The use of pedigree, sib-pair and association studies of common diseases for genetic mapping and epidemiology

Rare POLN mutations confer risk for familial nasopharyngeal carcinoma through weakened Epstein-Barr virus lytic replication

BACKGROUND

Nasopharyngeal carcinoma (NPC) exhibits significant familial aggregation; however, its susceptibility genes are largely unknown. Thus, this study aimed to identify germline mutations that might contribute to the risk of familial NPC, and explore their biological functions.

METHODS

Whole-exome sequencing was performed in 13 NPC pedigrees with multiple cases. Mutations co-segregated with disease status were further validated in a cohort composed of 563 probands from independent families, 2,953 sporadic cases, and 3,175 healthy controls. Experimental studies were used to explore the functions of susceptibility genes and their disease-related mutations.

FINDINGS

The three rare missense mutations in POLN (DNA polymerase nu) gene, P577L, R303Q, and F545C, were associated with familial NPC risk (5/576 [0·87%] in cases vs. 2/3374 [0·059%] in healthy controls with an adjusted OR of 44·84 [95% CI:3·91-514·34, p = 2·25 × 10^-3]). POLN was involved in Epstein-Barr virus (EBV) lytic replication in NPC cells in vitro. POLN promoted viral DNA replication, immediate-early and late lytic gene expression, and progeny viral particle production, ultimately affecting the proliferation of host cells. The three mutations were located in two pivotal functional domains and were predicted to alter the protein stability of POLN in silico. Further assays demonstrated that POLN carrying any of the three mutations displayed reduced protein stability and decreased expression levels, thereby impairing its ability to promote complete EBV lytic replication and facilitate cell survival.

INTERPRETATION

We identified a susceptibility gene POLN for familial NPC and elucidated its function.

FUNDING

This study was funded by the National Key Research and Development Program of China (2021YFC2500400); the National Key Research and Development Program of China (2020YFC1316902); the Basic and Applied Basic Research Foundation of Guangdong Province, China (2021B1515420007); the National Natural Science Foundation of China (81973131); the National Natural Science Foundation of China (82003520); the National Natural Science Foundation of China (81903395).

Evaluating endophenotypes for bipolar disorder

BACKGROUND

Phenotypic heterogeneity is a major impediment to the elucidation of the neurobiology and genetics of bipolar disorder. Endophenotype could help in reducing heterogeneity by defining biological traits that are more direct expressions of gene effects. The aim of this review is to examine the recent literature on clinical, epidemiological, neurobiological, and genetic findings and to select and evaluate candidate endophenotypes for bipolar disorder. Evaluating putative endophenotype could be helpful in better understanding the neurobiology of bipolar disorder by improving the definition of bipolar-related phenotypes in genetic studies. In this manner, research on endophenotypes could be useful to improve psychopathological diagnostics in the long-run by dissecting psychiatric macro phenotypes into biologically valid components.

MAIN BODY

The associations among the psychopathological and biological endophenotypes are discussed with respect to specificity, temporal stability, heritability, familiarity, and clinical and biological plausibility. Numerous findings regarding brain function, brain structure, neuropsychology and altered neurochemical pathways in patients with bipolar disorder and their relatives deserve further investigation. Overall, major findings suggest a developmental origin of this disorder as all the candidate endophenotypes that we have been able to select are present both in the early stages of the disorder as well as in subjects at risk.

CONCLUSIONS

Among the stronger candidate endophenotypes, we suggest circadian rhythm instability, dysmodulation of emotion and reward, altered neuroimmune state, attention and executive dysfunctions, anterior cingulate cortex thickness and early white matter abnormalities. In particular, early white matter abnormalities could be the result of a vulnerable brain on which new stressors are added in young adulthood which favours the onset of the disorder. Possible pathways that lead to a vulnerable brain are discussed starting from the data about molecular and imaging endophenotypes of bipolar disorder.

Improvement Effect of 5-Aminolevulinic Acid on Hyperlipidemia in Miniature Schnauzer Dogs: An Open Study in 5 Cases of One Pedigree

This is the first study to examine the long-term effect of 5-aminolevulinic acid mainly on serum lipoproteins in dogs with hyperlipidemia. We studied 5 Miniature Schnauzer cases whose fasting serum total triglyceride and very-low-density lipoprotein of triglyceride levels were extremely high (635 ± 116 and 520 ± 92 mg/dL, respectively). Although the total cholesterol values were normal, the very-low-density lipoprotein of cholesterol level was high (49 ± 7 mg/dL). Each dog received a 5-aminolevulinic acid supplement (5 mg/day) orally for 6 months. The mean values of total triglyceride, very-low-density lipoprotein of both triglyceride and cholesterol decreased significantly after the treatment period (319 ± 29, 245 ± 18, and 27 ± 2 mg/dL, respectively, P < 0.05). Our present results may present evidence that 5-ALA administration contributes to improvement of hyperlipidemia in Miniature Schnauzer.

Rediscovering the value of families for psychiatric genetics research

As it is likely that both common and rare genetic variation are important for complex disease risk, studies that examine the full range of the allelic frequency distribution should be utilized to dissect the genetic influences on mental illness. The rate limiting factor for inferring an association between a variant and a phenotype is inevitably the total number of copies of the minor allele captured in the studied sample. For rare variation, with minor allele frequencies of 0.5% or less, very large samples of unrelated individuals are necessary to unambiguously associate a locus with an illness. Unfortunately, such large samples are often cost prohibitive. However, by using alternative analytic strategies and studying related individuals, particularly those from large multiplex families, it is possible to reduce the required sample size while maintaining statistical power. We contend that using whole genome sequence (WGS) in extended pedigrees provides a cost-effective strategy for psychiatric gene mapping that complements common variant approaches and WGS in unrelated individuals. This was our impetus for forming the "Pedigree-Based Whole Genome Sequencing of Affective and Psychotic Disorders" consortium. In this review, we provide a rationale for the use of WGS with pedigrees in modern psychiatric genetics research. We begin with a focused review of the current literature, followed by a short history of family-based research in psychiatry. Next, we describe several advantages of pedigrees for WGS research, including power estimates, methods for studying the environment, and endophenotypes. We conclude with a brief description of our consortium and its goals.

Population structure in genetic studies: Confounding factors and mixed models

A genome-wide association study (GWAS) seeks to identify genetic variants that contribute to the development and progression of a specific disease. Over the past 10 years, new approaches using mixed models have emerged to mitigate the deleterious effects of population structure and relatedness in association studies. However, developing GWAS techniques to accurately test for association while correcting for population structure is a computational and statistical challenge. Using laboratory mouse strains as an example, our review characterizes the problem of population structure in association studies and describes how it can cause false positive associations. We then motivate mixed models in the context of unmodeled factors.

Early Diagnosis of Sepsis: Is an Integrated Omics Approach the Way Forward?

Sepsis remains one of the leading causes of death in the USA and it is expected to get worse as the population ages. Moreover, the standard of care, which recommends aggressive treatment with appropriate antibiotics, has led to an increase in multiple drug-resistant organisms. There is a dire need for the development of new antibiotics, improved antibiotic stewardship, and therapies that treat the host response. Development of new sepsis therapeutics has been a disappointment as no drugs are currently approved to treat the various complications from sepsis. Much of the failure has been blamed on animal models that do not accurately reflect the course of the disease. However, recent improvements in metabolomic, transcriptomic, genomic, and proteomic platforms have allowed for a broad-spectrum look at molecular changes in the host response using clinical samples. Integration of these multi-omic datasets allows researchers to perform systems biology approaches to identify novel pathophysiology of the disease. In this review, we highlight what is currently known about sepsis and how integrative omics has identified new diagnostic and predictive models of sepsis as well as novel mechanisms. These changes may improve patient care as well as guide future preclinical analysis of sepsis.

Next-generation sequencing in drug development: target identification and genetically stratified clinical trials

Next-generation sequencing (NGS) enabled high-throughput analysis of genotype-phenotype relationships on human populations, ushering in a new era of genetics-informed drug development. The year 2017 was remarkable, with the first FDA-approved gene therapy for cancer (Kymriah™) and for inherited diseases (LUXTURNA™), the first multiplex NGS panel for companion diagnostics (MSK-IMPACT™) and the first drug targeting a genetic signature rather than a disease (Keytruda^®). We envision that population-scale NGS with paired electronic health records (EHRs) will become a routine measure in the drug development process for the identification of novel drug targets, and that genetically stratified clinical trials could be widely adopted to improve power in precision-medicine-guided drug development.

Relationship between Deleterious Variation, Genomic Autozygosity, and Disease Risk: Insights from The 1000 Genomes Project

Genomic regions of autozygosity (ROAs) represent segments of individual genomes that are homozygous for haplotypes inherited identical-by-descent (IBD) from a common ancestor. ROAs are nonuniformly distributed across the genome, and increased ROA levels are a reported risk factor for numerous complex diseases. Previously, we hypothesized that long ROAs are enriched for deleterious homozygotes as a result of young haplotypes with recent deleterious mutations-relatively untouched by purifying selection-being paired IBD as a consequence of recent parental relatedness, a pattern supported by ROA and whole-exome sequence data on 27 individuals. Here, we significantly bolster support for our hypothesis and expand upon our original analyses using ROA and whole-genome sequence data on 2,436 individuals from The 1000 Genomes Project. Considering CADD deleteriousness scores, we reaffirm our previous observation that long ROAs are enriched for damaging homozygotes worldwide. We show that strongly damaging homozygotes experience greater enrichment than weaker damaging homozygotes, while overall enrichment varies appreciably among populations. Mendelian disease genes and those encoding FDA-approved drug targets have significantly increased rates of gain in damaging homozygotes with increasing ROA coverage relative to all other genes. In genes implicated in eight complex phenotypes for which ROA levels have been identified as a risk factor, rates of gain in damaging homozygotes vary across phenotypes and populations but frequently differ significantly from non-disease genes. These findings highlight the potential confounding effects of population background in the assessment of associations between ROA levels and complex disease risk, which might underlie reported inconsistencies in ROA-phenotype associations.

Weighted likelihood inference of genomic autozygosity patterns in dense genotype data

Background

Genomic regions of autozygosity (ROA) arise when an individual is homozygous for haplotypes inherited identical-by-descent from ancestors shared by both parents. Over the past decade, they have gained importance for understanding evolutionary history and the genetic basis of complex diseases and traits. However, methods to infer ROA in dense genotype data have not evolved in step with advances in genome technology that now enable us to rapidly create large high-resolution genotype datasets, limiting our ability to investigate their constituent ROA patterns.

Methods

We report a weighted likelihood approach for inferring ROA in dense genotype data that accounts for autocorrelation among genotyped positions and the possibilities of unobserved mutation and recombination events, and variability in the confidence of individual genotype calls in whole genome sequence (WGS) data.

Results

Forward-time genetic simulations under two demographic scenarios that reflect situations where inbreeding and its effect on fitness are of interest suggest this approach is better powered than existing state-of-the-art methods to infer ROA at marker densities consistent with WGS and popular microarray genotyping platforms used in human and non-human studies. Moreover, we present evidence that suggests this approach is able to distinguish ROA arising via consanguinity from ROA arising via endogamy. Using subsets of The 1000 Genomes Project Phase 3 data we show that, relative to WGS, intermediate and long ROA are captured robustly with popular microarray platforms, while detection of short ROA is more variable and improves with marker density. Worldwide ROA patterns inferred from WGS data are found to accord well with those previously reported on the basis of microarray genotype data. Finally, we highlight the potential of this approach to detect genomic regions enriched for autozygosity signals in one group relative to another based upon comparisons of per-individual autozygosity likelihoods instead of inferred ROA frequencies.

Conclusions

This weighted likelihood ROA inference approach can assist population- and disease-geneticists working with a wide variety of data types and species to explore ROA patterns and to identify genomic regions with differential ROA signals among groups, thereby advancing our understanding of evolutionary history and the role of recessive variation in phenotypic variation and disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-4312-3) contains supplementary material, which is available to authorized users.

Genome-Wide Association Studies: Progress in Identifying Genetic Biomarkers in Common, Complex Diseases

Novel, comprehensive approaches for biomarker discovery and validation are urgently needed. One particular area of methodologic need is for discovery of novel genetic biomarkers in complex diseases and traits. Here, we review recent successes in the use of genome wide association (GWA) approaches to identify genetic biomarkers in common human diseases and traits. Such studies are yielding initial insights into the allelic architecture of complex traits. In general, it appears that complex diseases are associated with many common polymorphisms, implying profound genetic heterogeneity between affected individuals.

Disease-Concordant Twins Empower Genetic Association Studies

Genome-wide association studies with moderate sample sizes are underpowered, especially when testing SNP alleles with low allele counts, a situation that may lead to high frequency of false-positive results and lack of replication in independent studies. Related individuals, such as twin pairs concordant for a disease, should confer increased power in genetic association analysis because of their genetic relatedness. We conducted a computer simulation study to explore the power advantage of the disease-concordant twin design, which uses singletons from disease-concordant twin pairs as cases and ordinary healthy samples as controls. We examined the power gain of the twin-based design for various scenarios (i.e., cases from monozygotic and dizygotic twin pairs concordant for a disease) and compared the power with the ordinary case-control design with cases collected from the unrelated patient population. Simulation was done by assigning various allele frequencies and allelic relative risks for different mode of genetic inheritance. In general, for achieving a power estimate of 80%, the sample sizes needed for dizygotic and monozygotic twin cases were one half and one fourth of the sample size of an ordinary case-control design, with variations depending on genetic mode. Importantly, the enriched power for dizygotic twins also applies to disease-concordant sibling pairs, which largely extends the application of the concordant twin design. Overall, our simulation revealed a high value of disease-concordant twins in genetic association studies and encourages the use of genetically related individuals for highly efficiently identifying both common and rare genetic variants underlying human complex diseases without increasing laboratory cost.

A genome-wide screen for acrophobia susceptibility loci in a Finnish isolate

Acrophobia, an abnormal fear of heights, is a specific phobia characterized as apprehension cued by the occurrence or anticipation of elevated spaces. It is considered a complex trait with onset influenced by both genetic and environmental factors. Identification of genetic risk variants would provide novel insight into the genetic basis of the fear of heights phenotype and contribute to the molecular-level understanding of its aetiology. Genetic isolates may facilitate identification of susceptibility alleles due to reduced genetic heterogeneity. We took advantage of an internal genetic isolate in Finland in which a distinct acrophobia phenotype appears to be segregating in pedigrees originally ascertained for schizophrenia. We conducted parametric, nonparametric, joint linkage and linkage disequilibrium analyses using a microsatellite marker panel, genotyped in families to search for chromosomal regions correlated with acrophobia. Our results implicated a few regions with suggestive evidence for linkage on chromosomes 4q28 (LOD = 2.17), 8q24 (LOD = 2.09) and 13q21-q22 (LOD = 2.22). We observed no risk haplotypes shared between different families. These results suggest that genetic predisposition to acrophobia in this genetic isolate is unlikely to be mediated by a small number of shared high-risk alleles, but rather has a complex genetic architecture.

Introduction to the analysis of next generation sequencing data and its application to venous thromboembolism

Despite knowledge of various inherited risk factors associated with venous thromboembolism (VTE), no definite cause can be found in about 50% of patients. The application of data-driven searches such as GWAS has not been able to identify genetic variants with implications for clinical care, and unexplained heritability remains. In the past years, the development of several so-called next generation sequencing (NGS) platforms is offering the possibility of generating fast, inexpensive and accurate genomic information. However, so far their application to VTE has been very limited. Here we review basic concepts of NGS data analysis and explore the application of NGS technology to VTE. We provide both computational and biological viewpoints to discuss potentials and challenges of NGS-based studies.

Assessing the quality of published genetic association studies in meta-analyses: the quality of genetic studies (Q-Genie) tool

Background

Advances in genomics technology have led to a dramatic increase in the number of published genetic association studies. Systematic reviews and meta-analyses are a common method of synthesizing findings and providing reliable estimates of the effect of a genetic variant on a trait of interest. However, summary estimates are subject to bias due to the varying methodological quality of individual studies. We embarked on an effort to develop and evaluate a tool that assesses the quality of published genetic association studies. Performance characteristics (i.e. validity, reliability, and item discrimination) were evaluated using a sample of thirty studies randomly selected from a previously conducted systematic review.

Results

The tool demonstrates excellent psychometric properties and generates a quality score for each study with corresponding ratings of ‘low’, ‘moderate’, or ‘high’ quality. We applied our tool to a published systematic review to exclude studies of low quality, and found a decrease in heterogeneity and an increase in precision of summary estimates.

Conclusion

This tool can be used in systematic reviews to inform the selection of studies for inclusion, to conduct sensitivity analyses, and to perform meta-regressions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0211-2) contains supplementary material, which is available to authorized users.

Molecular genetic studies of ADHD and its candidate genes: a review

Attention-deficit/hyperactivity disorder (ADHD) is a common childhood-onset psychiatric disorder with high heritability. In recent years, numerous molecular genetic studies have been published to investigate susceptibility loci for ADHD. These results brought valuable candidates for further research, but they also presented great challenge for profound understanding of genetic data and general patterns of current molecular genetic studies of ADHD since they are scattered and heterogeneous. In this review, we presented a retrospective review of more than 300 molecular genetic studies for ADHD from two aspects: (1) the main achievements of various studies were summarized, including linkage studies, candidate-gene association studies, genome-wide association studies and genome-wide copy number variation studies, with a special focus on general patterns of study design and common sample features; (2) candidate genes for ADHD have been systematically evaluated in three ways for better utilization. The thorough summary of the achievements from various studies will provide an overview of the research status of molecular genetics studies for ADHD. Meanwhile, the analysis of general patterns and sample characteristics on the basis of these studies, as well as the integrative review of candidate ADHD genes, will propose new clues and directions for future experiment design.

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.

Autism genetics: searching for specificity and convergence

Advances in genetics and genomics have improved our understanding of autism spectrum disorders. As many genes have been implicated, we look to points of convergence among these genes across biological systems to better understand and treat these disorders.

Autism genetics: searching for specificity and convergence

Advances in genetics and genomics have improved our understanding of autism spectrum disorders. As many genes have been implicated, we look to points of convergence among these genes across biological systems to better understand and treat these disorders.

Cerebral vasospasm after sub-arachnoid hemorrhage as a clinical predictor and phenotype for genetic association study

BACKGROUND

A typology of cerebral vasospasm has been proposed based on distinct clinical manifestations: delayed cerebral ischemia, symptomatic 'vasospasm', angiographic vasospasm, and transcranial Doppler vasospasm. We examined each distinct clinical manifestation in a nonparametric genetic association study.

AIMS

The purpose of this study was to examine and compare each four distinct acute clinical manifestations and test its perspectives in genetic association studies.

METHODS

Two hundred forty-five Caucasian patients with sub-arachnoid hemorrhage were evaluated for these four distinct clinical manifestations along with 906 600 single-nucleotide polymorphisms across the human genome.

RESULTS

The four clinical manifestations were significantly associated with each other as P-values ranged from 3·31 × 10(-4) to 8·10 × 10(-15) . Transcranial Doppler vasospasm showed significant genetic association with single nucleotide polymorphism (SNP) (rs999662, P = 3·39 × 10(-8) ). Statistical P-value of rs999662 in association with delayed cerebral ischemia, symptomatic 'vasospasm', and angiographic vasospasm was 0·0017, 0·0017, and 0·19, respectively.

CONCLUSIONS

Despite different criteria for each of the four clinical manifestations, they are significantly associated with each other. Our results suggest transcranial Doppler vasospasm may be an appropriate intermediate but still clinically relevant phenotype for genetic association studies. Association with SNP rs999662 indicates a potential role for the region containing the solute carrier family 12 member 3 (SLC12A3) gene in transcranial Doppler vasospasm following sub-arachnoid hemorrhage.

Familial and large-scale case-control studies identify genes associated with nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is an epithelial malignancy and has a remarkable geographic distribution, which is highly prevalent in southern China, Southeast Asia, and North Africa. Although most of the NPC are sporadic cases, the familial clustering of NPC has been demonstrated worldwide. Accumulating studies have proposed that the etiology of NPC is multi-stage and multi-factorial, involving genetic lesions, Epstein-Barr virus infection, and environmental exposure. Genetic variations result in differences in gene function, which in turn lead to different susceptibility to disease. Many studies have been carried out to dissect the genetic variants that contribute to NPC susceptibility. This article reviews the current progress of genetic studies to identify genes associated with NPC, focusing on the familial linkage and large-scale case-control study designs.

Linkage analysis in the next-generation sequencing era

Linkage analysis was developed to detect excess co-segregation of the putative alleles underlying a phenotype with the alleles at a marker locus in family data. Many different variations of this analysis and corresponding study design have been developed to detect this co-segregation. Linkage studies have been shown to have high power to detect loci that have alleles (or variants) with a large effect size, i.e. alleles that make large contributions to the risk of a disease or to the variation of a quantitative trait. However, alleles with a large effect size tend to be rare in the population. In contrast, association studies are designed to have high power to detect common alleles which tend to have a small effect size for most diseases or traits. Although genome-wide association studies have been successful in detecting many new loci with common alleles of small effect for many complex traits, these common variants often do not explain a large proportion of disease risk or variation of the trait. In the past, linkage studies were successful in detecting regions of the genome that were likely to harbor rare variants with large effect for many simple Mendelian diseases and for many complex traits. However, identifying the actual sequence variant(s) responsible for these linkage signals was challenging because of difficulties in sequencing the large regions implicated by each linkage peak. Current 'next-generation' DNA sequencing techniques have made it economically feasible to sequence all exons or the whole genomes of a reasonably large number of individuals. Studies have shown that rare variants are quite common in the general population, and it is now possible to combine these new DNA sequencing methods with linkage studies to identify rare causal variants with a large effect size. A brief review of linkage methods is presented here with examples of their relevance and usefulness for the interpretation of whole-exome and whole-genome sequence data.

Genetic modifiers of sickle cell disease

Sickle cell disease is one of the best characterized human monogenic disorders. Complex genotype/phenotype correlations clearly demonstrate the interaction of multiple genetic and environmental factors. In the last 20 years, scientific research has applied genetic approaches to dissect some of these modifiers. This review highlights the more recent genetic association studies that have been applied to unravel the genetic modifiers of sickle cell disease including Hb F genetics, and the key genetic variants identified. Illumination of such modifying factors may guide future therapeutic interventions and improve prediction of disease severity, with implications for genetic counseling, prenatal diagnosis and implementation of high risk therapy.

Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N=1198) using genome-wide search

The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural magnetic resonance imaging and genome-wide genotypes were acquired from two large cohorts, the Alzheimer's Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at single-nucleotide polymorphism rs163030 in the ADNI discovery sample (P=2.36 × 10⁻⁶) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79 and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.

Computer-based genealogy reconstruction in founder populations

This paper describes a software tool that reconstructs entire genealogies from data collected from different and heterogeneous sources, including municipal and parish records archived over centuries. The tool exploits a record linkage algorithm relying on a rule-based data matching approach. It applies a general strategy for managing the ambiguities due to missing, imprecise or erroneous input data. The process follows an iterative approach that combines automatic pedigree reconstruction with software-empowered human data revision to improve the quality and the accuracy of the results and to optimize the matching rules. The paper discusses the results obtained by reconstructing the entire genealogy of the population of the Val Borbera, a geographically isolated valley in Northern Italy. The genealogy could be reconstructed from data going back as far as the XVI century. The resulting pedigree includes 75,994 trios, 58.9% of which belonging to a unique big family, reconstructed over 13 generations.

Association of tumour necrosis factor-alpha -308 G/A polymorphism with primary open-angle glaucoma

BACKGROUND

Tumour necrosis factor-alpha (TNF-α) is an important proinflammatory cytokine driving axonal degeneration and retinal ganglion cell apoptosis in glaucoma. The aim of the study was to evaluate the association of TNF-α -308 G/A and -238 G/A polymorphisms with primary open-angle glaucoma (POAG).

DESIGN

A prospective, case-control study, university hospital setting.

PARTICIPANTS

Eighty-six POAG patients and 193 healthy unrelated controls.

METHODS

TNF-α polymorphisms were screened by using direct gene sequencing.

MAIN OUTCOME MEASURES

Frequency of TNF-α -308 G/A and TNF-α -238 G/A promoter polymorphisms in glaucoma and healthy subjects.

RESULTS

The frequencies of TNF-α -308 GA genotype and 'A' allele were higher in patients with POAG (22.1% and 12.2%, respectively) in comparison with the control group (10.9% and 6%, respectively) (P = 0.046 and 0.02, respectively), with odds ratios of 2.45 (P = 0.01, 95% CI = 1.23-4.87) and 2.19 (P = 0.013, 95% CI = 1.18-4.08), respectively. Genotype distribution of the TNF-α -238 variants did not yield a statistically significant difference between the two groups (P = 0.87).

CONCLUSION

TNF-α -308 G/A polymorphism seems to be associated with POAG in Turkish population. However, population-based studies with large number of subjects and long-term follow-up are needed to verify the association of TNF-α -308 G/A polymorphism with glaucoma susceptibility.

The genetic aspects of multiple sclerosis

The epidemiology of multiple sclerosis has been extensively investigated and two features have consistently emerged: marked geographical variation in prevalence and substantial familial clustering. At first sight, geographic variation would seem to imply an environmental cause for the disease, while familial clustering would seem to suggest that genetic factors have the predominant etiological effect. However, given that geographic variation in prevalence could result from variation in the frequency of genetic risk alleles and that familial clustering might result from shared environmental exposure rather than shared genetic risk alleles, it is clear that these crude inferences are unreliable. Epidemiologists have been resourceful in their attempts to resolve this apparent conflict between “nurture and nature” and have employed a whole variety of sophisticated methods to try and untangle the etiology of multiple sclerosis. The body of evidence that has emerged from these efforts has formed the foundation for decades of research seeking to identify relevant genes and this is the obvious place to start any consideration of the genetics of multiple sclerosis.

Population-based proband-oriented pedigree information system: application to hypertension with population-based screening data (KCIS No. 25)

OBJECTIVE

To develop a population-based proband-oriented pedigree information system that can be easily applied to various diseases in genetic epidemiological studies, making allowance for the capture of theoretical family relationships. DESIGNS AND MEASUREMENTS: A population-based proband-oriented pedigree information system with ties of consanguinity based on both population-based household registry data and Keelung Community Integrated Screening data was proposed to build a comprehensive extended family pedigree structure to accommodate a series of genetic studies on different diseases. We also developed an algorithm to efficiently assess how well theoretical family relationships affecting the occurrence of diseases across three generations with respect to the relative relationship score, a quantitative indicator of genetic influence, were captured.

RESULTS

We applied this population-based proband-oriented pedigree information system to estimate the rate of hypertension with various relative relationships given the selection of probands. The degree of capturing complete familial relationships was assessed for three generations. The risk for early onset of hypertension was proportional to the proband-oriented relative relationship score with 2% increased risk and 1% correction for incomplete capture.

CONCLUSIONS

The population-based proband-oriented pedigree information system is powerful and can support various genetic descriptive and analytic epidemiological studies.

Genetic analyses of interferon pathway-related genes reveal multiple new loci associated with systemic lupus erythematosus

OBJECTIVE

The overexpression of interferon (IFN)-inducible genes is a prominent feature of systemic lupus erythematosus (SLE); it serves as a marker for active and more severe disease, and is also observed in other autoimmune and inflammatory conditions. This study was undertaken to investigate the genetic variations responsible for sustained activation of IFN-responsive genes in SLE.

METHODS

We systematically evaluated association of SLE with a total of 1,754 IFN pathway-related genes, including IFN-inducible genes known to be differentially expressed in SLE patients and their direct regulators. We used a 3-stage study design in which 2 cohorts (total of 939 SLE cases and 3,398 controls) were analyzed independently and jointly for association with SLE, and the results were adjusted for the number of comparisons.

RESULTS

A total of 15,166 single-nucleotide polymorphisms (SNPs) passed all quality control filters; 305 of these SNPs demonstrated replicated association with SLE in both cohorts. Nine variants were further genotyped for confirmation in an average of 1,316 independent SLE cases and 3,215 independent controls. Association with SLE was confirmed for several genes, including those for the transmembrane receptor CD44 (CD44 [rs507230]; P = 3.98 × 10⁻¹²), the cytokine pleiotrophin (PTN [rs919581]; P = 5.38 × 10⁻⁴), the heat-shock protein DnaJ (DNAJA1 [rs10971259]; P = 6.31 × 10⁻³), and the nuclear import protein karyopherin α1 (KPNA [rs6810306]; P = 4.91 × 10⁻²).

CONCLUSION

This study expands the number of candidate genes that have been shown to be associated with SLE and highlights potential of pathway-based approaches for gene discovery. Identification of the causal alleles will help elucidate the molecular mechanisms responsible for activation of the IFN system in SLE.

Genomic polymorphisms in sickle cell disease: implications for clinical diversity and treatment

Sickle cell disease (SCD) is one of the best characterized human monogenic disorders. The development of molecular biology allowed the identification of several genomic polymorphisms responsible for its clinical diversity. Research on the first genetic modulators of SCD, such as coinheritance of α-thalassemia and haplotypes in the β-globin gene cluster, have been followed by studies associating single nucleotide polymorphisms (SNPs) with variable risks for stroke, leg ulceration, pulmonary hypertension, priapism and osteonecrosis, with differences in the response to hydroxyurea, and with variability in the management of pain. Furthermore, multigenic analyses based on genome-wide association studies have shed light on the importance of the TGF-β superfamily and oxidative stress to the pathogenesis of complex traits in SCD, and may guide future therapeutic interventions on a genetically oriented basis.

Neurocognitive phenotypes and genetic dissection of disorders of brain and behavior

Elucidating the molecular mechanisms underlying quantitative neurocognitive phenotypes will further our understanding of the brain's structural and functional architecture and advance the diagnosis and treatment of the psychiatric disorders that these traits underlie. Although many neurocognitive traits are highly heritable, little progress has been made in identifying genetic variants unequivocally associated with these phenotypes. A major obstacle to such progress is the difficulty in identifying heritable neurocognitive measures that are precisely defined and systematically assessed and represent unambiguous mental constructs, yet are also amenable to the high-throughput phenotyping necessary to obtain adequate power for genetic association studies. In this perspective we compare the current status of genetic investigations of neurocognitive phenotypes to that of other categories of biomedically relevant traits and suggest strategies for genetically dissecting traits that may underlie disorders of brain and behavior.

Lack of association between the Trp719Arg polymorphism in kinesin-like protein-6 and coronary artery disease in 19 case-control studies

OBJECTIVES

We sought to replicate the association between the kinesin-like protein 6 (KIF6) Trp719Arg polymorphism (rs20455), and clinical coronary artery disease (CAD).

BACKGROUND

Recent prospective studies suggest that carriers of the 719Arg allele in KIF6 are at increased risk of clinical CAD compared with noncarriers.

METHODS

The KIF6 Trp719Arg polymorphism (rs20455) was genotyped in 19 case-control studies of nonfatal CAD either as part of a genome-wide association study or in a formal attempt to replicate the initial positive reports.

RESULTS

A total of 17,000 cases and 39,369 controls of European descent as well as a modest number of South Asians, African Americans, Hispanics, East Asians, and admixed cases and controls were successfully genotyped. None of the 19 studies demonstrated an increased risk of CAD in carriers of the 719Arg allele compared with noncarriers. Regression analyses and fixed-effects meta-analyses ruled out with high degree of confidence an increase of ≥2% in the risk of CAD among European 719Arg carriers. We also observed no increase in the risk of CAD among 719Arg carriers in the subset of Europeans with early-onset disease (younger than 50 years of age for men and younger than 60 years of age for women) compared with similarly aged controls as well as all non-European subgroups.

CONCLUSIONS

The KIF6 Trp719Arg polymorphism was not associated with the risk of clinical CAD in this large replication study.

IL21R and PTH may underlie variation of femoral neck bone mineral density as revealed by a genome-wide association study

Bone mineral density (BMD) measured at the femoral neck (FN) is the most important risk phenotype for osteoporosis and has been used as a reference standard for describing osteoporosis. The specific genes influencing FN BMD remain largely unknown. To identify such genes, we first performed a genome-wide association (GWA) analysis for FN BMD in a discovery sample consisting of 983 unrelated white subjects. We then tested the top significant single-nucleotide polymorphisms (SNPs; 175 SNPs with p < 5 x 10(-4)) for replication in a family-based sample of 2557 white subjects. Combing results from these two samples, we found that two genes, parathyroid hormone (PTH) and interleukin 21 receptor (IL21R), achieved consistent association results in both the discovery and replication samples. The PTH gene SNPs, rs9630182, rs2036417, and rs7125774, achieved p values of 1.10 x 10(-4), 3.24 x 10(-4), and 3.06 x 10(-4), respectively, in the discovery sample; p values of 6.50 x 10(-4), 5.08 x 10(-3), and 5.68 x 10(-3), respectively, in the replication sample; and combined p values of 3.98 x 10(-7), 9.52 x 10(-6), and 1.05 x 10(-5), respectively, in the total sample. The IL21R gene SNPs, rs8057551, rs8061992, and rs7199138, achieved p values of 1.51 x 10(-4), 1.53 x 10(-4), and 3.88 x 10(-4), respectively, in the discovery sample; p values of 2.36 x 10(-3), 6.74 x 10(-3), and 6.41 x 10(-3), respectively, in the replication sample; and combined p values of 2.31 x 10(-6), 8.62 x 10(-6), and 1.41 x 10(-5), respectively, in the total sample. The effect size of each SNP was approximately 0.11 SD estimated in the discovery sample. PTH and IL21R both have potential biologic functions important to bone metabolism. Overall, our findings provide some new clues to the understanding of the genetic architecture of osteoporosis.

Reporting and evaluating genetic association studies

Genetic association studies have become an important part of our scientific landscape. This commentary discusses some basic scientific issues which should be considered when reporting and evaluating such studies including SNP Discovery, Genotyping and Haplotype Analysis; Population Size, Matching of Cases and Controls, and Population Stratification; Phenotype Definition and Multiple Related Phenotypes; Multiple Testing; Replication; Genome-wide Association Studies (GWAS); and the Role of Functional Studies. All of these elements are important in evaluating such studies and should be carefully considered when these studies are conceived and carried out.

Genome-wide association study of antipsychotic-induced parkinsonism severity among schizophrenia patients

RATIONALE

Antipsychotic-induced parkinsonism (AIP) is a severe adverse affect of neuroleptic treatment. Interindividual heterogeneity in AIP development and severity is associated with risk factors such as antipsychotic drug type, old age, and female gender. There is evidence for genetic predisposition to develop AIP but the variants that confer susceptibility or protection are mostly unknown.

OBJECTIVE

To identify genes related to AIP susceptibility, we performed a pharmacogenomic genome-wide association study (GWAS) for AIP severity.

METHODS

Three hundred ninety-seven American schizophrenia patients who participated in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE)-GWAS project were included in our analysis. Patients had been randomized to treatment with antipsychotic monotherapy for periods ranging from 2 weeks to 18 months during phase 1 of the CATIE trial. They were regularly assessed for AIP severity using the modified Simpson-Angus Scale (SAS). For statistical analysis, patients were dichotomized as cases (average SAS mean global score > 0.3 during CATIE phase 1, N = 199) or controls (average SAS mean global score 0, N = 198).

RESULTS

Using logistic regression and controlling for population stratification, age, gender, SAS score at baseline, and concomitant use of anticholinergic drugs, we identified several single-nucleotide polymorphisms associated with AIP severity. Although none reached the GWAS significance level of P < 4.2 x 10(-7), some promising candidate genes for further research on genetic predisposition to AIP were identified including EPF1, NOVA1, and FIGN.

CONCLUSIONS

Our finding may contribute to understanding of the pathophysiology of AIP as well as to a priori identification of patients vulnerable for development of AIP.

Powerful bivariate genome-wide association analyses suggest the SOX6 gene influencing both obesity and osteoporosis phenotypes in males

Background

Current genome-wide association studies (GWAS) are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically.

Principal Findings

To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI), with the osteoporosis risk phenotype, hip bone mineral density (BMD), scanning ∼380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6) gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82×10⁻⁷ and 1.47×10⁻⁶, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the ∼380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS) cohort containing 3,355 Caucasians (1,370 males and 1,985 females) from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene's dual role in both bone and fat.

Conclusions

Our findings, together with the prior biological evidence, suggest the SOX6 gene's importance in co-regulation of obesity and osteoporosis.

Cognitive ontologies for neuropsychiatric phenomics research

Now that genome-wide association studies (GWAS) are dominating the landscape of genetic research on neuropsychiatric syndromes, investigators are being faced with complexity on an unprecedented scale. It is now clear that phenomics, the systematic study of phenotypes on a genome-wide scale, comprises a rate-limiting step on the road to genomic discovery. To gain traction on the myriad paths leading from genomic variation to syndromal manifestations, informatics strategies must be deployed to navigate increasingly broad domains of knowledge and help researchers find the most important signals. The success of the Gene Ontology project suggests the potential benefits of developing schemata to represent higher levels of phenotypic expression. Challenges in cognitive ontology development include the lack of formal definitions of key concepts and relations among entities, the inconsistent use of terminology across investigators and time, and the fact that relations among cognitive concepts are not likely to be well represented by simple hierarchical "tree" structures. Because cognitive concept labels are labile, there is a need to represent empirical findings at the cognitive test indicator level. This level of description has greater consistency, and benefits from operational definitions of its concepts and relations to quantitative data. Considering cognitive test indicators as the foundation of cognitive ontologies carries several implications, including the likely utility of cognitive task taxonomies. The concept of cognitive "test speciation" is introduced to mark the evolution of paradigms sufficiently unique that their results cannot be "mated" productively with others in meta-analysis. Several projects have been initiated to develop cognitive ontologies at the Consortium for Neuropsychiatric Phenomics (www.phenomics.ucla.edu), in the hope that these ultimately will enable more effective collaboration, and facilitate connections of information about cognitive phenotypes to other levels of biological knowledge. Several free web applications are available already to support examination and visualisation of cognitive concepts in the literature (PubGraph, PubAtlas, PubBrain) and to aid collaborative development of cognitive ontologies (Phenowiki and the Cognitive Atlas). It is hoped that these tools will help formalise inference about cognitive concepts in behavioural and neuroimaging studies, and facilitate discovery of the genetic bases of both healthy cognition and cognitive disorders.

Reassessing the impact of donor HLA-C genotype on long-term liver transplant survival

HLA-C is the major inhibitory ligand for killer immunoglobulin-like receptors (KIRs) that are expressed on natural killer (NK) cells. Based on their KIR specificity, HLA-C alleles can be divided into two groups, termed HLA-C1 and HLA-C2. Donor HLA-C group has recently been identified by Hanvesakul et al. (Am J Transplant 2008) as a critical determinant of clinical outcome following liver transplantation: Possession of at least one HLA-C group 2 allele by the donor was associated with significantly improved long-term graft and patient survival, presumably due to an inhibition of host NK cell function. To verify this study, we performed genotyping of 913 deceased liver donors for the relevant KIR epitopes of HLA-C and correlated the presence or absence of donor HLA-C2 genotype with graft and patient survival. In our study, donor HLA-C2 genotype had no impact on 10-year graft or patient survival. We cannot confirm a major role of donor HLA-C2 genotype on long-term allograft survival after liver transplantation.

Genome-wide association analyses suggested a novel mechanism for smoking behavior regulated by IL15

Cigarette smoking is the leading preventable cause of death in the United States. Although smoking behavior has a significant genetic determination, the specific genes and associated mechanisms underlying the smoking behavior are largely unknown. Here, we carried out a genome-wide association study on smoking behavior in 840 Caucasians, including 417 males and 423 females, in which we examined approximately 380,000 single nucleotide polymorphisms (SNPs). We found that a cluster of nine SNPs upstream from the IL15 gene were associated with smoking status in males, with the most significant SNP, rs4956302, achieving a P-value (8.80 x 10(-8)) of genome-wide significance. Another SNP, rs17354547 that is highly conserved across multiple species achieved a P-value of 5.65 x 10(-5). These two SNPs, together with two additional SNPs (rs1402812 and rs4956396) were selected from the above nine SNPs for replication in an African-American sample containing 1251 subjects, including 412 males and 839 females. The SNP rs17354547 was replicated successfully in the male subgroup of the replication sample; it was associated with smoking quantity (SQ), the Heaviness of Smoking Index (HSI) and the Fagerstrom Test for Nicotine Dependence (FTND), with P-values of 0.031, 0.0046 and 0.019, respectively. In addition, a haplotype formed by rs17354547, rs1402812 and rs4956396 was also associated with SQ, HSI and FTND, achieving P-values of 0.039, 0.0093 and 0.0093, respectively. To further confirm our findings, we carried out an in silico replication study of the nine SNPs in a Framingham Heart Study sample containing 7623 Caucasians from 1731 families, among which, 3491 subjects were males and 4132 were females. Again, the male-specific association with smoking status was observed, for which seven of the nine SNPs achieved significant P-values (P<0.05) and two achieved marginally significant P-values (P<0.10) in males. Several of the nine SNPs, including the highly conserved one across species, rs17354547, are located at potential transcription factor binding sites, suggesting transcription regulation as a possible function for these SNPs. Through this function, the SNPs may modulate the gene expression of IL15, a key cytokine regulating immune function. As the immune system has long been recognized to influence drug addiction behavior, our association findings suggest a novel mechanism for smoking addiction involving immune modulation through the IL15 pathway.

Genetic contributions to clinical pain and analgesia: avoiding pitfalls in genetic research

Understanding the genetic basis of human variations in pain is critical to elucidating the molecular basis of pain sensitivity, variable responses to analgesic drugs, and, ultimately, to individualized treatment of pain and improved public health. With the help of recently accumulated knowledge and advanced technologies, pain researchers hope to gain insight into genetic mechanisms of pain and eventually apply this knowledge to pain treatment.

PERSPECTIVE

We critically reviewed the published literature to examine the strength of evidence supporting genetic influences on clinical and human experimental pain. Based on this evidence and the experience of false associations that have occurred in other related disciplines, we provide recommendations for avoiding pitfalls in pain genetic research.

A common variant in DRD3 receptor is associated with autism spectrum disorder

BACKGROUND

The presence of specific and common genetic etiologies for autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD) was investigated for 132 candidate genes in a two-stage design-association study.

METHODS

1,536 single nucleotide polymorphisms (SNPs) covering these candidate genes were tested in ASD (n = 144) and ADHD (n = 110) patients and control subjects (n = 404) from The Netherlands. A second stage was performed with those SNPs from Stage I reaching a significance threshold for association of p < .01 in an independent sample of ASD patients (n = 128) and controls (n = 124) from the United Kingdom and a Dutch ADHD (n = 150) and control (n = 149) sample.

RESULTS

No shared association was found between ASD and ADHD. However, in the first and second ASD samples and in a joint statistical analysis, a significant association between SNP rs167771 located in the DRD3 gene was found (joint analysis uncorrected: p = 3.11 x 10(-6); corrected for multiple testing and potential stratification: p = .00162).

CONCLUSIONS

The DRD3 gene is related to stereotyped behavior, liability to side effects of antipsychotic medication, and movement disorders and may therefore have important clinical implications for ASD.

Identifying heritable brain phenotypes in an extended pedigree of vervet monkeys

The area and volume of brain structural features, as assessed by high-resolution three-dimensional magnetic resonance imaging (MRI), are among the most heritable measures relating to the human CNS. We have conducted MRI scanning of all available monkeys >2 years of age (n = 357) from the extended multigenerational pedigree of the Vervet Research Colony (VRC). Using a combination of automated and manual segmentation we have quantified several correlated but distinct brain structural phenotypes. The estimated heritabilities (h(2)) for these measures in the VRC are higher than those reported previously for such features in humans or in other nonhuman primates: total brain volume (h(2) = 0.99, SE = 0.06), cerebral volume (h(2) = 0.98, SE = 0.06), cerebellar volume (h(2) = 0.86, SE = 0.09), hippocampal volume (h(2) = 0.95, SE = 0.07) and corpus callosum cross-sectional areas (h(2) = 0.87, SE = 0.07). These findings indicate that, in the controlled environment and with the inbreeding structure of the VRC, additive genetic factors account for almost all of the observed variance in brain structure, and suggest the potential of the VRC for genetic mapping of quantitative trait loci underlying such variance.

Genomic convergence analysis of schizophrenia: mRNA sequencing reveals altered synaptic vesicular transport in post-mortem cerebellum

Schizophrenia (SCZ) is a common, disabling mental illness with high heritability but complex, poorly understood genetic etiology. As the first phase of a genomic convergence analysis of SCZ, we generated 16.7 billion nucleotides of short read, shotgun sequences of cDNA from post-mortem cerebellar cortices of 14 patients and six, matched controls. A rigorous analysis pipeline was developed for analysis of digital gene expression studies. Sequences aligned to approximately 33,200 transcripts in each sample, with average coverage of 450 reads per gene. Following adjustments for confounding clinical, sample and experimental sources of variation, 215 genes differed significantly in expression between cases and controls. Golgi apparatus, vesicular transport, membrane association, Zinc binding and regulation of transcription were over-represented among differentially expressed genes. Twenty three genes with altered expression and involvement in presynaptic vesicular transport, Golgi function and GABAergic neurotransmission define a unifying molecular hypothesis for dysfunction in cerebellar cortex in SCZ.

Identification of PLCL1 gene for hip bone size variation in females in a genome-wide association study

Osteoporosis, the most prevalent metabolic bone disease among older people, increases risk for low trauma hip fractures (HF) that are associated with high morbidity and mortality. Hip bone size (BS) has been identified as one of the key measurable risk factors for HF. Although hip BS is highly genetically determined, genetic factors underlying the trait are still poorly defined. Here, we performed the first genome-wide association study (GWAS) of hip BS interrogating ∼380,000 SNPs on the Affymetrix platform in 1,000 homogeneous unrelated Caucasian subjects, including 501 females and 499 males. We identified a gene, PLCL1 (phospholipase c-like 1), that had four SNPs associated with hip BS at, or approaching, a genome-wide significance level in our female subjects; the most significant SNP, rs7595412, achieved a p value of 3.72×10⁻⁷. The gene's importance to hip BS was replicated using the Illumina genotyping platform in an independent UK cohort containing 1,216 Caucasian females. Two SNPs of the PLCL1 gene, rs892515 and rs9789480, surrounded by the four SNPs identified in our GWAS, achieved p values of 8.62×10⁻³ and 2.44×10⁻³, respectively, for association with hip BS. Imputation analyses on our GWAS and the UK samples further confirmed the replication signals; eight SNPs of the gene achieved combined imputed p values<10⁻⁵ in the two samples. The PLCL1 gene's relevance to HF was also observed in a Chinese sample containing 403 females, including 266 with HF and 177 control subjects. A SNP of the PLCL1 gene, rs3771362 that is only ∼0.6 kb apart from the most significant SNP detected in our GWAS (rs7595412), achieved a p value of 7.66×10⁻³ (odds ratio = 0.26) for association with HF. Additional biological support for the role of PLCL1 in BS comes from previous demonstrations that the PLCL1 protein inhibits IP3 (inositol 1,4,5-trisphosphate)-mediated calcium signaling, an important pathway regulating mechanical sensing of bone cells. Our findings suggest that PLCL1 is a novel gene associated with variation in hip BS, and provide new insights into the pathogenesis of HF.

Runs of homozygosity in European populations

Estimating individual genome-wide autozygosity is important both in the identification of recessive disease variants via homozygosity mapping and in the investigation of the effects of genome-wide homozygosity on traits of biomedical importance. Approaches have tended to involve either single-point estimates or rather complex multipoint methods of inferring individual autozygosity, all on the basis of limited marker data. Now, with the availability of high-density genome scans, a multipoint, observational method of estimating individual autozygosity is possible. Using data from a 300,000 SNP panel in 2618 individuals from two isolated and two more-cosmopolitan populations of European origin, we explore the potential of estimating individual autozygosity from data on runs of homozygosity (ROHs). Termed F(roh), this is defined as the proportion of the autosomal genome in runs of homozygosity above a specified length. Mean F(roh) distinguishes clearly between subpopulations classified in terms of grandparental endogamy and population size. With the use of good pedigree data for one of the populations (Orkney), F(roh) was found to correlate strongly with the inbreeding coefficient estimated from pedigrees (r = 0.86). Using pedigrees to identify individuals with no shared maternal and paternal ancestors in five, and probably at least ten, generations, we show that ROHs measuring up to 4 Mb are common in demonstrably outbred individuals. Given the stochastic variation in ROH number, length, and location and the fact that ROHs are important whether ancient or recent in origin, approaches such as this will provide a more useful description of genomic autozygosity than has hitherto been possible.

Catechol-O-methyltransferase contributes to genetic susceptibility shared among anxiety spectrum phenotypes

BACKGROUND

Catechol-O-methyltransferase (COMT) has been investigated for its possible role in a wide range of psychiatric phenotypes. In particular, several studies support association of this gene with panic disorder and other anxiety-related traits.

METHODS

We examined the COMT gene for association with genetic risk across a range of anxiety spectrum phenotypes. We used multivariate structural equation modeling to select twin pairs scoring at the extremes of a latent genetic risk factor shared by neuroticism, several anxiety disorders, and major depression from a large population-based twin sample. With one member from each of these pairs, the resulting sample of 589 cases and 539 control subjects were entered into a two-stage association study in which genetic markers were screened in stage 1, the positive results of which were tested for replication in stage 2.

RESULTS

The functional val158met polymorphism (rs4680) plus nine other single nucleotide polymorphism markers selected to capture the major allelic variation across the COMT locus were analyzed for differences between cases and control subjects. Although the val (G) allele of rs4680 showed marginally significant association in our combined stage 1 plus stage 2 sample, a high-risk haplotype of this allele with the A allele of rs165599 was significantly over-represented in cases (p = 1.97e-5, odds ratio = 1.95). This haplotype also predicted individual differences in neuroticism and risk for several anxiety disorders and major depression. Consistent with prior studies, our findings are female-specific.

CONCLUSIONS

Variations in the COMT gene contribute to genetic risk shared across a range of anxiety-related phenotypes.

Merging microsatellite data: enhanced methodology and software to combine genotype data for linkage and association analysis

Background

Correctly merged data sets that have been independently genotyped can increase statistical power in linkage and association studies. However, alleles from microsatellite data sets genotyped with different experimental protocols or platforms cannot be accurately matched using base-pair size information alone. In a previous publication we introduced a statistical model for merging microsatellite data by matching allele frequencies between data sets. These methods are implemented in our software MicroMerge version 1 (v1). While MicroMerge v1 output can be analyzed by some genetic analysis programs, many programs can not analyze alignments that do not match alleles one-to-one between data sets. A consequence of such alignments is that codominant genotypes must often be analyzed as phenotypes. In this paper we describe several extensions that are implemented in MicroMerge version 2 (v2).

Results

Notably, MicroMerge v2 includes a new one-to-one alignment option that creates merged pedigree and locus files that can be handled by most genetic analysis software. Other features in MicroMerge v2 enhance the following aspects of control: 1) optimizing the algorithm for different merging scenarios, such as data sets with very different sample sizes or multiple data sets, 2) merging small data sets when a reliable set of allele frequencies are available, and 3) improving the quantity and 4) quality of merged data. We present results from simulated and real microsatellite genotype data sets, and conclude with an association analysis of three familial dyslipidemia (FD) study samples genotyped at different laboratories. Independent analysis of each FD data set did not yield consistent results, but analysis of the merged data sets identified strong association at locus D11S2002.

Conclusion

The MicroMerge v2 features will enable merging for a variety of genotype data sets, which in turn will facilitate meta-analyses for powering association analysis.

Controlling false discoveries in genetic studies

A false discovery occurs when a researcher concludes that a marker is involved in the etiology of the disease whereas in reality it is not. In genetic studies the risk of false discoveries is very high because only few among the many markers that can be tested will have an effect on the disease. In this article, we argue that it may be best to use methods for controlling false discoveries that would introduce the same ratio of false discoveries divided by all rejected tests into the literature regardless of systematic differences between studies. After a brief discussion of traditional "multiple testing" methods, we show that methods that control the false discovery rate (FDR) may be more suitable to achieve this goal. These FDR methods are therefore discussed in more detail. Instead of merely testing for main effects, it may be important to search for gene-environment/covariate interactions, gene-gene interactions or genetic variants affecting disease subtypes. In the second section, we point out the challenges involved in controlling false discoveries in such searches. The final section discusses the role of replication studies for eliminating false discoveries and the complexities associated with the definition of what constitutes a replication and the design of these studies.