods for the distribution of phenotype, given genotype. The distribution of the score is computed as a function of offspring genotypes, conditional on parental genotypes and trait values for offspring and parents. This approach provides a natural extension of the transmission/disequilibrium test to any phenotype and to multiple genes or environmental factors and allows the study of gene-gene and gene-environment interaction. When the trait varies among subjects or when covariates are included in the association model, the score statistic depends on one or more nuisance parameters. We suggest two approaches for obtaining parameter estimates: (1) choosing the estimate that minimizes the variance of the test statistic and (2) maximizing the statistic over a nuisance parameter and using a corrected P value. We apply our methods to a sample of families with attention-deficit/hyperactivity disorder and provide examples of how covariates and gene-environment and gene-gene interactions can be incorporated.